1. Background
Nowadays, people all around the world are experiencing increasing longevity and the total number of people aged 60 and above in the world is expected to increase from 900 million in 2015, to 2 billion in 2050. At the same time, China’s aging population is moving much faster than other developing countries [
1]. By the end of 2020, the number of elderly people aged 60 and above in mainland China was 264 million, accounting for 18.7% of the total population. Since 2000, the proportion of the elderly population has increased by 8.4% [
2]. It is predicted that by 2050, China’s population above 60 years of age may be reach 498 million [
3]. With the marked decline in fertility, the increase in average life expectancy is leading to a rapid aging of the global population.
Human life extension will bring many benefits, but it relies heavily on the health of the elderly [
4]. With the deepening of aging, more and more attention has been paid to the elderly’s health. Previous studies have discussed the difference between urban and rural residents’ health, however, there was no consensus on the issue. Fogelholm et al. [
5] reported that the urban elderly had better physical health than the rural elderly, and most of the differences could be explained by educational background, physical activity, and smoking. Anderson et al. [
6] used the 2013 County Health Rankings data to evaluate the differences between the rural and urban residents, and found that rural residents were more likely to have poorer health outcomes. They found that a variety of factors attributed to the differences, including the limitations in infrastructure, socioeconomic differences, insurance coverage deficiencies, and higher rates of traffic accidents. K.V. Smith and N. Goldman [
7] used the Mexican Health and Aging Study to study the linkages of socioeconomic status (education, income, and wealth) and health, and found individuals with higher socioeconomic status were more likely to report better health than their lower counterparts in the urban areas.
The self-assessed health (SAH) was first proposed by Suchman et al. in 1958. They thought that SAH could comprehensively reflect the subjective feelings of the human body and objective physical functions, thereby obtaining a personal health status [
8]. SAH is a subjective measure that integrates the biological, psychological, and social functions of the individual, and is also considered to be a sensitive measure of the overall health of the individual [
9]. For example, Shadbolt et al. [
10] found that SAH of the elderly aged 60 and above was valid, reliable, and responsive to change as a predictor of survival of advanced cancer. Jose et al. [
11] thought that the SAH had been widely accepted as a reliable measure of overall health, since the concept of SAH was introduced in the early 20th century, meaning that many studies had proved the validity of SAH. Stina et al. [
12] found that factors, such as diet quality, physical activity, alcohol consumption, smoking, and sleep duration influenced SAH. The empirical studies on the health and SAH of the elderly were carried out earlier, and the results had laid the foundation for the later in-depth study of health problems.
Because of the absence of the urban–rural division in foreign countries, there are few comparative studies on the health status of the elderly between urban and rural areas. However, due to China’s urban–rural dual structure, and the differences in the economic development between the urban and rural areas, as well as factors such as the living environment, the health difference between the urban and rural elderly is becoming increasingly serious in China [
13,
14]. For China, it is a hot research topic to discuss health issues, according to the urban and rural attributes of the elderly. Thus far, there have been many studies on the influencing factors of the elderly’s health in China, which have involved population characteristics, economic status, social capital, family support, living style, and life care; the results have provided inspiration and references for our research. For example, Zeng et al. [
15] used data from the 2011 China National Survey of Aging Health and Longevity (CLHLS), and found that the rural elderly population reported better physical health than the urban elderly, and the urban elderly reported better mental health than the rural elderly. Li et al. [
16] also used CLHLS data and found that there was a significant difference in the elderly’s health between urban and rural areas. Ren et al. [
17] used 2010–2012 CHARLS data, and found income was a significant impact on the elderly’s health, and it was a greater impact on the rural elderly than the urban elderly. The urban–rural dual structure is an important influencing factor of the elderly’s health.
In terms of research methods, most studies that have focused on SAH of the urban and rural elderly and its influencing factors have done so through multiple regression methods; however, the method could not quantitatively explain the contribution of the differences between the two groups. Therefore, to further explore the factors leading to the difference in SAH between the urban and rural elderly, it is necessary to use decomposition technology. Interestingly, however, we know very little about the underlying causes of health disparity of the elderly by Fairlie decomposition. Should the dualistic urban–rural economy structure be viewed as a disparity that has important externalities, such as education, age, or job? Tao et al. [
13] used Fairlie decomposition analysis, and found that 51.29% of the urban–rural disparity in the elderly population’s health could be explained by observable factors, and 48.61% by regional characteristics of the elderly’s residence. However, Tao et al. did not include the economic status in their analysis, and did not to mention the contribution of economic status to the urban–rural disparity. In addition, Xie et al. [
18] used the Oaxaca decomposition and Fairlie decomposition to analyze the factors that affect the differences in health among three regions in China, but they only focused on the region disparity and ignored the differences in the urban and rural areas. Kan et al. [
19] investigated the disparity and factors of SAH between male and female elderly people (aged 65 and above) by the Fairlie decomposition, and found that the SAH of the male elderly was better than that of the female elderly. Although there are several previous studies on the SAH disparity, we know very little about the underlying causes of these differences in terms of dualistic urban–rural economy structure.
