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- Original article Educational disparities in labor market participation among middle-aged Koreans with chronic diseases: evidence from the Korean Longitudinal Study of Elderly Employment
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Seung Yeon Jeon1
, Dong-Wook Lee2, Jaesung Choi3, Mo-Yeol Kang1,* -
Annals of Occupational and Environmental Medicine [Epub ahead of print]
DOI: https://doi.org/10.35371/aoem.2025.37.e19
Published online: July 17, 2025
1Department of Occupational and Environmental Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
2Department of Occupational and Environmental Medicine, Inha University Hospital, Inha University College of Medicine, Incheon, Korea
3Department of Economics, Sungkyunkwan University, Seoul, Korea
- *Corresponding author: Mo-Yeol Kang Department of Occupational and Environmental Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Korea E-mail: snaptoon@naver.com
• Received: May 22, 2025 • Revised: July 3, 2025 • Accepted: July 9, 2025
© 2025 Korean Society of Occupational & Environmental Medicine
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract
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Background As South Korea experiences rapid population aging, preventing early retirement has become a critical concern. Ill health contributes to early retirement, and educational level moderates this relationship. Although well-studied in Europe, it remains less explored in Northeast Asia, where labor markets and educational attainment differ significantly. This study investigated the moderating role of education in the relationship between chronic diseases and labor force non-participation in South Korea, considering disease severity, type, and employment status.
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Methods Using data from the Korean Longitudinal Study of Elderly Employment, this study analyzed 5,758 individuals born between 1964 and 1976. Chronic diseases were categorized by severity and type. Labor force participation and retirement from lifetime primary occupation were measured. Education was categorized as low (≤high school) or high (≥college). Logistic regression analyses were conducted, adjusting for sociodemographic and lifestyle covariates, with stratification by education level, employment status, severity, and disease characteristics.
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Results Chronic diseases were significantly associated with labor market non-participation and early retirement, with stronger associations among individuals with lower educational levels. Educational disparities were particularly evident for severe and psychiatric disorders. Among wage workers, those with lower education were more likely to exit the labor market due to chronic diseases, whereas those with higher education generally maintained employment, except in cases of musculoskeletal diseases. Low-educated individuals with chronic diseases were also more likely to retire early from their lifetime primary occupations.
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Conclusions Education moderates the relationship between chronic diseases and labor non-participation, with greater disparities in severe or psychiatric illnesses and among wage workers. Low-educated workers are more vulnerable to early retirement due to ill health, highlighting the need for targeted policy interventions to support this group and prevent early exit from the workforce.
BACKGROUND
As populations age, many countries are seeking ways to maintain a productive workforce. For instance, in Europe, governments are attempting to raise the retirement age through pension reforms.1 In South Korea, one of the fastest-aging countries, there has been considerable discussion on preventing early retirement. This issue is particularly pressing as South Korea’s second baby boomer generation, born between 1964 and 1976, which comprises 18.6% of the population, approaches retirement age.2
Early retirement is influenced by both push and pull factors.3 Push factors are negative influences that drive workers out of the labor market involuntarily, such as poor working conditions and caregiving responsibilities. In contrast, pull factors encourage early retirement by offering retirement benefits like generous social security and financial incentives. Among push factors, poor health—including chronic diseases—is gaining attention, as workers with chronic illnesses are more likely to leave paid employment prematurely, often due to push factors rather than pull factors. Chronic diseases contribute to early retirement by reducing individual’s physical and functional capacity, leading to limitations in work ability and increased absenteeism. These health-related limitations can diminish productivity and increase the likelihood of exiting labor market.4-6
Individuals with lower education levels are more vulnerable to early retirement than those with higher educational attainment.7-9 This is partly because individuals with less education tend to have a higher prevalence of chronic diseases and face greater difficulty working. As a result, education plays a key role in moderating the impact of ill health on early retirement.10 Studies consistently show that workers with chronic diseases tend to leave employment earlier than their healthier counterparts, and this trend is even more pronounced among those with lower education levels. The moderating role of education in the relationship between ill health and early retirement is of particular significance as educational attainment is largely determined early in life and is strongly influenced by parental socioeconomic status, making it a structural factor that reflects broader social inequities. That individuals may be forced into early retirement due to educational disadvantage underscores systematic unfairness, and highlights which populations are likely to be most economically vulnerable to old-age poverty in the context of rising chronic disease prevalence and population aging.7-9
While many studies have explored the moderating effect of education in European contexts,7-9 there is limited research on this topic in Northeast Asian, particularly South Korea. South Korea presents an interesting study setting given its exceptionally high college enrollment rates, rapid population aging, and unique labor market, which includes a significant proportion of self-employed individuals.11 Therefore, this study aimed to investigate the moderating role of education in the relationship between ill health and labor force non-participation in South Korea. Additionally, we examined whether variations exist based on the types and severity of chronic diseases, as well as employment status, to better understand the factors that made less-educated individuals more vulnerable to early retirement.
