The Association of Alcohol Outlet Density with Alcohol Intake: The Multiethnic Cohort.

OBJECTIVE: Neighborhood characteristics have been shown to influence lifestyle behaviors. Here we characterized alcohol outlet density in Los Angeles County, California, and Hawaii and assessed the association of alcohol outlet density with self-reported alcohol intake in the Multiethnic Cohort. METHOD: Participants (n=178,977) had their addresses geocoded, at cohort entry (1993-1996), and appended to block group-level alcohol outlet densities (on- and off-premises). Multinomial logistic regression was performed to assess the association between self-reported alcohol intake and on- and off-premise alcohol outlet densities by each state. Stratified analysis was conducted by sex, race, and ethnicity. RESULTS: Overall, we did not find associations between alcohol outlet density and self-reported alcohol intake in Los Angeles County, but we found that on-premise alcohol outlets were associated with 59% (OR=1.59, 95% CI:1.29,1.96) increased odds of consuming >2 drinks per day in Hawaii. Women living in neighborhoods with high density of on-premise alcohol outlets (Los Angeles County OR=1.15, 95% CI: 0.95,1.40) and (Hawaii OR=2.07, 95% CI: 1.43,3.01) had an increased odds of >2 drinks per day. CONCLUSION: This study suggests that neighborhood factors are associated with individual level behaviors and that there may be a need for multilevel interventions.

Asian American Enclaves and Healthcare Accessibility: An Ecologic Study Across Five States.

INTRODUCTION: Access to primary care has been a long-standing priority for improving population health. Asian Americans, who often settle in ethnic enclaves, have been found to underutilize health care. Understanding geographic primary care accessibility within Asian American enclaves can help to ensure the long-term health of this fast-growing population. METHODS: U.S. Census data from five states (California, Florida, New Jersey, New York, and Texas) were used to develop and describe census-tract level measures of Asian American enclaves and social and built environment characteristics for years 2000 and 2010. The 2-step floating catchment area method was applied to National Provider Identifier data to develop a tract-level measure of geographic primary care accessibility. Analyses were conducted in 2022-2023, and associations between enclaves (versus nonenclaves) and geographic primary care accessibility were evaluated using multivariable Poisson regression with robust variance estimation, adjusting for potential area-level confounders. RESULTS: Of 24,482 census tracts, 26.1% were classified as Asian American enclaves. Asian American enclaves were more likely to be metropolitan and have less poverty, lower crime, and lower proportions of uninsured individuals than nonenclaves. Asian American enclaves had higher primary care accessibility than nonenclaves (adjusted prevalence ratio=1.23, 95% CI=1.17, 1.29). CONCLUSIONS: Asian American enclaves in five of the most diverse and populous states in the U.S. had fewer markers of disadvantage and greater geographic primary care accessibility. This study contributes to the growing body of research elucidating the constellation of social and built environment features within Asian American enclaves and provides evidence of health-promoting characteristics of these neighborhoods.

Neighborhood-level COVID vaccination and booster disparities: A population-level analysis across California.

Objectives: To describe vaccine and booster uptake by neighborhood-level factors in California. Methods: We examined trends in COVID-19 vaccination up to September 21, 2021, and boosters up to March 29, 2022 using data from the California Department of Public Health. Quasi-Poisson regression was used to model the association between neighborhood-level factors and fully vaccinated and boosted among ZIP codes. Sub-analyses on booster rates were compared among the 10 census regions. Results: In a minimally adjusted model, a higher proportion of Black residents was associated with lower vaccination (HR = 0.97; 95%CI: 0.96-0.98). However, in a fully adjusted model, proportion of Black, Hispanic/Latinx, and Asian residents were associated with higher vaccination rates (HR = 1.02; 95%CI: 1.01-1.03 for all). The strongest predictor of low vaccine coverage was disability (HR = 0.89; 95%CI: 0.86-0.91). Similar trends persisted for booster doses. Factors associated with booster coverage varied by region. Conclusions: Examining neighborhood-level factors associated with COVID-19 vaccination and booster rates uncovered significant variation within the large and geographically and demographically diverse state of California. Equity-based approaches to vaccination must ensure a robust consideration of multiple social determinants of health.

Probabilistic risk assessment of residential exposure to metal(loid)s in a mining impacted community.

