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Original research
Subjective social status, health and well-being among older adults in China and South Korea: a cross-sectional analysis
  1. Junwei Yan1,
  2. Yanjie Wang2,
  3. En Yang3,4,
  4. Jing Wang1,
  5. Benyan Lv5,
  6. Yan Cao6,
  7. Shangfeng Tang3,4
  1. 1 School of Nursing, Sanquan College of Xinxiang Medical University, Henan, China
  2. 2 School of International Education, Xinxiang Medical University, Henan, China
  3. 3 School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China
  4. 4 Department of Education, Research Center for Rural Health Service, Key Research Institute of Humanities & Social Sciences of Hubei Provincial, Hubei, China
  5. 5 School of Management, Xinxiang Medical University, Xinxiang, Henan, China
  6. 6 School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China
  1. Correspondence to Yan Cao; caoyan1216{at}163.com; Shangfeng Tang; sftang2018{at}hust.edu.cn

Abstract

Introduction Social status, which encompasses various psychosocial dimensions, such as income, education and social relationships, can have a significant impact on physical and mental health outcomes. The study aims to explore the association among subjective social status, health and well-being among individuals aged 55 years and older in China and South Korea.

Participants Sample population included individuals aged 55 years and older: China (n=1779) and South Korea (n=421).

Outcome measures Outcome measures included self-reported health status and well-being which were assessed by life satisfaction and general happiness.

Results The percentage of participants who reported a ‘very good’ health condition was higher in South Korea (14.5%) than in China (11.0%). The percentage of participants who reported feeling very satisfied (14.7%) with their life was lower in South Korea (11.8%). In China, 6.7% of the respondents reported their health as ‘very bad’ (rating 5), while in South Korea, this percentage was higher at 18.1%. Regression analysis revealed an inverse association among higher social status and poorer health, lower life satisfaction and lower happiness levels. For example, individuals who placed themselves in the highest social status category had 0.26 times lower odds (95% CI=0.13 to 0.55) of reporting poorer self-rated health status than those in the lowest category. Similarly, compared with individuals who place themselves in the lowest social status category, those who place themselves in the highest social status category have 0.03 times lower odds of reporting lower life satisfaction (95% CI=0.02 to 0.07).

Conclusion Overall, the results highlight a significant association among social status, subjective health, life satisfaction and general happiness in both the countries. Health policymakers should identify effective strategies to promote healthy ageing and reduce disparities in health and well-being outcomes among older adults from different social backgrounds.

  • PUBLIC HEALTH
  • Quality of Life
  • Old age psychiatry

Data availability statement

Data are available in a public, open access repository. Data source: https://www.eassda.org/index.php https://www.eassda.org/index.php.

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Strengths and limitations of this study

  • The present study provides insights into the relationship among social status, self-rated health, life satisfaction and general happiness.

  • We discussed the potential mechanisms through which social status influences health outcomes.

  • The study relies on self-reported measures, introducing potential response biases and subjective perceptions.

  • We used single-item measures for subjective social status, which may oversimplify the construct.

Introduction

Subjective social status (SSS) is a measure that reflects an individual’s perception of their place in the hierarchical structure of society.1 One’s perception of social status can be influenced by various psychosocial factors such as financial well-being, living condition, job satisfaction, educational achievements, cultural background and social connections. Research in health and social sciences has shown that social status plays a key role in individual’s physical and mental health outcomes, well-being and even mortality.2 Results of a systematic review and meta-analysis showed that lower social support status can significantly increase the odds of developing cardiovascular disease, hypertension, diabetes and dyslipidaemia.3 In older adults, lower SSS has been shown to be associated with functional decline.4 5 Individual social status is therefore frequently used as a reliable predictor for various outcomes related to health and health-related behaviours that can be of interest to clinicians and health policymakers.6

