Application of space-time scan statistics to describe geographic and temporal clustering of visible drug activity

Enhanced Cohort Methods for HIV Research and Epidemiology (ENCORE): Protocol for a Nationwide Hybrid Cohort for Transgender Women in the United States

BACKGROUND

In the United States, transgender women are disproportionately impacted by HIV and prioritized in the national strategy to end the epidemic. Individual, interpersonal, and structural vulnerabilities underlie HIV acquisition among transgender women and fuel syndemic conditions, yet no nationwide cohort monitors their HIV and other health outcomes.

OBJECTIVE

Our objective is to develop a nationwide cohort to estimate HIV incidence, identify risk factors, and investigate syndemic conditions co-occurring with HIV vulnerability or acquisition among US transgender women. The study is informed by the Syndemics Framework and the Social Ecological Model, positing that stigma-related conditions are synergistically driven by shared multilevel vulnerabilities.

METHODS

To address logistical and cost challenges while minimizing technology barriers and research distrust, we aim to establish a novel, hybrid community hub-supported digital cohort (N=3000). The digital cohort is the backbone of the study and is enhanced by hubs strategically located across the United States for increased engagement and in-person support. Study participants are English or Spanish speakers, are aged ≥18 years, identify as transgender women or along the transfeminine spectrum, reside in 1 of the 50 states or Puerto Rico, and do not have HIV (laboratory confirmed). Participants are followed for 24 months, with semiannual assessments. These include a questionnaire and laboratory-based HIV testing using self-collected specimens. Using residential zip codes, person-level data will be merged with contextual geolocated data, including population health measures and economic, housing, and other social and structural factors. Analyses will (1) evaluate the contribution of hub support to the digital cohort using descriptive statistics; (2) estimate and characterize syndemic patterns among transgender women using latent class analysis; (3) examine the role of contextual factors in driving syndemics and HIV prevention over time using multilevel regression models; (4) estimate HIV incidence in transgender women and examine the effect of syndemics and contextual factors on HIV incidence using Poisson regression models; and (5) develop dynamic, compartmental models of multilevel combination HIV prevention interventions among transgender women to simulate their impact on HIV incidence through 2030.

RESULTS

Enrollment launched on March 15, 2023, with data collection phases occurring in spring and fall. As of February 24, 2024, a total of 3084 individuals were screened, and 996 (32.3%) met the inclusion criteria and enrolled into the cohort: 2.3% (23/996) enrolled at a hub, and 53.6% (534/996) enrolled through a community hub-supported strategy. Recruitment through purely digital methods contributed 61.5% (1895/3084) of those screened and 42.7% (425/996) of those enrolled in the cohort.

CONCLUSIONS

Study findings will inform the development of evidence-based interventions to reduce HIV acquisition and syndemic conditions among US transgender women and advance efforts to end the US HIV epidemic. Methodological findings will also have critical implications for the design of future innovative approaches to HIV research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/59846.

Heterogeneity of influenza infection at precise scale in Yinchuan, Northwest China, 2012-2022: evidence from Joinpoint regression and spatiotemporal analysis

Identifying high-risk regions and turning points of influenza with a precise spatiotemporal scale may provide effective prevention strategies. In this study, epidemiological characteristics and spatiotemporal clustering analysis at the township level were performed. A descriptive study and a Joinpoint regression analysis were used to explore the epidemiological characteristics and the time trend of influenza. Spatiotemporal autocorrelation and clustering analyses were carried out to explore the spatiotemporal distribution characteristics and aggregation. Furthermore, the hotspot regions were analyzed by spatiotemporal scan analysis. A total of 4025 influenza cases were reported in Yinchuan showing an overall increasing trend. The tendency of influenza in Yinchuan consisted of three stages: increased from 2012 to the first peak in 2019 (32.62/100,000) with a slight decrease in 2016; during 2019 and 2020, the trend was downwards; then it increased sharply again and reached another peak in 2022. The Joinpoint regression analysis found that there were three turning points from January 2012 to December 2022, namely January 2020, April 2020, and February 2022. The children under ten displayed an upward trend and were statistically significant. The trend surface analysis indicated that there was a shifting trend from northern to central and southern. A significant positive spatial auto-correlation was observed at the township level and four high-incidence clusters of influenza were detected. These results suggested that children under 10 years old deserve more attention and the spatiotemporal distribution of high-risk regions of influenza in Yinchuan varies every year at the township level. Thus, more monitoring and resource allocation should be prone to the four high-incidence clusters, which may benefit the public health authorities to carry out the vaccination and health promotion timely.

