Sie können Operatoren mit Ihrer Suchanfrage kombinieren, um diese noch präziser einzugrenzen. Klicken Sie auf den Suchoperator, um eine Erklärung seiner Funktionsweise anzuzeigen.
Findet Dokumente, in denen beide Begriffe in beliebiger Reihenfolge innerhalb von maximal n Worten zueinander stehen. Empfehlung: Wählen Sie zwischen 15 und 30 als maximale Wortanzahl (z.B. NEAR(hybrid, antrieb, 20)).
Findet Dokumente, in denen der Begriff in Wortvarianten vorkommt, wobei diese VOR, HINTER oder VOR und HINTER dem Suchbegriff anschließen können (z.B., leichtbau*, *leichtbau, *leichtbau*).
The association between cognitive impairment and oral health or oral hygiene behaviors among multiethnic older adults in Western China: a cross-sectional multicenter study
Older adults with cognitive impairment tend to experience deteriorating oral health and inadequate oral hygiene behaviors, but few studies have addressed interethnic variability. This study aimed to explore the associations between cognitive impairment and oral health or oral hygiene behaviors in multiethnic older adults in Western China.
Methods
We conducted a cross-sectional multicenter study from four provinces of Western China, recruiting multiethnic older adults aged 50 years and older between July and December 2018. Oral health and oral hygiene behaviors were evaluated through an oral examination and a self-made questionnaire, whereas cognitive condition was assessed via the Chinese version of the Short Portable Mental Status Questionnaire (SPMSQ). Three multiple regression models were used to examine the associations between cognitive impairment and oral health or oral hygiene behaviors, with adjustments for relevant variables.
Results
A total of 6529 participants with a median age (interquartile range) of 62.4 (55, 68) years were included. The prevalence of cognitive impairment was 15.4%, with the Yi group having the highest prevalence (28.9%), followed by the Tibetan (19.1%) and Qiang (15.4%) groups. Poorer self-rated oral health, fewer residual teeth, less frequent use of toothbrushes and toothpaste, and irregular dental care were associated with a risk of cognitive impairment (p < 0.05). The SPMSQ scores and correlations between cognitive impairment and oral health or oral hygiene behaviors were heterogeneous among the multiethnic groups.
Conclusion
Inadequate oral hygiene behaviors and deteriorating oral health may be associated with a higher risk of cognitive impairment. Advancing oral health and oral hygiene behaviors is essential for preventing cognitive impairment among multiethnic older adults.
Yuqing Xie, Xin Xia, Xin Tian and Yuexia Hu contributed equally to this work and should be considered co-first authors.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
MCI
Mild cognitive impairment
WCHAT
West China Health and Aging Trend
SPMSQ
Short Portable Mental Status Questionnaire
MNA-SF
Mini Nutrition Assessment Short Form
IQR
Interquartile spacing
95%CI
95% Confidence interval
Background
Cognitive impairment in older adults presents a significant public health challenge amid the accelerating aging of the global population [1]. The global prevalence of mild cognitive impairment (MCI) is estimated at 15.56%, and MCI is considered an intermediate stage between normal aging and dementia [2]. Dementia, the seventh leading cause of death worldwide, imposes a substantial burden on global public health. The number of individuals with dementia is projected to increase from 57.4 million in 2019 to 152.8 million by 2050 [3]. The societal economic burden of Alzheimer's disease and related dementia is projected to increase significantly with global aging, reaching an estimated $16.9 trillion by 2050, encompassing direct medical costs and intangible costs, such as reduced productivity and premature mortality [4]. In the absence of a cure for dementia, early detection of cognitive impairment in older adults, followed by timely intervention, might be the most cost-effective strategy to prevent or delay progression to dementia. Therefore, identifying risk factors associated with cognitive impairment is crucial for preserving cognitive functioning and promoting healthy aging in older adults.
Research on the impact of oral health on the overall health in older adults has been emerging, including its effects on cognitive function [5, 6]. Although studies have indicated an association between cognitive function and oral health (e.g., tooth loss, periodontitis) [7‐9], as well as oral hygiene behaviors (e.g., tooth brushing) [10, 11], the conclusions remain inconsistent [12, 13]. This calls for large-scale, multicenter studies to better establish the link between oral health and cognitive function in older populations.
Anzeige
China accounts for nearly one quarter of the global dementia population [14]. Notably, the western region of China reported a relatively higher overall prevalence of dementia (7.2%) [15] and rate of MCI among older adults (14.33%) [16] than other regions in the country. Fitzpatrick [17] and Gupta et al. [18] reported differences in cognitive status among racial groups in the United States. In fact, China's minority population is mostly concentrated in the western region [19], making it highly representative of the country’s ethnic diversity. Differences in dietary habits [20], religious beliefs [21], educational levels [22], and healthcare resources [23, 24] among ethnic groups may lead to variations in oral hygiene behaviors, which can impact oral health [25, 26]. Therefore, this study focused on older individuals from diverse ethnic backgrounds in Western China, aiming to explore whether their oral health and oral hygiene behaviors are associated with their cognitive health.
This study hypothesized that deteriorating oral health and inadequate oral hygiene behaviors may be associated with cognitive impairment in older adults. We also examined whether ethnicity is a significant factor that influences the relationship between cognitive impairment and oral health or oral hygiene behaviors in Western China. The current study aims to identify modifiable risk factors related to cognitive impairment from the perspective of oral health, which may facilitate enhancing public awareness of oral health for successful aging.
Materials and methods
Study design and sample selection
This cross-sectional study obtained data from the West China Health and Trend (WCHAT) study, a multiethnic, multicenter observational cohort study designed to explore aging and health status in older adults residing in community settings. This study was conducted between July and December 2018. Data were collected by well-trained research staffs. This study was approved by the ethics committees of the West China Hospital of Sichuan University (Number: 2017–445) and was registered at the Chinese Clinical Trial Registry (Number: 1800018895). Informed consent was obtained from all participants before they officially participated in the study. Details of the study have been published elsewhere [27].
A total of 7,536 participants from 18 ethnic groups in Sichuan, Yunnan, Guizhou and Xinjiang Provinces were initially recruited, and 6,529 participants were included based on the following criteria: 1) aged 50 years or older and 2) had no missing data on cognitive function, oral health, oral hygiene behaviors, or other variables (Fig. 1).
