METHODS: This prospective cross-sectional study aimed to identify rural-urban differences in risk factors for low birth weight among women in Malaysia. Pregnant women at ≥20 weeks of gestation in urban and rural Malaysia (n = 437) completed questionnaires on sociodemographic characteristics and physical activity. Weight and middle-upper arm circumference were measured. Infant birth outcomes were extracted from medical records.

METHODS: This study employed cross-sectional, self-reported survey methodology. We used the 6-item Kessler screening scale (K6) to assess psychological distress (cutoff score ≥ 13, range 0-24, with higher scores indicating greater psychological distress). Participants self-reported their perceptions of whether they had been bullied at work and how frequently this occurred. A multivariate logistic regression was conducted with ever bullying and never bullying as dichotomous categories.

METHODS: This was a cross sectional study design. A total of 347 respondents from low household income groups, including persons with disability and Orang Asli were recruited from E-kasih. A semi-guided self-administered questionnaire was used. QOL measured by EQ. 5D utility value and health status measured by visual analogue score (VAS). Descriptive statistic, bivariate Chi-square analysis and binary logistic regression were conducted to determine factors influencing low QOL and poor health status.

RESULTS: Majority of the respondents were Malay, female (61%), 63% were married, 60% were employed and 46% with total household income of less than 1 thousand Ringgit Malaysia. 70% of them were not having any chronic medical problems. Factors that associated with low QOL were male, single, low household income, and present chronic medical illness, while poor health status associated with female, lower education level and present chronic medical illness. Logistic regression analysis has showed that determinants of low QOL was present chronic illness [AOR 4.15 95%CI (2.42, 7.13)], while determinants for poor health status were; female [AOR 1.94 95%CI (1.09,3.44)], lower education [AOR 3.07 95%CI (1.28,7.34)] and present chronic illness [AOR 2.53 95%CI (1.39,4.61)].

METHODS: University and secondary school students from low-income households (N = 202) were involved in this cross-sectional study. Participants completed the Depression Literacy Questionnaire (D-Lit), General Help Seeking Questionnaire (GHSQ), Mental Help Seeking Attitudes Scale (MHSAS), Self-Stigma of Seeking Help Scale (SSOSH), and Beliefs toward Mental Illness (BMI).

METHODS: A cross-sectional study was carried out on 446 older adults aged 50 years and above from 20 randomly selected villages. Respondents were interviewed to collect information on their demographic characteristics and oral health perception, followed by physical examination to measure height, weight and body mass index (BMI) of respondents. The validated Malay version of General Oral Health Assessment Index (GOHAI) was used to measure OHRQoL.

METHODS: This cross-sectional study was conducted among 202 caregivers to PWD in home-based settings. Recruited caregivers were administered questionnaires regarding BPSD which was measured using Neuropsychiatric Inventory-Questionnaire (NPI-Q), caregiver burden using Zarit Burden Interview (ZBI), Brief COPE for coping strategies and Big-Five Inventory which measured personality traits.

METHODS: An online health survey was conducted between May to July 2017 among employees from 47 private companies located in urban Malaysia. A total of 5235 respondents completed the 20-min online employee health survey on a voluntary basis. Chi-Square or Fisher's exact tests were used to determine association between income with demographic and categorical factors of absenteeism and presenteeism. Multivariate linear regression was used to identify factors predicting absenteeism and presenteeism.

METHODS: A total of 2406 Malaysian children aged 5 to 12 years, who had participated in the South East Asian Nutrition Surveys (SEANUTS), were included in this study. Cognitive performance [non-verbal intelligence quotient (IQ)] was measured using Raven's Progressive Matrices, while socioeconomic characteristics were determined using parent-report questionnaires. Body mass index (BMI) was calculated using measured weight and height, while BMI-for-age Z-score (BAZ) and height-for-age Z-score (HAZ) were determined using WHO 2007 growth reference.

