Abstract
Background
Mild cognitive impairment (MCI) and motoric cognitive risk syndrome (MCR) are two pre-dementia stages, which may exist independently or concurrently, and both increase the risk of dementia. The association between MCI, MCR, and their co-occurrence with dementia risk in the elderly Chinese population remains unclear.
Objective
This study aims to explore the relationship of MCI, MCR, and their co-occurrence with the incidence of dementia among the elderly population in China, based on a nationwide large-scale survey.
Methods
A total of 2,411 elderly individuals from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study. At baseline in 2011, all eligible participants were categorized into four groups: CHI (cognitively healthy individuals) group, MCI (individuals with MCI alone) group, MCR (individuals with MCR alone) group, and MCI + MCR (individuals with both MCI and MCR) group. After a 7-year follow-up, logistic regression models were used to analyze the longitudinal association between pre-dementia stages and the onset of dementia.
Results
At baseline, the prevalence rates were 14.5% for MCI group, 9.8% for MCR group, and 2.2% for MCI + MCR group. The median total cognitive scores at baseline were 16 points for both CHI group and MCR group, 9 points for MCI group, and 8.7 points for MCI + MCR group (P < 0.001). After 7 years of follow-up, the cognitive scores remained unchanged in MCI group, decreased by 1 point in both the CHI group and MCI + MCR group, and decreased by 2 points in MCR group (P < 0.001). The 7-year dementia incidence was 4.8%. Multivariate logistic regression model showed that the risk of dementia was significantly associated with MCI (OR = 2.319, 95%CI:1.420–3.785, P < 0.001), MCR (OR = 2.488, 95%CI:1.441–4.294, P = 0.001), and MCI + MCR (OR = 3.226, 95% CI:1.340–7.762, P = 0.009).
Conclusion
Both MCI and MCR were associated with an increased risk of dementia, and the co-occurrence of MCI and MCR conferred a higher risk of dementia. Although the MCR group showed no significant baseline cognitive impairment, their subsequent cognitive decline and dementia risk were higher than those of the MCI group. Therefore, promoting MCR screening in China’s primary healthcare system may be more feasible than MCI screening, which could help in early identification of high-risk populations and the implementation of targeted interventions to delay or prevent the onset of dementia.
Keywords: Older adults, Mild cognitive impairment, Motoric cognitive risk syndrome, Dementia, CHARLS
Introduction
With the accelerating process of global aging, the prevalence of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease have risen significantly, posing a major global public health challenge [1]. China has the largest number of dementia patients in the world, accounting for approximately 25% of the total global dementia cases [2]. The status quo not only severely affects patients’ quality of life but also impose a tremendous burden on China’s public healthcare system [3]. Currently, although pharmacological treatments can delay the progression of dementia in some individuals, there are no definitive curative therapies available in clinical practice for dementia [4]. Given the potential reversibility of the pre-dementia stage, it is crucial to emphasize the early identification of dementia to enable timely intervention strategies [5, 6]. Early intervention will help patients and caregivers prepare for managing the symptoms and its consequences of dementia [7].
Mild cognitive impairment (MCI) and motoric cognitive risk syndrome (MCR) are transitional stages between normal cognitive aging and dementia, both representing pre-dementia stages. MCI is defined as a cognitive state that lies between normal aging and dementia, characterized by a decline in cognitive function without impairment in activities of daily living. Its diagnosis is based on objective and quantifiable assessments of cognitive function [8, 9]. In China, the prevalence of MCI among older adults aged 60 years and above was 14.7% [10]. MCR is a pre-dementia syndrome proposed by Verghese et al. in 2013 [11]. Its diagnostic criterion includes the presence of subjective cognitive decline and slow gait speed, in the absence of dementia and mobility disorders [12]. The global prevalence of MCR among individuals aged 60 years and older was 9.7% [11], while in China, the prevalence among the same age group was 7.29% [13]. The introduction of MCR has provided a new perspective for dementia prevention, offering a practical and accessible approach in primary care [14].
