Green Michael J, Espie Colin A, Popham Frank, Robertson Tony, Benzeval Michaela
MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, 200 Renfield Street, Glasgow, G2 3QB, UK.
Nuffield Department of Clinical Neurosciences, Sleep & Circadian Neuroscience Institute, University of Oxford, Oxford, OX3 9DU, UK.
BMC Psychiatry. 2017 Mar 16;17(1):94. doi: 10.1186/s12888-017-1268-4.
Insomnia symptoms are associated with type 2 diabetes incidence but are also associated with a range of potential time-varying covariates which may confound and/or mediate associations. We aimed to assess whether cumulative exposure to insomnia symptoms has a causal effect on type 2 diabetes incidence.
A prospective cohort study in the West of Scotland, following respondents for 20 years from age 36. 996 respondents were free of diabetes at baseline and had valid data from up to four follow-up visits. Type 2 diabetes was assessed at the final visit by self-report, taking diabetic medication, or blood-test (HbA ≥ 6.5% or 48 mmol/mol). Effects of cumulative insomnia exposure on type 2 diabetes incidence were estimated with traditional regression and marginal structural models, adjusting for time-dependent confounding (smoking, diet, physical inactivity, obesity, heavy drinking, psychiatric distress) as well as for gender and baseline occupational class.
Traditional regression yielded an odds ratio (OR) of 1.34 (95% CI: 1.06-1.70) for type 2 diabetes incidence for each additional survey wave in which insomnia was reported. Marginal structural models adjusted for prior covariates (assuming concurrently measured covariates were potential mediators), reduced this OR to 1.20 (95% CI: 0.98-1.46), and when concurrent covariates were also included (viewing them as potential confounders) this dropped further to 1.08 (95% CI: 0.85-1.37).
The association between cumulative experience of insomnia and type 2 diabetes incidence appeared confounded. Evidence for a residual causal effect depended on assumptions as to whether concurrently measured covariates were confounders or mediators.
失眠症状与2型糖尿病的发病率相关,但也与一系列潜在的随时间变化的协变量有关,这些协变量可能会混淆和/或介导两者之间的关联。我们旨在评估失眠症状的累积暴露是否对2型糖尿病的发病率有因果影响。
在苏格兰西部进行的一项前瞻性队列研究,对36岁的受访者进行了20年的随访。996名受访者在基线时无糖尿病,并拥有多达四次随访的有效数据。在最后一次随访中通过自我报告、服用糖尿病药物或血液检测(糖化血红蛋白≥6.5%或48 mmol/mol)来评估2型糖尿病。使用传统回归和边际结构模型估计失眠累积暴露对2型糖尿病发病率的影响,并对时间依赖性混杂因素(吸烟、饮食、缺乏体育锻炼、肥胖、大量饮酒、精神困扰)以及性别和基线职业阶层进行调整。
传统回归得出,每多一次报告有失眠症状的调查波次,2型糖尿病发病率的比值比(OR)为1.34(95%置信区间:1.06-1.70)。针对先前的协变量进行调整的边际结构模型(假设同时测量的协变量是潜在的中介因素)将该OR降至1.20(95%置信区间:0.98-1.46),当同时纳入这些协变量(将它们视为潜在的混杂因素)时,该值进一步降至1.08(95%置信区间:0.85-1.37)。
失眠的累积经历与2型糖尿病发病率之间的关联似乎存在混杂。残余因果效应的证据取决于关于同时测量的协变量是混杂因素还是中介因素的假设。