Introduction

Health is related to quality of life, national security and social stability, and is the basis for human survival and development. It plays an important role in national economic development and is a basic condition for economic and social development [1]. In recent years, with social development and improved living standards, the health status of Chinese residents has significantly improved [2,3], and the average life expectancy has continued to increase. However, the longstanding urban-rural dual structure has led to disparities in opportunities for accumulating health-related human capital. According to the results of the National Health and Wellness Commission’s Health Literacy Monitoring Points for Residents in 2023, the health literacy level of urban residents nationwide was 33.25% in 2023, and that of rural residents was 26.23% [4]. The development of health literacy remains uneven between urban and rural areas. The issue of health disparities among different population groups has attracted widespread attention in both developed and developing countries. Health disparities are defined as systematic disparities in health outcomes between different population groups [5,6]. In this study, we used the Self-Rated Health (SRH) as an indicator of the health status of the population. The SRH not only reflects the health status of an individual, but also integrates subjective and objective aspects of health status [7].

Most studies have found that urban residents have better health than rural residents. It has been found that rural Americans are more likely to report risk factors associated with poorer health [8,9], and residents living in rural areas typically have poorer health than their urban counterparts [10]. In Brazil, although rural residents have better mortality indicators, urban residents report better self-rated health [11]. Kaczmarek’s study found that middle-aged women in urban areas have a higher quality of life than those in rural areas [12]. In fact, rural communities around the world are not only in poorer health than their urban counterparts, but also have more problems accessing health care [13]. The mechanisms that contributed to the urban-rural health disparity were multifactorial and complex. The management of multiple chronic diseases requires more health-care interactions, and the lack of access to health-care services in rural areas creates significant barriers to the management of chronic diseases [14]. In this study, urban areas refer to provincial capitals, prefecture-level cities, and their subordinate urban districts, while rural areas refer to townships and the villages under their jurisdiction.

In conclusion, with the transition of diseases, chronic diseases have been recognized as major threats to human health [15]. In 2016, non-communicable diseases caused 41 million deaths globally, accounting for 71% of global mortality. Studies have shown that chronic diseases are closely related to poor SRH [16], with some researchers finding that patients with chronic obstructive pulmonary disease (COPD) perceive their health status more negatively [17]. As age increases, the incidence of chronic diseases rises, and the prevalence of multimorbidity also increases, a trend that is expected to continue [18,19]. In China, studies show that chronic diseases have become a major threat to residents’ health, accounting for about 70% of the total disease burden [20], and have a significant negative impact on health-related quality of life [21].

However, although studies generally suggest that chronic diseases affect individuals’ SRH, the relationship between chronic diseases and SRH varies across different regions, cultures, and socioeconomic backgrounds. Few studies have specifically explored whether the disparities in chronic diseases between urban and rural residents are associated with SRH disparities, and to what extent chronic diseases contribute to the urban-rural SRH disparity. Some studies have indicated that chronic diseases affect SRH through physical symptoms, psychological distress, and functional limitations, and these factors may be exacerbated by differences in healthcare accessibility and social determinants of health [22]. To extend the current knowledge in explaining the urban–rural disparity in SRH among residents in China from the perspective of chronic diseases, this study aimed to address three questions: (1) to measure the disparities in SRH between urban and rural residents; (2) to examine the association between chronic diseases and residents’ SRH, and (3) to explore the extent to which the disparities in SRH between urban and rural residents can be explained by chronic disease disparities. Through these explorations, the aim is to gain a deeper understanding of the impact of chronic diseases on urban-rural health disparities, providing new insights for public health interventions to reduce inequalities.

Materials and methods

Statistical analyses

Multiple data analysis methods were performed to address each of our research questions. Descriptive analyses were used to describe the mean and distribution of the variables. Two-sample t-tests were used for continuous variables and chi-square tests for categorical variables to test for disparities between urban and rural groups, and the results are displayed in Table 1. In addition, listwise deletion was used to handle missing data, which involves excluding all observations with missing data, ensuring the simplicity and accuracy of the analysis results. This method is suitable for cases where the missing data is missing completely at random (MCAR) [39–41]. In order to investigate whether and to what extent chronic diseases are associated with the SRH of the residents, logistic regression for binary SRH were employed, the Linear coefficients and SRH odds ratios (OR) with 95% confidence intervals were reported. The model is as follows:

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Table 1. Descriptive and bivariate analyses of dependent and independent variables.

https://doi.org/10.1371/journal.pone.0324287.t001

(1)

Finally, the contribution of chronic disease was further explored by applying Fairlie’s non-linear decomposition (for urban-rural disparities in SRH) [42]. The model is as follows:

(2)

Some studies have shown that the Fairlie decomposition based on logistic regression model can solve the probability decomposition problem of the binary choice model, and can clearly portray the contribution of each factor to the urban-rural disparities in residents’ SRH [43]. Fairlie decomposition can be done by analysing the factors influencing the disparities in SRH between urban and rural residents and decomposing the disparities into explainable and unexplainable components. The explainable part is mainly caused by disparities in the characteristics of urban and rural residents, also known as the characteristics effect; the unexplainable part is mainly caused by unobservable factors, i.e., disparities due to urban-rural attributes when all explanatory variables are the same in urban and rural areas, also known as coefficient effects [44]. P < 0.05 was used to identify significant data in the analysis results. All statistical analyses were conducted using STATA 18.

