Introduction
Our study objectives were to evaluate the impact of malocclusion on oral health–related quality of life (OHRQOL) of adolescents aged 11-14 years in Ile-Ife, Nigeria.
Methods
Two hundred adolescents completed the Child Perceptions Questionnaire: Impact Short Form (CPQ 11-14 –ISF:16) and the Malocclusion Impact Questionnaire (MIQ). The Aesthetic Component of the Index of Orthodontic Treatment Need scale was used to determine malocclusion severity. The effect of sex, age, and socioeconomic class on OHRQOL were determined with the Mann-Whitney U test, Kruskal-Wallis H test, correlation tests, and multiple regression analysis using SPSS (version 22.0; IBM, Armonk, NY). Statistical significance was set at P <0.05.
Results
The CPQ 11-14 –ISF:16 and MIQ identified the impact of malocclusion on OHRQOL with mean (standard deviation) scores of 12.85 (10.17) and 8.33 (7.50), respectively. Sex, socioeconomic class, and malocclusion severity had no significant effect on OHRQOL ( P >0.05); however, OHRQOL differed significantly between the age groups (CPQ 11-14 –ISF:16, P = 0.002; MIQ, P = 0.041). Multiple regression analysis showed that age was a significant predictor of OHRQOL determined with CPQ 11-14 –ISF:16 (standardized coefficients B score = −0.242, P = 0.001). MIQ demonstrated good criterion validity with CPQ 11-14 –ISF:16 ( r = 0.59, P <0.001).
Conclusions
Both measures CPQ 11-14 –ISF:16 and MIQ identified the impact of malocclusion on the OHRQOL of adolescents. Sex, socioeconomic class, and malocclusion severity did not affect OHRQOL; however, age was a significant predictor of OHRQOL. Further studies among orthodontic patient populations are desirable.
Highlights
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Malocclusion Impact Questionnaire captured orthodontic concerns of adolescents.
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MIQ demonstrated good criterion validity with the CPQ.
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Age was a predictor of oral health–related quality of life.
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Sex, socioeconomic status, and malocclusion severity were not predictors of OHRQOL.
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Perceptions of overall well-being may not be strongly related to orthodontic concerns.
Oral health–related quality of life (OHRQOL) is a construct for assessing the self-perceived oral health of patients. It is a multidimensional construct that includes a subjective evaluation of a patient’s oral health, functional and emotional well-being, expectations and satisfaction with care, and a sense of self. This involves many aspects such as chewing ability, sleeping, social interactions, self-esteem, and satisfaction with life and oral health. Malocclusion has been reported in several studies to have a negative impact on OHRQOL.
Children and adolescents constitute a significant proportion of orthodontic patients whose quality of life can be affected by the presence of malocclusion. Among school children in Brazil, Guimarães et al found a high prevalence of malocclusion, which negatively affected OHRQOL. Similarly, Machry et al found that children with caries, gingivitis, and malocclusion had worse OHRQOL than their counterparts. Malocclusion also has a negative effect on the OHRQOL of young adults.
The impact of malocclusion on OHRQOL is related to its severity. , Children with normal occlusion or mild malocclusion are less likely to have their quality of life affected than children with severe malocclusion like obviously increased overjet. Overjet deviations >6 mm are associated with significant limitations of OHRQOL. Sun et al showed that weighted mean scores of CPQ increased with malocclusion severity; other studies also reported worse OHRQOL scores associated with higher Index of Orthodontic Treatment Need (IOTN) grades. ,
There have also been reports of improvement in the quality of life after orthodontic treatment and orthognathic surgery. However, some studies have been unable to identify significant impacts of malocclusion on OHRQOL. In Kenya, Kemoli et al found that only a few participants with malocclusion traits reported a substantial effect on their OHRQOL. Among children in Colombia and Brazil, the negative impact of malocclusions on OHRQOL was also not observed. , Individual determinants of OHRQOL may vary, with factors beyond clinical conditions such as sex, family type, parent’s and/or caregiver’s education, and age, household income, socioeconomic position, and personality traits moderating OHRQOL. , , , , Gomes et al opined that individual and contextual factors might influence OHRQOL in children.
