Evaluation of Sleep Quality in Pediatric Population in a Portuguese Primary Care Setting
Article information
Abstract
Sleep problems in children are common but often underrecognized by caregivers. This study evaluated sleep quality in children and compared it with parental perception. The Portuguese version of the Children’s Sleep Habits Questionnaire was applied in primary care setting to children aged 2 to 10 years between July and November 2021, with a cut-off value for sleep disturbance of 48. A total of 239 valid responses were obtained, 56% male, median age of 6 years. In our sample, 43% had positive score for sleep disturbance, while 67% had a sleep duration according to recommendations and only 12% of parents perceived a sleep problem. Sleep disturbances were more common in pre-schoolers and when caregivers perceived a problem. Given the potential impact of sleep problems, greater attention is required as parents will underrecognize them. Healthcare providers should regularly assess sleep quality, ideally using validated tools, in order to identify problems needing intervention.
INTRODUCTION
Sleep is an active neurophysiological process, being the primary activity of the developing brain [1]. It is essential for survival, promoting energy conservation and facilitating physical growth and mental development [2]. Due to the limited time during medical appointments, sleep evaluation often focuses solely on sleep duration, which has age-specific recommendations. According to the American Academy of Sleep Medicine, children from 3 to 5 years should sleep between 10 and 13 hours and from 6 to 12 years should sleep from 9 to 12 hours [3]. However, assessing this parameter alone is insufficient to fully characterize healthy sleep.
Healthy sleep is a multidimensional pattern of sleep-wake behavior adapted to individual needs and to social and environmental demands, contributing to physical and mental well-being. To capture these multiple dimensions, the B-SATED acronym was proposed for pediatric population, derived from the adult SATED model. It stands for: behaviors related to sleep, satisfaction with sleep (subjective or caregiver-reported), alertness during wakefulness, timing of sleep (the moments of the day when sleep occurs), efficiency (the ratio of time asleep to time in bed), and sleep duration. The inclusion of behavioral factors in pediatric sleep assessment highlights their critical role in promoting good sleep quality, particularly through routines and sleep hygiene, which are easily targetable for intervention [4].
Sleep problems are common, affecting up to 50% of the pediatric population, with significant repercussions for both children and caregivers across various domains, including academic/work performance, social relationships, and emotional well-being [2]. However, these issues are often overlooked, either due to lack of awareness or time constraints during medical evaluations, limiting comprehensive assessment.
Sleep disturbances can have multiple consequences, including neurological and cognitive issues (e.g., memory and attention deficits), poor academic performance, behavioral problems (e.g., depression, anxiety, and aggression), and physical health issues (e.g., increased risk of obesity, altered sugar metabolism, and hypertension) [5]. Given their high prevalence and potential consequences, early identification of sleep disturbances is essential for effective intervention. Several validated questionnaires for pediatric sleep assessment exist, although not all evaluate every dimension of sleep quality.
The Children’s Sleep Habits Questionnaire (CSHQ), validated for children aged 2 to 10 years, is a comprehensive tool covering all B-SATED domains. Higher scores indicate more frequent behaviors associated with sleep difficulties and a higher likelihood of sleep disturbances [4]. This questionnaire has been validated for the Portuguese population, with an adjusted cutoff score of 48 indicating a positive screen for sleep disturbance [6,7].
The primary objective of this study was to characterize the sleep habits in a pediatric sample evaluated during routine primary care visits using a validated instrument. A secondary objective was to compare parental perceptions of sleep problems with questionnaire results, and to identify the specific sleep domains that most influence caregiver concern.
METHODS
An analytical cross-sectional study was designed to evaluate sleep habits and disturbances in children, using the Portuguese validated version of CSHQ (CSHQ-PT). The study was conducted on an opportunistic sample obtained from routine appointments at a primary care unit located in the Centre Region of Portugal between July and November 2021. Ethical approvement was obtained by the Ethic Committee of Hospital Distrital da Figueira da Foz (22.OBS.24) and the principles of the Declaration of Helsinki were followed while conducting the research. Informed consent was obtained by the parents fulfilling the questionnaires.
Inclusion and Exclusion Criteria
Children aged 2 to 10 years attending routine visits, whose parents consented to participate, were included. Questionnaires with incorrect or incomplete filling of scorable items were excluded.
CSHQ-PT Overview
The CSHQ-PT (Supplementary Material in the online-only Data Supplement) is a parent-reported questionnaire assessing sleep patterns over the prior week. It consists of 45 multiple choice items with 3 response options: usually (5 to 7 times per week), sometimes (2 to 4 times per week), and rarely (never or 1 time per week. Of these, 33 items are scorable on a 1 to 3 scale, with higher scores indicating more frequent sleep problems. The total score for these 33 items is used to calculate the Sleep Disturbance Index (SDI). A score of 48 or above indicates significant sleep disturbance, adjusted for Portuguese sociocultural characteristics [6].
Some items of the questionnaire were grouped into subscales based on the type of problem they address, which are bedtime resistance, sleep onset delay, sleep duration, sleep anxiety, night wakings, parasomnias, sleep disordered breathing, and daytime sleepiness. Subscale scores were calculated to help identify areas where intervention may be most urgent. Additional items assess factor such as television use at bedtime, nap habits, bedtime and wake time on weekdays and weekends, total sleep time (including naps), and parental perception of the existence of a sleep problem (“Do you think your son/daughter has a problem with sleep or falling asleep?”). A demographic questionnaire was also completed by the parents.
Data Analysis
SDI and subscale scores were analyzed, along with total sleep time, bedtime, and waking time during weekdays and weekends, and the existence social jet lag. Social jet lag was defined as a difference of at least 2 hours in the sleep midpoint at weekdays and weekends [8].
Statistical analysis was performed using SPSS 26.0 (IBM Corp.). The normality of quantitative variables was assessed using the Kolmogorov-Smirnov test. Normally distributed data were characterized by mean and standard deviation, while non-normally distributed data were presented using median and interquartile range (IQR) if not normal. Categorical variables were described using absolute and relative frequencies. The Mann-Whitney U test was used to analyze associations between positive screening and variables such as sex, age group, and parents’ perception sleep problems. The association subscales score and parents’ perception were also analyzed. Statistical significance was set at p<0.05.
RESULTS
A total of 260 questionnaires were obtained, 21 (8%) were excluded due to incorrect or incomplete filling, resulting in a final sample of 239 children. In the sample, 56% were male, and the median age was 6 years (IQR, 4 years). Preschoolers (aged 2 to 5 years) represented 48% of the sample, and school-aged children (6–10 years) represented 52% (Table 1).
Demographic characteristics of the sample
Parental perception of a sleep problem was reported in 29 cases (12%), with no statistically significant differences between sex or age group.
Mean sleep duration was 10:03±1:09 hours, with no significant sex differences and with statistically significant difference between age groups (p<0.001), with school-aged children sleeping less. Sleep duration was appropriate in 67% of cases (at least 10 hours in preschool age and 9 hours in school age), with 20% of preschool-aged and 13% of school-aged children sleeping less than recommended. Habitual napping was reported in 51% of children.
The mean bedtime was 21:41±0:30 hours on weekdays and 22:17±0:35 hours in weekends, both later in school-aged children (p=0.021 and p<0.001, respectively) and in males (p=0.003 and p=0.019, respectively). The mean wake time was 07:42±0:39 hours during weekdays, with no differences between sex or age group, and 08:50±0:55 hours at weekend, which was later in school-aged children (p=0.039) and female (p=0.029). Only bedtime on weekends correlated with parents’ perception of a sleep problem, occurring later in the group where parents reported sleep problems (p=0.017). Television use to fall asleep was reported in 6% of cases. Social jetlag was presented in 5%, more commonly in school-aged children (75%), females (67%), and among those whose parents did not report a sleep problem (83%), though these differences were not statistically significant (Table 2).
Sleep metrics and Sleep Disturbance Index according to age group, sex, and parental perception of sleep disturbance
The median SDI score was 46 (IQR, 11), with 43% (103 children) screening positive (score ≥48). Positive score was more frequent among preschoolers (57% vs. 30% in school age, p< 0.001) and among children whose parents perceived a problem (83% vs. 38%, p<0.001), with no sex difference (42% females vs. 44% males, p=0.742). Subscale scores were evaluated for the whole sample and considering two subgroups: subgroup 1 corresponding to children whose parents report the existence of a problem and subgroup 2 corresponding to children whose parents do not (Table 3). Statistically significant differences were identified between the score of children in these two subgroups for the subscales of bedtime resistance, sleep duration, sleep anxiety, night wakings, and parasomnias. The scores for the subscales on sleep onset delay, sleep disordered breathing, and daytime sleepiness did not show statistically significant difference among the subgroups.
Subscale scores and comparison between subgroups
DISCUSSION
In our sample, 43% of children screened positive for sleep disturbances, consistent with literature reports indicating prevalence rates of up to 50% [2]. Sleep disturbances were more frequent among preschool-aged children and those whose parents recognized these issues.
There was a difference in total sleep time between age groups, with schoolers sleeping less, reflecting a decrease in sleep needs with age. Though 33% of children did not meet the recommended sleep durations, 43% screened positive for sleep disturbance, highlighting that assessing only sleep duration is insufficient for identifying children at risk. Social jetlag was identified in 5% of the cases, an important factor given its potential developmental, metabolic, and cardiovascular consequences.
Only 12% of parents reported a sleep problem, similarly to previous Portuguese studies, suggesting underrecognition by caregivers [7].
Sleep problems have a wide variety of negative consequences, involving physical, neurocognitive, and emotional/behavioral outcomes. In terms of physical outcomes, it is mainly linked to its potential negative impact in cardiometabolic factors, altering levels of appetite-regulating hormones and conditioning a higher risk of obesity, affecting glucose metabolism and elevating the risk of high blood pressure. In the neurocognitive area, sleep deficiency has shown to be linked with impaired memory retention and attentive behavior, lower neurocognitive functioning and overall intelligence quotient and poorer academic performance. Regarding emotional and behavioral outcomes, sleep problems can be a predictor of negative internalizing behaviors, such as anxiety and depression, and externalizing behaviors, such as aggressive behaviors [5].
Given all the possible negative consequences of sleep problems, there is a substantial need to identify them and to implement effective measures to prevent and mitigate them. The parents’ underrecognition of these problems highlights the essential role of healthcare professionals.
Subscale analysis revealed no statistically significant differences between the groups with or without parental perception of a sleep problem regarding sleep onset delay, sleep-disordered breathing, and daytime sleepiness, while the subscales on bedtime resistance, sleep duration, sleep anxiety, night wakings, and parasomnias showed statistically significant differences. This may indicate that caregivers are undervaluing the aspects of children sleep quality that probably have a lower impact on the night functioning for the families, but that are important to recognize as they also lead to negative consequences on children’s health and development.
Our findings reinforce the perception that sleep problems are often underidentified and underreported by caregivers, which can result in healthcare professionals failing to identify these issues during routine appointment. Therefore, it is essential to evaluate sleep patterns during every routine appointment, ideally using validated multidimensional tools. The CSHQ-PT is practical, validated tool that can help healthcare providers identifying sleep issues requiring intervention.
The strengths of the study include its implementation in a primary care setting during routine appointments, which ensures a diverse sample not limited to children undergoing hospital follow-ups. Additionally, the use of a validated tool for the country covering multiple sleep domains enhances the study’s reliability. However, limitations include the sample size and the fact that data were collected from a single center.
Supplementary Materials
The online-only Data Supplement is available with this article at https://doi.org/10.17241/smr.2025.03020.
Notes
Availability of Data and Material
The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.
Author Contributions
Data curation: Marta Martins Carvalho, Tânia Coelho. Formal analysis: Marta Martins Carvalho. Methodology: Marta Martins Carvalho, Filipa Inês Cunha. Supervision: Filipa Inês Cunha. Writing—original draft: Marta Martins Carvalho. Writing—review & editing: Tânia Coelho, Filipa Inês Cunha.
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
Funding Statement
None
Acknowledgements
None