Fig. 1
The flowchart of the study participants. (Note: Initially, a total of 7,536 community-dwelling multiethnic Chinese individuals aged 50 years or older were recruited, and 6529 participants were analyzed in this study. Among those excluded, 97 participants were under 50 years old, 619 participants were without cognition data, 186 participants were without covariate data, and 105 participants were without oral health data)
Assessment of oral health and oral hygiene behaviors
Oral health conditions were assessed based on self-reported oral health conditions, the number of residual teeth, and the use of dentures. Oral hygiene behaviors were evaluated through the frequency of toothbrushes, toothpicks, and toothpaste usage, as well as dental history, the latest time of dental care, and the reasons for performing the latest dental care, which are closely related to oral health [28‐30]. The number of residual teeth and denture use were examined by a professional dentist. Furthermore, other data were collected via a self-made oral health and oral hygiene behaviors questionnaire adapted from previous studies [31]. An additional file shows this in more detail [see Additional file 1 (Table A. 1)]. The questionnaire consisted of 9 questions, each with only one possible answer.
Assessment of cognitive health
Cognitive status was evaluated via the Chinese version of the Short Portable Mental Status Questionnaire (SPMSQ), which has been widely used as a well-established scale in the Chinese elderly population [32, 33] and comprises ten items that encompass short-term memory, long-term memory, orientation, and attention. Higher scores on the SPMSQ indicate more severe cognitive impairment. SPMSQ scores were categorized into four levels according to Pfeiffer's criteria [34]: 0–2 errors indicated normal mental functioning, 3–4 errors indicated mild cognitive impairment, 5–7 errors indicated moderate impairment, and 8 or more errors indicated severe impairment. The final score was adjusted based on participants’ educational level.
Covariates
The demographic and living condition information included 1) age, 2) gender, 3) ethnicity (Han, Qiang, Yi, Uyghur, Tibetan, and Others), 4) educational level, 5) occupation (Farmer, Blue-collar, White-collar, Others), 6) spouse status, 7) religious belief, 8) longevity families(parents, grandparents, brothers, sisters and children, if any, aged 90 or over), 9) nutritional status, 10) type of drinking water (Tap water, Well water, Spring water, Others), 11) smoking habits (smoking at least one cigarette daily for a continuous period of six months or longer), 12) alcohol use (at least once a week), and 13) tea-drinking habits (at least four days per week). Ethnic groups with fewer than 200 participants were combined into the "Others" category, including Zhuang, Kyrgyz, Dong, Hui, Mongolian, Miao, Uzbek, Man, Lisu, and Bai. Nutritional status was evaluated via the widely validated and reliable Mini Nutrition Assessment Short Form (MNA-SF) scale [31, 35], with increasing scores indicating malnutrition, risk of malnutrition, and normal nutritional status [36].
Statistical analysis
The one-sample Kolmogorov‒Smirnov test was used to determine the normalized distribution of variables. The data are presented as medians (interquartile ranges, IQRs), means (standard deviations, SDs) or frequencies. Pearson’s chi-square test was used examine the difference in the composition ratio of categorical variables in different cognitive function groups, and the Kruskal‒Wallis H test or one-way analysis of variance (ANOVA) was used to examine the difference of continuous variables in different cognitive function groups. The associations between oral health and oral hygiene behaviors factors and the cognitive score were analyzed via multiple generalized linear regression analyzes via three single models as follows: In Model 1, univariate generalized linear analysis was used without adjustment, followed by further utilization of multivariate generalized linear analysis in Model 2 (adjusted by some nonmodifiable factors, such as age, sex, ethnic group, and longevity families) and in Model 3 (adjusted by some nonmodifiable factors and some modifiable factors, such as educational level, occupation, spouse status, MNA-SF score, MNA-SF assessment status, type of drinking water, history of smoking, history of alcohol use, and history of drinking tea).
To test for differences in ethnic groups, we stratified for ethnic groups and then performed linear regression analysis via the same method as above. R (version 4.1.3) was used for statistical analysis of the data. A two-tailed p < 0.05 was regarded as statistically significant.
Results
The sample characteristics are presented in Table 1 [see the end of the document text file]. Among the included participants, the median (IQR) age was 62.4 (55, 68) years, and 62.5% were women. Finally, 1,005 participants (15.4%) were assessed as having cognitive impairment, and 1,670 (25.6%) were classified as having poor oral health status. Among the different ethnic groups, the Yi group had the highest prevalence of cognitive impairment (28.9%), followed by the Tibetan (19.0%) and “Others” (19.2%) groups. The median (IQR) number of residual teeth was 25 (16, 18). Compared with participants with normal cognitive conditions, those with cognitive impairment had worse self-rated oral health, fewer residual teeth, worse oral hygiene behaviors (i.e., infrequent use of toothbrushes, toothpicks, and toothpaste), and fewer frequent dental visits and receiving dental treatment or dental care (p < 0.05). Additionally, older adults with cognitive impairment were older, more likely to be female, had lower education levels, were more often farmers, were mostly without a spouse, did not have longevity families, had poorer nutritional status, drank more spring water, smoked, drank alcohol, and consumed tea less frequently (p < 0.01), an additional file shows this in more detail [see Additional file 1 (Table A. 2)].
