ABSTRACT
Objectives
To provide policy‐relevant evidence to reduce oral health disparities and improve dental care accessibility by considering characteristics of urban and rural areas.
Background
Individual and regional factors influence dental care access. Regional poverty and limited dental resources among older adults may contribute to unmet dental care needs due to cost.
Materials and Methods
A multilevel logistic regression analysis was conducted to examine the association between regional factors (regional deprivation, number of dentists per 10,000 and number of dental offices per 100,000) and unmet dental care needs due to cost. The analysis was adjusted for individual factors, such as sex, education, marital status, household income, subjective health status, chewing difficulty and limited daily activities, as determined by the 2021 Korean Community Health Survey (KCHS; n = 47,802).
Results
The prevalence of unmet dental care needs due to cost was 4.94% in urban and 4.80% in rural older adults. Individuals who lived in higher regional deprivation (poorer regions) were less likely to experience unmet dental care needs due to cost (OR = 0.66, 95% CI = 0.47–0.94) only in rural areas. Individuals residing in areas with a higher number of dentists per 10,000 were more likely to experience unmet dental care needs due to cost in urban (OR = 2.19, 95% CI = 1.01–4.73) and rural (OR = 1.97; 95% CI = 1.16–3.34). Household income and oral health status were the strongest predictors of unmet dental care needs due to cost.
Conclusions
The influence of regional poverty, dentist distribution and individual factors should be considered in developing policies to reduce the unmet dental care needs of older Koreans.
Keywords: affordability, dental care for aged, dentistry, multilevel analysis, older adults
1. Introduction
The health disparity between urban and rural areas has emerged as a significant public health issue, particularly given the rapid pace of urbanisation and development in modern society. Urban and rural areas significantly differ in terms of environment, economic conditions and access to healthcare, resulting in differences in the health status of their populations [1]. Residents in urban areas have high accessibility to healthcare facilities and services, including established support systems and diverse health resources. By contrast, residents of rural areas often have low healthcare accessibility due to geographic isolation and limited resources, potentially resulting in inadequate healthcare services [1, 2]. Thus, in resource‐limited areas such as rural regions, the utilisation rate of local health institutions, such as public health centres, tends to be higher than in metropolitan areas [3, 4]. Understanding the regional context of urban and rural areas is essential in the development of healthcare policies to decrease the regional gap in health.
The rate of unmet dental care needs as expressed by the oral health equity index [5, 6] refers to situations in which individuals with a perceived need for dental care do not receive appropriate services, due to economic, physical or geographical barriers [7]. Older adults, whose income typically declines post‐retirement, may be financially burdened by additional healthcare expenses such as dental care [8]. The resulting unmet need can lead to more severe oral health issues, thus creating a vicious cycle of higher dental healthcare costs [9]. Addressing dental health problems in older adults also alleviates the incidence of general diseases and supports health maintenance [10, 11], thus reducing societal healthcare costs. Therefore, analysing unmet dental care needs related to financial barriers can inform policies to improve overall healthcare costs.
Although individual and regional factors influence unmet dental care needs due to cost, previous studies have predominantly focused on individual‐level factors [12, 13, 14, 15]. Few studies have included regional factors as variables that may affect the unmet dental care needs of older adults [16, 17]; however, most did not consider the economic status of the region [16, 17] and used only limited indicators, such as community environment satisfaction [17]. Thus, this study aims to analyse the association between unmet dental care needs due to cost among older adults living in urban and rural areas and various regional factors, including the regional deprivation index, which has not been sufficiently addressed in prior studies [12, 13, 14, 15, 16, 17].
2. Materials and Methods
2.1. Data Collection and Sources
Multilevel cross‐sectional analyses were conducted based on data from the Korea Community Health Survey (KCHS) and the Korea Statistical Information Service (KOSIS). Maintained by the Korea Disease Control and Prevention Agency (KDCA) since 2008, the KCHS collects annual health data from adults 19 years of age and older across all local municipalities in South Korea. To ensure a representative sample, roughly 900 households per public health centre were selected using a multistage probability sampling method. Data were gathered through in‐person interviews (electronic surveys) performed by trained regional interviewers. As of 2021, the survey included 229,242 respondents. After excluding the population under 65 and those with incomplete responses related to unmet dental care needs and other variables, the present study was based on 47,802 individuals.
