Abstract
BackgroundInvestigating the validity of the self-reported values of weight allows for the proper assessment of studies using questionnaire-derived data. The study examined the accuracy of gender-specific self-reported weight in a sample of adults. The effects of age, education, race and ethnicity, income, general health and medical status on the degree of discrepancy (the difference between self-reported weight and measured weight) are similarly considered.MethodsThe analysis used data from the US Third National Health and Nutrition Examination Survey. Self-reported and measured weights were abstracted and analyzed according to sex, age, measured weight, self-reported weight, and body mass index (BMI). A proportional odds model was applied.ResultsThe weight discrepancy was positively associated with age, and negatively associated with measured weight and BMI. Ordered logistic regression modeling showed age, race-ethnicity, education, and BMI to be associated with the degree of discrepancy in both sexes. In men, additional predictors were consumption of more than 100 cigarettes and the desire to change weight. In women, marital status, income, activity level, and the number of months since the last doctor's visit were important.ConclusionsPredictors of the degree of weight discrepancy are gender-specific, and require careful consideration when examined.
Highlights
The National Health Interview Surveys, one of the oldest US national health surveys used to obtain data on the health of the resident, civilian, non-institutionalized population of the United States relies on the question "About how much [do you] weigh without shoes?"
Kuczmarski et al.[9] examined the effect of age on the extent to which the body mass index (BMI) calculated from self-reported anthropometric information compared with estimates calculated from measured val
Investigating the validity of the self-reported values of weight allows for the proper assessment of studies using questionnaire-derived data
Summary
Investigating the validity of the self-reported values of weight allows for the proper assessment of studies using questionnaire-derived data. The study examined the accuracy of gender-specific self-reported weight in a sample of adults. The effects of age, education, race and ethnicity, income, general health and medical status on the degree of discrepancy (the difference between self-reported weight and measured weight) are considered. In some surveys and large epidemiologic studies, self-reported measurements of these characteristics may replace actual instrument-derived data. Kuczmarski et al.[9] examined the effect of age on the extent to which the body mass index (BMI) calculated from self-reported anthropometric information compared with estimates calculated from measured val-
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have