Robust inference for skewed data in health sciences

Nandy, Amarnath; Basu, Ayanendranath; Ghosh, Abhik

doi:10.1080/02664763.2021.1891527

Cited by 5 publications

(1 citation statement)

References 51 publications

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“…Study derived covariates included total days of measurement, mean systolic blood pressure, and total sleep duration. To improve model fit, we transformed BPV, sleep interruptions, step count, age, and body mass index into tertiles due to right skew (Fig 2 ), which is common with physiologic and health science data [17][18][19][20].…”

Section: Study Outcome Exposure and Covariatesmentioning

confidence: 99%

Impact of sleep quality and physical activity on blood pressure variability

de Havenon,

Falcone,

Rivier

et al. 2024

PLoS ONE

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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.

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Section: Study Outcome Exposure and Covariatesmentioning

confidence: 99%