key: cord-0287371-xpbha4ay
authors: Fung, H.; Yeo, B. T. T.; Chen, C.; Lo, J. C.; Chee, M. W. L.; Ong, J. L.
title: Adherence to 24h movement recommendations and health indicators in the ABCD study: Cross-sectional and longitudinal associations with cognition, psychosocial health, BMI and brain structure
date: 2022-03-24
journal: nan
DOI: 10.1101/2022.03.23.22272692
sha: f9cbe635a1c5bf8d083c6cebdbacfacbfbcf8605
doc_id: 287371
cord_uid: xpbha4ay

Adherence to 24h movement guidelines of [≥]60min of physical activity, [≤]2h of screen time, and 9-11h of sleep has been shown to benefit cognition, physical and psychosocial health in children aged 5-13y. However, these findings are largely based on cross-sectional studies or small samples. Here we utilize data from the Adolescent Brain Cognitive Development (ABCD) study of 10000+ children aged 9-11y to examine whether adherence to 24h movement guidelines benefit cognition, BMI, psychosocial health and brain morphometric measures at baseline (T1) and 2 years later (T2). After adjustment for sociodemographic confounders in multivariable linear mixed models, we observed better cognitive scores, fewer behavioural problems, lower adiposity levels and greater gray matter volumes in children who met both sleep and screen time recommendations compared to those who met none. Longitudinal follow up further supports these findings; participants who met both recommendations at T1 and T2 evidenced better outcome measures than those who met none, even after controlling for T1 measures. These findings support consideration of integrated rather than isolated movement recommendations across the day for better cognitive, physical, psychosocial and brain health.

Adequate sleep, regular physical activity, and limitation of sedentary behaviour (including screen time) are well-recognized determinants of healthy development in childhood and adolescence. [1] [2] [3] While often dealt with separately, these modifiable lifestyle factors lie on a continuum of interacting 'movement' behaviours. 4 For example, health benefits of regular levels of moderate-to-vigorous physical activity (MVPA) could be attenuated if a child engages in excessive screen time / sedentary behaviours and has inadequate sleep. 5 Recognizing this, the WHO 6 and several countries 4,7-9 are shifting away from separate recommendations and moving towards the adoption of 24h movement guidelines for overall health and wellbeing. Based on a set of systematic reviews [10] [11] [12] and guidelines first proposed by the Canadian task-force in 2016 (i.e. the Canadian 24-Hour Movement Guidelines for Children and Youth), 4 24h guidelines typically recommend at least 60min of MVPA per day, 2h or less recreational screen time per day, and 9-11h sleep per night for children aged 5-13y.

In support of these guidelines, recent studies have found positive associations between the number of recommendations met and overall health indicators in children and adolescents. 13 Participants who fulfilled more guideline components had lower adiposity levels, 14, 15 higher health-related quality of life, 16-18 better psychosocial 19 and mental health scores, 20,21 lower risk of depression, 22 and superior academic performance 23 as well as global cognition scores. 24 However, these findings are mostly derived from cross-sectional studies or relatively small samples.

Results have been equivocal, limited health indicators have been studied at a time, and the relationships between adherence to 24h movement guidelines and brain 4 structure during this critical developmental period have not been studied. To answer these questions, we utilized data from a large sample of 10,000+ children aged 9-11y from the Adolescent Brain and Cognitive Development (ABCD) study, to investigate associations between adherence to movement guidelines from 24h movement behaviour data (24h-MB) surveying sleep, screen time and physical activity behaviours, and four commonly surveyed health indicators measuring: 1) cognition; 2) psychosocial health; 3) body mass index (BMI) and 4) brain morphometric measures, both at baseline and 2 years later.

