Time outdoors and residential greenness are associated with reduced systemic inflammation and allostatic load.

Contacts with nature are linked with reduced morbidity and mortality. Hypothesized pathways include relaxation, physical activity, and improved immune function. This cross-sectional study of 320 adults in central North Carolina assessed health benefits of residential greenness using allostatic load (AL) and systemic inflammation (INFL) indices, composite biomarker-based measures of physiological dysregulation and inflammation, respectively. Distance-to-residence weighted tree cover and vegetated land cover measures were estimated within 500 m of each residence; 37 biomarkers of immune, neuroendocrine, cardiovascular, and metabolic functions were dichotomized at distribution or health-based cut-offs. AL was calculated as a sum of potentially unhealthy values of all biomarkers; INFL was based on a subset of 18 immune biomarkers. Regression analysis used generalized additive models for Poisson-distributed outcome. An interquartile range (IQR) increase in tree cover was associated with 0.89 (95 % Confidence Limits 0.82; 0.97) and 0.90 (0.79; 1.03)-fold change in AL and INFL, respectively. Greater daily outdoor time was associated with reduced AL and INFL, while leisure screen time, problems with sleeping, and common chronic infections were linked with increased AL and INFL. Among 138 individuals spending more than 1 h outdoors daily, an IQR increase in tree cover was associated with 0.76 (0.67; 0.86) and 0.81 (0.65; 1.02)-fold changes in AL and INFL, respectively. Among individuals with residential tree cover above the 50th percentile, spending more than 3 h outdoors daily was associated with 0.54 (0.37; 0.78) and 0.28 (0.15; 0.54)-fold changes in AL and INFL, respectively, compared to spending less than 30 min outdoors; there were no significant effects in the low tree cover stratum. Consistent but weaker effects were observed for vegetated land cover. Interaction effects of tree and vegetative cover and time spent outdoors on AL and INFL were statistically significant. This biomarker-based approach can help to assess public health benefits of green spaces.

Environmental risk factors associated with pulmonary isolation of nontuberculous mycobacteria, a population-based study in the southeastern United States.

The prevalence of pulmonary nontuberculous mycobacteria (NTM) disease is increasing in the United States. Associations were evaluated among residents of central North Carolina between pulmonary isolation of NTM and environmental risk factors including: surface water, drinking water source, urbanicity, and exposures to soils favorable to NTM growth. Reports of pulmonary NTM isolation from patients residing in three counties in central North Carolina during 2006-2010 were collected from clinical laboratories and from the State Laboratory of Public Health. This analysis was restricted to patients residing in single family homes with a valid residential street address and conducted at the census block level (n = 13,495 blocks). Negative binomial regression models with thin-plate spline smoothing function of geographic coordinates were applied to assess effects of census block-level environmental characteristics on pulmonary NTM isolation count. Patients (n = 507) resided in 473 (3.4%) blocks within the study area. Blocks with >20% hydric soils had 26.8% (95% confidence interval (CI): 1.8%, 58.0%), p = 0.03, higher adjusted mean patient counts compared to blocks with ≤20% hydric soil, while blocks with >50% acidic soil had 24.8% (-2.4%, 59.6%), p = 0.08 greater mean patient count compared to blocks with ≤50% acidic soil. Isolation rates varied by county after adjusting for covariates. The effects of using disinfected public water supplies vs. private wells, and of various measures of urbanicity were not significantly associated with NTM. Our results suggest that proximity to certain soil types (hydric and acidic) could be a risk factor for pulmonary NTM isolation in central North Carolina.

Greater tree cover near residence is associated with reduced allostatic load in residents of central North Carolina.

BACKGROUND: Among urban residents, increased contacts with nature are associated with reduced morbidity and mortality. The concept of allostatic load, a biomarker-based composite measure of physiological dysregulation, can be applied to study subclinical benefits of exposure, and to elucidate pathways leading to improved health. OBJECTIVE: This research explored associations between residential vegetated land cover and an allostatic load index calculated using the statistical distance measure known as Mahalanobis distance. METHODS: This cross-sectional population-based study involved 186 adult residents of the Durham-Chapel Hill, North Carolina metropolitan area. Measures of tree and grass cover within 500 m of residence were derived from the U.S. Environmental Protection Agency's EnviroAtlas land cover database. Fifteen biomarkers of immune, neuroendocrine, and metabolic functions were analyzed in serum samples. Regression analysis was conducted using generalized additive models with thin-plate spline functions of geographic coordinates, adjusting for modelled traffic air pollution from local sources and sociodemographic covariates. RESULTS: The second and third tertiles of distance-weighted tree cover were associated with 14% (95% Confidence Limits 20%; 8%) and 15% (21%; 8%) reduction in adjusted median allostatic load, respectively, compared to the first tertile. The same tertiles of tree cover were also associated with 0.16 (0.03; 0.76) and 0.04 (0.01; 0.35) adjusted odds ratios of having allostatic load index above the 90th percentile of the sample distribution. Grass cover was inversely correlated with tree cover and was not associated with reduced allostatic load. CONCLUSIONS: Subclinical beneficial health effects of green spaces demonstrated in this study are consistent with reduced susceptibility to acute environmental and social stressors, and reduced risks of morbidity and mortality.

