Introduction

Thailand has grappled with the challenges of an aging society since 2000, where individuals aged 60 and above constitute over 10% of the Thai population [1]. Currently, the Thai older adult demographic accounts for 18.3% (12.1 million) of the total population. This comprises early older adults (60–69 years old) at 56.5% (6.8 million), mid-older adults (70–79 years old) at 29.1% (3.5 million), and late older adults (80 years old and above) at 14.4% (1.8 million) [2]. Chiang Mai, the second largest province, reflects this trend with 3% of its population classified as older adults, constituting 0.3 million individuals, and witnessing a steady increase [2]. The older adult demographic emerges as a vulnerable segment, facing challenges in both physical and mental health due to the inevitable effects of aging, particularly cognitive impairment [3]. This impairment can result in a decline in their daily functional capacities, affecting not only individuals but also families, communities, and even the broader Thai economy [3]. The vulnerability is particularly pronounced in rural areas, characterized by non-urban settings with fewer than 50,000 residents and limited access to formal care services, typically supported by only one or two generalist physicians, along with a nurse practitioner or physician assistant [4]. This urban-rural disparity also intensifies the impact on the health and well-being of older adults residing in rural communities, compounding the challenges of poorer access to necessary formal care services [5].

Mild cognitive impairment (MCI) represents the highest-risk condition leading to early dementia. Problems with forgetfulness may progress to dementia within one to three years, with a mortality rate about two times higher than that of the general older adult population [6, 7]. In Thailand, the prevalence of MCI among the urban population was 52.8%, surpassing the global average prevalence of 6.7–25.2% [8, 9]. Older adults with MCI typically experience impairment across five dimensions of the brain including memory, language, visual-spatial skill, attention, and executive function [10]. Several factors were associated with an increased risk of MCI in older adults. These include an age increase (1.1 to 1.6 times), a history of smoking (1.2 times), the presence of chronic medical conditions like diabetes, hypertension, and dyslipidemia (4.4 times), as well as anxiety disorders (2.2 times) [8, 11–16]. Additionally, heightened risk was observed in cases of polypharmacy and diminished physical activity [8, 11–16].

Frailty emerges as a prevalent geriatric syndrome, arising from physiological changes linked to the aging process. This transformation contributes to a decline in both physical and mental well-being, resulting in diminished quality of life, heightened mortality rates, and a demand for intricate and advanced care [17]. The indicators of frailty are intertwined with age-related degeneration, including muscle fatigue, reduced physical activity, slowed gait, unintentional weight loss, and increased vulnerability across physical, mental, and social domains. This results in compromised adaptability, disrupted homeostasis and heightened susceptibility to illness [18–21]. A recent systematic review revealed that frailty was 1.8 times (95% CI 1.1–2.9) associated with MCI while Asians such as Japanese and Singaporeans had a 6.4 times higher chance for MCI [16, 22, 23]. Participants who exhibited both frailty and MCI faced a higher mortality rate [16, 22, 24]. The presence of either MCI or frailty, or their combination, has the potential to significantly diminish the quality of life, escalate vulnerability, heighten the need for permanent caregiving, and increase the demand for healthcare assistance, ultimately leading to elevated mortality among community-dwelling older adults. However, there is currently insufficient evidence to establish a clear connection in the rural population [25, 26].

Currently, a substantial gap exists in the comprehension of frailty and MCI among older adults residing in rural regions of Thailand. The primary objectives of this study involve exploring the association between frailty and MCI and examining the risk factors linked to MCI among older adults in the rural areas of Chiang Mai Province. Consequently, investigating this knowledge will serve as a pivotal tool for identifying high-risk groups within the older adult population in rural communities. This endeavor aims to proactively prevent the progression of cognitive impairment or dementia among older adults in the future.

