Comparison of Trihalomethane exposure assessment metrics in epidemiologic analyses of reproductive and developmental outcomes
Background Researchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial and temporal variability, water consumption, and showering and bathing time with an expectation of decreasing exposure misclassifi...
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Published in | Journal of exposure science & environmental epidemiology Vol. 34; no. 1; pp. 115 - 125 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.01.2024
Nature Publishing Group |
Subjects | |
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Abstract | Background
Researchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial and temporal variability, water consumption, and showering and bathing time with an expectation of decreasing exposure misclassification compared to the use of measured concentrations at public water supply (PWS) monitoring locations alone.
Objective
We used exposure data collected for a previous study of DBPs to evaluate how different sources of information impact trihalomethane (THM) exposure estimates.
Methods
We compared gestational exposure estimates to THMs based on water utility monitoring data alone, statistical imputation of daily concentrations to incorporate temporal variability, and personal water consumption and use (bathing and showering). We used Spearman correlation coefficients and ranked kappa statistics to compare exposure classifications.
Results
Exposure estimates based on measured or imputed daily THM concentrations, self-reported consumption, or bathing and showering differed substantially from estimates based solely on concentrations from PWS quarterly monitoring reports. Ranked exposure classifications, high to low quartiles or deciles, were generally consistent across each exposure metric (i.e., a subject with “high” exposure based on measured or imputed THM concentrations generally remained in the “high” category across exposure metrics.) The measured concentrations and imputed daily (i.e., spline regression) concentrations were highly correlated (
r
= 0.98). The weighted kappa statistics comparing exposure estimates using different exposure metrics ranged from 0.27 to 0.89, with the highest values for the ingestion + bathing/showering metrics compared to metrics for bathing/showering only (0.76 and 0.89). Bathing and showering contributed the most to “total” THM exposure estimates.
Impact Statement
We compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data. Our results show exposure estimates based on imputed daily concentrations accounting for temporal variability were very similar to the measured THM concentrations. We observed low agreement between imputed daily concentrations and ingestion-based estimates. Considering additional routes of exposure (e.g., inhalation and dermal) slightly increased agreement with the measured PWS exposure estimate in this population. Overall, the comparison of exposure assessment metrics allows researchers to understand the added value of additional data collection for future epidemiologic analyses of DBPs. |
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AbstractList | Background
Researchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial and temporal variability, water consumption, and showering and bathing time with an expectation of decreasing exposure misclassification compared to the use of measured concentrations at public water supply (PWS) monitoring locations alone.
Objective
We used exposure data collected for a previous study of DBPs to evaluate how different sources of information impact trihalomethane (THM) exposure estimates.
Methods
We compared gestational exposure estimates to THMs based on water utility monitoring data alone, statistical imputation of daily concentrations to incorporate temporal variability, and personal water consumption and use (bathing and showering). We used Spearman correlation coefficients and ranked kappa statistics to compare exposure classifications.
Results
Exposure estimates based on measured or imputed daily THM concentrations, self-reported consumption, or bathing and showering differed substantially from estimates based solely on concentrations from PWS quarterly monitoring reports. Ranked exposure classifications, high to low quartiles or deciles, were generally consistent across each exposure metric (i.e., a subject with “high” exposure based on measured or imputed THM concentrations generally remained in the “high” category across exposure metrics.) The measured concentrations and imputed daily (i.e., spline regression) concentrations were highly correlated (
r
= 0.98). The weighted kappa statistics comparing exposure estimates using different exposure metrics ranged from 0.27 to 0.89, with the highest values for the ingestion + bathing/showering metrics compared to metrics for bathing/showering only (0.76 and 0.89). Bathing and showering contributed the most to “total” THM exposure estimates.
