Relationship between physical activity, sleep quality, and frailty in middle-aged and older adults: a cross-sectional study Running title: The correlation between physical activity, sleep quality, and frailty

Relationship between physical activity, sleep quality, and frailty in middle-aged and older adults: a cross-sectional study Running title: The correlation between physical activity, sleep quality, and frailty | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Relationship between physical activity, sleep quality, and frailty in middle-aged and older adults: a cross-sectional study Running title: The correlation between physical activity, sleep quality, and frailty Linpeng SUI, Donglin ZHANG, Wenhua WANG, Dan LI, Yue LIU, Mei XUE, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4230718/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Frailty is linked to numerous negative health consequences, with past research indicating that physical activity (PA) and sleep quality play a role in influencing frailty among older adults. As societal norms evolve, middle-aged adults are faced with time constraints that may result in differences in PA and sleep compared to older adults. Despite this, there is a limited amount of research focusing on middle-aged and older adults. This study seeks to examine the prevalence of frailty among middle-aged and older adults in the region, as well as investigate the connection between sleep quality, PA, and frailty. Methods: This cross-sectional study involved 1,265 middle-aged and elderly permanent residents from a region in Shaanxi Province, China. Participants were selected randomly for a physical examination and questionnaire survey. The questionnaires covered sociodemographic information, the Frailty Scale, the Pittsburgh Sleep Quality Index (PSQI) Scale, and the International Physical Activity Questionnaire (IPAQ). Statistical description and correlation analysis between variables were conducted using SPSS software. Results: A total of 1042 study participants were ultimately included in the analysis, with 74 classified as frailty and 444 as non-frailty. Adjusting for relevant covariates revealed that middle-aged and older adults engaging in light PA were more likely to be frailty compared to those with high PAL during non-frailty (CI 0.149-0.682; P < 0.01) and pre-frailty stages (CI 0.098-0.425; P < 0.001). Conversely, individuals without sleep disorders were less likely to be frailty (CI 1.241-3.720; P < 0.01). Occupational MET values were highest during the pre-frailty period in the presence of substantial PA ( P < 0.001). Sleep quality not only directly predicted frailty but also acted as a mediator in influencing the role of age on frailty, with a mediating effect of 12.43%. Conclusion: Both PA and sleep quality play a role in frailty. The impact of PA on frailty is influenced by the nature of the individual's occupation. Sleep disorders can heighten the risk of frailty, with sleep quality acting as a mediator in the relationship between age and frailty. Frailty Sleep quality Physical activity Middle-aged and elderly people Figures Figure 1 Figure 2 Figure 3 1. Background Population aging is a rapidly growing global phenomenon, leading to increasingly severe psychological and physical issues among older adults( 1 ). This presents a significant public health challenge and places a substantial economic burden on society( 2 ). Frailty serves as a crucial indicator of the overall health status of older individuals, encompassing physical, psychological, and social aspects( 3 ). It reflects the body's overall health and the extent of its functional decline( 4 ). Frailty is characterized by a reduced reserve capacity of multiple body systems, heightened vulnerability to diseases, and adverse outcomes such as falls, disabilities, hospitalizations, and mortality( 4 , 5 ). Frailty is a dynamic and changing process (especially in the early stages of disease)( 6 ), which gives an essential window of opportunity for disease prevention and treatment. Previous studies have identified women, advanced age, living alone, lower economic levels( 7 ), rural areas( 8 , 9 ), longer sedentary behavior(SB) time, less PA( 10 , 11 ), and poor sleep quality( 12 , 13 ) as risk factors for frailty, with PA and sleep quality being more intervenable in natural populations and considered an essential element in preventing frailty( 14 ). Regular PA has the potential to decrease age-related chronic inflammation and oxidative stress( 15 ), thus aiding in the prevention and mitigation of various chronic ailments( 16 , 17 ) and enhancing the physical and mental well-being of older individuals( 18 ). Engaging in moderate to high levels of PA is particularly beneficial for reducing disease risks among older adults. Sleep, a fundamental physiological necessity for the human body, plays a crucial role in overall health. Sleep-related issues affect over half of middle-aged and older adults ( 19 ), and the persistence of poor sleep quality contributes to the onset of numerous diseases( 20 , 21 ). Consequently, sleep problems have become a prevalent concern among this demographic. Reduced nighttime sleep duration and reduced sleep quality increase the risk of fragmented daytime sleepiness and narcolepsy( 22 ), both of which are associated with a higher incidence of frailty-related conditions and all-cause mortality( 23 ). However, the majority of the existing evidence is derived from surveys conducted among individuals aged 60 and above, primarily within communities, hospitals, and nursing homes. With the development of society, the life and economic pressure of middle-aged people has gradually increased, and their disposable time has decreased. Activities at work dominate some people's PA, and there are fewer and fewer PA based on fitness exercise, which is different from those of older people. Stress has been found to affect the quality of sleep in the population( 24 ), and fitness and exercise can also have a significant positive effect on sleep( 25 ), which also suggests that there may be some differences in the factors affecting the quality of sleep in middle-aged people compared to older people. Several studies in recent years have found that debilitating illness in middle-aged people also occurs frequently. Previous investigations indicate that the occurrence of pre-frailty is approximately 34.6% among individuals aged 50–59 in Korea( 26 ). Moreover, numerous other studies have demonstrated that the issue of pre-frailty within the middle-aged population should not be disregarded( 27 – 29 ). It has been posited that early intervention to prevent frailty could potentially delay mortality rates in 3–5% of older adults( 30 ). Therefore, exploring the risk factors affecting frailty and developing interventions for frailty should be more appropriately conducted with the middle-aged and elderly population in mind, and early interventions for poor lifestyle habits at an early age are more likely to help reduce the decline in quality of life and the incidence of a wide range of adverse outcomes. Therefore, this study aimed to explore the correlation between physical activity, sleep quality, and frailty in middle-aged and older adults over 45 years of age in order to intervene early in the prevalence of frailty in the population and to improve the quality of life of the population. 2. Material and methods 2.1 Study Design and Population We used the whole population sampling method to conduct a cross-sectional study in July-August 2023 by selecting resident middle-aged and elderly residents of a city in Shaanxi Province, China. After completing the informed consent form, all of these study participants completed the frailty-related questionnaire. The study questionnaire consisted of 45 items, including basic information (15 items), the Frailty Scale (5 items), the Pittsburgh Sleep Quality Scale (PSQI) (18 items), and the International Physical Activity Questionnaire Short Form (IPAQ) (7 items). Inclusion criteria: ( 1 ) aged ≥ 45 years; ( 2 ) having lived in the area for at least one year; ( 3 ) being able to understand the questions and complete the interview or completing the survey with the help of their family members. Exclusion Criteria: ( 1 ) Persons with severe mental illness or impaired consciousness; ( 2 ) Persons with severe visual or hearing impairment that interferes with regular communication. Before starting the data collection phase, the researchers professionally trained the investigators. (Fig. 1 ) To ensure that ethical principles were followed and the rights and safety of participants were maintained, this study was approved by the Medical Ethics Review Committee of Xi'an Medical College, China (Approval No. XYLS2023090). The study was conducted using the Declaration of Helsinki (2000 version). 2.2 Measurements 2.2.1 Frailty measure This study assessed the frailty of the respondents using The Frailty Scale( 31 ), which has been shown to predict death and disability with good construct validity and responsiveness( 32 ). The scale contains five entries, including fatigue, endurance, mobility, number of chronic conditions, and weight loss in the most recent year. Each entry was recorded as 1 point, and according to the score, it was categorized as non-frailty (0 points), pre-frailty (1–2 points), and frailty (3–5 points). Study participants filled in and double-checked the entries under the guidance of trained professionals to ensure that the data were accurate and valid. 2.2.2 PA assessment PA was measured using the short form of the IPAQ ( 33 ), which is widely used nationally and internationally and is more straightforward and accessible to the screen. The Chinese version of the IPAQ-SF is widely used and has been shown to have good reliability and validity( 34 – 36 ). The scale included high, medium, and light PAL in the most recent week. Participants completed the scale using recall, and a professional interpreted the content of the scale for them. The formula for IPAQ was " the total PA (MET/min/w) = MET assignment corresponding to PA × weekly frequency (d/w) × time per day (min/d)," with MET assignments of 3.3 for walking, 4.0 for moderate-intensity activity, and 8.0 for high-intensity activity. The total MET of the study subjects in the last week were calculated. Then, the continuous variable was converted into a categorical variable and categorized into three groups: light PAL (< 600 MET/min/w), moderate PAL (600–3000 MET/min/w), and vigorous PAL (≥ 3000 MET/min/w), which is similar to the grouping method in the previous literature( 37 ). 2.2.3 Sleep quality assessment In this study, sleep quality was assessed using The PSQI ( 38 ), which is used to evaluate better the sleep quality status of the study participants in the last month, and it is the most widely used subjective sleep assessment scale( 39 ). The Chinese version of the scale currently in use has been shown to have good reliability and validity( 40 ) and has been used in several studies( 39 , 41 ), with a Cronbach's alpha of 0.736 in this study. The scale consists of 18 self-assessment items divided into seven dimensions, namely subjective sleep quality, sleep duration, time to fall asleep, sleep disorders, sleep efficiency, use of hypnotic medication, and daytime dysfunction, with scores ranging from 0 to 3 for each dimension, and a total score ranging from 0 to 21, with higher scores being associated with poorer sleep quality. Most current studies use a score of > 7 as a criterion for sleep disorders( 42 , 43 ). 