BMC geriatrics · 2025
How physical activity influences motoric cognitive risk syndrome in older adults.
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Chen Xin, Zhang Zihao, Zhang Yijiang, Deng Lijuan, Guo Haihua, Zou Wen-Quan, Wang Dexin
Аннотация
OBJECTIVE: Motoric cognitive risk (MCR) is a pre-dementia syndrome linked to higher risks of cognitive decline and dementia. This study aims to investigate the relationship between total physical activity (TPA), healthy physical activity (PA), and MCR in older adults.
STUDY DESIGN: Population-based cohort study with both cross-sectional and longitudinal analyses.
METHODS: Logistic regression was used for cross-sectional analyses to examine the associations between TPA, healthy PA, and MCR at baseline. Using mediation analysis to explore the associations of gait speed and cognition in the link between physical activity and MCR. Cox regression was applied for longitudinal analyses to evaluate the relationships between TPA, healthy PA, and incident MCR risk over a 5-year follow-up. Restricted cubic splines (RCS) were employed to investigate potential nonlinear associations between TPA and MCR risk. Sensitivity analyses were conducted across different age groups to confirm the robustness of the results.
RESULTS: Logistic regression analysis revealed a significant negative association between TPA, healthy PA, and MCR. Participants engaging in healthy PA had a 36.9% lower risk of MCR (OR 0.631[0.502,0.793]). Mediation analysis showed that gait speed significantly mediated the association between PA and MCR. Cox regression further demonstrated that both TPA and healthy PA were significantly related to a lower risk of MCR. RCS analysis identified a nonlinear relationship between TPA and MCR risk, with the lowest risk observed at 86.1 METs. Sensitivity analyses across different age groups confirmed the robustness of these findings.
CONCLUSION: Higher levels of TPA and healthy PA are negatively associated with MCR, underscoring the importance of maintaining adequate PA in older adults.
STUDY DESIGN: Population-based cohort study with both cross-sectional and longitudinal analyses.
METHODS: Logistic regression was used for cross-sectional analyses to examine the associations between TPA, healthy PA, and MCR at baseline. Using mediation analysis to explore the associations of gait speed and cognition in the link between physical activity and MCR. Cox regression was applied for longitudinal analyses to evaluate the relationships between TPA, healthy PA, and incident MCR risk over a 5-year follow-up. Restricted cubic splines (RCS) were employed to investigate potential nonlinear associations between TPA and MCR risk. Sensitivity analyses were conducted across different age groups to confirm the robustness of the results.
RESULTS: Logistic regression analysis revealed a significant negative association between TPA, healthy PA, and MCR. Participants engaging in healthy PA had a 36.9% lower risk of MCR (OR 0.631[0.502,0.793]). Mediation analysis showed that gait speed significantly mediated the association between PA and MCR. Cox regression further demonstrated that both TPA and healthy PA were significantly related to a lower risk of MCR. RCS analysis identified a nonlinear relationship between TPA and MCR risk, with the lowest risk observed at 86.1 METs. Sensitivity analyses across different age groups confirmed the robustness of these findings.
CONCLUSION: Higher levels of TPA and healthy PA are negatively associated with MCR, underscoring the importance of maintaining adequate PA in older adults.