Evidence map›Paper›PMID 29948537›Full record

ArticleEnvironmental geochemistry and health2018

Geochemical valuation and intake of F, As, and Se in coal wastes contaminated areas and their potential impacts on local inhabitants, Shaanxi China.

Rahib Hussain, Kunli Luo

Abstract read
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In one paragraph

Article in Environmental geochemistry and health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.2field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 29 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Rahib HussainInstitute of Geographic Sciences and Natural Resource Research, Beijing, 100101, China.
Kunli LuoInstitute of Geographic Sciences and Natural Resource Research, Beijing, 100101, China. luokl@igsnrr.ac.cn.ORCID http://orcid.org/0000-0003-1345-0089
Institute of Geographic Sciences and Natural Resources Research · CN

Funding

National Basic Research Program of China, The National Natural Science Foundation of China and CAS-TWAS fellowship 41472322)National Basic Research Program of China, The National Natural Science Foundation of China and CAS-TWAS fellowship (Grant No.2014CB238906)National Basic Research Program of China, The National Natural Science Foundation of China and CAS-TWAS fellowship (Grant Nos. 41172310
6 · The paper itself

Abstract

This study probe the human health risk of fluoride (F), arsenic (As), and selenium (Se) and their daily intake available quantity to human through different sources in different regions of Shaanxi, China. For this purpose, a number of samples, including coal and coal wastes, rocks, soil, and vegetables were collected from south Qinling Mountain stone-like coal (Geo type-I), Binxian-Jurassic (Geo type-II), Hancheng Permo-Carboniferous (Geo type-III), and countryside (Huanglong County) of Shaanxi province. All these samples were analyzed through atomic fluorescence spectroscopy and combustion hydrolysis methods. Results showed that Geo type-I was enriched with As, Se, and F, Geo type-II, III, and the countryside were slightly enriched with As and F and deficient in Se. The average daily intake (ADI) of Se in Geo type-I was 0.005-0.0045, Geo type-II 0.0005-0.0004, Geo type-III 0.0006-0.0005, and countryside 0.0002-0.001 in mg kg

Indexed as

ArsenicChinaCoal MiningDietFluorineHumansIndustrial WasteModels, TheoreticalRisk AssessmentSeleniumSoilSoil PollutantsArsenicFluorineIndustrial WasteSeleniumSoilSoil PollutantsCambrianFluorideJurassicSeleniumToxicityWeibei coalfield

Identifiers

PMID29948537
OpenAlexW2808061348

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.