Acute Effects of Exercise on Blood Pressure: A Meta-Analytic Investigation

Abstract Hypertension affects 25% of the world's population and is considered a risk factor for cardiovascular disorders and other diseases. The aim of this study was to examine the evidence regarding the acute effect of exercise on blood pressure (BP) using meta-analytic measures. Sixty-five studies were compared using effect sizes (ES), and heterogeneity and Z tests to determine whether the ES were different from zero. The mean corrected global ES for exercise conditions were -0.56 (-4.80 mmHg) for systolic BP (sBP) and -0.44 (-3.19 mmHg) for diastolic BP (dBP; z ≠ 0 for all; p < 0.05). The reduction in BP was significant regardless of the participant's initial BP level, gender, physical activity level, antihypertensive drug intake, type of BP measurement, time of day in which the BP was measured, type of exercise performed, and exercise training program (p < 0.05 for all). ANOVA tests revealed that BP reductions were greater if participants were males, not receiving antihypertensive medication, physically active, and if the exercise performed was jogging. A significant inverse correlation was found between age and BP ES, body mass index (BMI) and sBP ES, duration of the exercise's session and sBP ES, and between the number of sets performed in the resistance exercise program and sBP ES (p < 0.05). Regardless of the characteristics of the participants and exercise, there was a reduction in BP in the hours following an exercise session. However, the hypotensive effect was greater when the exercise was performed as a preventive strategy in those physically active and without antihypertensive medication.

Modeling, evaluation and predicting of IT human resources performance

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Development of methodology for treating pressure waves from explosions accounting for modeling and data uncertainties

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012

Modeling the AppA/PpsR signal transduction system of rhodobacter sphaeroides

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2012

Mathematical modeling and evolution of signal transduction pathways and networks

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2013

Modeling the inelastic behavior of heat exchangers accounting for fluid-structure interactions

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

Modeling of micro- and nanostructures made of films and crystals/fibers arrays

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

Micro scale modeling grain boundary damage under creep conditions

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2014

Design, modeling and control of an autonomous field robot for white asparagus harvesting

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2014

Population balance modeling of influenza A virus replication in MDCK cells during vaccine production

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2015

Towards effective research-paper recommender systems and user modeling based on mind maps

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Dynamics in growth and metabolism of adherent MDCK cells unraveled by an integrated modeling approach

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Univ., Dissertation, 2015

Modeling usage of medical care services: the medical expenditure panel survey data, 1996-2000

We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required.

Likelihood-based approaches to modeling demand for medical care

We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.