Methods: This was an observational, cross-sectional study involving a total of 447 pregnant women who attended the Obstetrics and Gynecology Clinic, Hospital Kuala Lumpur (HKL), Malaysia. A validated, self-administered questionnaire was used to collect participant data.
Results: Most of pregnant women had taken medication during pregnancy and more than half of them (52.8%) showed a poor level of knowledge about the medication use during pregnancy. Eighty-three percent had a poor level of awareness and 56.5% had negative beliefs. Age and education level were significantly associated with the level of knowledge regarding medication use during pregnancy. Multiparous pregnant women, and pregnant women from rural areas were observed to have a higher level of awareness compared with those who lived in urban areas. Use of medication during pregnancy was determined to be significantly associated with education level, and race.
Conclusion: Although there was prevalent use of medication among pregnant women, many had negative beliefs, and insufficient knowledge and awareness about the risks of taking medication during pregnancy. Several sociodemographic characteristics were significantly associated with the use (race and education level), level of knowledge (age and education level), awareness (parity and place of residence), and beliefs (race, education level, and occupation status) towards medication use during pregnancy.
Methods: This was an observational prospective study carried out at multiple centers. In total, 172 breast cancer patients were included. The Functional Assessment of Chronic Illness Therapy-Fatigue Questionnaire was used to measure QOL, while the Brief Fatigue Inventory (BFI) was used to assess the severity of fatigue.
Results: The total average mean and standard deviation of QOL were 84.58±18.07 and 4.65±1.14 for BFI scores, respectively. A significant association between fatigue and QOL was found in linear and multiple regression analyses. The relationships between fatigue severity and cancer stage, chemotherapy dose delay, dose reduction, chemotherapy regimen, and ethnicity were determined using binary logistic regression analysis.
Conclusion: The findings of this study are believed to be useful for helping oncologists effectively evaluate, monitor, and treat fatigue related to QOL changes.
Methods: A total of 204 Malaysian parents of children aged 2 to 11 years old were recruited for this study using a combination of purposive and snowball sampling approaches. Parents were required to fill an online questionnaire hosted on Google Forms, which consisted of socio-demographic characteristics (including child's gender, age, and ethnicity, as well as parental income during the MCO) and a 35-item list from the Children's Eating Behaviour Questionnaire (CEBQ). Data analysis was conducted by further stratifying the children's eating behaviour according to socio-demographic characteristics.
Results: No significant differences were observed in the eating behaviour of the children across age and parental income groups during the MCO. Malaysian Indian children had significantly lower mean scores for the food responsiveness (2.50±0.64) and emotional over-eating (2.13±0.72) subscales than Malaysian Chinese children. Girls had a significantly higher mean score for the slowness in eating subscale during the MCO than boys.
Conclusion: Children's eating behaviour were comparable across socio-demographic characteristics. Nonetheless, the findings of the current study provide an overview of Malaysian children's eating behaviour during the MCO.
Methods: The dataset of visitors to 5 Asian countries with dengue were analyzed for 2016 and 2017, and in the Philippines, Thailand and Vietnam, imported cases of zika virus infection were also reported. For zika virus, a single imported case was reported from Brazil in 2016, and 2 imported cases reported from the Maldives in 2017. To understand the transmissibility in 5 Southeast Asian countries, the estimate of the force of infection, i.e., the hazard of infection per year and the average duration of travel has been extracted. Outbound travel numbers were retrieved from the World Tourism Organization, including business travelers.
Results: The incidence of imported dengue in 2016 was estimated at 7.46, 15.00, 2.14, 4.73 and 2.40 per 100,000 travelers visiting Philippines, Indonesia, Thailand, Malaysia and Vietnam, respectively. Similarly, 2.55, 1.65, 1.53, 1.86 and 1.70 per 100,000 travelers in 2017, respectively. It was estimated that there were 60.1 infections (range: from 16.8 to 150.7 infections) with zika virus in Brazil, 2016, and 345.6 infections (range: from 85.4 to 425.5 infections) with zika virus in the Maldives, 2017.
Conclusion: This study emphasizes that dengue and zika virus infections are mild in their nature, and a substantial number of infections may go undetected. An appropriate risk assessment of zika virus infection must use the estimated total size of infections.
METHODS: A cross-sectional anonymous web-based survey was disseminated to Malaysian adults aged ≥18 years old via social media platforms between July 10, 2020 and August 31, 2020.
