Quality of Life, Sleep and Physical Activity in Swedish Children &amp; Adolescents

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Quality of Life, Sleep and Physical Activity

in Swedish Children & Adolescents

Muhammad Ishaq

Two-year master thesis 15 credits Supervisor Lilly Augustine Interventions in Childhood

Examinator: Will Farr Spring Semester 2020

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SCHOOL OF EDUCATION AND COMMUNICATION (HLK) Jönköping University

Master Thesis 15 credits Interventions in Childhood Spring Semester 2020

ABSTRACT

Author: Muhammad Ishaq

Quality of Life, Sleep and Physical Activity in Swedish Children & Adolescents Pages: 33

All humans desire to have a good quality of life i.e. living in relation to their goals, expectations, standards and concerns in life. The quality of life is related to healthy lifestyle, therefore, practicing health behavior is crucial for children and adolescents as the habits developed in early life persist in later life. However, in the contemporary world it has become quite a challenge to practice health behavior due to exposure to technology, electronic devices and social media which has adversely affected two important components of health behavior i.e. sleep and vigorous physical activity. This study aimed at investigating the impact of sleep duration during school days and vigorous physical activity during the week on quality of life. The data collected from 7700 students aged 11,13 & 15 from Swedish schools within the HSBC study in 2014. ANOVA, linear regression and mean comparison were used to test the hypotheses. The results show that age, gender, long-term disability and physical activity effects sleep duration of children and adolescents. Moreover, children and adolescents who sleep longer hours and do vigorous physical activities have a higher quality of life. Sleep duration have also been found to be associated with a higher quality of life.

Keywords: sleep, quality of life, vigorous physical activity, disability

Postal address Högskolan för lärande och kommunikation (HLK) Box 1026 551 11 JÖNKÖPING Street address Gjuterigatan 5 Telephone 036–101000 Fax 036162585

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1. Introduction

Quality of life (QoL) is “an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” (WHOQoL, 1993). QoL embodies several domains of life such as physical, social, emotional, and environmental, thus is regarded as a highly desirable outcome of child’s wellbeing (Davis et al., 2018). Quality of life has been used interchangeably for different terms such as life satisfaction, happiness, subjective well-being and positive mental health (Levin & Currie, 2014, p. 1048).

A high quality of life is strictly connected to a healthy lifestyle (Gochman, 1997, p. 3). Health is more than the absence of disease and disability rather it is "a state of complete physical, mental and social well-being” (W.H.O., 1995). Thus, a healthy lifestyle constitutes the behavior that leads towards maintenance, restoration and improvement in health (Gochman, 1997, p. 3). Health behaviour includes but is not restricted to good diet, sufficient sleep, physical activity, abstinence of smoking, limited use of alcohol and looking for health caregiver advice if needed (Short & Mollborn, 2015). This study primarily focuses on sleep and physical activity as determinants of high quality of life.

Adolescents sleep and exercise less nowadays. Society today forces us into a 24/7 lifestyle, and it has become difficult to have a healthy lifestyle i.e. health behavior (Woods & Scott, 2016). In particular, the amount of screen time among adolescents has increased dramatically over time, especially during night-time. As a consequence of going to bed later at night, the amount of hours of sleep per night has decreased among adolescents (LeBourgeois et al., 2017). Recent studies have shown that a poor sleep quality is associated with an increased risk of anxiety and depression (Woods & Scott, 2016). Extensive use of electronic devices and social media has also contributed to a higher level of sedentary behaviors among young people, which can have a negative impact on health, especially because of the association between low physical activity levels and obesity (Sheldrick, Tyler, Mackintosh, & Stratton, 2018). In turn, a poor sleep quality and low physical activity levels have a negative impact on quality of life, thus a negative impact on well-being (Engström, 2008; Inchley, 2013).

Though good sleep and vigorous physical activity are vital aspects of health behavior for all human beings, it is more crucial for children and adolescents. This is due to the growth of brain and body, and the establishment of lifestyle patterns that happen in childhood and

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adolescence., and impact on health related activities in later life (Engström, 2008; Inchley, 2013). There might also be other aspects affecting sleep such as disability. Children with disability are more prone to have sleep related issues owing to their disability (Didden, Korzilius, Aperlo, Overloop, & Vries, 2002; Phillips & Appleton, 2004; Wiggs & Stores, 1996). Also, for some it is more challenging to participate in physical activity due to their functional limitations (Ostrosky, Favazza, Yang, McLaughlin, & Stalega, 2018) which makes them more sedentary than typical developing children (Brian, Grenier, Lieberman, Egan, & Taunton, 2017). Having a disability might therefore lower the perception of quality of life.

A Spanish study on adolescents found a relation between insufficient night sleep on school days and that reduced the odds of participating in any leisure-time and physical sport (Ortega et al., 2010). Lang et al. (2013) found that subjective rather than objectively measured levels of physical activities were related to shorter perceived sleep onset. This was a small study of older adolescents and therefore subjectively measuring psychical activity and sleep pattern in a larger sample are needed. However a larger US study looking at obesity, soft drinks, sleep and screen time, found a relation between excessive screen time usage, more than 5 hours a day, inadequate sleep and physical activity (Kenney & Gortmaker, 2017). Looking more closely on Swedish data Ortega et al. (2011) compared Estonian children with Swedish children finding that Swedish children to a higher extent met sleep recommendations, however they did not find any relation between sleep durations and activity, and argue that physical activity cannot be seen as mediator between short sleep duration and obesity. Another small Swedish study using focus groups found that barriers for achieving good night’s sleep, were striving for a sense of well-being, tiring yourself out and regulating electronic media availability (Hedin et al., 2020). Indicating a link between sedentary screen time and sleep duration. More studies are needed to confirm the association between sleep quality and physical activity in children and adolescents, especially considering their potential influence on quality of life. It may also be beneficial to study how the hindrance in participation in health behaviour impacts the quality of life of the children with disability.

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2. Background/Previous research

2.1 Sleeping Habit of Children & Adolescents

Sleeping habits and sleeping patterns refer to the time of going to bed and waking up, and also include napping behaviour (Roenneberg et al., 2015). Norell-Clarke and Hagquist (2017) argue that good sleep is indispensable for a healthy life and crucial for a high quality of life. Recommended sleep duration for children and adolescents are age-specific, although recommendations have not always been based on empirical research (Matricciani, Olds, Blunden, Rigney, & Williams, 2012). According to evidence-based recommendations, 8-10 hours of sleep per night are appropriate for adolescents aged 14-17 years, whereas 9-11 hours are appropriate for children aged 6-13 years (Hirshkowitz et al., 2015).

Sufficient sleep and easy sleep onset (i.e. falling asleep without difficulties) contribute towards to a healthy life (Segura-Jiménez, Carbonell-Baeza, Keating, Ruiz, & Castro-Piñero, 2015). Sleep onset difficulties and an insufficient sleep duration are both associated to adverse health outcomes (Astill, Van der Heijden, Van IJzendoorn, & Van Someren, 2012; Owens & Group, 2014) such as depression, insomnia and anxiety (Baglioni et al., 2011; Woods & Scott, 2016). Anxiety and depression connected to a lower sleep duration can lead to more serious mental illnesses across the life course, as well as to a reduction in life satisfaction and quality of life (Testa & Simonson, 1996) and to a higher risk of premature death (Weitoft & Rosén, 2005) .

