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Updated: Sep 3, 2025
Mimicking and Measuring Occlusal Erosive Tooth Wear with the "Rub&Roll" and Non-contact Profilometry
Published on: February 2, 2018
Risk prediction models for erosive wear in preschool-aged children: a prospective study
Gabriella Gatt1, Nikolai Attard2
1Department of Child Dental Health and Orthodontics, Faculty of Dental Surgery, University of Malta, Msida, Malta. gabriella.gatt@um.edu.mt.
Background:
Despite increasing prevalence, age-specific risk predictive models for erosive tooth wear in preschool-age children have not been developed. Identification of at-risk groups and the timely introduction of behavioural change or treatment will stop the progression of erosive wear in the permanent dentition. This study aimed to identify age-specific risk factors for erosive wear. Distinct risk prediction models for 3-year-old and 5-year-old children were developed.
Methods:
A prospective cohort study included school-based clinical examinations and parent administered questionnaires for consented 3 and 5-year-old healthy children. Calibrated examiners measured the following health parameters under standardised conditions: erosion, using the Basic Erosive Wear Examination Index (BEWE), caries using the International Caries Detection and Assessment System (ICDAS), plaque and calculus according to the British Association for the Study of Community Dentistry (BASCD) scores, dental traumatic injuries and soft tissue lesions, salivary testing and BMI. Other health conditions were collected via a parent-administered questionnaire that explored oral- and general-health. Non parametric tests were utilised to explore the temporal relation of erosion with, demographic factors, oral hygiene habits, general health and dietary habits. Variables showing significance with a difference in BEWE cumulative score over time were utilised to develop two risk prediction models. The models were evaluated by Receiver Operating Characteristics analysis.
Results:
Risk factors for the 3-year-old cohort (N = 336) included erosive wear (χ2(1, 92) = 12.829, p < 0.001), district (χ2(5, 92) = 17.032, p = 0.004) and family size (χ2(1, 92) = 4.547, p = 0.033). Risk factors for the 5-year-old cohort (N = 441) also included erosive wear (χ2(1, 144) = 4.768, p = 0.029), gender (χ2(1, 144) = 19.399, p < 0.001), consumption of iced tea (χ2(1, 144) = 8.872, p = 0.003) and dry mouth (χ2(1, 144) = 9.598, p = 0.002).
Conclusions:
Predictive risk factors for 3-year-old children are based on demographic factors and are distinct from those for 5-year-old children based on biological and behavioural factors. Erosive wear is a risk factor for further wear in both age cohorts.
