South Asia is urbanising at a pace that would have been unimaginable half a century ago. Between 1972 and 2019, millions of people in Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka moved from villages to towns and cities in search of work, services, and opportunity. At the same time, life expectancy in these countries rose dramatically, and infant mortality declined.
But has urbanisation itself helped people live longer, or has it made health worse by creating slums, pollution, and congestion? The answer is not obvious. Global research shows that cities can be both engines of better health and epicentres of disease. South Asia's experience is no different.
The research paper on which this article is based addresses this question systematically for the eight SAARC countries over a long span of 48 years, from 1972 to 2019. Using a panel-data regression framework, it examines how life expectancy at birth - a widely accepted summary indicator of population health - responds to three key drivers: (i) Urbanisation (the share of the population living in urban areas); (ii) GDP per capita (average income); and
(iii) Infant mortality rate (infant deaths per 1,000 live births).
The findings are clear. Urbanisation and higher income per person are associated with higher life expectancy, while higher infant mortality sharply reduces it. For Bangladesh, this means that the question is not whether to urbanise, but how - and whether policy can shape urban growth in ways that reinforce the gains from rising income and falling infant deaths rather than undermining them.
URBANISATION AND HEALTH-WHAT PREVIOUS STUDIES SHOW: Global research provides mixed but broadly consistent insights. Many studies find that urbanisation tends to improve health through better hospitals, sanitation, drinking water, schooling, and diversified diets. Others warn that when urban growth is unplanned or unequal, slums, pollution, and environmental degradation can offset these benefits.
Within South Asia, existing research confirms that income, sanitation, education, and especially infant mortality are decisive determinants of life expectancy. Some studies find that urbanisation has weak or insignificant effects when pollution or overcrowding is high; others report modest positive effects linked to access to services. The regional evidence remains context-dependent: urbanisation raises longevity when supported by governance and infrastructure but can have ambiguous effects when growth is chaotic.
The SAARC study builds on this literature by covering all eight countries over nearly five decades and by examining urbanisation, income, and infant mortality together in a unified framework.
DATA DESCRIPTION AND SOURCES: The study relies on a balanced panel of 384 observations: 8 countries observed over 48 years, from 1972 to 2019. Life expectancy at birth (LE) is the dependent variable, used as the summary measure of health.
Three explanatory variables are included: (i) Urbanisation (URB) - the percentage of the total population living in urban areas; (ii) GDP per capita (GDPPC) - gross domestic product divided by total population, measured in US dollars; and (iii)Infant mortality rate (IMR) - the number of infants per 1,000 live births who die before reaching their first birthday.
Most data are taken from the World Development Indicators database. For GDP per capita in Afghanistan, Bhutan, and Maldives, the authors use Country Economy data to fill gaps and ensure continuity.
Descriptive statistics over the full sample help to situate SAARC in the global context. The average life expectancy across all country-year observations is about 61 years. Average urbanisation is roughly 23 per cent, confirming that SAARC remains less urbanised than many other regions. Average GDP per capita is just over USD 1,050. The average infant mortality rate is about 76 deaths per 1,000 live births - high by current global standards.
Life expectancy is positively correlated with urbanisation and GDP per capita, and strongly negatively correlated with infant mortality. There is no perfect colinearity among the explanatory variables, allowing the model to separately identify the contribution of each.
EMPIRICAL METHODOLOGY IN SIMPLE TERMS: Because the data follow multiple countries over time, the study uses panel-data regression rather than simple cross-section or time-series models. This approach isolates how each variable affects life expectancy while controlling for unobserved country differences - such as culture, health systems, or political history - and time-specific global trends.
Statistical tests reject a pooled model and support the use of a two-way random-effects specification. The Hausman test indicates that random effects are appropriate. The model is estimated using EGLS, allowing the regression to incorporate random country-specific and time-specific components alongside idiosyncratic error.
In simpler terms, the methodology filters out noise and isolates the direct contribution of urbanisation, income, and infant mortality to life expectancy across SAARC.
EMPIRICAL RESULTS: The estimated coefficients from the two-way random-effects model are intuitive and statistically highly significant.
Urbanisation has a positive impact. The coefficient on URB is approximately 0.151. A 1-percentage-point rise in urban population raises life expectancy by about 0.15 years - a little under two months. A rise from 20 per cent to 30 per cent urbanisation corresponds to an associated gain of about 1.5 years in life expectancy, holding income and infant mortality constant.
GDP per capita also exerts a positive influence. An increase of US$ 1,000 in GDP per capita increases life expectancy by about 0.696 years - roughly eight months. Higher income gives governments more fiscal space to invest in health, education, and infrastructure, and allows households to afford better food, housing, sanitation, and medical care.
Infant mortality has a strong negative effect. A reduction of one infant death per 1,000 live births is associated with an increase of about 0.165 years - roughly two months - in life expectancy. Because infant mortality sharply lowers the average age at death, even small improvements in infant survival produce substantial gains in average lifespan.
The adjusted R-squared is about 0.986, indicating that the three variables together explain nearly 99 per cent of the variation in life expectancy once country and time effects are considered.
Bangladesh and Pakistan have positive random effects, suggesting that after controlling for urbanisation, income, and infant mortality, these countries achieve slightly higher life expectancy than predicted. Afghanistan and Bhutan have negative effects.
