Comparing Childhood Obesity Prevalence in Relation to Neighborhood Recreational Area Availability Using Harmonized National and Regional Data

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This study investigated the relationship between the availability and type of recreational areas and school children’s weight status, using national and regional levels, to inform community-tailored interventions. Subjects/Methods A cross-sectional analysis using harmonized data (N = 626) from the Hellenic National Nutrition and Health Survey (HNNHS) and Health4EUkids studies of children aged 7–13 years old. Recreational area availability was tabulated in national and regional areas. The probability of overweight and obesity was estimated following multinomial logistic regression analysis to investigate the likelihood of children with overweight or obesity by total recreational areas available and by type. All statistical analyses were performed using STATA 18.0 (Texas Ltd.). Results Overweight and obesity prevalence was 25.2% and 15.3% in total, with obesity rates being slightly higher in the regional sample compared to the national (17.6% and 13.1%, respectively). Patterns of area type and distribution differed between national and regional areas. Total recreational area access (≥ 2 areas) was associated with lower overweight/obesity prevalence (38.3% vs. 56.5% for 0–1 areas, p = 0.030), with sports-center availability linked to a 7% reduction in obesity probability. No significant effect was found with park presence alone. Conclusions Increased neighborhood recreational area availability, particularly sports centers, was associated with lower obesity risk among Greek children, with notable regional differences, highlighting the need for localized infrastructure distribution. Further studies should address obesogenic elements such as food outlet proximity and utilize larger regionally stratified samples for robust spatial analysis. Health sciences/Risk factors Health sciences/Health care/Public health/Epidemiology environment recreational areas physical activity childhood obesity regional disparities Figures Figure 1 Figure 2 Figure 3 Introduction Despite the physical activity (PA) guidelines for healthy living, in children and adolescents, globally 81% of students, aged 11–17 years old, remain insufficiently active ( 1 ), not meeting the 60-minute per day goal. This inactivity could be a factor that contributes to the increasing incidence of childhood obesity worldwide. Community-based interventions have shown positive effects on PA levels, with many intrinsic and extrinsic factors influencing children’s ability to meet these recommendations. The availability and access to recreational areas, including parks, playgrounds, and sports facilities, in children’s neighborhood is one such extrinsic factor. Participation in sports is often tied with access to recreational facilities, the latter acting as a barrier or facilitator to physical activity enrollment among children and adolescents ( 2 ). Numerous studies have examined how the urban built environment supports or hinders active lifestyles ( 3 ). An emphasis has been given to parks and green spaces ( 4 , 5 ), less is known about the influence of specific recreational programs and sports centers and evidence linking access to recreational areas and children’s weight status remains inconsistent. Specifically, a systematic review (Jia et al. 2021), reported that 13 out of 21 studies found evidence of negative association between access to green space and weight-related outcomes, findings varied greatly by geographical region ( 6 ). Likewise, nuanced relationships between parks, playgrounds, and youth obesity have been reported, affected by biological sex and socioeconomic (SES) level ( 7 ). Emerging evidence suggests that the type and distribution of recreational areas may have a different effect on PA, and obesity depending on demographic characteristic with differences being reported on national and regional levels ( 8 – 11 ). Demographic disparities, such as uneven access to high-quality facilities or safety concerns across regions, are a characteristic regional factor, have been found to be an important moderator in PA attainment ( 12 ) with subsequent side effects. For instance, a recent study found that the likelihood of being in a higher weight category increased as the number of amenities decreased, addressing specific amenities that included the presence of parks/playgrounds, recreation-community centers and clubs, walking paths and sidewalks, and libraries ( 13 ). The same study reported that the highest likelihood of obesity (6% higher) was found in neighborhoods with no amenities and much detraction, emphasizing once again regional differences associated with variations in SES level. All these results highlight the importance of distinguishing national from region-specific trends ( 9 , 13 ). Population lifestyle characteristics may therefore vary within a nation, and localized environments therefore uniquely contributing to children’s opportunities for PA attainment and healthy weight. Also, the type of recreational areas, such as open parks and playgrounds compared to sports facilities, has not been sufficiently examined. Meeting PA movement guidelines is a challenge for children, especially when recreational areas are not available in their neighborhood ( 4 , 5 , 14 ), a factor that can affect children’s weight status. One of the main questions is whether there are differences between regional and national data, providing valuable insights into local versus broader effects - hence adapting interventions to address community-based needs. This study, therefore, aimed to examine the association between the number and type of available recreational areas in children’s neighborhoods and obesity-related outcomes, comparing national and region-specific data. By exploring these relationships, this research seeks to provide insights for tailoring interventions to address community-based needs more effectively. Methods Study design The Hellenic National Nutrition and Health Survey (HNNHS) is a national representative study conducted between 2013 and 2015 and enrolled all individuals over 6 months of age residing in Greece at that time. In summary the selection of participants in HNNHS was performed with a random stratified design based on 2011 census data of the Hellenic Statistical Authority and resulted in 4574 participants over 6 months of age (42.5% male and 57.5% female), from all Greek prefectures. Individuals unable to provide informed consent of participation were excluded from the survey. Details on study design and methodology have been described in detail elsewhere ( 15 ). Ethical approval was obtained from the Ethics Committee of the Department of Food Science and Human Nutrition of the Agricultural University of Athens and by the Hellenic Data Protection Authority (HDPA). All members of the staff signed confidentiality agreements, and all adult volunteers signed an informed consent form. The Health4EUkids project is a European intervention program that aims to prevent childhood obesity through the adaptation of best practices in healthy living, aiming to combine physical activity and healthy diet. The project has been designed according to Grunau moves and Smart Family ( 16 , 17 ) best practices, taking into consideration national characteristics. The program commenced in 2023 and is still being implemented (till September 2025) in Patras, the 3rd larger city of Greece and the biggest capital of the 6th Health Administration Authority (Western Greece). More precisely, the project takes place in a specific neighbourhood/area, characterized of high socioeconomic differences. It’s an urban and overcrowded area that consists of government-subsidized housing areas. Additionally, in the area there are living many Romas and immigrants, whose children attend the local primary schools. Three elementary schools (3 out of 4 invited, 75%) consented to be included in the program. For this specific study, the community-based intervention baseline data of Grunau moves were used. Ethical approval was obtained from Bioethics Committee of University of Patras (Grant Number 101082462) and the Regional Directorate of Primary and Secondary Education of Western Greece (number of approval: 304; date: 26/10/2023). Children with co-morbidities, disabilities (physical and mental) from both studies were excluded in these analyses. The methodology in both studies followed the guidelines outlined in the World Medical Association (WMA) Declaration of Helsinki. Weight status The data were harmonized in terms of variable names, coding schemes, and groupings, to enable direct comparisons. Specific variables examined were biological sex, area of residence, age range (school-aged children attending primary school were only included), weight status, and total available recreational areas. Baseline data from each time period were compared. For data harmonization, a total of 313 school-aged children of the same age range were used from HNNHS and 313 from Health4EUkids. Weight and height data were self-reported by their primary guardians in the HNNHS study which were cross-referenced with 1. Random measurements, and 2. Medical records (the child’s health card when available). From Health4EUkids, data were obtained from their medical records as kept at the school districts or reported by parents if these were within the