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Int J Obes Relat Metab Disord. 1996 Jul;20(7):644-50.

Validation study of self-reported measures of fat distribution.

Author information

1
Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis 55454-1015, USA.

Abstract

OBJECTIVE:

To determine the validity of self-reported body circumferences and indices of body fatness in comparison with the same variables measure by technicians.

DESIGN:

Cross-sectional survey.

SUBJECTS:

66 women aged 40-81 years.

MEASUREMENTS:

Self-reported weight and height and waist, hip, chest and bust circumferences, by mail questionnaire. The same measurements taken by a trained technician during a clinic visit. Derived variables of body mass index, waist-to-hip ratio, and conicity index, based on both self-reports and technician measurements.

RESULTS:

Mean differences between technician measurements and self measurements indicated that, on average, women tended to systematically underestimate their body circumferences. Age-adjusted Pearson correlations between technician measurements and self measurements ranged from 0.93 (95% confidence interval: 0.89, 0.96) for hips to 0.99 (95% Cl: 0.98, 0.99) for weight. For derived variables (quotients of measures), the highest agreement (r = 0.98, 95% Cl: 0.97, 0.99) was observed for body mass index (weight in kg/height in m2). The ratio of circumferences of the waist and hips was correlated less strongly (r = 0.76, 95% Cl: 0.63, 0.85). The correlation for conicity index, a measure of fat distribution that is independent of hip measurement variability, was 0.82 (95% Cl: 0.72, 0.88). Overall, accuracy of self measurements did not appear to vary according to age. There was an indication that with increasing values of weight and waist measurements, there was an increasing tendency for women to underestimate the measurement. This was also reflected in the accuracy of the derived variables body mass index and waist-to-hip ratio, but not the conicity index.

CONCLUSIONS:

These results indicate that self measurements of these anthropometric variables are highly accurate even when used to formulate derived variables, and are therefore appropriate for epidemiologic studies.

PMID:
8817358
[Indexed for MEDLINE]

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