Influence of set-up conditions of exposure indicators on the estimate of short-term associations between urban pollution and mortality
Identifieur interne : 000218 ( PascalFrancis/Corpus ); précédent : 000217; suivant : 000219Influence of set-up conditions of exposure indicators on the estimate of short-term associations between urban pollution and mortality
Auteurs : Laurent Filleul ; Abdelkrim Zeghnoun ; Sylvie Cassadou ; Christophe Declercq ; Daniel Eilstein ; Alain Le Tertre ; Sylvia Medina ; Laurence Pascal ; Hélène Prouvost ; Philippe Saviuc ; Philippe QuenelSource :
- Science of the total environment [ 0048-9697 ] ; 2006.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
In the past few years many studies on air pollution and health based on time series have been carried out. Yet, this approach does not assess exposure to air pollution at an individual level but it is based on ambient concentrations measured by air quality monitoring networks. Questions on the estimates of exposure to pollutants have been raised, in particular the fact that background measuring stations only have been considered in the set up of pollution indicators. To assess the impact of exposure indicator characteristics on the results of time series analysis, two series (black smoke and sulfur dioxide, respectively) of exposure indicators to urban air pollution were set up taking into account a growing part of proximity measures (industrial sources) available in the studied urban area (Le Havre, France). For each pollutant, indicators distributions were almost similar, especially for black smoke. Whatever the pollutant, the most obvious heterogeneity could be observed between the 100% background indicator and the indicator including the arithmetic mean for all the stations (50% background stations and 50% proximity stations). Then the sensitivity of the associations between mortality and air pollution to these indicators was studied. These indicators did not show statistically significant differences in the estimated excess risk. Yet, confidence intervals were more statistically significant as the contribution of proximity stations was more substantial, in particular for SO2. To conclude, the use of proximity measurements did not influence dramatically on the mean estimates of the association between air pollution and mortality indicators in Le Havre. Therefore it does not seem relevant to include the data provided by the proximity stations in the urban exposure indicators within the context of the epidemiology monitoring system.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
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Format Inist (serveur)
NO : | PASCAL 06-0127638 INIST |
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ET : | Influence of set-up conditions of exposure indicators on the estimate of short-term associations between urban pollution and mortality |
AU : | FILLEUL (Laurent); ZEGHNOUN (Abdelkrim); CASSADOU (Sylvie); DECLERCQ (Christophe); EILSTEIN (Daniel); LE TERTRE (Alain); MEDINA (Sylvia); PASCAL (Laurence); PROUVOST (Hélène); SAVIUC (Philippe); QUENEL (Philippe) |
AF : | Institut de Veille Sanitaire-Cire Aquitaine, Espasse Rodesse, 103, bis rue Belleville, BP 952/33063 Bordeaux/France (1 aut., 2 aut., 3 aut., 5 aut., 6 aut., 7 aut., 8 aut., 10 aut., 11 aut.); Observatoire Régional de la Santé Nord Pas-de-Calais/France (4 aut., 9 aut.) |
DT : | Publication en série; Niveau analytique |
SO : | Science of the total environment; ISSN 0048-9697; Coden STENDL; Irlande; Da. 2006; Vol. 355; No. 1-3; Pp. 90-97; Bibl. 1 p.1/4 |
LA : | Anglais |
EA : | In the past few years many studies on air pollution and health based on time series have been carried out. Yet, this approach does not assess exposure to air pollution at an individual level but it is based on ambient concentrations measured by air quality monitoring networks. Questions on the estimates of exposure to pollutants have been raised, in particular the fact that background measuring stations only have been considered in the set up of pollution indicators. To assess the impact of exposure indicator characteristics on the results of time series analysis, two series (black smoke and sulfur dioxide, respectively) of exposure indicators to urban air pollution were set up taking into account a growing part of proximity measures (industrial sources) available in the studied urban area (Le Havre, France). For each pollutant, indicators distributions were almost similar, especially for black smoke. Whatever the pollutant, the most obvious heterogeneity could be observed between the 100% background indicator and the indicator including the arithmetic mean for all the stations (50% background stations and 50% proximity stations). Then the sensitivity of the associations between mortality and air pollution to these indicators was studied. These indicators did not show statistically significant differences in the estimated excess risk. Yet, confidence intervals were more statistically significant as the contribution of proximity stations was more substantial, in particular for SO2. To conclude, the use of proximity measurements did not influence dramatically on the mean estimates of the association between air pollution and mortality indicators in Le Havre. Therefore it does not seem relevant to include the data provided by the proximity stations in the urban exposure indicators within the context of the epidemiology monitoring system. |
