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2019
Nori-Sarma, A, Benmarhnia T, Rajiva A, Azhar GS, Gupta P, Pednekar MS, Bell ML.  2019.  Advancing our understanding of heat wave criteria and associated health impacts to improve heat wave alerts in developing country settings. International Journal of Environmental Research and Public Health. 16   10.3390/ijerph16122089   AbstractWebsite

Health effects of heat waves with high baseline temperatures in areas such as India remain a critical research gap. In these regions, extreme temperatures may affect the underlying population's adaptive capacity; heat wave alerts should be optimized to avoid continuous high alert status and enhance constrained resources, especially under a changing climate. Data from registrars and meteorological departments were collected for four communities in Northwestern India. Propensity Score Matching (PSM) was used to obtain the relative risk of mortality and number of attributable deaths (i.e., absolute risk which incorporates the number of heat wave days) under a variety of heat wave definitions (n = 13) incorporating duration and intensity. Heat waves' timing in season was also assessed for potential effect modification. Relative risk of heat waves (risk of mortality comparing heat wave days to matched non-heat wave days) varied by heat wave definition and ranged from 1.28 [95% Confidence Interval: 1.11-1.46] in Churu (utilizing the 95th percentile of temperature for at least two consecutive days) to 1.03 [95% CI: 0.87-1.23] in Idar and Himmatnagar (utilizing the 95th percentile of temperature for at least four consecutive days). The data trended towards a higher risk for heat waves later in the season. Some heat wave definitions displayed similar attributable mortalities despite differences in the number of identified heat wave days. These findings provide opportunities to assess the "efficiency" (or number of days versus potential attributable health impacts) associated with alternative heat wave definitions. Findings on both effect modification and trade-offs between number of days identified as "heat wave" versus health effects provide tools for policy makers to determine the most important criteria for defining thresholds to trigger heat wave alerts.

Aguilera, R, Gershunov A, Benmarhnia T.  2019.  Atmospheric rivers impact California's coastal water quality via extreme precipitation. Science of the Total Environment. 671:488-494.   10.1016/j.scitotenv.2019.03.318   AbstractWebsite

Precipitation in California is projected to become more volatile: less frequent but more extreme as global warming pushes midlatitude frontal cyclones further poleward while bolstering the atmospheric rivers (ARs), which tend to produce the region's extreme rainfall. Pollutant accumulation and delivery to coastal waters can be expected to increase, as lengthening dry spells will be increasingly punctuated by more extreme precipitation events. Coastal pollution exposes human populations to high levels of fecal bacteria and associated pathogens, which can cause a variety of health impacts. Consequently, studying the impact of atmospheric rivers as the mechanism generating pulses of water pollution in coastal areas is relevant for public health and in the context of climate change. We aimed to quantify the links between precipitation events and water quality in order to explore meteorological causes as first steps toward effective early warning systems for the benefit of population health in California and beyond. We used historical gridded daily precipitation and weekly multiple fecal bacteria indicators at similar to 500 monitoring locations in California's coastal waters to identify weekly associations between precipitation and water quality during 2003-09 using canonical correlation analysis to account for the nested/clustered nature of longitudinal data. We then quantified, using a recently published catalog of atmospheric rivers, the proportion of coastal pollution events attributable to ARs. Association between precipitation and fecal bacteria was strongest in Southern California. Over two-thirds of coastal water pollution spikes exceeding one standard deviation were associated with ARs. This work highlights the importance of skillful AR landfall predictions in reducing vulnerability to extreme weather improving resilience of human populations in a varying and changing climate. Quantifying the impacts of ARs on waterborne diseases is important for planning effective preventive strategies for public health. (C) 2019 Elsevier B.V. All rights reserved.

