City Tales - Relationship Between 24-Hour Movement Guidelines and Health-Related Quality of Life in Early Childhood in Singapore, Japan and China

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This study aimed to examine country-specific adherence to the 24-hour movement guidelines (24-h MG) and their associations with HRQoL among preschoolers in Singapore, Japan, and China. Methods: A cross-sectional survey was conducted among 6,634 children aged 3–6 years across Singapore (n = 3,672), Japan (n = 760), and China (n = 2,202). Movement behaviors were assessed using the validated SMALLQ® tool, and HRQoL was evaluated using the Pediatric Quality of Life Inventory (PedsQL™). Logistic regression models were applied to determine the associations between different patterns of 24-h MG adherence and HRQoL, adjusting for demographic variables. Results: Full adherence to all three 24-h MG components was significantly associated with higher physical and psychosocial HRQoL scores in Singapore and China. In Japan, adherence to physical activity guidelines alone was most strongly linked to improved HRQoL. Notably, Chinese children had the highest adherence rates across all individual and combined movement behaviors. Conversely, Japanese children had the lowest rates of full adherence and were more likely to fall short of all guidelines. Conclusions: This study provides novel evidence from three urban Asian contexts that adherence to the 24-hour movement guidelines positively correlates with HRQoL in preschool-aged children. The findings highlight the importance of integrated movement behavior frameworks and support the development of culturally tailored public health policies to improve early childhood well-being. Preschool children Health-related quality of life 24-hour movement guidelines Physical activity Screen time Sleep duration Asia Urban health Figures Figure 1 1. Introduction Health-related quality of life (HRQoL) is a level of well-being on the assessment of various dimensions of life, reflecting the impact of these dimensions on health status, and is subjective and multidimensional in nature [ 1 ]. According to the concept proposed by the World Health Organization (WHO), HRQoL encompasses physical, emotional, mental, social, and behavioral factors, serving as a significant indicator for evaluating progress toward ultimate health goals [ 2 ]. Traditionally, research on HRQoL has primarily focused on adults experiencing chronic illnesses, disabilities, or age-related conditions; however, there has been growing interest in infancy and early childhood, given increasing evidence that the foundations for lifelong well-being are established much earlier. In particular, researchers and policymakers have recognized that studying HRQoL in young children is crucial for understanding health inequalities among populations and for developing preventive strategies aimed at enhancing health outcomes [ 4 , 5 ]. This is particularly significant given the unique developmental characteristics of early childhood. Early childhood is characterized by rapid physical growth, cognitive development, and critical social-emotional maturation [ 6 ]. It is increasingly recognized as a pivotal stage for establishing lifelong healthy behaviors, especially since health-related behaviors in adulthood are significantly influenced by lifestyle habits formed during early childhood [ 7 , 8 ]. In recent years, the concept of 24-hour movement guidelines (24-h MG), integrating physical activity, screen time, and sleep duration, has gained traction within health behavior research. Canada has established 24-h MG across all age groups [ 9 – 11 ], and the WHO has also adopted 24-h MG specifically for children under five years of age [ 6 ]. Reflecting its global relevance and applicability, the concept is being introduced and expanded in many other countries worldwide [ 12 ]. This integrated approach represents a new paradigm that acknowledges the interrelated nature of physical activity, sedentary behavior, and sleep, recognizing that changes in one behavior typically influence others throughout the day. This holistic paradigm becomes particularly important in early childhood, as behavioral patterns established during this period can significantly influence HRQoL later in life [ 13 ]. Indeed, empirical evidence indicates that when the three components of 24-h MG are balanced (i.e., sufficient physical activity, appropriate screen time limits, and adequate sleep duration), children exhibit improved physical fitness [ 14 ], enhanced social-cognitive development [ 15 ], and fewer behavioral and emotional problems [ 16 ]. However, achieving such a balance has become increasingly challenging, especially in rapidly urbanizing contexts. Singapore, Japan, and China have undergone rapid urbanization and digitalization [ 17 ], resulting in widespread use of digital devices from infancy. Consequently, issues such as physical inactivity [ 18 , 19 ], excessive screen time [ 20 ], and insufficient sleep [ 21 ] may be more prevalent among young children in these countries. Therefore, examining adherence to the integrated 24-h MG is essential for enhancing HRQoL among Asian preschoolers. Despite this significance, research to date on the association between adherence to the 24-h MG and HRQoL has primarily been conducted in Western contexts, with limited studies involving preschool-aged children in major Asian cities, particularly Singapore, Japan, and China [ 22 , 23 ]. Furthermore, differences in childcare and education systems, cultural values, and lifestyle factors across these Asian countries could uniquely influence this association, limiting the generalizability of findings from other populations [ 24 ]. Given these contextual variations, investigating country-specific characteristics of adherence to the 24-h MG and their associations with HRQoL among preschool-aged children in Singapore, Japan, and China is crucial to addressing this knowledge gap. To address this knowledge gab, the purpose of this study was to identify the optimal combinations of adherence to the 24-h MG and to examine their associations with HRQoL among young children aged 3–6 years living in major urban areas in Singapore, Japan, and China. Additionally, this study aimed to analyze the characteristics of each component of the 24-h MG (physical activity, screen time, and sleep duration) by country. 2. Materials and Methods 2.1. Study Design and Participants This study utilized a cross-sectional design, with data collected through parental questionnaires for preschool-aged children (3–6 years old) participating in the International iPreschooler Surveillance Study Among Asians and otheRs (IISSAAR). Participants were recruited from major urban areas in three Asian countries: Singapore, Japan, and China. Detailed methodologies and data collection procedures for each country are described on the project website [ 25 ]. In Singapore, data were collected annually through cross-sectional surveys conducted in 2020, 2021, and 2022 from parents of preschool children enrolled in childcare centers across Singapore. In Japan, data collection took place in 2020 and 2022 through surveys completed by parents of preschoolers enrolled in kindergartens located in Sendai and Utsunomiya. In China, data were gathered in 2022 via surveys completed by parents of preschool-aged children enrolled in kindergartens located in Dalian, Shanghai, Hefei, and Guangzhou. All participating researchers adhered to the ethical standards outlined in the Declaration of Helsinki, and the study protocols were approved by institutional ethics committees in each respective country (Singapore: IRB2019-02-036, Japan: SU2019-31, China: HR 405 − 202). All data collected were anonymized, and the study procedures strictly followed the principles of informed consent, confidentiality, and privacy protection. 2.2. Measures After obtaining ethical approval and informed consent, standardized and validated measurement tools were employed to ensure consistency and accuracy across the different country contexts. Specifically, the Surveillance of digital Media hAbits in earLy chiLdhood Questionnaire® (SMALLQ®) was selected to assess core behaviors related to movement guidelines. The development and validation process of the SMALLQ® has been described in detail elsewhere. The SMALLQ® demonstrated satisfactory validity and reliability was used across different countries, cultures, and contexts [ 26 , 27 ]. For this study, the SMALLQ® was translated into the respective national languages using a standardized protocol recommended by the World Health Organization (WHO) for cultural adaptation and linguistic translation [ 28 ]. Internal consistency of the SMALLQ®, as measured by Cronbach’s alpha, was acceptable for all three countries: Singapore (α = 0.79), Japan (α = 0.71), and China (α = 0.74). 2.2.1. Physical activity In this study, physical activity (PA) was assessed using two open-ended items from the SMALLQ® questionnaire: (i) indoor play (e.g., dancing, crawling, playing with manipulative toys) and (ii) outdoor physical play (e.g., playing hide-and-seek in a playground or engaging in sports activities). The total amount of physical activity was calculated by summing the hours spent in indoor and outdoor play (Indoor play [hrs] + Outdoor play [hrs] = Total PA [hrs]). Additionally, moderate-to-vigorous physical activity (MVPA) was estimated by multiplying total PA hours by the percentage (%) of moderate and vigorous activities typically performed (Total PA [hrs] × % moderate/vigorous PA = MVPA [hrs]) [ 26 ]. 2.2.2. Recreational Screen time In this study, screen time was assessed using two open-ended items from the SMALLQ® questionnaire, which distinguished between weekdays and weekends: (i) media use for entertainment (e.g., watching videos or TV programs, playing games, listening to music), and (ii) media use for communication purposes (e.g., chatting with relatives via FaceTime or Skype) [ 26 ]. 2.2.3. Sleep duration In the SMALLQ® questionnaire, sleep duration was assessed through two parent-reported items, separately for weekdays and weekends: (i) "How many hours of sleep does your child have on a weekday?" and (ii) "How many hours of sleep does your child have on a weekend?" [ 26 ]. 2.2.4. 24-hour Movement Guidelines The adherence to the 24-h MG for preschool-aged children was evaluated based on the following components: (i) Physical activity (PA)—at least 180 minutes of total daily PA, including a minimum of 60 minutes of moderate-to-vigorous PA (MVPA); (ii) Screen time—no more than 1 hour per day of recreational screen use; and (iii) Sleep duration—between 10 to 13 hours of sleep within a 24-hour period [ 6 , 29 , 30 ]. 