Validation of Self-Reported Smoker and Second Hand Smoke Exposure by Urinary Cotinine within The Malaysian Cohort Project

Background: Validation of self-reported questionnaire is very crucial in ensuring the quality and reliability of data collection. Objective: The aim of this study were i) to validate the questionnaire on tobacco smoke intake and second hand smoke exposure among The Malaysian Cohort (TMC) subjects through the determination of urinary cotinine levels, ii) to determine the optimal cut-off point of urine cotinine that discriminates smokers from non-smokers and iii) to estimate misclassification rate between self-reported smoking and urinary cotinine level.Methods: Urine samples from a total of 775 The Malaysian Cohort subjects (104 smokers, 102 former smokers and 569 non-smokers) were obtained and urinary cotinine levels were determined by high-performance liquid chromatography (HPLC). Differences between groups were compared using Kruskal Wallis and Mann-Whitney tests. The Receiver Operating Characteristic (ROC) curved was performed to define the optimal urinary cotinine cut-off point.Results: Urinary cotinine concentration significantly (p<0.001) correlated with smoking status (r=0.46), the average number of cigarettes smoked per day (r=0.53), duration of smoking (r=0.33) and number of cigarettes packed per year (r=0.47). Smokers and second hand smokers have significantly higher median cotinine levels (978.40 and 21.31 respectively) compared to non-smokers (15.52) and non-exposed (13.60) subjects. Cotinine level at cut-off value of 1.51 ng/mg creatinine is able to distinguish smokers and non-smokers with a sensitivity of 84.62% and specificity of 81.97%.Conclusion: The Malaysian Cohort self-reported smoking questionnaire is a reliable tool in assessing the use of tobacco and second hand smoke exposure among the subjects

Long Non-Coding RNAs (lncRNAs) in Cardiovascular Disease Complication of Type 2 Diabetes

The discovery of non-coding RNAs (ncRNAs) has opened a new paradigm to use ncRNAs as biomarkers to detect disease progression. Long non-coding RNAs (lncRNA) have garnered the most attention due to their specific cell-origin and their existence in biological fluids. Type 2 diabetes patients will develop cardiovascular disease (CVD) complications, and CVD remains the top risk factor for mortality. Understanding the lncRNA roles in T2D and CVD conditions will allow the future use of lncRNAs to detect CVD complications before the symptoms appear. This review aimed to discuss the roles of lncRNAs in T2D and CVD conditions and their diagnostic potential as molecular biomarkers for CVD complications in T2D

The architecture of risk for Type 2 diabetes: understanding Asia in the context of global findings

The prevalence of Type 2 diabetes is rising rapidly in both developed and developing countries. Asia is developing as the epicentre of the escalating pandemic, reflecting rapid transitions in demography, migration, diet, and lifestyle patterns. The effective management of Type 2 diabetes in Asia may be complicated by differences in prevalence, risk factor profiles, genetic risk allele frequencies, and gene-environment interactions between different Asian countries, and between Asian and other continental populations. To reduce the worldwide burden of T2D, it will be important to understand the architecture of T2D susceptibility both within and between populations. This review will provide an overview of known genetic and nongenetic risk factors for T2D, placing the results from Asian studies in the context of broader global research. Given recent evidence from large-scale genetic studies of T2D, we place special emphasis on emerging knowledge about the genetic architecture of T2D and the potential contribution of genetic effects to population differences in risk

Hepatitis B and influenza vaccination coverage in healthcare workers, the elderly, and patients with diabetes in Malaysia

Adult immunization remains to be a neglected issue in developing countries including Malaysia. This nationwide study determined the vaccination coverage of hepatitis B and influenza among Malaysia’s healthcare workers (HCWs), the elderly (aged 60 y and above) and patients with diabetes, who are the participants of The Malaysia Cohort Program. The participants were categorized based on their occupation, age and medical history. Self-reported questionnaire was used to assess the participant’s hepatitis B and influenza vaccination status. A Chi-square test and logistic regression analyses were performed to determine the risk factors associated with vaccination behavior. The hepatitis B vaccination coverage for healthcare workers, elderly, and patients with diabetes were 34.6%, 10.1% and 9.8%, respectively. The influenza vaccination coverage rates for healthcare workers, the elderly and patients with diabetes were 26.3%, 5.5% and 6.4%, respectively. The Chinese were more likely to be vaccinated against hepatitis B, while Malay was more likely to be vaccinated against influenza. Individuals with higher education and living in urban areas were more likely vaccinated than those with low education levels and who lived in rural areas. The low vaccination coverage for healthcare workers was alarming because hepatitis B and influenza were subsidized for the healthcare workers. The hepatitis B and influenza vaccination coverage among healthcare workers, elderly and patients with diabetes in Malaysia were low. Specific interventions such as educational and awareness programs should be conducted to increase the vaccination rate among adults, especially those at high risk

Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review

Abstract Prediction model has been the focus of studies since the last century in the diagnosis and prognosis of various diseases. With the advancement in computational technology, machine learning (ML) has become the widely used tool to develop a prediction model. This review is to investigate the current development of prediction model for the risk of cardiovascular disease (CVD) among type 2 diabetes (T2DM) patients using machine learning. A systematic search on Scopus and Web of Science (WoS) was conducted to look for relevant articles based on the research question. The risk of bias (ROB) for all articles were assessed based on the Prediction model Risk of Bias Assessment Tool (PROBAST) statement. Neural network with 76.6% precision, 88.06% sensitivity, and area under the curve (AUC) of 0.91 was found to be the most reliable algorithm in developing prediction model for cardiovascular disease among type 2 diabetes patients. The overall concern of applicability of all included studies is low. While two out of 10 studies were shown to have high ROB, another studies ROB are unknown due to the lack of information. The adherence to reporting standards was conducted based on the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) standard where the overall score is 53.75%. It is highly recommended that future model development should adhere to the PROBAST and TRIPOD assessment to reduce the risk of bias and ensure its applicability in clinical settings. Potential lipid peroxidation marker is also recommended in future cardiovascular disease prediction model to improve overall model applicability

