ArticleBMC nutrition2026
Estimating multivitamin and mineral supplement use and associated nutrient intake in Saudi Arabia: a probabilistic modeling study.
Article in BMC nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMultivitamin and mineral supplements (MVMs) are extensively consumed worldwide; however, national-level data regarding their usage and associated nutrient intake in Saudi Arabia remain limited. Characterizing exposure and intake is crucial for regulatory assessments and public health planning.
methodsA probabilistic model was developed to estimate exposure to MVMs and quantify nutrient intake among adults in Saudi Arabia. The model integrated three probability distributions representing overall supplement use, MVMs use, and daily use, derived from population-based data, and combined them with nutrient concentration distributions obtained from 24 MVMs products available in the Saudi market. Monte Carlo simulation was applied to account for variability and uncertainty.
resultsThe median probability of exposure was 0.033 (95% uncertainty interval: 0.019-0.054) for males and 0.058 (95% uncertainty interval: 0.044-0.074) for females. Sensitivity analysis yielded comparable exposure estimates across the evaluated scenarios. Estimated nutrient intakes generally contributed modestly to daily values (DV), with vitamin B12 showing the highest contribution at the 50th percentile (117.7% DV for males and 203.7% DV for females). Estimated intakes for all nutrients remained below established upper levels (ULs). Indirect validation using per-capita expenditure showed that the observed market expenditure of 35 SAR/capita/year fell within the modeled uncertainty range of 4-50 SAR/capita/year .
conclusionsThe proposed probabilistic model provides a preliminary tool for estimating supplement-related nutrient exposure in the absence of national consumption surveys. The findings support its use in regulatory decision-making and highlight the need for further integration with food-based intake data.
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