Pub Date : 2022-03-31DOI: 10.1097/EE9.0000000000000206
P. Masselot, T. Ouarda, C. Charron, C. Campagna, É. Lavigne, A. St‐Hilaire, F. Chebana, P. Valois, P. Gosselin
Background: Heat-related mortality is an increasingly important public health burden that is expected to worsen with climate change. In addition to long-term trends, there are also interannual variations in heat-related mortality that are of interest for efficient planning of health services. Large-scale climate patterns have an important influence on summer weather and therefore constitute important tools to understand and predict the variations in heat-related mortality. Methods: In this article, we propose to model summer heat-related mortality using seven climate indices through a two-stage analysis using data covering the period 1981–2018 in two metropolitan areas of the province of Québec (Canada): Montréal and Québec. In the first stage, heat attributable fractions are estimated through a time series regression design and distributed lag nonlinear specification. We consider different definitions of heat. In the second stage, estimated attributable fractions are predicted using climate index curves through a functional linear regression model. Results: Results indicate that the Atlantic Multidecadal Oscillation is the best predictor of heat-related mortality in both Montréal and Québec and that it can predict up to 20% of the interannual variability. Conclusion: We found evidence that one climate index is predictive of summer heat-related mortality. More research is needed with longer time series and in different spatial contexts. The proposed analysis and the results may nonetheless help public health authorities plan for future mortality related to summer heat.
{"title":"Heat-related mortality prediction using low-frequency climate oscillation indices: Case studies of the cities of Montréal and Québec, Canada","authors":"P. Masselot, T. Ouarda, C. Charron, C. Campagna, É. Lavigne, A. St‐Hilaire, F. Chebana, P. Valois, P. Gosselin","doi":"10.1097/EE9.0000000000000206","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000206","url":null,"abstract":"Background: Heat-related mortality is an increasingly important public health burden that is expected to worsen with climate change. In addition to long-term trends, there are also interannual variations in heat-related mortality that are of interest for efficient planning of health services. Large-scale climate patterns have an important influence on summer weather and therefore constitute important tools to understand and predict the variations in heat-related mortality. Methods: In this article, we propose to model summer heat-related mortality using seven climate indices through a two-stage analysis using data covering the period 1981–2018 in two metropolitan areas of the province of Québec (Canada): Montréal and Québec. In the first stage, heat attributable fractions are estimated through a time series regression design and distributed lag nonlinear specification. We consider different definitions of heat. In the second stage, estimated attributable fractions are predicted using climate index curves through a functional linear regression model. Results: Results indicate that the Atlantic Multidecadal Oscillation is the best predictor of heat-related mortality in both Montréal and Québec and that it can predict up to 20% of the interannual variability. Conclusion: We found evidence that one climate index is predictive of summer heat-related mortality. More research is needed with longer time series and in different spatial contexts. The proposed analysis and the results may nonetheless help public health authorities plan for future mortality related to summer heat.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42483865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-30DOI: 10.1097/EE9.0000000000000204
Y. Nunez, A. Boehme, Jeff Goldsmith, Maggie Li, A. van Donkelaar, M. Weisskopf, D. Re, R. Martin, M. Kioumourtzoglou
Background: Long-term exposure to fine particulate matter (PM2.5) has been associated with disease aggravation in amyotrophic lateral sclerosis (ALS). In this study, we characterized long-term exposure to six major PM2.5 components and their individual association with disease aggravation in ALS. Methods: We leveraged 15 years of data from the New York Department of Health Statewide Planning and Research Cooperative System (2000–2014) to calculate annual ALS first hospitalizations in New York State. We used the first hospital admission as a surrogate of disease aggravation and a prediction model to estimate population-weighted annual black carbon, organic matter (OM), nitrate, sulfate, sea salt, and soil concentrations at the county level. We used a multi-pollutant mixed quasi-Poisson model with county-specific random intercepts to estimate rate ratios (RR) of 1-year exposure to each PM2.5 component and disease aggravation in ALS, adjusting for potential confounders. Results: We observed 5,655 first ALS-related hospitalizations. The annual average hospitalization count per county was 6.08 and the average PM2.5 total mass concentration per county was 8.1 μg/m3—below the United States’ National Ambient Air Quality Standard of 12 μg/m3. We found a consistent positive association between ALS aggravation and OM (1.17, 95% confidence intervals [CI], 1.11, 1.24 per standard deviation [SD] increase) and a negative association with soil (RR = 0.91, 95% CI, 0.86, 0.97). Conclusion: Our findings suggest that PM2.5 composition may influence its effect on ALS. We found that annual increases in county-level particulate OM may be associated with disease aggravation in ALS, even at PM2.5 levels below current standards.
