Excess mortality associated with high ozone exposure: A national cohort study in China

Yang, Yuan; Wang, Kai; Sun, Zhe; Zhan, Yu; Yang, Zhiming; Hu, Kejia; Zhang, Yunquan

doi:10.1016/j.ese.2023.100241

Cited by 17 publications

(10 citation statements)

References 49 publications

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“…However, this meta-analysis used large-scale O 3 exposure health risk studies up to 2022, which did not cover Asian, African, or Latin American regions. The latest finding based on another Chinese cohort identified an HR of 1.18 (95% CI: 1.13, 1.23) per 10 μg/m 3 increase of O 3 and all-cause mortality . Their population had a mean age of 57.7 (SD: 10.4), while our study population was aged 80 on average.…”

Section: Discussionmentioning

confidence: 54%

“…The latest finding based on another Chinese cohort identified an HR of 1.18 (95% CI: 1.13, 1.23) per 10 μg/m 3 increase of O 3 and all-cause mortality. 29 Their population had a mean age of 57.7 (SD: 10.4), while our study population was aged 80 on average. The different sources and resolution of O 3 exposure could be other reasons for the contradictory findings.…”

Section: Discussionmentioning

confidence: 81%

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Real-World Evidence of Multiple Air Pollutants and Mortality: A Prospective Cohort Study in an Oldest-Old Population

Liu,

Zeng,

2023

Environ. Health

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We aimed to report real-world longitudinal ambient air pollutants levels compared to WHO Air Quality Guidelines (AQG) and analyze multiple air pollutants' joint effect on longevity, and the modification and confounding from the climate and urbanization with a focus on the oldest-old. This study included 13,207 old participants with 73.3% aged 80 and beyond, followed up from 2008 to 2018 in 23 Chinese provinces. We used the Cox-proportional hazards model and quantile-based gcomputation model to measure separate and joint effects of the multiple pollutants. We adjusted for climate and area economic factors based on a directed acyclic graph. In 2018, no participants met the WHO AQG for PM 2.5 and O 3 , and about one-third met the AQG for NO 2 . The hazard ratio (HR) for mortality was 1.07 (95% confidence interval-CI: 1.05, 1.09) per decile increase in all three pollutants, with PM 2.5 being the dominant contributor according to the quantile-based g-computation model. In the three-pollutant model, the HRs (95% CI) for PM 2.5 and NO 2 were 1.27 (1.25, 1.3) and 1.08 (1.05, 1.12) per 10 μg/m 3 increase, respectively. The oldest-old experienced a much lower mortality risk from air pollution compared to the young-old. The mortality risk of PM 2.5 was higher in areas with higher annual average temperatures. The adjustment of road density considerably intensified the association between NO 2 and mortality. The ambient PM 2.5 and O 3 levels in China exceeded the WHO AQG target substantially. Multiple pollutants coexposure, confounding, and modification of the district economic and climate factors should not be ignored in the association between air pollution and mortality.

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Section: Discussionmentioning

confidence: 54%

Section: Discussionmentioning

confidence: 81%

Real-World Evidence of Multiple Air Pollutants and Mortality: A Prospective Cohort Study in an Oldest-Old Population

Liu,

Zeng,

2023

Environ. Health

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“…The machine learning models that are capable of handling complicated nonlinear interactions showed a decent performance in the cross-validation. Gridded datasets have been used for exposure assessments in previous studies [ 45 , 46 , 47 ]. Compared to the nearest-site matching method for exposure assessment, machine learning models provided more accurate air pollution data by fusing site observations with various environmental factors, such as land-use types and satellite retrieval [ 48 , 49 ].…”

Section: Discussionmentioning

confidence: 99%

The Influence of Airborne Particulate Matter on the Risk of Gestational Diabetes Mellitus: A Large Retrospective Study in Chongqing, China

Zeng,

Zhan,

Zhou

et al. 2023

Toxics

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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.

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“…This was presumable, as in previous studies higher concentrations (ppm) and longer durations (days to weeks) of ozone exposure were typically required to produce discernible changes. 10,13,52 However, studies have revealed that ozone of ambient concentration (around 110 μg/m 3 and above) was sufficient to pose health risks to humans, 53,54 yet no study has detected health impacts within such a 2 h exposure duration. Therefore, compared to traditional hematological assays, the detection of breath-borne gaseous biomarkers was proven to be a more rapid and sensitive approach to providing early warning of health impacts from air pollutants prior to health outcomes.…”

Section: Laboratory Controlled Ozone Exposure (Dose− Response Investi...mentioning

confidence: 99%

Real-Time Monitoring of Air Pollution Health Impacts Using Breath-Borne Gaseous Biomarkers from Rats

Zhu,

Yao

2024

Environ. Sci. Technol.

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Offline techniques are adopted for studying air pollution health impacts, thus failing to provide in situ observations. Here, we have demonstrated their real-time monitoring by online analyzing an array of gaseous biomarkers from rats' exhaled breath using an integrated exhaled breath array sensor (IEBAS) developed. The biomarkers include total volatile organic compounds (TVOC), CO 2 , CO, NO, H 2 S, H 2 O 2 , O 2 , and NH 3 . Specific breath-borne VOCs were also analyzed by a gas chromatography-ion mobility spectrometer (GC-IMS). After real-life ambient air pollution exposures (2 h), the pollution levels of PM 2.5 and O 3 were both found to significantly affect the relative levels of multiple gaseous biomarkers in rats' breath. Eleven biomarkers, especially NO, H 2 S, and 1-propanol, were detected as significantly correlated with PM 2.5 concentration, while heptanal was shown to be significantly correlated with O 3 . Likewise, significant changes were also detected in multiple breath-borne biomarkers from rats under labcontrolled O 3 exposures with levels of 150, 300, and 1000 μg/m 3 (2 h), compared to synthetic air exposure. Importantly, heptanal was experimentally confirmed as a reliable biomarker for O 3 exposure, with a notable dose−response relationship. In contrast, conventional biomarkers of inflammation and oxidative stress in rat sera exhibited insignificant differences after the 2 h exposures. The results imply that breath-borne gaseous biomarkers can serve as an early and sensitive indicator for ambient pollutant exposure. This work pioneered a new research paradigm for online monitoring of air pollution health impacts while obtaining important candidate biomarker information for PM 2.5 and O 3 exposures.

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Excess mortality associated with high ozone exposure: A national cohort study in China

Cited by 17 publications

References 49 publications

Real-World Evidence of Multiple Air Pollutants and Mortality: A Prospective Cohort Study in an Oldest-Old Population

Real-World Evidence of Multiple Air Pollutants and Mortality: A Prospective Cohort Study in an Oldest-Old Population

The Influence of Airborne Particulate Matter on the Risk of Gestational Diabetes Mellitus: A Large Retrospective Study in Chongqing, China

Real-Time Monitoring of Air Pollution Health Impacts Using Breath-Borne Gaseous Biomarkers from Rats

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