2.3 Statistical methods All statistical analyses were performed using SPSS Statistics 25.0. Missing primary variables were removed using case-by-case deletion (in the order of sleep quality, frailty, and PA), and missing information was filled in using SPSS Multiple Interpolation for the other variables. Information on continuous variables (skewed distribution) of the study population was statistically described using median and interquartile range (IQR) [e.g., age, Body Mass Index (BMI), sedentary time, sleep quality], and categorical variables were statistically described using rates and percentages [e.g., age group, gender, ethnicity, education level, occupation, marriage, living status, family disasters, hospitalization experience, per capita monthly household income, smoking, alcohol consumption, sleep disorders, sedentary time, BMI, PAL]. Categorical data were compared using non-parametric tests, and the Kruskal-Wallis test was used for comparisons involving more than two groups of people with different characteristics, while the Wilcoxon rank test was used for comparisons between two groups of people with different characteristics. Calibrated multivariate logistic regression models were also used to assess the relationship between sleep quality, PAL, and prevalence of frailty, and the results were expressed as odds ratios (OR) with corresponding 95% confidence intervals (CI). The Kendall's tau-b test was used in this study to assess the relationship between PAL, sleep quality, and frailty. In this study, the Kruskal-Wallis test was used to explore the relationship between total MET and frailty in participants from different occupations, and all comparisons were corrected for Bonferroni. The mediating effect analysis procedure of PROCESS v3.5 software was used to test the significance of the mediating effect using the percentile Bootstrap method and to calculate the various types of effects and their 95% CI in the mediation model, with 5,000 repetitive samples and a test level of α = 0.05, to analyze the mediating role of quality of sleep in the relationship between age and frailty in middle-aged and older adults. Correlation coefficients with P-values of less than 0.05 were considered statistically significant. 3. Results 3.1 Baseline information on participants A total of 1265 participants were included in this study. After excluding cases with missing primary variables, 1042 participants were included in the final survey, accounting for 82.37% of the initial sample. The participants ranged from 45 to 92 years, with a median age of 60 years. Among the participants, 47.12% were middle-aged (45–59 years), and 52.88% were female. The total number of patients with frailty was 74, with a prevalence of 7.1%. The prevalence of frailty was 4.6% in men and 8.4% in women. Furthermore, the prevalence of frailty was 5.7% in the middle-aged group and 8.3% in the elderly group. When examining different occupations, the highest prevalence rates were observed in agriculture (8.0%) and laborers (8.2%), while residents working in institutions had the lowest prevalence rate (1.5%). The findings of the univariate analyses indicated significant differences across various factors, including age, sleep quality, gender, education level, occupation, experience of hospitalization in the last year, per capita monthly household income, SB, BMI subgroups, and PAL in relation to different stages of frailty ( P < 0.05). ( Supplementary table 1 ) 3.2 Multifactorial logistic regression analysis of participant occurrence of frailty Adjusting for the inclusion in the regression model of variables that were significantly different based on the results of single factor analysis and variables that have been elaborated in the extensive literature to have an impact on frailty (living status ( 44 )), it was found that when the outcome variables were non-frailty, pre-frailty, and frailty, it was found that compared to high levels of PA, both in the non-frailty (OR 0.318; CI 0.149–0.682; P < 0.01) and pre-frailty (OR 0.204; CI 0.098–0.425; P < 0.001), middle-aged and older adults with light levels of PA were more likely to develop frailty, and middle-aged and older adults without sleep disorders (OR 2.148; CI 1.241–3.720; P < 0.01) had a lower risk of frailty. (Table 1 ) Table 1 Factors associated with participant frailty and pre-frailty using multi-categorical logistic regression analysis Variables Clusters Non-frailty vs. Frailty Pre-frailty vs. Frailty OR (95% CI) P OR (95% CI) P Age Groups(years) 45–59 1.605(0.920–2.798) 0.096 1.108(0.644–1.906) 0.712 ≥ 60 1 1 Gender Males 1.688(0.887–3.211) 0.111 1.294(0.687–2.436) 0.425 Females 1 1 Education level Primary school and below 0.865(0.321–2.334) 0.775 1.035(0.388–2.760) 0.944 Middle school 1.306(0.425–4.010) 0.641 1.088(0.356–3.319) 0.882 High school and above 1 1 Occupations Farming 0.561(0.292–1.078) 0.083 0.922(0.485–1.751) 0.804 Workers 0.416(0.149–1.165) 0.095 0.627(0.229–1.715) 0.363 Service worker 0.810(0.200-3.287) 0.768 0.935(0.233–3.762) 0.925 Employee or professional in an organization 2.775(0.316–24.370) 0.357 1.539(0.172–13.755) 0.700 Others 1 1 Living status Living alone 1.196(0.426–3.361) 0.734 1.317(0.487–3.562) 0.587 non-living alone 1 1 Hospitalization Experience No 1.748(0.959–3.188) 0.068 1.202(0.681–2.121) 0.526 Yes 1 1 Average monthly family income 10000RMB 1 1 Sleep disorder No 2.148(1.241–3.720) 0.006 1.215(0.718–2.058) 0.468 Yes 1 1 SB time <4h/d 0.919(0.336–2.513) 0.870 0.671(0.262–1.715) 0.404 4-6h/d 2.432(0.775–7.626) 0.128 1.706(0.577–5.044) 0.334 6-8h/d 0.876(0.269–2.853) 0.826 0.961(0.319–2.894) 0.943 ≥ 8h/d 1 1 BMI Thin and normal 1.704(0.799–3.633) 0.168 1.480(0.722–3.033) 0.284 overweight 1.801(0.873–3.713) 0.111 1.120(0.562–2.229) 0.748 obese 1 1 PAL Light 0.318(0.149–0.682) 0.003 0.204(0.098–0.425) 0.001 Moderate 1.104(0.510–2.389) 0.803 0.584(0.275–1.237) 0.160 Vigorous 1 1 Note : Adjusted for age group, sex, education level, occupation, residence, hospitalization in the past year, per capita monthly household income, sleep quality, SB time, BMI subgroup, and PAL covariates. BMI, Body Mass Index. SB, sedentary behavior. PAL, physical activity level. 3.3 Correlation analysis between PA, sleep quality, and frailty This study found that the prevalence of frailty and sleep disorders among middle-aged and elderly residents of the region was 7.1% and 34.5%, respectively. Residents with high levels of physical activity accounted for 26.0% of the total participants. Through Kendall's tau-b correlation analysis, a noteworthy positive correlation between sleep quality and frailty status ( P 0.01), suggesting a comparable correlation in both the middle-aged and elderly cohorts. ( Supplementary table 2 ) 3.4 Correlation analysis between total MET and frailty staging in different occupations This study analyzed the relationship between MET and the occurrence of frailty according to different occupations and found that MET were significantly correlated with frailty staging in the total population (H = 24.060, P < 0.001). Similar correlations were found in farming, laborers, and other occupations ( P < 0.05), but there were also differences. The highest and lowest values of median MET among farmers and laborers (construction workers/factory workers) occurred in the pre-frailty and frailty periods, respectively, while the highest and lowest values of median MET among other occupations occurred in the non-frailty and frailty periods, respectively. ( Supplementary table 3 ) We further analyzed the relationship by dividing the occupations into two groups based on the presence or absence of prolonged periods of heavy PA. It was found that there was a significant correlation between MET and the staging of frailty in both types of occupations. The difference was that the highest values of MET in Occupation 1 in the presence of substantial PA occurred in the pre-frailty period ( P < 0.001). In contrast, the highest values of metabolic equivalents in Occupation 2, which did not contain substantial physical activity, occurred in the no-frailty period ( P < 0.01). The results also showed that residents in occupation 1 (693–8466 MET/min/w) generally had significantly higher MET than occupation 2 (271-1140.5 MET/min/w). However, the prevalence of frailty was 8.0% among the inhabitants of occupation 1. In occupation 2, the prevalence is 5.4%. (Fig. 2 ) 3.5 Mediating effects of sleep quality between age and frailty Through the implementation of the Bootstrap method, 5,000 Bootstrap samples were randomly selected from the original sample (n = 1042) to conduct direct and indirect mediation effect tests. The results revealed that age played a significant role in predicting frailty (B = 0.016; SE = 0.004; P < 0.001). Additionally, when the mediating variable of sleep quality was introduced, age remained a significant positive predictor of sleep quality (B = 0.055; SE = 0.014; P < 0.001), while sleep quality also had a significant impact on frailty (B = 0.042; SE = 0.008; P < 0.001). Moreover, the Bootstrap confidence intervals for the direct effect of age on frailty and the mediating effect of sleep quality were evaluated, neither of which encompassed the value of 0. (Table 2 ) These findings indicate that sleep quality not only directly predicted frailty but also acted as a mediator in influencing the role of age on frailty, with a mediating effect of 12.43%. (Table 3 , Fig. 3 ) Table 2 Effects model with sleep quality as a mediating variable Variables Model Ⅰ (Sleep Quality) Model Ⅱ (Frailty) Model Ⅲ (Frailty) B SE β B SE β B SE β Age 0.055 0.014 0.122 0.019 0.004 0.161 0.016 0.004 0.141 Sleep Quality 0.042 0.008 0.163 R2 0.015 0.026 0.052 F 15.588 *** 27.572 *** 28.398 *** Note : *** P < 0.001. Each variable in the model is standardized to bring into the regression equation. Model Ⅰ: Age predicts Sleep Quality. Model Ⅱ: Age predicts frailty. Model Ⅲ: Sleep Quality and age together predict frailty. Table 3 Results of mediation effect analysis of sleep quality Effect type Efficacy value BOOT criteria Boot 95%CI Relative effect value lower bound upper bound Overall effect 0.019 0.004 0.012 0.026 Intermediary effect 0.002 0.001 0.001 0.004 12.43% Direct effect 0.016 0.004 0.010 0.023 87.57% Note : Boot standard errors, Boot 95% CI lower bounds, and upper bounds refer to the common errors, lower bounds, and upper bounds of the 95% confidence intervals of the indirect effects estimated by the bias-corrected percentile Bootstrap method, respectively; the variables in the model are standardized and brought into the regression equation. 4. Discussion 4.1 Comparison of frailty with different features This study found that frailty was 7.1% in the middle-aged and older adults in the region, and the prevalence in the middle-aged (5.7%) was low compared to the elderly (8.3%). A previous study has calculated the prevalence of frailty in elderly residents over 60 years of age in Northwest China to be 9.1%( 9 ), which is relatively high compared to the present study, and this may be related to the environment. The site is located under the Qinling Mountains, with large green areas and good air quality, which has a preventive effect on frailty( 45 ). In addition, because this study called on middle-aged and elderly residents in the area voluntarily, some older adults with mobility difficulties and those who were bedridden were unable to arrive at the site, which resulted in a bias in the health status of older people in this study, but this also indicates that the actual prevalence of frailty among older people may be higher than the results obtained in this study. The univariate analyses of variance results showed that the differences in residential status( 46 ), marital status( 46 ), and smoking status( 44 ) were not significant across the stages of frailty, which is different from the results of previous studies. People who live alone are more likely to contribute to the onset of loneliness, anxiety, and even depression( 47 , 48 ), which can seriously affect their quality of life. Loneliness accelerates the progression of frailty( 49 ) and serves as a mediator and moderator of a wide range of adverse health outcomes( 50 ). The fact that this study included some rural residents, with close interaction between neighbors, and living alone is less likely to result in loneliness compared to the community may have influenced the results, and it will be necessary to follow up the study to confirm the conjecture. Studies have shown that the high levels of harmful and potentially harmful substances in unburned tobacco smoke( 51 ) increase the risk of many cancers and chronic diseases( 52 ) and that prolonged exposure to secondhand smoke and some environmental pollutants accelerates the onset and progression of physical decline and frailty( 53 ). However, this study did not investigate the population exposed to secondhand smoke over a long period, and more research is needed to explore the effects of long-term exposure to secondhand smoke and other harmful substances on the health of residents in the region. 