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1. Introduction
Considering the objective of teaching children’s holistic development [1], the syllabus establishes a mark of reference, divided into three different ranges, based on children’s age and capacities. Currently, the division of compulsory education determines the ranges from 0 to 6 years as the early childhood education or preschool stage, from 6 to 12 years as primary or elementary education, and finally, from 12 to 16 years as the stage of secondary education. All of these stages represent a fundamental role in children’s development, although education with preschool-aged children may assume an added value due, among others physiological issues related to brain development, to the amount of neural connections that arise during the first years of life [2,3].
The educational process during preschool, as during other stages, does not consist simply of memorizing new concepts, but also of developing critical thinking, observing, listening, having experiences, feeding curiosity, and above all, encouraging integral personal development [1]. In this regard, physical education (PE), or any other referring term such as “physical play”, “exercise”, “health and well-being”, or “physical development and movement” [4], is an interesting subject that includes the opportunity to foster all of these areas, which all work to ensure that every child is emotionally, cognitively, and physically well [5]. In fact, this subject presents a great opportunity to make children adhere to health-related habits. Since the exponential growth of investigations aimed at demonstrating the positive influence of reducing sedentary behavior [5,6], the benefits of engaging in physical activity (PA) have been widely recognized. In particular, it contributes to lowering the likelihood of developing non-communicable chronic conditions such as type 2 diabetes, metabolic syndrome, and cardiovascular pathologies [7,8,9,10], and promotes physiologically related factors (e.g., greater bone mass index or lower fat mass) [10,11,12,13], as well as contributing to mental health, socialization, and emotional intelligence [14,15,16].
Fortunately, large numbers of children are attending preschools or kindergartens, giving teachers the possibility to adjust the amount of children’s PA to the guidelines established by different countries and organizations [17,18]. For example, the World Health Organization suggests 180 min of PA at different intensities and in different kinds of exercises [19]. Current PA guidelines, including those from the American Academy of Pediatrics, advocate that children under the age of six should accumulate at least three hours of PA daily, which equates to approximately 15 min per waking hour [20], while another based on waking hours recommends between 10,000 and 14,000 steps per day [21]. To a greater extent, and differing between ages, the National Association for Sport and Physical Education (NASPE) emphasizes the importance of engaging in broad, developmentally appropriate movement experiences during the early stages of childhood. For children aged one to three years, it is recommended that they engage in a minimum of 30 min of structured physical activities alongside at least 60 min of unstructured, spontaneous play each day with no more than 60 min of recess. Finally, children under six years of age should perform 60 min for each kind of these activities [22].
However, the time that children invest outside of school does not seem to contribute to meeting the suggestions provided by these guidelines. In fact, it has been highlighted that up to 81% of children are inactive globally [23], maybe aggravated by the high amount of screen time that children face every day [6], especially during weekend days when there are no classes. Thus, it is crucial to investigate their daily habits, whether there exist significant differences between weekdays and weekend days, and to determine what factors should be considered to foster PA habits during both weekdays and weekend days. A systematic review aimed at analyzing this issue could shed light on the necessity to look for solutions.
To date, given the importance of highlighting the levels of PA using objective methods, the exponential growth of technological devices has allowed professionals to analyze and measure children’s PA not only during school hours, but also out of school [24]. In fact, their empirically demonstrated validity and reliability highlight accelerometers as one of the most suitable tools for measuring PA in preschool settings [25].
Nonetheless, to the best of the authors’ knowledge, although various individual studies have attempted to explore this topic, there is still a lack of a comprehensive systematic review that synthesizes the existing body of evidence. Accordingly, the purpose of this study was to systematically compile and examine the scientific literature comparing PA patterns in preschool-aged children between weekdays and weekend days, based on data collected through technological monitoring devices, and highlight what factors correlate with children’s PA. This article aims to benefit teachers and professionals working with preschool-aged children to foster PA habits and adhere them to positive life habits from early years, which is supposed to be a crucial moment in a person’s lifespan. In fact, comparing PA during weekdays and weekend days could shed light on where professionals and policymakers should establish new considerations, while highlighting which factors correlate with them could show trends that could be considered by teachers and parents.
2. Materials and Methods
2.1. Experimental Approach to the Problem
This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework [26] in conjunction with established methodological recommendations for systematic reviews within the field of sports sciences [27].
2.2. Information Sources
A comprehensive search strategy was implemented across four electronic databases—PubMed and FECYT (which includes Web of Science, CCC, CIDW, KJD, MEDLINE, RSCI, and SCIELO)—to identify relevant studies published up to 21 April 2023.
2.3. Search Strategy
The Patient, Problem or Population–Intervention or Exposure–Comparison, Control or Comparator–Outcome[s] (PICO) design was explicitly used to state the question. The search strategy was used in the databases mentioned above. Where possible, the search was limited to scientific studies/journals and language (see exclusion criteria number 6). No lower date limit was applied for publication. The following search terms were used (see Table 1):
(Preschool OR kindergarten OR “early childhood”) AND (“microelectromechanical system *” OR MEMS OR gyroscope OR magnetometer OR accelerometer * OR wearable * OR pedometer OR “heart rate”) AND (“PA” OR sedentary)
2.4. Selection Process
To extract relevant information, the author recorded key data from each article (including title, authorship, publication date, and source database) into a Microsoft Excel spreadsheet (Microsoft Corporation, Redmond, WA, USA). Duplicate entries were subsequently removed. The remaining records were then screened based on the predefined inclusion and exclusion criteria (see Table 1). Additionally, other pertinent studies not initially captured through the database search were assessed following the same procedure and, if eligible, were incorporated under the label included from “external sources”.
2.5. Data Extraction
The Cochrane Consumers and Communication Review Group’s data extraction template was prepared using an Excel spreadsheet. The spreadsheet assessed inclusion and exclusion requirements for all selected studies. Full-text studies excluded from the analysis were recorded with reasons for exclusion. All records were stored in the spreadsheet. In this process, the authors who decided whether an article should be included or excluded disagreed in one study. For this reason, the third author agreed that both should be included because they met all the inclusion criteria.
The following information was provided: (i) sample characteristics, (ii) PA levels during weekdays and weekend days, (iii) duration of data collection, (iv) type and model of technological device used, (v) main findings, and (vi) study conclusions.
2.6. Quality of Studies
Methodological quality was evaluated using the Methodological Index for Non-Randomized Studies (MINORS) [28]. The MINORS scale consists of 8 core items, extended to 12 for comparative studies. In the present review, methodological quality was assessed using 9 applicable items (maximum score: 18 points), as three items were deemed not applicable (NA). Each item is scored from 0 to 2, reflecting the level of methodological quality (2 = high, 1 = moderate, 0 = low).
