Pub Date : 2023-08-25eCollection Date: 2023-10-01DOI: 10.1097/EE9.0000000000000266
Ettie M Lipner, Joshua P French, Rachel A Mercaldo, Stephen Nelson, Adrian M Zelazny, Julia E Marshall, Michael Strong, Joseph O Falkinham, D Rebecca Prevots
Rationale: The prevalence of nontuberculous mycobacterial (NTM) pulmonary disease varies geographically in the United States. Previous studies indicate that the presence of certain water-quality constituents in source water increases NTM infection risk.
Objective: To identify water-quality constituents that influence the risk of NTM pulmonary infection in persons with cystic fibrosis in the United States.
Methods: We conducted a population-based case-control study using NTM incidence data collected from the Cystic Fibrosis Foundation Patient Registry during 2010-2019. We linked patient zip code to the county and associated patient county of residence with surface water data extracted from the Water Quality Portal. We used logistic regression models to estimate the odds of NTM infection as a function of water-quality constituents. We modeled two outcomes: pulmonary infection due to Mycobacterium avium complex (MAC) and Mycobacterium abscessus species.
Results: We identified 484 MAC cases, 222 M. abscessus cases and 2816 NTM-negative cystic fibrosis controls resident in 11 states. In multivariable models, we found that for every 1-standardized unit increase in the log concentration of sulfate and vanadium in surface water at the county level, the odds of infection increased by 39% and 21%, respectively, among persons with cystic fibrosis with MAC compared with cystic fibrosis-NTM-negative controls. When modeling M. abscessus as the dependent variable, every 1-standardized unit increase in the log concentration of molybdenum increased the odds of infection by 36%.
Conclusions: These findings suggest that naturally occurring and anthropogenic water-quality constituents may influence the NTM abundance in water sources that supply municipal water systems, thereby increasing MAC and M. abscessus infection risk.
{"title":"The risk of pulmonary NTM infections and water-quality constituents among persons with cystic fibrosis in the United States, 2010-2019.","authors":"Ettie M Lipner, Joshua P French, Rachel A Mercaldo, Stephen Nelson, Adrian M Zelazny, Julia E Marshall, Michael Strong, Joseph O Falkinham, D Rebecca Prevots","doi":"10.1097/EE9.0000000000000266","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000266","url":null,"abstract":"<p><strong>Rationale: </strong>The prevalence of nontuberculous mycobacterial (NTM) pulmonary disease varies geographically in the United States. Previous studies indicate that the presence of certain water-quality constituents in source water increases NTM infection risk.</p><p><strong>Objective: </strong>To identify water-quality constituents that influence the risk of NTM pulmonary infection in persons with cystic fibrosis in the United States.</p><p><strong>Methods: </strong>We conducted a population-based case-control study using NTM incidence data collected from the Cystic Fibrosis Foundation Patient Registry during 2010-2019. We linked patient zip code to the county and associated patient county of residence with surface water data extracted from the Water Quality Portal. We used logistic regression models to estimate the odds of NTM infection as a function of water-quality constituents. We modeled two outcomes: pulmonary infection due to <i>Mycobacterium avium</i> complex (MAC) and <i>Mycobacterium abscessus</i> species.</p><p><strong>Results: </strong>We identified 484 MAC cases, 222 <i>M. abscessus</i> cases and 2816 NTM-negative cystic fibrosis controls resident in 11 states. In multivariable models, we found that for every 1-standardized unit increase in the log concentration of sulfate and vanadium in surface water at the county level, the odds of infection increased by 39% and 21%, respectively, among persons with cystic fibrosis with MAC compared with cystic fibrosis-NTM-negative controls. When modeling <i>M. abscessus</i> as the dependent variable, every 1-standardized unit increase in the log concentration of molybdenum increased the odds of infection by 36%.</p><p><strong>Conclusions: </strong>These findings suggest that naturally occurring and anthropogenic water-quality constituents may influence the NTM abundance in water sources that supply municipal water systems, thereby increasing MAC and <i>M. abscessus</i> infection risk.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"7 5","pages":"e266"},"PeriodicalIF":3.6,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569765/pdf/ee9-7-e266.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41233385","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 : 2023-08-24eCollection Date: 2023-10-01DOI: 10.1097/EE9.0000000000000263
Nadia G Diamond-Smith, Adrienne Epstein, Marya G Zlatnik, Emily Treleaven
Background: Past research on the impact of climatic events, such as drought, on birth outcomes has primarily been focused in Africa, with less research in South Asia, including Nepal. Existing evidence has generally found that drought impacts birthweight and infant sex, with differences by trimester. Additionally, less research has looked at the impact of excess rain on birth outcomes or focused on the impact of rainfall extremes in the preconception period. Using data from a large demographic surveillance system in Nepal, combined with a novel measure of drought/excess rainfall, we explore the impact of these on birthweight by time in pregnancy.
