Ambient Air Pollution and Hospitalizations for Ischemic Stroke: A Time Series Analysis Using a Distributed Lag Nonlinear Model in Chongqing, China
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ABSTRACT:
SUBMITTER: Chen H
PROVIDER: S-EPMC8804166 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We introduce spatial (DLfuse) and spatiotemporal (DLfuseST) distributed lag data fusion methods for predicting point-level ambient air pollution concentrations, using, as input, gridded average pollution estimates from a deterministic numerical air quality model. The methods incorporate predictive information from grid cells surrounding the prediction location of interest and are shown to collapse to existing downscaling approaches when this information adds no benefit. The spatial lagged parameters are allowed to vary spatially/spatiotemporally to accommodate the setting where surrounding geographic information is useful in one area/time but not in another. We apply the new methods to predict ambient concentrations of eight-hour maximum ozone and 24-hour average PM2.5 at unobserved spatial locations and times, and compare the predictions with those from several state-of-the-art data fusion approaches. Results show that DLfuse and DLfuseST often provide improved model fit and predictive accuracy when the lagged information is shown to be beneficial. Code to apply the methods is available in the R package DLfuse.
| S-EPMC8189329 | biostudies-literature
Project description:BACKGROUND:Stroke, especially ischemic stroke (IS), has been a severe public health problem around the world. However, the association between air pollution and ischemic stroke remains ambiguous. METHODS:A total of 63, 997 IS cases aged 18?years or above in Shenzhen were collected from 2008 to 2014. We used the time-stratified case-crossover design combining with distributed lag nonlinear model (DLNM) to estimate the association between air pollution and IS onset. Furthermore, this study explored the variability across gender and age groups. RESULTS:The cumulative exposure-response curves were J-shaped for SO2, NO2 and PM10, and V-shaped for O3, and crossed over the relative risk (RR) of one. The 99th, 50th (median) and 1st percentiles of concentration (?g/m3) respectively were 37.86, 10.06, 3.71 for SO2, 116.26, 41.29, 18.51 for NO2, 145.94, 48.29, 16.14 for PM10, and 111.57, 49.82, 16.00 for O3. Extreme high-SO2, high-NO2, high-PM10, high-O3, and low-O3 concentration increased the risk of IS, with the maximum RR values and 95% CIs: 1.50(1.22, 1.84) (99th vs median) at 0-12 lag days, 1.37(1.13, 1.67) (99th vs median) at 0-10 lag days, 1.26(1.04, 1.53) (99th vs median) at 0-12 lag days, 1.25(1.04, 1.49) (99th vs median) at 0-14 lag days, and 1.29(1.03, 1.61) (1st vs median) at 0-14 lag days, respectively. The statistically significant minimal RR value and 95% CI was 0.79(0.66,0.94) at 0-10 lag days for extreme low-PM10. The elderly aged over 65?years were susceptible to extreme pollution conditions. Difference from the vulnerability of males to extreme high-SO2, high-NO2 and low-O3, females were vulnerable to extreme high-PM10 and high-O3. Comparing with the elderly, adults aged 18-64?year were immune to extreme low-NO2 and low-PM10. However, no association between CO and IS onset was found. CONCLUSIONS:SO2, NO2, PM10 and O3 exerted non-linear and delayed influence on IS, and such influence varied with gender and age. These findings may have significant public health implications for the prevention of IS.
| S-EPMC6941275 | biostudies-literature
Project description:BACKGROUND:Evidence of the short-term effects of ambient air pollution on the risk of ischemic stroke in low- and middle-income countries is limited and inconsistent. We aimed to examine the associations between air pollution and daily hospital admissions for ischemic stroke in China. METHODS AND FINDINGS:We identified hospital admissions for ischemic stroke in 2014-2016 from the national database covering up to 0.28 billion people who received Urban Employee Basic Medical Insurance (UEBMI) in China. We examined the associations between air pollution and daily ischemic stroke admission using a two-stage method. Poisson time-series regression models were firstly fitted to estimate the effects of air pollution in each city. Random-effects meta-analyses were then conducted to combine the estimates. Meta-regression models were applied to explore potential effect modifiers. More than 2 million hospital admissions for ischemic stroke were identified in 172 cities in China. In single-pollutant models, increases of 10 ?g/m3 in particulate matter with aerodynamic diameter <2.5 ?m (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) and 1 mg/m3 in carbon monoxide (CO) concentrations were associated with 0.34% (95% confidence interval [CI], 0.20%-0.48%), 1.37% (1.05%-1.70%), 1.82% (1.45%-2.19%), 0.01% (-0.14%-0.16%), and 3.24% (2.05%-4.43%) increases in hospital admissions for ischemic stroke on the same day, respectively. SO2 and NO2 associations remained significant in two-pollutant models, but not PM2.5 and CO associations. The effect estimates were greater in cities with lower air pollutant levels and higher air temperatures, as well as in elderly subgroups. The main limitation of the present study was the unavailability of data on individual exposure to ambient air pollution. CONCLUSIONS:As the first national study in China to systematically examine the associations between short-term exposure to ambient air pollution and ischemic stroke, our findings indicate that transient increase in air pollution levels may increase the risk of ischemic stroke, which may have significant public health implications for the reduction of ischemic stroke burden in China.
