Getting up for brain health: association of sedentary behavior breaks with cognition and mental health in children

doi:10.21203/rs.3.rs-3760396/v1

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Getting up for brain health: association of sedentary behavior breaks with cognition and mental health in children

https://doi.org/10.21203/rs.3.rs-3760396/v1

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Aim

to verify the role of body mass index (BMI), cardiorespiratory fitness (CRF), and moderate to vigorous physical activity (MVPA) in the relationship between the break in sedentary time with cognitive and mental health in children.

Methods

Cross-sectional study with 129 children (62 boys), aged between six and 11 years (mean 8.73 ± 1.53) from a public school in southern Brazil. For the assessment of fluid intelligence, psychologists applied Raven's Colored Progressive Matrices test. Mental health was measured using the Strengths and Difficulties Questionnaire. Sedentary breaks were measured using accelerometers and CRF was determined by the 6-minute walk test. Generalized linear regression analyses were used to verify associations of sedentary breaks with fluid intelligence and mental health, according to children's BMI, CRF, and MVPA. All models were adjusted for sex, age, somatic maturation, and total time of accelerometer use.

Results

Our results indicated that sedentary breaks were associated with fluid intelligence in overweight/obese (β = 0.108; p = 0.021) and physically inactive children (β = 0.083; p = 0.010). Regarding mental health, no association was identified with sedentary breaks.

Conclusion

Sedentary breaks should be encouraged for the benefits of fluid intelligence, especially in children who do not meet physical activity recommendations and present overweight.

cognition

sedentary living

children

fitness

Children spend most of their waking time sedentary (56%) [1], and spent up to half of the after-school period in sedentary behaviors [2]. They are characterized by low energy expenditures while in a sitting or lying position [3]. This increase has been linked to increases in the quality and availability of technologies for entertainment, education, and socialization [4]. Available literature suggests that long periods of uninterrupted sedentary behaviors have been linked to adverse health outcomes in children [5–8]. Thus, recommendations have been published by government and public health agencies suggesting that they should be limited in this population. Despite the guidelines and policies promoting limited time spent on sedentary behaviors, it has been suggested that, only between 10 and 15% of Brazilian boys and less than 5% of Brazilian girls meet to the benchmark of these guidelines (≤ 2h/day of recreational screen time) [9, 10]. Considering that lowering sedentary behavior among youth has been challenging, other strategies, such as interrupting prolonged bouts of sedentary behaviors with active breaks may provide health benefits [11]. However, there is lack of evidence on the relation between sedentary behaviour break, characterized by a non-sedentary period between two sedentary sessions., cognitive and brain health [12].

A number of mechanisms have been proposed to explain the link between sedentary behaviours and health outcomes, including cognitive and mental health. A widely explored mechanism is the displacement of time, which means that more time in sedentary behaviours imply in a decrease in competing behaviours such as physical activity of different intensities and sleep [13, 14]. Physical activity has been linked to several health benefits, including metabolic, cognitive, and mental health [15, 16]. In this case, breaking sedentary behaviours even with light physical activity would already provide some benefits. A mechanism includes physiological and social responses to interrupting sedentary behaviours, but evidence to back them is lacking [17, 18]. This supports the results of several studies that observed associations between sedentary time with cognitive and mental health outcomes [19], yet, few have investigated indicators of sedentary behaviour breaks. Emerging evidence has linked breaks in sedentary behaviour with improved cognitive function and academic achievement among children [18, 20], however, it is unclear if breaks are also associated to mental health.

Mental and cognitive health are both multifactorial, being influenced by several individual characteristics and behaviours that have also been linked to sedentary behaviour. More specifically, studies showed that body mass index (BMI), cardiorespiratory fitness (CRF), and moderate to vigorous physical activity (MVPA) have a role in the relationships with cognition function, and mental health [21–24]. Unsurprisingly, they have all been linked to sedentary behaviours as well [25, 26], suggesting that they could play a moderator role in the relationship between sedentary behaviour breaks and mental and cognitive health. However, this should be further explored.

