***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The effects of industrial air pollution on human health have not been as thoroughly investigated as those of urban air pollution which originates mostly from automotive transport . To better assess the health impacts of point sources of industrial air pollution , a r and omized crossover exposure study was conducted . Sixty one young and healthy volunteers were r and omly assigned to spend five consecutive eight-hour days near a steel mill or at a location five kilometres away . After a nine or sixteen-day washout period , volunteers spent another five consecutive days at the second site . Meteorological conditions and air pollutants were monitored at both exposure sites . On each exposure day , the first morning urine was collected along with a second urine sample obtained immediately before leaving the exposure site at the end of the day . Urinary levels of biomarkers of oxidative stress 8-hydroxy-2'-deoxyguanosine ( 8-OHdG , a biomarker of oxidative DNA damage ) , malondialdehyde ( MDA , a biomarker of lipid peroxidation ) , 8-isoprostane ( 8-IsoP , a bioactive metabolite result ing from the peroxidation of arachidonic acid ) and Vascular Endothelial Growth Factor ( VEGF , involved in response to oxidative stress ) were measured . According to mixed-effects linear regression models , intra-individual variations in 8-OHdG urinary levels were significantly associated with exposure site , but surprisingly , lower levels were observed at the steel mill site . Delayed , temporally-defined associations with specific air pollutants were observed for 8-OHdG , 8-IsoP and VEGF . However , these associations were subtle , presented complex patterns and their biological consequences remain unclear CONTEXT Associations have been found between day-to-day particulate air pollution and increased risk of various adverse health outcomes , including cardiopulmonary mortality . However , studies of health effects of long-term particulate air pollution have been less conclusive . OBJECTIVE To assess the relationship between long-term exposure to fine particulate air pollution and all-cause , lung cancer , and cardiopulmonary mortality . DESIGN , SETTING , AND PARTICIPANTS Vital status and cause of death data were collected by the American Cancer Society as part of the Cancer Prevention II study , an ongoing prospect i ve mortality study , which enrolled approximately 1.2 million adults in 1982 . Participants completed a question naire detailing individual risk factor data ( age , sex , race , weight , height , smoking history , education , marital status , diet , alcohol consumption , and occupational exposures ) .  The risk factor data for approximately 500 000 adults were linked with air pollution data for metropolitan areas throughout the United States and combined with vital status and cause of death data through December 31 , 1998 . MAIN OUTCOME MEASURE All-cause , lung cancer , and cardiopulmonary mortality . RESULTS Fine particulate and sulfur oxide -- related pollution were associated with all-cause , lung cancer , and cardiopulmonary mortality . Each 10-microg/m(3 ) elevation in fine particulate air pollution was associated with approximately a 4 % , 6 % , and 8 % increased risk of all-cause , cardiopulmonary , and lung cancer mortality , respectively . Measures of coarse particle fraction and total suspended particles were not consistently associated with mortality . CONCLUSION Long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality Abstract Context : Fine particulate matter ( PM ) air pollution has been associated with alterations in circulating endothelial progenitor cell ( EPC ) levels , which may be one mechanism whereby exposures promote cardiovascular diseases . However , the impact of coarse PM on EPCs is unknown . Objective : We aim ed to determine the effect of acute exposure to coarse concentrated ambient particles ( CAP ) on circulating EPC levels . Methods : Thirty-two adults ( 25.9 ± 6.6 years ) were exposed to coarse CAP ( 76.2 ± 51.5 μg m−3 ) in a rural location and filtered air ( FA )  for 2 h in a r and omized double-blind crossover study . Peripheral venous blood was collected 2 and 20 h post-exposures for circulating EPC ( n = 21 ) , white blood cell ( n = 24 ) and vascular endothelial growth factor ( VEGF ) ( n = 16–19 ) levels . The changes between exposures were compared by matched Wilcoxon signed-rank tests . Results : Circulating EPC levels were elevated 2 [ 108.29 ( 6.24–249.71 ) EPC mL−1 ; median ( 25th–75th percentiles ) , p = 0.052 ] and 20 h [ 106.86 ( 52.91–278.35 ) EPC mL−1 , p = 0.008 ] post-CAP exposure compared to the same time points following FA [ 38.47 ( 0.00–84.83 ) and 50.16 ( 0.00–104.79 ) EPC mL−1 ] . VEGF and white blood cell ( WBC ) levels did not differ between exposures . Conclusions : Brief inhalation of coarse PM from a rural location elicited an increase in EPCs that persisted for at least 20 h. The underlying mechanism responsible may reflect a systemic reaction to an acute “ endothelial injury ” and /or a circulating EPC response to sympathetic nervous system activation We conducted an extended follow-up and spatial analysis of the American Cancer Society ( ACS ) Cancer Prevention Study II ( CPS-II ) cohort in order to further examine associations between long-term exposure to particulate air pollution and mortality in large U.S. cities . The current study sought to clarify outst and ing scientific issues that arose from our earlier HEI-sponsored Re analysis of the original ACS study data ( the Particle Epidemiology Re analysis Project ) . Specifically , we examined ( 1 ) how ecologic covariates at the community and neighborhood levels might confound and modify the air pollution-mortality association ; ( 2 ) how spatial autocorrelation and multiple levels of data ( e.g. , individual and neighborhood ) can be taken into account within the r and om effects Cox model ; ( 3 ) how using l and -use regression to refine measurements of air pollution exposure to the within-city ( or intra-urban ) scale might affect the size and significance of health effects in the Los Angeles and New York City regions ; and ( 4 ) what exposure time windows may be most critical to the air pollution-mortality association . The 18 years of follow-up ( extended from 7 years in the original study [ Pope et al. 1995 ] ) included vital status data for the CPS-II cohort ( approximately 1.2 million participants ) with multiple cause-of-death codes through December 31 , 2000 and more recent exposure data from air pollution monitoring sites for the metropolitan areas . In the Nationwide Analysis , the influence of ecologic covariate data ( such as education attainment , housing characteristics , and level of income ; data obtained from the 1980 U.S. Census ; see Ecologic Covariates sidebar on page 14 ) on the air pollution-mortality association were examined at the Zip Code area ( ZCA ) scale , the metropolitan statistical area ( MSA ) scale , and by the difference between each ZCA value and the MSA value ( DIFF ) . In contrast to previous analyses that did not directly include ecologic covariates at the ZCA scale , risk estimates increased when ecologic covariates were included at all scales . The ecologic covariates exerted their greatest effect on mortality from ischemic heart disease ( IHD ) , which was also the health outcome most strongly related with exposure to PM2.5 ( particles 2.5 microm or smaller in aerodynamic diameter ) , sulfate ( SO4(2- ) ) , and sulfur dioxide ( SO2 ) , and the only outcome significantly associated with exposure to nitrogen dioxide ( NO2 ) . When ecologic covariates were simultaneously included at both the MSA and DIFF levels , the hazard ratio ( HR ) for mortality from IHD associated with PM2.5 exposure ( average concentration for 1999 - 2000 ) increased by 7.5 % and that associated with SO4(2- ) exposure ( average concentration for 1990 ) increased by 12.8 % . The two covariates found to exert the greatest confounding influence on the PM2.5-mortality association were the percentage of the population with a grade 12 education and the median household income . Also in the Nationwide Analysis , complex spatial patterns in the CPS-II data were explored with an extended r and om effects Cox model ( see Glossary of Statistical Terms at end of report ) that is capable of clustering up to two geographic levels of data . Using this model tended to increase the HR estimate for exposure to air pollution and also to inflate the uncertainty in the estimates . Including ecologic covariates decreased the variance of the results at both the MSA and ZCA scales ; the largest decrease was in residual variation based on models in which the MSA and DIFF levels of data were included together , which suggests that partitioning the ecologic covariates into between-MSA and within-MSA values more completely captures the sources of variation in the relationship between air pollution , ecologic covariates , and mortality . Intra-Urban Analyses were conducted for the New York City and Los Angeles regions . The results of the Los Angeles spatial analysis , where we found high exposure