Body composition analysis, anthropometric indices and lipid profile markers as predictors for prediabetes

The role of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (nhhr) in prediabetes progression and the mediating effect of BMI: a longitudinal study in China

BACKGROUND

Diabetes prevalence in China is significant, with a large proportion in the prediabetes stage. Dyslipidemia is associated with abnormal glucose metabolism, and the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) shows potential in diabetes risk assessment, but its role in prediabetes progression is understudied.

METHODS

A longitudinal study from 2011 to 2015 using CHARLS data was conducted. After exclusions, 1408 participants were included. NHHR was calculated from serum TC and HDL - C levels. Diabetes and prediabetes were defined based on standard criteria. Covariates and mediators were assessed, and statistical analyses included logistic regression and mediation analysis, and mediation analysis was conducted to evaluate the involvement of BMI in the association between NHHR and the risk of prediabetes progression.

RESULTS

Among the 1423 people in the cohort analysis, 339 (23.8%) were diagnosed with prediabetes progression. The median NHHR was significantly larger in the progression group (136.99 vs. 124.95, p < 0.05). In the fully adjusted model, NHHR one-unitincrease led to a 10% higher risk. Subgroup analyses showed consistent associations in most subgroups. BMI mediated 33.8% of the NHHR - prediabetes progression association.

CONCLUSION

NHHR is correlated with the risk of prediabetes progressing to diabetes, and BMI may mediate this association. NHHR monitoring could help assess the risk of progression in prediabetes participants.

Contribution of body mass index, waist circumference, and 25-OH-D3 on the risk of pre-diabetes mellitus in the Chinese population

This study aimed to investigate the associations between body mass index (BMI), waist circumference (WC), 25-hydroxy-vitamin D3 (25-OH-D3), and the risk of pre-diabetes mellitus (PDM), as well as their predictive values in identifying PDM. A total of 1688 participants were included in this cross-sectional investigation. Spearman's correlation analysis was used to assess the relationships between candidate indicators and PDM. The impact of indicators on PDM risk was determined by multivariate logistic regression. The receiver operating characteristic (ROC) analysis was performed to evaluate the prognostic value of indicators. Our study indicated a positive correlation between WC, BMI, and 25-OH-D3 and PDM. WC (OR = 1.05, 95% CI = 1.04-1.06, p < 0.001), BMI (OR = 1.11, 95% CI = 1.08-1.15, p < 0.001), and 25-OH-D3 (OR = 1.01, 95% CI = 1.00-1.02, p = 0.037) and an increased risk of PDM. Additionally, the ROC analysis demonstrated that WC (AUC = 0.651, Specificity = 55.00%, Sensitivity = 67.900%) had a higher diagnostic value for predicting PDM compared to the other variables (BMI, 25-OH-D3, TG, TC, LDL-C, HDL-C, and UA). A cut-off value of WC > 80.5 cm predicted PDM with both good sensitivity and specificity. Additionally, the cut-off value of waist circumference (WC) for men with prediabetes was 86.500, while for women with prediabetes, it was 76.500.

Characteristics and risk factors associated with developing prediabetes in Saudi Arabia

OBJECTIVE

Prediabetes is prevalent in Saudi Arabia and globally. It is associated with adverse health outcomes and complications. Consequently, this study aimed to determine the risk factors associated with developing prediabetes in Saudi Arabia.

METHODS

This is a case-control study conducted at the Family and Community Medicine Department at Prince Sultan Military Medical City, Riyadh, Saudi Arabia. The cases included individuals with prediabetes (prediabetes group), and the control group included individuals with normal HbA1c levels who were not diagnosed with prediabetes or diabetes. The data collected included sociodemographic data, clinical parameters, laboratory tests, and medical conditions.

