Dataset Information

Association of Atmospheric Particulate Matter and Ozone with Gestational Diabetes Mellitus.

ABSTRACT: Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, evidence of the association is very limited, and no study has estimated the effects of ozone.Our aim was to determine the association of prenatal exposures to particulate matter ? 2.5 ?m (PM2.5) and ozone (O3) with GDM.We used Florida birth vital statistics records to investigate the association between the risk of GDM and two air pollutants (PM2.5 and O3) among 410,267 women who gave birth in Florida between 2004 and 2005. Individual air pollution exposure was assessed at the woman's home address at time of delivery using the hierarchical Bayesian space-time statistical model. We further estimated associations between air pollution exposures during different trimesters and GDM.After controlling for nine covariates, we observed increased odds of GDM with per 5-?g/m3 increase in PM2.5 (ORTrimester1 = 1.16; 95% CI: 1.11, 1.21; ORTrimester2 = 1.15; 95% CI: 1.10, 1.20; ORPregnancy = 1.20; 95% CI: 1.13, 1.26) and per 5-ppb increase in O3 (ORTrimester1 = 1.09; 95% CI: 1.07, 1.11; ORTrimester2 = 1.12; 95% CI: 1.10, 1.14; ORPregnancy = 1.18; 95% CI: 1.15, 1.21) during both the first trimester and second trimester as well as the full pregnancy in single-pollutant models. Compared with the single-pollutant model, the ORs for O3 were almost identical in the co-pollutant model. However, the ORs for PM2.5 during the first trimester and the full pregnancy were attenuated, and no association was observed for PM2.5 during the second trimester in the co-pollutant model (OR = 1.02; 95% CI: 0.98, 1.07).This population-based study suggests that exposure to air pollution during pregnancy is associated with increased risk of GDM in Florida, USA.Hu H, Ha S, Henderson BH, Warner TD, Roth J, Kan H, Xu X. 2015. Association of atmospheric particulate matter and ozone with gestational diabetes mellitus. Environ Health Perspect 123:853-859; http://dx.doi.org/10.1289/ehp.1408456.

SUBMITTER: Hu H

PROVIDER: S-EPMC4559952 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association of Atmospheric Particulate Matter and Ozone with Gestational Diabetes Mellitus.

Hu Hui H Ha Sandie S Henderson Barron H BH Warner Tamara D TD Roth Jeffrey J Kan Haidong H Xu Xiaohui X

Environmental health perspectives 20150320 9

<h4>Background</h4>Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, evidence of the association is very limited, and no study has estimated the effects of ozone.<h4>Objective</h4>Our aim was to determine the association of prenatal exposures to particulate matter ≤ 2.5 μm (PM2.5) and ozone (O3) with GDM.<h4>Methods</h4>We used Florida birth vital statistics records to investigate the association between the risk of GDM and two air pollutan ...[more]

PMID: 25794412

Similar Datasets

Project description:BackgroundEvidence from various epidemiological studies has shown an association between particulate matter 2.5 (PM2.5) and diabetes mellitus. A prospective study from the United States reported that exposure to PM2.5 alters endothelial function, and leads to insulin resistance and reduction in peripheral glucose uptake. There is a paucity of data on the relation between air pollution and diabetes in low- and middle-income countries.ObjectivesTo estimate the prevalence of type 2 diabetes among people living in areas with higher exposures of suspended PM2.5 compared to people living in areas with lower exposures in Chennai, Tamil Nadu, India.MethodsA cross-sectional study was carried out in two areas of Chennai city. The PM2.5 affecting vulnerable areas were stratified from a list of air quality monitoring stations in Tamil Nadu Pollution Control Board and Central Pollution Control Board. The highest and lowest areas of exposure were selected from the list. Households were randomly selected for the study. A total of 201 (67 male, 134 female) individuals from a high exposure area (HEA) and 209 (76 male 133 female) individuals from a low exposure area (LEA) were recruited for the study. Adults over 18 years of age were screened for random capillary blood glucose (RCBG) by glucometer (OneTouch Ultra).ResultsThe prevalence of diabetes (34.8% vs 19.6% p =0.001) was 77.5% higher among people living in areas of high particulate matter exposure compared to people living in less exposed areas. Multivariable logistic regression analysis showed that age, gender, residential area, and family history of diabetes were significantly associated with the prevalence of diabetes (p<0.05).ConclusionsThe present study indicates a link between high levels of exposure to PM2.5 and diabetes mellitus. Further prospective studies on populations exposed to elevated pollution are needed to establish whether this association has a causative link.Participant consentObtained.Ethics approvalThe study was approved by the Ethics Committee of the Prof. M Viswanathan Diabetes Research Centre, Chennai, India.Competing interestsThe authors declare no competing financial interests.