2.2. Measures
2.2.1. Dependent Variable
The dependent variable, unmet dental care needs due to cost, was assessed using self‐responses to the following questions, asked in person: ‘In the last year, have you been unable to go to the dental clinic or the hospital when you needed to?’ Those who responded ‘Yes’ and cited ‘for financial reasons’ as the cause were identified as having unmet dental care needs.
2.2.2. Independent Variables
In this study, independent variables were classified based on Andersen's behavioural model, which was proposed to explain healthcare utilisation patterns and describe why individuals use healthcare services [18].
Seven individual and three regional variables were selected as independent variables (Figure 1). The individual variables were drawn from the 2021 KCHS. Individual variables were grouped into predisposing, enabling and needs factors. Predisposing characteristics included sex (male, female), education (middle school or lower, high school or higher) and marital status (have a spouse) (yes, no). Enabling factors consisted of household income (in South Korean won, KRW): < 1,000,000; 1,000,000–3,000,000; and > 3000,000. Needs factors included subjective oral health status (good, bad), chewing problems (yes, no) and limitations in daily activities (yes, no).
FIGURE 1.
Conceptual model of individual and regional level characteristics on access to unmet dental care needs. The dark grey arrows represent Model 1, which includes individual factors, while the white arrows represent Model 2, which includes individual and regional factors.
For regional variables, data were obtained from the KOSIS and related to primary local government units. Regional factors included regional deprivation and the number of dentists per 10,000 and dentist offices per 100,000 people. The regional deprivation index used in this study is a multidimensional indicator reflecting the socioeconomic characteristics of a region, and it can broadly serve as a regional‐level variable that complements individual‐level socioeconomic indicators and comprehensively assesses the economic context of communities [19, 20]. Due to the lack of an officially measured deprivation index in South Korea, the data obtained by the Busan Public Health Policy Institute, based on the 2020 Population Census, were utilised. The index included indicators such as the proportion of individuals with less than a high school education, low social class (based on the household head), older population, single‐person households, homeownership rate, apartment household ratio, female household heads, divorce/widowhood rates and lack of a household car [21]. We classified the 1st quartile as areas with the least deprivation (more affluent) and the 4th quartile as areas with the most deprivation (poorer) [19, 20]. The number of dentists per 10,000 and dental offices per 100,000 people were expressed in quartiles with the 1st quartile as areas with the lowest and the 4th quartile with the highest values.
2.3. Analysis
The sample for the KCHS was extracted using a complex sample design, applying weights to ensure the sample's representativeness [13, 14, 16, 17, 20]. A multilevel analysis was performed, and three models were tested: a null model; Model 1, including individual factors; and Model 2, which added regional factors to Model 1 (Figure 1). The model was evaluated as follows. First, multicollinearity was assessed to ensure that the number of variance inflation factors (VIF) remained below 15. Second, the need for multilevel modelling was evaluated by calculating the intraclass correlation coefficients (ICC) using the formula σ 2 μ/(3.29 + σ 2 μ), where σ 2 μ represents the variance at the regional level and 3.29 is the variance of the logistic distribution at the individual level [22, 23]. Third, the −2 log likelihood (deviance) test was run, with smaller values indicating model adequacy. We analysed the data using SAS version 9.4.
2.4. Ethical Aspects
This study was exempt from review by the Chungnam National University Institutional Review Board (IRB) (approval provided on 22 August 2024; 202408‐SB‐115‐01) and did not require informed consent due to the use of secondary data.
3. Results
Table 1 presents the results of a complex sample χ 2 test for the individual and regional characteristics of the study population. The prevalence of unmet dental care needs due to cost was 4.9% in urban and 4.8% in rural areas. Among the individual predisposing factors, older women had higher unmet dental care needs due to cost than older men in urban and rural areas. Individuals with a lower education level had higher unmet dental care needs due to cost in both areas. Unmet dental care needs due to cost were also higher in individuals who do not have a spouse than in those who do. Among the enabling factors, unmet dental care needs due to cost were higher in households with a lower income in urban and rural areas. Among the needs factors, unmet dental care needs due to cost were higher in individuals reporting a ‘bad’ subjective oral health status, chewing problems, and limited daily activities. In urban areas, individuals in regions with the lowest number of dental offices per 100,000 reported more unmet dental care needs due to cost (p < 0.01). In contrast, in rural areas, individuals living in regions with the highest number of dental offices reported a higher prevalence of unmet dental care needs due to cost (p < 0.01).
TABLE 1.