RESULTS

The study included 46,201 patients (16,029 patients with prediabetes and 30,173 in the control group). The age of the patients (mean ± SD) with prediabetes was significantly higher than that of the control group (47.22 ± 14.04 versus 36.12 ± 11.83, p < 0.0001). A higher proportion of men was noted in the prediabetes group compared to the control group (36.32% versus 26.54%, p < 0.0001). The body mass index (mean ± SD) was higher in the prediabetes group compared to the control group (33.76 ± 6.75 versus 30.16 ± 7.26, p < 0.0001). The multiple logistic regression analysis showed six independent risk factors associated with prediabetes. These included age (aOR [95% CI] = 1.067 [1.065-1.069]) and gender, with women at a lower risk compared to men (aOR [95% CI] = 0.695 [0.664-0.728]). Other independent risk factors included polycystic ovarian syndrome (aOR [95% CI] = 58.102 (35.731-94.479]), obesity (aOR [95% CI] = 1.265 [1.075-1.487]), cardiac conditions (aOR [95% CI] = 4.870 [1.024-23.154]), and hypertension (aOR [95% CI] = 1.133 [1.031-1.245]).

CONCLUSIONS

The study showed that several risk factors are associated with the development of prediabetes in the Saudi population. Addressing these factors can help prevent prediabetes, and consequently, its burden and further progression to diabetes.

A digital health-supported and community pharmacy-based lifestyle intervention program for adults with pre-diabetes: a study protocol for a cluster randomised controlled trial

INTRODUCTION

Pre-diabetes indicates an elevated risk of developing type-2 diabetes and presents a window for preventive actions. The Pre-diabetes Intervention, Management and Evaluation (PRIME) programme is a community pharmacy-based pre-diabetes management programme that uses a mobile application for self-monitoring and pre-diabetes education, aiming to promote lifestyle changes among participants with pre-diabetes.

METHODS AND ANALYSIS

This is a protocol for a cluster randomised controlled trial that aims to evaluate the impact of the PRIME programme on participants' clinical outcomes and explore participants' and pharmacists' views towards its implementation. This protocol describes the development of the PRIME programme and mobile app, its feasibility and implementation in community pharmacy settings. 16 pharmacies from two states in Malaysia will be randomised to the intervention arm or standard care. The study will include overweight or obese adults with pre-diabetes. During each follow-up visit at the pharmacy, intervention participants will receive in-depth counselling from pharmacists after reviewing their self-monitoring data recorded in the PRIME app. They will also receive pre-diabetes education through the app and join a peer support chatgroup. The primary clinical outcome includes changes in body weight at 6 months, while the secondary clinical outcomes include changes in blood glucose profile, lipid profile, blood pressure and adiposity measures. The sustainability of the PRIME programme will be accessed using a follow-up questionnaire, while participants' engagement with the intervention will be evaluated using attendance rate and the app data. Focus group discussions and one-to-one interviews will be conducted for process evaluation. This study will inform the impact of community pharmacists-led digital health intervention in pre-diabetes management.

ETHICS AND DISSEMINATION

This study has been registered with clinicaltrials.gov (NCT04832984) and approved by the Monash University Human Research Ethics Committee (Project ID: 27512).

TRIAL REGISTRATION NUMBER

clinicaltrials.gov (NCT04832984).

A cohort study on the predictive capability of body composition for diabetes mellitus using machine learning

Purpose

We applied machine learning to study associations between regional body fat distribution and diabetes mellitus in a population of community adults in order to investigate the predictive capability. We retrospectively analyzed a subset of data from the published Fasa cohort study using individual standard classifiers as well as ensemble learning algorithms.