The ABCD Study (http://abcdstudy.org) is the largest longitudinal study on brain development and child health in the United States. It involves 22 nationally distributed research sites and aims to follow 11,878 children from pre-adolescence into early adulthood. Potential participants were identified through probability sampling of public and private elementary schools estimated to cover over 20% of eligible participants in the U.S. population. Additional procedures such as summer recruitment and referrals were adopted to recruit harder-to-reach populations such as home-schooled children to achieve a near-representative and diverse national sample. Informed consent, assent, and parental permission were obtained prior to all data collection. Further details on recruitment procedures, task design, data collection protocols, and neuroimage processing pipelines are described elsewhere. 25, 26 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 24, 2022. ;  https://doi.org/10.1101/2022.03.23.22272692 doi: medRxiv preprint 5 Analyses were conducted on data from the fourth annual release (http://dx.doi.org/10.15154/1523041). After excluding participants who did not provide sociodemographic information for age, sex, highest parental education, household income and race, 10574 and 9273 participants contributed data on 24h movement behaviours (24h-MB) for the baseline (T1) and 2-year follow up (T2) timepoints respectively (Table 1 ). For each of the outcome variables considered, a further number of participants had to be excluded due to missing data and quality checks (Supplementary Table 1 ). As only de-identified data were used, this study was exempted from a full review by the Institutional Review Board at the National University of Singapore.

Self and parental reports were used to extract the amount of time participants spent on each of the three movement behaviours (i.e. sleep, screen time and physical activity). These responses were then recoded as binary variables, with 1 indicating adherence, and 0 indicating non-adherence, to the 24h movement recommendations.

Participants were subsequently grouped into 8 categories of adherence to each combination of 24h-MBs to examine specificity of these MB categories to the different outcome variables investigated ( Figure 1 ).

Disturbance Scale for Children 27 that queried, "How many hours of sleep does your child get on most nights?". Parents selected one of five available options: 9-11h; 8-9h; 7-8h; 5-7h; and <5h. Children who received 9-11h of sleep were deemed to have met the 24h movement recommendations.

. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) ≥ 4h (coded as 4h). A weighted mean daily screen time was computed from the 12 values provided ([(total screen time on a weekday*5 + total screen time on a weekend*2)/7]). At T2, participants were asked to report total time spent on weekdays and weekends in these six categories combined, and a corresponding weighted value was computed using the 2 values provided ([(total screen time on a weekday*5 + total screen time on a weekend*2)/7]). Children who spent ≤ 2h on screens were deemed to have met screen time recommendations.

Time spent on physical activity was derived from the children's response to an item in the Youth Risk Behaviour Survey 29 that asked, "During the past 7 days, on how many days were you physically active for a total of at least 60 minutes per day? (Add up all the time you spent in any kind of physical activity that increased your heart rate and made you breathe hard some of the time)". Responses could vary between zero to seven days, and only those who indicated that they were active 7 days/week were considered to have met the activity recommendations. 7 

Cognition was assessed with the NIH Toolbox Cognition Battery that comprised seven tasks spanning six cognitive domains: attention, episodic memory, working memory, language, executive function, and processing speed. 30 

Parental reports of problem behaviours over the past 6 months were collected using the Child Behaviour Checklist (CBCL) for ages 6-18y. 31, 32 Composite scores summarizing internalizing problems (those directed towards 'self', e.g. from anxiety, depression and social withdrawal scales), externalizing problems (those directed towards 'others', e.g. from rule-breaking and aggressive behaviour scales) as well as an overall composite for total problems were extracted. Raw scores were converted to norm-referenced T-scores (M = 50, SD = 10), with higher scores indicating greater . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

Participants' height and weight were taken three times and averaged to obtain BMI scores using the formula weight (kg) / height (m 2 ). Extreme values of < 11 or > 36 kg/m2 were excluded as possible data entry errors/outliers (~1% of data).

Scanning parameters, pre-processing and analytical pipelines are described in separate papers. 26, 33 Structural brain images were processed using FreeSurfer 7.1.1 (https://surfer.nmr.mgh.harvard.edu) to obtain measures of estimated total intracranial volume (ICV), total cortical and subcortical gray matter volumes (GMVs).

Only participants whose structural data passed quality review checks by the ABCD Study team (imgincl_t1w_include==1) were included in the final analysis.

Cross-sectional analyses were conducted for both T1 and T2 separately.

Associations between adherence to each 24h-MB category (compared to a reference group meeting no recommendations) and outcome variables for cognition, psychosocial health, BMI and GMVs were investigated using multi-variable linear mixed effects models, controlled for age, sex, parental education, socioeconomic status and race. GMV models additionally controlled for ICV measures. As the ABCD study includes siblings, families nested within site were additionally modelled as a random effect. Unstandardized regression coefficients (b) are reported throughout . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted March 24, 2022. ; https://doi.org/10.1101/2022.03.23.22272692 doi: medRxiv preprint 9 the manuscript to show the difference between the mean of outcomes measured in each 24h-MB group to the mean of the reference group who did not meet any recommendations, keeping all other variables constant.

