Abstract
To reduce health disparities among migrant populations, it is critical to fully understand the barriers they face when accessing and utilizing healthcare services. This study uses data from a survey of 1,060 immigrants from various backgrounds to investigate the causes of unmet healthcare needs. The findings show that 298 respondents reported having unmet healthcare needs. Significant contributors to these unmet healthcare needs include country of origin, visa status, occupation, experiences of discrimination during the COVID-19 pandemic, self-assessed health status, anxiety, depression, and disability. Immigrant health disparities must be effectively addressed through policy reforms and increased budgetary allocations for migrant healthcare. Furthermore, developing educational programs and informational pamphlets to raise immigrants’ awareness of their healthcare rights is critical for empowering them to protect these rights. Furthermore, initiatives that promote integration and facilitate the exchange of information and mutual assistance between immigrants and native populations are critical for promoting social cohesion and addressing healthcare disparities.
Keywords: Immigrants, Unmet healthcare needs, Anderson model, Healthcare access
Introduction
According to the 2019 International Migration Report by DESA (UN Department of Economic and Social Affairs), while the population has grown by 11% since 2010, the number of immigrants increased by 23%, indicating that the growth of immigrants is more than twice that of the general population [1]. South Korea, located in East Asia, has a historically low immigration. However, South Korea’s rapid economic development and low birth rate have gradually boosted the influx of marriage immigrants and workers, raising the percentage of foreigners from 3.1% of the total population in 2013 to 4.9% by May 2023 [2].
Immigrants generally have less access to healthcare information than native residents, and they may encounter language barriers during medical consultations, as well as difficulties adjusting to Korea’s healthcare system, including health insurance [3, 4]. The UN’s Sustainable Development Goals (SDGs) acknowledge the link between health and migration, establishing specific targets to address inequalities faced by immigrants and viewing it as a critical issue for achieving social integration [5].
The difficulties that immigrants face in accessing healthcare services can be interpreted as unmet healthcare needs, which are useful indicators for evaluating the accessibility of healthcare systems [6, 7]. Unmet healthcare needs can be assessed by the difference between perceived and actual healthcare utilization [8, 9]. Previous research has primarily focused on perceived unmet healthcare needs, or subjective unmet healthcare [10].
Having universal health coverage, South Korea reports relatively high accessibility to healthcare services. Nonetheless, in 2021, 6.7% of the general population had unmet healthcare needs (KOSIS), with 10.6% of immigrants reporting similar experiences [11]. However, immigrants differ in terms of their country of origin, language, immigration visa status, and length of stay in the host country [12], and there has been little research into how these characteristics influence unmet healthcare needs. Furthermore, many studies on unmet healthcare needs among immigrants have used qualitative methods or small sample sizes (e.g., 112 or 465 participants), making it difficult to compare the effects of a variety of variables related to unmet healthcare needs [4, 13]. Notably, there are many studies that concentrate on specific immigrant groups, such as marriage immigrants, foreign workers, and students, making comparative research across different residency types difficult. Understanding which characteristics of immigrants are associated with unmet healthcare needs is critical for determining which subgroups of immigrants have the most limited access to healthcare. This knowledge can be used to provide social services to the most vulnerable immigrant groups. The purpose of this study was to identify differences in experiences with unmet healthcare needs based on specific backgrounds (e.g., visa type, occupation, health status) among immigrants in South Korea using a relatively large sample of 1,060 immigrants.
Conceptual Framework
Andersen’s Behavioral Model of Health Service Use is widely used to explain the factors contributing to unmet healthcare needs. Developed in 1968 to define and measure equitable access to healthcare services, the model has been revised several times and is used in various studies. The revised model from 1995 incorporates structural and contextual factors that influence healthcare utilization, shifting the emphasis from individual behavior to a broader context. The model explains healthcare utilization using three categories: predisposing factors, enabling factors, and need factors [14].
For immigrants, predisposing factors include demographic characteristics such as sex, age, marital status, country of origin, length of stay, and area of residence. Enabling factors relate to the capacity to use healthcare services, including financial and social resources, as well as healthcare accessibility. For immigrants, this may include language proficiency and discrimination. Need factors are direct reasons for using healthcare services, such as self-rated health status, chronic diseases, and stress [14, 15].
Previous research on unmet healthcare needs among immigrants found that being female and being an older immigrant are risk factors for experiencing unmet healthcare needs [16, 17]. Furthermore, those who are divorced or separated were more likely to have unmet healthcare needs, and it was discovered that the longer the duration of residence, the higher the healthcare utilization, with different patterns of utilization depending on the country of origin [18, 19]. Finally, irregular immigrants were more likely to have unmet healthcare needs than legal residents [20].
Among the enabling factors, lower income and receiving basic living assistance were associated with a higher likelihood of unmet healthcare needs [16, 18]. Furthermore, immigrants who were not enrolled in health insurance were more likely to have unmet healthcare needs than those who were enrolled [21]. Social stigma and discrimination created distrust in the healthcare system among immigrants, increasing the probability of experiencing unmet healthcare [18, 22]. Unmet healthcare needs were also reported differently across occupational groups [23]. Finally, among the need factors, individuals with depression, chronic illnesses, or stress were more likely to have unmet healthcare needs [16, 17, 19–21]. It was also discovered that those with poorer self-rated health and immigrants with disabilities were more likely to experience unmet healthcare needs [16–18].
Hypothesis
Based on the literature review, this study proposed the following hypotheses:
First, as predisposing factors, it is hypothesized that immigrants with shorter durations of residence in Korea are more likely to experience unmet healthcare needs, and that the likelihood of unmet healthcare needs differs by country of origin.
