Skip to main content
Download PDF

The relationship between self-assessment living standard and mental health among the older in rural China: the mediating role of sleep quality

BMC Public Health volume 23, Article number: 449 (2023) Cite this article

Abstract

Background and objective

Mental health imbalance are the main cause of anxiety, depression and happiness reduction in the older. Self-assessment living standard and sleep quality are both influencing factors of mental health. Meantime, self-assessment living standard has an impact on sleep quality. But there’s no research on the relationship between the three, we conducted this study to explore the relationship between self-assessment living standard and mental health and the mediating role of sleep quality among the older in rural areas of China.

Methods

Using typical field sampling method, M County, Anhui Province was selected as the investigation site, and a total of 1223 respondents were selected. With the help of questionnaires enclosing respondents’ sociodemographics information, 12 Items General Health Questionnaire (GHQ-12) and Pittsburgh Sleep Quality Scale (PSQI), face-to-face interviews were used to collect data. Bootstrap test was used for data analysis.

Results

The results showed that the age of the respondents ranged from 60 to 99 years, with an average age of (66.53 ± 6.77) years, the proportion of the older with a tendency to mental health problems was 24.7%. Most of the older people’s self-assessment living standard was normal (average score was 2.89 ± 0.726), accounting for 59.3% of the total. The average sleep quality score was (6.97 ± 4.066), and 2.5% of the respondents reported serious sleep problems. older with low self- assessment living standards were more likely to report a higher propensity for psychological problems (β = 0.420, P < 0.001) and poorer sleep quality (β = 0.608, P < 0.001) than older with high self- assessment living standards. Mental health of the older may be related to sleep quality (β = 0.117, P < 0.001). In addition, the effect of self- assessment living standard on mental health was significantly mediated by sleep quality (β = 0.071, P < 0.001).

Conclusion

Mental health is associated with self-assessment living standard, with this association mediated by sleep quality. A reasonable mechanism needs to be established to improve self-assessment living standard and sleep quality.

Peer Review reports

Introduction

According to the results of China’s seventh census, the number of Chinese aged 60 and above has reached 264 million, accounting for 18.70% of the total population. The population aged 65 and above is about 190 million, accounting for 13.50% [1]. With the deepening of the aging degree in China, the psychological problems of the older have become increasingly prominent due to the changes in social and family structure, physical aging, the influence of diseases, and inadequate support system [2]. The data showed that the proportion of the older with mental problems in various regions of China ranged from 2.26 to 69.68% [3], Among them, the proportion of the older in rural areas with mental health problems is 1.76 times that of the older in urban areas [4], meanwhile, the life security, physical function and social support of the older in rural areas are significantly lower than those in urban areas [5]. According to the China Statistical Yearbook, the per capita disposable income of rural residents was 18,931 yuan in 2021, while that of urban residents was 42,412 yuan. Urban residents’ per capita disposable income was 2.5 times that of rural residents [6]. Although the government provides certain security policies for the elderly, the national standard of 55 yuan per person per month for elderly people over 60 without employee pension insurance in China. Most rural residents do not enjoy the fair treatment of social endowment insurance. There are differences in pension funds paid and received by rural and urban residents. The pension funds paid by rural residents account for a larger proportion of their income, but the insurance funds received by rural residents are lower than those of urban residents [7].

WHO defines health as a state of complete physical, mental and social adaptation, not just no disease or infirmity [8]. Psychological imbalance not only has a direct impact on physical health, but also has an indirect impact on social support and quality of life, bringing a huge burden of disease [9]. Studies have shown that age, economic status, physical status, social support, social role and lifestyle change are the main factors affecting the mental health of the older [10]. Research shows that rural residents in health spending suffered greater economic burden, its proportion is 2.4 times that of urban residents [11], at the same time, another study found, catastrophic health expenditure of Chinese rural areas was obviously higher than that of urban areas [12], studies have shown that China’s rural older people’s quality of life in rural areas and the low state of the economy [13]. Jiang Haochen’s research proved that compared with the older with a more affluent living standard, the older with a poorer living standard reported worse mental health [1], and reveal the self- assessment living standards may have an important impact on the mental health of the older population. Research pointed out that in addition to the objective measurement of economic level, people’s subjective economic pressure measurement on the personal happiness and satisfaction occupy more important position [14], of the living standards of their subjective evaluation mainly from compare yourself with other living conditions, especially in rural areas of China the older by education degree is generally low, less mental recreation makes it easier to compare oneself with others. If one continues to believe that his or her standard of living is below the average or reference level, this long-term gap will indirectly affect his or her mental health. At present, China has achieved comprehensive poverty alleviation, and absolute poverty, which is measured by meeting basic survival needs, has been eliminated. However, the identification of relative poverty, which reflects the gap between individual economy, living conditions and local average living standards, has received little attention [15]. In addition, relevant studies on the living standards of the older in rural China focus more on objective evaluation of living standards, and less on subjective evaluation [16,17,18].

