UNMET HEALTH NEEDS OF RURAL PEOPLE: IS COMMUNITY FINANCING A SOLUTION ?

Case of malnutrition in rural India

Presented at 18th International Congress of Rural Health and Medicine at Panjim, Goa

10 – 12 December 2012

Dr. Dhruv Mankad, Mumbai

Rural India – Changes in needs

Changes in Demographic Profile•69% of total population lives in villages (800m/1210m) •During the last decade, there is a decrease in % but increase in number (91 m) of persons and of villages•Child Sex Ratio (0-6) in the country in Census the lowest since 1961 Census at 914. In Rural areas the fall is significant from 934 in 2001 to 919 in 2011•Pace of increase in Literacy rates of rural women has accelerated (13%)•Marginal Reduction in Rural IMR to 51

Unmet Social Needs in Rural India

Unmet Social Needs•Safe, adequate, accessible drinking water – paradigm shift•Sanitation and Hygiene•Food security•Social Exclusion – Gender, ‘caste’, tribal, geographical

•Poverty rank 88th but HD rank 134th !

Unmet Needs of Disease Burdens in Rural India

• Water borne diseases like diarrhea have declined but jaundice, illnesses from arsenic, lead, fluoride contaminated DW on increase

• Vector borne diseases: Malaria, Kala azars, JE persist• Accidents and occupation related illnesses increase• CVDs particularly high blood pressure and diabetes on increase• Maternal Deaths decreasing but illnesses suffered by women persist

including stress and work related illnesses• Unsafe/Spontaneous abortion• Child deaths decreasing but its after effects like malnutrition, low

immunity, faltered growth and development persist• Mental Health Illnesses becoming evident• Dental carries, middle ear Infection, piles, low back aches persist

AVERTING DEATHS WITHOUT IMPROVING QUALITY OF LIFE LEADS TO DISEASES OF DEPRIVATION

Unmet Needs of Rural Health Care*

• RURAL (Primary/ Secondary) per 1000

Beds 0.2

Doctors 0.6

PE 80,000

OoPs! 750,000

IMR 74/1000 LBs

U5MR 133/1000 LBs

Births Attended 33.5%

ANC median 2.5

Avg. Distance from FRU: 30 km

• URBAN (Secondary/ Tertiary) per 1000

Beds 3.0

Doctors 3.4

PE 560,000

OoPs!! 1,150,000

IMR 44/1000 LBs

U5MR 87/1000 LBs

Births Attended 73.3%

ANC median 4.2

Avg. Distance from FRU: 10 km

* www.vatsalya.com based on CII McKinsey Study, 2001

Malnutrition: A case for unmet needs• A routine survey conducted by the WCD, Nashik of

anganwadi children in November 2010 revealed that villages under the Chinchohol PHC, had highest number of SAM 0-6 years. (241 SAM, 212 MAM, 453 >=-2SD WHZ) VACHAN was assigned to carry out a study.

•

CAUSES OF MALNUTRITIONA Study of children 0-6 years age

Aims and Objectives of the StudyAim:•Find out immediate problems leading to malnutrition and rectify them urgently. •highlight the long term problems and strategize its solutions

Objectives:•To identify multiple causes of malnutrition in children 0-6 years in villages under Chinchohol PHC

Statistical analysis• Descriptive statistics to summarize the data. • WHO Anthro for z-scores of weight-for-age, height-for-age

and BMI for nutritional assessment of the cohort. • Weight-for-age for defining malnutrition and analysing its

causes • Association analysis for significance of epidemiologically

relevant risk factors and malnutrition. • Univariate and multivariate regression analysis using R

programme

Chinchohol PHC Profile

PHC Area Profile

Gram Panchayats 4

Villages 9

Habitations* 34

Population (Census 2001) 9656

% SC 3%

% ST 93%

HHs (est.) 2500

Anganwadis (ICDS, 2010) 32

Sub centres3+1(at PHC)

PHC Performance Profile

TotalInstitutional Deliveries

%

2008-09 47 16

2009-10 66 21

2010-11 133 37

Sources: Census 2001 Source: Chinchohol PHC reports 2009, 2010 and 2011

About the study

Population Pyramid

POPULATION PROFILE

Nutritional Assessment

 Girls

(n=401)Boys

(n=426)Total

(n=827)

WASTING (WHZ)93

(23%)127

(30%)220

(27%)UNDERWT.(WAZ)

258 (64%)

309 (73%)

567 (69%)

STUNTING(HAZ)264

(66%)294

(69%) 558

(68%)

Malnutrition = WHZ, WAZ, HAZ (<-2 SD) (WHO Standards)

Severity of malnutrition by prevalence ranges (%)

Indicator LowVery high

Chinchohol Survey

Wasting < 5 >=15% 27% 220

Underwt.

<10 >=30% 69% 567

Stunting <20 >=40% 68% 558

Families and Communities

Communities No of HHs % HHs

SC56 3%

ST1689 93%

Others67 4%

Total1812 100%

Land HoldingsLand Holding in the community Land Holding in the Scheduled Tribe

How much are they educated?women and men

Women – agewise (%) Men-agewise (%)

How many families are aware and using govt. schemes?

  AWARE NOT AWARE USED NOT USED

Anganwadi for Nutr. Suppl.

91% 5% 70% 26%

IFA for Adolescent

Girls55% 41% 39% 57%

NREGA/EGS 63% 34% 59% 37%

KHAVATI YOJANA

82% 15% 63% 33%

• Most families are aware of

and accessed Anganwadi

of WCD and Khavti Yojna

of TWD

• But, 34% are not aware

about any employment

guarantee scheme!

• EGS has not reached out

to 37% of the (mostly

landless) families

• 41% of families unaware

about adol. Girls

programme

Place of Deliveries

At home 472 76%

Government hospital

144 23%

Private hospital/Jeep

4 0.6%

Total 620 100%

Profile of children 0-60 months age

  No. %

Child clean 372 57

Child not clean

285 43

Total 657 100

Cleanliness of households

• 73% of Households have toilets

• Only 31% of HHs had clean kitchen (smokeless chullah, smoke outlet, waste water disposal system and glass tile or window)

Type of ration cards

Families having type

of ration cards

No. of familie

s

Other than Yellow Cards

242

Yellow Cards 384

  626

Families of 0-60 mths children migrating for work

 No. of

familiesMigrate for work

454

Do not migrate for work

202

Total 656

Types of work mothers engaged in• Most mothers

engaged in household chores (non earning work)

• 44% engaged in productive (21% earning, 23% farm based)

• 13% engaged in more than one type of work – farming+labour

• 9% engaged in other types of work (petty shops etc.)

Education level of mothers of 0-6 age children

• 43% with no education

• 41% 7th std. or above

• 16% up to 10th or above

• 2 mothers graduate (1 PG, too)

WHAT WORKS FOR THE 16%?

Attitude about Breastfeeding practices

17% mothers

consider less than

12 months

adequate for

breastfeeding

33% consider 12

months as

adequate

breastfeeding

50% consider

Breastfeeding

beyond 12 months

Knowledge about Weaning Period

• 49% do not know

correctly about

when to start

weaning (0-6 too

early, 12-36 late)

CAUSES OF MALNUTRITIONRegression Analysis using R Programme

Causes of Malnutrition –Key Findings Types of causes

Causes of Malnutrition Association Model 3 (N=510)Co-eff. (p-value)

Basic Age (in months) negative -0.007 (0.02)

No utilisation of NREGA/EGS negative (marginally) -0.196 (0.075)

No migration for work positive 0.208 (0.06)

Having small land positive 0.397 (0.006)

Underlying No Toilet negative -0.029

Child not clean negative -0.209 (0.07)

Having Pucca house positive 0.082

Mother’s education no association

Weaning food to be given between 6 months and 12 months

positive 0.188 (0.044)

Breast feeding for one year after birth positive (marginally) 0.168 (0.188)

ImmediateAnganwadi Nutrition Supplement scheme used

no association

Causes of Malnutrition: Variable

Association (p-value)

Model 1: Gender of the child

Age in months -0.005 (0.017)

Sex – Male (female as ref.) -0.111 (0.192)

Model 2: Breast feeding after birth (in hours) 

Age in month -0.006 (0.016)

Immediately (ref.)  

