Published Jan 14, 2026 | 7:00 AM ⚊ Updated Jan 14, 2026 | 7:00 AM
if unhealthy outlets are easily accessible within a 400-metre radius of the residences, the residents have a two-times higher risk of diabesity. (Wikimedia Commons)
Synopsis: The study reported that physical activity was “inversely associated with diabesity,” meaning active individuals had lower odds than sedentary individuals. This mattered because it was the one lever that still worked even when environments were imperfect. But the authors argued that it cannot be treated as an individual burden alone.
Step outdoors in Chennai, and a spread of yummy snacks and colourful drinks grabs instant attention. They even make the most health-conscious consider a ‘cheat day’.
A new study has suggested that the danger zone leading to an increase in body weight and diabetes could be the 400 metres around your doorstep, where there are about two fast-food and convenience outlets for every grocery store or produce vendor.
Researchers from Madras Diabetes Research Foundation, Chennai, in collaboration with doctors from the UK, surveyed 1,138 adults in two Chennai municipal corporation wards. They found that a mix of food access and limited places for physical activities is not a minor lifestyle issue. It is shaping who develops the “twin epidemic” of diabetes plus obesity, a condition public health experts increasingly call diabesity.
“This study captures what we see in clinics every day,” Dr RM Anjana, President of Madras Diabetes Research Foundation, who co-authored the study, told South First, referring to the Chennai findings.
“People think they are failing. But many neighbourhoods are designed in such a way that makes unhealthy food the most visible, and most available, and physical activity the hardest routine to sustain,” he stated.
The cross-sectional study was conducted in Mandaveli and Mylapore between December 2021 and February 2022. It was part of a wider South Asia Biobank project linked to the National Institute of Health Research’s Global Health Research Unit.
Investigators went door-to-door, collected data based on a questionnaire, measured height, weight and waist circumference, and drew fasting blood samples to check fasting plasma glucose and HbA1c.
The study defined obesity using both belly-fat and weight-based measures. Abdominal obesity was set at a waist circumference ≥90 cm for men and ≥80 cm for women, while general obesity was defined as a BMI of≥27.5 kg/m².
Diabetes is defined as a fasting glucose level of ≥126 mg/dL, or HbA1c ≥6.5%, besides diabetes medication use. Diabesity meant having both.
The results showed the spread of metabolic risk in the sample. The study reported an overall prevalence of diabetes at 43 percent, obesity at 69.7 percent, and diabesity at 32.5 percent.
To understand the everyday food choices available in residential neighbourhoods, researchers used GPS mapping and a measure called the Retail Food Environment Index (RFEI).
The study described RFEI as a way to compare the number of unhealthy outlets, such as fast-food and convenience stores, against healthier options, such as grocery stores and produce vendors.
The mapping was done within a 400-metre radius of each participant’s home. The radius mattered because it represented the small, practical zone where people actually bought snacks, tea, quick meals and “something to eat” without planning.
In the Chennai sample, the mean RFEI within that 400-metre ring was 1.9, which the researchers interpreted as roughly two fast-food and convenience outlets for every grocery store or produce vendor. Among people with diabesity, the study found higher exposure to convenience stores and fast-food outlets than among those without diabesity, and a higher average RFEI score.
A higher RFEI, the study said, “indicates a greater prevalence of unhealthy food options relative to healthier ones.” It is not that residents never noticed healthier food. But by default, repeated cues in the neighbourhood pointed the other way.
“A PhD student mapped food outlets around people’s homes, divided them into healthy and unhealthy points and created a food retailer index. What found that if unhealthy outlets are easily accessible within a 400-metre radius of the residences, the residents have a two-times higher risk of diabesity, because they have more opportunity to buy unhealthy food,” Dr Anjana told South First.
The finding gains importance since it gives policymakers a clear understanding. City planning and local bodies can use zoning and licensing to prevent unhealthy outlet clustering in dense residential pockets, especially near schools; incentivise and protect fruit-and-vegetable vending and neighbourhood markets so healthy options are actually present at street level.
Food was only half the picture. The study also mapped “spaces for physical activity,” including public parks, recreation centres, gyms, sports clubs, playgrounds and even health hubs designed for the elderly.
Using network distance from households, researchers found a consistent pattern: people with diabesity were more likely to live farther from these spaces. The study reported that 56.2 percent of those with diabesity lived more than 1.1 km from places for physical activity. The authors noted that living away from activity spaces was significantly associated with higher diabesity risk.
“A safe, usable space to walk is not a small thing,” she said. “If the nearest park is far, if footpaths are broken, if women don’t feel safe walking early or late, ‘just exercise’ becomes unrealistic for many families,” Dr Anjana said.
Instead of looking only at one factor at a time, the researchers used a statistical approach called reduced rank regression to identify combined patterns of lifestyle and environment that travelled together in real life.
Two patterns emerged. The most concerning one was labelled “Passive Lifestyle with an Unfavourable Environment.” It was characterised by low physical activity, lower fruit and vegetable intake, greater distance from activity spaces, and higher exposure to unhealthy food environments.
In other words, it was the exact scenario many urban residents described without using research lingo: you sit more because movement is inconvenient, you eat what is easily available, and you end up stuck in a loop.
When participants were grouped by how strongly they fit these patterns, those in the highest group for this “passive lifestyle” pattern showed worse metabolic markers, including higher BMI, waist circumference, fasting glucose and HbA1c, along with lower activity and higher exposure to unhealthy food outlets.
The study also ran multivariable models to find factors independently linked with diabesity even after adjusting for others.
It found that age remained a risk factor, as did being female, having a higher RFEI score, and living farther from spaces for physical activity. Physical activity, however, showed a protective association.
The study reported that physical activity was “inversely associated with diabesity,” meaning active individuals had lower odds than sedentary individuals. This mattered because it was the one lever that still worked even when environments were imperfect. But the authors argued that it cannot be treated as an individual burden alone.
“As doctors, we can counsel patients, but policy has to change the background conditions,” Dr Anjana said. “If we keep building food streets that promote constant snacking and neighbourhoods without easy movement, we will keep seeing younger diabetes, higher waistlines, and earlier complications.”
The authors suggest that tackling diabesity requires “urban planning and public health strategies to promote healthier food environments and increased physical activity opportunities.”
Their broader argument was that lifestyle advice was necessary but insufficient when daily surroundings repeatedly pushed people towards sedentary routines and calorie-dense food.
The study termed it a “built environment” problem as much as a medical one, calling for integrated strategies working at the individual, community and policy levels. In simple terms, neighbourhoods with easy access to fruits and vegetables, and with options for safe and convenient physical activities.
The researchers acknowledged key limitations. The study was cross-sectional, so it cannot prove cause and effect. Some behavioural data was self-reported, which could introduce bias. It focused on two wards, which may limit generalisability.
The authors also noted that they did not assess online food delivery or use detailed dietary assessment tools, a major gap in cities where food apps can make fast food closer than the nearest neighbourhood shop.
(Edited by Majnu Babu).
