Intensive care admissions and outcomes associated with short-term exposure to ambient air pollution: a time series analysis

Groves, C; Butland, B. K.; Atkinson, Richard; Delaney, Anthony; Pilcher, David

doi:10.1007/s00134-020-06052-z

Cited by 11 publications

(11 citation statements)

References 33 publications

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“…Numerous studies have shown that short-term exposure to ambient PM 2.5 within a few days could trigger acute onset of cardiorespiratory diseases including lower respiratory infections (LRI), coronary heart disease (CHD), and stroke [18][19][20] , which are among the major cardiorespiratory diseases responsible for population disease burden 2 . Several previous studies also show that short-term exposure to PM 2.5 could lead to more intensive care admissions and more hospital admissions of cardiorespiratory diseases [21][22][23] . Therefore, short-term exposure to ambient PM 2.5 has important adverse health effects in addition to that of long-term exposure to ambient PM 2.5 .…”

Section: Introductionmentioning

confidence: 82%

Short-Term Ambient Particulate Air Pollution and Hospitalization Expenditures of Cause-Specific Cardiorespiratory Diseases in China: A Multicity Analysis

Xie

Zhong

et al. 2021

The Lancet Regional Health - Western Pacific

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Background: Ambient air pollution is leading risk factor for health burden in China. Few studies in China have investigated the economic loss related to short-term exposure to ambient PM 2.5 , which could trigger acute onset of cardiorespiratory diseases within a few days.Methods: Daily ambient air pollutants data are obtained for each city from the National Air Quality Monitoring System and daily hospitalization data are obtained from the urban employee-based basic medical insurance scheme database in 74 Chinese cities with an average coverage of 88.5 million urban employees during 2016-2017. A three-stage time-series analytic approach is used in this study to investigate the impact of short-term exposure to ambient fine particulate (PM 2.5 ) air pollution on hospital admissions, expenses and hospital stays of three cause-specific cardiorespiratory diseases, including lower respiratory infections (LRI), coronary heart disease (CHD) and stroke in the included cities. Findings:Based on the time-series analysis using daily hospitalization data, 28,560 LRI cases, 54,600 CHD cases, and 23,989 stroke cases are attributable to ambient PM 2.5 in the 74 cities during the study period, and the related attributable expenses are 220 million CNY (US$ 32.9 million) for LRI, 458 million CNY (US$ 68.5 million) for CHD, and 410 million CNY (US$ 65.8 million) for stroke, respectively. These attributable numbers account for 1.45% to 2.05% of total hospital admissions and 1.10% to 1.51% of total expenses for the three diseases during 2016-2017, respectively. The attributable numbers for the three cause-specific cardiorespiratory diseases would increase to 362,007 hospital admission cases and 3.68 billion CNY expenses ($US550 million) in the entire urban employee population (299 million) in China during 2016-2017, and the related direct economic loss of absence from work would be 798 million CNY (US$ 119.3 million).

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Section: Introductionmentioning

confidence: 82%

Short-Term Ambient Particulate Air Pollution and Hospitalization Expenditures of Cause-Specific Cardiorespiratory Diseases in China: A Multicity Analysis

Xie

Zhong

et al. 2021

The Lancet Regional Health - Western Pacific

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“…Particular matters (PM), especially PM 2.5 and PM 10 , have been proved as the most significantly and consistently harmful components (Nwaichi et al 2020). A research with 46,965 patients in 87 separate ICUs in Australia demonstrated that a significantly positive relationship was found between ICU admissions with 30-day mortality and short-term exposure to PM 2.5 , while RR was 1.18 (95% CI 1.02-1.37) with per 10 μg/m3 increase in PM 2.5 (Groves et al 2020). In Los Angeles, another study ascertained that temporal changes in the risk of cardiovascular and asthma ED admissions occurred due to short-term increases in ambient PM 2.5 levels, which was partly similar with our results (Bi et al 2020).…”

Section: Discussionmentioning

confidence: 99%

Air pollution and hospital admissions for critical illness in emergency department: a tertiary-center research in Changsha, China, 2016–2020

Lin

Long

et al. 2021

Environ Sci Pollut Res

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We aimed to comprehensively investigate the associations of air pollutants with hospital admissions for critical illness in ED. Patients with critical illness including level 1 and level 2 of the Emergency Severity Index admitted in ED of Changsha Central Hospital from January 2016 to December 2020 were enrolled. Meteorological and air pollutants data source were collected from the National Meteorological Science Data Center. A Poisson generalized linear regression combined with a polynomial distributed lag model (PDLM) was utilized to explore the effect of air pollution on hospital admissions for critical illness in ED. Benchmarks as references (25th) were conducted for comparisons with high levels of pollutant concentrations (75th). At first, lagged effects of all different air pollutants were analyzed. Then, based on the most significant factor, analyses in subgroups were performed by gender (male and female), age (< 45, 45-65, and > 65), disorders (cardiovascular, neurological, respiratory), and seasons (spring, summer, autumn, and winter). A total of 47,290 patients with critical illness admitted in ED were included. The effects of air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , O 3 and CO) on critical illness ED visits were statistically significant. Strong collinearity between PM 2.5 and PM 10 (r = 0.862) was found. Both single-day lag and cumulative-day lag day models showed that PM 2.5 had the strongest effects (lag 0, RR = 1.025, 95% CI 1.008-1.043, and lag 0-14, RR = 1.067, 95% CI 1.017-1.120, respectively). In both PM 2.5 and PM 10 , the risks of critical illness in male, > 65 ages, respiratory diseases, and winter increased the most significant. Air pollutants, especially PM 2.5 and PM 10 exposure, could increase the risk of critical illness admission.

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“…On the other hand, the study period was from 2000 to 2012 in their study, and we observed the data in recent years. A recent study stated that point estimates for PM 2.5 and ICU admission were positive, suggesting a potential association exists, but they failed to observed it as statistically significant [ 6 ]. We observed all sepsis patients throughout the hospital, besides the ICU, with a larger sample size (58,064 sepsis cases versus 10,725 sepsis ICU cases [ 6 ]).…”

Section: Discussionmentioning

confidence: 99%

“…A recent study stated that point estimates for PM 2.5 and ICU admission were positive, suggesting a potential association exists, but they failed to observed it as statistically significant [ 6 ]. We observed all sepsis patients throughout the hospital, besides the ICU, with a larger sample size (58,064 sepsis cases versus 10,725 sepsis ICU cases [ 6 ]). Another study with 444,928 patients of sepsis also reported that exposure to increased levels of O 3 was associated with higher risk of mortality in patients with sepsis [ 7 ], while PM 2.5 was not associated with sepsis which is similar with our results.…”

Section: Discussionmentioning

confidence: 99%

“…In 2017, 48 million cases of sepsis were recorded globally, including 11 million sepsis related deaths, accounting for 19.7% of all deaths worldwide [ 5 ]. A recent study conducted by Christopher, et al demonstrated that higher level of PM 2.5 may increase the intensive care unit (ICU) mortality in patients with sepsis [ 6 ]. They believed that larger studies are required to determine if the frequency of ICU admissions is positively associated with short-term exposure to air pollution.…”

Section: Introductionmentioning

confidence: 99%

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Sepsis-related hospital admissions and ambient air pollution: a time series analysis in 6 Chinese cities

et al. 2021

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Background Some prevalent but rarely studied causes of hospital admissions, such as sepsis is still unknown whether affected by air pollution. Methods We used time-series regression within generalized additive models to estimate the effect of air pollutant level on the sepsis-related hospital admissions, for the years 2017–18, using data from six cities in Sichuan, China. Potential effect modifications by age and sex were also explored. The effects of air pollutant on hospital stays for sepsis were also quantified. Results Positive associations between short-term exposure to NO2 and O3 and risk of sepsis-related hospital admissions and stays were found. Each 10 μg/m3 increase in short-term NO2 at lag 03 and O3 at lag 4 was associated with an increase of 2.76% (95% CI: 0.67, 4.84%) and 0.64% (95% CI: 0.14, 1.14%) hospital admissions, respectively. An increase of 0.72% (95% CI: 0.05, 1.40%) hospital stay was associated with 10 μg/m3 increase in O3 concentration at lag 4. Besides, the adverse effect of exposure to NO2 was more significant in males and population aged less than 14 years; while more significant in females and population aged 14 ~ 65 and over 65 years for exposure to O3. These associations remained stable after the adjustment of other air pollutants.8. Conclusion Exposure to ambient NO2 and O3 may cause substantial sepsis hospitalizations, and hospital stays in Sichuan, China. These associations were different in subgroup by age and sex.

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Intensive care admissions and outcomes associated with short-term exposure to ambient air pollution: a time series analysis

Cited by 11 publications

References 33 publications

Short-Term Ambient Particulate Air Pollution and Hospitalization Expenditures of Cause-Specific Cardiorespiratory Diseases in China: A Multicity Analysis

Short-Term Ambient Particulate Air Pollution and Hospitalization Expenditures of Cause-Specific Cardiorespiratory Diseases in China: A Multicity Analysis

Air pollution and hospital admissions for critical illness in emergency department: a tertiary-center research in Changsha, China, 2016–2020

Sepsis-related hospital admissions and ambient air pollution: a time series analysis in 6 Chinese cities

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