Abstract
Background
Women with disabilities are susceptible to compounded discrimination based on gender and disability, which can constrain healthcare access and worsen health outcomes. Quantitative evidence on determinants of unmet healthcare needs in Women with disabilities remains limited. This study aimed to identify predictors of unmet healthcare needs among women with disabilities and to provide evidence to inform improvements in healthcare accessibility.
Methods
We conducted a cross-sectional analysis of 2873 Women with disabilities from the nationally representative 2023 Survey of People with Disabilities in Korea. Guided by Andersen’s Behavioral Model of Health Services Use, we examined predisposing, enabling, and need factors associated with unmet healthcare needs using descriptive statistics, chi-square tests, and multivariable logistic regression.
Results
Among women with disabilities, the prevalence of unmet healthcare needs was 19.7%. The most common reasons were difficulty traveling to healthcare facilities (41.2%) and financial constraints (25.8%). In multivariable analysis, the odds of experiencing unmet healthcare needs were higher among those with lower household income, physical disabilities, severe disability, dependence in instrumental activities of daily living (IADL), poor self-rated health, experience of depression, difficulty using transportation, and inability to go out alone.
Conclusions
Women with disabilities experience high rates of unmet healthcare needs. Limitations in daily living due to physical disability, low socioeconomic status (SES), and mental health vulnerability emerged as major factors underlying unmet healthcare needs among women with disabilities. Integrated policies addressing financial barriers, healthcare accessibility, and women’s health are needed to meet the unique needs of women with disabilities.
Keywords: Women with disabilities, Unmet health care needs, Andersen’s Behavioral Model of Health Services Use
Introduction
According to Article 25 of the United Nations Convention on the Rights of Persons with Disabilities, persons with disabilities have the right to enjoy the highest attainable standard of health without discrimination, and measures must be taken to guarantee access to health services in all aspects, including public health, prevention, geographic conditions, and ethical considerations [1]. However, approximately 16% of the world's population lives with a disability and faces numerous health inequalities. These inequities arise from unfair conditions—such as stigma, discrimination, poverty, exclusion from education and employment, and barriers within the health system itself—which contribute to poorer health outcomes and increase the risk of unmet healthcare needs among persons with disabilities [2]. Although access to health services has gradually improved, unmet health care needs remain a critical public health issue [3]. Unmet health care needs are defined as the medical gap between perceived or evaluated needs and the resources actually available [4]. They have been used as an indicator to assess problems in health care accessibility, and from the patient’s perspective, whether the demand for health services is met constitutes a key criterion for evaluating health systems overall [5]. Unmet health care needs are known to negatively affect individuals’ health and quality of life regardless of age or country. Previous studies have shown that disability increases the likelihood of not receiving needed routine care by more than 50% [6]. Persons with disabilities have three times more unmet health care needs than those without disabilities [7], and consequently experience poorer health outcomes.
In particular, women with disabilities (WWD) are more likely to experience dual discrimination and inequality based on both gender and disability, which can negatively affect their access to and use of health services. WWD have been reported to be more likely to have unmet healthcare needs compared with women without disabilities [8]. According to the World Health Survey, the prevalence of disability among women is estimated to be 60% higher than that among men [9], and WWD were found to be 7.2 times more likely (95% CI: 2.7–19.4) to have unmet needs due to the costs of treatment or medication compared with men without disabilities [10]. Additionally, WWD are at greater risk for chronic diseases, with more than 50% experiencing physical functional limitations [11]. Because women face unique health issues such as pregnancy and childbirth, it is estimated that 10%–12% of reproductive-aged women live with disabilities. WWD are more likely to begin antenatal care later and are at increased risk of health problems that affect maternal and infant outcomes, including gestational diabetes, obesity, chronic hypertension, hypertensive disorders of pregnancy, cesarean delivery, and low birth weight [12]. Nevertheless, WWD often do not seek medical services when health problems arise [13, 14]. This suggests that even minor health issues may be left untreated and neglected until they progress into life-threatening conditions. Therefore, it is necessary to remove the various barriers to healthcare that prevent women with disabilities from leading healthy lives [13].
In Korea, despite rapid population aging, low employment and income among women with disabilities, and persistent structural discrimination, research on women with disabilities remains limited; to date, within the scope of our review, no nationally representative study examining the determinants of unmet healthcare needs among women with disabilities has been identified. In the international literature, most studies have either been limited to specific types of disabilities or diseases, or have focused on particular domains such as financial, physical, attitudinal, or structural barriers, and are largely outdated [15–22]. The absence of such research may result in insufficient reflection of the unique healthcare needs and experiences of women with disabilities. Therefore, independent research focusing on women with disabilities is necessary to identify the factors influencing their unmet healthcare needs and to develop policies and measures to improve healthcare accessibility. Accordingly, this study utilized the most recent nationally representative empirical data—the 2023 National Survey on Persons with Disabilities—which enables a comprehensive and multidimensional examination of the living conditions of women with disabilities. Specifically, this study aimed to investigate the reasons why women with disabilities were unable to access healthcare services and to identify the factors influencing unmet healthcare needs. Based on Andersen’s Behavioral Model of Health Services Use, these factors were categorized into predisposing factors, enabling factors, and need factors [23, 24], allowing for a multidimensional understanding.