Second, as enabling factors, it is hypothesized that immigrants with lower income levels and those who have experienced discrimination are more likely to report unmet healthcare needs.
Third, as need factors, it is hypothesized that immigrants with poorer self-rated health and those with depressive symptoms are more likely to experience unmet healthcare needs.
Based on these hypotheses, the study aims to analyze the factors influencing unmet healthcare needs among immigrants using Andersen’s behavioral model of health service use. The conceptual framework of the study is presented in Fig. 1.
Fig. 1.
The conceptual framework of the study
Methods
Participants
The data used in this study come from Lee’s [24] “Survey on the Health Rights of Immigrants and the Improvement of the Medical Security System” (10.22687/KOSSDA-A1-2020-0098-V1.0). The survey was carried out by Solidarity with Immigrants and distributed by the Korea Social Science Data Archive (KOSSDA). The research team intended to recruit a sample of 1,000 participants, considering population distributions such as migrant workers, agricultural workers, ethnic Koreans from China, Korean-Chinese, refugees, students, undocumented immigrants, and others. The questionnaire was adapted into 14 languages, including Chinese, Vietnamese, and Thai, and administered through interviews by surveyors from various migrant support organizations across the country. The survey ran from July 1 to September 15, 2020, and had a total of 1,060 participants.
Ethical Considerations
This study used secondary data from Lee [24], which did not include any personally identifiable information about the participants. The study was authorized by the Research Ethics Committee of Soonchunhyang University (SCH 2024-07-024-001).
Dependent Variable
Unmet Healthcare Needs
The dependent variable, unmet healthcare needs, was defined based on responses to the following question: “While living in Korea, have you ever needed a diagnosis, tests, or treatment for physical or mental health issues but did not receive it?” A response of “yes” was interpreted as having unmet healthcare needs. This definition implies that unmet healthcare needs may arise at any time after migrating to Korea.
Independent Variable
Predisposing Factors
Gender was classified as male or female. Age was divided into three categories based on South Korea’s demographic characteristics and healthcare utilization patterns: under 45 years, 45 − 65 years, and over 65 years. Individuals under 45 years of age indicate the youth and early stages of economic activity, with generally good health and relatively low healthcare utilization. Those aged 45 to 65 years are in the midst of economic activity, necessitating chronic disease management and regular healthcare utilization. Finally, individuals aged 65 and up comprise the elderly population, which is distinguished by frail health and a high demand for healthcare services.
Marital status was determined by whether the individual was married. The regions of origin are categorized according to the consular regions established by the Ministry of Foreign Affairs [25]: Northeast Asia (China, Japan, Mongolia), Southeast Asia (Vietnam, Cambodia, Thailand, Myanmar, Indonesia), South Asia (India, Pakistan, Nepal, Bangladesh, Sri Lanka), Russia and Central Asia (Uzbekistan, Kyrgyzstan, Kazakhstan), the Middle East and North Africa (Iran, Iraq, Syria, Yemen, Egypt, Algeria, Morocco, Tunisia), Sub-Saharan Africa (Nigeria, South Africa, Liberia, Libya, Sudan, Angola, Ethiopia, Uganda, Cameroon, Kenya, Côte d’Ivoire, Democratic Republic of the Congo, Tanzania), and others (East Timor, Brazil, Azerbaijan, Ukraine, Romania). Among these, Northeast Asia, with the largest sample size, was chosen as the reference. The length of residence was divided into three categories: less than 5 years, 5 − 10 years, and more than 10 years. Visa categories included student, employment, marriage immigrant, undocumented, and refugee. Here, “refugees” were defined as asylum seekers, recognized refugees, and those granted humanitarian stay permits.
Enabling Factors
Income was divided into three categories: less than 1 million won per month, between 1 million and 2 million won, and more than 2 million won. In 2020, South Korea’s minimum living expense was 1,795,310 won [26]. Enrollment in health insurance was either yes or no. Occupation types included manufacturing, construction, agriculture and livestock, fisheries, services, others, and unemployment. Discrimination in healthcare utilization involving COVID-19 was defined as experiencing discrimination if one or more of the following questions were true: (1) I called 1339 or a public health center to inquire about COVID-19 but was unable to obtain the necessary information due to a language barrier. (2) I tried to buy masks at a pharmacy but was denied because I was a foreigner and did not have health insurance. (3) When masks were distributed to employees at my company, I did not receive one or received fewer than Koreans because I was a foreigner. (4) I was prevented from leaving the company dormitory due to the possibility of contracting COVID-19. (5) I was fired from my job due to the possibility of contracting COVID-19. (6) I was not permitted to enter stores, cafes, or restaurants due to the possibility of being infected with COVID-19.
Among these, experiences such as (4), (5), and (6) may be considered as general public health measures. However, they are likely to have been applied disproportionately to immigrants, instilling feelings of prejudice. In fact, in South Korea, migrant workers have been subjected to human rights violations, such as being barred from leaving their accommodations [27]. Chinese students studying abroad were identified as high-risk groups for infection, prompting measures such as dormitory closures [28]. Furthermore, monitoring results on immigrants’ human rights during the COVID-19 situation revealed that many immigrants saw these measures and experiences as discriminatory [29]. As a result, this study defined discrimination as having occurred if any of the aforementioned situations were met, demonstrating that socially vulnerable groups may perceive the same public health measures as discriminatory.
