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Peer-reviewedCC BY-NC-NDSSM: Population Health

Data approaches for lifecourse research on early-life determinants of late-life health outcomes: opportunities, limitations, and tradeoffs

  • Eleanor Hayes-Larson1
  • Suhani Amin2
  • Emma Nichols3
  • Sara D. Adar4
  • Yao-Yi Chiang5
  • Sarah M. Flood6
  • Alden L. Gross7
  • Birgit Claus Henn8
  • Kayleigh P. Keller9
  • David Knapp10
  • Jinkook Lee11
  • Regina A. Shih12
3 more authors
  • Jordan Weiss13
  • Jennifer Weuve14
  • Katrina L. Kezios14
14 affiliations
  1. 1Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA; Corresponding author.
  2. 2Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
  3. 3Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA; Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
  4. 4Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
  5. 5Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA
  6. 6Life Course Center and IPUMS Center for Data Integration, University of Minnesota, Minneapolis, MN, USA
  7. 7Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
  8. 8Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
  9. 9Department of Statistics, Colorado State University, Fort Collins, CO, USA
  10. 10Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
  11. 11Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA; Department of Economics, University of Southern California, Los Angeles, CA, USA
  12. 12Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
  13. 13Optimal Aging Institute & Division of Precision Medicine, NYU Grossman School of Medicine, New York City, USA
  14. 14Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
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Abstract

Identifying determinants of late-life disease and pathology, ascertaining when they exert their greatest impact (e.g., childhood, adolescence, midlife), and understanding how these factors accumulate and interact over time to shape disease development are central goals of lifecourse research. However, data availability, especially for early-life risk factors, is often an obstacle to the identification of lifecourse determinants of late-life health outcomes and impedes understanding of how they influence risk over time. To guide researchers in designing studies of the effects of early-life exposures on late-life health, here we review key data sources and approaches for obtaining early-life exposure information. We first consider birth cohort studies—in which exposures and outcomes may be prospectively observed in the same participants across the lifecourse—and then review alternative approaches for recovering or integrating early-life information when it is not directly available within a study, including data linkages, retrospective data collection, and synthetic cohorts. We discuss the benefits and disadvantages of each approach, emphasizing their tradeoffs and the importance of matching the research question to the selected data. To aid in researcher decision-making, we also discuss the types of research questions each approach is best suited to address, present examples of successful implementation, and provide a decision flowchart with critical questions to guide selection of the optimal approach for obtaining early-life data for one's study. Careful attention to these tradeoffs and considerations when undertaking lifecourse research will help advance understanding of how exposures over the lifecourse broadly shape late-life health.

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Cite

BibTeXRIS
BibTeX
@article{hayeslarson2026data,
  title = {{Data approaches for lifecourse research on early-life determinants of late-life health outcomes: opportunities, limitations, and tradeoffs}},
  author = {Eleanor Hayes-Larson and Suhani Amin and Emma Nichols and Sara D. Adar and Yao-Yi Chiang and Sarah M. Flood and Alden L. Gross and Birgit Claus Henn and Kayleigh P. Keller and David Knapp and Jinkook Lee and Regina A. Shih and Jordan Weiss and Jennifer Weuve and Katrina L. Kezios},
  journal = {SSM: Population Health},
  year = {2026},
  month = oct,
  doi = {10.1016/j.ssmph.2026.101985},
  url = {https://doi.org/10.1016/j.ssmph.2026.101985},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Data approaches for lifecourse research on early-life determinants of late-life health outcomes: opportunities, limitations, and tradeoffs
AU  - Eleanor Hayes-Larson
AU  - Suhani Amin
AU  - Emma Nichols
AU  - Sara D. Adar
AU  - Yao-Yi Chiang
AU  - Sarah M. Flood
AU  - Alden L. Gross
AU  - Birgit Claus Henn
AU  - Kayleigh P. Keller
AU  - David Knapp
AU  - Jinkook Lee
AU  - Regina A. Shih
AU  - Jordan Weiss
AU  - Jennifer Weuve
AU  - Katrina L. Kezios
PY  - 2026
DA  - 2026/10/19
JO  - SSM: Population Health
DO  - 10.1016/j.ssmph.2026.101985
UR  - https://doi.org/10.1016/j.ssmph.2026.101985
AB  - Identifying determinants of late-life disease and pathology, ascertaining when they exert their greatest impact (e.g., childhood, adolescence, midlife), and understanding how these factors accumulate and interact over time to shape disease development are central goals of lifecourse research. However, data availability, especially for early-life risk factors, is often an obstacle to the identification of lifecourse determinants of late-life health outcomes and impedes understanding of how they influence risk over time. To guide researchers in designing studies of the effects of early-life exposures on late-life health, here we review key data sources and approaches for obtaining early-life exposure information. We first consider birth cohort studies—in which exposures and outcomes may be prospectively observed in the same participants across the lifecourse—and then review alternative approaches for recovering or integrating early-life information when it is not directly available within a study, including data linkages, retrospective data collection, and synthetic cohorts. We discuss the benefits and disadvantages of each approach, emphasizing their tradeoffs and the importance of matching the research question to the selected data. To aid in researcher decision-making, we also discuss the types of research questions each approach is best suited to address, present examples of successful implementation, and provide a decision flowchart with critical questions to guide selection of the optimal approach for obtaining early-life data for one's study. Careful attention to these tradeoffs and considerations when undertaking lifecourse research will help advance understanding of how exposures over the lifecourse broadly shape late-life health.
SN  - 2352-8273
ER  -