Mortality Inequality: The Good News from a County-Level Approach.
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ABSTRACT:
SUBMITTER: Currie J
PROVIDER: S-EPMC5134744 | biostudies-literature | 2016
REPOSITORIES: biostudies-literature
Publications
Mortality Inequality: The Good News from a County-Level Approach.
Currie Janet J Schwandt Hannes H
The journal of economic perspectives : a journal of the American Economic Association 20160101 2
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Project description:The surgical work force distribution at the county level varies widely across the United States, and the impact of differential access on cancer outcomes is unclear. We used urologists as a test case because they are the first care providers for urologic cancers, can easily be identified from available data sources, and are unevenly distributed throughout the country. The goal of this study was to determine the effect of increasing urologist density on local prostate, bladder, and kidney cancer mortality.Using county-level data from the Area Resource File, US Census, National Cancer Institute, and Centers for Disease Control, regression models were built for prostate, bladder, and kidney cancer mortality, controlling for categorized urologist density, county demographics, socioeconomic factors, and preexisting health care infrastructure.For each of the three cancers, there was a statistically significant cancer-specific mortality reduction associated with counties that had more than zero urologists (16% to 22% reduction for prostate cancer, 17% to 20% reduction for bladder cancer, and 8% to 14% reduction for kidney cancer with increasing urologist density) relative to zero urologists. However, increasing density greater than two urologists per 100,000 people had no statistically significant impact on mortality for any of the tumors studied.The presence of a urologist is associated with lower mortality for urologic cancers in that county, but increasing urologist density does not yield further improvements. Therefore, a nuanced and geographically aware policy toward the size and distribution of the future work force is most likely to provide the greatest population-level improvement in cancer mortality outcomes.
| S-EPMC2881728 | biostudies-other
Project description:Background In China, income levels and living standards have improved significantly, but many Chinese citizens still do not feel any happier. This phenomenon may be attributed to increased income inequality. Methods Using data from the 2013 Chinese General Social Survey (CGSS), we employed multilevel structural equation modeling (MSEM) to investigate the impact of county-level income inequality on individual-level happiness in China and multilevel mediation analysis with structural equation modeling (MMSEM) to explore the mechanisms through which income inequality impacted happiness. Results A negative relationship between income inequality and happiness was found. The negative association between them was explained by two psychological mechanisms, i.e., fairness and trust. The findings explained a "Chinese puzzle," i.e., why people do not feel happier despite improved income and living standards. Conclusions Our findings may provide a reference for policy makers to implement policies designed to improve individual happiness. What is important now is to reduce income inequality, and to potentially improve perceptions of fairness and trust in China.
| S-EPMC6313330 | biostudies-literature
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:ImportanceIncreasing mortality from suicide, drug overdose, and alcohol-related liver disease (collectively referred to as deaths of despair) is a critical public health crisis. Income inequality and social mobility have been separately associated with all-cause mortality; however, no studies have examined their interaction with these preventable deaths.ObjectiveTo assess the interaction between income inequality and social mobility with deaths of despair among working-age Hispanic, non-Hispanic Black, and non-Hispanic White populations.Design, setting, and participantsThis cross-sectional study analyzed data from the Centers for Disease Control and Prevention WONDER (Wide-Ranging Online Data for Epidemiologic Research) database on county-level deaths of despair from 2000 to 2019 across racial and ethnic groups. Statistical analysis was performed from January 8 to May 20, 2023.ExposuresThe primary exposure of interest was county-level income inequality, measured by the Gini coefficient. Another exposure was race- and ethnicity-specific absolute social mobility. Tertiles for the Gini coefficient and social mobility were created to evaluate the dose-response association.Main outcomes and measuresThe main outcomes were adjusted risk ratios (RRs) of deaths from suicide, drug overdose, and alcoholic liver disease. The interaction between income inequality and social mobility was formally tested on both the additive and multiplicative scales.ResultsThe sample included 788 counties for Hispanic populations, 1050 counties for non-Hispanic Black populations, and 2942 counties for non-Hispanic White