Dataset Information

A Survey of Health Disparities, Social Determinants of Health, and Converging Morbidities in a County Jail: A Cultural-Ecological Assessment of Health Conditions in Jail Populations.

ABSTRACT: The environmental health status of jail populations in the United States constitutes a significant public health threat for prisoners and the general population. The ecology of jails creates a dynamic condition in relation to general population health due to the concentrated potential exposure to infectious diseases, difficult access to treatment for chronic health conditions, interruption in continuity of care for serious behavioral health conditions, as well as on-going issues for the prevention and treatment of substance abuse disorders. This paper reports on elements of a cross-sectional survey embedded in a parent project, "Health Disparities in Jail Populations." The overall project includes a comprehensive secondary data analysis of the health status of county jail populations, along with primary data collection that includes a cross-sectional health and health care services survey of incarcerated individuals, coupled with collection of biological samples to investigate infectious disease characteristics of a county jail population. This paper reports on the primary results of the survey data collection that indicate that this is a population with complex and interacting co-morbidities, as well as significant health disparities compared to the general population.

SUBMITTER: Trotter RT

PROVIDER: S-EPMC6267226 | biostudies-other | 2018 Nov

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

A Survey of Health Disparities, Social Determinants of Health, and Converging Morbidities in a County Jail: A Cultural-Ecological Assessment of Health Conditions in Jail Populations.

Trotter Robert T RT Lininger Monica R MR Camplain Ricky R Fofanov Viacheslav Y VY Camplain Carolyn C Baldwin Julie A JA

International journal of environmental research and public health 20181108 11

The environmental health status of jail populations in the United States constitutes a significant public health threat for prisoners and the general population. The ecology of jails creates a dynamic condition in relation to general population health due to the concentrated potential exposure to infectious diseases, difficult access to treatment for chronic health conditions, interruption in continuity of care for serious behavioral health conditions, as well as on-going issues for the preventi ...[more]

PMID: 30413098

Similar Datasets

Project description:Mitochondria, which are multi-functional, have been implicated in cancer initiation, progression, and metastasis due to metabolic alterations in transformed cells. Mitochondria are involved in the generation of energy, cell growth and differentiation, cellular signaling, cell cycle control, and cell death. To date, the mitochondrial basis of cancer disparities is unknown. The goal of this review is to provide an understanding and a framework of mitochondrial determinants that may contribute to cancer disparities in racially different populations. Due to maternal inheritance and ethnic-based diversity, the mitochondrial genome (mtDNA) contributes to inherited racial disparities. In people of African ancestry, several germline, population-specific haplotype variants in mtDNA as well as depletion of mtDNA have been linked to cancer predisposition and cancer disparities. Indeed, depletion of mtDNA and mutations in mtDNA or nuclear genome (nDNA)-encoded mitochondrial proteins lead to mitochondrial dysfunction and promote resistance to apoptosis, the epithelial-to-mesenchymal transition, and metastatic disease, all of which can contribute to cancer disparity and tumor aggressiveness related to racial disparities. Ethnic differences at the level of expression or genetic variations in nDNA encoding the mitochondrial proteome, including mitochondria-localized mtDNA replication and repair proteins, miRNA, transcription factors, kinases and phosphatases, and tumor suppressors and oncogenes may underlie susceptibility to high-risk and aggressive cancers found in African population and other ethnicities. The mitochondrial retrograde signaling that alters the expression profile of nuclear genes in response to dysfunctional mitochondria is a mechanism for tumorigenesis. In ethnic populations, differences in mitochondrial function may alter the cross talk between mitochondria and the nucleus at epigenetic and genetic levels, which can also contribute to cancer health disparities. Targeting mitochondrial determinants and mitochondrial retrograde signaling could provide a promising strategy for the development of selective anticancer therapy for dealing with cancer disparities. Further, agents that restore mitochondrial function to optimal levels should permit sensitivity to anticancer agents for the treatment of aggressive tumors that occur in racially diverse populations and hence help in reducing racial disparities.

