Components of population change: births and deaths

Detail

The three components of population change

• Components of population change: the three things that change the number of people in an area. They are births, deaths and migration.
• Births add people.
• Deaths remove people.

• Migration moves people from one place (the origin) to another (the destination). The origin loses people and the destination gains them.

• For the whole world, migration cancels out, because no one leaves the planet. So world population changes only through births and deaths.

• For a country or state, all three components count.
• Basic balancing equation: Population at the end of a period = population at the start + births − deaths + in-migrants − out-migrants.

Component	Effect on the area	Main measure
Births	Add people	Crude birth rate (CBR), total fertility rate (TFR)
Deaths	Remove people	Crude death rate (CDR), life expectancy
Migration	Moves people from the origin to the destination	Net migration (in-migrants − out-migrants)

Crude birth rate (CBR)

• Crude birth rate: the number of live births in a year for every 1,000 people.
• Formula: CBR = (B ÷ P) × 1,000
• B = live births in the year.

• P = the estimated mid-year population of the area, usually counted on 1 July.

• Why the mid-year population? Population changes during the year. The middle of the year is the best average of the people "at risk" of giving birth or dying.

• The UN uses the same rule. It divides annual births (or deaths) by the population at the middle of the period and shows the result per 1,000 people per year [2].
• Worked example (made-up figures): an area has 30,000 live births and a mid-year population of 15,00,000. CBR = (30,000 ÷ 15,00,000) × 1,000 = 20 per 1,000.

Crude death rate (CDR)

• Crude death rate: the number of deaths in a year for every 1,000 people.
• Formula: CDR = (D ÷ P) × 1,000, where D is the number of deaths in the year and P is the mid-year population.
• Population grows when deaths fall, not only when births rise.

• Better food, clean water, vaccines and medicine came into use → death rates fell sharply → births stayed high for some time → the gap between births and deaths widened → population grew fast. This is the "population explosion" of the developing world after about 1950.

• What deaths depend on:

• Demographic structure: the age and sex make-up of the people. More old people means more deaths.
• Social advancement: literacy, hygiene, the status of women, and access to health care.

• Economic development: income, nutrition and sanitation.

• Recent world trends in mortality (how often people die):

• World life expectancy at birth (the average number of years a newborn baby is expected to live at current death rates) reached 73.3 years in 2024. This is 8.4 years more than in 1995 [2].
• It fell to 70.9 years at the peak of COVID-19 (2020-21) and has since started rising again [2].
• It is projected to reach about 77.4 years by 2054 [2].
• In 2023, deaths of children under age 5 fell below 5 million for the first time in recent history. 95% of these deaths happened in countries whose populations are still growing, including the DR Congo, India, Nigeria and Pakistan [2].
• Chad, Niger, Nigeria, Somalia and South Sudan are likely to miss SDG target 3.2. This target is to bring under-5 deaths down to 25 per 1,000 live births or fewer by 2030 [2].
• Fewer deaths are expected to cause about 19% of the world's population growth up to 2054 [2].

Natural growth rate

• Natural growth rate (also called the rate of natural increase): CBR − CDR, given per 1,000 people. It leaves out migration.
• To turn it into a percentage, divide by 10.

• Example: CBR 20 − CDR 7 = 13 per 1,000 = 1.3% a year.

• Actual growth = natural growth + net migration.

• Negative natural growth: deaths are more than births (CDR > CBR). Countries whose population has already peaked, such as China, Germany, Japan and the Russian Federation, are in this group [2].

Why the rates are called "crude"

• They are "crude" because they divide by the whole population and ignore its age structure.
• A country with many old people will have many deaths, even if its health care is excellent.

• A country with many young people will have few deaths, even if its health care is poor.

• The Japan–Niger paradox:

• Japan is old and healthy. It has a higher CDR, because a large share of its people are elderly. Japan, the Republic of Korea and Hong Kong (China) had the world's highest life expectancy in 2024, at 84 years or more [2].
• Niger is young and poor. It has a lower CDR, because most of its people are children and young adults, who die less often than the elderly.

• So a higher CDR does not always mean worse health.

• How demographers fix this:

• Age-specific rates: births or deaths per 1,000 people within one age group (e.g. women aged 20-24).
• Life expectancy at birth: this is not affected by age structure, so it compares health across countries fairly.
• Standardised rates: one country's age-specific rates applied to a standard age structure.

Total fertility rate (TFR)

• Total fertility rate: the average number of children a woman would have in her lifetime if she gave birth at today's age-specific birth rates for every age from 15 to 49.

• Unlike the CBR, the TFR does not depend on how many women are in each age group. It is a better measure of fertility.

• World TFR: 2.25 live births per woman in 2024, down from 3.31 in 1990. Women today have about one child fewer than a generation ago [2]. (NCERT-based summary figure: about 2.2.)

• It is projected to fall to 2.1 by the late 2040s [2].