past months. Weight status was obtained following the latest WHO reference guidelines (WHO Growth Reference (2007) ( 18 ) in both studies. Specifically, Body Mass Index (BMI) for age was classified as: Severe thinness: BMI for age <-3SD Thinness: -3SD ≥ BMI for age <-2SD Healthy Weight: -2SD ≥ BMI for age < + 1 SD (equivalent to BMI < 25 kg/m² at 19 years). Overweight: +1 SD ≥ BMI for age < + 2SD (equivalent to BMI ≥ 25 kg/m² at 19 years). Obesity: BMI-for-age ≥ + 2 SD (equivalent to BMI ≥ 30 kg/m² at 19 years) Recreational Area Definition and Assessment Information on the availability of open areas was collected. In detail, each child’s primary guardian enrolled in the HNNHS study was asked to state the number of recreational areas present in their neighborhood, as performed by other large national surveys ( 5 ). To obtain accurate results, respondents were asked to state yes or no for the availability of (i) open areas, (ii) parks (including playgrounds), (iii) gyms, (iv) swimming pools, and (iv) other sports-clubs, including basketball and football courts, and gymnastics, in their neighborhood. Based on their answers, the sum of all available areas was calculated. The responses were then categorized as “0”, “1” and “≥2” available areas. Any open area or sports center was also tabulated. In the Health4EUkids study, the total available areas surrounding each elementary school where students were enrolled were tabulated following a detailed observation and cartography of the surrounding areas and subsequent map generation, which was based in EARPS direct observation tool (Environmental Assessment of Public Recreation Spaces). The EARPS tool is designed to assess physical environment of recreational areas and their use ( 19 , 20 ). Children’s neighborhoods were classified according to walkability to the various recreational areas, using their main school district as the point of reference. The resulting maps were printed and were distributed to each child for their information. They were also uploaded to the program’s website to be freely accessible (a QR code was also distributed to families so that they could easily access these maps). Total available areas and types of areas available were examined in relation to children’s weight status. Statistical analysis Descriptive statistics were calculated and presented as mean (± SD) for continuous normally distributed variables and relative frequencies for categorical data (N, %). Results were reported by study, and between-study group differences were assessed using student’s t-test and chi-square test, respectively. Data were aggregated in the beginning and were then stratified by study analyzed to address year and area differences (total Greek region compared to specific area of Patras). Graphs were generated to report the outcome in relation to the various levels of exposures assessed in total and by sub-study. The probability of children with overweight and obesity were estimated following multinomial logistic regression by total recreational areas available and by type (presence of parks and sports centers). All statistical analyses were performed using STATA 18.0 (Texas Ltd.). Results A total of 626 children were included in this study (SD 1.9; HNNHS: 331; 51.2%, and Health4EUkids: 316; 48.8%). The mean age differed by half year approximately being 10.3 in HNNHS and 9.8 years in Health4EUkids (p < 0.001) but no differences were found in mean BMI, weight status categorization and biological sex (Table 1 ). A total of 25.2% of children were categorized with overweight and 15.3% with obesity. Significant differences were found between studies in the number of available recreational areas (p < 0.001). Specifically, in HNNHS, a greater variation, including children with no available areas (9.4%) and some with as many as 6 areas (9.7%) was found, whereas in Health4EUkids study all children had at least 2 available recreational areas; highest proportions in 2 (44.9%), 3 (27.2%), and 4 (27.8%) areas. Table 1 Descriptive Characteristics of the Study Population (HNNHS and Health4EUkids) HNNHS Health4EUkids Total Test 316 (51.2%) 316 (48.8%) 647 (100.0%) Age in completed years (exact) 10.3 (2.3) 9.8 (1.3) 10.0 (1.9) 0.001 BMI (kg/m 2 ) 18.9 (3.8) 18.5 (4.0) 18.7 (3.9) 0.244 Gender Males 185 (55.9%) 165 (52.4%) 350 (54.2%) 0.371 Females 146 (44.1%) 150 (47.6%) 296 (45.8%) Weight Status Normal weight 188 (60.1%) 184 (58.8%) 372 (59.4%) 0.257 with overweight 84 (26.8%) 74 (23.6%) 158 (25.2%) With Obes status 41 (13.1%) 55 (17.6%) 96 (15.3%) Total Available Recreational Areas 0 31 (9.4%) 0 (0.0%) 31 (4.8%) < 0.001 1 36 (10.9%) 0 (0.0%) 36 (5.6%) 2 48 (14.6%) 142 (44.9%) 190 (29.5%) 3 61 (18.5%) 86 (27.2%) 147 (22.8%) 4 71 (21.6%) 88 (27.8%) 159 (24.7%) 5 50 (15.2%) 0 (0.0%) 50 (7.8%) 6 32 (9.7%) 0 (0.0%) 32 (5.0%) BMI: Body Mass Index; Weight Status as per WHO definition Figure 1 presents the total number of recreational areas categorized by type as per the study’s aim, parks and sports centers, and the proportion of children with overweight or obesity, pulling information from the total study population, the national HNNHS study, and the regional Health4EUkids study. Across the total population and in both sub-studies, over 2 recreational areas in the neighborhood corresponded to a lower proportion of children classified with overweight or obesity. This trend was observed in the total sample and the Health4EUkids sub-study, although in the HNNHS, over 2 available areas did not seem to modify the effect on children’s weight status. Overall, there was a parallel increase in number of parks with the increasing number of available recreational areas, but this was not consistent for sport-center availability (Fig. 1). In the national HNNHS sample, sports-centers were largely present only in neighborhoods with at least 3 recreational areas, whereas in the Health4EUkids study, both parks and sports-centers were present even when there were just two recreational areas per neighborhood. Also, the pattern differed between the national and the regional study with the availability of sports-centers being proportionally higher than parks in the national sample for neighborhoods with three recreational areas. Also in the regional study (Health4EUkids) at least 2 areas were available in each neighborhood examined, reinforcing the unique distribution of recreational infrastructure in that setting. In Fig. 1a, a decreasing trend of overweight and obesity rates are also seen as the number of recreational areas increase from 56.5% in neighborhoods with 0–1 areas compared to 38.3% for ≥ 3 recreational areas. Although the trend was observed in both studies, the total rates differed. In the HNNHS study (Fig. 1b), the proportion of overweight/obesity was higher with 0–1 areas (56.5%) and significantly dropped when 2 areas were available (28.9%), but this slightly rose again with ≥ 3 areas to 37.4%. In the Health4EUKids study, the overweight/obesity rates decreased less pronounced, from 43.6% in areas with 2 recreational sites to 39.3% in areas with ≥ 3. The presence of two recreational areas was associated with a 14.6 percentage point decrease in the probability of a child being overweight (p = 0.030), but this did not remain statistically significant as the number increased (Fig. 2 ). The absence of adequate available recreational areas was also associated with childhood overweight and obesity, increasing the probability by 16%. In Fig. 3 , results following an adjusted logistic regression are shown, with the probability for overweight or obesity decreasing by 7% with the presence of sports-centers. No effect was found with park presence. Discussion This study aimed to examine the association between the availability of recreational areas in the neighborhood (type and number) and childhood obesity prevalence, comparing national and region-specific data, in order to provide insights for tailoring interventions that address community-based needs more effectively. The main findings highlight that greater overall access to recreational areas was associated with lower rates of childhood overweight and obesity with a more pronounced effect being seen with the presence of sports-centers and no effect with park availability. However, the pattern of availability differed by study and by type of recreational facility, with sports-centers being less uniformly distributed compared to parks, especially on the national level and sports-centers being of particular importance in the regional study. This may be explained due to type and number of area availability, but it also may be due to the motivational factor and/or specific activities associated with sports centers that emphasize on specific trainings and not overall play. The above may be important for the specific age group that this study examined, including school-aged children 7 to 13 years of age. In the HNNHS, children’s access to recreational areas was highly variable, whereas in Health4EUkids, there was universal access to at least two areas per child. This marked difference in recreational area availability between the national (HNNHS) and regional (Health4EUkids) samples may have implications for analyses related to environment and health outcomes, as well as public health measures that need to be taken. In accordance to these results, Potwarka and colleagues found that proximity to park space was associated with higher likelihood of being normal weight ( 4 ), although