Need Factors
Need factors included self-rated health, depressive symptoms, disability, and chronic disease. Self-rated health was graded as very good/good/fair/bad/very bad, indicating the perceived overall health status. Severe anxiety or depression that occurred within the previous year was described as depressive anxiety. A physical or mental disability is defined as experiencing difficulties in daily activities or at work. If a person had ever been diagnosed with a chronic disease, they were considered to have it.
Analytic Method
First, descriptive statistical analyses were performed on all variables considered in the study (Table 1). Next, as a bivariate analysis, a chi-square test was used to investigate the relationship between independent variables and unmet healthcare needs. Furthermore, to identify differences between groups within an independent variable, pair-wise comparisons with the chi-square test were performed, followed by post-hoc tests with p-values adjusted with the Bonferroni method. As a result, the groups with significant differences were classified as a, b, c, and d, which are shown in Table 2.
Table 1.
The sample characteristics
| Category | N(%) | |
|---|---|---|
| Sex | Male | 522(49.25) |
| Female | 538(50.75) | |
| Age | < 45 | 813(76.70) |
| ≥ 45, < 65 | 215(20.28) | |
| ≥ 65 | 32(3.02) | |
| Region of origin | Northeast Asia | 348(32.83) |
| Southeast Asia | 434(40.94) | |
| Middle Asia | 108(10.19) | |
| Southwest Asia | 81(7.64) | |
| Middle East | 37(3.49) | |
| Africa | 43(4.06) | |
| Other | 9(0.85) | |
| Marital status | Married | 478(45.09) |
| Unmarried | 582(54.91) | |
| Length of stay | < 5 years | 587(55.38) |
| ≥ 5 years, < 10 years | 298(28.11) | |
| ≥ 10 years | 175(16.51) | |
| Visa type | Student | 95(8.98) |
| Employment | 413(39.04) | |
| Family/expatriate | 315(29.77) | |
| Refugee | 86(8.13) | |
| Unregistered | 149(14.08) | |
| Health insurance | Yes | 743(70.09) |
| No | 291(27.45) | |
| Job | Manufacturing | 418(39.43) |
| Construction | 96(9.06) | |
| Farming | 79(7.45) | |
| Fishing | 24(2.26) | |
| Service | 121(11.42) | |
| Other | 61(5.75) | |
| Not working | 228(21.51) | |
| Monthly income (1,000 KRW) | < 1,000 | 257(24.31) |
| ≥ 1,000, < 2,000 | 463(43.80) | |
| ≥ 2,000 | 337(31.89) | |
| Discrimination | Yes | 403(38.02) |
| No | 657(61.98) | |
| Self-rated health | Very good | 142(13.40) |
| Good | 358(33.77) | |
| Fair | 420(39.62) | |
| Bad | 116(10.94) | |
| Very bad | 24(2.26) | |
| Anxiety and depression | Yes | 370(34.91) |
| No | 690(65.09) | |
| Disability | Yes | 53(5.00) |
| No | 1,007(95.00) | |
| Chronic disease diagnosed | Yes | 152(14.34) |
| No | 908(85.66) | |
| Unmet healthcare needs | Yes | 298(28.22) |
| No | 758(71.78) | |
Table 2.
Unmet healthcare needs by sample characteristics
| Category | Yes | No | Chi-square (p-value) |
|
|---|---|---|---|---|
| Sex | Male | 112(21.58) | 407(78.42) | 22.21 (< 0.001***) |
| Female | 186(34.64) | 351(65.36) | ||
| Age | < 45 | 227(27.99) | 584(72.01) | 5.37(0.068) |
| ≥ 45, < 65 | 27(26.51) | 158(73.49) | ||
| ≥ 65 | 14(46.67) | 16(53.33) | ||
| Region of origin | Northeast Asia | 88(29.83)a | 207(70.17) |
54.33 (< 0.001***) |
| Southeast Asia | 118(27.25)a | 315(72.75) | ||
| Central Asia | 21(13.29)b | 137(86.71) | ||
| Southwest Asia | 21(25.93)b | 60(74.07) | ||
| Middle East | 28(62.22)c | 17(37.78) | ||
| Africa | 18(51.43)c | 17(48.57) | ||
| Other | 4(44.44)c | 5(55.56) | ||
| Marital status | Married | 151(25.99) | 430(74.01) | 3.17(0.075) |
| Unmarried | 147(30.95) | 328(69.05) | ||
| Length of stay | < 5 years | 153(26.11) | 433(73.89) | 3.21(0.201) |
| ≥ 5 years, < 10 years | 89(29.97) | 208(70.03) | ||
| ≥ 10 years | 56(32.37) | 117(67.63) | ||
| Visa type | Student | 21(22.11)a | 74(77.89) |
56.47 (< 0.001***) |
| Employment | 94(22.76)a | 319(77.24) | ||
| Family/expatriate | 83(26.60)a | 229(73.40) | ||
| Refugee | 53(61.63)b | 33(38.37) | ||
| Unregistered | 47(31.76)c | 101(68.24) | ||
| Health insurance | Yes | 197(26.62) | 543(73.38) | 3.86(0.049*) |
| No | 95(32.76) | 195(67.24) | ||
| Job | Manufacturing | 71(17.03)a | 346(82.97) |
82.00 (< 0.001***) |
| Construction | 21(22.34)a | 73(77.66) | ||
| Farming | 49(62.03)b | 30(37.97) | ||
| Fishing | 34(28.10)c | 87(71.90) | ||
| Service | 18(31.58)d | 39(68.42) | ||
| Other | 23(37.70)d | 38(62.30) | ||
| Not working | 82(36.12)d | 145(63.88) | ||
| Monthly income (1,000 KRW) | < 1,000 | 85(33.33)a | 170(66.67) |
16.40 (< 0.001***) |
| ≥ 1,000, < 2,000 | 144(31.10)a | 319(68.90) | ||
| ≥ 2,000 | 67(20.00)b | 268(80.00) | ||
| Discrimination | Yes | 147(36.48) | 256(63.52) |
21.93 (< 0.001***) |
| No | 151(23.12) | 502(76.88) | ||
| Self-rated health | Very good | 16(11.27)a | 126(88.73) |
80.84 (< 0.001***) |
| Good | 71(19.89)a | 286(80.11) | ||
| Fair | 137(32.78)b | 281(67.22) | ||
| Bad | 59(51.30)c | 56(48.70) | ||
| Very bad | 15(62.50)c | 9(37.50) | ||
| Anxiety and depression | Yes | 185(50.14) | 184(49.86) |
134.49 (< 0.001***) |
| No | 113(16.45) | 574(83.55) | ||
| Disability | Yes | 34(64.15) | 19(35.85) |
35.57 (< 0.001***) |
| No | 264(26.32) | 739(73.68) | ||
| Chronic disease diagnosed | Yes | 68(45.33) | 82(54.67) |
25.28 (< 0.001***) |
| No | 230(25.39) | 676(74.61) | ||
* p < 0.05, *** p < 0.001; a, b, c, d = post-hoc test results
