Question · asked by 1 review
Not applicable (single-group prevalence) vs Not applicable: Dental caries prevalence
- Population
- General Pakistani population (all ages and both sexes; predominantly children and adolescents)
- Intervention
- Not applicable (single-group prevalence)
- Comparison
- Not applicable
- Outcome
- Dental caries prevalence
Fixed-effect pooled dental caries prevalence was 57.0% (95% CI 56.4% to 57.6%).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Not applicable vs Not applicable Dental caries prevalence · Pakistani population of any sex or age · 2009 to 2020, Pakistan, Fixed-effects model Fixed-effect pooled dental caries prevalence was 57.0% (95% CI 56.4% to 57.6%). Prevalence of dental caries in Pakistan: a systematic review and meta-analysis. (2021) All outcomes | Prevalence 56.999 [56.415, 57.581] | 30 studies · 27878 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Prevalence of dental caries in Pakistan: a systematic review and meta-analysis. 2021 All outcomes | January 1970 to June 2020 | 40 | Not applicable |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Not applicable (single-group prevalence) vs Not applicable (single-group prevalence) · Primary school children in Ethiopia · 1 review
- Not applicable (single-group prevalence) vs Not applicable · Children aged 12 years (plus or minus one year) in Africa · 1 review
- Not applicable (single-group prevalence) vs Not applicable (single-group prevalence) · Children (<18 years) with intellectual and developmental disabilities (IDD) in India · 1 review
- Not applicable (single-group prevalence) vs Not applicable · Children and adolescents with type 1 diabetes assessed with DMFT · 1 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.