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PP74 Cross-sectional analysis of weekly levels and patterns of objectively measured physical behaviour with cardiometabolic health in middle-aged adults
  1. CD Dillon1,
  2. DD Dahly2,
  3. AD Donnelly3,
  4. IP Perry1,
  5. KR Rennie4,
  6. XL Li2,
  7. CP Phillips1
  1. 1HRB Centre for Diet and Health Research, Department Epidemiology and Public Health, University College Cork, Cork, Ireland
  2. 2Department Epidemiology and Public Health, University College Cork, Cork, Ireland
  3. 3Centre for Physical Activity and Health Research, University of Limerick, Limerick, Ireland
  4. 4School of Life and Medical Sciences, University of Hertfordshire, Hatfield, UK

Abstract

Background Little is known how combined weekly patterns of physical activity and sedentary behaviour are associated with cardiometabolic health. The objective of this paper is to identify weekly patterns of physical activity and sedentary behaviour and to examine cardiometabolic health status associated with different activity patterns.

Methods Data are from a subsample of the Mitchelstown cohort; 475 (59.7 ± 5.5 years) middle-aged adults. Participants wore the wrist GENEActiv accelerometer for 7-consecutive days. Data was summarised into 60s epochs and each time interval categorised based on thresholds. Latent profile analysis (LPA) defined classes based on observed clustering of sedentary behaviour and physical activity variables while multivariate latent class regression was used to compare cardiometabolic health status across classes.

Results LPA revealed 4 distinct physical behaviour patterns; Sedentary Group (20.9%), moderate-to-vigorous physical activity (MVPA) and High-Sedentary Activity Group (40.9%), MVPA and High-Light Activity Group (24.7%) and a Physically Active Group (13.5%). Overall the Sedentary Group had poorer outcomes, characterised by high Body Mass Index, triglycerides, fasting plasma glucose and insulin levels, and low high density lipoprotein-cholesterol levels. The remaining classes were characterised by healthier cardiometabolic profiles as sedentary behaviour decreased.

Discussion The classification of groups of adults with similar physical behaviour patterns offers important information for the identification and tailoring of public health and health promotion messages and intervention strategies. These findings could help identify optimal patterns of physical behaviour that improves cardiometabolic health as health policy should be directed towards altering patterns of behaviour rather than concentrating on a single type of behaviour.

  • weekly patterns physical behaviour accelerometers

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