Population Composition

Why this chapter matters for UPSC: Population composition questions appear in both Prelims and Mains. Sex ratio (globally and for India) is a consistent UPSC Prelims topic. Population pyramids are asked in GS1 Mains to explain demographic structures of developed vs developing countries. India's demographic dividend — the bulge in the working-age population — is critically assessed in both GS1 and GS2 (Social Justice, Education, Employment). This chapter gives you the vocabulary and frameworks for all such questions.

Contemporary hook: India's 2011 Census revealed a child sex ratio (0–6 years) of 918 girls per 1,000 boys — the worst since independence. The 2023 NFHS-5 data show improvement (929), but the problem persists in Haryana (916) and Punjab (922). Understanding why sex ratios matter — economically, socially, and ethically — requires population composition analysis.

PART 1 — Quick Reference Tables

Sex Ratio: Global and Indian Patterns

Population Pyramid Types

Rural vs Urban Population

Occupational Structure by Sector

PART 2 — Detailed Notes

Sex Ratio — Why It Matters

Sex ratio is defined as the number of females per 1,000 males (in India) or males per 100 females (internationally). The global average biological birth ratio is approximately 105–107 males per 100 females — slightly more males are born, but male mortality is higher at all ages, so older age groups have more females.

Where females outnumber males: Most of Europe and the Americas — partly a legacy of male emigration and male war mortality, partly longer female life expectancy.

Where males outnumber females: South Asia and China — son preference, female foeticide, neglect of girl children, maternal mortality. This is a development and social justice failure, not a natural demographic outcome.

Gulf States / UAE / Qatar: Extreme male excess because these countries host tens of millions of male migrant workers (from India, Bangladesh, Nepal, Pakistan) who have left families behind.

💡 Explainer: Population Pyramids

A population pyramid is a graphical representation of the age-sex structure of a population. Males are typically shown on the left, females on the right; youngest age groups at the bottom, oldest at top.

Reading a pyramid tells you:

• Whether the population is growing, stable, or declining
• The size of the working-age population (15–64) relative to dependents (0–14 and 65+)
• The sex ratio at each age group
• Historical events (baby boom = wide band; war/famine = narrow band)

India's pyramid: Currently expansive-to-stationary transition — a large working-age bulge (the demographic dividend) with a still-wide base in rural northern states. By 2050, it will look more constrictive as TFR falls.

Japan's pyramid: Classic constrictive — small young base, huge middle-aged and elderly cohorts. This creates severe old-age dependency burden and labour shortages.

📌 Key Fact: Demographic Dividend Window

India's demographic dividend window — when the working-age population (15–64) is larger than the dependent population — is roughly 2020–2040. During this window, each worker supports fewer dependents, boosting per-capita income IF employment and skill generation are adequate. East Asian economies (Japan, South Korea, Taiwan) successfully captured their dividend in the 1970s–1990s. India's challenge is creating 8–10 million jobs per year to absorb young entrants.

Age Structure and Dependency Ratio

Youth dependency ratio = (Population 0–14 ÷ Population 15–64) × 100 Old-age dependency ratio = (Population 65+ ÷ Population 15–64) × 100 Total dependency ratio = Sum of both

High youth dependency: characteristic of Stage 2/3 DTM countries — heavy burden on school, health, job systems. High old-age dependency: characteristic of Stage 4 — pension, healthcare burden; labour shortages. Low total dependency: the "sweet spot" — demographic dividend.

Literacy and Occupational Structure

Literacy is a basic measure of human capability. The NCERT notes that literacy levels are much higher in developed countries (near-universal) and vary widely in developing countries. India's literacy rate was 77.7% (NFHS-5); Kerala leads at ~96%, Bihar lags at ~66%.

Occupational structure reveals the stage of economic development:

• Agrarian economies — >50% in primary sector (Sub-Saharan Africa, parts of South Asia)
• Industrial economies — large secondary sector (Manufacturing Belt economies of 20th century)
• Service economies — >60% tertiary (USA, UK, France)
• India's anomaly: ~44% still in agriculture (2020-21), contributing only ~17% of GDP. India skipped the "industrial phase" to a large informal tertiary sector — premature tertiarisation.

