| Literature DB >> 35058530 |
Sana Sadat Sajjadi1, Sahar Foshati2, Sajjad Haddadian-Khouzani1, Mohammad Hossein Rouhani3.
Abstract
The results of human studies are inconsistent regarding selenium and depressive disorders. Therefore, we aimed to conduct a systematic review and meta-analysis of observational and interventional studies and provided an overview of the role of selenium in depression. Three databases including Medline, Scopus, and Web of Science were searched on June 30, 2020 and updated on April 12, 2021. Also, we searched in electronical databases of WHO Global Index Medicus and ClinicalTrials.gov. No time or language restrictions were used for the search. A random effects model was used to pool effect sizes. In total, 20 studies were included in the systematic review, and 15 studies were included in the meta-analysis. There were no significant differences in serum selenium levels between patients with depression and healthy subjects (WMD: 2.12 mg/L; 95% CI: - 0.11, 4.36; I2 = 98.0%, P < 0.001). Also, no significant correlation was found between serum levels of selenium and depression scores (r: - 0.12; 95% CI: - 0.33, 0.08; I2 = 73.5%, P = 0.010). Nevertheless, there was a significant negative association between high selenium intake and the risk of postpartum depression (OR: 0.97; 95% CI: 0.95, 0.99; I2 = 0.0%, P = 0.507). In addition, selenium supplementation significantly reduced depressive symptoms (WMD: - 0.37; 95% CI: - 0.56, - 0.18; I2 = 0.0%, P = 0.959). Taken these results together, selenium seems to have a protective role against postpartum depression and can be considered as a beneficial adjuvant therapy in patients with depression. Further studies are necessary to draw definitive conclusions.Entities:
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Year: 2022 PMID: 35058530 PMCID: PMC8776795 DOI: 10.1038/s41598-022-05078-1
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Flow diagram of the study selection process.
Overview of the studies included in the systematic review.
| First author (year) | Country | Sample size (male/female) | Age (mean ± SD, median (IQR), year) | Design | Reported data | Type of depression | Depression assessment tool | Results | Adjusted variables |
|---|---|---|---|---|---|---|---|---|---|
| Amini (2019) | Iran | 163 (0/163) | 27.79 ± 6.1 | Case–control | Risk of depression, Mean of dietary selenium | PPD | EPDS | A more selenium intake was associated with an reduced risk of depression | Energy intake and BMI |
| Banikazemi (2016) | Iran | 7172 (2725/4447) | 48.55 ± 7.4 | Cross-sectional | Risk of depression | NR | BDI | Selenium intake was negatively associated with the relative risk of a high depression score | Energy intake |
| Conner (2015) | New Zealand | 978 (357/621) | 19.6 ± 1.6 | Cross-sectional | Mean of depression score | NR | CESD | A negative association between serum selenium and risk of depression | Age, gender, ethnicity, BMI, and mean weekly alcohol intake |
| Ekramzadeh (2015) | Iran | 150 (17/133) | 47.23 ± 13.6 | Cross-sectional | Correlation between serum selenium and depression score, Mean of serum selenium | NR | BDI | No significant association between depression score and serum selenium | Age, sex, marriage, job, and education level |
| Ghimire (2019) | US | 7725 (3723/4002) | 46.4 (32.5–59.7) | Cross-sectional | Risk of depression (serum and dietary) | NR | PHQ-9 | An inverse association between dietary selenium and depression, No significant association between serum selenium and depression | Age, sex, race, ethnicity, marital status, educational status, family poverty income ratio, BMI, smoking, alcohol use, physical activity, use of dietary supplements, diabetes, kidney disease, cancer, heart disease, and energy intake |
| Gosney (2008) | UK | 59 (NR) | 82 (NR) | Randomized controlled trial | Correlation between serum selenium and depression score, Effect of selenium supplementation on depression score | NR | MADRS | A significant negative relationship between serum selenium and depression, Significant reduction in depression score in active group | NR |
