Mobile device data for the study of miscarriage and its causes
Miscarriage is a common pregnancy complication that is difficult to study. Using information on 580,000 US pregnancies from a menstrual- and pregnancy-tracking app, we demonstrate that mobile device data can detect miscarriage and replicate patterns of miscarriage risk found in high-quality Norwegian administrative data and in US clinical cohorts. App data may greatly expand research on miscarriage, including the contributions of "upstream" social, economic, and environmental factors that have eluded study.
Authors
- Lindsay M. Cannon (ORCID: https://orcid.org/0000-0001-8020-7148)
- Katie Noddin (ORCID: https://orcid.org/0000-0002-8123-5930)
- Sungsik Hwang
- Jenna Nobles (ORCID: https://orcid.org/0000-0001-5175-4265)
- Allen J. Wilcox (ORCID: https://orcid.org/0000-0002-3376-1311)
- Shannon Malloy
Institutions
- University of Wisconsin–Madison (US)
- National Institute of Environmental Health Sciences (US)
- IQVIA (United States) (US)
- University of California, Berkeley (US)
Publication Details
- Journal
- npj Women s Health
- Published
- 2026-03-02
- DOI
- https://doi.org/10.1038/s44294-026-00129-8
- Primary Topic
- Mobile Health and mHealth Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of Child Health and Human Development
- Eunice Kennedy Shriver National Institute of Child Health and Human Development