populations. Over the study period, 152 350, 149 589, and 1 250 156 deaths of despair were recorded for working-age Hispanic, non-Hispanic Black, and non-Hispanic White populations, respectively. Compared with the reference group (counties with low income inequality and high social mobility), counties with greater income inequality (high inequality: RR, 1.26 [95% CI, 1.24-1.29] for Hispanic populations; RR, 1.18 [95% CI, 1.15-1.20] for non-Hispanic Black populations; and RR, 1.22 [95% CI, 1.21-1.23] for non-Hispanic White populations) or less social mobility (low mobility: RR, 1.79 [95% CI, 1.76-1.82] for Hispanic populations; RR, 1.64 [95% CI, 1.61-1.67] for non-Hispanic Black populations; and RR, 1.38 [95% CI, 1.38-1.39] for non-Hispanic White populations) had higher RRs for deaths of despair. In counties with high income inequality and low social mobility, positive interactions were observed on the additive scale for Hispanic populations (relative excess risk due to interaction [RERI], 0.27 [95% CI, 0.17-0.37]), non-Hispanic Black populations (RERI, 0.36 [95% CI, 0.30-0.42]), and non-Hispanic White populations (RERI, 0.10 [95% CI, 0.09-0.12]). In contrast, positive interactions on the multiplicative scale were found only for non-Hispanic Black populations (ratio of RRs, 1.24 [95% CI, 1.18-1.31]) and non-Hispanic White populations (ratio of RRs, 1.03 [95% CI, 1.02-1.05]), but not for Hispanic populations (ratio of RRs, 0.98 [95% CI, 0.93-1.04]). In the sensitivity analyses using continuous Gini coefficient and social mobility, a positive interaction was observed between higher income inequality and lower social mobility with deaths of despair on both the additive and multiplicative scales for all 3 racial and ethnic groups.Conclusions and relevanceThis cross-sectional study found that the joint exposure of unequal income distribution and lack of social mobility was associated with additional risks for deaths of despair, suggesting that addressing the underlying social and economic conditions is crucial in responding to the epidemic of deaths of despair.
| S-EPMC10339154 | biostudies-literature
Project description: Not available
| S-EPMC4844007 | biostudies-literature
Project description:Recent research has explored the possibility of building attitudinal resistance against online misinformation through psychological inoculation. The inoculation metaphor relies on a medical analogy: by pre-emptively exposing people to weakened doses of misinformation cognitive immunity can be conferred. A recent example is the Bad News game, an online fake news game in which players learn about six common misinformation techniques. We present a replication and extension into the effectiveness of Bad News as an anti-misinformation intervention. We address three shortcomings identified in the original study: the lack of a control group, the relatively low number of test items, and the absence of attitudinal certainty measurements. Using a 2 (treatment vs. control) × 2 (pre vs. post) mixed design (N = 196) we measure participants' ability to spot misinformation techniques in 18 fake headlines before and after playing Bad News. We find that playing Bad News significantly improves people's ability to spot misinformation techniques compared to a gamified control group, and crucially, also increases people's level of confidence in their own judgments. Importantly, this confidence boost only occurred for those who updated their reliability assessments in the correct direction. This study offers further evidence for the effectiveness of psychological inoculation against not only specific instances of fake news, but the very strategies used in its production. Implications are discussed for inoculation theory and cognitive science research on fake news.
| S-EPMC6952868 | 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: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:We examine whether investor mood, driven by World Health Organization (WHO) alerts and media news on dangerous infectious diseases, is priced in pharmaceutical companies' stocks in the United States. We argue that disease-related news (DRNs) should not trigger rational trading. We find that DRNs have a positive and significant sentiment effect among investors (on Wall Street). The effect is stronger (weaker) for small (large) companies, who are less (more) likely to engage in the development of new vaccines. A potential negative investor climate (on Main Street) – induced by disease-related fear – does not alter the positive sentiment effect. Highlights • We examine whether investor mood, driven by World Health Organization alerts on infectious diseases, is priced in pharmaceutical stocks in the U.S.• Disease-related fear has a negative and significant effect on returns on pharmaceutical stocks.• Disease-related news (DRN) has a positive and significant effect on returns on pharmaceutical stocks.• The effect of DRN persists over several days following a WHO alert on infectious diseases.• The effect of DRN is stronger for smaller companies and is weaker for larger companies.• Our findings give rise to profitable trading strategies.
| S-EPMC7148704 | biostudies-literature