Effects of falls on self-rated health and anxiety in Chinese elderly chronic multimorbid patients : moderating role of psychological resilience

Effects of falls on self-rated health and anxiety in Chinese elderly chronic multimorbid patients : moderating role of psychological resilience | 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 Effects of falls on self-rated health and anxiety in Chinese elderly chronic multimorbid patients : moderating role of psychological resilience Shaoliang Tang, Jingyu Xu, Xiaoyan Mao, Huilin Jiao, Yuxin Qian, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4571446/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Sep, 2024 Read the published version in BMC Geriatrics → Version 1 posted 11 You are reading this latest preprint version Abstract Introduction This study enquired into the effects of falls on self-rated health and anxiety symptoms, and the moderating role of psychological resilience in China's elderly chronic multimorbid patients. Methods Data were taken from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). We used the linear regression model to delve into the association among falls and self-rated health and anxiety symptoms, the moderating roles of psychological resilience was verifed by the moderation analysis, and we also used the replacement model to test the robustness. Finally, the results of the study were further verified by completing the heterogeneity analysis through subgroup regression. Results 3141 older people with chronic multimorbidity were included in our study. The linear regression results showed that falling behavior was significantly negatively correlated with self-rated health symptoms of Chinese elderly chronic multimorbid patients (β = -0.2017, p < 0.01), and significantly positively correlated with anxiety symptoms (β = 0.7284, p < 0.01). Among the moderating effects, we found that psychological resilience played a moderating role between falling behavior and anxiety symptoms (β = − 0.147 [-0.214, -0.079], p < 0.01). Finally, we found heterogeneity in the study results by gender and place of residence. Conclusion The presence of falls tends to make Chinese elderly chronic multimorbid patients develop poorer self-rated health and higher anxiety levels. High levels of psychological resilience have a moderating effect on inhibiting the development of anxiety symptoms. Falls Anxiety Psychological resilience Chinese elderly chronic multimorbid patients Figures Figure 1 Figure 2 1. Introduction Falls are defined as an event in which a person unintentionally falls to the ground, floor, or other lower level causing them to lose consciousness[ 1 ]. Falls have now become a very high incidence of public health problems globally [ 2 ]. According to the survey, falls has become one of the public health problems that seriously threaten the life and health safety of the elderly worldwide, approximately 68,400 fatal falls happen each year[ 1 ]. Also, as a common geriatric syndrome, it is one of the leading causes of injury and death in the elderly [ 3 ]. A study showed that 27.5% of people over 65 years old had fallen at least once a year, and 10.2% of people over 65 years old rated at least one fall-related injury [ 4 ]. In China, Falls are also common among the elderly, with many fall risk factors increasing with age, including functional decline, polypharmacy, and chronic diseases in the elderly [ 5 ]. The presence of fall behavior not only predisposes older adults to physical health impairment issues (e.g. hip fracture) [ 6 ], but can also be detrimental to their mental health symptoms. Limb damage, mobility problems and reduced independence due to falls can strongly affect some emotionally vulnerable older adults, making them more likely to develop symptoms of anxiety and fear of falling again [ 7 ] . Chronic multimorbidity is usually regarded as the co-presence of two or more chronic diseases in a single individual [ 8 ]. A recent study showed that the overall prevalence of chronic multimorbidity is currently as high as 37.2% globally, with more than half of all adults over the age of 60 years suffering from two or more chronic diseases [ 9 ]. The interplay of multiple diseases in patients with chronic multimorbidity can easily lead to further declines in physical and cognitive function [ 10 ], making them susceptible to fall behavior. In turn, the consequences of falling behavior are even worse for patients with chronic multimorbidity, thus forming a vicious circle. In previous studies, scholars have focused more on the effects of falls on the physical and mental health of the elderly[ 5 , 11 , 12 ], and few studies have focused on the consequences of falls on patients with chronic multimorbidity. Therefore, this study will take the chronic multimorbid patients group as the research object to further explore the series of impacts on their physical and mental health caused by the emergence of falls. Self-rated health is a very effective clinical method for measuring overall health, which can reflect the continuity of a person's perceived health [ 6 ], and can enable patients to visually represent the changes in their own health before and after falls, so it is of some research significance to further study the relationship between falls and their physical health symptoms of patients with chronic multimorbidity through self-rated health. In addition, anxiety and depression are common psychological disorders in the elderly population and are two important factors affecting mental health. It has been suggested that falls are a potential contributor to anxiety or depression in older adults, but they have not yet been adequately studied [ 13 ]. However, in reality, more prior studies have discussed the association between falls and depression, and most scholars believe that there is a significant interaction between falls and depressive symptoms[ 12 , 14 – 16 ], and the physiological damage caused by falls will increase the risk of depression, which is more likely to lead to falling again. Some scholars have also delved into mechanisms of action between them, including the cognitive and motor delays, and functional limitations[ 17 , 18 ]. In contrast, very little research has adequately discussed the impact of fall events on anxiety, which is one of the most common mental health disorders with a global prevalence of 2.4% − 29.8% per year[ 19 , 20 ], and as far as we know, Only one study alone has explored separate changes in anxiety symptoms due to fall behavior[ 21 ], and its findings suggest that the elderly who have experienced falls are more likely to suffer high levels of anxiety due to physical or mental injury. It is thus clear that the association between falls and anxiety in chronic multimorbid patients is likewise of some research value, however, it has not been widely concerned by scholars. Therefore, to fill the aforementioned gaps, this study focused on a group of elderly chronic multimorbidity patients in China, aiming to delve into the impact of the emergence of fall behavior on their self-rated health and anxiety status., with a focus on post-fall interventions, which would be beneficial for the development of post-fall recovery measures for elderly chronic multimorbid patients. Also, in this case, it was further hypothesized that patients in different mental states may be affected to different degrees after falls. In positive psychology, there is a very important concept called psychological resilience, which refers to the process by which a set of abilities and characteristics interact dynamically to enable an individual to recover quickly and cope successfully in times of great stress and danger[ 22 ]. It has been shown that the level of psychological resilience has an impact on anxiety and depression in the elderly, which in turn affects their outlook on life[ 23 ]. People in the condition of their old age are always full of various challenges and stressors[ 24 ], such as declining health, and the mindset and the way they cope with the challenges become particularly important at this time. Whether psychological resilience plays a positive role in the adversity of elderly patients with chronic multimorbidity who are suffering from multiple illnesses and experiencing falls remains to be further examined. Therefore, the ability of psychological resilience to moderate the relationship between falls and self-rated health and anxiety status in elderly chronic multimorbid patients is another question to be considered in our study. 2. Materials and Methods 2.1. Participants The data for this paper were obtained from the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS).The CLHLS project randomly select nearly half of counties and cities in 22 provinces in China, and to comprehensively collect detailed information on the individual behaviors, families, and social environments of seniors aged 60 and above. This data has the advantages of large sample size, long follow-up period and strong representativeness, with good reliability and validity. Since information on falls, anxiety, and psychological resilience levels in older adults was rated only in 2018, we conducted a cross-sectional study. In this study, 15,874 samples of raw data were initially obtained, and the criteria for inclusion of study subjects were (a) age ≥ 60 years (b) two or more chronic diseases (c) complete answers to the relevant items of the "Anxiety Scale" and the assessment of "psychological resilience" in the CLHLS dataset (d) no other key variables were missing or abnormal. Finally, A total of 3,141 individuals were included in the study.The sample processing is shown in Fig. 1 . 2.2. Measurements 2.2.1. Anxiety In this study, we used the Generalized Anxiety Scale (GAD-7) in the CLHLS to assess anxiety symptoms in older patients with chronic multimorbidity. We assessed the frequency and severity of anxiety symptoms using participants' descriptions of their emotional feelings. The scale consists of seven items, each with four options. "The scores ranged from 0 to 21. Anxiety scores < 5 were classified as no anxiety symptoms, and ≥ 5 were classified as having anxiety symptoms. The higher the score, the worse the anxiety. The Cronbach's alpha coefficient of the GAD-7 was 0.91[ 25 ]. 2.2.2. Self-rated health Self-rated health, as a subjective health measure, can better reflect people's health. In order to better measure another dependent variable in this study, we selected the item "How do you feel about your own health now?" from the CLHLS questionnaire. This item measures the self-rated health symptoms of elderly chronic multimorbid patients. According to the question answer setting, we used SRH as a continuous variable with a range of 1–5, with higher scores reflecting better health symptoms. 2.2.3. Falls Falls were selected as the independent variable of the study, and for the measurement of fall behavior a question like this one from CLHLS was used, "Have you fallen in the past year?" If the respondent answered "yes", it was considered that a fall had occurred. 2.2.4. Psychological resilience According to existing research[ 26 ], the psychological resilience score needed for this study was specifically measured by five items in the CLHLS: "Are you able to think through whatever comes your way?", " Are you in charge of your own affairs?" "Do you feel that you are getting worse as you get older, and that you have trouble doing things?" "Do you feel nervous and scared?" and "Do you feel lonely?" All of the above items were on a five-point Likert scale, with items one and two being reverse questions, which were recoded in this study to summarize the scores, which ranged from 5 to 25. A high or low score predicts a high or low level of psychological resilience. In terms of internal consistency confidence, the acceptable value for the psychological resilience scale was 0.625. 2.2.5. Control variables This study also referred to previous studies and a range of control variables were selected that were likely to cause anxiety symptoms and changes in self-rated health[ 18 ], which contain a total of three aspects: socio-demographic characteristics, family socio-economic characteristics, and healthy living conditions. First, socio-demographic characteristics include age, gender, place of residence, and marital symptoms. Among them, for marital symptoms, we reclassified them into married and divorced/widowed/unmarried/never married categories based on the answers to the questionnaire. Second, considering that family socio-economic characteristics, type of residence, and insurance symptoms may have an impact on the physical and psychological conditions of chronic multimorbid patients after a fall, in this paper, we selected economic status, type of residence, and whether or not they have old-age pension and medical insurance as the socio-economic characteristics of the family, of which the variable of economic status was measured using the question "Which of the following categories does your life belong to when compared in the local area? " is used to measure. Third, healthy living conditions variables included whether or not they smoked or drank alcohol, daily exercise, hours of sleep, number of chronic diseases and ADL, in which ADL was calculated and assigned a total score based on the following variables: bathing, dressing, toilet, indoor activities, self-control, and eating (= 6 is unimpaired and assigned a value of "0"). <6 is impaired assigned a value of "1"). Detailed settings for each variable can be found in Table 1 . Table 1 Coding of variables Variable Coding Anxiety <5 = 0, ≥ 5 = 1 Levels of anxiety 0∼21 Self-rated health Very poor = 1, Poor = 2, Fair = 3, Good = 4, Very good = 5 Falls No = 1,Yes = 2 Psychological resilience 5∼25 Age ≥ 60 Gender Male = 1, Female = 2 Marital symptoms Married = 1, Divorced/Widowed/Never married = 2 Current residence Urban = 1, Rural = 2 Family economic symptoms Very rich = 1, Rich = 2, So so = 3, Poor = 4, Very poor = 5 Co-residence With household member(s) = 1,Alone = 2 In an institution = 3 Pension insurance Yes = 1,No = 2 Medical insurance Yes = 1,No = 2 ADL No impaired = 0, Impaired = 1 Smoke Yes = 1,No = 2 Drink Yes = 1,No = 2 Exercise Yes = 1,No = 2 Sleep time Continuous variable Chronic diseases Continuous variable 2.3. Statistical analysis First, we performed descriptive analysis by calculating the frequency and percentage of categorical variables, as well as the mean ± standard deviation of continuous variables. Second, we used a linear regression model to test whether there was a correlation between falls and self-rated health and anxiety symptoms in elderly chronic multimorbid patients. In addition, we incorporated a moderated effects model that utilized the multiplication of the independent and moderating variables to take shape an interaction item, and added the independent variable X, dependent variable Y, moderating variable W, and interaction item XW to the model in order to test the presence of moderating effects on psychological resilience. Finally, since both self-rated health and anxiety symptoms scores are continuous variables, we used the method of replacing the model to carry out the robustness test to verify the reliability of the regression results. We also analyzed the heterogeneity by different genders and places of residence according to group regression. The entire study was processed and analyzed using STATA 17.0. 