Depression prevalence in Type 2 diabetes is not related to diabetes–depression symptom overlap but is related to symptom dimensions within patient self‐report measures: a meta‐analysis. Issue 12 (29th September 2019) - Harding, K. A.; Pushpanathan, M. E.; Whitworth, S. R.; Nanthakumar, S.; Bucks, R. S.; Skinner, T. C.
What's new?: Prevalence of depression ranged from 1.8% to 88% (mean = 28.30%) across 147 studies. Younger sample age, higher HbA1c and clinic samples were associated with higher depression prevalence. There was no effect of depression–diabetes overlap items on depression estimates. Questionnaires with a higher proportion of anhedonia, cognition, cognitive, negative affect and sleep disturbance symptoms, and a lower proportion of somatic symptoms were consistently associated with higher depression prevalence. Depression measures that focus on the cardinal symptoms of depression (e.g. negative affect and cognition), limiting symptoms associated with increased diabetes symptomatology (e.g. sleep disturbance, cognitive) may most accurately diagnose depression. Abstract: Aim: Depression is common in Type 2 diabetes, yet rates vary. Overlap between symptoms of depression and diabetes may account for this variability in depression prevalence rates. We examined to what extent depression prevalence was a function of the proportion of depression–diabetes symptom overlap (items within symptom dimensions) and sample characteristics. Methods: Electronic and hand searching of published and unpublished works identified 147 eligible papers. Of 3656 screened, 147 studies (149 samples, N = 17–229 047, mean sample age 25.4–82.8 years, with 152 prevalence estimates), using 24 validated depression questionnaires were selected. Sample size, publication type, sample type, gender, age, BMI, HbA1c, depression questionnaire and prevalence rates were extracted. Results: Prevalence rates ranged from 1.8% to 88% (mean = 28.30%) and were higher in younger samples, samples with higher mean HbA1c and clinic samples. Diabetes–depression symptom overlap did not affect prevalence. A higher proportion of anhedonia, cognition, cognitive, negative affect and sleep disturbance symptoms, and a lower proportion of somatic symptoms were consistently associated with higher depression prevalence. Conclusions: The lack of an overall effect of diabetes–depression symptom overlap might suggest that assessment of depression in Type 2 diabetes is generally not confounded by co‐occuring symptoms. However, questionnaires with proportionally more or fewer items measuring other symptom categories were associated with higher estimates of depression prevalence. Depression measures that focus on the cardinal symptoms of depression (e.g. negative affect and cognition), limiting symptoms associated with increasing diabetes symptomatology (e.g. sleep disturbance, cognitive) may most accurately diagnose depression.