Tri-Ponderal Mass Index vs Body Mass Index in Estimating Body Fat During Adolescence

Peterson, Courtney M.; Su, Haiyan; Thomas, Diana M.; Heo, Moonseong; Golnabi, Amir H.; Pietrobelli, Angelo; Heymsfield, Steven B.

doi:10.1001/jamapediatrics.2017.0460

Cited by 190 publications

(259 citation statements)

References 21 publications

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“…In the absence of waist circumference data, we used the TMI, a new parameter found to estimate body fat levels more accurately than BMI, as first described by Peterson et al In our cohort, TMI values were found to be significantly higher among those with multiple cardiometabolic risk factors, clearly indicating that these patients had increased fat mass levels.…”

Section: Discussionmentioning

confidence: 96%

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Which predictors differentiate between obese children and adolescents with cardiometabolic complications and those with metabolically healthy obesity?

et al. 2018

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Section: Discussionmentioning

confidence: 96%

“…BMI was calculated as weight in kilograms divided by height in meters squared. Tri‐ponderal mass index (TMI) was calculated as weight divided by height cubed.…”

Section: Methodsmentioning

confidence: 99%

Which predictors differentiate between obese children and adolescents with cardiometabolic complications and those with metabolically healthy obesity?

et al. 2018

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“…For example, Nevill et al demonstrated that scaling WC to body size was more accurate than traditional methods of predicting metabolic risk indicators in adults. Further, it was recently suggested that the tri‐ponderal index (TPI) should be a more accurate surrogate of body fat, and since body fat is strongly related to metabolic risk, the TPI could more suitably describe the association with metabolic risk indicators in the paediatric population. Thus, the purpose of the present study was to investigate the association of six different anthropometric markers (BMI, BMI z‐score, TPI, WC, WC/H, and WC/H adj ) with metabolic syndrome in children and adolescents to find the best suited index to predict metabolic risk.…”

Section: Introductionmentioning

confidence: 99%

Identifying the best body‐weight‐status index associated with metabolic risk in youth

Gomes

Nevill

Katzmarzyk

et al. 2018

Scandinavian Med Sci Sports

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This study investigated the association of six different anthropometric markers with metabolic syndrome to find the most suited to predict children at risk. Sample comprises 1324 Portuguese youth (701 girls, 623 boys), aged 10-17 years. Six anthropometric markers were included: body mass index (BMI), BMI z-score, tri-ponderal index (TPI), waist circumference (WC), WC/height ratio (WC/H), and WC/H adjusted ratio (WC/H ). A standardized metabolic risk score (zMR) was computed by summing of standardized values for fasting glucose, triglycerides, high-density lipoprotein cholesterol, and mean arterial blood pressure. The associations between zMR and anthropometric markers were assessed using univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis was used to identify the optimal values that best predict metabolic risk of each anthropometric marker. Among the studied predictors, BMI z-score, followed by BMI and WC, was most highly associated with zMR, while WC/H was the weakest predictor. ROC analyses showed significant AUCs for all markers, yet the discrimination was poor (AUCs from 0.60 to 0.68), with sensitivity ranging from 45.5% to 67.5% and specificity from 72.6% to 81.9%. The optimal cut-off values to predict metabolic risk were 1.62, 23.1 kg/m , 71.0 cm, 18.0 kg/m , 0.47, and 0.50, for BMI z-score, BMI, WC, TPI, WC/H, and WC/H , respectively. BMI z-score, followed by BMI and WC, were the most relevant anthropometric markers to predict metabolic risk in youth, while WC/H was the worst predictor. Results suggest that anthropometric markers should continue to be used as clinical tools to identify youth at risk.

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“…Furthermore, BMI itself might not be a suitable criterion in early childhood, a period characterized by rapid growth. The accuracy of other body fat indices such as youth triponderal mass index, which was introduced to estimate the fat level in young children, has not been confirmed . Secondly, the study outcome was obesity at age 15 years only, and did not include diabetes or other cardiovascular outcomes in adulthood, which would have required a much longer follow‐up period.…”

Section: Discussionmentioning

confidence: 99%

Association of maternal prepregnancy weight and early childhood weight with obesity in adolescence: A population‐based longitudinal cohort study in Japan

et al. 2020

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Summary Background The impact of birth weight and obesity in early childhood on obesity in adolescence remains unclear. Objectives To examine the association of overweight/obesity at age 15 years with birth weight, overweight/obesity in early childhood and overweight/obesity in mothers. Methods This population‐based retrospective cohort study used early childhood and school age health check‐up data of 1581 children in Japan, followed‐up until age 15 years. Generalized estimation equation analyses were used to investigate the association of overweight/obesity at age 15 years with low/high birth weight, overweight/obesity in 3 years of age and overweight/obesity in mothers. The cutoff points for all variables were defined by international criteria. Results Of 1581 mother‐child pairs, 130 (8.2%) children had low birth weight, while 93 (5.9%) and 167 (10.6%) were overweight/obese at age 3 and 15 years, respectively. Overweight/obesity at age 3 years and overweight/obesity in mothers were associated with overweight/obesity at age 15 years (adjusted odds ratio [aOR], 4.26; 95% confidence interval [CI]: 2.51–7.25 and (aOR, 2.46; 95% CI: 1.41–4.30). No association between low birth weight and overweight/obesity at age 15 years was observed. Conclusions Overweight/obesity in mothers and overweight/obesity at 3 years of age, but not birth weight, were associated with overweight/obesity at age 15 years.

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Tri-Ponderal Mass Index vs Body Mass Index in Estimating Body Fat During Adolescence

Cited by 190 publications

References 21 publications

Which predictors differentiate between obese children and adolescents with cardiometabolic complications and those with metabolically healthy obesity?

Which predictors differentiate between obese children and adolescents with cardiometabolic complications and those with metabolically healthy obesity?

Identifying the best body‐weight‐status index associated with metabolic risk in youth

Association of maternal prepregnancy weight and early childhood weight with obesity in adolescence: A population‐based longitudinal cohort study in Japan

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