| Ibarra (2015) | Spain | 77 (18/59) | 50.46 ± 11.6 | Randomized controlled trial | Correlation between serum selenium and depression score | MDD | HDRS-17 BDI | Active group had a better outcome of depressive symptoms, An inverse association between serum selenium and depression | NR |
| Islam (2018) | Bangladesh | 495 (192/303) | 33.29 ± 0.6 | Case–control | Mean of serum selenium in healthy and depressed subjects | MDD | SCID-5 | MDD patients had lower levels of selenium | NR |
| Jin (2020) | New Zealand | 87 (0/87) | 31.5 ± 4.2 | Cohort | Median of serum selenium | PPD | EPDS | No significant association between plasma selenium values and prevalence of depression | NR |
| Leung (2013) | Canada | 475 (0/475) | 31.4 | Cohort | Risk of depression | PPD | EPDS | Supplementary selenium intake was negatively associated with the risk of depression | NR |
| Li (2018) | US | 14,834 (7399/ 7435) | 24.99 | Cross-sectional | Risk of depression | NR | PHQ-9 | Total selenium intake was negatively associated with depression | BMI, race, educational level, smoking status, family income, work activity, recreational activity, hypertension, diabetes, energy intake, age, and gender |
| Mokhber (2011) | Iran | 85 (0/85) | 21.61 ± 2.9 | Randomized controlled trial | Effect of selenium supplementation on depression score | PPD | EPDS | Selenium group had lower mean EPDS score | NR |
| Pasco (2012) | Australia | 316 (0/316) | 54.5 | Nested case–control | Risk of depression | MDD | SCID-I | A low selenium intake was associated with an increased risk of de novo MDD | Age, socioeconomic status, smoking, alcohol use, and physical activity |
| Perez-Cornago (2015) | Spain | 84 (47/37) | 49.4 ± 2.7 | Cross-sectional | Mean of dietary selenium | NR | BDI | Intake of more selenium was associated with better mood | Sex, age, and energy intake |
| Samad (2019) | Pakistan | 96 (13/83) | 50 | Case–control | Mean of serum selenium in healthy and depressed subjects | NR | HDRS-17 | Depression was associated with selenium deficiency | NR |
| Sánchez‑Villegas (2018) | Spain | 13,983 (5880/8103) | 38.2 ± 11.9 | Cohort | Risk of depression | NR | SCID-I | Inadequate selenium intake was related to increased risk of depression | Sex, age, physical activity, energy intake, alcohol intake, BMI, special diets, smoking, and prevalence of diseases such as cardiovascular disease, hypertension, and type 2 diabetes |
| Shor-Posner (2003) | Miami | 63 (32/31) | 40.0 ± 6.4 | Randomized controlled trial | Effect of selenium supplementation on depression score | NR | BDI | No significant change in the prevalence of depression | NR |
| Singh (2017) | Columbia | 108 (0/108) | 18.0 ± 1.2 | Cross-sectional | Correlation between selenium intake and depression score | Pregnant depression | RADS | No significant association between selenium intake and depressive symptoms | Energy intake |
| Wieder-Huszla (2020) | Poland | 102 (0/102) | 56.69 ± 6.0 | Cross-sectional | Correlation between serum selenium and depression score | Postmenopausal depression | BDI | No significant association between depression score and serum selenium | NR |
| Tatt (2019) | Malaysia | 112 (56/56) | 71.4 ± 7.0 | Cross-sectional | Correlation between selenium intake and depression score | NR | GDS-15 | No significant association between GDS score and selenium intake, but a negative association between selenium intake and GDS score in males | NR |
NR: Not reported, BMI: Body mass index, MDD: Major depressive disorder, PPD: Postpartum depression, EPDS: Edinburgh Postnatal Depression Scale, CESD: Center for Epidemiological Studies–Depression, BDI: Beck Depression Inventory, MADRS: Montgomery-Asberg Depression Rating Scale, HDRS-17: 17-item Hamilton Depression Rating Scale, PHQ-9: 9-item Patient Health Questionnaire, SCID-5: Structured Clinical Interview for DSM-5, SCID-I: Structured Clinical Interview for DSM-IV Axis I Disorders, RADS: Reynolds Adolescent Depression Scale. GDS-15:15-items Chinese Geriatric Depression Scale.
