Associations of the glycaemic index and the glycaemic load with risk of type 2 diabetes in 127 594 people from 20 countries (PURE): a prospective cohort study.

BACKGROUND: The association between the glycaemic index and the glycaemic load with type 2 diabetes incidence is controversial. We aimed to evaluate this association in an international cohort with diverse glycaemic index and glycaemic load diets. METHODS: The PURE study is a prospective cohort study of 127 594 adults aged 35-70 years from 20 high-income, middle-income, and low-income countries. Diet was assessed at baseline using country-specific validated food frequency questionnaires. The glycaemic index and the glycaemic load were estimated on the basis of the intake of seven categories of carbohydrate-containing foods. Participants were categorised into quintiles of glycaemic index and glycaemic load. The primary outcome was incident type 2 diabetes. Multivariable Cox Frailty models with random intercepts for study centre were used to calculate hazard ratios (HRs). FINDINGS: During a median follow-up of 11·8 years (IQR 9·0-13·0), 7326 (5·7%) incident cases of type 2 diabetes occurred. In multivariable adjusted analyses, a diet with a higher glycaemic index was significantly associated with a higher risk of diabetes (quintile 5 vs quintile 1; HR 1·15 [95% CI 1·03-1·29]). Participants in the highest quintile of the glycaemic load had a higher risk of incident type 2 diabetes compared with those in the lowest quintile (HR 1·21, 95% CI 1·06-1·37). The glycaemic index was more strongly associated with diabetes among individuals with a higher BMI (quintile 5 vs quintile 1; HR 1·23 [95% CI 1·08-1·41]) than those with a lower BMI (quintile 5 vs quintile 1; 1·10 [0·87-1·39]; p interaction=0·030). INTERPRETATION: Diets with a high glycaemic index and a high glycaemic load were associated with a higher risk of incident type 2 diabetes in a multinational cohort spanning five continents. Our findings suggest that consuming low glycaemic index and low glycaemic load diets might prevent the development of type 2 diabetes. FUNDING: Full funding sources are listed at the end of the Article.

Barriers to the Use of Insulin Therapy and Potential Solutions: A Narrative Review of Perspectives from the Asia-Pacific Region.

The rising prevalence of type 2 diabetes (T2D) is posing major challenges for the healthcare systems of many countries, particularly in the Asia-Pacific Region, in which T2D can present at younger ages and lower body mass index when compared with Western nations. There is an important role for insulin therapy in the management of T2D in these nations, but available evidence suggests that insulin is under-utilized and often delayed, to the detriment of patient prognosis. The authors of this article gathered as an advisory panel (representative of some of the larger Asia-Pacific nations) to identify their local barriers to insulin use in T2D, and to discuss ways in which to address these barriers, with their outputs summarized herein. Many of the key barriers identified are well-documented issues of global significance, including a lack of healthcare resources or of an integrated structure, insufficient patient education, and patient misconceptions about insulin therapy. Barriers identified as more innate to Asian countries included local inabilities of patients to afford or gain access to insulin therapy, a tendency for some patients to be more influenced by social media and local traditions than by the medical profession, and a willingness to switch care providers and seek alternative therapies. Strategies to address some of these barriers are provided, with hypothetical illustrative case histories.

Performance of European prediction models for classification of type 1 and type 2 diabetes in Indians.

