Abstract
Objective. A number of measures of childhood adiposity are in use, but all are relatively imprecise and prone to bias. We constructed an adiposity index (AI) using a number of different measures. Methods. Detailed body composition data on 460 of the Gateshead Millennium Study cohort at the age of 6–8 years were analysed. The AI was calculated using factor analysis on age plus thirteen measures of adiposity and/or size. Correlations between these variables, the AI, and more traditional measures of adiposity in children were investigated. Results. Based on the factor loading sizes, the first component, taken to be the AI, consisted mainly of measures of fat-mass (the skinfold measurements, fat mass score, and waist circumference). The second comprised variables measuring frame size, while the third consisted mainly of age. The AI had a high correlation with body mass index (BMI) (rho = 0.81). Conclusions. While BMI is practical for assessing adiposity in children, the AI combines a wider range of data related to adiposity than BMI alone and appears both valid and valuable as a research tool for studies of childhood adiposity. Further research is necessary to investigate the utility of AI for research in other samples of children and also in adults.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
