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    "idiomaDefecto" => true
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    "textoCompleto" => "<p class="elsevierStylePara"> Sabado 4 de Octubre &#47; Saturday 4&#44; October<br></br> 9&#58;00&#58;00 a&#47;to 11&#58;00&#58;00</p><p class="elsevierStylePara"> Moderador&#47;Chairperson&#58;<br></br> Manel Nebot</p><p class="elsevierStylePara"><span class="elsevierStyleBold">484 TOBACCO AND ALCOHOL CONSUMPTION&#44; SEDENTARY LIFESTYLE AND OVERWEIGHTNESS IN FRANCE&#58; A MULTILEVEL ANALYSIS OF INDIVIDUAL AND AREA-LEVEL DETERMINANTS</span></p><p class="elsevierStylePara"> Basile Chaix&#44; Pierre Chauvin</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">Research Unit in Epidemiology and Information Sciences&#44; National Institute of Health and Medical Research&#44; Paris&#44; France&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Introduction&#58;</span> We investigated the effect of the level of consumerism&#44; expressed as the gross domestic product &#40;GDP&#41; per capita in the broad area of residence&#44; on the risks of smoking&#44; drinking&#44; sedentary behaviour and overweightness&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> Using a representative sample of the French population&#44; multilevel logistic models allowed us to examine the effect of the GDP on such health-related behaviour&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> After adjustment for potential confounders&#44; we found no GDP effect on the odds of being a moderate smoker&#46; Conversely&#44; the risk of being a highly-dependent smoker as opposed to a moderate consumer or an abstainer increased with the area-level GDP per capita &#40;OR&#58; 1&#46;13&#44; 95&#37; CI&#58; 1&#46;04-1&#46;23 for an increment of one standard deviation&#41;&#46; A similar pattern was found for alcohol consumption&#58; the odds of being a moderate consumer were not related to the GDP per capita&#44; but a positive effect of the GDP on the odds of being an alcohol-dependent drinker as opposed to a moderate consumer or an abstainer was found among women &#40;OR&#58; 1&#46;14&#44; 95&#37; CI&#58; 1&#46;02-1&#46;28&#41;&#46; The gap between the sexes with respect to alcohol-dependency therefore appeared to be narrower when the GDP per capita was high&#46; On the other hand&#44; the risk of overweightness was found to increase with the area-level GDP per capita among blue-collar workers only &#40;OR&#58; 1&#46;21&#44; 95&#37; CI&#58; 1&#46;03-1&#46;43&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> Beyond the well-documented socioeconomic effects operating at both the individual and the local neighbourhood levels&#44; our study suggests that broader areas of residence&#44; through their level of economic development&#44; may also have an independent impact on health-related behaviour&#46; It is therefore relevant to take into account the level of consumerism in the broad area of residence when targeting health-promotion programs&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">485 MATERIAL DISADVANTAGE AND SMOKING</span></p><p class="elsevierStylePara"> Mikko Laaksonen&#42;&#44; Ossi Rahkonen&#42;&#42;&#44; Sakari Karvonen&#42;&#42;&#42;&#44; Eero Lahelma&#42;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">&#42;Department of Public Health&#44; University of Helsinki&#44; Helsinki&#44; Finland&#46; &#42;&#42;Department of Social Policy&#44; University of Helsinki&#44; Helsinki&#44; Finland&#46; &#42;&#42;&#42;STAKES&#44; Helsinki&#44; Finland&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Introduction&#58;</span> Smoking is more prevalent among those with lower income and poorer material circumstances&#46; It has been suggested that those with lower income may smoke as a response to stress caused by economic hardship&#46; The aim of this study was to analyse differences in smoking by several measures of material disadvantage&#44; and more specifically to examine whether the association between low income and smoking can be explained by people&#39;s perceived economic disadvantage&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> The data derive from surveys conducted among the employees of the City of Helsinki in 2000 and 2001&#46; The data include 6&#46;243 respondents aged 40-60 years &#40;response rate 70&#37;&#41;&#46; Indicators of material circumstances were household income per consumption unit&#44; perceived economic difficulties and economic satisfaction&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> In both men and women&#44; smoking was more common among those with lower income&#44; those who had experienced economic difficulties and those who were dissatisfied with their economic situation&#46; Economic difficulties and economic satisfaction explained about half of income differences in men&#44; and in women the inverse income gradient practically disappeared&#46; Economic difficulties showed only a modest association with smoking among women after the level of income and economic satisfaction were controlled for&#46; Economic dissatisfaction remained strongly associated with smoking even after income and economic difficulties were taken into account&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> Smoking was associated both with income and the measures describing people&#39;s perceived economic situation&#46; Economic difficulties and economic satisfaction partly explained the association between low income and smoking&#46; Economic dissatisfaction was associated with smoking independently of income and economic difficulties&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">486 TOBACCO SMOKING AS A PREDICTOR OF COMPLICATIONS IN GENERAL SURGERY&#46; A PROSPECTIVE STUDY</span></p><p class="elsevierStylePara"> Miguel Delgado-Rodr&#237;guez&#42;&#44; Marcelino Medina-Cuadros&#42;&#42;&#44; Gabriel Mart&#237;nez-Gallego&#42;&#42;&#44; Antonio G&#243;mez-Ortega&#42;&#42;&#44; Marcial Mariscal&#42;&#44; Silvia Palma&#42;&#44; Mar&#237;a Sillero-Arenas&#42;&#42;&#42;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">&#42;Med&#46; Preventiva&#44; Univ&#46; de Ja&#233;n&#44; Ja&#233;n&#46; &#42;&#42;S&#46; de Cirug&#237;a General&#44; Hosp&#46; Ciudad de Ja&#233;n&#44; Ja&#233;n&#46; &#42;&#42;&#42;Servicio de Salud&#44; Delegaci&#243;n Provincial de Salud&#44; Ja&#233;n&#44; Espa&#241;a&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> The evidence regarding the association of tobacco smoking and adverse effects&#44; mainly nosocomial infection&#44; in hospitalized patients is conflicting&#46; We have not found any report analyzing smoking and mortality in general surgery&#46; Te objective of this report is to analyze whether tobacco smoking is related to nosocomial infection&#44; admission to ICU&#44; in-hospital death&#44; and length of stay &#40;LOS&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> This was a prospective study on 2989 patients admitted consecutively to a Service of General Surgery in the period 1992-1997&#46; Tobacco consumption was assessed by a structured questionnaire&#46; Patients were interviewed at the outpatient office or within the first 24 hours after admission&#46; Postoperative infection was classified using the Centers for Disease Control