The Maternal and Infant Environmental Health Riskscape study of perinatal disparities in greater Houston: rationale, study design and participant profiles.

Introduction: The Maternal and Infant Environmental Health Riskscape (MIEHR) Center was established to address the interplay among chemical and non-chemical stressors in the biological, physical, social, and built environments that disproportionately impact perinatal health among Black pregnant people in a large and diverse urban area with documented disparities in the U.S. Methods: The MIEHR cohort is recruiting non-Hispanic Black and non-Hispanic white pregnant people who deliver their infants at major obstetric hospitals in Houston, Texas. At enrollment, all participants are asked to provide urine samples for chemical [metals, cotinine, and polycyclic aromatic hydrocarbons (PAHs)] analyses and blood samples. A subset of the cohort is asked to provide oral and vaginal swabs, and fecal samples. Questionnaire and electronic health record data gather information about residential address history during pregnancy, pregnancy history and prenatal care, sociodemographic and lifestyle factors, experiences of discrimination and stress, and sources of social support. Using information on where a participant lived during their pregnancy, features of their neighborhood environment are characterized. We provide summaries of key individual- and neighborhood-level features of the entire cohort, as well as for Black and white participants separately. Results: Between April 2021 and February 2023, 1,244 pregnant people were recruited. Nearly all participants provided urine samples and slightly less than half provided blood samples. PAH exposure patterns as assessed on 47% of participants thus far showed varying levels depending on metabolite as compared to previous studies. Additionally, analyses suggest differences between Black and white pregnant people in experiences of discrimination, stress, and levels of social support, as well as in neighborhood characteristics. Discussion: Our findings to date highlight racial differences in experiences of discrimination, stress, and levels of support, as well as neighborhood characteristics. Recruitment of the cohort is ongoing and additional neighborhood metrics are being constructed. Biospecimens will be analyzed for metals and PAH metabolites (urine samples), miRNAs (plasma samples) and the microbiome (oral swabs). Once enrollment ends, formal assessments are planned to elucidate individual- and neighborhood-level features in the environmental riskscape that contribute to Black-White disparities in perinatal health.

Relation of prenatal and postnatal PM2.5 exposure with cognitive and motor function among preschool-aged children.

The literature informing susceptible periods of exposure on children's neurodevelopment is limited. We evaluated the impacts of pre- and postnatal fine particulate matter (PM2.5) exposure on children's cognitive and motor function among 1303 mother-child pairs in the Spanish INMA (Environment and Childhood) Study. Random forest models with temporal back extrapolation were used to estimate daily residential PM2.5 exposures that we averaged across 1-week lags during the prenatal period and 4-week lags during the postnatal period. The McCarthy Scales of Children's Abilities (MSCA) were administered around 5 years to assess general cognitive index (GCI) and several subscales (verbal, perceptual-performance, memory, fine motor, gross motor). We applied distributed lag nonlinear models within the Bayesian hierarchical framework to explore periods of susceptibility to PM2.5 on each MSCA outcome. Effect estimates were calculated per 5 µg/m3 increase in PM2.5 and aggregated across adjacent statistically significant lags using cumulative ß (ßcum) and 95% Credible Intervals (95%CrI). We evaluated interactions between PM2.5 with fetal growth and child sex. We did not observe associations of PM2.5 exposure with lower GCI scores. We found a period of susceptibility to PM2.5 on fine motor scores in gestational weeks 1-9 (ßcum = -2.55, 95%CrI = -3.53,-1.56) and on gross motor scores in weeks 7-17 (ßcum = -2.27,95%CrI = -3.43,-1.11) though the individual lags for the latter were only borderline statistically significant. Exposure in gestational week 17 was weakly associated with verbal scores (ßcum = -0.17, 95%CrI = -0.26,-0.09). In the postnatal period (from age 0.5-1.2 years), we observed a window of susceptibility to PM2.5 on lower perceptual-performance (ß = -2.42, 95%CrI = -3.37,-1.46). Unexpected protective associations were observed for several outcomes with exposures in the later postnatal period. We observed no evidence of differences in susceptible periods by fetal growth or child sex. Preschool-aged children's motor function may be particularly susceptible to PM2.5 exposures experienced in utero whereas the first year of life was identified as a period of susceptibility to PM2.5 for children's perceptual-performance.