{"title":"PM2.5 composition and disease aggravation in amyotrophic lateral sclerosis","authors":"Y. Nunez, A. Boehme, Jeff Goldsmith, Maggie Li, A. van Donkelaar, M. Weisskopf, D. Re, R. Martin, M. Kioumourtzoglou","doi":"10.1097/EE9.0000000000000204","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000204","url":null,"abstract":"Background: Long-term exposure to fine particulate matter (PM2.5) has been associated with disease aggravation in amyotrophic lateral sclerosis (ALS). In this study, we characterized long-term exposure to six major PM2.5 components and their individual association with disease aggravation in ALS. Methods: We leveraged 15 years of data from the New York Department of Health Statewide Planning and Research Cooperative System (2000–2014) to calculate annual ALS first hospitalizations in New York State. We used the first hospital admission as a surrogate of disease aggravation and a prediction model to estimate population-weighted annual black carbon, organic matter (OM), nitrate, sulfate, sea salt, and soil concentrations at the county level. We used a multi-pollutant mixed quasi-Poisson model with county-specific random intercepts to estimate rate ratios (RR) of 1-year exposure to each PM2.5 component and disease aggravation in ALS, adjusting for potential confounders. Results: We observed 5,655 first ALS-related hospitalizations. The annual average hospitalization count per county was 6.08 and the average PM2.5 total mass concentration per county was 8.1 μg/m3—below the United States’ National Ambient Air Quality Standard of 12 μg/m3. We found a consistent positive association between ALS aggravation and OM (1.17, 95% confidence intervals [CI], 1.11, 1.24 per standard deviation [SD] increase) and a negative association with soil (RR = 0.91, 95% CI, 0.86, 0.97). Conclusion: Our findings suggest that PM2.5 composition may influence its effect on ALS. We found that annual increases in county-level particulate OM may be associated with disease aggravation in ALS, even at PM2.5 levels below current standards.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41694774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-22eCollection Date: 2022-04-01DOI: 10.1097/EE9.0000000000000203
Chloe Friedman, Dana Dabelea, Lizan D Bloemsma, Deborah S K Thomas, Jennifer L Peel, John L Adgate, Sheryl Magzamen, Sheena E Martenies, William B Allshouse, Anne P Starling
Prenatal air pollution exposure has been associated with adverse childhood cardiometabolic outcomes. It is unknown whether evidence of metabolic disruption associated with air pollution is identifiable at birth. We examined exposure to prenatal ambient air pollution and cord blood cardiometabolic biomarkers among 812 mother-infant pairs in the Healthy Start study.
Methods: Using inverse-distance-weighted interpolation of ambient concentrations obtained from stationary monitors, we estimated daily particulate matter ≤2.5 micrometers (PM2.5) and ozone (O3) concentrations at participant residences. Daily estimates were averaged by trimester, full-pregnancy, and the 7 and 30 days prior to delivery. Associations of air pollution with the following cord blood biomarkers were estimated via multivariable linear regression: glucose, insulin, glucose/insulin ratio (GIR), leptin, high-density lipoprotein (HDL) cholesterol, non-HDL cholesterol, free fatty acids, and triglycerides.
Results: In this Denver-based cohort, PM2.5 concentrations were lower than in many US urban areas, but O3 concentrations regularly exceeded federal air quality standards. Higher O3 concentrations during pregnancy were consistently associated with higher insulin and lower GIR in cord blood. For example, an interquartile range increase in full pregnancy O3 (6.3 parts per billion [ppb]) was associated with 0.13 log-µIU/ml (95% confidence interval [CI] = 0.04, 0.22) higher cord blood insulin, after adjusting for PM2.5 and other confounders. We found positive, but generally nonsignificant, associations between PM2.5 and leptin and isolated associations between pollutants during certain exposure periods and lipids.
Conclusions: In this cohort with moderately high O3 exposure, prenatal concentrations of O3 were positively associated with cord blood insulin. Future studies should examine the implications for offspring long-term health.