criteria&#46; Surveillance was extended to 30 days after hospital discharge&#44; to detect hospital infections clinically developed at home&#46; Relative risks and 95&#37; confidence intervals were estimated&#46; Confounding was controlled for by logistic regression analysis&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> 62 &#40;2&#46;1&#37;&#41; patients died&#44; 503 &#40;16&#46;8&#37;&#41; developed a nosocomial infection&#44; of whom 378 &#40;12&#46;6&#37;&#41; were surgical site infection &#40;SSI&#41; and 44 &#40;1&#46;5&#37;&#41; lower respiratory tract infection &#40;RTI&#41;&#46; Smoking &#40;mainly past smoking&#41; was associated to male sex&#44; advanced age&#44; chronic obstructive pulmonary disease&#44; cancer&#44; longer preoperative stay&#44; longer surgical time&#44; higher degree of wound contamination&#44; and higher ASA&#46; A long history of smoking &#40;51&#43; pack-years&#41;&#44; either past or current smoking&#44; increased postoperative admission to ICU &#40;adjusted OR &#61; 2&#46;86&#44; CI95&#44; 1&#46;21-6&#46;77&#41; and in-hospital mortality &#40;adjusted OR &#61; 2&#46;56&#44; CI95&#44; 1&#46;10-5&#46;97&#41;&#46; There was no relationship between current smoking and SSI &#40;either incisional or organ&#47;space&#41; &#40;adjusted OR &#61; 0&#46;99&#44; CI95 0&#46;72-1&#46;35&#41;&#44; whereas it was observed with past smoking &#40;adjusted OR &#61; 1&#46;46&#44; CI95&#44; 1&#46;02-2&#46;09&#41;&#46; Current smoking&#44; and in a lesser degree past smoking&#44; augmented RTI risk &#40;adjusted OR &#61; 3&#46;21&#44; CI95&#44; 1&#46;21-8&#46;51&#41;&#46; Smokers did not undergo more frequently additional surgical procedures during hospitalization&#46; In multivariate analysis LOS was similar for smokers and non-smokers&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusion&#58;</span> Smoking increases in-hospital mortality&#44; admission to ICU&#44; and lower respiratory tract infection&#44; but not SSI&#46; Deleterious effects of smoking are also observed in past smokers and they cannot be counteracted by hospital cessation programs&#46; This highlights the importance of community smoking cessation programs&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">487 PRICE AND CONSUMPTION OF TOBACCO IN SPAIN</span></p><p class="elsevierStylePara"> Esteve Fern&#225;ndez<span class="elsevierStyleSup">1</span>&#44; Anna Schiaffino<span class="elsevierStyleSup">1</span>&#44; Silvano Gallus<span class="elsevierStyleSup">2</span>&#44; Angel L&#243;pez-Nicolas<span class="elsevierStyleSup">3</span>&#44; Carlo La Vecchia<span class="elsevierStyleSup">2</span>&#44; Joy Townsend<span class="elsevierStyleSup">4</span></p><p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleSup">1</span>Cancer Prevention and Control Unit&#44; Catalan Institute of Oncology&#44; Hospitalet &#40;Barcelona&#41;&#46; <span class="elsevierStyleSup">2</span>Mario Negri Institute&#44; Milan&#46; <span class="elsevierStyleSup">3</span>Universitat Pompeu Fabra&#44; Barcelona&#46; <span class="elsevierStyleSup">4</span>Health Promotion Research Uni&#44; London School of Hygiene and Tropical Medicine&#44; London&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> In Spain&#44; there is a &#34;dual&#34; tobacco market with cigarette brands of national origin &#40;called black tobacco&#41; at relatively low prices smoked mainly by men and also foreign &#40;and national&#41; brands of blond tobacco&#46; The Spanish tobacco market has seen major transitions in these types of tobacco used in cigarettes in recent decades&#58; blond cigarettes have gradually supplanted Spain&#39;s traditionally preferred black tobacco cigarettes&#46; Another particularity of the epidemics of smoking in Spain is the recent spread &#40;beginning in the 1970&#39;s&#41; of the habit among women&#46; Among other determinants&#44; some studies have indicated that changes in cigarette price have had an appreciable impact on smoking consumption in several countries&#44; but scanty data are available for Spain&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Aim&#58;</span> To analyse the effect of price of cigarette on tobacco consumption between 1965 and 1995 in Spain&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> We used information on official legal tobacco sales from Tabacalera &#40;the former Spanish tobacco monopoly&#41; for sales of black and blond tobacco&#46; We used Tabacalera data on the average price of a 20-cigarette pack of black and blond cigarettes separately&#46; We computed the annual consumption of cigarettes per adult per day and the real price &#40;in Euro standardised to 2000&#41; of a pack of cigarettes&#46; We used multiple linear regression analysis with log transformation &#40;in the dependent and independent variables&#41; to obtain price elasticities of demand for cigarettes &#40;percentage change in cigarette consumption for a 1&#37; change in price&#41;&#44; adjusted for per capita annual gross domestic product&#46; We decided to fit separate models for each type of tobacco based&#44; to distinguish the different patterns of blond and black tobacco in Spain&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> A pack of blond cigarettes was cheaper in the 1990&#39;s than in the late 1950&#39;s&#46; At the beginning of the 1970&#39;s the real price of blond cigarettes descended markedly&#46; For blond tobacco&#44; the model explained almost all the annual variation in smoking consumption &#40;adjusted R2&#61;0&#46;98&#41;&#46; The real price of blond cigarettes was significantly and inversely associated with the blond cigarette consumption with a price elasticity of -0&#46;71 &#40;on average&#44; smoking prevalence decreased 0&#46;71&#37; for a 1&#37; increase in the real price of cigarettes&#41;&#46; For black cigarettes &#40;adjusted R2&#61;0&#46;82&#41;&#44; we found a lower but still high and significant elasticity of -0&#46;51&#46; Lack of reliable information on smuggling did not allow us to consider its influence&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> There is an inverse relation between price and consumption of cigarettes in Spain&#44; indicating that interventions at the economic level &#40;such as real increases in prices&#41; may have an important public health impact in tobacco control&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">Financial support&#58; European Commission&#44; Europe Against Cancer Programme &#40;agreement SI2&#46;32443&#44; 2001CVG2-008&#41;&#44; as part of the framework project of the European Network for Smoking Prevention</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">488 DETERMINANTS OF EXPOSURE TO ENVIRONMENTAL TOBACCO SMOKE IN A MEDITERRANEAN URBAN POPULATION</span></p><p class="elsevierStylePara"> Jorge Twose&#42;&#44; Anna Schiaffino&#42;&#44; Xavier Mart&#237;nez&#42;&#44; Montse Garc&#237;a&#42;&#44; Gloria P&#233;rez&#42;&#42;&#44; Merc&#232; Peris&#42;&#44; Esteve Fern&#225;ndez&#42;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">&#42;Cancer Prevention and Control Unit&#44; Catalan Institute of Oncology&#44; Hospitalet &#40;Barcelona&#41;&#46; &#42;&#42;Dep&#46; Sanitat i Seguretat Social&#44; Generalitat de Catalunya&#44; Barcelona&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> Although &#34;it is known&#34; that a high proportion of the population is exposed to environmental tobacco smoke &#40;ETS&#41;&#44; few attempts to estimate the actual extent of this hazard at the population level have been done&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Aim&#58;</span> The objective of this study was to assess the prevalence of exposure to ETS in general&#44; in the workplace&#44; at home&#44; and in leisure time&#44; and to describe their determinants&#44; in a sample of the population of Cornell&#224; &#40;Spain&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Subjects and methods&#58;</span> Data were obtained from the Cornell&#224; Health Interview Survey Follow-up &#40;CHIS&#46;FU&#41; study&#46; We analysed cross-sectional data on ETS exposure in non-smokers&#44; obtained from the follow-up questionnaire &#40;409 men and 605 women&#41;&#46; We calculated the prevalence of ETS exposure &#40;crude and age-stand&#41; in general and in different environments &#40;workplace&#44; home and leisure&#41;&#46; We computed age-adjusted odds ratios &#40;OR and 95&#37; confidence interval &#91;CI&#93;&#41; of ETS exposure according to self-perceived health and selected sociodemographic variables&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> The crude prevalence of ETS exposure &#40;in general&#41; were 51&#46;4&#37; &#40;46&#46;8&#37;-56&#46;1&#37;&#41; in men and 47&#46;9&#37; &#40;43&#46;9&#37;-51&#46;9&#37;&#41; in women&#46; We observed a decreasing trend of ETS exposure with age&#58; 78&#46;3&#37; &#40;68&#46;6&#37;-88&#46;0&#37;&#41; in &#60;25 years and 25&#46;4&#37; &#40;17&#46;5&#37;-33&#46;3&#37;&#41; in &#62;64 years in men and 83&#46;6&#37; &#40;73&#46;8&#37;-93&#46;4&#37;&#41; and 25&#46;0&#37; &#40;18&#46;7&#37;-31&#46;3&#37;&#41; in women&#44; respectively&#46; The age-standardised prevalence of ETS exposure was 54&#46;2&#37; &#40;49&#46;7&#37;-58&#46;8&#37;&#41; in men and 54&#46;1&#37; &#40;49&#46;9&#37;-58&#46;3&#37;&#41; in women&#46; The age-standardised prevalence rates of ETS exposure according to exposure source and sex were&#58; 25&#46;9&#37; &#40;21&#46;8&#37;-30&#46;1&#37;&#41; at home&#44; 34&#46;0&#37; &#40;23&#46;5&#37;-45&#46;6&#37;&#41; in the workplace and 55&#46;1&#37; &#40;50&#46;8&#37;-59&#46;4&#37;&#41; in leisure time in men and 34&#46;1&#37; &#40;29&#46;8&#37;-38&#46;5&#37;&#41;&#44; 30&#46;1&#37; &#40;18&#46;7&#37;-41&#46;3&#37;&#41; and 44&#46;3&#37; &#40;40&#46;5&#37;-48&#46;2&#37;&#41; in women&#46; In men&#44; there were no statistically significant differences in ETS exposure at home or workplace&#46; In leisure time ETS exposure was associated to being married &#40;OR&#61;0&#46;3&#59; 0&#46;1-0&#46;5 vs&#46; being unmarried&#41; and to alcohol intake &#62;17&#46;75 g&#47;day &#40;OR&#61;2&#46;1&#59; 1&#46;1-4&#46;0 vs&#46; absteiners&#41;&#46; In women ETS exposure at home was less prevalent among housewives &#40;OR&#61;0&#46;6&#59; 0&#46;37-0&#46;98 vs&#46; being employed&#41;&#59; in workplace&#44; ETS exposure was more prevalent among those women with universitary studies &#40;OR&#61;3&#46;3&#59; 1&#46;3-8&#46;3 vs&#46; less than primary studies&#41;&#59; and in leisure time&#44; it was related to education &#40;OR&#61;4&#46;2&#59; 1&#46;3-10&#46;1 universitary vs&#46; less than primary studies&#41;&#44; civil state &#40;OR&#61;0&#46;2&#59; 0&#46;1-0&#46;4 married vs&#46; unmarried&#41;&#44; occupation &#40;OR&#61;0&#46;5&#59; 0&#46;3-0&#46;9 housewife vs&#46; employed&#41;&#44; suboptimal health &#40;OR&#61;0&#46;3&#59; 0&#46;1-0&#46;5 vs&#46; optimal health&#41; and alcohol intake &#40;OR&#61;2&#46;7&#59; 1&#46;5-5&#46;1 &#62;17&#46;75 vs&#46; absteiners&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusion&#58;</span> Near 50&#37; of non-smokers of this study are exposed to ETS&#46; The major determinant of this exposure is age&#44; without differences by sex&#46; In men&#44; ETS exposure is related to civil state and alcohol intake&#44; while in women it is related to educational level&#44; civil state&#44; occupational status&#44; self-perceived health&#44; and alcohol intake&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">Partially funded by Fondo de Investigaci&#243;n Sanitaria &#40;PI02&#47;0261&#41; and Cornell&#224; de Llobregat City Council&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">489 DETERMINANTS OF SMOKING CESSATION IN A POPULATION-BASED COHORT FOLLOWED FOR 8 YEARS&#46; THE CORNELL&#192; HEALTH INTERVIEW SURVEY FOLLOW-UP &#40;CHIS&#46;FU&#41; STUDY</span></p><p class="elsevierStylePara"> Montse Garc&#237;a<span class="elsevierStyleSup">1</span>&#44; Anna Schiaffino<span class="elsevierStyleSup">1</span>&#44; Jorge Twose<span class="elsevierStyleSup">1</span>&#44; Esteve Salto<span class="elsevierStyleSup">2</span>&#44; Carme Borrell<span class="elsevierStyleSup">3</span>&#44; Merce Marti<span class="elsevierStyleSup">4</span>&#44; Esteve Fernandez<span class="elsevierStyleSup">1</span></p><p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleSup">1</span>Cancer Prevention and Control Unit&#44; Catalan Institute of Oncology&#44; Hospitalet &#40;Barcelona&#41;&#46; <span class="elsevierStyleSup">2</span>Dep&#46; Sanitat i Seguretat Social&#44; Generalitat de Catalunya&#44; Barcelona&#46; <span class="elsevierStyleSup">3</span>Servei d&#39;informaci&#243;&#44; Agencia de Salut P&#250;blica de Barcelona&#44; Barcelona&#46; <span class="elsevierStyleSup">4</span>Dep&#46; Salut P&#250;blica&#44; Ajuntament de Cornell&#224;&#44; Cornell&#224; de LLobregat&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> The study of the factors associated with successful quitting smoking is important to design interventions and campaigns addressed to favour smoking cessation&#46; Recent studies have identified a number of variables associated with quitting smoking &#40;i&#46;e&#46;&#44; smoking fewer cigarettes daily&#44; higher educational level&#44; past quit attempts&#44; older age&#41;&#46; This information is usually derived from cross-sectional studies&#44; and information from longitudinal designs is however scarce&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Objective&#58;</span> To study the determinants of smoking cessation in a population-based cohort in Cornell&#224; de Llobregat&#44; an industrial city in the Barcelona &#40;Spain&#41; metropolitan area&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Material and methods&#58;</span> We used data from the Cornella Health Interview Survey Follow-up Study&#46; 2&#44;500 subjects were interviewed face to face in 1994 and followed up in 2002 by a telephone interview&#46; The participation rate was 68&#46;1&#37;&#46; We included for the analysis those subjects who declared to be daily smokers at baseline and had complete follow-up with information on smoking status in 2002 &#40;n&#61;353&#41;&#46; We use Cox regression models to compute the relative risk &#40;RR&#41; of quitting &#40;and 95&#37; confidence intervals &#91;CI&#93;&#41;&#46; We considered as potential independent predictors sociodemographic variables &#40;civil status&#44; birth place&#44; occupational situation&#44; educational level and social class&#41;&#59; annual general preventive examination&#59; tobacco-related