A 4-year, cluster-randomized, controlled childhood obesity prevention study: STOPP



To assess the efficacy of a school-based intervention programme to reduce the prevalence of overweight in 6 to 10-year-old children.


Cluster-randomized, controlled study.


A total of 3135 boys and girls in grades 1–4 were included in the study.


Ten schools were selected in Stockholm county area and randomized to intervention (n=5) and control (n=5) schools. Low-fat dairy products and whole-grain bread were promoted and all sweets and sweetened drinks were eliminated in intervention schools. Physical activity (PA) was aimed to increase by 30 min day−1 during school time and sedentary behaviour restricted during after school care time. PA was measured by accelerometry. Eating habits at home were assessed by parental report. Eating disorders were evaluated by self-report.


The prevalence of overweight and obesity decreased by 3.2% (from 20.3 to 17.1) in intervention schools compared with an increase of 2.8% (from 16.1 to 18.9) in control schools (P<0.05). The results showed no difference between intervention and controls, after cluster adjustment, in the longitudinal analysis of BMIsds changes. However, a larger proportion of the children who were initially overweight reached normal weight in the intervention group (14%) compared with the control group (7.5%), P=0.017. PA did not differ between intervention and control schools after cluster adjustment. Eating habits at home were found to be healthier among families with children in intervention schools at the end of the intervention. There was no difference between children in intervention and control schools in self-reported eating disorders.


A school-based intervention can reduce the prevalence of overweight and obesity in 6 to 10-year-old children and may affect eating habits at home. The effect of the intervention was possibly due to its effect on healthy eating habits at school and at home rather than on increased levels of PA.


Childhood overweight and obesity are emerging health problems in all western countries and also in urban areas in developing countries.1, 2

In Sweden, the prevalence of overweight and obesity has been rapidly increasing.3, 4 Approximately 15–25% of Swedish 10-year-old children are overweight or obese.5, 6

Childhood obesity affects self-esteem and increases the risk of future diabetes, cardiovascular disease and malignancies.7, 8, 9, 10, 11 Thus, childhood obesity is a major threat to public health and may reduce life expectancy.11, 12, 13, 14

Behavioural obesity treatment approaches, including changes in dietary habits and exercise, have limited long-term effect on body weight.5, 15, 16 Anti-obesity drugs appear to have modest effects on body weight in adolescents.17, 18, 19, 20, 21, 22 Furthermore, the use of drugs to treat a disease, which in the vast majority of children is associated with environmental changes contributing to an unhealthy lifestyle is controversial. Therefore, preventive efforts aimed to reduce the increasing prevalence of childhood obesity are warranted.

Childhood obesity is multifactorial, including at least intrauterine, postnatal, socioeconomic, genetic and lifestyle factors. However, it is plausible that lifestyle changes explain the rapid increase in the prevalence of overweight and obesity in most western countries during the last 25 years.23 The most important factors explaining these changes are related to altered eating habits and physical activity (PA).23 Earlier preventive efforts have shown a limited success in reducing the prevalence of childhood obesity,24, 25, 26 which underlines how difficult it is to achieve and maintain lifestyle modifications. Still, it is reasonable to believe that preventive strategies aimed to curb the obesity epidemic should include a reduction in the amount of sweetened drinks, sweets and fat snacks consumed27, 28 together with an increase in PA levels.29

We aimed to assess whether a school-based prevention programme focused on reduced unhealthy eating and increased PA during school time over a 4-year period could reduce the prevalence of overweight and obesity among 6 to 10-year-old children. We also aimed to assess whether the intervention affected PA measured objectively by accelerometry and whether eating habits at home differed between control and intervention schools at the end of the intervention.


Study design and participants

The STOPP study was designed as a school-based intervention study over four school years between August 2001 and June 2005. The research design was mixed with a cluster-randomized design pre- and post-test for assessing changes in Body Mass Index standard deviations score (BMIsds) and a cluster-randomized continuous test design for the measurement of PA. A post-test design was used for eating behaviour assessments. Ten primary schools including children between 6 and 10 years of age within the Stockholm county area were selected. Participating schools had a mixed pupil population with children from middle and working class families living both in blocks of flats and in detached houses. The proportion of children with an immigrant background, defined as children requiring native-language teaching did not exceed 15%. Five of the selected schools were thereafter randomized to intervention and five schools to control.

