Urban health inequities and healthy longevitytraditional and emerging risk factors across the cities and policy implications

Stefano Cacciatore, Sofia Mao, Mayra Villalba Nuñez, Claudia Massaro, Luigi Spadafora et al. (+9)•View original

OverviewTechnicalshimmer voice

Let’s start with the sheer scale of what’s changing. Cities are now home to more than half of humanity, about four point two billion people, and the share is on track to hit roughly sixty-eight percent by mid-century. That isn’t just a demographic milestone. As Stefano Cacciatore and Sofia Mao argue, it rewires the conditions under which people live, work, and age. It concentrates advantages for some and hazards for many others. And it pushes inequities to show up earlier in life as multimorbidity, which affects about thirty-seven percent of people worldwide, while the average gap between healthspan and lifespan sits near nine point six years. Those aren’t abstract gaps. They’re years lived with two or more chronic conditions, pulled forward by where you happen to live in a city and what that place exposes you to. To make sense of this, three lenses help. The first is the exposome—everything you’re exposed to across the life course, from fine particles in the air and traffic noise to housing quality, night light, and chemical mixtures. The second is prevention anchored in Life’s Simple Seven and its 2022 expansion to Life’s Essential Eight, which takes the classic modifiable metrics—diet, activity, nicotine exposure, body weight, lipids, blood pressure, and glucose—and adds sleep, while widening the aperture to social and ecological context. The third is the social determinants of health: economic stability, neighborhood and built environment, education, social context, and access to care. Put together, you can trace a line from structure to exposure to vulnerability to access—who gets clean air, safe streets, and time to sleep, and who doesn’t. And you can see why older adults, women with caregiving burdens, and residents of informal settlements are so often at the pointy end of risk. What’s the evidence base for all this? A lot of it is longitudinal and pooled. Cohorts like Whitehall II and the UK Biobank have mapped cardiovascular inequalities across social gradients. Sundarakumar and colleagues followed aging populations prospectively; van der Heide in 2024 and Shin in 2016 compared urban and rural strata and different socioeconomic layers. Registry linkages have been used to quantify outcomes in people with dyslipidemia, as Lazo-Porras did in Peru. Pooled meta-analyses synthesize obesity, dyslipidemia, and metabolic syndrome patterns across settings. And when causality is in question, Mendelian randomization has been brought in—Ning’s work used genetic instruments to probe links between air pollution and cognitive outcomes. Across these designs, the stratifications recur: slum residence, migrant status, low income, age, and sex, with a Kathmandu slum study foregrounding how residence itself encodes exposure. If you zoom in on the air, the mechanisms are familiar but no less potent in dense, unequal cities. Fine particulate matter—PM two point five—reaches alveoli and crosses into circulation. It irritates endothelium, feeds chronic inflammation, and primes atherosclerosis. Nitrogen dioxide drives oxidative stress and decreases nitric oxide bioavailability, tightening vessels and degrading lung function. Ozone tilts the autonomic balance and sparks reactive oxygen species. Stack those together and you get thicker plaques, a stickier clotting system, and a higher probability of an acute event—myocardial infarction, stroke, or a bad respiratory exacerbation. In many low- and middle-income cities, that outdoor load is paired with indoor smoke from biomass cooking or incense. The concentrations reached in poorly ventilated rooms are not marginal; they’re hazardous. And they’re concentrated where poverty and proximity to traffic or industry overlap. Water and sanitation layer on top of that. In informal settlements or peri-urban fringes, aging pipes, industrial discharge, and absent treatment mean contamination is common. The clinical face is diarrheal disease and gastrointestinal infections, but the systems outcome is broader—children missing school, adults missing work, and a baseline of inflammation that interacts with cardiometabolic risk. When floods or heatwaves hit, those weaknesses are exposed. Health systems feel it, quickly. Now, take a life-course view. Cities alter diet, sleep, and stress in ways that amplify classic risk factors. One meta-analysis across low- and middle-income countries is striking: each additional gram of salt was associated with a forty-two percent rise in hypertension risk in urban settings, versus just seven percent in rural ones. In India, metabolic syndrome prevalence has been measured at roughly fifty-five percent in urban adults compared with forty-six percent in rural peers. Dyslipidemia profiles are uneven across countries—urban Pakistan showed hypercholesterolemia near thirty-nine percent, hypertriglyceridemia around forty-nine percent, and low high-density lipoprotein in nearly eighty-seven percent of sampled populations. In Peru, lipid profiles vary with urbanization level, and in Korea, residents of less affluent neighborhoods faced a sixty-four percent higher mortality risk tied to dyslipidemia, compared to a forty-eight percent increase in affluent areas. Layer in independent risks like elevated lipoprotein A, which affects an estimated fifteen to twenty-five percent of populations, and you start to see why cities—especially unequal ones—accelerate multimorbidity. Heat is the new accelerant. Urban heat islands store daytime warmth and refuse to let go at night. During heatwaves, hospitalizations and cardiovascular mortality rise; that pattern has been repeated across cities as nighttime minima climb. Sleep suffers, which pulls on glycemic control and blood pressure. The risk isn’t shared evenly. Older adults, outdoor workers, and low-income households in top-floor walk-ups without cooling bear the brunt. Chronic noise adds a steady drip of stress on the same axis. Traffic, construction, industry—it’s there all the time. Systematic reviews now show dose–response relationships between long-term traffic noise and hypertension and cardiovascular endpoints. And the light we bathe our nights in—screens, streetlamps—pushes circadian rhythms off axis, shortening sleep and nudging metabolic pathways toward weight gain and dysglycemia. Food environments nudge, too. Rapid urbanization shifts diets away from traditional staples toward ultra-processed options, especially