variables &#40;number of cigarettes smoked&#44; age at starting smoking&#44; physicians&#39; anti-smoking counselling&#44; motivation to quit&#44; and previous attempts to quit&#41;&#59; life-styles &#40;physical activity and alcohol consumption&#41;&#59; tobacco-related diseases and self-perceived health&#46; The analyses were carried out by sex and we adjusted all models for age&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> Of 353 daily smokers 101 quitted during the follow-up period&#44; corresponding to a cumulative quit rate of 28&#46;6&#37;&#46; The incidence quitting rate was 41&#46;7&#47;1&#44;000 person-years&#46; Men aged 65 years or older were more likely to be quitters &#40;RR&#61;3&#46;9&#59; 95&#37;CI&#58; 1&#46;2-12&#46;0&#41; as compared to men aged 15-24 years but no clear association with age was found in women&#46; The annual preventive examination was associated with quitting in men &#40;RR&#61;1&#46;9&#59; 95&#37;CI&#58; 1&#46;1-3&#46;2&#41;&#44; and in women &#40;RR&#61;2&#46;9&#59; 95&#37;1&#46;0-8&#46;5&#41;&#46; No apparent pattern of association according to civil status&#44; birth place&#44; educational level and social class&#44; physicians&#39; counselling to quit&#44; tobacco related variables&#44; motivational variables&#44; life-styles&#44; tobacco-related disease&#44; and self-perceived health were found in men neither in women&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> Age and having an annual preventive examination are the main determinants of smoking cessation in this cohort&#46; Although no clear pattern of association with educational level&#44; tobacco-related variables and other potential predictors of quitting was found in these preliminary analyses&#44; the potential effect modification role of age and other variables should further be investigated&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">This work is partially funded by Fondo de Investigaci&#243;n Sanitaria &#40;PI02&#47;0261&#41; and The Cornella City Council&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">490 SURVEILLANCE OF SECONDHAND TOBACCO SMOKE IN LATIN AMERICA&#46; COMPARISON OF LIMA&#44; PERU AND MONTEVIDEO&#44; URUGUAY</span></p><p class="elsevierStylePara"> Ana Navas-Acien<span class="elsevierStyleSup">1</span>&#44; Armando Peruga<span class="elsevierStyleSup">2</span>&#44; Adriana Blanco<span class="elsevierStyleSup">3</span>&#44; Alfonso Zavaleta<span class="elsevierStyleSup">4</span>&#44; Carmen Barco<span class="elsevierStyleSup">4</span>&#44; Beatriz Goja<span class="elsevierStyleSup">5</span>&#44; Jonathan Samet<span class="elsevierStyleSup">1</span></p><p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleSup">1</span>Institute for Global Tobacco Control&#44; Johns Hopkins Bloomberg School of Public Health&#44; Baltimore&#44; MD&#44; USA&#46; <span class="elsevierStyleSup"> 2</span>Panamerican Health Organization &#40;PAHO&#47;WHO&#41;&#44; Washington DC&#44; USA&#46; <span class="elsevierStyleSup">3</span>Intendencia Municipal&#44; Montevideo&#44; Uruguay&#46; <span class="elsevierStyleSup"> 4</span>CEDRO&#44; Lima&#44; Peru&#46; <span class="elsevierStyleSup">5</span>Facultad de Medicina&#44; Montevideo&#44; Uruguay&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Introduction&#58;</span> Secondhand smoke &#40;SHS&#41; is an involuntary exposure that poses serious health risk to passive smokers&#46; In Latin America&#44; there is insufficient information regarding range of exposure and locations where passive smoking is taking place&#46; The objective was to compare secondhand smoke exposure in Lima&#44; Peru and Montevideo&#44; Uruguay using a surveillance method for assessing SHS in public places in Latin American countries&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> Exposure was estimated by passive sampling of vapor-phase nicotine using a filter badge&#46; Both countries used similar protocols and a training workshop was held previously to the fieldwork to favor comparability&#46; In each city&#44; filters were placed for 7-14 days in 1 hospital&#44; 2 secondary schools&#44; 1 local government building&#44; the international airport&#44; and at least 10 restaurants&#47;bars&#46; The number of filters was 97 in Lima and 121 in Montevideo&#46; For quality control&#44; 10&#37; of the filters were duplicates and 10&#37; blanks&#46; Filters were checked daily or every 2 days to verify the correct placement&#44; count the number of persons and smokers&#44; the distance to the smoker nearby and to evaluate ventilation patterns&#46; After removal&#44; the airborne concentration of nicotine in &#181;g&#47;m<span class="elsevierStyleSup">3</span> was measured by gas-chromatography&#46; Since nicotine levels were markedly right-skewed&#44; medians and interquartile ranges &#40;IQR&#41; are presented&#46; For statistical comparisons between the two cities&#44; levels were log transformed and the differences in the means were estimated using a t-test with unequal variances&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> Overall&#44; median levels &#40;IQR&#41; were 0&#46;13 &#181;g&#47;m<span class="elsevierStyleSup">3</span> &#40;0&#46;01-0&#46;80&#41; in Lima and 0&#46;75 &#181;g&#47;m<span class="elsevierStyleSup">3</span> &#40;0&#46;29-1&#46;54&#41; in Montevideo&#44; and these differences were statistically significant &#40;p&#60;0&#46;001&#41;&#46; By institution&#44; levels were highly distinct between Peru and Uruguay in the hospital&#58; 0&#46;02 &#40;0&#46;01-0&#46;07&#41; and 0&#46;80 &#40;0&#46;30-1&#46;69&#41;&#44; respectively&#59; schools&#58; 0&#46;01 &#40;0&#46;01-0&#46;08&#41; and 0&#46;67 &#40;0&#46;47-0&#46;94&#41;&#59; and the local government building&#58; 0&#46;93 &#40;0&#46;20-1&#46;39&#41; and 1&#46;49 &#40;0&#46;53-2&#46;71&#41;&#46; For the airport&#44; levels in Lima 0&#46;93 &#40;0&#46;20-1&#46;29&#41;&#44; and Montevideo 1&#46;14 &#40;0&#46;73-2&#46;49&#41;&#44; were marginally different &#40;p&#61;0&#46;09&#41;&#46; Finally&#44; no differences were found in bars&#47;restaurants of the two cities&#44; 1&#46;61 &#40;0&#46;49-4&#46;98&#41; and 1&#46;49 &#40;0&#46;54-2&#46;71&#41; respectively&#44; p&#61;0&#46;72&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusion&#58;</span> Nicotine levels were minimal in schools and hospital of Lima&#44; while none of the institutions sampled in Uruguay showed levels close to zero&#46; This is possibly related to differences in legislation and its compliance&#46; The situation is of especial concern in the hospital and schools of Montevideo&#44; where 25&#37; of the samples were above moderate-high levels of exposure&#46; In local government buildings and airports&#44; there were moderate-high levels in both cities&#44; though higher in Montevideo&#46; The highest levels were found in bars&#47;restaurants&#44; with no differences between cities&#46; This surveillance study points out some priorities of action&#46; The project is being extended to five more countries in Latin America and will be used to support smoke-free policies and programs to reduce passive smoking in the region&#46;</p>"
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Comunicaciones orales : Estilos de vida: Tabaco
