Quantifying the intersection of disability and homelessness in Massachusetts public schools in 2018-2019.

BACKGROUND: Homelessness has a major impact on the educational and health trajectories of children. Youth with disabilities may be especially vulnerable to experiencing homelessness, but little epidemiological work has been done to characterize dual disparity. Our goal was to describe the relationship between homelessness and disability among students (age 3-21) receiving public education in Massachusetts in 2018-2019. We evaluated the proportion of students with and without disabilities experiencing homelessness by county and school district. METHODS: We used publicly available data from the United States and Massachusetts Department's of Education. These data used the McKinney Vento Homelessness Assistance Act definition of homelessness which is a lack of fixed, adequate, and regular housing, and disability was determined by the presence of an individualized education program or individualized family service plan. We calculated percentages of students with and without disabilities experiencing homelessness at the state, county, and district level and calculated and mapped risk of homelessness comparing students and without disability. We also determined the occurrence of disability among those experiencing homelessness. RESULTS: In Massachusetts public schools, 3.5% of students with disabilities experienced homelessness compared with 2.4% of students without disabilities (relative risk 1.50, 95% CI: 1.47, 1.53). A greater proportion of students with disabilities experienced homelessness compared with students without disabilities in all counties. In sum, 24.8% of students experiencing homelessness had a reported disability. CONCLUSIONS: In Massachusetts public schools, a greater proportion of students with disabilities experience homelessness compared with students without disabilities, and disability is common among students experiencing homelessness. We hypothesize potential mechanisms, such as the financial cost of disability, that may lead to this finding. Findings support the need for additional funding and interventions for school districts and communities to better serve vulnerable students with disabilities experiencing homelessness.

Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts.

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 (PM2.5), 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.

Manganese in residential drinking water from a community-initiated case study in Massachusetts.

BACKGROUND: Manganese (Mn) is a metal commonly found in drinking water, but the level that is safe for consumption is unknown. In the United States (U.S.), Mn is not regulated in drinking water and data on water Mn concentrations are temporally and spatially sparse. OBJECTIVE: Examine temporal and spatial variability of Mn concentrations in repeated tap water samples in a case study of Holliston, Massachusetts (MA), U.S., where drinking water is pumped from shallow aquifers that are vulnerable to Mn contamination. METHODS: We collected 79 residential tap water samples from 21 households between September 2018 and December 2019. Mn concentrations were measured using inductively coupled plasma mass spectrometry. We calculated descriptive statistics and percent of samples exceeding aesthetic (secondary maximum containment level; SMCL) and lifetime health advisory (LHA) guidelines of 50 µg/L and 300 µg/L, respectively. We compared these concentrations to concurrent and historic water Mn concentrations from publicly available data across MA. RESULTS: The median Mn concentration in Holliston residential tap water was 2.3 µg/L and levels were highly variable (range: 0.03-5,301.8 µg/L). Mn concentrations exceeded the SMCL and LHA in 14% and 12% of samples, respectively. Based on publicly available data across MA from 1994-2022, median Mn concentration was 17.0 µg/L (N = 37,210; range: 1-159,000 µg/L). On average 40% of samples each year exceeded the SMCL and 9% exceeded the LHA. Samples from publicly available data were not evenly distributed between MA towns or across sampling years. IMPACT STATEMENT: This study is one of the first to examine Mn concentrations in drinking water both spatially and temporally in the U.S. Findings suggest that concentrations of Mn in drinking water frequently exceed current guidelines and occur at concentrations shown to be associated with adverse health outcomes, especially for vulnerable and susceptible subpopulations like children. Future studies that comprehensively examine exposure to Mn in drinking water and its associations with children's health are needed to protect public health.

Homelessness and Disability in Public-School Students.

OBJECTIVE: To quantify students with disabilities experiencing homelessness in the Northeastern and Mid-Atlantic US state and district public schools and compare them with those without disabilities. METHODS: Data were compiled from state departments of education and federal homelessness data and were merged by using the Local Education Agency identifier. We calculated the proportion of students with and without disabilities experiencing homelessness and corresponding relative risk 95% confidence intervals. We examined changes in homelessness in Massachusetts counties compared with the 2018 to 2019 school year. RESULTS: Across the 7 states and Washington, DC, 4.7% of students with disabilities experienced homelessness, 58% greater than the percentage of students without disabilities (95% confidence interval 1.57-1.59). The highest proportion of students with disabilities experiencing homelessness was in Washington, DC, and New York, with the lowest proportion in Connecticut. There was little change comparing 2018 to 2019 with 2019 to 2020 statistics in Massachusetts. CONCLUSIONS: Quantifying students with disabilities experiencing homelessness provides policymakers with valuable information to be able to act to better support these students. Variations by state/district and time highlight the need for continued data collection and aggregation.

