Abstract: Background Trends in growth and development of children and adolescents are considered to be a " biological standard of living conditions", reflecting the combined effects of genetic trajectories, environmental factors centered on nutrition and disease, and socio-economic circumstances. Objective The aim of this study was to construct a non-invasive equation for the prediction of maturity offsets and to assess the level of physiological maturity of individuals through a longitudinal study. Design Mixed longitudinal study. Methods From the 2015-2021 cohort of the Child and Adolescent Growth and Development Longitudinal Study, children and adolescents with four or more monitoring records who could accurately calculate the age of peak height velocity (aPHV) were selected for the prediction of maturity offsets using the lasso method. After supplementing the data in 2022-2023, children and adolescents were selected based on the same selection criteria, and the equations were validated. All statistics were performed in R and GraphPad software. Main outcome Maturity offset equations. Results Male equation = -15.553 + 0.705 × age + 0.067 × sitting height + 0.063 × BMI, with a SEE of 0.625; female equation = -14.240 + 0.668 × age + 0.084 × sitting height + 0.002 × quetelet index, with a SEE of 0.542. These equations were more suitable for the current cohort of children and adolescents in Shanghai. Conclusion At the present period, children and adolescents still maintain the long-term trend of growth characterized by the advancement of the pubertal spurt. It is necessary to seize this strong momentum to give full expression to the growth potential and to promote the healthy development of the population. Maturity offset equations applicable to the current population could be adopted for the evaluation of individual physiological maturity, in order to achieve fair competition and early screening of sports talents during training and competition, and to promote the long-term development of youth sports literacy and ability level.

Key words: longitudinal study, children and adolescents, maturity offset, prediction equation