Because the unmet healthcare needs variable has only two values of 0 and 1, a logistic regression analysis was performed. Logistic regression ensures that predicted probabilities are between 0 and 1, and it provides odds ratios (OR) for interpretation, allowing for a more intuitive understanding of the variable’s influence [30]. Although the probit model can be used for binary variable analysis, logistic regression is better suited for calculating OR [31]. We also performed sensitivity analysis with the probit model, but the results were identical to those of the logistic regression. Furthermore, the linear probability model (LPM) has limitations because it can produce unrealistic values less than 0 or greater than 1 [32], rendering it unsuitable for the analytical purposes of this study.
Meanwhile, additional tests were carried out to see if subjective health status, chronic disease status, depression, and disability have endogenous links to unmet healthcare needs. To accomplish this, the relationship between the residuals of a logistic regression model with unmet healthcare needs as the dependent variable and the residuals of regression models with presumed endogenous variables as dependent variables was investigated. Because subjective health status ranges from 1 to 5, a linear regression model was used, whereas chronic disease status, depression, and disability are binary variables that were analyzed using logistic regression. The analysis results revealed that the correlation coefficient between the two residuals for subjective health status was − 0.0115 (p = 0.7135), for chronic disease status it was 0.0088 (p = 0.7791), for depression it was 0.0322 (p = 0.3046), and for disability, it was 0.0232 (p = 0.4590). Based on these findings, the study concluded that the issue of endogeneity is negligible.
We examined the data excluding the missing cases. All analyses in this study were carried out with STATA/SE 16.1.
Results
Characteristics of the Sample
Table 1 summarizes the sample’s characteristics. Among the predisposing factors, the age group under 45 years accounted for the majority with 76.70%. The regions of origin with the largest proportions were Southeast Asia and Northeast Asia, 40.94% and 32.84%, respectively. The proportion of the married was 45.09%. The majority of residents (55.38%) had lived in Korea for less than 5 years. Employment visas were the most common type, accounting for 39.04%, followed by family and overseas Korean visas at 29.77%.
Among the enabling factors, the health insurance enrollment rate was 70.09%. The percentage of immigrants with jobs was 78.49%, with nearly half (39.43%) working in manufacturing. Furthermore, 38.02% of the sample reported discrimination due to COVID-19.
In terms of need factors, 13.40% of respondents rated their health as “very good” and 33.77% as “good”. The percentage of people who had severe anxiety or depression in the previous year was 34.91%. Individuals with physical or mental disabilities accounted for 5% of the population, while 14.34% were diagnosed with chronic diseases.
Unmet Healthcare Needs by the Sample Characteristics
Table 2 shows the results of a chi-square analysis used to compare unmet healthcare experiences by each variable in the conceptual framework.
In predisposing factors, there were significant differences of unmet healthcare needs by such factors as gender, region of origin, and visa type. Unmet healthcare needs were more prevalent among women than in men. Among the regions of origin, those from Russia and Central Asia reported the lowest unmet healthcare experiences, as compared to those from South Asia. In contrast, individuals from the Middle East, Africa, and other regions reported considerably more unmet healthcare needs. Among visa types, refugees had the highest unmet healthcare experiences, with significant differences compared to international students, employment immigrants, and overseas Korean groups. Furthermore, undocumented immigrants had less unmet healthcare needs than refugees, but significantly more than those in the student/employment/marriage migrant or overseas Korean populations.
All variables included in the enabling factors demonstrated significant differences in unmet healthcare needs. Among occupations, individuals in manufacturing and construction reported fewer unmet healthcare needs, while those in agriculture and livestock reported the most. Meanwhile, people in the fishing, service industries, other occupations, and unemployed reported unmet healthcare needs that were lower than those in agriculture but significantly higher than in manufacturing. Groups without health insurance, those with low incomes, and those who faced discrimination reported higher unmet healthcare needs than their counterparts.
All variables related to need factors demonstrated significant differences in unmet healthcare experiences. Individuals who rated their subjective health as “very good” or “good” reported significantly less unmet healthcare experiences than those rated as “average”. In contrast, those who perceived their health as “poor” or “very poor” reported the most unmet healthcare needs. People with anxiety or depression, disabilities, or chronic diseases reported more unmet healthcare needs than those without these conditions.
