Association of Qi-stagnation and Subjective Sleep Characteristics with Mild Cognitive Impairment Among Non-depressed Elderly in Community: A Cross-Sectional Study


 Objective: Depression and sleep disturbance is commonly reported in patients with mild cognitive impairment (MCI). However, it remains unclear whether Qi-stagnation is still a risk factor for MCI before the older adults suffer from depression. The purpose of this study was to examine the association between Qi-stagnation and subjective sleep quality with MCI among non-depressed elderly in the Chinese community.Methods: A simple random sampling method was used to abstract research subjects from 34 community elderly day care centers in Fuzhou city based on their electronic health records from March 2019 to December 2020. Intensive face-to-face interviews were conducted using tools such as Montreal cognitive function assessment, AD8 dementia screening questionnaire, Pittsburgh Sleep Quality Index, and TCM constitution assessment scale, among others to analyze the proportion of older adults with MCI who suffer from sleep disturbance and Qi-stagnation in the community. Multi-factor logistical regression was employed to analyze the association among subjective sleep quality, TCM constitution, and MCI.Results: A total of 1,268 subjects were investigated and 1,071 cases were included in this study, among which 314 cases were of MCI patients, with a morbidity of 29.3%. The proportion of individuals having Qi-deficiency (12.4%) and Qi-stagnation (11.1%) was higher in MCI patients than in the controls with normal cognitive function (P<0.05). After adjusting for age, gender, and years of education, the probability of the old with Qi-deficiency and Qi-stagnation suffering from MCI was 1.559 times [95% confidence interval (CI): 1.009–2.407] and 1.706 times (95% CI: 1.078–2.700) higher than that of the older adults without Qi-deficiency and Qi-stagnation, respectively. In the Pittsburgh sleep quality index (PSQI) scale, individuals with MCI had poorer subjective sleep quality (Z=-3.404, P=0.001), longer sleep latency (Z=-3.398, P=0.001), shorter sleep duration (Z=-2.237, P=0.025), and aggravated daytime dysfunction (Z=-3.723, P<0.001) compared with those without MCI. The intergroup differences showed no statistical significance in the three dimensions including habitual sleep efficiency, sleep disturbance, and hypnotics between groups. The results of multi-factor logistical regression showed that sleep latency [odds ratio (OR)=1.168, 95% CI: 1.016–1.342], daytime dysfunction (OR=1.261, 95% CI: 1.087–1.463), and Qi-stagnation (OR=1.449, 95% CI: 1.022–2.055) were the risk factors for MCI; the OR for older adults with sleep disturbance and Qi-stagnation suffering from MCI was 2.581 (95% CI 1.706–3.907).Conclusion: MCI patients have a higher incidence of sleep disorders and Qi-stagnation, and may show specific changes in their daytime and nighttime sleep characteristics, with the specific manifestations such as difficulty in falling asleep, easily waking up at night/ early morning, and daytime dysfunction, among others.


Introduction
Patients with mild cognitive impairment (MCI) are at a high risk of developing Alzheimer's disease (AD) and other forms of dementia. In the current situation, given that dementia cannot be cured, early Page 3/22 prevention and control of the risk factors for cognitive decline are of particular importance. Previous studies have discovered that sleep quality is closely associated with MCI [1]. Levels of biomarkers, such as Aβ, tau, brain cell damage, and in ammation, are increased in the cerebrospinal uid of AD patients with poor sleep quality, sleep disturbance, and daytime sleepiness [2]. Tranah et al. [3] conducted a longitudinal study including 1,282 healthy females in the American communities and found that elderly women with reduced activity rhythms (OR = 1.57; 95% CI: 1.09-2.25) are more likely to suffer from dementia or MCI. However, because of limitations concerning the extrapolation of factors such as race and gender, the observational studies on sleep characteristics and MCI in the Chinese elderly population need further in-depth investigation.
Differences in TCM constitutions affect the susceptibility of older adults to pathogenic factors and the tendency of disease morbidity, determining the association between a particular constitution and cognitive impairment [4]. Previous studies have indicated that Qi-stagnation in Chinese medicine is a constitution associated with a higher risk of depression and sleep disturbance [5]. At present, a bidirectional relationship between depression and sleep disturbance have been fully demonstrated, which has a de nite connection with the subsequent decline in cognitive function. However, it remains unclear whether Qi-stagnation is still a risk factor for MCI before the older adults suffer from depression. If so, the speci c sleep characteristics of the circadian rhythm that are associated with Qi-stagnation in older adults and their relationship with MCI are unclear.
To better clarify the association of Qi-stagnation and sleep quality with MCI, we investigated subjective sleep quality, Qi-stagnation exposure, and cognitive function level in older adults of the community of China. The research objectives were as follows: (1) to compare the incidence rate of sleep disturbance and Qi-stagnation in MCI patients in contrast with that in individuals with normal cognition; (2) to analyze the subjective sleep characteristics of patients with MCI and investigate the association of overall sleep quality, daytime dysfunction, time in bed, sleep duration, sleep disruption, and other characteristics with diseases of cognitive function as well as in uencing factors. These ndings will enrich the theoretical connotation of biased constitution-induced disease in TCM, and provide a basis for the medical personnel to formulate early prevention and treatment strategies for "adjustable constitution", thus improving the sleep quality of the MCI population and delaying disease exacerbation.