Self-assessment living standard is a subjective evaluation of their own living standard, which reflects the satisfaction and expectation of the older to their living conditions. Evidence shows that the worse self-assessment living standard contributes to poor sleep health. For example, due to the rapid growth of social economy, rising price level, a large number of young and middle-aged people go out to work, the rural older people often feel helpless and declined the standard of living, think about things at night, and then suffer from poor sleep quality [19]. In turn, poor sleep quality will affect the older’s daily activities, social interactions and attitudes toward life, resulting in lower life satisfaction and worse self-assessment living standards [19].

Sleep quality usually declines gradually with age [20], and some older people may suffer from sleep disorders. The incidence of sleep disorders among the older over 60 years old in China is 30% ~ 40% [21]. Sleep disorders are mainly manifested as difficulty in falling asleep and maintaining sleep, which leads to sleep deficiency and fatigue, and patients find it difficult to recover from sleep [22]. A large number of studies have shown that poor sleep quality will not only increase the occurrence of chronic diseases, but also increase the risk of death [23,24,25]. According to the view of chronobiology theory, the biorhythmic system is closely related to many diseases, and regular sleep contributes to the stability of human psychological functions [26]. If the body’s sleep time changes and the body’s functions are disordered, it will affect the disorder of emotional function and lead to a decline in psychological conditions. Studies have shown that there is a significant correlation between sleep quality and mental health, and sleep disorders (such as insomnia, narcolepsy, sleep apnea and circadian complaints) have a high comorbidity rate with depression and anxiety [27, 28], optimizing sleep quality can promote mental health [29]. Meanwhile, the older with poor sleep quality are more likely to suffer from hypertension, depression and other diseases [25]. At present, there are many studies on the influencing factors of sleep disorders in the older in China. For example, moderate exercise is beneficial to improve the sleep quality of the older [30]. Interpersonal relationship can affect the sleep quality of the older by affecting their mood [31]. However, the potential causes of sleep quality among the older in China have not been fully appreciated.

Given that sleep quality is one of the important predictors of mental health [32]. Improving self-assessment living standards in older may reduce mental illness by improving sleep quality. However, little is known about the mechanisms that link self-assessment living standard and mental health prospectively. There are no studies that have tested whether poor sleep quality mediates the relation between self-assessment living standard and mental health [33,34,35]. In the context of the rapid development of aging society has become the basic national conditions of China, the mediation of the impact of self-assessment of living standards on mental health has become an issue that needs to be studied in the prevention of psychological abnormalities in the older. Therefore, we conducted a cross-sectional study to uncover the relationship between self-assessment living standards and mental health among older people in rural China, and to consider the role of sleep quality in this study. This study can provide a theoretical basis for improving the sleep quality and mental health of rural elderly.

Methods

Study design and data collection

From July to September 2021, we conducted a cross-sectional survey in M County, Anhui Province, central China. M county is a pilot county of compact county medical community. The local county and village medical and health service system is sound and relevant departments have strong coordination, providing good external conditions for the research work.

Two towns in M County, Anhui Province, China were randomly selected, and 5 villages were randomly selected in each town. M County is a typical rural area in central China. Its level of economic development and per capita income are below the average level of China. In 2021, the per capita disposable income of permanent residents in M County was 24,344 yuan, and the per capita disposable income of permanent rural residents was 17,221 yuan [36]. The annual per capita disposable income of Chinese residents was 35,128 yuan [37], the economic level of the older in M County was significantly lower than the national average.

The older ≥ 60 years old in the villages were investigated. The selection criteria of the research objects were as follows: (1) subjects aged 60 years and above (according to Article 2 of the Law on the Protection of the Rights and Interests of the older, the age of the older is 60 years old); (2) Subjects who have lived there for at least 1 year at the time of investigation. Exclusion criteria included sensory or cognitive impairment, contraindications to physical activity, a medical diagnosis of a primary sleep disorder (for example, sleep apnea or primary insomnia). Before the investigation, all subjects were told the purpose and procedure of the study orally. The investigators were all postgraduates from Anhui Medical University who had received unified training and doctors from local township health centers. Each subject was visited and interviewed face-to-face. A total of 1223 older people were surveyed, of whom 1188 completed the survey, with an effective response rate of 97.14% (1188/1223).

Measurement of self-assessment living standard

This study used self-assessment living standard to measure the living standard of the older. The respondents were asked “What is your living standard in the local area?“, the answers were divided into five levels: “very good”, “good”, “average”, “poor” and “very poor”, with a value of 1, 2, 3, 4 and 5 respectively. The higher the score was, the lower the self-assessment living standard.

