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: We conducted a cost-utility analysis using a Markov model to simulate lifetime costs and quality-adjusted life years (QALYs) of Thai smokers aged ≥35 years receiving smoking cessation services offered from FAHSAI Clinic or usual care over a horizon of 50 years. The model used a 6-month continuous abstinence rate from a multicenter prospective study of 24 FAHSAI Clinics. A series of sensitivity analyses including probabilistic sensitivity analysis were conducted to assess robustness of study findings. Cost data are presented in US$ for 2020.
RESULTS: The FAHSAI Clinic was dominant as it was less costly ($9537.92 vs $10964.19) and more effective (6.06 vs 5.96 QALYs) compared with usual care over the 50-year time horizon. Changes in risks of stroke and coronary heart disease among males had the largest impact on the cost-effectiveness findings. The probability that FAHSAI Clinic was cost-effective was 99.8% at a willingness-to-pay threshold of $5120.
CONCLUSIONS: The FAHSAI Clinic smoking cessation program was clinically superior and cost-saving compared to usual care for Thai patients with CVD in all scenarios. A budget impact analysis is needed to estimate the financial impact of adopting this program within the Thai healthcare system.
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 performed secondary analysis on data from 25461 respondents of the Global School Health Survey in Malaysia. Descriptive analyses and multivariable logistic regression were performed to determine factors associated with SHS exposure.
RESULTS: Respondents were adolescents of mean age 14.84 (SD=1.45) years, 50.2% of which were male and 49.8% female. Approximately four in ten respondents were exposed to SHS in the past week (41.5%). SHS exposure was significantly higher among respondents who smoked than among non-smokers (85.8% vs 35.7%, p<0.001). The likelihood of exposure to SHS was higher among smoking adolescents (Adjusted OR=1.66, 95% CI: 1.07-2.56) and non-smoking adolescents (AOR=3.15, 95% CI: 1.48-4.71) who had at least one smoking parent/guardian regardless of their own smoking status. Male adolescents had higher risk of SHS exposure compared to their female counterparts (current smoker AOR=1.66, 95% CI: 1.07-2.56; non-smoker AOR=1.50, 95% CI: 1.12-2.00) and increased with age, regardless of their smoking status.
CONCLUSIONS: Our findings suggest that prevalence of exposure to SHS among school-going adolescents in Malaysia is high. Parents should be advised to stop smoking or abstain from smoking in the presence of their children. Education programmes are recommended to increase awareness on avoidance of SHS as well as smoking cessation interventions for both adolescents and their parents.
METHODS: Electronic databases, including PubMed, EMBASE, Cochrane Library, Science Direct, Google Scholar, were systematically searched from the initiation of the database until 12 December 2020. All relevant studies about smoking and COVID-19 were screened using a set of inclusion and exclusion criteria. The Newcastle-Ottawa Scale was used to assess the methodological quality of eligible articles. Random meta-analyses were conducted to estimate odds ratios (ORs) with 95% confidence interval (CIs). Publication bias was assessed using the funnel plot, Begg's test and Egger's test.
RESULTS: A total of 1248 studies were retrieved and reviewed. A total of 40 studies were finally included for meta-analysis. Both current smoking and former smoking significantly increase the risk of disease severity (OR=1.58; 95% CI: 1.16-2.15, p=0.004; and OR=2.48; 95% CI: 1.64-3.77, p<0.001; respectively) with moderate appearance of heterogeneity. Similarly, current smoking and former smoking also significantly increase the risk of death (OR=1.35; 95% CI: 1.12-1.62, p=0.002; and OR=2.58; 95% CI: 2.15-3.09, p<0.001; respectively) with moderate appearance of heterogeneity. There was no evidence of publication bias, which was tested by the funnel plot, Begg's test and Egger's test.
CONCLUSIONS: Smoking, even current smoking or former smoking, significantly increases the risk of COVID-19 severity and death. Further causational studies on this association and ascertianing the underlying mechanisms of this relation is warranted.
METHODS: A self-administered validated questionnaire was used to obtain data from the nationally representative samples of school-going adolescents aged 11-19 years in Malaysia. Prevalence rates were computed and chi-squared tests and multiple logistic regression were conducted.
RESULTS: Of the participants, 23.3% reported exposure to SHS at least once in the car of their parents/guardians during the last 7 days before the survey. The prevalence and likelihood of SHS exposure were significantly higher in Malays, descendants of natives of Sabah and Sarawak, schools in rural areas, females, and current smokers. However, age group and knowledge on the harmful effects of SHS were not significant after adjusting for confounding effects.
CONCLUSIONS: A substantial proportion of school-going adolescents were exposed to secondhand smoke in the car of their parents/guardians. This highlights the need for effective tobacco control measures to include health promotion and smoke-free car regulations to be introduced to prevent severe health hazards and to reduce smoking initiation among non-smoking adolescents.
METHODS: The PubMed, SAGE, Science Direct, the Cochrane Library and Ovid databases were searched for observational studies before October 2018. Methodological quality was assessed using the Newcastle-Ottawa Quality Assessment Scale (NOS).