Study design
This study is a cross-sectional survey. Based on the estimated sample size of the survey, a simple random sampling method was used to interview and investigate 34 community day care centers under the jurisdiction of Fuzhou City, Fujian Province, and 30-40 cases of elderly individuals were randomly selected from the health records of each day care center in the community. If the following situations occurred, re-sampling was conducted: (1) the selected individuals refuse to participate; (2) the archival information is old or false; or (3) the selected individuals have died and therefore, the corresponding individuals cannot be contacted.

Study subjects
Individuals aged55-75 years; those with permanent residence in communities of Fuzhou; those having normal activities of daily living and self-care or basic self-care ability; and those able to understand and cooperate, voluntarily participate, and sign the informed consent form were included in the analysis.
The exclusion criteria were as follows: (1) GDS-15 > 8 points [6], or a history of depression; (2) presence of brain tumors, Parkinson's disease, or other unstable internal medical diseases that can affect brain function or the assessment of cognitive function; (3) an acute disease history within the past 3 months; (4) current diagnosis of active epilepsy; (5) secondary disturbance of sleeping-waking rhythms caused by somatic diseases or mental disorders; and (6) rejection or poor cooperation with the research.
MCI diagnostic criteria were as follows [7]: (1) cognitive impairment reported by patients or informant, or detected by experienced clinicians; (2) objective evidence of impairments in one or more cognitive elds (from cognitive testing); (3) slight impairments in complex instrumental activities of daily living, but maintenance of the ability to independently lead daily life; and (4) No current diagnosis of dementia.

Sample size estimation
According to the literature, the prevalence rate of cognitive impairment in older adults staying at home and in nursing institutions for the aged in Fuzhou is 30.17% [8]. The test level α was set at 0.05, and the permissible error δ was 3%. The sample size according to the calculation formula was about 931 subjects. Considering the possibility that 15% of survey data are incomplete, the survey sample size was accordingly adjusted to be approximately 1,071.
The calculation formula for sample size is Evaluation item (1) General survey Demographic data: age, gender, ethnicity, years of education, marital status, current state of residence, status of work, etc.
Behavior and lifestyle: diet structure, sports activities, social participation, etc. Health status: This included self-reported smoking and drinking status, past medical history, and medication use and height, weight, BMI, and blood pressure as measured by the assessors.
The cardiovascular risk scoring was conducted according to the "Chinese ICVD 10-year Morbidity Risk Assessment Form" recommended in Chinese Cardiovascular Disease Prevention Guidelines [9]. Based on the levels of seven risk factors of subjects (age, gender, systolic blood pressure, body mass index, hypercholesterolemia, smoking status, and diabetes status), the total scores for cardiovascular risks were calculated.
(2) Cognitive function assessment MoCA scale of Fuzhou version: The MoCA scale of Fuzhou version that has passed the reliability and validity test [10] was used to assess the subjects' cognitive function in a face-to-face interview, involving eight cognitive elds: executive function, visual space structure, memory, attention, speech uency, abstract ability, calculation ability, and orientation ability. The total score for the scale is 30 points; ≥24 points, and 19-24 points if the years of education are ≤6 years, indicate normal cognition, and 14-19 points indicate MCI [11].
AD8 Dementia Screening Scale: The AD8 Dementia Screening Scale was compiled by the University of Washington in 2005, which involves a total of eight items [12]. In its Chinese version, ≥2 points is considered as the cut-off value for cognitive dysfunction, with the sensitivity of 85.7% and the speci city of 77.6% [13]. The Chinese version of AD8 quicker and is convenient for the elderly to understand and selfassess. Accordingly, it is widely applied in non-specialist medical institutions such as communities and general medicine.