Measurement of sleep quality

The Pittsburgh Sleep Quality Scale (PSQI) was used in this study. PSQI was developed by Buysse et al. [38] for self-assessment of sleep in the past 1 month. The scale consists of 7 dimensions, including subjective sleep quality, sleep time, sleep time, sleep efficiency, sleep disorders, sleep drugs, and daytime dysfunction. Each dimension is 0 ~ 3 points, and the cumulative score is the total score. The lower the score, the better the sleep, the cumulative score of 7 or more indicating sleep disturbance [39]. The Cronbachα coefficient of the scale was 0.77, the half-fold reliability was 0.83, and the structural validity was 0.63–0.91, indicating that the scale had good reliability and validity and was widely used [38, 40].

Measurement of mental health

Mental health was measured using the 12 Items General Health Questionnaire (GHQ-12), a self-assessment screening tool that has been successfully applied to the Chinese sample. There are 12 items in the questionnaire, and the answers to each item are divided into four options. The first two items are counted as 0 points, and the last two items are counted as 1 point. The total score ranges from 0 to 12 points. The higher the GHQ-12 score, the higher the risk of developing psychological disorders [41]. The Cronbach’s alpha coefficient of GHQ-12 was 0.793.

Statistical analysis

First, we used the Chi-square test to examine differences in mental health among older adults with different living standards and quality of sleep. Rates and percentages are used to describe the demographic characteristics of different groups of subjects.

Next, Pearson correlation analysis was used to test the correlation between variables. In order to further explore the specific role path of sleep quality in the mediating effect of self-assessment living standard on mental health, this study adopted the mediating effect test method proposed by Hayes [42], taking self-assessment living standard as independent variable, mental health as dependent variable and sleep quality as intermediary variable to test the significance of the mediating effect. Mediation test Model 4, developed by Hayes based on the SPSS macro program PROCESS, uses the non-parametric percentage Bootstrap method with bias correction to extract an estimated 95% confidence interval repeatedly for 5000 times. When the confidence interval of each path coefficient does not include 0, it indicates that the mediation effect is significant. According to the test results, the mediation effect path analysis model is drawn, as shown in Fig. 1.

Results

Characteristics of participants

Table 1 describes the general demographic characteristics of the respondents. The study involved 1,188 participants, all participants are between the ages of 60–99 (mean age = 66.53 years, SD = 6.577). The average of self-assessment living standard is (2.89 ± 0.726), and the sleep quality was (6.97 ± 4.066), mental health is (2.08 ± 1.90). Of these participants, 895 reported good mental health and 293 reported poor mental health. There are statistically significant differences between the two groups in basic demographic characteristics such as gender, education level, living status, working status, chronic diseases and hospitalization, and sleep quality. Among the 895 subjects with good mental health, 50.72% (454/895) are male, 36.65% (328/895) are aged between 60 and 69, 21.90% (196/895) lived with their spouse, and 85.70% (767/895) had not seen a doctor in the last two weeks. 60.56% (542/895) had not been hospitalized in the past one year.

Table 1 General characteristics of the respondents and Chi-square test results of influencing factors of mental health in rural older people (N = 1188)
Full size table

The relationship between living standard, sleep quality and mental health

Pearson correlation analysis is conducted on the data of self- assessment living standard, sleep quality and mental health scales, and the results are shown in Table 2. The score of mental health status is significantly positively correlated with the score of self- assessment living standard and sleep quality.

In Table 3, bootstrap test analysis results showed that self-assessment living standard had a significant direct impact on mental health (β = 0.420, 95%CI 0.273–0.567). older people with higher self-assessment living standards are likely to report higher levels of mental health. Meanwhile, self-assessment living standard is significantly associated with sleep quality: higher self-assessment living standard is associated with better sleep quality compared with lower self-assessment living standard (β = 0.608, 95%CI 0.282–0.933). There is also a link between sleep quality and mental health. Higher sleep quality scores are associated with higher mental health level (β = 0.117, 95%CI 0.091–0.142). Based on the results, a path map of self-assessment living standards, sleep quality and mental health is drawn, as shown in Fig. 1.

Table 2 Correlation analysis of subjective evaluation of living standard, sleep quality and mental health
Full size table
Table 3 Bootstrap test of self- assessment living standard, sleep quality and mental health
Full size table
Fig. 1
figure 1

Mediating model of self-assessment living standard, sleep quality and mental health

Full size image

Mediating effect analysis of self-assessment living standard, sleep quality and mental health

Sleep quality is a potential mediator in the association between self-assessment living standards and mental health (β = 0.071, 95%CI 0.021–0.099). Bootstrap test results showed that the 95%CI of direct and indirect effects of self-assessment living standard on mental health score did not include 0. The results indicate that sleep quality plays a partial mediating role in the relationship between the self-assessment living standard and mental health of the older in rural areas, and the partial mediating effect value is 0.071, accounting for 14.46% of the total effect. The specific results are shown in Table 4.

