Risk factors and outcomes of anxiety symptom trajectories in type 2 diabetes: the Fremantle Diabetes Study Phase II

Abstract

Aim To identify determinants and outcomes of 4‐year trajectories of anxiety symptoms in a community‐based cohort with type 2 diabetes. Methods Some 1091 participants in the Fremantle Diabetes Study‐Phase II with type 2 diabetes completed the Generalized Anxiety Disorder Scale at baseline and biennially for 4 years, in addition to psychological, biomedical and self‐management measures. Latent growth mixture modelling identified trajectories of anxiety symptom severity, and regression models determined predictors of trajectory membership and associated outcomes. Results Two distinct groups of participants were identified: those with continuously low–no anxiety symptoms (87%) and those with improving but consistently high anxiety symptoms (elevated anxiety; 13%). Higher HbA1c and BMI, macrovascular complications and a history of generalized anxiety and/or major depressive disorder increased the risk of elevated anxiety. Elevated anxiety did not predict change in health‐related outcomes over time. Elevated anxiety and depression symptoms were highly comorbid and those with both displayed the most persistent anxiety symptoms. Conclusions A subgroup of individuals with type 2 diabetes are at risk of persistently elevated anxiety symptoms. Routine monitoring of the severity of psychological symptoms over time in this population should facilitate earlier and more intensive mood management.

Great diversity in the utilization and reporting of latent growth modeling approaches in type 2 diabetes: A literature review

“… 2-To identify predictors and associates of these trajectories. Psychological science Prevalent cases (n = 1,201) Predictors of trajectories: Clinical, biochemical, demographic, depression, psychosocial data Trajectories of depression symptoms Tool : Patient Health Questionnaire Comparison between groups: One-Way ANOVA, X 2 , Mann-Whitney U test, Kruskal-Wallis test Predictive model: Binary logistic regression model Time-point studied: 2 years Trajectory identification follow-up : 4 years Total follow-up: 4 years Latent class growth analysis [ 30 ] Whitworth 2020 [ 13 ] Cohort: Fremantle Diabetes Study Phase II (2008–2011, follow-up until 2016) Type of data source: Primary data (prospective cohort) 1-To identify distinct trajectories of anxiety symptoms in individuals with T2D over time. 2-To identify demographic, self-management and clinical predictors of anxiety trajectory membership.…”

“…A total of 6 studies considered within-class heterogeneity by using LGMM [ 12 , 13 , 14 , 15 , 16 ] or a General Growth Class Mixture Modeling (GGCMM) for randomized intervention [ 17 , 18 ]. Most studies (n = 32) used LCGA.…”

Relationship between nutritional status, anxiety, and depression in hospitalized diabetic patients in Turkey

“…12,32 In a study with 77 diabetic patients, Balhara et al 33 showed that BMI significantly correlated with anxiety and depression scores. Whitworth et al 34 also stated that high BMI could be a risk factor for anxiety in diabetic patients. Additionally, increased waist circumference was associated with anxiety by Mattei et al, 35 while Labad et al 36 associated it with depression.…”

Prevalence and risk factors for depression and anxiety in patients with nasolacrimal duct obstruction

“…The prevalence of depression was discovered to be higher in patients with severe glaucomatous disease, and anxiety disorders of glaucoma patients may also increase due to fear of potential blindness and limitation of daily activities ( 32 , 42 ). Diabetes was also reported a risk factor for anxiety disorders ( 43 , 44 ). A meta-analysis provides evidence that diabetes is related to an increased risk of presence of anxiety disorders and elevated anxious symptoms ( 44 ).…”