Weight Status and Dental Problems in Early Childhood: Classification Tree Analysis of a National Cohort

Abstract

A poor quality diet may be a common risk factor for both obesity and dental problems such as caries. The aim of this paper is to use classification tree analysis (CTA) to identify predictors of dental problems in a nationally representative cohort of Irish pre-school children. CTA was used to classify variables and describe interactions between multiple variables including socio-demographics, dietary intake, health-related behaviour, body mass index (BMI) and a dental problem. Data were derived from the second (2010/2011) wave of the ‘Growing Up in Ireland’ study (GUI) infant cohort at 3 years, n = 9793. The prevalence of dental problems was 5.0% (n = 493). The CTA model showed a sensitivity of 67% and specificity of 58.5% and overall correctly classified 59% of children. Ethnicity was the most significant predictor of dental problems followed by longstanding illness or disability, mother’s BMI and household income. The highest prevalence of dental problems was among children who were obese or underweight with a longstanding illness and an overweight mother. Frequency of intake of some foods showed interactions with the target variable. Results from this research highlight the interconnectedness of weight status, dental problems and general health and reinforce the importance of adopting a common risk factor approach when dealing with prevention of these diseases.

Mobility Analysis of AmpuTees (MAAT 4): classification tree analysis for probability of lower limb prosthesis user functional potential

“…While traditional predictive models such as logistic and linear regression are feasible, these models can have issues with their implementation and ultimately interpretation by healthcare providers with perceived "black box" results [8,9]. Classification and regression tree analysis (CART) is a technique that is gaining popularity within healthcare due to its ease of interpretation and implementation [8,[10][11][12][13][14][15] Common examples can be noted for guidelines on paediatric head trauma [16][17][18] and paediatric abdominal injuries [19][20][21]. Specifically, CART analysis starts with a large group of individuals, and then makes a series of binary node splits based on some criterion that improves group purity in order to effectively classify individuals.…”

“…The use of a CART analysis and subsequent production of a classification tree for the care of individuals with lower limb prostheses is unique. There is growing popularity and use of classification trees across healthcare (e.g., see references [8,[10][11][12][13][14][15]). The classification tree developed in this analysis provides probability for determining a patient's functional potential.…”

La obesidad en niños y adolescentes como factor desencadenante de caries dental, revisión bibliográfica

“…21,25 Aparentemente la presencia de un mayor consumo de alimentos si bien desencadena el incremento en el peso corporal reflejado en el IMC, también provocaría un estímulo en la secreción salival 26 provocando aumento en esta y por ende una acción de autoclisis de esta sobre el biofilm dental primer reservorio de los microrganismos, 27 lo que podría explicar los bajos índices de caries detectados en la población con peso elevado. 28 Como odontólogos se hace necesario guiar al paciente, a sus padres y/o responsables en los procesos de re-mineralización, este asesoramiento requiere involucrar la ejecución de hábitos de higiene y nutricionales 29 que como medida preventiva a la presencia de problemas en la cavidad oral, resulta básica.…”

Evaluation of the Relationship between the BMI and the Sequence and Chronology of Eruption in Permanent Dentition in Spanish Population

“…In the last decade, several studies have analyzed the influence of nutrition on dental eruption [ 6 , 11 , 12 , 15 , 17 , 20 , 21 , 26 , 29 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. Most studies found an association between being overweight and acceleration of tooth eruption, although it was not significant in all cases [ 6 , 12 , 37 , 39 , 42 ].…”