2016 Community dentistry and oral …

Estimating the effects of maternal education on child dental caries using marginal structural models: The Longitudinal Study of Indigenous Australian Children.

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Community dentistry and oral epidemiology Vol. 44 (6) : 602-610 • Dec 2016

OBJECTIVE: To estimate the effect of mothers' education on Indigenous Australian children's dental caries experience while controlling for the mediating effect of children's sweet food intake. METHODS: The Longitudinal Study of Indigenous Children is a study of two representative cohorts of Indigenous Australian children, aged from 6 months to 2 years (baby cohort) and from 3.5 to 5 years (child cohort) at baseline. The children's primary caregiver undertook a face-to-face interview in 2008 and repeated annually for the next 4 years. Data included household demographics, child health (nutrition information and dental health), maternal conditions and highest qualification levels. Mother's educational level was classified into four categories: 0-9 years, 10 years, 11-12 years and >12 years. Children's mean sweet food intake was categorized as <20%, 20-30%, and >30%. After multiple imputation of missing values, a marginal structural model with stabilized inverse probability weights was used to estimate the direct effect of mothers' education level on children's dental decay experience. RESULTS: From 2008 to 2012, complete data on 1720 mother-child dyads were available. Dental caries experience for children was 42.3% over the 5-year period. The controlled direct effect estimates of mother's education on child dental caries were 1.21 (95% CI: 1.01-1.45), 1.03 (95% CI: 0.91-1.18) and 1.07 (95% CI: 0.93-1.22); after multiple imputation of missing values, the effects were 1.21 (95% CI: 1.05-1.39), 1.06 (95% CI: 0.94-1.19) and 1.06 (95% CI: 0.95-1.19), comparing '0-9', '10' and '11-12' years to > 12 years of education. CONCLUSION: Mothers' education level had a direct effect on children's dental decay experience that was not mediated by sweet food intake and other risk factors when estimated using a marginal structural model.

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