CLASIFICACION DE SARNAT Y SARNAT PDF

Joan E. Sarnat at Psychoanalytic institute of Northern California. Joan E. Sarnat . O’Dea and Sarnat The Supervisory Relationship. (, pp. Air Pollution and Acute Respiratory Response in a Panel of Asthmatic. Children along the U.S.–Mexico Border. Stefanie Ebelt Sarnat,. 1. of newborns, several neurological scores have been created for newborns, such as the currently available Sarnat and. Sarnat,9 Thompson,10 and Garcia-Alix

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The health effects of ambient clasificacipn organic compounds VOCs have received less attention in epidemiologic studies than other commonly clasificacino ambient pollutants.

In this study, we estimated acute cardiorespiratory effects of sarant VOCs in an urban population. Daily concentrations of 89 VOCs were measured at a centrally-located srnat monitoring site in Atlanta and daily counts of emergency department visits for cardiovascular diseases and asthma in the 5-county Atlanta area were obtained for the — period.

To understand the health effects of sarat large number of species, we grouped these VOCs a priori by chemical structure and estimated the associations between VOC groups and daily counts of emergency department visits in a time-series framework using Poisson regression. We applied three analytic approaches to estimate the VOC group effects: We performed sensitivity analyses to evaluate co-pollutant confounding.

Hydrocarbon groups, particularly alkenes and alkynes, were associated with emergency department visits for cardiovascular diseases, while the ketone group was associated with emergency department visits for asthma.

The associations observed between emergency department visits for cardiovascular diseases and alkenes and satnat, may reflect the role of traffic j, while the association between asthma visits and ketones may reflect the role of secondary organic compounds.

The different patterns of associations we observed for cardiovascular diseases and asthma suggest different modes of action of these pollutants or the mixtures they represent. Ambient air pollution is a complex mixture of particulate matter varying in size and composition and gaseous pollutants. Health effects of particulate matter, its constituents, and criteria gases have been frequently investigated. Organic pollutants include a variety of compounds, such as hydrocarbons, halocarbons, and oxygenates.

These compounds reside in the vapor phase, particle phase, or both, depending on organic equilibrium properties e. There is claxificacion dynamic continuum among VOCs, semi-volatile organic compounds SVOCsand particle phase organics, and together they constitute total organic aerosol. Epidemiologic studies have suggested cardiorespiratory effects of mixtures from fossil fuel combustion, which contain large fractions of organic pollutants.

Previous epidemiologic studies have suggested respiratory effects of indoor VOCs. To advance our understanding of the health relevance of ambient VOCs, we estimated their acute cardiorespiratory effects in the Atlanta, Georgia, metropolitan population.

Grouping by chemical structure was motivated by several considerations: While we grouped these VOCs by shared characteristics, pollutants within a group may still differ in their health associations and be subject to different levels of measurement error. As there is little understanding of the nature of these classificacion, we applied three analytic approaches to estimate the group effects, each with different assumptions concerning the variations within a group.

Sampling details were previously published by Hansen et al. Data included daily concentrations of 89 identified individual species 77 hydrocarbons and 12 oxygenatestotal identified hydrocarbons, and total identified oxygenates Supplement, eTable 1.

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Concentrations were reported in part per billion, as carbon ppb-Cand the limit of detection LOD for all species was 0. We grouped individual VOCs a priori by chemical structure. Groups among the 77 hydrocarbons included alkanes, alkenes, alkynes, and aromatic hydrocarbons, and among the 12 oxygenates included aldehydes, acids, ketones, and ethers. Observations below LOD were replaced with half the detection limit 0. Daily counts of emergency department visits were aggregated from individual-level billing records from metropolitan Atlanta hospitals as part of SOPHIA.

Asthma visits were identified as those with primary ICD-9 diagnosis codes for asthma or wheeze We used these emergency department data in accordance with agreements with the hospitals and the Georgia Hospital Association.

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We first estimated the effects of total identified hydrocarbons and total identified oxygenates, and then estimated VOC group effects using three analytic approaches. All analyses were conducted in a time-series framework, in which we estimated the associations between daily levels of VOCs and daily counts of emergency department visits using Poisson regression accounting for over-dispersion.

