Background: This study aims to investigate the current impacts of extreme temperature and heatwaves on human health in terms of both mortality and morbidity. This systematic review analyzed the impact of heatwaves on mortality, morbidity, and the associated vulnerability factors, focusing on the sensitivity component. Methods: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 flow checklist. Four databases (Scopus, Web of Science, EBSCOhost, PubMed) were searched for articles published from 2012 to 2022. Those eligible were evaluated using the Navigation Guide Systematic Review framework. Results: A total of 32 articles were included in the systematic review. Heatwave events increased mortality and morbidity incidence. Sociodemographic (elderly, children, male, female, low socioeconomic, low education), medical conditions (cardiopulmonary diseases, renal disease, diabetes, mental disease), and rural areas were crucial vulnerability factors. Conclusions: While mortality and morbidity are critical aspects for measuring the impact of heatwaves on human health, the sensitivity in the context of sociodemographic, medical conditions, and locality posed a higher vulnerability to certain groups. Therefore, further research on climate change and health impacts on vulnerability may help stakeholders strategize effective plans to reduce the effect of heatwaves.

Background: Waist circumference (WC) is an accurate and simple measure of abdominal obesity as compared to waist-hip ratio (WHR). The aim of this study was to determine the correlation between body mass index (BMI) with WC and WHR and suggest cutoff points for WC among Rural Malaysian adults. Methods: A cross-sectional study was conducted among 669 respondents from three villages in Tanjung Karang, located in the district of Kuala Selangor. Data collection was carried out by guided questionnaires and anthropometric measures. Results: The prevalence of abdominal obesity for BMI was almost similar for both gender across Caucasian and Asian BMI cutoff points. Based on Caucasian cutoff points, the prevalence of abdominal obesity for WC was 23.8% (male) and 66.4% (female) while for WHR was 6.2% (male) and 54.2% (female). Asian cutoff points gave higher prevalence of abdominal obesity compared to that of WC among male respondents and WHR for both genders. WC showed strong and positive correlation with BMI compared to WHR (in male WC r = 0.78, WHR r = 0.24 and in female WC r = 0.72, WHR r = 0.19; P < 0.001). Receiver operating characteristic curve analysis suggested WC cutoff points of 92.5 cm in men and 85.5 cm in women is the optimal number for detection of abdominal obesity. Conclusions: WC is the best indicator as compared with WHR for abdominal obesity for Malaysian adults.

The trend of global prevalence for hypertension has been dramatically increasing for the past two decades in Southeast Asian countries. A systematic review aiming to assess the prevalence of hypertension and its risk factors among the urban population in Southeast Asian countries was conducted. We performed database searches of PubMed and Web of Science and performed meta-analysis to determine the pooled prevalence estimate. The overall pooled prevalence estimate of hypertension for Southeast Asian urban population was 33.82%. Among this, 33.98% of hypertension was reported in the community and 32.45% among adolescents in school. The common risk factors that we found were male, ethnicity, education and socioeconomic level, body mass index, waist circumference, smoking, and dyslipidaemia. The review indicates an urgent need for primary and secondary prevention activities. Therefore, a multisectoral and intersectoral approach and collaboration should be undertaken to improve the overall health outcomes of all populations in all Southeast Asian countries.

