Validation of self-reported anthropometrics in the Adventist Health Study 2
1 Dept. of Preventive Medicine and Public Health, School of Medicine, University of Navarra, Pamplona, Spain
2 Dept. of Nutrition, School of Public Health, Loma Linda University, Loma Linda, CA, USA
3 Dept. of Epidemiology and Statistics. School of Public Health, Loma Linda University, Loma Linda, CA, USA
BMC Public Health 2011, 11:213 doi:10.1186/1471-2458-11-213Published: 5 April 2011
Relying on self-reported anthropometric data is often the only feasible way of studying large populations. In this context, there are no studies assessing the validity of anthropometrics in a mostly vegetarian population. The objective of this study was to evaluate the validity of self-reported anthropometrics in the Adventist Health Study 2 (AHS-2).
We selected a representative sample of 911 participants of AHS-2, a cohort of over 96,000 adult Adventists in the USA and Canada. Then we compared their measured weight and height with those self-reported at baseline. We calculated the validity of the anthropometrics as continuous variables, and as categorical variables for the definition of obesity.
On average, participants underestimated their weight by 0.20 kg, and overestimated their height by 1.57 cm resulting in underestimation of body mass index (BMI) by 0.61 kg/m2. The agreement between self-reported and measured BMI (as a continuous variable), as estimated by intraclass correlation coefficient, was 0.97. The sensitivity of self-reported BMI to detect obesity was 0.81, the specificity 0.97, the predictive positive value 0.93, the predictive negative value 0.92, and the Kappa index 0.81. The percentage of absolute agreement for each category of BMI (normoweight, overweight, and obese) was 83.4%. After multivariate analyses, predictors of differences between self-reported and measured BMI were obesity, soy consumption and the type of dietary pattern.
Self-reported anthropometric data showed high validity in a representative subsample of the AHS-2 being valid enough to be used in epidemiological studies, although it can lead to some underestimation of obesity.