Methods

We measured segmental body composition using the Tanita Analyzer BC-418 MA (Tanita Corp, Japan). The following features were input to our machine learning model: fat-free mass, fat percentage, basal metabolic rate, total body water, right arm fat-free mass, right leg fat-free mass, trunk fat-free mass, trunk fat percentage, sex, age, right leg fat percentage, and right arm fat percentage. We performed classification into diabetes vs. no diabetes classes using linear support vector machine, decision tree, stochastic gradient descent, logistic regression, Gaussian naïve Bayes, k-nearest neighbors (k = 3 and k = 4), and multi-layer perceptron, as well as ensemble learning using random forest, gradient boosting, adaptive boosting, XGBoost, and ensemble voting classifiers with Top3 and Top4 algorithms. 4661 subjects (mean age 47.64 ± 9.37 years, range 35 to 70 years; 2155 male, 2506 female) were analyzed and stratified into 571 and 4090 subjects with and without a self-declared history of diabetes, respectively.

Results

Age, fat mass, and fat percentages in the legs, arms, and trunk were positively associated with diabetes; fat-free mass in the legs, arms, and trunk, were negatively associated. Using XGBoost, our model attained the best excellent accuracy, precision, recall, and F1-score of 89.96%, 90.20%, 89.65%, and 89.91%, respectively.

Conclusions

Our machine learning model showed that regional body fat compositions were predictive of diabetes status.

Reinstating acute-phase insulin release among sedentary adults at high risk for type 2 diabetes with Yoga and Walking based lifestyle modification

BACKGROUND

We compared the impact of 2 lifestyle modifying physical activities, yoga (YBLM) or walking (WBLM) on impaired beta cell function (IBF) or insulin resistance (IR) in restoring acute phase insulin release (APIR) among prediabetes at high risk for type 2 diabetes (HRDM).

METHOD

Male and female adults (N = 42, 38.1 ± 4.8 years) with abdominal obesity (Male:103 ± 8.1 cm) Female: 92 ± 11.1 cm), randomized into YBLM (n = 20) and WBLM (n = 22), were monitored for the practice of the intervention, 45 min a day/5 days a week for 12 weeks. Blood sample was collected at 0th minute to estimate the level of Fasting Blood Glucose (FBG), Sr. Insulin and lipid profile and at 10th minute (APIR). IBF, IR and sensitivity (IS) reading were checked in HOMA-2 calculator.

RESULT

Wilcoxon sign rank t-test denoted an improved APIR among the subjects with IBF (p = 0.008) and not among the subjects with IR (p = 0.332). However, regression analysis yielded an improved APIR among subjects with IBF (F(1,10) = 7.816, p = 0.002) with the management of body weight and lipid profile and IR (F(1,13) = 17.003, p = 0.001) being found influenced with selected lipid components. In all, during the post assessment period, an impressive boost in APIR was manifested among people shifted to Normoglycemia (n = 14, 35.9%).

CONCLUSION

Intriguingly, we postulate the potential role of YBLM over WBLM in the management of lipid profile and body weight on accelerating APIR either through improved Beta cell compensation or by sensitizing skeletal muscles regulating IR, helping improve glucose tolerance resulting in either remission or management of prediabetes.

Measurement of visceral fat for early prediction of prediabetes-Cross-sectional study from Southern India

Objective

Prediabetes is a precursor to type 2 diabetes mellitus and routine screening of prediabetes is crucial. Visceral fat (VF) is associated with prediabetes and insulin resistance. Ethnic and racial differences resulting in different levels of VF in the Indian population necessitates an India-specific study. There is a dearth of literature on the cut-off values of VF measured using a bioelectrical impedance analyzer (BIA) to predict prediabetes in the Indian population. Hence, the main objective of this study was to determine the sex-specific cut-off value of VF on BIA to predict prediabetes in the Indian population.

Methods

Three hundred individuals aged 18-55 years of both sexes were selected for this cross-sectional study. VF was evaluated as a part of body composition analysis using BIA. The body composition variables for the prediction of prediabetes were examined using backward logistic regression. Optimal cut-off levels of VF to predict prediabetes were identified using receiver operator characteristic curve (ROC) analysis.

