Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999-2009

Risk factors for persistent fatal opioid-involved overdose clusters in Massachusetts 2011-2021: a spatial statistical analysis with socio-economic, accessibility, and prescription factors

BACKGROUND

Fatal opioid-involved overdose rates increased precipitously from 5.0 per 100,000 population to 33.5 in Massachusetts between 1999 and 2022.

METHODS

We used spatial rate smoothing techniques to identify persistent opioid overdose-involved fatality clusters at the ZIP Code Tabulation Area (ZCTA) level. Rate smoothing techniques were employed to identify locations of high fatal opioid overdose rates where population counts were low. In Massachusetts, this included areas with both sparse data and low population density. We used Local Indicators of Spatial Association (LISA) cluster analyses with the raw incidence rates, and the Empirical Bayes smoothed rates to identify clusters from 2011 to 2021. We also estimated Empirical Bayes LISA cluster estimates to identify clusters during the same period. We constructed measures of the socio-built environment and potentially inappropriate prescribing using principal components analysis. The resulting measures were used as covariates in Conditional Autoregressive Bayesian models that acknowledge spatial autocorrelation to predict both, if a ZCTA was part of an opioid-involved cluster for fatal overdose rates, as well as the number of times that it was part of a cluster of high incidence rates.

RESULTS

LISA clusters for smoothed data were able to identify whether a ZCTA was part of a opioid involved fatality incidence cluster earlier in the study period, when compared to LISA clusters based on raw rates. PCA helped in identifying unique socio-environmental factors, such as minoritized populations and poverty, potentially inappropriate prescribing, access to amenities, and rurality by combining socioeconomic, built environment and prescription variables that were highly correlated with each other. In all models except for those that used raw rates to estimate whether a ZCTA was part of a high fatality cluster, opioid overdose fatality clusters in Massachusetts had high percentages of Black and Hispanic residents, and households experiencing poverty. The models that were fitted on Empirical Bayes LISA identified this phenomenon earlier in the study period than the raw rate LISA. However, all the models identified minoritized populations and poverty as significant factors in predicting the persistence of a ZCTA being part of a high opioid overdose cluster during this time period.

CONCLUSION

Conducting spatially robust analyses may help inform policies to identify community-level risks for opioid-involved overdose deaths sooner than depending on raw incidence rates alone. The results can help inform policy makers and planners about locations of persistent risk.

Enzyme-loaded rod-like microgel shapes: a step towards the creation of shape-specific microreactors for blood detoxification purposes

Rapid removal of toxic substances is crucial to restore the normal functions of our body and ensure survival. Due to their high substrate specificity and catalytic efficiency, enzymes are unique candidates to deplete toxic compounds. While enzymes display several limitations including low stability and high immunogenicity, these can be overcome by entrapping them in a diverse range of carriers. The resulting micro/nanoreactors shield the enzymes from their surroundings, preventing their misfolding or denaturation thus allowing them to conduct their function. The micro/nanoreactors must circulate in the blood stream for extended periods of time to ensure complete depletion of the toxic agents. Surprisingly, while it is widely acknowledged that non-spherical carriers exhibit longer residence time in the bloodstream than their spherical counterparts, so far, all the reported micro/nanoreactors have been assembled with a spherical architecture. Herein, we address this important issue by pioneering the first shape-specific microreactors. We use UV-assisted punching to create rod-like microgel shapes with dimensions of 8 μm × 1 μm × 2 μm and demonstrate their biocompatibility by conducting hemolysis and cell viability assays with a macrophage and an endothelial cell line. Upon encapsulation of the model enzyme β-lactamase, the successful fabrication of rod-shaped microreactors is demonstrated by their ability to convert the yellow nitrocefin substrate into its hydrolyzed product.

Rural health care worker wellness during COVID-19: Compassion fatigue, compassion satisfaction & utilization of wellness resources

OBJECTIVE

The goal of this study was to identify factors associated with compassion fatigue (CF) and compassion satisfaction (CS) among rural health care workers (HCWs) during the COVID-19 pandemic. The secondary purpose was to assess utilization of wellness resources and preferences for new resources.

METHODS

A survey was distributed (October-December 2020) and completed by faculty, clinicians and staff (n = 406) at a rural university. Measures included a modified version of the Professional Quality of Life Scale (PROQOL-21), the Patient Health Questionnaire-4 and the Brief Resilience Coping Scale. Respondents reported their use of wellness resources and their preferences for new resources.

RESULTS

The mean CF score was 21.1, the mean CS score was 26.8 and 42.0% screened positive for depression or anxiety. Few of the existing wellness resources were utilized and respondents' preferences for new wellness resources included time off (70.7%), onsite food trucks (43.0%) and support animals (36.5%). Younger age, depression and anxiety were associated with higher CF. Older age, better mental health and resilience were associated with higher CS.

CONCLUSIONS

Rural HCWs have high CF, yet few utilize wellness resources. Rural health care organizations may foster wellness by providing time off for self-care, expanding mental health services and building resilience.

Social vulnerability predictors of drug poisoning mortality: A machine learning analysis in the United States

BACKGROUND AND OBJECTIVES

Drug poisoning is a leading cause of unintentional deaths in the United States. Despite the growing literature, there are a few recent analyses of a wide range of community-level social vulnerability features contributing to drug poisoning mortality. Current studies on this topic face three limitations: often studying a limited subset of vulnerability features, focusing on small sample sizes, or solely including local data. To address this gap, we conducted a national-level analysis to study the impacts of several social vulnerability features in predicting drug mortality rates in the United States.

METHODS

We used machine learning to investigate the role of 16 social vulnerability features in predicting drug mortality rates for US counties in 2014, 2016, and 2018-the most recent available data. We estimated each vulnerability feature's gain relative contribution in predicting drug poisoning mortality.

RESULTS

Among all social vulnerability features, the percentage of noninstitutionalized persons with a disability is the most influential predictor, with a gain relative contribution of 18.6%, followed by population density and the percentage of minority residents (13.3% and 13%, respectively). Percentages of households with no available vehicles, mobile homes, and persons without a high school diploma are the following features with gain relative contributions of 6.3%, 5.8%, and 5.1%, respectively.

CONCLUSION AND SCIENTIFIC SIGNIFICANCE

We identified social vulnerability features that are most predictive of drug poisoning mortality. Public health interventions and policies targeting vulnerable communities may increase the resilience of these communities and mitigate the overdose death and drug misuse crisis.

Rethinking urban-rural designations in public health surveillance of the overdose crisis and crafting an agenda for future monitoring

Rurality has served as a key concept in popular and scientific understandings of the US overdose crisis, with White, rural, and low-income areas thought to be most heavily affected. However, we observe that overdose trends have risen nearly uniformly across the urban-rural designations employed in most research, implying that their importance has likely been overstated or incorrectly conceptualized. Nevertheless, urbanicity/rurality does serve as a key axis to understand inequalities in overdose mortality when assessed with more nuanced modalities-employing a more granular analysis of geography at the sub-county level, and intersecting rurality sociodemographic indices such as race/ethnicity. Using national overdose data from 1999-2021, we illustrate the intersectional importance of rurality for overdose surveillance. Finally, we offer recommendations for integrating these insights into drug overdose surveillance moving forward.

A Methodological Review of Drug-Related Toxicological Studies in Saudi Arabia

This study aimed to conduct a methodological review of drug-related toxicological studies in Saudi Arabia. A systematic review and a methodological analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Medline and Embase were searched for all types of studies reporting toxicological studies in the English language published until January 10, 2022. The search was conducted using both keywords and Medical Subject Headings (MeSH) terms. The methodological analysis of included studies was assessed using the Newcastle-Ottawa Scale. A total of 3,750 studies were extracted and screened. Of these, 30 observational studies (seven cohort studies and 23 cross-sectional studies) met the inclusion criteria. The methodological scores ranged from five to seven out of 10 possible points. Twelve studies had high quality, and 18 studies had moderate quality. Eight studies focused on adverse drug reactions, eight explored poisoning, four explored drug-related hospitalizations, nine explored drug-induced toxicity, and one explored drug overdose. This research project revealed that most of the drug-related toxicological studies conducted in Saudi Arabia were observational studies of moderate quality. Future studies should focus on the quality of the design and reporting.

