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Figure 1.
PRISMA Flowchart of Study Selection
PRISMA Flowchart of Study Selection

CIND indicates cognitive impairment with no dementia; MCI, mild cognitive impairment.

Figure 2.
Forest Plot for Prevalence of Depression in People With MCI Stratified by Population Source
Forest Plot for Prevalence of Depression in People With MCI Stratified by Population Source

MCI indicates mild cognitive impairment.

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Original Investigation
Meta-analysis
November 23, 2016

Prevalence of Depression in Patients With Mild Cognitive ImpairmentA Systematic Review and Meta-analysis

Author Affiliations
  • 1Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
  • 2Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
  • 3Keenan Research Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, Ontario, Canada
  • 4Division of Geriatric Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
  • 5Department of Clinical Health Psychology, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
  • 6Centre for Research on Ageing, Health, and Wellbeing, Australian National University College of Medicine, Canberra, Australian Capital Territory, Australia
  • 7Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
JAMA Psychiatry. Published online November 23, 2016. doi:10.1001/jamapsychiatry.2016.3162
Key Points

Question  What is the prevalence of depression in patients with mild cognitive impairment?

Findings  In this meta-analysis, of 57 studies that reported on the prevalence of depression in a population with mild cognitive impairment, representing 20 892 participants, the overall prevalence of depression was 32%. There were differences in prevalence estimates between community samples (25%) and clinical samples (40%).

Meaning  Depression is common in those with mild cognitive impairments.

Abstract

Importance  Depression is common in individuals with mild cognitive impairment (MCI) and may confer a higher likelihood of progression to dementia. Prevalence estimates of depression in those with MCI are required to guide both clinical decisions and public health policy, but published results are variable and lack precision.

Objective  To provide a precise estimate of the prevalence of depression in individuals with MCI and identify reasons for heterogeneity in the reported results.

Data Sources  A search of literature from database inception to March 2016 was performed using Medline, Embase, and PsycINFO. Hand searching of all included articles was performed, including a Google Scholar search of citations of included articles.

Study Selection  Articles were included if they (1) were published in English, (2) reported patients with MCI as a primary study group, (3) reported depression or depressive symptoms using a validated instrument, and (4) reported the prevalence of depression in patients with MCI.

Data Extraction and Synthesis  All abstracts, full-text articles, and other sources were reviewed, with data extracted in duplicate. The overall prevalence of depression in patients with MCI was pooled using a random-effects model. Heterogeneity was explored using stratification and random-effects meta-regression.

Main Outcomes and Measures  The prevalence of depression in patients with MCI, reported as a percentage with 95% CIs. Estimates were also stratified by population source (community-based or clinic-based sample), method of depression diagnosis (clinician-administered, informant-based, or self-report), and method of MCI diagnosis (cognitive vs global measure and amnestic vs nonamnestic).

Results  Of 5687 unique abstracts, 255 were selected for full-text review, and 57 studies, representing 20 892 patients, met all inclusion criteria. The overall pooled prevalence of depression in patients with MCI was 32% (95% CI, 27-37), with significant heterogeneity between estimates (I2 = 90.7%). When stratified by source, the prevalence of depression in patients with MCI in community-based samples was 25% (95% CI, 19-30) and was 40% (95% CI, 32-48) in clinic-based samples, which was significantly different (P < .001). The method used to diagnose depression did not significantly influence the prevalence estimate, nor did the criteria used for MCI diagnosis or MCI subtype.

Conclusions and Relevance  The prevalence of depression in patients with MCI is high. A contributor to heterogeneity in the reported literature is the source of the sample, with greater depression burden prevalent in clinic-based samples.

