Archive for category: Paper of the Week

Projected local rain events due to climate change and the impacts on waterborne diseases in Vancouver, British Columbia, Canada.

Bimal K. Chhetri, Eleni Galanis, Stephen Sobie, Jordan Brubacher, Robert Balshaw, Michael Otterstatter, Sunny Mak, Marcus Lem, Mark Lysyshyn, Trevor Murdock, Manon Fleury, Kirsten Zickfeld, Mark Zubel, Len Clarkson, Tim K. Takaro

Environmental Health volume 18, Article number: 116 (2019) https://dx.doi.org/10.14288/1.0387512

 

Abstract

Background

Climate change is increasing the number and intensity of extreme weather events in many parts of the world. Precipitation extremes have been linked to both outbreaks and sporadic cases of waterborne illness. We have previously shown a link between heavy rain and turbidity to population-level risk of sporadic cryptosporidiosis and giardiasis in a major Canadian urban population. The risk increased with 30 or more dry days in the 60 days preceding the week of extreme rain. The goal of this study was to investigate the change in cryptosporidiosis and giardiasis risk due to climate change, primarily change in extreme precipitation.

Methods

Cases of cryptosporidiosis and giardiasis were extracted from a reportable disease system (1997–2009). We used distributed lag non-linear Poisson regression models and projections of the exposure-outcome relationship to estimate future illness (2020–2099). The climate projections are derived from twelve statistically downscaled regional climate models. Relative Concentration Pathway 8.5 was used to project precipitation derived from daily gridded weather observation data (~ 6 × 10 km resolution) covering the central of three adjacent watersheds serving metropolitan Vancouver for the 2020s, 2040s, 2060s and 2080s.

Results

Precipitation is predicted to steadily increase in these watersheds during the wet season (Oct. -Mar.) and decrease in other parts of the year up through the 2080s. More weeks with extreme rain (>90th percentile) are expected. These weeks are predicted to increase the annual rates of cryptosporidiosis and giardiasis by approximately 16% by the 2080s corresponding to an increase of 55–136 additional cases per year depending upon the climate model used. The predicted increase in the number of waterborne illness cases are during the wet months. The range in future projections compared to historical monthly case counts typically differed by 10–20% across climate models but the direction of change was consistent for all models.

Discussion

If new water filtration measures had not been implemented in our study area in 2010–2015, the risk of cryptosporidiosis and giardiasis would have been expected to increase with climate change, particularly precipitation changes. In addition to the predicted increase in the frequency and intensity of extreme precipitation events, the frequency and length of wet and dry spells could also affect the risk of waterborne diseases as we observed in the historical period. These findings add to the growing evidence regarding the need to prepare water systems to manage and become resilient to climate change-related health risks.

Efficient Removal of Ultrafine Particles from Diesel Exhaust by Selected Tree Species: Implications for Roadside Planting for Improving the Quality of Urban Air. 

Wang H, Maher BA, Ahmed IA, Davison B.

Environ Sci Technol. 2019 Jun 18;53(12):6906-6916. doi: 10.1021/acs.est.8b06629 Epub 2019 May 28.

 

Abstract

Human exposure to airborne ultrafine (≪1 μm) particulate pollution may pose substantial hazards to human health, particularly in urban roadside environments where very large numbers of people are frequently exposed to vehicle-derived ultrafine particles (UFPs). For mitigation purposes, it is timely and important to quantify the deposition of traffic-derived UFPs onto leaves of selected plant species, with particularly efficient particle capture (high deposition velocity), which can be installed curbside, proximal to the emitting vehicular sources. Here, we quantify the size-resolved capture efficiency of UFPs from diesel vehicle exhaust by nine temperate-zone plant species, in wind tunnel experiments. The results show that silver birch (79% UFP removal), yew (71%), and elder (70.5%) have very high capabilities for capture of airborne UFPs. Metal concentrations and metal enrichment ratios in leaf leachates were also highest for the postexposure silver birch leaves; scanning electron microscopy showed that UFPs were concentrated along the hairs of these leaves. For all but two species, magnetic measurements demonstrated substantial increases in the concentration of magnetic particles deposited on the leaves after exposure to the exhaust particulates. Together, these new data show that leaf-deposition of UFPs is chiefly responsible for the substantial reductions in particle numbers measured downwind of the vegetation. It is critical to recognize that the deposition velocity of airborne particulate matter (PM) to leaves is species-specific and often substantially higher (∼10 to 50 times higher) than the “standard” V_d values (e.g., 0.1-0.64 cm s^-1 for PM_2.5) used in most modeling studies. The use of such low V_d values in models results in a major under-estimation of PM removal by roadside vegetation and thus misrepresents the efficacy of selected vegetation species in the substantial (≫20%) removal of PM. Given the potential hazard to health posed by UFPs and the removal efficiencies shown here (and by previous roadside measurements), roadside planting (maintained at or below head height) of selected species at PM “hotspots” can contribute substantially and quickly to improve in urban air quality and reductions in human exposure. These findings can contribute to the development and implementation of mitigation policies of traffic-derived PM on an international scale.

