Adolescent Tri-ponderal Mass Index Growth Trajectories and Incident Diabetes Mellitus in Early Adulthood

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 from 1996 until now. Physical exam results including blood test results were collected annually and the BMI z-score/TMI growth trajectory groups during 13–18 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 1,387 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 (CI): 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.

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

“…Table 1 describes the characteristics of the included studies including 14 for the association between TMI and body fat in childhood and adolescence ( 10 , 14 , 18 – 26 , 41 – 43 ), 20 for TMI and CVRFs in childhood and adolescence ( 13 – 18 , 21 , 26 – 34 , 42 – 45 ), and 4 for the association in adulthood ( 35 – 37 , 46 ). Twenty-five of the included studies used a cross-sectional design ( 10 , 13 , 15 – 28 , 30 – 34 , 41 – 43 , 45 ), 2 a retrospective design ( 14 , 44 ), 1 a case-control design ( 29 ), and 4 a cohort design ( 35 – 37 , 46 ).…”

“…The AUCs were low for TMI (0.53, 0.56, and 0.54), as well as for other adiposity indicators such as abdominal volume index (0.61, 0.62, and 0.61), BMI (0.59, 0.60, and 0.59), and WC (0.61, 0.61, and 0.61) in childhood to predict adult homeostasis model assessment 2-insulin resistance (HOMA2-IR), HOMA2-β, and high fasting insulin ( 36 ). However, when considering growth trajectory instead of a single measurement in childhood, a persistently high TMI during adolescence had predicted diabetes quite well in adults (AUC value as high as 0.81) ( 46 ).…”

“…BMI was better than TMI only in late adolescence to predict adult IR and hypertension, suggesting that the variation of BMI during adolescence influences the strength of the association ( 10 , 37 ). When considering trajectories, persistently high TMI during 13 and 18 years performed better than the BMI trajectory to predict adult diabetes ( 46 ), suggesting that, during adolescence, TMI trajectory (i.e., repeated measurements) may better reflect growth and predict adult CVRD outcomes. Therefore, further prospective studies with large sample sizes, multiethnic populations, and repeated measurements of anthropometric indicators are needed to confirm these findings.…”

“…Only four articles focused on the association of TMI vs. other obesity-related indicators in childhood or adolescence with CVRFs in adulthood (35)(36)(37)46) (Table 2). BMI at ages 2 to 20 years predicted the presence of CVRFs in young adults aged 20 years as well or better than TMI.…”

Factors correlated with targeted prevention for prediabetes classified by impaired fasting glucose, impaired glucose tolerance, and elevated HbA1c: A population-based longitudinal study

“…In addition, it could contribute to the evaluation of the predictive capacity of these indicators to identify people with high risk of prediabetes. Although a recent study reported that a specific PI growth trajectory pattern during adolescence might be critical for diabetes prevention efforts ( 49 ), few studies examined the association between PI and prediabetes in adults. Conicity index was considered as a simple anthropometric index of body fat distribution to assess the central obesity with high accuracy ( 25 ).…”