Geography (9696) | Natural increase as a component of population change

Welcome to Population Geography! Understanding Change

Hi there! This chapter is all about understanding how the number of people in a country or region changes over time. When we look at population change, we usually break it down into two main parts:

1. Natural Change (Births minus Deaths)
2. Migration (People moving in or out)

In this section, we're focusing entirely on the first part: Natural Increase. This concept is fundamental to understanding development, resource use, and future planning in geography. Don't worry if the formulas look intimidating; they are actually very straightforward!

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1. Defining the Core Components of Natural Increase

Natural increase is simply the difference between the number of babies born and the number of people who die in a given population.

1.1 Crude Birth Rate (CBR) and Crude Death Rate (CDR)

To measure births and deaths, demographers use 'Crude Rates'. Why "crude"? Because they look at the whole population, not just specific groups (like women of childbearing age).

Key Term: Crude Birth Rate (CBR)

The number of live births per 1,000 people in a population in a given year.

The formula is:
\[ \text{CBR} = \frac{\text{Number of births}}{\text{Total population}} \times 1000 \]

Key Term: Crude Death Rate (CDR)

The number of deaths per 1,000 people in a population in a given year.

The formula is:
\[ \text{CDR} = \frac{\text{Number of deaths}}{\text{Total population}} \times 1000 \]

1.2 Natural Increase Rate (NIR)

The Natural Increase Rate (or Natural Decrease) tells us how fast a population is growing purely from internal biological factors (births and deaths).

Key Term: Natural Increase Rate (NIR)

The difference between the Crude Birth Rate and the Crude Death Rate, usually expressed as a percentage or per 1,000 people.

Quick Calculation Trick: When calculating NIR, rates are usually given per 1,000, but the result is often converted into a percentage (per 100) for easier comparison.

\[ \text{NIR (\%)} = \frac{\text{CBR} - \text{CDR}}{10} \]

Example: If a country has a CBR of 30 (per 1000) and a CDR of 10 (per 1000), the NIR is 20 per 1000, or 2.0%. A high NIR, like 2.0% or more, means the population is growing rapidly!

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2. Specific Indicators: Fertility Rate and Infant Mortality Rate

While CBR and CDR are useful, demographers use more specific rates to understand *why* those numbers are high or low.

2.1 Fertility Rate (Total Fertility Rate - TFR)

The Total Fertility Rate is one of the most important metrics, as it predicts future population growth.

Key Term: Total Fertility Rate (TFR)

The average number of children a woman is expected to have during her childbearing years (ages 15 to 49).

Important Benchmark: The Replacement Level fertility is roughly 2.1. This is the TFR needed to keep the population size stable (i.e., replacing the two parents, plus accounting for some infant mortality).

Did you know? In many High-Income Countries (HICs) like Japan or Germany, the TFR is currently well below 1.5, suggesting their populations will naturally shrink dramatically unless migration fills the gap.

2.2 Infant Mortality Rate (IMR)

IMR is a crucial indicator of a country's health and development level.

Key Term: Infant Mortality Rate (IMR)

The number of deaths of children under one year of age per 1,000 live births.

Analogy: Think of the IMR as the Canary in the Coal Mine for a country's health system. A high IMR immediately signals severe issues with sanitation, basic healthcare, and maternal nutrition.

High IMR often leads to higher fertility rates. Why? If parents expect that some of their children may die before adulthood, they often choose to have more children to ensure that enough survive to support them in old age.

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3. Factors Affecting Fertility and Mortality Levels

The levels of fertility (BR) and mortality (DR/IMR) are determined by a complex mix of social, economic, environmental, and political factors. You must be able to explain these in detail.

3.1 Factors Affecting Fertility (Birth Rates)

These factors generally influence whether families choose to have more or fewer children.

• Social Factors:
  
  • Status of Women: In societies where women have greater access to education and employment, TFR usually drops significantly, as they marry later and prioritize careers over large families.
  • Religion and Culture: Some religious beliefs discourage or prohibit contraception, leading to higher BRs.
  • Availability of Family Planning/Contraception: Access to affordable and reliable birth control allows families to limit family size.
• Economic Factors:
  
  • Cost of Raising Children: In HICs, children are expensive (education, housing). In LICs (Low-Income Countries), children can be economic assets (labor on farms, support for elderly parents).
  • Government Support: High pensions or welfare support for the elderly can reduce the need for children as 'insurance'.
• Political Factors:
  
  • Anti-Natalist Policies: Policies designed to reduce births (e.g., China’s former One-Child Policy, which used financial incentives, fines, and sometimes coercive methods).
  • Pro-Natalist Policies: Policies designed to encourage births (e.g., generous parental leave or "baby bonuses" offered in France or Russia to combat population ageing).

