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- W2944761142 abstract "Self-reported anthropometrics are often used as proxies for measured anthropometrics, but research has shown that heights and weights are often misreported. Using the Study on global AGEing and adult health, I analyze misreporting patterns of height, weight, and BMI in China, India, Russia, and South Africa. Adjustments of self-reported heights and weights using demographic, social, and anthropometric characteristics are evaluated and found to be useful in studying the distribution of anthropometrics within a population. Measured, self-reported, and adjusted BMI are then compared in logistic regression models on the reporting of health outcomes, as well as the resulting accuracy of individual prediction. When BMI is used as a continuous variable in models of health outcomes, measured, self-reported, and adjusted BMI produce similar coefficient estimates, and so self-reported data would be a natural choice because of its accessibility and convenience. In other applications, such as models using categorical BMI and individual prediction using either continuous or categorical BMI, self-reported data in lieu of measured data might not be accurate enough, but adjustments could serve as a potential compromise." @default.
- W2944761142 created "2019-05-16" @default.
- W2944761142 creator A5052585719 @default.
- W2944761142 date "2019-04-01" @default.
- W2944761142 modified "2023-09-23" @default.
- W2944761142 title "Biases in self-reported height and weight measurements and their effects on modeling health outcomes" @default.
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- W2944761142 doi "https://doi.org/10.1016/j.ssmph.2019.100405" @default.
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