Disparities in joint exposure to environmental and social stressors in urban households in Greater Boston.

OBJECTIVES: Understanding how environmental and social stressors cluster is critical to explaining and addressing health disparities. It remains unclear how these stressors cluster at fine spatial resolution in low to medium-income, urban households. We explored patterns of environmental and social exposures at the household-level and potential predictors of these joint exposures in two environmental justice communities in the Greater Boston area. METHODS: We recruited 150 households in Chelsea, MA and the Dorchester neighborhood of Boston, MA, between 2016 and 2019 and collected data on two domains: environmental and social stressor. For each domain, we fit Latent Class Analysis (LCA) models to exposure data to assess intra-domain variability, and cross-classified the resultant classes to identify joint exposure profiles. We compared differences in the distribution of these profiles by participants' demographic and household characteristics using χ2, Fisher's exact, Analysis of Variance, and Kruskal-Wallis tests. RESULTS: We identified two latent classes in each domain: High environmental (n = 90; 60.4%), Low environmental (n = 59; 39.6%), High Social (n = 31; 20.8%), and Low Social (n = 118; 79.2%). Cross-classification yielded four joint exposure profiles: Both Low (n = 46, 30.9%); Both High (n = 18, 12.1%); High environmental-Low Social (n = 72, 48.3%); and Low environmental-High Social (n = 13, 8.7%). Significant group differences were found by housing type (e.g., single-family vs. multi-family) (Fisher's exact p = 0.0016), housing tenure (p = 0.0007), and study site (p < 0.0001). We also observed differences by race/ethnicity, income, and education: households that were Hispanic/Latinx, below the poverty level, and with lower education were more likely to be in the Both High group. CONCLUSIONS: Our analyses confirmed that environmental and social stressors cluster in socially disadvantaged households. Housing type, housing tenure, and location of the residence were also strong predictors of cluster membership, with renter and multi-family residents at risk of high exposures to environmental and social stressors.

Development of a multidimensional housing and environmental quality index (HEQI): application to the American Housing Survey.

BACKGROUND: Substandard housing conditions and hazardous indoor environmental exposures contribute to significant morbidity and mortality worldwide. Housing indices that capture the multiple dimensions of healthy housing are important for tracking conditions and identifying vulnerable households. However, most indices focus on physical deficiencies and repair costs and omit indoor environmental exposures, as few national data sources routinely collect this information. METHODS: We developed a multidimensional Housing and Environmental Quality Index (HEQI) based on the World Health Organization's Housing and Health Guidelines and applied it to the 2019 American Housing Survey (AHS). The HEQI consisted of ten domains associated with poor health: household fuel combustion, dampness and mold, pests and allergens, lead paint risk, high indoor temperatures, low indoor temperatures, household crowding, injury hazards, inadequate water and sanitation, and ventilation. We evaluated the validity and performance of the HEQI against three housing characteristics (i.e., year built, monthly rent costs, unit satisfaction rating) and two established indices (i.e., Adequacy Index, Poor Quality Index). RESULTS: Approximately 79% (92 million) of U.S. households reported at least one HEQI domain associated with poor health (mean per household: 1.3; range: 0,8). Prevalent domains included household fuel combustion (61.4%), dampness and mold (15.9%), inadequate water and sanitation (14.3%), and injury hazards (11.9%). Pests and allergens, low indoor temperatures, and injury hazards were consistently associated with older homes, lower rent costs, and lower unit satisfaction. Compared to established housing indices, the HEQI captured four new environmental domains which enabled the identification of 57.7 million (63%) more households with environmental risk factors like mold, cockroaches, crowding, household fuel combustion, and higher building leakage. CONCLUSIONS: Indoor environmental exposures are prevalent in U.S. households and not well-captured by existing housing indices. The HEQI is a multidimensional tool that can be used to monitor indoor environmental exposures and housing quality trends in the U.S. Some domains, including radon, pesticides, asbestos, noise, and housing accessibility could not be assessed due to the lack of available data in the AHS. The mounting evidence linking residential environmental exposures with adverse health outcomes underscore the need for this data in the AHS and other national surveys.

Real-time indoor PM2.5 monitoring in an urban cohort: Implications for exposure disparities and source control.

