Background
Urban-rural disparity in health has been shown to vary across time and place [
1,
2]. Historically, urban areas have had higher rates of infectious disease and mortality at the early stages of industrialization due to poor sanitation, hazardous working environments, and high population density—leading to a so-called urban mortality “penalty” [
3]. However, today’s urban areas usually have lower rates of mortality compared with rural areas due to improvements in infrastructure, better public health and medical systems, and overall advances in socioeconomic development [
4‐
7]. These macro-level and institutional factors, along with a number of individual-level factors such as socioeconomic status [
8], lifestyle and nutrition [
9], and social networks [
10], have been attributed to urban-rural disparity in mortality.
In contemporary China, mortality has been documented to be significantly lower in urban areas than in rural areas. According to the National Bureau of Statistics of China (NBSC), death rates at all ages have been lower for urban residents than for rural residents in the last four censuses [
11‐
14]. Several studies based on national survey data have also showed excessive mortality among rural older adults for deaths among all causes [
8,
15‐
19]. Other localized studies have further shown urban-rural disparity in colorectal cancer mortality and dementia-free life expectancy [
20,
21]. In the last two decades, however, residents in urban areas have been shown to exhibit higher rates of physical inactivity, unhealthy eating, obesity, and hypertension than residents in rural areas [
22‐
24].
Studies have further shown that improvements in healthcare services, socioeconomic resources, and infrastructure (e.g., transportation and safe drinking-water) in urban areas may partly explain the urban-rural disparity in mortality in contemporary China [
4,
5,
8,
15,
25]. Although China has witnessed a rapid urbanization since the 1990s [
26], the urban-rural disparity is still persistent in the healthcare system, pension system, and ultimately in health outcomes and mortality [
7,
8,
18,
19]. Thus, identifying factors contributing to the mortality disparity between urban and rural older adults could have important implications for China to reduce the “health inequality” and to achieve good health and well-being for all in Goal 3 and reduced inequalities in Goal 10 of the Sustainability Development Goals (SDGs) set by the United Nations [
27].
A notable limitation of the existing research is that although many studies have documented urban-rural disparity in mortality, most of them have not systematically examined which factors are the primary contributors to such mortality disparity [
8,
17]. One exception is a study by Zimmer et al. that examined the link between neighborhood and individual socioeconomic characteristic and mortality among adults aged 50+ in China [
8]. However, this analysis did not take into account other factors, such as social support, health behaviors, and baseline health status—which have been shown to influence risk of mortality among older adults in China, nor it examined the disparity by age group and gender [
17]. Another limitation of the existing literature is that most studies have not focused on the factors associated with urban-rural disparity in mortality at the oldest-old ages and by gender. It is unclear what kind of individual-level factors are dominants in causing the urban-rural mortality disparity, and which process may underlie the urban-rural disparity in mortality in China at older ages, especially at the oldest-old ages.
Numerous frameworks have been applied to examine factors associated with health disparities (including urban-rural health disparity), of which the biopsychosocial (BPS) model of health is one of the most commonly used and probably the most appropriate framework in examining factors associated with health disparity [
28]. The framework classifies factors associated with health/mortality disparities into biological factors, psychological factors, and social and ecological/environmental/contextual factors. Under this framework, two most widely recognized theories emerged. The cultural and behavioral theory suggests that differences in behaviors such as smoking, drinking, diet, and physical activities and differences in cultural norms that enhance or suppress such behaviors are the root causes of health disparity. The materialism and structuralism theory argues that it is disparities in socioeconomic environment such as income, wealth, power, opportunities, social capital, and institutions that lead to differences in health outcomes [
29,
30].
Along with this line of the materialism and structuralism theory, three hypotheses are relevant in explaining whether differences in socioeconomic resources continues to lead to health/mortality disparities at older ages: the cumulative dis/advantage theory, the age-as-leveler theory, and the persistent inequality theory [
31‐
35]. The cumulative dis/advantage argument suggests that differences in individual-level status and resources produce large and increasing disparities in health in later life. Alternatively, the age-as-leveler theory suggests that health/mortality disparities are largest in mid-life and largely diminish with advancing age—often attributable to mortality selection. The persistent inequality hypothesis argues that health disparities remain largely unchanged over the life course. All these three hypotheses have empirical support.