Next, longitudinal analyses were conducted to look at associations between changes from T1 to T2 (i.e. T2-T1) for each of the outcome variables considered, controlled for sociodemographic variables at T1 included in the cross-sectional analyses, outcomes at T1, and time elapsed between T1 and T2 assessments. Analyses were conducted first by comparing groups who met specific 24h-MB categories at both T1 and T2 with the group who did not meet any recommendations. As adherence to both sleep and screen time recommendations at both T1 and T2 most consistently showed favorable outcomes compared to the group who met no recommendations, we followed up this finding by also comparing groups who only met the sleep and screen time combination at either T1 or T2, compared to the rest of the sample.

p-values were corrected for multiple comparisons using the Benjamini-Hochberg procedure to control the False Discovery Rate (FDR) at 0.05. 34 This correction was carried out separately for T1 (9 outcomes x 7 24h-MB categories), T2 (8 outcomes x 7 24h-MB categories) and T2-T1 (8 outcomes x 7 24h-MB categories). Results are reported with and without this correction.

To follow-up on significant associations between adherence to each 24h-MB category and cortical GMV, we further inspected relationships by lobar region (frontal, . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All analyses were conducted using R version 4.1.0.

Sample characteristics of the 10574 children (M ± SD = 9.9 ± 0.6y, 52% male) and

9273 (M ± SD = 12.0 ± 0.7y, 52% male) who provided demographic and 24h-MB data at T1 and T2 respectively are provided in Table 1 . At T1, almost half of the sample (49%) met sleep guidelines of 9-11h/night, 35% met screen time guidelines of ≤ 2h/day, and only 17% met MVPA guidelines of ≥ 60min/day. Only 4% of participants met all three 24-h movement recommendations, while of concern, 31% did not meet any (Figure 1 ). At T2, the proportion of those who met sleep guidelines dropped to about a third (32%) of the sample, while the proportion meeting screen time (31%) and MVPA (16%) guidelines remained relatively stable. Notably, of the 9255 participants who provided 24h-MB data both at T1 and T2, only <1% met all three guidelines both at T1 and T2, while 20% did not meet any.

. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) 1 1

At T1, compared to participants who did not meet any recommendations, those who intelligence scores compared to those who did not meet any recommendations.

At T1, participants who met most combinations of 24h-MBs evidenced lower internalizing and total problems compared to participants who did not meet any recommendations ( Figure 2B ). However, participants who met activity only recommendations evidenced greater levels of externalizing problems (b = 0.97, p = 0.02, p FDR-corr = 0.04; Table 2 ). These associations were largely mirrored at T2, with the exception of those meeting sleep and activity and screen time only recommendations no longer evidencing lower levels of internalizing and total problems compared to the group who did not meet any recommendations.

. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) 1 2

At both T1 and T2, participants who met most combinations of 24h-MBs showed lower adiposity levels than those who did not meet any recommendations, with the exception of the group who only met activity recommendations at T2 (p = 0.36; Figure 2C ). 

When frequency of physical activity per week was coded as an interval variable (0 -7 days), non-linear relationships between frequency of physical activity per week and composite cognition, cortical GMV and externalizing behaviours were found (Supplementary Figure 3) whereby better health outcomes were associated with moderate levels of weekly physical activity.

. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) 1 4

In this study, we found that children aged 9-11y who both slept 9-11h and kept to 2h Considering psychosocial health scores, children who met combinations including sleep and screen time also tended to show fewer internalizing, externalizing and total . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) 1 5 problems scores compared to those who did not. Adequate sleep has been shown to be important for emotional regulation and mental wellbeing and has been linked to fewer behavioural problems in school-aged children, 10 and adequate levels of physical activity are known to regulate hormones related to growth, maturation and energy homeostasis, while insufficient levels could lead to energy imbalance and obesity 40 As higher BMI has been associated with poorer cognitive function across the lifespan 41 as well as a range of long-term health issues, 42 BMI levels need to be monitored throughout childhood and adolescence, and intervened appropriately.

