Fertility: Measures and Determinants of Fertility

• Fertility is the actual reproductive performance of a population: the number of live births to women of child-bearing age, conventionally 15–49 years.
• It is the most variable of the three components of population change. Small, sustained changes in fertility reshape growth, age structure, labour supply and dependency for generations.
• Fertility is not only biological. It is a behavioural and socio-economic outcome of marriage customs, household economics, women’s status, health and state policy, and it changes as societies pass through the demographic transition.

Concept of Fertility

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Fertility and Fecundity

• Fecundity is the biological capacity of a woman, man or couple to conceive and bear children.
  • Its absence is sterility or infecundity: primary (never able to conceive) or secondary (unable after an earlier birth).
• Fertility is the realised outcome: births that actually occur.
  • Fecundity sets the upper limit. A population that marries early and practises no birth control can approach about 15 births per woman, but none reaches it.
  • Natural fertility, a term of the French demographer Louis Henry (1961), is fertility without deliberate limitation by parity. The highest recorded natural fertility was among the Hutterites of North America in the 1920s, at about 10–11 children per woman.
• Fertility matters for population geography because:
  • it is the main reason why growth rates differ between regions today, as mortality has converged;
  • small changes have large cumulative effects through population momentum: a young population keeps growing for decades after fertility reaches replacement;
  • its patterns trace social change: schooling, urbanisation, women’s empowerment and economic transition;
  • with mortality, it drives both the demographic and the epidemiological transition.

Measures of Fertility

• Measures move from crude (all population in the denominator) to refined (only women at risk, by age and marital status), and from period measures (one year) to cohort measures (a generation of women followed through life).

Crude Birth Rate (CBR)

• Definition: live births in a year per 1000 mid-year population.
  • CBR = (B ÷ P) × 1000.
• Strength: simple; needs only total births and total population, so it is available almost everywhere.
• Limitations:
  • The denominator includes men, children and old women who cannot bear children, so it is not a true fertility rate.
  • It depends on the age and sex structure. A young population with many women of child-bearing age shows a high CBR even at modest fertility. It is therefore unsuitable for comparing populations with different structures.
• Values (2024): world 16.3; Central African Republic 46, Chad 43, Niger 41; South Korea 4.7, Hong Kong 4.9, Japan 5.7. India 18.3 (SRS): Bihar 26.8, Kerala 11.1.

General Fertility Rate (GFR)

• Definition: live births per 1000 women aged 15–49 in a year.
  • GFR = (B ÷ women 15–49) × 1000.
• Strength: more accurate than CBR, as only women of reproductive age are in the denominator.
• Limitation: it ignores how fertility differs within 15–49; a population with more women in their twenties shows a higher GFR.
• India: 63.6 in 2024 (rural 71.1, urban 49.8), down from about 79 a decade earlier.

General Marital Fertility Rate (GMFR)

• Definition: live births per 1000 currently married women aged 15–49.
• Relevance: in societies such as India, where almost all births occur within marriage, it separates the effect of marriage patterns from that of birth control within marriage.
• India: 103.1 in 2024 (SRS).

Age-Specific Fertility Rate (ASFR)

• Definition: live births to women of a given age group per 1000 women of that age group, usually in five-year groups from 15–19 to 45–49.
  • ASFR(x) = (births to women aged x ÷ women aged x) × 1000.
• Strength: reveals the age pattern of childbearing:
  • Teenage fertility (15–19), high where child marriage persists.
  • The peak age: 20–24 in India, shifting to 25–29 as marriage is delayed; 30–34 in most of Europe and East Asia.
  • The postponement of births as education lengthens.
• It is the building block of the TFR, GRR and NRR.

