Tri-ponderal Mass Index Research Articles

Tri-Ponderal Mass Index vs body Mass Index in discriminating central obesity and hypertension in adolescents with overweight

Background and aimsRecently, it has been hypothesized that Tri-Ponderal Mass Index (TMI) may be a valid alternative to Body Mass Index (BMI) when measuring body fat in adolescents. We aimed to verify whether TMI has better accuracy than BMI in discriminating central obesity and hypertension in adolescents with overweight. Methods and ResultsThis monocentric and retrospective cross-sectional study included 3749 pupils, 1889 males and 1860 females, aged 12–13. BMI (kg/m2) was calculated and expressed as percentiles and as z-scores. TMI (kg/m3) was calculated, and we used pre-defined cut-off previously proposed by Peterson et al.. For central obesity we adopted the Waist-to-Height Ratio (WHtR) discriminatory value of 0.5. Hypertension was defined as blood pressure ≥95th percentile of age- sex-, and height-specific references recommended by NHBPEP Working Group. The discriminant ability of TMI, BMI and BMI z-score, with respect to central obesity and hypertension, was investigated using non-parametric receiver operating characteristic analysis.The overall misclassification rate for central obesity was 8.88% for TMI vs 14.10% for BMI percentiles and vs 14.92% for BMI z-scores (P < 0.001). The overall misclassification rate for hypertension was 7.50% for TMI vs 22.03% for BMI percentiles and vs 25.19% for BMI z-scores (P < 0.001). ConclusionTMI is a superior body fat index and it could discriminate body fat distribution more accurately than BMI. This supports the use of TMI, in association with WHtR, to characterize adolescents with overweight and high cardio-metabolic risk. Our analysis needs to be extended to other ethnic groups and replicated in a wider age range and in longitudinal studies.

Diagnostic accuracy of the tri-ponderal mass index in identifying the unhealthy metabolic obese phenotype in obese patients

IntroductionThe metabolically healthy obese phenotype (FOMS) defines obese patients who have preserved insulin sensitivity and absence of metabolic complications. This phenotype is associated with a lower risk of cardiovascular disease and type 2 diabetes in adulthood. ObjectivesTo determine the prevalence of FOMS and the obese phenotype with metabolic risk (FORM) in a cohort of obese children and adolescents and to establish the predictive capacity of the tri-ponderal mass index (TMI) and other anthropometric parameters in order to identify these patients. Patients and methodsA cross-sectional study was conducted on 239 obese patients (125 males) from 8 to 18 years of age. Grade 3 obesity was present in 45.9% of the patients. ROC curves were used to find the best cut-off point for: TMI, body mass index (BMI), BMI z-score (BMIzs), and waist/height index (WHI). FOMS components: plasma blood glucose, plasma triglycerides, HDL-cholesterol, and blood pressure. ResultsThe prevalence of FOMS in the study cohort was 37.6%. No differences between genders were observed, and it was increasing with the age and the level of obesity. The TMI has a sensitivity of 75.8 and a specificity of 42.2 to identify the FORM patients. The best cut-off point for TMI is 18.7 kg/m3, for BMI it was 30.4 kg/m2, for BMIzs +3.5 SD, and 0.62 for WHI. ConclusionsThe diagnostic accuracy of TMI in identifying obese adolescents with metabolic risk was similar to BMI and WHI. However, the TMI makes it easier and simplifies the classification of the obesity level in both genders.

Identification of the most appropriate existing anthropometric index for home-based obesity screening in children and adolescents

ObjectivesHome-based self-screening and monitoring for obesity is particularly valuable for the prevention and control of chronic diseases. This study aimed to identify an anthropometric index suitable for home-based obesity screening in children and adolescents. Study designThe design of this study is a cross-sectional study. MethodsA total of 14,042 students (6–17 years) from the Qibao Community, Minhang District, Shanghai, were studied in 2018. The percentage body fat (PBF), height, weight, waist circumference (WC) and hip circumference were measured. Body mass index (BMI), triponderal mass index (TMI), body adiposity index (BAI), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Partial correlation analysis was used to evaluate the relationships between these indices and PBF, and receiver operating characteristic (ROC) curves were used to evaluate their performance for obesity screening. ResultsBMI, TMI, WC and WHtR were found to strongly correlate with PBF (r ≥ 0.830, all P < 0.001). The optimal index for obesity screening in children (6–11 years) was BMI (area under the ROC curve [AUC] = 0.980 for boys and 0.981 for girls) and in adolescents (12–17 years) was TIM (AUC = 0.976 for boys and 0.945 for girls); however, the optimal cut-off values for BMI and TMI differed among the subgroups. The ROC curve analysis showed that WHtR had similar cut-off values in each subgroup (0.45 for boys of 6–11 years and 0.43 for the other subgroups), excellent performance in children (AUC>0.90) and good performance in adolescents (AUC = 0.960 for girls and 0.878 for boys). ConclusionsOwing to its accuracy and stable cut-off value for defining obesity, WHtR should be recommended for home-based obesity screening in children and adolescents.