RESULTS: Overall, about a third (35.0%) of the children had above average non-verbal IQ (high average: 110-119; superior: ≥120 and above), while only 12.2% were categorized as having low/borderline IQ ( 3SD), children from very low household income families and children whose parents had only up to primary level education had the highest prevalence of low/borderline non-verbal IQ, compared to their non-obese and higher socioeconomic counterparts. Parental lack of education was associated with low/borderline/below average IQ [paternal, OR = 2.38 (95%CI 1.22, 4.62); maternal, OR = 2.64 (95%CI 1.32, 5.30)]. Children from the lowest income group were twice as likely to have low/borderline/below average IQ [OR = 2.01 (95%CI 1.16, 3.49)]. Children with severe obesity were twice as likely to have poor non-verbal IQ than children with normal BMI [OR = 2.28 (95%CI 1.23, 4.24)].

METHODS: Therefore, using linear programming, this study is aimed to develop a healthy and balanced menu with minimal cost in accordance to individual needs that could in return help to prevent cancer. A cross sectional study involving 100 adults from a local university in Kuala Lumpur was conducted in 3 phases. The first phase is the data collection for the subjects, which includes their socio demographic, anthropometry and diet recall. The second phase was the creation of a balanced diet model at a minimum cost. The third and final phase was the finalization of the cancer prevention menu. Optimal and balanced menus were produced based on respective guidelines of WCRF/AICR (World Cancer Research Fund/ American Institute for Cancer Research) 2007, MDG (Malaysian Dietary Guidelines) 2010 and RNI (Recommended Nutrient Intake) 2017, with minimum cost.

RESULTS: Based on the diet recall, most of subjects did not achieve the recommended micronutrient intake for fiber, calcium, potassium, iron, B12, folate, vitamin A, vitamin E, vitamin K, and beta-carotene. While, the intake of sugar (51 ± 19.8 g), (13% ± 2%) and sodium (2585 ± 544 g) was more than recommended. From the optimization model, three menus, which met the dietary guidelines for cancer prevention by WCRF/AICR 2007, MDG 2010 and RNI 2017, with minimum cost of RM7.8, RM9.2 and RM9.7 per day were created.

METHODS: A cross-sectional study was conducted to recruit a total of 357 mothers aged 18-50 years. Interviews were carried out among mothers to collect sociodemographic information, nutritional information, and physical activity. Anthropometric measurements [height, weight and waist circumference (WC)] were conducted with the mothers. Body Mass Index (BMI) was computed to determine the prevalence of overweight and obesity. Multinomial logistic regression was used to examine the associated factors of overweight and obesity.

METHODS: A total of 590 preschoolers, comprising 317 boys and 273 girls were included. Pre-pilot parental questionnaires were used to assess diet, physical activity (PA) and sedentary behaviour practices and anthropometry was assessed in preschoolers and their parents.

METHODS: The observational study (#NCT04367337) enrolled 6064 adults residing in Australia, Canada, China, France, Gambia, Germany, Israel, Italy, Malaysia, Poland, Portugal, Romania, Singapore, and Switzerland. Data on handwashing adherence across 8 situations (indicated in the WHO guidelines) were collected via an online survey (March-July 2020). Individual-level handwashing data were matched with the date- and country-specific values of the 6 indices of the trajectory of COVID-19 pandemic, obtained from the WHO daily reports.

RESULTS: Multilevel regression models indicated a negative association between both accumulation of the total cases of COVID-19 morbidity (B = -.041, SE = .013, p = .013) and mortality (B = -.036, SE = .014 p = .002) and handwashing. Higher levels of total COVID-related morbidity and mortality were related to lower handwashing adherence. However, increases in recent cases of COVID-19 morbidity (B = .014, SE = .007, p = .035) and mortality (B = .022, SE = .009, p = .015) were associated with higher levels of handwashing adherence. Analyses controlled for participants' COVID-19-related situation (their exposure to information about handwashing, being a healthcare professional), sociodemographic characteristics (gender, age, marital status), and country-level variables (strictness of containment and health policies, human development index). The models explained 14-20% of the variance in handwashing adherence.

