Journal Article
Research Support, Non-U.S. Gov't
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Assessing causal effects of early life-course factors on early childhood caries in 5-year-old Ugandan children using directed acyclic graphs (DAGs): A prospective cohort study.

OBJECTIVE: To estimate the effect of distal and proximal early life-course factors on early childhood caries (ECC) in 5-year-old Ugandan children, particularly focusing on the causal effect of exclusive breast feeding (EBF) on ECC using directed acyclic graphs (DAGs) for confounder selection.

METHODS: This study had a nested prospective cohort design, focusing on 5 years of follow-ups of caregiver-children pairs from the PROMISE-EBF trial (ClinicalTrials.gov no: NCT00397150) conducted in 2011 in Eastern Uganda. Data were from recruitment interviews, 24-week, 2-year and 5-year follow-ups of a cohort of 417 mother-children pairs. Trained research assistants performed interviews with caregivers in the local language and ECC was recorded under field conditions using the World Health Organization's (WHO) decayed missing or filled teeth (dmft) index. Early life-course factors in terms of socio-demographic characteristics, EBF and other feeding habits were assessed at the various follow-ups. The outcome (ECC; dmft>0) was assessed at the 5-year follow-up. Causal diagrams as DAGs were constructed to guide the selection of confounding and collider variables to be included in or excluded from the final multivariable analysis. Negative binomial regression analyses were performed based on two comparative DAGs representing different causal models.

RESULTS: Model 1 based on DAG 1, showed EBF to be a protective factor against ECC, with an IRR and 95% CI of 0.62 (0.43-0.91). According to Model 2 based on DAG 2, EBF and having both parents living together had protective effects: the corresponding IRRs and 95% CI were 0.60 (0.41-0.88) and 0.48 (0.25-0.90), respectively.

CONCLUSIONS: Both plausible models indicated that being exclusively breastfed for 24 weeks had a protective causal effect against ECC. Further research, examining the unmeasured variables included in the DAGs is necessary to strengthen the present finding and allow stronger causal claims.

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