AIMS AND METHODS: The present study aimed to examine the changes in mean daily cigarette consumption among random samples of the Malaysian current smoker population over 20 years using an age-period-cohort (APC) approach. We conducted APC analysis using a multilevel hierarchical age-period-cohort model and data from four nationally representative, repeated cross-sectional surveys (National Health and Morbidity Survey) conducted in 1996, 2006, 2011, and 2015 among individuals aged 18 to 80 years. Analyses were also stratified by gender and ethnicity.

RESULTS: Overall, mean daily cigarette consumption (smoking intensity) among current smokers increased with age until 60, after which a drop was observed. There were increases in daily cigarette consumption across birth cohorts. Age and cohort trends did not vary by gender but by ethnicity. The decreasing cigarette consumption after age 60 among the current smoker population was consistent with those observed among the Chinese and Indians, a trend that was not observed in Malays and other aborigines. In contrast, the increasing cohort trend was consistent with those observed among the Malays and other bumiputras.

CONCLUSIONS: The present study highlighted important ethnic-specific trends for mean daily cigarette consumption among the current smoker population in Malaysia. These findings are essential in guiding the formulation of interventional strategies or implementation of national tobacco control policies and help achieve the Ministry of Health Malaysia's 2025 and 2045 targets for smoking prevalence.

METHODS: Data from four population-based National Health and Morbidity Surveys conducted in 1996, 2006, 2010, and 2015 were pooled. Hierarchical Age-Period-Cohort (HAPC) analysis explored the trajectories of BMI and waist circumference across the life course and birth cohorts by sex and ethnicity. These models assumed no period effect.

RESULTS: Generally, BMI and waist circumference trajectories increased across age and birth cohorts. These trajectories varied by sex and ethnicity. Females have more profound increasing BMI and waist circumference trajectories than their male counterparts as they age and as cohort recency increases. Chinese have less profound BMI and waist circumference increases across the life course and birth cohorts than other ethnic groups.

RESULTS: The resazurin-based TB assay demonstrated that the L. cuprina larval extract was inhibitory against all tested bacteria, whilst the larval extract of S. peregrina and M. domestica were only inhibitory against the MRSA, with a MIC of 100 mg ml(-1). Subsequent sub-culture of aliquots revealed that the larval extract of L. cuprina was bactericidal against MRSA whilst the larval extracts of S. peregrina and M. domestica were bacteriostatic against MRSA. The GC-MS analysis had quantitatively identified 20 organic compounds (fatty acids or their derivatives, aromatic acid esters, glycosides and phenol) from the larval extract of L. cuprina; and 5 fatty acid derivatives with known antimicrobial activities from S. peregrina and M. domestica.

METHODS: A cross sectional study was conducted on three groups: individuals with alcohol use disorders (n=30), social drinkers (n=54) and alcohol-naive controls (n=60). 1H NMR-based metabolomics was used to obtain the metabolic profiles of plasma samples. Data were processed by multivariate principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) followed by univariate and multivariate logistic regressions to produce the best fit-model for discrimination between groups.

RESULTS: The OPLS-DA model was able to distinguish between the AUD group and the other groups with high sensitivity, specificity and accuracy of 64.29%, 98.17% and 91.24% respectively. The logistic regression model identified two biomarkers in plasma (propionic acid and acetic acid) as being significantly associated with alcohol use disorders. The reproducibility of all biomarkers was excellent (0.81-1.0).

OBJECTIVES: To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics.

METHOD: Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC).

RESULTS: The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0).