CC : | 002B03M02 |
FD : | Pollution air; Toxicité; Homme; Santé publique; Milieu urbain; Fumée noire; Soufre dioxyde; Mesure concentration; Teneur air ambiant; Zone industrielle; Proximité; Zone résidentielle; Mortalité; Evaluation; Exposition; Méthodologie; France |
FG : | Europe |
ED : | Air pollution; Toxicity; Human; Public health; Urban environment; Carbonaceous smoke; Sulfur dioxide; Concentration measurement; Ambient air concentration; Industrial area; Proximity; Residential zone; Mortality; Evaluation; Exposure; Methodology; France |
EG : | Europe |
SD : | Contaminación aire; Toxicidad; Hombre; Salud pública; Medio urbano; Humo negro; Dióxido sulfúrico; Medición concentración; Contenido aire ambiental; Zona industrial; Proximidad; Zona residencial; Mortalidad; Evaluación; Exposición; Metodología; Francia |
LO : | INIST-15662.354000115130750080 |
ID : | 06-0127638 |
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Pascal:06-0127638Le document en format XML
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<term>Evaluation</term>
<term>Exposure</term>
<term>France</term>
<term>Human</term>
<term>Industrial area</term>
<term>Methodology</term>
<term>Mortality</term>
<term>Proximity</term>
<term>Public health</term>
<term>Residential zone</term>
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<term>Toxicité</term>
<term>Homme</term>
<term>Santé publique</term>
<term>Milieu urbain</term>
<term>Fumée noire</term>
<term>Soufre dioxyde</term>
<term>Mesure concentration</term>
<term>Teneur air ambiant</term>
<term>Zone industrielle</term>
<term>Proximité</term>
<term>Zone résidentielle</term>
<term>Mortalité</term>
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<front><div type="abstract" xml:lang="en">In the past few years many studies on air pollution and health based on time series have been carried out. Yet, this approach does not assess exposure to air pollution at an individual level but it is based on ambient concentrations measured by air quality monitoring networks. Questions on the estimates of exposure to pollutants have been raised, in particular the fact that background measuring stations only have been considered in the set up of pollution indicators. To assess the impact of exposure indicator characteristics on the results of time series analysis, two series (black smoke and sulfur dioxide, respectively) of exposure indicators to urban air pollution were set up taking into account a growing part of proximity measures (industrial sources) available in the studied urban area (Le Havre, France). For each pollutant, indicators distributions were almost similar, especially for black smoke. Whatever the pollutant, the most obvious heterogeneity could be observed between the 100% background indicator and the indicator including the arithmetic mean for all the stations (50% background stations and 50% proximity stations). Then the sensitivity of the associations between mortality and air pollution to these indicators was studied. These indicators did not show statistically significant differences in the estimated excess risk. Yet, confidence intervals were more statistically significant as the contribution of proximity stations was more substantial, in particular for SO<sub>2</sub>
. To conclude, the use of proximity measurements did not influence dramatically on the mean estimates of the association between air pollution and mortality indicators in Le Havre. Therefore it does not seem relevant to include the data provided by the proximity stations in the urban exposure indicators within the context of the epidemiology monitoring system.</div>
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<fA02 i1="01"><s0>STENDL</s0>
</fA02>
<fA03 i2="1"><s0>Sci. total environ.</s0>
</fA03>
<fA05><s2>355</s2>
</fA05>
<fA06><s2>1-3</s2>
</fA06>
<fA08 i1="01" i2="1" l="ENG"><s1>Influence of set-up conditions of exposure indicators on the estimate of short-term associations between urban pollution and mortality</s1>
</fA08>
<fA11 i1="01" i2="1"><s1>FILLEUL (Laurent)</s1>
</fA11>
<fA11 i1="02" i2="1"><s1>ZEGHNOUN (Abdelkrim)</s1>
</fA11>
<fA11 i1="03" i2="1"><s1>CASSADOU (Sylvie)</s1>
</fA11>
<fA11 i1="04" i2="1"><s1>DECLERCQ (Christophe)</s1>
</fA11>
<fA11 i1="05" i2="1"><s1>EILSTEIN (Daniel)</s1>
</fA11>
<fA11 i1="06" i2="1"><s1>LE TERTRE (Alain)</s1>
</fA11>
<fA11 i1="07" i2="1"><s1>MEDINA (Sylvia)</s1>
</fA11>
<fA11 i1="08" i2="1"><s1>PASCAL (Laurence)</s1>
</fA11>
<fA11 i1="09" i2="1"><s1>PROUVOST (Hélène)</s1>
</fA11>
<fA11 i1="10" i2="1"><s1>SAVIUC (Philippe)</s1>
</fA11>
<fA11 i1="11" i2="1"><s1>QUENEL (Philippe)</s1>
</fA11>
<fA14 i1="01"><s1>Institut de Veille Sanitaire-Cire Aquitaine, Espasse Rodesse, 103, bis rue Belleville, BP 952</s1>
<s2>33063 Bordeaux</s2>
<s3>FRA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
<sZ>7 aut.</sZ>
<sZ>8 aut.</sZ>
<sZ>10 aut.</sZ>
<sZ>11 aut.</sZ>
</fA14>
<fA14 i1="02"><s1>Observatoire Régional de la Santé Nord Pas-de-Calais</s1>
<s3>FRA</s3>
<sZ>4 aut.</sZ>
<sZ>9 aut.</sZ>
</fA14>
<fA20><s1>90-97</s1>
</fA20>
