Impact of oral health problems on school absenteeism in public schoolchildren: A structural equation model

Impact of oral health problems on school absenteeism in public schoolchildren: A structural equation model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of oral health problems on school absenteeism in public schoolchildren: A structural equation model Natália dos Santos, Pablo Silveira Santos, Juliana Silva Moro, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8254244/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: Determine the prevalence and factors associated with school absenteeism due to oral health problems in schoolchildren aged 8 to 10 years. Methods: A cross-sectional study was conducted with children randomly selected from public schools in Florianópolis, Santa Catarina, Brazil. School absenteeism was collected through a question based on the Child Perception Questionnaire 8–10 years answered by the children. Independent variables included sociodemographic characteristics (sex, age, family income, and caregivers' educational level) and history of toothache. During clinical examinations, data were collected on untreated dental caries, PUFA index, and dental trauma. The pathways between school absenteeism and the independent variables were analyzed using structural equation modeling. A 5% significance level was considered. Results: In total, 1,482 children participated in the study. The prevalence of school absenteeism was 22.1%. School absenteeism was directly affected by the presence of toothache (CP: 0.186, P<0.01). The PUFA index (via toothache), dental caries (via PUFA), sex (via toothache), and age (via PUFA) had indirect effects on school absenteeism. Conclusion: It was concluded that school absenteeism is directly influenced by the presence of toothache in schoolchildren. School absenteeism toothache schoolchildren oral health Figures Figure 1 Introduction School absenteeism refers to a student’s absences, whether justified or not, during elementary and secondary education (Kearney, 2008 ). This situation is concerning and affects school systems worldwide, as it often precedes permanent school dropout (Gubbels et al., 2019 ; Kearney, 2008 ). In the long term, it can lead to mental, occupational, and economic deprivation problems in adulthood (Tramontina et al., 2001 ). Oral health may be associated with school absenteeism as it directly interferes with the psychosocial and clinical aspects of children and adolescents (Agaku et al., 2015 ). Dental problems can impact systemic health, cognitive, functional, and psychological aspects, as well as self-esteem, influencing growth, socialization, nutrition, and well-being. Consequently, children and adolescents with poor general and oral health tend to have a lower quality of life, which can negatively impact academic performance and increase school absenteeism (Piovesan et al., 2012 ; Shaikh et al., 2016 ). Karam (2024), in a systematic review with meta-analysis, concluded that students with a history of toothache were 3.7 times more likely to miss school and 71% more likely to miss classes due to toothache (Karam et al., 2024 ). These findings are consistent with previous evidence. Ruff et al. ( 2019 ) reported that children with high dental caries indices tend to have lower school attendance and academic performance (Ruff et al., 2019 ), while Piovesan et al. ( 2012 ) found that oral health-related quality of life was associated with missed school days and reduced academic achievement (Piovesan et al., 2012 ). Similarly, Paula et al. ( 2016 ) emphasized that even when carious lesions are treated during the school year, students who had the disease at the beginning of the academic year performed worse than those without carious lesions. This indicates that, even after treatment, the experience of active disease remains an important risk indicator for poor academic performance (Paula et al., 2016 ). To the best of our knowledge, this is the first study to examine the mechanisms through which these conditions may influence school absenteeism in children using Structural Equation Modeling (SEM). This analytical approach enables the simultaneous incorporation of multiple mediators and variables, allowing for the estimation of both direct and indirect pathways leading to the outcome. A clearer understanding of these complex mechanisms can assist dentists in identifying potential triggers of absenteeism among school-aged children and, consequently, support the development of preventive strategies to be integrated into students’ daily routines. Furthermore, ensuring regular access to dental services is essential. Through oral health programs aimed at school-aged children, dentists can mitigate the negative impact of poor oral health on quality of life and reduce unmet dental needs (Ruff et al., 2023 ). Understanding the risk factors for school absenteeism is significant for clinical practice and for the development of strategies to prevent or mitigate these factors. (Paula et al., 2016 ) Given that school absenteeism is a critical problem and that dental problems are associated with this adversity, it is important to determine the prevalence and factors associated with school absenteeism due to oral health problems. This knowledge can contribute to improving public health interventions in oral care, benefiting schoolchildren. Therefore, this study aimed to determine the prevalence and factors associated with school absenteeism due to oral health problems in children aged 8 to 10 years in Florianópolis, Santa Catarina, Brazil. Methods This study consists of a secondary analysis from an "umbrella" research project titled "Oral health-related quality of life in schoolchildren from Florianópolis/SC,", approved by the Ethics Committee on Research Involving Humans of the State University of Santa Catarina (UDESC), under protocol no. 902.663 (CAAE: 36599914.8.0000.0118). Data collection was conducted in 2015 and followed international statutes and national legislation on research ethics involving human subjects. All children and their legal guardians consented to participate by signing, respectively, an Assent Form and an Informed Consent Form. Study Design and Sample Selection A cross-sectional study was conducted with children randomly selected from public schools in Florianópolis, Santa Catarina, Brazil, between May and December 2015. The present report adheres to the guidelines from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE Statement) (Von Elm et al., 2008 ). To determine the sample size, the prevalence of school absenteeism was assumed to be 50%, since it was unknown for this population. A 95% confidence interval (CI) and a 5% standard error were adopted, resulting in 354 participants for each age group and a minimum sample size of 1,062 children. A correction factor of 1.2 was applied to increase precision due to the multi-stage sampling method, resulting in a sample of 1,275 children. Additionally, 20% was added to account for potential losses, leading to a minimum recruitment target of 1,530 children. Initially, stratification was performed based on the health districts of Florianópolis, according to the criteria of the Unified Health System (SUS). The 36 municipal schools in Florianópolis were listed and distributed across the corresponding health districts. Cluster sampling was then conducted, with schools being randomly selected while maintaining proportionality in the number of schools and students from 2nd to 5th grade within each district. Subsequently, all enrolled students were invited to participate. Children aged 8 to 10 who were enrolled in a public school and accompanied by a caregiver or guardian were eligible to participate in the study. Children who were non-literate or using fixed orthodontic appliances were excluded. Outcome The outcome assessed in this study was school absenteeism due to oral health problems. This information was collected through a question answered by the children themselves: “In the past month, how many times have you missed school because of your teeth or mouth?” The question was based on the Child Perception Questionnaire 8–10 years (CPQ8–10) (Barbosa et al., 2009 ). Possible answers included: “never,” “once or twice,” “sometimes,” “often,” and “every day or almost every day.” For statistical analysis, the variable was dichotomized into: no history of school absenteeism in the past month (“never”) and history of absenteeism (“once or twice,” “sometimes,” “often,” and “every day or almost every day”). Non-Clinical Data Collection The history of toothache was collected through a question directed to the child: “In the past month, how many times have you had a toothache?” Possible