Materials and methods

Results

This survey gathered 984 participants from older adult individuals residing in the community of Chiang Mai, Thailand. Among individuals identified with MCI was 35.5% (n = 350), and the mean age was 72.7 years (SD = 8.8). 60.9% (n = 213) were female. The median year of education was four years (IQR 0–5). 68.0% (n = 238) were married, 9.4% (n = 33) were living alone and 71.2% (n = 249) were retired or currently unemployed. 82.8% (n = 288) had chronic medical conditions and were taking an average of two medications (IQR 0–3). 33.7% (n = 118) were alcohol consumption and 16% (n = 56) were smoking. 71.1% (n = 249) had a caregiver and 80.9% (n = 283) reported a monthly salary below 26,000 THB (750 USD). Most of this group engaged in exercise two times a week (IQR 0–7). 32.0% (n = 112) reported feeling lonely. More than half (25.1%) were admitted to the hospital in the past year, and 28.3% (n = 99) had experienced falls during the last year. The majority of them slept for around eight hours, but around 39.7% (n = 139) had poor sleep quality. 45.1% (n = 158) considered their health condition to be poor and 27.4% (n = 96) believed their cognitive function to be poor as well. Participants had 8% frailty (n = 79), mild depression 6.5% (n = 64), and moderate to severe depression 1.1% (n = 11) (Table 1).

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Table 1. Socio-demographic characteristics of older adults living in rural areas in Chiang Mai.

https://doi.org/10.1371/journal.pone.0300264.t001

The unadjusted odds ratio (OR) for the relationship between frailty and MCI in older adults living in rural areas of Chiang Mai, Thailand, was 3.28 (95% CI = 2.038, 5.270, p- < 0.001). Table 2 presents the factors associated with MCI among older adults residing in rural areas of Chiang Mai, Thailand. There were four factors associated with an increased risk of MCI including age (aOR = 1.07, 95% CI 1.04–1.09, p < 0.001), cigarette smoking (aOR 1.95, 95% CI 1.27–2.98, p = 0.002), feelings of loneliness (aOR 1.43, 95% CI 1.01–2.03, p = 0.043), and presence of frailty (aOR 1.92, 95% CI 1.10–3.35, p = 0.022). There were two factors associated with a lower risk of MCI including higher education level (aOR 0.90, 95% CI 0.86–0.94, p < 0.001) and engaging in frequent exercise (aOR 0.9, 95% CI 0.86–0.95, p < 0.001) (Table 2).

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Table 2. Factors associated with mild cognitive impairment among older adults living in rural areas in Chiang Mai.

https://doi.org/10.1371/journal.pone.0300264.t002

Discussion

To our knowledge, this was the first study that represented the association between frailty and MCI within rural communities in Thailand. Among the older adult population residing in these rural areas, the prevalence of MCI was recorded at 35.6%. Several factors emerged as significant contributors to the elevated risk of MCI, encompassing age, current smoking, and feelings of loneliness. Conversely, engaging in regular exercise and having a high education level were associated with a reduced risk of MCI among the older adult inhabitants of these rural communities.

Our study findings demonstrated an association between frailty and MCI among older adults residing in rural communities, showing an elevated risk of MCI by 1.9 times (95% CI 1.1–3.5; p 0.02) for those with frailty. These results align with a systematic review and meta-analysis conducted in 2015 and 2019, which similarly reported a 1.8-fold increase in the risk of cognitive impairment (95% CI = 1.11–2.92; p = 0.02), with severity influenced by higher levels of frailty [22, 24]. Our research revealed a greater association compared to prior studies. Furthermore, a study conducted in rural India also provides backing for the correlation between frailty and cognitive impairment [31]. This suggests that older individuals residing in rural areas may possess a potential for developing age-related conditions such as frailty accompanied by cognitive impairment.

Our study revealed the highest documented prevalence of MCI, reaching 35.6%, among older adults residing in rural communities. This prevalence surpassed rates observed in rural Taiwanese older adults (25.1%) and in urban older adult populations of China and India, where the range spanned from 9.67% to 26.06% [14, 32–36]. This can be attributed to the fact that rural areas often exhibit lower levels of education, limited access to healthcare services and resources, lower socioeconomic status, and occupations with fewer skill requirements. These factors may potentially restrict the accumulation of cognitive reserve, contributing to a decline in brain function [32, 37, 38]. Additionally, residents in rural areas often experience delays in the screening and inadequate management of chronic diseases [32, 37]. In comparison to the urban Thai population, the occurrence was lower (35.6% vs. 52.8%). This discrepancy in prevalence can be clarified by variations in assessment tools. It likely stemmed from a selection bias, where urban environments tend to encompass a higher number of cases involving multiple medical conditions compared to community settings, sociodemographic factors, and living conditions.