Several factors contribute to a shorter sleep duration. Löfstedt, Corell, Telander, Mörk, and Bergh (2014) argues that, although sleeping is controlled by homeostatic and chronobiologic mechanisms, it is also significantly affected by sociocultural, familial and developmental factors (Löfstedt et al., 2014). Woods and Scott (2016) note that an unhealthy use of technology and social media by young generation can lead to a poorer sleep quality. Increasing exposure to electronic devices before sleeping, can negatively affect sleep duration (Ekstedt, Nyberg, Ingre, Ekblom, & Marcus, 2013). Sleep habits of children and adolescents in contemporary society have considerably worsened compared to the past, with later sleep onset and a sleep duration below the recommended levels (Norell-Clarke & Hagquist, 2017).

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In Sweden, approximately 50% of 11-year old use computers for school homework for two to three hours per weekday (Garmy, Clausson, Nyberg, & Jakobsson, 2018), a trend that has been connected to decreasing sleep times for the children. Moreover, due to intensive use of social media, younger generations have developed the unhealthy habit of keeping their mobile phones on or under their pillow when they sleep (Lenhart, Ling, Campbell, & Purcell, 2010). Social media alerts exert pressure for online presence and are associated to an increased fear of missing out and fear of become isolated, in addition to decreasing sleep quality (Thomée, Dellve, Härenstam, & Hagberg, 2010).

Other factors can negatively impact sleep duration and quality. Among these, obesity has been shown to be associated with unhealthy sleeping habits in children above ten years (Merga & Williams, 2016). As there are no objective measures of BMI in HBSC, and many, especially younger children might have difficulties assessing their height and weight correctly, therefore this study does not include obesity as a factor to impact physical activity or sleep duration. Another factor related to sleep-related issues are disabilities (Didden et al., 2002; Phillips & Appleton, 2004; Wiggs & Stores, 1996). In particular, children with autism spectrum disorder have approximately 40-80 % higher risk of sleep-related issues such as insomnia, compared to non-autistic children (Cortesi, Giannotti, Ivanenko, & Johnson, 2010). The same has been observed among children with intellectual neurodevelopmental disabilities (Jan et al., 2008), ADHD (Konofal, Lecendreux, & Cortese, 2010) and asthma (Sadeh, Horowitz, Wolach-Benodis, & Wolach, 1998). Thus, children with disabilities are more vulnerable to sleep-related issues compared to typically developing children. However, in HBSC, it is not possible to differentiate between different disabilities, even though this might give a clearer picture.

Gender has also been found to affect both sleep onset and duration. A study conducted on 8274 children in Japan showed that boys suffer more due to short sleep duration (Sekine et al., 2002). Chen, Beydoun, and Wang (2008) had similar findings, however, Hitze et al. (2009) could not find any evidence or explanation for this in their study. According to a study by Ekstedt et al. (2013) which involved 1538 children living in the Stockholm County, girls reported earlier sleep onset and higher sleep duration compared to boys across all age groups investigated.

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2.2 Physical Activity of Children & Adolescents

Being physically active is vital for our wellbeing. Physical activity is a fundamental component of a healthy lifestyle (Bertills, Granlund, Dahlström, & Augustine, 2018) and is associated to a higher well-being. UN guidelines recommend at least one hour of moderate or vigorous physical activity daily. Examples of moderate physical activity include aerobic exercise, such as walking or biking, gardening, briskly pushing a baby stroller, climbing the stairs, playing soccer, or dancing. Examples of vigorous physically activity include instead all activities that makes one sweat and pant. Physical activity is not only beneficial for physical health (Hallal, Victora, Azevedo, & Wells, 2006) but also for mental health (Iannotti et al., 2009). Thus, this study makes an attempt to understand how Swedish adolescents participate in physical activities and if that is sufficient or in line with the recommended duration by W.H.O.

There is an increasing concern that the growing use of technology, both in schools and at home, will cause a reduction in physical activities. Students use computers for their work and vehicles for travel which reduces their occasions for being physically active (Bauman et al., 2012). This escalation in sedentary lifestyle among children is breading a generation that is progressively less active (McCurdy, Winterbottom, Mehta & Roberts, 2010). Especially in developed countries, children are avoiding basic physical exercises including playing, dancing and walking. Arguably less children ever engage in vigorous physical activities. Instead, children stay most of the time indoors, and when leaving the house, they use motor-vehicles instead of walking or cycling (Dumuid et al., 2017).

In Sweden, there is a decline in the time children and adolescents spend doing physical activities and spend more time in sedentary activities such as watching TV and using computers or the Internet (Löfstedt et al., 2014). This phenomenon is associated to the changes occurring in contemporary lifestyles in the general population. Lower physical activity levels during childhood can increase the risk of lifestyle-related diseases (such as cardiovascular disease) later in life (Wennberg, Gustafsson, Dunstan, Wennberg, & Hammarström, 2013). Therefore, it is important to promote physical activity during childhood to reduce potential health consequences during adulthood (Iannotti et al., 2009). The findings from this study will help in formulating strategies that foster physical activity participation of Swedish adolescents.

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Notably, girls tend to be less physically active and less involved in sports than boys (Marques, Ekelund, & Sardinha, 2016; Pereira et al., 2017). However, a subgroup of children that is at particularly high risk of sedentary behaviors is represented by children with disabilities, due to their limited access to physical activities as a consequence of their special needs (Ericsson, 2011). These children’s special needs can be directly connected to their physical (Capio, Sit, Eguia, Abernethy, & Masters, 2015; Sit et al., 2019) or intellectual disability (Stanish et al., 2019) (for instance the inability of walking, running or engaging with other children), or the consequence of diseases such as cerebral palsy (Verschuren, Peterson, Balemans, & Hurvitz, 2016) and sensory problems (Williams et al., 2018). Though the study has included disability as a variable to predict quality of life, it should be noted that HBSC study did not include data about the type of disability. Moreover, as the children had self-reported disability in the survey, it is likely that the data would depict only chronic illnesses such as diabetes, asthma, and allergies for which the children use medication. It will not cover developmental or intellectual disabilities, however, the reason to include this variable is to check whether long term chronic illness has an impact on physical activity or not.

2.3 Relationship between physical activity and sleeping habits

A high level of both sleep quality and physical activity is associated to a better physical, mental and psychosocial health (Bouchard, Blair, Haskell, & Haskell, 2007; Norell-Clarke & Hagquist, 2017). However, modern children are characterized by multiple unhealthy behaviors. In particular, they sleep an insufficient number of hours, they go to bed late at night, they engage in several sedentary activities, particularly screen time, and they have poor health habits (Dumuid et al., 2017; Garmy et al., 2018; Norell-Clarke & Hagquist, 2017). Ekstedt et al. (2013) found that the intensity of physical activity was higher in children who slept more than 9 hours per night, i.e. according to the recommendations. Interestingly, children who had a “catch-up-sleep” during weekends, tended to engage in fewer physical activities the day after (Ekstedt et al., 2013).

