MATERIALS AND METHODS: We analysed internationally comparable representative household survey data from 33,482 respondents aged ≥ 15 years in Indonesia, Malaysia, Romania, Argentina and Nigeria for determinants of tobacco use within each country. Socio-demographic variables analysed included gender, age, residency, education, wealth index and awareness of smoking health consequences. Current tobacco use was defined as smoking or use of smokeless tobacco daily or occasionally.
RESULTS: The overall prevalence of tobacco use varied from 5.5% in Nigeria to 35.7% in Indonesia and was significantly higher among males than females in all five countries. Odds ratios for current tobacco use were significantly higher among males for all countries [with the greatest odds among Indonesian men (OR=67.4, 95% CI: 51.2-88.7)] and among urban dwellers in Romania. The odds of current tobacco use decreased as age increased for all countries except Nigeria where. The reverse was true for Argentina and Nigeria. Significant trends for decreasing tobacco use with increasing educational levels and wealth index were seen in Indonesia, Malaysia and Romania. Significant negative associations between current tobacco use and awareness of adverse health consequences of smoking were found in all countries except Argentina.
CONCLUSIONS: Males and the socially and economically disadvantaged populations are at the greatest risk of tobacco use. Tobacco control interventions maybe tailored to this segment of population and incorporate educational interventions to increase knowledge of adverse health consequences of smoking.
Objectives: A cross-sectional study was carried out to explore the association of occupational, socio-demographic, and lifestyle factors with lung functions in traffic policemen in Kuala Lumpur (KL) and Johor Bahru (JB).
Methods: A spirometer was used to measure lung function of subjects, whereas a self-administered questionnaire was used to obtain their information on background data, lifestyle, and occupational factors. The statistical test used was Spearman rho's test and chi-square test; then, the factors were further tested using Logistic regressions.
Findings: 134 male subjects were selected as respondents in this study with 83% response rate. Among all the factors tested, age (FVC: χ = 8.42(3), p = 0.04), (FEV: χ = 8.26(3), p = 0.04), rank (FVC: χ = 8.52(3), p = 0.04), (FEV: χ = 8.05(3), p = 0.04), duration of services (FVC: χ = 11.0(1), p = 0.04), (FEV: χ = 6.53(1), p = 0.01), and average working hours (with the Measured FVC (litre), r = -3.97, p < 0.001; Measured FEV1 (litre), r = -3.70, p < 0.001; Predicted FVC, r = -0.49, p < 0.001; Predicted FEV1, r = -0.47, p < 0.001; and %Ratio FEV1/FV, r = -0.47, p < 0.001) were significantly related to lung function among traffic police.
Conclusions: Occupational factors play a crucial role, and hence, the authorities should take action in generating flexible working hours and the duration of services accordingly. The data from this study can help by serving as a reference to the top management of traffic police officers to develop occupational safety and health guideline for police officers to comply with the Occupational Safety and Health Act (OSHA, Act 514 1994).
DESIGN: This was a population-based, cross-sectional study whereby subjects were adults aged 18 years old and above. A workshop on the identification of OML was held to train and calibrate dental officers prior to data collection in the field. Sociodemographic and risk habits data were collected via face-to-face interview, whilst presence of OML and clinical details of lesions such as type and site were collected following clinical oral examination by the examiners. Data analysis was carried out using the Statistical Package for Social Science (SPSS) version 12.0. The association between risk habits and risk of OPMD was explored using logistic regression analysis.
RESULTS: A total of 1634 subjects were recruited. Prevalence of OML for this population was 54.1%. Linea alba was the most common lesion seen (28.7%). This study showed an overall OPMD prevalence of 5.6%. The most common type of OPMD was leukoplakia (64.8%), followed by lichen planus (30.8%). Subjects who only smoked were found to have an increased risk for OPMD of almost four-fold (RR 3.74, 95%CI 1.89-7.41). The highest risk was found for betel quid chewers, where the increased risk observed was more than six times (RR 6.75, 95%CI 3.32-13.72). Alcohol consumption on its own did not seem to confer an increased risk for OPMD, however when practiced concurrently with smoking, a significant risk of more than five times was noted (RR 5.69 95%CI 3.14-10.29).