Fine particulate matter (PM2.5) concentrations are highly variable indoors, with evidence for exposure disparities. Real-time monitoring coupled with novel statistical approaches can better characterize drivers of elevated PM2.5 indoors. We collected real-time PM2.5 data in 71 homes in an urban community of Greater Boston, Massachusetts using Alphasense OPC-N2 monitors. We estimated indoor PM2.5 concentrations of non-ambient origin using mass balance principles, and investigated their associations with indoor source activities at the 0.50 to 0.95 exposure quantiles using mixed effects quantile regressions, overall and by homeownership. On average, the majority of indoor PM2.5 concentrations were of non-ambient origin (≥77%), with a higher proportion at increasing quantiles of the exposure distribution. Major source predictors of non-ambient PM2.5 concentrations at the upper quantile (0.95) were cooking (1.4-23 µg/m3) and smoking (15 µg/m3, only among renters), with concentrations also increasing with range hood use (3.6 µg/m3) and during the heating season (5.6 µg/m3). Across quantiles, renters in multifamily housing experienced a higher proportion of PM2.5 concentrations from non-ambient sources than homeowners in single- and multifamily housing. Renters also more frequently reported cooking, smoking, spray air freshener use, and second-hand smoke exposure, and lived in units with higher air exchange rate and building density. Accounting for these factors explained observed PM2.5 exposure disparities by homeownership, particularly in the upper exposure quantiles. Our results suggest that renters in multifamily housing may experience higher PM2.5 exposures due to a combination of behavioral and building factors that are amenable to intervention.

Biological and environmental exposure monitoring of volatile organic compounds among nail technicians in the Greater Boston area.

Nail technicians are exposed to volatile organic compounds (VOCs) from nail products, but no studies have previously measured VOC biomarkers for these workers. This study of 10 nail technicians aimed to identify VOCs in nail salons and explore relationships between air concentrations and biomarkers. Personal and area air samples were collected using thermal desorption tubes during a work shift and analyzed using gas chromatography/mass spectrometry (GC/MS) for 71 VOCs. Whole blood samples were collected pre-shift and post-shift, and analyzed using GC/MS for 43 VOCs. Ventilation rates were determined using continuous CO2 measurements. Predominant air VOC levels were ethyl methacrylate (median 240 µg/m3 ), methyl methacrylate (median 205 µg/m3 ), toluene (median 100 µg/m3 ), and ethyl acetate (median 639 µg/m3 ). Blood levels were significantly higher post-shift than pre-shift for toluene (median pre-shift 0.158 µg/L and post-shift 0.360 µg/L) and ethyl acetate (median pre-shift <0.158 µg/L and post-shift 0.510 µg/L); methacrylates were not measured in blood because of their instability. Based on VOCs measured in these seven nail salons, we estimated that emissions from Greater Boston area nail salons may contribute to ambient VOCs. Ventilation rates did not always meet the ASHRAE guideline for nail salons. There is a need for changes in nail product formulation and better ventilation to reduce VOC occupational exposures.

Federal Housing Assistance and Blood Lead Levels in a Nationally Representative US Sample Age 6 and Older: NHANES, 1999-2018.

BACKGROUND: Federal housing assistance is an important policy tool to ensure housing security for low-income households. Less is known about its impact on residential environmental exposures, particularly lead. OBJECTIVES: We conducted a quasi-experimental study to investigate the association between federal housing assistance and blood lead levels (BLLs) in a nationally representative US sample age 6 y and older eligible for housing assistance. METHODS: We used the 1999-2018 National Health and Nutrition Examination Survey (NHANES) linked with US Department of Housing and Urban Development (HUD) administrative records to assess BLLs of NHANES participants with concurrent HUD housing assistance (i.e., current recipients, n=3,071) and those receiving assistance within 2 y after the survey (i.e., pseudo-waitlist recipients, n=1,235). We estimated BLL least squares geometric means (LSGMs), odds ratio (OR) for BLL ≥3.5µg/dL, and percent differences in LSGMs by HUD housing assistance status adjusting for age, sex, family income-to-poverty ratio, education, country of birth, race/ethnicity, region, and survey year. We also examined effect modification using interaction terms and stratified analyses by program type [i.e., public housing, multifamily, housing choice vouchers (HCV)], and race/ethnicity. RESULTS: Current HUD recipients had a significantly lower LSGM [1.07µg/dL; 95% confidence interval (CI): 1.02, 1.12] than pseudo-waitlist recipients (1.21 µg/dL; 95% CI: 1.14, 1.28), with an adjusted OR of 0.60 (95% CI: 0.42, 0.87) for BLL ≥3.5µg/dL. Some effect modification were observed: The protective association of HUD assistance on BLL was strongest among public housing (-19.5% LSGM; 95% CI: -27.5%, -10.7%), multifamily (-12.5% LSGM; 95% CI: -20.7%, -3.5%), and non-Hispanic White (-20.6% LSGM; 95% CI: -29.8%, -10.3%) recipients. It was weaker to null among HCV (-5.7% LSGM; 95% CI: -12.7, 1.7%), non-Hispanic Black (-1.6% LSGM; 95% CI: -8.1%, 5.4%), and Mexican American (-12.5% LSGM; 95% CI: -31.9%, 12.5%) recipients. DISCUSSION: Our research underscores the importance of social-structural determinants like federal housing assistance in providing affordable, stable, and healthy housing to very low-income households. More attention is needed to ensure housing quality and racial equity across HUD's three major housing assistance programs. https://doi.org/10.1289/EHP12645.