{"title":"Ambient air pollution during pregnancy and cardiometabolic biomarkers in cord blood.","authors":"Chloe Friedman, Dana Dabelea, Lizan D Bloemsma, Deborah S K Thomas, Jennifer L Peel, John L Adgate, Sheryl Magzamen, Sheena E Martenies, William B Allshouse, Anne P Starling","doi":"10.1097/EE9.0000000000000203","DOIUrl":"10.1097/EE9.0000000000000203","url":null,"abstract":"<p><p>Prenatal air pollution exposure has been associated with adverse childhood cardiometabolic outcomes. It is unknown whether evidence of metabolic disruption associated with air pollution is identifiable at birth. We examined exposure to prenatal ambient air pollution and cord blood cardiometabolic biomarkers among 812 mother-infant pairs in the Healthy Start study.</p><p><strong>Methods: </strong>Using inverse-distance-weighted interpolation of ambient concentrations obtained from stationary monitors, we estimated daily particulate matter ≤2.5 micrometers (PM<sub>2.5</sub>) and ozone (O<sub>3</sub>) concentrations at participant residences. Daily estimates were averaged by trimester, full-pregnancy, and the 7 and 30 days prior to delivery. Associations of air pollution with the following cord blood biomarkers were estimated via multivariable linear regression: glucose, insulin, glucose/insulin ratio (GIR), leptin, high-density lipoprotein (HDL) cholesterol, non-HDL cholesterol, free fatty acids, and triglycerides.</p><p><strong>Results: </strong>In this Denver-based cohort, PM<sub>2.5</sub> concentrations were lower than in many US urban areas, but O<sub>3</sub> concentrations regularly exceeded federal air quality standards. Higher O<sub>3</sub> concentrations during pregnancy were consistently associated with higher insulin and lower GIR in cord blood. For example, an interquartile range increase in full pregnancy O<sub>3</sub> (6.3 parts per billion [ppb]) was associated with 0.13 log-µIU/ml (95% confidence interval [CI] = 0.04, 0.22) higher cord blood insulin, after adjusting for PM<sub>2.5</sub> and other confounders. We found positive, but generally nonsignificant, associations between PM<sub>2.5</sub> and leptin and isolated associations between pollutants during certain exposure periods and lipids.</p><p><strong>Conclusions: </strong>In this cohort with moderately high O<sub>3</sub> exposure, prenatal concentrations of O<sub>3</sub> were positively associated with cord blood insulin. Future studies should examine the implications for offspring long-term health.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":"e203"},"PeriodicalIF":3.8,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46267379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-25DOI: 10.1097/ee9.0000000000000202
[This corrects the article DOI: 10.1097/EE9.0000000000000174.].
[这更正了文章DOI:10.1097/EE90000000000000174.]。
{"title":"Erratum: Ambient air pollution associated with lower academic achievement among US children: A nationwide panel study of school districts: Erratum.","authors":"","doi":"10.1097/ee9.0000000000000202","DOIUrl":"https://doi.org/10.1097/ee9.0000000000000202","url":null,"abstract":"[This corrects the article DOI: 10.1097/EE9.0000000000000174.].","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"6 2 1","pages":"e202"},"PeriodicalIF":3.6,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41535488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-22DOI: 10.1097/ee9.0000000000000199
Ankan Mukherjee Das, R. Janardhanan
{"title":"Accelerating Research and Policy on PFAS in India","authors":"Ankan Mukherjee Das, R. Janardhanan","doi":"10.1097/ee9.0000000000000199","DOIUrl":"https://doi.org/10.1097/ee9.0000000000000199","url":null,"abstract":"","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43997204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-18DOI: 10.1097/EE9.0000000000000200
Noelle S. Liao, S. K. Van Den Eeden, S. Sidney, K. Deosaransingh, J. Schwartz, S. Uong, S. Alexeeff
Background: Fine particulate matter (PM2.5) is a known risk factor for cardiovascular disease (CVD). Neighborhood walkability and greenness may also be associated with CVD, but there is limited evidence on their joint or interacting effects with PM2.5. Methods: Cox proportional hazard models were used to estimate the risk of CVD mortality among adults with a history of acute myocardial infarction and/or stroke living in Northern California. We assessed the independent and joint effects of walkability, greenness (Normalized Differentiated Vegetation Index [NDVI]), and PM2.5 at residential addresses, controlling for age, sex, race/ethnicity, comorbidities, BMI, smoking, revascularization, medications, and socioeconomic status. Results: Greenness had a nonlinear association with CVD mortality (P = 0.038), with notably protective effects (HR = 0.87 [95% confidence interval {CI} = 0.78, 0.97]) at higher greenness levels (NDVI ≥ 0.3) and moderate attenuation after adjusting for PM2.5 (HR = 0.92 [95% CI = 0.82, 1.03]) per 0.1 increase in NDVI. Walkability had no independent effect on CVD mortality. PM2.5 had a strong independent effect in models adjusted for greenness and walkability (HR = 1.20 [95% CI = 1.08, 1.33)) per 10 μg/m3 increase in PM2.5. There was an interaction between walkability and PM2.5 (P = 0.037), where PM2.5 had slightly stronger associations in more walkable than less walkable neighborhoods (HR = 1.23 [95% CI = 1.06, 1.42] vs. 1.17 [95% CI = 1.04, 1.32]) per 10 μg/m3 increase in PM2.5. Greenness had no interaction with PM2.5 (P = 0.768) nor walkability (P = 0.385). Conclusions: High greenness may be protective of CVD mortality among adults with CVD history. PM2.5 associated CVD mortality risk varies slightly by level of neighborhood walkability, though these small differences may not be clinically meaningful.
