Women who experienced preterm birth vs Women who did not experience preterm birth (term): Dental caries
Women who experienced preterm birth did not have significantly higher DMFT than those who did not (mean difference 1.56, 95% CI -0.28 to 3.41; 5 studies; I2=92%); certainty of evidence not graded.
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Women who experienced preterm birth vs Women who did not experience preterm birth (term) DMFT index (decayed, missing and filled teeth) · Pregnant women · Pregnant women assessed around delivery in observational studies across multiple countries (Mexico, Malawi, India, France, Jordan, Finland, Tanzania); mostly retrospective cohort and case-control designs Women who experienced preterm birth did not have significantly higher DMFT than those who did not (mean difference 1.56, 95% CI -0.28 to 3.41; 5 studies; I2=92%); certainty of evidence not graded. Dental caries and preterm birth: a systematic review and meta-analysis. (2018) All outcomes | MD 1.56 [-0.28, 3.41] | 5 studies · 2963 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Dental caries and preterm birth: a systematic review and meta-analysis. 2018 All outcomes | November 2015; repeated December 2016 | 9 | Not applicable |
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.
- Association between periodontitis, periodontopathogens and preterm birth: is it real? · 2015 · included by 1 of these review
- Effect of Oral Diseases on Mothers Giving Birth to Preterm Infants · 2011 · included by 1 of these review
- Oral health in women with pregnancy and delivery complications · 2006 · 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.