Material and methods
Conceptual framework
This study analyzed predictors of unmet healthcare needs among women with disabilities, using Andersen’s Behavioral Model of Health Services Use (Fig. 1). The socio-behavioral model is useful for predicting healthcare utilization and identifying predictors of healthcare use, as it takes into account a wide range of factors such as psychosocial, individual, environmental, and institutional influences, with Andersen’s model being the most representative example [24]. According to Andersen’s Behavioral Model, healthcare utilization (including hospitalization and treatment) is determined by three epidemiological components: predisposing, enabling, and need factors. Predisposing factors refer to inherent characteristics that individuals possess regardless of their will, including sociodemographic and socioeconomic characteristics. Enabling factors represent the resources, means, and capacities that make healthcare utilization possible, such as income level, health insurance, and social support. Need factors are physiological and psychological conditions related to an individual’s disability or illness that directly cause the utilization of healthcare services [23–25].
Fig. 1.
Conceptual framework based on Andersen’s Behavioral Model
Data
This study utilized data from the 2023 National Survey on Persons with Disabilities, a nationally designated statistical survey (Approval No. 117032) that provides a detailed examination of the living conditions and welfare needs of persons with disabilities in Korea. The 2023 National Survey on Persons with Disabilities data used the Ministry of Health and Welfare’s registry of persons with disabilities as its sampling frame. The target population comprised 2,630,374 community-dwelling registered persons with disabilities out of 2,657,397 registrants nationwide. To obtain a nationally representative sample, the survey applied two-stage stratified cluster sampling. At stage 1, Korea’s 17 provinces served as strata, and eup/myeon/dong units (Primary Sampling Units) were selected using square-root proportional allocation, yielding 285 PSUs. At stage 2, within selected PSUs, individuals were sampled stratified by disability type and disability severity, resulting in a final sample of 8,000 respondents. This design ensures representativeness of the community-dwelling registered persons with disabilities at the national level.
Data were collected through face-to-face interviews by trained interviewers using a structured questionnaire and the Computer-Assisted Personal Interviewing (CAPI) system [26]. As this dataset consists of de-identified secondary public data, the present study was granted an exemption from ethical review by the Institutional Review Board of the National Rehabilitation Center (Approval number: NRC-2025–04–027).
Study population
Among the 8,000 persons with disabilities from the 2023 National Survey on Persons with Disabilities, 3137 were women with disabilities; of these, 3016 were aged 19 years or older. After excluding 143 cases due to nonresponse or missing data, the final analytic sample comprised 2873 women with disabilities (Fig. 2). The response rate was 95.3%.
Fig. 2.
Flow diagram of participant selection for women with disabilities
Measures
As shown in Fig. 1, the independent variables were classified into predisposing, enabling, and need factors, while the dependent variable was unmet healthcare need, measured by the survey item: “During the past year, have you ever been unable to visit a healthcare institution when you wanted to?”.
Independent variables under predisposing factors included age, marital status (presence or absence of a spouse), educational level (college graduate or higher vs. high school graduate or lower), and residential area (urban vs. rural).
Enabling factors included type of health insurance coverage (National Health Insurance, Medical Aid, or Other/uninsured), economic activity (employment), household income, and whether the respondent lived alone. Economic activity was defined as having worked for at least one hour during the previous week for the purpose of earning income. Household income referred to the average total monthly household income in 2022.
Need factors consisted of type of disability, severity of disability, presence of chronic disease, Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), self-rated health, stress, experience of depression, suicidal ideation, difficulty using transportation (transport difficulty), and ability to go out alone. Type of disability was classified in accordance with Article 2 of the Enforcement Decree of the Korean Act on Welfare of Persons with Disabilities into: external physical-function disabilities (physical disability, brain lesion, visual impairment, hearing impairment, speech impairment, facial impairment); internal organ disabilities (renal disability, cardiac disability, hepatic disability, respiratory disability, ostomy/urostomy disability, epilepsy); and mental disabilities (intellectual disability, autism spectrum disorder, mental disorder). Severity of disability was categorized as mild (persons with less severe disabilities) or severe (persons with more severe disabilities). ADL and IADL were each coded as either “independent” or “dependent.” Responses of “no assistance needed” across all items were classified as independent performance, whereas reporting “partial assistance needed,” “considerable assistance needed,” or “full assistance needed” for at least one item was classified as unable to perform independently. Experience of depression was defined as having felt sadness, despair that interfered with daily life for two or more consecutive weeks during the past year. Suicidal ideation referred to having ever thought of wanting to die during the past year.
Statistical analysis
To examine the frequency and distribution of the general characteristics of the participants, descriptive statistical analysis was conducted. To assess the associations between predisposing, enabling, and need factors and unmet healthcare needs among women with disabilities, the chi-squared test was employed. Furthermore, to account for the effects of multiple risk factors simultaneously and to estimate the independent contribution of each factor to unmet healthcare needs, we performed multivariable logistic regression. All predisposing, enabling, and need variables were included as covariates in the models. Results are reported as adjusted odds ratios (AORs) with 95% confidence intervals (95% CIs). Statistical significance was set at α < 0.05. Missing data were excluded from the analyses. All analyses were performed using SPSS version 27.0 (IBM Corp.).
Result
General characteristics
Among the 2,873 women with disabilities, those aged 65 years and older accounted for the largest proportion (57.4%), with a mean age of 65.7 years. Regarding marital status, 60.7% had no spouse, and in terms of education, the majority (85.7%) had completed high school or lower. With respect to residential area, 74.2% lived in urban settings. Regarding health insurance coverage, 78.5% were enrolled in National Health Insurance, while 21.4% were covered by Medical Aid. In terms of economic activity, 76.3% were not engaged in the labor force, and 52.8% of households reported a monthly income of ≤ 2 million KRW. By type of disability, external physical-function disabilities were most common (69.0%), followed by internal organ disabilities (17.5%) and mental disabilities (13.5%). In terms of severity, mild disability (54.9%) was somewhat more prevalent than severe disability (Table 1).