Spatio-temporal patterns of the mortality of diseases associated with malnutrition and their relationship with food establishments in Mexico

This study explores the spatio-temporal behavior of mortality due to multiple causes associated with several diseases and their relationship with the physical availability of food. We analyze data for the 2010-2020 period at the municipality level in Mexico. After collecting and standardizing national databases for each disease, we perform SATSCAN temporal and FleXScan spatial cluster analyses. We use the he Kruskal-Wallis test to analyze the differences between municipalities with high relative risk of mortality and their relationship with food retail units and food establishments. We found statistically significant relationships between clusters by disease and the physical availability of food per hundred thousand inhabitants. The main pattern is a higher average density of convenience stores, supermarkets, fast food chains and franchises, and Mexican snack restaurants in high-risk municipalities, while a higher density of grocery stores and inns, cheap kitchens, and menu restaurants exists in the municipalities with low risk. The density of convenience stores, fast food chains and franchises, and Mexican snack restaurants plays a very important role in mortality behavior, so measures must exist to regulate them and encourage and protect convenience stores, grocery stores, and local food preparation units.

Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries

BACKGROUND

Drug Use Disorder (DUD) is a major contributor to world-wide morbidity and mortality. The extensive national registers in Sweden provide the basis for a study of spatial and temporal patterns of DUD onset and recurrence in Sweden from 2001-2015.

METHODS

To identify patterns of DUD over space, time and gender for Swedish individuals aged 15-35, space-time clustering using SaTScan was applied. We used yearly information on residential locations in Demographic Statistical Areas (DeSO) for all of Sweden. The clustering analysis used a Poisson probability model and a null hypothesis that the expected number of cases in each DeSO was proportional to the population size of DeSOs. As SaTScan results can be unstable, steps were taken to determine stable clusters and to refine and optimize cluster size. Results for each gender-register combination were compared to the results of spatial clustering using Gi* statistics. The space-time scanning model was also run with an adjustment for neighborhood socioeconomic status to determine DUD prevalence as it relates to education, income, unemployment and receipt of social welfare.

RESULTS

DUD prevalence increased over time. Males yielded more significant clusters than females for both criminal and medical registers. Female DUD prevalence rates increased over time, especially after 2012. Higher correlations in DUD rates existed across the two registers than across gender. Male clusters were present from 2004 onwards while female-criminal clusters appeared after 2007, and female-medical clusters not until 2010. By 2013, clusters existed for all gender-register combinations. Male-criminal clusters were concentrated in Stockholm, Göteborg and Malmö as were male and female-medical clusters. Neighborhood SES was more highly related to the distribution of criminal than medical DUD clusters. A persistent gap in core clusters was identified in Stockholm in an area with notably high SES.

CONCLUSIONS

Persistent hotspots of DUD in Sweden were confirmed as well as new and emerging hotspots, especially in Stockholm, Göteborg and Malmö. Higher correlations existed in DUD rates across registers than across gender. The findings are useful for monitoring the current drug problem and for identifying drivers underlying patterns of spread and important causal pathways to DUD.

Spatiotemporal patterns of mortality associated with chronic non-communicable diseases and child malnutrition at the municipal level in Mexico

Malnutrition is one of the main risk factors related to chronic non-communicable diseases and child undernourishment on a planetary scale. Mexico is one of the countries with the highest levels of malnutrition, but there is also an accelerated increase in overweight or obesity. This study explored the spatiotemporal behaviour of mortality associated with chronic non-communicable diseases such as type II diabetes mellitus, hypertension, ischemic heart disease and cerebrovascular disease. The analysis was carried out at the municipality level for the 2000-2020 period targeting two age groups: ≥60-year olds and 20-59-year olds. In addition, 0-4-year olds were investigated with respect to undernourishment. National databases were gathered and standardized for each disease and SaTScan spatiotemporal cluster analyses were performed. We found that mortality associated with most of the diseases evaluated has increased since 2016 except for mortality caused by child undernourishment, which showed a downward trend during the study period. To focus on active conglomerates of diseases is important as they currently represent a threat to public health. Our results contribute to the potential spatial prioritization of the allocation of resources and campaigns for prevention and treatment of chronic non-communicable diseases and child undernourishment. Generally, geographical studies are fundamental for the discovery of disease aetiology and they provide valuable and timely information to multiple stakeholders.

Spatiotemporal epidemiology of cryptosporidiosis in the Republic of Ireland, 2008-2017: development of a space-time "cluster recurrence" index

Background

Ireland frequently reports the highest annual Crude Incidence Rates (CIRs) of cryptosporidiosis in the EU, with national CIRs up to ten times the EU average. Accordingly, the current study sought to examine the spatiotemporal trends associated with this potentially severe protozoan infection.

Methods

Overall, 4509 cases of infection from January 2008 to December 2017 were geo-referenced to a Census Small Area (SA), with an ensemble of geo-statistical approaches including seasonal decomposition, Local Moran’s I, and space–time scanning used to elucidate spatiotemporal patterns of infection.