Table 4 The mediating effect of sleep quality on self-assessment living standard and mental health
Full size table

Discussion

This study proved the relationship among self-assessment living standard, mental health and sleep quality among the older in rural areas of Anhui Province. The results showed that self-assessment living standard was closely related to mental health, and the older with low self-assessment living standard had a higher risk of psychological problems. However, this correlation occurs through both direct and indirect effects. Sleep quality played a significant partially mediating role between self-assessment living standard and mental health.

Rural older self-assessment living standard, sleep quality and mental health status

Among the 1,188 respondents, 702(59.34%) thought their living standard was average, 202(16.92%) thought their living standard was poor or even very poor, and 284(23.74%) thought their living standard was good, among which the proportion of self-assessment was average or poor was significantly higher than the research results of Jiang Haochen [43]. The reason may be that the regional distribution of the survey objects and the total number of samples are different. Meanwhile, the economic status and medical level of rural areas are lower than the national level [43]. Some studies have classified the lifestyle of the older in China into four types: survival type, healthy type, risk type and mixed type, with 45%, 25%, 13% and 17% respectively. The life style of the older in rural Areas of China is mainly subsistence lifestyle [44]. They control the living cost and have few social participation behaviors, mostly watching TV and listening to radio, and less intake of fresh fruits and fish in daily life, which may be an important reason for their low self-assessment of living standard [45].

The results of this study show that 24.7% of the rural older have a tendency to have mental health problems, which is similar to 18.5%~24.47% of the general older population [46,47,48]. Compared with the urban older, the rural older in China have less financial resources, social support, family companionship, etc., and relatively overlapping living environment, which may have a negative impact on their mental health [49]. Gender, education level and working state have statistical significance to mental health difference, which is consistent with the research conclusions of Liang Xiaoli ; Zhang Pei [50, 51].

Compared with men, women are more sensitive to emotions and more prone to mental problems [52]. The older with high education level have higher cognitive ability and health awareness, and can enrich themselves by reading books, reading newspapers and participating in social activities, so as to better cope with difficulties. On the other hand, the older with a low education level, limited by their cognitive level, have a poor ability to judge things and accept new things, and are prone to suffer from inferiority complex, loneliness and other psychological problems. Their enjoyment of life is relatively limited, which is more likely to cause psychological problems [53]. Older who are able to work regularly tend to report better mental health, possibly because working in rural areas is the norm. Older people who are unable to work normally always experience feelings of guilt, particularly if they are not able to work at all, they will see themselves as a burden on their families [54].

In addition, 48.4% of participants with PSQI scores above 7, and 2.5% of participants reported serious sleep problems, which was higher than the results of Ding Kunxiang’s study [55]. This may be due to the different time points we surveyed and changes in the social environment in rural areas [56].

The effect of self-assessment living standard on mental health

Previous studies have observed a correlation between self-assessment living standards and mental health [57,58,59]. Previous studies have revealed the impact of poverty on the mental health of the older. For example, one research (2012) found that poverty was significantly correlated with cognitive impairment and depression in the older in India [60]. A study (2017) on the older in rural China shows that the mental health status of the older in poor families is worse [61]. A scholar. (2021) conducted a study on the older aged 65 and above in China, which verified that the older with lower self-assessment living standards had more severe negative psychological emotions [62]. The negative impact of lower living standards on mental health may come from the negative impact of less economic foundation and resources on individuals’ physical health and social behavior, or the poverty-related living environment may lead to more stress and negative emotions, thus affecting mental health [1]. In addition, social comparison theory believes that social comparison is intra-group and inter-group comparison, and the latter has a more obvious impact on individual psychological development [63]. However, these studies use different participant groups (e.g., young adults) or analytical methods (e.g., traditional regression and correlation). Although those studies differed from ours in terms of specific details, the results regarding the negative relationship between self-assessment living standard and mental health were consistent, which confirms the results of our study.

The impact of self-assessment living standards on sleep quality

This study found that self-assessment living standard was associated with an increased likelihood of high sleep quality among the older in rural areas in Anhui province. A study conducted in Yunnan Province, China, showed that older people in rural areas with lower family property have a higher likelihood of sleep disorders [64]. It may be related to their sensitive emotions. The older with lower living standards are more likely to have negative thoughts and to have random thoughts before going to sleep, which affects their sleep. Low level of self-reported life means not only a single economic sources, less material resources, and poor living environment, also means that more stressful life events and negative mood [65], which will result in its sleep problems obviously increased, low level of self-reported life will bring such as difficulty falling asleep, wake up, wake up at night and having nightmares and other sleep problems.

