This landmark GBD 2023 study quantified the full toll of chronic respiratory diseases — asthma, COPD, and others — over 33 years, tracking how the COVID-19 pandemic disrupted decades of progress. For India, which carries a disproportionate burden of chronic respiratory disease due to biomass fuel use, air pollution, and tuberculosis co-morbidity, these estimates directly inform national air quality policy and pulmonology service planning. The data are used by WHO, the Indian ICMR, and state health departments to allocate respiratory health resources.

This analysis updates global estimates of lower respiratory infection burden and — critically — quantifies for the first time the contribution of antimicrobial resistance (AMR) to LRI deaths in 204 countries. India is among the countries with highest LRI mortality and rising AMR rates, making this study’s findings directly actionable for Indian hospital infection control and antibiotic stewardship programmes. The data underpin WHO’s global AMR action plan and India’s National Action Plan on AMR.

Cardiovascular disease is the leading cause of death in India, overtaking infectious disease as the primary driver of premature mortality. This comprehensive GBD 2023 update provides the most current national-level CVD burden estimates for India, enabling the Ministry of Health and hospital networks to project cardiologist workforce needs, catheterisation laboratory requirements, and preventive cardiology programme targets. For ophthalmology specifically, CVD shares major risk factors with diabetic retinopathy, retinal vein occlusion, and hypertensive retinopathy — conditions that define much of the medical retina workload at Suraj Eye Institute.

Effective cataract surgical coverage (eCSC) — the proportion of people who needed and received quality cataract surgery — is the key metric for measuring whether national eye care systems are actually delivering benefit. This study, published in Lancet Global Health in 2026, provides the first global multi-country estimates of eCSC. For India, where cataract remains the leading cause of blindness despite decades of surgical programmes, eCSC data identify whether high surgical volume translates into high quality outcomes and population-level coverage — a critical distinction for planning and funding eye care services across the subcontinent.

Age-related macular degeneration (AMD) is an increasingly important cause of irreversible vision impairment as India’s population ages rapidly. This GBD 2021 analysis provides the first country-level projections of AMD vision loss burden to 2050. For India, the ageing demographic dividend is becoming an ageing burden of untreatable vision loss — projections from this study are already being used to advocate for national anti-VEGF treatment access programmes and to plan retinal specialist workforce requirements for the coming decades.

Spectacles for uncorrected refractive error represent the highest-yield, most cost-effective vision intervention available. This VLEG analysis covering 76 countries identifies how far India and neighbouring countries are from the WHO 2030 refractive error coverage target — a key metric in WHO’s World Report on Vision. The findings directly inform India’s National Programme for Control of Blindness and Visual Impairment, guiding targeted spectacle provision programmes for school-age children and working-age adults whose productivity and education are being lost to uncorrected refractive error.

This landmark CIEMS paper established, for the first time, the true burden of glaucoma in rural Central India — the very population Suraj Eye Institute serves. The finding that the vast majority of glaucoma cases were undiagnosed at the time of examination underscores the silent nature of the disease and the critical need for active, community-based screening. The prevalence data directly informed SEI’s Nagpur Million Project and outreach screening programmes, targeting age groups and risk profiles where disease burden is highest. For patients and the public, this paper is the scientific foundation behind why SEI places such strong emphasis on glaucoma screening even in people who feel they see ‘perfectly fine’.

This CIEMS paper provided community-based epidemiological evidence for one of the most important evolving concepts in glaucoma: that it is the pressure difference across the optic nerve head (between the eye and the intracranial space) that drives axonal damage, rather than intraocular pressure in isolation. This explains why some patients develop glaucoma at normal intraocular pressures, and why others tolerate high IOP without damage — their intracranial pressure levels modulate the effective mechanical load on the optic nerve. For clinicians at Suraj Eye Institute, this means that patients with low body weight, low blood pressure, or conditions affecting cerebrospinal fluid pressure (such as intracranial hypertension or hypotension) deserve particular vigilance for glaucomatous progression.

