Добірка наукової літератури з теми "Dorchester / Neighborhoods"

Abstract Background Based on national recommendations,1 Beth Israel Lahey Health (BILH) in Eastern Massachusetts (MA) prioritized vulnerable communities in our distribution of COVID-19 vaccines. We hypothesized that creating prioritized access to appointments for patients in these communities would increase the likelihood vaccination. Methods The BILH health system sent vaccine invitations first to patients of two clinics in vulnerable neighborhoods in Boston (Wave 1), followed by other patients from vulnerable communities (Wave 2) up to 1 day later, and then by all other patients (Wave 3) after up to 1 more day later. To identify whether early access/prioritization increased the likelihood of receipt of vaccine at any site or a vaccine at a BILH clinic, we compared patients in Wave 1 in a single community with high cumulative incidence of COVID-19 (Dorchester) to patients in Wave 2 during a period of limited vaccine access, 1/27/21-2/24/21. Each wave was modeled using logistic regression, adjusted for language and race. By taking the difference between these two differences, we are left with the impact of early vaccination invitation in Wave 1 for a subset of our most vulnerable patients (termed difference-in-differences; Stata SE 16.0). Results In our study of Waves 1 and 2, we offered vaccinations to 24,410 patients. Of those, 6,712 (27.5%) scheduled the vaccine at BILH (Table 1). Patients in Wave 1 were much more likely to be vaccinated at BILH than patients in Wave 2. Patients offered the vaccine in Wave 1 and living in Dorchester were 1.7 percentage points more likely to be vaccinated at all (p=0.445) and 9.4 percentage points more likely to be vaccinated at BILH than another site in MA (p-value = 0.001), relative to patients living outside of Dorchester and offered the vaccine in Wave 2 (Table 2). The coefficient of interest is on Wave1*Dorchester, 0.094. This indicates that residents of Dorchester who were offered the vaccine in Wave 1 were 9.4 percentage points more likely to receive the vaccine at BILH, given that they were vaccinated, relative to patients living outside of Dorchester and offered the vaccine in Wave 2. Conclusion Patients residing in an urban community given prioritized access to vaccination had a higher likelihood of vaccination at our health system, given that they were vaccinated, than patients in other urban communities without prioritized access. We provide an example of a successful effort to move towards equity in access to COVID-19- vaccines, in contrast to larger national trends.2,3 Health systems can use a prioritization approach to improve vaccination equity. Disclosures All Authors: No reported disclosures

Background People from underserved communities such as those from lower socioeconomic positions or racial and ethnic minority groups are often disproportionately targeted by the tobacco industry, through the relatively high levels of tobacco retail outlets (TROs) located in their neighborhood or protobacco marketing and promotional strategies. It is difficult to capture the smoking behaviors of individuals in actual locations as well as the extent of exposure to tobacco promotional efforts. With the high ownership of smartphones in the United States—when used alongside data sources on TRO locations—apps could potentially improve tobacco control efforts. Health apps could be used to assess individual-level exposure to tobacco marketing, particularly in relation to the locations of TROs as well as locations where they were most likely to smoke. To date, it remains unclear how health apps could be used practically by health promotion organizations to better reach underserved communities in their tobacco control efforts. Objective This study aimed to demonstrate how smartphone apps could augment existing data on locations of TROs within underserved communities in Massachusetts and Texas to help inform tobacco control efforts. Methods Data for this study were collected from 2 sources: (1) geolocations of TROs from the North American Industry Classification System 2016 and (2) 95 participants (aged 18 to 34 years) from underserved communities who resided in Massachusetts and Texas and took part in an 8-week study using location tracking on their smartphones. We analyzed the data using spatial autocorrelation, optimized hot spot analysis, and fitted power-law distribution to identify the TROs that attracted the most human traffic using mobility data. Results Participants reported encountering protobacco messages mostly from store signs and displays and antitobacco messages predominantly through television. In Massachusetts, clusters of TROs (Dorchester Center and Jamaica Plain) and reported smoking behaviors (Dorchester Center, Roxbury Crossing, Lawrence) were found in economically disadvantaged neighborhoods. Despite the widespread distribution of TROs throughout the communities, participants overwhelmingly visited a relatively small number of TROs in Roxbury and Methuen. In Texas, clusters of TROs (Spring, Jersey Village, Bunker Hill Village, Sugar Land, and Missouri City) were found primarily in Houston, whereas clusters of reported smoking behaviors were concentrated in West University Place, Aldine, Jersey Village, Spring, and Baytown. Conclusions Smartphone apps could be used to pair geolocation data with self-reported smoking behavior in order to gain a better understanding of how tobacco product marketing and promotion influence smoking behavior within vulnerable communities. Public health officials could take advantage of smartphone data collection capabilities to implement targeted tobacco control efforts in these strategic locations to reach underserved communities in their built environment.