AIM: We aimed to determine the performance of European prediction models in an Indian population to classify type 1 diabetes(T1D) and type 2 diabetes(T2D). METHODS: We assessed discrimination and calibration of published models of diabetes classification, using retrospective data from electronic medical records of 83309 participants aged 18-50 years living in India. Diabetes type was defined based on C-peptide measurement and early insulin requirement. Models assessed combinations of clinical measurements: age at diagnosis, body mass index(mean = 26.6 kg/m2), sex(male = 64.9 %), Glutamic acid decarboxylase(GAD) antibody, serum cholesterol, serum triglycerides, and high-density lipoprotein(HDL) cholesterol. RESULTS: 67955 participants met inclusion criteria, of whom 0.8 % had T1D, which was markedly lower than model development cohorts. Model discrimination for clinical features was broadly similar in our Indian cohort compared to the European cohort: area under the receiver operating characteristic curve(AUC ROC) was 0.90 vs. 0.90 respectively, but was lower in the subset of young participants with measured GAD antibodies(n = 2404): and an AUC ROC of 0.87 when clinical features, sex, lipids and GAD antibodies were combined. All models substantially overestimated the likelihood of T1D, reflecting the lower prevalence of T1D in the Indian population. However, good model performance was achieved after recalibration by updating the model intercept and slope. CONCLUSION: Models for diabetes classification maintain the discrimination of T1D and T2D in this Indian population, where T2D is far more common, but require recalibration to obtain appropriate model probabilities. External validation and recalibration are needed before these tools can be used in non-European populations.

Construct validity of the 12-item Short Form Health Survey (SF-12) version 2 and the impact of lifestyle modifications on the health-related quality of life among Indian adults with prediabetes: results from the D-CLIP trial.

PURPOSE: This study aimed to validate the factor structure of the 12-item Short-Form (SF-12) health-related quality of life (HRQOL) survey for Indian adults and assess the impact of lifestyle modification on the SF-12 of Indian adults with prediabetes. METHODS: To validate the context-specific construct of the SF-12, two-factor confirmatory factor analysis (CFA) was performed using data from 1285 adults residing in Chennai, India, who screened for the Diabetes Community Lifestyle Improvement Program (D-CLIP). D-CLIP was a randomized controlled trial of 578 participants with prediabetes (283 treatment, 293 control), focusing on the effect of lifestyle modifications on the prevention of diabetes. Physical and mental component scores (PCS and MCS) were computed by using CFA standardized factor loadings. Multiple linear regression was subsequently conducted to estimate the effect of lifestyle modification on post-study changes of PCS and MCS among D-CLIP participants. RESULTS: Cronbach's alpha and CFA fit indices demonstrated acceptable reliability and model fit of the SF-12 for Indian adults. The intervention group showed greater mean change in PCS after study participation compared to the controls (1.63 ± 0.82, p = 0.046); no significant difference was observed for MCS between two groups (1.00 ± 0.85, p = 0.242). CONCLUSION: The study confirmed that the SF-12 is suitable for assessing the physical and mental health dimensions of HRQOL for Indian adults. Our findings suggest that the benefits of diabetes prevention lifestyle modification strategies may primarily enhance the physical well-being of adults with prediabetes. Further studies validating the SF-12 in a broader Asian Indian population are needed. TRIAL REGISTRATION: Clinicaltrials.gov, NCT01283308.

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities.

Background: Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse. Methods: Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders. Results: The mean annual exposure in Chennai and Delhi was 40 and 102 µg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi. Conclusion: These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

Circulatory levels of lysophosphatidylcholine species in obese adolescents: Findings from cross-sectional and prospective lipidomics analyses.

BACKGROUND AND AIMS: Obesity has reached epidemic proportions, emphasizing the importance of reliable biomarkers for detecting early metabolic alterations and enabling early preventative interventions. However, our understanding of the molecular mechanisms and specific lipid species associated with childhood obesity remains limited. Therefore, the aim of this study was to investigate plasma lipidomic signatures as potential biomarkers for adolescent obesity. METHODS AND RESULTS: A total of 103 individuals comprising overweight/obese (n = 46) and normal weight (n = 57) were randomly chosen from the baseline ORANGE (Obesity Reduction and Noncommunicable Disease Awareness through Group Education) cohort, having been followed up for a median of 7.1 years. Plasma lipidomic profiling was performed using the UHPLC-HRMS method. We used three different models adjusted for clinical covariates to analyze the data. Clustering methods were used to define metabotypes, which allowed for the stratification of subjects into subgroups with similar clinical and metabolic profiles. We observed that lysophosphatidylcholine (LPC) species like LPC.16.0, LPC.18.3, LPC.18.1, and LPC.20.3 were significantly (p < 0.05) associated with baseline and follow-up BMI in adolescent obesity. The association of LPC species with BMI remained consistently significant even after adjusting for potential confounders. Moreover, applying metabotyping using hierarchical clustering provided insights into the metabolic heterogeneity within the normal and obese groups, distinguishing metabolically healthy individuals from those with unhealthy metabolic profiles. CONCLUSION: The specific LPC levels were found to be altered and increased in childhood obesity, particularly during the follow-up. These findings suggest that LPC species hold promise as potential biomarkers of obesity in adolescents, including healthy and unhealthy metabolic profiles.