another study, on a national level, found that children without parks were 25% and 32% more likely to be with overweight or obesity, respectively ( 5 ). The potential preventive effect of available recreational areas was confirmed during the pandemic where children living in greener neighborhoods were found to experience smaller increases in obesity during this time compared to children in less green neighborhoods ( 21 ). Results, however, differed by urbanicity, suggesting that compiling data at regional level is important. The importance of green spaces, parks and recreational resources have been reported by longitudinal studies as well, where children with better access to park and recreational resources were less likely to experience significant increases in attained BMI ( 3 ) and green space availability was inversely associated with BMI with increasing age ( 22 ). In both cases a greater effect was reported in boys. Of great interest is a study that reported that the percentage of adolescents with overweight and obesity significantly increased with higher green area density, in the participants' surroundings. The authors speculated whether the results were due to the level of accessibility and attractiveness, since some children and adolescents might need more facilitated green areas for sport and physical activity ( 23 ), such as sports centers, and not overall green area presence. This confirms this study’s results where children of school aged years with higher availability to sports centers were less likely to be with overweight or obesity, with the hypothesis being that these children had higher physical activity level. The exposure to green spaces has been correlated with a lower incidence of obesity ( 24 ) and the built environment has been found to be a nonspecific predictor of treatment outcome and can influence behavioral interventions. School-based environments and interventions, play a particularly important role in communities with fewer neighborhood facilities, although demographic disparities, which is a characteristic regional factor, were found to be an important moderator in physical activity attainment in schools ( 12 ). This can help understand the variability of results reported between various community settings between weight status and availability of recreational areas. Therefore, although neighbourhood-built environment features ( 25 ) as well as park density following behavioural weight management intervention ( 26 ), could potentially help children attain lower weight status, results remain controversial, as shown by .the null results that were derived in an Australian randomised control trial (RCT), in students 8–13years old. In this RCT, physical activity environment including walkability, greenspace and recreational facilities, surrounding regional primary schools, was not associated with weight status or meeting physical activity recommendations in adjusted models ( 27 ), confirming results found in our study. These findings could be used to point out areas at higher need of interventions to reduce obesity burden (Carlson et el 2021). Another factor that could influence the effect of the number of recreation opportunities on children’s weight status is the concentration of fast-food outlets also within the vicinity or on the way to and from ( 28 ). Although this was not addressed in the specific study, these can be further cartographied and addressed when evaluating the Grunau Moves intervention program at the end of the study. The World Health Organization’s Health Promoting Schools (HPS) framework found that this approach improved students’ physical activity and fitness, and increased fruit and vegetable intake. However, there was considerable heterogeneity in reported impacts with process evaluations must move beyond simple measures of acceptability/fidelity to include detailed contextual information to illuminate exactly what works, for whom, in what contexts and why ( 29 ). Further work is required in order to understand the role these various neighborhood elements play, and how they may interact, in influencing the children’s weight status. Limitations of the study included the lack of statistical power to assess specific differences within the national (HNNHS) study when data are stratified by region. Also, the concentrations of fast-food restaurants and other obesogenic elements in the neighborhood were not accounted for, which may have affected the observed prevalence distribution and measure of effect. Other limitations include that weight and height data were self-reported when these were not recently documented in the children’s medical records, and the methods used to obtain information of total available recreational areas in HNNHS study were also self-reported. The questionnaire used specifically included all potential areas for probing to minimize reporting bias. This study takes an exploratory role in generating hypotheses for further investigation. The obesity prevention benefits should not be limited to formal recreation and physical activity programs but should enable age-appropriate activities found within the neighborhood. Total recreational areas may not be sufficient to reduce childhood obesity if these are not age specific while targeting facility type, accessibility, and quality is important. For school aged children sports centers showed a greater effect on weight status. This suggests that community and school-based interventions should prioritize both the presence and use of such venues, by creating awareness of their presence through maps for children and families that are unaware. Addressing local disparities in access and the specific needs and preferences of children is also important. Future research with larger, regionally representative samples would be needed to robustly examine more spatial differences. Abbreviations The following abbreviations are used in this manuscript: ADM Administrative region BMI Body Mass Index CI Confidence Interval EARPS Environmental Assessment of Public Recreation Spaces HNNHS Hellenic National Nutrition and Health Survey OR Odds Ratio OSF Open Science Framework PA Physical Activity RCT Random Clinical Trial(s) SD Standard Deviation WHO World Health Organization Declarations Author Contributions: EM was responsible for conceptualization of study; EP and AZ were responsible for data collection and acquisition; EM and EP for data curation and management; EM for formal analysis and statistical interpretation; and EM, EP, NM, AA for writing of original draft preparation; AP was responsible for reviewing and editing the project; AP, AZ and GK for project administration and coordination and funding acquisition. F unding This research was funded by European Union, EU4Health program. Ethical approval was obtained from Bioethics Committee of University of Patras (Grant Number 101082462) and the Regional Directorate of Primary and Secondary Education of Western Greece (number of approval: 304; date: 26/10/2023). Data Availability Statement All data supporting this study’s findings are available upon reasonable request from the corresponding author. Additionally, the data will be made publicly accessible on the Open Science Framework (OSF) after a provisional period of one year. Acknowledgments We would like to thank all health care professionals that selected and documented the information required. Special thanks to the whole HNNHS collaborators and the 6 th Heath ADM team. References Guthold R, Stevens GA, Riley LM, Bull FC. Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1·6 million participants. The Lancet Child & Adolescent Health. 2020;4(1):23–35. 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International Journal of Environmental Health Research. 2025;35(7):1772–92. Howell NA, Booth GL. The Weight of Place: Built Environment Correlates of Obesity and Diabetes. Endocrine Reviews. 2022;43(6):966–83. Armstrong B, Lim CS, Janicke DM. Park Density Impacts Weight Change in a Behavioral Intervention for Overweight Rural Youth. Behavioral Medicine. 2015;41(3):123–30. Jacobs J, Crooks N, Allender S, Strugnell C, Backholer K, Nichols M. Is the physical activity environment surrounding primary schools associated with students' weight status, physical activity or active transport, in regional areas of Victoria, Australia? A cross-sectional study. BMJ Open. 2021;11(7):e045785. Gilliland JA, Rangel CY, Healy MA, Tucker P, Loebach JE, Hess PM, et al. Linking Childhood Obesity to the Built Environment: A Multi-level Analysis of Home and School Neighbourhood Factors Associated With Body Mass Index. Canadian Journal of Public Health. 2012;103(S3):S15-S21. Langford R, Bonell C, Jones H, Campbell R. Obesity prevention and the Health promoting Schools framework: essential components and barriers to success. International Journal of Behavioral Nutrition and Physical Activity. 