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

Kaitlin Harding, Maria Pushpanathan, Stephanie Whitworth, Shenooka Nanthakumar, Romola Bucks, Timothy Skinner

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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 Electronic and hand searching of published and unpublished works identified 147 eligible papers.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, sampleswith 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.
Original languageEnglish
Number of pages12
JournalDiabetic Medicine: journal of diabetes UK
DOIs
Publication statusE-pub ahead of print - 18 Sep 2019

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Type 2 Diabetes Mellitus
Depression
Cognition
Sleep
Anhedonia
Sample Size
Publications

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@article{fa4f1123e343438f9b8f1e5256724b54,
title = "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",
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, sampleswith 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.",
keywords = "Diabetes Mellitus, Type 2, depression (symptoms and symptom management), meta-analysis",
author = "Kaitlin Harding and Maria Pushpanathan and Stephanie Whitworth and Shenooka Nanthakumar and Romola Bucks and Timothy Skinner",
year = "2019",
month = "9",
day = "18",
doi = "10.1111/dme.14139",
language = "English",
journal = "Diabetic Medicine: journal of diabetes UK",
issn = "0742-3071",
publisher = "John Wiley & Sons",

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TY - JOUR

T1 - 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

T2 - a meta‐analysis

AU - Harding, Kaitlin

AU - Pushpanathan, Maria

AU - Whitworth, Stephanie

AU - Nanthakumar, Shenooka

AU - Bucks, Romola

AU - Skinner, Timothy

PY - 2019/9/18

Y1 - 2019/9/18

N2 - 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, sampleswith 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.

AB - 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, sampleswith 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.

KW - Diabetes Mellitus, Type 2

KW - depression (symptoms and symptom management)

KW - meta-analysis

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DO - 10.1111/dme.14139

M3 - Article

JO - Diabetic Medicine: journal of diabetes UK

JF - Diabetic Medicine: journal of diabetes UK

SN - 0742-3071

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