D Faeh1, J Braun, M Bopp. 1. Institute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland. david.faeh@ifspm.uzh.ch
Abstract
BACKGROUND/ OBJECTIVE: Studies using self-report may underestimate obesity prevalence because participants tend to overestimate their height, underestimate their weight and thus seriously underestimate their Body Mass Index (BMI). In order to find ways to adjust for this misestimation, we tested two correction methods for self-report by comparing the derived obesity prevalence rates with those based on measured height and weight. METHODS: We used individual data from six studies based on self-reported BMI (1980-2007, n = 46589) and from five studies based on measured BMI (1977-2004, n = 20130). All studies were population-based samples and carried out in Switzerland. We limited to men and women aged 35 to 74 years. Obesity was defined as BMI > or =30 kg/m2. For correction method one, we used a lower BMI cutoff of 29.2 kg/m2 (for both sexes) for the definition of obesity; for method two, we adjusted weight and height (respecting age and sex) using equations that were derived from another population. Results were age-standardised. Differences were measured with a logistic regression model considering random effects. RESULTS: Adjustment of height and weight (method two) substantially approximated the BMI distribution based on unadjusted self-report to the BMI distribution based on measurement. In 2002/2003, obesity prevalence obtained with method two (men and women respectively: 16.3% and 13.0%) tended to be more similar to measured obesity prevalence (16.4% and 13.9%) than obesity prevalence obtained with method one (13.8% and 11.0%). CONCLUSION: Equation adjustment of self-reported weight and height provides an approximation of the real (measured) BMI distribution by sex and age and has advantages over the use of a universal lower cutoff level to adjust for self-report. However, to appropriately adjust for self-report, a Swiss-specific equation should be developed based on measured and self-reported heights and weights of the same individuals.
BACKGROUND/ OBJECTIVE: Studies using self-report may underestimate obesity prevalence because participants tend to overestimate their height, underestimate their weight and thus seriously underestimate their Body Mass Index (BMI). In order to find ways to adjust for this misestimation, we tested two correction methods for self-report by comparing the derived obesity prevalence rates with those based on measured height and weight. METHODS: We used individual data from six studies based on self-reported BMI (1980-2007, n = 46589) and from five studies based on measured BMI (1977-2004, n = 20130). All studies were population-based samples and carried out in Switzerland. We limited to men and women aged 35 to 74 years. Obesity was defined as BMI > or =30 kg/m2. For correction method one, we used a lower BMI cutoff of 29.2 kg/m2 (for both sexes) for the definition of obesity; for method two, we adjusted weight and height (respecting age and sex) using equations that were derived from another population. Results were age-standardised. Differences were measured with a logistic regression model considering random effects. RESULTS: Adjustment of height and weight (method two) substantially approximated the BMI distribution based on unadjusted self-report to the BMI distribution based on measurement. In 2002/2003, obesity prevalence obtained with method two (men and women respectively: 16.3% and 13.0%) tended to be more similar to measured obesity prevalence (16.4% and 13.9%) than obesity prevalence obtained with method one (13.8% and 11.0%). CONCLUSION: Equation adjustment of self-reported weight and height provides an approximation of the real (measured) BMI distribution by sex and age and has advantages over the use of a universal lower cutoff level to adjust for self-report. However, to appropriately adjust for self-report, a Swiss-specific equation should be developed based on measured and self-reported heights and weights of the same individuals.
Authors: Edward L Murphy; Karen Schlumpf; David J Wright; Ritchard Cable; John Roback; Ronald Sacher; Michael P Busch Journal: Public Health Nutr Date: 2012-01-10 Impact factor: 4.022