Dataset Information

STROBE-Long-Term Exposure to Ambient Fine Particulate Air Pollution and Hospitalization Due to Peptic Ulcers.

ABSTRACT: Little is known about the effect of air pollution on the gastrointestinal (GI) system. We investigated the association between long-term exposures to outdoor fine particles (PM2.5) and hospitalization for peptic ulcer diseases (PUDs) in a large cohort of Hong Kong Chinese elderly.A total of 66,820 subjects aged ?65 years who were enrolled in all 18 Government Elderly Health Service centers of Hong Kong participated in the study voluntarily between 1998 and 2001. They were prospectively followed up for more than 10 years. Annual mean exposures to PM2.5 at residence of individuals were estimated by satellite data through linkage with address details including floor level. All hospital admission records of the subjects up to December 31, 2010 were retrieved from the central database of Hospital Authority. We used Cox regression to estimate the hazard ratio (HR) for PUD hospitalization associated with PM2.5 exposure after adjustment for individual and ecological covariates.A total of 60,273 subjects had completed baseline information including medical, socio-demographic, lifestyle, and anthropometric data at recruitment. During the follow-up period, 1991 (3.3%) subjects had been hospitalized for PUD. The adjusted HR for PUD hospitalization per 10??g/m of PM2.5 was 1.18 (95% confidence interval: 1.02-1.36, P?=?0.02). Further analysis showed that the associations with PM2.5 were significant for gastric ulcers (HR 1.29; 1.09-1.53, P?=?0.003) but not for duodenal ulcers (HR 0.98; 0.78 to 1.22, P?=?0.81).Long-term exposures to PM2.5 were associated with PUD hospitalization in elder population. The mechanism underlying the PM2.5 in the development of gastric ulcers warrants further research.

SUBMITTER: Wong CM

PROVIDER: S-EPMC4863781 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

STROBE-Long-Term Exposure to Ambient Fine Particulate Air Pollution and Hospitalization Due to Peptic Ulcers.

Wong Chit-Ming CM Tsang Hilda H Lai Hak-Kan HK Thach Thuan-Quoc TQ Thomas G Neil GN Chan King-Pan KP Lee Siu-Yin SY Ayres Jon G JG Lam Tai-Hing TH Leung Wai K WK

Medicine 20160501 18

Little is known about the effect of air pollution on the gastrointestinal (GI) system. We investigated the association between long-term exposures to outdoor fine particles (PM2.5) and hospitalization for peptic ulcer diseases (PUDs) in a large cohort of Hong Kong Chinese elderly.A total of 66,820 subjects aged ≥65 years who were enrolled in all 18 Government Elderly Health Service centers of Hong Kong participated in the study voluntarily between 1998 and 2001. They were prospectively followed ...[more]

PMID: 27149464

Similar Datasets

Project description:BackgroundEcologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking.MethodsWe leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM2.5 with risk of hospitalization.ResultsThere were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%-12%) increase in risk of hospitalization. The association of PM2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure-response suggested increased risk at PM2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001).ConclusionsExposure to higher levels of PM2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM2.5 on risk of hospitalization in the setting of COVID-19.

Project description:Ambient particulate matter (PM) has been associated with mortality and morbidity for cardiovascular disease. MicroRNAs control gene expression at a posttranscriptional level. Altered microRNA expression has been reported in processes related to cardiovascular disease and PM exposure, such as systemic inflammation, endothelial dysfunction, and atherosclerosis. Polymorphisms in microRNA-related genes could influence response to PM.We investigated the association of exposure to ambient particles in several time windows (4-hour to 28-day moving averages) and blood leukocyte expression changes in 14 candidate microRNAs in 153 elderly males from the Normative Aging Study (examined 2005-2009). Potential effect modification by six single nucleotide polymorphisms (SNPs) in three microRNA-related genes was investigated. Fine PM (PM2.5), black carbon, organic carbon, and sulfates were measured at a stationary ambient monitoring site. Linear regression models, adjusted for potential confounders, were used to assess effects of particles and SNP-by-pollutant interaction. An in silico pathway analysis was performed on target genes of microRNAs associated with the pollutants.We found a negative association for pollutants in all moving averages and miR-1, -126, -135a, -146a, -155, -21, -222, and -9. The strongest associations were observed with the 7-day moving averages for PM2.5 and black carbon and with the 48-hour moving averages for organic carbon. The association with sulfates was stable across the moving averages. The in silico pathway analysis identified 18 pathways related to immune response shared by at least two microRNAs; in particular, the "high-mobility group protein B1/advanced glycosylation end product-specific receptor signaling pathway" was shared by miR-126, -146a, -155, -21, and -222. No important associations were observed for miR-125a-5p, -125b, -128, -147, -218, and -96. We found significant SNP-by-pollutant interactions for rs7813, rs910925, and rs1062923 in GEMIN4 and black carbon and PM2.5 for miR-1, -126, -146a, -222, and -9, and for rs1640299 in DGCR8 and SO4 for miR-1 and -135a.Exposure to ambient particles could cause a downregulation of microRNAs involved in processes related to PM exposure. Polymorphisms in GEMIN4 and DGCR8 could modify these associations.

