Research on the urban-rural differences and influencing factors of life satisfaction among elderly people in China

Abstract

Objective

To analyze the differences in life satisfaction and the factors that influence it among elderly people in urban and rural locations in China and to provide a reference for narrowing these differences.

Methods

Binary logistic regression was used to analyze 2018 data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) to understand the status of life satisfaction and urban-rural differences among the elderly.

Results

Among 4,910 elderly participants, the overall life satisfaction rate was 72.5% (3,560/4,910). The life satisfaction rate was higher in urban areas (75.5%) compared to rural areas (68.0%), with a statistically significant difference (χ²=33.817, P < 0.001). Multivariate analysis revealed that residence was an independent factor influencing life satisfaction among urban elderly (P < 0.05), while marital status and smoking status were independent factors among rural elderly (P < 0.05).

Conclusion

The study found significant urban-rural differences in life satisfaction among the elderly, with higher satisfaction in urban areas. Key factors influencing life satisfaction varied between urban and rural settings. These findings highlight the need for targeted interventions to address these disparities and improve the well-being of China’s elderly population.

Introduction

Aging is an increasingly critical national issue in China, with the country witnessing a rapid expansion of its elderly population. As of 2019, China had 164.5 million citizens aged 65 and older, including 26 million individuals over 80, making up 18% of the global elderly population [1]. Projections suggest that, by 2050, China’s elderly population will reach 365 million, constituting 26.1% of the total population [2]. This demographic transition is accompanied by growing demands for improved quality of life and better health among the elderly, driven by rapid economic and social advancements.

Life satisfaction, a key indicator of overall well-being among older adults, is influenced by a complex interplay of factors, including socioeconomic status, health, and living conditions [3, 4]. In China, the stark contrast between urban and rural environments results in varied living conditions that significantly impact the life satisfaction of elderly individuals. The dual structure of urban and rural areas not only shapes access to resources but also affects the experiences and outcomes of the aging population [5, 6].

Theoretical frameworks, such as the Disengagement Theory and the Activity Theory, have been employed to understand the determinants of life satisfaction among the elderly. These theories highlight the role of social engagement, economic security, and health status in shaping the subjective well-being of older adults. However, China’s unique context of urban-rural disparities adds another layer of complexity to these established frameworks, necessitating a more nuanced analysis.

Recent studies have underscored the importance of addressing urban-rural disparities to meet the needs of China’s aging population effectively. Socioeconomic factors such as income, education, and access to healthcare vary significantly between urban and rural areas, resulting in differences in life satisfaction [7, 8]. Additionally, health behaviors, including physical activity and chronic disease management, are crucial determinants of life satisfaction, with varying patterns observed across urban and rural settings [9]. Despite these insights, there remains a noticeable gap in comprehensive analyses addressing these factors within the Chinese context.

This study seeks to fill this gap by utilizing data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) to examine the differences in life satisfaction between elderly individuals in urban and rural China. This research aims to provide targeted insights for policymakers and healthcare professionals by identifying the factors contributing to these disparities. This study offers a unique contribution by being one of the first to systematically investigate the intersection of life satisfaction, health behaviors, and socioeconomic factors among elderly populations in both urban and rural settings in China. The findings reveal key urban-rural disparities that previous studies had not thoroughly explored. Additionally, the study introduces binary logistic regression in analyzing the factors contributing to life satisfaction, providing a more nuanced understanding of how these factors vary across different environments.

Materials and methods

Data sources

The data for this research were sourced from the 2018 China Elderly Health Impact Factors Tracking Survey (CLHLS), organized by the Health Aging and Development Research Center of Peking University. This survey targets the elderly population across 23 Chinese provinces, cities, and autonomous regions, with a random selection of approximately half of the counties and cities, ensuring broad representativeness. The study focused on individuals aged 60 and above who participated in the life satisfaction survey and had complete data on key variables, including demographic factors, socio-economic factors, health status, and behavioral habits. The original CLHLS dataset comprised 15,874 cases; however, 10,964 cases were excluded due to missing values for key variables, resulting in a final sample of 4,910.

Variable selection and definition

Dependent Variable Life satisfaction among the elderly, the dependent variable in this study, is based on responses to the survey question, “How do you feel about your current life?” The responses were categorized into five levels: “very good,” “good,” “average,” “not good,” and “very bad.” Due to the low proportions of “not good” (2.4%) and “very bad” (0.3%), these two categories were combined into “life dissatisfaction,” while “very good” and “good” were merged into “life satisfaction.”

