Introduction
Attention deficit-hyperactivity disorder is a behavioral disorder characterized by a lack of focus, impulsive behavior, and or excessive activity. This research aimed to evaluate the association between signs of attention deficit-hyperactivity disorder and malocclusion in schoolchildren.
Methods
A cross-sectional study was conducted with a representative sample of 633 children aged 7-12 years. The children were clinically examined for malocclusion using the Dental Aesthetic Index. The predominant breathing pattern was also determined. Parents answered a questionnaire addressing socioeconomic characteristics and the presence of nonnutritive sucking habits. The Swanson, Nolan, and Pelham Scale–IV was filled out by both parents and teachers to compare behavioral patterns. The children were submitted to a neuropsychological evaluation using the Raven’s Colored Progressive Matrix Test. Data analysis involved the chi-square test and Poisson regression analysis.
Results
The prevalence of malocclusion was 42% higher among children with signs of hyperactivity reported by both parents and teachers (prevalence ratio [PR], 1.42; 95% confidence interval [CI], 1.11-1.81; P = 0.004). In the final Poisson regression model, the prevalence of malocclusion was lower among schoolchildren aged 11 and 12 years (PR, 0.62; 95% CI. 0.52-0.73; P <0.001) and higher among those who used a pacifier for at least 4 years (PR, 1.25; 95% CI, 1.02-1.54; P = 0.029) as well as those classified as mouth breathers (PR, 1.28; 95% CI, 1.09-1.51; P = 0.003).
Conclusions
The prevalence of malocclusion was higher among children with signs of hyperactivity independently of age, pacifier use, and mouth breathing.
Highlights
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Malocclusion prevalence was higher in children who used a pacifier for 4 years.
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Malocclusion prevalence was higher in children classified as mouth breathers.
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Prevalence was 42% higher in children with signs of hyperactivity.
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Prevalence in these children was independent of age, pacifier use, mouth breathing.
Attention deficit-hyperactivity disorder (ADHD) is a behavioral disorder characterized by a lack of focus, impulsive behavior, and or excessive activity. ADHD can lead to the impairment of executive functions, compromising activities that require planning and concentration. , Some of the signs are a lack of attention to details, difficulty concentrating on tasks at school or during games, a lack of attention when addressed directly, failure to follow instructions, and difficulty organizing and completing tasks. Moreover, patients with ADHD avoid, dislike, or are reluctant to engage in activities that require sustained mental effort and are easily distracted. Children with signs of hyperactivity and impulsiveness often move about the classroom, run and climb on things when this type of activity is inappropriate, have difficulty playing quietly, tend to talk excessively, often answer questions in an abrupt manner, have difficulty waiting their turn, and often interrupt others.
The criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition include 9 signs and symptoms of inattention and 9 of hyperactivity and impulsivity. The diagnosis requires the occurrence of 6 or more signs and symptoms of at least 1 of these categories. It is also necessary for the symptoms to be present frequently for at least 6 months, be more pronounced than expected for the child’s level of development, occur in at least 2 different settings (eg, home and school), emerge before the age of 12 years (at least some symptoms), and exert a negative impact on functioning at home, school or work. Moreover, the symptoms cannot be better explained by another mental disorder (eg, mood, anxiety, dissociative, or personality disorder). The global prevalence of ADHD among school-age children ranges from 5% to 7%, , and this condition is reported to be more frequent in males. ,
Studies have shown that some comorbidities, such as autism spectrum disorders, depression, and anxiety, may be associated with ADHD. Children with ADHD are also more likely to have a shorter exclusive breastfeeding period and respiratory disorders involving upper airway obstruction, , sleep-disordered breathing, and obstructive sleep apnea. Respiratory disorders and a short period of exclusive breastfeeding are also associated with the occurrence of malocclusion, and studies have indicated a higher frequency of malocclusion and craniofacial changes in children with signs of ADHD. , , However, few studies have investigated the possible causal network, and it remains unclear how these variables are related.
To clarify the causal network of malocclusion in children with signs of ADHD, it is necessary to incorporate variables into a model on the basis of a conceptual framework. Thus, the present study hypothesized that children with signs of ADHD have higher frequencies of nonnutritive sucking habits and mouth breathing, with a consequently higher frequency of malocclusion. This study aimed to evaluate the possible association between signs of ADHD and malocclusion in schoolchildren aged 7-12 years and investigate the possible pathways for this association using a hierarchical approach.
