Establishing the Relative Accuracy of Using City Directories as Proxies to Define and Reconstruct Historical Alcohol Environments.

OBJECTIVE: Research on alcohol environments has established that poorer and minoritized communities are frequently overburdened by off-premise outlets (e.g., liquor stores). These outlets have more associated harms, including increased alcohol consumption and crime rates. Little, if any, research has shown how these socio-spatial disparities in exposure have grown or shifted over time, and no studies have established a method for re-creating historical alcohol environments. METHOD: Our results suggest that in our study city of Flint, MI, disparities in the alcohol environment have narrowed since 1950. Although liquor stores are still more likely to be located in poorer and more heavily African American neighborhoods, the pattern has become insignificant over time. Furthermore, the number of alcohol outlets per capita has declined. Thus, although the city remains more overburdened with alcohol outlets than its suburbs, the disparity has shrunk. CONCLUSIONS: This work has implications for those working in alcohol prevention and policy, as well as in urban planning. Practitioners and researchers can use this method to model alcohol availability over time in their own communities, which helps better inform the discussion on disparities experienced in poor and minoritized neighborhoods.

Linking Historical Discriminatory Housing Patterns to the Contemporary Alcohol Environment.

Research on alcohol outlet density consistently shows greater disparities in exposure in disinvested communities. Likewise, structural racism via discriminatory housing practices has created many of the issues that beset contemporary disinvested neighborhoods. Little work, however, has examined the relationship between housing practices and alcohol outlet disparities. The central premise of our work is that these discriminatory and inequitable practices create distinctions in the alcohol environment, and that such disparities have implications for work on alcohol policy. Here we link alcohol outlet density with a spatial database examining redlining, blockbusting, and gentrification in Baltimore, Maryland, and Flint, Michigan (two cities with common experiences of urban disinvestment over the last 50 years). Standard measures are used to account for the impacts of neighborhood racial, socioeconomic, and housing composition in a multilevel model. Our findings highlight that gentrification and redlining are strongly associated with alcohol outlet density, while blockbusting is not. Gentrification and redlining also frequently co-occur in inner-urban areas, while the more suburban phenomenon of blockbusting rarely overlaps with either. These findings further contextualize nascent work on structural racism in housing that illustrates important disparities along the lines of these distinct practices. Future work should consider how legacy impacts of discriminatory housing patterns impact our communities today.

Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan.

COVID-19's rapid onset left many public health entities scrambling. But establishing community-academic partnerships to digest data and create advocacy steps offers an opportunity to link research to action. Here we document disparities in COVID-19 death uncovered during a collaboration between a health department and university research center. We geocoded COVID-19 deaths in Genesee County, Michigan, to model clusters during two waves in spring and fall 2020. We then aggregated these deaths to census block groups, where group-based trajectory modeling identified latent patterns of change and continuity. Linking with socioeconomic data, we identified the most affected communities. We discovered a geographic and racial gap in COVID-19 deaths during the first wave, largely eliminated during the second. Our partnership generated added and immediate value for community partners, including around prevention, testing, treatment, and vaccination. Our identification of the aforementioned racial disparity helped our community nearly eliminate disparities during the second wave.

Validating a geospatial healthfulness index with self-reported chronic disease and health outcomes.

Leveraging community engagement from past research may yield frameworks on which to build new inquiries. We previously integrated community voice into the development of a healthfulness index to increase awareness of social determinants of health in the built environment and inform deployment of public health interventions in the Flint (Michigan, USA) Center for Health Equity Solutions. Here we combine the healthfulness index with self-reported chronic disease and health outcomes (n = 12,279) from a community-based healthcare entity, the Genesee Health Plan. The healthfulness index purports to predict how health-promoting a neighborhood is based on many spatially varying characteristics; by linking our health plan data to this index, we validate the effectiveness of the healthfulness index. After geocoding all enrollees and joining their healthfulness scores, we conducted a series of logistic regressions to compare the relationship between self-reported outcomes and healthfulness. Matching the two intervention projects of our center (revolving around healthy eating & physical activity in project 1 and mental health sustainment & substance use prevention in project 2), our analyses also focused on classes of outcomes related to a) cardiovascular disease and b) mental health. In only select cases, higher (better) healthfulness scores from each project were independently associated with better cardiovascular and mental health outcomes, controlling for age, race, and sex. Generally, however, healthfulness did not add predictive strength to the association between health and sociodemographic covariates. Even so, the use of composite healthfulness indices to describe the health-promoting or degrading qualities of a neighborhood could be valuable in identifying differences in health outcomes. Future researchers could further explore healthcare claims datasets to increase understanding of the links between healthfulness and health outcomes. This and future work will be valuable in advocacy toward additional healthfulness indices to aid other communities in enriching understanding between the built environment and health.

