Jose M Martínez-Sánchez1, Xisca Sureda2, Marcela Fu2, Raúl Pérez-Ortuño3, Montse Ballbè4, María J López5, Esteve Saltó6, José A Pascual7, Esteve Fernández2. 1. Tobacco Control Unit, Cancer Prevention and Control Program, Institut Català d'Oncologia, Av. Granvia de l'Hospitalet, 08908 L'Hospitalet de Llobregat, 199-203 Barcelona, Spain; Cancer Prevention and Control Group, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain; Biostatistics Unit, Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Spain. Electronic address: jmmartinez@iconcologia.net. 2. Tobacco Control Unit, Cancer Prevention and Control Program, Institut Català d'Oncologia, Av. Granvia de l'Hospitalet, 08908 L'Hospitalet de Llobregat, 199-203 Barcelona, Spain; Cancer Prevention and Control Group, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, Universitat de Barcelona, Barcelona, Spain. 3. IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. 4. Tobacco Control Unit, Cancer Prevention and Control Program, Institut Català d'Oncologia, Av. Granvia de l'Hospitalet, 08908 L'Hospitalet de Llobregat, 199-203 Barcelona, Spain; Cancer Prevention and Control Group, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, Universitat de Barcelona, Barcelona, Spain; Addictions Unit, Institute of Neurosciences, Hospital Clínic de Barcelona, Barcelona, Spain. 5. Agència de Salut Pública de Barcelona, Barcelona, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Spain; Institut d'Investigació Biomèdica-IBB Sant Pau, Barcelona, Spain. 6. Health Plan Directorate, Ministry of Health, Generalitat de Catalunya, Spain; Department of Public Health, Universitat de Barcelona, Barcelona, Spain. 7. IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Department of Experimental and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
Abstract
OBJECTIVE: We assessed and characterized the relationship among biomarkers of secondhand smoke (SHS) exposure in non-smokers according to their exposure at home as measured by airborne markers. METHODS: We conducted an observational study on exposure to SHS at home using airborne markers (nicotine and benzene) and biomarkers from the non-smokers living in these homes. We selected 49 non-smoking volunteers from different homes: 25 non-smokers living with at least one smoker and 24 non-smokers living in smoke-free homes. We installed two passive devices to measure nicotine and benzene concentrations in the main room of the house (i.e., the living room). One week later, the researcher returned to the volunteer's home to collect the two devices, obtain saliva and urine samples, and administer a SHS questionnaire. RESULTS: Salivary and urinary cotinine concentrations highly correlated with air nicotine concentrations measured at the volunteers'homes (rsp=0.738 and rsp=0.679, respectively). The concentrations of airborne markers of SHS and biomarkers in non-smokers increased with increasing self-reported intensity and duration of SHS exposure at home during the previous week (p<0.05). The multivariable regression model showed a significant association with nicotine in air at home (β=0.126, p=0.002 for saliva and β=0.115, p=0.010 for urine). CONCLUSIONS: Our findings suggest that, even in countries with comprehensive smoke-free legislation, exposure to SHS at home continues to be the main source of exposure for non-smokers who live in non-smoke-free homes. Therefore, public health policies should promote smoke-free homes.
OBJECTIVE: We assessed and characterized the relationship among biomarkers of secondhand smoke (SHS) exposure in non-smokers according to their exposure at home as measured by airborne markers. METHODS: We conducted an observational study on exposure to SHS at home using airborne markers (nicotine and benzene) and biomarkers from the non-smokers living in these homes. We selected 49 non-smoking volunteers from different homes: 25 non-smokers living with at least one smoker and 24 non-smokers living in smoke-free homes. We installed two passive devices to measure nicotine and benzene concentrations in the main room of the house (i.e., the living room). One week later, the researcher returned to the volunteer's home to collect the two devices, obtain saliva and urine samples, and administer a SHS questionnaire. RESULTS: Salivary and urinary cotinine concentrations highly correlated with air nicotine concentrations measured at the volunteers'homes (rsp=0.738 and rsp=0.679, respectively). The concentrations of airborne markers of SHS and biomarkers in non-smokers increased with increasing self-reported intensity and duration of SHS exposure at home during the previous week (p<0.05). The multivariable regression model showed a significant association with nicotine in air at home (β=0.126, p=0.002 for saliva and β=0.115, p=0.010 for urine). CONCLUSIONS: Our findings suggest that, even in countries with comprehensive smoke-free legislation, exposure to SHS at home continues to be the main source of exposure for non-smokers who live in non-smoke-free homes. Therefore, public health policies should promote smoke-free homes.
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