Does participation in a one-year family-centered lifestyle intervention affect school absence in children with obesity – 9 years follow-up

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While lifestyle interventions have some effects in reducing BMI in children with obesity, little is known about potential effects on school absence after lifestyle interventions. Methods : This observational cohort study examined changes in school absence among 836 children aged 5–10 years living with obesity, comparing those enrolled in a one-year family-centered lifestyle intervention (n = 293) with those not invited (n = 543). Data collected from 2010 to 2020 were analyzed using linear regression models to investigate total school absence, illness-related absence and illegal absence for each year following inclusion. Results : No significant differences in school absence were found between groups in the adjusted model in any of the years following the intervention. In both groups, total school absence peaked in year seven (6.6% (CI: 4.90–8.30) vs 5.1% (CI: 3.81–6.32), respectively). Illness-related absence accounted for the largest proportion of total absence. Conclusion : This study did not identify differences in school absence for children with obesity participating in a lifestyle intervention as compared to children not invited to participate. Future research should examine the effects of longer interventions and interventions more targeted towards school absenteeism. Obesity Children School Absence Absenteeism Lifestyle Intervention Figures Figure 1 Figure 2 Figure 3 “What is Known - What is New” What is Known: Children with obesity are more likely to be absent from school than their peers Frequent school absence is associated with social and academic disadvantages Lifestyle interventions have shown some effect in reducing BMI in children with obesity What is New: No difference in school absence was found between children living with obesity participating in a one-year family-centered lifestyle intervention, compared to children with obesity not invited to participate in the intervention Danish children with obesity experience higher rates of school absence than their peers Introduction Childhood obesity is a growing public health issue[ 1 ] and continuous obesity in adulthood is associated with several adverse long-term health outcomes including cardiovascular disease[ 2 – 5 ], and type 2 diabetes[ 6 ]. Furthermore, children living with obesity experience psychosocial challenges such as reduced quality of life[ 7 – 9 ], lower self-esteem[ 9 ], increased risk of depression[ 10 ], and a higher likelihood of being victims of bullying[ 11 – 13 ]. These combined physical and psychosocial challenges may influence children’s daily functioning, including their ability to attend to and engage in school activities. Emerging evidence suggests that children with overweight and obesity are more likely to be absent from school than their peers[ 14 – 19 ]. Frequent school absenteeism among children has been linked to both social and academic disadvantages, including lower social well-being[ 20 ], increased risk of experiencing mental health disorders[ 21 , 22 ], and lower academic performance[ 23 ]. Absenteeism may result from reduced motivation for school participation, potentially manifesting as truancy or school refusal, why the obesity-related increase in absenteeism highlights the importance of recognizing children with obesity as a priority group for targeted intervention. Lifestyle interventions focusing on physical activity and eating habits reduce body mass index (BMI) in children living with obesity[ 24 – 26 ] and are considered a cornerstone in the treatment of childhood obesity[ 27 ]. However, only limited knowledge exists on the association between lifestyle interventions offered children living with obesity and the potential effects on school absence. This study aims to investigate potential changes in school absence in children with obesity participating in a one-year family-centered lifestyle intervention as compared to children with obesity not invited into the intervention. We hypothesize that participation in the intervention will reduce school absence in children with obesity. Methods Study design This observational cohort study included children with obesity aged 5–10 years living in Aarhus Municipality, Denmark, who either participated in a family-centered lifestyle intervention (intervention group) or were not invited to participate (non-intervention group). Data on the children’s height and weight were collected during mandatory health examinations conducted by school nurses between January 1, 2010, and June 30, 2020. Data on the children’s school absence between August 1st, 2010, and June 30th, 2020, was obtained from the Danish Agency for IT and Learning (STIL), The Ministry of Education. Furthermore, characteristics of the children and their families were obtained from the Danish National Registers at Statistics Denmark (DST). Study participants In this study, we included children aged 5–10 years with obesity as defined by the International Obesity Task Force (IOTF) guidelines (iso-BMI \(\:\ge\:\) 30 kg/m2 for age and sex)[ 28 ]. The time of inclusion was defined as the month of enrollment into the intervention for the intervention group, and the month at which obesity was first identified for the non-intervention group. Exclusion criteria were children not categorized with obesity at time of inclusion as defined by the IOTF guidelines[ 28 ]. Furthermore, children with no data on school absence three months prior to inclusion were excluded from the study (Fig. 1 ). The family-centered lifestyle intervention enrolled children aged 5–8 years with obesity and has previously been described in detail[ 24 ]. The children were identified at a mandatory health examination at school performed by the school nurse. Both the children and their families were invited to participate in the intervention managed by specialized community health nurses. The intervention focused on healthy eating habits, mental health, screen time, daily physical activity, and sleep duration. Furthermore, the child was offered free participation in weekly supervised physical activity. The intended duration of the intervention was one year and normally included 3–4 consultations in the child’s home or at a local clinic. The non-intervention group consisted of children living in Aarhus Municipality who were classified as having obesity but were not invited to participate in the intervention for unknown reasons[ 24 ]. These children were identified using the IOTF obesity cutoff for all children living in Aarhus Municipality during the inclusion period. Data sources and study variables Children in both the intervention and non-intervention group were identified using data from TM-Sund, an electronic record system used by community health nurses. From this database, data on height and weight recorded during the mandatory health examinations were retrieved as well as information on participation in the intervention. Data on school absence was obtained from the absence register, STIL, and linked to the cohort by using the Centrale Personal Registration (CPR) number. The CPR-number is a unique personal identification number assigned to all residents in Denmark, enabling accurate linkage of data across national registers. In Denmark, school absence is recorded daily by the teacher[ 29 ]. For children in the lower and middle grades (approximately 5–6 to 12–13 years), school absence is recorded at the beginning of each school day, and such absence is counted as a full day. In the upper grades (approximately 13–16 years), attendance is registered both at the beginning and at the end of the school day. Students who are present at the morning registration but absent at the end-of-day registration are recorded as having a half-day absence. School absence is categorized by the teachers into three categories[ 29 ]: 1) Absence due to illness, disability, or similar reasons 2) Legal absence approved by the school management (e.g., extraordinary leave) 3) Illegal absence without permission or notice from the parents to the teachers This study focused on school absence due to illness and illegal absence. Days with legal absence were excluded from the analysis as they are not considered as problematic school absence. School absence was calculated as the percentage of school days absent out of the total number of school days in a year (200 days), starting from the month of inclusion. To estimate school absence at the time of inclusion, the percentage of days absent out of the total number of school days during the three months prior to inclusion (50 days) was used, with the month of the