County Rurality and Socioeconomic Deprivation Is Associated With Reduced Survival From Gastric Cancer in the United States.
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ABSTRACT:
SUBMITTER: Huang RJ
PROVIDER: S-EPMC7577922 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
Publications
County Rurality and Socioeconomic Deprivation Is Associated With Reduced Survival From Gastric Cancer in the United States.
Huang Robert J RJ Shah Shailja C SC Camargo M Constanza MC Palaniappan Latha L Hwang Joo Ha JH
Gastroenterology 20200507 4
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Project description:BackgroundIndividuals experiencing socioeconomic deprivation consistently demonstrate poorer physical and mental health. Income alone is inadequate as a measure of socioeconomic status (SES); a better measure for assessing the deprivation status of individuals is needed.MethodsThe New Zealand Index of Socioeconomic Deprivation for Individuals, a validated, eight-item measure of deprivation, was modified to create the United States Index of Socioeconomic Deprivation for Individuals (USiDep). The questionnaire was administered to patients with major depressive disorder participating in two clinical trials. Spearman's correlation coefficients evaluated associations between USiDep scores with income and other measures associated with deprivation.ResultsThe USiDep was completed by 118 participants, demonstrating adequate internal consistency (Crohnbach's alpha = 0.766) and strong item-total correlations. USiDep scores were moderately correlated with past-year personal income (Spearman's rho = -0.362, p < .001) and several other measures related to deprivation, including body mass index, level of education, quality of life, severity of childhood traumatic events, self-reported physical health, and negative life events. Patients scoring 5 on the USiDep (the highest possible score, indicating greater deprivation) had significantly lower rates of remission after 12 weeks of treatment than those scoring ≤ 4 (1/12, 8.3% vs 40/98, 40.8%, respectively, p = .03), whereas the lowest income group showed no significant associations with outcomes.ConclusionThe USiDep is a valid, brief questionnaire for assessing SES that has utility for clinical research and may serve as a predictor of treatment outcomes in clinical trials. Validation of the USiDep in healthy controls and other medically and psychiatrically ill populations is warranted.
| S-EPMC9355266 | biostudies-literature
Project description:ObjectiveTo determine the variability in county cardiovascular (CV) premature mortality explained by integrated metrics of socioeconomic deprivation and to explore temporal trends in CV mortality by county socioeconomic deprivation.MethodsThis is a cross-sectional analysis of US county-level death certificate data from 1999 to 2018 of age-adjusted premature (25 to 64 years) CV mortality. Integrated metrics of socioeconomic deprivation (Social Deprivation Index [SDI] and county Area Deprivation Index [ADI]) were associated with mortality using linear regression analysis. Relative change in county CV mortality from 1999 to 2018 was associated with indices using linear regression analysis.ResultsCounties with higher quartile SDI and ADI had significantly higher total, non-Hispanic Black/African American, and female premature CV mortality (P<.001). Both SDI and ADI were significantly associated with CV mortality by linear regression (P<.001) explaining 40% and 44% of county variability in CV mortality, respectively. Counties with lower deprivation indices experienced a larger decreased in premature CV mortality (P<.001).ConclusionThis study demonstrates an association between multiple integrated metrics of socioeconomic deprivation and premature cardiovascular mortality and shows potentially worsening disparities.
| S-EPMC10411485 | biostudies-literature
Project description:BackgroundGeographic disparities in survival after heart transplantation have received mixed support in prior studies, and specific geographic characteristics that might be responsible for these differences are unclear. We tested for differences in heart transplant outcomes across United States (US) counties after adjustment for individual-level covariates. Our secondary aim was to evaluate whether specific county-level socioeconomic characteristics explained geographic disparities in survival.MethodsData on patients aged ≥18 years undergoing a first-time heart transplant between July 2006 and December 2014 were obtained from the United Network for Organ Sharing. Residents of counties represented by <5 patients were excluded. Patient survival (censored in March 2016) was analyzed using multivariable Cox regression. Shared frailty models were used to test for residual differences in overall all-cause mortality across counties after adjusting for recipient and donor characteristics. Measures of county economic disadvantage, inequality, and racial segregation were obtained from US Census data and coded into quintiles. A likelihood ratio test determined whether adjusting for each county measure improved the fit of the Cox model.ResultsMultivariable analysis of 10,879 heart transplant recipients found that, adjusting for individual-level characteristics, there remained statistically significant variation in mortality hazard across US counties (P=.004). Adjusting for quintiles of community disadvantage, economic inequality, or racial segregation did not significantly improve model fit (likelihood ratio test P=.092, P=.273, and P=.107, respectively) and did not explain residual differences in patient survival across counties.ConclusionsHeart transplantation outcomes vary by county, but this difference is not attributable to county-level socioeconomic disadvantage.
