Modelling the potential impact of water fluoridation on dental caries in Scotland: a pilot study
Summary of findings
This pilot study aimed to explore the potential impact of water fluoridation on dental caries levels among Scottish children in 2023 and 2024, using baseline data from NDIP14,15 and effect sizes from the Cochrane Review.13 The analysis included both P1 and P7 children and considered overall values and SIMD quintile breakdowns. The findings suggest that fluoridation would reduce the overall mean dmft/DMFT and increase the proportion of caries-free children across both age groups.
Among P1 children, the baseline mean dmft was highest in SIMD 1 and lowest in SIMD 5. The least deprived group had a greater proportion of caries-free children at baseline compared to the most deprived group. After applying a fixed effect size, predicted mean dmft decreased across all quintiles and caries-free proportions increased, suggesting a beneficial effect.
A similar pattern was observed among P7 children, where the baseline DMFT was highest in the most deprived group and lowest in the least deprived group. Applying the effect size led to reductions in DMFT across all groups, with SIMD 4 and 5 predicted to have values of 0.00. Caries-free proportions also increased across all groups, with SIMD 5 achieving the highest predicted rates.
These findings demonstrate improvements in both dmft/DMFT scores and caries-free percentages across all socioeconomic groups. However, the least deprived groups showed the largest absolute improvements. This is likely to be due to their lower baseline caries levels, which led to predicted values near zero or zero when combined with a uniform effect size, and caries-free proportions nearing 100%. This likely reflects an overestimation of the benefit in low-risk groups and highlights a key limitation of using a uniform effect size across all SIMD quintiles.
P1 versus P7 comparison
Compared to P1 children, P7 children generally had better baseline oral health than P1, as reflected in lower DMFT scores and higher caries-free proportions. This may reflect the cumulative effects of existing preventive programmes such as Childsmile, which have been in place during the early years of the P7 cohort. The P7 group of 11-year-old children are unlikely to have second permanent molars, a caries-susceptible permanent tooth which may underestimate caries levels. The World Health Organization recommends that 12-year-olds are surveyed for national DMFT levels.22 As a result, estimated post-fluoridation outcomes among P7 children were more favourable, with some SIMD groups reaching predicted DMFT values of zero and caries-free proportions approaching 100%.
In contrast, P1 children had higher baseline dmft scores and lower caries-free rates, especially in the most deprived SIMD quintiles. Despite applying the same effect size, predicted improvements were more modest compared to P7. This suggests that younger children, having had less time to benefit from existing interventions, may benefit from early-life or additional population-level measures, such as water fluoridation. The comparison highlights the importance of timing in preventive strategies and supports the need for early-life interventions to reduce long-term oral health inequalities.
Comparison to other studies
Numerous studies have shown that water fluoridation is associated with lower levels of dental caries and improved oral health, particularly in children. A systematic review by Senevirathna et al.23 reported a 26–44% reduction in caries levels among children and adolescents in fluoridated areas in Australia. Even in the context of widespread fluoride toothpaste use, children exposed to water fluoridation had a 57% lower caries prevalence than those not exposed in Brazil.24
The CATFISH study in Cumbria found that 17.4% of children with a mean age of 4.8 years in fluoridated areas had caries experience, compared to 21.4% in non-fluoridated areas.25 Among children with mean age of 10.8 years, 19.1% had caries experience in fluoridated areas compared to 21.9% in non-fluoridated groups.25 This study has been criticised however as water fluoridation did not continue throughout the study period.26
Previous studies have also highlighted the potential for fluoridation to reduce oral health inequalities. Foster et al.27 suggested the greatest benefits were among children from the most deprived backgrounds. Roberts et al.28 found a positive association between water fluoridation and SES, with reductions in caries across all quintiles and differential benefits by SES. McGrady et al.29 observed lower caries levels and reduced socioeconomic inequalities in fluoridated populations. Similarly, Kim et al.30 reported both lower caries prevalence and reduced oral health inequalities associated with fluoridation.
Limitations
This modelling study has several limitations. First, the same effect size was applied across all SIMD quintiles, regardless of baselines caries levels. This study used population-level data and did not incorporate individual-level caries risk indicators or behavioural risk factors. While this allowed for a simplified modelling approach, it may not fully reflect the complexity of caries development. Therefore, this approach does not account for the possibility that fluoridation may have different impacts depending on the initial caries burden or other contextual factors. Caries risk assessment models typically account for variables such as diet, oral hygiene, socioeconomic context, and past dental history, which were beyond the scope of this analysis. As a result, this pilot study may overestimate benefits in low-risk groups and underestimate potential gains in more deprived populations. Additionally, the Cochrane Review applied strict inclusion criteria, which resulted in a limited number of included studies. This may have led to conservative effect size estimates that potentially underestimate the true impact of water fluoridation.
Second, in some SIMD quintiles, the effect size exceeded baseline dmft/DMFT value, resulting in predicted values falling below zero. These values were capped at 0.00 as caries scores cannot be assigned a negative value. This adjustment may have masked small but meaningful differences between groups and contributed to an unrealistic flattening of predicted outcomes in groups already exhibiting low caries levels.
Third, CIs were only calculated for overall dmft/DMFT and caries-free results, as SIMD-level NDIP data do not report CIs, and the Cochrane Review does not provide SIMD-stratified estimates. While including CIs could add statistical context to the predictions, the predicted CIs reported in this study were relatively wide, particularly in comparison to baseline values. This reflects the uncertainty surrounding the effect size estimates derived from the Cochrane Review, which reported a wide range of estimates across the included studies. These wider intervals do not necessarily indicate reduced reliability but rather highlight the variability in the available evidence used to model the predicted impact of water fluoridation. Additionally, due to the unavailability of raw data, standard deviations could not be calculated. SEs were used instead, as they could be derived from available CIs to indicate variability in the mean scores. Future studies should incorporate more advanced modelling and SES-specific effect sizes to better understand the full impact of fluoridation on oral health inequalities.
Despite these limitations, this pilot study offers a valuable tool in exploring the potential impact of fluoridation in Scotland and may help inform future study design and policy discussions.
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