Science of the Total Environment 470–471 (2014) 1189–1196

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Factors associated with second-hand smoke exposure in non-smokingpregnant women in Spain: Self-reported exposure andurinary cotinine levels

Juan J. Aurrekoetxea a,b,c,⁎, Mario Murcia d,e, Marisa Rebagliato d,e, Ana Fernández-Somoano d,f,Ane Miren Castilla d,g, Mònica Guxens d,h,i, María José López d,j,k, Aitana Lertxundi b,c,d, Mercedes Espada g,Adonina Tardón d,f, Ferran Ballester d,e,l, Loreto Santa-Marina a,c,d

a Public Health Department, Basque Government, San Sebastian, Spainb University of the Basque Country (UPV/EHU), San Sebastian, Spainc Health Research Institute (BIODONOSTIA), San Sebastian, Spaind Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Spaine Center for Public Health Research (CSISP), Valencia, Spainf Department of Preventive Medicine and Public Health, University of Oviedo, Oviedo, Spaing Public Health Laboratory, Basque Government, Spainh Hospital del Mar Research Institute (IMIM), Barcelona, Spaini Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spainj Public Health Agency of Barcelona, Barcelona, Spaink Sant Pau Institute of Biomedical Research (IIB Sant Pau), Barcelona, Spainl Department of Nursing, University of Valencia, Valencia, Spain

H I G H L I G H T S

• More than half non-smoker pregnant women were regularly exposed to SHS.• All studied sources of SHS exposure increased UC levels.• Passive smoking at home was the source of SHS with the greatest impact on UC levels.• Legal changes in Spain were followed by a SHS exposure reduction in public spaces.• Public health priority should focus to control SHS exposure in private indoor places.

⁎ Corresponding author at: Departamento de Salud delE-mail addresses: jj.aurreko@gmail.com (J.J. Aurrekoet

ane_m2002@yahoo.es (A.M. Castilla), mguxens@creal.catatardon@uniovi.es (A. Tardón), ballester_fer@gva.es (F. Ba

0048-9697/$ – see front matter © 2013 Elsevier B.V. All rihttp://dx.doi.org/10.1016/j.scitotenv.2013.10.110

a b s t r a c t

a r t i c l e i n f o

Article history:Received 17 July 2013Received in revised form 19 October 2013Accepted 29 October 2013Available online 16 November 2013

Keywords:Pregnant womenPassive smokingSHSCotinineBiological monitoring

The aim of this study was to evaluate the main sources of and sociodemographic factors associated with second-hand smoke (SHS) exposure, assessed both by questionnaire and by urinary cotinine (UC) levels, in non-smokingpregnant women.We conducted a cross-sectional study in pregnant women from 4 different regions in Spain. Atotal of 1783 non-smoking pregnant women completed a questionnaire about their previous smoking habit andSHS exposure in their 3rd trimester of pregnancy and provided a urine sample for measuring UC levels. We usedlogistic regression models to assess the relationship between several sociodemographic variables and some po-tential sources of SHS exposure. In addition, we analysed the association of several sociodemographic variablesand the SHS exposure according to UC levels, using Tobit regression analysis. More than half of women (55.5%)were exposed to SHS in their 3rd trimester of pregnancy. The following variables were associated with SHS ex-posure: having smoked previously, low educational level, and being primiparous. Data collection after the firstlaw banning smoking in public places was associated with lower risk of SHS exposure in restaurants and atwork. UC levels were higher among women exposed to more than one source. Having a partner who smokedat home was the source of SHS with the greatest impact on UC levels, followed by having a partner who smokedbut not at home, other people smoking in the household, being exposed during leisure time, at work and at

Gobierno Vasco, C/Sancho el Sabio 35, 20.010 San Sebastián, Spain. Tel.: +34 943 023003; fax: +34 943 023093.xea), murcia_mar@gva.es (M. Murcia), rebagliato_mar@gva.es (M. Rebagliato), capua.uo@uniovi.es (A. Fernández-Somoano),(M. Guxens), mjlopez@aspb.cat (M.J. López), aitana.lertxundi@ehu.es (A. Lertxundi), metabobi-san@ej-gv.es (M. Espada),llester), ambien4ss-san@ej-gv.es (L. Santa-Marina).

ghts reserved.

1190 J.J. Aurrekoetxea et al. / Science of the Total Environment 470–471 (2014) 1189–1196

restaurants. The most important source of SHS exposure was exposure at home. Prevention of SHS exposureshould be addressed not only with pregnant women but also with their families.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Maternal exposure to secondhand smoke (SHS) during pregnancy isassociatedwith several adverse reproductive outcomes, such as infertil-ity, premature rupture of the membranes, placental abruption andplacenta previa, reduced birthweight and foetal growth, as well aswith higher rates of sudden infant death syndrome, reduced levels ofoffspring cognitive development and suggestive evidence for increasedrisk of childhood cancer (CDC, 2006; Iñiguez et al., 2012; Salmasi et al.,2010), in addition to chronic respiratory illness and cancer risks formother (CDC, 2004). Öberg et al. (2011) estimated 603,000 deathsattributable to SHS in 2004 worldwide, mainly due to ischemic heartdisease in adults (379,000) and lower respiratory infections in childrenabove 5 years (165,000).

