Medical Physiology

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Browsing Medical Physiology by browse.metadata.advisor "Derman, Wayne"

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    Modeling changes in resting heart rate and its relationship to all-cause mortality in humans
    (Stellenbosch : Stellenbosch University, 2021-03) Ristow, Brandon Mark; Derman, Wayne; Heine, Martin; Nyabadza, Farai; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Biomedical Sciences: Medical Physiology.
    Background Resting heart rate (RHR) is an easily measurable proxy of cardiovascular and general health. Extensive cohort studies have indicated that a higher RHR among individuals, results in an increased risk of all-cause mortality. RHR has been found to change over time based on health and disease states, however it is still unknown whether a change in RHR will impact the relative risk of mortality and what lifestyle choices contribute the most to long term changes in RHR. Therefore, in this thesis we set out to I) understand the relative all-cause mortality risk associated with an increasing RHR over time; II) understand if a mechanism exists to standardise the way in which RHR is measured among studies; and III) model the daily changes in RHR using lifestyle proxies. Methods In chapter 2, a meta-analysis was performed to identify studies reporting the relative risk of all-cause mortality associated with long-term changes in RHR. These studies were required to have cohorts of adult humans with no known disease, RHR measurements taken at least one year apart, and follow-up for all-cause mortality over a minimum of one year. Relative risk of participants with increasing and decreasing RHR were compared to those with an unchanged RHR. Chapter 3 analyses a set of wearable device data from a representative cohort and determines the daily RHR as well as lifestyle proxies related to sleep and physical activity. Using these measures, daily changes in RHR were forecast under three different methods (population-level, grouped level and individual level) using generalized additive models created with the lifestyle proxies. Results In chapter 2, nine studies fulfilled the criteria for the meta-analysis, with a total of 108 625 participants. It was found that an increased RHR over time had a hazard ratio of 1.21 (95% CI 1.09-1.35, p<.01) compared to an unchanging RHR. When an unchanged RHR was compared to a decreased RHR over time, no significant results were found. The modeling of RHR at a population-level resulted in a best model accuracy of R2 = 0.039. When attempting to first cluster individuals into groups before creating multiple models, the best model accuracy was R2 = 0.114. When creating unique model’s for each individual, the best model’s had a mean accuracy of R2 = 0.426. It was found that a daily point measurement of RHR using heart rate values at the time of waking resulted in the best model accuracy. Conclusion A RHR that is increasing over time will lead to an increased risk of all-cause mortality, however it is uncertain what effect a decreasing RHR has on mortality risk. When attempting to understand the lifestyle mechanisms that influence changes in RHR, it is best to approach things from an individual level, as there exists a great deal of variability between people. While there is no known method for modeling next day RHR for all individuals, it is feasible for some.