# Documenting and archiving the Annual Health Survey of maternal and child outcomes

> **NIH NIH R03** · UNIVERSITY OF TEXAS AT AUSTIN · 2020 · $74,130

## Abstract

Project Summary
Despite global progress in maternal and child health, improvements have been uneven: some regions have
only seen slow reductions in early-life mortality. One such region is northern India, where prenatal care is rare;
hospital birth is not universal; and the under-five mortality rate is still as high as 1 in 10 in some places.
Existing data, which are often highly aggregated in developing countries, cannot explain such disparities. This
project aims to prepare, document, and archive a new dataset that will deepen researchers' understanding of
these trends and answer open questions in the area of maternal and child health. The Annual Health Survey
(AHS) was collected from approximately 4 million households in 9 high-mortality, high-fertility states of India.
There were three waves of data collection for a resulting panel dataset of over 12 million observations. The
AHS data hold enormous promise for deepening understanding of health and health policy: the panel structure
of the data would permit better causal inference than prior cross-sectional MCH datasets. Further, the AHS
data can be matched to other datasets, such as the NICHD-funded IHDS-II and the USAID-funded NFHS-
2015, to understand how social forces such as gender discrimination or health policies such as a conditional
cash transfer to promote hospital birth have impacted MCH. This proposal outlines a plan to make the
valuable AHS data usable and accessible to the scientific community.
The project aims to: (Aim 1) Prepare, clean, and document the AHS data. Much of the AHS data is already
publicly available, but in its current format it is very difficult to use. This project will: (1) clean and merge the
panel data, (2) match observations across rounds, (3) use Census district codes to match AHS districts to the
NHFS-2015 and the IHDS-II, (4) create Stata datasets with variable and value labels, (5) create metadata, (6)
create an AHS user's guide, and (7) create a variable codebook. (Aim 2) Archive the AHS with the NICHD-
supported Data Sharing for Demographic Research (DSDR) initiative and increase dissemination to the
research community. The PI and an Indian collaborator will publicize the AHS data among social science and
public health researchers through blog posts and articles, at the PAA annual meetings, at a presentation at
IFPRI, New Delhi, and through a webinar.
Given the large size of the AHS sample, the panel structure of the data, and the fact that these data can
answer open questions about maternal and child health in developing regions, the multiplier effects for public
health of investment in making AHS data usable and accessible to the scientific community are large.

## Key facts

- **NIH application ID:** 10023936
- **Project number:** 5R03HD098292-02
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Diane Coffey
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $74,130
- **Award type:** 5
- **Project period:** 2019-09-25 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10023936

## Citation

> US National Institutes of Health, RePORTER application 10023936, Documenting and archiving the Annual Health Survey of maternal and child outcomes (5R03HD098292-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10023936. Licensed CC0.

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