Evidence map›Paper›PMID 33995854›Full record

ArticleWorld journal of diabetes2021

Relationships between emissions of toxic airborne molecules and type 1 diabetes incidence in children: An ecologic study.

Agostino Di Ciaula, Piero Portincasa

Open access · diamondAbstract read
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Article in World journal of diabetes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 12 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.

Agostino Di CiaulaClinica Medica "A. Murri", Department of Biomedical Sciences and Human Oncology, University of Bari Medical School, Bari 70124, Italy. agostinodiciaula@tiscali.it.
Piero PortincasaClinica Medica "A. Murri", Department of Biomedical Sciences and Human Oncology, University of Bari Medical School, Bari 70124, Italy.
University of Bari Aldo Moro · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType 1 diabetes originates from gene-environment interactions, with increasing incidence over time.

aimTo identify correlates of childhood type 1 diabetes in European countries using an ecological approach. Several environmental variables potentially influencing the onset of type 1 diabetes have been previously evaluated. However, the relationships between epidemiologic data and exposure to toxic airborne molecules are scarcely studied.

methodsWe employed an ecological model to explore, in a wide time period (1990-2018), associations between type 1 diabetes incidence in 19 European countries (systematic literature review) and the nationwide production of five widely diffused air pollutants: particulate matter < 10 μm (PM10), nitrogen oxides (NO), non-methane volatile organic compounds (VOCs), sulphur oxide (SO

resultsData confirm a raising incidence of type 1 diabetes in 18 out of 19 explored countries. The average difference (last

conclusionEvidence justify further studies to explore better links between long-term air quality and type 1 diabetes onset at the individual level, which should include exposures during pregnancy. In this respect, type 1 diabetes could be, at least in part, a preventable condition. Thus, primary prevention policies acting through a marked abatement of pollutant emissions might attenuate future type 1 diabetes incidence throughout Europe.

Indexed as

Air pollutionEpidemiologyNitrogen oxideNon-methane volatile organic compoundsParticulate matterType 1 diabetes

Identifiers

PMID33995854
PMCPMC8107975
OpenAlexW3158655755

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.