Risk Factors for Depressive Symptoms in Korean Adult Stroke Survivors: The Korea National Health and Nutrition Examination Survey IV–VII (2007–2018)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Study Variables
2.3. Definition of Stroke Survivors and Depressive Symptoms
2.4. Statistical Analysis
3. Results
3.1. Comparison of Mental Health
3.2. Risk Factors for Depressive Symptoms in Stroke Survivors
3.3. Causes of Activity Limitations
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Angelelli, P.; Paolucci, S.; Bivona, U.; Piccardi, L.; Ciurli, P.; Cantagallo, A.; Antonucci, G.; Fasotti, L.; Di Santantonio, A.; Grasso, M. Development of neuropsychiatric symptoms in poststroke patients: A cross-sectional study. Acta Psychiatr. Scand. 2004, 110, 55–63. [Google Scholar] [CrossRef]
- Hackett, M.L.; Pickles, K. Part I: Frequency of depression after stroke: An updated systematic review and meta-analysis of observational studies. Int. J. Stroke 2014, 9, 1017–1025. [Google Scholar] [CrossRef]
- Villa, R.F.; Ferrari, F.; Moretti, A. Post-stroke depression: Mechanisms and pharmacological treatment. Pharmacol. Ther. 2018, 184, 131–144. [Google Scholar] [CrossRef]
- Guo, J.; Wang, J.; Sun, W.; Liu, X. The advances of post-stroke depression: 2021 update. J. Neurol. 2021, 1–14. [Google Scholar] [CrossRef]
- Gaete, J.M.; Bogousslavsky, J. Post-stroke depression. Expert Rev. Neurother. 2008, 8, 75–92. [Google Scholar] [CrossRef]
- Bartoli, F.; Di Brita, C.; Crocamo, C.; Clerici, M.; Carrà, G. Early post-stroke depression and mortality: Meta-analysis and meta-regression. Front. Psychiatry 2018, 9, 530. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wei, N.; Yong, W.; Li, X.; Zhou, Y.; Deng, M.; Zhu, H.; Jin, H. Post-stroke depression and lesion location: A systematic review. J. Neurol. 2015, 262, 81–90. [Google Scholar] [CrossRef]
- Shi, Y.; Yang, D.; Zeng, Y.; Wu, W. Risk factors for post-stroke depression: A meta-analysis. Front. Aging Neurosci. 2017, 9, 218. [Google Scholar] [CrossRef] [PubMed]
- Alajbegovic, A.; Djelilovic-Vranic, J.; Alajbegovic, S.; Nakicevic, A.; Todorovic, L.; Tiric-Campara, M. Post stroke depression. Med. Arch. 2014, 68, 47. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kutlubaev, M.A.; Hackett, M.L. Part II: Predictors of depression after stroke and impact of depression on stroke outcome: An updated systematic review of observational studies. Int. J. Stroke 2014, 9, 1026–1036. [Google Scholar] [CrossRef]
- Nickel, A.; Thomalla, G. Post-stroke depression: Impact of lesion location and methodological limitations—A topical review. Front. Neurol. 2017, 8, 498. [Google Scholar] [CrossRef] [Green Version]
- Kim, N.Y.; Lee, S.C.; Shin, J.-C.; Park, J.E.; Kim, Y.W. Voxel-based lesion symptom mapping analysis of depressive mood in patients with isolated cerebellar stroke: A pilot study. NeuroImage Clin. 2017, 13, 39–45. [Google Scholar] [CrossRef] [Green Version]
- Sarkar, A.; Sarmah, D.; Datta, A.; Kaur, H.; Jagtap, P.; Raut, S.; Shah, B.; Singh, U.; Baidya, F.; Bohra, M. Post-stroke depression: Chaos to exposition. Brain Res. Bull. 2021, 168, 74–88. [Google Scholar] [CrossRef] [PubMed]
- Kweon, S.; Kim, Y.; Jang, M.-j.; Kim, Y.; Kim, K.; Choi, S.; Chun, C.; Khang, Y.-H.; Oh, K. Data resource profile: The Korea national health and nutrition examination survey (KNHANES). Int. J. Epidemiol. 2014, 43, 69–77. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rabin, R.; de Charro, F. EQ-SD: A measure of health status from the EuroQol Group. Ann. Med. 2001, 33, 337–343. [Google Scholar] [CrossRef] [PubMed]
