RepoRt - UNICEF Georgiaunicef.ge/uploads/Report_of_the_Georgia_National_Nutrition_Survey... ·...

RepoRtof the 2009 Georgia National Nutrition Survey

RepoRtof the 2009 Georgia National Nutrition Survey

June 2010

Bradley A. Woodruff, MD MPH Consultant, UNICEF-Georgia

Levan Baramidze, MD MPH PhD First Deputy Director General, NCDC&PH Full Professor, Tbilisi State Medical University

Manana Beruchashvili, MD Deputy Director General, NCDC&PH

Marina Shakhnazarova, MS Head of Division of Data Analysis, NCDC&PH

Konstantine Gvetadze, MD Head, Imereti Zonal Branch, NCDC&PH

Vilma Qahoush Tyler, MS, MPH Nutrition Specialist, UNICEF Regional Office CEE/CIS

Tako Ugulava, MD, PhD Health Officer, UNICEF-Georgia

Nino Lortkipanidze, MD Nutrition Officer, UNICEF-Georgia

the Georgia National Nutrition Survey 2009 Steering Committee:

Mamuka Nadareishvili, Statistitian, Full Professor, Chavchavadze State University

Neli Chakvetadze, MD, PhD Academic Secretary, NCDC&PH

Konstantin Kazanjan, MS, Head of DB Department, NCDC&PH

Rusudan Kvanchakhadze, MD PhD Lead Specialist, NCDC&PH

Lela Sturua, MD MPH PhD Head of NCD Epidemiology and HP Department, NCDC&PH

Manana Tsintsadze, PhD Head of Medical Statistics Service, NCDC&PH

Consultants:

Paata Imnadze, MD PhD, Full Professor Tbilisi State University, General Director of NCDC&PH

Akaki Gamkrelidze, MD PhD, Full Professor Tbilisi State Medical University Deputy General Director of NCDC&PH

Special thanks to:

First Lady of Georgia Mrs Sandra Elisabeth Roelofs and the members of the Reproductive Health National Council under the Georgian Ministry of Health and Social Affairs:

Maka Mshvildadze, MD, Neonatologist, Technical Consultant in Pediatrics/Neonatology

Eugenia Tavadze, MD, MSc, PhD Technical Consultant in Safe Motherhood and Cancer Screening

Giovanna Barberis, Representative, UNICEF Senegal

Roeland Monasch, Representative, UNICEF Georgia

Benjamin Perks, Deputy Representative, UNICEF Georgia

David Brown, DSc, MScPH, MSc, UNICEF NY

George Gedevanishvili, Head of Office, and Asmat Beshidze, Medical Coordinator, United Methodists Committee on Relief (UMCOR) Georgia

James P. Wirth, Senior Associate, Performance Measurement and Research, Global Alliance for Improved Nutrition (GAIN)

Georgia National Nutrition Survey 2009 3

tABLe oF CoNteNtS

TABLE OF CONTENTS .................................................................................................... 3

LIST OF TABLES ............................................................................................................ 6

LIST OF FIGURES ..........................................................................................................10

LIST OF ABBREVIATIONS ..............................................................................................11

ExECUTIVE SUMMARY .................................................................................................12

Introduction ..........................................................................................................12

Results ................................................................................................................12

Conclusions, Discussion, and Recommendations .......................................................14

Anemia and iron deficiency ............................................................................14

Folate deficiency ...........................................................................................16

Bread fortification .........................................................................................17

Salt iodization, storage, and consumption ........................................................18

Acute protein-energy malnutrition ...................................................................18

Overweight and obesity .................................................................................18

Chronic protein-energy malnutrition .................................................................19

Underweight ................................................................................................19

Breastfeeding ...............................................................................................20

INTRODUCTION AND BACKGROUND ..............................................................................23

GOALS AND OBJECTIVES .............................................................................................25

METHODS ................................................................................................................... 26

Study population ...................................................................................................26

Case definitions and measurement methods of outcomes ...........................................27

Adequately iodized salt in households ..............................................................27

Iron fortification of bread ...............................................................................27

Birthweight ..................................................................................................27

Breastfeeding ...............................................................................................28

Protein-energy malnutrition in children less than 5 years of age ...........................29

Overnutrition in children less than 5 years of age ..............................................29

Chronic energy deficiency and overnutrition in non-pregnant women 15-49 years of age .......................................................................................29

Anemia ........................................................................................................30

Iron deficiency ..............................................................................................31

Folate deficiency ...........................................................................................32

Sampling scheme ..................................................................................................32

4 Georgia National Nutrition Survey 2009

Households, children, and non-pregnant women ...............................................32

Pregnant women ...........................................................................................33

Sample size calculation ..........................................................................................33


Pregnant women ...........................................................................................34

Enrollment and recruitment procedures ....................................................................35


Pregnant women ...........................................................................................36

Data collection ......................................................................................................36

Team composition .........................................................................................36

Household procedures ...................................................................................37

Data collection instruments ....................................................................................38

Training for study personnel ...................................................................................38

Data analysis ........................................................................................................39

Data entry, editing, and management ......................................................................39

Quality control ......................................................................................................39

RESULTS................... ..................................................................................................40

Households – Description of sample ........................................................................40

Households – Salt storage, usage, and iodization ......................................................43

Households – Bread consumption and iron content ....................................................46

Children – Description of sample .............................................................................56

Children – Birthweight ...........................................................................................57

Children – Breastfeeding ........................................................................................59

Children – Other dietary intake ...............................................................................71

Children – Protein-energy nutritional status...............................................................73

Acute protein-energy malnutrition (wasting) and overweight ...............................73

Chronic protein-energy malnutrition (stunting) ...................................................76

Underweight ................................................................................................80

Children – Micronutrient status ...............................................................................81

Anemia ........................................................................................................81

Iron deficiency ..............................................................................................84

Non-pregnant women – Description of sample ..........................................................85

Non-pregnant women – Protein-energy nutritional status ............................................88

Non-pregnant women – Micronutrient status ............................................................90

Anemia ........................................................................................................90

Iron deficiency ..............................................................................................92

Folate ..........................................................................................................94

Pregnant women – Description of sample .................................................................94


Pregnant women – Protein-energy nutritional status ..................................................97

Pregnant women – Micronutrient status ...................................................................98

Anemia ........................................................................................................98

ANNEx 1 – SAMPLING METHODOLOGY .......................................................................100

First stage sampling ............................................................................................100

Households, children, and non-pregnant women .............................................100

Pregnant women .........................................................................................100

Second stage sampling ........................................................................................101

Households, children and non-pregnant women ..............................................101

Pregnant women .........................................................................................101

Stratified sampling ..............................................................................................101

Children and non-pregnant women ................................................................101

Pregnant women .........................................................................................102

Basic sample size (for regional stratification) ...........................................................102

Households ................................................................................................104


Supplemental sample size (for ethnic stratification) ..................................................107


Pregnant women .........................................................................................110

ANNEx 2 – DATA COLLECTION FORMS ........................................................................111

ANNEx 3 – QUALITY ASSURANCE DURING AND AFTER DATA COLLECTION ..................126

Interview ...........................................................................................................126

Anthropometric measurements .............................................................................126

Physical examination ...........................................................................................126

Biologic specimen collection .................................................................................126

Laboratory measurements ....................................................................................127

Ferritin and CRP ..........................................................................................127

Salt iodine ..................................................................................................127

REFERENCES ..............................................................................................................129


LISt oF tABLeS

Table 1. Summary results for major indicators, GNNS 2009 ............................................. 12

Table 2. Prevalence rates of anemia in children less than 5 years of age, non-pregnant women, and pregnant women, in Georgia and selected other countries. ................ 14

Table 3. Prevalence rates and mean serum folate level, non-pregnant women 15-49 years of age, in Georgia and selected other countries before implementation of flour fortification with folate. .................................................................................. 16

Table 4. Prevalence rates of stunting in children less than 5 years of age, in Georgia and selected other countries. ........................................................................... 20

Table 5. Breastfeeding indicators in two prior MICS and GNNS 2009. ............................... 21

Table 6. Results of measurement of nutrition indicators included in nationwide surveys done since independence, Georgia 1999-2009 ....................................... 24

Table 7. Target groups, outcomes, and source of sample, GNNS 2009 ............................. 26

Table 8. Inclusion criteria, by target group, Georgia National Nutrition Survey 2009 ............ 26

Table 9. Categories of protein-energy nutrition, by value of BMI, GNNS 2009 .................... 30

Table 10. Definition of anemia by hemoglobin concentration for various age- and sex-specific groups, GNNS 2009 ..................................................................... 30

Table 11. Adjustments in cut-off defining anemia, by altitude of residence, GNNS 2009 ....... 31

Table 12. Adjustments in cut-off defining anemia, by smoking status, GNNS 2009 .............. 31

Table 13. Number of households and individuals from whom data are needed, for different target groups and outcomes, GNNS 2009 ....................................... 33

Table 14. Summary of biologic specimens to be taken, by target group, GNNS 2009. ........... 37

Table 15. Distribution of various demographic variables for sample households, GNNS 2009 . 41

Table 16. Distribution of household composition and ethnicity variables for sample households, GNNS 2009 ................................................................................. 42

Table 17. Distribution of socio-economic variables for sample households, GNNS 2009 ........ 43

Table 18. Number (weighted %) and 95% confidence intervals (CI) for variables concerning salt storage and use, sample households, GNNS 2009 ....................... 44

Table 19. Weighted mean average and 95% confidence intervals (CI) for iodine content in parts per million in household salt specimens, sample households, GNNS 2009 .. 45

Table 20. Number (weighted %) with salt iodine of various concentrations (in parts per million), sample households, GNNS 2009 .................................................... 46

Table 21. Weighted mean average of bread eaten per person per day (in grams) and 95% confidence intervals (CI), sample households, GNNS 2009 .................... 48

Table 22. Number (weighted %) most often consuming various types of bread, sample households, GNNS 2009 ...................................................................... 49


Table 23. Number (weighted %) purchasing most commonly eaten type of bread from various sources, sample households, GNNS 2009 ....................................... 50

Table 24. For most commonly used bread which is purchased in supermarkets, number (weighted %) with various brand names, sample households, GNNS 2009. ........... 51

Table 25. Number (weighted %) using various types of flour when baking bread at home, sample households in which bread is baked at home, GNNS 2009 ....................... 52

Table 26. Number (weighted %) of bread specimens for which packaging was marked as fortified with iron or not (does not include homemade bread), sample households, GNNS 2009 ...................................................................... 53

Table 27. Weighted mean average and 95% confidence intervals for iron content in parts per million, household bread specimens, GNNS 2009 .............................. 54

Table 28. Number (weighted %) and 95% confidence intervals (CI) of household bread specimens containing >30 parts per million iron, GNNS 2009 ............................. 55

Table 29. Description of sample children less than 5 years of age, GNNS 2009 ................... 56

Table 30. Point or period prevalence of various forms of morbidity, children less than 5 years of age, GNNS 2009 ................................................... 57

Table 31. Number (weighted %) with various birth weights, children less than 5 years of age, GNNS 2009 ................................................... 58

Table 32. Number (weighted %) with various times of breastfeeding initiation after birth, children < 24 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #1 Early initiation of breastfeeding) ..................................................... 61

Table 33. Number (weighted %) and 95% CI of children exclusively breastfed the day before the interview, children < 6 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #2 Exclusive breastfeeding under 6 months) ............. 62

Table 34. Number (weighted %) and 95% CI of children breastfed the day before the interview, children 12-15 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #3 Continued breastfeeding at 1 year) ..................... 63

Table 35. Number (weighted %) and 95% CI of children eating complementary food the day before the interview, children 6-8 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #4 Introduction of solid, semi-solid or soft foods) ...... 64

Table 36. Number (weighted %) with minimum dietary diversity the day before the interview, children 6-23 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #5 Minimum dietary diversity) ............ 65

Table 37. Number (weighted %) with minimum meal frequency the day before the interview, children 6-23 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #6 Minimum meal frequency) ............ 66

Table 38. Number (weighted %) with minimum acceptable diet the day before the interview, children 6-23 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #7 Minimum acceptable diet) ............. 67

Table 39. Number (weighted %) and 95% CI of children ever breastfed, children < 24 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #9 Children ever breastfed) .............. 68


Table 40. Number (weighted %) and 95% CI of children breastfed the day before the interview, children 20-23 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #10 Continued breastfeeding at 2 years) .................. 69

Table 41. Number (weighted %) and 95% CI of children with age-appropriate breastfeeding the day before the interview, children < 24 months of age, GNNS 2009 (WHO/UNICEF recommendations - Indicator #11 Age-appropriate breastfeeding) ............................................................................................... 70

Table 42. Number (weighted %) and 95% CI of children eating various foods the day before the interview, by age group, children < 5 years of age, GNNS 2009 .......... 72

Table 43. Number (weighted %) of children eating various foods the week before the interview with various frequencies, by age group, children < 24 months of age, GNNS 2009 .................................................................................................. 72

Table 44. Number (weighted %) of children eating various foods the week before the interview with various frequencies, by age group, children 24-59 months of age, GNNS 2009 .................................................................................................. 73

Table 45. Number (weighted %) with various levels of acute protein-energy malnutrition or wasting, overweight, or obesity (defined by weight-for-height z-score calculated using WHO Child Growth Standard), children less than 5 years of age, GNNS 2009 .................................................................................................. 75

Table 46. Number (weighted %) with overweight or obesity (defined by weight-for-height z-score calculated using WHO Child Growth Standard), children less than 5 years of age, GNNS 2009 ................................................... 76

Table 47. Number (weighted %) with various levels of chronic protein-energy malnutrition (defined by height-for-age z-score calculated using WHO Child Growth Standard), children less than 5 years of age, GNNS 2009 ................................................... 78

Table 48. Number (weighted %) with any chronic protein-energy malnutrition (defined by height-for-age z-score calculated using WHO Child Growth Standard), children less than 5 years of age, GNNS 2009 ................................................... 79

Table 49. Number (weighted %) with various levels of underweight (defined by height-for-age z-score calculated using WHO Child Growth Standard), children less than 5 years of age, GNNS 2009 ................................................... 80

Table 50. Number (weighted %) with various degrees of anemia, children 12-59 months of age, GNNS 2009 ....................................................... 82

Table 51. Number (weighted %) with any anemia, children 12-59 months of age, GNNS 2009 .................................................................................................. 83

Table 52. Number (weighted %) and 95% confidence intervals (CI) with iron deficiency, children less than 5 years of age, GNNS 2009 ................................................... 84

Table 53. Description of demographic variables, non-pregnant women 15-49 years of age, GNNS 2009 .................................................................................................. 85

Table 54. Description of reproductive and breastfeeding variables, non-pregnant women 15-49 years of age, GNNS 2009 ....................................... 87

Table 55. Description of behavioral variables, non-pregnant women 15-49 years of age, GNNS 2009 .................................................................................................. 87


Table 56. Number (weighted %) with various levels of malnutrition (defined by BMI), non-pregnant women 15-49 years of age, GNNS 2009 ....................................... 89

Table 57. Number (weighted %) with overweight or obesity (defined by BMI), non-pregnant women 15-49 years of age, GNNS 2009 ....................................... 90

Table 58. Distribution of levels of adjusted hemoglobin concentrations, non-pregnant women 15-49 years of age, GNNS 2009 ....................................... 91

Table 59. Number (weighted %) and 95% confidence intervals (CI) with any anemia (after adjustment of hemoglobin concentration for smoking status and altitude of residence), non-pregnant women 15-49 years of age, GNNS 2009 ....................... 92

Table 60. Number (weighted %) and 95% confidence intervals (CI) with iron deficiency, non-pregnant women 15-49 years of age, GNNS 2009 ....................................... 93

Table 61. Number (weighted %) with anemia, by iron deficiency status, non-pregnant women 15-49 years of age, GNNS 2009 ....................................... 93

Table 62. Description of demographic variables, pregnant women, GNNS 2009 ................... 94

Table 63. Description of reproductive history, pregnant women, GNNS 2009 ...................... 96

Table 64. Description of behavioral variables, pregnant women, GNNS 2009 ....................... 96

Table 65. Number (weighted %) and 95% confidence intervals (CI) with low MUAC, pregnant women, GNNS 2009 ......................................................................... 97

Table 66. Distribution of levels of hemoglobin concentrations, pregnant women, GNNS 2009 .................................................................................................. 98

Table 67. Number (weighted %) and 95% confidence intervals (CI) with any anemia, pregnant women, GNNS 2009 ......................................................................... 99

Table 68. Comparison of CRP testing results from Georgian laboratory and German laboratory, GNNS 2009 .................................................................... 127

Table 69. Comparison of ferritin testing results from Georgian laboratory and German laboratory, GNNS 2009 ................................................................................ 127


LISt oF FIGuReS

Figure 1. Recruitment procedures for household survey, GNNS 2009 ................................35

Figure 2. Weighted distribution of iodine concentrations in household salt specimens, GNNS 2009 .................................................................................................45

Figure 3. Weighted distribution of households with various per capita daily bread consumption, GNNS 2009.....................................................................48

Figure 4. Weighted distribution of iron concentrations in household bread specimens, GNNS 2009 .................................................................................................54

Figure 5. Weighted distribution of birthweights of children less than 5 years of age, GNNS 2009 .................................................................................................57

Figure 6. Weighted distribution of birthweights of children less than 5 years of age, GNNS 2009 .................................................................................................58

Figure 7. Weighted 3-month moving average percent of children breastfed the day before the interview, by age, children < 36 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #13 Duration of breastfeeding) .......71

Figure 8. Weighted distribution of weight-for-height z-scores in children less than 5 years of age, GNNS 2009..............................................................74

Figure 9. Weighted distribution of height-for-height z-scores in children less than 5 years of age, GNNS 2009..............................................................77

Figure 10. Weighted distribution of hemoglobin concentrations in children less than 5 years of age, GNNS 2009..............................................................81

Figure 11. Distribution of BMI values for non-pregnant women 15-49 years of age, GNNS 2009 .................................................................................................88

Figure 12. Weighted distribution of hemoglobin concentrations in non-pregnant women 15-49 years of age, GNNS 2009 ..................................91

Figure 13. Weighted distribution of MUAC measurements, pregnant women, GNNS 2009 .................................................................................................97

Figure 14. Weighted distribution of hemoglobin concentrations in pregnant women, GNNS 2009 .................................................................................................98

Figure 15. Scatterplot showing correlation between Georgian and Ukrainian laboratories’ results in testing household salt, GNNS 2009 .................128


LISt oF ABBReVIAtIoNS

BMI Body mass index

CI Confidence intervals

CRP C-reactive protein

ELISA Enzyme-linked immunosorbant assay

GNNS 2009 Georgia National Nutrition Survey 2009

ICC Intracluster correlation co-efficient

MICS Multiple Indicator Cluster Survey

MUAC Mid-upper arm circumference

NCDCPH Georgia National Center for Disease Control and Public Health

ppm Parts per million

RR Relative risk

UN United Nations

UNHCR United Nations High Commissioner for Refugees

WFP World Food Programme

WHO World Health Organization


exeCutIVe SummARy

Introduction

Over the past five years the government of Georgia has taken active steps to improve the nutri-tional status of the population of Georgia. In 2005 the Parliament of Georgia has adopted a Law called “Prevention of iodine, other microelement and vitamin deficiencies”. The law bans import and sale of non-iodized salt and puts in place the mechanisms for food fortification policy in the country. In addition, since 2006 Georgia has been implementing a program to fortify wheat flour with iron and folic acid. However, these positive developments may have not fully reversed the adverse impact on nutritional status of the difficult political situation and socio-economic changes.

This report analyses the results of the Georgia National Nutrition Survey 2009 (GNNS 2009), a cross-sectional, nationwide survey assessment of nutritional status in several target groups in Georgia. This survey randomly selected households from which children less than 5 years of age and non-pregnant women 15-49 years of age were recruited. A separate sample of pregnant women was consecutively recruited from a random selection of facilities providing ante-natal care in Georgia. The results of this survey can be generalized to the overall population of Georgia, and many estimates can be generalized to regions or combinations of regions.

This Executive Summary presents a summary of the estimates for major indicators in table form (see Table 1 below) and includes the Conclusions, Discussion, and Recommendations section which compares the results of this survey to prior assessments and compares Georgian results with those from neighboring and other countries. This section also gives recommendations for programmatic interventions. The Methods section then describes how the survey was carried out. The Results section presents a detailed analysis of the survey data. The annexes contain a more information on the sampling scheme, copies of the data collection forms in English which were used in this survey, and a description of the quality control strategies used during data col-lection.

Results

table 1. Summary results for major indicators, GNNS 2009

target group Indicator* Value table**

Anemia and iron deficiencyChildren < 5 years Anemia 22.8 % Table 51of age Severe anemia 0.6 %

Moderate anemia 9.4 % Mild anemia 12.8 %Iron deficiency 0.1 % Table 52

Non-pregnant women Anemia 24.1 % Table 59 Severe anemia 0.4 % Moderate anemia 9.1 % Mild anemia 14.6 %Elevated hemoglobin 4.9 % Mild elevation 2.5 % Moderate elevation 2.4 %Iron deficiency 1.6 % Table 60



Pregnant women Anemia 25.6 % Table 67 Severe anemia 0.7 % Moderate anemia 7.7 % Mild anemia 17.1 %

Folate deficiencyNon-pregnant women Folate deficiency 36.6 %

Mean serum folate level 7.2 ng/mlBread fortification

Households Average per capita daily bread consumption 414 grams Table 21

Most common type of bread eaten at home

Varies by region Table 22

Source of most common bread

Varies by region Table 23

Type of flour used at home Varies by region Table 25

Average iron content of bread 23.8 ppm Table 27Bread iron >30 ppm 24.9 % Table 28

Salt iodizationHouseholds Mean iodine content in salt 36.8 ppm Table 19

Salt iodine >15 ppm >99.9 % Salt iodine <15 ppm <0.1 %

Table 20 Salt iodine 15.1-40 ppm 73.4% Salt iodine 40+ ppm 26.5 %

protein-energy nutritional status

Children <5 years Any wasting (low weight-for-height) 1.6 % Table 45

Overweight or obesity 19.9 % Table 46Any stunting (low height-for-age) 11.3 % Table 48

Severe stunting 4.5 %Table 47

Moderate stunting 6.8 %Any underweight (low weight-for-age) 1.1 % Table 49

Non-pregnant women Any low BMI 5.3 % Table 56 Severe low BMI 0.3 % Moderate low BMI 1.1 % At risk 3.9 %Any high BMI 42.1 % Table 57 Overweight 24.1 % Obese 18.0 %

Pregnant women Low MUAC 4.8 % Table 65Infant and young child feeding

Children <5 years Low birthweight 4.9 % Table 31

Children <24 months Breastfeeding begun within 1 hour of birth 66.3 % Table 32

Children <6 months Exclusive breastfeeding 54.8 % Table 33

Children 12-15 months Continued breastfeeding at 1 year 36.5 % Table 34

Children 6-8 months Complementary food introduced 84.5 % Table 35

Children 6-23 months Minimum dietary diversity 47.7 % Table 36



Minimum meal frequency 85.3% Table 37Minimum acceptable diet 42.3 % Table 38

Children <24 months Ever breastfed 87.2 % Table 39

Children 20-23 months Continued breastfeeding at 2 years 16.6 % Table 40

Children <24 months Age-appropriate breastfeeding 37.7 % Table 41

Children <36 months Median duration of breastfeeding

9-10 months of age Figure 7

* See text of Methods section for definitions** See table indicated for more detailed analysis of outcome, including group-specific results by age, regional

stratum, rural/urban residence, and ethnicity

Conclusions, Discussion, and Recommendations

Anemia and iron deficiency

Anemia is a common health problem in children less than 5 years of age, non-pregnant women 15-49 years of age, and pregnant women in Georgia. Although severe anemia is relatively rare in these risk groups, moderate and mild anemia can still have deleterious effects on health. Ac-cording to WHO recommendations, anemia in all three target groups in Georgia is a “moderate” public health problem (prevalence 20-39%).1 As seen in Table 2, although the prevalence rates of anemia in young children and women in Georgia are generally lower than those of its neighbor-ing countries, they are substantially elevated when compared to developed countries in Europe and North America. Table 2 also demonstrates that, unlike Georgia, some advanced industrialized countries do not have precise measurements of the prevalence of anemia in these target groups.

table 2. prevalence rates of anemia in children less than 5 years of age, non-pregnant women, and pregnant women, in Georgia and selected other countries.

prevalence of anemia

Country Children < 5 years (year of survey)

Non-pregnant women(year of survey)

pregnant women (year of survey)

Georgia 22.8 % (2009) 24.1 % (2009) 25.6 % (2009)

Azerbaijan 31.8 % (2001) 40.2 (2001) 38.4 % (2001)

Armenia 36.5 % (2005) 24.2 % (2005) 38.6 % (2005)

Turkey 32.6 % * 26.3 % * 40.2 % *

Sweden 8.6 % * 13.3 % * 12.9 % *

Germany 7.8 % * 12.3 % * 12.3 % *

USA 3.1 % (2002) 6.9 % (2002) 5.7 % (2002)

* WHO estimate which is not based on national survey


Within Georgia, the prevalence of anemia in all three target groups differs substantially between regional strata, and anemia is generally most common in Azerbaijani children and women (see Table 51, Table 59, and Table 67).

In children less than 5 years of age and non-pregnant women 15-49 years of age, iron deficiency is rare, and therefore cannot be a major cause of anemia in these population subgroups. In non-pregnant women, only a very small proportion of women who had anemia also had iron deficien-cy. These findings are unexpected given the importance of iron deficiency as a cause of anemia worldwide, including in other developed countries.

These findings are different from some previous assessments of anemia in children and women in Georgia and are similar to others. One prior survey2 found that 34.8% of 150 children were anemic; however, these 150 children were a convenience sample selected in hospitals and clin-ics. Such children may be more likely to be ill than children in the general population, and may, therefore, have a substantially higher prevalence of anemia than the general population of Geor-gian children. This survey also included hemoglobin measurements on a convenience sample of 256 women and found a prevalence of anemia of 16.8%. Two nationwide surveys found anemia prevalence rates in non-pregnant women of 27.8% and 27.0%, more similar to the results of GNNS 2009.3, 4 In one of these surveys,4 83% of anemia was mild; however, this survey used a non-standard broader definition of “mild” anemia in non-pregnant women (10.0 – 11.9 g/dL) which included a greater proportion of survey subjects than the definition used for the GNNS 2009. The other survey3 found a prevalence of iron deficiency in non-pregnant women of 41.3%; however, the women included in this survey were a convenience sample of teachers, mothers, and female household members of selected children. These women may not be representative of all Georgian women. No prior population-based survey measured the prevalence of anemia in Georgian pregnant women.

Assuming the accuracy of the CRP and ferritin testing results (see Annex 3 for validation results), the lack of iron deficiency precludes many specific causes of anemia, such as insufficient dietary intake of iron, poor bioavailability of dietary iron, excessive loss of blood, etc. What then can be the major causes of anemia in children and women in Georgia? Answering this question goes beyond the scope of the current survey and requires additional investigation.

Recommendations

1. The causes of anemia, such as hemoglobinopathies, other vitamin or mineral deficien-cies, or chronic disease or inflammation, in young children and non-pregnant women in Georgia should be investigated further. These investigations may also include a more definitive investigation of iron status to confirm the rather surprising finding of very little iron deficiency in women and children. Such investigation may include: a) measurement of hemoglobin in adult men and b) measurement of other markers of iron status, such as transferrin receptor concentration, erythrocyte protoporphyrin, etc, and c) presence of hemoglobinopathies, such as alpha, beta, and delta thalessemias

2. Implementation of new programs to enhance dietary iron should be delayed until the im-portance of iron deficiency and the role of iron deficiency in producing anemia in women and children is definitively answered by the additional investigations recommended above. Nonetheless, existing program targeting iron deficiency should not be terminated before the results of the further investigation are known.

3. The role of iron deficiency in producing anemia in pregnant women should also be inves-tigated to determine whether or not to routinely offer iron supplements during ante-natal care, as is already done in many countries which have lower prevalence rates of anemia in pregnancy.


Folate deficiency

The prevalence of folate deficiency in non-pregnant women 15-49 years of age is quite high compared to other countries in which folate deficiency has been assessed in national surveys, as shown in Table 3. On the other hand, the mean serum folate level from GNNS 2009 is some-what higher than that found in other countries. Note that in order to compare GNNS 2009 folate results, which used an updated definition of folate deficiency, to the results of older surveys in other countries, the GNNS 2009 data were re-analyzed using 3.0 ng/mL as the cut-off point which defines low serum folate. The data analysis presented in the Results section uses the newer cut-off point of 4.0 ng/mL.

