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Estimating the mediating effect of different biomarkers on the relation of alcohol consumption with the risk of type 2 diabetes.
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- Author(s): Beulens JW;Beulens JW; van der Schouw YT; Moons KG; Boshuizen HC; van der A DL; Groenwold RH
- Source:
Annals of epidemiology [Ann Epidemiol] 2013 Apr; Vol. 23 (4), pp. 193-7. Date of Electronic Publication: 2013 Jan 29.- Publication Type:
Journal Article; Research Support, Non-U.S. Gov't- Language:
English - Source:
- Additional Information
- Source: Publisher: Elsevier Country of Publication: United States NLM ID: 9100013 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2585 (Electronic) Linking ISSN: 10472797 NLM ISO Abbreviation: Ann Epidemiol Subsets: MEDLINE
- Publication Information: Original Publication: New York, NY : Elsevier, c1990-
- Subject Terms: Alcohol Drinking/*blood ; Biomarkers/*blood ; Diabetes Mellitus, Type 2/*blood; Adult ; Alcohol Drinking/adverse effects ; C-Reactive Protein/metabolism ; Case-Control Studies ; Cholesterol, HDL/blood ; Cholesterol, HDL/metabolism ; Diabetes Mellitus, Type 2/complications ; Diabetes Mellitus, Type 2/epidemiology ; Female ; Health Surveys ; Humans ; Incidence ; Logistic Models ; Male ; Middle Aged ; Netherlands/epidemiology ; Prospective Studies ; Risk Factors ; Surveys and Questionnaires ; Young Adult
- Abstract: Purpose: Moderate alcohol consumption is associated with a reduced type 2 diabetes risk, but the biomarkers that explain this relation are unknown. The most commonly used method to estimate the proportion explained by a biomarker is the difference method. However, influence of alcohol-biomarker interaction on its results is unclear. G-estimation method is proposed to accurately assess proportion explained, but how this method compares with the difference method is unknown.
Methods: In a case-cohort study of 2498 controls and 919 incident diabetes cases, we estimated the proportion explained by different biomarkers on the relation between alcohol consumption and diabetes using the difference method and sequential G-estimation method.
Results: Using the difference method, high-density lipoprotein cholesterol explained the relation between alcohol and diabetes by 78% (95% confidence interval [CI], 41-243), whereas high-sensitivity C-reactive protein (-7.5%; -36.4 to 1.8) or blood pressure (-6.9; -26.3 to -0.6) did not explain the relation. Interaction between alcohol and liver enzymes led to bias in proportion explained with different outcomes for different levels of liver enzymes. G-estimation method showed comparable results, but proportions explained were lower.
Conclusions: The relation between alcohol consumption and diabetes may be largely explained by increased high-density lipoprotein cholesterol but not by other biomarkers. Ignoring exposure-mediator interactions may result in bias. The difference and G-estimation methods provide similar results.
(Copyright © 2013 Elsevier Inc. All rights reserved.) - Accession Number: 0 (Biomarkers)
0 (Cholesterol, HDL)
9007-41-4 (C-Reactive Protein) - Publication Date: Date Created: 20130205 Date Completed: 20130910 Latest Revision: 20151119
- Publication Date: 20231215
- Accession Number: 10.1016/j.annepidem.2012.12.014
- Accession Number: 23375342
- Source:
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