Associations between Historical Redlining and the Risk of Pregnancy Complications and Adverse Birth Outcomes in Massachusetts, 1995-2015.

Objective: To assess the impact of historical redlining on the risk of pregnancy complications and adverse birth outcomes in Massachusetts (MA) from 1995 to 2015. Methods: In total, 288,787 pregnant people from the MA Birth Registry had information on parental characteristics, pregnancy factors, and redlining data at parental residences at the time of delivery. Historic redlining data were based on MA Home Owners' Loan Corporation (HOLC) security maps, with grades assigned (A "best," B "still desirable," C "definitely declining," and D "hazardous"). We used covariate-adjusted binomial regression models to examine associations between HOLC grade and each chronic condition and pregnancy/birth outcome. Results: Living in HOLC grades B through D compared with A was associated with an increased risk of entering pregnancy with chronic conditions and adverse pregnancy/birth outcomes. The strongest associations were seen with pregestational diabetes (adjusted risk ratio [RR] Grade D: 1.7, 95% confidence interval [CI]: 1.3, 2.4) and chronic hypertension (adjusted RR Grade D: 1.5, 95% CI: 1.1, 1.9). Conclusions: Historical redlining policies from the 1930s were associated with adverse pregnancy outcomes and chronic conditions; associations were strongest for chronic conditions in pregnancy.

Restricted spatial models for the analysis of geographic and racial disparities in the incidence of low birthweight in Pennsylvania.

The incidence of low birthweight is a common measure of public health due to the increased risk of complications associated with infants having low and very low birthweights. Moreover, many factors that increase the risk of an infant having a low birthweight can be linked to the mother's socioeconomic status, leading to large racial/ethnic disparities in its incidence. Our objective is thus to analyze the incidence of low and very low birthweight in Pennsylvania counties by race/ethnicity. Due to the small number of births in many Pennsylvania counties when stratified by race/ethnicity, our methods must walk a fine line: While we wish to leverage spatial structure to improve the precision of our estimates, we also wish to avoid oversmoothing the data, which can yield spurious conclusions. As such, we develop a framework by which we can measure (and control) the informativeness of our spatial model. To analyze the data, we first model the Pennsylvania birth data using the conditional autoregressive model to demonstrate the extent to which it can lead to oversmoothing. We then reanalyze the data using our proposed framework and highlight its ability to detect (or not detect) evidence of racial/ethnic disparities in the incidence of low birthweight.

A two-stage bayesian model for assessing the geography of racialized economic segregation and premature mortality across US counties.

Racialized economic segregation, a key metric that simultaneously accounts for spatial, social and income polarization in communities, has been linked to adverse health outcomes, including morbidity and mortality. Due to the spatial nature of this metric, the association between health outcomes and racialized economic segregation could also change with space. Most studies assessing the relationship between racialized economic segregation and health outcomes have always treated racialized economic segregation as a fixed effect and ignored the spatial nature of it. This paper proposes a two-stage Bayesian statistical framework that provides a broad, flexible approach to studying the spatially varying association between premature mortality and racialized economic segregation while accounting for neighborhood-level latent health factors across US counties. The two-stage framework reduces the dimensionality of spatially correlated data and highlights the importance of accounting for spatial autocorrelation in racialized economic segregation measures, in health equity focused settings.

A Segmented Regression Analysis of Household Income and Recurrent Falls Among Adults in a National Cohort Study.

Falls can have life-altering consequences for older adults, including extended recovery periods and compromised independence. Higher household income may mitigate the risk of falls by providing financial resources for mobility tools, remediation of environmental hazards, and needed supports, or it may buffer the impact of an initial fall on subsequent risk through improved assistance and care. Household income has not had a consistently observed association with falls in older adults; however, a segmented association may exist such that associations are attenuated above a certain income threshold. In this study, we utilized segmented negative binomial regression analysis to examine the association between household income and recurrent falls among 2,302 participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited between 2003 and 2007. Income-fall association segments separated by changes in slope were considered. Model results indicated a 2-segment association between household income and recurrent falls in the past year. In the range below the breakpoint, household income was negatively associated with the rate of recurrent falls across all age groups examined; in a higher income range (from $20,000-$49,999 to ≥$150,000), the association was attenuated (weaker negative trend) or reversed (positive trend). These findings point to potential benefits of ensuring that incomes for lower-income adults exceed the threshold needed to confer a reduced risk of recurrent falls.

