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Data Mining for Seeking Relationships between Sickness Absence and Japanese Worker's Profile

机译:寻求疾病缺席与日本工人个人资料关系的数据挖掘

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Since sickness absence causes great losses for both individual employees and their companies, decreasing sickness absence is one of major concern in occupational healthcare field. We conducted worksite-based study to elucidate the influence of lifestyle, medical findings and present illness on sickness absence of 1 week or longer during the fiscal year. Subjects were 6,010 Japanese male employees in a large telecommunication telephone company, aged 30 to 59 (the mean age 46.3+-6.7 years), who had health check-up of in the fiscal year from 1991 to 1998 consecutively. We used data mining methods, such as 'the Association Rule Analysis', 'the Correlation Coefficient Analysis', and 'the Risk Ratio Analysis', to elucidate interrelationships in sickness absences, lifestyle (healthy/unhealthy), medical findings (normal/abnormal), and present illness (non-existent/existent), that were surveyed consecutively in the fiscal year from 1991 to 1998. In present illness, secular trend of Risk Ratio showed different patterns according to present illness category. Our results may contribute preventing sickness absence in Japanese worksite.
机译:由于疾病缺席导致个人员工及其公司的巨大损失,疾病缺席的减少是职业医疗保健领域的主要问题之一。我们进行了基于工地的研究,以阐明生活方式,医学发现和本财政年度在1周或更长的疾病的影响。受试者是一家大型电信电话公司的6,010名日本男性雇员,年龄在30至59岁(平均年龄46.3 + -6.7岁),他们在1991年至1998年的财政年度连续上卫生检查。我们使用数据挖掘方法,例如“关联规则分析”,“相关系数分析”和“风险比分析”,以阐明疾病缺勤的相互关系,生活方式(健康/不健康),医学发现(正常/异常) )和目前的疾病(不存在/存在),在1991年至1998年的财政年度连续调查。目前,据目前的疾病类别,风险比的世俗趋势显示出不同的模式。我们的结果可能有助于防止日本工地的疾病。

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