Environmental and Health Impacts of Pesticide-Based Malaria Control in Low- and Middle-Income Countries: A Scoping Review Introduction Malaria remains a major public health challenge in tropical and subtropical regions, necessitating effective vector control strategies. This scoping review aims to evaluate the environmental and health impacts of pesticide-based malaria control in low-and middle-income countries (LMICs). Methods A comprehensive search was conducted across Scopus, Web of Science and PubMed for studies published between 2004 and 2024, using a predefined search string based on the PEO framework. Inclusion criteria focused on studies addressing malaria control programmes and their effects on the environment and human health. Data extraction followed PRISMA 2020 guidelines. Results 12 studies were included, most of which focused on indoor residual spraying (IRS) and insecticide-treated nets (ITNs). The review identified significant direct and indirect impacts. While effective in reducing malaria transmission, IRS and ITNs pose substantial risks. Direct health effects included acute poisoning and long-term neurodevelopmental issues linked to pesticide exposure, with residues detected in breast milk. Environmental impacts included soil and water contamination, biodiversity loss and ecological disruption. The overlap of pesticide use in malaria control and agriculture was found to exacerbate insecticide resistance in mosquito populations. Conclusions Pesticide-based malaria control, while crucial, carries significant unintended consequences for human health and the environment. The findings underscore the urgent need for Integrated Vector Management (IVM) strategies that reduce reliance on chemical pesticides, mitigate resistance, and ensure environmental sustainability and public health safety.

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: N-Carboxymethyllysine (CML) is involved in diabetic nephropathy (DN) via production of oxidative stress, growth factors and cytokines. C-reactive protein (CRP) is an inflammatory marker associated with diabetes risk. This study is to determine the level of serum CML and CRP in Type 2 diabetes mellitus (T2DM) patients and healthy subjects and to determine the correlation between CML and CRP with glycated haemoglobin (HbA1c) in T2DM patients. Methods: This is a case-control study on 73 T2DM patients without nephropathy, 74 T2DM patients with nephropathy and 73 healthy subjects, aged from 18 to 65 years old. Fasting venous blood was taken and analysed for CML, CRP, HbA1c, and creatinine. The comparisons of serum CML and CRP among the three groups and the correlation between CML and CRP with HbA1c (in T2DM patients) were determined. Results: The differences in CML [median (Interquartile Range) (IQR)] between healthy subjects [131.80 (73.56) ng/ml] and T2DM patients without nephropathy [188.80 (55.95) ng/ml]; between healthy subjects and T2DM patients with nephropathy [237.70 (439.04) ng/ml] were statistically significant (P<0.001). The differences in CRP [median (IQR)] between healthy subjects [1.64 (1.91) ng/ml] and T2DM patients without nephropathy [2.15 (5.64) ng/ml]; between healthy subjects and T2DM patients with nephropathy [4.75 (6.91) ng/ml] were statistically significant (P<0.001). Logistic regression showed CML and CRP are independent predictors of diabetic groups. There was no correlation between HbA1c with CML and CRP in T2DM groups. Conclusion: Since serum CML and CRP are independent predictors of DN, their levels can be used to identify high-risk diabetic patients prone to developing DN.

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.