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Background/Aims Childhood obesity and associated metabolic comorbidities is a major global health concern. Metabolically healthy obesity (MHO) may represent a subgroup of individuals in which excessive body fat accumulation does not lead to adverse metabolic effects. We aimed to determine the prevalence of MHO among obese Israeli children and adolescents and to find predictors for metabolically unhealthy obesity (MUO). Methods In a retrospective study, demographic, anthropometric, lifestyle, and cardiometabolic data were retrieved from medical records of patients with a body mass index (BMI) >95th percentile aged 6 to 17.6 years, attending a tertiary pediatric obesity clinic between 2008 and 2015, with at least 1 year of follow‐up. Participants were dichotomized as either MHO or MUO based on cardiometabolic risk factor clustering (blood pressure, serum lipids, and glucose). Multivariable logistic regression was used to determine predictors of MUO. Results Of the 230 children (median age 9.9 years) fulfilling study criteria, 48 (20.9%) were classified as MHO. Occurrence of MUO was associated with male gender, Arabic ethnicity, higher BMI‐SD score, higher tri‐ponderal mass index (TMI), and higher insulin resistance (IR) (presence of acanthosis nigricans and a higher level of homeostasis model assessment‐IR [HOMA‐IR]). Male gender (odds ratio [OR] 2.27, P = .033), presence of acanthosis nigricans at baseline (OR 2.35, P = .035), and a greater increase in BMI‐SDS during follow‐up (OR 2.82, P = .05) were the best predictors of MUO. Conclusions The MHO phenotype was present in only 20.9% of obese Israeli children. MUO was significantly associated with male gender, with presence of acanthosis nigricans, and with a greater increase in BMI‐SDS during follow‐up.

Background: Prevalence of obesity in youths has drastically increased in both industrialised and non-industrialised countries, and this transition resulted in an increased prevalence of chronic diseases.Aim: The study aimed to comparatively examine prevalence of overweight and obesity status based on tri-ponderal mass index and body mass index in estimating body fat levels in South African children.Setting: The study was conducted in Limpopo and Mpumalanga provinces of South Africa.Methods: A cross-sectional survey of 1361 (boys: n = 678; girls: n = 683) children aged 9–13 years was undertaken. The children’s age and sex-related measurements of body weight, waist-to-height ratio, waist-to-hip ratio, triceps skinfold, subscapular skinfolds and sum of skinfold were taken using the International Society for Advancement of Kinanthropometry protocol. TMI and BMI calculations classified children according to weight and age categories. Descriptive statistics, Spearman’s correlations and multiple linear regression analyses were set at ≤ 0.05.Results: Obesity classifications on TMI and BMI among children were as follows: Boys: 7.3%, 2.6%; 2.2%, 0.7%; Girls: 4.0%, 1.0%; 1.8%, 0.6%. Body weight, WHtR, WHpR, TSKF, SSKF and ΣSKF significantly correlated with TMI (r = 0.40, p 0.001; r = 0.73, p 0.001; r = −0.09, p 0.001; r = 0.50, p 0.001; r = 0.51, p 0.001 and r = 0.52, p 0.001) and BMI (r = 0.81, p 0.001; r = 0.59, p 0.001; r = −0.22, p 0.001; r = 0.63, p 0.001; r = 0.67, p 0.001 and r = 0.66, p 0.001). Regression analysis revealed that body weight, WHtR, WHpR, TSKF, SSKF and ΣSKF accounted for 65% and 85% of variance in children’s TMI (R2 = 0.647, F[6 1354] = 413.977, p 0.001) and BMI (R2 = 0.851, F[6 1354] = 1288.218, p 0.001).Conclusion: TMI revealed strikingly higher incidence of overweight and obesity in South African boys and girls than BMI. Future studies are needed to clarify sensitivity of TMI over BMI in quantifying obesity prevalence in children and adolescents.

Abstract Context Body mass index percentiles are widely used to determine overweight and obesity status in children and adolescents. Their limitations in clinical settings can be addressed. Objective Reference 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. Design Cross-sectional study. Setting Korea National Health and Nutrition Examination Survey, 2007–2016. Patients Korean children and adolescents aged 10 to 20 years. Main Outcome Measures The 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. Results The 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. Conclusion The tri-ponderal mass index standard deviation score may be advantageous when defining overweight and obesity in children and adolescents.