Benmarhnia, T, Zhao X, Wang J, Macdonald M, Chen H.  2019.  Evaluating the potential public health impacts of the Toronto cold weather program. Environment International. 127:381-386.   10.1016/j.envint.2019.03.042   AbstractWebsite

Background: Extreme cold weather alert programs have been implemented in some areas to address the significant health impacts of exposure to cold. One such program is the Toronto Cold Weather Program (TCWP) that was implemented in the City of Toronto since 1996 to protect the public from extreme weather conditions. In this paper, we aim to evaluate the effectiveness of the TCWP in reducing mortality and morbidity outcomes related to cold temperatures. Methods: We applied a quasi-experimental study design using the Difference-in-Differences method coupled with propensity-score-matching to determine the effect of the TCMP on daily hospitalizations and deaths due to cardiovascular disease (CVD), coronary heart disease (CHD) or cerebrovascular disease, using two complementary analytical approaches. Results: Overall, the analysis did not detect an impact on reduced mortality/morbidity in the City of Toronto from the TCMP. For example, we obtained a Risk Difference (RD) of -0.88 (per 1,000,000 people) (95% CI: -3.27 to 1.51) and a Risk Ratio (RR) of 0.98 (95% CI: 0.91 to 1.05) people for CVD hospitalizations. Conclusions: The TCWP was not found to be effective in reducing cold related mortality and morbidity which demonstrates the importance of improving existing policies related to cold in Canada and other countries.

Bailey, J, Gerasopoulos E, Rojas-Rueda D, Benmarhnia T.  2019.  Potential health and equity co-benefits related to the mitigation policies reducing air pollution from residential wood burning in Athens, Greece. Journal of Environmental Science and Health Part a-Toxic/Hazardous Substances & Environmental Engineering.   10.1080/10934529.2019.1629211   AbstractWebsite

Athens, Greece has been in economic and social crises after the 2008 global recession, resulting in an increase in wood burning as a cheaper method of residential heating in the winter. Reducing wood burning emissions is a source-specific method to address air quality degradation, and indirectly climate change, through instituting policies aimed at human health co-benefits. In this work, we investigate and quantify the potential health co-benefits from policies reducing outdoor particulate matter (PM) pollution from residential wood burning by assessing the pollution conditions during the 2015 calendar year in Athens, Greece, emphasizing vulnerable populations. We conducted a systematic literature search to extract data regarding effective improvements to outdoor PM due to wood burning interventions, and get a range of potential ambient PM reduction estimates regarding realistic benefits from different interventions. We applied a health impact assessment methodology and used existing Athens specific data to calculate the preventable daily average non-accidental deaths associated with reducing PM, additionally considering low and high socioeconomic status (SES) groups. We found that the reduction in outdoor PM concentration showed the potential to benefit lower SES groups as much as 13.5 times more than the high SES group, representing an opportunity for policies to improve not only the health of the total population but also improve environmental equity and health disparities.

Heo, S, Nori-Sarma A, Lee K, Benmarhnia T, Dominici F, Bell ML.  2019.  The use of a quasi-experimental study on the mortality effect of a heat wave warning system in Korea. International Journal of Environmental Research and Public Health. 16   10.3390/ijerph16122245   AbstractWebsite

Many cities and countries have implemented heat wave warning systems to combat the health effects of extreme heat. Little is known about whether these systems actually reduce heat-related morbidity and mortality. We examined the effectiveness of heat wave alerts and health plans in reducing the mortality risk of heat waves in Korea by utilizing the discrepancy between the alerts and the monitored temperature. A difference-in-differences analysis combined with propensity score weighting was used. Mortality, weather monitoring, and heat wave alert announcement data were collected for 7 major cities during 2009-2014. Results showed evidence of risk reduction among people aged 19-64 without education (-0.144 deaths/1,000,000 people, 95% CI: -0.227, -0.061) and children aged 0-19 (-0.555 deaths/1,000,000 people, 95% CI: -0.993, -0.117). Decreased cardiovascular and respiratory mortality was found in several subgroups including single persons, widowed people, blue-collar workers, people with no education or the highest level of education (university or higher). No evidence was found for decreased all-cause mortality in the population (1.687 deaths/1,000,000 people per day; 95% CI: 1.118, 2.255). In conclusion, heat wave alerts may reduce mortality for several causes and subpopulations of age and socio-economic status. Further work needs to examine the pathways through which the alerts impact subpopulations differently.

