Impaired Fasting Glucose as a Pivotal Transition Stage in Diabetes Progression: A Multi-State Markov Model Analysis of Metabolic and Comorbidity Drivers in Middle-aged and older Chinese Populations

Abstract Background Diabetes mellitus, a global public health crisis affecting over 537 million adults, underscores the urgent need to delineate dynamic glycemic transitions for effective prevention. Impaired fasting glucose (IFG), a reversible prediabetic state, represents a critical yet underexplored window for intervention, particularly in aging populations with heterogeneous metabolic profiles. Methods Utilizing longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS, 2011–2015), we applied a continuous-time multi-state Markov model (MSM) to quantify transition intensities, sojourn times, and covariate effects among glycemic states (Normal, IFG, Diabetes) in 5,773 middle-aged and older Chinese adults (≥ 45 years). Covariates included metabolic, demographic, and clinical factors. Results The highest transition intensity was observed for Normal→IFG (0.453/year), surpassing IFG→Diabetes progression (0.052/year), while direct Normal→Diabetes transitions were negligible (0.0001/year). Regression from IFG→Normal dominated recovery pathways (0.974/year), whereas Diabetes→IFG reversal remained limited (0.156/year). Metabolic disturbances and comorbidities significantly accelerated progression: dyslipidemia (HR = 3.60, 95% CI:2.82–4.60), hypertension (HR = 2.26, 1.77–2.86), and obesity (HR = 1.67, 1.31–2.14) drove IFG→Diabetes transitions, while normal waist circumference (female ≤ 80 cm, male ≤ 85 cm) exerted protection (HR = 0.42, 0.29–0.59). Over a 50-year horizon, individuals spent 31.5 years in the Normal state, 14.3 years in IFG, and 4.2 years in Diabetes. Conclusions IFG emerges as a pivotal intervention stage with high metabolic plasticity. Targeted management of obesity, dyslipidemia, and hypertension, alongside waist circumference monitoring, may curb diabetes progression. This study advocates for precision prevention strategies integrating multisystem comorbidities and metabolic phenotypes, offering actionable insights for public health initiatives in aging populations.