High Traffic Roads and Adverse Birth Outcomes: Comparing Births Upwind and Downwind of the Same Road.

Traffic related air pollution is a major concern for perinatal health. Determining causal associations, however, is difficult since high-traffic areas tend to correspond with lower socioeconomic neighborhoods and other environmental exposures. To overcome confounding, we compared pregnant individuals living downwind and upwind of the same high-traffic road. We leveraged vital statistics data for Texas from 2007-2016 (n=3,570,272 births) and computed hourly wind estimates for residential addresses within 500 m of high-traffic roads (i.e., annual average daily traffic greater than 25,000) (10.9% of births). We matched pregnant individuals predominantly upwind to pregnant neighbors downwind of the same road segment (n=37,631 pairs). Living downwind was associated with an 11.6 gram (95% CI: -18.01, -5.21) decrease in term birth weight. No associations were observed with low term birth weight, preterm birth, or very preterm birth. In distance-stratified models, living downwind within 50 m was associated with a -36.3 gram (95% CI: -67.74, -4.93) decrease in term birth weight and living 51-100m downwind was associated with an odds ratio of 3.68 (95% CI: 1.71, 7.90) for very preterm birth. These results suggest traffic air pollution is associated with adverse birth outcomes, with steep distance decay gradients around major roads.

Roadway construction as a natural experiment to examine air pollution impacts on infant health.

Traffic-related air pollution (TRAP) poses a significant public health risk that is associated with adverse birth outcomes. Large roadway infrastructure projects present a natural experiment to examine how resulting congestion change is associated with adverse birth outcomes for nearby populations. This study is designed to examine the influence of living close to a roadway before, during, and after a construction project using a difference-in-differences design. We integrated data on all large roadway construction projects (defined as widening of existing roads, building new roads, improving bridges, installing intelligent transportation systems, improving intersections, and installing or upgrading traffic signals) in Texas from 2007 to 2016 with Vital Statistic data for all births with residential addresses within 1 km of construction projects. Our outcomes included term low birth weight, term birth weight, preterm birth, and very preterm birth. Using a difference-in-differences design, we included births within 3 years of construction start and 2 years of construction end. In our main model, the exposed group is limited to pregnant individuals residing within 300 m of a construction project, and the control group includes those living within 300-1000 m from a project. We used regression models to estimate the influence of construction on infant health. We included 1,360 large roadway construction projects linked to 408,979 births. During construction, we found that the odds of term low birth weight increased by 19% (95% CI: 1.05, 1.36). However, we saw little evidence of an association for other birth outcomes. Contrary to our hypothesis of decreased TRAP after construction ends, we did not observe consistent improvements post-construction for pregnant individuals living within 300 m. Continued consideration of the influence of traffic congestion programs on birth outcomes is necessary to inform future policy decisions.

Exposure to Residential Greenness, Perceived Stress, and Depressive Symptoms in a North American Preconception Cohort.

BACKGROUND: /Aims: Studies suggest that greater exposure to natural vegetation (i.e., greenness) is associated with better mental health. However, there is limited research on greenness and mental health in the preconception period, a critical window of exposure in the life course. We investigated the associations of residential greenness with perceived stress and depressive symptoms using cross-sectional data from a cohort of pregnancy planners. METHODS: From 2013 to 2019, we enrolled female-identified participants aged 21-45 years who were trying to conceive without the use of fertility treatment into a North American preconception cohort study (Pregnancy Study Online [PRESTO]). On the baseline questionnaire, participants completed the 10-item Perceived Stress Scale (PSS) and the Major Depression Inventory (MDI). Using geocoded addresses, we estimated residential greenness exposure via satellite imagery (Normalized Difference Vegetation Index [NDVI]) in a 100m buffer. We estimated mean differences and 95% confidence intervals for the association of greenness with perceived stress and depression scores using linear regression models, adjusting for individual and neighborhood sociodemographic characteristics. We also evaluated the extent to which associations were modified by urbanicity and neighborhood socioeconomic status (SES). RESULTS: Among 9,718 participants, mean age was 29.9 years, 81.5% identified as non-Hispanic White, 25% had household incomes <$50,000, and mean neighborhood income was $61,932. In adjusted models, higher greenness was associated with lower stress and depression scores (mean difference per interquartile range in greenness: -0.20, 95% CI: -0.39, -0.01; and -0.19, 95% CI: -0.48, 0.10, respectively). The association was stronger among residents of lower SES neighborhoods in urban areas (PSS: -0.57, 95% CI: -1.00, -0.15; MDI: -0.72, 95% CI: -1.40, -0.04). CONCLUSIONS: Higher greenness exposure was associated with lower stress and depressive symptoms among pregnancy planners, particularly in lower-SES neighborhoods.

