192 research outputs found

    Survival Analysis to Estimate Association between Short-Term Mortality and Air Pollution

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    BACKGROUND: Ecologic studies are commonly used to report associations between short-term air pollution and mortality. In such studies, the unit of observation is the day rather than the individual. Moreover, individual data on the subjects are rarely available, which limits the assessment of individual risk factors. These associations can also be investigated using case–crossover studies. However, by definition, individual risk factors are not studied, and such studies analyze only dead subjects, which limits the statistical power. OBJECTIVE: We suggest that the survival analysis is more suitable when cohorts are examined with a time-dependent ecologic exposure. To our knowledge, to date this type of analysis has never been proposed. DESIGN, PARTICIPANTS, MEASUREMENTS: In the present study we used a Cox proportional hazards model to investigate the distribution over time of the short-term effect of black smoke and sulfur dioxide in 439 nonaccidental and 158 cardiorespiratory deaths among the 1,469 subjects of the Personnes AgĂ©es QUID (PAQUID) cohort in Bordeaux, France. The model has a delayed entry and a polynomial distributed lag from 0 to 5 days. Results are adjusted for individual risk factors, temperature, relative humidity, weekday, season, influenza epidemics, and a time function to control temporal trends. RESULTS: We identified a positive and significant association between cardiorespiratory mortality and black smoke, with a 24% increase in deaths 3 days after a 10-ÎŒg/m(3) increase in black smoke (95% confidence interval, 4–47%). CONCLUSIONS: We conclude that the Cox proportional hazards model with time-dependent covariates is very suitable to investigate simultaneously the short-term effect of air pollution on health and the effect of individual risk factors on a cohort study

    Pathogens identified in calves with neonatal gastro-enteritis in Vendée (France)

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    The object of this study was to describe the relative involvement of major pathogens in neonatal gastroenteritis in calves less than one month of age in Vendée (France). One to four samples of faeces from affected calves were collected in 127 farms serviced by 20 veterinary practices between 2002 and 2004. The study confirmed that several pathogens were involved in bovine neonatal gastroenteritis in Vendée. One of the four types of pathogenic E. coli tested for was isolated in over 65% of the samples, and CS31A was the most prevalent type. Cryptosporidia were also identified frequently, often in large quantities. Rotaviruses were found more frequently than Coronaviruses. No coccidian oocysts were found in animals less than one month of age.Cette étude avait pour objectif de décrire l'implication relative des agents pathogÚnes majeurs dans les gastro-entérites néonatales (GENN) du veau, en Vendée. L'étude a porté sur des veaux de moins d'un mois ayant une gastro-entérite néonatale. Des prélÚvements de matiÚres fécales (un à quatre) de veaux malades ont été recueillis dans 127 exploitations de vingt clientÚles vétérinaires, durant la période 2002-2004. L'étude a confirmé l'origine multiple des GENN en Vendée. Plus de 65 % des prélÚvements ont conduit à l'isolement d'un des 4 types pathogÚnes d'E. coli recherchés. Le sérotype CS31A était prédominant.Les cryptosporidies ont aussi été fréquemment mises en évidence, souvent en quantité importante. Les rotavirus ont été retrouvés plus fréquemment que les coronavirus. En dessous d'un mois d'ùge, aucun ookyste de coccidies n'a été décelé

    The fraction of lung cancer incidence attributable to fine particulate air pollution in France: Impact of spatial resolution of air pollution models

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    Outdoor air pollution is a leading environmental cause of death and cancer incidence in humans. We aimed to estimate the fraction of lung cancer incidence attributable to fine particulate matter (PM2.5) exposure in France, and secondarily to illustrate the influence of the input data and the spatial resolution of information on air pollution levels on this estimate. The population attributable fraction (PAF) was estimated using a nationwide spatially refined chemistry-transport model with a 2-km spatial resolution, neighbourhood-scale population density data, and a relative risk from a published meta-analysis. We used the WHO guideline value for PM2.5 exposure (10??g/m3) as reference. Sensitivity analyses consisted in attributing the nation-wide median exposure to all areas and using alternative input data such as reference of PM2.5 exposure level and relative risk. Population-weighted median PM2.5 level in 2005 was 13.8??g/m3; 87% of the population was exposed above the guideline value. The burden of lung cancer attributable to PM2.5 exposure corresponded to 1466 cases, or 3.6% of all cases diagnosed in 2015. Sensitivity analyses showed that the use of a national median of PM2.5 exposure would have led to an underestimation of the PAF by 11% (population-weighted median) and by 72% (median of raw concentration), suggesting that our estimates would have been higher with even more finely spatially-resolved models. When the PM2.5 reference level was replaced by the 5th percentile of country-scale exposure (4.9??g/m3), PAF increased to 7.6%. Other sensitivity analyses resulted in even higher PAFs. Improvements in air pollution are crucial for quantitative health impacts assessment studies. Actions to reduce PM2.5 levels could substantially reduce the burden of lung cancer in France

    Lung function association with outdoor temperature and relative humidity and its interaction with air pollution in the elderly.