Individuals in lower socioeconomic status tend to experience poorer health conditions compared with those who have a higher socioeconomic standing.7 Some potential mechanisms behind this could be that individuals with lower social status may live in chronically deprived and unhealthy conditions or face more adversities such as financial constraints, inequality or discrimination in daily living which can lead to negative physical and mental health consequences.8–10 Additionally, individuals who have limited access to health-promoting resources, such as healthcare and healthy food and dietary habit, adequate time for relaxation, physical exercise, sleep and socialisation, may also experience worsening health outcomes.11–13 Previous research has focused the relationship between SSS and cognitive functioning in older adults, highlighting how individuals’ perceptions of their social status can influence their cognitive abilities and decline.14 Several studies have investigated the impact of SSS on mental health outcomes, such as depression and anxiety, among older populations.15 16 Moreover, SSS has been explored in relation to physical health outcomes in older adults. Some studies have also examined its association with chronic conditions, functional decline and mortality, emphasising the role of social status perceptions in shaping individuals’ overall health and well-being.3 4

Research shows that the health and well-being of older populations are increasingly becoming a concern in developed and transition economies in East Asia, including China and South Korea.17–19 Population ageing is associated with various epidemiological, economic and social challenges that are of particular concern for healthcare systems. For instance, age-based prejudice is common in many societies where policymakers often fail to pay adequate attention to the psychosocial needs of the older adults.20 Advanced age is associated with various physical and mental challenges such as functional decline and higher dependence on care which can have significant bearing on one’s socioeconomic condition. Older individuals may also think that their social status has decreased as feel that they are no longer as valued by society, or that they are not as productive or useful as they once were, which can lead to feelings of worthlessness.21 In certain settings, they may face discrimination in the workplace or in other areas of life because of their age can lead to feelings of being marginalised or excluded from society.22 Altogether, these experiences can negatively impact the psychosocial status of older adults and create feeling of lower social status. However, the relationship among SSS, health and life satisfaction outcomes among older populations has not been explored for East Asian countries. More research is needed in East Asian countries to understand how social status, health and well-being outcomes are connected among older people, as there is currently limited knowledge on this subject. This study therefore aims to fill this gap by examining the relationship among social status, health and well-being outcomes among older adults in China and South Korea, two of the largest and most rapidly ageing populations in the region. Understanding the relationship among SSS, health and well-being among older adults is crucial for developing effective policies and interventions to improve their overall quality of life, and therefore the findings of the present study can prove beneficial for healthy ageing programmes in these countries.

Methods

Data source

Data for this study were obtained from the East Asian Social Survey (EASS), 23 Cross-National Survey Data Sets: Families in East Asia, 2016–2018. Field work for the surveys took place between June 2018 and December 2018 in China, and between June 2018 and October 2018 in South Korea. To collect survey data, face-to-face interviews were conducted by trained interviewers. East Asian social survey is a research project aimed at studying the lives of people in East Asia. The countries surveyed include China, Japan, South Korea, and Taiwan. The study seeks to examine issues such as education, employment, income distribution, health status, well-being and family life among others. Thus, the EASS survey provides valuable insights into the social and economic conditions prevailing in East Asian societies.

Variables

The outcome variables included subjective health status and well-being. SSS, socioeconomic status and social support status are commonly used qualitative indicators of general well-being in social sciences and health research. While there may be overlaps among these concepts, each captures different aspects of social experiences and their impact on health outcomes. SSS refers to an individual’s perception of their own social standing, while socioeconomic status reflects their social and economic position. Understanding these constructs in relation to SSS provides a broader context for its significance in health research. The one-item measure of subjective health rating is commonly used in population surveys for its reliability and sensitivity to clinical health outcomes.24 The answer choices for this question were as follows: very good/1, 2, 3 and 4; very bad/5. Subjective health, a complex construct, is assessed using various tools, with life satisfaction25 and general happiness26 being commonly utilised measures. The answer choices for life satisfaction were as follows: very satisfied 1, 2, 3 and 4; very dissatisfied/5, and for general happiness were as follows: very happy/1, 2, 3 and 4; very unhappy/5. The main explanatory variable was SSS which was assessed by the variable: top bottom self-placement. The scores for this item ranged from lowest/01, 02, 03, 04, 05, 06, 07, 08, 09 to highest/10.27

