Increased blood pressure variability (BPV) is linked to cardiovascular disease and mortality, yet few modifiable BPV risk factors are known. We aimed to assess the relationship between sleep quality ...and activity level on longitudinal BPV in a cohort of community-dwelling adults (age ≥18) from 17 countries. Using Withings home measurement devices, we examined sleep quality and physical activity over one year, operationalized as mean daily step count and number of sleep interruptions, both transformed into tertiles. The primary study outcome was high BPV, defined as the top tertile of systolic blood pressure standard deviation. Our cohort comprised 29,375 individuals (mean age = 58.6 years) with 127.8±90.1 mean days of measurements. After adjusting for age, gender, country, body mass index, measurement days, mean blood pressure, and total time in bed, the odds ratio of having high BPV for those in the top tertile of sleep interruptions (poor sleep) was 1.37 (95% CI, 1.28-1.47) and 1.44 (95% CI, 1.35-1.54) for those in the lowest tertile of step count (physically inactive). Combining these exposures revealed a significant excess relative risk of 0.20 (95% CI, 0.04-0.35, p = 0.012), confirming their super-additive effect. Comparing individuals with the worst exposure status (lowest step count and highest sleep interruptions, n = 2,690) to those with the most optimal status (highest step count and lowest sleep interruptions, n = 3,531) yielded an odds ratio of 2.01 (95% CI, 1.80-2.25) for high BPV. Our findings demonstrate that poor sleep quality and physical inactivity are associated with increased BPV both independently and super-additively.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract INTRODUCTION Dementia often involves comorbid Alzheimer's and vascular pathology, but their combined impact warrants additional study. METHODS We analyzed the Systolic Blood Pressure ...Intervention Trial and categorized white matter hyperintensity (WMH) volume into highest versus lowest/mid tertile and the amyloid beta (Aβ)42/40 ratio into lowest versus mid/highest ratio tertile. Using these binary variables, we created four exposure categories: (1) combined low risk, (2) Aβ risk, (3) WMH risk, and (4) combined high risk. RESULTS In the cohort of 467 participants (mean age 69.7 ± 7.1, 41.8% female, 31.9% nonwhite or Hispanic) during 4.8 years of follow‐up and across the four exposure categories the rates of cognitive impairment were 5.3%, 7.8%, 11.8%, and 22.6%. Compared to the combined low‐risk category, the adjusted hazard ratio for cognitive impairment was 4.12 (95% confidence interval, 1.71 to 9.94) in the combined high‐risk category. DISCUSSION This study emphasizes the potential impact of therapeutic approaches to dementia prevention that target both vascular and amyloid pathology. Highlights White matter hyperintensity (WMH) and plasma amyloid (Aβ42/40) are additive risk factors for the development of cognitive impairment in the SPRINT MIND trial. Individuals in the high‐risk categories of both WMH and Aβ42/40 had a near fivefold increase in risk of cognitive impairment during 4.8 years of follow‐up on average. These findings suggest that treatment strategies targeting both vascular health and amyloid burden warrant further research.
