Residential bacteria and fungi identified by high-throughput sequencing and childhood respiratory health.

The objective of this study was to examine and compare environmental microbiota from dust and children's respiratory health outcomes at ages seven and twelve. At age seven, in-home visits were conducted for children enrolled in the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Floor dust was collected and analyzed for bacterial (16 S rRNA gene) and fungal (internal transcribed spacer region) microbiota. Respiratory outcomes, including physician-diagnosed asthma, wheeze, rhinitis, and aeroallergen sensitivity were assessed by physical examination and caregiver-report at ages seven and twelve. The associations between dust microbiota and respiratory outcomes were evaluated using Permanova, DESeq, and weighted quantile sum (WQS) regression models. Four types of WQS regression models were run to identify mixtures of fungi or bacteria that were associated with the absence or presence of health outcomes. For alpha or beta diversity of fungi and bacteria, no significant associations were found with respiratory health outcomes. DESeq identified specific bacterial and fungal indicator taxa that were higher or lower with the presence of different health outcomes. Most individual indicator fungal species were lower with asthma and wheeze and higher with aeroallergen positivity and rhinitis, whereas bacterial data was less consistent. WQS regression models demonstrated that a combination of species might influence health outcomes. Several heavily weighted species had a strong influence on the models, and therefore, created a microbial community that was associated with the absence or presence of asthma, wheeze, rhinitis, and aeroallergen+. Weights for specific species within WQS regression models supported indicator taxa findings. Health outcomes might be more influenced by the composition of a complex mixture of bacterial and fungal species in the indoor environment than by the absence or presence of individual species. This study demonstrates that WQS is a useful tool in evaluating mixtures in relation to potential health effects.

HEPA filtration improves asthma control in children exposed to traffic-related airborne particles.

Traffic-related airborne particles are associated with asthma morbidity. The aim of this study was to assess the impact of a high-efficiency particulate air (HEPA) filtration on the concentrations of traffic particles and the resultant effect on children with asthma. Forty-three children with asthma were enrolled in this double-blind, placebo-controlled crossover design. A HEPA air cleaner or a placebo "dummy" was placed in participants' homes for four weeks, interrupted by a one-month washout period, before crossing over to the other treatment arm for four weeks. Air sampling and health outcomes, including asthma control (ACQ) and quality of life (AQLQ) measures, were completed prior to and at the end of each treatment arm. Indoor concentrations of traffic particles were significantly reduced with the HEPA treatment but not with the "dummy" treatment. In participants with poorly controlled asthma and lower quality of life at baseline, ACQ and AQLQ scores were significantly improved (1.3 to 0.9, P = .003 and 4.9 to 5.5, P = .02, respectively) following the HEPA treatment. In this study, HEPA filtration is associated with improved clinical outcomes and quality of life measures in children with uncontrolled asthma.

Predicting Indoor Concentrations of Black Carbon in Residential Environments.

Black carbon (BC) is a descriptive term that refers to light-absorbing particulate matter (PM) produced by incomplete combustion and is often used as a surrogate for traffic-related air pollution. Exposure to BC has been linked to adverse health effects. Penetration of ambient BC is typically the primary source of indoor BC in the developed world. Other sources of indoor BC include biomass and kerosene stoves, lit candles, and charring food during cooking. Home characteristics can influence the levels of indoor BC. As people spend most of their time indoors, human exposure to BC can be associated to a large extent with indoor environments. At the same time, due to the cost of environmental monitoring, it is often not feasible to directly measure BC inside multiple individual homes in large-scale population-based studies. Thus, a predictive model for indoor BC is needed to support risk assessment in public health. In this study, home characteristics and occupant activities that potentially modify indoor levels of BC were documented in 23 homes, and indoor and outdoor BC concentrations were measured twice. The homes were located in the Cincinnati-Kentucky-Indiana tristate region and measurements occurred from September 2015 through August 2017. A linear mixed-effect model was developed to predict BC concentration in residential environments. The measured outdoor BC concentrations and the documented home characteristics were utilized as predictors of indoor BC concentrations. After the model was developed, a leave-one-out cross-validation algorithm was deployed to assess the predictive accuracy of the output. The following home characteristics and occupant activities significantly modified the concentration of indoor BC: outdoor BC, lit candles and electrostatic or high efficiency particulate air (HEPA) filters in heating, ventilation and air conditioning (HVAC) systems. Predicted indoor BC concentrations explained 78% of the variability in the measured indoor BC concentrations. The data show that outdoor BC combined with home characteristics can be used to predict indoor BC levels with reasonable accuracy.

