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

Documenting and archiving the Annual Health Survey of maternal and child outcomes
记录并存档孕产妇和儿童结果的年度健康调查
批准号:
9895234
负责人:
Diane Coffey
金额:
$7.33万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-25 至 2021-08-31

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中文摘要
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英文摘要
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.
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