Unveiling the Impact of Physical Geography on Poverty: A Comprehensive Analysis for Sustainable Development

This study examines the effects of physical geography, demographic characteristics of household heads, and poverty, with a specific focus on the number of poor household heads within districts of Terengganu. Through the utilization of a Poisson log-linear modeling approach, the research investigates the effects of physical geography and demographic factors, on the number of poor household heads for each of the sub-districts. The central concern of this research revolves around the need to comprehend the underlying reasons for differing poverty rates among sub-districts in Terengganu. To carry out the analysis, a Poisson log-linear modeling is employed for the data, leveraging SPSS and Rstudio for statistical analysis. This method enabled us to thoroughly assess how physical geography factors (including terrain and accessibility) and demographic characteristics of household heads (including age, education level, and employment status) influence poverty rates. To determine the distribution of spatial poverty, ArcMap is used to visualize the Standardised Poverty Ratio. The results of the study show that 31 sub-districts were identified as not being at risk of poverty and another 31 were labeled as having a high poverty rate. Furthermore, the Poisson regression analysis yielded several important insights into the factors influencing poverty rates. Specifically, it is found that a higher average age is associated with a decrease in poverty. Conversely, an increase in non-formal education levels, lower elevations, steeper slopes, and higher river density are linked to an increase in poverty. These findings have significant implications for policy formulation and targeted interventions in Terengganu, providing valuable guidance for addressing poverty-related challenges. The mapping of high-risk poverty areas offers crucial information for spatially targeted interventions, facilitating the implementation of more efficient poverty reduction measures. Furthermore, research findings enhance the understanding of the intricate dynamics between physical geography, demographic characteristics, and household poverty. By identifying the significant factors impacting poverty, this study provides valuable insights for developing targeted poverty alleviation strategies and formulating evidence-based policies. In conclusion, this study serves to inform policymakers, researchers, and practitioners about the multifaceted relationships between physical geography, demographic characteristics, and household poverty. By recognizing the critical role played by these factors, stakeholders can devise comprehensive approaches tailored to specific contexts, effectively addressing poverty, promoting inclusive growth, and improving the well-being of vulnerable populations

Relationship between common air pollutants with risk of cardio-respiratory hospitalization in urbanized areas in Kelantan

A high concentration of air pollution can lead to health problems which are the cardiovascular and respiratory systems (WHO, 2014). A study has been conducted to know the relationship between five criteria air pollutants with hospitalization related to cardiovascular and respiratory diseases in two cities in Kelantan. The secondary data from 2000 until 2015 analyzed in the study were obtained from DOE and MOH for the air pollutants concentration and hospitalization, respectively. This study shows that the mean concentration of all pollutants in the study area is below the RMAAQS. Significant Relative Risk (RR) values were found for cardiovascular hospitalization associated with SO2 (RR = 1.537, 95% CI = 2.970, 7.956), NO2 (RR = 1.212, 95% CI = 1.156, 1.272), and O3 (RR = 4.873, 95% CI = 2.768, 8.578). In contrast, significant RR for respiratory hospitalization was found to be associated with SO2 (RR = 1.952, 95% CI = 1.013, 3.762), NO2 (RR = 2.021, 95% CI = 6.170, 6.620), O3 (RR = 1.128, 95% CI = 4.427, 2.874), and PM10 (RR = 1.008, 95% CI = 1.007, 1.008). The highest value of Relative Risk is O3 and NO2 for hospitalization related to cardiovascular and respiratory diseases, respectively. In conclusion, the value of RR associated with air pollutants proves that air pollutants are associated with cardiovascular and respiratory-related hospitalization risk

