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1.
Ann. afr. med ; 10(2): 103-111, 2011.
Article in English | AIM | ID: biblio-1258851

ABSTRACT

Background: Tobacco control policy can only succeed if the burdens of smoking are known. The objective of this study was to determine the prevalence and correlates of secondhand smoke (SHS) exposure among nonsmoking adults in two Nigerian cities. Materials and Methods: We carried out a cross-sectional study from October 2009 to April 2010 among adult population of two Nigerian cities: Enugu and Ilorin. A semi-structured questionnaire was administered by interviewers to obtain socio-demographic information; and information regarding pattern of SHS exposure; wareness of tobacco control policy and the harmful effects of SHS. SHS exposure was defined as regular exposure to tobacco smoke in the previous 30 days in a nonsmoking adult. Results: Of the 585 nonsmoking adults that completed the study; 38.8had regular exposure to SHS; mostly; in public places (24.4). More men were exposed at public places when compared with women (27.0vs. 19.5). The strongest factor associated with exposure to SHS in women was having a smoking spouse [prevalence rate (PR) ratio-7.76; 95confidence interval (CI); 3.08-9.42]; and in men; it was lack of home smoking restriction (PR ratio-6.35; 95CI; 4.51-8.93). Among men; SHS exposure at any location was associated with lack of secondary school education; residing in slum apartment (house with many households); living with a smoking family member (non-spouse); lack of home smoking restriction; and alcohol intake. Among women; SHS exposure at any location was associated with having a smoking spouse; residing in slum apartment and lack of home smoking restriction. Seventy-two percent of respondents were aware of the harmful effects of SHS on their health. Lack of awareness of the harmful effects was significantly associated with increasing age (r= +0.45; P = 0.01); lack of secondary school education (rof the employees reported availability of outdoor smoking area at their workplaces. Conclusion: Our results show that prevalence of SHS exposure was the highest in public places. These findings underscore the need for enactment of comprehensive smoke-free legislation and implementation of educational strategies to reduce SHS exposure in homes


Subject(s)
Adult , Inhalation Exposure , Prevalence , Tobacco Smoke Pollution
2.
Article in English | IMSEAR | ID: sea-925

ABSTRACT

This paper examines inequalities in the use of, and access to, vaccination service in Bangladesh by analyzing national and small area-based datasets. The analysis showed that female children had a lower immunization coverage than male children--the difference persists for all antigens and widens against girls for higher doses. The immunization coverage was higher for children whose mothers were more educated. Children whose fathers had a higher-status occupation (salaried employment) were two-and-a-half times more likely to be immunized than children whose fathers held a lower-status job, e.g. day-labourer. The coverage for the poorest quintile was 70% of the well-to-do. Children residing in urban areas were more likely to be fully immunized than their rural counterparts (70% vs 59% for children aged 12-23 months). Within urban areas, the situation in slums was worse. Large differences existed among the various administrative regions of the country. Ethnic minorities in the Chittagong Hill Tracts had a lower immunization coverage than the Bangalees. In Sylhet, children of non-local workers in Bangladesh-owned tea estates had a lower coverage than their counterparts in foreign-owned tea estates. The study identifies children of various disadvantaged groups as having a lower coverage. Managers of immunization programmes must realize that only through removal of such disparities among groups will overall coverage be increased. Affirmative actions in targeting could be effective in reaching such groups.


Subject(s)
Bangladesh , Female , Health Services Accessibility , Humans , Immunization/trends , Immunization Programs/statistics & numerical data , Infant , Male , Rural Population , Sex Factors , Social Class , Socioeconomic Factors , Urban Population , Vaccination/statistics & numerical data , Vaccines/administration & dosage
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