Faculty Bibliography

BACKGROUND:Public health experts have urged governments around the world to regulate newly legalized cannabis as they do alcohol to effectively and efficiently protect health. However, research evaluating the alignment of alcohol and cannabis policies is sparse. We assessed similarities and differences in local alcohol and cannabis control policies across California, and characterized localities adopting distinct policy approaches. METHODS:Using standard legal epidemiologic techniques, we collected and coded local alcohol and cannabis control policies relevant to public health for 12 California counties and all incorporated cities within them (N=241). We assessed whether localities were equally stringent on alcohol and cannabis policies by comparing overall restrictiveness (summed policy scores) and 9 specific provisions that applied to both substances. We captured distinct local alcohol-cannabis policy approaches using latent class analysis, and examined this classification in relation to local demographic, socioeconomic, political, and retail market characteristics. RESULTS:All 241 localities permitted alcohol sales, while 71% banned cannabis sales. Among those that did not ban cannabis sales, more stringent alcohol policy scores were associated with more stringent cannabis policy scores (linear regression coefficient: 0.16 [95% CI: 0.07, 0.25]). Local governments rarely adopted the same provisions for alcohol and cannabis (e.g., limits on hours of sale, advertising restrictions), and only two regulated the co-location of cannabis and alcohol outlets. Localities that were restrictive on alcohol yet permissive on cannabis (12%) were more urban, politically progressive, and had more low-income and racial/ethnic minority residents. Localities that were more permissive on alcohol and restrictive on cannabis (51%) were more socioeconomically advantaged. CONCLUSION/CONCLUSIONS:We found few similarities between local alcohol and cannabis control policies. California's experience suggests that, as governments around the world legalize cannabis, lessons learned from regulating alcohol are not routinely applied to cannabis, particularly in communities distinguished by high social and economic advantages.

Substantial heterogeneity in effects of social policies on health across subgroups may be common, but has not been systematically characterized. Using a sample of 55 contemporary studies on health effects of social policies, we recorded how often heterogeneous treatment effects (HTEs) were assessed, for what subgroups (e.g., male, female), and the subgroup-specific effect estimates expressed as Standardized Mean Differences (SMDs). For each study, outcome, and dimension (e.g., gender), we fit a random-effects meta-analysis. We characterized the magnitude of heterogeneity in policy effects using the standard deviation of the subgroup-specific effect estimates (Ï„). Among the 44% of studies reporting subgroup-specific estimates, policy effects were generally small (<0.1 SMDs) with mixed impacts on health (67% beneficial) and disparities (50% implied narrowing of disparities). Across study-outcome-dimensions, 54% indicated any heterogeneity in effects, and 20% had Ï„ > 0.1 SMDs. For 26% of study-outcome-dimensions, the magnitude of Ï„ indicated that effects of opposite signs were plausible across subgroups. Heterogeneity was more common in policy effects not specified a priori. Our findings suggest social policies commonly have heterogeneous effects on health of different populations; these HTEs may substantially impact disparities. Studies of social policies and health should routinely evaluate HTEs.

OBJECTIVE:The growing availability of cannabis products through home delivery services may affect cannabis-related health outcomes. However, research is impeded by a lack of data measuring the scale of home delivery. Prior research demonstrated that crowdsourced websites can be used to validly enumerate brick-and-mortar cannabis outlets. We piloted an extension of this method to explore the feasibility of measuring availability of cannabis home delivery. METHOD:We tested implementation of an automated algorithm designed to webscrape data from Weedmaps, the largest crowdsourced website for cannabis retail, to count the number of legal cannabis retailers offering home delivery to the geographic centroid of each Census block group in California. We compared these estimates to the number of brick-and-mortar outlets within each block group. To assess data quality, we conducted follow-up telephone interviews with a subsample of cannabis delivery retailers. RESULTS:We successfully implemented the webscraping. Of the 23,212 block groups assessed, 22,542 (97%) were served by at least one cannabis delivery business. Only 461 block groups (2%) contained one or more brick-and-mortar outlets. In interviews, availability varied dynamically as a function of staffing levels, order sizes, time of day, competition, and demand. CONCLUSIONS:Webscraping crowdsourced websites could be a viable method for quantifying rapidly evolving availability of cannabis home delivery. However, key practical and conceptual challenges must be overcome to conduct a full-scale validation and develop methodological standards. Acknowledging data limitations, cannabis home delivery appears to be nearly universal in California, whereas availability of brick-and-mortar outlets is limited, underscoring the need for research on home delivery.