Research studies showed an association between physical activity levels and sleeping patterns. However, to date there is no consensus about the characteristics of this relationship. Based on their study on 2,241 Estonian and Swedish students, Ortega et al. (2011), could not find any association between sleep duration and physical activity levels. In a study that involved 856 Canadian students, Stone, Stevens, and Faulkner (2013) found

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instead a positive association between sleep duration and physical activity. The authors reported higher intensity of physical activity for those students who slept more than the minimum number of hours recommended per night (i.e. > 9 h). Those students who slept less than the recommended number of hours during school days and who tried to make up for their shortage of sleep during the weekend, were found comparatively less physically active. The studies mentioned above used either self-reported or parent-reported measures, thus the findings have limited reliability compared to objective measures.

In an earlier study Nixon et al. (2008) could not report any associations between physical activity and sleep duration. However, in a later study Nixon et al. (2009) reported that higher levels of physical activity were associated with shorter sleep latency. Pesonen et al. (2011) measured both sleep and daytime physical activity patterns for seven consecutive days in a cohort of 275 students aged eight and found a significant association between physical activities and sleep patterns. More specifically, a higher amount of physical activity during daytime resulted in poor sleep at night, and poor sleep resulted in less physical activity during the next day.

On the contrary, Ekstedt et al. (2013) found that an intensive physical activity during the day might promote a better sleep quality. Children who engaged in intense physical activities experienced interrupted sleep patterns, whereas children who were more involved in sedentary activities experienced a better sleep quality. However, Garmy et al. (2018) argue that an increased screen time can cause sleep problems and hyperactivity among children. Other factors such as children’s age, sex and social well-being can also significantly affect both sleeping habits and the level of physical activity (McCurdy et al., 2010). Older children have a lower sleep time and, as a result, they tend to undertake fewer physical activities (Ekstedt et al., 2013; Fleary, 2017).

According to Chahal, et al. (2013), a reduced sleep duration due to increased screen time at home is associated with lower physical activity levels in children. These findings are further supported by Merga (2015) who found that addiction to the internet significantly reduced the sleep onset duration and total sleep time. As a consequence, children were not able to engage in moderate-to-vigorous physical activities during the day (Ekstedt et al., 2013). Although in children there seems to be a relationships between sleeping habits and the level and intensity of physical activities during the day, it is difficult to detect a statistically-significant association between the above variables because of strong

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confounding effects by age, sex, socio-economic status, and lifestyle factors. The latter factors can also have significant effects on both physical activity levels and sleeping habits (Thorleifsdottir, Björnsson, Benediktsdottir, Gislason, & Kristbjarnarson, 2002).

For a higher quality of life, it is crucial for children and adolescents to adopt a healthy lifestyle such as good sleep and participation in vigorous physical activities from an earlier age, so that it persists in their older age as well. The lifestyle in contemporary society due to exposure to technology and social media does not contribute towards healthy lifestyle. In fact, it hinders a sufficient sleep duration and participation in vigorous physical activity, both of which are potentially associated with each other. Thus, the contemporary lifestyle makes children and adolescents vulnerable and children with disability even more vulnerable.

2.4 Aim

Sleeping and vigorous physical activity are two vital health behaviors, especially for adolescents. There are indications in previous research about reduced sleeping time (LeBourgeois et al., 2017) and more sedentary activities (Sheldrick et al., 2018). At the same time somatic issues are increasing in adolescents (Woods & Scott, 2016). As it has been established that two important aspects for health behaviour for adolescents are good sleep and vigorous physical activity. It is also evident that there is an increase in somatic issues and a decrease in physical activity of Swedish students aged 11, 13, and 15. The purpose of this study is to see how these two lifestyle habits, sleep and physical activity of Swedish students aged 11,13,15 years relate to their quality of life. The following hypotheses will be tested for students.

1. Does the amount of sleep during school days differ depending on age, gender and disability and the amount of vigorous physical activity?

2. Do children and adolescents who sleep the recommended amount of sleep on schooldays have a higher quality of life?

3. Do children and adolescents who have more vigorous activity have higher quality of life?

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3 Theoretical framework

3.1 System theory

According to the system theory, a system is a set of interrelated elements (Wachs, 2000). The human body is an example of a system consisting of interrelated elements, such as organs and tissues, for instance (Granlund, 2017). Failure of functioning of any of these elements, can results in troubles for the whole system, in this example, the whole human body. In order to understand a functioning and habits or recurring behavior of adolescents, it is important to understand that there are a series of transactions with distal antecedents (Sameroff & Fiese, 2000). For example, compared to older generations, there has been an increase in somatic issues observed among children and adolescents, especially among those characterized by reduced participation in vigorous physical activities, which can be a result of series of event having multiple factors contribute to this phenomenon.

Children and the environment where they live can influence each other in several ways (Must et al., 2015). Therefore, it is important to have a vertical analysis i.e. level of explanation that consider the bio- psycho-social interplay of interaction (Rönnberg, 2004). Vertical analysis can help to understand the relationships between several factors. As an example, how do developmental changes or disabilities (biologic components) interact with depression and anxiety (psychological components) and with social media use (social component) and how do these components relate to lifestyle habits.

One widely used model in vertical analysis is ICF-CY framework (W.H.O, 2007) supplemented by Bronfenbrenner ecological theory (Bronfenbrenner & Morris, 2006).

3.2 Bronfenbrenner ecological systems theory

“Human development takes place through processes of progressively more complex reciprocal interactions between an active evolving biopsychological human organism and the persons, objects and symbols in its immediate external environment” (Bronfenbrenner, 2005, p. 6). This theory mentions several interaction levels between children and a variety of systems in the environment where they live as well as in their everyday life. These systems can be classified into microsystem, mesosystem, exosystem, macrosystem and chronosystem. Microsystems refer to children’s interaction with their immediate environment, the latter consisting of the children’s biology, family, school and peers, among other factors. Mesosystems include the interactions between the actors in their

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mesosystem, for example, a family’s relationship with a child’s teachers or friends. Exosystem covers those elements which indirectly impact children such as, leave or vacation policies at their parent’s workplace, or parental commuting habits to the workplace. Finally, macrosystem refer to culture or national policies whereas chronosystem refers to what happens in the environment surrounding the child. Bronfenbrenner’s theory is useful to understand the environment where children and adolescents are experiencing their lifestyle habits.

Sleep is not just a homeostatic and chronobiologic mechanism, family, school (microsystems) but also the specific national environment including infrastructures for technology and affordability (macrosystem). Similarly, the vigorous physical activity is not only biological factors (microsystem) and culture (macrosystem) but also the trends and facilities of carrying out vigorous physical activities. The data in this study consists of sleeping habits and vigorous physical activity of Swedish children and adolescents.

