Association Between Movement Behaviors,Sleep Quality,and Anxiety Symptoms in Adolescents: A School-Based Cross-Sectional Study

Study Design

This is an observational study with a cross-sectional design. Data were collected at a federal public school in Brazil, located in Sousa/PB: Federal Institute of Education, Science and Technology of Paraíba (IFPB), between June and November 2023. The study followed the criteria established by STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) for observational studies (Von Elm et al., 2007). The study was conducted in accordance with the Helsinki Declaration and Resolution no. 466/2012 of the Brazilian National Health Council, after approval by the Research Ethics Committee of the UNIESP University Center (CAAE no. 49857421.0.0000.5184) on April 24, 2023. All participants or their legal guardians provided written informed consent before participating in the study.

Participants

Participants in this study were adolescents recruited from the integrated technical courses at IFPB, Sousa campus. IFPB is a federal public school offering integrated high school education alongside technical courses like agriculture, environment, and computing, all delivered in full-time schedules (morning and afternoon). Recruitment occurred through research promotion in classrooms and electronic platforms, such as Instagram and WhatsApp. Inclusion criteria encompassed adolescents of both sexes, aged 14 to 19 years, without diagnosed psychological, psychiatric, or cognitive disorders and not taking related medications. Exclusion criteria involved voluntary withdrawal or failure to complete study measures. Written informed consent was obtained from all participants and their legal guardians. Among the 297 students enrolled in this age group at the institution, 250 participants (84% of the target population) were included in the study analysis (see Supplemental Figure 1).

Collection Data

Data collection was acquired place at the Department of Physical Education on the Sousa campus of IFPB. The department is equipped with a climate-controlled physical assessment laboratory and a corporeality laboratory, both utilized for administering research instruments. All data collection was performed by a team of trained researchers, following ethical guidelines and methodological protocols recommended for observational studies. Volunteers experienced a structured data collection process, which involved completing several questionnaires in person with the evaluator. These included modules covering personal and demographic information, sleep quality, physical activity, and sedentary time from the adapted version of the Global School-based Student Health Survey (GSHS) (World Health Organization, 2021a), as well as the Brazilian Economic Classification Criterion (Brazilian Association of Research Companies, 2022). In-person administered questionnaire allowed researchers to clarify questions immediately and reduce misunderstandings. Previous evidence suggests that social desirability bias does not significantly differ between paper-based and computerized surveys (Dodou & de Winter, 2014). Subsequently, participants completed the Screen for Child Anxiety-Related Disorders (SCARED) (Birmaher et al., 1999). Finally, anthropometric measurements (height and weight) were obtained using standardized procedures, with participants barefoot and wearing light clothing.

Movement Behaviors and Sleep Quality

Movement behaviors and sleep quality variables were measured using an adapted version of the GSHS (World Health Organization, 2021b), as employed by the 2016 Brazilian Attitude Project (Lifestyle and Health Research Group, 2025). This temporal trend study evaluated high school students from the state of Pernambuco, Brazil, every 5 years. We used the adapted questionnaire from the 2016 survey wave, which is available in the anonymous repository provided for peer review. All items used to measure MVPA, SB, and sleep quality are presented in Supplemental Material 1. (i) MVPA was measured by the weekly frequency and time spent (in minutes) on moderate (requiring some physical effort) and vigorous (requiring a great deal of physical effort) physical activities performed during a typical week, without distinguishing between weekdays and weekends. MVPA level was classified as physically inactive (<60 min/day) and physically active (≥60 min/day) (Bull et al., 2020). (ii) Total SB was measured by the daily time spent on weekdays and weekends in sedentary activities when not at school or at work, including watching television, using a computer, and playing video games, as well as in sedentary activities, such as sitting, chatting with friends, playing cards or dominoes, talking on the phone, driving or being a passenger, reading, or studying. Time spent using smartphones and/or tablets was also assessed in the original survey but was not included in the analyses of the present study. The sedentary activities were summed up and conducted on a daily weighted average, considering weekdays and weekends. SB was classified as low (<8 h/day) and high (≥8 h/day). This cut-off point was adopted because it has been used in population-based studies with adolescents to identify high sedentary time, and for the reason that exceeding this amount has been associated with anxiety-related sleep disturbances (Werneck et al., 2019; Zhang et al., 2021). (iii) The quality of sleep was evaluated by the question, “How do you rate the quality of your sleep?,” which is included in the adapted Brazilian version of the GSHS. Those who indicated “good,” “very good,” or “excellent” options were rated as having “good sleep,” whereas those who indicated “poor” and “fair” were classified as having “poor sleep.”

Anxiety Symptoms

Anxiety symptoms were assessed using the SCARED (Birmaher et al., 1997, 1999). The SCARED is a validated and reliable scale for Brazilian children and adolescents (Isolan et al., 2011). The scale consists of 41 items that are grouped into five anxiety symptom factors, such as: panic (13 items), generalized anxiety (nine items), separation anxiety (eight items), social phobia (seven items) and school phobia (four items). For each item, the participant must choose the answer that most closely reflects how they have felt in the last 3 months. Each item is scored on a three-point Likert-type scale: 0 = “not true or rarely true”; 1 = “sometimes true”; 2 = “true or often true.” The scores range from 0 to 82, and higher scores reflect higher levels of anxiety. The presence of clinically significant anxiety is traditionally defined with a total score equal to or greater than 25 (≥ 25) points, however, the specificity at this cut-off point was only 67% when discriminating between anxiety and non-anxiety disorders (Birmaher et al., 1999). In contrast, by increasing the cut-off point to 30 (≥ 30) points, specificity increases to 83.5%, improving discrimination between anxiety and non-anxiety disorders (Canals et al., 2012; Chan et al., 2015). We therefore aimed for greater specificity and adopted ≥ 30 as the cut-off point for the study.