Since MCR and MCI can complement each other in identifying individuals at potential risk of dementia, focusing on the pre-dementia stages may serve as an effective entry point for dementia prevention. Studies had shown that the annual conversion rate from MCI to dementia was approximately 10–15%, whereas the conversion rate among cognitively healthy individuals was only 1–2% [15]. The annual dementia incidence rate in MCR patients was 11.7% [11], slightly lower than that of MCI. A longitudinal study found that 3-year follow-up dementia conversion rate was higher in MCI than in MCR [16]. Although MCR is associated with cognitive decline, not all individuals with MCR exhibit significant cognitive impairment, suggesting that MCR may represent an earlier stage than MCI. Moreover, imaging and pathological studies suggested that MCI is closer to dementia than MCR. Research has found that the MCI stage might already be accompanied by dementia-related neurobiological changes such as hippocampal atrophy, β-amyloid deposition, and tau protein pathology [17]. These changes make MCI patients more likely to progress to dementia. In contrast, MCR patients exhibit relatively fewer structural brain changes. Some studies suggested that MCR might be associated with executive dysfunction in the frontal lobe, white matter lesions, or cerebral small vessel disease [18], indicating that MCR could serve as an earlier marker of cognitive risk.
Previous studies had also suggested that the coexistence of MCR and MCI was linked to poorer cognitive performance, and the risk of progressing to dementia was the highest when both MCI and MCR were present, compared to MCR or MCI alone [19, 20]. However, there is a lack of research on the differences in cognitive performance and the risk of dementia progression among non-demented Chinese elderly individuals when MCR and MCI occur alone or concurrently. To address this research gap, we conducted a study using nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS). Through this study, we aim to explore the distribution characteristics of MCR and MCI in the Chinese elderly population, examine their differences in cognitive performance, and assess their respective risks for dementia progression. The findings are expected to provide scientific evidence for early prevention of dementia.
Methods
Study population
The CHARLS project is a nationwide longitudinal survey of individuals aged 45 and above in China. The baseline survey of CHARLS was conducted in 2011 using multistage probability sampling. The survey covered 28 provinces, 150 counties, and 450 villages across the country, and included more than 17,000 individuals from approximately 10,000 households. CHARLS is an ongoing survey with follow-ups every 2–3 years. To date, five waves of surveys have been completed [21]. The CHARLS project was approved by the Biomedical Ethics Committee of Peking University (approval number: IRB00001052-11015), and all participants had written informed consent.
This study utilized baseline data from the 2011 CHARLS database and follow-up data from the fourth wave conducted in 2018. The baseline sample in 2011 consisted of 18,308 individuals. Participants were excluded based on the following criteria: (1) age < 60 years (N = 10,473); (2) absence of cognitive-related information across 4 waves of follow-up and in 2018 (N = 3996); (3) absence of gait speed data (N = 1209); and (4) a previous diagnosis of memory-related diseases (e.g., Alzheimer’s disease, brain atrophy, Parkinson’s disease) or suspected dementia according to this study’s diagnostic criteria(N = 216). A total of 2,411 eligible participants were included in the final analysis.
Measurement of cognitive function
Referring to previous studies, we defined dementia as either (1) the coexistence of cognitive impairment (CI) and functional impairment (FI) or (2) self-reported dementia or memory-related diseases [22, 23]. The “memory-related disease” refers to participants who answered “yes” to the question “Have you been diagnosed with a memory-related disease (such as dementia, brain atrophy, and Parkinson’s disease) by a doctor?” in the CHARLS study. The cognitive module in this study assessed four domains through face-to-face evaluations: memory, calculation, orientation, and executive function (total score: 30 points). Memory assessment included both immediate and delayed recall. Each participant was randomly presented with 10 words for immediate recall, assessed by the number of words correctly recalled. After completing the depression scale, calculation test, and drawing tests, participants were asked to recall the words again, and each correct response was awarded 1 point, with a total memory score of 20 points. Calculation ability was tested by asking participants to subtract 7 from 100 for five times. Each correct subtraction earned 1 point, with a maximum score of 5 points. Orientation was assessed by asking participants to correctly identify the current year, month, date, and day of the week. Each correct answer earned 1 point, with a maximum score of 4 points. Executive function was evaluated by asking participants to draw a specified figure (two overlapping pentagons). Completing this task correctly earned 1 point. Cognitive impairment in each domain was defined as a score of 1.5 standard deviations or more below the mean score for individuals in this study with the same education level. CI was defined as impairment in two or more cognitive domains [24]. FI was defined as the inability to perform one or more basic activities of daily living (ADLs), including bathing, getting in and out of bed, dressing, using the toilet, controlling bowel and bladder functions, and eating. For example, using a walking cane due to orthopedic conditions such as severe osteoarthritis or hip fracture, or having an artificial anus due to the rectal cancer, can result in such impairments.