OHRQOL has been measured using social indicators, global self-ratings of OHRQOL, and multiple items questionnaires of OHRQOL. Multiple items questionnaires are the most widely used method, which includes generic and condition-specific instruments. Generic instruments have the advantage of measuring side-effects or complications of treatment between different conditions. Condition-specific measures focus on the particular problems relevant to a disease or disorder, making them more sensitive, acceptable to participants, with higher completion rates more readily achievable.
Few condition-specific OHRQOL measures have been developed in orthodontics. The Malocclusion Impact Questionnaire (MIQ) is a relatively new condition-specific tool developed by Patel et al and Benson et al. The aim was to design a measure capable of capturing the actual and perceived issues, problems, limitations, restrictions, and adaptive strategies specific to adolescents with malocclusion. It was intended to give a better understanding of the effect of malocclusion and its treatment on young people over time, serve as an outcome measure, and in combination with normative needs assessment help to determine orthodontic treatment need.
Generic and condition-specific measures, such as the United Kingdom OHRQOL questionnaire, , Child Perceptions Questionnaire (CPQ 11-14 ), , and the Psychosocial Impact of Dental Aesthetics Questionnaire , , , have been used to evaluate the effect of malocclusion on OHRQOL in the study environment. This study aimed to evaluate the impact of malocclusion on OHRQOL of adolescents aged 11-14 years in Ile-Ife, Osun State, Nigeria, and to determine the effect of sex, age, and socioeconomic class on OHRQOL. The study hypothesis was that there would be no effect of malocclusion, sex, age, and socioeconomic class on the OHRQOL of adolescents.
Material and methods
The study was a cross-sectional survey conducted among 200 secondary school adolescents in Ile-Ife, Osun State, Nigeria. The sample size was determined using Leslie Fischer formula for the study population >10,000. Based on a previous study and considering a fall out rate of 10%, the minimum sample size required was 165, which was rounded up to 200. The study sample was selected through a multistage sampling procedure. The first stage involved the selection of 1 public and 1 private secondary school using a stratified sampling technique; classes were selected by simple random sampling in the second stage from the first 4 years of secondary school. Stage 3 involved selecting actual respondents by using stratified sampling to obtain equal numbers of male and female participants. Only children aged 11-14 years were selected; none of the participants had previous or ongoing orthodontic treatment.
Data collection tools were questionnaires administered in the English language, the official language and primary language of instruction in schools in the entire States of Nigeria. The questionnaires were completed independently by the adolescents in May and June 2017. The first section included the participants’ sociodemographic information. Socioeconomic class was determined as described by Olusanya et al. Scores 1-3 were allocated for the father’s occupation as follows: 1 = “professionals, civil servants and businessmen,” 2 = “middle-level bureaucrats, technicians, skilled artisans, well-to-do farmers and traders,” and 3 = “unskilled workers including small scale farmers.” Scores from 0 to 2 were allocated to the mother’s level of education as follows: 0 = “university level,” 1 = “secondary to tertiary but below university level,” 2 = “primary school or no formal education.” The score for both parents was summed to obtain socioeconomic classes 1 and 2 (upper), 3 (middle), and 4 and 5 (lower).
The second section had the Item Impact Short Form of the Child Perceptions Questionnaire (CPQ 11-14 –ISF:16), developed by Jokovic et al. The questions are organized into 4 health domains: oral symptoms, functional limitations, emotional well-being, and social well-being. The questions ask about the frequency of events in the previous 3 months. The response options were as follows: “Never” = 0, “Once/twice” = 1, “Sometimes” = 2, “Often” = 3, and “Every day/almost every day” = 4. Domain and overall scores were computed by the summation of items with higher scores indicating worse OHRQOL.