Abstract Purpose Studies have reported the influence of adolescent obesity on development of adult diabetes, but the effect of the growth pattern during this period has rarely been explored. Also, the tri-ponderal mass index (TMI) was thought to be a better estimation of adolescent body fat levels than the body mass index (BMI), so we sought to investigate whether growth trajectories derived by these two indices could predict incident diabetes. Methods We conducted a study by using the Taipei City Hospital Radiation Building Database, a longitudinal cohort established in 1996. Physical exam results including blood test results were collected annually and the BMI z-score/TMI growth trajectory groups during 13 to 18 years of age were identified using growth mixture modeling. A Cox proportional hazard model for incident diabetes was used to examine the risk of baseline obese status and different BMI/TMI growth trajectories. Results Five growth trajectory groups were identified for the BMI z-score and the TMI. During approximately 20 400 person-years follow-up, 33 of 1387 participants developed diabetes. Baseline obesity defined by the BMI z-score and the TMI were both related to adult diabetes. The persistent increase TMI growth trajectory exhibited a significantly increased risk of diabetes after adjusting for baseline obese status and other correlated covariates (hazard ratio: 2.85, 95% confidence interval: 1.01-8.09). There was no association between BMI growth trajectory groups and incident diabetes. Conclusions A specific TMI growth trajectory pattern during adolescence might be critical for diabetes prevention efforts.

•25.3% of Brazilian postpubertal adolescents were insulin resistant.•Insulin resistance was more common in girls and people with overweight.•Reference value of lipid accumulation product: 13.5 (girls) and 13.8 (boys).•Tri-ponderal mass index cut-off point 13.9 kg/m3 (boys) and 14.5 kg/m3 (girls). This study aims to establish cut-off points for lipid accumulation product and tri-ponderal mass index to identify insulin resistance (IR) in Brazilian postpubertal adolescents. We conducted an analysis of postpubertal adolescents enrolled in the national school-based cross-sectional study of cardiovascular risks in adolescents (ERICA-BRAZIL) from February 2013 to November 2014. IR was defined by homeostatic model assessment index for IR values ≥2.32 for girls and ≥2.87 for boys. The analysis involved calculating the area under receiver operating characteristic curves, sensitivity values, specificity, positive and negative predictive values, and positive and negative likelihood ratios to determine reference values of indices with optimal performance. The sample was comprised of 14 026 adolescents, with 25.3% (95% confidence intervals: 24.6%–26.1%) exhibiting IR, more prevalent among girls and overweight individuals. The ideal lipid accumulation product cut-off points associated with IR were 13.5 for the total population, 13.8 for male adolescents, and 13.5 for girls. Regarding tri-ponderal mass index, the optimal cut-off values for identifying IR were 14.1, 13.9, and 14.5 kg/m³ in the general sample, boys, and girls, respectively. This study establishes cut-off points for adiposity indices, demonstrating their effectiveness in screening for IR in postpubertal Brazilian adolescents.

•The Tri-Ponderal Mass Index (TMI) is an important emerging tool for the early screening of obesity in adolescent populations.•This study showed that TMI compared with anthropometric measures, such as hip circumference, neck circumference, waist circumference, waist-height ratio, and waist-hip ratio, demonstrated the highest Youden Index for both overweight and obese adolescents, indicating its superior predictive ability for early screening of these conditions.•Ethnic-based age-specific, sex-specific, and age-plus-sex-specific reference TMI thresholds are established for estimating overweight and obesity among Indian adolescents. This study was designed to examine the reliability of the Tri-Ponderal Mass Index (TMI) for early screening of adolescent obesity compared with anthropometric measures such as hip circumference, neck circumference, waist circumference, waist-height ratio, waist-hip ratio, and body mass index. A school-based, cross-sectional study was conducted between July and December 2019 among 1101 school-going adolescents (both sexes) aged 12 to 17 years, in Rudrapur, Uttarakhand, India. Anthropometric measurements were collected using well-calibrated equipment, and age- and sex-specific BMI percentile cutoff values recommended by the Indian Academy of Pediatrics were used to define overweight and obesity. Statistical analysis was done using SPSS software version 16.0. Receiver operating characteristic curve analysis was conducted, and optimal cutoff values for anthropometric measurements were determined using the Youden Index (sensitivity + specificity – 1). Of 1101 study participants, 71.5% (n = 787) and 28.5% (n = 314) were males and females, respectively. The prevalences of overweight and obesity were 10.4% and 4.1%, respectively. Receiver operating characteristic curve analysis was conducted and TMI exhibited the highest Youden Index both in terms of overweight (0.835) and obesity (0.869) among adolescents. The optimal TMI cutoff values for overweight and obese males and females were >12 kg/m³ and >14 kg/m³ and >13 kg/m³ and >16 kg/m³, respectively. The TMI demonstrated superior predictive capacity for early screening of adolescent obesity, as indicated by high discriminative power, sensitivity, and specificity. The TMI can be used as a simple, reliable tool for early screening of overweight and obesity among adolescents.