To date, there is no consensus on the diagnostic criteria for MCI. In this study, we defined aging-associated cognitive decline (AACD) as MCI, which was characterized by cognitive function scores at least 1 standard deviation (SD) below the mean for the corresponding age group. All participants aged 60 and above were divided into age groups at 5-year intervals, with a separate group of 75 years and older. Individuals meeting the AACD criteria in each age group were classified as MCI [25, 26]. MCR was defined as the presence of subjective cognitive complaints combined with slow gait speed. In the CHARLS survey, subjective cognitive decline was assessed based on the respondent’s self-reported memory status, using a scale ranging from 1(Excellent) to 5(Poor). Participants who reported their memory status as “fair” or “poor” were classified as having subjective cognitive decline. Gait speed was measured by averaging the results of two trials in which participants walked a 2.5-meter distance along a 4-meter flat path. We defined slow gait speed as gait speed ≤ 1.0 SD below the mean for the same age and sex cohort [27].
Covariates
Based on previous studies, we considered potential covariates in this study, including age, gender, education level, marital status, residence area, polypharmacy, history or current status of smoking or alcohol consumption, and 13 common comorbidities (cancer, chronic pulmonary disease, heart disease, stroke, mood and mental disorders, arthritis, dyslipidemia, liver disease, kidney disease, gastrointestinal diseases, asthma, hypertension, hyperglycemia) [28–31].
Statistics
Based on baseline cognitive levels, we categorized the sample into four groups: CHI (cognitively healthy individuals) group, MCI (individuals with MCI alone) group, MCR (individuals with MCR alone) group, and MCI + MCR (individuals with both MCI and MCR) group. Quantitative data that did not conform to the normal distribution were described by quartile, qualitative data were reported by percentages, and differences between groups were compared by chi-square test. Based on the longitudinal data from 2011 to 2018, we used logistic regression models to analyze the relationship between different pre-dementia stages and the incidence of dementia. All statistical analyses were performed using SPSS software, and the significance level for statistical tests was set at 0.05.
Results
At baseline, 73.5% of participants showed neither MCR nor MCI. The detection rate of MCR was 9.8%, MCI was 14.5%, and the coexistence of MCR and MCI was 2.2%. Significant differences were observed among the different groups in terms of age, gender, education level, marital status and residential area (P < 0.005). In addition, significant differences were also observed among the groups in terms of comorbid conditions such as hypertension, stroke, or arthritis. Apart from these characteristics, no significant group differences were observed in other baseline characteristics, such as smoking, alcohol consumption, or comorbidities including cancer, chronic lung disease, heart disease, mood and psychiatric disorders, dyslipidemia, liver disease, kidney disease, digestive system diseases, asthma, or hyperglycemia (Table 1).
Table 1.