3. Results
3.1. Identification and Selection of Studies
A total of 1959 original articles were retrieved (Web of Science: 1196; PubMed: 763), from which 738 duplicates were removed, resulting in 1221 unique records. Following title and abstract screening, 1045 articles were excluded for not meeting inclusion criterion five. The full text of the remaining 176 articles was reviewed, leading to the exclusion of 12, 112, and 21 articles based on exclusion criteria one, two, and four, respectively. Additionally, one study was excluded due to a low-quality rating according to the MINORS checklist. Consequently, 30 articles fulfilled all inclusion criteria and were incorporated into the final qualitative synthesis (see Figure 1).
3.2. Quality Assessment
Table 2 presents the methodological assessment of the 30 studies retained in the final synthesis, based on the Methodological Index for Non-Randomized Studies (MINORS). The overall methodological quality of the included studies can be classified as moderate to high. Total MINORS scores ranged from 14 to 18 points, with a maximum possible score of 18. The mean score across all studies was 16.7 (±1.1), with a median value of 17. Using a cut-off point of ≥17 to denote high methodological quality, 60% of the studies (n = 18) were categorized as high quality, while the remaining 40% (n = 12) fell into the moderate quality range. Importantly, none of the studies met the criteria for low quality (i.e., scores below 14).
Most studies received the maximum score (2 points) in the initial MINORS domains, including the presence of a clearly stated aim, consecutive inclusion of participants, prospective data collection, the use of endpoints appropriate to the study objective, and unbiased assessment of the study outcome. These consistently high scores suggest good adherence to fundamental principles of observational research. Similarly, most studies demonstrated low rates of attrition or missing data, with the majority reporting less than 5% loss to follow-up, which supports the reliability of accelerometer-based assessments and the internal validity of the findings.
Despite these strengths, certain limitations were recurrent across the included literature. The most frequently downgraded item was the adequacy of the follow-up period in relation to the study aim. This reflects the predominance of cross-sectional designs or studies employing very short monitoring periods—typically one week or less—which may not capture habitual patterns of behavior or account for seasonal variability. Additionally, few studies provided a fully justified prospective sample size calculation. In approximately half of the cases, partial justification was given (e.g., citing previous literature), while the remaining studies offered no power analysis at all. Furthermore, the final three MINORS items related to the comparability of groups (items 8 to 10) were not applicable to most studies, given the observational, single-cohort design adopted across the review.
In summary, the quality of the included studies was generally robust in aspects related to internal validity and data completeness, supporting confidence in the findings derived from weekday and weekend PA comparisons. However, the limited duration of observation periods and the absence of formal sample size planning in several studies should be taken into account when interpreting the generalizability and reproducibility of the reported effects.
The results of the methodological quality assessment are presented in Table 2.
3.3. Study Characteristics
3.3.1. PA on Weekdays and Weekends
A total of 30 studies compared PA and/or sedentary behavior (SB) across weekdays and weekend days in preschool children. Among these, a substantial proportion reported higher PA or lower SB during weekdays. These differences were often attributed to the structured nature of school routines, which encourage regular activity through scheduled recesses and reduced opportunities for prolonged inactivity. For instance, Berglind and Tynelius [35] found that sedentary behavior accounted for 91.9% of total time on weekdays, increasing to 96.9% on weekends, while moderate-to-vigorous PA (MVPA) dropped from 6.3% to 2.0% between the two periods. Díaz-Quesada et al. [20,46] observed consistent weekday increases in step counts, with school-time activity levels notably surpassing those recorded during after-school hours and weekends.
In contrast, a smaller subset of studies documented higher PA or lower SB during weekends. These patterns were typically associated with greater parental involvement and opportunities for unstructured or outdoor play. For example, Eichinger et al. [32] found that participation in organized sports and parental perceptions of traffic safety were positively associated with weekend MVPA and total PA. Similarly, Hnatiuk et al. [54] reported that walking or cycling with a parent during weekend leisure was positively correlated with both children’s and mothers’ MVPA.
Nevertheless, the majority of studies did not report consistent differences between weekdays and weekends. Many observed either no significant variation or mixed results, depending on individual factors.
3.3.2. Parental/Maternal Behavior and PA During Weekdays and Weekends
Parental PA and sedentary behavior were consistently associated with corresponding patterns in their children. Multiple studies confirmed that both maternal and paternal behaviors play a significant role, although the timing and strength of their influence varied. Carson et al. [37] and Hnatiuk et al. [54] found that maternal activity was more strongly related to children’s weekday PA, while paternal activity was more influential during weekends. Díaz-Quesada et al. [20,46] corroborated this pattern, reporting distinct parental effects depending on the time of the week.
In terms of sedentary behavior, Määttä et al. [31] observed that children of fathers with intermediate educational levels had significantly lower sedentary time on weekends. Additionally, screen time was notably higher among children of less educated parents, particularly mothers, as documented by McKee et al. [40]. These results suggest that parental education, lifestyle, and engagement directly shape the movement behaviors of preschoolers.
Moreover, some studies emphasized the role of co-participation in activity. Hnatiuk et al. [54] highlighted that walking or cycling with children was a strong predictor of weekend MVPA for both children and parents. Conversely, frequent indoor play center visits were associated with decreased MVPA in both groups. Collectively, these findings reinforce the role of family-based strategies in promoting PA, especially on less structured days.
3.3.3. Gender as a Correlate for PA During Weekdays and Weekends
Sex-related differences in PA were a recurrent theme across the included studies, with boys generally exhibiting higher PA levels and lower sedentary behavior than girls, regardless of the day type. In the work by Roscoe et al. [24,44], boys averaged 72 min of MVPA per day compared to 62 min in girls, with both groups showing reduced PA during weekends. Similarly, Díaz-Quesada et al. [20,46] reported that boys engaged in more prolonged bouts of MVPA and accumulated higher step counts throughout the week.
Further distinctions emerged in the nature of activity engagement. Blaes et al. [41] found that boys consistently outperformed girls in object-control motor tasks and accumulated more MVPA during school hours. Conversely, girls demonstrated superior balance skills but recorded lower overall PA levels. In the study by Wang et al. [53], girls were particularly sensitive to the preschool environment, showing greater variability in activity based on institutional context, suggesting that environmental design may interact with sex in determining activity patterns.
Interestingly, some studies noted minimal or no sex differences. For instance, Pate et al. found no significant variation between boys and girls in MVPA compliance, although overall PA levels were generally low. These mixed findings indicate that while sex is a relevant correlate, its influence may be moderated by environmental, cultural, or educational factors.
3.3.4. Other Correlates of PA on Both Weekdays and Weekends
Beyond sex and parental influence, several additional correlates emerged as relevant in explaining differences in PA patterns. Socioeconomic status (SES), educational setting, seasonal variation, motor competence, and environmental perception were all identified as influential. For example, children attending Montessori preschools demonstrated significantly higher in-school MVPA compared to those in traditional settings, indicating that pedagogical structure may affect activity engagement.
