Multiresolution Analyses of Neighborhood Correlates of Crime: Smaller Is Not Better.

Population analyses of the correlates of neighborhood crime implicitly assume that a single spatial unit can be used to assess neighborhood effects. However, no single spatial unit may be suitable for analyses of the many social determinants of crime. Instead, effects may appear at multiple spatial resolutions, with some determinants acting broadly, others locally, and still others as some function of both global and local conditions. We provide a multiresolution spatial analysis that simultaneously examines US Census block, block group, and tract effects of alcohol outlets and drug markets on violent crimes in Oakland, California, incorporating spatial lag effects at the 2 smaller spatial resolutions. Using call data from the Oakland Police Department from 2010-2015, we examine associations of assaults, burglaries, and robberies with multiple resolutions of alcohol outlet types and compare the performance of single (block-level) models with that of multiresolution models. Multiresolution models performed better than the block models, reflected in improved deviance and Watanabe-Akaike information criteria and well-supported multiresolution associations. By considering multiple spatial scales and spatial lags in a Bayesian framework, researchers can explore multiresolution processes, providing more detailed tests of expectations from theoretical models and leading the way to more effective intervention efforts.

Measuring Relationships Between Proactive Reporting State-level Prescription Drug Monitoring Programs and County-level Fatal Prescription Opioid Overdoses.

BACKGROUND: Prescription drug monitoring programs (PDMPs) that collect and distribute information on dispensed controlled substances have been adopted by nearly all US states. We know little about program characteristics that modify PDMP impact on prescription opioid (PO) overdose deaths. METHODS: We measured associations between adoption of any PDMP and changes in fatal PO overdoses in 2002-2016 across 3109 counties in 49 states and D.C. We then measured changes related to the adoption of "proactive PDMPs," which report outlying prescribing/dispensing patterns and provide broader access to PDMP data by law enforcement. Comparisons were made within 3 time intervals that broadly represent the evolution of PDMPs (2002-2004, 2005-2009, and 2010-2016). We modeled overdoses using Bayesian space-time models. RESULTS: Adoption of electronic PDMP access was associated with 9% lower rates of fatal PO overdoses after three years (rate ratio [RR] = 0.91, 95% credible interval [CI]: 0.88-0.93) with well-supported effects for methadone (RR = 0.86,95% CI: 0.82-0.90) and other synthetic opioids (RR = 0.82, 95% CI: 0.77-0.86). Compared with states with no/weak PDMPs, proactive PDMPs were associated with fewer deaths attributed to natural/semi-synthetic opioids (2002-2004: RR = 0.72 [0.66-0.78]; 2005-2009: RR = 0.93 [0.90-0.97]; 2010-2016: 0.89 [0.86-0.92]) and methadone (2002-2004: RR = 0.77 [0.69-0.85]; 2010-2016: RR = 0.90 [0.86-0.94]). Unintended effects were observed for synthetic opioids other than methadone (2005-2009: RR = 1.29 [1.21-1.38]; 2010-2016: RR = 1.22 [1.16-1.29]). CONCLUSIONS: State adoption of PDMPs was associated with fewer PO deaths overall while proactive PDMPs alone were associated with fewer deaths related to natural/semisynthetic opioids and methadone, the specific targets of these programs. See video abstract at, http://links.lww.com/EDE/B619.

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.

Tobacco outlet density and adolescents' cigarette smoking: a meta-analysis.

OBJECTIVE: We conducted meta-analyses of studies that investigated the associations between tobacco outlet density around homes and schools and adolescents' past-month cigarette smoking. DATA SOURCES: Systematic literature searches of eight databases were carried out in February 2017. Searches were not limited by date, language, country or peer-reviewed status. STUDY SELECTION: After screening for quality, studies that examined the relationship between tobacco outlet density and adolescents' past-month smoking were selected for inclusion. DATA EXTRACTION: Two investigators screened study abstracts and full texts and independently extracted data. Consensus was reached at each stage. DATA SYNTHESIS: Random-effects meta-analyses were conducted on 11 studies that provided 13 effect sizes. Results showed that there was a significant association between tobacco outlet density around homes and adolescents' past-month smoking behaviour, with an overall effect size of OR=1.08 (95% CI 1.04 to 1.13; P<0.001; I2=0%). For density around schools, the association was not statistically significant (OR=1.01, 95% CI 0.98 to 1.03; P=0.53; I2=39%). CONCLUSIONS: These findings suggest that exposure to tobacco outlets near home environments may be important for understanding adolescents' past-month smoking. Restricting access to tobacco outlets and controlling the number of outlets in residential areas may be an effective preventive strategy to help reduce adolescents' smoking.