answers included: “never,” “once or twice,” “sometimes,” “often,” and “every day or almost every day.” The variable was dichotomized into: no history of toothache in the past month (“never”) and history of toothache (“once or twice,” “sometimes,” “often,” and “every day or almost every day”). Other non-clinical data were collected through a questionnaire sent to parents/guardians, which included questions on the child’s sociodemographic information (sex and age) and the guardian’s information (educational level and family income). The educational level of guardians was dichotomized as “≤8 years” and “>8 years” of schooling, categorized based on an 8-year cutoff point corresponding to elementary education in Brazil. Family income was classified based on the Brazilian minimum wage at the time of data collection (approximately R $ 788) and dichotomized as “≤2 minimum wages” and “>2 minimum wages.” Clinical Data Collection Clinical data collection was conducted by four examiners following a standardized protocol in the school environment, adhering to biosafety standards. Each child was seated in a school chair facing the examiner. The oral cavity was cleaned with gauze, and visual inspection was performed using artificial light (LED flashlight) and dental mirrors. Each examination was conducted individually in a private setting. Clinical signs of dental trauma in permanent anterior teeth were collected based on the classification proposed by Andreasen et al. ( 2007 ) (Andreasen, Jens Ove et al., 2007), which includes enamel fractures, enamel-dentin fractures, luxation, discoloration, and avulsion. Children were categorized as “with” or “without” dental trauma signs. Large overjet were measured with the aid of a millimetre periodontal probe. The largest irregularities were assessed and recorded in millimetres (mm). The overjet was considered large when it was equal to or superior to 6 mm since previous studies reported that laypeople only associate overjet with poor dental aesthetic when it is ≥ 6 mm (Soh et al., 2006 ). Examiner Calibration and Pilot Study Before data collection, four examiners and four assistants were trained. The assistants were trained to standardize the recording of information in clinical forms. Initially, the examiners received theoretical training, weekly, about oral health issues (dental caries and its clinical consequences [PUFA], as well as dental trauma). Subsequently, calibration was performed between the examiners and a “gold standard” (a pediatric dentistry specialist) using oral examinations of 20 children aged 8 to 10 years. The children were independently examined by the “gold standard” and the four examiners. After seven days, the same children were reexamined to assess the examiners' stability in accurately diagnosing conditions, with intra- and inter-examiner Kappa coefficients exceeding 0.7. A pilot study was conducted with 30 children to verify the reproducibility of the proposed methodology. No methodological changes were necessary, as the instruments were deemed adequate for the study's purpose. The children involved in the pilot study and calibration were excluded from the final sample. Statistical Analysis Data were analyzed using STATA 14.0 software (Stata Corporation, College Station, TX, USA). The pathways between school absenteeism, sociodemographic data, and clinical data were constructed using Structural Equation Modeling (SEM), which allows the estimation of direct and indirect effects of explanatory variables (sociodemographic and clinical) on the outcome variable (school absenteeism). Additionally, a Pathway Diagram was created to represent the relationships between the studied variables visually. A significance level of 5% was adopted. The model’s goodness-of-fit was assessed using the following Modification Indices (MI): Root Mean Square Error of Approximation (RMSEA) with its 90% confidence interval (CI), which should have values ≤ 0.05; Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) with values ≥ 0.9; and Standardized Root Mean Square Residual (SRMR) with values ≤ 0.08 (Menegazzo et al., 2022 ). Results A total of 1,482 children were included in the study and answered the question related to school absenteeism, corresponding to a response rate of 96.8%. The prevalence of school absenteeism was 22.1%. Table 1 presents information on the sociodemographic and clinical characteristics of the sample, considering the occurrence of school absenteeism. Table 1 Sample characteristics considering the occurrence of school absenteeism (n = 1482) Variables n (%) School absenteeism No n (%) Yes n (%) Sociodemographic variables Gender Male Female 630 (42,5) 852 (57,5) 482 (76,5) 673 (79,0) 148 (23,5) 179 (21,0) Age 8 years 9 years 10 years 503 (33,9) 528 (35,6) 451 (30,4) 369 (73,4) 405 (76,7) 381 (84,5) 134 (26,6) 123 (23,3) 70 (15,5) Caregiver’s educational level ≤ 8 years >8 years 764 (51,6) 718 (48,4) 579 (75,8) 576 (80,2) 185 (24,2) 142 (19,2) Household income ≤ 2 Minimum wage > 2 Minimum wage 412 (27,8) 1070 (72,2) 326 (79,1) 829 (77,5) 86 (20,9) 241 (22,5) Clinical oral conditions Toothache Absent Present 725 (48,9) 757 (51,1) 634 (87,5) 521 (68,8) 91 (12,6) 236 (31,2) Dental trauma Absent Present 1330 (89,7) 152 (10,3) 1036 (77,9) 119 (78,3) 294 (22,1) 33 (21,7) Large Overjet (≥ 6 mm) Absent Present 1345 (90,8) 137 (9,2) 1054 (78,4) 101 (73,7) 291 (21,6) 36 (26,3) PUFA/pufa index Absent Present 1174 (79,2) 308 (20,8) 939 (80,0) 216 (70,1) 235 (20,0) 92 (29,9) Untreated dental caries Absent Present 1228 (82,9) 254 (17,1) 973 (79,2) 182 (71,7) 255 (20,8) 72 (28,3) The standardized coefficients estimated for the initial and final structural models are presented in Table 2 . Figure 1 shows the pathway diagram. School absenteeism was directly affected by the presence of toothache (CP: 0.186, P < 0.01). Other variables did not have a direct impact on school absenteeism. However, toothache was directly related to the presence of the PUFA index and the child's sex. Additionally, the PUFA index was directly influenced by dental caries (CP: 0.129, P < 0.01), which, in turn, was directly influenced by the child's age (CP: 0.035, P < 0.01). Table 2 Estimated standardized coefficients for indicators of the initial and final structural models Pathways Standardizes coefficients Initial model Final model School absenteeism Toothache 0.186 (P < 0.01) 0.186 (P < 0.01) Toothache Dental trauma -0.007 (P = 0.86) - PUFA/pufa index 0.180 (P < 0.01) 0.183 (P < 0.01) Untreated dental caries 0.025 (P = 0.46) - Sex 0.077 (P < 0.01) 0.077 (P < 0.01) Age -0.002 (P = 0.89) - Dental trauma Sex -0.023 (P = 0.13) - Age 0.009 (P = 0.32) - Large Overjet (≥ 6 mm) 0.080 (P < 0.01) 0.080 (P < 0.01) PUFA/pufa index Untreated dental caries 0.129 (P < 0.01) 0.129 (P < 0.01) Untreated dental caries Sex -0.028 (P = 0.14) - Age 0.035 (P < 0.01) 0.034 (P < 0.01) Household income -0.018 (P = 0.39) - Household income Caregiver’s educational level -0.014 (P = 0.531) - Model fit RMSEA (90% CI) 0.035 (0.024–0.046) CFI 0.812 TLI 0.753 SRMR 0.032 Abreviations: CI – Confidence interval; CFI – Comparative Fit Index ; RMSEA – Root Mean Square Error of Approximation ; SRMR – Standardized Root Mean Square Residual ; TLI – Tucker-Lewis Index Font: Created by author in Canva (Perth, Sydney, Australia) Discussion The main finding of this study was that the prevalence of school absenteeism in the present sample was 22.1%, with this occurrence being directly influenced by self-reported toothache. Furthermore, the main factors associated with toothache included dental caries and its untreated clinical consequences (PUFA index), age, and sex. This finding is significant, as school absenteeism negatively affects children's academic performance and social interactions within the school environment (Ansari and Pianta, 2019 ; Cozzi and Barbi, 2020 ). Considering oral health as a causal factor, analyzing toothache and its associated factors can reveal population needs and guide the implementation of preventive measures to supportchildren and their families maintain good oral health, positively impacting school attendance (Santos et al., 2019 ). Pongpichit et al. ( 2008 ) reported a 22.5% prevalence of school absences due to dental reasons, including treatment. When considering only toothache as the reason for absenteeism, the prevalence dropped to 0.5%. This highlights that dental appointments were more common causes of absenteeism than toothache itself. Overall, daily attendance records showed that children missed 159 hours of school in a year for dental consultations or toothache. Additionally, 547 hours were spent on dental exams or treatments provided by the Thai healthcare system. A comparative analysis