The third section was the MIQ. The MIQ development involved interviews, framework data analysis, and identification of themes and subthemes to generate items. The final questionnaire consists of 2 global questions and 17 items. The global questions “Overall, how much do your teeth bother you?” and “Overall, how much do your teeth affect your life?” were answered on a 5-point response format: “Not at all” = 0, “A little” = 1, “Somewhat” = 2, “Quite a bit” = 3, and “Very much.” The 17 items were measured on a 3 severity or intensity response format “Don’t/doesn’t” = 0, “A bit” = 1, and “Very/a lot” = 2. Summation of the 17 item scores results in scores of 0-34, with higher scores indicating worse OHRQOL. Scores for the global questions are presented separately.
The fourth section had the Aesthetic Component of the Index of Orthodontic Treatment Need (AC-IOTN) scale, a 10-point photographic scale developed by Brook and Shaw, which was used to record the esthetic impairment contributed by the presence of malocclusion and estimate malocclusion severity by both the participants (subjective assessment) and examiner (objective assessment).
Ethical approval was obtained from the Health Research Ethics Committee of the Institute of Public Health, Obafemi Awolowo University, Ile-Ife, with Human Research Ethics Committee no. IPH/OAU/12/819. Approval to conduct the study was also obtained from appropriate school authorities. Written informed consent and assent were obtained from the participants and their parents after duly explaining the study objectives, risks and benefits, and voluntary nature of participation. All data were collected without identifier names. Participants did not receive any cash compensation.
Statistical analysis
Data analysis was done using SPSS software (version 22.0; IBM, Armonk, NY). The Kolmogorov-Smirnov test showed that the data was not normally distributed; therefore, nonparametric tests were used. Relationships between variables were determined using Mann-Whitney U and Kruskal-Wallis H tests. For multiple regression analysis to determine the predictors of OHRQOL, malocclusion severity was dichotomized into “no need for treatment” (IOTN grades 1-4) and “need for orthodontic treatment” (IOTN grades 5-10). Criterion validity was determined using Pearson correlation tests to evaluate the relationship between CPQ 11-14– ISF:16 and MIQ. Construct validity was determined with Spearman correlation tests between CPQ 11-14– ISF:16, MIQ, and the global ratings of oral health and well-being. Internal consistency reliability was determined using Cronbach α. P values of <0.05 were accepted as significant.
Results
Two hundred adolescents with a mean (standard deviation [SD]) age of 12.68 (1.10) years, participated in this study. The mean (SD) ages of male and female participants were 12.76 (1.11) years and 12.59 (1.08) years, respectively ( P = 0.275). Most participants (45%) belonged to the high socioeconomic class, 18% middle class, and 37% low socioeconomic class. To the global questions of the MIQ, “Overall, how much do your teeth bother you?” 35.5% responded “not at all,” 34.5% “a little,” a total of 30% responded with the options “somewhat,” “quite a bit,” and “very much.” To the question “Overall, how much do your teeth affect your life?” 48% responded “not at all,” 30% responded “a little,” whereas 22% chose the other options.
Table I shows the distribution of domain and total scores for CPQ 11-14 –ISF:16 and MIQ. With CPQ 11-14 –ISF:16, there were 10 participants (5%) with floor effects (minimum score), but none with the ceiling effect (maximum score). The mean (SD) score was 12.85 (10.17). Twenty-eight participants (14%) had floor effects with MIQ, but none had the maximum attainable score. The mean (SD) score was 8.33 (7.50). Mean scores standardized to 100% gave percentage for CPQ 11-14 –ISF:16 as 20% and MIQ as 24.5%.