Space-Time Analyses of Alcohol Outlets and Related Motor Vehicle Crashes: Associations at City and Census Block-Group Levels.

BACKGROUND: Past research has linked alcohol outlet densities to drinking, drunken driving, and alcohol-related motor vehicle crashes (MVCs). Because impaired drivers travel some distances from drinking places to crash locations, spatial relationships between outlets and crashes are complex. We investigate these relationships at 3 geographic levels: census block groups (CBGs), adjacent (nearby) areas, and whole cities. METHODS: We examined risks of all injury MVCs as well as "had been drinking" (HBD) and single-vehicle-nighttime (SVN) subgroups using data from the Statewide Integrated Traffic Records System across CBGs among 50 California cities from 2001 to 2008. Relationships between outlet densities at the city level, within CBGs, and in adjacent CBGs and crashes were examined using Bayesian Poisson space-time analyses controlling for population size income and other demographics (all as covariates). RESULTS: All injury MVCs were positively related to adjacent CBG population size (relative rate [RR] = 1.008, 95% credible interval (CI) = 1.004, 1.012), and outlet densities at CBG (RR = 1.027, CI = 1.020, 1.035), nearby area (RR = 1.084, CI = 1.060, 1.106) and city levels (RR = 1.227, CI = 1.147, 1.315), and proportion of bars or pubs at the city level (RR = 2.257, CI = 1.187, 4.125). HBD and SVN crashes were comparatively less frequent in high outlet density CBG (RR = 0.993, CI = 0.987, 0.999; RR = 0.963, CI = 0.951, 0.975) and adjacent areas (RR = 0.979, CI = 0.962, 0.996; RR = 0.909, CI = 0.883, 0.936), but positively associated with city-level proportions of bars (RR = 3.373, CI = 0.736, 15.644; RR = 10.322, CI = 1.704, 81.215). Overall, a 10% increase in all outlets was related to 2.8% more injury crashes (CI = 2.3, 3.3) and 2.5% more HBDs (CI = 1.7, 3.3). A 10% increase in bars was related to 1.4% more crashes, 4.3% more HBDs, and 10.3% more SVNs. CONCLUSIONS: Population size and densities of bars or pubs were found to be associated with crash rates, with population effects appearing across cities and outlet effects appearing within dense downtown areas. Summary estimates of outlet and population impacts on MVCs must consider varying contributions at multiple spatial scales.

Spatial Epidemiology of Alcohol- and Drug-Related Health Problems Among Northern Plains American Indians: Nebraska and South Dakota, 2007 to 2012.

BACKGROUND: Despite high abstinence rates, American Indians experience elevated rates of many alcohol and other drug problems. American Indians also predominantly reside in poor and rural areas, which may explain some observed health disparities. We investigated whether geographic areas including reservations or large American Indian populations exhibited greater incidence of alcohol- and drug-related hospitalizations. METHODS: We obtained inpatient hospitalization records for 2 Northern Plain states (Nebraska and South Dakota) for the years 2007 to 2012. We constructed zip code counts for 10 categories of hospitalization with diagnoses or injury causation commonly associated with alcohol or drug use. We related these to community sociodemographic characteristics using Bayesian Poisson space-time regression models and examined associations with and without controls for whether each zip code was located within an American Indian reservation. RESULTS: Controlling for other demographic and economic characteristics, zip codes with greater percentage of American Indians exhibited greater incidence for all 10 substance abuse-related health outcomes (9 of 10 well supported); zip code areas within American Indian reservations had greater incidence of self-inflicted injury and drug dependence and abuse, and reduced incidence of alcohol cirrhosis and prescription opioid poisoning. However, the analyses generally demonstrated no well-supported differences in incidence associated with local residence percentages of American Indian versus African American. CONCLUSIONS: In our analyses, ethnicity or heredity alone did not account for alcohol- and drug-related hospitalizations among Native populations. Aspects of social, economic, and political dimensions of Native lives must be considered in the etiology of alcohol- and drug-related problems for rural-dwelling indigenous peoples.

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.

