Prescription Drug Monitoring Programs and Opioid Overdoses: Exploring Sources of Heterogeneity.

BACKGROUND: Prescription drug monitoring program are designed to reduce harms from prescription opioids; however, little is known about what populations benefit the most from these programs. We investigated how the relation between implementation of online prescription drug monitoring programs and rates of hospitalizations related to prescription opioids and heroin overdose changed over time, and varied across county levels of poverty and unemployment, and levels of medical access to opioids. METHODS: Ecologic county-level, spatiotemporal study, including 990 counties within 16 states, in 2001-2014. We modeled overdose counts using Bayesian hierarchical Poisson models. We defined medical access to opioids as the county-level rate of hospital discharges for noncancer pain conditions. RESULTS: In 2010-2014, online prescription drug monitoring programs were associated with lower rates of prescription opioid-related hospitalizations (rate ratio 2014 = 0.74; 95% credible interval = 0.69, 0.80). The association between online prescription drug monitoring programs and heroin-related hospitalization was also negative but tended to increase in later years. Counties with lower rates of noncancer pain conditions experienced a lower decrease in prescription opioid overdose and a faster increase in heroin overdoses. No differences were observed across different county levels of poverty and unemployment. CONCLUSIONS: Areas with lower levels of noncancer pain conditions experienced the smallest decrease in prescription opioid overdose and the faster increase in heroin overdose following implementation of online prescription drug monitoring programs. Our results are consistent with the hypothesis that prescription drug monitoring programs are most effective in areas where people are likely to access opioids through medical providers.

Urban-rural variation in the socioeconomic determinants of opioid overdose.

BACKGROUND: Prescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown. METHODS: In this serial cross-sectional study of zip codes in 17 states, 2002-2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes. RESULTS: Percent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06-1.07]; 5% low education: 1.02 [1.02-1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87-0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11-1.13]; 5% unemployment: 1.04 [1.02-1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87-0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02-1.16]). CONCLUSIONS: Regardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.

Longitudinal impacts of two causal drivers of alcohol demand on outlet concentrations within community settings: Population size and income effects.

We analyzed counts of licensed bars, restaurants and off-premise alcohol outlets within 53 California cities from 2000-2013. Poisson models were used to assess overall space-time associations between outlet numbers and population size and median household income in local and spatially adjacent block groups. We then separated covariate effects into distinct spatial and temporal components ("decomposed" models). Overall models showed that densities of all outlet types were generally greatest within block groups that had lower income, were adjacent to block groups with lower income, had greater populations, and were adjacent to block groups that had greater populations. Decomposed models demonstrate that over time greater income was associated with increased counts of bars, and greater population was associated with greater numbers of restaurants and off-premise outlets. Acknowledging the many negative consequences for populations living in areas of high outlet density, these effects are a predictable and powerful social determinant of health.

Violent crime redistribution in a city following a substantial increase in the number of off-sale alcohol outlets: A Bayesian analysis.

INTRODUCTION AND AIMS: This study examined whether the introduction of a large number of off-premise alcohol outlets into a city over a brief period of time could affect rates of violent crime. DESIGN AND METHODS: The study analysed annual counts of violent crime across 172 US Census block groups in Lubbock, Texas from 2006 through 2011. Spatial Poisson models related annual violent crime counts within each block group to off-premise and on-premise alcohol outlets active during this time period as well as neighbourhood socio-demographic characteristics. The effects of alcohol outlets were assessed both within block groups and across adjacent block groups. RESULTS: On-premise outlets had a small, significant positive association with violence within a given block group. A similar well-supported local effect for off-premise outlets was not found. However, the spatially lagged effect for off-sale premises was well-supported, indicating that greater densities of these outlets were related to greater rates of violent crime in adjacent areas. DISCUSSION AND CONCLUSIONS: While these analyses confirmed a previous time-series analysis in finding no city-wide effect of the increase in off-premise outlets, they do suggest that such outlets in a local area may be related to violence in nearby geographic areas. They indicate the importance of examining neighbourhood-specific effects of alcohol outlets on violence in addition to the city-wide effects. They also present further evidence supporting the need to examine the differential effects of on-sale and off-sale premises.

Heterogeneous Costs of Alcohol and Drug Problems Across Cities and Counties in California.

BACKGROUND: Estimates of economic and social costs related to alcohol and other drug (AOD) use and abuse are usually made at state and national levels. Ecological analyses demonstrate, however, that substantial variations exist in the incidence and prevalence of AOD use and problems including impaired driving, violence, and chronic disease between smaller geopolitical units like counties and cities. This study examines the ranges of these costs across counties and cities in California. METHODS: We used estimates of the incidence and prevalence of AOD use, abuse, and related problems to calculate costs in 2010 dollars for all 58 counties and an ecological sample of 50 cities with populations between 50,000 and 500,000 persons in California. The estimates were built from archival and public-use survey data collected at state, county, and city levels over the years from 2009 to 2010. RESULTS: Costs related to alcohol use and related problems exceeded those related to illegal drugs across all counties and most cities in the study. Substantial heterogeneities in costs were observed between cities within counties. CONCLUSIONS: AOD costs are heterogeneously distributed across counties and cities, reflecting the degree to which different populations are engaged in use and abuse across the state. These findings provide a strong argument for the distribution of treatment and prevention resources proportional to need.

Prescription opioid poisoning across urban and rural areas: identifying vulnerable groups and geographic areas.

AIMS: To determine (1) whether prescription opioid poisoning (PO) hospital discharges spread across space over time, (2) the locations of 'hot-spots' of PO-related hospital discharges, (3) how features of the local environment contribute to the growth in PO-related hospital discharges and (4) where each environmental feature makes the strongest contribution. DESIGN: Hierarchical Bayesian Poisson space-time analysis to relate annual discharges from community hospitals to postal code characteristics over 10 years. SETTING: California, USA. PARTICIPANTS: Residents of 18 517 postal codes in California, 2001-11. MEASUREMENTS: Annual postal code-level counts of hospital discharges due to PO poisoning were related to postal code pharmacy density, measures of medical need for POs (i.e. rates of cancer and arthritis-related hospital discharges), economic stressors (i.e. median household income, percentage of families in poverty and the unemployment rate) and concentration of manual labor industries. FINDINGS: PO-related hospital discharges spread from rural and suburban/exurban 'hot-spots' to urban areas. They increased more in postal codes with greater pharmacy density [rate ratio (RR) = 1.03; 95% credible interval (CI) = 1.01, 1.05], more arthritis-related hospital discharges (RR = 1.08; 95% CI = 1.06, 1.11), lower income (RR = 0.85; 95% CI = 0.83, 0.87) and more manual labor industries (RR = 1.15; 95% CI = 1.10, 1.19 for construction; RR = 1.12; 95% CI = 1.04, 1.20 for manufacturing industries). Changes in pharmacy density primarily affected PO-related discharges in urban areas, while changes in income and manual labor industries especially affected PO-related discharges in suburban/exurban and rural areas. CONCLUSIONS: Hospital discharge rates for prescription opioid (PO) poisoning spread from rural and suburban/exurban hot-spots to urban areas, suggesting spatial contagion. The distribution of age-related and work-place-related sources of medical need for POs in rural areas and, to a lesser extent, the availability of POs through pharmacies in urban areas, partly explain the growth of PO poisoning across California, USA.