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Comparison of Subjective and Objective Methods to Measure the Physical Activity of Non-Depressed Middle-Aged Healthy Subjects with Normal Cognitive Function and Mild Cognitive Impairment-A Cross-Sectional Study.

Aleksandra MakarewiczMałgorzata JamkaMaria Wasiewicz-GajdzisJoanna BajerskaAnna Miśkiewicz-ChotnickaJaroslaw KwiecienAleksandra LisowskaDominque GagnonKarl-Heinz HerzigEdyta MądryJaroslaw Walkowiak
Published in: International journal of environmental research and public health (2021)
This study compared subjective and objective methods of measuring different categories of physical activity in non-depressed middle-aged subjects with normal cognitive function (NCF) and mild cognitive impairment (MCI). In total, 75 participants (NCF: n = 48, MCI: n = 27) were recruited and physical activity was assessed for seven days using the ActiGraph and the International Physical Activity Questionnaire (IPAQ). Anthropometric parameters, body compositions, resting metabolic rate, and energy expenditure were also assessed. ActiGraph data indicated that subjects with NCF were more active than MCI subjects. A comparison of the IPAQ and the ActiGraph data revealed a significant correlation between these methods for total (r = 0.3315, p < 0.01) and moderate (r = 0.3896, p < 0.01) physical activity in the total population and moderate activity (r = 0.2893, p < 0.05) within the NCF group. No associations between these methods were found within the MCI group. Independent predictors of subjectively evaluated total physical activity were alcohol consumption (p = 0.0358) and socio-professional status (p = 0.0288), while weight (p = 0.0285) and the Montreal Cognitive Assessment results (p = 0.0309) were independent predictors of objectively measured physical activity. In conclusion, the long version of IPAQ is a more reliable tool to assess PA in subjects with NCF than those with MCI. More studies are needed to confirm this finding.
Keyphrases
  • physical activity
  • mild cognitive impairment
  • cognitive decline
  • body mass index
  • middle aged
  • sleep quality
  • alcohol consumption
  • big data
  • risk factors
  • deep learning