METHODS
This study used data from the Korean Longitudinal Study of Elderly Employment (KLoEE), a nationally representative panel survey conducted by the Korea Employment Information Service.12 The target population comprised the second baby boomer generation, defined as individuals born between 1964 and 1976. Participants were selected through multistage probability sampling, stratified by geographic location. The survey collected sociodemographic, employment, and health-related data through face-to-face interviews. A total of 9,358 individuals participated in the 2022 KLoEE survey, and after excluding those with missing or incomplete information, 5,758 participants were included in this analysis. Information on lifetime primary occupation was available only in the 2021 survey, so this data was used for that aspect of the study. Due to the short duration of the panel study (2021–2022), a cross-sectional analysis was conducted.
Chronic disease
Participants who reported having at least one chronic disease were classified as having chronic diseases. These diseases were categorized based on two criteria. The first criterion was categorization according to the severity. Chronic diseases such as heart disease, kidney disease, and cancer were classified as “severe chronic disease,” as these are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea.13 Although “rare and intractable diseases” are also designated as “severe and intractable diseases” by the Ministry of Health and Welfare of Korea, they were excluded from the analysis because the KLoEE does not include “rare and intractable diseases” except for kidney disease. The rest of the diseases were classified as “non-severe chronic disease.” The second criterion was classification by types of diseases. Chronic diseases were broadly divided into five categories—cardiovascular diseases (CVD), musculoskeletal, psychiatric, gastrointestinal, and “other.” CVD-related chronic diseases included diabetes, hypertension, hyperlipidemia, and cerebrocardiovascular diseases. Musculoskeletal diseases included degenerative arthritis, rheumatoid arthritis, osteoporosis, and disc disease. Psychiatric disorders included depression, anxiety, and sleep disorders. Gastrointestinal diseases included gastric ulcers, duodenal ulcers, and gastritis, while "other” chronic diseases covered conditions affecting the lungs, thyroid, and liver, characterized by their rarity and frequent management in tertiary hospital outpatient departments.
Labor market participation and wage labor participation
Participants who were wage workers, self-employed, or unpaid family workers working more than 18 hours per week were considered as participating in the labor market. Those hired by others or companies were classified as wage workers, while those who were not employed by others were classified as self-employed or family workers. This distinction was described using the term “type of employment.” In this study, labor force non-participation refers to not participating in the labor market whereas wage labor non-participation includes not only those who are not participating in the labor market but also those who are self-employed or working as unpaid family workers, meaning they are not wage workers.
Educational level
It is common to divide educational levels into three groups according to 2011 International Standard Classification of Education (ISCED-2011): low (middle school graduates or less educated), intermediate (high school graduates), and high (college graduates or more educated). However, in South Korea, where people place great value on education, more than half of the population are college graduates or more educated.14 In addition, since only 273 participants (4.74%) in the dataset had an education level of middle school or less—making meaningful comparison difficult—educational level was categorized into two groups in this study: low (high school graduates or less) and high (some college or more).
Lifetime primary occupation
The “lifetime primary occupation” was defined as the job in which an individual spent the longest period in the labor market. If multiple jobs had equal duration, the occupation with the higher income were considered the lifetime primary occupation. Participants who answered “yes” to the question, “Are you retired from the lifetime primary occupation?” were classified as “retired” from their lifetime primary occupation, whereas those who answered “no” were classified as “not retired.” The lifetime primary occupation was categorized further based on types of employment (“wage workers” or “self-employed or family workers”). Participants who answered “yes” to the question, “Are you retired from the lifetime primary occupation” and answered their lifetime primary occupations were wage workers were categorized as “retirement from wage employment.”
Covariates
Basic characteristics, including age, sex, marital status (married with spouse vs. unmarried [never married, widowed, or divorced]), household income (divided into five quintiles), and health-related lifestyle factors (smoking, exercising, and drinking), were selected as covariates based on previous studies.6,15 Household income was measured using equivalized household median disposable income. As the selection of participants was geographically randomized, the distribution according to household income was uneven.
Demographic characteristics were described and stratified by education level. Multiple logistic regression analysis was used to compare labor force non-participation and retirement from lifetime primary occupation between participants with and without chronic illnesses. Variables related to chronic illness were included in the models in the following four ways: (1) presence of any chronic diseases, (2) presence of severe chronic disease, (3) presence of non-severe chronic disease, and (4) presence of each specific type of chronic diseases. For all models, the same reference group—participants without any chronic illnesses—was used. The analyses adjusted for age, sex, marital status, household income, and health-related lifestyle factors. Stratified analyses were conducted based on the education level and types of employment. Statistical significance was determined by non-overlapping 95% confidence intervals or a two-sided p-value of less than 0.05 when assessing heterogeneity. To evaluate whether the association between predictors and labor force non-participation varied by education level, we included interaction terms between education level and each covariate in the logistic regression model. Specifically, interaction terms between education level and sex, age, socioeconomic status, smoking status, marital status, physical activity, and alcohol consumption were incorporated. The statistical significance of these interactions was assessed using p-value for interaction values. All analyses were performed using Statistical Analysis System (SAS) version 9.4 (SAS Institute Inc., Cary, NC, USA).