Impact Statement
We compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data. Our results show exposure estimates based on imputed daily concentrations accounting for temporal variability were very similar to the measured THM concentrations. We observed low agreement between imputed daily concentrations and ingestion-based estimates. Considering additional routes of exposure (e.g., inhalation and dermal) slightly increased agreement with the measured PWS exposure estimate in this population. Overall, the comparison of exposure assessment metrics allows researchers to understand the added value of additional data collection for future epidemiologic analyses of DBPs. We compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data. Our results show exposure estimates based on imputed daily concentrations accounting for temporal variability were very similar to the measured THM concentrations. We observed low agreement between imputed daily concentrations and ingestion-based estimates. Considering additional routes of exposure (e.g., inhalation and dermal) slightly increased agreement with the measured PWS exposure estimate in this population. Overall, the comparison of exposure assessment metrics allows researchers to understand the added value of additional data collection for future epidemiologic analyses of DBPs. Researchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial and temporal variability, water consumption, and showering and bathing time with an expectation of decreasing exposure misclassification compared to the use of measured concentrations at public water supply (PWS) monitoring locations alone.BACKGROUNDResearchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial and temporal variability, water consumption, and showering and bathing time with an expectation of decreasing exposure misclassification compared to the use of measured concentrations at public water supply (PWS) monitoring locations alone.We used exposure data collected for a previous study of DBPs to evaluate how different sources of information impact trihalomethane (THM) exposure estimates.OBJECTIVEWe used exposure data collected for a previous study of DBPs to evaluate how different sources of information impact trihalomethane (THM) exposure estimates.We compared gestational exposure estimates to THMs based on water utility monitoring data alone, statistical imputation of daily concentrations to incorporate temporal variability, and personal water consumption and use (bathing and showering). We used Spearman correlation coefficients and ranked kappa statistics to compare exposure classifications.METHODSWe compared gestational exposure estimates to THMs based on water utility monitoring data alone, statistical imputation of daily concentrations to incorporate temporal variability, and personal water consumption and use (bathing and showering). We used Spearman correlation coefficients and ranked kappa statistics to compare exposure classifications.Exposure estimates based on measured or imputed daily THM concentrations, self-reported consumption, or bathing and showering differed substantially from estimates based solely on concentrations from PWS quarterly monitoring reports. Ranked exposure classifications, high to low quartiles or deciles, were generally consistent across each exposure metric (i.e., a subject with "high" exposure based on measured or imputed THM concentrations generally remained in the "high" category across exposure metrics.) The measured concentrations and imputed daily (i.e., spline regression) concentrations were highly correlated (r = 0.98). The weighted kappa statistics comparing exposure estimates using different exposure metrics ranged from 0.27 to 0.89, with the highest values for the ingestion + bathing/showering metrics compared to metrics for bathing/showering only (0.76 and 0.89). Bathing and showering contributed the most to "total" THM exposure estimates.RESULTSExposure estimates based on measured or imputed daily THM concentrations, self-reported consumption, or bathing and showering differed substantially from estimates based solely on concentrations from PWS quarterly monitoring reports. Ranked exposure classifications, high to low quartiles or deciles, were generally consistent across each exposure metric (i.e., a subject with "high" exposure based on measured or imputed THM concentrations generally remained in the "high" category across exposure metrics.) The measured concentrations and imputed daily (i.e., spline regression) concentrations were highly correlated (r = 0.98). The weighted kappa statistics comparing exposure estimates using different exposure metrics ranged from 0.27 to 0.89, with the highest values for the ingestion + bathing/showering metrics compared to metrics for bathing/showering only (0.76 and 0.89). Bathing and showering contributed the most to "total" THM exposure estimates.We compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data. Our results show exposure estimates based on imputed daily concentrations accounting for temporal variability were very similar to the measured THM concentrations. We observed low agreement between imputed daily concentrations and ingestion-based estimates. Considering additional routes of exposure (e.g., inhalation and dermal) slightly increased agreement with the measured PWS exposure estimate in this population. Overall, the comparison of exposure assessment metrics allows researchers to understand the added value of additional data collection for future