RESULTS: Nine case-control studies involving 4385 lung cancer cases and 4142 controls were included in the analysis. The random-effects model was used to combine results from individual studies. The pooled odds ratio was 0.39 (95% CI: 0.27-0.56). There was no heterogeneity across studies (χ2=2.49, p=0.96, I2=0%).
CONCLUSIONS: Current evidence from the case-control studies suggests that the CYP2A6 whole-gene deletion polymorphism decreases the risk of lung cancer. Further research is needed to identify any potential confounding factors that may impact this association.
METHODS: This secondary dataset analysis used data from the National Health and Morbidity Survey (NHMS) 2018. Data from 3914 participants were collected on elderly health in the Malaysian population. Sociodemographic characteristics were recorded. Smoking status was grouped as current smokers, former smokers, and non-smokers. A validated Malay language version of the Geriatric Depression Scale (M-GDS-14) was used to screen for depression among the elderly.
RESULTS: There was a significant association between smoking status with location, gender, employment status, marital status, ethnicity, education level, income, and depression. Current smokers are significantly higher in rural than urban areas. Among depressed participants, 65.7%, 17.1% and 17.2% were non-smokers, former smokers and current smokers, respectively. Multiple logistic regression showed that single (unmarried/separated/ divorced/widowed) participants were more likely to be depressed compared to married participants (AOR=1.68; 95% CI: 1.16-2.43). Whilst unemployed participants were more likely to be depressed than those who were employed (AOR=1.72; 95% CI: 1.22-2.44). Other Bumiputras were more likely to have depression compared to Malay, Chinese and Indian participants. Participants without formal education were more likely to be depressed compared to those having tertiary education. These participants have a 2-fold increased risk of depression (AOR=2.13; 95% CI: 1.02-4.45). Participants whose monthly salaries were <2000 MYR (AOR=3.67; 95% CI: 1.84-7.31) and 1000-1999 MYR (AOR=2.71; 95% CI: 1.23-5.94) were more likely to have depression compared with those who had received ≥3000 MYR. Ever smokers were more likely to be depressed than non-smokers (AOR=1.68; 95% CI: 1.23-2.29).
CONCLUSIONS: Elderly Malaysians are indeed at risk of developing depression particularly if they had ever smoked. Public health awareness and campaigning are pertinent to disseminate these outcomes in order to spread the awareness associated with smoking-related depression.
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 analyzed data from the PATH (Population Assessment of Tobacco and Health) study wave 4 (2016-2018) and wave 5 (2018-2019). Based on questionnaires from wave 4, we categorized tobacco use as: 1) non-use, 2) exclusive e-cigarette use, 3) combustible cigarette use, and 4) dual use. Presence of established cardiovascular disease was examined at wave 4, and participants aged >40 years were asked about chest pain during wave 5. We used binary logistic regression models to determine the association between tobacco exposures and self-reported chest pain.
RESULTS: We evaluated a total of 11254 adults. The rates of chest pain were 1518 out of 7055 non-users, 49 from 208 exclusive e-cigarette users, 1192 from 3722 combustible cigarette users, and 99 out of 269 dual users. In the multivariable models adjusted for relevant covariates, combustible cigarette users (adjusted odds ratio, AOR=1.77; 95% CI: 1.56-2.01) and dual users (AOR=2.22; 95% CI: 1.61-3.05) had higher odds of reporting ever having chest pain, as well as having chest pain in the past 30 days. Conversely, exclusive e-cigarette users had similar odds of reporting chest pain compared to non-users (AOR=1.03; 95% CI: 0.69-1.54) and lower odds than combustible and dual users. In sensitivity analyses, categorizing individuals based on their reported history of cardiovascular disease, overall findings were similar.
CONCLUSIONS: Exclusive e-cigarette use is associated with a lower rate of chest pain compared to combustible cigarette use and dual use.
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.
METHODS: The self-administered online survey utilized in this cross-sectional study was derived from the Global Health Professions Students Survey (GHPSS), which involved medical, dental, and pharmacy students. A total of 328 participants completed a questionnaire from June to August 2022, with a response rate of 91.1%.
RESULTS: The overall smoking prevalence was 4.6% among the medical, dental, and pharmacy students who participated in this study; 46.7% of current smokers were exposed to secondhand smoke at home compared to 17.6% of non-smokers (p=0.011); and 66.7% of smokers were exposed to secondhand smoke in public compared to 40.3% of non-smokers (p=0.043). In all, 99.1% of respondents supported the smoking ban and 46.7% of current smokers supported the smoking ban in discos/bars/pubs, compared to 82.0% of non-smokers (p=0.002). Of the participants, 96.6% received lessons on the danger of tobacco, and 65.5% received smoking cessation training. Among factors associated with current smoking was gender; male students had a 19-fold higher likelihood of smoking than female students (adjusted odds ratio, AOR=19.25; 95% CI: 4.25-87.19, p<0.001). In addition, home exposure to secondhand smoke was four times more common for current smokers (OR=4.11; 95% CI: 1.43-11.79, p=0.009).
CONCLUSIONS: Although smoking prevalence was low among the students in this study, there was a higher percentage of them exposed to secondhand smoke at home and in public.