From Medical to Recreational Marijuana Sales: Marijuana Outlets and Crime in an Era of Changing Marijuana Legislation.

A movement from medical to recreational marijuana use allows for a larger base of potential users who have easier access to marijuana, because they do not have to visit a physician before using marijuana. This study examines whether changes in the density of marijuana outlets were related to violent, property, and marijuana-specific crimes in Denver, CO during a time in which marijuana outlets began selling marijuana for recreational, and not just medical, use. We collected data on locations of crimes, marijuana outlets and covariates for 481 Census block groups over 34 months (N = 16,354 space-time units). A Bayesian Poisson space-time model assessed statistical relationships between independent measures and crime counts within "local" Census block groups. We examined spatial "lag" effects to assess whether crimes in Census block groups adjacent to locations of outlets were also affected. Independent of the effects of covariates, densities of marijuana outlets were unrelated to property and violent crimes in local areas. However, the density of marijuana outlets in spatially adjacent areas was positively related to property crime in spatially adjacent areas over time. Further, the density of marijuana outlets in local and spatially adjacent blocks groups was related to higher rates of marijuana-specific crime. This study suggests that the effects of the availability of marijuana outlets on crime do not necessarily occur within the specific areas within which these outlets are located, but may occur in adjacent areas. Thus studies assessing the effects of these outlets in local areas alone may risk underestimating their true effects.

Ethnic density effect on alcohol-related hospitalizations among Chinese enclaves and ethnoburbs in California, 2007-2011.

INTRODUCTION: Research suggests there is an 'ethnic density effect' whereby racial/ethnic minority populations appear healthier when they reside in neighborhoods with greater numbers of people from the same ethnic group. The purpose of this study is to test whether this effect is observed for residents in Chinese enclaves (immigrant neighborhoods in urban areas) and ethnoburbs (immigrant neighborhoods in suburban areas) for measures on alcohol abuse and dependence. METHODS: ZIP code areas of California that represented Chinese enclaves and ethnoburbs were identified and mapped. Spatial regression models were used to compare neighborhood-level effects, including the ethnic density of Chinese enclaves and ethnoburbs on observed rates of alcohol-related hospitalizations compared to the rest of California. Analyses used Bayesian Space-Time Misalignment Poisson models on the annual number of alcohol-related hospitalizations per ZIP code for the years 2007-2011 (n = 8488 space-by-time units). RESULTS: Ethnic density effect appeared for residents of ZIP code areas with greater proportions of Chinese Americans (RR=0.986, 95% CI: 0.982, 0.990). After controlling for sociodemographic characteristics, residents of ZIP code areas representing Chinese enclaves had lower risks for alcohol-related hospitalizations (RR=0.766, 95% CI: 0.630, 0.927); hospitalizations among residents of Chinese ethnoburbs no longer differed from the rest of the state. Compared to Chinese enclaves, Chinese ethnoburbs had a lower poverty rate (p < .001), a greater English fluency rate (p = .002), and similar proportions of residents who were Chinese and foreign-born. CONCLUSION: Despite the socioeconomic advantages of living in Chinese ethnoburbs, populations living in these neighborhoods experience more problems related to alcohol abuse and dependence.

Assessing the impacts of alcohol outlets on crime as a natural experiment: agglomeration, churning and spatial effects.

BACKGROUND AND AIMS: Retail alcohol outlets appear to open in neighborhoods with low land and structure rents near sources of demand; they may 'agglomerate', open near to one another or 'churn', replace one another, over time. We used the turnover in numbers of outlets over time to measure agglomeration and churning and the impacts of openings and closings of outlets on neighborhood crime. DESIGN: Interrupted quasi-experiments using spatial panel population data from 3768 synthetic block areas over 6 years. SETTING: City of Oakland, CA, USA. PARTICIPANTS: City population. MEASUREMENTS: Census-based socio-demographic estimates and counts of openings and closings of bars/pubs, restaurants and off-premises outlets related to assault, burglary and robbery crime incidents across synthetic Census blocks. Bayesian space-time models were used to assess agglomeration and churning and measure impacts of openings/closings on crime. FINDINGS: Churning was substantial; openings followed closings for all outlets [bars/pubs, relative risk (RR) = 50.9, 95% credible interval (CI) = 3.0-449.9; restaurants, RR = 3.1, CI = 1.5-6.1; off-premises, RR = 23.5, CI = 2.0-129.8]. Bars/pub and restaurant openings agglomerated with other outlets (e.g., RR = 1.02, CI = 1.00-1.03 and RR = 1.01, CI = 1.00-1.01), but off-premises outlets did not. Covarying out effects related to outlet densities, bar/pub openings were related to a 3.5% increase in assaults (RR = 1.04, CI = 1.01-1.06) and 6.9% increase in robberies (RR = 1.07, CI = 1.03-1.11). Restaurant openings were related to a 5.3% increase in burglaries (RR = 1.05, CI = 1.04-1.06). Openings and closings of off-premises outlets were unrelated to all three crime types. CONCLUSIONS: Retail alcohol outlets appear to follow a pattern of opening near to one another and replacing each other over time. Bar, pub and restaurant openings appear to be related to increases in neighborhood crime.

