V. Key Issues: Population Health >> B. Public Health >> Determinants of Health >> Social Determinants of Health (last updated 10.16.17)
- 1 General Resources
- 2 Socioeconomic Status
- 3 Psychosocial Factors
- 4 Employment Status and Health
- 5 Working Conditions and Health
- 6 Living Conditions and Health
- CDC. Social Determinants of Health Resources. Includes Background, Data, Maps and Statistics, Organizations – International, Federal, State, and Local and Other Web Resources
- World Health Organization. Commission on Social Determinants of Health (2008 ).
Poverty, Income and Health
Official Poverty Rate
- Federal Poverty Level (FPL). The Census Bureau determines family income as a percentage of the Federal Poverty Level (FPL), which is a definition of poverty used primarily for statistical purposes. For example, FPL is used to estimate the number of Americans living in poverty each year.
- Federal Poverty Guidelines (FPG). The U.S. Department of Health and Human Services annually releases Federal Poverty Guidelines (FPG), which is a measure used for administrative purposes. For example, FPG is used to determine eligibility for federal programs such as Medicaid and the Supplemental Nutrition Assistance Program (SNAP).
- FPL vs. FPG. To learn more about the difference between FPL and FPG, click here.
- Historical Poverty Rates. HOW MANY AMERICANS WERE REALLY IN POVERTY IN 1947? ESTIMATES OF THE U.S. POVERTY POPULATION BETWEEN 1947 AND 1963 UNDER TWO CONTEMPORARY (1949 AND 1959) DEFINITIONS OF POVERTY. 10.10.99. This paper by Gordon Fisher provides historical estimates of poverty from 1947-1963 with references to estimates going back to 1900.
Alternative Poverty Measures
- Edsall, Thomas. How Poor Are the Poor? New York Times 3.25.15. Explains that U.S. poverty ranges from 4.8% (according to Christopher Jencks) to nearly five times that level (according to Center for American Progress), depending on how poverty is defined.
- Matthews, Dylan. The official poverty measure is garbage. The census has found a better way. Vox 9.16.15. Explains how poverty currently is defined and contrasts this to how the Supplemental Poverty Measure (SPM) does so. It shows that according to SPM, pre-tax/pre-transfer poverty has stayed remarkably steady since 1967–hovering around 25%, but that after accounting for government cash and non-cash transfers, poverty has declined from 25% in 1967 to 16% in 2012.
Data from the Panel Study of Income Dynamics (PSID) starting in 1968, the first year the data was collected, through 2003, show:
- The average spell of poverty lasts 2.8 years. The longest were among households headed by single women (3.1 years), African American men (2.7 years) and those with less than a high school diploma (2.6 years).
- Many individuals experience multiple spells of poverty, so that these spell lengths substantially understate the total time spent in poverty. Thirty-six percent of individuals return to poverty within four years of ending a spell.
- Increased time spent in poverty is associated with lower chances an individual will exit poverty, which ranges from 56% after one year poor to 13% for those in poverty for 7 or more years.
Research and Analysis
- Subramanian SV, Belli P, Kawachi I. The macroeconomic determinants of health. Annual Review of Public Health (2002) 23:287–302. [Abstract]
- Marmot M. The influence of income on health: views of an epidemiologist. Health Affairs (2002) 21(2):31–46. [Full Text]
- Rehkopf DH, Berkman LF, Coull B, et al. The non-linear risk of mortality by income level in a healthy population: US National Health and Nutrition Examination Survey mortality follow-up cohort, 1988–2001. BMC Public Health (2008) 8:383. [Abstract]
- Muennig P, Franks P, Jia H, et al. The income-associated burden of disease in the United States. Social Science and Medicine 2005; 61:2018–26. [Abstract]
- Cristia, Julian P. The Empirical Relationship Between Lifetime Earnings and Mortality. Congressional Budget Office. August 2007.
- Bosworth, Barry, Gary Burtless, and Kan Zhang (2016). Later retirement, inequality in old age, and the growing gap in longevity between rich and poor. Brookings Institution. Female life expectancy at age 50 for those with incomes in bottom 10% was identical for those born in 1920 and 1940 (80.4 years), but for those in top 10%, LE@50 rose from 84.1 to 90.5. For men, LE@50 rose slightly for bottom 10% from 74.3 years to 76 years while for top 10% it rose from 79.3 to 88 years.
- Rector, Robert and Rachel Sheffield, ‘‘Air Conditioning, Cable TV, and an Xbox: What is Poverty in the United States Today,’’ The Heritage Foundation (July 19, 2011).
- Eli, Shari and Nicholas Li. Caloric Requirements and Food Consumption Patterns of the Poor. NBER Working Paper No. 21697. Issued in November 2015. How much do calorie requirements vary across households and how do they affect food consumption patterns? Since caloric intake is a widely-used indicator of poverty and welfare, investigating changes in caloric requirements and food consumption patterns is important, especially for the poor. Combining anthropometric and time-use data for India, we construct a quantitative measure of individual and household caloric requirements. We then link our estimates of caloric requirements with consumption data to examine how caloric requirements coupled with household expenditures shape food demand. Our applications include the measurement of hunger and the role of caloric requirements in explaining food consumption puzzles related to household-scale and changes in caloric intake over time.
- Household Percentile Ranking (New York Times). Enter your household income and see how you rank in 344 zones across the country; see summary table for selected household incomes ranging from $5,000 (bottom 2% to 383,001 (top 1%).
Wealth and Health
Research and Analysis
- Piketty, Thomas. Capital in the 21st Century. 2014. Argues that since growth in capital (5% annually) invariably exceeds growth in the economy (~3% annually), wealth inequality inevitably will grow. He uses data from 1810-2010 to make this case.
- Edward N. Wolff, Top Heavy (2nd ed. 2001). In 1929, before the stock market crash, the top 1 percent controlled 44.2 percent of the nation’s wealth.
- Louisa Kroll and Kerry A. Dolan, ‘‘Inside the List: Facts and Figures,’’ Forbes, Sept. 21, 2011, available at http://www.forbes.com/sites/luisakroll/2011/09/21/inside-the-list-facts-andfigures/.The Forbes 400 own approximately $1.53 trillion worth of assets, or almost $4 billion average.
- Wolff, Edward N. ‘‘Recent Trends in Household Wealth in the United States: Rising Debt and the Middle-Class Squeeze — an Update to 2007,’’ Levy Economics Institute of Bard College, Working Paper 589 (June 2007). The top 10 percent own approximately 75 percent of the nation’s wealth, and the top 1 percent own nearly half of that 75 percent.
- Flow of Funds Accounts of the U.S. (wealth statistics issued quarterly by the Federal Reserve Board).
- Household Net Worth Percentile, 2004 (Decisions Based on Evidence). A summary table for selected household net worths ranging from $50,000 (top 60%) to $6 million (top 1%), as reported in Frank, Robert. (2007). The Wealth Report.
Education and Health
Occupation and Health
Income Inequality and Health
- McCloskey, Deirdre. Measured, Unmeasured, Mismeasured, and Unjustified Pessimism: A Review Essay of Thomas Piketty’s
Capital in the Twenty-First Century. Erasmus Journal of Philosophy and Economics (2015).
- Wilkinson, Richard. How economic inequality harms societies. Provides cross-national and cross-state statistics linking inequality to various measures of adverse outcomes.
- Wilkinson, Richard and Kate Pickett. The Spirit Level: Why Greater Equality Makes Societies Stronger. Countries and times with lower inequality fare better on virtually every published index of health, well-being and quality of life.
- Daron Acemoglu on Inequality
- Avi Feller and Chad Stone, ‘‘Top 1 Percent of Americans Reaped Two-Thirds of Income Gains in Last Economic Expansion,’’ Center on Budget and Policy Priorities (Sept. 9, 2009), available at http://www.cbpp.org/cms/index.cfm?fa=view&id=2908. In 1928, the top 1 percent in the country earned 23.9 percent of all income.
- Stephen Rose. The Myth of Income Decline. How a flawed study [Piketty and Saez. Income Inequality in the United States, 1913-1998] based on IRS data, since corrected, continues to generate the idea that only the top one percent of Americans saw gains in income over the past 30 years, while 90 percent of Americans saw their incomes decline.
Racial/ethnic inequality and health
Employment Status and Health
Inverse Relationship Between Unemployment and Mortality
- Cutler/Huang/LLeras-Muney (2016). In their analysis of 100 birth-cohorts in 32 countries to determine how economic growth increases mortality, the authors found that small, but not large, booms increase contemporary mortality. Yet booms from birth to age 25, particularly those during adolescence, lower adult mortality. A simple model can rationalize these findings if economic conditions differentially affect the level and trajectory of both good and bad inputs into health. Indeed, air pollution and alcohol consumption increase in booms. In contrast, booms in adolescence raise adult incomes and improve social relations and mental health, suggesting these mechanisms dominate in the long run. Overall, two-thirds of the adverse effect on mortality effect can be attributed to air pollution alone.
- Ruhm (2000). A U.S. study found that total mortality and eight of the ten sources of fatalities examined are shown to exhibit a procyclical fluctuation, with suicides representing an important exception. The variations are largest for those causes and age groups where behavioral responses are most plausible, and there is some evidence that the unfavorable health effects of temporary upturns are partially or fully offset if the economic growth is long-lasting. An accompanying analysis of micro data indicates that smoking and obesity increase when the economy strengthens, whereas physical activity is reduced and diet becomes less healthy.
- Granados & Ionides (2017). A study of 27 European countries just before and during the Great Recession (2007-2009) found that a one-percentage-point increase in the unemployment rate is associated with an 0.5 percent decline in the overall age-adjusted mortality rate. “we conclude that in the European experience of the past 20 years, recessions, on average, have beneficial short-term effects on mortality of the adult population.” The authors further found that a one-percentage-point increase in the unemployment rate is associated with a one percent lower mortality rate for respiratory illnesses, as well as reductions in mortality for cardiovascular disease and heart conditions, which are known to be sensitive to air pollution.
- Gerdtham & Ruhm (2006). A study of 23 (OECD) countries over the 1960-1997 period showed that total mortality and deaths from several common causes rise when labor markets strengthen.
- Frakt (2017) notes that “during recessions, people without jobs may have more time to sleep and exercise and may eat more healthfully. One study found that higher unemployment is associated with lower rates of obesity, increased physical activity and a better diet. On the other hand, suicides increase during economic downturns.”
- Lam & Pierard (2015). We examine the relationship between total mortality, deaths due to motor vehicle accidents, cardiovascular disease and measures of business cycles for the USA, using a time-varying parameter model for the periods 1961–2010. We first present a theoretical model to outline the transmission mechanism from business cycles to health status, to motivate our empirical framework and to explain why the relationship between mortality and the economy may have changed over time. We find overwhelming evidence of structural breaks in the relationship between mortality and business cycles over the sample period. Overall, the relationship between total mortality, cardiovascular mortality and the economy has become less procyclical over time and even countercyclical in recent times for certain age groups. Deaths due to motor vehicle accidents have remained strongly procyclical. Using drugs and medical patent data and data on hours worked, we argue that important advances in medical technology and changes in the effects that working hours have on health are important reasons for this time-varying relationship.