Introduction

Depression commonly occurs in association with mild cognitive impairment (MCI).13 Individuals with MCI and depression perform more poorly on immediate and delayed memory tasks compared with nondepressed patients with MCI.4 Further, evidence suggests that depression confers a higher rate of progression along the neurodegenerative spectrum from MCI to dementia; a systematic review and meta-analysis5 of 18 studies determined the pooled relative risk of progressing to dementia was 1.28 (P = .003) in the group of patients with MCI with depressive symptoms compared with the those with MCI with no depressive symptoms. Even subsyndromal symptoms of depression have been identified as a significant factor associated with poorer function and quality of life in patients with MCI as well as a higher progression rate to dementia.68 Thus, appropriate screening strategies for depression and depressive symptoms are paramount in identifying what is a significant risk factor for cognitive, functional, and behavioral outcomes in those who are cognitively impaired.

However, depression is a heterogeneous disease with no clear biomarker or gold standard for diagnosis. Rather, a depressive syndrome is diagnosed based on clinical symptoms, and rating scales are used to assess and screen for depression. Further, evidence suggests depression is a difficult diagnosis in those with neurocognitive disorders, and depression in older adults has a cognitive profile that may or may not meet threshold criteria for MCI.9 Because MCI and depression can have overlapping symptoms, disentangling and differentiating between them can be problematic. Both depression and MCI tend to be underrecognized in clinical settings. However, inappropriate or delayed treatment of depression has negative repercussions for functioning, quality of life, general health status, and the clinical course.10,11

Despite the importance of this association between MCI and depression, to our knowledge, no consensus has emerged around certain foundational elements of knowledge in this area. Among these is the question of prevalence. Many studies examining depression prevalence in patients with MCI have been conducted, but the results have been inconsistent.1215 This knowledge gap is an impediment to policy and practice. For example, the success of screening programs is sensitive to the prevalent base rate. Given that inconsistencies are prominent in the current literature, a systematic review and meta-analysis will be useful in determining the best estimate of prevalence currently available and clarifying the reasons for differences in estimates.

Methods
Search Strategy

Using an a priori protocol that was registered with PROSPERO,16 we conducted our systematic review according to both MOOSE17 and PRISMA18 standards. The search strategy was developed in consultation with a research librarian and experts in both MCI (Z.I.) and depression (S.B.P.). Three electronic databases (ie, Medline, Embase, and PsycINFO) were searched from inception to March 2016 with no restriction on the year of the study. Medical Subject Headings and keywords related to depression or depressive symptoms, MCI, and prevalence were used (eAppendix in the Supplement). The reference lists of all included full-text articles were searched to identify any studies missed in the initial search, and Google Scholar was used to find academic articles citing eligible articles. Content-area experts on the author team were canvassed to determine if any relevant studies were missing and to provide information on ongoing or unpublished studies. References that consisted of abstracts alone were not considered. References were compiled and managed using Endnote X7 (Thomson Reuters), with duplicates removed using this software.

Study Selection

Nine reviewers screened titles and abstracts, each of which was reviewed independently by 2 individuals. At this stage, the criteria were purposely broad to allow inclusion of any relevant studies. To be included, studies had to be published in English and report original research using any observational design (eg, cross-sectional or cohort) that reported on depression in patients with MCI. Case reports and series were excluded.

The full text of any study selected by either of the 2 reviewers was reviewed. These were done in duplicate. Articles were included if they (1) were published in English, (2) reported patients with MCI as a primary study group, (3) reported depression or depressive symptoms using a validated instrument, and (4) reported the prevalence of depression in patients with MCI. Articles reporting patients with depression vs patients with MCI as the primary study population (ie, prevalence of MCI in depression) were excluded. Studies using only the Mini–Mental State Examination to diagnose MCI were also excluded because of the lack of sensitivity of this instrument for MCI.19 All studies meeting inclusion criteria at this stage were reviewed (by Z.I. or K.F.) to ensure appropriateness for inclusion in the final analysis. Disagreements of eligibility were reconciled by the original reviewers and, if required, a third reviewer (Z.I. or K.F.). An additional reviewer (Z.I. or K.F.) examined any studies that used the same sample of data. Studies providing the most detailed information were included, and the others were kept for reference.