Project description:Emerging research findings suggest that airborne particulate matter might be a risk factor for gestational diabetes mellitus (GDM). However, the concentration-response relationships and the susceptible time windows for different types of particulate matter may vary. In this retrospective analysis, we employ a novel robust approach to assess the crucial time windows regarding the prevalence of GDM and to distinguish the susceptibility of three GDM subtypes to air pollution exposure. This study included 16,303 pregnant women who received routine antenatal care in 2018-2021 at the Maternal and Child Health Hospital in Chongqing, China. In total, 2482 women (15.2%) were diagnosed with GDM. We assessed the individual daily average exposure to air pollution, including PM2.5, PM10, O3, NO2, SO2, and CO based on the volunteers' addresses. We used high-accuracy gridded air pollution data generated by machine learning models to assess particulate matter per maternal exposure levels. We further analyzed the association of pre-pregnancy, early, and mid-pregnancy exposure to environmental pollutants using a generalized additive model (GAM) and distributed lag nonlinear models (DLNMs) to analyze the association between exposure at specific gestational weeks and the risk of GDM. We observed that, during the first trimester, per IQR increases for PM10 and PM2.5 exposure were associated with increased GDM risk (PM10: OR = 1.19, 95%CI: 1.07~1.33; PM2.5: OR = 1.32, 95%CI: 1.15~1.50) and isolated post-load hyperglycemia (GDM-IPH) risk (PM10: OR = 1.23, 95%CI: 1.09~1.39; PM2.5: OR = 1.38, 95%CI: 1.18~1.61). Second-trimester O3 exposure was positively correlated with the associated risk of GDM, while pre-pregnancy and first-trimester exposure was negatively associated with the risk of GDM-IPH. Exposure to SO2 in the second trimester was negatively associated with the risk of GDM-IPH. However, there were no observed associations between NO2 and CO exposure and the risk of GDM and its subgroups. Our results suggest that maternal exposure to particulate matter during early pregnancy and exposure to O3 in the second trimester might increase the risk of GDM, and GDM-IPH is the susceptible GDM subtype to airborne particulate matter exposure.

Project description:PurposeThe association between atmospheric particulate matter and emergency room visits for cerebrovascular disease were evaluated in Beijing.MethodsA generalized additive model was used to evaluate the associations between particulate matter and cerebrovascular disease, based on the daily data of meteorological elements, PM concentrations, and emergency room (ER) visits for cerebrovascular disease in Beijing from 2009 to 2012. Long-term trends and the effects of holidays, the day of the week, and confounding factors were controlled to determine the lag effect at 0-6 days. Single- and double-pollutant models were employed for different age and sex groups.ResultsThe effect of PM2.5 concentration on the number of daily ER visits for cerebrovascular disease was much stronger than that of PM10 concentration. PM2.5 and PM10 had maximum RR values of 1.096 and 1.054 at lag 6 for patients aged 61-75 years. For each inter-quartile range (IQR) increase in PM10 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.024, 1.044, 1.043, 1.038, 1.054, and 1.032, respectively. For each IQR increase in PM2.5 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.038, 1.064, 1.076, 1.054, 1.096, and 1.049, respectively. The RR values of the double-pollutant models were lower than those of the single-pollutant models.ConclusionThis study showed that the effects of PM pollution on cerebrovascular disease were different among different gender and age groups, and aged 61-75 years were mostly sensitive to particulate matters. The effects of PM2.5 on cerebrovascular disease were stronger than those of PM10. Our results can provide scientific evidence for the local government to take effective measures to improve air quality and the health of residents.Supplementary informationThe online version contains supplementary material available at 10.1007/s40201-021-00776-w.

Project description:Exposures to ambient particulate matter (PM) are associated with increased morbidity and mortality. PM2.5 (<2.5 μm) and ozone exposures have been shown to associate with carotid intima media thickness in humans. Animal studies support a causal relationship between air pollution and atherosclerosis and identified adverse PM effects on HDL functionality. We aimed to determine whether brief exposures to PM2.5 and/or ozone could induce effects on HDL anti-oxidant and anti-inflammatory capacity in humans.Subjects were exposed to fine concentrated ambient fine particles (CAP) with PM2.5 targeted at 150 μg/m(3), ozone targeted at 240 μg/m(3) (120 ppb), PM2.5 plus ozone targeted at similar concentrations, and filtered air (FA) for 2 h, on 4 different occasions, at least two weeks apart, in a randomized, crossover study. Blood was obtained before exposures (baseline), 1 h after and 20 h after exposures. Plasma HDL anti-oxidant/anti-inflammatory capacity and paraoxonase activity were determined. HDL anti-oxidant/anti-inflammatory capacity was assessed by a cell-free fluorescent assay and expressed in units of a HDL oxidant index (HOI). Changes in HOI (ΔHOI) were calculated as the difference in HOI from baseline to 1 h after or 20 h after exposures.There was a trend towards bigger ΔHOI between PM2.5 and FA 1 h after exposures (p = 0.18) but not 20 h after. This trend became significant (p <0.05) when baseline HOI was lower (<1.5 or <2.0), indicating decreased HDL anti-oxidant/anti-inflammatory capacity shortly after the exposures. There were no significant effects of ozone alone or in combination with PM2.5 on the change in HOI at both time points. The change in HOI due to PM2.5 showed a positive trend with particle mass concentration (p = 0.078) and significantly associated with the slope of systolic blood pressure during exposures (p = 0.005).Brief exposures to concentrated PM2.5 elicited swift effects on HDL anti-oxidant/anti-inflammatory functionality, which could indicate a potential mechanism for how particulate air pollution induces harmful cardiovascular effects.

Dataset Information

Association of Atmospheric Particulate Matter and Ozone with Gestational Diabetes Mellitus.

Publications

Association of Atmospheric Particulate Matter and Ozone with Gestational Diabetes Mellitus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets