Abstract
BACKGROUND AND OBJECTIVES: Multimorbidity trajectories help to analyze the onset and development of multimorbidity over time and are an important public health matter. However, existing longitudinal studies have not adequately characterized trajectory differences nor their determinants across clinically distinct subpopulations stratified by baseline health status. This study explored and investigated evidence-based multimorbidity trajectories in populations with and without multimorbidity, and determined how factor trajectories and baseline factors impact multimorbidity trajectories. METHODS: Multimorbidity trajectories and factor trajectories were estimated by group-based trajectory modeling (GBTM) using data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018) and the 2014 Life History Survey. Determinants of multimorbidity trajectories were explored using multinomial logistic regression. RESULTS: Our analysis revealed similar multimorbidity trajectories in the multimorbidity population and the full population, whereas in the Non-multimorbidity population, we found four diverse trajectories. Poor Center for Epidemiologic Studies Depression (CESD) trajectories and poor functional status (FS) trajectories were consistently associated with poor multimorbidity trajectories. It was in the presence of underlying disease at baseline that age and early life adversity were associated with the negative development of multimorbidity. CONCLUSION: Multimorbidity trajectories were more complex in the non-multimorbidity population. Both CESD and FS were identified as important determinants of poor multimorbidity trajectories, underscoring the need for stratified interventions. For the non-multimorbidity population, primary prevention should integrate CESD/FS monitoring into primary care for early risk detection. For the multimorbidity population, secondary prevention requires integrated care models that concurrently manage depression and functional decline to curb progression.