Independent Variables The independent variables include demographic factors such as gender, age, marital status, region (urban vs. rural), educational background, and living arrangement. Socio-economic factors considered are economic level, presence of medical insurance, pension insurance, and social participation. Health indicators include self-rated health, chronic diseases, behavioral limitations, and psychological status. Finally, behavioral habits such as sleep quality, smoking status, alcohol consumption, and exercise habits were also included. These variables were selected based on their relevance to life satisfaction, as identified through literature review and theoretical considerations.

Statistical methods

Statistical analysis was performed using SPSS 26.0 software. Descriptive statistics summarized demographic and socio-economic characteristics. The Chi-square (χ²) test was employed to compare unordered categorical variables between groups, while ordered categorical variables were analyzed using the rank sum test. A binary logistic regression model was applied to identify determinants of life satisfaction among urban and rural elderly individuals. Statistical significance was set at P < 0.05; all tests were two-tailed.

Results

Life satisfaction and basic situation of elderly people in urban and rural areas

This study included 4,910 elderly people, with a life satisfaction rate of 72.5% (3,560/4,910). Life satisfaction was notably higher in urban areas (75.5%) compared to rural areas (68.0%), with this difference being statistically significant (χ2 = 33.817\chi^2 = 33.817χ2 = 33.817, P < 0.001). The urban elderly population comprised 60.1%, with a majority being female (52.8%) and a significant proportion being over 75 years old (70.2%). Differences in age, region, educational background, economic level, medical insurance, pension insurance, social activities, self-evaluation of health, chronic disease status, depression tendency, smoking status, and exercise habits were statistically significant between urban and rural areas (P < 0.05). However, no significant differences were found in gender, marital status, lifestyle, behavioral limitations, sleep quality, and alcohol consumption between urban and rural elderly (P > 0.05) (Table 1).

Table 1 Comparison of basic situation distribution of urban and rural elderly people

Single component analysis of factors impacting elderly people’s life satisfaction

Our analysis revealed significant differences in life satisfaction among elderly individuals living in urban and rural areas, including age, lifestyle, residential location, economic status, self-rated health, behavioral constraints, depressive tendencies, and sleep quality (P < 0.05). Notably, exercise status was identified as a unique factor influencing life satisfaction among urban elderly, with those engaged in regular exercise reporting higher satisfaction (χ2 = 11.667\chi^2 = 11.667χ2 = 11.667, P = 0.001). For rural elderly, marital status and smoking status emerged as unique factors affecting life satisfaction; those without a spouse exhibited higher life satisfaction compared to those with a spouse (χ2 = 4.078\chi^2 = 4.078χ2 = 4.078, P = 0.043), while smokers had lower life satisfaction than non-smokers (χ2 = 5.070\chi^2 = 5.070χ2 = 5.070, P = 0.024). Variables such as gender, educational background, medical insurance, pension insurance, social activities, chronic disease status, and alcohol consumption did not show significant differences in life satisfaction between urban and rural elderly (P > 0.05) (Table 2).

Table 2 Single factor analysis of influencing factors on life satisfaction of elderly people in urban and rural areas

Multivariate analysis of variables affecting senior citizens’ life satisfaction

Binary logistic regression analysis, using life satisfaction (satisfaction = 1, dissatisfaction = 0) as the dependent variable, highlighted significant factors for urban and rural elderly. For urban elderly, those aged 76 to 90 with good self-evaluation of health had higher life satisfaction. Conversely, those residing in central and western regions, not living with family, having average or poor economic standards, and displaying depressive tendencies had lower life satisfaction (Table 3). Among rural elderly, those aged 75 or above, without a spouse, and with good self-rated health reported higher life satisfaction. In contrast, those living in central areas, not living with family, having poor economic standards, prone to depression, and smoking exhibited lower life satisfaction (Table 4).

Table 3 Binary logistic regression analysis of influencing factors on life satisfaction of urban elderly people

Table 4 Binary logistic regression analysis of influencing factors on life satisfaction of elderlypeople in rural areas

Recent studies support these findings, indicating similar patterns in life satisfaction among elderly populations. For instance, a 2022 study by Zhang et al. found that exercise and social support significantly impact life satisfaction in urban elderly populations [10] (Zhang L. et al., 2022). Similarly, Li et al. (2023) highlighted the role of marital status and smoking on life satisfaction in rural elderly communities [11] (Li, Y., et al., 2023).