Baseline characteristics of participants
| Variables | Overall(n = 2411) n (%)/Median (Q1, Q3)* |
CHI(n = 1771) n (%)/Median (Q1, Q3)* |
MCI(n = 349) n (%)/Median (Q1, Q3)* |
MCR(n = 237) n (%)/Median (Q1, Q3)* |
MCR + MCI(n = 54) n (%)/Median (Q1, Q3)* |
P-value |
|---|---|---|---|---|---|---|
| Age | 64.0 (62.0, 68.0) | 64.0(62.0, 68.0) | 64.0(62.0, 68.0) | 65.0(62.0, 68.0) | 66.5 (62.0, 70.0) | 0.037 |
| Gender | < 0.001 | |||||
| Male | 1,425 (59.10%) | 1,102 (62.22%) | 162 (46.42%) | 133 (56.12%) | 28 (51.85%) | |
| Female | 986 (40.90%) | 669 (37.78%) | 187 (53.58%) | 104 (43.88%) | 26 (48.15%) | |
| Education | < 0.001 | |||||
| Illiterate | 836 (34.67%) | 499 (28.18%) | 225 (64.47%) | 74 (31.22%) | 38 (70.37%) | |
| Primary school | 854 (35.42%) | 651 (36.76%) | 95 (27.22%) | 96 (40.51%) | 12 (22.22%) | |
| Middle school | 465 (19.29%) | 390 (22.02%) | 20 (5.73%) | 52 (21.94%) | 3 (5.56%) | |
| High school | 192 (7.96%) | 170 (9.60%) | 8 (2.30%) | 13 (5.49%) | 1 (1.85%) | |
| Junior college or above | 64 (2.65%) | 61 (3.44%) | 1 (0.29%) | 2 (0.84%) | 0 (0.00%) | |
| Marital status | < 0.001 | |||||
| Married | 2016 (83.62%) | 1,486 (83.91%) | 286(81.95%) | 191 (80.59%) | 45 (83.33%) | |
| Separated | 94 (3.90%) | 73 (4.12%) | 13 (3.72%) | 7 (2.95%) | 1 (1.85%) | |
| Unmarried/divorced/widowed | 301 (12.48%) | 212 (11.97%) | 50 (14.33%) | 39 (16.46%) | 8 (14.81%) | |
| Residential area | < 0.001 | |||||
| Urban Community | 1012 (41.97%) | 797 (45.00%) | 94 (26.99%) | 102 (43.04%) | 16 (29.63%) | |
| Rural Village | 1399 (58.03%) | 974 (54.00%) | 255 (73.01%) | 135 (56.96%) | 38 (70.37%) | |
| Polypharmacy | 27 (1.12%) | 21 (1.19%) | 5 (1.43%) | 1 (0.42%) | 0 (0%) | 0.7 |
| Ever/current alcohol | 1,039 (43.09%) | 780 (44.04%) | 144 (41.26%) | 97 (40.93%) | 18 (33.33%) | 0.2 |
| Ever/current smoke | 1,091 (45.25%) | 823 (46.47%) | 139 (39.83%) | 106 (44.73%) | 23 (42.59%) | 0.11 |
| Comorbidities | 1,058 (43.88%) | 759 (42.86%) | 147 (42.12%) | 125 (52.74%) | 27 (50.00%) | 0.023 |
| Hypertension | 755 (31.31%) | 574 (32.41%) | 81 (23.21%) | 83 (35.02%) | 17 (31.48%) | 0.006 |
| Hyperglycaemia | 191 (7.92%) | 145 (8.19%) | 22 (6.30%) | 21 (8.86%) | 3 (5.56%) | 0.6 |
| Cancer | 22 (0.91%) | 17 (0.96%) | 1 (0.29%) | 4 (1.69%) | 0 (0.00%) | 0.4 |
| Chronic lung disease | 285 (11.82%) | 194 (10.95%) | 47 (13.47%) | 35 (14.77%) | 9 (16.67%) | 0.2 |
| Heart disease | 378 (15.68%) | 290 (16.38%) | 41 (11.75%) | 39 (16.46%) | 8 (14.81%) | 0.2 |
| Stroke | 55 (2.28%) | 40 (2.26%) | 2 (0.57%) | 10 (4.22%) | 3 (5.56%) | 0.008 |
| Emotional and mental disorders | 32 (1.33%) | 22 (1.24%) | 5 (1.43%) | 5 (2.11%) | 0 (0.00%) | 0.6 |
| Arthritis | 819 (33.97%) | 573 (32.36%) | 124 (35.53%) | 95 (40.08%) | 27 (50.00%) | 0.014 |
| Dyslipidaemia | 279 (11.57%) | 224 (12.65%) | 23 (6.59%) | 29 (12.24%) | 3 (5.56%) | 0.007 |
| Hepatic disease | 88 (3.65%) | 67 (3.78%) | 11 (3.15%) | 9 (3.80%) | 1 (1.85%) | > 0.9 |
| Kidney disease | 139 (5.77%) | 102 (5.76%) | 16 (4.59%) | 16 (6.75%) | 5 (9.26%) | 0.5 |