Selection of explanatory variables was facilitated by a PUBMED search using the following search strategy: (social status[Title/Abstract] OR social class[Title/Abstract] OR socioeconomic status[Title/Abstract] OR subjective social status[Title/Abstract]) AND (elderly[Title/Abstract] OR older adults[Title/Abstract] OR geriatric[Title/Abstract]) AND (health[Title/Abstract] OR wellbeing[Title/Abstract] OR well being[Title/Abstract] OR well-being[Title/Abstract]) AND (relationship[Title/Abstract] OR association[Title/Abstract]). Based on the literature review, the following variables were included in the analysis: Sex (Female and Male), Age Groups (15–24, 25–34, 35–44, 45–54, 55–64, 65–74 and 74+), Marital Status (Married, Widowed, Divorced, Separated, Never Married and Cohabiting), Religious Groups (No Religion, Christian, Buddhism and Other Religions), Education (No Formal Qualification, Elementary, Junior High, High School, Junior College, University and Graduate School), Employment Type (Employee, Self-Employed and Unemployed) and Number of Household Members.

Analysis

Data analyses were performed using Stata V.16.1. The percentage distribution of the sociodemographic characteristics, SSS, health status, life satisfaction and general happiness was presented separately for the two countries. Country-level differences for these variables were measured using χ2 tests. The distribution of the outcome variables by SSS scores was shown using bar charts. Next, we used ordinal logistic regression methods to measure the associations between the sociodemographic and the outcome variables. Ordinal logistic regression method was selected given the ordered nature of the three outcome variables, and Brant’s tests were used to make sure that the models met the proportional odds assumption. For each outcome variable, four separate regression models were run: one for the pooled sample and one for each of the countries. The results were presented as ORs with 95% CIs. All statistical tests were two-tailed and a p<0.05 was considered statistically significant for all analyses.

Patient and public involvement

None.

Results

Descriptive analysis

Table 1 presents the sociodemographic characteristics of the participants.

Table 1

Sample characteristics (n=1779)

Results indicate that the percentage of participants who rated their SSS as lowest (1) was similar in China (9.8%) and South Korea (8.9%). Conversely, the percentage of participants who rated their SSS as highest (10) was higher in South Korea (1.4%) than in China (0.5%). The differences in SSS between the countries were statistically significant.

The percentage of participants who reported a ‘very good’ health condition was higher in South Korea (14.5%) than in China (11.0%). Similarly, the percentage of participants who reported feeling ‘very satisfied’ with their life was higher in China (14.7%) than in South Korea (11.8%). Likewise, the percentage of participants who reported feeling ‘very happy‘ with their life was higher in China (20.1%) than in South Korea (12.8%). The differences in subjective health, life satisfaction and general happiness ratings between the countries were statistically significant (p<0.05).

Figure 1

Distribution of subjective health, happiness and life satisfaction categories by subjective social status. Figure 1 illustrates that the percentage of reporting ‘very good’ health status was generally higher among the higher social status categories, and lower among the lower social status categories. The percentage of reporting ‘very satisfied’ was relatively higher among the higher social status categories, while that of reporting ‘very dissatisfied’ was relatively lower among the higher social status categories. Similarly, the percentage of reporting ‘very happy’ was generally higher among the higher social status categories, and that of reporting ‘very unhappy’ was also lower among the higher social status categories.

Regression analysis

Table 2 presents the ORs of reporting bad health status by the sociodemographic variables. The odds of reporting poorer health status were 1.88 times higher (95% CI=1.61 to 2.19) in South Korea compared with China. Compared with individuals who place themselves in the lowest (1) social status category, those who placed themselves in higher categories had lower odds of reporting poorer self-rated health status. For example, individuals who placed themselves in category 10 had 0.26 times lower odds (95% CI=0.13 to 0.55) of reporting poorer health status than those in category 1.