3.2 Factors Affecting Mortality (Death Rates)

These factors determine the overall health and life expectancy of a population.

• Economic and Health Factors:
  
  • Access to Healthcare: Availability of doctors, hospitals, and immunisation programs significantly lowers DR, especially IMR.
  • Nutrition and Food Security: Adequate and balanced nutrition reduces vulnerability to disease. Food shortages or famine dramatically increase DR.
  • Poverty: Wealthy countries can afford better sanitation, medical research, and emergency services, reducing avoidable deaths.
• Environmental Factors:
  
  • Water Quality and Sanitation: Access to clean drinking water prevents deadly waterborne diseases like cholera and dysentery (a huge cause of child mortality in LICs).
  • Exposure to Pollution: High levels of air or water pollution (common in rapidly industrializing MICs) increase mortality from respiratory and other illnesses.
  • Natural Hazards: Frequent droughts, floods, or epidemics can spike mortality rates temporarily.
• Political Factors:
  
  • Conflict and War: Directly causes death and destroys infrastructure (hospitals, water treatment plants), leading to high indirect mortality.
  • Public Health Investment: Government commitment to vaccination programs, sanitation infrastructure, and disease control (like malaria nets).

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4. Population Structure and Dependency

Natural increase changes the structure of a population. This structure is visualized using a powerful geographical tool: the age/sex structure diagram, often called a Population Pyramid.

4.1 Interpreting Age/Sex Structure Diagrams

These diagrams divide the population by age (vertical axis) and gender (horizontal axis), typically showing males on the left and females on the right. The shape of the pyramid tells us about the country's recent history of births and deaths.

• Expansive (Pyramid Shape):
  

  Appearance: Wide base, rapidly tapering top.
  Meaning: High birth rate, high death rate, short life expectancy. Typical of many LICs, such as *Nigeria*.

• Stationary (Beehive/Column Shape):
  

  Appearance: Base is roughly the same width as the middle sections.
  Meaning: Low birth rate, low death rate, increasing life expectancy. Indicates a stable, developed population.

• Contractive (Inverted/Urn Shape):
  

  Appearance: Narrow base (fewer young people) and wide top (many elderly people).
  Meaning: Very low birth rate (well below replacement), very low death rate, high life expectancy. Typical of ageing HICs, such as *Italy* or *Japan*.

4.2 Understanding Population Structure: Age, Gender, and Dependency

The structure determines the level of Dependency, which is a key economic challenge for governments.

Population Age Groups for Dependency:

1. Youth Dependents (0–14 years): People who are too young to work.
2. Economically Active/Working Population (15–64 years): The people who pay taxes and support the dependents.
3. Elderly Dependents (65+ years): People who are typically retired and rely on state pensions or family support.

Key Term: Dependency Ratio

The Dependency Ratio is a numerical measure showing the relationship between the economically active population and the dependent population.

It is expressed as the number of dependents (youth + elderly) per 100 people in the working age group.

\[ \text{Dependency Ratio} = \frac{\text{Youth Dependents (0-14)} + \text{Elderly Dependents (65+)}}{\text{Economically Active (15-64)}} \times 100 \]

Why is the Dependency Ratio important?
A high ratio means a small working population must support a large number of dependents. This puts severe strain on public services (schools, pensions, healthcare) and slows economic growth.

• A pyramid with a wide base has high Youth Dependency (common in LICs).
• A pyramid with a wide top has high Elderly Dependency (common in HICs).

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Section Summary: Key Takeaway

Natural increase (NIR) is fundamentally driven by changes in fertility (TFR) and survival (IMR and CDR). These rates are deeply rooted in a country’s stage of development. Understanding the resulting population structure (the age/sex pyramid) helps us identify the socio-economic challenges a country faces, whether they stem from supporting a youthful population or caring for an ageing one.