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Inequities in Coronavirus Disease 2019 (COVID-19) vaccine and booster coverage may contribute to future disparities in morbidity and mortality within and between Massachusetts (MA) communities. We conducted a population-based cross-sectional study of primary series vaccination and booster coverage 18 months into the general population vaccine rollout. We obtained public-use data on residents vaccinated and boosted by ZIP code (and by age group: 5 to 19, 20 to 39, 40 to 64, 65+) from MA Department of Public Health, as of October 10, 2022. We constructed population denominators for postal ZIP codes by aggregating census tract population estimates from the 2015-2019 American Community Survey. We excluded nonresidential ZIP codes and the smallest ZIP codes containing 1% of the state's population. We mapped variation in ZIP code-level primary series vaccine and booster coverage and used regression models to evaluate the association of these measures with ZIP code-level socioeconomic and demographic characteristics. Because age is strongly associated with COVID-19 severity and vaccine access/uptake, we assessed whether observed socioeconomic and racial/ethnic inequities persisted after adjusting for age composition and plotted age-specific vaccine and booster coverage by deciles of ZIP code characteristics. We analyzed data on 418 ZIP codes. We observed wide geographic variation in primary series vaccination and booster rates, with marked inequities by ZIP code-level education, median household income, essential worker share, and racial/ethnic composition. In age-stratified analyses, primary series vaccine coverage was very high among the elderly. However, we found large inequities in vaccination rates among younger adults and children, and very large inequities in booster rates for all age groups. In multivariable regression models, each 10 percentage point increase in \"percent college educated\" was associated with a 5.1 (95% confidence interval (CI) 3.9 to 6.3, p < 0.001) percentage point increase in primary series vaccine coverage and a 5.4 (95% CI 4.5 to 6.4, p < 0.001) percentage point increase in booster coverage. Although ZIP codes with higher \"percent Black/Latino/Indigenous\" and higher \"percent essential workers\" had lower vaccine coverage (-0.8, 95% CI -1.3 to -0.3, p < 0.01; -5.5, 95% CI -7.3 to -3.8, p < 0.001), these associations became strongly positive after adjusting for age and education (1.9, 95% CI 1.0 to 2.8, p < 0.001; 4.8, 95% CI 2.6 to 7.1, p < 0.001), consistent with high demand for vaccines among Black/Latino/Indigenous and essential worker populations within age and education groups. Strong positive associations between \"median household income\" and vaccination were attenuated after adjusting for age. Limitations of the study include imprecision of the estimated population denominators, lack of individual-level sociodemographic data, and potential for residential ZIP code misreporting in vaccination data. Eighteen months into MA's general population vaccine rollout, there remained large inequities in COVID-19 primary series vaccine and booster coverage across MA ZIP codes, particularly among younger age groups. Disparities in vaccination coverage by racial/ethnic composition were statistically explained by differences in age and education levels, which may mediate the effects of structural racism on vaccine uptake. Efforts to increase booster coverage are needed to limit future socioeconomic and racial/ethnic disparities in COVID-19 morbidity and mortality.

Energy efficiency (EE) and renewable energy (RE) can benefit public health and the climate by displacing emissions from fossil-fuelled electrical generating units (EGUs). Benefits can vary substantially by EE/RE installation type and location, due to differing electricity generation or savings by location, characteristics of the electrical grid and displaced power plants, along with population patterns. However, previous studies have not formally examined how these dimensions individually and jointly contribute to variability in benefits across locations or EE/RE types. Here, we develop and demonstrate a high-resolution model to simulate and compare the monetized public health and climate benefits of four different illustrative EE/RE installation types in six different locations within the Mid-Atlantic and Lower Great Lakes of the United States. Annual benefits using central estimates for all pathways ranged from US$5.7–US$210 million (US$14–US$170 MWh −1 ), emphasizing the importance of site-specific information in accurately estimating public health and climate benefits of EE/RE efforts. Clean energy can provide different health and environmental benefits depending on location. Modelling shows that renewable energy and energy-saving projects could deliver annual benefits of up to US$210 million across six locations in the USA.

