Does Deciding Not to Participate in a Lifestyle Intervention Affect the Long-term Change in Psychosocial Well-being for Children With Obesity?
Conditions: Pediatric Obesity, Psychosocial Well-being
Sponsor: University of Aarhus

28-10-2024 
 
1 
 
Statistical analysis plan 
Title: 
Does deciding not to participate in a lifestyle intervention affect the long-term change in 
psychosocial well-being for children with obesity? 
Suggested authors: 
Camilla Raaby Benjaminsen  
Jens Meldgaard Bruun 
Malthe Jessen Pedersen 
Jane Nautrup Østergaard 
Loa Clausen 
Rasmus Møller Jørgensen 
Purpose: 
In this plan for statistical analysis, we provide an overview of the study’s context and objectives, as 
well as general aspects of data management and data analysis. The statistical analysis plan will be 
attached as a supplementary document upon submission. 
Introduction 
Childhood obesity is associated with an increased risk of developing non-communicable lifestyle 
diseases later in life(1-4), while reduced psychological well-being often occurs during childhood. 
Children living with obesity suffer from lower self-esteem, which have been associated with 
increased level of sadness and loneliness(5). They also experience higher degree of 
bullying/teasing(6, 7), have lower quality of life (8, 9) and increasing risk of depression (10) as 
compared to their peers living without obesity.  
Family-centered lifestyle interventions including a multifactorial approach are still considered the 
first line of treatment when handling childhood obesity(11, 12). The literature suggest that this type 
of intervention can stabilize or to some extent reduce weight when treating children with 
obesity(12-14). 
Previous studies have reported life stressors, societal norms of weight and body size, as well as 
earlier experiences with the health care system to be the primary determinants for caregivers not 
letting their children with obesity participate in lifestyle interventions(15-17). 

28-10-2024 
 
2 
 
However, no studies have been able to describe if deciding not to participate in a lifestyle 
intervention potentially affect the psychosocial well-being in children with obesity.  
 
Objective 
To investigate the impact in psychosocial well-being for children with obesity deciding not to 
participate in a family-centered lifestyle intervention (deciding not to participate group) compared 
to children who attended the intervention (intervention group), and to children never invited into the 
intervention (non-intervention group). As a secondary objective, we aim to investigate the effect 
that is not caused by the weight change by adjusting for this. 
 
Material and methods 
Design 
This is an observational cohort study investigating the impact in psychosocial well-being for 
children with obesity deciding not to participate in a lifestyle intervention. Data will be obtained 
from mandatory health check-ups at school, Danish national registries, and Danish National Well-
being Questionnaire (DNWQ). 
 
Participants 
Children were screened by a community health nurse during school time. If the child's BMI (age- 
and sex-adjusted) was above 30 kg/m2, the parents would be informed and invited to participate in 
the local lifestyle intervention. If the parents accepted, they would be referred to the intervention. 
The intervention had a maximum duration of one year and typical consisted of 3-4 consultations 
with a specialized community health care nurse. 
This study will include children with obesity with an inclusion visit between August 1st, 2014, and 
June 30th, 2020, from the city of Aarhus. February 1st, 2023, will be the last day of follow-up (figure 
1). The inclusion visit will be defined as the day of deciding not to participate in the intervention 
(decided not to participate group), the first day of attending the intervention (intervention group), or 
the first observation with obesity (non-intervention group).  
 

28-10-2024 
 
3 
 
The groups 
• Decided not to participate group: Children with obesity declining to participate in a lifestyle 
intervention. 
• Intervention group: Children with obesity who attended the lifestyle intervention.  
• Non-intervention group: Children with obesity never invited into the intervention. 
 
