METHODS: The National Health and Morbidity Survey (NHMS) 2017 (n = 8230) was used for analyses. It was a nationwide survey conducted in Malaysia. The dependent variables were measured by three risk behaviors (cigarette smoking, alcohol drinking and use of illicit drugs). Probit regressions were utilized to examine the effect of mental health on the probability of smoking, drinking and using illicit drugs. Demographic and lifestyle factors were used as the control variables. Truancy was identified as a mediating variable.
RESULTS: Anxiety, depression and suicidal ideation affected cigarette smoking, alcohol drinking and use of illicit drugs through mediation of truancy. After controlling for demographic and lifestyle factors, students with anxiety, depression and suicidal ideation were more likely to smoke, drink and use illicit drugs compared with their peers without any mental health disorders. Furthermore, the likelihood of consuming cigarettes, alcohol and illicit drugs was found to be higher among students who played truant than those who did not.
CONCLUSION: Mental health plays an important role in determining participation in risk behaviors among ethnic minority students in Malaysia. Public health administrators and schools have to be aware that students who suffer from mental health disorders are likely to indulge in risk behaviors.
METHODS: Sleep disturbances were measured in a sample of 65 youth with DS aged 6-17 years using the Children's Sleep Habits Questionnaire (CSHQ) and actigraph watches assessing sleep efficiency, sleep duration and wake after sleep onset. Behavioural challenges were evaluated through externalising and internalising subscales of the Child Behavior Checklist (CBCL) and of the Scales of Independent Behavior, Revised (SIB-R).
RESULTS: The findings demonstrated that over a period of time, sleep problems are significantly associated with both externalising and internalising behaviours as measured by CSHQ and CBCL, even after accounting for the effects of IQ and SIB-R Broad Independence. No significant correlations were observed on a daily basis over seven consecutive days, as measured by actigraphy and both externalising and internalising indices of SIB-R.
CONCLUSIONS: The results highlight the complexity of the sleep-behaviour relationship in DS, indicating that while chronic sleep issues impact long-term behaviours, nightly variations do not predict immediate behavioural changes.
OBJECTIVE: To determine the effectiveness of a teacher-led Healthy Lifestyle Program on eating behaviors among adolescents in Malaysia.
METHODS: This was a cluster randomized controlled trial (conducted in 2012 to 2014), with 100 schools randomly selected from 721 schools, then assigned to 50 intervention schools and 50 control schools. A Healthy Eating and Be Active among Teens (HEBAT) module was developed for pretrained teachers to deliver a Healthy Lifestyle Program on eating behaviors among adolescents. Eating behaviors of the respondents was determined using Eating Behaviors Questionnaire. Linear Mixed Model analysis and χ2 test were used to determine within- and between-group effects of studied variables.
RESULTS: A total of 4277 respondents participated in this study, with 2635 samples involved in the final analysis, comprised of 921 intervention and 1714 control respondents. There were 32.4% (36.4%) males and 67.6% (63.6%) females in the intervention (control) group. Mean age was comparable between the groups (intervention = 12.98 years; control = 12.97 years). Majority of the respondents skipped meals at baseline (intervention = 74.7%; control = 79.5%). After the program, intervention respondents had higher consumption frequency of lunch, dinner, and mid-morning snack but a lower consumption frequency of late-evening snack and meal skipping behaviors than their control counterparts.
CONCLUSION: The teacher-led Healthy Lifestyle Program was effective in reducing meal-skipping behaviors among Malaysian adolescents.
METHODS: A community-based cross-sectional study was conducted among 1,344 adolescents in Sarawak using face-to-face interviews. Hierarchical binary logistic regression analysis was performed to identify factors that determine the risk of suicide among adolescents.
RESULTS: Two predictive models were constructed. Both models revealed that being female (OR=1.578, 95 % CI: 1.191, 2.092, p=0.001), having Malay ethnicity (OR=1.733, 95 % CI: 1.236, 2.429, p=0.001) and having a disease significantly increased the risk of suicide (OR=1.895, 95 % CI: 1.221, 2.942, p=0.004). In particular, Model 2, which showed a better fit, found that occasional religious practice (OR=1.610, 95 % CI: 1.126, 2.303, p=0.009), poor parental relationships (OR=1.739, 95 % CI: 1.035, 2.922, p=0.037) and higher addiction (OR=1.015, 95 % CI: 1.008, 1.022, p=0.001), depression (OR=1.919, 95 % CI: 1.241, 2.968, p=0.003), and stress (OR=2.707, 95 % CI: 1.689, 4.340, p=0.001) scores were significantly associated with an increased risk of suicide.
CONCLUSIONS: This study sheds light on multiple factors that contribute to the risk of suicide among adolescents in Sarawak. These findings underscore the importance of holistic prevention strategies, including psychological and social dimensions, to mitigate the risk of suicide in this population. Further research is warranted to understand the complex interplay of these factors and guide the development of targeted interventions.
METHODS: The GYTS covered a total of 2,242 Bangladeshi, 1,444 Nepalese and 1,377 Sri-Lankan youths aged 13-15 years. They represented response rates of 88.9%, 94.6%, and 85.0% for the three countries, respectively. Socioeconomic, environmental, motivating, and programmatic predictors of TC were examined using cross tabulations and logistic regressions.
RESULTS: Prevalence of TC was 6.9% (9.1% in males, 5.1% in females) in Bangladesh, 9.4% (13.2% in males, 5.3% in females) in Nepal and 9.1% (12.4% in males, 5.8% in females) in Sri Lanka. The average tobacco initiation age was 9.6, 10.24 and 8.61 years, respectively. Cross tabulations showed that gender, smoking among parents and friends, exposure to smoking at home and public places, availability of free tobacco were significantly (P < 0.001) associated with TC in all three countries. The multivariable analysis [odds ratio (95% confidence interval)] indicated that the common significant predictors for TC in the three countries were TC among friends [1.9 (1.30-2.89) for Bangladesh, 4.10 (2.64-6.38) for Nepal, 2.34 (1.36-4.02) for Sri Lanka], exposure to smoking at home [1.7 (1.02-2.81) for Bangladesh, 1.81 (1.08-2.79) for Nepal, 3.96 (1.82-8.62) for Sri Lanka], exposure to smoking at other places [2.67 (1.59-4.47) for Bangladesh, 5.22 (2.76-9.85) for Nepal, 1.76 (1.05-2.88) for Sri Lanka], and the teaching of smoking hazards in schools [0.56 (0.38-0.84) for Bangladesh, 0.60 (0.41-0.89) for Nepal, 0.58 (0.35-0.94) for Sri Lanka].
CONCLUSIONS: An understanding of the influencing factors of youth TC provides helpful insights for the formulation of tobacco control policies in the South-Asian region.