Building on the 2013 CIEMS trans-lamina cribrosa paper, this Transactions of the American Ophthalmological Society study went a step further: it directly pitted two competing theories of glaucoma pathogenesis against each other at a population level. The vascular theory holds that inadequate blood supply to the optic nerve (low ocular perfusion pressure) is the primary insult; the neuro-mechanical theory holds that physical pressure across the lamina cribrosa crushes axons. The CIEMS data showed the neuro-mechanical model is the stronger predictor. This finding has important implications for patient management: lowering IOP remains the cornerstone of treatment, but monitoring patients’ systemic blood pressure, body habitus, and conditions affecting cerebrospinal fluid dynamics provides an additional layer of individualised risk stratification that SEI incorporates into its glaucoma service.

Chronic kidney disease (CKD) and age-related macular degeneration (AMD) share common systemic vascular risk factors — hypertension, diabetes, and dyslipidaemia. This AEEC analysis, using pooled Asian population data including Nangia’s CIEMS cohort, examines whether kidney function independently predicts AMD risk. If confirmed, this relationship suggests that ophthalmologists treating AMD should screen for CKD and that nephrologists should refer patients for retinal evaluation — creating an important clinical link between two specialties that currently operate in silos. The Indian cohort data contributed by Nangia is essential for generalisability to South Asian populations.

The CKD-EPI equation is the international standard for estimating glomerular filtration rate (eGFR) and thereby classifying CKD severity. This AEEC study evaluates whether the standard CKD-EPI equations — developed primarily in Western populations — correctly classify CKD among Asians, or systematically misclassify patients into incorrect CKD stages. Misclassification has direct clinical consequences: incorrect staging affects when to start dialysis, transplant listing decisions, and medication dosing. Nangia’s cohort provides rural Indian reference data to test equation performance in a South Asian population with distinct body composition and muscle mass profiles compared to Western subjects.

Obesity is a well-established risk factor for CKD in Western populations, but Asian populations develop cardiometabolic complications at lower BMI thresholds due to differences in body fat distribution. This participant-level meta-analysis using AEEC data — including the CIEMS Indian cohort — defines the BMI threshold at which CKD risk rises in Asian populations. The findings inform Asian-specific clinical cut-off values for obesity screening and intervention, with direct implications for primary care guidelines across India and the region, where rising obesity rates driven by urbanisation and dietary change are fuelling a parallel epidemic of CKD.

Meta-EyeFM is a large-scale multimodal foundation model for retinal image analysis evaluated systematically by clinical experts in ophthalmology. Nangia’s CIEMS data contributed to the South Asian validation cohort. AI models trained predominantly on Western or East Asian datasets frequently underperform on Indian retinal images due to population-specific features including pigmentation, disc morphology, and disease prevalence patterns. CIEMS data inclusion ensures this foundation model is clinically applicable to the hundreds of millions of patients who will be screened in India’s expanding diabetic eye disease and glaucoma detection programmes.

This study describes the world’s first global federated medical AI foundation model for retinal imaging — RETFound — built using a federated learning approach that preserves data privacy while training on retinal images from multiple countries including India. Nangia is a member of the Global RETFound Consortium. Federated learning is transformative for Indian healthcare because it allows AI model training across hospital networks without centralising sensitive patient data, overcoming data governance barriers that have historically prevented building AI tools on the scale needed for India’s population. This model has direct deployment potential in India’s National Digital Health Mission.

This study from Lancet Digital Health developed deep learning algorithms using retinal photographs for myopia screening and proposed a blockchain infrastructure for secure AI medical research data sharing. Nangia’s Indian cohort data contributed to the multi-ethnic validation. For India — where myopia is rising sharply in school-age children but optometric coverage is sparse in rural areas — a validated retinal-photograph-based AI screening tool deployable by non-specialist health workers could identify children requiring spectacles at a fraction of conventional optometric cost, preventing the educational disadvantage associated with uncorrected myopia.

Intraocular pressure (IOP) is the principal modifiable risk factor for glaucoma, the world’s leading cause of irreversible blindness. Understanding the ocular and systemic determinants of IOP across populations is fundamental to setting normal IOP reference ranges for different ethnicities and identifying individuals at highest risk of pressure-related optic nerve damage. This Two-Continent study — uniquely comparing rural Indian (CIEMS, Nangia) with Chinese (Beijing Eye Study, Prof. Jonas) populations — provides the most geographically diverse cross-continental IOP determinants data available, supporting development of Asia-specific IOP norms for glaucoma diagnosis.

