Environmental arsenic exposure and risk of diabetes type 2 in Ron Phibun subdistrict, Nakhon Si Thammarat Province, Thailand: unmatched and matched case–control studies
Authors Sripaoraya K, Siriwong W, Pavittranon S, Chapman RS
Received 20 November 2016
Accepted for publication 22 February 2017
Published 11 April 2017 Volume 2017:10 Pages 41—48
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Colin Mak
Peer reviewer comments 2
Editor who approved publication: Dr Kent Rondeau
Kwanyuen Sripaoraya,1,2 Wattasit Siriwong,1 Sumol Pavittranon,2 Robert S Chapman1
1College of Public Health Sciences, Chulalongkorn University, Bangkok, 2Medical Life Sciences Institute, Department of Medical Sciences, Ministry of Public Health, Nonthaburi, Thailand
Background: There are inconsistent findings on associations between low-to-moderate level of arsenic in water and diabetes risk from previous epidemiological reports. In Ron Phibun subdistrict, Nakhon Si Thammarat Province, Thailand, a low level of arsenic exposure among population was observed and increased diabetes mellitus (DM) rate was identified.
Objectives: We aimed to investigate the association between determinants (including low-level water arsenic exposure) of DM type 2 risk among residents of three villages of Ron Phibun subdistrict, Nakhon Si Thammarat Province.
Materials and methods: Secondary data from two previous community based-studies, conducted in 2000 and 2008, were utilized. Data on independent variables relating to arsenic exposure and sociodemographic characteristics were taken from questionnaires and worksheets for health-risk screening. Water samples collected during household visit were sent for analysis of arsenic level at certified laboratories. Diabetes cases (N=185) were those who had been diagnosed with DM type 2. Two groups of controls, one unmatched to cases (n=200) and one pair matched on age and gender (n=200), were selected for analysis as unmatched and matched case–control studies, respectively. A multiple imputation technique was used to impute missing values of independent variables. Multivariable logistic regression models, with independent variables for arsenic exposure and sociodemographic characteristics, were constructed. The unmatched and matched data sets were analyzed using unconditional and conditional logistic analyses, respectively.
Results: Older age, body mass index (BMI), having a history of illness in siblings and parents, and drinking were associated with increased DM type 2 risk. We found no convincing association between DM type 2 risk and water arsenic concentration in either study.
Conclusion: We did not observe meaningful association between diabetes risk and the low-to-moderate arsenic levels observed in this study. Further research is needed to confirm this finding in the study area and elsewhere in Thailand.
Keywords: diabetes, arsenic exposure, case–control, Ron Phibun subdistrict, Thailand
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