inclusion visit included in year 1. Data was available throughout the entire study period. Information on covariates was obtained from the national Danish registries at DST and linked to the children’s parents by using a unique family ID. Family type was identified using the Danish Population Register, distinguishing between children living with two adults and those who did not[ 30 ]. Highest completed household education was used as a proxy for socioeconomic status and was recoded into duration of education in years using the Danish Education Register and stratified into groups of primary education ( 15 years) for the parent with the longest education[ 31 ]. The Immigration Register was used for each child to stratify immigration status into first-generation immigrant, second-generation immigrant, or Danish origin[ 32 ]. The Danish National Patient Register was used for data regarding disposition for mental illness and psychiatric diagnosis for the child[ 33 – 35 ]. The child was categorized as having a mental disorder if any prior psychiatric diagnosis had been recorded, while disposition for mental illness was classified if at least one parent had a documented psychiatric diagnosis recorded at the time of inclusion. Statistics For the descriptive analyses at time of inclusion, normally distributed continuous variables were analyzed using a t-test, while non-normally distributed continuous variables were analyzed using a Wilcoxon rank-sum test. Categorical variables were analyzed using a Fisher’s exact test. A linear regression model was used to investigate mean school absence for each year following inclusion. From the models, mean annual school absence with 95% confidence intervals (CI) was estimated for both the intervention and non-intervention groups. Group differences were evaluated by comparing the estimated means and the corresponding p-values from the regression analyses. The analyses were performed in several steps. First, we used an unadjusted model, then we used a model adjusted for potential confounders as described above. As a secondary analysis, following the same approach as above, we performed stratified analyses of school absence by illegal absence or illness. To address missing data, a sensitivity analysis was conducted using complete-case analyses, as well as worst- and best-case scenarios. These approaches showed consistent results, suggesting that the handling of missing data did not substantially influence the findings. Consequently, the main analysis was conducted as a complete case analysis. Statistical significance was defined at the 5% level. All analyses were performed using Stata 18 College Station, TX: StataCorp LLC[ 36 ]. An analysis plan was formulated prior to conducting the analyses. Results Characteristics at time of inclusion As outlined in Fig. 1 , a total of 836 children were included in the study with 293 children in the intervention group and 543 children in the non-intervention group. Children in the intervention group were significantly younger than children in the non-intervention group with a median age of 6.9 years (interquartile range (IQR): 6.5–7.4) and 7.5 years (IQR: 6.7–8.2), respectively (p < 0.001). In addition, children in the intervention group had a significantly higher median BMI z-score at inclusion (p = 0.03), although the median difference of 0.1 suggests limited clinical relevance. No other differences were observed between groups at time of inclusion (Table 1 ). Table 1 General characteristics at time of inclusion of the 836 children with obesity aged 5–10 years, either enrolled in the one-year family-centered lifestyle intervention (intervention group) or not invited to participate (non-intervention group) N Intervention group Non-intervention group 293 543 Sex, n (%) Boys 132 (45.1) 267 (49.2) Girls 161 (54.9) 276 (50.8) Age, median (IQR) a 6.9 (6.5; 7.4) 7.5 (6.7; 8.2) BMI z-score, median (IQR) a 3.0 (2.6; 3.4) 2.9 (2.6; 3.2) Immigration status, n (%) Danish origin 154 (55.6) 282 (57.2) First generation immigrants 10 (3.6) 25 (5.1) Second generation immigrants 113 (40.8) 186 (37.7) Family type, n (%) Not two-adults family 100 (36.1) 173 (35.1) Two-adults family 177 (63.9) 320 (64.9) Highest completed household education, n (%) 15 years 30 (10.2) 62 (11.6) Psychiatric diagnosis, child, n (%) Yes 19 (6.5) 29 (5.3) No 274 (93.5) 514 (94.7) Parental mental illness, n (%) No 196 (66.9) 362 (66.7) Yes 97 (33.1) 181 (33.3) a Variables have been pseudo-anonymized and represent averages based on five individuals. School absence at time of inclusion At time of inclusion, no significant differences were observed in school absence (total school absence, illegal absence, or absence due to illness) when comparing the intervention and non-intervention group. Nonetheless, across all three measures of absence, both crude and adjusted models indicated a trend toward lower absence in the intervention group (Fig. 2 + 3). At time of inclusion, an average total school absence of 4.8% (CI: 4.01–5.56) was found for the intervention group compared to 5.4% (CI: 4.78–5.94) for the non-intervention group in the adjusted model (p = 0.25). When analyzed by types of absence, the averages of illegal absence at time of inclusion were 0.9% (CI: 0.46–1.27) in the intervention group and 1.3% (CI: 1.03–1.63) in the non-intervention group (p = 0.08), while absence due to illness were 3.9% (CI: 3.25–4.59) and 4.0% (CI: 3.53–4.53) (p = 0.79), respectively. Change in school absence between groups In the analysis of total school absence not adjusted for confounders, a difference was observed in year three, with the non-intervention group demonstrating a higher average total absence (4.2%, CI: 3.77–4.69) compared to the intervention group (3.4%, CI: 2.77–3.96) (p = 0.02). However, in the analysis adjusted for potential confounders, no significant differences in total school absence were observed between the groups in any of the years of follow-up. When stratifying the analyses into illegal absence and absence due to illness, the same tendency was observed. For absence due to illness, the crude analysis showed a significant difference between groups in year three with absence rates of 2.5% (CI: 2.07–2.97) in the intervention group and 3.1% (CI: 2.79–3.48) in the non-intervention group (p = 0.03). For illegal absence, the crude analysis showed a significant difference between groups in year nine with 1.7% (CI: 1.08–2.26) in the intervention group and 0.9% (CI: 0.47–1.37) in the non-intervention group (p = 0.046). Again, no statistically significant differences were observed in the adjusted models for either illegal absence or absence due to illness between groups at any time during follow-up. School absence over time For the total school absence, both groups showed a tendency towards higher absence at time of inclusion followed by a decline until year three and thereafter an increase in absence until year seven (Fig. 3 A). In year nine, pronounced reductions in both rates of total absence, absence due to illness and illegal absence in both groups compared to previous years were observed (Fig. 3 A-C). Except for year seven in the intervention group, absence due to illness accounted for the largest proportion of total absence compared to illegal absence in both groups. Rates of absence due to illness showed a tendency of higher absence at inclusion followed by a decline until year three and a subsequent stabilization of absence rates through year eight (Fig. 3 B). Rates of illegal absence remained relatively stable during the first three years post-inclusion, followed by a gradual rise peaking in year seven and a subsequent decline through year nine (Fig. 3 C). Discussion This study investigated the long-term impact of a one-year family-centered lifestyle intervention on school absence in children with obesity by comparing children participating in the intervention with children not invited to participate. In the models not adjusted for confounders, statistically significant group differences were found in a few of the years of follow-up, however, these differences were eliminated in the adjusted model. Across all adjusted models, no significant differences in school absence were found between groups at any year of follow-up, indicating that the lifestyle intervention did not affect school absence in children with obesity. Previous research has shown that children participating in the lifestyle intervention had a comparable reduction in BMI z-scores during the first six months of follow-up, with no sustained effects observed thereafter[ 24 ]. In this context, the present findings are consistent with prior evidence suggesting that the impact of such interventions may be transient and insufficient to affect longer-term outcomes