Abdou Y Omorou1, Joel Coste2, Hélène Escalon3, Anne Vuillemin1. 1. EA 4360 APEMAC, University of Lorraine, Paris Descartes University, Nancy 54505, France. 2. EA 4360 APEMAC, University of Lorraine, Paris Descartes University, Hôtel Dieu, Paris, France. 3. Institut National de Prévention et d'Education pour la Santé (INPES), Saint-Denis, Paris 93200, France.
Abstract
BACKGROUND: Few studies have focused on relating physical activity (PA) and sedentary behaviour (SB) to identify homogeneous groups. This study aimed to identify patterns of PA and SB in France general population and their correlates. METHODS: A sample of 3294 (mean age 44 ± 17 years) from the general population in France was included. PA and SB were assessed by the World Health Organization Global Physical Activity Questionnaire. Cluster analysis was used to identify PA and SB patterns, with polytomous logistic regression to identify their correlates. RESULTS: Five clusters were identified: (i) 'low total PA, active-transportation and low SB' (41%), (ii) 'low total PA and moderate SB' (22%), (iii) 'low total PA, leisure-time PA and high SB' (15%), (iv) 'high total PA, moderate occupational PA and moderate SB' (17%) and (v) 'high total PA, vigorous occupational PA and low SB' (5%). Occupational PA substantially contributed to total PA which depended on socioeconomic status (SES): low total PA and high SB in higher SES and high total PA and low SB in lower SES. CONCLUSIONS: Based on PA and SB, French adults were clustered into groups with socioeconomic differences emphasizing that adapted interventions may be more beneficial for health.
BACKGROUND: Few studies have focused on relating physical activity (PA) and sedentary behaviour (SB) to identify homogeneous groups. This study aimed to identify patterns of PA and SB in France general population and their correlates. METHODS: A sample of 3294 (mean age 44 ± 17 years) from the general population in France was included. PA and SB were assessed by the World Health Organization Global Physical Activity Questionnaire. Cluster analysis was used to identify PA and SB patterns, with polytomous logistic regression to identify their correlates. RESULTS: Five clusters were identified: (i) 'low total PA, active-transportation and low SB' (41%), (ii) 'low total PA and moderate SB' (22%), (iii) 'low total PA, leisure-time PA and high SB' (15%), (iv) 'high total PA, moderate occupational PA and moderate SB' (17%) and (v) 'high total PA, vigorous occupational PA and low SB' (5%). Occupational PA substantially contributed to total PA which depended on socioeconomic status (SES): low total PA and high SB in higher SES and high total PA and low SB in lower SES. CONCLUSIONS: Based on PA and SB, French adults were clustered into groups with socioeconomic differences emphasizing that adapted interventions may be more beneficial for health.
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