Guided story

India’s Population: How Many We Are and Where We’re Heading

India is the most populous country on earth, but fertility has fallen below replacement. Here is the full story in numbers, from the first child to the last projection.

How many Indians are there today, and how has the count changed since 1960?

India's population in 2024 is estimated at 145.1 crore people, according to the World Bank. In 1960, the country had only 43.6 crore. In a single generation, the number tripled. This is not a figure; the last full count was in 2011. All current numbers are estimates, built from surveys and population models. The line on the chart climbs steeply because death rates fell before birth rates did. Between 1960 and today, life expectancy nearly doubled, and famine was largely ended. So for decades, the population swelled even as each woman started having fewer children. Today that momentum is still carrying the total upward, but the pace is slower. The next census, now under way, will give a fresher picture. For now, 145 crore is the best estimate of how many Indians are alive.

Chart 1

India's population, 1960 to today

World Bank · SP.POP.TOTL

people
145.1 crore

2024 · latest point

050100150 crore1960197019801990200020102020thisindianlife.todaycrore0501001501960198020052024thisindianlife.today

India's population has more than tripled from 43.6 crore in 1960 to 145.1 crore in 2024.

The line shows a steep upward slope, especially after the 1960s. The growth rate was higher in the 1970s and 1980s, but the total kept climbing because momentum built up. Today, India is the most populous country, but growth is slowing. The last census was in 2011; this is an estimate from the World Bank based on surveys and models. The rise is driven by falling death rates before birth rates declined, creating a bulge that is still propagating. Now, with fertility below replacement, the line is still rising but will eventually flatten.

How to readLook at the long upward slope and the latest value of 145.1 crore.

Watch outThinking the line is a count from an annual census; it is an estimate.

How does India's population compare to China and the world?

India's population of 145.1 crore now edges past China's 140.9 crore, making it the world's most populous country. The crossover happened around 2023. In 1990, China had 113.5 crore and India 86.5 crore; the gap has been narrowing for decades as China's fertility plunged earlier and its population has begun to shrink. The world population stands at 814.2 crore. Together, India and China account for about 286 crore people, more than a third of all humans. The three lines on the chart, India, China, World, each show upward growth, but India's continues to climb while China's recently turned flat and may decline. This marks a historic shift: for the first time since the UN began such tracking, India is the most populous nation.

Chart 2

India, China and the world

World Bank · total population · 1990 to today

people
145.1 crore

India · 2024 · latest point

02004006008001,000 crore1990199520002005201020152020145.1 crore140.9 crore814.2 crorethisindianlife.todaycrore02004006008001,0001990200020152024145.1140.9814.2thisindianlife.today
IndiaChinaWorld

India overtook China around 2023 to become the world’s most populous country.

The multi-line chart plots three populations since 1990. India’s line starts lower than China’s and crosses it after 2017. China’s line flattened as its fertility fell below replacement decades ago, and its population has begun to shrink. The world line grows more steeply. India and China together make up over a third of humanity. The crossover is a historic shift, reflecting faster Indian growth and China’s earlier demographic transition.

How to readCompare the India and China lines; note the crossover around 2023.

Watch outThinking India’s line stops at China’s peak; it continues upward.

What share of the world's people are Indian?

India's share of world population was 14.4% in 1960. By 2024, it had risen to 17.8%. That means nearly one in every six people on the planet is Indian. The line on the chart moves upward steadily as India's growth rate outpaced the global average for much of the past six decades. This share will likely continue to rise for a few more decades, as the world's population growth slows but India still adds people. But eventually, as India's fertility falls further and other regions grow, the share will stabilise and perhaps dip. For now, India's demographic weight is enormous: around 145 crore lives out of a global 814 crore. That is more than the entire population of every other country except China.

Chart 3

India's share of world population

World Bank · SP.POP.TOTL

%
17.8%

2024 · latest point

1415161718%1960198020002020thisindianlife.today%14151617181960198020052024thisindianlife.today

India’s share rose from 14.4% in 1960 to 17.8% in 2024.

The line shows a steady increase, with a slight acceleration in the 2000s as global growth slowed. One in every six people alive is Indian. This share will likely peak in coming decades as India’s growth slows and other regions continue growing. The share metric captures India’s relative demographic weight. It is a derived number from World Bank totals. The upward trend reflects India outpacing the global average for decades.

How to readSee the steady rise from 14.4% to 17.8%.

Watch outAssuming share only rises; it will eventually stabilise and possibly decline.

Where do Indians live, and how quickly are cities growing?

India is still mostly a rural country, but the urban share is rising slowly. In 1960, only 17.9% of Indians lived in urban areas. By 2024, that figure had crept up to 35.4%. That means about two in every three Indians still live in villages. The pace of urbanisation is slower than many Asian peers. This matters for fertility because urban areas have much lower birth rates. The rural-urban divide in fertility is stark: rural women still average 2.1 children, while urban women average only 1.5. As more people move to towns and cities, the national fertility rate tends to fall. The chart shows a slow upward slope; urbanisation is happening, but not at the explosive pace some expect.

Chart 4

Where Indians live: the slow shift to cities

World Bank · SP.URB.TOTL.IN.ZS

% of population
35.4%

2024 · latest point

152025303540%1960197019801990200020102020thisindianlife.today%1520253035401960198020052024thisindianlife.today

Urban share doubled from 17.9% in 1960 to 35.4% in 2024, but two-thirds of Indians remain rural.

The line rises slowly, not explosively. India’s urbanisation lags behind many peers. This matters for fertility because urban areas have a TFR of only 1.5, while rural is 2.1. The slow shift means the national fertility decline is gradual. The World Bank data does not distinguish between city size; it includes all urban settlements. The chart reminds that population is also about location and density.

How to readTrack the urban share line from 17.9% to 35.4%.

Watch outThinking urban share equals city population; it includes towns.

Is India's population still growing, and when will growth peak?

India's population is still growing, but the annual growth rate is falling. In the year 2000, the rate was 1.9%. The UN's median shows it declining steadily: it will cross zero around 2061 and then turn negative, reaching -0.5% by 2100. So the population will keep rising, but more slowly each year, until it peaks. The peak is not when the growth rate first falls, but when the rate hits zero. This delay is : because about 68% of Indians are of working age (15-64) and many are young, births still outnumber deaths even though each woman has fewer children. The chart includes several UN scenarios; the high-fertility variant still has positive growth in 2100 (0.3%), while the low-fertility variant has a much deeper fall (-1.6%). The exact path depends on future fertility.

Chart 5

Annual population growth rate, to 2100

UN Population

%
-0.5%

2100 · latest point

-1012%200020202040206020802100thisindianlife.today%-10122000203520652100thisindianlife.today

Growth rate fell from 1.9% in 2000 and will turn negative around 2061, reaching -0.5% by 2100 (UN median).

The line shows a steady decline from historical highs. The UN median scenario crosses zero around 2061. Other scenarios fan out: high-fertility still shows 0.3% growth in 2100, while low-fertility shows -1.6%. The rate is a percentage; a falling rate does not mean a shrinking population until it goes below zero. Momentum keeps the total growing even as the rate drops. The chart visualises when the peak happens, the moment growth stops.

How to readFollow the downward trend; negative after about 2060.

Watch outConfusing growth rate with total population size.

How many babies are born each year relative to the population?

The , which counts live births per 1,000 people in the population, was 18.3 in 2024 according to India's Sample Registration System (SRS). This is down from 19.7 in 2019. The rural rate is higher: 20.2 per 1,000. In urban areas, it is 14.7. So even though the total number of births is still huge because the population is huge, the rate at which Indians are having babies has been falling. The crude birth rate is a useful snapshot of how many births are happening relative to overall numbers, but it can be influenced by the age structure. A young population can have many births even if fertility per woman is low. The rural-urban gap is visible on the chart; it reflects both differences in fertility and differences in the proportion of women of childbearing age.

Chart 6

Births per 1,000 people

SRS 2024 · crude birth rate · 2019 to 2024

per 1,000 population
18.3

All India · 2024 · latest point

141618202220192020202120222023202418.320.214.7thisindianlife.today141618202220192020202418.320.214.7thisindianlife.today
All IndiaRuralUrban

Crude birth rate was 18.3 per 1,000 in 2024, with rural at 20.2 and urban 14.7.

SRS data from 2019 to 2024 shows a decline. The three lines reflect the rural-urban gap. The crude birth rate does not adjust for age structure, so it can be influenced by the share of women of childbearing age. Still, the downward trend is clear. Rural areas have a higher rate partly because of higher fertility and partly because of a younger population. The urban rate is well below the replacement threshold.

How to readCompare the national rate (18.3) with rural and urban.

Watch outThinking this is births per woman; it’s per 1,000 total population.

How many children does the average Indian woman have?

The total fertility rate (TFR) is the average number of children a woman would have over her lifetime at current birth rates. In 1960, India's TFR was 5.92, among the highest in the world. By 2024, it had fallen to 1.96, a drop of two-thirds. This is not the number of children any specific woman has, but a composite snapshot. The chart shows a steady, almost linear decline since the 1960s, with a slight flattening recently. The fall is due to many factors: higher education, later marriage, more contraception, and economic change. The World Bank data reflects this long arc. Today, at 1.96, India is just below the of about 2.1 children per woman. That means the next generation, all else equal, would be smaller than the current one.

Chart 7

Births per woman, 1960 to today

World Bank · SP.DYN.TFRT.IN

births per woman
2

2024 · latest point

02461960197019801990200020102020thisindianlife.today02461960198020052024thisindianlife.today

Total fertility rate fell from 5.92 to 1.96 children per woman.

The long arc from 1960 to 2024 shows a persistent decline, with a slight flattening after 2010. This World Bank measure is an estimate synthesising multiple sources. The drop from nearly six to under two is among the steepest in the world. The line illustrates the demographic transition completed: from high fertility to below replacement. Each woman today, on average, has roughly the number of children needed to keep the population constant in the long run (absent migration).

How to readWatch the line drop from 5.92 to 1.96.

Watch outThinking fertility is only about family choices; it reflects broad social change.

Is India's fertility below replacement level?