Results

VF, total fat, and age were found to be associated with prediabetes (p ≤ 0.05). In females, the cut-off value of VF for predicting prediabetes was identified as 8 with 77.8% sensitivity and 69.3% specificity; in males, it was 11 with 84% sensitivity and 62.9% specificity.

Conclusion

This study contributes to the sex-specific cut-off values of VF level on BIA that can be used for predicting prediabetes in the Indian population.

Improvement in the metabolic markers of prediabetic subjects due to the partial substitution of Taiken9 rice by RD43 rice in their daily diet: a randomized clinical trial

Although RD43 rice is characterized by high amounts of undigestible starch, its potential health benefits for prediabetic individuals remain unknown. Thus, the effect of regular consumption of RD43 rice on the glycemic response, body composition, and metabolic markers was investigated in a sample of 34 participants with prediabetes (aged from 32 to 68 years) who were randomly allocated to either the treatment or the control group. The first were required to consume RD43 rice (Glycemic Index [GI] = 78) containing 14.1 g of undigestible starch daily as a substitute for two meals per day while the second were given the Taiken9 rice (GI = 98) for 12 continuous weeks. The evaluations were performed at baseline, at the end of week 6 and 12, and at follow-up conducted two weeks after the intervention had ended. The results obtained at the week 12 assessment clearly showed a significant decrease in fasting plasma glucose, insulin, HbA1c, and HOMA-IR in the group that consumed RD43 rice. In addition, daily ingestion of RD43 rice markedly reduced body weight, Body Mass Index (BMI), total fat mass, and waist circumference at both week 6 and 12 compared with the baseline. When compared with the controls, the treatment group also exhibited a significant decrease in fasting plasma insulin and HOMA-IR at week 12. However, no significant inter- or intra-group differences in lipid profiles were detected. These findings suggest that RD43 rice could be a potential staple food with the capacity to improve glycemic control and body composition in prediabetic individuals.

Predictive performance of lipid parameters in identifying undiagnosed diabetes and prediabetes: a cross-sectional study in eastern China

BACKGROUND

Dyslipidaemia is a risk factor for abnormal blood glucose. However, studies on the predictive values of lipid markers in prediabetes and diabetes simultaneously are limited. This study aimed to assess the associations and predictive abilities of lipid indices and abnormal blood glucose.

METHODS

A sample of 7667 participants without diabetes were enrolled in this cross-sectional study conducted in 2016, and all of them were classified as having normal glucose tolerance (NGT), prediabetes or diabetes. Blood glucose, blood pressure and lipid parameters (triglycerides, TG; total cholesterol, TC; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; non-high-density lipoprotein cholesterol, non-HDL-C; and triglyceride glucose index, TyG) were evaluated or calculated. Logistic regression models were used to analyse the association between lipids and abnormal blood glucose. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of lipid parameters for detecting prediabetes or diabetes.

RESULTS

After adjustment for potential confounding factors, the TyG was the strongest marker related to abnormal blood glucose compared to other lipid indices, with odds ratios of 2.111 for prediabetes and 5.423 for diabetes. For prediabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.605, 0.617, 0.481, 0.615, 0.603, 0.590, 0.626 and 0.660, respectively, and the cut-off points were 1.34, 4.59, 1.42, 2.69, 3.39, 1.00, 3.19 and 8.52, respectively. For diabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.712, 0.679, 0.440, 0.652, 0.686, 0.692, 0.705, and 0.827, respectively, and the cut-off points were 1.35, 4.68, 1.42, 2.61, 3.44, 0.98, 3.13 and 8.80, respectively.

CONCLUSIONS

The TyG, TG and non-HDL-C, especially TyG, are accessible biomarkers for screening individuals with undiagnosed diabetes.