Methods: Using survey data from the 2016 to 2019 Chitwan Valley Study in rural Nepal combined with data from Climate Hazards InfraRed Precipitation with Station, we explored the association between excess rainfall and drought and birthweight, looking at exposure in the preconception period, and by trimester of pregnancy. We also explore the impact of excess rainfall and drought on infant sex and delivery with a skilled birth attendant. We used multilevel regressions and explored for effect modification by maternal age.
Results: Drought in the first trimester is associated with lower birthweight (β = -82.9 g; 95% confidence interval [CI] = 164.7, -1.2) and drought in the preconception period with a high likelihood of having a male (odds ratio [OR] = 1.41; 95% CI = 1.01, 2.01). Excess rainfall in the first trimester is associated with high birthweight (β = 111.6 g; 95% CI = 20.5, 202.7) and higher odds of having a male (OR = 1.48; 95% CI = 1.02, 2.16), and in the third trimester with higher odds of low birth weight (OR = 2.50; 95% CI = 1.40, 4.45).
Conclusions: Increasing rainfall extremes will likely impact birth outcomes and could have implications for sex ratios at birth.
{"title":"The association between timing in pregnancy of drought and excess rainfall, infant sex, and birthweight: Evidence from Nepal.","authors":"Nadia G Diamond-Smith, Adrienne Epstein, Marya G Zlatnik, Emily Treleaven","doi":"10.1097/EE9.0000000000000263","DOIUrl":"10.1097/EE9.0000000000000263","url":null,"abstract":"<p><strong>Background: </strong>Past research on the impact of climatic events, such as drought, on birth outcomes has primarily been focused in Africa, with less research in South Asia, including Nepal. Existing evidence has generally found that drought impacts birthweight and infant sex, with differences by trimester. Additionally, less research has looked at the impact of excess rain on birth outcomes or focused on the impact of rainfall extremes in the preconception period. Using data from a large demographic surveillance system in Nepal, combined with a novel measure of drought/excess rainfall, we explore the impact of these on birthweight by time in pregnancy.</p><p><strong>Methods: </strong>Using survey data from the 2016 to 2019 Chitwan Valley Study in rural Nepal combined with data from Climate Hazards InfraRed Precipitation with Station, we explored the association between excess rainfall and drought and birthweight, looking at exposure in the preconception period, and by trimester of pregnancy. We also explore the impact of excess rainfall and drought on infant sex and delivery with a skilled birth attendant. We used multilevel regressions and explored for effect modification by maternal age.</p><p><strong>Results: </strong>Drought in the first trimester is associated with lower birthweight (<i>β</i> = -82.9 g; 95% confidence interval [CI] = 164.7, -1.2) and drought in the preconception period with a high likelihood of having a male (odds ratio [OR] = 1.41; 95% CI = 1.01, 2.01). Excess rainfall in the first trimester is associated with high birthweight (<i>β</i> = 111.6 g; 95% CI = 20.5, 202.7) and higher odds of having a male (OR = 1.48; 95% CI = 1.02, 2.16), and in the third trimester with higher odds of low birth weight (OR = 2.50; 95% CI = 1.40, 4.45).</p><p><strong>Conclusions: </strong>Increasing rainfall extremes will likely impact birth outcomes and could have implications for sex ratios at birth.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"7 5","pages":"e263"},"PeriodicalIF":3.6,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/62/6c/ee9-7-e263.PMC10569756.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41233374","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 : 2022-06-01DOI: 10.1097/EE9.0000000000000212
J. Laiho, O. Laitinen, Johannes Malkamäki, L. Puustinen, A. Sinkkonen, J. Pärkkä, H. Hyöty
The incidence of immune-mediated diseases (IMDs) is increasing rapidly in the developed countries constituting a huge medical, economic, and societal challenge. The exposome plays an important role since genetic factors cannot explain such a rapid change. In the Human Exposomic Determinants of Immune Mediated Diseases (HEDIMED) project, altogether 22 academic and industrial partners join their multidisciplinary forces to identify exposomic determinants that are driving the IMD epidemic. The project is based on a combination of data and biological samples from large clinical cohorts constituting about 350,000 pregnant women, 30,000 children prospectively followed from birth, and 7,000 children from cross-sectional studies. HEDIMED focuses on common chronic IMDs that cause a significant disease burden, including type 1 diabetes, celiac disease, allergy, and asthma. Exposomic disease determinants and the underlying biological pathways will be identified by an exploratory approach using advanced omics and