Other contextual elements, such as perceived safety, access to public facilities, and proximity to recreational areas, were positively associated with PA levels. Eichinger et al. [32] found that community safety perceptions and active transportation infrastructure correlated with increased MVPA in boys during weekdays and with light PA in girls on weekends. Seasonal factors were also relevant: children recorded 2000 fewer daily steps in winter than in spring, with step count increases of 2300 steps observed in children aged from 4 to 5 years.
Lastly, motor skill proficiency emerged as a partial determinant of PA. Studies noted that greater locomotor and object-control skill development was associated with higher MVPA, particularly on weekends. However, the association was inconsistent across weekdays, suggesting that skill development may interact with available time and environmental constraints to modulate activity behavior.
The characteristics of studies were extracted and clustered into Table 3.
4. Discussion
The primary objective of this systematic review was to synthesize and critically evaluate empirical studies examining PA patterns in preschool children during weekdays and weekends, utilizing technological monitoring devices, and highlight which factors correlate with children’s PA. The following lines summarize the main categories of analysis.
4.1. PA on Weekdays and Weekends
Research demonstrates that young children engage in greater amounts of active behaviors and exhibit reduced sedentary time on weekdays relative to weekend days [20,39,41,43,44,45]. The literature identifies patterns in PA levels during weekdays, highlighting the influence of both school hours and after-school periods on overall activity levels [45]. The reasons for this trend are mainly due to the presence of PA during school hours [20,41], a greater presence of preschoolers in outdoor environments during Early Childhood Education and Care (ECEC) hours [47], or the participation of children in after-school activities organized in the framework of sports [43].
On the contrary, although to a lesser extent, other studies have found a different trend. Some studies have reported comparable PA levels between weekdays and weekends [38,48,49]. Greater PA has been shown on weekend days compared with weekdays, and children spend longer sitting on weekdays compared with weekends [42,57].
However, the majority of studies did not report consistent differences between weekdays and weekends. Many observed either no significant variation or mixed results depending on contextual or methodological factors. Several studies suggested that activity levels may be influenced less by the day of the week and more by setting-specific or individual variables. These inconsistencies highlight the need to account for mediating factors when comparing PA patterns across different day types. This led authors to the need to highlight those correlated factors that could foster PA habits from early childhood.
4.2. Parental/Maternal Behavior and PA During Weekdays and Weekends
Parental/maternal sedentary behavior and PA levels exert a significant influence on those of their preschool-aged children [50,58]. Some research has found associations between weekday and weekend parental/maternal behavior with different impacts on PA levels among boys and girls [55]. Studies have demonstrated that weekend physical activities shared by parents and children, such as walking and cycling, are positively correlated with higher PA levels in children [54]. Carson et al. [58] reported that the relationships between parental sedentary behavior and PA and those of their children were consistent across weekdays and weekend days. According to sedentary behaviors, the time spent screen-viewing by both parents is strongly associated with the time the child spends screen-viewing [59], as well as during the school day; preschool-aged children allocate a substantial portion of their time to sedentary activities such as drawing, listening to music, reading, or engaging in non-academic after-school activities, including screen time [48].
These results suggest that parental education, lifestyle, and engagement directly shape the movement behaviors of preschoolers. Consequently, it is advisable to critically examine both the curricular practices implemented within ECEC settings and the duration of children’s screen time at home.
4.3. Gender as a Correlate for PA During Weekdays and Weekends
This systematic review identified two distinct patterns concerning the association between gender and PA across weekdays and weekends. Several studies have identified gender as a significant correlate influencing PA behaviors in ECEC settings, during both weekdays and weekends [33,34,41,45,49,51,60]. Overall, boys participated in higher levels of MVPA and total PA, and exhibited less sedentary behavior than girls across weekdays, weekends, or both. Specifically, boys engaged in more MVPA and light-to-moderate PA during weekdays, as well as increased MVPA on weekends, compared to girls [33,49]. Additionally, several studies have reported associations involving parental and child PA differentiated by gender [55], links between public activity facilities, gender, and children’s PA [53], as well as gender-related variations in motor competence and daily activity patterns [35].
By contrast, other research has not found any relationship between gender and PA [20,42,43,48]. These studies point out that other personal factors, rather than gender, may explain PA patterns.
4.4. Other Correlates of PA on Both Weekdays and Weekends
Additional research has concentrated on examining the relationship with other factors, such as PA levels and motor competence [24,33,57] and with BMI [51]. For instance, Bellows et al. [57] reported that the association between step counts and gross motor skills was evident only on weekend days, not weekdays. Additionally, locomotor skill competency was positively correlated with moderate-to-vigorous PA during weekdays and with light PA on weekends. Based on BMI classifications, Tanaka and Tanaka [51] observed that thinness was linked to reduced engagement in light, moderate, and vigorous PA among Japanese preschool children. However, in addition to these factors related to motor competence and morphology, different studies have highlighted correlates with the type of activity (indoor vs. outdoor) [47], age [48], meeting of PA guidelines [24,52], and the community transportation environment [53]. Nonetheless, further investigations into these or related associations remain limited in the literature.
4.5. Limitations Related to Measurement Methods
The ability to extract objective measures through technological devices has led to a reevaluation of traditional assessment methods like observational techniques and parental reports, which are thought to have limitations like the lack of precision needed for in-depth analysis [36,37]. As in this systematic review, where most of the articles used accelerometers (three articles used pedometers and two heart-rate monitors; the remaining article used accelerometers), the PA data extracted from microelectromechanical devices such as accelerometers has experienced an exponential growth [61,62].
However, the measures through accelerometers should be considered with caution since different issues, such as sampling frequency [63,64] or the used algorithm [64] can affect the extracted data, and most of the articles do not provide the most important information. In fact, the validity and reliability of accelerometers could change in different circumstances, making validation difficult to extrapolate if the environment changes from the validation study to the place where the data will be extracted. In this way, the authors encouraged the use of previously published surveys [64] to warrant the inclusion of relevant information when using technological devices.
5. Conclusions
Although it could be a trend that supports that PA level is greater during weekdays, several articles suggest that it depends on contextual or individual factors than on the day of the week. These inconsistencies highlight the need to account for mediating factors when comparing PA patterns across different day types: -. Parental/maternal influence: parental/maternal influence has been highlighted as crucial due to the established relationship between parental/maternal sedentary behavior, shared activities during weekend days (walking or cycling), parents’ educational level, and parental/maternal screen time. -. Gender influence: although several studies reflect a different trend in PA amount and type between girls and boys, some others highlight that it does not influence, suggesting that other factors, rather than gender, could influence the adherence to PA level. -. Other influences: other factors suggest that morphology, motor competence level, the type of activity (indoor vs. outdoor), age, meeting of PA guidelines, and the community transportation environment [53] could influence PA levels. However, since there are few studies that establish such correlations, these results should be considered with caution, awaiting future studies that corroborate them.