Therefore, this study aimed to decompose the disparities in SAH between the rural and urban elderly in China into its contributory factors. This study may contribute to the literature on health of the elderly in China, and more importantly, the results also can provide reference for narrowing the health differences between urban and rural elderly.
4. Discussion
As far as we know, this study was the first large-scale comparative study to examine the SAH disparity, specifically focusing on the elderly (aged 60 and above) in China, the country with the largest population of elderly. This paper provided new empirical evidence on the health outcomes between rural and urban elderly. In addition, we used Fairlie decomposition to describe the contribution of each factor of urban–rural differences in SAH status of the elderly.
Our research revealed that there were significant differences in SAH between the urban and rural elderly. The proportion of good SAH of elderly was significantly lower in the urban areas (19.99%) than in the rural areas (24.01%). The results were similar to the study in the U.S. conducted by Anderson et al. [
6], which reported rural residents were more likely to report poorer health outcomes compared with the urban residents. This might be because the urban elderly lived in cities with better health-care services, providing a buffer against health risks, which was conducive to their SAH [
29]. Moreover, it might be related to the poor health cognition and poor working environment of the rural elderly [
30].
We found that drinking and physical activities were significant factors in elderly with good SAH, but not with bad health (
Table 3). The elderly with bad health would be more likely to stop drinking than the elderly with good SAH, due to health selectivity [
15]. This finding was different from some studies [
31], which showed there was no association between SAH and drinking In line with other studies [
32,
33], the elderly who engaged in regular physical activity were healthier than those who did not.
Our logit regression results (
Table 4) showed that there were some major differences in factors associated with SAH in the rural and urban elderly. Firstly, there was a stronger association between SAH and sleeping time of the urban elderly (OR = 3.347 of 4–8 h; OR = 3.337 of above 8 h) than the rural elderly (OR = 1.630 of 4–8 h; OR = 2.293 of above 8 h). The rural elderly were more likely to have sleep disturbances, due to poor living conditions and less opportunity to receive health guidance [
34,
35,
36]. Secondly, smoking was significant only in the urban elderly. Compared with the rural elderly, the urban elderly generally had a higher constant pension in China, and, thus, had a stronger purchasing power for smoking [
37]. Social activity was also significant, only in the urban elderly. This might be due to the retirement of the urban elderly. The urban elderly are not accustomed to life after retirement, which might cause them to feel lonely, useless, and other problematic emotions. On the other hand, most of the rural elderly generally did not retire in China, and their social activities usually did not change. Thirdly, region and assets were associated with SAH, only in the rural elderly. Region and assets represented economic status, and a higher economic status could improve living conditions and healthcare [
38]. Generally, the urban elderly had better living conditions and better medical insurance than the rural elderly.
By Fairlie decomposition (
Table 5), we found that drinking (11.45%), region (−33.92%), and assets quantiles (73.50%) were the factors associated with urban–rural disparities, which indicated that drinking and economic status (region and assets) increased disparities between the rural and urban elderly. These were important findings, in order to address the overall research questions. In addition, it should be pointed out that some factors, such as smoking and drinking, were important factors associated with bad SAH and good SAH by single factor analysis (
Table 3); however, only drinking had a contribution to the urban–rural SAH disparity. This was found because the Fairlie decomposition could calculate the contribution of the factors to the urban–rural SAH disparities by multiple regressions between the rural and urban elderly.
Based on the urban–rural SAH disparities, our results have strong policy implications. Firstly, as for drinking, we suggest that the government should strengthen smoking education programs, to promote the healthy lifestyle of the elderly. Secondly, as for the region, we need to pay attention to the design of a well-functioning regional layout [
39], and the middle and western regions are proposed to be tilted in the government budget for the elderly. Thirdly, as for assets, the health assistance program for poverty alleviation should be strengthened, for example, by promoting free medical examinations for the poor elderly, strengthening financial support for public health, improving the health function of medical insurance, and so on [
40]. At the same time, differences in SAH between the rural and urban elderly in China were not only found in differences in health determinants, but also perceived and actual social discrimination. However, reducing drinking, narrowing the region gap, and strengthening the health assistance program for poverty alleviation may not be sufficient. Indeed, only richer rural and urban elderly have more opportunities to enjoy a healthy life and receive better healthcare.