multiplex technologies combined with cutting-edge data mining technologies. Emphasis is put on fetal and childhood exposome since the IMD disease processes start early. Inclusion of several IMDs makes it possible to identify common exposomic determinants for the diseases, thus facilitating the development of widely operating preventive and curative treatments. HEDIMED includes data and samples from birth cohorts and clinical trials that have used exposomic interventions and cell and organ culture models to identify mechanisms of the observed associations. Importantly, HEDIMED generates a toolbox that offers science-based functional tools for key stakeholders to control the IMD epidemic. Altogether, HEDIMED aims at innovations, which become widely exploited in diagnostic, therapeutic, preventive, and health economic approaches.
{"title":"Exposomic determinants of immune-mediated diseases","authors":"J. Laiho, O. Laitinen, Johannes Malkamäki, L. Puustinen, A. Sinkkonen, J. Pärkkä, H. Hyöty","doi":"10.1097/EE9.0000000000000212","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000212","url":null,"abstract":"The incidence of immune-mediated diseases (IMDs) is increasing rapidly in the developed countries constituting a huge medical, economic, and societal challenge. The exposome plays an important role since genetic factors cannot explain such a rapid change. In the Human Exposomic Determinants of Immune Mediated Diseases (HEDIMED) project, altogether 22 academic and industrial partners join their multidisciplinary forces to identify exposomic determinants that are driving the IMD epidemic. The project is based on a combination of data and biological samples from large clinical cohorts constituting about 350,000 pregnant women, 30,000 children prospectively followed from birth, and 7,000 children from cross-sectional studies. HEDIMED focuses on common chronic IMDs that cause a significant disease burden, including type 1 diabetes, celiac disease, allergy, and asthma. Exposomic disease determinants and the underlying biological pathways will be identified by an exploratory approach using advanced omics and multiplex technologies combined with cutting-edge data mining technologies. Emphasis is put on fetal and childhood exposome since the IMD disease processes start early. Inclusion of several IMDs makes it possible to identify common exposomic determinants for the diseases, thus facilitating the development of widely operating preventive and curative treatments. HEDIMED includes data and samples from birth cohorts and clinical trials that have used exposomic interventions and cell and organ culture models to identify mechanisms of the observed associations. Importantly, HEDIMED generates a toolbox that offers science-based functional tools for key stakeholders to control the IMD epidemic. Altogether, HEDIMED aims at innovations, which become widely exploited in diagnostic, therapeutic, preventive, and health economic approaches.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46090956","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 : 2022-06-01DOI: 10.1097/EE9.0000000000000213
P. Jain, Amit Kapoor, P. Rubeshkumar, Mohankumar Raju, Bency Joseph, P. Bhat, P. Ganeshkumar, C. Kesavachandran, D. Patel, N. Manickam, P. Kaur
Background: Chemical leakages cause devastating health effects on humans. On 6 February 2020, seven deaths were reported following a hazardous chemical leakage in a village in Uttar Pradesh, India. We investigated the event to identify the cause and propose recommendations. Methods: We defined a case as sudden onset of breathlessness, headache, or death in the village, 6–7 February 2020. We conducted a house-to-house case search and calculated attack rate (AR) and case-fatality rate (CFR) by age and gender. We conducted an environmental investigation at the leakage site and sent the chemicals for forensic analysis. We obtained the cause of death through autopsy reports. Results: Out of 2,942 residents, we identified 23 cases (AR = 8/1,000) and seven deaths (CFR = 30%). The median age of the case was 42 years (range, 2–64 years). The AR was higher among males (14/1,000 [19/1,402]). All the 23 case-patients who were sleeping at the chemical leakage site or visited to witness the event developed symptoms, and all seven cases who were sleeping within 150 meters of the leakage site died. The environmental investigation revealed leakage of hazardous substances from the storage tank. Toxicology analysis confirmed the leaked chemical as Lindane (gamma-hexachlorocyclohexane), and autopsy reports confirmed the cause of death as asphyxia. Conclusions: Asphyxia following the leakage of Lindane from the storage tank possibly led to sudden deaths. We recommend using leak-proof tanks to ensure safe storage and disposal, law enforcement, and regulations to prevent people from staying close to chemical storage sites.