- Kroenke, K.; Spitzer, R.L.; Williams, J.B. The PHQ-9: Validity of a brief depression severity measure. J. Gen. Intern. Med. 2001, 16, 606–613. [Google Scholar] [CrossRef] [PubMed]
- Levis, B.; Benedetti, A.; Thombs, B.D. Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: Individual participant data meta-analysis. BMJ 2019, 365, l1476. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Williams, L.S.; Brizendine, E.J.; Plue, L.; Bakas, T.; Tu, W.; Hendrie, H.; Kroenke, K. Performance of the PHQ-9 as a screening tool for depression after stroke. Stroke 2005, 36, 635–638. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Paolucci, S.; Gandolfo, C.; Provinciali, L.; Torta, R.; Sommacal, S.; Group), D.S.; Toso, V. Quantification of the risk of poststroke depression: The Italian multicenter observational study DESTRO. Acta Psychiatr. Scand. 2005, 112, 272–278. [Google Scholar] [CrossRef] [PubMed]
- Kim, I.J.; Suh, M.J.; Kim, K.S.; Cho, N.O.; Choi, H.J. Predicting factors of post-stroke depression. Korean J. Adult Nurs. 2000, 12, 147–162. [Google Scholar]
- Kuehner, C. Why is depression more common among women than among men? Lancet Psychiatry 2017, 4, 146–158. [Google Scholar] [CrossRef]
- Taylor-Rowan, M.; Momoh, O.; Ayerbe, L.; Evans, J.J.; Stott, D.J.; Quinn, T.J. Prevalence of pre-stroke depression and its association with post-stroke depression: A systematic review and meta-analysis. Psychol. Med. 2019, 49, 685–696. [Google Scholar] [CrossRef] [PubMed]
- Aström, M.; Adolfsson, R.; Asplund, K. Major depression in stroke patients. A 3-year longitudinal study. Stroke 1993, 24, 976–982. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lee, J. Pathways from education to depression. J. Cross-Cult. Gerontol. 2011, 26, 121–135. [Google Scholar] [CrossRef]
- Assari, S. Social determinants of depression: The intersections of race, gender, and socioeconomic status. Brain Sci. 2017, 7, 156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fuller-Rowell, T.E.; Curtis, D.S.; Doan, S.N.; Coe, C.L. Racial disparities in the health benefits of educational attainment: A study of inflammatory trajectories among African American and white adults. Psychosom. Med. 2015, 77, 33–40. [Google Scholar] [CrossRef]
- Blacksher, E. On being poor and feeling poor: Low socioeconomic status and the moral self. Theor. Med. Bioeth. 2002, 23, 455–470. [Google Scholar] [CrossRef] [PubMed]
- Backhouse, E.V.; McHutchison, C.A.; Cvoro, V.; Shenkin, S.D.; Wardlaw, J.M. Cognitive ability, education and socioeconomic status in childhood and risk of post-stroke depression in later life: A systematic review and meta-analysis. PLoS ONE 2018, 13, e0200525. [Google Scholar] [CrossRef] [Green Version]
- Van Agtmaal, M.J.; Houben, A.J.; Pouwer, F.; Stehouwer, C.D.; Schram, M.T. Association of microvascular dysfunction with late-life depression: A systematic review and meta-analysis. JAMA Psychiatry 2017, 74, 729–739. [Google Scholar] [CrossRef]
- Bandura, A. Self-efficacy: Toward a unifying theory of behavioral change. Psychol. Rev. 1977, 84, 191. [Google Scholar] [CrossRef]
- Gauvin, L.; Spence, J.C. Physical activity and psychological well-being: Knowledge base, current issues, and caveats. Nutr. Rev. 1996, 54, S53. [Google Scholar] [CrossRef]
- Mikkelsen, K.; Stojanovska, L.; Polenakovic, M.; Bosevski, M.; Apostolopoulos, V. Exercise and mental health. Maturitas 2017, 106, 48–56. [Google Scholar] [CrossRef]
