Non-Carcinogenic Health Risk Assessment due to Fluoride Exposure from Tea Consumption in Iran Using Monte Carlo Simulation.
Mohammad Amin KaramiYadollah FakhriShahabaldin RezaniaAbdol Azim AlinejadAli Akbar MohammadiMahmood YousefiMansour GhaderpooriMohammad Hossien SaghiMohammad AhmadpourPublished in: International journal of environmental research and public health (2019)
Excessive intake of fluoride can cause adverse health effects. Consumption of tea as a popular drink could be a potential source of fluoride exposure to humans. This research aimed to evaluate the fluoride concentration in tea among the Iranian people using the available data in the literature and to assess the health risk related to the consumption of tea in men, women, and children. The health risk assessment was conducted using the chronic daily intake and hazard quotient according to the approach suggested by the Environmental Protection Agency. The fluoride content in published studies varied noticeably, ranging from 0.13 to 3.27 mg/L. The results revealed that the hazard quotient (HQ) in age groups of women (21-72 years) and children (0-11 years) was within the safe zone (HQ < 1) which showed that there was no potential of non-carcinogenic risk associated with drinking tea in these groups. However, in one case of the men (21-72 years), the HQ > 1 which shows a probable risk of fluorosis. The order of non-carcinogenic health risks in the studied groups was in the order of men > women > children. The results of this can be useful for organizations with the responsibility of human health promotion.
Keyphrases
- drinking water
- health risk assessment
- health risk
- heavy metals
- polycystic ovary syndrome
- young adults
- health promotion
- pregnancy outcomes
- monte carlo
- endothelial cells
- systematic review
- weight gain
- cervical cancer screening
- breast cancer risk
- polycyclic aromatic hydrocarbons
- risk assessment
- emergency department
- physical activity
- insulin resistance
- type diabetes
- pregnant women
- machine learning
- body mass index
- big data
- skeletal muscle
- adverse drug
- case control