Guided by the PBS framework and aforementioned theories, the purpose of this study is threefold. First, it aims to examine urban-rural disparity in mortality at young-old (aged 65–79) and oldest-old (aged 80+) ages by gender in mainland China. Second, it aims to examine whether and to what extent socioeconomic conditions, family/social support, health behaviors, and baseline health status contribute to urban-rural disparity in mortality. Third, it aims to assess whether the associations differ by age group and by gender. The implications of the results are discussed in the context of population aging and geographical differences in mortality at older ages.
Results
Table
1 presents the weighted distributions of the study variables. Overall, the demographic profiles of urban and rural older adults were similar. The proportion of respondents who died over the 2002–2014 period was relatively lower among urban older adults than that among rural older adults. Compared to the rural sample, urban older adults had much higher a socioeconomic status (SES) and were more likely to be married; however, they had less close proximity to their children compared rural older adults. Urban older adults were more likely to engage in leisure activities and had less IADL and cognitive impairments than their rural counterparts. However, older adults in urban areas had lower ADL function and higher rates of chronic disease than older adults in rural areas.
Table 1
Weighted Distributions of the Study Sample, CLHLS, 2002–2014
Total sample # | 28,235 | 17,170 | 11,046 | Family/Social Support (continued) | | | |
| | | | First talking-to-person when needed | | | |
Death in 2002–2014a | 31.8 | 33.4 | 28.5*** | Spouse | 49.5 | 48.0 | 52.9*** |
Urban-rural residence | | | | Child/relative | 25.0 | 25.3 | 24.3*** |
Rural | 32.0 | 100.0 | – | Friend | 22.6 | 23.7 | 20.0*** |
Urban | 68.0 | – | 100.0 | Social worker/housekeeper | 0.6 | 0.4 | 0.9*** |
Demographic Background | | | | Nobody | 2.4 | 2.4 | 1.9*** |
Mean Age | 71.9 | 72.0 | 71.7*** | Health Behaviors | | | |
Sex | | | | Level of leisure activity | | | |
Women | 50.4 | 50.2 | 50.9 | Low | 8.7 | 9.4 | 7.1*** |
Men | 49.6 | 49.8 | 49.1 | Intermediate | 51.2 | 54.2 | 44.5*** |
Ethnicity | | | | High | 40.2 | 36.4 | 48.4*** |
Non-Han | 6.9 | 7.8 | 4.8*** | Currently smoking | | | |
Han | 93.1 | 92.2 | 95.2*** | No | 72.8 | 72.4 | 73.7 |
Socioeconomic Factors | | | | Yes | 27.2 | 27.6 | 26.3 |
Years of schooling | | | | Ever engaged in physical labor | | | |
0 | 46.5 | 52.1 | 34.6*** | No | 15.6 | 8.9 | 29.9*** |
1–6 | 38.3 | 38.2 | 38.4*** | Yes | 84.4 | 91.1 | 70.1*** |
7+ | 15.2 | 9.7 | 27.0*** | Health Conditions | | | |
Economic independence | | | | IADL disabled | | | |
No | 47.9 | 55.3 | 32.2*** | No | 68.8 | 67.5 | 71.5*** |
Yes | 52.1 | 44.7 | 67.8*** | Yes | 31.2 | 32.5 | 28.5*** |
White-collar occupation | | | | ADL disabled | | | |
No | 87.0 | 92.7 | 74.7*** | No | 93.8 | 94.3 | 92.8** |
Yes | 13.0 | 7.3 | 25.3*** | Yes | 6.2 | 5.7 | 7.2** |
Family economic condition | | | | Cognitively impaired | | | |
Not good | 84.3 | 85.9 | 81.0*** | No | 88.0 | 86.7 | 91.0*** |
Good | 15.7 | 14.1 | 19.0*** | Yes | 12.0 | 13.3 | 9.0*** |
Got adequate access to healthcare | | | | Has 1+ chronic disease | | | |
No | 7.7 | 9.1 | 4.7*** | No | 42.1 | 65.4 | 35.0*** |
Yes | 92.3 | 90.9 | 95.3*** | Yes | 57.9 | 54.6 | 65.0*** |
Family/Social Support | | | | Survey Year | | | |
Currently married | | | | 2002 | 48.0 | 48.1 | 47.9*** |
No | 34.8 | 35.6 | 33.0* | 2005 | 18.0 | 15.8 | 22.6*** |
Yes | 65.2 | 64.4 | 67.0* | 2008 | 24.1 | 23.3 | 25.7*** |
Close proximity to children | | | | 2011 | 9.9 | 12.8 | 3.8*** |