Background Traffic congestion is a significant issue in urban areas in the United States and around the world. Previous analyses have estimated the economic costs of congestion, related to fuel and time wasted, but few have quantified the public health impacts or determined how these impacts compare in magnitude to the economic costs. Moreover, the relative magnitudes of economic and public health impacts of congestion would be expected to vary significantly across urban areas, as a function of road infrastructure, population density, and atmospheric conditions influencing pollutant formation, but this variability has not been explored. Methods In this study, we evaluate the public health impacts of ambient exposures to fine particulate matter (PM 2.5 ) concentrations associated with a business-as-usual scenario of predicted traffic congestion. We evaluate 83 individual urban areas using traffic demand models to estimate the degree of congestion in each area from 2000 to 2030. We link traffic volume and speed data with the MOBILE6 model to characterize emissions of PM 2.5 and particle precursors attributable to congestion, and we use a source-receptor matrix to evaluate the impact of these emissions on ambient PM 2.5 concentrations. Marginal concentration changes are related to a concentration-response function for mortality, with a value of statistical life approach used to monetize the impacts. Results We estimate that the monetized value of PM 2.5 -related mortality attributable to congestion in these 83 cities in 2000 was approximately $31 billion (2007 dollars), as compared with a value of time and fuel wasted of $60 billion. In future years, the economic impacts grow (to over $100 billion in 2030) while the public health impacts decrease to $13 billion in 2020 before increasing to $17 billion in 2030, given increasing population and congestion but lower emissions per vehicle. Across cities and years, the public health impacts range from more than an order of magnitude less to in excess of the economic impacts. Conclusions Our analyses indicate that the public health impacts of congestion may be significant enough in magnitude, at least in some urban areas, to be considered in future evaluations of the benefits of policies to mitigate congestion.

Health impact assessments have estimated substantial health co-benefits of climate change mitigation strategies due to reductions in air pollution in the US; however, few studies have considered children’s health impacts and related equity implications. We estimated the potential health co-benefits to children related to improved air quality associated with various emissions cap and investment scenarios for the transportation sector in the Northeastern and Mid-Atlantic US proposed under the Transportation and Climate Initiative (TCI). We modeled changes in ambient fine particulate matter and nitrogen dioxide between 2022 and 2032 associated with on-road transportation sector emissions under nine hypothetical carbon dioxide (CO 2 ) emissions cap and investment scenarios proposed under TCI using the Community Multiscale Air Quality (CMAQ) model version 5.2. We estimated potential health co-benefits for adverse birth and pediatric respiratory and neurodevelopmental outcomes using an expanded version of the Environmental Benefits Mapping and Analysis Program, known as BenMAPR. We also examined impacts on pediatric asthma exacerbations across racial/ethnic groups. We found that health benefits to children increased as the CO 2 emission caps became more ambitious. The combination of the highest emissions cap (25%) and the investment scenario which prioritized public transit improvement (Diversified strategy) conferred the greatest children’s health benefits for the majority of health outcomes considered, resulting in approximately $82 million per year in economic savings. Assessment of the distribution of avoided pediatric asthma exacerbations showed benefits across all racial and ethnic groups, with a slightly greater reduction in cases for non-White populations. Decarbonization policies in the transportation sector in the Eastern US have the potential to provide important air quality and pediatric health co-benefits.