IRB approval was not required for this study as it utilized survey data collected by the Korea Employment Information Service with authorization from Statistics Korea.
RESULTS
According to Table 1, individuals with lower education levels had lower household income and engage in unhealthy behaviors, such as smoking, heavy drinking, and lack of exercise, compared to those with higher education. They were unemployed or retired from their lifetime primary occupation more often than people with higher education level. Among those with lower education levels, a higher percentage were self-employed or family workers in their lifetime primary occupation. Furthermore, individuals with lower education levels had chronic diseases, particularly severe chronic diseases more than those with higher levels of education.
Table 2 indicates that individuals with lower educational levels were more likely to be unemployed when they had chronic diseases, compared to their higher-educated counterparts. The risk of non-participation in the labor market varied according to the severity and type of chronic diseases. More specifically, individuals with severe chronic diseases were more likely to be unemployed than those with non-severe chronic diseases, and this phenomenon was more prominent among those with lower educational levels. Among the types of chronic diseases, psychiatric disorders showed the greatest difference by educational level, followed by “other” chronic diseases. Notably, for musculoskeletal diseases, highly educated individuals were more likely to exit the labor market than those with low education.
In Table 3, the analysis is limited to wage workers, excluding self-employed or family workers. The educational disparity in labor market participation was more evident among individuals with chronic diseases. The odds ratio of non-participation did not increase significantly among the highly educated group, regardless of the severity and type of chronic diseases, except for musculoskeletal disease. Additionally, the interaction between education level and chronic diseases was significantly related with non-participation in the labor market for chronic diseases in general, as well as for severe, gastrointestinal, and “other” chronic diseases.
As shown in Table 4, individuals with lower educational levels and chronic diseases were more likely to retire from their lifetime primary occupation. Among the highly educated group, the risk of retirement increased significantly only for non-severe, musculoskeletal, and psychiatric diseases. In contrast, the low-educated group showed an increased risk of retirement for all types of diseases, except for gastrointestinal diseases. The odds ratio was the highest for psychiatric disorders, followed by “other” chronic diseases. While this trend was more prominent for severe diseases, the odds ratio for retirement also increased significantly for non-severe diseases. The interaction between educational level and prevalence of chronic disease was statistically significant for severe and “other” chronic diseases.
Table 5 highlights the variation in the odds ratios for retirement from the lifetime primary occupation by educational background and types of employment. Among wage workers, the interaction between education level and chronic disease was significant, suggesting an educational disparity (p = 0.021). For wage workers, the odds ratio did not significantly increase with chronic diseases in the highly educated group, except for musculoskeletal and psychiatric diseases. In contrast, the low-education group showed a significant increase in the odds ratio for all types of chronic diseases, except for gastrointestinal disease.
DISCUSSION
This study examines the moderating role of education in the relationship between chronic diseases and labor market non-participation, as well as the relationship between chronic diseases and retirement from one’s lifetime primary occupation. The results show that individuals with lower education levels tend to participate less in the labor market and are more likely to retire from their lifetime primary occupations if they have a chronic diseases. This disparity was particularly prominent among wage workers.
Previous studies suggest that the educational disparity in labor force non-participation due to ill health is driven by the fact that individuals with higher education tend to be healthier. Higher education is associated with healthier lifestyles and better socioeconomic advantages, which promote better health outcomes.16,17 Our findings align with this, as individuals with lower education levels had poorer health, worse lifestyle habits, and lower socioeconomic status than those with higher education. However, even after adjusting for lifestyle factors and household income, and stratifying by the type and severity of chronic diseases, highly educated individuals were still more likely to remain in the labor market and less likely to retire from their lifetime primary occupation compared to their lower-educated counterparts. This trend was consistent even when stratification was performed according to the type of job (blue-collar, white-collar and pink-collar), indicating that individuals with lower educational level were more likely to leave their lifetime primary occupation in the presence of chronic disease regardless of the type of their jobs (Tables 2–5, Supplementary Tables 1–3).
The educational disparity was more pronounced for psychiatric diseases, which require more intensive medical care than other types of chronic diseases. In addition, when stratification was performed according to the severity of chronic diseases, educational disparity was more remarkable in severe chronic diseases. In summary, the difference in education level was greater in chronic diseases that required more medical treatment, which made it more difficult to manage illness while trying to work.
This tendency was also observed in the retirement pattern from primary lifetime occupations. Retirement from lifetime primary occupation was particularly evident in severe and “other” diseases, which showed statistically significant difference by educational level. This suggests that individuals with lower educated levels not only participate less in the labor market but also retire earlier due to chronic illness. Since lifetime primary occupation refers to the highest-earning job, this early retirement could result in significant economic hardship for low-educated individuals with chronic diseases. These findings highlight the importance of considering education as a structural determinant in policy efforts to reduce labor market non-participation due to ill health, as educational disadvantage which are deeply rooted in early-life socioeconomic conditions can lead to cumulative vulnerabilities including early retirement and economic insecurity in later life.