CONCLUSIONS: To better explain levels of protective behaviors such as handwashing, future research should account for indicators of the trajectory of the COVID-19 pandemic.

METHOD: A single-blind cluster randomized controlled trial will conduct at six districts in Selangor. Randomly selected respondents who fulfilled the inclusion criteria will be invited to participate in the study. Health education module based on Health Believed Theory will be delivered via health talks and videos coordinated by liaison officers. Data at three-time points at baseline, immediate, and 3 months post-intervention will be collected. A validated questionnaire will assess participants' background characteristics, knowledge, skill, and preparedness on disaster preparedness and perception towards disaster. Descriptive and inferential statistics will be applied for data analysis using IBM Statistical Package for Social Sciences version 25. Longitudinal correlated data on knowledge, skills, preparedness, and perception score at baseline, immediate post-intervention, and 6 months post-intervention will be analyzed using Generalized Estimating Equations (GEE).

DISCUSSION: It is expected that knowledge, skills, preparedness, and flood disaster perception score are more significant in the intervention group than the control group, indicating the Health Education Based Intervention (HEBI).

METHODS: Three national influenza surveillance systems with different levels of development (Australia, China and Malaysia) were compared and their adherence to World Health Organization (WHO) guidance was evaluated using a structured framework previously tested in several European countries consisting of seven surveillance sub-systems, 19 comparable outcomes and five evaluation criteria. Based on the results, experts from the Asia-Pacific Alliance for the Control of Influenza (APACI) issued recommendations for the improvement of existing surveillance systems.

RESULTS: Australia demonstrated the broadest scope of influenza surveillance followed by China and Malaysia. In Australia, surveillance tools covered all sub-systems. In China, surveillance did not cover non-medically attended respiratory events, primary care consultations, and excess mortality modelling. In Malaysia, surveillance consisted of primary care and hospital sentinel schemes. There were disparities between the countries across the 5 evaluation criteria, particularly regarding data granularity from health authorities, information on data representativeness, and data communication, especially the absence of publicly available influenza epidemiological reports in Malaysia. This dual approach describing the scope of surveillance and evaluating the adherence to WHO guidance enabled APACI experts to make a number of recommendations for each country that included but were not limited to introducing new surveillance tools, broadening the use of specific existing surveillance tools, collecting and sharing data on virus characteristics, developing immunization status registries, and improving public health communication.

METHODS: This cross-sectional nationwide study conducted in 2018 recruited convenience sample of 289 parents with children up to age 12 at public areas. Parents were asked to rate the risk level from 1 (no risk) to 5 (extremely high risk) by looking at photographs of an adult smoking in the presence of a child in 8 different situations. The implementation of smoking restriction rules was assessed. Mean scores were calculated with higher scores representing higher risk perception of SHS to child's health. Linear regression analysis was used to determine factors associated with the level of parental risk perception of SHS exposure to their children's health.

METHODS: A total of 607 Malay pupils, comprising 240 (39.5%) boys and 367 (60.5%) girls aged between 10 and 11, were recruited from 10 schools to answer the questionnaire, which measured their views on 24 items through a five-point Likert scale. The AEQ-PE was translated into Malay language (AEQ-PE-M) using forwarding to backward translation techniques. Certain phrases were adopted in accordance with the local culture and vocabulary appropriate for primary school pupils. CFA was performed using the Mplus 8.0 software, and the final model demonstrated high reliability in terms of the composite reliability and Cronbach's alpha.

RESULTS: Analysis of the CFA showed an acceptable fit indices in CFI (0.936), TLI (0.926), RMSEA = 0.039 (90% CI, 0.034, 0.045) and SRMR (0.049) of the AEQ-PE measurement model. All of the items in the original AEQ-PE version were retained and deemed suitable for Malay primary school pupils.