Geography, rurality, and community distress: deaths due to suicide, alcohol-use, and drug-use among Colorado Veterans

BACKGROUND

In the USA, deaths due to suicide, alcohol, or drug-related causes (e.g., alcohol-related liver disease, overdose) have doubled since 2002. Veterans appear disproportionately impacted by growing trends. Limited research has been conducted regarding the relationship between community-level factors (e.g., rurality, community distress resulting from economic conditions) and the presence of spatial clustering of suicide, alcohol-related, or drug-related deaths. We explored community-level relationships in Colorado Veterans and compared suicide, alcohol-, and drug-related death rates between the Colorado adult population and Veterans.

METHODS

2009-2020 suicide, alcohol-related, and/or drug-related deaths were identified using qualifying multiple cause-of-death International Classification of Disease (ICD)-10 codes in CDC WONDER for the general adult population and Colorado death data for Veteran populations. Age and race adjusted rates were calculated to compare risk overall and by mortality type (i.e., suicide, alcohol-related, drug-related). In Veteran decedents, age-adjusted rates were stratified by rurality and community distress, measured by the Distressed Communities Index. Standardized mortality ratios were calculated to measure spatial autocorrelation and identify clusters using global and local Moran's I, respectively.

RESULTS

6.4% of Colorado Veteran deaths (n = 6948) were identified as being related to suicide, alcohol, or drugs. Compared to rates in the general population of Colorado adults, Veterans had 1.8 times higher rates of such deaths overall (2.1 times higher for suicide, 1.8 times higher for alcohol-related, 1.3 times higher for drug-related). Among Veterans, community distress was associated with an increased risk of alcohol-related [age-adjusted rate per 100,000 (95% CI) = 129.6 (89.9-193.1)] and drug-related deaths [95.0 (48.6-172.0)]. This same significant association was not identified among those that died by suicide. Rurality was not associated with risk for any of the deaths of interest. There was significant spatial clustering for alcohol-related deaths in southeast Colorado.

CONCLUSIONS

Colorado Veterans have higher rates of deaths due to suicide, alcohol-related, and drug-related causes compared to members of the general adult population. Upstream prevention efforts, such as community-based interventions targeting alcohol-use and community economic distress, are warranted. More research is also needed to understand how community distress and other social determinants of health impact the community burden of suicide, alcohol-related, and drug-related mortality.

Supply-side predictors of fatal drug overdose in the Washington/Baltimore HIDTA region: 2016-2020

BACKGROUND

Rising rates of fentanyl- and polydrug-involved drug overdose deaths have prompted inquiry into the role of drug supply in fatal overdose outcomes in the United States. To date, however, there have been few empirical investigations of drug enforcement strategies on fatal overdose rates, despite knowledge that both drug use and supply are often geographically distributed. To address this limitation, we examined measures of drug enforcement as predictors of next-year fatal overdose rates in the Washington/Baltimore High Intensity Drug Trafficking Area (W/B HIDTA).

METHODS

We conducted mixed-effects models to examine the role of drug seizures and disruption in drug trafficking organizations (DTOs) and money laundering organizations (MLOs) on fatal overdose rates over a 5-year period (2016-2020) across 45 local jurisdictions in the W/B HIDTA region. Outcomes included any, opioid-involved, and fentanyl-involved fatal overdose.

RESULTS

Adjusting for covariates, both the total number of drug seizures and amount of cocaine seized (in dosage units per capita) positively predicted next-year opioid- and fentanyl-involved fatal overdose rates. Disruption to DTO and MLO operations did not significantly predict next-year fatal overdose rates for any outcome.

CONCLUSION

Supply-side enforcement activities alone may have limited impact on reducing fatal overdose rates, but may serve as important markers to identify communities at high risk of fatal overdose and facilitate targeted intervention. Our findings underscore the importance of comprehensive law enforcement approaches that extend beyond drug enforcement to integrate prevention, linkage to treatment, and harm reduction strategies as needed to address the overdose epidemic.

State level variation in substance use treatment admissions among criminal legal-referred individuals

BACKGROUND

Individuals involved in the criminal legal system face unique challenges to accessing substance use disorder (SUD) treatment, yet state-level variation in referrals for treatment remains largely unknown. To address disparities in the overdose crisis among individuals with criminal legal involvement, it is important to understand variation in SUD treatment across states.

METHODS

We conducted a retrospective comparison of substance use treatment referrals from the criminal legal system and other sources across participating states. Using data from the 2018-2019 Treatment Episode Dataset-Admissions, we characterized treatment referral rates from the criminal legal system, the substances most commonly leading to treatment, and rates of treatment with medication for opioid use disorder (MOUD) across states.

RESULTS

Across all states, criminal legal referral rates were higher than non-criminal legal rates. Criminal-legal referral rates, adjusted for state overdose deaths, were highest in the Northeast and Midwest. Methamphetamine use was the most common substance leading to treatment referral from the criminal legal system in 24 states while opioid use was the most common reason for non-criminal legal referrals in 34 states. In over half the states analyzed, fewer than 10% of opioid treatment referrals from the criminal legal system received MOUD. In almost all states, MOUD was more common in treatment referred from non-criminal legal settings.

CONCLUSION

State-specific policies and practices shape drug policy and the SUD treatment landscape for people with criminal legal involvement. Standards and ongoing monitoring for substance use treatment referrals from the criminal-legal system should be considered by federal agencies charged with addressing the ongoing overdose crisis.

Identifying counties at risk of high overdose mortality burden during the emerging fentanyl epidemic in the USA: a predictive statistical modelling study

BACKGROUND

The emergence of fentanyl around 2013 represented a new, deadly stage of the opioid epidemic in the USA. We aimed to develop a statistical regression approach to identify counties at the highest risk of high overdose mortality in the subsequent years by predicting annual county-level overdose death rates across the contiguous USA and to validate our approach against observed overdose mortality data collected between 2013 and 2018.

METHODS

We fit mixed-effects negative binomial regression models to predict overdose death rates in the subsequent year for 2013-18 for all contiguous state counties in the USA (ie, excluding Alaska and Hawaii). We used publicly available county-level data related to health-care access, drug markets, socio-demographics, and the geographical spread of opioid overdose as model predictors. The crude number of county-level overdose deaths was extracted from restricted US Centers for Disease Control and Prevention mortality records. To predict county-level overdose rates for the year 201X: (1) a model was trained on county-level predictor data for the years 2010-201(X-2) paired with county-level overdose deaths for the year 2011-201(X-1); (2) county-level predictor data for the year 201(X-1) was fed into the model to predict the 201X county-level crude number of overdose deaths; and (3) the latter were converted to a population-adjusted rate. For comparison, we generated a benchmark set of predictions by applying the observed slope of change in overdose death rates in the previous year to 201(X-1) rates. To assess the predictive performance of the model, we compared predicted values (of both the model and benchmark) to observed values by (1) calculating the mean average error, root mean squared error, and Spearman's correlation coefficient and (2) assessing the proportion of counties in the top decile (10%) of overdose death rates that were correctly predicted as such. Finally, in a post-hoc analysis, we sought to identify variables with greatest predictive utility.

FINDINGS

Between 2013 and 2018, among the 3106 US counties included, our modelling approach outperformed the benchmark strategy across all metrics. The observed average county-level overdose death rate rose from 11·8 per 100 000 people in 2013 to 15·4 in 2017 before falling to 14·6 in 2018. Our negative binomal modelling approach similarly identified an increasing trend, predicting an average 11·8 deaths per 100 000 in 2013, up to 15·1 in 2017, and increasing further to 16·4 in 2018. The benchmark model over-predicted average death rates each year, ranging from 13·0 per 100 000 in 2013 to 18·3 in 2018. Our modelling approach successfully ranked counties by overdose death rate identifying between 42% and 57% of counties in the top decile of overdose mortality (compared with 29% and 43% using the benchmark) each year and identified 194 of the 808 counties with emergent overdose outbreaks (ie, newly entered the top decile) across the study period, versus 31 using the benchmark. In the post-hoc analysis, we identified geospatial proximity of overdose in nearby counties, opioid prescription rate, presence of an urgent care facility, and several economic indicators as the variables with the greatest predictive utility.