All children participated in the study until the end of their fourth school year, that is, until the age of 9–10 years. Thus, the children who entered the study during their first school year in August 2001 participated in the programme for four years, whereas children who started school at a later year, participated in the programme for shorter time periods. Owing to unforeseen changes in the school organization, the number of children was reduced in some of the schools during the study period (Table 1). Children from one class in one control school withdrew from the programme due to the decision of the class teacher.

Table 1 Prevalence of overweight and obesity respectively by calendar year (2001 and 2005) and gender

In total, 1670 and 1465 children (51% boys) aged 6–10 years, mean age 7.4 years (s.d. 1.3) in intervention vs 7.5 years (s.d. 1.3) in control schools were included into the intervention and control regimen between 2001 and 2004 (Figure 1). Ninety-two to 100% of the children in the intervention schools and 90 to 100% in the control schools were entered into the study and participated in at least one occasion of weight and height assessment. At termination of the intervention, 188 and 123 children (11%) randomized to intervention and control schools, respectively had participated for the full duration of the intervention, 376 and 301 children (24%) participated for 3 years, 457 and 378 (29%) participated during 2 years and an additional 517 and 498 (36%) intervention and control children participated in the study for 1 year. The number of schools invited, those accepting the invitation to participate, those that were randomized and number of children accepting the invitation to participate, together with the number of children eligible for evaluation are presented in Figure 1.

Figure 1

Children in the STOPP study through each stage of the trial, that is, enrolment, allocation, follow-up and analysis.

The social and ethnic background was similar in control and intervention schools. The proportion of parents categorized as immigrants varied between 5 and 10% (range) in both intervention and control schools. The proportion of children living with two parents varied between 63 and 77% in intervention and between 63 and 80% in control schools, low-income households between 8 and 22% in intervention and between 7 and 22% in control schools and parents reporting an academic level of education (higher than upper secondary school) between 23 and 46% in intervention and between 26 and 46% in control schools.

In total, 1538 children in the intervention and 1300 children in the control schools had their heights and weights measured at least at two occasions during the study and were defined as the observed cases analysis population. In total, 132 children from intervention and 165 children from control schools only participated in one assessment. All children who had at least one measurement of height and weight are defined as the full analysis population (FAS). The average length of intervention was a mean (s.d.) duration of 613 days (361).


The intervention was aimed to be financed within the resources of the ordinary school budget. The activities of the research staff were restricted to documentation of school activities, to perform measurements of PA, height and weight and also to encourage the school and after school care centre staff to carry out suggested changes.

The main focus of the intervention was to change the school environment rather than on healthy lifestyle education, although the school and after school care centre staff were encouraged to emphasize the importance of healthy eating and PA.

Most Swedish 6 to 10-year-old children attend after school care centres after school hours. The centres are usually open until 1800 hours. More than 90% of the participating children ate their lunch at school (school lunch is free for all children in the Swedish school system) and had an afternoon snack at the after school care centre, that is, approximately 30–35% of the children's weekly meals were provided in a setting possible to control in the prevention programme.

Physical activity intervention

The intervention aimed to increase the amount of PA by 30 min per child per day. Therefore, an additional 30 min of daily PA was integrated into the regular school curriculum and facilitated by the class teachers. To reduce sedentary behaviour, children were not allowed to bring toys that might increase this behaviour, such as hand held computer games, to schools and after school care centres. The maximum time spent playing computer games at the after school care centres was restricted to 30 min per child per day.

