Lead (Pb) soil contamination in urban environments represents a considerable health risk for exposed populations, which often include environmental justice communities. In Philadelphia, Pennsylvania (PA), Pb pollution is a major concern primarily due to extensive historical Pb-smelting/processing activity and legacy use of Pb-based paints and leaded gasoline. The U.S. Environmental Protection Agency (USEPA) organized and/or compiled community-driven soil sampling campaigns to investigate Pb content in surface soils across Philadelphia. Using these data (n = 1277), combined with our own dataset (n = 1388), we explored the spatial distribution of Pb content in soils across the city using ArcGIS. While assessing Zone Improvement Plan (ZIP)-code level data, we found strong correlations between factors, such as the percentage of children with elevated blood lead levels (% EBLL) and % minority population as well as between % EBLL and % children in poverty. We developed a “Lead Index” that took demographics, median measured Pb-in-soil content, and % EBLLs into account to identify ZIP codes in need of further assessment. Our results will be used to help lower the Pb-exposure risk for vulnerable children living in disproportionately burdened communities.

Childhood lead poisoning is an issue that continues to plague major U.S. cities. Despite efforts by the Philadelphia Department of Public Health to curtail systemic childhood lead poisoning, children continue to be identified with elevated blood lead levels. The persistence of elevated blood lead levels in children is concerning because lead poisoning has been linked to decreases in academic achievement and IQ, with associated repercussions for entire communities. This paper reports the results of an analysis of the spatial distribution of houses with lead paint (i.e., pre‐1978), demolitions, and occurrence of historic smelters, in West and North Philadelphia, relative to elevated blood lead level data, to determine which lead sources act as primary lead‐risk factors. The presence of lead paint in homes and the number of demolitions of older properties were found to have the highest correlations to elevated blood lead levels for children in Philadelphia. Using lead‐risk factors including lead paint, housing code violations, demolitions, and owner‐occupied housing units, a lead‐risk assessment was performed at the census tract level to identify future soil sampling sites and high‐risk neighborhoods in Philadelphia. These sites of high risk for lead exposure, and in particular the census tracts 175 and 172, should be prioritized for lead poisoning prevention initiatives.

Scientific research is not value-neutral but builds on the stated and unstated values of those leading the research, influencing the choice of study topics; decisions about methods, judgments, or inferences with data; and considerations of the consequences of errors. In some fields, researchers create a positionality statement to disclose bias as a way to manage or neutralize the influence of values. Positionality refers to the way in which an individual’s worldview, and thus perceptions and research activities, is shaped by the frameworks, social identities, lived experiences, and sociopolitical context within which they live. Thinking about positionality is a valuable, yet missing, element for practitioners of participatory sciences. In this essay, we suggest that those leading participatory science projects explore their positionality, irrespective of whether or not they choose to disclose it, in order to manage values for several goals: research integrity, ethical data practices, and equity and inclusion. By reviewing and synthesizing literature, we created a tool to help leaders of participatory science projects think reflectively (for awareness of their identities and characteristics) and reflexively (from an external position for critical observation of themselves) to recognize their influence on project design and implementation. We view examining positionality as a precursor to anticipating and taking actions to minimize epistemic injustices and ultimately enhance the unique capacity of each project to advance equity, inclusion, and scientific productivity.

The majority of Americans do not regularly get the recommended amount of sleep and sleep deficiencies disproportionately burden marginalized communities. We conducted a longitudinal cohort study measuring bedroom air temperature and humidity over three non-consecutive weeks (N = 19 participants; 409 observation nights) using HOBO loggers and sleep health using wrist-actigraphy and sleep diaries. Outdoor temperature and humidity were obtained from a nearby weather station. Linear mixed-effects regression models assessed relationships between temperature and sleep health metrics. Nighttime indoor apparent temperature ranged from 26 to 35 °C and averaged 5 °C higher than outdoors. On average, participants slept 6.7 h per night with 83% sleep efficiency. After adjustment, a 5 °C increase in indoor nighttime dry bulb temperature was associated with a 23 min reduction in mean total sleep time (β = −23.30 [−43.30, −3.45]) and mean onset latency increase of approximately 2 min (β = 1.85 [0.50, 6.65]). Nighttime heat waves were associated with a 4% reduction in mean sleep efficiency (β = −3.71 [−6.83, −0.66]) and an 11 min increase in onset latency (β = 11.32 [2.60, 20.75]). We found evidence that rising summertime temperatures reduced sleep health in a disproportionately impacted community, suggesting that climate change will worsen existing sleep health disparities.

Elevated ambient temperatures are associated with preterm birth, which disproportionately occurs among ethno-racially and socio-economically marginalized populations. Existing literature on the reproductive health effects of heat primarily explores ambient temperatures, neglecting individual-level differences in exposure to extreme temperatures due to factors like housing, occupation, and neighborhood land cover. To address these individual differences, we linked 2015–2019 Los Angeles County administrative birth records to 2022 tax parcel data to estimate individual-level housing thermal performance, occupation in high-heat-risk professions, tract-level urban-heat-island intensity, and zip-code-level maximum and minimum ambient temperature exposures among birth parents ( N = 504 761). We use logistic regression to assess disparities in these four heat-exposure metrics by sociodemographic variables previously associated with preterm birth. Black, Latine, Mexican immigrant, and less formally educated parents had consistently higher odds of heat exposure across all four dimensions, relative to their White, US-born Latine, and highly formally educated counterparts. Survival analysis using Cox proportional hazards model indicated that exposure to weeks with an extreme heat day was associated with a 41% (95% confidence interval [CI]: 8%–83%) and 75% (95% CI: 16%–165%) higher hazard of very and extremely preterm births, respectively, relative to pregnancies that did not experience an extreme heat day. We did not find strong evidence for extreme heat exposure and late preterm births. When jointly exposed to poor housing thermal performance and an extreme heat day, the hazard of an extremely preterm birth rose to 177% (95% CI: 15%–567%). We did not find evidence of a joint effect for late or very preterm births. These findings illuminate how housing, occupation, and land cover compound heat-risk exposures among ethno-racially marginalized and socio-economically disadvantaged birth parents in Los Angeles, contributing to preterm birth.