TheWHO (2012) report for EU27 countries identified great variabil-ity in SHS exposure at home among pregnant women across the re-gions, ranging from 4 to 65%. Socioeconomic and other factors, such asweather or cultural differences, and the criteria for defining SHSexposure could explain these discrepancies. Many authors consideredthat self-reported assessments of SHS exposure would be inaccurate(Benowitz, 1996; De Chazeron et al., 2007; Woodward and Al-Delaimy, 1999). Cotinine is the best available biomarker of SHS expo-sure since it is accurate and objective. In fact, it has been proposed bythose authors as a tool to validate the information provided in question-naires (Benowitz, 1996; De Chazeron et al., 2007; Woodward and Al-Delaimy, 1999). Benowitz et al. (2009) considered that urinary cotinine(UC) measurement corrected for creatinine concentration was the bestpredictor of the cotinine plasma level during low-level nicotineexposure. So far, relatively few studies have assessed SHS exposure inpregnant women according to different settings, and even fewer haveassessed the exposure using a biomarker such as cotinine (Ashfordet al., 2010; Chiu et al., 2008; De Chazeron et al., 2007; Eiden et al.,2011; Jhun et al., 2010; Kvalvik et al., 2012; Paek et al., 2009;Rebagliato et al., 1995; Vardavas et al., 2013).

In Spain, a law of 1998 limited smoking at work and in public trans-port. Thefirst overall legislation in Spain against smoking atwork and inpublic places with the objective of reducing SHS exposure was imple-mented in January 2006 (Law 28/2005). It banned smoking at workand in cultural centres. In bars or pubs and restaurants, it allowedsmoking in rooms specifically enabled. However, this law allowedsmoking in the whole place when its total area was less than 100 m2.A second law (Law 42/2010) was implemented in January 2011, afterthe end of data collecting of this study, extending the smoking ban toall enclosed public places.

The objectives of this studywere: (1) to estimate prevalence and themain sources of SHS exposure in non-smoking pregnant women in fourdifferent Spanish areas; (2) to identify the sociodemographic factorsassociatedwith each source of SHS exposure; (3) to estimate the associ-ation of the sociodemographic factors and the different SHS exposuresources with the UC levels; and (4) to evaluate the influence of theoverall first law against smoking.

2. Methods

2.1. Study population

Population-based birth cohortswere established as part of the INMA–

INfancia y Medio Ambiente [Environment and Childhood] – Project inseveral areas of Spain following a common protocol (Guxens et al.,2012). Pregnant women were recruited during their first visit to the

obstetrician for pregnancy care (10–13th week of pregnancy). Thestudy was conducted in the corresponding health centres in four healthareas in Spain (Asturias, Gipuzkoa, Sabadell and Valencia) betweenMarch 2004 and June 2008. This cross-sectional study analyses thedata on SHS exposure in non-smoking pregnant women measuredduring their visit in the 3rd trimester of pregnancy.

Pregnant women were enrolled during the first trimester ofpregnancy at public primary health care centres or public hospitals, de-pending on the region, providing they fulfilled the inclusion criteria(≥16 years of age, intention to deliver at the reference hospital, noproblems of communication, singleton pregnancy, no assisted concep-tion); 99.5% of Spaniards have public health insurance, and 70–90% ofwomen use public health services during pregnancy (Regidor et al.,2008). Of all women invited, 56% agreed to participate, 54% in Valencia,60% in Sabadell, 45% in Asturias and 68% in Gipuzkoa. Of the 2644women who agreed to participate in the study, a total of 2263 womencompleted a questionnaire of their smoking habit and provided aurine sample for UC analysis while attending a check-up during the3rd trimester of their pregnancy (Aurrekoetxea et al., 2013). At thatstage, 418 of these women self-reported regular (381) or occasional(37) smoking, and as a result they were excluded from the analysis.Among those who reported not to smoke, 62 had cotinine levels higherthan 100 ng/ml, level which has been proposed as a cut-off fordistinguishing between smoking and non-smoking pregnant women(England et al., 2007). Furthermore, this cut-off value was found to bereliable for the present population, with high levels of exposure(Aurrekoetxea et al., 2013). These 62 women were also excluded fromthe analysis, as they were considered potential misreporters, leaving afinal sample of 1783 non-smoking pregnant women. All women partic-ipating in the study signed an informed consent form and the EthicalCommittees of the centres involved in the study approved the researchprotocol.

2.2. Self-reporting of SHS exposure

Current tobacco consumption, smoking history, and exposure to SHSwere assessed by a specific questionnaire filled out at 3rd trimester ofpregnancy. It was considered that participants were exposed to SHSwhen they reported exposure in any of the following environments:at work, at home, or in leisure time sites (restaurants, bars, pubs orother homes). Exposure at home was defined when their partner,other people living in the same house, or regular visitors (≥2 timesper week) smoked at home. SHS at workplace was assessed in the fol-lowing four categories: ‘nothing’, ‘little’, ‘quite a bit’ and ‘a lot’. Motherswho answered ‘quite a bit’ or ‘a lot’were classified as exposed. Exposedat restaurants and at other leisure time sites included thosewomen thatreported to be exposed in some of these places at least twice a week.

We analysed whether women had any SHS exposure (yes or no), aswell as the number of sources, that ranged from 0 to 3, according to thereported sites of exposure: at home, at work, and in restaurants and/orin other leisure time sites.