2.2.5 Health-related quality of life The Pediatric Quality of Life Inventory (PedsQL™ 4.0) is widely used for assessing HRQoL in healthy and chronically ill children and adolescents aged 2–18 years [ 3 , 31 ]. In this study, we utilized the acute parent-report version, which assesses parents' perceptions of their child's health status over the past 7 days [ 32 ]. The questionnaire consists of 21 items for parents of children aged 2–4 years and 23 items for parents of children aged 5–6 years. Each item is scored on a five-point Likert scale (0 = never a problem; 1 = almost never a problem; 2 = sometimes a problem; 3 = often a problem; 4 = almost always a problem). Responses are reverse-scored and linearly transformed to a 0–100 scale (0 = 100, 1 = 75, 2 = 50, 3 = 25, 4 = 0), with higher scores indicating better HRQoL. The Physical Health Summary Score corresponds directly to the Physical Functioning scale, which includes examples such as walking more than one block, running, lifting heavy objects, or experiencing low energy levels. The Psychosocial Health Summary Score is calculated by summing the mean scores of the Emotional, Social, and School Functioning scales. Examples of emotional functioning include feelings of fear or anger; social functioning examples include interacting well with other children or keeping pace during play; and examples of school functioning include paying attention in class or missing school due to illness. The PedsQL™ is widely used internationally to monitor pediatric health, with high reliability previously reported (Cronbach’s alpha ≥ 0.90) for both child self-report and parent-report versions [ 33 ]. In this study, we used questionnaires translated into English, Japanese, and Chinese [ 32 , 34 , 35 ]. 2.2.6 Demographic variables Demographic information on children and their parents was collected through a parent-reported questionnaire. The questionnaire included the child’s gender, age, height, and weight, as well as the parent’s gender, age, height, weight, income level, and educational level. 2.3. Statistical Analysis Complete data from 6,634 preschool-aged children in three Asian countries (Singapore: n = 3,672; Japan: n = 760; China: n = 2,202) were analyzed using statistical models aligned with the study objectives. In the first step, descriptive statistics were calculated for demographic variables, including children's age, height, weight, body mass index (BMI), and HRQoL scores, as well as parents' age, height, weight, BMI, income, and educational attainment. Continuous variables were presented as means and standard deviations, while categorical variables were summarized as percentages (%). In the second step, frequency analyses were conducted to determine the proportion of children in each country adhering to the 24-h MG for physical activity (PA), screen time, sleep duration, and all combinations thereof (PA + screen time, PA + sleep duration, screen time + sleep duration, and PA + screen time + sleep duration). Additionally, we calculated the proportion of children meeting individual and combined 24-h MG across the three countries. In the third step, logistic regression analyses were performed to examine associations between independent and dependent variables. The independent variables included (1) adherence to different combinations of 24-h MG (PA, screen time, and sleep duration) and (2) the total number of guidelines met. The dependent variables were the physical and psychosocial health dimensions of HRQoL among preschool-aged children in each country. Statistical significance was set at p < 0.05. All statistical analyses were conducted using IBM SPSS version 27.0 (IBM Corp., Armonk, NY, USA). 3. Results Table 1 presents the demographic characteristics of participants in each country. Children’s mean age was highest in Japan at 4.5 years (±1.0). Mean height and weight were lowest among Japanese participants (105.5 ± 8.2 cm; 17.3 ± 3.1 kg) and highest among Chinese participants (106.5 ± 8.0 cm; 18.2 ± 4.9 kg). Regarding BMI categories, Singapore had the highest proportions of both underweight (16.1%, n = 520) and obese children (16.8%, n = 540). HRQoL scores were highest among Japanese children in both physical health (82.9 ± 10.4) and psychosocial health domains (86.3 ± 10.1). Parental mean age was highest in Japan (37.2 ± 5 years). The prevalence of parental obesity was comparatively lower in Japan (13.4%, n = 100) and Singapore (10.7%, n = 369). Finally, high household income level (59.4%, n = 1307) and high parental educational level (80.0%, n = 1761) were most prevalent in China (Table 1). Table 1. Descriptive characteristics Abbreviations: BMI - Body Mass Index, PedsQL - Pediatric Quality of Life Inventory. Notes: Continuous variables that follow a normal distribution are presented as mean ± standard deviation (M ± SD). Continuous variables that do not follow a normal distribution are presented as median [25th percentile, 75th percentile]. Categorical variables are presented as n (%). Figure 1 presents the proportion of preschool children meeting each individual and combined component of the 24-h MG across the three countries. The percentage of children meeting all three 24-h MG recommendations was highest in China (16.3%), followed by Singapore (9.7%) and Japan (2.6%). Conversely, the proportion of children who did not meet any recommendations was highest in Japan (31.6%), compared with Singapore (15.1%) and China (5.8%). Regarding individual movement behaviors, China had the highest compliance rates across all components (physical activity: 60.5%, screen time: 48.7%, sleep duration: 71.5%), while Japan reported the lowest compliance rates for physical activity (20.3%) and screen time (20.5%), and a slightly lower compliance rate for sleep duration (71.5%) compared to China. Table 2 presents the associations between HRQoL and combinations of 24-h MG components, analyzed using logistic regression adjusted for child’s age, sex, BMI, household income, and parental education level. For physical health, a subdomain of HRQoL, significant associations were observed in Singapore and China across six combinations, excluding sleep duration alone. In Japan, significant associations were found in two combinations, both of which included physical activity. For psychosocial health, Singapore and China showed significant associations in four combinations of the 24-h MG components, while Japan demonstrated significant associations in three combinations. Table 2. Logistic regression examining the associations of 24-hour movement guidelines combinations with Health-Related Quality of Life Abbreviations: OR, odds ratio; CI, confidence interval. The OR (95% CI) represents the adjusted results. Model includes control variables, which consist of child sex, child age, child BMI, parent income, and educational level. Table 3 presents the association between HRQoL and the number of recommended 24-h MG components met, based on logistic regression analyses adjusted for relevant covariates. For physical health, a subdomain of HRQoL, significant associations were observed in Singapore (meeting all three guidelines: OR = 1.26, 95% CI: 1.09–1.45), in China (meeting two guidelines: OR = 1.22, 95% CI: 1.01–1.47), and again in China (meeting all three guidelines: OR = 1.36, 95% CI: 1.11–1.67). For psychosocial health, significant associations were found in Singapore (meeting all three guidelines: OR = 1.19, 95% CI: 1.04–1.36) and in China (meeting all three guidelines: OR = 1.27, 95% CI: 1.01–1.71). Table 3. Logistic regression examining the associations of number of 24-hour movement guidelines recommendations met with Health-Related Quality of Life Abbreviations: OR, odds ratio; CI, confidence interval. The OR (95% CI) represents the adjusted results. Model includes control variables, which consist of child sex, child age, child BMI, parent income, and educational level. 4. Discussion This study examined the association between optimal combinations of adherence to the 24-h MG and HRQoL among young children aged 3–6 years living in major urban areas of three Asian countries (Singapore, Japan, and China). In addition, the study explored country-specific characteristics and differences in adherence to the 24-h MG. Our first key finding was that both physical and psychosocial health—subdomains of HRQoL—were significantly improved when preschool children in Singapore and China met all three components of the 24-h MG, and when children in Japan met two or more of these recommendations. These results suggest that full adherence to the 24-h MG plays a critical role in enhancing overall HRQoL in young children. While many previous studies have examined the association between HRQoL and individual movement behaviors such as physical activity, screen time, and sleep duration [36–41], few have adopted an integrated approach that considers the combined effects of all 24-h MG. As a result, the unique contribution of these behaviors when considered together remains unclear. This underscores the need for research frameworks that take an integrated perspective, especially since no single behavior can fully compensate for the negative effects of another [42]. Furthermore, most existing studies have focused on partial adherence—meeting one or more individual recommendations [43,44]—or have limited their target population to school-aged children aged seven and older [45,46]. In contrast, the present study focused exclusively on preschool-aged children, providing valuable early evidence to inform early childhood health policies and support the adoption of a more comprehensive and integrated approach to 24-h MG. To improve HRQoL in young children through the effective integration of all daily movement behaviors, countries should establish 24-h MG that include clear and age-appropriate guidelines for physical activity, screen time, and sleep. Additionally, regular opportunities for both structured and unstructured physical activity should be encouraged in childcare centers and preschools. It is also necessary to implement training programs for caregivers and early childhood educators, ensure consistent monitoring and evaluation, and develop supportive environments and policies that promote safe and active lifestyles for young children. Our second key finding was that the relationship between physical health, psychosocial health, and 24-h MG, which are sub-factors of HRQoL, differed across countries. The results of this study lend support to the