Background Communities with large minority populations often are located near sources of pollution and have higher crime rates, which may work in combination with other factors to influence health. Poor self-rated health is related to chronic health conditions and premature mortality, with minority populations most likely to report poor health. To address how both resident perception of neighborhood environments and chronic health conditions individually and collectively influence health, we examined self-rated health and its association with multiple types of perceived environmental hazards in a majority-Hispanic urban population. Methods We conducted interviews with 354 residents of Chelsea, Massachusetts, US and asked about self-rated health, perceptions of their neighborhood, including participant-reported environmental hazards (e.g., air quality, odors and noise), aspects of the social environment (e.g., feeling safe, neighborhood crime, social cohesion), and culture-related stressors (e.g., immigration status, language stress, ethnic identity). Log-linear models examined the independent and multivariable associations between these factors and fair/poor self-rated health, controlling for socio-demographic characteristics and preexisting health conditions. Results Forty-one percent of participants reported fair/poor self-rated health. Participants frequently perceived environmental hazards such as problems with pests and regular noise disturbance as well as feeling unsafe. In a multivariable model, a greater number of reported noise disturbances (≥ 2 noise sources = 1.53 [1.04–2.26]) and reported insecurity with immigration status (1.66 [1.01–2.73]) were positively associated with fair/poor self-rated health. High social cohesion was inversely associated (0.74 [0.48–1.14]) with fair/poor self-rated health in the multivariable model. Conclusions Negative perceptions of environmental hazards and reported cultural stressors were significantly associated with fair/poor self-rated health among residents in a low-income majority-minority community, with social cohesion having a beneficial association with self-rated health. Efforts to improve health should recognize the importance of public perceptions of social and environmental hazards found in neighborhood environments, and benefits of strengthening community connections.

The growing frequency, intensity, and duration of extreme heat events necessitates interventions to reduce heat exposures. Local opportunities for heat adaptation may be optimally identified through collection of both quantitative exposure metrics and qualitative data on perceptions of heat. In this study, we used mixed methods to characterize heat exposure among urban residents in the area of Boston, Massachusetts, US, in summer 2020. Repeated interviews of N  = 24 study participants ascertained heat vulnerability and adaptation strategies. Participants also used low-cost sensors to collect temperature, location, sleep, and physical activity data. We saw significant differences across temperature metrics: median personal temperature exposures were 3.9 °C higher than median ambient weather station temperatures. Existing air conditioning (AC) units did not adequately control indoor temperatures to desired thermostat levels: even with AC use, indoor maximum temperatures increased by 0.24 °C per °C of maximum outdoor temperature. Sleep duration was not associated with indoor or outdoor temperature. On warmer days, we observed a range of changes in time-at-home, expected given our small study size. Interview results further indicated opportunities for heat adaptation interventions including AC upgrades, hydration education campaigns, and amelioration of energy costs during high heat periods. Our mixed methods design informs heat adaptation interventions tailored to the challenges faced by residents in the study area. The strength of our community-academic partnership was a large part of the success of the mixed methods approach.

Housing quality, which includes structural and environmental risks, has been associated with multiple physical health outcomes including injury and asthma. Cockroach and mouse infestations can be prime manifestations of diminished housing quality. While the respiratory health effects of pest infestation are well documented, little is known about the association between infestation and mental health outcomes. To address this gap in knowledge and given the potential to intervene to reduce pest infestation, we assessed the association between household pest infestation and symptoms of depression among public housing residents. We conducted a cross-sectional study in 16 Boston Housing Authority (BHA) developments from 2012 to 2014 in Boston, Massachusetts. Household units were randomly selected and one adult (n = 461) from each unit was surveyed about depressive symptoms using the Center for Epidemiologic Study-Depression (CES-D) Scale, and about pest infestation and management practices. In addition, a home inspection for pests was performed. General linear models were used to model the association between pest infestation and high depressive symptoms. After adjusting for important covariates, individuals who lived in homes with current cockroach infestation had almost three times the odds of experiencing high depressive symptoms (adjusted OR = 2.9, 95% CI 1.9–4.4) than those without infestation. Dual infestation (cockroach and mouse) was associated with over five times the odds (adjusted odds = 5.1, 95% CI 3.0–8.5) of experiencing high depressive symptoms. Using a robust measure of cockroach and mouse infestation, and a validated depression screener, we identified associations between current infestation and depressive symptoms. Although the temporal directionality of this association remains uncertain, these findings suggest that the health impact of poor housing conditions extend beyond physical health to include mental health. The study adds important information to the growing body of evidence that housing contributes to population health and improvements in population health may not be possible without addressing deficiencies in the housing infrastructure.