"There's no money in community dissemination": A mixed methods analysis of researcher dissemination-as-usual.

Background: The field of dissemination and implementation science has the potential to narrow the translational research-to-practice gap and improve the use of evidence-based practices (EBPs) within community-based settings. Yet, foundational research related to dissemination efforts, such as understanding researcher attitudes, practices, and the determinants to sharing research findings, is lacking within extant literature. Methods: A sequential explanatory (QUANqual) mixed methods design was used to examine 85 academic researchers' perspectives and self-reported dissemination methods used to share research outcomes with community stakeholders to better understand researcher's usual dissemination practices (referred to as dissemination-as-usual). Quantitative surveys collected researcher demographic data, attitudes toward dissemination efforts, and dissemination strategy use. Results: Multiple linear regression examined predictors of the quantity of dissemination strategies utilized by researchers, finding that years since earning their degree, time spent disseminating, and the number of reasons for engaging in dissemination efforts predicted greater numbers of dissemination strategies utilized by researchers. Individual, semi-structured interviews with a subset of researchers (n = 18) expanded upon quantitative findings, identifying barriers and facilitators to their dissemination efforts. Data strands were integrated using a joint display, and the Dissemination of Research model guided data interpretation. More established researchers experienced fewer barriers and more facilitators to support their use of a variety of dissemination strategies to share findings with community stakeholders. However, researchers reported needing specific training, institutional support, and/or dedicated time to plan and enact dissemination strategies. Conclusion: The necessary first step in research translation is the dissemination of research evidence, and understanding dissemination-as-usual can identify areas of need to advance translational science.

Trajectory Modeling of Spatio-Temporal Trends in COVID-19 Incidence in Flint and Genesee County, Michigan.

PURPOSE: The establishment of community-academic partnerships to digest data and create actionable policy and advocacy steps is of continuing importance. In this paper, we document COVID-19 racial and geographic disparities uncovered via a collaboration between a local health department and university research center. METHODS: We leverage individual level data for all COVID-19 cases aggregated to the census block group level, where group-based trajectory modeling was employed to identify latent patterns of change and continuity in COVID-19 diagnoses. RESULTS: Linking with socioeconomic data from the census, we identified the types of communities most heavily affected by each of Michigan's two waves (in spring and fall of 2020). This includes a geographic and racial gap in COVID-19 cases during the first wave, which is largely eliminated during the second wave. CONCLUSIONS: Our work has been extremely valuable for community partners, informing community-level response toward testing, treatment, and vaccination. In particular, identifying and conducting advocacy on the sizeable racial disparity in COVID-19 cases during the first wave in spring 2020 helped our community nearly eliminate disparities throughout the second wave in fall 2020.

Linking the Flint Food Store Survey: Is Objective or Perceived Access to Healthy Foods Associated with Glycemic Control in Patients with Type 2 Diabetes?

Type 2 diabetes mellitus (DM-2) remains a significant public health concern, particularly in low-income neighborhoods where healthy foods may be scarcer. Despite the well-known relationship between diet and diabetes, little evidence exists on the connections among the objectively measured community and consumer food environment, perception of food access, and diabetes management or outcomes. This cross-sectional, ecological study represents the first example of combining a GIS-based, objectively measured food store audit considering quality, variety, and price of foods in stores with a clinical survey of patients with DM-2 (n = 126). In this way, we offer evidence on the relationship between healthy food access-measured more robustly than proximity to or density of certain store types-and diabetes management knowledge, medication adherence, and glycemic control. Better glycemic control was not correlated with better overall food store score, meaning that people in neighborhoods with better access to healthy foods are not necessarily more likely to manage their diabetes. While perceived healthy food access was not correlated with glycemic control, it was strongly correlated with objective healthy food access at shorter distances from home. These results have great importance both for clinical understanding of the persistence of poor diabetes management outcomes and for the understanding of the influence of the food environment on health behaviors.

Is a school's neighborhood physical disorder related to its academic outcomes?