Yes. The replacement level is about 2.1 children per woman, the rate needed for each generation to exactly replace itself, accounting for some child mortality. India's SRS data for 2024 puts the national TFR at 1.9, below that threshold. The rural TFR is 2.1, exactly at replacement, while urban TFR is only 1.5. So the national average is being pulled down by cities, even though most Indians still live in rural areas. The SRS tracks this closely. Since 2019, the national rate has fallen from 2.1 to 1.9. Once a country falls below replacement, it enters a new demographic phase: population will eventually stop growing and begin to shrink, though momentum can delay this for decades. The chart with three lines, national, rural, urban, makes the gap clear. Urban fertility is already far below replacement, while rural is just hovering at the line.

Chart 8

Fertility is now below replacement

SRS 2024 · total fertility rate · 2019 to 2024

births per woman
1.9

All India · 2024 · latest point

1.41.61.822.22.42019202020212022202320241.92.11.5thisindianlife.today1.41.61.822.22.42019202020241.92.11.5thisindianlife.today
All IndiaRuralUrban

National TFR is 1.9, rural is 2.1, and urban is 1.5 (SRS 2024).

The three lines from 2019 to 2024 show the national rate crossing the 2.1 threshold. Rural is at replacement, urban far below. The SRS is India’s official vital rates survey. The gap means that as urbanisation proceeds, national fertility will fall further. The below-replacement status is a landmark: it signals that each generation will be smaller, though momentum delays the actual peak.

How to readNote the 1.9 national line versus the 2.1 threshold.

Watch outAssuming urban fertility drives the national average; rural is much larger.

How does India's fertility compare globally?

India's fertility decline is part of a worldwide trend, but it now sits in the middle of the global pack. The World Bank chart plots many countries. India's line, at 1.96, is above all advanced economies (United States, Germany, United Kingdom, Japan, South Korea) and far above East Asia's ultra-low rates, South Korea is below 1.0. However, India is below some neighbours like Bangladesh and Indonesia. The world average is about 2.3. India has joined the low-fertility world, but it is not exceptionally low. Its rate is still higher than most rich countries, and that difference matters because it means India's population will keep growing for longer than theirs. The chart also shows that fertility everywhere has been falling for decades. India's decline has been particularly steep and steady, converging with global norms.

Chart 9

India's fertility in a global context

World Bank · total fertility rate · 1960 to today

births per woman
2

India · 2024 · latest point

024681960197019801990200020102020replacement22.12.11.911.20.71.61.61.42.2thisindianlife.today024681960198020052024replacement22.12.11.911.20.71.61.61.42.2thisindianlife.today
IndiaBangladeshIndonesiaVietnamChinaJapanSouth KoreaUnited StatesUnited KingdomGermanyWorld

India’s fertility (1.96) is above all rich countries and East Asia but below Bangladesh and Indonesia.

The chart plots TFR since 1960 for multiple countries. India’s line shows a steady decline, converging with the world average (dashed). It is now above the US, UK, Germany, Japan, and South Korea (all below 1.8), but below Bangladesh (2.3) and Indonesia (2.2). China fell earlier and is now below India. The global trend is downward; India is part of that, but it’s not at ultra-low levels yet.

How to readCompare India’s line with peers; it’s converging but still higher.

Watch outThinking India’s rate is exceptionally low; many countries are much lower.

How do Indian states compare to rich nations on fertility?

Stand India’s states beside the rich world, and the picture is startling. Tamil Nadu and West Bengal, with a total fertility rate of about 1.3, sit below the United Kingdom, Denmark, Iceland, Portugal, and Norway. They are level with Finland, and only Japan, at 1.2, is lower. Maharashtra, at 1.4, matches Norway. Kerala, Karnataka, Andhra Pradesh, and Telangana all register 1.5, putting them on par with Denmark, Iceland, and Portugal. These are not outliers; several of India’s most populous states now have fertility rates that belong in the developed world, even though their income levels do not. For millions of Indian families, the two-child norm is now as entrenched as in Western Europe or Japan.

Chart 10

Indian states next to the rich world

SRS 2023 (states) and UN World Population Prospects 2024 (countries)

births per woman

Country

United Kingdom
1.6
Denmark
1.5
Iceland
1.5
Portugal
1.5
Norway
1.4
Finland
1.3
Japan
1.2

Indian state

Andhra Pradesh
1.5
Karnataka
1.5
Kerala
1.5
Telangana
1.5
Maharashtra
1.4
Tamil Nadu
1.3
West Bengal
1.3

Tamil Nadu and West Bengal, at 1.3, now have lower fertility than the UK, Denmark, and Norway, and are level with Finland.

The chart places Indian state TFRs next to selected rich countries. Tamil Nadu and West Bengal at 1.3 match Finland and are just above Japan's 1.2. Maharashtra at 1.4 aligns with Norway. Kerala, Karnataka, Andhra Pradesh, Telangana at 1.5 are on par with Denmark, Iceland, Portugal. The UK is at 1.6, so these states are below that. This underscores India's rapid fertility decline, now comparable to low-fertility rich economies even without similar income levels.

How to readLook along the horizontal bars: leftmost are lower fertility. Compare the TFR value for each Indian state with nearby countries.

Watch outDon't infer exact rankings; the chart groups similar values to show broad convergence, not precise standings.

How did India reach low fertility with so few women in paid work?

In most countries, fertility falls as more women take up paid work. India breaks that pattern. Its total fertility rate is now just under 2.0, roughly the same as Vietnam's. But while Vietnam got there with three-quarters of its women in the workforce, India's female labour-force participation hovers at barely a third. China and the United States, with fertility well below replacement, have over two-thirds of women working. Even Bangladesh, at a higher fertility of about 2.2, has nearly half of its women in jobs. India's journey to low fertility was driven not by formal employment for women, but by rising education, contraceptive access, and changing aspirations. This complicates the simple story that women's workforce entry is a necessary condition for fertility decline. ## Does fertility look different across India's states?

Yes, fertility is not uniform across India. The state-level map from NFHS-6 shows a clear north-south divide. In general, southern and western states have lower fertility, while northern and central states have higher. This pattern has been known for decades, shaped by differences in female education, income, and social norms. The map uses colour coding: darker shades indicate higher TFR. Bihar, Uttar Pradesh, and other states in the Hindi belt stand out with rates above replacement. In contrast, Kerala, Tamil Nadu, and others are well below. The national average of 1.9 masks this internal diversity. The map is a snapshot, and internal migration means some states' fertility may be influenced by the movement of people, but the broad geographic pattern is persistent.