Regression From Early GDM to Normal Glucose Tolerance and Adverse Pregnancy Outcomes in the Treatment of Booking Gestational Diabetes Mellitus Study.

OBJECTIVE: To compare pregnancy outcomes among women with a normal oral glucose tolerance test (OGTT) before 20 weeks' gestation (early) and at 24-28 weeks' gestation (late) (no gestational diabetes mellitus, or No-GDM), those with early GDM randomized to observation with a subsequent normal OGTT (GDM-Regression), and those with GDM on both occasions (GDM-Maintained). RESEARCH DESIGN AND METHODS: Women at <20 weeks' gestation with GDM risk factors who were recruited for a randomized controlled early GDM treatment trial were included. Women with treated early GDM and late GDM (according to the World Health Organization's 2013 criteria) were excluded from this analysis. Logistic regression compared pregnancy outcomes. RESULTS: GDM-Regression (n = 121) group risk factor profiles and OGTT results generally fell between the No-GDM (n = 2,218) and GDM-Maintained (n = 254) groups, with adjusted incidences of pregnancy complications similar between the GDM-Regression and No-GDM groups. CONCLUSIONS: Women with early GDM but normal OGTT at 24-28 weeks' gestation had pregnancy outcomes that were similar to those of individuals without GDM. Identifying early GDM likely to regress would allow treatment to be avoided.

Natural History of Type 2 Diabetes in Indians: Time to Progression.

OBJECTIVE: To describe the natural history of diabetes in Indians. RESEARCH DESIGN AND METHODS: Data are from participants older than 20 years in the Centre for Cardiometabolic Risk Reduction in South Asia longitudinal study. Glycemic states were defined per American Diabetes Association criteria. Markov models were used to estimate annual transition probabilities and sojourn time through states. RESULTS: Among 2,714 diabetes-free participants, 641 had isolated impaired fasting glucose (iIFG), and 341 had impaired glucose tolerance (IGT). The annual transition to diabetes for those with IGT was 13.9% (95% CI 12.0, 15.9) versus 8.6% (7.3, 9.8) for iIFG. In the normoglycemia ↔ iIFG → diabetes model, mean sojourn time in normoglycemia was 40.3 (34.6, 48.2) years, and sojourn time in iIFG was 9.7 (8.4, 11.4) years. For the normoglycemia ↔ IGT → diabetes model, mean sojourn time in normoglycemia was 34.5 (29.5, 40.8) years, and sojourn time in IGT was 6.1 (5.3, 7.1) years. CONCLUSIONS: Individuals reside in normoglycemia for 35-40 years; however, progression from prediabetes to diabetes is rapid.

National prevalence of vision impairment and blindness and associated risk factors in adults aged 40 years and older with known or undiagnosed diabetes: results from the SMART-India cross-sectional study.