Racialized economic segregation and potentially preventable hospitalizations among Medicaid/CHIP-enrolled children.

OBJECTIVE: To examine geographic variation in preventable hospitalizations among Medicaid/CHIP-enrolled children and to test the association between preventable hospitalizations and a novel measure of racialized economic segregation, which captures residential segregation within ZIP codes based on race and income simultaneously. DATA SOURCES: We supplement claims and enrollment data from the Transformed Medicaid Statistical Information System (T-MSIS) representing over 12 million Medicaid/CHIP enrollees in 24 states with data from the Public Health Disparities Geocoding Project measuring racialized economic segregation. STUDY DESIGN: We measure preventable hospitalizations by ZIP code among children. We use logistic regression to estimate the association between ZIP code-level measures of racialized economic segregation and preventable hospitalizations, controlling for sex, age, rurality, eligibility group, managed care plan type, and state. DATA EXTRACTION METHODS: We include children ages 0-17 continuously enrolled in Medicaid/CHIP throughout 2018. We use validated algorithms to identify preventable hospitalizations, which account for characteristics of the pediatric population and exclude children with certain underlying conditions. PRINCIPAL FINDINGS: Preventable hospitalizations vary substantially across ZIP codes, and a quarter of ZIP codes have rates exceeding 150 hospitalizations per 100,000 Medicaid-enrolled children per year. Preventable hospitalization rates vary significantly by level of racialized economic segregation: children living in the ZIP codes that have the highest concentration of low-income, non-Hispanic Black residents have adjusted rates of 181 per 100,000 children, compared to 110 per 100,000 for children in ZIP codes that have the highest concentration of high-income, non-Hispanic white residents (p < 0.01). This pattern is driven by asthma-related preventable hospitalizations. CONCLUSIONS: Medicaid-enrolled children's risk of preventable hospitalizations depends on where they live, and children in economically and racially segregated neighborhoods-specifically those with higher concentrations of low-income, non-Hispanic Black residents-are at particularly high risk. It will be important to identify and implement Medicaid/CHIP and other policies that increase access to high-quality preventive care and that address structural drivers of children's health inequities.

The Association between Changes in Built Environment and Changes in Walking among Older Women in Portland, Oregon.

Some cross-sectional evidence suggests that the objectively measured built environment can encourage walking among older adults. We examined the associations between objectively measured built environment with change in self-reported walking among older women by using data from the Study of Osteoporotic Fractures (SOF). We evaluated the longitudinal associations between built environment characteristics and walking among 1253 older women (median age = 71 years) in Portland, Oregon using generalized estimating equation models. Built environment characteristics included baseline values and longitudinal changes in distance to the closest bus stop, light rail station, commercial area, and park. A difference of 1 km in the baseline distance to the closest bus stop was associated with a 12% decrease in the total number of blocks walked per week during follow-up (eß = 0.88, 95% CI: 0.78, 0.99). Our study provided limited support for an association between neighborhood transportation and changes in walking among older women. Future studies should consider examining both objective measures and perceptions of the built environment.

Examining the Geospatial Distribution of Health and Support Services for Transgender, Gender Nonbinary, and Other Gender Diverse People in New York City.

A geospatial analysis of services that support transgender and gender diverse ("trans") people in New York City (NYC) was conducted to investigate associations with neighborhood-level sociodemographic characteristics. In June 2019, there were 5.3 services for every 100,000 of the general NYC population; controlling for other covariates, they were more commonly located in neighborhoods with larger populations of non-Hispanic Black (rate ratio [RR]=1.02, 95% confidence interval [CI]: 1.00-1.04), Hispanic/Latino (RR=1.03, 95% CI: 1.00-1.06), and gay/lesbian people (RR=1.53, 95% CI: 1.03-2.34). These findings suggest that the distribution of trans-focused services in NYC is proximal to communities that are most in need, but research should examine proximity to trans people specifically and distribution in nonurban areas.

Examining Associations between Adverse Childhood Experiences and Posttraumatic Stress Disorder Symptoms among Young Survivors of Urban Violence.

