Contextual Effects of Neighborhoods and Schools on Adolescent and Young Adult Marijuana Use in the United States

Individual and Community level Developmental Adversities: Associations with Marijuana and Alcohol Use in Late-Adolescents and Young Adults

Exposure to community and individual level stressors during adolescence has been reported to be associated with increased substance use. However, it remains unclear what the relative contribution of different community- and individual-level factors play when alcohol and marijuana use become more prevalent during late adolescence. The present study uses a large longitudinal sample of adolescents (Wave 1: N = 2017; 55% Female; 54.5% White, 22.3% Black, 8% Hispanic, 15% other) to evaluate the association and potential interactions between community- and individual-level factors and substance use from adolescence to young adulthood (Wave 1 to Wave 3 Age Mean [SD]: 16.7 [1.1], 18.3 [1.2], 19.3 [1.2]). Across three waves of data, multilevel modeling (MLM) is used to evaluate the association between community affluence and disadvantage, individual household socioeconomic status (SES, measured as parental level of education and self-reported public assistance) and self-reported childhood maltreatment with self-reported 12-month alcohol and 12-month marijuana use occasions. Sample-selection weights and attrition-adjusted weights are accounted for in the models to evaluate the robustness of the estimated effects. Across the MLMs, there is a significant positive association between community affluence and parental education with self-reported alcohol use but not self-reported marijuana use. In post hoc analyses, higher neighborhood affluence in older adolescents is associated with higher alcohol use and lower use in younger adolescents; the opposite association is found for neighborhood disadvantage. Consistent with past literature, there is a significant positive association between self-reported childhood maltreatment and self-reported 12-month alcohol and 12-month marijuana use. Results are largely consistent across weighted and unweighted analyses, however, in weighted analyses there is a significant negative association between community disadvantage and self-reported 12-month alcohol use. This study demonstrates a nuanced relationship between community- and individual-level factors and substance use during the transitional window of adolescence which should be considered when contextualizing and interpreting normative substance use during adolescence.

Cross-classified multilevel models (CCMM) in health research: A systematic review of published empirical studies and recommendations for best practices

Recognizing that health outcomes are influenced by and occur within multiple social and physical contexts, researchers have used multilevel modeling techniques for decades to analyze hierarchical or nested data. Cross-Classified Multilevel Models (CCMM) are a statistical technique proposed in the 1990s that extend standard multilevel modeling and enable the simultaneous analysis of non-nested multilevel data. Though use of CCMM in empirical health studies has become increasingly popular, there has not yet been a review summarizing how CCMM are used in the health literature. To address this gap, we performed a scoping review of empirical health studies using CCMM to: (a) evaluate the extent to which this statistical approach has been adopted; (b) assess the rationale and procedures for using CCMM; and (c) provide concrete recommendations for the future use of CCMM. We identified 118 CCMM papers published in English-language literature between 1994 and 2018. Our results reveal a steady growth in empirical health studies using CCMM to address a wide variety of health outcomes in clustered non-hierarchical data. Health researchers use CCMM primarily for five reasons: (1) to statistically account for non-independence in clustered data structures; out of substantive interest in the variance explained by (2) concurrent contexts, (3) contexts over time, and (4) age-period-cohort effects; and (5) to apply CCMM alongside other techniques within a joint model. We conclude by proposing a set of recommendations for use of CCMM with the aim of improved clarity and standardization of reporting in future research using this statistical approach.

The Relative Association of Collective Efficacy in School and Neighborhood Contexts With Adolescent Alcohol Use

Background

It is unclear whether either neighborhood collective efficacy or school collective efficacy is associated with adolescent alcohol use. This study aimed to examine the relative contributions of collective efficacy, both in school and in the neighborhood contexts, to alcohol use among Japanese adolescents.

Methods

A cross-sectional study was conducted in public high schools across Okinawa and Ibaraki Prefectures in Japan in 2016. The study participants consisted of 3,291 students in grades 10 through 12 cross-nested in 51 schools and 107 neighborhoods. Alcohol use was measured as current alcohol drinking, which was defined as self-reported drinking on at least 1 day in the past 30 days. Collective efficacy was measured using scales of social cohesion and informal social control in school and the neighborhood. Contextual-level collective efficacy was measured using aggregated school-level and neighborhood-level individual responses, respectively. We used non-hierarchical multilevel models to fit the cross-nested data.

Results

Significant variation in alcohol use was shown between schools but not between neighborhoods. After adjusting for covariates, school collective efficacy at individual- and contextual-levels was protectively associated with alcohol drinking (odds ratio [OR] for the increase of one standard deviation from the mean 0.72; 95% confidence interval [CI], 0.63–0.82 and OR 0.61; 95% CI, 0.49–0.75, respectively), whereas neighborhood collective efficacy at individual- and contextual-levels was not associated with alcohol consumption.

Conclusion

The school-level associations of collective efficacy with adolescent alcohol use may have the greater impact than the neighborhood-level associations. Adolescent drinking prevention efforts should include enhancing school collective efficacy.

Model-based and design-based inference goals frame how to account for neighborhood clustering in studies of health in overlapping context types

Accounting for non-independence in health research often warrants attention. Particularly, the availability of geographic information systems data has increased the ease with which studies can add measures of the local "neighborhood" even if participant recruitment was through other contexts, such as schools or clinics. We highlight a tension between two perspectives that is often present, but particularly salient when more than one type of potentially health-relevant context is indexed (e.g., both neighborhood and school). On the one hand, a model-based perspective emphasizes the processes producing outcome variation, and observed data are used to make inference about that process. On the other hand, a design-based perspective emphasizes inference to a well-defined finite population, and is commonly invoked by those using complex survey samples or those with responsibility for the health of local residents. These two perspectives have divergent implications when deciding whether clustering must be accounted for analytically and how to select among candidate cluster definitions, though the perspectives are by no means monolithic. There are tensions within each perspective as well as between perspectives. We aim to provide insight into these perspectives and their implications for population health researchers. We focus on the crucial step of deciding which cluster definition or definitions to use at the analysis stage, as this has consequences for all subsequent analytic and interpretational challenges with potentially clustered data.