| Digestive system disease | 532 (22.07%) | 369 (20.84%) | 85 (24.36%) | 64 (27.00%) | 14 (25.93%) | 0.14 |
| Asthma | 143 (5.93%) | 97 (5.48%) | 26 (7.45%) | 19 (8.02%) | 1 (1.85%) | 0.2 |
*Q1,First quartile; Q3,third quartile
At baseline assessment, the median total cognitive scores for the CHI group and MCR group were both 16, while the median scores for both the MCI group and MCR + MCI group were 9.0, 8.7, respectively, with statistically significant differences in cognitive scores among the four groups (P < 0.001). Follow-up data on cognitive scores after 7 years showed that the median decline in cognitive scores was 1.0 for both CHI group and MCI + MCR group, while no decline was observed in the MCI group, and the median decline was 2.0 for the MCR group. The differences in cognitive decline across the groups were statistically significant (P < 0.001). Among the 2,411 participants included in the longitudinal analysis, a total of 115 individuals (4.8%) were newly diagnosed with dementia during the 2018 follow-up. Group analysis revealed that the incidence rates of dementia in the CHI group, MCR group, MCI group, and MCR + MCI group were 3.2%, 8.4%, 8.9%, and 13.0%, respectively. Notably, the MCR + MCI group exhibited the highest incident dementia, which was significantly higher than that of the other groups (P < 0.001) (Table 2).
Table 2.
Cognitive scores and incident dementia
| Overall(n = 2411) n(%)/Median (Q1, Q3) |
CHI(n = 1771) n(%)/Median (Q1, Q3) |
MCI(n = 349) n(%)/Median (Q1, Q3) |
MCR(n = 237) n(%)/Median (Q1, Q3) |
MCR + MCI(n = 54) n(%)/Median(Q1, Q3) |
P-value | |
|---|---|---|---|---|---|---|
| Cognitive score in 2011 | 15.0 (12.0, 18.0) | 16.0(14.0,19.0) | 9.0 (7.3, 10.0) | 16.0(14.0, 18.0) | 8.7 (7.7, 10.0) | < 0.001 |
| Cognitive score in 2018 | 14.0 (10.0, 18.0) | 15.0(12.0,18.0) | 9.0 (6.0, 12.0) | 14.0(10.0, 17.0) | 8.0 (5.0, 11.0) | < 0.001 |
| Variation | 1.0 (−2.0, 4.0) | 1.0 (−2.0, 5.0) | 0.0 (−3.0, 2.0) | 2.0 (−1.0, 6.0) | 1.0 (−2.0, 3.0) | < 0.001 |
| Dementia in 2018 | 115 (4.8%) | 57 (3.2%) | 31 (8.9%) | 20 (8.4%) | 7 (13%) | < 0.001 |
Univariate logistic regression analysis showed that, compared to individuals without pre-dementia stages, those with MCR at baseline had a significantly higher risk of developing dementia (OR = 2.017, 95% CI:1.221–3.332, P = 0.006). The risk was even higher for individuals with MCI (OR = 2.296, 95%CI:1.495–3.524, P < 0.001). Individuals with both MCR and MCI had the highest risk of developing dementia (OR = 3.101, 95% CI:1.37–7.022, P = 0.007). In the multivariate logistic regression model adjusted for age, gender, education level, marital status, and residential area, similar results were observed. The risk of developing dementia was significantly associated with MCI alone (OR = 2.319, 95%CI:1.420–3.785, P < 0.001, MCR alone (OR = 2.488, 95% CI:1.441–4.294, P = 0.001), and coexisted MCI + MCR (OR = 3.226, 95%CI: 1.340–7.762, P = 0.009). Notably, the risk of developing dementia was higher in the MCR group than in the MCI group, with statistical significance (P < 0.001) (Table 3).