Chart 11

Low fertility without the jobs

World Bank WDI · fertility vs female labour-force participation · latest year

births per woman
0%18%36%54%72%90%0.01.42.84.25.67.0AFG: 5.4% Female labour-force participation (% of women 15-64), 4.9 Total fertility rate (births per woman)AGO: 74.2% Female labour-force participation (% of women 15-64), 5.2 Total fertility rate (births per woman)ALB: 63.3% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)ARE: 54.4% Female labour-force participation (% of women 15-64), 1.1 Total fertility rate (births per woman)ARG: 61% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)ARM: 68.5% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)AUS: 76.7% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)AUT: 73.5% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)AZE: 68.6% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)BDI: 81.6% Female labour-force participation (% of women 15-64), 5 Total fertility rate (births per woman)BEL: 66.8% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)BEN: 75.6% Female labour-force participation (% of women 15-64), 4.6 Total fertility rate (births per woman)BFA: 42.6% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)Bangladesh: 46.9% Female labour-force participation (% of women 15-64), 2.2 Total fertility rate (births per woman)BangladeshBGR: 69.8% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)BHR: 44.9% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)BHS: 75.1% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)BIH: 50.7% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)BLR: 76.1% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)BLZ: 51.4% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)BOL: 73.8% Female labour-force participation (% of women 15-64), 2.6 Total fertility rate (births per woman)Brazil: 61.3% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)BRB: 73.2% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)BRN: 58.5% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)BTN: 55.2% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)BWA: 62.7% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)CAF: 66.4% Female labour-force participation (% of women 15-64), 6 Total fertility rate (births per woman)CAN: 76.8% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)CHE: 79.2% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CHI: 66.3% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CHL: 58.3% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)China: 69.5% Female labour-force participation (% of women 15-64), 1 Total fertility rate (births per woman)ChinaCIV: 60.3% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)CMR: 57.7% Female labour-force participation (% of women 15-64), 4.4 Total fertility rate (births per woman)COD: 63.2% Female labour-force participation (% of women 15-64), 6.1 Total fertility rate (births per woman)COG: 67.2% Female labour-force participation (% of women 15-64), 4.2 Total fertility rate (births per woman)COL: 56.3% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)COM: 43% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)CPV: 55.9% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)CRI: 57.5% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)CUB: 50.2% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CYP: 73.6% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CZE: 70.1% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)Germany: 75.4% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)DJI: 19.5% Female labour-force participation (% of women 15-64), 2.6 Total fertility rate (births per woman)DNK: 78% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)DOM: 55% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)DZA: 15.5% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)ECU: 56.6% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)Egypt: 16.4% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)ERI: 75.5% Female labour-force participation (% of women 15-64), 3.8 Total fertility rate (births per woman)Spain: 69.9% Female labour-force participation (% of women 15-64), 1.2 Total fertility rate (births per woman)EST: 79.5% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)Ethiopia: 59.2% Female labour-force participation (% of women 15-64), 4.1 Total fertility rate (births per woman)EthiopiaFIN: 78.9% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)FJI: 41.2% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)France: 70.6% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)GAB: 43.6% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)United Kingdom: 73.5% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)GEO: 61.1% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)GHA: 63.6% Female labour-force participation (% of women 15-64), 3.4 Total fertility rate (births per woman)GIN: 43.5% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)GMB: 46.4% Female labour-force participation (% of women 15-64), 4.1 Total fertility rate (births per woman)GNB: 56% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)GNQ: 55.1% Female labour-force participation (% of women 15-64), 4.2 Total fertility rate (births per woman)GRC: 61.6% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)GTM: 42.1% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)GUM: 65.3% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)GUY: 43.7% Female labour-force participation (% of women 15-64), 2.4 Total fertility rate (births per woman)HKG: 65.5% Female labour-force participation (% of women 15-64), 0.7 Total fertility rate (births per woman)HND: 50.4% Female labour-force participation (% of women 15-64), 2.5 Total fertility rate (births per woman)HRV: 65.7% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)HTI: 62.5% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)HUN: 72.4% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)Indonesia: 54.6% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)IndonesiaIndia: 31.6% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)IndiaIRL: 71.9% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)Iran: 14.9% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)IRQ: 11.6% Female labour-force participation (% of women 15-64), 3.3 Total fertility rate (births per woman)ISL: 84% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)ISR: 71.4% Female labour-force participation (% of women 15-64), 2.9 Total fertility rate (births per woman)Italy: 56.4% Female labour-force participation (% of women 15-64), 1.2 Total fertility rate (births per woman)JAM: 65.4% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)JOR: 14.9% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)Japan: 74.5% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)JapanKAZ: 76.8% Female labour-force participation (% of women 15-64), 3 Total fertility rate (births per woman)KEN: 63.1% Female labour-force participation (% of women 15-64), 3.3 Total fertility rate (births per woman)KGZ: 56.5% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)KHM: 78.6% Female labour-force participation (% of women 15-64), 2.6 Total fertility rate (births per woman)South Korea: 62.1% Female labour-force participation (% of women 15-64), 0.8 Total fertility rate (births per woman)South KoreaKWT: 52.1% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)LAO: 64.2% Female labour-force participation (% of women 15-64), 2.5 Total fertility rate (births per woman)LBN: 31.3% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)LBR: 73.4% Female labour-force participation (% of women 15-64), 4 Total fertility rate (births per woman)LBY: 36% Female labour-force participation (% of women 15-64), 2.4 Total fertility rate (births per woman)LCA: 69.9% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)Sri Lanka: 35.7% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)LSO: 51.5% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)LTU: 77.5% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)LUX: 70% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)LVA: 74.4% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)MAC: 72.5% Female labour-force participation (% of women 15-64), 0.7 Total fertility rate (births per woman)MAR: 21.2% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)MDA: 73.8% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)MDG: 84.1% Female labour-force participation (% of women 15-64), 4 Total fertility rate (births per woman)MDV: 42.6% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)Mexico: 50% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)MKD: 54.2% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)MLI: 60% Female labour-force participation (% of women 15-64), 5.7 Total fertility rate (births per woman)MLT: 72.7% Female labour-force participation (% of women 15-64), 1.1 Total fertility rate (births per woman)MMR: 45% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)MNE: 53.2% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)MNG: 57.9% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)MOZ: 78.6% Female labour-force participation (% of women 15-64), 4.8 Total fertility rate (births per woman)MRT: 27.2% Female labour-force participation (% of women 15-64), 4.8 Total fertility rate (births per woman)MUS: 50.7% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)MWI: 64.2% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)MYS: 56.1% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)NAM: 56.8% Female labour-force participation (% of women 15-64), 3.3 Total fertility rate (births per woman)NCL: 60.7% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)NER: 61.2% Female labour-force participation (% of women 15-64), 6.1 Total fertility rate (births per woman)Nigeria: 78.1% Female labour-force participation (% of women 15-64), 4.5 Total fertility rate (births per woman)NigeriaNIC: 52.4% Female labour-force participation (% of women 15-64), 2.2 Total fertility rate (births per woman)NLD: 81.1% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)NOR: 77.8% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)Nepal: 29.4% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)NZL: 78.7% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)OMN: 32.2% Female labour-force participation (% of women 15-64), 2.5 Total fertility rate (births per woman)Pakistan: 25.6% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)PAN: 57.3% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)PER: 71.1% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)Philippines: 52.4% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)PNG: 51.4% Female labour-force participation (% of women 15-64), 3.2 Total fertility rate (births per woman)POL: 67.6% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)PRI: 44.5% Female labour-force participation (% of women 15-64), 0.9 Total fertility rate (births per woman)PRK: 86.5% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)PRT: 74.3% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)PRY: 62.8% Female labour-force participation (% of women 15-64), 2.4 Total fertility rate (births per woman)PSE: 20.1% Female labour-force participation (% of women 15-64), 3.4 Total fertility rate (births per woman)PYF: 53.3% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)QAT: 65.2% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)ROU: 56.9% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)RUS: 71% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)RWA: 57.2% Female labour-force participation (% of women 15-64), 3.8 Total fertility rate (births per woman)SAU: 35.4% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)SDN: 14.6% Female labour-force participation (% of women 15-64), 4.4 Total fertility rate (births per woman)SEN: 38.2% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)SGP: 70.5% Female labour-force participation (% of women 15-64), 1 Total fertility rate (births per woman)SLB: 84.2% Female labour-force participation (% of women 15-64), 3.6 Total fertility rate (births per woman)SLE: 52.9% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)SLV: 50.1% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)SOM: 21.7% Female labour-force participation (% of women 15-64), 6.3 Total fertility rate (births per woman)SRB: 66.2% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)SSD: 72.9% Female labour-force participation (% of women 15-64), 4 Total fertility rate (births per woman)STP: 23.1% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)SUR: 49.9% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)SVK: 72.2% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)SVN: 73.4% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)SWE: 81.3% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)SWZ: 48% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)SYR: 14.4% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)TCD: 48.9% Female labour-force participation (% of women 15-64), 6.2 Total fertility rate (births per woman)TGO: 57.2% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)Thailand: 68.4% Female labour-force participation (% of women 15-64), 1.2 Total fertility rate (births per woman)TJK: 32.9% Female labour-force participation (% of women 15-64), 3.1 Total fertility rate (births per woman)TKM: 52.2% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)TLS: 61.2% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)TON: 44.9% Female labour-force participation (% of women 15-64), 3.2 Total fertility rate (births per woman)TTO: 58.4% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)TUN: 31.2% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)Turkey: 39.7% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)TZA: 81.8% Female labour-force participation (% of women 15-64), 4.7 Total fertility rate (births per woman)UGA: 77.8% Female labour-force participation (% of women 15-64), 4.4 Total fertility rate (births per woman)URY: 69.7% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)United States: 67.7% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)United StatesUZB: 43.6% Female labour-force participation (% of women 15-64), 3.4 Total fertility rate (births per woman)VCT: 63.4% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)VEN: 41.7% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)VIR: 63.5% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)Vietnam: 75.7% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)VietnamVUT: 55.8% Female labour-force participation (% of women 15-64), 3.6 Total fertility rate (births per woman)WSM: 33.8% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)YEM: 5.2% Female labour-force participation (% of women 15-64), 4.6 Total fertility rate (births per woman)ZAF: 55.4% Female labour-force participation (% of women 15-64), 2.2 Total fertility rate (births per woman)ZMB: 54.4% Female labour-force participation (% of women 15-64), 4.2 Total fertility rate (births per woman)ZWE: 60.9% Female labour-force participation (% of women 15-64), 3.8 Total fertility rate (births per woman)Female labour-force participation (% of women 15-64) ->Total fertility rate (births per woman)thisindianlife.today0%18%36%54%72%90%0.01.83.55.37.0AFG: 5.4% Female labour-force participation (% of women 15-64), 4.9 Total fertility rate (births per woman)AGO: 74.2% Female labour-force participation (% of women 15-64), 5.2 Total fertility rate (births per woman)ALB: 63.3% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)ARE: 54.4% Female labour-force participation (% of women 15-64), 1.1 Total fertility rate (births per woman)ARG: 61% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)ARM: 68.5% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)AUS: 76.7% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)AUT: 73.5% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)AZE: 68.6% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)BDI: 81.6% Female labour-force participation (% of women 15-64), 5 Total fertility rate (births per woman)BEL: 66.8% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)BEN: 75.6% Female labour-force participation (% of women 15-64), 4.6 Total fertility rate (births per woman)BFA: 42.6% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)Bangladesh: 46.9% Female labour-force participation (% of women 15-64), 2.2 Total fertility rate (births per woman)BangladeshBGR: 69.8% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)BHR: 44.9% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)BHS: 75.1% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)BIH: 50.7% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)BLR: 76.1% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)BLZ: 51.4% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)BOL: 73.8% Female labour-force participation (% of women 15-64), 2.6 Total fertility rate (births per woman)Brazil: 61.3% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)BRB: 73.2% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)BRN: 58.5% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)BTN: 55.2% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)BWA: 62.7% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)CAF: 66.4% Female labour-force participation (% of women 15-64), 6 Total fertility rate (births per woman)CAN: 76.8% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)CHE: 79.2% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CHI: 66.3% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CHL: 58.3% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)China: 69.5% Female labour-force participation (% of women 15-64), 1 Total fertility rate (births per woman)ChinaCIV: 60.3% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)CMR: 57.7% Female labour-force participation (% of women 15-64), 4.4 Total fertility rate (births per woman)COD: 63.2% Female labour-force participation (% of women 15-64), 6.1 Total fertility rate (births per woman)COG: 67.2% Female labour-force participation (% of women 15-64), 4.2 Total fertility rate (births per woman)COL: 56.3% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)COM: 43% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)CPV: 55.9% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)CRI: 57.5% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)CUB: 50.2% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CYP: 73.6% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)CZE: 70.1% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)Germany: 75.4% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)DJI: 19.5% Female labour-force participation (% of women 15-64), 2.6 Total fertility rate (births per woman)DNK: 78% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)DOM: 55% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)DZA: 15.5% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)ECU: 56.6% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)Egypt: 16.4% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)ERI: 75.5% Female labour-force participation (% of women 15-64), 3.8 Total fertility rate (births per woman)Spain: 69.9% Female labour-force participation (% of women 15-64), 1.2 Total fertility rate (births per woman)EST: 79.5% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)Ethiopia: 59.2% Female labour-force participation (% of women 15-64), 4.1 Total fertility rate (births per woman)EthiopiaFIN: 78.9% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)FJI: 41.2% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)France: 70.6% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)GAB: 43.6% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)United Kingdom: 73.5% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)GEO: 61.1% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)GHA: 63.6% Female labour-force participation (% of women 15-64), 3.4 Total fertility rate (births per woman)GIN: 43.5% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)GMB: 46.4% Female labour-force participation (% of women 15-64), 4.1 Total fertility rate (births per woman)GNB: 56% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)GNQ: 55.1% Female labour-force participation (% of women 15-64), 4.2 Total fertility rate (births per woman)GRC: 61.6% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)GTM: 42.1% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)GUM: 65.3% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)GUY: 43.7% Female labour-force participation (% of women 15-64), 2.4 Total fertility rate (births per woman)HKG: 65.5% Female labour-force participation (% of women 15-64), 0.7 Total fertility rate (births per woman)HND: 50.4% Female labour-force participation (% of women 15-64), 2.5 Total fertility rate (births per woman)HRV: 65.7% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)HTI: 62.5% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)HUN: 72.4% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)Indonesia: 54.6% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)IndonesiaIndia: 31.6% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)IndiaIRL: 71.9% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)Iran: 14.9% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)IRQ: 11.6% Female labour-force participation (% of women 15-64), 3.3 Total fertility rate (births per woman)ISL: 84% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)ISR: 71.4% Female labour-force participation (% of women 15-64), 2.9 Total fertility rate (births per woman)Italy: 56.4% Female labour-force participation (% of women 15-64), 1.2 Total fertility rate (births per woman)JAM: 65.4% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)JOR: 14.9% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)Japan: 74.5% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)JapanKAZ: 76.8% Female labour-force participation (% of women 15-64), 3 Total fertility rate (births per woman)KEN: 63.1% Female labour-force participation (% of women 15-64), 3.3 Total fertility rate (births per woman)KGZ: 56.5% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)KHM: 78.6% Female labour-force participation (% of women 15-64), 2.6 Total fertility rate (births per woman)South Korea: 62.1% Female labour-force participation (% of women 15-64), 0.8 Total fertility rate (births per woman)South KoreaKWT: 52.1% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)LAO: 64.2% Female labour-force participation (% of women 15-64), 2.5 Total fertility rate (births per woman)LBN: 31.3% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)LBR: 73.4% Female labour-force participation (% of women 15-64), 4 Total fertility rate (births per woman)LBY: 36% Female labour-force participation (% of women 15-64), 2.4 Total fertility rate (births per woman)LCA: 69.9% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)Sri Lanka: 35.7% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)LSO: 51.5% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)LTU: 77.5% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)LUX: 70% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)LVA: 74.4% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)MAC: 72.5% Female labour-force participation (% of women 15-64), 0.7 Total fertility rate (births per woman)MAR: 21.2% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)MDA: 73.8% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)MDG: 84.1% Female labour-force participation (% of women 15-64), 4 Total fertility rate (births per woman)MDV: 42.6% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)Mexico: 50% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)MKD: 54.2% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)MLI: 60% Female labour-force participation (% of women 15-64), 5.7 Total fertility rate (births per woman)MLT: 72.7% Female labour-force participation (% of women 15-64), 1.1 Total fertility rate (births per woman)MMR: 45% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)MNE: 53.2% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)MNG: 57.9% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)MOZ: 78.6% Female labour-force participation (% of women 15-64), 4.8 Total fertility rate (births per woman)MRT: 27.2% Female labour-force participation (% of women 15-64), 4.8 Total fertility rate (births per woman)MUS: 50.7% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)MWI: 64.2% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)MYS: 56.1% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)NAM: 56.8% Female labour-force participation (% of women 15-64), 3.3 Total fertility rate (births per woman)NCL: 60.7% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)NER: 61.2% Female labour-force participation (% of women 15-64), 6.1 Total fertility rate (births per woman)Nigeria: 78.1% Female labour-force participation (% of women 15-64), 4.5 Total fertility rate (births per woman)NigeriaNIC: 52.4% Female labour-force participation (% of women 15-64), 2.2 Total fertility rate (births per woman)NLD: 81.1% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)NOR: 77.8% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)Nepal: 29.4% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)NZL: 78.7% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)OMN: 32.2% Female labour-force participation (% of women 15-64), 2.5 Total fertility rate (births per woman)Pakistan: 25.6% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)PAN: 57.3% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)PER: 71.1% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)Philippines: 52.4% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)PNG: 51.4% Female labour-force participation (% of women 15-64), 3.2 Total fertility rate (births per woman)POL: 67.6% Female labour-force participation (% of women 15-64), 1.3 Total fertility rate (births per woman)PRI: 44.5% Female labour-force participation (% of women 15-64), 0.9 Total fertility rate (births per woman)PRK: 86.5% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)PRT: 74.3% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)PRY: 62.8% Female labour-force participation (% of women 15-64), 2.4 Total fertility rate (births per woman)PSE: 20.1% Female labour-force participation (% of women 15-64), 3.4 Total fertility rate (births per woman)PYF: 53.3% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)QAT: 65.2% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)ROU: 56.9% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)RUS: 71% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)RWA: 57.2% Female labour-force participation (% of women 15-64), 3.8 Total fertility rate (births per woman)SAU: 35.4% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)SDN: 14.6% Female labour-force participation (% of women 15-64), 4.4 Total fertility rate (births per woman)SEN: 38.2% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)SGP: 70.5% Female labour-force participation (% of women 15-64), 1 Total fertility rate (births per woman)SLB: 84.2% Female labour-force participation (% of women 15-64), 3.6 Total fertility rate (births per woman)SLE: 52.9% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)SLV: 50.1% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)SOM: 21.7% Female labour-force participation (% of women 15-64), 6.3 Total fertility rate (births per woman)SRB: 66.2% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)SSD: 72.9% Female labour-force participation (% of women 15-64), 4 Total fertility rate (births per woman)STP: 23.1% Female labour-force participation (% of women 15-64), 3.7 Total fertility rate (births per woman)SUR: 49.9% Female labour-force participation (% of women 15-64), 2.3 Total fertility rate (births per woman)SVK: 72.2% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)SVN: 73.4% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)SWE: 81.3% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)SWZ: 48% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)SYR: 14.4% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)TCD: 48.9% Female labour-force participation (% of women 15-64), 6.2 Total fertility rate (births per woman)TGO: 57.2% Female labour-force participation (% of women 15-64), 4.3 Total fertility rate (births per woman)Thailand: 68.4% Female labour-force participation (% of women 15-64), 1.2 Total fertility rate (births per woman)TJK: 32.9% Female labour-force participation (% of women 15-64), 3.1 Total fertility rate (births per woman)TKM: 52.2% Female labour-force participation (% of women 15-64), 2.7 Total fertility rate (births per woman)TLS: 61.2% Female labour-force participation (% of women 15-64), 2.8 Total fertility rate (births per woman)TON: 44.9% Female labour-force participation (% of women 15-64), 3.2 Total fertility rate (births per woman)TTO: 58.4% Female labour-force participation (% of women 15-64), 1.5 Total fertility rate (births per woman)TUN: 31.2% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)Turkey: 39.7% Female labour-force participation (% of women 15-64), 1.6 Total fertility rate (births per woman)TZA: 81.8% Female labour-force participation (% of women 15-64), 4.7 Total fertility rate (births per woman)UGA: 77.8% Female labour-force participation (% of women 15-64), 4.4 Total fertility rate (births per woman)URY: 69.7% Female labour-force participation (% of women 15-64), 1.4 Total fertility rate (births per woman)United States: 67.7% Female labour-force participation (% of women 15-64), 1.7 Total fertility rate (births per woman)United StatesUZB: 43.6% Female labour-force participation (% of women 15-64), 3.4 Total fertility rate (births per woman)VCT: 63.4% Female labour-force participation (% of women 15-64), 1.8 Total fertility rate (births per woman)VEN: 41.7% Female labour-force participation (% of women 15-64), 2.1 Total fertility rate (births per woman)VIR: 63.5% Female labour-force participation (% of women 15-64), 2 Total fertility rate (births per woman)Vietnam: 75.7% Female labour-force participation (% of women 15-64), 1.9 Total fertility rate (births per woman)VietnamVUT: 55.8% Female labour-force participation (% of women 15-64), 3.6 Total fertility rate (births per woman)WSM: 33.8% Female labour-force participation (% of women 15-64), 3.9 Total fertility rate (births per woman)YEM: 5.2% Female labour-force participation (% of women 15-64), 4.6 Total fertility rate (births per woman)ZAF: 55.4% Female labour-force participation (% of women 15-64), 2.2 Total fertility rate (births per woman)ZMB: 54.4% Female labour-force participation (% of women 15-64), 4.2 Total fertility rate (births per woman)ZWE: 60.9% Female labour-force participation (% of women 15-64), 3.8 Total fertility rate (births per woman)Female labour-force participation (% of women 15-64)Total fertility rate (births per woman)thisindianlife.today
IndiaSelected comparatorsOther countries

