Introduction: This study looks at the patient’s perspective to determine the Catastrophic Health Expenditure (CHE) level and the possible factors which can be associated with CHE in cancer patients. Methods: This cross sectional study was done in National Cancer Institute, Malaysia with 206 patients sampled using the multilevel sampling method and data collected from interview with patients using a validated questionnaire. The CHE definition used in this study is when the monthly health expenditure exceeds more than 10% of the monthly household income. Results: This study showed a CHE level of 26.2%. CHE was higher in Indian ethnicity (P = 0.017), single marital status (P = 0.019), poverty income (P < 0.001), small household size (P = 0.006) and without Guarantee Letter (GL) (P = 0.002) groups. The significant predicting factors were poverty income aOR 5.60 (95% CI: 2.34 – 13.39), home distance near to hospital aOR 4.12 (95% CI: 1.74 – 9.76), small household size aOR 4.59 (95% CI: 1.07 – 19.72) and lack of Guarantee Letter aOR 3.21 (95% CI: 1.24 – 8.30). Conclusion: The information from this paper can be used by policy makers to formulate better strategies in terms of health financing so that high risk for CHE cancer patients groups can be protected under a better health financing system.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. 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.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. 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.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. 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.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. 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.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. 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.

Introduction: There has been growing recognition linking spread of COVID-19 with environmental factors. One of the environmental factors with robust epidemiological literature supporting its role in diseases is the housing or built environment. COVID-19 spread has been found to occur mostly at homes through secondary household transmission. As most people spend more times inside homes during the pandemic, household remains an important site of COVID-19 spread. The aim of this study is to examine how housing and indoor factors affect the transmission and spread of COVID-19. Methods: This review employed a comprehensive search strategy to gather a broad range of scholarly articles and grey literature to provide a comprehensive understanding of the housing-related aspects of COVID-19 transmission. Results: Three electronic databases (Web of Science, Scopus, and PubMed) were searched using specific keywords related to COVID-19, housing, residents, neighborhoods, and indoor environments. Additionally, a supplementary literature survey was conducted to include relevant grey literature sources Conclusions This article summarizes the housing indoor factors involved in COVID-19 transmission, including the role of transmission from contaminated household surfaces. Indoor transmission of COVID-19 is found to be more likely due to contact transmission and close-contact aerosol transmission in a crowded, confined, and poorly ventilated indoor environment, related to poor housing condition. Whilst role of spread through contaminated household surfaces is of low probability. Based on this review, it can be suggested that besides the existing measures including avoiding crowding, close contacts and proper ventilation, specific standards for indoor environmental quality control and housing condition might be required. Housing is a public health issue and healthy housing is of universal concern.

Introduction: C-reactive protein (CRP), urea, albumin, CRP/albumin ratio (CAR) and urea/albumin ratio (UAR) could be valuable biomarkers for determining the severity of illness in patients with COVID-19. This study aimed to determine the association between these markers and disease severity in COVID-19 patients on admission and days five to seven after admission. Methods: This retrospective study includes 153 adult COVID-19 patients admitted to Hospital Raja Perempuan Zainab II and Hospital Ampang from January 2021 to December 2021. Patients’ serum CRP, urea, albumin and creatinine levels were recorded on admission and on days five to seven after admission. The patients were categorised based on the Annex 2e guidelines published by the Ministry of Health, Malaysia and further classified as mild to moderate disease (stages 1-3) and severe to critical illness (stages 4-5). Results: On admission, urea, creatinine, CRP, UAR and CAR were significantly higher in the severe to critical group (p<0.001). The optimal cut-off value for the UAR was 0.16; the area under the curve (AUC) was 0.760, and sensitivity and specificity were 63.6% and 85.7%, respectively. The AUC of the CAR was 0.752, with 54.2% sensitivity and 91.4% specificity at an optimal cut-off value of 1.63. In severe to critical COVID-19 patients, albumin levels decreased significantly on days five to seven after admission, while urea levels remained significantly higher in this group (p<0.001, p<0.05, respectively). Conclusion: CRP, urea, albumin, CAR and UAR are promising biomarkers for predicting the severity of disease in COVID-19 patients.

Introduction: Infected diabetic foot ulcers may lead to serious complications if not recognised in the early stage. Diagnosis of infection is particularly challenging at that stage; thus, a sensitive inflammatory biomarker may be helpful. We aimed to evaluate the role of procalcitonin (PCT) as an early biomarker for infected diabetic foot ulcers (IDFU). Materials and method: This cross-sectional study was conducted at Klinik Rawatan Keluarga (KRK), Orthopedic clinic and wards in Hospital Universiti Sains Malaysia (USM) from May 2020 to December 2020. A total of 264 participants were recruited and divided into three groups: 50 diabetic patients with no ulcers (control), 107 patients with non-infected diabetic foot ulcers (NIDFU), and 107 patients with infected diabetic foot ulcers (IDFU). The level of PCT was taken for all patients. Total white count (TWC) and Creactive protein (CRP) were taken only for IDFU patients. Diagnosis of infection was based on the Infectious Disease Society of America-International Working Group of Diabetic Foot (IDSA-IMWGDF), and the severity of infection was graded according to the Wagner Classification. Results: The level of PCT was higher in IDFU than in NIDFU and diabetic patient, with a median (IQR) of 0.355 (0.63) ng/mL, 0.077 (0.15) ng/mL and 0.028 (0.02) ng/mL, respectively. PCT and CRP showed moderate positive correlations in IDFU patients (p<0.001). The sensitivity and specificity were 63.6% and 83.2%, respectively, at the best cut-off at 0.25 ng/mL. Conclusion: PCT is a valuable biomarker for the diagnosis of infection; however, it adds little value in the early diagnosis of IDFU in view of its low sensitivity.