The mediating role of sleep quality in self-assessment living standard and mental health

This study found that sleep quality was the mediating variable between the self-assessment living standard and mental health of the rural older, playing a partial mediating role, accounting for 14.46% of the total effect. Specifically, older who reported low self-assessment living standards are more likely to suffer from poor sleep quality, which in turn led to worse mental health over time. According to the theory of chronobiology [66], the onset of mental diseases is closely related to the biorhythmic system, and the elderly who report their poor living standards are prone to cranky thoughts at night, resulting in the disorder of the sleep system, destroying the normal regulatory mechanism of the human body, and increasing the risk of psychological problems.Earlier studies have also confirmed this conclusion. In a study of German communities and students found that when individuals’ sleep quality and mental health are not healthy, measures to improve sleep can better promote the improvement of mental health [63]. Another study found that poor sleep quality is associated with increased incidence of violations, aggression, depression and anxiety [67]. One study in China [68] shows that when the proportion of children going out is high, the negative missing time effect is dominant, which is not conducive to the improvement of parents’ health. Possible explanations for this result is that although China has comprehensive poverty alleviation, rural residents general living standards improve gradually, but the income of the rural older people in China still is generally low, cultural life still relatively monotonous and boring [69], coupled with the decline in physiological function, relative lack of medical resources, children migrant workers and other factors, It will have a negative impact on their economic status and living standards for a long time. At the same time, they are easy to fall into sleep difficulties, easy to wake up, nightmares and other sleep disorders, leading to their inability to relieve mental stress through sleep, resulting in psychological problems. When the quality of sleep is poor in the older, it will also affect their self-rated living standards [70]. Poor sleep quality will affect the older’s daily activities, social interactions and attitudes toward life, resulting in lower life satisfaction and worse self-assessment living standards [71]. Therefore, China can help prevent sleep and psychological problems in the older by strengthening the training of Primary healthcare workers in this therapy.

Advantages and limitations

Advantages: First, the effective response rate of this study is 99.00% (1188/1223), as we all know, studies with higher effective response rates were more reliable. Secondly, we used internationally recognized measurement questionnaires to make objective measurements of the study subjects. In addition, this is the first study to examine the relationship between the three variables and the mediating role of sleep quality in the older population in Anhui Province.

However, this study also has the following limitations: First, self-assessment living standards, sleep quality, and mental health were measured through questionnaires, which means that self-reported biases may affect the results. At the same time, because the measurement of the self-assessment living standard of the older is single, the reliability of the answer will be reduced, which may impact the research results. Second, since this study is a cross-sectional study, although there is a correlation between self-assessment living standards, sleep quality and mental health, it is difficult to determine the causal association. Finally, the investigation objects of this study only cover rural areas of Anhui Province, and the extensibility of the results of this study is limited by factors such as economic development and cultural background.

Conclusion

Our research shows that self-assessment low living standards and poor sleep quality can exacerbate psychological problems. In addition, sleep quality mediates the relationship between self-assessment living standards and mental health. Our results may help alleviate psychological problems and improve sleep quality of rural older, and provide information for clinical prevention of diseases. It is suggested that the government and society pay more attention to the health of the rural older, improve the rural older security system, and improve the level of security.

Availability of data and materials

The datasets generated during the study are not publicly available due to an ethical restriction but are available from the corresponding author on reasonable request.

References

  1. Jiang H, Jimin G. Empirical research on subjective relative poverty, Mental Health and Life satisfaction of the older. Popul Dev. 2021;27(05):24–35.

    Google Scholar 

  2. Zhang D, Zhonghong Z. Study on the current Situation and influencing factors for Mental Health Service demand in the Community older. J Qilu Nurs. 2021;27(21):17–20.

    Google Scholar 

  3. Guo Lixin W, Jianyu Z, Juan, et al. Mental health status of middle-aged and older in China. Chin J Gerontol. 2015;35(03):782–3.

    Google Scholar 

  4. Guo A, Lai DWL. A comparative study on depressive symptoms of Urban and Rural older Population in China. J Shandong Normal Univ. 2011;56(01):106–10.

    Google Scholar 

  5. Yang JL, Zhenjie HY. Matching of home care service supply and demand, satisfaction degree and its impact on mental health of disabled older in rural areas: An analysis of survey data in Shandong and Zhejiang. Popul Develop. 2022;28(05):70–83.

  6. People’s Republic of China Statistics Bureau. China Statistical yearbook [M]. Beijing: China Statistics Press; 2021.

    Google Scholar 

  7. Li B. Guiding Social Pension Security from “Fragmentation” to “systematization”. People’s Forum. 2018;No.608(27):58–59.

  8. Rudnicka E, Napierała P, Podfigurna A, Męczekalski B, Smolarczyk R, Grymowicz M. The World Organization (WHO) approach to healthy ageing. Maturitas. 2020;139:6–11.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Wulsin L, Herman J, Thayer JF. Stress, autonomic imbalance, and the prediction of metabolic risk: a model and a proposal for research. Neurosci Biobehav Rev. 2018;86:12–20.

    Article  PubMed  Google Scholar 

  10. Ohrnberger J, Fichera E, Sutton M. The relationship between physical and mental health: a mediation analysis. Soc Sci Med. 2017;195:42–9.

