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. 2026 Sep 2;52(5):e70341. doi: 10.1111/cch.70341

Preschool Environment and 24‐h Behaviour Movement in Uruguayan Early Childhood: A Compositional Data Analysis

Sofia Fernandez‐Gimenez 1,2,3,✉, Clarice L Martins 4, Enrique Pintos‐Toledo 1,2,3, Franco Souza‐Marabotto 2, Javier Brazo‐Sayavera 2,3,5
PMCID: PMC13537913  PMID: 42686371

ABSTRACT

Background

The preschool environment is a critical determinant of children movement behaviour; however, evidence integrating the 24‐h movement behaviour remains scarce, especially in the global south.

Objective

To identify the association between the preschool environment and 24‐h movement behaviour in Uruguayan preschoolers.

Methods

A cross‐sectional study was conducted with 112 preschoolers (45.32 ± 6.40 months) from Rivera, Uruguay. Movement behaviours were measured using accelerometry (Actigraph, wGT3X‐BT) and operationalized as a 24‐h composition. The preschool environment was audited in six domains: i) teacher role, ii) teacher training and education for family, iii) school policies, iv) indoor equipment, v) outdoor equipment, and vi) outdoor infrastructure. Multivariate linear regression models between preschool environment and isometric log‐ratio (ilr) coordinates of movement behaviours were conducted.

Results

The outdoor equipment environmental predictor significantly associated with the 24‐h movement behaviours composition (F = 3.40, p = 0.020), favouring the increase moderate‐to‐vigorous physical activity MVPA (β = 0.10, p = 0.027).

Conclusions

This research highlights Outdoor Equipment (availability, quantity and accessibility for preschoolers) as a key factor in promoting the movements behaviour and levelling the playing field for girls in moderate‐to‐vigorous physical activity.

Keywords: child, compositional data analysis, environment, physical activity, preschool, sedentary behaviour, sleep

Summary

  • Outdoor equipment is a key factor in increasing MVPA in preschool children.

  • A well equipment outdoor environment acts as a levelling factor for gender equity, as girls exhibit a higher relative proportion of MVPA when the preschool environmental is adjusted.

  • The use Compositional Data Analysis is essential to capture the interdependence of 24‐h daily movement behaviours.

  • First study in Uruguay, on the preschool environment and 24‐h movement behaviour.

1. Introduction

Physical activity (PA) provides numerous health benefits, including improvements in motor and cognitive development, as well as cardiometabolic, musculoskeletal, and psychosocial health (Carson et al. 2017). Recent research has also demonstrated that physical activity is consistently associated with the development and strengthening of behavioural and psychosocial self‐regulation in early childhood. Studies based on systematic reviews and meta‐analyses indicate positive associations with the behavioural domain—impulse control, goal‐oriented behaviour, and response inhibition—while also promoting skills in the cognitive and emotional dimensions (Cecic‐Mladinic et al. 2026; D'Cruz et al. 2024). Conversely, sedentary behaviour (SB) is associated with negative health outcomes and increased healthcare costs (Silva et al. 2022). The PA is defined as any bodily movement that increases energy expenditure above resting energy expenditure (Caspersen et al. 1985), while SB is defined as any behaviour characterized by energy expenditure ≤ 1.5 metabolic equivalents while sitting, reclining, or lying down (Tremblay et al. 2017). PA and SB are two independent but related lifestyle behaviours that occupy all waking hours of the day. Within a holistic 24‐h paradigm, sleep directly interacts with waking behaviours. The balance between vigorous PA, limited SB, and restorative sleep offers the greatest protection against non‐communicable diseases from the earliest years of life (Loo et al. 2023). Evidence compiled by Chaput et al. (2017) reinforces that insufficient sleep duration is linked to unfavourable health indicators, such as an increased risk of obesity, difficulties in emotional regulation, and reduced motor and cognitive development. WHO guidelines for the early years recommend a combination of movement behaviours along the day, comprising ≥ 180 min of PA (including ≥ 60 min of moderate to vigorous physical activity ‐MVPA‐), <60 min of sedentary screen time, and 10–13 h of good quality sleep (WHO 2019).