Data Abstraction and Study Quality

A standardized online data abstraction form was developed using FormsCentral (Adobe) and pilot tested in a random sample of articles to ensure all relevant study-related variables were captured. Two independent reviewers abstracted data on each included study. The following data were abstracted: study information (ie, author, journal, and year), study characteristics (ie, mean age of participants, location, and duration of data collection), condition information (ie, data sources, condition definition, and total number of participants), and the prevalence of depression in patients with MCI or the information necessary to calculate an estimate.

Study quality was assessed using the quality assessment tool for observational studies from the National Heart, Lung, and Blood Institute (eTable 1 in the Supplement).20 The tool contains 14 criteria on which quality is determined, including whether the study population was clearly specified and defined, whether outcome assessors were blind, and an evaluation of the participation rate. The criteria were rated as either yes, no, or “other” (ie, cannot determine, not reported, or not applicable), and an overall rating for the study as “good,” “fair,” or “poor” was provided. We did not evaluate item 14 of the scale (“Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure[s] and outcome[s]?”), as the goal of this study was to determine prevalence estimates. For item 10 (“Was the exposure[s] assessed more than once over time?”), the response was recorded as yes in cohort studies only if multiple measurements of the exposure (in this case, depression) were used. That is, if only the baseline exposure assessment was used, it was marked as no, regardless of the number of follow-up measurements. For cross-sectional studies, items 7 (“Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed?”) and 13 (“Was loss to follow-up after baseline 20% or less?”) were recorded as not applicable.

Data Synthesis and Analysis

A random-effects model was used because of assumed heterogeneity between the studies. The metaprop package in Stata 14.0 (StataCorp) was used to produce the pooled estimates, forest plots, and meta-regression. The meta-analysis of proportions uses the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances.21 Heterogeneity was quantified using the I2 statistic, and its significance was determined based on the accompanying Cochran Q test P value.22 An I2 value of 0% indicates no observed heterogeneity, and increasing values represent greater amounts of heterogeneity; values of 25%, 50%, and 75% indicate low, moderate, and high levels of heterogeneity, respectively.22 τ2 Values arising from the random-effects models were also used to quantify heterogeneity.

The effects of study population source (community-based or clinic-based), method of depression diagnosis (informant-rated, self-report, or clinician-administered), method of MCI diagnosis (cognitive or global criteria), and subtype of MCI (amnestic or nonamnestic) on the prevalence of depression in patients with MCI were assessed using random-effects meta-regression. Community samples were from nonclinical, population-based epidemiological studies, and clinic-based samples included participants in clinical care at academic research institutions. Informant-rated scales were those completed by a family member or other informant with adequate knowledge of the participant. If studies used multiple cut points to score the depression tools, then the least restrictive cut point was selected. The metabias command assessed publication bias using both Begg and Egger tests. Descriptive statistics were calculated using proportions and means and compared using t tests where appropriate. For all tests, P < .05 was considered statistically significant.

Results
Identification and Description of Studies

We screened a total of 5687 unique citations and excluded 5432 at this stage (Figure 1). We reviewed the full text of 255 articles, and of these, 57 met all inclusion criteria (eTable 2 in the Supplement).

Of the included studies, 23 were from North America, 22 from Europe, 8 from Asia, 2 from Australia, and 1 from each of Africa and South America. Dates of publication ranged from 2001 to 2015. Depression was identified by self-reported rating scales (variations of the Geriatric Depression Scale,23,24 Beck Depression Inventory,25 Personal Health Questionnaire,26 and Center for Epidemiological Studies Depression Scale27), caregiver rating scales (Behavioral Pathology in Alzheimer’s Disease,28 Neuropsychiatric Inventory,29 and Neuropsychiatric Inventory Questionnaire30), clinician-administered instruments (Cornell Scale for Depression in Dementia,31 Hamilton Depression Rating Scale,32 Montgomery-Åsberg Depression Rating Scale,33 and Comprehensive Psychopathological Rating Scale34), and semi-structured clinical interview (Cambridge Mental Disorders for the Elderly Examination35 and DSM36). Mild cognitive impairment or equivalent (ie, cognitive impairment with no dementia [CIND]) was analyzed as defined by the study authors. These criteria varied across studies; criteria, scales, and assessments included Petersen criteria,37,38 a determination of CIND,39 Winblad criteria,40 cutoffs on standardized cognitive rating scales (less than 1.5 SD below the mean),41 or by a Clinical Dementia Rating Scale (CDR) score of 0.5.42

