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

The relationship of visceral adiposity with endothelial functions and subclinical atherosclerosis in obese individuals

INTRODUCTION

On the cardiovascular system, obesity accelerates atherosclerosis progression, inducing pathophysiological changes that are detectable already from young adults. Endothelial dysfunction is one of the earliest vascular alterations observed in obesity. In this study, we aimed to determine endothelial functions and carotid intima-media thickness in patients with obesity without overt cardiovascular disease.

METHODS

The study was conducted with 112 individuals with obesity without overt cardiovascular disease and any chronical diseases (BMI>30 kg/m2) (84 female, 28 male, mean age: 46.3±11.2 years) and 49 healthy individuals with no diseases (33 female, 16 male, mean age: 44.6±10.2 years). All patients were examined for endothelial functions by the flow-mediated dilatation (FMD) method and carotid intima-media thicknesses (CIMT). All measurements were performed by the same imaging specialist, averaging 3 different measurements. In addition to the body mass index and waist circumference visceral adiposity index (VAI) and triponderal mass index (TPI) also calculated.

RESULTS

The percentage of FMD obtained by brachial artery ultrasound was significantly lower, visceral adipose tissue, perirenal adipose tissue thicknesses measured by abdominal ultrasound and CIMT were significantly thicker in Group 1 compared to Group 2. FMD had a negative significant correlation with body mass index, visceral adipose tissue thickness, perirenal adipose tissue thickness, and waist and hip circumferences, and carotid intima-media thickness and CIMT had a significant correlation with visceral adipose tissue thickness, perirenal adipose tissue thickness, VAI, TPI and waist, hip circumferences.

CONCLUSION

Individuals with obesity have impaired endothelial functions and greater carotid intima-media thicknesses compared to healthy individuals. This impairment in endothelial functions is proportional to the amount of visceral and perirenal fat accumulation. Parameterss reflecting visceral fat distribution such as VAI and TPI are also related with these impairment.

Evaluation of body mass index, ponderal index, visceral cross-sectional area, subcutaneous fat cross-sectional area, and liver volume as predictive factors for obesity-related comorbidities: a retrospective cohort study

BACKGROUND

The body mass index (BMI) is an imperfect clinical measure of obesity that should be used in conjunction with other valid measures of weight-related risk. We studied whether there is a superior measure of obesity-related comorbidities.

METHODS

Records of bariatric clinic patients who had an abdominal computed tomography (CT) within 1 year of visit were reviewed. The presence of obesity-related comorbidities was determined at the time of the scan. BMI and ponderal index (PI) were calculated, and CT scans were reviewed to determine the visceral cross-sectional area (VCSA), subcutaneous fat cross-sectional area (SFCSA), and liver volume (LV). Data were analyzed using the Kruskal-Wallis test and Mann-Whitney U test.

RESULTS

A higher number of comorbidities were found to be associated with a larger BMI (P = .011), VCSA (P = .014), SFCSA (P = .007), and LV (P = .014), but not a larger PI (P = .11). Of the 16 comorbidities assessed, VCSA and LV were associated with more than BMI and SFCSA. However, each measure could be associated with different comorbidities. A higher BMI was associated with increased insulin use (P = .034), hypertension (P = .007), and history of obstructive sleep apnea (P = .015), none of which were associated with PI. BMI and PI were the only measures associated with a history of deep vein thrombosis/pulmonary embolism (both P < .01). Only SFCSA was found to be associated with gastroesophageal reflux disease (P = .029). VCSA (P = .038) and LV (P = .001) were associated with nonalcoholic fatty liver disease.

CONCLUSION

No measure could account for all obesity-related comorbidities, implying the need for targeted measurements. However, PI was the least effective measure.

Tri-ponderal mass index and left ventricular hypertrophy in a cohort of caucasian children and adolescents with obesity

BACKGROUND

Pediatric obesity is a global emerging burden for society; among its health-related consequences there are hypertension (HTN) and left ventricular hypertrophy (LVH). Several anthropometric indices have been investigated for the early identification of cardiovascular risk in children. The aim of the present study was to assess whether tri-ponderal mass index (TMI) was associated with LVH in a cohort of Caucasian children and adolescents with obesity.

METHODS

In this observational study, 63 children and adolescents with obesity aged 7-to-16 years were enrolled. During outpatient visits, adiposity, and cardio-metabolic indices (BMI z-score, WHR, TMI, ABSI) were collected. All subjects underwent a 24-hour ambulatory blood pressure monitoring (ABPM) and transthoracic echocardiography.

RESULTS

Children and adolescents with obesity with LVH had significantly higher BMI z-score (p = 0.009), WHR (p = 0.006) and TMI (p = 0.026) compared to children without LVH. WC and WHR were the only indices significantly associated with left ventricular mass index (LVMI).