The prevalence of folate deficiency in non-pregnant women from the GNNS 2009 is almost iden-tical to that found in the United States before mandatory wheat flour fortification with folic acid was introduced in that country in 1995. Moreover, both the prevalence of deficiency and the mean serum folate in non-pregnant women in Georgia are higher than those found in Costa Rica just before that country implemented folate fortification of flour.

In four countries which had implemented mandatory folate fortification of flour before 2008, the mean serum folate levels substantially increased in all population groups and the rate of neural tube defects in newborns fell after fortification.5 Several studies have shown that the higher the intake of folate and the higher the concentration of serum folate in women when they become pregnant, the lower the rate of neural tube defects.6

table 3. prevalence rates and mean serum folate level, non-pregnant women 15-49 years of age, in Georgia and selected other countries before implementation of flour fortification with folate.

Country and reference

% with folate deficiency (year of survey)

mean or median serum folate in ng/mL(year of survey)

Georgia 24.6* % (2009) 7.2 (2009)

USA5 24.5% (1988) 5.7 (1988)

Newfoundland,Canada7 6.4 (1997)

Chile8 4.3 (1999)

Costa Rica9 19%† urban (1996) 31.4%† rural

10.1 urban (1996) 9.6 rural

Germany5 1 % (1998)

United Kingdom5 0 % (2000)

* GNNS 2009 data re-analyzed using 3.0 ng/mL as cut-off to enhance comparability with older surveys in other countries† Analysis used 6.0 ng/mL as cut-off defining low serum folate Recommendations

1. Given the overwhelming evidence of the effectiveness of folate fortification in prevent-ing neural tube defects in newborns, extra folate intake should be provided to both non-pregnant and pregnant women in Georgia according to international recommendations.10-12 As discussed below, the current coverage of fortified wheat flour in Georgia is quite poor.


If full implementation of wheat flour fortification with folic acid cannot be achieved within the next few years, folic acid supplementation for both pregnant and non-pregnant wom-en, as recommended by WHO,10 should be implemented as rapidly as possible

2. A system of monitoring folate status of women should be implemented. Such a system could include periodic population assessments of serum folate in non-pregnant women, market monitoring of fortified foods, and surveillance for neural tube defects. A more detailed description of such monitoring systems can be found in various publications.11, 13

Bread fortification

Bread consumption in Georgia is more than sufficient to justify using wheat flour as a vehicle for fortification. Unfortunately, the survey shows that the majority of bread in Georgia is made from wheat flour which does not meet national standards for iron content. This survey’s results indicate that homemade bread was most often made using first quality wheat flour, or 70-78% extraction rate flour for which national fortification standards exist. Notably, GNNS 2009 results indicate that the iron content of homemade bread was higher than that of commercially baked bread, indicating that commercial bakeries are either using non-fortified first quality flour, or using best quality flour (10-25% extraction rate flour for which national fortification standards do not exist).

Overall the survey found that only 24.9% of bread samples were adequately fortified, which would not be sufficient for reductions in micronutrient deficiencies at a population level. These bread sample results are supported by GAIN’s estimates of the market share of fortified wheat flour (based on total production of fortified flour and production of all flour) of 21.2%. Thus, to the extent that factories are currently equipped to fortify, the data suggests that these factories are adequately fortifying.

Regardless, most of the wheat flour used to make bread both in commercial bakeries and at home was not fortified with iron or fortified with insufficient iron. This lack of fortification is seen in all regional strata. In addition, because iron is often used as a marker for the presence and adequate coverage of fortification with other micronutrients, we can conclude that because Georgian bread is inadequately fortified with iron, it is probably inadequately fortified with other micronutrients, such as folic acid (see discussion above).

Recommendations

1. The current fortification efforts must continue and should be expanded. Though additional investigations have been recommended to better understand the etiology of iron deficien-cy, the current prevalence of folate deficiency must be addressed, and there is little risk of exposing the population to iron overload as the iron compound used in Georgia’s fortifica-tion program, electrolytic iron, has low bioavailability. The expansion of the fortification program and implementation of additional research should be conducted concurrently; thus enabling the fortification program to address folate deficiency while the etiology of anemia is investigated.

2. If the results of future investigation contradict the GNNS 2009 findings, and iron defi-ciency is indeed found to be an important health problem in Georgia, the necessary policy and regulatory steps should be taken to ensure that flour milled in Georgia or imported into Georgia is adequately fortified with iron and other micronutrients according to Georgian regulations and international recommendations.14 In this case, because bread consumed in Georgian households is both purchased from stores and made at home, all types of flour for human consumption should be adequately fortified, including flour sold at the retail level directly to consumers and flour used by large- and small-scale commercial bakeries.


3. If flour fortification with iron is expanded, a quality assurance and monitoring system should be established to ensure that wheat flour milled in Georgia or imported into Geor-gia meets the requirements of Georgian regulations and international recommendations. Several sets of recommendations exist to assist in the implementation of such monitoring systems.11, 13

Salt iodization, storage, and consumption

Salt consumed by Georgian household members is currently well iodized. All specimens collected had added iodine, and very few specimens had inadequate levels of iodine. This demonstrates some improvement when compared to the results of the 2005 survey15 in which school-aged chil-dren brought household salt to school. In that survey, 90.6% of household salt specimens were adequately iodized. Nonetheless, only about one-half of households respondents reported that their salt was iodized, and more than one-third did not know.

Salt storage practices in many households expose salt to humid ambient air which may result in dampening of the salt and seepage of iodine to the bottom of the container. Nonetheless, the results of iodine testing of household salt demonstrate that, if this occurs, it has little effect on the iodine content of household salt.

A large proportion of both non-pregnant and pregnant women add salt to their food before eat-ing it, and many add salt before tasting their food. Hence, salt consumption is common in these target groups. However, this survey did not measure the quantity of salt added to food nor con-tained in other foods.

Recommendations

1. Maintain and enhance current monitoring and evaluation practices of salt iodization. Such practices should follow international recommendations.16 Food fortification programs, even when functioning as well as salt iodization in Georgia, need frequent monitoring to ensure that proper fortification is performed, good coverage is maintained, and the desired outcomes are continuously achieved.

2. Given the advantages of salt consumption in maintaining iodine intake and the strong dis-advantages of salt consumption in enhancing the risk for hypertension and cardiovascular disease, a much more detailed measure of total salt intake should be carried out in the Georgian population.

Acute protein-energy malnutrition

Overall, acute protein-energy malnutrition is not a significant problem in children less than 5 years of age, non-pregnant women, or pregnant women. Although prior data for adult women are largely unavailable, the prevalence of acute protein-energy malnutrition has been stable in the past 10 years, as indicated by comparing GNNS 2009 results to those of prior Multiple Indicator Cluster Surveys (MICS): 1999 MICS, 2.3%; 2005 MICS, 2.1%, and GNNS 2009, 1.6%.

overweight and obesity

Overweight and obesity, found in 19.9% of young children and 42.1% of non-pregnant women, is a much greater problem. Overweight in pregnant women could not be assessed in the GNNS 2009 because there is no standard cut-off for mid-upper arm circumference (MUAC) in pregnant


women which defines overweight and obesity. However, given the high prevalence in non-preg-nant women, it may be safe to assume that overweight and obesity also exist in pregnant women.

In children less than 5 years of age, the decline in the prevalence of overweight and obesity with age may indicate a change in feeding or exercise habits as young children grow older. Similarly, the lower prevalence of overweight and obesity in Armenian children imply some difference in these factors between Armenian populations and the other ethnicities in Georgia. Although the MICS done in 199917 did not analyze the prevalence of overweight and obesity, the 2005 MICS4 showed that 15.2% of children less than 5 years of age had overweight or obesity. Unfortunately, the report from the 2005 MICS does not present a measure of the precision for this estimate, so we cannot determine if the increase from 15.2% in 2005 to 19.9% in 2009 is statistically significant. Moreover, the 2005 MICS used the NCHS:CDC:WHO reference popula-tion, whereas the GNNS 2009 used the WHO Growth Standard as a reference.

Recommendations

1. Factors leading to overweight and obesity in young children and adult women should be further investigated in order to design specific interventions appropriate for the Georgian population. Such investigation could include describing methods of infant and young child feeding, especially changes in feeding practices during early childhood. Of course, because overweight and obesity are largely dependent on complex combinations of behav-iors, their investigation requires specific expertise and long-term commitment.

2. An analysis of the morbidity and mortality associated with childhood and adult overweight and obesity should be done to help marshal resources for long-term interventions.

3. Additional data should be collected to quantify the severity and prevalence of overweight and obesity in pregnant women. Indicators could include pregnancy weight gain which must be collected in special prospective follow-up investigations of pregnant women.

Chronic protein-energy malnutrition

The prevalence of chronic protein-energy malnutrition (or stunting) in children less than 5 years of age is statistically significantly elevated above the level seen in the WHO Child Growth Standard (2.3%). According to the suggested classification from WHO, the current prevalence of stunting of 11.3% in Georgia is considered “low.”18 As shown in Table 4, stunting is substantially less common in Georgian children than in the children of the neighboring countries of Azerbaijan, Ar-menia, and Turkey, but more common than in Germany or the United States.

The prevalence of stunting has remained stable in the past 10 years: 1999 MICS, 11.7%; 2005 MICS, 10.4%, and GNNS 2009, 11.3%. Although measures of precision are not available for the two MICS, these estimates are most likely not statistically significant.

Nonetheless, this does not mean that stunting is without public health importance in Georgia. Any degree of stunting over and above that found in the WHO Child Growth Standard is cause for concern and should be addressed by nutrition and health programming.

underweight

Underweight is not a public health problem in Georgia. The prevalence of underweight in Geor-gian children less than 5 years of age was not elevated. Given the lack of wasting and the high prevalence of overweight, this is not surprising.


table 4. prevalence rates of stunting in children less than 5 years of age, in Georgia and selected other countries.

Country % stunted(year of survey)

Georgia 11.3 % (2009)

Azerbaijan 34.4 % (2000)

Armenia 21.4 % (1998)

Turkey 32.9 % (1993)

Sweden No data

Germany 1.5 % (2003)

USA 3.9 % (2001)

Breastfeeding

Low birthweight is not common in Georgia. The majority of newborns in Georgia are breastfed at some time in their lives. Breastfeeding is initiated promptly after delivery in most children; however, breastfeeding does not last long. Only about one-half of children less than 6 months of age are exclusively breastfed, and on average children are weaned at the age of 9-10 months. Continued breastfeeding at 12-14 months and 20-23 months of age is found in only a small pro-portion of children. WHO recommends that exclusive breastfeeding should be practiced until age 6 months and extended breastfeeding should be encouraged until age 2 years.19

Complementary feeding is introduced sufficiently early in most children; however, as indicated above by the low prevalence of exclusive breastfeeding, probably too early in many children. Moreover, complementary feeding has inadequate diversity in one-half of children. Although complementary feeding is given with sufficient daily frequency, a minimum acceptable diet is eaten by fewer than one-half of children 6-23 months of age. An age-appropriate combination of breastfeeding and complementary feeding is only practiced by slightly more than one-third of children less than 24 months of age.

As shown in Table 5, the proportion of children a) initiating breastfeeding early after delivery, b) exclusively breastfeeding, and c) having timely introduction and adequate frequency of comple-mentary feeding all improved substantially compared to MICS surveys done in 1999 and 2005. There may be several possible reasons for the sharp rise since 2005 in the prevalence of exclusive breastfeeding in children under 6 months of age.

First, this increase may be a result of an inaccurate estimate which does not accurately reflect a true change in infant feeding habits in the Georgian population. This may have resulted, at least in part, from differences between the questions asked of mothers in the MICS 2005 and GNNS 2009. The standard MICS3 questionnaire used in the Georgia MICS 2005 asked separate ques-tions about several specific liquids which mothers often do not consider to be food and which they may not consider when asked about exclusive breastfeeding. These liquids include water; sweetened, flavoured water or fruit juice or tea or infusion; oral rehydration solution; infant for-mula; and tinned, powdered, or fresh milk; as well as “any other liquids.” On the other hand, the GNNS 2009 mentioned such liquids in a list contained in the single question “Yesterday, did [name] eat anything other than breastmilk? This includes water, baby formula, juice, or any solid foods as well as regular food.” Although this difference in questions may seem small, because maternal recall of the introduction of non-breastmilk food is poor,20 the extra memory stimulation


provided by the MICS questions may lead to a somewhat lower estimate of exclusive breastfeed-ing because mothers more accurately recall giving their children non-breastmilk food and liquids.

Second, there may be inaccuracy in the results from the MICS 2005 leading to a low estimate of exclusive breastfeeding; however, this is less likely because MICS procedures, including data analyses, are quite standardized. All MICS surveys use the same questionnaire and most, if not all, use a standard data analysis program. One would expect an erroneous question or analysis procedure to be discovered in at least one of the other 50 MICS survey done every 5 years.

Third, there may have been a real change in the population in infant feeding habits. The MICS 2005 results show that a large proportion of young infants were not considered exclusively breastfed because they ate other types of milk or infant formula. If in the intervening years, be-cause of economic or other considerations, mothers were less able or willing to purchase milk and infant formula, the exclusive breastfeeding prevalence may have sharply increased. Moreover, a true increase in the exclusive breastfeeding prevalence is consistent with the improvement in other breastfeeding indicators seen between MICS 1999, MICS 2005, and GNNS 2009.

Nonetheless, the proportion of children with extended breastfeeding at 12-14 months of age and 20-23 months of age has not changed since 2005 and is still too low, as mentioned above.

table 5. Breastfeeding indicators (see reference 21 for definitions) in two prior MICS and GNNS 2009.

Indicator (age group) mICS 1999 mICS 2005 GNNS 2009

Breastfeeding initiated with 1 hour after deliver(<24 months of age)

Not available 36.6 % 66.3 %

Exclusive breastfeeding (0-5 months of age) 18 %** 10.9 % † 54.8 % †

Continued breastfeeding (12-15 months of age) 30.3 % 40.5 % 36.5 %

Continued breastfeeding (20-23 months of age) 12.0 % 19.6 % 16.6 %

Timely introduction of complementary feeding *

(6-9 months of age) 12.2 % 34.8 % 43.1 %

Adequate frequency of complementary feeding *

(6-11 months of age)Not available 28.1 % 40.2 %

Adequately fed infants *

(0-11 months of age) Not available 19.8 % 47.3 %

* This MICS indicator differs from any of the indicators listed in the WHO/UNICEF recommendations.22 As a result, this MICS indicator is not further considered or discussed in this report. ** MICS 1999 age group includes only children 0-3 months of age † See discussion in text above of possible reasons for large difference between MICS 2005 and GNNS 2009.


Recommendations

1. Ensure that all delivery facilities in Georgia properly encourage and facilitate early initiation of breastfeeding by mothers delivering in their facilities. Facilities in Achara and Guria and Samegrelo and those located in rural areas should be targeted first if resources are limited. UNICEF and WHO have published recommendations for appropriate hospital policy and practice.23

2. Ensure that all providers of preventive and curative health care for pregnant women, in-fants, and young children understand the benefits of breastfeeding and the current breast-feeding recommendations of the Ministry of Labor, Health, and Social Affairs. Ensure that all such providers encourage and support pregnant women and new mothers to breastfeed according to international recommendations.19 As above, Achara and Guria, Samegrelo, and rural areas in general should be especially targeted.

3. The difference between the MICS 2005 and GNNS 2009 results for exclusive breastfeed-ing is striking and warrants additional investigation. An independent estimate should be done of the exclusive breastfeeding prevalence in infants less than 6 months of age. Moreover, there should be a review of the MICS 2005 data and data analysis procedures to determine if the estimate of 10.9% exclusive breastfeeding is accurate.

4. Because there is evidence that children who are not breastfed are more likely to become overweight24, enhancing breastfeeding should be seen as a strategy to prevent childhood obesity, which, as seen above, is common in children less than 5 years of age in Georgia.

Efforts should be made to educate pregnant women and new mothers in proper feeding of infants and young children. As mentioned above for breastfeeding, practitioners who care for pregnant women and young mothers should be familiar with existing Georgian and international recommen-dations for infant and toddler feeding and should educate their patients to adhere to these recom-mendations. Measures of the diversity and frequency of complementary feeding were somewhat lower in Achara and Guria, Kakheti, and Samagrelo; programs to improve complementary feeding could be preferentially targeted to these areas first.


INtRoDuCtIoN AND BACKGRouND

Georgia has suffered repeated economic crises, war, and political instability since independence from the Soviet Union in 1991. As a result, social, economic, and health conditions have often been worse than those in other countries which were part of the Soviet Union. These conditions have had unknown effects on the nutritional status of the population. Past nutrition assessments have been small local surveys which measured only a small number of indicators. These have indicated the possible presence of elevated levels of stunting, overweight, and anemia in young children; overweight, anemia, iron deficiency, and resurgent iodine deficiency in non-pregnant women; iodine deficiency in pregnant women; and a decline in the coverage of adequately io-dized salt in households. In contrast, there have also been three nationwide nutrition assessment surveys since independence, as shown in Table 6 below. Clearly the coverage of salt iodization has increased since the 1999 Multiple Indicator Cluster Survey (MICS). Wasting in young chil-dren has not been a substantial problem in the past; however, there has been some stunting and overweight. School children had adequate urinary iodine in 2007, indicating good coverage with satisfactorily iodized salt. Anemia was a problem in non-pregnant women 15-49 years of age. Comprehensive data are still lacking on the prevalence of anemia and iron deficiency in young children and pregnant women, the predominant causes of anemia in any population group, the prevalence of iron and folate deficiency in women, the prevalence of chronic energy deficiency and overweight in adult men and women, as well as other nutritional conditions. Although there are no data on vitamin A deficiency in young children or women, there are no indications of a problem in Georgia at present.

The Georgia National Nutrition Survey (GNNS 2009) provides estimates for many of those nutri-tion indicators which have not been adequately measured in past surveys, thus providing to the Government of Georgia, UNICEF, other United Nations (UN) agencies, donors, and partners the comprehensive information on nutritional status needed to formulate nationwide, data-driven policy and evaluate ongoing nutrition programs. For example, flour fortification with iron and folic acid was begun in 2006. To date, no data are available to monitor the coverage of fortified flour products or the population effect of this program. Moreover, data on the iodine status of the population is needed to monitor the enforcement of the national Law on the Prevention of Disorders Caused by Iodine, Micronutrients and Vitamins. In addition, regional estimates, gener-ated by using a stratified sample, can be used by local authorities to target programs to areas and subgroups at greatest risk of various types of malnutrition.


table 6. Results of measurement of nutrition indicators included in nationwide surveys done since independence, Georgia 1999-2009

Indicator mICS199917

mICS200525

School200515

Households

Salt adequately iodized 8.1% 87.2% 90.6%

Children less than 5 years of age

Wasted 2.3% 2.1 %

Stunted 11.7% 10.4%

Overweight - 15.2%

School-age children

Low urinary I2 4.4%

Median urinary I2 320.7

Goiter 32.4%

Non-pregnant women 15-49 years of age

Anemia TOTAL 27.8%

Mild 23.1%

Moderate 4.4%

Severe 0.3%

Post-partum vitamin A supplementation 8.6% 15.8%


GoALS AND oBjeCtIVeS

The objectives of the GNNS 2009 included the following:

In the current population of Georgia, excepting those areas outside the control of the government of Georgia,

1) Estimate the current coverage of adequately iodized salt in households.

2) Estimate the current coverage of iron fortification in bread in households.

3) Estimate the current prevalence of acute malnutrition (wasting) and chronic malnutrition (stunting) in children less than 5 years of age.

4) Estimate the current prevalence of chronic energy deficiency and overweight in non-pregnant women 15-49 years of age.

5) Estimate the current prevalence of undernutrition among pregnant women.

6) Estimate the current prevalence and severity of anemia and of iron deficiency in children 12-59 months of age and non-pregnant women 15-49 years of age.

7) Estimate the current prevalence and severity of anemia in pregnant women.

8) Estimate the current prevalence of folate deficiency in non-pregnant women 15-49 years of age.

Additional variables which may influence various types of malnutrition or play a causative role were also assessed; however, their measurement was not the first priority. Such additional vari-ables included assessment of socio-economic status, individual food consumption patterns, infant feeding and breastfeeding practices, and other factors. The results of some of these variables may not be presented in this report. In addition, the survey collected data to assist in the evalu-ation of fortification programs, including collection of bread specimens for laboratory testing, as described below in greater detail.


metHoDS

Study population

The sampling universe for the GNNS 2009 included the entire country of Georgia with the excep-tion of areas outside the Georgian Government’s control. The target groups about whom data were collected included the following:

table 7. target groups, outcomes, and source of sample, GNNS 2009

target group outcome measured Source of sample

Households • Coverage and adequacy of salt iodization• Coverage and adequacy of iron fortification of

bread

Household sample of population


• Prevalence of acute protein-energy malnutrition (wasting)

• Prevalence of chronic protein-energy malnutrition (stunting)

• Prevalence of overweight and obesity• Prevalence of anemia (only in children 12-59

months of age)• Prevalence of iron deficiency (only in children

12-59 months of age)



• Prevalence of chronic energy deficiency• Prevalence of overweight and obesity• Prevalence of anemia• Prevalence of iron deficiency• Prevalence of folate deficiency


Pregnant women • Prevalence of undernutrition• Prevalence of anemia

Ante-natal clinic attendees

Table 8 shows the inclusion criteria used when recruiting individuals in the various target groups for data collection.

table 8. Inclusion criteria, by target group, Georgia National Nutrition Survey2009

target group Inclusion criteria

Households • An adult household member who gives written consent for survey data collection

• Household members reside in Georgia at the time of data collection


• Age 0-59 months at the time of survey data collection (that is, child has not yet reached 5th birthday)

• Parent or guardian gives written consent for survey data collection• Currently resides in Georgia and is considered a usual household

member by adults living in the household



• Age 15-49 years at the time of survey data collection• Gives written consent for survey data collection• Resides in Georgia and is considered a usual household member by

other adults living in the household at the time of data collection

Pregnant women • Appears at one of the selected ante-natal care facilities for ante-care visit during survey data collection days

• Is pregnant by self report at the time of data collection• Gives written consent for survey data collection• Resides in Georgia at the time of data collection

Case definitions and measurement methods of outcomes

Adequately iodized salt in households

Household salt specimens were tested using the titration method16 in the NCDCPH Imereti Zonal Branch Diagnostic Laboratory. Salt was considered adequately iodized if the iodine concentration was greater than 15 parts per million (ppm) and less than 40 ppm.16 This testing method was in accordance with the State Standard of Georgia #19-98 (salt iodine common food), titration meth-od, testing methodologies: a) sample collection and preparation- ,,GOST* 13685” and ,,GOST 26929”, b) testing methodologies - ,,GOST 26927, 26930, 26931, 26932, 26933 and 26934”.

The results of re-testing a subsample of salt specimens in a reference laboratory in the Ukraine (V. P. Komissarenko Institute of Endocrinology and Metabolism) showed excellent agreement be-tween the Georgian and Ukrainian laboratories. See Annex 3 “Quality assurance during and after data collection” for a more complete description of these results.

Iron fortification of bread

The iron concentration of household bread was measured using atomic absorption spectropho-tometry26 performed in the Central Laboratory of the Institute of Horticulture, Viticulture, and Oe-nology. The total iron content of the bread specimens cannot precisely distinguish which bread specimens are fortified and which are not because the innate concentration of iron in Georgian wheat flour and bread is largely unknown. However, one set of recommendations states that if the per capita consumption of bread is 200 grams or more, 30 mg/kg of iron should be added to wheat flour.14 In addition, Georgian regulations state that bakery products should contain 30-60 ppm of iron.27 Therefore, the proportion of bread specimens which had 30 ppm or greater iron concentration was calculated to determine what proportion of bread specimens may have been made from flour complying with Georgian regulations.

Birthweight

Low birthweight is defined by the World Health Organization (WHO) as a birthweight less than 2500 grams. High birthweight is defined as greater than or equal to 4500 grams.28

* GOST refers to a set of technical standards maintained by the EuroAsian Interstate Council for Standardization, Metrology and Certification (EASC), a regional standards organization operating under the auspices of the Commonwealth of Independent States.


Breastfeeding

The breastfeeding indicators measured in the GNNS 2009 were taken directly from a set of rec-ommendations from WHO and UNICEF.22 Because these indicators are calculated on a subset of children less than 5 years of age, some subgroup analyses have relatively little precision around group-specific estimates. For this reason, these analyses do not include the “Other” ethnic group. Estimates of breastfeeding indicators for this group, which included only 12 children < 24 months of age, would be too imprecise to draw any meaingful conclusions.

Although this reference gives detailed descriptions of each indicator, these definitions will be summarized below.

• Early initiation of breastfeeding: The proportion of children less than 24 months of age who were put to the breast within 1 hour of birth.

• Exclusive breastfeeding under 6 months: The proportion of infants less than 6 months of age who are fed only breastmilk and no other liquids or solids, with the exception of medi-cation and oral rehydration.

• Continued breastfeeding at 1 year: The proption of chldren 12-15 months of age who ate breastmilk the day before the interview.

• Introduction of solid, semi-solid, or soft foods as complementary foods: The proportion of infants 6-8 months of age who ate solid, semi-solid, or soft foods the day before the inter-view.

• Minimum dietary diversity: The proportion of children 6-23 months of age who ate foods from four or more of the seven food groups the day before the interview. These food groups include grains, roots and tubers; legumes and nuts; dairy products (milk, yogurt, cheese); flesh foods (meat, fish, poultry, liver/organ meats); eggs; vitamin-A rich fruits and vegetables; and other fruits and vegetables.

• Minimum meal frequency: The proportion of children 6-23 months of age who ate solid, semi-solid, or soft foods the minimum number of times the day before the interview. The minimum number of times depends on age and breastfeeding status:

o For breastfeeding children 6-8 months of age: 2 times

o For breastfeeding children 9-23 months of age: 3 times

o For non-breastfeeding children 6-23 months of age: 4 times

• Minimum acceptable diet: The proportion of children 6-23 months of age who eat a mini-mally acceptable diet, defined as eating food with minimal dietary diversity with minimum meal frequency, as defined above. This definition differs somewhat from that given in the recommendations.22 In these recommendations, a minimum acceptable diet in non-breast-fed children requires at least two milk feeds per day and does not count milk feeds when defining minimum dietary diversity. However, because the GNNS 2009 questionnaire did not distinguish milk feeds from other non-breastmilk foods, the definition used for minimum acceptable diet uses only the definitions given above for minimum dietary diversity and minimum meal frequency.

• Children ever breastfed: The proportion of children less than 24 months of age who were ever breastfed at any time in their lives.

• Continued breastfeeding at 2 years: The proportion of children 20-23 months of age who ate breastmilk the day before the interview.

• Age-appropriate breastfeeding: The proportion of children 0–23 months of age who are ap-propriately breastfed, defined as follows:


o For infants less than 6 months of age: exclusive breastfeeding, as defined above, the day before the interview

o For children 6-23 months of age: ate both breastmilk and solid, semi-solid, or soft foods the day before the interview

• Duration of breastfeeding: The median duration of breastfeeding among children less than 36 months of age. This is determined by calculating the one month age-specific propor-tions of children who ate breastmilk the day before the interview and determining the age at which 50% of children ate breastmilk the day before the interview. In this report, a chart of the 3-month moving averages of one-month age-specific proportions of children breastfeed-ing was produced and the median read from this chart.

Several indicators listed in the recommendations were not measured in the GNNS 2009. These included consumption of iron-rich or iron-fortified foods, predominant breastfeed-ing under 6 months, bottle feeding, and milk feeding frequency for non-breastfed children.

protein-energy malnutrition in children less than 5 years of age

Undernutrition (including wasting, stunting, and underweight) and overnutrition in children less than 5 years of age were defined using the WHO Child Growth Standard.29 Children with z-scores below -2.0 for weight-for-height, height-for-age, and weight-for-age were defined as wasted, stunted, or underweight, respectively. Moderate wasting, stunting, and underweight were de-fined as a z-score less than -2.0 but equal to or greater than -3.0. Z-scores less than -3.0 defined severe wasting, stunting, and underweight. Children with bilateral pitting edema in the feet or lower legs were automatically considered as having severe wasting, regardless of their weight-for-height z-score. All z-scores were calculated using computer program WHO Anthro v. 3.0.1.30

overnutrition in children less than 5 years of age

Overnutrition in children was also defined using z-scores calculated using the WHO Child Growth Standard. Any overnutrition was defined as a weight-for-height z-score greater than +2.0. Overweight was a weight-for-height z-score of greater than +2.0 but less than or equal to +3.0. Obesity was defined as a weight-for-height z-score greater than +3.0.

