Online Program

279283
Identifying the best metric to assess adiposity change in children: A comparison between changes in dual-energy x-ray absorptiometry (DEXA) and body mass index


Tuesday, November 5, 2013

Lisa Kakinami, PhD, Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
Melanie Henderson, MD, Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
Arnaud Chiolero, MD, PhD, University of Lausanne, Switzerland
Tim Cole, PhD, MRC Centre of Epidemiology for Child Health, United Kingdom
Gilles Paradis, MD, Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
Background: Accurately measuring childhood adiposity change has important clinical management and public health surveillance implications. Dual-energy X-ray absorptiometry (DEXA) is the method of choice to estimate fat mass, but is cost-prohibitive and proxies such as body mass index (BMI) are oftentimes used. However, limited data exist on the validity of BMI metrics to measure adiposity change among youth. Objective: Compare correlations between different BMI change metrics with different DEXA change metrics. Methods: Data were from QUALITY, a prospective cohort of children 8-10 years-old at recruitment from Qu├ębec, Canada (n=557). Height and weight were measured by trained nurses at baseline (2008) and follow-up (2010). Metrics of BMI change were: raw unit, adjusted for median BMI (BMI%), and age-sex-adjusted with the US CDC growth curves expressed as Z-scores (BMIz) or percentiles (BMI%ile). Metrics of DEXA change were raw unit (total fat mass: (TFM), percent (TFM%), height-adjusted (fat mass index; FMI) and internally age-sex-adjusted (TFMz). Spearman rank correlations between BMI change metrics and DEXA change metrics were derived. Results: Correlations ranged from 0.59 to 0.86. TFM change correlated most highly with BMI change (r=0.86), TFM% change with BMI% and BMIz changes (r=0.65), TFMz change with BMI% change (r=0.80), and FMI change with BMI and BMI% changes (r=0.83). Correlations with BMI%ile change were consistently the lowest for all DEXA change metrics. Conclusions: In 8-10 year-old children followed-up over 2 years, changes in BMI (raw unit) or in BMI% are the best proxies for changes in TFM or in FMI. BMI%ile performs less well.

Learning Areas:

Chronic disease management and prevention
Epidemiology
Public health or related research

Learning Objectives:
Describe the different body mass index (BMI) change metrics and Dual-energy X-ray absorptiometry (DEXA) change metrics used in youth populations. Analyze the correlation between different BMI change metrics with different DEXA change metrics. Differentiate the correlations based on demographic or health characteristics. Discuss the clinical management, public health surveillance, and research implications of using BMI change metrics as proxies for fat mass measured by DEXA.

Keyword(s): Pediatrics, Methodology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have a PhD in Epidemiology and have been studying the methodological tools used in pediatric clinical care and research as part of my postdoctoral research.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.