Susceptible windows of prenatal and postnatal fine particulate matter exposures and attention-deficit hyperactivity disorder symptoms in early childhood.

Few prior studies have explored windows of susceptibility to fine particulate matter (PM2.5) in both the prenatal and postnatal periods and children's attention-deficit/hyperactivity disorder (ADHD) symptoms. We analyzed data from 1416 mother-child pairs from the Spanish INMA (INfancia y Medio Ambiente) Study (2003-2008). Around 5 years of age, teachers reported the number of ADHD symptoms (i.e., inattention, hyperactivity/impulsivity) using the ADHD Diagnostic and Statistical Manual of Mental Disorders. Around 7 years of age, parents completed the Conners' Parent Rating Scales, from which we evaluated the ADHD index, cognitive problems/inattention, hyperactivity, and oppositional subscales, reported as age- and sex-standardized T-scores. Daily residential PM2.5 exposures were estimated using a two-stage random forest model with temporal back-extrapolation and averaged over 1-week periods in the prenatal period and 4-week periods in the postnatal period. We applied distributed lag non-linear models within the Bayesian hierarchical model framework to identify susceptible windows of prenatal or postnatal exposure to PM2.5 (per 5-µg/m3) for ADHD symptoms. Models were adjusted for relevant covariates, and cumulative effects were reported by aggregating risk ratios (RRcum) or effect estimates (ßcum) across adjacent susceptible windows. A similar susceptible period of exposure to PM2.5 (1.2-2.9 and 0.9-2.7 years of age, respectively) was identified for hyperactivity/impulsivity symptoms assessed ~5 years (RRcum = 2.72, 95% credible interval [CrI] = 1.98, 3.74) and increased hyperactivity subscale ~7 years (ßcum = 3.70, 95% CrI = 2.36, 5.03). We observed a susceptibility period to PM2.5 on risk of hyperactivity/impulsivity symptoms ~5 years in gestational weeks 16-22 (RRcum = 1.36, 95% CrI = 1.22, 1.52). No associations between PM2.5 exposure and other ADHD symptoms were observed. We report consistent evidence of toddlerhood as a susceptible window of PM2.5 exposure for hyperactivity in young children. Although mid-pregnancy was identified as a susceptible period of exposure on hyperactivity symptoms in preschool-aged children, this association was not observed at the time children were school-aged.

Data to Action: Community-Based Participatory Research to Address Concerns about Metal Air Pollution in Overburdened Neighborhoods near Metal Recycling Facilities in Houston.

BACKGROUND: Exposures to environmental contaminants can be influenced by social determinants of health. As a result, persons living in socially disadvantaged communities may experience disproportionate health risks from environmental exposures. Mixed methods research can be used to understand community-level and individual-level exposures to chemical and nonchemical stressors contributing to environmental health disparities. Furthermore, community-based participatory research (CBPR) approaches can lead to more effective interventions. OBJECTIVES: We applied mixed methods to identify environmental health perceptions and needs among metal recyclers and residents living in disadvantaged neighborhoods near metal recycling facilities in Houston, Texas, in a CBPR study, Metal Air Pollution Partnership Solutions (MAPPS). Informed by what we learned and our previous findings from cancer and noncancer risk assessments of metal air pollution in these neighborhoods, we developed an action plan to lower metal aerosol emissions from metal recycling facilities and enhance community capacity to address environmental health risks. METHODS: Key informant interviews, focus groups, and community surveys were used to identify environmental health concerns of residents. A diverse group from academia, an environmental justice advocacy group, the community, the metal recycling industry, and the local health department collaborated and translated these findings, along with results from our prior risk assessments, to inform a multifaceted public health action plan. RESULTS: An evidence-based approach was used to develop and implement neighborhood-specific action plans. Plans included a voluntary framework of technical and administrative controls to reduce metal emissions in the metal recycling facilities, direct lines of communication among residents, metal recyclers, and local health department officials, and environmental health leadership training. DISCUSSION: Using a CBPR approach, health risk assessment findings based on outdoor air monitoring campaigns and community survey results informed a multipronged environmental health action plan to mitigate health risks associated with metal air pollution. https://doi.org/10.1289/EHP11405.

Susceptible windows of exposure to fine particulate matter and fetal growth trajectories in the Spanish INMA (INfancia y Medio Ambiente) birth cohort.