One possible explanation for this educational disparity is that individuals with lower education levels may have difficulty managing chronic diseases, which could lead to disease exacerbation and ultimately to labor market non-participation or early retirement. Another possible explanation is that low-educated individuals have limited access to jobs that accommodate their health needs. Previous studies have shown that jobs held by low-educated individuals often offer less control over their jobs, reduced flexibility, and poorer psychosocial working conditions compared to those held by higher-educated individuals.18-21 The fact that the difference is particularly pronounced among wage workers, who typically have less control over their work environment, supports this theory. In contrast, self-employed or family workers, who have greater autonomy and control over their work environment, may be better able to manage chronic conditions.
Despite its contributions, this study has several limitations. First, because of its cross-sectional nature, it could not be fully confirmed whether education played a moderating role in the causal relationship between non-participation in the labor force or early retirement from lifetime primary occupation and ill health. Second, other covariates that might influence the relationship between health conditions and early retirement, but were not considered in this study, could affect the results. Third, the data used in the present study were self-reported. This methodological approach may have led to more subjective responses and introduced the potential for common method bias. Fourth, while the diseases classified as severe chronic diseases (cancer, heart disease, cerebrovascular disease, and kidney disease) are generally considered to be of high severity, the KLoEE did not include questions regarding disease severity. Therefore, it is possible that the actual severity of these conditions was not fully captured in the dataset. Fifth, this study stratified the analysis by lifetime primary occupation—blue-collar, white-collar, and pink-collar—and found a tendency for higher odds ratios among individuals with lower education levels. However, the limited sample size within each occupational group constrained further statistical analysis. Future research should enhance study design and sampling to allow a more detailed examination of occupational group differences. In addition, although age was included as an adjustment variable in the regression models to address potential cohort effects related to educational attainment, simple statistical adjustment may not be sufficient to fully control for the complex and cohort-specific historical experiences such as socioeconomic changes around the International Monetary Fund economic crisis. Therefore, residual confounding by age and birth cohort effects may still remain. Finally, psychosocial working conditions such as abundant social support, could not be fully captured through types of employment, which might contribute to the differences between highly educated and low-educated individuals in the workplace.
CONCLUSIONS
The results of our study show that individuals with lower education levels are less likely to participate in the labor market and are more likely to retire from their lifetime primary occupation when they have chronic diseases, especially those with severe or psychiatric conditions. This disparity may be linked to the poorer working conditions faced by low-educated individuals, such as less control over tasks, restricted work flexibility, and poorer psychosocial environments. Given their increased vulnerability to early retirement due to ill health, targeted policy interventions are needed to improve the work environments and support systems for this group.
Abbreviations
CVD
cardiovascular diseases
ISCED-2011
2011 International Standard Classification of Education
KLoEE
Korean Longitudinal Study of Elderly Employment
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Competing interests
Dong-Wook Lee and Mo-Yeol Kang contributing editors of the Annals of Occupational and Environmental Medicine, were not involved in the editorial evaluation or decision to publish this article. All remaining authors have declared no conflicts of interest.
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Author contributions
Conceptualization: Kang MY. Data curation: Lee DW. Formal analysis: Jeon SY. Validation: Kang MY. Writing - original draft: Jeon SY. Writing - review & editing: Lee DW, Choi J, Kang MY.
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Acknowledgments
The authors thank to all of the participants and working groups at Korean employment information service of Korean employment information service of Korean Longitudinal Study of Elderly Employment (KLoEE).
NOTES
SUPPLEMENTARY MATERIAL
Supplementary Table 1.
OR of retirement from blue-collar jobs by chronic disease and education level.
Supplementary Table 2.
OR of retirement from white-collar jobs by chronic disease and education level.
Supplementary Table 3.
OR of retirement from pink-collar jobs by chronic disease and education level.
Table 1.