Road proximity, air pollution, noise, green space and neurologic disease incidence: a population-based cohort study.

Yuchi W, Sbihi H, Davies H, Tamburic L, Brauer M.

Environ Health. 2020 Jan 21;19(1):8. DOI:10.1186/s12940-020-0565-4

 

Abstract

BACKGROUND:

Emerging evidence links road proximity and air pollution with cognitive impairment. Joint effects of noise and greenness have not been evaluated. We investigated associations between road proximity and exposures to air pollution, and joint effects of noise and greenness, on non-Alzheimer’s dementia, Parkinson’s and Alzheimer’s disease and multiple sclerosis within a population-based cohort.

METHODS:

We assembled administrative health database cohorts of 45-84 year old residents (N ~ 678,000) of Metro Vancouver, Canada. Cox proportional hazards models were built to assess associations between exposures and non-Alzheimer’s dementia and Parkinson’s disease. Given reduced case numbers, associations with Alzheimer’s disease and multiple sclerosis were evaluated in nested case-control analyses by conditional logistic regression.

RESULTS:

Road proximity was associated with all outcomes (e.g. non-Alzheimer’s dementia hazard ratio: 1.14, [95% confidence interval: 1.07-1.20], for living < 50 m from a major road or < 150 m from a highway). Air pollutants were associated with incidence of Parkinson’s disease and non-Alzheimer’s dementia (e.g. Parkinson’s disease hazard ratios of 1.09 [1.02-1.16], 1.03 [0.97-1.08], 1.12 [1.05-1.20] per interquartile increase in fine particulate matter, Black Carbon, and nitrogen dioxide) but not Alzheimer’s disease or multiple sclerosis. Noise was not associated with any outcomes while associations with greenness suggested protective effects for Parkinson’s disease and non-Alzheimer’s dementia.

CONCLUSIONS:

Road proximity was associated with incidence of non-Alzheimer’s dementia, Parkinson’s disease, Alzheimer’s disease and multiple sclerosis. This association may be partially mediated by air pollution, whereas noise exposure did not affect associations. There was some evidence of protective effects of greenness.

Mortality-Air Pollution Associations in Low-Exposure Environments (MAPLE): Phase 1.

Brauer M, Brook JR, Christidis T, Chu Y, Crouse DL, Erickson A, Hystad P, Li C, Martin RV, Meng J, Pappin AJ, Pinault LL, Tjepkema M, van Donkelaar A, Weichenthal S, Burnett RT.

Res Rep Health Eff Inst. 2019 Nov;(203):1-87. https://www.healtheffects.org/system/files/brauer-rr-203-phase1-report_0.pdf

Abstract

INTRODUCTION:

Fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter, or PM_2.5) is associated with mortality, but the lower range of relevant concentrations is unknown. Novel satellite-derived estimates of outdoor PM_2.5 concentrations were applied to several large population-based cohorts, and the shape of the relationship with nonaccidental mortality was characterized, with emphasis on the low concentrations (<12 μg/m³) observed throughout Canada.

METHODS:

Annual satellite-derived estimates of outdoor PM_2.5 concentrations were developed at 1-km² spatial resolution across Canada for 2000-2016 and backcasted to 1981 using remote sensing, chemical transport models, and ground monitoring data. Targeted ground-based measurements were conducted to measure the relationship between columnar aerosol optical depth (AOD) and ground-level PM_2.5. Both existing and targeted ground-based measurements were analyzed to develop improved exposure data sets for subsequent epidemiological analyses.

Residential histories derived from annual tax records were used to estimate PM_2.5 exposures for subjects whose ages ranged from 25 to 90 years. About 8.5 million were from three Canadian Census Health and Environment Cohort (CanCHEC) analytic files and another 540,900 were Canadian Community Health Survey (CCHS) participants. Mortality was linked through the year 2016. Hazard ratios (HR) were estimated with Cox Proportional Hazard models using a 3-year moving average exposure with a 1-year lag, with the year of follow-up as the time axis. All models were stratified by 5-year age groups, sex, and immigrant status. Covariates were based on directed acyclical graphs (DAG), and included contextual variables (airshed, community size, neighborhood dependence, neighborhood deprivation, ethnic concentration, neighborhood instability, and urban form). A second model was examined including the DAG-based covariates as well as all subject-level risk factors (income, education, marital status, indigenous identity, employment status, occupational class, and visible minority status) available in each cohort. Additional subject-level behavioral covariates (fruit and vegetable consumption, leisure exercise frequency, alcohol consumption, smoking, and body mass index [BMI]) were included in the CCHS analysis.