2.3. Assessment of urinary cotinine

Urine samples were collected at the visit to the obstetrician duringthe 3rd trimester of pregnancy. Urine sampling started in March 2004and ended in December 2005 for Valencia; from November 2004 toJanuary 2007 for Sabadell; from November 2004 to December 2007for Asturias; and from October 2006 to June 2008 for Gipuzkoa. Urinesamples were collected during the morning in 100 ml polyethylene

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containers and stored at −20 °C. One aliquot of the sample by partici-pant was sent to the Public Health Laboratory of Bilbao (Spain) to beanalysed. All urine samples were stored for a minimum of one yearand a maximum of five years before analysis. Laboratory method forUC quantification was described in a previous paper (Aurrekoetxeaet al., 2013). The quantification limit was 4.0 ng/ml.

2.4. Other variables

The women were interviewed at the 1st and the 3rd trimester ofpregnancy to obtain information about their sociodemographic charac-teristics and lifestyle. The following variables were taken into account:age of women at the beginning of pregnancy; maternal height andpre-pregnancy weight were used to calculate the body mass index(BMI) [kg/m2]; parity; country of birth (grouped in three categories:Spain, Latin America and others); maternal education (low: 11 yearsor less of school education; medium: from 12 to 14 years of school

Table 1Description of the sample and variables of interest in non-smoking pregnant women from INM

N %a SHS overall %b,c

Total 1783 100 55.5CohortAsturias 328 18.4 40.9⁎

Gipuzkoa 469 26.3 52.2Sabadell 481 27.0 58.0Valencia 505 28.3 65.7

Age (years)b25 99 5.6 68.7⁎

25–29 547 30.7 59.330–34 798 44.8 55.2≥35 338 19.0 46.1

Social classh

I–II (highest) 630 35.4 50.2⁎

III 456 25.6 56.0IV–V (lowest) 696 39.1 59.9

Level of educationUniversity 701 39.3 51.6⁎

Secondary 716 40.2 54.4Primary or less 364 20.4 65.3

Pre-pregnancy BMI (kg/m2)b18.5 (underweight) 72 4.0 65.3⁎

18.5–25 (healthy weight) 1260 70.7 54.325–30 (overweight) 317 17.8 55.2N30 (obesity) 134 7.5 61.4

Parity0 1009 56.4 59.1⁎

1 659 37.1 49.5≥2 115 6.4 57.4

Country of birthSpain 1619 91.0 55.6Latin America 110 6.2 51.4Others 50 2.8 61.2

Ever smoked during her lifei

No 873 49.0 50.8⁎

Yes 910 51.0 59.9Smoked at the beginning of pregnancyi

No 1510 84.7 52.9⁎

Yes 273 15.3 69.6Smoked at 1st trimester of pregnancyi

No 1758 98.6 55.1⁎

Yes 21 1.2 81.0Data collection after banning smoking in public placesNo 876 49.4 61.8⁎

Yes 897 50.6 49.3

a Percentage by column.b Percentage of women exposed to SHS with respect to the total exposed and not exposed tc ⁎: χ2 test p b 0.05; other: non-significant differences.d Partner and other people than the partner.e Bars, pubs, other homes or restaurants.f Geometric means (95% CI).g ⁎: Analysis of variance p b 0.05/⁎⁎: p for trend b 0.05; other: non-significant differences.h Social class, considering the most privileged from each woman or her partner.i Occasional or regular consumption of tobacco.

education; high: university or technical college degree); socioeconomicstatus was defined according to the most privileged occupation of themother or the father during pregnancy. Itwas defined using the Spanishadaptation of the British Registrar General classification system follow-ing the methodology proposed by the Spanish Epidemiological Society(Domingo-Salvany et al., 2000), and grouped in three categories: highsocial class (classes I and II), medium social class (class III), and low so-cial class (classes IV and V). A dummy variable was created to identifyurine samples that were collected after the implementation of the firstlaw against smoking in public places (January 2006).

2.5. Statistical methods

Maternal characteristics and their association with the severalsources of exposure to SHS were described using percentages andcontrasted using the Chi-square test. Differences in UC according toma-ternal characteristics and the sources of exposure to SHS were

A project cohorts in relation to SHS exposure and UC mean levels (Spain 2004–2008).

At home %b,c,d At work %b,c At leisure time %b,c,e Cotinine (μg/g creatinine)f,g

24.7 9.8 38.5 7.6 (7.3–7.9)

21.6⁎ 7.9⁎ 21.3⁎ 7.1 (6.4–7.8)11.3 4.7 46.9 8.0 (7.5–8.6)28.8 9.8 36.5 7.5 (6.9–8.2)35.5 15.9 43.8 7.7 (7.1–7.9)

42.4⁎ 12.1 41.4⁎ 9.8 (8.0–12.1)⁎/⁎⁎

27.5 9.1 41.2 8.3 (7.8–9.0)22.5 10.4 39.2 7.2 (6.8–7.6)20.5 8.9 31.7 7.0 (6.4–7.7)

15.3⁎ 7.9 38.0 6.9 (6.4–7.3)⁎/⁎⁎

24.6 10.7 39.9 7.3 (6.8–7.9)33.4 10.9 38.1 8.6 (8.0–9.2)

14.9⁎ 7.3⁎ 41.9 6.9 (6.5–7.3)⁎/⁎⁎

27.6 9.8 35.3 7.8 (7.3–7.9)38.2 14.8 40.1 8.9 (8.0–9.8)

