Understanding Demographic Processes: Fertility, Mortality, and Migration

Every country’s population is really just a running total shaped by three simple events: someone is born, someone dies, or someone moves. Demographers call these fertility, mortality, and migration, and together they explain why India’s cities are bursting at the seams while some villages are emptying out, why the average Indian today can expect to live decades longer than their grandparents, and why family sizes have shrunk so sharply in a single lifetime. Understanding how these three processes work, separately and together, is the starting point for making sense of population change anywhere in the world.

The three pillars of population change 🔗

Fertility, mortality, and migration are often described as the basic demographic processes because every change in a population’s size, density, or age-and-sex structure can be traced back to one of them. A population grows when births and in-migration outpace deaths and out-migration, and shrinks when the reverse happens. Demographers track how these three processes shift across regions and time periods, and study their ripple effects on everything from labour markets to healthcare planning to school enrolment. None of the three operates in isolation. A sharp drop in child mortality tends to be followed, a generation later, by a drop in fertility, and both can trigger new waves of migration as families reorganise around smaller households and different economic opportunities.

Fertility: the biology and culture of birth 🔗

Fertility refers to the actual number of children born, as distinct from fecundity, which is the biological capacity to reproduce. Fertility figures are generally lower than fecundity figures, because social and economic conditions, not just biology, decide how many children are actually born. This is why fertility is studied as much by sociologists and anthropologists as by biologists: contraceptive access, marriage age, religious norms, women’s education, and household income all shape the final number.

Micro and macro views of fertility 🔗

Demographers approach fertility at two levels. Micro-level analysis looks at an individual woman’s reproductive history: how many children she has by the end of her childbearing years, and how those births are spaced out. Macro-level analysis looks at the population as a whole, calculating the rate at which births occur across a given period, usually expressed as the Total Fertility Rate, or the average number of children a woman is expected to have over her lifetime. Both levels matter. Micro data explains individual decision-making around family planning, while macro data tells policymakers whether the overall population is growing, shrinking, or stabilising.

What drives fertility up or down 🔗

Scholars studying fertility have long pointed to a set of intermediate variables, factors like the frequency of intercourse, contraceptive use, marital disruption, induced abortion, and infertility, that stand between social conditions and the final birth outcome. These variables explain why two societies with similar cultural values can still end up with very different birth rates. India offers a vivid real-world example of how fast fertility can change once these variables shift. In the 1950s and 1960s, the country’s Total Fertility Rate stood close to 5.9 children per woman. That number has fallen consistently ever since, and recent estimates put India’s national fertility rate at around 1.9 children per woman, below the replacement level of 2.1 needed for a population to simply replace itself over generations. Expanding female literacy, greater workforce participation among women, and wider access to family planning services are usually cited as the main forces behind this shift.

Even within one country, fertility can vary enormously by region. Southern and western Indian states now report fertility levels comparable to many wealthy nations, while some northern states remain well above the national average, showing how strongly local economic conditions, healthcare access, and social norms around marriage and childbearing shape the numbers on the ground.

Mortality: reading how and when people die 🔗

Mortality refers to how frequently death occurs in a population. Demographers separate two related but distinct ideas here: life span, the maximum number of years a human being could theoretically live, and life expectancy, the average number of years a person born into a particular population can expect to live given current conditions. Life expectancy is the more useful measure for understanding a society’s health and development, because it responds directly to nutrition, sanitation, medical care, and living conditions.

How life expectancy has transformed 🔗

Historically, life expectancy stayed remarkably low for most of human history. In eighteenth-century Europe and the United States, average life expectancy hovered around 30 to 40 years, kept down by famines, epidemics, floods, war, and poor sanitation. India’s own trajectory illustrates just how much this can change: average life expectancy in India climbed from around 37 years in the early 1950s to over 70 years by the early 2020s, driven largely by falling infant and child mortality alongside broader improvements in healthcare access and nutrition. This kind of jump within a few generations is one of the clearest signs of demographic transition in action.

Infant mortality, birth spacing, and undercounted deaths 🔗

Infant mortality, the number of deaths of children under one year of age per 1,000 live births, is treated as one of the most sensitive indicators of a population’s overall wellbeing, because young children are the first to suffer when nutrition, sanitation, or healthcare access falls short. Close spacing between successive pregnancies is one well-documented driver of infant death, since repeated pregnancies in quick succession deplete a mother’s physical resources and reduce the care and breastfeeding time available to each child. India’s own infant mortality figures track this transition closely, falling from close to 190 deaths per 1,000 live births around 1950 to well under 30 by 2020, a decline of over 85 percent within seven decades.