Clustering Patterns of Physical Fitness, Physical Activity, Sedentary, and Dietary Behavior among School Children.

Background: Some healthy lifestyle behaviors may have a greater impact on childhood obesity in combination, compared to the independent effects of those behaviors in an isolated manner. The present study aimed to identify the different healthy lifestyle patterns of children according to their physical fitness, physical activity (PA) patterns, screen time, and adherence to the Mediterranean Diet, as well as to examine the association between anthropometric indicators and the membership to a certain cluster. Methods: A final sample of 353 Spanish school children (45.9% females) from the Region of Murcia (Spain) was included in this study (aged 6-13). First, we conducted a hierarchical cluster analysis using Ward's method; based on squared Euclidean distances. Second, we used the k-means cluster analysis to get the final cluster solution. Results: Three different clusters were established: Cluster 1 [high cardiorespiratory fitness (CRF), PA, and Mediterranean Diet], Cluster 2 (low CRF, PA, and Mediterranean Diet + high muscular strength), and Cluster 3 (low physical fitness and PA). Cluster 3 had negative values in all the health-related variables analyzed. Regarding the anthropometric parameters analyzed (BMI, tri-ponderal mass index, waist-to-height ratio, and body fat percentage), Cluster 3 presented the highest values in all anthropometric parameters than the other two clusters (p < 0.001), while Cluster 1 showed the lowest values. Conclusions: The study has identified three clusters respect to health-related variables with the higher prevalence in the cluster established as the unhealthiest lifestyle. Also, cluster classification is associated to obesity indicators such as BMI, tri-ponderal mass index, waist-to-height ratio, and body fat percentage.

Pediatric obesity-related non-alcoholic fatty liver disease: waist-to-height ratio best anthropometrical predictor.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disorder in pediatric obesity. Our study aims to identify a predictive anthropometrical measure for NAFLD in obese children. We retrospectively enrolled children and adolescents with obesity. Physical, biochemical, and ultrasound assessments were available. ROC curve tests were performed to identify the best predictor of NAFLD among waist-to-height ratio (WHR), BMI z-score, and triponderal mass index (TMI, an anthropometric index recently associated with increased adiposity in children). Subsequently, a cut-off value was identified. In total, 1900 children and adolescents (1011 with NAFLD) were included. WHR (AUC 0.62, 95% CI 0.59-0.64) was the best predictor of NAFLD compared to BMI z-score (AUC 0.58, 95% CI 0.55-0.60) and TMI (AUC 0.58, 95% CI 0.55-0.61). WHR ≥ 0.53 in boys and 0.63 in girls displayed the best sensitivity and specificity for NAFLD presence. In addition, children with high WHR showed a significantly higher risk of NAFLD (boys: OR 2.43, 95% CI 1.61-3.68, p < 0.0001; girls: OR 1.92, 95% CI 1.58-2.34, p < 0.0001) and elevated ALT (OR 5.71, 95% CI 2.09-15.56, p = 0.0007; girls: OR 2.16, 95% CI 1.70-2.74, p < 0.0001) independent of covariates. WHR might represent a good anthropometric tool to candidate children and adolescents to NAFLD screening. WHR cut-off differs according to sex, being lower in boys than girls. Waist-to-height ratio is a better predictor of non-alcoholic fatty liver disease risk compared to other anthropometric measures in obese children and adolescents. The predictive cut-off of waist-to-height ratio differs between boys and girls, being lower in boys than girls. The use of waist-to-height ratio measurement and its cut-off in clinical practice might help clinician in identifying obese children and adolescents at risk of non-alcoholic fatty liver disease.

Evaluation of Different Adiposity Indices and Association with Metabolic Syndrome Risk in Obese Children: Is there a Winner?