Table 3.
Association between pre-dementia stages and dementia
| OR(95%CI), P-value | ||
|---|---|---|
| Non-adjusted | Adjusted Model1 | |
| MCI | 2.296(1.495, 3.524), < 0.001 | 2.319(1.420, 3.785), < 0.001 |
| MCR | 2.017(1.221, 3.332), 0.006 | 2.488(1.411, 4.294), 0.001 |
| MCI + MCR | 3.101(1.370, 7.022), 0.007 | 3.226(1.340, 7.762), 0.009 |
1Model adjusted for age, gender, education level, marital status, and residential area
Discussion
We found that at the baseline assessment, there were significant differences in cognitive function scores among different groups. The MCI + MCR group had the lowest scores, while the CHI group had the highest scores. Individuals in the MCR group did not show a decline in cognitive scores compared to the CHI group at baseline, consistent with previous studies indicating that MCR may reflect discordance between cognitive performance and dementia progression. In other words, they may demonstrate normal cognitive function while still being at risk of progressing to dementia [19]. However, after a 7-year follow-up, the MCR group exhibited the most significant decline in cognitive scores while those in the MCI group did not show a noticeable decrease during the follow-up period. On the one hand, this result suggested that individuals with MCR experienced a more rapid cognitive decline, indicating that MCR was an important predictor of continuous cognitive deterioration. On the other hand, we found that the illiteracy rate in the MCI group was higher than that in the MCR group at baseline, which may be related to the cognitive assessment tasks used in this study, including drawing and calculation. Illiterate participants might have lower scores due to inability to complete these tasks, leading to an underestimation of baseline cognitive scores in the MCI group. Furthermore, if illiteracy caused the MCI group’s baseline scores to approach the lower limit of the tests, there would be limited room for further decline, potentially masking the true trend of cognitive deterioration. Nevertheless, the MCI + MCR group had the highest illiteracy rate and still exhibited the greatest cognitive decline, which might reflect a synergistic effect on cognitive impairment when MCI and MCR coexist.
Furthermore, our findings indicated that MCR, MCI, and their coexistence were significantly associated with incident dementia, with individuals in the MCR + MCI group having the highest risk of developing dementia. This is consistent with previous research findings, which indicated that individuals with coexisting MCR and MCI are at a greater risk of developing dementia. A possible explanation is that the coexistence of MCR and MCI may represent the final stage of the pre-dementia phase [19, 20]. After adjusting for potential confounding factors (e.g., age, gender, residence area, education level, and marital status), multivariate logistic regression analysis revealed that the OR for MCR was higher than that for MCI in assessing the risk of new-onset dementia. This indicated a greater risk of dementia in the MCR group compared to the MCI group, a result consistent with the finding from a study involving 22 cohorts across 17 countries [11]. However, it differed from another study, which reported a higher OR value for MCI than for MCR, supporting the conventional view that MCI was closer to the dementia stage and thus more likely to progress to dementia [20]. The difference may be explained by differences in population characteristics. The NuAge Study might have involved relatively healthier cohort, resulting in a lower incidence of dementia [20]. While our study included a larger sample size, a longer follow-up duration, and participants from different geographic regions. Moreover, in the unadjusted model, the OR for the MCI group was higher than that for the MCR group (2.296 vs. 2.017), whereas after adjusting for confounding factors, the OR of MCR exceeded that of MCI (2.488 vs. 2.319). One possible explanation was the higher illiteracy rate in the MCI group compared to the MCR group, as lower education level is an important risk factor for dementia [32]. Given the significant baseline differences between groups, not adjusting for education level may bias the association between MCI and incident dementia. Therefore, the adjusted multivariable logistic regression model employed in our analysis was likely to provide a more accurate estimation of the differential risks of dementia between MCI and MCR.