Green, H, Bailey J, Schwarz L, Vanos J, Ebi K, Benmarhnia T.  2019.  Impact of heat on mortality and morbidity in low and middle income countries: A review of the epidemiological evidence and considerations for future research. Environmental Research. 171:80-91.   10.1016/j.envres.2019.01.010   AbstractWebsite

Heat waves and high air temperature are associated with increased morbidity and mortality. However, the majority of research conducted on this topic is focused on high income areas of the world. Although heat waves have the most severe impacts on vulnerable populations, relatively few studies have studied their impacts in low and middle income countries (LMICs). The aim of this paper is to review the existing evidence in the literature on the impact of heat on human health in LMICs. We identified peer-reviewed epidemiologic studies published in English between January 1980 and August 2018 investigating potential associations between high ambient temperature or heat waves and mortality or morbidity. We selected studies according to the following criteria: quantitative studies that used primary and/or secondary data and report effect estimates where ambient temperature or heat waves are the main exposure of interest in relation to human morbidity or mortality within LMICs. Of the total 146 studies selected, eighty-two were conducted in China, nine in other countries of East Asia and the Pacific, twelve in South Asia, ten in Sub-Saharan Africa, eight in the Middle East and North Africa, and seven in each of Latin America and Europe. The majority of studies (92.9%) found positive associations between heat and human morbidity/mortality. Additionally, while outcome variables and study design differed greatly, most utilized a time-series study design and examined overall heath related morbidity/mortality impacts in an entire population, although it is notable that the selected studies generally found that the elderly, women, and individuals within the low socioeconomic brackets were the most vulnerable to the effects of high temperature. By highlighting the existing evidence on the impact of extreme heat on health in LMICs, we hope to determine data needs and help direct future studies in addressing this knowledge gap. The focus on LMICs is justified by the lack of studies and data studying the health burden of higher temperatures in these regions even though LMICs have a lower capacity to adapt to high temperatures and thus an increased risk.

Wang, Q, Benmarhnia T, Li CC, Knibbs LD, Bao JZ, Ren M, Zhang HH, Wang SH, Zhang YW, Zhao QG, Huang CR.  2019.  Seasonal analyses of the association between prenatal ambient air pollution exposure and birth weight for gestational age in Guangzhou, China. Science of the Total Environment. 649:526-534.   10.1016/j.scitotenv.2018.08.303   AbstractWebsite

Ambient air pollution has been linked to small for gestational age (SGA); however, the relationship with large for gestational age (ILA) is unclear and very few studies have investigated seasonal effects on the association between air pollution and SGA or LGA. Using birth registry data of 506,000 singleton live births from 11 districts in Guangzhou, China between January 2015 and July 2017, we examined associations between ambient air pollutants (PM2.5, PM10, NO2, SO2, and O-3) and SGA/LGA, and further assessed the modification effect of season. Daily concentrations of air pollutants from 11 monitoring stations were used to estimate district-specific exposures for each participant based on their district of residence during pregnancy. Two-level binary logistic regression models were used to evaluate associations between air pollution and SGA/LGA. Stratified analyses by season and a Cochran Q test were performed to assess the modification of season. Exposure to PM2.5, NO2, SO2, and O-3 was significantly associated with increased risk of SGA, especially for exposure during the second and trimester. For an interquartile range (IQR) increase in PM2.5(6.5 mu g/m(3)), NO2 (12.7 mu g/m(3)), SO2 (2.8 mu g/m(3)) and O-3 (20.8 mu g/m(3)) during the entire pregnancy, SGA risk increased by 2% (OR - 1.02, 95% CI: 1.00-1.04), 8% (OR = 1.08, 95% CI: 1.04-1.12), 2% (OR - 1.02, 95% CI: 1.01-1.03), and 14% (1.14, 1.11-1.17), respectively. A decreased risk of WA was found for PM2.5, PM10, SO2, and O-3 during the first trimester or entire pregnancy. When examined by season, significant associations between air pollutants and SGA were observed for women who conceived during summer or fall, and the patterns were consistent for all pollutants. Our study suggests that conception during different seasons might modify the association between ambient air pollution and SGA. (C) 2018 Elsevier B.V. All rights reserved.

