Abstract
Objectives
To evaluate the influence of self-esteem on oral health-related quality of life (OHRQoL) in the occlusal transition from childhood to adolescence.
Materials and Methods
This longitudinal observational study involved 785 children, ranging from mixed to permanent dentition, over a 4-year follow-up period. OHRQoL was assessed using the Child Perceptions Questionnaire (CPQ) for two age groups: 8 to 10 years for those in mixed dentition and 11 to 14 years for permanent dentition. Clinical variables related to malocclusion were evaluated using the Dental Aesthetic Index (DAI), and children’s self-esteem was measured using the Global Negative Self-Evaluation (GSE). Poisson regression analyses were conducted, with regression models adjusted to estimate relative risks and their respective 95% confidence intervals. A significance level of P < .20 was used for individual analyses, with an overall significance set at 5%.
Results
Individuals with low self-esteem had an 11%, 12%, 21%, and 20% higher risk of reporting a negative impact on OHRQoL in functional limitation, emotional well-being, social well-being, and total OHRQoL, respectively (P < .05).
Conclusions
Self-esteem may contribute to decreased OHRQoL in the transition from childhood to adolescence. The findings suggest that the need for orthodontic treatment does not significantly alter this relationship in childhood and does not affect OHRQoL.
Keywords: Malocclusion, Mixed dentition, Orthodontic treatment need
INTRODUCTION
Oral health-related quality of life (OHRQoL) is a multidimensional concept influenced by individual factors and may change over time. Malocclusion, as a dental condition, impacts OHRQoL in several aspects of well-being and social acceptance.1–4However, the repercussions of orthodontic needs may differ between childhood and adolescence.2,5As individuals age, the adverse effects of malocclusion on OHRQoL tend to intensify, affecting the psychological, social, esthetic, and functional dimensions.2,5,6This correlation becomes evident around 8 years of age, particularly during the mixed dentition stage. However, it is important to recognize that many contextual and individual factors influence the overall impact of malocclusion on OHRQoL.7–9
The need for orthodontic treatment impacts social interactions, affecting self-esteem and self-acceptance1,7,10and, in this context, self-esteem is related to malocclusion and OHRQoL. The literature suggests that individuals with lower self-esteem may be more vulnerable to the negative esthetic effects of malocclusion.9,11–14Conversely, higher levels of self-esteem have been identified as a potential protective factor for OHRQoL.7,15,16
Children and adolescents with malocclusion, particularly in severe cases, often experience lower self-esteem, making them more susceptible to bullying compared to their peers with normal occlusion.17Therefore, the relationship between low self-esteem and the esthetic perception of dental conditions suggests that certain malocclusions may increase the risk of being bullied.8,9Some studies suggest that malocclusion negatively affects self-esteem, particularly in adolescents.7,9,10,18
Increased overjet and dental crowding correlate with experiences of social stigma, thereby worsening self-esteem. Though the effects of malocclusion on self-esteem are documented, some studies contend that the psychological aspects may differ according to individual circumstances and age. In this context, age is pivotal in evaluating the perceived aesthetic implications. Individuals exhibiting severe malocclusion and lowered self-esteem report negative OHRQoL. Cross-sectional studies have investigated the relationship between malocclusion, OHRQoL, and self-esteem.7,9,10,15
Despite the lack of studies exploring how self-esteem affects OHRQoL in orthodontic treatment, this study aimed to investigate the relationship between malocclusion, self-esteem, and OHRQoL during the transition from mixed to permanent dentition over 4 years. The study hypothesis considered that self-esteem is a modulating factor in this relationship.
MATERIALS AND METHODS
Ethical Issues
This study was approved by the Research Ethics Committee of Piracicaba Dental School-UNICAMP (protocol no. 52809521.2.0000.5385). Participants were included only if their parents or legal guardians provided written consent in both assessment periods. Re-evaluation during follow-up required signed informed consent. The study followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines.
