A “Swiss paradox” in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans

Although a preponderance of research indicates that increased income inequality negatively impacts population health, several international studies found that a greater income inequality was associated with better population health when measured on a fine geographic level of aggregation. This finding is known as a “Swiss paradox”. To date, no studies have examined variability in the associations between income inequality and health outcomes by spatial aggregation level in the US. Therefore, this study examined associations between income inequality (Gini index, GI) and population health by geographic level using a large, nationally representative dataset of older adults. We geographically linked respondents’ county data from the 2012 Behavioral Risk Factor Surveillance System to 2012 American Community Survey data. Using generalized linear models, we estimated the association between GI decile on the state and county levels and five population health outcomes (diabetes, obesity, smoking, sedentary lifestyle and self-rated health), accounting for confounders and complex sampling. Although state-level GI was not significantly associated with obesity rates (b = − 0.245, 95% CI − 0.497, 0.008), there was a significant, negative association between county-level GI and obesity rates (b = − 0.416, 95% CI − 0.629, − 0.202). State-level GI also associated with an increased diabetes rate (b = 0.304, 95% CI 0.063, 0.546), but the association was not significant for county-level GI and diabetes rate (b = − 0.101, 95% CI − 0.305, 0.104). Associations between both county-level GI and state-level GI and current smoking status were also not significant. These findings show the associations between income inequality and health vary by spatial aggregation level and challenge the preponderance of evidence suggesting that income inequality is consistently associated with worse health. Further research is needed to understand the nuances behind these observed associations to design informed policies and programs designed to reduce socioeconomic health inequities among older adults

Disease Prevalence and Health Determinants in Nevada

In this report, we use recent data to describe the health of Nevada and update the previous report (Monnat, 2012) on health outcomes and health determinants in the Silver State. Data for this report are mainly obtained from the County Health Rankings, America’s Health Rankings, and the 2016 Center for Disease Control and Prevention’s Division of Nutrition, Physical Activity, and Obesity report. In line with the previous report by Monnat (2012), we reference Nevada’s disease prevalence in relation to the U.S. average and other states, as well as disease distribution among counties in Nevada. We also compaire health indicators in the U.S. with those in other countries, discuss the health determinants and examine their impact on Nevadans’ health. The chapter concludes with the recommendations on strategies to improve health of Nevada residents. Additional resources include the national, state and community public health organizations (Appendix 1) and examples of public health related legislative actions in Nevada (Appendix 2). In the last several decades, there has been growing interest in how modifiable risk factors contribute to disease and mortality rates. Studies point to five key domains as the principal determinants of health: (a) genetic predisposition, (b) social circumstances, (c) environmental conditions, (d) health behaviors, and (e) medical care. It is estimated that as much as 60% of disease risk is attributable to modifiable factors, such as health behaviors, social circumstances, and environmental conditions (McGinnis, Williams-Ruso, & Knickman, 2002). In recent years, health behaviors (e.g. tobacco use, poor diet, and physical inactivity) and social determinants (e.g. poverty, access to health care) have been singled out as contributing to health inequalities (Lewis & Burb-Sharps, 2010; Marmot, 2005). The effect of behavioral and social determinants of health outcomes is evident throughout the U.S and Nevada

Ambient Air Toxic Releases and Adverse Pregnancy Outcomes in Allegheny County, Pennsylvania

Previous studies have shown that women exposed to certain air pollutants are at an increased risk for preterm delivery and/or delivering a low birth weight newborn. Preterm delivery and low birth weight are associated with an increased risk for morbidity and mortality. In an effort to better understand the impact of local environmental factors on pregnancy health, duration and outcomes, this study investigated the relationship of hazardous air pollutant chemicals released by local industries and the adverse pregnancy outcomes of preterm delivery and term low birth weight in Allegheny County, PA.This study included 2,798 singleton birth records for deliveries that occurred in Allegheny County in January through March of 2004. The Toxic Release Inventory provided data for 2003 fugitive and stack air releases of all facilities in Allegheny County reporting air releases of lead and toluene. This data was used for determining proxy maternal exposure measurements. ArcGIS software was used to calculate the distance from each maternal residence to each TRI facility. The distances and reported total pounds of release from each facility were then used to calculate a total lead and toluene exposure value for every birth record. Binary logistic regression was used to assess maternal characteristics' effects on birth outcomes. Chi square tests were used to assess maternal characteristics and levels of exposure to lead and toluene. Chi square tests and binary logistic regression were then used to assess pregnancy outcomes in relation to quartiles of exposure.This study found that mothers with certain age, race, education, and marital characteristics were significantly associated with lower exposure levels of lead and toluene. However, exposure to higher levels of lead or toluene, as measured in this study, was not significantly associated with an increased risk for preterm delivery or term low birth weight.Adverse pregnancy outcomes negatively impact an individual's immediate and lifelong health. Decreasing the incidence of preterm delivery and low birth weight are of great importance to public health. Research that helps to identify environmental determinants of adverse pregnancy outcomes is of vital public health significance