suggestion that cultural and environmental factors may influence both 24-h MG and HRQoL outcomes among preschool-aged children in different Asian contexts [45]. Previous research on 24-h MG in Asian young children has shown that, compared to their Western counterparts, Asian children tend to engage in lower levels of physical activity [47], spend more time on screens [48], and have shorter average sleep durations [22]. These earlier findings are consistent with the trends observed in this study and point to important implications for adherence to 24-h MG among Asian preschoolers. In particular, the low adherence rates to physical activity and screen time guidelines across the three countries (Singapore, Japan, and China) highlight the need for culturally tailored interventions to support healthy lifestyle formation in early childhood. In Singapore, physical health—a sub-factor of HRQoL—was strongly associated with physical activity and screen time, while psychosocial health—another sub-factor—was strongly associated with sleep, which also affected combinations of other movement behaviors. Singapore’s highly digitalized urban environment has been shown to contribute to increased screen time in young children. Furthermore, previous studies have found that an increased emphasis on early academic education and screen-based learning is associated with reduced physical activity and greater sedentary time, including screen use [27]. These challenges mirror findings from a prior study involving 2–4-year-old children in Singapore [26]. To mitigate issues related to excessive screen time and insufficient physical activity among young children in Singapore, strategies such as limiting screen and digital game use at home and removing sleep-disrupting media devices from children's bedrooms are recommended [49]. In addition, parents should model positive physical activity behaviors, such as spending active time outdoors with their children. Research has also shown that psychosocial well-being—a sub-factor of HRQoL—is influenced by various combinations of movement behaviors, supporting the idea that longer sleep duration during early childhood contributes to better psychosocial outcomes [50]. Efforts to improve sleep quality and duration in young children in Singapore will require a multidimensional approach that includes general strategies such as sleep hygiene education, while also addressing culturally specific factors such as family sleep environments and daily sleep habits. This study found a positive association between physical activity and HRQoL—including both physical and psychosocial sub-factors—with the strongest effects observed among Japanese young children. These findings are consistent with previous research demonstrating that higher levels of physical activity contribute to improvements in both physical and psychosocial health in early childhood [51,52]. Among Japanese children, adherence to physical activity guidelines appeared to have a greater impact on HRQoL than adherence to other movement behavior guidelines. Moreover, the positive association with HRQoL was even stronger when physical activity guidelines were met in combination with other 24-h MG components. Consistent with earlier studies, one possible explanation for this stronger association is that physical activity may interact synergistically with other beneficial behaviors, such as reduced screen time, enhanced social engagement, and better sleep quality [53]. However, the physical activity guideline adherence rate among Japanese young children (20.3%) was considerably lower compared to their peers in China (60.5%) and Singapore (39.2%). This suggests that increasing physical activity opportunities should be considered a priority in Japan’s early childhood health policy. Urban environments in Japan often present challenges such as limited outdoor play spaces and safety concerns, which may restrict children’s ability to engage in active outdoor play. To address these barriers, policy efforts should focus on developing multi-purpose recreational facilities, improving traffic safety infrastructure, and expanding community-based physical activity programs for families and children. Additionally, since Japanese young children spend extended hours in childcare settings, it is essential to enhance physical activity opportunities and implement structured and unstructured physical activity programs within these centers to support higher levels of physical activity and healthy development [54]. In China, screen time was found to be strongly associated with both physical and psychosocial health, the two sub-factors of HRQoL, and was also shown to influence other movement behaviors. Additionally, this study revealed that Chinese young children demonstrated significantly higher adherence rates to the 24-hour movement guidelines (24-h MG) compared to their counterparts in Japan and Singapore, particularly in terms of physical activity and sleep duration. These findings are in line with previous research suggesting that higher parental socioeconomic status and educational level are associated with greater awareness of, and stricter regulation of, children's movement behaviors—including physical activity, screen time, and sleep [55,56]. In China, national-level health policies such as the Healthy China 2030 Blueprint and the National Fitness Program (2021–2025) have emphasized the importance of adopting the 24-h MG as a core strategy for promoting population-wide health. These policies are expected to play a vital role in further improving adherence to the 24-h MG among Chinese preschoolers by shaping family practices, educational programming, and broader community norms around early childhood health behaviors [57,58]. This study offers several important distinctions from previous research on 24-h MG. First, it is a multinational comparative study conducted across three Asian countries—Singapore, Japan, and China—focusing specifically on preschool-aged children living in large urban areas. This design captures the unique regional characteristics and lifestyle patterns of urbanized Asian contexts. Second, unlike most existing studies that have been conducted in Western populations, this study is among the first to explore the relationship between 24-h MG and HRQoL within an Asian context. Third, While this study examined the individual and combined effects of physical activity, screen time, and sleep duration at the national level, future research could explore how cultural norms and policy environments in each country may serve as potential determinants of 24-h movement behaviors in preschool children. This approach enables a more nuanced understanding of how national public health strategies shape movement behaviors in early childhood—an area that has been largely underexplored in previous research. However, this study has several limitations that should be acknowledged. First, its cross-sectional design limits the ability to draw causal inferences regarding the relationship between adherence to the 24-h MG and HRQoL. Second, the study sample consisted of preschool-aged children (3–6 years old) from Singapore, Japan, and China, and therefore the findings may not be generalizable to school-aged children or other age groups. Third, although the study included participants from three countries, all samples were drawn from large urban areas, and rural populations were not represented. As a result, the sample may not reflect national-level characteristics, particularly given that children from economically disadvantaged or rural backgrounds may experience poorer physical health, which can directly influence HRQoL outcomes [58]. Finally, all data in this study were collected through parent-reported questionnaires, which may not fully capture children’s subjective perceptions of their own health and well-being. Overall, these findings highlight the need for culturally tailored public health interventions in each country. Policymakers in Singapore, Japan, and China should incorporate country-specific cultural practices and environmental contexts when formulating early childhood health guidelines. Additionally, future research should address potential confounders such as the COVID-19 pandemic's influence on daily routines. The study’s strength lies in its large-scale multinational design, standardized measurement tools, and comprehensive assessment of daily movement behaviors. Longitudinal studies and intervention trials are recommended to determine causal relationships and inform policy. Finally, collaboration among policymakers, educators, and families is essential for fostering sustainable behavioral changes and improving HRQoL outcomes in young children across Asia. 5. Conclusion This study found that adherence to the 24-h MG was significantly associated with better physical and psychosocial health—two sub-factors of HRQoL—among young children in Singapore and China. These findings support the growing body of evidence linking 24-hour movement behaviors to HRQoL in Asian preschool-aged children. The study contributes to the advancement of movement behavior research by strengthening the evidence base for future revisions of 24-h MG and promoting integrated approaches to health promotion in early childhood. Furthermore, by examining country-specific patterns using multinational data, this study offers insights that may inform the development of culturally and contextually appropriate intervention strategies tailored to each country. However, additional longitudinal and experimental research is needed to provide conclusive evidence on whether an integrated 24-h MG approach yields optimal HRQoL outcomes in Asian young children. Despite these limitations, this study provides a valuable foundation for policy development and practical strategies aimed at promoting early childhood health and enhancing the overall quality of life among young children in the region. Declarations Human Ethics and Consent to Participate and Publish All participating researchers adhered to the ethical standards outlined in the Declaration of Helsinki. The study protocols were approved by the institutional ethics committees in each respective country (Singapore: IRB2019-02-036; Japan: SU2019-31; China: HR 405 − 202). Considering the involvement of minor participants, informed consent for participation and publication of anonymized data was obtained from their parents and/or legal guardians prior to participation. Funding This study was funded by the Singapore Ministry of Education under the Education Research Funding Programme (OER 29/19 MCYH) and administered by the National Institute of Education, Nanyang Technological University, Singapore. The funders had no role in the design of the study; in the collection, analysis, and interpretation of data; or in writing the manuscript. Author Contribution Conceptualization MYHC and HJC, methodology HK, JM, MYHC and HJC, validation HK and MYHC, formal analysis TC, STL, DL, HJC, HK and MYHC, data curation HK, JM, and MYHC, writing—original draft preparation HK, JM, MYHC and HJC, writing—review and editing JM and MYHC, visualization JM and HK, supervision HJC, MYHC and HK, project administration TC, STL, and DL, funding acquisition MYHC. All authors have read and agreed to the published version of the manuscript. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References The WHOQOL Group. The World Health Organization Quality of Life Assessment (WHOQOL). Position paper from the World Health Organization. Soc Sci Med. 1995;41(10):1403–9. Ravens-Sieberer U, Herdman M, Devine J, Otto C, Bullinger M, Rose M, Klasen F. 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Use-of-time and health-related quality of life in 10- to 13-year-old children: not all screen time or physical activity minutes are the same. Qual Life Res. 2017;26(11):3119–29. Rapley M. Quality of life research: a critical introduction. London: Sage; 2003. IISSAAR (International iPreschooler Surveillance Study Among Asians and otheRs.), Available from: https://www.iissaar.com [Accessed 2 Mar 2025]. Chia MYH, Tay LY, Chua TBK. The development of an online surveillance of digital media use in early childhood questionnaire - SMALLQ™ - for Singapore. Montenegrin J Sports Sci Med. 2019;8(2):77–80. Chia M, Komar J, Chua T, Tay LY, Kim JH, Hong K, Kim H, Ma J, Vehmas H, Sääkslahti A. Screen media and non-screen media habits among preschool children in Singapore, South Korea, Japan, and Finland: insights from an unsupervised clustering approach. Digit Health. 2022;8:20552076221139090. Weech-Maldonado R, Dreachslin JL, Brown J, Pradhan R, Rubin KL, Schiller C, Hays RD. Cultural competency assessment tool for hospitals: evaluating hospitals' adherence to the culturally and linguistically appropriate services standards. Health Care Manage Rev. 2012 Jan-Mar;37(1):54–66. Kim H, Ma J, Harada K, Lee S, Gu Y. Associations between adherence to combinations of 24-hour movement guidelines and overweight and obesity in Japanese preschool children. Int J Environ Res Public Health. 2020;17(24):9320. Chia MYH, Tay LY, Chua TBK. Quality of life and meeting 24-hour WHO guidelines among preschool children in Singapore. Early Child Educ J. 2020;48(3):313–23. Varni JW, Seid M, Rode CA. The PedsQL: measurement model for the Pediatric Quality of Life Inventory. Med Care. 1999;37(2):126–39. Reinfjell T, Diseth TH, Veenstra M, Vikan A. Measuring health-related quality of life in young adolescents: reliability and validity in the Norwegian version of the Pediatric Quality of Life Inventory 4.0 (PedsQL) generic core scales. Health Qual Life Outcomes. 2006;4:61. PedsQL™ (Pediatric Quality of Life Inventory™). Available from: https://www.pedsql.org/pedsql2.html [Accessed 7 Feb 2025]. Kobayashi K, Kamibeppu K. Measuring quality of life in Japanese children: development of the Japanese version of PedsQL. Pediatr Int. 2010;52. Chan LF, Chow SM, Lo SK. Preliminary validation of the Chinese version of the Pediatric Quality of Life Inventory. Int J Rehabil Res. 2005;28(3):219–27. Wafa SW, Shahril MR, Ahmad AB, Zainuddin LR, Ismail KF, Aung MM, Mohd Yusoff NA. Association between physical activity and health-related quality of life in children: a cross-sectional study. Health Qual Life Outcomes. 2016;14:71. Marker AM, Steele RG, Noser AE. Physical activity and health-related quality of life in children and adolescents: a systematic review and meta-analysis. Health Psychol. 2018;37(10):893–903. Xiang H, Lin L, Chen W, Li C, Liu X, Li J, Ren Y, Guo VY. Associations of excessive screen time and early screen exposure with health-related quality of life and behavioral problems among children attending preschools. BMC Public Health. 2022;22(1):2440. Stiglic N, Viner RM. Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open. 2019;9(1):e023191. Sundell AL, Angelhoff C. Sleep and its relation to health-related quality of life in 3-10-year-old children. BMC Public Health. 2021;21(1):1043. Wong CKH, Wong RS, Cheung JPY, Tung KTS, Yam JCS, Rich M, Fu KW, Cheung PWH, Luo N, Au CH, et al. Impact of sleep duration, physical activity, and screen time on health-related quality of life in children and adolescents. Health Qual Life Outcomes. 2021;19(1):145. Chen M, Chua T, Shen Z, Tay LY, Wang X, Chia M. The associations between 24-hour movement behaviours and quality of life in preschoolers: a compositional analysis of cross-sectional data from 2018–2021. Int J Environ Res Public Health. 2022;19(22):14969. Xiong X, Dalziel K, Carvalho N, Xu R, Huang L. Association between 24-hour movement behaviors and health-related quality of life in children. Qual Life Res. 2022;31(1):231–40. Tan SYX, Padmapriya N, Bernard JY, Toh JY, Wee HL, Tan KH, Yap FKP, Lee YS, Chong YS, Godfrey K, et al. Cross-sectional and prospective associations between children's 24-hour time use and their health-related quality of life: a compositional isotemporal substitution approach. Lancet Reg Health West Pac. 2023;41:100918. Sampasa-Kanyinga H, Standage M, Tremblay MS, Katzmarzyk PT, Hu G, Kuriyan R, Maher C, Maia J, Olds T, Sarmiento OL, et al. Associations between meeting combinations of 24-hour movement guidelines and health-related quality of life in children from 12 countries. Public Health. 2017;153:16–24. López-Gil JF, Tremblay MS, Tapia-Serrano MÁ, Tárraga-López PJ, Brazo-Sayavera J. Meeting 24-hour movement guidelines and health-related quality of life in youths during the COVID-19 lockdown. Appl Sci. 2022;12(16):8056. Lee ST, Wong JE, Ong WW, Ismail MN, Deurenberg P, Poh BK. Physical activity pattern of Malaysian preschoolers: environment, barriers, and motivators for active play. Asia Pac J Public Health. 2016;28(5 Suppl):S21–34. Kim H, Ma J, Lee S, Gu Y. Change in Japanese children's 24-hour movement guidelines and mental health during the COVID-19 pandemic. Sci Rep. 2021;11(1):22972. Fuller C, Lehman E, Hicks S, Novick MB. Bedtime use of technology and associated sleep problems in children. Glob Pediatr Health. 2017;4:2333794X17736972. Sivertsen B, Harvey AG, Reichborn-Kjennerud T, Ystrom E, Hysing M. Sleep problems and depressive symptoms in toddlers and 8-year-old children: a longitudinal study. J Sleep Res. 2021;30(1):e13150. Carson V, Lee EY, Hewitt L, Jennings C, Hunter S, Kuzik N, Stearns JA, Unrau SP, Poitras VJ, Gray C, et al. Systematic review of the relationships between physical activity and health indicators in the early years (0–4 years). BMC Public Health. 2017;17(Suppl 5):854. Rhodes RE, Sui W. Physical activity maintenance: a critical narrative review and directions for future research. Front Psychol. 2021;12:725671. Lubans D, Richards J, Hillman C, Faulkner G, Beauchamp M, Nilsson M, Kelly P, Smith J, Raine L, Biddle S. Physical activity for cognitive and mental health in youth: a systematic review of mechanisms. Pediatrics. 2016;138(3):e20161642. Jerrim J. Why do East Asian children perform so well in PISA? An investigation of Western-born children of East Asian descent. Oxf Rev Educ. 2015;41(3):310–33. De Craemer M, Verloigne M, Ghekiere A, Loyen A, Dargent-Molina P, Brug J, Lien N, Froberg K, Wedderkopp N, Chastin S, et al. Changes in children's television and computer time according to parental education, parental income and ethnicity: a 6-year longitudinal EYHS study. PLoS ONE. 2018;13(9):e0203592. Spurrier NJ, Sawyer MG, Clark JJ, Baghurst P. Socio-economic differentials in the health-related quality of life of Australian children: results of a national study. Aust N Z J Public Health. 2003;27(1):27–33. Chen P, Li F, Harmer P. Healthy China 2030: moving from blueprint to action with a new focus on public health. Lancet Public Health. 2019;4(9):e447. Menhas R, Dai J, Ashraf MA, Noman SM, Khurshid S, Mahmood S, Weng Y, Ahmad Laar R, Sang X, Kamran M, et al. Physical inactivity, non-communicable diseases and national fitness plan of China for physical activity. Risk Manag Healthc Policy. 2021;14:2319–31. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Jul, 2025 Read the published version in Health and Quality of Life Outcomes → Version 1 posted Editorial decision: Revision requested 30 May, 2025 Reviews received at journal 27 May, 2025 Reviews received at journal 26 May, 2025 Reviews received at journal 22 May, 2025 Reviewers agreed at journal 16 May, 2025 Reviewers agreed at journal 16 May, 2025 Reviewers agreed at journal 15 May, 2025 Reviewers invited by journal 15 May, 2025 Editor assigned by journal 12 May, 2025 Submission checks completed at journal 07 May, 2025 First submitted to journal 24 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6517464","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":457939213,"identity":"db519059-7a8d-4963-96be-9b14debd12f1","order_by":0,"name":"Ho Jin Chung","email":"","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":false,"prefix":"","firstName":"Ho","middleName":"Jin","lastName":"Chung","suffix":""},{"id":457939214,"identity":"1a8d9607-08b5-433c-b954-24f3ba9fe39f","order_by":1,"name":"Hyunshik Kim","email":"","orcid":"","institution":"Sendai University","correspondingAuthor":false,"prefix":"","firstName":"Hyunshik","middleName":"","lastName":"Kim","suffix":""},{"id":457939215,"identity":"e95d1e3d-dfdc-4e9d-8488-9de1c1050549","order_by":2,"name":"Jiameng Ma","email":"","orcid":"","institution":"Sendai University","correspondingAuthor":false,"prefix":"","firstName":"Jiameng","middleName":"","lastName":"Ma","suffix":""},{"id":457939216,"identity":"76eae385-de69-4dc3-a0dc-1b62dde34ced","order_by":3,"name":"Terence Chua","email":"","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":false,"prefix":"","firstName":"Terence","middleName":"","lastName":"Chua","suffix":""},{"id":457939217,"identity":"513217fa-0e0b-4732-84f8-4b144c14d5f3","order_by":4,"name":"Seow Ting Low","email":"","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":false,"prefix":"","firstName":"Seow","middleName":"Ting","lastName":"Low","suffix":""},{"id":457939218,"identity":"6757ff91-973e-4050-9f22-84337452ed73","order_by":5,"name":"Dan Li","email":"","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Li","suffix":""},{"id":457939219,"identity":"00052d4d-c28b-448a-81c3-9bd73cfe6082","order_by":6,"name":"Michael Yong Hwa Chia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYDACZgY2IGnBwCDB2MDwgUECJGZAjBYJsBbGGURpYYBrAWrngYjg16LbzvzswY8KCQb+2c2Nn213WMgxsDdvk2D4U4tTi9lhNnPDnjMSDBJ3DjZL556RMGbgOVYmwdh2HI8WHjYJ3jYJBgOJxAbp3DYgKZFjBvTXMbxaJP/+A2tp/m3ZJlHfIP/GDOgw/FqkeRvAWtqkGdskEhgkeIBa2Grw+cVMWuaYBI/EjcQ2y942CcM2nrRii8S2A7i1nD/8TPJNjY0c/4z0xzd+ttXJ87Mf3njjw586nFpggAfOAkUTQwLDYYJaMABhW0bBKBgFo2DEAADVLEeo0R3w1AAAAABJRU5ErkJggg==","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":true,"prefix":"","firstName":"Michael","middleName":"Yong Hwa","lastName":"Chia","suffix":""}],"badges":[],"createdAt":"2025-04-24 06:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6517464/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6517464/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12955-025-02408-5","type":"published","date":"2025-07-28T16:29:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83128820,"identity":"8f4526d6-7605-4196-93a3-077fa7e10964","added_by":"auto","created_at":"2025-05-20 09:58:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":110213,"visible":true,"origin":"","legend":"\u003cp\u003ePercentages meeting 24-h movement guidelines among (a) Singapore (n = 3672), (b) Japan (n = 760) and (c) China (n = 2202) preschool children.