BACKGROUND: Neighborhood environment for student residences has been linked to differences in academic outcomes. However, school neighborhood has not been studied as a potential additional environmental factor in academic outcomes. OBJECTIVE: The goal of this study was to explore the association between school neighborhood disorder and academic outcomes. METHODS: School neighborhood physical disorder data were paired with school academic achievement and attendance data. Using regression analyses, we examined whether academic achievement and attendance were predicted using NIfETy neighborhood physical disorder scores for the 21 schools within the boundaries of Flint. RESULTS: Neighborhood physical disorder was significantly negatively associated with mathematics scores (ß=-7.71707, p=0.0430425), but not with English Language Arts (ELA) scores (ß=-4.35, p=0.13). We found a significant curvilinear relationship between neighborhood physical disorder and attendance. CONCLUSIONS: This study supplements existing literature by focusing on neighborhood physical disorder at the school. We found evidence that school neighborhood may impact academic achievement. These findings complement previous research showing that neighborhood of residence factors, such as structural disadvantage, impact school performance. Students exposed to economically disadvantaged neighborhoods at school, regardless of where they live, may have poorer academic skills.

Discrepancies in Local, State, and National Alcohol Outlet Listings: Implications for Research and Interventions.

BACKGROUND: The availability of local, state, and national data on alcohol outlet density have important implications for policies and interventions aiming to reduce alcohol-related problems. High-quality data on locations of alcohol outlets is important to accurately inform community interventions and public health initiatives, but such data is often not maintained, readily available, or of sufficient quality. Objectives: This study aims to examine the discrepancies between alcohol outlet databases and how neighborhood characteristics (i.e. income, majority racial population, urbanicity) are associated with the discrepancies between databases. Methods: Data was collected from national (n = 1), local (n = 2), and state databases (n = 3). Negative binomial regression models were used to assess discrepancies in alcohol outlet count at the ZIP code level based on the data source. Results: The average density of alcohol outlets (per 1000 residents) ranged from 0.71 to 2.17 in Maryland, 1.65 to 5.17 in Wisconsin, and 1.09 to 1.22 in Oregon based on different sources of data. Findings suggest high income areas (>200% poverty level) have fewer discrepancies (IR = 0.775, p < 0.01), low income areas (below poverty level) have greater discrepancies (IR = 4.990, p < 0.01), and urban areas tend to have fewer discrepancies (IR = 0.378, p < 0.01) between datasets. Conclusion: Interventions and policies depend on valid and reliable data; researchers, policymakers, and local agencies need to collaborate to develop methods to maintain accurate and accessible data.

Reactivity of salivary uric acid in response to social evaluative stress in African Americans.

High uric acid (UA) is associated with hypertension and cardiovascular disease (CVD), both of which occur disproportionately among African Americans. High UA also predicts greater blood pressure reactivity responses to acute social stress. However, whether UA itself shows reactivity in response to stress is unknown. We evaluated salivary uric acid (sUA) and blood pressure reactivity in response to acute social stress. Healthy African Americans (N = 103; 32 % male; M age = 31.36 years), completed the Trier Social Stress Test. sUA and blood pressure measurements were taken before, during and after the stressor task. sUA showed significant reactivity and recovery, especially among older African Americans. Total sUA activation was also associated with systolic and diastolic blood pressure total activation. Findings illuminate that acute stress may be a way in which UA is implicated in hypertension and CVD, suggesting a critical need to explore UA reactivity as a novel parameter of the acute stress response.

The population randomization observation process (PROP) assessment method: using systematic habitation observations of street segments to establish household-level epidemiologic population samples.

BACKGROUND: Identifying and intervening on health disparities requires representative community public health data. For cities with high vacancy and transient populations, traditional methods of population estimation for refining random samples are not feasible. The aim of this project was to develop a novel method for systematic observations to establish community epidemiologic samples. RESULTS: We devised a four-step population randomization observation process for Flint, Michigan, USA: (1) Use recent total population data for community areas (i.e., neighborhoods) to establish the proportional sample size for each area, (2) Randomly select street segments of each community area, (3) Deploy raters to conduct observations about habitation for each randomly selected segment, and (4) Complete observations for second and third street segments, depending on vacancy levels. We implemented this systematic observation process on 400 randomly selected street segments. Of these, 130 (32.5%) required assessment of secondary segments due to high vacancy. Among the 130 primary segments, 28 (21.5%) required assessment of tertiary (or more) segments. For 71.5% of the 400 primary street segments, there was consensus among raters on whether the dwelling inhabited or uninhabited. CONCLUSION: Houses observed with this method could have easily been considered uninhabited via other methods. This could cause residents of ambiguous dwellings (likely to be the most marginalized residents with highest levels of unmet health needs) to be underrepresented in the resultant sample.