such as school absence. The lifestyle intervention had a relatively short duration, and previous research indicates that longer interventions with more clinical consultations result in more pronounced effects on the children’s BMI[ 24 , 37 , 38 ]. It is therefore likely that longer interventions could have an alternating effect on school absence. Also to consider is the content of the lifestyle intervention, which was aimed at reducing BMI rather than school absence. Previous studies have demonstrated that in cases where children experience school refusal or other school attendance problems, cognitive behavioral therapy can be effective in reducing absenteeism[ 39 – 41 ]. Integrating such approaches into future lifestyle interventions could enhance their impact on school absenteeism. Both groups exhibited a similar pattern of total school absence and since the adjusted analyses showed no differences between groups, the similar trend may suggest a general pattern of total school absence, such as e.g. an age-related variation, rather than effects of the intervention. Absence due to illness accounted for the largest proportion of total absence, suggesting that illness and disabilities remain the predominant drivers of school absence across age groups. The increase in illegal absence observed in the later years of follow-up suggests an age-dependent trend, with higher rates among older students. This may be linked to developmental changes, increased autonomy or other contextual factors[ 42 ] representing a potential area for future research. Rates of school absence at inclusion in this study exceeded those reported for all children of the same age in Aarhus Municipality during the corresponding period (STIL data[ 43 ]). Specifically, the total absence rates were 4.8% (CI: 4.01–5.56) in the intervention group and 5.4% (CI: 4.78–5.94) in the non-intervention group (p = 0.25) (adjusted estimates), compared to an average of 3.1% among 5–10-year-olds in Aarhus Municipality between 2014 and 2020[ 43 ]. This suggests that children with obesity experience higher levels of school absenteeism than their peers, aligning with existing literature[ 14 – 19 , 23 ]. A meta-analysis found 27% and 54% higher odds of absenteeism among children with overweight and obesity, respectively, compared to their classmates[ 14 ]. Moreover, the elevated school absence at time of inclusion comprised both illegal and illness-related absence, suggesting that higher absence among children with obesity may stem from a greater illness burden[ 44 ], and an increased risk of truancy or school refusal, potentially linked to bullying or weight-related stigma[ 11 – 13 , 45 ]. The study is strengthened by the inclusion of both an intervention and a non-intervention group with comparable characteristics at time of inclusion, and with children in both groups living in Aarhus Municipality. This comparability reduces potential confounding and enhances the internal validity of the study, allowing for a more robust comparison. Furthermore, the use of comprehensive data on school absence enabled by the mandatory registration of absence in the Danish public school system[ 46 ] strengthens the reliability and external validity of the findings. Nevertheless, to our knowledge, no study has yet examined the validity of school absence registration in Denmark. That said, certain limitations of the study must be acknowledged. Firstly, we were not able to adjust the analyses for potential weight changes over time. If weight change was associated with both the intervention effects and the level of school absence (as we may expect), this could have introduced bias and altered the interpretations of the results. Next, some children may have received other treatments during follow-up periods, which could have obscured any association. In addition, absence rates were calculated based on a standardized assumption of 200 school days per year. However, in Denmark, it is up to schools and municipalities to decide how teaching is organized, including the number and length of school days[ 47 ]. This may have introduced inconsistencies in absence rates and thereby influenced the study results - most likely introducing bias towards no association and potentially obscuring a true relationship. However, this was addressed by restricting the population to the same municipality and age group. Furthermore, the rate of school absence at time of inclusion was calculated as the percentage of school days absent out of the total number of school days in the three months prior to inclusion, which was set to 50 days based on the standard of 200 school days in a year. However, the calculations do not account for differing numbers of school days across months (e.g., due to holidays), which affects the validity of the school absence rate at inclusion. Finally, registration practices during the spring of 2020 may have been affected by the COVID-19 pandemic, which prompted a nationwide lockdown in Denmark from March 2020, including the closure of all schools. This may have influenced the reported rates of school absence, particularly in year nine of follow-up. In addition, reduced sample sizes in the later years of follow-up may have increased uncertainty in the estimates. Conclusion In conclusion, this study did not identify any differences in school absence between children living with obesity participating in a one-year family-centered lifestyle intervention, compared to children with obesity not invited to participate. However, the findings indicated that Danish children with obesity experience higher rates of school absence than their peers, aligning with existing literature. The findings of this study underline the complexity of addressing school absence among children with obesity and suggest that lifestyle interventions of short duration focusing on diet and physical activity may have limited impact on absence rates. Abbreviations BMI, Body mass index; STIL, Danish Agency for IT and Learning; DST, Statistics Denmark; IOTF, International Obesity Task Force; CI, Confidence interval; IQR, Interquartile range Declarations Competing Interests R.M.J. and J.M.B. are employed at Steno Diabetes Center Aarhus, Aarhus University Hospital, a public hospital and research institution in the Central Denmark Region, partly funded by an unrestricted grant from Novo Nordisk Foundation. L.B.N. and C.R.B. has no conflicts of interest to disclose. The Novo Nordisk Foundation had no role in the study’s design and conduct. Conflicts of Interest Statement RMJ and JMB are employed at Steno Diabetes Center Aarhus, Aarhus University Hospital, a public hospital and research institution in the Central Denmark Region, partly funded by an unrestricted grant from Novo Nordisk Foundation. LBN and CRB has no conflicts of interest to disclose. The Novo Nordisk Foundation had no role in the study’s design and conduct. Statement of Ethics This study was conducted in accordance with the principles of the Declaration of Helsinki[ 48 ] and approved by the Central Jutland Regional Committee on Health Research Ethics (record No. 1-45-70-27-20). The Danish Data Protection Agency approved use of registers from Statistics Denmark. Consent to participate The Central Jutland Regional Committee on Health Research Ethics waived the requirement for collecting written or verbal consent. The study relied solely on pseudo-anonymized registry data and involved no contact with the participating children or families. Additionally, no information was reported on an individual level. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contribution L.B.N., R.M.J., C.R.B. and J.M.B. jointly developed the analysis plan. R.M.J. was responsible for data collection and obtaining the relevant permits for the project. Data processing and statistical analyses were conducted by L.B.N. in collaboration with R.M.J. and C.R.B. L.B.N. drafted the manuscript and prepared figures. R.M.J., C.R.B. and J.M.B. contributed with guidance and critical review of the manuscript. All authors approved the final version of the manuscript and agree to be accountable for all aspects of the work. Acknowledgement We would like to thank Professor Henrik Støvring for valuable input on the statistical analysis. 