Total Fertility Rate (TFR)

• Definition: the average number of children a woman would bear if she lived through her reproductive years experiencing the current ASFRs. It is a synthetic (hypothetical) cohort measure.
  • TFR = 5 × Σ ASFR ÷ 1000, when ASFRs are for five-year groups per 1000 women.
• Importance:
  • It is independent of age structure, so it is the most widely used measure for comparing populations.
  • It shows whether a population will grow, stabilise or decline in the long run.
• Replacement-level fertility: about 2.1 children per woman in low-mortality populations.
  • The extra 0.1 covers the surplus of boys at birth (about 105 per 100 girls) and the deaths of girls before they reach child-bearing age.
  • Where female mortality is high, replacement needs a TFR of 2.5–3.3; in parts of Sub-Saharan Africa it is still near 2.5.
• A worked example (illustrative): if the ASFRs per 1000 women for 15–19 to 45–49 are 20, 120, 130, 80, 30, 10 and 0, their sum is 390. Multiplied by the five-year width, this gives 1950 births per 1000 women, a TFR of 1.95.
• Limitation: when women postpone births, the period TFR falls even if completed family size does not. This tempo effect depresses TFR in Europe and East Asia.
• India: 1.9 (SRS 2024), below replacement since 2020; NFHS-6 (2023–24) gave 2.0 (urban 1.6, rural 2.1).

Total Marital Fertility Rate (TMFR)

• Definition: the number of children a woman would bear in her reproductive span if she were married throughout and experienced current marital ASFRs.
• Use: comparing TMFR with TFR isolates the effect of age at marriage from fertility control within marriage.
  • India’s TMFR was 4.9 in 2024 against a TFR of 1.9. Much of the decline in TFR has come from later marriage and sterilisation after the desired family size.

Gross Reproduction Rate (GRR)

• Definition: the average number of daughters a woman would bear over her reproductive life at current ASFRs, ignoring mortality.
  • GRR = TFR × proportion of births that are female (about 0.488).
• Significance: it shows whether women are producing enough daughters to replace themselves, if all daughters survived.
• Limitation: it assumes no deaths among the daughters before child-bearing age.
• India: 0.9 in 2024 (rural 1.0, urban 0.7); Bihar 1.4 in 2021.

Net Reproduction Rate (NRR)

• Definition: the average number of daughters a woman would bear who survive to the age of their mothers at childbearing, at current fertility and female mortality.
  • NRR = Σ (female ASFR × probability of surviving from birth to that age).
• Interpretation:
  • NRR = 1: each generation of women exactly replaces itself; this is true replacement level. The population becomes stationary in the long run, once momentum works out.
  • NRR above 1: long-run growth. NRR below 1: long-run decline.
• NRR and TFR:
  • TFR 2.1 is replacement only because, at low mortality, it gives an NRR of about 1.
  • At high female mortality or a masculine sex ratio at birth, a TFR of 2.1 gives an NRR below 1. The NRR is therefore the more exact test of replacement.
  • A population with NRR below 1 can still grow for decades through momentum, as large young cohorts pass through child-bearing ages. India is in this phase.

Child–Woman Ratio (CWR)

• Definition: children aged 0–4 per 1000 women aged 15–49, from a single census.
• Use: an indirect estimate of fertility where birth registration is incomplete: remote areas, historical censuses, small areas below the reach of surveys.
• Limitations: it counts surviving children, so high infant mortality lowers it; and it is distorted by under-enumeration of infants and by migration of women.

Cohort Measures

• Completed (cohort) fertility: the average number of children actually born to a group of women by the end of their reproductive life, often measured as children ever born to women aged 45–49.
• Strength: it is a real, not hypothetical, family size and is free of tempo effects.
• Limitation: it is known only after the cohort has finished childbearing, so it describes the past.

Sources of Fertility Data in India

• Census: children ever born and the child–woman ratio, every ten years. The next count has a reference date of 1 March 2027.
• Sample Registration System (SRS): annual CBR, GFR, ASFR, TFR, GRR and marital rates for India and the larger States, from a large, continuous sample of households.
• National Family Health Survey (NFHS): TFR, its proximate determinants and their social correlates.
  • NFHS-6 (2023–24) found 69.1% of currently married women using a contraceptive method (36.5% female sterilisation, 0.5% male sterilisation) and an unmet need of 8.5%, against 66.7% and 9.4% in NFHS-5.
• Civil Registration System: registered births, now near-complete in the south but still incomplete in parts of the north.

