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The influx of immigrants to urban areas throughout the United States has raised concerns about accessibility of safe, affordable housing and the health consequences of poor-quality housing, particularly among immigrant children. We conducted a population-based study of home environmental conditions among recently immigrated Mexican families (weighted n = 473), generally of low socioeconomic status, and the health conditions of their children, in an urban industrial area north of Denver, Colorado. The majority of recent immigrants had low socioeconomic status; virtually all had household incomes below the Colorado median ($50,841). Approximately one quarter of homes were overcrowded. Adverse environmental conditions were present across recent immigrant homes. These conditions include dampness or mold (44%), pests (28%), and minimal to no ventilation potential (26%), all of which are associated with asthma and atopic diseases. At least one of these three environmental hazards was found in 67% of homes; multiple hazards were present in 27% of homes. Children of recent immigrant families had active symptoms within the past 12 months suggestive of asthma (4%) and atopic disorders (10%); however, fewer than 2% had been diagnosed with these conditions. The prevalence of asthma and atopic symptoms among Mexican immigrant children, albeit lower than in other low income and minority communities, is partially explained by housing conditions. Many of the conditions identified (e.g., pest infestation, mold resulting from plumbing leaks, and lack of exhaust fans) are amenable to low cost interventions. Solutions to address unhealthy housing conditions among recent immigrants must be multi-faceted and include strategies that target household-level improvements and access to health care. [ABSTRACT FROM AUTHOR]

Previous research has found increased home ventilation, which may affect health by altering the composition of indoor air, is associated with improvement of respiratory health, but evidence linking home ventilation to objectively measured lung function is sparse. The Colorado Home Energy Efficiency and Respiratory health (CHEER) study, a cross-sectional study of low-income, urban, nonsmoking homes across the Northern Front Range of Colorado, USA, focused on elucidating this link. We used a multipoint depressurization blower door test to measure the air tightness of the homes and calculate the annual average infiltration rate (AAIR). Lung function tests were administered to eligible participants. We analyzed data from 253 participants in 187 homes with two or more acceptable spirometry tests. We used generalized estimating equations to model forced expiratory volume in 1 s (FEV 1 ), forced vital capacity (FVC), and FEV 1 /FVC z-scores as a function of AAIR. AAIRs ranged from 0.10 to 1.98 air changes per hour. Mean z-scores for FEV 1 , FVC, and FEV 1 /FVC were -0.57, 0.32, and -0.43, respectively. AAIR was positively associated with increased FEV 1 /FVC z-scores, such that a 1-unit change in AAIR corresponded to a half of a standard deviation in lung function (β = 0.51, CI: 0.02-0.99). These associations were strongest for healthy populations and weaker for those with asthma and asthma-like symptoms. AAIR was not associated with FEV 1 or FVC. Our study is the first in the United States to link home ventilation by infiltration to objectively measured lung function in low-income, urban households.

Indoor and outdoor number concentrations of fine particulate matter (PM 2.5 ), black carbon (BC), carbon monoxide (CO), and nitrogen dioxide (NO 2 ) 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 NO 2 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.

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.

Odor pollution was identified as a top priority of the community of North Denver. Previous studies that investigated the impact of air pollution in North Denver focused on adverse health effects, rather than mental well-being. This study assessed the impact of odors from industrial sources on the subjective well-being (SWB) of North Denver residents, and of four similar communities in Colorado for comparison. An online survey was sent to participants from Greeley, Fort Collins, Fort Lupton, North Denver, and Pueblo, asking questions about SWB and odors in their areas ( n = 351). The evaluation of SWB was performed using a novel approach that appraises three aspects of SWB. This approach of evaluating SWB has not been used in odor exposure studies. A proportional odds logistic regression model was used to estimate nine measures of SWB. The results showed that participants who reported that the air is very fresh or the odor is highly acceptable had higher levels of SWB. This association suggests that residents who live in areas exposed to strong industrial odors had lower levels of SWB. A subset of participants in this study took the survey four times in one year. Longitudinal analysis showed that evaluative satisfaction was slightly associated with seasonality. Both satisfaction with how life turned out and satisfaction with standards of living slightly increased during the fourth quarter of the year. The study also found that four of the nine measures can be used to represent SWB in future studies. Two of those measures were evaluative SWB, and the other two were positive hedonic SWB measures. A comparison between the five communities showed that well-being levels in North Denver and Greeley were not significantly different than those in Fort Collins or Fort Lupton. The comparison, however, showed that Pueblo had the lowest levels of well-being among all communities.