While prior studies report associations between fine particulate matter (PM2.5) exposure and fetal growth, few have explored temporally refined susceptible windows of exposure. We included 2328 women from the Spanish INMA Project from 2003 to 2008. Longitudinal growth curves were constructed for each fetus using ultrasounds from 12, 20, and 34 gestational weeks. Z-scores representing growth trajectories of biparietal diameter, femur length, abdominal circumference (AC), and estimated fetal weight (EFW) during early (0-12 weeks), mid- (12-20 weeks), and late (20-34 weeks) pregnancy were calculated. A spatio-temporal random forest model with back-extrapolation provided weekly PM2.5 exposure estimates for each woman during her pregnancy. Distributed lag non-linear models were implemented within the Bayesian hierarchical framework to identify susceptible windows of exposure for each outcome and cumulative effects [ßcum, 95% credible interval (CrI)] were aggregated across adjacent weeks. For comparison, general linear models evaluated associations between PM2.5 averaged across multi-week periods (i.e., weeks 1-11, 12-19, and 20-33) and fetal growth, mutually adjusted for exposure during each period. Results are presented as %change in z-scores per 5 µg/m3 in PM2.5, adjusted for covariates. Weeks 1-6 [ßcum = -0.77%, 95%CrI (-1.07%, -0.47%)] were identified as a susceptible window of exposure for reduced late pregnancy EFW while weeks 29-33 were positively associated with this outcome [ßcum = 0.42%, 95%CrI (0.20%, 0.64%)]. A similar pattern was observed for AC in late pregnancy. In linear regression models, PM2.5 exposure averaged across weeks 1-11 was associated with reduced late pregnancy EFW and AC; but, positive associations between PM2.5 and EFW or AC trajectories in late pregnancy were not observed. PM2.5 exposures during specific weeks may affect fetal growth differentially across pregnancy and such associations may be missed by averaging exposure across multi-week periods, highlighting the importance of temporally refined exposure estimates when studying the associations of air pollution with fetal growth.

Maternal occupational exposure to chemicals and child cognitive function.

BACKGROUND: Limited data exist regarding child neurodevelopment in relation to maternal occupational exposure to endocrine-disrupting chemicals (EDCs). METHODS: We included 1058 mother-child pairs from the INfancia y Medio Ambiente (INMA) project (2003-2008). Using a job-exposure matrix, exposure probability scores for ten EDC groups were assigned to each mother based on her longest held job during pregnancy. At the child's 5-year visit, the McCarthy Scales of Children's Abilities was administered, yielding the general cognitive index and scales for specific cognitive domains. We analyzed region-specific associations between EDC exposures and each outcome separately using adjusted linear regression and combined region-specific effect estimates using random-effects meta-analyses. RESULTS: Approximately 24% of women were exposed to at least one EDC group, but exposure to most individual EDC groups was low (<5%). Maternal organic solvent exposure was associated with lower quantitative scores among children (-5.8 points, 95% confidence interval: -11.0, -0.5). Though statistically non-significant, exposures to polycyclic aromatic hydrocarbons, phthalates, alkylphenolic compounds, and miscellaneous chemicals were associated with poorer offspring performance for most or all cognitive domains. CONCLUSIONS: This study found limited evidence for a role of maternal occupational EDC exposures on child cognition. Further research is needed to better characterize exposures among pregnant workers. IMPACT: Using data from a prospective birth cohort, we help fill an important research gap regarding the potential consequences of work-related exposure to endocrine-disrupting chemicals (EDCs) among pregnant women on child neurodevelopment. We expand on existing literature-largely limited to pesticide and organic solvent exposures-by using a job-exposure matrix to estimate exposure to several EDC groups. We found limited evidence of an association between maternal occupational EDC exposure and children's overall cognition. We did observe specific associations between exposure to organic solvents and lower quantitative reasoning scores.

Maternal occupational exposures and fetal growth in a Spanish birth cohort.