Table 2

ORs of reporting lower level of health status by the sociodemographic variables

Men have 0.90 times lower odds (95% CI=0.82 to 0.98) of reporting poorer health status than women. Compared with the age group of 55–64 years, the odds of reporting poorer health status were 4.83 times higher (95% CI=3.74 to 6.24) for the 65–74 age group and 5.49 times higher (95% CI=4.11 to 7.33) for the 74+age group. Compared with the married individuals, the odds of reporting poorer health status were 1.60 times higher (95% CI=1.25 to 2.06) among the divorced and 1.31 times higher (95% CI=1.11 to 1.55) among the never married individuals. Compared with individuals with no religion, Christians had 0.78 times lower odds (95% CI=0.64 to 0.94) of reporting poorer health status. In South Korea, Christians had 0.71 times lower odds (95% CI=0.54 to 0.93) of reporting poorer health status compared with individuals with no religion.

Compared with individuals with no formal education, those with higher levels of education had lower odds of reporting poorer health status. For example, individuals with graduate school education had 0.32 times lower odds (95% CI=0.24 to 0.43) of reporting poorer health status than those with no formal qualifications. Compared with employees, the odds of reporting poorer health status were 1.44 times higher (95% CI=1.28 to 1.62) for the unemployed group. In South Korea for instance, the odds of reporting poorer health status were 1.61 times higher (95% CI=1.36 to 1.91) for the unemployed group compared with employees.

Table 3 presents the ORs of reporting lower life satisfaction by the sociodemographic variables. Compared with China, individuals in South Korea have 3.26 times higher odds of reporting lower life satisfaction (95% CI=2.78 to 3.82).

Table 3

ORs of reporting lower level of life satisfaction by the sociodemographic variables

Individuals who place themselves in lower social status categories have increased odds of reporting lower life satisfaction, with ORs decreasing with progressively higher social status categories. For instance, compared with individuals who place themselves in the highest social status category (10), those who place themselves in the lowest social status category (1) have 3.26 times increased odds of reporting lower life satisfaction (95% CI=2.78 to 3.82). Compared with women, men are 1.17 times as likely to report lower life satisfaction in the overall sample (95% CI=1.06 to 1.29). This association is significant in China (OR=1.29, 95% CI=1.13 to 1.48) only. Compared with individuals aged 55–64, those aged 65–74 have 1.54 times higher odds of reporting lower life satisfaction (95% CI=1.24 to 1.92), and those aged 74 or above have 1.38 times higher odds of reporting lower life satisfaction (95% CI=1.08 to 1.76) in the overall sample.

Compared with married individuals, those who are divorced have 2.05 times higher odds of reporting lower life satisfaction (95% CI=1.57 to 2.67), and those who are separated with intention to divorce have 3.63 times higher odds of reporting lower life satisfaction (95% CI=2.01 to 6.54) in the overall sample. Compared with individuals with no formal qualification, those with a graduate school education have 0.36 times lower odds of reporting lower life satisfaction (95% CI=0.26 to 0.49).

Table 4 presents the ORs of reporting lower levels of happiness by the sociodemographic variables. Results indicate that compared with China, individuals in South Korea have 3.95 times increased odds of reporting lower levels of happiness (95% CI=3.38 to 4.62). Social status score showed an inverse association with general happiness as well, that is, the odds of reporting lower levels of happiness decreases with higher social status categories. For example, in China, individuals who placed themselves in the highest social category had 0.03 times decreased odds (95% CI=0.01 to 0.09) of reporting lower levels of happiness compared with those who placed themselves in the lowest stratum. In terms of sex, being male was associated with increased odds of reporting lower levels of happiness in China (OR=1.26, 95% CI=1.10 to 1.43). Regarding age groups, individuals aged 65–74 and 74+had increased odds of reporting lower levels of happiness in most countries compared with those aged 55–64.