India reached a fertility rate of about 2.0 even though barely one in three women are in the labour force, breaking the usual pattern seen in Vietnam or China.

The chart plots TFR against female labor force participation for select countries. India sits low on the right (low participation) with TFR around 2.0, while Vietnam, with nearly identical TFR, has over double the participation. China, with even lower fertility, has high participation too. The US and Bangladesh also follow the inverse trend. India is an outlier, showing that fertility decline can happen through other pathways like rising education and contraceptive use, even when formal work for women remains rare.

How to readThe vertical axis is TFR; the horizontal axis is women's labour-force participation rate. Each dot is a country; locate India's dot and compare it to others with similar fertility.

Watch outDon't conclude that keeping women out of work lowers fertility; the chart shows association, not causation, and many other factors are at play.

What will India's fertility map look like in a decade?

Official projections for 2031-35 paint a future where almost the entire Indian subcontinent converges to a fertility rate of about 1.5. That is well below the replacement level of 2.1. The map becomes nearly uniform, with only Bihar holding out at a projected 2.4. Madhya Pradesh is expected to be around 2.0, while Uttar Pradesh, Rajasthan, and Jharkhand come in at about 1.9. These projections, from the National Commission on Population, are based on trends up to 2019 and must be read as scenarios, not certainties. In fact, several states are already falling faster than projected, suggesting the reality could be even lower. The post-transition era, where most women have two or fewer children, is approaching rapidly. ## Which states have the highest and lowest fertility?

