Modelling the potential impact of water fluoridation on dental caries in Scotland: a pilot study.

Dental caries is one of the most widespread and preventable oral health conditions globally and remains a major contributor to the overall burden of oral disease.¹ In Scotland, dental caries continues to affect a high proportion of children, with significant inequalities across socioeconomic groups.^2,3

To address this, Scotland introduced the Childsmile programme, which was fully implemented in 2011 and combines supervised toothbrushing, fluoride varnish applications and community-based dental care.^2,3,4,5 Childsmile has contributed to improvements in children’s oral health; however, recent data suggest that progress has plateaued, with children living in the most deprived areas still experiencing higher caries levels compared to those in the least deprived areas.^3,6

Water fluoridation is a well-established population-level public health intervention that has consistently been shown to reduce dental caries and narrow socioeconomic inequalities.^7,8 In the past, some regions in Scotland implemented water fluoridation, with evidence from the 1950s to the 1980s indicating significant benefits.⁹ However, no active fluoridation schemes currently exist in Scotland and naturally occurring fluoride levels remain below 0.1 parts per million (ppm).^10,11

The 2015 and 2024 Cochrane Reviews confirmed that water fluoridation reduces dental caries, reporting effect sizes derived from a meta-analysis of international studies.^12,13 Nonetheless, these findings have not yet been applied to recent Scottish data. This pilot study aimed to estimate the potential impact of water fluoridation on dental caries among Scottish children, using data from the National Dental Inspection Programme (NDIP) and published effect sizes, with a particular focus on socioeconomic variation.

Study design

This pilot study is a descriptive, estimation-based quantitative analysis. Publicly available national data of Primary 1 (P1) and Primary 7 (P7) Scottish children were used, along with simple mathematical calculations to estimate the potential effect of fluoridation on dental health outcomes.

Data sources

The primary datasets were obtained from the NDIP 2024¹⁴ report and the NDIP 2023¹⁵ report, which are publicly available online. These reports provide national-level surveillance data on dental caries experience among P1 and P7 children, with average ages of 5.5 and 11.5 years, respectively.

The following data were extracted from the reports:

• Mean decayed, missing, and filled primary and permanent teeth (dmft and DMFT)
• Mean dmft and DMFT scores by Scottish Index of Multiple Deprivation (SIMD) quintile
• Overall proportion of children with no obvious decay experience (caries-free percentages)
• Caries-free percentages across SIMD quintiles
• SIMD quintile classification (1 = most deprived, 5 = least deprived).

Dental caries in the NDIP reports was assessed using a visual inspection and follows the diagnostic criteria set by the British Association for the Study of Community Dentistry (BASCD).^14,15 Examiners were trained and calibrated to ensure consistent application of the BASCD guidelines.^14,15 The surveys used the d₃mft/D₃MFT index, which defines caries at the dentinal levels, excluding enamel-only lesions.

Effect sizes for estimating the impact of fluoridation were taken from the 2024 Cochrane Review.¹³ These values represent expected reductions in caries levels following lifetime exposure of children to fluoridation. Only the main meta-analysis results were used, and sensitivity analysis results were excluded to ensure consistency.

Effect sizes applied:

• Mean dmft reduction: 0.24 (95% confidence interval [CI]: -0.03 to 0.52)
• Mean DMFT reduction: 0.27 (95% CI: -0.11 to 0.66)
• Caries-free proportion in primary teeth increase: -0.04 (95% CI: -0.09 to 0.01)
• Caries-free proportion in permanent teeth increase: -0.03 (95% CI: -0.07 to 0.01).

CIs were only available for overall NDIP values and were used to calculate standard errors (SE) for dmft/DMFT and caries-free proportions. These were then used to estimate CIs and SEs for the predicted post-fluoridation values. CIs were not included for the SIMD-level data and the Cochrane Review did not provide socioeconomic status (SES)-specific effect sizes. As a result, SIMD results are presented as point estimates without CIs and SEs for consistency.

Outcome prediction

To estimate the potential impact of water fluoridation, effect sizes were applied directly to the baseline NDIP values. Predicted post-fluoridation mean dmft/DMFT scores were calculated by subtracting the effect size from the baseline mean dmft/DMFT values. The same method was used to calculate the predicted dmft/DMFT across SIMD quintiles.

A similar approach was used to calculate the predicted post-fluoridation caries-free percentages in primary and permanent teeth, in addition to the caries-free percentages across SIMD quintiles. The baseline caries-free percentages were first converted to decimals to match the effect size format, then reconverted back to percentages after the calculations.