Within half-an-hour -0.138 (0.306)

Between 0.5 and 1 hour -0.109 (0.363)

Between 1 and 2 hours -0.071 (0.606)

Between 2 and 6 hours -0.102 (0.616)

Univariate Regression Analysis•Age a significant variate as a cause of malnutrition•Gender is not an important cause, both male and female are equally malnourished

Causes of Malnutrition: Variable

Association (p-value)

Model 3: Duration of breast feeding (in months) 

Age in month -0.005 (0.017)

Less than one year (ref.)  

One year 0.168 (0.188)

Between 1 to 2 years -0.004 (0.977)

Two years 0.182 (0.158)

Between 2 to 5 years 0.042 (0.826)

Model 4: When weaning food should be given 

Age in months -0.005 (0.017)

Before 6 months of age (ref.)  

Between 6 and 12 months 0.188 (0.044)

Between 12 and 36 months 0.112 (0.434)

Univariate Regression Analysis•Attitude about breast feeding after birth is not significant cause•Attitude about duration of breast feeding of one/two year is significant one•Knowledge about weaning between 6-12 months a significant one

Causes of Malnutrition: Variable Coefficient

(p-value)

Model 5: Accessing Employment 

Age in months -0.005 (0.014)

No utilization of NREGA/EGS -0.137 (0.169)

Model 6: Utilizing Anganwadi supplements 

Age in months -0.005 (0.032)

No utilization of A'wadi supplementary food

-0.019 (0.889)

Univariate Regression Analysis•No utilization of any employment guarantee scheme a significant cause•No access to Anganwadi supplementary food also an important cause

Causes of Malnutrition:

VariablesModel 1

(N = 620)Model 2

(N = 579 )Model 3

(N = 510)

Individual characteristics

Age -0.006 (0.03) -0.006 (0.02) -0.007 (0.02)

Sex- male (female as ref.) -0.109 -0.139 -0.123

Home delivery -0.067 -0.069 -0.107

Basic Causes: Human, Economic and Societal

Type of family      

Nuclear (ref.)      

Joint     -0.014

Family land      

Landless (< 0.01 H) (ref)      

Marginal (0.01 – 1.00 H)     0.285 (0.03)

Small (1.01 – 2.00 H)    0.397

(0.006)

Semi-medium+ (> 2.00 H)    0.126

(0.518)Migration      

Yes (ref.)      

No     0.208 (0.06)

Employment      

Utilization of NREGA/EGS (ref)

     

No utilization of NREGA/EGS

   -0.196

(0.075)

Multivariate Regression Analysis•Child’s age a significant cause•Place of delivery is not important cause•Joint family an important cause•Even a small piece of land is better than no land causing malnutrition•Migrating to work an important cause•No access to any EGS a cause

Causes of Malnutrition:

VariablesModel 1 (N = 620)

Model 2 (N = 579 )

Model 3 (N = 510)

Mother's characteristics

Work      

Not working (ref)      

Farm   0.049 -0.083

Labour   -0.022 0.056

Other source   -0.028 -0.154

More than one   -0.107 -0.087

Education      

Illiterate (ref.)      