Results

Regression analysis

Regression analyses examined independent associations between chronic diseases and residents’ SRH, and the results were shown in Table 2.

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Table 2. Logistic regression analysis of the relationship between chronic diseases and self-rated health.

https://doi.org/10.1371/journal.pone.0324287.t002

In the regression results, the OR values for chronic diseases were significantly less than 1 for both urban (OR=0.205) and rural (OR=0.167) residents, suggesting that increased chronic disease conditions were largely significantly associated with lower odds of improving SRH (p < 0.001). In addition, age (p < 0.001), marital status (p < 0.05), socio-economic status (p < 0.001), physical activity (p < 0.05), and sleep quality (p < 0.001) were significantly associated with SRH among urban residents. Age (p < 0.001), socio-economic status (p < 0.001), sleep quality (p < 0.001) were significantly associated with SRH among rural residents. In contrast, the regression results showed that there is no statistical significance for urban residents in terms of gender, education, smoking, drinking, sleep duration, and insurance status. Rural residents were not statistically significant in terms of gender, marital status, education, physical activity, smoking, drinking, sleep duration, and insurance status.

Decomposition analyses

Through decomposition, this study further revealed the contribution of different factors to the disparities in SRH between urban and rural residents. The results of Fairlie’s decomposition were presented in Table 3.

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Table 3. Fairlie decomposition analysis of disparity in self-rated healt between urban and rural residents.

https://doi.org/10.1371/journal.pone.0324287.t003

The results of the Fairlie decomposition showed that the proportion of the explainable part of the total disparities were 87.851% and the proportion of the unexplainable part were 12.149%, i.e., 87.851% of the urban-rural disparities in the SRH of the Chinese residents were due to the observable factors, and the other 12.149% were related to the unexplainable part (coefficient effect). The results of the decomposition of the factors showed that the disparity between chronic diseases on the SRH of urban and rural residents was statistically significant (β = -0.029, p < 0.001), which contributed the most, accounting for 38.915% of the total; In addition, age (β = -0.007, p < 0.001), socioeconomic status (β = -0.021, p < 0.001), physical activity (β = -0.010, p < 0.05), and sleep quality (β = -0.004, p < 0.001) were statistically significant in the disparity between the SRH of the urban and rural residents, with a contribution of 10.026%, 28.280%, 13.277%, and 5.915%; all other factors were not statistically significant (p > 0.05).

Discussion

This study used data from the CGSS 2021, focused on the disparities in SRH between urban and rural residents in China, and quantified the extent to which chronic diseases explained the disparities in SRH between urban and rural residents in China. The results of descriptive, regression analyses confirmed that the SRH rate of urban residents (58.82%) was higher than that of rural residents (50.40%), which is consistent with the findings of Liu Yehong et al. [45] and Wang Yijie et al. [46], indicating that the SRH of urban residents was better than that of rural residents. Urban residents were less likely to suffer from chronic diseases (32.89%) than rural residents (39.97%), and an increase in the prevalence of chronic diseases was largely significantly associated with a decrease in the odds of improving SRH. With this in mind, we turned our attention to explaining the urban-rural disparities in SRH by conducting decomposition analyses.

The results of the study showed that 87.851% of the disparity in SRH rates between urban and rural residents was due to observed influencing factors, including chronic diseases, age, socio-economic status, physical activity and sleep quality. Among them, the disparity in the SRH rate of urban and rural residents due to chronic diseases is statistically significant (p < 0.001), and the disparity in the SRH of urban and rural residents with a contribution rate of 38.915% could be explained by the urban-rural disparity in chronic diseases, i.e., the disparity in the SRH rate between urban and rural areas decreases by 38.915% when the urban and rural areas are equally probable to suffer from the same condition of chronic diseases, indicating that the chronic disease disparity was the most important factor influencing the disparity in SRH between urban and rural residents. This phenomenon reflected the rural population’s lack of awareness of chronic diseases and their weak self-management capacity, which is consistent with the findings of scholars such as Lu Jiehua and Sun Yang [47].

