Abstract
BackgroundPrevalence rates for overweight and obesity based on self-reported height and weight are underestimated, whereas the prevalence rate for underweight is slightly overestimated. Therefore a correction is needed. Aim of this study is to apply correction procedures to the prevalence rates developed on basis of (self-reported and measured) data from the representative German National Health Interview and Examination Survey for Children and Adolescents (KiGGS) to (self-reported) data from the German Health Behaviour in School Aged Children (HBSC) study to determine whether correction leads to higher prevalence estimates of overweight and obesity as well as lower prevalence rates for underweight.MethodsBMI classifications based on self-reported and measured height and weight from a subsample of the KiGGS study (2,565 adolescents aged 11–15) were used to estimate two different correction formulas. The first and the second correction function are described. Furthermore, the both formulas were applied to the prevalence rates from the HBSC study (7,274 adolescents aged 11–15) which are based on self-reports collected via self-administered questionnaires.ResultsAfter applying the first correction function to self-reported data of the HBSC study, the prevalence rates of overweight and obesity increased from 5.5% to 7.8% (compared to 10.4% in the KiGGS study) and 2.7% to 3.8% (compared to 7.8% in the KiGGS study), respectively, whereas the corrected prevalence rates of underweight and severe underweight decreased from 8.0% to 6.7% (compared to 5.7% in the KiGGS study) and from 5.5% to 3.3% (compared to 2.4% in the KiGGS study), respectively. Application of the second correction function, which additionally considers body image, led to further slight corrections with an increase of the prevalence rates for overweight to 7.9% and for obese to 3.9%.ConclusionSubjective BMI can be used to determine the prevalence of overweight and obesity among children and adolescents. Where there is evidence of bias, the prevalence estimates should be corrected using conditional probabilities that link measured and subjectively assessed BMI from a representative validation study. These corrections may be improved further by considering body image as an additional influential factor.
Highlights
Prevalence rates for overweight and obesity based on self-reported height and weight are underestimated, whereas the prevalence rate for underweight is slightly overestimated
The prevalence rates of overweight and obesity increased from 5.5% to 7.8% and 2.7% to 3.8%, respectively, whereas the corrected prevalence rates of underweight and severe underweight decreased from 8.0% to 6.7%
The present study shows that the correction of subjectively estimated body mass index (BMI) with a correction formula developed on the basis of the representative KiGGS sample leads to more accurate prevalence rates for overweight and obesity
Summary
Prevalence rates for overweight and obesity based on self-reported height and weight are underestimated, whereas the prevalence rate for underweight is slightly overestimated. A former publication [13] presented two procedures to correct subjectively assessed BMI using data from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) which provides both self-reported and measured height and weight from a representative subsample [14]. This procedure can be applied to studies of adolescents in Germany in which weight, height and body image are determined by selfreport
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.