Community and caregiver oral health education plus media campaign vs Pre-intervention BBTD rate: Baby bottle tooth decay prevalence
- Population
- Alaska Native Head Start children
- Intervention
- Community and caregiver oral health education plus media campaign
- Comparison
- Pre-intervention BBTD rate
- Outcome
- Baby bottle tooth decay prevalence
The Alaska Native site had a 20% increase in BBTD prevalence, without a GRADE rating.
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Community and caregiver oral health education plus media campaign vs Pre-intervention BBTD rate Baby bottle tooth decay prevalence · Alaska Native Head Start children · 3 years, Alaska Native Head Start site, Alaska Native site The Alaska Native site had a 20% increase in BBTD prevalence, without a GRADE rating. Reducing Alaska Native paediatric oral health disparities: a systematic review of oral health interventions… (2013) All outcomes | Percent increase in BBTD prevalence 20 | 1 study | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Reducing Alaska Native paediatric oral health disparities: a systematic review of oral health interventions and a case study on multilevel… 2013 All outcomes | October 5, 2012 | 11 | Critically Low / Critically Low |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Community and caregiver oral health education plus media campaign vs Pre-intervention BBTD rate · Alaska Native and American Indian Head Start children · 1 review
Studies behind the findings
The primary studies the full-text reviews tie to this outcome. Reviews with headline outcomes only do not list them here.
- Bruerd et al. 1989 · included by 1 of these review
- Bruerd & Jones 1996 · included by 1 of these review
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.