Background: No longitudinal studies have explored the relationship between tri-ponderal mass index (TMI) and blood pressure (BP) in children. This study is aimed to investigate the temporal associations between TMI and BP among children in China. Methods: A longitudinal study was carried out with Chinese children from 2014 to 2019. Data of the anthropometric examination and blood pressure were collected annually. TMI was calculated by dividing weight by the cube of height. BP was measured using a standard mercury sphygmomanometer. We investigated temporal associations between TMI and BP with a cross-lagged panel model using repeated measure data from 2014 (Wave 1), 2016 (Wave 2), and 2018 (Wave 3). Results: Results of the cross-lagged panel model showed that TMI was associated with subsequent BP. Participants with higher levels of TMI presented higher levels of BP (Wave 1: β = 0.737 for systolic blood pressure (SBP) and β = 0.308 for diastolic blood pressure (DBP), Wave 2: β = 0.422 for SBP and β = 0.165 for DBP, p < 0.01). In addition, children with higher BP could also present higher TMI (Wave 1: β = 0.004 for SBP and β = 0.006 for DBP, Wave 2: β = 0.003 for SBP and β = 0.005 for DBP, p < 0.01), but the cross-lag path coefficient indicated that the influence of TMI on BP was stronger than the influence of BP on TMI. Conclusions: There was a temporal association between TMI and BP in Chinese children. Higher TMI predicted higher subsequent BP rather than the reverse relationship.

•Our data showed that tri-ponderal mass index was stable across the age span.•It is appropriate to use a static tri-ponderal mass index cutoff value to classify weight status in a representative sample of Brazilian adolescents.•The obesity classified by tri-ponderal mass index was strongly associated with cardiovascular risk. The aims of this study was to determine the cutoff values for tri-ponderal mass index (TMI) and investigate the association between overweight/obesity as classified by TMI and cardiometabolic risk factors in Brazilian adolescents aged 12 to 17 y. This was a cross-sectional study comprising 37 815 adolescents (40 % boys; 12–17 y) enrolled in the Study of Cardiovascular Risks in Adolescents. TMI was calculated as weight divided by cubed height (kg/m3). Overweight (TMI-for-age ≥85th percentile to <95th percentile) and obesity (TMI-for-age ≥95th percentile) were determined for both sexes. Poisson regression model analyses were used to test associations. TMI was stable across the age span (12–17 y) in both sexes. Boys and girls classified by TMI as obese had higher prevalence ratios (PR) for hypertension (PR, 4.98; 95% confidence interval [CI], 3.26–7.61 for boys; PR, 6.88; 95% CI, 3.70–12.78 for girls), insulin resistance (PR, 19.72; 95% CI, 13.56–28.69 for boys; PR, 10.04; 95% CI, 7.47–13.50 for girls), hypercholesterolemia (PR,5.05; 95% CI, 3.68–6.94 for boys; PR, 1.44; 95% CI, 1.00–2.11 for girls), and hypertriacylglycerolemia (PR,7.36; 95% CI, 5.16–10.50 for boys; PR, 3.37; 95% CI, 2.52–4.51 for girls) when compared with normal weight counterparts. Obesity, as classified by TMI, was strongly associated with several cardiovascular risk factors. Our data showed that TMI was stable across the age span. Therefore, a fixed cutoff value to determine weight status in Brazilian adolescents seems appropriate.

