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Physical Activity Recommendations Tailored by a Predictive Model for Adults With High Blood Pressure: Observational
Yuhui Yang1, Manqing Chen1, Weiwei Hu1
1Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta Xilu Road, Xi'an, Shaanxi, 710061, China, 86 13772075793.
Journal of Medical Internet Research
|January 9, 2026
Summary
Personalized physical activity (PA) patterns can significantly impact mortality risk in adults with high blood pressure (BP). Tailoring PA based on individual characteristics improves prognosis and reduces all-cause mortality risk.
Area of Science:
- Cardiovascular Health
- Exercise Physiology
- Biostatistics
Background:
- The benefits of physical activity (PA) for adults with high blood pressure (BP) may vary based on individual characteristics, an area requiring further investigation.
- Understanding this heterogeneity is crucial for optimizing health outcomes in hypertensive populations.
Purpose of the Study:
- To investigate how individual characteristics modify the association between physical activity (PA) patterns and mortality.
- To develop and validate a predictive model for optimal PA patterns tailored to individual patient profiles.
Main Methods:
- Four distinct PA patterns (active weekend warrior, active regular, active light PA, baseline PA) were defined using accelerometer data.
- A machine learning model was trained in the UK Biobank (UKB) cohort and validated in the National Health and Nutrition Examination Survey (NHANES) cohort to predict optimal PA patterns.
- Multivariable Cox models assessed the association between current PA patterns and all-cause mortality compared to predicted optimal patterns.
Main Results:
- The predictive model demonstrated strong performance with an area under the receiver operating characteristic curve of 86.4% for 10-year mortality prediction.
- Key factors influencing optimal PA patterns included stroke history, age, sex, BP class, and antihypertension medication.
- Inconsistency between current and predicted optimal PA patterns was associated with a 28% increased risk of all-cause mortality in the UKB cohort.
Conclusions:
- Individual characteristics significantly influence the optimal physical activity (PA) patterns for adults with high blood pressure (BP).
- The developed predictive model and web application can aid clinicians in providing personalized PA recommendations.
- Tailored PA strategies based on individual profiles hold the potential to improve prognosis and reduce mortality in hypertensive patients.
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