Evidence map›Paper›PMID 29342195›Full record

ArticlePloS one2018

Association between PM10, PM2.5, NO2, O3 and self-reported diabetes in Italy: A cross-sectional, ecological study.

Riccardo Orioli, Giuseppe Cremona, Luisella Ciancarella, Angelo G Solimini

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
4.3field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 67 citations in OpenAlex.

  1. The effect of ambient ozone exposure on three types of diabetes: a meta-analysis.Environmental health : a global access science source · 2023
    Pooled it
  2. Pooled it
  3. Article
  4. Potential causal links of long-term PMSustainable cities and society · 2025
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  11. PMBMC public health · 2021
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  15. The Effects of Social, Personal, and Behavioral Risk Factors and PMInternational journal of environmental research and public health · 2020
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  19. Associations of long-term exposure to PMEnvironment international · 2019
    Article
  20. Synergistic Association of House Endotoxin Exposure and Ambient Air Pollution with Asthma Outcomes.American journal of respiratory and critical care medicine · 2019
    Article
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

4 authors at 2 institutions in 1 country.

Riccardo OrioliDepartment of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy.ORCID 0000-0002-4767-3558
Giuseppe CremonaSustainable Territorial and Production Systems Department, National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Bologna, Italy.
Luisella CiancarellaSustainable Territorial and Production Systems Department, National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Bologna, Italy.
Angelo G SoliminiDepartment of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy.
National Agency for New Technologies, Energy and Sustainable Economic Development · ITSapienza University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAir pollution represents a serious threat to health on a global scale, being responsible for a large portion of the global burden of disease from environmental factors. Current evidence about the association between air pollution exposure and Diabetes Mellitus (DM) is still controversial. We aimed to evaluate the association between area-level ambient air pollution and self-reported DM in a large population sample in Italy. MATERIALS AND

methodsWe extracted information about self-reported and physician diagnosed DM, risk factors and socio-economic status from 12 surveys conducted nationwide between 1999 and 2013. We obtained annual averaged air pollution levels for the years 2003, 2005, 2007 and 2010 from the AMS-MINNI national integrated model, which simulates the dispersion and transformation of pollutants. The original maps, with a resolution of 4 x 4 km2, were normalized and aggregated at the municipality class of each Italian region, in order to match the survey data. We fit logistic regression models with a hierarchical structure to estimate the relationship between PM10, PM2.5, NO2 and O3 four-years mean levels and the risk of being affected by DM.

resultsWe included 376,157 individuals aged more than 45 years. There were 39,969 cases of DM, with an average regional prevalence of 9.8% and a positive geographical North-to-South gradient, opposite to that of pollutants' concentrations. For each 10 μg/m3 increase, the resulting ORs were 1.04 (95% CI 1.01-1.07) for PM10, 1.04 (95% CI 1.02-1.07) for PM2.5, 1.03 (95% CI 1.01-1.05) for NO2 and 1.06 (95% CI 1.01-1.11) for O3, after accounting for relevant individual risk factors. The associations were robust to adjustment for other pollutants in two-pollutant models tested (ozone plus each other pollutant).

conclusionsWe observed a significant positive association between each examined pollutant and prevalent DM. Risk estimates were consistent with current evidence, and robust to sensitivity analysis. Our study adds evidence about the effects of air pollution on diabetes and suggests a possible role of ozone as an independent factor associated with the development of DM. Such relationship is of great interest for public health and deserves further investigation.

Indexed as

AgedCross-Sectional StudiesDiabetes MellitusFemaleHumansItalyMaleMiddle AgedParticulate MatterSelf ReportParticulate Matter

Identifiers

PMID29342195
PMCPMC5771616
OpenAlexW2784686862

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.