The "Gold Country" region of California is impacted by legacy and active gold mines. Concomitantly, Gold Country has an increased rate of female breast cancer relative to the state average. Using community-based participatory research methods, 40 participants completed surveys and collected a total of 354 water, soil, home-grown foods, and dust samples from their homes, which we compared to state, federal, and international contamination standards for arsenic, cadmium, and lead. All soil samples exceeded U.S. EPA and California EPA soil standards for arsenic. When comparing other media to state, federal and international standards for arsenic, cadmium, and lead, 15 additional exceedances for indoor/outdoor dust, drinking water, and/or vegetable were documented. A probabilistic risk assessment was conducted to determine an adult female's exposure to arsenic, cadmium, and lead and estimated risk. Arsenic exposure, due largely to water (63.5 %) and homegrown food (33.3 %), presents carcinogenic risks in excess of the EPA recommended upper limit for contaminated sites (1 × 10-4) in 12.5 % of scenarios, and exceeds a risk level of 1 × 10-6 in 98.0 % of cases. Cadmium exposure results mainly from homegrown food consumption (83.7 %), and lead exposure results from a broader range of sources. This research indicates that rural areas in Gold Country face environmental exposures different than in urban areas. Exposure to arsenic in the female population of Gold Country may be driven by consumption of home-grown foods and water, and exposure to cadmium is driven by home-grown food intake. Since mining sites are of concern internationally, this risk assessment process and associated findings are significant and can be used to inform and tailor public health interventions. The weight of the evidence suggests that the arsenic exposure identified in this study could contribute to increases in the cancer rate among those living in Gold Country, California.

Geographic mobility and its impact on sexual health and ongoing HIV transmission among migrant latinx men who have sex with men.

An understudied social process that may determine variable HIV risk, testing, and linkage to care is geographic mobility, including immigration as well as short-term mobility, especially among sexual minority populations. We aimed to assess how geographic mobility over the lifecourse between Latin America and the U.S., and within the U.S., was linked to sexual risk and health behaviors among Latinx migrant men who have sex with men (MSM) in San Bernardino County, California. Qualitative analysis of 16 semi-structured interviews revealed four major domains of influence on participants' sexual risk behaviors. At the micro level, these included social environment/interpersonal factors (e.g., family and peer support) and geographic factors and pathways (e.g., migration journey to the U.S.). At the macro level data centered on cultural factors (e.g., gender norms in home country) and structural factors (e.g., HIV healthcare). Our results can illuminate and promote effective health policies and HIV reduction efforts for Latinx migrant MSM in metro areas.

Neighborhood Factors Associated with COVID-19 Cases in California.

BACKGROUND: There is a need to assess neighborhood-level factors driving COVID-19 disparities across racial and ethnic groups. OBJECTIVE: To use census tract-level data to investigate neighborhood-level factors contributing to racial and ethnic group-specific COVID-19 case rates in California. DESIGN: Quasi-Poisson generalized linear models were used to identify neighborhood-level factors associated with COVID-19 cases. In separate sequential models for Hispanic, Black, and Asian, we characterized the associations between neighborhood factors on neighborhood COVID-19 cases. Subanalyses were conducted on neighborhoods with majority Hispanic, Black, and Asian residents to identify factors that might be unique to these neighborhoods. Geographically weighted regression using a quasi-Poisson model was conducted to identify regional differences. MAIN MEASURES: All COVID-19 cases and tests reported through January 31, 2021, to the California Department of Public Health. Neighborhood-level data from census tracts were obtained from American Community Survey 5-year estimates (2015-2019), United States Census (2010), and United States Department of Housing and Urban Development. KEY RESULTS: The neighborhood factors associated with COVID-19 case rate were racial and ethnic composition, age, limited English proficiency (LEP), income, household size, and population density. LEP had the largest influence on the positive association between proportion of Hispanic residents and COVID-19 cases (- 2.1% change). This was also true for proportion of Asian residents (- 1.8% change), but not for the proportion of Black residents (- 0.1% change). The influence of LEP was strongest in areas of the Bay Area, Los Angeles, and San Diego. CONCLUSION: Neighborhood-level contextual drivers of COVID-19 burden differ across racial and ethnic groups.

Geographic Mobility, Place Attachment, and the Changing Geography of Sex among African American and Latinx MSM Who Use Substances in Los Angeles.

The places that people go and interact with others, along with the characteristics of those places, determine degrees of sexual health risk and concomitant prevention opportunities for gay, bisexual, and other men who have sex with men (MSM). The objective of this paper is to use syndemic theory to guide analyses of 20 in-depth interviews with African American and Hispanic/Latinx MSM living in Los Angeles. We describe the places in which African American and Latinx MSM interviewees live and socialize, and how these places influence sexual behavior, drug use, and access to health care. We find common spatial patterns in mobility, incongruence in residential and sexual places, and differing geographic patterns of sex by men who use geo-social hook-up apps. Significant instability in home life and varying forms of mobility and risk-taking were a response to cumulative disadvantage and intersecting structural forces including poverty, racism, and homophobia. Our results strongly suggest that geographic mobility is a syndemic factor for HIV risk among MSM in Los Angeles, as mobility amplified negative impacts of other syndemic factors. Innovative place-interventions to reduce HIV incidence and disparities in HIV need to acknowledge the synergistic factors that drive higher HIV incidence among AA and Latinx MSM.

