Abstract
There is growing interest in the role of environmental exposures in the development of diabetes. Previous studies in rural Saskatchewan have raised concerns over drinking water contaminants, including arsenic, which has been identified as a possible risk factor for diabetes. Using administrative health and water-quality surveillance data from rural Saskatchewan, an ecological study design was used to investigate associations between concentrations of arsenic, water health standards and aesthetic objectives, and the incidence and prevalence of diabetes. Mixtures of contaminants measured as health standards or as aesthetic objectives were summarized using principal component (PC) analysis. Associations were modeled using Bayesian hierarchical models incorporating both spatial and unstructured random effects, standardized for age and sex, and adjusted for socioeconomic factors and a surrogate measure for smoking rates. Arsenic was not associated with an increased risk of diabetes. For private wells, having groundwater arsenic concentrations in the highest quintile was associated with decreased cumulative diabetes incidence for 2010–2012 (risk ratio [RR] = 0.854, 95% credible interval [CrI] 0.761–0.958) compared with the lowest quintile, a result inconsistent with other studies. For public water supplies, having a first PC score for health standards (primarily summarized selenium, nitrate, and lead) in the third quintile (RR = 1.101, 95% CrI 1.019–1.188), fourth quintile (RR = 1.088, 95% CrI 1.003–1.180), or fifth quintile (RR = 1.115, 95% CrI 1.026–1.213) was associated with an increase in 2010 diabetes prevalence compared with the first quintile. An increase in the PC scores for the third aesthetic objective in private wells (characterized primarily by iron and manganese) was associated with decreased diabetes incidence, although a meaningful dose–response relationship was not evident. No other associations between PC scores for health standards or aesthetic objectives from public or private water supplies and diabetes were identified.
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Acknowledgements
The authors gratefully acknowledge the Saskatchewan Health Quality Council for assistance in accessing the administrative health data and especially Shan Jin for her assistance in extracting the health data. The authors thank Dr. Lisa Lix for advice regarding the identification of diabetes cases from administrative health data and the Saskatchewan Water Security Agency for providing access to water-quality surveillance data.
Funding
The study was funded by a Grant from the Saskatchewan Health Research Foundation. LM also was the recipient of an Interprovincial Graduate Student Fellowship. The funding bodies had no role in the design of the study and collection, analysis, and interpretation of data or writing the manuscript.
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CLW, LB, and TE conceived the study objectives; LM analyzed the data in consultation with CLW; LM wrote the paper; CLW edited the paper, and LB and TE reviewed the manuscript and provided comments. All authors approved the final manuscript.
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The de-identified administrative health data that support the findings of this study were provided by Saskatchewan Ministry of Health through the Saskatchewan Health Quality Council. Access to the data was based on a license that limited use and access to the current study, and the data are not publicly available. Similarly, restrictions apply to the de-identified water-quality datasets that were provided by the Water Security of Agency of Saskatchewan; these were used under license for the current study and are not publicly available. The census data used to derive covariates is publicly available from Statistics Canada at http://www12.statcan.gc.ca/census-recensement/2006/dp-pd/tbt/index-eng.cfm (Statistics Canada 2014).
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Ethics approval for the use of health records data was obtained from the University of Saskatchewan Behavioral Research Ethics Board (Bio 12-332). Consent to participate was not applicable as the study made use of only secondary data sources.
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Disclaimer: This study is based in part on de-identified data provided by the Saskatchewan Ministry of Health. The interpretation and conclusions contained herein do not necessarily represent those of the Government of Saskatchewan or the Ministry of Health.
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McLeod, L., Bharadwaj, L., Epp, T.Y. et al. Bayesian Hierarchical Models as Tools to Evaluate the Association Between Groundwater Quality and the Occurrence of Type 2 Diabetes in Rural Saskatchewan, Canada. Arch Environ Contam Toxicol 76, 375–393 (2019). https://doi.org/10.1007/s00244-018-00588-4
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DOI: https://doi.org/10.1007/s00244-018-00588-4