Table 1
Sample characteristics stratified by cognitive function status (n = 6529)
Characteristic, n (%)
All n = 6529 (100%)
Normal n = 5524 (84.6%)
Mild CI n = 722 (11.1%)
Moderate to Severe CI
n = 283 (4.3%)
P value
Age, median (IQR)
62 (55–68)
62 (55–67)
64 (56–71)
66 (59–73)
< 0.001
Age group
< 0.001
50–59
2591 (39.7%)
2270 (41.1%)
249 (34.5%)
72 (25.4%)
60–69
2604 (39.9%)
2244 (40.6%)
263 (36.4%)
97 (34.3%)
70–79
1154 (17.7%)
888 (16.1%)
176 (24.4%)
90 (31.8%)
80 +
180 (2.8%)
122 (2.2%)
34 (4.7%)
24 (8.5%)
Sex
< 0.001
Male
2450 (37.5%)
2230 (40.4%)
172 (23.8%)
48 (17.0%)
Female
4079 (62.5%)
3294 (59.6%)
550 (76.2%)
235 (83.0%)
Ethnic group
< 0.001
Han
2352 (36%)
2131 (38.6%)
173 (24.0%)
48 (17.0%)
Tibetan
1264 (19.4%)
1023 (18.5%)
171 (23.7%)
70 (24.7%)
Qiang
1253 (19.2%)
1060 (19.2%)
152 (21.1%)
41 (14.5%)
Yi
602 (9.2%)
428 (7.7%)
103 (14.3%)
71 (25.1%)
Uyghur
558 (8.5%)
478 (8.7%)
68 (9.4%)
12 (4.2%)
Others
500 (7.7%)
404 (7.3%)
55 (7.6%)
41 (14.5%)
Self-rated oral health
< 0.001
Moderate and good
4859 (74.4%)
4191 (75.9%)
481 (66.6%)
187 (66.1%)
Poor
1670 (25.6%)
1333 (24.1%)
241 (33.4%)
96 (33.9%)
Number of residual teeth, median (IQR)
25 (16–28)
25 (18–28)
22 (9–27)
17 (5–26)
< 0.001
Number of residual teeth
< 0.001
0–8
983 (15.1%)
733 (13.3%)
165 (22.9%)
85 (30.0%)
9–16
713 (10.9%)
553 (10.0%)
107 (14.8%)
53 (18.7%)
17–24
1483 (22.7%)
1253 (22.7%)
179 (24.8%)
51 (18.0%)
25–32
3350 (51.3%)
2985 (54.0%)
271 (37.5%)
94 (33.2%)
Denture usage
0.021
No
4039 (61.9%)
3455 (62.5%)
414 (57.3%)
170 (60.1%)
Yes
2490 (38.1%)
2069 (37.5%)
308 (42.7%)
113 (39.9%)
Toothbrush usage
< 0.001
Never
493 (7.6%)
337 (6.1%)
88 (12.2%)
68 (24.0%)
Occasionally
485 (7.4%)
354 (6.4%)
93 (12.9%)
38 (13.4%)
Everyday
5551 (85%)
4833 (87.5%)
541 (74.9%)
177 (62.5%)
Toothpicks usage
< 0.001
Never
3669 (56.2%)
3044 (55.1%)
415 (57.5%)
210 (74.2%)
Occasionally
1162 (17.8%)
1019 (18.4%)
107 (14.8%)
36 (12.7%)
Everyday
1698 (26%)
1461 (26.4%)
200 (27.7%)
37 (13.1%)
Toothpaste usage
< 0.001
No
703 (10.8%)
501 (9.1%)
117 (16.2%)
85 (30.0%)
Yes
5826 (89.2%)
5023 (90.1%)
605 (83.8%)
198 (70.0%)
Teeth cleaning
0.130
No
6106 (93.5%)
5152 (93.3%)
687 (95.2%)
267 (94.3%)
Yes
423 (6.5%)
372 (6.7%)
35 (4.8%)
16 (5.7%)
History of dental treatment
0.012
No
3141 (48.1%)
2628 (47.6%)
353 (48.9%)
160 (56.5%)
Yes
3388 (51.9%)
2896 (52.4%)
369 (51.1%)
123 (43.5%)
LTDCa
0.029
Never
3141 (48.1%)
2628 (47.6%)
353 (48.9%)
160 (56.5%)
More than 12 months
2555 (39.1%)
2170 (39.3%)
281 (38.9%)
104 (36.7%)
Between 6 and 12 months
336 (5.1%)
294 (5.3%)
34 (4.7%)
8 (2.8%)
Less than 6 months
497 (7.6%)
432 (7.8%)
54 (7.5%)
11 (3.9%)
RLDCb
0.035
Not seeing a dentist
5696 (87.2%)
4798 (86.9%)
634 (87.8%)
264 (93.3%)
Therapy
770 (11.8%)
671 (12.1%)
81 (11.2%)
18 (6.4%)
Consultation or prevention
63 (1%)
55 (1.0%)
7 (1.0%)
1 (0.4%)
Abbreviations:aLTDC Latest time of dental care, bRLDC Reason for latest dental care
The three regression models revealed a significant correlation between oral health and oral hygiene behaviors factors and cognitive impairment, adjusted for nonmodifiable and modifiable factors (Table 2). A significant positive correlation between poor self-rated oral health and cognitive impairment was observed in the three models (model 1: β = 0.291, 95% CI 0.209–0.374; model 2: β = 0.199, 95% CI 0.119–0.278; model 3: β = 0.123, 95% CI 0.050–0.196). Cognitive impairment was negatively associated with the number of residual teeth in the unadjusted model and remained significant in the adjusted models when the number of residual teeth exceeded 16 (model 3: 17–24 group β = −0.132, 95% CI = −0.242–0.023; 25–32 group β = −0.177, 95% CI = −0.281–0.073). Participants who reported a lower frequency of toothbrushes (model 3 β = −0.524, 95% CI −0.650 to −0.398) and toothpaste usage (model 3 β = −0.381, 95% CI −0.488 to −0.273) seemed more prone to cognitive impairment after adjustment. Participants who received dental care within the past 6–12 months had a lower risk of cognitive impairment (model 3: β = −0.176, 95% CI −0.323 to −0.029).
Table 2
Associations between cognitive impairment and oral hygiene behaviors based on the study
Characteristic
Model 1 [β (95%CI)]
Model 2 [β (95%CI)]
Model 3 [β (95%CI)]
Self-rated oral health
Moderate & good
Reference
Poor
0.291 (0.209 to 0.374)
0.199 (0.119 to 0.278)
0.123 (0.050 to 0.196)
Number of residual teeth
0–8
Reference
9–16
−0.200 (−0.342 to −0.059)
−0.104 (−0.242 to 0.034)
0.008 (−0.119 to 0.134)
17–24
−0.485 (−0.603 to −0.366)
−0.327 (−0.446 to −0.208)
−0.132 (−0.242 to −0.023)
25–32
−0.682 (−0.787 to −0.578)
−0.394 (−0.506 to −0.281)
−0.177 (−0.281 to −0.073)
Denture usage
No
Reference
Yes
0.114 (0.039 to 0.188)
−0.036 (−0.120 to 0.039)
−0.050 (−0.118 to 0.018)
Toothbrush usage
Never
Reference
Occasionally
−0.200 (−0.384 to −0.016)
−0.117 (−0.295 to 0.061)
−0.021 (−0.184 to 0.142)
Everyday
−0.835 (−0.970 to −0.700)
−0.671 (−0.806 to −0.535)
−0.524 (−0.650 to −0.398)
Toothpicks usage
Never
Reference
Occasionally
−0.154 (−0.252 to −0.056)
−0.110 (−0.204 to −0.015)
−0.066 (−0.153 to 0.021)
Everyday
−0.193 (−0.278 to −0.107)
−0.137 (−0.220 to −0.053)
−0.064 (−0.141 to 0.013)
Toothpaste usage
No
Reference
Yes
−0.723 (−0.838 to −0.607)
−0.542 (−0.657 to −0.427)
−0.381 (−0.488 to −0.273)
Teeth cleaning
No
Reference
Yes
−0.067 (−0.214 to 0.080)
−0.069 (−0.210 to 0.072)
−0.047 (−0.176 to 0.082)
History of dental treatment
No
Reference
Yes
−0.0130 (−0.085 to 0.060)
−0.052 (−0.122 to 0.019)
−0.042 (−0.107 to 0.023)
Latest time of dental care
Never
Reference
> 12 months
0.011 (−0.067 to 0.088)
−0.033 (−0.109 to 0.042)
−0.025 (−0.094 to 0.045)
6 ~ 12 months
−0.128 (−0.296 to 0.040)
−0.173 (−0.334 to −0.013)
−0.176 (−0.323 to −0.029)
< 6 months
−0.056 (−0.197 to 0.085)
−0.064 (−0.200 to 0.072)
−0.039 (−0.163 to 0.085)
Reason for latest dental care
Not seeing a dentist
Reference
Therapy
−0.080 (−0.192 to 0.032)
−0.085 (−0.192 to 0.023)
−0.077 (−0.177 to 0.020)
Consultation or Prevention
−0.208 (−0.578 to 0.162)
−0.186 (−0.538 to 0.167)
−0.135 (−0.458 to 0.188)
In Model 1, univariate generalized linear analysis was used without adjustment. In Model 2, multivariate generalized linear analysis was adjusted for some nonmodifiable factors, such as age, sex, ethnic group, and longevity families. In Model 3, multivariate generalized linear analysis was adjusted for some nonmodifiable factors and some modifiable factors, such as educational level, occupation, spouse status, MNA-SF score, MNA-SF assessment status, type of drinking water, history of smoking, history of alcohol use, and history of tea consumption