3. Results 3.1. Descriptive statistical analysis As shown in Table 1 , there are 3,141 elderly patients with chronic multimorbidity in this study. Among them, the proportion of males is 41.32% ; 14.25%, 32.31%, 29.67%, and 23.77% of the total population were aged 60–70, 71–80, 81–90, and 90 years or older, respectively; 45.69% of the population were married. 52.02% of the population were residing in urban areas compared to rural areas; 79.91% were living with family members. 18.75% were in wealthy families; 39.99% and 59.10% had pension insurance and medical insurance, respectively; daily living activities were not impaired. 79.91% live with family members. 18.75% are rich. 39.99% have pension insurance and 59.10% have medical insurance. 78.51% are not impaired in activities of daily living. 85.90% and 87.97% do not have the habit of drinking and smoking. 33.21% exercise consistently and the average sleep time is 7.17 h. In addition, nearly half of the chronic multimorbid patients in this study had three or more illnesses 48.39%. 26.27% of the sample population had fallen in the past year. 83.89% had no anxiety symptoms, and 78.64% considered their overall health symptoms to be good. Table 2 Descriptive statistical analysis. Characteristics N / Mean ± SD % Sex Male 1298 41.32 Female 1843 58.68 Age 60–70 448 14.25 71–80 1015 32.31 81–90 932 29.67 91 above 746 23.77 Marital symptoms Married 1435 45.69 Divorced/Widowed/Never married 1706 54.31 Residence unban 1634 52.02 rural 1507 47.98 Family economic symptoms very rich 68 2.16 rich 521 16.59 so so 2123 67.59 poor 381 12.13 very poor 48 1.53 Co-residence with household member(s) 2510 79.91 alone 550 17.51 in an institution 81 2.58 Pension insurance Yes 1256 39.99 No 1885 60.01 Medical insurance Yes 1668 53.10 No 1473 46.90 ADL Impaired 675 21.49 No impaired 2466 78.51 Smoke Yes 443 14.10 No 2698 85.90 Drink Yes 378 12.03 No 2763 87.97 Exercise Yes 1043 33.21 No 2098 66.79 Sleep 7.17 ± 2.37 Chronic diseases 2 1621 51.61 3 840 26.74 3 above 680 21.65 Falls Yes 825 26.27 No 2316 73.73 Anxiety symptoms 1.86 ± 3.128 Self-rated health very good 270 8.60 good 895 28.49 so so 1305 41.55 bad 617 19.64 very bad 54 1.72 3.2. Regression model results First, we used linear regression model to confirm the correlation between falls and self-rated health and anxiety symptoms of elderly chronic disease multimorbid patients, and the regression results are shown in Table 3 and Table 4 . Among them, Table 3 uses anxiety symptoms as the dependent variable, and in the unadjusted model (Model 1), it can be concluded that falling behavior has a great impact on the anxiety symptoms of elderly patients with chronic multimorbidity, That is to say, the appearance of falling behavior tends to contribute to the emergence of anxiety symptoms in elderly chronic multimorbid patients. After the model was adjusted several times (from Model 2 to 4), i.e., after incorporating control variables related to socio-demographic characteristics (age, gender, place of residence, marital symptoms), family socio-economic characteristics (family economic symptoms, type of residence, pension insurance, health insurance), and healthy living conditions (smoking, alcohol consumption, daily exercise, hours of sleep, the number of chronic illnesses, and ADLs), it can be found that the relationship between falls and anxiety symptoms of elderly chronic multimorbid patients is significant. It can be found that falls were still significantly associated with the elderly chronic multimorbid patients༇own anxiety symptoms, but this coefficient has slightly decreased. In Table 4 , we replaced the dependent variable with self-rated health and found that the falling behavior was significantly associated with the self-rated health of elderly chronic multimorbid patients, that is, the more frequent the falls, the worse the elderly chronic multimorbid patients' assessment of their own health level. As the model was adjusted by incorporating groups of control variables several times, it was still possible to find a significant negative effect of falls on the self-rated health of elderly patients with chronic multimorbidity. Table 3 Results of the regression analysis between falls and anxiety symptoms. Model 1 Model 2 Model 3 Model 4 Anxiety symptoms Anxiety symptoms Anxiety symptoms Anxiety symptoms Falls 0.9701*** 0.9526*** 0.8108*** 0.7284*** (7.7200) (7.5914) (6.5975) (6.0163) Age -0.0230*** -0.0177*** -0.0226*** (-3.7755) (-2.9407) (-3.5231) Sex 0.7530*** 0.7110*** 0.5810*** (6.4690) (6.2377) (4.8406) Marital status 0.0307 -0.0003 0.0399 (0.2336) (-0.0020) (0.2910) Residence -0.1237 -0.2435** -0.2042* (-1.1253) (-2.2545) (-1.8952) Family economic status 1.0472*** 0.9478*** (12.6915) (11.5708) Co-residence 0.0831 0.0009 (0.6760) (0.0075) Pension insurance -0.1135 -0.1194 (-1.0313) (-1.0958) Medical insurance 0.1610 0.1858* (1.4894) (1.7486) ADL 0.5676*** (3.9275) Smoke -0.1220 (-0.7391) Drink 0.2544 (1.4810) Exercise 0.1532 (1.3056) Sleep -0.2256*** (-9.9815) Chronic diseases 0.1020*** (2.6981) _cons 0.6344*** 1.4900*** -1.7133*** -0.0594 (3.7760) (2.8995) (-2.8901) (-0.0818) N 3141 3141 3141 3141 adj. R 2 0.018 0.036 0.083 0.118 Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01 Table 4 Results of the regression analysis between falls and self-rated health. Model 5 Model 6 Model 7 Model 8 Self-rated health Self-rated health Self-rated health Self-rated health Falls -0.2688*** -0.2739*** -0.2250*** -0.2017*** (-7.2782) (-7.3710) (-6.2606) (-5.7579) Age 0.0025 0.0010 0.0056*** (1.4015) (0.5429) (3.0130) Sex -0.0556 -0.0408 0.0177 (-1.6120) (-1.2237) (0.5098) Marital status 0.0652* 0.0840** 0.0717* (1.6740) (2.0585) (1.8070) Residence -0.0316 0.0154 0.0048 (-0.9701) (0.4869) (0.1542) Family economic status -0.3674*** -0.3314*** (-15.2233) (-13.9846) Co-residence -0.0436 -0.0251 (-1.2126) (-0.7162) Pension insurance -0.0352 -0.0309 (-1.0941) (-0.9791) Medical insurance -0.0775** -0.0877*** (-2.4518) (-2.8538) ADL -0.2517*** (-6.0201) Smoke 0.1178** (2.4662) Drink -0.2926*** (-5.8865) Exercise -0.1815*** (-5.3496) Sleep 0.0446*** (6.8162) Chronic diseases -0.0656*** (-5.9955) _cons 3.5654*** 3.3982*** 4.6486*** 4.6175*** (72.2104) (22.3303) (26.8107) (21.9862) N 3141 3141 3141 3141 adj. R 2 0.016 0.019 0.090 0.143 Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01 3.3. Analysis of moderating effect Table 5 and Fig 2 show the moderating role of psychological resilience between falls and self-rated health and anxiety status in elderly chronic multimorbid patients. In particular, when anxiety was used as the dependent variable, we can find that psychological resilience had a significant interaction on the occurrence of falls and anxiety (β = - 0.147 [-0.214, -0.079], p < 0.01) , that is to say, the effect of falls and anxiety symptoms of elderly patients with chronic multimorbidity would be mitigated in participants with higher levels of psychological resilience. disease would be mitigated by the effects of anxiety symptoms. In contrast, when self-rated health was used as the dependent variable, there was no significant interaction of psychological resilience on falls and self-rated health (β = -0.003, p = 0.771), which means that psychological resilience failed to play a moderating role between falls and self-rated health among the elderly chronic multimorbid patients. Table 5 Results of moderating effects. Variables Coefficient SE t p 95% CI Lower Upper Anxiety symptoms(Y) Independent variable Falls(X) 3.362 0.654 5.14 < 0.01 2.078 4.645 Moderator variable Psychological resilience(W) -0.302 0.046 -6.45 < 0.01 -0.394 -0.210 Interaction X × W -0.147 0.034 -4.26 < 0.01 -0.214 -0.079 Constant 6.891 0.902 7.64 < 0.01 5.123 8.661 Self-reported health(Y) Independent variable Falls(X) -0.131 0.206 -0.64 0.524 -0.535 0.272 Moderator variable Psychological resilience(W) 0.112 0.015 7.60 < 0.01 0.083 0.141 Interaction X × W -0.003 0.011 -0.29 0.771 -0.024 0.018 Constant 1.329 0.284 4.68 < 0.01 0.773 1.886 3.4. Robustness test In this study, we replaced the test model to test robustness. Table 6 shows when the dependent variable is anxiety, the coefficients before and after the model replacement are 0.7284 and 0.3880 respectively, both significant at 1% test level, and when the dependent variable is self-rated health, the coefficients before and after the model replacement are − 0.201 and − 0.3931 respectively, also significant at 1% test level. The results obtained from both regressions were consistent. This shows that the correlation between the occurrence of falling behavior and the anxiety status and self-rated health of elderly chronic multimorbid patients is indeed statistically significant and passes the robustness test. Table 6 Results of robustness test. Variable Logit model OLS model Logit model OLS model Anxiety Anxiety Self-reported health Self-reported health Falls 0.3880 *** 0.7284 *** -0.3931 *** -0.2017 *** (3.5449) (6.0163) (-4.2155) (-5.7579) Age -0.0188 *** -0.0226 *** 0.0144 *** 0.0056 *** (-3.0404) (-3.5231) (3.0051) (3.0130) Sex 0.4979 *** 0.5810 *** 0.0135 0.0177 (4.0680) (4.8406) (0.1507) (0.5098) Marital status 0.0583 0.0399 0.2496 ** 0.0717 * (0.4410) (0.2910) (2.4507) (1.8070) Residence -0.0624 -0.2042 * 0.0771 0.0048 (-0.6013) (-1.8952) (0.9597) (0.1542) Family economic status 0.6415 *** (7.9896) 0.9478 *** (11.5708) -0.6942 *** (-10.5157) -0.3314 *** (-13.9846) Co-residence -0.0887 0.0009 -0.0966 -0.0251 (-0.7508) (0.0075) (-1.0652) (-0.7162) Pension insurance -0.1173 -0.1194 -0.0227 -0.0309 (-1.1205) (-1.0958) (-0.2791) (-0.9791) Medical insurance 0.1760 * 0.1858 * -0.1050 -0.0877 *** (1.7172) (1.7486) (-1.3272) (-2.8538) ADL 0.4290 *** 0.5676 *** -0.5605 *** -0.2517 *** (3.2006) (3.9275) (-4.9889) (-6.0201) Smoke -0.1495 -0.1220 0.2796 ** 0.1178 ** (-0.8873) (-0.7391) (2.2490) (2.4662) Drink 0.3677 * 0.2544 -0.5906 *** -0.2926 *** (1.9263) (1.4810) (-4.6954) (-5.8865) Exercise 0.2457 ** 0.1532 -0.3755 *** -0.1815 *** (2.0962) (1.3056) (-4.3541) (-5.3496) Sleep -0.1871 *** -0.2256 *** 0.0970 *** 0.0446 *** (-8.0275) (-9.9815) (5.7263) (6.8162) Chronic diseases 0.0342 0.1020 *** -0.1767 *** -0.0656 *** (0.9794) (2.6981) (-5.2880) (-5.9955) _cons -3.1090 *** -0.0594 1.7006 *** 4.6175 *** (-4.2010) (-0.0818) (3.1346) (21.9862) N 3141 3141 3141 3141 adj. R 2 0.118 0.143 Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01 3.5. Heterogeneity analysis On the basis of the above-mentioned research, we divided the gender and residence groups to discuss the heterogeneity of the regression relationship and the moderating effect. Table 7 shows the regression by gender group, and it was found that the effects of falls on self-rated health and anxiety in Chinese elderly chronic multimorbid patients were heterogeneous, with the female patient group being more likely to have a poorer assessment of their own health and more likely to develop anxiety symptoms in the future after falls. In addition, the moderating effect of psychological resilience on anxiety symptoms was also more pronounced in female than in male patients. Table 8 shows the results of the heterogeneity test for the different residence groups. The results show that when the dependent variable is anxiety symptoms, the effect of falls is more significant for urban elderly chronic multimorbid patients, whereas when the dependent variable is self-rated health, the effect of falls is more significant for rural elderly chronic multimorbid patients. In other words, patients living in cities were more likely to experience anxiety symptoms after a fall, whereas patients living in rural areas were more likely to experience poorer self-rated health after falls. In addition, among the moderating effects, there was a significant moderating effect of psychological resilience on fall behavior and anxiety among urban elderly chronic multimorbid patients. Table 7 Results of the regression analysis by gender. Variable Anxiety Self-reported health Female Male Female Male Falls 2.9091 *** (3.5554) 2.5293 ** (2.4109) -0.1761 *** (-4.1312) -0.1532 *** (-2.7646) Interaction (Psychological resilience) -0.1211 *** (-2.7821) -0.1154 ** (-2.1275) _cons 9.8612 *** (5.9961) 8.8579 *** (5.2575) 2.3304 *** (6.4735) 2.2537 *** (6.1545) N 1843 1298 1843 1298 adj.R 2 0.325 0.228 0.229 0.213 * p < 0.1, ** p < 0.05, *** p < 0.01 Table 8 Results of the regression analysis by residence. Variable Anxiety Self-reported health Urban Rural Urban Rural Falls 3.7537 *** (4.1603) 2.3010 ** (2.5436) -0.1227 *** (-2.6099) -0.2110 *** (-4.3843) Interaction (Psychological resilience) -0.1645 *** (-3.4738) -0.1015 ** (-2.1307) _cons 7.6740 *** (4.8388) 8.4548 *** (5.2480) 2.1970 *** (6.6705) 2.3998 *** (7.0202) N 1634 1507 1634 1507 adj.R 2 0.318 0.284 0.237 0.207 * p < 0.1, ** p < 0.05, *** p < 0.01 4. Discussion In this study, we investigated the relationship between falls and the self-rated health status and anxiety symptoms of elderly chronic multimorbid patients and the moderating role played by psychological resilience using a cross-sectional data from the CLHLS, and our findings showed that falls were significantly negatively correlated with the self-rated