Results

One or more confirmed cases were notified in 3413 of 18,641 Census SAs (18.3%), with highest case numbers occurring in the 0–5-year range (n = 2672, 59.3%). Sporadic cases were more likely male (OR 1.4) and rural (OR 2.4), with outbreak-related cases more likely female (OR 1.4) and urban (OR 1.5). Altogether, 55 space–time clusters (≥ 10 confirmed cases) of sporadic infection were detected, with three “high recurrence” regions identified; no large urban conurbations were present within recurrent clusters.

Conclusions

Spatiotemporal analysis represents an important indicator of infection patterns, enabling targeted epidemiological intervention and surveillance. Presented results may also be used to further understand the sources, pathways, receptors, and thus mechanisms of cryptosporidiosis in Ireland.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06598-3.

A spatio-temporal Bayesian model to estimate risk and evaluate factors related to drug-involved emergency department visits in the greater Baltimore metropolitan area

The ongoing opioid overdose epidemic in the United States presents a major public health challenge. Opioid-involved morbidity, especially nonfatal emergency department (ED) visits, are a key opportunity to prevent mortality and measure the extent of the problem in the local substance use landscape. Data on the rate of ED visits is normally distributed by federal agencies. However, state- and substate-level rates of ED visit demonstrate significant geographic variation. This study uses an ongoing sample of ED visits from four hospitals in the University of Maryland Medical System from January 2016 to December 2019 to provide locally sensitive information on ED visit rates and risk for drug-related health outcomes. Using exploratory spatial data analysis and spatio-temporal Bayesian models, this study analyzes both the frequency and risk of heroin-, methadone-, and cocaine-involved ED visits across the greater Baltimore Maryland area at the Zip Code Tabulation Area-level (ZCTA). The Global Moran's I for total heroin-, methadone-, and cocaine-involved ED visits in 2019 was 0.44, 0.56, and 0.53, demonstrating strong positive spatial autocorrelation. Spatio-temporal Bayesian models indicated that ZCTA with a higher score in a deprivation index, with a higher share of Centers for Medicare Services claims, and adjacent to a sampled UMMS hospital had an increased risk of ED visits, with variation in the magnitude of this increased risk depending on the drug-demographic strata. Modeled disease risk surfaces - including posterior median risk and posterior exceedance probabilities - showed distinctly different risk surfaces between the substances of interest, probabilistically identifying ZCTA with a lower or higher risk of ED visits. The modeling approach used a sample of ED visits from a larger health system to estimate recent, locally sensitive drug-related morbidity across a large metropolitan area.

Evaluation of Policy Effectiveness by Mathematical Modeling for the Opioid Crisis with Spatial Study and Trend Analysis

The current opioid epidemic in the US presents a great problem which calls for policy supervision and regulation. In this work, the opioid cases of five states were used for trend analysis and modeling for the estimation of potential policy effects. An evaluation model was established to analyze the severity of the opioid abuse based on the entropy weight method (EWM) and rank sum ratio (RSR). Four indexes were defined to estimate the spatial distribution of development and spread of the opioid crisis. Thirteen counties with the most severe opioid abuse in five states were determined using the EWM-RSR model and those indexes. Additionally, a forecast of the development of opioid abuse was given based on an autoregressive (AR) model. The RSR values of the thirteen counties would increase to the range between 0.951 and 1.226. Furthermore, the least absolute shrinkage and selection operator (LASSO) method was adopted. The previous indexes were modified, incorporating the comprehensive socioeconomic effects. The optimal penalty term was found to facilitate the stability and reliability of the model. By using the comprehensive model, it was found that three factors—VC112, VC114, VC115—related to disabled people have a great influence on the development of opioid abuse. The simulated policies were performed in the model to decrease the values of the indicators by 10%–50%. The corresponding RSR values can decline to the range between 0.564 and 0.606. Adopting policies that benefit the disabled population should inhibit the trend of opioid abuse.

Exploratory Space-Time Analyses of Reported Lyme Borreliosis Cases in France, 2016-2019

In recent decades, the incidence of Lyme borreliosis (LB) in Europe seems to have increased, underpinning a growing public health concern. LB surveillance systems across the continent are heterogeneous, and the spatial and temporal patterns of LB reports have been little documented. In this study, we explored the spatio-temporal patterns of LB cases reported in France from 2016 to 2019, to describe high-risk clusters and generate hypotheses on their occurrence. The space-time K-function and the Kulldorf's scan statistic were implemented separately for each year to evaluate space-time interaction between reported cases and searching clusters. The results show that the main spatial clusters, of radius size up to 97 km, were reported in central and northeastern France each year. In 2017-2019, spatial clusters were also identified in more southern areas (near the Alps and the Mediterranean coast). Spatio-temporal clustering occurred between May and August, over one-month to three-month windows in 2016-2017 and in 2018-2019. A strong spatio-temporal interaction was identified in 2018 within 16 km and seven days, suggesting a potential local and intense pathogen transmission process. Ongoing improved surveillance and accounting for animal hosts, vectors, meteorological factors and human behaviors are keys to further elucidate LB spatio-temporal patterns.

