Despite various efforts introduced, private health insurance coverage is still low in Malaysia. The objective of this article is to find the factors associated with not having a private health insurance in Malaysia. We analyze data involving 19 959 respondents from the 2015 National Health Morbidity Survey. In this article, we describe the prevalence of not having health insurance and conducted binary logistic regression to identify determinants of uninsured status. A total of 56.6% of the study population was uninsured. After adjusting for other variables, the likelihood of being uninsured was higher among those aged 50 years and above, females, Malay/other Bumiputra ethnicities, rural, government/semigovernment, self-employed, unpaid workers and retirees, unemployed, lower education level, without home ownership and single/widowed/divorced, daily smoker, underweight body mass index, and current drinker. The likelihood of being uninsured also increased with increasing household size while the inversed trend was seen for household income. A substantial proportion of population in Malaysia did not have private health insurance, and these subgroups have limited preferential choices for provider, facility, and care.
This study aimed to identify the prevalence of psychological distress and its association with sociodemographic characteristics, burden of care, and the coping strategies used by childminders in residential homes. A total of 151 childminders (median age = 39; 64.7% female) participated in the study. The prevalence of psychological distress was 59.4%, and 74.0% recorded mild to moderate burden. Multivariate analyses showed that caregiver burden (adjusted beta = 0.464, P = .01), lesser application of problem-focused coping (adjusted beta = -0.292, P = .012), lower salary (adjusted beta = -0.196, P = .040), and lower educational qualification (adjusted beta = -0.212, P = .038) predicted higher psychological distress. Regular screening of psychological distress and burden of care is recommended among this population.
Plasmodium knowlesi is an emerging species for malaria in Malaysia, particularly in East Malaysia. This infection contributes to almost half of all malaria cases and deaths in Malaysia and poses a challenge in eradicating malaria. The aim of this study was to develop a predictive model for P. knowlesi susceptibility areas in Sabah, Malaysia, using geospatial data and artificial neural networks (ANNs). Weekly malaria cases from 2013 to 2014 were used to identify the malaria hotspot areas. The association of malaria cases with environmental factors (elevation, water bodies, and population density, and satellite images providing rainfall, land surface temperature, and normalized difference vegetation indices) were statistically determined. The significant environmental factors were used as input for the ANN analysis to predict malaria cases. Finally, the malaria susceptibility index and zones were mapped out. The results suggested integrating geospatial data and ANNs to predict malaria cases, with overall correlation coefficient of 0.70 and overall accuracy of 91.04%. From the malaria susceptibility index and zoning analyses, it was found that areas located along the Crocker Range of Sabah and the East part of Sabah were highly susceptible to P. knowlesi infections. Following this analysis, targetted entomological mapping and malaria control programs can be initiated.
Obesity is a rising concern globally. This study investigated the prevalence and factors associated with obesity and abdominal obesity (AO) among 5613 Malaysians aged 40 years and older via computer-assisted personal interviewing and anthropometric measurements. Obesity and AO prevalence were 37.8% and 63.1%, respectively. Significant associations were observed between: obesity with higher risk in patients aged between 40 and 49 years, Indians, females, income ≥RM 2000, and health status, and AO with higher risk in patients aged between 50 and 59 years, Indians, females, never married, income ≥RM 2000, and vigorous physical activity. Hence, age, sex, income, and ethnicity are associated with both obesity and AO. Promoting healthy body mass index and waist circumference is essential for healthy ageing.
This cross-sectional study examines the prevalence of sleep deprivation and its associated factors among 1017 undergraduate students in Malaysia. Sociodemographic and lifestyle factors such as smoking, alcohol, dietary habits, Internet/smartphone use, physical activity, and sedentary behavior were assessed. Sleep deprivation was defined as sleeping less than 7 hours in a day. There were almost equal proportions of females (51.0%) and males (49.0%), and the average age was 20.71 ± 1.47 years. Prevalence of sleep deprivation was 58.1% and its associated factors were students in Year 3 and Year 4, Chinese ethnicity, Indian ethnicity, and consuming fast food more than once a week. Understanding the associated lifestyle factors with sleep deprivation among young generation will be beneficial to develop public health policies and programs to tackle the issue.
Nurses' preparedness has been very important for them to treat patients effectively during the COVID-19 pandemic and serve the community. Nurses provide a vital role in mitigating the effects of health crises. In order to help nurses better understand their skills, abilities, and knowledge, as well as the actions that they should take to manage care, the research aims of this study are to (1) investigate the level of preparedness, readiness, and anxiety among nurses during the COVID-19 outbreak in Sabah, Malaysia; (2) examine the effects of various differences in preparedness and readiness among nurses; and (3) examine the effect of COVID-19 preparedness on anxiety among nurses. The results revealed that the nurses were moderately competent in managing the COVID-19 care situation. Each of the 3 differentiating characteristics (age, work experience, and previous disaster experience) did not predict how nurses would manage COVID-19 preparedness significantly. Besides, we also found only 2 dimensions of preparedness (familiarity with epidemiology and surveillance and familiarity with psychological issues) significantly predicted nurses' anxiety levels. Familiarity with epidemiology and surveillance predicted nurses' anxiety positively; in contrast, familiarity with psychological issues negatively influenced nurses' anxiety.