Discussion

Numerous problems in the social, economic, welfare, and healthcare systems arise as people age. It is acknowledged that life satisfaction is a good measure of life quality [7]. The financial, medical, and economic spheres are crucial for promoting the growth of good aging. Furthermore, prioritizing social involvement, mobility, health education, and living environments is essential. These metrics impact the development of healthy aging in various locations and the degree of life satisfaction among older adults [8].

Our study adds to the existing literature by providing new insights into the urban-rural disparity in life satisfaction among elderly individuals in China. While previous research, such as Sørensen’s study on EU member states, found higher life satisfaction in rural areas than urban ones [12], our study reveals the opposite trend in China [14]. This discrepancy underscores the importance of contextualizing findings within national and regional settings. The results show that urban elderly individuals report higher life satisfaction than their rural counterparts, consistent with studies conducted in developed nations [13,14,15,16,17]. This could be attributed to better access to healthcare, social services, and economic resources in urban areas, which may not be as readily available in rural regions [18,19,20].

Our findings also align with recent research highlighting the role of socioeconomic factors in life satisfaction. For instance, Zhang et al. (2022) emphasize the significant impact of exercise and social support on urban elderly populations [21]. Similarly, Li et al. (2023) discuss how marital status and smoking affect life satisfaction in rural areas [22]. These studies corroborate our findings that economic level and self-rated health are pivotal in determining life satisfaction.

The increased life satisfaction with higher economic status is particularly pronounced in rural areas. Elderly individuals with better economic conditions report significantly higher life satisfaction, although the marginal impact is smaller for those already in relatively better economic conditions [23, 24]. This finding highlights the critical role of economic resources in enhancing life satisfaction, especially in rural settings where economic disparities are more pronounced.

Our study significantly advances the understanding of urban-rural differences in life satisfaction among elderly populations in China. Previous research has examined individual factors, but this study integrates multiple socioeconomic and health-related variables to provide a comprehensive view. A large-scale dataset and advanced statistical methods such as binary logistic regression allow for a more robust analysis. This research contributes new insights into how location-specific factors—such as access to healthcare and economic conditions—affect life satisfaction differently in urban versus rural areas. Moreover, the study’s findings highlight the need for targeted interventions to improve economic conditions and healthcare access in rural areas, which policymakers can use to reduce disparities.

Moreover, our study identifies the impact of psychological factors, such as depression, on life satisfaction. Depression is a common issue among the elderly and is closely related to both physical health and overall well-being [24, 25]. This underscores the need for targeted mental health interventions to improve life satisfaction among older adults.

The study’s limitations include the subjective nature of life satisfaction assessments and the potential methodological constraints of the CLHLS-2018 questionnaire. Future research should address these limitations and explore additional factors influencing life satisfaction.

Given the limitations of the Disengagement Theory and Activity Theory highlighted in our study, we recommend that future research on life satisfaction among the elderly explore alternative theoretical frameworks. One emerging framework is the “Life Enhancement and Positivity” (LEP) model, which encompasses three axes: life-deep, life-wide, and life-long. This framework can provide a comprehensive understanding of the factors influencing life satisfaction.

For instance, the variables examined in our study, including socioeconomic status, health behaviors, and social support, can be categorized under the “life-wide” axis of LEP. This classification emphasizes the interconnectedness of these variables within broader life contexts, facilitating a deeper understanding of their collective impact on life satisfaction. Future studies could leverage the LEP framework to investigate how these factors operate across different environments systematically. By doing so, researchers can identify targeted interventions to enhance the quality of life for older adults in diverse settings.

Conclusion

This study highlights significant disparities in life satisfaction between urban and rural elderly populations in China, emphasizing the profound impact of socioeconomic factors and health status. Unlike previous research, this study integrates a comprehensive analysis of multiple variables—including health behaviors, economic conditions, and demographic factors—using advanced statistical techniques such as binary logistic regression. Our findings reveal that urban elderly individuals generally experience higher life satisfaction than their rural counterparts, largely influenced by differences in access to healthcare and economic resources. This research advances our understanding of the specific factors driving these disparities and introduces a new approach to examining life satisfaction through a nuanced, location-specific lens. Policymakers and healthcare professionals can leverage these insights to develop targeted interventions that address the distinct needs of elderly populations in urban and rural settings. Reducing these disparities, mainly through improving economic conditions and healthcare access in rural areas, can foster more equitable life satisfaction across regions. This study lays the groundwork for future research and policy development to enhance the well-being of China’s senior population, particularly through innovative methodological approaches.