<fA21><s1>2006</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>15662</s2>
<s5>354000115130750080</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2006 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>1 p.1/4</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>06-0127638</s0>
</fA47>
<fA60><s1>P</s1>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>Science of the total environment</s0>
</fA64>
<fA66 i1="01"><s0>IRL</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>In the past few years many studies on air pollution and health based on time series have been carried out. Yet, this approach does not assess exposure to air pollution at an individual level but it is based on ambient concentrations measured by air quality monitoring networks. Questions on the estimates of exposure to pollutants have been raised, in particular the fact that background measuring stations only have been considered in the set up of pollution indicators. To assess the impact of exposure indicator characteristics on the results of time series analysis, two series (black smoke and sulfur dioxide, respectively) of exposure indicators to urban air pollution were set up taking into account a growing part of proximity measures (industrial sources) available in the studied urban area (Le Havre, France). For each pollutant, indicators distributions were almost similar, especially for black smoke. Whatever the pollutant, the most obvious heterogeneity could be observed between the 100% background indicator and the indicator including the arithmetic mean for all the stations (50% background stations and 50% proximity stations). Then the sensitivity of the associations between mortality and air pollution to these indicators was studied. These indicators did not show statistically significant differences in the estimated excess risk. Yet, confidence intervals were more statistically significant as the contribution of proximity stations was more substantial, in particular for SO<sub>2</sub>
. To conclude, the use of proximity measurements did not influence dramatically on the mean estimates of the association between air pollution and mortality indicators in Le Havre. Therefore it does not seem relevant to include the data provided by the proximity stations in the urban exposure indicators within the context of the epidemiology monitoring system.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>002B03M02</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Pollution air</s0>
<s5>02</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Air pollution</s0>
<s5>02</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Contaminación aire</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Toxicité</s0>
<s5>03</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Toxicity</s0>
<s5>03</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Toxicidad</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Homme</s0>
<s5>05</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Human</s0>
<s5>05</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Hombre</s0>
<s5>05</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Santé publique</s0>
<s5>06</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Public health</s0>
<s5>06</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Salud pública</s0>
<s5>06</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Milieu urbain</s0>
<s5>08</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Urban environment</s0>
<s5>08</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Medio urbano</s0>
<s5>08</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Fumée noire</s0>
<s5>09</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Carbonaceous smoke</s0>
<s5>09</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Humo negro</s0>
<s5>09</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Soufre dioxyde</s0>
<s2>NK</s2>
<s2>FX</s2>
<s5>11</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Sulfur dioxide</s0>
<s2>NK</s2>
<s2>FX</s2>
<s5>11</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Dióxido sulfúrico</s0>
<s2>NK</s2>
<s2>FX</s2>
<s5>11</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Mesure concentration</s0>
<s5>12</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Concentration measurement</s0>
<s5>12</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Medición concentración</s0>
<s5>12</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Teneur air ambiant</s0>
<s5>16</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Ambient air concentration</s0>
<s5>16</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Contenido aire ambiental</s0>
<s5>16</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Zone industrielle</s0>
<s5>17</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Industrial area</s0>
<s5>17</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Zona industrial</s0>
<s5>17</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Proximité</s0>
<s5>18</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Proximity</s0>
<s5>18</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Proximidad</s0>
<s5>18</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Zone résidentielle</s0>
<s5>19</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Residential zone</s0>