INTERPRETATION

Our model shows that a regression approach can effectively predict county-level overdose death rates and serve as a risk assessment tool to identify future high mortality counties throughout an emerging drug use epidemic.

FUNDING

National Institute on Drug Abuse.

Establishing Peer Recovery Support Services to Address the Central Appalachian Opioid Epidemic: The West Virginia Peers Enhancing Education, Recovery, and Survival (WV PEERS) Pilot Program

Introduction

Central Appalachia has been disproportionately affected by the opioid epidemic and overdose fatalities. We developed West Virginia Peers Enhancing Education, Recovery, and Survival (WV PEERS), a program based on peer recovery support, to engage individuals using opioids and link them with a range of services.

Methods

Community partners providing services to individuals with opioid use disorder (OUD) were identified and collaborations were formalized using a standardized memorandum of understanding. The program was structured to offer ongoing peer recovery support specialist (PRSS) services, not just a one-time referral. A website and cards describing the WV PEERS program were developed and disseminated via community partners and community education sessions.

Results

Overall, 1456 encounters with individuals with OUD (mean= 2 encounters per individual) occurred in a variety of community settings over 8 months. The majority of referrals were from harm reduction programs. Overall, 63.9% (n=931) of individuals served by WV PEERS accessed services for substance use disorders and/or mental health problems. Over half (52.3%; n = 487) of individuals entered substance use and/or mental health treatment, and nearly a third (30.4%; n = 283) remained in treatment over six months.

Implications

Using the WV PEERS model, PRSSs effectively engaged and linked individuals with OUD to mental health and substance use treatment in rural central Appalachia. Future research is needed to determine whether these services reduce the risk of overdose mortality.

Spatiotemporal Trends in Opioid Overdose Deaths by Race for Counties in Ohio

BACKGROUND

The opioid epidemic continues to be an ongoing public health crisis in the United States. Initially, large increases in overdose death rates were observed in largely rural, White communities, leading to the initial perception that the opioid epidemic was primarily a problem for the White population. Recent findings have shown increasing rates of overdose death among Blacks. We compare overdose rates between Blacks and Whites and explore county-level spatiotemporal heterogeneity in Ohio.

METHODS

We obtained county-level opioid overdose death counts for Whites and Blacks from 2007 to 2018 in Ohio. We fit a Bayesian multivariate spatial rates model to estimate annual standardized mortality ratios for Whites and Blacks for each county. We accounted for correlation between racial groups in the same county and across space and time. We also estimated differences in the mean trends between urban and rural counties for each racial group.

RESULTS

The overall overdose death rate in the state was increasing until 2018. County-level death rates for Whites were higher than Blacks throughout the state early in the study period. Death rates for Blacks increased throughout the study period and were comparable to the rates for Whites by the end of the study in many counties.

CONCLUSIONS

County-level opioid overdose death rates increased faster for Blacks than Whites during the study. By 2018, death rates were comparable for Blacks and Whites in many counties. The opioid epidemic spans racial groups in Ohio and trends indicate that overdose is a growing problem among Blacks.

Something to despair: Gender differences in adverse childhood experiences among rural patients

Existing research has demonstrated that patients in treatment for an opioid use disorder (OUD) have high rates of adverse childhood experiences (ACE) compared to community-based samples. While research has documented important gender differences in ACEs in patients with OUD receiving treatment in urban areas, research has not shown whether these findings would generalize to rural and Appalachian areas, which are known to have lower ACE scores. We conducted a secondary analysis of existing clinical data, utilizing intake assessment data from a rural Appalachian outpatient buprenorphine program. We restricted the sample to patients with an OUD who presented for treatment between June 2018 and June 2019 (n = 173). The clinical intake assessment included a modified 17-item ACE instrument that patients self-administered. More than half (54.3%) of patients reported having experienced 4+ categories of adverse childhood experiences. On average, females endorsed 4.5 categories of adverse experiences, whereas males endorsed 3.3 (p < 0.00); female patients were significantly more likely to have experienced sexual abuse (42.4% versus 10.6%, p < 0.00). Alarmingly, 25.9% of females and 8.2% of males reported being forced to have sex before age 18. Disproportionately high rates of childhood adversities, particularly among females, may partially explain despair in rural Appalachian areas. OUD treatment programs should conduct clinical assessments of trauma and integrate trauma-informed care into drug treatment, especially for female patients residing in rural Appalachia.

How does socioeconomic status affect the incidence of hospital-treated poisonings? A retrospective study

BACKGROUND

Hospital-treated poisonings have a good outcome in general. The role of regional differences and socioeconomic status has been established in intensive care admissions and various causes of death, but not yet in hospital-treated poisonings. We set out to determine whether the incidence of hospital-treated poisonings is affected by the annual income of the residential area.

METHODS

All poisonings in Northern Ostrobothnia region of Finland treated in Oulu University Hospital during 2013-2016 were studied. Oulu University Hospital is the primary hospital in the area. Postal code areas of the county were categorized on the basis of their median annual net income as low-, middle- and high-income areas.

RESULTS

A total of 2142 poisoning cases were studied. The number of individual patients was 1525. In the low-income areas, the crude incidence of poisonings was more than 2-fold when compared with the middle- and high-income areas. In adolescents aged 13 to 17 years, the incidence in the low-income areas was almost 3-fold compared with the other two categories at 335/100 000/year (95% CI, 236-463). Four patients (0.2%) died during the hospital stay and 50 patients (2.3%) died within 6 months from the last admission.

CONCLUSIONS

The incidence of hospital-treated poisoning was at least 2-fold in low-income areas when compared with middle- or high-income areas. For adolescent population from 13 to 17 years, the incidence in low-income areas was almost 3-fold when compared with other areas.

The Bell Tolls for Thee & Thine: Compassion Fatigue & the Overdose Epidemic

Non-fatal and fatal overdoses are traumatic events that have been increasing over the past 20 years and disproportionately impacting rural communities in the United States. The human suffering caused by the opioid epidemic is rarely described in the empirical literature. The purpose of this article is to 1) define individual- and community-level overdose-related compassion fatigue (OCF), 2) review measurement of compassion fatigue (CF) and interventions to reduce CF, 3) discuss strategies that may reduce OCF and 4) briefly discuss policy implications. OCF is distress resulting from knowledge of or exposure to overdose-related harms, which at the community-level may prohibit collaboration and adaptive agency to effectively respond. When OCF occurs at a community-level, it could have negative consequences by eroding support for evidence-based services and fueling stigma-driven policies that blame people who use drugs. Empathy underlies both OCF and vicarious resilience by allowing one to understand the suffering caused by overdose deaths and to witness the joy of addiction recovery. Using the risk environment framework, OCF at the micro- and macro-levels of the social environment, may increase rural communities' vulnerability to harm by emphasizing individual responsibility for reducing overdoses rather than community-level infrastructure and resource management. Additional research is needed to develop a measure of OCF and to confirm whether OCF is associated with increased stigma and decreased support for harm reduction in rural areas.

Trends in Hospital Mortality for Uninsured Rural and Urban Populations, 2012-2016

PURPOSE

Rural-urban health disparities have received increasing scrutiny as rural individuals continue to have worse health outcomes. However, little is known about how insurance status contributes to urban-rural disparities. This study characterizes how rural uninsured patients compare to the urban uninsured, determines whether rurality among the uninsured is associated with worse clinical outcomes, and examines how clinical outcomes based on rurality have changed over time.

METHODS

We conducted a retrospective cohort study of the 2012-2016 National Inpatient Sample hospital discharge data including 1,478,613 uninsured patients, of which 233,816 were rural. Admissions were broken into 6 rurality categories. Logistic regression models were used to determine the independent association between rurality and hospital mortality.

FINDINGS

Demographic and clinical characteristics differed significantly between rural and urban uninsured patients: rural patients were more often white, lived in places with lower median household income, and were more often admitted electively and transferred. Rurality was associated with significantly higher in-hospital mortality rates (1.44% vs 1.89%, OR 1.32, P < .001). This association strengthened after adjusting for medical comorbidities and hospital characteristics. Further, disparities between urban and rural mortality were found to be growing, with the gap almost doubling between 2012 and 2016.

