TITLE:
An Analysis of Health Factors Affecting Employees’ Absenteeism: Influences of HDL Cholesterol and Blood Sugar Levels
AUTHORS:
Kazumitsu Nawata
KEYWORDS:
Absenteeism, Reduction of Absence Days, High-Density Lipoprotein Cholesterol (HDL-C), Blood Sugar
JOURNAL NAME:
Health,
Vol.15 No.5,
May
17,
2023
ABSTRACT: Background: Workers’ health condition is an important issue. It affects not only the well-being of workers but also the firms and society as a whole through medical costs and productivity losses due to absenteeism and presenteeism. Data and Methods: Data were obtained from 1136 employees at an operational site of a large corporation. The dataset contained both medical checkups and working record information. Health factors affecting long-term absence (over three days in three months) were analyzed. Logistic regression models and the procedure for selecting proper covariates based on likelihood test statistics and the Akaike information criterion were used. Results: Among health factors, high-density lipoprotein cholesterol (HDL-C) and blood sugar levels were important in the selected model. For HDL-C, the odds ratio (OR) based on one standard deviation difference was 0.75 with a 95% confidence interval (CI) of 0.59 - 0.95. For blood sugar, the OR was 1.20 with a 95% CI of 1.01 - 1.42. Improving HDL-C and blood sugar levels would reduce long-term absence by 25% and 20%, respectively. Conclusion: Controlling HDL-C and blood sugar levels is important to reduce long-term absenteeism. These factors can be improved by modifying eating habits. Since the operational site has its own company cafeterias, which most employees use, nutritional intervention is relatively easy with little or no cost. It may be worthwhile to implement nutritional intervention, especially for patients with low HDL-C or high blood sugar levels. Limitations: The results of this study were based on one operational site of a corporation. The employees were mainly operators working inside the building. The results may be different from other types of jobs and working conditions, such as fieldwork. Analyses of different types of jobs and working conditions are necessary.