Figure 2.1 Bronfenbrenner’s Ecological Model

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3.3 ICF-CY

ICF-CY is a multidimensional model and an internationally recognized tool to study a child’s functioning in his/her own specific context. This tool considers all aspects of a vertical bio-psycho-socio analysis. “The ICF-CY offers a conceptual framework and a common language and terminology for recording problems manifested in infancy, childhood and adolescence such as those involving functions and structures of the body, activity limitations and participation restrictions, as well as environmental factors are important for children and youth” (WHO, 2007).

ICF CY is divided into two main categories: functioning/disability and context. Biological aspects are covered under the category of functioning/disability which is related to body function and structure. It also covers psychological (activities) and social (participation) aspects. Contextual category mainly covers environmental factors. The context in ICF-CY consists of environmental and personal factors (Adolfsson, Malmqvist, Pless, & Granuld, 2011).

As noted earlier, sleep is a homeostatic and chronobiologic mechanisms (biological) and can be affected by sociocultural, familial and developmental changes (personal and environmental factors). Sleep-related issues can cause depression, insomnia, anxiety and have other biological & psychological consequences; therefore, it is quite relevant to use Bronfenbrenner’s theory and ICF-CY framework. ICF-CY can also be used to analyze/include participation in sedentary behavior due to technology and social media (social), since this is an environmental factor.

Vigorous physical activities are also related to physical ability to participate (activity) as well as the willingness and actual behavior (participation), and they can also be analyzed/included into the ICF-CY. Physical activity is not only consist of physical ability but also cognitive ability.

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Figure 2.2: ICF- CY Framework

Source: ICF-CY (W.H.O, 2007) / Adolfsson, Sjöman, and Björck-Åkesson (2018)

For this thesis, children and adolescents’ bodies are considered as systems, and their current habits are considered the results of series of transaction. A vertical analysis is made using Bronfenbrenner and ICF-CY integrated framework, which considers bio-psycho-social aspects of human bodies of the students for understanding lifestyle habits of sleep and vigorous physical activity.

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4 Methodological framework

4.1 Study Design

Swedish data from the HBSC study 2013/14 have been used. HBSC is a survey conducted across 43 countries every fourth year. The participating countries of HBSC have a national team of a research leader and number of researchers. In Sweden, research director at the Public Health Agency and the researchers at colleges and universities around the country formed the team, which also included overall coordination center and computer center, an international network that jointly developed, managed and disseminated the results of the survey. HBSC is "WHO Collaborative Study", therefore the World Health Organization (WHO) published international collection of reports.

4.2 Sampling Strategy

Since HBSC is aimed at collecting the data from the students aged 11,13 & 15, the sample consisted of the students from grade 5,7 & 9. The selection is made for each grade with a cluster design in two steps. Initially, a number of schools selected in a random way so that they are representative of the whole country. Subsequently the classes were randomly selected at each school. If there were more than one class in a specific grade, one of them was randomly selected. In response to a progressively declining response rate, selection criteria in 2013-14 were relaxed to recruit a minimum of 4500 participants (i.e. 1500 students per grade). A total of 7700 students participated in

4.3 Participants

The Swedish 2013/14 survey (table 4.1) describes age and prevalence of self-reported disability among study participants. A total of 1577 students (754 boys and 823 girls) had self-rated as having a disability.

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Table 4.2 Distribution of disability of participant, both overall and stratified by age.

Age Boys Girls

Disability No disability Disability No disability 11 years 271 1021 263 1020 13 years 223 868 251 877 15 years 260 1045 309 1056 Total 754 2934 823 2953 4.4 Instruments

Several items were used to collect all the information needed in the HBSC 2013/14 study, which are described below.

a) Background questions

Demographic information about gender, grade, month and year of birth and country of residence were collected by standardized questionnaires. The participating students belonged to 3 grades, i.e. 5th, 7th and 9th, and their years of birth were included from 1996 to 2005.

b) Sleep Duration during school days

Information about the time of going to bed and the wake-up time in the morning during school days was collected by a standardized questionnaire. For the time of going to bed, participants could choose among 11 alternative answers ranging from no later than 21:00 to later than 2:00. Similarly, the participants could choose among 7 alternative answers for waking up time during school days, ranging from no later than 05:00 to 08:00 or later. All alternatives within the above ranges were 30 minutes apart from each other. Sleep duration was calculated as the difference between the time of waking up and the time of going to bed. A dichotomous variable was created to distinguish between participants who slept the recommended number hours per night from those who did not.

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c) Vigorous physical activity duration

Vigorousphysical activity duration was self-reported. Participants were asked how many hours a week they worked out during their leisure time (i.e. outside school hours). In order to help them understand what distinguishes vigorous physical activity from other types of physical activities, participants were instructed to report only those activities that made them either get out of breath or sweat. Participants could choose between the following options: No vigorous physical activity, about 30 minutes/week, 1 hour/week, 2-3 hours/week, 4-6 hours/week & 7 hours/week or more.

d) Presence of disability

Participants were asked whether they had any chronic disease or disability diagnosed by an official diagnosis done by a doctor. Participants could reply either Yes or No.

e) Quality of Life (Life Satisfaction)

An adapted version of the Cantril ladder (Cantril, 1965), including the picture of a ladder, was used to collect data about general well-being and life satisfaction (Levin & Currie, 2014). The top of the ladder corresponds to the best life the students can imagine whereas the bottom of the ladder corresponds to the worst life they can imagine. Based on the above, participants could therefore rate their life satisfaction on a scale from 0 (worst possible life) to 10 (best possible life).

4.5 Validity & Reliability

“Validity is concerned with the integrity of the conclusions that are generated from a piece of research” (Bryman & Bell, 2015, p. 41). In this thesis all four types of validity such as statistical conclusion validity, internal validity, construct validity and external validity was assured which in result makes the study and conclusions reliable. However, it is worth noting that full validity is beyond the reach of the researcher.

In this thesis for statistical conclusion validity has been attempted through the relevant tests. For internal validity there are different aspects to consider. There was no such historical event (such as covid-19, war etc.) that could influence the behaviour of the children. The participants were not familiar with the survey instrument as there was not pre- test. The administration of the survey was uniform throughout Sweden. As the study

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was cross sectional there was no maturation of the student and its effect on their behaviour. Randomized selection of school and classes reduces the selection bias. The instruments were standardized and being prepared and tested by the experts, so there was no issue with the construct validity. External validity was obtained through a huge data set which was representative of the whole country.

4.6 Procedure

During winter 2013/14 the Swedish Public Health Agency collected data from Statistics Sweden (SCB) regarding students aged 11, 13 and 15 years and attending grades 5, 7, and 9 in the Swedish school system. Due to the comparability of data to other countries of the HBSC, data should be gathered when children are 11.5, 13.5, and 15.5 years of age, as a mean. Prior to data-collection in 2013/14, Schools sent out informational letters to parents through a channel they saw fit. Explaining the purpose and the background of the study. This information was also reported on the first page of the study brochure. Anonymous questionnaires were filled in by students in class during school time.

