Associations of accelerometer measured school- and non-school based physical activity and sedentary time with body mass index: IPEN Adolescent study

Van Dyck, Delfien; Barnett, Anthony; Cerin, Ester; Conway, Terry L.; Esteban-Cornejo, Irene; Hinckson, Erica; Rubín, Lukáš; Rush, Elaine; Baron-Epel, Orna; Cain, Kelli L.; Christiansen, Lars Breum; Islam, Mohammed Zakiul; Mitáš, Josef; Molina-García, Javier; Oyeyemi, Adewale; Ranjani, Harish; Reis, Rodrigo; Santos, Maria Paula; Sit, Cindy; Timperio, Anna; Muda, Wan Abdul Manan Wan; Sallis, James F.

doi:10.1186/s12966-022-01324-x

International Journal of Behavioral Nutrition and Physical Activity

Table 4 Associations of MVPA and ST with WHO BMI-SD: full models including moderating effects

From: Associations of accelerometer measured school- and non-school based physical activity and sedentary time with body mass index: IPEN Adolescent study

Model 1: Total MVPA/ST			Model 2: School and non-school MVPA/ST
Regression term	b (95% CIs)	p-value	Regression term	b (95% CIs)	p-value
			MVPA during school (main effect)	-0.004 (-0.008, 0.001)	.154
			ST during school (main effect)	-0.002 (-0.003, -0.0004)	.010
City-specific effects of total MVPA			City-specific effects of non-school MVPA
Seattle, USA	-0.006 (-0.012, 0.001)	.091	Seattle, USA	-0.006 (-0.014, 0.002)	.139
Baltimore, USA	-0.009 (-0.015, -0.003)	.003	Baltimore, USA	-0.010 (-0.017, -0.002)	.009
Gombe, NGA	-0.015 (-0.021, -0.010)	< .001	Gombe, NGA	-0.017 (-0.024, -0.010)	< .001
Ghent, BEL	-0.006 (-0.017, 0.004)	.242	Ghent, BEL	-0.0002, (-0.014, 0.014)	.975
Valencia, ESP	0.004 (-0.002, 0.011)	.170	Valencia, ESP	0.006 (-0.001, 0.013)	.105
Porto region, PRT	0.002 (-0.008, 0.012)	.704	Porto region, PRT	0.003 (-0.009, 0.016)	.605
Olomouc, CZE	-0.008 (-0.021, 0.004)	.199	Olomouc, CZE	-0.009 (-0.023, 0.005)	.219
Hradec Králové, CZE	0.002 (-0.015, 0.020)	.786	Hradec Králové, CZE	0.004 (-0.016, 0.025)	.681
Odense, DNK	-0.003 (-0.015, 0.009)	.621	Odense, DNK	-0.002 (-0.018, 0.014	.804
Curitiba, BRA	-0.004 (-0.010, 0.001)	.106	Curitiba, BRA	-0.003 (-0.009, 0.004)	.430
Kuala Lumpur, MYS	0.010 (0.002, 0.019)	.016	Kuala Lumpur, MYS	0.015 (0.003, 0.026)	.014
Melbourne, AUS	-0.004 (-0.010, 0.003)	.247	Melbourne, AUS	-0.004 (-0.013, 0.005)	.394
Auckland, NZL	-0.001 (-0.007, 0.005)	.701	Auckland, NZL	-0.001 (-0.008, 0.006)	.815
Wellington, NZL	-0.006 (-0.014, 0.002)	.158	Wellington, NZL	-0.008 (-0.018, 0.002)	.100
Hong Kong, CHN	0.002 (-0.004, 0.008)	.532	Hong Kong, CHN	0.003 (-0.004, 0.011)	.400
Dhaka, BGD	-0.001 (-0.011, 0.010)	.886	Dhaka, BGD	-0.001 (-0.014, 0.012)	.879
Chennai, IND	-0.012 (-0.020, -0.003)	.007	Chennai, IND	-0.015 (-0.026, -0.004)	.009
Haifa, ISR	-0.001 (-0.010, 0.008)	.806	Haifa, ISR	0.001 (-0.010, 0.011)	.860
Accelerometer-comparability-specific effects of total ST			Accelerometer-comparability-specific effects of non-school ST
Not comparable accelerometers	0.001 (-0.001, 0.003)	.208	Not comparable accelerometers	0.002 (-0.0002, 0.004)	.087
Comparable accelerometers	-0.001 (-0.002, -0.001)	< .001	Comparable accelerometers	-0.001 (-0.002, 0.0003)	.140

Abbreviations: AUS Australia, BGD Bangladesh, BEL Belgium, BRA Brazil, CZE Czechia, DNK Denmark, CHN China, IND India, ISR Israel, MYS Malaysia, NZL New Zealand, NGA Nigeria, PRT Portugal, ESP Spain, USA United States of America, MVPA Moderate-to-vigorous physical activity, ST Sedentary time, BMI Body Mass Index, WHO World Health Organization, OR Odds ratio, CI Confidence interval. Estimates from generalized additive mixed models with random intercepts at the administrative-unit and school levels (pooled estimates from 10 imputed datasets). Models were adjusted for adolescent sex, age, city, area-level walkability and SES, valid days of accelerometer wear, average wear time per day and accelerometer comparability

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ISSN: 1479-5868

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