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1.
Soc Sci Med ; 314: 115236, 2022 12.
Article in English | MEDLINE | ID: mdl-36308889

ABSTRACT

Increases in minimum wages have been associated with reductions in suicide rates in the United States, but little evidence is available for Asia where social and contextual factors, as well as drivers of suicide, may be different. We investigated the impact of the introduction of the minimum wage in Hong Kong in May 2011 on suicide rates using an interrupted time series design for the period January 2006 to December 2016. We investigated both immediate and gradual changes in monthly suicide rates after the introduction of the minimum wage taking into account secular trends. We conducted stratified analyses by age and gender. In total 9396 suicides were recorded in Hong Kong during the 11-year study period. Introduction of the minimum wage was associated with an immediate decrease of 13.0% in the monthly suicide rate (95% confidence interval (CI) 5.4%-19.9%, P = 0.001). There was an immediate decrease of 15.8% in older working aged (25-64 years) men (95% CI: 4.2%-25.9%, P = 0.009). Point estimates of immediate effect for other subgroups were also in a negative direction, but were not statistically significant. There was no evidence of a gradual effect on suicide rates at the population level or by subgroup other than a small increase in younger working aged men. We estimate that 633 suicides were prevented by the minimum wage legislation for the period from May 2011 to December 2016, the majority in older working aged men. Our results provide new evidence that, similar to findings in Western settings, minimum wages may help to reduce suicide in Asia, particularly for working age men. Our study highlights the importance of examining the health impacts of government economic policy and suggests minimum wages may provide policy makers with an upstream population-based strategy to reduce suicide rates.


Subject(s)
Suicide , Male , Humans , United States , Aged , Hong Kong/epidemiology , Income , Salaries and Fringe Benefits , Interrupted Time Series Analysis
2.
Eur J Clin Nutr ; 75(11): 1668-1678, 2021 11.
Article in English | MEDLINE | ID: mdl-33828238

ABSTRACT

BACKGROUND: The impact of selenium on coronary artery disease (CAD) and type 2 diabetes (T2D) remains unclear with inconsistent results from observational studies and randomized controlled trials. We used Mendelian randomization to obtain unconfounded estimates of the effect of selenium on CAD, T2D, lipids and glycemic traits. METHODS: We applied genetic variants strongly (P < 5 × 10-8) associated with blood and toenail selenium to publicly available summary statistics from large consortia genome-wide association studies of CAD (76,014 cases and 264,785 non-cases), T2D (74,124 cases and 824,006 controls), lipids and glycemic traits. Variant specific Wald estimates were combined using inverse variance weighting, with several sensitivity analyses. RESULTS: Genetically predicted selenium was associated with higher T2D (OR 1.27, 95% CI 1.07-1.50, P = 0.006). There was little evidence of an association with CAD. Genetically predicted selenium was associated with lower low-density lipoprotein (LDL) cholesterol, lower high-density lipoprotein (HDL) cholesterol, higher fasting insulin and higher homeostasis model assessment of insulin resistance. These results were not robust to all sensitivity analyses. No associations with triglycerides, fasting glucose or homeostasis model assessment of ß-cell function were evident. CONCLUSIONS: Our study suggests selenium may increase the risk of T2D, possibly through insulin resistance rather than pancreatic beta cell function, but may reduce lipids. We found little evidence of an association with CAD, although an inverse association cannot be definitively excluded. The effect of selenium on these outcomes warrants further investigation.


Subject(s)
Coronary Artery Disease , Diabetes Mellitus, Type 2 , Selenium , Coronary Artery Disease/genetics , Diabetes Mellitus, Type 2/genetics , Genome-Wide Association Study , Humans , Mendelian Randomization Analysis , Polymorphism, Single Nucleotide , Risk Factors
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