Validity of spot urine samples for estimating systemic fluoride exposure in children across diverse fluoridation modalities

This is the authors' abstract. We don't add key points for this paper.

Objective Reliable biomarkers are essential for assessing children's fluoride exposure, yet 24-h urinary fluoride excretion (24 h-UFE), the gold standard, is logistically challenging to collect. The validity of spot urine samples as a proxy across fluoridation modalities has not been evaluated. This study is the first to assess the predictive accuracy of spot urine fluoride concentration (U FC ), creatinine-adjusted (U F/CR ), and specific gravity-adjusted (U F/SG ) for estimating 24 h-UFE across multiple fluoride exposure modalities. Methods In this multi-modality observational study, 178 children aged 4–6 years residing in regions with different fluoride modalities were included: water fluoridation (UK, Brazil), salt fluoridation (Colombia), milk fluoridation (Chile), and non-fluoridated areas (UK, Chile). Each child provided one 24-h urine sample and four spot samples during a separate session (post-breakfast, post-lunch, before bedtime, first morning void). Linear regression models assessed the predictive validity of U FC , U F/CR , and U F/SG . Results Mean urinary fluoride ranged 0.48–1.38 mg/L (U FC ), 1.13–2.30 mg/g (U F/CR ), and 0.55–1.70 mg/L (U F/SG ). UFC showed the strongest association with 24 h-UFE (mean R 2 = 77%), particularly in water-fluoridated areas (up to 85%). U F/CR and U F/SG correlations were weaker (mean R 2 = 58% and 61%). Accuracy improved when multiple spot samples were used. Timing of peak fluoride excretion varied: post-breakfast (water), post-lunch (salt), first morning void (milk and non-fluoridated areas). Conclusion Spot U FC provides a practical alternative for population-level monitoring of fluoride exposure in children, although accuracy depends on sampling time and fluoridation modality. This multi-modality study demonstrates variability in fluoride excretion across sources and informs optimized sampling strategies for public health surveillance.