Urologist density and county-level urologic cancer mortality.
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ABSTRACT:
SUBMITTER: Odisho AY
PROVIDER: S-EPMC2881728 | biostudies-other | 2010 May
REPOSITORIES: biostudies-other
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Project description:Background Hispanics are the fastest growing ethnic group in the United States, and little is known about how Hispanic ethnic population density impacts cardiovascular disease ( CVD ) mortality. Methods and Results We examined county-level deaths for Hispanics and non-Hispanic whites from 2003 to 2012 using data from the National Center for Health Statistics' Multiple Cause of Death mortality files. Counties with more than 20 Hispanic deaths (n=715) were included in the analyses. CVD deaths were identified using International Classification of Diseases, Tenth Revision (ICD-10), I00 to I78, and population estimates were calculated using linear interpolation from 2000 and 2010 census data. Multivariate linear regression was used to examine the association of Hispanic ethnic density with Hispanic and non-Hispanic white age-adjusted CVD mortality rates. County-level age-adjusted CVD mortality rates were adjusted for county-level demographic, socioeconomic, and healthcare factors. There were a total of 4 769 040 deaths among Hispanics (n=382 416) and non-Hispanic whites (n=4 386 624). Overall, cardiovascular age-adjusted mortality rates were higher among non-Hispanic whites compared with Hispanics (244.8 versus 189.0 per 100 000). Hispanic density ranged from 1% to 96% in each county. Counties in the highest compared with lowest category of Hispanic density had 60% higher Hispanic mortality (215.3 versus 134.2 per 100 000 population). In linear regression models, after adjusting for county-level demographic, socioeconomic, and healthcare factors, increasing Hispanic ethnic density remained strongly associated with mortality for Hispanics but not for non-Hispanic whites. Conclusions CVD mortality is higher in counties with higher Hispanic ethnic density. County-level characteristics do not fully explain the higher CVD mortality among Hispanics in ethnically concentrated counties.
| S-EPMC6404884 | biostudies-literature
Project description:Background Persistent racial/ethnic disparities in cardiovascular disease (CVD) mortality are partially explained by healthcare access and socioeconomic, demographic, and behavioral factors. Little is known about the association between race/ethnicity-specific CVD mortality and county-level factors. Methods and Results Using 2017 county-level data, we studied the association between race/ethnicity-specific CVD age-adjusted mortality rate (AAMR) and county-level factors (demographics, census region, socioeconomics, CVD risk factors, and healthcare access). Univariate and multivariable linear regressions were used to estimate the association between these factors; R2 values were used to assess the factors that accounted for the greatest variation in CVD AAMR by race/ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx individuals). There were 659 740 CVD deaths among non-Hispanic White individuals in 2698 counties; 100 475 deaths among non-Hispanic Black individuals in 717 counties; and 49 493 deaths among Hispanic/Latinx individuals across 267 counties. Non-Hispanic Black individuals had the highest mean CVD AAMR (320.04 deaths per 100 000 individuals), whereas Hispanic/Latinx individuals had the lowest (168.42 deaths per 100 000 individuals). The highest CVD AAMRs across all racial/ethnic groups were observed in the South. In unadjusted analyses, the greatest variation (R2) in CVD AAMR was explained by physical inactivity for non-Hispanic White individuals (32.3%), median household income for non-Hispanic Black individuals (24.7%), and population size for Hispanic/Latinx individuals (28.4%). In multivariable regressions using county-level factor categories, the greatest variation in CVD AAMR was explained by CVD risk factors for non-Hispanic White individuals (35.3%), socioeconomic factors for non-Hispanic Black (25.8%), and demographic factors for Hispanic/Latinx individuals (34.9%). Conclusions The associations between race/ethnicity-specific age-adjusted CVD mortality and county-level factors differ significantly. Interventions to reduce disparities may benefit from being designed accordingly.
| S-EPMC8174200 | biostudies-literature
Project description:As of August 2020, the United States is the global epicenter of the COVID-19 pandemic. Emerging data suggests that "essential" workers, who are disproportionately more likely to be racial/ethnic minorities and immigrants, bear a disproportionate degree of risk. We used publicly available data to build a series of spatial autoregressive models assessing county level associations between COVID-19 mortality and (1) percentage of individuals engaged in farm work, (2) percentage of households without a fluent, adult English-speaker, (3) percentage of uninsured individuals under the age of 65, and (4) percentage of individuals living at or below the federal poverty line. We further adjusted these models for total population, population density, and number of days since the first reported case in a given county. We found that across all counties that had reported a case of COVID-19 as of July 12, 2020 (n = 3024), a higher percentage of farmworkers, a higher percentage of residents living in poverty, higher density, higher population, and a higher percentage of residents over the age of 65 were all independently and significantly associated with a higher number of deaths in a county. In urban counties (n = 115), a higher percentage of farmworkers, higher density, and larger population were all associated with a higher number of deaths, while lower rates of insurance coverage in a county was independently associated with fewer deaths. In non-urban counties (n = 2909), these same patterns held true, with higher percentages of residents living in poverty and senior residents also significantly associated with more deaths. Taken together, our findings suggest that farm workers may face unique risks of contracting and dying from COVID-19, and that these risks are independent of poverty, insurance, or linguistic accessibility of COVID-19 health campaigns.
