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 Table of Contents  
Year : 2023  |  Volume : 6  |  Issue : 2  |  Page : 56-63

Socioeconomic disparities in adolescents' caries prevalence: Do oral health-related behaviors play intermediary roles?

Department of Social Welfare, Institute of Social Welfare, Seoul National University, Seoul, Korea

Date of Submission25-Nov-2022
Date of Decision12-Jan-2023
Date of Acceptance23-Mar-2023
Date of Web Publication30-May-2023

Correspondence Address:
Seongha Cho
1 Gwanak-ro, Gwanak-gu, Seoul 08826
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/shb.shb_228_22

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Introduction: Policymakers and academics have explored the behavioral approach in their attempts to explain and address the socioeconomic disparities in adolescents' oral health. However, evidence regarding this issue is scarce in the Korean adolescent population. This study aimed to examine whether socioeconomic status is associated with dental caries and whether oral health-related behaviors (OHRBs) explain or moderate the hypothesized association in Korean adolescents. Methods: A secondary analysis was conducted using the Korea National Health and Nutrition Examination Survey data from 2016 to 2019. Adolescents (n = 1062) aged 13–18 years were included in the analysis. The association between income and untreated decayed permanent teeth (DT) was investigated, focusing on the intermediary roles of OHRBs, using hierarchical negative binomial regression models. Results: Higher income (incidence rate ratio [IRR] 0.70, P < 0.001), regular breakfast intake (IRR 0.64, P < 0.001), higher fruit and vegetable consumption (IRR 0.93, P < 0.001), preventive dental check-ups (IRR 0.84, P < 0.001), and frequent toothbrushing (IRR 0.73, P < 0.001) were associated with lower DT. The income-DT association remained significant and its magnitude was only slightly attenuated, after adjusting for OHRBs (IRR 0.74, P < 0.001). Significant interaction effects were found between income and each OHRB on DT (all with P < 0.001), and interaction patterns differed by behavior type: The income-DT association was stronger in the presence of unfavorable dietary-and favorable dental care-behaviors. Conclusion: The study findings suggested that adolescent oral health equity interventions should prioritize the structural approach and give more thorough consideration to the interactions between socioeconomic and behavioral factors.

Keywords: Adolescents, dental caries, Korea, oral health behaviors, socioeconomic disparities

How to cite this article:
Cho S. Socioeconomic disparities in adolescents' caries prevalence: Do oral health-related behaviors play intermediary roles?. Asian J Soc Health Behav 2023;6:56-63

How to cite this URL:
Cho S. Socioeconomic disparities in adolescents' caries prevalence: Do oral health-related behaviors play intermediary roles?. Asian J Soc Health Behav [serial online] 2023 [cited 2023 Sep 23];6:56-63. Available from: http://www.healthandbehavior.com/text.asp?2023/6/2/56/377925

  Introduction Top

Oral health in adolescence determines lifelong oral health.[1] Dental problems during adolescence can cause irreversible damage to oral health and tend to intensify over the life course;[2],[3] therefore, early intervention is an essential public health agenda. Furthermore, adolescence is a critical formative period in which oral health-related behaviors (OHRBs) form and become habitual.[4]

Oral diseases disproportionately affect disadvantaged children and adolescents.[5] In a systematic review, lower socioeconomic status (SES) was generally associated with higher caries prevalence among children and adolescents under 18.[6] In Korea, the average decayed, missing, and filled teeth (DMFT) score among 12-year-olds was 1.8 in 2018, and it varied by socioeconomic status; 1.75 for those with high subjective SES and 2.04 for those with low subjective SES.[7] The score in other similarly high-income OECD countries was generally lower than that in Korea: 1.40 in Japan, 1.20 in New Zealand, and 1.12 in Spain.[8] So, in Korea, reducing adolescent oral health problems and its socioeconomic disparities comprise key health policy concerns.