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.

Investigating the Social Ecological Contexts of Opioid Use Disorder and Poisoning Hospitalizations in Pennsylvania.

OBJECTIVE: Opioid use disorder (OUD) and overdose rates have been sharply on the rise in the United States. Although systematic patterns of geographic variation in OUD and opioid overdose have been identified, the factors that explain why opioid-related hospitalizations increase in certain areas are not well understood. METHOD: We examined Pennsylvania Health Care Cost Containment Council (PHC4) hospital inpatient discharge data at the ZIP code level to measure the geographic growth and spread of OUD as measured by 44 quarters of inpatient hospitalization data (from 2004 through 2014) for the entire state of Pennsylvania (n = 16,275 ZIP codes). We assessed the relative contribution of specific attributes of areas (e.g., population density) to patterns of OUD, heroin poisonings, and non-heroin opioid poisonings. Unit misalignment and spatial autocorrelation were corrected for using Bayesian space-time conditional autoregressive models. RESULTS: The associations between a greater density of manual labor establishments and all opioid-related hospitalizations were well supported and positive. A dose-response relationship between population density and opioid-related hospitalizations existed, with a stronger association for heroin poisonings (relative rate, densest quintile vs. least dense: 3.40 [95% credible interval 2.68, 4.39]). CONCLUSIONS: Posterior distributions from these models enabled the identification of locations most vulnerable to problems related to the opioid epidemic in Pennsylvania. Understanding spatial patterns of OUD and poisonings can enhance the development and implementation of effective prevention programs.

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.

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.

A micro-temporal geospatial analysis of medical marijuana dispensaries and crime in Long Beach, California.

AIMS: To determine whether the density of marijuana dispensaries in California, USA, in 2012-13 was related to violent and property crimes, both locally and in adjacent areas, during a time in which local law enforcement conducted operations to reduce the number of storefront medical marijuana dispensaries. DESIGN: Data on locations of crimes and medical marijuana dispensaries as well as other covariates were collected for a sample of 333 Census block groups. SETTING: Long Beach, California, USA from January 2012 to December 2013. OBSERVATIONS: A total of 7992 space-time observations (from 333 Census block groups over 24 time-points). MEASUREMENTS: Outcome measures focused on block-group counts of violent and property crimes. Predictors were numbers of local and adjacent-area medical marijuana dispensaries. Covariates included markers of alcohol availability as well as area demographic and economic characteristics. FINDINGS: After adjustment for covariates, density of medical marijuana dispensaries was unrelated to property and violent crimes in local areas but related positively to crime in spatially adjacent areas [incident rate ratio (IRR) = 1.0248, CI (1.0097, 1.0402) for violent crime, IRR = 1.0169, CI (1.0071, 1.0268) for property crime]. CONCLUSIONS: Using law enforcement to reduce medical marijuana dispensaries in California appears to have reduced crime in residential areas near to, but not in, these locations.

Are community level prescription opioid overdoses associated with child harm? A spatial analysis of California zip codes, 2001-2011.