BACKGROUND: National estimates of the prevalence of vision impairment and blindness in people with diabetes are required to inform resource allocation. People with diabetes are more susceptible to conditions such as diabetic retinopathy that can impair vision; however, these are often missed in national studies. This study aims to determine the prevalence and risk factors of vision impairment and blindness in people with diabetes in India. METHODS: Data from the SMART-India study, a cross-sectional survey with national coverage of 42 147 Indian adults aged 40 years and older, collected using a complex sampling design, were used to obtain nationally representative estimates for the prevalence of vision impairment and blindness in people with diabetes in India. Vulnerable adults (primarily those who did not have capacity to provide consent); pregnant and breastfeeding women; anyone deemed too ill to be screened; those who did not provide consent; and people with type 1 diabetes, gestational diabetes, or secondary diabetes were excluded from the study. Vision impairment was defined as presenting visual acuity of 0·4 logMAR or higher and blindness as presenting a visual acuity of 1·0 logMAR or higher in the better-seeing eye. Demographic, anthropometric, and laboratory data along with geographic distribution were analysed in all participants with available data. Non-mydriatic retinal images were used to grade diabetic retinopathy, and risk factors were also assessed. FINDINGS: A total of 7910 people with diabetes were included in the analysis, of whom 5689 had known diabetes and 2221 were undiagnosed. 4387 (55·5%) of 7909 participants with available sex data were female and 3522 (44·5%) participants were male. The estimated national prevalence of vision impairment was 21·1% (95% CI 15·7-27·7) and blindness 2·4% (1·7-3·4). A higher prevalence of any vision impairment (29·2% vs 19·6%; p=0·016) and blindness (6·7% vs 1·6%; p<0·0001) was observed in those with ungradable images. In known diabetes, diabetic retinopathy (adjusted odds ratio [aOR] 3·06 [95% CI 1·25-7·51]), vision-threatening diabetic retinopathy (aOR 7·21 [3·52-14·75]), and diabetic macular oedema (aOR 5·41 [2·20-13·33]) were associated with blindness in adjusted analysis. Common sociodemographic risk factors for vision impairment and blindness include older age, lower educational attainment, and unemployment. INTERPRETATION: Based on the estimated 101 million people with diabetes in 2021 and the interpretation of the data from this study, approximately 21 million people with diabetes have vision impairment in India, of whom 2·4 million are blind. Higher prevalence is observed in those from lower socio-economic strata and policy makers should focus on these groups to reduce inequalities in health care. FUNDING: Global Challenge Research Fund of United Kingdom Research and Innovation through the Medical Research Council.

International Diabetes Federation Position Statement on the 1-hour post-load plasma glucose for the diagnosis of intermediate hyperglycaemia and type 2 diabetes.

Many individuals with intermediate hyperglycaemia (IH), including impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT), as presently defined, will progress to type 2 diabetes (T2D). There is confirmatory evidence that T2D can be prevented by lifestyle modification and/or medications, in people with IGT diagnosed by 2-h plasma glucose (PG) during a 75-gram oral glucose tolerance test (OGTT). Over the last 40 years, a wealth of epidemiological data has confirmed the superior value of 1-h plasma glucose (PG) over fasting PG (FPG), glycated haemoglobin (HbA1c) and 2-h PG in populations of different ethnicity, sex and age in predicting diabetes and associated complications including death. Given the relentlessly rising prevalence of diabetes, a more sensitive, practical method is needed to detect people with IH and T2D for early prevention or treatment in the often lengthy trajectory to T2D and its complications. The International Diabetes Federation (IDF) Position Statement reviews findings that the 1-h post-load PG ≥ 155 mg/dL (8.6 mmol/L) in people with normal glucose tolerance (NGT) during an OGTT is highly predictive for detecting progression to T2D, micro- and macrovascular complications, obstructive sleep apnoea, cystic fibrosis-related diabetes mellitus, metabolic dysfunction-associated steatotic liver disease, and mortality in individuals with risk factors. The 1-h PG of 209 mg/dL (11.6 mmol/L) is also diagnostic of T2D. Importantly, the 1-h PG cut points for diagnosing IH and T2D can be detected earlier than the recommended 2-h PG thresholds. Taken together, the 1-h PG provides an opportunity to avoid misclassification of glycaemic status if FPG or HbA1c alone are used. The 1-h PG also allows early detection of high-risk people for intervention to prevent progression to T2D which will benefit the sizeable and growing population of individuals at increased risk of T2D. Using a 1-h OGTT, subsequent to screening with a non-laboratory diabetes risk tool, and intervening early will favourably impact the global diabetes epidemic. Health services should consider developing a policy for screening for IH based on local human and technical resources. People with a 1-h PG ≥ 155 mg/dL (8.6 mmol/L) are considered to have IH and should be prescribed lifestyle intervention and referred to a diabetes prevention program. People with a 1-h PG ≥ 209 mg/dL (11.6 mmol/L) are considered to have T2D and should have a repeat test to confirm the diagnosis of T2D and then referred for further evaluation and treatment. The substantive data presented in the Position Statement provides strong evidence for redefining current diagnostic criteria for IH and T2D by adding the 1-h PG.

