To examine trends in opioid overdose deaths by race/ethnicity from 2018 to 2019 across 67 HEALing Communities Study (HCS) communities in Kentucky, New York, Massachusetts, and Ohio.
We used state ...death certificate records to calculate opioid overdose death rates per 100 000 adult residents of the 67 HCS communities for 2018 and 2019. We used Poisson regression to calculate the ratio of 2019 to 2018 rates. We compared changes by race/ethnicity by calculating a ratio of rate ratios (RRR) for each racial/ethnic group compared with non-Hispanic White individuals.
Opioid overdose death rates were 38.3 and 39.5 per 100 000 for 2018 and 2019, respectively, without a significant change from 2018 to 2019 (rate ratio = 1.03; 95% confidence interval CI = 0.98, 1.08). We estimated a 40% increase in opioid overdose death rate for non-Hispanic Black individuals (RRR = 1.40; 95% CI = 1.22, 1.62) relative to non-Hispanic White individuals but no change among other race/ethnicities.
Overall opioid overdose death rates have leveled off but have increased among non-Hispanic Black individuals.
An antiracist public health approach is needed to address the crisis of opioid-related harms. (
. 2021;111(10):1851-1854. https://doi.org/10.2105/AJPH.2021.306431).
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Opioid use disorder is a serious public health crisis in the United States. Manifestations such as opioid overdose events (OOEs) vary within and across communities and there is growing evidence that ...this variation is partially rooted in community-level social and economic conditions. The lack of high spatial resolution, timely data has hampered research into the associations between OOEs and social and physical environments. We explore the use of non-traditional, “found” geospatial data collected for other purposes as indicators of urban social-environmental conditions and their relationships with OOEs at the neighborhood level. We evaluate the use of Google Street View images and non-emergency “311” service requests, along with US Census data as indicators of social and physical conditions in community neighborhoods. We estimate negative binomial regression models with OOE data from first responders in Columbus, Ohio, USA between January 1, 2016, and December 31, 2017. Higher numbers of OOEs were positively associated with service request indicators of neighborhood physical and social disorder and street view imagery rated as boring or depressing based on a pre-trained random forest regression model. Perceived safety, wealth, and liveliness measures from the street view imagery were negatively associated with risk of an OOE. Age group 50–64 was positively associated with risk of an OOE but age 35–49 was negative. White population, percentage of individuals living in poverty, and percentage of vacant housing units were also found significantly positive however, median income and percentage of people with a bachelor’s degree or higher were found negative. Our result shows neighborhood social and physical environment characteristics are associated with likelihood of OOEs. Our study adds to the scientific evidence that the opioid epidemic crisis is partially rooted in social inequality, distress and underinvestment. It also shows the previously underutilized data sources hold promise for providing insights into this complex problem to help inform the development of population-level interventions and harm reduction policies.
•A lack of timely, small-area data hampers research into the social and environmental determinants of opioid use disorder.•We explore the use of non-traditional, “found” geospatial data such as neighborhood service requests and street imagery.•Results provide new insights into social and neighborhood conditions that may contribute to opioid use disorder.•Non-traditional found geospatial data sources are valuable for understanding the opioid overdose crisis.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In a study of over 14,000 out-of-hospital cardiac arrests, bystander-initiated CPR was provided in about 28% of cases. Patients with cardiac arrest in low-income black neighborhoods were less likely ...to receive bystander-initiated CPR than those in high-income white neighborhoods.
More than 300,000 cases of out-of-hospital cardiac arrest occur in the United States each year.
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Outcomes of out-of-hospital cardiac arrest vary markedly,
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with survival rates ranging from 0.2% in Detroit
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to 16.0% in Seattle.
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This variation in survival rates can be explained, in part, by different rates of bystander-initiated cardiopulmonary resuscitation (CPR).
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,
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On average, bystanders administer CPR during fewer than one third of all out-of-hospital cardiac arrests.
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Prior studies have shown racial or ethnic-group and socioeconomic disparities in the provision of bystander-initiated CPR.