2015;12(1):15. Additional Declarations There is NO conflict of interest to disclose Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7502433","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":516873487,"identity":"9f708c9b-3fa2-440e-ae5a-ab85e4133cfb","order_by":0,"name":"Emmanuela Magriplis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYNACAwYZNgbmA6Rp4WFjYEsgzR4eIDIgTim/2OHHrysK7vDw8Z/5+JmnhsFuewMBLZKz08wszxg842GTyN0szXOMIXnOAQJaDG4nmBk2GBwGauHdIA30UbIEIYfZ307/BtHCf+bxb55/RGgxkM4xfgjWwpDDJs3bxmBHUIvE7ZwyxgawX4CemtsnkUBQC//s9M0fG/7ckZPvP/z4xptvNvYEtQABG1DRAbitiQ1EaGH+gKSFwZ4IHaNgFIyCUTDCAADx8Dl3/UyWDwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-6517-6857","institution":"Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Emmanuela","middleName":"","lastName":"Magriplis","suffix":""},{"id":516873488,"identity":"116f7033-6663-471b-8344-6ac7b4bcc2e8","order_by":1,"name":"Eleni Papachatzi","email":"","orcid":"","institution":"University of Patras","correspondingAuthor":false,"prefix":"","firstName":"Eleni","middleName":"","lastName":"Papachatzi","suffix":""},{"id":516873489,"identity":"2c07e395-3225-4ae9-9c9a-6153380d56b6","order_by":2,"name":"Niki Myrintzou","email":"","orcid":"","institution":"Agricultural University of Athens, Athens, Greece","correspondingAuthor":false,"prefix":"","firstName":"Niki","middleName":"","lastName":"Myrintzou","suffix":""},{"id":516873490,"identity":"5fd9ce83-5af8-4205-bcd1-6f8c3f2c743d","order_by":3,"name":"Antonis Zampelas","email":"","orcid":"","institution":"Agricultural University of Athens, Athens, Greece","correspondingAuthor":false,"prefix":"","firstName":"Antonis","middleName":"","lastName":"Zampelas","suffix":""},{"id":516873491,"identity":"a8bfdd30-6543-4682-b60c-9146b7de8185","order_by":4,"name":"Alexandra Angelakopoulou","email":"","orcid":"","institution":"University General Hospital of Patras, Patras, Greece","correspondingAuthor":false,"prefix":"","firstName":"Alexandra","middleName":"","lastName":"Angelakopoulou","suffix":""},{"id":516873492,"identity":"d2a4845c-9e8c-4502-8429-1b4ea461f1b8","order_by":5,"name":"George Karydas","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"","lastName":"Karydas","suffix":""},{"id":516873493,"identity":"c7f4ed38-16b9-4951-b507-026a4c7ce246","order_by":6,"name":"Apostolos Vantarakis","email":"","orcid":"","institution":"University of Patras, Medical School","correspondingAuthor":false,"prefix":"","firstName":"Apostolos","middleName":"","lastName":"Vantarakis","suffix":""}],"badges":[],"createdAt":"2025-08-31 18:55:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7502433/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7502433/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92474729,"identity":"7e4c3857-381f-4d14-bdc2-e7fae01da5e3","added_by":"auto","created_at":"2025-09-30 07:13:19","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":156913,"visible":true,"origin":"","legend":"","description":"","filename":"Childhoodobesityinrelationtorecreationalareashnnhshealth4eukidsfinalversion.docx","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/ec73f9d45c7c4f47f135ef0c.docx"},{"id":92476424,"identity":"938c5483-71b8-41cb-ab03-559797d4b4fe","added_by":"auto","created_at":"2025-09-30 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07:13:20","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3908,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/7f3d7a177d52a1c2d2f37774.png"},{"id":92474735,"identity":"985173e4-f8a7-4338-89da-5f6a49fcc3f4","added_by":"auto","created_at":"2025-09-30 07:13:20","extension":"xml","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":88529,"visible":true,"origin":"","legend":"","description":"","filename":"2025IJO015070structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/06641857fae926175025eb4f.xml"},{"id":92474738,"identity":"217c3265-917b-4732-981f-bdcd020c72dd","added_by":"auto","created_at":"2025-09-30 07:13:20","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95699,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/f583a5309d194c51163d0ca2.html"},{"id":92474725,"identity":"40abd64f-7fa0-4d9d-bb6e-955a0808ecb1","added_by":"auto","created_at":"2025-09-30 07:13:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78063,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of overweight/obesity status by Number of Recreational Areas, and Presence of Parks and Sports-Centers (a) total study population; (b) in HNNHS study; (c) in Health4EUkids study\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/d46f403cefb8033a0af8cdef.png"},{"id":92476425,"identity":"5d400ae0-d3b4-49e8-9b9e-5cbe0ae5f912","added_by":"auto","created_at":"2025-09-30 07:21:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":12346,"visible":true,"origin":"","legend":"\u003cp\u003eProbability of childhood overweight-obesity status by number of available recreational areas in the neighborhood\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/e649ba76a0a2901d1a388eba.png"},{"id":92474727,"identity":"31dc10b3-8082-4d73-b98f-e6584321f853","added_by":"auto","created_at":"2025-09-30 07:13:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":13098,"visible":true,"origin":"","legend":"\u003cp\u003eProbability of childhood overweight-obesity status by type of recreational area\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/52ddc925de329c25176b0dbb.png"},{"id":94728806,"identity":"2b653ca9-89ee-40ee-ab43-8d8d7cfe5aae","added_by":"auto","created_at":"2025-10-30 07:04:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":644419,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7502433/v1/30171bdb-6ba8-4bdb-bc61-354367acdd52.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Comparing Childhood Obesity Prevalence in Relation to Neighborhood Recreational Area Availability Using Harmonized National and Regional Data","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDespite the physical activity (PA) guidelines for healthy living, in children and adolescents, globally 81% of students, aged 11\u0026ndash;17 years old, remain insufficiently active (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), not meeting the 60-minute per day goal. This inactivity could be a factor that contributes to the increasing incidence of childhood obesity worldwide.\u003c/p\u003e\u003cp\u003eCommunity-based interventions have shown positive effects on PA levels, with many intrinsic and extrinsic factors influencing children\u0026rsquo;s ability to meet these recommendations. The availability and access to recreational areas, including parks, playgrounds, and sports facilities, in children\u0026rsquo;s neighborhood is one such extrinsic factor. Participation in sports is often tied with access to recreational facilities, the latter acting as a barrier or facilitator to physical activity enrollment among children and adolescents (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNumerous studies have examined how the urban built environment supports or hinders active lifestyles (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). An emphasis has been given to parks and green spaces (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), less is known about the influence of specific recreational programs and sports centers and evidence linking access to recreational areas and children\u0026rsquo;s weight status remains inconsistent. Specifically, a systematic review (Jia et al. 2021), reported that 13 out of 21 studies found evidence of negative association between access to green space and weight-related outcomes, findings varied greatly by geographical region (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Likewise, nuanced relationships between parks, playgrounds, and youth obesity have been reported, affected by biological sex and socioeconomic (SES) level (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEmerging evidence suggests that the type and distribution of recreational areas may have a different effect on PA, and obesity depending on demographic characteristic with differences being reported on national and regional levels (\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Demographic disparities, such as uneven access to high-quality facilities or safety concerns across regions, are a characteristic regional factor, have been found to be an important moderator in PA attainment (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) with subsequent side effects. For instance, a recent study found that the likelihood of being in a higher weight category increased as the number of amenities decreased, addressing specific amenities that included the presence of parks/playgrounds, recreation-community centers and clubs, walking paths and sidewalks, and libraries (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The same study reported that the highest likelihood of obesity (6% higher) was found in neighborhoods with no amenities and much detraction, emphasizing once again regional differences associated with variations in SES level. All these results highlight the importance of distinguishing national from region-specific trends (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Population lifestyle characteristics may therefore vary within a nation, and localized environments therefore uniquely contributing to children\u0026rsquo;s opportunities for PA attainment and healthy weight. Also, the type of recreational areas, such as open parks and playgrounds compared to sports facilities, has not been sufficiently examined.\u003c/p\u003e\u003cp\u003eMeeting PA movement guidelines is a challenge for children, especially when recreational areas are not available in their neighborhood (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), a factor that can affect children\u0026rsquo;s weight status. One of the main questions is whether there are differences between regional and national data, providing valuable insights into local versus broader effects - hence adapting interventions to address community-based needs. This study, therefore, aimed to examine the association between the number and type of available recreational areas in children\u0026rsquo;s neighborhoods and obesity-related outcomes, comparing national and region-specific data. By exploring these relationships, this research seeks to provide insights for tailoring interventions to address community-based needs more effectively.