Validity of self-reported height and weight and derived body mass index in middle-aged and elderly individuals in Australia

Suan Peng Ng, Rosemary Korda, Mark Clements, Isabel Latz, Adrian Bauman, Hilary Bambrick, Bette Liu, Kris Rogers, Nicol Herbert, Emily Banks*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

138 Citations (Scopus)

Abstract

Background: Body mass index (BMI) is an important measure of adiposity. While BMI derived from self-reported data generally agrees well with that derived from measured values, evidence from Australia is limited, particularly for the elderly. Methods: We compared self-reported with measured height and weight in a random sample of 608 individuals aged ≥45 from the 45 and Up Study, an Australian population-based cohort study. We assessed degree of agreement and correlation between measures, and calculated sensitivity and specificity to quantify BMI category misclassification. Results: On average, in males and females respectively, height was overestimated by 1.24cm (95% CI: 0.75-1.72) and 0.59cm (0.26-0.92); weight was underestimated by 1.68kg (-1.99-1.36) and 1.02kg (-1.24-0.80); and BMI based on self-reported measures was underestimated by 0.90kg/m2 (-1.09-0.70) and 0.60 kg/m2 (-0.75-0.45). Underestimation increased with increasing measured BMI. There were strong correlations between self-reported and measured height, weight and BMI (r=0.95, 0.99 and 0.95, respectively, p<0.001). While there was excellent agreement between BMI categories from self-reported and measured data (kappa=0.80), obesity prevalence was underestimated. Findings did not differ substantially between middleaged and elderly participants. Conclusions: Self-reported data on height and weight quantify body size appropriately in middle-aged and elderly individuals for relative measures, such as quantiles of BMI. However, caution is necessary when reporting on absolute BMI and standard BMI categories, based on self-reported data, particularly since use of such data is likely to result in underestimation of the prevalence of obesity.

Original languageEnglish
Pages (from-to)557-563
Number of pages7
JournalAustralian and New Zealand Journal of Public Health
Volume35
Issue number6
DOIs
Publication statusPublished - Dec 2011

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