We conducted additional regression analyzes based on different ethnic groups to investigate the disparities in the associations between oral health and oral hygiene behaviors and cognitive impairment (Fig. 2 and Table A. 3 [see Additional file 1]). In most ethnic groups (Han, Tibetan, Yi), cognitive impairment was significantly negatively correlated with the number of residual teeth and toothpaste usage (β < 0, p < 0.05). In the Han, Tibetan, and Qiang groups, poor self-rated oral health was significantly associated with cognitive impairment (β > 0, p < 0.05). In the Han group, participants who did not use dentures (β = −0.156, p = 0.003) and those who used toothbrushes (β = −0.732, p < 0.001) or toothpicks (β = −0.203, p = 0.001) daily had a lower risk of cognitive impairment. Compared with Tibetan participants who brushed their teeth daily, those who never used toothbrushes were more prone to cognitive impairment (β = −0.967, p < 0.001). In the Qiang and Yi groups, participants who used toothpicks had a lower risk of cognitive impairment (Qiang: β = −0.311, p = 0.008; Yi: β = −0.499, p = 0.024). In the Uyghur group, most oral health and oral hygiene behavior factors, except for toothpaste and teeth cleaning, were not significantly associated with cognitive impairment (p > 0.05).
Fig. 2
Relationships between oral health and cognitive impairment in different ethnic groups. (Note: Rhombuses indicate that this group served as the linear regression analysis reference. There was a positive association (β > 0) between oral health risk factors, represented by round marks, and cognitive impairment. There was a negative association (β < 0) between oral health protective factors, represented by square marks, and cognitive impairment. The color represents the negative logarithmic transformation of the p value, with the color turning red as the p value decreases
The disparities of SPMSQ scores among multiethnic older adults are shown in Fig. 3. The error rates for SPMSQ items 1, 2, 4, 6, 7, 8, and 10 were higher and more scattered than those for items 3, 5, and 9 among all ethnic groups with cognitive impairment. Moreover, item 10 had the highest error rate (Fig. 3a). The Yi group generally had the highest error rates across most items, whereas the Uyghur and Han groups had comparatively lower error rates among participants with cognitive impairment. The Uyghur group showed heterogeneous performance across different items, with lower error rates for items 1, 2, and 7 than for the other items in both the mild and moderate to severe cognitive impairment groups. (Fig. 3b and c).
Fig. 3
Radar chart of SPMSQ 10-item error rates among multiethics participants. (Note: Fig. 3a depicts the distribution of error rates on the SPMSQ cognitive dimensions for all participants with cognitive impairment across various ethnic groups. Figure 3b and c show the error rates of the SPMSQ cognitive dimensions in participants with mild and moderate to severe cognitive impairment, respectively. Different colored lines represent the error rates of the SPMSQ items for different ethnic groups)
In this multicenter study of 6,529 older adults from Western China, a robust correlation was found between cognitive impairment and suboptimal oral health, as well as inadequate oral hygiene behaviors. Specifically, older adults with lower self-rated oral health, fewer residual teeth, infrequent use of toothbrushes and toothpaste, and irregular dental care were more vulnerable to cognitive impairment than their counterparts were. Stratified analysis by ethnicity revealed variations in the associations between oral health, oral hygiene behaviors, and cognitive impairment. Significant correlations were primarily observed in the Han, Tibetan, Yi, and Qiang populations but not in the Uyghur group.
Consistent with previous studies suggesting that maintaining more than 20 residual teeth is essential for cognitive health in older adults [37, 38], our findings revealed an independent and negative association between having more than 16 residual teeth and cognitive impairment. These findings support the link between the number of residual teeth and cognitive function in older adults. Previous studies have noted that a lower number of residual teeth can impact both the diversity and quantity of food consumption [39]. Tooth loss may lead older adults to consume fewer fruits, vegetables, nuts and meat [40‐42], which are rich in omega-3 fatty acids, vitamin C, B vitamins, and tyrosine. These nutrients have been demonstrated to have neuroprotective properties [43‐45]. The present study also revealed that poorer nutritional status, reflected by lower MNA-SF scores, was associated with a higher risk of severe cognitive impairment, supporting the hypothesis that nutrition mediates the relationship between oral health and cognitive function [46]. Furthermore, the loss of teeth, particularly posterior occluding teeth, impairs masticatory function in older adults [47], which may adversely affect cerebral blood flow and cognitive performance [48, 49]. Specifically, it has been reported that calculation ability is significantly and independently associated with the number of natural teeth [38]. The current study revealed that most ethnic groups had higher error rates for item 10 (calculation ability) than for the other items did, highlighting the need for longitudinal prospective studies to further explore the causal relationships and mechanisms between the number of teeth and specific cognitive domains. In addition, inadequate use of toothbrushes and toothpaste was associated with cognitive impairment, which is consistent with the findings of previous studies [50, 51]. Poor oral hygiene behaviors may result in the accumulation of dental plaque and disruption of the oral biofilm, ultimately leading to further tooth loss [52, 53], which may contribute to cognitive decline in older adults [54, 55]. Therefore, we propose that oral hygiene behaviors could be a modifiable factor for cognitive maintenance in older adults. Moreover, older adults with cognitive impairment may experience memory problems, attention deficits, and impaired motor skills [56, 57] and may even be unable to express oral discomfort [58, 59], which may hinder the maintenance of adequate oral hygiene behaviors and the timely treatment of oral problems [60], ultimately exacerbating cognitive decline.
