Identifying the best body mass index metric to assess adiposity change in children.
OBJECTIVE
Although dual-energy X-ray absorptiometry (DEXA) is the preferred method to estimate adiposity, body mass index (BMI) is often used as a proxy. However, the ability of BMI to measure adiposity change among youth is poorly evidenced. This study explored which metrics of BMI change have the highest correlations with different metrics of DEXA change.


METHODS
Data were from the Quebec Adipose and Lifestyle Investigation in Youth cohort, a prospective cohort of children (8-10 years at recruitment) from Québec, Canada (n=557). Height and weight were measured by trained nurses at baseline (2008) and follow-up (2010). Metrics of BMI change were raw (ΔBMIkg/m(2) ), adjusted for median BMI (ΔBMIpercentage) and age-sex-adjusted with the Centers for Disease Control and Prevention growth curves expressed as centiles (ΔBMIcentile) or z-scores (ΔBMIz-score). Metrics of DEXA change were raw (total fat mass; ΔFMkg), per cent (ΔFMpercentage), height-adjusted (fat mass index; ΔFMI) and age-sex-adjusted z-scores (ΔFMz-score). Spearman's rank correlations were derived.


RESULTS
Correlations ranged from modest (0.60) to strong (0.86). ΔFMkg correlated most highly with ΔBMIkg/m(2) (r = 0.86), ΔFMI with ΔBMIkg/m(2) and ΔBMIpercentage (r = 0.83-0.84), ΔFMz-score with ΔBMIz-score (r = 0.78), and ΔFMpercentage with ΔBMIpercentage (r = 0.68). Correlations with ΔBMIcentile were consistently among the lowest.


CONCLUSIONS
In 8-10-year-old children, absolute or per cent change in BMI is a good proxy for change in fat mass or FMI, and BMI z-score change is a good proxy for FM z-score change. However change in BMI centile and change in per cent fat mass perform less well and are not recommended.
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
Lisa
L
Kakinami
Division of Endocrinology, Department of Pediatrics, CHU Sainte-Justine and Université de Montréal, Montreal, QC, Canada.
Mélanie
M
Henderson
Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland.
Arnaud
A
Chiolero
Population, Policy and Practice Programme, University College London Institute of Child Health, London, UK.
Tim J
TJ
Cole
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
Gilles
G
Paradis
D015502:Absorptiometry, Photon / Q000379:methods*; D050154:Adiposity / Q000502:physiology*; D000886:Anthropometry / Q000379:methods*; D015992:Body Mass Index; D002170:Canada; D002648:Child; D015331:Cohort Studies; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D063766:Pediatric Obesity / Q000175:diagnosis*; D011446:Prospective Studies