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    While the effects of weather variability on cardio-respiratory mortality are well described, research examining the effects on morbidity, especially for vulnerable populations, is warranted. We investigated the associations between lung function and outdoor temperature (T in Celsius degrees (°C)) and relative humidity (RH), in a cohort of elderly men, the Normative Aging Study. Our study included 1103 participants whose forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and weather exposures were assessed one to five times during the period 1995-2011 (i.e. 3162 observations). Temperature and relative humidity were measured at one location 4 h to 7 days before lung function tests. We used linear mixed-effects models to examine the associations with outdoor T and RH. A 5-degree increase in the 3-day moving average T was associated with a significant 0.7% decrease (95%CI: -1.24, -0.20) in FVC and a 5% increase in the 7-day moving average RH was associated with a significant 0.2% decrease (95%CI: -0.40, -0.02) in FVC and FEV1. The associations with T were greater when combined with higher exposures of black carbon with a 1.6% decrease (95%CI -2.2; -0.9) in FVC and a 1% decrease (95%CI -1.7; -0.4) in FEV1. The relationships between T and RH and lung function were linear. No synergistic effect of T and RH was found. Heat and lung function are two predictors of mortality. Our findings suggest that increases in temperature and relative humidity are related to decreases in lung function, and such observations might be amplified by high black carbon levels

    Impact of geocoding methods on associations between long-term exposure to urban air pollution and lung function

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    Background: Errors in address geocodes may affect estimates of the effects of air pollution on health.Objective: We investigated the impact of four geocoding techniques on the association between urban air pollution estimated with a fine-scale (10 m × 10 m) dispersion model and lung function in adults.Methods: We measured forced expiratory volume in 1 sec (FEV1) and forced vital capacity (FVC) in 354 adult residents of Grenoble, France, who were participants in two well-characterized studies, the Epidemiological Study on the Genetics and Environment on Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Home addresses were geocoded using individual building matching as the reference approach and three spatial interpolation approaches. We used a dispersion model to estimate mean PM10 and nitrogen dioxide concentrations at each participant's address during the 12 months preceding their lung function measurements. Associations between exposures and lung function parameters were adjusted for individual confounders and same-day exposure to air pollutants. The geocoding techniques were compared with regard to geographical distances between coordinates, exposure estimates, and associations between the estimated exposures and health effects.Results: Median distances between coordinates estimated using the building matching and the three interpolation techniques were 26.4, 27.9, and 35.6 m. Compared with exposure estimates based on building matching, PM10 concentrations based on the three interpolation techniques tended to be overestimated. When building matching was used to estimate exposures, a one-interquartile range increase in PM10 (3.0 ÎŒg/m3) was associated with a 3.72-point decrease in FVC% predicted (95% CI: -0.56, -6.88) and a 3.86-point decrease in FEV1% predicted (95% CI: -0.14, -3.24). The magnitude of associations decreased when other geocoding approaches were used [e.g., for FVC% predicted -2.81 (95% CI: -0.26, -5.35) using NavTEQ or 2.08 (95% CI -4.63, 0.47, p = 0.11) using Google Maps].Conclusions: Our findings suggest that the choice of geocoding technique may influence estimated health effects when air pollution exposures are estimated using a fine-scale exposure model.Citation: Jacquemin B, Lepeule J, Boudier A, Arnould C, Benmerad M, Chappaz C, Ferran J, Kauffmann F, Morelli X, Pin I, Pison C, Rios I, Temam S, KĂŒnzli N, Slama R, Siroux V. 2013. Impact of geocoding methods on associations between long-term exposure to urban air pollution and lung function. Environ Health Perspect 121:1054-1060; http://dx.doi.org/10.1289/ehp.1206016

    Prenatal environmental exposures associated with sex differences in childhood obesity and neurodevelopment

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    Background Obesity and neurodevelopmental delay are complex traits that often co-occur and differ between boys and girls. Prenatal exposures are believed to influence children’s obesity, but it is unknown whether exposures of pregnant mothers can confer a different risk of obesity between sexes, and whether they can affect neurodevelopment. Methods We analyzed data from 1044 children from the HELIX project, comprising 93 exposures during pregnancy, and clinical, neuropsychological, and methylation data during childhood (5–11 years). Using exposome-wide interaction analyses, we identified prenatal exposures with the highest sexual dimorphism in obesity risk, which were used to create a multiexposure profile. We applied causal random forest to classify individuals into two environments: E1 and E0. E1 consists of a combination of exposure levels where girls have significantly less risk of obesity than boys, as compared to E0, which consists of the remaining combination of exposure levels. We investigated whether the association between sex and neurodevelopmental delay also differed between E0 and E1. We used methylation data to perform an epigenome-wide association study between the environments to see the effect of belonging to E1 or E0 at the molecular level. Results We observed that E1 was defined by the combination of low dairy consumption, non-smokers’ cotinine levels in blood, low facility richness, and the presence of green spaces during pregnancy (ORinteraction¿=¿0.070, P¿=¿2.59¿×¿10-5). E1 was also associated with a lower risk of neurodevelopmental delay in girls, based on neuropsychological tests of non-verbal intelligence (ORinteraction¿=¿0.42, P¿=¿0.047) and working memory (ORinteraction¿=¿0.31, P¿=¿0.02). In line with this, several neurodevelopmental functions were enriched in significant differentially methylated probes between E1 and E0. Conclusions The risk of obesity can be different for boys and girls in certain prenatal environments. We identified an environment combining four exposure levels that protect girls from obesity and neurodevelopment delay. The combination of single exposures into multiexposure profiles using causal inference can help determine populations at risk.Peer ReviewedPostprint (published version
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