Understanding movement behaviours in early childhood requires a comprehensive socio‐ecological approach to capture that allows for the systematic summarization of the multiple factors associated with them. From this perspective, the movement behaviours should be explored through distinct and complementary microsystems, such as the family and the school context, comprehensively analysing their activities patterns, roles, interpersonal relationships (Bronfenbrenner 1999). In the context, Early Childhood Education and Care Centres (ECECCs) emerge as a critical and multidimensional microsystem where the physical environment, institutional policies, and pedagogical climate converge to shape children's daily activities. These spaces are consolidated as strategically designed built environments for human activities, acting as valuable settings for the movement behaviour (Seyedrezaei et al. 2023).

In particular, ECECCs that offer appropriate structures and resources (i.e., jumping and play equipment, spinning equipment, or floor games) have the potential to optimized preschoolers´ movement behaviours along the day (Sisson et al. 2016). For instance, a recent systematic review reported that the quality of play equipment and infrastructures associates with PA, while playground green areas has positive effects on children's social and mental health (Schipperijn et al. 2024). Moreover, adequately sized outdoor play areas allows preschoolers to remain physically active for longer periods of time in their centres and reducing SB (Martin et al. 2022).

Besides school areas and equipment, professional experience of Physical Education teachers may impact children's movements (Haav et al. 2024). In order to create active environments, the Global Action Plan for PA (World Health Organization 2018) suggests to develop and implement design guidelines for educational facilities and daycare centres based on an adequate provision of safe and accessible environments for children to be physically active (e.g., play areas or recreational spaces) and to reduce their time seated. Recent literature also highlights the importance of preschool staff as key contributors to preschoolers´ movement behaviour, through their participation and organization of outdoor activities (Kippe et al. 2021). Finally, preschoolers seem to be more active in those centres where there is a formalized PA policy, compared to preschoolers within centres without such policies. A similar association exists between preschool children who spend most of their time outdoors and those who spend less time outdoors (Chen et al. 2020).

In this sense, we hypothesize that these preschool environment‐related factors shape children's daily movement behaviours from the earliest years of life. While the 24‐h movement behaviour paradigm emphasizes that all behaviours across the continuum are co‐dependent and collectively impact children's health (Chaput et al. 2014; WHO 2019; Rollo et al. 2020), understanding how specific microsystems—such as the preschool environment—influence these daily patterns requires examining both environmental determinants and individual characteristics in an integrated manner. Thus, considering both the systemic nature of preschool contexts and the combined dynamics of co‐dependent movement behaviours, this study analyses how environmental factors interact with children's movement patterns.

At the national level, Uruguay, has taken steps toward this integration through the implementation of policies that promote healthy practices, most notably the Guide for health promotion in early childhood centres of the Uruguayan Institute for Children and Adolescents (INAU in Spanish) (Andrés et al. 2012). This guide advances in the field, by emphasizing the importance of space organization and accessible, safe and durable equipment to respond to the diverse interests and needs of children at different developmental stages. Nonetheless, the continuum nature of movement behaviours along the day requires an integrative approach that considers SB and sleep, besides PA. Given the lack of national evidence, there is a need of empirical Uruguayan evidence to inform public policies. This study aimed to identify the association between the preschool environment and 24‐h movement behaviour in Uruguayan early childhood.

