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首页> 外文期刊>Diabetic medicine: A journal of the British Diabetic Association >Predicting diabetes distress in patients with Type 2 diabetes: a longitudinal study.
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Predicting diabetes distress in patients with Type 2 diabetes: a longitudinal study.

机译：预测2型糖尿病患者的糖尿病困扰：一项纵向研究。

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AIMS: Diabetes distress (DD) is a condition distinct from depression that is related to diabetes outcomes. In those without distress initially, little is known about what indicators place patients at risk for subsequent distress over time. METHODS: From a community-based, three-wave, 18-month study of Type 2 diabetic patients (n = 506), we identified patients with no DD at T1 who displayed DD at T2, T3 or both (n = 57). Using logistic regression with full and trimmed models, we compared them with patients with no DD at all three time points (n = 275) on three blocks of variables: patient characteristics (demographics, depression, extra-disease stress), biological (HbA(1c), body mass index, comorbidities, complications, blood pressure, non-high-density lipoprotein-cholesterol), and behavioural variables (diet, exercise). Selected interactions with stress and major depressive disorder (MDD) were explored. RESULTS: The odds of becoming distressed over time were higher for being female, previously having had MDD, experiencing more negative events or more chronic stress, having more complications, and having poor diet and low exercise. Negative life events increased the negative effects of both high HbA(1c) and high complications on the emergence of distress over time. CONCLUSIONS: We identified a list of significant, independent direct and interactive predictors of high DD that can be used for patient screening to identify this high-risk patient cohort. Given the impact of high DD on diabetes behavioural and biological indicators, the findings suggest the usefulness of regularly appraising both current life and disease-related stressors in clinical care.
机译：目的：糖尿病困扰（DD）是一种与抑郁有关的疾病，与糖尿病结局有关。在最初没有困扰的患者中，对于哪些指标使患者随着时间的推移而遭受后续困扰的风险知之甚少。方法：通过一项基于社区的三波18个月的2型糖尿病患者研究（n = 506），我们确定T1时无DD的患者在T2，T3或两者同时显示DD（n = 57）。使用具有完整模型和修剪模型的逻辑回归，我们将其与在所有三个时间点（n = 275）没有DD的患者进行三个变量块的比较：患者特征（人口统计学，抑郁，疾病外应激），生物学（HbA（ 1c），体重指数，合并症，并发症，血压，非高密度脂蛋白胆固醇）和行为变量（饮食，运动）。探索了与压力和重度抑郁症（MDD）的选择性相互作用。结果：随着时间的流逝，成为女性的女性的风险更高，以前患有MDD，经历更多的负面事件或更多的慢性压力，具有更多的并发症，饮食不良和运动量少。负性生活事件随着时间的流逝增加了高HbA（1c）和高并发症对不良事件的负面影响。结论：我们确定了一系列重要的，独立的直接和交互式的高DD预测因子，可用于患者筛查以鉴定该高危患者队列。考虑到高DD对糖尿病行为和生物学指标的影响，研究结果表明定期评估当前生活和与疾病相关的应激源在临床护理中的作用。

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