SEs for the NDIP and Cochrane Review data were first calculated from the 95% CI provided in the report and review. These SEs were then used to calculate the predicted SEs for the post-fluoridation estimates by combining the variance from both sources, assuming independence. Finally, the predicted SEs were used to compute the 95% CIs for the estimated post-fluoridation outcomes.

The following formulas were used:

• Predicted dmft/DMFT = baseline dmft/DMFT – effect size dmft/DMFT
• Predicted caries-free proportion = baseline caries-free proportion – effect size caries-free proportion

All predicted dmft/DMFT values were capped at 0.00, as these are count variables and cannot fall below zero.

Data analysis and visualisation

All data processing, prediction calculations, and visualisations were carried out using R software.¹⁶ Packages used in R included ggplot2¹⁷ for data visualisation, dplyr¹⁸ and tidyr¹⁹ for data manipulation, readxl²⁰ for data import, and openxlsx²¹ for exporting results. Microsoft Excel was used for data review and organisation.

Two formats were used to report predicted and baseline values. Tables were used to provide the baseline and predicted values for dmft/DMFT and caries-free percentages. Bar charts were used to illustrate baseline and predicted values side-by-side, comparing findings before and after fluoridation.

All predicted values were rounded to two decimal places for dmft/DMFT and one decimal place for caries-free percentages. Consistent dataset structure was maintained across P1 and P7 analysis to ensure comparability.

P1 overall results

At baseline, the mean dmft score among 13,144 P1 children was 0.99 (95% CI: 0.95 to 1.02). After applying the Cochrane Review¹³ effect size, the predicted mean dmft decreased to 0.75 (95% CI: 0.47 to 1.03) (Table 1). Moreover, the proportion of caries-free children at baseline was 73.2% (95% CI: 72.6% to 73.9%). This increased to a predicted caries-free proportion of 77.2% (95% CI: 72.2% to 82.2%) following the modelling (Table 1).

P1 SIMD results

Mean dmft decreased across all SIMD quintiles after prediction. At baseline, the highest dmft was observed in SIMD quintile one (most deprived) at 1.73, while the lowest was in quintile five (least deprived) at 0.47. Predicted dmft values ranged from 1.49 (SIMD 1) to 0.23 (SIMD 5) (Fig. 1). Caries-free percentages at baseline ranged from 60.1% to 83.6%. After applying the effect size, these increased across all quintiles from 64.1% to 87.6% (Fig. 2).

Primary 1 mean decayed, missing and filled teeth by Scottish Index of Multiple Deprivation quintiles

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Primary 1 caries-free% by Scottish Index of Multiple Deprivation quintiles

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P7 overall results

The mean DMFT score at baseline for 13,114 P7 children was 0.36 (95% CI: 0.35 to 0.38) which decreased to a predicted value of 0.09 (95% CI: -0.30 to 0.48) after applying the effect size (Table 2). The baseline caries-free percentage was 81.9% (95% CI: 81.3% to 82.5%), increasing to 84.9% (95% CI: 80.9% to 88.9%) after modelling (Table 2).

P7 SIMD results

DMFT scores decreased in all SIMD quintiles. SIMD 1 had the highest baseline DMFT score at 0.61, and SIMD 5 had the lowest at 0.21. Predicted DMFT ranged from 0.34 (SIMD 1) to 0.00 (SIMD 4 and 5), with values capped at zero where predictions were negative (Fig. 3). At baseline, caries-free percentages ranged from 71.9% to 88.0%, with predicted values ranging from 74.9% to 91.0% (Fig. 4).

Primary 7 mean decayed, missing and filled teeth by Scottish Index of Multiple Deprivation quintiles

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Primary 7 caries-free% by Scottish Index of Multiple Deprivation quintiles

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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 NDIP^14,15 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.

This pilot estimation study suggests that introducing water fluoridation in Scotland could lead to meaningful improvements in dental health among children, particularly by increasing the proportion of caries-free children and reducing dmft/DMFT values. While the estimated benefits were most visible in low-risk groups, this likely reflects methodological limitations in the approach, rather than the true distribution of benefit. In practice, children from more deprived areas may stand to benefit the most, especially when fluoridation is introduced alongside existing preventive programmes, such as Childsmile.

These findings support further exploration of water fluoridation as a complementary public health intervention in Scotland. Although this study used a simplified estimation method, it highlights the potential value of applying evidence-based effect sizes to national surveillance data to inform oral health policy and service planning. This pilot approach provides a simple, transparent model that could be adapted for use in other non-fluoridated populations with similar data availability.