The Impact of Unemployment on Antidepressant Purchasing: Adjusting for Unobserved Time-constant Confounding in the g-Formula.
The Impact of Unemployment on Antidepressant Purchasing: Adjusting for Unobserved Time-constant Confounding in the g-Formula.
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DOI：
10.1097/ede.0000000000000985
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发表时间：
2019-05
期刊：
影响因子：
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通讯作者：
Martikainen P
中科院分区：
文献类型：
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作者：
Bijlsma MJ;Wilson B;Tarkiainen L;Myrskylä M;Martikainen P
补充数字内容可在文本中找到。失业对抑郁的估计影响可能会受到时变、中间和时间常数混淆的影响。可以解释这些偏差来源的为数不多的方法之一是参数g公式，但到目前为止，该方法要求测量所有相关的混杂因素。我们将g公式与调整未测量时间常数混淆的方法结合起来。我们使用这种方法来估计抗抑郁药的购买是如何受到一个假设的干预，为失业者提供就业的影响。该分析基于1995年30-35岁芬兰人口中11%的随机样本（n = 49,753），并一直持续到2012年。我们比较了调整了测量基线混杂因素和时变社会经济协变量（混杂因素和中介因素）的估计值与还包括个人水平固定效应截距的估计值。在经验数据中，大约10%的人年处于失业状态。将这些人-年设定为使用时间，没有个体截距的g公式发现，在人群水平上，抗抑郁药的购买减少了5%（95%置信区间[CI] = 2.5%, 7.4%）。然而，当也调整个人拦截时，我们发现没有关联（- 0.1%;95% CI = - 1.8%, 1.5%）。结果表明，失业和抗抑郁药物之间的关系被剩余时间常数混淆（选择）所混淆。然而，当使用单个截点时，对有效样本的限制可能会损害结果的有效性。总的来说，我们的方法强调了在流行病学研究中调整未观察到的时间常数混淆的潜在重要性，并展示了一种可以做到这一点的方法。
Supplemental Digital Content is available in the text. The estimated effect of unemployment on depression may be biased by time-varying, intermediate, and time-constant confounding. One of the few methods that can account for these sources of bias is the parametric g-formula, but until now this method has required that all relevant confounders be measured. We combine the g-formula with methods to adjust for unmeasured time-constant confounding. We use this method to estimate how antidepressant purchasing is affected by a hypothetical intervention that provides employment to the unemployed. The analyses are based on an 11% random sample of the Finnish population who were 30–35 years of age in 1995 (n = 49,753) and followed until 2012. We compare estimates that adjust for measured baseline confounders and time-varying socioeconomic covariates (confounders and mediators) with estimates that also include individual-level fixed-effect intercepts. In the empirical data, around 10% of person-years are unemployed. Setting these person-years to employed, the g-formula without individual intercepts found a 5% (95% confidence interval [CI] = 2.5%, 7.4%) reduction in antidepressant purchasing at the population level. However, when also adjusting for individual intercepts, we find no association (−0.1%; 95% CI = −1.8%, 1.5%). The results indicate that the relationship between unemployment and antidepressants is confounded by residual time-constant confounding (selection). However, restrictions on the effective sample when using individual intercepts can compromise the validity of the results. Overall our approach highlights the potential importance of adjusting for unobserved time-constant confounding in epidemiologic studies and demonstrates one way that this can be done.