A spatiotemporal analysis of opioid poisoning mortality in Ohio from 2010 to 2016

Opioid-related deaths have severely increased since 2000 in the United States. This crisis has been declared a public health emergency, and among the most affected states is Ohio. We used statewide vital statistic data from the Ohio Department of Health (ODH) and demographics data from the U.S. Census Bureau to analyze opioid-related mortality from 2010 to 2016. We focused on the characterization of the demographics from the population of opioid-related fatalities, spatiotemporal pattern analysis using Moran's statistics at the census-tract level, and comorbidity analysis using frequent itemset mining and association rule mining. We found higher rates of opioid-related deaths in white males aged 25-54 compared to the rest of Ohioans. Deaths tended to increasingly cluster around Cleveland, Columbus and Cincinnati and away from rural regions as time progressed. We also found relatively high co-occurrence of cardiovascular disease, anxiety or drug abuse history, with opioid-related mortality. Our results demonstrate that state-wide spatiotemporal and comorbidity analysis of the opioid epidemic could provide novel insights into how the demographic characteristics, spatiotemporal factors, and/or health conditions may be associated with opioid-related deaths in the state of Ohio.

Perceived neighborhood disorder and frequency of marijuana use among emerging adult African American females

Emerging adult African American females are at increased risk for cannabis use disorders. Ecological models suggest that African Americans' increased risk for substance use disorders and associated adverse outcomes may result from chronic exposure to contextual disadvantages, such as living in economically deprived and disorganized communities. However levels of vulnerability for developing cannabis use disorders vary, even among residents of disadvantaged neighborhoods. Therefore, studies focused on within group differences are necessary. This study examined the relationship between frequency of marijuana use and perceived neighborhood disorder. The sample included 117 African American emerging adult females (M_age = 23.6 ± 3.4). After providing informed consent, participants completed a semi-structured interview that included the Neighborhood Environment Scale and a self-report measure of marijuana use. Additionally, participants provided a urine sample that was tested for the presence of psychoactive drugs. 46% tested positive for marijuana and 45% reported using marijuana in the past 30 days. 27% reported frequent/heavy use. Results from multinomial logistic regression analysis indicated a significant relationship between perceived neighborhood disorder and heavy marijuana use (AOR = 3.3; 95% CI = 1.06 - 10.29). Findings suggest African American emerging adult female residents of economically disadvantaged neighborhoods who appraise their environments as disorganized may be at heighten risk for problematic marijuana use and should be targeted for intervention. Moreover, the findings support the need for multi-systems interventions. As policy makers consider the legalization of marijuana, it is important that differences in marijuana use behaviors and negative outcomes across groups and contexts are taken into consideration.

Spatiotemporal pattern of COVID-19 and government response in South Korea (as of May 31, 2020)

OBJECTIVES

The aim of this study was to assess how coronavirus disease 2019 (COVID-19) clustered across districts in South Korea and to assess whether the pattern and duration of clusters changed following the country's containment strategy.

METHODS

A spatiotemporal analysis of COVID-19 daily confirmed cases by 250 districts in South Korea from January 20 to May 31, 2020, obtained from the Korea Centers for Disease Control and Prevention and each provincial website, was conducted. The global Moran's I statistic was used for spatial autocorrelation analysis, and the retrospective space-time scan statistic was used to analyze spatiotemporal clusters of COVID-19.

RESULTS

The geographical distribution showed strong spatial autocorrelation, with a global Moran's I coefficient of 0.784 (p=0.0001). Twelve statistically significant spatiotemporal clusters were identified by space-time scan statistic using a discrete Poisson model. The spatial pattern of clusters changed and the duration of clusters became shorter over time.

CONCLUSIONS

The results indicate that South Korea's containment strategy for COVID-19 was highly effective in both early detection and mitigation, with recent clusters being small in size and duration. Lessons from South Korea should spark a discussion on epidemic response.

Epidemiological and aetiological characteristics of hand, foot, and mouth disease in Sichuan Province, China, 2011-2017

Hand, foot, and mouth disease (HFMD) remains a threat to the Asia-Pacific region. The epidemiological characteristics and pathogen spectrum of HFMD vary with space and time. These variations are crucial for HFMD interventions but poorly understood in Sichuan Province, China, particularly after the introduction of the EV-A71 vaccine. Using descriptive methods, regression analyses, spatial autocorrelation analysis, and space-time scan statistics, we analysed the epidemiological and aetiological characteristics of HFMD surveillance data in Sichuan Province between 2011 and 2017 to identify spatio-temporal variations. The dominant serotypes of HFMD have changed from enterovirus 71 and coxsackievirus A16 to other enteroviruses since 2013. The seasonal pattern of HFMD showed two peaks generally occurring from April to July and November to December; however, the seasonal pattern varied by prefecture and enterovirus serotype. From 2011 to 2017, spatio-temporal clusters were increasingly concentrated in Chengdu, with several small clusters in northeast Sichuan. The clusters observed in southern Sichuan from 2011 to 2015 disappeared in 2016–2017. These findings highlight the importance of pathogen surveillance and vaccination strategies for HFMD interventions; future prevention and control of HFMD should focus on Chengdu and its vicinity.

