Exploring the Relationship Between Depression and Adherence in Individuals with Type 2 Diabetes

  • Author / Creator
    Niaz, Diva
  • Background: Depression is a well-known risk factor for poor medication adherence in individuals with diabetes; however, this association is based on cross-sectional and cohort studies measuring adherence after depression is diagnosed. Symptoms of depression often progress before medical attention is sought and diagnosis is made by a clinician. Prodromal symptoms of depression could affect medication adherence earlier than currently reported in literature. Additionally, little is known about changes in adherence rates once depression is treated. Given the strong association between depression and poor adherence to antihyperglycemic medications, early recognition and treatment of depression may improve adherence, leading to better glycemic control and prevention of future complications.
    Objectives: In individuals with diabetes and a new episode of depression, I sought to: 1) determine if symptoms of depression occurring before a diagnosis are associated with poor medication adherence; 2) determine if treatment of depression affects adherence to oral antihyperglycemic medications.
    Methods: Two retrospective cohort studies following adult new metformin users identified in Alberta Health’s administrative database between 2008 and 2018. Both studies identified a new depressive episode ≥1 year after metformin initiation using a validated case definition for depression. The first study examined adherence patterns in the year before the depression date. People with a new depressive episode were the exposed group and those without depression served as controls. Proportion of Days Covered (PDC) and Group Based Trajectory Modelling (GBTM)  

    were used to examine adherence to oral antihyperglycemic medications one year prior to the depression date. Multivariable logistic regression was used to determine if depression was independently associated with a higher risk of poor adherence antecedent to depression diagnosis. The second study examined association between treatment of a new depressive episode and adherence. The exposure group included those who received at least 2 dispensations of any antidepressant medication within 90 days of depression date while the control group included those with 0.95 [34.8% of cohort]), discontinued antihyperglycemics (PDC=0 [18.3% of cohort], poor initial adherence (PDC 0.75) that declined either rapidly (9.2% of cohort) or

    gradually (30.1% of cohort), and poor initial adherence (PDC 0.26) that increased gradually (7.6% of cohort). Individuals with depression were more likely to be in one of the four trajectories of poor adherence compared to controls (adjusted odds ratio 1.24; 95% CI 1.19-1.29).
    The second study included 7,220 (22.9%) individuals with a new depressive episode who had at least 1 year of data available before their study exit date, no antidepressant dispensations in the previous 6 months and not hospitalized for >50% of the outcome assessment window. A total 1,899 (26.3%) received ≥2 dispensations for antidepressants within 90 days of index date. After adjusting for other comorbidities and characteristics at baseline, individuals treated for depression were associated with a lower, but non-significant likelihood of poor adherence compared to those with no antidepressant treatment (adjusted odds ratio 0.91; 95%CI 0.81,1.02).
    Conclusion: Individuals with a depressive episode were more likely to have poor adherence in the year preceding diagnosis. Although treatment of a new depressive episode appears to be associated with a lower likelihood of poor adherence, the observed association did not reach statistical significance. These studies suggest depression screening and treatment may improve care for patients living with type 2 diabetes. By following adherence patterns, clinicians may identify individuals with diabetes who are experiencing symptoms of depression earlier and intervene sooner.

  • Subjects / Keywords
  • Graduation date
    Fall 2020
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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