Association of cardiovascular health score trajectory and risk of subsequent cardiovascular disease in non-diabetic population: a cohort study.

BACKGROUND

Diabetes is an important risk factor for cardiovascular disease (CVD), but in the non-diabetic population, high glucose values within the normal range are also positively associated with CVD risk. There is a lack of concern for people without diabetes and evidence is lacking regarding the association between changes in cardiovascular health score (CVHS) and CVD risk in the non-diabetic population.

METHODS

The current study included 37,970 non-diabetic participants free of CVD events in or before 2010 from the Kailuan Study and calculated CVHS according to the overall status of 7 cardiovascular health metrics between the 2006 and 2010 waves. Latent mixture models were used to explore the subgroups with different development trends included in the context of the Kailuan non-diabetic population and to identify the trajectory of each subgroup. The outcomes of the current study were CVD events, including myocardial infarction and stroke. CVHS trajectory was developed to predict subsequent CVD risk from 2010 to 2020. The Cox proportional hazard model was established to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) of CVD across different trajectory patterns.

RESULTS

Five distinct CVHS trajectory patterns were identified, including low-stable pattern (n = 2835), moderate-increasing pattern (n = 3492), moderate-decreasing pattern (n = 7526), high-stable I pattern (n = 17,135), and high-stable II pattern (n = 6982). Compared with the low-stable pattern, participants with the high-stable II pattern had a lower subsequent risk of CVD (HR = 0.22, 95%CI = 0.18-0.28); In stratification analysis, the lower risk for CVD was observed in females (HR = 0.10, 95%CI = 0.05-0.23, P for interaction < 0.05) and those aged < 60 years (HR = 0.16, 95%CI = 0.11 to 0.22, P for interaction < 0.05).

CONCLUSIONS

CVHS trajectory patterns were associated with an altered CVD risk in the non-diabetic population. When stratified by age and sex, the association was stronger in young adults and females.