Before analysis of the prevalence of both under- and over-nutrition, outlying z-score values were excluded according to the criteria recommended by WHO.18 For the calculation of the prevalence of acute protein-energy malnutrition, overweight, and obesity, children with weight-for-height z-scores less than -5.0 or greater than +5.0 were excluded. For the calculation of the preva-lence of stunting, children with height-for-age z-scores less than -5.0 or greater than +3.0 were excluded. For the calculation of the prevalence of underweight, children with weight-for-age z-scores less than -4.0 or greater than +5.0 were excluded from the analysis.

Chronic energy deficiency and overnutrition in non-pregnant women 15-49 years of age

Chronic energy deficiency and overnutrition in non-pregnant women 15-49 years of age were as-sessed using body mass index (BMI), which is calculated by dividing the weight in kilograms by the square of the standing height in meters. The most common cut-off points for BMI to define levels of under and over nutrition in non-pregnant adults are shown below.31


table 9. Categories of protein-energy nutrition, by value of BmI, GNNS 2009

BmI Category of malnutrition

< 16.0 Severe

16.0 - 16.9 Moderate

17.0 - 18.4 At risk

18.5 - 24.9 Normal

25.0 - 29.9 Overweight

> 30 Obese

Because BMI is not valid in pregnant women, mid-upper arm circumference (MUAC) measure-ments were used in this group to assess protein-energy malnutrition. Although no international consensus exists, the World Food Programme (WFP) and the United Nations High Commissioner for Refugees (UNHCR) suggest defining malnutrition in pregnant women as a MUAC less than 22.0 cm.32

Anemia

Hemoglobin concentrations were measured on blood obtained by fingerstick or venipuncture us-ing a portable hemoglobinometer made by Human GmbH of Wiesbaden, Germany. The machine was operated according to the methods recommended by the manufacturer. The basic cut-off points for hemoglobin concentration used to define anemia depend on the age and sex of the person tested,1 as shown below:

Table 10. Definition of anemia by hemoglobin concentration for various age- and sex-specific groups, GNNS 2009

Age and sex group Hemoglobin concentration (g/dL)defining anemia

Children 6 months - 5 years < 11.0

Children 5-11 years < 11.5

Children 12-13 years < 12.0

Non-pregnant girls and women >13 years < 12.0

Pregnant women >13 years < 11.0

Boys and men >13 years < 13.0

The cut-off defining normal hemoglobin concentrations was also adjusted for survey subjects who live at high altitude.33 The altitude-specific adjustments are shown below.


Table 11. Adjustments in cut-off defining anemia, by altitude of residence, GNNS 2009

Altitude (in meters) of residence

Increase in cut-offpoint defining anemia (g/dL)

< 1000 No adjustment

1000 – 1249 + 0.2

1250 – 1749 + 0.5

1750 – 2249 + 0.8

2250 – 2749 + 1.3

2750 – 3249 + 1.9

3250 – 3749 + 2.7

3750 – 4249 + 3.5

4250 – 4749 + 4.5

4750 – 5249 + 5.5

5250 + + 6.7

The cut-off defining normal hemoglobin concentration in adults was also adjusted for smoking, as shown below.34

Table 12. Adjustments in cut-off defining anemia, by smoking status, GNNS 2009

Cigarettes smoked per dayIncrease in cut-off

point defining anemia (g/dL)

< 10 per day No adjustment

10 – 19 per day + 0.3

20 – 39 per day + 0.5

40 + per day + 0.7

Smoker but number of cigarettes per day unknown + 0.3

Iron deficiency

Iron deficiency in survey participants was measured using ferritin concentration in plasma. Fer-ritin is one of the two biomarkers recommended for use in population-based assessments of iron deficiency.34 The cut-off points defining iron deficiency are taken from WHO recommendations: 1) in children less than 5 years of age, a serum ferritin concentration below 12 µg/l defines iron deficiency, and 2) in non-pregnant women 15-49 years of age, a serum ferritin concentration below 15 µg/l defines iron deficiency.1 Because ferritin is an acute phase reactant which rises with inflammation, its measurement was accompanied by the measurement of C-reactive protein (CRP), an indicator of acute inflammation. A concentration of CRP of 5 mg/l or above was con-sidered indicative of acute inflammation in young children and women. Ferritin values in survey subjects with elevated CRP levels were excluded from the analysis of iron deficiency.


Both ferritin and CRP were tested in the NCDCPH Imereti Zonal Diagnostic Laboratory using the photometric turbidimetric method using the “Turbi-Quick” Immuno/ Coagulation Analyzer made by Vital Diagnostics Srl in Forli, Italy. Reagents for ferritin and CRP testing were supplied by Hu-man GmbH of Wiesbaden, Germany. Test reagents included a memory stick which maintained the calibration curve needed for the test. An aliquot of a random selection of 400 serum speci-mens obtained from children and women during GNNS 2009 data collection were sent to the Human GmbH laboratory in Wiesbasden for validation. The comparison of the results from the Georgian and the German laboratories can be seen in Annex 3.

Folate deficiency

Folate deficiency was assessed using folate concentration measured in plasma separated from blood obtained by venipuncture. As recommended by WHO, a plasma folate concentration be-low 4.0 ng/mL (10 nmol/L) was considered indicative of folate deficiency.12 However, in order to compare the GNNS 2009 results to prior surveys done in other countries, as shown in the Conclusions, Discussion, and Recommendations section, re-analysis of the data was carried out using the older cut-off point of 3.0 ng/mL. Testing was done using in the NCDCPH Imereti Zonal Branch Diagnostic Laboratory using an enzyme-linked immunosorbant assay (ELISA) method and a microbiologic test kit (DRG International Inc., USA.). All procedures followed the laboratory kit manufacturer’s recommendations.35

Sampling scheme

A summary of the sampling scheme and sample size calculation is presented below. For a much more detailed explanation of these procedures, see Annex 1.

Households, children, and non-pregnant women

Cluster sampling of households was done to obtain a random sample of households, children less than 5 years of age, and non-pregnant women in the Georgian population. In the first stage of sampling, census units were selected as primary sampling units using equal probability from a list of 606 census units which had already been selected probability proportional to size from all census units in Georgia for use in population-based surveys. In each of eight regional strata, 25 census units were selected. The two largest ethnic minorities, Azerbaijanis and Armenians, were oversampled in order to generate independent estimates for each minority. This was done by selecting additional census units in the two regional strata in which a large proportion of the population consists of one of these minorities. As a result, the total sample of households were distributed in 236 census units (or clusters).

During a second stage of sampling, the required number of households from the household list in each selected census unit was selected. Systematic random sampling was used, starting at a randomly selected starting point. Once households were selected, sampling was complete for children; all eligible children less than 5 years of age who lived in selected households were re-cruited for the survey sample. All eligible non-pregnant women 15-49 years of age who lived in a randomly selected subsample of these households were also eligible for inclusion in the survey sample. Bread and salt specimens were collected in the same households in which non-pregnant women were eligible for recruitment. Pregnant women found in selected households were not included in the survey nor were any data collected from them.

In census units which had an insufficient number of households to select the required number of households for that cluster, all households were eligible for child recruitment, and the number of households needed to recruit non-pregnant women and obtain bread and salt specimens were se-


lected from this original census unit. The number of households required to complete the desired number of children were selected randomly from an adjacent census unit.

pregnant women

Selection of pregnant women began with a random selection with equal probability of 25 facilities providing ante-natal care in Georgia. Because in each selected facility women were recruited for the same number of days, and the number of visits per day varies greatly among facilities, the number of women recruited from each facility (and therefore the number of women in each clus-ter) were quite different. However, because the facilities were selected with equal probability, the resulting sample of pregnant women is equally weighted by region. Sampling was stratified on ethnicity by selecting additional ante-natal care facilities in regions with a substantial number of minority pregnant women.

Sample size calculation

The required minimum sample size for the GNNS 2009 sample was calculated separately for each major outcome and target group. All sample size calculations used the following assumptions:

1) The limit of statistical significance (alpha) = 0.05

2) The power (1-beta) = 0.8

3) The population size from which the sample was selected was assumed to be greater than 10,000; hence, the finite population correction factor was not used


Table 13 below shows the calculated total minimum number of households and individuals from whom data had to be collected to achieve the desired precision around the estimate of prevalence for each target group and for each survey outcome in each regional stratum. Wherever possible, the assumptions used to calculate desired sample size were based on the results of previous surveys. However, for variables for which no prior data were available, assumptions were inten-tionally conservative. For example, in the absence of any prior data, the prevalence of anemia in children was assumed to be quite high with a high design effect.

table 13. Number of households and individuals from whom data are needed, for different tar-get groups and outcomes, GNNS 2009

target group and type of malnutrition

Assumed current prev-alence

precision required in each stratum

(percentage points)

Design effect

assumed

Number needed with

data in each

stratum

minimum total

number needed

with data

Households

Iodized salt 90 % ±5 1.8 243 1,944

Iron fortified bread 50 % ±10 2.0 193 1,544

Children 0-59 months

Wasting (z-score <-2.0) 3 % ±3 2.0 249 1,992


Stunting (z-score <-2.0) 12 % ±5 2.0 325 2,600

Overweight (z-score >-2.0) 15 % ±6 2.0 273 2,184

Anemia (< 11.0 g/dl) 35 % ±9 2.5 270 2,160

Iron deficiency 50 % ±10 2.5 241 1,928

Non-pregnant women

Malnutrition (BMI <17.0) 5 % ±5 2.0 146 1,168

Overweight (BMI > 25.0) 50 % ±10 2.0 193 1,544

Anemia 28 % ±8 2.0 243 1,944

Iron deficiency 41 % ±10 2.0 186 1,488

Folate deficiency 50 % ±10 2.0 193 193*

Pregnant women**

Low MUAC 50 % ±10 2.0 193 579

Anemia 50 % ±10 2.0 193 579

* Sample specimens for folate testing were not stratified because only a single nationwide estimate was to be calculated

** Sample sizes for pregnant women are much lower because regional stratification was not done, and ethnic-ity-specific stratified sampling resulted in only three strata.

The outcomes shown in italics are those which required the largest number of individuals in that target group and, thus, determined the minimum number of that target group for the survey sample. Because the sample tested for folate deficiency was not stratified, it required a much smaller sample size than other outcomes. To obtain this much smaller sample size, folate testing was done on only two women in each cluster.

The number of households to select for the survey was then calculated from 1) the minimum number of households and individuals from whom data were needed, 2) the estimated individual non-response rate, 3) the estimated household non-response, and 4) the average number of in-dividuals in each household. For example, to collect hemoglobin data on 2,160 children 12-59 months of age, survey teams had to recruit children from 23,716 households; however, to collect hemoglobin data on 1,944 non-pregnant women, women had to be recruited from only 3,396 households because there are, on average, many more eligible women than eligible children per Georgian household. Therefore, it was necessary to select women from only a subsample of the total sample of 23,716 households. Because response rates and the average number of women are different for each stratum, the fraction of households from which to recruit women varied by stratum.

pregnant women

The sample size for pregnant women, as shown in Table 13 above, is 193 for each of the three ethnic strata. Assuming 90% response, the total number of pregnant women to be selected in ante-natal facilities was at least 215 (193 divided by 0.9) in each ethnic group for a total sample size of 645.


enrollment and recruitment procedures


In each selected census unit, survey teams traveled to each selected household (and to no other households) to begin recruitment and collect survey data. Household data were collected from: 1) all households containing an eligible child less than 5 years of age, 2) all households from which non-pregnant women were eligible to be recruited, and 3) all households from which a salt or bread specimen was obtained. In those households which were not identified as households in which non-pregnant women should be recruited and bread and salt specimens collected, if no eligible child lived in that household, the household was skipped and no data collected. In such households, because no individuals were enrolled and no specimens collected, no household in-terview was conducted. Households in which non-pregnant women were eligible for recruitment and bread and salt specimens requested represent a random sample of all households in each re-gional stratum and altogether in Georgia. The household data from households in which children were recruited but in which non-pregnant women were not eligible provide additional information of interest regarding the households in which children live, but are not a representative sample of all Georgian households and were not included in analysis of only household variables. Figure 1 below shows a decision algorithm which was used to determine whom to recruit and what speci-mens to collect in each selected household.

Figure 1. Recruitment procedures for household survey, GNNS 2009

Approach household

on list

Yes No

Is there a child under 5 years of

age?

No

1. Do not complete any forms.

2. Go to next household.

Yes

1. Recruit all children in household.

2. Administer household and child questionnaires.

3. Collect fingerstick blood from children 12-59 months of age.

1. Recruit all children in household.

2. Recruit all non-pregnant women 15-49 years of age in household.

3. Administer household questionnaire.

4. Administer child and woman questionnaires, as needed.

5. Collect blood on all children and women recruited (venipuncture blood on 1st two women in cluster).

6. Collect salt specimen. 7. Collect bread specimen.

Are non-pregnant women eligible in this

household?


Upon arrival at a selected household, survey team members explained the survey’s purpose, methods, and procedures, and requested written consent from a responsible caretaker for eligible children’s participation and from eligible non-pregnant women in those households from which women were recruited. For both children and women, all eligible individuals in a household were recruited for survey participation. If an eligible child or woman was missing at the start of the survey team’s visit, household members or others in the community were asked to fetch them; however, the teams could often not wait for potential survey participants who had not arrived by the time collection of other data has been completed. In such cases, survey team members made an appointment for a return visit when the eligible individual would be home. If no one in the household was at home at the time of the survey team’s visit, the team determined from a neigh-bor when the household members would return home and asked the neighbor to notify the family of the appointed time for the revisit. Survey teams attempted to make two return visits over at least 2 days before abandoning data collection for a selected household or individual child or woman. However, sometimes such return visits might substantially delay departure from a cen-sus unit; in such cases, in the interest of efficiency, the survey team left before three visits had been completed. Survey teams recorded for each selected household or individual whether data collection was completed, and, if data collection was not completed, why. These data allowed calculation of response rates and the determination of reasons for non-response. Households or individuals from which data collection could not be completed were not replaced; the sample size calculations presented above already account for loss due to non-response.

pregnant women

During scheduled days, survey teams recruited consecutive pregnant women who visited the selected ante-natal facility. After an eligible pregnant woman had completed her ante-natal visit at the clinic, survey team members explained the survey purpose, methods, and procedures, and requested verbal consent for her participation. After consent was given, data were collected from the woman. If consent was not given, or for some other reason the woman did not provide complete data, the reasons were recorded on the data collection form.

Data collection

team composition

Households, children, and non-pregnant women. Each survey team visiting selected households consisted of four people: one driver, one interviewer, one anthropometrist, and one laboratorian. The driver will have no additional duties other than transport. One individual who was not the driver was designated team supervisor and was responsible for all aspects of household sam-pling and data collection. The interviewer conducted all interviews of household members to collect data. The interviewer and anthropometrist were both trained in anthropometry, with the interviewer acting as the anthropometry assistant. The laboratorian carried out the fingerstick on eligible children and fingerstick or venipuncture on eligible non-pregnant women. He or she also measured the hemoglobin concentration and collected and processed blood obtained either by fingerstick or venipuncture for later testing for iron status indicators and folate concentration.

Pregnant women. Because the survey of pregnant women will, in most ante-natal facilities, re-quire collection of data from few pregnant women each day, a single person easily carried out all the necessary data collection, including the interview, fingerstick, and measurement of hemoglo-bin concentration.


Household procedures

Interviews. Interviews were conducted by appropriate survey team members who had received instruction in the type of data to be collected by each specific question and the reason these data are being collected. Interview questions were read verbatim from the interview form. Respon-dents were allowed to refuse answers to any or all of the questions.

Anthropometric measurements. All anthropometric measurements were taken using standard methods. For example, for children less than 5 years of age, all measurements were taken using the procedures outlined in the UNICEF training manual “How to Weight and Measure Children.”36 Children’s height or length was measured using a height board manufactured by Shorr Produc-tions, USA. Weight was measured using a UniScale, a bathroom-type scaled used in nutrition sur-veys, including UNICEF MICS, for many years. For non-pregnant women, weight was measured using the same scale as used for children. Height was measured using a portable stadiometer while the subject stood against a vertical surface.

Physical examination. In all cases where protein-energy malnutrition is assessed in children, the feet and lower legs were examined for edema by the anthropometrist to rule out edematous mal-nutrition which invalidates anthropometric indices which include weight. Although theoretically, adults should also be examined for edema, the many non-nutritional causes of pitting edema produce too many false positive findings in populations where edematous malnutrition is not common. Therefore, adults were not be examined for edema. In many children, some measure of mild restraint is required for certain portions of such examinations. Such restraint is minimized and carried out only with parents’ permission or by parents themselves.

Collection and processing of laboratory specimens. Table 14 below summarizes the biologic specimens collected from each target group in the survey.

table 14. Summary of biologic specimens to be taken, by target group, GNNS 2009.

target group Specimen methods of collection Storage matrix outcome measured

Children 12-59 months of age

Blood Fingerstick Immediate testing for hemoglobin

Anemia

Microtainer Iron deficiency


Blood Fingerstick or venipuncture

Immediate testing for hemoglobin

Anemia

Microtainer Iron deficiency

Venipuncture Blood tube Folate deficiency

Pregnant women Blood Fingerstick Immediate testing for hemoglobin

Anemia

Household Salt Self-collect Dry, in plastic bag Iodine level

Bread Self-collect Dry, in plastic bag Iron level

Fingerstick blood was collected by piercing the skin with a new, disposal lancet after cleaning the skin with alcohol. In children, a pediatric lancet was used which penetrated the skin no deeper than 1.5 mm, while adult lancets penetrated the skin to a depth of 2.0 mm. As much blood


as possible, up to 1.0 ml, was collected from the fingerstick site into a microtainer. From this microtainer, 20 microliters were pipetted using an auto-pipette into the cuvette for use in the Hu-maMeter® portable hemoglobinometer. The remaining blood remained in the microtainer for later centrifugation and separation of serum. Centrifugation and separation was done in the evening of the day the blood specimen was collected. The resulting serum specimens were kept frozen at -20 or -70 degrees C until analyzed in the laboratory.

In two women per cluster, venipuncture was done instead of fingerstick. Blood was collected into an appropriate tube using the Vacutainer® system. From this tube, as from the microtainer, 20 microliters were auto-pipetted into the HumaMeter® cuvette for hemoglobin testing in the household. The remaining blood was kept in cold storage until centrifuged and separated the same evening. Serum from these specimens was stored in small plastic tubes suitable for freez-ing at -60 degrees C.

Bread specimens were placed in a small sealable plastic bag. After stirring the salt in the house-hold storage container, approximately 5 g of salt was placed into a clean bag. For bread, only one specimen consisting of 100 grams was collected per household. If possible, survey teams collected a specimen of the type of bread eaten most frequently in that household. If, at the time of data collection, there was no such bread in the household, a specimen of whatever bread was available in the household was collected.

Data collection instruments

Data collection forms (one for each target group) were written originally in English, then translat-ed into Georgian, Azerbaijani, and Armenian. Experienced translators of Azerbaijani and Armenian will accompany survey teams in minority regions. A translated copy of the questionnaires was provided to these translators to read to survey respondents; however, data were recorded on the Georgian data collection form. See Annex 2 for copies of these data collection forms.

training for study personnel

Training for survey team members consisted of 5 days of classroom instruction and practice and 2 days of pretesting all survey procedures, including interviews, examination for edema, anthro-pometric measurement, and biologic specimen collection (except venipuncture). Two survey workers from each survey team were taught to measure and record height, length, weight, and MUAC for children and adults in a standardized fashion. Inter-measurer variability, intra-measurer variability, and difference from an expert measurement was measured and excess variability corrected. Training for anthropometrists included a description of edema and how to examine children for its presence.

At least one experienced laboratorian on each survey team was trained to collect the biologic specimens necessary for this survey. Such training included the use of the HumaMeter® hemoglo-binometer to measure hemoglobin concentration. Fingerstick and venipuncture technique were reviewed and practiced on other survey team members. The processing and storage of speci-mens was also taught during the training period and closely supervised during the first days of the survey.

Team leaders were selected and specially trained at the end of the training session.


Data analysis

Data analysis was done using EpiInfo v. 3.5.1 for Windows. Nationwide prevalence rates were calculated using weighted analysis to account for the unequal probability of selection between strata. For individuals selected from the household sample, statistical weights were calculated for each regional stratum. For pregnant women, statistical weights were calculated for each ethnic-specific stratum. All measures of statistical precision, including confidence limits, were calcu-lated accounting for the complex sampling, including the cluster and stratified sampling. The statistical significance of apparent differences were judged by comparison of confidence intervals in one subgroup to point estimates in other subgroups. If the confidence intervals in subgroup A did not overlap the point estimate in subgroup B and if the confidence intervals in subgroup B did not overlap the point estimate in subgroup A, the p value for the difference was determined to be less than 0.05, making the difference statistically significant.

Data entry, editing, and management

Computer data entry was done twice into two separate data sets which were then compared to detect errors in data entry. The database variable names were added to a copy of the data col-lection form to create a data key indicating the origin of the data in each field of the database.

Quality control

Extensive training was provided to all survey workers before data collection began. Moreover, most survey workers had prior experience in nutrition and health assessment surveys, specifically the 2005 MICS. During data collection at each selected household, survey team leaders super-vised all steps of data collection, including the interview, physical examination, anthropometric measurement, and biologic specimen collection. Upon completion of data collection at each household, the survey team leader reviewed the entire data collection form to ensure complete-ness and accuracy. As mentioned above, the two datasets resulting from duplicate data entry were exhaustively compared to ensure accurate data entry. Specific data analyses were carried out to assessment data accuracy. For a more complete description of specific measures for qual-ity control, see Annex 3.


ReSuLtS

Households – Description of sample

The household sample includes a total of 4,043 households of which 2,426 (60.0%) are house-holds in which non-pregnant women 15-49 years of age were recruited and bread and salt speci-mens collected. These 2,426 households represent a random sample of households in Georgia. Because the remaining 1,617 households were only included in the survey sample because they had children less than 5 years of age, they do not represent a random sample of Georgian house-holds and are not included in the following analysis of household data. Their household data is included in the analysis of data from children.

The characteristics of these 2,426 households are shown below in Table 15, Table 16, and Table 17 below. Although the actual number of households in each regional stratum does not reflect the distribution of the Georgian population, the weighted distribution does. About one-half of the sample households are rural and one-half are urban. This is similar to the rural/urban distribution of the general population of Georgia. Only a small proportion of households had lived in their present location for less than 10 years, demonstrating that a minority of survey households had been recently displaced. The median number of household members was 4 persons, and few households had more than 6 members. Almost one-third of households had no women 15-49 years of age, and more than two-thirds had no children less than 5 years of age. The major-ity of households were of Georgian ethnicity and spoke Georgian as their home language. Most households had at least one person employed outside the home, and in such households, more than one-third had two or more people employed outside the home.


table 15. Distribution of various demographic variables for sample households, GNNS 2009

Survey sample Georgia population*

CharacteristicActual

number of households

Weighted % of

households% population

TOTAL 2426 100.0 100.0

Region Tbilisi 292 25.1 25.9 Achara and Guria 205 9.4 11.9 Imereti and Racha-Leckhumi 232 17.7 16.9 Kakheti 365 11.6 9.2 Kvemo Kartli 459 10.5 11.2 Samegrelo 240 9.8 10.7 Samtckhe-Javakheti 346 4.5 4.7 Shida Kartli and Mtckheta-Mtianeti 287 11.5 9.5

Rural/Urban Rural 1432 48.9 47.3 Urban 994 51.1 52.7

Years lived in current location 0-9 356 17.4 10-19 363 15.8 20-29 567 23.4 30-39 312 12.8 40-49 288 11.5 50-59 281 9.2 60-69 112 4.6 70-79 65 2.7 80+ 65 2.6

* Population estimates for 2009 from National Statistics Office of Georgia (http://www.geostat.ge/index.php?action=page&p_id=473&lang=eng, accessed 12 March 2010)


table 16. Distribution of household composition and ethnicity variables for sample households, GNNS 2009

Characteristic Actual number of households

Weighted % of households

Number of household members 1 251 10.6 2 367 16.0 3 323 14.6 4 447 19.2 5 436 17.2 6 325 11.8 7 171 6.3 8 62 2.6 9 24 0.8 10+ 20 0.9 Number of women 15-49 usually in household 0 765 32.9 1 1247 50.0 2 314 13.0 3 89 3.5 4 9 0.5 5 2 0.1 Number of children <5 years usually in household 0 1576 67.8 1 599 23.2 2 226 8.1 3 23 0.8 4 2 0.1 Ethnic group of household head Georgian 1891 86.9 Armenian 270 5.8 Azerbaijani 192 4.6 Other 59 2.7

Most common home language Georgian 1921 88.1 Armenian 251 5.0 Azerbaijani 189 4.5 Russian 34 1.8 Other 17 0.6


table 17. Distribution of socio-economic variables for sample households, GNNS 2009

Characteristic Actual number of households

Weighted % of households

Household has employed person Yes 1856 79.3 No 559 20.7

If someone employed, how many 1 1182 64.4 2 529 28.3 3 110 5.9 4 28 1.2 5+ 7 0.2

Households – Salt storage, usage, and iodization

In the representative sample of 2,426 households, the distribution of various variables concerning salt storage and use is shown in Table 18 below. Almost one-third of households stored salt in the original closed container in which it was purchased, while another 23% stored salt in a dif-ferent plastic container. Almost 40% of households stored salt in an open container or a clay, wooden, or cardboard container which presumably left the salt exposed to air. Almost two-thirds kept this container in a closed cabinet, while almost one-third kept it on an open shelf. Very few households stored salt near a heat source, such as near a stove or window. The vast majority of households had salt on the day of data collection and contributed a salt specimen for labora-tory testing. Among those respondents who reported having salt in the household, one-half of respondents said their households salt was iodized, and more than one-third reported that they did not know.

The weighted distribution of iodine concentrations in household salt specimens is shown in Figure 2 below. In virtually all the specimens, the concentration of iodine was greater than 15 ppm, and the highest iodine concentration was 50.3 ppm.

The weighted mean iodine content of salt specimens tested in the laboratory is shown in Table 19 below. There is little differences in the iodine concentration of household salt in different regional strata, between urban and rural households, in different ethnic groups, or by respondents’ report of salt iodization.


Table 20 shows the proportion of household salt specimens which were 15 ppm or below, above 15 ppm but below 40 ppm, and 40 ppm or above. The iodine content of about three-quarters of all specimens fell in the recommended range of 15-40 ppm. About one-quarter were 40 ppm or above.

