MATERIALS AND METHODS: This prospective randomised control trial was conducted on smokers in a factory. A total of 163 participants were recruited and randomised into control and intervention groups using a table of random numbers. The intervention group received a ten-minute brief physician counselling session to quit smoking. Stages of smoking behaviour were measured in both groups using a translated and validated questionnaire at baseline, one month and three months post intervention.
RESULTS: There was a significant improvement in smoking behaviour at one-month post intervention (p=0.024, intention to treat analysis; OR=2.525; CI=1.109-5.747). This was not significant at three-month post intervention (p=0.946, intention to treat analysis; OR=1.026; 95% CI=0.486-2.168).
CONCLUSIONS: A session of brief physician counselling was effective in improving smokers' behaviour at workplace, but the effect was not sustained.
METHOD: Based on the proposed model, a quantitative method was employed to obtain data from G7 construction industry operating within the peninsular Malaysia. Out of the 180 copies of questionnaire, 165 copies were properly filled, returned, and used for the analysis. PLS-SEM was used to analyze the obtained data.
RESULTS: The findings of the study affirmed that specialization, centralization, and management of risk by the construction industry had positive correlation.
CONCLUSIONS: As anticipated, coercive pressure had positive moderating correlation with both formalization and the management of risk by the construction industry. Similarly, it was also found that in the course of carrying out construction activities, coercive pressure made significant interactive influence on formalization, specialization, and centralization. Practical Applications: Coercive pressure reduced the frequency of accidents among workers in the process of carrying out construction works.
METHODS: An online health survey was conducted between May to July 2017 among employees from 47 private companies located in urban Malaysia. A total of 5235 respondents completed the 20-min online employee health survey on a voluntary basis. Chi-Square or Fisher's exact tests were used to determine association between income with demographic and categorical factors of absenteeism and presenteeism. Multivariate linear regression was used to identify factors predicting absenteeism and presenteeism.
RESULTS: More than one third of respondents' monthly income were less than RM4,000 (35.4%), 29.6% between RM4,000-RM7,999 and 35.0% earned RM8,000 and above. The mean age was 33.8 years (sd ± 8.8) and 49.1% were married. A majority were degree holders (74.4%) and 43.6% were very concerned about their financial status. Mean years of working was 6.2 years (sd ± 6.9) with 68.9% satisfied with their job. More than half reported good general physical health (54.5%) (p = 0.065) and mental health (53.5%) (p = 0.019). The mean hours of sleep were 6.4 h (sd ± 1.1) with 63.2% reporting being unwell due to stress for the past 12 months. Mean work time missed due to ill-health (absenteeism) was 3.1% (sd ± 9.1), 2.8% (sd ± 9.1) and 1.8% (sd ± 6.5) among employees whose monthly income was less than RM4,000, RM4,000-RM7,999 and over RM8,000 respectively (p = 0.0066). Mean impairment while working due to ill-health (presenteeism) was 28.2% (sd ± 25.3), 24.9% (sd ± 25.5) and 20.3% (sd ± 22.9) among employees whose monthly income was less than RM4,000, RM4,000-RM7,999 and over RM8,000 respectively (p health, sleep length and being unwell due to stress.
CONCLUSIONS: A combination of socioeconomic, physical and mental health factors predicted absenteeism and presenteeism with different strengths. Having insufficient income may lead to second jobs or working more hours which may affect their sleep, subjecting them to stressful condition and poor physical health. These findings demand holistic interventions from organizations and the government.
METHODS: A baseline cross-sectional analysis of the Malaysian Cohort was conducted, which included 105 391 adults. Multiple logistic regression analyses were conducted for these three diseases across 20 job sectors compared with the unemployed/homemaker sector.
RESULTS: The prevalence of T2DM, hypercholesterolemia and obesity was 16.7%, 38.8% and 33.3%, respectively. The Accommodation & Food Service Activities and Transportation & Storage sectors had significantly higher odds for T2DM (adjusted [adj.] prevalence odds ratio [POR] 1.18, p=0.007 and adj. POR 1.15, p=0.008, respectively). No job sector had significantly higher odds for hypercholesterolemia compared with the unemployed/homemaker sector. Only the Accommodation & Food Service Activities sector had significantly higher odds for obesity (adj. POR 1.17, p≤0.001).
CONCLUSIONS: Many job sectors were significantly associated with lower odds of having these three diseases when compared with the unemployed/homemaker sector. These differing associations between diverse job sectors and these diseases are important for public health intervention initiatives and prioritization.