Adolescent oral health disparity is a complex health and social issue with broad ramifications, notably accentuating inequalities in the quality of life and school performance across socioeconomic gradients.[5],[9] The material/materialist, cultural/behavioral, psychosocial, and life course approaches to socioeconomic disparities in oral health are prevalent in the literature.[10],[11] In particular, the behavioral approach has received substantial attention, especially due to its potential policy implications. It posits that lower SES individuals engage more in health-compromising OHRBs which increase oral health risks, and calls for behavioral modifications to reduce oral health disparities.[10],[11],[12] However, scholars have recently proposed extending the conventional behavioral approach by recognizing more profound structural contexts that shape behavioral choices.[5],[12]

On the role of OHRBs, previous empirical studies have yielded inconclusive findings, varying from OHRBs' substantial,[12] moderate to limited contributions to socioeconomic disparities in oral health.[13],[14] Hence, more empirical research is needed to shed further light on the issue. Moreover, little research has been conducted on this topic among Korean adolescents. A thorough search of the relevant literature yielded only one study that analyzed the association between subjective SES and self-reported oral symptoms, controlling for behavioral and other factors.[15] Others simply examined the association between SES and OHRBs or between the latter and oral health status.[16],[17]

In addition, research on this topic is much needed in Korea, where government action to remedy socioeconomic disparities in adolescent oral health is still lacking despite their persistence.[18] Only in 2010 the government first included the targets for health equity in the national health plan.[19] The objective of promoting oral health equity appeared at a later date in Korea's first national oral health plan in 2017.[20] Hence, empirical evidence on the key approaches to oral health disparities can provide useful guidance in formulating oral health equity policies that need much development and refinement.

To bridge the above-mentioned knowledge gap, this study examined whether SES is associated with caries prevalence and whether OHRBs account for or moderate this hypothesized association in Korean adolescents. In particular, empirically assessing the intermediary roles of OHRBs is expected to provide useful inputs for policymakers to appropriately tackle oral health disparities. Existing studies suggested that material and behavioral factors tend to overlap, mainly because the latter often depends on the former.[21] For clarity, this study considered all behaviors and habits relevant to oral health to belong to the behavioral category.

  Methods Top

Data and participants

This study used nationally representative secondary data derived from the Korea National Health and Nutrition Examination Survey (KNHANES) from 2016 to 2019. KNHANES is a cross-sectional survey conducted annually by the Korea Disease Control and Prevention Agency (KDCA) that uses a two-stage stratified, clustered sampling method based on national census data to adequately represent the Korean population. The survey comprises a health interview, general and dental health examinations, and a nutrition survey employing the 24-h recall method. The data used in this study are publicly available from the KNHANES website at https://knhanes.kdca.go.kr/knhanes/main.do.

The data of 1884 adolescents aged 13–18 years were included in the 4-year pooled data. Of these, 803 were excluded as they did not undergo oral examinations or nutrition survey. Moreover, 19 were excluded due to missing values or unrealistic fruit and vegetable (F and V) intake frequency (≥50/day). The final sample consisted of 1062 adolescents.

Outcome variable

The outcome variable was the number of untreated decayed permanent teeth (DT). DT was chosen as a measure of present caries status rather than the DMFT index, for the latter can be more aptly considered to measure individuals' dental history.[22] Trained public health dentists recorded DT during naked-eye detection of cavities or community periodontal index probe detection of softened lesions. Oral examinations were conducted at mobile examination centers using dental mirrors and periodontal probes under a dental light, following the World Health Organization criteria.[23],[24] A tooth surface totally/partially missing permanent filling or with both caries and filling was recorded as DT.[24]

Predictor variables

The SES and OHRBs data were obtained from face-to-face health and nutrition interviews performed by trained interviewers and dietitians. Log-transformed equivalized personal income was used to measure SES. Equivalized personal income was obtained by applying the OECD and KNHANES recommended square root equivalence scaling, which accounts for economies of scale in consumption. To do this, the monthly household income variable was divided by the square root of the household size.[25] Given the variable's right-skewness, log transformation and winsorization were applied to mitigate the influence of extreme values as commonly recommended in the literature.[26] With the winsorization, the data were bounded to the 0.05 and 0.95 percentiles; values below the 5th percentile were replaced with that at the 5th percentile and values above the 95th percentile with that at the 95th percentile.

Regarding OHRBs, breakfast intake habits were measured using the weekly intake frequency in the previous year (5–7 times/week; 3–4 times/week; 1–2 times/week; 0 times/week). Responses were dichotomized into ≥3–4 times/week (1) and ≤1–2 times/week (0). Daily F and V intake (g) was calculated using the food code and food intake (g) items from the nutrition survey. Only raw F and Vs were included because there was stronger evidence for their oral health benefits than other forms (e.g., cooked, processed, juiced, or dried).[27],[28] To address skewness, the variable was log-transformed after adding a constant (1) to avoid zero values.