Emergence of dengue virus type 4 during COVID-19 pandemic in patients admitted to a teaching hospital in Malaysia

Prior to COVID-19, dengue was an important public health problem in Malaysia. Due to the movement control order imposed by the Malaysian government to curb the COVID-19 transmission, a study predicted that mosquito-borne diseases would increase during lockdown and partial lockdown seasons. Thus, this study aims to determine the current situation of dengue incidence during the pre-COVID-19 pandemic (2019) and during the COVID-19 pandemic (2020 and 2021). We compared the number of laboratory-confirmed cases in the pre-COVID19 year (2019) and during the COVID-19 pandemic (2020 and 2021). In addition to that, we characterized the clinical manifestation, dengue serotype and viremia levels of dengue patients that were admitted to the Hospital Cancelor Tuanku Muhriz. We found a significant decrease in the number of laboratory-confirmed cases between COVID-19 pandemic and the pre-covid period (p2020=0.064; p2021<0.001). In this study, we found DENV 4 serotype was the most common serotype in dengue patients admitted to our hospital. There was no significant correlation between DENV serotype/viremia level with clinical manifestation of dengue fever and dengue with warning signs. However, patients infected with DENV4 had the highest viral load compared to patients infected with other serotypes. We also found high viremia levels were significantly associated with the febrile phase

Development and Relative Validity of a Semiquantitative Food Frequency Questionnaire to Estimate Dietary Intake among a Multi-Ethnic Population in the Malaysian Cohort Project

Measuring dietary intakes in a multi-ethnic and multicultural setting, such as Malaysia, remains a challenge due to its diversity. This study aims to develop and evaluate the relative validity of an interviewer-administered food frequency questionnaire (FFQ) in assessing the habitual dietary exposure of The Malaysian Cohort (TMC) participants. We developed a nutrient database (with 203 items) based on various food consumption tables, and 803 participants were involved in this study. The output of the FFQ was then validated against three-day 24-h dietary recalls (n = 64). We assessed the relative validity and its agreement using various methods, such as Spearman’s correlation, weighed Kappa, intraclass correlation coefficient (ICC), and Bland–Altman analysis. Spearman’s correlation coefficient ranged from 0.24 (vitamin C) to 0.46 (carbohydrate), and almost all nutrients had correlation coefficients above 0.3, except for vitamin C and sodium. Intraclass correlation coefficients ranged from −0.01 (calcium) to 0.59 (carbohydrates), and weighted Kappa exceeded 0.4 for 50% of nutrients. In short, TMC’s FFQ appears to have good relative validity for the assessment of nutrient intake among its participants, as compared to the three-day 24-h dietary recalls. However, estimates for iron, vitamin A, and vitamin C should be interpreted with caution

Participants Attrition in a Longitudinal Study: The Malaysian Cohort Study Experience

The attrition rate of longitudinal study participation remains a challenge. To date, the Malaysian Cohort (TMC) study follow-up rate was only 42.7%. This study objective is to identify the cause of attrition among TMC participants and the measures to curb it. A total of 19,343 TMC participants from Kuala Lumpur and Selangor that was due for follow-up were studied. The two most common attrition reasons are undergoing medical treatment at another government or private health center (7.0%) and loss of interest in participating in the TMC project (5.1%). Those who were inclined to drop out were mostly Chinese, aged 50 years and above, unemployed, and had comorbidities during the baseline recruitment. We have also contacted 2183 participants for the home recruitment follow-up, and about 10.9% agreed to join. Home recruitment slightly improved the overall follow-up rate from 42.7% to 43.5% during the three-month study period

10-Year Cardiovascular Disease Risk Estimation Based on Lipid Profile-Based and BMI-Based Framingham Risk Scores across Multiple Sociodemographic Characteristics: The Malaysian Cohort Project

Cardiovascular disease (CVD) leads to high morbidity and mortality rate worldwide. Therefore, it is important to determine the risk of CVD across the sociodemographic factors to strategize preventive measures. The current study consisted of 53,122 adults between the ages of 35 and 65 years from The Malaysian Cohort project during recruitment phase from year 2006 to year 2012. Sociodemographic profile and physical activity level were assessed via self-reported questionnaire, whereas relevant CVD-related biomarkers and biophysical variables were measured to determine the Framingham Risk Score (FRS). The main outcome was the 10-year risk of CVD via FRS calculated based on lipid profile and body mass index (BMI) associated formulae. The BMI-based formula yielded a higher estimation of 10-year CVD risk than the lipid profile-based formula in the study for both males (median = 13.2% and 12.7%, respectively) and females (median = 4.3% and 4.2%, respectively). The subgroup with the highest risk for 10-year CVD events (based on both FRS formulae) was the Malay males who have lower education level and low physical activity level. Future strategies for the reduction of CVD risk should focus on screening via BMI-based FRS in this at-risk subpopulation to increase the cost-effectiveness of the prevention initiatives