Specifically, the problem of low accessibility to basic health services in rural areas may lie behind this discrepancy. The relative scarcity of medical resources and the limited level of medical services in rural areas have led to poorer management and control of chronic diseases in rural areas compared to urban areas, which is consistent with the findings of scholars such as Vicky et al [48]. Some scholars have pointed out that the primary healthcare management of non-communicable diseases in rural areas largely relies on grassroots doctors, who have received limited medical education and training [49]. In 2012, 84% of rural doctors in China did not hold a university degree, compared to 60% in urban areas [50]. At the same time, there was also a disparity between urban and rural residents in terms of health awareness, health literacy, and medical behavior. The rural residents have insufficient awareness of healthy lifestyles and behaviors, and their failure to develop good habits and healthy lifestyles not only increased their risk of illness, but also reduced their SRH [51]. On the contrary, urban residents were better able to manage chronic diseases due to more abundant healthcare resources and greater health awareness, thus improving their SRH. In addition, previous studies had shown that people with different health levels have different needs for healthcare [52]. According to some scholars’ research, the results of the study that most of the urban residents had significantly higher levels of health knowledge, attitude holding and behaviour than the rural residents also corroborated the findings of this study [53,54]. Therefore, reducing the health disparity between urban and rural residents required attention to the impact of chronic diseases. Through the implementation of chronic disease prevention and treatment, it was possible to enhance rural residents’ knowledge of chronic diseases, improve their ability to self-manage chronic diseases, advocate for rural residents to change unhealthy lifestyles and reduce health disparities between urban and rural residents, thereby promoting health equity between urban and rural residents.

Firstly, the construction of basic health services in rural areas has been strengthened, and the quality of medical services has been upgraded by raising the level of medical resource allocation in rural areas and improving the conditions of medical services. At the same time, rural health education and publicity have been strengthened to raise rural residents’ health literacy and awareness of chronic disease prevention and treatment. Secondly, chronic disease prevention and treatment have been promoted, and the early detection and treatment rates of chronic diseases have been increased through the establishment and improvement of chronic disease prevention and treatment systems and the strengthening of chronic disease monitoring and screening. At the same time, health management and follow-up work for chronic disease patients has been strengthened to enhance their self-management capabilities. Thirdly, healthy lifestyles are being promoted, and urban and rural residents (especially in rural areas) are being encouraged to take an active part in health activities by stepping up publicity and promotion of healthy lifestyles. Furthermore, to narrow the disparity between urban and rural areas, measures such as promoting telemedicine services, providing subsidies for chronic disease management to alleviate the financial burden on rural residents, improving their health security, and dispatching community health workers to underserved areas can help reduce disparities in medical resources, economic conditions, and social support. The standard of living and health protection of rural residents has been raised, thereby narrowing the disparity between urban and rural residents in terms of chronic diseases and SRH status.

Urban-rural disparities in age, socio-economic status, physical activity, and sleep quality were also important factors associated with urban-rural disparities in the SRH of the residents. Disparities in the socio-economic status of urban and rural residents are associated with 28.280% of the disparity in SRH between urban and rural areas. It indicates that the higher the socio-economic status of Chinese residents, the more positive their SRH tends to be. This was because higher socio-economic status leads to increased spending on diet and health, which in turn improves one’s health. There were great disparities in socioeconomic status and health service utilization between urban and rural residents in China [55]. For example, the elderly living in living in rural areas often do not afford medical care and were less likely to use hospitalization services [56].

This study had several limitations. First, our choice of SRH as a measure of health status, although widely validated, still had the disadvantage of subjectivity, which may pose a threat to the accuracy of health status. Second, this study only established a association, not a causal relationship, between chronic diseases and disparities in SRH between urban and rural residents. Due to the use of cross-sectional data in this study, it is not possible to rule out the influence of potential confounding factors and reverse causality. Therefore, although our study shows that chronic disease differences play an important role in the urban-rural disparity in SRH, we cannot conclude that chronic diseases directly cause these disparities. Third, Unobservable cultural factors may have an impact on the results of the analyses in this study and the generalizability of the results. Due to the unobservability of cultural factors and the inherent complexity of urban-rural health disparities, the use of cross-sectional data may not capture all relevant factors. In the future, research should collect more data for further validation, while rigorous clinical diagnostic techniques, well-designed longitudinal surveys, and experimental analyses under ethical approval will help address these limitations.

Conclusion

Based on the results of regression and decomposition analyses, rural residents have poorer SRH and a higher prevalence of chronic diseases compared to urban residents. The increase in chronic diseases significantly reduces the likelihood of improved SRH, making the rural-urban disparity in chronic diseases a primary factor in explaining SRH disparities. Additionally, age, socioeconomic status, social participation, and sleep quality also contribute to these disparities. It is recommended to strengthen health education, emphasize disease prevention and health behavior guidance, and focus on low-education populations, labor force groups, and underdeveloped regions. Furthermore, 12.149% of the SRH disparity remains unexplained, likely due to inherent rural-urban disparities. Therefore, breaking the urban-rural divide is crucial for narrowing health disparities.

Acknowledgments

We would like to thank all individuals and organizations who provided assistance and support throughout this research. Special thanks to colleagues for their valuable feedback and to all staff members involved in the study, as well as to the institutions that provided resources for the research.