Study Design, Setting, and Participants
A longitudinal observational study followed children from mixed to permanent dentition over 4 years. The initial assessment in 2018 included 785 children (8–10 years old) in the late mixed dentition stage, determined by clinical examination.19,20At baseline, the sample was calculated considering a confidence interval (CI) of 95%, a test power of 80%, and an effect size of 1.5. The minimum required sample size was estimated at 640 children. To account for potential loss during follow-up, an additional 20% was added, resulting in a target sample of 768 participants. Exclusion criteria included individuals in active orthodontic treatment, those with primary or permanent dentition, and those with craniofacial syndromes. In 2022, all initially assessed children were contacted for follow-up through phone calls and school records. Of the original cohort, 352 children (44.9%) were reevaluated, all with complete permanent dentition, including erupted second molars. Losses to follow-up (55.1%) were mainly due to an inability to locate participants because they had transferred to different schools or moved to other regions; in addition, children who had undergone or completed orthodontic treatment during the follow-up were considered ineligible, and those who declined to participate were not included in the second assessment. The final sample provided a test power greater than 80%.
Data Collection and Variables
Data collection was conducted in a standardized manner during all follow-up assessments. A training and calibration process was implemented using the same method for both assessment periods (T1 and T2). The training included theoretical and practical discussions to ensure a comprehensive understanding of the Dental Aesthetic Index (DAI). The calibration process involved theoretical and practical training, followed by evaluation of inter- and intra-examiner agreement using the kappa coefficient, as the study variables were categorical. Agreement values were higher than 0.92 at T1 and 0.97 at T2, indicating acceptable reliability.
OHRQoL was determined by the Child Perceptions Questionnaire for the mixed (CPQ8–10)21,22and permanent dentition (CPQ11–14).23The CPQ was self-administered, and questions about the frequency of events in the last 3 months were presented. For the analysis, the total score and domains of the CPQ were used as variables. The median dichotomized the results; higher scores negatively impacted OHRQoL.23
CPQ8–10 consists of questions divided into four domains: oral symptoms, functional limitations, emotional well-being, and social well-being. Responses followed the Likert scale: never (0), once/twice (1), sometimes (2), often (3), and every day or almost every day (4). The total score was obtained as the sum of the items. The scores for each domain were obtained by adding each question.21,22The CPQ11–14 consists of questions divided into four domains: oral symptoms, functional limitations, emotional well-being, and social well-being. Responses followed the Likert scale: never (0), once/twice (1), sometimes (2), often (3), and every day or almost every day (4). The total score was obtained as the sum of the items. The scores for each domain were obtained by adding each question.22,23
Self-esteem was determined by the Global Negative Self-Evaluation (GSE).24The scale presents six items with six response alternatives, quantified in ascending order (1 to 6), following the arrangement on the scale. The sum of the answers allows classifying individual self-esteem into four categories: very little negative (1–1.69), slightly negative (1.7–2.69), negative (2.7–3.99), and very negative (4.0–6.0). The results were dichotomized into slightly negative (1–2.69) and very negative (2.7–6) self-esteem.24
Malocclusion was assessed using the DAI, which evaluates missing teeth, crowding, spacing, maxillomandibular misalignment, overjet, open bite, and molar relationship.25,26DAI score is calculated by summing the scores for each characteristic, with a constant value added. The DAI classification indicates the severity of malocclusion and treatment need: DAI 1 (<25) for normal/mild malocclusion with no or mild treatment need; DAI 2 (26–30) for malocclusion requiring elective treatment; DAI 3 (31–35) for severe malocclusion needing highly desirable treatment; DAI 4 (>36) for very severe malocclusion requiring mandatory treatment.
Statistical Methodology
The data underwent initial descriptive analyses followed by Poisson regression analyses for each variable individually in conjunction with the outcomes (total score and CPQ domains), utilizing robust variances. The regression models were fine-tuned to estimate crude and adjusted relative risks with their corresponding 95% confidence intervals. For Poisson multiple regression models, variables with a significance level of P < .20 in individual analyses were incorporated. All statistical analyses upheld a significance threshold of 5%. The R program (R Foundation for Statistical Computing, Vienna, Austria) was used for data analysis.