No | 15.7 | 12.0 | 23.5*** | | | | |
Yes | 84.3 | 88.0 | 76.5*** | | | | |
Table
2 presents the adjusted hazard ratios (HR) of mortality for urban versus rural older adults. Model I shows that urban older adults had about 11% lower risks of mortality (HR = 0.89;
p < 0.01) than rural older adults after including demographic background and survey year. However, we found no urban-rural difference in mortality after including socioeconomic factors in Model II. Inclusion of family/social support (HR = 0.89;
p < 0.01), health behaviors (HR = 0.91;
p < 0.01), and health-related factors (HR = 0.90;
p < 0.01) had a limited influence on the mortality differential between urban and rural older adults. Even when all three sets of factors were included in Model VI, urban older adults still had significantly lower risk of mortality (HR = 0.92;
p < 0.05) than rural older adults—suggesting that these factors had limited power in explaining the urban-rural difference in mortality. Finally, there was no significant difference in mortality when all factors were included in Model VII.
Table 2
Adjusted Hazard Ratios of Mortality for Urban-Rural Residence, CLHLS 2002–2014
Urban (rural) | 0.89** | 0.97 | 0.89** | 0.91** | 0.90** | 0.92* | 0.96 |
Demographic Background |
Age | 1.10*** | 1.09*** | 1.09*** | 1.09*** | 1.08*** | 1.07*** | 1.07*** |
Male | 1.31*** | 1.45*** | 1.37*** | 1.30*** | 1.45*** | 1.45*** | 1.51*** |
Han (non-Han) | 0.93 | 0.94 | 0.94 | 0.91 | 0.87* | 0.88* | 0.89* |
Socioeconomic Factors |
1–6 years of schooling (0) | | 0.93+ | | | | | 0.98 |
7+ years of schooling (0) | | 0.82** | | | | | 0.90+ |
Economic independence (no) | | 0.75*** | | | | | 0.81*** |
White collar occupation (no) | | 1.11* | | | | | 1.07 |
Good family economic condition (no) | | 0.97 | | | | | 1.01 |
Adequate access to healthcare (no) | | 0.80*** | | | | | 0.91+ |
Family/Social Support |
Currently married (no) | | | 0.88** | | | 0.91+ | 0.94 |
Close proximity to children (no) | | | 1.02 | | | 1.01 | 1.00 |
Primary support, child/relative (spouse) | | | 1.05 | | | 1.05 | 1.04 |
Primary support, friend (spouse) | | | 0.98 | | | 1.01 | 0.99 |
Primary support, other (spouse) | | | 1.40+ | | | 1.14 | 1.15 |
Primary support, nobody (spouse) | | | 1.45*** | | | 1.23** | 1.22** |
Health Behaviors |
Leisure activity level, intermediate (low) | | | | 0.59*** | | 0.71*** | 0.73*** |
Leisure activity level, high (low) | | | | 0.47*** | | 0.61*** | 0.64*** |
Currently smoking (no) | | | | 1.07 | | 1.08+ | 1.08+ |
Ever engaged in physical labor (no) | | | | 0.98 | | 1.00 | 0.96 |
Health Conditions |
IADL disabled (no) | | | | | 1.40*** | 1.33*** | 1.30*** |
ADL disabled (no) | | | | | 1.52*** | 1.39*** | 1.39*** |
Cognitively impaired (no) | | | | | 1.36*** | 1.26*** | 1.25*** |
Has 1+ chronic disease (no) | | | | | 1.09* | 1.10** | 1.10** |
Survey Year |
Wave 2005 (2002) | 0.82*** | 0.84*** | 0.83*** | 0.81*** | 0.84*** | 0.83*** | 0.84*** |
Wave 2008 (2002) | 0.60*** | 0.61*** | 0.60*** | 0.58*** | 0.60*** | 0.60*** | 0.60*** |
Wave 2011 (2002) | 0.30*** | 0.31*** | 0.30*** | 0.29*** | 0.31*** | 0.31*** | 0.31*** |
Df | 7 | 13 | 13 | 11 | 11 | 21 | 27 |
Wald test χ2 value | 2423.6*** | 2436/3*** | 2522.4*** | 2921.7*** | 3031.3*** | 3377.1*** | 3388.6*** |
Wald test χ2 value fort models vs. Model I a | – | 95.1*** | 54.1*** | 258.9*** | 349.1*** | 508.6*** | 538.4*** |
Wald test χ2 value for Model VII vs. models b | 538.4*** | 433.5*** | 477.8*** | 274.6*** | 159.8*** | 34.7*** | – |
Table