44.4⁎ 12.5 37.5 9.8 (7.9–12.2)24.1 9.2 38.2 7.6 (7.2–8.0)22.7 11.4 38.8 7.5 (6.8–8.2)24.6 10.5 41.4 7.0 (5.9–8.3)

27.6⁎ 10.8 40.6 8.1 (7.7–8.5)⁎/⁎⁎

19.9 8.2 34.6 6.9 (6.5–7.4)27.0 9.6 42.6 7.6 (6.5–9.1)

24.2⁎ 9.4 39.4 7.6 (7.3–7.9)25.5 15.5 27.5 7.5 (6.3–8.8)42.0 12.0 32.7 8.9 (6.7–11.9)

19.4⁎ 9.4 35.1⁎ 6.9 (6.5–7.3)⁎

29.8 10.2 41.7 8.4 (7.9–8.9)

21.4⁎ 9.4 37.7 7.2 (6.9–7.5)⁎

42.9 12.1 42.9 10.6 (9.4–11.8)

24.5⁎ 9.8 38.4 7.6 (7.3–7.9)⁎

47.6 14.3 42.9 11.4 (7.5–17.4)

32.5⁎ 13.9⁎ 39.7 7.9 (7.4–8.4)17.1 5.8 37.4 7.4 (7.0–7.8)

o SHS in each file.

Table 2UCC geometricmean and 95% confidence intervals in non-smoking pregnantwomen fromINMA project cohorts according to different sources of exposure (Spain 2004–2008).

N (%) Cotinine(μg/g creatinine)a

pb

Her partners smokesNo 1225 (68.7%) 6.2 (5.9–6.5) b0.001Yes, but not at home 175 (9.8%) 9.0 (8.0–10.1)Yes, at home also 383 (21.5%) 13.7 (12.5–14.9)

Exposed to SHS at home by othermembers of the household orvisitors to the homeNo 1657 (93.2%) 7.3 (7.0–7.6) b0.001Yes 122 (6.8%) 13.1 (10.9–15.7)

Exposed to SHS at workNo 1607 (90.2%) 7.5 (7.2–7.8) 0.023Yes 175 (9.8%) 8.8 (7.7–10.0)

Exposed to SHS at restaurants(breakfast, lunch or dinner)No 1434 (80.6%) 7.4 (7.1–7.8) 0.020Yes 345 (19.4%) 8.4 (7.6–9.2)

Exposed to SHS during other leisuretime activities (at bars etc. orother homes)No 1325 (74.9%) 7.0 (6.7–7.3) b0.001Yes 455 (25.1%) 9.8 (9.0–10.6)

Overall exposure to SHS (1 or moresource of exposure)No 790 (44.5%) 5.7 (5.4–6.0) b0.001Yes 984 (55.5%) 9.6 (9.0–10.1)

Number of sources of SHS exposure1 704 (39.7%) 8.6 (8.0–9.2)2 251 (14.1%) 12.4 (11.1–13.8)3 29 (1.6%) 14.2 (10.9–18.7) b0.001c

a Geometric means (95% CI).b p-value from t-test or analysis of variance for the comparison of log (cotinine) accord-

ing to SHS exposure source.c p for trend for 0, 1, 2, 3 exposure sources (at home, at work, or at leisure time or

restaurant).

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contrasted using the Student's t-test and analysis of variance, using alsoa trend test for ordinal variables. In bivariate analysis, theUC levelswereadjusted for creatinine to minimise the effect of renal clearance –

urinary cotinine corrected (UCC) for creatinine – and log-transformedto approach normality. Prior to correction for creatinine, values forsamples under the detection limit were divided by the square root of2. In order to identify the variables independently associated with SHSexposure, multiple logistic regression models were built including geo-graphical area and the variables related with the outcome at p b 0.20 inthe univariate analysis, and sequentially excluding those variables notrelated at p b 0.10 in the adjusted model using the likelihood ratiotest.We used adjusted Tobit regressionmodels to determine themater-nal characteristics independently associated with the logarithm of UClevels accounting for the left-censoring of the data at the cut-off of4.0 ng/ml (Wilson et al., 2011), including geographical area, creatinineconcentration,maternal age, and the variables relatedwith the outcomeat p b 0.20 in the univariate analysis, excluding sequentially thosevariables not related at p b 0.10 in the adjustedmodel based on the like-lihood ratio. A further model including the variables from the previousmodel and various sources of SHS exposure was also fitted, regardlessof the corresponding p values and expressed by a figure. Results wereexpressed as percentage change in cotinine (ng/ml) related to a changefrom the reference category to the current of the independent variables.The normality of the residuals was checked graphically. Statisticalanalysis was carried out using SPSS, version 17.0 (Norušis, 2008), andR 2.15.3 (R Development Core Team, 2013).

3. Results

Of the 1783 non-smoking pregnant women included in the analysis,more than half (55.5%) reported SHS exposure; 38.5% at leisure time(including bars and restaurants), 24.7% at home and 9.8% at work. Weobserved a higher probability of overall SHS exposure and higher levelsof UCC among younger women, women from low social class and loweducational level, and those that had smoked previously, either at thebeginning or at the 1st trimester of pregnancy (Table 1). Women witha previous child had a lower probability of SHS exposure at home andlower levels of UCC. Women with the lowest BMI showed higherproportion of SHS exposure at home without differences in the UCClevels. There were significant statistical differences among areas in thepatterns of the sources of SHS exposure, but no differences werefound after adjusting by creatinine (UCC). Among 790 women that re-ported non-SHS exposure, 289 (36.6%) had detectable levels of UC(N4 ng/ml). The overall median of UC was 4.1 ng/ml, 6.6 ng/ml inthose who reported SHS exposure and less than 4.0 ng/ml in thosethat reported non-SHS exposure (p b 0.01) (data not shown).

