U.S. County Life Expectancy, 1989-2009, Ali Mokdad, April 2012

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Dr. Ali Mokdad from the Institute for Health Metrics and Evaluation (IHME) at the University of Washington presents the latest U.S. County Life Expectancy estimates from 1989 to 2009, at the Association of Health Care Journalists conference in Atlanta, GA, April 19, 2012.

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  • Population – US Adults ages 30+Age-standardized to 2000 Census distribution
  • Out of entire population
  • U.S. County Life Expectancy, 1989-2009, Ali Mokdad, April 2012

    1. 1. Latest life expectancy estimates bycounty reveal big differencesnationwideApril 19, 2012Ali H. Mokdad, PhDProfessor, Global Health UNIVERSITY OF WASHINGTON
    2. 2. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 2
    3. 3. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 3
    4. 4. How does US health compare globally?1. US spends the most on health and medical care in the world: 16.2% of GDP2. The vigorous debate on health reform follows three themes: • Lack of insurance • Rising costs • Poor outcomes3. But how are we actually doing? 4
    5. 5. Adult mortality trends: US, Australia, Japan Females Males 5
    6. 6. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 6
    7. 7. Life expectancy by countyIHME’s county life expectancy estimates take CDCmortality data and use small area measurement to find:• County trends by sex• County trends by race (black and white) 7
    8. 8. Life expectancy for men nationwide 1989 2009 1999 8
    9. 9. Life expectancy for women nationwide 1989 2009 1999 9
    10. 10. Within states, there are wide gapsWomen in Fairfax, Virginia, have some of the best lifeexpectancies in the US.Women in Greensville and Sussex have among theworst. 10
    11. 11. Urban progress Rates of change in life expectancy (in years), 1989-2009State County Men Women Black White Black WhiteNY NEW YORK 17.1 12 9 6.1CA SAN FRANCISCO 15.5 10.9 6.6 4.4 DISTRICT OFDC COLUMBIA 10.4 7.9 6.1 4.2GA FULTON 10.4 7.7 5.7 3.7FL MIAMI-DADE 9 6.7 6.5 4.6CA LOS ANGELES 8.3 6.2 6.1 4.3IL COOK 7.7 5.8 5.5 3.7TX HARRIS 7 5.5 3.9 2.6 UNITED STATES 7.4 4.2 4.7 2.2 11
    12. 12. Counties vs. nations: men, 2009 Greece (77.3) 90% of counties (66.3-77.1) Cuba (76.9) 87% of counties (66.3-76.9) Syria (72.5) 22% of counties (66.3-72.5) Iran (70.3) 6% of counties (66.3-70.4) 12
    13. 13. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 13
    14. 14. Women losing ground with each decadeLife expectancy for women in 661 counties eitherstopped dead or went backward from 1999 to 2009.For men, that happened in 166 counties. 14
    15. 15. Widening disparitiesGap between best- and worst-performing counties Year Men Women 1989 14.7 years 8.7 years 1999 15.4 years 9.3 years 2009 15.5 years 11.7 years 15
    16. 16. Best- and worst-performing counties, women 16
    17. 17. Black Americans have improved rapidly Between 1989 and 2009, life expectancy for black American men improved by 7.4 years, compared to 4.2 years for white men Gap between black men and white men shrinking 17
    18. 18. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 18
    19. 19. What are the drivers of these trends?Socio-economic inequalitiesLack of financial access to health carePoor quality of carePreventable causes of death 19
    20. 20. Socio-economic status and health • Compelling evidence that individual and community socio-economic status is a powerful determinant of health mediated through multiple mechanisms • Progress on increasing educational attainment, reducing poverty, decreasing discrimination, reducing inequality will have health benefits 20
    21. 21. Lack of financial access • Central topic in US health care reform • Lack of insurance clearly creates barriers for primary care, acute care, and long-term management of chronic diseases • Lack of insurance not distributed uniformly in the US 21
    22. 22. Quality of care• Large variations in quality of care across race/ethnicity, socio-economic status, and communities• Time from onset to intervention• Effective coverage 22
    23. 23. Preventable causes of death • Evidence for at least 12 risk factors is strong enough that the burden of disease for each can be assessed for US • Cohort studies and intervention trials provide strong evidence on the relative risks of death associated with these risk factors • Community surveys provide information on exposures 23
    24. 24. US deaths attributable to major risk factors,2005 Danaei et al., 2009 PLOS Medicine 24
    25. 25. Hypertension prevalenceAdults 30+, 2009 SBP ≥140 mm hg and/or self-reported antihypertensive medication use
    26. 26. High cholesterol prevalenceAdults 30+, 2009 Total serum cholesterol ≥240 mg/dL and/or prior diagnosis
    27. 27. Declining improvements in women Change in life expectancy, 1989-2009 Men Women 4.6 years 2.7 years 27
    28. 28. Lung cancer mortality rates in the US(per 100,000) 80 70 60 Lung Cancer Mortality Rate per 100,000 50 40 Males Females 30 20 10 0 1980 1985 1990 1995 2000 2005 2010 Year 28
    29. 29. Diabetes: prevalence, diagnosis, andtreatment, ages 35-64 29
    30. 30. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 30
    31. 31. What does this all add up to? 1. Regardless of the metric of population health, the US performs poorly relative to other high-income countries. 2. The US and most of its communities are steadily falling behind each year compared to high-income nations. 3. Females are falling behind faster than males in most parts of the country. 4. Large disparities exist across the US. 5. Disparities are worsening. 31
    32. 32. What should be done? • Provide local data and burden of disease • Focus on preventable risk factors • Engage medical providers in accountable care • Fund local strategies to cut risk factors 32
    33. 33. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 33
    34. 34. A tornado hits Oklahoma and makes headlines Photo by Niccolò Ubalducci 34
    35. 35. Health disparities should be news, tooPercentage of counties that are above the US nationalaverage for male life expectancyWhy should Iowans live longer than Oklahomans? 35
    36. 36. Lifespans: King County vs. Fulton County 36
    37. 37. Media’s role1. Keep all of us honest2. Focus the debate on what really matters3. Ask the hard questions: • Why do we have such disparities? • What are you doing about it? • Where are the success stories?4. Focus on science and ignore politics5. Get the word out 37
    38. 38. Outline How does US health compare globally? How do local health outcomes compare to each other and compare to global outcomes? Are disparities getting better or worse? What is driving these disparities? Summary and road map What can be the media’s role? Tools demonstration 38
    39. 39. Data visualizationsHighest and lowest life expectancy by county and sex (US), 1989-2009http://www.healthmetricsandevaluation.org/tools/data-visualization/highest-and-lowest-life-expectancy-county-and-sex-us-1989-2009Life expectancy by county and sex (US) with country comparison (Global),1989, 1999, 2009http://www.healthmetricsandevaluation.org/tools/data-visualization/life-expectancy-county-and-sex-us-country-comparison-global-1989-1999-2009Life expectancy by county and sex (US), 1989-2009http://www.healthmetricsandevaluation.org/tools/data-visualization/life-expectancy-county-and-sex-us-1989-2009 39
    40. 40. Thank YouFor more information:www.healthmetricsandevaluation.org 40

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