3 demonstrates that the urban-rural disparity in mortality is generally consistent by age group and gender. Likewise, we found that the urban-rural mortality differential was largely eliminated after including socioeconomic factors but not family/social support, health behaviors, and health-related factors. However, we found that urban older adults still had significantly lower risk of mortality at the oldest-old ages (HR = 0.93;
p < .05) compared with rural older adults despite inclusion of all factors.
Table 3
Adjusted Hazard Ratios of Mortality for Urban-Rural Residence by Age Group and Sex, CLHLS 2002–2014
Ages 65–79 | 0.88** | 0.97 | 0.88** | 0.90* | 0.90* | 0.92+ | 0.96 |
Ages 80+ | 0.91** | 0.96 | 0.90** | 0.93* | 0.90** | 0.91** | 0.93* |
Women | 0.91* | 0.98 | 0.91* | 0.91+ | 0.92+ | 0.92+ | 0.98 |
Men | 0.87** | 0.96 | 0.88** | 0.91+ | 0.88** | 0.92+ | 0.96 |
Discussion
This study provides new evidence to understand the urban-rural disparity in mortality among older adults in China. Using longitudinal data from the largest nationally representative study of older adults in the contemporary China, we found that older adults living in urban areas had lower risk of mortality compared with older adults living in rural areas, even at the oldest-old ages, and regardless of gender. We further found that the urban advantage in mortality was largely explained by better socioeconomic factors in urban areas for both women and men and for both young-old and oldest-old adults. On the other hand, we found that factors such as family/social support, health behaviors, and health-related conditions had a limited role in explaining the urban-rural disparity in mortality. These findings support the argument that urban areas in China generally provide greater access to healthcare services and more socioeconomic resources than rural areas [
8,
15,
17,
19]. Thus, the positive association we found between living in urban areas and reduced mortality risks was attenuated once individual-level socioeconomic factors were taken into account. This finding is consistent with a previous study conducted in Beijing, which showed that the urban advantage in older-age mortality was either largely reduced or eliminated once individual demographics and socioeconomic characteristics were taken into account [
19]. Our findings build on this research and provide new evidence at a national level to highlight the importance of socioeconomic factors in influencing mortality at older ages in a country, such as China.
Overall, our findings of significant urban-rural disparity in mortality at older or oldest ages and between women and men support the persistent inequality theory that the urban-rural disparity in mortality is large and largely unchanged in later life [
33,
34]. We found no or little evidence to support the age-as-leveler theory (i.e., diminishing urban-rural disparity in mortality at older and oldest-ages). There is evidence to show that urban-rural difference in mortality seems greater at oldest-old ages as compared to that at young-old ages, which may support the accumulative dis/advantage theory. The more important finding of this study is that urban-rural disparity in mortality at older ages disappeared after including individual socioeconomic factors. This provides empirical support to the materialism and structuralism theory; that is, it is the disparities in socioeconomic resources between urban and rural older adults rather than the disparities in their behaviors that are dominant factors in causing differences in health outcomes [
29,
30]. However, there is also some evidence that urban-rural mortality disparity cannot be entirely explained by socioeconomic resources or other factors used in the study at oldest-old ages, which may be because of selective mortality or unobserved heterogeneity. More research is clearly warranted to further disentangle the causes.
