Department of Occupational Health Surveillance, National Institute of Occupational Health, Norway.
Scand J Public Health. 2018 May;46(3):314-320. doi: 10.1177/1403494817748263. Epub 2017 Dec 19.
Number of sick leave days vary by county, but little is known about the extent to which this gradient may be explained by differences pertaining to occupational composition and occupational exposure.
A randomly drawn cohort from the general population in Norway, aged 18-69 years, was interviewed by telephone in the second half of 2009 ( n=12,255; response at baseline=60.9%) and followed up in national registries to the end of 2010. Eligible respondents were registered with an active employee relationship in 2009 and 2010 ( n=8275). Information on counties ( n=19) was based on the administrative register. The outcome of interest was the number of physician-certified sick-leave days divided by scheduled man-days during 2010 (i.e. sick-leave percentage (SLP)).
The average SLP during 2010 was 5.2%. The between-county variation in SLP ranged from 4.0% to 7.2%. Compared to the age- and gender-adjusted model, adjustment for occupation, economic sector and self-reported occupational exposure reduced the median difference in SLP between the county with the lowest SLP (reference county) and the SLP in the other counties by 1.08 percentage points (i.e. a 58% reduction). The impact of occupational composition and occupational exposure on the total between-county variance in SLP was a 16% reduction.
Occupational composition and self-reported occupational exposure help to explain a significant part of the difference in SLP between counties, and appear to be more important explanatory factors than demographic variables, self-reported health and smoking.
休假天数因县而异，但对于这种梯度在多大程度上可以归因于职业构成和职业暴露的差异，知之甚少。
挪威从一般人群中随机抽取的一个队列，年龄在 18-69 岁之间，在 2009 年下半年通过电话进行了访谈（n=12255；基线时的反应率为 60.9%），并在 2010 年底前通过国家登记处进行了随访。符合条件的受访者在 2009 年和 2010 年有活跃的雇佣关系（n=8275）。县的信息（n=19）基于行政登记。感兴趣的结果是 2010 年经医生证明的病假天数除以计划工作日数（即病假百分比（SLP））。
2010 年的平均 SLP 为 5.2%。SLP 的县间差异范围为 4.0%至 7.2%。与年龄和性别调整模型相比，调整职业、经济部门和自我报告的职业暴露后，SLP 最低的县（参照县）和其他县之间的 SLP 中位数差异降低了 1.08 个百分点（即减少了 58%）。职业构成和自我报告的职业暴露对 SLP 县间总方差的影响降低了 16%。
职业构成和自我报告的职业暴露有助于解释县际 SLP 差异的很大一部分，并且似乎比人口统计学变量、自我报告的健康状况和吸烟更重要的解释因素。
