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

被引:50
|
作者
Orioli, Riccardo [1 ]
Cremona, Giuseppe [2 ]
Ciancarella, Luisella [2 ]
Solimini, Angelo G. [1 ]
机构
[1] Sapienza Univ Rome, Dept Publ Hlth & Infect Dis, Rome, Italy
[2] Natl Agcy New Technol Energy & Sustainable Econ D, Sustainable Terr & Prod Syst Dept, Bologna, Italy
来源
PLOS ONE | 2018年 / 13卷 / 01期
关键词
FINE PARTICULATE MATTER; LONG-TERM EXPOSURE; AIR-POLLUTION EXPOSURE; INSULIN-RESISTANCE; MELLITUS; INFLAMMATION; RISK; PREVALENCE; ATHEROSCLEROSIS; HYPERTENSION;
D O I
10.1371/journal.pone.0191112
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Introduction Air 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 methods We 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 03 four-years mean levels and the risk of being affected by DM. Results We 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 fag/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 03, 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). Conclusions We 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.
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页数:17
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