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[与疾病无关的缺勤原因——模型分析]

[Causes of absenteeism not related to illness--model analysis].

作者信息

Szubert Z

出版信息

Med Pr. 1988;39(2):142-8.

PMID:3210964
Abstract

The study carried out at the Institute of Occupational Medicine in Lódź promoted an analysis of the impact of many non-disease-related factors--such as demographic, economic, social and living conditions, as well as working environment--on sickness absenteeism rates. The analysis was based on empirical data collected in one of electronic industry plants. The analysis of sickness absenteeism causes involved cause-effect models estimated by multivariate regression. The models were constructed for men and women aged up to 29, 30-39, 40-49, over 50, and total. Two parameters served as variables of absenteeism: number of absenteeism days in a given year and average duration of absenteeism case. Explanatory variables in particular models were selected from many non-disease-related variables. Multiple correlation coefficients indicated at the p = 0.05 significance level--a statistically significant correlation between the adopted explanatory variables and the variable being explained in every model. The results of estimation of particular models indicate that in the absenteeism of men and women alike, workers' health self-evaluation is essential and affects workers absenteeism in younger groups and totally. This variable significantly affects men and women's absenteeism rates exerting effects on the duration of absenteeism cases, thus also through the severity of diseases. Other variables determining--in the statistically significant way--sickness absenteeism involve: length of employment, influencing men and women's absenteeism in elder age, and occupational exposure to some hazards, which refers mainly to women. In addition, the studies demonstrated that the average duration of a disease is largely connected with workers' age.

摘要

在罗兹职业医学研究所开展的这项研究,推动了对诸多与疾病无关的因素——如人口统计学、经济、社会和生活条件,以及工作环境——对病假缺勤率影响的分析。该分析基于在一家电子工厂收集的实证数据。对病假缺勤原因的分析涉及通过多元回归估计的因果模型。这些模型是针对年龄在29岁及以下、30 - 39岁、40 - 49岁、50岁以上以及总体的男性和女性构建的。两个参数用作缺勤变量:给定年份的缺勤天数和缺勤案例的平均持续时间。特定模型中的解释变量是从许多与疾病无关的变量中选取的。多重相关系数在p = 0.05的显著性水平表明——在每个模型中,所采用的解释变量与被解释变量之间存在统计学上的显著相关性。特定模型的估计结果表明,在男性和女性的缺勤情况中,工人的健康自我评估至关重要,并且影响年轻群体和总体的工人缺勤情况。这个变量显著影响男性和女性的缺勤率,对缺勤案例的持续时间产生影响,从而也通过疾病的严重程度产生影响。以统计学显著方式决定病假缺勤的其他变量包括:就业时长,影响老年男性和女性的缺勤情况,以及职业接触某些危害,这主要涉及女性。此外,研究表明疾病的平均持续时间在很大程度上与工人年龄相关。

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