Preventive check-up was assessed by asking the respondents whether they had undergone a dental check-up the previous year even though they did not have a particular oral health issue (yes or no). Tooth brushing frequency was calculated by adding all the binary items having the value of 1 if the respondents brushed their teeth at a specific time of day and dichotomized into ≥3 times/da (1) and ≤2 times/day (0). Frequency ≥3 times/day was interpreted as a healthy behavior, following the general recommendation for the Korean population.[29] Controls included demographic variables (age and gender [male = 1]) and a psychosocial factor (perceived stress level measured on a 4-point scale [very much = 1 and almost none = 4]).

Ethical consideration

KNHANES was conducted following the Helsinki Declaration and was approved by the KDCA Institutional Review Board (Approval Nos. 2018-01-03-P-A and 2018-01-03-C-A). KDCA obtained written, informed consent from participants or their parent or legal guardian if they were under 14 (from 2016 to 2018) or 18 (2019). This study was granted an exemption from ethics review (Exemption Determination No. E2204/001-001) because it was a secondary analysis of publicly available, anonymized data, and the participants had already given their consent before the original survey.

Statistical analysis

Statistical analyses were performed mainly using the glm.nb function from the MASS package in R (version 4.1.2; R Core Team, Vienna, Austria). Sample weights provided in the datasets were used throughout the analysis to obtain estimates representative of the Korean population. Provided weights were the product of the reciprocal of selection probabilities, nonresponse adjustment, and poststratification adjustment to match the sample to the distribution of the entire Korean population in sex and age. Following the KNHANES guideline on multiple years' analyses, sample weights were averaged over the years from 2016 to 2019.[30] Negative binomial regression was selected as the main statistical approach to best accommodate skewness, overdispersion, and many zeros in the outcome count variable DT.[26]

The analysis was conducted as follows. For descriptive purposes, bivariate associations between each predictor and DT were examined using simple negative binomial regressions. Next, hierarchical negative binomial regressions were performed to assess the associations between each block of predictors and DT accounting for other blocks. The following blocks were manually added sequentially based on theoretical considerations: Demographic and control variables: Age, gender, and perceived stress level (Block 1); socioeconomic predictor: Income (Block 2); behavioral predictors (OHRBs): Breakfast consumption frequency, daily F and V intake, preventive dental check-ups, and tooth brushing frequency (Block 3); interaction terms between income and OHRBs: Income × breakfast consumption frequency, income × daily F and V intake, income × preventive dental check-up, income × tooth brushing frequency (Block 4). The hierarchical modeling approach was selected, and the interaction effects were estimated to assess the intermediary roles of OHRBs in the income-DT association. The incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were calculated for all variables in the models. Continuous variables were mean-centered to avoid multicollinearity. The full model's variance inflation factors indicated no serious multicollinearity problem.

  Results Top

[Table 1] shows sample characteristics and bivariate analysis results. Of the 1062 participants, approximately 52% were male, and the mean age was 15.51 years (standard deviation [SD] = 1.73). Average monthly equivalized personal income on the original scale was 2,355,648 KRW (2,021.52 USD, at the exchange rate of 1 USD = 1,165.29 KRW on average in 2019). The mean number of DT was 0.42 (SD = 1.21). 70% (SD = 0.46) of the participants were regular breakfast consumers, and the average value of daily raw F and V intake on the original scale was 108.80 g. A little less than half of the participants underwent preventive check-ups in the previous year (mean = 0.44, SD = 0.50) and brushed their teeth three times or more a day (mean = 0.48, SD = 0.50). All predictors had significant bivariate associations with DT. Higher-income and healthy OHRBs were associated with lower caries prevalence.
Table 1: Descriptive statistics and bivariate analysis of associations between predictors and number of decayed teeth (n=1062)

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[Table 2] presents the associations of income, OHRBs, and income-OHRB interactions with DT, analyzed using the hierarchical negative binomial regression models. Adding blocks of predictors successively reduced the Akaike information criterion, which indicated improvements in the model fit. In the model including only demographic and control variables, being male (IRR 0.96, 95% CI 0.96–0.97, P < 0.001) and lower stress (IRR 0.97, 95% CI 0.97–0.98, P < 0.001) were associated with fewer DT (model 1). After adjusting for block 1, higher income was associated with lower caries prevalence (IRR 0.70, 95% CI 0.69–0.70, P < 0.001) (model 2). After adjustments for blocks 1 and 2, all OHRBs were associated with DT (model 3). Regular breakfast intake of ≥3–4 times a week (IRR 0.64, 95% CI 0.63–0.65, P < 0.001), higher F and V consumption (IRR 0.93, 95% CI 0.93–0.94, P < 0.001), preventive dental check-up experience (IRR 0.84, 95% CI 0.83–0.84, P < 0.001), and regular tooth brushing of ≥3 times a day (IRR 0.73, 95% CI 0.72–0.74, P < 0.001) were associated with lower DT. The income-DT association was only slightly attenuated and remained significant (IRR 0.74, 95% CI 0.74–0.75, P < 0.001). In model 4, statistically significant interaction effects were detected between income and each OHRB (income × breakfast consumption frequency, income × daily F and V intake, income × preventive dental check-up, income × tooth brushing frequency; all with P < 0.001), suggesting that OHRBs moderated the association between income and DT.
Table 2: Negative binomial regression results: Income, oral health-related behaviors and decayed teeth (n=1062)