{"title":"Sudden deaths due to accidental leakage of Lindane from a storage tank in a village, Sitapur, Uttar Pradesh, India, 2020","authors":"P. Jain, Amit Kapoor, P. Rubeshkumar, Mohankumar Raju, Bency Joseph, P. Bhat, P. Ganeshkumar, C. Kesavachandran, D. Patel, N. Manickam, P. Kaur","doi":"10.1097/EE9.0000000000000213","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000213","url":null,"abstract":"Background: Chemical leakages cause devastating health effects on humans. On 6 February 2020, seven deaths were reported following a hazardous chemical leakage in a village in Uttar Pradesh, India. We investigated the event to identify the cause and propose recommendations. Methods: We defined a case as sudden onset of breathlessness, headache, or death in the village, 6–7 February 2020. We conducted a house-to-house case search and calculated attack rate (AR) and case-fatality rate (CFR) by age and gender. We conducted an environmental investigation at the leakage site and sent the chemicals for forensic analysis. We obtained the cause of death through autopsy reports. Results: Out of 2,942 residents, we identified 23 cases (AR = 8/1,000) and seven deaths (CFR = 30%). The median age of the case was 42 years (range, 2–64 years). The AR was higher among males (14/1,000 [19/1,402]). All the 23 case-patients who were sleeping at the chemical leakage site or visited to witness the event developed symptoms, and all seven cases who were sleeping within 150 meters of the leakage site died. The environmental investigation revealed leakage of hazardous substances from the storage tank. Toxicology analysis confirmed the leaked chemical as Lindane (gamma-hexachlorocyclohexane), and autopsy reports confirmed the cause of death as asphyxia. Conclusions: Asphyxia following the leakage of Lindane from the storage tank possibly led to sudden deaths. We recommend using leak-proof tanks to ensure safe storage and disposal, law enforcement, and regulations to prevent people from staying close to chemical storage sites.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48017334","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 : 2022-04-22eCollection Date: 2022-06-01DOI: 10.1097/EE9.0000000000000201
Elena Colicino, Katerina Margetaki, Damaskini Valvi, Nicolo Foppa Pedretti, Nikos Stratakis, Marina Vafeiadi, Theano Roumeliotaki, Soterios A Kyrtopoulos, Hannu Kiviranta, Euripides G Stephanou, Manolis Kogevinas, Rob McConnell, Kiros T Berhane, Leda Chatzi, David V Conti
Background: Prenatal exposure to organochlorine compounds (OCs) has been associated with increased childhood body mass index (BMI); however, only a few studies have focused on longitudinal BMI trajectories, and none of them used multiple exposure mixture approaches.
Aim: To determine the association between in-utero exposure to eight OCs and childhood BMI measures (BMI and BMI z-score) at 4 years and their yearly change across 4-12 years of age in 279 Rhea child-mother dyads.
Methods: We applied three approaches: (1) linear mixed-effect regressions (LMR) to associate individual compounds with BMI measures; (2) Bayesian weighted quantile sum regressions (BWQSR) to provide an overall OC mixture association with BMI measures; and (3)Bayesian varying coefficient kernel machine regressions (BVCKMR) to model nonlinear and nonadditive associations.