Table 1.
Characteristics of the subject of study (N = 2873)
| Variable | Category | N | (%) |
|---|---|---|---|
| Age | 19 ~ 39 | 220 | (7.7) |
| 40 ~ 64 | 1005 | (35.0) | |
| ≥ 65 | 1648 | (57.4) | |
| Marital status | With spouse | 1128 | (39.3) |
| Without spouse | 1745 | (60.7) | |
| Education level | College graduate or higher | 410 | (14.3) |
| High school graduate or lower | 2463 | (85.7) | |
| Residential area | Urban | 2132 | (74.2) |
| Rural | 741 | (25.8) | |
| Health insurance coverage | National Health Insurance | 2256 | (78.5) |
| Medical Aid | 616 | (21.4) | |
| Other/uninsured | 1 | (0.0) | |
| Economic activity | Yes | 681 | (23.7) |
| No | 2192 | (76.3) | |
| household income(KRW) | ≥ 4010000 | 586 | (20.4) |
| 3010000 ~ 4000000 | 311 | (10.8) | |
| 2010000 ~ 3000000 | 460 | (16.0) | |
| ≤ 2000000 | 1516 | (52.8) | |
| Living alone | No | 1896 | (66.0) |
| Yes | 977 | (34.0) | |
| Type of disability | External physical-function disabilities | 1983 | (69.0) |
| Internal organ disabilities | 503 | (17.5) | |
| Mental disabilities | 387 | (13.5) | |
| Disability severity | Mild | 1577 | (54.9) |
| Severe | 1296 | (45.1) | |
| Chronic disease | No | 331 | (11.5) |
| Yes | 2542 | (88.5) | |
| ADL | Independent | 1633 | (56.8) |
| dependent | 1240 | (43.2) | |
| IADL | Independent | 1170 | (40.7) |
| dependent | 1703 | (59.3) | |
| SRH | Good | 1326 | (46.2) |
| Poor | 1547 | (53.8) | |
| Stress | Hardly at all | 595 | (20.7) |
| A little | 1303 | (45.4) | |
| A lot | 975 | (33.9) | |
| Experience of depression | No | 2418 | (84.2) |
| Yes | 455 | (15.8) | |
| Suicidal ideation | No | 2578 | (89.7) |
| Yes | 295 | (10.3) | |
| transport difficulty | No difficulty | 1575 | (54.8) |
| Difficulty | 1298 | (45.2) | |
| Ability to go out alone | Able | 2261 | (78.7) |
| Unable | 612 | (21.3) |
SRH Self-rated health, ADL Activities of Daily Living, IADL Instrumental Activities of Daily Living
Unmet Healthcare needs and their reasons among women with disabilities
Among the 2873 women with disabilities, 566 reported experiencing unmet healthcare needs, accounting for 19.7% of the total. The most common reason was ‘difficulty in getting to a healthcare facility (41.2%)’. The next most common reason was ‘financial difficulties (25.8%)’, followed by ‘no one to accompany them when visiting a healthcare facility (9.9%)’, ‘lack of time (6.5%)’, ‘mild symptoms (4.9%)’, ‘communication difficulties (4.8%)’, and ‘inconvenience due to the lack of disability-friendly facilities and equipment in healthcare institutions (3.5%)’. Other reasons included ‘difficulty in making an appointment’, ‘lack of understanding of disability by healthcare providers’, ‘Did not know which clinic to visit’, ‘reluctance to wait a long time at the healthcare facility’, and ‘other’ (Table 2).
Table 2.
Prevalence and Reasons for Unmet Healthcare Needs among Women with Disabilities
| Category | Unmet healthcare needs | |||
|---|---|---|---|---|
| No Unmet healthcare needs | Unmet healthcare needs | |||
| N | (%) | N | (%) | |
| 2307 | (80.3) | 566 | (19.7) | |
| Unmet healthcare needs and why | ||||
| Financial difficulties | 146 | (25.8) | ||
| Difficulty in getting to a healthcare facility | 233 | (41.2) | ||
| Lack of understanding of disability by healthcare providers | 4 | (0.7) | ||
| Communication difficulties | 27 | (4.8) | ||
| Lack of time | 37 | (6.5) | ||
| Inconvenience due to the lack of disability-friendly facilities and equipment in healthcare institutions | 20 | (3.5) | ||
| No one to accompany them when visiting a healthcare facility | 56 | (9.9) | ||
| Did not know which clinic to visit | 3 | (0.5) | ||
| Difficulty in making an appointment | 7 | (1.2) | ||
| Mild symptoms | 28 | (4.9) | ||
| Reluctance to wait a long time at the healthcare facility | 1 | (0.2) | ||
| Other | 4 | (0.7) | ||
| Total | 566 | 100.0 | ||
Associations between various factors and unmet healthcare needs among women with disabilities
In univariate analysis, unmet healthcare needs were significantly associated with age, marital status, education level, health insurance coverage, economic activity, household income, living alone, type of disability, Disability severity, presence of chronic disease, ADL, IADL, self-rated health, stress, experience of depression, suicidal ideation, difficulty using transportation, and ability to go out alone (Table 3).
Table 3.
