“Sex differences in morbidity and mortality.” Demography, 42(2), 189-214.

- The gender paradox in health refers to the fact that women have worse self-rated health and more hospitalization episodes than men in early and middle age, but are less likely to die at each age

-Researchers examine whether or not this paradox is true, and if so, why

Some possible explanations

1. Sex differences in the distribution of chronic conditions;

-women may be more likely to suffer from conditions, such as headaches and arthritis, that result in poorer self-rated health but contribute relatively little to mortality,

-whereas men may be more likely to have conditions such as cardiovascular disease that have relatively large effects on the probability of death

2. Women may simply report worse health than men on surveys

Findings

Use data from the National Health Interview Survey (1986-1994; 1997-2001)

- Women do indeed report worse self-rated health than men but are less likely to die

- Men and women with the same health conditions report similar self-rated health

- This suggests that differences in self-reports are due to differing distributions of disease, rather than reporting differences

- Women are more likely to get chronic but not fatal conditions (headaches, arthritis, depression) whereas men more likely to get fatal conditions

- Men are also more likely to die from smoking-related diseases than women with the same diseases

- Specifically, 50% of sex difference in mortality explained by 14 chronic health conditions,

with 25% of this difference explained by men being more likely than women to have conditions that have larger effects on mortality and

75% of it explained by men having greater probability of dying than women with same chronic conditions

“Inequality in life spans and a new perspective on mortality convergence across industrialized countries.” Population and Development Review, 31(4), 645-674.

- Authors want to know whether the age pattern of mortality has converged across industrialized countries as life expectancy has

- Examine the standard deviation of ages at death past age 10 (S₁₀)

- Also examine within-group versus between group variation

- Analysis of 7 industrialized countries reveals only a slight decrease in the variation of death rates since 1960

  - The US has the highest S₁₀ of the countries examined

- What accounts for high S₁₀ in the US?

- Increasing differentials in life expectancy for males and females

- In addition, males have greater variation in mortality rates than females

- Race doesn’t seem to be driving high US S₁₀

- However, blacks have greater variation than whites

- SES (measured by dichotomized education and income) doesn’t account for higher US S₁₀

- However, disadvantaged groups have higher variance than advantaged ones

- Although authors did not find clear patterns of what’s driving S₁₀, they argue that it remains a useful measure for revealing life-span inequality (which may be the most fundamental form of inequality in the human population), as well as for forecasting future mortality, planning for work, saving, and investing, and for determining Old Age Support policies

Longevity by County in the US

From 1983-199

LE droped significantly in 11 counties for men and 180 for women

why?

consistent with

smoking

high blood pressure

obesity

 “Cumulative disadvantage and health: Long-term consequences of obesity?” American Sociological Review, 68, 707-729.

Paper investigates the long-term risks of obesity on health inequality in adulthood, drawing on cumulative disadvantage theory

Cumulative disadvantage theory proposes that early advantages or disadvantages are critical to how individuals within cohorts become differentiated over time

- A theoretical consideration that has typically been overlooked is that health disadvantages are potentially reversible

- Are there compensatory mechanisms that can reduce the effects of previous disadvantages?

- A second limitation of empirical work is the issue of selective survival

4 research questions addressed in paper:

1) Is obesity associated with physical disability?

2) If obesity is related to disability, is the effect of obesity more substantial during certain periods of the life course?

3) Does the timing of obesity influence health inequality?

4) Can compensatory mechanisms reduce or eliminate the effects of obesity on health decline?

Findings

- Evidence for both lagged and immediate effects of obesity on lower body disability

- Only modest effects of obesity on upper body disability

- Transitioning from the obese to the non-obese state between waves 1 and 2 did not reduce the risk of lower body disability compared to those who did not transfer

- No evidence for exiting risk on health

- However, regular exercise did reduce the effect of obesity on disability

- Evidence for compensatory mechanism that occurs via exercise but not via weight loss

- Effects of obesity reduces the independent effects of socioeconomic status on health measures

Etimate that combined sex life expectancy in the US would equal 86.1 in 2065, whereas official estimates suggested it would equal 80.7

  “Measuring the global burden of disease and epidemiological transitions: 2002-2030. Annals of Tropical Medicine and Parasitology, 100(5), 481-499.