epidemiologic analyses of DBPs.IMPACT STATEMENTWe compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data. Our results show exposure estimates based on imputed daily concentrations accounting for temporal variability were very similar to the measured THM concentrations. We observed low agreement between imputed daily concentrations and ingestion-based estimates. Considering additional routes of exposure (e.g., inhalation and dermal) slightly increased agreement with the measured PWS exposure estimate in this population. Overall, the comparison of exposure assessment metrics allows researchers to understand the added value of additional data collection for future epidemiologic analyses of DBPs. BackgroundResearchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial and temporal variability, water consumption, and showering and bathing time with an expectation of decreasing exposure misclassification compared to the use of measured concentrations at public water supply (PWS) monitoring locations alone.ObjectiveWe used exposure data collected for a previous study of DBPs to evaluate how different sources of information impact trihalomethane (THM) exposure estimates.MethodsWe compared gestational exposure estimates to THMs based on water utility monitoring data alone, statistical imputation of daily concentrations to incorporate temporal variability, and personal water consumption and use (bathing and showering). We used Spearman correlation coefficients and ranked kappa statistics to compare exposure classifications.ResultsExposure estimates based on measured or imputed daily THM concentrations, self-reported consumption, or bathing and showering differed substantially from estimates based solely on concentrations from PWS quarterly monitoring reports. Ranked exposure classifications, high to low quartiles or deciles, were generally consistent across each exposure metric (i.e., a subject with “high” exposure based on measured or imputed THM concentrations generally remained in the “high” category across exposure metrics.) The measured concentrations and imputed daily (i.e., spline regression) concentrations were highly correlated (r = 0.98). The weighted kappa statistics comparing exposure estimates using different exposure metrics ranged from 0.27 to 0.89, with the highest values for the ingestion + bathing/showering metrics compared to metrics for bathing/showering only (0.76 and 0.89). Bathing and showering contributed the most to “total” THM exposure estimates.Impact StatementWe compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data. Our results show exposure estimates based on imputed daily concentrations accounting for temporal variability were very similar to the measured THM concentrations. We observed low agreement between imputed daily concentrations and ingestion-based estimates. Considering additional routes of exposure (e.g., inhalation and dermal) slightly increased agreement with the measured PWS exposure estimate in this population. Overall, the comparison of exposure assessment metrics allows researchers to understand the added value of additional data collection for future epidemiologic analyses of DBPs. Researchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial and temporal variability, water consumption, and showering and bathing time with an expectation of decreasing exposure misclassification compared to the use of measured concentrations at public water supply (PWS) monitoring locations alone. We used exposure data collected for a previous study of DBPs to evaluate how different sources of information impact trihalomethane (THM) exposure estimates. We compared gestational exposure estimates to THMs based on water utility monitoring data alone, statistical imputation of daily concentrations to incorporate temporal variability, and personal water consumption and use (bathing and showering). We used Spearman correlation coefficients and ranked kappa statistics to compare exposure classifications. Exposure estimates based on measured or imputed daily THM concentrations, self-reported consumption, or bathing and showering differed substantially from estimates based solely on concentrations from PWS quarterly monitoring reports. Ranked exposure classifications, high to low quartiles or deciles, were generally consistent across each exposure metric (i.e., a subject with "high" exposure based on measured or imputed THM concentrations generally remained in the "high" category across exposure metrics.) The measured concentrations and imputed daily (i.e., spline regression) concentrations were highly correlated (r = 0.98). The weighted kappa statistics comparing exposure estimates using different exposure metrics ranged from 0.27 to 0.89, with the highest values for the ingestion + bathing/showering metrics compared to metrics for bathing/showering only (0.76 and 0.89). Bathing and showering contributed the most to "total" THM exposure estimates. We compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data. Our results show exposure estimates based on imputed daily concentrations accounting for temporal variability were very similar to the measured THM concentrations. We observed low agreement between imputed daily concentrations and ingestion-based estimates. Considering additional routes of exposure (e.g., inhalation and dermal) slightly increased agreement with the measured PWS exposure estimate in this population. Overall, the comparison of exposure assessment metrics allows researchers to understand the added value of additional data collection for future epidemiologic analyses of DBPs. |