Logistic Regression
Table 3 shows the results of the logistic regression analysis with all the variables included in the conceptual framework. Among the predisposing factors, only region of origin was significant, with unmet healthcare experiences significantly lower in Central Asia than in Southeast Asia.
Table 3.
Logistic regression analysis of factors associated with unmet healthcare needs among immigrants
| Category | Odds Ratio | SE | |
|---|---|---|---|
| Predisposing factors | |||
| Sex | Male | 1 | |
| Female | 1.35 | 0.29 | |
| Age | < 45 | 1 | |
| ≥ 45, < 65 | 0.65 | 0.16 | |
| ≥ 65 | 1.15 | 0.59 | |
| Region of origin | Northeast Asia | 1.26 | 0.32 |
| Southeast Asia | 1 | ||
| Central Asia | 0.45* | 0.15 | |
| Southwest Asia | 0.93 | 0.35 | |
| Middle East | 1.10 | 0.64 | |
| Africa | 0.92 | 0.48 | |
| Other | 1.68 | 2.17 | |
| Marital status | Married | 1 | 0.26 |
| Unmarried | 1.22 | ||
| Length of stay | < 5 years | 1 | |
| ≥ 5 years, < 10 years | 1.09 | 0.23 | |
| ≥ 10 years | 1.32 | 0.36 | |
| Enabling factors | |||
| Visa type | Student | 0.94 | 0.41 |
| Employment | 0.72 | 0.19 | |
| Family/expatriate | 1 | ||
| Refugee | 5.29** | 2.63 | |
| Unregistered | 1.24 | 0.56 | |
| Health insurance | Yes | 1 | 0.31 |
| No | 0.88 | ||
| Job | Manufacturing | 1 | |
| Construction | 1.12 | 0.40 | |
| Farming | 8.10*** | 2.77 | |
| Fishing | 1.26 | 0.40 | |
| Service | 1.13* | 0.43 | |
| Other | 2.22 | 0.86 | |
| Not working | 1.48 | 0.47 | |
| Monthly income (1,000 KRW) | < 1,000 | 1 | |
| ≥ 1,000, < 2,000 | 1.41 | 0.39 | |
| ≥ 2,000 | 1.37 | 0.44 | |
| Discrimination | Yes | 1.58* | 0.29 |
| No | 1 | ||
| Need factors | |||
| Self-rated health | Very good | 1 | |
| Good | 2.55** | 0.91 | |
| Fair | 3.86*** | 1.37 | |
| Bad | 5.76*** | 2.31 | |
| Very bad | 5.86** | 3.73 | |
| Anxiety and depression | Yes | 4.47*** | 0.82 |
| No | 1 | ||
| Disability | Yes | 2.44* | 0.89 |
| No | 1 | ||
| Chronic disease diagnosed | Yes | 1.22 | 0.32 |
| No | 1 | ||
| No. of Obs 1,025; LR chi2(33) = 317.38; Prob > chi2 = 0.0000; Pseudo R2 = 0.2599 | |||
* p < 0.05, ** p < 0.01, *** p < 0.001
Visa type, occupation, and discrimination experiences were identified as significant enabling factors for unmet healthcare needs. Refugees had significantly more unmet healthcare experiences compared to family members and overseas Koreans (OR = 5.29, p < 0.01). In terms of occupation types, unmet healthcare experiences were more prevalent in agriculture (OR = 8.10, p < 0.001) and the service sectors (OR = 1.13, p < 0.05) than in the manufacturing sector. Additionally, groups who faced discrimination during the COVID-19 response had higher unmet healthcare needs compared to those who did not (OR = 1.58, p < 0.05).
Among the need factors, all variables except having chronic diseases were associated with unmet healthcare. The OR for unmet healthcare needs increased as subjective health worsened. The OR for anxiety or depression was 4.47 (p < 0.001), while for disabilities it was 2.44 (p < 0.05).
Discussion
This study examined a sample of 1,060 immigrants in South Korea to determine the various factors influencing unmet healthcare needs. Among the participants, 298 (28.2%) reported having unmet healthcare needs, which is considerably higher than the overall unmet healthcare experience rate of 15.0% for the South Korean population in 2020 [33]. The predisposing factors affecting unmet healthcare included country of origin and visa type, while enabling factors encompassed occupation, experiences of discrimination during the COVID-19 pandemic, and the need factors included subjective health status, anxiety and depression, and disability.
While this study assumed that all three factors affect immigrants’ unmet healthcare needs, we found that enabling factors, particularly occupation type, are the most influential variables affecting unmet healthcare experiences (OR = 8.10). Therefore, to address unmet healthcare needs among immigrants, it is critical to develop occupation-specific policies, with a focus on increasing healthcare accessibility for vulnerable occupational groups, such as agricultural workers.
Immigrants working in South Korea are mostly engaged in 3D (difficult, dirty, dangerous) industries that native workers avoid, and they frequently work long hours without breaks [34]. Furthermore, 82.3% of licensed hospitals in South Korea are concentrated in urban areas, creating a significant disparity between regions [35]. As a result, immigrant residents in rural areas face significant barriers to accessing healthcare services due to a lack of medical institutions and inconvenient transportation options compared to urban areas [36].
For these reasons, migrant agricultural workers may be hesitant to visit healthcare facilities [37, 38]. Consistent with previous studies, our logistic regression analysis also showed that agricultural workers had significantly higher odds of reporting unmet healthcare needs compared to those in other occupations (OR = 8.10, p < 0.001). This, combined with the regional disparity in healthcare access in South Korea, likely increases the likelihood of unmet healthcare needs among immigrants working in agriculture as compared to those in other occupations. To address these issues, home visit services and nighttime clinics must be expanded, as well as shuttle buses to make healthcare facilities more accessible.
