Periodontal and dental conditions of a school population in a volcanic region of Tanzania with highly fluoridated community drinking water

Miranda‐Rius, Jaume; Brunet‐Llobet, Lluís; Lahor-Soler, Eduard; Mrina, Ombeni; Mashala, Elias Isaack; Mahande, Michael Johnson

doi:10.4314/ahs.v20i1.54

Cited by 5 publications

(4 citation statements)

References 42 publications

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“…Firstly, dental fluorosis is endemic in around volcanic areas, due to the high fluoride content in daily drinking water. Scholars have analyzed the correlative relationship between dental fluorosis and high fluoride [ 33 ]. Secondly, the TDS is screened owing to the agricultural purpose of groundwater in the study area.…”

Section: Methodsmentioning

confidence: 99%

Predicting Groundwater Indicator Concentration Based on Long Short-Term Memory Neural Network: A Case Study

Liu

et al. 2022

IJERPH

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Prediction of groundwater quality is an essential step for sustainable utilization of water resources. Most of the related research in the study area focuses on water distribution and rational utilization of resources but lacks results on groundwater quality prediction. Therefore, this paper introduces a prediction model of groundwater quality based on a long short-term memory (LSTM) neural network. Based on groundwater monitoring data from October 2000 to October 2014, five indicators were screened as research objects: TDS, fluoride, nitrate, phosphate, and metasilicate. Considering the seasonality of water quality time series data, the LSTM neural network model was used to predict the groundwater index concentrations in the dry and rainy periods. The results suggest the model has high accuracy and can be used to predict groundwater quality. The mean absolute errors (MAEs) of these parameters are, respectively, 0.21, 0.20, 0.17, 0.17, and 0.20. The root mean square errors (RMSEs) are 0.31, 0.29, 0.28, 0.27, and 0.31, respectively. People can be given early warnings and take measures according to the forecast situation. It provides a reference for groundwater management and sustainable utilization in the study area in the future and also provides a new idea for coastal cities with similar hydrogeological conditions.

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Section: Methodsmentioning

confidence: 99%

Predicting Groundwater Indicator Concentration Based on Long Short-Term Memory Neural Network: A Case Study

Liu

et al. 2022

IJERPH

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“…Флюороз зубів і скелета став гострою клінічною проблемою і проблемою громадського здоров'я в кількох частинах світу, особливо у Великій рифтовій долині, яка пролягає від північної Сирії до центрального Мозамбіку в Східній Африці [26]. Високу поширеність флюорозу зубів (75,22%) виявлено в Північній Танзанії в Африці, особливо у вулканічних районах, що пояснюється високим умістом фтору в щоденній питній воді -3,6 мг/л [27]. У різних регіонах Судану вміст фтору в питній воді коливається від 0,5 до 4,0 мг/л, тому поширеність теж різна: від 42,5% до 100% [6].…”

Section: результати дослідження та їх обговоренняunclassified

Fluorosis Prevalence at Different Regions of the Earth (Literature Review)

Kaskova,

Morhun,

Vashchenko

et al. 2024

Ukr. Dent. Alm.

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The aim of the study is to analyze the literature about the fluorosis prevalence and the factors which lead to dental and bone fluorosis. The search for articles published in 2016-2023 was conducted by the authors in Scopus and Web of Science scientific data bases using the keywords “fluorosis”, “dental fluorosis”. To classify the severity of dental fluorosis, the index of developmental defects of enamel (DDE), the index of tooth surface fluorosis (TSIF), and mostly Dean’s index Thylstrup & Fejerskov Index (TFI) are used. The risk factors for dental fluorosis include living in regions with high level of fluoride, drinking water with high level of fluoride or salt fluoridation, drinking bottled water, use of fluoride toothpastes among preschool children, early weaning, and use of infant formula for long time, and, as well as, a hot climate and high fluoride content in soil and food. The studies from India and China demonstrated that the average concentration of dental fluorosis and skeletal fluorosis at fluoride contained 6 mg/l. The prevalence of dental fluorosis in NorthernTanzania, where the fluorine content in daily drinking water is 3.6 mg/l, reaches 75,22%. In Ethiopia, where fluorine content is 5.09 mg/l, the prevalence of skeletal fluorosis ranges from 55.1% to 72.4%. In Kenya, the fluoride content in drinking water reaches 72 mg/l, so the prevalence of dental fluorosis is 80%. The prevalence of dental fluorosis is lower in South Western Saudi Arabia and Iran where fluoride level is lower. In Jordan, the prevalence of dental fluorosis reaches 39.9% due to the high fluoride content in miner rocks. Skeletal fluorosis is wide spread in some areas of Pakistan due to the contamination of ground water by industrial production. The prevalence of mild dental fluorosis is 39% in New castle where water is fluoridated, and 24% in non-fluoridated Manchester in England. Dean’s index and TFI index are mostly used to classify these variety of fluorosis. Various factors affect the appearance of dental and bone fluorosis worldwide, so the prevalence of fluorosis varies from 11,1 up to 100%.

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“…Despite their clear benefits in enamel remineralization, high‐dose fluoride intake can be harmful. In certain geographical areas where public drinking water naturally has high fluoride concentrations, high rates of dental and even skeletal fluorosis have been found (Miranda‐Rius et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

The use of silver diamine fluoride in a children's hospital: Critical analysis and action protocol

Brunet‐Llobet

Auría‐Martín

González‐Chópite

et al. 2022

Clinical & Exp Dental Res

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Objectives The present critical analysis aims to propose an action protocol for the use of silver diamine fluoride (SDF) in pediatric patients in a hospital setting, especially for those who are currently awaiting hospital dental treatment under general anesthesia. Material and Methods A literature search was performed in the PubMed/MEDLINE from 2009 to 2021 using the search terms “silver diamine fluoride”, “pediatrics silver diamine fluoride”, “application silver diamine fluoride”, and “AND” ‐ combined with terms: “potassium iodide”, “properties”, “adverse effects”, “early childhood caries”, “patient with disability”, “management”, “special health care needs patient”. Articles that recorded the type of teeth, application protocol, the concentration of the product, and possible complications of the treatment were selected. Results Four hundred and sixteen related articles were obtained, of which 13 were finally chosen on the basis of the search criteria. The age at which the use of SDF was recommended ranged from the first year of life to 12 years, in most cases in primary teeth. The study populations varied in size from 53 to 799 patients. An analysis of the characteristics of SDF and its use in pediatric patients with dental caries was performed. The recommended concentration was 38% SDF, applied twice yearly. The main complication reported was staining. A decision algorithm was designed including SDF as an agent for caries control in patients attending the specific population of our hospital (divided into two groups: healthy children aged 0−4 years and patients with special health care needs (SHCNs) aged 0−18 years). Conclusions SDF therapy appears to be effective in the control of caries in pediatric patients. We propose an action protocol for patients with early childhood caries to reduce risk, complications, and the progression of lesions. The protocol is aimed especially at pediatric patients who also have some systemic pathology, disability, SHCNs, and/or behavioral difficulties.

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Periodontal and dental conditions of a school population in a volcanic region of Tanzania with highly fluoridated community drinking water

Cited by 5 publications

References 42 publications

Predicting Groundwater Indicator Concentration Based on Long Short-Term Memory Neural Network: A Case Study

Predicting Groundwater Indicator Concentration Based on Long Short-Term Memory Neural Network: A Case Study

Fluorosis Prevalence at Different Regions of the Earth (Literature Review)

The use of silver diamine fluoride in a children's hospital: Critical analysis and action protocol

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