Advances in spatiotemporal models for non-communicable disease surveillance

Surveillance systems are commonly used to provide early warning detection or to assess an impact of an intervention/policy. Traditionally, the methodological and conceptual frameworks for surveillance have been designed for infectious diseases, but the rising burden of non-communicable diseases (NCDs) worldwide suggests a pressing need for surveillance strategies to detect unusual patterns in the data and to help unveil important risk factors in this setting. Surveillance methods need to be able to detect meaningful departures from expectation and exploit dependencies within such data to produce unbiased estimates of risk as well as future forecasts. This has led to the increasing development of a range of space-time methods specifically designed for NCD surveillance. We present an overview of recent advances in spatiotemporal disease surveillance for NCDs, using hierarchically specified models. This provides a coherent framework for modelling complex data structures, dealing with data sparsity, exploiting dependencies between data sources and propagating the inherent uncertainties present in both the data and the modelling process. We then focus on three commonly used models within the Bayesian Hierarchical Model (BHM) framework and, through a simulation study, we compare their performance. We also discuss some challenges faced by researchers when dealing with NCD surveillance, including how to account for false detection and the modifiable areal unit problem. Finally, we consider how to use and interpret the complex models, how model selection may vary depending on the intended user group and how best to communicate results to stakeholders and the general public.

Alcohol Outlet Density and Area-Level Heavy Drinking Are Independent Risk Factors for Higher Alcohol-Related Complaints

Alcohol outlet density has well-documented associations with social and health indicators such as crime and injury. However, significantly less is known about the relationships among alcohol-related complaints. Bayesian hierarchical Poisson regression with spatial autocorrelation was used to model the association between on- and off-premises alcohol outlet density and area-level prevalence of current drinkers and heavy drinking, and graffiti density-an indicator of physical disorder-in association with calls from civilians reporting illegal use, alcohol sales, and other alcohol-related activities (hereafter alcohol-related complaints). Complaints were separated into two groups based on whether they occurred at (a) clubs/bars/restaurants or (b) elsewhere. Alcohol-related complaints and graffiti were collected from NYC Open Data. Alcohol density data are from ESRI Business Analyst and information on the prevalence of drinking from the New York City Community Health Survey. The unit of analysis consisted of ZIP codes in New York City (n = 167), and the design was a cross-sectional analysis of aggregated data between 2009 and 2015. In multivariable models, a one-unit increase in off-premises alcohol outlet density was associated with a 47% higher risk of alcohol-related complaints at clubs, bars, and restaurants [rate ratio (RR = 1.46, 95% CI = 1.21, 1.77)]. Area-level prevalence of heavy drinking was associated with a 59% higher risk of alcohol-related complaints at the club, bars, and restaurants (RR = 1.59, 95% CI = 1.34, 1.86) and a 40% higher risk of complaints elsewhere (RR = 1.40, 95% CI = 1.20, 1.63). In New York City, area-level heavy drinking prevalence is a strong independent mechanism that links alcohol outlet density to alcohol-related complaints. Area-level heavy drinking should be investigated as a predictor of other public health problems such as drug overdose mortality.

Detection of Spatiotemporal Prescription Opioid Hot Spots With Network Scan Statistics: Multistate Analysis

Background

Overuse and misuse of prescription opioids have become significant public health burdens in the United States. About 11.5 million people are estimated to have misused prescription opioids for nonmedical purposes in 2016. This has led to a significant number of drug overdose deaths in the United States. Previous studies have examined spatiotemporal clusters of opioid misuse, but they have been restricted to circular shaped regions.

Objective

The goal of this study was to identify spatiotemporal hot spots of opioid users and opioid prescription claims using Medicare data.

Methods

We examined spatiotemporal clusters with significantly higher number of beneficiaries and rate of prescriptions for opioids using Medicare payment data from the Centers for Medicare & Medicaid Services. We used network scan statistics to detect significant clusters with arbitrary shapes, the Kulldorff scan statistic to examine the significant clusters for each year (2013, 2014, and 2015) and an expectation-based version to examine the significant clusters relative to past years. Regression analysis was used to characterize the demographics of the counties that are a part of any significant cluster, and data mining techniques were used to discover the specialties of the anomalous providers.