The NFHS-6 data for 2023-24 ranks states. The highest TFR is in Bihar at 2.7 children per woman. The next four highest are Meghalaya (2.2), Jharkhand (2.2), Uttar Pradesh (2.2), and Rajasthan (2.1). All are above replacement. At the other end, the lowest is Andaman and Nicobar Islands at 0.9, an extremely low rate. Next are Sikkim (1.0), Arunachal Pradesh (1.5), Delhi (1.6), and Punjab (1.6). These are far below replacement. So the range is wide: from 0.9 to 2.7. A handful of states with large populations like Uttar Pradesh and Bihar pull the national average up; many others are already deeply below replacement. The table of top five and bottom five makes the contrast stark.

Chart 12

The same map, projected to 2031-35

ncp · by state

births per woman
2.1 replacement
1.52.4births per womannot surveyed
HighestBihar2.4Madhya Pradesh2.0Jharkhand1.9

States shown in grey (Ladakh, Sikkim, Mizoram, Manipur, Nagaland, Tripura, Arunachal Pradesh, Goa, Meghalaya, Dadra and Nagar Haveli and Daman and Diu, Chandigarh, Andaman and Nicobar Islands) were not covered by the survey sample, so no estimate exists for them. They are left uncoloured rather than counted as zero.

By 2031-35, only Bihar is projected to remain clearly above replacement level, with a fertility of about 2.4, while the rest of India settles near 1.5.

The map shades states by projected TFR for 2031-35 from the National Commission on Population. Darker shades indicate higher fertility. Almost the entire map is light, with most states at 1.5. Bihar stands out at 2.4, still above the 2.1 replacement line. Madhya Pradesh, Uttar Pradesh, Rajasthan, and Jharkhand hover around 1.9-2.0, but may fall further if current trends continue. These are medium-variant projections, not predictions, and recent SRS data suggests the decline is accelerating beyond the 2019 assumptions.

How to readLighter shades on the map represent lower projected fertility. Focus on the color gradient: almost everywhere is pale, except for a darker Bihar.

Watch outDon't treat these as forecasts; they are demographic scenarios based on past trends, and actual fertility could fall even lower.

How fast is fertility falling across India's states?

The last decade has seen a breathtaking fall in fertility across India's major states. In about ten years, Bihar dropped from roughly 3.4 to 2.8, Uttar Pradesh from 3.3 to 2.6, Madhya Pradesh to 2.4, and Rajasthan to 2.3. Even the already low-fertility southern states kept declining: Tamil Nadu tightened from 1.7 to 1.3, and Kerala slid from 1.8 to 1.5. By 2023, only five states (Bihar, Uttar Pradesh, Madhya Pradesh, Rajasthan and Chhattisgarh) remained above the replacement line of 2.1. The speed matters as much as the levels. Every state is moving in one direction, and the gaps are closing fast. The question is not if the high-fertility states will cross the line, but when. ## At what age do Indian women typically have children?

The age pattern of childbearing in India is compressed. The SRS age-specific fertility rates for 2024 show that births peak sharply in the 25-29 age group, at 134.7 births per 1,000 women. The 30-34 group follows at 78.3, and 20-24 at 105.5. Very few births occur to teenagers (10.9 per 1,000) or to women over 40 (11 per 1,000). The shape of the bars is like a bell, skewed right. This means the average Indian woman now has most of her children in a relatively short window in her twenties and early thirties. The concentration reduces total fertility because each year of delay lowers lifetime births. The chart shows that by age 35-39, rates drop to 33; after 40, to 11. So childbearing is almost complete by age 35.

Chart 13

Every state is falling, fast

SRS · total fertility rate · about 2013 vs 2023

births per woman
State~2013 avg2023Change
Bihar
3.3
2.9
-0.4
Uttar Pradesh
3.2
2.6
-0.6
Madhya Pradesh
2.8
2.5
-0.4
Rajasthan
2.8
2.4
-0.4
Chhattisgarh
2.6
2.3
-0.4
Jharkhand
2.8
2.2
-0.6
Assam
2.3
2.1
-0.3
Haryana
2.3
2
-0.3
Gujarat
2.3
1.9
-0.4
Uttarakhand
2
1.8
-0.3
Odisha
2.1
1.7
-0.4
Himachal Pradesh
1.7
1.6
-0.1
Andhra Pradesh
1.8
1.6
-0.3
Jammu & Kashmir
1.8
1.6
-0.2
Karnataka
1.9
1.6
-0.3
Telangana
1.8
1.6
-0.3
Kerala
1.9
1.5
-0.4
Punjab
1.7
1.5
-0.2
Maharashtra
1.8
1.5
-0.4
West Bengal
1.6
1.4
-0.3
Tamil Nadu
1.7
1.3
-0.4

In a decade, Uttar Pradesh's fertility plunged from about 3.3 to 2.6, while Tamil Nadu dropped to 1.3; only five states now remain above replacement level.

The chart shows paired bars for each state, comparing TFR around 2013 to 2023. The drop is universal. Bihar remains highest at 2.8, down from 3.4. Uttar Pradesh fell from 3.3 to 2.6. Even among the below-replacement states, declines continued: Kerala from 1.8 to 1.5, Tamil Nadu from 1.7 to 1.3. This rapid convergence reflects the spread of smaller families across the country, driven by rising contraception, education, and aspirations.

How to readEach state has two bars: the left bar (or darker shade) for about 2013, the right bar (lighter) for 2023. The gap shows how much fertility fell; note how even low-fertility states show a visible drop.

Watch outDon't focus only on the highest; the declines among already low-fertility states are equally significant because they push India's average even lower.

Are women having children later?

Yes, women in India are having children later than before. The UN median projection for shows a rise from 25.5 years in 2000 to 30.5 years by 2100. The line on the chart moves gradually upward. This reflects several changes: girls are staying in school longer, marrying later, and increasingly participating in the workforce. Even in the short term, delays in the age at first birth push down total fertility because the childbearing years are biologically limited. Later childbearing also often means fewer children overall, as couples stop earlier. The chart projects this trend out to 2100, assuming continued social change. If fertility remains constant, the mean age would stay lower, but UN projections anticipate that childbearing will shift later and later, as in all modernising societies.

Chart 14

Women are having children later

UN Population

years
30.5

2100 · latest point

2426283032200020202040206020802100thisindianlife.today24262830322000203520652100thisindianlife.today

Mean age at childbearing rose from 25.5 years in 2000 to a projected 30.5 years by 2100.

The UN projection shows a steady upward trend. This reflects later marriage, higher education, and career participation. Delaying childbirth reduces lifetime births because the window of fertility is finite. Even small shifts in mean age can lower TFR. The projection assumes continued social change; if fertility were constant, the mean age would stay lower. The chart uses the median scenario.

How to readSee the line rise from 25.48 to 30.49.

Watch outAssuming mean age rising means fewer children; it also compresses childbearing.

Why are Indian families shrinking? The answer lies in the last birth.

The story of India's shrinking families is not about women starting childbearing much later. The age at first birth has crept up only slightly, from about 19.4 to 21.2 over three decades. What has changed dramatically is when women stop. The age at last birth has tumbled from roughly 32.8 to 27.6. That is a compression of over five years in the childbearing window. As a result, women spend far less time in their reproductive lives actually having children. This earlier stop is driven by the widespread desire for small families, often two children, and the means to achieve it through contraception. The window is closing from the top, and that is what is driving India's fertility to new lows. ## How does India prevent pregnancy, and who bears that responsibility?

Contraception is the direct means by which fertility falls, and in India the method mix is heavily skewed toward female sterilisation. The NFHS-6 data shows that among married women aged 15-49, female sterilisation accounted for the largest share of modern method use, while male sterilisation was negligible. Female sterilisation is a permanent method, and it is often provided to women after they have had their desired number of children. This pattern places the burden of contraception almost entirely on women. Unmet need for family planning, women who want to stop or delay childbearing but are not using contraception, remains significant. The chart compares different methods: any method, any modern method, female sterilisation, male sterilisation, and unmet need. The bars show female sterilisation dominating, a feature of India's family planning programme for decades. This reflects both accessibility and cultural expectations about who manages fertility.

Chart 15

The childbearing window is closing from the top

NFHS rounds 1-5 · median age at marriage, first birth and last birth

age in years
18.8

First marriage · 2020 · latest point

01020304019952000200520102015202018.821.227.6thisindianlife.today010203040199220002010202018.821.227.6thisindianlife.today
First marriageFirst birthLast birth

The years a woman spends bearing children in India have shrunk by about five years, mostly because she stops at 27.6 instead of 32.8.

The chart shows median ages for first and last births from NFHS surveys spanning 1992 to 2020. Age at first birth rose gently from 19.4 to 21.2. Meanwhile, age at last birth fell sharply from 32.8 to 27.6. The period between these events narrowed from about 13.4 years to just 6.4 years. This trend reflects deliberate fertility control: women are marrying slightly later but, more importantly, are ceasing childbearing soon after reaching their desired family size, often by their late twenties. The rise in contraceptive use and the dominance of the two-child norm are the main forces.

How to readFollow the two lines: one for age at first birth (nearly flat, slight rise) and one for age at last birth (steep drop). The gap between them narrows dramatically.

Watch outDon't assume a later first birth was the main factor; the closing window is driven by the sharp decline in the age at last birth.

Are families getting smaller?

Yes, the composition of births by birth order confirms that families are shrinking. In 2024, according to SRS, 66.4% of all live births were first children. Another 22.7% were second children. Only 7.3% were third children, and a mere 3.5% were fourth or higher order. This means that nearly 90% of births are to mothers having their first or second child. The share of fourth-and-higher births has been steadily declining. Two decades ago, larger families were common; now they are rare. The chart of birth order percentages is a direct sign that below-replacement fertility has already reshaped the typical family. Most couples are stopping after one or two children, and the three or four child family is becoming unusual. This is consistent with the TFR of 1.9: the average woman stops after about two children.

Chart 16

Families are getting smaller

SRS 2024 · live births by birth order

% of live births
1st child
66.4%
2nd child
22.7%
3rd child
7.3%
4th or higher
3.5%

Two-thirds of births are first children; only 3.5% are fourth or higher.

SRS 2024 data on birth order shows 66.4% first, 22.7% second, 7.3% third, 3.5% fourth or higher. This distribution indicates that the norm is now a two-child family at most. The share of higher-order births has been declining for decades. This is the signature of below-replacement fertility: families are completing their desired size quickly and then stopping.

How to readMajority of births are first children (66.4%); fourth+ only 3.5%.

Watch outForgetting that this is share, not absolute numbers.

How common is child marriage and teenage motherhood?

Despite overall fertility decline, child marriage and teenage motherhood still occur. The NFHS-6 data reports the percentage of women aged 20-24 who were married before age 18, a widely used measure of child marriage. Also, the share of women aged 15-19 who are already mothers or pregnant. These figures are highest in poorer, more rural states. Over the last decade, both indicators have fallen, but they remain significant. Child marriage often leads to early childbearing, which can contribute to higher total fertility because these women spend more years at risk of pregnancy and may have less access to contraception. The chart presents these two figures side by side. While they do not dominate the national fertility picture, they indicate that at the margins, early marriage and early births persist, especially in certain regions.

Chart 17

Marrying and giving birth young

NFHS-6 (2023-24)

%
Married before 18 (women 20-24)
20.1%
Already mothers or pregnant (women 15-19)
6.7%

Child marriage and teenage motherhood persist, though rates have declined.

NFHS-6 reports two indicators: women 20-24 married before 18, and women 15-19 already mothers or pregnant. These are concentrated in poorer, rural states. They contribute to higher fertility at the margins because early marriage leads to longer exposure to pregnancy and often less access to contraception. The chart juxtaposes the two figures. Both have fallen over time but remain concerns, especially in certain regions.

How to readNote the percentages and compare with earlier rounds if known.

Watch outAssuming these figures are only about fertility; they reflect gender norms.

Does fertility depend on a woman's education?

Fertility falls sharply as a woman's schooling increases. NFHS-5 data (2019-21) shows that women with no schooling had a TFR of 2.82 children on average. For women with less than 5 years of schooling, it dropped to 2.3. With 5-7 years, 2.21; 8-9 years, 2.12; 10-11 years, 1.88; and for those with 12 or more years, only 1.78. The gradient is steep and consistent. Education delays marriage and first birth, increases knowledge and use of contraception, and often changes aspirations. It also gives women more agency within households. So schooling is one of the strongest predictors of lower fertility. The chart is a bar chart that makes the drop visible. Since more Indian girls are now completing secondary school, this trend alone will push national fertility further down over time.

Chart 18

Fertility falls with schooling

NFHS-5 (2019-21) · TFR by years of schooling

births per woman
No schooling
2.8
<5 years
2.3
5-7 years
2.2
8-9 years
2.1
10-11 years
1.9
12+ years
1.8

TFR drops from 2.82 for women with no schooling to 1.78 for those with 12+ years.

NFHS-5 data shows a steep gradient. Each additional level of schooling is associated with lower fertility. The mechanism includes later marriage, greater awareness and use of contraception, and changes in desired family size. Education is one of the strongest predictors of fertility decline. As more girls complete secondary education, national fertility is likely to fall further. The bars show a monotonic decrease.

How to readSee the steady drop from 2.82 to 1.78 as schooling increases.

Watch outThinking education is the sole cause; it correlates with many changes.

Does fertility fall as households get wealthier?

Yes, fertility declines with household wealth. NFHS-5 data divides households into five wealth quintiles. Women in the lowest wealth quintile had a TFR of 2.63. In the second quintile, 2.12; middle, 1.89; fourth, 1.74; and the highest quintile, just 1.57. That is more than a full child difference between the poorest and richest groups. Wealth influences fertility through several channels: richer households tend to invest more in each child's education, mothers may have more opportunities to work, and contraception is more accessible. But wealth and education overlap heavily; richer households also have more educated women. So the two factors together explain much of the fertility decline. The bar chart shows a clear, monotonic downward slope from left to right. This gradient is a signature of modern demographic transitions everywhere.

Chart 19

Fertility falls with wealth

NFHS-5 (2019-21) · TFR by wealth quintile

births per woman
Lowest
2.6
Second
2.1
Middle
1.9
Fourth
1.7
Highest
1.6

TFR goes from 2.63 in the poorest quintile to 1.57 in the richest.

NFHS-5 wealth quintile data shows a similar gradient to education. The richest households have about one child less than the poorest. Wealth and education are correlated; together they drive fertility decline. The chart illustrates that fertility is not only a health or choice matter but deeply linked to material conditions. As poverty declines, fertility tends to follow.

How to readLook at the gradient from lowest quintile (2.63) to highest (1.57).

Watch outAssuming wealth causes low fertility; both are part of development.

Does fertility vary by religion?

Fertility levels differ by religious group, and this is often misunderstood. NFHS-5 data shows that Muslim women had a TFR of 2.36, Hindu women 1.94, Christian 1.88, Sikh 1.61, Buddhist/Neo-Buddhist 1.39, and Jain 1.6. So Muslim fertility is the highest among these groups, but still well below replacement in some groups and far below historical levels. The important context is that all religious groups have experienced a steep decline in fertility over the past few decades, and the gap between Muslims and others has narrowed. For instance, in NFHS-3 (2005-06), the Muslim TFR was 3.1 and Hindu was 2.6; the gap was 0.5. By NFHS-5, the gap had shrunk to 0.4. Fertility is converging, not diverging. The differences today are primarily linked to socioeconomic factors like education and poverty, rather than religion per se. The chart simply presents the numbers; what matters is the trend toward convergence.

Chart 20

Fertility by religion

NFHS-5 (2019-21) · TFR by religion

births per woman
Hindu
1.9
Muslim
2.4
Christian
1.9
Sikh
1.6
Buddhist/Neo-Buddhist
1.4
Jain
1.6

Muslim TFR (2.36) is the highest; Hindu (1.94) is near the national average; Sikh, Buddhist, Jain are lower.

NFHS-5 data shows differences, but the key is convergence. All groups have seen steep declines. The Hindu TFR fell from 2.6 to 1.9 between NFHS-3 and NFHS-5; the Muslim TFR fell from 3.1 to 2.4 in the same period, so the gap narrowed from 0.5 to 0.4. Fertility differences are largely due to socioeconomic factors rather than religion. The chart presents the numbers without moralising; what matters is the direction of change.

How to readCompare groups, but note the convergence context.

Watch outInterpreting differences as permanent or driven by religion alone.

How many girls are born for every boy in India?

The in India is skewed toward boys. The SRS reports a ratio of 918 females per 1,000 males for the period 2022-24, a three-year moving average. This is below the natural ratio of around 950-970 girls per 1,000 boys, indicating that some girls are 'missing' due to son preference and sex-selective practices. The ratio has improved from 907 in 2018-20, but the distortion remains. The rural ratio is lower (914) than the urban ratio (928), meaning the imbalance is more severe in villages. The chart shows three lines: all-India, rural, urban. Over the past few years, the lines have moved upward slightly, but they are still far from natural levels. This matters because a skewed sex ratio can create social tensions and reflects deep-rooted gender preferences. The data does not tell us why directly, but the pattern is clear.

Chart 21

Boys per girl at birth: the son-preference signal

SRS · sex ratio at birth · 3-year averages

females per 1,000 males
918

All India · 2022-24 · latest point

9009109209302019202020212022918914928thisindianlife.today900910920930201920202023918914928thisindianlife.today
All IndiaRuralUrban

Sex ratio at birth is 918 females per 1,000 males, improved from 907 but still below natural.

SRS three-year averages show the national rate at 918 for 2022-24. Rural is lower (914) than urban (928). The natural rate is around 950-970, so there are still missing girls. The ratio has been improving slowly, possibly due to policy and changing norms. The chart shows three lines over recent periods. The gap between rural and urban suggests son preference is stronger in villages.

How to readCheck all-India line at 918, and note rural vs urban gap.

Watch outThinking 918 is close to natural ratio; it indicates missing girls.

What does India's population look like by age and sex?

India's age-sex structure in 2030, projected by the UN, is a classic pyramid with a wide base and a narrow top, but it is evolving. The pyramid shows both sexes separately. The largest age group is 0-4 years with about 11.1 crore children (both sexes). The pyramid is broad up to age 30, reflecting past high fertility. Above age 30, the numbers start declining, and after 60, they shrink sharply. Females outnumber males in older ages because women live longer. The shape indicates a young population overall, but the base is already narrower than it was in the past. In 2000, the under-5 group was larger relative to the total. The pyramid is a snapshot, but it is drawn from projections, so it shows what the population might look like in 2030, not a current census. It reveals the demographic momentum: the large cohorts of young adults will keep having children, but each new cohort is smaller than the one before, so the base will continue to narrow.

Chart 22

India's age pyramid today

UN median variant · 2025

2025
14,715
100+
23,273
1.3 lakh
95-99
1.9 lakh
6.3 lakh
90-94
9.4 lakh
19.4 lakh
85-89
27 lakh
42.7 lakh
80-84
53.4 lakh
83.7 lakh
75-79
96.1 lakh
1.5 crore
70-74
1.6 crore
2.1 crore
65-69
2.2 crore
2.7 crore
60-64
2.7 crore
3.3 crore
55-59
3.2 crore
3.9 crore
50-54
3.8 crore
4.5 crore
45-49
4.3 crore
5.3 crore
40-44
4.9 crore
5.9 crore
35-39
5.4 crore
6.2 crore
30-34
5.7 crore
6.6 crore
25-29
6 crore
6.8 crore
20-24
6.2 crore
6.6 crore
15-19
6 crore
6.4 crore
10-14
5.9 crore
6.1 crore
5-9
5.6 crore
5.9 crore
0-4
5.5 crore
MaleFemale

The pyramid shows a wide base of young people and a narrow top of elderly, but the base is shrinking.