Associations with Unmet Healthcare Needs among Women with Disabilities
| Variable | Category | Unmet Healthcare Needs | x2(p-value) | |||
|---|---|---|---|---|---|---|
| Yes | No | |||||
| Predisposing factors | N | (%) | N | (%) | ||
| Age | 19 ~ 39 | 28 | (12.7) | 192 | (87.3) | 17.565(< 0.001) |
| 40 ~ 64 | 172 | (17.1) | 833 | (82.9) | ||
| ≥ 65 | 366 | (22.2) | 1282 | (77.8) | ||
| Marital status | With spouse | 187 | (16.6) | 941 | (83.4) | 11.447(0.001) |
| Without spouse | 379 | (21.7) | 1366 | (78.3) | ||
| Education level | College graduate or higher | 53 | (12.9) | 357 | (87.1) | 13.872(< 0.001) |
| High school graduate or lower | 513 | (20.8) | 1950 | (79.2) | ||
| Residential area | Urban | 420 | (19.7) | 1712 | (80.3) | .000(0.998) |
| Rural | 146 | (19.7) | 595 | (80.3) | ||
| Enabling factors | ||||||
| Health insurance coverage | National Health Insurance | 417 | (18.5) | 1839 | (81.5) | 10.198(0.006) |
| Medical Aid | 149 | (24.2) | 467 | (75.8) | ||
| Other/uninsured | 0 | (0.0) | 1 | (100.0) | ||
| Economic activity | Yes | 99 | (14.5) | 582 | (85.5) | 15.041(< 0.001) |
| No | 467 | (21.3) | 1725 | (78.7) | ||
| Household income(KRW) | ≥ 4,010,000 | 75 | (12.8) | 511 | (87.2) | 33.054(< 0.001) |
| 3,010,000 ~ 4,000,000 | 49 | (15.8) | 262 | (84.2) | ||
| 2,010,000 ~ 3,000,000 | 89 | (19.3) | 371 | (80.7) | ||
| ≤ 2,000,000 | 353 | (23.3) | 1163 | (76.7) | ||
| Living alone | No | 338 | (17.8) | 1558 | (82.2) | 12.373(< 0.001) |
| Yes | 228 | (23.3) | 749 | (76.7) | ||
| Need factors | ||||||
| Type of disability | External physical-function disabilities | 435 | (21.9) | 1548 | (78.1) | 20.481(< 0.001) |
| Internal organ disabilities | 77 | (15.3) | 426 | (84.7) | ||
| Mental disabilities | 54 | (14.0) | 333 | (86.0) | ||
| Disability severity | Mild | 280 | (17.8) | 1297 | (82.2) | 8.364(0.004) |
| Severe | 286 | (22.1) | 1010 | (77.9) | ||
| Chronic disease | No | 51 | (15.4) | 280 | (84.6) | 4.358(0.037) |
| Yes | 515 | (20.3) | 2027 | (79.7) | ||
| ADL | Independent | 232 | (14.2) | 1401 | (85.8) | 72.183(< 0.001) |
| dependent | 334 | (26.9) | 906 | (73.1) | ||
| IADL | Independent | 148 | (12.6) | 1022 | (87.4) | 62.034(< 0.001) |
| dependent | 418 | (24.5) | 1285 | (75.5) | ||
| SRH | Good | 164 | (12.4) | 1162 | (87.6) | 83.698(< 0.001) |
| Poor | 402 | (26.0) | 1145 | (74.0) | ||
| Stress | Hardly at all | 99 | (16.6) | 496 | (83.4) | 37.648(< 0.001) |
| A little | 213 | (16.3) | 1090 | (83.7) | ||
| A lot | 254 | (26.1) | 721 | (73.9) | ||
| Experience of depression | No | 425 | (17.6) | 1993 | (82.4) | 43.547(< 0.001) |
| Yes | 141 | (31.0) | 314 | (69.0) | ||
| Suicidal ideation | No | 467 | (18.1) | 2111 | (81.9) | 39.914(< 0.001) |
| Yes | 99 | (33.6) | 196 | (66.4) | ||
| Transport difficulty | No difficulty | 199 | (12.6) | 1376 | (87.4) | 110.018(< 0.001) |
| Difficulty | 367 | (28.3) | 931 | (71.7) | ||
| Ability to go out alone | Able | 376 | (16.6) | 1885 | (83.4) | 63.272(< 0.001) |
| Unable | 190 | (31.0) | 422 | (69.0) | ||
SRH Self-rated health, ADL Activities of Daily Living, IADL Instrumental Activities of Daily Living
Predictors of unmet healthcare needs among women with disabilities
Based on multivariable logistic regression analysis, the variables retained as appropriate for identifying risk factors for unmet healthcare needs were household income, type of disability, severity of disability, IADL, SRH, experience of depression, difficulty in using transportation, and ability to go out alone; all were statistically significant. Compared with a monthly household income of ≥ 4.01 million KRW, incomes of 2.01–3.00 million KRW (OR, 1.440; p = 0.041) and ≤ 2.00 million KRW (OR, 1.632; p = 0.001) were associated with higher odds of unmet need. Relative to mild disability, severe disability showed higher odds (OR, 1.275; p = 0.031). Compared with being able to perform IADL independently, being unable to perform IADL independently was associated with higher odds (OR, 1.343; p = 0.020). Compared with good self-rated health, poor self-rated health (OR, 1.740; p < 0.001); compared with no experience of depression, having experienced depression (OR, 1.349; p = 0.044); compared with not having difficulty using transportation, having difficulty (OR, 1.711; p < 0.001); and compared with being able to go out alone, being unable to go out alone (OR, 1.308; p = 0.029) had higher odds of experiencing unmet healthcare needs. By disability type, compared with external physical-function disabilities, internal organ disabilities (OR, 0.656; p = 0.004) and mental disabilities (OR, 0.484; p < 0.001) were associated with lower odds of unmet need. The model’s explanatory power (R2) was 13.2%, and the Hosmer–Lemeshow goodness-of-fit test indicated adequate fit (p = 0.206) (Table 4). The results of the multicollinearity assessment were as follows: VIFs ranged from 1.005 to 4.385 and tolerances from 0.228 to 0.959; most variables exhibited VIFs around 1–1.7, indicating that no concerning multicollinearity was observed.