Results

We examined anomalous spatial clusters with respect to opioid prescription claims and beneficiary counts and found some common patterns across states: the counties in the most anomalous clusters were fairly stable in 2014 and 2015, but they have shrunk from 2013. In Virginia, a higher percentage of African Americans in a county lower the odds of the county being anomalous in terms of opioid beneficiary counts to about 0.96 in 2015. For opioid prescription claim counts, the odds were 0.92. This pattern was consistent across the 3 states and across the 3 years. A higher number of people in the county with access to Medicaid increased the odds of the county being in the anomalous cluster to 1.16 in both types of counts in Virginia. A higher number of people with access to direct purchase of insurance plans decreased the odds of a county being in an anomalous cluster to 0.85. The expectation-based scan statistic, which captures change over time, revealed different clusters than the Kulldorff statistic. Providers with an unusually high number of opioid beneficiaries and opioid claims include specialties such as physician’s assistant, nurse practitioner, and family practice.

Conclusions

Our analysis of the Medicare claims data provides characteristics of the counties and provider specialties that have higher odds of being anomalous. The empirical analysis identifies highly refined spatial hot spots that are likely to encounter prescription opioid misuse and overdose. The methodology is generic and can be applied to monitor providers and their prescription behaviors in regions that are at a high risk of abuse.

The Impact of the Urban Neighborhood Environment on Marijuana Trajectories During Emerging Adulthood

Although there is little difference in rates of marijuana use between White and Black youth, Blacks have significantly higher rates of marijuana use and disorder in young adulthood. Theory suggests that factors tied to social disadvantage may explain this disparity, and neighborhood setting may be a key exposure. This study sought to identify trajectories of marijuana use in an urban sample during emerging adulthood, neighborhood contexts that predict these trajectories and social role transitions or "turning points" that may redirect them. Data are from a longitudinal cohort study of 378 primarily Black emerging adults who were first sampled in childhood based on their residence in low-income neighborhoods in Baltimore City and followed up annually. Group-based trajectory modeling identified three groups: No Use (68.8%), Declining Use (19.6%), and Chronic Use (11.7%). Living in close proximity to an alcohol outlet, and living in a neighborhood with more female-headed households and higher rates of violent crime increased the odds of membership in the Chronic Use group relative to No Use. Living in a neighborhood with more positive social activity increased the odds of membership in the Declining Use group relative to No Use. Not receiving a high school diploma or GED, pregnancy, and parenting also increased the odds of membership in the Declining Use group relative to No Use. These findings provide support that minority youth living in socially toxic and disordered neighborhoods are at increased risk of continuing on a trajectory of marijuana use during emerging adulthood while positive social activity in neighborhoods has the potential to redirect these negative trajectories. Besides taking on the responsibilities of parenting, emerging adults in the marijuana user groups had similar educational and family outcomes, suggesting that early marijuana use may have long-term implications.

Combining ecological momentary assessment with objective, ambulatory measures of behavior and physiology in substance-use research

Whereas substance-use researchers have long combined self-report with objective measures of behavior and physiology inside the laboratory, developments in mobile/wearable electronic technology are increasingly allowing for the collection of both subjective and objective information in participants' daily lives. For self-report, ecological momentary assessment (EMA), as implemented on contemporary smartphones or personal digital assistants, can provide researchers with near-real-time information on participants' behavior and mood in their natural environments. Data from portable/wearable electronic sensors measuring participants' internal and external environments can be combined with EMA (e.g., by timestamps recorded on questionnaires) to provide objective information useful in determining the momentary context of behavior and mood and/or validating participants' self-reports. Here, we review three objective ambulatory monitoring techniques that have been combined with EMA, with a focus on detecting drug use and/or measuring the behavioral or physiological correlates of mental events (i.e., emotions, cognitions): (1) collection and processing of biological samples in the field to measure drug use or participants' physiological activity (e.g., hypothalamic-pituitary-adrenal axis activity); (2) global positioning system (GPS) location information to link environmental characteristics (disorder/disadvantage, retail drug outlets) to drug use and affect; (3) ambulatory electronic physiological monitoring (e.g., electrocardiography) to detect drug use and mental events, as advances in machine learning algorithms make it possible to distinguish target changes from confounds (e.g., physical activity). Finally, we consider several other mobile/wearable technologies that hold promise to be combined with EMA, as well as potential challenges faced by researchers working with multiple mobile/wearable technologies simultaneously in the field.

