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. 2022 Sep 8;19(1):116.
doi: 10.1186/s12966-022-01296-y.

Systematic review of accelerometer-based methods for 24-h physical behavior assessment in young children (0-5 years old)

Annelinde Lettink  1   2   3 , Teatske M Altenburg  4   5   6 , Jelle Arts  4   6 , Vincent T van Hees  4   7 , Mai J M Chinapaw  4   5   6
Affiliations

Systematic review of accelerometer-based methods for 24-h physical behavior assessment in young children (0-5 years old)

Annelinde Lettink et al. Int J Behav Nutr Phys Act. .

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.

Keywords: 24-h physical behavior; Accelerometer; Cut-points; Infants; Machine learning; Measurement properties; Physical activity; Preschoolers; Reliability; Sedentary behavior; Sleep; Toddlers; Validity.

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Conflict of interest statement

Annelinde Lettink, Teatske M. Altenburg, Jelle Arts, Vincent T. van Hees, and Mai J. M. Chinapaw declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) flow diagram of study inclusion
See this image and copyright information in PMC

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