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      Geographic and Racial Variation in Premature Mortality in the U.S.: Analyzing the Disparities

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          Abstract

          Life expectancy at birth, estimated from United States period life tables, has been shown to vary systematically and widely by region and race. We use the same tables to estimate the probability of survival from birth to age 70 (S 70), a measure of mortality more sensitive to disparities and more reliably calculated for small populations, to describe the variation and identify its sources in greater detail to assess the patterns of this variation. Examination of the unadjusted probability of S 70 for each US county with a sufficient population of whites and blacks reveals large geographic differences for each race-sex group. For example, white males born in the ten percent healthiest counties have a 77 percent probability of survival to age 70, but only a 61 percent chance if born in the ten percent least healthy counties. Similar geographical disparities face white women and blacks of each sex. Moreover, within each county, large differences in S 70 prevail between blacks and whites, on average 17 percentage points for men and 12 percentage points for women. In linear regressions for each race-sex group, nearly all of the geographic variation is accounted for by a common set of 22 socio-economic and environmental variables, selected for previously suspected impact on mortality; R 2 ranges from 0.86 for white males to 0.72 for black females. Analysis of black-white survival chances within each county reveals that the same variables account for most of the race gap in S 70 as well. When actual white male values for each explanatory variable are substituted for black in the black male prediction equation to assess the role explanatory variables play in the black-white survival difference, residual black-white differences at the county level shrink markedly to a mean of −2.4% (+/−2.4); for women the mean difference is −3.7% (+/−2.3).

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          Impact of regional climate change on human health.

          The World Health Organisation estimates that the warming and precipitation trends due to anthropogenic climate change of the past 30 years already claim over 150,000 lives annually. Many prevalent human diseases are linked to climate fluctuations, from cardiovascular mortality and respiratory illnesses due to heatwaves, to altered transmission of infectious diseases and malnutrition from crop failures. Uncertainty remains in attributing the expansion or resurgence of diseases to climate change, owing to lack of long-term, high-quality data sets as well as the large influence of socio-economic factors and changes in immunity and drug resistance. Here we review the growing evidence that climate-health relationships pose increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world. Potentially vulnerable regions include the temperate latitudes, which are projected to warm disproportionately, the regions around the Pacific and Indian oceans that are currently subjected to large rainfall variability due to the El Niño/Southern Oscillation sub-Saharan Africa and sprawling cities where the urban heat island effect could intensify extreme climatic events.
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            Fine-particulate air pollution and life expectancy in the United States.

            Exposure to fine-particulate air pollution has been associated with increased morbidity and mortality, suggesting that sustained reductions in pollution exposure should result in improved life expectancy. This study directly evaluated the changes in life expectancy associated with differential changes in fine particulate air pollution that occurred in the United States during the 1980s and 1990s. We compiled data on life expectancy, socioeconomic status, and demographic characteristics for 211 county units in the 51 U.S. metropolitan areas with matching data on fine-particulate air pollution for the late 1970s and early 1980s and the late 1990s and early 2000s. Regression models were used to estimate the association between reductions in pollution and changes in life expectancy, with adjustment for changes in socioeconomic and demographic variables and in proxy indicators for the prevalence of cigarette smoking. A decrease of 10 microg per cubic meter in the concentration of fine particulate matter was associated with an estimated increase in mean (+/-SE) life expectancy of 0.61+/-0.20 year (P=0.004). The estimated effect of reduced exposure to pollution on life expectancy was not highly sensitive to adjustment for changes in socioeconomic, demographic, or proxy variables for the prevalence of smoking or to the restriction of observations to relatively large counties. Reductions in air pollution accounted for as much as 15% of the overall increase in life expectancy in the study areas. A reduction in exposure to ambient fine-particulate air pollution contributed to significant and measurable improvements in life expectancy in the United States. 2009 Massachusetts Medical Society
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              An Estimate of the Global Burden of Anthropogenic Ozone and Fine Particulate Matter on Premature Human Mortality Using Atmospheric Modeling

              Background Ground-level concentrations of ozone (O3) and fine particulate matter [≤ 2.5 μm in aerodynamic diameter (PM2.5)] have increased since preindustrial times in urban and rural regions and are associated with cardiovascular and respiratory mortality. Objectives We estimated the global burden of mortality due to O3 and PM2.5 from anthropogenic emissions using global atmospheric chemical transport model simulations of preindustrial and present-day (2000) concentrations to derive exposure estimates. Methods Attributable mortalities were estimated using health impact functions based on long-term relative risk estimates for O3 and PM2.5 from the epidemiology literature. Using simulated concentrations rather than previous methods based on measurements allows the inclusion of rural areas where measurements are often unavailable and avoids making assumptions for background air pollution. Results Anthropogenic O3 was associated with an estimated 0.7 ± 0.3 million respiratory mortalities (6.3 ± 3.0 million years of life lost) annually. Anthropogenic PM2.5 was associated with 3.5 ± 0.9 million cardiopulmonary and 220,000 ± 80,000 lung cancer mortalities (30 ± 7.6 million years of life lost) annually. Mortality estimates were reduced approximately 30% when we assumed low-concentration thresholds of 33.3 ppb for O3 and 5.8 μg/m3 for PM2.5. These estimates were sensitive to concentration thresholds and concentration–mortality relationships, often by > 50%. Conclusions Anthropogenic O3 and PM2.5 contribute substantially to global premature mortality. PM2.5 mortality estimates are about 50% higher than previous measurement-based estimates based on common assumptions, mainly because of methodologic differences. Specifically, we included rural populations, suggesting higher estimates; however, the coarse resolution of the global atmospheric model may underestimate urban PM2.5 exposures.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                17 April 2012
                : 7
                : 4
                : e32930
                Affiliations
                [1 ]General Medical Disciplines, Stanford University School of Medicine, Stanford, California, United States of America
                [2 ]Departments of Economics and Health Research and Policy, Stanford University, Stanford, California, United States of America
                Public Health Agency of Barcelona, Spain
                Author notes

                Conceived and designed the experiments: MRC CC VRF. Performed the experiments: MRC CC VRF. Analyzed the data: MRC CC VRF. Contributed reagents/materials/analysis tools: MRC CC VRF. Wrote the paper: MRC CC VRF.

                Article
                PONE-D-11-14236
                10.1371/journal.pone.0032930
                3328498
                22529892
                f3d76ee8-fcb1-4848-b247-17699b9841c6
                Cullen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 25 July 2011
                : 7 February 2012
                Page count
                Pages: 13
                Categories
                Research Article
                Biology
                Population Biology
                Epidemiology
                Environmental Epidemiology
                Epidemiology of Aging
                Life Course Epidemiology
                Social Epidemiology
                Medicine
                Epidemiology
                Environmental Epidemiology
                Epidemiology of Aging
                Lifecourse Epidemiology
                Social Epidemiology
                Non-Clinical Medicine
                Health Care Policy
                Child and Adolescent Health Policy
                Geographic and National Differences
                Health Education and Awareness
                Health Risk Analysis
                Health Statistics
                Health Economics
                Health Services Research
                Socioeconomic Aspects of Health
                Public Health
                Behavioral and Social Aspects of Health
                Child Health
                Environmental Health
                Socioeconomic Aspects of Health
                Social and Behavioral Sciences
                Economics
                Health Economics
                Sociology
                Demography

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