Table 4.
Predictors of Unmet Healthcare Needs among Women with Disabilities
| Category | B | SE | Adjusted OR | 95% Cl | p-value | |||
|---|---|---|---|---|---|---|---|---|
| Enabling factors | ||||||||
| Household Income (KRW) | ≥ 4,010,000 | 1 | ||||||
| 3,010,000 ~ 4,000,000 | 0.261 | 0.207 | 1.298 | (0.866 | - | 1.946) | 0.207 | |
| 2,010,000 ~ 3,000,000 | 0.365 | 0.179 | 1.440* | (1.015 | - | 2.044) | 0.041 | |
| ≤ 2,000,000 | 0.490 | 0.149 | 1.632** | (1.220 | - | 2.185) | 0.001 | |
| Need factors | ||||||||
| Type of disability | External physical-function disabilities | 1 | ||||||
| Internal organ disabilities | −0.421 | 0.148 | 0.656** | (0.491 | - | 0.876) | 0.004 | |
| Mental disabilities | −0.726 | 0.176 | 0.484*** | (0.342 | - | 0.684) | < 0.001 | |
| Disability severity | Mild | 1 | ||||||
| Severe | 0.243 | 0.112 | 1.275* | (1.023 | - | 1.589) | 0.031 | |
| IADL | Independent | 1 | ||||||
| dependent | 0.295 | 0.127 | 1.343* | (1.047 | - | 1.721) | 0.020 | |
| SRH | Good | 1 | ||||||
| Poor | 0.554 | 0.118 | 1.740*** | (1.381 | - | 2.192) | < 0.001 | |
| Experience of depression | No | 1 | ||||||
| Yes | 0.299 | 0.149 | 1.349* | (1.007 | - | 1.805) | 0.044 | |
| transport difficulty | No difficulty | 1 | ||||||
| Difficulty | 0.537 | 0.112 | 1.711*** | (1.374 | - | 2.132) | < 0.001 | |
| Ability to go out alone | Able | 1 | ||||||
| Unable | 0.268 | 0.123 | 1.308* | (1.028 | - | 1.664) | 0.029 | |
Multivariable-adjusted OR
SRH Self-rated health, IADL Instrumental Activities of Daily Living
−2LL = 2603.077, R2 = 0.132, Hosmer–Lemeshow test: x2 = 10.922 (p = 0.206)
*p < 0.05, **p < 0.01, ***p < 0.001
Discussion
This study is the first in Korea to analyze factors associated with unmet healthcare needs among women with disabilities, applying Andersen’s Behavioral Model and using microdata from the 2023 Survey of People with Disabilities, a nationally representative dataset. To date, most prior studies have focused on specific disability types or vulnerable subgroups and have examined access to gynecologic care and reproductive health services (e.g., breast and cervical cancer) and screening for conditions such as osteoporosis, or they have been qualitative studies on healthcare accessibility [15, 27–30]. Because quantitative, empirical studies on unmet healthcare needs and barriers to healthcare among women with disabilities are largely lacking—and prior research has predominantly qualitative designs with no quantitative estimates—there are limitations in comparing our findings with the existing literature.
In this study, the prevalence of unmet healthcare needs among women with disabilities was 19.7%. In Jung et al., an analysis of the 2013–2017 Korea National Health and Nutrition Examination Surveys reported a 9.5% prevalence of unmet healthcare needs among Korean adults aged ≥ 19 years. Even when considering only the Korean context, it can be seen that women with disabilities constitute a highly vulnerable, marginalized group with respect to healthcare access [31]. According to the Proceedings of the 2025 Disability Health and Healthcare Statistics Conference (National Rehabilitation Center, Ministry of Health and Welfare), health screening uptake in 2022 was 63.5% among persons with disabilities versus 75.5% among persons without disabilities—12.0 percentage points lower among persons with disabilities [32].
According to the Disability Health and Healthcare Statistics on Korea’s national statistics portal, KOSIS [33], as of 2023 the general health screening uptake among women with disabilities was 59.6%, which was 5.7 percentage points lower than that of men with disabilities (65.3%). For female-specific cancers, the screening rates among women without disabilities were 64.7% (breast) and 60.3% (cervical), whereas among women with disabilities they were only 46.2% and 38.1%, respectively. In one study, women with disabilities also showed low rates of gynecologic care: only 27.9% reported regular gynecologic visits, 72.1% had never used specialized gynecologic services, and only 5.9% had undergone cervical cancer screening [30]. Matin et al. likewise reported that women with disabilities face serious barriers to accessing healthcare [15], and prior studies have shown that women with disabilities are at higher risk of unmet healthcare needs than men [7, 34].