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To visualize the interactions between income and OHRBs derived from model 4 [Table 2], the predictive margins were calculated and plotted [Figure 1]. The figure shows that across all income levels, adolescents with favorable OHRBs (regular breakfast intake, higher F and V consumption, preventive check-up experience, and regular tooth brushing) generally had fewer DT. However, different interaction patterns were observed between dietary and dental care behaviors. Regarding dietary behaviors, the income-DT association was stronger when oral health-compromising habits (i.e., irregular breakfast intake of ≤1–2 times a week and lower F and V consumption) were present, as indicated by steeper slopes. A larger distance between the lines at lower income levels suggested greater differences in DT prevalence according to dietary habits in these strata. Regarding dental care behaviors, the income-DT association was stronger in the presence of oral health-promoting behaviors (i.e., preventive check-up and regular toothbrushing of ≥3 times a day), as indicated by steeper slopes, and differences in DT prevalence according to these behaviors were greater at higher income levels.
Figure 1: Income–OHRBs interactions. *Shaded areas represent 99% CIs around the predicted values. (a) Interaction effect of income and breakfast frequency on DT. (b) Interaction effect of income and F and V intake on DT (F and V variable was mean-centered; its three representative values were selected to estimate the slopes: The mean and the values one SD above and below mean). (c) Interaction effect of income and preventive check-up on DT. (d) Interaction effect of income and tooth brushing frequency on DT. CIs: Confidence intervals, DT: Untreated decayed permanent teeth, SD: Standard deviation, OHRBs: Oral health-related behaviors

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  Discussion Top

The analysis of 2016–2019 KNHANES data showed that Korean adolescents with higher income and favorable OHRBs tended to have lower caries prevalence. More importantly, the income-DT association remained significant and its magnitude was only minimally attenuated, after adjusting for OHRBs– suggesting that OHRBs did not markedly account for socioeconomic disparities in adolescent oral health. Interaction analysis showed that OHRBs could moderate the income-DT association, and the interaction patterns can differ by behavior type.

To the author's knowledge, this is the first study to suggest different patterns of income-OHRBs interaction effects on DT by OHRB type in an adolescent population. This finding complements previous studies that have presented such effects without consideration of the different patterns by behavior, thus enriching the literature on behavioral approaches to oral health disparities.[12],[31] Another strength of this study is that using the KNHANES data, dietary and dental care habits could be analyzed as behavioral predictors of adolescent oral health. This complemented the existing literature on Korean adolescent oral health disparities, which generally considered either one type of behavior, thereby running the potential risk of omitted variable bias.[17] In addition, rather than the self-reported oral health measure, this study used the objective clinical health indicator obtained from dental examinations by trained dentists. The latter is known to be more appropriate than the former for estimating economic disparities in health.[32] Methodologically, negative binomial approach was used, one of the most appropriate models for use in case of dental data.[33]

The finding that unfavorable economic conditions and OHRBs are associated with higher caries occurrence among adolescents corroborates the results of a previous systematic review.[34] The associations of preventive visits, regular tooth brushing, and adequate breakfast and F and V intake with lower caries prevalence align with previous studies with children or adolescents from developed country contexts.[31],[35],[36],[37] Contrary to this study, a cross-sectional study on US adolescents reported a higher likelihood of caries experience when the adolescents had undergone a preventive dental visit.[38] A possible explanation for these conflicting findings may be using different outcome measures. The latter study used the subjective variable “parent-reported difficulties due to carious teeth in the past year,” which reflected parents' awareness of their child's oral health status. Because preventive visits often reveal oral health problems, they likely increased the parents' awareness of carious teeth.[38] Such parental reporting bias was not present in this study, which used an objective clinical outcome measure.