Anzeige
Ethnicity, encompassing differences in genomics [61], culture [62], and lifestyle habits [20, 63], may further contribute to the heterogeneity of diseases development and progression [64, 65]. In this study, the prevalence of cognitive impairment varied among ethnic groups: 28.9% in the Yi, 19.1% in the Tibetan, 15.4% in the Qiang, and 14.3% in the Uyghur, all of which were higher than the observed 9.3% prevalence in Han individuals. This disparity may be attributed to lower income levels and a lack of healthcare knowledge among ethnic minorities, compared to the Han population [66, 67]. Additionally, dietary habits may constitute another contributing factor. A 14-year longitudinal study of individuals aged 80 years and above [68] revealed that the regular consumption of fruits, vegetables, meat, and soy products could significantly reduce the risk of cognitive impairment. However, minority groups tend to have less diverse diets and limited access to fresh vegetables, fruits and fish than the Han population does, which may contribute to their higher risk of cognitive impairment [20, 63]. Additionally, the Yi group presented the highest prevalence of cognitive impairment among the ethnic groups, potentially because of their stronger preference for sugary and pickled foods [69] and their more conservative and isolated social activities [70]. In contrast, Uyghurs had a lower prevalence of cognitive impairment, particularly in terms of temporal orientation questions, which may be attributed to 1) a higher educational level [71], 2) the unique role of the Uyghur language in brain plasticity [72], and 3) the higher proportion of archaic introgression segments relative to other minorities [61], all of which may benefit the maintenance of cognitive functioning. Genetic differences may also account for the lack of significant correlations between cognitive impairment and oral health or oral hygiene behaviors among Uyghurs. Furthermore, it is important to consider that the oral microbiome affects both oral health [73] and cognitive function [74]. Compared with Han and Tibetan individuals, Uyghurs have different oral colonizing bacterial species [75], which could impact cognition as well as oral health.
Moreover, older adults with advanced age, lower educational levels, primary engagement in farming, single status, absence of longevity families, poorer nutritional status, higher consumption of spring water, and lower tea consumption were found to have a higher risk of cognitive impairment. Notably, older adults with longevity families appear to have a lower incidence of cognitive impairment than their counterparts do, which could be partially explained by genetics [76] or family lifestyles [77]. In this study, individuals with cognitive impairment were less likely to report a history of smoking and alcohol use, which contrasts with findings from previous reports [78, 79]. However, some studies have not identified a significant association between cognition and smoking or alcohol consumption [79, 80], highlighting a research gap in understanding these relationships. Although a European multinational cohort study [81] reported that religious rituals and prayers are associated with better cognitive functioning, our study did not find a significant relationship between religious belief and cognitive impairment. These conflicting findings may arise from variations in religious practices and the age at which individuals are exposed to religious education.
Previous studies have predominantly examined the association between the oral microbiome and dementia, with relatively little focus on the relationship between early cognitive impairment and oral health or oral hygiene behaviors. This study, which targeted multiethnic older adults in Western China, explored the correlations between different domains of mild to moderate cognitive impairment and oral health or oral hygiene behaviors from the perspective of preventive healthcare. Our findings suggest that healthcare providers should routinely screen older adults for cognitive function and oral health. Additionally, the study advocated incorporating these medical services into basic health insurance plans, thereby extending coverage to older adults residing in remote and multiethnic regions. Finally, this study has several limitations. First, the cross-sectional design cannot establish a causal relationship between cognitive impairment and oral health or oral hygiene behaviors. Second, limited information on cultural, socioeconomic, and lifestyle factors necessitates caution when interpreting differences among ethnic groups. Third, the potential role of participants' income in relation to cognition was limited by its lack of inclusion. However, collecting income information is challenging because of its sensitive and private nature, particularly in many Asian countries [82]. Fourth, given that our WHCAT cohort initially included a large sample size of 7,536 older adults, many indicators were assessed via simple and rapid tools (e.g., oral health and oral hygiene behavior variables and general cognition measured by the SPMSQ), which may limit the robustness of these findings to some extent. Therefore, future studies should incorporate long-term longitudinal follow-ups, combining both quantitative and qualitative methods, while collecting detailed cultural variables related to customs among minority groups. Additionally, including income variables, objective oral examinations (e.g., salivary microbiota and periodontal disease), and comprehensive cognitive assessments (e.g., neuropsychological assessment battery [83]) would enrich the study’s content and strengthen the evidence.
Conclusions
Inadequate oral hygiene behaviors and poor oral health are associated with cognitive impairment in multiethnic groups in Western China, with some degree of ethnic heterogeneity. Significant variations in the prevalence of cognitive impairment were also observed among these groups, potentially influenced by factors such as dietary habits and education levels. Therefore, exploring factors related to ethnic variability and promoting oral health and oral hygiene behaviors could be an alternative approach to preventing cognitive impairment among multiethnic older adults.
Anzeige
Acknowledgements
The authors would like to thank all the clinicians who participated in the study.
Declarations
Ethics approval and consent to participate
The study was approved by The Ethical Review Committee of West China Hospital of Sichuan University (approval number 2017[445]). The study was conducted in accordance with ethical standards established in the 1964 Declaration of Helsinki and its later amendments. All participants provided written informed consent prior to participating in the study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Anzeige
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The association between cognitive impairment and oral health or oral hygiene behaviors among multiethnic older adults in Western China: a cross-sectional multicenter study
Verfasst von
Yuqing Xie
Xin Xia
Xin Tian
Yuexia Hu
Yun Li
Xiao Tan
Wenwen Wu
Birong Dong
Yanyan Wang
Livingston G, Huntley J, Liu KY, Costafreda SG, Selbæk G, Alladi S, et al. Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission. Lancet. 2024;404(10452):572–628.PubMedCrossRef
2.
Bai W, Chen P, Cai H, Zhang Q, Su Z, Cheung T, et al. Worldwide prevalence of mild cognitive impairment among community dwellers aged 50 years and older: a meta-analysis and systematic review of epidemiology studies. Age Ageing. 2022;51(8):afac173.PubMed
3.
GBD 2019 Dementia Forecasting Collaborators. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. Lancet Public Health. 2022;7(2):e105-e125.
4.
Nandi A, Counts N, Chen S, Seligman B, Tortorice D, Vigo D, et al. Global and regional projections of the economic burden of Alzheimer’s disease and related dementias from 2019 to 2050: a value of statistical life approach. EClinicalMedicine. 2022;51:101580.PubMedPubMedCentralCrossRef
5.
Dibello V, Lobbezoo F, Solfrizzi V, Custodero C, Lozupone M, Pilotto A, et al. Oral health indicators and bone mineral density disorders in older age: a systematic review. Ageing Res Rev. 2024;100:102412.PubMedCrossRef
6.
