Estimating the effect of annual PM exposure on mortality in India: a difference-in-differences approach.

Background: In 2019, the Global Burden of Diseases, Injuries, and Risk Factors Study attributed 0·98 million deaths to ambient air pollution in India based on potentially inappropriate exposure-response functions from countries with low air pollution levels. Instead, using data from India, we investigated long-term exposure to PM and all-cause mortality with a causal inference method.

Methods: We collected national counts of annual mortality from 2009 to 2019 from the Civil Registration System at the district level to calculate annual district-level mortality rate as our main outcome and obtained annual PM concentrations from a high-resolution spatiotemporal model.

Nationwide analysis of air pollution hotspots across India: A spatiotemporal PM trend analysis (2008-2019).

Introduction: India experiences high levels of air pollution as measured by fine particulate matter <2.5 μm (PM) across the country. With limited resources, it is imperative to identify the most impacted areas.

Quantifying urban park use in the USA at scale: empirical estimates of realised park usage using smartphone location data.

Background: A large body of evidence connects access to greenspace with substantial benefits to physical and mental health. In urban settings where access to greenspace can be limited, park access and use have been associated with higher levels of physical activity, improved physical health, and lower levels of markers of mental distress. Despite the potential health benefits of urban parks, little is known about how park usage varies across locations (between or within cities) or over time.

Nationwide estimation of daily ambient PM from 2008 to 2020 at 1 km in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM) pollution in India. We developed a model for daily average ambient PM between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories.

The Exposure Peaks of Traffic-Related Ultrafine Particles Associated with Inflammatory Biomarkers and Blood Lipid Profiles.

In this article, we explored the effects of ultrafine particle (UFP) peak exposure on inflammatory biomarkers and blood lipids using two novel metrics-the intensity of peaks and the frequency of peaks. We used data previously collected by the Community Assessment of Freeway Exposure and Health project from participants in the Greater Boston Area. The UFP exposure data were time-activity-adjusted hourly average concentration, estimated using land use regression models based on mobile-monitored ambient concentrations.

Climate stress and anxiety, environmental context, and civic engagement: A nationally representative study.

There is increasing recognition that people are experiencing stress and anxiety around climate change, and that this climate stress/anxiety may be associated with more pro-environmental behavior. However, less is known about whether people's own environmental exposures affect climate stress/anxiety or the relationship between climate stress/anxiety and civic engagement. Using three waves of survey data (2020-2022) from the nationally representative Tufts Equity in Health, Wealth, and Civic Engagement Study of US adults (n = 1071), we assessed relationships among environmental exposures (county-level air pollution, greenness, number of toxic release inventory sites, and heatwaves), self-reported climate stress/anxiety, and civic engagement measures (canvasing behavior, collaborating to solve community problems, personal efficacy to solve community problems, group efficacy to solve community problems, voting behavior).

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.

Characterizing temporal trends in populations exposed to aircraft noise around U.S. airports: 1995-2015.

Background: Aircraft noise is a key concern for communities surrounding airports, with increasing evidence for health effects and inequitable distributions of exposure. However, there have been limited national-scale assessments of aircraft noise exposure over time and across noise metrics, limiting evaluation of population exposure patterns.

Objective: We evaluated national-scale temporal trends in aviation noise exposure by airport characteristics and across racial/ethnic populations in the U.

Evaluating COVID-19 Risk to Essential Workers by Occupational Group: A Case Study in Massachusetts.

Occupational exposure to SARS-CoV-2 varies by profession, but "essential workers" are often considered in aggregate in COVID-19 models. This aggregation complicates efforts to understand risks to specific types of workers or industries and target interventions, specifically towards non-healthcare workers. We used census tract-resolution American Community Survey data to develop novel essential worker categories among the occupations designated as COVID-19 Essential Services in Massachusetts.

Environmental equity and COVID-19 experiences in the United States: Results from three survey waves of a nationally representative study conducted between 2020-2022.

Certain environmental exposures, such as air pollution, are associated with COVID-19 incidence and mortality. To determine whether environmental context is associated with other COVID-19 experiences, we used data from the nationally representative Tufts Equity in Health, Wealth, and Civic Engagement Study data (n=1785; three survey waves 2020-2022). Environmental context was assessed using self-reported climate stress and county-level air pollution, greenness, toxic release inventory site, and heatwave data.

Assessing the impact of aircraft arrival on ambient ultrafine particle number concentrations in near-airport communities in Boston, Massachusetts.

Aircraft emissions contribute to overall ambient air pollution, including ultrafine particle (UFP) concentrations. However, accurately ascertaining aviation contributions to UFP is challenging due to high spatiotemporal variability along with intermittent aviation emissions. The objective of this study was to evaluate the impact of arrival aircraft on particle number concentration (PNC), a proxy for UFP, across six study sites 3-17 km from a major arrival aircraft flight path into Boston Logan International Airport by utilizing real-time aircraft activity and meteorological data.