Developmental Pathways from Parental Socioeconomic Status to Adolescent Substance Use: Alternative and Complementary Reinforcement

Although lower socioeconomic status has been linked to increased youth substance use, much less research has determined potential mechanisms explaining the association. The current longitudinal study tested whether alternative (i.e., pleasure gained from activities without any concurrent use of substances) and complementary (i.e., pleasure gained from activities in tandem with substance use) reinforcement mediate the link between lower socioeconomic status and youth substance use. Further, we tested whether alternative and complementary reinforcement and youth substance use gradually unfold over time and then intersect with one another in a cascading manner. Potential sex differences are also examined. Data were drawn from a longitudinal survey of substance use and mental health among high school students in Los Angeles. Data collection involved four semiannual assessment waves beginning in fall 2013 (N = 3395; M baseline age = 14.1; 47% Hispanic, 16.2% Asian, 16.1% multiethnic, 15.7% White, and 5% Black; 53.4% female). The results from a negative binomial path model suggested that lower parental socioeconomic status (i.e., lower parental education) was significantly related to an increased number of substances used by youth. The final path model revealed that the inverse association was statistically mediated by adolescents' diminished engagement in pleasurable substance-free activities (i.e., alternative reinforcers) and elevated engagement in pleasurable activities paired with substance use (i.e., complementary reinforcers). The direct effect of lower parental education on adolescent substance use was not statistically significant after accounting for the hypothesized mediating mechanisms. No sex differences were detected. Increasing access to and engagement in pleasant activities of high quality that do not need a reinforcement enhancer, such as substances, may be useful in interrupting the link between lower parental socioeconomic status and youth substance use.

Neoliberalization's Propagation of Health Inequity in Urban Rebuilding Processes: The Dependence on Context and Path

This article will discuss how neoliberal processes during urban redevelopment sustain and increase health inequities through uneven wealth accumulation and development. It will use examples of urban development in Baltimore, Maryland, United States, to highlight how key neoliberal strategies of territorial development, economic development, and place promotion- mediated through the process of creative destruction-result in uneven development and wealth accumulation, which in turn result in health inequities. The history of rebuilding processes in Baltimore offers insight into the context and path-dependency of current neoliberalization rebuilding processes and current health inequities.

Cross-sectional association between ZIP code-level gentrification and homelessness among a large community-based sample of people who inject drugs in 19 US cities

BACKGROUND

Housing instability has been associated with poor health outcomes among people who inject drugs (PWID). This study investigates the associations of local-level housing and economic conditions with homelessness among a large sample of PWID, which is an underexplored topic to date.

METHODS

PWID in this cross-sectional study were recruited from 19 large cities in the USA as part of National HIV Behavioral Surveillance. PWID provided self-reported information on demographics, behaviours and life events. Homelessness was defined as residing on the street, in a shelter, in a single room occupancy hotel, or in a car or temporarily residing with friends or relatives any time in the past year. Data on county-level rental housing unaffordability and demand for assisted housing units, and ZIP code-level gentrification (eg, index of percent increases in non-Hispanic white residents, household income, gross rent from 1990 to 2009) and economic deprivation were collected from the US Census Bureau and Department of Housing and Urban Development. Multilevel models evaluated the associations of local economic and housing characteristics with homelessness.

RESULTS

Sixty percent (5394/8992) of the participants reported homelessness in the past year. The multivariable model demonstrated that PWID living in ZIP codes with higher levels of gentrification had higher odds of homelessness in the past year (gentrification: adjusted OR=1.11, 95% CI=1.04 to 1.17).

CONCLUSIONS

Additional research is needed to determine the mechanisms through which gentrification increases homelessness among PWID to develop appropriate community-level interventions.

The Spatial-Temporal Pattern of Policing Following a Drug Policy Reform: Triangulating Self-Reported Arrests With Official Crime Statistics

BACKGROUND

In 2009, Mexico enacted a drug policy reform (Narcomenudeo) designed to divert persons possessing small amounts of illicit drugs to treatment rather than incarceration. To assess reform impact, this study examines the spatial-temporal trends of drug-related policing in Tijuana, Mexico post-enactment.

METHOD

Location of self-reported arrests (N = 1,160) among a prospective, community-recruited cohort of people who inject drugs (PWID) in Tijuana (N = 552) was mapped across city neighborhoods. Official police reports detailing drug-related arrests was triangulated with PWID self-reported arrests. Exploratory spatial data analysis examined the distribution of arrests and spatial association between both datasets across three successive years, 2011-2013.

RESULTS

In 2011, over half of PWID reported being detained but not officially charged with a criminal offense; in 2013, 90% of arrests led to criminal charges. Official drug-related arrests increased by 67.8% (p <.01) from 2011 to 2013 despite overall arrest rates remaining stable throughout Tijuana. For each successive year, we identified a high degree of spatial association between the location of self-reported and official arrests (p <.05).

CONCLUSION

Two independent data sources suggest that intensity of drug law enforcement had risen in Tijuana despite the promulgation of a public health-oriented drug policy reform. The highest concentrations of arrests were in areas traditionally characterized by higher rates of drug crime. High correlation between self-reported and official arrest data underscores opportunities for future research on the role of policing as a structural determinant of public health.