Based on our previous research on ambient air pollution and emergency department visits in Atlanta, [ 26 — 29 ] and studies on ambient VOC health effects in other cities, [ 2224 ] we used same-day lag 0 pollution levels in models predicting emergency department visits for cardiovascular diseases and 3-day moving average of lags 0, 1, and 2 pollution levels in models predicting emergency department visits for asthma.

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All models included the same covariate control for temporal trends and meteorology: The estimated associations were reported as rate ratios per interquartile range IQR increase in pollutant concentrations. Analyses of emergency department visits for cardiovascular diseases included all ages. We used single-pollutant models to estimate the effect of total identified hydrocarbons and total identified oxygenates, as follows:.

We estimated VOC group effects using three analytic approaches: Pollutants in the same group may not be equally well measured. This approach is based on the assumption that the pollutant with the concentration distribution furthest from the LOD is less prone to instrument-related measurement error.

The effects of indicator pollutants were estimated using single-pollutant models as follows:. The effect of a given indicator pollutant may not fully represent the effect of its group if pollutant effects within a group differ.

To capture the contribution of different pollutants within a group, we estimated a joint effect per IQR increase in all pollutants of a group as follows:.

In the joint effect analysis, we considered the individual pollutant effects as fixed, and estimated a combined effect per increase in all pollutants in a group. In this random effect meta-analysis, we considered pollutant effects within a group as random normally distributed and estimated the group mean as the group effect. We applied a two-stage regression to estimate the group means and the within-group variance.

We obtained the estimated pollutant effects and their estimated variance-covariance matrix from the first stage model. In the second stage, we regressed the first stage estimates ssrnat indicator variables representing the groups:. We estimated the group means and within-group variance under a Bayesian framework using Markov chain Monte Carlo. We performed a series of sensitivity analyses for the indicator warnat approach, using emergency department visits among all sarnwt.

Third, we evaluated potential confounding by selected major pollutants by controlling for them one at a time in each VOC indicator pollutant model. The major clasidicacion considered in this analysis included hour average PM 2. These pollutants were also measured at the Atlanta Jefferson Street ambient monitor during the study period. Descriptive statistics and grouping information for the 46 VOCs included in the analysis are listed in Table 1and their Pearson correlations are listed in Supplementary eTable 2.

Hydrocarbons had moderate-to-strong positive correlations with one another r from 0. Oxygenates had weak-to-moderate positive correlations with one another r from 0. Descriptive statistics of the major pollutants PM 2. Hydrocarbons had moderate-to-strong positive correlations with PM 2.

We first estimated associations between total VOCs and emergency department visits using single-pollutant models. We then estimated VOC group effects using the three analytic approaches Table 2. Note that the alkyne, acid, clasificacoon ketone groups included only one pollutant, and thus their joint effect estimates were the same as their indicator pollutant effect estimates. Among oxygenates, associations with cardiovascular diseases were generally consistent with the null except for the aldehyde group in the joint effects analysis Table 2.

Estimated associations between VOC groups and cardiovascular ssarnat asthma emergency department ED visits using three analytic approaches. In comparison, the associations for hydrocarbon groups were weaker Table 2.

We performed sensitivity analyses claisficacion emergency department visits among all ages. Sensitivity analyses evaluating model misspecification and confounding by VOCs. We estimated the association for each VOC group conditioning on others sarjat including the 10 VOC indicator pollutants in one model. The estimated associations between emergency department visits of cardiovascular diseases and the alkene and alkyne groups had little change compared to those in the primary analysis using the indicator pollutant approach, while the estimated associations for dlasificacion hydrocarbon groups were closer j the null Table 3.

For asthma visits, results of this clasifucacion analysis appeared to be unstable. We estimated the association for each VOC indicator pollutant controlling for major pollutants one at a time in two-pollutant models. Sarhat estimated associations between emergency department visits for cardiovascular diseases and hydrocarbon groups were weaker when controlling for CO; the associations for CO were also weaker in two-pollutant models with the alkene or alkyne groups, compared to its estimated association in a single-pollutant model Table 4.

The associations between sarnah visits and hydrocarbon groups, on the other hand, were weaker when controlling for OC, CO, or NO 2 Table 5. Sensitivity analysis controlling for selected major pollutants one at a time in each VOC indicator pollutant model predicting cardiovascular ED visits among all ages.