Evaluation of a Physiologically Based Pharmacokinetic (PBPK) Model for Inorganic Arsenic Exposure Using Data from Two Diverse Human Populations.

BACKGROUND: Multiple epidemiological studies exist for some of the well-studied health endpoints associated with inorganic arsenic (iAs) exposure; however, results are usually expressed in terms of different exposure/dose metrics. Physiologically based pharmacokinetic (PBPK) models may be used to obtain a common exposure metric for application in dose-response meta-analysis. OBJECTIVE: A previously published PBPK model for inorganic arsenic (iAs) was evaluated using data sets for arsenic-exposed populations from Bangladesh and the United States. METHODS: The first data set was provided by the Health Effects of Arsenic Longitudinal Study cohort in Bangladesh. The second data set was provided by a study conducted in Churchill County, Nevada, USA. The PBPK model consisted of submodels describing the absorption, distribution, metabolism and excretion (ADME) of iAs and its metabolites monomethylarsenic (MMA) and dimethylarsenic (DMA) acids. The model was used to estimate total arsenic levels in urine in response to oral ingestion of iAs. To compare predictions of the PBPK model against observations, urinary arsenic concentration and creatinine-adjusted urinary arsenic concentration were simulated. As part of the evaluation, both water and dietary intakes of arsenic were estimated and used to generate the associated urine concentrations of the chemical in exposed populations. RESULTS: When arsenic intake from water alone was considered, the results of the PBPK model underpredicted urinary arsenic concentrations for individuals with low levels of arsenic in drinking water and slightly overpredicted urinary arsenic concentrations in individuals with higher levels of arsenic in drinking water. When population-specific estimates of dietary intakes of iAs were included in exposures, the predictive value of the PBPK model was markedly improved, particularly at lower levels of arsenic intake. CONCLUSIONS: Evaluations of this PBPK model illustrate its adequacy and usefulness for oral exposure reconstructions in human health risk assessment, particularly in individuals who are exposed to relatively low levels of arsenic in water or food. https://doi.org/10.1289/EHP3096.

Gender and Racial/Ethnic Disparities: Cumulative Screening of Health Risk Indicators in 20-50 Year Olds in the United States.

This study explored potential gender and racial/ethnic disparities in overall health risk related to 24 health risk indicators selected across six domains: socioeconomic, health status and health care, lifestyle, nutritional, clinical, and environmental. Using the 2003-2006 National Health and Nutrition Examination Surveys (NHANES), it evaluated cross-sectional data for 5,024 adults in the United States. Logistic regression models were developed to estimate prevalence odds ratios (PORs) adjusted for smoking, health insurance status, and age. Analyses evaluated disparities associated with 24 indicator variables of health risk, comparing females to males and four racial/ethnic groups to non-Hispanic Whites. Non-Hispanic Blacks and Mexican Americans were at greater risk for at least 50% of the 24 health risk indicators, including measures of socioeconomic status, health risk behaviors, poor/fair self-reported health status, multiple nutritional and clinical indicators, and blood lead levels. This demonstrates that cumulative health risk is unevenly distributed across racial/ethnic groups. A similarly high percentage (46%) of the risk factors was observed in females. Females as compared to males were more likely to have lower income, lower blood calcium, poor/fair self-reported health, more poor mental health days/month, higher medication usage and hospitalizations, and higher serum levels of some clinical indicators and blood cadmium. This analysis of cumulative health risk is responsive to calls for broader-based, more integrated assessment of health disparities that can help inform community assessments and public health policy.

Factors associated with self-reported health: implications for screening level community-based health and environmental studies.