2018
Wang, Q, Benmarhnia T, Zhang HH, Knibbs LD, Sheridan P, Li CC, Bao JZ, Ren M, Wang SH, He YL, Zhang YW, Zhao QG, Huang CR.  2018.  Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth. Environment International. 121:317-324.   10.1016/j.envint.2018.09.021   AbstractWebsite

Maternal exposure to ambient air pollution has been associated with preterm birth (PTB), however, entire pregnancy or trimester-specific associations were generally reported, which may not sufficiently identify windows of susceptibility. Using birth registry data from Guangzhou, a megacity of southern China (population -14.5 million), including 469,975 singleton live births between January 2015 and July 2017, we assessed the association between weekly air pollution exposure and PTB in a retrospective cohort study. Daily average concentrations of PM2.5, PM10, NO2, SO2, and O-3 from 11 monitoring stations were used to estimate district-specific exposures for each participant based on their district residency during pregnancy. Distributed lag models (DLMs) incorporating Cox proportional hazard models were applied to estimate the association between weekly maternal exposure to air pollutant and PTB risk (as a time-to-event outcome), after controlling for temperature, seasonally, and individual-level covariates. We also considered moderate PTB (32-36 gestational weeks) and very PTB (28-31 gestational weeks) as outcomes of interest. Hazard ratios (HRs) and 95% confidential intervals (95% CIs) were calculated for an interquartile range (IQR) increase in air pollutants during the study period. An IQR increase in PM2.5 exposure during the 20th to 28th gestational weeks (27.0 mu g/m(3)) was significantly associated with PTB risk, with the strongest effect in the 25th week (HR = 1.034, 95% CI:1.010-1.059). The significant exposure windows were the 19th-28th weeks for PM10, the 18th-31st weeks for NO2, and the 23rd-31A weeks for O-3, respectively. The strongest associations were observed in the 25th week for PM10 (IQR = 37.0 mu g/m(3); HR = 1.048, 95% CI:1.034-1.062), the 26th week for NO2 (IQR = 29.0 mu g/m(3); HR = 1.060, 95% CI:1.028-1.094), and in the 28th week for O-3 (IQR = 90.0 mu g/m(3); HR = 1.063, 95% CI:1.046-1.081). Similar patterns were observed for moderate PTB (32-36 gestational weeks) and very PTB (28-31 gestational weeks) for PM2.5, PM10, NO2 exposure, but the effects were greater for very PTB. We did not observe any association between pregnancy SO2 exposure and the risk of PTB. Our results suggest that middle to late pregnancy is the most susceptible air pollution exposure window for air pollution and PTB among women in Guangzhou, China.

Loizeau, M, Buteau S, Chaix B, McElroy S, Counil E, Benmarhnia T.  2018.  Does the air pollution model influence the evidence of socio-economic disparities in exposure and susceptibility? Environmental Research. 167:650-661.   10.1016/j.envres.2018.08.002   AbstractWebsite