Dibello V, Lobbezoo F, Lozupone M, Sardone R, Ballini A, Berardino G, et al. Oral frailty indicators to target major adverse health-related outcomes in older age: a systematic review. Geroscience. 2023;45(2):663–706.PubMedCrossRef
7.
Li L, Zhang Q, Yang D, Yang S, Zhao Y, Jiang M, et al. Tooth loss and the risk of cognitive decline and dementia: A meta-analysis of cohort studies. Front Neurol. 2023;14:1103052.PubMedPubMedCentralCrossRef
8.
Qi X, Zhu Z, Plassman BL, Wu B. Dose-response meta-analysis on tooth loss with the risk of cognitive impairment and dementia. J Am Med Dir Assoc. 2021;22(10):2039–45.PubMedPubMedCentralCrossRef
9.
Beydoun HA, Hossain S, El-Hajj ZW, Weiss J, Zonderman AB. Clinical and Bacterial Markers of Periodontitis and Their Association with Incident All-Cause and Alzheimer’s Disease Dementia in a Large National Survey. J Alzheimers Dis. 2020;75(1):157–72.PubMedPubMedCentralCrossRef
10.
Zhu Z, Yang Z, Qi X, Mao W, Pei Y, Wu B. Association between oral hygiene behaviours and cognitive decline in adults: a systematic review and meta-analysis. J Adv Nurs. 2024. https://doi.org/10.1111/jan.16525.
11.
Yang Y, Liang L, Cai J, You J, Liao X. Improving oral hygiene for better cognitive health: Interrelationships of oral hygiene habits, oral health status, and cognitive function in older adults. J Adv Nurs. 2024;80(1):275–86.PubMedCrossRef
12.
Tuuliainen E, Autonen-Honkonen K, Nihtilä A, Komulainen K, Nykänen I, Hartikainen S, et al. Oral health and hygiene and association of functional ability: a cross-sectional study among old home care clients. Oral Health Prev Dent. 2020;18(2):253–62.PubMed
13.
Barbe AG, Küpeli LS, Hamacher S, Noack MJ. Impact of regular professional toothbrushing on oral health, related quality of life, and nutritional and cognitive status in nursing home residents. Int J Dent Hyg. 2020;18(3):238–50.PubMedCrossRef
14.
GBD 2016 Dementia Collaborators. Global, regional, and national burden of Alzheimer's disease and other dementias, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(1):88-106.
15.
Wu YT, Ali GC, Guerchet M, Prina AM, Chan KY, Prince M, et al. Prevalence of dementia in mainland China, Hong Kong and Taiwan: an updated systematic review and meta-analysis. Int J Epidemiol. 2018;47(3):709–19.PubMedPubMedCentralCrossRef
16.
Xue J, Li J, Liang J, Chen S. The prevalence of mild cognitive impairment in china: a systematic review. Aging Dis. 2018;9(4):706–15.PubMedPubMedCentralCrossRef
17.
Fitzpatrick AL, Rapp SR, Luchsinger J, Hill-Briggs F, Alonso A, Gottesman R, et al. Sociodemographic Correlates of Cognition in the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Geriatr Psychiatry. 2015;23:684–97.PubMedPubMedCentralCrossRef
18.
Gupta S. Racial and ethnic disparities in subjective cognitive decline: a closer look, United States, 2015–2018. BMC Public Health. 2021;21(1):1173.PubMedPubMedCentralCrossRef
Xiao X, Qin Z, Lv X, Dai Y, Ciren Z, Yangla Y, et al. Dietary patterns and cardiometabolic risks in diverse less-developed ethnic minority regions: results from the China Multi-Ethnic Cohort (CMEC) Study. Lancet Reg Health West Pac. 2021;15: 100252.PubMedPubMedCentral
21.
Ying Z, Liu S, Bao S, Zhou J. Religious diversity and regional development in China. China Econ Rev. 2017;46:1–9.CrossRef
22.
Chia T, Hruschka D. Educational & income disparities among ethnic minorities of China. Int J Educ Dev. 2023;102: 102846.CrossRef
23.
Yang G, Wan X. Measuring progress in health in China and its provinces. Lancet. 2019;394(10204):1115–6.PubMedCrossRef
24.
Wang YJ, Chen XP, Chen WJ, Zhang ZL, Zhou YP, Jia Z. Ethnicity and health inequalities: an empirical study based on the 2010 China survey of social change (CSSC) in Western China. BMC Public Health. 2020;20(1):637.PubMedPubMedCentralCrossRef
25.
Madera M, Delgado-Angulo EK, Bashir NZ, Bernabe E. The intersections of socioeconomic position, gender, race/ethnicity and nationality in relation to oral conditions among American adults. Commun Dent Oral Epidemiol. 2023;51:644–52.CrossRef
26.
Wu SC, Ma XX, Zhang ZY, Lo ECM, Wang X, Wang B, et al. Ethnic disparities in dental caries among adolescents in China. J Dent Res. 2021;100(5):496–506.PubMedCrossRef
27.
Hou L, Liu X, Zhang Y, Zhao W, Xia X, Chen X, et al. Cohort profile: West China Health and Aging Trend (WCHAT). J Nutr Health Aging. 2021;25:302–10.PubMedCrossRef
28.
Reyes Garita P, Tran VT, Chatzopoulou E, Toko-Kamga L, Bouchard P, Carra MC. Oral hygiene behaviors and periodontitis among patients with chronic diseases and its impact on tooth loss and oral health-related quality of life: a cross-sectional study of data from the ComPaRe e-cohort. Clin Oral Investig. 2024;28(10):518.PubMedCrossRef
29.
Harnacke D, Stein K, Stein P, Margraf-Stiksrud J, Deinzer R. Training in different brushing techniques in relation to efficacy of oral hygiene in young adults: a randomized controlled trial. J Clin Periodontol. 2016;43(1):46–52.PubMedCrossRef
30.
Chang Y, Woo HG, Lee JS, Song TJ. Better oral hygiene is associated with lower risk of stroke. J Periodontol. 2021;92(1):87–94.PubMedCrossRef
31.
Dye BA, Afful J, Thornton-Evans G, Iafolla T. Overview and quality assurance for the oral health component of the National Health and Nutrition Examination Survey (NHANES). BMC Oral Health. 2019;19:95.PubMedPubMedCentralCrossRef
32.
Wang YY, Yue JR, Xie DM, Carter P, Li QL, Gartaganis SL, et al. Effect of the tailored, family-involved hospital elder life program on postoperative delirium and function in older adults: a randomized clinical trial. JAMA Intern Med. 2020;180(1):17–25.PubMedCrossRef
33.