While the epidemiologic literature suggests certain maternal occupational exposures may be associated with reduced measures of size at birth, the occupational literature employing fetal biometry data to assess fetal growth is sparse. The present study examines associations between maternal occupational exposures and ultrasound-measured fetal growth. We included 1,739 singleton pregnancies from the INfancia y Medio Ambiente (INMA) project (2003-2008). At 32 weeks of pregnancy, interviewers ascertained mothers' employment status and assessed job-related physical loads, work schedules, and job strain during pregnancy. Job titles were linked to a job-exposure matrix to estimate exposure to 10 endocrine disrupting chemical (EDC) groups. We calculated z-scores from longitudinal growth curves representing trajectories from 0-12, 12-20 and 20-34 gestational weeks for abdominal circumference (AC), biparietal diameter (BPD), femur length (FL), and estimated fetal weight (EFW). Linear mixed models clustered by IMNA region (i.e., Gipuzkoa, Sabadell, Valencia) were used to examine associations between occupational exposures and fetal growth. Effect estimates are presented as percentage change in fetal growth. There was limited evidence of associations between work-related non-chemical stressors and fetal growth. We observed associations of similar magnitude between multiple EDC groups and decreased EFW trajectories during 20-34 gestational weeks (phthalates: -1.4% [-3.5, 0.6%]; alkylphenolic compounds (APCs): -1.1% [-2.3, 0.1%]; miscellaneous chemicals: -1.5% [-3.7, 0.8%]), while miscellaneous chemicals were associated with increased BPD from 12-20 weeks (2.1% [0.8, 3.5%]). Notably, 67% of women exposed to phthalates were hairdressers; 68% of women exposed to APCs worked as domestic cleaners. In conclusion, we found limited evidence that maternal occupational exposures impact fetal growth. Further research should consider the combined impact of multiple workplace exposures.

Identifying Sensitive Windows of Exposure to NO2 and Fetal Growth Trajectories in a Spanish Birth Cohort.

BACKGROUND: We previously identified associations between trimester-specific NO2 exposures and reduced fetal growth in the Spanish INfancia y Medio Ambiente (INMA) project. Here, we use temporally refined exposure estimates to explore the impact of narrow (weekly) windows of exposure on fetal growth. METHODS: We included 1,685 women from INMA with serial ultrasounds at 12, 20, and 34 gestational weeks. We measured biparietal diameter (BPD), femur length, and abdominal circumference (AC) and from them calculated estimated fetal weight (EFW). We calculated z-scores describing trajectories of each parameter during early (0-12 weeks), mid (12-20 weeks), and late (20-34 weeks) pregnancy, based on longitudinal growth curves from mixed-effects models. We estimated weekly NO2 exposures at each woman's residence using land-use regression models. We applied distributed lag nonlinear models to identify sensitive windows of exposure. We present effect estimates as the percentage change in fetal growth per 10 µg/m3 increase in NO2 exposure, and we calculated cumulative effect estimates by aggregating estimates across adjacent lags. RESULTS: We identified weeks 5-12 as a sensitive window for NO2 exposure on late EFW (cumulative ß = -3.0%; 95% CI = -4.1%, -1.9%). We identified weeks 6-19 as a sensitive window for late growth in BPD (cumulative ß = -2.0%; 95% CI = -2.7%, -1.4%) and weeks 8-13 for AC (cumulative ß = -0.68%; 95% CI = -0.97%, -0.40%). We found suggestive evidence that third trimester NO2 exposure is associated with increased AC, BPD, and EFW growth in late pregnancy. CONCLUSIONS: Our findings are consistent with the hypothesis that NO2 exposure is associated with alterations in growth of EFW, BPD, and AC dependent on the specific timing of exposure during gestation.

Effects of Road Traffic on the Accuracy and Bias of Low-Cost Particulate Matter Sensor Measurements in Houston, Texas.

Although PM2.5 measurements of low-cost particulate matter sensors (LCPMS) generally show moderate and strong correlations with those from research-grade air monitors, the data quality of LCPMS has not been fully assessed in urban environments with different road traffic conditions. We examined the linear relationships between PM2.5 measurements taken by an LCPMS (Dylos DC1700) and two research grade monitors, a personal environmental monitor (PEM) and the GRIMM 11R, in three different urban environments, and compared the accuracy (slope) and bias of these environments. PM2.5 measurements were carried out at three locations in Houston, Texas (Clinton Drive largely with diesel trucks, US-59 mostly with gasoline vehicles, and a residential home with no major sources of traffic emissions nearby). The slopes of the regressions of the PEM on Dylos and Grimm measurements varied by location (e.g., PEM/Dylos slope at Clinton Drive = 0.98 (R2 = 0.77), at US-59 = 0.63 (R2 = 0.42), and at the residence = 0.29 (R2 = 0.31)). Although the regression slopes and coefficients differed across the three urban environments, the mean percent bias was not significantly different. Using the correct slope for LCPMS measurements is key for accurately estimating ambient PM2.5 mass in urban environments.