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVenn diagram\u003c/strong\u003e: The numbers within each circle are added to the proportion of children meeting each individual guideline (i.e., 10.1% for physical activity in Singapore, 6.3% in Japan, and 7.2% in China; 9.8% for screen time in Singapore, 7.5% in Japan, and 11.7% in China; 19.4% for sleep duration in Singapore, 31.4% in Japan, and 10.9% in China). The total nonoverlap area of each circle represents the proportion of children meeting one of the three guidelines (i.e., 10.1% + 9.8% + 19.4% = 39.3%) for Singapore, (i.e., 6.3% + 7.5% + 31.4% = 45.2%) for Japan, (i.e., 7.2% + 11.7% + 10.9% = 29.8%) for China. The total overlap areas of two circles represent the proportion of children meeting two of the three guidelines: (i.e., 4.1% + 16.5% + 15.3% = 35.9%) for Singapore, (i.e., 1.3% + 9.1% + 10.1% = 20.5%) for Japan, and (i.e., 42.9% + 1.5% + 11.4% = 48.3%) for China. The overlap area of three circles represents the proportion of children meeting all three guidelines (i.e., 9.7% in Singapore + 2.6% in Japan + 16.3% in China). The outside area of the circle represents the proportion of children not meeting any of the guidelines (i.e., 15.1% in Singapore + 31.6% in Japan + 5.8% in China = 26.5%).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6517464/v1/9959056e1586148bf2435ff2.png"},{"id":88268821,"identity":"e821dfff-93b1-4ad2-b0b8-20edf26f62e3","added_by":"auto","created_at":"2025-08-04 16:52:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":779685,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6517464/v1/44923968-b75f-46c4-9c5e-4cc9df24b132.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"City Tales - Relationship Between 24-Hour Movement Guidelines and Health-Related Quality of Life in Early Childhood in Singapore, Japan and China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHealth-related quality of life (HRQoL) is a level of well-being on the assessment of various dimensions of life, reflecting the impact of these dimensions on health status, and is subjective and multidimensional in nature [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the concept proposed by the World Health Organization (WHO), HRQoL encompasses physical, emotional, mental, social, and behavioral factors, serving as a significant indicator for evaluating progress toward ultimate health goals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Traditionally, research on HRQoL has primarily focused on adults experiencing chronic illnesses, disabilities, or age-related conditions; however, there has been growing interest in infancy and early childhood, given increasing evidence that the foundations for lifelong well-being are established much earlier. In particular, researchers and policymakers have recognized that studying HRQoL in young children is crucial for understanding health inequalities among populations and for developing preventive strategies aimed at enhancing health outcomes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This is particularly significant given the unique developmental characteristics of early childhood.\u003c/p\u003e \u003cp\u003eEarly childhood is characterized by rapid physical growth, cognitive development, and critical social-emotional maturation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It is increasingly recognized as a pivotal stage for establishing lifelong healthy behaviors, especially since health-related behaviors in adulthood are significantly influenced by lifestyle habits formed during early childhood [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In recent years, the concept of 24-hour movement guidelines (24-h MG), integrating physical activity, screen time, and sleep duration, has gained traction within health behavior research. Canada has established 24-h MG across all age groups [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and the WHO has also adopted 24-h MG specifically for children under five years of age [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Reflecting its global relevance and applicability, the concept is being introduced and expanded in many other countries worldwide [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This integrated approach represents a new paradigm that acknowledges the interrelated nature of physical activity, sedentary behavior, and sleep, recognizing that changes in one behavior typically influence others throughout the day. This holistic paradigm becomes particularly important in early childhood, as behavioral patterns established during this period can significantly influence HRQoL later in life [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Indeed, empirical evidence indicates that when the three components of 24-h MG are balanced (i.e., sufficient physical activity, appropriate screen time limits, and adequate sleep duration), children exhibit improved physical fitness [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], enhanced social-cognitive development [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and fewer behavioral and emotional problems [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, achieving such a balance has become increasingly challenging, especially in rapidly urbanizing contexts. Singapore, Japan, and China have undergone rapid urbanization and digitalization [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], resulting in widespread use of digital devices from infancy. Consequently, issues such as physical inactivity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], excessive screen time [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and insufficient sleep [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] may be more prevalent among young children in these countries. Therefore, examining adherence to the integrated 24-h MG is essential for enhancing HRQoL among Asian preschoolers.\u003c/p\u003e \u003cp\u003eDespite this significance, research to date on the association between adherence to the 24-h MG and HRQoL has primarily been conducted in Western contexts, with limited studies involving preschool-aged children in major Asian cities, particularly Singapore, Japan, and China [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Furthermore, differences in childcare and education systems, cultural values, and lifestyle factors across these Asian countries could uniquely influence this association, limiting the generalizability of findings from other populations [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Given these contextual variations, investigating country-specific characteristics of adherence to the 24-h MG and their associations with HRQoL among preschool-aged children in Singapore, Japan, and China is crucial to addressing this knowledge gap.\u003c/p\u003e \u003cp\u003eTo address this knowledge gab, the purpose of this study was to identify the optimal combinations of adherence to the 24-h MG and to examine their associations with HRQoL among young children aged 3\u0026ndash;6 years living in major urban areas in Singapore, Japan, and China. Additionally, this study aimed to analyze the characteristics of each component of the 24-h MG (physical activity, screen time, and sleep duration) by country.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design and Participants\u003c/h2\u003e \u003cp\u003eThis study utilized a cross-sectional design, with data collected through parental questionnaires for preschool-aged children (3\u0026ndash;6 years old) participating in the International iPreschooler Surveillance Study Among Asians and otheRs (IISSAAR). Participants were recruited from major urban areas in three Asian countries: Singapore, Japan, and China. Detailed methodologies and data collection procedures for each country are described on the project website [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Singapore, data were collected annually through cross-sectional surveys conducted in 2020, 2021, and 2022 from parents of preschool children enrolled in childcare centers across Singapore. In Japan, data collection took place in 2020 and 2022 through surveys completed by parents of preschoolers enrolled in kindergartens located in Sendai and Utsunomiya. In China, data were gathered in 2022 via surveys completed by parents of preschool-aged children enrolled in kindergartens located in Dalian, Shanghai, Hefei, and Guangzhou. All participating researchers adhered to the ethical standards outlined in the Declaration of Helsinki, and the study protocols were approved by institutional ethics committees in each respective country (Singapore: IRB2019-02-036, Japan: SU2019-31, China: HR 405\u0026thinsp;\u0026minus;\u0026thinsp;202). All data collected were anonymized, and the study procedures strictly followed the principles of informed consent, confidentiality, and privacy protection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Measures\u003c/h2\u003e \u003cp\u003eAfter obtaining ethical approval and informed consent, standardized and validated measurement tools were employed to ensure consistency and accuracy across the different country contexts. Specifically, the Surveillance of digital Media hAbits in earLy chiLdhood Questionnaire\u0026reg; (SMALLQ\u0026reg;) was selected to assess core behaviors related to movement guidelines. The development and validation process of the SMALLQ\u0026reg; has been described in detail elsewhere. The SMALLQ\u0026reg; demonstrated satisfactory validity and reliability was used across different countries, cultures, and contexts [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. For this study, the SMALLQ\u0026reg; was translated into the respective national languages using a standardized protocol recommended by the World Health Organization (WHO) for cultural adaptation and linguistic translation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Internal consistency of the SMALLQ\u0026reg;, as measured by Cronbach\u0026rsquo;s alpha, was acceptable for all three countries: Singapore (α\u0026thinsp;=\u0026thinsp;0.79), Japan (α\u0026thinsp;=\u0026thinsp;0.71), and China (α\u0026thinsp;=\u0026thinsp;0.74).