Dataset Information

Variability of indoor fungal microbiome of green and non-green low-income homes in Cincinnati, Ohio.

ABSTRACT: "Green" housing is designed to use low-impact materials, increase energy efficiency and improve occupant health. However, little is known about the indoor mycobiome of green homes. The current study is a subset of a multicenter study that aims to investigate the indoor environment of green homes and the respiratory health of asthmatic children. In the current study, the mycobiome in air, bed dust and floor dust was compared between green (study site) and non-green (control site), low-income homes in Cincinnati, Ohio. The samples were collected at baseline (within four months following renovation), and 12months after the baseline at the study site. Parallel sample collection was conducted in non-green control homes. Air samples were collected by PM2.5 samplers over 5-days. Bed and floor dust samples were vacuumed after the air sampling was completed. The DNA sample extracts were analyzed using ITS amplicon sequencing. Analysis indicated that there was no clear trend in the fungal communities between green and non-green homes. Instead, fungal community differences were greatest between sample types - air, bed, and floor. Microbial communities also changed substantially between sampling intervals in both green and non-green homes for all sample types, potentially indicating that there was very little stability in the mycobiomes. Research gaps remain regarding how indoor mycobiome fluctuates over time. Longer follow-up periods might elucidate the effect of green renovation on microbial load in buildings.

SUBMITTER: Coombs K

PROVIDER: S-EPMC6728913 | biostudies-other | 2018 Jan

REPOSITORIES: biostudies-other

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Variability of indoor fungal microbiome of green and non-green low-income homes in Cincinnati, Ohio.

Coombs Kanistha K Taft Diana D Ward Doyle V DV Green Brett J BJ Chew Ginger L GL Shamsaei Behrouz B Meller Jaroslaw J Indugula Reshmi R Reponen Tiina T

The Science of the total environment 20170810

"Green" housing is designed to use low-impact materials, increase energy efficiency and improve occupant health. However, little is known about the indoor mycobiome of green homes. The current study is a subset of a multicenter study that aims to investigate the indoor environment of green homes and the respiratory health of asthmatic children. In the current study, the mycobiome in air, bed dust and floor dust was compared between green (study site) and non-green (control site), low-income home ...[more]

PMID: 28803198

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Project description:ObjectivesThe condition of the home is a strong predictor of exposure to environmental contaminants, with low-income households being particularly vulnerable. Therefore, improving housing standards is a priority. Housing built to "green" standards, with improved building methods and materials, has been suggested to reduce contaminants. However, evidence is limited as to which contaminants are reduced. The Green Housing Study was conducted to address this issue. The study hypothesis was that housing built using green components has lower concentrations of environmental contaminants compared to conventional housing.MethodsA repeated-measures, 12-month cohort study was performed in three U.S. cities. Data were collected in the home at three time points throughout a year. The level of contaminants were estimated using air samples for particulate matter and black carbon, dust samples for aeroallergens and pesticides, and resident or study staff reporting evidence of mold. To investigate source(s) of PM2.5 and black carbon, multivariable models using stepwise variable selection were developed.ResultsIn adjusted generalized estimating equations (GEE) models, black carbon concentration (μg/m3) (β = -0.22, 95% CI = -0.38 to -0.06, p = 0.01), permethrin (OR = 0.28, 95% CI = 0.15-0.49, p < 0.0001), and reported mold (OR = 0.29, 95% CI = 0.13-0.68, p = 0.003) were significantly lower in green homes. Cockroach antigen was also lower in green homes (OR = 0.59, 95% CI = 0.33-1.08, p = 0.09), although not statistically significant. We found that 68% of PM2.5 was explained by dwelling type and smoking and 42% of black carbon was explained by venting while cooking and use of a gas stove.ConclusionsThis study provides quantitative data suggesting benefits of incorporating green building practices on the level of numerous environmental contaminants known to be associated with health. Occupant behavior, particularly smoking, is an important contributor to indoor air pollution.