Household conditions, COVID-19, and equity: Insight from two nationally representative surveys.

Background: With people across the United States spending increased time at home since the emergence of COVID-19, housing characteristics may have an even greater impact on health. Therefore, we assessed associations between household conditions and COVID-19 experiences. Methods: We used data from two nationally representative surveys: the Tufts Equity Study (TES; n = 1449 in 2021; n = 1831 in 2022) and the Household Pulse Survey (HPS; n = 147,380 in 2021; n = 62,826 in 2022). In the TES, housing conditions were characterized by heating/cooling methods; smoking inside the home; visible water damage/mold; age of housing unit; and self-reported concern about various environmental factors. In TES and HPS, household size was assessed. Accounting for sampling weights, we examined associations between each housing exposure and COVID-19 outcomes (diagnosis, vaccination) using separate logistic regression models with covariates selected based on an evidence-based directed acyclic graph. Results: Having had COVID-19 was more likely among people who reported poor physical housing condition (odds ratio [OR] = 2.32; 95% confidence interval [CI] = 1.17-4.59; 2021), visible water damage or mold/musty smells (OR = 1.50; 95% CI = 1.10-2.03; 2022), and larger household size (5+ versus 1-2 people; OR = 1.53, 95% CI = 1.34-1.75, HPS 2022). COVID-19 vaccination was less likely among participants who reported smoke exposure inside the home (OR = 0.53; 95% CI = 0.31-0.90; 2022), poor water quality (OR = 0.42; 95% CI = 0.21-0.85; 2021), noise from industrial activity/construction (OR = 0.44; 95% CI = 0.19-0.99; 2022), and larger household size (OR = 0.57; 95% CI = 0.46-0.71; HPS 2022). Vaccination was also positively associated with poor indoor air quality (OR = 1.96; 95% CI = 1.02-3.72; 2022) and poor physical housing condition (OR = 2.27; 95% CI = 1.01-5.13; 2022). Certain heating/cooling sources were associated with COVID-19 outcomes. Conclusions: Our study found poor housing conditions associated with increased COVID-19 burden, which may be driven by systemic disparities in housing, healthcare, and financial access to resources during the COVID-19 pandemic.

The immigrant birthweight paradox in an urban cohort: Role of immigrant enclaves and ambient air pollution.

