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

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