Distribution of unmet dental care needs due to cost by general characteristics among Korean older adults. Units: weighted, n (%).
| Variables | Urban | Rural | ||||||
|---|---|---|---|---|---|---|---|---|
| Unmet | Met | Unmet | Met | |||||
| Individual level (1‐level) | ||||||||
| Predisposing factors | ||||||||
| Sex | ||||||||
| Men | 408 | (3.9) | 9450 | (96.1) | 405 | (4.2) | 10,011 | (95.8) |
| Women | 717 | (5.8) | 12,172 | (94.2) | 740 | (5.3) | 13,899 | (94.7) |
| p | *** | * | ||||||
| Education | ||||||||
| High school or higher | 270 | (3.1) | 8358 | (96.9) | 111 | (2.4) | 4834 | (97.6) |
| Middle school or lower | 855 | (6.3) | 13,264 | (93.7) | 1034 | (5.5) | 19,076 | (94.5) |
| p | *** | *** | ||||||
| Marital status (have a spouse) | ||||||||
| Yes | 509 | (3.4) | 14,551 | (96.5) | 525 | (3.5) | 15,317 | (96.5) |
| No | 616 | (8.1) | 7071 | (91.9) | 620 | (7.3) | 8593 | (92.7) |
| p | *** | *** | ||||||
| Enabling factors | ||||||||
| Household income | ||||||||
| Upper 3000 | 140 | (2.4) | 6145 | (97.6) | 72 | (3.2) | 3600 | (96.8) |
| 1000–3000 | 406 | (4.0) | 10,256 | (96.0) | 349 | (3.1) | 10,060 | (96.9) |
| Lower 1000 | 579 | (10.3) | 5221 | (89.7) | 724 | (7.4) | 10,250 | (92.5) |
| p | *** | *** | ||||||
| Needs factors | ||||||||
| Subjective oral health status | ||||||||
| Good | 26 | (0.5) | 4296 | (99.5) | 20 | (0.5) | 3976 | (99.5) |
| Bad | 1099 | (6.0) | 17,326 | (94.0) | 1125 | (5.7) | 19,934 | (94.3) |
| p | *** | *** | ||||||
| Chewing problem | ||||||||
| No | 252 | (1.6) | 15,123 | (98.4) | 179 | (1.4) | 14,755 | (98.6) |
| Yes | 873 | (12.2) | 6499 | (87.8) | 966 | (10.3) | 9155 | (89.7) |
| p | *** | *** | ||||||
| Limited daily activities | ||||||||
| No | 642 | (3.7) | 17,045 | (96.3) | 582 | (3.6) | 16,630 | (96.4) |
| Yes | 483 | (9.5) | 4577 | (90.5) | 563 | (7.8) | 7280 | (92.2) |
| p | *** | *** | ||||||
| Regional level (2‐level) | ||||||||
| Regional deprivation | ||||||||
| Q1 | 320 | (4.8) | 6190 | (95.2) | 112 | (5.1) | 2198 | (94.9) |
| Q2 | 378 | (5.0) | 7132 | (95.0) | 106 | (5.7) | 2727 | (94.3) |
| Q3 | 319 | (5.1) | 6297 | (94.9) | 341 | (4.3) | 6576 | (95.7) |
| Q4 | 108 | (4.3) | 2003 | (95.7) | 586 | (4.6) | 12,409 | (95.4) |
| p | 0.68 | 0.08 | ||||||
| No. of dentists per 10,000 | ||||||||
| Q1 | 67 | (5.1) | 1324 | (94.9) | 562 | (4.1) | 12,307 | (95.9) |
| Q2 | 227 | (4.5) | 4642 | (95.5) | 331 | (4.4) | 7443 | (95.6) |
| Q3 | 359 | (5.5) | 6116 | (94.5) | 188 | (5.0) | 3350 | (95.0) |
| Q4 | 472 | (4.8) | 9540 | (95.3) | 64 | (13.2) | 810 | (86.8) |
| p | 0.06 | |||||||
| No. of dental offices per 100,000 | ||||||||
| Q1 | 56 | (5.8) | 999 | (94.2) | 609 | (4.2) | 13,174 | (95.8) |
| Q2 | 176 | (4.3) | 3595 | (95.7) | 390 | (4.8) | 7884 | (95.2) |
| Q3 | 422 | (5.7) | 7042 | (94.3) | 146 | (6.1) | 2852 | (93.9) |
| Q4 | 471 | (4.5) | 9986 | (95.5) | NA | |||
| p | ** | ** | ||||||
| Total | 1125 | (4.9) | 21,622 | (95.1) | 1145 | (4.8) | 23,910 | (95.2) |
Note: *p < 0.05, **p < 0.01, ***p < 0.001.
