Sarah E Barlow1,2, Meliha Salahuddin3,4, Casey Durand5, Stephen J Pont6, Deanna M Hoelscher5, Nancy F Butte7. 1. Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, USA. 2. Children's Health, Dallas, Texas, USA. 3. Department of Community Health, University of Texas Health Science Center at Tyler, Austin, Texas, USA. 4. Population Health, Office of Health Affairs, University of Texas System, Austin, Texas, USA. 5. Michael & Susan Dell Center for Healthy Living, University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Austin, Texas, USA. 6. Department of Pediatrics, Department of Population Health, University of Texas at Austin Dell Medical School, Austin, Texas, USA. 7. Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
Abstract
OBJECTIVE: This study aimed to examine the relation between change in different BMI metrics and change in adiposity over a 12-month weight management intervention. METHODS: Baseline and 12-month weights and heights from 399 children aged 2 to 12 years with BMI ≥ 85th percentile were used to calculate BMI, %BMIp95, %BMIp50, BMI z-score (BMIz), and modified BMI z-score (BMImz). Changes (Δ) in these measures were compared with changes in body fat percent (Δfat%) from bioelectrical impedance assessment. Correlation and regression models predicting associations between ΔBMI metrics and Δfat% were examined. RESULTS: A total of 89% of the cohort was Hispanic, and 34% had class 2 or 3 obesity. In models predicting Δfat% adjusting for age, sex, and weight category, R2 for ΔBMI, ΔBMIz, BMImz, Δ%BMIp95, and Δ%BMIp50 were 0.53, 0.38, 0.45, 0.53, and 0.54, respectively (all P < 0.001). Only the ΔBMIz model had an interaction with weight status. Among the models with the highest R2, age group and sex interacted with the Δ%BMIp95 model but not ΔBMI or ΔBMIp50 models. CONCLUSIONS: Longitudinal analyses demonstrate the utility of several BMI metrics other than z-score in capturing adiposity change consistently across a range of obesity severity. Characteristics of studied groups and interpretability could influence metric choice.
OBJECTIVE: This study aimed to examine the relation between change in different BMI metrics and change in adiposity over a 12-month weight management intervention. METHODS: Baseline and 12-month weights and heights from 399 children aged 2 to 12 years with BMI ≥ 85th percentile were used to calculate BMI, %BMIp95, %BMIp50, BMI z-score (BMIz), and modified BMI z-score (BMImz). Changes (Δ) in these measures were compared with changes in body fat percent (Δfat%) from bioelectrical impedance assessment. Correlation and regression models predicting associations between ΔBMI metrics and Δfat% were examined. RESULTS: A total of 89% of the cohort was Hispanic, and 34% had class 2 or 3 obesity. In models predicting Δfat% adjusting for age, sex, and weight category, R2 for ΔBMI, ΔBMIz, BMImz, Δ%BMIp95, and Δ%BMIp50 were 0.53, 0.38, 0.45, 0.53, and 0.54, respectively (all P < 0.001). Only the ΔBMIz model had an interaction with weight status. Among the models with the highest R2, age group and sex interacted with the Δ%BMIp95 model but not ΔBMI or ΔBMIp50 models. CONCLUSIONS: Longitudinal analyses demonstrate the utility of several BMI metrics other than z-score in capturing adiposity change consistently across a range of obesity severity. Characteristics of studied groups and interpretability could influence metric choice.