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J Adolesc Health 52(1):64–69 Pont SJ et al (2017) Stigma Experienced by Children and Adolescents With Obesity. Pediatrics, 140(6) Børne- og Undervisningsministeriet. Vejledning til bekendtgørelse om elevers fravær fra undervisningen i folkeskolen (2023) January 11, 2023 November 2, 2025]; Available from: https://www.retsinformation.dk/eli/retsinfo/2023/9008 Børne- og Undervisningsministeriet. Undervisningstidens samlede længde i folkeskolen (2025) October 23, 2025 November 4, 2025]; Available from: https://www.uvm.dk/folkeskolen/fag-og-indhold/timetal-og-skoledagens-laengde/undervisningens-samlede-laengde World Medical Association (2013) Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310(20):2191–2194 Additional Declarations Competing interest reported. R.M.J. and J.M.B. are employed at Steno Diabetes Center Aarhus, Aarhus University Hospital, a public hospital and research institution in the Central Denmark Region, partly funded by an unrestricted grant from Novo Nordisk Foundation. L.B.N. and C.R.B. has no conflicts of interest to disclose. The Novo Nordisk Foundation had no role in the study’s design and conduct. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 15 May, 2026 Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviews received at journal 17 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers invited by journal 16 Apr, 2026 Editor assigned by journal 15 Apr, 2026 Submission checks completed at journal 15 Apr, 2026 First submitted to journal 13 Apr, 2026 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. 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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-9407469","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626856807,"identity":"5a9bdd37-2c2b-4b8b-bc60-9909f6e06a50","order_by":0,"name":"Lærke Bjertrup Nielsen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYBACfmbG9h8JPDb1bewNcEFjvFok25sbJD7IpDH28RwAchOI0GJw5niD5Aybw4zzJBKI1MJwI7HBmCfnMDOb5NuDD3/+YJA3OMC82QCfDsYZiQ3JPGfS2dik85KNeRIYDDccYCtOwKeFWSKx4TBvjzUPm3SOmTTQYYwbDvAYH8CnhU0isbGZ9x+zBJvkGTPJHwkM9gS18PAcbGacweNswCbBYyYBdFgiSAteh0mwN7YxfOBJS2DjAfklTSJ55mG2Yrzetz/M/owBGJUJ8u1nDz78YWNj23e8ebMEPi3IbgTbCgwRItXDtIyCUTAKRsEowAQAb/ZFGt40YRMAAAAASUVORK5CYII=","orcid":"","institution":"Steno Diabetes Center","correspondingAuthor":true,"prefix":"","firstName":"Lærke","middleName":"Bjertrup","lastName":"Nielsen","suffix":""},{"id":626856808,"identity":"090360fe-554c-4344-8e87-46fafe5b9cdd","order_by":1,"name":"Rasmus Møller Jørgensen","email":"","orcid":"","institution":"Steno Diabetes Center","correspondingAuthor":false,"prefix":"","firstName":"Rasmus","middleName":"Møller","lastName":"Jørgensen","suffix":""},{"id":626856811,"identity":"dbc3280b-989e-4251-9544-30c551945906","order_by":2,"name":"Camilla Raaby Benjaminsen","email":"","orcid":"","institution":"Steno Diabetes Center","correspondingAuthor":false,"prefix":"","firstName":"Camilla","middleName":"Raaby","lastName":"Benjaminsen","suffix":""},{"id":626856813,"identity":"921220a8-0f5c-4372-91c6-e64830e8e44b","order_by":3,"name":"Jens Meldgaard Bruun","email":"","orcid":"","institution":"Steno Diabetes Center","correspondingAuthor":false,"prefix":"","firstName":"Jens","middleName":"Meldgaard","lastName":"Bruun","suffix":""}],"badges":[],"createdAt":"2026-04-13 18:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9407469/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9407469/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107834270,"identity":"5b2ac267-53a4-48cf-865a-a65d0ec029ce","added_by":"auto","created_at":"2026-04-26 15:43:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":358016,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for inclusion and exclusion of children with obesity aged 5-10 years from Aarhus Municipality, Denmark, either enrolled in the one-year family-centered lifestyle intervention (intervention group) or not invited to participate (non-intervention group).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9407469/v1/f46008f011a858c71f7853d1.png"},{"id":107869975,"identity":"928df1b3-0c1f-48e3-a06f-3534e19b6b1d","added_by":"auto","created_at":"2026-04-27 07:38:34","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":112336,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal school absence (%) (A), absence due to illness (%) (B) and illegal absence (%) (C) during nine years of follow-up in children with obesity, crude models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlue circles represent the intervention group (children participating in the one-year family-centered lifestyle intervention), and orange triangles represent the non-intervention group (children not invited to participate). Below the x-axis, unadjusted mean rates of school absence (%) with 95% confidence intervals (CI) and sample sizes (n) for each group and year are displayed. Unadjusted model estimates: no covariates were included in the analysis.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9407469/v1/0f3fbc7065b03a7ef3713b30.jpg"},{"id":107834272,"identity":"96a3b1f9-b66c-4495-a577-6fc519fa6c52","added_by":"auto","created_at":"2026-04-26 15:43:53","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":117178,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal school absence (%) (A), absence due to illness (%) (B) and illegal absence (%) (C) during nine years of follow-up in children with obesity, adjusted for covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlue circles represent the intervention group (children participating in the one-year family-centered lifestyle intervention), and orange triangles represent the non-intervention group (children not invited to participate). Below the x-axis, adjusted mean rates of school absence (%) with 95% confidence intervals (CI) and sample sizes (n) for each group and year are displayed. All estimates are adjusted for the covariates specified in the “Methods” section.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9407469/v1/ba761c9c08439eddac3b5c0e.jpg"},{"id":107872074,"identity":"4b519cfe-b62b-4416-8a03-bd09ceb3f87c","added_by":"auto","created_at":"2026-04-27 07:55:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":813735,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9407469/v1/44e65219-21f7-49d1-bf68-265d8f0d1280.pdf"}],"financialInterests":"Competing interest reported. R.M.J. and J.M.B. are employed at Steno Diabetes Center Aarhus, Aarhus University Hospital, a public hospital and research institution in the Central Denmark Region, partly funded by an unrestricted grant from Novo Nordisk Foundation. L.B.N. and C.R.B. has no conflicts of interest to disclose. The Novo Nordisk Foundation had no role in the study’s design and conduct.","formattedTitle":"Does participation in a one-year family-centered lifestyle intervention affect school absence in children with obesity – 9 years follow-up","fulltext":[{"header":"“What is Known - What is New”","content":"\u003ch2\u003e\u003cstrong\u003e\u003cem\u003eWhat is Known:\u003c/em\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cul\u003e\n \u003cli\u003eChildren with obesity are more likely to be absent from school than their peers\u003c/li\u003e\n \u003cli\u003eFrequent school absence is associated with social and academic disadvantages\u003c/li\u003e\n \u003cli\u003eLifestyle interventions have shown some effect in reducing BMI in children with obesity\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWhat is New:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eNo difference in school absence was found between children living with obesity participating in a one-year family-centered lifestyle intervention, compared to children with obesity not invited to participate in the intervention\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDanish children with obesity experience higher rates of school absence than their peers\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eChildhood obesity is a growing public health issue[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e] and continuous obesity in adulthood is associated with several adverse long-term health outcomes including cardiovascular disease[\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e], and type 2 diabetes[\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]. Furthermore, children living with obesity experience psychosocial challenges such as reduced quality of life[\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e], lower self-esteem[\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e], increased risk of depression[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e], and a higher likelihood of being victims of bullying[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]. These combined physical and psychosocial challenges may influence children’s daily functioning, including their ability to attend to and engage in school activities. Emerging evidence suggests that children with overweight and obesity are more likely to be absent from school than their peers[\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. Frequent school absenteeism among children has been linked to both social and academic disadvantages, including lower social well-being[\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e], increased risk of experiencing mental health disorders[\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e], and lower academic performance[\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. Absenteeism may result from reduced motivation for school participation, potentially manifesting as truancy or school refusal, why the obesity-related increase in absenteeism highlights the importance of recognizing children with obesity as a priority group for targeted intervention.