CONCLUSION

Left ventricular remodeling is associated with the cardio-metabolic risk markers WC and WHR, but not with the adiposity index TMI among children with obesity.

Association between tri-ponderal mass index and glucose metabolism disorder in children with obesity in China: A case-control study

Obesity is a risk factor for glucose metabolism disorder. This study explored the association between the tri-ponderal mass index (TMI) and indicators of glucose metabolism disorder in children with obesity in China. This retrospective case-control study included children aged 3 to 18 years old diagnosed with obesity at Jiangxi Provincial Children's Hospital (China) between January 2020 and April 2022. Demographic and clinical characteristics were obtained from the medical records. Factors associated with glucose metabolism disorder were explored by logistic regression analysis. Pearson correlations were calculated to evaluate the relationships between TMI and indicators of glucose metabolism disorder. The analysis included 781 children. The prevalence of glucose metabolism disorder was 22.0% (172/781). The glucose metabolism disorder group had an older age (11.13 ± 2.19 vs 10.45 ± 2.33 years old, P = .001), comprised more females (76.8% vs 66.9%, P = .008), had a higher Tanner index (P = .001), and had a larger waist circumference (89.00 [82.00-95.00] vs 86.00 [79.00-93.75] cm, P = .025) than the non-glucose metabolism disorder group. There were no significant differences between the glucose metabolism disorder and non-glucose metabolism disorder groups in other clinical parameters, including body mass index (26.99 [24.71-30.58] vs 26.57 [24.55-29.41] kg/m2) and TMI (18.38 [17.11-19.88] vs 18.37 [17.11-19.88] kg/m3). Multivariable logistic regression did not identify any factors associated with glucose metabolism disorder. Furthermore, TMI was only very weakly or negligibly correlated with indicators related to glucose metabolism disorder. TMI may not be a useful indicator to screen for glucose metabolism disorder in children with obesity in China.

Tri-ponderal mass index as a screening tool for obesity prediction in children aged 6-9 years

Objective

This study aimed to evaluate the efficiency of tri-ponderal mass index (TMI) in determining obesity in Chinese children aged 6-9 years, using the criteria of percentage of body fat (PBF) and body mass index z-scores (BMI-Z).

Methods

The cross-sectional study included 5365 children, aged 6-9 years, who participated in the project survey "Group prevention and treatment of obesity among students and school health promotion in Shanghai" from September 2007 to September 2009. Height, weight, waist circumference, body mass index (BMI), TMI, waist-to-height ratio (WHtR), and PBF were recorded. Statistical analyses including Kolmogorov-Smirnov test, chi-square test, receiver operating characteristics curve, and kappa chi-square test were performed.

Results

TMI for both sexes was relatively constant with increasing age, and statistically significant differences were not observed at some ages (P > 0.05 at 6, 7, 8, and 9 years). WHtR showed subtle changes, while BMI and PBF increased significantly with age in boys and girls (P < 0.01). Using BMI-Z criteria as the measure of general obesity, the results indicated that TMI cutoff values for 6-9 years were 14.60 kg/m3 for boys and 14.84 kg/m3 for girls (P < 0.001). Analysis of the agreement between TMI and BMI-Z showed that the kappa statistic was 0.826 in boys and 0.709 in girls (P < 0.001).

Conclusion

TMI, as a constant tool, holds great potential as an alternative screening method for identifying children aged 6-9 years who may be at risk of obesity at an early stage.

Associations between tri-ponderal mass index, body mass index, and high blood pressure among children and adolescents: a cross-sectional study

High blood pressure (HBP) and obesity are major public health issues globally. The aim of the study was to evaluate the associations between tri-ponderal mass index (TMI) and body mass index (BMI) and HBP and to determine which anthropometric parameters may best predict HBP among Lithuanian children and adolescents aged 7-18 years. This cross-sectional study included 3710 Lithuanian children and adolescents aged 7-18 (52.7% boys and 47.3% girls). Each subject's height, weight, and other anthropometric parameters, as well as blood pressure were measured according to standardized protocols; subsequently, TMI and BMI were calculated. The prevalence of HBP was 27% (the prevalence of elevated BP and hypertension was 13.7% and 13.3%, respectively), significantly higher for boys than for girls. The Pearson correlation coefficients between the BMI z-score and BP were higher than those between the TMI z-score and BP. In both sexes combined, the adjusted odds ratios (aOR) for HBP were increased significantly with increasing quartiles of TMI and BMI as compared to the first quartile (Q1) (Q2: aOR = 1.37 and aOR = 1.69; Q3: aOR = 2.10 and aOR = 2.27; Q4: aOR = 3.95 and aOR = 4.91, respectively). Significant associations also were observed between overweight and obesity (defined according to two methods: age- and sex-specific TMI percentiles and IOTF criteria) among boys and girls separately. BMI presented a higher area under the curve value than TMI for predicting HBP in children and adolescents. The findings of the study suggest that BMI and TMI are significantly associated with HBP. However, BMI is a better predictor for HBP than TMI among Lithuanian children and adolescents aged 7-18 years.