(3) Instrumental activity of daily living
The scale is compiled by Lawton et al., with good reliability and validity [14]. The scale involves eight items such as phone use, shopping, food cooking, housekeeping, clothes washing, transportation, drug administration, and nancial management. The total score ranges between 0 and 23. The higher the score, the more complete the ability of daily living. A score that is 2 standard deviations less than the norm indicates that the ability of daily living is severely impaired [15].

(4) Subjective sleep quality assessment
The subjects completed the assessment of the Pittsburgh Sleep Quality Index (PSQI) through selfassessment [16]. Its Chinese version has passed the reliability and validity test [17]. The PSQI scale is composed of 19 self-assessment items, constituting seven dimensions such as sleep quality, sleep latency, sleep duration, habitual sleep e ciency, sleep disturbance, hypnotics, and daytime dysfunction. Each dimension is scored from 0 to 3, with a total score of 21 points. The higher the points, the worse the sleep quality. The result of 0-5 points indicates good sleep quality; points ≥ 6 indicate sleep disturbance.

(5) Determination of TCM constitution
The data of the surveyed subjects were collected according to the 33 items in the standard questionnaire of "TCM Service Record Sheet for the Elderly" issued by the State Administration of Traditional Chinese Medicine in 2013, and the results of constitution determination were analyzed. The types of TCM constitution included biased constitution (Qi de ciency, Yang de ciency, Yin de ciency, phlegm, dampheat, blood stasis, Qi stagnation, and special constitution) and gentle constitution. Criteria for the identi cation of biased constitution were: "Yes" if the cumulative score of all items ≥11; "Tendency" if the cumulative score of all items =9-10; "No" if the cumulative score of all items ≤ 8. Criteria for the identi cation of gentle constitution: "Yes" if the cumulative score of all items ≥17 and the nal score of each of the other eight constitutions < 8; "Roughly yes" if the cumulative score of all items ≥17 and the nal score of each of the other eight constitutions <10.

(6) Evaluation of the simpli ed geriatric depression scale
The geriatric depression scale has been simpli ed by Burke et al. [18], and the Cronbach's α coe cient for internal consistency in the Chinese version of the scale is 0.82 [19]. The scale involves 15 items, among which items 1, 5, 7, 11, and 13 have negative scoring, and the remaining 10 items have positive scoring. A score of 0 or 1 point is given to each item, with the maximum score of 15 points. The higher the score, the more obvious the tendency of depression. If GDS-15 score is higher than 8 points, it indicates the existence of depressive symptoms.

Statistical analysis
The SPSS 24.0 software was used for data processing and analysis. Independent sample t test was used for the intergroup comparison of measurement data conforming to the normal distribution; the Mann-Whitney U test was performed for the intergroup comparison of the measurement data not conforming to normal distribution; the χ 2 test was used for the intergroup comparison of disordered classi cation data; chi-square trend test and Wilcoxon test were used for the intergroup comparison of ranked data. Inspection level was set at α=0.05. The binary logistical stepwise regression model was used to screen the in uencing factors, and the OR value for relative risk of a single factor and the corresponding 95% con dence interval were obtained. The dependent variables were MCI events (binary classi cation), and the exposure variables were age, gender, years of education, BMI, ICVD, marital status, status of work, exercise, smoking, PSQI score, various sleep dimensions, and TCM constitution.
Based on the selected potential in uencing factors, multi-factor logistical regression model was constructed: (1) Model 1: a crude model only with the exposure as independent variables; (2) Model 2: Based on of Model 1, the general demographic data such as age and the years of education were adjusted; (3) Model 3: A Fully adjusted model. Through the Directed Acyclic Graph (DAG) theory [20], the causal relationship network was explored to determine the independent variables that t the model, with the focus on exploring the association of subjective sleep characteristics and Qi-stagnation with the MCI outcome ( Figure 1). After the construction of different models, the Akaike information criterion (AIC) and Area Under the Curve (AUC) were calculated, and the AIC and AUC of different models were compared. The smaller the values of AIC and AUC, the better performance of the model.
The Delta method was employed to analyze the additive interaction between sleep disturbance and Qistagnation, and the obtained regression coe cient β for the independent factors and interactive items was substituted into the Excel table compiled by Andersson [21] to calculate the three important indices for the interaction strength of the additive model: relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and Synergy index (S) as well as their 95% CI. When the 95% CI of RERI and AP does not contain 0, or the 95% CI of S does not contain 1, it is considered that an additive model interaction synergy exists.
Missing data processing: If the exposure factors (PSQI scale, TCM constitution scale) in the research hypothesis was missing without being evaluated, they were removed. For other missing data, the multiple imputation method was used to perform statistical analysis on the lled data.