6. Practical Applications for the Teachers in Early Years
All these conclusions lead the authors to provide some key areas for improvement, considering recommendations from ECEC during weekdays and for parents during both weekdays and weekend days.
Recommendations to consider from ECEC: Taken together, the analysis of the results indicates that the ECEC context is an appropriate environment for children to accumulate opportunities for movement that translate into higher levels of PA during the school day (weekdays) compared to the weekend. In those cases where this does not occur, curricular practices should be reviewed because it is possible that they encourage sedentary behaviors rather than active ones. ECEC settings should serve as compensatory environments addressing the deficits in work-family balance that limit children’s opportunities for physical, natural, and social exploration through movement. In fact, for families that cannot offer positive PA contexts, the ECEC institution must act as a compensator or promoter of this inequality.
Recommendations for parents/mothers: During weekend days, it can be considered that, at least during early childhood, healthy habits are primarily learned by imitation. In this sense, adults act as role models in this way. As a result, children who are active during their early years typically continue to be active throughout their lives. For this reason, while ECEC environments play a key role in educating active behavior during the week, at the weekend, more examples of active behavior by families translate into elevated PA levels. In this regard, another strategy could be involving children in extracurricular activities that establish activity not only during weekdays, but also during weekend days. In fact, during both weekdays and weekend days, children should follow those recommendations established by PA guidelines, such as WHO guidelines, that suggest, at least, 30 min in tummy time position for infants (
In summary, preschool environment and parental influence constitute key factors in fostering PA during early childhood. Therefore, communication between families and schools in the ECEC context should be bidirectional: sharing information and resources to create or reinforce those practices that promote active behaviors. Specifically, disparities in PA levels between girls and boys could be explained more through socializing factors (both during the week as a consequence of ECEC attendance and at the weekend through the proposals offered by families to children). In this sense, young children, but particularly young girls, should be encouraged to participate more in PA on weekdays and weekends and be provided with ample opportunities for practice and instruction to develop fundamental motor skill competence.
Conceptualization, V.M.-B. and R.M.-M.; methodology, A.M.-V. and M.R.-G.; software, A.M.-V. and M.R.-G.; validation, A.M.-V., V.M.-B. and R.M.-M.; formal analysis, A.M.-V. and M.R.-G.; investigation, M.R.-G.; resources, V.M.-B. and A.M.-V.; writing—original draft preparation, M.R.-G. and R.M.-M.; writing—review and editing, A.M.-V. and M.R.-G.; supervision, R.M.-M. All authors have read and agreed to the published version of the manuscript.
The authors declare no conflicts of interest.
Footnotes
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Figure 1 Flow diagram of the study.
Eligibility criteria for the inclusion and exclusion of studies.
| Item | Inclusion | Exclusion | Search Coherence |
|---|---|---|---|
| Population | Preschool children | Children beyond preschool age (e.g., primary or secondary education). | Preschool OR kindergarten OR “early childhood” |
| Intervention or Exposure | Measuring PA through big data technologies. | Measuring PA with questionnaires. | “microelectromechanical system *”, MEMS, gyroscope, magnetometer, accelerometer *, wearable *, pedometer, “heart rate” |
| Comparison | Comparing PA in weekdays vs. weekend days. | No comparison was made between weekdays and weekend days. | |
| Outcome[s] | PA-related outcomes. | Non-PA variables or studies lacking outcome data (e.g., protocols). | “PA”, sedentary |
| Study design | No restriction | - | - |
| Other criteria | Original, peer-reviewed full-text articles published in English or Spanish. | Articles in languages other than English or Spanish, or not peer-reviewed full-text originals. | - |
Note: The addition of “*” refers to the inclusion of the plural of the term it accompanies.
Methodological assessment of the included studies.
| References | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| van Ekris et al. [ | 2 | 2 | 2 | 2 | 2 | 1 | 2 | NA | NA | NA | 1 | 2 | 16/18 |
| Van Stappen et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 18/18 |
| Määttä et al. [ | 2 | 2 | 2 | 2 | 2 | 1 | 2 | NA | NA | NA | 2 | 2 | 17/18 |
| Eichinger et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 1 | NA | NA | NA | 2 | 2 | 17/18 |
| Foweather et al. [ | 1 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 1 | 2 | 16/18 |
| Quan et al. [ | 2 | 2 | 1 | 2 | 2 | 2 | 2 | NA | NA | NA | 1 | 2 | 16/18 |
| Berglind and Tynelius [ | 2 | 2 | 2 | 2 | 1 | 2 | 2 | NA | NA | NA | 2 | 2 | 17/18 |
| Chen et al. [ | 2 | 2 | 2 | 1 | 2 | 2 | 1 | NA | NA | NA | 2 | 2 | 16/17 |
| Carson et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 18/18 |
| Díaz-Quesada et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 18/18 |
| Benham-Deal [ | 2 | 2 | 2 | 1 | 2 | 2 | 1 | NA | NA | NA | 2 | 2 | 16/17 |
| Olesen et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 1 | NA | NA | NA | 1 | 2 | 16/18 |
| McKee et al. [ | 2 | 2 | 2 | 1 | 2 | 2 | 1 | NA | NA | NA | 2 | 2 | 16/18 |
| Blaes et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 18/18 |
| Roscoe et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 1 | 2 | 17/18 |
| Aguilar-Farías et al. [ | 2 | 2 | 2 | 2 | 1 | 2 | 2 | NA | NA | NA | 2 | 2 | 17/18 |
| Bergqvist-Norén et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 1 | 2 | 17/18 |
| Roscoe et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 1 | NA | NA | NA | 2 | 2 | 17/18 |
| Berglind et al. [ | 2 | 2 | 2 | 1 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 17/18 |
| Díaz-Quesada et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 1 | 2 | 17/18 |
| Raustorp et al. [ | 2 | 2 | 2 | 2 | 2 | 0 | 2 | NA | NA | NA | 1 | 2 | 16/18 |
| Taylor et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 17/18 |
| Jago et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 1 | NA | NA | NA | 1 | 2 | 16/18 |
| Jago et al. [ | 2 | 2 | 2 | 2 | 2 | 1 | 2 | NA | NA | NA | 2 | 1 | 16/18 |
| Tanaka & Tanaka [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 1 | 2 | 17/18 |
| Gidlow et al. [ | 2 | 1 | 1 | 2 | 2 | 2 | 1 | NA | NA | NA | 1 | 2 | 14/18 |
| Wang et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 1 | NA | NA | NA | 2 | 2 | 17/18 |
| Hnatiuk et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 18/18 |
| Xu et al. [ | 2 | 2 | 2 | 2 | 2 | 2 | 1 | NA | NA | NA | 2 | 2 | 17/18 |
| Pate et al. [ | 2 | 1 | 2 | 1 | 2 | 2 | 2 | NA | NA | NA | 2 | 2 | 16/18 |
Note: NA = not applicable. The MINORS checklist (2 = High quality; 1= Medium quality; 0 = Low quality): Clearly defined objective (item 1); Inclusion of patients consecutively (item 2); Information collected retrospectively (item 3); Assessments adjusted to objective (item 4); Evaluations carried out in a neutral way (item 5); Follow-up phase consistent with the objective (item 6); Dropout rate during follow-up less than 5% (item 7); Prospective estimation of sample size (item 8); Adequate control group (item 9); Simultaneous groups (item 10); Homogeneous starting groups (item 11); and, appropriate statistical analysis (item 12).
