Demographic indicators and the one-child norm

Detail

1. The data table: select demographic indicators, 2021-23 (World Development Indicators 2024)

Indicator	India	China	Pakistan
Population (million)	1,428	1,411	240
Annual population growth (%)	0.81	−0.10	1.96
Density (per sq km)	473	150	300
Sex ratio (females per 1,000 males)	930	898	948
Fertility rate (children per woman)	2.0	1.2	3.4
Urbanisation (%)	36	65	38

• World Development Indicators (WDI) is the World Bank's main database of development data for all countries. NCERT's table uses the 2024 edition.
• Bold cells mark the highest or lowest value in a row.

2. Size of population

• Share of the world: out of every six people in the world, one is Indian and one is Chinese (2021-23).
• India became the most populous country in 2023 (UN estimate).
• The UN projected that India's population would reach 1,425,775,850 by the end of April 2023. This would match and then pass mainland China [2].
• China's population peaked at 1.426 billion in 2022 and then started to fall [3].
• The UN projects China's population could drop below 1 billion before 2100 [3].

• The UN projects India's population will peak around 2064 and then fall slowly [3].

• Pakistan vs India: Pakistan has 240 million people and India has 1,428 million.

• Worked example: 240 ÷ 1,428 ≈ 0.17, so Pakistan has roughly one-sixth of India's population.
• NCERT says "about one-tenth". Use the WDI numbers: about one-sixth is correct.

3. Population density

• Population density means the number of people living on each square kilometre of land.
• Formula: Density = Total population ÷ Land area (sq km).

• Worked example: 1,428 million people ÷ about 3.02 million sq km ≈ 473 per sq km for India.

• China has the largest area and the lowest density (150 per sq km).

• India has the highest density (473 per sq km). It has about the same number of people as China on about one-third of the land.
• Pakistan is in between (300 per sq km).

4. Population growth

• Annual population growth rate is the percentage change in population in one year.
• Formula: Growth rate (%) = [(Population this year − Population last year) ÷ Population last year] × 100.

• It also equals (birth rate − death rate) ± net migration.

• Ranking (2021-23): Pakistan grows fastest (1.96%), then India (0.81%). China's population is shrinking (−0.10%).

• Worked example: doubling time. The Rule of 70 says: doubling time (years) ≈ 70 ÷ growth rate (%).
• Pakistan: 70 ÷ 1.96 ≈ 36 years to double.
• India: 70 ÷ 0.81 ≈ 86 years to double.
• China: the rate is negative, so its population will never double at this rate. It will shrink.

5. Sex ratio

• Sex ratio means the number of females for every 1,000 males.
• Formula: Sex ratio = (Number of females ÷ Number of males) × 1,000.

• Worked example: 930 females for every 1,000 males means that out of every 1,930 people, 70 more are male than female.

• The ratio is biased against females in all three countries. China is the lowest (898), then India (930), then Pakistan (948).

• NCERT's reason is son preference. Son preference means families want sons more than daughters. This can lead to sex-selective abortion, where a female foetus is aborted, and to neglect of girls.
• India's own survey data (NFHS-5, 2019-21) gives a different picture from the WDI:
• Overall sex ratio: 1,020 females per 1,000 males (2019-21), up from 991 (NFHS-4, 2015-16) [5][4].
• Rural 1,037 and urban 985 (2019-21) [4].
• Sex ratio at birth (girls born per 1,000 boys born in the last five years) rose from 919 (2015-16) to 929 (2019-21) [5].

• Why the numbers differ: NFHS is a household survey. It counts people who usually live in the home, and it does not count many male migrant workers who live away from home. The WDI uses UN estimates for the whole population. For exams, quote the source with the figure. (WDI 2021-23: 930.)

• Sample Registration System (SRS) is the Registrar General of India's large sample survey of births and deaths. Its sex ratio at birth figures are based on three years of data averaged together, and the three-year window moves forward each year [5].

6. Fertility and the replacement level

• Total Fertility Rate (TFR) means the average number of children a woman would have in her lifetime if she followed the current birth rates at each age.
• Replacement level fertility = 2.1 children per woman.
• This is the TFR at which each generation just replaces itself, with no rise or fall in the long run.

• Why 2.1 and not 2.0? Two children replace the two parents. The extra 0.1 covers girls who die before they can have children, and the fact that slightly more boys than girls are born.

• Where the three countries stand (2021-23):

• China 1.2: far below replacement, so its population is shrinking.
• India 2.0: just below replacement.

• Pakistan 3.4: very high, so its population keeps growing fast.

• India's fertility fall (NFHS):

• TFR fell from 2.2 (NFHS-4, 2015-16) to 2.0 (NFHS-5, 2019-21) [4].
• State TFRs range from 1.4 in Chandigarh to 2.4 in Uttar Pradesh (2019-21) [4].

• Among the Phase-II states, Madhya Pradesh, Rajasthan, Jharkhand and Uttar Pradesh were still above replacement level [4].