A 16-year prospective cohort study to evaluate effects of long-term fluctuations in obesity indices of prediabetics on the incidence of future diabetes

This study aimed to evaluate the patterns of changes in obesity indices over time in prediabetic subjects and to classify these subjects as either having a low, moderate, and high risk for developing diabetes in the future. This study was conducted among 1228 prediabetics. The patterns of changes in obesity indices based on three measurements including first, mean values during the follow-up period, and last visit from these indices were evaluated by using the latent Markov model (LMM). The mean (standard deviation) age of subjects was 44.0 (6.8) years and 73.6% of them were female. LMM identified three latent states of subjects in terms of change in all anthropometric indices: a low, moderate, and high tendency to progress diabetes with the state sizes (29%, 45%, and 26%), respectively. LMM showed that the probability of transitioning from a low to a moderate tendency to progress diabetes was higher than the other transition probabilities. Based on a long-term evaluation of patterns of changes in obesity indices, our results reemphasized the values of all five obesity indices in clinical settings for identifying high-risk prediabetic subjects for developing diabetes in future and the need for more effective obesity prevention strategies.

Comparative evaluation of inflammatory parameters and substitute insulin resistance indices in elderly women with and without type 2 diabetes mellitus

PURPOSE

To analyze the influence of inflammatory parameters and substitute insulin resistance indices on the risk of type 2 diabetes mellitus (DM) development in elderly women, as well as to compare anthropometric measures and metabolic parameters according to the presence of type 2 DM and HbA1c levels.

PATIENTS AND METHODS

One hundred and twenty elderly women (67.9 ± 6.0 years) were submitted to anthropometric analysis, determination of inflammatory and metabolic parameters. They also underwent indices of lipid accumulation product (LAP), high density triglyceride/lipoprotein ratio (TG/HDL), triglyceride glucose index (TyG), as well as TyG by body mass index (BMI) ratio (TyG-BMI) assessment.

RESULTS

Body mass index, tumor necrosis factor alpha, interleukin-2, blood glucose, TG, LAP, TG/HDL, TyG and TyG-BMI were significantly higher in elderly women with DM compared to non-diabetic women. LAP ≥ 55.4 (OR = 2.29; P = .027); TyG ≥ 8.8 (OR = 3.52; P < .001) and TyG-BMI ≥ 264.8 (OR = 3.54; P = .001) were identified as risk factors for DM.

CONCLUSION

High pro-inflammatory parameters, low levels of anti-inflammatory markers and higher levels of substitute insulin resistance indices are risk predictors for DM development in elderly women in primary health care.

Body composition and handgrip strength in patients with prediabetes: A case-control study from Haryana, North India

BACKGROUND AND AIMS

Previous studies suggest that body composition and handgrip strength are significantly altered in individuals with type 2 diabetes mellitus. Only few studies are available in prediabetic individuals. The aim is to study the change in body composition in adult individuals with prediabetes and compare it with age and sex-matched normoglycemic individuals.

METHODS

100 diagnosed cases of prediabetes and 100 age and sex-matched normoglycemic controls were recruited in the study. Body composition was assessed with Omron HBF 510w and Slim guide skinfold caliper. Handgrip strength was assessed with Camry digital dynamometer.

RESULTS

Out of 100 subjects with prediabetes; 53 were female and 47 were male. In this study, there was higher mean body fat percentage (29.37 ± 5.65 vs 25.46 ± 5.27) and visceral fat (11.21 ± 1.92 vs 7.27 ± 2.82) in individuals with prediabetes compared to normoglycemic individuals. Also, there was a lower mean of skeletal muscle percentage (27.21 ± 4.32 vs 31.19 ± 4.63) and handgrip strength (29.61 ± 6.38 vs 33.75 ± 6.8) in individuals with prediabetes compared to normoglycemic individuals. In this study, body fat percentage was positively correlated (r = 0.3385) with prediabetes. The skeletal muscle percentage (r = -0.40721) and handgrip strength (r = -0.301) were negatively correlated with prediabetes.

CONCLUSIONS

It can be concluded that there is a significant change in body composition and handgrip strength in the individuals with prediabetes, and changes in body composition and handgrip strength can be included as a primary care strategy to motivate lifestyle modifications.

Burden and determinants of multimorbidity among women in reproductive age group: a cross-sectional study based in India

Background: India's government is currently running several programs with a sole focus on women's health during their child-bearing years. However, none of these programs incorporate the management of chronic health conditions during the reproductive span. This issue is an emerging public health concern; therefore, the present study aims to identify the patterns and correlates of multimorbidity among women in reproductive age groups in India. Methods: The study utilizes nationally-representative cross-sectional data from the Demographic and Health Survey on 661,811 women in the reproductive age group of 15-49 years. The study uses information on seven chronic morbidities, namely asthma, cancers, heart disease, diabetes, tuberculosis, hypertension, and thyroid disorder. Descriptive, bivariate, and multivariable techniques were utilized to accomplish the study objective. Results: The findings show that 17.4 and 3.5 per 100 women of reproductive age suffered from any one morbidity and multimorbidity, respectively. Hypertension, diabetes, and thyroid disorders were commonly occurring morbidities. The prevalence of having any one morbidity or multimorbidity increased with age. Variables like religion, wealth, parity, menopause, consumption of tobacco and alcohol, body mass index, and type of diet were found to be significantly related to the burden of multimorbidity. The prevalence of multimorbidity was found to be higher for women who belong to the Southern, Eastern, and North-Eastern regions of India. Conclusions: Findings suggest the importance of multimorbidity in the context of women of reproductive age. Inclusion of chronic disease management strategies with maternal and child health services needs to be taken into consideration by the program and policymakers. The annexation of social marketing approaches at the primary level of healthcare would assist policy-makers in educating women about the importance of leading a healthy lifestyle. Practicing dietary diversity can help in maintaining optimal estrogen levels, which would further help in decreasing multimorbidity rates among women in India.

No Association between 25-Hydroxyvitamin D and Insulin Resistance or Thyroid Hormone Concentrations in a Romanian Observational Study

Background and objectives: Vitamin D is involved in insulin resistance through genomic and non-genomic mechanisms. Several observational and randomized studies have discrepant results; some of them showed an improved insulin resistance (IR), and others a neutral effect after vitamin D deficiency is corrected. Materials and Methods: We designed a retrospective observational study that included all women who presented for 33 months in an outpatient clinic in Bucharest, Romania. Results: We analyzed 353 patients with a mean age of 58.5 ± 13.7 years, a mean body mass index (BMI) of 27.36 ± 4.87 kg/m^-2, and a mean level of 25-hydroxyvitamin D (25OHD) of 39.53 ± 15.73 ng/mL. There were no differences in the calculated Homeostatic Model Assessment of Insulin Resistance variants 1 and 2 (HOMA-IR) and the Quantitative Insulin Sensitivity Check Index (QUICKI) between women with vitamin D deficit versus normal values. In multivariate analysis, there was no significant relation between 25OHD and the response variables considered by us. Conclusions: We observed a small positive correlation between a higher level of 25OHD and increased glycosylated hemolobin (HbA1c) or IR indices without clinical significance. Other modifiable or non-modifiable factors override 25OHD influence on IR in adult women with a normal serum level and may contribute to the remainder of the variability observed.

Burden and determinants of multimorbidity among women in reproductive age group: a cross-sectional study based in India