Characteristics of the study population
| Total | Low education level | High education level | |
|---|---|---|---|
| Age (years) | |||
| 40–49 | 2,094 (36.4) | 980 (46.8) | 1,114 (53.2) |
| 50–60 | 3,664 (63.6) | 2,328 (63.5) | 1,336 (36.5) |
| Sex | |||
| Men | 2,419 (42.0) | 1,246 (51.5) | 1,173 (48.5) |
| Women | 3,339 (58.0) | 2,062 (61.8) | 1,277 (38.2) |
| Marital status | |||
| Married | 4,236 (73.6) | 2,321 (54.8) | 1,915 (45.2) |
| Unmarried, divorced, bereavement | 1,522 (26.4) | 987 (64.9) | 535 (35.2) |
| Household income | |||
| First quintile | 1,292 (22.4) | 896 (69.4) | 396 (30.7) |
| Second quintile | 1,344 (23.3) | 825 (61.4) | 519 (38.6) |
| Third quintile | 1,378 (23.9) | 790 (57.3) | 588 (42.7) |
| Fourth quintile | 1,106 (19.2) | 543 (49.1) | 563 (50.9) |
| Fifth quintile | 638 (11.1) | 254 (39.8) | 384 (60.2) |
| Smoking | |||
| Yes | 1,017 (17.7) | 604 (59.4) | 413 (40.6) |
| No | 4,741 (82.3) | 2,704 (57.0) | 2,037 (43.0) |
| Exercise | |||
| Yes | 2,837 (49.3) | 1,451 (51.3) | 1,386 (48.9) |
| No | 2,921 (50.7) | 1,857 (63.6) | 1,064 (36.4) |
| Drinking | |||
| Twice, more than twice a week | 804 (14.0) | 483 (60.1) | 321 (39.9) |
| Less than twice a week | 4,954 (86.0) | 2,825 (57.0) | 2,129 (43.0) |
| Types of employment | |||
| Wage workers | 2,838 (49.3) | 1,475 (52.0) | 1,363 (48.0) |
| Self-employed or family workers | 1,822 (31.6) | 1,145 (62.8) | 677 (37.2) |
| Unemployed | 1,098 (19.1) | 688 (62.7) | 410 (37.3) |
| Retired from lifetime primary occupation | |||
| Yes | 2,018 (35.1) | 1,169 (57.9) | 849 (42.1) |
| No | 3,740 (65.0) | 2,139 (57.2) | 1,601 (42.8) |
| Types of employment of lifetime primary occupation | |||
| Employed | 3,829 (66.5) | 2,075 (54.2) | 1,754 (45.8) |
| Non-employed | 1,929 (33.5) | 1,233 (63.9) | 696 (36.1) |
| Chronic disease | |||
| Yes | 1,680 (29.2) | 1,029 (61.3) | 651 (38.8) |
| No | 4,078 (70.8) | 2,279 (55.9) | 1,799 (44.1) |
| Severity of chronic diseasea,b | |||
| Severe | 231 (4.0) | 142 (61.5) | 89 (38.5) |
| Non-severe | 1,466 (25.5) | 900 (61.4) | 566 (38.6) |
| Types of chronic diseaseb | |||
| CVD-related | 1,199 (20.8) | 755 (63.0) | 444 (37.0) |
| Musculoskeletal | 393 (6.8) | 254 (64.6) | 139 (35.4) |
| Psychiatric | 103 (1.8) | 64 (62.1) | 39 (37.9) |
| Gastrointestinal | 186 (3.2) | 80 (43.0) | 106 (57.0) |
| Other | 283 (4.9) | 166 (58.7) | 117 (41.3) |
Values are presented as number (%).
CVD, cardiovascular disease.
a“Severity of chronic disease” and “Types of chronic disease” were assessed only among respondents who reported having a chronic disease (n = 1,680). Multiple responses were allowed for the severity and types of chronic diseases; therefore, the total count exceeded the number of individuals with chronic diseases;
bFor severity of chronic disease and types of chronic disease, the totals represent the number of individuals who answered “yes” to having a chronic disease. For all other variables, the total indicates column percentages (vertical sum), while for educational level, it indicates row percentages (horizontal sum).
Table 2.
OR of labor force non-participation by chronic disease and education level
|
Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.92 | 1.66–2.23 | 1.63 | 1.26–2.11 | 2.15 | 1.79–2.59 | 0.073 |
| Severity of chronic disease | |||||||
| Severea | 3.39 | 2.50–4.59 | 2.22 | 1.27–3.89 | 4.09 | 2.82–5.94 | 0.071 |
| Non-severe | 1.76 | 1.51–2.06 | 1.56 | 1.19–2.05 | 1.95 | 1.61–2.37 | 0.162 |
| Specific chronic disease | |||||||
| CVD-related | 1.79 | 1.51–2.13 | 1.55 | 1.14–2.11 | 1.98 | 1.61–2.44 | 0.166 |
| Musculoskeletal | 2.26 | 1.77–2.88 | 2.39 | 1.54–3.70 | 2.33 | 1.73–3.14 | 0.976 |
| Psychiatric | 8.97 | 5.69–14.13 | 5.34 | 2.48–11.50 | 13.44 | 7.29–24.78 | 0.059 |
| Gastrointestinal | 1.51 | 1.02–2.24 | 1.14 | 0.62–2.11 | 1.98 | 1.17–3.35 | 0.173 |
| Other | 2.68 | 2.04–3.53 | 1.65 | 1.02–2.66 | 3.49 | 2.48–4.91 | 0.011 |
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea.
OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease.
aNumber of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n=393), psychiatric (n=103), gastrointestinal (n=186), other (n=283).
Table 3.
