Volume 21, Issue 2 (6-2024)
J Res Dev Nurs Midw 2024, 21(2): 40-42 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Rostami Z, Rahmati M, Rostamnia L, salari N. Mild cognitive impairment and its determinants in urban and rural areas among older adults:
A Cross-Sectional Study. J Res Dev Nurs Midw 2024; 21 (2) :40-42
URL: http://nmj.goums.ac.ir/article-1-1677-en.html
URL: http://nmj.goums.ac.ir/article-1-1677-en.html
1- International Student Research Committee, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
2- Department of Geriatric and Psychiatric Nursing, School of Nursing and Midwifery, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
3- Department of Nursing, School of Nursing and Midwifery, Kermanshah University of Medical Sciences, Kermanshah, Iran ,l.rostamniya@gmail.com
4- Department of Biostatistics, Faculty of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
2- Department of Geriatric and Psychiatric Nursing, School of Nursing and Midwifery, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
3- Department of Nursing, School of Nursing and Midwifery, Kermanshah University of Medical Sciences, Kermanshah, Iran ,
4- Department of Biostatistics, Faculty of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
Abstract: (467 Views)
Background: Mild Cognitive Impairment (MCI) is a transitional stage between normal cognitive aging and dementia, often marked by noticeable cognitive decline without significant interference in daily activities. This study aimed to investigate the prevalence and determinants of MCI among older adults in urban and rural areas of Kermanshah City.
Methods: A cross-sectional study was conducted involving 506 older adults recruited from urban and rural areas using a cluster random sampling method. The participants completed assessments of cognitive function, social relationships, stress management, and socio-demographic factors. Logistic regression analyses and the Kruskal-Wallis and Mann-Whitney U tests were performed to examine the associations between these factors and MCI using SPSS version 25.
Results: The prevalence of MCI was 21.9% overall, with a higher prevalence in rural areas. In both areas, social relationships (urban: p = 0.001; rural: p = 0.04) and age (urban: p = 0.001; rural: p = 0.013) were significantly associated with MCI. In the rural elderly, education (p = 0.02) and economic situation (p = 0.012) were significant predictors, while in urban areas, gender (p = 0.002) and stress management (p = 0.001) were key determinants.
Conclusion: This study highlights the importance of considering psychosocial factors, such as social relationships and stress management, in understanding cognitive health among older adults. Targeted interventions are needed to address the higher prevalence of MCI in rural areas. Further research should explore strategies to improve cognitive health in aging rural and urban populations.
Methods: A cross-sectional study was conducted involving 506 older adults recruited from urban and rural areas using a cluster random sampling method. The participants completed assessments of cognitive function, social relationships, stress management, and socio-demographic factors. Logistic regression analyses and the Kruskal-Wallis and Mann-Whitney U tests were performed to examine the associations between these factors and MCI using SPSS version 25.
Results: The prevalence of MCI was 21.9% overall, with a higher prevalence in rural areas. In both areas, social relationships (urban: p = 0.001; rural: p = 0.04) and age (urban: p = 0.001; rural: p = 0.013) were significantly associated with MCI. In the rural elderly, education (p = 0.02) and economic situation (p = 0.012) were significant predictors, while in urban areas, gender (p = 0.002) and stress management (p = 0.001) were key determinants.
Conclusion: This study highlights the importance of considering psychosocial factors, such as social relationships and stress management, in understanding cognitive health among older adults. Targeted interventions are needed to address the higher prevalence of MCI in rural areas. Further research should explore strategies to improve cognitive health in aging rural and urban populations.
perspective: Original Article |
Subject:
Psychology and Psychiatry
References
1. Economic U. Social Affairs PD. World Population Ageing 2020 Highlights: Living arrangements of older persons. United Nations: ST/ESA/SERA/451; 2020. [View at Publisher]
2. Fathi E. The phenomenon of population aging in Iran. Iranian Journal of Official Statistics Studies (IJOSS). 2020;30(2):387-413. [View at Publisher] [DOI] [Google Scholar]
3. Martin E, Velayudhan L. Neuropsychiatric symptoms in mild cognitive impairment: a literature review. Dement Geriatr Cogn Disord. 2020;49(2):146-55. [View at Publisher] [DOI] [PMID] [Google Scholar]
4. Lee J, Sung J, Choi M. The factors associated with subjective cognitive decline and cognitive function among older adults. J Adv Nurs. 2020;76(2):555-65. [View at Publisher] [DOI] [PMID] [Google Scholar]