Ten questions concerning the implications of carpet on indoor chemistry and microbiology.

Carpet and rugs currently represent about half of the United States flooring market and offer many benefits as a flooring type. How carpets influence our exposure to both microorganisms and chemicals in indoor environments has important health implications but is not well understood. The goal of this manuscript is to consolidate what is known about how carpet impacts indoor chemistry and microbiology, as well as to identify the important research gaps that remain. After describing the current use of carpet indoors, questions focus on five specific areas: 1) indoor chemistry, 2) indoor microbiology, 3) resuspension and exposure, 4) current practices and future needs, and 5) sustainability. Overall, it is clear that carpet can influence our exposures to particles and volatile compounds in the indoor environment by acting as a direct source, as a reservoir of environmental contaminants, and as a surface supporting chemical and biological transformations. However, the health implications of these processes are not well known, nor how cleaning practices could be optimized to minimize potential negative impacts. Current standards and recommendations focus largely on carpets as a primary source of chemicals and on limiting moisture that would support microbial growth. Future research should consider enhancing knowledge related to the impact of carpet in the indoor environment and how we might improve the design and maintenance of this common material to reduce our exposure to harmful contaminants while retaining the benefits to consumers.

Effectiveness of a portable air cleaner in removing aerosol particles in homes close to highways.

Outdoor traffic-related airborne particles can infiltrate a building and adversely affect the indoor air quality. Limited information is available on the effectiveness of high efficiency particulate air (HEPA) filtration of traffic-related particles. Here, we investigated the effectiveness of portable HEPA air cleaners in reducing indoor concentrations of traffic-related and other aerosols, including black carbon (BC), PM2.5 , ultraviolet absorbing particulate matter (UVPM) (a marker of tobacco smoke), and fungal spores. This intervention study consisted of a placebo-controlled cross-over design, in which a HEPA cleaner and a placebo "dummy" were placed in homes for 4-weeks each, with 48-hour air sampling conducted prior to and during the end of each treatment period. The concentrations measured for BC, PM2.5 , UVPM, and fungal spores were significantly reduced following HEPA filtration, but not following the dummy period. The indoor fraction of BC/PM2.5 was significantly reduced due to the HEPA cleaner, indicating that black carbon was particularly impacted by HEPA filtration. This study demonstrates that HEPA air purification can result in a significant reduction of traffic-related and other aerosols in diverse residential settings.

Transmission of SARS-CoV-2 in the workplace: Key findings from a rapid review of the literature.

At the beginning of the COVID-19 pandemic, the primary route of transmission of the SARS-CoV-2 virus was not well understood. Research gathered from other respiratory infectious diseases, including other coronaviruses, was the basis for the initial perceptions for transmission of SARS-CoV-2. To better understand transmission of SARS-CoV-2, a rapid literature review was conducted from literature generated March 19, 2020, through September 23, 2021. 18,616 unique results were identified from literature databases and screened. Of these, 279 key articles were reviewed and abstracted covering critical topics such as environmental/workplace monitoring, sampling and analytical method evaluation, and the ability of the virus to remain intact and infectious during sampling. This paper describes the results of the rapid literature review, which evaluated pathways that contribute to transmission as well as the strengths and limitations of current sampling approaches. This review also evaluates how different factors, including environmental conditions and surface characteristics, could impact the transmission potential of SARS-CoV-2. A continual rapid review in the midst of a pandemic proved particularly useful for quickly understanding the transmission parameters of the virus and enabled us to comprehensively assess literature, respond to workplace questions, and evaluate our understanding as the science evolved. Air and surface sampling with the accompanying analytical methods were not generally effective in recovering SARS-CoV-2 viable virus or RNA in many likely contaminated environments. In light of these findings, the development of validated sampling and analysis methods is critical for determining worker exposure to SARS-CoV-2 and to assess the impact of mitigation efforts.

Associations of observed home dampness and mold with the fungal and bacterial dust microbiomes.