Inclusion criteria 
1. An inclusion visit between August 1st, 2014, and June 30th, 2020 (figure 1). 
2. Obesity at time of referral as defined by the International Obesity Task Force (IOTF) 
guideline(18). 
3. A measure of weight and height within 6 months before or after time of inclusion 
4. Age at inclusion between 5 to 10 years of age. 
5. A completed DNWQ at inclusion: 
- The deciding not to participate / non-intervention group - with a timeframe between 
6 months prior to and 6 months after inclusion. 
- The intervention group - with a timeframe between 10 months prior to and 2 months 
after inclusion. 
6. A completed DNWQ at follow-up (1 to 3 years after inclusion). 
 
Exclusion criteria 
1. Children first decided not to participate, but subsequently accepting the intervention. 
 
Outcome 
The outcome of this study will be the dichotomized responses at follow-up to specific items 
obtained from the DNWQ. The DNWQ is used to examine how primary school children perceive 
their psychosocial well-being and learning environment in school. The DNWQ has been a 
mandatory assignment for the public schools in Denmark and was introduced in 2015. DNWQ 
consist of 20 items for children in 0th to 3rd grade assessed using a three-point Likert scale ranging 
from 1 to 3. For children in 4th to 9th grade the DNWQ consist of 40 items assessed on a five-point 
Likert scale ranging from 1 to 5.  

28-10-2024 
 
4 
 
For this study we have selected 7 items to best describe the psychosocial well-being in our cohort. 
We will include completed questionnaires at time of inclusion and at follow-up. At follow-up, we 
will prioritize completed questionnaires closest to two years from time of inclusion visit. 
All answers will be dichotomized into: Good well-being / Poor well-being, depending on the item. 
Responses 1 and 2 for grades 0-3 and response 1-3 for grades 4-9 will be characterized as poor 
well-being.  
 
The psychosocial well-being items: 
 
Question 1: 
Are you happy with your school? (0th to 9th grade) 
 
Question 2: 
Do you feel lonely at school? (0th to 3rd grade)  
Do you feel lonely? (4th to 9th grade) 
 
Question 3: 
Is anyone teasing you so that you feel sad? (0th to 3rd grade) 
Have you been bullied this school year? (4th to 9th grade) 
 
Question 4: 
Does your stomach ache when you are at school? (0th to 3rd grade) 
How often does your stomach ache? (4th to 9th grade) 
 
Question 5: 
Are you good at solving your problems? (0th to 3rd grade) 
How often can you find a solution to problems, just by trying hard enough? (4th to 9th grade) 
 
Question 6: 
Can you concentrate during class? (0th to 9th grade) 
 
Question 7: 

28-10-2024 
 
5 
 
Are you good at helping each other in class? (0th to 3rd grade) 
Most students in my class are friendly and helpful. (4th to 9th grade) 
 
Data sources and study variables 
Data sources 
TM-Sund: TM-Sund is a data capturing tool used by community health nurses and has been used to 
record data on height and weight obtained from health check-ups at the school and data on children 
attending or deciding not to participate in the intervention.  
The National Registers at Statistic Denmark (DST): DST will be used to identify relevant co-
variables such as proxies for Socioeconomic status, immigration background, family structure and 
psychiatric diagnoses of the child or parents. 
The Department of IT and Learning (STIL): The DNWQ will be obtained from STIL, Ministry of 
Children and Youth. 
 
Study variables: 
 
We wish to include the following co-variates at inclusion: 
• BMI z-score (e.g. 3.0 SD) (19) 
• Sex (girl/boy)  
• Highest completed Household Education (HHE)  
o “Short”: Primary school (UNESCO’s International Standard Classification of 
Education (ISCED) level 1-2). 
o “Middle”: Highschool, vocational education, and similar shorter education (ISCED 
level 3-5). 
o “Long”: Tertiary education at bachelor level or higher (ISCED level 6-8)  
• Immigration status (Danish origin / immigrants 1. or 2. generation)  
• Disposition for mental illness (lifetime) (yes / no) 
• Mental illness, child (lifetime) (yes / no)  
• Family structure (two caretakers / not-two caretakers) 
 

28-10-2024 
 
6 
 
Statistical methods: 
All statistical analyses will be performed using Stata/SE 15 (StataCorp LP, College Station, Texas, 
USA). All statistical tests will be two-sided with a significance level at 0.05. 
 