Leptospirosis is a neglected emerging zoonotic disease with a profound public health impact worldwide with higher burden of disease in resource-poor countries. The environmental and occupational exposures contribute to human and animal transmission, but the interaction was less explored. A deeper understanding of the critical environmental and occupational drivers in different contexts will provide useful information for disease control and prevention measures. This review aimed to summarize the potential environmental and occupational risk factors associated with leptospirosis infection. Four databases (Scopus, Web of Science, Ovid MEDLINE, EBSCOhost) were searched for articles published from 2012 to 2021. Eligible articles were assessed using a checklist for assessing the quality of the studies. The quality of the articles was assessed based on the laboratory diagnosis approach and statistical analysis method. A total of 32 studies were included in this systematic review. Water-related risk factors such as natural water as the primary water source (AOR 1.8-18.28), water-related recreational activities (AOR 2.36-10.45), flood exposure (AOR 1.54-6.04), contact with mud (AOR 1.57-4.58) and stagnant water (AOR 2.79-6.42) were associated with increased risk of leptospirosis. Infrastructural deficiencies such as un-plastered house walls and thatched houses presented a higher risk (AOR 2.71-5.17). Living in low-lying areas (AOR 1.58-3.74), on clay loam soil (OR 2.72), agricultural land (OR 2.09), and near rubber tree plantations (AOR 11.65) is associated with higher risk of leptospirosis. Contact with rats (AOR 1.4-3.5), livestock (AOR 1.3-10.4), and pigs (AOR 1.54-7.9) is associated with an increased risk of leptospirosis. Outdoor workers (AOR 1.95-3.95) and slaughterhouse workers (AOR 5.1-7.5) have higher risk of leptospirosis. The environmental and occupational components related to water, infrastructure, landscape, agriculture, and exposed animals play an essential role in leptospirosis transmission. The magnitude of those risk factors differs with geographical region, climate factor, urbanization and population growth, and the country's socioeconomic status.

Severe floods increase the risk of leptospirosis outbreaks in endemic areas. This study determines the spatial-temporal distribution of leptospirosis in relation to environmental factors after a major flooding event in Kelantan, Malaysia. We conducted an observational ecological study involving incident leptospirosis cases, from the 3 months before, during, and three months after flood, in reference to the severe 2014 Kelantan flooding event. Geographical information system was used to determine the spatial distribution while climatic factors that influenced the cases were also analyzed. A total of 1,229 leptospirosis cases were notified within the three study periods where incidence doubled in the postflood period. Twelve of 66 subdistricts recorded incidence rates of over 100 per 100,000 population in the postflood period, in comparison with only four subdistricts in the preflooding period. Average nearest neighborhood analysis indicated that the cases were more clustered in the postflood period as compared with the preflood period, with observed mean distance of 1,139 meters and 1,666 meters, respectively (both at P < 0.01). Global Moran’s I was higher in the postflood period (0.19; P < 0.01) as compared with the preflood period (0.06; P < 0.01). Geographic weighted regression showed that living close to water bodies increased the risk of contracting the disease. Postflooding hotspots were concentrated in areas where garbage cleanup occurred and the incidence was significantly associated with temperature, humidity, rainfall, and river levels. Postflooding leptospirosis outbreak was associated with several factors. Understanding the spatial distribution and associated factors of leptospirosis can help improve future disease outbreak management after the floods.

Early warning system (EWS) for vector-borne diseases is incredibly complex due to numerous factors originating from human, environmental, vector and the disease itself. Dengue EWS aims to collect data that leads to prompt decision-making processes that trigger disease intervention strategies to minimize the impact on a specific population. Dengue EWS may have a similar structural design, functions, and analytical approaches but different performance and ability to predict outbreaks. Hence, this review aims to summarise and discuss the evidence of different EWSs, their performance, and their ability to predict dengue outbreaks. A systematic literature search was performed of four primary databases: Scopus, Web of Science, Ovid MEDLINE, and EBSCOhost. Eligible articles were evaluated using a checklist for assessing the quality of the studies. A total of 17 studies were included in this systematic review. All EWS models demonstrated reasonably good predictive abilities to predict dengue outbreaks. However, the accuracy of their predictions varied greatly depending on the model used and the data quality. The reported sensitivity ranged from 50 to 100%, while specificity was 74 to 94.7%. A range between 70 to 96.3% was reported for prediction model accuracy and 43 to 86% for PPV. Overall, meteorological alarm indicators (temperatures and rainfall) were the most frequently used and displayed the best performing indicator. Other potential alarm indicators are entomology (female mosquito infection rate), epidemiology, population and socioeconomic factors. EWS is an essential tool to support district health managers and national health planners to mitigate or prevent disease outbreaks. This systematic review highlights the benefits of integrating several epidemiological tools focusing on incorporating climatic, environmental, epidemiological and socioeconomic factors to create an early warning system. The early warning system relies heavily on the country surveillance system. The lack of timely and high-quality data is critical for developing an effective EWS.