Our study examines the association between Adverse Childhood Experience (ACE) exposure and posttraumatic stress disorder (PTSD) symptoms among survivors of violence. In this cross-sectional study, an ACE questionnaire and PTSD Checklist for DSM-5 (PCL-5) were completed by 147 participants ≤ 3 months after presenting to a Philadelphia, PA emergency department between 2014 and 2019 with a violent injury. This study treated ACEs, both separate and cumulative, as exposures and PTSD symptom severity as the outcome. Most participants (63.3%) met criteria for provisional PTSD, 90% reported experiencing ≥ 1 ACE, and 39% reported experiencing ≥ 6 ACEs. Specific ACEs were associated with increasing PCL-5 scores and increased risk for provisional PTSD. Additionally, as participants' cumulative ACE scores increased, their PCL-5 scores worsened (b = 0.16; p < 0.05), and incremental ACE score increases predicted increased odds for a positive provisional PTSD screen. Results provide further evidence that ACEs exacerbate the development of PTSD in young survivors of violence. Future research should explore targeted interventions to treat PTSD among survivors of interpersonal violence.

Prenatal Diet as a Modifier of Environmental Risk Factors for Autism and Related Neurodevelopmental Outcomes.

PURPOSE OF REVIEW: Environmental chemicals and toxins have been associated with increased risk of impaired neurodevelopment and specific conditions like autism spectrum disorder (ASD). Prenatal diet is an individually modifiable factor that may alter associations with such environmental factors. The purpose of this review is to summarize studies examining prenatal dietary factors as potential modifiers of the relationship between environmental exposures and ASD or related neurodevelopmental outcomes. RECENT FINDINGS: Twelve studies were identified; five examined ASD diagnosis or ASD-related traits as the outcome (age at assessment range: 2-5 years) while the remainder addressed associations with neurodevelopmental scores (age at assessment range: 6 months to 6 years). Most studies focused on folic acid, prenatal vitamins, or omega-3 fatty acids as potentially beneficial effect modifiers. Environmental risk factors examined included air pollutants, endocrine disrupting chemicals, pesticides, and heavy metals. Most studies took place in North America. In 10/12 studies, the prenatal dietary factor under study was identified as a significant modifier, generally attenuating the association between the environmental exposure and ASD or neurodevelopment. Prenatal diet may be a promising target to mitigate adverse effects of environmental exposures on neurodevelopmental outcomes. Further research focused on joint effects is needed that encompasses a broader variety of dietary factors, guided by our understanding of mechanisms linking environmental exposures with neurodevelopment. Future studies should also aim to include diverse populations, utilize advanced methods to optimize detection of novel joint effects, incorporate consideration of timing, and consider both synergistic and antagonistic potential of diet.

Spatially varying racial inequities in cardiovascular health and the contribution of individual- and neighborhood-level characteristics across the United States: The REasons for geographic and racial differences in stroke (REGARDS) study.

Black-White inequities in cardiovascular health (CVH) pose a significant public health challenge, with these disparities also varying geographically across the US. There remains limited evidence of the impact of social determinants of health on these inequities. Using a national population-based cohort from the REasons for Geographic and Racial Differences in Stroke study, we assessed the spatial heterogeneity in Black-White differences in CVH and determined the extent to which individual- and neighborhood-level characteristics explain these inequities. We utilized a Bayesian hierarchical statistical framework to fit spatially varying coefficient models. Results showed overall and spatially varying inequities, where Black participants had significantly poorer CVH. The maps of the state level random effects also highlighted how inequities vary. The evidence produced in this study further highlights the importance of multilevel approaches - at the individual- and neighborhood-levels - that need to be in place to address these geographic and racial differences in CVH.

Spatial predictors of heavy metal concentrations in epiphytic moss samples in Seattle, WA.

The use of bio-indicators is an emerging, cost-effective alternative approach to identifying air pollution and assessing the need for additional air monitoring. This community science project explores the use of moss samples as bio-indicators of the distribution of metal air particulates in two residential neighborhoods of the industrial Duwamish Valley located in Seattle, WA (USA). We applied geographically weighted regression to data from 61 youth-collected samples to assess the location-specific area-level spatial predictors of the concentrations of 25 elements with focus on five heavy metals of concern due to health and environmental considerations. Spatial predictors included traffic volume, industrial land uses, major roadways, the airport, dirt roads, the Duwamish River, impervious surfaces, tree canopy cover, and sociodemographics. Traffic volume surrounding sample locations was the most consistent positive predictor of increasing heavy metal concentration. Greater distance from the heavy-industry corridor surrounding the Duwamish River predicted lower concentrations of all metals, with statistically significant associations for chromium and lead in some areas. As the distance from dirt roads increased, the concentration of arsenic and chromium decreased significantly. Percent tree canopy within 200 m of sample locations was a significant protective factor for cadmium concentrations. In addition, percent people of color was significantly positively associated with increasing lead, chromium and nickel concentrations. Our findings underscore the potential influence of heavy industry and mobile sources on heavy metal concentrations, the buffering potential of trees in local environments, and persistent opportunity to improve environmental justice.