For the characteristics at inclusion 
• 
Normally distributed data will be analyzed using a one-way ANOVA (several means) and a 
t-test (two means). 
• 
Non-normally distributed data will be analyzed using a Wilcoxon ranksum test (2 groups) 
and Kruskal-Wallis test (> 2 groups).  
• 
Categorical variables will be analyzed using a Fisher's exact test. 
 
For missing data (education, immigration status, and family-type), a multiple imputation (MI) with 
chained equations will be utilized to replace missing values with imputed values. Rubin’s rule will 
be applied to obtain overall estimates of 100 imputed datasets. 
 
We will perform the analyses in several steps: 
Firstly, the McNemar’s test will be used to investigate potential change in psychosocial well-being 
from time of inclusion to follow-up for each of the dichotomized items (Q1-Q7) in all three groups. 
All items will be dichotomized into: Good well-being/Poor well-being. 
 
Secondly, the impact in psychosocial well-being for children declining participation will be 
compared to the intervention group and to the non-intervention group by a logistic regression.  
The logistic regression analysis will be reported as both a crude (only including the outcome and the 
groups) and a multivariable model. The psychosocial well-being at inclusion will act as an 
explanatory variable in the models. 
The multivariable model will be adjusted for no more than 1 co-variate per 10 observations of the 
least common outcome. The co-variates are listed in prioritized order: 1) BMI z-score 2) sex, 3) 
highest completed household education, 4) immigration status, 5) disposition for mental illness, 6) 
mental illness and 7) family structure. 
 
As an explorative outcome, a logistic regression model adjusted for change in BMI z-score (from 
inclusion to follow-up) will be performed to remove the potential effect of weight change on the 

28-10-2024 
 
7 
 
association between exposure and psychosocial well-being. The BMI z-score observed closest to 
the included DNWQ at follow-up will be used.  
 
If possible, we wish to investigate the stratified effect of sex, BMI z-score at inclusion, parental 
level of education, immigration status, disposition for mental illness and change in BMI z score 
before we examine their potential for effect modification for the impact in psychosocial well-being 
for the items Q1-Q4 for the decided not to participate group compared to the non-intervention and 
intervention groups.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

28-10-2024 
 
8 
 
Results: 
 
Figure 1:  
Lexi diagram for time of inclusion (x-axis), inclusion age of the participants (y-axis), and time points for the 
DNWQ. 
 
 
 
 
 

28-10-2024 
 
9 
 
Table 1:  
Characteristics at inclusion, divided by groups. 
 
Decided not to 
participate group  
Intervention group  
Non-intervention group 
 
n 
 
n 
 
n 
 
Age at inclusion, median (IQR) 
 
 
 
 
 
 
Sex (% boys) 
 
 
 
 
 
 
BMI z-score at inclusion mean (SD) 
 
 
 
 
 
 
Highest completed household education, n (%)  
 
 
 
 
 
   Short 
 
 
 
 
 
 
   Medium 
 
 
 
 
 
 
   Long 
 
 
 
 
 
 
Family type, n (%) 
 
 
 
 
 
 
   Two caretakers 
 
 
 
 
 
 
   not-two caretakers 
 
 
 
 
 
 
Immigration status (%) 
 
 
 
 
 
 
   Danish 
 
 
 
 
 
 
   First or second generation immigrants 
 
 
 
 
 
 
Psychiatric diagnosis, child (% yes) 
 
 
 
 
 
 
Parental mental illness (% yes) 
 
 
 
 
 
 
 
 
 

28-10-2024 
 
10 
 
Table 2:  
Descriptive presentation of the distribution of answers to each of the items on psychosocial well-
being at inclusion and follow-up, divided by groups. 
n (%) 
Decided not to participate 
group 
 