Table 4

ORs of lower levels of happiness by the sociodemographic variables

In terms of marital status, being divorced or never married was associated with increased odds of reporting lower levels of happiness in most countries. For example, in China, individuals who were divorced had 1.89 times increased odds of reporting lower levels of happiness (95% CI=1.45 to 2.45) compared with those who were married. Education was negatively associated with lower levels of happiness in most countries, with higher levels of education being associated with decreased odds of reporting lower levels of happiness. For example, in China, individuals with a graduate degree had 0.42 times decreased odds of reporting lower levels of happiness (95% CI=0.24 to 0.76) compared with those with no formal qualifications.

Overall, the results show consistent associations between SSS and happiness across the two countries. In China, higher SSS was associated with lower odds of reporting lower health status (OR=0.28, 95% CI=0.21 to 0.36) and lower life satisfaction (OR=0.19, 95% CI=0.15 to 0.24). Conversely, in South Korea, the associations were weaker or non-significant for both lower health status (OR=0.35, 95% CI=0.18 to 0.70) and lower life satisfaction (OR=0.07, 95% CI=0.03 to 0.13).

Discussion

While objective indicators of social status are important predictors of health outcomes, SSS may have a more direct link with overall physical and psychosocial well-being. A large number of studies have explored the association among objective social standing, health and quality of life outcomes in community and clinical settings.28–30 In this study, we assessed the relationship among SSS, health and well-being among individuals aged 55 years and older in China, and South Korea. SSS is conceptualised as an indicator of one’s perception of social standing in comparison with others in their society, and the findings suggest that there are significant differences in the SSS of individuals across China and South Korea. The results showed that a relatively higher percentage of participants in China and South Korea rated their SSS as lowest. Although it is hard to pinpoint the root causes behind these disparities, some possible links may be rooted to greater awareness of income inequality and social stratification in these countries.

Regression analysis revealed that there is a consistent negative association among SSS and poorer self-rated health, lower life satisfaction and lower general happiness between the countries. These findings are in line with previous studies that showed that individuals who perceive themselves to be in a lower social stratum are more likely to report poorer health.7 31 While the results of these studies are not directly comparable due to methodological heterogeneity, for example, indicator of social status or health conditions, they provide insights on underlying mechanisms through which social status is linked to health outcomes. The cross-sectional study by Xiaoyong et al in Southwest China reported that social class exerts its impact on health through its mediating role of health self-management.31 Health self-management includes behaviours, such as regular exercise, healthy eating habits and medication adherence, which are vital for optimum good health outcomes and preventing chronic diseases. Studies have shown that individuals from lower social classes are less likely to engage in poor self-management behaviours such as smoking, drug abuse and inadequate exercise than those from higher social classes.32–34 Another study by Jian et al based on Chinese General Social Survey found that lifestyle indeed mediates the relationship between socioeconomic status and health.7

The findings on the inverse association among social status, life satisfaction and general happiness are also consistent with previous studies.35–37 A large cross-sectional study in China reported that social capital is significantly associated with life satisfaction, with the association being particularly stronger among participant who were married/cohabiting and were 65 years of old or higher.38 The relationship between social status and well-being is complex and multifaceted that can be influenced by various material and psychosocial factors. One possible explanation is that those who perceive themselves as being socially disadvantaged may also lack access to healthcare or other resources that are necessary for maintaining good health. Additionally, those who feel that they occupy a low rank on the social ladder experience stress due to the pressure of trying to climb higher. It is worth noting that the associations between social status and the three outcome variables are stronger for general happiness and life satisfaction compared with health. This may be due to the fact that health is a more objective measure compared with happiness and life satisfaction, which are more subjective and influenced by individual perceptions and expectations.