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    "titulo" => "Comunicaciones orales &#58; Estilos de vida&#58; Tabaco"
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    "textoCompleto" => "<p class="elsevierStylePara"> Sabado 4 de Octubre &#47; Saturday 4&#44; October<br></br> 9&#58;00&#58;00 a&#47;to 11&#58;00&#58;00</p><p class="elsevierStylePara"> Moderador&#47;Chairperson&#58;<br></br> Manel Nebot</p><p class="elsevierStylePara"><span class="elsevierStyleBold">484 TOBACCO AND ALCOHOL CONSUMPTION&#44; SEDENTARY LIFESTYLE AND OVERWEIGHTNESS IN FRANCE&#58; A MULTILEVEL ANALYSIS OF INDIVIDUAL AND AREA-LEVEL DETERMINANTS</span></p><p class="elsevierStylePara"> Basile Chaix&#44; Pierre Chauvin</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">Research Unit in Epidemiology and Information Sciences&#44; National Institute of Health and Medical Research&#44; Paris&#44; France&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Introduction&#58;</span> We investigated the effect of the level of consumerism&#44; expressed as the gross domestic product &#40;GDP&#41; per capita in the broad area of residence&#44; on the risks of smoking&#44; drinking&#44; sedentary behaviour and overweightness&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> Using a representative sample of the French population&#44; multilevel logistic models allowed us to examine the effect of the GDP on such health-related behaviour&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> After adjustment for potential confounders&#44; we found no GDP effect on the odds of being a moderate smoker&#46; Conversely&#44; the risk of being a highly-dependent smoker as opposed to a moderate consumer or an abstainer increased with the area-level GDP per capita &#40;OR&#58; 1&#46;13&#44; 95&#37; CI&#58; 1&#46;04-1&#46;23 for an increment of one standard deviation&#41;&#46; A similar pattern was found for alcohol consumption&#58; the odds of being a moderate consumer were not related to the GDP per capita&#44; but a positive effect of the GDP on the odds of being an alcohol-dependent drinker as opposed to a moderate consumer or an abstainer was found among women &#40;OR&#58; 1&#46;14&#44; 95&#37; CI&#58; 1&#46;02-1&#46;28&#41;&#46; The gap between the sexes with respect to alcohol-dependency therefore appeared to be narrower when the GDP per capita was high&#46; On the other hand&#44; the risk of overweightness was found to increase with the area-level GDP per capita among blue-collar workers only &#40;OR&#58; 1&#46;21&#44; 95&#37; CI&#58; 1&#46;03-1&#46;43&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> Beyond the well-documented socioeconomic effects operating at both the individual and the local neighbourhood levels&#44; our study suggests that broader areas of residence&#44; through their level of economic development&#44; may also have an independent impact on health-related behaviour&#46; It is therefore relevant to take into account the level of consumerism in the broad area of residence when targeting health-promotion programs&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">485 MATERIAL DISADVANTAGE AND SMOKING</span></p><p class="elsevierStylePara"> Mikko Laaksonen&#42;&#44; Ossi Rahkonen&#42;&#42;&#44; Sakari Karvonen&#42;&#42;&#42;&#44; Eero Lahelma&#42;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">&#42;Department of Public Health&#44; University of Helsinki&#44; Helsinki&#44; Finland&#46; &#42;&#42;Department of Social Policy&#44; University of Helsinki&#44; Helsinki&#44; Finland&#46; &#42;&#42;&#42;STAKES&#44; Helsinki&#44; Finland&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Introduction&#58;</span> Smoking is more prevalent among those with lower income and poorer material circumstances&#46; It has been suggested that those with lower income may smoke as a response to stress caused by economic hardship&#46; The aim of this study was to analyse differences in smoking by several measures of material disadvantage&#44; and more specifically to examine whether the association between low income and smoking can be explained by people&#39;s perceived economic disadvantage&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> The data derive from surveys conducted among the employees of the City of Helsinki in 2000 and 2001&#46; The data include 6&#46;243 respondents aged 40-60 years &#40;response rate 70&#37;&#41;&#46; Indicators of material circumstances were household income per consumption unit&#44; perceived economic difficulties and economic satisfaction&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> In both men and women&#44; smoking was more common among those with lower income&#44; those who had experienced economic difficulties and those who were dissatisfied with their economic situation&#46; Economic difficulties and economic satisfaction explained about half of income differences in men&#44; and in women the inverse income gradient practically disappeared&#46; Economic difficulties showed only a modest association with smoking among women after the level of income and economic satisfaction were controlled for&#46; Economic dissatisfaction remained strongly associated with smoking even after income and economic difficulties were taken into account&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> Smoking was associated both with income and the measures describing people&#39;s perceived economic situation&#46; Economic difficulties and economic satisfaction partly explained the association between low income and smoking&#46; Economic dissatisfaction was associated with smoking independently of income and economic difficulties&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">486 TOBACCO SMOKING AS A PREDICTOR OF COMPLICATIONS IN GENERAL SURGERY&#46; A PROSPECTIVE STUDY</span></p><p class="elsevierStylePara"> Miguel Delgado-Rodr&#237;guez&#42;&#44; Marcelino Medina-Cuadros&#42;&#42;&#44; Gabriel Mart&#237;nez-Gallego&#42;&#42;&#44; Antonio G&#243;mez-Ortega&#42;&#42;&#44; Marcial Mariscal&#42;&#44; Silvia Palma&#42;&#44; Mar&#237;a Sillero-Arenas&#42;&#42;&#42;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">&#42;Med&#46; Preventiva&#44; Univ&#46; de Ja&#233;n&#44; Ja&#233;n&#46; &#42;&#42;S&#46; de Cirug&#237;a General&#44; Hosp&#46; Ciudad de Ja&#233;n&#44; Ja&#233;n&#46; &#42;&#42;&#42;Servicio de Salud&#44; Delegaci&#243;n Provincial de Salud&#44; Ja&#233;n&#44; Espa&#241;a&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> The evidence regarding the association of tobacco smoking and adverse effects&#44; mainly nosocomial infection&#44; in hospitalized patients is conflicting&#46; We have not found any report analyzing smoking and mortality in general surgery&#46; Te objective of this report is to analyze whether tobacco smoking is related to nosocomial infection&#44; admission to ICU&#44; in-hospital death&#44; and length of stay &#40;LOS&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> This was a prospective study on 2989 patients admitted consecutively to a Service of General Surgery in the period 1992-1997&#46; Tobacco consumption was assessed by a structured questionnaire&#46; Patients were interviewed at the outpatient office or within the first 24 hours after admission&#46; Postoperative infection was classified using the Centers for Disease Control