Table 2 presents the multilevel analysis of the models of unmet dental care needs due to cost. In urban areas, the ICC was 0.06 according to a variance of 0.19 in the null model, such that the contribution of the variance between regions to the total variance was 6.0%. At the individual level, all variables except sex and education level had a statistically significant association with unmet dental care needs due to cost. Among the enabling factors, household income had a highly significant effect on unmet dental care needs due to cost, as determined by the odds ratio (OR) and 95% confidence interval (CI): 1,000,000–3,000,000 KRW (OR = 1.6, 95% CI: 1.3–1.9), below 1,000,000 KRW (OR = 2.7, 95% CI:2.2–3.3). Among the needs variables, oral health status variables were strongly related to unmet dental care needs due to cost: poorer subjective oral health (OR = 3.7, 95% CI: 2.5–5.5), discomfort in chewing (OR = 5.1, 95% CI: 4.4–6.0), and limitations in daily activities (OR = 1.5, 95% CI: 1.3–1.7). At the regional level, there was no significant association between regional deprivation and unmet needs. The higher number of dentists per 10,000 had more likely to experience unmet dental care needs (OR = 2.2 for the highest vs. the lowest quartile; 95% CI = 1.0–4.7).
TABLE 2.
Multilevel analysis of unmet dental care needs according to region (rural, urban).
| Variables | Urban | Rural | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Null | Model 1 | Model 2 | Null | Model 1 | Model 2 | |||||
| Individual level (1‐level) | ||||||||||
| Predisposing factors | ||||||||||
| Sex | ||||||||||
| Women (vs. Men) | 1.0 | (0.8–1.1) | 1.0 | (0.8–1.1) | 0.8 | (0.7–1.0) | 0.8 | (0.7–1.0) | ||
| Education | ||||||||||
| Middle school or lower (vs. High school or higher) | 1.1 | (0.9–1.3) | 1.1 | (1.0–1.3) | 1.3 | (1.1–1.6) | 1.3 | (1.1–1.6) | ||
| Marital status (have a spouse) | ||||||||||
| No (vs. Yes) | 1.5 | (1.3–1.8) | 1.5 | (1.3–1.8) | 1.5 | (1.3–1.7) | 1.5 | (1.3–1.7) | ||
| Enabling factors | ||||||||||
| Household income | ||||||||||
| 1000–3000 | 1.6 | (1.3–1.9) | 1.6 | (1.3–1.9) | 1.5 | (1.2–2.0) | 1.5 | (1.2–2.0) | ||
| ≤ 1000 (vs. ≥ 3000) | 2.7 | (2.2–3.3) | 2.7 | (2.2–3.3) | 2.1 | (1.5–2.6) | 2.0 | (1.6–2.7) | ||
| Needs factors | ||||||||||
| Subjective oral health status | ||||||||||
| Bad (vs. Good) | 3.7 | (2.5–5.5) | 3.7 | (2.5–5.5) | 3.5 | (2.2–5.5) | 3.4 | (2.2–5.4) | ||
| Chewing difficulty | ||||||||||
| Yes (vs. No) | 5.1 | (4.4–6.0) | 5.1 | (4.4–6.0) | 6.4 | (5.4–7.6) | 6.4 | (5.4–7.6) | ||
| Limited daily activities | ||||||||||
| Yes (vs. No) | 1.5 | (1.3–1.7) | 1.5 | (1.3–1.7) | 1.2 | (1.0–1.4) | 1.2 | (1.0–1.4) | ||
| Regional level (2‐level) | ||||||||||
| Regional deprivation | ||||||||||
| Q2 | 0.9 | (0.7–1.1) | 0.7 | (0.5–1.1) | ||||||
| Q3 | 0.9 | (0.7–1.2) | 0.8 | (0.6–1.1) | ||||||
| Q4 (Most) (vs. Q1 least) | 0.8 | (0.6–1.2) | 0.7 | (0.5–0.9) | ||||||
| No. of dentists per 10,000 | ||||||||||
| Q2 | 1.4 | (0.7‐2.8) | 0.9 | (0.7–1.3) | ||||||
| Q3 | 1.8 | (0.9–3.8) | 1.1 | (0.8–1.7) | ||||||
| Q4 (Highest) (vs. Lowest) | 2.2 | (1.0–4.7) | 2.0 | (1.2–3.3) | ||||||
| No. of dental offices per 100,000 | ||||||||||
| Q2 | 0.6 | (0.3–1.3) | 1.1 | (0.8–1.4) | ||||||
| Q3 | 0.7 | (0.3–1.5) | 1.1 | (0.7–1.6) | ||||||
| Q4 (Highest) (vs. Lowest) | 0.5 | (0.2–1.1) | NA | |||||||
| Variance | 0.19 | 0.20 | 0.18 | 0.23 | 0.28 | 0.24 | ||||
| ICC | 0.06 | 0.06 | 0.05 | 0.07 | 0.08 | 0.07 | ||||
| –2log likelihood | 8855.3 | 7501.8 | 7491.9 | 9174.7 | 8001.0 | 7986.1 | ||||
Note: Significant differences in the analysed variables are indicated in bold.