Determinants of Fertility

Proximate and Fundamental Determinants

• The sociologists Kingsley Davis and Judith Blake (1956) showed that social and economic factors can affect fertility only through a small set of intermediate variables. These act on three sequential steps:
  • Exposure to intercourse:
    • age at entry into marriage or sexual union;
    • permanent celibacy;
    • time spent outside unions through widowhood, divorce or separation;
    • voluntary abstinence (post-partum taboos), involuntary abstinence (illness, spousal migration), coital frequency.
  • Conception:
    • involuntary fecundity or infecundity (natural sterility, sterility from venereal disease);
    • lactation and post-partum amenorrhoea;
    • contraception and voluntary sterilisation.
  • Gestation and live birth:
    • spontaneous foetal loss (miscarriage);
    • induced abortion.
• John Bongaarts (1978) reduced these to four proximate determinants that explain almost all variation in fertility between populations:
  • marriage (the proportion of women in union),
  • contraception,
  • post-partum infecundability (mainly breastfeeding),
  • induced abortion.
  • Each subtracts from a biological maximum of about 15 births per woman: TFR = Cm × Cc × Ci × Ca × total fecundity.
• Behind these lie the fundamental (ultimate) determinants: the socio-economic, cultural, institutional and environmental setting. They work only through the proximate variables.
  • Female education lowers fertility by raising the age at marriage and increasing contraceptive use, not directly.
• India through this lens:
  • Most of the decline came from contraception, overwhelmingly female sterilisation after the desired family size, and from a rising age at marriage.
  • Post-partum infecundability is weakening as breastfeeding shortens, which by itself would push fertility up.
  • Induced abortion plays a smaller, but in some states a sex-selective, role.
• How the fundamental determinants lower fertility:
  • Urbanisation: children are no longer needed as farm labour, and housing and schooling are costly in cities.
  • Pensions and social insurance: the state, not children, supports people in old age, sickness and unemployment.
  • Compulsory schooling: it removes children from work and adds costs (fees, uniforms, books), turning children from an asset into a cost.
  • Education, especially of women: wider horizons, awareness of contraception and paid careers.
  • The changing status of women: paid work raises the opportunity cost of childbearing and delays marriage.
  • Consumption: fewer children leave more of the household budget for wants beyond needs.
  • Secularisation: religion loosens its hold on marriage, contraception and abortion.

Theories of Fertility Decline

• Classical transition theory (Frank W. Notestein, 1945): industrialisation, urbanisation and falling mortality change the costs and benefits of children; fertility follows mortality down after a lag.
• Ansley J. Coale (1973) set three preconditions for a lasting decline, drawn from the Princeton European Fertility Project:
  • fertility must be within the calculus of conscious choice;
  • smaller families must be seen as advantageous;
  • effective means of control must be available.
  • The project found that European provinces sharing a language or culture declined together, whatever their economic level. This pointed to the diffusion of ideas as well as economics.
• Economic theories:
  • Gary Becker (1960): rising income shifts parents from the quantity to the quality of children, investing more in fewer.
  • Richard Easterlin (relative income hypothesis): couples have more children when their income is high relative to their material aspirations, which explains swings such as the post-war baby boom.
  • John C. Caldwell (1976): the transition follows the reversal of intergenerational wealth flows. In traditional families wealth flows from children to parents, so many children pay; in modern nuclear families it flows from parents to children, so few are rational.