\u003c/p\u003e \u003cp\u003eLifestyle interventions focusing on physical activity and eating habits reduce body mass index (BMI) in children living with obesity[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e] and are considered a cornerstone in the treatment of childhood obesity[\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, only limited knowledge exists on the association between lifestyle interventions offered children living with obesity and the potential effects on school absence.\u003c/p\u003e \u003cp\u003eThis study aims to investigate potential changes in school absence in children with obesity participating in a one-year family-centered lifestyle intervention as compared to children with obesity not invited into the intervention. We hypothesize that participation in the intervention will reduce school absence in children with obesity.\u003c/p\u003e "},{"header":"Methods","content":"\u003ch3\u003eStudy design\u003c/h3\u003e\u003cp\u003eThis observational cohort study included children with obesity aged 5–10 years living in Aarhus Municipality, Denmark, who either participated in a family-centered lifestyle intervention (intervention group) or were not invited to participate (non-intervention group). Data on the children’s height and weight were collected during mandatory health examinations conducted by school nurses between January 1, 2010, and June 30, 2020. Data on the children’s school absence between August 1st, 2010, and June 30th, 2020, was obtained from the Danish Agency for IT and Learning (STIL), The Ministry of Education. Furthermore, characteristics of the children and their families were obtained from the Danish National Registers at Statistics Denmark (DST).\u003c/p\u003e\u003ch2\u003eStudy participants\u003c/h2\u003e\u003cp\u003eIn this study, we included children aged 5–10 years with obesity as defined by the International Obesity Task Force (IOTF) guidelines (iso-BMI \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\ge\\:\\)\u003c/span\u003e\u003c/span\u003e30 kg/m2 for age and sex)[\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. The time of inclusion was defined as the month of enrollment into the intervention for the intervention group, and the month at which obesity was first identified for the non-intervention group.\u003c/p\u003e\u003cp\u003eExclusion criteria were children not categorized with obesity at time of inclusion as defined by the IOTF guidelines[\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. Furthermore, children with no data on school absence three months prior to inclusion were excluded from the study (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe family-centered lifestyle intervention enrolled children aged 5–8 years with obesity and has previously been described in detail[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. The children were identified at a mandatory health examination at school performed by the school nurse. Both the children and their families were invited to participate in the intervention managed by specialized community health nurses. The intervention focused on healthy eating habits, mental health, screen time, daily physical activity, and sleep duration. Furthermore, the child was offered free participation in weekly supervised physical activity. The intended duration of the intervention was one year and normally included 3–4 consultations in the child’s home or at a local clinic.\u003c/p\u003e\u003cp\u003eThe non-intervention group consisted of children living in Aarhus Municipality who were classified as having obesity but were not invited to participate in the intervention for unknown reasons[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. These children were identified using the IOTF obesity cutoff for all children living in Aarhus Municipality during the inclusion period.\u003c/p\u003e\u003ch3\u003eData sources and study variables\u003c/h3\u003e\u003cp\u003eChildren in both the intervention and non-intervention group were identified using data from TM-Sund, an electronic record system used by community health nurses. From this database, data on height and weight recorded during the mandatory health examinations were retrieved as well as information on participation in the intervention. Data on school absence was obtained from the absence register, STIL, and linked to the cohort by using the Centrale Personal Registration (CPR) number. The CPR-number is a unique personal identification number assigned to all residents in Denmark, enabling accurate linkage of data across national registers.\u003c/p\u003e\u003cp\u003eIn Denmark, school absence is recorded daily by the teacher[\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]. For children in the lower and middle grades (approximately 5–6 to 12–13 years), school absence is recorded at the beginning of each school day, and such absence is counted as a full day. In the upper grades (approximately 13–16 years), attendance is registered both at the beginning and at the end of the school day. Students who are present at the morning registration but absent at the end-of-day registration are recorded as having a half-day absence.\u003c/p\u003e\u003cp\u003eSchool absence is categorized by the teachers into three categories[\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]:\u003c/p\u003e\u003cp\u003e1) Absence due to illness, disability, or similar reasons\u003c/p\u003e\u003cp\u003e2) Legal absence approved by the school management (e.g., extraordinary leave)\u003c/p\u003e\u003cp\u003e3) Illegal absence without permission or notice from the parents to the teachers\u003c/p\u003e\u003cp\u003eThis study focused on school absence due to illness and illegal absence. Days with legal absence were excluded from the analysis as they are not considered as problematic school absence.\u003c/p\u003e\u003cp\u003eSchool absence was calculated as the percentage of school days absent out of the total number of school days in a year (200 days), starting from the month of inclusion. To estimate school absence at the time of inclusion, the percentage of days absent out of the total number of school days during the three months prior to inclusion (50 days) was used, with the month of the inclusion visit included in year 1. Data was available throughout the entire study period.\u003c/p\u003e\u003cp\u003e Information on covariates was obtained from the national Danish registries at DST and linked to the children’s parents by using a unique family ID. Family type was identified using the Danish Population Register, distinguishing between children living with two adults and those who did not[\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Highest completed household education was used as a proxy for socioeconomic status and was recoded into duration of education in years using the Danish Education Register and stratified into groups of primary education (\u0026lt; 10 years), high school or vocational education (10–12 years), short- and medium-cycle higher education (12–15 years) and university degree or equivalent (\u0026gt; 15 years) for the parent with the longest education[\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. The Immigration Register was used for each child to stratify immigration status into first-generation immigrant, second-generation immigrant, or Danish origin[\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. The Danish National Patient Register was used for data regarding disposition for mental illness and psychiatric diagnosis for the child[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. The child was categorized as having a mental disorder if any prior psychiatric diagnosis had been recorded, while disposition for mental illness was classified if at least one parent had a documented psychiatric diagnosis recorded at the time of inclusion.\u003c/p\u003e\u003ch3\u003eStatistics\u003c/h3\u003e\u003cp\u003eFor the descriptive analyses at time of inclusion, normally distributed continuous variables were analyzed using a t-test, while non-normally distributed continuous variables were analyzed using a Wilcoxon rank-sum test. Categorical variables were analyzed using a Fisher’s exact test.