Our logistic regression analysis showed that immigrants from Central Asia were less likely to experience unmet healthcare needs compared to immigrants from Southeast Asia (OR = 0.45, p < 0.05). This result suggests potential differences in healthcare access by country of origin. However, there is limited research that directly examines disparities in unmet healthcare needs across different immigrant groups, and studies specifically targeting Central Asian immigrants are particularly scarce. Therefore, our study could not fully elucidate the underlying reasons for these differences.
One explanation might be related to the fact that there are Korean immigrants among those who migrated to Korea from the Central Asia region. Korean immigrants are people who were forcibly relocated from Russia to Central Asia by Stalin’s order in 1937 [39]. It is known that they tend to experience less racial prejudice or discrimination in Korean society and have a tendency to build their own communities to live in [40]. For this reason, they may experience less unmet healthcare needs compared to other immigrants with different ethnic and cultural backgrounds such as Southeast Asian immigrants.
Refugees are more likely to have unmet healthcare needs than immigrants with family or overseas Korean visas. This is because recognized refugees in South Korea can generally receive social security benefits comparable to those of South Korean citizens [41], whereas asylum seekers or those with humanitarian status face barriers to accessing such healthcare benefits [42]. Furthermore, the actual referral rate for refugee status determination in South Korea is low, indicating that refugees frequently lack adequate healthcare coverage [43].
As a result, refugees face significant financial burdens when seeking medical care, as they pay much higher prices than other groups with residence visas or native residents, making healthcare access difficult [44]. In some cases, they can receive limited assistance through the “Healthcare Support Project for Disadvantaged Groups, including Foreign Workers,” but this program only partially covers medical costs for hospitalization and surgery, not outpatient care, limiting its effectiveness and budget [45]. To address the healthcare accessibility issues that refugees face, it is critical to raise awareness of refugee issues, identify and improve the flaws in refugee healthcare support administration, and increase funding for these services.
The COVID-19 pandemic disproportionately impacted low-income and socially vulnerable populations within a country [46]. Vulnerable groups based on gender, age, race, and ethnicity had limited access to healthcare during the COVID-19 pandemic, resulting in inadequate disease prevention, treatment, and management [47]. Furthermore, the South Korean government implemented discriminatory public health policies, such as barring immigrants from the public mask distribution system and withholding emergency relief funds [48]. During this period, there was also an increase in hatred and discrimination against immigrants, which psychologically hampered their mobility and caused healthcare providers to be hesitant or refuse to treat them, further reducing healthcare accessibility [49, 50]. The social exclusion and discrimination endured by immigrants during the COVID-19 pandemic most likely increased distrust in the South Korean government and healthcare institutions, posing a significant barrier to healthcare access. This could mean that immigrants who have faced discrimination are more likely to have unmet healthcare needs. To change immigrants’ perceptions, educational programs or pamphlets should be developed to raise awareness of their rights, assist them in protecting those rights, and reduce the anxiety they may experience when using healthcare services.
The likelihood of unmet healthcare needs increased as subjective health status decreased from “very good” to “very bad”, which is consistent with many previous research findings [51, 52]. Subjective health levels are a proxy for an individual’s self-assessment of their current health status, and they can predict disability and mortality rates [53]. Moreover, when people have negative perceptions about their health, they are less likely to engage in health-promoting behaviors. As a result, it is critical to examine and improve the accessibility and availability of healthcare services for those who believe their subjective health status is poor [54, 55]. Despite these findings, this study has several limitations.
First, this study is a cross-sectional analysis of secondary data, so causal relationships between unmet healthcare experiences cannot be clearly established. Second, the data was based on self-reported information, which may have resulted in bias due to possible distortions in respondents’ memories. Third, the survey included immigrants from various linguistic and cultural backgrounds, which could have resulted in inconsistencies in responses due to these differences. Fourth, while this study examined the immigrants’ unmet healthcare needs during the COVID-19 pandemic (July to September 2020), we could not determine when the sample migrated to South Korea. As a result, we could not compare the differential unmet healthcare needs of those who migrated to South Korea before and during the pandemic. Lastly, the dataset did not include information on immigrants’ area of residence (urban vs. rural) or employment status (temporary vs. regular), which are potentially important factors for understanding disparities in healthcare access. The absence of these variables limits the scope of inference regarding regional and occupational differences in unmet healthcare needs.
However, this study was carried out in a context where little research has been conducted to identify the various factors associated with unmet healthcare needs among South Korean immigrants. It is significant because it presents practical solutions to reduce unmet healthcare needs among immigrants based on the analysis results. Although it is difficult to generalize the study’s findings to all countries, structural and institutional factors suggest that they may apply to countries with similar healthcare systems (UHC), such as Taiwan and Japan. Nonetheless, the study’s findings have the potential to positively contribute to international efforts to improve healthcare access for immigrants and may have policy implications, particularly in countries with similar migration patterns.
Conclusion
To address unmet healthcare needs among immigrants, it is critical to determine which subgroup is most vulnerable. This study discovered that factors influencing immigrants’ unmet healthcare needs included country of origin, visa type, occupation, experiences with discrimination during the COVID-19 pandemic, subjective health status, anxiety, depression, and disabilities. To reduce health disparities among immigrants, policy changes are required, as well as increased funding for those in need.
Acknowledgements
This study was funded by the 2023 Hayngseol Convergence Research Program of Soonchunhyang University.
