The impact of using self-report versus objective measures of cardiometabolic conditions in epidemiologic research: a case study from India using data from the longitudinal aging study in India
Anti-conservative bias due to the use of self-reported measures of chronic cardiometabolic conditions in surveys conducted in low- and middle-income contexts may be common. Future studies may seek to quantify the magnitude of anticipated bias in existing data resources and use quantitative bias analysis to formally estimate the potential implications of misclassification.
Authors
- T. V. Sekher
- David E. Bloom (ORCID: https://orcid.org/0000-0003-3731-3345)
- Jinkook Lee (ORCID: https://orcid.org/0000-0002-6209-719X)
- Emma L. Nichols (ORCID: https://orcid.org/0000-0002-9005-3872)
- Peifeng Hu
Institutions
- University of Southern California (US)
- University of California, Los Angeles (US)
- International Institute for Population Sciences (IN)
- Harvard Global Health Institute (US)
Publication Details
- Journal
- Frontiers in Epidemiology
- Published
- 2025-07-25
- DOI
- https://doi.org/10.3389/fepid.2024.1372972
- Primary Topic
- Health disparities and outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Health and Family Welfare
- National Institutes of Health
- National Institute on Aging