health status of elderly chronic multimorbid patients in China and were significantly positively associated with anxiety symptoms in Chinese elderly chronic multimorbidity patients. Among the moderating effects, there is a moderating role of psychological resilience between falls and anxiety symptoms. In addition, we further confirmed the heterogeneity of falls with both self-rated health and anxiety status across gender and residence groups. First, the present study found that falls were negatively associated with self-rated health in Chinese elderly chronic multimorbid patients. This result is consistent with past related studies. Previous studies have shown that falls interact with older adults' health levels, with more falls predicting poorer physical health, more negative emotions, and less physical activity in the near future for older adults living in the community[ 27 ]. In turn, more poor health also promotes the occurrence of falls in the elderly. Some medical studies have shown that the decline in muscle function of the lower extremities is a significant contributor to falls in older adults, and that this state is not an inevitable consequence of aging, but is related to an individual's underlying chronic health condition[ 28 – 31 ]. Therefore, elderly patients with chronic multimorbidity are more prone to falls, and the health problems that may be associated with falls, such as limb injuries (e.g. hip fracture), deterioration of physical and cognitive functioning, and poor trajectory of recovery from chronic diseases, These will directly affect patients' assessment of their own health and lead to a low self-rated of their health status. Another correlation result of this study showed that falls were positively correlated with anxiety symptoms in Chinese elderly with chronic multimorbidity. This finding is generally consistent with previous studies, indicating that falls contribute to anxiety symptoms and adversely affect the mental health of older adults[ 4 , 21 , 32 ]. It has been noted that anxiety symptoms are commonly associated with four psychological disorders triggered by falls, including fear of falling, fall-related self-efficacy, balance confidence, and outcome expectations[ 18 ]. For elderly patients with chronic multimorbidity, they are inherently prone to poor mental health due to suffering from multiple chronic conditions over time[ 33 ]. The occurrence of falls also puts patients at risk for recurrent falls and physical impairment, which in turn triggers a fear of repeated falls and a reduced sense of self-efficacy. Previous studies have shown that it becomes more difficult for the elderly to recover from fall-related injuries[ 34 ], so after experiencing a fall older patients are more likely to develop a fear of falling again, which can be manifested as a loss of confidence in the ability to perform everyday behaviors, limiting and avoiding participation in certain activities, which contributes to the development of anxiety symptoms, and the stronger the fear, the more severe the anxiety symptoms[ 35 ]. In addition, the impaired health, functional deterioration, and decreased independence caused by falls may lead to a gradual resistance to social participation, which not only reduces the exchange of daily information, but also does not facilitate the venting of negative emotions, and has a serious negative impact on all areas of the patient's life, thus eroding the patient's sense of self-efficacy[ 36 ], and triggering the emergence of anxiety symptoms. Furthermore, the present study revealed the existence of the moderating role of psychological resilience. It has been previously shown that psychological resilience as a moderator is effective in reducing anxiety and depression after falls in older adults, and improving psychological resilience may be an effective way to intervene and prevent fall-related anxiety and depression symptoms[ 18 ]. In addition to this, many studies have confirmed the assertion that the moderating effects of psychological resilience can modify the impact of risk factors on psycho-social functioning[ 37 ], and are reflected in different groups. For example, soldiers exposed to military operations[ 38 ], COVID-19 experiencers[ 39 ], and groups of children and adolescents[ 40 , 41 ]. Therefore, a high level of psychological resilience is also effective in regulating one's own state of mind and suppressing anxiety symptoms triggered by negative events such as falls for a group of Chinese elderly chronic multimorbid patients. But in the relationship between falls and self-rated health of elderly patients with chronic multimorbidity, our study showed that psychological resilience did not play a significant moderating role, and we speculate that positive mental status is not sufficient to influence patients' assessment of their physical health status. Self-rated health is a reliable and effective indicator of an individual's own health[ 42 ], and has been regarded as an important reference factor for determining morbidity, hospitalization and mortality[ 43 ], which reinforces the need for patients to ensure objectivity and truthfulness in assessing their own health status. Therefore, psychological resilience fails to play a moderating role between falls and self-rated health as it is difficult to influence patients' assessment of their objective conditions such as disease, functional status, and other health problems through changes in mindset. Finally, this study found that the effects of falls on self-rated health and anxiety symptoms of Chinese elderly chronic multimorbid patients varied by gender and place of residence. First, from the gender perspective, the female patient group was more likely to have poorer self-rated health and more severe anxiety symptoms in the future after a fall. The moderating effect of psychological resilience was similarly more pronounced in female patient group compared to males. A study showed that the prevalence of post-fall fear was higher in women and increased with age[ 44 ]. This suggests that the significant presence of post-fall fear in female patients means that they are more likely to develop anxiety symptoms after a fall. It has also been shown that women are generally more emotional than men, and are more susceptible to external influences on a mental level[ 45 ]. Therefore, the female chronic multimorbid group may experience greater fluctuations in their psychological state and level of cognition about themselves compared to males after experiencing fall behavior, resulting in poorer self-rated health and more severe anxiety symptoms, and psychological resilience as a positive mental state, may also play a stronger moderating role in the female patient group. From the perspective of place of residence, the results of the study showed that elderly chronic multimorbid patients living in urban areas were more likely to experience anxiety after a fall and that psychological resilience had a more significant moderating effect, whereas patients living in rural areas were more likely to experience poorer self-rated health after a fall. A possible explanation for this is that urban and rural patients experience different health shocks after falls. For older urban patients, the relatively higher level of education leads to higher expectations of educational rewards, and thus the fluctuations in psychological state may be greater in the event of a setback similar to a fall. Moreover, life in towns and cities is richer than in rural areas, which leads to greater life changes after a fall, which can have a more severe negative impact on mental health. In addition, in the relationship between falls and self-rated health, many studies have shown that Chinese rural residents generally have worse self-rated health outcomes than their urban counterparts due to unequal health opportunities and uneven utilization of healthcare services [ 46 ]. On the basis of this assertion, we can further confirm that rural elderly patients with chronic diseases are more likely to have a poorer assessment of their own health after experiencing an adverse event of a fall. The strengths of this study are the selection of a sample from the National Population Survey which provided sufficient data to explore the relationship between falls and self-rated health and anxiety symptoms in older people with chronic multimorbidity, and the focus on older people with chronic multimorbidity, which provided insight into the impact of falls on their physical and mental health, and the role of psychological resilience in this. Limitations of this study are as follows: First, the study was analyzed based on a cross-sectional data set. Therefore, our predicted results cannot be explained in depth in terms of causality and can only be understood statistically, and further research on falls and Chinese elderly chronic multimorbid patients' self-rated health and anxiety symptoms needs to be explored with longitudinal data. Second, the present study used a self-rated approach for the identification of falls, in which participants were asked to recall whether a fall had occurred in the past year; this approach may be subject to recall bias, and further research should also take a more accurate approach to the recording of falls. 5. Conclusion Our findings suggest that there is a significant correlation between falls and self-rated health and anxiety symptoms in Chinese elderly chronic multimorbid patients, and a significant moderating effect of psychological resilience on inhibiting the development of anxiety symptoms. In view of this, we should pay timely attention to the changes in physical and mental health of elderly patients with chronic multimorbidity after falls, and develop a series of interventions to promote patients' physical recovery after a fall and alleviate anxiety. At the same time, future psychiatric interventions for anxiety in elderly patients with chronic multimorbidity can also start from improving their psychological resilience, so that they can cope with the fall in a more positive way and minimize the negative impact of the fall on themselves. Declarations Authorship contributions Shaoliang Tang: research design, conceptualization, revision of the manuscript, language and supervision, funding acquisition. Jingyu Xu: data analysis, writing and revision of the manuscript. Xiaoyan Mao and Huilin Jiao: data collation and inspection, revision. Yuxin Qian: inspection, revision. Gaoling Wang: project administration, resources, and supervision. All authors contributed to the article and approved the final manuscript. Funding The research was supported by the National Natural Science Foundation of China (grant number 72074125). Availability of data and materials The data that support the findings of this study are available in https://opendata. pku.edu.cn/dataverse/CHADS. Ethics approval and consent to participate The Peking University Institutional Review Board (IRB00001052-13074) has approved the study protocol of the current study. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author detail 1 School of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China. + Shaoliang Tang and Jingyu Xu contributed equally to the work and share the first authorship. References WHO.[Internet]. Falls [cited 2021 April 26]. Available from: https://www.who.int/news-room/fact-sheets/detail/falls. Kruschke C. Evidence-Based Practice Guideline Fall Prevention for Older Adults. Journal of Gerontological Nursing. 2017;43(11):15-21. Tinetti ME, Speechley M, Ginter SF. RISK-FACTORS FOR FALLS AMONG ELDERLY PERSONS LIVING IN THE COMMUNITY. New England Journal of Medicine. 1988;319(26):1701-7. Dellinger A. Older Adult Falls: Effective Approaches to Prevention. Current trauma reports. 2017;3(2):118-23. Moreland B, Kakara R, Henry A. Trends in Nonfatal Falls and Fall-Related Injuries Among Adults Aged ≥65 Years - United States, 2012-2018. 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Physical Medicine and Rehabilitation Clinics of North America. 2017;28(4):727-+. Walker JE, Howland J. FALLS AND FEAR OF FALLING AMONG ELDERLY PERSONS LIVING IN THE COMMUNITY - OCCUPATIONAL-THERAPY INTERVENTIONS. American Journal of Occupational Therapy. 1991;45(2):119-22. Adhaye AM, Jolhe DA. GAIT MEASUREMENT METHODS: SYSTEMATIC REVIEW AND COMPARATIVE STUDIES. Journal of Mechanics in Medicine and Biology. 2023. Yang K, Yang S, Chen Y, Cao G, Xu R, Jia X, et al. Multimorbidity Patterns and Associations with Gait, Balance and Lower Extremity Muscle Function in the Elderly: A Cross-Sectional Study in Northwest China. International Journal of General Medicine. 2023;16:3179-92. Hallford DJ, Nicholson G, Sanders K, McCabe MP. The Association Between Anxiety and Falls: A Meta-Analysis. Journals of Gerontology Series B-Psychological Sciences and Social Sciences. 2017;72(5):729-41. Gould CE, O'Hara R, Goldstein MK, Beaudreau SA. Multimorbidity is associated with anxiety in older adults in the Health and Retirement Study. International Journal of Geriatric Psychiatry. 2016;31(10):1105-15. Kempen G, Ormel J, Scaf-Klomp W, van Sonderen E, Ranchor AV, Sanderman R. The role of perceived control in the process of older peoples' recovery of physical functions after fall-related injuries: A prospective study. Journals of Gerontology Series B-Psychological Sciences and Social Sciences. 2003;58(1):P35-P41. van Haastregt JCM, Zijlstra GAR, van Rossum E, van Eijk JTM, Kempen GIJM. Feelings of anxiety and symptoms of depression in community-living older persons who avoid activity for fear of falling. American Journal of Geriatric Psychiatry. 2008;16(3):186-93. Hull SL, Kneebone II, Farquharson L. Anxiety, Depression, and Fall-Related Psychological Concerns in Community-Dwelling Older People. American Journal of Geriatric Psychiatry. 2013;21(12):1287-91. Masten AS, Reed MGJ. Resilience in development. Snyder CR, Lopez SJE, editors. Handbook of Positive Psychology: Oxford University Press; 2002. p. 74-88. Pietrzak RH, Johnson DC, Goldstein MB, Malley JC, Southwick SM. PSYCHOLOGICAL RESILIENCE AND POSTDEPLOYMENT SOCIAL SUPPORT PROTECT AGAINST TRAUMATIC STRESS AND DEPRESSIVE SYMPTOMS IN SOLDIERS RETURNING FROM OPERATIONS ENDURING FREEDOM AND IRAQI FREEDOM. Depression and Anxiety. 