Evolution of green space under rapid urban expansion in Southeast Asian cities

Globally, rapid urban expansion has caused green spaces in urban areas to decline considerably. In this study, the rapid expansion of three Southeast Asia cities were considered, namely, Kuala Lumpur City, Malaysia; Jakarta, Indonesia; and Metro Manila, Philippines. This study evaluates the changes in spatial and temporal patterns of urban areas and green space structure in the three cities over the last two decades. Land use land cover (LULC) maps of the cities (1988/1989, 1999 and 2014) were developed based on 30-m resolution satellite images. The changes in the landscape and spatial structure were analysed using change detection, landscape metrics and statistical analysis. The percentage of green space in the three cities reduced in size from 45% to 20% with the rapid expansion of urban areas over the 25-year period. In Metro Manila and Jakarta, the proportion of green space converted to urban areas was higher in the initial 1989 to 1999 period than over the latter 1999 to 2014 period. Significant changes in green space structure were observed in Jakarta and Metro Manila. Green space gradually fragmented and became less connected and more unevenly distributed. These changes were not seen in Kuala Lumpur City. Overall, the impact of spatial structure of urban areas and population density on green space is higher in Jakarta and Metro Manila when this is compared to Kuala Lumpur. Thus, the results have the potential to clarify the relative contribution of green space structure especially for cities in Southeast Asia where only a few studies in urban areas have taken place

Habitat quality assessment in the Royal Belum rainforest, Malaysia using spatial analysis

Royal Belum rainforest contains various flora and fauna species, however, the assessment of habitat quality is still lacking. This study aims to develop the habitat quality zone in the Royal Belum rainforest. The downloaded Landsat 8 OLI/TIRS CI satellite images in the year 2020 from the United States Geological Survey (USGS) were processed using supervised classification and exported into vector data in ArcGis 10.8. Land use, normalized difference vegetation index (NDVI), buffer, and land structure were then analyzed. The result shows that the highest percentage and density of the land use of the Royal Belum rainforest is vegetation. Buffer zone analysis identifies the risky area for habitat in the range of 1km and 5km from the built-up area. The area within the buffer ring should be protected from building and construction to ensure habitat quality in that area can be maintained. This study will give a better understanding of land use and vegetation index assessment for future planning in the Royal Belum rainforest. Therefore, habitat quality assessment is an important tool that can help to identify areas of high-quality habitat that are crucial for the survival and reproduction of target species and to prioritize these areas for conservation and management

Unveiling the Impact of Physical Geography on Poverty: A Comprehensive Analysis for Sustainable Development

This study examines the effects of physical geography, demographic characteristics of household heads, and poverty, with a specific focus on the number of poor household heads within districts of Terengganu. Through the utilization of a Poisson log-linear modeling approach, the research investigates the effects of physical geography and demographic factors, on the number of poor household heads for each of the sub-districts. The central concern of this research revolves around the need to comprehend the underlying reasons for differing poverty rates among sub-districts in Terengganu. To carry out the analysis, a Poisson log-linear modeling is employed for the data, leveraging SPSS and Rstudio for statistical analysis. This method enabled us to thoroughly assess how physical geography factors (including terrain and accessibility) and demographic characteristics of household heads (including age, education level, and employment status) influence poverty rates. To determine the distribution of spatial poverty, ArcMap is used to visualize the Standardised Poverty Ratio. The results of the study show that 31 sub-districts were identified as not being at risk of poverty and another 31 were labeled as having a high poverty rate. Furthermore, the Poisson regression analysis yielded several important insights into the factors influencing poverty rates. Specifically, it is found that a higher average age is associated with a decrease in poverty. Conversely, an increase in non-formal education levels, lower elevations, steeper slopes, and higher river density are linked to an increase in poverty. These findings have significant implications for policy formulation and targeted interventions in Terengganu, providing valuable guidance for addressing poverty-related challenges. The mapping of high-risk poverty areas offers crucial information for spatially targeted interventions, facilitating the implementation of more efficient poverty reduction measures. Furthermore, research findings enhance the understanding of the intricate dynamics between physical geography, demographic characteristics, and household poverty. By identifying the significant factors impacting poverty, this study provides valuable insights for developing targeted poverty alleviation strategies and formulating evidence-based policies. In conclusion, this study serves to inform policymakers, researchers, and practitioners about the multifaceted relationships between physical geography, demographic characteristics, and household poverty. By recognizing the critical role played by these factors, stakeholders can devise comprehensive approaches tailored to specific contexts, effectively addressing poverty, promoting inclusive growth, and improving the well-being of vulnerable populations

COMPRESSED OIL PALM FRONDS COMPOSITE: A PRELIMINARY STUDY ON MECHANICAL PROPERTIES

Abstract: The mechanical properties of composites consisting of compressed oil palm fronds have been investigated. Three maturity groups at different portion were bind together using two types of formaldehyde resin which were phenol and urea. Modulus of rupture (MOR) for bending strength of the compressed oil palm fronds composite increase from young to intermediate and mature maturity group for each portion, meanwhile decrease from bottom to middle and top portion for each maturity group. Same results trend have been recorded for modulus of elasticity (MOE) for bending strength and modulus of rupture (MOR) for compression strength. Statistical analysis indicated significant differences between compressed oil palm fronds composite made from each maturity group and portion, but no differences were observed in the type of resin used