It is important to note that social status can be greatly impacted by social cohesion, networks and support systems. The changing social values and non-traditional family structures such as smaller families and higher rates of divorce may impact the availability of familial and social support and caregiving for older adults. Studies have shown that social support is a major determinant of health status and positive lifestyle behaviours among older adults due to higher prevalence of non-communicable chronic diseases.39–41 Additionally, the feeling of belongingness in a community may provide greater protection against stressors related to poverty or low socioeconomic conditions. Rapid economic growth, health systems reform and social changes in recent decades have led to significant shifts in social structures and values in East Asian countries, which may have profound implications for the health and well-being of the population. As life expectancy continues to rise in the region, there is a growing need to understand the factors that contribute to healthy ageing and to identify effective strategies to promote the health and well-being of older adults.

The findings of this study demonstrate the important role of subjective perceptions and feelings in influencing objective health outcomes. While our study focused on examining these associations, it is crucial to situate our findings within the broader context of key theories that explain the mechanisms underlying these relationships. One such theory is the social determinants of health, which emphasises the impact of social and economic factors on health outcomes.41–43 Social determinants, including income, education, employment and social support, shape individuals’ subjective perceptions and experiences, which, in turn, influence their health status.9 Integrating the concept of social determinants of health into our study highlights the broader structural factors that contribute to the observed associations between subjective experiences and objective health outcomes. Furthermore, theories related to social inclusion and social capital provide valuable insights into the ways social relationships and community resources influence health. Social inclusion theory emphasises the importance of social networks, social support and community cohesion in promoting well-being and positive health outcomes.

While SSS is a valuable tool for studying the relationship between health and well-being, it does have its limitations. First, the measure is self-reported which can be influenced by personal biases and perceptions. Additionally, the single-item measures may not capture the full complexity and nuances of the construct, potentially resulting in a loss of important information. Therefore, researchers should be cautious in interpreting findings solely based on SSS measures and consider incorporating other objective measures as well. Future research should aim to use multiple measures of social status and incorporate other relevant factors such as social support and more objective measures of health and well-being to gain a more comprehensive understanding of the complex relationship between social determinants and health during ageing. Another important limitation of the data is the small sample size and cross-sectional nature of the surveys which reduce the power of generalisability and causality of the findings, respectively.

Conclusion

In summary, our study highlights the importance of social status for the health and well-being of older individuals. The associations among social self-placement, self-rated health, life satisfaction and general happiness provide valuable insights into the potential impact of SSS on these outcomes. However, it is important to note that our study’s cross-sectional design limits our ability to establish causality or draw definitive practice and policy implications. Caution should be exercised when extrapolating findings from cross-sectional data to larger contexts. Therefore, it is essential to emphasise the need for further research, particularly longitudinal studies, to better understand the temporal and causal relationships among social self-placement, health and well-being outcomes. Longitudinal evidence would provide a more comprehensive understanding of the complex interplay between social status and these outcomes over time, including potential bidirectional relationships and cumulative effects. Future studies should employ longitudinal designs, incorporating multiple time points and assessing changes in SSS, health measures and well-being outcomes. This would strengthen the evidence base and inform targeted interventions and policies.

Supplemental material

Data availability statement

Data are available in a public, open access repository. Data source: https://www.eassda.org/index.php https://www.eassda.org/index.php.

Ethics statements

Patient consent for publication

Ethics approval

This study used secondary data that were available in the public domain, and no institutional approval was therefore required to contact the secondary analysis.

References

Footnotes

  • Contributors JY: conceptualisation, data curation and software; YW: data curation and software; EY: validation, review and editing; JW: formal analysis, review and editing; BL: formal analysis and review; YC: conceptualisation; ST: conceptualisation, writing and software; all authors have read and agreed to the published version of the manuscript.

  • Funding This work was funded by the National Key R&D Program of China (grant 2022YFE0133000),the National Natural Science Foundation of China (grant 72374079, 72004073,71804159), the Chinese Ministry of Education of Humanities and Social Science project (grant 20YJC630134), the Soft Science Project of Henan Provincial Science and Technology Department (grant 222400410262).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.