- The aim of the Global Burden of Disease Study was to assess global patterns of disease burden and recommend interventions

- This articles utilizes a measure called the Disability Adjusted Life Year (DALY)

- Composed of years of life lost due to premature death and years of life lived with disability

Diseases classified into 3 groups

   - Group I: Communicable diseases

   - Group II: Non-communicable diseases

   - Group III: Injuries

- Find that globally ½ of deaths among 15-59 year olds in 2002 due to Group II and 1/3 due to Group I

- If HIV is removed, only 1/5 of death due to Group I

- Group I deaths predominate in low and middle income countries (esp. in Africa)

- Ten leading causes of disease differ in low/middle income countries versus high income countries

- 3 main causes of death globally are cardiac diseases, stroke, and respiratory diseases

- In high income countries, depression, heart disease, and cardiovascular disease are the three main causes of loss of productive life years

- In low/middle income countries, perinatal conditions, respiratory infections, and AIDS are the three main causes of loss of productive life years

- These diseases rank much higher in terms of years of life lost than the leading causes in high income countries

- People in developing countries not only have lower life expectancies, but they also live a larger proportion of their lives in poor health

Small number of risk factors account for a large percentage of mortality and disease burden

These include poor nutrition, unsafe sex, smoking, and alcohol use

- Policies and programs that target these risk factors could reduce multiple causes of poor health

- Over the next 30 years, authors predict decrease in overall Group I diseases, except for HIV/AIDS

Also predict increase number of deaths caused by Group II and III diseases

Smoking, BMI, and mortality

BMI

Increase mortality @ BMI 15 or less.

Mortality declines until BMI = 20

relatively stable until BMI = 35

then mortality increases againg (but never as high as the very underweight)

HR of death is higher at underweight and class 2/3 obese compared to normal weight, overweight, obese.

No difference in HR between normal weight, overweight and class 1 obese.

Smoking accounts for a many fold percent increase in death than obest cat 2/3

“Causes and consequences of mortality decline in less developed countries during the twentieth century.” In Population and Economic Change in Developing Countries. Edited by Richard A. Easterlin. Pp. 289-360.

Less developed countries have experienced dramatic increases in life expectancy since 1940

Largest absolute declines in mortality have occurred to those below age 5 and above age 40

2 objectives of paper are

1. to identify the factors responsible for these mortality improvements and

2. to begin tracing the effects of these improvements on demographic and economic processes

3 possible causes of reduced mortality:

1. by-product of social and economic development,

2. social policy,

3. technical changes

- Preston demonstrates that individual income does play a significant role in reducing individual mortality

- Decrease in infectious diseases (respiratory, diarrhoeal, and malaria) primary contributor to decrease in mortality

- Poor nutrition may contribute to increase risk of infection and death from disease

- Preventative measures have been more effective than curative ones in decreasing infectious disease fatalities, even though improvements in water supply are occurring much slower in LDCs than they did in MDCs

- Mortality reductions have not merely been a by-product of socioeconomic development, but rather major structural changes have occurred in the relationship between mortality and other indices of development

- Structural factors that are exogenous to national levels of income, calorie consumption, and literacy (such as changes in government investment in health care and technological advances) account for about ½ of the gains in life expectancy between 1940 and 1970

- Structural factors have contributed the most in Latin America and the least in Africa

Consequences of mortality reductions

- Changes in mortality and fertility both influence population size by affecting the total number of births

- Populations may respond to decreased mortality by declines in crude birth rates via quasi-biological effects (proportion of population in childbearing years reduced, extending breastfeeding due to survival of child) and behavioral effects

- However, data indicates that birth rates have not declined much in response to mortality declines in LDCs

- Mortality decline hasn’t really contributed to changes in net migration

- Mortality decline may increase labor production of a population, or it may lead to economic decline due to decreased availability of resources

- Unclear whether shifts in mortality versus fertility should have different effects on economic growth

- Malenbaum (1970) interestingly argues that mortality decline gives people a sense that they can control their own destiny, which contributes to increased labor production

“The timing and pace of health transitions around the world.” Population and Development Review, 31(4), 741-764.

Aim of article is to describe regional and global life expectancy gains across time and space

3 divergent trends in life expectancy since the early 1980s

1. Most countries, even those with already high levels of life expectancy, continued to add years at a fairly robust pace

2. A second group of countries that were previously part of the Soviet Union saw a stagnation or slight decline in life expectancy, particularly among males

3. A third group of countries, primarily in central and southern Africa where HIV/AIDS in rampant, saw a dramatic decrease in life expectancy by as much as 19 years

- It is often difficult to determine when a health transition begins

- Population composition can greatly affect death rates

- For example, in GB and FR in the mid-1800s, death rates at the national level appeared to be stagnant, but in reality death rates were decreasing while greater numbers of people were migrating to urban areas (where death rates were higher)

- Countries that began the health transition prior to 1850 experienced slower gains in life expectancy than countries that began the transition more recently

- It is difficult to generalize common causes of life expectancy gain because countries have experienced gains under very diverse circumstances

- Gains have been made under differing stages of economic development, historical conditions, and levels of literacy and education, among other things

- Riley suggests that rather than studying mortality transitions in one country during one period in time, a more comparative approach is necessary to test specific explanations that may be relevant for reducing mortality in countries where life expectancy is still low

Levels of mortality by age

- Vallin created graph of mortality in France by age 1720-1914

- Finds that decrease in mortality happened at pretty much all ages

- Main exception: death rates among young adults higher in 1877-1881 than in 1820-1829

- Most likely due to migrating to cities

Cutler and miller 2004