- Tendzegolskis, Z.; Viru, A.; Orlova, E. Exercise-induced changes of endorphin contents in hypothalamus, hypophysis, adrenals and blood plasma. Int. J. Sports Med. 1991, 12, 495–497. [Google Scholar] [CrossRef]
- Maletic, V.; Robinson, M.; Oakes, T.; Iyengar, S.; Ball, S.; Russell, J. Neurobiology of depression: An integrated view of key findings. Int. J. Clin. Pract. 2007, 61, 2030–2040. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Meyer, J.H.; Ginovart, N.; Boovariwala, A.; Sagrati, S.; Hussey, D.; Garcia, A.; Young, T.; Praschak-Rieder, N.; Wilson, A.A.; Houle, S. Elevated monoamine oxidase a levels in the brain: An explanation for the monoamine imbalance of major depression. Arch. Gen. Psychiatry 2006, 63, 1209–1216. [Google Scholar] [CrossRef] [Green Version]
- Hood, S.D.; Bell, C.J.; Nutt, D.J. Acute tryptophan depletion. Part I: Rationale and methodology. Aust. N. Z. J. Psychiatry 2005, 39, 558–564. [Google Scholar] [CrossRef]
- Wipfli, B.; Landers, D.; Nagoshi, C.; Ringenbach, S. An examination of serotonin and psychological variables in the relationship between exercise and mental health. Scand. J. Med. Sci. Sports 2011, 21, 474–481. [Google Scholar] [CrossRef] [PubMed]
- Melancon, M.O.; Lorrain, D.; Dionne, I.J. Changes in markers of brain serotonin activity in response to chronic exercise in senior men. Appl. Physiol. Nutr. Metab. 2014, 39, 1250–1256. [Google Scholar] [CrossRef] [PubMed]
- Beneito-Montagut, R.; Cassián-Yde, N.; Begueria, A. What do we know about the relationship between internet-mediated interaction and social isolation and loneliness in later life? Qual. Ageing Older Adults 2018, 19, 14–30. [Google Scholar] [CrossRef] [Green Version]
- Cattan, M.; Newell, C.; Bond, J.; White, M. Alleviating social isolation and loneliness among older people. Int. J. Ment. Health Promot. 2003, 5, 20–30. [Google Scholar] [CrossRef]
- Pettigrew, S.; Donovan, R.; Boldy, D.; Newton, R. Older people’s perceived causes of and strategies for dealing with social isolation. Aging Ment. Health 2014, 18, 914–920. [Google Scholar] [CrossRef] [PubMed]
- Taylor, H.O.; Taylor, R.J.; Nguyen, A.W.; Chatters, L. Social isolation, depression, and psychological distress among older adults. J. Aging Health 2018, 30, 229–246. [Google Scholar] [CrossRef] [PubMed]
Variable | Stroke Survivors (N = 1558) | Non-Stroke (N = 32,433) | p |
---|---|---|---|
Age (years) | 67.5 ± 10.0 | 50.8 ± 16.7 | <0.001 * |
Body mass index (kg/m2) | 24.5 ± 3.3 | 23.9 ± 3.5 | <0.001 * |
Male sex | 808 (51.9%) | 13,840 (42.7%) | <0.001 * |
Hypertension | 1064 (80.0%) | 7451 (23.0%) | <0.001 * |
Diabetes mellitus | 451 (44.2%) | 2886 (8.9%) | <0.001 * |
Hyperlipidemia | 489 (49.4%) | 5234 (16.2%) | <0.001 * |
Education level | <0.001 * | ||
Elementary school graduate and lower | 876 (56.8%) | 6934 (21.5%) | |
Higher than elementary school graduate | 665 (43.2%) | 25,296 (78.5%) | |
Employment status | <0.001 * | ||
Unemployed | 1068 (69.4%) | 12,823 (39.8%) | |
Employed | 470 (30.6%) | 19,428 (60.2%) | |
Marital status | <0.001 * | ||
Unmarried | 37 (2.4%) | 5362 (16.5%) | |
Married | 1520 (97.6%) | 27,069 (83.5%) | |
Family income | <0.001 * | ||
Quartile 1 (lowest) | 725 (47.1%) | 6092 (18.8%) | |
Quartile 2 | 387 (25.2%) | 7999 (24.7%) | |
Quartile 3 | 243 (15.8%) | 8886 (27.5%) | |
Quartile 4 (highest) | 183 (11.9%) | 9343 (28.9%) | |
Activity limitations | 625 (40.4%) | 2617 (8.1%) | <0.001 * |
