Key result
Adverse joint cardiometabolic and inflammatory trajectories linked to up to ~46% higher incident CVD risk.
Why the study?
CVD risk assessment from single-time-point measurements may inadequately capture the dynamic interplay of obesity, metabolic dysfunction, and chronic inflammation.
Does the dynamic co-evolution of obesity, metabolic dysfunction, and inflammation (joint trajectories of BMI, TyG index, and hsCRP) predict incident cardiovascular disease in middle-aged and older adults?
Cohort (n=4,483)
Yes
Does the dynamic co-evolution of obesity, metabolic dysfunction, and inflammation (joint trajectories of BMI, TyG index, and hsCRP) predict incident cardiovascular disease in middle-aged and older adults?
Hazard Ratio: 1.46 (95% CI 1.16–1.84)
p-value: p=0.001
Longitudinal co-evolution patterns of obesity, metabolic dysfunction, and inflammation identify distinct phenotypes with significantly elevated risks of incident cardiovascular disease compared to a sustained low-risk profile.
Adverse joint trajectories identify higher-risk CVD phenotypes; extends single-marker analyses but remains hypothesis-generating pending trials.
BACKGROUND: Cardiovascular disease (CVD) risk assessment based on single-time-point measurements may inadequately capture the dynamic interplay of obesity, metabolic dysfunction, and chronic inflammation. Understanding their long-term co-evolution may improve CVD risk stratification. METHODS: We conducted a prospective cohort study using data from the China Health and Retirement Longitudinal Study. Participants aged ≥ 45 years with repeated measurements of body mass index (BMI), triglyceride-glucose (TyG) index, and high-sensitivity C-reactive protein (hsCRP) between 2011 and 2015 were included. Joint trajectories of these obesity-metabolic-inflammatory markers were identified using the KmL3D clustering algorithm. Incident CVD (heart disease or stroke) was ascertained during follow-up from 2015 to 2020. Cox proportional hazards models were applied to evaluate associations between trajectory groups and CVD risk after adjustment for demographic, lifestyle, and clinical covariates. RESULTS: Among 4483 participants (mean age 57.8 years; 52.6% women), four distinct joint trajectory patterns were identified: a sustained low-risk profile (46.8%), an obesity-predominant profile (26.7%), a metabolic-obesity-driven profile (17.1%), and an inflammation-dominant profile (9.4%). During a median follow-up of 5.0 years, 592 incident CVD events occurred. Compared with the low-risk profile, all adverse trajectory groups were associated with significantly higher CVD risk, with hazard ratios ranging from 1.35 to 1.46 after full adjustment. Associations were more pronounced for stroke, particularly among individuals with a metabolic-obesity-driven trajectory. Findings were robust across sensitivity analyses. CONCLUSIONS: Distinct dynamic co-evolution patterns of obesity, metabolic dysfunction, and inflammation identify population subgroups with substantially different risks of incident CVD.
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Wang et al. (2026) conducted a cohort in Middle-aged and older adults without baseline CVD (n=4,483). Adverse joint trajectories of BMI, TyG index, and hsCRP (obesity-predominant, metabolic-obesity-driven, and inflammation-dominant profiles) vs. Sustained low-risk profile was evaluated on Incident CVD (heart disease or stroke) (HR 1.46, 95% CI 1.16-1.84, p=0.001). Compared with a sustained low-risk profile, adverse joint trajectories of obesity, metabolic dysfunction, and inflammation were associated with significantly higher risk of incident CVD (HRs ranging from 1.35 to 1.46).
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