Our findings are consistent with previous studies that have shown a mortality advantage among urban older adults relative to rural older adults in China [
5,
7,
8,
16]. With few exceptions, however, most of these studies did not distinguish urban-rural mortality differences by age or gender; and none of these studies explored the factors contributing to the differences in mortality by age or gender [
5,
7,
16].
The possible reasons for these underlying associations are fourfold. First, older adults with higher SES tend to have a better quality of life in terms of better housing, better neighborhood/residential environments, and better access to facilities for exercise and healthcare [
8,
45]. Second, older adults with higher SES have greater access to services that allow them to get timely medical treatment when needed and to benefit from other social services that provide assistance in times of need and/or adversity [
46]. Because rural older adults possess a lower standing in society because of their limited resources, they are often socially disadvantaged, marginalized, and even discriminated against, which in turn, create barriers for them to get needed assistance to prevent premature mortality. Third, older adults with higher SES tend to have a better psychological well-being. For example, older adults with greater economic resources are less likely to suffer from financial strains and associated stressors [
47]. Relatedly, older adults with higher SES also tend to be more optimistic and have positive attitudes, views, expectations, and perceptions toward their future; and likewise, have more opportunities for involvement in social activities [
40]. Finally, people with higher SES are more likely to be aware of and afford healthier diets and lifestyles [
45,
48]. All these advantages/privileges possessed by socioeconomic resourceful older adults could offset the contextual or institutional disadvantages (such as living in a rural area) to their health.
A key strength of the present study is the use of a large national sample, which included more than 28,000 older adults, to examine urban-rural disparity in mortality over a 12-year period. The large sample and repeated longitudinal measures used in this study allowed us to obtain robust results of the potential factors associated with urban-rural differences in mortality in men and women and across age groups [
8]. Another strength of this study is that the data come from a nationally representative survey of older adults in China, a transitional non-Western society, where there are established institutions in place for socioeconomic development, health care, and pension systems. Such institutional differences could result in unintended disparities in the resources available to individuals for their health promotion. A third uniqueness of the present study is the comparison of urban-rural mortality disparity between men and women and between adults at ages 65–79 and ages 80+. As noted earlier, we build upon previous studies by providing new evidence of urban-rural disparity among key subpopulations in a developing country such as China.
Policy implications
Our findings have important implications for public policy and planning. First, in contemporary China, rural older adults face significant social disadvantages compared to their urban counterparts. Older adults in rural areas have much less access to healthcare and lower pension benefits because of the urban-rural dual development system. Therefore, reforms to improve these institutional systems and formulate favorable policies that increase rural older adults’ access/benefits to public goods such as healthcare and pensions are clearly warranted [
4,
7]. Relatedly, rural development should be highlighted in the national socioeconomic strategic plans. Intervention programs focusing on socioeconomic development and poverty reduction in rural areas should be prioritized. These macro-perspective policies are indeed the necessary foundation to narrow the urban-rural differences in healthcare and social services, improved housing and infrastructure, and overall better economic conditions. To have equal access to healthcare and adequate social security is human right that is consistent with SDG guidelines. Thus, only when there is greater equality/equity between urban and rural residents in their access to healthcare and pension systems can rural residents achieve similarly low risks of mortality as urban residents.