2. Methods

2.1. Design and Sample

A cross‐sectional study was conducted within the SUNRISE international pilot project framework. The specific population consisted of children aged 3–4 years residing in Rivera, Uruguay. A convenience sample, including public and private Early Childhood Education and Care (ECEC) centers, was selected. The inclusion criteria were: i) children aged between 36 and 59 months at the time of evaluation, and ii) parents or legal guardians who provided signed informed consent. Recruitment and data collection were systematically conducted between December 2024 and September 2025. Of the 189 preschool‐aged children invited, 163 agreed to participate. The final sample consisted of 135 participants who: a) completed all planned assessments and b) The self‐assessment form completed by the person responsible for the ECECC was submitted. Participants without valid accelerometry data were excluded from the analysis according to the SUNRISE study protocol, resulting in a final analytical sample of 112 participants. The study was approved by the Ethics Committee of the University Centre of the North Littoral Region of the University of the Republic (Exp. No. 311170–000102‐23) in accordance with the Declaration of Helsinki.

2.2. Measurements

2.2.1. 24‐H Movement Behaviour

PA, SB and sleep were measured using triaxial accelerometers (Actigraph, model wGT3X‐BT). Participants wore the device on their right hip for five consecutive 24‐h periods, except for bathing or other water activities. The devices were programmed to collect data at a frequency of 30 Hz at 15 s intervals. A valid day was defined as one in which the child reported at least 600 min of accelerometer use. Pate cut‐off points were used to categorize SB (< 200 counts/15 s), light physical activity ‐LPA‐ (200–419 counts/15 s), and MVPA (≥ 420 counts/15 s) (Pate et al. 2006). The sleep analysis was based on the criteria of the SADEY (Sleep and Activity Database for Early Years) approach adapted for preschool children. This method focuses on the automatic detection of sleep periods based on activity patterns on the vertical axis, a procedure already used in accelerometery studies with young children (Cliff et al. 2024). But as a prelude to sleep detection, any consecutive period of zero activity of 20 min or more was classified as no device use. Sleep episodes were identified from segments automatically generated by ActiLife's algorithms, applied to data reintegrated at 15‐s intervals, following the SUNRISE protocol (Okely et al. 2021). Therefore, the temporal definition of sleep was adapted from the SADEY logic for this age group, where nighttime sleep was considered detected between 18:00 and 10:00 the next day, while naps corresponded to sleep episodes between 10:00 and 18:00. The total sleep duration in 24 h was obtained by adding nighttime sleep and naps. An average daily sleep duration (min/day) was used for the analyses, including only the days considered valid; in addition, inclusion in analyses required a minimum of three valid days of accelerometry data, in line with previous research in preschool children (Zhang et al. 2022). ActiLife version 6 software (Pensacola, Florida, USA) was used to initialize, download, and process accelerometer data.

2.2.2. Preschool Environment

To assess the preschool environment from a socioecological perspective, the Child Care Nutrition and Physical Activity Self‐Assessment (NAP SACC), which is a reliable, valid instrument (Benjamin et al. 2007), was used. This tool is adapted to be self‐completed by those responsible for the centre (Ward et al. 2017). Six scores were created, one for each environmental domain: Teacher Role; Teacher Training and Education for Family; School Policy; Outdoor Equipment; Indoor Equipment; Outdoor Infrastructure. Higher scores in each domain indicate greater availability, quality, and supportive conditions for PA and healthy movement behaviours. The internal consistency analysis of the scores can be found in supplemented material. This tool was completed by nine institutional representatives (coordinator or director), one for each ECECs participating in the study and reviewed by one researcher to identify any discordance with the observations during the visits.

2.3. Statistical Analysis

For the analysis of 24‐h movement behaviour, only participants with valid accelerometry records in all movement's behaviours were included. Due to variations in accelerometer usage time, a compositional closure procedure was applied to normalize each subject's data to a constant sum of 1440 min (24 h). This ensures that the analyses focus on the proportional distribution of time rather than absolute values, respecting the geometry of the simplex (SD) (Dumuid et al. 2020). Considering the intrinsic co‐dependency of these behaviours (where increased time spent on one activity implies decreased time spent on another) (Jašková et al. 2023), the data were analysed using Compositional Data Analysis (CoDA). This methodological framework allows time to be treated as a closed whole, overcoming the limitations of collinearity and spurious correlations inherent in constant‐sum data (Lau et al. 2024).