IMPORTANCE/UNASSIGNED:Psychosis is a hypothesized consequence of cannabis use. Legalization of cannabis could therefore be associated with an increase in rates of health care utilization for psychosis. OBJECTIVE/UNASSIGNED:To evaluate the association of state medical and recreational cannabis laws and commercialization with rates of psychosis-related health care utilization. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:Retrospective cohort design using state-level panel fixed effects to model within-state changes in monthly rates of psychosis-related health care claims as a function of state cannabis policy level, adjusting for time-varying state-level characteristics and state, year, and month fixed effects. Commercial and Medicare Advantage claims data for beneficiaries aged 16 years and older in all 50 US states and the District of Columbia, 2003 to 2017 were used. Data were analyzed from April 2021 to October 2022. EXPOSURE/UNASSIGNED:State cannabis legalization policies were measured for each state and month based on law type (medical or recreational) and degree of commercialization (presence or absence of retail outlets). MAIN OUTCOMES AND MEASURES/UNASSIGNED:Outcomes were rates of psychosis-related diagnoses and prescribed antipsychotics. RESULTS/UNASSIGNED:This study included 63 680 589 beneficiaries followed for 2 015 189 706 person-months. Women accounted for 51.8% of follow-up time with the majority of person-months recorded for those aged 65 years and older (77.3%) and among White beneficiaries (64.6%). Results from fully-adjusted models showed that, compared with no legalization policy, states with legalization policies experienced no statistically significant increase in rates of psychosis-related diagnoses (medical, no retail outlets: rate ratio [RR], 1.13; 95% CI, 0.97-1.36; medical, retail outlets: RR, 1.24; 95% CI, 0.96-1.61; recreational, no retail outlets: RR, 1.38; 95% CI, 0.93-2.04; recreational, retail outlets: RR, 1.39; 95% CI, 0.98-1.97) or prescribed antipsychotics (medical, no retail outlets RR, 1.00; 95% CI, 0.88-1.13; medical, retail outlets: RR, 1.01; 95% CI, 0.87-1.19; recreational, no retail outlets: RR, 1.13; 95% CI, 0.84-1.51; recreational, retail outlets: RR, 1.14; 95% CI, 0.89-1.45). In exploratory secondary analyses, rates of psychosis-related diagnoses increased significantly among men, people aged 55 to 64 years, and Asian beneficiaries in states with recreational policies compared with no policy. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this retrospective cohort study of commercial and Medicare Advantage claims data, state medical and recreational cannabis policies were not associated with a statistically significant increase in rates of psychosis-related health outcomes. As states continue to introduce new cannabis policies, continued evaluation of psychosis as a potential consequence of state cannabis legalization may be informative.

INTRODUCTION/BACKGROUND:Understanding educational patterns in excess mortality during the coronavirus disease 2019 (COVID-19) pandemic may help to identify strategies to reduce disparities. It is unclear whether educational inequalities in COVID-19 mortality have persisted throughout the pandemic, spanned the full range of educational attainment, or varied by other demographic indicators of COVID-19 risks, such as age or occupation. METHODS:This study analyzed individual-level California Department of Public Health data on deaths occurring between January 2016 and February 2021 among individuals aged ≥25 years (1,502,202 deaths). Authors applied ARIMA (autoregressive integrated moving average) models to subgroups defined by the highest level of education and other demographics (age, sex, race/ethnicity, U.S. nativity, occupational sector, and urbanicity). Authors estimated excess deaths (the number of observed deaths minus the number of deaths expected to occur under the counterfactual of no pandemic) and excess deaths per 100,000 individuals. RESULTS:Educational inequalities in excess mortality emerged early in the pandemic and persisted throughout the first year. The greatest per-capita excess occurred among people without high-school diplomas (533 excess deaths/100,000), followed by those with a high-school diploma but no college (466/100,000), some college (156/100,000), and bachelor's degrees (120/100,000), and smallest among people with graduate/professional degrees (101/100,000). Educational inequalities occurred within every subgroup examined. For example, per-capita excess mortality among Latinos with no college experience was 3.7 times higher than among Latinos with at least some college experience. CONCLUSIONS:Pervasive educational inequalities in excess mortality during the pandemic suggest multiple potential intervention points to reduce disparities.

