Low Birth Weight

MICS3 Data Analysis and Report Writing

Background

• Low birth weight carries a range of grave health risks for children. Low birthweight babies face a greatly increased risk of dying during their early months and years.

• Those who survive have impaired immune function and increased risk of disease; are likely to remain malnourished, with reduced muscle strength, throughout their lives, and suffer a higher incidence of diabetes and heart disease in later life.

Background

• Children born underweight also tend to have a lower IQ and cognitive disabilities that affect their performance in school and their job opportunities as adults.

International Goals & Targets

Reduction in the rate of low birth weight by at least

one-third of the current rate

Definition of Indicator

% of infants who weighless than 2,500 grams

(2.5 kg) at birth

Numerator: Number of last live births in the 2 years preceding the survey weighing below 2,500 grams (2.5 kg)

Denominator: Total number of last live births in the 2 years preceding the survey

Methodological Issues

• Prior to about 1990, estimates of low birth weight were based primarily on data from health facilities. These data are often biased.

• Since about 1990, birth weight information has been collected systematically from mothers participating in national HH surveys.

• Early assessments of survey data showed that mothers are often unable to provide numerical birth weights, mostly because they are not weighed at birth.

74

6560

30

2117

58

0

20

40

60

80

100

South Asia Sub-Saharan

Africa

Middle East/North Africa

East Asia/Pacific

CEE/CIS Latin America/Caribbean

Developing Countries

Methodological Issues

Percentage of births NOT weighed

Methodological Issues

Comparison of births weighed and not weighed

0 20 40 60 80 100

Delivered in a medical facility

Delivered with medicalassistance

First births

Secondary education

No education

Urban

Percent

Not weighed Weighed

Methodological Issues

Adjustment Procedure

• An adjustment procedure was proposed by Boerma and colleagues (1996) that uses additional information on the mother’s assessment of the child’s size at birth.

• MICS and DHS surveys collect information on mother’s assessment of birth size. Three questions:

– When [child’s name] was born, was he/she very large, larger than average, average, smaller than average, or very small?

– Was [child’s name] weighed at birth?– If yes, what did [child’s name] weigh?

Methodological Issues

Adjustment Procedure

Numerical birth weight

Mothers’ assessments of birth size

100% of survey sample

Methodological Issues

Heaping of Birth Weight, Tanzania 1999

0

50

100

150

200

250

300

1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000

Birth weight in grams

Nu

mb

er

of

bir

ths

Methodological Issues

Effect of Adjustment

11.2

12.5

15.6

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

Unweighted average (62 surveys)

% lo

w b

irth

wei

gh

t

Based on weight only Adjusted for underreporting Adjusted for heaping

Methodological Issues

Note that updated estimates are

available in The State of the World’s

Children 2006

Methodological Issues

In MICS, 2 items in the questionnaire are used to estimate low birth weight.

– Mother’s recall of the child’s size at birth (i.e. very small, smaller than average, larger than average, very large)

– Mother’s recall of the child’s weight or the weight recorded on a health card if the child was weighed at birth

Tabulation Plan

Table NU.8: Low Birth Weight

Methodological Issues

• Tabulate children’s size by their weight for those weighed at birth to obtain proportion of births in each size category who weighed less than 2,500 grams

• Multiply this proportion by the total number of children in size category to obtain estimated number of children by size category with low birth weight

• Sum the estimated number of children in each size category with low birth weight in order to obtain the total number of low birth weight children

• Divide by the total number of live births to obtain the percentage with low birth weight

Tabulation Plan

Table NU.8E: Low Birth Weight Estimation

Regional Data

Low Birth Weight

31

15 15 149 9 7

17

0

20

40

60

80

100

% o

f in

fan

ts w

ith lo

w b

irth

wei

gh

t

Low Birthweight (CEE/CIS)

9

34455566667777891011

1516

0 20 40 60 80 100

CEE/CIS

AlbaniaBosnia/HerzegovinaSerbia/Montenegro

BelarusMoldova, Rep of

Ukraine Croatia

Russian FederationMacedonia TFYR

TurkmenistanArmeniaGeorgia

KyrgyzstanUzbekistan

KazakhstanRomaniaBulgaria

AzerbaijanTajikistan

Turkey

% infants with low birth weight

Low Birthweight (ROSA)

Low Birth Weight

3630

22 22 21 19 15

31

0

20

40

60

80

100

Bangladesh

India

Mal

dives

Sri Lan

ka

Nepal

Pakis

tan

Bhutan

South A

sia%

of

infa

nts

wit

h l

ow

bir

th w

eig

ht

Low Birthweight (TACRO)

9

5667777888889999910101010101011111212121314

1621

23

0 20 40 60 80 100

Latin America/Caribbean

ChileBelizeCuba

BahamasBolivia

Costa RicaEl Salvador

Antigua/BarbudaArgentina

MexicoSaint Lucia

UruguayColombiaGrenada

ParaguaySaint Kitts/Nevis

VenezuelaBarbados

BrazilDominica

JamaicaPanama

Saint Vincent/GrenadinesDR

PeruGuatemala

GuyanaNicaraguaSurinameHonduras

EcuadorHaiti

Trinidad/Tobago

% infants with low birth weight

15

66777778891010111112

1515

3132

0 20 40 60 80 100

Middle East/North Africa

LebanonSyria

AlgeriaIran

KuwaitLibya

TunisiaBahrain

OmanOPT

JordanQatar

MoroccoSaudi Arabia

EgyptIraqUAE

SudanYemen

% infants with low birth weight

Low Birthweight (MENA)

Low Birthweight (EAPRO)

7

00

344455677899999101011111212131415

1820

0 20 40 60 80 100

East Asia/Pacific

NiueTonga

Cook IslandsChina

Korea, Rep ofSamoa

KiribatiTuvalu

VanuatuKorea, Dem Rep

MongoliaSingaporeIndonesia

MalaysiaPalau

ThailandViet Nam

BruneiFiji

CambodiaPNG

MarshallTimor-Leste

SolomonLao PDR

MyanmarMicronesiaPhilippines

% infants with low birth weight

Low Birthweight (ESARO)

14

9

9

10

10

11

12

12

12

13

14

14

14

15

15

15

16

16

17

21

25

0 20 40 60 80 100

East/Southern Africa

RwandaSwazilandBotswana

KenyaZimbabwe

AngolaUgandaZambia

TanzaniaLesotho

MauritiusNamibiaEthiopia

MozambiqueSouth Africa

BurundiMalawi

MadagascarEritrea

Comoros

% infants with low birth weight

Low Birthweight (WCARO)

15

101112131313141414161616171718181920222323

0 20 40 60 80 100

West/Central Africa

ChadCameroon

Congo, Dem RepCape VerdeEq. Guinea

NigerCAR

GabonNigeria

BeninGhana

GuineaCôte d'Ivoire

GambiaSenegal

TogoBurkina Faso

Sao Tome/PrincipeGuinea-Bissau

MaliSierra Leone

% infants with low birth weight