BACKGROUND: Advocates for environmental justice, local, state, and national public health officials, exposure scientists, need broad-based health indices to identify vulnerable communities. Longitudinal studies show that perception of current health status predicts subsequent mortality, suggesting that self-reported health (SRH) may be useful in screening-level community assessments. This paper evaluates whether SRH is an appropriate surrogate indicator of health status by evaluating relationships between SRH and sociodemographic, lifestyle, and health care factors as well as serological indicators of nutrition, health risk, and environmental exposures. METHODS: Data were combined from the 2003-2006 National Health and Nutrition Examination Surveys for 1372 nonsmoking 20-50 year olds. Ordinal and binary logistic regression was used to estimate odds ratios and 95 % confidence intervals of reporting poorer health based on measures of nutrition, health condition, environmental contaminants, and sociodemographic, health care, and lifestyle factors. RESULTS: Poorer SRH was associated with several serological measures of nutrition, health condition, and biomarkers of toluene, cadmium, lead, and mercury exposure. Race/ethnicity, income, education, access to health care, food security, exercise, poor mental and physical health, prescription drug use, and multiple health outcome measures (e.g., diabetes, thyroid problems, asthma) were also associated with poorer SRH. CONCLUSION: Based on the many significant associations between SRH and serological assays of health risk, sociodemographic measures, health care access and utilization, and lifestyle factors, SRH appears to be a useful health indicator with potential relevance for screening level community-based health and environmental studies.

Biological and behavioral factors modify urinary arsenic metabolic profiles in a U.S. population.

BACKGROUND: Because some adverse health effects associated with chronic arsenic exposure may be mediated by methylated arsenicals, interindividual variation in capacity to convert inorganic arsenic into mono- and di-methylated metabolites may be an important determinant of risk associated with exposure to this metalloid. Hence, identifying biological and behavioral factors that modify an individual's capacity to methylate inorganic arsenic could provide insights into critical dose-response relations underlying adverse health effects. METHODS: A total of 904 older adults (≥45 years old) in Churchill County, Nevada, who chronically used home tap water supplies containing up to 1850 µg of arsenic per liter provided urine and toenail samples for determination of total and speciated arsenic levels. Effects of biological factors (gender, age, body mass index) and behavioral factors (smoking, recent fish or shellfish consumption) on patterns of arsenicals in urine were evaluated with bivariate analyses and multivariate regression models. RESULTS: Relative contributions of inorganic, mono-, and di-methylated arsenic to total speciated arsenic in urine were unchanged over the range of concentrations of arsenic in home tap water supplies used by study participants. Gender predicted both absolute and relative amounts of arsenicals in urine. Age predicted levels of inorganic arsenic in urine and body mass index predicted relative levels of mono- and di-methylated arsenic in urine. Smoking predicted both absolute and relative levels of arsenicals in urine. Multivariate regression models were developed for both absolute and relative levels of arsenicals in urine. Concentration of arsenic in home tap water and estimated water consumption were strongly predictive of levels of arsenicals in urine as were smoking, body mass index, and gender. Relative contributions of arsenicals to urinary arsenic were not consistently predicted by concentrations of arsenic in drinking water supplies but were more consistently predicted by gender, body mass index, age, and smoking. CONCLUSIONS: These findings suggest that analyses of dose-response relations in arsenic-exposed populations should account for biological and behavioral factors that modify levels of inorganic and methylated arsenicals in urine. Evidence of significant effects of these factors on arsenic metabolism may also support mode of action studies in appropriate experimental models.

Epidemiology of nontuberculous mycobacteria isolations among central North Carolina residents, 2006-2010.

BACKGROUND: Nontuberculous mycobacteria (NTM) are environmental mycobacteria associated with a range of infections. Reports of NTM epidemiology have primarily focused on pulmonary infections and isolations, however extrapulmonary infections of the skin, soft tissues and sterile sites are less frequently described. METHODS: We comprehensively reviewed laboratory reports of NTM isolation from North Carolina residents of three counties during 2006-2010. We describe age, gender, and race of patients, and anatomic site of isolation for NTM species. RESULTS: Among 1033 patients, overall NTM isolation prevalence was 15.9/100,000 persons (13.7/100,000 excluding Mycobacterium gordonae). Prevalence was similar between genders and increased significantly with age. Extrapulmonary isolations among middle-aged black males and pulmonary isolations among elderly white females were most frequently detected. Most isolations from pulmonary sites and blood cultures were Mycobacterium avium complex; rapidly growing NTM (e.g. Mycobacterium chelonae, Mycobacterium fortuitum) were most often isolated from paranasal sinuses, wounds and skin. CONCLUSIONS: We provide the first characterization of NTM isolation prevalence in the Southeastern United States (U.S.). Variation in isolation prevalence among counties and races likely represent differences in detection, demographics and risk factors. Further characterization of NTM epidemiology is increasingly important as percentages of immunocompromised individuals and the elderly increase in the U.S.