Characteristics of study subjects
From March 2019 to December 2020, a total of 1,821 subjects were recruited, among whom 1,268 subjects completed the assessment, and 181 subjects without Pittsburgh sleep scale data and 37 without TCM constitution scale data were excluded. Finally, 1,071 cases were included in the statistical analysis, with the research owchart shown in Figure 2.
Among the 1,071 study subjects, 314 suffered from MCI, with the prevalence rate of 29.3%. Compared with the control group with normal cognition, the subjects with MCI were more likely to be females, who had a lower educational level and working status, and a higher proportion of them were widows and lived with children. The MCI group shows more types of combined chronic diseases. Compared with the control group with normal cognition (45.6%), the MCI group showed a higher possibility of suffering from sleep disturbance (57.6%), and the intergroup differences were statistically signi cant (P<0.05), as shown in Table 1.

TCM constitution distribution of MCI patients
The proportion of MCI patients with Qi-de ciency (12.4%) and Qi-stagnation (11.1%) was higher than that of normal controls (P<0.05). After correcting for age and years of education, individuals with Qi-de ciency and Qi-stagnation presented increased risk of MCI, with the OR (95% CI) of 1.559 (1.009-2.407) and 1.706 (1.078-2.700), respectively, as shown in Table 2.

Subjective sleep quality of MCI patients
With regard to the sleep characteristics as per the PSQI scale with sub-dimensions, the subjective sleep quality of individuals with MCI was poorer (Z=-3.404, P=0.001), with prolonged sleep latency (Z=-3.398, P=0.001), shortened sleep duration (Z=-2.237, P=0.025), and aggravated daytime dysfunction (Z=-3.723, P 0.001), than that of individuals with normal cognition. However, the differences in the three dimensions of sleep e ciency, nighttime sleep disturbances, and hypnotics were not statistically signi cant (Table 3).

Multi-factor analysis of the in uence of sleep characteristics and Qi-stagnation on MCI
Multi-factor logistical regression was conducted on the screened single-factor variables. Among them, Qide ciency and daytime dysfunction represented similar scale items, with a moderate rank correlation between the two variables (r s =0.436, P<0.001). Therefore, only select daytime dysfunction was selected to be included in the models. The results in Table 4 show that the dangerous effect of sleep duration on MCI was replaced by sleep latency, daytime dysfunction, and Qi-stagnation; therefore, it was not included in the models. In Model 1, sleep latency (OR=1.181, 95% CI: 1.035-1.347), daytime dysfunction (OR=1.197, 95% CI: 1.039-1.379), and Qi-stagnation (OR=1.436, 95% CI: 1.031-1.999) were included in the core index set. The OR values for corrected Model 2 and Model 3 did not change signi cantly, indicating that the results are robust.

Analysis of the additive interaction effect of Qi-stagnation and sleep quality on MCI
Considering the bidirectional effect of sleep and mood, and taking MCI as the dependent variable and the sleep disturbance and Qi-stagnation as independent variables, the interaction of sleep disturbance and Qi-stagnation with MCI was further analyzed through logistic regression, after controlling the confounding factors of age, gender, and education level. The results in Table 5