Material and methods
The present study was approved by the Human Research Ethics Committee of Universidade Federal dos Vales do Jequitinhonha e Mucuri (certificate no. 045/2011). Parents and guardians received clarifications regarding the objectives and signed a statement of informed consent. This study was conducted in accordance with the principles for medical research involving human subjects stipulated in the Declaration of Helsinki. All data remained anonymous and confidential.
A cross-sectional study was conducted with a representative sample of children aged 7-12 years attending public and private schools in the city of Diamantina, Brazil. A list of the number of students enrolled in public and private schools in the city was obtained from the Municipal Department of Education. Children were randomly selected proportionately to the distribution among municipal public schools (70%), state-run public schools (20%), and private schools (10%). Children with a past or current history of orthodontic treatment, those with intellectual disability (score at or below the fifth percentile of Raven’s Colored Progressive Matrices test), and those with neurologic diseases (based on parental reports) were excluded from the study.
The sample size was calculated considering a 40.1% prevalence rate of malocclusion, 95% confidence interval (CI), and 4% acceptable estimate error. As 2-stage sampling was performed (schools and classes), a design effect of 1.1 was also considered, leading to a minimum sample of 635 participants. To compensate for possible dropouts, we increased this number by 64 patients, leading to a total of 699 children.
Data collection took place in private rooms at the schools, with the child sitting in a chair in front of the examiner. Disposable mouth mirrors (PRISMA, São Paulo, São Paulo, Brazil), a periodontal probe (Trinity, Campo Mourão, PA, Brazil), headlamp (PETZL, Tikka XP, Crolles, France), and gauze were used for the clinical dental examination.
Dental examinations were performed by 2 dentists (I.M.V.; M.A.H.) and 2 assistants (L.D.R.; L.E.P.C.). The examiners participated in theoretical and practical training as well as calibration exercises for the diagnosis of malocclusion. Interexaminer and intraexaminer kappa values were higher than 0.82. Neuropsychological tests were performed by another team composed of 2 examiners. The results of the neuropsychological tests were analyzed and interpreted by a psychologist (F.O.F).
The Dental Aesthetic Index (DAI) was used for the investigation of malocclusion. The results were interpreted as follows: DAI ≤25 = normal, no need or slight need for treatment; 26≤ DAI ≤30 = definite malocclusion, treatment elective; 31 ≤ DAI ≤ 35 = severe malocclusion, treatment highly desirable; and DAI ≥36 = very severe malocclusion, treatment mandatory. Malocclusion was dichotomized as absent (DAI ≤25) or present (DAI ≥26).
The intellectual evaluation involved the use of the Raven’s Colored Progressive Matrices test, which has been validated for children aged from 5 to 12 years in Brazil. The test consists of a book with 36 drawings. Each drawing has 1 missing piece and 6 options to complete the drawing. The result is interpreted on the basis of the percentile, with percentiles equal to or less than 5 indicating intellectual disability.
The Swanson, Nolan, and Pelham Scale–IV is used to analyze child behavioral patterns through subscales for the identification of inattention, hyperactivity and/or impulsivity, and oppositional and/or defiant behavior. Considering the objectives of the present study, we used only the subscales for signs of inattention and hyperactivity and/or impulsivity. The Swanson, Nolan, and Pelham Scale–IV was answered by the parents or caregivers and teachers of each participant as a way of comparing behavioral patterns in the family and school settings, as this is part of the criteria for the diagnosis of ADHD. Thus, signs of ADHD were identified on the basis of the reports of both the parents or caregivers and teachers. Each subscale has 9 items scored with the following options: 0 = not at all , 1 = just a little , 2 = quite a bit , and 3 = very much . The total is calculated by the sum of the item scores of each subscale divided by the total number of items on the subscale. Signs of ADHD were considered present when the mean score on the inattention subscale was >1.78 according to parents and caregivers and >2.56 according to teachers and when the score on the hyperactivity subscale was >1.44 according to parents and caregivers and >1.78 according to teachers.
The parents and caregivers answered a questionnaire addressing socioeconomic and/or demographic data and nonnutritive sucking habits. Information was collected on the child’s age and sex, parent’s or caregiver’s schooling, and family income. Age was dichotomized by the median. Parent’s or caregiver’s schooling was dichotomized as ≤8 or >8 years of study (cutoff point corresponding to a complete elementary school education). Family income was categorized on the basis of the Brazilian monthly minimum wage (approximately $270). Information was collected on the history and duration of pacifier use, finger and/or thumb sucking, and bottle feeding. Sucking habits were dichotomized as <48 or ≥48 months, on the basis of the findings of a previous study.