Background Associations between community-level risk factors and COVID-19 incidence have been used to identify vulnerable subpopulations and target interventions, but the variability of these associations over time remains largely unknown. We evaluated variability in the associations between community-level predictors and COVID-19 case incidence in 351 cities and towns in Massachusetts from March to October 2020. Methods Using publicly available sociodemographic, occupational, environmental, and mobility datasets, we developed mixed-effect, adjusted Poisson regression models to depict associations between these variables and town-level COVID-19 case incidence data across five distinct time periods from March to October 2020. We examined town-level demographic variables, including population proportions by race, ethnicity, and age, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM 2.5 ), and institutional facilities. We calculated incidence rate ratios (IRR) associated with these predictors and compared these values across the multiple time periods to assess variability in the observed associations over time. Results Associations between key predictor variables and town-level incidence varied across the five time periods. We observed reductions over time in the association with percentage of Black residents (IRR = 1.12 [95%CI: 1.12–1.13]) in early spring, IRR = 1.01 [95%CI: 1.00–1.01] in early fall) and COVID-19 incidence. The association with number of long-term care facility beds per capita also decreased over time (IRR = 1.28 [95%CI: 1.26–1.31] in spring, IRR = 1.07 [95%CI: 1.05–1.09] in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidences of COVID-19 throughout the pandemic (e.g., IRR = 1.30 [95%CI: 1.27–1.33] in spring, IRR = 1.20 [95%CI: 1.17–1.22] in fall). Towns with higher proportions of Latinx residents also had sustained elevated incidence over time (IRR = 1.19 [95%CI: 1.18–1.21] in spring, IRR = 1.14 [95%CI: 1.13–1.15] in fall). Conclusions Town-level COVID-19 risk factors varied with time in this study. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence may have decreased across the first 8 months of the pandemic, perhaps indicating greater success in risk mitigation in selected communities. Our approach can be used to evaluate effectiveness of public health interventions and target specific mitigation efforts on the community level.

Background: Disproportionate life stress and consequent physiologic alteration (i.e., immune dysregulation) has been proposed as a major pathway linking socioeconomic position, environmental exposures, and health disparities. Asthma, for example, disproportionately affects lower-income urban communities, where air pollution and social stressors may be elevated. Objectives: We aimed to examine the role of exposure to violence (ETV), as a chronic stressor, in altering susceptibility to traffic-related air pollution in asthma etiology. Methods: We developed geographic information systems (GIS)-based models to retrospectively estimate residential exposures to traffic-related pollution for 413 children in a community-based pregnancy cohort, recruited in East Boston, Massachusetts, between 1987 and 1993, using monthly nitrogen dioxide measurements for 13 sites over 18 years. We merged pollution estimates with questionnaire data on lifetime ETV and examined the effects of both on childhood asthma etiology. Results: Correcting for potential confounders, we found an elevated risk of asthma with a 1-SD (4.3 ppb) increase in NO2exposure solely among children with above-median ETV [odds ratio (OR) = 1.63; 95% confidence interval (CI), 1.14-2.33)]. Among children always living in the same community, with lesser exposure measurement error, this association was magnified (OR = 2.40; 95% CI, 1.48-3.88). Of multiple exposure periods, year-of-diagnosis NO2was most predictive of asthma outcomes. Conclusions: We found an association between traffic-related air pollution and asthma solely among urban children exposed to violence. Future studies should consider socially patterned susceptibility, common spatial distributions of social and physical environmental factors, and potential synergies among these. Prospective assessment of physical and social exposures may help determine causal pathways and critical exposure periods.