Aug 2026· Frontiers in Clinical Diabetes and Healthcare· Vol 7· 0 citations· 42 references
Medicine
TL;DR
This study identified and temporally validated key metabolic and clinical markers associated with prevalent T2D in obese Indians using age- and sex-matched case-control analysis and demonstrated good discrimination in obese Indian individuals.
Abstract
Introduction Type 2 diabetes (T2D) is a significant metabolic disorder with disproportionately high burden in obese South Asian populations, yet not all obese individuals develop the disease. This study identified the metabolic, inflammatory, and pharmacological markers associated with prevalent T2D in obese Indians using age- and sex-matched case-control analysis. Methods A matched-pair analysis was performed on 514 age- and sex-matched pairs with and without T2D. Patients had obesity [body mass index (BMI) 25–45 kg/m², aged 20–75 years] and participated in a one-year lifestyle intervention program in India. Anthropometric, biochemical markers and medical history were analyzed. Homeostatic model assessment for insulin resistance (HOMA2IR) and beta-cell function (HOMA2%B) was calculated. Significant markers were incorporated into a logistic regression model and temporally validated in an independent time-cohort (n=966). Performance was evaluated through discrimination [receiver operating characteristics area under the curve (ROC-AUC)], calibration, and decision curve analysis. A nomogram was constructed based on the logistic regression model. Results Median age and BMI were 46 (IQR 12) years and 29.7 (IQR 5.5) kg/m². Key markers associated with prevalent T2D were poor beta-cell function (HOMA2%B ≤50; OR = 40.9, 95% CI: 24.5–68.2), insulin resistance (HOMA2IR ≥2; OR = 4.5, 95% CI: 3.0–6.7), low HDL-C (OR = 2.1, 95% CI: 1.5–3.0), elevated hsCRP ≥3 mg/L (OR = 1.9, 95% CI: 1.4–2.7), Obesity Class I (BMI 25.0–29.9 kg/m²; OR = 2.1, 95% CI: 1.5–2.9), and antihypertensive medication use (OR = 1.7, 95% CI: 1.2–2.4). Model discrimination was good (AUC 0.860 development, 0.865 validation, both p<0.001). The Hosmer-Lemeshow test showed good model fit (p=0.562). Isotonic-calibrated Models 1 and 2 had Brier scores 0.14 and 0.162, indicating acceptable calibration. Decision curve analysis confirmed net clinical benefit across threshold probabilities 0.10–0.85. Conclusion This study identified and temporally validated key metabolic and clinical markers associated with prevalent T2D, demonstrating good discrimination (AUC 0.860) in obese Indian individuals. External validation and prospective evaluation are needed before clinical application.
The metabolic phenotypes were explored in a primary care T2DM cohort, supporting their reproducibility across clinical settings and vitamin D status varied by phenotype severity, with more severe phenotypes more likely to exhibit insufficiency.
Liliane Viana Pires, Matheus Menezes-Santos, Andréa Costa Goes et al.· Diabetes, obesity and metabo...· 0 citations
OBJECTIVE
To examine whether sarcopenic obesity (SO) is associated with incident type 2 diabetes (T2D) beyond obesity or sarcopenia alone and whether associations differ by sex, age, and transitions in body composition phenotypes over time.
RESEARCH DESIGN AND METHODS
We studied 479,607 diabetes-free UK Biobank participants. SO was defined using handgrip strength, skeletal muscle mass-to-weight ratio, and fat mass percentage. Cox models estimated hazard ratios (HRs). A landmark analysis (n = 53,107) examined phenotype transitions.
RESULTS
Over a median follow-up of 14.2 years, T2D developed in 32,948 participants. SO conferred the highest risk (HR 3.54 [95% CI 3.34-3.74]), exceeding obesity alone and sarcopenia alone. Transitioning to SO (HR 2.90 [95% CI 2.07-4.07]) and persistent SO (HR 3.07 [95% CI 1.63-5.79]) both elevated risks.