should consider that this study evaluated school records and dental health documentation over 1-year period (Pongpichit et al., 2008 ). The relationship between toothache and school absenteeism aligns with findings by Krisdapong et al. ( 2013 ), who concluded that children with toothache or poor oral health were more likely to miss school or perform poorly academically. This can be explained by the emotional, psychological, and biological significance of toothache for patients, especially in the age group studied. (Krisdapong et al., 2013 ) Toothaches can cause functional limitations and impair children's ability to fulfill their expected roles at school. It is also associated with sleep disturbances, difficulties in chewing, and socializing (Brondani et al., 2018 ; Santos et al., 2019 ). Children experiencing a negative impact on quality of life are up to three times more likely to miss school compared to those with little or no effect (Krisdapong et al., 2013 ). Our results indicate that the clinical consequences of untreated dental caries, represented by the PUFA index, and the child's sex were directly associated with toothache. This finding is consistent with other studies (Santos et al., 2019 ). Regarding the PUFA index, it is an important indicator as it reveals that the clinical consequences of untreated dental caries - such as pulp involvement and dental abscess - can be more severe than the carious lesions themselves and are often associated with reports of pain (Karki et al., 2019 ; Monse et al., 2010 ; Santos et al., 2019 ). Regarding sex, when evaluated independently, a higher percentage of boys reported missing school. Gubbels et al. ( 2019 ) found, in their systematic review, that boys tend to have a more negative attitude toward school than girls (Gubbels et al., 2019 ). Additionally, Piovesan et al. ( 2012 ) found that being female was associated with better academic performance. (Piovesan et al., 2012 ) However, when related to pain, other studies in children and adolescents reported that girls were significantly more likely to report oral health problems (Krisdapong et al., 2013 ). In Santos et al. ( 2019 ), toothache was more frequent among girls. The justification used was that this difference between sexes may reflect cultural norms, where boys express less pain and, consequently, report fewer dental issues. Therefore, this result should be interpreted cautiously (Santos et al., 2019 ). Another established relationship was between dental caries and the child’s age. In our study, the age group most affected by school absenteeism was 8 years old. In Krisdapong et al. ( 2013 ), a statistically significant association was found between school absenteeism and the DMFT index for 12-year-old children, but not for 15-year-olds. (Krisdapong et al., 2013 ) A possible explanation is that children’s cognitive development regarding health and disease increases with age. Consequently, younger children, who have less understanding of their symptoms, tend to interpret them differently than older children. Agaku et al. ( 2015 ) found a higher prevalence of decayed teeth among children under nine years old. (Agaku et al., 2015 ) In our study, the factors indirectly influencing school absenteeism were the PUFA index and sex (via toothache), as well as dental caries and age (via the PUFA index). Overall, these pathways summarize what has already been discussed: the consequences of untreated dental caries, including pain and absenteeism, and the central role of toothache in school absenteeism. The independent variables, increased overjet and dental trauma, were included in our analyses because dental trauma can cause toothache, which could justify school absenteeism (Moura-Leite et al., 2011 ). As a result, overjet was positively associated with dental trauma, a relationship well-established in the literature (Da Silva et al., 2021 ). However, neither variable directly or indirectly influenced our outcome, which can be explained by the episodic nature of such cases, reducing the likelihood of statistical significance. Thus, school absenteeism can be seen as a "socio-dental" indicator, measuring the extent to which children’s oral health problems and their treatment interfere with everyday routines and impact behaviors of both the children and their families (Pongpichit et al., 2008 ). The findings from this study can inform and justify the development and improvement of interventions aimed at preventing further occurrences of school absenteeism through the prevention and treatment of oral diseases (Agaku et al., 2015 ; Gubbels et al., 2019 ; Krisdapong et al., 2013 ). It is essential to emphasize that dental policymakers should plan interventions so that school dental services are predominantly available outside of school hours (Pongpichit et al., 2008 ). The results of this study are important because we obtained a representative sample with a high response rate, ensuring the reliability of the research. Furthermore, a toothache can negatively affect not only the learning process but also other important aspects such as socialization. In adulthood, the absence of education may impact an individual’s professional skills, hinder entry into the labor market, and affect the country’s economy (Ansari and Pianta, 2019 ; Santos et al., 2019 ). Studies on academic performance are critical because schools have traditionally been the primary target of oral health promotion initiatives, which deliver health education messages to entire school populations. These studies are also relevant for public health program planning and can help identify groups with higher levels of need (Piovesan et al., 2012 ; Santos et al., 2019 ). Study Limitations The study's limitations include the relatively short evaluation period for absenteeism (1 month) and the method of data collection, which relied on self-reporting. The dichotomization of responses for statistical analysis may also have overestimated the effect. Additionally, the sample only included children from public schools. For future studies, we suggest that data collection be conducted over a longer time frame, such as three months, to allow for inferences about academic performance (Piovesan et al., 2012 ). Moreover, school attendance records can be obtained through documentation provided by schools and/or dental records, avoiding recall bias in children's self-reported questionnaires. Conclusion It was found that 22.1% of students aged 8 to 10 years in public schools in Florianópolis, Santa Catarina, were absent from school. Self-reported toothache is directly linked to this issue. Other factors, such as sex, age, untreated dental caries, and its clinical consequences (PUFA/pufa index), are indirectly related to school absenteeism. Declarations Author Contribution NS, PSS, JSM, FCV, CMS, MB, and MC conceived the ideas (conceptualization); NS, PSS and JSM collected the data; NS, PSS and JSM formal analysis; NS, PSS, JSM and FCV led the writing (original draft), and all authors revised the final version of the manuscript. Acknowledgement This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior—Brasil (CAPES), Grant number 001. 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Time Absent from School due to Dental Conditions and Dental Care in Thai Schoolchildren. J Public Health Dent 68, 76–81. https://doi.org/10.1111/j.1752-7325.2007.00051.x Ruff, R.R., Habib, R., Godín, T.B., Niederman, R., 2023. School-based caries prevention and the impact on acute and chronic student absenteeism. The Journal of the American Dental Association 154, 753–759. https://doi.org/10.1016/j.adaj.2023.05.007 Ruff, R.R., Senthi, S., Susser, S.R., Tsutsui, A., 2019. Oral health, academic performance, and school absenteeism in children and adolescents. The Journal of the American Dental Association 150, 111-121.e4. https://doi.org/10.1016/j.adaj.2018.09.023 Santos, P.S., Martins-Júnior, P.A., Paiva, S.M., Klein, D., Torres, F.M., Giacomin, A., Gonçalves, B.M., Konrath, A.C., Bolan, M., Cardoso, M., 2019. Prevalence of self-reported dental pain and associated factors among eight- to ten-year-old Brazilian schoolchildren. PLoS ONE 14, e0214990. https://doi.org/10.1371/journal.pone.0214990 Shaikh, S., Siddiqui, A.A., Aljanakh, M., 2016. School Absenteeism due to Toothache among Secondary School Students Aged 16–18 Years in the Ha’il Region of Saudi Arabia. Pain Research and Treatment 2016, 1–4. https://doi.org/10.1155/2016/7058390 Soh, J., Chew, M.T., Chan, Y.H., 2006. Perceptions of dental esthetics of Asian orthodontists and laypersons. American Journal of Orthodontics and Dentofacial Orthopedics 130, 170–176. https://doi.org/10.1016/j.ajodo.2005.05.048 Tramontina, S., Martins, S., Michalowski, M.B., Ketzer, C.R., Eizirik, M., Biederman, J., Rohde, L.A., 2001. School Dropout and Conduct Disorder in Brazilian Elementary School Students. Can J Psychiatry 46, 941–947. https://doi.org/10.1177/070674370104601006 Von Elm, E., Altman, D.G., Egger, M., Pocock, S.J., Gøtzsche, P.C., Vandenbroucke, J.P., 2008. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Journal of Clinical Epidemiology 61, 344–349. https://doi.org/10.1016/j.jclinepi.2007.11.008 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8254244","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559322448,"identity":"0de8ccec-5d0b-4615-888a-9e6de798ddd9","order_by":0,"name":"Natália dos 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11:00:54","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81058,"visible":true,"origin":"","legend":"","description":"","filename":"ae9306bfe76f48f396964618c22cd49b1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8254244/v1/a7324593eae22ddc29d91080.xml"},{"id":98218272,"identity":"9475757e-21ba-4988-a57e-2876180cdf59","added_by":"auto","created_at":"2025-12-15 11:00:54","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":87396,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8254244/v1/af43a267d0f3bdd3a08ed97e.html"},{"id":98218265,"identity":"2c7ebbba-efd7-4993-9c30-a886eb50fc2f","added_by":"auto","created_at":"2025-12-15 11:00:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":66083,"visible":true,"origin":"","legend":"\u003cp\u003ePathways analysis between scholar absenteeism and associated factors (final model)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8254244/v1/1b27db2b6879a4694f4f95d0.png"},{"id":103923985,"identity":"3cb7dd3e-76f3-479f-aee6-95d272440a3b","added_by":"auto","created_at":"2026-03-04 14:57:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":795464,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8254244/v1/a3b18e58-e262-436e-950c-a9aff334a930.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of oral health problems on school absenteeism in public schoolchildren: A structural equation model","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSchool absenteeism refers to a student\u0026rsquo;s absences, whether justified or not, during elementary and secondary education (Kearney, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This situation is concerning and affects school systems worldwide, as it often precedes permanent school dropout (Gubbels et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kearney, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In the long term, it can lead to mental, occupational, and economic deprivation problems in adulthood (Tramontina et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOral health may be associated with school absenteeism as it directly interferes with the psychosocial and clinical aspects of children and adolescents (Agaku et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Dental problems can impact systemic health, cognitive, functional, and psychological aspects, as well as self-esteem, influencing growth, socialization, nutrition, and well-being. Consequently, children and adolescents with poor general and oral health tend to have a lower quality of life, which can negatively impact academic performance and increase school absenteeism (Piovesan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Shaikh et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eKaram (2024), in a systematic review with meta-analysis, concluded that students with a history of toothache were 3.7 times more likely to miss school and 71% more likely to miss classes due to toothache (Karam et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These findings are consistent with previous evidence. Ruff et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported that children with high dental caries indices tend to have lower school attendance and academic performance (Ruff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while Piovesan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) found that oral health-related quality of life was associated with missed school days and reduced academic achievement (Piovesan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Similarly, Paula et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) emphasized that even when carious lesions are treated during the school year, students who had the disease at the beginning of the academic year performed worse than those without carious lesions. This indicates that, even after treatment, the experience of active disease remains an important risk indicator for poor academic performance (Paula et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, this is the first study to examine the mechanisms through which these conditions may influence school absenteeism in children using Structural Equation Modeling (SEM). This analytical approach enables the simultaneous incorporation of multiple mediators and variables, allowing for the estimation of both direct and indirect pathways leading to the outcome. A clearer understanding of these complex mechanisms can assist dentists in identifying potential triggers of absenteeism among school-aged children and, consequently, support the development of preventive strategies to be integrated into students\u0026rsquo; daily routines.\u003c/p\u003e\u003cp\u003eFurthermore, ensuring regular access to dental services is essential. Through oral health programs aimed at school-aged children, dentists can mitigate the negative impact of poor oral health on quality of life and reduce unmet dental needs (Ruff et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Understanding the risk factors for school absenteeism is significant for clinical practice and for the development of strategies to prevent or mitigate these factors. (Paula et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) Given that school absenteeism is a critical problem and that dental problems are associated with this adversity, it is important to determine the prevalence and factors associated with school absenteeism due to oral health problems. This knowledge can contribute to improving public health interventions in oral care, benefiting schoolchildren. Therefore, this study aimed to determine the prevalence and factors associated with school absenteeism due to oral health problems in children aged 8 to 10 years in Florian\u0026oacute;polis, Santa Catarina, Brazil.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study consists of a secondary analysis from an \"umbrella\" research project titled \"Oral health-related quality of life in schoolchildren from Florian\u0026oacute;polis/SC,\", approved by the Ethics Committee on Research Involving Humans of the State University of Santa Catarina (UDESC), under protocol no. 902.663 (CAAE: 36599914.8.0000.0118). Data collection was conducted in 2015 and followed international statutes and national legislation on research ethics involving human subjects. All children and their legal guardians consented to participate by signing, respectively, an Assent Form and an Informed Consent Form.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Sample Selection\u003c/h2\u003e\u003cp\u003eA cross-sectional study was conducted with children randomly selected from public schools in Florian\u0026oacute;polis, Santa Catarina, Brazil, between May and December 2015. The present report adheres to the guidelines from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE Statement) (Von Elm et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). To determine the sample size, the prevalence of school absenteeism was assumed to be 50%, since it was unknown for this population. A 95% confidence interval (CI) and a 5% standard error were adopted, resulting in 354 participants for each age group and a minimum sample size of 1,062 children. A correction factor of 1.2 was applied to increase precision due to the multi-stage sampling method, resulting in a sample of 1,275 children. Additionally, 20% was added to account for potential losses, leading to a minimum recruitment target of 1,530 children.\u003c/p\u003e\u003cp\u003eInitially, stratification was performed based on the health districts of Florian\u0026oacute;polis, according to the criteria of the Unified Health System (SUS). The 36 municipal schools in Florian\u0026oacute;polis were listed and distributed across the corresponding health districts. Cluster sampling was then conducted, with schools being randomly selected while maintaining proportionality in the number of schools and students from 2nd to 5th grade within each district. Subsequently, all enrolled students were invited to participate. Children aged 8 to 10 who were enrolled in a public school and accompanied by a caregiver or guardian were eligible to participate in the study. Children who were non-literate or using fixed orthodontic appliances were excluded.