The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
The global prevalence of major depressive disorder (MDD) among the elderly: A systematic review and meta-analysis
Open accessAbstract
BACKGROUND Major depressive disorder is characterized by a depressed mood or feeling of sadness, loss of interest or pleasure in everyday activities. Depressed individuals have a cognitive impairment, low self-esteem, difficulty making decisions, feeling helpless and hopeless. The factors that have been associated with depression include the lack of social support, living in rural areas, suffering from chronic diseases, smoking, and alcohol abuse. This study aimed to investigate the global prevalence of major depressive disorder in the elderly. METHOD The electronic database such as Web of Science (WoS), Scopus, SID, PubMed, Google Scholar, Mag Iran, and IranDoc were systematically searched for studies reporting the prevalence of major depressive disorderin the elderly published up to March 2021. Meta-analysis was performed using Comprehensive Meta-Analysis (CMA) software. Heterogeneity between the studies was evaluated using the I2 index. Begg and Mazumdar rank correlation test was used to assess publication bias. RESULT A total of 20 studies involving 18953 participants were included in this study. The global prevalence of major depression in the elderly was 13.3 % (95 % CI: 8.4-20.3 %). In the subgroup analysis, the prevalence of major depression in elderly women was 11.9 % (95 % CI: 7.6-18.6) and men 9.7 % (95 % CI: 5.2-17.3). No comparison was made between the two sexes, but based on the confidence intervals and large overlap, the two groups are not statistically different. Among continents, Australia had the highest prevalence of major depression in the elderly at 20.1 % (CI: 14.5-27.2 %). This was followed by Europe at 12.9 % (95 % CI: 5.1-28.9 %). CONCLUSION Major depressive disorder has a growing trend in the elderly population of the world. The prevalence of major depression in the elderly depends on various clinical and demographic factors such as age and gender. Therefore, mental health and the quality of life (QoL) of the elderly are important. The present study emphasizes the importance of social support in mental health that can reduce depression in the elderly.
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PRISMA-P Group, Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015) · Systematic Reviews · doi:10.1186/2046-4053-4-1 · Cited by 26,223
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2014) · International Journal of Surgery · doi:10.1016/j.ijsu.2014.07.013 · Cited by 9,909
Alexopoulos, G. S. (2005) · The Lancet · doi:10.1016/s0140-6736(05)66665-2 · Cited by 2,024
Why is depression more common among women than among men?
Kuehner, C. (2017) · The Lancet Psychiatry · doi:10.1016/s2215-0366(16)30263-2 · Cited by 1,752
Luppa, M., Sikorski, C., Luck, T., Ehreke, L., Konnopka, A., Wiese, B., Weyerer, S., König, H.-H., & Riedel-Heller, S. G. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2010.11.033 · Cited by 855
Depression as a disease of modernity: explanations for increasing prevalence
Hidaka, B. H. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.12.036 · Cited by 769
Depression and cardiovascular disease in elderly: Current understanding
Zhang, Y., Chen, Y., & Ma, L. (2018) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2017.09.022 · Cited by 490
Gender differences in depression and anxiety: The role of age
Faravelli, C., Alessandra Scarpato, M., Castellini, G., & Lo Sauro, C. (2013) · Psychiatry Research · doi:10.1016/j.psychres.2013.09.027 · Cited by 359
Gender, mental health and ageing
Kiely, K. M., Brady, B., & Byles, J. (2019) · Maturitas · doi:10.1016/j.maturitas.2019.09.004 · Cited by 316
Cited by
Prevalence of depression in older adults: A systematic review and meta-analysis
Hu, T., Zhao, X., Wu, M., Li, Z., Luo, L., Yang, C., & Yang, F. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114511 · Cited by 409
Jalali, A., Ziapour, A., Karimi, Z., Rezaei, M., Emami, B., Kalhori, R. P., Khosravi, F., Sameni, J. S., & Kazeminia, M. (2024) · BMC Geriatrics · doi:10.1186/s12877-024-05311-8 · Cited by 171
Salari, N., Heidarian, P., Hassanabadi, M., Babajani, F., Abdoli, N., Aminian, M., & Mohammadi, M. (2024) · Journal of Prevention · doi:10.1007/s10935-024-00789-9 · Cited by 90
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Metadata
- Authors
- Abdoli, N., Salari, N., Darvishi, N., Jafarpour, S., Solaymani, M., Mohammadi, M., & Shohaimi, S.
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 132
- Pages
- 1067-1073
- ISSN
- 0149-7634 (ISSN-L)
- OpenAlex
- W3211143280
- Cited by
- 403
- References
- 46
- FWCI
- 8.85
- Type
- journal article
- Language
- en
- Open access
- green
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- Abdoli, N., Salari, N., Darvishi, N., Jafarpour, S., Solaymani, M., Mohammadi, M., & Shohaimi, S. (2022). The global prevalence of major depressive disorder (MDD) among the elderly: A systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews. https://doi.org/10.1016/j.neubiorev.2021.10.041
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