Biological Determinants

• Fecundity:
  • Shaped by genetics, hormonal balance, reproductive anatomy and general health.
  • It peaks in the twenties and falls after the mid-thirties as the ovarian reserve declines. Delayed childbearing in Indian cities therefore brings more involuntary infertility and demand for assisted reproduction.
• Age at menarche and menopause: an earlier menarche and a later menopause lengthen the reproductive span. Better nutrition has lowered the age at menarche worldwide.
• Health and nutrition: severe undernutrition delays ovulation and raises pregnancy loss; deficiencies of iron, iodine and folate impair reproduction.
• Breastfeeding and post-partum amenorrhoea: lactation delays ovulation and naturally spaces births.
  • Societies with prolonged breastfeeding have birth intervals of 2–3 years.
  • A shift to bottle feeding shortens intervals unless contraception replaces it.
• Disease:
  • Reproductive tract and sexually transmitted infections (gonorrhoea, chlamydia, syphilis) cause pathological sterility.
  • Central Africa had an “infertility belt” from untreated infections in the mid-20th century.
• Child replacement effect: when a child dies, parents have another to “replace” it. Where infant mortality is high, couples also have extra births as insurance.

Socio-Cultural Determinants

• Marriage: the age at marriage is the strongest social predictor of fertility in societies where births occur within marriage.
  • Early marriage lengthens exposure. NFHS-6 (2023–24) found 20.1% of women aged 20–24 married before 18, and about 35% in Bihar, which has the highest TFR.
  • West Bengal has even more child marriage (36%) but a TFR of 1.3 (SRS 2024): early, near-universal sterilisation after two children offsets early marriage.
• Religion: doctrines affect the acceptance of contraception and abortion and the value placed on large families.
  • Israel’s ultra-Orthodox (Haredi) community has a TFR above 6.
  • In India, fertility differences between religious groups have narrowed sharply and follow education and income more than religion.
• Family structure:
  • Joint families spread the costs and care of children and favour larger families.
  • Nuclear families bear the full cost and favour fewer children.
• Gender norms and son preference:
  • Patriarchal, patrilineal societies want sons for lineage, inheritance, old-age support and ritual.
  • Couples keep having children until the desired number of sons is born: the “stopping rule” of north India.
• The value of children:
  • In agrarian societies children are labour and security.
  • In urban-industrial societies they are an expense and an emotional good: rural Madhya Pradesh against urban Bengaluru.

Economic Determinants

• Level of development: pre-industrial agriculture favours high fertility; urban-industrial economies favour low fertility. In India the rural TFR (2.1) exceeds the urban (1.5) (SRS 2024).
• Children as asset or liability: where children work on farms and support parents in old age, they repay their cost; where schooling is long and pensions exist, they do not. This is the economic core of the theories of Becker and Caldwell.
• Women’s employment: paid formal work raises the opportunity cost of childbearing; career women marry and bear children later.
• Cost of child-rearing: in South Korea and Japan, the costs of housing, private tutoring and long working hours are central to TFRs of 0.75 and 1.15 (2024).

Demographic Determinants

• Infant and child mortality:
  • High mortality leads to insurance and replacement births.
  • Falling mortality is followed, after a lag, by falling fertility: the core sequence of the demographic transition.
  • Kerala’s low IMR went with its early fertility decline.
• Age structure: a young population has many women entering child-bearing ages and so many births; an ageing one has fewer.
• Migration:
  • Rural–urban migrants usually adopt the lower fertility of the city within a generation.
  • Spousal separation through male labour migration lowers fertility in the source areas (the Kosi plain of Bihar, the Uttarakhand hills).

Educational Determinants

• Female education is the most powerful single socio-economic determinant. It leads to:
  • later marriage and first birth;
  • better knowledge and use of contraception;
  • greater autonomy in household decisions;
  • lower desired family size and lower child mortality.
  • Kerala and Tamil Nadu combined high female literacy with early fertility decline.
• Male education: educated men favour smaller families and invest more in each child. NFHS data show an inverse relation between parents’ schooling and the TFR.

Technological and Health-System Determinants

• Contraceptive technology: access to pills, IUDs, injectables, implants and sterilisation lowers fertility.
  • Female sterilisation is the dominant method in India and drove much of its decline.
• Reproductive health services: antenatal care, safe delivery, counselling and abortion services reduce unplanned births. Kerala’s strong primary health system stabilised its fertility early.
• Medical technologies:
  • Assisted reproduction (IVF) extends childbearing to later ages.
  • Prenatal sex determination lets couples reach the desired number of sons with fewer births. It lowers fertility but distorts the sex ratio at birth.

