visualization-intensity-levels-to-reduce-gap-between-self-reported

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Physical activity (PA) assessment needs tools that are inexpensive and easy to administer. Common questionnaires inquire time spent in light, moderate, ...

University Medicine Greifswald

DZHK (German Centre for Cardiovascular Research)

Measuring physical activity (PA) and sedentary time (ST) by self-report or device as well as assessing related health factors may alter those behaviors. Thus, in intervention trials assessments may bias intervention effects. The aim of our study was to examine whether leisure-time PA, transport-related PA, and overall ST measured via self-report vary after assessments and whether a brief tailored letter intervention has an additional effect.

The effect of mere measurement from a cardiovascular examination program on physical activity and sedentary time in an adult population.

The aim of this study was to conduct a comprehensive investigation of the association between different types of leisure-time sedentary behavior (watching television, using a computer, reading and socializing) and clustered cardiometabolic risk in apparently healthy adults aged 40 to 65 years.

A cross-sectional analysis of the associations between leisure-time sedentary behaviors and clustered cardiometabolic risk.

We aimed to identify patterns of sedentary behavior (SB) and examined whether cardiorespiratory fitness differs between classes with distinct patterns of SB. One hundred and seventy participants (57% women, mean age = 56.4 years) received accelerometry monitoring for 7 days. Prior to accelerometry assessment, cardiorespiratory fitness was assessed by peak oxygen uptake (VO ). VO was directly measured during a symptom-limited cardiopulmonary exercise testing on a cycle ergometer. Patterns in accelerometer data were classified based on time spent in SB per day using growth mixture modeling. Model-implied class-specific VO means were compared using adjusted equality test of means. Growth mixture modeling revealed four patterns of SB: "High, stable" (n = 120, M = 724.9 min/d), "Low, increase" (n = 14, M = 622.2 min/d), "Low, decrease" (n = 11, M = 540.2 min/d), and "High, decrease" (n = 25, M = 694.8 min/d). Persons in class "High, stable" had significantly lower VO values (M = 25.0 mL/kg/min, SD = 0.6) compared to persons in class "Low, increase" (M = 30.5 mL/kg/min, SD = 3.6; P = 0.001), in class "Low, decrease" (M = 30.1 mL/kg/min, SD = 5.0; P = 0.009), and in class "High, decrease" (M = 29.6 mL/kg/min, SD = 5.9; P = 0.032). No differences among the other classes were found. We identified four classes of individuals with distinct patterns of SB and showed that VO partially differs between classes. Especially, individuals with stable high SB levels throughout the week might be addressed in public health recommendations and interventions.

Antje Ullrich

Institute of Social Medicine and Prevention

University Medicine Greifswald

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Antje Ullrich

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Institute of Social Medicine and Prevention

University Medicine Greifswald

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Institute of Social Medicine and Prevention