RESULTS
Table 1 presents the descriptive data from the evaluation of 352 children (50.6% girls and 49.4% boys). The final sample comprised 352 children, with a balanced distribution between girls and boys. At baseline (T1), very severe malocclusion (DAI 4) was the most prevalent classification. Over the 4-year follow-up, 39.8% showed improvement in orthodontic treatment need, whereas 56.5% experienced a decline in self-esteem from mixed to permanent dentition (Table 2). Table 3 shows the frequency distribution of independent variables regarding outcomes (worsening impact of oral health on quality of life) for the mixed-dentition sample. The highest negative impacts on OHRQoL were observed in the social well-being and functional limitation domains. Age-related patterns indicated that younger children reported greater impacts, particularly in oral symptoms and overall CPQ scores. Girls reported higher impacts in the social well-being domain compared to boys. Table 4 presents the association between self-esteem and OHRQoL domains at T1. Children with high negative self-esteem had greater risks of reporting negative impacts: 11% for functional limitations, 12% for emotional well-being, 21% for social well-being, and 20% for overall scores (all P < .05). Girls also had a 9% higher risk of high social well-being scores (P < .05).
Table 1.
Descriptive Analysis of the Study Sample (n = 352)a
| Variable | Category | Frequency (%) |
|---|---|---|
| Sex | Male | 174 (49.4%) |
| Female | 178 (50.6%) | |
| Age at first assessment (y) | 8 | 94 (26.7%) |
| 9 | 151 (42.9%) | |
| 10 | 107 (30.4%) | |
| Race | White | 216 (61.4%) |
| Nonwhite | 136 (38.6%) | |
| Orthodontic need (DAI) | DAI 1 (Mild) | 97 (27.6%) |
| DAI 2 (Defined) | 84 (23.9%) | |
| DAI 3 (Severe) | 61 (17.3%) | |
| DAI 4 (Very severe) | 110 (31.2%) |
| Variable | Mean (Standard Deviation) | Median (Minimum and Maximum Value) |
|---|---|---|
| Self-esteem (GSE) | 8.7 (2.6) | 8.0 (6.0; 17.0) |
| Oral symptoms (CPQ8–10) | 5.3 (3.8) | 5.0 (0.0; 20.0) |
| Functional limitations (CPQ8–10) | 2.3 (3.4) | 0.5 (0.0; 20.0) |
| Emotional well-being (CPQ8–10) | 3.4 (4.5) | 2.0 (0.0; 20.0) |
| Social well-being (CPQ8–10) | 2.2 (4.8) | 0.0 (0.0; 36.0) |
| OHRQoL total score (CPQ8–10) | 13.2 (13.6) | 10.0 (0.0; 92.0) |
CPQ indicates Child Perceptions Questionnaire; DAI, Dental Anesthetic Index; GSE, Global Negative Self-Evaluation; OHRQoL, oral health-related quality of life.
Table 2.
Frequency Distribution of the Sample in the Mixed Dentition, According to Changes Over Time (n = 352)a
| Variable | Variation Over Time |
||
|---|---|---|---|
| Worse | Maintained | Improved | |
| Orthodontic need (DAI) | 90 (25.6%) | 122 (34.7%) | 140 (39.8%) |
| Self-esteem (GSE) | 199 (56.5%) | 11 (3.1%) | 142 (40.3%) |
| Oral symptoms (CPQ8–10) | 63 (17.9%) | 34 (9.7%) | 255 (72.4%) |
| Functional limitations (CPQ8–10) | 123 (34.9%) | 90 (25.6%) | 139 (39.5%) |
| Emotional well-being (CPQ8–10) | 106 (30.1%) | 87 (24.7%) | 159 (45.2%) |
| Social well-being (CPQ8–10) | 168 (47.7%) | 93 (26.4%) | 91 (25.8%) |
| OHRQoL total score (CPQ8–10) | 113 (32.1%) | 20 (5.7%) | 219 (62.2%) |
CPQ indicates Child Perceptions Questionnaire; DAI, Dental Anesthetic Index; GSE, Global Negative Self-Evaluation.