Background: India's government is currently running several programs with a sole focus on women's health during their child-bearing years. However, none of these programs incorporate the management of chronic health conditions during the reproductive span. This issue is an emerging public health concern; therefore, the present study aims to identify the patterns and correlates of multimorbidity among women in reproductive age groups in India. Methods: The study utilizes nationally-representative cross-sectional data from the Demographic and Health Survey on 661,811 women in the reproductive age group of 15-49 years. The study uses information on seven chronic morbidities, namely asthma, cancers, heart disease, diabetes, tuberculosis, hypertension, and thyroid disorder. Descriptive, bivariate, and multivariable techniques were utilized to accomplish the study objective. Results: The findings show that 17.4 and 3.5 per 100 women of reproductive age suffered from any one morbidity and multimorbidity, respectively. Hypertension, diabetes, and thyroid disorders were commonly occurring morbidities. The prevalence of having any one morbidity or multimorbidity increased with age. Variables like religion, wealth, parity, menopause, consumption of tobacco and alcohol, body mass index, and type of diet were found to be significantly related to the burden of multimorbidity. The prevalence of multimorbidity was found to be higher for women who belong to the Southern, Eastern, and North-Eastern regions of India. Conclusions: Findings suggest the importance of multimorbidity in the context of women of reproductive age. Inclusion of chronic disease management strategies with maternal and child health services needs to be taken into consideration by the program and policymakers. The annexation of social marketing approaches at the primary level of healthcare would assist policy-makers in educating women about the importance of leading a healthy lifestyle. Practicing dietary diversity can help in maintaining optimal estrogen levels, which would further help in decreasing multimorbidity rates among women in India.

Predictive performance of traditional and novel lipid combined anthropometric indices to identify prediabetes

BACKGROUND AND AIMS

Diabetes mellitus is one of the critical public health challenges in the Indian healthcare scenario. Novel anthropometric indices are promising surrogate markers to detect prediabetes compared to the traditional anthropometric indices that only reflect gross obesity. Thus, the authors aim to analyse the potential of three novel lipid combined anthropometric indices in predicting prediabetes in the Asian Indian population.

METHODS

We conducted an age and gender-matched case-control study to identify the predictors of prediabetes. Prediabetes was diagnosed as per the American Diabetes Association (ADA) guidelines 2010. The traditional anthropometric measurements including waist circumference (WC), waist to hip ratio (WHR) and body mass index (BMI) were executed using standardised methods. Fasting lipid profile was obtained and using standardised formulas, the novel lipid combined anthropometric indices such as lipid accumulation product (LAP), visceral adiposity index (VAI) and triglyceride glucose index (TyG index) were derived. TyG related indices such as triglyceride glucose-waist circumference (TyG-WC) and triglyceride glucose-body mass index (TyG-BMI) were also calculated.

RESULTS

The novel lipid combined anthropometric indices LAP, VAI, TyG index, TyG-WC and TyG-BMI were significantly higher in subjects with prediabetes of both the genders (p < 0.05). During receiver operating characteristic (ROC) curve evaluation, TyG index (AUC = 0.802) was the superior predictive measure in males, while in females, TyG-WC (AUC = 0.767) was the best among all the markers.

CONCLUSION

TyG index and TyG-WC seem to be a superior indicator of prediabetes in the Asian Indian population in comparison with other anthropometric indices to screen prediabetes.

Patterns of changes in serum lipid profiles in prediabetic subjects: results from a 16-year prospective cohort study among first-degree relatives of type 2 diabetic patients

BACKGROUND

Lipid abnormality pervasively is associated with the risk of type 2 diabetes mellitus. To the best of our knowledge, there is no study that has examined the longitudinal changes in a wide range of serum lipid profiles in prediabetic subjects in association with the risk of developing type 2 diabetes mellitus in the future. This study aimed to identify the patterns of changes in lipid profiles over time in prediabetic patients and to classify these subjects in order to highlight which patients are at high risk for future diabetes.

METHODS

This prospective 16-year (2003-2019) cohort study was conducted among 1228 prediabetic subjects. The study subjects were followed, and the changes in their lipid profiles, including triglycerides, cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol, were evaluated. The latent Markov model was used for data analysis.