Background: Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5 chemical components. Daily concentrations of PM2.5 components were measured over five years in Denver to investigate whether specific PM2.5 components are associated with daily mortality., Methods: Daily counts of total and cause-specific deaths were obtained for the 5-county Denver metropolitan region from 2003 through 2007. Daily 24-hour concentrations of PM2.5, elemental carbon (EC), organic carbon (OC), sulfate and nitrate were measured at a central residential monitoring site. Using generalized additive models, we estimated relative risks (RRs) of daily death counts for daily PM2.5 and four PM2.5 component concentrations at single and distributed lags between the current and three previous days, while controlling for longer-term time trend and meteorology., Results: RR of total non-accidental mortality for an inter-quartile increase of 4.55 μg/m(3) in PM2.5 distributed over 4 days was 1.012 (95 % confidence interval: 0.999, 1.025); RRs for EC and OC were larger (1.024 [1.005, 1.043] and 1.020 [1.000, 1.040] for 0.33 and 1.67 μg/m(3) increases, respectively) than those for sulfate and nitrate. We generally did not observe associations with cardiovascular and respiratory mortality except for associations with ischemic heart disease mortality at lags 3 and 0-3 depending on the component. In addition, there were associations with cancer mortality, particularly for EC and OC, possibly reflecting advanced deaths of a frail population., Conclusions: PM2.5 components possibly from combustion-related sources are more strongly associated with daily mortality than are secondary inorganic aerosols.

Flood-damaged homes typically have elevated microbial loads, and their occupants have an increased incidence of allergies, asthma, and other respiratory ailments, yet the microbial communities in these homes remain under-studied. Using culture-independent approaches, we characterized bacterial and fungal communities in homes in Boulder, CO, USA 2-3 months after the historic September, 2013 flooding event. We collected passive air samples from basements in 50 homes (36 flood-damaged, 14 non-flooded), and we sequenced the bacterial 16S rRNA gene (V4-V5 region) and the fungal ITS1 region from these samples for community analyses. Quantitative PCR was used to estimate the abundances of bacteria and fungi in the passive air samples. Results indicate significant differences in bacterial and fungal community composition between flooded and non-flooded homes. Fungal abundances were estimated to be three times higher in flooded, relative to non-flooded homes, but there were no significant differences in bacterial abundances. Penicillium (fungi) and Pseudomonadaceae and Enterobacteriaceae (bacteria) were among the most abundant taxa in flooded homes. Our results suggest that bacterial and fungal communities continue to be affected by flooding, even after relative humidity has returned to baseline levels and remediation has removed any visible evidence of flood damage.

In studies of coarse particulate matter (PM10-2.5), mass concentrations are often estimated through the subtraction of PM2.5 from collocated PM10 tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM10-2.5 estimation when using the possible combinations of PM10 and PM2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural-Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM10-2.5 mass and spatial characteristics due to the very low semivolatile PM10-2.5 concentrations in Colorado. Estimation using either a PM2.5 or PM10 monitor without FDMS introduced absolute biases of 2.4 microg/m3 (25%) to -2.3 microg/m3 (-24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM2.5 TEOM and PM10 TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM2.5 from total PM2.5 concentrations. By estimating nonvolatile PM2.5 concentrations from this relationship, PM10-2.5 was calculated as the difference between nonvolatile PM10 and PM2.5 concentrations.

To evaluate the utility and consistency of different speciation data sets in source apportionment of PM(2.5), positive matrix factorization (PMF) coupled with a bootstrap technique for uncertainty assessment was applied to four different 1-year data sets composed of bulk species, bulk species and water-soluble elements (WSE), bulk species and organic molecular markers (OMM), and all species. The five factors resolved by using only the bulk species best reproduced the observed concentrations of PM(2.5) components. Combining WSE with bulk species as PMF inputs also produced five factors. Three of them were linked to soil, road dust, and processed dust, and together contributed 26.0% of reconstructed PM(2.5) mass. A 7-factor PMF solution was identified using speciated OMM and bulk species. The EC/sterane and summertime/selective aliphatic factors had the highest contributions to EC (39.0%) and OC (53.8%), respectively. The nine factors resolved by including all species as input data are consistent with those from the previous two solutions (WSE and bulk species, OMM and bulk species) in both factor profiles and contributions (r = 0.88-1.00). The comparisons across different solutions indicate that the selection of input data set may depend on the PM components or sources of interest for specific source-oriented health study.

Wildfires and prescribed burns are receiving increasing attention as sources of fine particulate matter (PM2.5). The goal of this research project was to understand the impact of mitigation strategies for residences impacted by scheduled prescribed burns and wildfires. Pairs of residences were solicited to have PM2.5 concentrations monitored inside and outside of their houses during four fires. The effect of using air cleaners on indoor PM2.5 was investigated, as well as the effect of keeping windows closed. Appropriately sized air cleaners were provided to one of each pair of residences; occupants of all of the residences were asked to keep windows shut and minimize opening of exterior doors. Additionally, residents were asked to record all of the activities that may be a source of particulate matter, such as cooking and cleaning. Measurements were made during one prescribed burn and three wildfires during the 2002 fire season. Outdoor 24-hr average PM2.5 concentrations ranging from 6 to 38 microg/m3 were measured during the fires, compared with levels of 2-5 microg/m3 during background measurements when no fires were burning. During the fires, PM2.5 was < 3 microg/m3 inside all of the houses with air cleaners installed. This corresponds with a decrease of 63-88% in homes with the air cleaners operating when compared with homes without air cleaners. In the homes without the air cleaners, measured indoor concentrations were 58-100% of the concentrations measured outdoors.