Early Childhood Nutrition and Adult Outcomes in India

July 5, 2017 updated by: University of Chicago

Analysis of the Association Between Early Childhood Nutrition and Adult Outcomes Using Andhra Pradesh Children and Parents Study (APCAPS) Data

This study will investigate the association between exposure to a daily nutritional supplement in utero and during the first three years of life and adult educational, marriage, and labor market outcomes in India. During 1987-1990, a controlled nutrition trial offered a daily cooked meal to pregnant women and children below the age of six years in 15 intervention villages near the city of Hyderabad in South India. No supplementation was offered during the study in another 14 control villages. The trial and its follow up surveys are together known as the Andhra Pradesh Children and Parents Study (APCAPS).

This protocol registration is for an analysis of the publicly available APCAPS third follow up wave (2010-2012) data. It is not a registration of the underlying 1987-1990 nutrition trial.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

The investigators plan to use the 2010-2012 wave of the APCAPS data. They will access these publicly available data by applying for collaboration with the APCAPS study group.

The 2010-2012 follow-up survey invited all surviving children born during the original trial period of 1987-1990 (hereafter called index children) to participate. These index children were 20-25 years old at the time of this survey. Of the invited index children, 1,360 (715 in intervention villages and 645 in control villages) participated. The APCAPS surveys have collected a wide variety of data on socio-demographics, lifestyle, medical history, mental and reproductive health, anthropometry, cardiovascular physiology, spirometry, and biomarkers.

Using these data, the investigators will examine the association between birth in an intervention village and adult educational, marriage and labor market outcomes. For each study participant, a survey question collected information on the highest level of education attained by the participant (self-reported). From this variable, the investigators will create two indicators of whether the adult: (1) completed at least secondary school, i.e. class X/XII, intermediate, vocational course, or equivalent; (2) completed at least graduate level, i.e. Bachelor's degree, diploma, or equivalent.

The third outcome variable of the analysis will be whether the adult was ever-married (currently married, widowed, or divorced) at the time of the survey. Finally, the investigators will also examine whether the adult was either employed in paid or unpaid (e.g. household agriculture) work, or enrolled in higher education (degree or training course).

The investigators will use at least two different analytical methods. First, they will conduct a multivariate regression analysis (logit or probit) of each of the four outcome indicators. Along with the main independent variable of interest - birth in an intervention village - the model will include the following covariates: age, sex (whether female), and birth order of the index child, indicators of parental schooling attainment, religion, caste, and household standard of living as measured by quintiles of a composite asset index. All standard errors of regression will be heteoskedasticity-robust and clustered at the village level. The analysis will be conducted (and results reported) for the full sample and separately for the male and female subsamples.

In order to mitigate any bias arising from systematic differences in the characteristics of the intervention and control village adults (e.g. due to non-random attrition or other reasons), the investigators will also use quasi-experimental matching methods. One widely used methodology is matching based on propensity scores. The investigators will first conduct a selection analysis in which the likelihood of birth in an intervention village is regressed (probit or logit model) on the set of participant, parental, and household covariates mentioned above. Then, based on the predicted probability of intervention assignment (called propensity score) obtained from this model, participants in the intervention group will be matched with similar participant(s) in the control group. The investigators will use a variety of matching algorithms in order to test the sensitivity of the results, e.g. one-to-one nearest neighbor, Kernel, and multiple nearest neighbors matching. Common metrics for the quality of matching exercise and covariate balancing tests will be reported.

After matching, the investigators will report the average difference in outcome indicators between the intervention and matched control groups (technically named as the average treatment effect on the treated) as the estimated association between birth in an intervention village and adult outcomes. Findings from the full sample as well as male and female subsamples will be reported.

Study Type

Observational

Enrollment (Actual)

1360

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

20 years to 25 years (Adult)

Accepts Healthy Volunteers

N/A

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

The 1987-1990 Hyderabad Nutrition Trial enrolled pregnant women and young children from 29 villages in administrative areas near the city of Hyderabad in the state of Andhra Pradesh (now in Telangana). First, two adjacent sub-districts (group of villages, called a block) were selected for the study - one for the intervention group and the other as control. Then, 15 intervention and 14 control villages were selected. Intervention and control group villages had similar levels of access to other public health programs such as immunization and anemia control in pregnancy.

The children originally born in the study villages during 1987-1990 have been tracked and surveyed several times during 2003-2012. This study will use the the 2010-2012 survey data which include 1,360 (715 intervention and 645 control) adults of age 20-25 years who were originally born during the trial.

Description

Inclusion Criteria:

  • All participants in the publicly available data from the APCAPS 2010-2012 survey round.

Exclusion Criteria:

  • None

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Intervention
In 15 intervention villages, a balanced protein-calorie supplement - made from locally available corn-soya ingredients and called 'upma' - was offered daily to pregnant women and children under six years of age during 1987-1990. The meal provided on average 500 kcal energy and 20-25g of protein to women and half of those amounts to children.
A balanced protein-calorie supplement - made from locally available corn-soya ingredients and called 'upma'.
Control
No supplement was provided in 14 control villages.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
The likelihood of a study participant completing at least secondary school, i.e. class X/XII, intermediate, vocational course, or equivalent
Time Frame: Up to 25 years
Binary indicator of secondary level education
Up to 25 years
The likelihood of a study participant completing at least graduate level education, i.e. Bachelor's degree, diploma, or equivalent
Time Frame: Up to 25 years
Binary indicator of graduate level education
Up to 25 years
The likelihood of a study participant being ever-married (currently married, widowed, or divorced)
Time Frame: Up to 25 years
Binary indicator of marriage
Up to 25 years
The likelihood of a study participant being employed in paid or unpaid work, or enrolled in further education (degree or training courses)
Time Frame: Up to 25 years
Binary indicator of employment or higher education enrollment
Up to 25 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Arindam Nandi, PhD, University of Chicago
  • Principal Investigator: Jere R Behrman, PhD, University of Pennsylvania
  • Principal Investigator: Sanjay Kinra, PhD, London School of Hygiene and Tropical Medicine
  • Principal Investigator: Ramanan Laxminarayan, PhD, Center for Disease Dynamics, Economics & Policy

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 1987

Primary Completion (Actual)

December 31, 1990

Study Completion (Actual)

December 31, 2012

Study Registration Dates

First Submitted

June 29, 2017

First Submitted That Met QC Criteria

June 29, 2017

First Posted (Actual)

July 2, 2017

Study Record Updates

Last Update Posted (Actual)

July 11, 2017

Last Update Submitted That Met QC Criteria

July 5, 2017

Last Verified

July 1, 2017

More Information

Terms related to this study

Other Study ID Numbers

  • APCAPS2017

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Study Data/Documents

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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