RESULTS

The mean (standard deviation) age of subjects was 44.0 (6.8) years, and 73.6% of them were female. The latent Markov model identified two latent states of subjects in terms of changes in lipid profiles: a low tendency to progress diabetes / high tendency to progress diabetes (74, 26%). The latent Markov model showed that the transition probability from a "low tendency to progress diabetic" state to a "high tendency to progress diabetic" state was lower than the transition probability from "high tendency to progress diabetic" state to "low tendency to progress diabetic" state.

CONCLUSIONS

The present study showed that more than half of the first-degree relatives of T2DM had approximately normal lipid profiles and that these patients are more inclined to transition from a higher- to a lower-tendency diabetic state. These findings confirm the value of regular screening of first-degree relatives of T2DM. Moreover, preventive intervention strategies are recommended to reduce their risk of developing T2DM.

Relation of adipose tissue insulin resistance to prediabetes

PURPOSE

The degree of adipose tissue insulin resistance increases in obesity, prediabetes and type 2 diabetes, but whether it associates with prediabetes is unclear.

METHODS

This is a cross-sectional study of 426 participants. The degree of adipose tissue insulin resistance was assessed using the index of adipose tissue insulin resistance (Adipo-IRI), calculated as the product of fasting insulin and free fatty acids. The association of adipose tissue insulin resistance and prediabetes was assessed by multivariate logistic regression. Area under curves (AUCs) of receiver operating characteristic cure analyses were calculated to assess their diagnostic value in distinguishing prediabetes of the following: insulin resistance in the adipose tissue and peripheral tissue, general and abdominal obesity, and elevated triglycerides.

RESULTS

The median age of the participants was 59 years with males accounting for 47.7%. After adjustment for potential confounding factors, Adipo-IRI was associated with prediabetes and its phenotypes in both genders. The diagnostic value of adipose tissue insulin resistance (AUC, male: 0.71 (95% CI, 0.65-0.77) and female: 0.74 (95% CI, 0.68-0.95)) for prediabetes were superior or similar to peripheral tissue insulin resistance, body mass index, waist circumference and triglycerides.

CONCLUSIONS

Adipose tissue insulin resistance is associated with prediabetes and should be considered for use in population studies.

Tracking lipid profile and atherogenic indices in the prediabetics of Andaman Nicobar Islands: A retrospective hospital-based study

CONTEXT

Cardio vascular disease (CVD) is the leading cause of mortality and morbidity in diabetes mellitus (DM) contributing to 65% of all deaths with diabetic complications. The most important cause of CVD is atherosclerosis, and dyslipidemia acts as a marker of developing atherosclerosis. The derangement of lipid profile and atherogenic indices start in the prediabetic state, much before the development of DM. Detection of the deranged lipid profile and atherogenic indices in the prediabetic state can help devise the aggressive treatment strategy right from this stage, so as to arrest the development of CVD as a complication of diabetes.

AIMS

To compare the lipid profile and atherogenic indices of prediabetics with controls and diabetics.

SETTINGS AND DESIGN

The electronic medical records of 239 subjects were reviewed retrospectively.

MATERIALS AND METHODS

About 187 cases consisting of 137 diabetics and 50 prediabetics were evaluated for serum fasting blood sugar, post prandial blood sugar, HbA1c, total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (HDLc), and low-density lipoprotein cholesterol (LDLc). Atherogenic indices [TC/HDLc, LDLc/HDLc, (TC-HDLc)/HDLc, TG/HDLc] were also evaluated in the two groups. Rest 52 age- and sex-matched subjects were taken as controls.

STATISTICAL ANALYSIS USED

The comparisons were evaluated using SPSS statistical package version 20.

RESULTS

TC, TG, LDLc, and the atherogenic indices were significantly increased in prediabetics as compared with controls. HDLc was significantly decreased in prediabetics.

CONCLUSIONS

The altered lipid profile and atherogenic indices in prediabetics signify the increased susceptibility of prediabetics to CVD in the long run. Hence, we recommend screening of prediabetics for dyslipidemia to arrest the development of cardiovascular complications.