Intervention group 
 
Non-intervention group 
 
 
Inclusion 
Follow-up 
Inclusion 
Follow-up 
Inclusion 
Follow-up 
Question 1:  
Are you happy with your school? 
Good well-being (yes) 
 
 
 
 
 
 
Poor well-being (no) 
 
 
 
 
 
 
Question 2: 
Do you feel lonely at school? (0-3 grade) 
Do you feel lonely? (4-9 grade) 
Good well-being (no) 
 
 
 
 
 
 
Poor well-being (yes) 
 
 
 
 
 
 
Question 3: 
Is anyone teasing you so that you feel sad? (0-3 grade) 
Have you been bullied this school year? ? (4-9 grade) 
Good well-being (no) 
 
 
 
 
 
 
Poor well-being (yes) 
 
 
 
 
 
 
Question 4:  
Does your stomach ache when you are at school? (0-3 grade) 
How often does your stomach ache? (4-9 grade) 
Good well-being (no/rarely) 
 
 
 
 
 
 
Poor well-being (yes/often) 
 
 
 
 
 
 
Question 5:  
Are you good at solving your problems? (0-3 grade) 
How often can you find a solution to problems,  
just by trying hard enough? (4-9 grade) 
Good well-being (yes/often) 
 
 
 
 
 
 
Poor well-being (no/rarely) 
 
 
 
 
 
 
Question 6:  
Can you concentrate during class? 
Good well-being (yes) 
 
 
 
 
 
 
Poor well-being (no) 
 
 
 
 
 
 
Question 7: 
Are you good at helping each other in class? (0-3 grade) 
Most students in my class are friendly and helpful? (4-9 grade) 
Good well-being (yes) 
 
 
 
 
 
 
Poor well-being (no) 
 
 
 
 
 
 
 
 
 

28-10-2024 
 
11 
 
Table 3:  
Logistic regression analyses comparing the decided not to participate group and the intervention 
group. 
The multivariable model will be adjusted for up to 1 co-variable per 10 observations. 
Decided not to participate group vs. intervention group 
 
OR (95% CI), p-value 
Q1 – Enjoyment at school 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q2 – Feelings of loneliness at school 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q3 –Experiences of bullying  
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q4 – Experiences of stomach aches  
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q5 – Problem-solving 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q6 – Concentration in the classroom 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q7 – Helpfulness in the classroom 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
 
 
 

28-10-2024 
 
12 
 
Table 4:  
Logistic regression analyses comparing the decided not to participate group and the non-
intervention group. 
The multivariable model will be adjusted for up to 1 co-variable per 10 observations. 
Decided not to participate group vs. non-intervention group 
 
OR (95% CI), p-value 
Q1 – Enjoyment at school 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q2 – Feelings of loneliness at school 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q3 –Experiences of bullying  
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q4 – Experiences of stomach aches  
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q5 – Problem-solving 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q6 – Concentration in the classroom 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
Q7 – Helpfulness in the classroom 
 
Univariable logistic regression 
 
Multivariable logistic regression 
 
 
 
 