Time compositions were transformed into Isometric Log‐Coordinates (ilr) using the compositions package in RStudio (version 2025.09.2 + 418). A sequential binary partition was employed, placing the MVPA as the first component (pivot), for interpretation of the results. This transformation projected the compositions from the simplex to a real Euclidean space, allowing the application of multivariate linear regression models without collinearity issues. Multivariate linear regression models were fitted to examine the association between the five environmental dimensions and the 24‐h cycle composition. The models were controlled for sex and age (in months). The assumptions of normality and independence of the residuals were verified in the Euclidean space of the ilr coordinates.

The overall significance of each predictor on the total composition was assessed using a Type II MANOVA (Pillai‐Bartlett Trace) test with the car package. In cases of overall significance, the regression coefficients (β) for each ilr coordinate were examined to identify the direction and magnitude of the effect on the specific behaviours. Analyses were performed in RStudio (version 2025.09.2 + 418) using the Compositions, Car, and ggtern packages.

3. Results

A final sample of 112 out of 135 eligible preschoolers (83% participation rate) with an average age of 45.32 ± 6.40 months (50.9% girls) and with valid accelerometry data was included in the analysis.

The preschool environment domains showed heterogeneity among the evaluated ECECCs (Table 1). Of the standardized scores (Z‐scores), the outdoor infrastructure showed the greatest dispersion (range: −0.92 to 1.91), followed by the indoor equipment (−1.87 to 1.20). Sleep was the predominant behaviour within a 24‐h composition, with an average of 781.69 min/day. During the waking period, SB occupied most of the time (480.80 min/day), while MVPA represented the smallest proportion of the day, with an average of 81.27 min/day (Table 1).

TABLE 1.

Characterization of the sample and 24‐h composition.

Variable M ± SD) Range (Min‐Max)
Age (months) 45.7 ± 6.47 36–59
School Environment (z‐score)
Teacher Role 0.03 ± 0.3 −0.9‐0.86
Teacher Training and Education for Family −0.05 ± 0.74 −1.37‐1.69
School Policy −0.01 ± 0.58 −0.59‐2.26
Outdoor equipment 0.05 ± 0.79 −1.72‐1.27
Indoor equipment −0.04 ± 0.9 −1.87‐1.2
Outdoor infrastructure 0.02 ± 0.62 −0.92‐1.91
24‐h Movement Behaviours Composition (a) (M)

Total Sample

n = 112

Boys

n = 55

(49.1)

Girls

n = 57

(50.9)
LPA 96.24 94.82 97.62
MVPA 81.27 85.85 76.86
SB 480.80 475.22 486.18
Sleep 781.69 784.12 779.34
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Note: M Mean; SD: Standard deviation; a: 24‐h compositional mean normalized to 1440 min); b: Environment indices are standardized (Z‐scores) and their ranges (minimum and maximum) are reported to illustrate the variability observed in educational centres. LPA: Level Physical Activity. MVPA: Moderate to Vigorous Physical Activity. SB. Sedentary Behaviour.

The variation matrix revealed a greater proportional stability (var = 0.054) in the relationship between LPA and SB, suggesting a strong co‐dependency between these two behaviours in the preschool setting. Conversely, the relationship between MVPA and sleep showed the greatest relative instability (var = 0.193), indicating that changes in MVPA had a more heterogeneous and less predictable relationship with sleep duration in this group of preschoolers (Table 2).

TABLE 2.

Variation matrix between 24‐h composition.

