Edges are the most basic structures in complex networks, representing relationships of node pairs. However, many higher-order interactions in reality are beyond node-to-node relationships. In recent years, the conceptualization of “higher-order structures” is considered to provide information on multiple scales, which is helpful to discover new conclusions or achieve better results in issues such as propagation, synchronization, and evolution. But for community identification, the impact of higher-order interactions may not be positive. In this study, we discovered that higher-order interactions disproportionately increase the count of edges. This poses a substantial challenge for community detection, especially when we found that higher-order interactions tend to cross multiple communities. The existence of higher-order interactions obscures the community structure in the network. And once we realize this, removing some of the higher-order interactions is an easy way to improve the accuracy of community detection.