Teachers were responsible for collecting data in each class. The students submitted their questionnaires in a sealed envelope, that the teachers sent to SCB. Statistics were compiled from the collected data to a data file that was anonymized. The data file compiled by SCB was subsequently delivered to the Swedish Public Health Agency.

This study belongs to HBSC, which is a collaboration study including 43 countries. In Sweden the survey materials were translated from English to Swedish, and then re-translated back into English by another person and controlled against the original version for discrepancies. The questionnaires included questions related to the participants' background (i.e. age, sex, family composition and parents’ employment) and more in-depth questions on physical activity and sleep duration. Background questions and basic questions were the same for students in all participating countries, while each country chose which specific in-depth questions to ask. After the basic questions, the questions were asked regarding alcohol, tobacco and nutrition, physical activity, health, somatic and psychological disorders, body image, relationships to peers and parents, school environment and bullying. Students in grade 9 also answered questions about sex and relationships and drug habits.

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In Sweden, in the survey 2013/14, in-depth questions were enquired about sleep habits, the prevalence of chronic diseases and functional impairment, as well as about the relationship between participants and their parents. It should be noted that sleep patterns or disability were both self- reported and no objective measurements were used. Finally, the questionnaire also included a series of questions related to physical activity and sleeping habits.

5. Ethical Considerations

The study was anonymous, and informed consent from all students was collected prior to the survey. In case of 11 and 13 year-old children assent was obtained from parents. In order to avoid any ambiguity, all questions were translated into the local language, and formulated in a simple and easy way. A pilot study was conducted to make sure that the participants were able to understand all questions correctly. Participants were free to not answer any of the questions that could make them feel uncomfortable.

Parents, study participants and their teachers were provided with relevant and sufficient information about the purpose and background of the research, which provided them with an opportunity to make an informed decision about their participation in the study. In addition to that, teachers were available to help if there was any difficulty in understanding the questions. The research was conducted by trained researchers. The teachers were mainly responsible for the confidentiality of the data and they received the data from students and sent it to SCB in sealed envelopes.

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6. Data Analysis

SPSS 25 has been used for the data analyses. Information on the recommended sleep duration was obtained from the National sleep foundation. Children from age 6-13 have recommended sleep duration of 9 to 11 hours; 7 - 8 or 12 hours may be considered acceptable, whereas more than 12 or less than 7 hours of sleep are not recommended. For adolescents age 14-17 the recommended sleep duration is 8 to 10 hours, 7 or 11 may also be acceptable and less than 7 and more than 11 are not appropriate. These standards were used for the data analysis.

A three-way between subjects ANOVA was conducted to compare the number of hours slept per night during school days across categories of the following variables: sex, vigorous physical activity, and disability. Interaction terms were also added to test the reciprocal interactions between the latter variables. Models were stratified by grade. Initially all tests were performed together, however, a post hoc indicated significant differences in the sleep duration among the students across all age groups (see table 6.1). Therefore, the sample was stratified for each grade so that the results are more reliable and meaningful.

Table 6.1.Number of hours Schooldays

Tukey HSDa,b,c Subset Age N 1 2 3 11 Years old 2406 7.8148 13 Years old 2007 8.4078 15 Years old 2293 9.2126 Sig. 1.000 1.000 1.000

A multiple regression model was used to study the association between a higher quality of life (dependent variable), vigorous physical activity during the previous 7 days and number of hours slept per night. The model was adjusted by potential covariates such as sex, age, and the presence of disability. The latter variables were chosen because they satisfied the definition of covariates, i.e. they are potentially correlated to both the outcome (quality of life) and the exposures (sleep duration and physical activity).

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Mean differences in quality of life between participants who slept the recommended number of hours and those who did not, were compared by using compared means. Moreover, mean score of the quality of life across categories of increasing levels of vigorous physical activity (i.e. none, 30 min, 1 h, 2-3 h, 4-6 h, >7 h) were compared.

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7. Results

7.1 Factors Affecting Sleep Hours During School days

Descriptive analyses (means and standard deviations) of sleep duration, quality of life (QoL), and vigorous physical activity (VPA) were run and stratified by age, sex, and long-term disability (see table 7.1). The number of hours slept per night was highest among 11-year-olds and lowest among 15-11-year-olds, indicating a progressive reduction in sleep duration with growing ages. Among 11-year-olds, girls slept more hours than boys, whereas the opposite was true for 13-year-olds. No difference between boys and girls was found for 9th graders.

No differences in sleep duration between participants with and without disability was found among 13 and 15-year-olds. However, among 11-year-olds, participants with disability slept less hours compared to those who had no disability.

Boys showed higher level of vigorous physical activity compared to girls, whereas similar levels were observed across all age groups. Moreover, there was no big difference in physical activity based on disability, suggesting that no students had such severe disability to hinder them to participate in physical activities.

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Table 7.1. Descriptive information regarding sleep duration, VPA and QoL

11-Year-olds 13-Year-olds 15-Year-olds

Disability Typical Disability Typical Disability Typical Boys Girl s Boys Girl s Boys Girl s Boys Girl s Boys Girl s Boys Girl s N 271 263 1021 1020 223 251 868 877 260 309 1045 1056 Sleep Duratio n (M) 9.01 9.25 9.22 9.22 8.51 8.31 8.52 8.29 7.76 7.82 7.87 7.76 (SD) 1.02 0.70 0.78 0.75 1.11 1.19 1.04 1.07 1.27 1.17 1.04 1.05 QoL (M) 7.73 7.66 8.20 8.03 7.18 6.45 7.70 6.93 6.78 6.10 7.30 6.57 (SD) 2.18 5 1.77 8 1.67 4 1.66 1 1.88 3 2.20 0 1.68 5 1.94 8 1.89 6 2.03 6 1.75 4 1.76 VPA (M) 3.77 3.73 3.83 3.69 3.68 3.67 3.97 3.68 3.72 3.68 3.98 3.70 (SD) 1.53 1.36 1.41 1.33 1.52 1.52 1.59 1.44 1.59 1.52 1.54 1.43

Since all three age groups have different sleep duration depending on the age, the analyses were run separately for each grade.

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Analyses among 11-year-olds

Among 11-year-olds, a statistically significant differences in sleep duration between subjects with disability and subjects with typical development was found, with the latter reporting a longer sleep duration (See table 7.2). The difference in the number of hours slept by boys and girls was statistically significant, with girls reporting longer sleep durations. A statistically significant interaction between sex and disability was found, showing that the difference in sleep duration between disabled and typically developing participants was confirmed among boys only.