Category	Countries / regions (2024)	TFR
Highest fertility	Sahel and other parts of sub-Saharan Africa: Niger, Chad, Somalia, Central African Republic, DR Congo	Above 5. In about one-fifth of fast-growing countries (all in sub-Saharan Africa except Afghanistan), the TFR is 4 or more [2]
"Ultra-low" fertility	China, Italy, Republic of Korea, Spain; nearly one-fifth of all countries and areas	Below 1.4 [2]
Lowest	Republic of Korea and Hong Kong SAR (China)	Below 0.75 [2]
Lowest in the "peaking" group	Macao SAR (0.68), Singapore (0.95)	[2]
Below replacement but still growing	Canada, Luxembourg, UAE (TFR below 1.4; population still growing, mainly through immigration)	[2]

• Regional pattern:
• Countries in Eastern and South-Eastern Asia whose population has already peaked average only 1.0 birth per woman [2].
• Countries still growing through 2054 average 2.72 [2].

Replacement-level fertility

• Replacement-level fertility: the TFR at which each generation exactly replaces the one before it. At this level, population size stays the same in the long run if there is no migration.
• Why 2.1 and not 2.0?
• Two children are needed to replace two parents.
• The extra 0.1 makes up for children who die before they grow up, and for the fact that slightly more boys than girls are born.
• 2.1 holds for populations at a late stage of the demographic transition, where few children die [2].

• Where many children die, the replacement level is higher (about 2.5-3+).

• Where the world stands (2024):

• More than half of all countries and areas have a TFR below 2.1 [2].
• Two-thirds of the world's population lives in a country or area where the TFR is below 2.1 [2].

• In the 24 countries that have ultra-low fertility and have already peaked, the chance of returning to 2.1 within 30 years is only 0.1% [2].

• Population momentum: the population keeps growing after the TFR reaches replacement level.

• Cause: past high fertility left a large number of young people.
• Process: many women are still entering the childbearing ages (15-49). Their number is projected to peak at about 2.2 billion in the late 2050s, up from nearly 2.0 billion in 2024 [2].
• Result: births stay high even though each woman has fewer children. Momentum will cause 79% of world population growth up to 2054, about 1.4 billion people [2].
• The reverse also happens. Negative momentum keeps shrinking a population that has had low fertility for a long time, even if its TFR rises again.

India's fertility transition

• India's TFR fell from 2.2 (NFHS-4, 2015-16) to 2.0 (NFHS-5, 2019-21). This is below the replacement level of 2.1 [3].
• Only five States were still above replacement in NFHS-5. Bihar was the highest, at 2.98 [3].
• Sikkim had the lowest TFR of any State.
• Pattern:
• High fertility: the northern Hindi heartland (Bihar, Uttar Pradesh, Jharkhand) and Meghalaya in the north-east.

• Low fertility: the southern States, West Bengal, Punjab and the Himalayan States.

• India is still among the countries whose population is projected to grow through 2054. This is because of momentum from its young age structure, even though its TFR is below replacement [2].

Prelims Hooks

• CBR = (B ÷ P) × 1,000 and CDR = (D ÷ P) × 1,000. P is the mid-year population, not the population on 1 January or in the Census.
• Natural growth rate = CBR − CDR, per 1,000. It leaves out migration. Divide by 10 to get a percentage.
• Trap: a higher CDR does not always mean poorer health. Japan (old population) has a higher CDR than Niger (young population), because crude rates ignore age structure.
• Replacement-level TFR ≈ 2.1 where few children die. It is higher where many children die.
• World TFR: 3.31 (1990) → 2.25 (2024). Projected to reach 2.1 by the late 2040s (UN WPP 2024).
• Lowest TFR (2024): Republic of Korea and Hong Kong SAR, below 0.75. Highest: the Sahel (Niger, Chad) and Somalia, above 5.
• "Ultra-low" fertility means a TFR below 1.4. Examples: China, Italy, Republic of Korea, Spain.
• World life expectancy at birth: 73.3 years (2024). It fell to 70.9 in 2020-21 (COVID-19). Projected at 77.4 by 2054.
• India TFR: 2.2 (NFHS-4) → 2.0 (NFHS-5, 2019-21). Highest State: Bihar (2.98). Lowest State: Sikkim.
• Two-thirds of humanity lives where the TFR is below replacement (2024).

Mains Points

• Falling deaths, not rising births, drove modern population growth.
• Public health, vaccines and food security cut the CDR before the CBR fell → the gap between births and deaths widened.

• This is stage 2 of the demographic transition. It is seen today in the Sahel (Niger, Chad), where population may double between 2024 and 2054.

• Crude rates can mislead policy.

• They depend on age structure. Japan's high CDR comes from ageing, not poor health.

• Planners should use age-specific rates, TFR and life expectancy (GS-I: population and associated issues).

• India's below-replacement TFR does not mean the population has stopped growing.

• Population momentum and a young age structure keep it growing.

• Fertility differs widely between regions (Bihar 2.98 vs Sikkim, the lowest). This calls for different policies by region: family planning and girls' education in the high-fertility north, and preparing for an ageing population in the south.

• The ultra-low fertility trap. East Asia and southern Europe have a TFR below 1.4. This brings shrinking workforces, a rising share of old people dependent on workers, and dependence on immigration. India's southern States show early signs of the same trend.