BACKGROUND: Non-medical prescription opioid use is increasing globally within high-income countries, particularly the United States. However, little is known about whether it is associated with negative outcomes for children. In this study, we use prescription opioid overdose as a proxy measure for non-medical prescription opioid use and ask the following: Do California communities with greater rates of non-medical prescription opioid use also have higher rates of child maltreatment and unintentional child injury? METHODS: We used longitudinal population data to examine ecological associations between hospital discharges involving overdose of prescription opioids and those for child maltreatment or child injury in California zip codes between 2001 and 2011 (n=18,517 zip-code year units) using Bayesian space-time misalignment models. RESULTS: The percentage of hospital discharges involving prescription opioid overdose was positively associated with the number of hospital discharges for child maltreatment (relative rate=1.089, 95% credible interval (1.004, 1.165)) and child injury (relative rate=1.055, 95% credible interval (1.012, 1.096)) over the ten-year period, controlling for other substance use and environmental factors. CONCLUSIONS: Increases in community level prescription opioid overdoses between 2001 and 2011 are associated with a 2.06% increase in child maltreatment discharges and a 1.27% increase in discharges for child injury. Communities with higher rates of non-medical prescription opioid use may experience greater levels of child harms.

School-Based Health Centers' Presence: The Role of School and Community Factors.

INTRODUCTION: School-based health centers (SBHCs) offer an efficient mechanism for delivering health services to large numbers of underserved youth; however, their availability varies across communities. Data on sociocontextual variables were analyzed to investigate factors that inhibit and facilitate SBHCs. METHODS: Secondary data from 2012 to 2015 state databases were linked to examine the association between SBHCs' presence in California high schools and demand, resource, and political conservatism at the school and community levels that may influence where SBHCs are located and the number of provided health services. Data were analyzed in 2015 using hierarchical binary and Poisson models. RESULTS: Presence of a local non-school-based family planning clinic was the strongest correlate of SBHC presence. School size, percentage non-white, and percentage receiving free or reduced-price lunches were positively associated with SBHC presence. Percentage who voted Republican in the 2012 general election and teen pregnancy rates were negatively associated with SBHC presence. None of the predictors were associated with number of services provided by SBHCs. CONCLUSIONS: School and community factors appear to play a role in supporting or impeding the establishment of SBHCs. In addition to variables tapping communities' need for and resources available to support SBHCs, political conservatism appears to affect SBHC availability. SBHC advocates can use this information to understand where opportunities for growth might exist, identify collaborative partners, and prepare for challenges to supporting new SBHCs. Researchers may also use this information in evaluation studies to control for school-level confounders and develop appropriate comparison samples through matching procedures.

Youth activity spaces and daily exposure to tobacco outlets.

We explored whether exposure to tobacco outlets in youths' broader activity spaces differs from that obtained using traditional geographic measures of exposure to tobacco outlet within buffers around homes and schools. Youths completed an initial survey, daily text-prompted surveys, and carried GPS-enabled phones for one week. GPS locations were geocoded and activity spaces were constructed by joining sequential points. We calculated the number of tobacco outlets around these polylines and around homes and schools. Results suggest that activity spaces provide a more accurate measure of tobacco outlet exposures than traditional measures. Assessing tobacco outlet exposure within activity spaces may yield significant information to advance the field.

The impacts of marijuana dispensary density and neighborhood ecology on marijuana abuse and dependence.

BACKGROUND: As an increasing number of states liberalize cannabis use and develop laws and local policies, it is essential to better understand the impacts of neighborhood ecology and marijuana dispensary density on marijuana use, abuse, and dependence. We investigated associations between marijuana abuse/dependence hospitalizations and community demographic and environmental conditions from 2001 to 2012 in California, as well as cross-sectional associations between local and adjacent marijuana dispensary densities and marijuana hospitalizations. METHODS: We analyzed panel population data relating hospitalizations coded for marijuana abuse or dependence and assigned to residential ZIP codes in California from 2001 through 2012 (20,219 space-time units) to ZIP code demographic and ecological characteristics. Bayesian space-time misalignment models were used to account for spatial variations in geographic unit definitions over time, while also accounting for spatial autocorrelation using conditional autoregressive priors. We also analyzed cross-sectional associations between marijuana abuse/dependence and the density of dispensaries in local and spatially adjacent ZIP codes in 2012. RESULTS: An additional one dispensary per square mile in a ZIP code was cross-sectionally associated with a 6.8% increase in the number of marijuana hospitalizations (95% credible interval 1.033, 1.105) with a marijuana abuse/dependence code. Other local characteristics, such as the median household income and age and racial/ethnic distributions, were associated with marijuana hospitalizations in cross-sectional and panel analyses. CONCLUSIONS: Prevention and intervention programs for marijuana abuse and dependence may be particularly essential in areas of concentrated disadvantage. Policy makers may want to consider regulations that limit the density of dispensaries.