In rural areas, the ICC was 0.07 according to a variance of 0.23, such that the contribution of the variance between regions to the total variance was 6.6%. All predisposing factors (including sex, education level and marital status) were associated with unmet dental care needs due to cost. Among the enabling factors, the lower the household income level, the greater the unmet dental care needs due to cost. Among the needs variables, oral health status was most strongly related to unmet dental care needs, including poorer subjective oral health (OR = 3.4, 95% CI: 2.2–5.4), discomfort in chewing (OR = 6.4, 95% CI: 5.4–7.6), and limited daily activities (OR = 1.2, 95% CI: 1.0–1.4). Notably, regarding the regional economic factor, regional deprivation was inversely associated with unmet dental care needs due to cost (OR = 0.7 for the most quartile [poorer] compared to the least [more affluent]). Unmet dental care needs due to cost were highest when the density of dentists per 10,000 was in the 4th quartile (highest) than the 1st quartile (lowest) (OR = 2.0, 95% CI: 1.2–3.3).
4. Discussion
We examined the individual and regional factors associated with cost‐related unmet dental care needs among older adults living in urban and rural areas. There were three main findings: (1) those living in higher regional deprivation (poorer regions) had a lower likelihood of experiencing unmet dental care needs due to cost, but only in rural areas, (2) those residing in either urban or rural areas with higher dentist‐to‐population ratios were more likely to experience unmet needs, and (3) household income and oral health status were most strongly associated with unmet dental care needs due to cost.
The main findings of our study are discussed as follows: First, in rural areas, a higher regional deprivation in rural areas was inversely associated with unmet dental care needs due to costs. Although research on the association between the regional deprivation index and unmet dental care needs due to cost is limited, our findings can be explained for two reasons: (1) The awareness of dental care may be lower among residents in areas with a high regional deprivation index. A previous study showed that the greater the need for dental treatment, the higher the rate of dental care utilisation [24], which implies that the appropriate use of dental services can help resolve unmet dental care needs as perceived by the individual. However, in areas with a high regional deprivation index and limited dental care access, such as rural areas, oral health may be deprioritised, as it is less urgent than life‐threatening emergencies. (2) Redistributing medical resources in areas with a high regional deprivation index is likely to be more effective in rural areas than in urban areas. Regions with high deprivation have less dental care utilisation, including oral examinations [19, 25]. To address this issue, many OECD countries have implemented strategies such as remote dental care and enhanced dental coverage in vulnerable areas, particularly in rural or racially isolated communities [26]. In South Korea, regional disparities in medical care and resource allocation have been addressed through measures such as the Regional Public Health Act (1996) and the Special Act for Health Care in Rural Areas (1980). Despite existing policies, lower‐income individuals in deprived rural areas continue to experience significant unmet dental care needs. This suggests that economic barriers persist alongside geographic disparities. Interventions should enhance access to services and provide financial support tailored to lower‐income populations to improve dental care equity.
Second, as the number of dentists in urban and rural areas increased, the rate of unmet dental care needs due to costs increased. The results of this study differ from previous studies, which show that a higher number of dentists leads to higher dental care utilisation rates [27, 28]. Our results suggest that differences in the regional characteristics of urban and rural areas lead to different experiences: (1) In urban areas, unmet dental care needs may arise due to the concentration of dental resources and excessive competition between medical institutions. Areas that are likely urban or affluent have a high density of dental resources, and providers may encourage visits or promote non‐covered treatments to generate revenue [29]. (2) In rural areas, the concentration imbalance of medical institutions leads to unmet dental care needs. This situation can be understood through the ‘Matthew effect’, in which regions well equipped with infrastructure—such as the number of hospital beds and access to medical services—tend to develop further, whereas poorer regions face more significant shortages of medical resources. In other words, an increase in the number of dentists in rural areas may improve access to dental care to some extent [26]; the concentration of resources in specific locations (primarily town centres) [30] can exacerbate disparities in the distribution of medical resources within rural areas. Additionally, in rural areas, high‐income individuals often travel greater distances to access medical institutions than low‐income individuals [30, 31, 32]. This disparity in access based on income can further widen the gap in unmet dental care needs within the rural community.