Project description:ObjectiveTo quantitate the 2016 global and national burden of chronic kidney disease (CKD) attributable to ambient fine particulate matter air pollution ≤ 2.5 μm in aerodynamic diameter (PM2.5).DesignWe used the Global Burden of Disease (GBD) study data and methodologies to estimate the 2016 burden of CKD attributable to PM2.5 in 194 countries and territories. Population-weighted PM2.5 levels and incident rates of CKD for each country were curated from the GBD study publicly available data sources.SettingGBD global and national data on PM2.5 and CKD.Participants194 countries and territories.Main outcome measuresWe estimated the attributable burden of disease (ABD), years living with disability (YLD), years of life lost (YLL) and disability-adjusted life-years (DALYs).ResultsThe 2016 global burden of incident CKD attributable to PM2.5 was 6 950 514 (95% uncertainty interval: 5 061 533-8 914 745). Global YLD, YLL and DALYs of CKD attributable to PM2.5 were 2 849 311 (1 875 219-3 983 941), 8 587 735 (6 355 784-10 772 239) and 11 445 397 (8 380 246-14 554 091), respectively. Age-standardised ABD, YLL, YLD and DALY rates varied substantially among geographies. Populations in Mesoamerica, Northern Africa, several countries in the Eastern Mediterranean region, Afghanistan, Pakistan, India and several countries in Southeast Asia were among those with highest age-standardised DALY rates. For example, age-standardised DALYs per 100 000 were 543.35 (391.16-707.96) in El Salvador, 455.29 (332.51-577.97) in Mexico, 408.41 (283.82-551.84) in Guatemala, 238.25 (173.90-303.98) in India and 178.26 (125.31-238.47) in Sri Lanka, compared with 5.52 (0.82-11.48) in Sweden, 6.46 (0.00-14.49) in Australia and 12.13 (4.95-21.82) in Canada. Frontier analyses showed that Mesoamerican countries had significantly higher CKD DALY rates relative to other countries with comparable sociodemographic development.ConclusionsOur results demonstrate that the global toll of CKD attributable to ambient air pollution is significant and identify several endemic geographies where air pollution may be a significant driver of CKD burden. Air pollution may need to be considered in the discussion of the global epidemiology of CKD.

Project description:BackgroundThe systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias.MethodsWe evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 ?m or less (PM10) and fine PM with an aerodynamic diameter of 2.5 ?m or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived.ResultsOn average, an increase of 10 ?g per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations.ConclusionsOur data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).

Project description:BackgroundAmbient 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 PM2.5, which could trigger acute onset of cardiorespiratory diseases within a few days.MethodsDaily 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 (PM2.5) 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.FindingsBased 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 PM2.5 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).InterpretationOur results support that short-term exposure to ambient PM2.5 pollution could lead to significant health and economic impacts in China. Reducing levels of ambient PM2.5 can avoid substantial health damage and expenditures, and generate appreciable economic benefits from decreasing absence from work.FundingNatural Science Foundation of China (82073509, 71903010, 71903011), and the National Key Research and Development Program of China (2017YFC0211600, 2017YFC0211601).

Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Dataset Information

STROBE-Long-Term Exposure to Ambient Fine Particulate Air Pollution and Hospitalization Due to Peptic Ulcers.

Publications

STROBE-Long-Term Exposure to Ambient Fine Particulate Air Pollution and Hospitalization Due to Peptic Ulcers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets