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Background: The United States health care debate has focused on the nation's uniquely high rates of lack of insurance and poor health outcomes relative to other high-income countries. Large disparities in health outcomes are well-documented in the US, but the most recent assessment of county disparities in mortality is from 1999. It is critical to tracking progress of health reform legislation to have an up-to-date assessment of disparities in life expectancy across counties. US disparities can be seen more clearly in the context of how progress in each county compares to international trends. Methods: We use newly released mortality data by age, sex, and county for the US from 2000 to 2007 to compute life tables separately for each sex, for all races combined, for whites, and for blacks. We propose, validate, and apply novel methods to estimate recent life tables for small areas to generate up-to-date estimates. Life expectancy rates and changes in life expectancy for counties are compared to the life expectancies across nations in 2000 and 2007. We calculate the number of calendar years behind each county is in 2000 and 2007 compared to an international life expectancy time series. Results: Across US counties, life expectancy in 2007 ranged from 65.9 to 81.1 years for men and 73.5 to 86.0 years for women. When compared against a time series of life expectancy in the 10 nations with the lowest mortality, US counties range from being 15 calendar years ahead to over 50 calendar years behind for men and 16 calendar years ahead to over 50 calendar years behind for women. County life expectancy for black men ranges from 59.4 to 77.2 years, with counties ranging from seven to over 50 calendar years behind the international frontier; for black women, the range is 69.6 to 82.6 years, with counties ranging from eight to over 50 calendar years behind. Between 2000 and 2007, 80% (men) and 91% (women) of American counties fell in standing against this international life expectancy standard. Conclusions: The US has extremely large geographic and racial disparities, with some communities having life expectancies already well behind those of the best-performing nations. At the same time, relative performance for most communities continues to drop. Efforts to address these issues will need to tackle the leading preventable causes of death. [ABSTRACT FROM AUTHOR]

Background: There has been substantial research on psychosocial and health care determinants of health disparities in the United States (US) but less on the role of modifiable risk factors. We estimated the effects of smoking, high blood pressure, elevated blood glucose, and adiposity on national life expectancy and on disparities in life expectancy and disease-specific mortality among eight subgroups of the US population (the ''Eight Americas'') defined on the basis of race and the location and socioeconomic characteristics of county of residence, in 2005. Methods and Findings: We combined data from the National Health and Nutrition Examination Survey and the Behavioral Risk Factor Surveillance System to estimate unbiased risk factor levels for the Eight Americas. We used data from the National Center for Health Statistics to estimate age-sex-disease-specific number of deaths in 2005. We used systematic reviews and meta-analyses of epidemiologic studies to obtain risk factor effect sizes for disease-specific mortality. We used epidemiologic methods for multiple risk factors to estimate the effects of current exposure to these risk factors on death rates, and life table methods to estimate effects on life expectancy. Asians had the lowest mean body mass index, fasting plasma glucose, and smoking; whites had the lowest systolic blood pressure (SBP). SBP was highest in blacks, especially in the rural South-5-7 mmHg higher than whites. The other three risk factors were highest in Western Native Americans, Southern low-income rural blacks, and/or low-income whites in Appalachia and the Mississippi Valley. Nationally, these four risk factors reduced life expectancy at birth in 2005 by an estimated 4.9 y in men and 4.1 y in women. Life expectancy effects were smallest in Asians (M, 4.1 y; F, 3.6 y) and largest in Southern rural blacks (M, 6.7 y; F, 5.7 y). Standard deviation of life expectancies in the Eight Americas would decline by 0.50 y (18%) in men and 0.45 y (21%) in women if these risks had been reduced to optimal levels. Disparities in the probabilities of dying from cardiovascular diseases and diabetes at different ages would decline by 69%-80%; the corresponding reduction for probabilities of dying from cancers would be 29%-50%. Individually, smoking and high blood pressure had the largest effect on life expectancy disparities. Conclusions: Disparities in smoking, blood pressure, blood glucose, and adiposity explain a significant proportion of disparities in mortality from cardiovascular diseases and cancers, and some of the life expectancy disparities in the US. [ABSTRACT FROM AUTHOR]

Majid Ezzati and colleagues analyze US county-level mortality data for 1961 to 1999, and find a steady increase in mortality inequality across counties between 1983 and 1999. [ABSTRACT FROM AUTHOR]