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design\u003c/h2\u003e\u003cp\u003eThe Hellenic National Nutrition and Health Survey (HNNHS) is a national representative study conducted between 2013 and 2015 and enrolled all individuals over 6 months of age residing in Greece at that time. In summary the selection of participants in HNNHS was performed with a random stratified design based on 2011 census data of the Hellenic Statistical Authority and resulted in 4574 participants over 6 months of age (42.5% male and 57.5% female), from all Greek prefectures. Individuals unable to provide informed consent of participation were excluded from the survey. Details on study design and methodology have been described in detail elsewhere (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Ethical approval was obtained from the Ethics Committee of the Department of Food Science and Human Nutrition of the Agricultural University of Athens and by the Hellenic Data Protection Authority (HDPA). All members of the staff signed confidentiality agreements, and all adult volunteers signed an informed consent form.\u003c/p\u003e\u003cp\u003eThe Health4EUkids project is a European intervention program that aims to prevent childhood obesity through the adaptation of best practices in healthy living, aiming to combine physical activity and healthy diet. The project has been designed according to Grunau moves and Smart Family (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) best practices, taking into consideration national characteristics. The program commenced in 2023 and is still being implemented (till September 2025) in Patras, the 3rd larger city of Greece and the biggest capital of the 6th Health Administration Authority (Western Greece). More precisely, the project takes place in a specific neighbourhood/area, characterized of high socioeconomic differences. It\u0026rsquo;s an urban and overcrowded area that consists of government-subsidized housing areas. Additionally, in the area there are living many Romas and immigrants, whose children attend the local primary schools. Three elementary schools (3 out of 4 invited, 75%) consented to be included in the program. For this specific study, the community-based intervention baseline data of Grunau moves were used. Ethical approval was obtained from Bioethics Committee of University of Patras (Grant Number 101082462) and the Regional Directorate of Primary and Secondary Education of Western Greece (number of approval: 304; date: 26/10/2023). Children with co-morbidities, disabilities (physical and mental) from both studies were excluded in these analyses. The methodology in both studies followed the guidelines outlined in the World Medical Association (WMA) Declaration of Helsinki.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eWeight status\u003c/h3\u003e\n\u003cp\u003eThe data were harmonized in terms of variable names, coding schemes, and groupings, to enable direct comparisons. Specific variables examined were biological sex, area of residence, age range (school-aged children attending primary school were only included), weight status, and total available recreational areas. Baseline data from each time period were compared.\u003c/p\u003e\u003cp\u003eFor data harmonization, a total of 313 school-aged children of the same age range were used from HNNHS and 313 from Health4EUkids. Weight and height data were self-reported by their primary guardians in the HNNHS study which were cross-referenced with 1. Random measurements, and 2. Medical records (the child\u0026rsquo;s health card when available). From Health4EUkids, data were obtained from their medical records as kept at the school districts or reported by parents if these were within the past months.\u003c/p\u003e\u003cp\u003eWeight status was obtained following the latest WHO reference guidelines (WHO Growth Reference (2007) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) in both studies. Specifically, Body Mass Index (BMI) for age was classified as:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eSevere thinness: BMI for age \u0026lt;-3SD\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThinness: -3SD\u0026thinsp;\u0026ge;\u0026thinsp;BMI for age \u0026lt;-2SD\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eHealthy Weight: -2SD\u0026thinsp;\u0026ge;\u0026thinsp;BMI for age\u0026thinsp;\u0026lt;\u0026thinsp;+\u0026thinsp;1 SD (equivalent to BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m\u0026sup2; at 19 years).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eOverweight: +1 SD\u0026thinsp;\u0026ge;\u0026thinsp;BMI for age\u0026thinsp;\u0026lt;\u0026thinsp;+\u0026thinsp;2SD (equivalent to BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u0026sup2; at 19 years).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eObesity: BMI-for-age\u0026thinsp;\u0026ge;\u0026thinsp;+\u0026thinsp;2 SD (equivalent to BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2; at 19 years)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003eRecreational Area Definition and Assessment\u003c/h3\u003e\n\u003cp\u003eInformation on the availability of open areas was collected. In detail, each child\u0026rsquo;s primary guardian enrolled in the HNNHS study was asked to state the number of recreational areas present in their neighborhood, as performed by other large national surveys (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). To obtain accurate results, respondents were asked to state yes or no for the availability of (i) open areas, (ii) parks (including playgrounds), (iii) gyms, (iv) swimming pools, and (iv) other sports-clubs, including basketball and football courts, and gymnastics, in their neighborhood. Based on their answers, the sum of all available areas was calculated. The responses were then categorized as \u0026ldquo;0\u0026rdquo;, \u0026ldquo;1\u0026rdquo; and \u0026ldquo;\u0026ge;2\u0026rdquo; available areas. Any open area or sports center was also tabulated.\u003c/p\u003e\u003cp\u003eIn the Health4EUkids study, the total available areas surrounding each elementary school where students were enrolled were tabulated following a detailed observation and cartography of the surrounding areas and subsequent map generation, which was based in EARPS direct observation tool (Environmental Assessment of Public Recreation Spaces). The EARPS tool is designed to assess physical environment of recreational areas and their use (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Children\u0026rsquo;s neighborhoods were classified according to walkability to the various recreational areas, using their main school district as the point of reference. The resulting maps were printed and were distributed to each child for their information. They were also uploaded to the program\u0026rsquo;s website to be freely accessible (a QR code was also distributed to families so that they could easily access these maps). Total available areas and types of areas available were examined in relation to children\u0026rsquo;s weight status.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were calculated and presented as mean (\u0026plusmn;\u0026thinsp;SD) for continuous normally distributed variables and relative frequencies for categorical data (N, %). Results were reported by study, and between-study group differences were assessed using student\u0026rsquo;s t-test and chi-square test, respectively. Data were aggregated in the beginning and were then stratified by study analyzed to address year and area differences (total Greek region compared to specific area of Patras). Graphs were generated to report the outcome in relation to the various levels of exposures assessed in total and by sub-study.\u003c/p\u003e\u003cp\u003eThe probability of children with overweight and obesity were estimated following multinomial logistic regression by total recreational areas available and by type (presence of parks and sports centers). All statistical analyses were performed using STATA 18.0 (Texas Ltd.).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 626 children were included in this study (SD 1.9; HNNHS: 331; 51.2%, and Health4EUkids: 316; 48.8%). The mean age differed by half year approximately being 10.3 in HNNHS and 9.8 years in Health4EUkids (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but no differences were found in mean BMI, weight status categorization and biological sex (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A total of 25.2% of children were categorized with overweight and 15.3% with obesity. Significant differences were found between studies in the number of available recreational areas (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Specifically, in HNNHS, a greater variation, including children with no available areas (9.4%) and some with as many as 6 areas (9.7%) was found, whereas in Health4EUkids study all children had at least 2 available recreational areas; highest proportions in 2 (44.9%), 3 (27.2%), and 4 (27.8%) areas.