Project description:BackgroundMass incarceration has collateral consequences for community health, which are reflected in county-level health indicators, including county mortality rates. County jail incarceration rates are associated with all-cause mortality rates in the USA. We assessed the causes of death that drive the relationship between county-level jail incarceration and mortality.MethodsIn this retrospective, longitudinal study, we assessed the association between county-level jail incarceration rates and county-level cause-specific mortality using county jail incarceration data (1987-2017) for 1094 counties in the USA obtained from the Vera Institute of Justice and cause-specific mortality data for individuals younger than 75 years in the total county population (1988-2018) obtained from the US National Vital Statistics System. We fitted quasi-Poisson models for nine common causes of death (cerebrovascular disease, chronic lower respiratory disease, diabetes, heart disease, infectious disease, malignant neoplasm, substance use, suicide, and unintentional injury) with county fixed effects, controlling for all unmeasured stable county characteristics and measured time-varying confounders (county median age, county poverty rate, county percentage of Black residents, county crime rate, county unemployment rate, and state incarceration rate). We lagged county jail incarceration rates by 1 year to assess the short-term, by 5 years to assess the medium-term, and by 10 years to assess the long-term associations of jail incarceration with premature mortality.FindingsA 1 per 1000 within-county increase in jail incarceration rate was associated with a 6·5% increase in mortality from infectious diseases (risk ratio 1·065, 95% CI 1·061-1·070), a 4·9% increase in mortality from chronic lower respiratory disease (1·049, 1·045-1·052), a 2·6% increase in mortality induced from substance use (1·026, 1·020-1·032), a 2·5% increase in suicide mortality (1·025, 1·020-1·029), and smaller increases in mortality from heart disease (1·021, 1·019-1·023), unintentional injury (1·015, 1·011-1·018), malignant neoplasm (1·014, 1·013-1·016), diabetes (1·013, 1·009-1·018), and cerebrovascular disease (1·010, 1·007-1·013) after 1 year. Associations between jail incarceration and cause-specific mortality rates weakened as time lags increased, but to a greater extent for causes of death with generally shorter latency periods (infectious disease and suicide) than for those with generally longer latency periods (heart disease, malignant neoplasm, and cerebrovascular disease).InterpretationJail incarceration rates are potential drivers of many causes of death in US counties. Jail incarceration can be harmful not only to the health of individuals who are incarcerated, but also to public health more broadly. Our findings suggest important points of intervention, including disinvestment from carceral systems and investment in social and public health services, such as community-based treatment of substance-use disorders.FundingUS National Institute on Drug Abuse (National Institutes of Health).

Project description:OBJECTIVE:We aimed to analyze regional disparities of health care resources in traditional Chinese medicine (TCM) county hospitals and their time trends, and to assess the changes of regional disparities before and after 2009 health care reforms. METHODS:We used hospital-based, longitudinal data from all TCM county hospitals in China between 2004 and 2016. To measure the key development features of TCM county hospitals, data were collected on government hospital investment, hospital numbers (the average number of TCM hospitals per county), hospital scale (the number of medical staff and hospital beds) and doctors' workload (the daily visits and inpatient stays per doctor). We used segmented linear regression to test the time trend for outcome variables. We set a breakpoint at 2011, dividing the pre-reform (2004-2011) and post-reform (2012-2016) periods. RESULTS:After the 2009 health reforms, TCM hospitals continued to display large disparities in the number, scale, and doctors' workload across the three regions. In the pre-reform period, yearly government subsidies for TCM hospitals in western area were roughly RMB0.6 million (US$89 thousand) more than those in central and eastern region, which increased under the 2009 reforms to roughly RMB2 million (US$298 thousand) more per yer in post-reform period. These increased subsidies saw an increase in the number of TCM hospitals in the western area, partly addressing regional disparities. But there was no improvement in the regional disparities in terms of scale (number of beds) and the doctors' workload (daily outpatient visits and inpatients per doctor) increased or remained unchanged between the western and other regions. CONCLUSION:Although TCM hospital number, scale, and doctors' workload increased over the past 13 years, substantial regional disparities remained. The 2009 health reforms did not significantly change the regional disparities in health care resources, especially between the eastern and western regions.