BACKGROUND:Cannabis outlets may affect health and health disparities. Local governments can regulate outlets, but little is known about the effectiveness of local policies in limiting outlet densities and discouraging disproportionate placement of outlets in vulnerable neighborhoods. METHODS:For 241 localities in California, we measured seven policies pertaining to density or location of recreational cannabis outlets. We geocoded outlets using web-scraped data from the online finder Weedmaps between 2018 and 2020. We applied Bayesian spatiotemporal models to evaluate associations of local cannabis policies with Census block group-level outlet counts, accounting for confounders and spatial autocorrelation. We assessed whether associations differed by block group median income or racial-ethnic composition. RESULTS:Seventy-six percent of localities banned recreational cannabis outlets. Bans were associated with fewer outlets, particularly in block groups with higher median income, fewer Hispanic residents, and more White and Asian residents. Outlets were disproportionately located in block groups with lower median income [posterior RR (95% credible interval): 0.76 (0.70, 0.82) per $10,000], more Hispanic residents [1.05 (1.02, 1.09) per 5%], and fewer Black residents [0.91 (0.83, 0.98) per 5%]. For the six policies in jurisdictions permitting outlets, two policies were associated with fewer outlets and two with more; two policy associations were uninformative. For these policies, we observed no consistent heterogeneity in associations by median income or racial-ethnic composition. CONCLUSIONS:Some local cannabis policies in California are associated with lower cannabis outlet densities, but are unlikely to deter disproportionate placement of outlets in racial-ethnic minority and low-income neighborhoods.

Violations of the positivity assumption (also called the common support condition) challenge health policy research and can result in significant bias, large variance, and invalid inference. We define positivity in the single- and multiple-timepoint (i.e., longitudinal) health policy evaluation setting, and discuss real-world threats to positivity. We show empirical evidence of the practical positivity violations that can result when attempting to estimate the effects of health policies (in this case, Naloxone Access Laws). In such scenarios, an alternative is to estimate the effect of a shift in law enactment (e.g., the effect if enactment had been delayed by some number of years). Such an effect corresponds to what is called a modified treatment policy, and dramatically weakens the required positivity assumption, thereby offering a means to estimate policy effects even in scenarios with serious positivity problems. We apply the approach to define and estimate the longitudinal effects of Naloxone Access Laws on opioid overdose rates.

Background/UNASSIGNED:The coronavirus disease 2019 (COVID-19) pandemic is co-occurring with a drug addiction and overdose crisis. Methods/UNASSIGNED:We fit overdispersed Poisson models, accounting for seasonality and secular trends, to estimate the excess fatal drug overdoses (i.e., deaths greater than expected), using data on all deaths in California from 2016 to 2020. Findings/UNASSIGNED:Between January 5, 2020 and December 26, 2020, there were 8605 fatal drug overdoses-a 44% increase over the same period one year prior. We estimated 2084 (95% CI: 1925 to 2243) fatal drug overdoses were excess deaths, representing 5·28 (4·88 to 5·68) excess fatal drug overdoses per 100,000 population. Excess fatal drug overdoses were driven by opioids (4·48 [95% CI: 4·18 to 4·77] per 100,000), especially synthetic opioids (2·85 [95% CI: 2·56 to 3·13] per 100,000). The non-Hispanic Black and Other non-Hispanic populations were disproportionately affected with 10·1 (95% CI: 7·6 to 12·5) and 13·26 (95% CI: 11·0 to 15·5) excess fatal drug overdoses per 100,000 population, respectively, compared to 5·99 (95% CI: 5.2 to 6.8) per 100,000 population in the non-Hispanic white population. There was a steep, nonlinear educational gradient with the highest rate among those with only a high school degree. There was a strong spatial patterning with the highest levels of excess mortality in the southernmost region and consistently lower levels at progressively more northern latitudes (7·73 vs 1·96 per 100,000). Interpretation/UNASSIGNED:Fatal drug overdoses disproportionately increased in 2020 among structurally marginalized populations and showed a strong geographic gradient. Local, tailored public health interventions are urgently needed to reduce growing inequities in overdose deaths. Funding/UNASSIGNED:US National Institutes of Health and Department of Veterans Affairs.