In short, the evidence supports three clear propositions: More urbanisation, on average, is associated with longer lives. Higher income per person is associated with longer lives. Higher infant mortality sharply reduces life expectancy.
READING THE EVIDENCE THROUGH A BANGLADESH LENS: Although the study covers eight countries together, its findings carry powerful lessons for Bangladesh.
Urbanisation in Bangladesh is not a marginal trend; it is one of the central forces reshaping the economy and society. Industrialisation, especially in ready-made garments, has pulled workers from rural areas into urban and peri-urban zones. Along with this, there has been a proliferation of informal settlements and slums, often lacking basic services such as clean water, sanitation, and secure housing.
The model's positive coefficient for urbanisation should not be interpreted as an endorsement of any kind of urban growth. Rather, it tells us that, on average across SAARC, the health-promoting effects of urbanisation - proximity to hospitals, more diversified diets, better schools, and employment opportunities - outweigh the negative effects associated with congestion, pollution, and crowding. For Bangladesh, this means the task is to amplify the positive mechanisms and aggressively tackle the negative ones.
Second, the strong role of GDP per capita in explaining life expectancy reinforces the link between economic development and health. Bangladesh's growth over recent decades has lifted millions out of extreme poverty and expanded access to electricity, transport, and communication. The study suggests that such growth is not just a story of higher consumption and investment; it directly translates into longer lives. In policy terms, this underlines the importance of sustaining growth while making it more inclusive.
Third, the dominant impact of infant mortality on life expectancy provides a sharp policy focus. Bangladesh has made major strides in reducing infant and child mortality through vaccination campaigns, expanded immunisation, community health workers, and maternal health programmes. Yet the model reminds us that further reductions in infant mortality yield disproportionately large gains in national life expectancy.
The country-specific random effect for Bangladesh is positive, indicating that Bangladesh still achieves higher life expectancy than the SAARC average after accounting for the key variables. This reflects decades of investment in primary healthcare, community-based services, and low-cost public health interventions. However, the same evidence also carries a warning. If urbanisation proceeds without planning - with expanding slums, unsafe water, poor sanitation, and rising air pollution - the positive contribution of urbanisation to life expectancy may diminish or even reverse.
POLICY DIRECTIONS FOR HEALTHIER URBANISATION: The policy implications of the study are closely aligned with Bangladesh's commitments under the Sustainable Development Goals, especially SDG 3 (good health and well-being) and SDG 11 (sustainable cities and communities). Since urbanisation and GDP per capita both contribute positively to life expectancy, the answer is not to slow down urban growth or industrialisation, but to steer them.
This requires planned urbanisation: better land-use planning, upgraded slum infrastructure, reliable water and sanitation services, and enforcement of building and environmental
standards.
Urban planning must integrate transport, housing, and environmental management. Without this integration, the unpriced health costs of pollution and accidents can quietly erode some of the gains measured in the study.
The strong role of infant mortality demands continued and targeted investment in maternal and child health. Antenatal care, skilled birth attendance, neonatal care, nutrition programmes, and postnatal follow-up must remain central pillars. As urban slums grow, these services must be brought to the doorstep of the urban poor, not just to formal clinics.
Equally, the income-health relationship highlighted in the regression underscores that macroeconomic policy is not separate from health policy. Strategies that sustain per capita income growth - export diversification, productivity gains, financial development, and human capital formation - indirectly raise life expectancy.
CLIMATE, DEMOGRAPHY, AND EMERGING URBAN HEALTH PRESSURES: A forward-looking interpretation of the findings also requires attention to Bangladesh's demographic transition. As fertility declines and the population ages, the health impact of urbanisation will evolve. Older populations are more vulnerable to non-communicable diseases-cardiovascular illness, diabetes, stroke, chronic respiratory problems-many of which are intensified by urban pollution, sedentary lifestyles, and the nutritional shifts associated with rapid modernisation. Without preventive services, early detection, and redesigned urban environments that promote physical activity and reduce exposure to pollutants, the health gains associated with urbanisation may flatten or reverse.
Climate change adds another layer of vulnerability. Bangladesh's cities are experiencing rising temperatures, waterlogging, heat-island effects, and climate-induced migration from coastal regions. These pressures will place enormous strain on urban health systems, increasing vector-borne diseases, heat-related morbidity, and demand for emergency care. The SAARC findings on urbanization and income suggest that economic growth can offset some of these risks, but only if cities become more climate-resilient-through green spaces, improved drainage, heat-reducing infrastructure, and decentralised service delivery.
CONCLUSION: Based solely on long-run evidence from eight SAARC countries, the study delivers a clear and consistent message. Urbanisation, on balance, has been a friend rather than a foe of health in the region; higher income per capita has helped people live longer; and high infant mortality remains the most powerful drag on life expectancy.
For Bangladesh, the findings carry both encouragement and responsibility. The country appears to have used its limited resources relatively well, achieving higher life expectancy than its level of urbanisation, income, and infant mortality alone would predict. But the same forces that have delivered these gains can quickly turn against public health if left unmanaged.
Urbanisation will continue. The real policy question is whether Bangladesh can convert that urban growth into healthier, safer, and more equitable cities. If those priorities are kept at the centre of economic and social policy, the statistical relationships revealed in SAARC's past can become a roadmap for a healthier future - not just for the region, but for Bangladesh in particular.
Dewan Tahmid is a research and data analysis professional.
dtahmid71@gmail.com