in neighborhoods saturated with cheap calories and few fresh alternatives—the so-called food swamps. Longitudinal data track the same trend as incomes and urban footprints change. The obesity burden doesn’t map cleanly onto an urban to rural binary: in some contexts, rural children show up to thirty percent higher odds of overweight or obesity than urban peers, while in cities, low-income women and minority groups often carry more of the load due to food insecurity, limited green space, unsafe walking routes, and time poverty. Endocrine-disrupting chemicals are the invisible backdrop—plasticizers, cosmetic additives, and industrial byproducts that act in adolescence and beyond on adiposity, insulin sensitivity, and reproductive axes. Add informal electronic waste sites to the mix and you have heavy metals, too. It’s a web, not a single thread. Mechanistically, these strands converge. High sodium diets and chronic psychosocial stress push up blood pressure—remember that forty-two percent versus seven percent salt gradient between urban and rural. Sleep disruption and circadian misalignment worsen glycemic control. Endocrine-disrupting chemicals and obesogenic environments push adiposity higher. Chronic noise and heat stress raise sympathetic tone and constrict vasculature. Mental health suffers under the same load, showing up as higher anxiety and depressive symptoms where stress, noise, and sleep loss are relentless. And across it all, the constraints of the built environment—unsafe streets, missing sidewalks, and scarce parks—make Life’s Essential Eight’s behaviors harder to sustain day to day. Infectious disease dynamics aren’t exempt from this urban patterning. During the early COVID-19 waves, cities with higher intra-urban connectivity and heavy reliance on public transit saw faster spread. Milan is the canonical European example; a place like Cottbus, with far lower transit dependence, saw far fewer cases in the same window. Education and health literacy mapped onto infection and mortality gradients. And the long tail—post-acute sequelae—appeared more frequently in less advantaged urban populations, where baseline health and access were already constrained. Migration and aging add more texture. The ImmiDem project in Italy documented how language barriers and cultural distance delay dementia diagnosis for older migrants. Tools exist—the Rowland Universal Dementia Assessment Scale was designed for cross-cultural assessment—but they’re underused. This isn’t just about screening instruments. It’s about language-concordant care, stable housing and documentation, and work protections that prevent people from having to choose between seeing a clinician and keeping a job. Social isolation and discrimination pull mental health the wrong way, and they do it in parallel with the environmental load. Internal migrants into informal settlements face their own version of this story: overcrowding, inadequate sanitation, intermittent water, and clinics that are far away or financially out of reach. Across these studies, a consistent analytic challenge shows up: context heterogeneity and data scarcity where urban growth is fastest. Reconciling slum areas in Kathmandu with peri-urban belts in Lima or secondary cities in sub-Saharan Africa isn’t trivial. But the designs have adapted. Pooled analyses smooth some variance. Mendelian randomization helps test whether polluted air really accelerates cognitive decline beyond confounding. And repeated findings across cohorts—Whitehall II’s social gradients, UK Biobank’s imaging markers tied to Life’s Essential Eight scores—anchor the life-course framing in measurable outcomes. The state of the art is moving toward multi-exposure, multi-level models that can keep the exposome and Life’s Essential Eight in the same equation, then stratify by social position. Step back and the causal chain is visible. Structural determinants—land markets, transport systems, labor precarity—shape exposure landscapes. Those exposures cluster: air, heat, noise, light at night, food swamps, chemicals. Vulnerability is patterned by age, sex, migrant status, and wealth. And access—primary care, mental health services, green space—modulates whether an adverse exposure becomes a chronic disease. That’s why multimorbidity shows up earlier in disadvantaged groups, often by a decade or more relative to wealthier counterparts. It’s why the average nine point six year healthspan gap can stretch or shrink depending on the city and your position in it. So what do the researchers say we should do? Cacciatore and Mao argue for changing the decision-making machinery, not just issuing health advice. That means participatory governance with communities at the table and a Health in All Policies approach so transport, housing, energy, and education are accountable for health impacts. Health Impact Assessments can make those impacts explicit before projects break ground. Multi-sectoral partnerships and joint budgets align incentives rather than letting costs and benefits fall on different actors. And cities need an innovation ecosystem—dedicated spaces for experimentation and tactical urbanism, the short, low-cost pilots that let you test a bus-only lane, a cooling corridor, or a healthy food zoning rule before scaling. The levers are concrete and already on the list. Tighten air quality standards and enforcement, and expand clean cooking to cut indoor pollution. Plant and protect urban green to cool heat islands, paired with building standards that mitigate nighttime heat. Control noise through traffic calming and insulation retrofits. Make active mobility and transit the easy choice with safe sidewalks and frequent service. Reform food environments so fresh options aren’t priced out or zoned out in low-income neighborhoods. Upgrade informal settlements with water, sanitation, and hygiene infrastructure, and expand primary and mental healthcare to meet the multimorbidity that is already here. Crucially, measure it all—data-driven monitoring to track equity, not just averages. If there’s a through line, it’s this: the city is a powerful exposure machine, but it’s also a policy machine. The science—cohort by cohort, meta-analysis by meta-analysis—shows how urban form and social structure push risk across the life course. The advances here are less about discovering a new molecule and more about integrating an exposome perspective with Life’s Essential Eight and social determinants, then testing causality and stratifying by equity. That integration is what moves us from describing disparities to compressing that nine point six year gap, in real neighborhoods, for real people.

