ArticleBMC public health2025
Comparison of the cumulative exposure to four measures of blood pressure for predicting cardiovascular disease risk in the Chinese Uyghurs.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Longitudinal changes and cumulative exposure of estimated glucose disposal rate and all-cause mortality in middle-aged and older Chinese adults.Scientific reports · 2026Article
- Optimal Surgical Timing and Outcome Prediction in Hemorrhagic Moyamoya Disease: A Retrospective Cohort Study.CNS neuroscience & therapeutics · 2026Article
- Association between cumulative metabolic score for visceral fat and cardiovascular disease risk in cardiovascular-kidney-metabolic syndrome stage 0-3 patients: a prospective cohort analysis based on CHARLS database.BMC cardiovascular disorders · 2026Article
- Machine learning and SHAP values for predicting coronary artery disease risk in Xinjiang, China.European journal of medical research · 2026Article
- Blood pressure indices for predicting incident cardiovascular disease: A 13-year follow-up study in Japanese population.American journal of preventive cardiology · 2025Article
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11 authors.
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Abstract
objectiveThis study aimed to explore and compare the role of cumulative exposure to four blood pressure (BP) markers [systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure (PP)] in predicting cardiovascular disease (CVD) risk in the Uyghur population.
methodsWe recruited 3,553 Uyghurs from Tumxuk City, and conducted blood pressure measurements on them at least three times, with a minimum interval of two years between consecutive measurements. Cumulative BP was defined as the sum of the product of the average BP between consecutive examinations and the time interval between visits. Cox proportional hazard models and restricted cubic spline (RCS) analysis were used to estimate the association between cumBP and CVD risk. The incremental predictive value of cumBP was further assessed using the net reclassification index (NRI) and integrated discrimination improvement (IDI).
resultsOver a median follow-up of 6.29 years, 383 (10.78%) incidents of CVD occurred. All four cumBP markers were associated with CVD risk, with cumulative SBP (cumSBP) and cumulative PP (cumPP) showing the strongest associations. For each 1-SD increase in cumSBP and cumPP, the CVD risk increased by 31% [HR (95% CI): 1.310 (1.153, 1.489)] and 28% [HR (95% CI): 1.284 (1.132, 1.457)], respectively. Additionally, 1-SD values corresponded to 107.90 mmHg·years for cumSBP and 65.33 mmHg·years for cumPP. RCS analysis showed a linear relationship between cumBP and CVD risk. CumSBP provided the best incremental predictive value for CVD after adding cumSBP to the conventional model, improving the NRI by 0.126 (P = 0.019) and the IDI by 0.009 (P = 0.001). Although cumulative MAP and cumulative PP also improved the predictive capabilities to varying degrees, the effect sizes were smaller than those of cumSBP.
conclusionAll four cumBP markers were significantly associated with CVD risk in this population. Compared with the other three cumBP measures, cumSBP had the strongest association with CVD events and provided a superior incremental predictive value for CVD events.
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