Calculating access to parks and other polygonal resources: A description of open-source methodologies.

Public health studies routinely use simplistic methods to calculate proximity-based "access" to greenspace, such as by measuring distances to the geographic centroids of parks or, less frequently, to the perimeter of the park area. Although computationally efficient, these approaches oversimplify exposure measurement because parks often have specific entrance points. In this tutorial paper, we describe how researchers can instead calculate more-accurate access measures using freely available open-source methods. Specifically, we demonstrate processes for calculating "service areas" representing street-network-based buffers of access to parks within set distances and mode of transportation (e.g., 1-km walk or 20-minute drive) using OpenRouteService and QGIS software. We also introduce an advanced method involving the identification of trailheads or parking lots with OpenStreetMap data and show how large parks particularly benefit from this approach. These methods can be used globally and are applicable to analyses of a wide range of studies investigating proximity access to resources.

Benefits of Increasing Greenness on All-Cause Mortality in the Largest Metropolitan Areas of the United States Within the Past Two Decades.

Across the United States, cities are creating sustainability and climate action plans (CAPs) that call to increase local vegetation. These greening initiatives have the potential to not only benefit the environment but also human health. In epidemiologic literature, greenness has a protective effect on mortality through various direct and indirect pathways. We aimed to assess how an increase in greenness could decrease mortality in the largest urban areas in the United States. We conducted a nationwide quantitative health impact assessment to estimate the predicted reduction in mortality associated with an increase in greenness across two decades (2000, 2010, and 2019). Using a recently published exposure-response function, Landsat 30 m 16-day satellite imagery from April to September, and publicly available county-level mortality data from the CDC, we calculated the age-adjusted reduction in all-cause mortality for those 65 years and older within 35 of the most populated metropolitan areas. We estimated that between 34,000 and 38,000 all-cause deaths could have been reduced in 2000, 2010, and 2019 with a local increase in green vegetation by 0.1 unit across the most populated metropolitan areas. We found that overall greenness increased across time with a 2.86% increase from 2000 to 2010 to 11.11% from 2010 to 2019. These results can be used to support CAPs by providing a quantitative assessment to the impact local greening initiatives can have on mortality. Urban planners and local governments can use these findings to calculate the co-benefits of local CAPs through a public health lens and support policy development.

Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts.

BACKGROUND: Associations between community-level risk factors and COVID-19 incidence are 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. We examined town-level demographic variables, including z-scores of percent Black, Latinx, over 80 years and undergraduate students, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM 2.5 ), and institutional facilities. 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 Black residents (IRR=1.12 CI=(1.12-1.13) in spring, IRR=1.01 CI=(1.00-1.01) in fall). The association with number of long-term care facility beds per capita also decreased over time (IRR=1.28 CI=(1.26-1.31) in spring, IRR=1.07 CI=(1.05-1.09)in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidence of COVID-19 throughout the pandemic (e.g., IRR=1.30 CI=(1.27-1.33) in spring, IRR=1.20, CI=(1.17-1.22) in fall). Towns with higher percentages of Latinx residents also had sustained elevated incidence over time (e.g., IRR=1.19 CI=(1.18-1.21) in spring, IRR=1.14 CI=(1.13-1.15) in fall). CONCLUSIONS: Town-level COVID-19 risk factors vary with time. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence have decreased over time, 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.

A tree-planting decision support tool for urban heat mitigation.

Heat poses an urgent threat to public health in cities, as the urban heat island (UHI) effect can amplify exposures, contributing to high heat-related mortality and morbidity. Urban trees have the potential to mitigate heat by providing substantial cooling, as well as co-benefits such as reductions in energy consumption. The City of Boston has attempted to expand its urban canopy, yet maintenance costs and high tree mortality have hindered successful canopy expansion. Here, we present an interactive web application called Right Place, Right Tree-Boston that aims to support informed decision-making for planting new trees. To highlight priority regions for canopy expansion, we developed a Boston-specific Heat Vulnerability Index (HVI) and present this alongside maps of summer daytime land surface temperatures. We also provide information about tree pests and diseases, suitability of species for various conditions, land ownership, maintenance tips, and alternatives to tree planting. This web application is designed to support decision-making at multiple spatial scales, to assist city officials as well as residents who are interested in expanding or maintaining Boston's urban forest.