BACKGROUND: Foreign-born Black and Latina women on average have higher birthweight infants than their US-born counterparts, despite generally worse socioeconomic indicators and prenatal care access, i.e., "immigrant birthweight paradox" (IBP). Residence in immigrant enclaves and associated social-cultural and economic benefits may be drivers of IBP. Yet, enclaves have been found to have higher air pollution, a risk factor for lower birthweight. OBJECTIVE: We investigated the association of immigrant enclaves and children's birthweight accounting for prenatal ambient air pollution exposure. METHODS: In the Boston-based Children's HealthWatch cohort of mother-child dyads, we obtained birthweight-for-gestational-age z-scores (BWGAZ) for US-born births, 2006-2015. We developed an immigrant enclave score based on census-tract percentages of foreign-born, non-citizen, and linguistically-isolated households statewide. We estimated trimester-specific PM2.5 concentrations and proximity to major roads based residential address at birth. We fit multivariable linear regressions of BWGAZ and examined effect modification by maternal nativity. Analyses were restricted to nonsmoking women and term births. RESULTS: Foreign-born women had children with 0.176 (95% CI: 0.092, 0.261) higher BWGAZ than US-born women, demonstrating the IBP in our cohort. Immigrant enclave score was not associated with BWGAZ, even after adjusting for air pollution exposures. However, this association was significantly modified by maternal nativity (pinteraction = 0.014), in which immigrant enclave score was positively associated with BWGAZ for only foreign-born women (0.090, 95% CI: 0.007, 0.172). Proximity to major roads was negatively associated with BWGAZ (-0.018 per 10 m, 95% CI: -0.032, -0.003) and positively correlated with immigrant enclave scores. Trimester-specific PM2.5 concentrations were not associated with BWGAZ. SIGNIFICANCE: Residence in immigrant enclaves was associated with higher birthweight children for foreign-born women, supporting the role of immigrant enclaves in the IBP. Future research of the IBP should account for immigrant enclaves and assess their spatial correlation with potential environmental risk factors and protective resources.

Expanding Reach of Occupational Health Knowledge: Contributing Subject-Matter Expertise to Wikipedia as a Class Assignment.

The National Institute for Occupational Safety and Health (NIOSH) and several university programs have collaborated on a large effort to expand and improve occupational safety and health content in Wikipedia using a platform developed by Wiki Education. This article describes the initiative, student contributions, and evaluations of this effort by instructors from two universities between 2016 and 2020. The Wiki Education platform allowed instructors to set timelines and track students' progress throughout the semester while students accessed training to best expand health content in Wikipedia. Students chose topics in occupational health based on their interests and by a set of topics deemed as a priority by the "WikiProject Occupational Safety and Health." Students' contributions were peer-reviewed by instructors, NIOSH Wikipedians-in-Residence, and traditional Wikipedians. Students presented their projects in class at the end of the semester. Students from both schools expanded 55 articles, created 8 new articles, and translated 2 articles to Spanish, adding 1270 references; these articles were viewed over 8 million times by May 2020. Feedback received from the implementation suggested that students learned about science communication and digital literacy-providing valuable content on occupational health while reducing misinformation in the public domain. The process of identifying and addressing gaps in occupational health in Wikipedia requires participation and engagement toward improving access to information that otherwise would be restricted to the scientific literature, often behind a paywall. The Wikipedia assignment proved to be an engaging approach for instruction and information literacy. It helped students improve their science communication skills and digital literacy, tools that are likely to be critical for successful communication of science in their future careers.

Acculturation and endocrine disrupting chemical-associated personal care product use among US-based foreign-born Chinese women of reproductive age.

BACKGROUND: Personal care products (PCPs) are an important source of endocrine disrupting chemicals (EDCs) linked to adverse reproductive health outcomes. OBJECTIVE: We evaluated EDC-associated PCP use and acculturation among Asian women. METHODS: Our study included 227 foreign-born Chinese women ages 18-45 seeking obstetrics-gynecology care at community health centers (Boston, MA). Acculturation was measured by English-language use, length of US residence, and age at US entry. Self-reported use of PCPs (crème rinse/conditioner, shampoo, perfume/cologne, bar soap/body wash, liquid hand soap, moisturizer/lotion, colored cosmetics, sunscreen, and nail polish) in the last 48 h was collected. Latent class analysis was used to identify usage patterns. We also conducted multivariable logistic to determine the cross-sectional associations of acculturation measures and the use of individual PCP types. RESULTS: Those who used more PCP types, overall and by each type, tended to be more acculturated. Women who could speak English had 2.77 (95% CI: 1.10-7.76) times the odds of being high PCP users compared to their non-English speaking counterparts. English-language use was associated with higher odds of using perfume/cologne and nail polish. SIGNIFICANCE: Our findings give insight about EDC-associated PCP use based on acculturation status, which can contribute to changes in immigrant health and health disparities.

Phthalate metabolite exposures among immigrants living in the United States: findings from NHANES, 1999-2014.

