4.2 Article

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

Journal

Publisher

WILEY
DOI: 10.1111/j.1753-6405.2011.00742.x

Keywords

BMI; weight; height; validity; Australia

Funding

  1. Cancer Council NSW
  2. National Health and Medical Research Council [585402]
  3. National Health and Medical Research Council

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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 middle-aged 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.

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