\u003c/p\u003e\u003cp\u003eA linear regression model was used to investigate mean school absence for each year following inclusion. From the models, mean annual school absence with 95% confidence intervals (CI) was estimated for both the intervention and non-intervention groups. Group differences were evaluated by comparing the estimated means and the corresponding p-values from the regression analyses. The analyses were performed in several steps. First, we used an unadjusted model, then we used a model adjusted for potential confounders as described above.\u003c/p\u003e\u003cp\u003eAs a secondary analysis, following the same approach as above, we performed stratified analyses of school absence by illegal absence or illness.\u003c/p\u003e\u003cp\u003eTo address missing data, a sensitivity analysis was conducted using complete-case analyses, as well as worst- and best-case scenarios. These approaches showed consistent results, suggesting that the handling of missing data did not substantially influence the findings. Consequently, the main analysis was conducted as a complete case analysis.\u003c/p\u003e\u003cp\u003eStatistical significance was defined at the 5% level. All analyses were performed using Stata 18 College Station, TX: StataCorp LLC[\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. An analysis plan was formulated prior to conducting the analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics at time of inclusion\u003c/h2\u003e \u003cp\u003eAs outlined in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, a total of 836 children were included in the study with 293 children in the intervention group and 543 children in the non-intervention group. Children in the intervention group were significantly younger than children in the non-intervention group with a median age of 6.9 years (interquartile range (IQR): 6.5\u0026ndash;7.4) and 7.5 years (IQR: 6.7\u0026ndash;8.2), respectively (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In addition, children in the intervention group had a significantly higher median BMI z-score at inclusion (p\u0026thinsp;=\u0026thinsp;0.03), although the median difference of 0.1 suggests limited clinical relevance. No other differences were observed between groups at time of inclusion (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eGeneral characteristics at time of inclusion of the 836 children with obesity aged 5\u0026ndash;10 years, either enrolled in the one-year family-centered lifestyle intervention (intervention group) or not invited to participate (non-intervention group)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntervention group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-intervention group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e293\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e132 (45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e267 (49.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e276 (50.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (IQR)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.9 (6.5; 7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.5 (6.7; 8.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI z-score, median (IQR)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0 (2.6; 3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.9 (2.6; 3.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmigration status, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDanish origin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e282 (57.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst generation immigrants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond generation immigrants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e113 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e186 (37.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily type, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot two-adults family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e173 (35.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo-adults family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e177 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e320 (64.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest completed household education, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (7.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;12 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143 (26.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u0026ndash;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e289 (53.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (11.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric diagnosis, child, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29 (5.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e274 (93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e514 (94.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParental mental illness, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e196 (66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e362 (66.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181 (33.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003ea\u003c/sup\u003eVariables have been pseudo-anonymized and represent averages based on five individuals.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSchool absence at time of inclusion\u003c/h2\u003e \u003cp\u003eAt time of inclusion, no significant differences were observed in school absence (total school absence, illegal absence, or absence due to illness) when comparing the intervention and non-intervention group. Nonetheless, across all three measures of absence, both crude and adjusted models indicated a trend toward lower absence in the intervention group (Fig.\u0026nbsp;2\u0026thinsp;+\u0026thinsp;3). At time of inclusion, an average total school absence of 4.8% (CI: 4.01\u0026ndash;5.56) was found for the intervention group compared to 5.4% (CI: 4.78\u0026ndash;5.94) for the non-intervention group in the adjusted model (p\u0026thinsp;=\u0026thinsp;0.25). When analyzed by types of absence, the averages of illegal absence at time of inclusion were 0.9% (CI: 0.46\u0026ndash;1.27) in the intervention group and 1.3% (CI: 1.03\u0026ndash;1.63) in the non-intervention group (p\u0026thinsp;=\u0026thinsp;0.08), while absence due to illness were 3.9% (CI: 3.25\u0026ndash;4.59) and 4.0% (CI: 3.53\u0026ndash;4.53) (p\u0026thinsp;=\u0026thinsp;0.79), respectively.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChange in school absence between groups\u003c/h3\u003e\n\u003cp\u003eIn the analysis of total school absence not adjusted for confounders, a difference was observed in year three, with the non-intervention group demonstrating a higher average total absence (4.2%, CI: 3.77\u0026ndash;4.69) compared to the intervention group (3.4%, CI: 2.77\u0026ndash;3.96) (p\u0026thinsp;=\u0026thinsp;0.02). However, in the analysis adjusted for potential confounders, no significant differences in total school absence were observed between the groups in any of the years of follow-up.\u003c/p\u003e \u003cp\u003eWhen stratifying the analyses into illegal absence and absence due to illness, the same tendency was observed. For absence due to illness, the crude analysis showed a significant difference between groups in year three with absence rates of 2.5% (CI: 2.07\u0026ndash;2.97) in the intervention group and 3.1% (CI: 2.79\u0026ndash;3.48) in the non-intervention group (p\u0026thinsp;=\u0026thinsp;0.03). For illegal absence, the crude analysis showed a significant difference between groups in year nine with 1.7% (CI: 1.08\u0026ndash;2.26) in the intervention group and 0.9% (CI: 0.47\u0026ndash;1.37) in the non-intervention group (p\u0026thinsp;=\u0026thinsp;0.046). Again, no statistically significant differences were observed in the adjusted models for either illegal absence or absence due to illness between groups at any time during follow-up.\u003c/p\u003e\n\u003ch3\u003eSchool absence over time\u003c/h3\u003e\n\u003cp\u003eFor the total school absence, both groups showed a tendency towards higher absence at time of inclusion followed by a decline until year three and thereafter an increase in absence until year seven (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In year nine, pronounced reductions in both rates of total absence, absence due to illness and illegal absence in both groups compared to previous years were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-C).