28-10-2024 
 
13 
 
References: 
1. 
Bjerregaard LG, Adelborg K, Baker JL. Change in body mass index from 
childhood onwards and risk of adult cardiovascular disease. Trends in cardiovascular 
medicine. 2019. 
2. 
Bjerregaard LG, Jensen BW, Angquist L, Osler M, Sorensen TIA, Baker 
JL. Change in Overweight from Childhood to Early Adulthood and Risk of Type 2 
Diabetes. NEJM. 2018;378(14):1302-12. 
3. 
Adelborg K, Angquist L, Ording A, Gjaerde LK, Bjerregaard LG, 
Sorensen HT, et al. Levels of and Changes in Childhood Body Mass Index in 
Relation to Risk of Atrial Fibrillation and Atrial Flutter in Adulthood. Am J 
Epidemiol. 2019;188(4):684-93. 
4. 
Yuan Y, Chu C, Zheng WL, Ma Q, Hu JW, Wang Y, et al. Body Mass 
Index Trajectories in Early Life Is Predictive of Cardiometabolic Risk. J Pediatr. 
2020;219:31-7 e6. 
5. 
Strauss RS. Childhood obesity and self-esteem. Pediatrics. 
2000;105(1):e15. 
6. 
van Geel M, Vedder P, Tanilon J. Are overweight and obese youths more 
often bullied by their peers? A meta-analysis on the correlation between weight status 
and bullying. Int J Obes (Lond). 2014;38(10):1263-7. 
7. 
Koyanagi A, Veronese N, Vancampfort D, Stickley A, Jackson SE, Oh H, 
et al. Association of bullying victimization with overweight and obesity among 
adolescents from 41 low- and middle-income countries. Pediatr Obes. 
2020;15(1):e12571. 
8. 
Schwimmer JB, Burwinkle TM, Varni JW. Health-related quality of life 
of severely obese children and adolescents. JAMA. 2003;289(14):1813-9. 
9. 
Buttitta M, Iliescu C, Rousseau A, Guerrien A. Quality of life in 
overweight and obese children and adolescents: a literature review. Qual Life Res. 
2014;23(4):1117-39. 
10. 
Sutaria S, Devakumar D, Yasuda SS, Das S, Saxena S. Is obesity 
associated with depression in children? Systematic review and meta-analysis. Arch 
Dis Child. 2019;104(1):64-74. 
11. 
Kumar S, Kelly AS. Review of Childhood Obesity: From Epidemiology, 
Etiology, and Comorbidities to Clinical Assessment and Treatment. Mayo Clin Proc. 
2017;92(2):251-65. 
12. 
Colquitt JL, Loveman E, O'Malley C, Azevedo LB, Mead E, Al-Khudairy 
L, et al. Diet, physical activity, and behavioural interventions for the treatment of 
overweight or obesity in preschool children up to the age of 6 years. Cochrane 
Database Syst Rev. 2016;3:CD012105. 
13. 
Jorgensen RM, Bruun JM, Kremke B, Bahnsen RF, Nielsen BW, 
Vestergaard ET. Sustainable weight loss over three years in children with obesity: a 
pragmatic family-centered lifestyle intervention. Eat Weight Disord. 2020. 

28-10-2024 
 
14 
 
14. 
Peirson L, Fitzpatrick-Lewis D, Morrison K, Warren R, Usman Ali M, 
Raina P. Treatment of overweight and obesity in children and youth: a systematic 
review and meta-analysis. CMAJ Open. 2015;3(1):E35-46. 
15. 
Wild CE, Rawiri NT, Willing EJ, Hofman PL, Anderson YC. 
Determining barriers and facilitators to engagement for families in a family-based, 
multicomponent healthy lifestyles intervention for children and adolescents: a 
qualitative study. BMJ Open. 2020;10(9):e037152. 
16. 
Cave TL, Derraik JGB, Willing EJ, Hofman PL, Anderson YC. Caregiver 
perceptions of weight in preschool children, and determinants of engagement in a 
multidisciplinary intervention service for weight issues. Obes Res Clin Pract. 
2021;15(3):262-7. 
17. 
Taylor RW, Williams SM, Dawson AM, Taylor BJ, Meredith-Jones K, 
Brown D. What factors influence uptake into family-based obesity treatment after 
weight screening? J Pediatr. 2013;163(6):1657-62 e1. 
18. 
Cole TJ, Lobstein T. Extended international (IOTF) body mass index cut-
offs for thinness, overweight and obesity. Pediatr Obes. 2012;7(4):284-94. 
19. 
Nysom K, Molgaard C, Hutchings B, Michaelsen KF. Body mass index 
of 0 to 45-y-old Danes: reference values and comparison with published European 
reference values. Int j Obes Relat Meta Disord. 2001;25(2):177-84.