CONCLUSIONS

Rural and urban uninsured patients differed significantly, specifically in terms of race and median income. Among the uninsured, rurality was associated with higher in-hospital mortality, and the gap between urban and rural in-hospital mortality was widening. Our findings suggest the rural uninsured are a vulnerable population in need of informed, tailored policies to reduce these disparities.

Using socially-sensed data to infer ZIP level characteristics for the spatiotemporal analysis of drug-related health problems in Maryland

This research investigated how socially sensed data can be used to detect ZIP level characteristics that are associated with spatial and temporal patterns of Emergency Department patients with a chief complaint and/or diagnosis of overdose or drug-related health problems for four hospitals in Baltimore and Anne Arundel County, MD during 2016-2018. Dynamic characteristics were identified using socially-sensed data (i.e., geo-tagged Twitter data) at ZIP code level over varying temporal resolutions. Data about three place-based variables including comments and concerns about crime, drug use, and negative or depressed sentiments, were extracted from tweets, along with data from four socio-environmental variables from the American Community Survey were collected to explore socio-environmental characteristics during the same period. Our study showed a statistically significant increase in adjusted rates of Emergency Department (ED) visits occurred between June and November 2017 for patients residing in ZIP codes in western Baltimore and northeastern Anne Arundel County. During this period, the three topics extracted from Twitter data were highly correlated with the ZIP codes where the patients were residing. Exploring the dynamic spatial associations between socio-environmental variables and ED visits for acute overdose assists local health officials in optimizing interventions for vulnerable locations.

Individual and county-level variation in outcomes following non-fatal opioid-involved overdose

BACKGROUND

A lack of large-scale, individually linked data often has impeded efforts to disentangle individual-level variability in outcomes from area-level variability in studies of many diseases and conditions. This study investigated individual and county-level variability in outcomes following non-fatal overdose in a state-wide cohort of opioid overdose patients.

METHODS

Participants were 24 031 patients treated by emergency medical services or an emergency department for opioid-involved overdose in Indiana between 2014 and 2017. Outcomes included repeat non-fatal overdose, fatal overdose and death. County-level predictors included sociodemographic, socioeconomic and treatment availability indicators. Individual-level predictors included age, race, sex and repeat non-fatal opioid-involved overdose. Multilevel models examined outcomes following non-fatal overdose as a function of patient and county characteristics.

RESULTS

10.9% (n=2612) of patients had a repeat non-fatal overdose, 2.4% (n=580) died of drug overdose and 9.2% (n=2217) died overall. Patients with a repeat overdose were over three times more likely to die of drug-related causes (OR=3.68, 99.9% CI 2.62 to 5.17, p<0.001). County-level effects were limited primarily to treatment availability indicators. Higher rates of buprenorphine treatment providers were associated with lower rates of mortality (OR=0.82, 95% CI 0.68 to 0.97, p=0.024), but the opposite trend was found for naltrexone treatment providers (OR=1.20, 95% CI 1.03 to 1.39, p=0.021). Cross-level interactions showed higher rates of Black deaths relative to White deaths in counties with high rates of naltrexone providers (OR=1.73, 95% CI 1.09 to 2.73, p=0.019).

CONCLUSION

Although patient-level differences account for most variability in opioid-related outcomes, treatment availability may contribute to county-level differences, necessitating multifaceted approaches for the treatment and prevention of opioid abuse.

Compositional and contextual factors associated with drug overdose deaths in the United States

Background: In 2017, the US Department of Health and Human Services declared the Opioid epidemic a public health emergency. In the US, emergency rooms treat more than 1,000 people each day for drug overdose, and 115 of them die. This study examines compositional and contextual factors associated with drug overdose deaths rates in the US. Methods: Local spatial autocorrelation statistics were used to estimate hot spot areas to identify census tracts with high risk of drug overdose death. Logistic regressions investigated the relationship between drug overdose death rates and various compositional and contextual variables across census tracks. Results: The adjusted logistic model shows that compositional variables: depression (OR = 2.47 [2.37-2.58]), poor mental health (OR = 1.71 [1.63-1.79]), median age 1.41 (1.36-1.47) and the percentage of people with a high school diploma (OR = 1.30 [1.24-1.35]) were positively associated with the rate of drug overdose deaths. On the other hand, contextual variables: the percentage having health insurance (OR = 0.66 [0.64-0.69]), the Theil's H index (OR = 0.69 [0.66-0.71]), population density (OR = 0.80 [0.77-0.84]), poverty (OR = 0.90 [0.86-0.95]), and median household income (OR = 0.91[0.86-0.96]) were negatively associated with drug overdose deaths. Discussion: The analysis reveals a consistently strong association between compositional mental health factors and census tract-level death rates from drug overdose.

Racial differences in overdose events and polydrug detection in Indianapolis, Indiana

BACKGROUND

We examine racial disparities in drug overdose death rates by analyzing trends in fatal and nonfatal overdose outcomes in a large metropolitan area (Indianapolis, Indiana).

METHODS

Death certificate and toxicology records for accidental drug overdose deaths from 2011 to 2018 were linked with emergency medical services (EMS) data. Bivariate comparisons examined differences in toxicology findings at the time of death as well as prior EMS events both overall and by indicator of non-fatal overdose.

RESULTS

From 2011-2018, 2204 residents (29.4 per 100,000) died of drug overdose, 18.6% were Black (N = 410, 19.5 per 100,000) and 78.5% White (N = 1730, 35.2 per 100,000). In the year prior to death, 33.5% (N = 656) of decedents had an EMS event, 12.1% (N = 237) had an overdose event, and 9.4% (N = 185) had naloxone administered. Overdose complaint and naloxone administration were more likely to occur among White than Black patients. White decedents were more likely than Black decedents to have had naloxone administered in the year prior to death (10.1% vs. 6.8%, χ² = 4.0, p < .05, Cramer's V=.05). Toxicology data illustrate changing polydrug combinations, with Black decedents more likely to test positive for fentanyl-cocaine polydrug use in recent years.

CONCLUSIONS

Recent racial disparities in overdose deaths are driven by a combination of fentanyl and cocaine, which disproportionally impacts African American drug users, but may be addressed through expanded harm reduction and community outreach services. Additionally, there is a need to assess the role of differing practices in overdose emergency service provision as a contributing factor to disparities.

Concurrent Alcohol and Opioid Use Among Harm Reduction Clients

BACKGROUND

Harm reduction services infrequently address alcohol use among clients using opioids, despite the evaluated risk of overdose or medical consequences for clients with viral infections. The purpose of this study is to assess concurrent alcohol and opioid use among syringe services and overdose prevention program participants predominately in southern Ohio and northern Kentucky.

METHODS

This is a cross-sectional study using self-report data (n = 1,142) pooled across regional overdose prevention programs and a mobile syringe services program. The outcome variable was concurrent use categorized as no concurrent alcohol, prescription opioid or heroin use; alcohol and heroin or prescription opioid use; and alcohol, prescription opioid and heroin use in the past three months.

RESULTS

The sample was predominantly white (95%), 56% were male and the mean age was 33 years old. Forty-seven percent of the clients had no concurrent use of alcohol and opioids; 20.1% reported concurrent use of alcohol and either heroin or prescription opioids; and 33.4% reported concurrent use of alcohol, heroin and prescription opioids in the past 3 months. Lifetime suicidal ideation and non-opioid drug use were associated with concurrent alcohol and opioid use in the multivariable model.

CONCLUSION

Harm reduction clients with concurrent alcohol and opioid use may warrant enhanced overdose prevention services. Syringe services and overdose prevention program participants may benefit from education or a brief intervention on alcohol consumption.

