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Using statutory health insurance data to evaluate non-response in a cross-sectional study on depression among patients with diabetes in Germany.
International Journal of Epidemiology ( IF 7.7 ) Pub Date : 2020-01-28 , DOI: 10.1093/ije/dyz278
Ute Linnenkamp 1, 2, 3 , Veronika Gontscharuk 1, 2, 4 , Manuela Brüne 1, 2, 4 , Nadezda Chernyak 1, 2, 4 , Tatjana Kvitkina 1, 2 , Werner Arend 4 , Annett Fiege 4 , Imke Schmitz-Losem 5 , Johannes Kruse 6 , Silvia M A A Evers 3, 7 , Mickaël Hiligsmann 3 , Barbara Hoffmann 8 , Silke Andrich 1, 2, 4 , Andrea Icks 1, 2, 4
Affiliation  

BACKGROUND Low response rates do not indicate poor representativeness of study populations if non-response occurs completely at random. A non-response analysis can help to investigate whether non-response is a potential source for bias within a study. METHODS A cross-sectional survey among a random sample of a health insurance population with diabetes (n = 3642, 58.9% male, mean age 65.7 years), assessing depression in diabetes, was conducted in 2013 in Germany. Health insurance data were available for responders and non-responders to assess non-response bias. The response rate was 51.1%. Odds ratios (ORs) for responses to the survey were calculated using logistic regression taking into consideration the depression diagnosis as well as age, sex, antihyperglycaemic medication, medication utilization, hospital admission and other comorbidities (from health insurance data). RESULTS Responders and non-responders did not differ in the depression diagnosis [OR 0.99, confidence interval (CI) 0.82-1.2]. Regardless of age and sex, treatment with insulin only (OR 1.73, CI 1.36-2.21), treatment with oral antihyperglycaemic drugs (OAD) only (OR 1.77, CI 1.49-2.09), treatment with both insulin and OAD (OR 1.91, CI 1.51-2.43) and higher general medication utilization (1.29, 1.10-1.51) were associated with responding to the survey. CONCLUSION We found differences in age, sex, diabetes treatment and medication utilization between responders and non-responders, which might bias the results. However, responders and non-responders did not differ in their depression status, which is the focus of the DiaDec study. Our analysis may serve as an example for conducting non-response analyses using health insurance data.

中文翻译:

使用法定健康保险数据来评估德国糖尿病患者抑郁症横断面研究中的无反应情况。

背景 如果无应答完全随机发生,低应答率并不表明研究人群代表性差。无答复分析可以帮助调查无答复是否是研究中偏差的潜在来源。方法 2013 年在德国对健康保险糖尿病人群(n = 3642,58.9% 男性,平均年龄 65.7 岁)进行了一项横断面调查,评估糖尿病引起的抑郁症。健康保险数据可供响应者和非响应者用来评估不响应偏差。回应率为51.1%。使用逻辑回归计算对调查的反应的比值比(OR),考虑到抑郁症诊断以及年龄、性别、降血糖药物、药物使用、住院和其他合并症(来自健康保险数据)。结果 有反应者和无反应者在抑郁症诊断上没有差异[OR 0.99,置信区间 (CI) 0.82-1.2]。无论年龄和性别,仅使用胰岛素治疗(OR 1.73,CI 1.36-2.21)、仅使用口服降血糖药(OAD)治疗(OR 1.77,CI 1.49-2.09)、同时使用胰岛素和OAD治疗(OR 1.91,CI) 1.51-2.43)和较高的一般药物利用率(1.29、1.10-1.51)与对调查的回应相关。结论 我们发现有反应者和无反应者之间在年龄、性别、糖尿病治疗和药物使用方面存在差异,这可能会使结果产生偏差。然而,有反应者和无反应者的抑郁状况没有差异,这是 DiaDec 研究的重点。我们的分析可以作为使用健康保险数据进行无响应分析的示例。
更新日期:2020-01-29
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