Psychological and Ideational Determinants

• Desired family size: values, aspirations and lifestyle set the ideal; the urban middle class increasingly chooses one or two children.
• Attitudes to contraception: myths, misinformation and taboos reduce use; counselling and education improve it.
• Women’s aspirations: careers and autonomy delay or limit childbearing.
• The second demographic transition (Ron Lesthaeghe and Dirk van de Kaa, 1986): in post-industrial societies, individualism, self-fulfilment and the decline of marriage push fertility below replacement and keep it there.

Environmental Determinants

• Climate and altitude: harsh environments and nutritional stress lower fecundity. Some high-altitude Himalayan societies (Ladakh, Spiti) historically restrained births through fraternal polyandry and monastic celibacy.
• Urban and rural settings:
  • Cities bring high living costs, crowding and career opportunities, and so low fertility.
  • Rural livelihoods based on agriculture favour larger families.

Policy and Institutional Determinants

• Family planning programmes:
  • Coercive policies cut fertility fast. China’s one-child policy (1980–2015) was followed by two- and then three-child (2021) policies as fertility fell to about 1.0.
  • Voluntary, target-free programmes work more slowly: India’s population policy, from the National Population Policy 2000 to Mission Parivar Vikas (2016) for high-fertility districts of seven states.
• Pro-natalist support: parental leave, child allowances and childcare can slow the decline but rarely reverse it.
  • South Korea has spent heavily on incentives since 2006; its TFR fell to 0.72 in 2023 before a first small rise, to 0.75, in 2024.
  • The Nordic countries, long cited as successes at about 1.8, have fallen to about 1.25–1.5 (2024).
  • The rationale and types of these policies are set out in population policy: rationale and elements.
• Health policy: immunisation and maternal and child health cut infant deaths and so the need for insurance births. India’s IMR fell from 68 in 2000 to 24 in 2024.
• Legal age of marriage: 18 for women in India. A 2021 Bill to raise it to 21 lapsed with the dissolution of the Lok Sabha in 2024.

Trends and Patterns: World and India

World

• Global TFR was about 2.2 in 2024, less than half its level of about 5 in the 1950s (UN WPP 2024). It is projected to fall below 2.1 around the 2050s.
• More than half of all countries are now below replacement: 119 of 217 countries and territories in 2024; 66 were below 1.5 (World Bank, from UN WPP 2024).
• Regions (TFR, 1990 → 2024):
  • Sub-Saharan Africa: 6.3 → 4.3. The slowest transition, with persistent poverty, low female schooling, early marriage, weak family-planning services and a high value placed on children. It now accounts for nearly 30% of the world’s births.
  • Middle East, North Africa, Afghanistan and Pakistan: 5.4 → 3.0. Pakistan is still at 3.5 and Afghanistan above 4.
  • South Asia (India, Bangladesh, Nepal, Sri Lanka and neighbours): 4.1 → 2.0, now below replacement.
  • Latin America and the Caribbean: 3.3 → 1.8.
  • East Asia and the Pacific: 2.6 → 1.3, now the world’s lowest-fertility region.
  • Europe and North America: about 1.6. Below replacement since the 1970s.
• Extremes (2024):
  • Highest: Chad, Somalia and DR Congo (about 6.0), the Central African Republic, Niger (5.9), Mali and Angola. Every country with a TFR above 5 is in Africa, mostly the Sahel and Central Africa.
  • Lowest: Macao (0.6), South Korea (0.75), Hong Kong (0.8), Puerto Rico, Singapore and Ukraine (about 1.0), China (1.0). These are urban, high-cost societies with late marriage, or societies hit by war and emigration.
• The most populous countries sit at different stages: China 1.0, the USA 1.6, India 2.0 (UN estimate), Indonesia 2.1, Pakistan 3.5, Nigeria 4.4.
• Changing fertility is redrawing the world map of population. Under UN WPP 2022, more than half of the growth to 2050 will come from eight countries: DR Congo, Egypt, Ethiopia, India, Nigeria, Pakistan, the Philippines and Tanzania. Africa’s share of world population will rise while Europe’s and East Asia’s fall.
• Very low fertility brings ageing, shrinking workforces and rising dependency, as in Japan and South Korea. Their parallels with Western Europe show that ageing is now the dominant demographic challenge of rich countries.