5. Peng C, Burr JA, Han SH. Cognitive function and cognitive decline among older rural Chinese adults: the roles of social support, pension benefits, and medical insurance. Aging Ment Health. 2023;27(4):771-9. [View at Publisher] [DOI] [PMID] [Google Scholar]
6. Huang X, Tan ZM, Tan CS, Ng YL, van Dam RM, Hilal S. Association between nutrition and cognition in a multi-ethnic cohort from Singapore. Eur J Nutr. 2023;62(6):2387-97. [View at Publisher] [DOI] [PMID] [Google Scholar]
7. Tham R, Wheeler AJ, Carver A, Dunstan D, Donaire-Gonzalez D, Anstey KJ, et al. Associations between traffic-related air pollution and cognitive function in Australian urban settings: the moderating role of diabetes status. Toxics. 2022;10(6):289. [View at Publisher] [DOI] [PMID] [Google Scholar]
8. Bae S, Lee S, Harada K, Makino K, Chiba I, Katayama O, et al. Engagement in lifestyle activities is associated with increased Alzheimer's disease-associated cortical thickness and cognitive performance in older adults. J Clin Med. 2020;9(5):1424. [View at Publisher] [DOI] [PMID] [Google Scholar]
9. Jia X, Wang Z, Huang F, Su C, Du W, Jiang H, et al. A comparison of the Mini-Mental State Examination (MMSE) with the Montreal Cognitive Assessment (MoCA) for mild cognitive impairment screening in Chinese middle-aged and older population: a cross-sectional study. BMC psychiatry. 2021;21(1):485. [View at Publisher] [DOI] [PMID] [Google Scholar]
10. Seyediyan M, Fallah M, Noroziyan M, Nejat S, Delavar A, Ghasemzadeh G. Validation of the Persian version of the brief short test of mental status. J Med Counc Iran. 2008;25(4):408-14. [View at Publisher] [Google Scholar]
11. Eshaghi SR, Farajzadegan Z, Babak A. Healthy lifestyle assessment questionnaire in elderly: translation, reliability and validity. Payesh. 2010;9(1):91-9. [View at paplisher] [DOI] [Google Scholar]
12. Ishikawa KM, Davis J, Chen JJ, Lim E. The prevalence of mild cognitive impairment by aspects of social isolation. PLoS One. 2022;17(6):e0269795. [View at paplisher] [DOI] [PMID] [Google Scholar]
13. Manly JJ, Jones RN, Langa KM, Ryan LH, Levine DA, McCammon R, et al. Estimating the prevalence of dementia and mild cognitive impairment in the US: the 2016 health and retirement study harmonized cognitive assessment protocol project. JAMA Neurol. 2022;79(12):1242-9. [View at paplisher] [DOI] [PMID] [Google Scholar]
14. Reilly M. Health Disparities and Access to Healthcare in Rural vs. Urban Areas. Theory in Action. 2021;14(2):6. [View at paplisher] [DOI] [Google Scholar]
15. Sharifi S, Khorzoughi KB, Khaledi-Paveh B, Rahmati M. Association of intergenerational relationship and supports with cognitive performance in older adults: A systematic review. Geriatr Nurs. 2023;52:146-51. [View at paplisher] [DOI] [PMID] [Google Scholar]
16. Kuiper JS, Zuidersma M, Zuidema SU, Burgerhof JG, Stolk RP, Oude Voshaar RC, et al. Social relationships and cognitive decline: a systematic review and meta-analysis of longitudinal cohort studies. Int J Epidemiol. 2016;45(4):1169-206. [View at paplisher] [DOI] [PMID] [Google Scholar]
17. Meister LM, Zahodne LB. Associations between social network components and cognitive domains in older adults. Psychol Aging. 2022;37(5):591-603. [View at paplisher] [DOI] [PMID] [Google Scholar]
18. Schmitz W, Mauritz S, Wagner M. Social relationships, living arrangements and loneliness. Z Gerontol Geriatr. 2021;54(Suppl 2):120-5. [View at paplisher] [DOI] [PMID] [Google Scholar]
19. Luchetti M, Terracciano A, Aschwanden D, Lee JH, Stephan Y, Sutin AR. Loneliness is associated with risk of cognitive impairment in the Survey of Health, Ageing and Retirement in Europe. Int J Geriatr Psychiatry. 2020;35(7):794-801. [View at paplisher] [DOI] [PMID] [Google Scholar]
20. Conrad CD, Bimonte-Nelson HA. Impact of the hypothalamic-pituitary-adrenal/gonadal axes on trajectory of age-related cognitive decline. Prog Brain Res. 2010;182:31-76. [View at paplisher] [DOI] [PMID] [Google Scholar]
21. Law R, Clow A. Stress, the cortisol awakening response and cognitive function. Int Rev Neurobiol. 2020;150:187-217. [View at paplisher] [DOI] [PMID] [Google Scholar]
22. Mac Giollabhui N, Hartman CA. Examining inflammation, health, stress and lifestyle variables linking low socioeconomic status with poorer cognitive functioning during adolescence. Brain Behav Immun. 2022;104:1-5. [View at paplisher] [DOI] [PMID] [Google Scholar]
23. Gargano A, Olabiyi BF, Palmisano M, Zimmer A, Bilkei-Gorzo A. Possible role of locus coeruleus neuronal loss in age-related memory and attention deficits. Front Neurosci. 2023;17:1264253. [View at paplisher] [DOI] [PMID] [Google Scholar]
24. O'Caoimh R. Hypertension and Mild Cognitive Impairment: Understanding the Complexities of the Relationship in Understudied Populations. J Alzheimers Dis. 2024;98(2):421-4. [View at paplisher] [DOI] [PMID] [Google Scholar]
25. Makino K, Lee S, Bae S, Chiba I, Harada K, Katayama O, et al. Diabetes and prediabetes inhibit reversion from mild cognitive impairment to normal cognition. J Am Med Dir Assoc. 2021;22(9):1912-8. e2. [View at paplisher] [DOI] [PMID] [Google Scholar]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