Most common exposure took place during other leisure time activi-ties (25.1%), followed by exposure at home by their partner (21.5%) andin restaurants (19.4%). Women who reported SHS exposure in any ofthe considered sites had higher UCC levels (Table 2). Those who report-ed SHS exposure at home had higher mean UCC levels than those notexposed at home andwomenwhose partnerswere smokers but report-ed not to smoke at home had also higher UCC levels than those withnon-smoker partners. Women exposed to more than one SHS sourceshowed higher UCC levels than those exposed only to one source,with a statistically significant trend.

The risk of SHS exposure at home (from other people than thepartner) or in places where women spent their leisure time other thanin restaurants was higher among women younger than 25 years ofage, than those in older age groups (Table 3).Women from lower socialclasses were more likely to be exposed at home, while a lower level ofeducation was associated with higher rates of exposure in all the sitesconsidered, except restaurants. Women with a BMI lower than 18.5had greater risk of exposure at home. Those who already had childrenhad a lower risk of exposure at work, from their partner at home, andin restaurants. Latin American women were less exposed to SHS from

their partner at home or in restaurants, while those from othercountries of birth (Europe, Asia, and Africa) were more often exposedto SHS at home fromother people than their partner. Smoking at the be-ginning of thepregnancywas associatedwith a greater risk of SHS expo-sure at home from their partner. The approval of first lawwas related toa statistically significant decrease in the risk of SHS exposure in restau-rants and close to the limit of statistical significance in work and inoverall exposure.

Table 4 shows the sociodemographic variables associated with UClevels using a censored linear regression model and adjusting for creat-inine as an independent term. The UC levels were higher in womenbelow 30 years, those in lower social classes or with low educationlevels and those who had a history of smoking, especially those whosmoked at the beginning of pregnancy. UC levels were higher onMondays, and in seasons other than spring, particularly in winter. Themonth-by-month analysis did not improve the fit of the model, buthigher levels were observed in December, July, March, January, andAugust. After adjusting for the sociodemographic variables, all SHS ex-posure sources were associated with higher UC levels, showing higherincreases with SHS exposure at home by her partner; secondly whenthe women referred that her partner smoked but not at home; whenother people smoked at home; when the SHS exposure happenedduring leisure time;when it happened atwork; andfinallywith SHS ex-posure in the restaurants (Fig. 1).

4. Discussion

In this study, the self-reported prevalence of SHS exposure in non-smoking Spanish pregnant women at the 3rd trimester was 55.5%. Themost frequent exposure to SHS was at leisure time (38.5%), including

Table 3Variables associated with reported SHS exposure in different settings. Adjusted logistic regression analyses. Only variables shown in the table were included in each logistic regression(Spain 2004–2008).

SHS overalla SHS at home bythe partnera

SHS at home by anotherperson or visitorsa

SHS at worka SHS at restauranta SHS during other leisuretime activitiesa

CohortAsturias 1 1 1 1 1 1Gipuzkoa 1.82 (0.34–2.47) 0.55 (0.36–0.83) 0.49 (0.21–1.11) 0.72 (0.39–1.35) 1.70 (1.01–2.87) 3.68 (2.61–5.19)Sabadell 1.81 (1.34–2.45) 1.49 (1.04–2.14) 1.18 (0.62–2.24) 1.04 (0.86–1.76) 3.93 (2.47–6.25) 0.78 (0.53–1.15)Valencia 2.17 (1.52–3.11) 1.64 (1.15–2.33) 1.98 (1.09–3.59) 1.52 (0.86–2.67) 3.49 (2.11–5.78) 1.26 (0.88–1.80)

Ageb25 – – 1 – – 125–29 – – 0.48 (0.27–0.87) – – 0.68 (0.42–1.09)30–34 – – 0.37 (0.20–0.68) – – 0.55 (0.34–0.89)≥35 – – 0.41 (0.20–0.83) – – 0.43 (0.26–0.73)

Social classb

I–II (highest) – 1 1 – – –

III – 1.28 (0.90–1.80) 1.48 (0.75–2.94) – – –

IV–V (lowest) – 1.53 (1.09–2.15) 2.16 (1.13–4.14) – – –

Level of educationUniversity 1 1 1 1 – 1Secondary 1.04 (0.83–1.29) 1.41 (1.03–1.94) 1.44 (0.79–2.62) 1.17 (0.80–1.73) – 1.07 (0.82–1.39)Primary or less 1.57 (1.19–2.07) 2.01 (1.39–2.94) 2.21 (1.16–4.14) 1.81 (1.19–2.76) – 1.47 (1.07–2.02)