Distinguishing moderate from high myopia in ageing adults has significant clinical implications: high myopia (typically >-6 dioptres or axial length >26mm) carries substantially elevated risks of myopic macular degeneration, retinal detachment, glaucoma, and cataract. This Two-Continent study examines the morphological and demographic differentiators between moderate and high myopia in older adults across Indian and Chinese rural populations — two populations with distinct myopia onset ages and progression trajectories. The findings support targeted surveillance protocols for high myopia patients in India, where the myopia epidemic is emerging rapidly in the younger generation who will age into this high-risk group.

High myopia is a leading cause of glaucomatous optic neuropathy, yet distinguishing myopia-related optic disc changes from true glaucoma is one of the most challenging problems in clinical ophthalmology. Highly myopic eyes have elongated globes that distort the optic disc’s appearance, making standard glaucoma grading criteria unreliable. This Two-Continent study, comparing Indian and Chinese myopic populations, characterises the specific OCT and structural features that differentiate glaucomatous from myopic optic disc changes — providing clinically actionable diagnostic guidance for the growing population of myopic patients at Suraj Eye Institute and across India.

This landmark genome-wide association meta-analysis identified 139 loci for refractive error, with light-induced signalling pathways emerging as central biological drivers — suggesting that outdoor light exposure’s protective effect against myopia operates through specific retinal molecular cascades. Nangia’s CIEMS cohort contributed South Asian genetic and phenotypic data that are essential for identifying variants relevant to Indian populations, who show distinct refractive error patterns and lower myopia prevalence compared to East Asian populations despite similar urbanisation pressures. These genetic loci are the foundation for polygenic risk scores now being developed to identify children at highest risk of severe myopia before it develops.

This gene-environment interaction study found that accounting for education level — a proxy for near-work and indoor time — revealed additional genetic loci for refractive error not detectable in standard GWAS. The Indian CIEMS cohort, with its rural agrarian population that has lower educational attainment and more outdoor time than urban populations, provided a natural comparison group for disentangling genetic from environmental myopia risk. Understanding these interactions is critical for India as urbanisation and increased schooling rapidly change the environmental exposures of the next generation, translating latent genetic myopia susceptibility into manifest high myopia at epidemic scale.

This CREAM Consortium study examined how the effects of myopia-associated genetic variants change with age and are modified by childhood environmental exposures — near work, outdoor time, educational pressure. The Indian CIEMS adult cohort contributes a population with historically low childhood near-work exposure, providing the environmental contrast needed to demonstrate gene-environment interactions that are invisible in homogeneous urban cohorts. The findings suggest that the same genetic variants lead to vastly different refractive outcomes depending on childhood environment — a finding with profound implications for India’s rapidly urbanising children and the timing of myopia control interventions.

India is now estimated to have the largest number of adults with diabetes in the world — over 100 million — making this NCD-RisC analysis, to which Nangia’s rural CIEMS population data contributed, of direct national relevance. The dramatic rise in diabetes prevalence in South Asia documented here translates directly into future burden on ophthalmology services: every percentage point increase in diabetes prevalence forecasts a proportional increase in diabetic retinopathy, diabetic macular oedema, and diabetes-related cataract. The study’s findings on treatment gaps — critically low rates of diabetes control even in diagnosed patients — underscore why early diabetic retinopathy screening and treatment must be integrated into diabetes care pathways.

This analysis documents a historic global epidemiological shift — for the first time, the number of obese individuals now exceeds the number of underweight individuals worldwide. India shows a unique dual burden: rising adult obesity alongside persistent childhood undernutrition. Rising obesity in Nangia’s study population in rural Nagpur district — captured by the CIEMS cohort data included in this analysis — directly forecasts increasing rates of obesity-related eye disease: diabetic retinopathy, hypertensive retinopathy, retinal vein occlusion, and age-related macular degeneration. For Suraj Eye Institute, this demographic transition means that the medical retina and vitreoretinal surgery workload will expand substantially over the next decade.

This study reveals major discordance between diabetes prevalence estimates derived from fasting glucose versus HbA1c criteria — with HbA1c systematically identifying fewer cases in South Asian populations. This is clinically important because it means the true prevalence of diabetes in India may differ substantially depending on which diagnostic criterion is used, with implications for the estimated burden of all diabetes complications including retinopathy. CIEMS-derived population data from Nangia’s cohort inform the South Asian estimates. For diabetic retinopathy screening programmes, the diagnostic criterion used to define the at-risk diabetic population directly determines which patients are referred for retinal evaluation.