Mortality estimates are important parameters for health monitoring and are routinely used as evidence for health policy and planning. This study aimed to estimate the mortality component of Burden of Disease in Malaysia in 2008. The 2008 mortality data from the Statistics Department were used to estimate cause-specific mortality (by age and sex) in Malaysia. Data were coded using the ICD10 (International Classification of Disease) coding. Calculation of mortality component of Burden of Disease (ie: Years of Life Lost (YLL) was done using the standard Global Burden of Disease Methodology. The total estimated deaths in Malaysia in 2008 were 124,857, of which 72,202 (57.8%) were males. The total years of life lost (YLL) for the Malaysian population in 2008 was 1.51 million in which 0.92 million (60.7%) was among males. Almost three quarter (68%) of the burden of premature deaths resulted from non-communicable diseases, followed by communicable diseases (20%) and injury (12%). Among the top three leading causes of YLL were ischaemic heart disease (17.1%), stroke (9.6%) and road traffic injuries (8.3%). In Malaysia, premature mortality mainly contributed by non-communicable diseases followed by communicable diseases and injury. A multi-agency collaboration is needed to prevent premature death and to improve quality of life.
mortality ; Cause of Death ; Life Expectancy ; Mortality, Premature

The most effective and affordable public health strategy to prevent hypertension, stroke and renal disease is by reducing daily salt consumption. Therefore, this study aims to determine the association of knowledge, attitude and practice on salt diet intake and to identify foods contributing to high sodium intake. Secondary data analysis was performed on MySalt 2016 data. It was conducted from November 2015 until January 2016 which involving Ministry of Health Staff worked at 16 study sites in Malaysia. Salt intake was measured using 24 hours urinary sodium excretion. Food frequency questionnaire was used to determine the sodium sources. Knowledge, attitude and practice of salt intake were assessed using a validated questionnaire adapted from WHO. Demographic data and anthropometric measures also were collected. Sodium levels of more than 2400mg/day was categorised as high sodium intake. Data were analysed using SPSS software version 21. The mean sodium intake estimated by 24 hours urinary sodium excretion was 2853.23 + 1275.8 mg/day. Food groups namely rice/noodles (33.8%), sauces/seasoning (20.6%), meat and poultry (12.6%) and fish/seafoods (9.3%) were the major contributors of dietary sodium. In multiple logistic regression analysis, being a male (aOR=2.83, 95% CI 2.02 – 3.96) and obese (aOR=6.78, 95% CI 1.98 – 23.18) were significantly associated with high urinary sodium excretions. In addition, those who were unsure that high salt intake can cause hypertension (aOR=1.24, 95% CI 0.65 – 2.36), those who think that they consumed too much salt (aOR=2.10, 95% CI 1.13 – 3.87) and those who only use salt rather than other spices for cooking (aOR=2.07, 95% CI 1.29 – 3.30) were significantly associated with high urinary sodium excretion. This study showed that the main sources of sodium among Malay healthcare staff is cooked food. Poor knowledge and practice towards reducing salt consumption among them contributes to the high sodium consumption. The practice of healthy eating among them together with continuous awareness campaign is essential in order to educate them to minimize sodium consumption and to practice healthy eating.​

Introduction: Cardiovascular disease (CVD) caused significant burden to Malaysia as it accounted for 36% of total deaths. This study aims to evaluate the burden of cardiovascular risk factors among Malaysian adult and assess the difference between urban and rural population in the selected communities. Methods: This study is part of the ongoing Prospective Urban Rural Epidemiology (PURE) database, whereby the baseline data were collected since June 2008. CVD risk was measured using INTERHEART risk score which comprised of eleven risk factors i.e. age and gender, family history of heart attack, smoking status, exposure to second hand smoke, diabetes mellitus, hypertension status, waist-hip ratio, self-reported stress, depression, dietary habits and physical activity status. Results: Majority of the studied participants had low cardiovascular risk (57%). Participants from rural area were generally older, had lower educational status, higher prevalence of smokers, obesity, hypertension, diabetes, and more likely to be depressed. In comparison, urbanites had lower physical activities and more likely to be stressful. Mean INTERHEART score among rural participants were higher, especially for male, in comparison to urbanite (11.5±5.83 vs. 10.01±5.74, p<0.001). Conclusion: Contradict to common beliefs, participants in rural areas generally have higher cardiovascular risk factors compared to their urban counterparts. The rural population should be targeted for focused preventive interventions, taking account the socioeconomic and cultural context.