Table 18. Number (weighted %) and 95% confidence intervals (CI) for variables concerning salt storage and use, sample households, GNNS 2009

Characteristic Number (weighted %) of households 95% CI

How salt is stored in household Original plastic container 326 (16.2) 12.9, 19.5 Original open glass container 232 (11.6) 8.6, 14.5 Original closed glass container 384 (16.5) 14.0, 19.1 Clay or wood container 221 (9.7) 7.9, 11.5 Plastic container 617 (23.3) 20.6, 26.0 Cardboard box 474 (18.2) 15.6, 20.7 Other 112 (4.5) 3.3, 5.7

Where salt is stored in household In a closed cabinet 1495 (64.8) 61.3, 68.3 On an open shelf 751 (30.4) 27.0, 33.9 On a counter near the stove 65 (2.7) 1.6, 3.8 By a window 49 (1.7) 1.1, 2.3 Other 8 (0.4) 0.1, 0.7

Had salt at time of survey visit Yes 2340 (98.4) 97.7, 99.2 No 30 (1.6) 0.8, 2.3

Salt reported by respondent as iodized Yes 1113 (50.9) 45.9, 55.9 No 385 (15.1) 12.4, 17.8 Unknown 842 (34.0) 29.9, 38.1


Figure 2. Weighted distribution of iodine concentrations in household salt specimens, GNNS 2009

0

2

4

6

8

10

12

14

11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

Iodine concentration in salt (ppm)

Wei

ghte

d %

of s

alt s

peci

men

s

Table 19. Weighted mean average and 95% confidence intervals (CI) for iodine content in parts per million in household salt specimens, sample households, GNNS 2009

Characteristic Weighted mean 95% CI

TOTAL 36.8 36.4, 37.2

Region Tbilisi 37.3 36.4, 38.3 Achara and Guria 36.7 35.6, 37.8 Imereti and Racha-Leckhumi 36.8 35.9, 37.8 Kakheti 36.5 35.7, 37.4 Kvemo Kartli 37.1 36.5, 37.6 Samegrelo 36.1 35.2, 37.1 Samtckhe-Javakheti 36.4 35.4, 37.4 Shida Kartli and Mtckheta-Mtianeti 36.5 35.6, 37.4

Rural/Urban Rural 36.7 36.2, 37.2 Urban 36.9 36.3, 37.5

Ethnic group of household head Georgian 36.8 36.4, 37.2 Armenian 37.0 35.6, 38.3 Azerbaijani 36.9 36.0, 37.8 Other 36.2 34.7, 37.7

Reported salt iodized Yes 37.1 36.5, 37.6 No 36.1 35.5, 36.8 Unknown 36.7 36.2, 37.2


table 20. Number (weighted %) with salt iodine of various concentrations (in parts per million), sample households, GNNS 2009

Characteristic < 15 >15 - <40 40+

TOTAL 1 (<0.1) 1400 (73.4) 490 (26.5)

Region Tbilisi 0 146 (68.2) 68 (31.8) Achara and Guria 0 139 (76.0) 44 (24.0) Imereti and Racha-Leckhumi 1 (0.5) 149 (73.0) 54 (26.5) Kakheti 0 169 (73.8) 60 (26.2) Kvemo Kartli 0 275 (72.9) 102 (27.1) Samegrelo 0 168 (78.9) 45 (21.1) Samtckhe-Javakheti 0 187 (73.9) 66 (26.1) Shida Kartli and Mtckheta-Mtianeti 0 167 (76.6) 51 (23.4)

Rural/Urban Rural 1 (0.2) 829 (74.3) 278 (25.5) Urban 0 571 (72.4) 212 (27.6)

Ethnic group Georgian 1 (0.1) 1105 (73.4) 380 (26.4) Armenian 0 132 (72.2) 49 (27.8) Azerbaijani 0 123 (74.9) 43 (25.1) Other 0 32 (77.2) 14 (22.8)

Households – Bread consumption and iron content

The average per capita daily bread consumption was, when averaged among the members of each household, 414 grams per day. As shown below in Figure 3, most households had a per capita daily bread consumption above 200-300 grams. As shown in Table 21 below, average daily per capita bread consumption was statistically significantly lower in households in Tbilisi than in households in other regional strata. It was also higher in rural households than in urban households. Consumption was also higher in Azerbaijani households; however, only the differ-ence between Azerbaijani and Armenian households was statistically significant.

As shown in Table 22 below, the type of bread most commonly eaten in the household varied by regional stratum and by urban vs. rural location, but not by ethnicity. Factory-produced bread was the most commonly eaten bread in 85% of Tbilisi households. In contrast, it was the most commonly eaten bread in only one-half or less of households in the other regional strata. Home-made bread was the most commonly eaten bread in more households outside of Tbilisi, and was much more often reported as the most commonly eaten bread in rural households than in urban households. The distribution of bread types was similar in different ethnicities with the exception of lavash which was more often reported in Georgian households than in Azerbaijani or Armenian households.

The source of the most commonly eaten household bread is shown in Table 23 below. Baker-ies are a source of the most commonly eaten bread for only a small proportion of households in all regional strata, in both urban and rural households, and in households of all ethnicities. As shown in Table 24, of bread purchased in supermarkets for which the brand was known, Ipkli


brand is the most common; however, it was commonly reported only in Tbilisi, Imeretic and Racha-Leckhumi, and Kvemo Kartli. The brand could not be identified for many bread specimens.

In those households in which bread is baked at home, the most common flour used, as shown in Table 25 below, is first quality white flour. Although the type of flour does not differ substantially between urban and rural households or by ethnicity, there are some differences among regional strata. Respondents in many households did not know what type of flour was used to bake bread in their household.

For bread purchased from outside the home, Table 26 show the proportion for which the pack-age or label indicated fortification with iron or no fortification. Overall, a small minority of bread packaging indicated fortification; however, for a relatively large proportion of bread specimens, the original packaging was unavailable or the survey teams could not inspect the labeling for some other reason. Packaging indicating fortification was somewhat more common in Tbilisi and Kvemo Kartli. It was also more common among Azerbaijani households, probably because they predominantly live in Kvemo Kartli.

Figure 4 below shows the distribution of values for iron content in bread specimens collected from households. Table 27 below shows the weighted mean iron content for bread specimens. Lavash had statisti-cally significantly more iron than other types of bread. In addition, the iron content of bread was higher in some regional strata than in others and higher in specimens from rural households than specimens from urban households. Iron content did not substantially differ by ethnicity of the members of the household.

Table 28 below shows the weighted proportion of bread specimens above the minimum iron con-tent for flour (30 mg/kg or 30 ppm) as set by the Ministry of Labor, Health, and Social Affairs27 and international recommendations14. Overall, less than one-quarter of bread specimens met this criterion. A larger proportion of specimens of lavash contained the minimum 30 ppm of iron. As expected, bread specimens from the same regional strata which had a higher average iron content also had a higher proportion of specimens with 30 ppm or greater. The proportion of bread from Samtckhe-Javakheti with more than 30 ppm iron was statistically significantly higher than in any other regional stratum. A larger proportion of bread specimens from rural households than urban households had 30 ppm or greater of iron. A larger proportion of specimens from Armenian households than households of other ethnicities had 30 ppm or greater of iron, but this difference may be statistically significant only for the difference between Georgian and Armenian households.


Figure 3. Weighted distribution of households with various per capita daily bread consumption, GNNS 2009

0

5

10

15

20

25

0-99 100-199

200-299

300-399

400-499

500-599

600-699

700-799

800-899

999-1000

1000-1099

1100+

Daily per capita bread consumption (grams)

Wei

ghte

d %

of h

ouse

hold

s

table 21. Weighted mean average of bread eaten per person per day (in grams) and 95% con-fidence intervals (CI), sample households, GNNS 2009

Characteristic Weighted mean 95% CI

TOTAL 414 393, 435

Region Tbilisi 323 289, 356 Achara and Guria 481 446, 517 Imereti and Racha-Leckhumi 436 377, 495 Kakheti 492 456, 527 Kvemo Kartli 428 393, 462 Samegrelo 385 347, 423 Samtckhe-Javakheti 401 377, 425 Shida Kartli and Mtckheta-Mtianeti 465 392, 537

Rural/Urban Rural 467 439, 495 Urban 363 341, 386

Ethnic group of household head Georgian 416 396, 436 Armenian 380 338, 422 Azerbaijani 457 397, 517 Other 365 285, 445


table 22. Number (weighted %) most often consuming various types of bread, sample house-holds, GNNS 2009

Characteristic Lavash Factory white bread

other factory bread Homemade other

TOTAL 217 (9.2) 972 (46.8) 94 (4.8) 1073 (38.7) 9 (0.5)

Region

Tbilisi 40 (14.0) 223 (78.2) 19 (6.7) 1 (0.4) 2 (0.7)

Achara and Guria 6 (3.0) 86 (42.8) 7 (3.5) 102 (50.7) 0 Imereti and Racha- Leckhumi 2 (0.9) 97 (42.4) 15 (6.6) 113 (49.3) 2 (0.9)

Kakheti 70 (19.5) 53 (14.8) 13 (3.6) 223 (62.1) 0

Kvemo Kartli 50 (11.6) 213 (49.4) 14 (3.2) 154 (35.7) 0

Samegrelo 16 (6.7) 74 (31.1) 14 (5.9) 134 (56.3) 0 Samtckhe-Javakheti 7 (2.1) 123 (36.1) 8 (2.3) 202 (59.2) 1 (0.3)

Shida Kartli and Mtckheta-Mtianeti 26 (9.3) 103 (36.7) 4 (1.4) 144 (51.2) 4 (1.4)

Rural/Urban Rural 93 (6.2) 320 (21.4) 46 (4.2) 935 (67.7) 4 (0.5)

Urban 124 (12.1) 652 (71.1) 48 (5.3) 138 (10.9) 5 (0.5)

Ethnic group

Georgian 198 (10.0) 746 (45.5) 81 (4.9) 823 (38.9) 9 (0.6)

Armenian 6 (2.7) 90 (48.6) 9 (5.1) 151 (43.7) 0 Azerbaijani 8 (4.2) 93 (50.5) 1 (2.0) 81 (43.3) 0 Other 4 (6.2) 37 (73.8) 2 (2.8) 14 (17.2) 0


table 23. Number (weighted %) purchasing most commonly eaten type of bread from various sources, sample households, GNNS 2009

Characteristic Supermarket or shop Bakery Bake at home other

TOTAL 1041 (51.1) 205 (8.8) 1090 (39.3) 26 (0.8)

Region Tbilisi 243 (85.0) 41 (14.3) 2 (0.7) 0 Achara and Guria 92 (45.8) 6 (3.0) 101 (50.2) 2 (1.0) Imereti and Racha-Leckhumi 106 (46.3) 8 (3.5) 114 (49.8) 1 (0.4) Kakheti 92 (25.7) 32 (8.9) 233 (65.1) 1 (0.3) Kvemo Kartli 209 (48.5) 51 (11.8) 157 (36.4) 14 (3.2) Samegrelo 83 (34.9) 18 (7.6) 133 (55.9) 4 (1.7) Samtckhe-Javakheti 109 (32.1) 25 (7.4) 203 (59.7) 3 (0.9) Shida Kartli and Mtckheta-Mtianeti 107 (38.4) 24 (8.6) 147 (52.7) 1 (0.4)

Rural/Urban Rural 355 (25.4) 67 (4.3) 950 (69.0) 22 (1.3) Urban 686 (75.6) 138 (13.1) 140 (11.0) 4 (0.3)

Ethnic group Georgian 828 (50.5) 176 (9.3) 835 (39.6) 14 (0.6) Armenian 89 (50.8) 14 (5.5) 153 (43.5) 1 (0.2) Azerbaijani 79 (44.6) 9 (4.7) 84 (44.9) 11 (5.8) Other 38 (78.2) 5 (4.6) 14 (17.2) 0


tab

le 2

4.

For m

ost co

mm

only

use

d br

ead

whi

ch is

pur

chas

ed in

sup

erm

arke

ts, nu

mbe

r (w

eigh

t-ed

%) w

ith v

ario

us b

rand

nam

es, sa

mpl

e ho

useh

olds

, G

NN

S 2

009.

Bra

nd o

f br

ead

Cha

ract

eris

ticIp

kli

Dik

am

argi

mkh

neob

aN

one

oth

eru

nkno

wn

TO

TA

L

114

(16.3

)

1

(0.2

)

3

(0.5

)

3

(0.4

)

687

(59.5

)

111

(12.8

) 1

20 (

10.2

)

Reg

ion

Tbi

lisi

67

(27.6

)

1

(0.4

)

3

(1.2

)

2

(0.8

)

118

(48.6

)

30

(12.3

)

22

(9.1

)

Ach

ara

and

Gur

ia

0

0

0

1

(1.1

)

79

(85.9

)

6

(6.5

)

6

(6.5

)

Im

eret

i and

Rac

ha-L

eckh

umi

24

(22.6

)

0

0

0

41

(38.7

)

28

(26.4

)

13 (

12.3

)

Kak

heti

1

(1.1

)

0

0

0

87

(94.6

)

1

(1.1

)

3

(3.3

)

Kve

mo

Kar

tli

22

(10.6

)

0

0

0

107

(51.4

)

24

(11.5

)

55 (

26.4

)

Sam

egre

lo

0

0

0

0

53

(63.9

)

18

(21.7

)

12 (

14.5

)

Sam

tckh

e-Ja

vakh

eti

0

0

0

0

97

(89.8

)

2

(1.9

)

9

(8.3

)

Shi

da K

artli

and

Mtc

khet

a-

M

tiane

ti

0

0

0

0

105

(98.1

)

2

(1.9

)

0

Rur

al/U

rban

Rur

al

21

(7.1

)

0

0

0

266

(76.0

)

27

(7.8

)

41

(9.1

)

Urb

an

93

(19.2

)

1

(0.2

)

3

(0.7

)

3

(0.6

)

421

(54.3

)

84

(14.4

)

79 (

10.6

)

Ethn

ic g

roup

Geo

rgia

n

93

(16.9

)

1

(0.2

)

2

(0.4

)

1

(0.2

)

554

(59.3

)

92

(13.2

)

84

(9.7

)

Arm

enia

n

7

(10.4

)

0

1

(3.1

)

1

(3.1

)

68

(70.5

)

4

(6.8

)

7

(6.0

)

Aze

rbai

jani

9

(10.7

)

0

0

0

35

(47.9

)

10

(11.8

)

25 (

29.6

)

Oth

er

5

(17.8

)

0

0

1

(2.2

)

25

(60.0

)

3

(9.4

)

4 (

10.6

)


Table 25. Number (weighted %) using various types of flour when baking bread at home, sam-ple households in which bread is baked at home, GNNS 2009

Characteristic First quality white flour

Whole wheat flour

Both white and whole

wheatother unknown

TOTAL 971 (75.1) 113 (6.2) 38 (2.9) 113 (7.4) 136 (8.4)

Region Tbilisi 50 (72.5) 3 (4.3) 1 (1.4) 1 (1.4) 14 (20.3) Achara and Guria 75 (57.7) 5 (3.8) 4 (3.1) 40 (30.8) 6 (4.6) Imereti and Racha- Leckhumi 133 (93.0) 2 (1.4) 4 (2.8) 3 (2.1) 1 (0.7)

Kakheti 223 (80.2) 11 (4.0) 17 (6.1) 2 (0.7) 25 (9.0) Kvemo Kartli 152 (77.3) 18 (9.1) 3 (1.5) 7 (3.6) 17 (8.6) Samegrelo 140 (94.6) 0 0 0 8 (5.4) Samtckhe-Javakheti 106 (46.1) 41 (17.8) 2 (0.9) 34 (14.8) 47 (20.4)

Shida Kartli and Mtckheta-Mtianeti

92 (52.3) 33 (18.8) 7 (4.0) 26 (14.8) 18 (10.2)

Rural/Urban Rural 757 (74.0) 101 (6.9) 29 (3.1) 102 (9.3) 97 (6.8) Urban 214 (78.0) 12 (4.5) 9 (2.3) 11 (2.5) 39 (12.7)

Ethnic group Georgian 768 (75.8) 66 (5.3) 35 (3.2) 108 (8.2) 81 (7.5) Armenian 103 (70.1) 26 (11.5) 1 (0.4) 2 (2.0) 36 (15.9) Azerbaijani 78 (68.1) 18 (15.6) 2 (1.7) 1 (0.9) 15 (13.7) Other 17 (75.4) 2 (7.6) 0 1 (2.3) 3 (14.7)


table 26. Number (weighted %) of bread specimens for which packaging was marked as forti-fied with iron or not (does not include homemade bread), sample households, GNNS 2009

Characteristic marked as fortified

Not marked as fortified

unknown or original package

unavailable

TOTAL 64 (6.5) 890 (77.5) 146 (16.0)

Type of bread Lavash 4 (3.0) 172 (87.3) 16 (9.8) Factory white bread 55 (7.1) 649 (75.4) 117 (17.4) Other factory bread 5 (7.2) 61 (78.3) 12 (14.4) Other 0 2 (100.0) 0 Unknown 0 6 (90.8) 1 (9.2)

Region Tbilisi 25 (11.1) 166 (73.5) 35 (15.5) Achara and Guria 2 (2.0) 87 (88.8) 9 (9.2) Imereti and Racha-Leckhumi 3 (2.9) 64 (61.0) 38 (36.2) Kakheti 1 (1.0) 91 (90.1) 9 (8.9) Kvemo Kartli 25 (10.1) 209 (84.6) 13 (5.3) Samegrelo 0 90 (95.7) 4 (4.3) Samtckhe-Javakheti 5 (4.1) 99 (80.5) 19 (15.4) Shida Kartli and Mtckheta-Mtianeti 3 (2.8) 84 (79.2) 19 (17.9)

Rural/Urban Rural 23 (4.1) 339 (87.0) 38 (8.9) Urban 41 (7.3) 551 (74.3) 108 (18.5)

Ethnic group Georgian 46 (6.5) 698 (77.0) 119 (16.5) Armenian 3 (1.9) 77 (83.9) 13 (14.1) Azerbaijani 13 (12.4) 81 (82.8) 5 (4.8) Other 2 (5.7) 27 (72.2) 8 (22.1)


Figure 4. Weighted distribution of iron concentrations in household bread specimens, GNNS 2009

0

1

2

3

4

5

6

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90+

Iron concentration in bread (ppm)

Wei

ghte

d %

of b

read

spe

cim

ens

Table 27. Weighted mean average and 95% confidence intervals for iron content in parts per million, household bread specimens, GNNS 2009

Characteristic Weighted mean iron content

95% confidence interval

TOTAL 23.8 22.9, 24.7

Type of bread Lavash 28.9 25.7, 32.2 Factory white bread 22.2 21.0, 23.4 Other factory bread 24.0 20.0, 28.1 Homemade 24.7 23.3, 26.1 Other 25.2 15.7, 34.6

Region Tbilisi 21.1 19.4, 22.8 Achara and Guria 22.2 19.7, 24.7 Imereti and Racha-Leckhumi 24.2 22.1, 26.3 Kakheti 27.1 24.0, 30.2 Kvemo Kartli 23.1 21.1, 25.2 Samegrelo 26.7 24.2, 29.3 Samtckhe-Javakheti 31.6 28.5, 34.7 Shida Kartli and Mtckheta-Mtianeti 22.0 19.8, 24.2

Rural/Urban Rural 24.8 23.6, 26.1 Urban 22.8 21.6, 24.0


Characteristic Weighted mean iron content

95% confidence interval

Ethnic group of household head Georgian 23.7 22.8, 24.6 Armenian 25.9 22.3, 29.5 Azerbaijani 24.4 20.7, 28.0 Other 23.2 18.5, 27.8

Table 28. Number (weighted %) and 95% confidence intervals (CI) of household bread speci-mens containing >30 parts per million iron, GNNS 2009

CharacteristicNumber

(weighted %) of households

95% CI

TOTAL 543 (24.9) 22.5, 27.4

Type of bread Lavash 77 (36.4) 28.9, 43.9 Factory white bread 202 (21.1) 17.4, 24.7 Other factory bread 18 (21.8) 8.2, 35.5 Homemade 233 (27.5) 23.5, 31.4

Region Tbilisi 38 (16.7) 11.8, 21.5 Achara and Guria 37 (20.0) 12.9, 27.1 Imereti and Racha-Leckhumi 57 (28.1) 21.9, 34.3 Kakheti 76 (32.2) 23.8, 40.6 Kvemo Kartli 93 (24.6) 19.0, 30.2 Samegrelo 71 (33.0) 25.4, 40.7 Samtckhe-Javakheti 126 (45.5) 36.4, 54.5 Shida Kartli and Mtckheta-Mtianeti 45 (20.3) 14.6, 25.9

Rural/Urban Rural 333 (27.8) 24.3, 31.3 Urban 210 (22.4) 19.0, 25.9

Ethnic group of household head Georgian 418 (24.9) 22.3, 27.5 Armenian 69 (28.8) 19.7, 37.9 Azerbaijani 44 (26.7) 16.4, 37.0 Other 11 (20.5) 8.4, 32.6


Children – Description of sample

Table 29 shows the characteristics of the 3,069 children included in the survey sample. The sample contained more boys than girls and more children 48-59 months of age than other ages. The weighted distribution of children by regional strata is similar to distribution of the Georgian population. Approximately equal numbers of children lived in rural and urban households, similar to the distribution of the general population of Georgia.

As shown in Table 30 below, only a small proportion of respondents, usually mothers, reported that their children had a chronic disease; however, in almost two-thirds of such children, medica-tion was required for management of their chronic illness. A much larger proportion of children had fever, cough, or diarrhea in the 2 weeks prior to the survey interview.

table 29. Description of sample children less than 5 years of age, GNNS 2009

Survey sample Georgia census*

Characteristic Actual number of children

Weighted % of children % population

TOTAL 3069 100.0 100.0

Sex Male 1658 54.2 Female 1411 45.8

Age <12 months 580 19.4 12-23 months 643 21.0 24-35 months 586 19.2 36-47 months 538 17.2 48-59 months 722 23.3


Rural/Urban Rural 1831 49.2 47.3 Urban 1238 50.8 52.7

Ethnic group Georgian 2253 84.5 Armenian 403 7.9 Azerbaijani 365 5.9 Other 44 1.7

* Population estimates for 2009 from National Statistics Office of Georgia (http://www.geostat.ge/index.php?action=page&p_id=473&lang=eng, accessed 12 March 2010)


table 30. point or period prevalence of various forms of morbidity, children less than 5 years of age, GNNS 2009

morbidityActual

number of children

Weighted % of children 95% CI

Chronic disease 93 3.3 2.5, 3.9 Takes medication 54 61.4 49.2, 73.5

Fever in past 2 weeks 442 15.6 13.7, 17.5

Cough in past 2 weeks 669 23.1 20.5, 25.7

Diarrhea in past 2 weeks 253 8.1 6.7, 9.6

Children – Birthweight

Figure 5 and Figure 6 below shows the weighted distribution of the reported birthweights of chil-dren less than 5 years of age. Overall, less than 5% of children had low birthweight (<2500 g), and another 1.2% of children had high birthweight (>4500 g). As seen in Table 31 below, the weighted prevalence of low birthweight did not differ substantially by sex, age, regional stratum, rural vs. urban households, or ethnic group.

Figure 5. Weighted distribution of birthweights of children less than 5 years of age, GNNS 2009

0

1

2

3

4

5

6

7

8

9

10

900-9

99

1100

-1199

1300

-1399

1500

-1599

1700

-1799

1900

-1999

2100

-2199

2300

-2399

2500

-2599

2700

-2799

2900

-2999

3100

-3199

3300

-3399

3500

-3599

3700

-3799

3900

-3999

4100

-4199

4300

-4399

4500

-4599

4700

-4799

4900

-4999

5100

-5199

5300

-5399

5500

-5599

Birthweight (grams)

Wei

ghte

d %

of c

hild

ren


Figure 6. Weighted distribution of birthweights of children less than 5 years of age, GNNS 2009

Normal birthweight (2500-

4500 g)93.9%

Low birthweight (1500-2499 g)

4.6%

High birthweight (>4500 g)

1.2%

Very low birth-weight (<1500 g)

0.3%

table 31. Number (weighted %) with various birth weights, children less than 5 years of age, GNNS 2009

Birthweight

Characteristic Very low(<1500 g)

Low(1500-2499 g)

Normal(2500-4500 g)

High(>4500 g)

TOTAL 8 (0.3) 132 (4.6) 2886 (93.9) 34 (1.2)

Sex

Male 2 (0.2) 66 (4.0) 1557 (93.8) 29 (2.0) Female 6 (0.4) 66 (5.3) 1329 (94.1) 5 (0.3)

Age

<12 months 0 24 (4.9) 551 (94.6) 4 (0.5) 12-23 months 4 (0.5) 27 (3.5) 597 (94.0) 13 (2.0) 24-35 months 1 (0.2) 31 (6.2) 547 (92.9) 4 (0.7) 36-47 months 0 20 (3.1) 513 (95.5) 5 (0.9) 48-59 months 3 (0.5) 30 (5.3) 678 (92.6) 8 (1.6)

Region

Tbilisi 1 (0.3) 25 (6.8) 339 (91.9) 4 (1.1) Achara and Guria 1 (0.3) 14 (4.0) 327 (94.2) 5 (1.4)

Imereti and Racha-Leckhumi 0 5 (2.3) 206 (95.8) 4 (1.9)

Kakheti 0 12 (3.9) 292 (95.1) 3 (1.0) Kvemo Kartli 3 (0.4) 24 (3.1) 737 (95.8) 5 (0.7) Samegrelo 2 (0.7) 10 (3.6) 266 (95.0) 2 (0.7) Samtckhe-Javakheti 0 24 (4.7) 477 (94.1) 6 (1.2)

Shida Kartli and Mtckheta-Mtianeti 1 (0.4) 18 (6.8) 242 (91.0) 5 (1.9)


Birthweight

Characteristic Very low(<1500 g)

Low(1500-2499 g)

Normal(2500-4500 g)

High(>4500 g)

Rural/Urban

Rural 4 (0.3) 70 (3.7) 1731 (94.9) 21 (1.2) Urban 4 (0.3) 62 (5.5) 1155 (93.0) 13 (1.2)

Ethnic group

Georgian 6 (0.3) 109 (4.8) 2103 (93.6) 29 (1.3) Armenian 0 9 (2.8) 351 (95.8) 5 (1.3) Azerbaijani 2 (0.7) 10 (3.1) 388 (96.3) 0 Other 0 4 (9.1) 40 (90.9) 0

Children – Breastfeeding

Overall, about two-thirds of children less than 24 months of age were breastfed within 1 hour of birth, as shown in Table 32. This proportion does not differ substantially by sex or by age. How-ever, some differences exist among regional strata; a smaller proportion of children in Achara and Guria and Samegrelo were breastfed within 1 hour of birth than children in other regional strata. Moreover, a small proportion of children living in rural areas were breastfed within 1 hour than children living in urban areas. A higher proportion of Armenian children were breastfed within 1 hour that than either Georgian or Azerbaijani children.

As shown in Table 33, a little more than one-half of children less than 6 months of age were exclusively breastfed the day before data collection. The apparent difference between boys and girls was not statistically significant. On the other hand, some regional strata, such as Shida Kar-tli and Meckheta-Mtianeti, had substantially higher prevalence rates of exclusive breastfeeding. The prevalence in Samegrelo was statistally significantly lower than the prevalence in any other regional stratum. Although the difference was not statistically significant, a somewhat greater proportion of rural children were exclusively breastfed than urban children. A statistically signifi-cantly higher proportion of Azerbaijani children were exclusively breastfed than either Georgian or Armenian children.

Slightly more than one-third of children 12-15 months of age were still breastfeeding, as shown in Table 34. Apparent differences between sexes, urban/rural residence, and ethnic group were not statistically significant. This lack of statistical significance is largely due to the narrow age range for this indicator and the subsequent small number of children in each subgroup. However, in spite of this limitation, there were statistically significant differences in this indicator between regional strata, with Achara and Guria having a particularly low prevalence of continued breast-feeding after 1 year of age.

A large majority of children 6-8 months of age had eaten solid, semi-solid, or soft food the day before the interview, as shown in Table 35. Because of the small numbers of children in each subgroup, none of the apparent differences among subgroups (sex, age, urban/rural residence, regional stratum, or ethnicity) are statistically significant.

As shown in Table 36, less than one-half of children 6-23 months of age achieved minimum dietary diversity. A larger proportion of girls than boys had minimum dietary diversity, and the proportion increased with age. As with other breastfeeding indicators, the regional strata showed some differences, with Achara and Guria and Kakheti showing a smaller proportion of children


with minimum dietary diversity. Urban children had a higher prevalence of minimum dietary diversity than rural children, and a larger proportion of Armenian children had minimum dietary diversity than Georgian or Azerbaijani children; however, only the difference between Armenian and Georgian children was statistically significant.

Minimum meal frequency was achieved in a large majority of children 6-23 months of age, as shown in Table 37. The proportion of children meeting this criterion did not differ between sexes, but it declined with age. Although there were differences between regional stata, the range was only from 74.3% in Samtckhe-Javakheti to 89.9% in Shida Kartli and Mtckheta-Mtianeti. In addition, a larger proportion of children in urban areas met the minimum meal frequency than children in rural areas. Armenian children had the lowest proportion of children with minumum meal frequency, and the differences between Armenian children and the children of the other two ethnicities were statistically significant.

As shown in Table 38, fewer than one-half of children 6-23 months had a minimum acceptable diet (an indicator combining dietary diversity and meal frequency). This proportion was higher in girls than in boys and higher in children 18-23 months of age than younger children, albeit without statistical significance in either case. A smaller proportion of children in Achara and Guria and Kakheti had a minimum acceptable diet than children in other regional strata; however, only some of the differences were statistically significant. A substantially greater proportion of children in urban areas had a minimum acceptable diet than children in rural areas, but there was little dif-ference among ethnicities.

The proportion of children < 24 months who had ever been breastfed was very high overall and in all subgroups, as shown in Table 39. Differences between age groups, regional strata, rural/ur-ban residence, and ethnicities, although occasionally statistically significant, are relatively small.