Spatial Distribution of COVID-19 Infected Cases in Kelantan, Malaysia

Kota Bharu city in Kelantan, Malaysia was reported with the highest cases of coronavirus disease 2019 (COVID-19) among other districts. Kota Bharu is the capital city of Kelantan, which acts as the administrative, commercial, and financial areas. A large population pool may become a potential carrier for disease transmission to become an epidemic. However, the impact of population density on the COVID-19 outbreak in Malaysia is still unknown and undiscovered. Therefore, this study investigates the impact of population density on COVID-19 as a potential virus transmission carrier using linear regression models. The chances of formulating new strategies for combating COVID-19 are higher when the driver of transmission potential is identified. This study shows that the highest value of infected area density is in Kota Bharu (0.76), while the infected risk area was highest in Jeli (0.33). This study found that there is a strong relationship between COVID-19 infection cases in Kelantan and population density (R2 which is 0.845). Therefore, high population density was identified as a potential driver of transmission of COVID-19 outbreak. Understanding the potential drivers of the disease in a local setting is very important for better preparation and management. The outcome of the study can aid in the development of a new analytical model for strategic planning of Zero COVID-19 for securing the public health and wellness, both social and economic, by researchers, scientists, planners, resource managers, and decision-makers

Case Series of Genetically Confirmed Index Cases of Familial Hypercholesterolemia in Primary Care

BACKGROUND: In Malaysia, the prevalence of genetically confirmed heterozygous familial hypercholesterolemia (FH) was reported as 1 in 427. Despite this, FH remains largely underdiagnosed and undertreated in primary care.CASE REPORT: In this case series, we report 3 FH cases detected in primary care due to mutations in the low-density lipoprotein receptor (LDLR), apolipoprotein-B (APOB), and proprotein convertase subtilisin/kexin type 9 (PCSK9) genes. The mutations in case 1 (frameshift c.660del pathogenic variant in LDLR gene) and case 2 (missense c.10579C>T pathogenic variant in APOB gene) were confirmed as pathogenic, while the mutation in case 3 (missense c.277C>T mutation in PCSK9 gene) may have been benign. In case 1, the patient had the highest LDL-c level, 8.6 mmol/L, and prominent tendon xanthomas. In case 2, the patient had an LDL-c level of 5.7 mmol/L and premature corneal arcus. In case 3, the patient had an LDL-c level of 5.4 mmol/L but had neither of the classical physical findings. Genetic counseling and diagnosis were delivered by primary care physicians. These index cases were initially managed in primary care with statins and therapeutic lifestyle modifications. They were referred to the lipid specialists for up-titration of lipid lowering medications. First-degree relatives were identified and referred for cascade testing.CONCLUSIONS: This case series highlights different phenotypical expressions in patients with 3 different FH genetic mutations. Primary care physicians should play a pivotal role in the detection of FH index cases, genetic testing, management, and cascade screening of family members, in partnership with lipid specialists

Habitat quality assessment in the Royal Belum rainforest, Malaysia using spatial analysis

Royal Belum rainforest contains various flora and fauna species, however, the assessment of habitat quality is still lacking. This study aims to develop the habitat quality zone in the Royal Belum rainforest. The downloaded Landsat 8 OLI/TIRS CI satellite images in the year 2020 from the United States Geological Survey (USGS) were processed using supervised classification and exported into vector data in ArcGis 10.8. Land use, normalized difference vegetation index (NDVI), buffer, and land structure were then analyzed. The result shows that the highest percentage and density of the land use of the Royal Belum rainforest is vegetation. Buffer zone analysis identifies the risky area for habitat in the range of 1km and 5km from the built-up area. The area within the buffer ring should be protected from building and construction to ensure habitat quality in that area can be maintained. This study will give a better understanding of land use and vegetation index assessment for future planning in the Royal Belum rainforest. Therefore, habitat quality assessment is an important tool that can help to identify areas of high-quality habitat that are crucial for the survival and reproduction of target species and to prioritize these areas for conservation and management