Population Change: Fertility, Mortality, Growth Rates, and Age Structure

Why Population Change Matters for Settlements

Settlements must continuously adapt to how many people live in a place, how fast that number is changing, and which age groups are growing or shrinking. A city gaining 50,000 people in a year faces immediate pressure on housing, water, transport, and jobs; a region with a shrinking working-age population may struggle to keep schools open while needing more healthcare and accessible housing. Population change is therefore not just “more or fewer people,” but a shift in the mix of needs across the life course.

Two Different Ideas: Absolute Growth vs. Growth Rate

Absolute growth is the change in the number of people (e.g., +20,000 residents). Growth rate expresses change relative to the starting population (e.g., +2% per year). A small town can have a high growth rate with modest absolute growth, while a large city can add many people with a lower rate.

• Absolute growth = Population at end − Population at start
• Growth rate (%) = (Absolute growth ÷ Population at start) × 100

Example: Town A grows from 50,000 to 55,000: absolute growth = 5,000; growth rate = (5,000/50,000)×100 = 10%. City B grows from 2,000,000 to 2,050,000: absolute growth = 50,000; growth rate = (50,000/2,000,000)×100 = 2.5%. Planning implications differ: Town A may face rapid land-use change; City B may face large-scale infrastructure expansion.

Core Measures of Population Change

Crude Birth Rate (CBR)

CBR measures births per 1,000 people per year.

CBR = (Number of births in a year ÷ Mid-year population) × 1,000

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Step-by-step example:

• Births in one year: 12,600
• Mid-year population: 840,000
• CBR = (12,600 ÷ 840,000) × 1,000 = 0.015 × 1,000 = 15 births per 1,000

Interpretation for settlements: Higher CBR often signals future demand for maternity services now and schools, playgrounds, and family housing soon. However, CBR is “crude” because it uses the total population, not just women of childbearing age.

Crude Death Rate (CDR)

CDR measures deaths per 1,000 people per year.

CDR = (Number of deaths in a year ÷ Mid-year population) × 1,000

Step-by-step example:

• Deaths in one year: 9,240
• Mid-year population: 840,000
• CDR = (9,240 ÷ 840,000) × 1,000 = 0.011 × 1,000 = 11 deaths per 1,000

Interpretation for settlements: A higher CDR can reflect older age structure (more elderly) rather than poor health conditions. This matters because an older population increases demand for clinics, long-term care, accessible transit, and smaller, adaptable housing.

Rate of Natural Increase (RNI)

RNI is population change from births minus deaths, excluding migration. It is often expressed as a percentage per year.

RNI (%) ≈ (CBR − CDR) ÷ 10

Step-by-step example using the CBR and CDR above:

• CBR = 15 per 1,000
• CDR = 11 per 1,000
• RNI ≈ (15 − 11) ÷ 10 = 4 ÷ 10 = 0.4% per year

Alternative method (counts):

• Natural increase (people) = births − deaths = 12,600 − 9,240 = 3,360
• Natural increase rate (%) = (3,360 ÷ 840,000) × 100 = 0.4%

Interpretation for settlements: A positive RNI suggests internal growth pressure even if migration is zero. A negative RNI (more deaths than births) can lead to school closures and housing oversupply unless offset by in-migration.

Total Fertility Rate (TFR)

TFR estimates the average number of children a woman would have over her lifetime if current age-specific fertility rates remain constant. Unlike CBR, it focuses on fertility behavior rather than the whole population structure.

How to interpret:

• TFR around 2.1 is often called “replacement-level” in many contexts (enough births to replace parents over time, accounting for mortality).
• Higher TFR tends to produce youthful age structures and strong future school and housing demand.
• Lower TFR tends to produce aging populations, smaller future labor force, and shifting service needs.

Practical settlement link: Two cities can have the same CBR today, but the one with higher TFR may sustain births over time, while the other may have a temporarily high CBR because it currently has many people in childbearing ages.

Life Expectancy

Life expectancy at birth is the average number of years a newborn is expected to live if current mortality patterns persist. It summarizes survival conditions across ages.

Interpretation for settlements: Higher life expectancy usually increases the share of older residents over time, raising demand for chronic disease management, home care, age-friendly public space, and accessible housing. It can also extend working lives, affecting commuting patterns and labor markets.

Doubling Time

Doubling time estimates how long it takes a population to double at a constant growth rate.

Rule of 70 (approximation):

Doubling time (years) ≈ 70 ÷ Annual growth rate (%)

Step-by-step examples:

• If growth rate = 2%: doubling time ≈ 70 ÷ 2 = 35 years
• If growth rate = 0.5%: doubling time ≈ 70 ÷ 0.5 = 140 years

Interpretation for settlements: A 2% growth rate can force rapid expansion of housing supply, utilities, and transport corridors. A 0.5% rate may allow incremental upgrades, but aging or uneven neighborhood change can still create urgent localized needs.

Age Structure and Population Momentum

Why Age Structure Can “Lock In” Future Growth

Population momentum is continued population growth (or decline) that occurs because of the existing age structure, even if fertility rates change immediately. If a population has a large cohort of young people entering reproductive ages, births can remain high for decades even after TFR falls. Conversely, a population with few young adults may keep shrinking even if TFR rises, because there are fewer potential parents.

Planning implication: Momentum affects the timing of settlement needs. A youthful population creates predictable waves: maternity care now, primary schools soon, then secondary schools, then job creation and housing for young adults. An older-heavy population creates different waves: healthcare capacity, accessible housing retrofits, and labor shortages.