Discussion
The study in this paper investigated the correlation between the subjective sleep quality and MCI among 1,071 older adults without depression in the community in Fuzhou. The research results verify the research hypothesis. Compared with the control group with normal cognitions, older adults with MCI have a higher prevalence of sleep disturbance (57.6%) and Q-stagnation (11.1%). The risk of MCI occurrence was 1.625 times higher than that of sleep problems. This ratio is comparable to the result of 1.68 times reported in a systematic review and meta-analysis [22].
The TCM constitution refers to the comprehensive and relatively stable intrinsic characteristics in terms of morphological structure, physiological function, and psychological state of the human body in the course of life, which is formed on the basis of congenital endowments and acquired in the postnatal period [23]. The differences in individuals' constitution determine the differences in their susceptibility to and tendency of suffering from certain diseases. Therefore, they show differences in the time of cognitive impairment. Accordingly, delaying the cognitive impairment should follow the principle of taking measures suited to individual conditions [24]. According to the research in this study, it was found that the risk of MCI among older adults with sleep disturbances and Qi-stagnation is 2.581 times higher than that among normal controls. Those with MCI may suffer from a more serious sleep disturbance, and their daytime and nighttime sleep rhythms may have undergone speci c changes, which is especially manifested as having di culty falling asleep, being easy to wake or wake earlier at night, and having daytime dysfunction and is related to the Qi-stagnation physique. However, sleep quality and Qistagnation have no interactive synergistic effect on the onset of MCI among older adults.
Consistent with the results of previous studies, yin-yang maladjustment and ying-wei disharmony are the main pathogenesis of insomnia, with Qi-stagnation [25]. If not adjusted in a timely manner, this can lead to an introvert personality, emotional instability, sentimentality, depression, and anxiety in individuals. Thus, these individuals often have the symptom of hyperarousal, resulting in di culty in falling asleep, cognitive decline, as well as MCI [26]. A previous meta-analysis [27] report indicated that the prevalence rate of MCI patients with the complication of depression from community source samples was 25% (95% CI: [19][20][21][22][23][24][25][26][27][28][29][30]. Relatively stable Qi-stagnation and low mood are closely associated with sleep disturbances, which mediate the deterioration of the disease in cognitive impairment [28]. However, although Qi-stagnation is a risk factor for MCI patients, Qi-stagnation combined with sleep disturbance does not have a synergistic effect on the occurrence of MCI. Compared with the formed relatively stable depression, Qi-stagnation is adjusted in a timely manner to improve the sleep quality, the occurrence of MCI can be prevented. Some studies have reported that Qi-stagnation can signi cantly and positively predict depression in older adults, and has a direct impact on depression in older adults (95% CI: 0.017-0.249), with the relative effect value of 24.01% [29]. A series of studies conducted by the California Paci c Medical Center[30] evaluated the depressive symptoms among 3,020 older women. Their Circadian rhythms were measured by wrist activity tractography, and it was found that the higher the level of depressive symptoms, the less synchronous the Circadian rhythms. Higher scores for depression are associated with decreased diurnal amplitudes (height df = 3014, t= -11.31, linear trend p < 0.001). Among the evaluated women, 1282 were followed up for 4.9 years[31]; of these195 (15%) suffered from dementia and 302 (24%) suffered from MCI. The amplitude of Circadian rhythms was reduced, and the risk of dementia and MCI among elderly healthy women with delayed rhythms was increased.
The strong association between Qi-stagnation and sleep disturbance reminds healthcare workers to evaluate mood and sleep status of individuals with MCI. Ignoring any symptom will cause patients with MCI to fall into a vicious cycle of low mood and lack of sleep. The important effects of Qi-stagnation and depressive symptoms on sleep disturbance among individuals with MCI can also be treated through the adoption of evidence-based psychological interventions (including cognitive behavioral therapy, supportive psychotherapy, problem-solving therapy, and interpersonal therapy). Based on the theories of "body recuperation and preventive treatment of diseases" including "body-disease correlation," "adjustable constitution," and "body regulation intervention," regulating the body is proposed to improve the state of Qi-stagnation, thus providing reference and guidance for the early prevention and clinical intervention of MCI[32].
This study has several limitations. First, the cross-sectional design of this study fails to determine the direction of the relationship. A longitudinal study design should be performed to further verify the causal inference of the research results of this study in future studies. Second, because of the limitation of manpower and material resources, although the research sites involve the community daycare centers in the six districts and counties under the jurisdiction of Fuzhou City, the method of simple random sampling may result in uncertainties in the parameter estimation results. Hence, stricter random sampling methods are required to be employed in future studies to enhance the universality of research results. Third, limited by the sample size, only the relationships of main TCM constitution and sleep disturbance with MCI was investigated in this study. However, the effects of ambidextrous TCM constitution on sleep quality and cognitive disturbance need to be further explored to more comprehensively evaluate the prediction model. Finally, only subjective sleep exposure is used in this study. In exploring the correlation of sleep with MCI, other objective sleep-related indices should be tested as independent variables in future models.  Tables   Table 1 Comparison of the distribution of general demographic data between the two groups n=1071     Flow diagram of the study