Social Sciences
Wenxi Luo, MD
Postgraduate
The first medical center, Chinese PLA General hospital
Haidian, Beijing, Beijing, China (People's Republic)
Ming Zhou, MD
Doctor
The first medical center, Chinese PLA General hospital
Beijing, Beijing, China (People's Republic)
Hao Liu, MD
Postgraduate
The first medical center, Chinese PLA General hospital
Beijing, Beijing, China (People's Republic)
Ziyi Han, MD
Postgraduate
Medical School of Chinese PLA, Beijing, China
haidian, Beijing, China (People's Republic)
Gongzi Zhang, MD
Doctor
The first medical center, Chinese PLA General hospital
Beijing, Beijing, China (People's Republic)
Liping Huang, MD
Professor
The first medical center, Chinese PLA General hospital
Beijing, Beijing, China (People's Republic)
Socioeconomic status (SES) is linked to adverse health outcomes, yet it remains unclear whether the SES are associated with frailty and sarcopenia.
Design:
Data in the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Using latent class analysis (LCA), distinct subgroups were identified based on three SES indicators: education, income and occupation. Frailty and sarcopenia trajectories were assessed using group-based trajectory model (GBTM). Multivariable regression models were then utilized to examine the associations between SES and the identified trajectories. Linear mixed-effects models were also used to analyze the relationships between SES and changes in frailty and sarcopenia over time. Finally, both univariable and multivariable Mendelian randomization analyses were conducted to evaluate the causality.
Results:
Total 4,527 participants were included in the frailty and 5,754 in the sarcopenia analysis. LCA identified three distinct SES classes: low, medium, and high. GBTM revealed three frailty trajectories (low-stable, fluctuating, accelerated-rising) and four sarcopenia trajectories (persistently low, moderate-to-low, low-to-high, persistently high). Compared to the low SES class, medium SES was associated with lower risk of both the fluctuating frailty (OR [95%CI] = 0.379 [0.307, 0.469]) and the accelerated-rising frailty trajectory (0.252 [0.193, 0.328]). Furthermore, high SES was associated with significantly lower odds of the moderate-to-low sarcopenia (OR [95%CI] = 0.378 [0.246, 0.581]) and the persistently high sarcopenia trajectory (0.280 [CI: 0.164, 0.476]). Mixed-effects models confirmed that higher SES had a significantly lower risk and slower progression of these conditions over time (p< 0.001). MR analyses provided evidence supporting that higher educational attainment is causally associated with a lower frailty index/score, faster gait speed.
Conclusion:
Lower SES was significantly associated with an increased risk and more rapid progression of both frailty and sarcopenia. SES may thus serve as a valuable indicator for preventing or delaying the onset and progression of frailty and sarcopenia.