Table 3.
Frequency Distribution of Independent Variables About Outcomes (Worsening Impact of Oral Health on Quality of Life) for the Mixed-Dentition Sample (n = 352)a
| Variable | Global | Frequency (%) of Participants With Worsening Impact |
||||
|---|---|---|---|---|---|---|
| Oral Symptoms |
Functional Limitations | Emotional Well-Being |
Social Well-Being |
Quality of Life Score | ||
| Global | 352 (100.0%) | 63 (17.9%) | 123 (34.9%) | 106 (30.1%) | 168 (47.7%) | 113 (32.1%) |
| Sex | ||||||
| Male | 174 (49.4%) | 32 (18.4%) | 55 (31.6%) | 49 (28.2%) | 65 (37.4%) | 52 (29.9%) |
| Female | 178 (50.6%) | 31 (17.4%) | 68 (38.2%) | 57 (32.0%) | 103 (57.9%) | 61 (34.3%) |
| Age at first assessment (y) | ||||||
| 8 | 94 (26.7%) | 25 (26.6%) | 36 (38.3%) | 35 (37.2%) | 49 (52.1%) | 42 (44.7%) |
| 9 | 151 (42.9%) | 21 (13.9%) | 49 (32.4%) | 42 (27.8%) | 75 (49.7%) | 43 (28.5%) |
| 10 | 107 (30.4%) | 17 (15.9%) | 38 (35.5%) | 29 (27.1%) | 44 (41.1%) | 28 (26.2%) |
| Race | ||||||
| White | 216 (61.4%) | 45 (20.8%) | 78 (36.1%) | 65 (30.1%) | 104 (48.2%) | 76 (35.2%) |
| Nonwhite | 136 (38.6%) | 18 (13.2%) | 45 (33.1%) | 41 (30.2%) | 64 (47.1%) | 37 (27.2%) |
| Orthodontic need (DAI) worsened | ||||||
| No | 262 (74.4%) | 46 (17.6%) | 89 (34.0%) | 84 (32.1%) | 129 (49.2%) | 89 (34.0%) |
| Yes | 90 (25.6%) | 17 (18.9%) | 34 (37.8%) | 22 (24.4%) | 39 (43.3%) | 24 (26.7%) |
| Worsening in self-esteem (GSE) | ||||||
| No | 153 (43.5%) | 27 (17.6%) | 41 (26.8%) | 33 (21.6%) | 46 (30.1%) | 28 (18.3%) |
| Yes | 199 (56.5%) | 36 (18.1%) | 82 (41.2%) | 73 (36.7%) | 122 (61.3%) | 85 (42.7%) |
DAI indicatesDental Anesthetic Index; GSE, Global Negative Self-Evaluation.
Table 4.
