Selected Article of Journal (IKU)

The construction industry is recognized as one of the most hazardous industries globally due to the dynamic on site activities and labour-intensive characteristics. The construction tasks are physically and cognitively demanding therefore the construction workers are prone to work fatigue which compromises safety performance. The evaluation of fit for duty, or fitness for work (FFW) aims to determine if workers are at risk of adverse impacts of ill-health, injury or accidents. This systematic review aimed to critically summarize up-to-date measures and evaluation tools that were employed to monitor work fitness or fatigue specifically among construction workers. Adhering with the PRISMA protocol, three databases were searched from the inception to 2022, with a total combination of 37 keywords, concluding to the selection of 20 relevant articles. The Mixed Method Appraisal Tool (MMAT) was used as the guide for the study appraisal. A total of 20 articles were reviewed, published from 2008–2022. Majority of the studies employed experimental design. The review identified the subjective evaluation scales and objective measurement tool. The subjective self-response questionnaires can be categorized into single dimension or multidimension covering both physical and mental fitness; whereas the objective measurement tool can be categorized into physiological metrics, physical and cognitive performance measure. The available scientific evidence has raised the relevant issues for on-site practicality and potentially guide the formulation of evidence-based guidelines for the FFW assessment in the construction industry.

Aedes aegypti exhibit a higher preference for ovipositing their eggs in water that possess with dissolved mineral and nutrient for the survival of their progeny. These solutions usually contain ammonia which was formed due to decomposing process of decaying organic matter in the water. Therefore, the understanding of oviposition preferences is crucial for developing effective strategies in vector control programme. The attractiveness of aqueous ammonia, ammonium nitrate and a mixture of ammonium and acid lactic to gravid Ae. aegypti were accessed through dual and multiple choice bioassays under laboratory conditions. In dual and multiple choice bioassays, female mosquitoes was highly tend to oviposit their eggs in the mixture of ammonium and acid lactic solution (152.87±11.06) compared to the ammonium nitrate (134.13±10.32)) and ammonium aqueos (141.60±11.93). Solution of ammonium nitrate was less effective to attract gravid Aedes in dual bioassays’ studies (P>0.05). This finding indicates that the combination of ammonium and acid lactic could be used in ovitrap surveillance programme. However, further research on combination of ammonium and acid lactic is warranted to find a better oviposition attractant for Ae. aegypti

The consequences of polycystic ovary syndrome (PCOS) in adolescents go beyond infertility during reproductive age. Therefore, research on PCOS should be methodically designed to address gaps and enhance the diagnosis and clinical management of the condition. This scoping review aims to describe the characteristics of research on PCOS among adolescents, and summarise the available methods of diagnosing PCOS among adolescents in epidemiological research. This review followed the standard protocols by Arksey and O’Malley and adheres to the Preferred Reported Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review (PRISMA-ScR) 2018 statement checklist. We included studies of female adolescents aged 13 to 18 years old and published from January 2011 up to December 2023. 341 articles were reviewed. Majority of the studies were observational and primarily conducted in Western countries, indicating the paucity of research on PCOS in Asian adolescents. The main limitations of existing studies are small sample size and potential admission bias due to the non-community-based nature of research. Additionally, the use of adult definitions for PCOS diagnosis in adolescent studies is also debatable. This scoping review assembles and provides insights into the characteristics of current PCOS studies in adolescents, aiming to guide future research directions in the field of PCOS.

Obesity among adolescent is a public health issue with increasing burden of disease. Predicting imbalanced health data with Machine Learning may introduce bias and lead to diminished model performance. Misclassification in healthcare data could lead to misdiagnosing a patient or failing to detect a health issue when it is present. The purpose of this study is to predict adolescent obesity using machine learning along with implementation of multiple approaches on the imbalanced dataset. This study used secondary dataset from National Health and Morbidity Survey 2017. Samples 13 – 17 years were selected for the classification. SPSS V26 was used for data pre-processing, data cleaning, and data analysis. Meanwhile, Python language used for prediction and evaluation of the models. Approaches on the imbalanced dataset including resampling method (Random Oversampling, Random Under-sampling) and hybrid method (SMOTE and ADASYN) were implemented. This dataset was used for the formation of predictive models on ML algorithm including Artificial Neural Network, Decision Tree, K-Nearest Neighbour, Logistic Regression, Naïve Bayes, Random Forest and Support Vector Machine. The performance of each model was evaluated and compared using accuracy, precision, recall, F- score and Area under the Curve (AUC). Random Oversampling approached with Decision Tree Algorithm performs the best with accuracy (91.35%), precision (0.93), recall (0.91), F- score (0.91) and AUC (0.91) for the prediction of obesity among adolescent in Malaysia. The presented ML model development workflow along with the imbalanced techniques can be adapted to other health survey-based studies and may be valuable for developing other clinical prediction models.

Introduction: Malnutrition in hospitalised patients is a problem that is frequently observed all around the world. Malnutrition in hospitalised patients is related to poor patient outcomes and high healthcare expenditures. The purpose of this study is to assess the nutrition risk and explore the associated risk factors of malnutrition among hospitalised patient. Methods: A cross-sectional study was done in Sarawak General Hospital located in Kuching, Sarawak using convenience sampling among adult aged 18 and above. The Malnutrition Screening Tool (MST) was used to assess the nutritional risk. Demographic characteristics, anthropometric and biochemical data were compared according to nutritional status. The chi-square test was performed to compare the differences between categorical variables. The risk factors of malnutrition were identified using logistic regression analysis. Result: A total of 207 respondents were involved in this study with 63.3% and 36.7% were male and female, respectively. Malnutrition risk was observed in 61.3% of respondents according to MST score. The malnutrition risk was significantly higher in older age, those who were admitted to oncology wards and those with lower BMI and impaired biochemical profile. Multivariate analysis revealed that age and BMI of less than 18.5 kg/m2 were the main factors contributing to the presence of risk of malnutrition. Conclusion: The risk of malnutrition is observed to be prevalent among hospitalised patients in Sarawak General Hospital. Therefore, it is important to have a routine nutritional screening and assessment to allow for early nutritional intervention and therapy.