Kojaie-Bidgoli A, Fadayevatan R, Sharifi F, Alizadeh-Khoei M, Vahabi Z, Aminalroaya R. Applicability of SPMSQ in illiterate outpatients in clinics: the validity and reliability of the short portable mental status questionnaire. Appl Neuropsychol Adult. 2022;29(4):591–7.PubMedCrossRef
34.
Chen TC, Lee YC, Wang YC, Hsieh TL, Chen MH. A comparison of test-retest reliability and practice effects of short portable mental state questionnaire and montreal cognitive assessment in patients with stroke. J Geriatr Psychiatry Neurol. 2025;38(1):53–61.PubMedCrossRef
35.
Wei K, Nyunt MS, Gao Q, Wee SL, Yap KB, Ng TP. Association of frailty and malnutrition with long-term functional and mortality outcomes among community-dwelling older adults: results from the Singapore longitudinal aging study 1. JAMA Netw Open. 2018;1(3):e180650.PubMedPubMedCentralCrossRef
36.
Kaluźniak-Szymanowska A, Krzymińska-Siemaszko R, Lewandowicz M, Deskur-Śmielecka E, Stachnik K, Wieczorowska-Tobis K. Diagnostic performance and accuracy of the MNA-SF against GLIM Criteria in community-dwelling older adults from Poland. Nutrients. 2021;13(7):2183.PubMedPubMedCentralCrossRef
37.
Yang H-L, Li F-R, Chen P-L, Cheng X, Mao C, Wu X-B. Tooth loss, denture use, and cognitive impairment in chinese older adults: a community cohort study. J Gerontol A Biol Sci Med Sci. 2022;77:180–7.PubMedCrossRef
38.
Kato H, Takahashi Y, Iseki C, Igari R, Sato H, Sato H, et al. Tooth loss-associated cognitive impairment in the elderly: a community-based study in Japan. Intern Med. 2019;58:1411–6.PubMedPubMedCentralCrossRef
39.
Kossioni AE. The association of poor oral health parameters with malnutrition in older adults: a review considering the potential implications for cognitive impairment. Nutrients. 2018;10:1709.PubMedPubMedCentralCrossRef
40.
Logan D, McEvoy CT, McKenna G, Kee F, Linden G, Woodside JV. Association between oral health status and future dietary intake and diet quality in older men: The PRIME study. J Dent. 2020;92:103265.PubMedCrossRef
41.
Shen J, Qian S, Huang L, Tao Y, Chen H, Deng K, et al. Association of the number of natural teeth with dietary diversity and nutritional status in older adults: A cross-sectional study in China. J Clin Periodontol. 2023;50(2):242–51.PubMedCrossRef
42.
Kühn S, Düzel S, Colzato L, Norman K, Gallinat J, Brandmaier AM, et al. Food for thought: association between dietary tyrosine and cognitive performance in younger and older adults. Psychol Res. 2019;83(6):1097–106.PubMedCrossRef
Gil Martínez V, Avedillo Salas A, Santander BS. Vitamin supplementation and dementia: a systematic review. Nutrients. 2022;14(5):1033.PubMedPubMedCentralCrossRef
45.
Hensel C, Becker M, Düzel S, Demuth I, Norman K, Steinhagen-Thiessen E, et al. Influence of nutritional tyrosine on cognition and functional connectivity in healthy old humans. Neuroimage. 2019;193:139–45.PubMedCrossRef
46.
Li Y, Xia X, Wu W, Tian X, Hu Y, Dong B, et al. The mediating effects of nutritional status on the relationship between number of residual teeth and cognitive function among older adults: a cross-sectional multicenter study. Nutrients. 2023;15:3089.PubMedPubMedCentralCrossRef
47.
Kim HE, Lee H. Factors affecting subjective and objective masticatory function in older adults: Importance of an integrated approach. J Dent. 2021;113:103787.PubMedCrossRef
48.
Wang X, Hu J, Jiang Q. Tooth loss-associated mechanisms that negatively affect cognitive function: a systematic review of animal experiments based on occlusal support loss and cognitive impairment. Front Neurosci. 2022;16:811335.PubMedPubMedCentralCrossRef
49.
Asher S, Suominen AL, Stephen R, Ngandu T, Koskinen S, Solomon A. Association of tooth location, occlusal support and chewing ability with cognitive decline and incident dementia. J Clin Periodontol. 2024. https://doi.org/10.1111/jcpe.13970.
50.
Jockusch J, Hopfenmüller W, Nitschke I. Influence of cognitive impairment and dementia on oral health and the utilization of dental services : Findings of the Oral Health, Bite force and Dementia Study (OrBiD). BMC Oral Health. 2021;21(1):399.PubMedPubMedCentralCrossRef
51.
Gil-Montoya JA, Sánchez-Lara I, Carnero-Pardo C, Fornieles-Rubio F, Montes J, Barrios R, et al. Oral hygiene in the elderly with different degrees of cognitive impairment and dementia. J Am Geriatr Soc. 2017;65:642–7.PubMedCrossRef
52.
Shin NR, Choi JS. Manual dexterity and dental biofilm accumulation in independent older adults without hand disabilities: A cross-sectional study. Photodiagnosis Photodyn Ther. 2019;25:74–83.PubMedCrossRef
53.
Kramer A, Splieth C. Health promotion through structured oral hygiene and good tooth alignment. GMS Hyg Infect Control. 2022;17:Doc08.PubMedPubMedCentral
54.
Sureda A, Daglia M, Argüelles Castilla S, Sanadgol N, Fazel Nabavi S, Khan H, et al. Oral microbiota and Alzheimer’s disease: Do all roads lead to Rome? Pharmacol Res. 2020;151:104582.PubMedCrossRef
55.
Shoemark DK, Allen SJ. The microbiome and disease: reviewing the links between the oral microbiome, aging, and Alzheimer’s disease. J Alzheimer’s Dis. 2015;43:725–38.CrossRef
56.
Curreri C, Trevisan C, Carrer P, Facchini S, Giantin V, Maggi S, et al. Difficulties with fine motor skills and cognitive impairment in an elderly population: the Progetto Veneto Anziani. J Am Geriatr Soc. 2018;66(2):350–6.PubMedCrossRef
57.
Schmidt LI, Wahl HW. Predictors of performance in everyday technology tasks in older adults with and without mild cognitive impairment. Gerontologist. 2019;59(1):90–100.PubMedCrossRef
58.
Chen X, Clark JJ, Chen H, Naorungroj S. Cognitive impairment, oral self-care function and dental caries severity in community-dwelling older adults. Gerodontology. 2015;32(1):53–61.PubMedCrossRef
59.
Alsaleh A, Kapila A, Shahriar I, Kapila YL. Dental informed consent challenges and considerations for cognitively impaired patients. Periodontol 2000. 2021;87(1):43.PubMedPubMedCentralCrossRef
60.
