Diabetes increases the risk of depression: A systematic review, meta-analysis and estimates of population attributable fractions based on prospective studies

Chireh, Batholomew; Li, Muzi; D’Arcy, Carl

doi:10.1016/j.pmedr.2019.100822

Cited by 104 publications

(89 citation statements)

References 70 publications

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“…A systematic review with meta-analysis of 11 longitudinal studies showed that, compared with individuals without diabetes, people with type 2 diabetes have a 24% increased risk of developing depression [23]. A later systematic review with meta-analysis of 16 longitudinal studies reported a higher pooled OR for incident depression among respondents with diabetes (1.34, 95% CI 1.14-1.57, v 2 = 76.65, I 2 = 80.4%; P < 0.001), again confirming diabetes as a risk factor for depression [24]. Nefs et al [25] conducted a 3-year longitudinal study of 2460 people with type 2 diabetes and ª 2020 Diabetes UK examined the course (incidence, recurrence/persistence) of depressive symptoms by self-report questionnaire in a primary care setting.…”

Section: Depression In Diabetes: Results From Prospective Studiesmentioning

confidence: 91%

“…A systematic review with meta‐analysis of 11 longitudinal studies showed that, compared with individuals without diabetes, people with type 2 diabetes have a 24% increased risk of developing depression . A later systematic review with meta‐analysis of 16 longitudinal studies reported a higher pooled OR for incident depression among respondents with diabetes (1.34, 95% CI 1.14–1.57, χ 2 = 76.65, I 2 = 80.4%; P < 0.001), again confirming diabetes as a risk factor for depression . Nefs et al .…”

Section: What We Now Know After 25 Years Of Research Into Diabetes Anmentioning

confidence: 91%

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How 25 years of psychosocial research has contributed to a better understanding of the links between depression and diabetes

et al. 2020

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This narrative review of the literature provides a summary and discussion of 25 years of research into the complex links between depression and diabetes. Systematic reviews have shown that depression occurs more frequently in people with type 1 or type 2 diabetes compared with people without diabetes. Currently, it remains unclear whether depression is also more common in people with impaired glucose metabolism or undiagnosed type 2 diabetes compared with people without diabetes. More prospective epidemiological research into the course of depression and an exploration of mechanisms in individuals with diabetes are needed. Depression in diabetes is associated with less optimal self‐care behaviours, suboptimal glycaemic control, impaired quality of life, incident micro‐ and macrovascular diseases, and elevated mortality rates. Randomized controlled trails concluded that depression in diabetes can be treated with antidepressant medication, cognitive–behavioural therapy (individual, group‐based or web‐based), mindfulness‐based cognitive therapy and stepped care. Although big strides forward have been made in the past 25 years, scientific evidence about depression in diabetes remains incomplete. Future studies should investigate mechanisms that link both conditions and test new diabetes‐specific web‐ or app‐based interventions for depression in diabetes. It is important to determine whether treatment or prevention of depression prevents future diabetes complications and lowers mortality rates.

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Section: Depression In Diabetes: Results From Prospective Studiesmentioning

confidence: 91%

Section: What We Now Know After 25 Years Of Research Into Diabetes Anmentioning

confidence: 91%

How 25 years of psychosocial research has contributed to a better understanding of the links between depression and diabetes

et al. 2020

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“…Both depression and diabetes are highly prevalent, often co-occurring diseases that are among the major causes of global disability. [1][2][3] Comorbid diabetes and depression are associated with a worse prognosis of both diseases, including a higher rate of complications of diabetes, greater disability and an increased risk of mortality. 4 Vulnerable populations, including low-income, low health literacy and ethnic minority individuals experience higher prevalences and worse outcomes for both diabetes and depression.…”

