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. 2018 Jul 16;13(7):e0200525.
doi: 10.1371/journal.pone.0200525. eCollection 2018.

Cognitive Ability, Education and Socioeconomic Status in Childhood and Risk of Post-Stroke Depression in Later Life: A Systematic Review and Meta-Analysis

Free PMC article

Cognitive Ability, Education and Socioeconomic Status in Childhood and Risk of Post-Stroke Depression in Later Life: A Systematic Review and Meta-Analysis

Ellen V Backhouse et al. PLoS One. .
Free PMC article


Background: Depression after stroke is common and is associated with poorer recovery. Risk factors such as gender, age and stroke severity are established, but it is unclear whether factors from earlier in life might also contribute.

Methods: We searched MEDLINE, PsycINFO, EMBASE and meta-analysed all available evidence on childhood (premorbid) IQ, socioeconomic status (SES), education and stroke in adulthood. We included all studies reporting data on >50 patients, calculating overall odds ratios (OR), mean difference, correlation, 95% confidence intervals (CI) and 95% predictive intervals (PI) using random effects methods. We quality assessed all studies, performed sensitivity analyses, assessed heterogeneity and publication bias.

Results: We identified 33 studies including 2,664 participants with post-stroke depression and 5,460 without (314 participants not classified). Low education (< = 8 years) was associated with post-stroke depression in studies which defined depression as score of mild and above on a depression rating scale (OR 1.47 95% CI 1.10-1.97, p<0.01) but not in studies where depression was defined as severe depressive symptoms or a clinical diagnosis of major depression (OR 1.04 95% CI 0.90-1.31, p = 0.60). Low education was not associated with an increased risk for post-stroke depression in studies that adjusted for age and sex (OR 0.86 95% CI 0.50-1.48 p = 0.58). Those with post-stroke depression had fewer years of education than those without post-stroke depression (MD 0.68 95% CI 0.05-1.31 p = 0.04). Few studies adjusted for vascular risk factors or stroke severity. Heterogeneity between studies was moderate and was partly explained by severity of depression. In the one study identified premorbid IQ did not differ between those with post-stroke depression (mean IQ 10.1.8 SD 9.8) vs those without (mean IQ 104 SD 10.1). There were no studies that examined childhood socioeconomic status and risk of post-stroke depression.

Conclusions: Having less education is associated with an increased risk of post-stroke depressive symptoms but with large confidence intervals and heterogeneity. Future studies should explore the relationship between early and late life risk factors to improve risk identification and to target prevention and treatment strategies.

Conflict of interest statement

E Backhouse and CAM have no conflicts of interest. V Cvoro reports grants from NHS Research Scotland which funded the study. S Shenkin reports no conflicts of interest relevant to the manuscript. J Wardlaw reports grants from Chest Heart and Stroke Scotland, grants from the European Union Horizon 2020 project No 666881, 'SVDs@target' and the Fondation Leducq. This does not alter our adherence to PLOS ONE policies on sharing data and materials.


Fig 1
Fig 1. PRISMA flow chart of search process.
Fig 2
Fig 2. Forest plot comparing low vs high education and risk of depressive symptoms following stroke.
OR<1: low education decreases risk post-stroke depression; OR>1 low education increases risk of post-stroke depression. Random effects model.
Fig 3
Fig 3. Sensitivity analysis comparing studies with depression defined as mild symptoms and above vs clinical depression or severe depressive symptoms only.
Fig 4
Fig 4. Sensitivity analysis comparing studies adjusted for age and sex vs unadjusted studies.
Fig 5
Fig 5. Mean years of education for those with and without post-stroke depression.
Random effects model for the mean difference. Negative mean difference = lower education decreases risk of post-stroke depression and positive mean difference = higher education decreases risk of post-stroke depression.
Fig 6
Fig 6. Forest plot showing correlation between education and depressive symptoms in stroke patients.
Negative correlation = low education increases depressive symptoms; Positive correlation = low education decreases depressive symptoms. DS = depressive symptoms. * adjusted for sex, income, smoking, age, cognitive dysfunction and activities of daily living. DS = depressive symptoms.

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