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Aust N Z J Public Health. 2011 Dec;35(6):557-63. doi: 10.1111/j.1753-6405.2011.00742.x. Epub 2011 Sep 12.

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

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  • 1National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australian Capital Territory.

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 1.24 cm (95% CI: 0.75-1.72) and 0.59 cm (0.26-0.92); weight was underestimated by 1.68 kg (-1.99- -1.36) and 1.02 kg (-1.24- -0.80); and BMI based on self-reported measures was underestimated by 0.90 kg/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.

© 2011 The Authors. ANZJPH © 2011 Public Health Association of Australia.

PMID:
22151163
[PubMed - indexed for MEDLINE]
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