Third, among the individual factors, household income and oral health status (subjective oral health status, chewing difficulty) were the strongest predictors of unmet needs, consistent with previous studies [13, 14, 33, 34]. The significance of these subjective variables highlights the importance of considering patient‐reported outcomes alongside clinical measures when addressing unmet dental care needs [33]. Given that self‐perceived oral health influences treatment‐seeking behaviour [14, 34], interventions should integrate patient perspectives and clinical evaluations to ensure comprehensive care. To address these issues, we recommend expanding financial support, such as public dental insurance and subsidies for low‐income groups, while implementing targeted education programs to improve oral health literacy, preventive care and patient engagement in treatment decisions.
The limitations of this study should be noted. In particular, a causal association between unmet dental care needs due to costs and the influencing factors could not be established because the data were cross‐sectional. In addition, not all variables associated with unmet dental care needs were included in the present study due to limited resources. Therefore, future research should be based on longitudinal data, such as cohort studies, and conduct in‐depth analyses of the variables associated with unmet dental care needs due to cost to provide a more comprehensive understanding of this issue.
Our study is the first to analyse how regional deprivation and urban–rural differences affect unmet dental care needs due to costs among older adults living in urban and rural areas. The results provide a foundational resource for improving dental care accessibility across regions tailored to the characteristics of urban and rural areas.
5. Conclusion
Regional factors, including regional deprivation and the number of dentists, influence unmet dental care needs among older adults in urban and rural areas. These findings emphasise the need for targeted interventions that address regional disparities to improve dental care access.
Author Contributions
Ji‐Yeon Lim: writing – original draft, formal analysis, data curation, investigation. Ju‐Mi Lee: writing – review and editing, supervision, conceptualisation, project administration, resources. Hae‐Sung Nam: writing – review and editing, supervision, conceptualisation, project administration, resources.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgements
The authors have nothing to report.
Funding: The authors received no specific funding for this work.
Contributor Information
Ju‐Mi Lee, Email: jmlee01@cnu.ac.kr.
Hae‐Sung Nam, Email: hsnam@cnu.ac.kr.
Data Availability Statement
The Community Health Survey data provided by the Korea Disease Control and Prevention Agency (KDCA) with approval cannot be publicly shared. However, data obtained from the Korean Statistical Information Service (KOSIS) (https://kosis.kr/index/index.do) and the Busan Public Health Policy Institute are publicly (https://www.bhi.or.kr/bppi/main.do) available and can be downloaded from their respective websites.
References
- 1. Gaber A., Galarneau C., Feine J. S., and Emami E., “Rural–Urban Disparity in Oral Health‐Related Quality of Life,” Community Dentistry and Oral Epidemiology 46, no. 2 (2018): 132–142, 10.1111/cdoe.12344. [DOI] [PubMed] [Google Scholar]
- 2. Douthit N., Kiv S., Dwolatzky T., and Biswas S., “Exposing Some Important Barriers to Health Care Access in the Rural USA,” Public Health 129, no. 6 (2015): 611–620, 10.1016/j.puhe.2015.04.001. [DOI] [PubMed] [Google Scholar]
- 3. Nuako A., Liu J., Pham G., et al., “Quantifying Rural Disparity in Healthcare Utilization in the United States: Analysis of a Large Midwestern Healthcare System,” PLoS One 17, no. 2 (2022): e0263718, 10.1371/journal.pone.0263718. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Park E.‐A. and Choi S.‐Y., “Analysis of Factors Influencing the Utilization Rate of Public Health Centers in Korea,” Journal of the Korea Academia‐Industrial Cooperation Society 20, no. 3 (2019): 203–215, 10.5762/KAIS.2019.20.3.203. [DOI] [Google Scholar]
