Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study

Abstract

This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), “A” body-shape index (ABSI), conicity index (C), visceral adiposity index (VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI (TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307 elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator, using the prediabetes classification to identify their sensitivity and specificity, and these indicated that the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes, and multivariate logistic regression analysis showed that the ORs for prediabetes increased across quartiles (p < 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and optimal cut-off = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggesting that compared to the other parameters, the TyG index has the best discriminative power to predict prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary marker for assessing prediabetes in older adults.

U-Shaped Association Between the Triglycerides-Glucose index and the Risk of Incident Diabetes in Apparently Healthy Population: A Population-based Cohort Study

“…More importantly, previous cohort studies showed a positive relationship between high levels of the TyG index and the risk of incident diabetes [17][18][19][20], but the positive association disappeared at low levels of the TyG index [17,18,20]. This trend suggested a nonlinear association which had never been well characterized in previous studies.…”

“…The TyG index was suggested to be considered as a screening tool for identifying people at a high risk of T2DM in clinical practice [18]. Although studies on the TyG index as a risk of T2DM have been conducted in Singapore, Korean, Thailand, and the white European population [17][18][19][20], no data on the Japanese population are currently available.…”

Relative Handgrip Strength Diminishes the Negative Effects of Excess Adiposity on Dependence in Older Adults: A Moderation Analysis

“…The data for this secondary cross-sectional study were obtained from the Health and Well-being and Aging Survey in Colombia 2015 (SABE, from initials in Spanish: Salud, Bienestar y Envejecimiento, 2015), a multicenter project conducted from 2014 to 2015 by (in Spanish: Ministerio de Salud y la Protección Social de Colombia) [27]. The study included the Colombian population aged ≥60 years, and the indicators were disaggregated by age ranges, sex, ethnicity, and socioeconomic level.…”

Efficacy and safety assessment of traditional Chinese medicine for metabolic syndrome

“…Moreover, the increased rate of MetS in low-incomed countries is dramatic 3. MetS is regarded as a risk factor for the development of type 2 diabetes mellitus (T2DM),4 cardiovascular disease,5 stroke,6 polycystic ovary syndrome, non-alcoholic steatohepatitis7 and cancer,8 which may all lead to mortality 9. MetS pandemic may cause heavy social and economic burden.…”