背景:细颗粒物(PM2.5)是已知的心血管疾病(CVD)危险因素。社区步行和绿化也可能与心血管疾病有关，但关于它们与PM2.5的联合或相互作用的证据有限。方法:采用Cox比例风险模型估计北加州有急性心肌梗死和/或中风史的成人心血管疾病死亡风险。在控制年龄、性别、种族/民族、合并症、BMI、吸烟、血运重建、药物和社会经济地位的情况下，我们评估了居住地址的步行性、绿化率(归一化分化植被指数[NDVI])和PM2.5的独立和联合影响。结果:绿化与心血管疾病死亡率呈非线性相关(P = 0.038)，在较高的绿化水平(NDVI≥0.3)和调整PM2.5后的中度衰减(HR = 0.92 [95% CI = 0.82, 1.03])每增加0.1，具有显著的保护作用(HR = 0.87[95%可信区间{CI} = 0.78, 0.97])。可步行性对心血管疾病死亡率无独立影响。PM2.5每增加10 μg/m3，在绿色和步行性调整后的模型中，PM2.5具有很强的独立效应(HR = 1.20 [95% CI = 1.08, 1.33))。可步行性与PM2.5之间存在交互作用(P = 0.037)， PM2.5每增加10 μg/m3，可步行性较好的社区与PM2.5的关联略强(HR = 1.23 [95% CI = 1.06, 1.42] vs. 1.17 [95% CI = 1.04, 1.32])。绿化度与PM2.5无交互作用(P = 0.768)，步行度与PM2.5无交互作用(P = 0.385)。结论:高绿度可能对有心血管疾病病史的成年人的心血管疾病死亡率有保护作用。PM2.5相关的心血管疾病死亡风险因社区步行水平的不同而略有不同，尽管这些微小的差异可能没有临床意义。
{"title":"Joint associations between neighborhood walkability, greenness, and particulate air pollution on cardiovascular mortality among adults with a history of stroke or acute myocardial infarction","authors":"Noelle S. Liao, S. K. Van Den Eeden, S. Sidney, K. Deosaransingh, J. Schwartz, S. Uong, S. Alexeeff","doi":"10.1097/EE9.0000000000000200","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000200","url":null,"abstract":"Background: Fine particulate matter (PM2.5) is a known risk factor for cardiovascular disease (CVD). Neighborhood walkability and greenness may also be associated with CVD, but there is limited evidence on their joint or interacting effects with PM2.5. Methods: Cox proportional hazard models were used to estimate the risk of CVD mortality among adults with a history of acute myocardial infarction and/or stroke living in Northern California. We assessed the independent and joint effects of walkability, greenness (Normalized Differentiated Vegetation Index [NDVI]), and PM2.5 at residential addresses, controlling for age, sex, race/ethnicity, comorbidities, BMI, smoking, revascularization, medications, and socioeconomic status. Results: Greenness had a nonlinear association with CVD mortality (P = 0.038), with notably protective effects (HR = 0.87 [95% confidence interval {CI} = 0.78, 0.97]) at higher greenness levels (NDVI ≥ 0.3) and moderate attenuation after adjusting for PM2.5 (HR = 0.92 [95% CI = 0.82, 1.03]) per 0.1 increase in NDVI. Walkability had no independent effect on CVD mortality. PM2.5 had a strong independent effect in models adjusted for greenness and walkability (HR = 1.20 [95% CI = 1.08, 1.33)) per 10 μg/m3 increase in PM2.5. There was an interaction between walkability and PM2.5 (P = 0.037), where PM2.5 had slightly stronger associations in more walkable than less walkable neighborhoods (HR = 1.23 [95% CI = 1.06, 1.42] vs. 1.17 [95% CI = 1.04, 1.32]) per 10 μg/m3 increase in PM2.5. Greenness had no interaction with PM2.5 (P = 0.768) nor walkability (P = 0.385). Conclusions: High greenness may be protective of CVD mortality among adults with CVD history. PM2.5 associated CVD mortality risk varies slightly by level of neighborhood walkability, though these small differences may not be clinically meaningful.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46589821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-18DOI: 10.1097/EE9.0000000000000198
D. Hicks
Background: A number of papers by Young and collaborators have criticized epidemiological studies and meta-analyses of air pollution hazards using a graphical method that the authors call a P value plot, claiming to find zero effects, heterogeneity, and P hacking. However, the P value plot method has not been validated in a peer-reviewed publication. The aim of this study was to investigate the statistical and evidentiary properties of this method. Methods: A simulation was developed to create studies and meta-analyses with known real effects δ, integrating two quantifiable conceptions of evidence from the philosophy of science literature. The simulation and analysis is publicly available and automatically reproduced. Results: In this simulation, the plot did not provide evidence for heterogeneity or P hacking with respect to any condition. Under the right conditions, the plot can provide evidence of zero effects; but these conditions are not satisfied in any actual use by Young and collaborators. Conclusion: The P value plot does not provide evidence to support the skeptical claims about air pollution hazards made by Young and collaborators.