Reading Population Pyramids

What a Population Pyramid Shows

A population pyramid is a bar chart showing the number or percentage of people by age group and sex. Typically:

• Vertical axis: age groups (e.g., 0–4, 5–9, …, 80+)
• Horizontal axis: population size (left often male, right often female)

Common Pyramid Shapes and What They Suggest

• Expansive (wide base, narrow top): high share of children; likely high fertility and strong momentum. Settlement pressures: rapid school expansion, family housing, child health services, and future job creation.
• Stationary (more rectangular): balanced age distribution; steadier demand across services. Settlement pressures: maintaining infrastructure, mixed housing types, stable labor markets.
• Constrictive (narrow base, wider middle/older): low fertility and aging. Settlement pressures: fewer schools, more eldercare, accessible transport, and potential labor shortages.

How to Spot Momentum in a Pyramid (Practical Checklist)

• Large 0–14 cohort relative to adults: strong future growth potential even if fertility falls.
• Bulge in 15–34: near-term housing demand (rentals, starter homes), higher mobility, and strong labor market entry.
• Bulge in 55+: near-term healthcare demand, retirement housing, and potential increase in deaths (which can raise CDR).
• Indentations (missing cohorts): future “gaps” in school enrollments or labor supply.

Dependency Ratios: Turning Age Structure into Planning Signals

Definitions

Dependency ratios compare the number of people typically considered “dependent” to those typically considered “working-age.” A common convention is:

• Youth: ages 0–14
• Working-age: 15–64
• Older: ages 65+

Youth dependency ratio = (Population 0–14 ÷ Population 15–64) × 100

Old-age dependency ratio = (Population 65+ ÷ Population 15–64) × 100

Total dependency ratio = ((0–14 + 65+) ÷ 15–64) × 100

Step-by-step Calculation Example

Suppose a region has:

• Population 0–14: 240,000
• Population 15–64: 600,000
• Population 65+: 160,000

Youth dependency:

• (240,000 ÷ 600,000) × 100 = 0.4 × 100 = 40

Old-age dependency:

• (160,000 ÷ 600,000) × 100 = 0.2667 × 100 = 26.7

Total dependency:

• ((240,000 + 160,000) ÷ 600,000) × 100 = (400,000 ÷ 600,000) × 100 = 0.6667 × 100 = 66.7

Interpretation: For every 100 working-age people, there are about 40 children and 27 older adults. This does not mean all 15–64 are employed or that all dependents are economically inactive, but it is a useful planning signal for service demand and fiscal pressure.

Connecting Measures to Settlement Needs

Housing Demand and Neighborhood Form

• Youthful age structure + high RNI: demand for larger units, family-oriented neighborhoods, and rapid housing supply. Informal or peripheral expansion may occur if supply lags.
• Young-adult bulge (15–34): demand for rentals, smaller units, transit access, and proximity to jobs; can intensify inner-city densification or corridor development.
• Aging structure + low/negative RNI: demand shifts toward accessible housing, assisted living, and retrofits (elevators, step-free access). Some areas may see vacancy if out-migration occurs.

Schools and Child Services

• High CBR and wide pyramid base: immediate need for prenatal care and childcare; within 5–10 years, primary schools and safe routes to school; later, secondary schools and vocational training.
• Narrowing base: school consolidation, repurposing buildings, and rebalancing budgets toward adult services.

Healthcare and Social Care

• Rising life expectancy + larger 65+ cohort: more chronic care, geriatric services, home-based care, and emergency response capacity.
• High old-age dependency: pressure on caregivers and local health systems; may increase demand for compact, walkable settlements and frequent public transport.

Labor Markets and Commuting

• Large working-age cohort entering labor market: need for job creation, skills training, and transport capacity; if jobs concentrate in certain nodes, commuting corridors intensify.
• Shrinking working-age cohort: labor shortages, potential wage increases in key sectors (healthcare, construction), and incentives to attract migrants or retain older workers.

Worked Mini-Scenario: Same Growth Rate, Different Planning Pressures

Even with identical growth rates, settlement planning differs because age structure changes what “growth” means in daily life.

Structured Exercise: Interpreting Two Population Pyramids for Planning

Instructions

Below are two simplified pyramids described in words. For each pyramid, answer the questions that follow. Focus on likely planning pressures and how they may reshape settlement patterns (densification, sprawl, corridor growth, service relocation, neighborhood change).

Pyramid A (Youthful, Expansive)

• Very wide base (0–4 and 5–9 are the largest bars).
• Bars steadily narrow with age.
• Small 65+ share.

Pyramid B (Aging, Constrictive)

• Narrow base (0–4 and 5–9 are small).
• Largest bars are 45–59 and 60–69.
• Noticeable 80+ share, especially among women.

Questions (Answer for A and for B)

1. Momentum: Is population momentum likely to be positive, neutral, or negative over the next 20 years if fertility suddenly fell to replacement level? Explain using the pyramid shape.
2. Dependency: Which dependency ratio is likely higher (youth or old-age)? What does that imply for local budgets and service staffing?
3. Housing: What housing types will be most demanded in the next 5 years and in the next 15 years? Consider unit size, accessibility, and location.
4. Schools vs. healthcare: Which facilities need expansion, which might consolidate, and where should they be located relative to neighborhoods?
5. Labor market and commuting: Will the area need to create many new jobs, attract workers, or adapt to labor shortages? How might commuting patterns change?
6. Settlement pattern shifts: Choose two likely spatial outcomes and justify them: (a) outward expansion at the edge, (b) infill densification, (c) redevelopment of underused land, (d) service hubs around transit, (e) decline and vacancy in some neighborhoods, (f) growth of retirement-oriented districts.

Optional Quantification Add-on

If you are given totals for 0–14, 15–64, and 65+ for each pyramid, compute youth and old-age dependency ratios using the formulas above and add one sentence linking each ratio to a concrete planning decision (e.g., “build two new primary schools in the north corridor” or “prioritize step-free bus stops and clinics in older districts”).