The proportion of children 20-23 months of age with continued breastfeeding is quite small, as seen in Table 40. Boys are more commonly still breastfeeding at this age than girls, and a sta-tistically significantly greater proportion of children in Samegrelo are still breastfeeding than in any other regional stratum. However, this is little difference between children in rural and urban locations or among children of different ethnicities.

As seen in Table 41, age-appropriate breastfeeding occurred in slightly more than one-third of children less than 24 months of age. There was little difference between the sexes, between children with rural or urban residence, or among ethnicities. The proportion of children with age-appropriate breastfeeding declines substantially with age and is somewhat lower in Kakheti than in other regional strata.

Among children less than 36 months of age, the median duration of breastfeeding is between 9 and 10 months, as shown in Figure 7. By the age of 24 months, very few children are still be breastfed.


table 32. Number (weighted %) with various times of breastfeeding initiation after birth, children < 24 months of age, GNNS 2009 (WHO/UNICEF recommendations22- Indicator #1 Early initiation of breastfeeding)

CharacteristicInitiated

breastfeeding in first hour

Initiated breastfeeding 1-12 hours

Initiated breastfeeding > 12 hours

TOTAL 678 (66.3) 283 (25.3) 101 (8.4)

Sex Male 362 (64.2) 161 (26.2) 57 (9.6) Female 316 (68.8) 122 (24.1) 44 (7.1)

Age <12 months 323 (65.9) 140 (26.2) 47 (7.9) 12-23 months 355 (66.6) 143 (24.4) 54 (9.0)

Region Tbilisi 114 (82.6) 20 (14.5) 4 (2.9) Achara and Guria 51 (37.2) 69 (50.4) 17 (12.4) Imereti and Racha-Leckhumi 47 (78.3) 9 (15.0) 4 (6.7) Kakheti 66 (62.3) 32 (30.2) 8 (7.5) Kvemo Kartli 193 (65.2) 68 (23.0) 35 (11.8) Samegrelo 33 (41.8) 28 (35.4) 18 (22.8) Samtckhe-Javakheti 99 (68.8) 35 (24.3) 10 (6.9) Shida Kartli and Mtckheta-Mtianeti 75 (73.5) 22 (21.6) 5 (4.9)


Ethnic group Georgian 488 (65.8) 211 (25.6) 82 (8.7) Armenian 86 (81.1) 25 (16.7) 3 (2.2) Azerbaijani 99 (65.1) 42 (26.7) 13 (8.2)


Table 33. Number (weighted %) and 95% CI of children exclusively breastfed* the day before the interview, children < 6 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #2 Exclusive breastfeeding under 6 months)

CharacteristicNo. (weighted %) of children exclusively

breastfed 95% CI

TOTAL 161 (54.8) 48.5, 61.2

Sex Male 87 (57.5) 48.8, 66.0 Female 74 (52.2) 42.7, 61.7



Ethnic group Georgian 114 (53.4) 46.2, 60.6 Armenian 17 (53.7) 28.5, 78.9 Azerbaijani 28 (69.7) 55.4, 83.9

* See text for definition of exclusively breastfed


table 34. Number (weighted %) and 95% CI of children breastfed the day before the interview, children 12-15 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #3 Continued breastfeeding at 1 year)

Characteristic No. (weighted %) of children breastfed 95% CI

TOTAL 96 (36.5) 29.3, 43.8

Sex Male 56 (38.5) 28.0, 48.9 Female 40 (34.3) 24.9, 43.8

Region Tbilisi 14 (35.9) 20.6, 51.2 Achara and Guria 4 (15.4) 0, 32.6 Imereti and Racha-Leckhumi 7 (35.0) 14.9, 55.1 Kakheti 7 (29.2) 10.0, 48.4 Kvemo Kartli 27 (41.5) 29.3, 53.8 Samegrelo 15 (55.6) 32.7, 78.4 Samtckhe-Javakheti 11 (35.5) 20.7, 50.3 Shida Kartli and Mtckheta-Mtianeti 11 (44.0) 22.6, 65.4




table 35. Number (weighted %) and 95% CI of children eating complementary food the day before the interview, children 6-8 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #4 Introduction of solid, semi-solid or soft foods)

CharacteristicNo. (weighted %) of children eating solid,

semi-solid, or soft food 95% CI

TOTAL 124 (84.5) 77.1, 91.8

Sex Male 67 (82.6) 73.3, 91.9 Female 57 (86.7) 77.7, 95.7

Region Tbilisi 18 (94.7) 84.3, 100 Achara and Guria 15 (75.0) 48.4, 100 Imereti and Racha-Leckhumi 3 (75.0) 44.5, 100 Kakheti 15 (68.2) 45.9, 90.5 Kvemo Kartli 32 (82.1) 68.1, 96.0 Samegrelo 9 (90.0) 70.9, 100 Samtckhe-Javakheti 14 (93.3) 80.3, 100 Shida Kartli and Mtckheta-Mtianeti 18 (90.0) 76.2, 100

Rural/Urban Rural 61 (74.6) 62.0, 87.1 Urban 63 (92.6) 85.0, 100

Ethnic group Georgian 106 (85.3) 77.4, 93.1 Armenian 8 (76.1) 45.1, 100 Azerbaijani 8 (68.6) 37.0, 100


table 36. Number (weighted %) with minimum dietary diversity* the day before the interview, children 6-23 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #5 Minimum dietary diversity)

Characteristic

No. (weighted %) of children with minimum dietary

diversity

95% CI

TOTAL 426 (47.7) 42.2, 53.2

Sex Male 218 (43.6) 37.2, 50.1 Female 208 (52.6) 45.4, 59.8

Age 6-11 months 109 (41.5) 33.2, 49.9 12-17 months 152 (45.1) 37.6, 52.7 18-23 months 165 (57.6) 49.9, 65.3




* See text for definition of minimum dietary diversity


table 37. Number (weighted %) with minimum meal frequency* the day before the interview, children 6-23 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #6 Minimum meal frequency)

Characteristic

No. (weighted %) of children with minimum meal

frequency

95% CI

TOTAL 772 (85.3) 82.2, 88.4

Sex Male 413 (85.5) 81.7, 89.3 Female 359 (85.1) 81.0, 89.2





* See text for definition of minimum meal frequency


table 38. Number (weighted %) with minimum acceptable diet* the day before the interview, children 6-23 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #7 Minimum acceptable diet)

CharacteristicNo. (weighted %) of

children with minimum acceptable diet

95% CI

TOTAL 367 (42.3) 37.0, 47.9

Sex Male 188 (39.4) 33.1, 45.7 Female 179 (46.2) 39.1, 53.3





* See text for definition of minimum acceptable diet


table 39. Number (weighted %) and 95% CI of children ever breastfed, children < 24 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #9 Children ever breastfed)

CharacteristicNo. (weighted %) of children ever

breastfed95% CI

TOTAL 1068 (87.2) 84.6, 89.7

Sex Male 583 (88.4) 85.2, 91.7 Female 485 (85.7) 81.7, 89.7

Age

< 6 months 263 (92.1) 87.7, 96.4 6-11 months 250 (83.8) 78.6, 89.0 12-17 months 294 (85.8) 81.7, 89.9 18-23 months 261 (87.6) 83.1, 92.0



Ethnic group Georgian 785 (86.6) 83.8 89.4 Armenian 114 (85.1) 75.4, 94.8 Azerbaijani 155 (92.5) 88.3, 96.7


table 40. Number (weighted %) and 95% CI of children breastfed the day before the interview, children 20-23 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #10 Continued breastfeeding at 2 years)

Characteristic No. (weighted %) of children breastfed 95% CI

TOTAL 38 (16.6) 11.3, 21.9

Sex Male 24 (22.7) 14.4, 31.1 Female 14 (10.2) 4.5, 15.9

Region Tbilisi 2 (10.0) 0, 23.1 Achara and Guria 3 (16.7) 0, 35.4 Imereti and Racha-Leckhumi 0 Kakheti 1 (4.3) 0, 13.0 Kvemo Kartli 13 (22.4) 11.9, 32.9 Samegrelo 6 (54.5) 27.0, 82.1 Samtckhe-Javakheti 7 (17.5) 4.8, 30.2 Shida Kartli and Mtckheta-Mtianeti 6 (24.0) 9.0, 39.0




table 41. Number (weighted %) and 95% CI of children with age-appropriate breastfeeding* the day before the interview, children < 24 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #11 Age-appropriate breastfeeding)

Characteristic

No. (weighted %) of children with age-appropriate breast-

feeding

95% CI

TOTAL 463 (37.7) 34.6, 40.9

Sex Male 260 (39.1) 35.0, 43.1 Female 203 (36.2) 31.7, 40.7

Age < 6 months 161 (54.8) 48.5, 61.2 6-11 months 122 (42.5) 36.5, 48.4 12-17 months 113 (32.7) 26.7, 38.7 18-23 months 67 (21.7) 16.5, 27.0




* See text for definition of age-appropriate breastfeeding


Figure 7. Weighted 3-month moving average percent of children breastfed the day before the interview, by age, children < 36 months of age, GNNS 2009 (WHO/UNICEF recommendations22 - Indicator #13 Duration of breastfeeding)

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36

Age (in months)

Wei

ghte

d %

of c

hild

ren

brea

stfe

d ye

ster

day

Children – other dietary intake

Table 42 below shows the proportion of children less than 5 years of age who ate various foods the day before the survey interview. Almost one-third of children less than 24 months of age consumed breast milk substitute. More than two-thirds ate bread or other grain products and fruits and vegetables. However, relatively few ate protein-rich foods, such as beans or nuts, meat, fish, chicken, or eggs. Dairy products were consumed by more than one-half; however, vitamin A rich fruits and vegetables were consumed by fewer than one-quarter. Sweet tea was commonly drunk in this age group.

As might be expected, children 24-59 months of age consumed breast milk substitute much less frequently. Although eaten by a larger proportion of older children, the protein sources of beans or nuts, meat, fish, chicken, and eggs were still eaten by only one-half or fewer of children, al-though dairy products were consumed by about three-quarters of children. Although most chil-dren in this age group at some fruits or vegetables, vitamin A rich fruits and vegetables were only eaten by slightly more than one-third of children. Fatty foods and sweet tea were consumed by a large majority of children.

Table 43 and Table 44 show the number of times in the week prior to the survey interview vari-ous foods in these categories were eaten. Among children less than 24 months of age, more than one-third never consumed breast milk substitute. On the other hand, more than one-half ate bread or grain products at least five times per week. Most young children ate dairy products at least once per week. Protein-rich foods, such as beans or nuts, meat, fish, chicken, and eggs were eaten less frequently. About one-half of children ate other fruits and vegetables, fatty foods, and sweet tea five times per week or more, but more than one-third never ate vitamin A rich fruits and vegetables.

About 7% of children 24-59 months of age had consumed baby formula during the week prior to the interview. As with the younger children, bread or other grain products, dairy products, other


fruits and vegetables, fatty foods, and sweet tea were consumed frequently in this age group. However, again as with younger children, foods rich in protein, other than dairy products, and vitamin A rich fruits and vegetables were not eaten so frequently.

table 42. Number (weighted %) and 95% CI of children eating various foods the day before the interview, by age group, children < 5 years of age, GNNS 2009

Age < 24 months Age 24-59 months

Food category Number(weighted %) 95% CI Number

(weighted %) 95% CI

Baby formula 308 (30.1) 26.1, 34.2 65 (5.1) 2.4, 7.8

Bread or grain products 811 (68.5) 65.4, 71.5 1512 (82.3) 78.7, 85.9

Beans or nuts 69 (5.7) 4.1, 7.3 435 (23.5) 20.6, 26.5

Dairy products 716 (58.7) 55.2, 62.2 1421 (76.8) 73.5, 80.1

Meat, fish, or chicken 352 (30.7) 26.3, 35.1 930 (54.2) 50.3, 58.2

Eggs 178 (16.0) 13.5, 18.5 603 (32.4) 29.0, 35.8

Vitamin A rich fruits or vegetables 259 (21.7) 18.1, 25.3 663 (36.4) 32.0, 40.8

Other fruits or vegetables 795 (67.1) 64.1, 70.0 1579 (87.2) 85.0, 89.4

Oily or fatty foods 651 (51.9) 47.7, 56.1 1583 (85.8) 82.8, 88.8

Sweet tea 690 (57.0) 52.7, 61.3 1474 (80.2) 77.4, 83.0

table 43. Number (weighted %) of children eating various foods the week before the interview with various frequencies, by age group, children < 24 months of age, GNNS 2009

Food category Never <1 day/week

1-2 days/week

3-4 days/week

5-7 days/week

Baby formula 898 (69.7) 12 (1.3) 18 (2.0) 21 (2.1) 257 (24.8)

Bread or grain products 300 (24.8) 32 (2.0) 71 (5.7) 109 (9.8) 694 (57.8)

Beans or nuts 716 (60.7) 249 (19.6) 150 (12.6) 67 (5.3) 19 (1.7)

Dairy products 289 (24.4) 56 (4.6) 168 (14.0) 239 (18.9) 454 (38.1)

Meat, fish, or chicken 375 (30.8) 171 (14.2) 335 (25.1) 230 (20.4) 90 (9.6)

Eggs 516 (43.5) 228 (18.9) 313 (25.2) 115 (10.1) 30 (2.2)

Vitamin A rich fruits or vegetables 479 (40.3) 168 (15.6) 229 (17.1) 190 (15.6) 136 (11.4)

Other fruits or vegetables 286 (23.6) 27 (2.2) 66 (4.9) 192 (16.8) 627 (52.5)

Oily or fatty foods 371 (31.1) 25 (2.4) 74 (7.0) 151 (13.1) 583 (46.4)

Sweet tea 358 (30.5) 19 (2.0) 79 (7.0) 151 (11.6) 601 (48.8)


table 44. Number (weighted %) of children eating various foods the week before the interview with various frequencies, by age group, children 24-59 months of age, GNNS 2009

Food category Never <1 day/week

1-2 days/week

3-4 days/week

5-7 days/week

Baby formula 1733 (93.1) 14 (0.7) 29 (2.2) 25 (2.3) 26 (1.8)

Bread or grain products 60 (3.4) 60 (2.9) 194 (10.2) 248 (15.0) 1265 (68.5)

Beans or nuts 287 (15.2) 637 (36.5) 615 (31.5) 219 (12.8) 66 (4.1)

Dairy products 25 (1.4) 84 (4.7) 346 (18.9) 571 (29.6) 799 (45.4)

Meat, fish, or chicken 29 (1.5) 264 (13.2) 766 (38.2) 528 (30.8) 243 (16.3)

Eggs 91 (5.0) 398 (22.6) 828 (45.4) 405 (21.7) 99 (5.3)

Vitamin A rich fruits or vegetables 95 (5.6) 363 (22.3) 598 (31.0) 508 (28.7) 250 (12.5)

Other fruits or vegetables 14 (0.7) 34 (2.0) 119 (7.1) 428 (24.1) 1224 (66.1)

Oily or fatty foods 6 (0.4) 17 (1.1) 112 (5.8) 348 (19.8) 1344 (72.9)

Sweet tea 60 (3.8) 42 (2.5) 111 (6.7) 308 (16.0) 1311 (71.0)

Children – protein-energy nutritional status

Acute protein-energy malnutrition (wasting) and overweight

The weighted distribution of weight-for-height z-scores is shown in Figure 8. The entire distribu-tion is displaced rightward compared to the WHO Child Growth Standard, showing that overall, Georgian children less than 5 years of age are fatter than children in the standard population.

As shown in Table 45 below, the overall prevalence and the majority of the subgroup-specific prevalence rates of acute protein-energy malnutrition are at or below the 2.3% prevalence found in the WHO Growth Standard which is considered normal. Moreover, in those groups in which the subgroup-specific prevalence is greater than 2.3% (children less than 12 months of age and children in the Azerbaijani and the “Other” ethnicity category), the difference between the mea-sured prevalence and 2.3% is almost certainly not statistically significant.

On the other hand, overweight and obesity are much more common nutritional problems. Over-all, as shown in Table 46, almost one in five children less than 5 years of age are overweight or obese. Overweight and obesity prevalence rates are not statistically different in boys and girls, but do decrease in prevalence with age. Although there is an apparent difference between some regional strata in the prevalence of overweight and obesity, few of these differences are statistically significant. There is very little difference between children living in rural households and those in urban households. Children of Armenia ethnicity have statistically significantly less overweight and obesity than Georgian and Azerbaijani children.


Figure 8. Weighted distribution of weight-for-height z-scores in children less than 5 years of age, GNNS 2009

0

5

10

15

20

-4.99to -4.5

-4.49to -4.0

-3.99to -3.5

-3.49to -3.0

-2.99to -2.5

-2.49to -2.0

-1.99to -1.5

-1.49to -1.0

-0.99to -0.5

-0.49to 0.0

0.01to 0.5

0.51to 1.0

1.01to 1.5

1.51to 2.0

2.01to 2.5

2.51to 3.0

3.01to 3.5

3.51to 6.0

4.01to 4.5

4.51to 5.0

Weight-for-height z-score

Wei

ghte

d %

of c

hild

ren

Georgia

WHO Child Growth Standard

Georgia z-scoresMean = 0.98 SD = 1.29


table 45. Number (weighted %) with various levels of acute protein-energy malnutrition or wasting, overweight, or obesity* (defined by weight-for-height z-score calculated using WHo Child Growth Standard), children less than 5 years of age, GNNS 2009

Characteristic Severewasting

moderatewasting

None(normal) overweight obese

TOTAL 19 (0.6) 29 (1.0) 2352 (78.5) 371 (13.1) 180 (6.8)

Sex Male 13 (0.8) 16 (1.0) 1244 (74.9) 201 (13.0) 147 (10.3) Female 11 (0.7) 13 (0.8) 1108 (79.2) 170 (12.6) 86 (6.6)

Age <12 months 7 (0.9) 15 (2.9) 396 (69.0) 95 (17.1) 53 (10.1) 12-23 months 6 (1.0) 1 (0.2) 471 (72.7) 99 (16.2) 61 (9.9) 24-35 months 3 (0.3) 5 (0.6) 456 (80.1) 61 (9.8) 44 (9.1) 36-47 months 5 (1.1) 3 (0.6) 433 (81.3) 51 (10.5) 32 (6.5) 48-59 months 3 (0.5) 5 (0.6) 596 (81.2) 65 (10.4) 43 (7.2)

Region Tbilisi 3 (0.8) 2 (0.5) 292 (80.2) 35 (9.6) 32 (8.8) Achara and Guria 1 (0.3) 4 (1.2) 235 (69.5) 49 (14.5) 49 (14.5) Imereti and Racha- Leckhumi 1 (0.5) 3 (1.4) 140 (67.0) 44 (21.1) 21 (10.0)

Kakheti 3 (1.0) 4 (1.3) 255 (83.9) 31 (10.2) 11 (3.6) Kvemo Kartli 8 (1.1) 6 (0.8) 590 (77.6) 96 (12.6) 60 (7.9) Samegrelo 2 (0.7) 1 (0.4) 222 (80.4) 36 (13.0) 15 (5.4) Samtckhe-Javakheti 4 (0.8) 5 (1.0) 418 (83.9) 49 (9.8) 22 (4.4) Shida Kartli and Mtckheta-Mtianeti 2 (0.8) 4 (1.5) 200 (76.9) 31 (11.9) 23 (8.8)

Rural/Urban Rural 16 (0.9) 15 (0.9) 1400 (76.3) 228 (13.6) 137 (8.3) Urban 8 (0.6) 14 (1.0) 952 (77.6) 143 (12.1) 96 (8.9)

Ethnic group Georgian 13 (0.5) 22 (0.9) 1715 (76.7) 270 (12.9) 179 (9.0) Armenian 2 (0.6) 2 (0.4) 314 (86.4) 38 (11.0) 6 (1.5) Azerbaijani 7 (1.7) 3 (0.7) 289 (72.5) 59 (14.3) 45 (10.8) Other 2 (6.7) 2 (5.7) 30 (71.7) 4 (11.0) 3 (5.0)

* Severe = z-score < -3.0 or edema; Moderate = z-score -3.0 - <-2.0 without edema; None = z-score > -2.0 without edema


table 46. Number (weighted %) with overweight or obesity* (defined by weight-for-height z-score calculated using WHo Child Growth Standard), children less than 5 years of age, GNNS 2009

CharacteristicNo. (weighted %) with overweight or

obesity*95% CI

TOTAL 551 (19.9) 17.5, 22.3

Sex Male 312 (21.3) 18.7, 23.9 Female 239 (18.3) 15.2, 21.5

Age <12 months 134 (25.3) 20.5, 30.0 12-23 months 146 (24.4) 20.3, 28.4 24-35 months 96 (17.6) 13.4, 21.9 36-47 months 78 (16.1) 12.2, 20.1 48-59 months 97 (16.2) 11.3, 21.1



Ethnic group Georgian 409 (20.3) 17.6, 23.0 Armenian 44 (12.6) 7.4, 17.7 Azerbaijani 92 (23.0) 17.5, 28.6 Other 6 (14.6) 1.9, 27.2

* Overweight or obesity = weight-for-height z-score > +2.0

Chronic protein-energy malnutrition (stunting)

In contrast to acute protein-energy malnutrition, there is substantial chronic protein-energy mal-nutrition, or stunting, in Georgian children less than 5 years of age. Figure 9 shows the weighted distribution of height-for-age z-scores among children less than 5 years of age in Georgia. The curve is shifted slightly to the left compared to that of the WHO Child Growth Standard, demon-strating that Georgian children less than 5 years of age are, on average, somewhat shorter than age-matched children in the standard population. As seen in Table 47, 40% of the stunting in Georgia is severe. As seen in Table 48, although boys seem to have more stunting than girls, this difference is not statistically significant. There is little trend in stunting with age. In contrast, there are substantial differences in the prevalence rates of stunting between regional strata, with


a range of 6.0% to 19.7%. Many of the differences between strata are statistically significant. On the other hand, there is no statistically significant difference in stunting between children in rural households and those in urban households. Stunting prevalence differs substantially by ethnicity, with the prevalence in Azerbaijani children being almost twice that in other children.

Figure 9. Weighted distribution of height-for-age z-scores in children less than 5 years of age, GNNS 2009

0

5

10

15

20

-5.99to -5.5

-5.49to -5.0

-4.99to -4.5

-4.49to -4.0

-3.99to -3.5

-3.49to -3.0

-2.99to -2.5

-2.49to -2.0

-1.99to -1.5

-1.49to -1.0

-0.99to -0.5

-0.49to 0.0

0.01to 0.5

0.51to 1.0

1.01to 1.5

1.51to 2.0

2.01to 2.5

2.51to 3.0

3.01to 3.5

3.51to 6.0

4.01to4.5

4.51to5.0

5.01gto5.5

Height-for-age z-score

Wei

ghte

d %

of c

hild

ren

Georgia

WHO Child Growth Standard

Georgia z-scoresMean = -0.32SD = 1.51


table 47. Number (weighted %) with various levels of chronic protein-energy malnutrition (defined by height-for-age z-score calculated using WHO Child Growth Standard*), children less than 5 years of age, GNNS 2009

Characteristic Severestunting*

moderate stunting*

None*

(normal)

TOTAL 125 (4.5) 223 (6.8) 2579 (88.7)

Sex Male 78 (5.3) 127 (7.0) 1363 (87.7) Female 47 (3.6) 96 (6.6) 1216 (89.8)

Age <12 months 28 (4.7) 38 (6.5) 475 (88.8) 12-23 months 25 (3.8) 57 (8.2) 532 (88.1) 24-35 months 26 (5.5) 50 (7.6) 478 (87.0) 36-47 months 21 (4.6) 36 (5.9) 455 (89.5) 48-59 months 25 (4.2) 42 (6.0) 639 (89.8)

Region Tbilisi 13 (3.7) 13 (3.7) 326 (92.6) Achara and Guria 31 (9.4) 34 (10.3) 265 (80.3) Imereti and Racha-Leckhumi 13 (6.3) 18 (8.8) 174 (84.9) Kakheti 6 (2.0) 12 (4.0) 280 (94.0) Kvemo Kartli 36 (4.9) 77 (10.5) 621 (84.6) Samegrelo 4 (1.5) 19 (7.0) 247 (91.5) Samtckhe-Javakheti 15 (3.0) 43 (8.7) 434 (88.2) Shida Kartli and Mtckheta-Mtianeti 7 (2.8) 7 (2.8) 232 (94.3)


Ethnic group Georgian 86 (4.4) 137 (6.0) 1917 (89.6) Armenian 7 (1.9) 31 (9.7) 322 (88.4) Azerbaijani 31 (8.0) 51 (12.8) 302 (79.2) Other 1 (2.6) 4 (9.2) 34 (88.3)

* Severe = z-score < -3.0; Moderate = z-score -3.0 - <-2.0; None = z-score > -2.0


Table 48. Number (weighted %) with any chronic protein-energy malnutrition (defined by height-for-age z-score calculated using WHo Child Growth Standard*), children less than 5 years of age, GNNS 2009

Characteristic No. (weighted %) with stunting* 95% CI

TOTAL 348 (11.3) 9.1, 13.6

Sex Male 205 (12.3) 9.6, 15.0 Female 143 (10.2) 7.6, 12.9

Age <12 months 66 (11.2) 8.1, 14.2 12-23 months 82 (11.9) 9.0, 14.9 24-35 months 76 (13.0) 8.8, 17.2 36-47 months 57 (10.5) 6.9, 14.0 48-59 months 67 (10.2) 5.9, 14.5




* Stunting = height-for-age z-score < -2.0


underweight

As shown in Table 49, underweight is uncommon in children less than 5 years of age in Georgia. Overall, and in all subgroups individually, the prevalence of underweight was less than the 2.3% prevalence in the WHO Child Growth Standard which is considered normal.

table 49. Number (weighted %) with various levels of underweight* (defined by height-for-age z-score calculated using WHo Child Growth Standard*), children less than 5 years of age, GNNS 2009

Characteristic Severeunderweight*

moderate underweight* None*

TOTAL 14 (0.5) 25 (0.6) 2981 (98.8)

Sex Male 7 (0.4) 19 (0.9) 1599 (98.7) Female 7 (0.6) 6 (0.4) 1382 (99.0)

Age <12 months 3 (0.4) 7 (0.8) 561 (98.7) 12-23 months 3 (0.7) 4 (0.7) 627 (98.6) 24-35 months 1 (0.1) 2 (0.3) 573 (99.6) 36-47 months 5 (1.3) 4 (0.6) 518 (98.1) 48-59 months 2 (0.2) 8 (0.8) 702 (99.0)

Region Tbilisi 3 (0.8) 1 (0.3) 360 (98.9) Achara and Guria 2 (0.6) 1 (0.3) 337 (99.1) Imereti and Racha-Leckhumi 1 (0.5) 2 (1.0) 204 (98.6) Kakheti 2 (0.7) 1 (0.3) 304 (99.0) Kvemo Kartli 2 (0.3) 8 (1.1) 751 (98.7) Samegrelo 1 (0.4) 3 (1.1) 272 (98.6) Samtckhe-Javakheti 3 (0.6) 8 (1.6) 490 (97.8) Shida Kartli and Mtckheta-Mtianeti 0 1 (0.4) 263 (99.6)


Ethnic group Georgian 11 (0.5) 11 (0.5) 2188 (99.0) Armenian 1 (0.4) 5 (0.9) 359 (98.6) Azerbaijani 2 (0.5) 8 (2.1) 390 (97.4) Other 0 1 (2.2) 40 (97.8)

* Severe = z-score < -3.0; Moderate = z-score -3.0 - <-2.0; None = z-score > -2.0


Children – micronutrient status

Anemia

Anemia is quite common in children less than 5 years of age in Georgia. The weighted distri-bution of hemoglobin concentrations in children less than 5 years of age is shown in Figure 10 below. A substantial proportion of hemoglobin values are below the cut-off defining anemia in young children (11.0 g/dL). Although anemia is quite common, severe anemia is relatively rare, as shown in Table 50.

As shown in Table 51, the prevalence of anemia did not differ substantially between boys and girls. The prevalence of anemia declines with age. The prevalence of anemia is also quite dif-ferent between regional strata, from 9.2% of children living in Imereti and Racha-Leckhumi to 32.2% of children living in Kvemo Kartli. There was little difference in weighted anemia preva-lence between children living in rural households and those living in urban households. Azerbai-jani children had a substantially and statistically significantly higher prevalence of anemia than children of other ethnicities.

