The document presents an analysis of unmet health needs, focusing on malnutrition among children in rural India, particularly in the Chinchohol Primary Health Centre area. It identifies various causes and risk factors contributing to malnutrition, such as economic conditions, maternal education, and access to employment and nutritional services. Community financing is discussed as a potential solution, along with recommendations for both short-term and long-term actions to improve health and nutrition in these communities.

1. 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

2. 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

3. 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 !

4. 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

5. Unmet Needs of Rural Health Care*
• RURAL (Primary/ • URBAN (Secondary/
Secondary) per 1000 Tertiary) per 1000
Beds 0.2 Beds 3.0
Doctors 0.6 Doctors 3.4
PE 80,000 PE 560,000
OoPs! 750,000 OoPs!! 1,150,000
IMR 74/1000 LBs IMR 44/1000 LBs
U5MR 133/1000 LBs U5MR 87/1000 LBs
Births Attended 33.5% Births Attended 73.3%
ANC median 2.5 ANC median 4.2
Avg. Distance from FRU: 30 km Avg. Distance from FRU: 10 km
* www.vatsalya.com based on CII McKinsey Study, 2001

7. 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.
•

8. CAUSES OF
MALNUTRITION
A Study of children 0-6 years age

9. Aims and Objectives of the
Study
Aim:
•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

10. 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

11. Chinchohol PHC Profile
PHC Area Profile PHC Performance Profile
Gram Panchayats 4
Total %
Institutional
Villages 9 Deliveries
Habitations* 34
Population (Census 2001) 9656 2008-09 47 16
% SC 3%
% ST 93% 2009-10 66 21
HHs (est.) 2500
Anganwadis (ICDS, 2010) 32
2010-11 133 37
3+1(at
Sub centres PHC)
Sources: Census 2001 Source: Chinchohol PHC reports 2009, 2010 and 2011

12. About the Population Pyramid
study

13. POPULATION PROFILE

14. Nutritional Assessment
Girls Boys Total
(n=401) (n=426) (n=827)
93 127 220
WASTING (WHZ) (23%) (30%) (27%)
UNDERWT. 258 309 567
(WAZ) (64%) (73%) (69%)
264 294 558
STUNTING(HAZ) (66%) (69%) (68%)
Malnutrition = WHZ, WAZ, HAZ (<-2 SD)
(WHO Standards)

15. Severity of malnutrition by prevalence ranges
(%)
Very Chinchohol
Indicator Low
high Survey
Wasting < 5 >=15% 27% 220
Underwt
<10 >=30% 69% 567
.
Stunting <20 >=40% 68% 558

16. Families and Communities
Communities No of HHs % HHs
SC
56 3%
ST
1689 93%
Others
67 4%
Total
1812 100%

17. Land Holdings
Land Holding in the community Land Holding in the Scheduled Tribe

18. How much are they educated?
women and men
Women – agewise (%) Men-agewise (%)

19. How many
families are
aware and
using govt. AWARE NOT AWARE USED NOT USED
schemes? Anganwadi
for Nutr. 91% 5% 70% 26%
• Most families are aware of Suppl.
and accessed Anganwadi
IFA for
of WCD and Khavti Yojna Adolescent 55% 41% 39% 57%
of TWD Girls
• But, 34% are not aware
about any employment
NREGA/EGS 63% 34% 59% 37%
guarantee scheme!
• EGS has not reached out
KHAVATI
to 37% of the (mostly 82% 15% 63% 33%
YOJANA
landless) families
• 41% of families unaware
about adol. Girls
programme

20. Place of Deliveries
At home 472 76%
Government
144 23%
hospital
Private
4 0.6%
hospital/Jeep
Total 620 100%

21. Profile of children 0-60 months age
No. %
Child clean 372 57
Child not
285 43
clean
Total 657 100

22. 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)

23. Type of ration
cards
Families
No. of
having type
familie
of ration
s
cards
Other than
242
Yellow Cards
Yellow Cards 384
626

24. Families of 0-
60 mths
children
migrating for
work
No. of
families
Migrate for
454
work
Do not
migrate for 202
work
Total 656

25. 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.)

26. 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%?

27. 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

28. Knowledge
about
Weaning
Period
• 49% do not know
correctly about
when to start
weaning (0-6 too
early, 12-36 late)

29. CAUSES OF
MALNUTRITION
Regression Analysis using R Programme

30. Causes of Malnutrition –Key
Findings
Types of Model 3 (N=510)
Causes of Malnutrition Association
causes 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
positive 0.188 (0.044)
months and 12 months
Breast feeding for one year after birth positive (marginally) 0.168 (0.188)
Anganwadi Nutrition Supplement
Immediate no association
scheme used

31. Causes of
Association (p-
Malnutrition: Variable
value)
Univariate Regression Model 1: Gender of the child
Analysis
•Age a significant variate
Age in months -0.005 (0.017)
as a cause of Sex – Male (female as ref.) -0.111 (0.192)
malnutrition
•Gender is not an Model 2: Breast feeding after birth (in hours)
important cause, both
male and female are Age in month -0.006 (0.016)
equally malnourished 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)

