In this in‑depth interview, Dr. R.M. Anjana- Managing Director at Dr. Mohan’s Diabetes Specialities Centre and President of the Madras Diabetes Research Foundation (MDRF), draws on insights from the ICMR‑INDIAB study and MDRF’s long-running research to unpack how India’s diabetes landscape is rapidly shifting—from early-onset disease and “metabolic obesity” at lower BMI to stark rural–urban and regional gaps in risk.
To begin with, how would you describe the current “state of the nation” in terms of diabetes and related metabolic NCDs in India, based on the latest ICMR‑INDIAB data? Which trends worry you the most?
India is facing a major public health emergency driven by diabetes and related metabolic NCDs. The ICMR-INDIAB study shows that 11.4% of Indian adults—over 101 million people—have diabetes, while 15.3% (136 million) have prediabetes. This means nearly one in four adults already has dysglycaemia. Alongside this, 35.5% have hypertension, 28.6% generalised obesity, 39.5% abdominal obesity, and over 80% have some form of dyslipidaemia.
What is most worrying is not just prevalence, but early onset, rapid progression and clustering of multiple risk factors in the same individuals. Diabetes rarely occurs alone; it is increasingly accompanied by hypertension, abnormal lipids and obesity, sharply increasing cardiovascular and kidney disease risk. Another major concern is the narrowing rural–urban gap, indicating that the epidemic is no longer confined to cities.
India is therefore dealing with a multimorbidity crisis, not a single-disease problem. Without urgent action focused on early detection and prevention, this burden will overwhelm health systems and reduce productive years of life.
ICMR‑INDIAB has highlighted striking regional and rural–urban differences in the prevalence of diabetes, prediabetes, hypertension, dyslipidaemia and obesity. Which of these geographic patterns stand out to you, and how should they shape our prevention and screening strategies?
ICMR-INDIAB highlights striking regional and rural–urban variations in metabolic NCDs across India. Southern and western states such as Kerala, Tamil Nadu, Goa, Puducherry and Delhi show particularly high prevalence of diabetes, obesity and dyslipidaemia, reflecting longer exposure to urbanisation and lifestyle transitions. In contrast, many northern and eastern states show lower diabetes prevalence but very high prediabetes and hypertension, signalling that they are earlier on the same trajectory.
Urban areas continue to have a higher burden of diagnosed diabetes, obesity and lipid abnormalities. However, what stands out is the rapid rise of prediabetes, hypertension and abdominal obesity in rural populations. This suggests that rural India is entering a critical window where prevention can still be effective if action is taken early.
These patterns demand region-specific strategies. Urban areas require better management of established disease and complications, while rural urban regions need aggressive screening, risk stratification and lifestyle-based prevention. A uniform national approach will miss these nuances and reduce impact.
Could you explain how the concept of “metabolic obesity” at relatively low BMI has emerged from Indian data, and what this phenotype means for how we define and detect “high‑risk” individuals in routine practice?
Indian research has fundamentally changed how we understand obesity and diabetes risk. Data from ICMR-INDIAB and MDRF show that many Indians develop diabetes and cardiometabolic abnormalities at relatively low BMI levels, a phenomenon now described as “metabolic obesity.” This phenotype is characterised by higher body fat percentage, excess abdominal fat, lower muscle mass and metabolic dysfunction, even when BMI appears normal. As a result, many individuals who would be classified as “non-obese” using Western BMI cut-offs are actually at high metabolic risk. This explains why diabetes and cardiovascular disease occur at younger ages and lower body weights in Indians. The implication for routine practice is clear: BMI alone is insufficient. Risk assessment must include waist circumference, glycaemic measures, lipid profile, blood pressure and family history. Screening strategies must move beyond appearance-based judgments. Recognising metabolic obesity allows clinicians to identify high-risk individuals earlier and intervene before irreversible complications develop.
From ICMR‑INDIAB and MDRF studies, what have we learnt about physical activity and inactivity patterns among Indians—across age groups, genders and regions—and how strongly do these patterns track with diabetes and cardiometabolic risk?
ICMR-INDIAB provides the first national evidence on physical activity and inactivity patterns in India. The findings are stark: fewer than 10% of Indians engage in recreational physical activity. Women, adolescents and urban residents are consistently the least active groups. With urbanisation, occupational and transport-related activity has declined sharply, while sedentary time has increased.
MDRF’s research shows a strong association between inactivity and obesity, diabetes, hypertension and dyslipidaemia. Importantly, physical activity patterns are heavily shaped by the built environment. Poor walkability, unsafe roads, lack of parks and open spaces, and safety concerns—especially for women—significantly limit daily movement. Adolescents are further affected by high screen time and limited play spaces.
These findings make it clear that inactivity is not merely a matter of individual choice but a structural issue. Addressing diabetes risk, therefor,e requires changes beyond counselling, including safer neighbourhoods, accessible public spaces and environments that make physical activity a natural part of daily life.
The Indian Diabetes Risk Score (IDRS) is often cited as a practical, low‑cost tool. In your experience, how well does IDRS perform in real‑world primary care and community settings, and what are the best ways to integrate it into large‑scale screening and risk stratification?