Table 7.2. Three-way ANOVA regarding 11-year-olds gender disability and VPA on

sleep duration

Tests of Between-Subjects Effectsa

Dependent Variable: Number of Sleep Hours during School Days

Source

Type III Sum of Squares Df Mean Square F Sig. Partial Eta Squared Corrected Model 39.684b ₂₃ _1.725 _2.966 _.000 _.029 Intercept 101329.690 1 101329.690 174189.863 .000 .987 Gender 2.129 1 2.129 3.659 .056 .002 VPA 11.249 5 2.250 3.867 .002 .008 Disability 2.015 1 2.015 3.464 .063 .002 Gender x VPA 3.039 5 .608 1.045 .389 .002 Gender x Disability 4.983 1 4.983 8.567 .003 .004 VPA x Disability 4.656 5 .931 1.601 .156 .004 Error 1319.922 2269 .582 Total 195971.250 2293 Corrected Total 1359.606 2292

a. Grade = 5 (i.e. 11-year-olds)

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In this age group, a statistically significant difference in sleep duration was found between boys and girls, with boys sleeping more hours than girls, opposite to what was found for 11-year-olds (see table 7.3). No statistically significant differences were found for disability and vigorous physical activity and their interactions.

sleep duration

Dependent Variable: duration of sleep school days

Type III Sum of Squares Df Mean Square F Sig. Partial Eta Squared Corrected Model 52.715b ₂₃ _2.292 _1.986 _.004 _.023 Intercept 82918.364 1 82918.364 71857.695 .000 .973 Gender 8.597 1 8.597 7.450 .006 .004 VPA 6.332 5 1.266 1.097 .360 .003 Disability .100 1 .100 .086 .769 .000 Gender * VPA 11.175 5 2.235 1.937 .085 .005 Gender * Disability .453 1 .453 .393 .531 .000 VPA* Diability 7.311 5 1.462 1.267 .275 .003 Error 2288.233 1983 1.154 Total 144218.750 2007 Corrected Total 2340.947 2006 a. GRADE = 7 (13 Years)

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In this age group, vigorous physical activity was the only variable that showed a statistically-significant association with sleep duration during schooldays, as the participants doing vigorous physical activity reported more sleeping hours than other participants (See table 7.4). On the contrary, no differences in sleep duration were found for sex and disability.

sleep duration

Tests of Between-Subjects Effectsa

Dependent Variable: number of hours schooldays

Source

Type III Sum of Squares Df Mean Square F Sig. Partial Eta Squared Corrected Model 80.551b ₂₃ _3.502 _3.065 _.000 _.029 Intercept 87929.330 1 87929.330 76954.470 .000 .970 Gender .375 1 .375 .329 .567 .000 VPA 17.128 5 3.426 2.998 .011 .006 Disability .035 1 .035 .030 .862 .000 Gender * VPA 11.013 5 2.203 1.928 .087 .004 Gender * Disability 3.662 1 3.662 3.205 .074 .001 VPA * Disability 7.770 5 1.554 1.360 .236 .003 Error 2721.709 2382 1.143 Total 149740.750 2406 Corrected Total 2802.260 2405

a. GRADE = 9TH GRADE (15 years)

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7.2 Quality of life

A multiple regression analysis was used to study whether sleep duration and VPA predicted quality of life, adjusted for sex, age and the presence of disability (see table 7.5).

All variables put into the model were significant. Both VPA and sleep duration were associated with a higher quality of life. Regarding potential covariates, we found that girls and older participants reported a significantly lower quality of life than boys and younger participants, and that the absence of disabilities was associated with a higher quality of life.

Table 7.5. Multiple Linear Regression to Predict QoL through Sleep Duration and

Vigorous Physical Activity

Multiple Linear Regression

Coefficientsa Unstandardized

Coefficients

Standardized Coefficients

Model B Std. Error Beta t Sig.

(Constant) 4.939 .259 19.057 .000

Girls -.485 .044 -.128 -11.118 .000

Age (years) -.374 .030 -.165 -12.365 .000

Vigorous Physical Activity (days/week)

.111 .015 .088 7.645 .000

No disability .419 .053 .090 7.843 .000

Numbers Hours of sleep/night (school days)

.323 .022 .194 14.512 .000

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a) Sleep Hours During Weekdays and Quality of Life

Most study participants (86.5%) reported to sleep the recommended number of hours per night. In order to test whether adolescents with recommended sleep hours have a better quality of life compared to those who did not follow these recommendations, means were used to compare mean differences of the number of hours slept per night between participants sleeping the recommended number of hours and those who did not.

Table 7.6. Means Compared for Predicting Quality of Life based on Sleep duration

Life Satisfaction

Sleep Hours During Weekdays

Mean N Std. Deviation

Recommended or Appropriate 7.49 6448 1.808

Not Recommended 6.52 1003 2.295

Total 7.36 7451 1.909

Table 7.7. One Way ANOVA for QoL and Sleep Duration Sum of squares Df Mean Square F Sig. QoL* Sleep Hours Weekday Between Groups (Combined) 805.738 1 805.738 227.802 .000 Within Groups 26347.208 7449 3.537 Total 27152.946 7450

Table 7.8. Measures of Association

Eta Eta Squared

QoL * Sleep Hours During Weekdays .172 .030

The results indicated that the students who slept the recommended number of hours per night reported a statistically significant higher quality of life compared to the remaining participants (See table 7.6). However, an Eta squared value of 0.03 indicates a small effect size, indicating that other factors explain more to quality of life than sleep (See table 7.8).)

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b) Vigorous Physical Activity Duration and Quality of Life

Mean scores for vigorous physical activity duration and quality of life were compared across categories representing increasing levels of vigorous physical activity duration.

The results shows statistically significant differences in quality of life across categories of vigorous physical activity duration (p < 0.001). In particular, a higher duration of vigorous physical activity was associated with a greater quality of life (See table 7.9). For example, among students who did not have any physical activity during the week, the quality of life scored (on average) 6.78, whereas among physically-active students (i.e. 7 hours or more) the average score for quality of life was equal to 7.61. However, Eta squared value of 0.013 indicates a small effect size (See table 7.11).

Table 7.9. Descriptive for Quality of Life and Physical Activity

Quality of Life Vigorous Physical Activity Duration Mean N Std. Deviation None 6.78 712 2.192 Half an Hour 7.20 678 1.956 1 Hour 7.35 1402 1.929 2-3 Hours 7.40 1749 1.856 4-6 Hours 7.46 1463 1.790 7 Hours or More 7.61 1090 1.763 Total 7.35 7094 1.902

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Table 7.10. One Way ANOVA for Quality of Life based on Vigorous Physical

Activity Sum of squares Df Mean Square F Sig. QOL * VPA Between Groups (Combined) 340.101 5 68.020 19.048 .000 Within Groups 26347.208 25311.226 7088 3.571 Total 27152.946 25651.326 7093

Table 7.11. Measures of Association

Eta Eta Squared

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8. Discussion

This study showed that gender, age, physical activity and disability matters when it comes to sleep duration during school days, although the pattern differ in different age groups indicating a support for the first hypothesis. The second hypothesis suggested that children and adolescents who slept recommended hours of sleep on school days had a higher quality of life, which was also supported by the study. Regarding the third hypothesis children who have more vigorous physical activity showed higher quality of life, thus also supported.