Lipid Association of India 2023 update on cardiovascular risk assessment and lipid management in Indian patients: Consensus statement IV.

OBJECTIVE: In 2016, the Lipid Association of India (LAI) developed a cardiovascular risk assessment algorithm and defined low-density lipoprotein cholesterol (LDL-C) goals for prevention of atherosclerotic cardiovascular disease (ASCVD) in Indians. The recent refinements in the role of various risk factors and subclinical atherosclerosis in prediction of ASCVD risk necessitated updating the risk algorithm and treatment goals. METHODS: The LAI core committee held twenty-one meetings and webinars from June 2022 to July 2023 with experts across India and critically reviewed the latest evidence regarding the strategies for ASCVD risk prediction and the benefits and modalities for intensive lipid lowering. Based on the expert consensus and extensive review of published data, consensus statement IV was commissioned. RESULTS: The young age of onset and a more aggressive nature of ASCVD in Indians necessitates emphasis on lifetime ASCVD risk instead of the conventional 10-year risk. It also demands early institution of aggressive preventive measures to protect the young population prior to development of ASCVD events. Wide availability and low cost of statins in India enable implementation of effective LDL-C lowering therapy in individuals at high risk of ASCVD. Subjects with any evidence of subclinical atherosclerosis are likely to benefit the most from early aggressive interventions. CONCLUSIONS: This document presents the updated risk stratification and treatment algorithm and describes the rationale for each modification. The intent of these updated recommendations is to modernize management of dyslipidemia in Indian patients with the goal of reducing the epidemic of ASCVD among Indians in Asia and worldwide.

Perinatal Outcomes in Early and Late Gestational Diabetes Mellitus After Treatment From 24-28 Weeks' Gestation: A TOBOGM Secondary Analysis.

OBJECTIVE: In most gestational diabetes mellitus (GDM) studies, cohorts have included women combined into study populations without regard to whether hyperglycemia was present earlier in pregnancy. In this study we sought to compare perinatal outcomes between groups: women with early GDM (EGDM group: diagnosis before 20 weeks but no treatment until 24-28 weeks if GDM still present), with late GDM (LGDM group: present only at 24-28 weeks), and with normoglycemia at 24-28 weeks (control subjects). RESEARCH DESIGN AND METHODS: This is a secondary analysis of a randomized controlled treatment trial where we studied, among women with risk factors, early (<20 weeks' gestation) GDM defined according to World Health Organization 2013 criteria. Those receiving early treatment for GDM treatment were excluded. GDM was treated if present at 24-28 weeks. The primary outcome was a composite of birth before 37 weeks' gestation, birth weight ≥4,500 g, birth trauma, neonatal respiratory distress, phototherapy, stillbirth/neonatal death, and shoulder dystocia. Comparisons included adjustment for age, ethnicity, BMI, site, smoking, primigravity, and education. RESULTS: Women with EGDM (n = 254) and LGDM (n = 467) had shorter pregnancy duration than control subjects (n = 2,339). BMI was lowest with LGDM. The composite was increased with EGDM (odds ratio [OR] 1.59, 95% CI 1.18-2.12)) but not LGDM (OR 1.19, 95% CI 0.94-1.50). Induction of labor was higher in both GDM groups. In comparisons with control subjects there were higher birth centile, higher preterm birth rate, and higher rate of neonatal jaundice for the EGDM group (but not the LGDM group). The greatest need for insulin and/or metformin was with EGDM. CONCLUSIONS: Adverse perinatal outcomes were increased with EGDM despite treatment from 24-28 weeks' gestation, suggesting the need to initiate treatment early, and more aggressively, to reduce the effects of exposure to the more severe maternal hyperglycemia from early pregnancy.

