Mild Cognitive Impairment in Rural Areas: Research Advances and Implications for Clinical Practice and Healthcare Policy
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Studies Reporting on Risk Factors for MCI
3.2. Studies Reporting on Diagnosis and Prognosis
4. Discussion
4.1. Risk Factors for MCI: Differences between Rural and Urban Areas
4.2. Diagnosis, Prognosis and Mortality of People with MCI in Urban and Rural Areas
4.3. Strengths and Limitations of the Present Review
4.4. Limitations of Research
4.5. Implications for Care and Future Research
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study | Country | Objective | Study Design | Participants | Main Findings | |
---|---|---|---|---|---|---|
Rural | Urban | |||||
Srivastana and Muhammad, 2022 [13] | India | To explore the association between food insecurity and cognitive impairment | Cross-sectional | 31,464, 60 years or older | Participants with food insecurity in rural areas had higher odds of cognitive impairment | Lower prevalence of cognitive impairment. Participants reported less food insecurity |
Zhang & Zhang, 2022 [14] | China | To explore the association of adverse childhood experiences with MCI | Cross-sectional | 11,475, 45 years or older | Family socioeconomic status, food deprivation, neighborhood environment and social relations were associated with MCI | Lower prevalence of MCI. Only father’s education and social relations were associated with MCI |
Zhang et al., 2021 [15] | China | To investigate the association between BMI and cognitive impairment in urban and rural areas | Cross-sectional | 8221, 65 years or older | Being overweight was associated with cognitive impairment in ages 80+. Being underweight was associated with higher dementia risk in ages 80+. | Obesity was associated with cognitive impairment in ages 65–69 |
Luo et al., 2019 [16] | China | To explore the association between productive activities and cognitive decline in rural and urban residents | Cross-sectional | 13,596, 50 years or older | Paid employment was most beneficial for men. None of the studied productive activities was significantly associated with cognitive decline in women | Lower prevalence of MCI. Caring for grandchildren and volunteering were most beneficial for women |
Butcher et al., 2018 [17] | France | To study the differences in plasma CCL11 (eotaxin-1) and cognitive status between rural and urban residents | Cross-sectional | 833, 65 years or older | Increased CCL11 was associated with poorer cognitive performance | No association of CCL11 with cognitive performance |
Vintimilla et al., 2018 [18] | USA | To study the relationship between potassium plasma levels and MCI | Cross-sectional | 510, 50 years or older | Potassium levels were significantly associated with MCI | Potassium was the only electrolyte that successfully predicted MCI status |
Tiraphat, 2018 [19] | Thailand | To study the prevalence and risk factors of cognitive impairment in Thai older population living in urban and rural areas | Cross-sectional | 6633, 60 years or older | Higher prevalence of MCI. Poor economic condition was a significant predictor of MCI | Perceived poor health status was a significant predictor of MCI |
Female gender, age, education, and active leisure were significant predictors of MCI in both areas | ||||||
Tang et al., 2016 [20] | China | To address risk factors for cognitive impairment in urban and rural population | Cross-sectional | 7900, 50 years or older | Cognitive impairment was associated with female gender, exposure to pesticides, history of encephalitis or meningitis and head trauma | Cognitive impairment was associated with lack of physical activities and presence of diabetes mellitus |
Prevalence of MCI did not differ between rural and urban residents |
Study | Country | Objective | Design | Participants | Main Findings | |
---|---|---|---|---|---|---|
Rural | Urban | |||||
Li et al., 2021 [21] | China | To explore the association of cognitive impairment with all-cause mortality | Longitudinal study | 25,285, 80 years or older | No differences in mortality risk compared with urban population with cognitive impairment | Participants had better cognitive function |
Xiang et al., 2018 [22] | China | To study the impact of rural-urban community settings on cognitive decline | Cross-sectional, longitudinal | 1709, 65 years or older | Poor cognitive initial status | Cognitive decline rate was faster |
Mattos et al., 2017 [23] | USA | To compare MCI symptom severity among older rural and urban Appalachians | Cross-sectional | 289, 65 years or older | Patients presented for evaluation earlier since symptoms’ onset | Longer time lapse from symptom identification to diagnosis |
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Peritogiannis, V.; Roganaki, A.; Siarava, E.; Samakouri, M. Mild Cognitive Impairment in Rural Areas: Research Advances and Implications for Clinical Practice and Healthcare Policy. Healthcare 2022, 10, 1340. https://doi.org/10.3390/healthcare10071340
Peritogiannis V, Roganaki A, Siarava E, Samakouri M. Mild Cognitive Impairment in Rural Areas: Research Advances and Implications for Clinical Practice and Healthcare Policy. Healthcare. 2022; 10(7):1340. https://doi.org/10.3390/healthcare10071340
Chicago/Turabian StylePeritogiannis, Vaios, Aglaia Roganaki, Eleftheria Siarava, and Maria Samakouri. 2022. "Mild Cognitive Impairment in Rural Areas: Research Advances and Implications for Clinical Practice and Healthcare Policy" Healthcare 10, no. 7: 1340. https://doi.org/10.3390/healthcare10071340
APA StylePeritogiannis, V., Roganaki, A., Siarava, E., & Samakouri, M. (2022). Mild Cognitive Impairment in Rural Areas: Research Advances and Implications for Clinical Practice and Healthcare Policy. Healthcare, 10(7), 1340. https://doi.org/10.3390/healthcare10071340