This study explored the relationship between pre-dementia stages and the risk of new-onset dementia in the elderly Chinese, highlighting the significant impact of their coexistence on dementia progression. Individuals with both MCR and MCI had a significantly higher risk of developing dementia than cognitively healthy individuals or either pre-dementia stage alone. The coexistence of MCR and MCI may have a synergistic effect on cognitive decline, accelerating the onset of dementia. This synergistic effect might, on one hand, reflect the strong association between gait and cognitive function. Previous studies had shown that slow gait speed was associated with declines in episodic memory and executive function [33]. This association might be attributed to age-related degeneration of the neurotransmitter systems in old adults, which could contribute simultaneously to both motor impairments and cognitive decline [34]. On the other hand, dementia is often characterized by multiple brain pathologies [35]. Prior research had demonstrated that MCI might be accompanied by dementia-related neurobiological changes such as β-amyloid deposition [17], while MCR had been associated with frontal-executive dysfunction or cerebral small vessel disease [18]. Therefore, the coexistence of MCR and MCI in old adults may indicate the presence of more extensive brain pathology, which in turn may explain the elevated risk of dementia observed in this group.
Although individuals in the MCR group did not show significant cognitive decline at baseline, long-term follow-up data revealed that this group experienced the most pronounced cognitive deterioration, and their risk of new-onset dementia was even higher than that of the MCI group. This finding underscored the importance of MCR in the early prediction of dementia, warranting greater attention. Furthermore, MCR is not only associated with cognitive decline but has also been shown to increase the risk of adverse outcomes such as falls, dementia, and mortality [31, 36]. Unlike MCI, the diagnosis of MCR does not rely on objective cognitive testing but is based on subjective cognitive decline and gait abnormalities. This characteristic makes MCR easier to identify than MCI in clinical practice, particularly in resource-limited primary healthcare settings. Therefore, promoting MCR screening in China’s primary healthcare system is more feasible than MCI screening, facilitating the early identification of high-risk populations and the development of targeted interventions to prevent or delay the onset of dementia.
This study has several limitations. First, since the CHARLS database sample is drawn from the middle-aged and elderly population in China, the findings may not be generalizable to other regions or ethnic groups. Therefore, further validation of the role of MCR and MCI in dementia development is needed in diverse populations. Second, although we have controlled for several confounding factors in the analysis (such as age, gender, residential area, education level, and marital status), there may still be unmeasured potential confounders, such as genetic factors, environmental exposures, and social support, which might influence the results. Additionally, differences in diagnostic criteria for MCI and dementia across studies may affect the comparability of results between different studies. Thus, future research should further refine diagnostic criteria and incorporate multi-center data to enhance the reliability and generalizability of the findings.
Conclusion
This study provided new evidence for the clinical value of MCR in dementia risk assessment and highlighted the necessity of early screening and intervention in the elderly population of China. In the future, large-scale, multicenter longitudinal studies are needed to validate the predictive efficacy of MCR and explore potential mechanisms, offering a robust scientific foundation for the early prevention of dementia.
Acknowledgements
The authors express sincere gratitude to the China Health and Retirement Longitudinal Study (CHARLS) team for data access and to all study participants for their valuable contributions.
Authors’ contributions
BC.N and D.C designed the research. ZZ.N and BC.N collected and analyzed the data. BC.N and D.C drafted the original manuscript. J.W revised the manuscript. BC.N and D.C contributed equally to this research and should be considered equivalent authors. All authors read and approved the final manuscript.
Funding
Not applicable.
Data availability
The CHARLS study data are publicly available and are open to researchers all over the world. Our study is a secondary analysis conducted by using CHARLS public data. The CHARLS dataset is accessible at http://charls.pku.edu.cn/.
Declarations
Ethics approval and consent to participate
Ethical approval for collecting data on human subjects was obtained and renewed annually at the Peking University Institutional Review Board (IRB00001052-11015). The ethical approval was covered by the original surveys and was not necessary for the present study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Bochao Niu and Dan Chen contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The CHARLS study data are publicly available and are open to researchers all over the world. Our study is a secondary analysis conducted by using CHARLS public data. The CHARLS dataset is accessible at http://charls.pku.edu.cn/.