Details

Autor(en) / Beteiligte

• Curtis, Alexandra M.
• VanBuren, John
• Cavanaugh, Joseph E.
• Warren, John J.
• Marshall, Teresa A.
• Levy, Steven M.

Titel

Longitudinal associations between dental caries increment and risk factors in late childhood and adolescence

Ist Teil von

• Journal of public health dentistry, 2018-09, Vol.78 (4), p.321-328

Ort / Verlag

United States: Wiley Subscription Services, Inc

Erscheinungsjahr

2018

Link zum Volltext

Quelle

Wiley-Blackwell Journals

Beschreibungen/Notizen

• Objectives To assess longitudinal associations between permanent tooth caries increment and both modifiable and non‐modifiable risk factors, using best subsets model selection. Methods The Iowa Fluoride Study has followed a birth cohort with standardized caries exams without radiographs of the permanent dentition conducted at about ages 9, 13, and 17 years. Questionnaires were sent semi‐annually to assess fluoride exposures and intakes, select food and beverage intakes, and tooth brushing frequency. Exposure variables were averaged over ages 7‐9, 11‐13, and 15‐17, reflecting exposure 2 years prior to the caries exam. Longitudinal models were used to relate period‐specific averaged exposures and demographic variables to adjusted decayed and filled surface increments (ADJCI) (n = 392). The Akaike Information Criterion (AIC) was used to assess optimal explanatory variable combinations. Results From birth to age 9, 9‐13, and 13‐17 years, 24, 30, and 55 percent of subjects had positive permanent ADJCI, respectively. Ten models had AIC values within two units of the lowest AIC model and were deemed optimal based on AIC. Younger age, being male, higher mother's education, and higher brushing frequency were associated with lower caries increment in all 10 models, while milk intake was included in 3 of 10 models. Higher milk intakes were slightly associated with lower ADJCI. Conclusions With the exception of brushing frequency, modifiable risk factors under study were not significantly associated with ADJCI. When possible, researchers should consider presenting multiple models if fit criteria cannot discern among a group of optimal models.