Synthesizing our results, the findings are consistent with prior studies that have identified factors such as poverty, unemployment, financial dependence, being without a spouse, high transportation costs, and health insurance as major barriers to healthcare access for women with disabilities [15]. In this study, 76.3% of women with disabilities were not engaged in economic activity, and 52.8% were in the low-income group based on household income. Non-participation in economic activity and lower income were associated with unmet healthcare needs. Women with disabilities are often unemployed themselves, have family members who are unemployed, or belong to low-income households earning income in the informal sector [16, 17]. Kim et al. also found that healthcare costs were a major factor influencing unmet needs among women with disabilities [35].
Due to the dual disadvantage of being both female and having a disability, the employment rate of women with disabilities is inevitably lower than that of men with disabilities. Among persons with disabilities, the employment-to-population rate was 45.7% for men, whereas it was only 25.7% for women with disabilities [26]. According to our analysis, the leading reasons for non-employment among women with disabilities were difficulty performing job tasks due to disability (43.4%); being considered too young or too old (21.2%); not wanting or not needing to work (13.2%); and health problems (10.6%). These findings underscore the urgent need for employment measures, such as creating tailored job opportunities according to disability characteristics and severity.
In this study, women with disabilities who had external physical-function disabilities and those unable to go out alone were more likely to experience unmet healthcare needs. This may be attributable to difficulties using the lower extremities, brain lesion–related impairments, and sensory impairments such as vision or hearing loss, which can lead to limitations in activities of daily living and gait and make transportation use difficult, thereby reducing access to healthcare [35]. Women with severe disabilities are at higher risk of unmet health needs due to restrictions in daily life [35]. Mobility limitations are a major issue among adults with disabilities [36].
In addition, poor self-rated health and having experienced depression were associated with 1.7-fold and 1.3-fold higher odds of experiencing unmet healthcare needs, respectively, which is consistent with prior studies reporting that poor self-rated health and severe depression are linked to unmet healthcare needs [31, 37]. As self-rated health worsens, the healthcare needs of women with disabilities become more pressing. Moreover, as depression becomes more severe, social activity and participation tend to decline and overall health deteriorates, thereby substantially affecting healthcare access.
According to prior studies, even among women without disabilities, certain factors—older age, socioeconomic disadvantage (low income), marital status, household size, educational attainment, and job insecurity—affect healthcare access [38–42]. In particular, financial dependence and economic conditions are among the most important determinants of women’s healthcare access, regardless of disability status [38–40]. Despite these similar challenges, women with disabilities experience disproportionately greater disparities in healthcare access because of the dual burden of disability and gender-based discrimination.
To reduce disparities in healthcare access, several countries have recently standardized communication accessibility, guaranteed medical transportation, established standards for accessible diagnostic equipment, and enforced nondiscrimination effectively.
In England, the NHS Accessible Information Standard applies a uniform standard across all organizations to identify, record, flag, share, provide for, and review patients’ communication needs [43]. In the United States, Medicaid’s non-emergency medical transportation (NEMT) has been consolidated under guidance (SMD 23–006) to alleviate barriers to travel for outpatient care [44, 45], and, at the federal level, standards for accessible medical diagnostic equipment (MDE) are specified [46]. The 2024 ACA Sect. 1557 final rule more clearly prohibits discrimination on the basis of disability and sex across health programs [47]. In addition, England’s Women’s Health Strategy and the WHO Global report on health equity for persons with disabilities emphasize a systems approach of disability-inclusive governance, participation, and monitoring [48, 49]. Considering these international trends and our study findings, improving healthcare service access for women with disabilities requires the institutional guarantee of disability-friendly transportation infrastructure and mobility support; the strengthening of home-based rehabilitation and treatment services; the phased introduction and expansion of disability-friendly equipment for women with disabilities; and the strengthening of financial-protection policies. Ultimately, a tailored delivery system aligned with disability characteristics and life-course needs, built within a standardized, integrated health-service system, should be established.
Limitations
Although this study used nationally approved data designed to be representative of community-dwelling registered persons with disabilities, it has several limitations. First, because institutionalized persons with disabilities—who account for 1% of all registered persons with disabilities nationwide—were not included in the Survey, the prevalence of unmet healthcare needs may be slightly affected. Facility-based on-site care can reduce reported unmet need, but unmet need may increase as disability severity is higher and barriers to external specialty care are greater. Therefore, the findings of this study are representative of community-dwelling registered women with disabilities. Second, the cross-sectional design precludes causal inference. Third, unmet healthcare needs were assessed using a single self-reported item, which limits construct coverage (e.g., severity, timing, and specific access domains), may lead to recall bias, and can result in nondifferential misclassification, potentially attenuating the observed associations. Additionally, because proxy interviews were permitted when self-report was difficult, selection bias related to communication difficulties was mitigated; however, due to potential differences between proxy and self-reports, the possibility of measurement bias remains. Fourth, because this study was conducted based on Andersen’s Behavioral Model of Health Services Use [23–25], other potential factors that may influence unmet healthcare needs among women with disabilities (e.g., health-system and environmental factors, provider attitudes, social capital, caregiving burden) were not considered. Future research needs longitudinal studies that add detailed social determinants.
Conclusion
Based on Andersen’s Behavioral Model of Health Services Use, predictors of unmet healthcare needs among women with disabilities included lower household income; external physical-function disabilities; severe disability; inability to perform IADL independently; poor self-rated health; experience of depression; difficulty using transportation; and inability to go out alone. The main reasons for unmet healthcare needs were ‘difficulty in getting to a healthcare facility’ and ‘financial reasons,’ accounting for the majority of responses. From the perspective of enabling and need factors, interventions are warranted to expand life-course healthcare access and improve the quality of care for women with disabilities.
