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Systematic Review of Accelerometer-based Methods for 24-h Physical Behavior Assessment in Young Children (0-5 years Old)

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Abstract

Background: Accurate accelerometer-based methods are required for assessment of 24-h physical behavior in young children. We aimed to summarize evidence on measurement properties of accelerometer-based methods for assessing 24-h physical behavior in young children.

Methods: We searched PubMed (MEDLINE) up to June 2021 for studies evaluating reliability or validity of accelerometer-based methods for assessing physical activity (PA), sedentary behavior (SB), or sleep in 0-5-year-olds. Studies using a subjective comparison measure or an accelerometer-based device that did not directly output time series data were excluded. We developed a Checklist for Assessing the Methodological Quality of studies using Accelerometer-based Methods (CAMQAM) inspired by COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN).

Results: Sixty-two studies were included, examining conventional cut-point-based methods or multi-parameter methods. For infants (0-12 months), several multi-parameter methods proved valid for classifying SB and PA. From three months of age, methods were valid for identifying sleep. In toddlers (1-3 years), cut-points appeared valid for distinguishing SB and light PA (LPA) from moderate-to-vigorous PA (MVPA). One multi-parameter method distinguished toddler specific SB. For sleep, no studies were found in toddlers. In preschoolers (3-5 years), valid hip and wrist cut-points for assessing SB, LPA, MVPA, and wrist cut-points for sleep were identified. Several multi-parameter methods proved valid for identifying SB, LPA, and MVPA, and sleep. Despite promising results of multi-parameter methods, few models were open-source. While most studies used a single device or axis to measure physical behavior, more promising results were found when combining data derived from different sensor placements or multiple axes.

Conclusions: Up to age three, valid cut-points to assess 24-h physical behavior were lacking, while multi-parameter methods proved valid for distinguishing some waking behaviors. For preschoolers, valid cut-points and algorithms were identified for all physical behaviors. Overall, we recommend more high-quality studies evaluating 24-h accelerometer data from multiple sensor placements and axes for physical behavior assessment. Standardized protocols focusing on including well-defined physical behaviors in different settings representative for children's developmental stage are required. Using our CAMQAM checklist may further improve methodological study quality.

Prospero Registration Number: CRD42020184751.

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References
1.
Tremblay M, Carson V, Chaput J, Connor Gorber S, Dinh T, Duggan M . Canadian 24-Hour Movement Guidelines for Children and Youth: An Integration of Physical Activity, Sedentary Behaviour, and Sleep. Appl Physiol Nutr Metab. 2016; 41(6 Suppl 3):S311-27. DOI: 10.1139/apnm-2016-0151. View

2.
Hewitt L, Stanley R, Cliff D, Okely A . Objective measurement of tummy time in infants (0-6 months): A validation study. PLoS One. 2019; 14(2):e0210977. PMC: 6392225. DOI: 10.1371/journal.pone.0210977. View

3.
Hagenbuchner M, Cliff D, Trost S, Tuc N, Peoples G . Prediction of activity type in preschool children using machine learning techniques. J Sci Med Sport. 2014; 18(4):426-31. DOI: 10.1016/j.jsams.2014.06.003. View

4.
Klesges L, Klesges R . The assessment of children's physical activity: a comparison of methods. Med Sci Sports Exerc. 1987; 19(5):511-7. View

5.
Kuzik N, Poitras V, Tremblay M, Lee E, Hunter S, Carson V . Systematic review of the relationships between combinations of movement behaviours and health indicators in the early years (0-4 years). BMC Public Health. 2017; 17(Suppl 5):849. PMC: 5773877. DOI: 10.1186/s12889-017-4851-1. View