Pre-pregnancy BMI (kg/m2)b18.5 (underweight) – – 1 – – –

18.5–25 (healthy weight) – – 0.36 (0.18–0.72) – – –

25–30 (overweight) – – 0.33 (0.15–0.71) – – –

N30 (obesity) – – 0.23 (0.09–0.61) – – –

Parity0 1 1 – 1 1 –

1 0.64 (0.52–0.79) 0.64 (0.49–0.83) – 0.70 (0.49–0.99) 0.67 (0.51–0.88) –

≥2 0.80 (0.53–1.20) 0.77 (0.47–1.27) – 0.71 (0.36–1.38) 0.85 (0.52–1.40) –

Country or birthSpain – 1 1 – 1 –

Latin America – 0.49 (0.28–0.85) 1.77 (0.95–3.30) – 0.39 (0.21–0.71) –

Others – 1.47 (0.78–2.75) 3.30 (1.57–6.95) – 0.90 (0.45–1.82) –

Ever smoked during her lifeNo – – 1 – – 1Yes – – 1.50 (1.00–2.25) – – 1.38 (1.10–1.73)

Smoked at the beginning of pregnancyNo 1 1 – – – –

Yes 1.80 (1.35–2.39) 2.50 (1.88–3.34) – – – –

Data collection after banning smokingin public placesNo 1 – – 1 1 –

Yes 0.77 (0.57–1.03) – – 0.61 (0.37–1.02) 0.57 (0.39–0.84) –

a Only variables showed in the table were entered in the logistic equation.b Considering the most privileged from each woman or her partner.

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bars and restaurants, followed by exposure at home (24.7%), but UClevels were highest in women exposed to SHS at home, especiallywhen their partners smoked there.

4.1. SHS exposure prevalence

The self-reported prevalence of SHS exposure in this study is higherthan those reported by De Chazeron et al. (2007) in France (44%).Vardavas et al. (2010) reported an even higher prevalence of SHS expo-sure in Greece (94%) and Kvalvik et al. (2012) showed a low prevalence(18.6%) in Norway. Indeed, the WHO report for EU27 countries iden-tified great variability in SHS exposure at home among pregnantwomen across the regions, ranging from 4 to 65%. Further, out ofEurope, Paek et al. (2009) and Sasaki et al. (2011) observed slightlyhigher prevalence in Korea and in Japan (60% and 63%, respectively),while Eiden et al. (2011) showed a prevalence of 82% in the UnitedStates for SHS exposure. Prevalence of SHS exposure is assessed byquestionnaires and the differences found between studies might be ex-plained in part by the differences in the definitions of SHS exposure. Inour study, we chose “contact with SHS at least twice a week” as a defi-nition of SHS exposure. Furthermore, we did not collect SHS exposurein motor vehicles that could still increase the overall prevalence ofSHS exposure. However, the highest prevalence observed by Vardavas

et al. (2010) could be explained because they included any exposureto SHS during pregnancy.

4.2. Prevalence of SHS exposure by sources

This paper shows some differences in the prevalence and sources ofexposure to SHS among four Spanish areas where the collection of thedata was done in different moments in relation to the banning ofsmoking in public places. The higher prevalence of SHS exposure ob-served in Valencia could be explained by the fact that data collectionended there first, right before the first law against smoking in publicplaces. The lower overall SHS exposure prevalence, in fact, was observedin Gipuzkoa, the last area starting data collection, after the first banningof smoking in public places. The prevalence of SHS exposure amongnon-smoking pregnant women in a sample of Valencia was 80%, dueto their partner smoking 41%, at work 19% and 54% in leisure time(Rebagliato et al., 1995), substantially higher than in this study. Thelower prevalence rates referred in the WHO (2012) report for Spain(45–50% of women exposed to SHS), collecting information for 2009,could be interpreted as the consequence of the effectiveness of thefirst law. After the date of the first law this work showed a decrease inthe risk of SHS exposure in restaurants and close to the limit of statisticalsignificance at work. No decrease was observed in bars or other leisure

Table 4Variables associated with the logarithm of the urinary cotinine levels (ng/ml). Censoredlinear regression analyses (Spain 2004–2008).

Cotininea

% change (95% CI)

Creatinine (mg/dl)b 168.4 (137.0 to 204.0)Cohort Asturias Reference

Gipuzkoa 31.3 (7.3 to 60.5)Sabadell 2.0 (−16.4 to 24.5)Valencia 0.1 (−20.5 to 26.1)

Age (years) b25 Reference25–29 −3.5 (−26.6 to 26.8)30–34 −16.2 (−36.4 to 10.4)≥35 −21.1 (−41.7 to 6.8)

Social class I–II (highest) ReferenceIII 7.9 (−9.0 to 27.9)IV–V (lowest) 26.6 (6.7 to 50.3)

Level of education University ReferenceSecondary 9.6 (−6.5 to 28.3)Primary or less 29.2 (6.1 to 57.2)

Parity 0 Reference1 −16.9 (−27.6 to −4.6)≥2 0.2 (−22.6 to 29.8)

Day of the week the sample wascollected

Monday 45.4 (19.5 to 76.8)Tuesday 4.8 (−14.0 to 27.6)Wednesday 4.9 (−14.2 to 28.2)Thursday 10.7 (−9.4 to 35.2)Friday Reference

Season the sample was collected Winter 25.0 (5.1 to 48.6)Spring ReferenceSummer 12.1 (−6.2 to 33.9)Autumn 15.8 (−2.5 to 37.5)

Ever smoked during her life No ReferenceYes 15.8 (1.1 to 32.6)

Smoked at the beginning of pregnancy No ReferenceYes 52.9 (27.7 to 83.2)

Data collection after banning smokingin public places

No ReferenceYes −16.0 (−30.7 to 1.7)

a Percentage change in cotinine (ng/ml) associated with a change from the referencecategory to the current or with an increase of one unit in log (creatinine (mg/dl)). Allthe variables of the table were included in the adjusted model.

b In logarithmic scale (natural logarithm).