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eOutcome\u003c/h3\u003e\n\u003cp\u003eThe outcome assessed in this study was school absenteeism due to oral health problems. This information was collected through a question answered by the children themselves: \u0026ldquo;In the past month, how many times have you missed school because of your teeth or mouth?\u0026rdquo; The question was based on the Child Perception Questionnaire 8\u0026ndash;10 years (CPQ8\u0026ndash;10) (Barbosa et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Possible answers included: \u0026ldquo;never,\u0026rdquo; \u0026ldquo;once or twice,\u0026rdquo; \u0026ldquo;sometimes,\u0026rdquo; \u0026ldquo;often,\u0026rdquo; and \u0026ldquo;every day or almost every day.\u0026rdquo; For statistical analysis, the variable was dichotomized into: no history of school absenteeism in the past month (\u0026ldquo;never\u0026rdquo;) and history of absenteeism (\u0026ldquo;once or twice,\u0026rdquo; \u0026ldquo;sometimes,\u0026rdquo; \u0026ldquo;often,\u0026rdquo; and \u0026ldquo;every day or almost every day\u0026rdquo;).\u003c/p\u003e\n\u003ch3\u003eNon-Clinical Data Collection\u003c/h3\u003e\n\u003cp\u003eThe history of toothache was collected through a question directed to the child: \u0026ldquo;In the past month, how many times have you had a toothache?\u0026rdquo; Possible answers included: \u0026ldquo;never,\u0026rdquo; \u0026ldquo;once or twice,\u0026rdquo; \u0026ldquo;sometimes,\u0026rdquo; \u0026ldquo;often,\u0026rdquo; and \u0026ldquo;every day or almost every day.\u0026rdquo; The variable was dichotomized into: no history of toothache in the past month (\u0026ldquo;never\u0026rdquo;) and history of toothache (\u0026ldquo;once or twice,\u0026rdquo; \u0026ldquo;sometimes,\u0026rdquo; \u0026ldquo;often,\u0026rdquo; and \u0026ldquo;every day or almost every day\u0026rdquo;). Other non-clinical data were collected through a questionnaire sent to parents/guardians, which included questions on the child\u0026rsquo;s sociodemographic information (sex and age) and the guardian\u0026rsquo;s information (educational level and family income).\u003c/p\u003e\u003cp\u003eThe educational level of guardians was dichotomized as \u0026ldquo;\u0026le;8 years\u0026rdquo; and \u0026ldquo;\u0026gt;8 years\u0026rdquo; of schooling, categorized based on an 8-year cutoff point corresponding to elementary education in Brazil. Family income was classified based on the Brazilian minimum wage at the time of data collection (approximately R\u003cspan\u003e$\u003c/span\u003e788) and dichotomized as \u0026ldquo;\u0026le;2 minimum wages\u0026rdquo; and \u0026ldquo;\u0026gt;2 minimum wages.\u0026rdquo;\u003c/p\u003e\n\u003ch3\u003eClinical Data Collection\u003c/h3\u003e\n\u003cp\u003eClinical data collection was conducted by four examiners following a standardized protocol in the school environment, adhering to biosafety standards. Each child was seated in a school chair facing the examiner. The oral cavity was cleaned with gauze, and visual inspection was performed using artificial light (LED flashlight) and dental mirrors. Each examination was conducted individually in a private setting.\u003c/p\u003e\u003cp\u003eClinical signs of dental trauma in permanent anterior teeth were collected based on the classification proposed by Andreasen et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) (Andreasen, Jens Ove et al., 2007), which includes enamel fractures, enamel-dentin fractures, luxation, discoloration, and avulsion. Children were categorized as \u0026ldquo;with\u0026rdquo; or \u0026ldquo;without\u0026rdquo; dental trauma signs.\u003c/p\u003e\u003cp\u003eLarge overjet were measured with the aid of a millimetre periodontal probe. The largest irregularities were assessed and recorded in millimetres (mm). The overjet was considered large when it was equal to or superior to 6 mm since previous studies reported that laypeople only associate overjet with poor dental aesthetic when it is \u0026ge;\u0026thinsp;6 mm (Soh et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eExaminer Calibration and Pilot Study\u003c/h3\u003e\n\u003cp\u003eBefore data collection, four examiners and four assistants were trained. The assistants were trained to standardize the recording of information in clinical forms.\u003c/p\u003e\u003cp\u003eInitially, the examiners received theoretical training, weekly, about oral health issues (dental caries and its clinical consequences [PUFA], as well as dental trauma). Subsequently, calibration was performed between the examiners and a \u0026ldquo;gold standard\u0026rdquo; (a pediatric dentistry specialist) using oral examinations of 20 children aged 8 to 10 years. The children were independently examined by the \u0026ldquo;gold standard\u0026rdquo; and the four examiners. After seven days, the same children were reexamined to assess the examiners' stability in accurately diagnosing conditions, with intra- and inter-examiner Kappa coefficients exceeding 0.7.\u003c/p\u003e\u003cp\u003eA pilot study was conducted with 30 children to verify the reproducibility of the proposed methodology. No methodological changes were necessary, as the instruments were deemed adequate for the study's purpose. The children involved in the pilot study and calibration were excluded from the final sample.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eData were analyzed using STATA 14.0 software (Stata Corporation, College Station, TX, USA). The pathways between school absenteeism, sociodemographic data, and clinical data were constructed using Structural Equation Modeling (SEM), which allows the estimation of direct and indirect effects of explanatory variables (sociodemographic and clinical) on the outcome variable (school absenteeism). Additionally, a Pathway Diagram was created to represent the relationships between the studied variables visually. A significance level of 5% was adopted. The model\u0026rsquo;s goodness-of-fit was assessed using the following Modification Indices (MI): Root Mean Square Error of Approximation (RMSEA) with its 90% confidence interval (CI), which should have values\u0026thinsp;\u0026le;\u0026thinsp;0.05; Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) with values\u0026thinsp;\u0026ge;\u0026thinsp;0.9; and Standardized Root Mean Square Residual (SRMR) with values\u0026thinsp;\u0026le;\u0026thinsp;0.08 (Menegazzo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 1,482 children were included in the study and answered the question related to school absenteeism, corresponding to a response rate of 96.8%. The prevalence of school absenteeism was 22.1%. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents information on the sociodemographic and clinical characteristics of the sample, considering the occurrence of school absenteeism.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSample characteristics considering the occurrence of school absenteeism (n\u0026thinsp;=\u0026thinsp;1482)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eSchool absenteeism\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSociodemographic variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003cp\u003eMale\u003c/p\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e630 (42,5)\u003c/p\u003e\u003cp\u003e852 (57,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e482 (76,5)\u003c/p\u003e\u003cp\u003e673 (79,0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e148 (23,5)\u003c/p\u003e\u003cp\u003e179 (21,0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003cp\u003e8 years\u003c/p\u003e\u003cp\u003e9 years\u003c/p\u003e\u003cp\u003e10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e503 (33,9)\u003c/p\u003e\u003cp\u003e528 (35,6)\u003c/p\u003e\u003cp\u003e451 (30,4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e369 (73,4)\u003c/p\u003e\u003cp\u003e405 (76,7)\u003c/p\u003e\u003cp\u003e381 (84,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e134 (26,6)\u003c/p\u003e\u003cp\u003e123 (23,3)\u003c/p\u003e\u003cp\u003e70 (15,5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaregiver\u0026rsquo;s educational level\u003c/p\u003e\u003cp\u003e\u0026le; 8 years\u003c/p\u003e\u003cp\u003e\u0026gt;8 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e764 (51,6)\u003c/p\u003e\u003cp\u003e718 (48,4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e579 (75,8)\u003c/p\u003e\u003cp\u003e576 (80,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e185 (24,2)\u003c/p\u003e\u003cp\u003e142 (19,2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHousehold income\u003c/p\u003e\u003cp\u003e\u0026le;\u0026thinsp;2 Minimum wage\u003c/p\u003e\u003cp\u003e\u0026gt;\u0026thinsp;2 Minimum wage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e412 (27,8)\u003c/p\u003e\u003cp\u003e1070 (72,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e326 (79,1)\u003c/p\u003e\u003cp\u003e829 (77,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86 (20,9)\u003c/p\u003e\u003cp\u003e241 (22,5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eClinical oral conditions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eToothache\u003c/p\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e725 (48,9)\u003c/p\u003e\u003cp\u003e757 (51,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e634 (87,5)\u003c/p\u003e\u003cp\u003e521 (68,8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91 (12,6)\u003c/p\u003e\u003cp\u003e236 (31,2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDental trauma\u003c/p\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1330 (89,7)\u003c/p\u003e\u003cp\u003e152 (10,3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1036 (77,9)\u003c/p\u003e\u003cp\u003e119 (78,3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e294 (22,1)\u003c/p\u003e\u003cp\u003e33 (21,7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLarge Overjet (\u0026ge;\u0026thinsp;6 mm)\u003c/p\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1345 (90,8)\u003c/p\u003e\u003cp\u003e137 (9,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1054 (78,4)\u003c/p\u003e\u003cp\u003e101 (73,7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e291 (21,6)\u003c/p\u003e\u003cp\u003e36 (26,3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePUFA/pufa index\u003c/p\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1174 (79,2)\u003c/p\u003e\u003cp\u003e308 (20,8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e939 (80,0)\u003c/p\u003e\u003cp\u003e216 (70,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e235 (20,0)\u003c/p\u003e\u003cp\u003e92 (29,9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUntreated dental caries\u003c/p\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1228 (82,9)\u003c/p\u003e\u003cp\u003e254 (17,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e973 (79,2)\u003c/p\u003e\u003cp\u003e182 (71,7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e255 (20,8)\u003c/p\u003e\u003cp\u003e72 (28,3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe standardized coefficients estimated for the initial and final structural models are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the pathway diagram. School absenteeism was directly affected by the presence of toothache (CP: 0.186, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Other variables did not have a direct impact on school absenteeism. However, toothache was directly related to the presence of the PUFA index and the child's sex. Additionally, the PUFA index was directly influenced by dental caries (CP: 0.129, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), which, in turn, was directly influenced by the child's age (CP: 0.035, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEstimated standardized coefficients for indicators of the initial and final structural models\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePathways\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eStandardizes coefficients\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInitial model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFinal model\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool absenteeism\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eToothache\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.186 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.186 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eToothache\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDental trauma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.007 (P\u0026thinsp;=\u0026thinsp;0.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePUFA/pufa index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.180 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.183 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUntreated dental caries\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.025 (P\u0026thinsp;=\u0026thinsp;0.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.077 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.077 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.002 (P\u0026thinsp;=\u0026thinsp;0.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDental trauma\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.023 (P\u0026thinsp;=\u0026thinsp;0.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.009 (P\u0026thinsp;=\u0026thinsp;0.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLarge Overjet (\u0026ge;\u0026thinsp;6 mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.080 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.080 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePUFA/pufa index\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUntreated dental caries\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.129 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.129 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUntreated dental caries\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.028 (P\u0026thinsp;=\u0026thinsp;0.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.035 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.034 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHousehold income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.018 (P\u0026thinsp;=\u0026thinsp;0.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHousehold income\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaregiver\u0026rsquo;s educational level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.014 (P\u0026thinsp;=\u0026thinsp;0.531)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModel fit\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRMSEA (90% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.035 (0.024\u0026ndash;0.046)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.812\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTLI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.753\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSRMR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbreviations: CI \u0026ndash; Confidence interval; CFI \u0026ndash; \u003cem\u003eComparative Fit Index\u003c/em\u003e; RMSEA \u0026ndash; \u003cem\u003eRoot Mean Square Error of Approximation\u003c/em\u003e; SRMR \u0026ndash; \u003cem\u003eStandardized Root Mean Square Residual\u003c/em\u003e; TLI \u0026ndash; \u003cem\u003eTucker-Lewis Index\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFont: Created by author in Canva (Perth, Sydney, Australia)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main finding of this study was that the prevalence of school absenteeism in the present sample was 22.1%, with this occurrence being directly influenced by self-reported toothache. Furthermore, the main factors associated with toothache included dental caries and its untreated clinical consequences (PUFA index), age, and sex. This finding is significant, as school absenteeism negatively affects children's academic performance and social interactions within the school environment (Ansari and Pianta, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Cozzi and Barbi, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Considering oral health as a causal factor, analyzing toothache and its associated factors can reveal population needs and guide the implementation of preventive measures to supportchildren and their families maintain good oral health, positively impacting school attendance (Santos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePongpichit et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) reported a 22.5% prevalence of school absences due to dental reasons, including treatment. When considering only toothache as the reason for absenteeism, the prevalence dropped to 0.5%. This highlights that dental appointments were more common causes of absenteeism than toothache itself. Overall, daily attendance records showed that children missed 159 hours of school in a year for dental consultations or toothache. Additionally, 547 hours were spent on dental exams or treatments provided by the Thai healthcare system. A comparative analysis should consider that this study evaluated school records and dental health documentation over 1-year period (Pongpichit