CONCLUSION: The prevalence of OML was 54.1%, with linea alba being the most commonly occurring lesion. Smoking, alcohol consumption and betel quid chewing were found to be associated with the prevalence of OPMD, which was 5.6%.
METHODS: A quasi experimental interventional study involving 166 non-smokers adolescents, aged 13 to 14 years old were carried out in two schools located in two different suburbs. Both schools had equal number of participants. One school was given the smoking prevention module for intervention while the control school only received the module after the study had been completed. The knowledge on smoking and its harmful effects and smoking refusal skill score were assessed using a set of validated Malay questionnaires at baseline, two weeks and eight weeks after the intervention. Repeated measure ANCOVA was used to analyse the mean score difference of both groups at baseline and after intervention.
RESULT: Baseline analysis shows no significant difference in knowledge score between the study groups (p = 0.713) while post intervention, it shows significant inclination of knowledge score in intervention group and the difference was significant after controlling the gender [F(df) = 15.96(1.5), p <0.001]. The mean baseline for refusal skills score in the control and intervention groups were 30.89(6.164) and 28.02(6.241) respectively (p= 0.003). Post intervention, there is a significant difference in the crude mean and the estimated marginal means for smoking refusal skills score between the two groups after controlling for sex [F(df) = 5.66(1.8), p = 0.005].
CONCLUSION: This smoking prevention module increased the level of knowledge on smoking and its harmful effects and smoking refusal skill among the secondary school students. Thus, it is advocated to be used as one of the standard modules to improve the current method of teaching in delivering knowledge related to harmful effects of smoking and smoking refusal skill to the adolescents in Malaysia.
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METHODS: We analysed Demographic and Health Survey data on tobacco use collected from large nationally representative samples of men and women in 54 LMICs. We estimated the weighted prevalence of any current tobacco use (including smokeless tobacco) in each country for 4 educational groups and 4 wealth groups. We calculated absolute and relative measures of inequality, that is, the slope index of inequality (SII) and relative index of inequality (RII), which take into account the distribution of prevalence across all education and wealth groups and account for population size. We also calculated the aggregate SII and RII for low-income (LIC), lower-middle-income (lMIC) and upper-middle-income (uMIC) countries as per World Bank classification.
FINDINGS: Male tobacco use was highest in Bangladesh (70.3%) and lowest in Sao Tome (7.4%), whereas female tobacco use was highest in Madagascar (21%) and lowest in Tajikistan (0.22%). Among men, educational inequalities varied widely between countries, but aggregate RII and SII showed an inverse trend by country wealth groups. RII was 3.61 (95% CI 2.83 to 4.61) in LICs, 1.99 (95% CI 1.66 to 2.38) in lMIC and 1.82 (95% CI 1.24 to 2.67) in uMIC. Wealth inequalities among men varied less between countries, but RII and SII showed an inverse pattern where RII was 2.43 (95% CI 2.05 to 2.88) in LICs, 1.84 (95% CI 1.54 to 2.21) in lMICs and 1.67 (95% CI 1.15 to 2.42) in uMICs. For educational inequalities among women, the RII varied much more than SII varied between the countries, and the aggregate RII was 14.49 (95% CI 8.87 to 23.68) in LICs, 3.05 (95% CI 1.44 to 6.47) in lMIC and 1.58 (95% CI 0.33 to 7.56) in uMIC. Wealth inequalities among women showed a pattern similar to that of men: the RII was 5.88 (95% CI 3.91 to 8.85) in LICs, 1.76 (95% CI 0.80 to 3.85) in lMIC and 0.39 (95% CI 0.09 to 1.64) in uMIC. In contrast to men, among women, the SII was pro-rich (higher smoking among the more advantaged) in 13 of the 52 countries (7 of 23 lMIC and 5 of 7 uMIC).
INTERPRETATION: Our results confirm that socioeconomic inequalities tobacco use exist in LMIC, varied widely between the countries and were much wider in the lowest income countries. These findings are important for better understanding and tackling of socioeconomic inequalities in health in LMIC.