Results: In the LMR, yearly change of BMI measures was consistently associated with a quartile increase in hexachlorobenzene (HCB) (estimate [95% Confidence or Credible interval] BMI: 0.10 [0.06, 0.14]; BMI z-score: 0.02 [0.01, 0.04]). BWQSR results showed that a quartile increase in mixture concentrations was associated with yearly increase of BMI measures (BMI: 0.10 [0.01, 0.18]; BMI z-score: 0.03 [0.003, 0.06]). In the BVCKMR, a quartile increase in dichlorodiphenyldichloroethylene concentrations was associated with higher BMI measures at 4 years (BMI: 0.33 [0.24, 0.43]; BMI z-score: 0.19 [0.15, 0.24]); whereas a quartile increase in HCB and polychlorinated biphenyls (PCB)-118 levels was positively associated with BMI measures yearly change (BMI: HCB:0.10 [0.07, 0.13], PCB-118:0.08 [0.04, 012]; BMI z-score: HCB:0.03 [0.02, 0.05], PCB-118:0.02 [0.002,04]). BVCKMR suggested that PCBs had nonlinear relationships with BMI measures, and HCB interacted with other compounds.
Conclusions: All analyses consistently demonstrated detrimental associations between prenatal OC exposures and childhood BMI measures.
{"title":"Prenatal exposure to multiple organochlorine compounds and childhood body mass index.","authors":"Elena Colicino, Katerina Margetaki, Damaskini Valvi, Nicolo Foppa Pedretti, Nikos Stratakis, Marina Vafeiadi, Theano Roumeliotaki, Soterios A Kyrtopoulos, Hannu Kiviranta, Euripides G Stephanou, Manolis Kogevinas, Rob McConnell, Kiros T Berhane, Leda Chatzi, David V Conti","doi":"10.1097/EE9.0000000000000201","DOIUrl":"10.1097/EE9.0000000000000201","url":null,"abstract":"<p><strong>Background: </strong>Prenatal exposure to organochlorine compounds (OCs) has been associated with increased childhood body mass index (BMI); however, only a few studies have focused on longitudinal BMI trajectories, and none of them used multiple exposure mixture approaches.</p><p><strong>Aim: </strong>To determine the association between <i>in-utero</i> exposure to eight OCs and childhood BMI measures (BMI and BMI z-score) at 4 years and their yearly change across 4-12 years of age in 279 Rhea child-mother dyads.</p><p><strong>Methods: </strong>We applied three approaches: (1) linear mixed-effect regressions (LMR) to associate individual compounds with BMI measures; (2) Bayesian weighted quantile sum regressions (BWQSR) to provide an overall OC mixture association with BMI measures; and (3)Bayesian varying coefficient kernel machine regressions (BVCKMR) to model nonlinear and nonadditive associations.</p><p><strong>Results: </strong>In the LMR, yearly change of BMI measures was consistently associated with a quartile increase in hexachlorobenzene (HCB) (estimate [95% Confidence or Credible interval] BMI: 0.10 [0.06, 0.14]; BMI z-score: 0.02 [0.01, 0.04]). BWQSR results showed that a quartile increase in mixture concentrations was associated with yearly increase of BMI measures (BMI: 0.10 [0.01, 0.18]; BMI z-score: 0.03 [0.003, 0.06]). In the BVCKMR, a quartile increase in dichlorodiphenyldichloroethylene concentrations was associated with higher BMI measures at 4 years (BMI: 0.33 [0.24, 0.43]; BMI z-score: 0.19 [0.15, 0.24]); whereas a quartile increase in HCB and polychlorinated biphenyls (PCB)-118 levels was positively associated with BMI measures yearly change (BMI: HCB:0.10 [0.07, 0.13], PCB-118:0.08 [0.04, 012]; BMI z-score: HCB:0.03 [0.02, 0.05], PCB-118:0.02 [0.002,04]). BVCKMR suggested that PCBs had nonlinear relationships with BMI measures, and HCB interacted with other compounds.</p><p><strong>Conclusions: </strong>All analyses consistently demonstrated detrimental associations between prenatal OC exposures and childhood BMI measures.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"66 3","pages":"e201"},"PeriodicalIF":3.3,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9187184/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41304130","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 : 2022-03-31eCollection Date: 2022-04-01DOI: 10.1097/EE9.0000000000000207
Ibrahim Zaganjor, Alexander P Keil, Thomas J Luben, Tania A Desrosiers, Lawrence S Engel, Jennita Reefhuis, Adrian M Michalski, Peter H Langlois, Andrew F Olshan
In population research, exposure to environmental contaminants is often indirectly assessed by linking residence to geocoded databases of environmental exposures. We explored the potential for misclassification of residence-based environmental exposure as a result of not accounting for the workplace environments of employed pregnant women using data from a National Birth Defects Prevention Study (NBDPS) analysis of drinking water haloacetic acids and hypospadias.