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive Characteristics of the Study Population (HNNHS and Health4EUkids)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHNNHS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHealth4EUkids\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTest\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e316 (51.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e316 (48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e647 (100.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge in completed years (exact)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.3 (2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.8 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.0 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18.9 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.5 (4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.7 (3.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.244\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMales\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e185 (55.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e165 (52.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e350 (54.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.371\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemales\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e146 (44.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e150 (47.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e296 (45.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e188 (60.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e184 (58.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e372 (59.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.257\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ewith overweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e84 (26.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74 (23.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e158 (25.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWith Obes status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41 (13.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55 (17.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e96 (15.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Available Recreational Areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31 (9.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31 (4.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36 (10.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48 (14.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e142 (44.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e190 (29.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61 (18.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e86 (27.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e147 (22.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e71 (21.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88 (27.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e159 (24.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50 (15.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50 (7.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32 (9.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32 (5.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eBMI: Body Mass Index; Weight Status as per WHO definition\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure 1 presents the total number of recreational areas categorized by type as per the study\u0026rsquo;s aim, parks and sports centers, and the proportion of children with overweight or obesity, pulling information from the total study population, the national HNNHS study, and the regional Health4EUkids study. Across the total population and in both sub-studies, over 2 recreational areas in the neighborhood corresponded to a lower proportion of children classified with overweight or obesity. This trend was observed in the total sample and the Health4EUkids sub-study, although in the HNNHS, over 2 available areas did not seem to modify the effect on children\u0026rsquo;s weight status.\u003c/p\u003e\u003cp\u003eOverall, there was a parallel increase in number of parks with the increasing number of available recreational areas, but this was not consistent for sport-center availability (Fig.\u0026nbsp;1). In the national HNNHS sample, sports-centers were largely present only in neighborhoods with at least 3 recreational areas, whereas in the Health4EUkids study, both parks and sports-centers were present even when there were just two recreational areas per neighborhood. Also, the pattern differed between the national and the regional study with the availability of sports-centers being proportionally higher than parks in the national sample for neighborhoods with three recreational areas. Also in the regional study (Health4EUkids) at least 2 areas were available in each neighborhood examined, reinforcing the unique distribution of recreational infrastructure in that setting. In Fig.\u0026nbsp;1a, a decreasing trend of overweight and obesity rates are also seen as the number of recreational areas increase from 56.5% in neighborhoods with 0\u0026ndash;1 areas compared to 38.3% for \u0026ge;\u0026thinsp;3 recreational areas. Although the trend was observed in both studies, the total rates differed. In the HNNHS study (Fig.\u0026nbsp;1b), the proportion of overweight/obesity was higher with 0\u0026ndash;1 areas (56.5%) and significantly dropped when 2 areas were available (28.9%), but this slightly rose again with \u0026ge;\u0026thinsp;3 areas to 37.4%. In the Health4EUKids study, the overweight/obesity rates decreased less pronounced, from 43.6% in areas with 2 recreational sites to 39.3% in areas with \u0026ge;\u0026thinsp;3.\u003c/p\u003e\u003cp\u003eThe presence of two recreational areas was associated with a 14.6 percentage point decrease in the probability of a child being overweight (p\u0026thinsp;=\u0026thinsp;0.030), but this did not remain statistically significant as the number increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The absence of adequate available recreational areas was also associated with childhood overweight and obesity, increasing the probability by 16%.\u003c/p\u003e\u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, results following an adjusted logistic regression are shown, with the probability for overweight or obesity decreasing by 7% with the presence of sports-centers. No effect was found with park presence.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to examine the association between the availability of recreational areas in the neighborhood (type and number) and childhood obesity prevalence, comparing national and region-specific data, in order to provide insights for tailoring interventions that address community-based needs more effectively. The main findings highlight that greater overall access to recreational areas was associated with lower rates of childhood overweight and obesity with a more pronounced effect being seen with the presence of sports-centers and no effect with park availability. However, the pattern of availability differed by study and by type of recreational facility, with sports-centers being less uniformly distributed compared to parks, especially on the national level and sports-centers being of particular importance in the regional study. This may be explained due to type and number of area availability, but it also may be due to the motivational factor and/or specific activities associated with sports centers that emphasize on specific trainings and not overall play. The above may be important for the specific age group that this study examined, including school-aged children 7 to 13 years of age.\u003c/p\u003e\u003cp\u003eIn the HNNHS, children\u0026rsquo;s access to recreational areas was highly variable, whereas in Health4EUkids, there was universal access to at least two areas per child. This marked difference in recreational area availability between the national (HNNHS) and regional (Health4EUkids) samples may have implications for analyses related to environment and health outcomes, as well as public health measures that need to be taken. In accordance to these results, Potwarka and colleagues found that proximity to park space was associated with higher likelihood of being normal weight (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), although another study, on a national level, found that children without parks were 25% and 32% more likely to be with overweight or obesity, respectively (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The potential preventive effect of available recreational areas was confirmed during the pandemic where children living in greener neighborhoods were found to experience smaller increases in obesity during this time compared to children in less green neighborhoods (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Results, however, differed by urbanicity, suggesting that compiling data at regional level is important. The importance of green spaces, parks and recreational resources have been reported by longitudinal studies as well, where children with better access to park and recreational resources were less likely to experience significant increases in attained BMI (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) and green space availability was inversely associated with BMI with increasing age (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In both cases a greater effect was reported in boys. Of great interest is a study that reported that the percentage of adolescents with overweight and obesity significantly increased with higher green area density, in the participants' surroundings. The authors speculated whether the results were due to the level of accessibility and attractiveness, since some children and adolescents might need more facilitated green areas for sport and physical activity (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), such as sports centers, and not overall green area presence. This confirms this study\u0026rsquo;s results where children of school aged years with higher availability to sports centers were less likely to be with overweight or obesity, with the hypothesis being that these children had higher physical activity level.