| Instrument | Domain | Range of possible values | Minimum | Maximum | Median | Mean | SD |
|---|---|---|---|---|---|---|---|
| CPQ 11-14 –ISF:16 | Oral symptoms | 0-16 | 0 | 12 | 4.0 | 4.27 | 2.92 |
| Functional limitations | 0-16 | 0 | 13 | 2.0 | 2.87 | 3.10 | |
| Emotional well-being | 0-16 | 0 | 12 | 2.0 | 2.91 | 3.20 | |
| Social well-being | 0-16 | 0 | 13 | 2.0 | 2.80 | 3.05 | |
| Total Score | 0-64 | 0 | 40 | 11.0 | 12.85 | 10.17 | |
| MIQ | Total score | 0-34 | 0 | 33 | 6.5 | 8.33 | 7.50 |
Comparisons of OHRQOL on the basis of sex, age, socioeconomic class, and malocclusion severity are shown in Table II (median [interquartile range]). No significant sex differences in OHRQOL were observed with both instruments ( P = 0.512 and P = 0.067, respectively). Age comparisons with the CPQ 11-14 –ISF:16 showed decreased OHRQOL median scores from the youngest to oldest age groups. Kruskal-Wallis H test showed a significant difference between them (H = 14.57, P = 0.002). A significant difference in OHRQOL between age groups was also identified with the MIQ ( H = 8.231, P = 0.041). Median scores of participants in the socioeconomic classes are as presented. Kruskal-Wallis H test showed no significant difference between the classes [(CPQ 11-14 –ISF:16, P = 0.287) (MIQ, P = 0.748)].
| Variable | n (%) | CPQ 11-14 –ISF:16 Median (Q1-Q3) | MIQ Median (Q1-Q3) |
|---|---|---|---|
| Sex | |||
| Male | 100 (50.0%) | 9.00 (3.00-17.00) | 7.00 (3.00-12.75) |
| Female | 100 (50.0%) | 13.50 (5.25-21.00) | 6.00 (1.00-15.75) |
| Mann-Whitney U | U = 4250.0, P = 0.512 | U = 4732.5, P = 0.067 | |
| Age, y | |||
| 11 | 40 (20.0%) | 17.00 (9.50-21.75) | 9.50 (3.00-16.00) |
| 12 | 43 (21.5%) | 11.00 (5.00-24.00) | 4.00 (1.00-16.00) |
| 13 | 59 (29.5%) | 10.00 (2.00-16.00) | 5.00 (1.00-12.00) |
| 14 | 58 (29.0%) | 8.00 (2.75-16.00) | 8.00 (3.00-11.25) |
| Kruskal-Wallis H | H = 14.567, df = 3, P = 0.002 ∗ | H = 8.231, df = 3, P = 0.041 ∗ | |
| SES | |||
| High SES | 90 (45.0%) | 11.00 (6.00-19.00) | 7.00 (2.75-12.25) |
| Middle SES | 36 (18.0%) | 11.50 (4.25-25.00) | 6.50 (2.00-15.00) |
| Low SES | 74 (37.0%) | 10.50 (2.00-17.00) | 6.00 (1.00-3.50) |
| Kruskal-Wallis H | H = 2.499, df = 2, P = 0.287 | H = 0.582, df = 2, P = 0.748 | |
| Subjective assessment by participants (AC-IOTN) | |||
| Grade 1 | 174 (87.0%) | 11.00 (4.00-18.25) | 7.00 (2.00-13.00) |
| Grade 2 | 20 (10.0%) | 13.50 (4.50-23.50) | 4.50 (1.00-16.75) |
| Grade 3 | 6 (3.0%) | 13.00 (5.00-16.75) | 5.00 (0.75-11.25) |
| Kruskal-Wallis H | H = 0.718, df = 2, P = 0.699 | H = 0.412, df = 2, P = 0.814 | |
| Objective assessment by examiner (AC-IOTN) | |||
| Grade 1 | 117 (58.0%) | 10.00 (3.00-17.00) | 6.00 (1.00-12.50) |
| Grade 2 | 72 (36.0%) | 12.50 (5.25-22.00) | 8.00 (3.00-15.75) |
| Grade 3 | 11 (5.5%) | 6.00 (2.00-22.00) | 4.00 (2.00-9.00) |
| Kruskal-Wallis H | H = 2.513, df = 2, P = 0.285 | H = 3.672, df = 2, P = 0.159 |
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