Dataset Information

Urban-Rural Disparities in Deaths of Despair: A County-Level Analysis 2004-2016 in the U.S.

ABSTRACT:

Introduction

The purpose of this study is to examine nationwide disparities in drug, alcohol, and suicide mortality; evaluate the association between county-level characteristics and these mortality rates; and illustrate spatial patterns of mortality risk to identify areas with elevated risk.

Methods

The authors applied a Bayesian spatial regression technique to investigate the association between U.S. county-level characteristics and drug, alcohol, and suicide mortality rates for 2004-2016, accounting for spatial correlation that occurs among counties.

Results

Mortality risks from drug, alcohol, and suicide were positively associated with the degree of rurality, the proportion of vacant housing units, the population with a disability, the unemployed population, the population with low access to grocery stores, and the population with no health insurance. Conversely, risks were negatively associated with Hispanic population, non-Hispanic Black population, and population with a bachelor's degree or higher.

Conclusions

Spatial disparities in drug, alcohol, and suicide mortality exist at the county level across the U.S. social determinants of health; educational attainment, degree of rurality, ethnicity, disability, unemployment, and health insurance status are important factors associated with these mortality rates. A comprehensive strategy that includes downstream interventions providing equitable access to healthcare services and upstream efforts in addressing socioeconomic conditions is warranted to effectively reduce these mortality burdens.

SUBMITTER: Lee JH

PROVIDER: S-EPMC10997338 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Urban-Rural Disparities in Deaths of Despair: A County-Level Analysis 2004-2016 in the U.S.

Lee Jong Hyung JH Wheeler David C DC Zimmerman Emily B EB Hines Anika L AL Chapman Derek A DA

American journal of preventive medicine 20221028 2

<h4>Introduction</h4>The purpose of this study is to examine nationwide disparities in drug, alcohol, and suicide mortality; evaluate the association between county-level characteristics and these mortality rates; and illustrate spatial patterns of mortality risk to identify areas with elevated risk.<h4>Methods</h4>The authors applied a Bayesian spatial regression technique to investigate the association between U.S. county-level characteristics and drug, alcohol, and suicide mortality rates for ...[more]

PMID: 38584644

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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.

Project description:BackgroundThe US pregnancy-related mortality ratio has not improved over the past decade and includes striking disparities by race and ethnicity and by state. Understanding differences in pregnancy-related mortality across and within urban and rural areas can guide the development of interventions for preventing future pregnancy-related deaths.ObjectiveWe sought to compare pregnancy-related mortality across and within urban and rural counties by race and ethnicity and age.Study designWe conducted a descriptive analysis of 3747 pregnancy-related deaths during 2011-2016 (the most recent available data) with available zone improvement plan code or county data in the Pregnancy Mortality Surveillance System, among Hispanic and non-Hispanic White, Black, American Indian or Alaska Native, and Asian or Pacific Islander women aged 15 to 44 years. We aggregated data by US county and grouped counties per the National Center for Health Statistics Urban-Rural Classification Scheme for Counties. We used R statistical software, epitools, to calculate the pregnancy-related mortality ratio (number of pregnancy-related deaths per 100,000 live births) for each urban-rural grouping, obtain 95% confidence intervals, and perform exact tests of ratio comparisons using the Poisson distribution.ResultsOf the total 3747 pregnancy-related deaths analyzed, 52% occurred in large metro counties, and 7% occurred in noncore (rural) counties. Large metro counties had the lowest pregnancy-related mortality ratio (14.8; 95% confidence interval, 14.2-15.5), whereas noncore counties had the highest (24.1; 95% confidence interval, 21.4-27.1), including race and ethnicity and age groups. Pregnancy-related mortality ratio age disparities increased with rurality. Women aged 25 to 34 years and 35 to 44 years living in noncore counties had pregnancy-related mortality ratios 1.5 and 3 times higher, respectively, than women of the same age groups in large metro counties. Within each urban-rural category, pregnancy-related mortality ratios were higher among non-Hispanic Black women than non-Hispanic White women. Non-Hispanic American Indian or Alaska Native pregnancy-related mortality ratios in small metro, micropolitan, and noncore counties were 2 to 3 times that of non-Hispanic White women in the same areas.ConclusionAlthough more than half of pregnancy-related deaths occurred in large metro counties, the pregnancy-related mortality ratio rose with increasing rurality. Disparities existed in urban-rural categories, including by age group and race and ethnicity. Geographic location is an important context for initiatives to prevent future deaths and eliminate disparities. Further research is needed to better understand reasons for the observed urban-rural differences and to guide a multifactorial response to reduce pregnancy-related deaths.

