Excessive Daytime Sleepiness Affects Over 70% of Brazilian Adolescents, Tied to Depression, Smartphone Addiction, Diet

Results from a recently published population-based study in Ciência & Saúde Coletiva showed that nearly three-quarters of first-year high school students in a Brazilian public school system experienced excessive daytime sleepiness (EDS), with the condition disproportionately linked to modifiable behavioral and mental health risk factors.¹

These findings, drawn from more than 1,600 adolescents, add to a growing body of evidence suggesting that EDS in adolescence is not merely a symptom of insufficient sleep but a marker of broader behavioral and psychological vulnerability, with implications for how clinicians screen and counsel young patients. The study's authors reported that EDS prevalence in this cohort exceeded rates seen in several prior international samples, and that the strongest associated factors, including smartphone addiction and severe depressive symptoms.

Study Overview

Led by Nayra Suze Souza e Silva, PhD, professor in the Department of Physical Education and Sports at Universidade Estadual de Montes Claros, the analysis was part of the ELCAS Project. For context, ELCAS was a 2-stage longitudinal study on adolescent behavior, physical activity, and health; the present findings come from its cross-sectional baseline phase, conducted between September 2022 and December 2023.

Investigators surveyed 1,616 adolescents aged 14 to 19 years (mean age, 15.3 years) across 20 state public schools in Montes Claros, Brazil. EDS was assessed using the Pediatric Daytime Sleepiness Scale (PDSS), validated for Brazilian adolescents, with a cutoff score of 15 or higher indicating the presence of EDS.

Additional validated instruments included the Depression, Anxiety and Stress Scale-21 (DASS-21) and the Smartphone Addiction Inventory (SPAI). Independent variables spanned sociodemographic characteristics, stage of behavior change for physical activity, dietary patterns, mental health symptoms, and anthropometric measures. Associations were estimated using Poisson regression with robust variance, yielding adjusted prevalence ratios (PR).

Key Findings

Overall, 72% of adolescents (n = 1,131) met criteria for EDS. In the adjusted model, prevalence was higher among female students (PR, 1.22; 95% CI, 1.13-1.32; P <.001) and among those attending morning (PR, 1.35; 95% CI, 1.10-1.65; P = .004) or full-time (PR, 1.35; 95% CI, 1.10-1.67; P = .004) school shifts compared with night-shift peers. Adolescents in the precontemplation stage of behavior change for physical activity, those with no intention to become active, showed higher EDS prevalence than those in the maintenance stage (PR, 1.15; 95% CI, 1.03-1.28; P = .012).

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Daily consumption of ultra-processed foods (PR, 1.09; 95% CI, 1.02-1.16; P = .009), severe depressive symptoms (PR, 1.16; 95% CI, 1.09-1.24; P <.001), and smartphone addiction (PR, 1.36; 95% CI, 1.25-1.47; P <.001) were each independently associated with EDS. No safety outcomes were assessed, as the study was observational. Sensitivity analyses using alternative variable categorizations and logistic regression produced largely consistent results, with body image dissatisfaction emerging as an additional associated factor in one supplementary model.

Clinical Context and Interpretation

Excessive daytime sleepiness (EDS) is increasingly recognized as a distinct clinical entity rather than simply a consequence of insufficient sleep, with behavioral, circadian, and neuropsychiatric factors potentially contributing to its development.² Prevalence estimates among adolescents vary widely, from 21.1% in a Chinese cohort of more than 7000 students to 72% in the current study, potentially reflecting differences in measurement tools, thresholds, and population characteristics.³ The elevated prevalence among morning- and full-time-shift students also highlights the potential relevance of delayed school start times, which have been proposed as a strategy for improving adolescent sleep health.⁵

In the current study, depressive symptoms and smartphone addiction emerged as the strongest independent factors associated with EDS, suggesting that mood symptoms and bedtime screen use may contribute to sleep disruption through overlapping mechanisms. The association with depression is consistent with meta-analytic evidence linking subjective sleep disturbances with depressive symptoms in adolescents, reinforcing the potential for sleepiness to serve as both a consequence and marker of underlying mood pathology.⁴ However, given the study's cross-sectional design, the findings cannot establish causality and should instead help inform further investigation into the behavioral and psychological factors contributing to adolescent EDS.

Limitations and Future Research

The study relied on self-reported questionnaires, introducing potential recall and social desirability bias. The sample was restricted to first-year public high school students in a single municipality, limiting generalizability to private-school populations or adolescents in other regions of Brazil. The cross-sectional design cannot establish temporal or causal relationships between EDS and its associated factors. The authors pointed to the ongoing ELCAS follow-up phase, conducted 24 months after baseline, as an opportunity to assess longitudinal and potentially causal relationships between behavioral risk factors and EDS.

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REFERENCES
1. Silva NSSE, Soares KT, Haikal DS, Silva RRV. Excessive daytime sleepiness and health risk behaviors among adolescents: a population-based study. Sonolência diurna excessiva e comportamentos de risco para a saúde entre adolescentes: estudo de base populacional. Cien Saude Colet. 2026;31(4):e07002024. doi:10.1590/1413-81232026314.07002024
2. Pérez-Carbonell L, Mignot E, Leschziner G, Dauvilliers Y. Understanding and approaching excessive daytime sleepiness. Lancet. 2022;400(10357):1033-1046. doi:10.1016/S0140-6736(22)01018-2
3. Liu ZZ, Jia CX, Liu X. Excessive daytime sleepiness mediates the relationship between insomnia symptoms and suicidal behavior in adolescents. Sleep. 2022;45(11):zsac221. doi:10.1093/sleep/zsac221
4. O'Callaghan VS, Couvy-Duchesne B, Strike LT, McMahon KL, Byrne EM, Wright MJ. A meta-analysis of the relationship between subjective sleep and depressive symptoms in adolescence. Sleep Med. 2021;79:134-144. doi:10.1016/j.sleep.2021.01.011
5. Mousavi Z, Troxel WM. Later school start times as a public health intervention to promote sleep health in adolescents. Curr Sleep Medicine Rep. 2023;9(3):152-160.