Effects of aerosol particle size on the measurement of airborne PM2.5 with a low-cost particulate matter sensor (LCPMS) in a laboratory chamber.

Previous validation studies found a good linear correlation between the low-cost particulate matter sensors (LCPMS) and other research grade particulate matter (PM) monitors. This study aimed to determine if different particle size bins of PM would affect the linear relationship and agreement between the Dylos DC1700 (LCPMS) particle count measurements (converted to PM2.5 mass concentrations) and the Grimm 11R (research grade instrument) mass concentration measurements. Three size groups of PM2.5 (mass median aerodynamic diameters (MMAD): < 1 µm, 1-2 µm, and > 2 µm) were generated inside a laboratory chamber, controlled for temperature and relative humidity, by dispersing sodium chloride crystals through a nebulizer. A linear regression comparing 1-min average PM2.5 particle counts from the Dylos DC1700 (Dylos) to the Grimm 11R (Grimm) mass concentrations was estimated by particle size group. The slope for the linear regression was found to increase as MMAD increased (< 1 µm, 0.75 (R2 = 0.95); 1-2 µm, 0.90 (R2 = 0.93); and > 2 µm, 1.03 (R2 = 0.94). The linear slopes were used to convert Dylos counts to mass concentration, and the agreement between converted Dylos mass and Grimm mass was estimated. The absolute relative error between converted Dylos mass and the Grimm mass was smaller in the < 1 µm group (16%) and 1-2 µm group (16%) compared to the > 2 µm group (32%). Therefore, the bias between converted Dylos mass and Grimm mass varied by size group. Future studies examining particle size bins over a wider range of coarse particles (> 2.5 µm) would provide useful information for accurately converting LCPMS counts to mass concentration.

Responding to Natural and Industrial Disasters: Partnerships and Lessons Learned.

OBJECTIVES: The aim of this study was to provide insights learned from disaster research response (DR2) efforts following Hurricane Harvey in 2017 to launch DR2 activities following the Intercontinental Terminals Company (ITC) fire in Deer Park, Texas, in 2019. METHODS: A multidisciplinary group of academic, community, and government partners launched a myriad of DR2 activities. RESULTS: The DR2 response to Hurricane Harvey focused on enhancing environmental health literacy around clean-up efforts, measuring environmental contaminants in soil and water in impacted neighborhoods, and launching studies to evaluate the health impact of the disaster. The lessons learned after Harvey enabled rapid DR2 activities following the ITC fire, including air monitoring and administering surveys and in-depth interviews with affected residents. CONCLUSIONS: Embedding DR2 activities at academic institutions can enable rapid deployment of lessons learned from one disaster to enhance the response to subsequent disasters, even when those disasters are different. Our experience demonstrates the importance of academic institutions working with governmental and community partners to support timely disaster response efforts. Efforts enabled by such experience include providing health and safety training and consistent and reliable messaging, collecting time-sensitive and critical data in the wake of the event, and launching research to understand health impacts and improve resiliency.

Heavy metal pollution of soils and risk assessment in Houston, Texas following Hurricane Harvey.

In August 2017, after Hurricane Harvey made landfall, almost 52 inches of rain fell during a three-day period along the Gulf Coast Region of Texas, including Harris County, where Houston is located. Harris County was heavily impacted with over 177,000 homes and buildings (approximately 12 percent of all buildings in the county) experiencing flooding. The objective of this study was to measure 13 heavy metals in soil in residential areas and to assess cancer and non-cancer risk for children and adults after floodwaters receded. Between September and November 2017, we collected 174 surface soil samples in 10 communities, which were classified as "High Environmental Impact" or "Low Environmental Impact" communities, based on a composite metric of six environmental parameters. A second campaign was conducted between May 2019 and July 2019 when additional 204 soil samples were collected. Concentrations of metals at both sampling campaigns were higher in High Environmental Impact communities than in Low Environmental Impact communities and there was little change in metal levels between the two sampling periods. The Pollution Indices of lead (Pb), zinc, copper, nickel, and manganese in High Environmental Impact communities were significantly higher than those in Low Environmental Impact communities. Further, cancer risk estimates in three communities for arsenic through soil ingestion were greater than 1 in 1,000,000. Although average soil Pb was lower than the benchmark of the United States Environmental Protection Agency, the hazard indices for non-cancer outcomes in three communities, mostly attributed to Pb, were greater than 1. Health risk estimates for children living in these communities were greater than those for adults.