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Physical activity\u003c/h2\u003e \u003cp\u003eIn this study, physical activity (PA) was assessed using two open-ended items from the SMALLQ\u0026reg; questionnaire: (i) indoor play (e.g., dancing, crawling, playing with manipulative toys) and (ii) outdoor physical play (e.g., playing hide-and-seek in a playground or engaging in sports activities). The total amount of physical activity was calculated by summing the hours spent in indoor and outdoor play (Indoor play [hrs]\u0026thinsp;+\u0026thinsp;Outdoor play [hrs]\u0026thinsp;=\u0026thinsp;Total PA [hrs]). Additionally, moderate-to-vigorous physical activity (MVPA) was estimated by multiplying total PA hours by the percentage (%) of moderate and vigorous activities typically performed (Total PA [hrs] \u0026times; % moderate/vigorous PA\u0026thinsp;=\u0026thinsp;MVPA [hrs]) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Recreational Screen time\u003c/h2\u003e \u003cp\u003eIn this study, screen time was assessed using two open-ended items from the SMALLQ\u0026reg; questionnaire, which distinguished between weekdays and weekends: (i) media use for entertainment (e.g., watching videos or TV programs, playing games, listening to music), and (ii) media use for communication purposes (e.g., chatting with relatives via FaceTime or Skype) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Sleep duration\u003c/h2\u003e \u003cp\u003eIn the SMALLQ\u0026reg; questionnaire, sleep duration was assessed through two parent-reported items, separately for weekdays and weekends: (i) \"How many hours of sleep does your child have on a weekday?\" and (ii) \"How many hours of sleep does your child have on a weekend?\" [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. 24-hour Movement Guidelines\u003c/h2\u003e \u003cp\u003eThe adherence to the 24-h MG for preschool-aged children was evaluated based on the following components: (i) Physical activity (PA)\u0026mdash;at least 180 minutes of total daily PA, including a minimum of 60 minutes of moderate-to-vigorous PA (MVPA); (ii) Screen time\u0026mdash;no more than 1 hour per day of recreational screen use; and (iii) Sleep duration\u0026mdash;between 10 to 13 hours of sleep within a 24-hour period [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5 Health-related quality of life\u003c/h2\u003e \u003cp\u003eThe Pediatric Quality of Life Inventory (PedsQL\u0026trade; 4.0) is widely used for assessing HRQoL in healthy and chronically ill children and adolescents aged 2\u0026ndash;18 years [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this study, we utilized the acute parent-report version, which assesses parents' perceptions of their child's health status over the past 7 days [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The questionnaire consists of 21 items for parents of children aged 2\u0026ndash;4 years and 23 items for parents of children aged 5\u0026ndash;6 years. Each item is scored on a five-point Likert scale (0\u0026thinsp;=\u0026thinsp;never a problem; 1\u0026thinsp;=\u0026thinsp;almost never a problem; 2\u0026thinsp;=\u0026thinsp;sometimes a problem; 3\u0026thinsp;=\u0026thinsp;often a problem; 4\u0026thinsp;=\u0026thinsp;almost always a problem). Responses are reverse-scored and linearly transformed to a 0\u0026ndash;100 scale (0\u0026thinsp;=\u0026thinsp;100, 1\u0026thinsp;=\u0026thinsp;75, 2\u0026thinsp;=\u0026thinsp;50, 3\u0026thinsp;=\u0026thinsp;25, 4\u0026thinsp;=\u0026thinsp;0), with higher scores indicating better HRQoL. The Physical Health Summary Score corresponds directly to the Physical Functioning scale, which includes examples such as walking more than one block, running, lifting heavy objects, or experiencing low energy levels. The Psychosocial Health Summary Score is calculated by summing the mean scores of the Emotional, Social, and School Functioning scales. Examples of emotional functioning include feelings of fear or anger; social functioning examples include interacting well with other children or keeping pace during play; and examples of school functioning include paying attention in class or missing school due to illness. The PedsQL\u0026trade; is widely used internationally to monitor pediatric health, with high reliability previously reported (Cronbach\u0026rsquo;s alpha\u0026thinsp;\u0026ge;\u0026thinsp;0.90) for both child self-report and parent-report versions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this study, we used questionnaires translated into English, Japanese, and Chinese [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.6 Demographic variables\u003c/h2\u003e \u003cp\u003eDemographic information on children and their parents was collected through a parent-reported questionnaire. The questionnaire included the child\u0026rsquo;s gender, age, height, and weight, as well as the parent\u0026rsquo;s gender, age, height, weight, income level, and educational level.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical Analysis\u003c/h2\u003e \u003cp\u003eComplete data from 6,634 preschool-aged children in three Asian countries (Singapore: n\u0026thinsp;=\u0026thinsp;3,672; Japan: n\u0026thinsp;=\u0026thinsp;760; China: n\u0026thinsp;=\u0026thinsp;2,202) were analyzed using statistical models aligned with the study objectives. In the first step, descriptive statistics were calculated for demographic variables, including children's age, height, weight, body mass index (BMI), and HRQoL scores, as well as parents' age, height, weight, BMI, income, and educational attainment. Continuous variables were presented as means and standard deviations, while categorical variables were summarized as percentages (%). In the second step, frequency analyses were conducted to determine the proportion of children in each country adhering to the 24-h MG for physical activity (PA), screen time, sleep duration, and all combinations thereof (PA\u0026thinsp;+\u0026thinsp;screen time, PA\u0026thinsp;+\u0026thinsp;sleep duration, screen time\u0026thinsp;+\u0026thinsp;sleep duration, and PA\u0026thinsp;+\u0026thinsp;screen time\u0026thinsp;+\u0026thinsp;sleep duration). Additionally, we calculated the proportion of children meeting individual and combined 24-h MG across the three countries. In the third step, logistic regression analyses were performed to examine associations between independent and dependent variables. The independent variables included (1) adherence to different combinations of 24-h MG (PA, screen time, and sleep duration) and (2) the total number of guidelines met. The dependent variables were the physical and psychosocial health dimensions of HRQoL among preschool-aged children in each country. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All statistical analyses were conducted using IBM SPSS version 27.0 (IBM Corp., Armonk, NY, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eTable 1 presents the demographic characteristics of participants in each country. Children\u0026rsquo;s mean age was highest in Japan at 4.5 years (\u0026plusmn;1.0). Mean height and weight were lowest among Japanese participants (105.5 \u0026plusmn; 8.2 cm; 17.3 \u0026plusmn; 3.1 kg) and highest among Chinese participants (106.5 \u0026plusmn; 8.0 cm; 18.2 \u0026plusmn; 4.9 kg). Regarding BMI categories, Singapore had the highest proportions of both underweight (16.1%, n = 520) and obese children (16.8%, n = 540). HRQoL scores were highest among Japanese children in both physical health (82.9 \u0026plusmn; 10.4) and psychosocial health domains (86.3 \u0026plusmn; 10.1). Parental mean age was highest in Japan (37.2 \u0026plusmn; 5 years). The prevalence of parental obesity was comparatively lower in Japan (13.4%, n = 100) and Singapore (10.7%, n = 369). Finally, high household income level (59.4%, n = 1307) and high parental educational level (80.0%, n = 1761) were most prevalent in China (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1. Descriptive characteristics\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbbreviations: BMI - Body Mass Index, PedsQL - Pediatric Quality of Life Inventory. Notes: Continuous variables that follow a normal distribution are presented as mean \u0026plusmn; standard deviation (M \u0026plusmn; SD). Continuous variables that do not follow a normal distribution are presented as median [25th percentile, 75th percentile]. Categorical variables are presented as n (%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 1 presents the proportion of preschool children meeting each individual and combined component of the 24-h MG across the three countries. The percentage of children meeting all three 24-h MG recommendations was highest in China (16.3%), followed by Singapore (9.7%) and Japan (2.6%). Conversely, the proportion of children who did not meet any recommendations was highest in Japan (31.6%), compared with Singapore (15.1%) and China (5.8%). Regarding individual movement behaviors, China had the highest compliance rates across all components (physical activity: 60.5%, screen time: 48.7%, sleep duration: 71.5%), while Japan reported the lowest compliance rates for physical activity (20.3%) and screen time (20.5%), and a slightly lower compliance rate for sleep duration (71.5%) compared to China.\u003c/p\u003e\n\u003cp\u003eTable 2 presents the associations between HRQoL and combinations of 24-h MG components, analyzed using logistic regression adjusted for child\u0026rsquo;s age, sex, BMI, household income, and parental education level. For physical health, a subdomain of HRQoL, significant associations were observed in Singapore and China across six combinations, excluding sleep duration alone. In Japan, significant associations were found in two combinations, both of which included physical activity. For psychosocial health, Singapore and China showed significant associations in four combinations of the 24-h MG components, while Japan demonstrated significant associations in three combinations.