Body shape index (ABSI) and triponderal mass index (TMI) have been recently associated with cardiovascular risk in adults. A cross-sectional study was conducted to evaluate the relationship between different anthropometric adiposity indexes and metabolic syndrome (MetS) in Caucasian obese children and adolescents. Consecutive obese children aged ≥7 years have been enrolled. Anthropometric parameters, body composition (by bioelectrical impedance), and systolic and diastolic blood pressure have been measured. Fasting blood samples have been analyzed for lipids, insulin, glucose. A multivariate logistic regression analyses, with body mass index z-score, waist to height ratio, ABSI z-score, TMI, conicity index as predictors for MetS (IDEFICS and IDF criteria according to age) has been performed. Four hundred and three (179 boys and 224 girls) obese children, aged 7–20 years, have been evaluated. When we explored the joint contribution of each anthropometric and adiposity index of interest and BMIz on the risk of MetS, we found that the inclusion of ABSIz improved the prediction of MetS compared to BMIz alone. ABSI-BMI can be a useful index for evaluating the relative contribution of central obesity to cardiometabolic risk in clinical management of obese children and adolescents.

Accuracy of Different Indexes of Body Composition and Adiposity in Identifying Metabolic Syndrome in Adult Subjects with Prader-Willi Syndrome.

(1) Objective: To compare the accuracy of different indexes of adiposity and/or body composition in identifying metabolic syndrome (MetS) in adult patients suffering from Prader‒Willi syndrome (PWS). (2) Study Design: One hundred and twenty PWS patients (69 females and 51 males), aged 29.1 ± 9.4 years, body mass index (BMI) 36.7 ± 9.9, were evaluated. The following indexes were assessed in each subject: body mass index (BMI), fat-free mass index (FFMI), fat mass index (FMI), tri-ponderal mass index (TMI), waist-to-height ratio (WtHR) and the body mass fat index (BMFI), which adjusts the BMI for the percentage of body fat and waist circumference. Thereafter, a threshold value adjusted for age and sex, which could identify MetS, was calculated for each index. (3) Results: A significant correlation was found among all indexes (p < 0.0001 for all). However, when the area under the curve (AUC) was compared, BMFI performed better than FMI (p < 0.05) and BMI better than TMI (p < 0.05), but only in females. (4) Conclusions: Besides small differences, all the indexes taken into consideration seem to have the same ability to identify MetS in adults with PWS. Consequently, the most easily calculated index, i.e., BMI, should be considered as the best choice. The use of thresholds appropriate for sex and age can further improve its accuracy.

Precisión diagnóstica del índice de masa triponderal (kg/m3) para identificar el fenotipo de riesgo metabólico en pacientes obesos

The metabolically healthy obese (MHO) phenotype defines obese patients who have preserved insulin sensitivity and absence of metabolic complications. This phenotype is associated with a lower risk of cardiovascular disease and type2 diabetes in adulthood. To determine the prevalence of MHO and the metabolically unhealthy obesity (MUO) phenotype in a cohort of obese children and adolescents and to establish the predictive capacity of the tri-ponderal mass index (TMI) and other anthropometric parameters in order to identify these patients. A cross-sectional study was conducted on 239 obese patients (125males) from 8 to 18years of age. Grade3 obesity was present in 45.9% of the patients. ROC curves were used to find the best cut-off point for: TMI, body mass index (BMI), BMI z-score (BMIzs), and waist/height index (WHI). MHO components: plasma blood glucose, plasma triglycerides, HDL-cholesterol, and blood pressure. The prevalence of MUO in the study cohort was 62.4%. No differences between genders were observed, and it was increasing with the age and obesity degree. The TMI has a sensitivity of 75.8 and a specificity of 42.2 to identify the MUO patients. The best cut-off point for TMI is 18.7kg/m3, for BMI it was 30.4kg/m2, for BMIzs +3.5SD, and 0.62 for WHI. The diagnostic accuracy of TMI in identifying obese adolescents with metabolic risk was similar to BMI and WHI. However, the TMI is much simpler to use and simplifies the categorization of the obesity in both genders.

Validity and accuracy of body fat prediction equations using anthropometrics measurements in adolescents.