Brain structural findings revealed that it was again the combination of sleep and screen time recommendations which consistently yielded greater GMVs compared to the group who met none, both cross-sectionally and longitudinally. Gray matter densities typically increase from birth before reaching a peak at around the onset of puberty, before declining throughout adolescence and early adulthood, [43] [44] [45] suggestive of pruning or reorganization for efficient neural processing. This could . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 24, 2022. ; 1 6 suggest premature GMV decreases in children who do not meet/consistently meet optimal movement recommendations. Post-hoc analyses show that these crosssectional differences tended to occur in the frontal and temporal regions -areas that mature later and could be most vulnerable to insults during this period, while longitudinal differences were more widespread across the brain. While prior neuroimaging work has focused separately on associations between 24h-MB components (e.g. sleep 20 or screen time 46, 47 ) and brain structure, these findings suggest that these movement behaviours need to be simultaneously targeted for better developmental outcomes.

Intriguingly, combinations with adherence to activity recommendations appeared to have either non-significant or even detrimental effects on some of the health indicators surveyed here (unless they were combined with adherence to both sleep and screen time recommendations). For cognition and GMV, this could seem contradictory to many cross-sectional studies which show a positive association between physical fitness and academic success, 48 likely through a facilitation of neuroplasticity on certain brain structures and consequently cognitive function. 49 Considering that this group also exhibited more externalizing problems at both T1 and T2, this could suggest a coping mechanism in children with behavioural disorders who are also more likely to be hyperactive, act out more and may also be more attracted to physical activity, or that their parents themselves encourage physical activity as a means to dealing with behavioural issues. 20 Children with higher symptom attention-deficit/hyperactivity-disorder severity have been shown to exhibit poorer cognition and smaller GMV in widespread regions. 50 In addition, posthoc analyses at T1 showed a beneficial relationship between meeting physical . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 24, 2022 

In conclusion, children aged 9-11y who met 24h movement recommendations of both sleep and screen time consistently demonstrated better cognition, psychosocial health, lower levels of adiposity and greater gray matter volumes than those who did not meet these recommendations. These associations persisted in longitudinal analyses conducted 2 years later suggesting the importance of maintaining these behaviours for overall health and wellbeing. Positive associations between moderate amounts of weekly physical activity and health outcome measures also suggest a need for further refinements into its optimal amount. . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) 1 9

This study was supported by grants from the National Medical Research Council, 

The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of the funders.

Data used in the preparation of this article were obtained from the Adolescent Brain

Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9-10 and follow them over 10 years into early adulthood. The 

The ABCD data repository grows and changes over time. The ABCD data used in this report came from the Curated Annual Release 4.0, also defined in NDA Study 1223 (doi:10.15154/1522595). All de-identified participant data are available upon request from the NIMH Data Archive (https://nda.nih.gov/abcd).

. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 24, 2022. ; https://doi.org/10.1101/2022.03.23.22272692 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Plots show unstandardized estimates of regression coefficients from multilevel models for baseline (T1; left panel) and follow-up (T2; right panel) timepoints respectively. Error bars indicate 95% confidence intervals while asterisks denote level of significance, uncorrected ('***' p< 0.001 '**' p < 0.01 '*' p< 0.05). Significant p-values (p<0.05) that survive multiple comparisons corrections are denoted in bold font, while those that do not are underlined. The gray reference line refers to the group who did not meet any recommendations. All models were controlled for age, sex, highest level of education (parent), race, household income and intracranial volume (GMV models only). Families nested within site were additionally modelled as a random effect. . Plots show unstandardized estimates of regression coefficients from multilevel models. The gray reference line refers to the group who did not meet any recommendations. Error bars indicate 95% confidence intervals while asterisks denote level of significance, uncorrected ('***' p< 0.001 '**' p < 0.01 '*' p< 0.05). Significant p-values (p<0.05) that survive multiple comparisons corrections are denoted in bold font, while those that do not are underlined. All models were controlled for age, sex, highest level of education (parent), race, household income, intracranial volume (GMV models only) as well as time elapsed between baseline and follow-up and baseline measures of all dependent variables. Families nested within site were additionally modelled as a random effect.

. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Cortical Subcortical . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted March 24, 2022. ; https://doi.org/10.1101/2022.03.23.22272692 doi: medRxiv preprint

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