1194 J.J. Aurrekoetxea et al. / Science of the Total Environment 470–471 (2014) 1189–1196

time activities. This could be explained by the existing prior lawrestricting smoking in some work places and because this first law didnot forbid smoking in bars.

0

24

16

Her partner do not smoke

Her partner smokes: not at home

Her partner smokes: at home

Other persons smoke at home

SHS exposure at work

SHS exposure in restaurants

SHS other leisure time activities

0

Fig. 1. Association between urinary cotinine and sources of SHS. Censored linear regression anaTable 4. Percentage change in cotinine (ng/ml) associated with a change from the reference ca

SHS exposure at home among reproductive-agedwomen from 2008to 2010 is so common in 14 low- andmiddle-income countries (Caixetaet al., 2012). Vardavas et al. (2013) reported from Greece a far higherprevalence of SHS exposure than Kvalvik et al. (2012) in Norway.Eiden et al. (2011) in United States and Paek et al. (2009) in Korea re-ported too high exposure rates to ETS. In our study pregnant womenwere exposed to SHS in bars and other homes during leisure time(25.1%), at home (24.7%), at home by their partner (21.5%) and inrestaurants (19.4%). Most studies showed that exposure to SHS occurmost frequently at home. Our study is consistent with these data,adding exposure in leisure time.

4.3. Socioeconomic variables, the profile of the SHS exposed pregnantwomen

Theprofile of a pregnantwoman exposed overall to SHS in this studyis that of a woman with low level of education, previous history ofsmoking and being primiparous. This pattern can be applied to thesources of exposure, adding other variables such as low age, low socialclass or low BMI. Further, results vary by country of origin, which isanother social and cultural indicator. The social or cultural pattern wasdifferent in SHS exposure in the restaurant, which requires greaterpurchasing power.

Consistently with our study, a report from the WHO (2012) statedthat, in EU27 countries, the mean prevalence of SHS exposure was 23%for pregnant women from higher social positions, increasing to 30%among those in lower social positions. De Chazeron et al. (2007) report-ed higher exposure among younger and among manual workers inpregnant women. The WHO (2012) report for the EU27 countries re-ported associationwith lower social positions. Yoo et al. (2010) showedalso a higher prevalence of SHS exposure in women or spouses withlower levels of education or with lowest incomes. We found thatwomen who already had children had a lower risk of SHS exposure,but the pattern of exposure was not clear after the first child.

4.4. Sources of SHS exposure and UC levels

This study shows that the main contributor of increased UC levels ishaving a partner that smoke at home, followed by having a partner thatdoes not smoke at homebut is a smoker, and the third contributor is theother people in the house smoking at home. It has less influence on the

65

173

41

34

50 100 150 200% change in cotinine

lyses (Spain 2004–2008). The model was also adjusted for sociodemographic variables oftegory to the current.

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UC levels of the SHS exposure in places of leisure, at work and in restau-rants. Chiu et al. (2008) and Kvalvik et al. (2012) observed that cotininelevels both in plasma and in urine were higher among women exposedto SHS at home than in those exposed at work. Rebagliato et al. (1995)reported higher cotinine levels in pregnant women exposed to SHS inpublic places, followed by exposure from a partner smoking, exposureat work and other sources. Exposure to SHS at home by a smokingspouse was the major source of UC levels for most non-smokingwomen aged 35 to 65 years. The cotinine levels observed by St Helenet al. (2012) in the United States, measured immediately post-exposure to SHS, in an outdoor smoking area of a bar, and the followingday, were higher than those observed in people who went to restau-rants, an observation that is in agreement with our data. Overall, themost relevant sources of SHS exposure are the environment at homeand where leisure time is spent.

We do not take into account other sources of SHS exposure, such as inpublic or private transport, among others. However, we consider unlike-ly that the contribution of these sources was important, given thatsmoking in public transport is banned in Spain since 1998. Vardavaset al. (2013) nevertheless, observed statistically significant increases inUC levels associated with SHS exposure at home and in cars, as well asincreases close to statistical significance due to exposure at work andin public places, although SHS exposure in cars was considerably lesscommon than in other places. Becher et al. (1992) showed that SHS ex-posure in motor vehicles was the lowest in terms of prevalence, medianexposure duration and in detectable UC levels. Eiden et al. (2011) ob-served also a low frequency of SHS exposure at the motor vehicles.

It is interesting that pregnantwomenwith partnerswho only smokedoutside the home showed the second highest increments of UC in the re-gressionmodel. This observation has already been reported in hair cotin-ine levels (Yoo et al., 2010). It could be explained by the fact that womennear the smokers had higher probability of SHS contact than others.

Another point of interest in our study is that our data shows thathavingmore than one source of SHS exposure leads to higher UC levels.Kvalvik et al. (2012) observed also higher cotinine levels in womenexposed to SHS at home and at work. SHS exposure implies absorptionthrough the respiratory system. SHS exposure depends on the frequen-cy of contact with the source, the environmental concentration and theduration of the exposure. Chiu et al. (2008) found that cotinine levelswere even higher in women who were exposed both at home and atwork. Yoo et al., (2010) reported a clear increasing of hair cotininelevels with intensity of exposure in the home. Ashford et al. (2010),Rebagliato et al. (1995) and Spierto et al. (1994) observed that cotininelevels increase with length of SHS exposure in pregnant women. Ac-cording to Rebagliato et al. (1995), exposure is longer term at homebut less intense, it is shorter-term in public places but more intense,and it is variable at work.