4.2 Correlations between PA, sleep quality and frailty 4.2.1 Correlation analysis between sleep quality and PA An investigation demonstrates that the occurrence of sleep quality disorders among the elderly in Tianjin stands at 14.39%( 54 ), which is less than satisfactory when compared to the prevalence of sleep disorders in rural areas of Shaanxi Province among middle-aged and elderly individuals. Based on Kendall's tau-b test, there is no notable correlation observed between the quality of sleep and PA. This comes after a cohort study showed that poor sleep can lead to a significant increase in the risk of several diseases and even death and that higher levels of PA, or meeting the World Health Organization (WHO) recommendations for moderate-to-vigorous physical activity (MVPA), can significantly mitigate the harmful effects of poor sleep( 55 ). A study conducted in Africa comparing the quality of sleep in rural and urban areas found that sleep quality in rustic regions was inferior to that in urban areas, potentially due to more vigorous PA and multiple sleep schedules( 56 ). Various forms of exercise exert different effects on the body, with the fusion of muscular endurance training and walking exhibiting a particularly notable influence on sleep( 57 ). The discrepancy between PA and sleep quality, as well as the outcomes of earlier studies, may be attributed to the specificity of PA in rural settings (see details below). 4.2.2 Correlation analysis between sleep quality and frailty In this study, age was found to impact frailty, with the risk of frailty increasing. Sleep quality can be involved as a mediator in age's influence on frailty in middle-aged and elderly residents. Decreased sleep quality linked to the onset of frailty ( 29 ), chronic loss of sleep quality negatively affects the immune system( 58 ). In addition, long-term sleep quality decline can limit the activity level of the organism( 59 ), resulting in a decline in physical function( 60 ), which seriously affects physical( 61 ) and mental health( 62 , 63 ), significantly reducing the quality of life( 64 ) and greatly increasing the risk of death. Long-term chronic diseases can also lead to declining sleep quality( 65 ), resulting in a vicious circle. Subsequent studies can reduce the incidence of frailty by exploring the relevant factors that affect sleep quality. 4.2.3 Analysis of the correlation between PA and frailty in different occupational characteristics The results of previous studies suggest that PAL is associated with the occurrence of frailty. However, the present study found no significant correlation between the two, considering that this may be related to the grouping of PAL in this study. The characteristics of PA in occupations such as farmers, where there is a large amount of PA over a long period, are different from the PA based on fitness exercise in previous studies, and exploring the correlation between the total metabolic equivalents and the staging of frailty in different occupations is more likely to illustrate the association between PA and frailty. Therefore, we analyzed the occupations in groups, and the results confirmed the above view. The highest prevalence of frailty was found in the occupations of farmers and laborers, and the relationship between PA and frailty was different from that of the other occupations, probably because of the long periods of heavy PA in both occupations. In order to further confirm the above conjecture, this study will be divided into two groups based on whether or not the occupations have long-term high levels of PA. It was found that Occupation 1, which has long-term high levels of PA, is more likely to have a pre-frailty period as the intensity of PA reaches its highest value. In contrast, occupation 2 that do not have long periods of high levels of PA are more likely to experience periods of non-frailty as the level of PA increases, which is consistent with the results of previous studies. Nevertheless, regardless of occupation, residents with low PA contribute to the development of frailty. In addition, we have found that the prevalence of the disease is higher in residents with a long history of heavy PA. The risk of frailty generally decreases with progressively higher levels of PA. However, excessive PA hurts the organism, counteracting the positive effects of PA on the body, and may produce a different developmental trajectory. We have speculated about this. On the one hand, those residents whose own course reversed to a non-frailty stage have progressed to a pre-frailty stage due to the effects of prolonged periods of heavy PA; on the other hand, it is possible that residents in a pre-frailty stage are prevented from reversing to a non-frailty stage due to the long-term effects of the disease. The reasons for this result may be multifaceted, and more longitudinal studies are needed to explore this. Firstly, PA has different effects on the human body depending on the environment in which it takes place and the way in which it is carried out. PA related to home and physical exercise was associated with a reduced risk of death, and occupational and transportation-related PA was not associated with an adverse risk( 66 ). Additionally, Rachel E. et al( 67 ) study compared different types of PA found that regular fitness exercise reduces the risk of heart disease and that strenuous, heavy, occupational-related physical labor causes arterial stiffness and a negative effect on the nerve. Work-related backbreaking physical work negatively affects arterial stiffness and nerve reflexes, which increases the risk of heart problems; nevertheless, this does not indicate that all work-related PA can harm health, only chronic, strenuous PA can adversely affect the body. Secondly, with increasing age, significant changes occur in the cardiovascular system of middle-aged and older adults. Thickening and hardening of the aorta and thickening of the ventricular wall due to hypertrophy of the ventricular cells predispose them to increased cardiac load and diminished left ventricular contractile performance( 68 ). The impairment of cardiovascular function is accelerated in middle-aged and older adults under the effect of prolonged high levels of PA. Since cardiovascular disease and frailty have similar inflammatory response mechanisms, it is easier to accelerate the process of frailty development( 69 ). The reason for the difference between the results of this study and previous studies may also be related to the characteristics of the life of the inhabitants of the area. More than half of the people in the present study work in agriculture. Due to the imperfections in transportation, public fitness facilities, and lack of health care awareness, most residents lack regular PA based on fitness exercises, and the heavy physical labor generated by long-term agriculture produces chronic damage to the body, leading to the onset of frailty. In addition, the occupations of agriculturalists as well as construction workers are characterized by long-term exposure to ultraviolet ray radiation, which can trigger a state of cellular senescence and skin inflammation, stimulate immune senescence as well as degeneration of neighboring cells, and evoke a remodeling of the immune system similar to that of normal aging( 70 ). Some studies have found that long-term occupational exposure to pesticides increases the prevalence of chronic neurological and cardiovascular diseases( 71 – 73 ), as well as cancer, and even increases the risk of cognition, memory, and the occurrence of psychological distress and suicide in adults( 74 ) and that the gradual accumulation of these adverse effects may lead to the premature onset of frailty. Moreover, the period investigated in this study was from July to August, when local temperatures could reach 40°C or more. The farmers had just finished their heavy agricultural production. PA in hot conditions increases the risk of Exercise Heat Stroke (EHS) ( 75 ) and affects β-activities in most areas of the brain( 76 ). The prevalence of negative emotions increases significantly when a person is outdoors in the heat for more than 120 min( 77 ). Older adults with hypertension or diabetes, when physically active for long periods in hot environments, may exhibit tremendous cellular stress, leading to cellular damage( 78 ). Thus, hot weather may have contributed to the higher prevalence of frailty obtained in this study, and considering that the development of frailty is reversible, subsequent studies may consider comparing the changes in prevalence across seasons to confirm the above observation. 4.3 Limitations This study has the following shortcomings. Firstly, the relatively large number of people working in agriculture in this study area is subject to selection bias. Secondly, this is a cross-sectional study, and the results obtained can only represent the current state of the participants. Considering that frailty is a dynamic process, subsequent longitudinal follow-ups can be conducted at different periods to compare the differences in frailty over time. Thirdly, the subjects of this study are not representative of all middle-aged and older adults, and larger sample sizes and multi-center studies can be conducted in the future to refine the types of PA and better explore the relationship between the three. 