Organophosphate ester flame retardants and plasticizers in house dust and mental health outcomes among Canadian mothers: A nested prospective cohort study in CHILD.

Organophosphate ester flame retardants and plasticizers (OPEs) are common exposures in modern built environments. Toxicological models report that some OPEs reduce dopamine and serotonin in the brain. Deficiencies in these neurotransmitters are associated with anxiety and depression. We hypothesized that exposure to higher concentrations of OPEs in house dust would be associated with a greater risk of depression and stress in mothers across the prenatal and postpartum periods. We conducted a nested prospective cohort study using data collected on mothers (n = 718) in the CHILD Cohort Study, a longitudinal multi-city Canadian birth cohort (2008-2012). OPEs were measured in house dust sampled at 3-4 months postpartum. Maternal depression and stress were measured at 18 and 36 weeks gestation and 6 months and 1 year postpartum using the Centre for Epidemiologic Studies for Depression Scale (CES-D) and Perceived Stress Scale (PSS). We used linear mixed models to examine the association between a summed Z-Score OPE index and continuous depression and stress scores. In adjusted models, one standard deviation increase in the OPE Z-score index was associated with a 0.07-point (95% CI: 0.01, 0.13) increase in PSS score. OPEs were not associated with log-transformed CES-D (ß: 0.63%, 95% CI: -0.18%, 1.46%). The effect of OPEs on PSS score was strongest at 36 weeks gestation and weakest at 1 year postpartum. We observed small increases in maternal perceived stress levels, but not depression, with increasing OPEs measured in house dust during the prenatal and early postpartum period in this cohort of Canadian women. Given the prevalence of prenatal and postpartum anxiety and the ubiquity of OPE exposures, additional research is warranted to understand if these chemicals affect maternal mental health.

Ambient air pollution and rate of spontaneous abortion.

Spontaneous abortion (SAB), defined as a pregnancy loss before 20 weeks of gestation, affects up to 30% of conceptions, yet few modifiable risk factors have been identified. We estimated the effect of ambient air pollution exposure on SAB incidence in Pregnancy Study Online (PRESTO), a preconception cohort study of North American couples who were trying to conceive. Participants completed questionnaires at baseline, every 8 weeks during preconception follow-up, and in early and late pregnancy. We analyzed data on 4643 United States (U.S.) participants and 851 Canadian participants who enrolled during 2013-2019 and conceived during 12 months of follow-up. We used country-specific national spatiotemporal models to estimate concentrations of particulate matter <2.5 µm (PM2.5), nitrogen dioxide (NO2), and ozone (O3) during the preconception and prenatal periods at each participant's residential address. On follow-up and pregnancy questionnaires, participants reported information on pregnancy status, including SAB incidence and timing. We fit Cox proportional hazards regression models with gestational weeks as the time scale to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of time-varying prenatal concentrations of PM2.5, NO2, and O3 with rate of SAB, adjusting for individual- and neighborhood-level factors. Nineteen percent of pregnancies ended in SAB. Greater PM2.5 concentrations were associated with a higher incidence of SAB in Canada, but not in the U.S. (HRs for a 5 µg/m3 increase = 1.29, 95% CI: 0.99, 1.68 and 0.94, 95% CI: 0.83, 1.08, respectively). NO2 and O3 concentrations were not appreciably associated with SAB incidence. Results did not vary substantially by gestational weeks or season at risk. In summary, we found little evidence for an effect of residential ambient PM2.5, NO2, and O3 concentrations on SAB incidence in the U.S., but a moderate positive association of PM2.5 with SAB incidence in Canada.