8.1 Sleep Hours During School days

Children develop lifestyle habits over time, as a result of their biological, social and psychological development and a vertical analysis helped in understanding this development (Rönnberg, 2004). Looking through, ICF-CY, as sleep is considered a homeostatic and chronobiologic mechanisms, the different results obtained in each age group are probably reconnected to the fact that the recommendations for sleep duration are age specific. This is what Hirshkowitz et al. (2015) notes that sleep duration for children and adolescents varies from 8 to 11 hours, depending on their age. However, other than biological development there also seems an influence how the interaction with the external environment (Bronfenbrenner & Morris, 2006) as their family & school life as well as availability and exposure to social media which has created sleep related issues.

8.2 Sleep Duration & Quality of Life

The second focus of this thesis was the association between sleep duration and a greater quality of life. As previous research studies have found, an adequate amount of sleep and a natural sleep onset are paramount in improving both children’s and adolescents’ health and well-being (Hirshkowitz et al., 2015). The results support these findings by showing that sleeping the recommended number of hours is associated with a higher quality of life, the latter expressed as a higher score in life satisfaction.

Participants who slept the recommended number of hours or more were more likely to show a higher quality of life than those who did not follow the recommendations. This is again related to system theory (e.g. Bronfenbrenner, 1979) model focusing on environment

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on different levels and the interaction between these levels. Despite sleep being a determinant of a higher quality of life, the contemporary society (macrosystem) promotes unhealthy changes in sleep patterns (microsystem), especially in adolescents. This phenomenon is primarily caused by the increased access to electronic gadgets compared to what was common until two decades ago (Woods & Scott, 2016).

8.3 Vigorous Physical Activity & Quality of Life

The third focus of the thesis was the association between physical activity duration and a greater quality of life. Physical activity is crucial to the maintenance of a good health status. Physical activity promotes mental health, body fitness (Bertills et al., 2018). The children and adolescents who participated more in vigorous physical activity were more likely to have a higher quality of life. However, modern society, owing to environmental changes and participant interaction at different levels of environment (Bronfenbrenner, 1979) has become a source for promoting sedentary behaviour. As a direct consequence of these environmental changes, more people seem to have modified their lifestyle by reducing the amount of time spent doing physical activities, which can negatively impact the individual quality of life. In addition, children and adolescents are responding to changes in social norms, especially those connected to their interactions through social media, that further seem to decrease their physical activity levels and negatively impact on their sleep behavior.

Participants who reported a higher duration of vigorous physical activities also reported longer sleep. Since the presence of disability can affect both the participants’ engagement in exercise and sleep duration, disability is a potential covariate of sleep duration and vigorous physical activity. The results show that disability matters for both sleep duration and physical activity, but it does not appear to be the main determinant which may be linked to the type of disability reported by the participant (not intellectual or developmental issues). These findings support what previously indicated by Bauman et al. (2012) i.e. that an extraneous variable can interfere with how physical activity affects sleep duration in both adolescents and children.

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Both vigorous physical activity and sleep duration were associated with a higher quality of life. Notably, quality of life decreased with increasing age. The results indicate that most study participants reported to follow the recommendations for both vigorous physical activities and sleep duration. According to the results, quality of life increases with the number hours spent performing intense exercise. In addition, the quality of life was higher in participants who slept an adequate or recommended number of hours per night.

Based on the findings of this research, as age increases, physical activity and sleep duration decreases. These results contradict what (Norell-Clarke & Hagquist, 2017) previously found, indicating that as children become adolescents, the level of physical exercise intensifies and more defined sleep patterns are established. The results indicate an opposite trend, although the observational nature of this study makes it difficult to identify the causes of this phenomenon.

In summary, this research study showed age, gender, long-term disability and physical activity effects sleep duration of the children and adolescents. Moreover, children and adolescents who sleep longer hours and do vigorous physical activities have a higher quality of life. Sleep duration has also been found to be associated with a higher quality of life.

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9. Conclusion

In contemporary society, living a healthy lifestyle has become difficult due to the penetration of social media and access to both electronic devices and the Internet (Woods & Scott, 2016). Health behavior has changed over time, making children and adolescents sleep an inadequate amount of time (LeBourgeois et al., 2017) and engage in less vigorous physical activities (Sheldrick et al., 2018). However, the consequences on quality of life also depend on various other factors, including gender, age, and long-term disability. In Sweden, in particular, a significant reduction in sleep duration at increasing ages has been observed (Norell-Clarke & Hagquist, 2017) and several factors seem to contribute to this problem other than maturation. Although the trend may not be necessarily the same for the entire population of children and adolescents, most of them have shown this characteristic from previous research. Similarly, there has been a decline in the vigorous physical activities of children owing to an increase in sedentary behavior.

A good quality of life is crucial for both children and adolescents to practice healthy behavior, since behavior in early life can persist over the rest of the lifespan (Engström, 2008; Inchley, 2013). Sleep duration and vigorous physical activity are two important elements of health behavior, and both may have a direct impact on the quality of life (Norell-Clarke & Hagquist, 2017). A good amount of sleep may not only prevents anxiety, depression, insomnia or similar, but also improves overall health (Baglioni et al., 2011; Woods and Scott, 2016). Similarly, participating in vigorous physical activities may also contributes toward health and a better quality of life. Thus, participation in physical activities may promotes good sleep, and can potentially be a positive contributor in a healthy lifestyle improving the quality of life.

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Reference list

Adolfsson, M., Malmqvist, J., Pless, M., & Granuld, M. (2011). Identifying child functioning from an ICF-CY perspective: Everyday life situations explored in measures of participation. Disability and Rehabilitation, 33(13-14), 1230-1244.

Adolfsson, M., Sjöman, M., & Björck-Åkesson, E. (2018). ICF-CY as a framework for understanding child engagement in preschool. Paper presented at the Frontiers in Education.

Astill, R. G., Van der Heijden, K. B., Van IJzendoorn, M. H., & Van Someren, E. J. (2012). Sleep, cognition, and behavioral problems in school-age children: A century of research meta-analyzed. Psychological bulletin, 138(6), 1109.

Baglioni, C., Battagliese, G., Feige, B., Spiegelhalder, K., Nissen, C., Voderholzer, U., . . . Riemann, D. (2011). Insomnia as a predictor of depression: a meta-analytic evaluation of longitudinal epidemiological studies. Journal of affective disorders, 135(1-3), 10-19. Bertills, K., Granlund, M., Dahlström, Ö., & Augustine, L. (2018). Relationships between

physical education (PE) teaching and student self-efficacy, aptitude to participate in PE and functional skills: with a special focus on students with disabilities. Physical Education and Sport Pedagogy, 23(4), 387-401.

Bouchard, C., Blair, S. N., Haskell, W. L., & Haskell, W. (2007). Physical activity and health: Human Kinetics 1.

Brian, A., Grenier, M., Lieberman, L. J., Egan, C., & Taunton, S. (2017). 50 million strong for all: Universally designing CSPAPs to align with APE best practices. Journal of Physical Education, Recreation & Dance, 88(7), 30-36.

Bronfenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human development: Sage.

Bronfenbrenner, U., & Morris, P. A. (2006). The Bioecological Model of Human Development. Handbook of Child Psychology.