Association of Maternal-Clinician Ethnic Concordance With Latinx Youth Receipt of Family-Centered Care.

Importance: Disparities in medical home provisions, including receipt of family-centered care (FCC), have persisted for Latinx youths in the US. Objective: To examine the association between maternal-clinician ethnic concordance and receipt of FCC among US-born Latinx youths. Design, Setting, and Participants: A cross-sectional secondary analysis of data from the Medical Expenditure Panel Survey from January 1, 2010, to December 31, 2017, was conducted. Data analysis was performed from January 6 to February 3, 2020. Latinx youths (age, ≤17 years) born in the US who had a usual source of care and used care in the past year, their Latina mothers (age, 18-64 years), and youths' health care clinician characteristics (eg, race, ethnicity, and sex) were evaluated using χ2 tests and propensity-score matching methods. Main Outcomes and Measures: Maternal reports on whether their youths' clinician listened carefully to the parent, explained things in a way the parent could understand, showed respect, and spent enough time with the patient. Results: There were 2515 US-born Latinx youths with linked maternal characteristics during the study period; 51.67% (95% CI, 48.87%-54.45%) of the youths were male, mean (SD) age was 8.48 (0.17) years (30.86% [95% CI, 28.39%-33.44%] were between ages 5 and 9 years), 61.53% (95% CI, 57.15%-65.74%) had public insurance coverage, and 39.89% (95% CI, 32.33%-47.89%) had mothers who were ethnically concordant with the youths' medical care clinician. We found that for youths with maternal-clinician ethnic concordance, the probabilities of reporting FCC were significantly higher than they would have been in the absence of concordance: that the medical care clinician listened carefully to the parent (average treatment effect on the treated [ATET], 5.44%; 95% CI, 2.14%-8.74%), explained things in a way the parent could understand (ATET, 4.82%; 95% CI, 1.60%-8.03%), showed respect for what the parent had to say (ATET, 5.51%; 95% CI, 2.58%-8.45%), and spent enough time with the patient (ATET, 5.28%; 95% CI, 1.68%-8.88%). Conclusions and Relevance: Given the increase of Latinx populations and the simultaneous shortage of underrepresented minority health care clinicians, the findings of this study suggest that increasing the number of clinicians from underrepresented minority backgrounds and ethnic-concordant parental-clinician relationships may help reduce disparities in receipt of medical home provision among US-born Latinx youths.

Posttraumatic Stress, Depression, and Sleep Among Young Survivors of Violence.

Survivors of violence often suffer psychological harm in addition to physical wounds. This study explored (1) the prevalence of Posttraumatic Stress Disorder (PTSD) symptoms, depression symptoms, and disordered sleep among young, violently injured, emergency department patients; and (2) how PTSD and depression symptoms are associated with sleep quality. Clinical scales for PTSD (PCL-5), depression (PHQ-8), and sleep (PROMIS®) were completed by 88 survivors of violent assault (gunshot, stabbing or assault) one month or less after presenting to an urban emergency department. High proportions of participants met criteria for prospective PTSD (59.1%), major depression (44.3%) or disordered sleep (34.1%), with 27.3% meeting criteria for all three conditions. Poorer sleep quality was correlated with higher levels of depression symptoms and PTSD symptoms. Survivors of violence experience symptoms that may further impair their sleep and behavioral health. Emergency providers should ask survivors about sleep/trauma symptoms and consider referral to trauma-informed behavioral health care.

Evaluating the informativeness of the Besag-York-Mollié CAR model.

The use of the conditional autoregressive framework proposed by Besag, York, and Mollié (1991; BYM) is ubiquitous in Bayesian disease mapping and spatial epidemiology. While it is understood that Bayesian inference is based on a combination of the information contained in the data and the information contributed by the model, quantifying the contribution of the model relative to the information in the data is often non-trivial. Here, we provide a measure of the contribution of the BYM framework by first considering the simple Poisson-gamma setting in which quantifying the prior's contribution is quite clear. We then propose a relationship between gamma and lognormal priors that we then extend to cover the framework proposed by BYM. Following a brief simulation study in which we illustrate the accuracy of our lognormal approximation of the gamma prior, we analyze a dataset comprised of county-level heart disease-related death data across the United States. In addition to demonstrating the potential for the BYM framework to correspond to a highly informative prior specification, we also illustrate the sensitivity of death rate estimates to changes in the informativeness of the BYM framework.