Indoor and Personal PM2.5 Samples Differ in Chemical Composition and Alter Zebrafish Behavior Based on Primary Fuel Source.

Fine particulate matter (PM2.5) exposure has been linked to diverse human health impacts. Little is known about the potential heterogeneous impacts of PM2.5 generated from different indoor fuel sources and how exposure differs between personal and indoor environments. Therefore, we used PM2.5 collected by one stationary sampler in a kitchen and personal samplers (female and male participants), in homes (n = 24) in Kheri, India, that used either biomass or liquified petroleum gas (LPG) as primary fuel sources. PM2.5 samples (pooled by fuel type and monitor placement) were analyzed for oxidative potential and chemical composition, including elements and 125 organic compounds. Zebrafish (Danio rerio) embryos were acutely exposed to varying concentrations of PM2.5 and behavioral analyses were conducted. We found relatively high PM2.5 concentrations (5-15 times above World Health Organization daily exposure guidelines) and varied human health-related chemical composition based on fuel type and monitor placement (up to 15% carcinogenic polycyclic aromatic hydrocarbon composition). Altered biological responses, including changes to mortality, morphology, and behavior, were elicited by exposure to all sample types. These findings reveal that although LPG is generally ranked the least harmful compared to biomass fuels, chemical characteristics and biological impacts were still present, highlighting the need for further research in determining the safety of indoor fuel sources.

Ethnoracial Disparities in Nitrogen Dioxide Pollution in the United States: Comparing Data Sets from Satellites, Models, and Monitors.

In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15-50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5-15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.

A cross-sectional analysis of ambient fine particulate matter (PM2.5) exposure and haemoglobin levels in children aged under 5 years living in 36 countries.

Low haemoglobin (Hb) concentrations and anaemia in children have adverse effects on development and functioning, some of which may have consequences in later life. Exposure to ambient air pollution is reported to be associated with anaemia, but there is little evidence specific to low- and middle-income countries (LMICs), where childhood anaemia prevalence is greatest. We aimed to determine if long-term ambient fine particulate matter (≤2.5 µm in aerodynamic diameter [PM2.5]) exposure was associated with Hb levels and the prevalence of anaemia in children aged <5 years living in 36 LMICs. We used Demographic and Health Survey data, collected between 2010 and 2019, which included blood Hb measurements. Satellite-derived estimates of annual average PM2.5 was the main exposure variable, which was linked to children's area of residence. Anaemia was defined according to standard World Health Organization guidelines (Hb < 11 g/dL). The association of PM2.5 with Hb levels and anaemia prevalence was examined using multivariable linear and logistic regression models, respectively. We examined whether the effects of ambient PM2.5 were modified by a child's sex and age, household wealth index, and urban/rural place of residence. Models were adjusted for relevant covariates, including other outdoor pollutants and household cooking fuel. The study included 154,443 children, of which 89,904 (58.2%) were anaemic. The country-level prevalence of anaemia ranged from 15.8% to 87.9%. Mean PM2.5 exposure was 33.0 (±21.6) µg/m3. The adjusted model showed that a 10 µg/m3 increase in annual PM2.5 concentration was associated with greater odds of anaemia (OR = 1.098 95% CI: 1.087, 1.109). The same increase in PM2.5 was associated with a decrease in average Hb levels of 0.075 g/dL (95% CI: 0.081, 0.068). There was evidence of effect modification by household wealth index and place of residence, with greater adverse effects in children from lower wealth quintiles and children in rural areas. Exposure to annual PM2.5 was cross-sectionally associated with decreased blood Hb levels, and greater risk of anaemia, in children aged <5 years living in 36 LMICs.

Application of an Ultra-Low-Cost Passive Sampler for Light-Absorbing Carbon in Mongolia.