UC levels were higher on Monday than other days of the week,reflecting exposure during the previous day, namely Sunday. Giventhe short half-life of UC in pregnancy (Dempsey et al., 2002;Rebagliato et al., 1998) and that most of the samples were collected inthe morning, it is reasonable to conclude that the concentration of UCreflects the SHS exposure during the previous day. One limitation ofthis study is that no samples were taken on Saturday or Sunday morn-ings, readings that would provide us with information regarding expo-sure on Friday and Saturday, which is likely to be higher than on otherdays. Interestingly, however, cotinine levels were higher in the monthswithmore bank holidays. Overall, our results suggest that SHS exposureis greater on days when there are more leisure activities. Furthermore,higher levels were detected in winter, when more time is spent at thehome or in bars, and with poorer ventilation. These factors may leadto a more prolonged exposure and higher environmental concentra-tions of tobacco smoke. There were geographical differences in SHS ex-posure. The highest UC levels were found in Gipuzkoa. This area has acolder and more humid climate than Sabadell and particularly thanValencia, which would lead you to assume that people would spend

more time inside in closed premises andwith a prolonged SHS exposureand higher concentrations.

4.5. Limitations and strengths of this study

The questionnaire was not aimed to collect information of SHSexposure just before the sample collection but to characterize regularexposure; therefore the correlation between the information of thequestionnaire and the UC is not expected to be exact. Moreover, urinesamples were collected at different hours in the morning. All this,added to the fact that the elimination of the UC is faster in pregnantwomen (Dempsey et al., 2002; Rebagliato et al., 1998) reduces the reli-ability of UC in this study. However, UC appears to be a sensitive indica-tor both overall SHS exposure and for exposure from several sources.Also, UC provides useful information regarding socioeconomic variablesin relation to SHS exposure. As well as being a method to differentiatebetween active and passive smoking, this study shows that in womennot exposed to SHS, UC levels are genuinely low, which is consistentwith the fact that apart from dietary intake of nicotine there are noother sources of nicotine, and in the absence of tobacco smoke it is dif-ficult to produce levels above 4 ng/ml (Benowitz, 1996).

Participation rates in this study, between 45% and 68% in Asturiasand Gipuzkoa, respectively, are not low for a cohort study, but cross-sectional studies usually show higher participation rates. Non-participation could have a lower social class and a low educationallevel (Strandhagen et al., 2010). Some information was availableabout women who did not participate. Educational achievement ofwomen who refused was lower than that of the participants, but therewere no differences in age. In Valencia, a higher proportion of olderwomen and ofworkingwomenagreed to participate. Therewere nodif-ferences in age between participants and non-participants in Asturias.In Gipuzkoa, a high proportion of working women were included(Guxens et al., 2012).

5. Conclusion

Smoking in indoor public places is an important source of SHS expo-sure, as shown by the high prevalence of exposure and UC levels foundin the study. This public health problem has, however, been addressedrecently by new legislation in Spain in 2010. The smoking ban in publicplaces is an important resource for reducing exposure to SHS, but didnot affect the home, where there is the greatest contribution of nicotinein pregnantwomen, as this study shows. Therefore, it is particularly im-portant to bear in mind that the source that provides the highest dosesof SHS to pregnant women is their own home. Useful tools are requiredfor the effective reduction of SHS exposure in this area.

Contributors

All authors contributed to various aspects of this paper. JJA, MM andMR designed the study and analysed the data. AMC and ME analysedcotinine in urine samples. MJL, AMC, LSM, MG, AF-S, ME, AL, AT and FBrevised the design of the study and the results. JJA redacted the manu-script and the other authors participated in the review of the differentdraughts and approved the final version.

Conflict of interest statement

The authors declare that there are no conflicts of interest.

Patient consent

Obtained.

1196 J.J. Aurrekoetxea et al. / Science of the Total Environment 470–471 (2014) 1189–1196

Ethics approval

This study was conducted with the approval for each of the fourcohorts.

Funding

INMA project is funded by grants from Instituto de Salud Carlos III(Red INMA G03/176 and CB06/02/0041) and Fundación Roger Torné.The studies in the specific regions were funded by the Spanish Ministryof Health (FIS 03/1615, 04/1436, 04/1509, 04/1112, 04/1931, 05/1079,05/1052, 06/0867, 06/1213, 07/0314, 08/1151, 09/02647, 04/2018, 09/02311), the Generalitat de Catalunya (CIRIT 1999SGR00241), theDiputación Foral de Gipuzkoa (DFG06/004), the Department of Healthof the Basque Government (2005111093), the Regional Governmentof Andalucía (SAS 07/183), Obra social Cajastur, University of Oviedoand the Conselleria de Sanitat Generalitat Valenciana. http://www.proyectoinma.org/instituciones-participantes/en_entidades-colaboradoras/

Data sharing statement

There is no additional data available.

Acknowledgements

The authors are grateful to all fieldworkers for their assistance inadministering the questionnaires. A full listing of the INMA projectresearchers can be found at http://www.proyectoinma.org/presentacioninma/listado-investigadores/en_listado-investigadores.html.

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