Considering that sedentary behaviours are widespread among children and that lowering its levels has been challenging to policymakers, practitioners, and researchers, investigating the relation of sedentary behaviour breaks in improving cognitive and mental health is relevant for public health promotion, as breaking prolonged periods of sedentary behaviour might be easier than lowering its total habitual volumes. Furthermore, considering that mental and cognitive health can vary according to BMI, CRF, and MVPA, elucidating the role of these variables in relation to sedentary behaviour breaks is desirable. In this sense, the aim of the present study was to verify the role of BMI, CRF and MVPA on the relationship between the total break in sedentary time with cognitive and mental health in children.

Study design

This study was developed with the baseline evaluation of the longitudinal soccer intervention project on different health-related outcomes, which took place between March and June 2017. The sample was selected by convenience and included 129 children (62 boys), aged between six and 11 years (mean 8.73 ± 1.53) from a public school in Southern Brazil. Written consent was obtained from the school principal, parents, and children prior to the beginning of the project. This study was approved by the Ethics and Research Committee of the Federal University of Rio Grande do Sul (2014997).

General measurements procedures

The measurements were carried out at the school by trained researchers and collaborators psychologists (partnership made with the psychology department of the Federal University of Rio Grande do Sul). Initially, a meeting was held at the school with parents to explain the project's objectives and its phases. On that occasion, the parents answered questionnaires, including the one on mental health and sociodemographic data. For those who were unable to attend, individual meetings were arranged. The second step was to collect anthropometric measurements and physical fitness at school during a period of classes. Besides, physical activity and sedentary behavior were obtained by accelerometers that were placed by researchers in the school. Finally, psychologists performed the assessment of fluid intelligence.

Cognitive health

Fluid intelligence was measured as an indicator of cognitive health. Fluid intelligence, is a measure of non-verbal intelligence, evaluated using the Raven's Colored Progressive Matrix Test [27]. This test consists of three series of 12 items, arranged in ascending order of difficulty. The items show an incomplete drawing or matrix, in which the child must choose the correct missing part out of six options. This test was conducted by trained psychologists, with small groups of children in a classroom, during class time. Each session lasted around 60 minutes. The points vary between zero and 36. The higher the score, the better.

Mental health

The Strengths and Difficulties Questionnaire (SDQ) was used to evaluate mental health, which consists of a tool for the behavioral screening of children aged 3 to 12 years. In the present study, the parents/guardians’ version was used [28]. It contains 25 items on which parents/guardians should consider the children's last six months to indicate "True", "More or Less True" and "False" for each item. The questions generate scores according to responses and for the analysis, the sum of all questions was recorded, except for questions related to prosocial behavior (as this is the only positive behavior). The score considers an interval from zero to 40 points, in which the higher the score, the higher the risk.

Body mass index

Weight was evaluated with a digital anthropometric balance with a precision of 0.5 kg with a maximum weight of 150 kg. Height was measured with the metric tape fixed on the wall and extended from the bottom upwards. The children should wear light clothing and be barefoot and was instructed to remain in the vertical position, with feet and trunk leaning against the wall. Both procedures followed the protocols suggested by Projeto Esporte Brasil (PROESP-Br)[29]. Then, the BMI was calculated by dividing body mass (in kilograms) by height (in square meters) and classified as normal weight and overweight/obesity, according to Conde and Monteiro [30].

MVPA and breaks

MVPA and total breaks in sedentary time were measured using Actigraph wActiSleep-BT accelerometers (ActiGraph Corp., Pensacola, FL, USA). The accelerometer was placed on the child's waist in the midaxillary line on the right side, in an elastic belt. Participants were encouraged to use it for seven consecutive days. Researchers instructed the participants on how to wear the accelerometers, and to wear it during waking hours and only remove it when performing water-based activities such as swimming or showering. The minimum amount of accelerometer data that was acceptable for analysis purposes was four days (including at least one weekend day), with at least 10 hours/day of usage time. Actilife software (version 5.6) was used to initialize, download, and analyze accelerometer data, which were collected at a sampling rate of 80 Hz, downloaded in one-second epochs, and aggregated to 15-second epochs. We used the cut-off points proposed by Evenson[31] for periods of 15 seconds to classify physical activity variables (574–1002 counts/15 seconds to moderate physical activity; ≥1003 counts/15 seconds to vigorous physical activity). For the child to be classified as active, they should practice on average at least 60 minutes of moderate to vigorous physical activity per day. The total breaks in sedentary time per day were calculated by the Actilife software (i.e., total sedentary breaks - number of periods between sedentary bouts). For this, the time between the start of one sedentary bout and the end of the previous bout was considered.