- 5. Shetty A., Bhandary R., Ahuja D., et al., “The Impact of Unmet Treatment Need on Oral Health Related Quality of Life: A Questionnaire Survey,” BMC Oral Health 24, no. 1 (2024): 432, 10.1186/s12903-024-04169-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Kailembo A., Preet R., and Stewart Williams J., “Socioeconomic Inequality in Self‐Reported Unmet Need for Oral Health Services in Adults Aged 50 Years and Over in China, Ghana, and India,” International Journal for Equity in Health 17 (2018): 1–14, 10.1186/s12939-018-0812-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Joudi A., Sargeran K., and Hessari H., “To Appreciate the Influence of Contributed Determinants on Dental Care Utilization in the Context of Socioeconomic Inequalities,” International Journal for Equity in Health 23, no. 1 (2024): 141, 10.1186/s12939-024-02220-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Boissonneault M., Mulders J. O., Turek K., and Carriere Y., “A Systematic Review of Causes of Recent Increases in Ages of Labor Market Exit in OECD Countries,” PLoS One 15, no. 4 (2020): e0231897, 10.1371/journal.pone.0231897. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Griffin S. O., Jones J. A., Brunson D., Griffin P. M., and Bailey W. D., “Burden of Oral Disease Among Older Adults and Implications for Public Health Priorities,” American Journal of Public Health 102, no. 3 (2012): 411–418, 10.2105/AJPH.2011.300362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Atanda A. J., Livinski A. A., London S. D., et al., “Tooth Retention, Health, and Quality of Life in Older Adults: A Scoping Review,” BMC Oral Health 22, no. 1 (2022): 185, 10.1186/s12903-022-02210-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Janto M., Iurcov R., Daina C. M., et al., “Oral Health Among Elderly, Impact on Life Quality, Access of Elderly Patients to Oral Health Services and Methods to Improve Oral Health: A Narrative Review,” Journal of Personalized Medicine 12, no. 3 (2022): 372, 10.3390/jpm12030372. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Taylor H., Holmes A. M., and Blackburn J., “Prevalence of and Factors Associated With Unmet Dental Need Among the US Adult Population in 2016,” Community Dentistry and Oral Epidemiology 49, no. 4 (2021): 346–353, 10.1111/cdoe.12607. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Kim N., Kim C.‐y., and Shin H., “Inequality in Unmet Dental Care Needs Among South Korean Adults,” BMC Oral Health 17 (2017): 1–9, 10.1186/s12903-017-0370-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Chae S., Lee Y., Kim J., Chun K. H., and Lee J. K., “Factors Associated With Perceived Unmet Dental Care Needs of Older Adults,” Geriatrics & Gerontology International 17, no. 11 (2017): 1936–1942, 10.1111/ggi.12997. [DOI] [PubMed] [Google Scholar]
- 15. Jang Y., Yoon H., Park N. S., Chiriboga D. A., and Kim M. T., “Dental Care Utilization and Unmet Dental Needs in Older Korean Americans,” Journal of Aging and Health 26, no. 6 (2014): 1047–1059, 10.1177/0898264314538663. [DOI] [PubMed] [Google Scholar]
- 16. Kim W. J. and Shin Y. J., “A Multi‐Level Analysis of Factors Affecting the Unmet Needs of Dental Care Service: Focusing on Comparison by Age Group,” Journal of Korean Academy of Oral Health 45, no. 3 (2021): 126–137, 10.11149/jkaoh.2021.45.3.126. [DOI] [Google Scholar]
- 17. Kim M. Y. and Kim J. H., “Relationship Between Unmet Dental Needs and Social Determinants of Health,” Journal of the Korea Contents Association 20, no. 2 (2020): 360–370, 10.5392/JKCA.2020.20.02.360. [DOI] [Google Scholar]
- 18. The Korean Society for Preventive Medicine , Preventive Medicine and Public Health, 3rd ed. (Gyechuk Munhwasa, 2017). [Google Scholar]
- 19. Kim C.‐S., Han S.‐Y., Lee S. E., Kang J.‐H., and Kim C.‐W., “Dental Care Utilization for Examination and Regional Deprivation,” Journal of Preventive Medicine and Public Health 48, no. 4 (2015): 195, 10.3961/jpmph.15.026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Lee S. E., Yeon M., Kim C. W., Yoon T. H., Kim D., and Choi J., “Neighborhood Deprivation and Unmet Health Care Needs: A Multilevel Analysis of Older Individuals in South Korea,” Osong Public Health and Research Perspectives 10, no. 5 (2019): 295, 10.24171/j.phrp.2019.10.5.06. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Busan Public Health Policy Institute , “Regional Statistics,” Busan Public Health Policy Institute Website, accessed September 1, 2025, https://www.bhi.or.kr/bppi/view.do?no=160.