Sensitivity analyses evaluated adjustment for covariates and gaseous copollutants (nitrogen dioxide [NO₂] and ozone [O₃]), as well as exposure time windows and spatial scales. Estimates were evaluated across strata of age, sex, and immigrant status. The shape of the PM_2.5-mortality association was examined by first fitting restricted cubic splines (RCS) with a large number of knots and then fitting the shape-constrained health impact function (SCHIF) to the RCS predictions and their standard errors (SE). This method provides graphical results indicating the RCS predictions, as a nonparametric means of characterizing the concentration-response relationship in detail and the resulting mean SCHIF and accompanying uncertainty as a parametric summary.

Sensitivity analyses were conducted in the CCHS cohort to evaluate the potential influence of unmeasured covariates on air pollution risk estimates. Specifically, survival models with all available risk factors were fit and compared with models that omitted covariates not available in the CanCHEC cohorts. In addition, the PM_2.5 risk estimate in the CanCHEC cohort was indirectly adjusted for multiple individual-level risk factors by estimating the association between PM_2.5 and these covariates within the CCHS.

RESULTS:

Satellite-derived PM_2.5 estimates were low and highly correlated with ground monitors. HR estimates (per 10-μg/m³ increase in PM_2.5) were similar for the 1991 (1.041, 95% confidence interval [CI]: 1.016-1.066) and 1996 (1.041, 1.024-1.059) CanCHEC cohorts with a larger estimate observed for the 2001 cohort (1.084, 1.060-1.108). The pooled cohort HR estimate was 1.053 (1.041-1.065). In the CCHS an analogous model indicated a HR of 1.13 (95% CI: 1.06-1.21), which was reduced slightly with the addition of behavioral covariates (1.11, 1.04-1.18). In each of the CanCHEC cohorts, the RCS increased rapidly over lower concentrations, slightly declining between the 25th and 75th percentiles and then increasing beyond the 75th percentile. The steepness of the increase in the RCS over lower concentrations diminished as the cohort start date increased. The SCHIFs displayed a supralinear association in each of the three CanCHEC cohorts and in the CCHS cohort.

In sensitivity analyses conducted with the 2001 CanCHEC, longer moving averages (1, 3, and 8 years) and smaller spatial scales (1 km² vs. 10 km²) of exposure assignment resulted in larger associations between PM_2.5 and mortality. In both the CCHS and CanCHEC analyses, the relationship between nonaccidental mortality and PM_2.5 was attenuated when O₃ or a weighted measure of oxidant gases was included in models. In the CCHS analysis, but not in CanCHEC, PM_2.5 HRs were also attenuated by the inclusion of NO₂. Application of the indirect adjustment and comparisons within the CCHS analysis suggests that missing data on behavioral risk factors for mortality had little impact on the magnitude of PM_2.5-mortality associations. While immigrants displayed improved overall survival compared with those born in Canada, their sensitivity to PM_2.5 was similar to or larger than that for nonimmigrants, with differences between immigrants and nonimmigrants decreasing in the more recent cohorts.

CONCLUSIONS:

In several large population-based cohorts exposed to low levels of air pollution, consistent associations were observed between PM_2.5 and nonaccidental mortality for concentrations as low as 5 μg/m³. This relationship was supralinear with no apparent threshold or sublinear association.

Early Life Exposure to Air Pollution and Incidence of Childhood Asthma, Allergic Rhinitis and Eczema.

To T, Zhu J, Stieb D, Gray N, Fong I, Pinault L, Jerrett M, Robichaud A, Ménard R, van Donkelaar A, Martin RV, Hystad P, Brook JR, Dell S.

Eur Respir J. 2019 Dec 5. pii: 1900913. DOI: 10.1183/13993003.00913-2019  [Epub ahead of print]

 

Abstract

RATIONALE:

There is growing evidence that air pollution may contribute to the development of childhood asthma and other allergic diseases. In this follow-up of the Toronto Child Health Evaluation Questionnaire (T-CHEQ) study, we examined associations between early life exposures to air pollution and incidence of asthma, allergic rhinitis and eczema from birth through adolescence.

METHODS:

1286 T-CHEQ participants were followed from birth until outcome, March 31, 2016, or loss-to-follow-up with a mean of 17 years of follow-up. Concentrations of NO₂, O₃ and PM_2.5 from January 1, 1999, to December 31, 2012 were assigned to participants based on their postal codes at birth using ground observations, chemical/meteorological models, remote sensing and land use regression (LUR) models. Study outcomes included incidence of physician-diagnosed asthma, allergic rhinitis and eczema. Cox proportional hazard regression models were used to estimate hazard ratios (HR) per interquartile range of exposures and outcomes, adjusting for potential confounders.

RESULTS:

HRs of 1.17 (95%CI: 1.05, 1.31) for asthma and 1.07 (95%CI: 0.99, 1.15) for eczema were observed for total oxidants (O₃ and NO₂) at birth. No significant increase in risk was found for PM_2.5.

CONCLUSION:

Exposures to oxidant air pollutants (O₃ and NO₂), but not PM_2.5 were associated with an increased risk of incident asthma and eczema in children. This suggests that improving air quality may contribute to the prevention of asthma and other allergic disease in childhood and adolescence.