et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe relationship between toothache and school absenteeism aligns with findings by Krisdapong et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who concluded that children with toothache or poor oral health were more likely to miss school or perform poorly academically. This can be explained by the emotional, psychological, and biological significance of toothache for patients, especially in the age group studied. (Krisdapong et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) Toothaches can cause functional limitations and impair children's ability to fulfill their expected roles at school. It is also associated with sleep disturbances, difficulties in chewing, and socializing (Brondani et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Children experiencing a negative impact on quality of life are up to three times more likely to miss school compared to those with little or no effect (Krisdapong et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur results indicate that the clinical consequences of untreated dental caries, represented by the PUFA index, and the child's sex were directly associated with toothache. This finding is consistent with other studies (Santos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Regarding the PUFA index, it is an important indicator as it reveals that the clinical consequences of untreated dental caries - such as pulp involvement and dental abscess - can be more severe than the carious lesions themselves and are often associated with reports of pain (Karki et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Monse et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRegarding sex, when evaluated independently, a higher percentage of boys reported missing school. Gubbels et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found, in their systematic review, that boys tend to have a more negative attitude toward school than girls (Gubbels et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, Piovesan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) found that being female was associated with better academic performance. (Piovesan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) However, when related to pain, other studies in children and adolescents reported that girls were significantly more likely to report oral health problems (Krisdapong et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In Santos et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), toothache was more frequent among girls. The justification used was that this difference between sexes may reflect cultural norms, where boys express less pain and, consequently, report fewer dental issues. Therefore, this result should be interpreted cautiously (Santos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAnother established relationship was between dental caries and the child\u0026rsquo;s age. In our study, the age group most affected by school absenteeism was 8 years old. In Krisdapong et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), a statistically significant association was found between school absenteeism and the DMFT index for 12-year-old children, but not for 15-year-olds. (Krisdapong et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) A possible explanation is that children\u0026rsquo;s cognitive development regarding health and disease increases with age. Consequently, younger children, who have less understanding of their symptoms, tend to interpret them differently than older children. Agaku et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found a higher prevalence of decayed teeth among children under nine years old. (Agaku et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) In our study, the factors indirectly influencing school absenteeism were the PUFA index and sex (via toothache), as well as dental caries and age (via the PUFA index). Overall, these pathways summarize what has already been discussed: the consequences of untreated dental caries, including pain and absenteeism, and the central role of toothache in school absenteeism.\u003c/p\u003e\u003cp\u003eThe independent variables, increased overjet and dental trauma, were included in our analyses because dental trauma can cause toothache, which could justify school absenteeism (Moura-Leite et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). As a result, overjet was positively associated with dental trauma, a relationship well-established in the literature (Da Silva et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, neither variable directly or indirectly influenced our outcome, which can be explained by the episodic nature of such cases, reducing the likelihood of statistical significance.\u003c/p\u003e\u003cp\u003eThus, school absenteeism can be seen as a \"socio-dental\" indicator, measuring the extent to which children\u0026rsquo;s oral health problems and their treatment interfere with everyday routines and impact behaviors of both the children and their families (Pongpichit et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The findings from this study can inform and justify the development and improvement of interventions aimed at preventing further occurrences of school absenteeism through the prevention and treatment of oral diseases (Agaku et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Gubbels et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Krisdapong et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It is essential to emphasize that dental policymakers should plan interventions so that school dental services are predominantly available outside of school hours (Pongpichit et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results of this study are important because we obtained a representative sample with a high response rate, ensuring the reliability of the research. Furthermore, a toothache can negatively affect not only the learning process but also other important aspects such as socialization. In adulthood, the absence of education may impact an individual\u0026rsquo;s professional skills, hinder entry into the labor market, and affect the country\u0026rsquo;s economy (Ansari and Pianta, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Studies on academic performance are critical because schools have traditionally been the primary target of oral health promotion initiatives, which deliver health education messages to entire school populations. These studies are also relevant for public health program planning and can help identify groups with higher levels of need (Piovesan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStudy Limitations\u003c/h2\u003e\u003cp\u003eThe study's limitations include the relatively short evaluation period for absenteeism (1 month) and the method of data collection, which relied on self-reporting. The dichotomization of responses for statistical analysis may also have overestimated the effect. Additionally, the sample only included children from public schools. For future studies, we suggest that data collection be conducted over a longer time frame, such as three months, to allow for inferences about academic performance (Piovesan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Moreover, school attendance records can be obtained through documentation provided by schools and/or dental records, avoiding recall bias in children's self-reported questionnaires.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIt was found that 22.1% of students aged 8 to 10 years in public schools in Florian\u0026oacute;polis, Santa Catarina, were absent from school. Self-reported toothache is directly linked to this issue. Other factors, such as sex, age, untreated dental caries, and its clinical consequences (PUFA/pufa index), are indirectly related to school absenteeism.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNS, PSS, JSM, FCV, CMS, MB, and MC conceived the ideas (conceptualization); NS, PSS and JSM collected the data; NS, PSS and JSM formal analysis; NS, PSS, JSM and FCV led the writing (original draft), and all authors revised the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis study was financed in part by the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de Nivel Superior\u0026mdash;Brasil (CAPES), Grant number 001.