OR of wage labor non-participation by chronic disease and education level
|
Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.25 | 1.11–1.40 | 1.10 | 0.91–1.32 | 1.37 | 1.18–1.60 | 0.050 |
| Severity of chronic disease | |||||||
| Severea | 1.30 | 0.99–1.71 | 0.88 | 0.56–1.38 | 1.68 | 1.17–2.42 | 0.025 |
| Non-severe | 1.25 | 1.10–1.41 | 1.12 | 0.92–1.36 | 1.35 | 1.15–1.59 | 0.107 |
| Specific chronic disease | |||||||
| CVD-related | 1.25 | 1.09–1.43 | 1.10 | 0.88–1.36 | 1.37 | 1.15–1.62 | 0.086 |
| Musculoskeletal | 1.43 | 1.15–1.77 | 1.53 | 1.07–2.19 | 1.38 | 1.05–1.81 | 0.711 |
| Psychiatric | 2.55 | 1.64–3.99 | 1.81 | 0.92–3.57 | 3.48 | 1.89–6.40 | 0.159 |
| Gastrointestinal | 1.02 | 0.76–1.38 | 0.65 | 0.42–0.99 | 2.00 | 1.23–3.27 | 0.001 |
| Other | 1.30 | 1.01–1.67 | 0.89 | 0.60–1.31 | 1.75 | 1.25–2.45 | 0.010 |
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea.
OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease.
aNumber of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n = 393), psychiatric (n = 103), gastrointestinal (n = 186), other (n = 283).
Table 4.
OR of retirement from lifetime primary occupation by chronic disease and education level
|
Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.38 | 1.22–1.56 | 1.24 | 1.02–1.51 | 1.53 | 1.31–1.79 | 0.093 |
| Severity of chronic disease | |||||||
| Severea | 1.96 | 1.48–2.58 | 1.08 | 0.68–1.72 | 2.84 | 1.98–4.07 | 0.001 |
| Non-severe | 1.31 | 1.15–1.49 | 1.25 | 1.02–1.54 | 1.40 | 1.19–1.66 | 0.388 |
| Specific chronic disease | |||||||
| CVD-related | 1.27 | 1.11–1.46 | 1.10 | 0.87–1.38 | 1.44 | 1.20–1.71 | 0.072 |
| Musculoskeletal | 1.62 | 1.31–2.02 | 1.51 | 1.05–2.17 | 1.77 | 1.35–2.33 | 0.471 |
| Psychiatric | 4.17 | 2.66–6.54 | 3.64 | 1.79–7.38 | 4.71 | 2.61–8.51 | 0.526 |
| Gastrointestinal | 1.18 | 0.86–1.62 | 1.01 | 0.65–1.57 | 1.38 | 0.86–2.19 | 0.332 |
| Other | 1.84 | 1.43–2.36 | 1.25 | 0.84–1.86 | 2.39 | 1.72–3.33 | 0.012 |
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea.
OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease.
aNumber of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n = 393), psychiatric (n = 103), gastrointestinal (n = 186), other (n = 283).
Table 5.
OR of retirement from wage employment by chronic disease and education level
|
Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.43 | 1.24–1.66 | 1.20 | 0.96–1.50 | 1.69 | 1.39-2.05 | 0.020 |
| Severity of chronic disease | |||||||
| Severea | 1,67 | 1.21–2.30 | 0.81 | 0.47–1.38 | 2.72 | 1.76–4.19 | <0.001 |
| Non-severe | 1.41 | 1.21–1.64 | 1.26 | 0.99–1.60 | 1.58 | 1.29–1.94 | 0.130 |
| Specific chronic disease | |||||||
| CVD-related | 1.33 | 1.13–1.57 | 1.05 | 0.81–1.37 | 1.61 | 1.30–2.01 | 0.013 |
| Musculoskeletal | 1.89 | 1.45–2.47 | 1.83 | 1.18–2.85 | 2.03 | 1.46–2.84 | 0.668 |
| Psychiatric | 3.48 | 2.06–5.88 | 2.19 | 1.01–4.76 | 5.32 | 2.50–11.32 | 0.092 |
| Gastrointestinal | 1.15 | 0.80–1.65 | 0.85 | 0.52–1.39 | 1.73 | 0.97–3.06 | 0.058 |
| Other | 1.65 | 1.23–2.20 | 1.13 | 0.73–1.74 | 2.28 | 1.52–3.43 | 0.017 |
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea.
OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease.
aNumber of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n = 393), psychiatric (n = 103), gastrointestinal (n = 186), other (n = 283).
