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Patterns of accelerometer-based sedentary behavior and their association with cardiorespiratory fitness in adults.

Antje UllrichSophie BaumannLisa VoigtUlrich JohnNeeltje van den BergMarcus DörrSabina Ulbricht
Published in: Scandinavian journal of medicine & science in sports (2018)
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 (VO2peak ). VO2peak 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 VO2peak 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 VO2peak 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 VO2peak partially differs between classes. Especially, individuals with stable high SB levels throughout the week might be addressed in public health recommendations and interventions.
Keyphrases
  • public health
  • physical activity
  • type diabetes
  • clinical trial
  • adipose tissue
  • big data
  • artificial intelligence
  • machine learning
  • metabolic syndrome
  • skeletal muscle
  • electronic health record
  • insulin resistance