Data-driven asthma endotypes defined from blood biomarker and gene expression data.

The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels.

Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes.

BACKGROUND: Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets. RESULTS: A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student's t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups. CONCLUSIONS: The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease.

Biological and behavioral factors modify biomarkers of arsenic exposure in a U.S. population.

Although consumption of drinking water contaminated with inorganic arsenic is usually considered the primary exposure route, aggregate exposure to arsenic depends on direct consumption of water, use of water in food preparation, and the presence in arsenicals in foods. To gain insight into the effects of biological and behavioral factors on arsenic exposure, we determined arsenic concentrations in urine and toenails in a U.S. population that uses public or private water supplies containing inorganic arsenic. Study participants were 904 adult residents of Churchill County, Nevada, whose home tap water supplies contained <3 to about 1200 µg of arsenic per liter. Biomarkers of exposure for this study were summed urinary concentrations of inorganic arsenic and its methylated metabolites (speciated arsenical), of all urinary arsenicals (total arsenical), and of all toenail arsenicals (total arsenical). Increased tap water arsenic concentration and consumption were associated with significant upward trends for urinary speciated and total and toenail total arsenical concentrations. Significant gender differences in concentrations of speciated and total arsenicals in urine and toenails reflected male-female difference in water intake. Both recent and higher habitual seafood consumption significantly increased urinary total but not speciated arsenical concentration. In a stepwise general linear model, seafood consumption significantly predicted urinary total arsenical but not urinary speciated or toenail total arsenical concentrations. Smoking behavior significantly predicted urinary speciated or total arsenical concentration. Gender, tap water arsenic concentration, and primary drinking water source significantly predicted urinary speciated and total concentrations and toenail total arsenical concentrations. These findings confirm the primacy of home tap water as a determinant of arsenic concentration in urine and toenails. However, biological and behavioral factors can modify exposure-response relations for these biomarkers. Refining estimates of the influence of these factors will permit better models of dose-response relations for this important environmental contaminant.

Allergens in household dust and serological indicators of atopy and sensitization in Detroit children with history-based evidence of asthma.

BACKGROUND: Home exposure to allergens is an important factor in the development of sensitization and subsequent exacerbations of allergic asthma. We investigated linkages among allergen exposure, immunological measurements, and asthma by examining (1) reservoir dust allergen levels in homes, (2) associations between presence of allergens in homes and sensitization status of resident children, and (3) associations between asthma status and total IgE, atopy (by Phadiatop), and positive allergen-specific tests. METHODS: The study protocol was approved by Institutional Review Boards (IRBs) of the University of North Carolina Chapel Hill; Westat, Inc.; and the US Environmental Protection Agency Human Research Protocol Office. Data were collected from questionnaires, serum analyses, and household vacuum dust. Children (n = 205) were predominately African American (AA) (85.4%) and 51.6% were asthmatic. Sera from 185 children and home dust samples (n = 141) were analyzed for total and specific IgE antibodies to allergens from cat and dog dander, cockroach, dust mites, mice, rats, and molds. RESULTS: Sixty percent of the homes had detectable levels of three or more dust allergens. The proportions of children with positive allergen-specific IgE tests were dust mite (32%), dog (28%), cat (23%), cockroach (18%), mouse (5%), rat (4%), and molds (24-36%). Children testing positive to a single allergen also had positive responses to other allergens. Those children with positive serum tests for cat, dog, and dust mite lived in homes with detectable levels of cat (51%), dog (90%), and dust mite (Der f 1) (92%) allergens. Correlations between children's specific IgE levels and dust levels were linearly related for dog (p < .04), but not for cat (p = .12) or dust mite (Der f 1) (p = .21). Odds ratios (95% CI) for the associations between asthma and serum-specific IgE were over 1.0 for cat, dog, dust mite (Der f 1), cockroach, and four types of molds. House dust allergen exposure levels, however, exhibited no differences between asthmatic and non-asthmatic homes. CONCLUSIONS: Both the co-occurrence of multiple allergens in dust and the high frequency of multiple allergen sensitizations indicate that a broad-based intervention aimed at reducing multiple allergens (pets, pests, and molds) would be more successful than any approach that aimed at reducing one type of allergen.

Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population.

