Objective The stable isotopic composition of human tissue is related to the individual’s diet, environment and metabolic status. Once grown, human hair is no longer exchanged with the body and is chemically stable and easy to collect, making it a good subject for studying the stable isotope composition of human tissue. The oxygen and hydrogen elements that make up the human body are mainly derived from the water and food, of which the oxygen and hydrogen stable isotope composition is recorded in hair keratin. Differences in the stable isotope composition of oxygen and hydrogen in the human hair of different regions can be used to infer information about people’s diets, living areas and activity trajectories, which is of great importance in forensic science and other research fields.Methods In this study, oxygen and hydrogen stable isotope ratios of hair samples from permanent residents in different regions of China were detected and analyzed using an elemental analyzer-isotope ratio mass spectrometer (EA-IRMS).Results The results showed that there were significant differences in δ¹⁸O and δ²H between some cities, and a significant positive correlation between overall δ¹⁸O and δ²H. The overall discrimination accuracy of the stable isotope data was 63.9% for the cross-validation, and increased significantly when combined with the carbon and nitrogen stable isotope data, reaching an overall discrimination accuracy of 76.0% for the cross-validation. As the type of stable isotopes used in the discriminant analysis increased, the model’s discriminant ability was significantly enhanced.Conclusion The overall discriminative accuracy of the multi-layer perceptron neural network model built by using the stable isotope data of the 4 elements was 82.8%, and the overall discriminative accuracy of the radial basis function neural network model was 78.8%. The multilayer perceptron neural network model had the highest discriminative accuracy among the three traceability mathematical models.