The use of the intensity gradient and average acceleration metrics to explore associations with BMI z-score in children

Buchan, Duncan S.; McLellan, Gillian; Donnelly, Samantha; Arthur, Rosie

doi:10.1080/02640414.2019.1664536

Cited by 18 publications

(34 citation statements)

References 39 publications

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“…No significant associations were found between 24-h activity metrics and BMI z- scores in both children and adolescents. This is an unexpected finding, as other cross-sectional studies have shown a negative association of AvAcc and IG with BMI z -score [ 16 , 19 , 39 , 40 ]. A plausible explanation for this finding may be that BMI has low sensitivity in identifying individuals with excess adiposity, especially in youth [ 20 , 21 ].…”

Section: Discussionmentioning

confidence: 50%

Associations of novel 24-h accelerometer-derived metrics with adiposity in children and adolescents

Dygrýn

Medrano

Molina-García

et al. 2021

Environ Health Prev Med

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Background Further research is required to explore the associations between 24-h movement behaviours and health outcomes in the paediatric population. Therefore, this study aimed to examine the associations between novel data-driven 24-h activity metrics and adiposity among children and adolescents. Methods The sample included 382 children (8–13 years) and 338 adolescents (14–18 years). The average acceleration (AvAcc) of activity, intensity gradient (IG), and metrics representing the initial acceleration for the most active time periods of the 24-h cycle were calculated from raw acceleration data. Adiposity measures included body mass index z-score, fat mass percentage (FM%), and visceral adipose tissue (VAT). Data analysis was performed using multiple linear regression adjusted for wear time, sex, maternal education level, and maternal overweight and obesity. Results Children demonstrated higher values in all 24-h activity metrics than did adolescents (p < 0.001 for all). For children, the initial acceleration for the most active 2, 5, 15, and 30 min of the 24-h cycle were negatively associated with FM% (p ≤ 0.043 for all) and VAT (p <0.001 for all), respectively. For adolescents, the IG was negatively associated with FM% (p = 0.002) and VAT (p = 0.007). Moreover, initial acceleration for the most active 2, 5, 15, 30, 60, and 120 min were associated with FM% (p ≤ 0.007 for all) and with VAT (p ≤ 0.023 for all). Conclusions The intensity distribution of activity and initial acceleration for the most active 2, 5, 15, 30, 60, and 120 min within the 24-h cycle are beneficial for the prevention of excess adiposity in the paediatric population.

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Section: Discussionmentioning

confidence: 50%

Associations of novel 24-h accelerometer-derived metrics with adiposity in children and adolescents

Dygrýn

Medrano

Molina-García

et al. 2021

Environ Health Prev Med

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“…Consequently, the intensity gradient was not independently associated with conventional cut‐points, a finding in contrast with the previous literature. This lack of independence from MVPA might therefore limit the ability to explore the relative importance of physical activity volume and intensity in cardiovascular health 53 . S uch discrepancies might be partially due to the high volume of physical activity in which both populations engaged, which could mask the importance of intensity.…”

Section: Discussionmentioning

confidence: 99%

Association of physical activity metrics with indicators of cardiovascular function and control in children with and without type 1 diabetes

et al. 2020

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Objective Little is known about the role of physical activity accumulation in cardiovascular disease risk for children with type 1 diabetes. Improved insight to identify factors of influence in key health outcomes could be provided by considering the entire physical activity profile. Methods Pulse wave velocity (PWV), augmentation index and heart rate variability (HRV) were assessed cross‐sectionally in children with (n = 29, 12.1 ± 2.1 years) and without (n = 19, 12.1 ± 2.1 years) type 1 diabetes. Time spent sedentary and in each physical activity intensity, intensity gradient and average acceleration were derived from seven consecutive days of monitoring with wrist‐worn accelerometry. Comparison between groups and influence of physical activity accumulation on cardiovascular metrics were explored with linear mixed models. Results Diabetic children demonstrated a higher PWV and a greater volume of light physical activity (p < 0.01), a more negative intensity gradient (p < 0.01), a lower average acceleration and less time in bouted moderate‐to‐vigorous physical activity (MVPA; p < 0.05). Overall, intensity gradient was strongly correlated with average acceleration, MVPA and bouted MVPA (r2 = 0.89, r2 = 0.80, r2 = 0.79, respectively; all p < 0.05), while average acceleration was correlated with MVPA and bouted MVPA (r2 = 0.85, r2 = 0.83, respectively; p < 0.05). Accounting for disease status, intensity gradient and average acceleration were significant predictors of HRV indices (p < 0.05) and PWV (p < 0.01, p < 0.05, respectively). Conclusion Overall, MVPA was most associated with central stiffness, highlighting the importance of meeting activity guidelines. Diabetic children demonstrated poorer cardiovascular health than their counterparts, likely attributable to a lower intensity and physical activity volume, identifying physical activity intensity as a key target for future interventions.

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“…Direct measures of acceleration have been used to describe the physical activity profile and its association with health (e.g., Buchan et al, 2019;Fairclough et al, 2019;Rowlands et al, 2018a). For example, the average acceleration reflects the overall level of activity, the intensity gradient (Rowlands et al, 2018a) describes the distribution of acceleration intensity across the 24 h profile, and the MX metrics describe the intensity of the most active periods of the day (e.g., M30 for the most active 30 min) (Rowlands et al, 2019a(Rowlands et al, , 2019c.…”

Section: Introductionmentioning

confidence: 99%

Comparability of Postural and Physical Activity Metrics from Different Accelerometer Brands Worn on the Thigh: Data Harmonization Possibilities

Edwardson

Maylor

Dawkins

et al. 2021

Measurement in Physical Education and Exercise Science

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The aim was to establish which postural and physical activity outcomes are comparable across different accelerometer brands worn on the thigh when processed using open-source methods. Twenty participants wore four accelerometers (Axivity, ActiGraph, activPAL, GENEActiv) for three free-living days. Postural and physical activity outputs (average acceleration, intensity gradient, intensity of the most active 30 min, 60 min, and 8 h) were generated. Postural outputs: Mean absolute percent errors (MAPEs) were low, reliability excellent, and equivalency within the 5% zone across all monitor pairings for sitting/lying and upright times, but not specific lying postures. Physical activity outputs: MAPEs were higher and reliability lower than for sitting/lying and upright time. However, the majority of the outcomes were within the 10% equivalency zone for Axivity/ GENEActiv and Axivity/ActiGraph pairings. Total sitting/lying and upright times show strong potential for harmonization across studies utilizing different thigh-worn accelerometers. The majority of acceleration outcomes compare well for Axivity, GENEActiv, and ActiGraph.

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The use of the intensity gradient and average acceleration metrics to explore associations with BMI z-score in children

Abstract: R. (2019). The use of the intensity gradient and average acceleration metrics to explore associations with BMI z-score in children.

Cited by 18 publications

References 39 publications

Associations of novel 24-h accelerometer-derived metrics with adiposity in children and adolescents

Associations of novel 24-h accelerometer-derived metrics with adiposity in children and adolescents

Association of physical activity metrics with indicators of cardiovascular function and control in children with and without type 1 diabetes

Comparability of Postural and Physical Activity Metrics from Different Accelerometer Brands Worn on the Thigh: Data Harmonization Possibilities

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