Designing Equitable, Transparent Community-Engaged Disaster Research.

Disaster research faces significant infrastructure challenges: regional and federal coordination, access to resources, and community collaboration. Disasters can lead to chemical exposures that potentially impact human health and cause concern in affected communities. Community-engaged research, which incorporates local knowledge and voices, is well-suited for work with communities that experience impacts of environmental exposures following disasters. We present three examples of community-engaged disaster research (CEnDR) following oil spills, hurricanes, and wildfires, and their impact on long-term social, physical, and technical community infrastructure. We highlight the following CEnDR structures: researcher/community networks; convenient research tools; adaptable data collection modalities for equitable access; and return of data.

Air Pollution, Residential Greenness and Metabolic Dysfunction during Early Pregnancy in the INfancia y Medio Ambiente (INMA) Cohort.

Despite extensive study, the role of air pollution in gestational diabetes remains unclear, and there is limited evidence of the beneficial impact of residential greenness on metabolic dysfunction during pregnancy. We used data from mothers in the Spanish INfancia y Medio Ambiente (INMA) Project from 2003-2008. We obtained spatiotemporally resolved estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposures in early pregnancy and estimated residential greenness using satellite-based Normal Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding the mother's residence. We applied logistic regression models to evaluate associations between each of the three exposures of interest and (a) glucose intolerance and (b) abnormal lipid levels. We found limited evidence of associations between increases in PM2.5 and NO2 exposures and the metabolic outcomes. Though not statistically significant, high PM2.5 exposure (≥25 µg/m3) was associated with increased odds of glucose intolerance (OR = 1.16, 95% CI: 0.82, 1.63) and high cholesterol (OR = 1.14, 95% CI: 0.90, 1.44). High NO2 exposure (≥39.8 µg/m3) was inversely associated with odds of high triglycerides (OR = 0.70, 95% CI: 0.45, 1.08). Whereas NDVI was not associated with glucose intolerance, odds of high triglycerides were increased, although the results were highly imprecise. Results were unchanged when the air pollutant variables were included in the regression models. Given the equivocal findings in our study, additional investigations are needed to assess effects of air pollution and residential greenness on metabolic dysfunction during pregnancy.

Population-Based Estimates of SARS-CoV-2 Seroprevalence in Houston, Texas as of September 2020.

BACKGROUND: In contrast to studies that relied on volunteers or convenience sampling, there are few population-based severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence investigations and most were conducted early in the pandemic. The health department of the fourth largest US city recognized that sound estimates of viral impact were needed to inform decision making. METHODS: Adapting standardized disaster research methodology, in September 2020 the city was divided into high and low strata based on reverse-transcriptase polymerase chain reaction (RT-PCR) positivity rates; census block groups within each stratum were randomly selected with probability proportional to size, followed by random selection of households within each group. Using 2 immunoassays, the proportion of infected individuals was estimated for the city, by positivity rate and sociodemographic and other characteristics. The degree of underascertainment of seroprevalence was estimated based on RT-PCR-positive cases. RESULTS: Seroprevalence was estimated to be 14% with near 2-fold difference in areas with high (18%) versus low (10%) RT-PCR positivity rates and was 4 times higher compared to case-based surveillance data. CONCLUSIONS: Seroprevalence was higher than previously reported and greater than estimated from RT-PCR data. Results will be used to inform public health decisions about testing, outreach, and vaccine rollout.

Houston hurricane Harvey health (Houston-3H) study: assessment of allergic symptoms and stress after hurricane Harvey flooding.