The pediatric relative fat mass (RFM) has been recently presented and validated as an index for estimating percentage body fat (%BF) in North American children and adolescents. Similar to body mass index (BMI) and tri-ponderal mass index (TMI), RFM uses anthropometric measures (i.e., weight, height and waist circumference) to estimate body composition. The primary purpose of this study was to validate the newly developed RFM equation for %BF prediction in Southern Brazilian adolescents; as secondary objective, we compared %BF estimation from BMI- and TMI-derived equations. A total of 631 individuals (434 boys) aged 11 to 18 were analyzed. Bland-Altman analyses were used to determine concordance between predicted equations and %BF measured by DXA; results are presented using mean difference (i.e., bias) and standard deviation. Sensitivity and specificity were calculated for %BF percentile classifications. RFM underestimated %BF in 65.2% of boys (-4.3 ± 2.8%) and 84.8% of girls (-5.3 ± 2.7%). In contrast, TMI overestimated %BF in 62.9% of boys (4.0 ± 2.9%) and 56.3% (3.5 ± 3.0%) of girls. The performance of BMI showed mixed results; %BF was overestimated in 68.4% of boys (5.0 ± 4.0%) and underestimated in 67.5% of girls (-3.9 ± 2.6%), all p < 0.001. Although, RFM had the highest specificity for %BF percentile classifications, sensitivity was low and inferior to BMI and TMI. TMI was superior to RFM and BMI in predicting %BF in Southern Brazilian adolescents. Using RFM, BMI or TMI equations for %BF prediction without a population-specific correction factor may lead to incorrect interpretations. We suggest that correction factors should be investigated to improve the accuracy of these surrogate indices for body composition assessment. Level V, cross sectional descriptive study.

Tri-ponderal mass index and body mass index in prediction of pediatric metabolic syndrome: the CASPIAN-V study.

Objective Body mass index (BMI) and tri-ponderal mass index (TMI) are anthropometric measures to evaluate body adiposity in the various age groups. The present study aims to compare the predictive value of TMI and BMI for metabolic syndrome (Mets) in children and adolescents of both genders. Subjects and methods A cross-sectional study conducted on 3731 Iranian children and adolescents aged 7-18 years obtained from the fifth survey of 'Childhood and Adolescence Surveillance and Prevention of Adult Non-communicable Disease' (CASPIAN-V) study. The predictive value of BMI and TMI for MetS were determined using Receiver-operator curves. Logistic regression analysis was used to assess the relationship between these indices with MetS. Results 52.6% of participants were boys. The mean (standard deviations) age for boys and girls were 12.62 (3.02) and 12.25 (3.05) years, respectively. In boys, the area under the curve (AUC) of TMI was greater than BMI for all age groups. AUC of TMI was also greater than BMI for age group of 11-14 years (AUC = 0.74; 95% CI (0.67, 0.81)) in girls. Furthermore, our findings showed that odds ratio of Mets for TMI was greater than BMI in age groups of 11-14 years (OR = 1.33 vs 1.22) and 15-18 years (1.16 vs 1.15) in girls and boys, respectively. Conclusion TMI and BMI had moderate predictive value for identifying MetS. However, TMI was a better predictor of MetS than BMI in both genders, especially in age groups of 11-14 and 15-19 years for girls and boys.

Association ofdietary acid load with anthropometric indices in children and adolescents.

High dietary acid load (DAL) may have an influence on anthropometric indices. Given that there was no study on the association between DAL and anthropometric indices children and adolescents, the current study was aimed to examine the association between DAL and anthropometric indices in Iranian children and adolescents. Students aged 6-18years were recruited using a multi-stage, cluster sampling method from 30 provinces of Iran. Dietary intake was assessed through a validated food frequency questionnaire. Height (Ht), weight (Wt), neck circumference (NC), waist circumference (WC), wrist circumference, and hip circumference (HC) were measured. WC-to-HC ratio (WHR), WC-to-Ht ratio (WHtR), body mass index (BMI) z-score, tri-ponderal mass index (TMI), and parental BMI were computed. Potential renal acid load (PRAL) and net endogenous acid production (NEAP) were used to estimate DAL. The association between DAL and anthropometric indices was evaluated using linear regression models. In total, 5326 students (46.92% girls), with mean (standard deviations (SD)) age of 12.50 (3.14) years participated in the study (response rate: 98.13%). After adjusting for confounders, there was a significant association between NEAP and NC (P < 0.05). Also, an inverse association was observed between PRAL and NEAP with parental BMI (P < 0.05). Our findings showed a direct association between diet-induced acid load and NC and an inverse association between DAL indices and parental BMI. More well-designed clinical studies are warranted to confirm our results and the underlying mechanisms. Level V, cross-sectional descriptive study.