Author Contributions
M.B. drafted the introduction, discussion, and conclusion. E.K. decided the research question, obtained the data, and analyzed the data. E.K. also drafted the methods and results and edited the entire paper. All authors have reviewed the manuscript and made revisions in response to the reviewers’ comments.
Data Availability
No datasets were generated or analysed during the current study.
Declarations
Competing Interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.United Nations, Department of Economic and Social Affairs, Population Division 2019. International Migration 2019: Report (ST/ESA/SER.A/438).
- 2.Ministry of Law. Immigration statistics: Staying foreigners. 2024. https://www.moj.go.kr/moj/2412/subview.do. Accessed July 13, 2024.
- 3.Cha SJ. Unmet health care needs of marriage migrant women in Korea. Unpublished master’s thesis. Seoul National University. Seoul. 2012.
- 4.Yang SJ. Health status, health care utilization and related factors among Asian immigrant women in Korea. J Korean Acad Public Health Nurs. 2010;24(2):323–35. [Google Scholar]
- 5.Paik HJ. Factors Affecting Unmet Healthcare Needs among Married Immigrant Women. Unpublished master’s thesis. Seoul National University. Seoul. 2024.
- 6.Lasser KE, Himmelstein DU, Woolhandler S. Access to care, health status, and health disparities in the united States and canada: results of a cross-national population-based survey. Am J Public Health. 2006;96(7):1300–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Jang HY, Lee HY. Factors influencing unmet healthcare needs among elderly living alone. J Korean Data Anal Soc. 2017;19(6):3317–29. [Google Scholar]
- 8.Aday LA, Andersen R. A framework for the study of access to medical care. Health Service Res. 1974;9(3);208– 20. [PMC free article] [PubMed]
- 9.Hun SI, LEE HJ. Unmet health care needs and attitudes towards health care system in Korea. Korean J Health Econ Policy. 2016;22(1):59–89. [Google Scholar]
- 10.Ha R, Jung-Choi K, Kim CY. Employment status and self-reported unmet healthcare needs among South Korean employees. Int J Environ Res Public Health. 2019;16(9):1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kin HR. Health status of marriage-based immigrants in Korea and policy directions. Health Welf Policy Forum. 2010;165:46–57. [Google Scholar]
- 12.Yang PQ, Hwang SH. Explaining immigrant health service utilization: A theoretical framework. Sage Open. 2016;6(2). 10.1177/2158244016648137
- 13.Shon CW, Yi SJ, Hwang JN. Factors affecting unmet healthcare needs among Korean migrants in Hong Kong. Korean Public Health Res. 2015;41(1):107–21. [Google Scholar]
- 14.Andersen RM. Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav. 1995;36(1):1–10. [PubMed] [Google Scholar]
- 15.Shin HY, Kang SW. Factors affecting unmet medical care depending on the economic activity of married migrant women in korea: application of the andersen’s behavioral model. Social Welf Policy Pract. 2023;9(2);227– 54.
- 16.Park S, Kim HY, Lee YM. Unmet healthcare needs and related factors among immigrants: A cross-sectional secondary analysis of 2019 Korea community health survey data. INQUIRY: J Health Care Organ Provis Financing. 2023;60:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Pan L, Wang C, Cao X, Zhu H, Luo L. Unmet healthcare needs and their determining factors among unwell migrants: A comparative study in Shanghai. Int J Environ Res Public Health. 2022;19(9):5499. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hwang MC, Jang IH. A study on the factors influencing the use of health care services by married immigrant women: focusing on the analysis of differences using the Andersen model. J Gov Stud. 2017;12(1):31–57. [Google Scholar]
- 19.Yi J, Lee I. Factors affecting unmet healthcare needs of working married immigrant women in South Korea. J Korean Acad Community Health Nurs. 2018;29(1):41–53. [Google Scholar]
- 20.Busetta A, Cetorelli V, Wilson B. A universal health care system? Unmet need for medical care among regular and irregular immigrants in Italy. J Immigr Minor Health. 2018;20:416–21. [DOI] [PubMed] [Google Scholar]
- 21.Ridde V, Aho J, Ndao EM, Benoit M, Hanley J, Lagrange S, Cloos P. Unmet healthcare needs among migrants without medical insurance in montreal, Canada. Glob Public Health. 2020;15(11):1603–16. [DOI] [PubMed] [Google Scholar]
- 22.Derose KP, Escarce JJ, Lurie N. Immigrants and health care: sources of vulnerability. Health Aff. 2007;26(5):1258–68. [DOI] [PubMed] [Google Scholar]
- 23.Howe Hasanali S. Immigrant-native disparities in perceived and actual met/unmet need for medical care. J Immigr Minor Health. 2015;17:1337–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lee HS, Survey on the Health Rights of Migrants and the Improvement of the Medical Security System. 2020 [Dataset]. Solidarity with Migrants [Producers]. Korea Social Science Data Archive (KOSSDA) [Distributors], 2023-06-05, 10.22687/KOSSDA-A1-2020-0098-V1.0
- 25.Ministry of Foreign Affairs. Consulate regions and countries. 2024. https://www.mofa.go.kr/www/wpge/m_24316/contents.do. Accessed July 13, 2024.
- 26.Ministry of Employment and Labor. Minimum wage policy: 2020 decision and implementation. 2020. https://www.minimumwage.go.kr/minWage/policy/decisionMain.do. Accessed 27 February 2025.
- 27.SisaIN. 6 out of 10 Koreans delay children’s marriage due to housing difficulties. SisaIN. https://www.sisain.co.kr/news/articleView.html?idxno=49598. Accessed 24 February 2025.