Studies assessing socio-economic disparities in air pollution exposure and susceptibility are usually based on a single air pollution model. A time stratified case-crossover study was designed to assess the impact of the type of model on differential exposure and on the differential susceptibility in the relationship between ozone exposure and daily mortality by socio-economic strata (SES) in Montreal. Non-accidental deaths along with deaths from cardiovascular and respiratory causes on the island of Montreal for the period 1991-2002 were included as cases. Daily ozone concentration estimates at partictaipants' residence were obtained from the five following air pollution models: Average value (AV), Nearest station model (NS), Inverse-distance weighting interpolation (IDW), Land-use regression model with back-extrapolation (LUR-BE) and Bayesian maximum entropy model combined with a land-use regression (BME-LUR). The prevalence of a low household income ( < 20,000/year) was used as socio-economic variable, divided into two categories as a proxy for deprivation. Multivariable conditional logistic regressions were used considering 3-day average concentrations. Multiplicative and additive interactions (using Relative Excess Risk due to Interaction) as well as Cochran's tests were calculated and results were compared across the different air pollution models. Heterogeneity of susceptibility and exposure according to socio-economic status (SES) were found. Ratio of exposure across SES groups means ranged from 0.75 [0.74-0.76] to 1.01 [1.00-1.02], respectively for the LUR-BE and the BME-LUR models. Ratio of mortality odds ratios ranged from 1.01 [0.96-1.05] to 1.02 [0.97-1.08], respectively for the IDW and LUR-BE models. Cochran's test of heterogeneity between the air pollution models showed important heterogeneity regarding the differential exposure by SES, but the air pollution model was not found to influence heterogeneity regarding the differential susceptibility. The study showed air pollution models can influence the assessment of disparities in exposure according to SES in Montreal but not that of disparities in susceptibility.

Benmarhnia, T, Delpla I, Schwarz L, Rodriguez MJ, Levallois P.  2018.  Heterogeneity in the relationship between disinfection by-products in drinking water and cancer: A systematic review. International Journal of Environmental Research and Public Health. 15   10.3390/ijerph15050979   AbstractWebsite

The epidemiological evidence demonstrating the effect of disinfection by-products (DBPs) from drinking water on colon and rectal cancers is well documented. However, no systematic assessment has been conducted to assess the potential effect measure modification (EMM) in the relationship between DBPs and cancer. The objective of this paper is to conduct a systematic literature review to determine the extent to which EMM has been assessed in the relationship between DBPs in drinking water in past epidemiological studies. Selected articles (n = 19) were reviewed, and effect estimates and covariates that could have been used in an EMM assessment were gathered. Approximately half of the studies assess EMM (n = 10), but the majority of studies only estimate it relative to sex subgroups (n = 6 for bladder cancer and n = 2 both for rectal and colon cancers). Although EMM is rarely assessed, several variables that could have a potential modification effect are routinely collected in these studies, such as socioeconomic status or age. The role of environmental exposures through drinking water can play an important role and contribute to cancer disparities. We encourage a systematic use of subgroup analysis to understand which populations or territories are more vulnerable to the health impacts of DBPs.

Schinasi, LH, Benmarhnia T, De Roos AJ.  2018.  Modification of the association between high ambient temperature and health by urban microclimate indicators: A systematic review and meta-analysis. Environmental Research. 161:168-180.   10.1016/j.envres.2017.11.004   AbstractWebsite

Background: Landscape characteristics, including vegetation and impervious surfaces, influence urban micro climates and may lead to within-city differences in the adverse health effects of high ambient temperatures. Objective: Our objective was to quantitatively summarize the epidemiologic literature that assessed microclimate indicators as effect measure modifiers (EMM) of the association between ambient temperature and mortality or morbidity. Methods: We systematically identified papers and abstracted relative risk estimates for hot and cool micro climate indicator strata. We calculated the ratio of the relative risks (RRR) and 95% confidence intervals (95% CI) to assess differences in health effects across strata, and pooled the RRR estimates using random effects meta analyses. Results: Eleven papers were retained. In the pooled analyses, people living in hotter areas within cities (based on land surface temperature or modeled estimates of air temperature) had 6% higher risk of mortality/morbidity compared to those in cooler areas (95% CI: 1.03-1.09). Those living in less vegetated areas had 5% higher risk compared to those living in more vegetated areas (95% CI: 1.00-1.11). Discussion: There is epidemiologic evidence that those living in hotter, and less vegetated areas of cities have higher risk of morbidity or mortality from higher ambient temperature. Further research with improved assessment of landscape characteristics and investigation of the joint effects of physiologic adaptation and landscape will advance the current understanding. Conclusion: This review provides quantitative evidence that intra-urban differences in landscape characteristics and micro-urban heat islands contribute to within-city variability in the health effects of high ambient temperatures.