Low-cost, long-term measures of air pollution concentrations are often needed for epidemiological studies and policy analyses of household air pollution. The Washington passive sampler (WPS), an ultra-low-cost method for measuring the long-term average levels of light-absorbing carbon (LAC) air pollution, uses digital images to measure the changes in the reflectance of a passively exposed paper filter. A prior publication on WPS reported high precision and reproducibility. Here, we deployed three methods to each of 10 households in Ulaanbaatar, Mongolia: one PurpleAir for PM2.5; two ultrasonic personal aerosol samplers (UPAS) with quartz filters for the thermal-optical analysis of elemental carbon (EC); and two WPS for LAC. We compared multiple rounds of 4-week-average measurements. The analyses calibrating the LAC to the elemental carbon measurement suggest that 1 µg of EC/m3 corresponds to 62 PI/month (R2 = 0.83). The EC-LAC calibration curve indicates an accuracy (root-mean-square error) of 3.1 µg of EC/m3, or ~21% of the average elemental carbon concentration. The RMSE values observed here for the WPS are comparable to the reported accuracy levels for other methods, including reference methods. Based on the precision and accuracy results shown here, as well as the increased simplicity of deployment, the WPS may merit further consideration for studying air quality in homes that use solid fuels.

Discrimination, Mediating Psychosocial or Economic Factors, and Antihypertensive Treatment: A 4-Way Decomposition Analysis in the Health and Retirement Study.

Untested psychosocial or economic factors mediate associations between perceived discrimination and suboptimal antihypertensive therapy. This study included 2 waves of data from Health and Retirement Study participants with self-reported hypertension (n = 8,557, 75% non-Hispanic White, 15% non-Hispanic Black, and 10% Hispanic/Latino) over 4 years (baselines of 2008 and 2010, United States). Our primary exposures were frequency of experiencing discrimination, in everyday life or across 7 lifetime circumstances. Candidate mediators were self-reported depressive symptoms, subjective social standing, and household wealth. We evaluated with causal mediation methods the interactive and mediating associations between each discrimination measure and reported antihypertensive use at the subsequent wave. In unmediated analyses, everyday (odds ratio (OR) = 0.86, 95% confidence interval (CI): 0.78, 0.95) and lifetime (OR = 0.91, 95% CI: 0.85, 0.98) discrimination were associated with a lower likelihood of antihypertensive use. Discrimination was associated with lower wealth, greater depressive symptoms, and decreased subjective social standing. Estimates for associations due to neither interaction nor mediation resembled unmediated associations for most discrimination-mediator combinations. Lifetime discrimination was indirectly associated with reduced antihypertensive use via depressive symptomatology (OR = 0.99, 95% CI: 0.98, 1.00). In conclusion, the impact of lifetime discrimination on the underuse of antihypertensive therapy appears partially mediated by depressive symptoms.

Critical Time Windows for Air Pollution Exposure and Birth Weight in a Multicity Canadian Pregnancy Cohort.

BACKGROUND: Maternal prenatal exposure to air pollution has been associated with adverse birth outcomes. However, previous studies focused on a priori time intervals such as trimesters reported inconsistent associations. OBJECTIVES: We investigated time-varying vulnerability of birth weight to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) using flexible time intervals. METHODS: We analyzed 1,300 live, full-term births from Maternal-Infant Research on Environmental Chemicals, a Canadian prospective pregnancy cohort spanning 10 cities (2008-2011). Daily PM2.5 and NO2 concentrations were estimated from ground-level monitoring, satellite models, and land-use regression, and assigned to participants from pre-pregnancy through delivery. We developed a flexible two-stage modeling method-using a Bayesian Metropolis-Hastings algorithm and empirical density threshold-to identify time-dependent vulnerability to air pollution without specifying exposure periods a priori. This approach identified critical windows with varying lengths (2-363 days) and critical windows that fell within, or straddled, predetermined time periods (i.e., trimesters). We adjusted the models for detailed infant and maternal covariates. RESULTS: Critical windows associated with reduced birth weight were identified during mid- to late-pregnancy for both PM2.5 and NO2: -6 g (95% credible interval: -11, -1 g) and -5 g (-10, -0.1 g) per µg/m3 PM2.5 during gestational days 91-139 and 249-272, respectively; and -3 g (-5, -1 g) per ppb NO2 during days 55-145. DISCUSSION: We used a novel, flexible selection method to identify critical windows when maternal exposures to air pollution were associated with decrements in birth weight. Our results suggest that air pollution impacts on fetal development may not be adequately captured by trimester-based analyses.