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XML DownloadEducational disparities in labor market participation among middle-aged Koreans with chronic diseases: evidence from the Korean Longitudinal Study of Elderly Employment
Educational disparities in labor market participation among middle-aged Koreans with chronic diseases: evidence from the Korean Longitudinal Study of Elderly Employment
| Total | Low education level | High education level | |
|---|---|---|---|
| Age (years) | |||
| 40–49 | 2,094 (36.4) | 980 (46.8) | 1,114 (53.2) |
| 50–60 | 3,664 (63.6) | 2,328 (63.5) | 1,336 (36.5) |
| Sex | |||
| Men | 2,419 (42.0) | 1,246 (51.5) | 1,173 (48.5) |
| Women | 3,339 (58.0) | 2,062 (61.8) | 1,277 (38.2) |
| Marital status | |||
| Married | 4,236 (73.6) | 2,321 (54.8) | 1,915 (45.2) |
| Unmarried, divorced, bereavement | 1,522 (26.4) | 987 (64.9) | 535 (35.2) |
| Household income | |||
| First quintile | 1,292 (22.4) | 896 (69.4) | 396 (30.7) |
| Second quintile | 1,344 (23.3) | 825 (61.4) | 519 (38.6) |
| Third quintile | 1,378 (23.9) | 790 (57.3) | 588 (42.7) |
| Fourth quintile | 1,106 (19.2) | 543 (49.1) | 563 (50.9) |
| Fifth quintile | 638 (11.1) | 254 (39.8) | 384 (60.2) |
| Smoking | |||
| Yes | 1,017 (17.7) | 604 (59.4) | 413 (40.6) |
| No | 4,741 (82.3) | 2,704 (57.0) | 2,037 (43.0) |
| Exercise | |||
| Yes | 2,837 (49.3) | 1,451 (51.3) | 1,386 (48.9) |
| No | 2,921 (50.7) | 1,857 (63.6) | 1,064 (36.4) |
| Drinking | |||
| Twice, more than twice a week | 804 (14.0) | 483 (60.1) | 321 (39.9) |
| Less than twice a week | 4,954 (86.0) | 2,825 (57.0) | 2,129 (43.0) |
| Types of employment | |||
| Wage workers | 2,838 (49.3) | 1,475 (52.0) | 1,363 (48.0) |
| Self-employed or family workers | 1,822 (31.6) | 1,145 (62.8) | 677 (37.2) |
| Unemployed | 1,098 (19.1) | 688 (62.7) | 410 (37.3) |
| Retired from lifetime primary occupation | |||
| Yes | 2,018 (35.1) | 1,169 (57.9) | 849 (42.1) |
| No | 3,740 (65.0) | 2,139 (57.2) | 1,601 (42.8) |
| Types of employment of lifetime primary occupation | |||
| Employed | 3,829 (66.5) | 2,075 (54.2) | 1,754 (45.8) |
| Non-employed | 1,929 (33.5) | 1,233 (63.9) | 696 (36.1) |
| Chronic disease | |||
| Yes | 1,680 (29.2) | 1,029 (61.3) | 651 (38.8) |
| No | 4,078 (70.8) | 2,279 (55.9) | 1,799 (44.1) |
| Severity of chronic disease |
|||
| Severe | 231 (4.0) | 142 (61.5) | 89 (38.5) |
| Non-severe | 1,466 (25.5) | 900 (61.4) | 566 (38.6) |
| Types of chronic disease |
|||
| CVD-related | 1,199 (20.8) | 755 (63.0) | 444 (37.0) |
| Musculoskeletal | 393 (6.8) | 254 (64.6) | 139 (35.4) |
| Psychiatric | 103 (1.8) | 64 (62.1) | 39 (37.9) |
| Gastrointestinal | 186 (3.2) | 80 (43.0) | 106 (57.0) |
| Other | 283 (4.9) | 166 (58.7) | 117 (41.3) |
| Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.92 | 1.66–2.23 | 1.63 | 1.26–2.11 | 2.15 | 1.79–2.59 | 0.073 |
| Severity of chronic disease | |||||||
| Severe |
3.39 | 2.50–4.59 | 2.22 | 1.27–3.89 | 4.09 | 2.82–5.94 | 0.071 |
| Non-severe | 1.76 | 1.51–2.06 | 1.56 | 1.19–2.05 | 1.95 | 1.61–2.37 | 0.162 |
| Specific chronic disease | |||||||
| CVD-related | 1.79 | 1.51–2.13 | 1.55 | 1.14–2.11 | 1.98 | 1.61–2.44 | 0.166 |
| Musculoskeletal | 2.26 | 1.77–2.88 | 2.39 | 1.54–3.70 | 2.33 | 1.73–3.14 | 0.976 |
| Psychiatric | 8.97 | 5.69–14.13 | 5.34 | 2.48–11.50 | 13.44 | 7.29–24.78 | 0.059 |
| Gastrointestinal | 1.51 | 1.02–2.24 | 1.14 | 0.62–2.11 | 1.98 | 1.17–3.35 | 0.173 |
| Other | 2.68 | 2.04–3.53 | 1.65 | 1.02–2.66 | 3.49 | 2.48–4.91 | 0.011 |
| Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.25 | 1.11–1.40 | 1.10 | 0.91–1.32 | 1.37 | 1.18–1.60 | 0.050 |
| Severity of chronic disease | |||||||
| Severe |
1.30 | 0.99–1.71 | 0.88 | 0.56–1.38 | 1.68 | 1.17–2.42 | 0.025 |
| Non-severe | 1.25 | 1.10–1.41 | 1.12 | 0.92–1.36 | 1.35 | 1.15–1.59 | 0.107 |
| Specific chronic disease | |||||||
| CVD-related | 1.25 | 1.09–1.43 | 1.10 | 0.88–1.36 | 1.37 | 1.15–1.62 | 0.086 |
| Musculoskeletal | 1.43 | 1.15–1.77 | 1.53 | 1.07–2.19 | 1.38 | 1.05–1.81 | 0.711 |
| Psychiatric | 2.55 | 1.64–3.99 | 1.81 | 0.92–3.57 | 3.48 | 1.89–6.40 | 0.159 |
| Gastrointestinal | 1.02 | 0.76–1.38 | 0.65 | 0.42–0.99 | 2.00 | 1.23–3.27 | 0.001 |