32. Causes of
Malnutrition: Variable
Association (p-
value)
Univariate Regression Model 3: Duration of breast feeding (in months)
Analysis
•Attitude about breast Age in month -0.005 (0.017)
feeding after birth is not Less than one year (ref.)
significant cause
One year 0.168 (0.188)
•Attitude about duration
of breast feeding of Between 1 to 2 years -0.004 (0.977)
one/two year is Two years 0.182 (0.158)
significant one Between 2 to 5 years 0.042 (0.826)
•Knowledge about
Model 4: When weaning food should be given
weaning between 6-12
months a significant one 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)

33. Causes of
Malnutrition: Variable
Coefficient
(p-value)
Univariate Regression Model 5: Accessing Employment
Analysis
•No utilization of any Age in months -0.005 (0.014)
employment guarantee
scheme a significant No utilization of NREGA/EGS -0.137 (0.169)
cause
•No access to
Model 6: Utilizing Anganwadi supplements
Anganwadi
supplementary food also
an important cause Age in months -0.005 (0.032)
No utilization of A'wadi
-0.019 (0.889)
supplementary food

34. Model 1 Model 2 Model 3
Variables
(N = 620) (N = 579 ) (N = 510)
Individual characteristics
Age -0.006 (0.03) -0.006 (0.02) -0.007 (0.02)
Causes of Sex- male (female as ref.) -0.109 -0.139 -0.123
Malnutrition: Home delivery -0.067 -0.069 -0.107
Basic Causes: Human, Economic and Societal
Multivariate
Regression Analysis Type of family
•Child’s age a significant Nuclear (ref.)
cause Joint -0.014
Family land
•Place of delivery is not
important cause Landless (< 0.01 H) (ref)
•Joint family an
important cause Marginal (0.01 – 1.00 H) 0.285 (0.03)
•Even a small piece of 0.397
Small (1.01 – 2.00 H)
land is better than no (0.006)
land causing Semi-medium+ (> 2.00 H)
0.126
malnutrition (0.518)
•Migrating to work an Migration
important cause Yes (ref.)
•No access to any EGS No 0.208 (0.06)
a cause Employment
Utilization of NREGA/EGS
(ref)
No utilization of -0.196
NREGA/EGS (0.075)

35. Model 1 Model 2 Model 3
Variables
(N = 620) (N = 579 ) (N = 510)
Mother's characteristics
Causes of Work
Malnutrition: Not working (ref)
Farm 0.049 -0.083
Multivariate Regression
Analysis Labour -0.022 0.056
•Non earning mother an Other source -0.028 -0.154
important cause of More than one -0.107 -0.087
malnourished child
Education
•Mother’s education not
important cause Illiterate (ref.)
•Knowledge about Education up to
Weaning period 0.014 0.121
primary school (4th)
important cause
Education up to
-0.041 -0.033
secondary school (7th)
Education above
0.113 0.145
secondary
Weaning
When weaning food
0.229
should be given (6 to
(0.023)
12 mths)

36. Model 1 (N Model 2 (N = Model 3 (N
Variables
= 620) 579 ) = 510)
Underlying Causes: Food Security, Environment, MCH and
Causes of Health Care Services
Malnutrition: Ration card
‘Yellow’ ration card
Multivariate Regression (ref)
Analysis
•Yellow ration card
Other than ‘yellow’
-0.015
ration card
holding is important
cause House type
•Kaccha household also Kaccha (ref)
an important factor Pucca 0.082
•No cleanliness has a
Toilet
significant effect
Yes (ref.)
No -0.029
Clean kitchen
Yes (ref.)
No 0.048
Cleanliness of child
Yes (ref.)
No -0.209 (0.07)

37. Most important causes
Basic Causes:
•Age – improve family economic conditions before its
birth
Underlying 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)

38. CAUSES OF
MALNUTRITION
Short and Long Term Action Plan

39. DS
IC
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PD nly…
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in ere
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Mo ut in
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hen
…w !!

40. Short Term Action Plan
Family 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

41. Spider map for Long Term Action Plan
HEALTH CARE SERVICES
FOR MOTHERS AND SUPPLEMENTARY FOOD
CHILDREN FOR CHILDREN
ENHANCED FOOD
SECURITY FOR FAMILIES
HEALTH CARE SERVICES
HAVING VULNERABLE
FOR ADOLESCENT GIRLS
CHILDREN AND ADULTS
Again
, econom
ic improv
IMPROVED ement
NUTRITION
EDCUATION INCL. LIFE IMPROVED NUTRITIONAL
SKILL EDUCATION STATUS AS A GOAL OF
POVERTY ALLEVIATION
ADOLESCENT GIRLS
PROGRAMMES
VOCATIONAL TRAINING/ NUTRITION DEFICIT AS A
EMPLOYMENT ORIENTED BASIS OF POVERTY LINE
EDUCATION TO BOYS AND WAGES
AND GIRLS

42. FINANCING HEALTH
CARE
OPPOR

43. 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

44. 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?

45. Is community financing a solution?