Analysis of Associations With the Outcomes Worsening of the Impact of Oral Health on Quality of Life in Mixed Dentition (n = 352)
| Outcome | Variables | Crude Effect |
Adjusted Effect (Final Model) |
||
|---|---|---|---|---|---|
| RR (CI 95%) | p-value | RR (C I95%) | p-value | ||
| Worsening of oral symptoms | Sex | 0.99 (0.93–1.06) | .8114 | — | — |
| Age 8 years (Ref: over 8 years) | 1.10 (1.02–1.20) | .0159 | 1.10 (1.02–1.20) | .0142 | |
| Skin color (Ref: Non-white) | 1.06 (1.00–1.14) | .0588 | 1.06 (1.00–1.14) | .0546 | |
| Worse in malocclusion (Ref: No) | 1.01 (0.94–1.09) | .7785 | — | — | |
| Worse in self-esteem (Ref: No) | 1.00 (0.94–1.07) | .9142 | — | — | |
| Worsening of functional limitation | Sex | 1.05 (0.98–1.13) | .1933 | — | — |
| Age 8 years (Ref: over 8 years) | 1.03 (0.95–1.12) | .4275 | — | — | |
| Skin color (Ref: Non-white) | 1.02 (0.95–1.10) | .5614 | — | — | |
| Worse in malocclusion (Ref: No) | 1.03 (0.94–1.12) | .5149 | — | — | |
| Worse in self-esteem (Ref: No) | 1.11 (1.03–1.20) | .0041 | 1.11 (1.03–1.20) | .0041 | |
| Worsening emotional well-being | Sex | 1.03 (0.96–1.11) | .4291 | — | — |
| Age 8 years (Ref: over 8 years) | 1.07 (0.99–1.17) | .0832 | 1.08 (0.99–1.17) | .0707 | |
| Skin color (Ref: Non-white) | 1.00 (0.93–1.08) | .9913 | — | — | |
| Worse in malocclusion (Ref: No) | 0.94 (0.87–1.02) | .1617 | 0.95 (0.88–1.04) | .2586 | |
| Worse in self-esteem (Ref: No) | 1.12 (1.04–1.21) | .0016 | 1.12 (1.04–1.21) | .0019 | |
| Worsening social well-being | Sex | 1.15 (1.07–1.23) | <.0001 | 1.09 (1.02–1.17) | .0145 |
| Age 8 years (Ref: over 8 years) | 1.04 (0.96–1.12) | .3139 | — | — | |
| Skin color (Ref: Non-white) | 1.00 (0.94–1.08) | .8422 | — | — | |
| Worse in malocclusion (Ref: No) | 0.96 (0.88–1.04) | .3355 | — | — | |
| Worse in self-esteem (Ref: No) | 1.24 (1.16–1.33) | <.0001 | 1.21 (1.12–1.30) | <.0001 | |
| Worsening quality of life | Sex | 1.03 (0.96–1.11) | .3776 | — | — |
| Age 8 years (Ref: over 8 years) | 1.13 (1.04–1.23) | .0024 | 1.14 (1.05–1.23) | .0010 | |
| Skin color (Ref: Non-white) | 1.06 (0.98–1.14) | .1135 | 1.06 (0.98–1.13) | .1457 | |
| Worse in malocclusion (Ref: No) | 0.94 (0.87–1.03) | .1902 | 0.97 (0.90–1.06) | .5404 | |
| Worse in self-esteem (Ref: No) | 1.20 (1.12–1.29) | <.0001 | 1.20 (1.12–1.29) | <.0001 | |
DISCUSSION
The design of a longitudinal study presents findings that contribute to understanding the management of occlusion progression from mixed dentition to permanent dentition. In this context, development of occlusion represents a challenge for orthodontics, as it demands the diagnosis of normal physiological occlusion conditions and malocclusion, and determination of what should be preserved and what should undergo orthodontic intervention.27–29At the same time, it is essential to recognize the esthetic impact of malocclusion and its potential influence on self-esteem. This knowledge highlights the motivation to consider early orthodontic intervention when necessary.
To answer this question, this study evaluated the influence of OHRQoL on dentition development, considering the occlusal transition in childhood and the role of self-esteem in a 4-year follow-up. Of the original cohort, 44.9% of children were reassessed. It is important to note that participant attrition is a common challenge in longitudinal observational studies. In this study, losses were mainly due to logistical factors, such as transfer to other schools or change of region, and not to clinical or demographic characteristics of the participants, in addition to the exclusion of children who underwent orthodontic treatment during the period, indicating that the loss was predominantly random and unlikely to introduce systematic bias.
