AS Geography (3910) — AS 2: Human Geography
Chapter 1: Population Change
Welcome to your study notes for Population Change! Understanding how human populations grow, shrink, and move is central to understanding the world around us. Whether you find human geography straightforward or a bit daunting, these notes break down every syllabus requirement step-by-step with clear definitions, comparisons, models, and case studies.
1 (a) Population Data
To plan schools, hospitals, roads, and pensions, governments need accurate figures about who lives in their country. There are two primary ways governments gather demographic data: national census taking and vital registration.
Distinguishing Census Taking and Vital Registration
• National Census Taking: A nationwide survey conducted periodically (usually every 10 years) that counts the total population and collects detailed social, economic, and demographic data (e.g., age, household size, employment, religion, housing conditions) at a single snapshot in time.
• Vital Registration: A continuous, legal recording of civil life events as they happen day-to-day. This includes the mandatory registration of births, deaths, marriages, and divorces.
Analogy to remember the difference: Think of a census like a whole-school photo taken once every few years, capturing everyone on that exact day. Vital registration is like the daily attendance register and office log, continuously recording every time a new student enrols or leaves.
Contrasts Between MEDCs and LEDCs
Collecting population data is far more challenging in More Economically Developed Countries (MEDCs) compared to Less Economically Developed Countries (LEDCs).
1. How Data is Collected:
• MEDCs: Heavily digitalised and automated. Forms are distributed by mail or completed securely online (e.g., digital self-completion). High literacy rates allow self-enumeration.
• LEDCs: Relies heavily on face-to-face interviews by trained enumerators travelling door-to-door. Paper forms are widely used due to limited internet infrastructure and varying literacy levels.
2. Reliability of Data:
• MEDCs: Generally high reliability. However, minor errors occur due to undercounting specific groups (e.g., the homeless, undocumented migrants, or students living away from home).
• LEDCs: Lower reliability. Significant barriers include remote or inaccessible terrain, physical conflicts, language diversity (multiple regional dialects), low literacy, and suspicion/fear of government taxation. Vital registration is often incomplete because births and deaths occurring at home in rural areas frequently go unregistered.
3. Use Made of the Data:
• MEDCs: Used for long-term strategic planning, such as calculating state pension obligations, planning healthcare services for an ageing population, adjusting local taxation, and redrawing electoral boundaries.
• LEDCs: Used primarily for basic resource allocation, identifying regions experiencing acute poverty or food shortages, planning primary healthcare interventions (such as vaccination programmes), and distributing international aid.
Contrasting National Case Studies: UK vs. Kenya
MEDC Case Study: The United Kingdom
• Collection: The UK census is conducted every 10 years (managed by the Office for National Statistics). The 2021 Census was predominantly 'digital-first', with over \(85\%\) of households completing it online.
• Vital Registration: Legally mandated; births must be registered within 42 days (in England and Wales) and deaths within 5 days, resulting in near \(100\%\) accuracy.
• Reliability: Very high, backed by post-enumeration surveys to cross-check uncounted individuals.
• Use of Data: Allocating billions in funding to NHS trusts, planning transport networks, and managing social care provision.
LEDC Case Study: Kenya
• Collection: Kenya conducts a census every 10 years (e.g., 2019 Kenya Population and Housing Census). Enumerators use digital handheld tablets to visit households across arid and rural regions.
• Vital Registration: Historically low coverage; many births and deaths occurring in remote rural communities (e.g., Turkana or Mandera) go unregistered due to the distance to administrative offices.
• Reliability: Challenged by nomadic pastoralist communities who move across borders, high population mobility in informal urban settlements (e.g., Kibera in Nairobi), and boundary disputes.
• Use of Data: Planning basic infrastructure, targeting famine relief, building new primary schools, and allocating national revenue shares among Kenya's 47 counties.
Section 1(a) Key Takeaway: Censuses provide comprehensive periodic snapshots, while vital registration provides continuous tracking. MEDCs benefit from high literacy, online systems, and complete vital records, whereas LEDCs face logistical, financial, and geographical hurdles.
1 (b) Population Change: Measures & Models
Main Fertility and Mortality Measures
Demographers use specific standard rates per 1,000 people to compare countries of different sizes.
1. Crude Birth Rate (CBR):
The number of live births per 1,000 of the total population in a given year.
\( \text{CBR} = \left( \frac{\text{Total Live Births}}{\text{Total Population}} \right) \times 1000 \)
2. Crude Death Rate (CDR):
The number of deaths per 1,000 of the total population in a given year.