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe present research has been conducted in full accordance with ethical principles, including the World Medical Association Declaration of Helsinki. The study protocol was approved by the local Human Research Ethics Committee under Protocol number 902.663. The data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgaku, I.T., Olutola, B.G., Adisa, A.O., Obadan, E.M., Vardavas, C.I., 2015. Association between unmet dental needs and school absenteeism because of illness or injury among U.S. school children and adolescents aged 6\u0026ndash;17years, 2011\u0026ndash;2012. Preventive Medicine 72, 83\u0026ndash;88. https://doi.org/10.1016/j.ypmed.2014.12.037\u003c/li\u003e\n\u003cli\u003eAndreasen, Jens Ove, Andreasen, Frances M, Andersson, Lars, 2007. Wiley: Textbook and Color Atlas of traumatic Injuries to the Teeth, 4th ed. Copenhagen, Blackwell Munksgaard.\u003c/li\u003e\n\u003cli\u003eAnsari, A., Pianta, R.C., 2019. School absenteeism in the first decade of education and outcomes in adolescence. Journal of School Psychology 76, 48\u0026ndash;61. https://doi.org/10.1016/j.jsp.2019.07.010\u003c/li\u003e\n\u003cli\u003eBarbosa, T.S., Tureli, M.C.M., Gavi\u0026atilde;o, M.B.D., 2009. Validity and reliability of the Child Perceptions Questionnaires applied in Brazilian children. BMC Oral Health 9, 13. https://doi.org/10.1186/1472-6831-9-13\u003c/li\u003e\n\u003cli\u003eBrondani, B., Emmanuelli, B., Alves, L.S., Soares, C.J., Ardenghi, T.M., 2018. The effect of dental treatment on oral health-related quality of life in adolescents. Clin Oral Invest 22, 2291\u0026ndash;2297. https://doi.org/10.1007/s00784-017-2328-3\u003c/li\u003e\n\u003cli\u003eCozzi, G., Barbi, E., 2020. Chronic school absenteeism as a diagnostic clue for paediatricians. J Paediatrics Child Health 56, 191\u0026ndash;193. https://doi.org/10.1111/jpc.14689\u003c/li\u003e\n\u003cli\u003eDa Silva, R.M., Mathias, F.B., Da Costa, C.T., Da Costa, V.P.P., Goettems, M.L., 2021. Association between malocclusion and the severity of dental trauma in primary teeth. Dental Traumatology 37, 275\u0026ndash;281. https://doi.org/10.1111/edt.12615\u003c/li\u003e\n\u003cli\u003eGubbels, J., Van Der Put, C.E., Assink, M., 2019. Risk Factors for School Absenteeism and Dropout: A Meta-Analytic Review. J Youth Adolescence 48, 1637\u0026ndash;1667. https://doi.org/10.1007/s10964-019-01072-5\u003c/li\u003e\n\u003cli\u003eKaram, S.A., Costa, F.D.S., Chisini, L.A., Darley, R., Demarco, F.F., Correa, M.B., 2024. Can oral health have an impact on academic performance and school absenteeism?: a systematic review and meta-analysis. Braz. J. Oral Sci. 23, e240322. https://doi.org/10.20396/bjos.v23i00.8670322\u003c/li\u003e\n\u003cli\u003eKarki, S., P\u0026auml;kkil\u0026auml;, J., Laitala, M., Humagain, M., Anttonen, V., 2019. Influence of dental caries on oral health‐related quality of life, school absenteeism and school performance among Nepalese schoolchildren. Comm Dent Oral Epid 47, 461\u0026ndash;469. https://doi.org/10.1111/cdoe.12485\u003c/li\u003e\n\u003cli\u003eKearney, C.A., 2008. An Interdisciplinary Model of School Absenteeism in Youth to Inform Professional Practice and Public Policy. Educ Psychol Rev 20, 257\u0026ndash;282. https://doi.org/10.1007/s10648-008-9078-3\u003c/li\u003e\n\u003cli\u003eKrisdapong, S., Prasertsom, P., Rattanarangsima, K., Sheiham, A., 2013. School absence due to toothache associated with sociodemographic factors, dental caries status, and oral health‐related quality of life in 12‐ and 15‐year‐old T hai children. J Public Health Dent 73, 321\u0026ndash;328. https://doi.org/10.1111/jphd.12030\u003c/li\u003e\n\u003cli\u003eMenegazzo, G.R., Fagundes, M.L.B., Do Amaral Junior, O.L., De Vasconcellos, N.B.T., Felin, C.M., De Camargo, F.D., Do Amaral Giordani, J.M., 2022. Pathways Between Religiosity and Tooth Loss in Older Adults in Brazil. J Relig Health 61, 552\u0026ndash;563. https://doi.org/10.1007/s10943-021-01291-w\u003c/li\u003e\n\u003cli\u003eMonse, B., Heinrich‐Weltzien, R., Benzian, H., Holmgren, C., Van Palenstein Helderman, W., 2010. PUFA \u0026ndash; An index of clinical consequences of untreated dental caries. Comm Dent Oral Epid 38, 77\u0026ndash;82. https://doi.org/10.1111/j.1600-0528.2009.00514.x\u003c/li\u003e\n\u003cli\u003eMoura-Leite, F.R., Ramos-Jorge, J., Ramos-Jorge, M.L., De Paiva, S.M., Vale, M.P., Pordeus, I.A., 2011. Impact of dental pain on daily living of five-year-old Brazilian preschool children: prevalence and associated factors. 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J Public Health Dent 68, 76\u0026ndash;81. https://doi.org/10.1111/j.1752-7325.2007.00051.x\u003c/li\u003e\n\u003cli\u003eRuff, R.R., Habib, R., God\u0026iacute;n, T.B., Niederman, R., 2023. School-based caries prevention and the impact on acute and chronic student absenteeism. The Journal of the American Dental Association 154, 753\u0026ndash;759. https://doi.org/10.1016/j.adaj.2023.05.007\u003c/li\u003e\n\u003cli\u003eRuff, R.R., Senthi, S., Susser, S.R., Tsutsui, A., 2019. Oral health, academic performance, and school absenteeism in children and adolescents. The Journal of the American Dental Association 150, 111-121.e4. https://doi.org/10.1016/j.adaj.2018.09.023\u003c/li\u003e\n\u003cli\u003eSantos, P.S., Martins-J\u0026uacute;nior, P.A., Paiva, S.M., Klein, D., Torres, F.M., Giacomin, A., Gon\u0026ccedil;alves, B.M., Konrath, A.C., Bolan, M., Cardoso, M., 2019. Prevalence of self-reported dental pain and associated factors among eight- to ten-year-old Brazilian schoolchildren. PLoS ONE 14, e0214990. https://doi.org/10.1371/journal.pone.0214990\u003c/li\u003e\n\u003cli\u003eShaikh, S., Siddiqui, A.A., Aljanakh, M., 2016. School Absenteeism due to Toothache among Secondary School Students Aged 16\u0026ndash;18 Years in the Ha\u0026rsquo;il Region of Saudi Arabia. Pain Research and Treatment 2016, 1\u0026ndash;4. https://doi.org/10.1155/2016/7058390\u003c/li\u003e\n\u003cli\u003eSoh, J., Chew, M.T., Chan, Y.H., 2006. Perceptions of dental esthetics of Asian orthodontists and laypersons. American Journal of Orthodontics and Dentofacial Orthopedics 130, 170\u0026ndash;176. https://doi.org/10.1016/j.ajodo.2005.05.048\u003c/li\u003e\n\u003cli\u003eTramontina, S., Martins, S., Michalowski, M.B., Ketzer, C.R., Eizirik, M., Biederman, J., Rohde, L.A., 2001. School Dropout and Conduct Disorder in Brazilian Elementary School Students. Can J Psychiatry 46, 941\u0026ndash;947. https://doi.org/10.1177/070674370104601006\u003c/li\u003e\n\u003cli\u003eVon Elm, E., Altman, D.G., Egger, M., Pocock, S.J., G\u0026oslash;tzsche, P.C., Vandenbroucke, J.P., 2008. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Journal of Clinical Epidemiology 61, 344\u0026ndash;349. https://doi.org/10.1016/j.jclinepi.2007.11.008\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"School absenteeism, toothache, schoolchildren, oral health ","lastPublishedDoi":"10.21203/rs.3.rs-8254244/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8254244/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e Determine the prevalence and factors associated with school absenteeism due to oral health problems in schoolchildren aged 8 to 10 years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA cross-sectional study was conducted with children randomly selected from public schools in Florianópolis, Santa Catarina, Brazil. School absenteeism was collected through a question based on the Child Perception Questionnaire 8–10 years answered by the children. Independent variables included sociodemographic characteristics (sex, age, family income, and caregivers' educational level) and history of toothache. During clinical examinations, data were collected on untreated dental caries, PUFA index, and dental trauma. The pathways between school absenteeism and the independent variables were analyzed using structural equation modeling. A 5% significance level was considered.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In total, 1,482 children participated in the study. The prevalence of school absenteeism was 22.1%. School absenteeism was directly affected by the presence of toothache (CP: 0.186, P\u0026lt;0.01). The PUFA index (via toothache), dental caries (via PUFA), sex (via toothache), and age (via PUFA) had indirect effects on school absenteeism. Conclusion: It was concluded that school absenteeism is directly influenced by the presence of toothache in schoolchildren.\u003c/p\u003e","manuscriptTitle":"Impact of oral health problems on school absenteeism in public schoolchildren: A structural equation model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 11:00:49","doi":"10.21203/rs.3.rs-8254244/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c848db84-42bc-4966-875c-7f04302f53af","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-04T14:57:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-15 11:00:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8254244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8254244","identity":"rs-8254244","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}