| S-EPMC6171821 | biostudies-literature
Project description:An emerging body of evidence suggests that ambient levels of air pollution during pregnancy are associated with preterm birth.To further investigate these relationships we used vital record data to construct a retrospective cohort of 476,489 births occurring between 1994 and 2004 in 5 central counties of metropolitan Atlanta. Using a time-series approach, we examined aggregated daily counts of preterm birth in relation to ambient levels of carbon monoxide, nitrogen dioxide, sulfur dioxide, ozone, particulate matter <10 microm in diameter (PM10), particulate matter <2.5 microm in diameter (PM2.5), and speciated PM measurements. Daily pollutant levels in 5-county Atlanta were characterized using a population-weighted spatial average of air quality monitors in the study area. We also examined ambient concentrations at individual monitors in analyses limited to mothers with residential geocodes within 4 miles of each monitor. Relationships between average pollution levels during 3 gestational windows of interest were modeled using Poisson generalized linear models. Results were adjusted for seasonal and long-term time trends.Although most results were null, there were 3 positive associations between ambient pollution levels and preterm birth in the 4-mile capture-area analyses. Daily preterm birth rates were associated with average NO2 concentrations in the preceding 6 weeks and with average PM2.5 sulfate and PM2.5 water-soluble metal concentrations in the preceding week.Results provide limited support for late-pregnancy effects of ambient air pollution on preterm birth.
| S-EPMC3780365 | biostudies-literature
Project description:The link between daily changes in level of ambient fine particulate matter (PM) air pollution (PM <2.5 ?m in diameter [PM(2.5)]) and cardiovascular morbidity and mortality is well established. Whether PM(2.5) levels below current US National Ambient Air Quality Standards also increase the risk of ischemic stroke remains uncertain.We reviewed the medical records of 1705 Boston area patients hospitalized with neurologist-confirmed ischemic stroke and abstracted data on the time of symptom onset and clinical characteristics. The PM(2.5) concentrations were measured at a central monitoring station. We used the time-stratified case-crossover study design to assess the association between the risk of ischemic stroke onset and PM(2.5) levels in the hours and days preceding each event. We examined whether the association with PM(2.5) levels differed by presumed ischemic stroke pathophysiologic mechanism and patient characteristics.The estimated odds ratio (OR) of ischemic stroke onset was 1.34 (95% CI, 1.13-1.58) (P < .001) following a 24-hour period classified as moderate (PM(2.5) 15-40 ?g/m(3)) by the US Environmental Protection Agency's (EPA) Air Quality Index compared with a 24-hour period classified as good (?15 ?g/m(3)). Considering PM(2.5) levels as a continuous variable, we found the estimated odds ratio of ischemic stroke onset to be 1.11 (95% CI, 1.03-1.20) (P = .006) per interquartile range increase in PM(2.5) levels (6.4 ?g/m(3)). The increase in risk was greatest within 12 to 14 hours of exposure to PM(2.5) and was most strongly associated with markers of traffic-related pollution.These results suggest that exposure to PM(2.5) levels considered generally safe by the US EPA increase the risk of ischemic stroke onset within hours of exposure.
| S-EPMC3639313 | biostudies-literature
Project description:Although there have been enormous demands and efforts to develop an early warning system for malaria, no sustainable system has remained. Well-organized malaria surveillance and high-quality climate forecasts are required to sustain a malaria early warning system in conjunction with an effective malaria prediction model. We aimed to develop a weather-based malaria prediction model using a weekly time-series data including temperature, precipitation, and malaria cases from 1998 to 2015 in Vhembe, Limpopo, South Africa and apply it to seasonal climate forecasts. The malaria prediction model performed well for short-term predictions (correlation coefficient, r?>?0.8 for 1- and 2-week ahead forecasts). The prediction accuracy decreased as the lead time increased but retained fairly good performance (r?>?0.7) up to the 16-week ahead prediction. The demonstration of the malaria prediction process based on the seasonal climate forecasts showed the short-term predictions coincided closely with the observed malaria cases. The weather-based malaria prediction model we developed could be applicable in practice together with skillful seasonal climate forecasts and existing malaria surveillance data. Establishing an automated operating system based on real-time data inputs will be beneficial for the malaria early warning system, and can be an instructive example for other malaria-endemic areas.