OBJECTIVE -- The aim of this study was to increase the cross-state comparability of diabetes mortality statistics related in the U.S. and Mexico. RESEARCH DESIGN AND METHODS -- We used multinomial logistic regression to estimate the effects of individual and community factors on a death for which diabetes was recorded as one of the multiple contributing causes of death (MCD) being assigned to diabetes as the underlying cause of death, (UCD) versus assignment to cardiovascular, other noncommunicable, or communicable diseases. We used the model to estimate state-level diabetes death rates that are standardized in the individual and community factors. RESULTS -- Deaths with diabetes as one of the MCD were more likely to be assigned to cardiovascular causes as the UCD if they occurred in hospitals or if an autopsy was performed and if the decedents were from states with higher BMI and systolic blood pressure, were more educated, or had insurance. Adjusting for individual- and community-level factors substantially increased the cross-state correlation of diabetes as the UCD and diabetes as one of the MCD mortality rates. The adjustment also reduced the number of direct diabetes deaths by 10% in the U.S. and by 24% in Mexico. In the U.S., deaths with diabetes as the UCD declined most in Utah, New Mexico, New Jersey, and Louisiana and increased in California and Hawaii. In Mexico, the numbers of adjusted diabetes deaths were smaller than those observed in all states by 3-34%. An additional 126,300 deaths due to ischemic heart disease and stroke in the U.S. and 19,497 in Mexico were attributable to high blood glucose. CONCLUSIONS -- There is a need to improve the comparability of diabetes cause-of-death assignment, especially in relation to cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Abstract: The Eight Americas Study divides the U.S. population into eight distinct groups with different epidemiologic patterns and mortality experience. The Eight Americas are Asians (America 1), below-median-income whites living in the Northland (America 2), middle America (America 3), poor whites living in Appalachia and the Mississippi Valley (America 4), Native Americans living on reservations in the West (America 5), black middle-America (America 6), poor blacks living in the rural South (America 7), and blacks living in high-risk urban environments (America 8). Life expectancy for males in America 8 is 21 years lower than life expectancy for females in America 1. For males, the gap between America 1 and America 8, 16.1 years, is as large as the gap between Iceland with the highest male life expectancy in the world and Bangladesh. Even in Americas 5, 6, 7, and 8, U.S. child mortality is in the middle of the range defined by the Organization of Economic Cooperation and Development (OECD) countries. For young and middle-aged males and females, however, mortality experience in the disadvantaged Americas is up to two times worse than the worst OECD country. The enormous excess of young and middle-aged mortality is largely due to chronic disease death. Based on the World Health Organization Comparative Risk Assessment project, we expect the major risks in the United States to be tobacco, alcohol, obesity, blood pressure, and cholesterol. Risk factor analysis using Behavioral Risk Factor Surveillance System data for the Eight Americas suggests that the pattern for tobacco, alcohol, and obesity is distinct for each America. Currently available data in the public domain do not provide an adequate basis to assess levels of blood pressure and cholesterol in the Eight Americas. To tackle disparities in the United States, public health will need to increase its focus on chronic diseases in young and middle-aged Americans. In particular, if blood pressure and cholesterol are confirmed as major contributors to current mortality patterns, innovative strategies such as the Polypill™ and unique individual and population approaches need to be explored. [Copyright &y& Elsevier]

Background: The gap between the highest and lowest life expectancies for race-county combinations in the United States is over 35 y. We divided the race-county combinations of the US population into eight distinct groups, referred to as the "eight Americas," to explore the causes of the disparities that can inform specific public health intervention policies and programs.Methods and Findings: The eight Americas were defined based on race, location of the county of residence, population density, race-specific county-level per capita income, and cumulative homicide rate. Data sources for population and mortality figures were the Bureau of the Census and the National Center for Health Statistics. We estimated life expectancy, the risk of mortality from specific diseases, health insurance, and health-care utilization for the eight Americas. The life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was 20.7 y in 2001. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 y for males (Asians versus high-risk urban blacks) and 12.8 y for females (Asians versus low-income southern rural blacks). Mortality disparities among the eight Americas were largest for young (15-44 y) and middle-aged (45-59 y) adults, especially for men. The disparities were caused primarily by a number of chronic diseases and injuries with well-established risk factors. Between 1982 and 2001, the ordering of life expectancy among the eight Americas and the absolute difference between the advantaged and disadvantaged groups remained largely unchanged. Self-reported health plan coverage was lowest for western Native Americans and low-income southern rural blacks. Crude self-reported health-care utilization, however, was slightly higher for the more disadvantaged populations.Conclusions: Disparities in mortality across the eight Americas, each consisting of millions or tens of millions of Americans, are enormous by all international standards. The observed disparities in life expectancy cannot be explained by race, income, or basic health-care access and utilization alone. Because policies aimed at reducing fundamental socioeconomic inequalities are currently practically absent in the US, health disparities will have to be at least partly addressed through public health strategies that reduce risk factors for chronic diseases and injuries. [ABSTRACT FROM AUTHOR]

Background: Coronary heart disease (CHD) represents the largest share of cardiovascular disease in the United States, but there are conspicuous discrepancies between CHD and total cardiovascular death rates across the states, possibly due in part to variations in physician assignment of causes of death. Our aim was to identify exogenous individual- and community-level predictors of cause-of-death assignment and variability and to use these predictors to improve the comparability of CHD mortality estimates across states., Methods and Results: We performed a multinomial logistic regression analysis to estimate the effect of individual- and community-level factors on the likelihood of a death being certified as 1 of 3 ill-defined clusters (general atherosclerosis and unspecified heart disease, heart failure, and cardiac arrest) relative to being certified as CHD. The individual-level variables were the decedent's race, sex, age, education, and place of death; the community-level variable was the number of cardiologists per capita. We used the model to estimate state-level CHD rates that are standardized with regard to the levels of individual- and community-level determinants of cause-of-death assignment. Decedents who died in hospitals and in counties with more cardiologists per capita were more likely to be assigned to CHD than to the ill-defined categories, as were white males relative to other race-sex combinations. Adjustment for these factors resulted in substantially improved correlation between death rates for CHD and all cardiovascular causes. Increases in CHD death rates across states after adjustment for external predictors of cause-of-death assignment ranged from 2% (North Dakota) to 72% (Washington, DC); New York had a decrease (1%) in CHD death rates after adjustment. Nationally, CHD death rates increased 10% for males and 15% for females. The total number of deaths in 2001 attributed to CHD in patients over 30 years of age rose from 433,625 to 489,836 after adjustment., Conclusions: Greater presence of medical knowledge at the time of death, reflected by place of death and cardiologists per capita, reduces the use of the ill-defined cardiovascular clusters. Racial and gender effects on CHD assignment may reflect disparities in access to care and quality of care. By adjusting for differentials in these parameters, a comparable and consistent set of CHD mortality estimates can be created. The role of the exogenous predictors in validity and comparability of cause-of-death statistics should be confirmed in carefully designed validation autopsy studies.