The correlation between breastfeeding and anemia could only be analyzed in children 12-23 months of age because children less than 12 months of age did not undergo the fingerstick necessary to measure hemoglobin. Moreover, among children 24 months of age and older, the prevalence of breastfeeding was too low. Among the 578 children 12-23 months of age who had both breastfeeding information and a hemoglobin measurement, children who were breastfed the day before the interview were 25% more likely to be anemic than children who had not breastfed (adjusted relative risk [RR] = 1.25, 95% CI: 0.96, 1.63).

Figure 10. Weighted distribution of hemoglobin concentrations in children less than 5 years of age, GNNS 2009

0

5

10

15

20

25

5.0-5.9

6.0-6.9

7.0-7.9

8.0-8.9

9.0-9.9

10.0-10.9

11.0-11.9

12.0-12.9

13.0-13.9

14.0-14.9

15.0-15.9

16.0-16.9

17.0-17.9

18.0-18.9

19.0-19.9

Hemoglobin concentration (g/dl)

Wei

ghte

d %

of c

hild

ren


table 50. Number (weighted %) with various degrees of anemia*, children 12-59 months of age, GNNS 2009

Characteristic Severeanemia*

moderateanemia*

mild anemia*

No anemia*

(normal)

TOTAL 13 (0.6) 232 (9.4) 287 (12.8) 1690 (77.2)

Sex Male 8 (0.8) 138 (10.3) 139 (11.5) 911 (77.4) Female 5 (0.4) 94 (8.4) 148 (14.3) 779 (76.9)

Age <12 months NA* NA NA NA 12-23 months 6 (1.0) 95 (13.6) 117 (21.3) 358 (64.1) 24-35 months 3 (0.5) 48 (9.4) 63 (11.1) 403 (79.0) 36-47 months 0 34 (6.7) 50 (8.7) 386 (84.7) 48-59 months 4 (0.7) 54 (7.6) 57 (9.6) 542 (82.2)

Region Tbilisi 2 (0.9) 22 (9.6) 40 (17.5) 165 (72.1) Achara and Guria 0 13 (5.8) 29 (12.9) 183 (81.3) Imereti and Racha-Leckhumi 0 5 (2.9) 11 (6.3) 158 (90.8) Kakheti 0 16 (7.0) 29 (12.8) 182 (80.2) Kvemo Kartli 5 (0.9) 88 (16.2) 89 (16.4) 362 (66.5) Samegrelo 4 (1.7) 34 (14.7) 22 (9.5) 171 (74.0) Samtckhe-Javakheti 1 (0.3) 33 (8.5) 44 (11.3) 310 (79.9) Shida Kartli and Mtckheta-Mtianeti 1 (0.5) 21 (10.3) 23 (11.3) 159 (77.9)

Rural/Urban Rural 10 (0.7) 164 (11.2) 158 (11.4) 1049 (76.7) Urban 3 (0.5) 68 (7.4) 129 (14.3) 641 (77.8)

Ethnic group Georgian 7 (0.5) 142 (8.4) 186 (12.0) 1247 (79.0) Armenian 1 (0.2) 31 (9.8) 46 (16.7) 219 (73.3) Azerbaijani 5 (1.6) 56 (17.8) 51 (16.2) 196 (64.4) Other 0 3 (12.8) 4 (18.4) 26 (68.8)

* Severe = Altitude-adjusted hemoglobin < 7.0 g/dl; Moderate = altitude-adjusted hemoglobin 7.0 – 9.99 g/dl;

Mild = altitude-adjusted hemoglobin 10.0 – 10.99; No anemia = altitude-adjusted hemoglobin > 11.0 g/dl NA = Not applicable; subgroup not measured


table 51. Number (weighted %) with any anemia*, children 12-59 months of age, GNNS 2009

Characteristic No. (weighted %) with anemia* 95% CI

TOTAL 532 (22.8) 19.5, 26.1

Sex Male 285 (22.6) 19.1, 26.0 Female 247 (23.1) 18.6, 27.5

Age <12 months Not available Not available 12-23 months 218 (35.9) 30.5, 41.2 24-35 months 114 (21.0) 15.9, 26.2 36-47 months 84 (15.3) 11.5, 19.1 48-59 months 115 (17.8) 13.7, 22.0




* Anemia = Altitude-adjusted hemoglobin concentration < 11.0 g/dl


Iron deficiency

Overall, 496 (24.7%) of the 2144 children less than 5 years of age in whom CRP was measured had an elevated CRP indicating the presence of acute inflammation. After exclusion of these children, very few children had iron deficiency, as seen in Table 52 below.

Table 52. Number (weighted %) and 95% confidence intervals (CI) with iron deficiency*, children less than 5 years of age, GNNS 2009

Characteristic No. (weighted %) with iron deficiency* 95% CI

TOTAL 3 (0.1) 0, 0.3

Sex Male 1 (0.1) 0, 0.2 Female 2 (0.2) 0, 0.5

Age (months) <12 months Not available Not available 12-23 months 2 (0.3) 0, 0.7 24-35 months 0 36-47 months 1 (0.3) 0, 1.0 48-59 months 0

Region Tbilisi 0 Achara and Guria 0 Imereti and Racha-Leckhumi 0 Kakheti 0 Kvemo Kartli 2 (0.5) 0, 1.2 Samegrelo 0 Samtckhe-Javakheti 0 Shida Kartli and Mtckheta-Mtianeti 1 (0.7) 0, 2.0

Rural/Urban Rural 3 (0.3) 0, 0.6 Urban 0

Ethnic group Georgian 1 (0.1) 0, 0.2 Armenian 1 (0.5) 0, 1.6 Azerbaijani 1 (0.4) 0, 1.3 Other 0

Degree of anemia Severe (Hb < 7.0 g/dl) 0 Moderate (Hb 7.0-10.9 g/dl) 1 (0.3) 0, 0.9 None (Hb > 11.0 g/dl) 2 (0.1) 0, 0.2

* Iron deficient = Serum ferritin < 12.0 µg/l and CRP < 5.0 mg/l. Children with CRP > 5.0 mg/l excluded from analysis.


Non-pregnant women – Description of sample

Table 53 shows demographic characteristics of the 1,846 non-pregnant women 15-49 years of age recruited from households in the GNNS 2009 survey sample. This table also compares them to Georgian census data. The weighted age distribution of survey sample non-pregnant women roughly matches the age distribution of the population of all Georgian women 15-49 years of age. Similarly the weighted regional and rural/urban distribution of the survey sample of non-pregnant women matches that of the general population of Georgia quite well. The proportions of survey sample non-pregnant women who are Georgian ethnicity and who are married are somewhat greater than the corresponding proportions in the population of Georgian women 15-49 years of age. Survey sample non-pregnant women were quite well educated, with more than one-half having some university or vocational school education.

Table 54 shows the reproductive and breastfeeding history of non-pregnant women in the GNNS 2009 sample. Slightly more than one-quarter had never been pregnant, and almost one-third had been pregnant five or more times. Few women had had four or more live births in the past. Fewer than one in 10 non-pregnant women in the survey sample were breastfeeding at the time of data collection.

Table 55 shows the distribution of selected behavioral variables. Only a small minority of women smoked cigarettes. About one-half added salt to their food; however, a smaller proportion added salt to their food before testing it.

table 53. Description of demographic variables, non-pregnant women 15-49 years of age, GNNS 2009

Survey sample Census*

Characteristic Actual number of women

Weighted % of women % population

TOTAL 1846 100.0 100.0

Age 15-19 203 10.9 15.3 20-24 318 16.3 14.2 25-29 289 14.9 13.7 30-34 266 14.8 13.4 35-39 246 13.9 14.8 40-44 225 12.6 15.3 45-49 299 16.5 13.2


Rural/Urban Rural 1125 49.0 47.3


Survey sample Census*


Weighted % of women % population

Urban 721 51.0 52.7

Ethnic group Georgian 1479 88.6 84.1 Armenian 168 4.0 5.7 Azerbaijani 168 5.4 6.5 Other 31 2.0 3.6

Religion Orthodox 1407 86.0 Muslim 254 9.3 Armenian Gregorian 139 3.1 Roman Catholic 27 0.5 None 3 0.2 Other 13 0.9

Marital status Married 1355 71.2 60.8 Widowed 40 2.0 3.8 Divorced 36 2.3

4.4 Separated 14 0.9 Never married 397 23.6 31.1

Years of formal education 4-9 (Some or completed secondary school) 258 11.6

10-11 (Some or completed high school) 682 33.6

12-14 (Some university or vocational school) 394 22.2

15+ (Completed university or more) 512 32.6

* Data from National Statistics Office of Georgia For regional and urban/rural distribution: 2009 estimates of general population (http://www.geostat.ge/in-

dex.php?action=page&p_id=473&lang=eng, accessed 12 March 2010) For distribution of age, ethnic group, and marital status: 2002 census data for women 15-49 years of age

(http://www.geostat.ge/, accessed 24 March 2010)


table 54. Description of reproductive and breastfeeding variables, non-pregnant women 15-49 years of age, GNNS 2009


Weighted % of women

Number of prior pregnancies 0 471 27.5 1 200 10.6 2 248 12.7 3 182 9.6 4 167 8.9 5+ 578 30.6

Number of prior live births 0 483 28.3 1 326 18.4 2 710 36.6 3 246 12.5 4 58 2.9 5+ 23 1.4

Breastfeeding now (among women with prior live birth) Yes 120 8.4 No 1248 91.6

table 55. Description of behavioral variables, non-pregnant women 15-49 years of age, GNNS 2009


Weighted % of women

Number of cigarettes smoked per day 0 (Does not smoke) 1779 94.0 1-9 20 2.1 10-19 25 2.2 20-39 19 1.6 40+ 1 0.1

Usually add salt to food before eating Yes 1011 54.6 No 826 45.4

Usually add salt to food before tasting Yes 699 38.6 No 1137 61.4


Non-pregnant women – protein-energy nutritional status

The distribution of BMI values for non-pregnant women 15-49 years of age, shown in Figure 11 below, demonstrates that few women have low BMI, but many woman have high BMI. Table 56 shows the overall and group-specific prevalence rates for the various degrees of malnutrition as measured by BMI. Severe and moderate energy deficiency are quite rare, and only a few percent of women fall into the category “at risk of energy deficiency.” On the other hand, overweight and obesity are much more common. As shown in Table 57, the prevalence of overweight or obesity increases markedly with age. The prevalence also varies by regional stratum, with the lowest stratum-specific prevalence being 30.2% in Tbilisi and the highest being 53.3% in Imereti and Racha-Leckhumi. The prevalence is also statistically significantly higher in women living in rural households; however, the prevalence does not differ substantially among ethnic groups.

Figure 11. Distribution of BmI values for non-pregnant women 15-49 years of age, GNNS 2009

0

1

2

3

4

5

6

7

8

9

10

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 4950+

BMI

Wei

ghte

d %

of w

omen

Normal Overweight Obese


Table 56. Number (weighted %) with various levels of malnutrition (defined by BMI*), non-pregnant women 15-49 years of age, GNNS 2009

CharacteristicSevere energy

deficiency*

moderate energy

deficiency*

At risk of energy

deficiency*Normal* overweight* obese*

TOTAL 3 (0.3) 13 (1.1) 71 (3.9) 959 (52.7) 468 (24.1) 314 (18.0)

Age (years) 15-24 2 (0.8) 9 (2.6) 38 (8.6) 383 (72.6) 65 (12.2) 16 (3.2) 25-34 0 4 (1.2) 20 (3.2) 331 (61.5) 126 (21.4) 69 (12.8) 35-44 1 (0.2) 0 9 (1.5) 171 (39.8) 166 (32.1) 121 (26.3) 45-49 0 0 4 (1.0) 74 (25.0) 111 (35.5) 108 (38.4)

Region Tbilisi 2 (1.0) 6 (2.9) 11 (5.4) 124 (60.5) 33 (16.1) 29 (14.1) Achara and Guria 0 1 (0.5) 9 (4.1) 119 (53.6) 60 (27.0) 33 (14.9)

Imereti and Racha-Leckhumi

0 1 (0.6) 2 (1.2) 74 (44.8) 43 (26.1) 45 (27.3)

Kakheti 0 1 (0.6) 12 (6.7) 100 (55.9) 41 (22.9) 25 (14.0) Kvemo Kartli 0 2 (0.6) 18 (5.0) 183 (50.8) 99 (27.5) 58 (16.1) Samegrelo 0 1 (0.5) 4 (2.0) 98 (47.8) 54 (26.3) 48 (23.4) Samtckhe-Javakheti 0 0 7 (2.5) 156 (54.7) 81 (28.4) 41 (14.4)


1 (0.5) 1 (0.5) 8 (3.9) 105 (50.7) 57 (27.5) 35 (16.9)

Rural/Urban Rural 1 (0.1) 6 (0.6) 41 (3.4) 568 (50.3) 302 (26.7) 191 (18.9) Urban 2 (0.4) 7 (1.5) 30 (4.3) 391 (55.0) 166 (21.6) 123 (17.2)

Ethnic group Georgian 3 (0.3) 12 (1.2) 56 (3.6) 759 (52.5) 364 (24.0) 268 (18.4) Armenian 0 0 3 (2.2) 92 (53.7) 53 (27.6) 19 (16.5) Azerbaijani 0 1 (0.6) 10 (5.6) 88 (52.8) 46 (26.5) 23 (14.5) Other 0 0 2 (11.1) 20 (59.1) 5 (14.7) 4 (15.1)

* Severe = BMI<16.0; Moderate = BMI 16.0-16.9; At risk = BMI 17.0-18.4; Normal = BMI 18.5-24.9; Over-weight = BMI 25.0-29.9; Obese = BMI>30.0


table 57. Number (weighted %) with overweight or obesity* (defined by BMI), non-pregnant women 15-49 years of age, GNNS 2009

CharacteristicNo. (weighted %) with overweight or

obesity*95% CI

TOTAL 782 (42.1) 39.2, 45.0

Age (years) 15-24 81 (15.4) 11.7, 19.0 25-34 195 (34.2) 29.7, 38.6 35-44 287 (58.4) 52.7, 64.2 45-49 219 (73.9) 67.7, 80.2




* Overweight = BMI > 25.0

Non-pregnant women – micronutrient status

Anemia

The weighted distribution of hemoglobin concentrations in non-pregnant women 15-49 years of age is shown in Figure 12. The pink bars in this figure show anemic women and demonstrate that anemia is quite common in non-pregnant women in Georgia. In addition, the brown bars show women with excessive hemoglobin concentrations. Although not as common as anemia, exces-sive hemoglobin may also be a problem in Georgian women.

Although 24.1% of non-pregnant women had any level of anemia, severe anemia is relatively rare, as shown in Table 58. Table 59 shows that anemia is not strongly related to age. How-ever, the prevalence of anemia in non-pregnant women differs substantially by regional stratum ranging from 14.5% in Imereti and Racha-Leckhumi to 32.4% in Kakheti. As seen in Table 51 and Table 59, with the exception of Kakheti, those regional strata with higher prevalence rates of


anemia in children less than 5 years of age are the same as those with higher prevalence rates of anemia in non-pregnant women 15-49 years of age. Anemia prevalence did not differ substan-tially between women living in rural households and those living in urban households. Although Georgian women apparently have a lower prevalence than Armenian or Azerbaijani women, these differences may not be statistically significant.

Figure 12. Weighted distribution of hemoglobin concentrations in non-pregnant women 15-49 years of age, GNNS 2009

0

5

10

15

20

25

6.0-6.9

7.0-7.9

8.0-8.9

9.0-9.9

10.0-10.9

11.0-11.9

12.0-12.9

13.0-13.9

14.0-14.9

15.0-15.9

16.0-16.9

17.0-17.9

18.0-18.9

19.0-19.9


Wei

ghte

d %

of w

omen

table 58. Distribution of levels of adjusted* hemoglobin concentrations, non-pregnant women 15-49 years of age, GNNS 2009

Category of adjusted hemoglobin concentration

No. (weighted %) with adjusted

hemoglobin concentration

95% CI

Severe anemia (Hb < 7.0 g/dl) 7 (0.4) 0.1, 0.7

Moderate anemia (Hb 7.0-10.9 g/dl) 164 (9.1) 7.3, 11.0

Mild anemia (Hb 11.0-11.9 g/dl) 251 (14.6) 12.3, 16.9

Normal (Hb 12.0-15.9 g/dl) 1227 (71.0) 67.9, 74.0

Mild elevation (Hb 16.0-16.9 g/dl) 42 (2.5) 1.4, 3.6

Moderate elevation (Hb 17.0+ g/dl) 30 (2.4) 0.9, 3.9

* Adjusted for number of cigarettes smoked per day and altitude of residence


Table 59. Number (weighted %) and 95% confidence intervals (CI) with any anemia* (after ad-justment of hemoglobin concentration for smoking status and altitude of residence), non-pregnant women 15-49 years of age, GNNS 2009


TOTAL 422 (24.1) 21.0, 27.2

Age (years) 15-24 108 (22.8) 18.1, 27.5 25-34 133 (26.0) 21.1, 31.0 35-44 110 (24.6) 20.0, 29.3 45-49 71 (22.0) 15.3, 28.7




* Anemia = Adjusted hemoglobin concentration < 12.0 g/dl; Not anemic = adjusted hemoglobin concentration 12.0+ g/ dl

Iron deficiency

Overall, 472 (29.5%) of the 1,688 non-pregnant women 15-49 years of age in whom CRP was measured had an elevated CRP indicating the presence of acute inflammation. After exclusion of these 472 women, very few women had iron deficiency, as seen in Table 60 below. Nonetheless, iron deficient non-pregnant women were more than twice as likely to be anemic as non-pregnant women who were not iron deficient (adjusted RR = 2.5, 95% CI: 1.6, 3.9). (Table 61) On the other hand, because it is so rare, iron deficiency contributes to very little to anemia in Georgia. Only 9 (weighted % = 3.8%) of the 281 anemic non-pregnant women in whom iron deficiency was assessed had iron deficiency.


Table 60. Number (weighted %) and 95% confidence intervals (CI) with iron deficiency,* non-pregnant women 15-49 years of age, GNNS 2009

CharacteristicNo. (weighted %) with iron deficiency*

95% CI

TOTAL 19 (1.6) 0.8, 2.4 Age (years) 15-24 4 (1.0) 0, 2.1 25-34 5 (1.7) 0.1, 3.3 35-44 8 (1.9) 0.5, 3.4 45-49 2 (2.0) 0, 4.8

Region Tbilisi 1 (0.9) 0, 2.8 Achara and Guria 3 (2.1) 0, 4.2 Imereti and Racha-Leckhumi 2 (1.8) 0, 4.3 Kakheti 1 (0.8) 0, 2.4 Kvemo Kartli 4 (1.6) 0.1, 3.1 Samegrelo 1 (0.7) 0, 2.0 Samtckhe-Javakheti 2 (1.1) 0, 2.6 Shida Kartli and Mtckheta-Mtianeti 5 (3.5) 0, 7.0


Ethnic group Georgian 15 (1.6) 0.7, 2.6 Armenian 2 (1.2) 0, 3.0 Azerbaijani 2 (1.7) 0, 4.0 Other 0

* Iron deficiency = Serum ferritin concentration < 15 µg/l and CRP < 5.0 mg/l. Women with CRP > 5.0 mg/l excluded from analysis.

table 61. Number (weighted %) with anemia,* by iron deficiency status*, non-pregnant women 15-49 years of age, GNNS 2009

Characteristic No. (weighted %) with anemia*

No. (weighted %) without anemia*

Iron deficient 9 (54.1) 10 (45.9) Not iron deficient 242 (20.8) 910 (79.2)

* Anemia = Adjusted hemoglobin concentration < 12.0 g/dl; Iron deficiency = Serum ferritin concentration < 15 µg/l AND CRP < 5.0 mg/l. Wom-

en with CRP > 5.0 mg/l excluded from analysis.


Folate

More than one-third of the 407 non-pregnant women 15-49 years of age who were tested had folate deficiency (weighted % = 36.6%; 95% CI: 29.8, 43.3). The mean serum folate level was 7.2 ng/mL (95% confidence intervals: 6.3, 8.2).

pregnant women – Description of sample

Table 62 shows the demographic characteristics of the 613 pregnant women recruited from ante-natal facilities in Georgia for the GNNS 2009. Because women frequently seek ante-natal care in facilities outside their province of residence, the distribution of sample pregnant women cannot be compared to the general population of Georgia. It is instead compared to the number of routine ante-care visits expected to occur in all facilities in each regional stratum during the time of the survey teams’ data collection in that province. As expected, most pregnant women in the sample were of Georgian ethnicity and were of Orthodox religion. Almost all the women reported being married. As with non-pregnant women, pregnant women were quite well educated with almost one-half having some university or vocational school education.

Table 63 shows the reproductive history of pregnant women. For less than one-half, the cur-rent pregnancy is the first. As with non-pregnant women in the household sample, few pregnant women had had four or more live births in the past. Pregnant women in the survey sample in-cluded women in all three trimesters of pregnancy. As expected, a larger proportion of women were in the second and third trimesters when women are more likely to seek ante-natal care.

Table 64 shows the distribution of selected behavioral variables. Fewer than one-half of pregnant women had taken vitamins or other nutritional supplements during the current pregnancy. Of those who did, slightly more than one-third had taken iron supplements. As with non-pregnant women, about one-half of pregnant women usually add salt to their food before eating, but a smaller proportion add salt before tasting the food. Smoking is quite rare among pregnant women in Georgia.

table 62. Description of demographic variables, pregnant women, GNNS 2009

Survey sample program data


Weighted % of women

% routine ANC visits

TOTAL 613 100

Age 15-19 105 10.7 20-24 257 39.7 25-29 149 25.7 30-34 67 15.2 35-39 21 4.4 40-44 11 3.0 45-49 3 1.1

Region Tbilisi 115 32.4 10.9 Achara and Guria 13 4.8 1.7


Survey sample program data


Weighted % of women

% routine ANC visits

Imereti and Racha-Leckhumi 10 3.7 1.1 Kakheti 2 0.7 0.1 Kvemo Kartli 241 23.3 48.7 Samegrelo 15 5.6 2.4 Samtckhe-Javakheti 215 28.7 34.6 Shida Kartli and Mtckheta-Mtianeti 2 0.7 0.5

Ethnic group Georgian 241 89.4 Armenian 184 3.5 Azerbaijani 183 6.4 Other 5 0.7

Religion Orthodox 242 81.9 Muslim 201 14.0 Armenian Gregorian 156 3.3 Roman Catholic 11 0.2 None 3 0.5 Other

Marital status Married 610 99.6 Widowed 1 0.4 Divorced 0 Separated 1 0.0 Never married 0

Years of formal education 4-9 (Some or completed secondary school) 155 12.9

10-11 (Some or completed high school) 197 19.7

12-14 (Some university or vocational school) 92 21.9

15+ (Completed university or more) 169 45.5


table 63. Description of reproductive history, pregnant women, GNNS 2009


Weighted % of women

Number of prior pregnancies 0 265 42.3 1 160 24.0 2 89 14.4 3 39 6.3 4 27 5.3 5+ 33 7.8

Number of prior live births 0 295 46.9 1 212 33.8 2 90 16.0 3 12 2.4 4 1 0.0 5+ 2 0.7

Current pregnancy trimester 1 99 20.1 2 285 44.2 3 229 35.6

table 64. Description of behavioral variables, pregnant women, GNNS 2009

CharacteristicActual number

of pregnant women

Weighted % of pregnant

women

Taken vitamins or supplements during this pregnancy Yes 253 44.2 No 360 55.8

Type of vitamin or supplement taken Iron 44 35.2 Vitamin C 22 10.5 Other 83 50.4 Unknown 17 3.9

Usually add salt to food before eating Yes 345 50.0 No 251 50.0

Usually add salt to food before tasting Yes 169 20.5 No 441 79.5

Number of cigarettes smoked per day Does not smoke 605 98.8 1-9 6 1.2 10-19 0 20-39 0 40+ 0


pregnant women – protein-energy nutritional status

Overall, as shown in Figure 13, protein-energy malnutrition is not a common or severe problem in pregnant women in Georgia. As seen in Table 65, the prevalence of low MUAC was low and did not differ substantially between subgroups.

Figure 13. Weighted distribution of muAC measurements, pregnant women, GNNS 2009

0

2

4

6

8

10

12

14

16

18

18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

MUAC (cm)

Wei

ghte

d %

of p

regn

ant w

omen

Table 65. Number (weighted %) and 95% confidence intervals (CI) with low MUAC* , pregnant women, GNNS 2009

Characteristic No. (weighted %) with low muAC* 95% CI

TOTAL 24 (4.8) 1.8, 7.9

Age in years 15-24 14 (5.5) 1.3, 9.8 25-34 9 (4.8) 0.9, 8.8 35-44 1 (0.5) 0, 1.4 45-49 0

Ethnic group Georgian 12 (5.0) 1.6, 8.4 Armenian 4 (2.2) 0, 5.4 Azerbaijani 8 (4.4) 0.9, 7.9 Other 0

Current pregnancy trimester 1 3 (3.9) 0, 9.4 2 14 (7.1) 0.7, 13.4 3 7 (2.5) 0, 5.6

* Low MUAC = MUAC < 22.0 cm


pregnant women – micronutrient status

Anemia

As shown in Figure 14 and Table 66, anemia is common in pregnant women in Georgia; however, as with non-pregnant women, only a small proportion of the anemia in this group is severe. The prevalence of anemia in pregnant women does not differ substantially by age of the woman, as seen in Table 67. There is, however, a higher prevalence of anemia in pregnant Azerbaijani women than in Georgian or Armenian women, and these differences are statistically significant. Anemia also becomes more common with pregnancy stage; by the third trimester, almost one-third of pregnant women in Georgia are anemic.

Figure 14. Weighted distribution of hemoglobin concentrations in pregnant women, GNNS 2009

0

5

10

15

20

25

5.0-5.9

6.0-6.9

7.0-7.9

8.0-8.9

9.0-9.9

10.0-10.9

11.0-11.9

12.0-12.9

13.0-13.9

14.0-14.9

15.0-15.9

16.0-16.9

17.0-17.9

18.0-18.9

19.0-19.9


Wei

ghte

d %

of w

omen

table 66. Distribution of levels of hemoglobin concentrations, pregnant women, GNNS 2009

Category of hemoglobin concentrationNo. (weighted %) with hemoglobin

concentration95% CI

Severe anemia (Hb < 7.0 g/dl) 2 (0.7) 0, 2.1

Moderate anemia (Hb 7.0-10.9 g/dl) 50 (7.7) 2.6, 12.9

Mild anemia (Hb 11.0-11.9 g/dl) 112 (17.1) 10.8, 23.6

Normal (Hb 12.0-15.9 g/dl) 448 (74.4) 66.0, 82.8


Table 67. Number (weighted %) and 95% confidence intervals (CI) with any anemia*, pregnant women, GNNS 2009


TOTAL 164 (25.6) 17.2, 34.0

Age (years) 15-24 98 (26.3) 18.2, 34.5 25-34 57 (24.4) 11.0, 37.7 35-44 9 (31.2) 4.8, 57.6 45-49 0

Ethnic group Georgian 60 (24.9) 15.5, 34.3 Armenian 32 (17.4) 7.6, 27.1 Azerbaijani 70 (38.5) 28.9, 48.0 Other 2 (40.0) 0, 85.2

Current pregnancy trimester 1 21 (15.8) 1.3, 30.2 2 71 (24.7) 16.1, 33.3 3 72 (32.3) 18.8, 45.8

* Anemia = Hemoglobin < 11.0 g/dl. No survey subjects required adjustment for smok-ing status, and altitude adjustment could not be done due to lack of data on altitude of residence.


ANNex 1 – SAmpLING metHoDoLoGy

First stage sampling


Cluster sampling of households was done to obtain a random sample of the population of Georgia. The primary sampling unit was census unit. Census units were selected using equal probability from a list of 606 census units already selected probability proportional to size from all census units in Georgia. The State Department of Statistics periodically updates the household lists in these 606 clusters.

In each of the eight regional strata in the GNNS 2009 sample (see description of stratification in section “Details of regional stratification” below) 25 primary sampling units were selected; these 200 clusters were used to achieve independent estimates for each of the eight regional strata. However, to be able to derive independent estimates for the two minority communities of Azerbaijanis and Armenians separate from ethnic Georgians, these minorities had to be overs-ampled. To this end, additional clusters were added in the two regional strata which contain large proportions of these minorities (see section “Supplemental sample size (for ethnic stratification)” below). As a result, the total sample of households were distributed in 236 clusters (see section “Supplemental sample size (for ethnic stratification)” below for explanation of why the number of clusters added to the sample is 36).