Project description:ImportanceStudies suggest the risk of suicide among people with cancer diagnosis is higher compared with the general population. However, little is known about how suicide risk among people diagnosed with cancer might vary according to area-level income and rurality.ObjectiveTo examine whether the risks and patterns of suicide mortality among people with a cancer diagnosis differ by US county-level median income and rural or urban status.Design, setting, and participantsA retrospective, population-based cohort study following up individuals who were diagnosed with cancer between January 1, 2000, and December 31, 2016, was conducted. The Surveillance, Epidemiology, and End Results Program 18 registries (SEER 18) database was used to obtain data on persons diagnosed with a first primary malignant tumor. Comparisons with the general US population were based on mortality data collected by the National Center for Health Statistics. Analyses were conducted from February 22 to October 14, 2020.ExposuresCounty-level median household income and urban or rural status.Main outcomes and measuresStandardized mortality ratios (SMRs) of suicide deaths and annual percentage changes (APCs) of SMRs.ResultsThe SEER 18 database included 5 362 782 persons with cancer diagnoses living in 635 counties. Most study participants were men (51.2%), White (72.2%), and older than 65 years (49.7%). Among them, 6357 persons died of suicide (SMR, 1.41; 95% CI, 1.38-1.44). People with cancer living in the lowest-income counties had a significantly higher risk (SMR, 1.94; 95% CI, 1.76-2.13) than those in the highest-income counties (SMR, 1.30; 95% CI, 1.26-1.34). Those living in rural counties also had significantly higher SMR than those in urban counties (SMR, 1.81; 95% CI, 1.70-1.92 vs SMR, 1.35; 95% CI, 1.32-1.39). For all county groups, the SMRs were the highest within the first year following cancer diagnosis. However, among people living in the lowest-income counties, the risk remained significantly high even after 10 or more years following cancer diagnosis (SMR, 1.83; 95% CI, 1.31-2.48). The comparative risk of suicide mortality within 1 year following cancer diagnosis significantly decreased over the years but then plateaued in the highest-income (2005-2015: APC, 2.03%; 95% CI, -0.97% to 5.13%), lowest-income (2010-2015: APC, 4.80%; 95% CI, -19.97% to 37.24%), and rural (2004-2015: APC, 1.83; 95% CI, -1.98% to 5.79%) counties.Conclusions and relevanceThis cohort study showed disparities in suicide risks and their patterns among people diagnosed with cancer by county-level income and rural or urban status. The findings suggest that additional research and effort to provide psychological services addressing these disparities among people with cancer may be beneficial.

Project description:ObjectiveTo characterize health disparities in common chronic diseases among adults by socioeconomic status (SES) and ethnicity in a mixed rural-urban community of the United States.Patients and methodsWe conducted a cross-sectional study to assess the association of the prevalence of the 5 most burdensome chronic diseases in adults with SES and ethnicity and their interaction. The Rochester Epidemiology Project medical records linkage system was used to identify the prevalence of coronary heart disease, asthma, diabetes, hypertension, and mood disorder using International Classification of Diseases, Ninth Revision codes recorded from January 1, 2005, through December 31, 2009, among all adult residents of Olmsted County, Minnesota, on April 1, 2009. For SES measurements, an individual HOUsing-based index of SocioEconomic Status (HOUSES) derived from real property data was used. Logistic regression models were used to examine the association of the prevalence of chronic diseases with ethnicity and HOUSES score and their interaction.ResultsWe identified 88,010 eligible adults with HOUSES scores available, of whom 48,086 (54.6%) were female and 80,699 (91.7%) were non-Hispanic white; the median (interquartile range) age was 45 years (30-58 years). Overall and in the subgroup of non-Hispanic whites, SES measured by HOUSES was inversely associated with the prevalence of all 5 chronic diseases independent of age, sex, and ethnicity (P<.001). While an association of ethnicity with disease prevalence was observed for all the chronic diseases, SES modified the effect of ethnicity for clinically less overt conditions (interaction P<.05 for each condition [diabetes, hypertension, and mood disorder]) but not for coronary heart disease, a clinically more overt condition.ConclusionIn a mixed rural-urban setting with a predominantly non-Hispanic white population, health disparities in chronic diseases still exist across SES. The extent to which SES modifies the effect of ethnicity on the risk of chronic diseases may depend on the nature of the disease.

Dataset Information

Urban-Rural Disparities in Deaths of Despair: A County-Level Analysis 2004-2016 in the U.S.

Introduction

Methods

Results

Conclusions

Publications

Urban-Rural Disparities in Deaths of Despair: A County-Level Analysis 2004-2016 in the U.S.

Similar Datasets

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