METHODS: This cross-sectional study included 346 adult males aged 18 years old to 68 years old. Socio-demographic characteristics, oral hygiene practices, and shammah use history were surveyed by using a structured interview questionnaire. The clinical assessment for the presence or absence of periodontal pockets was assessed on the basis of community periodontal index. The chi-square test was used to assess significant differences in study groups in terms of the presence of periodontal pockets. Multivariable logistic regression was selected to assess potential associated factors with the development of periodontal pockets.

RESULTS: Among the 346 adult males, 248 (71.7 %), 30 (8.6 %), and 68 (19.7 %) males never used shammah, were former shammah users, and were current shammah users, respectively. The significant associated factors with the development of periodontal pocket were age group (30 years old and above) (Adjusted Odds Ratio (AOR) = 2.03, 95 % CI: 1.13, 3.65; P = 0.018), low family income category (AOR = 2.35, 95 % CI: 1.39, 3.99; P = 0.001), former shammah user (AOR = 2.66, 95 %: CI: 1.15, 6.15; P = 0.022), and current shammah user (AOR = 6.62, 95 %: CI: 3.59, 12.21; P = 0.001).

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).

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.

METHODS: A multistage sampling was performed across rural primary schools in Kuala Krai, Kelantan, Malaysia. Data were collected using self-administered questionnaires and the children aged 10-11 years (n=312) were subjected to cognitive tests including digit span, letter-number sequencing, coding, and symbol search. Cognitive performance was tested using subscales derived from the Wechsler Intelligence Scale for Children.

RESULTS: The prevalence of SHS exposure at home was 55.8%, where 11.9% of children lived with one smoker, while 43.9% of children lived with ≥2 smokers. There was a significant difference in the mean score of the combined cognitive tests between SHS-exposed and non-exposed children after adjustment for sex, parental educational level, family income and academic performance [Pillai's Trace=0.084, F statistic (df)=6.803 (4302), p<0.001].

METHODS: Two overlapping cohorts of adults who reported smoking factory- made cigarettes from Malaysia and Thailand were interviewed face-to-face (3189 were surveyed at baseline and 1781 re-contacted at Wave 2; 2361 current smokers were surveyed at Wave 2 and 1586 re-contacted at Wave 3). In Thailand at baseline, large text only warnings were assessed, while at Wave 2 new large graphic warnings were assessed. In Malaysia, during both waves small text only warnings were in effect. Reactions were used to predict interest in quitting, and to predict making quit attempts over the following inter-wave interval.

RESULTS: Multivariate predictors of "interest in quitting" were comparable across countries, but predictors of quit attempts varied. In both countries, cognitive reactions to warnings (adjusted ORs; 1.57 & 1.69 for Malaysia at wave 1 and wave 2 respectively and 1.29 & 1.19 for Thailand at wave 1 and wave 2 respectively), forgoing a cigarette (except Wave 2 in Malaysia) (adjusted ORs; 1.77 for Malaysia at wave 1 and 1.54 & 2.32 for Thailand at wave 1 and wave 2 respectively), and baseline knowledge (except wave 2 in both countries) (adjusted ORs; 1.71 & 1.51 for Malaysia and Thailand respectively) were positively associated with interest in quitting at that wave. In Thailand only, "cognitive reactions to warnings" (adjusted ORs; 1.12 & 1.23 at wave 1 and wave 2 respectively), "forgoing a cigarette" (adjusted OR = 1.55 at wave 2 only) and "an interest in quitting" (adjusted ORs; 1.61 & 2.85 at wave 1 and wave 2 respectively) were positively associated with quit attempts over the following inter-wave interval. Salience was negatively associated with subsequent quit attempts in both Malaysia and Thailand, but at Wave 2 only (adjusted ORs; 0.89 & 0.88 for Malaysia and Thailand respectively).

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.

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.

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%).

METHODS: The current study estimated the annual spending and lifetime spending of smokers in the target Asia-Pacific countries (Hong Kong, Malaysia, Thailand, South Korea, Singapore, and Australia) on purchasing cigarettes, as well as predicted the revenue that could be generated if smokers spent the money on investment instead of buying cigarettes. Smokers' spending on cigarettes and the potential revenue generated from investment were estimated based on the selling prices of cigarettes, Standards & Poor's 500 Index, and life expectancies of smokers. Data were extracted from reports released by the World Health Organization or government authorities.

RESULTS: The annual expenses (in US$) on purchasing one pack of cigarettes, in decreasing order, were: Australia ($5628.30), Singapore ($3777.75), Hong Kong ($2799.55), Malaysia ($1529.35), South Korea ($1467.30), and Thailand ($657.00). The lifetime spending on purchasing one pack of cigarettes each day were: Australia ($308993.67), Singapore ($207398.48), Hong Kong ($151735.61 for male and $166853.18 for female), South Korea ($80261.31), Malaysia ($72338.26), and Thailand ($31207.50).

METHODS: We analyzed data from the Global Youth Tobacco Survey (GYTS) 2003, GYTS 2009, and the Tobacco and Electronic Cigarette Survey among Malaysia Adolescents (TECMA) 2016. The surveys employed multistage sampling to select representative samples of adolescents attending secondary school in Malaysia. Data were collected using a pre-validated self-administered anonymous questionnaire adopted from the GYTS.

RESULTS: Between 2003 and 2016, major changes occurred in which there were reductions in the prevalence of ever smoking, current smoking, and susceptibility to smoking. Reductions were also observed in exposure to SHS in public places and in the home. The proportion of school-going adolescents who support a ban on smoking in public places increased between 2013 to 2016, and there was a significant reduction in the proportion of respondents that were offered 'free' cigarettes by tobacco company representatives. However, there was no difference in the proportion of adolescents who initiated smoking before the age of 10 years and current smokers seeking advice to quit smoking across the time period.

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.

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%).

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].