The objective of this analysis was to examine and compare quantitative metrics of observed dampness and mold, including visible mold and moisture damage, and fungal and bacterial microbiomes. In-home visits were conducted at age 7 for children enrolled in the Cincinnati Childhood Allergy and Air Pollution Study. Trained study staff evaluated the primary residence and measured total areas of visible moisture and mold damage in the home. Floor dust was collected and archived. Archived dust samples collected from each home (n = 178) were extracted and analyzed using bacterial (16S rRNA gene) and fungal (internal transcribed spacer region) sequencing. Fungi were also divided into moisture requirement categories of xerophiles, mesophiles, and hydrophiles. Data analyses used Spearman's correlation, Kruskal-Wallis, Permanova, DESeq, and negative binomial regression models. Comparing high moisture or mold damage to no damage, five fungal species and two bacterial species had higher concentrations (absolute abundance) and six fungal species and three bacterial species had lower concentrations. Hydrophilic and mesophilic fungi showed significant dose-related increases with increasing moisture damage and mold damage, respectively. When comparing alpha or beta diversity of fungi and bacteria across mold and moisture damage levels, no significant associations or differences were found. Mold and moisture damage did not affect diversity of fungal and bacterial microbiomes. Instead, both kinds of damage were associated with changes in species composition of both bacterial and fungal microbiomes, indicating that fungal and bacterial communities in the home might be influenced by one another as well as by mold or moisture in the home.

Field sampling of indoor bioaerosols.

Because bioaerosols are related to adverse health effects in exposed humans and indoor environments represent a unique framework of exposure, concerns about indoor bioaerosols have risen over recent years. One of the major issues in indoor bioaerosol research is the lack of standardization in the methodology, from air sampling strategies and sample treatment to the analytical methods applied. The main characteristics to consider in the choice of indoor sampling methods for bioaerosols are the sampler performance, the representativeness of the sampling, and the concordance with the analytical methods to be used. The selection of bioaerosol collection methods is directly dependent on the analytical methods, which are chosen to answer specific questions raised while designing a study for exposure assessment. In this review, the authors present current practices in the analytical methods and the sampling strategies, with specificity for each type of microbe (fungi, bacteria, archaea and viruses). In addition, common problems and errors to be avoided are discussed. Based on this work, recommendations are made for future efforts towards the development of viable bioaerosol samplers, standards for bioaerosol exposure limits, and making association studies to optimize the use of the big data provided by high-throughput sequencing methods.

Quantitative and semiquantitative estimates of mold exposure in infancy and childhood respiratory health.

BACKGROUND: Previous epidemiologic studies of dampness and mold relied on metrics that did not fully assess exposure-response relationships. Our objective was to examine quantitative metrics of dampness and mold during infancy and respiratory health outcomes during childhood. METHODS: In-home visits were conducted before age 1 for children in the Cincinnati Childhood Allergy and Air Pollution Study. Respiratory outcomes included age 3 wheeze and age 7 asthma and wheeze. The associations between home exposure and respiratory outcomes were evaluated for 779 children using logistic regression adjusting for household income, neighborhood socioeconomic status, and the presence of pests. RESULTS: Children residing in homes with ≥0.29 m2 of moisture damage were significantly more likely to have wheezing at age 3 and persistent wheeze through age 7 (adjusted odds ratio [aOR] = 2.2; 95% confidence interval [CI] = 1.0, 4.3 and aOR = 3.2; CI = 1.3, 7.5, respectively). Additionally, homes having ≥0.19 m2 of mold damage were associated with wheezing at age 3 and early transient wheeze assessed at age 7 (aOR = 2.9; CI = 1.3, 6.4 and aOR = 3.5; CI = 1.5, 8.2, respectively). Mold damage <0.19 m2 and moisture damage <0.29 m2 were not associated with health outcomes. Mold and moisture damage were also not associated with asthma. CONCLUSION: Our data indicate that only the highest categories analyzed for mold (≥0.19 m2) and moisture damage (≥0.29 m2) in homes at age 1 were significantly associated with wheeze at ages 3 and 7; however, data below these levels were too sparse to assess the shape of the relationship or explore potential health-relevant thresholds.

Indoor particulate matter and lung function in children.