Sensitivity analysis controlling for selected major pollutants one at a time in each VOC indicator pollutant model predicting asthma ED visits among all ages. In this clasificacionn, we estimated acute cardiorespiratory effects of ambient VOCs by grouping these compounds based on chemical structure and estimating VOC group effects.

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Because few epidemiologic studies have examined the health effect of ambient VOCs, there is little understanding of the variation of pollutant clasicicacion and clasificaxion error within a group, confounding by VOCs, and confounding by other fractions of air pollution. Because of these challenges, we applied multiple analytic approaches to estimate VOC group sarat, and performed a range of sensitivity analyses.

We used the indicator pollutant approach as an attempt to minimize the instrument measurement error by using what we believed to be the best-measured pollutant. In the joint effect analysis, we considered individual pollutant effects as fixed and estimated a combined effect per increment of all pollutants in a group. In the random effect meta-analysis, we considered individual pollutant effects as random normally distributed within a group and estimated the group mean effect.

Any inconsistency among group effect estimates using these approaches does not necessarily indicate that any of the estimates are wrong, but could reflect that these approaches define the group effects differently. In our primary analysis of emergency department visits for cardiovascular diseases, we observed similar associations across hydrocarbon groups when using the indicator pollutant approach Table 2.

We performed a sensitivity analysis to estimate the effect of each group conditioning on others, and the results suggested that many of the hydrocarbon groups might be surrogates of the alkene and the alkyne groups Table 3. The finding of alkynes being associated with cardiovascular diseases conditioning on other VOC groups agreed with the random effect meta-analysis results in the primary analysis, in which the sqrnat associations for each group were adjusted for others Table 2.

However, it is also possible that these VOC groups are surrogates for other pollutants in the ambient air, and that the alkene and the alkyne groups in our analysis were merely better surrogates than other VOCs. To understand what the VOCs might be surrogates for, we performed an additional sensitivity analysis controlling for selected major pollutants one at a time in each VOC indicator pollutant model.

When controlling for Sanrat, the estimated associations between cardiovascular visits and the alkene and the alkyne groups were weaker, and the CO association was also weaker Table 4.

The alkene and the alkyne groups may be part of a causal mixture with CO, or, these pollutants could all be surrogates of other unmeasured pollutants in the causal mixture.

Considering that clasificacin in the alkene and alkyne groups are mainly generated from combustion, among which acetylene the pollutant in the alkyne group is a marker of automobile emissions, and CO is a classic traffic marker, their associations with cardiovascular sarnah may reflect the clasifciacion of traffic exhaust. In our primary analysis of asthma visits, we observed relatively strong associations with the ketone group among all ages Table 2 and among specific age categories Supplement, eTable 5.

We performed sensitivity analyses on asthma visits of all ages, and found that the estimated associations for the ketone group had little change after controlling for any of the major pollutants Table 5. While certain ketones are byproducts of ozone formation, and the pollutant in our ketone group is moderately correlated with ozone in this analysis, the association between ketone and asthma visits had little change after controlling for ozone.

The association between ketone and asthma sanrat could reflect something beyond the effect of ozone: Overall, we found that hydrocarbon groups, particularly the alkene and alkyne groups, were associated with emergency department visits for cardiovascular diseases, while the ketone group was associated with asthma visits.

Some hydrocarbon groups were associated with asthma visits, however, the magnitudes of their associations were smaller compared to the ketone group. The different patterns of associations we observed for the cardiovascular diseases and asthma suggest there could be different modes of action of these pollutants or the pollution mixtures they represent.

The hydrocarbons included in our analysis are primarily emitted from traffic or other combustion sources, while oxygenates such as ketones are largely secondary. Previous studies of particle-phase pollutants have suggested that secondary organic compounds are more related to respiratory inflammation, as they are hydrophilic and thus more readily react with constituents in the respiratory tract, [ 6 ] while primary organic compounds are more related to systemic inflammation.

Previous epidemiologic studies reported positive dee between cardiovascular health outcomes and ambient hydrocarbons. Previous epidemiologic studies reported positive associations between respiratory health outcomes and ambient hydrocarbons, aldehydes, and ketones.