Obtaining a Probability Sample of a Pregnancy Cohort of Births: A Review of the Problem and a Practical Solution.
Recommended Citation
Elliott MR, Kerver JM, Drew A, Watson K, Kornatowski B, Norman GS, Copeland GE, Leissou E, Ridenour T, Kruger-Ndiaye S, Ma T, Ruden D, Barone C, Keating DP, Sokol RJ, Johnson CC, and Paneth N. Obtaining a Probability Sample of a Pregnancy Cohort of Births: A Review of the Problem and a Practical Solution. Am J Epidemiol 2025.
Document Type
Article
Publication Date
5-23-2025
Publication Title
American journal of epidemiology
Abstract
The Michigan Archive for Research on Child Health (MARCH) study produced a probability sample of Michigan births between 2017 and 2023, with data collection beginning at first prenatal visit and continuing up to age 4. Birth certificate data were used to create a sampling frame of hospitals and associated obstetric clinics, from which a probability-proportional-size sample of 10 hospitals was drawn. Close to 100 pregnancies were then recruited in clinics serving each sampled hospital, yielding a probability sample of 1,021 births. This sample was supplemented with 109 births from a certainty selection of a Flint, MI hospital, for a total sample of 1,130. The resulting response rate was high, with 100% of sampled hospitals and 65% of sampled clinics participating. Comparing the resulting sample with all 2017-2023 Michigan births showed close correspondence with respect to birth outcomes (birthweight, gestational age, Apgar scores, gestational diabetes) and mothers' demographics (age, race, education, marital status), with underrepresentation of Hispanic ethnicity and overrepresentation of reported smoking. Given the recent failures of two major prospective birth cohorts (the US National Childrens' Study and the UK Life Study), our work shows a way forward for representative pre- and post-natal studies of births.
Medical Subject Headings
Birth certificates; Michigan Archive for Research on Child Health; Probability-proportional-to-size; Prospective study; Sampling weights
PubMed ID
40407221
ePublication
ePub ahead of print
