Gender differences in the distribution of children’s physical activity: evidence from nine countries

(2023) 20:103 Kretschmer et al. Int J Behav Nutr Phys Act https://doi.org/10.1186/s12966-023-01496-0 International Journal of Behavioral Nutrition and Physical Activity Open Access RESEARCH Gender differences in the distribution of children’s physical activity: evidence from nine countries Luke Kretschmer1,2* , Gul Deniz Salali2, Lars Bo Andersen3, Pedro C. Hallal4, Kate Northstone5, Luís B. Sardinha6, Mark Dyble2, David Bann1 and International Children’s Accelerometry Database (ICAD) Collaborators Abstract Background Physical activity in childhood is thought to influences health and development. Previous studies have found that boys are typically more active than girls, yet the focus has largely been on differences in average levels or proportions above a threshold rather than the full distribution of activity across all intensities. We thus examined differences in the distribution of physical activity between girls and boys in a multi-national sample of children. Methods We used the harmonised International Children Accelerometry Database (ICAD), including waist-worn accelerometry data from 15,461 individuals (Boys: 48.3%) from 9 countries. Employing Generalised Additive Models of Location, Shape, and Scale (GAMLSS) we investigated gender differences in the distribution of individuals, including comparisons of variability (SD) and average physical activity levels (mean and median) and skewness. We conducted this analysis for each activity intensity (Sedentary, Light, and Moderate-to-Vigorous (MVPA)) and a summary measure (counts per minute (CPM)). Results Sizable gender differences in the distribution of activity were found for moderate to vigorous activity and counts per minute, with boys having higher average levels (38% higher mean volumes of MVPA, 20% higher CPM), yet substantially more between-person variability (30% higher standard deviation (SD) for MVPA, 17% higher SD for CPM); boys’ distributions were less positively skewed than girls. Conversely, there was little to no difference between girls and boys in the distribution of sedentary or light-intensity activity. Conclusions Inequality in activity between girls and boys was driven by MVPA. The higher mean volumes of MVPA in boys occurred alongside greater variability. This suggests a need to consider the underlying distribution of activity in future research; for example, interventions which target gender inequality in MVPA may inadvertently lead to increased inequality within girls. Keywords Physical activity, Childhood, Accelerometer, Gender, GAMLSS, ICAD, ALSPAC *Correspondence: Luke Kretschmer Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Kretschmer et al. Int J Behav Nutr Phys Act (2023) 20:103 Introduction Physical activity levels during childhood and adolescence have implications for health and development throughout the lifecourse [1]. Low levels of activity in childhood have been linked to a series of unfavourable outcomes: higher incidence of infectious [2] and chronic disease [3–8], poorer mental health outcomes [3, 9], lower cognitive function and school performance [9, 10], and delayed physical development [3, 7, 8, 10–15]. Gender is frequently observed to be a correlate of objectively measured physical activity in youth samples [16, 17], with boys on average typically undertaking more activity than girls, with the effect size relatively stable across ages [18–25]. Since childhood activity levels tend to track into later life [26], such differences may have lasting implications for gender disparities in subsequent health [27]. Understanding the distribution of individuals across all active behaviours could help to better understand causes of gender differences in activity profiles However, such an approach is underutilised [28]. Research to date has largely focussed on comparing summary measures of physical activity (frequently average counts [29, 30] or MVPA [1, 5, 8, 17, 19, 23]) with little research examining the distribution of activity across individuals. One identified paper investigated the Gini (an index of inequality for an outcome) of activity between countries, but did not examine gender [28]. Analysing the full distribution of activity across all intensities, drivers of differences between girls and boys may be better understood, furthering an understanding of whether differences are due to a whole population shift, or owes to a subset skewing the sample. To address this gap, the present research explores the full distribution of activity using Generalised Additive Models of Location Shape and Scale (GAMLSS) which allows for comparisons between medians, standard deviations and skewness in addition to the mean [31, 32]. This analysis is repeated for the mean intensity of activity and each intensity threshold. Given the observed differences between girls and boys in volumes of MVPA, similar differences in the mean should be observed here. If this difference emerges due to volitional activity, such as sport or active play with a larger subset of one gender undertaking such activities [33], it may result in that gender having a wider distribution of activity and more skew. For light-intensity activities, those that are constituent of ‘everyday’ activities, it may be that there is less of a difference between girls and boys, with limited difference in the deviation or skew. Page 2 of 10 Methods Sample The International Children’s Accelerometry Database (ICAD) was used in this analysis [34]. ICAD is a harmonised dataset of accelerometry data from a series of youth activity studies that employed waist-worn accelerometers in comparable means [34]. Data was harmonised by reprocessing the raw accelerometer data from each study with a consistent methodology [35]. Further, social and demographic information were recoded to a consistent reporting, with multiple harmonised variables created fo (...truncated)