\u003c/p\u003e\u003cp\u003eThe exposure to green spaces has been correlated with a lower incidence of obesity (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and the built environment has been found to be a nonspecific predictor of treatment outcome and can influence behavioral interventions. School-based environments and interventions, play a particularly important role in communities with fewer neighborhood facilities, although demographic disparities, which is a characteristic regional factor, were found to be an important moderator in physical activity attainment in schools (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). This can help understand the variability of results reported between various community settings between weight status and availability of recreational areas. Therefore, although neighbourhood-built environment features (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) as well as park density following behavioural weight management intervention (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), could potentially help children attain lower weight status, results remain controversial, as shown by .the null results that were derived in an Australian randomised control trial (RCT), in students 8\u0026ndash;13years old. In this RCT, physical activity environment including walkability, greenspace and recreational facilities, surrounding regional primary schools, was not associated with weight status or meeting physical activity recommendations in adjusted models (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), confirming results found in our study.\u003c/p\u003e\u003cp\u003eThese findings could be used to point out areas at higher need of interventions to reduce obesity burden (Carlson et el 2021).\u003c/p\u003e\u003cp\u003eAnother factor that could influence the effect of the number of recreation opportunities on children\u0026rsquo;s weight status is the concentration of fast-food outlets also within the vicinity or on the way to and from (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Although this was not addressed in the specific study, these can be further cartographied and addressed when evaluating the Grunau Moves intervention program at the end of the study. The World Health Organization\u0026rsquo;s Health Promoting Schools (HPS) framework found that this approach improved students\u0026rsquo; physical activity and fitness, and increased fruit and vegetable intake. However, there was considerable heterogeneity in reported impacts with process evaluations must move beyond simple measures of acceptability/fidelity to include detailed contextual information to illuminate exactly what works, for whom, in what contexts and why (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurther work is required in order to understand the role these various neighborhood elements play, and how they may interact, in influencing the children\u0026rsquo;s weight status.\u003c/p\u003e\u003cp\u003eLimitations of the study included the lack of statistical power to assess specific differences within the national (HNNHS) study when data are stratified by region. Also, the concentrations of fast-food restaurants and other obesogenic elements in the neighborhood were not accounted for, which may have affected the observed prevalence distribution and measure of effect. Other limitations include that weight and height data were self-reported when these were not recently documented in the children\u0026rsquo;s medical records, and the methods used to obtain information of total available recreational areas in HNNHS study were also self-reported. The questionnaire used specifically included all potential areas for probing to minimize reporting bias.\u003c/p\u003e\u003cp\u003eThis study takes an exploratory role in generating hypotheses for further investigation. The obesity prevention benefits should not be limited to formal recreation and physical activity programs but should enable age-appropriate activities found within the neighborhood. Total recreational areas may not be sufficient to reduce childhood obesity if these are not age specific while targeting facility type, accessibility, and quality is important. For school aged children sports centers showed a greater effect on weight status. This suggests that community and school-based interventions should prioritize both the presence and use of such venues, by creating awareness of their presence through maps for children and families that are unaware. Addressing local disparities in access and the specific needs and preferences of children is also important. Future research with larger, regionally representative samples would be needed to robustly examine more spatial differences.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eThe following abbreviations are used in this manuscript:\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eADM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAdministrative region\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBody Mass Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEARPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEnvironmental Assessment of Public Recreation Spaces\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHNNHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHellenic National Nutrition and Health Survey\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOSF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOpen Science Framework\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePhysical Activity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRandom Clinical Trial(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWHO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWorld Health Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEM was responsible for conceptualization\u0026nbsp;of study; EP and AZ were responsible for data collection and acquisition; EM and EP for data curation and management; EM for formal analysis and statistical interpretation; and EM, EP, NM, AA for writing of original draft preparation; AP was responsible for reviewing and editing the project; AP, AZ and GK for project administration and coordination and funding acquisition.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003cstrong\u003eunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by European Union, EU4Health program. Ethical approval was obtained from Bioethics Committee of University of Patras (Grant Number\u0026nbsp;101082462)\u0026nbsp;and the Regional Directorate of Primary and Secondary Education of Western Greece (number of approval: 304; date: 26/10/2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting this study’s findings are available upon reasonable request from the corresponding author. Additionally, the data will be made publicly accessible on the Open Science Framework (OSF) after a provisional period of one year.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all health care professionals that selected and documented the information required. Special thanks to the whole HNNHS collaborators and the 6\u003csup\u003eth\u003c/sup\u003e Heath ADM team.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGuthold R, Stevens GA, Riley LM, Bull FC. Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1\u0026middot;6 million participants. The Lancet Child \u0026amp; Adolescent Health. 2020;4(1):23\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlliott O, Ryan M, Fairbrother H, Van Sluijs E. Do adolescents' experiences of the barriers to and facilitators of physical activity differ by socioeconomic position? A systematic review of qualitative evidence. Obesity Reviews. 2022;23(3).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWolch J, Jerrett M, Reynolds K, McConnell R, Chang R, Dahmann N, et al. Childhood obesity and proximity to urban parks and recreational resources: A longitudinal cohort study. Health \u0026amp; Place. 2011;17(1):207\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePotwarka LR, Kaczynski AT, Flack AL. Places to Play: Association of Park Space and Facilities with Healthy Weight Status among Children. Journal of Community Health. 2008;33(5):344\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReuben A, Rutherford GW, James J, Razani N. Association of neighborhood parks with child health in the United States. Preventive Medicine. 2020;141:106265.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJia P, Cao X, Yang H, Dai S, He P, Huang G, et al. Green space access in the neighbourhood and childhood obesity. Obesity Reviews. 