Judith Lumley Centre, La Trobe University, Melbourne, Australia; Murdoch Children's Research Institute, Melbourne Australia; Department of Paediatrics, University of Melbourne, Melbourne, Australia.
National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australia.
Soc Sci Med. 2018 Jul;209:160-168. doi: 10.1016/j.socscimed.2018.03.009. Epub 2018 Mar 19.
Understanding the long-term health effects of employment - a major social determinant - on population health is best understood via longitudinal cohort studies, yet missing data (attrition, item non-response) remain a ubiquitous challenge. Additionally, and unique to the work-family context, is the intermittent participation of parents, particularly mothers, in employment, yielding 'incomplete' data. Missing data are patterned by gender and social circumstances, and the extent and nature of resulting biases are unknown.
This study investigates how estimates of the association between work-family conflict and mental health depend on the use of four different approaches to missing data treatment, each of which allows for progressive inclusion of more cases in the analyses. We used 5 waves of data from 4983 mothers participating in the Longitudinal Study of Australian Children.
Only 23% had completely observed work-family conflict data across all waves. Participants with and without missing data differed such that complete cases were the most advantaged group. Comparison of the missing data treatments indicate the expected narrowing of confidence intervals when more sample were included. However, impact on the estimated strength of association varied by level of exposure: At the lower levels of work-family conflict, estimates strengthened (were larger); at higher levels they weakened (were smaller).
Our results suggest that inadequate handling of missing data in extant longitudinal studies of work-family conflict and mental health may have misestimated the adverse effects of work-family conflict, particularly for mothers. Considerable caution should be exercised in interpreting analyses that fail to explore and account for biases arising from missing data.
通过纵向队列研究可以更好地了解就业这一主要社会决定因素对人群健康的长期影响,但数据缺失(流失、项目无应答)仍然是一个普遍存在的挑战。此外,与工作-家庭环境相关的独特之处是父母,尤其是母亲,间歇性地参与就业,导致数据“不完整”。数据缺失存在性别和社会环境差异,由此产生的偏差程度和性质尚不清楚。
本研究调查了工作-家庭冲突与心理健康之间关联的估计值如何取决于四种不同缺失数据处理方法的使用,每种方法都允许在分析中逐步纳入更多的案例。我们使用了 4983 名参与澳大利亚儿童纵向研究的母亲的 5 波数据。
只有 23%的参与者在所有波次中都有完全观察到的工作-家庭冲突数据。有缺失数据和无缺失数据的参与者存在差异,完整案例组是最具优势的群体。缺失数据处理的比较表明,当更多的样本被纳入时,预期的置信区间会变窄。然而,关联估计值的影响因暴露水平而异:在工作-家庭冲突的较低水平下,估计值增强(更大);在较高水平下,它们减弱(更小)。
我们的结果表明,在工作-家庭冲突与心理健康的现有纵向研究中,对缺失数据处理不当可能高估了工作-家庭冲突的不良影响,特别是对母亲而言。在解释未能探索和解释因缺失数据而产生的偏差的分析时,应非常谨慎。