Depressive symptoms | 404 (26.1%) | 3369 (10.4%) | <0.001 * |
Variable | Stroke Survivors | Non-Stroke | p |
---|---|---|---|
Patient Health Questionnaire-9 | 4.4 (4.0–4.8) | 2.6 (2.5–2.6) | <0.001 * |
Prevalence of major depression † (%) | 16.2 (14.0–18.8) | 5.3 (5.0–5.6) | <0.001 * |
Prevalence of depressive symptoms (%) | 24.7 (23.2–26.3) | 9.3 (9.0–9.6) | <0.001 * |
Prevalence of antidepressant treatment (%) | 3.8 (3.4–4.3) | 1.4 (1.3–1.5) | <0.001 * |
Prevalence of suicidal ideation during the past year (%) | 21.7 (20.5–23.1) | 4.8 (4.4–5.1) | <0.001 * |
Prevalence of a suicide attempt during the past year (%) | 2.5 (2.0–3.2) | 0.6 (0.5–0.6) | <0.001 * |
Variable | Univariate Analysis | Multivariate Analysis | ||
---|---|---|---|---|
OR (95% CI) | p | OR (95% CI) | p | |
Age (per year) | 1.012 (1.004–1.020) | 0.002 * | 0.995 (0.986–1.004) | 0.285 |
Female gender | 1.480 (1.257–1.743) | <0.001 * | 1.381 (1.157–1.649) | <0.001 * |
Body mass index (per kg/m2) | 0.981 (0.957–1.005) | 0.125 | N/A | |
Hypertension | 0.968 (0.750–1.248) | 0.800 | N/A | |
Diabetes mellitus | 1.068 (0.862–1.323) | 0.548 | N/A | |
Hyperlipidemia | 1.151 (0.906–1.463) | 0.248 | N/A | |
Unemployed | 1.869 (1.511–2.312) | <0.001 * | 1.229 (1.012–1.492) | 0.037 * |
Unmarried | 1.283 (0.886–1.858) | 0.187 | N/A | |
Low education level | 1.682 (1.421–1.990) | <0.001 * | 1.338 (1.064–1.683) | 0.013 * |
Family income | <0.001 * | <0.001 * | ||
Quartile 1 (lowest) | Reference | Reference | ||
Quartile 2 | 0.697 (0.583–0.834) | 0.776 (0.636–0.946) | ||
Quartile 3 | 0.473 (0.399–0.561) | 0.601 (0.493–0.732) | ||
Quartile 4 (highest) | 0.500 (0.334–0.746) | 0.812 (0.541–1.219) | ||
Activity limitations | 3.488 (2.975–4.090) | <0.001 * | 3.225 (2.731–3.809) | <0.001 * |
Causes | Number (%) |
---|---|
Stroke | 337 (53.9) |
Musculoskeletal | 256 (41.0) |
Vision | 58 (9.3) |
Hypertension | 53 (8.5) |
Diabetes mellitus | 45 (7.2) |
Aging | 41 (6.6) |
Mental | 37 (5.9) |
Heart | 31 (5.0) |
Oral | 30 (4.8) |
Respiratory | 28 (4.5) |
Hearing | 26 (4.2) |
Dementia | 13 (2.1) |
Others | 43 (6.9) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Hong, M.-W.; Lee, J.-H.; Lee, K.-W.; Kim, S.-B.; Kang, M.-G. Risk Factors for Depressive Symptoms in Korean Adult Stroke Survivors: The Korea National Health and Nutrition Examination Survey IV–VII (2007–2018). Int. J. Environ. Res. Public Health 2021, 18, 8178. https://doi.org/10.3390/ijerph18158178
Hong M-W, Lee J-H, Lee K-W, Kim S-B, Kang M-G. Risk Factors for Depressive Symptoms in Korean Adult Stroke Survivors: The Korea National Health and Nutrition Examination Survey IV–VII (2007–2018). International Journal of Environmental Research and Public Health. 2021; 18(15):8178. https://doi.org/10.3390/ijerph18158178
Chicago/Turabian StyleHong, Min-Woo, Jong-Hwa Lee, Kyeong-Woo Lee, Sang-Beom Kim, and Min-Gu Kang. 2021. "Risk Factors for Depressive Symptoms in Korean Adult Stroke Survivors: The Korea National Health and Nutrition Examination Survey IV–VII (2007–2018)" International Journal of Environmental Research and Public Health 18, no. 15: 8178. https://doi.org/10.3390/ijerph18158178
APA StyleHong, M.-W., Lee, J.-H., Lee, K.-W., Kim, S.-B., & Kang, M.-G. (2021). Risk Factors for Depressive Symptoms in Korean Adult Stroke Survivors: The Korea National Health and Nutrition Examination Survey IV–VII (2007–2018). International Journal of Environmental Research and Public Health, 18(15), 8178. https://doi.org/10.3390/ijerph18158178