The Impact of the Opioid Epidemic on Children and Adolescents

Although an epidemic of opioid-related overdose deaths has continued to increase in the United States for 2 decades, the impact of opioid use disorders (OUDs) on children and families receives minimal attention. The purpose of this commentary was to provide an overview of the impact of the opioid epidemic on children and adolescents, as well as to summarize challenges to improving outcomes for children. Children and adolescents who grow up in households with opioid misuse and OUDs may experience a myriad of adverse consequences, including: increased risk of mental health problems and drug use; accidental opioid poisoning; increased risk of developing a substance use disorder; and family dissolution that results from parents' incarceration, foster care placement, or loss of parent to an opioid overdose. Parental drug use may result in child neglect or deficits in parent-child attachment, and parents with an OUD may be less likely to be reunified with their children. OUD treatment is effective at reducing parental opioid use and improving child outcomes; however, stigma and cross-system collaboration may limit access to treatment and timely reunification of families. Children are the most vulnerable witnesses of the opioid epidemic, and further research is urgently needed to expand prevention interventions.

Evidence that social-economic factors play an important role in drug overdose deaths

BACKGROUND

Drug overdose deaths in the United States increased from approximately 16,000 per year in 2001 to 41,000 per year in 2014. Although every US state witnessed an increase, the increases were much larger in some states than others. There was also variation as a function of race and ethnicity. Non-Hispanic Whites accounted for more than 80% of the deaths, and in some states their rates were about ten times greater per capita than Hispanic and Non-White rates. State and temporal differences provide an opportunity to evaluate explanations of what is driving drug overdose deaths. In this report, we evaluate the degree to which state level variation in opioid prescription rates and social-economic conditions explain state level variation in overdose death rates.

METHODS AND DATA

We used publicly available data from the Center for Disease Control (CDC), Bureau of Labor Statistics (BLS), Drug Enforcement Agency (DEA) and the Opportunity Insights project.

RESULTS

Legally prescribed opioids, social capital and work force participation accounted for 53-69% of the between-state variation in overdose deaths in Non-Hispanic Whites. Prescriptions and the two social economic measures accounted for about the same amounts of unique variation, but shared variation among the three independent variables was the strongest predictor of overdose deaths. Panel regression results of the year-to-year changes in overdose deaths were similar. However, the pattern of correlations for Hispanics and Non-Whites was quite different. Neither opioid prescriptions nor social capital were significant predictors of overdose deaths in the between-state and between-year Hispanic and Non-White regression analyses.

CONCLUSIONS

Common variation in opioid prescriptions rates, social capital, and work force participation proved the strongest predictor of drug overdose deaths in Non-Hispanic Whites. We discuss reasons why the same did not hold for the Hispanic/Non-White population.

The opioid and related drug epidemics in rural Appalachia: A systematic review of populations affected, risk factors, and infectious diseases

Background/aims: To examine trends in rural Appalachian opioid and related drug epidemics during the past 10 years, including at-risk populations, substance use shifts and correlates, and associated infections. Methods: We conducted this review in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. Seven databases were searched for quantitative studies, published between January 2006 and December 2017, of drug use, drug-related mortality, or associated infections in rural Appalachia. Results: Drug-related deaths increased in study states, and a high incidence of polydrug toxicity was noted. Rural substance use was most common among young, white males, with low education levels. A history of depression/anxiety was common among study populations. Prescription opioids were most commonly used, often in conjunction with sedatives. Women emerged as a distinct user subpopulation, with different routes of drug use initiation and drug sources. Injection drug use was accompanied by risky injection behaviors and was associated with hepatitis C. Conclusions: This review can help to inform substance use intervention development and implementation in rural Appalachian populations. Those at highest risk are young, white males who often engage in polysubstance use and have a history of mental health issues. Differences in risk factors among other groups and characteristics of drug use in rural Appalachian populations that are conducive to human immunodeficiency virus (HIV) spread also warrant consideration.

Using Census Data to Understand County-Level Differences in Overall Drug Mortality and Opioid-Related Mortality by Opioid Type

Objectives. To examine associations of county-level demographic, socioeconomic, and labor market characteristics on overall drug mortality rates and specific classes of opioid mortality. Methods. We used National Vital Statistics System mortality data (2002-2004 and 2014-2016) and county-level US Census data. We examined associations between several census variables and drug deaths for 2014 to 2016. We then identified specific classes of counties characterized by different levels and rates of growth in mortality from specific opioid types between 2002 to 2004 and 2014 to 2016. We ran multivariate and multivariable regression models to predict probabilities of membership in each "opioid mortality class" on the basis of county-level census measures. Results. Drug mortality rates overall are higher in counties characterized by more economic disadvantage, more blue-collar and service employment, and higher opioid-prescribing rates. High rates of prescription opioid overdoses and overdoses involving both prescription and synthetic opioids cluster in more economically disadvantaged counties with larger concentrations of service industry workers. High heroin and "syndemic" opioid mortality counties (high rates across all major opioid types) are more urban, have larger concentrations of professional workers, and are less economically disadvantaged. Syndemic opioid counties also have greater concentrations of blue-collar workers. Conclusions. Census data are essential tools for understanding the importance of place-level characteristics on opioid mortality. Public Health Implications. National opioid policy strategies cannot be assumed universally applicable. In addition to national policies to combat the opioid and larger drug crises, emphasis should be on developing locally and regionally tailored interventions, with attention to place-based structural economic and social characteristics.

Association between altitude, prescription opioid misuse, and fatal overdoses

OBJECTIVE

Prescription opioid misuse and fatal overdoses have increased significantly over the last two decades. Living at altitude has been linked to greater reward benefits of other drugs of abuse, and living at altitude may also exacerbate the respiratory depression linked to opioid use. Therefore, we examined the relationships between living at altitude, and prescription opioid misuse and fatal overdoses.

METHOD

State-level past year rates of prescription opioid misuse were retrieved from the Substance Abuse and Mental Health Services Administration. County-level overdose data were extracted from the Centers for Disease Control and Prevention. Multiple linear regression models were fit to determine the relationship between average state elevation and state rates of opioid misuse. Logistic regression models were fit to determine the relationship between county elevation and county-level fatal opioid overdose prevalence.

RESULTS

After controlling for state opioid prescribing rates and other confounders, we identified a significant positive association between mean state altitude and state-level opioid misuse rates for women, but not men. We also found a significant positive association between county-level altitude and prevalence of fatal opioid overdose.

CONCLUSIONS

Living at altitude is thus demographically associated with increasing rates of misuse of prescription opioids, as well as of cocaine and methamphetamine. Animal studies suggest that the hypobaric hypoxia exposure involved with living at altitude may disrupt brain neurochemistry, to increase reward benefits of drugs of abuse. This increased misuse of both stimulants and opioids may increase likelihood of overdose at altitude, with overdoses by opioid use also potentially facilitated by altitude-related hypoxia.

Disparities in opioid related mortality between United States counties from 2000 to 2014

BACKGROUND

The general increase in opioid-related deaths is well documented, and disparities by geographic regions and demographic characteristics have been observed as well. However, the distribution of opioid-related deaths among U.S. counties and the trends in that distribution have not been fully explored. This study examines the inequality in opioid death rates to assess convergence or divergence in opioid-related mortality between counties.

METHODS

Using mortality data from the NVSS for 2000-2014, this study examines the Gini coefficient of the county opioid mortality distribution.

RESULTS

The distribution of opioid mortality became more equal, with the Gini coefficient falling from 0.81 in 2000 to 0.61 in 2014. Counties with lower initial opioid mortality rates experienced faster growth in mortality than counties with high initial mortality.

CONCLUSIONS

Counties have experienced a convergence in opioid mortality rates. This poses potential challenges for addressing the crisis, as measures must become much broader in scope and be implemented in areas in which the dangers of the opioid crisis are not as apparent.

Increasing Disparities in Mortality by Socioeconomic Status

This review focuses on the widening disparities in death rates by socioeconomic class. In recent years, there has been a major increase in the availability of data linking mortality risk and measures of socioeconomic status. The result has been a virtual explosion of new empirical research showing not only the existence of large inequities in the risk of death between those at the top and those at the bottom of the socioeconomic distribution, but also that the gaps have been growing. This assessment of the empirical research finds a consistent pattern of growing disparities within the United States. However, this widening gap in death rates does appear to be a uniquely American phenomenon, as the disparities by socioeconomic class appear to be stable or even declining in Europe and Canada.

