The research team, led by Zeynab Ghaemi of the Department of Water Engineering at Shiraz University, together with Masoud Noshadi and Rezvan Talebnejad, set out to address a persistent gap in how defluoridation policies are evaluated. Previous assessments, the authors note, have largely overlooked the population-level health benefits of water treatment interventions, the variability in how well different technologies actually perform, and the direct mathematical link between treatment efficacy and health outcomes. By integrating disability-adjusted life year (DALY) modeling with kernel density estimation and stochastic simulation, the team built a strategic framework that connects water chemistry directly to the number of healthy life years at stake.

Fluoride is a paradoxical element in public health. In trace amounts, it strengthens tooth enamel and reduces dental caries, which is why it is deliberately added to water supplies in many countries. But in arid regions where groundwater circulates through fluoride-rich rocks such as fluorite, apatite, and micas, natural concentrations can climb far above the World Health Organization guideline of 1.5 milligrams per liter. Chronic ingestion of elevated fluoride causes dental fluorosis, a permanent discoloration and pitting of tooth enamel that develops during childhood, and, at higher exposures, skeletal fluorosis, a debilitating condition in which fluoride accumulates in bone tissue, causing pain, stiffness, calcification of ligaments, and eventually severe joint immobility.

To map the geography of this risk, the researchers applied hierarchical clustering to their extensive dataset, delineating Fars Province into four distinct fluoride risk zones: low, moderate, high, and extreme. The spatial pattern that emerged was strikingly consistent. The highest proportions of samples exceeding the hazard quotient threshold of one, meaning the estimated exposure posed a potential non-carcinogenic health risk, were concentrated in the southern and southwestern zones of the province, and this pattern held across all age groups examined. Kernel density estimation allowed the team to visualize these hotspots as continuous risk surfaces rather than isolated sampling points, revealing how the geological and hydrogeochemical conditions of the region concentrate fluoride in specific aquifers.

The disease burden calculations revealed dental fluorosis as the dominant health outcome in every risk zone. In the extreme fluoride zone, the cumulative burden reached 669.14 DALYs, with a 95 percent uncertainty interval spanning 478.54 to 859.74, and normalized rates climbing as high as 1,888.55 per 100,000 population. Skeletal fluorosis contributed a smaller share of the total burden in all clusters, yet even it imposed a substantial toll, reaching 132.95 DALYs, or 458.72 per 100,000, in the extreme zone. The DALY metric, which combines years of life lost with years lived in disability, translates these clinical conditions into a currency that policymakers can compare against other health priorities, making the invisible burden of fluorosis visible in economic and planning terms.

What distinguishes this study from earlier risk assessments is its treatment of uncertainty. Rather than relying on single-point estimates of fluoride concentration, water intake, and body weight, the team employed Monte Carlo simulation to propagate probability distributions through their entire risk model. Intervention scenarios were stochastically modeled using fluoride-removal efficiency ranges drawn from the published literature, meaning that each policy was evaluated not as a fixed promise but as a realistic range of possible outcomes. This approach acknowledges a truth that deterministic analyses often obscure: the performance of a water treatment technology in the field varies with water chemistry, maintenance, operator skill, and countless local factors.

When the researchers ran nine defluoridation policies through this probabilistic framework, a clear hierarchy emerged. Reverse osmosis, the membrane-based process that forces water through a semi-permeable barrier that rejects fluoride ions along with many other dissolved solutes, proved the most effective intervention, achieving reductions of more than 98 percent in DALYs. Ion exchange and chemical precipitation methods followed closely, delivering approximately 96 percent reductions. These engineered treatments significantly outperformed the alternatives. Phytoremediation, which uses plants to accumulate or stabilize contaminants, achieved reductions in the range of 60 to 90 percent, while nutritional interventions, such as supplementing calcium to reduce fluoride absorption in the gut, delivered less than 50 percent reductions in disease burden.

One particularly notable finding was that the percentage reduction in DALYs was identical for dental and skeletal outcomes across all nine policies. This makes mathematical sense, since both conditions stem from the same exposure pathway, and reducing fluoride concentration in drinking water proportionally lowers the risk of each. But it also carries a practical implication: policymakers do not need to choose between protecting children’s teeth and protecting adults’ bones. Any intervention that meaningfully lowers fluoride exposure delivers benefits across the entire spectrum of fluorosis, and the choice among technologies can be driven by cost, scalability, and local infrastructure rather than by competing health objectives.

The implications extend well beyond Fars Province. Fluoride contamination in groundwater is a persistent challenge across arid and semi-arid regions worldwide, from the Rift Valley of Ethiopia and the bedrock aquifers of India and Pakistan to the coastal plains of China and the volcanic soils of Mexico and Italy. In many of these settings, rural communities depend entirely on hand pumps and shallow wells, and the geological source of fluoride means the problem cannot be solved by simply drilling deeper or moving the well. The framework developed by the Shiraz University team, which links spatiotemporal water quality monitoring to probabilistic health risk modeling and intervention scenario analysis, offers a transferable template for other fluorosis-endemic regions seeking to prioritize scarce resources.

Ultimately, the study demonstrates how probabilistic health-risk modeling can inform adaptive water governance and resource allocation. By quantifying exactly how many DALYs each defluoridation strategy could prevent, and by attaching uncertainty intervals to those estimates, the research gives decision-makers a defensible basis for investing in reverse osmosis and ion exchange infrastructure where the burden is greatest. As climate change intensifies pressure on groundwater resources across the Middle East and beyond, and as populations in fluoride-endemic regions continue to grow, the ability to connect a water chemistry measurement to a human health outcome, and that outcome to a specific, costed intervention, may prove to be one of the most valuable tools in the global effort to ensure that the water people drink sustains them rather than silently harms them.

Subject of Research: Groundwater fluoride contamination, fluorosis health risk, and defluoridation policy assessment in Fars Province, Iran

Article Title: Spatiotemporal distribution, health risk assessment, and preventable disease burden of dental and skeletal fluorosis via defluoridation scenarios in Fars Province, Iran

Article References: Ghaemi, Z., Noshadi, M., & Talebnejad, R. (2026). Spatiotemporal distribution, health risk assessment, and preventable disease burden of dental and skeletal fluorosis via defluoridation scenarios in Fars Province, Iran. Environmental Geochemistry and Health, 48(15), Article 592. https://doi.org/10.1007/s10653-026-03474-4

Image Credits: AI Generated

DOI: 10.1007/s10653-026-03474-4

Keywords: fluoride, fluorosis, groundwater, defluoridation, DALY, Monte Carlo simulation, health risk assessment, reverse osmosis, ion exchange, Fars Province, Iran, drinking water