    Article  PubMed  Google Scholar 

  11. Chen S, Guo L, Wang Z, Mao W, Ge Y, Ying X, et al. Current situation and progress toward the 2030 health-related sustainable development goals in China: a systematic analysis. PLoS Med. 2019;16:e1002975.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Ma X, Wang Z, Liu X. Progress on catastrophic health expenditure in China: evidence from china family panel studies (CFPS) 2010 to 2016. Int J Environ Res Public Health. 2019;16:4775.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Ran L, Jiang X, Li B, et al. Association among activities of daily living, instrumental activities of daily living and health-related quality of life in older Yi ethnic minority. BMC Geriatr. 2017;17:74.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Selenko E, Batinic B. Beyond debt. A moderator analysis of the relationship between perceived financial strain and mental health. Soc Sci Med. 2011;73(12):1725–32.

    Article  PubMed  Google Scholar 

  15. Wu C, Ling W. Focus on poverty among the older in rural China. Social Stud. 2005;22(S1):1–8.

  16. Gao Li L, Shuzhuo WZ. Urban-rural differences in the Effect of Community Poverty on older Mental Health–A Study based on the 2014 chinese longitudinal aging Social Survey. Popul Dev. 2019;25(05):28–49.

    Google Scholar 

  17. Ma C, Song Z, Zong Q. Urban-rural inequality of opportunity in Health Care: evidence from China. Int J Environ Res Public Health. 2021;18(15):7792. Published 2021 Jul 22.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Wang C, Lang J, Xuan L, Li X, Zhang L. The effect of health literacy and self-management efficacy on the health-related quality of life of hypertensive patients in a western rural area of China: a cross-sectional study. Int J Equity Health. 2017;16(1):58.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Haiyan L, Lining Y, Shaoquan Z, Junrong S, Baoshi Z, Jiang W. Study on quality of life and its influencing factors of Dong older people in rural areas of Guizhou. J Qiannan Med Coll Nationalities. 2022;35(03):188–92.

  20. Tian Yuan L. Epidemiological study of sleep disorder in the older. Chin J Epidemiol. 2017;38(07):988–92.

    Google Scholar 

  21. Song Aiqing C. Analysis of sleep quality and risk factors of older in community in Tangshan city. Nurs Res. 2011;25(04):298–9.

    Google Scholar 

  22. Xie Z, Chen F, Li WA, et al. A review of sleep disorders and melatonin. Neurol Res. 2017;39(06):559–65.

    Article  CAS  PubMed  Google Scholar 

  23. Tao F, Cao Z, Jiang Y, et al. Associations of sleep duration and quality with incident cardiovascular disease, cancer, and mortality: a prospective cohort study of 407500 UK biobank participants. Sleep Med. 2021;81:401–9.

    Article  PubMed  Google Scholar 

  24. Zhao J. Sleep deprivation is 180% more likely to kill people. Consumer Electron Mag. 2017;19(04):34–7.

  25. Fu P, Zhou C, Meng Q. Associations of Sleep Quality and Frailty among the older adults with chronic disease in China: the Mediation Effect of Psychological distress. Int J Environ Res Public Health. 2020;17(14):5240.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Kirlioglu SS, Balcioglu YH. Chronobiology Revisited in Psychiatric Disorders: from a translational perspective. Psychiatry Investig. 2020;17(8):725–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Janati Idrissi A, Lamkaddem A, Benouajjit A, et al. Sleep quality and mental health in the context of COVID-19 pandemic and lockdown in Morocco. Sleep Med. 2020;74:248–53.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Feng Mingyu Xu, Tong. Han Hui. In western China rural older anxiety status and influence factors analysis. J health Educ China. 2022;38(02):173–6.

    Google Scholar 

  29. Hosker DK, Elkins RM, Potter MP. Promoting Mental Health and Wellness in Youth through Physical Activity, Nutrition, and sleep. Child Adolesc Psychiatr Clin N Am. 2019;28(02):171–93.

    Article  PubMed  Google Scholar 

  30. Palma JA, Urrestarazu E, Iriarte J. Sleep loss as risk factor for neurologic disorders: a review. Sleep Med. 2013;14(03):229–36.

    Article  PubMed  Google Scholar 

  31. Hartescu I, Morgan K, Stevinson CD. Increased physical activity improves sleep and mood outcomes in inactive people with insomnia: a randomized controlled trial. Sleep Res. 2015;24(05):526–34.

    Article  Google Scholar 

  32. Dorrance Hall E, Meng J, Reynolds RM. Confidant network and Interpersonal Communication Associations with Depression in older adulthood. Health Commun. 2020;35(07):872–81.

    Article  PubMed  Google Scholar 

  33. Xiantao Q, Jianping R, Mengyan H, Lixian R, Qingchun C, Jinjing W. Wang Wenting. Study on the implementation effect and influencing factors of traditional Chinese medicine health management service in community population with chronic neck and shoulder pain: based on goal achievement assessment method. Chin J Gen Pract. 2022;25(34):4292–7.