Geographical Patterns in Drug-Related Mortality and Suicide: Investigating Commonalities in English Small Areas

There are increasing concerns regarding upward trends in drug-related deaths in a number of developed societies. In some countries, these have been paralleled by upward trends in suicide. Of frequent concern to public health policy are local variations in these outcomes, and the factors underlying them. In this paper, we consider the geographic pattern of drug-related deaths and suicide for 2012-2016 across 6791 small areas in England. The aim is to establish the extent of commonalities in area risk factors between the two outcomes, with a particular focus on impacts of deprivation, fragmentation and rurality.

West Virginia's model of buprenorphine expansion: Preliminary results

West Virginia (WV) is situated at the epicenter of the opioid epidemic with the highest rates of overdose deaths and some of the lowest rates of access to life saving evidence-based medication assisted treatment (MAT) for patients with opioid use disorder (OUD). WV used a modified hub-and-spoke model to build organizational capacity for facilities to use buprenorphine to treat patients with OUD and to provide ongoing case consultation. The purpose of this study is to 1) describe the group-base model of buprenorphine treatment and the model used to build organizational capacity, 2) to describe the preliminary results of buprenorphine expansion in WV and 3) to report preliminary data describing and comparing the characteristics of the patients served across five hubs. A single Coordinating Center uses video conferencing to train hubs and provide ongoing case consultation, as well as clinical support. Hubs were trained to deliver a buprenorphine treatment model that is multi-disciplinary and includes group-based medication management and psychosocial therapy. Five regional hubs independently treat patients and are leading MAT expansion in their local areas by training and mentoring spokes (n = 13). As a result of the WV STR funding, 14 health care facilities have started to use buprenorphine, 56 health professionals were trained and 196 patients with OUD have been treated. There were few sociodemographic characteristic differences across patients treated at the five hubs, while there were differences in self-reported alcohol and drug use in the 30 days prior to intake. Additional research is needed to determine whether the WV modified hub-and-spoke model resulted in statistically significant improvements in buprenorphine treatment capacity; there is a need to address MAT stigma and regulatory barriers in order to ensure the long-term sustainability of the buprenorphine expansion.

Trend of fatal poisoning at national and provincial levels in Iran from 1990 to 2015

OBJECTIVES

Comprehensive and up-to-date data on fatal injury trends are critical to identify challenges and plan priority setting. This study provides a comprehensive assessment of poisoning mortality trends across Iran.

STUDY DESIGN

The data were gathered from various resources, including death registration systems, cemetery databases of Tehran and Esfahan, the Demographic and Health Survey of 2000, and three rounds of national population and housing censuses.

METHODS

After addressing incompleteness for child and adult death data separately and using a spatio-temporal model and Gaussian process regression, the level and trend of child and adult mortality were estimated. For estimating cause-specific mortality, the cause fraction was calculated and applied to the level and trend of death.

RESULTS

From 1990 to 2015, 40,586 deaths due to poisoning were estimated across the country. The poisoning-related age-standardized death rate per 100,000 was estimated to have changed from 3.08 (95% uncertainty interval [UI]: 2.32-4.11) in 1990 to 0.96 (95% UI: 0.73-1.25) in 2015, and the male/female ratio was 1.35 during 25 years of study with an annual percentage change of -5.4% and -4.0% for women and men, respectively. The annual mortality rate was higher among children younger than 5 years and the elderly population (≥70 years) in the study period.

CONCLUSIONS

This study showed that mortality from poisoning declined in Iran over the period from 1990 to 2015 and varied by province. Understanding the reasons for the differences of poisoning mortality by province will help in developing and implementing measures to reduce this burden in Iran.

Trends in Emergency Department Use by Rural and Urban Populations in the United States

IMPORTANCE

Patterns in emergency department (ED) use by rural populations may be an important indicator of the health care needs of individuals in the rural United States and may critically affect rural hospital finances.

OBJECTIVE

To describe urban and rural differences in ED use over a 12-year period by demographic characteristics, payers, and characteristics of care, including trends in ambulatory care-sensitive conditions and ED safety-net status.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study of ED visit data from the nationally representative National Hospital Ambulatory Medical Care Survey examined ED visit rates from January 2005 to December 2016. Visits were divided by urban and rural classification and stratified by age, sex, race/ethnicity, and payer. Emergency departments were categorized as urban or rural in accordance with the US Office of Management and Budget classification. Codes from the International Classification of Diseases, Ninth Revision (ICD-9), were used to extract visits related to ambulatory care-sensitive conditions. Safety-net status was determined by the Centers for Disease Control and Prevention definition. Visit rates were calculated using annual US Census Bureau estimates. National Hospital Ambulatory Medical Care Survey estimates were generated using provided survey weights and served as the numerator, yielding an annual, population-adjusted rate. Data were analyzed from June 2017 to November 2018.

MAIN OUTCOMES AND MEASURES

Emergency department visit rates for 2005 and 2016 with 95% confidence intervals, accompanying rate differences (RDs) comparing the 2 years, and annual rate change (RC) with accompanying trend tests using weighted linear regression models.

RESULTS

During the period examined, rural ED visit estimates increased from 16.7 million to 28.4 million, and urban visits increased from 98.6 million to 117.2 million. Rural ED visits increased for non-Hispanic white patients (13.5 million to 22.5 million), Medicaid beneficiaries (4.4 million to 9.7 million), those aged 18 to 64 years (9.6 million to 16.7 million), and patients without insurance (2.7 million to 3.4 million). Rural ED visit rates increased by more than 50%, from 36.5 to 64.5 visits per 100 persons (RD, 28.9; RC, 2.2; 95% CI, 1.2 to 3.3), outpacing urban ED visit rates, which increased from 40.2 to 42.8 visits per 100 persons (RD, 2.6; RC, 0.2; 95% CI, -0.1 to 0.6). By 2016, nearly one-fifth of all ED visits occurred in the rural setting. From 2005 to 2016, rural ED utilization rates increased for non-Hispanic white patients (RD, 26.1; RC, 1.6; 95% CI, 0.4 to 2.8), Medicaid beneficiaries (RD, 56.4; RC, 4.1; 95% CI, 2.1 to 6.1), those aged 18 to 44 years (46.9 to 81.6 visits per 100 persons; RD, 34.7; RC, 2.3; 95% CI, 1.1 to 3.5) as well as those aged 45 to 64 years (27.5 to 53.9 visits per 100 persons; RD, 26.5; RC, 1.6; 95% CI, 0.7 to 2.5), and patients without insurance (44.0 to 66.6 visits per 100 persons per year; RD, 22.6; RC, 2.7; 95% CI, 0.2 to 5.2), with a larger proportion of rural EDs categorized as safety-net status.

CONCLUSIONS AND RELEVANCE

Rural EDs are experiencing important changes in utilization rates, increasingly serving a larger proportion of traditionally disadvantaged groups and with greater pressure as safety-net hospitals.

Increased overdose mortality during the first week of the month: Revisiting the "check effect" through a spatial lens

BACKGROUND

The timing of social service benefit issuance is thought to be associated with increased drug overdose fatalities. However, the extent to which this excess mortality is concentrated in communities with higher levels of benefit receipt has not been studied. We sought to examine if benefit receipt at the neighborhood level was associated with spatiotemporal patterns of overdose fatalities.

METHODS

We conducted a retrospective review of all accidental overdose deaths recorded in Rhode Island from 2014 to 2016 (n = 838). Overdose incident locations were geocoded to the census block group level. Clusters of census block groups with excess overdose mortality at the beginning of a month were identified using spatial scan methods. Logistic regression models were fit to identify characteristics associated with the inclusion of a census block group within a cluster.

RESULTS

Increased rates of overdose fatalities at the beginning of a month were observed relative to the end of a preceding month (Ratio: 1.17; 95% CI: 1.04, 1.38). The proportions of residents receiving cash public assistance or Supplemental Security Income were not associated with excess mortality at the beginning of a month; however, the proportion of residents living in unaffordable housing was (OR: 1.42; 95% CI: 1.05, 1.91).

CONCLUSION

Despite previous research on benefit check issuance and overdose, welfare receipt was not associated with excess overdose mortality at the beginning of a month at the neighborhood level. Future research on housing cost burden and its influence on overdose death risk at the individual level is needed.

The association between county-level safety net treatment access and opioid hospitalizations and mortality in New York

BACKGROUND

Increases in pharmaceutical opioid sales have paralleled the quadrupling of prescription opioid overdose deaths and spikes in emergency department visits for non-medical opioid prescription overdoses. In response, federal and state governments have advanced a myriad of policies to reduce opioid availability and increase treatment access, aimed to ultimately reduce opioid-related mortality. Despite these efforts, including ACA Medicaid expansion and more robust prescription drug monitoring programs, opioid-related mortality has continued to rise in NY and 29 other states. This study examined whether geographic access to Federally Qualified Health Centers, opioid treatment programs, and buprenorphine providers mitigated opioid-related hospital visits (emergency department, inpatient, and all visits) and mortality, by county, between 2012 and 2014.

METHODS

The authors examined the relationships among opioid-related health outcomes and geographic access to treatment options using spatial error regression models at the county (n = 62) level in 2012 and 2014. Z-tests further assessed significant differences in access coefficients between 2012 and 2014.

RESULTS

Of the 62 counties in New York State in 2014, 54 (87.1%) showed increased opioid overdose-related emergency department rates (t = 9.125, p < 0.001), and 37 (59.7%) showed mortality rate increases (t = 1.687, p < 0.1), compared to 2012. Regression models demonstrated significant negative relationships between county-level opioid-related mortality rates and geographic access to opioid treatment programs, Federally Qualified Health Centers in both 2012 and 2014 and buprenorphine providers concentration in 2014 while adjusting for county socio-demographics (all p values < 0.05). Access coefficients were not significantly different between 2012 and 2014 (p > 0.05).

CONCLUSIONS

Greater geographic access to treatment services was protective against opioid-related mortality. Access to opioid treatment may not be sufficient to mitigate opioid-related hospital visits or mortality, but may offset climbing mortality rates in select counties.

Injection drug use, HIV/HCV, and related services in nonurban areas of the United States: A systematic review

BACKGROUND

Injection drug use (IDU) in nonurban areas of the United States is a growing public health concern, but there has been no comprehensive assessment of existing research on injection-related HIV and hepatitis C (HCV) in nonurban communities. We conducted a systematic review to assess the current literature and identify knowledge gaps.

METHODS

We systematically searched six databases for relevant articles published between January 1990 and June 2016 and screened, extracted, and analyzed the resulting data. Studies were included if they reported original findings from the nonurban U.S. related to 1) IDU and its role in HIV/HCV transmission, and/or 2) HIV/HCV services for people who inject drugs (PWID).

RESULTS

Of 2330 studies, 34 from 24 unique research projects in 17 states met inclusion criteria. Despite increasing HCV and high vulnerability to injection-related HIV outbreaks in nonurban areas, only three studies since 2010 recruited and tested PWID for HIV/HCV. Twelve reported on sharing injection equipment but used varying definitions of sharing, and only eight examined correlates of injection risk. Nine studies on syringe access suggest limited access through syringe exchange programs and pharmacies. Only two studies addressed HCV testing, none addressed HIV testing, and three examined behavioral or other interventions.

CONCLUSIONS

Despite growing concern regarding nonurban IDU there are few studies of HIV/HCV and related services for PWID, and the existing literature covers a very limited geographical area. Current research provides minimal insights into any unique factors that influence injection risk and HIV/HCV service provision and utilization among nonurban PWID.

The Impact of Prescription Drug Monitoring Programs on U.S. Opioid Prescriptions

This paper seeks to understand the treatment effect of Prescription Drug Monitoring Programs (PDMPs) on opioid prescription rates. Using county-level panel data on all opioid prescriptions in the U.S. between 2006 and 2015, we investigate whether state interventions like PDMPs have heterogeneous treatment effects at the sub-state level, based on regional and temporal variations in policy design, extent of urbanization, race, and income. Our models comprehensively control for a set of county and time fixed effects, countyspecific and time-varying demographic controls, potentially endogenous time-series trends in prescription rates, and other state-level opioid interventions such as Naloxone Access and Good Samaritan laws, Medicaid expansion, and the provision of Methadone Assistance Treatment. We find that PDMPs are only effective in reducing prescription rates if they obligate doctors to check for patients' history prior to filling out a prescription, but the frequency at which a state requires its PDMP to be updated is irrelevant to its effectiveness. Moreover, the significant treatment effects of PDMPs are almost exclusively driven by urban and predominantly white counties, with the relatively more affluent regions showing greater responsiveness than their less affluent counterparts.

Ambient PM2.5 air pollution exposure and hepatocellular carcinoma incidence in the United States

PURPOSE

To conduct the first epidemiologic study prospectively examining the association between particulate matter air pollution < 2.5 µm in diameter (PM2.5) exposure and hepatocellular carcinoma (HCC) risk in the U.S.

METHODS

Surveillance, Epidemiology, and End Results (SEER) provided information on HCC cases diagnosed between 2000 and 2014 from 16 population-based cancer registries across the U.S. Ambient PM2.5 exposure was estimated by linking the SEER county with a spatial PM2.5 model using a geographic information system. Poisson regression with robust variance estimation was used to calculate incidence rate ratios and 95% confidence intervals (CIs) for the association between ambient PM2.5 exposure per 10 µg/m3 increase and HCC risk adjusting for individual-level age at diagnosis, sex, race, year of diagnosis, SEER registry, and county-level information on health conditions, lifestyle, demographic, socioeconomic, and environmental factors.

RESULTS

Higher levels of ambient PM2.5 exposure were associated with a statistically significant increased risk for HCC (n = 56,245 cases; adjusted IRR per 10 µg/m3 increase = 1.26, 95% CI 1.08, 1.47; p < 0.01).

CONCLUSIONS

If confirmed in studies with individual-level PM2.5 exposure and risk factor information, these results suggest that ambient PM2.5 exposure may be a risk factor for HCC in the U.S.

Factors Associated With County-Level Differences in U.S. Drug-Related Mortality Rates

INTRODUCTION

Over the past 2 decades, drug-related deaths have grown to be a major U.S. public health problem. County-level differences in drug-related mortality rates are large. The relative contributions of social determinants of health to this variation, including the economic, social, and healthcare environments, are unknown.

METHODS

Using data from the U.S. Centers for Disease Control and Prevention Multiple-Cause of Death Files (2006-2015, analyzed in 2017); U.S. Census Bureau; U.S. Department of Agriculture Economic Research Service; Agency for Healthcare Research and Quality; and Northeast Regional Center for Rural Development, this paper modeled associations between county-level drug-related mortality rates and economic, social, and healthcare environments. Spatial autoregressive models controlled for state fixed effects and county demographic characteristics.

RESULTS

The average county-level age-adjusted drug-related mortality rate was 16.6 deaths per 100,000 population (2006-2015), but there were substantial geographic disparities in rates. Controlling for county demographic characteristics, average mortality rates were significantly higher in counties with greater economic and family distress and in counties economically dependent on mining. Average mortality rates were significantly lower in counties with a larger presence of religious establishments, a greater percentage of recent in-migrants, and counties with economies reliant on public (government) sector employment. Healthcare supply factors did not contribute to between-county disparities in mortality rates.

CONCLUSIONS

Drug-related mortality rates are not randomly distributed across the U.S. Future research should consider the specific pathways through which economic, social, and healthcare environments are associated with drug-related mortality.

Trends and Patterns of Geographic Variation in Mortality From Substance Use Disorders and Intentional Injuries Among US Counties, 1980-2014

IMPORTANCE

Substance use disorders, including alcohol use disorders and drug use disorders, and intentional injuries, including self-harm and interpersonal violence, are important causes of early death and disability in the United States.

OBJECTIVE

To estimate age-standardized mortality rates by county from alcohol use disorders, drug use disorders, self-harm, and interpersonal violence in the United States.

DESIGN AND SETTING

Validated small-area estimation models were applied to deidentified death records from the National Center for Health Statistics (NCHS) and population counts from the US Census Bureau, NCHS, and the Human Mortality Database to estimate county-level mortality rates from 1980 to 2014 for alcohol use disorders, drug use disorders, self-harm, and interpersonal violence.

EXPOSURES

County of residence.

MAIN OUTCOMES AND MEASURES

Age-standardized mortality rates by US county (N = 3110), year, sex, and cause.

RESULTS

Between 1980 and 2014, there were 2 848 768 deaths due to substance use disorders and intentional injuries recorded in the United States. Mortality rates from alcohol use disorders (n = 256 432), drug use disorders (n = 542 501), self-harm (n = 1 289 086), and interpersonal violence (n = 760 749) varied widely among counties. Mortality rates decreased for alcohol use disorders, self-harm, and interpersonal violence at the national level between 1980 and 2014; however, over the same period, the percentage of counties in which mortality rates increased for these causes was 65.4% for alcohol use disorders, 74.6% for self-harm, and 6.6% for interpersonal violence. Mortality rates from drug use disorders increased nationally and in every county between 1980 and 2014, but the relative increase varied from 8.2% to 8369.7%. Relative and absolute geographic inequalities in mortality, as measured by comparing the 90th and 10th percentile among counties, decreased for alcohol use disorders and interpersonal violence but increased substantially for drug use disorders and self-harm between 1980 and 2014.

CONCLUSIONS AND RELEVANCE

Mortality due to alcohol use disorders, drug use disorders, self-harm, and interpersonal violence varied widely among US counties, both in terms of levels of mortality and trends. These estimates may be useful to inform efforts to target prevention, diagnosis, and treatment to improve health and reduce inequalities.

Risk markers for fatal and non-fatal prescription drug overdose: a meta-analysis

BACKGROUND

Drug overdose is a public health crisis in the United States, due in part to the unintended consequences of increases in prescribing of opioid analgesics. Many clinicians evaluate risk markers for opioid-related harms when prescribing opioids for chronic pain; however, more data on predictive risk markers are needed. Risk markers are attributes (modifiable and non-modifiable) that are associated with increased probability of an outcome. This review aims to identify risk markers associated with fatal and non-fatal prescription drug overdose by synthesizing findings in the existing peer-reviewed and grey literature. Eligible cohort, case-control, cross-sectional, and case-cohort studies were reviewed and data were extracted for qualitative and quantitative synthesis.

FINDINGS

Summary odds ratios (SOR) were estimated from 29 studies for six risk markers: sex, age, race, psychiatric disorders, substance use disorder (SUD), and urban/rural residence. Heterogeneity was assessed and effect estimates were stratified by study characteristics. Of the six risk markers identified, SUD had the strongest association with drug overdose death (SOR = 5.24, 95% confidence interval (CI) = 3.53 - 7.76), followed by psychiatric disorders (SOR = 3.94, 95% CI = 3.09 - 5.01), white race (SOR = 2.28, 95% CI = 1.93 - 2.70), the 35-44 year age group relative to the 25-34 year reference group (SOR = 1.52, 95% CI = 1.31 - 1.76), and male sex (SOR = 1.33, 95% CI = 1.17 - 1.51).

CONCLUSIONS

This review highlights fatal and non-fatal prescription drug risk markers most frequently assessed in peer-reviewed and grey literature. There is a need to better understand modifiable risk markers and underlying reasons for drug misuse in order to inform interventions that may prevent future drug overdoses.

Geographic Variation in Opioid and Heroin Involved Drug Poisoning Mortality Rates

INTRODUCTION

An important barrier to formulating effective policies to address the rapid rise in U.S. fatal overdoses is that the specific drugs involved are frequently not identified on death certificates. This analysis supplies improved estimates of state opioid and heroin involved drug fatality rates in 2014, and changes from 2008 to 2014.

METHODS

Reported mortality rates were calculated directly from death certificates and compared to corrected rates that imputed drug involvement when no drug was specified. The analysis took place during 2016-2017.

RESULTS

Nationally, corrected opioid and heroin involved mortality rates were 24% and 22% greater than reported rates. The differences varied across states, with particularly large effects in Pennsylvania, Indiana, and Louisiana. Growth in corrected opioid mortality rates, from 2008 to 2014, were virtually the same as reported increases (2.5 deaths per 100,000 people) whereas changes in corrected heroin death rates exceeded reported increases (2.7 vs 2.3 per 100,000). Without corrections, opioid mortality rate changes were considerably understated in Pennsylvania, Indiana, New Jersey, and Arizona, but dramatically overestimated in South Carolina, New Mexico, Ohio, Connecticut, Florida, and Kentucky. Increases in heroin death rates were understated in most states, and by large amounts in Pennsylvania, Indiana, New Jersey, Louisiana, and Alabama.

CONCLUSIONS

The correction procedures developed here supply a more accurate understanding of geographic differences in drug poisonings and supply important information to policymakers attempting to reduce or slow the increase in fatal drug overdoses.

Ambient ultraviolet radiation exposure and hepatocellular carcinoma incidence in the United States

BACKGROUND

Hepatocellular carcinoma (HCC), the most commonly occurring type of primary liver cancer, has been increasing in incidence worldwide. Vitamin D, acquired from sunlight exposure, diet, and dietary supplements, has been hypothesized to impact hepatocarcinogenesis. However, previous epidemiologic studies examining the associations between dietary and serum vitamin D reported mixed results. The purpose of this study was to examine the association between ambient ultraviolet (UV) radiation exposure and HCC risk in the U.S.

METHODS

The Surveillance, Epidemiology, and End Results (SEER) database provided information on HCC cases diagnosed between 2000 and 2014 from 16 population-based cancer registries across the U.S. Ambient UV exposure was estimated by linking the SEER county with a spatiotemporal UV exposure model using a geographic information system. Poisson regression with robust variance estimation was used to calculate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for the association between ambient UV exposure per interquartile range (IQR) increase (32.4 mW/m2) and HCC risk adjusting for age at diagnosis, sex, race, year of diagnosis, SEER registry, and county-level information on prevalence of health conditions, lifestyle, socioeconomic, and environmental factors.

RESULTS

Higher levels of ambient UV exposure were associated with statistically significant lower HCC risk (n = 56,245 cases; adjusted IRR per IQR increase: 0.83, 95% CI 0.77, 0.90; p < 0.01). A statistically significant inverse association between ambient UV and HCC risk was observed among males (p for interaction = 0.01) and whites (p for interaction = 0.01).

CONCLUSIONS

Higher ambient UV exposure was associated with a decreased risk of HCC in the U.S. UV exposure may be a potential modifiable risk factor for HCC that should be explored in future research.

Geospatial Analysis of Drug Poisoning Deaths Involving Heroin in the USA, 2000-2014

We investigate the geographic patterns of drug poisoning deaths involving heroin by county for the USA from 2000 to 2014. The county-level patterns of mortality are examined with respect to age-adjusted rates of death for different classes of urbanization and racial and ethnic groups, while rates based on raw counts of drug poisoning deaths involving heroin are estimated for different age groups and by gender. To account for possible underestimations in these rates due to small areas or small numbers, spatial empirical Baye's estimation techniques have been used to smooth the rates of death and alleviate underestimation when analyzing spatial patterns for these different groups. The geographic pattern of poisoning deaths involving heroin has shifted from the west coast of the USA in the year 2000 to New England, the Mid-Atlantic region, and the Great Lakes and central Ohio Valley by 2014. The evolution over space and time of clusters of drug poisoning deaths involving heroin is confirmed through the SaTScan analysis. For this period, White males were found to be the most impacted population group overall; however, Blacks and Hispanics are highly impacted in counties where significant populations of these two groups reside. Our results show that while 35-54-year-olds were the most highly impacted age group by county from 2000 to 2010, by 2014, the trend had changed with an increasing number of counties experiencing higher death rates for individuals 25-34 years. The percentage of counties across the USA classified as large metro with deaths involving heroin is estimated to have decreased from approximately 73% in 2010 to just fewer than 56% in 2014, with a shift to small metro and non-metro counties. Understanding the geographic variations in impact on different population groups in the USA has become particularly necessary in light of the extreme increase in the use and misuse of street drugs including heroin and the subsequent rise in opioid-related deaths in the USA.