The Indian Diabetes Risk Score (IDRS) has emerged as one of the most practical tools for large-scale diabetes screening in India. Validated nationally through the ICMR-INDIAB study, IDRS uses simple parameters—age, waist circumference, physical activity and family history—to identify individuals at high risk for diabetes. In real-world primary care and community settings, IDRS performs well in detecting undiagnosed diabetes and prediabetes, especially where laboratory testing is limited. Its greatest strength lies in its simplicity, low cost and scalability, making it ideal for use by frontline health workers, workplace health programmes and national NCD initiatives.
IDRS works best when integrated into a stepwise screening strategy—first identifying high-risk individuals, followed by targeted blood testing and lifestyle intervention. Digital integration of IDRS into apps and electronic medical records can further enhance reach and efficiency. Used thoughtfully, IDRS can significantly improve early detection and reduce the burden of late diagnosis.
Indian dietary patterns and urban lifestyles are rapidly changing. Which specific dietary shifts and urban behaviours do you see as the most important drivers of metabolic obesity and diabetes, and where do you think course correction is most urgent?
India’s dietary landscape has changed rapidly over the past two decades. Traditional diets rich in whole grains, pulses and vegetables are increasingly replaced by refined carbohydrates, ultra-processed foods, unhealthy fats and sugar-sweetened beverages. At the same time, dietary diversity has declined, particularly in urban and low-income settings.
These dietary shifts, combined with sedentary lifestyles, prolonged sitting, high screen time and disrupted sleep, are major drivers of metabolic obesity and diabetes. Indian data show that excess carbohydrate intake, especially refined grains, plays a key role in insulin resistance, even without excess calorie intake.
ICMR-INDIAB provides strong evidence supporting isocaloric substitution of refined carbohydrates with plant protein, dairy, lean meat and fish to prevent diabetes and prediabetes. Course correction is most urgent in urban food environments, school meals, workplace canteens and public nutrition messaging. Without addressing these upstream drivers, individual-level advice alone will have limited impact.
There is growing talk of treating physical activity as a “vital sign” in diabetes care. How can clinicians, especially in busy OPDs, realistically assess and prescribe physical activity, and what kind of environment or system‑level changes would support this?
Treating physical activity as a “vital sign” recognises its importance on par with blood pressure or heart rate. In busy OPDs, clinicians can realistically assess activity using brief standardised questions on daily movement, sitting time and barriers to exercise. This need not take more than a minute.
Instead of generic advice, clinicians should provide simple, personalised activity prescriptions, such as walking goals, reducing sitting time or culturally relevant activities. Even modest increases in activity can significantly improve glycaemic control and cardiometabolic risk.
However, individual counselling must be supported by system-level changes. These include integrating activity assessment into electronic medical records, referral pathways to structured programmes, and community-based options. MDRF’s research shows that without supportive environments—safe walking paths, parks, lighting and women-friendly spaces—patients struggle to sustain activity.
Drawing on MDRF’s work, could you describe some of your key preventive and digital health initiatives—such as mobile or worksite interventions, EMR‑linked cohorts and biobanks—and what your evaluations are showing about behaviour change and cardiometabolic outcomes?
MDRF has developed a strong ecosystem combining population research, preventive interventions, digital health tools, EMR-linked cohorts and biobanks. Mobile-based and worksite interventions have demonstrated meaningful improvements in weight, glycaemia, blood pressure and lipid profiles.
More recent digital initiatives integrate AI-enabled support, lifestyle tracking and risk stratification, allowing personalised and continuous care. Ongoing studies using mobile health platforms are evaluating long-term behaviour change, adherence and cardiometabolic outcomes across urban and rural populations.
The strength of MDRF’s approach lies in linking real-world data with intervention design, enabling continuous refinement of strategies. Evidence consistently shows that culturally adapted, low-cost digital tools—especially when combined with human support—can drive sustainable lifestyle change at scale in India.
If we think about cities, schools and workplaces as critical settings for diabetes prevention, what concrete, evidence‑based changes would you like to see in built environments, policies and programmes over the next 5–10 years?
Evidence clearly shows that diabetes prevention must move beyond clinics into everyday environments. Cities should prioritise walkable streets, safe cycling infrastructure, traffic calming, lighting and accessible parks, particularly to support women and older adults. These changes directly influence daily physical activity levels.
Schools are critical for early prevention. Daily physical education, movement breaks, safe play areas and reduced screen exposure can shape lifelong habits. Workplaces, where adults spend most of their day, must address prolonged sitting through active breaks, stair use, flexible schedules and wellness programmes.
These interventions are not optional lifestyle add-ons; they are public health investments. Over the next 5–10 years, integrating health considerations into urban planning, education policy and workplace norms will be essential to slowing India’s diabetes epidemic.
Finally, looking ahead, which populations in India should be prioritised first, and what should be the top three changes in how primary care, national NCD programmes and policymakers use risk scores, digital tools and lifestyle evidence to truly “bend the diabetes curve” in the coming decade?
Priority populations include those with obesity and pre-diabetes, and rural and underserved communities. Prevention must begin early, well before diabetes is diagnosed.
The top changes needed are:
- Early risk detection using tools like IDRS, embedded into primary care and national NCD programmes
- Massive education and awareness programmes about prevention, especially to children and youth.
- Intersectoral government cooperation for the availability of healthy foods at affordable prices and safe places to exercise.
- Making lifestyle care central to clinical practice, treating physical activity and diet as core health metrics
- Scaling digital and data-driven prevention, using mobile tools, EMRs and real-world evidence to personalise care
By integrating prevention, technology, supportive environments and strong primary care, India can realistically bend its diabetes curve over the next decade.