Association of Neck Circumference with Anthropometric Indicators and Body Composition Measured by DXA in Young Spanish Adults

Background: Due to a clinical and public health interest of neck circumference (NC), a better understanding of this simple anthropometric measurement, as a valid marker of body composition is necessary. Methods: A total of 119 young healthy adults participated in this study. NC was measured over the thyroid cartilage and perpendicular to the longitudinal axis of the neck. Body weight, height, waist circumference (WC), and hip circumference were measured. A Dual X-ray absorptiometry (DXA) scan was used to determine fat mass, lean mass, and visceral adipose tissue (VAT). Additionally, body mass index (BMI) and triponderal mass index (TMI), the waist to hip and waist to height ratios, and the fat mass and lean mass indexes (FMI and LMI, respectively) were calculated. Results: NC was positively associated in women (W) and men (M), with BMI (rW = 0.70 and rM = 0.84, respectively), TMI (rW = 0.63 and rM = 0.80, respectively), WC (rW = 0.75 and rM = 0.86, respectively), VAT (rW = 0.74 and rM = 0.82, respectively), Waist/hip (rW = 0.51 and rM = 0.67, respectively), Waist/height (rW = 0.68 and rM = 0.83, respectively) and FMI (rW = 0.61 and rM = 0.81, respectively). The association between NC and indicators of body composition was however weaker than that observed by BMI, TMI, WC and Waist/height in both women and men. It is of note that in women, NC was associated with FMI, VAT and LMI independently of BMI. In men, adding NC to anthropometric variables did not improve the prediction of body composition, while slight improvements were observed in women. Conclusions: Taken together, the present study provides no indication for NC as a useful proxy of body composition parameters in young adults, yet future studies should explore its usefulness as a measure to use in combination with BMI, especially in women.

Distribution of Tri-Ponderal Mass Index and its Relation to Body Mass Index in Children and Adolescents Aged 10 to 20 Years

ContextBody mass index percentiles are widely used to determine overweight and obesity status in children and adolescents. Their limitations in clinical settings can be addressed.ObjectiveReference ranges for the tri-ponderal mass index percentiles of Korean children and adolescents are presented for a comparison of their clinical variables with those of body mass index.DesignCross-sectional study.SettingKorea National Health and Nutrition Examination Survey, 2007–2016.PatientsKorean children and adolescents aged 10 to 20 years.Main Outcome MeasuresThe age- and sex-specific least mean square parameters (skewness, median, and coefficient of variation) for the tri-ponderal mass index of 9749 subjects aged 10 to 20 years.ResultsThe factors associated with metabolic syndrome, except diastolic blood pressure, were more likely to be worse in the subjects with tri-ponderal mass index values indicative of overweight status than in those with normal tri-ponderal mass index values. Body mass index tends to underestimate obesity-related comorbidities more than tri-ponderal mass index does.ConclusionThe tri-ponderal mass index standard deviation score may be advantageous when defining overweight and obesity in children and adolescents.

Tri-ponderal mass index as a tool for insulin resistance prediction in overweight adolescents: A cross-sectional study.

The aims of this study were to assess the capacity of tri-ponderal mass index (TMI) to screen and predict insulin resistance (IR) in overweight Brazilian adolescents, comparing it with body mass index (BMI) predictive capacity; and to verify the IR predictive capacity of other assessment tools such as waist circumference (WC), and waist-to-height ratio (WHR). A cross-sectional study was carried out with 217 overweight adolescents, from both sexes, between 12 and 18 y of age. The participants were classified as having IR according to a previous established cutoff point of ≤3.16. IR was determined by the homeostasis model assessment of insulin resistance. The other assessment tools were measured with standard protocols. There was no difference between TMI and BMI to explain the presence of IR. In girls, BMI presented a slightly better predictive capacity to explain IR than TMI. Moreover, WC was reported to be the most effective IR screening methods for girls. Receiver operating characteristic curves showed that TMI and BMI presented similar values of sensibility and specificity for boys. Nevertheless, BMI had a better sensibility and TMI had a better specificity for girls. Interestingly, WC demonstrated a strong sensibility for both sexes. TMI did not present a superior predictive accuracy for IR screening in overweight Brazilian adolescents when compared with BMI. TMI and BMI presented similar values of sensitivity and specificity for boys and WC a slightly superior IR predictive capacity for girls.