The finding that OHRBs play a minimal role in accounting for socioeconomic disparities in DT aligns with several empirical studies on adolescents showing that OHRBs did not substantially explain the association between SES and objective or subjective oral health conditions.[13],[39],[40] One study on Korean adolescents showed a similar finding,[15] although the latter used SES and oral health measures derived from a self-reported online survey. Some cross-sectional studies on adults presented contrasting findings, reporting that OHRBs significantly[12],[41] or at least partly[14] accounted for socioeconomic disparities in oral health.

Another key finding was that patterns of income-OHRB interaction effects on DT could differ by behavior. The income-DT association was weaker when positive dietary behaviors were present; while stronger when positive dental care behaviors were present. A possible explanation for the former pattern is that a healthy oral microbial environment fostered by appropriate breakfast and F and V intake habits[42],[43] can provide resilient and stable protection against oral health risk factors associated with economic disadvantage.[44] However, greater differences in DT according to dietary habits at lower income levels suggest more negative implications of unhealthy eating habits for this stratum. For instance, skipping breakfast can lead to increased snack consumption, which may entail greater oral health risks for lower-income individuals who consume nutrient-poor, cariogenic snacks more frequently.[36],[45]

The pattern for dental care behaviors is consistent with a Dutch study reporting a stronger association between dental attendance and oral health status in higher SES groups than in lower SES groups.[12] The pattern may be attributable to varying care effectiveness across income levels. For example, care quality and outcomes can be better among higher-income individuals, with their lower financial barriers in choosing superior-quality service providers and timely proceeding with the recommended treatments, as well as parents' better communication experience with the dentist.[46],[47],[48] Furthermore, preventive measures could be less effective among lower-income adolescents whose oral health tends to be already compromised. Similarly, a randomized controlled study on Brazilian children found the anticaries effect of a preventive dental care measure to be greater when children had better baseline oral health status.[49]

The persistent income-DT association, after adjusting for OHRBs, lends support to prioritizing the structural approach to address socioeconomic gradients in oral health. Studies have increasingly advocated for structural solutions that place health policies within the broader social policy agenda.[5],[14],[50] Notably, a meta-analysis suggested income support to be a highly promising social policy for improving the health of lower-income populations.[50] Nonetheless, current policies on oral health disparities tend to focus on modifying behaviors. For example, the 2022–2026 Korea National Oral Health Plan prioritizes downstream interventions, such as expanding access to dental services and behavioral education.[51] Policymakers should consider upstream interventions like child allowance or child tax benefits more targeted towards lower-income households as oral health equity policy options, which could increase lower-income parents' financial and time resources and enable them to make healthier choices for their children's oral health.[52]

The findings on different patterns of income-OHRBs interaction effects on DT by behavior type imply that the effectiveness of behavioral interventions on oral health could vary by participants' SES, and suggest a need to consider the target population's socioeconomic conditions. Indeed, while some behavioral interventions can benefit adolescent oral health,[53] their effectiveness could be improved if incorporated with upstream approaches.[54] More specifically, greater differences in DT according to dietary habits among lower-income strata suggest that dietary interventions can potentially be more beneficial for the latter. Thus, allocating more resources to supporting healthy dietary choices among lower-income children would be recommended. The potential lower effectiveness of preventive care intervention on oral health improvement among lower-income adolescents suggests a need to: Reorient Korea's policy for adolescent oral health equity focused on expanding preventive care coverage, which has, in effect, not reduced socioeconomic disparities in adolescent caries;[18] and unravel underlying reasons for, and remedy, such lesser effectiveness. The latter may partly be influenced by lower-income adolescents' pre-existing conditions or delayed or lower-quality care. Hence, various aspects of care would need to be improved, including reinforcing dentist-parent communication or early-age intervention for lower-income adolescents.


This study has a few limitations. First, cross-sectional data did not allow establishing causality between the predictors and outcome. Second, certain known behavioral predictors of oral health could not be included in the analysis due to limitations in the survey data. For example, a dichotomous current smoking status measure was not included because it was highly imbalanced, with only about 4% of currently smoking respondents (n = 44). Including such imbalanced items poses threats to the model's robustness.[55] Future studies, using appropriate data, should examine the intermediary roles of more various OHRBs. Third, 24-h recall data used to assess F and V intake may be biased by under-or overreporting. Finally, one should consider the potential reverse causality of DT's effect on F and V intake and dentist visits. For example, dental problems can hinder fibrous food intake[56] and dental visits[57] by reducing chewing abilities and heightening dental fear, respectively.