{"title":"The P value plot does not provide evidence against air pollution hazards","authors":"D. Hicks","doi":"10.1097/EE9.0000000000000198","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000198","url":null,"abstract":"Background: A number of papers by Young and collaborators have criticized epidemiological studies and meta-analyses of air pollution hazards using a graphical method that the authors call a P value plot, claiming to find zero effects, heterogeneity, and P hacking. However, the P value plot method has not been validated in a peer-reviewed publication. The aim of this study was to investigate the statistical and evidentiary properties of this method. Methods: A simulation was developed to create studies and meta-analyses with known real effects δ, integrating two quantifiable conceptions of evidence from the philosophy of science literature. The simulation and analysis is publicly available and automatically reproduced. Results: In this simulation, the plot did not provide evidence for heterogeneity or P hacking with respect to any condition. Under the right conditions, the plot can provide evidence of zero effects; but these conditions are not satisfied in any actual use by Young and collaborators. Conclusion: The P value plot does not provide evidence to support the skeptical claims about air pollution hazards made by Young and collaborators.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44122640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-17DOI: 10.1097/EE9.0000000000000185
A. Pronk, Miranda Loh, E. Kuijpers, M. Albin, Jenny Selander, L. Godderis, Manosij Ghosh, Roel C. H. Vermeulen, S. Peters, I. Mehlum, M. Turner, V. Schlünssen, M. Goldberg, M. Kogevinas, Barbara N Harding, S. Solovieva, T. Garani-Papadatos, M. V. van Tongeren, R. Stierum
Exposures at work have a major impact on noncommunicable diseases (NCDs). Current risk reduction policies and strategies are informed by existing scientific evidence, which is limited due to the challenges of studying the complex relationship between exposure at work and outside work and health. We define the working life exposome as all occupational and related nonoccupational exposures. The latter includes nonoccupational exposures that may be directly or indirectly influenced by or interact with the working life of the individual in their relation to health. The Exposome Project for Health and Occupational Research aims to advance knowledge on the complex working life exposures in relation to disease beyond the single high exposure–single health outcome paradigm, mapping and relating interrelated exposures to inherent biological pathways, key body functions, and health. This will be achieved by combining (1) large-scale harmonization and pooling of existing European cohorts systematically looking at multiple exposures and diseases, with (2) the collection of new high-resolution external and internal exposure data. Methods and tools to characterize the working life exposome will be developed and applied, including sensors, wearables, a harmonized job exposure matrix (EuroJEM), noninvasive biomonitoring, omics, data mining, and (bio)statistics. The toolbox of developed methods and knowledge will be made available to policy makers, occupational health practitioners, and scientists. Advanced knowledge on working life exposures in relation to NCDs will serve as a basis for evidence-based and cost-effective preventive policies and actions. The toolbox will also enable future scientists to further expand the working life exposome knowledge base.