5. Conclusion PA and sleep quality both play a role in influencing frailty, although there is no significant correlation between PA and sleep quality. Sleep disorders can increase the likelihood of developing frailty and act as a mediator in the relationship between age and frailty. On the other hand, the impact of PA on frailty can differ based on the specific characteristics of the individual's occupation. These factors are closely tied to the lifestyle and habits of the population. Abbreviations PA (Physical activity) PSQI (Pittsburgh Sleep Quality Index) IPAQ (International Physical Activity Questionnaire) PAL (Physical activity level) MET (Metabolic equivalent) IQR (Interquartile range) BMI (Body Mass Index) OR (Odds ratio) CI (Confidence interval) SB (Sedentary behavior) WHO (The World Health Organization) MVPA (Moderate-to-vigorous physical activity) EHS (Exercise Heat Stroke) Declarations Ethics approval and consent to participate: Participants gave written informed consent. The study was approved by the Ethics Committees of Xi’an Medical University and conducted in accordance with the Declaration of Helsinki (Ethics approval No. XYLS2023090). Consent for publication: Not applicable. Availability of data and materials: The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests: The authors declare no conflict of interest. Funding: Natural Science Basic Research Program of Shaanxi (Program No. 2023-JC-YB-827) Authors' contributions: LS, DZ, and WW were involved in the conceptualization of the paper, the survey, data collation, formal analysis, and writing of the first draft; DL and MW contributed to data collection, data collation, and analysis. YL contributed to the conceptualization of the study, access to funding, the survey, the methodology, supervision, and editing. MX was involved in the survey, data collation, and data management of the paper. JH and LZ Participated in the survey, analyses, and other work on this paper. All authors have read and approved the manuscript. Acknowledgments: We thank all study participants and clinicians. We thank the Shaanxi Provincial Medical Association, the Third Affiliated Hospital of Xi'an Medical College of Xi'an Medical College, and the Ankang Medical Association. We thank all medical student volunteers and clinicians who participated in this study. 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[Q1, Q3] indicates [First Quartile, Third Quartile]. BMI, Body Mass Index. SB, sedentary behavior. PAL, physical activity level. Supplementarytable2.CorrelationoffrailtywithPALandsleepqualityindifferentagegroups.xls Supplementary table 2. Correlation of frailty with PAL and sleep quality in different age groups Notes: *P＜0.05, **P＜0.01. The relationship between the three at different ages was analyzed according to the Kendall's tau-b test. PAL, physical activity level. Supplementarytable3.KruskalWallistestfortotalMETandfrailtystaginginparticipantswithdifferentoccupations.xls Supplementary table 3. Kruskal-Wallis test for total MET and frailty staging in participants with different occupations Note: [Q1, Q3] indicates [First Quartile, Third Quartile]. MET, metabolic equivalents. “–” indicates that the sample size is too small for the value to be measured. The “a” means statistically significant differences from the non-frailty period, and “b” represents statistically significant differences from the pre-frailty period. All comparisons were Bonferroni corrected. The significance level is 0.05. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4230718","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":296831751,"identity":"d3b6fde5-81d4-4f07-b548-d6e990b5b4e6","order_by":0,"name":"Linpeng SUI","email":"","orcid":"","institution":"The Third Affiliated Hospital of Xi'an Medical University","correspondingAuthor":false,"prefix":"","firstName":"Linpeng","middleName":"","lastName":"SUI","suffix":""},{"id":296831753,"identity":"5591e39a-fe54-4e1f-a768-8b8c1f497e2b","order_by":1,"name":"Donglin ZHANG","email":"","orcid":"","institution":"The First Affiliated Hospital of Xi'an 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09:45:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4230718/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4230718/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55767316,"identity":"61ce8e6a-fdfd-4a7d-8d60-787e6f82e17c","added_by":"auto","created_at":"2024-05-02 20:17:33","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":281978,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for the selection of research participants\u003c/p\u003e","description":"","filename":"Figure1.Flowchartfortheselectionofresearchparticipants.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4230718/v1/dfaa0cda49d5569366103e20.jpg"},{"id":55767318,"identity":"9f1a54b1-c96a-439b-abaa-9044fac2ab62","added_by":"auto","created_at":"2024-05-02 20:17:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":121778,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between physical activity and frailty in different occupations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e Figure a represents the relationship between PA and frailty for residents of occupation 1, and figure b represents the relationship between PA and frailty for residents of occupation 2. (Based on the Kruskal-Wallis test)\u003c/p\u003e\n\u003cp\u003eOccupation 1 represents occupations with a high level of PA over a long period, including farmers and laborers (construction workers, factory workers). Occupation 2 represents occupations with relatively low PA requirements, including services, establishments, and other occupations.\u003c/p\u003e\n\u003cp\u003e***\u003cem\u003eP\u003c/em\u003e＜0.001, **\u003cem\u003eP\u003c/em\u003e＜0.01\u003c/p\u003e","description":"","filename":"Figure2.Relationshipbetweenphysicalactivityandfrailtyindifferentoccupations.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4230718/v1/b5c481a82c7c19006402d0ca.jpg"},{"id":55767322,"identity":"4ee72087-3f05-4172-bfbe-03f5954eacc9","added_by":"auto","created_at":"2024-05-02 20:17:33","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":130601,"visible":true,"origin":"","legend":"\u003cp\u003eMediated model relationship between age and frailty for sleep quality\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: \u003c/strong\u003e*** \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003ePath \u003cem\u003ec\u003c/em\u003e: the total effect of age on frailty; path \u003cem\u003ea\u003c/em\u003e: the link between age and sleep quality; path \u003cem\u003eb\u003c/em\u003e: the link between sleep quality and frailty; and path \u003cem\u003ec'\u003c/em\u003e: the direct effect of age on frailty when accounting for the mediating effect of sleep quality.\u003c/p\u003e","description":"","filename":"Figure3.Mediatedmodelrelationshipbetweenageandfrailtyforsleepquality.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4230718/v1/733de181cbc49e5b7245f837.jpg"},{"id":83448387,"identity":"6a21c01e-26f0-487f-9ad5-4d728661d673","added_by":"auto","created_at":"2025-05-26 12:01:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1767954,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4230718/v1/ca6f123e-4b12-409f-840b-f62baeba0a2a.pdf"},{"id":55767319,"identity":"c1beb262-8945-442e-8303-ea0808d612c7","added_by":"auto","created_at":"2024-05-02 20:17:33","extension":"xls","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35840,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 1.\u003c/strong\u003eBaseline information of participants\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003ea Represents Z values, others represent H values.\u003c/p\u003e\n\u003cp\u003eZ-values represent comparisons of two non-normally distributed samples using the Mann-Whitney U test, and H-values represent comparisons of multiple non-normally distributed samples using the Kruskal-Wallis test.\u003c/p\u003e\n\u003cp\u003e[Q1, Q3] indicates [First Quartile, Third Quartile]. BMI, Body Mass Index. SB, sedentary behavior. PAL, physical activity level.\u003c/p\u003e","description":"","filename":"Supplementarytable1.Baselineinformationofparticipants.xls","url":"https://assets-eu.researchsquare.com/files/rs-4230718/v1/ade3d7c99b549d4bc1676e13.xls"},{"id":55768210,"identity":"863882eb-8f51-4d02-92d5-3d0aaffd6534","added_by":"auto","created_at":"2024-05-02 20:25:33","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":21504,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 2.\u003c/strong\u003e Correlation of frailty with PAL and sleep quality in different age groups\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNotes: \u003c/strong\u003e*P＜0.05, **P＜0.01.\u003c/p\u003e\n\u003cp\u003eThe relationship between the three at different ages was analyzed according to the Kendall's tau-b test.\u003c/p\u003e\n\u003cp\u003ePAL, physical activity level.\u003c/p\u003e","description":"","filename":"Supplementarytable2.CorrelationoffrailtywithPALandsleepqualityindifferentagegroups.xls","url":"https://assets-eu.researchsquare.com/files/rs-4230718/v1/c25de95f7255851cbf56944e.xls"},{"id":55768211,"identity":"37397189-1f37-4b44-80ea-efef6adac8fe","added_by":"auto","created_at":"2024-05-02 20:25:33","extension":"xls","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":23552,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 3.\u003c/strong\u003e Kruskal-Wallis test for total MET and frailty staging in participants with different occupations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e [Q1, Q3] indicates [First Quartile, Third Quartile]. MET, metabolic equivalents. “–” indicates that the sample size is too small for the value to be measured.\u003c/p\u003e\n\u003cp\u003eThe “a” means statistically significant differences from the non-frailty period, and “b” represents statistically significant differences from the pre-frailty period. All comparisons were Bonferroni corrected. The significance level is 0.05.\u003c/p\u003e","description":"","filename":"Supplementarytable3.KruskalWallistestfortotalMETandfrailtystaginginparticipantswithdifferentoccupations.xls","url":"https://assets-eu.researchsquare.com/files/rs-4230718/v1/1de9bd2bffbbd8603e437b3f.xls"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationship between physical activity, sleep quality, and frailty in middle-aged and older adults: a cross-sectional study Running title: The correlation between physical activity, sleep quality, and frailty","fulltext":[{"header":"1. Background","content":"\u003cp\u003ePopulation aging is a rapidly growing global phenomenon, leading to increasingly severe psychological and physical issues among older adults(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This presents a significant public health challenge and places a substantial economic burden on society(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Frailty serves as a crucial indicator of the overall health status of older individuals, encompassing physical, psychological, and social aspects(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). It reflects the body's overall health and the extent of its functional decline(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Frailty is characterized by a reduced reserve capacity of multiple body systems, heightened vulnerability to diseases, and adverse outcomes such as falls, disabilities, hospitalizations, and mortality(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Frailty is a dynamic and changing process (especially in the early stages of disease)(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), which gives an essential window of opportunity for disease prevention and treatment. Previous studies have identified women, advanced age, living alone, lower economic levels(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), rural areas(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), longer sedentary behavior(SB) time, less PA(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), and poor sleep quality(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) as risk factors for frailty, with PA and sleep quality being more intervenable in natural populations and considered an essential element in preventing frailty(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegular PA has the potential to decrease age-related chronic inflammation and oxidative stress(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), thus aiding in the prevention and mitigation of various chronic ailments(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and enhancing the physical and mental well-being of older individuals(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Engaging in moderate to high levels of PA is particularly beneficial for reducing disease risks among older adults. Sleep, a fundamental physiological necessity for the human body, plays a crucial role in overall health. Sleep-related issues affect over half of middle-aged and older adults (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), and the persistence of poor sleep quality contributes to the onset of numerous diseases(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Consequently, sleep problems have become a prevalent concern among this demographic. Reduced nighttime sleep duration and reduced sleep quality increase the risk of fragmented daytime sleepiness and narcolepsy(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), both of which are associated with a higher incidence of frailty-related conditions and all-cause mortality(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). However, the majority of the existing evidence is derived from surveys conducted among individuals aged 60 and above, primarily within communities, hospitals, and nursing homes.