  Conclusion Top

Higher-income and favorable OHRBs were associated with lower DT prevalence in Korean adolescents. OHRBs played a minimal role in accounting for socioeconomic disparities in oral health. A novel finding was that OHRBs moderated the income-DT association and interaction patterns differed by behavior type: The income-DT association was stronger in the presence of unfavorable dietary- and favorable dental care-behaviors. These results implied that behavioral interventions might have varying levels of effectiveness by SES. Policy-wise, adolescent oral health equity interventions should prioritize the structural approach and more thoroughly consider the interactions between socioeconomic and behavioral factors, for improved effectiveness. Such a task would require greater coordination between government sectors responsible for social and health policies.


The author thanks Professor Joan Yoo for her valuable comments on an earlier draft of this article.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Drummond BK, Meldrum AM, Boyd D. Influence of dental care on children's oral health and wellbeing. Br Dent J 2013;214:E27.  Back to cited text no. 1
Peres KG, Peres MA, Araujo CL, Menezes AM, Hallal PC. Social and dental status along the life course and oral health impacts in adolescents: A population-based birth cohort. Health Qual Life Outcomes 2009;7:95.  Back to cited text no. 2
AAPD. Adolescent Oral Health Care. The Reference Manual of Pediatric Dentistry. Chicago, Ill: American Academy of Pediatric Dentistry; 2021. p. 267-76.  Back to cited text no. 3
Nasir EF, Vu J. Oral hygiene practice among 18-year-old norwegian adolescents using health belief model: A cross-sectional study. Eur J Dent 2022;16:56-63.  Back to cited text no. 4
Watt RG, Mathur MR, Aida J, Bönecker M, Venturelli R, Gansky SA. Oral health disparities in children: A canary in the coalmine? Pediatr Clin North Am 2018;65:965-79.  Back to cited text no. 5
Reisine ST, Psoter W. Socioeconomic status and selected behavioral determinants as risk factors for dental caries. J Dent Educ 2001;65:1009-16.  Back to cited text no. 6
Choi CH, Choi YH, Jeong SH, Cho HJ, Son CK, Jeong SH, et al. 2018 Korea National Children's Oral Health Survey. Sejong: Ministry of Health and Welfare; 2018.  Back to cited text no. 7
Bernabé E, Sheiham A. Extent of differences in dental caries in permanent teeth between childhood and adulthood in 26 countries. Int Dent J 2014;64:241-5.  Back to cited text no. 8
Ruff RR, Senthi S, Susser SR, Tsutsui A. Oral health, academic performance, and school absenteeism in children and adolescents: A systematic review and meta-analysis. J Am Dent Assoc 2019;150:111-21.e4.  Back to cited text no. 9
Sisson KL. Theoretical explanations for social inequalities in oral health. Community Dent Oral Epidemiol 2007;35:81-8.  Back to cited text no. 10
Singh A, Peres MA, Watt RG. The relationship between income and oral health: A critical review. J Dent Res 2019;98:853-60.  Back to cited text no. 11
Duijster D, Oude Groeniger J, van der Heijden GJ, van Lenthe FJ. Material, behavioural, cultural and psychosocial factors in the explanation of socioeconomic inequalities in oral health. Eur J Public Health 2018;28:590-7.  Back to cited text no. 12
Perera I, Ekanayake L. Influence of oral health-related behaviours on income inequalities in oral health among adolescents. Community Dent Oral Epidemiol 2011;39:345-51.  Back to cited text no. 13
Sabbah W, Tsakos G, Sheiham A, Watt RG. The role of health-related behaviors in the socioeconomic disparities in oral health. Soc Sci Med 2009;68:298-303.  Back to cited text no. 14
Jung SH, Watt RG, Sheiham A, Ryu JI, Tsakos G. Exploring pathways for socio-economic inequalities in self-reported oral symptoms among Korean adolescents. Community Dent Oral Epidemiol 2011;39:221-9.  Back to cited text no. 15
Park JB, Han K, Park YG, Ko Y. Association between socioeconomic status and oral health behaviors: The 2008-2010 Korea national health and nutrition examination survey. Exp Ther Med 2016;12:2657-64.  Back to cited text no. 16
Kim JA, Choi HM, Seo Y, Kang DR. Relations among obesity, family socioeconomic status, oral health behaviors, and dental caries in adolescents: The 2010-2012 Korea National Health and nutrition examination survey. BMC Oral Health 2018;18:114.  Back to cited text no. 17