Influence of geospatial resolution on sociodemographic predictors of COVID-19 in Massachusetts.

Purpose: When studying health risks across a large geographic region such as a state or province, researchers often assume that finer-resolution data on health outcomes and risk factors will improve inferences by avoiding ecological bias and other issues associated with geographic aggregation. However, coarser-resolution data (e.g.

Examining the Optimal Placement of Cooling Centers to Serve Populations at High Risk of Extreme Heat Exposure in 81 US Cities.

Objective: Although extreme heat can impact the health of anyone, certain groups are disproportionately affected. In urban settings, cooling centers are intended to reduce heat exposure by providing air-conditioned spaces to the public. We examined the characteristics of populations living near cooling centers and how well they serve areas with high social vulnerability.

Relationship between traffic-related air pollution and inflammation biomarkers using structural equation modeling.

Background: Evidence suggests that exposure to traffic-related air pollution (TRAP) and social stressors can increase inflammation. Given that there are many different markers of TRAP exposure, socio-economic status (SES), and inflammation, analytical approaches can leverage multiple markers to better elucidate associations. In this study, we applied structural equation modeling (SEM) to assess the association between a TRAP construct and a SES construct with an inflammation construct.

Critical windows of susceptibility for the effects of prenatal exposure to heat and heat variability on gestational growth.

Background: Studies have shown that prenatal heat exposure may impact fetal growth, but few studies have examined the critical windows of susceptibility. As extreme heat events and within season temperature variability is expected to increase in frequency, it is important to understand how this may impact gestational growth.

Objectives: We investigated associations between various measures of weekly prenatal heat exposure (mean and standard deviation (SD) of temperature and heat index (HI), derived using temperature in °C and dew point) and term birthweight or odds of being born small for gestational age (SGA) to identify critical windows of susceptibility.

Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts.

Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized.

Digital Global Recruitment for Women's Health Research: Cross-sectional Study.

Background: With the increased popularity of mobile menstrual tracking apps and boosted Facebook posts, there is a unique opportunity to recruit research study participants from across the globe via these modalities to evaluate women's health. However, no studies to date have assessed the feasibility of using these recruitment sources for epidemiological research on ovulation and menstruation.

Objective: The objective of this study was to assess the feasibility of recruiting a diverse sample of women to an epidemiological study of ovulation and menstruation (OM) health (OM Global Health Study) using digital recruitment sources.

Fine particulate matter and polycystic ovarian morphology.

Background: Polycystic ovary morphology (PCOM) is an ultrasonographic finding that can be present in women with ovulatory disorder and oligomenorrhea due to hypothalamic, pituitary, and ovarian dysfunction. While air pollution has emerged as a possible disrupter of hormone homeostasis, limited research has been conducted on the association between air pollution and PCOM.

Methods: We conducted a longitudinal cohort study using electronic medical records data of 5,492 women with normal ovaries at the first ultrasound that underwent a repeated pelvic ultrasound examination during the study period (2004-2016) at Boston Medical Center.

Impacts of the choice of distance measurement method on estimates of access to point-based resources.

Background/objective: Lack of access to resources such as medical facilities and grocery stores is related to poor health outcomes and inequities, particularly in an environmental justice framework. There can be substantial differences in quantifying "access" to such resources, depending on the geospatial method used to generate distance estimates.

Methods: We compared three methods for calculating distance to the nearest grocery store to illustrate differential access at the census block-group level in the Atlanta metropolitan area, including: Euclidean distance estimation, service areas incorporating roadways and other factors, and cost distance for every point on the map.

The immigrant birthweight paradox in an urban cohort: Role of immigrant enclaves and ambient air pollution.

Background: Foreign-born Black and Latina women on average have higher birthweight infants than their US-born counterparts, despite generally worse socioeconomic indicators and prenatal care access, i.e., "immigrant birthweight paradox" (IBP).

Community predictors of COVID-19 cases and deaths in Massachusetts: Evaluating changes over time using geospatially refined data.

Background: The COVID-19 pandemic has highlighted the need for targeted local interventions given substantial heterogeneity within cities and counties. Publicly available case data are typically aggregated to the city or county level to protect patient privacy, but more granular data are necessary to identify and act upon community-level risk factors that can change over time.

Methods: Individual COVID-19 case and mortality data from Massachusetts were geocoded to residential addresses and aggregated into two time periods: "Phase 1" (March-June 2020) and "Phase 2" (September 2020 to February 2021).

A new exposure metric for the cumulative effect of short-term exposure peaks of traffic-related ultrafine particles.

Introduction: The adverse health outcomes of traffic-related ultrafine particles (UFPs) disproportionally impact near-highway neighborhoods. Current studies focus on either short-term health outcomes associated with short-term UFP exposures averaged over days or weeks, or long-term outcomes associated with long-term (yearly or longer) average UFP exposures. We hypothesized that frequent and repeated exposure to short-term UFP peaks that last for just hours could overwhelm or alter physiological defensive responses, resulting in long-term health issues.