Performance of a Low-Cost Sensor Community Air Monitoring Network in Imperial County, CA.

Air monitoring networks developed by communities have potential to reduce exposures and affect environmental health policy, yet there have been few performance evaluations of networks of these sensors in the field. We developed a network of over 40 air sensors in Imperial County, CA, which is delivering real-time data to local communities on levels of particulate matter. We report here on the performance of the Network to date by comparing the low-cost sensor readings to regulatory monitors for 4 years of operation (2015-2018) on a network-wide basis. Annual mean levels of PM10 did not differ statistically from regulatory annual means, but did for PM2.5 for two out of the 4 years. R2s from ordinary least square regression results ranged from 0.16 to 0.67 for PM10, and increased each year of operation. Sensor variability was higher among the Network monitors than the regulatory monitors. The Network identified a larger number of pollution episodes and identified under-reporting by the regulatory monitors. The participatory approach of the project resulted in increased engagement from local and state agencies and increased local knowledge about air quality, data interpretation, and health impacts. Community air monitoring networks have the potential to provide real-time reliable data to local populations.

Community-Engaged Air Monitoring to Build Resilience Near the US-Mexico Border.

Initiated in response to community concerns about high levels of air pollution and asthma, the Imperial County Community Air Monitoring Project was conducted as a collaboration between a community-based organization, a non-governmental environmental health program, and academic researchers. This community-engaged research project aimed to produce real-time, community-level air quality information through the establishment of a community air monitoring network (CAMN) of 40 low-cost particulate matter (PM) monitors in Imperial County, California. Methods used to involve the community partner organization and residents in the development, operation, and use of the CAMN included the following: (1) establishing equitable partnerships among the project collaborators; (2) forming a community steering committee to guide project activities; (3) engaging residents in data collection to determine monitor sites; (4) providing hands-on training to assemble and operate the air monitors; (5) conducting focus groups to guide display and dissemination of monitoring data; and (6) conducting trainings on community action planning. This robust community engagement in the project resulted in increased awareness, knowledge, capacity, infrastructure, and influence for the community partner organization and among community participants. Even after the conclusion of the original research grant funding for this project, the CAMN continues to be operated and sustained by the community partner, serving as a community resource used by residents, schools, researchers, and others to better understand and address air pollution and its impacts on community health, while strengthening the ability of the community to prepare for, respond to, and recover from harmful air pollution.

Next-Generation Community Air Quality Sensors for Identifying Air Pollution Episodes.

Conventional regulatory air quality monitoring sites tend to be sparsely located. The availability of lower-cost air pollution sensors, however, allows for their use in spatially dense community monitoring networks, which can be operated by various stakeholders, including concerned residents, organizations, academics, or government agencies. Networks of many community monitors have the potential to fill the spatial gaps between existing government-operated monitoring sites. One potential benefit of finer scale monitoring might be the ability to discern elevated air pollution episodes in locations that have not been identified by government-operated monitoring sites, which might improve public health warnings for populations sensitive to high levels of air pollution. In the Imperial Air study, a large network of low-cost particle monitors was deployed in the Imperial Valley in Southeastern California. Data from the new monitors is validated against regulatory air monitoring. Neighborhood-level air pollution episodes, which are defined as periods in which the PM2.5 (airborne particles with sizes less than 2.5 µm in diameter) hourly average concentration is equal to or greater than 35 µg m-3, are identified and corroborate with other sites in the network and against the small number of government monitors in the region. During the period from October 2016 to February 2017, a total of 116 episodes were identified among six government monitors in the study region; however, more than 10 times as many episodes are identified among the 38 community air monitors. Of the 1426 episodes identified by the community sensors, 723 (51%) were not observed by the government monitors. These findings suggest that the dense network of community air monitors could be useful for addressing current limitations in the spatial coverage of government air monitoring to provide real-time warnings of high pollution episodes to vulnerable populations.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network.

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

Traffic-Related Air Pollution and All-Cause Mortality during Tuberculosis Treatment in California.