Behaviour pairs Log‐ratio (a) variance Interpretation
LPA—SB 0.054 Maximum stability
SB—Sleep 0.069 High stability
MVPA – LPA 0.082 Moderate stability
LPA—Sleep 0.102 Low stability
MVPA—SB 0.149 Hight variability
MVPA—Sleep 0.193 Maximum variability
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Note: a (log‐ratios): variation matrix; Lower values indicate greater proportional stability (synchrony) between activities. Values close to 0 indicate greater proportional stability. LPA: Level Physical Activity. MVPA: Moderate to Vigorous Physical Activity. SB. Sedentary Behaviour.

The multivariate regression model applied to the ilr showed that Outdoor Equipment score was the only predictor of the preschool environment, significantly associated with the 24‐h compositional structure (F = 3.40; p = 0.020) (Table 3). Analysis of specific coordinates revealed that this score showed a positive association with coordinate ilr 1 (MVPA vs. Rest of the Day: β = 0.10, p = 0.027). Moreover, girls exhibited a significantly higher proportion of MVPA in their 24‐h composition compared to boys, after adjusting for environmental variables (β = 0.09, p = 0.019). These associations are visualized in the Forest Plot (Figure 1), where Outdoor Equipment and sex (female) are the only variables whose 95% confidence intervals lie entirely to the right of the null line.

TABLE 3.

Multivariate regression model for the preschool‐built environment, adjusted for age and sex.

Dimensions Index of the school environment F (Wilks) p
Teacher Role 0.722 0.541
Teacher Training and Education for Family 0.337 0.799
School Policy 0.169 0.917
Outdoor equipment 3.400 0.020
Indoor equipment 0.466 0.707
Outdoor infrastructure 0.785 0.505
Sex 2.243 0.093
Age (months) 0.958 0.416
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Note: F Wilks statistic/F‐ratio), quantifies the magnitude of the relationship between the predictor and the day composition; Values in bold indicate statistical significance (p < 0.05).

FIGURE 1.

FIGURE 1

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Association between the domains of the preschool environment and the compositional coordinate Ilr1 (MVPA vs. Rest of the day).

No significant associations were found between the other domains of the preschool environment and the remaining coordinates (ilr 2 and ilr 3 ) (Table 4).

TABLE 4.

Association between the dimensions of the school environment and the composition of the 24‐h cycle: Results of the multivariate linear regression model on isometric logarithmic coordinates (ilr).

Predictor (Domains School Environment/Covariate) ilr1 (MVPA vs. Rest) ilr2 (LPA vs. Stationary) ilr3 (SB vs. Sleep)
β (p) β (p) β (p)
Teacher Role 0.06 (0.502) −0.07 (0.496) −0.03 (0.790)
Teacher Training and Education for Family 0.01 (0.751) 0.02 (0.741) −0.04 (0.548)
School Policy
Outdoor equipment 0.05 (0.492) 0.03 (0.778) 0.04 (0.727)
Indoor equipment 0.10 (0.027) 0.07 (0.198) −0.07 (0.294)
Outdoor infrastructure Sex (Girls) −0.03 (0.450) −0.02 (0.580) 0.02 (0.682)
Age (months) −0.08 (0.187) −0.01 (0.857) 0.00 (0.998)
0.09 (0.019) 0.07 (0.165) 0.00 (0.922)
−0.00 (0.207) 0.00 (0.845) −0.00 (0.977)
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Note: n = 112. β: represents the unstandardized regression coefficients. Movement behaviours were transformed using isometric log coordinates (ilr) following a sequential binary partition: ilr 1 represents the time spent in MVPA relative to the geometric mean of the remaining behaviours (LPA, SB, and Sleep); ilr 2 represents the time spent in LPA relative to the stationary behaviours (SB and Sleep); ilr 3 represents the balance between SB and Sleep. Model fitted for all listed variables. The sex variable refers to males. Values in bold indicate statistical significance (p < 0.05).

4. Discussion

The present study aimed to identify the association between the preschool environment and 24‐h movement behaviours in Uruguayan preschoolers based on the analysis the composition data. The main finding highlighted the positive association between Outdoor Equipment (availability, quantity and accessibility for preschoolers) and MVPA in Uruguayan preschoolers.

The availability, quantity and accessibility of the outdoor equipment for preschoolers, act as the strongest predictor of shifting daily activity levels toward high‐intensity PA. These findings are consistent with international scientific evidence confirming an association positive between the availability and number of play structures and MVPA (Vilar Pereira et al. 2024). Specifically, our results support the premise that outdoor equipment acts as a predictor of shifting daily activity levels toward higher intensity and a reduction in SB. This result reinforce the idea that the material configuration of the outdoor space influences children's autonomous movement decisions and individual health behaviours (Sallis et al. 2006). By considering equipment as one of the possible resources to improved PA levels, this study reinforces the need to view them as a tool for public health intervention. Consequently, ECEC centers and educational authorities should prioritize optimizing the quality, variety, and physical accessibility of outdoor play structures. Enhancing these supportive outdoor features to promote physical activity may yield indirect benefits for children's holistic development, particularly by supporting behavioural and psychosocial self‐regulation, cognitive function, and emotional well‐being in early childhood (Cecic‐Mladinic et al. 2026; D'Cruz et al. 2024).

Results showed no association between movement composition and school policy, teacher role, or pedagogical climate. These finding are supported by current evidence, which shows the absence of key correlates at the institutional level (such as written policies) that consistently influence children play or outdoor time (Lee et al. 2021). Similarly, it has been reported that most interventions based exclusively on the preschool curriculum have struggled to produce significant changes in physical behaviour (Larouche et al. 2023). This pattern is consistent with the findings reported by Sisson et al. (2016), who also conclude that the availability of physical equipment for movement are stronger predictors of PA than written school policies. Furthermore, the external environment provides diverse and dynamic stimuli (i.e., play structures, natural elements) that inspire spontaneous and self‐directed active play (Lee et al. 2025). This relevance of outdoor equipment becomes highly relevant, where the scarcity of structured PA extra‐curricular programs or the absence of physical education classes means that these resources are the only constant stimulus for PA for preschool children within the preschool context. However, the absence of statistically significant associations among these variables must be interpreted with caution and does not necessarily imply the absence of a real‐world relationship. Moreover, the institutional policies designed to mandate active opportunities or teacher practices that actively encourage movement would theoretically be expected to be foster higher PA levels. The lack of statistical significance in our study may stem from methodological constraints, such as samples size limitations, potential ceiling effects in self‐reported policy compliance, or the need for instruments with higher sensitivity to capture the qualitative nuances of daily policy implementation and teacher‐child interactions.

Initial descriptive data indicated that boys accumulate a greater minutes of PA that girls, which aligns with international literature on the marked gender difference, as being a girl is consistently identified as negative correlatee for total outdoor time and active play (Larouche et al. 2023). In Uruguay, this disparity in PA is algo evident and significant, although studies focus on children and adolescents (Brazo‐Sayavera et al. 2023). However, the adjusted multivariate regression model revealed that girls exhibit a higher relative proportion of MVPA within their 24‐h structure. This apparent discrepancy may indicate that, after adjusting for the preschool environment, Uruguayan girls exhibit a higher relative proportion of MVPA within their 24‐h movement composition compared by boys. Our findings suggest that, although girls may accumulate less total movement time, MVPA represents a relatively greater share of their daily movement behaviours, particularly in outdoor environments with equipment.

This may be due to the potential of diverse infrastructure, where in natural, green, or equipment‐rich environments, PA levels between boys and girls tend to equalize by providing diverse stimuli, leading to opportunities for creative and symbolic play—areas where girls show a greater inclination toward and use of space‐ (Haase 2026). In turn, this finding can be supported by the fact that some environmental modifications, such as in the outdoor environment, have a positive impact specifically on increasing girls PA, therefore, a well‐designed environment can be a tool for equity (Vilar Pereira et al. 2024).

In this sense, the outdoor equipment available at the analysed centres in Uruguay, could be acting as a levelling factor, mitigating traditional gender barriers and promoting more equitable participation in high‐intensity play. These results underscore the need to evaluate not only the amount of time spent playing, but also the internal structure of daily activities to capture the true dynamics of children's behaviour. The CoDA analysis revealed what traditional analysis may have obscured: that the environment can be an agent of gender equity.

This study presents some limitations. First, a local sample, which is not representative of the entire country, nor is the number of participants or the number of centres, was recruited; therefore, generalizations should be made with caution. Second, being a cross‐sectional study, a definitive causal relationship between the equipment and MVPA cannot be established, only a robust association. Third, although the instrument used to assess the environment has been validated internationally, cross‐cultural adaptation and validation within the Uruguayan context remain necessary. Finally, the assessment of the preschool environment relied on a self‐administered audit completed by centre directors and coordinators, which may introduce potential response or reporting bias. Although this method allowed for a standardized collection of institutional data, future studies should consider integrating independent, direct observational tools to complement staff reports.

However, this study has several strengths that should be considered. The use of accelerometry as an objective measure of 24‐h movement behaviours allows for the capture of intensities that parental reports often omit. The use of CoDA in this study overcomes the limitations of traditional linear statistics, which ignore the interdependence of the 24‐h period. Another strength is the socio‐ecological approach, which is not limited to the child but includes the preschool environment, allowing for public policy recommendations based on real infrastructure.

5. Conclusions

This research demonstrates the importance of the preschool physical environment in promoting an active lifestyle. Outdoor equipment (availability, quantity and accessibility for preschoolers) emerges as the relevant factor in shifting the daily schedule toward periods of healthy movement, in addition to acting as a levelling element that encourages girls' participation in vigorous activities. It is concluded that preschool health policies in Uruguay, must guarantee direct investment in tangible and accessible material resources in outdoor play areas. Optimizing the 24‐h timeframe in early childhood requires a holistic perspective. This approach should integrate improvements to the built environment within the preschool setting with the implementation of strategies focused on integral behavioural patterns and opportunity for physical development and health in childhood.

Author Contributions

Franco Souza‐Marabotto: data curation, investigation, writing – review and editing, writing – original draft. Clarice L. Martins: validation, supervision, writing – review and editing, writing – original draft. Sofia Fernandez‐Gimenez: conceptualization, methodology, data curation, investigation, validation, formal analysis, writing – original draft, writing – review and editing, project administration. Enrique Pintos‐Toledo: data curation, investigation, project administration, writing – review and editing, writing – original draft. Javier Brazo‐Sayavera: conceptualization, data curation, validation, supervision, methodology, project administration, writing – review and editing, writing – original draft.

Funding

The authors wish to thank the Sistema Nacional de Investigadores (SNI) and Universidad de la Republica for their partial funding of this study. The funding entity's role consisted of providing human resources for data collection, analysis, and interpretation, as well as some material resources.

Ethics Statement

All the authors confirm that the study was conducted in accordance with the ethical principles for medical research involving human subjects as outlined in the Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Ethics Committee of the University Centre of the North Littoral Region of the University of the Republic (Exp. No. 311170–000102‐23).

Consent

Informed consent was obtained from the parents or legal guardians of all participating children prior to their inclusion in the study.

Conflicts of Interest

The authors declare that they have no conflicts of interest related to the research, authorship, or publication of this article.

Supporting information

Data S1: Internal consistency and statistics of the items of the scores of the school environment.

CCH-52-e70341-s001.docx (23.8KB, docx)

Acknowledgements

The authors thank the members of the Human Performance Research Group for their collaboration in data collection. We express our sincere gratitude to the preschools, teachers, and families for their participation. We also thank international advisor Dr. Anthony David Okely for his valuable guidance and support throughout the study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1: Internal consistency and statistics of the items of the scores of the school environment.

CCH-52-e70341-s001.docx (23.8KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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