Study on the Differences in the Impact of the American Welfare System on the Health of Different Races Based on Data Mining

In the context of increasing social diversity and racial differences, the impact of welfare systems on various social groups has gained widespread attention. Focusing on the welfare system in the United States, this study tries to explore the optimal combination of welfare plans to enhance the overall health level of society. Utilizing data mining methods and based on the Apriori algorithm, a new SAP-Apriori algorithm is proposed. It incorporates dynamic parameter adjustment to enhance model accuracy and robustness. Meanwhile, multidimensional evaluation criteria are employed to comprehensively assess the quality and credibility of association rules. The analysis reveals that there are health disparities between different racial groups under the same welfare conditions. Furthermore, within the same racial group, there is a correlation between the number of welfare plans received and the health status of that race. Based on these findings, some suggestions for relevant welfare plan combinations are given to the government. This study offers a new perspective on understanding racial health disparities within the U.S. welfare system and provides a basis for formulating more effective public policies.