The UN projection for 2030 shows the age structure. The largest 5-year group is 0-4 (11.1 crore). The pyramid is broad up to age 30, then narrows. Males slightly outnumber females in younger ages, but females outnumber males in older ages. Compared to 2000, the base has narrowed while the middle has thickened. This shape indicates the momentum: many potential parents in the next two decades will keep births high, but each new cohort will be smaller.

How to readLook at the wide base (youth) and the narrow top (elderly).

Watch outForgetting this is a snapshot; the pyramid shape evolves.

How is the mix of children, working-age adults, and elderly changing?

The shares of three broad age groups have shifted dramatically. In 1960, children (0-14) made up 40.6% of the population; by 2024, that share fell to 24.6%. Meanwhile, the working-age population (15-64) rose from 56.1% to 68.2%, giving India a potential demographic dividend. The elderly share (65+) rose from 3.3% to 7.1%. The chart with three lines crossing over time shows these transitions. The children's share has been declining steadily; the working-age share is now near its peak and may soon start to fall as fertility continues to drop and the large cohorts age. The elderly share will only increase. This shifting composition means that while India still has a large workforce, the dependency burden, especially of the old, will rise in the coming decades. The chart makes visible the window of opportunity before ageing accelerates.

Chart 23

The age mix is shifting

World Bank · share of population · 1960 to today

% of population
24.6%

Children (0-14) · 2024 · latest point

020406080%196019701980199020002010202024.6%68.2%7.1%thisindianlife.today%020406080196019802005202424.6%68.2%7.1%thisindianlife.today
Children (0-14)Working age (15-64)Older (65+)

Children share fell from 40.6% to 24.6%; working-age rose from 56.1% to 68.2%; elderly rose from 3.3% to 7.1%.

Three lines on one chart show the composition from 1960 to 2024. The children' share has been declining steadily; the working-age share is near its peak and will eventually fall; the elderly share is rising. This is the classic demographic transition. The current high working-age share is the so-called demographic dividend, but it will last only a few more decades before the elderly share swells.

How to readWatch the children share fall, working-age rise, then plateau, and elderly rise.

Watch outThinking working-age share will stay high; it will eventually decline.

How old is the typical Indian, and where is that heading?

The , the age that splits the population in half, was just 21.2 years in 2000. The UN's median projection shows it rising to 47.8 years by 2100. That is a doubling. Today, India is a young country: half its people are under about 28. But within a few decades, the median will cross 30, then 40. The line on the chart moves upward, more steeply after 2040. Other scenarios vary: the high-fertility scenario keeps the median lower (39.4 by 2100), while low-fertility pushes it to 57.7. The median age is a quick summary of population ageing. Like the , it is locked in by fertility. Once fertility is below replacement, the median age will inevitably rise. The chart shows that even in the most optimistic scenario for fertility, India will age substantially.

Chart 24

Median age, to 2100

UN Population

years
47.8

2100 · latest point

01020304050200020202040206020802100thisindianlife.today010203040502000203520652100thisindianlife.today

Median age will double from 21.2 in 2000 to 47.8 in 2100 (UN median).

The line rises slowly at first, then steepens. Other UN scenarios show a range: high-fertility leads to 39.4, low-fertility to 57.7 by 2100. The median age is a succinct ageing measure. Even in the high-fertility scenario, India ages considerably. The rise is baked in by past fertility declines; it cannot be reversed quickly. The chart extends to 2100, showing the long-term trajectory.

How to readSee the projection from today’s young age to near 48 by 2100.

Watch outConfusing median with life expectancy.

How many older Indians will each working-age person support?

The old-age dependency ratio, the number of people aged 65 and older per 100 people of working age (15-64), was 7.35 in 2000 (UN median, 65+/15-64). By 2030, it is projected to be 12.4, and it will continue to rise to much higher levels later in the century. The chart shows the trajectory. In 2000, for every 100 working-age Indians, there were about 7 elderly. By mid-century, that could be 15 or 20, and by 2100, far higher. This ratio matters because it gives a rough indicator of economic support: more elderly relative to workers can mean greater strain on pensions, healthcare, and family resources. There are different measures; some narrower ones (like 65+/20-64) yield slightly different numbers. The chart uses the most common measure. The upward curve is relentless, driven by falling fertility and rising life expectancy.

Chart 25

Old-age dependency ratio

UN median variant · per 100 working-age adults

ratio
12.4

2030 · latest point

681012142000201020202030thisindianlife.today681012142000201020202030thisindianlife.today

The ratio rises from 7.35 per 100 in 2000 to 12.4 in 2030 and higher thereafter.

Using the 65+/15-64 measure, the UN shows a slow rise initially, then a steep climb after 2030. The ratio indicates how many elderly each 100 working-age persons support. In 2000 it was 7.35; by 2030 it will be 12.4, and by later in the century it will be much higher. The upward trend is relentless due to falling fertility and rising life expectancy. This will strain support systems, especially because India's income per person is still low.

How to readLook at the upward trend beyond 2030.

Watch outAssuming all working-age adults are employed.

How long are Indians living today?

in India has almost doubled since 1960, from 45.6 years to 72.2 years in 2024, according to World Bank data. This is a remarkable improvement driven by better healthcare, sanitation, nutrition, and living standards. The line on the chart shows a steady upward trajectory. Each additional year of life expectancy adds more people to the older age categories. Combined with falling fertility, longer lives accelerate population ageing. Women tend to live longer than men, so the elderly population is disproportionately female. The chart is a simple line, but behind it are millions of stories of reduced infant mortality and controlled infectious diseases. Life expectancy at birth is a summary measure; it does not guarantee any individual will live that long, but it reflects the overall health environment of the country.

Chart 26

Indians are living longer

World Bank · SP.DYN.LE00.IN

years
72.2

2024 · latest point

40506070801960198020002020thisindianlife.today40506070801960198020052024thisindianlife.today

Life expectancy doubled from 45.6 in 1960 to 72.2 in 2024.

The World Bank line shows steady improvement. This is a result of better healthcare, sanitation, nutrition, and living standards. Longer life expectancy adds to population ageing: more people survive to old age. The gains have been particularly rapid since the 1970s. The chart highlights the longevity engine alongside falling fertility.

How to readSee the rise from 45.61 to 72.24 years.

Watch outConfusing life expectancy with median age.

What share of Indians are now elderly, and what does that mean?

The share of the population aged 65 and over was 3.3% in 1960; by 2024, it reached 7.1%. That is still relatively low compared to rich countries, but the growth is accelerating. The chart shows the share rising, and in projections it will climb steeply after 2030. This is the "ageing" signal. India is still in the early stages of population ageing, but the direction is clear. As fertility remains below replacement, fewer children are born and the proportion of elderly grows. The rapidity of this change is what makes the "old before rich" concern acute: India is ageing at a much lower income level than Western Europe or East Asia. The elderly share alone does not fully capture the pressure; the old-age dependency ratio is more directly about support. But the share is the most intuitive indicator: in 1960, only 1 in 30 Indians was elderly; today it is about 1 in 14, and it will become 1 in 6 by mid-century.

Chart 27

Share of Indians aged 65 and over

World Bank · SP.POP.65UP.TO.ZS

% of population
7.1%

2024 · latest point

02468%1960198020002020thisindianlife.today%024681960198020052024thisindianlife.today

The elderly share rose from 3.3% in 1960 to 7.1% in 2024.

The line climbs slowly at first, then accelerates. This is the most direct ageing indicator. While 7% may seem small, it will double in the coming decades. The rapid rise after 2030 reflects the ageing of large cohorts born during high fertility, coupled with longer life expectancy. The chart visualises the growing proportion of older citizens.

How to readNote the current 7.1% and the steep projected rise.

Watch outThinking 7% is small; it doubles quickly in demographic transitions.

How wealthy is India as it grows older?

India's , a measure of average economic output per person, was only $85 in 1960. By 2024, it had risen to $2,695. That is a thirty-fold increase, but in current US dollars, it is still low. The chart shows a rising line, but the level is far below the thresholds at which rich countries faced ageing. When Japan and Western European nations aged, their incomes were $20,000 to $40,000 or more per person. India is greying at a fraction of that affluence. This means there is less fiscal capacity for universal pensions, social security, and elder care. The burden will fall heavily on families, especially women. GDP per capita is an average; inequality means many Indians earn far less. The chart is a line on a linear scale, but the message is about a profound misalignment: the population is ageing faster than the economy is prospering.

Chart 28

Income per person as India ages

World Bank · NY.GDP.PCAP.CD

current US$ per person
$2,695

2024 · latest point

$0$1,000$2,000$3,0001960197019801990200020102020thisindianlife.today$0$1,000$2,000$3,0001960198020052024thisindianlife.today

GDP per capita was $85 in 1960 and $2,695 in 2024, far below rich-country levels when they aged.

The line shows strong growth, but the level remains low in international terms. This is the 'old before rich' context. While India's economy has grown, the elderly share is rising while the average income is still a fraction of that in advanced economies. This creates challenges for funding pensions and healthcare. The chart highlights the gap between economic development and demographic change.

How to readSee GDP per capita at $2,695 today, but remember context.

Watch outUsing GDP per capita as typical income; it's an average.

When will India's population peak and start declining?

According to the UN's median projection, India's population will peak around 2061 at about 1.70 billion people. It will then plateau for a few years before beginning a slow decline. By 2100, it is projected to be about 1.51 billion, close to where it is today. So the total increase from now until the peak is about 250 million, roughly the population of Brazil. The line on the chart rises, crests, and then gently slopes downward. This peak is not a sudden stop; it is a gradual levelling off and turning. The exact year and magnitude depend on future fertility. But the direction is robust: the population will eventually stop growing because fertility is already below replacement and life expectancies are increasing only slowly. This projection is central to planning for everything from schools to pensions. The chart extends from 2000 to 2100, so you can see the long rise and the expected decline.

Chart 29

India's population to 2100: the peak

UN Population · WPP 2024, indicator 49 (total population), Median variant

people
150.5 crore

2100 · latest point

100120140160180 crore200020202040206020802100thisindianlife.todaycrore1001201401601802000203520652100thisindianlife.today

UN median projection shows a peak around 2061 at 1.70 billion, then decline to 1.51 billion by 2100.

The line rises from current levels, crests, and gently slopes down. The peak is not sharp but a gradual plateau. The projection reflects continued low fertility and moderate life expectancy gains. The decline after the peak will be slow. The chart is the most-cited future path for India's population.

How to readLook for the peak around 2061, then gradual decline.

Watch outAssuming the peak is guaranteed; it depends on fertility assumptions.

How high could India's population go? Different UN scenarios to 2100.

The UN produces many projection scenarios to show how sensitive the future is to fertility. The median scenario gives the peak at 1.70 billion. But the high-fertility scenario, where fertility stays just slightly above replacement for longer, results in a population of 2.20 billion by 2100 and still growing. The low-fertility scenario, where fertility drops faster and stays lower, yields a much smaller population of 991 million, with a steep decline after mid-century. The chart shows a fan of lines spreading out after 2050. The differences are huge. The low-fertility line is almost half the high-fertility line by 2100. This spread shows that the future is not predetermined. Policies on family planning, female education, and child health will shape which path India follows. But all scenarios agree that growth will slow and eventually reverse, because even the high scenario assumes fertility will eventually decline.

Chart 30

How high, how soon? Scenarios to 2100

Total population by sex · UN variants

people
Low
150.4 crore
Median
152.5 crore
High
154.7 crore
Constant
152.9 crore

High-fertility scenario leads to 2.20 billion; low-fertility to only 991 million by 2100.

The fan of lines from the UN shows outcomes based on different fertility assumptions. The high scenario assumes fertility stays just above replacement for longer, resulting in continuous growth. The low scenario assumes rapid decline to very low fertility, causing a steep fall. The median lies between them. This spread illustrates that the future population size is not fixed; it depends on policy and social change.

How to readSee the fan of lines; low fertility leads to much smaller population.

Watch outTreating any single scenario as the true future.

How does the IHME model compare to the UN projection?

The Institute for Health Metrics and Evaluation (IHME) published a different model in 2020 that projects an earlier and lower peak for India's population. IHME's reference scenario sees fertility falling faster than the UN assumes, leading to a peak around 2048 at about 1.61 billion, and then a sharp decline to about 1.09 billion by 2100. The UN's median peak is around 2061 at 1.70 billion. So the two most-cited models disagree by about a decade in timing and about 600 million people by 2100. The chart puts both lines on the same axes. The IHME projection is more pessimistic about future fertility, it assumes that as female education and contraception increase, fertility will drop quickly, following the path of many East Asian countries. The UN is more conservative, assuming a slower decline. Both are informed extrapolations, not facts. The truth likely lies somewhere in between, but the divergence is a reminder that population projections are uncertain.

Chart 31

The models disagree on the peak

UN WPP 2024 vs IHME (Vollset 2020)

people
150.5 crore

UN (median) · 2100 · latest point

100120140160180 crore200020202040206020802100150.5 crore109.3 crorethisindianlife.todaycrore1001201401601802000203520652100150.5109.3thisindianlife.today
UN (median)IHME (reference)

UN projects peak around 2061 at 1.70 billion; IHME projects earlier peak around 2048 at 1.61 billion and steeper decline.

The two lines start close but diverge after 2020. IHME assumes faster fertility decline, more like East Asia, leading to an earlier and lower peak. The UN is more conservative. By 2100, UN projects 1.51 billion, while IHME projects 1.09 billion. Both agree a peak is coming, but they differ on its height and timing. This disagreement is a reminder that projections are not facts.

How to readNote UN median vs IHME reference; IHME peaks earlier and lower.

Watch outThinking models are facts; they are informed guesses.

More from the data

Fertility by state

NFHS · by state

births per woman
2.1 replacement
0.92.7births per womannot surveyed
HighestBihar2.7Meghalaya2.2Jharkhand2.2
LowestAndaman and Nicobar Islands0.9Sikkim1.0Arunachal Pradesh1.5

States shown in grey (Manipur) were not covered by the survey sample, so no estimate exists for them. They are left uncoloured rather than counted as zero.

The map shows a north-south gradient: higher fertility in Bihar, UP, and central states; lower in south and west.

NFHS-6 data colours states by TFR. Darker shades are above 2.1; lighter are well below. The pattern is stark and historically persistent. The map highlights that the national average conceals wide variation. States like Kerala and Tamil Nadu have had below-replacement fertility for decades. Meanwhile, Bihar at 2.7 is still above replacement. Migration and socioeconomic differences contribute to this divide.

How to readLook at the colour gradient; darkest in north-central India.

Watch outAssuming uniform progress across all states.

Highest and lowest fertility states

NFHS-6 (2023-24) · top 5 and bottom 5 of 33 surveyed states/UTs

births per woman

Highest

Bihar
2.7
Meghalaya
2.2
Jharkhand
2.2
Uttar Pradesh
2.2
Rajasthan
2.1

Lowest

Andaman and Nicobar Islands
0.9
Sikkim
1
Arunachal Pradesh
1.5
Delhi
1.6
Punjab
1.6

Bihar has the highest TFR (2.7); Andaman and Nicobar Islands the lowest (0.9).

The horizontal bars rank top five and bottom five from NFHS-6. The top five are all above replacement: Bihar (2.7), Meghalaya (2.2), Jharkhand (2.2), Uttar Pradesh (2.2), Rajasthan (2.1). The bottom five are far below: Andaman and Nicobar Islands (0.9), Sikkim (1.0), Arunachal Pradesh (1.5), Delhi (1.6), Punjab (1.6). The range is nearly threefold. Large-population states like UP and Bihar pull the national average up.

How to readScan the top and bottom five values.

Watch outIgnoring population weights; small states can have extreme values.

At what age Indian women have children

SRS 2024 · age-specific fertility rate

births per 1,000 women
15-19
10.9
20-24
106
25-29
135
30-34
78.3
35-39
33
40-44
11
45-49
3.5

Childbearing peaks at ages 25-29 with a rate of 134.7 births per 1,000 women.

The SRS age-specific fertility rates for 2024 show a sharp peak in the late twenties. Rates are low at 15-19 (10.9), rise to 105.5 at 20-24, peak at 134.7 at 25-29, then decline to 78.3 at 30-34, 33 at 35-39, 11 at 40-44, and 3.5 at 45-49. The shape is compressed: most childbearing is concentrated in a 10-15 year window. This pattern reflects later marriage and effective family planning after desired family size is reached.

How to readSpot the peak at 25-29 (134.7) and the steep drop after 34.

Watch outThinking teen births are common; they are low per 1,000.

How India avoids pregnancy, and who carries it

NFHS-6 (2023-24)

% of married women 15-49
Any method
69.1%
Any modern method
52.7%
Female sterilisation
36.5%
Male sterilisation
0.5%
Unmet need
8.5%

Female sterilisation dominates contraceptive use; male sterilisation is negligible.

NFHS-6 data for currently married women 15-49 shows the method mix. A majority of modern method users rely on female sterilisation, a permanent method. Male sterilisation is extremely low, placing the burden almost entirely on women. Unmet need for family planning remains significant. This pattern has been a feature of India’s family planning programme for decades. The bars illustrate a gendered distribution of contraceptive responsibility.

How to readCompare female sterilisation bar to male sterilisation.

Watch outThinking all contraception is modern; permanent methods dominate.

Plain English concepts

Total fertility rate (TFR)

The average number of children a woman would have over her lifetime if she experienced current birth rates at each age. It is a snapshot of fertility in a given year, not how many children any real woman has.

TFR is the key number driving India's population future; below 2.1 means eventually, the population will stop growing without migration.

Replacement level

About 2.1 children per woman, the level at which each generation exactly replaces itself in the long run, accounting for some children not surviving. Below 2.1, each generation is smaller than the last.

India's TFR at 1.9 (SRS 2024) means it has fallen below replacement, signalling eventual population decline, though momentum delays it.

Demographic momentum

The tendency for a population to keep growing for decades even after fertility drops, because many young people are still entering childbearing age. Like a heavy train that keeps rolling after the engine is cut.

India's growth today is mainly momentum from earlier high fertility, not current birth rates.

Median age

The age that divides the population into two equal halves: half are younger, half are older. It is a measure of how old a population is overall.

India's median age is rising from 21 to nearly 48 by 2100 (UN median), showing rapid ageing.

Old-age dependency ratio

The number of people aged 65 and older per 100 people of working age (15-64). It gives a rough sense of the economic burden of supporting the elderly.

As India ages, this ratio will rise sharply, putting pressure on families and social systems.

GDP per capita

Total economic output (goods and services) of a country divided by its population, in current US dollars. It's an average, so it doesn't reflect how much a typical person earns.

India is ageing with a GDP per capita around $2,700, far lower than rich countries when they aged, raising the 'old before rich' concern.

Crude birth rate

The number of live births in a year per 1,000 people in the total population. It is 'crude' because it doesn't account for whether the population is young or old.

Used to show raw birth flow; India's SRS 2024 rate is 18.3.

Life expectancy at birth

The average number of years a newborn would live if current death rates stayed the same throughout their life. It summarizes mortality conditions.

Rising life expectancy (from 46 to 72) means more Indians reaching old age, accelerating ageing.

Sex ratio at birth

The number of girls born per 1,000 boys. A natural ratio is around 950-970 girls per 1,000 boys; lower numbers indicate missing girls, often due to sex-selective practices.

India's ratio of 918 (SRS 2022-24) signals persistent son preference, though it has improved.

Mean age at childbearing

The average age at which women give birth, weighted by age-specific fertility rates. A rising mean age means women are having children later in life.

India's mean age rose from 25.5 to 30.5 (UN projection), indicating delayed childbearing which lowers fertility.

Projection

A calculation of what the population would be in the future based on assumptions about fertility, mortality, and migration. It is not a prediction; different assumptions produce different projections.

All future population figures are projections, and the range of outcomes shows we cannot be certain about the exact peak.

Census

An official count of every person in the country, usually done every 10 years. It provides the most accurate population figure.

India's last census was in 2011; all current total population numbers are estimates, not counts. The 2024 census is underway.