High-frequency sugar consumption (three or more times daily) vs Low sugar intake (fewer than three times daily): Dental caries prevalence
- Population
- Nigerian individuals, including children and adults, with primary or permanent dentition
- Intervention
- High-frequency sugar consumption (three or more times daily)
- Comparison
- Low sugar intake (fewer than three times daily)
- Outcome
- Dental caries prevalence
High-frequency sugar consumption was associated with 18% higher but non-significant odds of dental caries in Nigeria (OR 1.18, 95% CI 0.87 to 1.59; I2=36%; ungraded).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
High-frequency sugar consumption (three or more times daily) vs Low sugar intake (fewer than three times daily) Dental caries experience (prevalence) · Nigerian individuals, including children and adults, with primary or permanent dentition · Community and school-based observational studies in Nigeria (12 of 14 in Southwest Nigeria), Overall (all dentitions pooled) High-frequency sugar consumption was associated with 18% higher but non-significant odds of dental caries in Nigeria (OR 1.18, 95% CI 0.87 to 1.59; I2=36%; ungraded). A systematic review and meta-analysis of the association between sugar intake and dental caries in Nigeria. (2024) All outcomes | OR 1.18 [0.87, 1.59] | 7 studies | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| A systematic review and meta-analysis of the association between sugar intake and dental caries in Nigeria. 2024 All outcomes | January 2001 to November 2024 (per Methods; Abstract states January 2001 to March 2023) | 15 | 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.
- El Tantawi 2021 · 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.