\( \text{CDR} = \left( \frac{\text{Total Deaths}}{\text{Total Population}} \right) \times 1000 \)
Note on "Crude": It is called 'crude' because it does not take into account the age or gender structure of the population. A country with an elderly population (like Italy or Japan) may have a higher CDR than a youthful LEDC, even though living conditions are better.
3. Total Fertility Rate (TFR):
The average number of children a woman is expected to have throughout her childbearing years (ages 15–49), based on current age-specific fertility rates.
• Replacement Level Fertility: Globally recognized as approximately \(2.1\) children per woman. At this level, a population replaces itself exactly from one generation to the next without migration.
4. Infant Mortality Rate (IMR):
The number of deaths of infants under one year of age per 1,000 live births in a given year.
\( \text{IMR} = \left( \frac{\text{Deaths of Children Under 1 Year}}{\text{Total Live Births}} \right) \times 1000 \)
Why IMR is crucial: It is widely regarded as one of the most sensitive indicators of a country's overall socioeconomic development and healthcare quality.
The Demographic Transition Model (DTM)
The DTM illustrates how birth rates and death rates change over time as a country develops economically. It consists of 5 distinct stages:
• Stage 1: High Stationary
Birth Rate: High and fluctuating. Death Rate: High and fluctuating (due to famine, disease, lack of clean water). Natural Increase: Very low. Examples: Isolated tribes; no entire countries remain in Stage 1 today.
• Stage 2: Early Expanding
Birth Rate: Remains high (children needed for farm labour; cultural traditions). Death Rate: Falls rapidly due to improvements in clean water, basic sanitation, medical access, and food supply. Natural Increase: Very high (rapid population growth). Examples: Niger, Mali, Afghanistan.
• Stage 3: Late Expanding
Birth Rate: Falls rapidly (increasing female education, urbanisation, access to contraception, falling IMR means fewer replacement births needed). Death Rate: Continues to fall, but at a slower rate. Natural Increase: Slowing down. Examples: India, Brazil, Kenya.
• Stage 4: Low Stationary
Birth Rate: Low. Death Rate: Low. Natural Increase: Very low or stable. Examples: UK, USA, France.
• Stage 5: Declining
Birth Rate: Drops below the death rate (TFR falls well below \(2.1\)). Death Rate: Rises slightly due to an ageing population structure. Natural Increase: Negative (population decline). Examples: Germany, Italy, Japan.
The Epidemiological Transition Model (ETM)
Developed by Abdel Omran, the ETM explains how the primary causes of human mortality change as societies develop economically and medically:
• Phase 1: The Age of Pestilence and Famine
Mortality is high and unpredictable. Major causes of death: Infectious diseases (cholera, plague, smallpox), malnutrition, and widespread epidemics. Life expectancy is low (20–40 years).
• Phase 2: The Age of Receding Pandemics
Mortality declines steadily as pandemics become less frequent. Public health infrastructure, sanitation systems, clean piped water, and early antibiotics reduce communicable infections. Life expectancy rises to 50+ years.
• Phase 3: The Age of Degenerative and Man-Made Diseases
Infectious diseases decline to low levels. Deaths are primarily caused by non-communicable, chronic lifestyle diseases associated with ageing: cardiovascular disease, stroke, cancers, and type 2 diabetes. Life expectancy exceeds 70–80 years.
Section 1(b) Key Takeaway: As countries develop, death rates drop first (due to sanitation and medicine), followed by birth rates (due to education and family planning). Disease patterns transition from infectious epidemics to chronic, degenerative conditions.
1 (c) Population and Resources
Key Balance Concepts
The balance between population size and available resources (food, water, energy, technology) determines living standards:
• Optimum Population: The theoretical ideal number of people which, when combined with available resources and technology, produces the highest possible standard of living and quality of life for all inhabitants.
• Overpopulation: A situation where the population exceeds the available resources and carrying capacity of the environment, resulting in a declining standard of living, resource depletion, overcrowding, and poverty.
• Underpopulation: A situation where there are too few people to fully exploit and utilize the available resources of an area efficiently (e.g., parts of Australia or Canada). An increase in population would raise living standards.
Theories of Population Sustainability: Malthus vs. Boserup
1. Thomas Malthus (1798) — The Pessimistic View:
• Core Argument: Population grows geometrically (exponentially: \(1, 2, 4, 8, 16, 32 \dots\)), whereas food production increases only arithmetically (linearly: \(1, 2, 3, 4, 5, 6 \dots\)).
