Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

The increasing number of homeless children is concerning. This study aimed to assess the dietary intake, diet quality, and nutritional status of homeless children in Klang Valley, as well as the relationship between diet quality and nutritional status. Methods: Approximately 120 homeless children aged 7 to 12 years from four locations in Klang Valley were enrolled. Their dietary intake and nutritional status were assessed using a two-day 24-hour dietary recall and body mass index-for-age, respectively. The Healthy Eating Index (HEI) was used to examine diet quality. Results: Prevalence of normal weight respondents was 58.3% (mean±SD: -0.79±1.80), with 25.0% classified as moderately and severely thin. Mean energy intake was significantly lower than recommended nutrient intakes (RNI) (p<0.050), while protein intake was higher (p<0.050). Calcium and zinc intakes were also significantly lower (p<0.001). Boys aged 7-9 years had significantly higher iron intake (median=11.6, IQR=8.7 mg, p=0.003), whereas girls aged 10-12 years had significantly lower intakes of iron (mean±SD=11.4±5.1, 11.1±4.7) and vitamin A (median=416.6, IQR=450.4 µgRE, p<0.001 for both). Mean HEI score was 51.30±6.78, indicating a need for diet quality improvement. No significant association between diet quality and nutritional status was observed (p=0.380). Conclusion: This study provided insights into dietary intake, diet quality, and nutritional status of homeless children. Further research is vital to shape evidence-based nutrition interventions.

Prediabetes is a condition in which blood glucose level is above the normal but below the diagnostic value of diabetes mellitus. Hyperglycaemia can upregulate markers of chronic inflammation and contribute to the overproduction of reactive oxygen species (ROS), which ultimately causes increased oxidative stress. This leads to beta-cell dysfunction and insulin resistance, which are involved in the pathogenesis of prediabetes status. Proper treatment of hyperglycaemia, inhibition of ROS overproduction, and suppression of inflammation are crucial for delaying the onset of diabetes. Therefore, it is essential to determine and understand the mechanisms involved in prediabetes. This review discusses the relationship between oxidative stress and prediabetes, along with the inflammation’s role in prediabetes. Additionally, the effects of some biomarkers of oxidative stress in prediabetes, inflammatory markers, and their influence on chronic inflammation are also briefly reviewed. Finally, the role of antioxidant and anti-inflammatory markers are discussed.

Introduction: This research was conducted to extend the theoretical construct of positive orientation (PO) to psychiatric outpatients. This research also examined the effect of PO on alleviating stress, anxiety, and depression among psychiatric outpatients. Methods: This cross-sectional survey recruited 301 psychiatric outpatients online. As these respondents have a short attention span, short measures were used to measure PO-related variables (life satisfaction, optimism, self-esteem) and indicators of psychological distress (depression, anxiety, and stress). These outpatients are at the legal age to provide consent for themselves (M = 30.12, SD= 8.11). The majority of them have been identified as male (80.07%). Similarly, the ethnic distribution was unequal, with the majority of these outpatients identified as Malay (85.05%), followed by those who were identified as Chinese (7.31%), Indian (4.32%), and from other ethnic groups (3.32%). Results: Generalized structured component analysis (GSCA) supported that satisfaction with life, optimism, and self-esteem reflect the construct of PO. Furthermore, PO predicted depression, anxiety, and depression negatively. Conclusion: It is possible to replicate the construct of PO with psychiatric outpatients using single item measures for life satisfaction, optimism, and self-esteem. PO is beneficial to psychiatric outpatients as it reduces the severity of depression, anxiety, and stress.

A cell-based model of Parkinson’s disease (PD) is a well-established in vitro experimental prototype to investigate the disease mechanism and therapeutic approach for a potential anti-PD drug. The SH-SY5Y human neuroblastoma cells and 6-OHDA combo is one of the many neurotoxininduced neuronal cell models employed in numerous neuroscience-related research for discovering neuroprotective drug compounds. Emerging studies have reported a significant correlation between PD and epigenetic alterations, particularly DNA methylation. However, the DNA methylation changes of PD-related CpG sites on the 6-OHDA-induced toxicity on human neuronal cells have not yet been reported. We performed a genome-wide association study (GWAS) using Infinium Epic beadchip array surveying 850000 CpG sites in differentiated human neuroblastoma cells exposed to 6-OHDA. We identified 236 differentially methylated probes (DMPs) or 163 differentially methylated regions (DMRs) in 6-OHDA treated differentiated neuroblastoma cells than the untreated reference group with p<0.01, Δbeta cut-off of 0.1. Among 236 DMPs, hypermethylated DMPs are 110 (47%), whereas 126 (53%) are hypomethylated. Our bioinformatic analysis revealed 3 DMRs that are significantly hypermethylated and associated with neurological disorders, namely AKT1, ITPR1 and GNG7. This preliminary study demonstrates the methylation status of PD-related CpGs in the 6-OHDA-induced toxicity in the differentiated neuroblastoma cells model.

Vaccines are vital tools in public health as they play critical roles in preventing and controlling infectious diseases. Vaccine technology has advanced from virus-infected lesions to live attenuated, inactivated or killed pathogens, toxoids, and subunits that consist of only specific pathogen parts needed to elicit an immune response. The progression of virus-like particle vaccines, recombinant viral-vectored vaccines, toxoids, protein or polysaccharide-based vaccines designed to conjugate with a distinct carrier protein to enhance immune reaction is a significant milestone. However, some infectious pathogens can avoid the adaptive immune system, while traditional methods may be unsuitable against non-infectious diseases like cancer. Recent studies have demonstrated the potential of messenger RNA (mRNA) vaccines as an alternative to traditional vaccine approaches. mRNA vaccines contain mRNA that encodes the specific antigen and triggers a directed immune response. The two main forms of mRNA used in the study of mRNA vaccines are conventional non-amplifying mRNA and self-amplifying mRNA (saRNA). This article discusses the mRNA vaccine structure, delivery strategies, and protective functions, focusing on mRNA vaccines’ safety and therapeutic potential. Pre-clinical research has demonstrated the broad utility of mRNA vaccines in animal models. Human clinical trials, however, are still under validation. Hence, further studies will need to focus on adapting reliable results of preclinical trials to human applications. The evidence to date suggests that mRNA vaccines are promising next-generation vaccines and, in the future, clinical trials would transform basic research into mRNA therapeutics in medical practices.
COVID-19 ; mRNA Vaccines ; Safety ; Vaccination