Knapstad Marit, Löve Jesper, Holmgren Kristina, Hensing Gunnel, Øverland Simon
Department of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway.
Department of Clinical Psychology, University of Bergen, Bergen, Norway.
BMJ Open. 2016 Oct 21;6(10):e012372. doi: 10.1136/bmjopen-2016-012372.
Selective participation can bias results in epidemiological surveys. The importance of health status is often suggested as a possible explanation for non-participation but few empirical studies exist. In a population-based study, explicitly focused on sickness absence, health and work, we examined whether a history of high levels of sickness absence was associated with non-participation.
The study is based on data from official sickness absence registers from participants, non-participants and the total target population of the baseline survey of the Health Assets Project (HAP).
HAP is a population-based cohort study in the Västra Götaland region in South Western Sweden.
HAP included a random population cohort (n=7984) and 2 cohorts with recent sickness absence (employees (n=6140) and non-employees (n=990)), extracted from the same overall general working-age population.
We examined differences in participation rates between cohorts (2008), and differences in previous sickness absence (2001-2008) between participants (individual-level data) and non-participants or the target population (group-level data) within cohorts.
Participants had statistically significant less registered sickness absence in the past than non-participants and the target population for some, but not all, of the years analysed. Yet these differences were not of substantial size. Other factors than sickness absence were more important in explaining differences in participation, whereby participants were more likely to be women, older, born in Nordic countries, married and have higher incomes than non-participants.
Although specifically addressing sickness absence, having such experience did not add any substantial layer to selective participation in the present survey. Detailed measures are needed to gain a better understanding for health selection in health-related surveys such as those addressing sickness absence, for instance in order to discriminate between selection due to ability or motivation for participation.
在流行病学调查中，选择性参与可能会使结果产生偏差。健康状况的重要性常被认为是不参与调查的一个可能解释，但实证研究却很少。在一项基于人群的研究中，该研究明确聚焦于病假、健康和工作，我们调查了高病假记录史是否与不参与调查有关。
本研究基于健康资产项目（HAP）基线调查中参与者、非参与者及总目标人群的官方病假登记数据。
HAP是瑞典西南部韦斯特罗斯-哥德堡地区的一项基于人群的队列研究。
HAP包括一个随机人群队列（n = 7984）以及两个近期有过病假记录的队列（员工（n = 6140）和非员工（n = 990）），这些队列均从相同的总体劳动年龄人口中抽取。
我们研究了各队列之间（2008年）参与率的差异，以及各队列中参与者（个体层面数据）与非参与者或目标人群（群体层面数据）之间过去（2001 - 2008年）病假记录的差异。
在分析的部分而非所有年份中，参与者过去的病假登记统计上显著少于非参与者和目标人群。然而，这些差异规模不大。除病假外，其他因素在解释参与差异方面更为重要，参与者比非参与者更可能是女性、年龄更大、出生在北欧国家、已婚且收入更高。
尽管本研究专门针对病假情况，但有此类经历并未给本次调查中的选择性参与增加任何实质性影响。需要采取详细措施，以便更好地理解与健康相关调查中的健康选择，例如那些涉及病假情况的调查，例如为了区分因参与能力或动机导致的选择。