Measuring mortality accurately is harder than it sounds. In many developing regions, deaths that occur outside the formal medical system, at home, in remote villages, or during migration, often go unregistered entirely, which can distort official statistics. Cultural practices around gender also shape mortality patterns in ways that pure biology cannot explain. Historical and regional evidence of female infanticide and neglect of girl children in parts of South Asia shows why demographers insist on looking beyond raw death counts to the social conditions producing them, since gender-based differences in care, nutrition, and medical attention directly show up in mortality data.

Migration: population on the move 🔗

Unlike birth and death, which happen exactly once to each person, migration can happen repeatedly over a lifetime. Migration is the movement of people from one place of residence to another, either within a country, known as internal migration, or across international borders. Of the three demographic processes, internal migration is generally considered the most significant for redistributing population within a country, reshaping which regions grow, which shrink, and how cities expand.

India’s internal migration story 🔗

India offers one of the largest internal migration systems in the world. According to Census data, India had over 45 crore internal migrants in 2011, making up roughly 38 percent of the population, with the number of migrants growing far faster than the population itself over the preceding decade. Most of this movement happens within a person’s own state rather than across state lines, and a significant share is rural-to-rural rather than the rural-to-urban flow that often dominates public imagination. States such as Uttar Pradesh and Bihar remain the largest sources of migrants, while Maharashtra and Delhi consistently rank among the biggest destinations. Notably, women make up the majority of internal migrants, largely because marriage remains the single most common reason for female migration in both rural and urban India, while men more often move for employment.

Push and pull factors 🔗

Migration decisions are usually explained through push and pull factors. Push factors are the conditions that drive people away from a place: job loss, discrimination, limited access to social and marriage partners, or catastrophes like floods and epidemics. Pull factors are the conditions that draw people toward a new place: better education and employment prospects, more favourable environmental conditions, or simply the presence of family and community networks. In practice, most migration decisions involve a mix of both, and studies examining rural-to-urban movement have found that economic opportunity and access to education and facilities typically outweigh environmental pressures as the dominant driver, even in regions where environmental degradation is visible.

One category of movement that official statistics often miss is temporary, short-duration migration tied to life events. Research using demographic surveillance data in Maharashtra found that a large share of women temporarily relocate to their natal homes around childbirth, a pattern that complicates how health systems track and provide continuity of maternal care, since women may give birth or seek postpartum care far from where they usually live. This kind of migration rarely shows up in census counts, yet it has real consequences for how health data should be interpreted.

International migration: immigration and emigration 🔗

International migration involves crossing national borders, and is classified from two directions: immigration, or movement into a new country, and emigration, or permanent departure from one’s country of origin. India is a major source of both. Twentieth and twenty-first century emigration from India has included economic migrants moving for better-paid work, professionals moving into specialised sectors abroad, and members of the Indian diaspora settling permanently in destination countries. India today produces more international migrants than any other country and hosts the world’s largest diaspora abroad, a pattern often summarised through the idea of “brain drain,” where educated professionals trained at subsidised public institutions end up contributing their skills to other economies rather than India’s own.

Immigration into India, while smaller in scale, carries its own significance, driven by family reunification, refuge from conflict in neighbouring countries, and economic opportunity for migrants from countries such as Nepal, Bangladesh, and Bhutan. Together, these flows show that migration, unlike fertility and mortality, is rarely a one-directional or one-time event; the same person may migrate for education, again for marriage, and again for retirement, each move driven by a different combination of push and pull factors.

Why these processes cannot be studied in isolation 🔗

Fertility, mortality, and migration rarely move independently. Falling infant mortality is closely linked to declining fertility, since parents who expect more of their children to survive tend to have fewer of them. Migration, in turn, reshapes both fertility and mortality patterns in origin and destination regions, since young working-age adults who migrate often delay childbearing, while healthcare access at the destination can alter mortality outcomes for the migrants and the families they leave behind. Studying these three processes together, rather than as separate statistics, is what allows demographers and anthropologists to explain not just how many people live somewhere, but who they are, how their households are structured, and how their communities are likely to change in the decades ahead.

What do you think? Which of the three demographic processes do you think will reshape your own city or state the most over the next twenty years? And how might falling fertility rates change the kinds of support systems that families and governments need to build going forward?

References

1. https://openstax.org/books/introduction-sociology-3e/pages/20-1-demography-and-population
2. https://www.dataforindia.com/fertility/
3. https://www.business-standard.com/health/indians-are-living-longer-80-years-of-india-s-health-transformation-126081401293_1.html
4. https://www.drishtiias.com/to-the-points/paper1/human-migration-in-india
5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12173446/