Cardiorespiratory fitness

CRF was assessed using a six-minute walk/run test [29]. Children had to perform as many laps as possible, running or walking, in a multi-sport court with a perimeter demarcated with cones and a floor with meter indication. The evaluator announced the passage of time within 3 and 5 minutes of the test. Finally, the number of laps successfully completed, plus the additional distance achieved in children who failed to perform a complete lap at the end of the test were added. The CRF was obtained by multiplying the number of laps by the meters covered. To classify as fit and unfit, the 75th percentile was considered.

Covariates

The literature indicates that somatic maturation, sex, and age are aspects that influence the variables considered in this study (mental health, fluid intelligence, CRF, MVPA, BMI) [32].

Somatic maturation was assessed using anthropometric variables (height, weight, height of the brainstem, and length of the lower limbs). Equations for each sex were used [33] to determine the number of years predicted for each individual to reach their peak growth velocity, which may be negative (before reaching peak growth velocity) or positive (after reaching peak growth velocity).

Statistical analysis

Descriptive data are presented as means, standard deviations, and frequencies. Continuous variables were checked for normality. Two-tailed independent Student’s t-tests and Pearson chi-square tests were used to examine the differences according to sex.

Generalized linear regression analyses were used to verify associations of total breaks in sedentary time with cognitive health and mental health according to children's BMI, CRF, and MVPA. All models were adjusted for sex, age, somatic maturation, and accelerometer wear-time. The software IBM SPSS, version 20.0 was used for all analyses, and the alpha was set at 0.05.

Multiple linear regression was used as a statistical test for post-hoc sample size calculation on G* Power 3.1 program (Heinrich- Heine-Universität), considering the following parameters: a significance level of α = 0.05, and effect size of 0.15. The number of predictors considered was seven, and the sample size of 125 children for fluid intelligence, and 98 children for mental health, and test power was (1-β) = 0.88, and (1-β) = 0.77, respectively.

Table 1 presents the characteristics of the sample. It was composed by 129 children, being mostly in the normal weight category, and were classified as physically active. Significant differences were observed between boys and girls for somatic maturation and CRF.

Table 1

Descriptive characteristics of the sample according to sex.
Characteristics of sample	Total (n = 129)		Boys (n = 62)		Girls (n = 67)
	N	Mean (SD)	N	Mean (SD)	N	Mean (SD)
Mental health (range points)	98	11.18 (5.77)	43	10.37 (5.76)	55	11.82 95.75)
Fluid intelligence (points)	125	25.66 (6.26)	60	25.78 (6.87)	65	25.54 (5.68)
Total breaks in sedentary time (number of times)	129	66.02 (21.75)	62	68.85 (24.48)	67	63.39 (18.69)
Total accelerometer usage (minutes)	129	6651.71 (844.41)	62	6598.78 (1080.06)	67	6700.68 (658.58)
Age (years)	129	8.73 (1.53)	62	8.76 (1.63)	67	8.70 (1.43)
Somatic maturation (years)	122	-6.36 (2.73)	56	-3.55 (1.09)	66	-8.75 (0.58)*
	N	%	N	%	N	%
BMI
Normal weight	77	62.1	37	64.9	40	59.7
Children with overweight/obesity	47	37.9	20	35.1	27	40.3
CRF
Fit (≥ 75th percentile)	28	23.9	18	35.3	10	15.2*
Unfit (< 75th percentile)	89	76.1	33	64.7	56	84.8
MVPA
Active (≥ 60min/day)	67	51.9	35	56.5	32	47.8
Inactive (< 60min/day)	62	48.1	27	43.5	35	52.2

BMI: body mass index; MVPA: moderate to vigorous physical activity; CRF: cardiorespiratory fitness (75th percentile); * denotes statistical differences between sex using the t-test for paired samples (p < 0.05).

