METHODS: A nationwide data set was examined for this secondary data analysis. The dependent variable was the degree of risk, which was measured based on the number of high-risk behaviours in which adolescents participated. Age, gender, ethnicity, self-rated academic performance, family size, parental marital status and parental academic attainment were included as independent variables. Analyses stratified by educational level were conducted. Odds ratios (ORs) were calculated using ordered logit.
RESULTS: The most common high-risk behaviour among Malaysian adolescents was physical inactivity (35.97%), followed by smoking (13.27%) and alcohol consumption (4.45%). The majority of adolescents had low risks (52.93%), while only a small proportion had high risks (6.08%). Older age was associated with increased odds of having high risks (OR: 1.26). Male adolescents had higher odds of being in a high-risk category compared to female adolescents (OR: 1.28). Compared to Malays, Chinese adolescents had higher odds of being in a high-risk category (OR: 1.71), whereas Indian adolescents had lower odds (OR: 0.65). Excellent academic performance was associated with reduced odds of participating in high-risk behaviours (OR: 0.41).
CONCLUSION: Personal factors are important determinants of high-risk behaviours. This study provides a better understanding of those adolescent groups that are at greater risk.
PRACTICAL IMPLICATIONS: An intervention directed towards reducing participation in high-risk behaviours among adolescents who have both poor academic performance and less-educated parents may yield promising outcomes.
PATIENTS AND METHODS: A nationally representative data of adolescents that consists of 25399 respondents is used. The demographic (age, gender, education) and lifestyle (fruits and vegetables consumption, carbonated soft drink consumption, cigarette smoking, alcohol drinking, sex behaviour, participation in physical education class, obesity) determinants of physical activity are assessed using binomial regression.
RESULTS: The results show that age is negatively associated with time spent in physical activity. However, being male and education levels are positively related to time spent in physical activity. Having unhealthy lifestyle and being obese are associated with low levels of physical activity. Physical education seems to promote participation in physical activity.
CONCLUSION: In conclusion, demographic and lifestyle factors play an important role in determining levels of physical activity among adolescents. In order to reduce the prevalence of physically inactive adolescents, policy makers should focus primarily on late adolescents, females, adolescents who engage in unhealthy lifestyle and seldom attend physical education classes, as well as obese adolescents.
METHODS: A cross-sectional study among 15,639 Malaysian adult males aged 18 years and above was conducted using proportional to size stratified sampling method. The socio-demographic variables examined were level of education, occupation, marital status, residential area, age group and monthly household income.
RESULTS: The prevalence of smoking among adult males in Malaysia was 46.5% (95% CI: 45.5-47.4%), which was 3% lower than a decade ago. Mean age of smoking initiation was 18.3 years, and mean number of cigarettes smoked daily was 11.3. Prevalence of smoking was highest among the Malays (55.9%) and those aged 21-30 years (59.3%). Smoking was significantly associated with level of education (no education OR 2.09 95% CI (1.67-2.60), primary school OR 1.95, 95% CI (1.65-2.30), secondary school OR 1.88, 95% CI (1.63-2.11), with tertiary education as the reference group). Marital status (divorce OR 1.67, 95% CI (1.22-2.28), with married as the reference group), ethnicity (Malay, OR 2.29, 95% CI ( 1.98-2.66; Chinese OR 1.23 95% CI (1.05-1.91), Other Bumis OR 1.75, 95% CI (1.46-2.10, others OR 1.48 95% CI (1.15-1.91), with Indian as the reference group), age group (18-20 years OR 2.36, 95% CI (1.90-2.94); 20-29 years OR 3.31 , 95% CI 2.82-3.89; 31-40 years OR 2.85 , 95% CI ( 2.47-3.28); 41-50 years OR 1.93, 95% CI (1.69-2.20) ; 51-60 years OR 1.32, 95% CI (1.15-1.51), with 60 year-old and above as the reference group) and residential area (rural OR 1.12 , 95% CI ( 1.03-1.22)) urban as reference.
CONCLUSION: The prevalence of smoking among Malaysian males remained high in spite of several population interventions over the past decade. Tobacco will likely remain a primary cause of premature mortality and morbidity in Malaysia. Continuous and more comprehensive anti-smoking policy measures are needed in order to further prevent the increasing prevalence of smoking among Malaysian men, particularly those who are younger, of Malay ethnicity, less educated, reside in rural residential area and with lower socio-economic status.
METHODS: A quasi-experimental (before-after) study design was adopted. Pre-intervention data were collected over 7 months (January-July 2017). Subsequently, the workflow redesign (eaST system) was implemented and the effect of the intervention (August 2017-February 2018) was evaluated. Univariate analysis was used to compare the differences between pre-intervention and post-intervention of pharmacy waiting time and near-missed events. Significant factors affecting study outcomes were analysed using linear regression analysis.
KEY FINDINGS: A total of 210,530 prescriptions were analysed. The eaST system significantly increases the percentage of prescriptions dispensed within 30 min per day (median = 68 (interquartile range (IQR) = 41) vs. median = 93 (IQR = 33), P < 0.001) and reduced the mean percentage of near-missed events (mean = 50.71 (standard deviation (SD) = 23.95) vs. mean = 27.87 (SD = 12.23), P < 0.001). However, the eaST system's effects on related outcomes were conditional on a three-way interaction effect. The eaST system's effects on pharmacy waiting time were influenced by the number of prescriptions received and the number of PhIS server disruptions. Conversely, the eaST system's effects on near-missed events were influenced by the number of pharmacy personnel and number of controlled medications.
CONCLUSIONS: Overall, the eaST system improved the pharmacy waiting time and reduced near-missed events.