| S-EPMC5705041 | biostudies-literature
Project description:Millions of people move within the U.S. each year. We propose that people function as proxies for their locations, bringing the culture of their previous residence to their new homes. As a result, migration might systematically influence regional biases across geographic units over time. Using county-to-county migration data from the U.S. census and county-level racial attitude estimates from Project Implicit, the present research examined the impact of people relocating from one U.S. county to another on racial attitudes in their new county. Consistent with our prediction, the bias brought by the migrants positively predicts county-level racial bias after migration, even after controlling for county-level racial bias before migration. This finding remains robust across various sample inclusion criteria and spans three time periods (2006-2010, 2011-2015, and 2016-2020). These results highlight the significant role of migration in spreading and shaping regional racial attitudes, emphasizing the importance of considering macro-societal processes such as migration when studying changes in regional racial attitudes.
| S-EPMC11845736 | biostudies-literature
Project description:Harvested wood products found in the built environment are an important carbon sink, helping to mitigate climate change, and their trends in use are determined by economic and demographic factors, which vary spatially. Spatially detailed projections of construction and stored carbon are needed for industry and public decision making, including for appreciating trends in values at risk from catastrophic disturbances. We specify econometric models of single-family and multifamily housing starts by U.S. Census Region, design a method for their spatial downscaling to the county level, and project their quantities and carbon content according to the five Shared Socioeconomic Pathways (SSPs). Starts are projected to decline across all scenarios and potentially drop to below housing replacement levels under SSP3 by mid-century. Wood products carbon stored nationally in structures in use and in landfills is projected to grow across all scenarios but with significant spatial heterogeneity related to disparate trends in construction across counties, ranging from strong growth in the urban counties of the coastal South and West to stagnation in rural counties of the Great Plains and the northern Rockies. The estimated average annual carbon stored in wood products used in and discarded from US residential housing units between 2015-2070 ranged from 51 million t CO2e in SSP3 to 85 million t CO2e in SSP5, representing 47% to 78% of total carbon uptake relative to uptake by all wood products in the United States in 2019.
| S-EPMC9371325 | biostudies-literature
Project description:ObjectiveWest Virginia's (WV) suicide rate is 50% higher than the national average and is the highest in the Appalachian Region. Appalachia has several social factors that have contributed to greater socioeconomic deprivation, a known contributor of suicide. Given WV's high prevalence of suicide and poverty, the current study aims to examine the relationship between socioeconomic deprivation and suicide rates in WV.MethodsThe Townsend Deprivation Index (TDI), Social Deprivation Index (SDI), and Social Vulnerability Index (SVI) measured socioeconomic deprivation. Negative binomial regression models assessed the relationship between socioeconomic deprivation scores, individual index items, and suicide rates. Model comparisons evaluated the indices' ability to assess suicide rates. A backward selection strategy identified additional key items for examining suicide rates.ResultsThere was a significant increase in suicide rates for every 10% increase in TDI (β = 0.04; p < 0.01), SDI (β = 0.03; p = 0.04), and SVI scores (β = 0.05; p < 0.01). Household overcrowding and unemployment had a positive linear relationship with suicide in TDI (β = 0.04, p = 0.02; β = 0.07, p = 0.01), SDI (β = 0.10, p = 0.02; β = 0.01, p<0.01), and the SVI (β = 0.10, p = 0.02; β = 0.03, p<0.01). The backwards selection strategy identified additional key items included by the SVI when assessing suicide.ConclusionGreater socioeconomic deprivation, measured by the TDI, SDI, and SVI, was significantly associated with higher suicide rates. Expanding unemployment benefits and increasing the availability of affordable housing, especially in rural areas, may be useful in reducing suicide rates. Our results suggest racial and ethnic minorities and adults living with a disability may benefit from targeted suicide prevention strategies.