\u003c/p\u003e \u003cp\u003eExcept for year seven in the intervention group, absence due to illness accounted for the largest proportion of total absence compared to illegal absence in both groups. Rates of absence due to illness showed a tendency of higher absence at inclusion followed by a decline until year three and a subsequent stabilization of absence rates through year eight (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eRates of illegal absence remained relatively stable during the first three years post-inclusion, followed by a gradual rise peaking in year seven and a subsequent decline through year nine (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the long-term impact of a one-year family-centered lifestyle intervention on school absence in children with obesity by comparing children participating in the intervention with children not invited to participate. In the models not adjusted for confounders, statistically significant group differences were found in a few of the years of follow-up, however, these differences were eliminated in the adjusted model. Across all adjusted models, no significant differences in school absence were found between groups at any year of follow-up, indicating that the lifestyle intervention did not affect school absence in children with obesity. Previous research has shown that children participating in the lifestyle intervention had a comparable reduction in BMI z-scores during the first six months of follow-up, with no sustained effects observed thereafter[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this context, the present findings are consistent with prior evidence suggesting that the impact of such interventions may be transient and insufficient to affect longer-term outcomes such as school absence.\u003c/p\u003e \u003cp\u003eThe lifestyle intervention had a relatively short duration, and previous research indicates that longer interventions with more clinical consultations result in more pronounced effects on the children\u0026rsquo;s BMI[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. It is therefore likely that longer interventions could have an alternating effect on school absence. Also to consider is the content of the lifestyle intervention, which was aimed at reducing BMI rather than school absence. Previous studies have demonstrated that in cases where children experience school refusal or other school attendance problems, cognitive behavioral therapy can be effective in reducing absenteeism[\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Integrating such approaches into future lifestyle interventions could enhance their impact on school absenteeism.\u003c/p\u003e \u003cp\u003eBoth groups exhibited a similar pattern of total school absence and since the adjusted analyses showed no differences between groups, the similar trend may suggest a general pattern of total school absence, such as e.g. an age-related variation, rather than effects of the intervention. Absence due to illness accounted for the largest proportion of total absence, suggesting that illness and disabilities remain the predominant drivers of school absence across age groups. The increase in illegal absence observed in the later years of follow-up suggests an age-dependent trend, with higher rates among older students. This may be linked to developmental changes, increased autonomy or other contextual factors[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] representing a potential area for future research.\u003c/p\u003e \u003cp\u003eRates of school absence at inclusion in this study exceeded those reported for all children of the same age in Aarhus Municipality during the corresponding period (STIL data[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]). Specifically, the total absence rates were 4.8% (CI: 4.01\u0026ndash;5.56) in the intervention group and 5.4% (CI: 4.78\u0026ndash;5.94) in the non-intervention group (p\u0026thinsp;=\u0026thinsp;0.25) (adjusted estimates), compared to an average of 3.1% among 5\u0026ndash;10-year-olds in Aarhus Municipality between 2014 and 2020[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. This suggests that children with obesity experience higher levels of school absenteeism than their peers, aligning with existing literature[\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A meta-analysis found 27% and 54% higher odds of absenteeism among children with overweight and obesity, respectively, compared to their classmates[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, the elevated school absence at time of inclusion comprised both illegal and illness-related absence, suggesting that higher absence among children with obesity may stem from a greater illness burden[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and an increased risk of truancy or school refusal, potentially linked to bullying or weight-related stigma[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study is strengthened by the inclusion of both an intervention and a non-intervention group with comparable characteristics at time of inclusion, and with children in both groups living in Aarhus Municipality. This comparability reduces potential confounding and enhances the internal validity of the study, allowing for a more robust comparison. Furthermore, the use of comprehensive data on school absence enabled by the mandatory registration of absence in the Danish public school system[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] strengthens the reliability and external validity of the findings. Nevertheless, to our knowledge, no study has yet examined the validity of school absence registration in Denmark.\u003c/p\u003e \u003cp\u003eThat said, certain limitations of the study must be acknowledged. Firstly, we were not able to adjust the analyses for potential weight changes over time. If weight change was associated with both the intervention effects and the level of school absence (as we may expect), this could have introduced bias and altered the interpretations of the results. Next, some children may have received other treatments during follow-up periods, which could have obscured any association. In addition, absence rates were calculated based on a standardized assumption of 200 school days per year. However, in Denmark, it is up to schools and municipalities to decide how teaching is organized, including the number and length of school days[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This may have introduced inconsistencies in absence rates and thereby influenced the study results - most likely introducing bias towards no association and potentially obscuring a true relationship. However, this was addressed by restricting the population to the same municipality and age group. Furthermore, the rate of school absence at time of inclusion was calculated as the percentage of school days absent out of the total number of school days in the three months prior to inclusion, which was set to 50 days based on the standard of 200 school days in a year. However, the calculations do not account for differing numbers of school days across months (e.g., due to holidays), which affects the validity of the school absence rate at inclusion. Finally, registration practices during the spring of 2020 may have been affected by the COVID-19 pandemic, which prompted a nationwide lockdown in Denmark from March 2020, including the closure of all schools. This may have influenced the reported rates of school absence, particularly in year nine of follow-up. In addition, reduced sample sizes in the later years of follow-up may have increased uncertainty in the estimates.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study did not identify any differences in school absence between children living with obesity participating in a one-year family-centered lifestyle intervention, compared to children with obesity not invited to participate. However, the findings indicated that Danish children with obesity experience higher rates of school absence than their peers, aligning with existing literature. The findings of this study underline the complexity of addressing school absence among children with obesity and suggest that lifestyle interventions of short duration focusing on diet and physical activity may have limited impact on absence rates.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI, Body mass index; STIL, Danish Agency for IT and Learning; DST, Statistics Denmark; IOTF, International Obesity Task Force; CI, Confidence interval; IQR, Interquartile range\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eR.M.J. and J.M.B. are employed at Steno Diabetes Center Aarhus, Aarhus University Hospital, a public hospital and research institution in the Central Denmark Region, partly funded by an unrestricted grant from Novo Nordisk Foundation. L.B.N. and C.R.B. has no conflicts of interest to disclose. The Novo Nordisk Foundation had no role in the study\u0026rsquo;s design and conduct.