DESIGN: Cross-sectional study.
SETTING: Primary and secondary schools in Malaysia.
PARTICIPANTS: 11 246 non-smoking school-going adolescents.
OUTCOME MEASURES: The prevalence and factors associated with smoking susceptibility among non-smoking school-going adolescents in Malaysia.
RESULTS: Approximately 14% of non-smokers were susceptible to smoking, and the prevalence of susceptibility was significantly higher among males, ever-smokers and e-cigarette users. The odds of susceptibility to smoking were higher among males, e-cigarette users, those aged 12 years and under and those who had ever smoked or tried cigarettes. Students from schools with educational programmes on the health effects of second-hand smoke (SHS) and who perceived smoking to be harmful were less likely to be susceptible to smoking.
CONCLUSION: Smoking susceptibility is prevalent among school-going adolescents. A comprehensive approach that enhances or reinforces health education programmes on the adverse health effects of smoking and SHS among school children, that considers multiple factors and that involves all stakeholders is urgently needed to reduce the prevalence of smoking susceptibility among vulnerable subgroups, as identified from the present findings.
METHODS: We collected data from participants of a public smoking cessation clinic in Selangor. A trained pharmacist conducted face-to-face interviews with 152 daily smokers using a structured validated questionnaire. Respondents were classified as having high nicotine dependence using both the HSI (score ≥4) and the FTND (score ≥6), and concordance between the two measures, kappa statistics and sensitivity, specificity of the HSI were then determined with the FTND classification as the reference standard.
RESULTS: The HSI had a substantial agreement with the FTND (Cohen's kappa=0.72) in measuring high levels of nicotine addiction, with good sensitivity (83.3%) and specificity (89.4%).
CONCLUSIONS: The findings suggest that the HSI can be used instead of the FTND in clinical-based investigations to screen for high nicotine dependence among daily smokers in the clinical setting.
METHODS: Using confirmatory factor analysis (CFA), four measurement models with the best relative fit were compared, one uni-dimensional model, and three different two-domain (morning and daytime smoking) models.
RESULTS: The findings indicate that the best model of the FTND-M was a two-domain model, wherein domain one represented morning smoking (time to first cigarette of the day, smoking more in the morning, and which cigarette would you hate to give up) and domain two represented daytime smoking (cigarettes per day, difficulty refraining from smoking, and smoking when ill) which showed good model fit [χ2/df=1.932, goodness of fit (GFI) of 0.967, comparative fix index (CFI) of 0.945, incremental fit index (IFI) of 0.98, Tucker-Lewis index (TLI) of 0.95 and a real mean square end of approximation (RMSEA) of 0.079, and substantial reliability >0.70].
CONCLUSIONS: This study indicates that the FTND-M can be used to assess these two dimensions of nicotine addiction among daily smokers in a clinical setting.
METHODS: The data were derived from the Malaysian Global Adult Tobacco Survey (GATS-M), collected in 2011-2012, involving 4250 respondents. Data analyses involved 1343 respondents reported to be in the working population.
RESULTS: More than half of the respondents (58.5%) were reportedly working in smoke-free workplaces. Almost a quarter (24.8%) of those who worked in smoke-free workplaces stayed in smoke-free homes, which was more than two times higher than their counterparts who worked at non-smoke-free workplaces (24.8% vs 12.0%, p<0.001). Multivariable analyses further substantiated this finding (AOR=2.01, 95% CI: 1.11-3.61, reference group = worked at non-smoke-free workplaces).
CONCLUSIONS: This study found an association between living in smoke-free homes and working at smoke-free workplaces, which could suggest a positive impact of implementing smoke-free workplaces.
METHODS: We derived data from the Global School Health Survey (GSHS) 2012 and GSHS 2017, which was carried out in Malaysia using multistage sampling to select representative samples of secondary school-going adolescents. Both surveys used similar questionnaires to measure SHS exposure. Descriptive and multivariate logistic regression was used to determine the prevalence and factors associated with SHS exposure.
