Utilization of ICDS: Does it

make a difference to child weight?

CONFERENCE ON CHILD HEIGHT, STUNTING,

EARLY-LIFE DISEASE & SANITATION

Nitya Mittal (PhD Scholar, DSE)

Introduction

□ ICDS was one of the programmes launched by the Indian government for holistic development of children□Universalized in 11th five year plan with huge budgetary

allocation□Poor uptake of ICDS(only 35% as per NFHS 3)□Mixed evidence of impact on health outcome

□ Need to evaluate performance and investigate reasons for underperformance

Objectives

□ Analyze the factors that determine demand for utilization of ICDS services.

□ Measure the impact of ICDS on health outcomes.

Literature Review

□ Selected literature review

□ Lokshin (2005) and Bredankamp and Akin (2004) – no impact of ICDS on stunting

□ Deolalikar (2004) and Kandpal (2009) – negative impact on probability of underweight and stunting respectively.

□ Saiyed and Seshadri (2000) find lower impact of partial utilization of ICDS services.

□ Monika Jain – (2011) accounts for selective placement and utilization. She finds no impact of availability but a positive effect of utilization on health care outcomes. But she considers only one service of ICDS – supplementary nutrition.

Theoretical Model - I

□ Assume a three member household, with a mother (m), father (f) and child (c). Its welfare function is given by-

where F is food consumption, G is non-food consumption and H is health status

□ The household maximizes its welfare function subject to health production function and budget constraint.

Theoretical Model - II

□ The household maximization can be divided in two cases□ Case 1 Maximize s.t.

□ Case 2 Maximize s.t.

Theoretical Model - III

□ Let W1* and W0

* be the maximum welfare for case 1 and

case 2 respectively.□ The household will choose to utilize ICDS services if and

only if:

□ The underlying demand for ICDS services is given by

□ The reduced form for health outcome is

or

Data

□ Study Area – East India, VDSA villages□ Age group – 6 months – 6 years□ Sample size – 278 children in 11 VDSA villages,

34 ICDS centers□ Study funded by VDSA, ICRISAT□ Two Questionnaires – household and anganwadi□ Household Questionnaire

□ Availability and utilization of each ICDS service, anthropometric outcomes, demographics, assets, monthly expenditure, prices

□ Anganwadi Questionnaire □ Availability of equipments, facilities and services

Summary Statistics - I

□ Difference between de-juro and de-facto availability, and actual utilization.

□ The actual utilization of services is much lower than availability, indicating that households do not choose to utilize all the services available at the ICDS center.

Number of services that ICDS center says are available 3.5Number of services household perceive to be available 3.2

Number of services utilized 1.7

Summary Statistics Variables Bihar Jharkhand Orissa TotalSample size (N) 104 118 56 278ICDS utilization (%) 42 84 87 69ICDS utilization NFHS-3(%) 8.8 38.6 60.5Underweight (%) 50 56 33 49Underweight NFHS-3 (%) 55 56 41 Age (months) 40 39 43 40Male (%) 49 51 50 50Mother - working (%) 12 10 6 10Mother Education (years) 5 3 7 5Father Education (years) 9 6 7 7Schedule Caste (%) 22 10 10 15Schedule Tribe (%) 0 64 9 29Backward Class (%) 55 24 56 41Non-Hindu (%) 2 27 2 13Open defecation (%) 63 97 89 83

Summary Statistics - III Yes No

Significant differenceVariables Utilized ICDS services

Underweight (%) 49 44 NoDistance (meter) 225 583 YesSchedule Tribe (%) 34 17 Yes

UnderweightMother - working (%) 12 6 YesSchedule Tribe (%) 37 25 YesOpen defecation (%) 90 80 Yes

Underweight (%)

Utilized ICDS service (%)

Yes No

Yes 35 14

No 36 15

Empirical Estimation - I

□ System of recursive equations

□ Systems estimation with one discrete and one continuous dependent variable□ Simultaneous estimation – LPM□ Maddala (1976)

Empirical Estimation - II

□ Determinants of Utilization of ICDS services

□ Individual specific covariates – Age, gender

□ Household specific covariates - Distance to ICDS center, Mother’s education, Mother’s occupational status, Economic status, Caste category, Religion

□ State fixed effects

Utilization of ICDS services LPM Probit

Age (months) -0.004** -0.020***(0.001) (0.005)

Gender (1=Male) 0.029 0.124(0.046) (0.197)

Distance (meter) -0.299*** -1.454***(0.070) (0.340)

Assets -0.042*** -0.190***(0.013) (0.055)

Jharkhand 0.398*** 1.242***(0.074) (0.323)

Orissa 0.380*** 1.113***(0.073) (0.291)

Observations 227 259

Log-likelihood -6300 -107

Standard Error in parenthesis. ***p<0.01, **p<0.05, *p<0.10

Empirical Estimation - III

□ Health outcomes – standardized weight

□ Individual specific covariates – ICDS utilization, Dietary diversification, Vaccination (number of vaccines received out of 9 government mandated vaccines), Dummy for morbidity (fell sick in last one month), Size at birth

□ Household specific covariates – Sanitation, Source of water supply, Economic status, Mother’s education, Father’s education, Mother’s occupational status, Household size, Caste category, Religion

□ State fixed effects

Weight-Standardized LPM 2 stageICDS utilization 1.289** 0.980*

(0.733) (0.554)Dietary Diversity 0.044** 0.030*

(0.019) (0.018)Vaccination 0.089* 0.082

(0.049) (0.052)Morbidity (Dummy) -0.532*** -0.646***

(0.204) (0.230)Open Defecation -0.606* -0.723**

(0.323) (0.335)Log(Monthly per

capita expenditure)0.610** 0.635**(0.297) (0.308)

Household size 0.084** 0.077**(0.034) (0.035)

Jharkhand -1.106** -0.847**(0.536) (0.425)

Orissa -0.447 -0.156(0.482) (0.381)

Observations 227 227LL / R-squared -6300 24.34

Conclusion

□ Proximity to ICDS center is crucial to utilization of ICDS services.

□ Low economic status correlated with higher utilization. There are no gender, caste or religion differences in utilization of ICDS services, but there are regional differences.

□ ICDS utilization has a positive impact on weight but magnitude appears large.

□ Economic status, hygienic sanitation facility, vaccinations, better diet quality all affect weight.

Way Forward

□ Examining if utilization of each individual service is demand driven or supply constrained.

□ Examine impact of individual service utilization on anthropometric outcome.

Acknowledgements

□ Funding – PhD Research Fellowship under VDSA, ICRISAT

□ Institutional Support - ICRISAT, NCAP, ICAR – Patna

□ Enumerators – Amit Kumar, Chittaranjan Sharma, Dayanand Tripurari, Ganesh Prasad Behura, Harendra Kumar Chaubey, Nalini Ranjan Sahoo, Prakash Kumar , Rajesh Kumar, Sanjay Kumar, Sant Kumar Rai, Saroj Kumar Majhi