Authors’ contributions
MK performed project administration, software, supervision, statistical analysis, validation, visualization, writing—original draft, and writing—review & editing; HK contributed to project administration, supervision, and validation; and SHH contributed to project administration, resources, supervision, and validation. All authors reviewed the manuscript and approved the final version.
Funding
This research was funded by a grant from the Ministry of Health & Welfare (MOHW) in South Korea, grant number 2025-MOHW.
Data availability
The data used in this study are publicly available from the Korea Institute for Health and Social Affairs through the Health and Welfare Data Portal (https://www.kihasa.re.kr/dataportal/main.html). Access to the microdata requires prior approval and agreement from the data manager.
Declarations
Ethics approval and consent to participate
This study used de-identified secondary public data from a national survey. The Institutional Review Board of the National Rehabilitation Center exempted the study from review (Approval No. NRC-2025–04-027).
Consent to participate
Not applicable.
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. Final report of the Ad Hoc Committee on a Comprehensive and Integral International Convention on the Protection and Promotion of the Rights and Dignity of Persons with Disabilities. New York: UN: Annex I; 2006.
- 2.World Health Organization. Disability: Key facts. https://www.who.int/news-room/fact-sheets/detail/disability-and-health. Accessed 10 June 2025.
- 3.Park BH, Yeob KE, Choi EH, Kim SY, Park JH. Factor influencing unmet healthcare needs among people with disabilities. Health Policy Manag. 2024;34(3):271–81. [Google Scholar]
- 4.Aday LA, Andersen R. Development of indices of access to medical care. Chicago: Health Administration Press; 1975. [Google Scholar]
- 5.Cunningham PJ, Hadley J, Kenny G, Davidoff AJ. Identifying affordable sources of medical care among uninsured persons. Health Serv Res. 2007;42(1 Pt 1):265–85. 10.1111/j.1475-6773.2006.00603.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Sanmartin C, Pierre F, Tremblay S. Waiting for care in Canada: findings from the health services access survey. Healthcare Policy | Politiques de Santé. 2006;2(2):43. [PMC free article] [PubMed] [Google Scholar]
- 7.McColl MA, Jarzynowska A, Shortt S. Unmet health care needs of people with disabilities: population level evidence. Disabil Soc. 2010;25(2):205–18.
- 8.Sapag JC, Herrera CA, Gómez NR, Caneo C, Poblete FC, Alberti VF, et al. Barriers in access to healthcare for women with disabilities: a systematic review in qualitative studies. Int J Equity Health. 2023;22(1):197.37759247 [Google Scholar]
- 9.World Health Organization. World disability report. Geneva: World Health Organization; 2011. [Google Scholar]
- 10.Sakellariou D, Rotarou ES. Access to healthcare for men and women with disabilities in the UK: secondary analysis of cross-sectional data. BMJ Open. 2017;7:e016614. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Khoury AJ, Hall A, Andresen E, Zhang J, Ward R, Jarjoura C. The association between chronic disease and physical disability among female Medicaid beneficiaries 18–64 years of age. Disabil Health J. 2013;6(2):141–8. [DOI] [PubMed] [Google Scholar]
- 12.Centers for Disease Control and Prevention. Women’s health: supporting women with disabilities to achieve optimal health. https://www.cdc.gov/womens-health/features/women-disabilities.html. Accessed 30 July 2025.
- 13.Maxwell J, Watts Belser J, David D. A health handbook for women with disabilities. Berkeley, CA: Hesperian Foundation; 2007.
- 14.Oh HY. The right to health for women with disabilities: focusing on their experiences. Gender Cult. 2016;9(1):131–60. [Google Scholar]
- 15.Matin BK, Williamson HJ, Karyani AK, et al. Barriers in access to healthcare for women with disabilities: a systematic review in qualitative studies. BMC Womens Health. 2021;21:44. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Gartrell A, Baesel K, Becker C. “We do not dare to love”: women with disabilities’ sexual and reproductive health and rights in rural Cambodia. Reprod Health Matters. 2017;25(50):31–42. [DOI] [PubMed] [Google Scholar]
- 17.Soltani S, Takian A, Akbari Sari A, Majdzadeh R, Kamali M. Cultural barriers in access to healthcare services for people with disability in Iran: a qualitative study. Med J Islam Repub Iran. 2017;31:51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Prevatt B. Gynecological care for women with mental retardation. J Obstet Gynecol Neonatal Nurs. 1998;27(3):251–6. [DOI] [PubMed] [Google Scholar]
- 19.Seiedzadeh M, Khanjani MS, Abdi K, Latifian M. Content analysis of barriers to delivering maternity care to women with physical disabilities: a qualitative study. BMC Public Health. 2025;25:1208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Elkins TE, McNeeley SG, Rosen D, Heaton C, Sorg C, DeLancey JOL, et al. A clinical observation of a program to accomplish pelvic exams in difficult-to-manage patients with mental retardation. Adolesc Pediatr Gynecol. 1988;1(3):195–8. [Google Scholar]
- 21.Mitra M, Smith LD, Smeltzer SC, Long-Bellil LM, Sammet Moring N, Iezzoni LI. Barriers to providing maternity care to women with physical disabilities: perspectives from health care practitioners. Disabil Health J. 2017;10(3):445–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Schildberger B, Zenzmaier C, Konig-Bachmann M. Experiences of Austrian mothers with mobility or sensory impairments during pregnancy, childbirth and the puerperium: a qualitative study. BMC Pregnancy Childbirth. 2017;17(1):201. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Andersen R. A behavioral model of families’ use of health service. Chicago: Center for Health Administration Studies; 1968. [Google Scholar]
- 24.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]
- 25.Andersen R, Newman JF. Societal and individual determinants of medical care utilization in the United States. Milbank Q. 1973;51(1):95–124. [PubMed] [Google Scholar]
- 26.Ministry of Health and Welfare, Korea Institute for Health and Social Affairs. National survey on persons with disabilities. Sejong: Ministry of Health and Welfare; 2023. https://www.kihasa.re.kr/publish/report/all/list.