BACKGROUND: In August 2017, Hurricane Harvey caused unprecedented flooding across the greater Houston area. Given the potential for widespread flood-related exposures, including mold and sewage, and the emotional and mental toll caused by the flooding, we sought to evaluate the short- and long-term impact of flood-related exposures on the health of Houstonians. Our objectives were to assess the association of flood-related exposures with allergic symptoms and stress among Houston-area residents at two time points: within approximately 30 days (T1) and 12 months (T2) after Hurricane Harvey's landfall. METHODS: The Houston Hurricane Harvey Health (Houston-3H) Study enrolled a total of 347 unique participants from four sites across Harris County at two times: within approximately 1-month of Harvey (T1, n = 206) and approximately 12-months after Harvey (T2, n = 266), including 125 individuals who participated at both time points. Using a self-administered questionnaire, participants reported details on demographics, flood-related exposures, and health outcomes, including allergic symptoms and stress. RESULTS: The majority of participants reported hurricane-related flooding in their homes at T1 (79.1%) and T2 (87.2%) and experienced at least one allergic symptom after the hurricane (79.4% at T1 and 68.4% at T2). In general, flood-exposed individuals were at increased risk of upper respiratory tract allergic symptoms, reported at both the T1 and T2 time points, with exposures to dirty water and mold associated with increased risk of multiple allergic symptoms. The mean stress score of study participants at T1 was 8.0 ± 2.1 and at T2, 5.1 ± 3.2, on a 0-10 scale. Participants who experienced specific flood-related exposures reported higher stress scores when compared with their counterparts, especially 1 year after Harvey. Also, a supplementary paired-samples analysis showed that reports of wheezing, shortness of breath, and skin rash did not change between T1 and T2, though other conditions were less commonly reported at T2. CONCLUSION: These initial Houston-3H findings demonstrate that flooding experiences that occurred as a consequence of Hurricane Harvey had lasting impacts on the health of Houstonians up to 1 year after the hurricane.

The Post Hurricane Harvey Respiratory Protection Training Program.

OBJECTIVES: This study evaluated the effectiveness of an outreach program which included safety training and the distribution of personal protection kits in the Houston area in the aftermath of Hurricane Harvey. METHODS: Outreach: 71 volunteers conducted training sessions at 19 different sites and distributed a total of 1187 kits. Follow-up study: We conducted telephonic interviews to collect data on respiratory symptoms and obtain perceptions of the quality of the safety training provided among 83 participants. RESULTS: Participants reported an increase in airway symptoms four weeks after Hurricane Harvey. Outreach efforts were felt to be effective by a majority of participants. CONCLUSION: Future studies may adopt some of the best practices from our training efforts in terms of utilizing a combination of verbal demonstrations and written training guidelines on proper respirator usage.

Particle air pollution and gestational diabetes mellitus in Houston, Texas.

BACKGROUND: There is mixed evidence implicating prenatal exposure to particulate matter <2.5 µm in aerodynamic diameter (PM2.5) in the risk of gestational diabetes mellitus (GDM) and only one study has examined exposure to PM2.5 constituents, which vary with location because of different emission sources. METHODS: We conducted a retrospective cohort study of singleton live births in Harris County, Texas from 2008 to 2013. With data from the Texas Commission on Environmental Quality (TCEQ), we spatially interpolated maternal exposures to total and speciated PM2.5, nitrogen dioxide (NO2) and ozone (O3) over the 12-week preconception period and trimesters 1 and 2. We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between pre-conception and pregnancy exposures to total and speciated PM2.5 and odds of GDM, adjusted for temperature and maternal covariates. We also evaluated confounding from NO2 and O3 exposures in multi-pollutant models. RESULTS: An interquartile range (IQR) increase in total PM2.5 exposure was associated with elevated odds for developing GDM over the preconception (adjusted OR = 1.09, 95% CI: 1.06, 1.12), first trimester (OR = 1.13, 95% CI: 1.10, 1.17) and second trimester (OR = 1.13, 95% CI: 1.09, 1.17) periods. Effect estimates increased with adjustment for NO2 and O3. We observed modest increases in odds of GDM for IQR increases in first trimester ammonium ion PM2.5 (OR = 1.03, 95% CI: 1.00, 1.05) and sulfate PM2.5 (OR = 1.03, 95% CI: 1.00, 1.05) exposures, as well as preconception Cr PM2.5 exposures (OR = 1.05, 95% CI: 1.02, 1.07). CONCLUSION: Exposures to PM2.5, before and during pregnancy were associated with elevated odds of GDM. Mitigating air pollution exposures may reduce the risk of GDM and its long-term implications for maternal and child health.