{"title":"Applying the exposome concept to working life health","authors":"A. Pronk, Miranda Loh, E. Kuijpers, M. Albin, Jenny Selander, L. Godderis, Manosij Ghosh, Roel C. H. Vermeulen, S. Peters, I. Mehlum, M. Turner, V. Schlünssen, M. Goldberg, M. Kogevinas, Barbara N Harding, S. Solovieva, T. Garani-Papadatos, M. V. van Tongeren, R. Stierum","doi":"10.1097/EE9.0000000000000185","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000185","url":null,"abstract":"Exposures at work have a major impact on noncommunicable diseases (NCDs). Current risk reduction policies and strategies are informed by existing scientific evidence, which is limited due to the challenges of studying the complex relationship between exposure at work and outside work and health. We define the working life exposome as all occupational and related nonoccupational exposures. The latter includes nonoccupational exposures that may be directly or indirectly influenced by or interact with the working life of the individual in their relation to health. The Exposome Project for Health and Occupational Research aims to advance knowledge on the complex working life exposures in relation to disease beyond the single high exposure–single health outcome paradigm, mapping and relating interrelated exposures to inherent biological pathways, key body functions, and health. This will be achieved by combining (1) large-scale harmonization and pooling of existing European cohorts systematically looking at multiple exposures and diseases, with (2) the collection of new high-resolution external and internal exposure data. Methods and tools to characterize the working life exposome will be developed and applied, including sensors, wearables, a harmonized job exposure matrix (EuroJEM), noninvasive biomonitoring, omics, data mining, and (bio)statistics. The toolbox of developed methods and knowledge will be made available to policy makers, occupational health practitioners, and scientists. Advanced knowledge on working life exposures in relation to NCDs will serve as a basis for evidence-based and cost-effective preventive policies and actions. The toolbox will also enable future scientists to further expand the working life exposome knowledge base.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47586093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-11DOI: 10.1097/EE9.0000000000000196
Joanne Kim, Seungmi Yang, E. Moodie, M. Obida, R. Bornman, B. Eskenazi, J. Chevrier
Background: As part of malaria control programs, many countries spray dichlorodiphenyltrichloroethane (DDT) or pyrethroid insecticides inside dwellings in a practice called indoor residual spraying that results in high levels of exposure to local populations. Gestational exposure to these endocrine- and metabolism-disrupting chemicals may influence child cardiometabolic health. Methods: We measured the serum concentration of DDT and dichlorodiphenyldichloroethylene (DDE) and urinary concentration of pyrethroid metabolites (cis-DBCA, cis-DCCA, trans-DCCA, 3-PBA) in peripartum samples collected between August 2012 and December 2013 from 637 women participating in the Venda Health Examination of Mothers, Babies and their Environment (VHEMBE), a birth cohort study based in Limpopo, South Africa. We applied marginal structural models to estimate the relationship between biomarker concentrations and child-size (height and weight), adiposity (body mass index [BMI], body fat percentage, waist circumference) and blood pressure at 5 years of age. Results: Maternal concentrations of all four pyrethroid metabolites were associated with lower adiposity including reduced BMI z-scores, smaller waist circumferences, and decreased body fat percentages. Reductions in BMI z-score were observed only among children of mothers with sufficient energy intake during pregnancy (βcis-DCCA, trans-DCCA=−0.4, 95% confidence interval (CI) = −0.7,−0.1; pinteraction=0.03 and 0.04, respectively) but there was no evidence of effect modification for the other measures of adiposity. Maternal p,p’-DDT concentrations were associated with a reduction in body fat percentage (β = −0.4%, 95% CI = −0.8,−0.0). Conclusions: Gestational exposure to pyrethroids may reduce adiposity in children at 5 years of age.
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Pub Date : 2022-02-07eCollection Date: 2022-02-01DOI: 10.1097/EE9.0000000000000197
[This corrects the article DOI: 10.1097/EE9.0000000000000170.].
[这更正了文章DOI: 10.1097/EE9.0000000000000170.]。
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