OBJECTIVE: To determine the pattern of polysubstance use and its associated factors among general adults in Malaysia.

METHODOLOGY: This was a secondary data analysis from the National Health and Morbidity Survey (NHMS) 2019), a cross-sectional population survey with a two-stage stratified random sampling design. A total of 10,472 Malaysians aged 18 years and above participated in this survey. Polysubstance use was defined as concurrent use of more than one substance, either alcohol, tobacco, or drugs (opioids, marijuana, amphetamine/ methamphetamine or kratom). A latent class analysis (LCA) was used to identify the membership of polysubstance groups. The association of class membership with demographic profiles was examined using Multinomial Logistic Regression analysis.

RESULTS: Fit indices (AIC = 16458.9, BIC = 16443.6) from LCA supported 3 classes solution: Class 1; "moderate-drug" group primarily combination used of tobacco and alcohol (2.4%), Class 2; "high-drug" group using multiple substance including kratom (0.3%) and Class 3; "low-drug" group reporting minimal alcohol and tobacco use or non-user (97.3%). The multinomial model showed young adults (18-40 years) had a higher likelihood of being polysubstance users both for moderate-drug class (OR = 4.1) and high-drug class (OR = 3.9) compared to older age (≥60 years). Chinese (OR = 18.9), Indian (OR = 23.3), Indigenous Sabah & Sarawak (OR = 34.6) and others ethnicity (OR = 8.9) showed higher odds of being moderate-drug users than Malays. The greater odds of moderate-drug use for males (OR = 35.5), working groups (OR = 1.5) and low education level group (OR = 3.2).

METHODS: The study used data from the National Health and Morbidity Survey in 2018. It was a cross-sectional study with two-staged stratified cluster sampling design. In total, 3977 adults aged ≥60 years were selected for this study. Respondents were interviewed face to face using a structured questionnaire. Self-reported diabetes, hypertension or hypercholesterolemia was defined as having ever been told they have these diseases by a medical doctor or paramedic. Data were analyzed using SPSS version 25. The multiple logistic regression model was used to examine the factors associated with the prevalence of self-reporting.

RESULTS: The prevalence of self-reported diabetes, hypertension and hypercholesterolemia among older persons in Malaysia were 27.7%, 51.1% and 41.8% respectively. Presence of other comorbidities and being obese showed higher odds for all three diseases. Indians, unemployed, inactive had higher odds for diabetes. Other Bumiputras, unemployed, non-smoker, obese and inactive had higher odds for hypertension. Non-smoker had higher odds for hypercholesterolemia.

METHODS: This study was a secondary data analysis from the National Health and Morbidity Survey (NHMS) 2017, a cross-sectional survey conducted among Malaysian school-going adolescents aged 13 to 17. The NHMS utilised a two-stage stratified cluster sampling. Multivariate Multinomial Logistic Regression analysis was applied.

RESULTS: The overall prevalence of single substance use and polysubstance use among adolescents were 17.2% and 5.1% respectively. The multinomial model showed a higher likelihood of being single or polysubstance user among male (single user OR = 3.0, poly user OR = 4.6), others Bumiputeras vs Malay (single user OR = 1.7, poly user OR = 5.3), those who live with a single parent (single user OR = 1.2, poly user OR = 1.4), involved in truancy (single user OR = 1.7, poly user OR = 3.6) and being bullied (single user OR = 1.3, poly user OR = 3.4), those who had lack of peer support (single user OR = 1.3, poly user OR = 1.4), poor parental bonding (single user OR = 1.4, poly user OR = 1.8), depression (single user OR = 1.4, poly user OR = 3.2) and those who had no close friend (single user OR = 1.3, poly user OR = 2.7).

METHODS: Baseline and sixth month data from the MyBFF@home study were used for this purpose. A total of 169 of overweight and obese respondents answered the IPAQ-SF and were asked to use a pedometer for 7 days. Data from IPAQ-SF were categorised as inactive and active while data from pedometer were categorised as insufficiently active and sufficiently active by standard classification. Data on sociodemographic and anthropometry were also obtained. Cohen's kappa was applied to measure the agreement of IPAQ-SF and pedometer in determining the physical activity level. Pre-post cross tabulation table was created to evaluate the changes in physical activity over 6 months.

RESULTS: From 169 available respondents, 167 (98.8%) completed the IPAQ-SF and 107 (63.3%) utilised the pedometer. A total of 102 (61.1%) respondents were categorised as active from the IPAQ-SF. Meanwhile, only 9 (8.4%) respondents were categorised as sufficiently active via pedometer. Cohen's κ found there was a poor agreement between the two methods, κ = 0.055, p > 0.05. After sixth months, there was + 9.4% increment in respondents who were active when assessed by IPAQ-SF but - 1.3% reductions for respondents being sufficiently active when assessed by pedometer. McNemar's test determined that there was no significant difference in the proportion of inactive and active respondents by IPAQ-SF or sufficiently active and insufficiently active by pedometer from the baseline and sixth month of intervention.

METHODS: This cross-sectional seroprevalence study with a two-stage stratified random cluster sampling design included 5,131 representative community dwellers in Malaysia aged ≥1 year. Data collection lasted from 7 August to 11 October 2020 involving venous blood sampling and interviews for history of COVID-19 symptoms and diagnosis. Previous SARS-CoV-2 infection was defined as screened positive using the Wantai SARS-CoV-2 Total Antibody enzyme-linked immunosorbent assay and confirmed positive using the GenScript SARS-CoV-2 surrogate Virus Neutralization Test. We performed a complex sampling design analysis, calculating sample weights considering probabilities of selection, non-response rate and post-stratification weight.