Comparison of children’s PA during weekdays vs. weekend days and extracted correlates.
| Ref. | Sample | Weekdays and Weekend Days | Technology | Results | Conclusions and Practical | ||
|---|---|---|---|---|---|---|---|
| Activity | Time Recording Data | Correlates | |||||
| Parental/Maternal Behavior-Related Correlates | |||||||
| Van Stappen et al. [ | 3578 preschoolers (mean age: 4.8 ± 0.4). | Free daily PA. | Six consecutive days, including both weekend days, and were instructed to remove it during sleep and water-based activities. | Pedometers (Omron Walking Style Pro HJ-720IT-E2, Omron Healthcare Co., Ltd. (Kyoto, Japan) were used in Bulgaria, Germany, Greece, Poland, and Spain, while accelerometers (ActiGraph GT1M, GT3X, GT3X+; Pensacola, FL, USA) were employed in Belgium. | ↑ Higher PA on weekdays, with step count patterns reflecting structured kindergarten routines, including peaks during recess and drops during nap times. | Greater parental sedentary time was associated with increased child sedentary behavior, particularly on weekends. | Differences in step count patterns across countries may be explained by variations in educational policies, cultural norms, and lifestyles; therefore, interventions should focus on reducing inactivity during specific daily periods. |
| Määttä et al. [ | 821 children, aged 3–6 years. | Free daily PA and screen time. | Continuous monitoring over 7 full days using ActiGraph devices. | Actigraph W-GT3X accelerometer (ActiGraph, Pensacola, FL, USA). | ↓ Lower sedentary time on weekends among children whose fathers had intermediate education levels, suggesting higher PA; no other significant associations were found. | Girls accumulated less prolonged sedentary time than boys after school hours. | Preschool children from families with lower parental education levels show higher daily screen time at home, emphasizing the need for targeted strategies to reduce screen exposure in this group. |
| Bergqvist-Norén et al. [ | A sample of 61 children (51% female) aged 3 years. | Free daily PA. | Data were collected over seven consecutive days, with a valid day defined as having a minimum of 10 h of PA recording. | Tri-axial accelerometer (ActiGraph GT3X+). | ↑ Higher PA levels on weekdays compared to weekends (p < 0.01), with activity peaks mid-morning and mid-afternoon; children with less-educated parents were more active (p = 0.01). | Children of parents with lower educational attainment were more active (p = 0.01) than those whose parents had higher education levels. | PA levels were similar between sexes and unaffected by weight status; higher activity was seen in children of less-educated parents, with weekday-weekend differences indicating modifiable behavior in 3-year-olds. |
| Xu et al. [ | 346 preschool children and parents. | Free daily PA | Participants were monitored from 6 a.m. to 11 p.m. daily over seven consecutive days, spanning from Saturday through the following Sunday, including five weekdays and one weekend day. | ActiGraph GT3X+ accelerometer (ActiGraph, Pensacola, FL, USA). | ↔ Girls’ TPA positively correlated with parental PA; maternal activity influenced weekday PA, while paternal activity was more impactful on weekends—no clear difference in overall PA levels between periods. | Total PA levels of both mothers and fathers were positively correlated with those of their daughters, but not sons. Parental sedentary behavior during weekends showed significant associations with girls’ sedentary levels, but not boys’. Children’s weekend PA appeared to be more influenced by paternal activity, whereas maternal activity had a stronger impact during weekdays. | Parental PA and sedentary patterns strongly influence preschoolers, with maternal effects stronger on weekdays and paternal on weekends; the impact is greater on girls than boys. |
| Hnatiuk et al. [ | One hundred twenty-three 4–6-year-old children and their mothers. | Free daily PA. | Participants wore the device continuously for seven consecutive days, removing it only during sleep and water-based activities, with a minimum daily wear time of six hours on at least three weekdays and one weekend day. | ActiGraph GT1M accelerometers. | ↓ Weekend walking or cycling with parents increased children’s MVPA and LMVPA, while frequent or occasional visits to indoor play centers were negatively associated with weekend MVPA. | “Frequent visits (once or more per week) to indoor play centers were inversely associated with mothers’ LMVPA. Conversely, weekend walking or cycling with their child during leisure time was positively correlated with both children’s and mothers’ MVPA, as well as children’s LMVPA. Occasional visits (1–3 times per month) to indoor play centers were negatively associated with children’s weekend MVPA. | Maternal-child PA relationships depend on the type of shared activities and may differ by day type; promoting joint walking and cycling during leisure may boost MVPA in both. |
| Jago et al. [ | A sample of 1267 Year 1 pupils aged five to six years. | Free daily PA. | Data collection spanned five days, including a weekend day. Inclusion criteria required at least three valid days, with a valid day defined as recording a minimum of 500 min of data. | ActiGraph GT3X accelerometer. | ↔ 29% of boys and 47% of girls (aged 5–6) did not meet PA guidelines; each 10 min of parental MVPA associated with a 1 min increase in child MVPA. | While 80% of parents met PA guidelines, 29% of boys and 47% of girls aged five to six years did not. Each additional 10 min of parental MVPA was linked to a one-minute increase in child MVPA. No significant differences were found in these associations between boys and girls or between maternal and paternal influences. | Weak MVPA correlations between 5–6-year-olds and their parents suggest shared activity time isn’t the main driver of child PA; parents should be encouraged to provide more activity opportunities. |
| Taylor et al. [ | Two hundred and forty-four children (44% female) | Daily free play and screen time. | Continuous 24-h monitoring over five consecutive days. | Mini-Mitter (Bend, OR, USA) omnidirectional Actical accelerometers. | ↔ Decline in PA with age observed, and paternal activity predicted child PA; no specific comparison between weekdays and weekends reported. | Paternal activity remained a significant predictor of child PA. | PA declined in both boys and girls from age 3 to 4–5, according to objective measures and parental reports. |
| Gender-Related Correlates | |||||||
| van Ekris et al. [ | 1456 children from a potential 2600. | Free daily PA. | 5 consecutive days, incorporating both weekend days. Data from a given day were considered valid if the accelerometer was worn for a minimum of 8 h. | ActiGraph wGT3X (Pensacola, FL, USA) accelerometers. | ↓ Higher sedentary time observed on weekends in children, linked to greater parental sedentary behavior; MVPA inversely relates to sedentary behavior. | Boys showed significantly higher MVPA levels and lower sedentary time than girls across both weekdays and weekends. | Higher MVPA in children was consistently associated with lower total and prolonged sedentary time, indicating a substitution effect whereby increased PA replaces sedentary behavior. |