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–
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However, it is unclear to what extent such disparities are due to neighborhood effects, which . . .
Increasing evidence from experimental and non-experimental research has shown that children residing in disadvantaged neighborhoods exhibit greater levels of internalizing and externalizing ...behaviors, above and beyond individual characteristics, and family or school contexts. Using the ECLS-K, a nationally representative, longitudinal survey of U.S. school children, this study examined direct neighborhood effects on internalizing (N = 14,870; N = 10,610) and externalizing (N = 14,960; N = 10,730) behaviors at the beginning and end of elementary school. Using IPTW propensity scores to mitigate selection bias and ordinary least squares regression, we examined direct neighborhood effects when children were 7 years old (1st grade) and when they were 11 years old (5th grade). We also examined neighborhood effect modification by child child race/ethnicity, sex, family structure, and family SES. Both the direct effect and effect modification models indicated that living in disadvantaged neighborhoods had no impact on either internalizing or externalizing behaviors at the beginning of elementary school (age 7). At the end of elementary school (age 11), we found small, yet significant direct neighborhood associations with effect sizes ranging from 0.12 to 0.18 standard deviations. The effect modification analysis revealed that being black (relative to white) was the strongest moderator of the relationship between neighborhood context and internalizing and externalizing behaviors in 5th grade, with effect sizes ranging from 0.27 to 0.59 standard deviations. Being Hispanic in high poverty neighborhoods was found to be protective for externalizing behaviors, suggesting the presence of the Hispanic health paradox. We also found, that in some neighborhood contexts, child sex, family structure, and family socioeconomic status amplified or dampened the effect of neighborhood, but only for externalizing behaviors. These results demonstrate the importance of age-dependent neighborhood effects and that children with different demographic profiles respond differently to the social contexts in which they are exposed.
•Neighborhood effects on childhood behaviors were estimated at age 7 and 11.•Effect modification-sex, race/ethnicity, married, SES was examined at age 7 and 11.•No neighborhood effects at age 7; small direct neighborhood effects at age 11.•Race/ethnicity was the largest moderator of neighborhood-behavior association.•Sex, marital status, and SES impacted the way children responded to neighborhood.
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The International Initiative on Spatial Lifecourse Epidemiology (ISLE) convened its first International Symposium on Lifecourse Epidemiology and Spatial Science at the Lorentz Center in Leiden, ...Netherlands, 16–20 July 2018. Its aim was to further an emerging transdisciplinary field: Spatial Lifecourse Epidemiology. This field draws from a broad perspective of scientific disciplines including lifecourse epidemiology, environmental epidemiology, community health, spatial science, health geography, biostatistics, spatial statistics, environmental science, climate change, exposure science, health economics, evidence-based public health, and landscape ecology. The participants, spanning 30 institutions in 10 countries, sought to identify the key issues and research priorities in spatial lifecourse epidemiology. The results published here are a synthesis of the top 10 list that emerged out of the discussion by a panel of leading experts, reflecting a set of grand challenges for spatial lifecourse epidemiology in the coming years. https://doi.org/10.1289/EHP4868.
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Indoor and outdoor number concentrations of fine particulate matter (PM
), black carbon (BC), carbon monoxide (CO), and nitrogen dioxide (NO
) were monitored continuously for two to seven days in 28 ...low-income homes in Denver, Colorado, during the 2016 and 2017 wildfire seasons. In the absence of indoor sources, all outdoor pollutant concentrations were higher than indoors except for CO. Results showed that long-range wildfire plumes elevated median indoor PM
concentrations by up to 4.6 times higher than outdoors. BC, CO, and NO
mass concentrations were higher indoors in homes closer to roadways compared to those further away. Four of the homes with mechanical ventilation systems had 18% higher indoor/outdoor (I/O) ratios of PM
and 4% higher I/O ratios of BC compared to other homes. Homes with exhaust stove hoods had PM
I/O ratios 49% less than the homes with recirculating hoods and 55% less than the homes with no stove hoods installed. Homes with windows open for more than 12 hours a day during sampling had indoor BC 2.4 times higher than homes with windows closed. This study provides evidence that long-range wildfire plumes, road proximity, and occupant behavior have a combined effect on indoor air quality in low-income homes.