RESULTS: The overall weighted prevalence of SARS-CoV-2 infection was 0.49% (95%CI 0.28-0.85) (N = 150,857). Among the estimated population with past infection, around 84.1% (95%CI 58.84-95.12) (N = 126 826) were asymptomatic, and 90.1% (95%CI 67.06-97.58) (N = 135 866) were undiagnosed.

METHODS: This systematic review will be based on the review of original articles on the impact of kiddie packs on smoking. There is no restriction on the publication dates. The Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Web of Science and Scopus will be searched to retrieve potential original articles. Additional records identified through other sources: Google Scholar, as well as Journal of Substance Use and Tobacco Control, are also to be searched. These will include original articles in any language which included all study designs (randomised controlled trials, quasi experimental and experimental studies, observational cross-sectional and cohort studies) comparing kiddie packs with regular cigarette packs. The primary outcomes of interest will be initiation of smoking and urge/tendency to buy cigarettes in the general population and attempts to reduce cigarette consumption among current smokers. Secondary outcomes will be the prevalence of smoking using kiddie packs among the current smokers.

DISCUSSION: This systematic review will provide evidence to support the impact of kiddie packs on smoking in terms of smoking initiation, smoking prevalence, urge/tendency to purchase cigarettes and attempts to reduce cigarette consumption. The findings from this review could be helpful to policymakers in regulating kiddie packs to control the consumption of tobacco.

OBJECTIVE: To identify the studies on premature cardiovascular disease (CVD) mortality and synthesise their findings on YLL based on the regional area, main CVD types, sex, and study time.

METHOD: We conducted a systematic review of published CVD mortality studies that reported YLL as an indicator for premature mortality measurement. A literature search for eligible studies was conducted in five electronic databases: PubMed, Scopus, Web of Science (WoS), and the Cochrane Central Register of Controlled Trials (CENTRAL). The Newcastle-Ottawa Scale was used to assess the quality of the included studies. The synthesis of YLL was grouped into years of potential life lost (YPLL) and standard expected years of life lost (SEYLL) using descriptive analysis. These subgroups were further divided into WHO (World Health Organization) regions, study time, CVD type, and sex to reduce the effect of heterogeneity between studies.

RESULTS: Forty studies met the inclusion criteria for this review. Of these, 17 studies reported premature CVD mortality using YPLL, and the remaining 23 studies calculated SEYLL. The selected studies represent all WHO regions except for the Eastern Mediterranean. The overall median YPLL and SEYLL rates per 100,000 population were 594.2 and 1357.0, respectively. The YPLL rate and SEYLL rate demonstrated low levels in high-income countries, including Switzerland, Belgium, Spain, Slovenia, the USA, and South Korea, and a high rate in middle-income countries (including Brazil, India, South Africa, and Serbia). Over the past three decades (1990-2022), there has been a slight increase in the YPLL rate and the SEYLL rate for overall CVD and ischemic heart disease but a slight decrease in the SEYLL rate for cerebrovascular disease. The SEYLL rate for overall CVD demonstrated a notable increase in the Western Pacific region, while the European region has experienced a decline and the American region has nearly reached a plateau. In regard to sex, the male showed a higher median YPLL rate and median SEYLL rate than the female, where the rate in males substantially increased after three decades.

CONCLUSION: Estimates from both the YPLL and SEYLL indicators indicate that premature CVD mortality continues to be a major burden for middle-income countries. The pattern of the YLL rate does not appear to have lessened over the past three decades, particularly for men. It is vitally necessary to develop and execute strategies and activities to lessen this mortality gap.

METHODS: Secondary online data provided by the Ministry of Health, Malaysia and Malaysia's national COVID-19 immunisation programme were used: i) COVID-19 deaths data; ii) vaccination coverage data and iii) population estimate data. Quasi-Poisson regression was performed to determine the risk factors for COVID-19 mortality.

RESULTS: Four risk factors were identified: i) vaccination status (partial versus unvaccinated, incidence rate ratio [IRR]: 0.59; 95% CI: 0.54, 0.64; complete versus unvaccinated, IRR: 0.50; 95% CI: 0.45, 0.56; booster versus unvaccinated, IRR: 0.13; 95% CI: 0.05, 0.26); ii) age group (19 years old-59 years old versus above 60 years old, IRR: 0.90; 95% CI: 0.84, 0.97; 13 years old-18 years old versus above 60 years old, IRR: 0.09; 95% CI: 0.04, 0.19; 6 years old-12 years old versus above 60 years old, IRR: 0.09; 95% CI: 0.03, 0.22; below 5 years old versus above 60 years old, IRR: 0.11; 95% CI: 0.04, 0.23); iii) gender (male versus female, IRR: 1.23; 95% CI: 1.14, 1.32) and iv) comorbidity (yes versus no, IRR: 2.13; 95% CI: 1.96, 2.32).

METHODS: Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NOx, NO2, SO2, O3 and PM10) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated.

RESULTS: The PM10 concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NOx decreased while O3 increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM10, 1.553 (95% CI, 1.328, 1.816) for O3, 1.271 (95% CI, 1.088, 1.486) for SO2, 1.124 (95% CI, 1.048, 1.207) for NO2, and 1.087 (95% CI, 1.024, 1.153) for NOx for NHMS 2006. The adjusted annual average levels of PM10 [1.187 (95% CI, 1.088, 1.294)], O3 [1.701 (95% CI, 1.387, 2.086)], NO2 [1.120 (95% CI, 1.026, 1.222)] and NOx [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO2, and 0.910 for NOx].