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study.

BACKGROUND: The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system. METHODS: We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ground-level ozone (O3), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals' long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage. RESULTS: Among the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM2.5 (1.70 µg/m3), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01-1.12), 1.09 (95% CI 0.98-1.21) and 1.00 (95% CI 0.90-1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO2. We also estimated odds ratios of 1.15 (95% CI 1.06-1.23), 1.30 (95% CI 1.12-1.50) and 1.18 (95% CI 1.02-1.36) per interquartile range increase of 5.14 ppb in O3 for hospital admission, ICU admission and death, respectively. INTERPRETATION: Chronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O3.

Neighborhood Greenspace and Socioeconomic Risk are Associated with Diabetes Risk at the Sub-neighborhood Scale: Results from the Prospective Urban and Rural Epidemiology (PURE) Study.

Greenspace and socioeconomic status are known correlates of diabetes prevalence, but their combined effects at the sub-neighborhood scale are not yet known. This study derives, maps, and validates a combined socioeconomic/greenspace index of individual-level diabetes risk at the sub-neighborhood scale, without the need for clinical measurements. In two Canadian cities (Vancouver and Hamilton), we computed 4 greenspace variables from satellite imagery and extracted 11 socioeconomic variables from the Canadian census. We mapped 5125 participants from the Prospective Urban and Rural Epidemiology Study by their residential address and used age- and sex-dependent walking speeds to estimate individual exposure zones to local greenspace and socioeconomic characteristics, which were then entered into a principal component analysis to derive a novel diabetes risk index (DRI-GLUCoSE). We mapped index scores in both study areas and validated the index using fully adjusted logistic regression models to predict individual diabetes status. Model performance was then compared to other non-clinical diabetes risk indices from the literature. Diabetes prevalence among participants was 9.9%. The DRI-GLUCoSE index was a significant predictor of diabetes status, exhibiting a small non-significant attenuation with the inclusion of dietary and physical activity variables. The final models achieved a predictive accuracy of 75%, the highest among environmental risk models to date. Our combined index of local greenspace and socioeconomic factors demonstrates that the environmental component of diabetes risk is not sufficiently explained by diet and physical activity, and that increasing urban greenspace may be a suitable means of reducing the burden of diabetes at the community scale.

Street-view greenspace exposure and objective sleep characteristics among children.

Greenspace may benefit sleep by enhancing physical activity, reducing stress or air pollution exposure. Studies on greenspace and children's sleep are limited, and most use satellite-derived measures that do not capture ground-level exposures that may be important for sleep. We examined associations of street view imagery (SVI)-based greenspace with sleep in Project Viva, a Massachusetts pre-birth cohort. We used deep learning algorithms to derive novel metrics of greenspace (e.g., %trees, %grass) from SVI within 250m of participant residential addresses during 2007-2010 (mid-childhood, mean age 7.9 years) and 2012-2016 (early adolescence, 13.2y) (N = 533). In early adolescence, participants completed >5 days of wrist actigraphy. Sleep duration, efficiency, and time awake after sleep onset (WASO) were derived from actigraph data. We used linear regression to examine cross-sectional and prospective associations of mid-childhood and early adolescence greenspace exposure with early adolescence sleep, adjusting for confounders. We compared associations with satellite-based greenspace (Normalized Difference Vegetation Index, NDVI). In unadjusted models, mid-childhood SVI-based total greenspace and %trees (per interquartile range) were associated with longer sleep duration at early adolescence (9.4 min/day; 95%CI:3.2,15.7; 8.1; 95%CI:1.7,14.6 respectively). However, in fully adjusted models, only the association between %grass at mid-childhood and WASO was observed (4.1; 95%CI:0.2,7.9). No associations were observed between greenspace and sleep efficiency, nor in cross-sectional early adolescence models. The association between greenspace and sleep differed by racial and socioeconomic subgroups. For example, among Black participants, higher NDVI was associated with better sleep, in neighborhoods with low socio-economic status (SES), higher %grass was associated with worse sleep, and in neighborhoods with high SES, higher total greenspace and %grass were associated with better sleep time. SVI metrics may have the potential to identify specific features of greenspace that affect sleep.