| S-EPMC6884483 | biostudies-literature
Project description:To investigate the association between short-term changes in ambient pollution (particulate matter <2.5 ?m in aerodynamic diameter (PM2.5) and ozone (O3)) and the risk of ischemic stroke among individuals living in a bi-ethnic community and whether this association is modified by ethnicity.We identified incident ischemic stroke cases from the population-based Brain Attack Surveillance in Corpus Christi (BASIC) project between 2000 and 2012. Associations between PM2.5 (mean 24-h) and O3 (maximal 8-h) levels, measured on the same-day and lags of 1-3 days, and odds of ischemic stroke were assessed using a time-stratified case-crossover design and modeled using conditional logistic regression. We explored race/ethnicity (Mexican American versus non-Hispanic white) as a modifier by including interaction terms in the models.There were 2948 ischemic strokes with median age 71 years (IQR: 59-80). We observed no overall associations between the air pollutants and odds of ischemic stroke at any lag. When stratified by ethnicity, higher O3 was consistently associated with greater odds of ischemic stroke for non-Hispanic whites, but not for Mexican Americans. Higher PM2.5 was generally associated with lower odds of ischemic stroke for non-Hispanic whites but modestly greater odds for Mexican Americans.Ethnic differences in the associations between ischemic stroke and short-term exposures to O3 and PM2.5 were suggested indicating that further study in diverse populations may be warranted.
| S-EPMC4641766 | biostudies-literature
Project description:Distributed lag models have been used to identify critical pregnancy periods of exposure (i.e. critical exposure windows) to air pollution in studies of pregnancy outcomes. However, much of the previous work in this area has ignored the possibility of spatial variability in the lagged health effect parameters that may result from exposure characteristics and/or residual confounding. We develop a spatially varying Gaussian process model for critical windows called 'SpGPCW' and use it to investigate geographic variability in the association between term low birth weight and average weekly concentrations of ozone and PM2:5 during pregnancy by using birth records from North Carolina. SpGPCW is designed to accommodate areal level spatial correlation between lagged health effect parameters and temporal smoothness in risk estimation across pregnancy. Through simulation and a real data application, we show that the consequences of ignoring spatial variability in the lagged health effect parameters include less reliable inference for the parameters and diminished ability to identify true critical window sets, and we investigate the use of existing Bayesian model comparison techniques as tools for determining the presence of spatial variability. We find that exposure to PM2:5 is associated with elevated term low birth weight risk in selected weeks and counties and that ignoring spatial variability results in null associations during these periods. An R package (SpGPCW) has been developed to implement the new method.
| S-EPMC7319179 | biostudies-literature
Project description:Prolonged exposures can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant. Summary measures such as cumulative exposure or average intensity of exposure may not fully capture these relationships. We applied penalized and unpenalized distributed-lag nonlinear models (DLNMs) with flexible exposure-response and lag-response functions in order to examine the association between crystalline silica exposure and mortality from lung cancer and nonmalignant respiratory disease in a cohort study of 2,342 California diatomaceous earth workers followed during 1942-2011. We also assessed associations using simple measures of cumulative exposure assuming linear exposure-response and constant lag-response. Measures of association from DLNMs were generally higher than those from simpler models. Rate ratios from penalized DLNMs corresponding to average daily exposures of 0.4 mg/m3 during lag years 31-50 prior to the age of observed cases were 1.47 (95% confidence interval (CI): 0.92, 2.35) for lung cancer mortality and 1.80 (95% CI: 1.14, 2.85) for nonmalignant respiratory disease mortality. Rate ratios from the simpler models for the same exposure scenario were 1.15 (95% CI: 0.89, 1.48) and 1.23 (95% CI: 1.03, 1.46), respectively. Longitudinal cohort studies of prolonged exposures and chronic health outcomes should explore methods allowing for flexibility and nonlinearities in the exposure-lag-response.
| S-EPMC6030974 | biostudies-literature
Project description:BACKGROUND:Ambient air pollution is associated with systemic increases in oxidative stress, to which sperm are particularly sensitive. Although decrements in semen quality represent a key mechanism for impaired fecundability, prior research has not established a clear association between air pollution and semen quality. To address this, we evaluated the association between ambient air pollution and semen quality among men with moderate air pollution exposure. METHODS:Of 501 couples in the LIFE study, 467 male partners provided one or more semen samples. Average residential exposure to criteria air pollutants and fine particle constituents in the 72?days before ejaculation was estimated using modified Community Multiscale Air Quality models. Generalized estimating equation models estimated the association between air pollutants and semen quality parameters (volume, count, percent hypo-osmotic swollen, motility, sperm head, morphology and sperm chromatin parameters). Models adjusted for age, body mass index, smoking and season. RESULTS:Most associations between air pollutants and semen parameters were small. However, associations were observed for an interquartile increase in fine particulates ?2.5?µm and decreased sperm head size, including -0.22 (95% CI -0.34, -0.11) µm2 for area, -0.06 (95% CI -0.09, -0.03) µm for length and -0.09 (95% CI -0.19, -0.06) µm for perimeter. Fine particulates were also associated with 1.03 (95% CI 0.40, 1.66) greater percent sperm head with acrosome. CONCLUSIONS:Air pollution exposure was not associated with semen quality, except for sperm head parameters. Moderate levels of ambient air pollution may not be a major contributor to semen quality.
| S-EPMC5878741 | biostudies-literature