Performance of triponderal mass index, body mass index z scores, and body mass index performance in the diagnosis of obesity in children and adolescents

OBJECTIVES

Childhood obesity is a global health problem that affects millions of children and causes obesity-related adverse health outcomes in both childhood and adulthood. Although body mass index (BMI) z scores and percentiles are used in the diagnosis of obesity in children, it has been emphasized in recent years that the triponderal mass index (TMI) may be more accurate for this purpose. We aimed to compare TMI with BMI in the diagnosis of obesity in Turkish children and adolescents.

METHODS

The records of 3540 children who applied to Gülhane Training and Research Hospital were retrospectively scanned and the data of 1161 children were included in the study. The body fat percentage (BF%) was calculated by a formula, and children with body fat in the ≥95th percentile were classified as obese. Receiver study characteristics analysis was performed to compare the effectiveness of TMI and BMI in the diagnosis of obesity.

RESULTS

TMI correlated more with BF% (r = 0.863) than fat mass (r = 0.664); BMI correlated more with fat mass (r = 0.957) than BF% (r = 0.714) (P < 0.001). TMI had the highest area under the curve (AUC) in boys at diagnosis of obesity (6-11 y = 0.981; 12-15 y = 0.994). Girls ages 6 to 11 y had the same AUC for all 3 indexes (AUC = 0.977), whereas girls ages 12 to 15 y had the highest AUC for TMI (AUC = 0.967). However, the AUC values between all indices were very close.

CONCLUSIONS

TMI can be used to diagnose obesity in Turkish children and adolescents in both boys and girls similarly and with good performance. The correlation with BF% and stability of TMI makes this index more advantageous. However, it should be noted that the performance of each of the 3 indices is very close to that of the others, and adjustments should be made according to age and sex.

Triponderal mass index and markers of metabolic risk in children and adolescents with obesity

BACKGROUND AND OBJECTIVE

Triponderal mass index (TMI) would estimate excess adiposity better than body mass index (BMI), maintaining stable values during childhood. This work aims to determine the correlation between TMI and markers of metabolic risk as well as set values of TMI that are related to an increase of metabolic risk.

MATERIAL AND METHODS

Multicenter, observational, cross-sectional and prospective study in children under 14 years of age with obesity.

VARIABLES

age, sex, pubertal stage, weight, height, abdominal circumference, BMI, TMI, basal glucose and insulin, HOMA index, blood pressure, lipoprotein profile, transaminases and uric acid. BMI and TMI were expressed according to the values of the Barcelona longitudinal study. Statistical analysis was performed with the SPSS* program.

RESULTS

One hundred and ninety-nine patients (50.3% male), age 11.08 (2.48) years, TMI 19.68 (2.36)kg/m³. Correlation between TMI and abdominal circumference (r=0.571; p=0), insulin (r=0.198; p=0.005), HOMA index (r=0.189; p=0.008) and HDL-c (r=-0.188; p=0.008) was observed. IMT>20.15kg/m³ was associated with insulin≥15mIU/ml (p=0.029) and IMT>20.36kg/m³ with HDL-c<40mg/dl (p=0.023).

CONCLUSIONS

TMI was correlated with increase of abdominal circumference, insulin and HOMA index and decrease of HDL-c. IMT>20kg/m³ can be associated with increased insulin and decreased HDL-c. Therefore, the IMT seems to be a useful parameter in the assessment of pediatric patients with obesity.

Comparisons of tri-ponderal mass index and body mass index in discriminating hypertension at three separate visits in adolescents: A retrospective cohort study

OBJECTIVE

To estimate whether the new obesity indicator tri-ponderal mass index (TMI) has a better capacity to predict adolescent hypertension (HTN) and HTN subtypes at three separate blood pressure (BP) visits than the conventionally used body mass index (BMI).

METHODS

A total of 36,950 adolescents who had initial normal BP from 2012 to 2019 were included in Suzhou, China. HTN was defined as having three separate visits of elevated BP in 2020. The area under the receiver-operating characteristic curve (AUC), false-positive rate, false-negative rate, total misclassification rates, net reclassification improvement (NRI), and integrated discrimination improvement were calculated to compare the discriminative ability of HTN between BMI and TMI.

RESULTS

TMI had better predictive abilities than BMI among all of the participants when predicting HTN (difference in AUC = 0.019, 95% CI = 0.007-0.031; NRI = 0.067, 95% CI = 0.008-0.127) and isolated systolic hypertension (difference in AUC = 0.021, 95% CI = 0.005-0.036; NRI = 0.106, 95% CI = 0.029-0.183). The difference in prediction abilities between BMI and TMI was more obvious in the subgroup of age ≥16. Also, TMI outperformed BMI in predicting adolescent HTN in girls but not in boys.

CONCLUSION

Compared with BMI, TMI may have a better predictive capacity for HTN, particularly in girls and older adolescents. TMI has the potential to be used as an effective predictor for HTN in clinic practice. Further studies are needed to verify the utility of TMI.

Temporal Associations between Tri-Ponderal Mass Index and Blood Pressure in Chinese Children: A Cross-Lag Analysis

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.

Impact of Insulin Resistance on Cardiometabolic Risk Factors and an Anthropometry-Based Predictive Nomogram for Insulin Resistance Among Adolescents in China

OBJECTIVE

We aimed to investigate the impact of insulin resistance (IR), as determined by the homeostasis model assessment of insulin resistance (HOMA-IR), on cardiometabolic risk factors (CMRFs), and develop an anthropometry-based predictive nomogram for IR among adolescents in China.

DESIGN

Data were acquired from a cross-sectional study with a stratified cluster sampling method, conducted among adolescents in Northeast China.

PARTICIPANTS

A total of 882 adolescents (aged 12-16 years, 468 boys) were included.

MEASUREMENTS

All participants underwent anthropometric and biochemical examinations. The thresholds of IR included the 90th percentile of the HOMA-IR for adolescents with a normal body mass index (BMI) and fasting plasma glucose (FPG) level within each sex group (Cutoff A), and the 75th percentile for all participants of the same sex (Cutoff B).

RESULTS

The HOMA-IR was associated with CMRFs. IR, as defined by both cutoffs A and B, was significantly associated with most CMRFs, except decreased HDL-C levels. Excellent concordance (κ = 0.825) was found between these two criteria in diagnosing IR. However, IR using cutoff A, was more closely associated with cardiometabolic risk. The incidence of IR, as defined by cutoff A, was 18.93% and increased from 10.99% to 43.87% based on the different BMI categories. Further, an anthropometry-based predictive model for IR, incorporating sex, age, waist-to-hip ratio, weight and BMI, was developed and presented as a nomogram.

CONCLUSIONS

IR among adolescents is strongly related to cardiometabolic risk. We developed an anthropometry-based predictive nomogram for IR among adolescents, which may facilitate health counselling and self-risk assessments.

Interaction between Autonomic Regulation, Adiposity Indexes and Metabolic Profile in Children and Adolescents with Overweight and Obesity

Early obesity predicts initial modifications in cardiac and vascular autonomic regulation. The aim of this study was to assess the possible interaction between non-invasive measures of autonomic cardiovascular control and peripheral endothelium regulation in children with overweight and obesity. We involved 114 young subjects (77M/37F, 12.7 ± 2.2 years) with normal weight (NW, n = 46) to overweight or obesity (OB, n = 68). Multivariate statistical techniques utilizing a collection of modern indices of autonomic regulation, adiposity indexes and metabolic profile were employed. Resting values show substantial equivalence of data. Conversely, blood pressure variance is greater in NW/OB groups. The correlation matrix between major autonomic and metabolic/hemodynamic variables shows a clustered significant correlation between homogeneous indices. A significant correlation between metabolic indices and endothelial and autonomic control, mostly in its vascular end, was recorded. Particularly, the alpha index is significantly correlated with triglycerides (r = −0.261) and endothelial indices (RHI, r = 0.276). Children with obesity show a link between indices of autonomic and endothelial function, fat distribution and metabolic profile. The optimization of autonomic control, for instance by exercise/nutrition interventions, could potentially prevent/delay the occurrence of structural vascular damage leading to reduced cardiovascular health.

Tri-Ponderal Mass Index as a Screening Tool for Identifying Body Fat and Cardiovascular Risk Factors in Children and Adolescents: A Systematic Review

Because of the limitation of body mass index (BMI) in distinguishing adipose mass from muscle, the tri-ponderal mass index (TMI) has been proposed as a new indicator for better assessing adiposity in children and adolescents. However, it remains unclear whether TMI performs better than BMI or other adiposity indices in predicting obesity status in childhood and obesity-related cardiovascular risk factors (CVRFs) in childhood or adulthood. We searched PubMed, Cochrane Library, and Web of Science for eligible publications until June 15, 2021. A total of 32 eligible studies were included in this systematic review. We found that TMI had a similar or better ability to predict body fat among children and adolescents than BMI. However, most of the included studies suggested that TMI was similar to BMI in identifying metabolic syndrome although TMI was suggested to be a useful tool when used in combination with other indicators (e.g., BMI and waist circumference). In addition, limited evidence showed that TMI did not perform better than BMI for identifying specific CVRFs, including insulin resistance, high blood pressure, dyslipidemia, and inflammation in children and adolescents, as well as CVRFs in adults.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero, CRD42021260356.