Associations between total breaks in sedentary time and cognitive health according to BMI, CRF, and MVPA were presented in Table 2. The results suggest a positive association between total breaks in sedentary time with cognitive health in children with overweight/obesity and physically inactive children.

Table 2

Association between total break in sedentary time and cognitive health according to nutritional profile, cardiorespiratory fitness and moderate to vigorous physical activity.
	Fluid Intelligence
	β	95%CI	p	β	95%CI	p
	Normal weight			Children with overweight/obesity
Total break in sedentary time	-0.030	-0.017 0.076	0.218	0.108	0.017 0.199	0.021*
	High CRF			Low CRF
	0.071	-0.004 0.145	0.064	0.036	-0.019 0.090	0.199
	Active			Inactive
	0.0001	-0.064 0.063	0.996	0.083	0.020 0.147	0.010*
CRF: Cardiorespiratory fitness; CI: Confidence interval. All analyzes were adjusted for sex, age, somatic maturation, and total accelerometer usage. *Statistical significance p < 0.05

The association between total breaks in sedentary time and mental health in children is presented in Table 3. The results did not indicate a relationship in any of the categories.

Table 3

Association between total break in sedentary time and mental health according to nutritional profile, cardiorespiratory fitness and moderate to vigorous physical activity.
	Mental Health
	β	95%CI	p	β	95%CI	p
	Normal weight			Children with overweight/obesity
Total break in sedentary time	-0.025	-13.209 12.779	0.456	-0.108	-0.227 0.012	0.077
	High CRF			Low CRF
	-0.076	-0.189 0.037	0.186	-0.013	-0.086 0.059	0.716
	Active			Inactive
	-0.004	-0.081 0.073	0.922	-0.094	-0.202 -0.014	0.089

All analysis were adjusted for sex, age, somatic maturation, and total accelerometer usage. *Statistical significance p < 0.05

The present study aimed to verify the role of BMI, CRF and MVPA on the relationship between the total break in sedentary time with cognitive health and mental health in children. Our results indicate that total breaks in sedentary time was associated with cognitive health in overweight/obesity and physically inactive children. Furthermore, regarding mental health, no significant association was observed with total breaks in sedentary time. Despite these results, it is important to emphasize that the strength of associations found in cognitive health and mental health were similar. However, the calculation used to identify the test power of each of the variables showed a more pronounced fragility in mental health, which may interfere with statistical significance.

Evidence has emerged indicating that breaking long periods of sedentary behavior could bring health benefits [34, 35]. With regard to mental health, a study with adults showed a positive relationship between the number of breaks in sedentary behavior and mood [36]. In addition, Peiris et al., (2021) [37] developed an intervention with university students and reported significantly higher levels of alertness, concentration and pleasure in classes with breaks in movement. According to them, based on the effort-recovery model, it seems that the movement breaks allowed the fatigue of the mentally demanding task to be recovered and, therefore, there were improvements in concentration and alertness.

In the child population there are some studies investigating the influence of sedentary behavior on brain health [38–40]. However, we have approached the breaks in sedentary behavior that are a less studied behavior in childhood along with the role of lifestyle habits. In this context, an intervention at school indicated that cognitively engaged breaks are able to improve brain efficiency in the prefrontal cortex, the neural substrate of executive functions, as well as response inhibition in children aged between six and eight years [41]. Furthermore, our results showed associations of fluid intelligence with total breaks in sedentary behavior in children with overweight/obesity and physically inactive children. In this sense, studies indicate that breaks in sedentary behavior proved to be a protective factor for obesity outcomes [35, 42], in addition to being related to a greater number of steps and light physical activity [13].

Thus, these studies may assist in understanding the observed associations only for children with overweight/obesity and inactive. Indeed, breaks in sedentary behaviors can be really effective in specific groups, such as children with overweight/obesity and that do not achieve the recommendation of physical activity. This profile is associated with higher cardiometabolic risk, as well as impairments in mental health, and cognition [43, 44]. In this sense, our findings highlight that adopting breaks in sedentary behavior may promote benefits for children especially those presenting unfavorable conditions.