Quality assessment of the included randomized controlled trials according to the Cochrane Collaboration Risk of Bias Tool.
| First author (year) | Random sequence generation (selection bias) | Allocation concealment (selection bias) | Blinding of participants and personnel (performance bias) | Blinding of outcome assessment (detection bias) | Incomplete outcome data (attrition bias) | Selective reporting (reporting bias) | Other sources of bias | Score |
|---|---|---|---|---|---|---|---|---|
| Shor-Posner (2003) | + | + | + | + | + | + | + | High |
| Mokhber (2011) | + | + | + | + | – | + | + | High |
| Ibarra (2015) | + | + | ? | ? | + | + | + | High |
| Gosney (2008) | + | + | + | + | + | + | + | High |
Symbols: +, low risk of bias; ?, unclear risk of bias; –, high risk of bias.
Quality assessment of the included case–control studies according to the Newcastle–Ottawa Scale.
| First author (year) | Adequate definition of cases | Representativeness of cases | Selection of controls | Definition of controls | Control for important factors or additional factors | Exposure assessment | Same method of ascertainment for cases and controls | Non-response rate | Total quality score |
|---|---|---|---|---|---|---|---|---|---|
| Amini (2019) | – | – | – | – | * | – | * | * | 3 |
| Islam (2018) | – | – | * | * | – | * | * | – | 4 |
| Pasco (2012) | – | – | – | * | ** | – | * | – | 4 |
| Samad (2019) | – | – | – | – | – | * | – | – | 1 |
Quality assessment of the included cohort studies according to the Newcastle–Ottawa Scale.
| First author (year) | Representativeness of the exposed cohort | Selection of the non-exposed cohort | Ascertainment of exposure | Outcome not present at start of study | Comparability of cohorts | Assessment of outcome | Follow-up long enough for outcomes to occur | Adequacy of follow-up of cohorts | Total quality score |
|---|---|---|---|---|---|---|---|---|---|
| Jin (2020) | – | * | * | – | – | – | – | – | 2 |
| Leung (2013) | – | * | – | – | – | – | – | – | 1 |
| Sánchez‑Villegas (2018) | – | * | – | * | * | – | * | – | 4 |
Quality assessment of the included cross-sectional studies according to the Newcastle–Ottawa Scale.
| First author (year) | Representativeness of the sample | Sample size | Non-respondents | Ascertainment of the exposure | Comparability of outcome groups | Assessment of outcome | Statistical test | Total score |
|---|---|---|---|---|---|---|---|---|
| Banikazemi (2016) | – | – | – | – | – | * | – | 1 |
| Conner (2015) | – | – | – | * | * | * | * | 4 |
| Ekramzadeh (2015) | – | – | – | * | – | * | * | 3 |
| Ghimire (2019) | * | – | – | * | ** | * | * | 6 |
| Li (2018) | * | * | – | * | ** | * | * | 7 |
| Perez-Cornago (2015) | – | – | – | * | – | * | * | 3 |
| Singh (2017) | – | – | * | * | – | * | * | 4 |
| Wieder-Huszla (2020) | – | – | – | * | – | * | * | 3 |
| Tatt (2019) | * | – | * | * | – | * | * | 5 |
Figure 2Forest plot of the correlation between serum selenium levels and depression scores.
Figure 3Forest plot of the comparison of serum selenium levels between depressive patients and healthy controls.
Figure 4Forest plot of the association between selenium intake and the risk ratio of depression stratified by the type of depression.
Figure 5Forest plot of the effect of selenium supplementation on depression scores.