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflicts of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRMJ and JMB are employed at Steno Diabetes Center Aarhus, Aarhus University Hospital, a public hospital and research institution in the Central Denmark Region, partly funded by an unrestricted grant from Novo Nordisk Foundation. LBN and CRB has no conflicts of interest to disclose. The Novo Nordisk Foundation had no role in the study\u0026rsquo;s design and conduct.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eStatement of Ethics\u003c/h2\u003e \u003cp\u003eThis study was conducted in accordance with the principles of the Declaration of Helsinki[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] and approved by the Central Jutland Regional Committee on Health Research Ethics (record No. 1-45-70-27-20). The Danish Data Protection Agency approved use of registers from Statistics Denmark.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent to participate\u003c/h2\u003e \u003cp\u003eThe Central Jutland Regional Committee on Health Research Ethics waived the requirement for collecting written or verbal consent. The study relied solely on pseudo-anonymized registry data and involved no contact with the participating children or families. Additionally, no information was reported on an individual level.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eL.B.N., R.M.J., C.R.B. and J.M.B. jointly developed the analysis plan. R.M.J. was responsible for data collection and obtaining the relevant permits for the project. Data processing and statistical analyses were conducted by L.B.N. in collaboration with R.M.J. and C.R.B. L.B.N. drafted the manuscript and prepared figures. R.M.J., C.R.B. and J.M.B. contributed with guidance and critical review of the manuscript. All authors approved the final version of the manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank Professor Henrik St\u0026oslash;vring for valuable input on the statistical analysis. Also, we would like to thank the school health nurses at Aarhus Municipality for measuring and recording the height and weight of the children included in this study and the Department of Child and Youth, Aarhus Municipality, for providing access to their database.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAnonymized study data will be available to researchers upon reasonable request following publication. Data originating from national registries and STIL cannot be shared due to restrictions under the Danish General Data Protection Regulation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. Obesity and overweight (2025) May 7, 2025 September 8, 2025]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBjerregaard LG, Adelborg K, Baker JL (2020) Change in body mass index from childhood onwards and risk of adult cardiovascular disease(). 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J Anxiety Disord 25(7):870\u0026ndash;878\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnsen DB et al (2024) The Effectiveness of Modular Transdiagnostic Cognitive Behavioral Therapy Versus Treatment as Usual for Youths Displaying School Attendance Problems: A Randomized Controlled Trial. Res Child Adolesc Psychopathol 52(9):1397\u0026ndash;1412\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKing NJ et al (1998) Cognitive-behavioral treatment of school-refusing children: a controlled evaluation. J Am Acad Child Adolesc Psychiatry 37(4):395\u0026ndash;403\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKearney CA (2008) School absenteeism and school refusal behavior in youth: a contemporary review. Clin Psychol Rev 28(3):451\u0026ndash;471\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB\u0026oslash;rne- og Undervisningsministeriet \u003cem\u003eStatistik om elevfrav\u0026aelig;r\u003c/em\u003e. Uddannelsesstatistik n.d. September 4, 2025]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://uddannelsesstatistik.dk/Pages/Topics/15.aspx\u003c/span\u003e\u003cspan address=\"https://uddannelsesstatistik.dk/Pages/Topics/15.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan L et al (2013) The association of obesity and school absenteeism attributed to illness or injury among adolescents in the United States, 2009. J Adolesc Health 52(1):64\u0026ndash;69\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePont SJ et al (2017) Stigma Experienced by Children and Adolescents With Obesity. Pediatrics, 140(6)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB\u0026oslash;rne- og Undervisningsministeriet. 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Undervisningstidens samlede l\u0026aelig;ngde i folkeskolen (2025) October 23, 2025 November 4, 2025]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uvm.dk/folkeskolen/fag-og-indhold/timetal-og-skoledagens-laengde/undervisningens-samlede-laengde\u003c/span\u003e\u003cspan address=\"https://www.uvm.dk/folkeskolen/fag-og-indhold/timetal-og-skoledagens-laengde/undervisningens-samlede-laengde\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Medical Association (2013) Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310(20):2191\u0026ndash;2194\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Obesity, Children, School Absence, Absenteeism, Lifestyle Intervention","lastPublishedDoi":"10.21203/rs.3.rs-9407469/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9407469/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eIntroduction\u003c/em\u003e: Childhood obesity is associated with adverse health consequences and psychosocial outcomes including increased school absence. While lifestyle interventions have some effects in reducing BMI in children with obesity, little is known about potential effects on school absence after lifestyle interventions.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMethods\u003c/em\u003e: This observational cohort study examined changes in school absence among 836 children aged 5\u0026ndash;10 years living with obesity, comparing those enrolled in a one-year family-centered lifestyle intervention (n\u0026thinsp;=\u0026thinsp;293) with those not invited (n\u0026thinsp;=\u0026thinsp;543). Data collected from 2010 to 2020 were analyzed using linear regression models to investigate total school absence, illness-related absence and illegal absence for each year following inclusion.\u003c/p\u003e \u003cp\u003e \u003cem\u003eResults\u003c/em\u003e: No significant differences in school absence were found between groups in the adjusted model in any of the years following the intervention. In both groups, total school absence peaked in year seven (6.6% (CI: 4.90\u0026ndash;8.30) vs 5.1% (CI: 3.81\u0026ndash;6.32), respectively). Illness-related absence accounted for the largest proportion of total absence.\u003c/p\u003e \u003cp\u003e \u003cem\u003eConclusion\u003c/em\u003e: This study did not identify differences in school absence for children with obesity participating in a lifestyle intervention as compared to children not invited to participate. Future research should examine the effects of longer interventions and interventions more targeted towards school absenteeism.\u003c/p\u003e","manuscriptTitle":"Does participation in a one-year family-centered lifestyle intervention affect school absence in children with obesity – 9 years follow-up","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-26 15:43:49","doi":"10.21203/rs.3.rs-9407469/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-15T19:51:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T16:33:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251041161185312435359503300166654442846","date":"2026-04-19T12:35:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-17T15:27:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133372186745998952046519696705892339808","date":"2026-04-17T13:43:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251156765810605559582928094332980537513","date":"2026-04-17T13:02:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-16T19:18:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-15T11:57:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-15T11:56:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Pediatrics","date":"2026-04-13T18:18:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9db93d33-aabf-4b99-8386-e6b48ce852f7","owner":[],"postedDate":"April 26th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-15T19:51:52+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T19:53:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-26 15:43:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9407469","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9407469","identity":"rs-9407469","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}