Shin BM, Jung SH, Kim MH, Ryu JI. Did the extended coverage policy contribute to alleviating socioeconomic inequality in untreated dental caries of both children and adolescents in South Korea? BMC Oral Health 2020;20:124.  Back to cited text no. 18
Khang YH, Lee SI. Health inequalities policy in Korea: Current status and future challenges. J Korean Med Sci 2012;27 Suppl:S33-40.  Back to cited text no. 19
Ministry of Health and Welfare. 1st (2017-2021) National Oral Health Plan. Sejong: Ministry of Health and Welfare; 2017.  Back to cited text no. 20
Schrijvers CT, Stronks K, van de Mheen HD, Mackenbach JP. Explaining educational differences in mortality: The role of behavioral and material factors. Am J Public Health 1999;89:535-40.  Back to cited text no. 21
Kent G. Dental health: Psychosocial aspects. In: Smelser NJ, Baltes PB, editors. International Encyclopedia of the Social & Behavioral Sciences. Oxford: Pergamon; 2001. p. 3498-501.  Back to cited text no. 22
World Health Organization. Oral Health Surveys: Basic Methods. 5th ed. Geneva: World Health Organization; 2013.  Back to cited text no. 23
Park DY. Standardization for Oral Health Survey in KNHANES. Osong: Korea Centers for Disease Control and Prevention; 2016.  Back to cited text no. 24
OECD. What are equivalence scales? Paris: OECD; n.d. Available from: https://www.oecd.org/els/soc/OECD-Note-EquivalenceScales.pdf. [Last accessed on 2023 Mar 31].  Back to cited text no. 25
Green JA. Too many zeros and/or highly skewed? A tutorial on modelling health behaviour as count data with Poisson and negative binomial regression. Health Psychol Behav Med 2021;9:436-55.  Back to cited text no. 26
Palacios CJ, Joshipura K. Nutrition and oral health: A two-way relationship. In: Bales CW, Locher JL, Saltzman E, editors. Handbook of Clinical Nutrition and Aging. 3rd ed. New York: Springer; 2015.  Back to cited text no. 27
Flagg EW, Coates RJ, Jones DP, Byers TE, Greenberg RS, Gridley G, et al. Dietary glutathione intake and the risk of oral and pharyngeal cancer. Am J Epidemiol 1994;139:453-65.  Back to cited text no. 28
Han K, Park JB. Association between oral health behavior and periodontal disease among Korean adults: The Korea national health and nutrition examination survey. Medicine (Baltimore) 2017;96:e6176.  Back to cited text no. 29
Kim Y. The Korea National Health and Nutrition Examination Survey (KNHANES): Current status and challenges. Epidemiol Health 2014;36:e2014002.  Back to cited text no. 30
Crocombe LA, Broadbent JM, Thomson WM, Brennan DS, Poulton R. Impact of dental visiting trajectory patterns on clinical oral health and oral health-related quality of life. J Public Health Dent 2012;72:36-44.  Back to cited text no. 31
Johnston DW, Propper C, Shields MA. Comparing subjective and objective measures of health: Evidence from hypertension for the income/health gradient. J Health Econ 2009;28:540-52.  Back to cited text no. 32
Solinas G, Campus G, Maida C, Sotgiu G, Cagetti MG, Lesaffre E, et al. What statistical method should be used to evaluate risk factors associated with dmfs index? Evidence from the National Pathfinder Survey of 4-year-old Italian children. Community Dent Oral Epidemiol 2009;37:539-46.  Back to cited text no. 33
Abreu LG, Elyasi M, Badri P, Paiva SM, Flores-Mir C, Amin M. Factors associated with the development of dental caries in children and adolescents in studies employing the life course approach: A systematic review. Eur J Oral Sci 2015;123:305-11.  Back to cited text no. 34
Chestnutt IG, Schäfer F, Jacobson AP, Stephen KW. The influence of toothbrushing frequency and post-brushing rinsing on caries experience in a caries clinical trial. Community Dent Oral Epidemiol 1998;26:406-11.  Back to cited text no. 35
Bruno-Ambrosius K, Swanholm G, Twetman S. Eating habits, smoking and toothbrushing in relation to dental caries: A 3-year study in Swedish female teenagers. Int J Paediatr Dent 2005;15:190-6.  Back to cited text no. 36
Dye BA, Shenkin JD, Ogden CL, Marshall TA, Levy SM, Kanellis MJ. The relationship between healthful eating practices and dental caries in children aged 2-5 years in the United States, 1988-1994. J Am Dent Assoc 2004;135:55-66.  Back to cited text no. 37