Methods: The original analysis used NBDPS data from women with haloacetic acid exposure information in eight states who delivered an infant with second- or third-degree hypospadias (cases) or a male infant without a birth defect (controls) between 2000 and 2005. In this bias analysis, we used a uniform distribution to randomly select 11%-14% of employed women that were assumed to change municipal water systems between home and work and imputed new contaminant exposures for tap water beverages consumed at work among the selected women using resampled values from the control population. Multivariable logistic regression was used to estimate the association between hypospadias and haloacetic acid ingestion with the same covariates and exposure cut-points as the original study. We repeated this process across 10,000 iterations and then completed a sensitivity analysis of an additional 10,000 iterations where we expanded the uniform distribution (i.e., 0%, 28%).
Results: In both simulations, the average results of the 10,000 iterations were nearly identical to those of the initial study.
Conclusions: Our results suggest that household estimates may be sufficient proxies for worksite exposures to haloacetic acids in tap water.
{"title":"Is maternal employment site a source of exposure misclassification in studies of environmental exposures and birth outcomes? A simulation-based bias analysis of haloacetic acids in tap water and hypospadias.","authors":"Ibrahim Zaganjor, Alexander P Keil, Thomas J Luben, Tania A Desrosiers, Lawrence S Engel, Jennita Reefhuis, Adrian M Michalski, Peter H Langlois, Andrew F Olshan","doi":"10.1097/EE9.0000000000000207","DOIUrl":"10.1097/EE9.0000000000000207","url":null,"abstract":"<p><p>In population research, exposure to environmental contaminants is often indirectly assessed by linking residence to geocoded databases of environmental exposures. We explored the potential for misclassification of residence-based environmental exposure as a result of not accounting for the workplace environments of employed pregnant women using data from a National Birth Defects Prevention Study (NBDPS) analysis of drinking water haloacetic acids and hypospadias.</p><p><strong>Methods: </strong>The original analysis used NBDPS data from women with haloacetic acid exposure information in eight states who delivered an infant with second- or third-degree hypospadias (cases) or a male infant without a birth defect (controls) between 2000 and 2005. In this bias analysis, we used a uniform distribution to randomly select 11%-14% of employed women that were assumed to change municipal water systems between home and work and imputed new contaminant exposures for tap water beverages consumed at work among the selected women using resampled values from the control population. Multivariable logistic regression was used to estimate the association between hypospadias and haloacetic acid ingestion with the same covariates and exposure cut-points as the original study. We repeated this process across 10,000 iterations and then completed a sensitivity analysis of an additional 10,000 iterations where we expanded the uniform distribution (i.e., 0%, 28%).</p><p><strong>Results: </strong>In both simulations, the average results of the 10,000 iterations were nearly identical to those of the initial study.</p><p><strong>Conclusions: </strong>Our results suggest that household estimates may be sufficient proxies for worksite exposures to haloacetic acids in tap water.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"6 1","pages":"e207"},"PeriodicalIF":3.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005252/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44229329","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 : 2022-03-31DOI: 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 : 2022-03-22DOI: 10.1097/EE9.0000000000000203
Chloe Friedman, D. Dabelea, L. Bloemsma, D. S. Thomas, J. Peel, J. Adgate, S. Magzamen, S. Martenies, W. Allshouse, A. Starling
Background/Objectives: 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, D. Dabelea, L. Bloemsma, D. S. Thomas, J. Peel, J. Adgate, S. Magzamen, S. Martenies, W. Allshouse, A. Starling","doi":"10.1097/EE9.0000000000000203","DOIUrl":"https://doi.org/10.1097/EE9.0000000000000203","url":null,"abstract":"Background/Objectives: 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.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46267379","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 : 2022-02-25DOI: 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}