Linear Regression Analysis To Measure The Correlation Between Poverty Rate And Stunting Rate

Abstract

Children's stunting or growth disorders are becoming major global health issues, particularly in impoverished nations. It is characterized by short height for children and affects future economic potential, health, and cognitive development over the long run. Stunting has a detrimental effect on cognitive growth, schooling, and future economic production in addition to being a sign of dietary deficiencies. This study aims to analyze the relationship between poverty levels and stunting rates. Using secondary data from health surveys and population censuses, this study analyzed the rate of stunting in children aged 0-5 years and correlated it with poverty indicators at the household and community levels. Correlation analysis methods were used to assess the relationship between these variables, while controlling for confounding variables such as parental education, access to health services, and nutrition. The multiple linear regression test results prove that the incidence of stunting is influenced by the poor population variable by 34.1%, so there are other factors that influence it by 64.9%. The results of the analysis show that there is a significant positive correlation between the poverty rate and the prevalence of stunting. This finding underscores the importance of cooperation between the health and economic sectors in efforts to reduce stunting and poverty.