Mild Cognitive Impairment in Rural Areas: Comparison
View Latest Version
Please note this is a comparison between Version 3 by Dean Liu and Version 2 by Dean Liu.

Mild cognitive or neurocognitive impairment (MCI) may be more prevalent in rural areas. Differences between rural and urban MCI patients in terms of risk factors, course and prognosis are rarely reported. The present review aims to summarize the latest research on MCI in rural areas. 

  • mild cognitive impairment
  • mild neurocognitive disorder
  • rural areas

1. Introduction

Mild cognitive impairment (MCI), or mild neurocognitive disorder, according to the latest classification of the American Psychiatric Association (DSM-5), is a condition that is characterized by cognitive decline with minimal impairment of instrumental activities of daily living of the individual and the preservation of baseline functioning [1][2]. Large population-based studies have shown that the overall prevalence of MCI in the elderly may be up to 12.5%. Hypertension and stroke have been found to be significant risk factors for MCI, whereas higher educational levels and active social engagement are significant protective factors [3]. MCI is widely considered to be the intermediate stage of cognitive impairment between the changes seen in normal cognitive aging and those associated with dementia. Progression to dementia related to Alzheimer’s disease is the most common outcome of MCI, although potentially reversible causes, such as metabolic or systemic, should be taken into account [4]. Although persons with MCI are at higher risk of progressing to dementia than age-matched controls, in several cases cognitive function may remain stable, or even return to intact [2].
Less is known regarding MCI in the rural context. It has been suggested that despite improved access to health services, inadequate diagnosis and management of dementia may be still common, particularly in rural areas [5]. According to recent research, receiving an early diagnosis of cognitive decline may be difficult in rural areas due to the limited access to assessments [6]. In an earlier population-based study in northern Portugal, it was found that the prevalence of cognitive impairment with or without dementia in rural areas was much higher than in urban locations. Cerebrovascular disease and other vascular factors accounted for almost half of the overall cognitive impairment, whereas other medical and neuropsychiatric comorbidities and low levels of education had been also associated with cognitive impairment [7]. A more recent systematic review of Chinese studies confirmed that the prevalence of MCI in rural areas was higher than the corresponding prevalence in urban ones [8]. Such differences in cognitive function between rural and urban Chinese older residents were very recently found to be mediated by social participation [9].

2. Risk Factors for MCI: Differences between Rural and Urban Areas

Recent research addressing risk factors for MCI in rural and urban contexts has yielded interesting results. Some risk factors have been associated with MCI in both rural and urban areas [10][11][12][13], whereas there were also marked differences in several factors associated with MCI across settings [14][15][16]. The association between low BMI and cognitive impairment in rural older adults is a noticeable finding, given that the prevalence of being underweight in rural areas may be higher than in urban ones [15]. Undernutrition in rural-dwelling older adults may be a serious public health concern in certain countries, such as China [15]. Moreover, the types of productive activities that are most beneficial for cognition may vary between urban and rural residence. This finding suggests that environmental demands and resources may play a role in shaping the effects of such participation on cognitive function [11]. The association of MCI in rural-dwelling older adults with the exposure to pesticides, history of encephalitis, meningitis and head trauma [13], may be in part mediated by CCL11, which is a negative regulator of neurogenesis [16]. According to recent research, it seems that the risk for developing MCI may be mediated by environmental factors. Urbanicity and the so-called urban stress have been consistently implicated in the pathophysiology of major mental disorders, such as schizophrenia [17]. However, in the case of cognitive function in the elderly it seems that urban environments may have a protective effect. This may be partly mediated by the higher education and the more opportunities for social participation of the elderly in urban locations [11][12]. There may also be other protective components of urban environments on cognitive function that should be addressed by future research. It should be mentioned that the female gender was not consistently reported as a risk factor for MCI in both rural and urban residents across studies [12][13]. Such inconsistencies may reflect differences in methodology and measurements across studies. Moreover, recent research did not find any protective factors against MCI in rural women, and the authors suggested that the traditional and constrained role of those women as caregivers may limit the benefits they derive from caregiving [11]. These observations should raise awareness in the study on MCI in females in rural areas to elucidate potential risk and protective factors.