Background The diagnostic accuracy of anthropometric measurements for obesity screening in high-altitude pediatric populations remains understudied, particularly since existing measurements have been validated predominantly in lowland populations. This study evaluated the effectiveness of 19 anthropometric measurements for obesity screening among youth residing in the Tibetan Plateau region, aiming to identify the most reliable measurement approach for this distinct demographic. Methods This study included 1,650 Tibetan and Han Chinese students aged 8–18 years from six schools in Lhasa's Chengguan District (altitude 3,650 m). Anthropometric measurements comprised both basic anthropometric parameters and computed indices. The basic anthropometric parameters included height, weight, waist circumference, mid-upper arm circumference as well as skinfold thickness measured at three sites, such as abdominal skinfold thickness (AST). The computed indices consisted of Body Mass Index (BMI), the tri-ponderal mass index (TMI), the sum of skinfold thickness from two or three (SuST 3 ) sites, the waist-to-height ratio, the mid-upper arm-to-height ratio, the conicity index (C-index), the relative fat mass, the body roundness index, two variants of a body shape index (ABSI OR and ABSI CN ), and two percentage body fat values derived from two skinfold thickness equations (such as Y-PBF). Bioelectrical impedance analysis-derived percentage of body fat (PBF BIA ) was used as the reference method to construct Receiver Operating Characteristic (ROC) curves for the 19 anthropometric measurements, and the Area Under the Curve (AUC) was calculated to evaluate the performance of each measurement in obesity screening. Results Statistical analysis revealed that TMI, SuST 3 , AST, and BMI consistently demonstrated robust correlations with PBF BIA across all demographic subgroups ( p  < 0.001, r > 0.7) and exhibited strong diagnostic capabilities (AUC > 0.800). Among all anthropometric measurements, the TMI, SuST 3 , AST, Y-PBF, and BMI had the highest subgroup mean rankings according to the AUC (top 5), and the ABSI OR , C-index, and ABSI CN were the worst (bottom 3). DeLong's test confirmed these measurements as optimal measures in the majority of population subgroups (> 10 out of 19 subgroups), with the TMI showing the most comprehensive applicability (valid for the total sample and 17 subgroups). Notably, the TMI also demonstrated the highest stability in cutoff values (SD = 0.49, range = 1.89) and superior diagnostic performance (accuracy = 0.84, precision = 0.70, recall = 0.83, F score = 0.75). Conclusions Our findings indicate that the TMI is the best anthropometric indices for screening for obesity in children and adolescents on the Tibetan Plateau, with a wide range of applicability to population subgroups and a stable optimal cutoff value.

Background/Objectives: Obesity is a significant risk factor for obstructive sleep apnea (OSA); however, conventional anthropometric measures, such as body mass index (BMI), may not fully reflect the physiological burden associated with adiposity. The triponderal mass index (TMI) has been proposed as an alternative anthropometric indicator, while inflammation-related biomarkers have emerged as potential complementary tools for characterizing OSA severity. This study aimed to evaluate the relationships between BMI, TMI, hypoxemia, and systemic inflammation, and to assess whether combining anthropometric indices with inflammatory biomarkers improves the identification of severe OSA. Methods: In this retrospective cross-sectional study, 238 adults undergoing full-night polysomnography were classified into four groups: non-OSA, mild OSA, moderate OSA, and severe OSA, based on the apnea–hypopnea index (AHI). Anthropometric indices, polysomnographic parameters, and a comprehensive panel of laboratory biomarkers—including C-reactive protein (CRP), neutrophil- and platelet-derived inflammatory indices, prognostic nutritional index (PNI), CRP-to-albumin ratio (CAR), and CRP-to-lymphocyte ratio (CLR)—were analyzed. Associations were evaluated using Spearman correlation analyses, and diagnostic performance for severe OSA (AHI ≥ 30 events/h) was assessed using receiver operating characteristic (ROC) analyses, DeLong tests, and multivariable models. Results: Both BMI and TMI increased progressively with OSA severity (both p < 0.001) and showed comparable correlations with AHI and nocturnal oxygenation parameters. ROC analyses demonstrated similar discriminative performance for severe OSA (BMI AUC = 0.834; TMI AUC = 0.823; p = 0.229). Among inflammatory biomarkers, CRP, multi-inflammatory index (MII), CAR, and CLR showed moderate diagnostic accuracy. Among the evaluated markers, serum albumin (AUC = 0.836) and PNI demonstrated the highest diagnostic accuracy (AUC = 0.994). A combined model integrating BMI or TMI with PNI achieved near-perfect discrimination for severe OSA (BMI-based AUC = 0.9956; TMI-based AUC = 0.9969), while the addition of CRP-based inflammatory markers did not yield meaningful incremental benefit. Conclusions: BMI and TMI exhibit comparable performance in relation to OSA severity, hypoxemia, and systemic inflammation, with no clear superiority of TMI over BMI in adult patients. Inflammation-related biomarkers—particularly PNI—provide additional discriminatory value beyond anthropometric measures alone. Integrating simple biochemical markers with anthropometric and polysomnographic parameters may enhance risk stratification and identification of severe OSA phenotypes.