Dietary intervention: school lunch and afternoon snack

The teachers were instructed to encourage the children to increase the intake of vegetables during the school lunch. To facilitate this, all intervention schools had agreed to offer a variety of vegetables, and the food was arranged so that the children first served themselves vegetables and thereafter the main course. White bread was substituted with whole-grain bread or similar products including a high amount of dietary fibres. The sugar content in the school lunches and in the afternoon snacks was reduced by strategies such as replacing fruit yogurt with plain yogurt and eliminating fruit juices, soft drinks, lemonades and desserts. Whole-fat (3% fat content) or medium-fat (1.5% fat content) milk was substituted by skimmed milk (0.5% fat) and low-fat butter, cheese and yoghurt were provided. Sandwich ingredients were required to be low fat.

Other aspects on food intake

Intervention schools were encouraged to eliminate sweets, sweet buns and ice cream in association with festivities. When celebrating birthdays, parents were asked not to provide these products at schools and after school care centres. Furthermore, parents of the children in the intervention schools were instructed not to supply sweetened drinks, sweets and other unhealthy products in the packed lunch during school excursions and sports days.

Awareness intervention

A STOPP newsletter was distributed to parents and school staff of intervention schools twice annually aimed to increase the awareness of the intervention. Furthermore, the research staff had meetings with the school personnel once every term also aimed at increasing the awareness of the intervention. School nurses received education in obesity-related problems. The compliance with the STOPP concept was checked regularly when the research staff visited schools during lunches, after school care activities and sports days. Furthermore, the STOPP staff also performed random unannounced school visits. Deviations were documented and discussed with the school staff and the headmasters. All control schools continued their normal curriculum and none of the intervention activities were performed except for yearly measurements of height, weight and PA. However, the parents in the control schools received information regarding the aim but not the content of the study.



Weight and height measures were performed in all children at the yearly school start in the autumn. For children who finished the fourth grade and therefore left the study, weight and height were also measured at the end of the school year (May to June). At the study completion, all children still participating in the study were assessed for efficacy in May to June 2005. Height and weight were measured using the standard clinical procedures with a transportable Harpenden Stadiometer and a digital scale (Tanita BWB 800S, Tanita, Tokyo, Japan). Height was measured to the nearest 0.1 cm and weight to the nearest 0.1 kg. Overweight and obesity were defined according to IOTF recommendations.30 All the children were measured after 0900 hours in the morning but before lunch, wearing light underwear and without shoes. Trained research assistants performed all anthropometric measurements. The range between the first measurement (baseline) of weight and height varied between October 2001 and August 2004. The range between the last measurements varied between May 2002 and June 2005.

Physical activity

The accelerometer, Actiwatch (AW) (model 4, Cambridge Neurotechnology Ltd, Cambridge, UK), was used to assess PA, during seven consecutive days, from Tuesday to Monday. The AW is a validated uniaxial accelerometer31 found to be feasible for long-term studies of PA in children.32 Ten children from the intervention schools and 10 from the control schools were randomly selected for weekly assessments each week during the intervention. Children who provided valid AW counts32 during at least 600 min day−1 and for at least 4 school days were included in the analysis population. The children wore the AW on the non-dominant arm for 24 h day−1 and were instructed not to remove or release the AW from the arm except while swimming and bathing.

Physical activity was assessed in a total of 1538 children during the study. A total of 245 children (16%) were excluded due to missing data (that is, invalid registrations and technical failures). Thus, 1293 children had valid PA data, 653 girls and 640 boys (mean 8.1 years, s.d. 1.2), and were included in the evaluation. Each child included in this study was measured once. The children were equally distributed between intervention (n=653) and control schools (n=640). The range between the first and last measurements of PA varied between April 2002 and June 2005.

Eating habits

At the end of the study a questionnaire regarding eating habits at home was distributed by the school staff to the parents of all children in the third and the fourth grade. The questionnaire consists of 14 multiple choice questions and assessed the frequency of food items served at home, with the following alternatives; every day, several times a week, 1–2 times a week, rarely/never. Overall, 692 of 770 families (89.9%) filled out the questionnaire, 91% in intervention and 87% in control schools, after one reminding letter.