| Van Stappen et al. [ | 3578 preschoolers (mean age: 4.8 ± 0.4). | Free daily PA. | Six consecutive days, including both weekend days, and were instructed to remove it during sleep and water-based activities. | Pedometers (Omron Walking Style Pro HJ-720IT-E2) were used in Bulgaria, Germany, Greece, Poland, and Spain, while accelerometers (ActiGraph GT1M, GT3X, GT3X+; Pensacola, FL, USA) were employed in Belgium. | ↑ Higher PA on weekdays, with step count patterns reflecting structured kindergarten routines, including peaks during recess and drops during nap times. | Boys were more active and less sedentary than girls across both weekdays and weekends. | Differences in step count patterns across countries may be explained by variations in educational policies, cultural norms, and lifestyles; therefore, interventions should focus on reducing inactivity during specific daily periods. |
| Määttä et al. [ | 821 children, aged 3–6 years | Free daily PA and screen time. | Continuous monitoring over 7 full days using ActiGraph devices. | Actigraph W-GT3X accelerometer (ActiGraph, Pensacola, FL, USA). | ↓ Lower sedentary time on weekends among children whose fathers had intermediate education levels, suggesting higher PA; no other significant associations were found. | Girls accumulated less prolonged sedentary time than boys after school hours. | Preschool children from families with lower parental education levels show higher daily screen time at home, emphasizing the need for targeted strategies to reduce screen exposure in this group. |
| Foweather et al. [ | A cohort of 99 children (53% male) aged 3 to 5 years (mean age 4.6 ± 0.5 years). | A 6-week educational programme called “The Children’s Activity and Movement in Preschool Study Motor Skills Protocol. PA”. | Seven consecutive days, with children instructed to wear the devices during all waking hours except during water-based activities. | Hip-mounted uni-axial accelerometers (GT1M ActiGraph, Pensacola, FL, USA). | ↔ Motor competence positively associated with MVPA on weekdays and weekends, with no clear predominance of PA in either period. | Boys showed significantly higher PA levels and better object-control skills than girls; locomotor skills were associated with MVPA on weekdays and LPA on weekends. | Improving locomotor and object-control skills may be crucial for promoting an active lifestyle in young children across both weekdays and weekends. |
| Quan et al. [ | A sample of 303 preschool children, comprising 174 boys and 129 girls. | Free daily PA. | Seven consecutive days, with inclusion criteria requiring accelerometer wear between 7:00 a.m. and 11:00 p.m. each day, including at least two weekdays and one weekend day, and a minimum daily wear time of 480 min. | ActiGraph GT3X+ accelerometers. | ↔ PA levels reported without specific comparison between weekdays and weekend days; no directional trend identified. | Boys recorded higher MVPA and TPA levels than girls (72.8 vs. 68.3 min/day MVPA; 171.9 vs. 162.9 min/day TPA), with 72.9% meeting MVPA guidelines and 35.3% meeting TPA recommendations. | There is significant potential to improve PA behaviors among preschool children in Shanghai, highlighting the need for targeted public health interventions and policies to boost activity levels. |
| Berglind and Tynelius [ | A cohort of 899 four-year-old children from Sweden. | Free play and screen time. | PA was monitored over four days, including one weekend day, with data collected continuously except for the period between 9 p.m. and 7 a.m., which was excluded as sleep time. | GT3X+ Actigraph accelerometer. | ↑ Higher PA and lower sedentary time on weekdays compared to weekends; screen time significantly increased on weekends. | Accelerometer data indicated that boys were more physically active and less sedentary than girls on both weekdays and weekends, with higher activity levels observed on weekdays for both sexes. | Interventions should reduce weekend screen time and promote activity during key hours on both weekends and weekdays to decrease sedentary behavior in preschoolers. |
| Chen et al. [ | 72 preschool children. | Free daily PA. | Continuous monitoring over seven consecutive days and nights to capture 24-h activity patterns throughout the week. | Triaxial accelerometer (ActiGraph wGT3X-BT). | ↓ Median sedentary behavior was 7.8 h/day and MVPA 0.5 h/day; MVPA remained stable across the week, but sedentary time was slightly higher on non-school days. | Children engaged in a median of 7.8 h/day of sedentary behavior and 0.5 h/day of MVPA, with MVPA levels stable across the week; boys showed higher activity levels than girls. | Preschoolers in urban Asia showed low MVPA and high sedentary behavior, highlighting the need for targeted interventions addressing school and home environments. |
| Carson et al. [ | 177 children between 3 and 5 years of age. | Free daily PA | Seven consecutive days. | ActiGraph Model GT1M accelerometers. | ↔ Increases in daily sedentary time (34–54 min/day) and sedentary bouts (18–29 min/day) observed across all days and during school hours; no specific weekday vs. weekend comparison. | Both boys and girls showed increases in sedentary time from baseline to follow-up (+34 to +54 min/day); however, boys consistently exhibited higher PA levels than girls. | Reducing overall sedentary time through changes in educational practices and environments may be more effective than focusing only on prolonged bouts. |
| Berglind et al. [ | A cohort of 540 four-year-old children. | Unstructured daily PA. | Wearing the device for over ten hours daily on at least three days, including one weekend day. | ActiGraph GT3X+ accelerometer | ↔ No significant differences in PA between weekdays and weekends; boys were more active and less sedentary than girls across all intensity levels. | No significant differences were observed in the number of valid days or average wear time based on children’s sex, body size, or between weekdays and weekends. However, boys exhibited significantly higher PA levels across all intensities and spent less time sedentary compared to girls. | Four-year-olds spent nearly 50% of their day sedentary, and only one-third met PA guidelines—raising concerns due to links with obesity risk and long-term health. |
| Benham-Deal [ | 39 children (20 girls, 19 boys) with a mean age of 4.3 ± 0.7 years. | An eight-week university-led developmental movement intervention incorporating unstructured play. | Over one month, including two weekdays (Thursday and Friday) and one weekend day (Saturday). Sleep period was defined from 9 p.m. to 8 a.m. | Heart rate data were recorded using the Polar Vantage XL watch (Polar USA, Inc., Woodbury, NY, USA). | ↔ No significant differences in children’s heart rates between weekdays and weekends, indicating similar PA levels. | Boys demonstrated higher MVPA levels compared to girls during school days; information for weekend MVPA by gender was not specified. | Educators should design interventions based on children’s activity patterns, prioritizing vigorous outdoor motor activities to counter physical inactivity risks. |