| S-EPMC7556498 | biostudies-literature
Project description: Not available
| S-EPMC5134744 | biostudies-literature
Project description:Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions-especially anger-emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level.
| S-EPMC4433545 | biostudies-literature
Project description:The highly variable occurrence of primary liver cancers across the United States emphasize the relevance of location-based factors. Social determinants such as income, educational attainment, housing, and other factors may contribute to regional variations in outcomes. To evaluate their impact, this study identified and analyzed clusters of high mortality from primary liver cancers and the association of location-based determinants with mortality across the contiguous United States. A geospatial analysis of age-adjusted incidence and standardized mortality rates from primary liver cancers from 2000 to 2020 was performed. Local indicators of spatial association identified hot-spots, clusters of counties with significantly higher mortality. Temporal analysis of locations with persistent poverty, defined as high (>20%) poverty for at least 30 years, was performed. Social determinants were analyzed individually or globally using composite measures such as the social vulnerability index or social deprivation index. Disparities in county level social determinants between hot-spots and non-hot-spots were analyzed by univariate and multivariate logistic regression. There are distinct clusters of liver cancer incidence and mortality, with hotspots in east Texas and Louisiana. The percentage of people living below the poverty line or Hispanics had a significantly higher odds ratio for being in the top quintile for mortality rates in comparison to other quintiles and were highly connected with mortality rates. Current and persistent poverty were both associated with an evolution from non-hotspots to new hotspots of mortality. Hotspots were predominantly associated with locations with significant levels of socioeconomic vulnerability or deprivation. Poverty at a county level is associated with mortality from primary liver cancer and clusters of higher mortality. These findings emphasize the importance of addressing poverty and related socio-economic determinants as modifiable factors in public health policies and interventions aimed at reducing mortality from primary liver cancers.
| S-EPMC11297446 | biostudies-literature
Project description:ImportanceTropical cyclones have a devastating effect on society, but a comprehensive assessment of their association with cause-specific mortality over multiple years of study is lacking.ObjectiveTo comprehensively evaluate the association of county-level tropical cyclone exposure and death rates from various causes in the US.Design, setting, and participantsA retrospective observational study using a Bayesian conditional quasi-Poisson model to examine how tropical cyclones were associated with monthly death rates. Data from 33.6 million deaths in the US were collected from the National Center for Health Statistics over 31 years (1988-2018), including residents of the 1206 counties in the US that experienced at least 1 tropical cyclone during the study period.ExposuresTropical cyclone days per county-month, defined as number of days in a month with a sustained maximal wind speed 34 knots or greater.Main outcomes and measuresMonthly cause-specific county-level death rates by 6 underlying causes of death: cancers, cardiovascular diseases, infectious and parasitic diseases, injuries, neuropsychiatric conditions, and respiratory diseases. The model yielded information about the association between each additional cyclone day per month and monthly county-level mortality compared with the same county-month in different years, up to 6 months after tropical cyclones, and how these estimated associations varied by age, sex, and social vulnerability. The unit of analysis was county-month.ResultsThere were 33 619 393 deaths in total (16 691 681 females and 16 927 712 males; 8 587 033 aged 0-64 years and 25 032 360 aged 65 years or older) from the 6 causes recorded in 1206 US counties. There was a median of 2 tropical cyclone days experienced in total in included US counties. Each additional cyclone day was associated with increased death rates in the month following the cyclone for injuries (3.7% [95% credible interval {CrI}, 2.5%-4.9%]; 2.0 [95% CrI, 1.3-2.7] additional deaths per 1 000 000 for 2018 monthly age-standardized median rate [DPM]; 54.3 to 56.3 DPM), infectious and parasitic diseases (1.8% [95% CrI, 0.1%-3.6%]; 0.2 [95% CrI, 0.0-0.4] additional DPM; 11.7 to 11.9 DPM), respiratory diseases (1.3% [95% CrI, 0.2%-2.4%]; 0.6 [95% CrI, 0.1-1.1] additional DPM; 44.9 to 45.5 DPM), cardiovascular diseases (1.2% [95% CrI, 0.6%-1.7%]; 1.5 [95% CrI, 0.8-2.2] additional DPM; 129.6 to 131.1 DPM), neuropsychiatric conditions (1.2% [95% CrI, 0.1%-2.4%]; 0.6 [95% CrI, 0.1-1.2] additional DPM; 52.1 to 52.7 DPM), with no change for cancers (-0.3% [95% CrI, -0.9% to 0.3%]; -0.3 [95% CrI, -0.9 to 0.3] additional DPM; 100.4 to 100.1 DPM).Conclusions and relevanceAmong US counties that experienced at least 1 tropical cyclone from 1988-2018, each additional cyclone day per month was associated with modestly higher death rates in the months following the cyclone for several causes of death, including injuries, infectious and parasitic diseases, cardiovascular diseases, neuropsychiatric conditions, and respiratory diseases.
