5.2 Trends in mortality and life expectancy

Mortality trends and life expectancy have drastically improved globally since the 1900s. The average lifespan jumped from 30 to 70 years, thanks to better healthcare, living conditions, and public health measures. However, significant regional differences persist due to varying economic and social factors.

Understanding these trends is crucial for grasping population dynamics. The epidemiological transition theory explains how societies shift from high mortality from infectious diseases to lower mortality from chronic conditions as they develop. This shift shapes demographic patterns and healthcare needs worldwide.

Mortality Trends and Life Expectancy

Global Improvements and Regional Variations

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• Mortality rates and life expectancy improved significantly worldwide since early 20th century varied in pace and timing across regions and countries
• Epidemiological transition theory explains shift from high mortality due to infectious diseases to lower mortality from chronic diseases as societies develop
• Global average life expectancy increased from ~30 years in 1900 to over 70 years in 2020 substantial regional differences remain
• Infant and child mortality rates declined dramatically in most parts of the world contributed significantly to overall life expectancy increases
• Compression of mortality phenomenon describes concentration of deaths at older ages as life expectancy increases
• Regional variations in mortality trends reflect differences in:
  • Economic development
  • Healthcare systems
  • Social conditions
• National-level mortality trends often show periods of stagnation or reversal due to specific historical events:
  • Wars (World War II)
  • Epidemics (1918 influenza pandemic)
  • Economic crises (Great Depression)

Theoretical Frameworks and Demographic Concepts

• Epidemiological transition theory stages:
  1. Age of pestilence and famine
  2. Age of receding pandemics
  3. Age of degenerative and man-made diseases
  4. Age of delayed degenerative diseases
• Compression of mortality components:
  • Rectangularization of survival curve
  • Increase in modal age at death
  • Decrease in variability of age at death
• Life expectancy calculation methods:
  • Period life expectancy: based on current mortality rates
  • Cohort life expectancy: follows actual birth cohorts over time
• Mortality measures:
  • Crude death rate: $CDR = \frac{\text{Number of deaths in a year}}{\text{Mid-year population}} \times 1000$
  • Age-specific mortality rate: $ASMR = \frac{\text{Number of deaths in age group}}{\text{Population in age group}} \times 1000$
  • Standardized mortality ratio: $SMR = \frac{\text{Observed deaths}}{\text{Expected deaths}} \times 100$

Factors Influencing Mortality Decline

Medical and Public Health Advancements

• Medical knowledge and technology advancements reduced mortality from infectious diseases and other health conditions:
  • Vaccinations (smallpox eradication)
  • Antibiotics (penicillin discovery)
  • Improved surgical techniques (minimally invasive surgeries)
• Public health interventions crucial in reducing mortality especially in developing countries:
  • Improved sanitation (sewage systems)
  • Clean water supply (water treatment plants)
  • Health education programs (anti-smoking campaigns)
• Government policies and investments enhanced population health outcomes:
  • Healthcare infrastructure development (building hospitals)
  • Improved healthcare accessibility (universal healthcare systems)

Socioeconomic and Educational Factors

• Socioeconomic development contributed to lower mortality rates and increased life expectancy:
  • Rising living standards (improved housing conditions)
  • Better nutrition (increased access to diverse food sources)
  • Improved working conditions (occupational safety regulations)
• Declining fertility rates indirectly contributed to improved child survival and maternal health:
  • Reduced strain on maternal health
  • Increased resources available per child
• Educational attainment particularly for women strongly associated with improved health outcomes:
  • Enhanced health literacy
  • Better decision-making regarding health behaviors
• Technological innovations in food production and distribution reduced malnutrition and famine-related mortality:
  • Green Revolution (high-yield crop varieties)
  • Improved food preservation and transportation methods

Disparities in Mortality and Life Expectancy

Socioeconomic and Demographic Disparities

• Socioeconomic gradients in mortality persist within and between countries:
  • Higher income and education levels generally associated with lower mortality rates and longer life expectancy
  • Example: Life expectancy gap between highest and lowest income quartiles in the US ~10-15 years
• Gender differences in life expectancy observed globally:
  • Women typically live longer than men
  • Gender gap varies across cultures and time periods (ranges from 2-10 years)
• Racial and ethnic disparities in mortality and life expectancy prevalent in many countries:
  • Reflect historical and ongoing social inequalities
  • Example: In the US, life expectancy for Black population ~4 years lower than for White population
• "Deaths of despair" concept highlights increasing mortality rates among certain demographic groups:
  • Causes include suicide, drug overdose, and alcohol-related deaths
  • Particularly observed in developed countries (US middle-aged, non-Hispanic white population)

Healthcare Access and Environmental Factors

• Access to healthcare services and quality of care vary significantly based on socioeconomic status:
  • Contributes to mortality disparities
  • Example: Rural-urban divide in healthcare access in many countries
• Environmental justice issues disproportionately affect low-income and minority communities:
  • Exposure to pollution (industrial zones near low-income neighborhoods)
  • Hazardous living conditions (lack of safe drinking water)
• Cultural factors contribute to mortality differences across population subgroups:
  • Health beliefs (traditional medicine practices)
  • Behaviors (dietary habits)
  • Lifestyle choices (physical activity levels)

Future Mortality Changes and Population Dynamics

Population Aging and Demographic Dividend

• Continued mortality rate improvements expected to lead to further population aging:
  • Significant implications for healthcare systems (increased demand for geriatric care)
  • Social services (pension systems sustainability)
  • Economic structures (changing labor force composition)
• Demographic dividend concept highlights potential economic benefits of declining mortality rates:
  • Particularly when coupled with falling fertility rates
  • Window of opportunity for economic growth (working-age population increases relative to dependents)

Life Course Changes and Health Projections

• Increasing life expectancy may lead to changes in life course patterns:
  • Delayed retirement (extending working years)
  • Extended periods of active aging (increased participation in social and economic activities)
• Compression of morbidity hypothesis suggests future mortality improvements may be accompanied by:
  • Reduction in the period of disability or ill health at the end of life
  • Potential for healthier aging and reduced healthcare costs
• Potential emergence of new health challenges could impact future mortality trends:
  • New infectious diseases (COVID-19 pandemic)
  • Antimicrobial resistance (superbugs)
• Climate change and environmental degradation may introduce new mortality risks:
  • Extreme weather events (heat waves, floods)
  • Altered disease patterns (expansion of tropical disease ranges)

Technological Advancements and Future Scenarios

• Advancements in biotechnology and personalized medicine could lead to more rapid life expectancy improvements:
  • Gene therapy
  • Targeted cancer treatments
• Potential exacerbation of health inequalities due to uneven access to advanced medical technologies
• Scenarios for future mortality trends:
  • Optimistic: continued linear increases in life expectancy
  • Pessimistic: plateauing or reversal due to obesity epidemic or environmental factors
  • Uncertain: impact of artificial intelligence and robotics on healthcare and mortality