People generally spend more time indoors than outdoors resulting in a higher proportion of exposure to particulate matter (PM) occurring indoors. Consequently, indoor PM levels, in contrast to outdoor PM levels, may have a stronger relationship with lung function. To test this hypothesis, indoor and outdoor PM2.5 and fungal spore data were simultaneously collected from the homes of forty-four asthmatic children aged 10-16 years. An optical absorption technique was utilized on the collected PM2.5 mass to obtain concentrations of black carbon (BC) and ultraviolet light absorbing particulate matter, (UVPM; a marker of light absorbing PM2.5 emitted from smoldering organics). Enrolled children completed spirometry after environmental measurements were made. Given the high correlation between PM2.5, BC, and UVPM, principal component analysis was used to obtain uncorrelated summaries of the measured PM. Separate linear mixed-effect models were developed to estimate the association between principal components of the PM variables and spirometry values, as well as the uncorrelated original PM variables and spirometry values. A one-unit increase in the first principal component variable representing indoor PM (predominantly composed of UVPM and PM2.5) was associated with 4.1% decrease (99% CI = -6.9, -1.4) in FEV1/FVC ratio. 11.3 µg/m3 increase in indoor UVPM was associated with 6.4% and 14.7% decrease (99% CI = -10.4, -2.4 and 99% CI = -26.3, -2.9, respectively) in percent predicted FEV1/FVC ratio and FEF25-75 respectively. Additionally, 17.7 µg/m3 increase in indoor PM2.5 was associated with 6.1% and 12.9% decrease (99% CI = -10.2, -1.9 and 99% CI = -24.9, -1.0, respectively) in percent predicted FEV1/FVC ratio and FEF25-75, respectively. Outdoor PM, indoor BC, and indoor fungal spores were not significantly associated with lung function. The results indicate that indoor PM is more strongly associated with lung function in children with asthma as compared with outdoor PM.

Combining sensor-based measurement and modeling of PM2.5 and black carbon in assessing exposure to indoor aerosols.

Accurate, cost-effective methods are needed for rapid assessment of traffic-related air pollution (TRAP). Typically, real-time data of particulate matter (PM) from portable sensors have been adjusted using data from reference methods such as gravimetric measurement to improve accuracy. The objective of this study was to create a correction factor or linear regression model for the real-time measurements of the RTI's Micro Personal Exposure Monitor (MicroPEM™) and AethLab's microAeth® black carbon (AE51) sensor to generate accurate real-time data for PM2.5 (PM2.5RT) and black carbon (BCRT) in Cincinnati metropolitan homes. The two sensors and an SKC PM2.5 Personal Modular impactor were collocated in 44 indoor sampling events for 2 days in residences near major roadways. The reference filter-based analyses conducted by a laboratory included particle mass (SKC PM2.5 and MicroPEM™ PM2.5) and black carbon (SKC BC); these methods are more accurate than real-time sensors but are also more cumbersome and costly. For PM2.5, the average correction factor, a ratio of gravimetric to real-time, for the MicroPEM™ PM2.5 and SKC PM2.5 utilizing the PM2.5RT and was 0.94 and 0.83, respectively, with a coefficient of variation (CV) of 84% and 52%, respectively; the corresponding linear regression model had a CV of 54% and 25%. For BC, the average correction factor utilizing the BCRT and SKC BC was 0.74 with a CV of 36% with the associated linear regression model producing a CV of 56%. The results from this study will help ensure that the real-time exposure monitors are capable of detecting an estimated PM2.5 after an appropriate statistical model is applied.

Comparison of indoor air sampling and dust collection methods for fungal exposure assessment using quantitative PCR.

Evaluating fungal contamination indoors is complicated because of the many different sampling methods utilized. In this study, fungal contamination was evaluated using five sampling methods and four matrices for results. The five sampling methods were a 48 hour indoor air sample collected with a Button™ inhalable aerosol sampler and four types of dust samples: a vacuumed floor dust sample, newly settled dust collected for four weeks onto two types of electrostatic dust cloths (EDCs) in trays, and a wipe sample of dust from above floor surfaces. The samples were obtained in the bedrooms of asthmatic children (n = 14). Quantitative polymerase chain reaction (qPCR) was used to analyze the dust and air samples for the 36 fungal species that make up the Environmental Relative Moldiness Index (ERMI). The results from the samples were compared by four matrices: total concentration of fungal cells, concentration of fungal species associated with indoor environments, concentration of fungal species associated with outdoor environments, and ERMI values (or ERMI-like values for air samples). The ERMI values for the dust samples and the ERMI-like values for the 48 hour air samples were not significantly different. The total cell concentrations of the 36 species obtained with the four dust collection methods correlated significantly (r = 0.64-0.79, p < 0.05), with the exception of the vacuumed floor dust and newly settled dust. In addition, fungal cell concentrations of indoor associated species correlated well between all four dust sampling methods (r = 0.68-0.86, p < 0.01). No correlation was found between the fungal concentrations in the air and dust samples primarily because of differences in concentrations of Cladosporium cladosporioides Type 1 and Epicoccum nigrum. A representative type of dust sample and a 48 hour air sample might both provide useful information about fungal exposures.