The questionnaire was categorized into eight domains; dairy products (milk, butter and cheese), cereals, bread, fast food (hamburgers, pizzas and french fries), crisps/nuts (crisps, peanuts and pop corn), sweet products (ice cream, buns, cookies and sweets), drinks (soft drinks, syrup, juice and sweet milk drinks), and fruit and vegetables. Before analyses, all domains were dichotomized into healthy and unhealthy levels of food consumption. The unhealthy choices in the dairy products were defined as whole-fat milk (3% fat), butter (>40% fat) and cheese (24–40% fat) every day or several times a week. Furthermore, unhealthy choices included sweetened cereals or white bread, fast food products and sugar-containing drinks when being selected every day or several times a week. The criterion for an unhealthy/energy-dense/high-fat choice for crisps/nuts and sweet products was whether being selected once or twice a week in addition to every day and several times a week. The consumption of fruits and vegetables was categorized as unhealthy if consumed 1–2 times per week, a few times per week or never.

Breakfast and dinner eating habits were categorized into a weekly breakfast and dinner score, respectively. The score was derived from the number of days with intake of breakfast and dinner multiplied by the number of family members who were present during the meal. Number of family members were scored as, at least one parent (=3), a sibling (=2) and alone (=1). The number of days with intake were scored 0–2 (=1), 3–5 (=2) and 6–7 (=3). The total score ranges from 0 to 9 with higher scores indicating ‘better’ eating habits. The level of parental educational background was divided into high (3 years at upper secondary school or more) and low (less than 3 years at upper secondary school) and used as an indicator of socioeconomic status. The range between the first and last measurements of eating behaviour varied between April 2005 and June 2005.

Eating attitudes were assessed by a Swedish version of ChEAT (Children's Eating Attitude Test).33, 34 All children were requested by the teachers to fill in the ChEAT questionnaire before terminating the project in grade 4, (n=1750), that is, when the children were 9–10 years old. The questionnaire was administered by teachers according to the written instructions. In total, 78% questionnaires were returned (n=1368). Questionnaires with missing values were omitted and complete questionnaires were received for 70% of the children (n=1227). The range between the first and last measurements of eating attitudes varied between May 2002 and June 2005.


The prevalence of overweight and obesity in children (grades 2–4) in intervention and control schools was calculated in the calendar years 2001 and 2005 (independent observations). The children in grade one were excluded to compare independent observations. The prevalence proportions are presented with corresponding 95% confidence intervals for difference between intervention and control schools.

The change in BMIsds was calculated according to Rolland-Cachera35 as the change between the first and the last measurements of BMI, that is, eligible assessments were any two or more of the five assessments during the study period (repeated measures). The primary analysis was carried out using the observed cases population, and a sensitivity analysis was performed using the FAS population. The FAS population was evaluated with replacement for missing data by the last observation carried forward approach, ie, where only one measurement was observed, and the estimated change in BMIsds was set to 0.

The change in BMIsds was evaluated using analysis of covariance, including gender as a fixed factor, age and baseline BMIsds as covariates. Analyses were performed with and without correction for the cluster variation, ie, with school as a random factor in the analysis of covariance model to estimate the explained fraction due to variation between schools.

Subsequently, the analysis of differences in PA between intervention and control schools followed the same principles including corrections for activity-related variation (ie, calendar year and months of measurement) as random factors in the analysis of covariance model. The power calculation for this study was carried out using the t-test and the statistical package Nquery. The estimated sample size was calculated for a two-sided test with the significance level of 0.05, power 80% s.d. for the change in BMIsds of 0.9, to detect a minimum difference of 0.1 with respect to the change in BMIsds. The required number of subjects was, 1273 per group. It was decided to randomize 5+5 schools with approximately 1500 children in each intervention arm to have a margin for dropouts and withdrawals.

Logistic regression analysis was used to investigate the impact of parental education (low vs high), gender and the intervention on the healthy choice behaviour in food consumption measured at termination of the study. Finally, to examine whether parental education modified the association between intervention and healthy eating, an interaction term (parental education × intervention) was included in the model. The effect of clustering was not evaluated for the eating behaviour questionnaire.

