title: Differential patterns of tobacco use among black men and women in Cape Town: the cardiovascular risk in black South Africans study.
abstract: BACKGROUND
  To examine the prevalence and determinants of tobacco use in the 25-74-year-old urban Black population of Cape Town and to examine the changes between 1990 and 2008-2009 in the 25-64-year-old sample.
  
  
  METHODS
  In 2008-2009 (n = 1,099), a representative cross-sectional sample was randomly selected from the same townships sampled in 1990 (n = 986). Sociodemographic characteristics, tobacco use by the World Health Organization (WHO) STEP-wise questionnaire, and psychosocial stress, including sense of coherence (SOC), locus of control, and adverse life events, were determined. Survey logistic regression analysis assessed the determinants of smoking ≥ 1 cigarette/day.
  
  
  RESULTS
  There were 392 men and 707 women. Age-standardized prevalence of smoking ≥ 1 cigarette/day was 48.5% (95% confidence interval [CI] = 43.0-54.0) in men and 7.8% (95% CI = 5.8-10.5) in women (p < .001). Prevalence in men was lower in 2008-2009 (51.0%, 95% CI = 45.2-56.7) compared with 1990 (59.7%, 95% CI = 53.8-65.4) but unchanged in women (2008/09: 8.0%, 95% CI = 5.9-10.7; 1990: 8.4%, 95% CI = 6.0-11.8). In the logistic model for men, smoking was associated with younger age (p = .005) and being poor (p = .024). In women, spending more than half their lives in the city (p < .001), being poor (p = .002), and coping poorly with stress (defined by lower SOC; OR = 1.04, 95% CI = 1.01-1.08; p = .035) were associated with smoking. Increasing number of adverse events, which replaced SOC in the same models, was significant for women (OR = 1.10, 95% CI = 1.01-1.21; p = .047) but not for men. Education level, employment status, and housing quality were not relevant for men or women.
  
  
  CONCLUSIONS
  The high smoking prevalence in men and unchanged rate in women require additional interventions to curtail this behavior.
authors.affiliation: Non-communicable Diseases Research Unit, Medical Research Council, Durban, South Africa; nasheeta.peer@mrc.ac.za.
authors.forename: Nasheeta
authors.initials: N
authors.lastname: Peer
authors.affiliation: Biostatistics Unit, Medical Research Council, Cape Town, South Africa;
authors.forename: Carl
authors.initials: C
authors.lastname: Lombard
authors.affiliation: Department of Medicine, Chronic Disease Initiative for Africa, University of Cape Town, Cape Town, South Africa;
authors.forename: Krisela
authors.initials: K
authors.lastname: Steyn
authors.affiliation: Department of Medicine, Chronic Disease Initiative for Africa, University of Cape Town, Cape Town, South Africa; Department of Medicine, Division of Endocrinology and Diabetes, University of Cape Town, Cape Town, South Africa.
authors.forename: Naomi
authors.initials: N
authors.lastname: Levitt
mesh_terms: D000328:Adult; D000368:Aged; D044383:Black People / Q000706:statistics & numerical data*; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology*; D013019:South Africa / Q000453:epidemiology; D011795:Surveys and Questionnaires; D062789:Tobacco Products; D014505:Urban Population