criteria&#46; Surveillance was extended to 30 days after hospital discharge&#44; to detect hospital infections clinically developed at home&#46; Relative risks and 95&#37; confidence intervals were estimated&#46; Confounding was controlled for by logistic regression analysis&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> 62 &#40;2&#46;1&#37;&#41; patients died&#44; 503 &#40;16&#46;8&#37;&#41; developed a nosocomial infection&#44; of whom 378 &#40;12&#46;6&#37;&#41; were surgical site infection &#40;SSI&#41; and 44 &#40;1&#46;5&#37;&#41; lower respiratory tract infection &#40;RTI&#41;&#46; Smoking &#40;mainly past smoking&#41; was associated to male sex&#44; advanced age&#44; chronic obstructive pulmonary disease&#44; cancer&#44; longer preoperative stay&#44; longer surgical time&#44; higher degree of wound contamination&#44; and higher ASA&#46; A long history of smoking &#40;51&#43; pack-years&#41;&#44; either past or current smoking&#44; increased postoperative admission to ICU &#40;adjusted OR &#61; 2&#46;86&#44; CI95&#44; 1&#46;21-6&#46;77&#41; and in-hospital mortality &#40;adjusted OR &#61; 2&#46;56&#44; CI95&#44; 1&#46;10-5&#46;97&#41;&#46; There was no relationship between current smoking and SSI &#40;either incisional or organ&#47;space&#41; &#40;adjusted OR &#61; 0&#46;99&#44; CI95 0&#46;72-1&#46;35&#41;&#44; whereas it was observed with past smoking &#40;adjusted OR &#61; 1&#46;46&#44; CI95&#44; 1&#46;02-2&#46;09&#41;&#46; Current smoking&#44; and in a lesser degree past smoking&#44; augmented RTI risk &#40;adjusted OR &#61; 3&#46;21&#44; CI95&#44; 1&#46;21-8&#46;51&#41;&#46; Smokers did not undergo more frequently additional surgical procedures during hospitalization&#46; In multivariate analysis LOS was similar for smokers and non-smokers&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusion&#58;</span> Smoking increases in-hospital mortality&#44; admission to ICU&#44; and lower respiratory tract infection&#44; but not SSI&#46; Deleterious effects of smoking are also observed in past smokers and they cannot be counteracted by hospital cessation programs&#46; This highlights the importance of community smoking cessation programs&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">487 PRICE AND CONSUMPTION OF TOBACCO IN SPAIN</span></p><p class="elsevierStylePara"> Esteve Fern&#225;ndez<span class="elsevierStyleSup">1</span>&#44; Anna Schiaffino<span class="elsevierStyleSup">1</span>&#44; Silvano Gallus<span class="elsevierStyleSup">2</span>&#44; Angel L&#243;pez-Nicolas<span class="elsevierStyleSup">3</span>&#44; Carlo La Vecchia<span class="elsevierStyleSup">2</span>&#44; Joy Townsend<span class="elsevierStyleSup">4</span></p><p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleSup">1</span>Cancer Prevention and Control Unit&#44; Catalan Institute of Oncology&#44; Hospitalet &#40;Barcelona&#41;&#46; <span class="elsevierStyleSup">2</span>Mario Negri Institute&#44; Milan&#46; <span class="elsevierStyleSup">3</span>Universitat Pompeu Fabra&#44; Barcelona&#46; <span class="elsevierStyleSup">4</span>Health Promotion Research Uni&#44; London School of Hygiene and Tropical Medicine&#44; London&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> In Spain&#44; there is a &#34;dual&#34; tobacco market with cigarette brands of national origin &#40;called black tobacco&#41; at relatively low prices smoked mainly by men and also foreign &#40;and national&#41; brands of blond tobacco&#46; The Spanish tobacco market has seen major transitions in these types of tobacco used in cigarettes in recent decades&#58; blond cigarettes have gradually supplanted Spain&#39;s traditionally preferred black tobacco cigarettes&#46; Another particularity of the epidemics of smoking in Spain is the recent spread &#40;beginning in the 1970&#39;s&#41; of the habit among women&#46; Among other determinants&#44; some studies have indicated that changes in cigarette price have had an appreciable impact on smoking consumption in several countries&#44; but scanty data are available for Spain&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Aim&#58;</span> To analyse the effect of price of cigarette on tobacco consumption between 1965 and 1995 in Spain&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> We used information on official legal tobacco sales from Tabacalera &#40;the former Spanish tobacco monopoly&#41; for sales of black and blond tobacco&#46; We used Tabacalera data on the average price of a 20-cigarette pack of black and blond cigarettes separately&#46; We computed the annual consumption of cigarettes per adult per day and the real price &#40;in Euro standardised to 2000&#41; of a pack of cigarettes&#46; We used multiple linear regression analysis with log transformation &#40;in the dependent and independent variables&#41; to obtain price elasticities of demand for cigarettes &#40;percentage change in cigarette consumption for a 1&#37; change in price&#41;&#44; adjusted for per capita annual gross domestic product&#46; We decided to fit separate models for each type of tobacco based&#44; to distinguish the different patterns of blond and black tobacco in Spain&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> A pack of blond cigarettes was cheaper in the 1990&#39;s than in the late 1950&#39;s&#46; At the beginning of the 1970&#39;s the real price of blond cigarettes descended markedly&#46; For blond tobacco&#44; the model explained almost all the annual variation in smoking consumption &#40;adjusted R2&#61;0&#46;98&#41;&#46; The real price of blond cigarettes was significantly and inversely associated with the blond cigarette consumption with a price elasticity of -0&#46;71 &#40;on average&#44; smoking prevalence decreased 0&#46;71&#37; for a 1&#37; increase in the real price of cigarettes&#41;&#46; For black cigarettes &#40;adjusted R2&#61;0&#46;82&#41;&#44; we found a lower but still high and significant elasticity of -0&#46;51&#46; Lack of reliable information on smuggling did not allow us to consider its influence&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> There is an inverse relation between price and consumption of cigarettes in Spain&#44; indicating that interventions at the economic level &#40;such as real increases in prices&#41; may have an important public health impact in tobacco control&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">Financial support&#58; European Commission&#44; Europe Against Cancer Programme &#40;agreement SI2&#46;32443&#44; 2001CVG2-008&#41;&#44; as part of the framework project of the European Network for Smoking Prevention</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">488 DETERMINANTS OF EXPOSURE TO ENVIRONMENTAL TOBACCO SMOKE IN A MEDITERRANEAN URBAN POPULATION</span></p><p class="elsevierStylePara"> Jorge Twose&#42;&#44; Anna Schiaffino&#42;&#44; Xavier Mart&#237;nez&#42;&#44; Montse Garc&#237;a&#42;&#44; Gloria P&#233;rez&#42;&#42;&#44; Merc&#232; Peris&#42;&#44; Esteve Fern&#225;ndez&#42;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">&#42;Cancer Prevention and Control Unit&#44; Catalan Institute of Oncology&#44; Hospitalet &#40;Barcelona&#41;&#46; &#42;&#42;Dep&#46; Sanitat i Seguretat Social&#44; Generalitat de Catalunya&#44; Barcelona&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> Although &#34;it is known&#34; that a high proportion of the population is exposed to environmental tobacco smoke &#40;ETS&#41;&#44; few attempts to estimate the actual extent of this hazard at the population level have been done&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Aim&#58;</span> The objective of this study was to assess the prevalence of exposure to ETS in general&#44; in the workplace&#44; at home&#44; and in leisure time&#44; and to describe their determinants&#44; in a sample of the population of Cornell&#224; &#40;Spain&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Subjects and methods&#58;</span> Data were obtained from the Cornell&#224; Health Interview Survey Follow-up &#40;CHIS&#46;FU&#41; study&#46; We analysed cross-sectional data on ETS exposure in non-smokers&#44; obtained from the follow-up questionnaire &#40;409 men and 605 women&#41;&#46; We calculated the prevalence of ETS exposure &#40;crude and age-stand&#41; in general and in different environments &#40;workplace&#44; home and leisure&#41;&#46; We computed age-adjusted odds ratios &#40;OR and 95&#37; confidence interval &#91;CI&#93;&#41; of ETS exposure according to self-perceived health and selected sociodemographic variables&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> The crude prevalence of ETS exposure &#40;in general&#41; were 51&#46;4&#37; &#40;46&#46;8&#37;-56&#46;1&#37;&#41; in men and 47&#46;9&#37; &#40;43&#46;9&#37;-51&#46;9&#37;&#41; in women&#46; We observed a decreasing trend of ETS exposure with age&#58; 78&#46;3&#37; &#40;68&#46;6&#37;-88&#46;0&#37;&#41; in &#60;25 years and 25&#46;4&#37; &#40;17&#46;5&#37;-33&#46;3&#37;&#41; in &#62;64 years in men and 83&#46;6&#37; &#40;73&#46;8&#37;-93&#46;4&#37;&#41; and 25&#46;0&#37; &#40;18&#46;7&#37;-31&#46;3&#37;&#41; in women&#44; respectively&#46; The age-standardised prevalence of ETS exposure was 54&#46;2&#37; &#40;49&#46;7&#37;-58&#46;8&#37;&#41; in men and 54&#46;1&#37; &#40;49&#46;9&#37;-58&#46;3&#37;&#41; in women&#46; The age-standardised prevalence rates of ETS exposure according to exposure source and sex were&#58; 25&#46;9&#37; &#40;21&#46;8&#37;-30&#46;1&#37;&#41; at home&#44; 34&#46;0&#37; &#40;23&#46;5&#37;-45&#46;6&#37;&#41; in the workplace and 55&#46;1&#37; &#40;50&#46;8&#37;-59&#46;4&#37;&#41; in leisure time in men and 34&#46;1&#37; &#40;29&#46;8&#37;-38&#46;5&#37;&#41;&#44; 30&#46;1&#37; &#40;18&#46;7&#37;-41&#46;3&#37;&#41; and 44&#46;3&#37; &#40;40&#46;5&#37;-48&#46;2&#37;&#41; in women&#46; In men&#44; there were no statistically significant differences in ETS exposure at home or workplace&#46; In leisure time ETS exposure was associated to being married &#40;OR&#61;0&#46;3&#59; 0&#46;1-0&#46;5 vs&#46; being unmarried&#41; and to alcohol intake &#62;17&#46;75 g&#47;day &#40;OR&#61;2&#46;1&#59; 1&#46;1-4&#46;0 vs&#46; absteiners&#41;&#46; In women ETS exposure at home was less prevalent among housewives &#40;OR&#61;0&#46;6&#59; 0&#46;37-0&#46;98 vs&#46; being employed&#41;&#59; in workplace&#44; ETS exposure was more prevalent among those women with universitary studies &#40;OR&#61;3&#46;3&#59; 1&#46;3-8&#46;3 vs&#46; less than primary studies&#41;&#59; and in leisure time&#44; it was related to education &#40;OR&#61;4&#46;2&#59; 1&#46;3-10&#46;1 universitary vs&#46; less than primary studies&#41;&#44; civil state &#40;OR&#61;0&#46;2&#59; 0&#46;1-0&#46;4 married vs&#46; unmarried&#41;&#44; occupation &#40;OR&#61;0&#46;5&#59; 0&#46;3-0&#46;9 housewife vs&#46; employed&#41;&#44; suboptimal health &#40;OR&#61;0&#46;3&#59; 0&#46;1-0&#46;5 vs&#46; optimal health&#41; and alcohol intake &#40;OR&#61;2&#46;7&#59; 1&#46;5-5&#46;1 &#62;17&#46;75 vs&#46; absteiners&#41;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusion&#58;</span> Near 50&#37; of non-smokers of this study are exposed to ETS&#46; The major determinant of this exposure is age&#44; without differences by sex&#46; In men&#44; ETS exposure is related to civil state and alcohol intake&#44; while in women it is related to educational level&#44; civil state&#44; occupational status&#44; self-perceived health&#44; and alcohol intake&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">Partially funded by Fondo de Investigaci&#243;n Sanitaria &#40;PI02&#47;0261&#41; and Cornell&#224; de Llobregat City Council&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">489 DETERMINANTS OF SMOKING CESSATION IN A POPULATION-BASED COHORT FOLLOWED FOR 8 YEARS&#46; THE CORNELL&#192; HEALTH INTERVIEW SURVEY FOLLOW-UP &#40;CHIS&#46;FU&#41; STUDY</span></p><p class="elsevierStylePara"> Montse Garc&#237;a<span class="elsevierStyleSup">1</span>&#44; Anna Schiaffino<span class="elsevierStyleSup">1</span>&#44; Jorge Twose<span class="elsevierStyleSup">1</span>&#44; Esteve Salto<span class="elsevierStyleSup">2</span>&#44; Carme Borrell<span class="elsevierStyleSup">3</span>&#44; Merce Marti<span class="elsevierStyleSup">4</span>&#44; Esteve Fernandez<span class="elsevierStyleSup">1</span></p><p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleSup">1</span>Cancer Prevention and Control Unit&#44; Catalan Institute of Oncology&#44; Hospitalet &#40;Barcelona&#41;&#46; <span class="elsevierStyleSup">2</span>Dep&#46; Sanitat i Seguretat Social&#44; Generalitat de Catalunya&#44; Barcelona&#46; <span class="elsevierStyleSup">3</span>Servei d&#39;informaci&#243;&#44; Agencia de Salut P&#250;blica de Barcelona&#44; Barcelona&#46; <span class="elsevierStyleSup">4</span>Dep&#46; Salut P&#250;blica&#44; Ajuntament de Cornell&#224;&#44; Cornell&#224; de LLobregat&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Background&#58;</span> The study of the factors associated with successful quitting smoking is important to design interventions and campaigns addressed to favour smoking cessation&#46; Recent studies have identified a number of variables associated with quitting smoking &#40;i&#46;e&#46;&#44; smoking fewer cigarettes daily&#44; higher educational level&#44; past quit attempts&#44; older age&#41;&#46; This information is usually derived from cross-sectional studies&#44; and information from longitudinal designs is however scarce&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Objective&#58;</span> To study the determinants of smoking cessation in a population-based cohort in Cornell&#224; de Llobregat&#44; an industrial city in the Barcelona &#40;Spain&#41; metropolitan area&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Material and methods&#58;</span> We used data from the Cornella Health Interview Survey Follow-up Study&#46; 2&#44;500 subjects were interviewed face to face in 1994 and followed up in 2002 by a telephone interview&#46; The participation rate was 68&#46;1&#37;&#46; We included for the analysis those subjects who declared to be daily smokers at baseline and had complete follow-up with information on smoking status in 2002 &#40;n&#61;353&#41;&#46; We use Cox regression models to compute the relative risk &#40;RR&#41; of quitting &#40;and 95&#37; confidence intervals &#91;CI&#93;&#41;&#46; We considered as potential independent predictors sociodemographic variables &#40;civil status&#44; birth place&#44; occupational situation&#44; educational level and social class&#41;&#59; annual general preventive