RESULTS: In the analysis of 4,164 complete responses, 93.2% of participants indicated that they would accept the COVID-19 vaccine if it was offered for free by the Malaysian government. The median out-of-pocket cost that participants were willing to pay for a COVID-19 vaccine was Malaysian ringgit (MYR) 100 (interquartile range [IQR], 100) if it was readily available and MYR 150 (IQR, 200) if the supply was limited. Respondents with a low likelihood of vaccine hesitancy had 13 times higher odds of accepting the COVID-19 vaccine (95% confidence interval [CI], 8.69 to 19.13). High perceived risk and severity were also associated with willingness to be vaccinated, with adjusted odds ratios of 2.22 (95% CI, 1.44 to 3.41) and 2.76 (95% CI, 1.87 to 4.09), respectively. Age and ethnicity were the only independent demographic characteristics that predicted vaccine uptake.
CONCLUSION: Public health strategies targeting perceived risk, perceived susceptibility and vaccine hesitancy could be effective in enhancing vaccine uptake.
METHODS: An analysis of forensic autopsy investigations was conducted between 2019 and 2022 on a selected urban population in Colombo, Sri Lanka, assessing the effects of the COVID-19 pandemic on mortality within these communities.
RESULTS: During the COVID-19 restrictions, there was a 2.5-fold increase in the total number of deaths, with a significantly higher percentage of female deaths than before. The majority of these deaths were due to cardiovascular causes, while COVID-19-related deaths ranked third overall. The highest proportion of COVID-19 deaths occurred among unvaccinated females. The monthly frequency of deaths from traffic accidents, poisoning, and asphyxiation decreased, while deaths from blunt trauma, sharp trauma, burns, and immersion increased. There was also a rise in blunt homicides and a greater number of femicides during the COVID-19 restrictions than in the pre-pandemic period. A significantly higher percentage of males who received the COVID-19 vaccine died from cardiovascular causes compared to those in the unvaccinated group.
CONCLUSION: The significant changes in mortality demographics and causes of death within this community during the COVID-19 restrictions underscore the disruption in healthcare, healthseeking behavior, and social interactions during this period. The vulnerability of individuals residing in highly urbanized areas with lower socioeconomic status, particularly women, is brought into sharp focus.
METHODS: This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators. Several advanced deep learning models, including long short-term memory (LSTM), bidirectional LSTM, convolutional neural network (CNN), CNN-LSTM, multilayer perceptron, and recurrent neural network (RNN) models, were trained and evaluated. Bayesian optimization was also implemented to fine-tune these models.
RESULTS: The evaluation framework revealed that each model exhibited different levels of predictive accuracy and precision. Specifically, the RNN model outperformed the other architectures even without optimization. Comprehensive predictive and perspective analytics were conducted to scrutinize the COVID-19 dataset.
CONCLUSION: This study transcends academic boundaries by offering critical insights that enable public health authorities in the UAE to deploy targeted data-driven interventions. The RNN model, which was identified as the most reliable and accurate for this specific context, can significantly influence public health decisions. Moreover, the broader implications of this research validate the capability of deep learning techniques in handling complex datasets, thus offering the transformative potential for predictive accuracy in the public health and healthcare sectors.
METHODS: This scientometric study systematically mined health and social science publications from the Web of Science and Scopus databases using keywords associated with infectious disease. The analysis included only English-language articles and review articles by authors from any ASEAN country. Publication, citation, and text co-occurrence network analyses were performed. R Studio and VOSviewer enabled data management, analysis, and visualization.
RESULTS: Searches identified 12,511 articles published between 1925 and 2022, with a notable increase in research publications since 2003. The leading journals on infectious disease were associated with established publishing houses, including BMC, BMJ, and The Lancet. The most-cited articles were primarily global burden of disease studies, with 7,367 citations. Among ASEAN countries, Thailand, Malaysia, and Singapore had the most publications and collaborative efforts on the topic. Analysis of keyword co-occurrence revealed clusters related to global health, dengue, bacterial studies, non-dengue viral topics, and diagnostics. Most early studies examined diagnostics, gene and sequencing methodologies, and virology; later, the focus shifted toward herbal and alternative medicine.
CONCLUSION: Recently, the research capacity of Southeast Asia has expanded dramatically, with substantial contributions from high-income countries. Intense cooperation between member states is essential, emphasizing the role of HICs in supporting their neighbors. Increased research efforts and collaboration must be dedicated to innovative approaches to combat persistent health conditions, along with emerging issues like climate change.
METHODS: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk.
RESULTS: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02-1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42- 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07-2.69), travel history (aOR, 2.30; 95% CI, 1.13-4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72-0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16- 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97-0.99) were significant determinants.
CONCLUSION: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.