• The Outcome: Population inevitably outstrips food supply, reaching a "Malthusian ceiling" (carrying capacity catastrophe).
• Checks to Population:
— Preventative Checks (lowering birth rates): Celibacy, delayed marriage, moral restraint.
— Positive Checks (increasing death rates): Famine, war, disease, and misery.
• Evaluation: Malthus failed to foresee major technological advancements in agriculture (e.g., fertilisers, tractors, the Green Revolution, genetically modified crops) and widespread voluntary adoption of contraception.
2. Esther Boserup (1965) — The Optimistic View:
• Core Argument: "Necessity is the mother of invention." Population growth acts as the primary stimulus for technological change and agricultural innovation.
• The Outcome: When food shortages loom, humans invent new techniques to increase output (e.g., irrigation, multi-cropping, selective breeding, biotechnology). Food supply rises to meet population demand.
• Evaluation: Boserup's model holds true in many modern contexts, but has limitations: severe overpopulation can lead to environmental degradation (desertification, soil erosion, aquifer depletion) where technology cannot keep pace.
Fertility Policies
When a country experiences a severe population-resource imbalance, governments intervene with national fertility policies:
• Anti-Natalist Policies: Aim to reduce birth rates when rapid population growth threatens to outstrip national resources and infrastructure (e.g., China's One-Child Policy, family planning programmes in India).
• Pro-Natalist Policies: Aim to increase birth rates when an ageing population and sub-replacement fertility threaten economic productivity and workforce size (e.g., France's subsidised childcare and parental leave, Singapore's "Baby Bonus" scheme).
Detailed Case Study: China's Anti-Natalist Policy (The One-Child Policy)
1. Context and Need for the Policy:
In the 1950s and 1960s, China's population grew rapidly (reaching nearly 1 billion by the late 1970s) under policies encouraging large families. Severe famines (such as the Great Chinese Famine, 1959–1961) highlighted the acute risk of exceeding carrying capacity. In 1979, the Chinese government introduced the nationwide One-Child Policy to avert catastrophic resource shortages.
2. Methods and Enforcement:
• Incentives: Couples with one child received higher wages, priority housing, free healthcare, and preferred schooling for their child.
• Disincentives & Sanctions: Heavy financial fines (the "social compensation fee"), loss of state employment, and removal of healthcare benefits for unauthorized births.
• Strict Controls: Minimum marriage ages were raised; contraception, IUD insertion, and sterilization were strictly enforced by local family planning committees.
• Exceptions: Rural families whose first child was a girl or disabled were often permitted a second child after a waiting period; ethnic minority groups were exempt.
3. Evaluation of Impacts:
• Successes / Positive Impacts:
— Prevented an estimated 300 to 400 million births, dramatically reducing pressure on China's land, water, food, and energy supplies.
— Accelerated economic growth and poverty reduction by reducing the youth dependency ratio.
— Improved education and healthcare access for the smaller cohorts of single children.
• Negative Consequences & Criticisms:
— Gender Imbalance: Traditional cultural preference for sons led to sex-selective abortions, abandonment of baby girls, and a skewed sex ratio at birth (at its peak, approximately \(118\) males per \(100\) females), creating a surplus of millions of unmarried men ("bare branches").
— Ageing Population & The "4-2-1" Problem: One working-age adult child is left financially and physically responsible for supporting two parents and four grandparents.
— Shrinking Workforce: Depletion of the labour supply led China to officially relax the policy, moving to a universal Two-Child Policy in 2016 and a Three-Child Policy in 2021.
Section 1(c) Key Takeaway: Optimum population is the ideal balance. Malthus warned of natural limits and crisis, while Boserup highlighted human innovation. China successfully curbed unsustainable growth through its One-Child Policy, but created severe long-term demographic imbalances.
Chapter Summary & Revision Checklist
Before sitting your exam on Population Change, make sure you can:
• Clearly define and contrast national census and vital registration.
• Explain the differences in data collection, reliability, and usage between an MEDC (UK) and an LEDC (Kenya).
• Define and write the formulas for CBR, CDR, TFR, and IMR.
• Sketch and explain all 5 stages of the Demographic Transition Model.
• Describe the 3 phases of the Epidemiological Transition Model.
• Contrast overpopulation, underpopulation, and optimum population.
• Critically compare Malthus's pessimistic theory with Boserup's optimistic theory.
• Evaluate the reasons for and consequences of China's One-Child Policy.