examination&#59; tobacco-related variables &#40;number of cigarettes smoked&#44; age at starting smoking&#44; physicians&#39; anti-smoking counselling&#44; motivation to quit&#44; and previous attempts to quit&#41;&#59; life-styles &#40;physical activity and alcohol consumption&#41;&#59; tobacco-related diseases and self-perceived health&#46; The analyses were carried out by sex and we adjusted all models for age&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> Of 353 daily smokers 101 quitted during the follow-up period&#44; corresponding to a cumulative quit rate of 28&#46;6&#37;&#46; The incidence quitting rate was 41&#46;7&#47;1&#44;000 person-years&#46; Men aged 65 years or older were more likely to be quitters &#40;RR&#61;3&#46;9&#59; 95&#37;CI&#58; 1&#46;2-12&#46;0&#41; as compared to men aged 15-24 years but no clear association with age was found in women&#46; The annual preventive examination was associated with quitting in men &#40;RR&#61;1&#46;9&#59; 95&#37;CI&#58; 1&#46;1-3&#46;2&#41;&#44; and in women &#40;RR&#61;2&#46;9&#59; 95&#37;1&#46;0-8&#46;5&#41;&#46; No apparent pattern of association according to civil status&#44; birth place&#44; educational level and social class&#44; physicians&#39; counselling to quit&#44; tobacco related variables&#44; motivational variables&#44; life-styles&#44; tobacco-related disease&#44; and self-perceived health were found in men neither in women&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusions&#58;</span> Age and having an annual preventive examination are the main determinants of smoking cessation in this cohort&#46; Although no clear pattern of association with educational level&#44; tobacco-related variables and other potential predictors of quitting was found in these preliminary analyses&#44; the potential effect modification role of age and other variables should further be investigated&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleItalic">This work is partially funded by Fondo de Investigaci&#243;n Sanitaria &#40;PI02&#47;0261&#41; and The Cornella City Council&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">490 SURVEILLANCE OF SECONDHAND TOBACCO SMOKE IN LATIN AMERICA&#46; COMPARISON OF LIMA&#44; PERU AND MONTEVIDEO&#44; URUGUAY</span></p><p class="elsevierStylePara"> Ana Navas-Acien<span class="elsevierStyleSup">1</span>&#44; Armando Peruga<span class="elsevierStyleSup">2</span>&#44; Adriana Blanco<span class="elsevierStyleSup">3</span>&#44; Alfonso Zavaleta<span class="elsevierStyleSup">4</span>&#44; Carmen Barco<span class="elsevierStyleSup">4</span>&#44; Beatriz Goja<span class="elsevierStyleSup">5</span>&#44; Jonathan Samet<span class="elsevierStyleSup">1</span></p><p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleSup">1</span>Institute for Global Tobacco Control&#44; Johns Hopkins Bloomberg School of Public Health&#44; Baltimore&#44; MD&#44; USA&#46; <span class="elsevierStyleSup"> 2</span>Panamerican Health Organization &#40;PAHO&#47;WHO&#41;&#44; Washington DC&#44; USA&#46; <span class="elsevierStyleSup">3</span>Intendencia Municipal&#44; Montevideo&#44; Uruguay&#46; <span class="elsevierStyleSup"> 4</span>CEDRO&#44; Lima&#44; Peru&#46; <span class="elsevierStyleSup">5</span>Facultad de Medicina&#44; Montevideo&#44; Uruguay&#46;</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Introduction&#58;</span> Secondhand smoke &#40;SHS&#41; is an involuntary exposure that poses serious health risk to passive smokers&#46; In Latin America&#44; there is insufficient information regarding range of exposure and locations where passive smoking is taking place&#46; The objective was to compare secondhand smoke exposure in Lima&#44; Peru and Montevideo&#44; Uruguay using a surveillance method for assessing SHS in public places in Latin American countries&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Methods&#58;</span> Exposure was estimated by passive sampling of vapor-phase nicotine using a filter badge&#46; Both countries used similar protocols and a training workshop was held previously to the fieldwork to favor comparability&#46; In each city&#44; filters were placed for 7-14 days in 1 hospital&#44; 2 secondary schools&#44; 1 local government building&#44; the international airport&#44; and at least 10 restaurants&#47;bars&#46; The number of filters was 97 in Lima and 121 in Montevideo&#46; For quality control&#44; 10&#37; of the filters were duplicates and 10&#37; blanks&#46; Filters were checked daily or every 2 days to verify the correct placement&#44; count the number of persons and smokers&#44; the distance to the smoker nearby and to evaluate ventilation patterns&#46; After removal&#44; the airborne concentration of nicotine in &#181;g&#47;m<span class="elsevierStyleSup">3</span> was measured by gas-chromatography&#46; Since nicotine levels were markedly right-skewed&#44; medians and interquartile ranges &#40;IQR&#41; are presented&#46; For statistical comparisons between the two cities&#44; levels were log transformed and the differences in the means were estimated using a t-test with unequal variances&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Results&#58;</span> Overall&#44; median levels &#40;IQR&#41; were 0&#46;13 &#181;g&#47;m<span class="elsevierStyleSup">3</span> &#40;0&#46;01-0&#46;80&#41; in Lima and 0&#46;75 &#181;g&#47;m<span class="elsevierStyleSup">3</span> &#40;0&#46;29-1&#46;54&#41; in Montevideo&#44; and these differences were statistically significant &#40;p&#60;0&#46;001&#41;&#46; By institution&#44; levels were highly distinct between Peru and Uruguay in the hospital&#58; 0&#46;02 &#40;0&#46;01-0&#46;07&#41; and 0&#46;80 &#40;0&#46;30-1&#46;69&#41;&#44; respectively&#59; schools&#58; 0&#46;01 &#40;0&#46;01-0&#46;08&#41; and 0&#46;67 &#40;0&#46;47-0&#46;94&#41;&#59; and the local government building&#58; 0&#46;93 &#40;0&#46;20-1&#46;39&#41; and 1&#46;49 &#40;0&#46;53-2&#46;71&#41;&#46; For the airport&#44; levels in Lima 0&#46;93 &#40;0&#46;20-1&#46;29&#41;&#44; and Montevideo 1&#46;14 &#40;0&#46;73-2&#46;49&#41;&#44; were marginally different &#40;p&#61;0&#46;09&#41;&#46; Finally&#44; no differences were found in bars&#47;restaurants of the two cities&#44; 1&#46;61 &#40;0&#46;49-4&#46;98&#41; and 1&#46;49 &#40;0&#46;54-2&#46;71&#41; respectively&#44; p&#61;0&#46;72&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conclusion&#58;</span> Nicotine levels were minimal in schools and hospital of Lima&#44; while none of the institutions sampled in Uruguay showed levels close to zero&#46; This is possibly related to differences in legislation and its compliance&#46; The situation is of especial concern in the hospital and schools of Montevideo&#44; where 25&#37; of the samples were above moderate-high levels of exposure&#46; In local government buildings and airports&#44; there were moderate-high levels in both cities&#44; though higher in Montevideo&#46; The highest levels were found in bars&#47;restaurants&#44; with no differences between cities&#46; This surveillance study points out some priorities of action&#46; The project is being extended to five more countries in Latin America and will be used to support smoke-free policies and programs to reduce passive smoking in the region&#46;</p>"
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