Depression or Depressive Symptoms in Patients With MCI

The overall pooled prevalence of depression or depressive symptoms in patients with MCI was 32% (95% CI, 27-37) with significant heterogeneity present (I2 = 90.7%; Q P < .001; τ2 = 0.013).

Sources of Heterogeneity
Sample Source

When stratified by the source of the sample, the prevalence of depression in patients with MCI from the 28 community-based samples was significantly lower than patients from the 29 studies reporting on clinic-based samples (25%; 95% CI, 19-30; vs 40%; 95% CI, 32-48; P < .001) (Figure 2). Significant heterogeneity existed within the estimates for community-based samples (I2 = 82.1%; Q P < .001; τ2 = 0.0065) and clinic-based samples (I2 = 93.3%; Q P < .001; τ2 = 0.0.013). In community studies, estimates ranged from 11% to 63%. In clinic-based samples, estimates ranged from 20% to 79%.

Method of Depression Diagnosis

There was no difference in the prevalence of depression in patients with MCI based on how depression was diagnosed (P = .80). Prevalence estimates from 24 informant-rated (31%; 95% CI, 24-38), 18 self-reported (32%; 95% CI, 23-43), and 15 clinician-administered (35%; 95% CI, 25-45) sources were similar. Significant heterogeneity between estimates in each strata were noted (P < .001; τ2 = 0.014).

Method of MCI Diagnosis

When stratified by whether MCI diagnosis was based on cognitive criteria3840 or a global measure (ie, CDR),42 there was no difference in the estimates of depression prevalence (P = .89). The 6 studies using the CDR had a very slightly lower prevalence (31%; 95% CI, 16-49) than the 51 studies using cognitive criteria (32%; 95% CI, 27-38), with significant heterogeneity present within both strata (P < .001; τ2 = 0.013). Studies using the Petersen criteria37,38 or Winblad criteria40 to diagnose MCI had a slightly higher prevalence than those that did not (33%; 95% CI, 27-37; vs 30%; 95% CI, 20-40; P = .60).

The prevalence of depression was highest in studies using the Winblad criteria40 (36%; 95% CI, 22-52), followed by CIND (32%; 95% CI, 20-46), Petersen criteria37,38 (32%; 95% CI, 26-39), and CDR (29%; 95% CI, 12-50) and was lowest in studies using only standardized neuropsychological testing (24%; 95% CI, 16-33) to diagnose MCI (P = .53).

MCI Subtype

The subtype of MCI was reported by 15 studies; all 15 studies reported amnestic subtype, and of these, 8 studies reported depression prevalence for patients with the nonamnestic subtype as well. The prevalence of depression was higher in patients with amnestic MCI (34%; 95% CI, 25-42; I2 = 76.1%; Q P < .001; τ2 = 0.07) than patients with nonamnestic MCI (26%; 95% CI, 14-40; I2 = 83.0%; Q P < .001; τ2 = 0.13), although this difference was not significant (P = .30).

Other Demographic Variables

In the 43 studies reporting on the mean age of participants (range, 53.2 to 88.5 years), study mean age was not significantly associated with the prevalence of depression in patients with MCI (P = .19). Because there was only 1 study conducted in Africa and 1 from South America, a meta-analysis including these continents was not possible. Among the remaining continents, the prevalence of depression in patients with MCI was significantly lower in the 2 studies from Australia (13%; 95% CI, 4-25) compared with the 22 from Europe (37%; 95% CI, 29-46; P < .001) and the 23 from North America (30%; 95% CI, 23-38; P = .03).