Author | Weber, Kari A. Luben, Thomas J. Nuckols, John Kenyon, Elaina Wright, J. Michael Shaffer, Rachel M. Nembhard, Wendy N. |
AuthorAffiliation | 3 Arkansas Center for Birth Defects Research and Prevention and the Department of Epidemiology, Fay. W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA 4 Colorado State University, Fort Collins, CO, USA; JRN Environmental Health Sciences, LTD, North Bethesda, MD, USA 1 Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency. RTP, NC, Washington, DC; Cincinnati, OH, USA 2 Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA |
AuthorAffiliation_xml | – name: 2 Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA – name: 1 Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency. RTP, NC, Washington, DC; Cincinnati, OH, USA – name: 4 Colorado State University, Fort Collins, CO, USA; JRN Environmental Health Sciences, LTD, North Bethesda, MD, USA – name: 3 Arkansas Center for Birth Defects Research and Prevention and the Department of Epidemiology, Fay. W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA |
Author_xml | – sequence: 1 givenname: Thomas J. surname: Luben fullname: Luben, Thomas J. email: Luben.tom@epa.gov organization: Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency. RTP, NC, Washington, DC – sequence: 2 givenname: Rachel M. surname: Shaffer fullname: Shaffer, Rachel M. organization: Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency. RTP, NC, Washington, DC – sequence: 3 givenname: Elaina surname: Kenyon fullname: Kenyon, Elaina organization: Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, RTP – sequence: 4 givenname: Wendy N. surname: Nembhard fullname: Nembhard, Wendy N. organization: Arkansas Center for Birth Defects Research and Prevention and the Department of Epidemiology, Fay. W. Boozman College of Public Health, University of Arkansas for Medical Sciences – sequence: 5 givenname: Kari A. surname: Weber fullname: Weber, Kari A. organization: Arkansas Center for Birth Defects Research and Prevention and the Department of Epidemiology, Fay. W. Boozman College of Public Health, University of Arkansas for Medical Sciences – sequence: 6 givenname: John surname: Nuckols fullname: Nuckols, John organization: Colorado State University, Fort Collins, CO, USA; JRN Environmental Health Sciences, LTD – sequence: 7 givenname: J. Michael surname: Wright fullname: Wright, J. Michael organization: Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency. RTP, NC, Washington, DC |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37316533$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1038_s41370_024_00639_0 crossref_primary_10_1016_j_ecoenv_2024_117421 |
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Copyright | This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023. |
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Keywords | Trihalomethanes Exposure Assessment Temporal Variation Disinfection By-Products Water Utility Monitoring Data |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 TJL, RMS, and JMW conceived and designed the study, WNN and KW provided the analytic sample and specified relevant exposure variables, EK developed PBPK-based exposure metrics, TJL conducted the analyses. TJL, RMS, JMW, and JN interpreted the results. TJL, RMS EK and JMW prepared the draft manuscript. WNN, KW and JN reviewed the manuscript and provided substantial feedback. All authors reviewed the results and approved the final version of the manuscript. Author Contribution Statement |
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PublicationSubtitle | Official journal of the International Society of Exposure Science |
PublicationTitle | Journal of exposure science & environmental epidemiology |
PublicationTitleAbbrev | J Expo Sci Environ Epidemiol |
PublicationTitleAlternate | J Expo Sci Environ Epidemiol |
PublicationYear | 2024 |
Publisher | Nature Publishing Group US Nature Publishing Group |
Publisher_xml | – name: Nature Publishing Group US – name: Nature Publishing Group |
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Researchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting... Researchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting for spatial... BackgroundResearchers have developed exposure assessment metrics for disinfection by-products (DBPs) utilizing drinking water monitoring data and accounting... We compare exposure metrics capturing temporal variability and multiple estimates of personal THM exposure with THM concentrations from PWS monitoring data.... |
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StartPage | 115 |
SubjectTerms | Bathing Classification Correlation coefficient Correlation coefficients Data Collection Disinfection Drinking water Epidemiology Estimates Exposure Household Products Humans Ingestion Inhalation Medicine Medicine & Public Health Public waters Respiration Statistical analysis Statistics Trihalomethanes Water consumption Water monitoring Water supply Water utilities |
Title | Comparison of Trihalomethane exposure assessment metrics in epidemiologic analyses of reproductive and developmental outcomes |
URI | https://link.springer.com/article/10.1038/s41370-023-00559-5 https://www.ncbi.nlm.nih.gov/pubmed/37316533 https://www.proquest.com/docview/2933662047 https://www.proquest.com/docview/2826218660 https://pubmed.ncbi.nlm.nih.gov/PMC11898099 |
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