\u003c/p\u003e \u003cp\u003eWith the development of society, the life and economic pressure of middle-aged people has gradually increased, and their disposable time has decreased. Activities at work dominate some people's PA, and there are fewer and fewer PA based on fitness exercise, which is different from those of older people. Stress has been found to affect the quality of sleep in the population(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), and fitness and exercise can also have a significant positive effect on sleep(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), which also suggests that there may be some differences in the factors affecting the quality of sleep in middle-aged people compared to older people. Several studies in recent years have found that debilitating illness in middle-aged people also occurs frequently. Previous investigations indicate that the occurrence of pre-frailty is approximately 34.6% among individuals aged 50\u0026ndash;59 in Korea(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Moreover, numerous other studies have demonstrated that the issue of pre-frailty within the middle-aged population should not be disregarded(\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). It has been posited that early intervention to prevent frailty could potentially delay mortality rates in 3\u0026ndash;5% of older adults(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Therefore, exploring the risk factors affecting frailty and developing interventions for frailty should be more appropriately conducted with the middle-aged and elderly population in mind, and early interventions for poor lifestyle habits at an early age are more likely to help reduce the decline in quality of life and the incidence of a wide range of adverse outcomes. Therefore, this study aimed to explore the correlation between physical activity, sleep quality, and frailty in middle-aged and older adults over 45 years of age in order to intervene early in the prevalence of frailty in the population and to improve the quality of life of the population.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Population\u003c/h2\u003e \u003cp\u003eWe used the whole population sampling method to conduct a cross-sectional study in July-August 2023 by selecting resident middle-aged and elderly residents of a city in Shaanxi Province, China. After completing the informed consent form, all of these study participants completed the frailty-related questionnaire. The study questionnaire consisted of 45 items, including basic information (15 items), the Frailty Scale (5 items), the Pittsburgh Sleep Quality Scale (PSQI) (18 items), and the International Physical Activity Questionnaire Short Form (IPAQ) (7 items). Inclusion criteria: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) aged\u0026thinsp;\u0026ge;\u0026thinsp;45 years; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) having lived in the area for at least one year; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) being able to understand the questions and complete the interview or completing the survey with the help of their family members. Exclusion Criteria: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Persons with severe mental illness or impaired consciousness; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Persons with severe visual or hearing impairment that interferes with regular communication. Before starting the data collection phase, the researchers professionally trained the investigators. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e To ensure that ethical principles were followed and the rights and safety of participants were maintained, this study was approved by the Medical Ethics Review Committee of Xi'an Medical College, China (Approval No. XYLS2023090). The study was conducted using the Declaration of Helsinki (2000 version).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Measurements\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Frailty measure\u003c/h2\u003e \u003cp\u003eThis study assessed the frailty of the respondents using The Frailty Scale(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), which has been shown to predict death and disability with good construct validity and responsiveness(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). The scale contains five entries, including fatigue, endurance, mobility, number of chronic conditions, and weight loss in the most recent year. Each entry was recorded as 1 point, and according to the score, it was categorized as non-frailty (0 points), pre-frailty (1\u0026ndash;2 points), and frailty (3\u0026ndash;5 points). Study participants filled in and double-checked the entries under the guidance of trained professionals to ensure that the data were accurate and valid.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 PA assessment\u003c/h2\u003e \u003cp\u003ePA was measured using the short form of the IPAQ (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), which is widely used nationally and internationally and is more straightforward and accessible to the screen. The Chinese version of the IPAQ-SF is widely used and has been shown to have good reliability and validity(\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The scale included high, medium, and light PAL in the most recent week. Participants completed the scale using recall, and a professional interpreted the content of the scale for them. The formula for IPAQ was \" the total PA (MET/min/w)\u0026thinsp;=\u0026thinsp;MET assignment corresponding to PA \u0026times; weekly frequency (d/w) \u0026times; time per day (min/d),\" with MET assignments of 3.3 for walking, 4.0 for moderate-intensity activity, and 8.0 for high-intensity activity. The total MET of the study subjects in the last week were calculated. Then, the continuous variable was converted into a categorical variable and categorized into three groups: light PAL (\u0026lt;\u0026thinsp;600 MET/min/w), moderate PAL (600\u0026ndash;3000 MET/min/w), and vigorous PAL (\u0026ge;\u0026thinsp;3000 MET/min/w), which is similar to the grouping method in the previous literature(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Sleep quality assessment\u003c/h2\u003e \u003cp\u003eIn this study, sleep quality was assessed using The PSQI (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), which is used to evaluate better the sleep quality status of the study participants in the last month, and it is the most widely used subjective sleep assessment scale(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). The Chinese version of the scale currently in use has been shown to have good reliability and validity(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) and has been used in several studies(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), with a Cronbach's alpha of 0.736 in this study. The scale consists of 18 self-assessment items divided into seven dimensions, namely subjective sleep quality, sleep duration, time to fall asleep, sleep disorders, sleep efficiency, use of hypnotic medication, and daytime dysfunction, with scores ranging from 0 to 3 for each dimension, and a total score ranging from 0 to 21, with higher scores being associated with poorer sleep quality. Most current studies use a score of \u0026gt;\u0026thinsp;7 as a criterion for sleep disorders(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical methods\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using SPSS Statistics 25.0. Missing primary variables were removed using case-by-case deletion (in the order of sleep quality, frailty, and PA), and missing information was filled in using SPSS Multiple Interpolation for the other variables. Information on continuous variables (skewed distribution) of the study population was statistically described using median and interquartile range (IQR) [e.g., age, Body Mass Index (BMI), sedentary time, sleep quality], and categorical variables were statistically described using rates and percentages [e.g., age group, gender, ethnicity, education level, occupation, marriage, living status, family disasters, hospitalization experience, per capita monthly household income, smoking, alcohol consumption, sleep disorders, sedentary time, BMI, PAL]. Categorical data were compared using non-parametric tests, and the Kruskal-Wallis test was used for comparisons involving more than two groups of people with different characteristics, while the Wilcoxon rank test was used for comparisons between two groups of people with different characteristics. Calibrated multivariate logistic regression models were also used to assess the relationship between sleep quality, PAL, and prevalence of frailty, and the results were expressed as odds ratios (OR) with corresponding 95% confidence intervals (CI). The Kendall's tau-b test was used in this study to assess the relationship between PAL, sleep quality, and frailty. In this study, the Kruskal-Wallis test was used to explore the relationship between total MET and frailty in participants from different occupations, and all comparisons were corrected for Bonferroni. The mediating effect analysis procedure of PROCESS v3.5 software was used to test the significance of the mediating effect using the percentile Bootstrap method and to calculate the various types of effects and their 95% CI in the mediation model, with 5,000 repetitive samples and a test level of α\u0026thinsp;=\u0026thinsp;0.05, to analyze the mediating role of quality of sleep in the relationship between age and frailty in middle-aged and older adults. Correlation coefficients with P-values of less than 0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline information on participants\u003c/h2\u003e \u003cp\u003eA total of 1265 participants were included in this study. After excluding cases with missing primary variables, 1042 participants were included in the final survey, accounting for 82.37% of the initial sample. The participants ranged from 45 to 92 years, with a median age of 60 years. Among the participants, 47.12% were middle-aged (45\u0026ndash;59 years), and 52.88% were female. The total number of patients with frailty was 74, with a prevalence of 7.1%. The prevalence of frailty was 4.6% in men and 8.4% in women. Furthermore, the prevalence of frailty was 5.7% in the middle-aged group and 8.3% in the elderly group. When examining different occupations, the highest prevalence rates were observed in agriculture (8.0%) and laborers (8.2%), while residents working in institutions had the lowest prevalence rate (1.5%). The findings of the univariate analyses indicated significant differences across various factors, including age, sleep quality, gender, education level, occupation, experience of hospitalization in the last year, per capita monthly household income, SB, BMI subgroups, and PAL in relation to different stages of frailty (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (\u003cb\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/b\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Multifactorial logistic regression analysis of participant occurrence of frailty\u003c/h2\u003e \u003cp\u003eAdjusting for the inclusion in the regression model of variables that were significantly different based on the results of single factor analysis and variables that have been elaborated in the extensive literature to have an impact on frailty (living status (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e)), it was found that when the outcome variables were non-frailty, pre-frailty, and frailty, it was found that compared to high levels of PA, both in the non-frailty (OR 0.318; CI 0.149\u0026ndash;0.682; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and pre-frailty (OR 0.204; CI 0.098\u0026ndash;0.425; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), middle-aged and older adults with light levels of PA were more likely to develop frailty, and middle-aged and older adults without sleep disorders (OR 2.148; CI 1.241\u0026ndash;3.720; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) had a lower risk of frailty. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFactors associated with participant frailty and pre-frailty using multi-categorical logistic regression analysis\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClusters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNon-frailty vs. Frailty\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePre-frailty vs. Frailty\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge Groups(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026ndash;59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.605(0.920\u0026ndash;2.798)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.108(0.644\u0026ndash;1.906)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.688(0.887\u0026ndash;3.211)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.294(0.687\u0026ndash;2.436)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.865(0.321\u0026ndash;2.334)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.035(0.388\u0026ndash;2.760)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.944\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.306(0.425\u0026ndash;4.010)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.088(0.356\u0026ndash;3.319)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh school and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccupations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarming\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.561(0.292\u0026ndash;1.078)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.922(0.485\u0026ndash;1.751)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWorkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.416(0.149\u0026ndash;1.165)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.627(0.229\u0026ndash;1.715)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eService worker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.810(0.200-3.287)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.935(0.233\u0026ndash;3.762)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployee or professional in an organization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.775(0.316\u0026ndash;24.370)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.539(0.172\u0026ndash;13.755)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiving status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.196(0.426\u0026ndash;3.361)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.317(0.487\u0026ndash;3.562)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003enon-living alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHospitalization Experience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.748(0.959\u0026ndash;3.188)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.202(0.681\u0026ndash;2.121)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage monthly family income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2500RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.378(0.046\u0026ndash;3.135)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.237(0.030\u0026ndash;1.898)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500-5000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.698(0.077\u0026ndash;6.341)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.432(0.049\u0026ndash;3.807)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5000-10000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.934(0.091\u0026ndash;9.606)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.477(0.048\u0026ndash;4.750)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;10000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.148(1.241\u0026ndash;3.720)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.215(0.718\u0026ndash;2.058)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSB time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;4h/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.919(0.336\u0026ndash;2.513)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.671(0.262\u0026ndash;1.715)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4-6h/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.432(0.775\u0026ndash;7.626)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.706(0.577\u0026ndash;5.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6-8h/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.876(0.269\u0026ndash;2.853)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.961(0.319\u0026ndash;2.894)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;8h/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThin and normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.704(0.799\u0026ndash;3.633)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.480(0.722\u0026ndash;3.033)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.284\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eoverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.801(0.873\u0026ndash;3.713)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.120(0.562\u0026ndash;2.229)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.748\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eobese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.318(0.149\u0026ndash;0.682)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.204(0.098\u0026ndash;0.425)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.104(0.510\u0026ndash;2.389)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.584(0.275\u0026ndash;1.237)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVigorous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: Adjusted for age group, sex, education level, occupation, residence, hospitalization in the past year, per capita monthly household income, sleep quality, SB time, BMI subgroup, and PAL covariates.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003cp\u003eBMI, Body Mass Index. SB, sedentary behavior. PAL, physical activity level.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Correlation analysis between PA, sleep quality, and frailty\u003c/h2\u003e \u003cp\u003eThis study found that the prevalence of frailty and sleep disorders among middle-aged and elderly residents of the region was 7.1% and 34.5%, respectively. Residents with high levels of physical activity accounted for 26.0% of the total participants. Through Kendall's tau-b correlation analysis, a noteworthy positive correlation between sleep quality and frailty status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was observed. Nevertheless, there was no substantial correlation between PAL and frailty and sleep quality (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.01), suggesting a comparable correlation in both the middle-aged and elderly cohorts. (\u003cb\u003eSupplementary table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/b\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Correlation analysis between total MET and frailty staging in different occupations\u003c/h2\u003e \u003cp\u003eThis study analyzed the relationship between MET and the occurrence of frailty according to different occupations and found that MET were significantly correlated with frailty staging in the total population (H\u0026thinsp;=\u0026thinsp;24.060, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similar correlations were found in farming, laborers, and other occupations (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but there were also differences. The highest and lowest values of median MET among farmers and laborers (construction workers/factory workers) occurred in the pre-frailty and frailty periods, respectively, while the highest and lowest values of median MET among other occupations occurred in the non-frailty and frailty periods, respectively. (\u003cb\u003eSupplementary table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/b\u003e)\u003c/p\u003e \u003cp\u003eWe further analyzed the relationship by dividing the occupations into two groups based on the presence or absence of prolonged periods of heavy PA. It was found that there was a significant correlation between MET and the staging of frailty in both types of occupations. The difference was that the highest values of MET in Occupation 1 in the presence of substantial PA occurred in the pre-frailty period (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, the highest values of metabolic equivalents in Occupation 2, which did not contain substantial physical activity, occurred in the no-frailty period (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The results also showed that residents in occupation 1 (693\u0026ndash;8466 MET/min/w) generally had significantly higher MET than occupation 2 (271-1140.5 MET/min/w). However, the prevalence of frailty was 8.0% among the inhabitants of occupation 1. In occupation 2, the prevalence is 5.4%. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Mediating effects of sleep quality between age and frailty\u003c/h2\u003e \u003cp\u003eThrough the implementation of the Bootstrap method, 5,000 Bootstrap samples were randomly selected from the original sample (n\u0026thinsp;=\u0026thinsp;1042) to conduct direct and indirect mediation effect tests. The results revealed that age played a significant role in predicting frailty (B\u0026thinsp;=\u0026thinsp;0.016; SE\u0026thinsp;=\u0026thinsp;0.004; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, when the mediating variable of sleep quality was introduced, age remained a significant positive predictor of sleep quality (B\u0026thinsp;=\u0026thinsp;0.055; SE\u0026thinsp;=\u0026thinsp;0.014; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while sleep quality also had a significant impact on frailty (B\u0026thinsp;=\u0026thinsp;0.042; SE\u0026thinsp;=\u0026thinsp;0.008; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Moreover, the Bootstrap confidence intervals for the direct effect of age on frailty and the mediating effect of sleep quality were evaluated, neither of which encompassed the value of 0. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e) These findings indicate that sleep quality not only directly predicted frailty but also acted as a mediator in influencing the role of age on frailty, with a mediating effect of 12.43%. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects model with sleep quality as a mediating variable\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eModel Ⅰ (Sleep Quality)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eModel Ⅱ (Frailty)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eModel Ⅲ (Frailty)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep Quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.588\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.572\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.398\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003eNote\u003c/b\u003e: *** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Each variable in the model is standardized to bring into the regression equation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eModel Ⅰ: Age predicts Sleep Quality.\u003c/p\u003e \u003cp\u003eModel Ⅱ: Age predicts frailty.\u003c/p\u003e \u003cp\u003eModel Ⅲ: Sleep Quality and age together predict frailty.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of mediation effect analysis of sleep quality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEffect type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEfficacy value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBOOT criteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eBoot 95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRelative effect value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003elower bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eupper bound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediary effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.43%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e87.57%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote\u003c/b\u003e: Boot standard errors, Boot 95% CI lower bounds, and upper bounds refer to the common errors, lower bounds, and upper bounds of the 95% confidence intervals of the indirect effects estimated by the bias-corrected percentile Bootstrap method, respectively; the variables in the model are standardized and brought into the regression equation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Comparison of frailty with different features\u003c/h2\u003e \u003cp\u003eThis study found that frailty was 7.1% in the middle-aged and older adults in the region, and the prevalence in the middle-aged (5.7%) was low compared to the elderly (8.3%). A previous study has calculated the prevalence of frailty in elderly residents over 60 years of age in Northwest China to be 9.1%(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), which is relatively high compared to the present study, and this may be related to the environment. The site is located under the Qinling Mountains, with large green areas and good air quality, which has a preventive effect on frailty(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). In addition, because this study called on middle-aged and elderly residents in the area voluntarily, some older adults with mobility difficulties and those who were bedridden were unable to arrive at the site, which resulted in a bias in the health status of older people in this study, but this also indicates that the actual prevalence of frailty among older people may be higher than the results obtained in this study.\u003c/p\u003e \u003cp\u003eThe univariate analyses of variance results showed that the differences in residential status(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), marital status(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), and smoking status(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e) were not significant across the stages of frailty, which is different from the results of previous studies. People who live alone are more likely to contribute to the onset of loneliness, anxiety, and even depression(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e), which can seriously affect their quality of life. Loneliness accelerates the progression of frailty(\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) and serves as a mediator and moderator of a wide range of adverse health outcomes(\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). The fact that this study included some rural residents, with close interaction between neighbors, and living alone is less likely to result in loneliness compared to the community may have influenced the results, and it will be necessary to follow up the study to confirm the conjecture. Studies have shown that the high levels of harmful and potentially harmful substances in unburned tobacco smoke(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e) increase the risk of many cancers and chronic diseases(\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e) and that prolonged exposure to secondhand smoke and some environmental pollutants accelerates the onset and progression of physical decline and frailty(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). However, this study did not investigate the population exposed to secondhand smoke over a long period, and more research is needed to explore the effects of long-term exposure to secondhand smoke and other harmful substances on the health of residents in the region.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Correlations between PA, sleep quality and frailty\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1 Correlation analysis between sleep quality and PA\u003c/h2\u003e \u003cp\u003eAn investigation demonstrates that the occurrence of sleep quality disorders among the elderly in Tianjin stands at 14.39%(\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e), which is less than satisfactory when compared to the prevalence of sleep disorders in rural areas of Shaanxi Province among middle-aged and elderly individuals. Based on Kendall's tau-b test, there is no notable correlation observed between the quality of sleep and PA. This comes after a cohort study showed that poor sleep can lead to a significant increase in the risk of several diseases and even death and that higher levels of PA, or meeting the World Health Organization (WHO) recommendations for moderate-to-vigorous physical activity (MVPA), can significantly mitigate the harmful effects of poor sleep(\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). A study conducted in Africa comparing the quality of sleep in rural and urban areas found that sleep quality in rustic regions was inferior to that in urban areas, potentially due to more vigorous PA and multiple sleep schedules(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Various forms of exercise exert different effects on the body, with the fusion of muscular endurance training and walking exhibiting a particularly notable influence on sleep(\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). The discrepancy between PA and sleep quality, as well as the outcomes of earlier studies, may be attributed to the specificity of PA in rural settings (see details below).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2 Correlation analysis between sleep quality and frailty\u003c/h2\u003e \u003cp\u003eIn this study, age was found to impact frailty, with the risk of frailty increasing. Sleep quality can be involved as a mediator in age's influence on frailty in middle-aged and elderly residents. Decreased sleep quality linked to the onset of frailty (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), chronic loss of sleep quality negatively affects the immune system(\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). In addition, long-term sleep quality decline can limit the activity level of the organism(\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), resulting in a decline in physical function(\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e), which seriously affects physical(\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e) and mental health(\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e), significantly reducing the quality of life(\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e) and greatly increasing the risk of death. Long-term chronic diseases can also lead to declining sleep quality(\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e), resulting in a vicious circle. Subsequent studies can reduce the incidence of frailty by exploring the relevant factors that affect sleep quality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3 Analysis of the correlation between PA and frailty in different occupational characteristics\u003c/h2\u003e \u003cp\u003eThe results of previous studies suggest that PAL is associated with the occurrence of frailty. However, the present study found no significant correlation between the two, considering that this may be related to the grouping of PAL in this study. The characteristics of PA in occupations such as farmers, where there is a large amount of PA over a long period, are different from the PA based on fitness exercise in previous studies, and exploring the correlation between the total metabolic equivalents and the staging of frailty in different occupations is more likely to illustrate the association between PA and frailty. Therefore, we analyzed the occupations in groups, and the results confirmed the above view. The highest prevalence of frailty was found in the occupations of farmers and laborers, and the relationship between PA and frailty was different from that of the other occupations, probably because of the long periods of heavy PA in both occupations.\u003c/p\u003e \u003cp\u003eIn order to further confirm the above conjecture, this study will be divided into two groups based on whether or not the occupations have long-term high levels of PA. It was found that Occupation 1, which has long-term high levels of PA, is more likely to have a pre-frailty period as the intensity of PA reaches its highest value. In contrast, occupation 2 that do not have long periods of high levels of PA are more likely to experience periods of non-frailty as the level of PA increases, which is consistent with the results of previous studies. Nevertheless, regardless of occupation, residents with low PA contribute to the development of frailty. In addition, we have found that the prevalence of the disease is higher in residents with a long history of heavy PA.\u003c/p\u003e \u003cp\u003eThe risk of frailty generally decreases with progressively higher levels of PA. However, excessive PA hurts the organism, counteracting the positive effects of PA on the body, and may produce a different developmental trajectory. We have speculated about this. On the one hand, those residents whose own course reversed to a non-frailty stage have progressed to a pre-frailty stage due to the effects of prolonged periods of heavy PA; on the other hand, it is possible that residents in a pre-frailty stage are prevented from reversing to a non-frailty stage due to the long-term effects of the disease. The reasons for this result may be multifaceted, and more longitudinal studies are needed to explore this.\u003c/p\u003e \u003cp\u003eFirstly, PA has different effects on the human body depending on the environment in which it takes place and the way in which it is carried out. PA related to home and physical exercise was associated with a reduced risk of death, and occupational and transportation-related PA was not associated with an adverse risk(\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). Additionally, Rachel E. et al(\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e) study compared different types of PA found that regular fitness exercise reduces the risk of heart disease and that strenuous, heavy, occupational-related physical labor causes arterial stiffness and a negative effect on the nerve. Work-related backbreaking physical work negatively affects arterial stiffness and nerve reflexes, which increases the risk of heart problems; nevertheless, this does not indicate that all work-related PA can harm health, only chronic, strenuous PA can adversely affect the body.