BACKGROUND: Asthma and allergy represent complex phenotypes, which disproportionately burden ethnic minorities in the United States. Strong evidence for genomic factors predisposing subjects to asthma/allergy is available. However, methods to utilize this information to identify high risk groups are variable and replication of genetic associations in African Americans is warranted. METHODS: We evaluated 41 single nucleotide polymorphisms (SNP) and a deletion corresponding to 11 genes demonstrating association with asthma in the literature, for association with asthma, atopy, testing positive for food allergens, eosinophilia, and total serum IgE among 141 African American children living in Detroit, Michigan. Independent SNP and haplotype associations were investigated for association with each trait, and subsequently assessed in concert using a genetic risk score (GRS). RESULTS: Statistically significant associations with asthma were observed for SNPs in GSTM1, MS4A2, and GSTP1 genes, after correction for multiple testing. Chromosome 11 haplotype CTACGAGGCC (corresponding to MS4A2 rs574700, rs1441586, rs556917, rs502581, rs502419 and GSTP1 rs6591256, rs17593068, rs1695, rs1871042, rs947895) was associated with a nearly five-fold increase in the odds of asthma (Odds Ratio (OR) = 4.8, p = 0.007). The GRS was significantly associated with a higher odds of asthma (OR = 1.61, 95% Confidence Interval = 1.21, 2.13; p = 0.001). CONCLUSIONS: Variation in genes associated with asthma in predominantly non-African ethnic groups contributed to increased odds of asthma in this African American study population. Evaluating all significant variants in concert helped to identify the highest risk subset of this group.

Comparative microarray analysis and pulmonary changes in Brown Norway rats exposed to ovalbumin and concentrated air particulates.

The interaction between air particulates and genetic susceptibility has been implicated in the pathogenesis of asthma. The overall objective of this study was to determine the effects of inhalation exposure to environmentally relevant concentrated air particulates (CAPs) on the lungs of ovalbumin (ova) sensitized and challenged Brown Norway rats. Changes in gene expression were compared with lung tissue histopathology, morphometry, and biochemical and cellular parameters in bronchoalveolar lavage fluid (BALF). Ova challenge was responsible for the preponderance of gene expression changes, related largely to inflammation. CAPs exposure alone resulted in no significant gene expression changes, but CAPs and ova-exposed rodents exhibited an enhanced effect relative to ova alone with differentially expressed genes primarily related to inflammation and airway remodeling. Gene expression data was consistent with the biochemical and cellular analyses of the BALF, the pulmonary pathology, and morphometric changes when comparing the CAPs-ova group to the air-saline or CAPs-saline group. However, the gene expression data were more sensitive than the BALF cell type and number for assessing the effects of CAPs and ova versus the ova challenge alone. In addition, the gene expression results provided some additional insight into the TGF-beta-mediated molecular processes underlying these changes. The broad-based histopathology and functional genomic analyses demonstrate that exposure to CAPs exacerbates rodents with allergic inflammation induced by an allergen and suggests that asthmatics may be at increased risk for air pollution effects.

Total arsenic concentrations in toenails quantified by two techniques provide a useful biomarker of chronic arsenic exposure in drinking water.

Accurate quantitation of any contaminant of interest is critical for exposure assessment and metabolism studies that support risk assessment. A preliminary step in an arsenic exposure assessment study in Nevada quantified total arsenic (TAs) concentrations in tissues as biomarkers of exposure. Participants in this study (n=95) were at least 45 years old, had lived in the area for more than 20 years, and were exposed to a wide range of arsenic concentrations in drinking water (3-2,100 ppb). Concentrations of TAs in blood, urine, and toenails determined by hydride generation-atomic fluorescence spectrometry (HG-AFS) ranged from below detection to 0.03, 0.76, and 12 ppm, respectively; TAs in blood rarely exceeded the limit of detection. For comparison, TAs in toenails determined by neutron activation analysis (NAA) ranged from below detection to 16 ppm. Significant (P<0.0001) positive regressions were seen between the TAs concentration in toenails and in drinking water (adjusted r(2)=0.3557 HG-AFS, adjusted r(2)=0.3922 NAA); TAs concentrations in urine were not described by drinking water As (adjusted r(2)=0.0170, P=0.1369). Analyses of TAs in toenails by HGAFS and NAA yielded highly concordant estimates (r=0.7977, P<0.0001). These results suggest that toenails are a better biomarker of chronic As exposure than urine in the current study, because the sequestration of As in toenails provides an integration of exposure over time that does not occur in urine.