Publication Bias

Publication bias in the prevalence of depression in patients with MCI was not detected using the Begg test (P = .91) or Egger test (P = .08).

Study Quality

Most studies (48 [84.2%]) had an overall rating of fair quality, while 4 (7.0%) studies were rated as good and 5 (8.8%) as poor (eTable 1 in the Supplement). The most frequently met quality criteria were item 1 (“Was the research question or objective in this paper clearly stated”; reported by all studies) and item 2 (“Was the study population clearly specified and defined”; reported by 96.5% [55 of 57] of studies). A number of items were rarely reported, including item 5 (“Was a sample size justification, power description, or variance and effect estimates provided”; reported by 3.5% [2 of 57] studies) and item 12 (“Were the outcome assessors blinded to the exposure status of participants”; reported by none of the studies).

Discussion

We conducted a systematic review and meta-analysis to determine the best estimate of prevalence of depression in patients with MCI. The overall pooled prevalence of depression was 32%, which is comparable with previous studies on patients with MCI1215 and on patients with dementia.94,95 A recent systematic review and meta-analysis95 on the prevalence of depression in patients with Alzheimer disease found significant heterogeneity in estimates (5%-48%) based on patient sampling, dementia severity, and diagnostic criteria used. Similarly, a meta-analysis94 of depression prevalence in patients with frontotemporal lobar dementia determined an omnibus depression prevalence of 33% but with significant heterogeneity. Thus, in patients with MCI, while there is less cognitive impairment than in the dementia population by definition, depression prevalence is comparable, as is the heterogeneity in prevalence estimates (I2 = 90.8%). We explored 3 sources of heterogeneity identified a priori: population source, method of depression diagnosis, and method of MCI classification. When stratified by source, the prevalence of depression in patients with MCI was significantly different, with 25% in community-based samples and 42% in clinic-based samples. The method used to diagnose depression did not significantly influence the prevalence estimate, nor did the criteria used for MCI diagnosis.

While the prevalence of depression in patients with MCI was high in both community and clinical samples, there was higher prevalence in the clinical population. Stratification by referral source reconciled a small degree of heterogeneity within samples, but significant heterogeneity remained. This finding is consistent with previous smaller systematic reviews on the topic13,15 and intuitively makes sense. In general, one can speculate that people with depression are more likely to present to clinicians for help compared with nondepressed people, notwithstanding the fact that depression can go diagnosed and untreated. Whether or not there is an interaction or cumulative effect of depression in patients with MCI on rates of presentation for clinical care is speculative at this point and requires further study. Evidence suggests that depression confers a higher rate of progression along the neurodegenerative spectrum from MCI to dementia.5,96,97 The construct mild behavioral impairment8 describes the relationship between neuropsychiatric symptoms and this progression. Depression is a prominent subdomain in the mild behavioral impairment construct (in addition to apathy, impulsivity/aggression, social cognition, and psychosis), reflecting the effect of depression on cognitive and functional outcomes in patients with MCI.8 With this in mind, if depression reflects underlying dementia pathology in some people with MCI, it may be a reflection of underlying dementia burden and increase the likelihood of people being in clinical care as opposed to having MCI in the community without clinical support. Again, further studies are required to explore this finding.