Understanding geographic and community-level factors associated with suicide can inform targeted suicide prevention efforts.
To estimate suicide rates and trajectories, assess associated county-level ...contextual factors, and explore variation across the rural-urban continuum.
This cross-sectional study included all individuals aged 25 to 64 years who died by suicide from January 1, 1999, to December 31, 2016, in the United States. Spatial analysis was used to map excess risk of suicide, and longitudinal random-effects models using negative binomial regression tested associations of contextual variables with suicide rates as well as interactions among county-level contextual variables. Data analyses were conducted between January 2019 and July 2019.
County of residence.
Three-year county suicide rates during an 18-year period stratified by rural-urban location.
Between 1999 and 2016, 453 577 individuals aged 25 to 64 years died by suicide in the United States. Decedents were primarily male (349 082 77.0%) with 101 312 (22.3%) aged 25 to 34 years, 120 157 (26.5%) aged 35 to 44 years, 136 377 (30.1%) aged 45 to 54 years, and 95 771 (21.1%) aged 55 to 64 years. Suicide rates were higher and increased more rapidly in rural than in large metropolitan counties. The highest deprivation quartile was associated with higher suicide rates compared with the lowest deprivation quartile, especially in rural areas, although this association declined during the period studied (rural, 1999-2001: incidence rate ratio IRR, 1.438; 95% CI, 1.319-1.568; P < .001; large metropolitan, 1999-2001: 1.208; 95% CI, 1.149-1.270; P < .001; rural, 2014-2016: IRR, 1.121; 95% CI, 1.032-1.219; P = .01; large metropolitan, 2014-2016: IRR, 0.942; 95% CI, 0.887-1.001; P = .06). The presence of more gun shops was associated with an increase in county-level suicide rates in all county types except the most rural (rural: IRR, 1.001; 95% CI, 0.999-1.004; P = .40; micropolitan: IRR, 1.005; 95% CI, 1.002-1.007; P < .001; small metropolitan: IRR, 1.010; 95% CI, 1.006-1.014; P < .001; large metropolitan: IRR, 1.012; 95% CI, 1.006-1.018; P < .001). High social capital was associated with lower suicide rates than low social capital (IRR, 0.917; 95% CI, 0.891-0.943; P < .001). High social fragmentation, an increasing percentage of the population without health insurance, and an increasing percentage of veterans in a county were associated with higher suicide rates (high social fragmentation: IRR, 1.077; 95% CI, 1.050-1.103; P < .001; percentage of population without health insurance: IRR, 1.005; 95% CI, 1.004-1.006; P < .001; percentage of veterans: IRR, 1.025; 95% CI, 1.021-1.028; P < .001).
This study found that suicide rates have increased across the nation and most rapidly in rural counties, which may be more sensitive to the impact of social deprivation than more metropolitan counties. Improving social connectedness, civic opportunities, and health insurance coverage as well as limiting access to lethal means have the potential to reduce suicide rates across the rural-urban continuum.
Deaths of despair (i.e., suicide, drug/alcohol overdose, and chronic liver disease and cirrhosis) have been increasing over the past 2 decades. However, no large-scale studies have examined ...geographic patterns of deaths of despair in the U.S. This ecologic study identifies geographic and temporal patterns of individual and co-occurring clusters of deaths of despair.
All individuals aged ≥10 years who died in the U.S. between 2000 and 2019 and resided within the 48 contiguous states and Washington, District of Columbia were included (N=2,171,105). Causes of death were limited to deaths of despair, namely suicide, drug/alcohol overdose, and chronic liver disease and cirrhosis. Univariate and multivariate space-time scan statistics were used to identify individual and co-occurring clusters with excess risk of deaths of despair. County-level RRs account for heterogeneity within each cluster. Analyses were conducted from late 2021 to early 2022.