| Olesen et al. [ | A cohort of 627 children aged 5 to 6 years. | Free daily PA. | Five weekdays and two weekend days. | PA was monitored using ActiGraph devices (GT1M version 4 and GT3X; Pensacola, FL, USA). | ↔ No specific differences in PA levels between weekdays and weekends; focus was on motor skill differences by gender. | Boys and girls displayed similar levels of PA, with no significant sex differences across weekdays and weekends. | PA levels varied widely across preschools, with girls showing particular sensitivity to environmental influences on their activity. |
| McKee et al. [ | A sample of 85 preschool children aged 3 and 4 years. | Free daily PA. | Data were collected over a one-year follow-up period, encompassing four weekdays and two weekend days. Inclusion criteria required at least 9 h of daily monitoring, with a minimum of three weekdays and one weekend day per participant. | PA was assessed using Digiwalker™ DW-200 pedometers (Yamax, Tokyo, Japan). | ↔ Weekday/weekend comparison not reported; children took ≈2000 fewer steps day−1 in winter than in spring (−20%) and ≈2300 more steps day−1 at age 5 vs. age 4 (+20%). | Boys exhibited significantly higher PA levels and lower sedentary time than girls across both weekdays and weekends. | The study captured the preschool-to-primary transition, a phase linked to rising sedentary behavior, with minimal age-related bias due to the narrow baseline age range. |
| Blaes et al. [ | Preschoolers (Ps, n = 94) | Free daily PA. | A seven-day monitoring period, including four school days and three non-school days. | Uniaxial accelerometer (The ActiGraph, Manufacturing Technologies, Inc. (Sterling Heights, MI, USA), model GT1M). | ↑ Boys showed significantly higher MVPA during weekdays; no data reported for weekend comparison. | Boys accumulated significantly more MVPA and were less sedentary than girls across both weekdays and weekends. | MVPA decreased and light activity increased from childhood to adolescence, with greater changes on free days than on school days. |
| Roscoe et al. [ | A cohort of 185 preschool children (99 boys and 86 girls) aged 3 to 4 years. | Free daily PA. | PA was monitored over four consecutive days, including two weekdays and two weekend days. | GENEActiv waveform triaxial accelerometer (ActivInsights Ltd., Cambridge, UK). | ↔ No significant associations between fundamental motor skills and MVPA on weekdays or weekends; none of the children met the 180 min/day PA recommendation. | Boys recorded higher MVPA and lower sedentary behavior than girls on both weekdays and weekends, with a sharper decline in both sexes during weekend days. | Wrist-worn accelerometers pose practical challenges in preschoolers; no differences in PA or weight were found across motor skill levels. |
| Díaz-Quesada et al. [ | A sample of 63 children (33 boys, 30 girls) with a mean age of 2.15 ± 0.35 years. | Free daily PA. | Participants wore the device continuously for seven consecutive days, capturing a full week of the school routine with 24-h monitoring. | PA was measured using the Garmin Vivofit® Jr. device (Garmin Ltd., Schaffhausen, Switzerland). | ↓ Trend toward higher PA and step counts on weekends and during out-of-school periods, indicating greater PA outside structured school settings. | No significant gender differences were observed. | The study suggests school-based strategies and the use of activity trackers to promote early PA and support active urban mobility like walking. |
| Jago et al. [ | 1299 children and their parents in year 1, with 1223 children reassessed in year 4. | Free daily PA. | Monitoring was conducted over five full days, comprising three weekdays and two weekend days. | ActiGraph wGT3X accelerometer | ↔ Boys’ MVPA decreased from 72 to 69 min/day and girls’ from 62 to 56 min/day; boys’ CPM dropped from 747 to 673 and girls’ from 686 to 587; sedentary time increased in both sexes—no weekday vs. weekend comparison provided. | Boys’ CPM decreased from 747 to 673, and girls’ CPM declined from 686 to 587. Correspondingly, boys’ daily MVPA decreased from 72 to 69 min, while girls’ MVPA reduced from 62 to 56 min. Sedentary time increased for both genders during this period. | From ages 5–6 to 8–9, sedentary behavior increased in both sexes, with greater MVPA declines in girls, underscoring the need for early interventions to prevent age-related PA reductions. |
| Other Correlates | |||||||
| Eichinger et al. [ | A sample of 735 children aged 3 to 6 years enrolled in 52 preschools across southern Germany. | Free daily PA. | A six-day monitoring period encompassing both weekend days. | Accelerometry data were collected using Actiheart monitors (software version 13.1.4; CamNtech, Cambridge, UK). | ↑ Higher MVPA and TPA on weekends associated with positive parental perceptions of traffic safety and children’s participation in organized sports. | Step count patterns closely mirrored kindergarten routines, with notable increases during recess and drops during nap times, highlighting the influence of structured daily schedules. | Shaping parental perceptions of environmental conditions and increasing their support for PA during preschool years may be effective strategies for public health promotion. |
| Díaz-Quesada et al. [ | Seventy-three children (36 boys, 37 girls) with a mean age of 2.12 ± 0.46 years. | Unstructured daily PA. | Seven continuous days of a routine school week. | ActiGraph GT3X accelerometer. | ↑ Greater step counts and PA levels observed from Monday to Friday, with higher values during school hours compared to out-of-school periods. | Children exhibited higher step counts and PA levels during school hours compared to out-of-school periods, with a trend toward greater activity on weekdays. | School hours are key for promoting PA in preschoolers, underscoring the need for further research and targeted interventions in educational settings. |
| Olesen et al. [ | A cohort of 627 children aged 5 to 6 years. | Free daily PA. | Five weekdays and two weekend days. | PA was monitored using ActiGraph devices (GT1M version 4 and GT3X; Pensacola, FL, USA). | ↔ No specific differences in PA levels between weekdays and weekends; focus was on motor skill differences by gender. | Variation in activity levels was observed across preschool settings, indicating that environmental context (school-level differences) significantly influenced MVPA. | PA levels varied widely across preschools, with girls showing particular sensitivity to environmental influences on their activity. |
| Blaes et al. [ | Preschoolers (Ps, n = 94) | Free daily PA. | A seven-day monitoring period, including four school days and three non-school days. | Uniaxial accelerometer (ActiGraph, Manufacturing Technologies, Inc. (Sterling Heights, MI, USA), model GT1M), | ↑ Boys showed significantly higher MVPA during weekdays; no data reported for weekend comparison. | Superior object-control skills in boys were associated with higher MVPA, particularly during school hours. | MVPA decreased and light activity increased from childhood to adolescence, with greater changes on free days than on school days. |