• Speed of the fall in China and India:

• In 1971 both countries had a TFR of just under 6 [3].
• China's TFR fell below 3 by the end of the 1970s. This happened before the one-child norm began [3].
• India took about 35 years to achieve the fall that China made in about 7 years in the 1970s [3].
• In 2022, China's TFR was 1.2 and India's was 2.0 [3].

7. Urbanisation

• Urbanisation means the share of the population living in towns and cities.
• China is the highest (65%) and India the lowest (36%). Pakistan is at 38% (2021-23).
• Link to fertility: in cities, raising children costs more and women have more chances to study and work. So urban families usually have fewer children. This helps explain China's low TFR.

8. The one-child norm (China)

• What it was: the one-child norm was China's population policy from about 1979-80. It limited most couples to one child.
• It was coercive, meaning people were forced to follow it through targets and penalties.

Effects

• It arrested population growth. It slowed the growth that had begun under Mao.
• It lowered the sex ratio:
• families could have only one child
• many wanted that one child to be a son
• this led to sex-selective abortion

• so China's sex ratio is now the lowest of the three (898).

• It sped up ageing:

• fewer babies were born each year
• so the share of young people fell
• within a few decades there are more elderly people for every young person.
• A higher old-age dependency ratio means fewer workers support each retired person.

Relaxation

• Two-child policy: 2016
• Three-child policy: 2021
• NCERT is outdated here. It mentions only the two-child relaxation.

9. Beyond NCERT: the three countries' population outlook

• China:
• Its population has fallen every year since 2022, after peaking at 1.426 billion in 2022 [3]. Its workforce is shrinking.
• It is becoming "old before rich", which means it is ageing before it reaches high income.

• It now gives pro-natal incentives (rewards that encourage people to have children), such as a national childcare subsidy announced in 2025.

• India:

• It has a demographic dividend. This is the extra growth a country can get when working-age people (15-64 years) are a large share of the population compared with children and the elderly.
• The window lasts until about the 2040s.

• The dividend is only a chance, not a certainty. It pays off only if these people get skills and jobs. Otherwise it can turn into a "demographic burden".

• Pakistan:

• High fertility (TFR 3.4) keeps the population growing fast (1.96% a year).
• This puts pressure on schools, jobs and food, and its demographic dividend comes later.

10. NCERT debate: could India adopt a one-child norm?

• Coercive policy (targets and penalties):
• Pro: it works fast.
• Con: it causes sex-ratio distortion, faster ageing and human-rights costs.

• Indian lesson: India's own coercive sterilisation drive during the 1975-77 Emergency backfired. People lost trust in family planning for years afterwards.

• Voluntary policy (girls' education, health care, women's empowerment):

• Pro: it builds lasting change without distorting the sex ratio.
• Evidence: India's TFR has fallen to 2.0 (NFHS-5, 2019-21) this way, with no one-child rule [4].

• Nuance: China's own TFR had already fallen from about 6 to below 3 during the 1970s, before the one-child norm began [3]. Development and voluntary family planning did much of the work.

• Conclusion: development lowers fertility without coercion.

Prelims Hooks

• Replacement level fertility = 2.1 children per woman. India's TFR is 2.0 (NFHS-5, 2019-21; WDI 2021-23), just below it. China is 1.2 and Pakistan 3.4.
• Negative population growth among the three (2021-23): only China (−0.10%). The fastest growth is Pakistan (1.96%).
• Highest density: India (473/sq km). Lowest density: China (150/sq km), even though China has the largest area. Trap: China has the most land, not the most people per sq km.
• Lowest sex ratio of the three: China (898). The highest is Pakistan (948) (WDI 2021-23).
• Highest urbanisation: China (65%). Lowest: India (36%).
• India passed China as the most populous country in April 2023 (UN DESA). China's population peaked in 2022 at 1.426 billion [2][3].
• China's population policy timeline: one-child norm 1979-80 → two-child 2016 → three-child 2021.
• NFHS-5 (2019-21): overall sex ratio 1,020. Sex ratio at birth 929 [4][5]. Trap: don't mix these up with the WDI figure of 930.
• UN projection: India's population will peak around 2064 [3].

Mains Points

• Coercion vs development (GS-II/GS-III):
• China's one-child norm cut growth, but it left a skewed sex ratio (898), rapid ageing and a shrinking workforce.
• India brought its TFR down to 2.0 through voluntary means, such as girls' education and health care.

• The 1975-77 sterilisation drive showed that coercion backfires in a democracy.

• Demographic dividend as a window of opportunity:

• India's working-age bulge lasts until about the 2040s.
• It pays off only through skilling, female labour force participation and job creation.

• Otherwise it becomes a burden.

• Ageing before income:

• China's "old before rich" problem is a warning for India's southern states, where TFR is below replacement.

• India needs early planning for pensions and elderly care.

• Son preference as a structural issue:

• Sex ratios are biased against females in all three countries.
• India's sex ratio at birth rose from 919 to 929 between 2015-16 and 2019-21 [5].
• Laws against sex-selective abortion work best alongside schemes that raise the value of girls, such as girls' education and women's property rights.