Second, the State (or the local rural communities) should develop free or affordable healthcare or social services delivered though home visits to rural older adults. With limited resources, rural older adults often cannot afford or access these services, which in turn, contribute to worsening health and increased mortality risks. According to the CLHLS, 53 and 12% of rural older adults attributed their reasons of not seeking medical treatment when in needed to limited financial resources and difficulties in access healthcare, respectively, compared with 46 and 5% among urban older adults. Such home- and community-based services could indirectly improve their access to resources and help rural older adults receive regular health check-ups and prevention services that would otherwise not be affordable or accessible. These programs also could improve older adults’ knowledge about the benefits of a healthy lifestyle via dissemination of health literacy information. Indeed, there is existing evidence to show that favorable healthcare policies and programs may mitigate health disparity in later life [
49].
Limitations
Several limitations should be taken into account when interpreting our findings. First, our study only used information on current residence and did not consider possible changes in urban-rural residence during an individual’s life course. Studies have shown an association between urban and rural exposure during his/her lifetime and health-related outcomes at later ages [
4,
39,
50]. Relatedly, although our classification of urban-rural residence is consistent with official definitions used by the Chinese government, we were not able to determine whether possible rural-to-urban residence change was permanent (obtained an urban
hukou status) or temporary (living in urban areas with rural
hukou). Alternatively, with rapid urbanization and in situ urbanization, the residential status of many rural inhabitants may have changed even if their current residence remained in the same location, village, or township [
51]. Therefore, we recognize that urban-rural residence may be dynamic over one’s lifetime and incorporating such information may provide additional insights into urban-rural mortality differentials [
4].
Second, we also recognize that the urban-rural health disparity is also directly or indirectly influenced by many biological, environmental, and/or other contextual factors as embedded in the BPS framework. Unfortunately, a lack of these measures in the CLHLS prohibited us from examining them in the current study. With regard to contextual factors, urban areas often have better infrastructure (e.g., transportation and safe drinking-water) than rural areas—particularly in China with the implementation of the urban-rural dual development system starting in the 1950s—which certainly contributes to excessive mortality in rural areas [
8]. We also did not consider increasing crowdedness and polluted environments—thus, urban residents may have greater exposure to environments with relatively greater health-risks than their rural peers [
52]. In addition to further including potential biological factors in the analyses, it is important for future research to consider the environmental, socio-political, and other contextual factors characterizing the living environments of older adults in urban and rural areas [
17,
22].
Third, we acknowledge that health/mortality selection may affect our findings. This selection process has two aspects. On the one hand, the rural population may exhibit a loss of “healthier people” due to their out-migration to urban areas. According to some research, older adults who migrated from rural-to-urban areas when they were young have lower risk of mortality compared with rural older adults who did not migrate [
4]. Because these migrants are generally healthier and more socioeconomically advantaged than rural non-migrant counterparts [
4,
53], it is possible that such migration could make the current urban population healthier because of the commensurate changes in population composition [
4]. On the other hand, older adults in rural China likely encountered greater adversities in their life—and consequently had higher rates of mortality in earlier life—which may result in healthier older adults as their rural frail peers were eliminated from the cohort [
4,
54].
Finally, as noted earlier, the CLHLS did not include nine minority provinces where urbanization, socioeconomic development, and healthcare coverage are relatively low in comparison with the other 22 sampled provinces. Consequently, mortality rates at older ages in these nine provinces are higher than those of the 22 sampled provinces [
55]. However, it is unclear whether the urban-rural difference in these non-included provinces is more or less pronounced compared with the sampled provinces. Fortunately, because the overall proportion of the population from these non-sampled provinces is relatively small (around 10%), we remain confident about the robustness of our findings. Nevertheless, we encourage additional studies to include these nine provinces to further verify our findings.
Conclusions
By using five waves of a nationally representative survey with large sample of nearly 30,000 older adults in China, we investigated the role of socioeconomic conditions, family/social support, health behaviors, and baseline health status in contributing to urban-rural differences in mortality at older ages. Our study found that differences in socioeconomic factors between urban and rural areas were the primary causes for the urban-rural disparity in mortality at older ages, and that other factors such as family/social support, health behaviors, and health-related factors had a limited influence on the urban-rural mortality disparity. These conclusions were generally consistent by age group and gender. Our findings have important implications for possibly intervention programs aiming to close the urban-rural mortality gap at older ages.
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