  34. Rossier G, Bonnet C, Soura D, Corker AB. Mental health and urban living in sub-saharan Africa: major depressive episodes among the urban poor in Ouagadougou, Burkina Faso. Popul Health Metr. 2016;14:18.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Myhrvold T, Småstuen MC. The mental healthcare needs of undocumented migrants: an exploratory analysis of psychological distress and living conditions among undocumented migrants in Norway. J Clin Nurs. 2017;26(5–6):825–39.

    Article  PubMed  Google Scholar 

  36. Shu-hua Liu. The analysis of the influence factors of self-evaluation of health older [D]. Jilin University; 2022. 001208.

  37. M County People’s Government. M County 2021 National Economic and Social Development Statistical Bulletin [R]. 2021.

  38. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28:193–213.

    Article  CAS  PubMed  Google Scholar 

  39. National Bureau of Statistics. National Economic and Social Development Bulletin [R]. 2021.

  40. Grandner MA, Kripke DF, Yoon IY, et al. Criterion validity of the Pittsburgh Sleep Quality Index: investigation in a non-clinical sample. Sleep Biol Rhythms. 2006;4(2):129-39.

  41. Manzar MD, BaHammam AS, Hameed UA, et al. Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review. Health Qual Life Outcomes. 2018;16(01):89.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Gan Yiqun. New trends in mediating effect research: study design and data statistical methods. Chin Mental Health J. 2014;28(08):584–5.

    Google Scholar 

  43. Md M, Hasan, et al. Socioeconomic inequalities of undiagnosed diabetes in a resource-poor setting: insights from the cross-sectional Bangladesh Demographic and Health Survey 2011. Int J Environ Res Public Health. 2019;16(1):115–5.

    Article  Google Scholar 

  44. Xu DT. Does rural basic medical insurance reduce catastrophic medical expenditure and poverty caused by illness?. Nanjing Agricultural University, 2019.

  45. Zhang Yun LH. Socio-Economic Status and patterns of Lifestyle of the older adults in China: convergence at lower levels while divergence at higher Levels. Popul Res. 2021;45(03):114–28.

    Google Scholar 

  46. Yu CF. Effects of different pension modes on the quality of life and burden level of the older and their satisfaction evaluation. Chin J Geriatric Healthcare Med. 2021;19(06):83–85.

  47. Nie Yumei. Life Quality and influencing factors of aged In-patients with chronic Diseases. Chin Primarv Health Care. 2014;28(09):83–4.

    Google Scholar 

  48. Fang Jintao L, Wenxiu LX. Anxious and depressive symptoms and their influencing factors among people in Community aged in Beijing Haidian District. China J Health Psychol. 2015;23(03):447–50.

    Google Scholar 

  49. Wu Yiling L, Ruichun Z, Shanshang, et al. Mental health status and its influence factors among senior citizens in Jinhua,Zhejiang province. Chin Rural Health Service Adm. 2015;35(02):213–5.

    Google Scholar 

  50. Jiang W, Juanjuan S. Residential style, residential environment and mental health of the older in urban and rural areas: an analytical framework for the construction of an age-friendly community. Urban Problems. 2022;No318(01):65–74.

  51. Liang Xiaoli Y, Zhou L, Ju, et al. Study on mental health status, influencing factors and countermeasures of the older in Sichuan Province from the perspective of active aging. Occuptional Health. 2021;37(13):1789–92.

    Google Scholar 

  52. Zhang Pei. Study on the influencing factors of mental health of the older in Xi ‘an [D]. Xi ‘an Univ Arch Technol. 2021;37(13):1789–92.

    Google Scholar 

  53. Zhu EDY, Zhang D. Subjective Social Class and the Sense of Gain of Chinese Residents: The Multiple Mediating Roles of Social Exclusion and Social Support. Chin J Clin Psychol. 2022;30(01):111–5.

  54. Liu XX, Yu G-LY-E, Li M-z. Research on improving mental health status of Shidu older from the perspective of positive psychology. Chongqing Med J. 2020;49(12):2009–2012.

  55. Yang TBX. Does adult children going out weaken family support for the older in rural areas? -- Analysis based on propensity score matching method. China Rural Observation. 2020;No154(04):50–69.

  56. Kunxiang D. Correlation analysis between sleep quality and cognitive function and dietary intake of rural older in Jiaozhou city. Qingdao University. 2021.

  57. Jiang WW, Nian S, Qiuju F, Qingxuan L, Wenzhu HX. Analysis of sleep quality and its influencing factors in the older in military rest homes in Hefei. China Med Rev. 2022;19(05):56–9.

