Health Services Life Expectancy Lecture 13

Results (local)

--Life expectancy varied significant across areas within the U.S. - especially for low- income individuals --New York, San Francisco, Dallas, and Detroit had substantial variation across these areas for low-income individuals but little variation for high-income individuals --In the bottom income quartile, Nevada, Indiana, and Oklahoma had the lowest life expectancies (<77.9 years)

Leading Causes of Death

1. Diseases of the Heart (heart disease) 2. Malignant Neoplasms (cancer) 3. Chronic Lower Respiratory Diseases 4. Accidents (unintentional injuries) Unintentional poisoning Unintentional motor vehicle traffic-related injuries 5. Cerebrovascular Disease (stroke)

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Dramatic increase in life expectancy since 1900 to now Still seeing disparities between non-hispanic blacks and non-hispanic whites

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Japan has highest life expectancy for females (86.6) Switzerland has highest for men (80.7)

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Once again, US lower life expectancy, higher spending

Trends in Life Expectancy

Trends varied significantly across geographic areas: • Hawaii, Maine, and Massachusetts had the largest gains in life expectancy (gaining >0.19 years annually) • Alaska, Iowa, and Wyoming experienced the largest losses in life expectancy (losing >0.09 years annually

Results (nationals)

• Higher income was associated with longer life at all income levels • Men in the bottom 1% of the income distribution at the age of 40 years had an expected age of death of 72.7 years/top 1% 87.3 years • Women in the bottom 1% of the income distribution at the age of 40 years had an expected age of death of 78.8 years/top 1% 88.9 years (Higher income associated with longer life)

Why is this?

•Administrative costs in the health sector are higher in the U.S. than any other country •Large inequality in health spending by little access for some and very high expenditures on health by others •The top 5% of spenders accounts for almost half of all health care spending in the U.S. •Unequal distribution in income (GINI coefficient)

Trends

•From 2013 to 2014, life expectancy increased for black males (0.2 years), Hispanic males (0.1), Hispanic females (0.2) and non-Hispanic black males (0.2), while decreasing for non-Hispanic white females (-0.1) •The difference in life expectancy between the non-Hispanic black and non- Hispanic white populations narrowed by 0.2 years from 3.8 years in 2013 to 3.6 years in 2014

Implications for Practice and Policy

•Health professionals could make targeted efforts to improve health among low-income populations in cities such as Las Vegas, Tulsa, and Oklahoma City •Strong association between geographic variation in life expectancy and health behaviors suggest policy interventions related to changing health behaviors •Uneven distribution in Social Security and Medicare payments

Age-Adjusted Death Rate

•In 2014 a total of 2,626,418 resident deaths were registered in the U.S. •The age-adjusted death rate, which accounts for the aging of the population, was 724.6 deaths per 100,000 U.S. standard population

Additional Correlations

•Life expectancy was negatively correlated with rates of smoking, obesity, and positively correlated with exercise rates among individuals in the bottom income quartile •Measures of health insurance coverage and spending were not significantly associated with life expectancy for individuals in the bottom income quartile

GINI Coefficient (2011)

•Most commonly used measure of income equality •Scoring (0 would mean income is perfectly, evenly distributed; A score of 1 means that a single has all the income in that society) ***(GINI=distribution of wealth in a country United states is the highest towards 1, meaning our wealth is not spread out equally. The more wealthy you are the better the health outcomes.)***

Trends

•Refers to the number of years a person is expected to live based on the statistical average •In 2014, life expectancy in the U.S. was 78.8 years (Males 76.4/Females 81.2) •Between 2004 and 2014, life expectancy at birth increased 1.4 years for males and 1.1 years for females

The Association between Income and Life Expectancy

•Study conducted by Chetty et. al (2016) •Importance - the relationship between income and mortality is well established but remains poorly understood •Objectives - to measure the level, trend, and geographics between income and life expectancy in the United States between 2001-2014 •Design - income data for the U.S. population were obtained from tax records. Mortality data obtained from Social Security Administration death records (Compared tax records against death records)

Link between health spending and life expectancy

•The U.S. - spends far more than any other country, yet the life expectancy is shorter than countries who spend less •All countries have followed an upward trajectory - more spending > longer life expectancy •Large inequality between the U.S. and other rich countries

Potential Explanations

•Who do low-income individuals who live in affluent, highly-educated cities live longer? • Public policies that restrict smoking •Greater funding for public services •Influence of others living in the vicinity that behave in healthier ways •Different characteristics, consistent with the larger share of immigrants in these areas