contrasts within the Los Angeles region , showed that air pollution-mortality risks were nearly 3 times greater than those reported from earlier analyses . This suggests that chronic health effects associated with intra-urban gradients in exposure to PM2.5 may be even larger between ZCAs within an MSA than the associations between MSAs that have been previously reported . However , in the New York City spatial analysis , where we found very little exposure contrast between ZCAs within the New York region , mortality from all causes , cardiopulmonary disease ( CPD ) , and lung cancer was not elevated . A positive association was seen for PM2.5 exposure and IHD , which provides evidence of a specific association with a cause of death that has high biologic plausibility . These results were robust when analyses controlled ( 1 ) the 44 individual-level covariates ( from the ACS enrollment question naire in 1982 ; see 44 Individual-Level Covariates sidebar on page 22 ) and ( 2 ) spatial clustering using the r and om effects Cox model . Effects were mildly lower when unemployment at the ZCA scale was included . To examine whether there is a critical exposure time window that is primarily responsible for the increased mortality associated with ambient air pollution , we constructed individual time-dependent exposure profiles for particulate and gaseous air pollutants ( PM2.5 and SO2 ) for a subset of the ACS CPS-II participants for whom residence histories were available . The relevance of the three exposure time windows we considered was gauged using the magnitude of the relative risk ( HR ) of mortality as well as the Akaike information criterion ( AIC ) , which measures the goodness of fit of the model to the data . For PM2.5 , no one exposure time window stood out as demonstrating the greatest HR ; nor was there any clear pattern of a trend in HR going from recent to more distant windows or vice versa . Differences in AIC values among the three exposure time windows were also small . The HRs for mortality associated with exposure to SO2 were highest in the most recent time window ( 1 to 5 years ) , although none of these HRs were significantly elevated . Identifying critical exposure time windows remains a challenge that warrants further work with other relevant data sets . This study provides additional support toward developing cost-effective air quality management policies and strategies . The epidemiologic results reported here are consistent with those from other population -based studies , which collectively have strongly supported the hypothesis that long-term exposure to PM2.5 increases mortality in the general population . Future research using the extended Cox-Poisson r and om effects methods , advanced geostatistical modeling techniques , and newer exposure assessment techniques will provide additional insight BACKGROUND Ambient air pollution is suspected to cause lung cancer . We aim ed to assess the association between long-term exposure to ambient air pollution and lung cancer incidence in European population s. METHODS This prospect i ve analysis of data obtained by the European Study of Cohorts for Air Pollution Effects used data from 17 cohort studies based in nine European countries . Baseline addresses were geocoded and we assessed air pollution by l and -use regression models for particulate matter ( PM ) with diameter of less than 10 μm ( PM10 ) , less than 2·5 μm ( PM2·5 ) , and between 2·5 and 10 μm ( PMcoarse ) , soot ( PM2·5absorbance ) , nitrogen oxides , and two traffic indicators . We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and r and om effects models for meta-analyses . FINDINGS The 312 944 cohort members contributed 4 013 131 person-years at risk . During follow-up ( mean 12·8 years ) , 2095 incident lung cancer cases were diagnosed . The meta-analyses showed a statistically significant association between risk for lung cancer and PM10 ( hazard ratio [ HR ] 1·22 [ 95 % CI 1·03 - 1·45 ] per 10 μg/m(3 ) ) . For PM2·5 the HR was 1·18 ( 0·96 - 1·46 ) per 5 μg/m(3 ) . The same increments of PM10 and PM2·5 were associated with HRs for adenocarcinomas of the lung of 1·51 ( 1·10 - 2·08 ) and 1·55 ( 1·05 - 2·29 ) , respectively . An increase in road traffic of 4000 vehicle-km 
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Other subgroup analyses indicated that the effects of PM2.5 exposure on VEGF differed per the in different exposure assessment methods , study design s , and study setting s. It was concluded that elevated VEGF levels was significantly positive associated with PM2.5 exposure .