  58. Downward P, Rasciute S, Kumar H. Health subjective financial situation and well-being: a longitudinal observational study. Health Qual Life Outcomes. 2020;18(01):203.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Wong ES, Hebert PL, Hernandez SE, et al. Association between local area unemployment rates and use of Veterans Affairs outpatient health services. Med Care. 2014;52(2):137–43.

    Article  PubMed  Google Scholar 

  60. Bhattacharjee B, Acharya T, “The. COVID-19 pandemic and its Effect on Mental Health in USA - A Review with some coping Strategies”. Psychiatr Q. 2020;91(4):1135–45.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Reddy NB, Pallavi M, Reddy NN, et al. Psychological morbidity Status among the Rural Geriatric Population of Tamil Nadu, India: A Cross - sectional study. Indian J Psychol Med. 2013;34(03):227–31.

    Article  Google Scholar 

  62. Xingxiang W, Chao C. Whether poverty affects mental health of middle-aged and older people in rural Areas–an empirical study based on CHARLS Data. Southern Economy. 2017;No.322(12):47–65.

  63. Haushofer J, Fehr E. On the psychology of poverty. Science. 2014;344(6186):862–7.

    Article  CAS  PubMed  Google Scholar 

  64. Wang Daoyang W, Wei Y, Xin. Migration Children’s inferiority and perceived academic Self-efficacy: the moderating role of emotion regulation strategies. Stud Psychol Behav. 2019;17(01):48–55.

    Google Scholar 

  65. Ma Guoyu C, Le Y, Jiatian, et al. Analysis of sleep disorders and socio-economic differences among rural older in Ninger County, Yunnan Province. Mod Prev Med. 2019;46(20):3724–7.

    Google Scholar 

  66. Zaki NFW, Spence DW, BaHammam AS, Pandi-Perumal SR, Cardinali DP, Brown GM. Chronobiological theories of mood disorder. Eur Arch Psychiatry Clin Neurosci. 2018;268(2):107–18.

    Article  PubMed  Google Scholar 

  67. Kim JJ, Oldham M, Fernando AT, et al. Compassion Mediates Poor Sleep Quality and Mental Health Outcomes Mindfulness. 2021;12:1252–61.

    Google Scholar 

  68. Su Y, Wang SB, Zheng H, et al. The role of anxiety and depression in the relationship between physical activity and sleep quality: a serial multiple mediation model. Affect Disord. 2021;290:219–26.

    Article  Google Scholar 

  69. Guanghui J, Ying W, Hao H. Re-examining the relationship between Adult Children Migration and Rural Left-behind parents’ health from the perspective of intergenerational support. Popul Econ. 2021;No.249(06):108–25.

  70. Haiyan Y. Investigation and reflection on the Current Situation of the spiritual and cultural life of the Rural older: a case study of Lu’an City. J Chongqing Univ Arts Sciences: Social Sci Ed. 2019;38(05):1–8.

    Google Scholar 

  71. Zheng H, Peng ZHongXu, Junyun C. Related factors affecting - year - old people sleep time and quality analysis. J Pract Med J. 2019;4(12):1096–9.

    Google Scholar 

Download references

Acknowledgements

The authors would like to appreciate the involvement of the participants who joined this study.

Funding

This research was funded by Research Projects of Humanities and Social Sciences in Colleges and Universities of Anhui Province (No. SK2018A0165) and Doctoral Fund Project of Anhui Medical University (No. XJ201545). The funders had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Author information

Author notes

  1. Beibei Zhang and Xianwen Wang contributed equally to this work.

Authors and Affiliations

  1. Department of Health Service Management, School of Health Management, Anhui Medical University, Hefei, Anhui, China

    Beibei Zhang, Song Liu, Min Zhang, Xinran He, Weizheng Zhu & Hong Ding

  2. School of Public Health and Health Management, Anhui Medical College, No. 81 Meishan Road, Hefei, 230032, Anhui, China

    Xianwen Wang

Authors
  1. Beibei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xianwen Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Song Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Min Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xinran He
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weizheng Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hong Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

BBZ conceptualized the study. XW, SL, MZ, contributed to the study design, data collection and data processing and statistical analysis. XR contributed to the literature review. BBZ wrote the article. BBZ, XW and WZ revised the article. All authors reviewed the manuscript and approved the final manuscript.

Corresponding author

Correspondence to Hong Ding.

Ethics declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Research Ethics Committee of Anhui Medical University. All participants were fully informed about the study purpose and methods. Before conducting the survey, explain the purpose and procedures of the research to all interviewees, and ensure that all interviewees have informed consent to this research. For the illiterate interviewees, the informed consent of the guardian was also obtained.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, B., Wang, X., Liu, S. et al. The relationship between self-assessment living standard and mental health among the older in rural China: the mediating role of sleep quality. BMC Public Health 23, 449 (2023). https://doi.org/10.1186/s12889-023-15157-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-023-15157-1

Keywords

BMC Public Health

ISSN: 1471-2458

Contact us