Residential proximity to greenness and adverse birth outcomes in urban areas: Findings from a national Canadian population-based study.

BACKGROUND: Over the last decade, several studies have reported that residential proximity to vegetation, or 'greenness', is associated with improved birth outcomes, including for term birth weight (TBW), preterm birth (PTB), and small for gestational age (SGA). However, there remain several uncertainties about these possible benefits including the role of air pollution, and the extent to they are influenced socioeconomic status. METHODS: We addressed these gaps using a national population-based study of 2.2 million singleton live births in Canadian metropolitan areas between 1999 and 2008. Exposures to greenness, fine particulate matter (PM2.5), and nitrogen dioxide (NO2) were assigned to infants using the postal code of their mother's residence at the time of birth. The Normalized Difference Vegetation Index (NDVI) was used to characterize greenness, while estimates of ambient PM2.5 and NO2 were estimated using remote sensing, and a national land-use regression surface, respectively. Multivariable regression analysis was performed to describe associations between residential greenness and the birth outcomes. Stratified analyses explored whether these associations were modified by neighbourhood measures of socioeconomic status. RESULTS: Mothers who lived in greener areas had a lower risk of low TBW, PTB, and SGA babies. These associations persisted after adjustment for ambient NO2 and PM2.5. Specifically, in fully adjusted models, an interquartile range (IQR = 0.16) increase in the NDVI within a residential buffer of 250 m yielded odds ratios of 0.93 (95% confidence interval (CI): 0.92, 0.94), 0.94 (95% CI: 0.92, 0.95), and 0.94 (95% CI: 0.93, 0.95) for the outcomes of PTB, low TBW, and SGA, respectively. Similarly, an IQR increase in greenness was associated with a 16.3 g (95% CI: 15.3, 17.4) increase in TBW. We found inverse associations between greenness and the occurrence of adverse birth outcomes regardless of the socioeconomic status of the neighbourhood. INTERPRETATION: Our findings support the hypothesis that residential greenness contributes to healthier pregnancies, that these associations are independent from exposure to air pollution. , and that proximity to greenness benefits all mothers regardless of socioeconomic status.

A prospective study of arsenic and manganese exposures and maternal blood pressure during gestation.

BACKGROUND: Pregnancy is a sensitive time for maternal cardiovascular functioning and exposures to arsenic or manganese may adversely affect blood pressure (BP). OBJECTIVES: This study examined the associations between arsenic and manganese exposures and maternal BP measured during pregnancy. Effect modification by pre-pregnancy body mass index (BMI) was evaluated. METHODS: Pregnant women (N = 1522) were recruited for a prospective cohort study in Bangladesh (2008-2011). Exposure to arsenic and manganese was measured in drinking water at <16 weeks gestation and toenails at one-month postpartum. Systolic and diastolic BP were measured monthly. Linear mixed models estimated mean BP and differences in mean BP over gestation for arsenic or manganese exposures and adjusted for covariates. RESULTS: Arsenic levels had an increasing dose-response association with maternal BP after 25 weeks gestation. Effect modification was observed for BMI. Participants with lower BMI (<23 kg/m2) exposed to 50 µg/L arsenic had 2.83 mmHg (95% CI:1.74-3.92) greater mean systolic and 1.96 mmHg (95% CI: 1.02-2.91 mmHg) diastolic BP compared to those exposed to ≤ 1 µg/L arsenic at 40 weeks gestation. Participants with higher BMI (≥23 kg/m2) showed a greater mean systolic BP of 5.72 mmHg (95% CI: 3.18-8.27 mmHg) and diastolic BP change of 6.09 mmHg (95% CI: 4.02-8.16 mmHg) at 40 weeks gestation when exposed to 50 µg/L compared to ≤ 1 µg/L arsenic. Participants with lower BMI exposed to drinking water manganese in the 2nd quartile (181-573 µg/L) had 1.04 mmHg higher mean diastolic BP (95% CI: 0.01-2.07 mmHg) at 40 weeks gestation compared to those in the 1st quartile (0.5-180 µg/L). CONCLUSION: Arsenic exposures during pregnancy were consistently associated with increased average maternal systolic and diastolic BP. The effect of manganese on BP was less consistent.