RESULTS: Approximately four in ten respondents were exposed to SHS in the past week in both surveys (41.5% in GSHS 2012 and 42.0% in GSHS 2017, respectively). Both surveys revealed a significantly higher SHS exposure among respondents who smoked than among non-smokers and higher among males compared to females. The likelihood of SHS exposure in both surveys was also similar, with a higher likelihood of SHS exposure among smoking adolescents and non-smoking adolescents who had at least one smoking parent/guardian, regardless of their own smoking status. Male adolescents had a higher risk of SHS exposure compared to their female counterparts. Meanwhile, SHS risk also increased with age, regardless of smoking status.
CONCLUSIONS: Our findings suggested that there were no changes in the prevalence of SHS exposure and recorded only a slight change in the factors associated with exposure to SHS among school-going adolescents in Malaysia between the years 2012 and 2017. A more pro-active, extensive and comprehensive programme should be implemented to address the problem of SHS exposure. Parents should be advised to stop smoking or abstain from smoking in the presence of their children, and smoking cessation interventions are necessary for smoking adolescents and their parents.
METHODS: We administered the BM-PTSQ to 669 secondary school students selected through multistage sampling; 60% of respondents were male (n=398), and 69.9% (n=463) were from rural areas. Respondents were aged 13-16 years, 36.4% (n=241) were 13 years, 40.0% (n=265) were 14 years, and 23.6% (n=156) were 16 years old. We used parallel and exploratory factor analysis (EFA) to determine the domains of the questionnaire. In addition, we also employed EFA, confirmatory factor analyses (CFA), and Cronbach's alpha to evaluate the construct validity and reliability of the BM-PTSQ.
RESULTS: EFA and parallel analysis identified two domains in the BM-PTSQ that accounted for 62.9% of the observed variance, and CFA confirmed the two-domain structure. The two domains' internal consistency scores ranged from 0.702 to 0.80, which suggested adequate reliability.
CONCLUSIONS: The BM-PTSQ has acceptable psychometric validity and is appropriate for assessing smoking perception and intention among Malaysian secondary school-aged youth. Researchers should further evaluate this tool's applicability in a more sociodemographically diverse population.
DESIGN: Retrospective cohort study.
SETTING: The Malaysian Non-Communicable Disease Surveillance (MyNCDS-1) 2005/2006.
PARTICIPANTS: A total of 2525 adults (1013 men and 1512 women), aged 24-64 years, who participated in the MyNCDS-1 2005/2006.
METHODS: Participants' anthropometric indices, blood pressure, fasting lipid profile and fasting blood glucose levels were evaluated to determine the prevalence of metabolic syndrome by the Harmonized criteria. Participants' mortality status were followed up for 13 years from 2006 to 2018. Mortality data were obtained via record linkage with the Malaysian National Registration Department. The Cox proportional hazards regression model was applied to determine association between metabolic syndrome (MetS) and risk of CVD mortality and all-cause mortality with adjustment for selected sociodemographic and lifestyle behavioural factors.
RESULTS: The overall point prevalence of MetS was 30.6% (95% CI: 28.0 to 33.3). Total follow-up time was 31 668 person-years with 213 deaths (111 (11.3%) in MetS subjects and 102 (6.1%) in non-MetS subjects) from all-causes, and 50 deaths (33 (2.9%) in MetS group and 17 (1.2%) in non-MetS group) from CVD. Metabolic syndrome was associated with a significantly increased hazard of CVD mortality (adjusted HR: 2.18 (95% CI: 1.03 to 4.61), p=0.041) and all-cause mortality (adjusted HR: 1.47 (95% CI: 1.00 to 2.14), p=0.048). These associations remained significant after excluding mortalities in the first 2 years.
CONCLUSIONS: Our study shows that individuals with MetS have a higher hazard of death from all-causes and CVD compared with those without MetS. It is thus imperative to prescribe individuals with MetS, a lifestyle intervention along with pharmacological intervention to improve the individual components of MetS and reduce this risk.
METHODS: A study was carried out in 2013, which involved a total of 40 secondary schools. They were randomly selected using a two-stage clustering sampling method. Subsequently, all upper secondary school students (aged 16 to 17 years) from each selected school were recruited into the study. Data was collected using a validated standardised questionnaire.
RESULTS: This study revealed that the prevalence of smoking was 14.6% (95% CI:13.3-15.9), and it was significantly higher among males compared to females (27.9% vs 2.4%, p