BMJ Open

ObjectivesTo evaluate associations of community types and features with new onset type 2 diabetes in diverse communities. Understanding the location and scale of geographic disparities can lead to community-level interventions.DesignNested case\u2013control study within the open dynamic cohort of health system patients.SettingLarge, integrated health system in 37 counties in central and northeastern Pennsylvania, USA.Participants and analysisWe used electronic health records to identify persons with new-onset type 2 diabetes from 2008 to 2016 (n=15\u2009888). Persons with diabetes were age, sex and year matched (1:5) to persons without diabetes (n=79\u2009435). We used generalised estimating equations to control for individual-level confounding variables, accounting for clustering of persons within communities. Communities were defined as (1) townships, boroughs and city census tracts; (2) urbanised area (large metro), urban cluster (small cities and towns) and rural; (3) combination of the first two; and (4) county. Community socioeconomic deprivation and greenness were evaluated alone and in models stratified by community types.ResultsBorough and city census tract residence (vs townships) were associated (OR (95% CI)) with higher odds of type 2 diabetes (1.10 (1.04 to 1.16) and 1.34 (1.25 to 1.44), respectively). Urbanised areas (vs rural) also had increased odds of type 2 diabetes (1.14 (1.08 to 1.21)). In the combined definition, the strongest associations (vs townships in rural areas) were city census tracts in urban clusters (1.41 (1.22 to 1.62)) and city census tracts in urbanised areas (1.33 (1.22 to 1.45)). Higher community socioeconomic deprivation and lower greenness were each associated with increased odds.ConclusionsUrban residence was associated with higher odds of type 2 diabetes than for other areas. Higher community socioeconomic deprivation in city census tracts and lower greenness in all community types were also associated with type 2 diabetes.U01 DP006293/DP/NCCDPHP CDC HHSUnited States/U01 DP006296/DP/NCCDPHP CDC HHSUnited States/U01DP006293/ACL/ACL HHSUnited States/33441365PMC78121101203

Healthcare Utilization, Deprivation, and Heart-Related Disease In Kentucky

A report submitted by Timothy S. Hare to the Research and Creative Productions Committee in 2005 on the relationship between patterns of healthcare facility utilization for heart-related disease in Kentucky

Impact of Community Factors on the Donor Quality Score in Liver Transplantation

An increasing prevalence of metabolic syndrome and obesity has been linked to the rise in transplant indication for cryptogenic cirrhosis and nonalcoholic fatty liver disease (NAFLD), creating a growing challenge to public health. NAFLD liver transplant (LT) candidates are listed with low priority, and their waiting mortality is high. The impact of community/geographic factors on donor risk models is unknown. The purpose of this study was to develop a parsimonious donor risk-adjusted model tailored to NAFLD recipients by assessing the impact of donor, recipient, transplant, and external factors on graft survival. The theoretical framework was the social ecological model. Secondary data were collected from 3,165 consecutive recipients from the Scientific Registry of Transplant Recipients and Community Health Scores, a proxy of community health disparities derived from the Robert Wood Johnson Foundation\u27s community health rankings. Data were examined using univariate and multivariate analyses. The donor risk-adjusted model was developed using donor-only factors and supplemented with recipient and transplant factors, classifying donors as low, medium, and high risk. NAFLD residents in high-risk counties had increased likelihood of liver graft failure. Findings may be used to allocate high-risk donors to a subset of NAFLD with excellent outcomes, increasing the donor pool and decreasing mortality on the wait list