| S-EPMC8905400 | biostudies-literature
Project description:BackgroundHousing instability is a key social determinant of health and has been linked to adverse short- and long-term health. Eviction reflects a severe form of housing instability and disproportionately affects minority and women residents in the USA; however, its relationship with mortality has not previously been described.ObjectiveTo evaluate the independent association of county-level eviction rates with all-cause mortality in the USA after adjustment for county demographic, socioeconomic, and health-related characteristics.DesignCross-sectional.ParticipantsSix hundred eighty-six US counties with available 2016 county-level eviction and mortality data.Exposure2016 US county-level eviction rate.Outcome2016 US county-level age-adjusted all-cause mortality.Key resultsAmong 686 counties (66.1 million residents, 50.5% [49.7-51.2] women, 2% [0.5-11.1] Black race) with available eviction and mortality data in 2016, we observed a significant and graded relationship between county-level eviction rate and all-cause mortality. Counties in the highest eviction tertile demonstrated a greater proportion of residents of Black race and women and a higher prevalence of poverty and comorbid health conditions. After adjustment for county-level sociodemographic traits and prevalent comorbid health conditions, age-adjusted all-cause mortality was highest among counties in the highest eviction tertile (Tertile 3 vs 1 (per 100,000 people) 33.57: 95% CI: 10.5-56.6 p=.004). Consistent results were observed in continuous analysis of eviction, with all-cause mortality increasing by 9.32 deaths per 100,000 people (4.77, 13.89, p<.0001) for every 1% increase in eviction rates. Significant interaction in the relationship between eviction and all-cause mortality was observed by the proportion of Black and women residents.ConclusionsIn this cross-sectional analysis, county-level eviction rates were significantly associated with all-cause mortality with the strongest effects observed among counties with the highest proportion of Black and women residents. State and federal protections from evictions may help to reduce the health consequences of housing instability and address disparities in health outcomes.
| S-EPMC9640832 | biostudies-literature
Project description:BACKGROUND:Radon is an inert gas formed from the decay of naturally-occurring materials in the earth's crust. It infiltrates into homes from soil, water, and construction materials. Its decay products are radionuclides, which attach to ambient particles. Residential radon is one of the leading risk factors for lung cancer. The scarce evidence for associations with other mortality causes originates mostly from occupational studies. METHODS:In a cohort study with 14?years of follow-up (2000-2013), we evaluated the association between chronic radon exposure and all-cause mortality, and explored whether there are subpopulations who are more vulnerable to radon effects. We included 87,296,195 person-years of follow-up from all Medicare beneficiaries in the Mid-Atlantic and Northeastern U.S. states. We examined the association between the logarithm of county-averaged radon (ln(Rn)) and mortality and assessed effect modification by chronic conditions. RESULTS:An interquartile range increase in the ln(Rn) was associated with a 2·62% increase (95% CI 2·52%; 2·73%) in mortality, independent of PM2.5 exposure. Larger mortality risks were observed among individuals with respiratory, cardiovascular and metabolic diseases, with the highest associations observed among those with diabetes (4·98% increase), heart failure (4·58% increase), and chronic obstructive pulmonary disease (4·49% increase). CONCLUSION:We found an increased risk for all-cause mortality associated with increased radon exposure. The risk was enhanced among susceptible individuals with chronic conditions. We believe this is the first cohort study to identify populations at higher risk for non-malignant health consequences of radon exposure. Due to the limitations in exposure assessment and availability of individual confounders, these findings should be interpreted with caution.
| S-EPMC6679989 | biostudies-literature
Project description:BackgroundPreliminary studies have suggested a link between socio-economic characteristics and COVID-19 mortality. Such studies have been carried out on particular geographies within the USA or selective data that do not represent the complete experience for 2020.MethodsWe estimated COVID-19 mortality rates, number of years of life lost to SARS-CoV-2 and reduction in life expectancy during each of the three pandemic waves in 2020 for 3144 US counties grouped into five socio-economic status categories, using daily death data from the Johns Hopkins University of Medicine and weekly mortality age structure from the Centers for Disease Control.ResultsDuring March-May 2020, COVID-19 mortality was highest in the most socio-economically advantaged quintile of counties and lowest in the two most-disadvantaged quintiles. The pattern reversed during June-August and widened by September-December, such that COVID-19 mortality rates were 2.58 times higher in the bottom than in the top quintile of counties. Differences in the number of years of life lost followed a similar pattern, ultimately resulting in 1.002 (1.000, 1.004) million years in the middle quintile to 1.381 (1.378, 1.384) million years of life lost in the first (most-disadvantaged) quintile during the whole year.ConclusionsDiverging trajectories of COVID-19 mortality among the poor and affluent counties indicated a progressively higher rate of loss of life among socio-economically disadvantaged communities. Accounting for socio-economic disparities when allocating resources to control the spread of the infection and to reinforce local public health infrastructure would reduce inequities in the mortality burden of the disease.
| S-EPMC8755340 | biostudies-literature