Association of pro-inflammatory cytokines, adipokines and hepatokine with incident diabetes in India: a nested case-control study within CARRS cohort.

AIMS: To study the association of pro-inflammatory markers with incident diabetes in India. METHODS: We did a nested case-control study within the CARRS (Centre for Ardiometabolic Risk Reduction in South Asia) cohort. Of the 5739 diabetes-free individuals at the baseline, 216 participants with incident diabetes and 432 age-, gender- and city-matched controls at 2-year follow-up were included. We measured high sensitive C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 ( MCP-1), adiponectin, leptin and fetuin-A in the stored baseline blood samples. We did multivariate conditional logistic regression to estimate association of inflammatory markers (as quartiles) and incident diabetes. Covariates were baseline fasting plasma glucose (FPG) and lipids, body mass index (BMI), family history of diabetes, smoking and alcohol use. RESULTS: Baseline hsCRP and TNF-α were higher, and IL-6 and adiponectin were lower among cases vs. controls. In multivariate conditional logistic regression models, only quartile-3 (odds ratio [OR]: 2.96 [95% CI:1.39, 6.30]) and quartile-4 (OR: 2.58 [95% CI: 1.15, 5.79]) of TNF-α and quartile-4 of MCP-1 (OR: 2.55 [95% CI: 1.06, 6.16]) were positively associated with diabetes after adjusting for baseline FPG and BMI. These associations did not remain after adjusting for family history. High level (quartile-4) of IL-6 was negatively associated with diabetes after adjusting for all factors (OR: 0.18 [95% CI: 0.06, 0.55]). CONCLUSIONS: Higher TNF-α and MCP-1 levels and lower IL-6 were associated with higher risk of developing diabetes. Better understanding and potential methods of addressing these biomarkers, especially in relation to family history, are needed to address diabetes in South Asians.

Association of collaborative care intervention features with depression and metabolic outcomes in the INDEPENDENT study: A mixed methods study.

AIMS: The INtegrating DEPrEssioN and Diabetes treatmENT (INDEPENDENT) trial tested a collaborative care model including electronic clinical decision support (CDS) for treating diabetes and depression in India. We aimed to assess which features of this clinically and cost-effective intervention were associated with improvements in diabetes and depression measures. METHODS: Post-hoc analysis of the INDEPENDENT trial data (189 intervention participants) was conducted to determine each intervention feature's effect: 1. Collaborative case reviews between expert psychiatrists and the care team; 2. Patient care-coordinator contacts; and 3. Clinicians' CDS prompt modifications. Primary outcome was baseline-to-12-months improvements in diabetes control, blood pressure, cholesterol, and depression. Implementer interviews revealed barriers and facilitators of intervention success. Joint displays integrated mixed methods' results. RESULTS: High baseline HbA1c≥ 74.9 mmol/mol (9%) was associated with 5.72 fewer care-coordinator contacts than those with better baseline HbA1c (76.8 mmol/mol, 9.18%, p < 0.001). Prompt modification proportions varied from 38.3% (diabetes) to 1.3% (LDL). Interviews found that providers' and participants' visit frequencies were preference dependent. Qualitative data elucidated patient-level factors that influenced number of clinical contacts and prompt modifications explaining their lack of association with clinical outcomes. CONCLUSION: Our mixed methods approach underlines the importance of the complementarity of different intervention features. Qualitative findings further illuminate reasons for variations in fidelity from the core model.

Perceived stress and progression of cardiometabolic risk factors among South Asians with prediabetes in a lifestyle intervention trial.