Rozas NS, Sadowsky JM, Jeter CB. Strategies to improve dental health in elderly patients with cognitive impairment: A systematic review. J Am Dent Assoc. 2017;148(4):236-245.e3.PubMedCrossRef
61.
Gao Y, Yang X, Chen H, Tan X, Yang Z, Deng L, et al. A pangenome reference of 36 Chinese populations. Nature. 2023;619(7968):112–21.PubMedPubMedCentralCrossRef
62.
He S. An overview of China’s ethnic groups and their interactions. Sociology Mind. 2017;7:1–10.CrossRef
63.
Wang Z, Mashford-Pringle A. Nutritional Challenges and Dietary Practices of Ethnic Minority (Indigenous) Groups in China: A Critical Appraisal [J]. Frontiers in Sustainable Food Systems. 2022;6: 867848.CrossRef
64.
Huisman BJMV, Agyemang C, van den Born BH, Peters RJG, Snijder MB, Vogt L. Discrepancies in estimated glomerular filtration rate and albuminuria levels in ethnic minority groups - The multiethnic HELIUS cohort study. EClinicalMedicine. 2022;45: 101324.PubMedPubMedCentralCrossRef
65.
Perini W, Snijder MB, Peters RJ, Kunst AE, van Valkengoed IG. Estimation of cardiovascular risk based on total cholesterol versus total cholesterol/high-density lipoprotein within different ethnic groups: The HELIUS study. Eur J Prev Cardiol. 2019;26(17):1888–96.PubMedPubMedCentralCrossRef
66.
Hu H, Xu Y, Shao Y, et al. A latent profile analysis of residents’ knowledge, attitude, and practice toward common chronic diseases among ethnic minority area in China. Front Public Health. 2022;10: 940619.PubMedPubMedCentralCrossRef
67.
Li Y, Nima Q, Yu B, Liang Y, Wang Q, Luo S, et al. Determinants of self-rated health among an older Tibetan population in a Chinese plateau area: analysis based on the conceptual framework for determinants of health. BMC Public Health. 2021;21(1):489.PubMedPubMedCentralCrossRef
68.
An R, Liu G, Khan N, Yan H, Wang Y. Dietary Habits and Cognitive Impairment Risk Among Oldest-Old Chinese. J Gerontol B Psychol Sci Soc Sci. 2019;74(3):474–83.PubMedCrossRef
69.
ZENG Susu, MENG Qiong, ZHANG Xue-hui. Prevalence and risk factors of healthy lifestyle among 30 – 79 years old Yi ethnic residents i n Chuxiong Yi Autonomous Prefecture, Yunnan province: a cross-sectional survey in 2019. Chin J Public Health. 2022;38(7):876–878.
70.
Lai AH-Y, Chui CHK, Hausmann-Stabile C, Yao H, Wong JKY, Di S. Ethnic identity in school context: The case of Yi ethnic minority adolescents in rural China. Child Soc. 2024;38(1):176–96.CrossRef
71.
Ge M, Zhang Y, Zhao W, Yue J, Hou L, Xia X, et al. Prevalence and Its Associated Factors of Physical Frailty and Cognitive Impairment: Findings from the West China Health and Aging Trend Study (WCHAT). J Nutr Health Aging. 2020;24(5):525–33.PubMedCrossRef
72.
Lu J, Jiang C, Wang J, Jia W. Comprehensive cortical thickness and surface area comparison between young Uyghur and Han Chinese cohorts. Magn Reson Imaging. 2016;34:1043–9.PubMedCrossRef
73.
Gao L, Xu T, Huang G, Jiang S, Gu Y, Chen F. Oral microbiomes: more and more importance in oral cavity and whole body. Protein Cell. 2018;9(5):488–500.PubMedPubMedCentralCrossRef
74.
Jungbauer G, Stähli A, Zhu X, Auber Alberi L, Sculean A, Eick S. Periodontal microorganisms and Alzheimer disease - A causative relationship? Periodontol 2000. 2022;89(1):59–82.PubMedPubMedCentralCrossRef
75.
Li BB, Wu ZY, Yang T, Cao HF, Dong Y, Zhao Y. The dominant bacterial communities in the oral saliva of children among three nationalities in Bozhou. Xinjiang Chin J Microecol. 2019;31(03):310–4.
76.
Inglés M, Belenguer-Varea A, Serna E, Mas-Bargues C, Tarazona-Santabalbina FJ, Borrás C, Vina J. Functional Transcriptomic Analysis of Centenarians’ Offspring Reveals a Specific Genetic Footprint That May Explain That They Are Less Frail Than Age-Matched Noncentenarians’ Offspring. J Gerontol A Biol Sci Med Sci. 2022;77(10):1931–8.PubMedCrossRef
77.
Jin X, He W, Zhang Y, Gong E, Niu Z, Ji J, et al. Association of APOE ε4 genotype and lifestyle with cognitive function among Chinese adults aged 80 years and older: A cross-sectional study. PLoS Med. 2021;18(6):e1003597.PubMedPubMedCentralCrossRef
78.
Bahorik AL, Sidney S, Kramer-Feldman J, Jacobs DR Jr, Mathew AR, Reis JP, et al. Early to midlife smoking trajectories and cognitive function in middle-aged US adults: the CARDIA study. J Gen Intern Med. 2022;37(5):1023–30.PubMedCrossRef
79.
Yen FS, Wang SI, Lin SY, Chao YH, Wei JC. The impact of heavy alcohol consumption on cognitive impairment in young old and middle old persons. J Transl Med. 2022;20(1):155.PubMedPubMedCentralCrossRef
80.
Sun X, Harris KE, Hou L, Xia X, Liu X, Ge M, et al. The prevalence and associated factors of motoric cognitive risk syndrome in multiple ethnic middle-aged to older adults in west China: a cross-sectional study. Eur J Neurol. 2022;29(5):1354–65.PubMedCrossRef
81.
Ahrenfeldt LJ, Stripp TA, Möller S, Viftrup DT, Nissen RD, Hvidt NC. Cognitive function among religious and non-religious Europeans: a cross-national cohort study. Aging Ment Health. 2024;28(3):502–510.
82.
Antonoplis S. Studying Socioeconomic Status: Conceptual Problems and an Alternative Path Forward. Perspect Psychol Sci. 2023;18(2):275–92.PubMedCrossRef
83.
Lace JW, Grant AF, Ruppert P, Kaufman DAS, Teague CL, Lowell K, et al. Detecting noncredible performance with the neuropsychological assessment battery, screening module: A simulation study. Clin Neuropsychol. 2021;35(3):572–96.PubMedCrossRef