- 27.Shin DW, Lee JW, Jung JH, Han K, Kim SY, Choi KS, et al. Disparities in cervical cancer screening among women with disabilities: a national database study in South Korea. J Clin Oncol. 2018;36(27):2778–86. [DOI] [PubMed] [Google Scholar]
- 28.Ganle JK, Otupiri E, Obeng B, Edusie AK, Ankomah A, Adanu R. Challenges women with disability face in accessing and using maternal healthcare services in Ghana: a qualitative study. PLoS One. 2016;11(6):e0158361. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Jara-Rosales S, Rotarou ES. Cervical cancer screening uptake among women with disabilities: findings from a cross-sectional study in Chile. Int J Environ Res Public Health. 2024;21(12):1578. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Ameer Jaafar Z, Salman DA, Obeid RZ, et al. Healthcare disparities in gynecological health services for women with disabilities: a cross-sectional study from Iraq. BMC Womens Health. 2025;25:323. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Jung B, Ha IH. Determining the reasons for unmet healthcare needs in South Korea: a secondary data analysis. Health Qual Life Outcomes. 2021;19(1):99. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.National Rehabilitation Center. Proceedings of the 2025 Disability Health and Healthcare Statistics Conference. Seoul, Republic of Korea: Ministry of Health and Welfare, National Rehabilitation Center; 2025. https://tinyurl.com/2m9h8fak.
- 33.Korean Statistical Information Service (KOSIS). https://kosis.kr/statisticsList/statisticsListIndex.do?vwcd=MT_ZTITLE&menuId=M_01_01. Accessed 3 August 2025.
- 34.Hwang B, Chun SM, Park JH, Shin HI. Unmet healthcare needs in people with disabilities: comparison with the general population in Korea. Ann Rehabil Med. 2011;35(5):627–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Kim H, Jung YH, Park S, et al. Effects of disability-related limitations in daily living on unmet needs: a longitudinal study. BMC Public Health. 2024;24:351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Okoro CA, Hollis ND, Cyrus AC, Griffin-Blake S. Prevalence of disabilities and health care access by disability status and type among adults—United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(32):882. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Starkes JM, Poulin CC, Kisely SR. Unmet need for the treatment of depression in Atlantic Canada. Can J Psychiatry. 2005;50(10):580–90. [DOI] [PubMed] [Google Scholar]
- 38.Seccombe K, Beeghley L. Gender and medical insurance: a test of human capital theory. Gender Soc. 1992;6(2):283–300. [Google Scholar]
- 39.Clancy CM, Massion CT. American women’s health care: a patchwork quilt with gaps. JAMA. 1992;268(14):1918–20. [PubMed] [Google Scholar]
- 40.Hsia J, Kemper E, Kiefe C, Zapka J, Sofaer S, Pettinger M, et al. The importance of health insurance as a determinant of cancer screening: evidence from the women’s health initiative. Prev Med. 2000;31(3):261–70. [DOI] [PubMed] [Google Scholar]
- 41.Aldridge ML, Daniels JL, Jukic AM. Mammograms and healthcare access among US Hispanic and non-Hispanic women 40 years and older. Fam Community Health. 2006;29(2):80–8. [DOI] [PubMed] [Google Scholar]
- 42.Liao MN, Chen MF, Chen SC, Chen PL. Healthcare and support needs of women with suspected breast cancer. J Adv Nurs. 2007;60(3):289–98. [DOI] [PubMed] [Google Scholar]
- 43.NHS England. Accessible Information Standard – requirements (DAPB1605). London: NHS England; 2025. https://www.england.nhs.uk/long-read/accessible-information-standard-requirements-dapb1605/.
- 44.Centers for Medicare & Medicaid Services. Assurance of Transportation: A Medicaid Transportation Coverage Guide (SMD #23-006). Baltimore (MD): CMS; 2023.
- 45.Medicaid.gov. Assurance of Transportation. Baltimore (MD): Centers for Medicare & Medicaid Services; 2023–2025. https://www.medicaid.gov/medicaid/benefits/assurance-of-transportation.
- 46.U.S. Access Board. Standards for Accessible Medical Diagnostic Equipment; Final Rule. Federal Register. 2024;89(143). [PubMed]
- 47.U.S. Department of Health and Human Services, Office for Civil Rights. Nondiscrimination in Health Programs and Activities; Final Rule (ACA Section 1557). Federal Register. 2024;89(88).
- 48.Department of Health and Social Care (UK). Women’s Health Strategy for England. London: DHSC; 2022. https://www.gov.uk/government/publications/womens-health-strategy-for-england/womens-health-strategy-for-england.
- 49.World Health Organization. Global report on health equity for persons with disabilities. Geneva: WHO; 2022.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used in this study are publicly available from the Korea Institute for Health and Social Affairs through the Health and Welfare Data Portal (https://www.kihasa.re.kr/dataportal/main.html). Access to the microdata requires prior approval and agreement from the data manager.