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Logistic regression examining the associations of 24-hour movement guidelines combinations with Health-Related Quality of Life\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: OR, odds ratio; CI, confidence interval. The OR (95% CI) represents the adjusted results. Model includes control variables, which consist of child sex, child age, child BMI, parent income, and educational level.\u003c/p\u003e\n\u003cp\u003eTable 3 presents the association between HRQoL and the number of recommended 24-h MG components met, based on logistic regression analyses adjusted for relevant covariates. For physical health, a subdomain of HRQoL, significant associations were observed in Singapore (meeting all three guidelines: OR = 1.26, 95% CI: 1.09\u0026ndash;1.45), in China (meeting two guidelines: OR = 1.22, 95% CI: 1.01\u0026ndash;1.47), and again in China (meeting all three guidelines: OR = 1.36, 95% CI: 1.11\u0026ndash;1.67). For psychosocial health, significant associations were found in Singapore (meeting all three guidelines: OR = 1.19, 95% CI: 1.04\u0026ndash;1.36) and in China (meeting all three guidelines: OR = 1.27, 95% CI: 1.01\u0026ndash;1.71).\u003c/p\u003e\n\u003cp\u003eTable 3. Logistic regression examining the associations of number of 24-hour movement guidelines recommendations met with Health-Related Quality of Life\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: OR, odds ratio; CI, confidence interval. The OR (95% CI) represents the adjusted results. Model includes control variables, which consist of child sex, child age, child BMI, parent income, and educational level.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study examined the association between optimal combinations of adherence to the 24-h MG and HRQoL among young children aged 3–6 years living in major urban areas of three Asian countries (Singapore, Japan, and China). In addition, the study explored country-specific characteristics and differences in adherence to the 24-h MG.\u003c/p\u003e\n\u003cp\u003eOur first key finding was that both physical and psychosocial health—subdomains of HRQoL—were significantly improved when preschool children in Singapore and China met all three components of the 24-h MG, and when children in Japan met two or more of these recommendations. These results suggest that full adherence to the 24-h MG plays a critical role in enhancing overall HRQoL in young children. While many previous studies have examined the association between HRQoL and individual movement behaviors such as physical activity, screen time, and sleep duration [36–41], few have adopted an integrated approach that considers the combined effects of all 24-h MG. As a result, the unique contribution of these behaviors when considered together remains unclear. This underscores the need for research frameworks that take an integrated perspective, especially since no single behavior can fully compensate for the negative effects of another [42]. Furthermore, most existing studies have focused on partial adherence—meeting one or more individual recommendations [43,44]—or have limited their target population to school-aged children aged seven and older [45,46]. In contrast, the present study focused exclusively on preschool-aged children, providing valuable early evidence to inform early childhood health policies and support the adoption of a more comprehensive and integrated approach to 24-h MG. To improve HRQoL in young children through the effective integration of all daily movement behaviors, countries should establish 24-h MG that include clear and age-appropriate guidelines for physical activity, screen time, and sleep. Additionally, regular opportunities for both structured and unstructured physical activity should be encouraged in childcare centers and preschools. It is also necessary to implement training programs for caregivers and early childhood educators, ensure consistent monitoring and evaluation, and develop supportive environments and policies that promote safe and active lifestyles for young children.\u003c/p\u003e\n\u003cp\u003eOur second key finding was that the relationship between physical health, psychosocial health, and 24-h MG, which are sub-factors of HRQoL, differed across countries. The results of this study lend support to the suggestion that cultural and environmental factors may influence both 24-h MG and HRQoL outcomes among preschool-aged children in different Asian contexts [45]. Previous research on 24-h MG in Asian young children has shown that, compared to their Western counterparts, Asian children tend to engage in lower levels of physical activity [47], spend more time on screens [48], and have shorter average sleep durations [22]. These earlier findings are consistent with the trends observed in this study and point to important implications for adherence to 24-h MG among Asian preschoolers.\u003c/p\u003e\n\u003cp\u003eIn particular, the low adherence rates to physical activity and screen time guidelines across the three countries (Singapore, Japan, and China) highlight the need for culturally tailored interventions to support healthy lifestyle formation in early childhood. In Singapore, physical health—a sub-factor of HRQoL—was strongly associated with physical activity and screen time, while psychosocial health—another sub-factor—was strongly associated with sleep, which also affected combinations of other movement behaviors. Singapore’s highly digitalized urban environment has been shown to contribute to increased screen time in young children. Furthermore, previous studies have found that an increased emphasis on early academic education and screen-based learning is associated with reduced physical activity and greater sedentary time, including screen use [27]. These challenges mirror findings from a prior study involving 2–4-year-old children in Singapore [26].\u003c/p\u003e\n\u003cp\u003eTo mitigate issues related to excessive screen time and insufficient physical activity among young children in Singapore, strategies such as limiting screen and digital game use at home and removing sleep-disrupting media devices from children's bedrooms are recommended [49]. In addition, parents should model positive physical activity behaviors, such as spending active time outdoors with their children. Research has also shown that psychosocial well-being—a sub-factor of HRQoL—is influenced by various combinations of movement behaviors, supporting the idea that longer sleep duration during early childhood contributes to better psychosocial outcomes [50].\u003c/p\u003e\n\u003cp\u003eEfforts to improve sleep quality and duration in young children in Singapore will require a multidimensional approach that includes general strategies such as sleep hygiene education, while also addressing culturally specific factors such as family sleep environments and daily sleep habits.\u003c/p\u003e\n\u003cp\u003eThis study found a positive association between physical activity and HRQoL—including both physical and psychosocial sub-factors—with the strongest effects observed among Japanese young children. These findings are consistent with previous research demonstrating that higher levels of physical activity contribute to improvements in both physical and psychosocial health in early childhood [51,52]. Among Japanese children, adherence to physical activity guidelines appeared to have a greater impact on HRQoL than adherence to other movement behavior guidelines. Moreover, the positive association with HRQoL was even stronger when physical activity guidelines were met in combination with other 24-h MG components. Consistent with earlier studies, one possible explanation for this stronger association is that physical activity may interact synergistically with other beneficial behaviors, such as reduced screen time, enhanced social engagement, and better sleep quality [53]. However, the physical activity guideline adherence rate among Japanese young children (20.3%) was considerably lower compared to their peers in China (60.5%) and Singapore (39.2%). This suggests that increasing physical activity opportunities should be considered a priority in Japan’s early childhood health policy. Urban environments in Japan often present challenges such as limited outdoor play spaces and safety concerns, which may restrict children’s ability to engage in active outdoor play. To address these barriers, policy efforts should focus on developing multi-purpose recreational facilities, improving traffic safety infrastructure, and expanding community-based physical activity programs for families and children. Additionally, since Japanese young children spend extended hours in childcare settings, it is essential to enhance physical activity opportunities and implement structured and unstructured physical activity programs within these centers to support higher levels of physical activity and healthy development [54].\u003c/p\u003e\n\u003cp\u003eIn China, screen time was found to be strongly associated with both physical and psychosocial health, the two sub-factors of HRQoL, and was also shown to influence other movement behaviors. Additionally, this study revealed that Chinese young children demonstrated significantly higher adherence rates to the 24-hour movement guidelines (24-h MG) compared to their counterparts in Japan and Singapore, particularly in terms of physical activity and sleep duration.\u003c/p\u003e\n\u003cp\u003eThese findings are in line with previous research suggesting that higher parental socioeconomic status and educational level are associated with greater awareness of, and stricter regulation of, children's movement behaviors—including physical activity, screen time, and sleep [55,56]. In China, national-level health policies such as the \u003cem\u003eHealthy China 2030 Blueprint\u003c/em\u003e and the \u003cem\u003eNational Fitness Program (2021–2025)\u003c/em\u003e have emphasized the importance of adopting the 24-h MG as a core strategy for promoting population-wide health. These policies are expected to play a vital role in further improving adherence to the 24-h MG among Chinese preschoolers by shaping family practices, educational programming, and broader community norms around early childhood health behaviors [57,58].