🎯 UPSC Connect: Human Development Index (HDI)

HDI was introduced by UNDP (United Nations Development Programme) in 1990 at the initiative of Pakistani economist Mahbub ul Haq and Indian Nobel laureate Amartya Sen. It measures three dimensions:

1. Health — Life expectancy at birth
2. Education — Mean years of schooling + expected years of schooling
3. Income — GNI per capita (PPP, in international dollars)

HDI score ranges from 0 to 1. Countries above 0.8 are "Very High HDI" (developed); below 0.55 are "Low HDI." India's HDI in 2023 Report: 0.644 (rank 134 of 193) — Medium HDI category.

Rural-Urban Composition

The rural-urban divide is not just a settlement question — it reflects economic structure, literacy, income, and access to services.

Global urbanisation trend: The world crossed the 50% urban threshold around 2007. By 2050, the UN projects 68% urban. Most urban growth is now in Africa and Asia.

Rural-urban continuum: The boundary between rural and urban is blurring — peri-urban areas, "rurban" clusters, million-plus agglomerations spreading into formerly rural hinterlands.

India (2011 Census): 31.16% urban population. 2031 projection: ~40% urban. This transition is driving massive infrastructure demand, urban planning challenges, and rural out-migration.

🔗 Beyond the Book: Why Occupational Structure Matters for Policy

The shift from primary to secondary to tertiary occupations is the classic pathway of structural transformation in development economics (Lewis model, Kuznets). When agriculture employs 40% of the workforce but contributes only 17% of GDP, it signals low agricultural productivity AND underemployment — workers who would be more productive elsewhere. This is the core challenge behind India's "farm income doubling" debate and rural-to-urban migration policy.

PART 3 — Frameworks and Analysis

Reading a Population Pyramid: Step-by-Step

1. Look at the base (youngest cohort) — wide = high birth rate; narrow = low birth rate
2. Look at the shape — triangular (expansive), rectangular (stationary), or bulging middle (constrictive/transitional)
3. Look at the top — wide top = ageing population; narrow top = short life expectancy
4. Look for asymmetry — more males at young ages (labour force); more females at old ages (longevity)
5. Look for cohort anomalies — unusually thin or wide bands indicate historical events (war, famine, baby boom)

Three Key Demographic Indicators for Mains

Composite View: What a Population Composition Analysis Should Cover

For any country/region asked in Mains, cover: (1) absolute size and growth rate, (2) sex ratio and causes, (3) age structure and dependency, (4) rural-urban distribution, (5) literacy and education, (6) occupational structure — primary/secondary/tertiary split.

Exam Strategy

For Prelims: Sex ratio values (India 2011: 943; child sex ratio: 918; worst states: Haryana, Punjab), HDI rank, India's literacy rate, urban population percentage.

For Mains GS1: Pyramid questions — always name the three types, describe the shape, give a country example, and explain the policy implications. For sex ratio, go beyond just stating the figure — explain causes (son preference, foeticide, maternal mortality) and consequences (skewed marriage market, missing women phenomenon as coined by Amartya Sen).

Mains GS2 link: Population composition links directly to social justice — sex ratio (gender inequality), literacy (education policy), occupational structure (labour rights, MGNREGA, skill India).

Amartya Sen's "Missing Women": Sen calculated that given normal biological ratios, Asia and Africa have ~100 million "missing women" who would be alive if not for discrimination-linked excess female mortality. Highly quotable in Mains answers.

Previous Year Questions

1. UPSC Mains GS1 2019: "Discuss the major factors responsible for the adverse sex ratio in India. What measures have been taken by the government to address this?" (Population composition + policy)

2. UPSC Mains GS1 2016: "Draw and explain the population pyramids of a young growing population and an ageing population. Discuss the implications of each for economic development." (Classic pyramid question)

3. UPSC Mains GS2 2018: "How does India's demographic profile affect its HDI ranking? What structural changes are needed to improve India's human development outcomes?" (Occupational + HDI link)

4. UPSC Prelims 2023: "Which of the following is the correct definition of physiological density? / Which state in India has the highest sex ratio?" (Data-based recall)