Association of Maternal Citizenship and State-Level Immigrant Policies With Health Insurance Coverage Among US-Born Latino Youths.

Importance: The association of state-level immigrant policies with uninsurance among Latino youths remains unknown. Objective: To assess the association of state-level immigrant integration and criminalization policies with health insurance coverage among US-born Latino youths by maternal citizenship. Design, Setting, and Participants: This cross-sectional study analyzed secondary data from the American Community Survey, January 1, 2016, to December 31, 2018, for US-born Latino youths (age, ≤17 years) and their mothers (age, 18-64 years) as well as state-level indicators of immigrant integration and criminalization policies (in all 50 states and the District of Columbia). Exposures: Immigrant integration and criminalization policies. Main Outcomes and Measures: The main outcome was maternal reports of youth uninsurance status at the time of the American Community Survey interview. Variation in youth uninsurance by maternal citizenship, state immigrant integration policy context, and state immigrant criminalization policy context were examined. All analyses were conducted with weighted survey data. Results: Of the 226 691 US-born Latino youths (115 431 [50.92%] male; mean [SD] age, 7.66 [4.92] years) included in the study, 36.64% (95% CI, 36.21%-36.92%) had noncitizen mothers. Overall, 7.09% (95% CI, 6.78%-7.41%) of noncitizen mothers reported that their youths were uninsured compared with 4.68% (95% CI, 4.49%-4.88%) of citizen mothers. Of uninsured youths who resided in states with a low level of immigrant integration policies, 9.10% (8.22%-10.06%) had noncitizen mothers and 4.75% (95% CI, 4.19%-5.37%) had citizen mothers; of uninsured youths who resided in states with high criminalization policies, 9.37% (95% CI, 8.90%-9.87%) had noncitizen mothers and 5.91% (95% CI, 5.64%-6.20%) had citizen mothers. In states with few immigrant integration policies, the probability of uninsurance among youths with noncitizen mothers was 3.3% (95% CI, 2.3%-4.4%) higher than that among youths with citizen mothers. Among youths with noncitizen mothers, the difference in the probability of uninsurance between those residing in states with a low level vs a high level of immigrant integration policies was 2.1% (95% CI, 0.6%-3.6%). Among youths residing in states with high levels of immigrant criminalization policies, those with noncitizen mothers had a 2.6% (95% CI, 1.9%-3.0%) higher probability of being uninsured compared with those whose mothers were citizens. Among youths with noncitizen mothers, the difference in the probability of uninsurance between those who resided in a state with a low level vs a state with a high level of immigrant criminalization policies was 1.7% (95% CI, 0.7%-2.7%). Conclusions and Relevance: The findings of this cross-sectional study suggest that among US-born Latino youths, disparities in uninsurance by maternal citizenship are associated with state-level immigrant integration and criminalization policies and that anti-immigrant policies may be associated with disparities in health care access for US-born Latino youths.

Association of maternal characteristics with latino youth health insurance disparities in the United States: a generalized structural equation modeling approach.

BACKGROUND: Disparities in access to care persist for Latino youth born in the United States (US). The association of maternal characteristics, such as maternal citizenship status and insurance coverage, on youth health insurance coverage is unclear and is important to examine given the recent sociopolitical shifts occurring in the US. METHODS: We analyzed pooled cross-sectional data from the 2010-2018 National Health Interview Survey to examine the association of Latina maternal citizenship status on maternal insurance coverage status and youth uninsurance among US-born Latino youth. Our study sample consisted of 15,912 US-born Latino youth (ages < 18) with linked mothers. Our outcome measures were maternal insurance coverage type and youth uninsurance and primary predictor was maternal citizenship status. Generalized structural equation modeling was used to examine the relationships between maternal characteristics (maternal citizenship, maternal insurance coverage status) and youth uninsurance. RESULTS: Overall, 7% of US-born Latino youth were uninsured. Just 6% of youth with US-born mothers were uninsured compared to almost 10% of those with noncitizen mothers. Over 18% of youth with uninsured mothers were uninsured compared to 2.2% among youth with mothers who had private insurance coverage. Compared to both US-born and naturalized citizen Latina mothers, noncitizen Latina mothers had 4.75 times the odds of reporting being uninsured. Once adjusted for predisposing, enabling, and need factors, maternal uninsurance was strongly associated with youth uninsurance and maternal citizenship was weakly associated with youth uninsurance among US-born Latino youth. CONCLUSION: Maternal citizenship was associated with both maternal uninsurance and youth uninsurance among US-born Latino youth. Federal- and state-level health policymaking should apply a two-generational approach to ensure that mothers of children are offered affordable health insurance coverage, regardless of their citizenship status, thus reducing uninsurance among US-born Latino youth.