These benefits may be do to several altered physiologic aspects promoted by adopting breaks, once a long time spent in sedentary behavior may lead to insufficient brain glucose utilization due to altered postprandial hyperglycemia, altered cortical hypoxia, impaired arousal due to the insufficient release of brain-derived neurotrophic factor (BDNF), and interaction hormones such as cortisol. Due to these deficiencies, there may be an increase in reactive oxygen species and interleukins, which can promote increased fatigue and reduced synaptic plasticity and memory ([18]

Regarding the role of CRF, the observed results do not confirm our hypothesis that this important component of physical fitness could moderate the relationship between total time in sedentary behavior bouts and cognitive health. Indeed, the literature presents controversial results regarding this issue, once some studies showed associations between CRF with fluid intelligence[45] and mental health[46] and others indicate no associations among these variables [47]. These discrepancies may be due to the use of different instruments to measure CRF, and possibly the children do not achieve a level of CRF enough to exert positive influences in the analyzed variables.

This study brings new evidence in order to understand the role of BMI, CRF, and physical activity levels in the relationship between breaks in sedentary time and cognitive and mental health in children. Data regarding sedentary behavior and physical activity were evaluated by a gold standard measure, and two indicators of brain health were evaluated, fluid intelligence which is a cognitive component, while mental health has a psychological aspect. Another important factor is that we have approached different lifestyle behavior that could be changed through the development of interventions and strategies for health promotion.

However, some limitations must be considered. Our sample was selected by convenience, which implies care in interpreting the results. The interval time and intensity of the break were not considered. In addition, the CRF was evaluated through an indirect measure, although this evaluation is commonly used in many studies with children [48, 49]. Mental health was evaluated through a questionnaire answered by the parents which could underestimate the real profile of health. Finally, the physical activity recommendations were not developed based on accelerometry data. Despite this topic is under discussion, Poitras et al., (2016) [50]suggest that the recommendations may also be used with accelerometry data.

In conclusion, this study provides evidence that breaks in sedentary behavior are associated with better fluid intelligence in children with overweight/obesity and inactive. This points a direction for future interventions to promote brain health, once strategies to decrease sedentary behavior may be conducted also in limited settings or conditions, such as small places, including apartments and classrooms. It also highlights the importance of the results for the implementation of policies aimed at teachers and parents/caregivers to encourage children to interrupt long periods of sedentary behavior. Additionally, programs based on breaks in sedentary behavior may be more viable and effective in specific groups.

BDNF

brain-derived neurotrophic factor

BMI

body mass index

CRF

cardiorespiratory fitness

MVPA

moderate to vigorous physical activity

Statements and Declarations

Funding:

This work was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and the financial aid provided by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, National Council for Scientific and Technological Development) under number 401969/2016-9.

Competing Interests:

The authors report there are no competing interests to declare.

Author contributions

Conceptualization: Anelise Reis Gaya, Adroaldo Gaya, Camila Felin Fochesatto; Methodology: Anelise Reis Gaya, Adroaldo Gaya, Caroline Brand, Camila Felin Fochesatto; Formal analysis and investigation: Carlos Cristi-Montero, Bruno Galdino da Costa, Caroline Brand, Arieli Dias, Camila Felin Fochesatto; Writing - original draft preparation: Bruno Galdino da Costa, Caroline Brand, Arieli Dias, Camila Felin Fochesatto; Writing - review and editing: Carlos Cristi-Montero, Bruno Galdino da Costa, Anelise Reias Gaya, Adroaldo Gaya; Funding acquisition: Anelise Reis Gaya, Adroaldo Gaya, Caroline Brand, Camila Felin Fochesatto; Supervision: Anelise Reis Gaya, Carlos Cristi-Montero e Adroaldo Gaya.

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No competing interests reported.

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Getting up for brain health: association of sedentary behavior breaks with cognition and mental health in children

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Abstract

Aim

Methods

Results

Conclusion

Introduction

Methods

Study design

General measurements procedures

Cognitive health

Mental health

Body mass index

MVPA and breaks

Cardiorespiratory fitness

Covariates

Statistical analysis

Results

Discussion

Abbreviations

Declarations

References

Additional Declarations

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