The total number of clusters in each regional stratum were distributed into the districts (or rayons) in each regional stratum proportional to the population of each district in that regional stratum. For example, if a district in a given regional stratum has one-fifth of that regional stratum’s popu-lation, five of that regional stratum’s 25 census units will be selected from that district. However, because dividing a regional stratum’s population by a district’s population rarely results in a whole number, and a census unit cannot be divided into fractions, such assignment will not precisely result in a self-weighting sample within a given regional stratum. Therefore, the actual number of households to be selected in a given district will be determined by multiplying the total sample size for that regional stratum by the fraction of that regional stratum’s population which is located in the given district. This number of households will then be apportioned to the number of census units selected in the given district, as described above. As a result, cluster sizes within a regional stratum will be slightly different. For example, let us say that a given regional stratum with 25 clusters should have a total sample size of 2,277 households. One of the four districts in that regional stratum has one-third of the total population of the regional stratum. As a result, the survey sample in that district should have 759 households (1/3 x 2,277 households) distributed in 8 clusters (1/3 x 25 = 8.33 or 8 clusters). The resulting cluster size in that district will be 95 households (759 households / 8 clusters = 94.875 or 95 households). In another district which has one-half of that regional stratum’s population, there will be 13 clusters, each with 88 households (½ x 2,277 households = 1138.5 or 1139 households; ½ x 25 clusters = 12.5 or 13 clusters; 1139 households / 13 clusters = 87.6 or 88 households).

pregnant women

Selection of pregnant women began with a random selection of 25 facilities providing ante-natal care in Georgia; therefore, the primary sampling unit is ante-natal care facility. Ante-natal care facilities were selected with equal probability, not probability proportional to size. Because in each selected facility women will be recruited for the same number of days, and the number of


visits per day varies greatly among facilities, the number of women recruited from each facility (and therefore the number of women in each cluster) will be quite different. However, because the facilities were selected with equal probability, the resulting sample of pregnant women will be equally weighted.

Second stage sampling

Households, children and non-pregnant women

The second stage of sampling selected the required number of households from the household list in each selected census unit. Systematic random sampling was used, starting at a randomly selected starting point. Once households were selected, sampling was complete for children; all eligible children less than 5 years of age who live in selected households were recruited for the survey sample. All eligible non-pregnant women 15-49 years of age who lived in a randomly selected subsample of selected households were also eligible for inclusion in the survey sample. Pregnant women found in selected households were not included in the survey nor were any data collected from them.

Some selected census units did not have a sufficient number of households to select the required number of households for that cluster. In these census units, all households were eligible for child recruitment, and the number of households needed to recruit non-pregnant women and obtain bread and salt specimens were selected from this original census unit. Then an adjacent census unit, not necessarily from the 606 pre-selected census units, was selected. The number of households required to complete the cluster were randomly selected from this adjacent census unit in order to recruit a sufficient number of children into the survey sample. No non-pregnant women were recruited nor any bread or salt specimens obtained from this adjacent census unit.

pregnant women

In each selected ante-natal care facility, consecutive women coming to selected facilities for rou-tine ante-natal care visits were recruited for the GNNS 2009 for a specified number of days. In order to determine how many days such recruitment should occur, the estimated total number of routine ante-natal visits per day in all selected facilities together was determined or calculated from routine service data. The total sample size of pregnant women needed was divided by this total number of visits per day to determine the number of days data must be collected in each facility.

Stratified sampling

Children and non-pregnant women

Because local and national government authorities and other organizations wish to have region-specific estimates for many of the outcomes measured by the GNNS 2009 in children and non-pregnant women, stratified sampling of households was carried out by region. Regions with very small populations were combined to make up a stratum. Strata have quite different populations but similar samples sizes; therefore, because the sampling fraction differs by stratum, a weighted data analysis is required when calculating nationwide estimates for nutritional outcomes. Table A1.1. below shows some basic information on the Georgian population and the 606 pre-selected census units in each stratum.


table A1.1. List of sampling strata and regions contained in each, GNNS 2009

% of total population

Region(s) in stratum total population

Number of pre-selected census units

Number of households in smallest census unit

Armenian Azerbaijani

Tbilisi 1,106,700 150 46 - -

Achara and Guria 519,000 78 58 - -

Imereti andRacha-Leckhumi 742,400 102 42 - -

Kakheti 401,900 54 85 - 9.8%

Kvemo Kartli 503,900 66 47 5.1% 48.0%

Samegrelo 469,600 48 40 - -

Samtckhe-Javakheti 207,700 36 46 62.3% -

Shida Qartli andMtckheta-Mtianeti 430,900 72 74 - -

Total 4,382,100 606

pregnant women

For pregnant women, only ethnicity-specific estimates, not region-specific estimates, were de-sired. As a result, sampling of pregnant women was stratified only by ethnicity. Pregnant women were selected in three strata based on ethnicity: Georgian, Azerbaijani, and Armenian. “Georgian” ethnicity included other smaller minorities, such as Russians, Ukrainians, Greeks, etc. who reside in Georgia. The procedure used to ensure sufficient sample sizes of Azerbaijani and Armenian women is described below in the section “Supplemental sample size (for ethnic strati-fication).”

Basic sample size (for regional stratification)

The required minimum sample size for the basic GNNS 2009 sample was calculated separately for each outcome and target group. All sample size calculations used the following assumptions:

1) The limit of statistical significance (alpha) = 0.05

2) The power (beta) = 0.8

3) The population size from which the sample was selected was assumed to be greater than 10,000; hence, the finite population correction factor was not used


Table A1. 2 below shows the calculated total minimum number of households and individuals from whom data must be collected to achieve the desired precision around the estimate of preva-lence for each target group and for each survey outcome for each regional stratum. Wherever possible, the assumptions used to calculate desired sample size were based on the results of pre-vious surveys. For example, the MICS 2005 survey demonstrated that the prevalence of anemia was 27.7% in non-pregnant women 15-49 years of age.21 In this MICS survey, the design effect for the weighted, nationwide prevalence of underweight in children under 5 years of age was 1.339. Given the average cluster size of 4.3 children in the MICS survey, the intracluster cor-relation co-efficient (ICC or roh) for this variable was 0.103. Because the GNNS 2009 will have a larger overall sample size of young children and women divided into fewer clusters, the average cluster size is larger, thus increasing the design effect somewhat. Given these assumptions, we assumed a design effect of 2.0 for all anthropometric indices in young children.

However, for most variables there are no data available to assist in formulating the assumptions necessary to calculate sample size. For these variables, because of the wide variation in climate, altitude, diet, and culture in Georgia, we have estimated design effects somewhat larger than those seen in other populations. Although stratified sampling tends to decrease design effects, the extent of any such decrease was entirely unknown when the sample sizes were calculated; therefore, this effect was not taken into account. However, when calculating precision from the survey data during data analysis, this stratification benefit was certainly included.

table A1. 2. Number of units of analysis on whom data are needed, for different target groups and outcomes, GNNS 2009

target group and type of malnutrition

Assumed current prev-alence

precision required in each stratum

(percentage points)

Design effect

assumed

Number needed with

data in each

stratum

minimum total

number needed with

data

Households

Iodized salt 90 % ±5 1.8 243 1,944

Iron fortified bread 50 % ±10 2.0 193 1,544

Children 0-59 months

Wasting (z-score <-2.0) 3 % ±3 2.0 249 1,992

Stunting (z-score <-2.0) 12 % ±5 2.0 325 2,600

Overweight (z-score >-2.0) 15 % ±6 2.0 273 2,184

Anemia (< 11.0 g/dl) 35 % ±9 2.5 270 2,160

Iron deficiency 50 % ±10 2.5 241 1,928

Non-pregnant women

Malnutrition (BMI <17.0) 5 % ±5 2.0 146 1,168

Overweight (BMI > 25.0) 50 % ±10 2.0 193 1,544

Anemia 28 % ±8 2.0 243 1,944

Iron deficiency 41 % ±10 2.0 186 1,488

Folate deficiency 50 % ±10 2.0 193 193*


Pregnant women**

Low MUAC 50 % ±10 2.0 193 579

Anemia 50 % ±10 2.0 193 579

* Sample specimens for folate testing were not stratified because only a single nationwide estimate was to be calculated

** Sample sizes for pregnant women are much lower because regional stratification was not done, and ethnic-ity-specific stratified sampling resulted in only three strata.

The outcomes shown in italics are those which required the largest number of individuals in that target group. For households, testing iodized salt requires the largest sample size. For non-preg-nant women 15-49 years of age and pregnant women, the outcome anemia required the largest sample size of individuals. For children less than 5 years of age, anemia did not require the larg-est number of individuals with data; however, because hemoglobin was to be measured only in children 12-59 months of age, a larger number of households had to be selected in order to find the required number of children in this age group. For this reason, anemia was used in the next step of sample size calculation for all target groups.

Households

The survey needed salt testing results from a total of 1,944 households and bread testing results from a total of 1,544 households. As described below, the desired sample sizes for non-pregnant women, salt testing, and bread testing are similar. In order to simplify field procedures, the same subsample of households was used to recruit non-pregnant women and request salt and bread specimens.


Because the sample tested for folate deficiency was not stratified, it required a much smaller sample size than other outcomes. To obtain this much smaller sample size, folate testing was done on only two women in each cluster, resulting in the collection of 472 specimens for testing (see explanation below for the number of clusters). Because bread specimens were collected in households in which non-pregnant women were eligible to be enrolled, many women contribut-ing specimens for folate testing will live in households in which bread was collected for testing, permitting the analysis of the correlation between the household presence of fortified bread and folate levels in non-pregnant women.

Because children and non-pregnant women were selected from a random sample of households, the sample size for these target groups had to be adjusted for two additional factors: 1) house-hold non-response, that is, the proportion of selected households which are entirely unavailable or refuse participation in the survey; and 2) the average number of individuals in each household. Data from Georgian Welfare Monitoring Survey (GWMS 2009) and Household Integrated Survey (HIS 2009) were used to estimate household response rates, individual response rates for non-pregnant women, and number of non-pregnant women in each household. These estimates were made for each stratum separately. These data are given in Table A1.3 and Table A1.4 below.


table A1.4. Household non-response and individual non-response for non-pregnant women, by stratum, Georgian Welfare monitoring Survey, june 2009

Stratum

No residential building at address

No one living at address

total HH non-response

Respondent not at home

Respondent refused to

answer

total individual

non-response

total non-response*

Kakheti 0.5% 1.9% 2.4% 10.4% 1.0% 11.4% 13.8%

Tbilisi 3.2% 2.5% 5.7% 23.0% 16.9% 39.9% 45.6%


2.2% 5.0% 7.2% 11.0% 1.8% 12.8% 20.0%

Kvemo Kartli 3.4% 4.6% 8.0% 3.6% 1.3% 4.9% 12.9%

Samtckhe-Javakheti 3.7% 3.7% 7.4% 5.3% 2.4% 7.7% 15.1%

Achara and Guria 1.6% 3.2% 4.8% 0.5% 0.3% 0.8% 5.6%

Samegrelo 4.5% 3.5% 8.0% 20.5% 0.8% 21.3% 29.3%


1.5% 1.3% 2.8% 4.0% 1.1% 5.1% 7.9%

Total 2.5% 3.0% 5.5% 11.2% 4.6% 15.8% 21.3%

* Total non-response is total household non-response plus total individual non-response because in the Georgian Welfare Monitoring Survey, non-response was categorized as one or the other. Thus, the total non-response is additive.

table A1.4. Average number of women* 15-49 years of age per household, by stratum, House-hold Integrated Survey 2009

Stratum Average number of women 15-49 years per HHKakheti 0.74

Tbilisi 0.99

Shida Qartli and Mtckheta-Mtianeti 0.77

Kvemo Kartli 0.95

Samtckhe-Javakheti 0.85

Achara and Guria 0.97

Samegrelo 0.81

Imereti and Racha-Leckhumi 0.75

Georgia 0.86

* Because fertility is so low in Georgia, the point prevalence of pregnancy is very low. Therefore, we assume that the average number of all women 15-49 years of age approximates the average number of non-pregnant women 15-49 years of age


The non-response rate for children and the average number of children per household used in the adjustment of sample size were derived from the MICS 2005. The MICS found that Georgian households contained, on average, 0.183 children less than 5 years of age. To calculate the number of households to select to obtain the minimum number of hemoglobin measurements on children 12-59 months of age, we assumed that children 12-59 months of age group represented about 80% of all children less than 5 years of age. As a result, households should contain on average 0.146 children 12-59 months of age (80% of 0.183). Because consent for children’s participation usually comes from mothers, the non-response rate for children is often similar to that of their mothers. However, mothers may be less willing to consent to a fingerstick for their young children. Also, when collecting blood from a fingerstick, an additional source of non-response results from the failure to obtain enough blood for testing. Therefore, the non-response rate of women was increased by five percentage points to estimate the non-response rate for young children.

Table A1.5 and Table A1.6 below show the number of households to select per stratum and in the total GNNS 2009 survey sample to obtain the minimum number for hemoglobin measurements in non-pregnant women 15-49 years of age and children 12-59 months of age. To calculate this number of households in each stratum, the required number of hemoglobin measurements (column 2 in the tables below) was divided by the household response rate plus the individual response rate (response rate is the complement of the non-response rate, or 100 – (column 3 plus column 4) in the tables below). This result was then divided by the average number of individuals per household (column 5 in the tables below) to obtain the number of households which must be randomly selected.

table A1.5. Number of households to select to get the minimum number of hemoglobin mea-surements in children 12-59 months of age, GNNS 2009

1 2 3 4 5 6

Stratum minimum number of hemoglobin measurements in children

House-hold non-response rate

Individual non-response rate

Average number of children 12-59 months per household*

Number households to select in one stratum

Kakheti 270 2.4% 16.4% 0.146 2,277

Tbilisi 270 5.7% 44.9% 0.146 3,744


270 7.2% 17.8% 0.146 2,466

Kvemo Kartli 270 8.0% 9.9% 0.146 2,253

Samtckhe-Javakheti 270 7.4% 12.7% 0.146 2,315

Achara and Guria 270 4.8% 5.8% 0.146 2,069

Samegrelo 270 8.0% 26.3% 0.146 2,815


270 2.8% 10.1% 0.146 2,123

total in all strata 2160 20062

* Based on the 2005 UNICEF MICS


table A1.6. Number of households to select to get minimum number of hemoglobin measure-ments in non-pregnant women, GNNS 2009

1 2 3 4 5 6

Stratum minimum number of hemoglobin measurements in women

House-hold non-response rate*

Individual non-response rate*

Average number of women 15-49 years per household*

Number households to select in one stratum

Kakheti 243 2.4% 11.4% 0.74 381

Tbilisi 243 5.7% 39.9% 0.99 451


243 7.2% 12.8% 0.77 394

Kvemo Kartli 243 8.0% 4.9% 0.95 294

Samtckhe-Javakheti 243 7.4% 7.7% 0.85 337

Achara and Guria 243 4.8% 0.8% 0.97 265

Samegrelo 243 8.0% 21.3% 0.81 424


243 2.8% 5.1% 0.75 352

total in all strata 1944 2898

* Based on the Georgian Welfare Monitoring Survey (GWMS 2009) and Household Integrated Survey (HIS 2009)

Therefore, to collect hemoglobin data on 2,160 children 12-59 months of age, survey teams had to recruit children from 20,060 households for the basic sample. To collect hemoglobin data on 1,944 non-pregnant women, women had to be recruited from 2,899 households for the basic sample. Therefore, it was necessary to select women from only a subsample of the total sample of 20,062 households. Because response rates and the average number of women are different for each stratum, the fraction of households from which to recruit women varied by stratum (see below).

Supplemental sample size (for ethnic stratification)

In order to obtain estimates for the two ethnic minorities of Azerbaijanis and Armenians, the number of households in these minorities from whom data are collected must be the same as the number calculated for each stratum. Therefore, the sample size and sampling scheme must be further adjusted by selecting a supplemental sample of minority households and pregnant women.


An alternative sampling strategy was used in those two regional strata with substantial popula-tions of ethnic minorities, as shown in Table A1.1 above. In order to ensure an adequate sample size for these two minorities, the total sample sizes in these two strata were increased by se-lecting a supplemental sample of census units. The population of Kvemo Kartli is approximately 50% Azerbaijani. To be sure that the household sample in Kvemo Kartli contained at least the


2,253 Azerbaijani households necessary to make independent estimates for Azerbaijani children and women, the total sample size for this stratum was doubled by selecting 50 clusters in this stratum. As with the basic sample, 84 households were selected in each of the additional 25 clusters.

The population of Samtchke-Javakheti is 62.3% Armenian. To ensure an adequate sample of Armenian households, the sample size in Samtckhe-Javakheti was increased by 1401 households to ensure selection of at least 2,315 Armenian households. However, Samtckhe-Javakheti has only 36 pre-selected clusters, too few to add 1401 households and maintain the same cluster size. As a result, all 36 of these clusters were selected during the first stage of sampling, and the cluster size was increased to ensure the needed sample size. The final household sample sizes and the proportion of households in which all non-pregnant women 15-49 years of age were to be recruited is shown in Table A1.7 below.


tab

le A

1.7

. Fi

nal sa

mpl

e si

ze (

incl

udin

g ba

sic

sam

ple

plus

sup

plem

enta

l sa

mpl

e) f

or c

hild

ren

and

non-

preg

nant

wom

en a

nd d

istr

ibut

ion

of

clus

ters

, G

NN

S 2

009.

Str

atum

Num

ber

of

hous

ehol

ds t

o se

lect

for

chi

ldre

n(B

asic

* +

su

pple

men

tal)

Num

ber

of

hous

ehol

ds

to s

elec

t fo

r w

omen

(B

asic

** +

su

pple

men

tal)

Num

ber

of

clus

ters

(B

asic

+

supp

lem

enta

l)

Frac

tion

of

hous

ehol

ds

from

whi

ch t

o re

crui

t w

omen

Num

ber

of

hous

ehol

ds t

o se

lect

for

eac

h cl

uste

r

Num

ber

of

child

ren

with

fin

gers

tick

Num

ber

of

wom

en w

ith

finge

rstic

k or

ve

nipu

nctu

re

Kak

heti

2,2

77

381

25

1/6

91

243

270

Tbi

lisi

3,7

44

451

25

1/8

75

243

270

Shi

da K

artli

an

d M

tckh

eta-

Mtia

neti

2,4

66

394

25

1/6

99

243

270

Kve

mo

Kar

tli2,2

53 +

2,2

53

294 +

294

25 +

25 =

50

1/8

90

486

540

Sam

tckh

e-Ja

vakh

eti

2,3

15 +

1,4

01

337 +

204

25 +

11 =

36

1/7

103

390

433

Ach

ara

and

Gur

ia2,0

69

265

25

1/8

83

243

270

Sam

egre

lo2,8

15

424

25

1/7

113

243

270

Imer

eti a

nd

Rac

ha-L

eckh

umi

2,1

23

352

25

1/6

85

243

270

tot

al23,7

16

3,3

96

236

2334

2593

*

From

Tab

le A

1.5

abo

ve**

From

Tab

le A

1.6

abo

ve


pregnant women

The sample size for pregnant women, as shown in Table 13 above, is 193 for each of the three ethnic strata. Each of these women underwent anthropometric measurements, a fingerstick blood specimen for hemoglobin measurement, and collection of a urine specimen for iodine test-ing. Assuming 90% response, the total number of pregnant women to be selected in ante-natal facilities was at least 215 (193 divided by 0.9) in each ethnic group for a total sample size of 645.

The number of ante-natal visits per day by Georgian pregnant women was calculated by adding together the number of visits per day for ante-natal care facilities in those regions which do not have substantial minority populations. Then, for each of the two regional strata which have a large minority population, the number of visits by Georgian women was calculated by multiplying the total number of visits in each region by the proportion of the population in that region which is of Georgian ethnicity. These numbers of daily visits were then added to the total number of visits in regions which do not have substantial minority populations to derive the total number of daily visits in all of Georgia by Georgian pregnant women. As a result, it was calculated that to achieve 193 hemoglobin measurements in pregnant women, Georgian women were recruited for one day in the sample of 25 ante-natal care facilities.

In addition to these 25 facilities, all remaining facilities in Samtckhe-Javakheti and Kvemo Kartli were included in the sample. In those facilities not included in the random sample of 25 facili-ties, Georgian women will not be recruited. The number of days of data collection for Azerbaijani and Armenian women in the original sample of facilities and in the additional facilities will differ depending on the location of the facilities. For the minority regions, using the data contained in Table A1.1, the average number of visits per day for Armenian women was calculated by multiplying the number of visits per day in Samtckhe-Javakheti by 0.623, the proportion of the region’s population which is Armenian. The average number of visits per day for Azerbaijani women was calculated by multiplying the number of visits per day in Kvemo Kartli by 0.48, the proportion of the population which is Azerbaijani. For simplicity’s sake, the 5.1% of Kvemo Kar-tli’s population which is Armenian is not included in these calculations. The final number of days of data collection for each minority ethnicity is shown below in Table A1.8.

table A1.8. Number of days of data collection in ante-natal clinics, by ethnicity, GNNS 2009.

ethnicity Average number of visits per day

Number of pregnant women needed

Number of days of data collection

Georgian 610 215 0.35(round to 1)

Azerbaijani 35.2 215 6

Armenian 20.5 215 11

Although for Georgian women, data collection need only be done for one-third of a day, it was difficult for survey teams to determine a standard method of measuring a data collection period of less than 1 day. As a result, in those facilities in the original sample of 25 facilities which provide care to more than one ethnicity, Georgian women were recruited for only 1 day, after which they will no longer be eligible for recruitment. However, in these facilities and in all other facilities in the region, Azerbaijani women were recruited for another 6 days and Armenian women were re-cruited for another 11 days after this first day of data collection in all facilities in their respective regional strata.


ANNex 2 – DAtA CoLLeCtIoN FoRmS

GEORGIA NATIONAL NUTRITION SURVEY 2009

HOUSEHOLD QUESTIONNAIRE

1. Data entry clerk ................................ 2. Household Questionnaire ID ......

3. District: ______________________________ 4. Village/Place__________________________________

5. Region Tbilisi ................................................1 Achara and Guria..............................................2 Imereti and Racha-Leckhumi ..........................3 Kakheti 4 Kvemo Kartli ...................................................5 Samegrelo ........................................................6 Samtckhe-Javakheti .........................................7 Shida Qartli and Mtckheta-Mtianeti ................8

6. Urban .......................................................................... 1 Rural ........................................................................... 2

7. Cluster number ......................... 8. Cluster control form household number .

9. Team number .................................. 10. Interviewer number .......................................

11. Name of head of household _____________________________________

12. Date of interview.......... / / raeY htnoM yaD

13. Interviewer/supervisor notes: Use this space to record notes about the interview with this household, such as call-back times, incomplete individual interview forms, number of attempts to re-visit, etc

WE ARE FROM THE NATIONAL CENTER FOR DISEASE CONTROL AND PUBLIC HEALTH (MOLHSA)AND UNICEF. WE ARE WORKING ON A PROJECT CONCERNED WITH NUTRITION AND HEALTH. IWOULD LIKE TO TALK TO YOU ABOUT THIS. THE INTERVIEW WILL TAKE ABOUT 20-30 MINUTES. ALLTHE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND YOUR ANSWERS WILL NEVER BE IDENTIFIED. AFTER THESE QUESTIONS TO YOU, I WILL SPEAK WITH SOME OF THE WOMEN IN YOUR HOUSEHOLD AND THE WOMEN WHO TAKE CARE OF THE CHILDREN 0-59 MONTHS.

14. Time data collection began ........................................................................................ :

FIRST, I WOULD LIKE TO ASK YOU SOME GENERAL QUESTIONS ABOUT THE PEOPLE WHO LIVE IN THIS HOUSEHOLD.

15. How many years have you lived in this house or apartment? ......................Unk = 99

16. How many people usually live in this household? .........................................Unk = 99

17. How many women between the ages 15 and 49 years old usually ................ live in this household?

-> If 0, go Q19


18. For each of these women, please tell me her first name and age List women in order from the oldest to the youngest

No. First and family name Age (in years) Result *

010203040506

* Result Codes: 1 = completed; 2 = partly completed; 3 = refused; 4 = incompetent; 5 = revisit

19. How many children less than 5 years of age usually live in this household? -> If 0, skip to Q21

20. For each of these children, please tell me the first name and age. No. First and family name Age

(in months) Result *

111213141516

* Result Codes: 1 = completed; 2 = partly completed; 3 = refused; 4 = incompetent; 5 = revisit

21. What is the ethnicity of the head of the household? Georgian ................................ 1 Circle only one. 2.................................nainemrA

3....................................... irezA 8........................................rehtO

_______________ )yficepS( 9.................................nwonknU

22. What language does your family speak most often Georgian.................................. 1 at home? 2.................................nainemrA

Circle only one. 3....................................... irezA 4....................................naissuR 8....................................... rehtO

_______________ )yficepS( 9................................ nwonknU

23. Are any of household members employed or earning income? Yes ......................... 1 2 ......................... oN

-> Next Q -> Skip to Q25

24. How many household members are employed or earning income? ..............

IF THE HOUSEHOLD IS NOT SELECTED FOR BREAD AND SALT SELECTION, SKIP TO Q 48.IF IT IS SELECTED, CONTINUE.


NOW I WOULD LIKE TO ASK YOU SOME QUESTIONS ABOUT THE SALT MOST COMMONLY USED IN THIS HOUSEHOLD.

25. How do you usually store salt in the house? Original plastic container............... 1 Circle only one. 2 .... )nepo( reniatnoc ssalg lanigirO

3 . )desolc( reniatnoc ssalg lanigirO 4 ............ reniatnoc nedoow ro yalC 5 ........................... reniatnoc citsalP 6 ............................. xob draobdraC 8............................................. rehtO

____________________ )yficepS( 9 ...................................... nwonknU

26. Where do you usually keep the salt container? In a closed cabinet ....................... 1 Circle all applicable answers. On an open shelf .......................... 2

On the counter near the stove ...... 3 By the window ............................. 4 Other ............................................ 8 (Specify) ____________________ Unknown ...................................... 9

27. Do you have salt in your house now? 1 ........................ seY 2...........................oN

9 .............. nwonknU


28. Is it iodized? Yes ........................ 1 oN ......................... 2

nwonknU .............. 9

29. May I have a small sample of the salt? Yes ........................ 1 oN ......................... 2

-> Collect salt

NOW I WOULD LIKE TO ASK YOU SOME QUESTIONS ABOUT THE BREAD EATEN IN THIS HOUSEHOLD.

30. On average, how many kilograms of bread does your family eat per day? . If unknown, enter 9.9

31. What type of bread do you eat most often in this household? Lavash ......................... 1

Circle only one. 2 ..... daerb etihw yrotcaF 3 yrotcaf morf daerb rehtO 4 .................. edam emoH 8 ............................ rehtO ____________ )yficepS(

nwonknU ..................... 9

32. Where do you most often purchase this bread? From the supermarket or shop ..... 1 Circle only one. 2 ........................... yrekab eht morF

3.......... emoh ta daerb ekab yllausU 8............................................. rehtO

__________________ )yficeps( 9....................................... nwonknU Skip to Q34

-> Next Q -> Skip to Q34-> Skip to Q34-> Skip to Q34

->


33. What is the brand name of the supermarket bread you buy? Ipkli ...................... 1 akiD ...................... 2

Ask to see package if respondent does not know Margi .................... 3 aboenhkM ............. 4

5 ..... eman dnarb oN rehtO ..................... 8

(Specify) ________ nwonknU .............. 9

34. When you bake bread at home, White flour first quality ...................... 1 what type of flour do you use? Whole wheat ....................................... 2 Circle only one. 3 .............. taehw elohw dna etihw htoB

4 ....... emoh ta daerb ekab ton od ,enoN 8 ................................................... rehtO

_____________________ )yficeps( 9............................................. nwonknU

35. Do you have a sample of the bread you most commonly Yes ........................ 1 eat in the household now? 2 ......................... oN

Ask to see package of bread. Unknown .............. 9

-> Next Q -> Skip to Q40 -> Skip to Q40

36. Is the bread labeled as fortified? Yes ........................ 1 oN ......................... 2

Unknown (original packaging not available) .. 9

37. May I take a sample of this bread to test in the laboratory? Yes ........................ 1 oN ......................... 2

-> Next Q-> Skip to Q40

38. Type of bread from which specimen taken? Lavash ............................. 1 Circle only one. 2 ......... daerb etihw yrotcaF

Other bread from factory . 3 emoH made ..................... 4 rehtO ............................... 8

(specify) ____________ nwonknU ......................... 9

39. Where did you get this bread? From the supermarket or shop .. 1 Circle only one. From the bakery ........................ 2

Baked at home .......................... 3 nwonknU .................................. 9

All answersSkip to Q45

40. Do you have any other type of bread in the house now? Yes ........................ 1 2 ......................... oN

9 .............. nwonknU


41. Is the bread labeled as fortified? Yes ........................ 1 oN ......................... 2

Unknown (original packaging not available) .. 3

42. May I take a sample of this bread to test in the laboratory? Yes ........................ 1 oN ......................... 2

Next Q Skip to Q45


43. Type of bread from which specimen taken? Lavash ......................... 1 Circle only one. 2 ..... daerb etihw yrotcaF

Other bread from factory 3 emoH made .................. 4 rehtO ............................ 8

(Specify) ____________ nwonknU ..................... 9

44. Where did you get this bread? From the supermarket or shop .. 1 Circle only one. 2 ........................ yrekab eht morF

Baked at home .......................... 3 nwonknU ............................... 9

45. Number of interviews completed in the household: Children ...................

nemoW ....................