Ambient air pollution and the risk of acute myocardial infarction and stroke: A national cohort study.

We used a large national cohort in Canada to assess the incidence of acute myocardial infarction (AMI) and stroke hospitalizations in association with long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3). The study population comprised 2.7 million respondents from the 2006 Canadian Census Health and Environment Cohort (CanCHEC), followed for incident hospitalizations of AMI or stroke between 2006 and 2016. We estimated 10-year moving average estimates of PM2.5, NO2, and O3, annually. We used Cox proportional hazards models to examine the associations adjusting for various covariates. For AMI, each interquartile range (IQR) increase in exposure was found to be associated with a hazard ratio of 1.026 (95% CI: 1.007-1.046) for PM2.5, 1.025 (95% CI: 1.001-1.050) for NO2, and 1.062 (95% CI: 1.041-1.084) for O3, respectively. Similarly, for stroke, an IQR increase in exposure was associated with a hazard ratio of 1.078 (95% CI: 1.052-1.105) for PM2.5, 0.995 (95% CI: 0.965-1.030) for NO2, and 1.055 (95% CI: 1.028-1.082) for O3, respectively. We found consistent evidence of positive associations between long-term exposures to PM2.5, and O3, and to a lesser degree NO2, with incident AMI and stroke hospitalizations.

Personal and household PM2.5 and black carbon exposure measures and respiratory symptoms in 8 low- and middle-income countries.

BACKGROUND: Household air pollution (HAP) from cooking with solid fuels has been associated with adverse respiratory effects, but most studies use surveys of fuel use to define HAP exposure, rather than on actual air pollution exposure measurements. OBJECTIVE: To examine associations between household and personal fine particulate matter (PM2.5) and black carbon (BC) measures and respiratory symptoms. METHODS: As part of the Prospective Urban and Rural Epidemiology Air Pollution study, we analyzed 48-h household and personal PM2.5 and BC measurements for 870 individuals using different cooking fuels from 62 communities in 8 countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Self-reported respiratory symptoms were collected after monitoring. Associations between PM2.5 and BC exposures and respiratory symptoms were examined using logistic regression models, controlling for individual, household, and community covariates. RESULTS: The median (interquartile range) of household and personal PM2.5 was 73.5 (119.1) and 65.3 (91.5) µg/m3, and for household and personal BC was 3.4 (8.3) and 2.5 (4.9) x10-5 m-1, respectively. We observed associations between household PM2.5 and wheeze (OR: 1.25; 95%CI: 1.07, 1.46), cough (OR: 1.22; 95%CI: 1.06, 1.39), and sputum (OR: 1.26; 95%CI: 1.10, 1.44), as well as exposure to household BC and wheeze (OR: 1.20; 95%CI: 1.03, 1.39) and sputum (OR: 1.20; 95%CI: 1.05, 1.36), per IQR increase. We observed associations between personal PM2.5 and wheeze (OR: 1.23; 95%CI: 1.00, 1.50) and sputum (OR: 1.19; 95%CI: 1.00, 1.41). For household PM2.5 and BC, associations were generally stronger for females compared to males. Models using an indicator variable of solid versus clean fuels resulted in larger OR estimates with less precision. CONCLUSIONS: We used measurements of household and personal air pollution for individuals using different cooking fuels and documented strong associations with respiratory symptoms.