3. Diagnosis, Prognosis and Mortality of People with MCI in Urban and Rural Areas

There is some evidence that people living in rural areas may be diagnosed with MCI earlier than their urban counterparts [18]. On the other hand, it has been suggested that despite improved access to health services, the inadequate diagnosis of cognitive decline may be still common in rural areas [5]. Taken together, these notions could mean that MCI may indeed present earlier in rural residents. The confirmation of this suggestion by future research would be important if researchers are to employ preventive interventions for cognitive decline in rural residents. Interestingly, other recent research showed that rural residents with MCI display a lower rate of cognitive decline [19] compared with MCI patients living in urban areas. This may mean that once MCI is established in urban residents, progression to dementia is hastened by factors associated with the urban environment. It has been suggested that a high population density, which is often the case in urban environments, may lead to constricted life space (defined as the extent of movement through the environment covered in daily functioning) for the elderly, which has been shown to be associated with cognitive decline [20]. That would be particularly relevant in the case of urban elderly residents with MCI, who may have a potentially faster decline rate afterwards. On the other hand, rural environments may be less constricted for elderly patients with MCI, thus the rate of cognitive decline may be delayed. Notably, despite differences in the onset and course of MCI, the all-cause mortality in patients was found to be similar in rural and urban locations in a Chinese study. According to the authors, this observation indicates the scarcity of healthcare and treatment for cognitive impairment in China [21]. This suggestion is in line with the results of a previous meta-analysis, which found that the prevalence of undetected dementia was high globally, and that the rate of under-detection was higher in China and India compared with Europe and North America [22].