46. Salt specimen collected? Yes ........................ 1 2 ......................... oN

47. Bread specimen collected? Most commonly eaten ........... 1 Not most commonly eaten....... 2 No bread specimen collected... 3

48. Time data collection completed: ...................................................... : Hour Minutes

49. Other comments about data collection at this household:

The form was reviewed by: _______________________________________ Date: ________________ Supervisor’s signature



CHILDREN’S QUESTIONNAIRE (HH SAMPLE)

1. Data entry clerk: ..................................... 2. Household Questionnaire ID ......

3. Cluster number: ............................... 4. Cluster form household number ........

5. Team number: ............................................... 6. Interviewer number: ..................................

7. Child number (from HH form) ................ 8. Date of interview: / / Day Month Year


1

WE ARE FROM THE NATIONAL CENTER FOR DISEASE CONTROL AND PUBLIC HEALTH (MOLHSA)AND UNICEF. WE ARE WORKING ON A PROJECT CONCERNED WITH NUTRITION AND HEALTH. IWOULD LIKE TO TALK TO YOU ABOUT THIS. THE INTERVIEW WILL TAKE ABOUT 10 MINUTES. ALLTHE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND YOUR ANSWERS WILL NEVER BE IDENTIFIED. AFTER THESE QUESTIONS TO YOU, I WILL SPEAK WITH SOME OF THE WOMEN IN YOUR HOUSEHOLD AND THE WOMEN WHO TAKE CARE OF THE CHILDREN 0-59 MONTHS.

10. Time interview begun :FIRST, I WOULD LIKE TO ASK YOU SOME GENERAL QUESTIONS ABOUT YOUR CHILD.

11. What is your child’s name and family name? ......... ___________________________

12. What is [name]’s birthdate? ................ ........................ / / Day Month Year .

Unk=99/99/99

13. What is [name]’s age in completed months? ..................................................Unk = 99

14. What is [name]’s sex? 1 ....................................... elaM 2 ................................... elameF

15. What is [name]’s ethnicity? Georgian ................................ 1 Circle only one. 2.................................nainemrA

3....................................... irezA 8........................................rehtO

_______________ )yficepS( 9.................................nwonknU


NOW WE WOULD LIKE TO ASK SOME QUESTIONS ABOUT [NAME]’S HEALTH AND DIET.16. Does [name] have any chronic diseases or conditions, Yes .................. 1 such as asthma, anemia, heart diseases, rickets, etc.)? No ................... 2

8 ........ nwonknU 9 ............. esufeR

-> Next Q -> Skip to Q18 -> Skip to Q18 -> Skip to Q18

17. Does [name] take any medicines for this disease or condition? Yes .................. 1No ................... 2

8 ........ nwonknU 9 ............. esufeR

18. Has [name] had any fever in the past 14 days? Yes .................. 1No ................... 2

8 ........ nwonknU 9 ............. esufeR

19. Has [name] had any cough in the past 14 days? Yes .................. 1No ................... 2

8 ........ nwonknU 9 ............. esufeR

20. Has [name] had any diarrhea in the past 14 days? Yes .................. 1No ................... 2

nwonknU ........ 8 esufeR ............. 9

21. At birth, how much did [name] weigh? Record answer in grams ... Unknown=8888 Refused=9999

22. Was [name] ever breastfed? 1................... seY 2 ................... oN 8 ........ nwonknU 9 ........... desufeR


23. How soon after birth was did his/her In first the first hour ................................... 1 mother start to breastfeed [name]? After the first hour but within 12 hours .... 2 Ask for specific response, then mark More than 12 hours after birth ................... 3

mark appropriate answer. Unknown ................................................... 8 9 ....................................................... esufeR

24. Now I will ask you questions about what [name] ate yesterday. Yes ................... 1 Did [name] take any breastmilk yesterday? No ................... 2

8 ........ nwonknU 9 ........... desufeR

25. Yesterday, did [name] eat anything other than breastmilk? Yes ................... 1 This includes water, baby formula, juice, or any solid foods No ................... 2 as well as regular food. nwonknU ........ 8

Refused ........... 9

26. Yesterday, did [name] eat any solid, semi-solid, or soft foods? Yes ................... 1 2 ................... oN 8 ........ nwonknU

9 ........... desufeR


27. Yesterday, how many times did [name] eat solid, semi-solid, ...................... mushy foods or any animal milk or baby formula?

Unknown = 88 Refusal = 99

28. Please tell me if [name] ate any of the following foods yesterday. Be sure to think about all meals and any snacks [name] ate. Read each item and let respondent answer, then circle the appropriate answer.

Yes No UnknownBaby formula 1 2 8 Bread, porridge, or other grains 1 2 8 Beans or nuts 1 2 8 Milk, cheese, yogurt, cottage cheese 1 2 8 Meat, fish, or chicken 1 2 8 Eggs 1 2 8 Vitamin A rich fruits or vegetables (carrots, pumpkins, tomatoes, spinach) 1 2 8

Other fruits or vegetables 1 2 8 Food made with vegetable oil, butter, or other oil 1 2 8 Sweet tea 1 2 8

29. Now think about a period of one week. Remember, a week is 7 days, for example, Monday through Sunday. How frequently on average does [name] usually eat each of the following foods per week? Read each item and let respondent answer, then circle the appropriate answer.

Never <1 day a week

1-2days a week

3-4 days a week

5-7days a week

Unk-nown Refused

Baby formula 1 2 3 4 5 8 9 Bread, porridge, or other grains 1 2 3 4 5 8 9 Beans or nuts 1 2 3 4 5 8 9 Milk, cheese, yogurt, cottage cheese 1 2 3 4 5 8 9 Meat, fish, or chicken 1 2 3 4 5 8 9 Eggs 1 2 3 4 5 8 9 Vitamin A rich fruits or vegetables (carrots, pumpkins, tomatoes, spinach)

1 2 3 4 5 8 9

Other fruits or vegetables 1 2 3 4 5 8 9 Food made with vegetable oil, butter, or other oil 1 2 3 4 5 8 9

Sweet tea 1 2 3 4 5 8 9

NOW WE WOULD LIKE TO MEASURE [NAME]’S HEIGHT AND WEIGHT.

30. Weight (in kilograms) .............................................................................. .31. Child weighed Alone .................. 1

With mother ....... 2

32. Child weighed wearing Underwear or no clothes ... 1 Light clothes ...................... 2 Heavy clothes .................... 3

33. Height (in cm) ................................................................................... .


34. MUAC (in cm) .......................................................................................... .35. Edema, bilateral in feet or lower legs Yes .................. 1

oN ................... 2

36. Reason for no weight, height, or MUAC Disabled, cannot stand on scale ....... 1 2 ..... thgieh erusaem tonnac ,delbasiD tnemerusaem

Circle all applicable answers. Uncooperative or uncontrolable ....... 3 rehtO ................................................ 8

(Specify) ____________________ desufeR ............................................ 9

IMPORTANT: Check the child’s age. If child’s age is less than 12 full months, that is, if the child has not yet reached his/her first birthday, do NOT collect blood. End interview and skip to Q 41 interviewers comments.

NOW WE WOULD LIKE TO TAKE SOME BLOOD FROM [NAME]’S FINGER FOR TESTING FOR VITAMIN LEVELS.IS THIS OK?

37. Consent granted for fingerstick Yes ......................... 1 2 ......................... oN


38. Hemoglobin concentration (g / dl) .......................................................... .39. Approximate volume of blood collected in microtainer (ml) ............................ . 0

40. Time data collection completed ....................................................... :Hour Minutes

41. Comments about data collection at this household:




WOMAN’S QUESTIONNAIRE (HH SAMPLE)

1. Data entry clerk .................................. 2. Household Questionnaire ID

3. Cluster number ............................ 4. Cluster control form household number

5. Team number ..................................... 6 Interviewer number ............................................

7. Woman number (from HH form) ......... 8. Date of interview ....... / / Day Month Year .


0

WE ARE FROM THE NATIONAL CENTER FOR DISEASE CONTROL AND PUBLIC HEALTH (MOLHSA)AND UNICEF. WE ARE WORKING ON A PROJECT CONCERNED WITH NUTRITION AND HEALTH. IWOULD LIKE TO TALK TO YOU ABOUT THIS. THE INTERVIEW WILL TAKE ABOUT 10 MINUTES. ALLTHE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND YOUR ANSWERS WILL NEVER BE IDENTIFIED. AFTER THESE QUESTIONS TO YOU, I WILL SPEAK WITH SOME OF THE WOMEN IN YOUR HOUSEHOLD AND THE WOMEN WHO TAKE CARE OF THE CHILDREN 0-59 MONTHS.

10. Time interview begun:.................................................................................... :

FIRST, I WOULD LIKE TO ASK YOU SOME GENERAL QUESTIONS ABOUT YOURSELF.

11. Are you currently pregnant? Yes ......................... 1 oN ......................... 2

If YES, thank woman and END THE INTERVIEW;If NO, continue

12. What is your date of birth? ................. ........................ / / Day Month Year

Unk=99/99/99

13. What is your age in completed years? ............................................................Unk = 99

14. What is your ethnicity? Georgian ................................ 1 Circle only one. 2.................................nainemrA

3....................................... irezA 8........................................rehtO

_______________ )yficepS( 9.................................nwonknU


15. What is your religion? Orthodox ............................... 1 Circle only one. 2 .................................. milsuM

3 .............. nairogerG nainemrA 4 ..................... cilohtaC namoR 5 ............................ noigiler oN 8 ...................................... rehtO

_______________ )yficepS( 9 .................................. desufeR

16. What is your marital status? 1 .... rentrap htiw sevil/deirraM Circle only one. Widowed .............................. 2

3 ............................... decroviD 4 .............................. detarapeS 5 ....................... deirram reveN 8 .............................. nwonknU

9 ................................. desufeR

17. How many years of school did you complete? ...............................................

18. In the past 3 months, including today, have you taken Yes ......................... 1 food supplements or vitamins? 2 ......................... oN


19. What kind of supplements or vitamins? Iron .......................................... 1 Circle all applicable answers. Vitamin C ............................... 2

8........................................rehtO (Specify) _______________

nwonknU ................................ 9

20. How many times have you been pregnant? .................................................... If 0, skip to Q24

21. How many of these pregnancies resulted in a live birth? .............................

22. Are you currently breastfeeding? 1......................... seY No ......................... 2

9 ................. desufeR


23. How many months old is the child you are breastfeeding? ..........................

24. When did you start your last menstrual period? ...... / / Day Month Year .

If not applicable, 99/99/99

25. Do you smoke cigarettes? Yes ......................... 1 2 ......................... oN 8 .............. nwonknU

9 ................. desufeR

-> Next Q ->Skip to Q27 ->Skip to Q27 ->Skip to Q27

26. How many cigarettes per day, on average, do you smoke? ...........................

27. Do you usually add salt to your food just before eating it? Yes ......................... 1 2 ......................... oN 8 .............. nwonknU

9 ................. desufeR


28. Do you usually add the salt without first tasting the food? Yes ......................... 1 oN ......................... 2

nwonknU .............. 8 desufeR ................. 9

NOW WE WOULD LIKE TO MEASURE YOUR HEIGHT AND WEIGHT.

29. Weight (in kilograms) ....................................................................... .

30. Height (in cm) ................................................................................... .31. Reason for no height or weight measurement : Disabled, cannot stand on scale ....... 1

Circle all applicable answers. Disabled, cannot measure height ..... 2 8 ................................................ rehtO

____________________ )yficepS( 9 ............................................ desufeR

NOW I WOULD LIKE TO TAKE SOME BLOOD FROM YOUR FINGER / VEIN FOR TESTING.

32. If woman eligible for folate testing, was venipuncture Yes ......................... 1 2 ......................... oN ?deniatbo doolb


32a. Volume of blood in vacutainer (ml) .................. .33. Is blood obtained by fingerstick? Yes ......................... 1

oN ......................... 2-> Next Q -> Skip to Q35

33a. Hemoglobin concentration (in g / dl) ...................................................... .34. If fingerstick done, approximate volume of blood collected in microtainer (ml) . 0






PREGNANT WOMAN’S QUESTIONNAIRE (ANC SAMPLE)

Pregnant Woman Questionnaire ID

1. Data entry clerk ..................................... 2. District: _________________________________

3. Region Tbilisi ......................................................... 1 Achara and Guria ........................................................... 2 Imereti and Racha-Leckhumi ........................................ 3 Kakheti 4 Kvemo Kartli ................................................................ 5 Samegrelo 6 Samtckhe-Javakheti ...................................................... 7 Shida Qartli and Mtckheta-Mtianeti .............................. 8

4. ANC clinic name ___________________________

5. ANC clinic number: .............................. 6. Team number: .......................................

7. Name of woman ____________________________ 8. Date of interview: / / Day Month Year


WE ARE FROM THE NATIONAL CENTER FOR DISEASE CONTROL AND PUBLIC HEALTH (MOLHSA) AND UNICEF.WE ARE WORKING ON A PROJECT CONCERNED WITH NUTRITION AND HEALTH. I WOULD LIKE TO TALK TO YOU ABOUT THIS. THE INTERVIEW WILL TAKE ABOUT 10 MINUTES. ALL THE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND YOUR ANSWERS WILL NEVER BE IDENTIFIED. AFTER THESE QUESTIONS TO YOU, IWILL SPEAK WITH SOME OF THE WOMEN IN YOUR HOUSEHOLD AND THE WOMEN WHO TAKE CARE OF THE CHILDREN 0-59 MONTHS.

10. Time interview begun: :FIRST, I WOULD LIKE TO ASK YOU SOME GENERAL QUESTIONS ABOUT YOURSELF.

11. Are you currently pregnant? Yes ......................... 1

oN ......................... 2

If NO, thank woman and ENDINTERVIEW;If YES, continue

12. What is your date of birth? ................. ........................ / / Day Month Year .

Unk=99/99/99

13. What is your age in completed years? ............................................................Unk = 99

14. What is your ethnicity? Georgian ................................ 1 Circle only one. 2.................................nainemrA

3....................................... irezA 8........................................rehtO

_______________ )yficepS( 9.................................nwonknU


15. What is your religion? Orthodox ............................... 1 Circle only one. 2 .................................. milsuM

3 .............. nairogerG nainemrA 4 ..................... cilohtaC namoR 5 ............................ noigiler oN 8 ...................................... rehtO

_______________ )yficepS( 9 .................................. desufeR

16. What is your marital status? 1 .... rentrap htiw sevil/deirraM Circle only one. Widowed .............................. 2

3 ............................... decroviD 4 .............................. detarapeS 5 ....................... deirram reveN 8 .............................. nwonknU

9 ................................. desufeR

17. How many years of school did you complete? ...............................................

18. During this pregnancy, have you taken food supplements Yes ......................... 1 or vitamins? 2 ......................... oN


19. If yes, what kind? 1..........................................norI Circle all applicable answers. Vitamin C ............................... 2

3 ....................... snimativ-itluM 8........................................rehtO

_______________ )yficepS( 9................................ nwonknU

20. How many months have you been pregnant? ....................................................... Unknown=99

21. When did you start your last menstrual period? ...... / / Day Month Year .

Unknown enter 99/99/99

22. How many times have you been pregnant before this pregnancy? ............... If 0, skip to Q24

23. How many of these pregnancies resulted in a live birth? .............................

24. Do you smoke cigarettes now? Yes ......................... 1 2 ......................... oN 8 .............. nwonknU

9 ................. desufeR


25. How many cigarettes per day, on average? .....................................................

26. Do you usually add salt to your food just before eating it? Yes ......................... 1 2 ......................... oN 8 .............. nwonknU

9 ................. desufeR

27. Do you usually add the salt without first tasting the food? Yes ......................... 1 2 ......................... oN 8 .............. nwonknU

9 ................. desufeR


NOW WE WOULD LIKE TO MEASURE YOUR ARM.

28. MUAC (in cm) ......................................................................................... .29. Reason for no MUAC measurement Disabled, cannot measureMUAC .... 1

Circle all applicable answers. Other ................................................ 8 ____________________ )yficepS(

9 ............................................ desufeR

NOW I WOULD LIKE TO TAKE SOME BLOOD FROM YOUR FINGER FOR TESTING FOR HEMOGLOBIN LEVELS. WE WOULD ALSO LIKE TO COLLECT SOME URINE FROM YOU. IS THIS OK?

30. Blood obtained from fingerstick Yes ......................... 1 2 ......................... oN

31. Hemoglobin concentration (in g/dl) ........................................................ .32. Urine specimen collected Yes ......................... 1

2 ......................... oN



The form was reviewed by: ________________________________________ Date: ____________ Supervisor’s signature


ANNex 3 – QuALIty ASSuRANCe DuRING AND AFteR DAtA CoLLeCtIoN

During data collection at each selected household, survey team leaders supervised all steps of data collection, including the interview, physical examination, anthropometric measurement, and biologic specimen collection. Upon completion of data collection at each household, the survey team leader reviewed the entire data collection form to ensure completeness and accuracy. As mentioned above, the two datasets resulting from duplicate data entry were exhaustively com-pared to ensure accurate data entry. Specific measures for the various types of data collected in the GNNS 2009 are listed below.

Interview

Survey interviewers may influence the answers given by survey participants. To reduce this bias, interview questions were carefully written and pretested on individuals from a population similar to that in the survey sample. Careful review of translations ensured that questions collected the data they are meant to collect. Survey interviewers were carefully trained and supervised to en-sure that they read questions verbatim from the data collection form. In addition, most questions were relatively simple and not require extensive interpretation by respondents.

Anthropometric measurements

As mentioned above, complete training was provided in measurement technique and included a standardization exercise. The height boards, scales, and tapes used for measurement were care-fully constructed and calibrated periodically throughout the data collection period. As mentioned above, during data analysis, outlying anthropometric indices were excluded from analysis accord-ing to the criteria recommended by WHO.18 Additional analysis was done to judge the validity of anthropometric measurements, including an analysis for digit preference in height measurements, calculation of the standard deviations of all z-scores, and analysis of the age distribution of chil-dren less than 5 years of age by one-month intervals.

Physical examination

Training for survey workers who examined survey participants used photographs of edema; no example of actual edema were available to demonstrate to survey workers. Team supervisors confirmed all positive findings during data collection.

Biologic specimen collection

Training for survey workers covered all aspects of specimen collection and any laboratory testing to be done in the field. For example, training included all the aspects of obtaining fingerstick blood and operating and calibrating the HumaMeter® hemoglobinometer. Biologic specimens were processed, stored, and transported according to instructions from the laboratory which did the testing.


Laboratory measurements

Ferritin and CRp

The validity of the ferritin and CRP laboratory results from the NCDCPH Imereti Zonal Branch Diagnostic Laboratory has been confirmed by blinded duplicate testing by Human GmbH in Wies-baden, Germany. Table 68 and Table 69 below shows the agreement between the two labora-tories for the 400 serum specimens from young children and non-pregnant women which were tested in both laboratories.

table 68. Comparison of CRp testing results from Georgian laboratory and German laboratory, GNNS 2009

German laboratory results

Georgian laboratory result Elevated* Normal

Elevated* 56 3

Normal 2 339

* Elevated = CPR > 5.0 mg/lKappa statistic for agreement = 0.95(strength of agreement is almost perfect)

table 69. Comparison of ferritin testing results from Georgian laboratory and German labora-tory, GNNS 2009

German laboratory results

Georgian laboratory result Low* Normal

Low* 10 1

Normal 5 384

* Low = For children < 5 years of age ferritin < 12.0 µg/L; for adult women ferritin < 15.0 µg/LKappa statistic for agreement = 0.76 (strength of agreement is substantial)

Salt iodine

A subsample of 30 salt specimens obtained from households during data collection for the GNNS 2009 were re-tested in a salt iodine reference laboratory in Ukraine. Figure 15 below shows the correlation between the results obtained by the Georgian and Ukrainian laboratories. The correla-tion coefficient is quite high and the Y-axis intercept of the linear correlation line is very near 0, demonstrating that the results are very similar.


Figure 15. Scatterplot showing correlation between Georgian and ukrainian laboratories’ results in testing household salt, GNNS 2009

y = 1.0237x + 1.3805R2 = 0.9297

0

10

20

30

40

50

60

0 10 20 30 40 50 60Salt testing results from Georgian laboratory (ppm iodine)

Sal

t tes

ting

resu

lts fr

om U

krai

nian

labo

rato

ry

(ppm

iodi

ne)


ReFeReNCeS

1. WHO/UNICEF/UNU. Iron deficiency anaemia: assessment, prevention, and control - A guide for programme managers. Geneva and New York: World Health Organization/United Nations Childrens Fund/United Nations University; 2001.

2. Esther Wong SA, Lindsay Margoles, Jami Schaffner, and Parmi Suchdev. National Nutrition Survey of Women and Children - Republic of Georgia 2008: Survey Report. In: UNICEF and Emory University; 2007.

3. Georgian National Iron Deficiency and Anemia Survey 2007 (Estimation of the prevalence of iron deficiency and anemia in women of reproductive age (15-49) by measuring serum ferritin concentration); 2007.

4. Monitoring the situation of children and women: Multiple Indicator Cluster Survey 2005. Tbilisi: State Department of Statistics of Georgia and National Centre for Disease Control of Georgia 2005.

5. McLean E, de Benoist B, Allen LH. Review of the magnitrude of folate and vitamin B12 defi-ciencies worldwide. Food and Nutrition Bulletin 2008;29:S38-S51.

6. Wald NJ, Law MR, Morris JK, Wald DS. Quantifying the effect of folic acid. Lancet 2001;358:2069-73.

7. Ray JG. Efficacy of Canadian folic acid food fortification. Food and Nutrition Bulletin 2008;29:S225-S30.

8. Hertrampf E, Cortes F. Folic acid fortification of wheat flour: Chile. Nutrition Reviews 2004;6:S44-S8.

9. Chen LT, Rivera MA. The Costa Rican experience: Reduction of neural tube defects following food fortification programs. Nutrition Reviews 2004;6:S40-S3.

10. Weekly iron-folic acid supplementation (WIFS) in women of reproductive age: its role in promoting optimal maternal and child health: Position statement. World Health Organiza-tion, 2009. (Accessed at <http://www.who.int/nutrition/publications/micronutrients/week-ly_iron_folicacid.pdf>.)

11. WHO/FAO. Guidelines on food fortification with micronutrients. Geneva: World Health Orga-nization and Food and Agricultural Organization of the United Nations; 2006.

12. Participants in consultation. Conclusions of a WHO Technical Consultation on folate and vi-tamin B12 deficiencies. Food and Nutrition Bulletin 2008;29:S238-S44.

13. Wesley A, Ranum P, eds. Fortification Handbook: Vitamin and Mineral Fortification of Wheat Flour and Maize Meal. Ottawa, Canada: The Micronutrient Initiative; 2004.


14. Wheat Flour Fortification: Current Knowledge and Practical Applications. Summary Report of an International Technical Workshop. Flour Fortification Initiative. Cuernavaca, Mexico; 2004 December 1-3, 2004.

15. UNICEF/WHO. Eliminating Iodine Deficiency in the Republic of Georgia: Overview of 2005 National Survey. Tbilisi; 2006.

16. WHO/UNICEF/ICCIDD. Assessment of iodine deficiency disorders and monitoring their elimi-nation: A guide for programme managers, 3d ed. Geneva: WHO; 2007.

17. State Department of Statistics, National Center for Disease Control, UNICEF. Republic of Georgia - Multiple Indicator Cluster Survey, 1999. Tbilisi; 2000.

18. WHO. Physical Status: The Use and Interpretation of Anthropometry: Report of a WHO Ex-pert Committee. WHO Technical Report Series #854. Geneva: World Health Organization; 1995.

19. WHO. The optimal duration of exclusive breastfeeding: Report of an expert consultation. Ge-neva: World Health Organization; 2002.

20. Li R, Scanlong KS, Serdula MK. The validity and reliability of maternal recall of breastfeeding practice. Nutrition Reviews 2005;63(4):103-10.

21. Multiple Indicator Cluster Survey Manual 2005: Monitoring the Situation of Children and Women. Appendix One: Indicators for Global Reporting. New York: Division of Policy and Planning, UNICEF; 2006.

22. WHO/UNICEF. Indicators for assessing infant and young child feeding practices: conclusions of a consensus meeting held 6–8 November 2007 in Washington D.C., USA. Washington, D.C.; 2008.

23. UNICEF/WHO. Baby-Friendly Hospital Initiative: Revised, updated and expanded for integrat-ed care. New York and Geneva: United Nations Childrens Fund and World Health Organiza-tion; 2009.

24. Owen CG, Martin RM, Whincup PH, Smith GD, Cook DG. Effect of infant feeding on the risk of obesity across the life course: A quantitative review of published evidence. Pediatrics 2005;115:1367-77.

25. State Department of Statistics of Georgia and National Centre for Disease Control of Geor-gia. Monitoring the situation of children and women: Multiple Indicator Cluster Survey 2005. Tbilisi; 2008 June

26. Nalubola R, Nestel P. Manual For Wheat Flour Fortification with Iron - Part 3 Analytical Meth-ods for Monitoring Wheat Flour Fortification with Iron: Appendix 3.8 Elements by atomic absorption spectrophotometry, AACC method 40-70. Washington DC: MOST; 2000.

27. Ministry of Labor, Health and Social Affairs Order #300/n, 19.10.2007: Technical Regulation of Food Fortification. Tbilisi.


28. WHO International Classification of Diseases 10, version 2007. (Accessed at <http://apps.who.int/classifications/apps/icd/icd10online/>.)

29. de Onis M, Garza C, Victora CG, Onyango AW, Frongillo EA, Martines J. The WHO Multicen-tre Growth Reference Study: planning, study design, and methodology. Food and Nutrition Bulletin 2004;25(1 Suppl):S15-26.

30. WHO Anthro for Personal Computers Manual: Software for assessing growth and develop-ment of the world’s children. World Health Organization, 2009. (Accessed at <http://www.who.int/childgrowth/software/en/index.html>.)

31. Shetty P, James W. Body mass index: a measure of chronic energy deficiency in adults. Food and Nutrition Paper No. 56. Rome: Food and Agriculture Organization of the United Nations; 1994.

32. UNHCR/WFP. Guidelines for Selective Feeding Programmes in Emergency Situations. Geneva and Rome: United Nations High Commissioner for Refugees and World Food Programme; 1999.

33. Sullivan KM, Mei Z, Grummer-Strawn L, Parvanta I. Haemoglobin adjustments to define anae-mia. Tropical Medicine and International Health 2008;13:1267-71.

34. Assessing the Iron Status of Populations: Report of a Joint World Health Organization/Cen-ters for Disease Control and Prevention Technical Consultation on the Assessment of Iron Status at the Population Level. Geneva and Atlanta: WHO and CDC; 2004.

35. DRG package insert: DRG® Vitamin Folic Acid (BIO-4886). (Accessed 24 March 2010, at <http://www.drg-international.com/ifu/bio-4886.pdf>.)

36. How to weigh and measure children: Assessing the nutritional status of young children in household surveys. New York: United Nations Department of Technical Co-operation for De-velopment and Statistical Office; 1986.


Date post:	29-Jun-2018
Category:	Documents
Upload:	dinhtram
View:	221 times
Download:	0 times

RepoRt - UNICEF Georgiaunicef.ge/uploads/Report_of_the_Georgia_National_Nutrition_Survey... ·...

Documents