| Other | 1.30 | 1.01–1.67 | 0.89 | 0.60–1.31 | 1.75 | 1.25–2.45 | 0.010 |
| Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.38 | 1.22–1.56 | 1.24 | 1.02–1.51 | 1.53 | 1.31–1.79 | 0.093 |
| Severity of chronic disease | |||||||
| Severe |
1.96 | 1.48–2.58 | 1.08 | 0.68–1.72 | 2.84 | 1.98–4.07 | 0.001 |
| Non-severe | 1.31 | 1.15–1.49 | 1.25 | 1.02–1.54 | 1.40 | 1.19–1.66 | 0.388 |
| Specific chronic disease | |||||||
| CVD-related | 1.27 | 1.11–1.46 | 1.10 | 0.87–1.38 | 1.44 | 1.20–1.71 | 0.072 |
| Musculoskeletal | 1.62 | 1.31–2.02 | 1.51 | 1.05–2.17 | 1.77 | 1.35–2.33 | 0.471 |
| Psychiatric | 4.17 | 2.66–6.54 | 3.64 | 1.79–7.38 | 4.71 | 2.61–8.51 | 0.526 |
| Gastrointestinal | 1.18 | 0.86–1.62 | 1.01 | 0.65–1.57 | 1.38 | 0.86–2.19 | 0.332 |
| Other | 1.84 | 1.43–2.36 | 1.25 | 0.84–1.86 | 2.39 | 1.72–3.33 | 0.012 |
| Total |
High education level |
Low education level |
p for interaction | ||||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Chronic disease | |||||||
| Yes | 1.43 | 1.24–1.66 | 1.20 | 0.96–1.50 | 1.69 | 1.39-2.05 | 0.020 |
| Severity of chronic disease | |||||||
| Severe |
1,67 | 1.21–2.30 | 0.81 | 0.47–1.38 | 2.72 | 1.76–4.19 | <0.001 |
| Non-severe | 1.41 | 1.21–1.64 | 1.26 | 0.99–1.60 | 1.58 | 1.29–1.94 | 0.130 |
| Specific chronic disease | |||||||
| CVD-related | 1.33 | 1.13–1.57 | 1.05 | 0.81–1.37 | 1.61 | 1.30–2.01 | 0.013 |
| Musculoskeletal | 1.89 | 1.45–2.47 | 1.83 | 1.18–2.85 | 2.03 | 1.46–2.84 | 0.668 |
| Psychiatric | 3.48 | 2.06–5.88 | 2.19 | 1.01–4.76 | 5.32 | 2.50–11.32 | 0.092 |
| Gastrointestinal | 1.15 | 0.80–1.65 | 0.85 | 0.52–1.39 | 1.73 | 0.97–3.06 | 0.058 |
| Other | 1.65 | 1.23–2.20 | 1.13 | 0.73–1.74 | 2.28 | 1.52–3.43 | 0.017 |
Table 1. Characteristics of the study population
Values are presented as number (%). CVD, cardiovascular disease. “Severity of chronic disease” and “Types of chronic disease” were assessed only among respondents who reported having a chronic disease (n = 1,680). Multiple responses were allowed for the severity and types of chronic diseases; therefore, the total count exceeded the number of individuals with chronic diseases; For severity of chronic disease and types of chronic disease, the totals represent the number of individuals who answered “yes” to having a chronic disease. For all other variables, the total indicates column percentages (vertical sum), while for educational level, it indicates row percentages (horizontal sum).
Table 2. OR of labor force non-participation by chronic disease and education level
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea. OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease. Number of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n=393), psychiatric (n=103), gastrointestinal (n=186), other (n=283).
Table 3. OR of wage labor non-participation by chronic disease and education level
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea. OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease. Number of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n = 393), psychiatric (n = 103), gastrointestinal (n = 186), other (n = 283).
Table 4. OR of retirement from lifetime primary occupation by chronic disease and education level
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of Korea. OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease. Number of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n = 393), psychiatric (n = 103), gastrointestinal (n = 186), other (n = 283).
Table 5. OR of retirement from wage employment by chronic disease and education level
The model was adjusted for age, sex, marital status, socioeconomic status and whether one does exercise, drinking and smoking. Severe chronic
disease is heart disease, kidney disease, and cancer, which are designated “severe and intractable diseases” by the Ministry of Health and Welfare of
Korea. OR: odds ratio; CI: confidence interval; CVD: cerebrovascular disease. Number of participants by category: chronic disease (yes: n = 1,680; no: n = 4,078), severe (n = 231), non-severe (n = 1,466), CVD-related (n = 1,199), musculoskeletal (n = 393), psychiatric (n = 103), gastrointestinal (n = 186), other (n = 283).