TRI-PONDERAL MASS INDEX IS USEFUL FOR SCREENING CHILDREN AND ADOLESCENTS WITH INSULIN RESISTANCE.

ABSTRACTObjective: To investigate whether tri-ponderal mass index and body mass index Z scores are equivalent for screening children and adolescents with insulin resistance.Methods: Cross-sectional study with 296 children and adolescents enrolled at public schools of Vitória, Espírito Santo, Brazil, aged eight to 14 years. The tri-ponderal mass index was calculated as the ratio between weight and height cubed. The body mass index was calculated as the ratio between weight and height squared. Insulin resistance was defined with the homeostatic model assessment (HOMA-IR).Results: The HOMA-IR was higher in the 4th quartile of body mass index Z scores and tri-ponderal mass index compared to 1st and 2nd quartiles for both girls and boys. The areas under the age-adjusted receiver operating characteristic curves were similar between the indices for girls (body mass index Z scores=0.756; tri-ponderal mass index=0.763) and boys (body mass index Z scores=0.831; tri-ponderal mass index=0.843). In addition, according to the simple linear regression analyses estimations, both body mass index Z scores and tri-ponderal mass index explained a significant fraction of the homeostatic model assessment variability for girls (body mass index Z scores: R2=0.269; tri-ponderal mass index: R2=0.289; p<0.001) and boys (body mass index Z scores: R2=0.175; tri-ponderal mass index: R2=0.210; p<0.001).Conclusions: The tri-ponderal mass index and body mass index Z scores were similar to discriminate children and adolescents with insulin resistance. It is noteworthy that the use of tri-ponderal mass index is clearly advantageous, because it can be calculated with no concerns on adjustments for the age, a fact that makes it very applicable in the clinical practice.

Evidence in obese children: contribution of tri-ponderal mass index or body mass index to dyslipidemia, obesity-inflammation, and insulin sensitivity.

Background Chronic inflammation plays a critical role in the development of obesity-related metabolic dysfunction. The tri-ponderal mass index (TMI) may be more effective than body mass index (BMI) for estimating body fat levels. This study compared the efficacy of BMI and TMI in screening for dyslipidemia, insulin sensitivity, and inflammation in childhood obesity. Methods This study included 80 children who were classified as normal weight, overweight or obese using standardized BMI (BMI standard deviation score [SDS]) and TMI measurements. Fasting blood glucose, insulin, homeostasis model assessment of insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), triglycerides, total cholesterol, liver function enzymes, leptin, serum free fatty acid (FFA), fetuin-A, monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-α), and interleukin (IL)-6 levels were evaluated using both classification systems. Results LDL-C levels significantly differed within the groups by BMI, and serum FFA levels differed only according to the TMI. Serum MCP-1, TNF-α, IL-6, and fetuin-A levels showed no difference according to the TMI or BMI SDS. Fetuin-A levels did not differ between the insulin-resistant and non-resistant cases. Fetuin-A was the only inflammatory marker positively correlated with BMI. No inflammatory markers correlated with TMI. Fetuin-A, MCP-1, TNF-α, and IL-6 correlated with each other, but not with metabolic parameters. Conclusions BMI SDS and TMI were associated with metabolic disturbances in childhood obesity. Weight versus heightn values may be related more to metabolic parameters than to inflammatory changes.

Accuracy of Tri-ponderal Mass Index and Body Mass Index in Estimating Insulin Resistance, Hyperlipidemia, Impaired Liver Enzymes or Thyroid Hormone Function and Vitamin D Levels in Children and Adolescents

Objective:Tri-ponderal mass index (TMI) has been reported to estimate body fat more accurately than body mass index (BMI). This study aimed to compare the efficacy of TMI and BMI in predicting insulin resistance (IR), hyperlipidemia, impaired liver enzymes or thyroid hormone function and vitamin D concentration.Methods:One hundred and forty-three overweight or obese children, based on BMI-standard deviation (SD) scoring (BMI-SDS) were studied retrospectively. TMI thresholds for overweight status were 16.0 kg/m3 for boys and 16.8 kg/m3 for girls and 18.8 kg/m3 for boys and 19.7 kg/m3 for girls for obese status.Results:Twenty-two overweight and eight obese children by BMI-SDS were classified as normal by TMI. Of the overweight children 22 (22.7%) had IR and IR was detected in 2 of 8 obese children with normal TMI. There was no increase in liver enzymes in any of the children with normal TMI. Forty-four obese children were overweight according to TMI and IR was detected in 40.9%. Thyroid stimulating hormone levels were significantly higher in BMI-based obese children. Vitamin D levels were similar in all groups of both classifications.Conclusion:When TMI was used there may be a risk of overlooking IR. However, if it is assumed that liver enzymes are elevated as a result of visceral adiposity, TMI can be used as an auxiliary parameter to show visceral effects of adiposity. Normal TMI may indicate that visceral organ functions have not deteriorated yet. More studies are needed to evaluate TMI as a clinical tool.