References

  1. Stokin, G.; Krell-Roesch, J.; Petersen, R.; Geda, Y. Mild Neurocognitive Disorder: An Old Wine in a New Bottle. Harv. Rev. Psychiatry 2015, 23, 368–376.
  2. Petersen, R.C.; Lopez, O.; Armstrong, M.J.; Getchius, T.S.; Ganguli, M.; Gloss, D.; Gronseth, G.S.; Marson, D.; Pringsheim, T.; Day, G.S.; et al. Practice guideline update summary: Mild cognitive impairment: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology 2018, 90, 126–135.
  3. Liu, L.Y.; Lu, Y.; Shen, L.; Li, C.-B.; Yu, J.-T.; Yuan, C.R.; Ye, K.X.; Chao, Y.X.; Shen, Q.-F.; Mahendran, R.; et al. Prevalence, risk and protective factors for mild cognitive impairment in a population-based study of Singaporean elderly. J. Psychiatry Res. 2021, 145, 111–117.
  4. Vega, J.N.; Newhouse, P.A. Mild cognitive impairment: Diagnosis, longitudinal course, and emerging treatments. Curr. Psychiatry Rep. 2014, 16, 490.
  5. Jia, L.; Quan, M.; Fu, Y.; Zhao, T.; Li, Y.; Wei, C.; Tang, Y.; Qin, Q.; Wang, F.; Qiao, Y.; et al. Dementia in China: Epidemiology, clinical management, and research advances. Lancet Neurol. 2020, 19, 81–92.
  6. Barth, J.; Nickel, F.; Kolominsky-Rabas, P.L. Diagnosis of cognitive decline and dementia in rural areas—A scoping review. Int. J. Geriatr. Psychiatry 2018, 33, 459–474.
  7. Nunes, B.; Silva, R.D.; Cruz, V.T.; Roriz, J.M.; Pais, J.; Silva, M.C. Prevalence and pattern of cognitive impairment in rural and urban populations from Northern Portugal. BMC Neurol. 2010, 10, 42.
  8. Xue, J.; Li, J.; Liang, J.; Chen, S. The Prevalence of Mild Cognitive Impairment in China: A Systematic Review. Aging Dis. 2018, 9, 706–715.
  9. Yang, L.; Cheng, J.; Wang, H. Place of Residence and Cognitive Function in Older Adults in China: The Mediating Role of Social Participation. Int. J. Environ. Res. Public Health 2021, 19, 13.
  10. Srivastava, S.; Muhammad, T. Rural-urban differences in food insecurity and associated cognitive impairment among older adults: Findings from a nationally representative survey. BMC Geriatr. 2022, 22, 287.
  11. Luo, Y.; Pan, X.; Zhang, Z. Productive activities and cognitive decline among older adults in China: Evidence from the China Health and Retirement Longitudinal Study. Soc. Sci. Med. 2019, 229, 96–105.
  12. Tiraphat, S.; Aekplakorn, W. Comparison of Prevalence and Risk Factors Associated with Cognitive Impairment between Rural and Urban Elderly in Thailand. J. Med. Assoc. Thail. 2018, 101, 331–337.
  13. Tang, H.D.; Zhou, Y.; Gao, X.; Liang, L.; Hou, M.-M.; Qiao, Y.; Ma, J.-F.; Chen, S.-D. Prevalence and Risk Factor of Cognitive Impairment were Different between Urban and Rural Population: A Community-Based Study. J. Alzheimers Dis. 2016, 49, 917–925.
  14. Zhang, K.; Zhang, W. Adverse Childhood Experiences and Mild Cognitive Impairment in Later Life: Exploring Rural/Urban and Gender Differences Using CHARLS. J. Appl. Gerontol. 2021, 7334648211064796.
  15. Zhang, J.J.; Li, L.; Liu, D.; Hu, F.-F.; Cheng, G.-R.; Xu, L.; Yan, P.-T.; Tian, Y.; Hu, H.; Yu, Y.-F.; et al. Urban-Rural Disparities in the Association Between Body Mass Index and Cognitive Impairment in Older Adults: A Cross-Sectional Study in Central China. J. Alzheimers Dis. 2021, 83, 1741–1752.
  16. Butcher, L.; Pérès, K.; André, P.; Morris, R.H.; Walter, S.; Dartigues, J.-F.; Rodriguez-Mañas, L.; Feart, C.; Erusalimsky, J.D. Association between plasma CCL11 (eotaxin-1) and cognitive status in older adults: Differences between rural and urban dwellers. Exp. Gerontol. 2018, 113, 173–179.
  17. Abrahamyan Empson, L.; Baumann, P.S.; Söderström, O.; Codeluppi, Z.; Söderström, D.; Conus, P. Urbanicity: The need for new avenues to explore the link between urban living and psychosis. Early Interv. Psychiatry 2020, 14, 398–409.
  18. Mattos, M.K.; Snitz, B.E.; Lingler, J.H.; Burke, L.E.; Novosel, L.M.; Sereika, S.M. Older Rural- and Urban-Dwelling Appalachian Adults with Mild Cognitive Impairment. J. Rural Health 2017, 33, 208–216.
  19. Xiang, Y.; Zare, H.; Guan, C.; Gaskin, D. The impact of rural-urban community settings on cognitive decline: Results from a nationally-representative sample of seniors in China. BMC Geriatr. 2018, 18, 323.
  20. James, B.D.; Boyle, P.A.; Buchman, A.S.; Barnes, L.L.; Bennett, D.A. Life space and risk of Alzheimer disease, mild cognitive impairment, and cognitive decline in old age. Am. J. Geriatr. Psychiatry 2011, 19, 961–969.
  21. Li, Y.; Jiang, H.; Jin, X.; Wang, H.; Ji, J.S.; Yan, L.L. Cognitive impairment and all-cause mortality among Chinese adults aged 80 years or older. Brain Behav. 2021, 11, e2325.
  22. Lang, L.; Clifford, A.; Wei, L.; Zhang, D.; Leung, D.; Augustine, G.; Danat, I.; Zhou, W.; Copeland, J.; Anstey, K.; et al. Prevalence and determinants of undetected dementia in the community: A systematic literature review and a meta-analysis. BMJ Open 2017, 7, e011146.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Video Production Service
Feedback