The following are the most striking characteristics of mouth breathing: tongue with the dorsum raised and tip lowered; tongue on the floor of the mouth or interposed anteriorly between the arches; thick, everted lower lip; over-functioning of the mentalis muscle; flaccidity of the lips, tongue, and cheeks; atypical swallowing; facial asymmetry; noisy respiration; an increased height of the face; maxillary atresia; malocclusion; and a narrow, high palate. These characteristics were observed as complementary factors to establish the diagnosis of the breathing pattern. The examiner also kept the children seated comfortably for 5 minutes for observation and evaluation of the predominant breathing type. If a child spent a larger portion of the time with his or her mouth open, mouth breathing was recorded. In this investigation, a child was considered to be a mouth breather when presenting predominantly oral breathing during the examiner’s observation and at least 1 of the clinical characteristics described above.
Statistical analysis
The data were analyzed using SPSS Statistics for Windows (version 22.0; IBM, Armonk, NY). A conceptual proposal was structured to explain the possible pathways of associations between the explanatory variables and malocclusion ( Fig ). Socioeconomic and/or demographic variables, nonnutritive sucking habits, and mouth breathing may act as confounding variables interfering in the association between signs of ADHD and malocclusion. These variables can also act as mediators between the main independent variable (signs of ADHD) and malocclusion. Descriptive statistics (absolute and relative frequencies) were performed. The chi-square test was used to investigate associations between the categorical variables and the occurrence of malocclusion. Independent variables with a P <0.25 in the bivariate analysis and those with theoretical justification were incorporated into the multivariate model. The Poisson regression model followed a hierarchical approach from distal to proximal determinants in the following order: socioeconomic and/or demographic factors, characteristics of the child, signs of ADHD, and oral habits. On each level, Poisson regression with robust variance was performed to determine associations between the independent variables and malocclusion (absent or present). Prevalence ratios (PR) and 95% CIs were calculated. The level of significance was set at 5% ( P <0.05).
Results
A total of 633 (90.55%) schoolchildren participated through to the end of the study. The main reason for losses was incomplete questionnaires. The majority of the participants (57.1%) had malocclusion. The mean age of the overall sample was 9.42 ± 1.58 years, and the female sex accounted for 59.0% (n = 374). Significant differences between groups (with and without malocclusion) were found regarding age, pacifier use, finger and/or thumb sucking, mouth breathing, and reports of signs of hyperactivity by parents or guardians and teachers. No significant associations were found between malocclusion and child’s sex, caregiver’s schooling, household income, or inattention (reported in both contexts) ( Table I ).
| Variables | Malocclusion | ||
|---|---|---|---|
| No | Yes | P ∗ | |
| Child’s sex | 0.198 | ||
| Male | 103 (38.0) | 156 (43.1) | |
| Female | 168 (62.0) | 206 (56.9) | |
| Age, y | <0.001 | ||
| 7-10 | 124 (45.8) | 236 (65.2) | |
| 11-12 | 137 (50.6) | 102 (28.2) | |
| Caregiver’s schooling, y | 0.143 | ||
| >8 | 177 (65.6) | 255 (71.0) | |
| ≤8 | 93 (34.4) | 104 (29.0) | |
| Household income | 0.377 | ||
| ≥2 × BMMW | 103 (38.3) | 150 (41.8) | |
| <2 × BMMW | 166 (61.7) | 209 (58.2) | |
| Pacifier use, mo | 0.034 | ||
| <48 | 261 (96.3) | 334 (92.3) | |
| ≥48 | 10 (3.7) | 28 (7.7) | |
| Finger and/or thumb sucking, mo | 0.044 | ||
| <48 | 247 (91.1) | 311 (85.9) | |
| ≥48 | 24 (8.9) | 51 (14.1) | |
| Mouth breathing | 0.031 | ||
| No | 239 (88.8) | 296 (82.7) | |
| Yes | 30 (11.2) | 62 (17.3) | |
| Inattention (reported in both contexts) | 0.717 | ||
| No | 261 (97.0) | 351 (97.5) | |
| Yes | 8 (3.0) | 9 (2.5) | |
| Hyperactivity (reported in both contexts) | 0.051 | ||
| No | 266 (98.5) | 345 (95.8) | |
| Yes | 4 (1.5) | 15 (4.2) | |
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