Phthalates exposure has been linked to multiple health risks, and US immigrants may have different exposures to phthalates due to lifestyle differences. Urinary concentrations of eight phthalate metabolites (mono-ethyl phthalate [MEP], mono-n-butyl phthalate [MnBP], mono-isobutyl phthalate [MiBP], mono-(3-carboxypropyl) phthalate [MCPP], mono-benzyl phthalate [MBzP], mono-2-ethylhexyl phthalate [MEHP], mono-(2-ethyl-5-hydroxyhexyl) phthalate [MEHHP], mono-(2-ethyl-5-oxohexyl) phthalate [MEOHP]) were measured in 10318 US-born and 3511 foreign-born individuals from NHANES 1999-2014. Using multivariate adjusted linear regression, we assessed whether phthalate metabolite levels differed by nativity in the whole population, within racial/ethnic groups, and by years in the US. We also tested whether immigrant demographics predicted phthalate metabolite levels. In fully adjusted models, MEP, MnBP, and MiBP were significantly higher, and MBzP significantly lower, among immigrants than US-born participants. Among immigrants, MnBP and MiBP significantly declined with longer time in the US (Ptrend = 0.029 and Ptrend = 0.039, respectively), while MCPP and MBzP significantly rose (Ptrend = 0.019 and Ptrend = 0.043, respectively). Results within each racial/ethnic group were consistent with the whole population. Among immigrants, women had significantly higher metabolite levels than men (all p < 0.01), and MEP, MnBP, and MCPP differed by race/ethnicity. Due to higher phthalate exposures, immigrants may be especially vulnerable to phthalate-associated health problems.

Development of an in-home, real-time air pollutant sensor platform and implications for community use.

Air pollution exposure characterization has been shaped by many constraints. These include technologies that lead to insufficient coverage across space and/or time in order to characterize individual or community-level exposures with sufficient accuracy and precision. However, there is now capacity for continuous monitoring of many air pollutants using comparatively inexpensive, real-time sensors. Crucial questions remain regarding whether or not these sensors perform adequately for various potential end uses and whether performance varies over time or across ambient conditions. Performance scrutiny of sensors via lab- and field-testing and calibration across their lifetime is necessary for interpretation of data, and has important implications for end users including cost effectiveness and ease of use. We developed a comparatively lower-cost, portable, in-home air sampling platform and a guiding development and maintenance workflow that achieved our goal of characterizing some key indoor pollutants with high sensitivity and reasonable accuracy. Here we describe the process of selecting, validating, calibrating, and maintaining our platform - the Environmental Multi-pollutant Monitoring Assembly (EMMA) - over the course of our study to-date. We highlight necessary resources and consider implications for communities or researchers interested in developing such platforms, focusing on PM2.5, NO, and NO2 sensors. Our findings emphasize that lower-cost sensors should be deployed with caution, given financial and resource costs that greatly exceed sensor costs, but that selected community objectives could be supported at lesser cost and community-based participatory research strategies could be used for more wide-ranging goals.

Bayesian decision support for coding occupational injury data.

INTRODUCTION: Studies on autocoding injury data have found that machine learning algorithms perform well for categories that occur frequently but often struggle with rare categories. Therefore, manual coding, although resource-intensive, cannot be eliminated. We propose a Bayesian decision support system to autocode a large portion of the data, filter cases for manual review, and assist human coders by presenting them top k prediction choices and a confusion matrix of predictions from Bayesian models. METHOD: We studied the prediction performance of Single-Word (SW) and Two-Word-Sequence (TW) Naïve Bayes models on a sample of data from the 2011 Survey of Occupational Injury and Illness (SOII). We used the agreement in prediction results of SW and TW models, and various prediction strength thresholds for autocoding and filtering cases for manual review. We also studied the sensitivity of the top k predictions of the SW model, TW model, and SW-TW combination, and then compared the accuracy of the manually assigned codes to SOII data with that of the proposed system. RESULTS: The accuracy of the proposed system, assuming well-trained coders reviewing a subset of only 26% of cases flagged for review, was estimated to be comparable (86.5%) to the accuracy of the original coding of the data set (range: 73%-86.8%). Overall, the TW model had higher sensitivity than the SW model, and the accuracy of the prediction results increased when the two models agreed, and for higher prediction strength thresholds. The sensitivity of the top five predictions was 93%. CONCLUSIONS: The proposed system seems promising for coding injury data as it offers comparable accuracy and less manual coding. PRACTICAL APPLICATIONS: Accurate and timely coded occupational injury data is useful for surveillance as well as prevention activities that aim to make workplaces safer.