Alcohol consumption and employment: a cross-sectional study of office workers and unemployed people.

2020 
Background: Alcohol is a psychoactive substance with toxic and addictive properties. Biomarkers like GGT, AST, ALT and MCV are influenced by excessive ethanol consumption. Alcohol consumption represents a health risk and it has been linked to unemployment. The aim of this study how working status predict alcohol consumption through a cross sectional study comparing alcohol-related biomarkers levels in office workers and unemployed people. Methods: This study includes 157 office workers and 157 unemployed people, who were recruited from January to December 2018. A propensity score matching procedure was applied to obtain two homogenous groups in terms of age and gender. A non-parametric analysis was performed on serum biomarkers that are generally altered by alcohol consumption. Logistic regression models were designed to evaluate how working status predict abnormal biomarker levels related with alcohol consumption. Results: No differences in median biomarker values were found between groups. Logistic regression analysis showed that office work is a negative predictor of pathological biomarker levels. Office workers had a significant relation with the levels of GGT (OR 0.48; 95% CI [0.28-0.84]), AST (OR 0.42; 95% CI [0.22-0.78]), ALT (OR 0.39; 95% CI [0.23-0.66]), and MCV (OR 0.37; 95% CI [0.19-0.70]). Conclusion: Office workers had lower absolute frequencies of pathological values of alcohol consumption biomarkers, after matching for age and gender compared with unemployed people. In addition, a significant negative association between office work is a negative predictor of biomarker levels of alcohol consumption. These results showed that work is an important determinant of health and that can represent a benefit for workers in terms of reducing the risk of consuming alcohol.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    52
    References
    0
    Citations
    NaN
    KQI
    []