\u003c/p\u003e\n\u003cp\u003eThis study offers several important distinctions from previous research on 24-h MG. First, it is a multinational comparative study conducted across three Asian countries—Singapore, Japan, and China—focusing specifically on preschool-aged children living in large urban areas. This design captures the unique regional characteristics and lifestyle patterns of urbanized Asian contexts. Second, unlike most existing studies that have been conducted in Western populations, this study is among the first to explore the relationship between 24-h MG and HRQoL within an Asian context. Third, While this study examined the individual and combined effects of physical activity, screen time, and sleep duration at the national level, future research could explore how cultural norms and policy environments in each country may serve as potential determinants of 24-h movement behaviors in preschool children. This approach enables a more nuanced understanding of how national public health strategies shape movement behaviors in early childhood—an area that has been largely underexplored in previous research.\u003c/p\u003e\n\u003cp\u003eHowever, this study has several limitations that should be acknowledged. First, its cross-sectional design limits the ability to draw causal inferences regarding the relationship between adherence to the 24-h MG and HRQoL. Second, the study sample consisted of preschool-aged children (3–6 years old) from Singapore, Japan, and China, and therefore the findings may not be generalizable to school-aged children or other age groups. Third, although the study included participants from three countries, all samples were drawn from large urban areas, and rural populations were not represented. As a result, the sample may not reflect national-level characteristics, particularly given that children from economically disadvantaged or rural backgrounds may experience poorer physical health, which can directly influence HRQoL outcomes [58]. Finally, all data in this study were collected through parent-reported questionnaires, which may not fully capture children’s subjective perceptions of their own health and well-being.\u003c/p\u003e\n\u003cp\u003eOverall, these findings highlight the need for culturally tailored public health interventions in each country. Policymakers in Singapore, Japan, and China should incorporate country-specific cultural practices and environmental contexts when formulating early childhood health guidelines. Additionally, future research should address potential confounders such as the COVID-19 pandemic's influence on daily routines. The study’s strength lies in its large-scale multinational design, standardized measurement tools, and comprehensive assessment of daily movement behaviors. Longitudinal studies and intervention trials are recommended to determine causal relationships and inform policy. Finally, collaboration among policymakers, educators, and families is essential for fostering sustainable behavioral changes and improving HRQoL outcomes in young children across Asia.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study found that adherence to the 24-h MG was significantly associated with better physical and psychosocial health—two sub-factors of HRQoL—among young children in Singapore and China. These findings support the growing body of evidence linking 24-hour movement behaviors to HRQoL in Asian preschool-aged children. The study contributes to the advancement of movement behavior research by strengthening the evidence base for future revisions of 24-h MG and promoting integrated approaches to health promotion in early childhood. Furthermore, by examining country-specific patterns using multinational data, this study offers insights that may inform the development of culturally and contextually appropriate intervention strategies tailored to each country. However, additional longitudinal and experimental research is needed to provide conclusive evidence on whether an integrated 24-h MG approach yields optimal HRQoL outcomes in Asian young children. Despite these limitations, this study provides a valuable foundation for policy development and practical strategies aimed at promoting early childhood health and enhancing the overall quality of life among young children in the region.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eHuman Ethics and Consent to Participate and Publish\u003c/h2\u003e\n\u003cp\u003eAll participating researchers adhered to the ethical standards outlined in the Declaration of Helsinki. The study protocols were approved by the institutional ethics committees in each respective country (Singapore: IRB2019-02-036; Japan: SU2019-31; China: HR 405\u0026thinsp;\u0026minus;\u0026thinsp;202). Considering the involvement of minor participants, informed consent for participation and publication of anonymized data was obtained from their parents and/or legal guardians prior to participation.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was funded by the Singapore Ministry of Education under the Education Research Funding Programme (OER 29/19 MCYH) and administered by the National Institute of Education, Nanyang Technological University, Singapore. The funders had no role in the design of the study; in the collection, analysis, and interpretation of data; or in writing the manuscript.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization MYHC and HJC, methodology HK, JM, MYHC and HJC, validation HK and MYHC, formal analysis TC, STL, DL, HJC, HK and MYHC, data curation HK, JM, and MYHC, writing\u0026mdash;original draft preparation HK, JM, MYHC and HJC, writing\u0026mdash;review and editing JM and MYHC, visualization JM and HK, supervision HJC, MYHC and HK, project administration TC, STL, and DL, funding acquisition MYHC. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThe WHOQOL Group. The World Health Organization Quality of Life Assessment (WHOQOL). Position paper from the World Health Organization. Soc Sci Med. 1995;41(10):1403\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRavens-Sieberer U, Herdman M, Devine J, Otto C, Bullinger M, Rose M, Klasen F. The European KIDSCREEN approach to measure quality of life and well-being in children: development, current application, and future advances. Qual Life Res. 2014;23(3):791\u0026ndash;803.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVarni JW, Seid M, Kurtin PS. 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Risk Manag Healthc Policy. 2021;14:2319\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Preschool children, Health-related quality of life, 24-hour movement guidelines, Physical activity, Screen time, Sleep duration, Asia, Urban health","lastPublishedDoi":"10.21203/rs.3.rs-6517464/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6517464/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Health-related quality of life (HRQoL) is increasingly recognized as a critical indicator of well-being in early childhood, yet its associations with 24-hour movement behaviors—physical activity, screen time, and sleep—remain underexplored in Asian populations. This study aimed to examine country-specific adherence to the 24-hour movement guidelines (24-h MG) and their associations with HRQoL among preschoolers in Singapore, Japan, and China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional survey was conducted among 6,634 children aged 3–6 years across Singapore (n = 3,672), Japan (n = 760), and China (n = 2,202). Movement behaviors were assessed using the validated SMALLQ® tool, and HRQoL was evaluated using the Pediatric Quality of Life Inventory (PedsQL™). Logistic regression models were applied to determine the associations between different patterns of 24-h MG adherence and HRQoL, adjusting for demographic variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Full adherence to all three 24-h MG components was significantly associated with higher physical and psychosocial HRQoL scores in Singapore and China. In Japan, adherence to physical activity guidelines alone was most strongly linked to improved HRQoL. Notably, Chinese children had the highest adherence rates across all individual and combined movement behaviors. Conversely, Japanese children had the lowest rates of full adherence and were more likely to fall short of all guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This study provides novel evidence from three urban Asian contexts that adherence to the 24-hour movement guidelines positively correlates with HRQoL in preschool-aged children. The findings highlight the importance of integrated movement behavior frameworks and support the development of culturally tailored public health policies to improve early childhood well-being.\u003c/p\u003e","manuscriptTitle":"City Tales - Relationship Between 24-Hour Movement Guidelines and Health-Related Quality of Life in Early Childhood in Singapore, Japan and China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 09:50:24","doi":"10.21203/rs.3.rs-6517464/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-30T11:50:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-27T20:09:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-26T23:02:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-22T09:10:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126670931584204539371315245344833163110","date":"2025-05-16T20:01:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45878267661964356224240040813262796399","date":"2025-05-16T07:11:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261042460039211954416508737152017597995","date":"2025-05-15T11:13:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-15T08:08:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-12T18:02:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-08T02:41:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Health and Quality of Life Outcomes","date":"2025-04-24T05:57:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d33f1eac-c11a-431c-9f98-ee97e14e4da9","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-04T16:47:58+00:00","versionOfRecord":{"articleIdentity":"rs-6517464","link":"https://doi.org/10.1186/s12955-025-02408-5","journal":{"identity":"health-and-quality-of-life-outcomes","isVorOnly":false,"title":"Health and Quality of Life Outcomes"},"publishedOn":"2025-07-28 16:29:18","publishedOnDateReadable":"July 28th, 2025"},"versionCreatedAt":"2025-05-20 09:50:24","video":"","vorDoi":"10.1186/s12955-025-02408-5","vorDoiUrl":"https://doi.org/10.1186/s12955-025-02408-5","workflowStages":[]},"version":"v1","identity":"rs-6517464","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6517464","identity":"rs-6517464","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}