Abstract Background. Inequitable access to health-harming substances in the built environment can create and exacerbate race and SES-based disparities in cancer incidence and mortality. Availability and density of tobacco and alcohol outlets is associated with increased experimentation, initiation, and regular use of alcohol and tobacco products. Prior studies examining the sale of tobacco and alcohol indicate that these outlets tend to be concentrated in communities of color and low-income areas. Massachusetts has highlighted environmental justice (EJ), one’s right to be protected from hazards and live in clean, health-promoting environments, as a priority issue and identified block group populations who are at most risk of environmental burdens. The objective of this study was to (a) examine the distribution of tobacco and alcohol outlets in environmental justice block groups in Boston, and (b) compare outlet density in more deprived neighborhoods to more privileged neighborhoods. Methods. Publicly available licensing lists for tobacco and alcohol retailers with geocoded data were obtained from the City of Boston’s open data hub. Lists were de-duplicated so that retailers that sell both tobacco and alcohol products were only represented once. The environmental justice block group layer (2020) was downloaded from Mass.gov. EJ block groups meet one or more of the following criteria: ‘high minority’ (>40% non-white population), ‘low-income’, or ‘high English isolation.’ ArcGIS Pro software was used to spatially join retailer data to Boston block groups and calculate tobacco and alcohol outlet density (the number of retailers per 1,000 people). Sociodemographic and cancer mortality data from the Health of Boston Report was used to classify neighborhoods as ‘more privileged’ (Back Bay, Beacon Hill, North End, West End) or ‘more deprived’ (Dorchester, Hyde Park, Mattapan, Roslindale, Roxbury). Results. Of the 560 Boston block groups analyzed, 458 (81.8%) were considered environmental justice block groups with 60% of EJ block groups classified as ‘high minority’. There were 931 retailers that sell tobacco or alcohol products for off-premises consumption in Boston, with 86% of these retailers (n=811) located in EJ block groups. On average, tobacco and alcohol outlet density was greater in EJ block groups compared to non-EJ block groups (2.09 vs 1.25 retailers per 1,000 residents). Nearly half (48%) of environmental justice block groups in Boston are located in the most deprived neighborhoods compared to only 3.7% in the most privileged neighborhoods. Tobacco outlet density is significantly higher in deprived neighborhoods compared to privileged neighborhoods (1.25 vs 0.98, p < 0.01). However, alcohol density is lower in more deprived block groups compared to more privileged ones (0.35 vs 0.74, p < 0.01). Conclusion. Environmental justice mapping can be used as a tool to identify areas where cancer prevention efforts may be enhanced by modifying the built environment to reduce clusters of alcohol and tobacco outlets. Citation Format: Lindsay Kephart. An examination of tobacco and alcohol outlet density in Boston to identify priority areas for cancer prevention efforts using environmental justice mapping [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR003.

This is the second of two chapters (Chapters 6 and 7) that analyze the Dartmouth-based fieldwork data in eastern Massachusetts. This chapter “zooms in” to focus on particular subgroups within the Hub data set. First, the chapter provides statistical and graphical comparisons of traditional New England dialect features by contrasting two nearby groups: White speakers in the traditional working-class South Boston neighborhood, and Black/African American speakers in nearby Dorchester, Hyde Park, and other neighborhoods. The chapter concludes with a fieldwork project in Cape Cod. In each case, the chapter provides detailed plots of dialect features and statistical analyses with respect to age, gender, social class, ethnicity, and other factors