CONCLUSIONS
SO was associated with higher T2D risk than obesity or sarcopenia alone, supporting integrated assessment of muscle health and adiposity in T2D risk stratification.
Z. Guan, Blossom C. M. Stephan, Mario Siervo· Diabetes Care· 0 citations
BACKGROUND
Poor glycaemic control is common among adults with type 2 diabetes mellitus (T2DM) in low- and middle-income settings in South-Eastern Europe, yet patient-level data on its correlates from Albania are scarce. We examined the demographic, clinical and treatment-related factors associated with poor glycaemic control (HbA1c ≥ 7%) in Albanian adults with T2DM.
METHODS
Cross-sectional study of 176 consecutive adults with T2DM attending a hospital-based outpatient diabetes service in northern Albania. Poor glycaemic control was defined a priori as HbA1c ≥ 7% (53 mmol/mol). Sociodemographic characteristics, diabetes duration, insulin therapy and physician-confirmed comorbidities were recorded. Associations were assessed using univariate and multivariable logistic regression, estimating odds ratios (OR) with 95% confidence intervals (CI); comorbidity was modelled both as individual conditions (primary model) and as a comorbidity-burden index (sensitivity model). Model calibration and discrimination were evaluated using the Hosmer-Lemeshow test and the area under the ROC curve.
RESULTS
Mean age was 65 years, 51% were men and mean diabetes duration was 11 years. The prevalence of poor glycaemic control was 58.5% (95% CI 50.9-65.9%), and 54% were receiving insulin. In univariate analyses, poor control was more frequent with insulin therapy (OR 5.64, 95% CI 2.93-10.87), longer diabetes duration (OR 1.42 per 5 years, 1.09-1.85) and ischaemic heart disease (OR 2.10, 1.09-4.08). After mutual adjustment, insulin therapy was the only factor independently associated with poor control (adjusted OR 6.32, 95% CI 2.71-14.71); age, diabetes duration, hypertension, ischaemic heart disease and multimorbidity were not. Results were unchanged in the sensitivity model. The primary model was well calibrated (Hosmer-Lemeshow p = 0.96), with moderate discrimination (area under the ROC curve 0.74).
CONCLUSIONS
In this Albanian outpatient population, poor glycaemic control was common and insulin therapy was the only factor independently associated with it. This reflects confounding by indication rather than harm from insulin: insulin is initiated when oral therapy no longer maintains targets, so insulin-treated patients form a clinically identifiable subgroup with more advanced disease who warrant priority for structured treatment intensification and individualised follow-up. Prospective multicentre studies are needed to confirm these associations and their temporal direction.
TRIAL REGISTRATION
Not applicable (observational, non-interventional study).
AIM
To determine the prevalence of overweight and obesity among youth with type 1 diabetes (T1D) in a multi-ethnic cohort and examine associations with clinical characteristics.
METHODS
We conducted a retrospective study of all participants enrolled in the Accurate Diagnosis in Diabetes for Appropriate Management (ADDAM) Biobank at the Montreal Children's Hospital (n = 352). Logistic regression was used to evaluate associations between overweight/obesity (BMI ≥ 85th percentile for age and sex) and age, sex, diabetes duration, hemoglobin A1C, genetic ancestry, and weight-adjusted total daily insulin dose.
RESULTS
Overall, 70.5% of participants had BMI < 85th percentile, while 29.5% had BMI ≥ 85th percentile, including 10.7% with obesity (BMI > 95th percentile). Higher weight-adjusted total daily insulin dose was independently associated with BMI ≥ 85th percentile. However, when analyses were restricted to participants with obesity, this association was no longer statistically significant after multivariable adjustment (P = 0.06).
CONCLUSIONS
Nearly one-third of youth with T1D in this cohort had overweight or obesity. Higher weight-adjusted insulin requirements may reflect increased insulin resistance in this population. Further studies are needed to identify modifiable risk factors and inform obesity prevention strategies in youth with T1D.
Marie-Edelyne St Jacques, J. L. Guevara, R. Agnihotram et al.· Diabetes Research and Clinic...· 0 citations