Dental caries clusters among adolescents

Abstract

Objectives There have been very few longitudinal studies of dental caries in adolescents, and little study of the caries risk factors in this age group. The purpose of this study was to describe different caries trajectories and associated risk factors among members of the Iowa Fluoride Study (IFS) cohort. Methods The IFS recruited a birth cohort from 1992 to 1995, and has gathered dietary, fluoride and behavioral data at least twice yearly since recruitment. Examinations for dental caries were completed when participants were ages 5, 9, 13 and 17 years. For the current study, only participants with DFS caries data at ages 9, 13, and 17 were included (N=396). The individual DFS counts at age 13 and the DFS increment from 13 to 17 were used to identify distinct caries trajectories using Ward’s hierarchical clustering algorithm. A number of multinomial logistic regression models were developed to predict trajectory membership, using longitudinal dietary, fluoride and demographic/behavioral data from 9 to 17 years. Model selection was based on the Akaike Information Criterion (AIC). Results Several different trajectory schemes were considered, and a 3 trajectory scheme – no DFS at age 17 (n=142), low DFS (n=145) and high DFS (n=109) – was chosen to balance sample sizes and interpretability. The model selection process resulted in use of an arithmetic average for dietary variables across the period from 9 to 17 years. The multinomial logistic regression model with the best fit included the variables maternal education level, 100% juice consumption, brushing frequency and sex. Other favored models also included water and milk consumption and home water fluoride concentration. The high caries cluster was most consistently associated with lower maternal education level, lower 100% juice consumption, lower brushing frequency and being female. Conclusions The use of a clustering algorithm and use of Akaike’s Information Criterion (AIC) to determine the best representation of the data were useful means in presenting longitudinal caries data. Findings suggest that high caries incidence in adolescence is associated with lower maternal educational level, less frequent tooth brushing, lower 100% juice consumption and being female.

Child Caries Management: A Randomized Controlled Trial in Dental Practice

“…The overall levels of dental pain and/or infection are probably comparable to single tooth studies and possibly even lower in FiCTION participants (de Amorim et al 2018;Dorri et al 2017;Innes et al 2015;Santos et al 2016;Yengopal et al 2009). Nonetheless, the trajectory of dental caries, once established (Hall-Scullin et al 2017;Warren et al 2017), means that these high risk children require a high level of care. It is possible that low use of T e increased the potential for non-or late-management of lesions contributing to occurrences of dental pain and infection, although a counterargument is that unnecessarily invasive treatment was avoided (Bader et al 2001;Schwendicke et al 2015;Wenzel 2004).…”

Inequalities in oral health among adolescents in Gangneung, South Korea

“…A study from Sweden showed that there is limited effect from SEP only after considering the previous experience of caries [ 20 ]. Polk et al [ 21 ] and Newacheck [ 22 ] also reported that there was an SEP gradient in caries experiences in the U.S. Another longitudinal study from Iowa cohort revealed that there is a gap by SEP, especially maternal educational levels [ 23 ]. However, Curtis, using the same cohort data from Iowa Fluoride Study (IFS), recently argued that ‘the role of SES in caries may not be as important as previously thought’.…”

Examining caries aetiology in adolescence with structural equation modelling

“…Female participants overall had more caries, despite having lower %SSB intakes and better oral health habits. Sex could be associated with caries incidence, as shown by some results in the literature, as well as previous IFS results during the adolescent period, however, there is not a consensus in the literature 30,31,32 . This possible difference could be due to earlier tooth eruption in females, differences in dental care utilization, hormonal changes during puberty, and genetic differences 30,31,33,34 .…”

“…Eating frequency has been associated with caries in young children 29 . Although there is not sufficient evidence for a consensus, some evidence of sex differences in caries incidence have been observed in the literature, with females having greater caries experience than their male counterparts 30,31,32,33,34 . Therefore, it was hypothesized that factors related to being female were associated with more caries, and a direct relationship between sex and ADJCI was considered.…”