- 22. Rao A. S., Pai Y. P., Kamath P. R., Sethumadhavan L., Prabhu N., and Pai R. Y., “Service Recovery System and Service Recovery in Retail Banks a Multilevel Analysis,” Cogent Business & Management 11, no. 1 (2024): 234, 10.1080/23311975.2024.2349260. [DOI] [Google Scholar]
- 23. Shin S., Woo K., and Shin Y., “A Systematic Review of Studies on Public Health Using Multilevel Analysis: Focused on Research Trends and the Assessment of Risk of Bias,” Health & Social Work 35, no. 4 (2015): 157–189. [Google Scholar]
- 24. Ghanbari‐Jahromi M., Bastani P., Jalali F., and Delavari S., “Factors Affecting Oral and Dental Services Utilization Among Elderly: A Scoping Review,” BMC Oral Health 23, no. 1 (2023): 597, 10.1186/s12903-023-03285-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Lang I., Gibbs S., Steel N., and Melzer D., “Neighbourhood Deprivation and Dental Service Use: A Cross‐Sectional Analysis of Older People in England,” Journal of Public Health 30, no. 4 (2008): 472–478, 10.1093/pubmed/fdn047. [DOI] [PubMed] [Google Scholar]
- 26. Ghanbarzadegan A., Balasubramanian M., Luzzi L., Brennan D., and Bastani P., “Inequality in Dental Services: A Scoping Review on the Role of Access Toward Achieving Universal Health Coverage in Oral Health,” BMC Oral Health 21 (2021): 1–11, 10.1186/s12903-021-01765-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Lutfiyya M. N., Gross A. J., Soffe B., and Lipsky M. S., “Dental Care Utilization: Examining the Associations Between Health Services Deficits and Not Having a Dental Visit in Past 12 Months,” BMC Public Health 19 (2019): 1–13, 10.1186/s12889-019-6590-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Lee W., Kim S.‐J., Albert J. M., and Nelson S., “Community Factors Predicting Dental Care Utilization Among Older Adults,” Journal of the American Dental Association 145, no. 2 (2014): 150–158, 10.14219/jada.2013.22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Chung W., “Exploring Regional Disparities in Unmet Healthcare Needs and Their Causes in South Korea: A Policy‐Oriented Study,” International Journal of Health Policy and Management 33, no. 3 (2023): 273–294, 10.4332/KJHPA.2023.33.3.273. [DOI] [Google Scholar]
- 30. Hamano T., Takeda M., Tominaga K., Sundquist K., and Nabika T., “Is Accessibility to Dental Care Facilities in Rural Areas Associated With Number of Teeth in Elderly Residents?,” International Journal of Environmental Research and Public Health 14, no. 3 (2017): 327, 10.3390/ijerph14030327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Fellows J. L., Atchison K. A., Chaffin J., Chávez E. M., and Tinanoff N., “Oral Health in America: Implications for Dental Practice,” Journal of the American Dental Association (1939) 153, no. 7 (2022): 601–609, 10.1016/j.adaj.2022.04.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Sangar S., Dutt V., and Thakur R., “Rural–Urban Differentials in Out‐Of‐Pocket Health Expenditure and Resultant Impoverishment in India: Evidence From NSSO 71st Round,” Asia‐Pacific Journal of Regional Science 3 (2019): 273–291, 10.1007/s41685-018-0095-z. [DOI] [Google Scholar]
- 33. Zardak A. N., Amini‐Rarani M., Abdollahpour I., Eslamipour F., and Tahani B., “Utilization of Dental Care Among Adult Populations: A Scoping Review of Applied Models,” BMC Oral Health 23, no. 1 (2023): 596, 10.1186/s12903-023-03323-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Hajek A., Kretzler B., and Koenig H.‐H., “Factors Associated With Dental Service Use Based on the Andersen Model: A Systematic Review,” International Journal of Environmental Research and Public Health 18, no. 5 (2021): 2491, 10.3390/ijerph18052491. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The Community Health Survey data provided by the Korea Disease Control and Prevention Agency (KDCA) with approval cannot be publicly shared. However, data obtained from the Korean Statistical Information Service (KOSIS) (https://kosis.kr/index/index.do) and the Busan Public Health Policy Institute are publicly (https://www.bhi.or.kr/bppi/main.do) available and can be downloaded from their respective websites.