Socioeconomic disparities in adolescent substance use: Role of enjoyable alternative substance-free activities

OBJECTIVE

To examine whether reduced substance-free enjoyable activity (i.e., 'alternative reinforcers') is a mediating mechanism linking lower socioeconomic status and adolescent substance use risk.

METHOD

High school students in Los Angeles, CA (N = 2,553, 2013-2014, M age baseline = 14.1) were administered three semiannual surveys. Socioeconomic status was measured by highest parental education reported at Wave 1 (the beginning of 9th grade). Three elements of alternative reinforcement at Wave 2 (six-month follow-up) were assessed as mediators: ratings of frequency of engagement, level of enjoyment, and frequency × enjoyment product scores of substance-free typically pleasant activities (like participation in sports teams or school clubs). Study outcomes included prior six-month alcohol, marijuana, tobacco, and other substance use at Wave 3 (twelve-month follow-up). Logistic regression models adjusting for alternative reinforcers and substance use from the preceding wave as well as other co-factors were used to examine the association of Wave 1 parental education with Wave 3 substance use and mediation by Wave 2 alternative reinforcement.

RESULTS

Lower parental education at Wave 1 was associated with a greater likelihood of reporting alcohol (β = -0.122, 95% CI = -0.234, -0.009) and marijuana (β = -0.168, 95% CI = -0.302, -0.034) use at Wave 3. The inverse association between parental education and substance use was statistically mediated by each element of diminished alternative reinforcement at Wave 2. Lower parental education at Wave 1 was associated with lower alternative reinforcement at Wave 2, which in turn was associated with greater likelihood of alcohol (range of β_{indirect effects} : -0.007 [95% CI = -0.016, -0.001] to -0.01 [95% CI = -0.018, -0.004]) and marijuana (βs: -0.011 [95% CI = -0.022,-0.002] to -0.018 [95% CI = -0.035, -0.005]) use at Wave 3. Parental education was not associated with use of combustible tobacco products or other drugs at Wave 3 adjusting for Wave 1 combustible tobacco and other drug use, respectively (ps ≥ 0.061).

CONCLUSION

Diminished access to and engagement in substance-free enjoyable activity may in part underlie socioeconomic disparities in adolescent alcohol and marijuana use risk. Increasing substance-free enjoyable activities may be useful in substance abuse prevention in socioeconomically disadvantaged youth.

Policing, Community Fragmentation, and Public Health: Observations from Baltimore

Studies show that policing, when violent, and community fragmentation have a negative impact on health outcomes. This current study investigates the connection of policing and community fragmentation and public health. Using an embedded case study analysis, semi-structured interviews were conducted with 21 African-American female and male residents, ages 21-64 years of various neighborhoods of high arrest rates and health and socioeconomic depravation in Baltimore City, MD. Baltimore residents' perceptions of policing, stress, community fragmentation, and solutions are presented. Analysis of the perceptions of these factors suggests that violent policing increases community fragmentation and is a public health threat. Approaches to address this public health threat are discussed.

Association of exposure to neighborhood drug activity, neurobehavioral traits, and marijuana use among at-risk African American females

INTRODUCTION

Theories of relative deprivation suggest African Americans in disadvantaged communities are at increased risk for drug use. This increased risk may be due, in part, to exposure to drugs and drug subcultures. Given the significance of the prefrontal cortex (PFC) functioning in yielding behavior that is strategically guided rather than reactive to environmental demands, it is important to examine the relationship between PFC functioning, neighborhood drug activity and substance use among African Americans residing in high risk communities.

METHODS

A sample of 120 young adult African American females was recruited from high-risk neighborhoods. Each completed the modified version of the neighborhood environment scale, a neurobehavioral assessment designed to measure apathy, behavioral disinhibition and executive dysfunction, and provided a urine sample that was tested for the presence of psychoactive drugs.

RESULTS

Logistic regression analyses indicated that females with higher scores on behavioral disinhibition were 2.6 times more likely to test positive for marijuana (95%CI = 1.02, 6.57). Neither apathy nor executive dysfunction was related to marijuana use. No relationship emerged between neighborhood drug activity and marijuana use.

CONCLUSIONS

Among the neurobehavioral traits considered only behavioral disinhibition was associated with marijuana use, suggesting that different neurobehavioral domains may be uniquely related to marijuana use. For females living in high risk environments, the extent to which they are able to control impulses may provide some protection against marijuana use. Future studies focused on the moderating effects of behavioral disinhibition on the association of exposure to risk environments and marijuana use may prove beneficial. Further, the study adds to the small base of literature supporting the Frontal Systems Behavior Scale as a brief assessment to evaluate frontally-mediated neurobehavioral traits relevant to substance use. However, future studies aimed at examining the influence of neighborhood drug activity might benefit from more precise measures of exposure to neighborhood drug activity. More research to replicate and expand on the present findings is warranted.