- 28.Zhang Y, Kim MA. Chinese international students’ experiences of social stigma during the covid-19 pandemic in Korea. Health Social Welf Rev. 2021;41(41):22–41. [Google Scholar]
- 29.National Human Rights Commission of Korea. 2023 national survey on human rights awareness. https://www.humanrights.go.kr/base/board/read?boardManagementNo=24%26boardNo=7606058%26menuLevel=3%26menuNo=91
- 30.Szumilas M. Explaining odds ratios. J Can Acad Child Adolesc Psychiatry. 2010;19(3):227. [PMC free article] [PubMed] [Google Scholar]
- 31.Long JS. Regression models for categorical and limited dependent variables. Adv Quant Techniques Social Sci. 1997;7:328. [Google Scholar]
- 32.Angrist JD, Pischke JS. Mostly harmless econometrics: an empiricist’s companion. Princeton University Press 2009.
- 33.Park EJ, Park JH, Park NY, Kwak YK, Chun HR, Oh YH. Analysis of changes in health behavior, health status, and medical use during the COVID-19 pandemic. Korea Institute for Health and Social Affairs; 2023. Accessed 27 February 2025. https://www.kihasa.re.kr/publish/report/research/view?seq=60985
- 34.Choi JH. Research on the condition of free medical treatment and secondary treatment for foreign workers: Focused on Ansan city. A Study on Multicultural Contents. 2011;10:301– 39.
- 35.Ministry of the Interior. and Safety (MIS).2017. Local Administration Licensing Information. http://www.localdata.kr/
- 36.Kim SA, Seo YW, Woo KS, Shin YJ. A systematic review of studies on current status and influencing factors of unmet medical needs in Korea. J Crit Social Policy. 2019;62:53–92. [Google Scholar]
- 37.Chung JA. A study on the life culture of Koryosaram and Sakhalin Koreans living in Korea and their cultural conflicts with South Koreans. Unified Humanit. 2014;58:34–65. [Google Scholar]
- 38.Kim KH, Rabbani MG. Discrimination and exclusion, and socio-economic impacts of COVID-19 experienced by Bangladeshi migrant workers in Korea. J DIASPORA Stud. 2020;14(2):7–46. [Google Scholar]
- 39.Kim K-H. A Study on the Health and Care of Later-Life Koryeoin Migrants in Korea - Centered on Babushkas(grandmothers) in Gwangju Metropolitan. Studies of Koreans Abroad. 2024;64;1–40.
- 40.Kim Y-S, Hong I-H. A Study on Central Asian Koryoin Migration in Gwangju Area and Acculturation. J Diaspora Studies. 2013;7(1);131–161. https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001775857
- 41.Ministry of Justice, Immigration and Foreigner Policy Headquarters. Refugee division. Refugee status determination procedures in Korea. Gwacheon: Ministry of Justice 2015. [Google Scholar]
- 42.Hong SM. Refugee medical administration in Republic of Korea. Health Policy Manage. 2023;33(2);214– 22.
- 43.SBS Magic Needle. Refugee problem, let’s look at this first. SBS News. 2018. https://mabu.newscloud.sbs.co.kr/201807refugee/index.html. Accessed September 9, 2024.
- 44.Ministry of Health and Welfare. Guide to 2020 medical support for foreign workers, etc. Sejong: Ministry of Health and Welfare. 2020. https://www.129.go.kr/info/info04_view.jsp?n=1463. Accessed September 9, 2024.
- 45.Germain S, Yong A. COVID-19 highlighting inequalities in access to healthcare in england: A case study of ethnic minority and migrant women. Fem Legal Stud. 2020;28(3):301–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Piao ZH, Kim BJ. The effect of perceived discrimination on depression of Chinese nationals in South Korea during the COVID-19 pandemic: moderating effect of social support. Convergence Soc Public Policy. 2023;17(1);152– 84.
- 47.National Human Rights Commission of Korea. 2020a. Corona19wa ijumin ingwon monitoring gyeolgwabogo.
- 48.National Human Rights Commission of Korea. 2020b. Corona19wa hyeomoui pandemig.
- 49.Son IS. Korean-Chinese care workers’ career transition in korea: aged and Racialized perceptions and immigrant inequality. Econ Soc. 2020;312– 44.
- 50.Kim KS, Lee HO. Household catastrophic health expenditure and unmet needs depending on the types of health care system. Social Welf Policy. 2012;39(4);255– 79.
- 51.Song KS, Lee JH, Rhim KH. Factors associated with unmet needs for health care. Korean Public Health Res. 2011;37(1);131– 40.
- 52.Lim JH. Analysis of unmet medical need status based on the Korean health pane. Health Social Sci. 2013;34(1);237– 56.
- 53.Idler EL, Kasl SV. Self-ratings of health: do they also predict change in functional ability? Journals Gerontol Ser B: Psychol Sci Social Sci. 1955;50(6):344–53. [DOI] [PubMed] [Google Scholar]
- 54.Lee SJ, Kim SH. Factors affecting the unmet medical needs of adults based on anderson’s behavioral model. Health Welf. 2023;25(4):141–64. [Google Scholar]
- 55.Bailis DS, Segall A, Chipperfield JG. Two views of self-rated general health status. Soc Sci Med. 2003;56(2);203– 17. [DOI] [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Citations
- Lee HS, Survey on the Health Rights of Migrants and the Improvement of the Medical Security System. 2020 [Dataset]. Solidarity with Migrants [Producers]. Korea Social Science Data Archive (KOSSDA) [Distributors], 2023-06-05, 10.22687/KOSSDA-A1-2020-0098-V1.0
Data Availability Statement
No datasets were generated or analysed during the current study.