The DAI was used to assess occlusion because it is a well-established epidemiological tool used in different populations to estimate the prevalence of malocclusion and the need for orthodontic treatment.30,31The findings revealed that 39.8% of children showed improvement in the need for orthodontic treatment. This result suggests that many conditions diagnosed as malocclusion during the mixed dentition may be physiological, supporting the hypothesis that some occlusal changes observed during this period are transient.32Additionally, it was observed that variation in the DAI over the follow-up period was associated with changes in OHRQoL scores and self-esteem. Children who showed a reduction in DAI scores upon transitioning to the permanent dentition tended to report fewer negative impacts on the social and functional well-being domains, possibly reflecting a more favorable esthetic perception and greater confidence in social interactions. On the other hand, the maintenance or increase in DAI was associated with greater negative impacts, especially on self-esteem, suggesting that the persistence of clinically evident malocclusions can amplify esthetic and psychosocial concerns. These findings reinforce the relevance of DAI not only as an epidemiological indicator of the need for treatment, but also as an indirect marker of possible repercussions on quality of life and emotional well-being. An important reason for the decreased need for orthodontic treatment is that some malocclusions can self-correct when the underlying etiological factors are treated or can improve with growth.
The association analyses explored the worsening results in the outcome variables related to OHRQoL, considering the domains and the total score of the instrument. This innovative approach allowed us to identify the factors associated with a more negative impact on the perception of OHRQoL, highlighting the individual and contextual characteristics that may contribute to this worsening, to understand the possible relationships between clinical conditions and changes in the different aspects assessed by the instrument.
The findings indicated that OHRQoL worsened during the transition from mixed to permanent dentition. This decrease was primarily observed in oral symptoms, functional limitations, emotional well-being, and social well-being. The permanent dentition stage occurs during adolescence when individuals become more concerned about appearance and peer interactions. Additionally, the adverse effects of malocclusion on OHRQoL tend to worsen with age, impacting psychological well-being, social interactions, esthetic concerns, and functional capabilities.33Also, as reported in previous studies, self-esteem is a significant psychosocial factor influencing OHRQoL.2,34High self-esteem can serve as a psychological buffer, shielding individuals from the detrimental effects of poor oral health. Conversely, children with low self-esteem may be more anxious about their malocclusion.
The literature has demonstrated in a 3-year cohort study that self-esteem was a stronger predictor of OHRQoL than the clinical severity of malocclusion.35Similar to Benson et al.,35results of the current study confirmed that the influence of self-esteem persisted even when the need for orthodontic treatment was controlled. This outcome supports the premise that psychosocial factors may mediate the relationship between malocclusion and quality of life, particularly during the transition to adolescence, when social comparisons and esthetic awareness become more pronounced. In contrast, some investigations1–4have reported stronger associations between malocclusion severity and OHRQoL than those found in the present study. Such differences may be attributed to differences in study design, cultural background, and age range, which can influence how children perceive and report the impacts of their dental appearance.1–4
Assessing self-esteem is just as important as evaluating dental esthetics and may play a significant role in OHRQoL. When it comes to children, clinical observations strengthen the need to consider orthodontic treatment options in addition to assessing their needs. It is necessary to evaluate whether elective treatments can enhance emotional well-being, psychological factors, and the functional aspects of oral health. This broader evaluation is important for understanding how orthodontic intervention impacts an individual’s overall well-being rather than focusing solely on the necessity of treatment.
A strength of this study was that it considered the worsening of the variables analyzed as an outcome: the need for orthodontic treatment, OHRQoL, and self-esteem throughout the transition from mixed to permanent dentition. Although the literature generally highlights improvements over time, this study found that many participants experienced declines in OHRQoL and self-esteem during this transition. This individual perspective underscores the importance of evaluating the positive and negative aspects of dental and psychosocial development in children. Such insights are important for informed clinical decision-making and highlight the need for early interventions. It is important to note that the sample comes from a population-based study with a high response rate, which helps to minimize the risk of bias. Future studies should focus on young adults to evaluate the impact of self-esteem and its relationship with OHRQoL.
CONCLUSIONS
Self-esteem may contribute to a decrease in OHRQoL during the transition from mixed to permanent dentition.
The findings indicate that the need for orthodontic treatment does not significantly change this relationship in childhood nor affect OHRQoL.
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