Other Variables

The other variables used to characterize the sample or as confounding variables (covariates) in the multiple models were collected using standardized questionnaires and measurements. Covariates were considered as potential confounders based on conceptual directed acyclic graphs (see Figure 1) and previous literature (Ferrari et al., 2020; Lindberg et al., 2020; Lopes et al., 2016; McLaughlin et al., 2012; Weimann et al., 2025). Demographic and socioeconomic data were collected using the GSHS (World Health Organization, 2021a) and according to the Brazilian Economic Classification Criteria (Brazilian Association of Research Companies, 2022), respectively. The age (years), ethnicity (white/yellow and brown/black) and area of residence (urban and rural) were registered. Regarding socioeconomic status, the participants were grouped into two categories: low and middle/high class. Weight and height were measured using a digital scale (W200, Welmy, Brazil) and a portable stadiometer (ES2060, Sanny, Brazil), respectively. Body mass index (BMI) was calculated as the ratio between weight and height squared (kg/m²) and classified according to World Health Organization reference standards, based on age and sex, and categorized into normal weight and overweight/obesity (World Health Organization, 2000, 2006).

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Figure 1.

Direct Acyclic Graph.

Statistical Analysis

Continuous variables were described as mean ± standard deviation (SD), while categorical variables were described as absolute (n) and relative (%) frequencies with a 95% percentile bootstrap confidence interval (CI). Group differences by sex were assessed using the generalized gamma model for continuous variables and the chi-square test for categorical variables. The prevalence of anxiety symptoms was compared between categories of movement behavior using the chi-square test. Poisson regression with robust variance was used to determine the prevalence ratio (PR) and 95% CI for anxiety symptoms, considering MVPA, SB, sleep quality (model 1) or a combination of risk behaviors (models 2 and 3), adjusted for the confounding variables: age, gender, BMI (normal and overweight) and socioeconomic class (low and middle/high). Model assumptions, including multicollinearity, were assessed. The quality of fit of the models was assessed using the Omnibus test (p < .05 considered a satisfactory fit). A p-value < 0.05 was considered statistically significant for all analyses. All analyses were conducted using SPSS v.27 software (IBM Corp., Armonk, NY, USA).

Strengths, Limitations, and Practical Implications

This study has strengths and limitations that need to be considered. Positive points include the combined analysis of movement behaviors (i.e., MVPA and SB) and sleep quality, allowing for a more detailed understanding of their interactions with anxiety symptoms in adolescents. In addition, the choice of self-reported measures to assess anxiety symptoms may provide important information about adolescents’ perception of their mental health, complementing more clinical approaches (Feiten et al., 2021; Tavares et al., 2024). However, the study has some important limitations. First, because it is a cross-sectional study, there are no causal relationships between movement behaviors, sleep quality, and anxiety symptoms. Longitudinal studies are needed to confirm the direction of these associations over time. Second, the assessment of movement behaviors relied on self-reported measures, which may be subject to recall and social desirability biases. Future studies should incorporate more objective assessment methods, such as accelerometry for precise measurement of MVPA and SB, and polysomnography, the gold standard, for comprehensive evaluation of sleep parameters. In addition, although our questionnaire was based on the GSHS, we used an adapted version tailored to the Brazilian context. As detailed in Supplemental Material 1, the set of items and response options does not fully replicate the original instrument, and some wording and content adjustments were made. These differences may restrict the direct comparison of our results with studies that used the complete standardized GSHS questionnaire. Third, we did not control pubertal status, which could influence both movement behaviors and anxiety symptoms, representing a potential confounding factor. Future studies should consider including this variable to better elucidate these relationships. Fourth, we recognize the potential for social desirability bias when administering questionnaires in person. Furthermore, a meta-analysis has shown no significant differences in social desirability scores between paper-based and computerized surveys (Dodou & de Winter, 2014), suggesting that the mode of administration may not substantially affect self-reported data. Nonetheless, future studies could further explore this aspect by randomly assigning participants to different administration modes (e.g., online vs. in-person) to assess any potential influence on response patterns.

In practical implications for school-based interventions, our study suggests that schools could play a pivotal role in promoting MVPA, reducing SB, and improving sleep hygiene among adolescents. Strategies may include incorporating structured physical activities (e.g., exercises or sports programs), educating students on the importance of good sleep quality (e.g., offering workshops that teach bedtime routines, limit screen use before sleep, and emphasize the benefits of consistent sleep quality), and limiting prolonged sedentary periods through initiatives, such as active breaks during lessons or encouraging active commuting (e.g., standing up and stretching every 50 minutes or integrating short movement breaks between classes). By integrating these strategies into school health programs, it may be possible to mitigate anxiety symptoms and support the mental well-being of adolescents during this critical developmental stage.