Second, we found that prevalence based on informant-rated scales was not significantly different from self-reported prevalence or prevalence based on clinician-administered scales, with significant heterogeneity between strata. A previous systematic review and meta-analysis98 of depression in patients with epilepsy, completed by members of this group, determined increased odds of depression in people with epilepsy with substantial heterogeneity between estimates, driven largely by the method of depression diagnosis. However, studies have attempted to determine the best tools for diagnosing depression in people with dementia, but these have generally found poor correlation between rating scales,99 low sensitivity,100 or decreased scale performance with greater cognitive impairment,101,102 in part because of several misfit items in people who are cognitively impaired.103 Thus, our findings are more consistent with dementia than epilepsy. Mild cognitive impairment is a heterogeneous syndrome, diagnosed based primarily on cognitive testing without clear exploration of underlying etiology. For example, cognitive impairment due to anticholinergic medication burden, cerebrovascular disease, or preclinical dementia (eg, Alzheimer disease, Lewy body dementia, or frontotemporal dementia) can all fall under the MCI umbrella but represent a great heterogeneity of etiologies, which may manifest in different proportions in different patient samples. Mild cognitive impairment itself can be divided into amnestic and nonamnestic and single-domain and multi domain subtypes, which may reflect different etiologies or pathophysiologies.40 In people with MCI, there may be heterogeneity in underlying depression etiology (ie, idiopathic depressive symptoms vs depression secondary to neurodegenerative/vascular burden vs depression as a response to cognitive decline).3

Nonetheless, despite within-sample heterogeneity, prevalence estimates were remarkably similar irrespective of method of diagnosis. This speaks to the challenges in a defining depressive syndrome and determining if the classic definition of depression is different in neurology patients as well as between different neurological illnesses (ie, epilepsy vs MCI vs dementia). While stratification of depression ascertainment methods did not reconcile heterogeneity in prevalence estimates, this does not mean that all depression screening and diagnostic instruments are equal. Until there are methodological guidelines and consensus on the best tool to screen for depression and diagnose MCI, these are the most comprehensive available data. Age may contribute to diagnostic challenges in older adults because of phase-of-life issues, comorbid illness burden, loss of friends and social isolation, and pain and other somatic symptoms making diagnosis more challenging.104,105 However, in our analysis, study mean age was not significantly associated with the prevalence of depression in those with MCI. It is possible that the cognitive impairment itself affects the performance of the rating scales and their ability to detect depression reliably or that clinicians misattribute other aspects of neurodegenerative disease to depression. It has been shown that in neurodegenerative disease, rating scales that capture agitation and psychosis can have different sensitivities, specificities, and optimum cut points, despite being ostensibly similar.106 It may be similar with depression, and interscale differences may be amplified in this patient population. Further research is warranted, specifically in those with MCI.

The third source of explored heterogeneity was method of MCI diagnosis. Mild cognitive impairment is a predementia syndrome or at-risk state, which is generally defined by cognitive decline but maintenance of function (thus precluding a dementia diagnosis). The diagnosis of MCI has evolved over time, and while there is growing demand for unified MCI diagnostic criteria, there is no clear consensus.107,108 The commonly used criteria in research have included the Petersen or Mayo criteria,37,38 CIND,39 and Winblad or International Working Group criteria,40 which adhere to the aforementioned definition.

One of the major areas of inconsistency in MCI diagnosis has been in the measurement of cognitive impairment, with differences from normed scores of both 1 SD and 1.5 SD deemed acceptable.41 For this study, we used more stringent criteria of cognitive impairment 1.5 SD below the norms and also excluded any studies that diagnosed MCI solely based on Mini–Mental State Examination, given the biases of language, education, and culture on Mini–Mental State Examination scores.109 Thus, our sample is slightly more homogenous but may be skewed to the more cognitively impaired individuals. Early iterations of MCI criteria focused on amnestic deficits, but subsequent MCI criteria (eg, Winblad/International Working Group40) also include a search for nonamnestic deficits as important and relevant. When stratified by amnestic vs nonamnestic MCI, there was no difference in depression prevalence, again suggesting that MCI criteria are more similar than different when it comes to depressive symptoms. Developed in advance of the MCI construct, the CDR is a severity scale used in dementia research and ranges from no dementia (CDR = 0) to increasing stages of dementia (CDR = 1-3).42 A CDR score of 0.5 has been considered to be a functional equivalent of MCI in clinical trials. A sample of individuals with a CDR score of 0.5 may include not only people with MCI but also people with very early Alzheimer disease, and in fact a CDR of 0.5 was defined as “questionable dementia.”38 While a global CDR of 0.5 per se is not the best criterion for a diagnosis of MCI, in clinical practice (and for a number of research studies), the CDR score is often used to at least support if not make a diagnosis of MCI. We felt it was important to examine its potential effect on our results. However, in our sample, the prevalence of depression was not significantly different in CDR-diagnosed MCI vs cognitive criteria alone, suggesting CDR may capture a comparable population with other MCI criteria. In sum, despite differences in operationalizing MCI in the context of the studies cited, estimates did not differ significantly based on MCI criteria.