Bryman, A., & Bell, E. (2015). Business Research Methods: Oxford University Press, USA. Cantril, H. (1965). Pattern of human concerns. New Brunswick, NJ: Rutgers University Press. Capio, C. M., Sit, C. H., Eguia, K. F., Abernethy, B., & Masters, R. S. (2015). Fundamental

movement skills training to promote physical activity in children with and without disability: A pilot study. Journal of Sport and Health Science, 4(3), 235-243. Chen, X., Beydoun, M. A., & Wang, Y. (2008). Is sleep duration associated with childhood

obesity? A systematic review and meta‐analysis. Obesity, 16(2), 265-274.

Cortesi, F., Giannotti, F., Ivanenko, A., & Johnson, K. (2010). Sleep in children with autistic spectrum disorder. Sleep medicine, 11(7), 659-664.

Davis, E., Young, D., Gilson, K.-M., Swift, E., Chan, J., Gibbs, L., . . . Williams, K. (2018). A rights-based approach for service providers to measure the quality of life of children with a disability. Value in Health, 21(12), 1419-1427.

Didden, R., Korzilius, H., Aperlo, B. v., Overloop, C. v., & Vries, M. d. (2002). Sleep problems and daytime problem behaviours in children with intellectual disability. Journal of Intellectual Disability Research, 46(7), 537-547.

Dumuid, D., Olds, T., Lewis, L. K., Martin-Fernández, J. A., Katzmarzyk, P. T., Barreira, T., . . . Hu, G. (2017). Health-related quality of life and lifestyle behavior clusters in school-aged children from 12 countries. The Journal of pediatrics, 183, 178-183. e172.

Ekstedt, M., Nyberg, G., Ingre, M., Ekblom, Ö., & Marcus, C. (2013). Sleep, physical activity and BMI in six to ten-year-old children measured by accelerometry: a cross-sectional study. International Journal of Behavioral Nutrition and Physical Activity, 10(1), 82. Engström, L.-M. (2008). Who is physically active? Cultural capital and sports participation from

adolescence to middle age—a 38-year follow-up study. Physical Education and Sport Pedagogy, 13(4), 319-343. doi:10.1080/17408980802400510

Ericsson, I. (2011). Effects of increased physical activity on motor skills and marks in physical education: an intervention study in school years 1 through 9 in Sweden. Physical Education & Sport Pedagogy, 16(3), 313-329.

(37)

34

Garmy, P., Clausson, E. K., Nyberg, P., & Jakobsson, U. (2018). Insufficient sleep is associated with obesity and excessive screen time amongst ten-year-old children in Sweden. Journal of pediatric nursing, 39, e1-e5.

Gochman, D. S. (1997). Handbook of Health Behavior Research I: Personal and Social Determinants (Vol. 1): Springer Science & Business Media.

Hallal, P. C., Victora, C. G., Azevedo, M. R., & Wells, J. C. (2006). Adolescent physical activity and health. Sports medicine, 36(12), 1019-1030.

Hedin, G., Norell-Clarke, A., Hagell, P., Tønnesen, H., Westergren, A., & Garmy, P. (2020). Facilitators and Barriers for a Good Night’s Sleep Among Adolescents. Frontiers in neuroscience, 14, 92.

Hirshkowitz, M., Whiton, K., Albert, S. M., Alessi, C., Bruni, O., DonCarlos, L., . . . Kheirandish-Gozal, L. (2015). National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health, 1(1), 40-43. Hitze, B., Bosy-Westphal, A., Bielfeldt, F., Settler, U., Plachta-Danielzik, S., Pfeuffer, M., . . .

Müller, M. (2009). Determinants and impact of sleep duration in children and adolescents: data of the Kiel Obesity Prevention Study. European journal of clinical nutrition, 63(6), 739-746.

Iannotti, R. J., Janssen, I., Haug, E., Kololo, H., Annaheim, B., & Borraccino, A. (2009).

Interrelationships of adolescent physical activity, screen-based sedentary behaviour, and social and psychological health. International journal of public health, 54(2), 191-198. Inchley, J. (2013). Let’s get physical: a public health priority. Perspectives in Public Health,

133(2), 92-93. doi:10.1177/1757913913475755

Jan, J. E., Owens, J. A., Weiss, M. D., Johnson, K. P., Wasdell, M. B., Freeman, R. D., & Ipsiroglu, O. S. (2008). Sleep hygiene for children with neurodevelopmental disabilities. Pediatrics, 122(6), 1343-1350.

Kenney, E. L., & Gortmaker, S. L. (2017). United States adolescents' television, computer, videogame, smartphone, and tablet use: associations with sugary drinks, sleep, physical activity, and obesity. The Journal of pediatrics, 182, 144-149.

Konofal, E., Lecendreux, M., & Cortese, S. (2010). Sleep and ADHD. Sleep medicine, 11(7), 652-658.

Lang, C., Brand, S., Feldmeth, A. K., Holsboer-Trachsler, E., Pühse, U., & Gerber, M. (2013). Increased self-reported and objectively assessed physical activity predict sleep quality among adolescents. Physiology & behavior, 120, 46-53.

LeBourgeois, M. K., Hale, L., Chang, A.-M., Akacem, L. D., Montgomery-Downs, H. E., & Buxton, O. M. (2017). Digital media and sleep in childhood and adolescence. Pediatrics, 140(Supplement 2), S92-S96.

Lenhart, A., Ling, R., Campbell, S., & Purcell, K. (2010). Teens and mobile phones: Text messaging explodes as teens embrace it as the centerpiece of their communication strategies with friends. Pew Internet & American Life Project.

Levin, K. A., & Currie, C. (2014). Reliability and validity of an adapted version of the Cantril Ladder for use with adolescent samples. Social Indicators Research, 119(2), 1047-1063. Löfstedt, P., Corell, M., Telander, J., Mörk, E., & Bergh, D. (2014). Skolbarns hälsovanor i

Sverige 2013/14. Grundrapport: Folkhälsomyndigheten Stockholm.

Marques, A., Ekelund, U., & Sardinha, L. B. (2016). Associations between organized sports participation and objectively measured physical activity, sedentary time and weight status in youth. Journal of Science and Medicine in Sport, 19(2), 154-157.

Matricciani, L. A., Olds, T. S., Blunden, S., Rigney, G., & Williams, M. T. (2012). Never enough sleep: a brief history of sleep recommendations for children. Pediatrics, peds. 2011-2039. Merga, M. K., & Williams, R. (2016). The role of health educators in mitigating health risk from

increasing screen time in schools and at home. Asia-Pacific Journal of Health, Sport and Physical Education, 7(2), 157-172.

Nixon, G. M., Thompson, J. M., Han, D. Y., Becroft, D. M., Clark, P. M., Robinson, E., . . . Mitchell, E. A. (2008). Short sleep duration in middle childhood: risk factors and consequences. Sleep, 31(1), 71-78.

Quality of Life, Sleep and Physical Activity in Swedish Children &amp;amp; Adolescents