RESUMO
Resumo O objetivo deste estudo foi identificar os fatores associados ao não comparecimento dos usuários ao tratamento ortodôntico, em três centros de especialidades odontológicas regionais (CEO-R) localizados no estado do Ceará. Metodologia: Os dados foram extraídos de prontuários de pacientes que concluíram o tratamento ortodôntico. Foi calculada a taxa de ausências, com o objetivo de estabelecer um coeficiente de faltas entre os municípios. A fim de descrever o padrão geográfico da ocorrência, foram construídos mapas temáticos baseados nas distribuições. Para as associações entre a variável desfecho (falta ao tratamento) e as independentes (sexo, idade, quebra de aparelho, mudança de profissional, renda e local de residência do usuário), utilizou-se a análise de regressão logística múltipla com p ≤ 0,05. Resultados: Foram examinados 237 prontuários em 20 municípios, com 8.283 consultas ortodônticas realizadas e 2.665 (32,17%) faltas. Apresentou diferença estatisticamente significativa a variável mudança de profissional. Conclusão: O maior número de faltas foi associado à mudança de profissional.
Abstract The aim of this study was to identify the factors associated with the users failing to keep orthodontic treatment appointments (absences), in three regional dental specialty centers (CEO-R) located in the State of Ceará. Methodology: This was a cross-sectional epidemiological study with secondary data source of 3 CEO-R, from which 237 medical records of complete orthodontic treatments were examined, with 8.283 appointments and 2.665 (32.17%) missing appointments. Data collection was standardized by an electronic questionnaire.. Factors associated with users missing appointments were calculated by means of absence rates and thematic maps were constructed based on distributions of the geographical pattern of occurrence. To evaluate the association between the outcome variable (absence from treatment) and the independent variables (sex, age, breakage of appliance, change of professional, income and place of user's residence) multiple logistic regression analysis was used with p ≤ 0.05. Results: There were high absence rates for both city headquarters and non-headquarter CEO-Rs. The variable change of professional showed statistical significance, in relation to the number of absences. Conclusion: The highest number of absences was associated with change of professional.