\u003c/p\u003e \u003cp\u003eSecondly, with increasing age, significant changes occur in the cardiovascular system of middle-aged and older adults. Thickening and hardening of the aorta and thickening of the ventricular wall due to hypertrophy of the ventricular cells predispose them to increased cardiac load and diminished left ventricular contractile performance(\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e). The impairment of cardiovascular function is accelerated in middle-aged and older adults under the effect of prolonged high levels of PA. Since cardiovascular disease and frailty have similar inflammatory response mechanisms, it is easier to accelerate the process of frailty development(\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe reason for the difference between the results of this study and previous studies may also be related to the characteristics of the life of the inhabitants of the area. More than half of the people in the present study work in agriculture. Due to the imperfections in transportation, public fitness facilities, and lack of health care awareness, most residents lack regular PA based on fitness exercises, and the heavy physical labor generated by long-term agriculture produces chronic damage to the body, leading to the onset of frailty. In addition, the occupations of agriculturalists as well as construction workers are characterized by long-term exposure to ultraviolet ray radiation, which can trigger a state of cellular senescence and skin inflammation, stimulate immune senescence as well as degeneration of neighboring cells, and evoke a remodeling of the immune system similar to that of normal aging(\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). Some studies have found that long-term occupational exposure to pesticides increases the prevalence of chronic neurological and cardiovascular diseases(\u003cspan additionalcitationids=\"CR72\" citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e), as well as cancer, and even increases the risk of cognition, memory, and the occurrence of psychological distress and suicide in adults(\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e) and that the gradual accumulation of these adverse effects may lead to the premature onset of frailty. Moreover, the period investigated in this study was from July to August, when local temperatures could reach 40\u0026deg;C or more. The farmers had just finished their heavy agricultural production. PA in hot conditions increases the risk of Exercise Heat Stroke (EHS) (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e) and affects β-activities in most areas of the brain(\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). The prevalence of negative emotions increases significantly when a person is outdoors in the heat for more than 120 min(\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e). Older adults with hypertension or diabetes, when physically active for long periods in hot environments, may exhibit tremendous cellular stress, leading to cellular damage(\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). Thus, hot weather may have contributed to the higher prevalence of frailty obtained in this study, and considering that the development of frailty is reversible, subsequent studies may consider comparing the changes in prevalence across seasons to confirm the above observation.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Limitations\u003c/h2\u003e \u003cp\u003eThis study has the following shortcomings. Firstly, the relatively large number of people working in agriculture in this study area is subject to selection bias. Secondly, this is a cross-sectional study, and the results obtained can only represent the current state of the participants. Considering that frailty is a dynamic process, subsequent longitudinal follow-ups can be conducted at different periods to compare the differences in frailty over time. Thirdly, the subjects of this study are not representative of all middle-aged and older adults, and larger sample sizes and multi-center studies can be conducted in the future to refine the types of PA and better explore the relationship between the three.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003ePA and sleep quality both play a role in influencing frailty, although there is no significant correlation between PA and sleep quality. Sleep disorders can increase the likelihood of developing frailty and act as a mediator in the relationship between age and frailty. On the other hand, the impact of PA on frailty can differ based on the specific characteristics of the individual\u0026apos;s occupation. These factors are closely tied to the lifestyle and habits of the population.\u003c/p\u003e\n"},{"header":"Abbreviations","content":"\u003cp\u003ePA (Physical activity)\u003c/p\u003e\n\u003cp\u003ePSQI (Pittsburgh Sleep Quality Index)\u003c/p\u003e\n\u003cp\u003eIPAQ (International Physical Activity Questionnaire)\u003c/p\u003e\n\u003cp\u003ePAL (Physical activity level)\u003c/p\u003e\n\u003cp\u003eMET (Metabolic equivalent)\u003c/p\u003e\n\u003cp\u003eIQR (Interquartile range)\u003c/p\u003e\n\u003cp\u003eBMI (Body Mass Index)\u003c/p\u003e\n\u003cp\u003eOR (Odds ratio)\u003c/p\u003e\n\u003cp\u003eCI (Confidence interval)\u003c/p\u003e\n\u003cp\u003eSB (Sedentary behavior)\u003c/p\u003e\n\u003cp\u003eWHO (The World Health Organization)\u003c/p\u003e\n\u003cp\u003eMVPA (Moderate-to-vigorous physical activity)\u003c/p\u003e\n\u003cp\u003eEHS (Exercise Heat Stroke)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants gave written informed consent. The study was approved by the Ethics Committees of Xi’an Medical University and conducted in accordance with the Declaration of Helsinki (Ethics approval No. XYLS2023090).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNatural Science Basic Research Program of Shaanxi (Program No. 2023-JC-YB-827)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLS, DZ, and WW were involved in the conceptualization of the paper, the survey, data collation, formal analysis, and writing of the first draft; DL and MW contributed to data collection, data collation, and analysis. YL contributed to the conceptualization of the study, access to funding, the survey, the methodology, supervision, and editing. MX was involved in the survey, data collation, and data management of the paper. JH and LZ Participated in the survey, analyses, and other work on this paper. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e We thank all study participants and clinicians. We thank the Shaanxi Provincial Medical Association, the Third Affiliated Hospital of Xi'an Medical College of Xi'an Medical College, and the Ankang Medical Association. We thank all medical student volunteers and clinicians who participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen LK. Editorial: Aging, Body Composition, and Cognitive Decline: Shared and Unique Characteristics. 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Nat Rev Cardiol. 2018 Sep;15(9):505\u0026ndash;22. \u003c/li\u003e\n\u003cli\u003eSalminen A, Kaarniranta K, Kauppinen A. Photoaging: UV radiation-induced inflammation and immunosuppression accelerate the aging process in the skin. Inflamm Res. 2022 Aug;71(7\u0026ndash;8):817\u0026ndash;31. \u003c/li\u003e\n\u003cli\u003ede Graaf L, Boulanger M, Bureau M, Bouvier G, Meryet-Figuiere M, Tual S, et al. Occupational pesticide exposure, cancer and chronic neurological disorders: A systematic review of epidemiological studies in greenspace workers. Environ Res. 2022 Jan;203:111822. \u003c/li\u003e\n\u003cli\u003eOhlander J, Fuhrimann S, Basinas I, Cherrie JW, Galea KS, Povey AC, et al. Impact of occupational pesticide exposure assessment method on risk estimates for prostate cancer, non-Hodgkin\u0026rsquo;s lymphoma and Parkinson\u0026rsquo;s disease: results of three meta-analyses. 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Available from: https://pubmed.ncbi.nlm.nih.gov/36462879/\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Frailty, Sleep quality, Physical activity, Middle-aged and elderly people","lastPublishedDoi":"10.21203/rs.3.rs-4230718/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4230718/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Frailty is linked to numerous negative health consequences, with past research indicating that physical activity (PA) and sleep quality play a role in influencing frailty among older adults. As societal norms evolve, middle-aged adults are faced with time constraints that may result in differences in PA and sleep compared to older adults. Despite this, there is a limited amount of research focusing on middle-aged and older adults. This study seeks to examine the prevalence of frailty among middle-aged and older adults in the region, as well as investigate the connection between sleep quality, PA, and frailty.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This cross-sectional study involved 1,265 middle-aged and elderly permanent residents from a region in Shaanxi Province, China. Participants were selected randomly for a physical examination and questionnaire survey. The questionnaires covered sociodemographic information, the Frailty Scale, the Pittsburgh Sleep Quality Index (PSQI) Scale, and the International Physical Activity Questionnaire (IPAQ). Statistical description and correlation analysis between variables were conducted using SPSS software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 1042 study participants were ultimately included in the analysis, with 74 classified as frailty and 444 as non-frailty. Adjusting for relevant covariates revealed that middle-aged and older adults engaging in light PA were more likely to be frailty compared to those with high PAL during non-frailty (CI 0.149-0.682; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01) and pre-frailty stages (CI 0.098-0.425; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Conversely, individuals without sleep disorders were less likely to be frailty (CI 1.241-3.720; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01). Occupational MET values were highest during the pre-frailty period in the presence of substantial PA (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Sleep quality not only directly predicted frailty but also acted as a mediator in influencing the role of age on frailty, with a mediating effect of 12.43%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Both PA and sleep quality play a role in frailty. The impact of PA on frailty is influenced by the nature of the individual's occupation. Sleep disorders can heighten the risk of frailty, with sleep quality acting as a mediator in the relationship between age and frailty.\u003c/p\u003e","manuscriptTitle":"Relationship between physical activity, sleep quality, and frailty in middle-aged and older adults: a cross-sectional study Running title: The correlation between physical activity, sleep quality, and frailty","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 20:17:28","doi":"10.21203/rs.3.rs-4230718/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9ffa6b83-2bbc-4672-9a35-09777231af4e","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T11:53:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-02 20:17:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4230718","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4230718","identity":"rs-4230718","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}