Education up to primary school (4th)

  0.014 0.121

Education up to secondary school (7th)

  -0.041 -0.033

Education above secondary

  0.113 0.145

Weaning      

When weaning food should be given (6 to 12 mths)

   0.229

(0.023)

Multivariate Regression Analysis•Non earning mother an important cause of malnourished child•Mother’s education not important cause•Knowledge about Weaning period important cause

Causes of Malnutrition:

VariablesModel 1 (N

= 620)Model 2 (N =

579 )Model 3 (N

= 510)

Underlying Causes: Food Security, Environment, MCH and Health Care Services

Ration card      

‘Yellow’ ration card (ref)

     

Other than ‘yellow’ ration card

    -0.015

House type      

Kaccha (ref)      

Pucca     0.082

Toilet      

Yes (ref.)      

No     -0.029

Clean kitchen      

Yes (ref.)      

No     0.048

Cleanliness of child      

Yes (ref.)      

No     -0.209 (0.07)

Multivariate Regression Analysis•Yellow ration card holding is important cause•Kaccha household also an important factor•No cleanliness has a significant effect

Most important causes

Basic Causes:•Age – improve family economic conditions before its birthUnderlying Causes:•Small land holding•No utilisation of NREGA/EGS leading to low purchase power•Availability of and information about weaning food between 6-12 months should be given (between 6 to 12 months)

CAUSES OF MALNUTRITIONShort and Long Term Action Plan

……when it is needed

when it is needed

here also!!

here also!!

Money into PDF, ICDS is

put in here only…

Short Term Action PlanFamily centered, simultaneous implementation approach

1. Ensure adequate food (incl. proteins, micronutrients and not just energy) for economic safety and sustainability• Train adolescent girls and boys in life cycle and earning skills through

vocational training • Encourage special services including temporary day care for 0-2 year old

children by trained dais, elderly or experienced women for working women• Ensure at least that the families having underweight children and gainful

employment to all able bodied members through employment guarantee schemes and have food security through effective PDS

• Direct Cash Transfer for all BPL (do we have adequate infrastructure for microbanking?)

• Consider minimum wages as a package for family’s food requirements and not just the ‘workers’ one

IMPROVED NUTRITION

HEALTH CARE SERVICES FOR MOTHERS AND CHILDREN

SUPPLEMENTARY FOOD FOR CHILDREN

HEALTH CARE SERVICES FOR ADOLESCENT GIRLS

ENHANCED FOOD SECURITY FOR FAMILIES HAVING VULNERABLE CHILDREN AND ADULTS

EDCUATION INCL. LIFE SKILL EDUCATION ADOLESCENT GIRLS

IMPROVED NUTRITIONAL STATUS AS A GOAL OF POVERTY ALLEVIATION PROGRAMMES

VOCATIONAL TRAINING/ EMPLOYMENT ORIENTED EDUCATION TO BOYS AND GIRLS

NUTRITION DEFICIT AS A BASIS OF POVERTY LINE AND WAGES

Spider map for Long Term Action Plan

Again, economic improvement

FINANCING HEALTH CAREOPPOR

Social Protection in Health Financing - Options• Tax based NHS: Every one gets ‘free’ services from

direct or indirect tax paid through NHS, unless regulated OPP cannot be ruled out

• Social Health Insurance (SHI): mandatory contribution by employees and employers e.g. govt. healthcare services, CGHS, AFMS, Railway HS etc. Tata Medical Care services etc. Requires organized sector and economies of scale, requires govt. subsidy for poor

• Community based Health Insurance (CBHI): utilises pre-existing solidarity groups such as dairies, SHGs. Premium collected by members. community management makes flexible payment possible

Community Financing • User Fee – negative equity impact, no health impact,

didn’t work - so withdrawn • SHI – difficult to operationalize it• Community based Health Insurance – will it work?

• For the BPL/APL? Its utilization? Its claims? Require solidarity groups, are there such groups?

• How would it avoid the ‘Catch-22’ of cross-subsidy?• Would TPA, Insurance Co. be able to bear its administrative cost?

Is cost recovery possible?

• Pvt. Health Insurance for poor???• AND WHAT ABOUT SOCIAL DETERMINANTS OF

HEALTH? WHO CAN FINANCE IT?

Is community financing a solution?