2009;26(8):745-51. Havnen A, Anyan F, Hjemdal O, Solem S, Gurigard Riksfjord M, Hagen K. Resilience Moderates Negative Outcome from Stress during the COVID-19 Pandemic: A Moderated-Mediation Approach. International Journal of Environmental Research and Public Health. 2020;17(18). Ding H, Han J, Zhang M, Wang K, Gong J, Yang S. Moderating and mediating effects of resilience between childhood trauma and depressive symptoms in Chinese children. Journal of Affective Disorders. 2017;211:130-5. Hjemdal O, Vogel PA, Solem S, Hagen K, Stiles TC. The Relationship between Resilience and Levels of Anxiety, Depression, and Obsessive-Compulsive Symptoms in Adolescents. Clinical Psychology & Psychotherapy. 2011;18(4):314-21. Mikolajczyk RT, Brzoska P, Maier C, Ottova V, Meier S, Dudziak U, et al. Factors associated with self-rated health status in university students: a cross-sectional study in three European countries. Bmc Public Health. 2008;8. Hossain S, Anjum A, Hasan MT, Uddin ME, Hossain MS, Sikder MT. Self-perception of physical health conditions and its association with depression and anxiety among Bangladeshi university students. Journal of Affective Disorders. 2020;263:282-8. Scheffer AC, Schuurmans MJ, van Dijk N, van Der Hooft T, De Rooij SE. Fear of falling: measurement strategy, prevalence, risk factors and consequences among older persons. Age and Ageing. 2008;37(1):19-24. Fuhrer R, Stansfeld SA. How gender affects patterns of social relations and their impact on health: a comparison of one or multiple sources of support from "close persons". Social Science & Medicine. 2002;54(5):811-25. Liu Y, Guo H, Shi X. Measurement and Trend Analysis of Health Opportunity Inequality among Urban and Rural Residents in China. Population and Development. 2023;29( 06 ):72-87. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 05 Sep, 2024 Read the published version in BMC Geriatrics → Version 1 posted Editorial decision: Revision requested 08 Jul, 2024 Reviews received at journal 07 Jul, 2024 Reviewers agreed at journal 03 Jul, 2024 Reviewers agreed at journal 02 Jul, 2024 Reviews received at journal 30 Jun, 2024 Reviewers agreed at journal 24 Jun, 2024 Reviewers invited by journal 23 Jun, 2024 Editor invited by journal 20 Jun, 2024 Editor assigned by journal 18 Jun, 2024 Submission checks completed at journal 18 Jun, 2024 First submitted to journal 12 Jun, 2024 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. 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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-4571446","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":324297321,"identity":"1daf8867-3f3c-4601-b47d-8e5d88142405","order_by":0,"name":"Shaoliang Tang","email":"","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shaoliang","middleName":"","lastName":"Tang","suffix":""},{"id":324297323,"identity":"f3141068-06fb-4f95-8ca3-9f5202609357","order_by":1,"name":"Jingyu Xu","email":"","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jingyu","middleName":"","lastName":"Xu","suffix":""},{"id":324297324,"identity":"b32a7930-f050-4efe-9425-693fa4893492","order_by":2,"name":"Xiaoyan Mao","email":"","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyan","middleName":"","lastName":"Mao","suffix":""},{"id":324297325,"identity":"f3f81af8-09a9-4967-ad75-0e5ea85db276","order_by":3,"name":"Huilin Jiao","email":"","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Huilin","middleName":"","lastName":"Jiao","suffix":""},{"id":324297326,"identity":"4d30cc6e-1202-4932-b764-c3a49f6671e8","order_by":4,"name":"Yuxin Qian","email":"","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuxin","middleName":"","lastName":"Qian","suffix":""},{"id":324297327,"identity":"24233e9a-0d76-4e52-b504-d20bce206b91","order_by":5,"name":"Gaoling Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACfvbGhgMf/9kwMDaA+cyEtUj2HD74cAZbGglaDG6kJRvzsB2G8YnQwnDmjJk0D8/5POYZyU83MFRYJzawnz2AVwdje4+Z5ByJ28WMM9LMbjCcSU9s4MlLwKuFmeeMmcQbg9uJjTNy2G4wth1ObJDgMcCrhU0ix0yCJ+EcVMs/IrTwSKQlG/IcOADV0kCEFgkeYCDPbEhObOx5ZnYj4Vi6cRtPDn4t9sdBUdlgl7ixPfnZjQ811rL97Gfwa4EDwwYgkQDyHXHqgUCeaJWjYBSMglEw4gAA649MdrYkz8QAAAAASUVORK5CYII=","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Gaoling","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-06-12 15:52:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4571446/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4571446/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-024-05338-x","type":"published","date":"2024-09-05T15:58:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60598904,"identity":"9a09f9cf-19ef-4875-941d-d8962e78376b","added_by":"auto","created_at":"2024-07-18 15:56:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26879,"visible":true,"origin":"","legend":"\u003cp\u003eSample selection process\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4571446/v1/f93d3eeede02ae8d710d03b0.png"},{"id":60598905,"identity":"4e4a9313-2db9-4549-be9f-bd04c1c25e0f","added_by":"auto","created_at":"2024-07-18 15:56:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24660,"visible":true,"origin":"","legend":"\u003cp\u003eThe moderating role of psychological resilience in falls and anxiety symptoms.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4571446/v1/d84dd6c065f2268c71d76e93.png"},{"id":64186225,"identity":"4be35cd4-5da2-40ef-91c2-3e4f20ec944f","added_by":"auto","created_at":"2024-09-09 16:25:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1224727,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4571446/v1/f2e3fb36-e825-43a3-a809-7de3e4e1636f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of falls on self-rated health and anxiety in Chinese elderly chronic multimorbid patients : moderating role of psychological resilience","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eFalls are defined as an event in which a person unintentionally falls to the ground, floor, or other lower level causing them to lose consciousness[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Falls have now become a very high incidence of public health problems globally [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to the survey, falls has become one of the public health problems that seriously threaten the life and health safety of the elderly worldwide, approximately 68,400 fatal falls happen each year[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Also, as a common geriatric syndrome, it is one of the leading causes of injury and death in the elderly [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A study showed that 27.5% of people over 65 years old had fallen at least once a year, and 10.2% of people over 65 years old rated at least one fall-related injury [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In China, Falls are also common among the elderly, with many fall risk factors increasing with age, including functional decline, polypharmacy, and chronic diseases in the elderly [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The presence of fall behavior not only predisposes older adults to physical health impairment issues (e.g. hip fracture) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], but can also be detrimental to their mental health symptoms. Limb damage, mobility problems and reduced independence due to falls can strongly affect some emotionally vulnerable older adults, making them more likely to develop symptoms of anxiety and fear of falling again [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eChronic multimorbidity is usually regarded as the co-presence of two or more chronic diseases in a single individual [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A recent study showed that the overall prevalence of chronic multimorbidity is currently as high as 37.2% globally, with more than half of all adults over the age of 60 years suffering from two or more chronic diseases [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The interplay of multiple diseases in patients with chronic multimorbidity can easily lead to further declines in physical and cognitive function [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], making them susceptible to fall behavior. In turn, the consequences of falling behavior are even worse for patients with chronic multimorbidity, thus forming a vicious circle. In previous studies, scholars have focused more on the effects of falls on the physical and mental health of the elderly[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and few studies have focused on the consequences of falls on patients with chronic multimorbidity. Therefore, this study will take the chronic multimorbid patients group as the research object to further explore the series of impacts on their physical and mental health caused by the emergence of falls.\u003c/p\u003e \u003cp\u003eSelf-rated health is a very effective clinical method for measuring overall health, which can reflect the continuity of a person's perceived health [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and can enable patients to visually represent the changes in their own health before and after falls, so it is of some research significance to further study the relationship between falls and their physical health symptoms of patients with chronic multimorbidity through self-rated health. In addition, anxiety and depression are common psychological disorders in the elderly population and are two important factors affecting mental health. It has been suggested that falls are a potential contributor to anxiety or depression in older adults, but they have not yet been adequately studied [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, in reality, more prior studies have discussed the association between falls and depression, and most scholars believe that there is a significant interaction between falls and depressive symptoms[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and the physiological damage caused by falls will increase the risk of depression, which is more likely to lead to falling again. Some scholars have also delved into mechanisms of action between them, including the cognitive and motor delays, and functional limitations[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In contrast, very little research has adequately discussed the impact of fall events on anxiety, which is one of the most common mental health disorders with a global prevalence of 2.4% \u0026minus;\u0026thinsp;29.8% per year[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and as far as we know, Only one study alone has explored separate changes in anxiety symptoms due to fall behavior[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and its findings suggest that the elderly who have experienced falls are more likely to suffer high levels of anxiety due to physical or mental injury. It is thus clear that the association between falls and anxiety in chronic multimorbid patients is likewise of some research value, however, it has not been widely concerned by scholars. Therefore, to fill the aforementioned gaps, this study focused on a group of elderly chronic multimorbidity patients in China, aiming to delve into the impact of the emergence of fall behavior on their self-rated health and anxiety status., with a focus on post-fall interventions, which would be beneficial for the development of post-fall recovery measures for elderly chronic multimorbid patients.\u003c/p\u003e \u003cp\u003eAlso, in this case, it was further hypothesized that patients in different mental states may be affected to different degrees after falls. In positive psychology, there is a very important concept called psychological resilience, which refers to the process by which a set of abilities and characteristics interact dynamically to enable an individual to recover quickly and cope successfully in times of great stress and danger[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It has been shown that the level of psychological resilience has an impact on anxiety and depression in the elderly, which in turn affects their outlook on life[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. People in the condition of their old age are always full of various challenges and stressors[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], such as declining health, and the mindset and the way they cope with the challenges become particularly important at this time. Whether psychological resilience plays a positive role in the adversity of elderly patients with chronic multimorbidity who are suffering from multiple illnesses and experiencing falls remains to be further examined. Therefore, the ability of psychological resilience to moderate the relationship between falls and self-rated health and anxiety status in elderly chronic multimorbid patients is another question to be considered in our study.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Participants\u003c/h2\u003e \u003cp\u003eThe data for this paper were obtained from the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS).The CLHLS project randomly select nearly half of counties and cities in 22 provinces in China, and to comprehensively collect detailed information on the individual behaviors, families, and social environments of seniors aged 60 and above. This data has the advantages of large sample size, long follow-up period and strong representativeness, with good reliability and validity. Since information on falls, anxiety, and psychological resilience levels in older adults was rated only in 2018, we conducted a cross-sectional study. In this study, 15,874 samples of raw data were initially obtained, and the criteria for inclusion of study subjects were (a) age\u0026thinsp;\u0026ge;\u0026thinsp;60 years (b) two or more chronic diseases (c) complete answers to the relevant items of the \"Anxiety Scale\" and the assessment of \"psychological resilience\" in the CLHLS dataset (d) no other key variables were missing or abnormal. Finally, A total of 3,141 individuals were included in the study.The sample processing is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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. Anxiety\u003c/h2\u003e \u003cp\u003eIn this study, we used the Generalized Anxiety Scale (GAD-7) in the CLHLS to assess anxiety symptoms in older patients with chronic multimorbidity. We assessed the frequency and severity of anxiety symptoms using participants' descriptions of their emotional feelings. The scale consists of seven items, each with four options. \"The scores ranged from 0 to 21. Anxiety scores\u0026thinsp;\u0026lt;\u0026thinsp;5 were classified as no anxiety symptoms, and \u0026ge;\u0026thinsp;5 were classified as having anxiety symptoms. The higher the score, the worse the anxiety. The Cronbach's alpha coefficient of the GAD-7 was 0.91[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Self-rated health\u003c/h2\u003e \u003cp\u003eSelf-rated health, as a subjective health measure, can better reflect people's health. In order to better measure another dependent variable in this study, we selected the item \"How do you feel about your own health now?\" from the CLHLS questionnaire. This item measures the self-rated health symptoms of elderly chronic multimorbid patients. According to the question answer setting, we used SRH as a continuous variable with a range of 1\u0026ndash;5, with higher scores reflecting better health symptoms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Falls\u003c/h2\u003e \u003cp\u003eFalls were selected as the independent variable of the study, and for the measurement of fall behavior a question like this one from CLHLS was used, \"Have you fallen in the past year?\" If the respondent answered \"yes\", it was considered that a fall had occurred.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Psychological resilience\u003c/h2\u003e \u003cp\u003eAccording to existing research[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], the psychological resilience score needed for this study was specifically measured by five items in the CLHLS: \"Are you able to think through whatever comes your way?\", \" Are you in charge of your own affairs?\" \"Do you feel that you are getting worse as you get older, and that you have trouble doing things?\" \"Do you feel nervous and scared?\" and \"Do you feel lonely?\" All of the above items were on a five-point Likert scale, with items one and two being reverse questions, which were recoded in this study to summarize the scores, which ranged from 5 to 25. A high or low score predicts a high or low level of psychological resilience. In terms of internal consistency confidence, the acceptable value for the psychological resilience scale was 0.625.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5. Control variables\u003c/h2\u003e \u003cp\u003eThis study also referred to previous studies and a range of control variables were selected that were likely to cause anxiety symptoms and changes in self-rated health[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], which contain a total of three aspects: socio-demographic characteristics, family socio-economic characteristics, and healthy living conditions. First, socio-demographic characteristics include age, gender, place of residence, and marital symptoms. Among them, for marital symptoms, we reclassified them into married and divorced/widowed/unmarried/never married categories based on the answers to the questionnaire. Second, considering that family socio-economic characteristics, type of residence, and insurance symptoms may have an impact on the physical and psychological conditions of chronic multimorbid patients after a fall, in this paper, we selected economic status, type of residence, and whether or not they have old-age pension and medical insurance as the socio-economic characteristics of the family, of which the variable of economic status was measured using the question \"Which of the following categories does your life belong to when compared in the local area? \" is used to measure. Third, healthy living conditions variables included whether or not they smoked or drank alcohol, daily exercise, hours of sleep, number of chronic diseases and ADL, in which ADL was calculated and assigned a total score based on the following variables: bathing, dressing, toilet, indoor activities, self-control, and eating (=\u0026thinsp;6 is unimpaired and assigned a value of \"0\"). \u0026lt;6 is impaired assigned a value of \"1\"). Detailed settings for each variable can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\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 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoding of variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoding\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;5\u0026thinsp;=\u0026thinsp;0, \u0026ge;\u0026thinsp;5\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevels of anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0∼21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery poor\u0026thinsp;=\u0026thinsp;1, Poor\u0026thinsp;=\u0026thinsp;2, Fair\u0026thinsp;=\u0026thinsp;3, Good\u0026thinsp;=\u0026thinsp;4, Very good\u0026thinsp;=\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u0026thinsp;=\u0026thinsp;1,Yes\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychological resilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5∼25\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\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u0026thinsp;=\u0026thinsp;1, Female\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u0026thinsp;=\u0026thinsp;1, Divorced/Widowed/Never married\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u0026thinsp;=\u0026thinsp;1, Rural\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily economic symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery rich\u0026thinsp;=\u0026thinsp;1, Rich\u0026thinsp;=\u0026thinsp;2, So so =\u0026thinsp;3, Poor\u0026thinsp;=\u0026thinsp;4, Very poor\u0026thinsp;=\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith household member(s)\u0026thinsp;=\u0026thinsp;1,Alone\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003cp\u003eIn an institution\u0026thinsp;=\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u0026thinsp;=\u0026thinsp;1,No\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u0026thinsp;=\u0026thinsp;1,No\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo impaired\u0026thinsp;=\u0026thinsp;0, Impaired\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u0026thinsp;=\u0026thinsp;1,No\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u0026thinsp;=\u0026thinsp;1,No\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u0026thinsp;=\u0026thinsp;1,No\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical analysis\u003c/h2\u003e \u003cp\u003eFirst, we performed descriptive analysis by calculating the frequency and percentage of categorical variables, as well as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation of continuous variables. Second, we used a linear regression model to test whether there was a correlation between falls and self-rated health and anxiety symptoms in elderly chronic multimorbid patients. In addition, we incorporated a moderated effects model that utilized the multiplication of the independent and moderating variables to take shape an interaction item, and added the independent variable X, dependent variable Y, moderating variable W, and interaction item XW to the model in order to test the presence of moderating effects on psychological resilience. Finally, since both self-rated health and anxiety symptoms scores are continuous variables, we used the method of replacing the model to carry out the robustness test to verify the reliability of the regression results. We also analyzed the heterogeneity by different genders and places of residence according to group regression. The entire study was processed and analyzed using STATA 17.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Descriptive statistical analysis\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, there are 3,141 elderly patients with chronic multimorbidity in this study. Among them, the proportion of males is 41.32% ; 14.25%, 32.31%, 29.67%, and 23.77% of the total population were aged 60\u0026ndash;70, 71\u0026ndash;80, 81\u0026ndash;90, and 90 years or older, respectively; 45.69% of the population were married. 52.02% of the population were residing in urban areas compared to rural areas; 79.91% were living with family members. 18.75% were in wealthy families; 39.99% and 59.10% had pension insurance and medical insurance, respectively; daily living activities were not impaired. 79.91% live with family members. 18.75% are rich. 39.99% have pension insurance and 59.10% have medical insurance. 78.51% are not impaired in activities of daily living. 85.90% and 87.97% do not have the habit of drinking and smoking. 33.21% exercise consistently and the average sleep time is 7.17 h. In addition, nearly half of the chronic multimorbid patients in this study had three or more illnesses 48.39%. 26.27% of the sample population had fallen in the past year. 83.89% had no anxiety symptoms, and 78.64% considered their overall health symptoms to be good.\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistical analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN / Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e71\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e81\u0026ndash;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e91 above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital symptoms\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/Widowed/Never married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily economic symptoms\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003every rich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eso so\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003every poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCo-residence\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewith household member(s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ealone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ein an institution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePension insurance\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical insurance\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADL\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo impaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoke\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrink\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExercise\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic diseases\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFalls\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnxiety symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-rated health\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003every good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eso so\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003every bad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Regression model results\u003c/h2\u003e \u003cp\u003eFirst, we used linear regression model to confirm the correlation between falls and self-rated health and anxiety symptoms of elderly chronic disease multimorbid patients, and the regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Among them, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e uses anxiety symptoms as the dependent variable, and in the unadjusted model (Model 1), it can be concluded that falling behavior has a great impact on the anxiety symptoms of elderly patients with chronic multimorbidity, That is to say, the appearance of falling behavior tends to contribute to the emergence of anxiety symptoms in elderly chronic multimorbid patients. After the model was adjusted several times (from Model 2 to 4), i.e., after incorporating control variables related to socio-demographic characteristics (age, gender, place of residence, marital symptoms), family socio-economic characteristics (family economic symptoms, type of residence, pension insurance, health insurance), and healthy living conditions (smoking, alcohol consumption, daily exercise, hours of sleep, the number of chronic illnesses, and ADLs), it can be found that the relationship between falls and anxiety symptoms of elderly chronic multimorbid patients is significant. It can be found that falls were still significantly associated with the elderly chronic multimorbid patients༇own anxiety symptoms, but this coefficient has slightly decreased.\u003c/p\u003e \u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, we replaced the dependent variable with self-rated health and found that the falling behavior was significantly associated with the self-rated health of elderly chronic multimorbid patients, that is, the more frequent the falls, the worse the elderly chronic multimorbid patients' assessment of their own health level. As the model was adjusted by incorporating groups of control variables several times, it was still possible to find a significant negative effect of falls on the self-rated health of elderly patients with chronic multimorbidity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the regression analysis between falls and anxiety symptoms.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 4\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\u003eAnxiety symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnxiety symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnxiety symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnxiety symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9701***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9526***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8108***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7284***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(7.7200)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7.5914)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(6.5975)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(6.0163)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0230***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0177***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0226***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-3.7755)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-2.9407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-3.5231)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7530***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7110***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5810***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6.4690)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(6.2377)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4.8406)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.2336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-0.0020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.2910)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.1237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.2435**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.2042*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-1.1253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-2.2545)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-1.8952)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily economic status\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 \u003cp\u003e1.0472***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9478***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(12.6915)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(11.5708)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-residence\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 \u003cp\u003e0.0831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(0.6760)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0075)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension insurance\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 \u003cp\u003e-0.1135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.1194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-1.0313)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-1.0958)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance\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 \u003cp\u003e0.1610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1858*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(1.4894)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.7486)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADL\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 \u003cp\u003e0.5676***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(3.9275)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\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 \u003cp\u003e-0.1220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-0.7391)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrink\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 \u003cp\u003e0.2544\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(1.4810)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise\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 \u003cp\u003e0.1532\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(1.3056)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep\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 \u003cp\u003e-0.2256***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-9.9815)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic diseases\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 \u003cp\u003e0.1020***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(2.6981)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6344***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4900***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.7133***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0594\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(3.7760)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.8995)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-2.8901)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.0818)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadj. \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStandard errors in parentheses.\u003c/p\u003e \u003cp\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.1, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the regression analysis between falls and self-rated health.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 8\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\u003eSelf-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSelf-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSelf-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSelf-rated health\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.2688***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.2739***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.2250***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.2017***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-7.2782)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-7.3710)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-6.2606)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-5.7579)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0056***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.4015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.5429)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.0130)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-1.6120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-1.2237)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.5098)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0652*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0840**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0717*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.6740)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.0585)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8070)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-0.9701)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.4869)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.1542)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily economic status\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 \u003cp\u003e-0.3674***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.3314***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-15.2233)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-13.9846)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-residence\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 \u003cp\u003e-0.0436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-1.2126)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.7162)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension insurance\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 \u003cp\u003e-0.0352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-1.0941)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.9791)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance\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 \u003cp\u003e-0.0775**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0877***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-2.4518)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-2.8538)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADL\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 \u003cp\u003e-0.2517***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-6.0201)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\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 \u003cp\u003e0.1178**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(2.4662)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrink\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 \u003cp\u003e-0.2926***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-5.8865)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise\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 \u003cp\u003e-0.1815***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-5.3496)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep\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 \u003cp\u003e0.0446***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(6.8162)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic diseases\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 \u003cp\u003e-0.0656***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003e(-5.9955)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5654***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3982***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6486***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6175***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(72.2104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(22.3303)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(26.8107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(21.9862)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadj. \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStandard errors in parentheses.\u003c/p\u003e \u003cp\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.1, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Analysis of moderating effect\u003c/h2\u003e\u003cp\u003eTable 5 and Fig 2 show the moderating role of psychological resilience between falls and self-rated health and anxiety status in elderly chronic multimorbid patients. In particular, when anxiety was used as the dependent variable, we can find that psychological resilience had a significant interaction on the occurrence of falls and anxiety (\u0026beta; = - 0.147 [-0.214, -0.079], p \u0026lt; 0.01) , that is to say, the effect of falls and anxiety symptoms of elderly patients with chronic multimorbidity would be mitigated in participants with higher levels of psychological resilience. disease would be mitigated by the effects of anxiety symptoms. In contrast, when self-rated health was used as the dependent variable, there was no significant interaction of psychological resilience on falls and self-rated health (\u0026beta; = -0.003, p = 0.771), which means that psychological resilience failed to play a moderating role between falls and self-rated health among the elderly chronic multimorbid patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of moderating effects.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% CI\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\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 \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety symptoms(Y)\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFalls(X)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerator variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePsychological resilience(W)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-6.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX \u0026times; W\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.661\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-reported health(Y)\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFalls(X)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerator variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePsychological resilience(W)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX \u0026times; W\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.886\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Robustness test\u003c/h2\u003e \u003cp\u003eIn this study, we replaced the test model to test robustness. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows when the dependent variable is anxiety, the coefficients before and after the model replacement are 0.7284 and 0.3880 respectively, both significant at 1% test level, and when the dependent variable is self-rated health, the coefficients before and after the model replacement are \u0026minus;\u0026thinsp;0.201 and \u0026minus;\u0026thinsp;0.3931 respectively, also significant at 1% test level. The results obtained from both regressions were consistent. This shows that the correlation between the occurrence of falling behavior and the anxiety status and self-rated health of elderly chronic multimorbid patients is indeed statistically significant and passes the robustness test.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of robustness test.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLogit model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOLS model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogit model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOLS model\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\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSelf-reported health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSelf-reported health\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3880\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7284\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.3931\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.2017\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(3.5449)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6.0163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-4.2155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-5.7579)\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\u003e-0.0188\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0226\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0144\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0056\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-3.0404)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-3.5231)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.0051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.0130)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4979\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5810\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.0680)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.8406)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.1507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.5098)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2496\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0717\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.4410)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.2910)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.4507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8070)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.2042\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-0.6013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-1.8952)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.9597)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.1542)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily economic status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6415\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(7.9896)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9478\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(11.5708)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.6942\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-10.5157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.3314\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-13.9846)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-0.7508)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-1.0652)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.7162)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.1194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-1.1205)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-1.0958)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-0.2791)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.9791)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1760\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1858\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.1050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0877\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.7172)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.7486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-1.3272)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-2.8538)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4290\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5676\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.5605\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.2517\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(3.2006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.9275)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-4.9889)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-6.0201)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.1220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2796\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1178\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-0.8873)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-0.7391)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.2490)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.4662)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3677\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.5906\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.2926\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.9263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.4810)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-4.6954)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-5.8865)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2457\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.3755\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.1815\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2.0962)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.3056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-4.3541)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-5.3496)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1871\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.2256\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0970\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0446\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-8.0275)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-9.9815)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(5.7263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(6.8162)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1020\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.1767\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0656\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.9794)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.6981)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-5.2880)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-5.9955)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.1090\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7006\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6175\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-4.2010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-0.0818)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.1346)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(21.9862)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadj. \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStandard errors in parentheses.\u003c/p\u003e \u003cp\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.1, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Heterogeneity analysis\u003c/h2\u003e \u003cp\u003eOn the basis of the above-mentioned research, we divided the gender and residence groups to discuss the heterogeneity of the regression relationship and the moderating effect. Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows the regression by gender group, and it was found that the effects of falls on self-rated health and anxiety in Chinese elderly chronic multimorbid patients were heterogeneous, with the female patient group being more likely to have a poorer assessment of their own health and more likely to develop anxiety symptoms in the future after falls. In addition, the moderating effect of psychological resilience on anxiety symptoms was also more pronounced in female than in male patients.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the results of the heterogeneity test for the different residence groups. The results show that when the dependent variable is anxiety symptoms, the effect of falls is more significant for urban elderly chronic multimorbid patients, whereas when the dependent variable is self-rated health, the effect of falls is more significant for rural elderly chronic multimorbid patients. In other words, patients living in cities were more likely to experience anxiety symptoms after a fall, whereas patients living in rural areas were more likely to experience poorer self-rated health after falls. In addition, among the moderating effects, there was a significant moderating effect of psychological resilience on fall behavior and anxiety among urban elderly chronic multimorbid patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the regression analysis by gender.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSelf-reported health\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\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9091\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.5554)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5293\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.4109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.1761\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-4.1312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.1532\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.7646)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction \u003c/p\u003e \u003cp\u003e(Psychological resilience)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1211\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.7821)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.1154\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.1275)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.8612\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.9961)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.8579\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.2575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3304\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(6.4735)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2537\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(6.1545)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadj.R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.1, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the regression analysis by residence.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSelf-reported health\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\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7537\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(4.1603)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3010\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.5436)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.1227\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.6099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.2110\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-4.3843)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction \u003c/p\u003e \u003cp\u003e(Psychological resilience)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1645\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-3.4738)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.1015\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.1307)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd 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p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\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":"\u003cp\u003eIn this study, we investigated the relationship between falls and the self-rated health status and anxiety symptoms of elderly chronic multimorbid patients and the moderating role played by psychological resilience using a cross-sectional data from the CLHLS, and our findings showed that falls were significantly negatively correlated with the self-rated health status of elderly chronic multimorbid patients in China and were significantly positively associated with anxiety symptoms in Chinese elderly chronic multimorbidity patients. Among the moderating effects, there is a moderating role of psychological resilience between falls and anxiety symptoms. In addition, we further confirmed the heterogeneity of falls with both self-rated health and anxiety status across gender and residence groups.\u003c/p\u003e \u003cp\u003eFirst, the present study found that falls were negatively associated with self-rated health in Chinese elderly chronic multimorbid patients. This result is consistent with past related studies. Previous studies have shown that falls interact with older adults' health levels, with more falls predicting poorer physical health, more negative emotions, and less physical activity in the near future for older adults living in the community[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In turn, more poor health also promotes the occurrence of falls in the elderly. Some medical studies have shown that the decline in muscle function of the lower extremities is a significant contributor to falls in older adults, and that this state is not an inevitable consequence of aging, but is related to an individual's underlying chronic health condition[\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, elderly patients with chronic multimorbidity are more prone to falls, and the health problems that may be associated with falls, such as limb injuries (e.g. hip fracture), deterioration of physical and cognitive functioning, and poor trajectory of recovery from chronic diseases, These will directly affect patients' assessment of their own health and lead to a low self-rated of their health status.\u003c/p\u003e \u003cp\u003eAnother correlation result of this study showed that falls were positively correlated with anxiety symptoms in Chinese elderly with chronic multimorbidity. This finding is generally consistent with previous studies, indicating that falls contribute to anxiety symptoms and adversely affect the mental health of older adults[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. It has been noted that anxiety symptoms are commonly associated with four psychological disorders triggered by falls, including fear of falling, fall-related self-efficacy, balance confidence, and outcome expectations[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. For elderly patients with chronic multimorbidity, they are inherently prone to poor mental health due to suffering from multiple chronic conditions over time[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The occurrence of falls also puts patients at risk for recurrent falls and physical impairment, which in turn triggers a fear of repeated falls and a reduced sense of self-efficacy. Previous studies have shown that it becomes more difficult for the elderly to recover from fall-related injuries[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], so after experiencing a fall older patients are more likely to develop a fear of falling again, which can be manifested as a loss of confidence in the ability to perform everyday behaviors, limiting and avoiding participation in certain activities, which contributes to the development of anxiety symptoms, and the stronger the fear, the more severe the anxiety symptoms[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In addition, the impaired health, functional deterioration, and decreased independence caused by falls may lead to a gradual resistance to social participation, which not only reduces the exchange of daily information, but also does not facilitate the venting of negative emotions, and has a serious negative impact on all areas of the patient's life, thus eroding the patient's sense of self-efficacy[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and triggering the emergence of anxiety symptoms.\u003c/p\u003e \u003cp\u003eFurthermore, the present study revealed the existence of the moderating role of psychological resilience. It has been previously shown that psychological resilience as a moderator is effective in reducing anxiety and depression after falls in older adults, and improving psychological resilience may be an effective way to intervene and prevent fall-related anxiety and depression symptoms[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In addition to this, many studies have confirmed the assertion that the moderating effects of psychological resilience can modify the impact of risk factors on psycho-social functioning[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and are reflected in different groups. For example, soldiers exposed to military operations[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], COVID-19 experiencers[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and groups of children and adolescents[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Therefore, a high level of psychological resilience is also effective in regulating one's own state of mind and suppressing anxiety symptoms triggered by negative events such as falls for a group of Chinese elderly chronic multimorbid patients. But in the relationship between falls and self-rated health of elderly patients with chronic multimorbidity, our study showed that psychological resilience did not play a significant moderating role, and we speculate that positive mental status is not sufficient to influence patients' assessment of their physical health status. Self-rated health is a reliable and effective indicator of an individual's own health[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], and has been regarded as an important reference factor for determining morbidity, hospitalization and mortality[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], which reinforces the need for patients to ensure objectivity and truthfulness in assessing their own health status. Therefore, psychological resilience fails to play a moderating role between falls and self-rated health as it is difficult to influence patients' assessment of their objective conditions such as disease, functional status, and other health problems through changes in mindset.\u003c/p\u003e \u003cp\u003eFinally, this study found that the effects of falls on self-rated health and anxiety symptoms of Chinese elderly chronic multimorbid patients varied by gender and place of residence. First, from the gender perspective, the female patient group was more likely to have poorer self-rated health and more severe anxiety symptoms in the future after a fall. The moderating effect of psychological resilience was similarly more pronounced in female patient group compared to males. A study showed that the prevalence of post-fall fear was higher in women and increased with age[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This suggests that the significant presence of post-fall fear in female patients means that they are more likely to develop anxiety symptoms after a fall. It has also been shown that women are generally more emotional than men, and are more susceptible to external influences on a mental level[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Therefore, the female chronic multimorbid group may experience greater fluctuations in their psychological state and level of cognition about themselves compared to males after experiencing fall behavior, resulting in poorer self-rated health and more severe anxiety symptoms, and psychological resilience as a positive mental state, may also play a stronger moderating role in the female patient group. From the perspective of place of residence, the results of the study showed that elderly chronic multimorbid patients living in urban areas were more likely to experience anxiety after a fall and that psychological resilience had a more significant moderating effect, whereas patients living in rural areas were more likely to experience poorer self-rated health after a fall. A possible explanation for this is that urban and rural patients experience different health shocks after falls. For older urban patients, the relatively higher level of education leads to higher expectations of educational rewards, and thus the fluctuations in psychological state may be greater in the event of a setback similar to a fall. Moreover, life in towns and cities is richer than in rural areas, which leads to greater life changes after a fall, which can have a more severe negative impact on mental health. In addition, in the relationship between falls and self-rated health, many studies have shown that Chinese rural residents generally have worse self-rated health outcomes than their urban counterparts due to unequal health opportunities and uneven utilization of healthcare services [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. On the basis of this assertion, we can further confirm that rural elderly patients with chronic diseases are more likely to have a poorer assessment of their own health after experiencing an adverse event of a fall.\u003c/p\u003e \u003cp\u003eThe strengths of this study are the selection of a sample from the National Population Survey which provided sufficient data to explore the relationship between falls and self-rated health and anxiety symptoms in older people with chronic multimorbidity, and the focus on older people with chronic multimorbidity, which provided insight into the impact of falls on their physical and mental health, and the role of psychological resilience in this. Limitations of this study are as follows: First, the study was analyzed based on a cross-sectional data set. Therefore, our predicted results cannot be explained in depth in terms of causality and can only be understood statistically, and further research on falls and Chinese elderly chronic multimorbid patients' self-rated health and anxiety symptoms needs to be explored with longitudinal data. Second, the present study used a self-rated approach for the identification of falls, in which participants were asked to recall whether a fall had occurred in the past year; this approach may be subject to recall bias, and further research should also take a more accurate approach to the recording of falls.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur findings suggest that there is a significant correlation between falls and self-rated health and anxiety symptoms in Chinese elderly chronic multimorbid patients, and a significant moderating effect of psychological resilience on inhibiting the development of anxiety symptoms. In view of this, we should pay timely attention to the changes in physical and mental health of elderly patients with chronic multimorbidity after falls, and develop a series of interventions to promote patients' physical recovery after a fall and alleviate anxiety. At the same time, future psychiatric interventions for anxiety in elderly patients with chronic multimorbidity can also start from improving their psychological resilience, so that they can cope with the fall in a more positive way and minimize the negative impact of the fall on themselves.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthorship contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShaoliang Tang:\u003c/strong\u003eresearch design, conceptualization, revision of the manuscript, language and supervision, funding acquisition. \u003cstrong\u003eJingyu Xu:\u003c/strong\u003edata analysis, writing and revision of the manuscript. \u003cstrong\u003eXiaoyan Mao and Huilin Jiao:\u003c/strong\u003e data collation and inspection, revision. \u003cstrong\u003eYuxin\u0026nbsp;Qian:\u003c/strong\u003einspection, revision.\u003cstrong\u003eGaoling Wang:\u003c/strong\u003eproject administration, resources, and supervision. All authors contributed to the article and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was supported by the National Natural Science Foundation of China (grant number 72074125).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available in https://opendata. pku.edu.cn/dataverse/CHADS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Peking University Institutional Review Board (IRB00001052-13074) has approved the study protocol of the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor detail\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eSchool of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eShaoliang Tang and Jingyu Xu contributed equally to the work and share the first authorship.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO.[Internet]. 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Journals of Gerontology Series B-Psychological Sciences and Social Sciences. 2015;70(3):470-80.\u003c/li\u003e\n\u003cli\u003eRuthig JC, Chipperfield JG, Newall NE, Perry RP, Hall NC. Detrimental effects of falling on health and well-being in later life - The mediating roles of perceived control and optimism. Journal of Health Psychology. 2007;12(2):231-48.\u003c/li\u003e\n\u003cli\u003eCuevas-Trisan R. Balance Problems and Fall Risks in the Elderly. Physical Medicine and Rehabilitation Clinics of North America. 2017;28(4):727-+.\u003c/li\u003e\n\u003cli\u003eWalker JE, Howland J. FALLS AND FEAR OF FALLING AMONG ELDERLY PERSONS LIVING IN THE COMMUNITY - OCCUPATIONAL-THERAPY INTERVENTIONS. American Journal of Occupational Therapy. 1991;45(2):119-22.\u003c/li\u003e\n\u003cli\u003eAdhaye AM, Jolhe DA. GAIT MEASUREMENT METHODS: SYSTEMATIC REVIEW AND COMPARATIVE STUDIES. Journal of Mechanics in Medicine and Biology. 2023.\u003c/li\u003e\n\u003cli\u003eYang K, Yang S, Chen Y, Cao G, Xu R, Jia X, et al. Multimorbidity Patterns and Associations with Gait, Balance and Lower Extremity Muscle Function in the Elderly: A Cross-Sectional Study in Northwest China. International Journal of General Medicine. 2023;16:3179-92.\u003c/li\u003e\n\u003cli\u003eHallford DJ, Nicholson G, Sanders K, McCabe MP. The Association Between Anxiety and Falls: A Meta-Analysis. Journals of Gerontology Series B-Psychological Sciences and Social Sciences. 2017;72(5):729-41.\u003c/li\u003e\n\u003cli\u003eGould CE, O\u0026apos;Hara R, Goldstein MK, Beaudreau SA. Multimorbidity is associated with anxiety in older adults in the Health and Retirement Study. International Journal of Geriatric Psychiatry. 2016;31(10):1105-15.\u003c/li\u003e\n\u003cli\u003eKempen G, Ormel J, Scaf-Klomp W, van Sonderen E, Ranchor AV, Sanderman R. 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Fear of falling: measurement strategy, prevalence, risk factors and consequences among older persons. Age and Ageing. 2008;37(1):19-24.\u003c/li\u003e\n\u003cli\u003eFuhrer R, Stansfeld SA. How gender affects patterns of social relations and their impact on health: a comparison of one or multiple sources of support from \u0026quot;close persons\u0026quot;. Social Science \u0026amp; Medicine. 2002;54(5):811-25.\u003c/li\u003e\n\u003cli\u003eLiu Y, Guo H, Shi X. Measurement and Trend Analysis of Health Opportunity Inequality among Urban and Rural Residents in China. Population and Development. 2023;29( 06 ):72-87.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Falls, Anxiety, Psychological resilience, Chinese elderly chronic multimorbid patients","lastPublishedDoi":"10.21203/rs.3.rs-4571446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4571446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study enquired into the effects of falls on self-rated health and anxiety symptoms, and the moderating role of psychological resilience in China's elderly chronic multimorbid patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were taken from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). We used the linear regression model to delve into the association among falls and self-rated health and anxiety symptoms, the moderating roles of psychological resilience was verifed by the moderation analysis, and we also used the replacement model to test the robustness. Finally, the results of the study were further verified by completing the heterogeneity analysis through subgroup regression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e3141 older people with chronic multimorbidity were included in our study. The linear regression results showed that falling behavior was significantly negatively correlated with self-rated health symptoms of Chinese elderly chronic multimorbid patients (β = -0.2017, p \u0026lt; 0.01), and significantly positively correlated with anxiety symptoms (β = 0.7284, p \u0026lt; 0.01). Among the moderating effects, we found that psychological resilience played a moderating role between falling behavior and anxiety symptoms (β = − 0.147 [-0.214, -0.079], p \u0026lt; 0.01). Finally, we found heterogeneity in the study results by gender and place of residence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe presence of falls tends to make Chinese elderly chronic multimorbid patients develop poorer self-rated health and higher anxiety levels. High levels of psychological resilience have a moderating effect on inhibiting the development of anxiety symptoms.\u003c/p\u003e","manuscriptTitle":"Effects of falls on self-rated health and anxiety in Chinese elderly chronic multimorbid patients : moderating role of psychological resilience","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 15:55:57","doi":"10.21203/rs.3.rs-4571446/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-08T16:19:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-07T12:16:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"159427253938524685908048355594013977","date":"2024-07-03T04:13:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45227523609598727899242472957928063008","date":"2024-07-02T11:51:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-30T09:29:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"284664752897053770609088956044900749185","date":"2024-06-24T06:27:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-24T01:57:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-20T10:24:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-18T14:23:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-18T14:23:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2024-06-12T15:51:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e83cc7da-e5be-4d34-8b23-44a7f81ad35d","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-09T16:16:37+00:00","versionOfRecord":{"articleIdentity":"rs-4571446","link":"https://doi.org/10.1186/s12877-024-05338-x","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2024-09-05 15:58:05","publishedOnDateReadable":"September 5th, 2024"},"versionCreatedAt":"2024-07-18 15:55:57","video":"","vorDoi":"10.1186/s12877-024-05338-x","vorDoiUrl":"https://doi.org/10.1186/s12877-024-05338-x","workflowStages":[]},"version":"v1","identity":"rs-4571446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4571446","identity":"rs-4571446","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}