AIMS: To examine associations between perceived stress and cardiometabolic risk factors in South Asians with prediabetes and assess whether a diabetes prevention program mitigates the impact of stress on cardiometabolic health. METHODS: We conducted a secondary analysis of the Diabetes Community Lifestyle Improvement Program, a lifestyle modification trial for diabetes prevention in India (n = 564). Indicators for cardiometabolic health (weight, waist circumference, blood pressure, glucose, HbA1c, and lipids) were measured at each visit while perceived stress was assessed via questionnaire at baseline. Multivariable linear regression assessed associations between stress and cardiometabolic parameters at baseline and 3-year follow up. RESULTS: At baseline, perceived stress was associated with higher weight (b=0.16; 95% CI: 0.04, 0.29) and waist circumference (b=0.11; 95% CI: 0.01, 0.21) but lower 30-minute postload glucose (b=-0.44; 95% CI: -0.76, -0.14) and LDL cholesterol (b=-0.40; 95% CI: -0.76, -0.03). Over the study period, perceived stress was associated with weight gain (b=0.20; 95% CI: 0.07, 0.33) and increased waist circumference (b=0.14; 95% CI: 0.04, 0.24). Additionally, higher perceived stress was associated with lower HDL cholesterol among the control arm (pinteraction = 0.02). CONCLUSIONS: Baseline stress was associated with negative cardiometabolic risk factor outcomes over time in those with prediabetes.

Evaluating bias with loss to follow-up in a community-based cohort: empirical investigation from the CARRS Study.

BACKGROUND: Retention of participants is a challenge in community-based longitudinal cohort studies. We aim to evaluate the factors associated with loss to follow-up and estimate attrition bias. METHODS: Data are from an ongoing cohort study, Center for cArdiometabolic Risk Reduction in South Asia (CARRS) in India (Delhi and Chennai). Multinomial logistic regression analysis was used to identify sociodemographic factors associated with partial (at least one follow-up) or no follow-up (loss to follow-up). We also examined the impact of participant attrition on the magnitude of observed associations using relative ORs (RORs) of hypertension and diabetes (prevalent cases) with baseline sociodemographic factors. RESULTS: There were 12 270 CARRS cohort members enrolled in Chennai and Delhi at baseline in 2010, and subsequently six follow-ups were conducted between 2011 and 2022. The median follow-up time was 9.5 years (IQR: 9.3-9.8) and 1048 deaths occurred. Approximately 3.1% of participants had no follow-up after the baseline visit. Younger (relative risk ratio (RRR): 1.14; 1.04 to 1.24), unmarried participants (RRR: 1.75; 1.45 to 2.11) and those with low household assets (RRR: 1.63; 1.44 to 1.85) had higher odds of being lost to follow-up. The RORs of sociodemographic factors with diabetes and hypertension did not statistically differ between baseline and sixth follow-up, suggesting minimal potential for bias in inference at follow-up. CONCLUSION: In this representative cohort of urban Indians, we found low attrition and minimal bias due to the loss to follow-up. Our cohort's inconsistent participation bias shows our retention strategies like open communication, providing health profiles, etc have potential benefits.

Wide-field imaging with smartphone based fundus camera: grading of severity of diabetic retinopathy and locating peripheral lesions in diabetic retinopathy.