As Stefano Cacciatore and Sofia Mao argue, it rewires the conditions under which people live, work, and age. It concentrates advantages for some and hazards for many others. And it pushes inequities to show up earlier in life as multimorbidity, which affects about thirty-seven percent of people worldwide, while the average gap between healthspan and lifespan sits near nine point six years.

Those aren’t abstract gaps. They’re years lived with two or more chronic conditions, pulled forward by where you happen to live in a city and what that place exposes you to.

To make sense of this, three lenses help. The first is the exposome—everything you’re exposed to across the life course, from fine particles in the air and traffic noise to housing quality, night light, and chemical mixtures. The second is prevention anchored in Life’s Simple Seven and its 2022 expansion to Life’s Essential Eight, which takes the classic modifiable metrics—diet, activity, nicotine exposure, body weight, lipids, blood pressure, and glucose—and adds sleep, while widening the aperture to social and ecological context.

The third is the social determinants of health: economic stability, neighborhood and built environment, education, social context, and access to care. Put together, you can trace a line from structure to exposure to vulnerability to access—who gets clean air, safe streets, and time to sleep, and who doesn’t. And you can see why older adults, women with caregiving burdens, and residents of informal settlements are so often at the pointy end of risk.

What’s the evidence base for all this? A lot of it is longitudinal and pooled. Cohorts like Whitehall II and the UK Biobank have mapped cardiovascular inequalities across social gradients.

Sundarakumar and colleagues followed aging populations prospectively; van der Heide in 2024 and Shin in 2016 compared urban and rural strata and different socioeconomic layers. Registry linkages have been used to quantify outcomes in people with dyslipidemia, as Lazo-Porras did in Peru. Pooled meta-analyses synthesize obesity, dyslipidemia, and metabolic syndrome patterns across settings.

And when causality is in question, Mendelian randomization has been brought in—Ning’s work used genetic instruments to probe links between air pollution and cognitive outcomes. Across these designs, the stratifications recur: slum residence, migrant status, low income, age, and sex, with a Kathmandu slum study foregrounding how residence itself encodes exposure.

