Validation of obesity based on self-reported data in Spanish women participants in breast cancer screening programmes
1 Cancer and Environmental Epidemiology Unit, National Centre for Epidemiology, Carlos III Institute of Health, Madrid, Spain
2 Department of Preventive Medicine, Puerta de Hierro Majadahonda University Teaching Hospital, Madrid, Spain
3 Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain
4 Castile-León Breast Cancer Screening Programme, General Directorate of Public Health (Gerencia Regional de Salud - SACyL), Castile-León, Spain
5 Balearic Islands Breast Cancer Screening Programme, Health Promotion for Women and Children, General Directorate of Public Health & Participation, Regional Authority for Health & Consumer Affairs, Balearic Islands, Spain
6 Galician Breast Cancer Screening Programme, Galician Regional Health Authority, Pamplona, Spain
7 Aragon Breast Cancer Screening Programme, Aragon Health Service, Zaragoza, Spain
8 Cancer Prevention and Control Unit, Catalonian Institute of Oncology (Institut Català d'Oncologia-ICO), Barcelona, Spain
9 Valencian Breast Cancer Screening Programme, General Directorate of Public Health, Valencia, Spain
10 Public Health Research Centre (Centro Superior de Investigación en Salud Pública -CSISP), Valencia, Spain
11 Navarre Breast Cancer Screening Programme, Public Health Institute, Pamplona, Spain
BMC Public Health 2011, 11:960 doi:10.1186/1471-2458-11-960Published: 30 December 2011
Measurement of obesity using self-reported anthropometric data usually involves underestimation of weight and/or overestimation of height. The dual aim of this study was, first, to ascertain and assess the validity of new cut-off points, for both overweight and obesity, using self-reported Body Mass Index furnished by women participants in breast cancer screening programmes, and second, to estimate and validate a predictive model that allows recalculate individual BMI based on self-reported data.
The study covered 2927 women enrolled at 7 breast cancer screening centres. At each centre, women were randomly selected in 2 samples, in a ratio of 2:1. The larger sample (n = 1951) was used to compare the values of measured and self-reported weight and height, to ascertain new overweight and obesity cut-off points with self-reported data, using ROC curves, and to estimate a predictive model of real BMI using a regression model. The second sample (n = 976) was used to validate the proposed cut-off points and the predictive model.
Whereas reported prevalence of obesity was 19.8%, measured prevalence was 28.2%. The sensitivity and specificity of this classification would be maximised if the new cut-off points were 24.30 kg/m2 for overweight and 28.39 kg/m2 for obesity. The probability of classifying women correctly in their real weight categories on the basis of these points was 82.5% in the validation sample. Sensitivity and specificity for determining obesity using the new cut-off point in the validation sample were 90.0% and 92.3% respectively. The predictive model for real BMI included the self-reported BMI, age and educational level (university studies vs lower levels of education). This model succeeded in correctly classifying 90.5% of women according to BMI categories, but its performance was similar to that obtained with the new cut-off points.
Quantification of self-reported obesity entails a considerable underestimation of this problem, thereby questioning its validity. The new cut-off points established in this study and the predictive equation both allow for more accurate estimation of these prevalences.