Section: Introduction Backgroundmentioning

confidence: 99%

mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study

et al. 2020

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IntroductionDepression and diabetes are highly disabling diseases with a high prevalence and high rate of comorbidity, particularly in low-income ethnic minority patients. Though comorbidity increases the risk of adverse outcomes and mortality, most clinical interventions target these diseases separately. Increasing physical activity might be effective to simultaneously lower depressive symptoms and improve glycaemic control. Self-management apps are a cost-effective, scalable and easy access treatment to increase physical activity. However, cutting-edge technological applications often do not reach vulnerable populations and are not tailored to an individual’s behaviour and characteristics. Tailoring of interventions using machine learning methods likely increases the effectiveness of the intervention.Methods and analysisIn a three-arm randomised controlled trial, we will examine the effect of a text-messaging smartphone application to encourage physical activity in low-income ethnic minority patients with comorbid diabetes and depression. The adaptive intervention group receives messages chosen from different messaging banks by a reinforcement learning algorithm. The uniform random intervention group receives the same messages, but chosen from the messaging banks with equal probabilities. The control group receives a weekly mood message. We aim to recruit 276 adults from primary care clinics aged 18–75 years who have been diagnosed with current diabetes and show elevated depressive symptoms (Patient Health Questionnaire depression scale-8 (PHQ-8) >5). We will compare passively collected daily step counts, self-report PHQ-8 and most recent haemoglobin A1c from medical records at baseline and at intervention completion at 6-month follow-up.Ethics and disseminationThe Institutional Review Board at the University of California San Francisco approved this study (IRB: 17-22608). We plan to submit manuscripts describing our user-designed methods and testing of the adaptive learning algorithm and will submit the results of the trial for publication in peer-reviewed journals and presentations at (inter)-national scientific meetings.Trial registration numberNCT03490253; pre-results.

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“…The number of new cases of depression increased from 17.2 million in 1990 to 25.8 million in 2017 [9]. Over 9.5 million of global depression cases are attributable to diabetes [10]. The occurrence of depression in people with diabetes mellitus is about two to three times higher compared to the general population [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Depression and Its Associated Factors among Diabetes Mellitus Patients Attending Selected Hospitals in Southwest Ethiopia: A Cross-Sectional Study

et al. 2020

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Background. Diabetes mellitus and depression are very common diseases worldwide, and the prevalence rates of both conditions are increasing rapidly. Depression among patients with diabetes mellitus results in poor glycemic control through different mechanisms. Besides, the coexistence of a chronic medical illness with depression reduces the probability of recognizing and treating depression. The study is aimed at assessing the prevalence and factors associated with depression among adults with diabetes mellitus. Methods. A hospital-based cross-sectional study was conducted among adult diabetes mellitus patients on follow-up in Mizan-Tepi University Teaching Hospital and Tepi General Hospital. A consecutive sampling technique was employed to recruit the study participants, and data were collected through face-to-face interview and medical chart review. Depression was measured using Patient Health Questionnaire-nine (PHQ-9). Binary logistic regression analysis was done and a p value of less than 0.05 was used as a level of significance. Results. The prevalence of depression among study participants was 37.0% (95% CI 32.0%-42.0%). The majority (44.7%) of the patients had mild depression, while only 2% had severe depression. Being male (AOR=1.92, 95% CI: 1.15-3.22), urban residence (AOR=3.02, 95% CI: 1.57-5.78), single marital status (AOR=7.72, 95% CI: 3.6-16.53), duration of diabetes mellitus 5 years and more (AOR=2.00, 95% CI: 1.21-3.5), and having sexual dysfunction (AOR=3.55, 95% CI: 2.13-5.91) were associated with increased odds of depression among diabetes mellitus patients. Conclusions. The prevalence of depression among diabetes mellitus was high. Therefore, the patients should be thoroughly screened for this comorbid condition, and the significant factors should be addressed during routine follow-up.

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Diabetes increases the risk of depression: A systematic review, meta-analysis and estimates of population attributable fractions based on prospective studies

Cited by 104 publications

References 70 publications

How 25 years of psychosocial research has contributed to a better understanding of the links between depression and diabetes

How 25 years of psychosocial research has contributed to a better understanding of the links between depression and diabetes

mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study

Depression and Its Associated Factors among Diabetes Mellitus Patients Attending Selected Hospitals in Southwest Ethiopia: A Cross-Sectional Study

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