Background: Previous studies suggest that frailty increases the risk of mortality, but the risk of cardiovascular disease (CVD) and all-cause mortality in Chinese community-dwelling older adults remains understudied. Our aim was to explore the effect of frailty on cardiovascular and all-cause mortality in older adults based on a large-scale prospective survey of community-dwelling older adults in China.
Methods: We utilized the 2014-2018 cohort of the Chinese Longitudinal Healthy Longevity Survey and constructed a frailty index (FI) to assess frailty status. Propensity score matching was used to equalize the baseline characteristics of participants to strengthen the reliability of the findings. Hazard ratios and 95% confidence intervals (CIs) were estimated using multivariate Cox models, adjusting for potential confounders, to assess the association between frailty and cardiovascular and all-cause mortality. The relationship between frailty and cardiovascular mortality was further explored using a competing risk model considering death as a competing event. The dose-response relationships between them were estimated using restricted cubic spline models.
Results: The results of the multivariate Cox model found that the frailty group had a higher risk of CVD mortality (1.94, 95% CI: 1.43-2.63) and all-cause mortality (1.87, 95% CI: 1.63-2.14) in compared with the non-frailty group. The multivariate competing risks model suggested a higher risk of CVD mortality in the frailty group (1.94, 95% CI: 1.48-2.53). The analysis found no non-linear relationship between FI and the risk of CVD mortality but a non-linear dose-response relationship with the risk of all-cause mortality.
Conclusions: Frail older adults demonstrated a stronger risk of CVD and all-cause mortality. Reversing frailty in older adults is therefore expected to reduce the risk of death in older adults.
Keywords: Chinese older adults; all-cause mortality; cardiovascular disease mortality; competing risk; frailty; geriatric epidemiology.
© 2024 Gao, Ma, Li and Zhang.