Age-Specific Estimates and Comparisons of Youth Tri-Ponderal Mass Index and Body Mass Index in Predicting Adult Obesity-Related Outcomes

To estimate and compare tri-ponderal mass index (TMI) and body mass index (BMI) at each age from childhood to young adulthood in the prediction of adulthood obesity-related outcomes. Participants of this observational study (n=432) were from a 20-year infancy-onset randomized atherosclerosis prevention trial. BMI and TMI were calculated using weight and height measured annually from participants between ages 2 and 20years. Outcomes were aortic intima-media thickness (at the age of 15, 17, or 19years), impaired fasting glucose and elevated insulin levels, homeostasis model assessment of insulin resistance index, serum lipids, and hypertension at the age of 20years. Poisson regressions, Pearson correlation, logistic regression, and area under the curve (AUC) were used to estimate and/or compare associations and predictive utilities between BMI and TMI with all outcomes. The associations and predictive utilities of BMI and TMI with all outcomes were stronger at older ages. BMI had significantly stronger correlations than TMI with insulin (at age 16years), systolic blood pressure (age 5-20years), and triglycerides (age 18years). BMI had significantly greater predictive utilities than TMI for insulin resistance (at age 14-16years; difference in AUC=0.018-0.024), elevated insulin levels (age 14-16years; difference in AUC=0.018 and 0.025), and hypertension (age 16 to 20years; difference in AUC=0.017-0.022) but they were similar for other outcomes. TMI is not superior to BMI at any ages from childhood to young adulthood in the prediction of obesity-related outcomes in young adulthood.

The Relationship Between Tri-ponderal Mass Index and Metabolic Syndrome and Its Components in Youth Aged 10\u201320 Years

The current study aimed to evaluate the distribution of the tri-ponderal mass index (TMI) according to sex and age and the relationship of obesity groups according to sex- and age-specific TMI with metabolic syndrome (MetS) and its components. A total of 8,464 subjects aged 10–20 years were classified into 4 groups according to sex- and age-specific TMI: (i) underweight, (ii) normal weight, (iii) overweight, and (iv) obese. The range of the 50th percentiles of TMI was from 13.24 kg/m3 at 10 years to 12.94 kg/m3 at 20 years among males and from 12.19 kg/m3 to 12.84 kg/m3 among females. In the analysis of covariance, obesity groups according to sex- and age-specific TMI were positively correlated with waist circumference (WC) standard deviation score; systolic blood pressure (BP); diastolic BP; and levels of glucose, total cholesterol, triglycerides (TGs), and low-density lipoprotein cholesterol, but for both sexes, the obesity groups were negatively related to high-density lipoprotein cholesterol (HDL-C). In the multiple logistic regression, subjects in the overweight group had higher odds ratios (ORs) for elevated WC (29.18), elevated BP (1.33), elevated TGs (2.55), reduced HDL-C (2.31), and MetS (8.93) than those with normal weight. Participants in the obesity group had increased ORs for elevated WC (154.67), elevated BP (2.22), elevated glucose (3.54), elevated TGs (4.12), reduced HDL-C (3.69), and MetS (25.57) compared to participants with normal weight after adjustment for confounders. Our results suggest that sex- and age-specific TMI may be applicable in the clinical setting as a useful screening tool.

Association of youth triponderal mass index vs body mass index with obesity-related outcomes in adulthood

The large prospective Cardiovascular Risk in Young Finns Study included 3596 participants aged 3 to 18 years at baseline, and followed the large majority up to 20–30 years later. Comparing various measures of adiposity at baseline, Body Mass Index (BMI) outperformed the Triponderal Mass Index (TMI) and skinfold thicknesses in predicting later Type 2 diabetes, hypertension and LDL cholesterol levels, and carotid intimal thickness.