The inability to meet the necessities of life or what is usually called is one of the challenges often experienced by several countries. One of these countries is Indonesia, with the highest poverty rate in Papua Province. Poverty can be caused by various conditions such as low education, declining health rates, increasing unemployment and population growth. This research examines the relationship between variables that cause poverty, which are thought to have a significant influence on increasing poverty rates in the region. This research method involves multiple linear regression analysis using time series data, with the SPSS 25 analysis tool. The regression results of this research show that health levels have a significant impact on poverty levels, with a strong positive correlation. However, education level and unemployment do not show a significant influence, even though they have a positive correlation. Meanwhile, population growth does not have a significant impact and has a negative correlation with poverty levels.