| S-EPMC11573156 | biostudies-literature
Project description:PurposeTo estimate percent excess deaths during the COVID-19 pandemic by rural-urban residence in the United States and to describe rural-urban disparities by age, sex, and race/ethnicity.MethodsUsing US mortality data, we used overdispersed Poisson regression models to estimate monthly expected death counts by rurality of residence, age group, sex, and race/ethnicity, and compared expected death counts with observed deaths. We then summarized excess deaths over 6 6-month time periods.FindingsThere were 16.9% (95% confidence interval [CI]: 16.8, 17.0) more deaths than expected between March 2020 and February 2023. The percent excess varied by rurality (large central metro: 18.2% [18.1, 18.4], large fringe metro: 15.6% [15.5, 15.8], medium metro: 18.1% [18.0, 18.3], small metro: 15.5% [15.3, 15.7], micropolitan rural: 16.3% [16.1, 16.5], and noncore rural: 15.8% [15.6, 16.1]). The percent excess deaths were 20.2% (20.1, 20.3) for males and 13.6% (13.5, 13.7) for females, and highest for Hispanic persons (49% [49.0, 49.6]), followed by non-Hispanic Black persons (28% [27.5, 27.9]) and non-Hispanic White persons (12% [11.6, 11.8]). The 6-month time periods with the highest percent excess deaths for large central metro areas were March 2020-August 2020 and September 2020-February 2021; for all other areas, these time periods were September 2020-February 2021 and September 2021-February 2022.ConclusionPercent excess deaths varied by rurality, age group, sex, race/ethnicity, and time period. Monitoring excess deaths by rurality may be useful in assessing the impact of the pandemic over time, as rural-urban patterns appear to differ.
| S-EPMC11164822 | biostudies-literature
Project description:Vitelliform dystrophies are a group of macular degenerative diseases characterized by round yellow lesions in the macula. While often idiopathic, vitelliform dystrophies include inherited maculopathies such as Best disease and some cases of pattern dystrophy. The prevalence of vitelliform dystrophies in the United States has not been reported. This study examined the prevalence of vitelliform dystrophies in Olmsted County, Minnesota.The Rochester Epidemiology Project database was used to identify all cases of vitelliform or pattern dystrophy in Olmsted County from 1 January 2000-31 December 2014.Overall, 27 patients had true vitelliform lesions, indicating a prevalence of 1 in 5500. Of these, two had genetically confirmed Best disease, and an additional five to seven carried a diagnosis of Best disease, which chart reviews confirmed as probable cases; 18-20 patients had adult-onset vitelliform macular dystrophy. The prevalence of Best disease was 1 in 16,500 to 1 in 21,000. Adult-onset vitelliform macular dystrophy was found in 1 in 7400 to 1 in 8200.Vitelliform dystrophies affect 1 in 5500 individuals in Olmsted County. While the values in this study provide good estimates for the prevalence of Best disease versus adult-onset vitelliform macular dystrophy, the results are limited by dependence on diagnoses made by other ophthalmologists and underutilization of genetic testing. Thus, these diseases should be thought of as at least as prevalent as reported here. As therapies for Best disease and other macular degenerative diseases are quickly becoming a reality, genetic testing should be employed as the gold standard for diagnosis of these diseases.
| S-EPMC5638045 | biostudies-other
Project description:PurposeInvestigating CRC screening rates and rurality at the county-level may explain disparities in CRC survival in Georgia. Although a few studies examined the relationship of CRC screening rates, rurality, and/or CRC outcomes, they either used an ecological study design or focused on the larger population.MethodsWe conducted a retrospective analysis utilizing data from the 2004-2010 Surveillance, Epidemiology, and End Results Program. The 2013 United States Department of Agriculture rural-urban continuum codes and 2004-2010 National Cancer Institute small-area estimates for screening behaviors were used to identify county-level rurality and CRC screening rates. Kaplan-Meier method and Cox proportional hazard regression were performed.ResultsAmong 22,160 CRC patients, 5-year CRC survival rates were lower among CRC patients living in low screening areas in comparison with intermediate/high areas (69.1% vs. 71.6% /71.3%; p-value = 0.030). Patients living in rural high-screening areas also had lower survival rates compared to non-rural areas (68.2% vs. 71.8%; p-value = 0.009). Our multivariable analysis demonstrated that patients living in intermediate (HR, 0.91; 95% CI, 0.85-0.98) and high-screening (HR, 0.92; 95% CI, 0.85-0.99) areas were at 8%-9% reduced risk of CRC death. Further, non-rural CRC patients living in intermediate and high CRC screening areas were 9% (HR, 0.91; 95% CI, 0.83-0.99) and 10% (HR, 0.90; 95% CI, 0.82-0.99) less likely to die from CRC.ConclusionsLower 5-year survival rates were observed in low screening and rural high-screening areas. Living in intermediate/high CRC screening areas was negatively associated with the risk of CRC death. Particularly, non-rural patients living in intermediate/high-screening areas were 8%-9% less likely to die from CRC. Targeted CRC screening resources should be prioritized for low screening and rural communities.
| S-EPMC10807605 | biostudies-literature
Project description: Not available
| S-EPMC9514344 | biostudies-literature