Limitations

There are a number of strengths of this study but also some limitations. First, to our knowledge, this is the largest systematic review and meta-analysis of depression in people with MCI. Results included 57 studies (28 from community samples and 29 from clinical samples), representing 20 892 participants from 22 countries and 6 continents. Although based on only 2 studies, the prevalence of depression in people with MCI was lower in Australian studies compared with 22 from Europe and 23 from North America. The significance of this finding is unknown, and further studies are required in all the remaining continents. Second, the study methods have been successfully used by this team before and have proven to be rigorous.98 These methods included duplicate reviews at every stage, including abstract and full-text reviews as well as study quality assessments. The large number of included studies is a strength of the analysis; however, this is potentially a limitation as well. While the broad spectrum of included studies likely contributed to heterogeneity, the inclusion of only validated rating scales may have mitigated this somewhat. While sex proportions were reported in overall samples, sex-specific prevalence estimates were generally not reported. As this is a study-level meta-analysis, a limitation of the methods is that individual-level characteristics cannot be explored. Future studies could explore this via a pooled or individual-level meta-analysis. Another limitation of the study is the inclusion of English-language studies only, as we may have missed some studies. However, given the large number of included studies, we would not expect missed studies to significantly affect the findings.

Conclusions

Depression is common in people with MCI, with an overall pooled prevalence of 32%. A contributor to heterogeneity in the reported literature regarding the prevalence of depression in those with MCI is the source of the sample, with greater depression burden prevalent in clinical samples compared with community samples. Other sources of heterogeneity have been explored, but more research on depression in people with MCI is required.

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Article Information

Corresponding Author: Zahinoor Ismail, MD, FRCPC, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, Canada T2N 4Z6 (zahinoor@gmail.com).

Accepted for Publication: September 27, 2016.

Published Online: November 23, 2016. doi:10.1001/jamapsychiatry.2016.3162

Author Contributions: Drs Ismail and Fiest have full access to the study data and take responsibility for data integrity and accuracy of the data analysis.

Concept and design: Ismail, Patten, Fiest.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Ismail, Elbayoumi, Hogan, Patten, Fiest.

Critical revision of the manuscript for important intellectual content: Fischer, Hogan, Millikin, Schweizer, Mortby, Smith, Patten, Fiest.

Statistical analysis: Elbayoumi, Patten, Fiest.

Obtained funding: Ismail.

Administrative, technical, or material support: Elbayoumi, Schweizer.

Conflict of Interest Disclosures: Dr Ismail is supported by the Alzheimer Society of Calgary via the Hotchkiss Brain Institute. Dr Patten was a co-applicant on a research grant funded by a joint Hotchkiss Brain Institute/Pfizer Canada funding competition. He receives salary support from Alberta Innovates and Health Solutions and has received operating funds from the Canadian Institutes of Health Research and the Hotchkiss Brain Institute. Dr Mortby is supported by dementia research development fellowship grant 1102028 from the Australian National Health and Medical Research Council Australian Research Council. Dr Smith is funded by the Canadian Institutes of Health Research. Dr Fiest is supported by the O’Brien Institute of Public Health and the Department of Critical Care Medicine at the Cumming School of Medicine, University of Calgary. No other disclosures were reported.

Funding/Support: This study was funded by the University of Calgary Department of Psychiatry, the Katthy Taylor Chair in Vascular Dementia, and the Alzheimer Society of Calgary via the Hotchkiss Brain Institute.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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