Our study findings indicate that regular physical exercise among older adults was associated with a 14% reduction in the risk of MCI (95% CI 0.857, 0.945; p < 0.001). This outcome aligns with investigations conducted by Smith et al. and Li et al. in various countries, including China, Ghana, India, Mexico, Russia, and South Africa. These studies demonstrated that greater engagement in physical activities or maintaining high levels of physical activity was linked to a decreased risk of MCI [12, 34, 36]. Moreover, one study conducted among older adults living in rural northern China demonstrated that engaging in physical activity was a protective factor for MCI (p < 0.05), and the saturation point was identified at 6546 MET x min/week [39]. Engaging in aerobic or resistance exercises among older adults can enhance cardiovascular function, provide greater nourishment to brain tissue cells, preserve brain functionality, enhance memory, and postpone the progression of neurodegenerative processes [40, 41].

It is recommended that Thai older adult populations living in rural communities undergo early frailty screening with T-FRAIL and cognitive screening with TMSE [27–29]. Community health volunteers and primary care physicians could play a pivotal role in administering that screening tool to identify older adults at risk. To mitigate this prevalence in Thailand, the establishment of elder-friendly community centers (schools for elders) and senior citizen clubs could serve as an engaging solution. Those centers could gather older adults from the community, enhancing physical and mental well-being. The program should aim for a minimum of 150 minutes of moderate aerobic physical activity weekly, supplemented by resistance training or multifaceted exercise. Moreover, it holds the potential to alleviate feelings of loneliness among older adults living alone, consequently reducing the risk of later cognitive impairment. A study conducted in Singapore lends support to this notion, indicating that engaging in social activities during later life can reduce the risk of MCI by approximately 57% [42, 43]. This comprehensive approach targets modifiable risk factors for cognitive decline. The success of such a program could be tailored through collaborative efforts involving doctors and physical therapists within each respective catchment area [44, 45].

Our study had a few limitations, primarily relying on a convenient sampling of older adults within rural communities. Additionally, the cross-sectional design of the study prevented the establishment of causal relationships between frailty and MCI among these older adults. Loneliness was subjectively evaluated without the use of comprehensive tools. To overcome these limitations, future research should encompass multiple sites across Thailand, employing proper screening tools in a prospective cohort design that compares urban and rural settings. This approach would allow for a comprehensive overview, guiding policymakers and stakeholders in advocating for the implementation of screening programs and the development of health promotion initiatives for older adults in rural communities. Such efforts would contribute to empowering these older adults, enabling them to have self-efficacy in sustaining their competence and decreasing potential modifiable risks that could lead to cognitive impairment in the foreseeable future.

Conclusion

Approximately 35.6% of the senior population residing in rural areas experience MCI. The likelihood of developing MCI is heightened among older adults who are frail or experience feelings of loneliness. However, the risk can be mitigated by fostering increased physical activity. For those older adult individuals at a higher risk, it is recommended to employ accessible screening methods like the TMSE to identify cognitive impairment and the T-FRAIL assessment for identifying frailty. These tools can effectively detect issues early on, preventing the progression towards irreversible disabilities. To address this concern, supporting community initiatives like older adult schools and senior citizen clubs becomes crucial. By establishing health promotion programs within these contexts, we can encourage greater participation in engaging activities among older adults and promote enhanced physical activity levels, especially among those residing in rural settings.

Supporting information

Acknowledgments

We extend our heartfelt gratitude to the village health volunteers in Sanpatong, Mae Tang, and Doi Saket, Chiang Mai, Thailand, as well as the dedicated staff at the Department of Community Medicine, Faculty of Medicine, Chiang Mai University.