Project description:BackgroundCommunities with more Black or Hispanic residents have higher coronavirus rates than communities with more White residents, but relevant community characteristics are underexplored. The purpose of this study was to investigate poverty-, race- and ethnic-based disparities and associated economic, housing, transit, population health and health care characteristics.MethodsSix-month cumulative coronavirus incidence and mortality were examined using adjusted negative binomial models among all U.S. counties (n = 3142). County-level independent variables included percentages in poverty and within racial/ethnic groups (Black, Hispanic, Native American, Asian), and rates of unemployment, lacking a high school diploma, housing cost burden, single parent households, limited English proficiency, diabetes, obesity, smoking, uninsured, preventable hospitalizations, primary care physicians, hospitals, ICU beds and households that were crowded, in multi-unit buildings or without a vehicle.ResultsCounties with higher percentages of Black (IRR = 1.03, 95% CI: 1.02-1.03) or Hispanic (IRR = 1.02, 95% CI: 1.01-1.03) residents had more coronavirus cases. Counties with higher percentages of Black (IRR = 1.02, 95% CI: 1.02-1.03) or Native American (IRR = 1.02, 95% CI: 1.01-1.04) residents had more deaths. Higher rates of lacking a high school diploma was associated with higher counts of cases (IRR = 1.03, 95% CI: 1.01-1.05) and deaths (IRR = 1.04, 95% CI: 1.01-1.07). Higher percentages of multi-unit households were associated with higher (IRR = 1.02, 95% CI: 1.01-1.04) and unemployment with lower (IRR = 0.96, 95% CI: 0.94-0.98) incidence. Higher percentages of individuals with limited English proficiency (IRR = 1.09, 95% CI: 1.04-1.14) and households without a vehicle (IRR = 1.04, 95% CI: 1.01-1.07) were associated with more deaths.ConclusionsThese results document differential pandemic impact in counties with more residents who are Black, Hispanic or Native American, highlighting the roles of residential racial segregation and other forms of discrimination. Factors including economic opportunities, occupational risk, public transit and housing conditions should be addressed in pandemic-related public health strategies to mitigate disparities across counties for the current pandemic and future population health events.

Project description:BackgroundWith the increased availability of data, a growing number of studies have been conducted to address the impact of social determinants of health (SDOH) factors on population health outcomes. However, such an impact is either examined at the county level or the state level in the United States. The results of analysis at lower administrative levels would be useful for local policy makers to make informed health policy decisions.ObjectiveThis study aimed to investigate the ecological association between SDOH factors and population health outcomes at the census tract level and the city level. The findings of this study can be applied to support local policy makers in efforts to improve population health, enhance the quality of care, and reduce health inequity.MethodsThis ecological analysis was conducted based on 29,126 census tracts in 499 cities across all 50 states in the United States. These cities were grouped into 5 categories based on their population density and political affiliation. Feature selection was applied to reduce the number of SDOH variables from 148 to 9. A linear mixed-effects model was then applied to account for the fixed effect and random effects of SDOH variables at both the census tract level and the city level.ResultsThe finding reveals that all 9 selected SDOH variables had a statistically significant impact on population health outcomes for ≥2 city groups classified by population density and political affiliation; however, the magnitude of the impact varied among the different groups. The results also show that 4 SDOH risk factors, namely, asthma, kidney disease, smoking, and food stamps, significantly affect population health outcomes in all groups (P<.01 or P<.001). The group differences in health outcomes for the 4 factors were further assessed using a predictive margin analysis.ConclusionsThe analysis reveals that population density and political affiliation are effective delineations for separating how the SDOH affects health outcomes. In addition, different SDOH risk factors have varied effects on health outcomes among different city groups but similar effects within city groups. Our study has 2 policy implications. First, cities in different groups should prioritize different resources for SDOH risk mitigation to maximize health outcomes. Second, cities in the same group can share knowledge and enable more effective SDOH-enabled policy transfers for population health.

Dataset Information

A Survey of Health Disparities, Social Determinants of Health, and Converging Morbidities in a County Jail: A Cultural-Ecological Assessment of Health Conditions in Jail Populations.

Publications

A Survey of Health Disparities, Social Determinants of Health, and Converging Morbidities in a County Jail: A Cultural-Ecological Assessment of Health Conditions in Jail Populations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets