A joint spatial model of opioid-associated deaths and treatment admissions in Ohio

A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research

With the advancement of spatial analysis approaches, methodological research addressing the technical and statistical issues related to joint spatial and spatiotemporal models has increased. Despite the benefits of spatial modelling of several interrelated outcomes simultaneously, there has been no published systematic review on this topic, specifically when such models would be useful. This systematic review therefore aimed at reviewing health research published using joint spatial and spatiotemporal models. A systematic search of published studies that applied joint spatial and spatiotemporal models was performed using six electronic databases without geographic restriction. A search with the developed search terms yielded 4077 studies, from which 43 studies were included for the systematic review, including 15 studies focused on infectious diseases and 11 on cancer. Most of the studies (81.40%) were performed based on the Bayesian framework. Different joint spatial and spatiotemporal models were applied based on the nature of the data, population size, the incidence of outcomes, and assumptions. This review found that when the outcome is rare or the population is small, joint spatial and spatiotemporal models provide better performance by borrowing strength from related health outcomes which have a higher prevalence. A framework for the design, analysis, and reporting of such studies is also needed.

County-level predictors of US drug overdose mortality: A systematic review

BACKGROUND

This systematic review summarized published literature on county-level predictors of drug overdose mortality in the United States (US).

METHODS

Peer-reviewed studies and doctoral dissertations published in English between 1990 and July 19, 2022 were identified from PubMed, Web of Science, ProQuest Dissertations & Theses, PsycINFO, CINAHL, and EconLit. Eligible studies examined at least one county-level predictor of drug overdose mortality in US counties. Two reviewers independently completed screening, quality assessment (with an adapted National Institutes of Health Quality Assessment Tool), and data extraction. Results were qualitatively summarized and grouped by predictor categories.

RESULTS

Of 56 studies included, 42.9% were subnational, and 53.6% were limited to opioid overdose. In multiple studies, measures related to opioid prescribing, illness/disability, economic distress, mining employment, incarceration, family distress, and single-parent families were positively associated with drug overdose mortality outcomes, while measures related to cannabis dispensaries, substance use treatment, social capital, and family households were negatively associated with drug overdose mortality outcomes. Both positive and negative associations were documented for smoking, uninsurance, healthcare professional shortage status, physicians per capita, unemployment, income, poverty, educational attainment, racial composition, and rurality. Findings within studies also differed by subpopulation (by race/ethnicity, gender, age, or rurality) and the type of drugs involved in overdose.

CONCLUSIONS

The findings of this review provide relatively mixed evidence regarding many county-level predictors of overdose mortality, several of which also vary between subpopulations, supporting the importance of additional research to elucidate pathways through which the county context may shape risk of fatal overdose.

Endogenous opiates and behavior: 2019

This paper is the forty-second consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2019 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Methodological Challenges and Proposed Solutions for Evaluating Opioid Policy Effectiveness

Opioid-related mortality increased by nearly 400% between 2000 and 2018. In response, federal, state, and local governments have enacted a heterogeneous collection of opioid-related policies in an effort to reverse the opioid crisis, producing a policy landscape that is both complex and dynamic. Correspondingly, there has been a rise in opioid-policy related evaluation studies, as policymakers and other stakeholders seek to understand which policies are most effective. In this paper, we provide an overview of methodological challenges facing opioid policy researchers when evaluating the effects of opioid policies using observational data, as well as some potential solutions to those challenges. In particular, we discuss the following key challenges: (1) Obtaining high-quality opioid policy data; (2) Appropriately operationalizing and specifying opioid policies; (3) Obtaining high-quality opioid outcome data; (4) Addressing confounding due to systematic differences between policy and non-policy states; (5) Identifying heterogeneous policy effects across states, population subgroups, and time; (6) Disentangling effects of concurrent policies; and (7) Overcoming limited statistical power to detect policy effects afforded by commonly-used methods. We discuss each of these challenges and propose some ways forward to address them. Increasing the methodological rigor of opioid evaluation studies is imperative to identifying and implementing opioid policies that are most effective at reducing opioid-related harms.