Indoor and outdoor number concentrations of fine particulate matter (PM_2.5), black carbon (BC), carbon monoxide (CO), and nitrogen dioxide (NO₂) were monitored continuously for two to seven days in 28 low-income homes in Denver, Colorado, during the 2016 and 2017 wildfire seasons. In the absence of indoor sources, all outdoor pollutant concentrations were higher than indoors except for CO. Results showed that long-range wildfire plumes elevated median indoor PM_2.5 concentrations by up to 4.6 times higher than outdoors. BC, CO, and NO₂ mass concentrations were higher indoors in homes closer to roadways compared to those further away. Four of the homes with mechanical ventilation systems had 18% higher indoor/outdoor (I/O) ratios of PM_2.5 and 4% higher I/O ratios of BC compared to other homes. Homes with exhaust stove hoods had PM_2.5 I/O ratios 49% less than the homes with recirculating hoods and 55% less than the homes with no stove hoods installed. Homes with windows open for more than 12 hours a day during sampling had indoor BC 2.4 times higher than homes with windows closed. This study provides evidence that long-range wildfire plumes, road proximity, and occupant behavior have a combined effect on indoor air quality in low-income homes.

We studied 226 low-income households as a part of the Colorado Home Energy Efficiency and Respiratory Health (CHEER) study to investigate the relationship between energy-efficiency retrofits (EERs) specific to air sealing of residential building envelopes, annual average infiltration rates (AAIR), and qualitative indicators of “healthy” homes. Blower door tests quantified the leakage area in each home, which was used to estimate the AAIR. Walk-through inspections were used to record observations of air-sealing retrofits conducted as part of Colorado’s Weatherization Assistance Program and indirect indicators of poor indoor environmental quality (IEQ) in the homes, such as visible mold or stains, visible dust on hard surfaces, vapor condensation on windows, dampness, and perceived air quality. Results showed that building characteristics like age and volume affected AAIR more significantly than air-sealing EERs. Among the air-sealing EERs, homes with the air-handler ductwork sealed and windows weather-stripped were found to have significantly lower AAIR compared to the homes without these features. Mold growth, wall stains, notably higher levels of dust, and unacceptable odor levels were more frequently reported in homes with higher AAIR, showing that leakier homes do not necessarily have better IEQ.

Consensus is growing on the need to investigate the joint impact of neighborhood-level social factors and environmental hazards on respiratory health. This study used latent profile analysis (LPA) to empirically identify distinct neighborhood subtypes according to a clustering of social factors and environmental hazards, and to examine whether those subtypes are associated with lung function. The study included 182 low-income participants who were enrolled in the Colorado Home Energy Efficiency and Respiratory Health (CHEER) study during the years 2015–2017. Distinct neighborhood typologies were identified based on analyses of 632 census tracts in the Denver-Metro and Front Range area of Colorado; neighborhood characteristics used to identify typologies included green space, traffic-related air pollution, violent and property crime, racial/ethnic composition, and socioeconomic status (SES). Generalized estimating equations were used to examine the association between neighborhood typology and lung function. We found four distinct neighborhood typologies and provide evidence that these social and environmental aspects of neighborhoods cluster along lines of advantage/disadvantage. We provide suggestive evidence of a double jeopardy situation where low-income populations living in disadvantaged neighborhoods may have decreased lung function. Using LPA with social and environmental characteristics may help to identify meaningful neighborhood subtypes and inform research on the mechanisms by which neighborhoods influence health.

Epidemiologic evidence consistently links urban air pollution exposures to health, even after adjustment for potential spatial confounding by socioeconomic position (SEP), given concerns that air pollution sources may be clustered in and around lower-SEP communities. SEP, however, is often measured with less spatial and temporal resolution than are air pollution exposures (i.e., census-tract socio-demographics vs. fine-scale spatio-temporal air pollution models). Although many questions remain regarding the most appropriate, meaningful scales for the measurement and evaluation of each type of exposure, we aimed to compare associations for multiple air pollutants and social factors against cardiovascular disease (CVD) event rates, with each exposure measured at equal spatial and temporal resolution. We found that, in multivariable census-tract-level models including both types of exposures, most pollutant–CVD associations were non-significant, while most social factors retained significance. Similarly, the magnitude of association was higher for an IQR-range difference in the social factors than in pollutant concentrations. We found that when offered equal spatial and temporal resolution, CVD was more strongly associated with social factors than with air pollutant exposures in census-tract-level analyses in New York City.

Background The opioid overdose mortality crisis in the USA is an ongoing public health epidemic. Ongoing law enforcement strategies to disrupt local unregulated drug markets can have an iatrogenic effect of increasing overdose by driving consumers towards new suppliers with unpredictable drug products of unknown potency. Methods Cross-sectional study using point-level information on law enforcement opioid-related drug seizures from property room data, opioid-related non-fatal overdose events from emergency medical services and block group-level social determinants of health data from multiple sources. Using an endemic-epidemic spatiotemporal regression model, we estimated the degree to which exposure to drug supply disruptions triggers future overdose events within small space-time distances in Indianapolis, Indiana. Results Neighbourhoods with more structural racism, economic deprivation or urban blight were associated with higher rates of non-fatal overdose. Exposure to an opioid-related drug seizure event had a significant and positive effect on the epidemic probability of non-fatal overdose. An opioid seizure that occurred within 250 m and 3 days, 250 m and 7 days, and 250 m and 14 days of an overdose event increased the risk of a new non-fatal overdose by 2.62 (rate ratio (RR)=2.62, 95% CI 1.87 to 3.67), 2.17 (RR=2.17, 95% CI 1.87 to 2.59) and 1.83 (RR=1.83, 95% CI 1.66 to 2.02), respectively. Similar spatiotemporal patterns were observed in a smaller spatial bandwidth. Conclusions Results demonstrated that overdoses exhibit a community spread process, which is exacerbated following law enforcement strategies to disrupt the unregulated drug market. We discuss decriminalisation and increasing resources that promote safer drug use to combat this public health crisis.