Type 2 diabetes (T2D) is a complex disease with a heterogeneous clinical presentation. Recently, five distinct clusters of T2D have been identified in the Emirati population of long-standing T2D with complications. This study aimed to validate these clusters in newly diagnosed T2D patients without any complications and determine whether severe and mild phenotypes are detectable early in the disease course.

Retrospective, cross-sectional, non-interventional study.

Primary healthcare centres in Dubai, UAE.

A total of 451 adults, including both Emiratis and expatriates, diagnosed with T2D in the last 5 years and without T2D-related complications at the time of visit, were enrolled. Patients with complications, incomplete clinical data or higher duration of T2D were excluded from the study.

Identification of distinct T2D clusters using machine learning-based clustering analysis. Five clinical variables: age at diagnosis, body mass index, glycated haemoglobin, fasting serum insulin and fasting blood glucose served as predictors. Overlap between clusters was assessed via the Silhouette Index and Bayesian probability.

Five clusters were identified, replicating prior findings: severe insulin-resistant diabetes (SIRD), severe insulin-deficient diabetes (SIDD), mild age-related diabetes (MARD), mild obesity-related diabetes (MOD) and mild early-onset diabetes (MEOD). As confirmed by a Silhouette Index and Bayesian probability of 1, 55.43% of the patients showed cluster-exclusiveness, while 44.56% of the cohort showed overlap between clusters. The highest overlap was recorded for mild forms of T2D in the order MOD>MARD>MEOD.

The study confirms that both severe and mild T2D phenotypes are present in newly diagnosed, complication-free patients, supporting the applicability of cluster-based classification early in disease. These results highlight the potential for personalised treatment strategies to optimise management and prevent complications. Future studies should investigate longitudinal outcomes and therapeutic response across clusters.

Air pollution is a significant global health concern, with studies from the USA and Europe linking long-term exposure to respiratory issues and poor school attendance in children. While Indian cities experience much higher pollution levels, the impact on lung development in Indian children remains unclear. This study aims to assess the burden of impaired lung function in Indian children and identify key factors contributing to pollution-induced lung injury.

This longitudinal, prospective cohort study is conducted in four cities categorised by particulate matter 2.5 (PM_2.5) levels: ‘very high’ (Delhi), ‘high’ (Mumbai, Bangalore) and ‘moderate’ (Mysore). A total of 4000 participants (1000 from each city) will be included in the study. Participants will complete a structured questionnaire covering sociodemographics, asthma and allergy history (International Study of Asthma and Allergies in Childhood core questionnaire), dietary intake (24-hour recall and Food Frequency Questionnaire), Physical Activity-C Questionnaire and air pollution exposure. Spirometry and Forced Oscillation Technique will be used to assess lung function. Blood samples will be collected for identification of biomarkers to predict lung impairment. After quality checks, data will be compiled, summarising pulmonary function parameters alongside covariates and confounders. Analysis of Variance (ANOVA) will assess between-city and within-city differences in lung function.

We anticipate a higher prevalence of reduced lung function in children residing in cities with very high and high PM_2.5 levels compared with the moderately polluted city. Findings from this study could establish normal age-appropriate lung function reference values for Indian urban children, aiding in clinical diagnosis.If a reliable biomarker for identifying children at risk of lung impairment is available, it could serve as an early predictor of poor lung health in asymptomatic children.

The approval from individual site institutional review board (IRB) is obtained prior to initiation of the study from institutional ethics committee, St. John’s Medical College and Hospital, Bangalore; institutional ethics committee, JSS Medical College, Mysore; institute ethics committee, Indian Institute of Technology Bombay and institute ethics committee, All India Institute of Medical Sciences. Findings from this study will be disseminated through conference presentations, peer-reviewed publications and establishment of normal age-appropriate lung function reference values for children living in urban India.