If you zoom in on the air, the mechanisms are familiar but no less potent in dense, unequal cities. Fine particulate matter—PM two point five—reaches alveoli and crosses into circulation. It irritates endothelium, feeds chronic inflammation, and primes atherosclerosis.

Nitrogen dioxide drives oxidative stress and decreases nitric oxide bioavailability, tightening vessels and degrading lung function. Ozone tilts the autonomic balance and sparks reactive oxygen species. Stack those together and you get thicker plaques, a stickier clotting system, and a higher probability of an acute event—myocardial infarction, stroke, or a bad respiratory exacerbation.

In many low- and middle-income cities, that outdoor load is paired with indoor smoke from biomass cooking or incense. The concentrations reached in poorly ventilated rooms are not marginal; they’re hazardous. And they’re concentrated where poverty and proximity to traffic or industry overlap.

Water and sanitation layer on top of that. In informal settlements or peri-urban fringes, aging pipes, industrial discharge, and absent treatment mean contamination is common. The clinical face is diarrheal disease and gastrointestinal infections, but the systems outcome is broader—children missing school, adults missing work, and a baseline of inflammation that interacts with cardiometabolic risk.

When floods or heatwaves hit, those weaknesses are exposed. Health systems feel it, quickly.

Now, take a life-course view. Cities alter diet, sleep, and stress in ways that amplify classic risk factors. One meta-analysis across low- and middle-income countries is striking: each additional gram of salt was associated with a forty-two percent rise in hypertension risk in urban settings, versus just seven percent in rural ones.

In India, metabolic syndrome prevalence has been measured at roughly fifty-five percent in urban adults compared with forty-six percent in rural peers. Dyslipidemia profiles are uneven across countries—urban Pakistan showed hypercholesterolemia near thirty-nine percent, hypertriglyceridemia around forty-nine percent, and low high-density lipoprotein in nearly eighty-seven percent of sampled populations. In Peru, lipid profiles vary with urbanization level, and in Korea, residents of less affluent neighborhoods faced a sixty-four percent higher mortality risk tied to dyslipidemia, compared to a forty-eight percent increase in affluent areas.

Layer in independent risks like elevated lipoprotein A, which affects an estimated fifteen to twenty-five percent of populations, and you start to see why cities—especially unequal ones—accelerate multimorbidity.

Heat is the new accelerant. Urban heat islands store daytime warmth and refuse to let go at night. During heatwaves, hospitalizations and cardiovascular mortality rise; that pattern has been repeated across cities as nighttime minima climb.

Sleep suffers, which pulls on glycemic control and blood pressure. The risk isn’t shared evenly. Older adults, outdoor workers, and low-income households in top-floor walk-ups without cooling bear the brunt.

Chronic noise adds a steady drip of stress on the same axis. Traffic, construction, industry—it’s there all the time. Systematic reviews now show dose–response relationships between long-term traffic noise and hypertension and cardiovascular endpoints.

And the light we bathe our nights in—screens, streetlamps—pushes circadian rhythms off axis, shortening sleep and nudging metabolic pathways toward weight gain and dysglycemia.

Food environments nudge, too. Rapid urbanization shifts diets away from traditional staples toward ultra-processed options, especially in neighborhoods saturated with cheap calories and few fresh alternatives—the so-called food swamps. Longitudinal data track the same trend as incomes and urban footprints change.

The obesity burden doesn’t map cleanly onto an urban to rural binary: in some contexts, rural children show up to thirty percent higher odds of overweight or obesity than urban peers, while in cities, low-income women and minority groups often carry more of the load due to food insecurity, limited green space, unsafe walking routes, and time poverty. Endocrine-disrupting chemicals are the invisible backdrop—plasticizers, cosmetic additives, and industrial byproducts that act in adolescence and beyond on adiposity, insulin sensitivity, and reproductive axes. Add informal electronic waste sites to the mix and you have heavy metals, too. It’s a web, not a single thread.

Mechanistically, these strands converge. High sodium diets and chronic psychosocial stress push up blood pressure—remember that forty-two percent versus seven percent salt gradient between urban and rural. Sleep disruption and circadian misalignment worsen glycemic control.

