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Published on: July 17, 2020
More than step counts: Slow walking speed, limited running, and fewer long walks predict cardiovascular mortality in
Beatriz Herrero Pinilla1, Serena Hong2, Matthew A Brodie3
1Hospital Universitario Rey Juan Carlos, Madrid, Spain.
Insights
Real-world walking speed and duration are better predictors of cardiovascular death risk than step counts alone in older adults. Objective gait measures offer a non-invasive option for early risk assessment.
Area of Science:
- Gerontology
- Cardiovascular Health
- Biomedical Engineering
Background:
- Low daily step counts are linked to cardiovascular death risk.
- Objective real-world gait measures may offer superior prediction.
- This study investigates gait characteristics and cardiovascular mortality in older adults.
Purpose of the Study:
- To examine the relationship between real-world gait measures and cardiovascular death.
- To assess the predictive value of walking speed, quality, and bout distributions.
- To compare digital gait biomarkers with traditional cardiovascular risk scores.
Main Methods:
- Population-based observational cohort study of UK Biobank participants (aged 60-78).
- Gait data collected using wrist-worn devices and analyzed with Watch Walk methods.
- Cardiovascular death tracked via National Health Service databases; Cox proportional-hazard models used.
Main Results:
- Slower maximal walking speed, reduced daily running duration, and a higher proportion of short walks independently predicted cardiovascular death.
- A multivariable model incorporating these gait measures achieved a C-statistic of 0.75.
- This predictive accuracy was comparable to traditional risk scores like SCORE2 and Framingham Risk Score.
Conclusions:
- Real-world walking speed, running duration, and walk bout distribution are crucial for cardiovascular death risk assessment.
- Predictive models using these gait characteristics demonstrate significant accuracy.
- These digital gait biomarkers offer a promising non-invasive tool for early cardiovascular risk stratification.
Background:
Low daily step counts have traditionally been associated with cardiovascular death risk, suggesting other objective real-world gait measures may be complementary or better predictors. This study examined the relationship between real-world walking speed, quality, and walking bout distributions, measured using a wrist-worn device, and cardiovascular death in a large cohort of older people.
Methods:
Participants aged 60 to 78 years from the UK Biobank who wore a wrist-worn device were included in this population-based observational cohort study. Gait data were analyzed using Watch Walk methods. Cardiovascular death, defined as death within nine years of follow-up due to heart disease, stroke, or vascular conditions, was tracked using National Health Service databases. Minimally adjusted and multivariable Cox proportional-hazard models assessed the relationship between digital gait biomarkers and cardiovascular death.
Results:
Among 38 766 participants, 485 (1.3%) had cardiovascular deaths during follow-up. In minimally adjusted models, maximal walking speed, running duration, step count, longest walk duration, and the proportion of short walks were associated with cardiovascular death. In multivariable models adjusted for age, sex and smoking status, slower maximal walking speed, reduced daily running duration, and a higher proportion of short walks remained independent predictors. This model had a C-statistic of 0.75, comparable to traditional risk scores including SCORE2 and the Framingham Risk Score (both 0.74).
Conclusions:
Walking speed, running duration, and the proportion of longer walks are key real-world walking characteristics to consider when assessing cardiovascular death risk. Predictive models with these measures demonstrate good accuracy, suggesting a noninvasive option for early risk assessment.
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