Revealing the burden of obesity using weight histories
Open accessAbstract
Significance: There is substantial uncertainty about the association between obesity and mortality. A major issue is the treatment of reverse causation, a phrase referring to the loss of weight among people who become ill. Weight histories are vital to addressing reverse causality, but few studies incorporate them. Here we introduce nationally representative data on lifetime maximum weight to distinguish individuals who were never obese from those who were formerly obese and lost weight. We formally investigate the performance of various models, finding that models that incorporate history perform better than the conventional approach based on a single observation of weight at the time of survey. We conclude that the burden of obesity is likely to be greater than is commonly appreciated.
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- Authors
- Stokes, A., & Preston, S. H.
- Affiliations
- Boston University (US)
- University of Pennsylvania (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2016-01-04
- Volume
- 113
- Issue
- 3
- Pages
- 572-577
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4725464
- OpenAlex
- W2227287239
- Cited by
- 99
- References
- 66
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 11 · 2023: 11 · 2022: 12 · 2021: 4 · 2020: 7 · 2019: 9 · 2018: 14 · 2017: 15 · 2016: 10
- FWCI
- 15.86
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HHS | NIH | National Institute on Aging (R01AG040212)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Oncology › Cancer Risks and Factors
- Health Sciences › Health Professions › Pharmacy › Obesity and Health Practices
- Keywords
- obesity, mortality, weight history, weight loss, body mass index, overweight, NHANES
- MeSH terms
- Aged, Aged, 80 and over, Body Weight, Diabetes Mellitus, Humans, Middle Aged, Obesity, Reference Standards, United States, Body Mass Index, Prevalence, Proportional Hazards Models, Cost of Illness
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