Endocrine-disrupting chemicals and obesogenic environments push adiposity higher. Chronic noise and heat stress raise sympathetic tone and constrict vasculature. Mental health suffers under the same load, showing up as higher anxiety and depressive symptoms where stress, noise, and sleep loss are relentless.

And across it all, the constraints of the built environment—unsafe streets, missing sidewalks, and scarce parks—make Life’s Essential Eight’s behaviors harder to sustain day to day.

Infectious disease dynamics aren’t exempt from this urban patterning. During the early COVID-19 waves, cities with higher intra-urban connectivity and heavy reliance on public transit saw faster spread. Milan is the canonical European example; a place like Cottbus, with far lower transit dependence, saw far fewer cases in the same window.

Education and health literacy mapped onto infection and mortality gradients. And the long tail—post-acute sequelae—appeared more frequently in less advantaged urban populations, where baseline health and access were already constrained.

Migration and aging add more texture. The ImmiDem project in Italy documented how language barriers and cultural distance delay dementia diagnosis for older migrants. Tools exist—the Rowland Universal Dementia Assessment Scale was designed for cross-cultural assessment—but they’re underused.

This isn’t just about screening instruments. It’s about language-concordant care, stable housing and documentation, and work protections that prevent people from having to choose between seeing a clinician and keeping a job. Social isolation and discrimination pull mental health the wrong way, and they do it in parallel with the environmental load.

Internal migrants into informal settlements face their own version of this story: overcrowding, inadequate sanitation, intermittent water, and clinics that are far away or financially out of reach.

Across these studies, a consistent analytic challenge shows up: context heterogeneity and data scarcity where urban growth is fastest. Reconciling slum areas in Kathmandu with peri-urban belts in Lima or secondary cities in sub-Saharan Africa isn’t trivial. But the designs have adapted.

Pooled analyses smooth some variance. Mendelian randomization helps test whether polluted air really accelerates cognitive decline beyond confounding. And repeated findings across cohorts—Whitehall II’s social gradients, UK Biobank’s imaging markers tied to Life’s Essential Eight scores—anchor the life-course framing in measurable outcomes.

The state of the art is moving toward multi-exposure, multi-level models that can keep the exposome and Life’s Essential Eight in the same equation, then stratify by social position.

Step back and the causal chain is visible. Structural determinants—land markets, transport systems, labor precarity—shape exposure landscapes. Those exposures cluster: air, heat, noise, light at night, food swamps, chemicals.

Vulnerability is patterned by age, sex, migrant status, and wealth. And access—primary care, mental health services, green space—modulates whether an adverse exposure becomes a chronic disease. That’s why multimorbidity shows up earlier in disadvantaged groups, often by a decade or more relative to wealthier counterparts.

It’s why the average nine point six year healthspan gap can stretch or shrink depending on the city and your position in it.

So what do the researchers say we should do? Cacciatore and Mao argue for changing the decision-making machinery, not just issuing health advice. That means participatory governance with communities at the table and a Health in All Policies approach so transport, housing, energy, and education are accountable for health impacts.

Health Impact Assessments can make those impacts explicit before projects break ground. Multi-sectoral partnerships and joint budgets align incentives rather than letting costs and benefits fall on different actors. And cities need an innovation ecosystem—dedicated spaces for experimentation and tactical urbanism, the short, low-cost pilots that let you test a bus-only lane, a cooling corridor, or a healthy food zoning rule before scaling.

The levers are concrete and already on the list. Tighten air quality standards and enforcement, and expand clean cooking to cut indoor pollution. Plant and protect urban green to cool heat islands, paired with building standards that mitigate nighttime heat.

Control noise through traffic calming and insulation retrofits. Make active mobility and transit the easy choice with safe sidewalks and frequent service. Reform food environments so fresh options aren’t priced out or zoned out in low-income neighborhoods.

Upgrade informal settlements with water, sanitation, and hygiene infrastructure, and expand primary and mental healthcare to meet the multimorbidity that is already here. Crucially, measure it all—data-driven monitoring to track equity, not just averages.

If there’s a through line, it’s this: the city is a powerful exposure machine, but it’s also a policy machine. The science—cohort by cohort, meta-analysis by meta-analysis—shows how urban form and social structure push risk across the life course. The advances here are less about discovering a new molecule and more about integrating an exposome perspective with Life’s Essential Eight and social determinants, then testing causality and stratifying by equity.

That integration is what moves us from describing disparities to compressing that nine point six year gap, in real neighborhoods, for real people.