<s5>19</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Zona residencial</s0>
<s5>19</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Mortalité</s0>
<s5>20</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Mortality</s0>
<s5>20</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Mortalidad</s0>
<s5>20</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Evaluation</s0>
<s5>21</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Evaluation</s0>
<s5>21</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Evaluación</s0>
<s5>21</s5>
</fC03>
<fC03 i1="15" i2="X" l="FRE"><s0>Exposition</s0>
<s5>22</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>Exposure</s0>
<s5>22</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Exposición</s0>
<s5>22</s5>
</fC03>
<fC03 i1="16" i2="X" l="FRE"><s0>Méthodologie</s0>
<s5>23</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG"><s0>Methodology</s0>
<s5>23</s5>
</fC03>
<fC03 i1="16" i2="X" l="SPA"><s0>Metodología</s0>
<s5>23</s5>
</fC03>
<fC03 i1="17" i2="X" l="FRE"><s0>France</s0>
<s2>NG</s2>
<s5>24</s5>
</fC03>
<fC03 i1="17" i2="X" l="ENG"><s0>France</s0>
<s2>NG</s2>
<s5>24</s5>
</fC03>
<fC03 i1="17" i2="X" l="SPA"><s0>Francia</s0>
<s2>NG</s2>
<s5>24</s5>
</fC03>
<fC07 i1="01" i2="X" l="FRE"><s0>Europe</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="X" l="ENG"><s0>Europe</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="X" l="SPA"><s0>Europa</s0>
<s2>NG</s2>
</fC07>
<fN21><s1>079</s1>
</fN21>
</pA>
</standard>
<server><NO>PASCAL 06-0127638 INIST</NO>
<ET>Influence of set-up conditions of exposure indicators on the estimate of short-term associations between urban pollution and mortality</ET>
<AU>FILLEUL (Laurent); ZEGHNOUN (Abdelkrim); CASSADOU (Sylvie); DECLERCQ (Christophe); EILSTEIN (Daniel); LE TERTRE (Alain); MEDINA (Sylvia); PASCAL (Laurence); PROUVOST (Hélène); SAVIUC (Philippe); QUENEL (Philippe)</AU>
<AF>Institut de Veille Sanitaire-Cire Aquitaine, Espasse Rodesse, 103, bis rue Belleville, BP 952/33063 Bordeaux/France (1 aut., 2 aut., 3 aut., 5 aut., 6 aut., 7 aut., 8 aut., 10 aut., 11 aut.); Observatoire Régional de la Santé Nord Pas-de-Calais/France (4 aut., 9 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Science of the total environment; ISSN 0048-9697; Coden STENDL; Irlande; Da. 2006; Vol. 355; No. 1-3; Pp. 90-97; Bibl. 1 p.1/4</SO>
<LA>Anglais</LA>
<EA>In the past few years many studies on air pollution and health based on time series have been carried out. Yet, this approach does not assess exposure to air pollution at an individual level but it is based on ambient concentrations measured by air quality monitoring networks. Questions on the estimates of exposure to pollutants have been raised, in particular the fact that background measuring stations only have been considered in the set up of pollution indicators. To assess the impact of exposure indicator characteristics on the results of time series analysis, two series (black smoke and sulfur dioxide, respectively) of exposure indicators to urban air pollution were set up taking into account a growing part of proximity measures (industrial sources) available in the studied urban area (Le Havre, France). For each pollutant, indicators distributions were almost similar, especially for black smoke. Whatever the pollutant, the most obvious heterogeneity could be observed between the 100% background indicator and the indicator including the arithmetic mean for all the stations (50% background stations and 50% proximity stations). Then the sensitivity of the associations between mortality and air pollution to these indicators was studied. These indicators did not show statistically significant differences in the estimated excess risk. Yet, confidence intervals were more statistically significant as the contribution of proximity stations was more substantial, in particular for SO<sub>2</sub>
. To conclude, the use of proximity measurements did not influence dramatically on the mean estimates of the association between air pollution and mortality indicators in Le Havre. Therefore it does not seem relevant to include the data provided by the proximity stations in the urban exposure indicators within the context of the epidemiology monitoring system.</EA>
<CC>002B03M02</CC>
<FD>Pollution air; Toxicité; Homme; Santé publique; Milieu urbain; Fumée noire; Soufre dioxyde; Mesure concentration; Teneur air ambiant; Zone industrielle; Proximité; Zone résidentielle; Mortalité; Evaluation; Exposition; Méthodologie; France</FD>
<FG>Europe</FG>
<ED>Air pollution; Toxicity; Human; Public health; Urban environment; Carbonaceous smoke; Sulfur dioxide; Concentration measurement; Ambient air concentration; Industrial area; Proximity; Residential zone; Mortality; Evaluation; Exposure; Methodology; France</ED>
<EG>Europe</EG>
<SD>Contaminación aire; Toxicidad; Hombre; Salud pública; Medio urbano; Humo negro; Dióxido sulfúrico; Medición concentración; Contenido aire ambiental; Zona industrial; Proximidad; Zona residencial; Mortalidad; Evaluación; Exposición; Metodología; Francia</SD>
<LO>INIST-15662.354000115130750080</LO>
<ID>06-0127638</ID>
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</inist>
</record>
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