Predicting diabetes distress in patients with Type 2 diabetes: a longitudinal study

Authors


Lawrence Fisher, Department of Family and Community Medicine, UCSF, PO Box 0900, San Francisco, CA 94143, USA. E-mail: fisherl@fcm.ucsf.edu

Abstract

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 (HbA1c, 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 HbA1c 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.

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