AIM: To assess the performance of smartphone based wide-field retinal imaging (WFI) versus ultra-wide-field imaging (UWFI) for assessment of sight-threatening diabetic retinopathy (STDR) as well as locating predominantly peripheral lesions (PPL) of DR. METHODS: Individuals with type 2 diabetes with varying grades of DR underwent nonmydriatic UWFI with Daytona Plus camera followed by mydriatic WFI with smartphone-based Vistaro camera at a tertiary care diabetes centre in South India in 2021-22. Grading of DR as well as identification of PPL (DR lesions beyond the posterior pole) in the retinal images of both cameras was performed by senior retina specialists. STDR was defined by the presence of severe non-proliferative DR, proliferative DR or diabetic macular oedema (DME). The sensitivity and specificity of smartphone based WFI for detection of PPL and STDR was assessed. Agreement between the graders for both cameras was compared. RESULTS: Retinal imaging was carried out in 318 eyes of 160 individuals (mean age 54.7 ± 9 years; mean duration of diabetes 16.6 ± 7.9 years). The sensitivity and specificity for detection of STDR by Vistaro camera was 92.7% (95% CI 80.1-98.5) and 96.6% (95% CI 91.5-99.1) respectively and 95.1% (95% CI 83.5-99.4) and 95.7% (95% CI 90.3-98.6) by Daytona Plus respectively. PPL were detected in 89 (27.9%) eyes by WFI by Vistaro camera and in 160 (50.3%) eyes by UWFI. However, this did not translate to any significant difference in the grading of STDR between the two imaging systems. In both devices, PPL were most common in supero-temporal quadrant (34%). The prevalence of PPL increased with increasing severity of DR with both cameras (p < 0.001). The kappa comparison between the 2 graders for varying grades of severity of DR was 0.802 (p < 0.001) for Vistaro and 0.753 (p < 0.001) for Daytona Plus camera. CONCLUSION: Mydriatic smartphone-based widefield imaging has high sensitivity and specificity for detecting STDR and can be used to screen for peripheral retinal lesions beyond the posterior pole in individuals with diabetes.

A novel stop-loss mutation in NKX2-2 gene as a cause of neonatal diabetes mellitus: molecular characterization and structural analysis.

AIM: To identify the genetic etiology of neonatal diabetes in an infant and to elucidate the molecular mechanism of the identified mutation underlying the pathogenesis. METHODS: Genetic analysis was carried out by sequencing of known etiological genes associated with NDM. Molecular characterization was performed by constructing a identified mutation in NKX2-2 gene and  functional aspects was tested using transactivation, protein expression, DNA binding, nuclear localization assays. Structural analysis was performed by modeling the NKX2-2 protein structure. RESULTS: A novel homozygous frameshift mutation  c.772delC, p.Q258SFs*59 in the NKX2-2 gene was identified in a patient with neonatal diabetes. Functional studies revealed that this mutation resulted in an elongated protein sequence, affecting DNA binding activity and transcriptional function. Structural analysis suggested alterations in the protein's tertiary structure, likely contributing to its dysfunction. CONCLUSION: This study presents the first report of a stop-loss mutation in the NKX2-2 gene associated with NDM. Our findings emphasize the importance of functional and structural characterization to understand the biological consequences of such mutations. This comprehensive analysis provides insights into the molecular mechanisms underlying NDM and its clinical phenotype, which may aid in better diagnosis and management of patients with similar variants in the future.

Population-Based Artificial Intelligence Assessment of Relationship Between the Risk Factors for Diabetic Retinopathy in Indian Population.

PURPOSE: Risk factors (RFs), like 'body mass index (BMI),' 'age,' and 'gender' correlate with Diabetic Retinopathy (DR) diagnosis and have been widely studied. This study examines how these three secondary RFs independently affect the predictive capacity of primary RFs. METHODS: The dataset consisted of four population-based studies on the prevalence of DR and associated RFs in India between 2001 and 2010. An Autoencoder was employed to categorize RFs as primary or secondary. This study evaluated six primary RFs coupled independently with each secondary RF on five machine-learning models. RESULTS: The secondary RF 'gender' gave a maximum increase in Area under the curve (AUC) score to predict DR when combined separately with 'insulin treatment,' 'fasting plasma glucose,' 'hypertension history,' and 'glycosylated hemoglobin' with a maximum increase in AUC for the Naive Bayes model from 0.573 to 0.646, for the Support Vector Machines (SVM) model from 0.644 to 0.691, for the SVM model from 0.487 to 0.607, and for the Decision Tree model from 0.8 to 0.848, respectively. The secondary RFs 'age' and 'BMI' gave a maximum increase in AUC score to predict DR when combined separately with 'diabetes mellitus duration' and 'systolic blood pressure,' with a maximum increase in AUC for the SVM model from 0.389 to 0.621, and for the Decision Tree model from 0.617 to 0.713, respectively. CONCLUSION: The risk factor 'gender' was the best secondary RF in predicting DR compared to 'age' and 'BMI,' increasing the predictive power of four primary RFs.