Air Pollution as a Risk Factor for Incident Chronic Obstructive Pulmonary Disease and Asthma. A 15-Year Population-based Cohort Study.

Rationale: Current evidence on the relationship between long-term exposure to air pollution and new onset of chronic lung disease is inconclusive.Objectives: To examine associations of incident chronic obstructive pulmonary disease (COPD) and adult-onset asthma with past exposure to fine particulate matter ≤ 2.5 µm in diameter (PM2.5), nitrogen dioxide (NO2), ozone (O3), and the redox-weighted average of NO2 and O3 (Ox) and characterize the concentration-response relationship.Methods: We conducted a population-based cohort study of all Ontarians, aged 35-85 years, from 2001 to 2015. A 3-year moving average of residential exposures to selected pollutants with a 1-year lag were estimated during follow-up. We used Cox proportional hazard models and Aalen additive-hazard models to quantify the pollution-disease associations and characterized the shape of these relationships using newly developed nonlinear risk models.Measurements and Main Results: Among 5.1 million adults, we identified 340,733 and 218,005 incident cases of COPD and asthma, respectively. We found positive associations of COPD with PM2.5 per interquartile-range (IQR) increase of 3.4 µg/m3 (hazard ratio, 1.07; 95% confidence interval, 1.06-1.08), NO2 per IQR increase of 13.9 ppb (1.04; 1.02-1.05), O3 per IQR increase of 6.3 ppb (1.04; 1.03-1.04), and Ox per IQR increase of 4.4 ppb (1.03; 1.03-1.03). By contrast, we did not find strong evidence linking these pollutants to adult-onset asthma. In addition, we quantified that each IQR increase in pollution exposure yielded 3.0 (2.4-3.6), 3.2 (2.0-4.3), 1.9 (1.3-2.5), and 2.3 (1.7-2.9) excess cases of COPD per 100,000 adults for PM2.5, NO2, O3, and Ox, respectively. Furthermore, most pollutant-COPD relationships exhibited supralinear shapes.Conclusions: Air pollution was associated with a higher incidence of COPD but was not associated with a higher incidence of adult-onset asthma.

Developing indicators of age-friendly neighbourhood environments for urban and rural communities across 20 low-, middle-, and high-income countries.

BACKGROUND: By 2050, the global population of adults 60 + will reach 2.1 billion, surging fastest in low- and middle-income countries (LMIC). In response, the World Health Organization (WHO) has developed indicators of age-friendly urban environments, but these criteria have been challenging to apply in rural areas and LMIC. This study fills this gap by adapting the WHO indicators to such settings and assessing variation in their availability by community-level urbanness and country-level income. METHODS: We used data from the Prospective Urban and Rural Epidemiology (PURE) study's environmental-assessment tools, which integrated systematic social observation and ecometrics to reliably capture community-level environmental features associated with cardiovascular-disease risk factors. The results of a scoping review guided selection of 18 individual indicators across six distinct domains, with data available for 496 communities in 20 countries, including 382 communities (77%) in LMIC. Finally, we used both factor analysis of mixed data (FAMD) and multitrait-multimethod (MTMM) approaches to describe relationships between indicators and domains, as well as detailing the extent to which these relationships held true within groups defined by urbanness and income. RESULTS: Together, the results of the FAMD and MTMM approaches indicated substantial variation in the relationship of individual indicators to each other and to broader domains, arguing against the development of an overall score and extending prior evidence demonstrating the need to adapt the WHO framework to the local context. Communities in high-income countries generally ranked higher across the set of indicators, but regular connections to neighbouring towns via bus (95%) and train access (76%) were most common in low-income countries. The greatest amount of variation by urbanness was seen in the number of streetscape-greenery elements (33 such elements in rural areas vs. 55 in urban), presence of traffic lights (18% vs. 67%), and home-internet availability (25% vs. 54%). CONCLUSIONS: This study indicates the extent to which environmental supports for healthy ageing may be less readily available to older adults residing in rural areas and LMIC and augments calls to tailor WHO's existing indicators to a broader range of communities in order to achieve a critical aspect of distributional equity in an ageing world.