Question · asked by 0 reviews

Started toothbrushing with fluoride toothpaste at or before 24 months (earlier start) vs Started after 24 months (later start): Fluorosis (percentage prevalence in permanent teeth)

Population
Children who used topical fluoride under 6 years old; fluorosis assessed in permanent teeth at 6 to 17 years
Intervention
Started toothbrushing with fluoride toothpaste at or before 24 months (earlier start)
Comparison
Started after 24 months (later start)
Outcome
Fluorosis (percentage prevalence in permanent teeth)

Started toothbrushing with fluoride toothpaste at or before 24… showed no clear difference in fluorosis (percentage prevalence in permanent teeth) compared with started after 24 months (later start); GRADE not reported.

What each review found

Current versions only
FindingEffectStudiesGRADE certainty
Started toothbrushing with fluoride toothpaste at or before 24 months (earlier start) vs Started after 24 months (later start)
Fluorosis (percentage prevalence in permanent teeth) · Children who used topical fluoride under 6 years old; fluorosis assessed in permanent teeth at 6 to 17 years · Fluorosis assessed when most permanent teeth of interest had erupted (6 to 17 years)
Started toothbrushing with fluoride toothpaste at or before 24… showed no clear difference in fluorosis (percentage prevalence in permanent teeth) compared with started after 24 months (later start); GRADE not reported.
Topical fluoride as a cause of dental fluorosis in children (2010) · Cochrane All outcomesearlier version CD007693.PUB2, superseded
OR 0.92 [0.71, 1.18]5 studiesGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Topical fluoride as a cause of dental fluorosis in children
2024 · Cochrane All outcomes
2022-07Not listedNot assessed

The same intervention and outcome, asked in another population or against another comparator.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.