Project description:BackgroundThe exposure of house occupants to indoor air pollutants has increased in recent decades. Among microbiological contaminants, bacterial and fungal aerosols remain poorly studied and the debate on the impact of these aerosols on respiratory health is still open. This study aimed to assess the diversity of indoor microbial communities in relationship with the health of occupants.MethodsMeasurements were taken from dwellings of 2 cohorts in Brittany (France), one with children without any pathology and the other with children and adults with asthma. Thirty dust samples were analyzed by next generation sequencing with a 16S and 18S targeted metagenomics approach. Analysis of sequencing data was performed using qiime 2, and univariate and multivariate statistical analysis using R software and phyloseq package.ResultsA total of 2,637 prokaryotic (589 at genus level) and 2,153 eukaryotic taxa were identified (856 fungal taxa (39%) and 573 metazoa (26%)). The four main bacterial phyla were identified: Proteobacteria (53%), Firmicutes (27%), Actinobacteria (11%), Bacteroidetes (8%). Among Fungi, only 136 taxa were identified at genus level. Three main fungal phyla were identified: Ascomycota (84%), Basidiomycota (12%) and Mucoromycota (3%). No bacterial nor fungal phyla were significantly associated with asthma versus control group. A significant over representation in control group versus asthma was observed for Christensenellaceae family (p-value = 0.0015, adj. p-value = 0.033). Besides, a trend for over representation in control group was observed with Dermabacteraceae family (p-value = 0.0002, adj. p-value = 0.815).ConclusionsOur findings provide evidence that dust samples harbor a high diversity of human-associated bacteria and fungi. Molecular methods such as next generation sequencing are reliable tools for identifying and tracking the bacterial and fungal diversity in dust samples, a less easy strategy for the detection of eukaryotes at least using18S metagenomics approach. This study showed that the detection of some bacteria might be associated to indoor air of asthmatic patients. Regarding fungi, a higher number of samples and sequencing with more depth could allow reaching significant signatures.

Project description:Highlights • Changes to access to care measures among low-income smokers following Medicaid expansion have not been characterized.• Health care access measures among smokers related to affordability of care and unmet needs improved following Medicaid expansion in Ohio.• The was no change in having a usual source of care, an important indicator of preventive care use.• A comprehensive improvement on access to care is essential for tobacco cessation efforts, early management of health problems, and reduction in smoking-related health care costs and disparities. Smokers are more likely to be low-income with limited access to health services. Although Medicaid expansion under the Patient Protection and Affordable Care Act improved access to care for low-income adults, long-term trends in health care access among low-income smokers remain uncharacterized. The study evaluated changes in five access measures among low-income nonelderly (19–64) adults (N = 28976) across smoking status using pooled data from a statewide survey in Ohio covering pre- (i.e., 2012) and post-Medicaid expansion periods (2015, 2017, and 2019) guided by a comprehensive framework of health care access. We found improvements in some, but not all, health care access measures among low-income smokers in the post-Medicaid-expansion period compared to the pre-expansion period. Compared to 2012, the odds for unmet dental care needs declined in 2015 (aOR = 0.67, 95 % CI = 0.45–1.01), 2017 (aOR = 0.53, 95 % CI = 0.35–0.81), and 2019 (aOR = 0.65, 95 % CI = 0.40–1.05) (p trend < 0.001). Similarly, the odds for unmet other health care needs (i.e., medical exams and supplies) were lower in 2015 (aOR = 0.64, 95 % CI = 0.39–1.06), 2017 (aOR = 0.56, 95 % CI = 0.34–0.93), and 2019 (aOR = 0.47, 95 % CI = 0.27–0.83) (p trend < 0.001). Difficulty paying medical bills was also significantly lower in 2015 (aOR = 0.62, 95 % CI = 0.43–0.89), 2017 (aOR = 0.57, 95 % CI = 0.39–0.83) and 2019 (aOR = 0.57, 95 % CI = 0.37–0.87) (p trend < 0.001). While there was notable progress in measures of affordability (i.e., paying medical bills) as well as care availability and accommodation (i.e., unmet needs), there were no meaningful changes in the approachability of care (i.e., having a usual source of care).

Dataset Information

Variability of indoor fungal microbiome of green and non-green low-income homes in Cincinnati, Ohio.

Publications

Variability of indoor fungal microbiome of green and non-green low-income homes in Cincinnati, Ohio.

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