Six suicide clusters, four overdose clusters, nine liver disease clusters, and three co-occurring clusters of all three types of deaths were identified. A large portion of the western U.S., southeastern U.S., and Appalachia/rust belt were contained within the co-occurring clusters. The co-occurring clusters had average county RRs ranging from 1.17 (p<0.001) in the southeastern U.S. to 4.90 (p<0.001) in the western U.S.
Findings support identifying and targeting risk factors common to all types of deaths of despair when planning public health interventions. Resources and policies that address all deaths of despair simultaneously may be beneficial for the areas contained within the co-occurring high-risk clusters.
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Previous studies have investigated spatial patterning and associations of area characteristics with suicide rates in Western and Asian countries, but few have been conducted in the United States. ...This ecological study aims to identify high-risk clusters of suicide in Ohio and assess area level correlates of these clusters. We estimated spatially smoothed standardized mortality ratios (SMR) using Bayesian conditional autoregressive models (CAR) for the period 2004 to 2013. Spatial and spatio-temporal scan statistics were used to detect high-risk clusters of suicide at the census tract level (N=2952). Logistic regression models were used to examine the association between area level correlates and suicide clusters. Nine statistically significant (p<0.05) high-risk spatial clusters and two space-time clusters were identified. We also identified several significant spatial clusters by method of suicide. The risk of suicide was up to 2.1 times higher in high-risk clusters than in areas outside of the clusters (relative risks ranged from 1.22 to 2.14 (p<0.01)). In the multivariate model, factors strongly associated with area suicide rates were socio-economic deprivation and lower provider densities. Efforts to reduce poverty and improve access to health and mental health medical services on the community level represent potentially important suicide prevention strategies.
•There was marked geographic variation in the incidence of suicide rates across the state of Ohio.•Suicide risk is associated with markers of socioeconomic deprivation and lower access to providers.•Reducing poverty and improving access to health services are important suicide prevention strategies.•Geospatial analyses have potential to inform public health efforts to prevent suicide.
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•Declaration of the COVID-19 national public health emergency impacted emergency department encounters for opioid overdose.•An immediate decline in ED rates for opioid overdose occurred after March ...14, 2020 in New York, Massachusetts, and Ohio.•Kentucky and Ohio saw a significant increase in opioid overdose after the emergency declaration.•The impact of the COVID-19 pandemic on encounters for suspected opioid overdose was highly heterogeneous across the 4 states.
Although national syndromic surveillance data reported declines in emergency department (ED) visits after the declaration of the national stay-at-home order for COVID-19, little is known whether these declines were observed for suspected opioid overdose.
This interrupted time series study used syndromic surveillance data from four states participating in the HEALing Communities Study: Kentucky, Massachusetts, New York, and Ohio. All ED encounters for suspected opioid overdose (n = 48,301) occurring during the first 31 weeks of 2020 were included. We examined the impact of the national public health emergency for COVID-19 (declared on March 14, 2020) on trends in ED encounters for suspected opioid overdose.
Three of four states (Massachusetts, New York and Ohio) experienced a statistically significant immediate decline in the rate of ED encounters for suspected opioid overdose (per 100,000) after the nationwide public health emergency declaration (MA: -0.99; 95 % CI: -1.75, -0.24; NY: -0.10; 95 % CI, -0.20, 0.0; OH: -0.33, 95 % CI: -0.58, -0.07). After this date, Ohio and Kentucky experienced a sustained rate of increase for a 13-week period. New York experienced a decrease in the rate of ED encounters for a 10-week period, after which the rate began to increase. In Massachusetts after a significant immediate decline in the rate of ED encounters, there was no significant difference in the rate of change for a 6-week period, followed by an immediate increase in the ED rate to higher than pre-COVID levels.
The heterogeneity in the trends in ED encounters between the four sites show that the national stay-at-home order had a differential impact on opioid overdose ED presentation in each state.
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