| Pate et al. [ | 301 4-year-old children | Free daily PA. | For 5 consecutive weekdays (Monday–Friday). | PA was measured using ActiGraph accelerometers (models GT1M and GT3X; Pensacola, FL, USA). | ↔ Children in Montessori settings showed higher MVPA, especially in private institutions; no comparison between weekdays and weekends reported. | Within Montessori programs, in-school PA was greater among children enrolled in private institutions versus public ones. | Children in Montessori preschools had higher PA levels than those in traditional settings, suggesting the Montessori approach may help promote PA in young children. |
| Wang et al. [ | A cohort of 304 preschool children (mean age 5.07 ± 0.94 years; 50.66% male). | Free daily PA. | Participants wore the device on the right hip for seven consecutive days (five weekdays and two weekend days), removing it only during bathing, swimming, and sleep. | ActigraphGT3X+ accelerometer (ActiGraph, LLC, Pensacola, FL, USA). | ↔ Weekend LPA positively associated with transportation environment in girls; weekday VPA in boys linked to perceived community safety—bidirectional effects reported without clear predominance of one period over the other. | Proximity to public activity facilities was positively correlated with the frequency of active trips among all children. The community transportation environment was associated with overall average daily light physical activity, weekend light PA, moderate PA, total PA, and frequency of active trips in girls. Additionally, perceptions of community personal safety were linked to boys’ vigorous PA during weekdays. | Parental views on walking distances, PA facilities, safety, and transport environment are key factors in preventing declines in preschoolers’ PA. |
| Gidlow et al. [ | 57 preschool children (4.5 + 0.64 year) | Free daily PA. | Devices were worn during all waking hours for seven consecutive days, covering both weekdays and weekends, excluding water-based activities. | ActiGraph GT1M accelerometers. | ↔ All participants met the 60 min/day MVPA guideline; no specific comparison between weekdays and weekends reported. | The sample demonstrated adherence to the recommended 60 min of daily moderate-to-vigorous physical activity, with 100% of preschool participants meeting this guideline. | PA was lower during school hours than outside, as most children did not compensate after school. Increasing PA opportunities at school is essential. |
| Roscoe et al. [ | A cohort of 185 preschool children (99 boys, 86 girls) aged 4 to 5 years. | Free daily PA. | PA was monitored over four consecutive days, comprising two weekdays in the setting and two weekend days, with a minimum of six hours of wear time per day. | GENEActiv waveform triaxial accelerometer (ActivInsights Ltd., Kimbolton, UK). | ↑ MVPA accounted for 6.3% of the day on weekdays vs. 2.0% on weekends; sedentary time was 91.9% on weekdays and 96.9% on weekends—indicating higher PA during weekdays. | None of the children in the sample met the UK guideline of at least 180 min of PA daily. A significant difference was found in sedentary behavior, with children spending 91.9% of time sedentary on week-days compared to 96.9% on weekends. Time spent in moderate-to-vigorous physical activity accounted for 6.3% and 2.0% of the day on weekdays and weekends, respectively. | British preschoolers show high sedentary behavior and lower MVPA on weekends, highlighting weekdays as more consistent opportunities for PA. |
| Tanaka & Tanaka [ | A cohort of 425 Japanese children, both girls and boys, aged 4 to 6 years. | Free daily PA. | PA was continuously monitored over six days, typically including four weekdays and two weekend days. | Triaxial accelerometer (ActivTracer, GMS, Tokyo, Japan). | ↔ Underweight children engaged in significantly less light and MVPA and more low-intensity activity than peers; no comparison between weekdays and weekends reported. | After adjusting for age and gender, PA levels in overweight children were similar to those in normal-weight peers. However, underweight children spent significantly more time in low-intensity activities and less time in both light-intensity and moderate-to-vigorous PA compared to normal-weight and overweight groups. | The findings indicate that, in Japanese preschool children, low body weight rather than overweight status is linked to reduced engagement in light, moderate, and vigorous PA. |
| Taylor et al. [ | Two hundred and forty-four children (44% female). | Daily free play and Screen time | Continuous 24-h monitoring over five consecutive days. | Mini-Mitter (Bend, OR) omnidirectional Actical accelerometers. | ↔ Decline in PA with age observed, and paternal activity predicted child PA; no specific comparison between weekdays and weekends reported. | PA levels significantly declined at ages 4 and 5 compared to age 3 in both boys and girls. | PA declined in both boys and girls from age 3 to 4–5, according to objective measures and parental reports. |
| Aguilar-Farías et al. [ | Twenty-five children (4.8 ± 0.50 years. | Walking, standing, sitting/lying, and daily steps were analyzed by weekday/weekend and time of day to assess activity patterns. | Continuous 24-h monitoring for a minimum of four days, including two weekend days. | ActivPALTM micro (AP, PAL Technologies Ltd., Glasgow, UK) and inclinometer. | ↔ No explicit comparison between weekdays and weekends; step accumulation and sedentary behavior patterns described without temporal differentiation. | Half of the total steps were accumulated at rates below 100 steps per minute, while 50% of sedentary behavior time occurred in bouts lasting 35 s or less. | Longer sedentary periods on weekdays suggest classroom time as a key opportunity to reduce inactivity in preschoolers. |
| Raustorp et al. [ | A sample of 50 children with a mean age of 52 months. | Daily free play and screen time. | Participants wore an accelerometer secured by an elastic belt continuously throughout five weekdays. | ActiGraph GT1M accelerometer (Pensacola, FL, USA) | ↔ Differences observed between locations (Raleigh vs. Malmö) and indoor vs. outdoor settings, but no specific comparison between weekdays and weekends reported. | Preschool children in Raleigh spent significantly more time indoors compared to their counterparts in Malmö. In both locations, higher levels of MVPA were observed outdoors. Conversely, Malmö children exhibited significantly greater activity counts per minute while indoors. | PA counts per minute were significantly greater outdoors than indoors in both Malmö and Raleigh. Time engaged in MVPA at preschool was minimal and primarily occurred outdoors. |
Note: BMI = body mass index; CPM = counts per minute; FAT = frequency of active trips; FMS = fundamental movement; LMVPA = light-to-vigorous-intensity PA; LPA = light PA; MPA = moderate PA; MS = motor skills; MVPA = moderate-to-vigorous PA; PA = PA; TPA = total PA; SB = sedentary behavior; SED = overall sedentary time; VPA = vigorous PA. ↑ indicates an increase in the measured variable compared to baseline; ↓ indicates a decrease; ↔ indicates no relevant changes or non-significant differences.
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