Assessing the spatial heterogeneity in black-white differences in optimal cardiovascular health and the impact of individual- and neighborhood-level risk factors: The Multi-Ethnic Study of Atherosclerosis (MESA).

Racial disparities in cardiovascular health (CVH) continue to remain a public health concern in the United States. We use unique population-based data from the Multi-Ethnic Study of Atherosclerosis cohort to explore the black-white differences in optimal CVH. Utilizing geographically weighted regression methods, we assess the spatial heterogeneity in black-white differences in optimal CVH and the impact of both individual- and neighborhood-level risk factors. We found evidence of significant spatial heterogeneity in black-white differences that varied within and between the five sites. Initial models showed decreased odds of optimal CVH for blacks that ranged from 60% to 70% reduced odds - with noticeable variation of these decreased odds within each site. Adjusting for risk factors resulted in reductions in the black-white differences in optimal CVH. Further understanding of the reasons for spatial heterogeneities in black-white differences in nationally representative cohorts may provide important clues regarding the drivers of these differences.

Exploring the Spatial Patterning in Racial Differences in Cardiovascular Health Between Blacks and Whites Across the United States: The REGARDS Study.

Background Cardiovascular health (CVH) disparities between blacks and whites have persisted in the United States for some time, and although there have been remarkable improvements in addressing cardiovascular disease, it still remains the leading cause of death in the United States. In addition, well-documented disparities are unfortunately widening incidence gaps across certain regions of the United States. Our focus was on answering the following questions: (1) How much spatial heterogeneity exists in the racial differences in CVH between blacks and whites across this country? and (2) Is the spatial heterogeneity in the racial differences significantly explained by living in the Stroke Belt? Methods and Results To explore the spatial patterning in the racial differences in CVH between blacks and whites across the country, we used geographically weighted regression methods, which result in local estimates of the racial differences in CVH. Using data from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study, we found significant spatial patterning in these racial differences, even beyond the well-known Stroke Belt and Stroke Buckle. All of the estimated differences indicated blacks consistently having diminishing CVH compared with whites, where this difference was largely noted in pockets of the Stroke Belt and Stroke Buckle, in addition to moderate to large disparities noted in the Great Lakes region, portions of the Northeast, and along the West coast. Conclusions Efforts to improve CVH and ultimately reduce disparities between blacks and whites require culturally competent methods, with a strong focus on geography-based interventions and policies.

Density of Medical Marijuana Dispensaries and Current Marijuana Use among Young Adult Marijuana Users in Los Angeles.

Background: While tobacco and alcohol studies have focused on density of outlets as a determinant of consumption, research has begun examining the effects of medical marijuana (MM) dispensaries on marijuana use. Objectives: Examine the relationship between density of MM dispensaries and frequency of marijuana use among young adult medical marijuana patients (MMP) and nonpatient users (NPU). Methods: Young adult marijuana users (n = 329) aged 18- to 26-year old were sampled in Los Angeles in 2014-2015 and separated into MMP (n = 198) and NPU (n = 131). In 2014, 425 operational MM dispensaries were identified within the City of Los Angeles. Sequential multilevel Poisson random effect models examined density of MM dispensaries per square mile and 90 d marijuana use among MMP and NUP at the ZIP code level while controlling for demographic, behavioral, and community characteristics. Results: Density of MM dispensaries was not related to 90 d use of marijuana (days of use or hits per day) among either MMP or NPU. MMP reported significantly greater days of marijuana use in the past 90 d compared to NPU but no differences were found for hits per day. African-Americans reported significantly greater hits per day compared to whites. Hispanics reported significantly fewer hits per day compared to non-Hispanics. Conclusion: Concentration of MM dispensaries surrounding young adult marijuana users in Los Angeles was unrelated to days of marijuana use irrespective of having a MM recommendation or not. Rather, individual factors related to consumer choices and behaviors were more important in determining recent marijuana use among MMP and NPU.