Lebrun-Harris LA, Canto MT, Vodicka P. Preventive oral health care use and oral health status among US children: 2016 National Survey of Children's Health. J Am Dent Assoc 2019;150:246-58.  Back to cited text no. 38
Polk DE, Weyant RJ, Manz MC. Socioeconomic factors in adolescents' oral health: Are they mediated by oral hygiene behaviors or preventive interventions? Community Dent Oral Epidemiol 2010;38:1-9.  Back to cited text no. 39
Peres MA, Nascimento GG, Peres KG, Demarco FF, Menezes AB. Oral health-related behaviours do not mediate the effect of maternal education on adolescents' gingival bleeding: A birth cohort study. Community Dent Oral Epidemiol 2018;46:169-77.  Back to cited text no. 40
Wamala S, Merlo J, Boström G. Inequity in access to dental care services explains current socioeconomic disparities in oral health: The Swedish National Surveys of Public Health 2004-2005. J Epidemiol Community Health 2006;60:1027-33.  Back to cited text no. 41
Viljakainen J, Raju SC, Viljakainen H, Figueiredo RA, Roos E, Weiderpass E, et al. Meal regularity plays a role in shaping the saliva microbiota. Front Microbiol 2020;11:757.  Back to cited text no. 42
Jain S, Bansal K, Marwaha M, Sehrawat N, Singla S. Effect of diet modification on salivary parameters and oratest in high-caries-risk individuals. Int J Clin Pediatr Dent 2018;11:34-9.  Back to cited text no. 43
Rosier BT, Marsh PD, Mira A. Resilience of the oral microbiota in health: Mechanisms that prevent dysbiosis. J Dent Res 2018;97:371-80.  Back to cited text no. 44
Drouillet-Pinard P, Dubuisson C, Bordes I, Margaritis I, Lioret S, Volatier JL. Socio-economic disparities in the diet of French children and adolescents: A multidimensional issue. Public Health Nutr 2017;20:870-82.  Back to cited text no. 45
Gilbert GH, Litaker MS, Makhija SK. Differences in quality between dental practices associated with race and income mix of patients. J Health Care Poor Underserved 2007;18:847-67.  Back to cited text no. 46
Thompson B, Cooney P, Lawrence H, Ravaghi V, Quiñonez C. The potential oral health impact of cost barriers to dental care: Findings from a Canadian population-based study. BMC Oral Health 2014;14:78.  Back to cited text no. 47
Reich SM, Hoeft KS, Díaz G, Ochoa W, Gaona A. Disparities in the quality of pediatric dental care: New research and needed changes. Soc Policy Rep 2018;31:1-27.  Back to cited text no. 48
Oliveira BH, Salazar M, Carvalho DM, Falcão A, Campos K, Nadanovsky P. Biannual fluoride varnish applications and caries incidence in preschoolers: A 24-month follow-up randomized placebo-controlled clinical trial. Caries Res 2014;48:228-36.  Back to cited text no. 49
Courtin E, Kim S, Song S, Yu W, Muennig P. Can social policies improve health? A systematic review and meta-analysis of 38 randomized trials. Milbank Q 2020;98:297-371.  Back to cited text no. 50
Ministry of Health and Welfare. Announcement of 2022-2026 National Oral Health Plan. South Korea: Ministry of Health and Welfare; 2022.  Back to cited text no. 51
Collins CC, Villa-Torres L, Sams LD, Zeldin LP, Divaris K. Framing young childrens oral health: A participatory action research project. PLoS One 2016;11:e0161728.  Back to cited text no. 52
Tsai C, Raphael S, Agnew C, McDonald G, Irving M. Health promotion interventions to improve oral health of adolescents: A systematic review and meta-analysis. Community Dent Oral Epidemiol 2020;48:549-60.  Back to cited text no. 53
Bracksley-O'Grady S, Anderson K, Masood M. Oral health academics' conceptualisation of health promotion and perceived barriers and opportunities in dental practice: A qualitative study. BMC Oral Health 2021;21:165.  Back to cited text no. 54
Blankmeyer E. How robust is linear regression with dummy variables? Faculty Publications – Finance and Economics, Texas State University-San Marcos: San Marcos, Texas; 2006.  Back to cited text no. 55
Moynihan P. The interrelationship between diet and oral health. Proc Nutr Soc 2005;64:571-80.  Back to cited text no. 56
Bell JF, Huebner CE, Reed SC. Oral health need and access to dental services: Evidence from the National Survey of Children's Health, 2007. Matern Child Health J 2012;16 Suppl 1:S27-34.  Back to cited text no. 57


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  [Table 1], [Table 2]


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