In China, although policies promoting physical-medical integration have received widespread national attention, the existence and manifestation of health equity promotion within these policies still require further exploration. This study used text analysis to examine 62 policy documents on physical-medical integration issued by various Chinese governmental departments from June 2016 to June 2023, utilizing KH Coder software for qualitative analysis. The analysis revealed a strong emphasis on public health, promoting health management and disease prevention across all age groups. The policies aimed to ensure the equitable distribution of health care resources, particularly those benefiting rural and underserved populations, and they underscored the importance of collaboration among the government, sports, and health care sectors to foster sports-health integration. The integration of sports and health policy is a key initiative to address chronic diseases in China, as it aligns closely with health equity principles. Achieving these goals requires ongoing improvements in implementation and monitoring, with a focus on the diverse needs of various populations.

With the acceleration of the socialist modernization process, people’s living standards continue to improve, and the modernization of cities is also developing rapidly. In the process of urban construction, a series of problems such as how to deal with the relationship between citizens and the surrounding environment, how to carry out citizens' health activities, and how to organize citizens to exercise healthily are becoming more and more obvious. With the introduction of the National Sports Outline, as an important sports activity, Chinese martial arts has a long history and profound cultural heritage, and it still plays an irreplaceable role in promoting the national spirit and building a harmonious society today. Therefore, this paper introduced the LSTM recurrent neural network algorithm to collect and extract the current data on martial arts fitness in the pursuit of health. By constructing the LSTM neuron structure and building the LSTM recurrent neural network structure, a state estimation based on LSTM feature extraction was proposed. The algorithm used the memory ability of LSTM to extract the relevant features of the data stream, which significantly improved the accuracy of the data stream collection. The experimental results showed that the time required by the method in this paper were 12.7, 10.2, 12.4 s and 11.8 min respectively, and the accuracy rates were 98.78, 98.26, 99.03 and 97.89%, respectively, which were greatly improved compared with the existing methods.