India

• Long-term decline (SRS): TFR 5.2 in 1971, 4.5 in 1981, 3.6 in 1991, 3.1 in 2001, 2.4 in 2011, 2.0 in 2020 and 1.9 in 2023–24.
  • The CBR fell from 36.9 to 18.3 over 1971–2024.
  • NFHS rounds show the same path: 3.4 (1992–93), 2.9, 2.7, 2.2, 2.0 (2019–21) and 2.0 (2023–24).
• Rural 2.1 and urban 1.5 (2024): rural India reached replacement only in 2023.
• Inter-state divergence (SRS 2024):
  • Above replacement (six states): Bihar 2.9, Uttar Pradesh 2.6, Madhya Pradesh 2.4, Rajasthan 2.3, Chhattisgarh and Jharkhand 2.2.
  • Lowest: Delhi 1.2; Kerala, Tamil Nadu and West Bengal 1.3; Andhra Pradesh, Maharashtra, Punjab and Jammu and Kashmir 1.4.
• NFHS-6 (2023–24), covering the smaller States/UTs too (Manipur’s results were not released):
  • Highest in Bihar (2.7); Uttar Pradesh, Jharkhand, Meghalaya and Lakshadweep (2.2); Madhya Pradesh and Rajasthan (2.1).
  • Lowest in the Andaman and Nicobar Islands (0.9) and Sikkim (1.0).
  • Meghalaya fell from 2.9 to 2.2 in four years, one of the fastest declines recorded.
  • Survey and SRS values differ for some states (Kerala 1.8 in NFHS-6 against 1.3 in SRS 2024), because of sampling and the reference period.
• The spatial pattern:
  • The south, west and Punjab–Himachal reached replacement in the 1990s and 2000s, through female literacy, health systems and later marriage.
  • The north-central Hindi belt lags, with early marriage, low female schooling, son preference and weak services.
  • The national figure therefore hides two demographic Indias: an ageing south and a young north.
• Why the south went first:
  • Kerala: universal literacy, a strong public health system, land reform and a tradition of women’s education brought replacement fertility by the late 1980s.
  • Tamil Nadu: political commitment, social reform movements, the noon-meal scheme and effective services.
  • Andhra Pradesh reached low fertility at modest literacy through sterilisation after two children, showing that services can lead development.

• Projections:
  • The UN medium variant keeps India’s TFR below replacement throughout the century.
  • The Global Burden of Disease forecast (The Lancet, 2024) puts it at 1.29 in 2050 and 1.04 in 2100.
  • Because of momentum, India’s population will keep growing until the early 2060s (UN WPP 2024), even with below-replacement fertility. Its trajectory is traced under population growth in India.

Implications of Declining Fertility

• Momentum: a population whose fertility has just fallen below replacement still has large cohorts entering child-bearing ages, so births stay high for a generation. Growth stops only when the age structure catches up.
• Benefits:
  • a falling child dependency ratio opens a demographic dividend: more workers per dependant, higher savings, more investment per child;
  • better maternal and child health, and more time for women’s education and work.
• Costs of sustained very low fertility:
  • ageing, a shrinking labour force and pressure on pensions and health care, as in Japan (1.15), Italy and South Korea;
  • shrinking villages and schools, and dependence on immigration.
• India’s policy challenge sits at both ends:
  • completing the transition in the north-central states;
  • preparing the south, already below 1.5, for early ageing, labour shortages and in-migration from the north.
  • Divergent growth also bears on the delimitation of parliamentary seats once the freeze based on the 1971 Census ends.
• The global and Indian fertility transition is therefore near universal but uneven. Policy must manage not only the decline but its consequences: balancing population stabilisation, economic growth and social well-being.