BACKGROUND: Ambient air pollution and tuberculosis (TB) have an impact on public health worldwide, yet associations between the two remain uncertain. OBJECTIVE: We determined the impact of residential traffic on mortality during treatment of active TB. METHODS: From 2000-2012, we enrolled 32,875 patients in California with active TB and followed them throughout treatment. We obtained patient data from the California Tuberculosis Registry and calculated traffic volumes and traffic densities in 100- to 400-m radius buffers around residential addresses. We used Cox models to determine mortality hazard ratios, controlling for demographic, socioeconomic, and clinical potential confounders. We categorized traffic exposures as quintiles and determined trends using Wald tests. RESULTS: Participants contributed 22,576 person-years at risk. There were 2,305 deaths during treatment for a crude mortality rate of 1,021 deaths per 10,000 person-years. Traffic volumes and traffic densities in all buffers around patient residences were associated with increased mortality during TB treatment, although the findings were not statistically significant in all buffers. As the buffer size decreased, fifth-quintile mortality hazards increased, and trends across quintiles of traffic exposure became more statistically significant. Increasing quintiles of nearest-road traffic volumes in the 100-m buffer were associated with 3%, 14%, 19%, and 28% increased risk of death during TB treatment [first quintile, referent; second quintile hazard ratio (HR)=1.03 [95% confidence interval (CI): 0.86, 1.25]; third quintile HR=1.14 (95% CI: 0.95, 1.37); fourth quintile HR=1.19 (95% CI: 0.99, 1.43); fifth quintile HR=1.28 (95% CI: 1.07, 1.53), respectively; p-trend=0.002]. CONCLUSIONS: Residential proximity to road traffic volumes and traffic density were associated with increased all-cause mortality in patients undergoing treatment for active tuberculosis even after adjusting for multiple demographic, socioeconomic, and clinical factors, suggesting that TB patients are susceptible to the adverse health effects of traffic-related air pollution. https://doi.org/10.1289/EHP1699.

The Imperial County Community Air Monitoring Network: A Model for Community-based Environmental Monitoring for Public Health Action.

SUMMARY: The Imperial County Community Air Monitoring Network (the Network) is a collaborative group of community, academic, nongovernmental, and government partners designed to fill the need for more detailed data on particulate matter in an area that often exceeds air quality standards. The Network employs a community-based environmental monitoring process in which the community and researchers have specific, well-defined roles as part of an equitable partnership that also includes shared decision-making to determine study direction, plan research protocols, and conduct project activities. The Network is currently producing real-time particulate matter data from 40 low-cost sensors throughout Imperial County, one of the largest community-based air networks in the United States. Establishment of a community-led air network involves engaging community members to be citizen-scientists in the monitoring, siting, and data collection process. Attention to technical issues regarding instrument calibration and validation and electronic transfer and storage of data is also essential. Finally, continued community health improvements will be predicated on facilitating community ownership and sustainability of the network after research funds have been expended. https://doi.org/10.1289/EHP1772

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA.

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM2.5 and PM10 (particulate matter with aerodynamic diameters <2.5 and <10 µm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R2 for converted hourly averaged Dylos mass measurements versus a PM2.5 BAM was 0.79 and that versus a PM10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R2 = 0.35-0.81). IMPLICATIONS: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.

Development of a Web-based tool to collect and display water system customer service areas for public health action.

CONTEXT: Significant illness is associated with biological contaminants in drinking water, but little is known about health effects from low levels of chemical contamination in drinking water. To examine these effects in epidemiological studies, the sources of drinking water of study populations need to be known. OBJECTIVE: The California Environmental Health Tracking Program developed an online application that would collect data on the geographic location of public water system (PWS) customer service areas in California, which then could be linked to demographic and drinking water quality data. DESIGN: We deployed the Water Boundary Tool (WBT), a Web-based geospatial crowdsourcing application that can manage customer service boundary data for each PWS in California and can track changes over time. We also conducted a needs assessment for expansion to other states. SETTING/PARTICIPANTS: The WBT was designed for water system operators, local and state regulatory agencies, and government entities. RESULTS: Since its public launch in 2012, the WBT has collected service area boundaries for about 2300 individual PWS, serving more than 90% of the California population. Results of the needs assessment suggest interest and utility for deploying such a tool among states lacking statewide PWS service area boundary data. CONCLUSIONS: Although the WBT data set is incomplete, it has already been used for a variety of applications, including fulfilling legislatively mandated reporting requirements and linking customer service areas to drinking water quality data to better understand local water quality issues. Development of this tool holds promise to assist with outbreak investigations and prevention, environmental health monitoring, and emergency preparedness and response.