2021;22(S1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMorgan Hughey S, Kaczynski AT, Child S, Moore JB, Porter D, Hibbert J. Green and lean: Is neighborhood park and playground availability associated with youth obesity? Variations by gender, socioeconomic status, and race/ethnicity. Preventive Medicine. 2017;95:S101-S8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilhelm Stanis SA, Oftedal A, Schneider I. Association of outdoor recreation availability with physical activity and weight status in Minnesota youth. Prev Med. 2014;60:124\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee KH, Heo J, Jayaraman R, Dawson S. Proximity to parks and natural areas as an environmental determinant to spatial disparities in obesity prevalence. Applied Geography. 2019;112:102074.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGallotta MC, Zimatore G, Falcioni L, Migliaccio S, Lanza M, Schena F, et al. Influence of Geographical Area and Living Setting on Children's Weight Status, Motor Coordination, and Physical Activity. Frontiers in Pediatrics. 2022;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBenjamin-Neelon SE, Platt A, Bacardi-Gascon M, Armstrong S, Neelon B, Jimenez-Cruz A. Greenspace, physical activity, and BMI in children from two cities in northern Mexico. Prev Med Rep. 2019;14:100870.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMonnat SM, Lounsbery MAF, McKenzie TL, Chandler RF. Associations between demographic characteristics and physical activity practices in Nevada schools. Preventive Medicine. 2017;95:S4-S9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorsley S, McMahon EL, Samuels LR, White MJ, Heerman WJ. The Associations between Neighborhood Characteristics and Childhood Overweight and Obesity in a National Dataset. Academic Pediatrics. 2024;24(8):1266\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMolina-Garc\u0026iacute;a J, Menescardi C, Estevan I, Queralt A. Associations between Park and Playground Availability and Proximity and Children\u0026rsquo;s Physical Activity and Body Mass Index: The BEACH Study. International Journal of Environmental Research and Public Health. 2021;19(1):250.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMagriplis E, Dimakopoulos I, Karageorgou D, Mitsopoulou A-V, Bakogianni I, Micha R, et al. Aims, design and preliminary findings of the Hellenic National Nutrition and Health Survey (HNNHS). BMC Medical Research Methodology. 2019;19(1):37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003egel U GR, L\u0026uuml;ck M, Molis D, Lipek T, Schubert K, Kiess W, et al. Community-based health promotion for prevention of childhood obesity: Study design of a project in Leipzig-Gr\u0026uuml;nau.. Ernahrungs Umschau international. 2016;63:8\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNordic Healthcare Group 2024 [cited 2025 Aug 20]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nordichealthcaregroup.com/articles/nhg-supported-the-finnish-heart-association-in-improving-the-implementation-of-their-smart-family-method-in-europe/\u003c/span\u003e\u003cspan address=\"https://nordichealthcaregroup.com/articles/nhg-supported-the-finnish-heart-association-in-improving-the-implementation-of-their-smart-family-method-in-europe/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85(9):660\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSaelens BE, Frank LD, Auffrey C, Whitaker RC, Burdette HL, Colabianchi N. Measuring Physical Environments of Parks and Playgrounds: EAPRS Instrument Development and Inter-Rater Reliability. J Phys Act Health. 2006;3(s1):S190-s207.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeremia CM, Cain KL, Conway TL, Sallis JF, Saelens BE. Validating and Shortening the Environmental Assessment of Public Recreation Spaces Observational Measure. J Phys Act Health. 2018:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMayne SL, Kelleher S, Hannan C, Kelly MK, Powell M, Dalembert G, et al. Neighborhood Greenspace and Changes in Pediatric Obesity During COVID-19. American Journal of Preventive Medicine. 2023;64(1):33\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSanders T, Feng X, Fahey PP, Lonsdale C, Astell-Burt T. Greener neighbourhoods, slimmer children? Evidence from 4423 participants aged 6 to 13 years in the Longitudinal Study of Australian children. International Journal of Obesity. 2015;39(8):1224\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilhelmsen CK, Skalleberg K, Raanaas RK, Tveite H, Aamodt G. Associations between green area in school neighbourhoods and overweight and obesity among Norwegian adolescents. Preventive Medicine Reports. 2017;7:99\u0026ndash;105.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLu M, Murphy M, Kim A, Lingwall M, Barr EA. The relationship between natural environments and obesity: a systematic review. International Journal of Environmental Health Research. 2025;35(7):1772\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHowell NA, Booth GL. The Weight of Place: Built Environment Correlates of Obesity and Diabetes. Endocrine Reviews. 2022;43(6):966\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArmstrong B, Lim CS, Janicke DM. Park Density Impacts Weight Change in a Behavioral Intervention for Overweight Rural Youth. Behavioral Medicine. 2015;41(3):123\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJacobs J, Crooks N, Allender S, Strugnell C, Backholer K, Nichols M. Is the physical activity environment surrounding primary schools associated with students' weight status, physical activity or active transport, in regional areas of Victoria, Australia? A cross-sectional study. BMJ Open. 2021;11(7):e045785.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGilliland JA, Rangel CY, Healy MA, Tucker P, Loebach JE, Hess PM, et al. Linking Childhood Obesity to the Built Environment: A Multi-level Analysis of Home and School Neighbourhood Factors Associated With Body Mass Index. Canadian Journal of Public Health. 2012;103(S3):S15-S21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangford R, Bonell C, Jones H, Campbell R. Obesity prevention and the Health promoting Schools framework: essential components and barriers to success. International Journal of Behavioral Nutrition and Physical Activity. 2015;12(1):15.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"environment, recreational areas, physical activity, childhood obesity, regional disparities","lastPublishedDoi":"10.21203/rs.3.rs-7502433/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7502433/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground/Objectives\u003c/h2\u003e\u003cp\u003eNatural and built environment is an important factor of children\u0026rsquo;s physical activity and weight status. This study investigated the relationship between the availability and type of recreational areas and school children\u0026rsquo;s weight status, using national and regional levels, to inform community-tailored interventions.\u003c/p\u003e\u003ch2\u003eSubjects/Methods\u003c/h2\u003e\u003cp\u003eA cross-sectional analysis using harmonized data (N\u0026thinsp;=\u0026thinsp;626) from the Hellenic National Nutrition and Health Survey (HNNHS) and Health4EUkids studies of children aged 7\u0026ndash;13 years old. Recreational area availability was tabulated in national and regional areas. The probability of overweight and obesity was estimated following multinomial logistic regression analysis to investigate the likelihood of children with overweight or obesity by total recreational areas available and by type. All statistical analyses were performed using STATA 18.0 (Texas Ltd.).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOverweight and obesity prevalence was 25.2% and 15.3% in total, with obesity rates being slightly higher in the regional sample compared to the national (17.6% and 13.1%, respectively). Patterns of area type and distribution differed between national and regional areas. Total recreational area access (\u0026ge;\u0026thinsp;2 areas) was associated with lower overweight/obesity prevalence (38.3% vs. 56.5% for 0\u0026ndash;1 areas, p\u0026thinsp;=\u0026thinsp;0.030), with sports-center availability linked to a 7% reduction in obesity probability. No significant effect was found with park presence alone.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIncreased neighborhood recreational area availability, particularly sports centers, was associated with lower obesity risk among Greek children, with notable regional differences, highlighting the need for localized infrastructure distribution. Further studies should address obesogenic elements such as food outlet proximity and utilize larger regionally stratified samples for robust spatial analysis.\u003c/p\u003e","manuscriptTitle":"Comparing Childhood Obesity Prevalence in Relation to Neighborhood Recreational Area Availability Using Harmonized National and Regional Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 07:13:15","doi":"10.21203/rs.3.rs-7502433/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"08df58ea-a3ea-4790-b64c-0522dd7706ed","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":54919346,"name":"Health sciences/Risk factors"},{"id":54919347,"name":"Health sciences/Health care/Public health/Epidemiology"}],"tags":[],"updatedAt":"2025-10-29T16:44:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 07:13:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7502433","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7502433","identity":"rs-7502433","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}