Descriptive statistics are shown as mean, s.d. and range for continuously distributed variables. The mode, median range mean and s.d. were calculated for the data from ChEAT. These data were analysed using the Mann–Whitney test for comparison between intervention schools and control schools and also for comparison between genders.

All tests were two-sided and statistical significance was defined at 0.05. All calculations were carried out in STATISTICA 7.0 or higher, Statsoft Inc., Tulsa, USA.

We certify that all applicable institutional and governmental regulations concerning the ethical use of human volunteers were followed during this research. The study was approved by the Regional Ethical Review Board in Stockholm (2001/336).


The prevalence of overweight and obesity in grades 2–4 was significantly reduced in the intervention group between baseline and follow-up (P<0.05), shown in Table 1. In contrast, an increase in prevalence of overweight and obesity was observed in the control group (Table 1). The corresponding 95% confidence interval for difference between intervention and control with respect to the proportion of children with a change including both overweight and obesity was 1.3–10.6%, (P<0.05) in favour of the intervention (Table 1). In gender-stratified analyses, only a minor increase in the proportion of children classified as overweight or obese was observed in control girls and no statistically significant difference was found compared with intervention girls. For boys, the prevalence of overweight and obesity in the intervention schools was significantly reduced, whereas it increased in control schools (Table 1). For children in grades 3–4, the difference in favour of the intervention was more pronounced 9.2%, 95% confidence interval 3.3–16.9% (P<0.01). There was a statistically significant difference between boys in control and intervention schools (P<0.05), but no difference was found among girls.

In analyses including the observed cases a mean change from the first to the last observation in BMIsds was observed in favour of the intervention group (−0.01 BMIsds vs 0.3 BMIsds, effect size, 95% confidence interval 0.09–0.00; P=0.049). However, this difference was attenuated after adjustment for cluster of schools (P=0.14). The cluster correlation coefficient was low, <1%. Changes in BMIsds were correlated with age (P<0.001) with a more pronounced intervention effect in the older children. Sensitivity analyses using the FAS population showed similar results as the analysis of the primary efficacy variable (data not shown). Analyses with a subgroup of children who had participated in the intervention for more than 2 school years showed no significant difference between intervention and control schools in mean change in BMIsds.

An increase in the proportion of children with normal weight was observed in the intervention group, compared with the control group, (2.3 vs 1.1%). The corresponding proportions of children who shifted from overweight or obesity to normal weight were 14 and 7.5%, respectively (P=0.017). In lean children in the intervention group (defined as, individuals with BMIsds <0), there were no signs of a negative effect on BMIsds, that is, a decrease in BMIsds over time (P=0.31).

The overall levels of total PA tended to be higher for children in the intervention schools compared with controls (P=0.06); however, this association was attenuated after adjustment for cluster by school (P=0.10), Table 2a. Physical activity during after school care time was significantly higher for children in the intervention schools compared with controls (P=0.004), but this difference was also attenuated after cluster adjustment (P=0.27). No differences between intervention and control schools were observed in PA during school time and during evening time. The cluster correlation coefficient was low, <3%. Gender differences in PA levels are shown in Table 2b. Physical activity measurements were collected during 4 years, 2002 (n=249), 2003 (n=435), 2004 (n=412) and 2005 (n=197). Mean (s.d.) unadjusted total PA (0800–2100 hours) expressed in counts per minute (c.p.m.) for intervention/control was 800 c.p.m. (170)/816 c.p.m. (161) in 2002, 795 c.p.m. (149)/767 c.p.m. (164) in 2003, 752 c.p.m. (159)/741 c.p.m. (145) in 2004 and 805 c.p.m. (166)/766 c.p.m. (162) in 2005.

Table 2a Physical activity levels in children
Table 2b Physical activity levels in girls and boys

Families with children from intervention schools in grades 3 and 4 reported healthier eating habits at home (ie, decreases in high-fat dairy products, sweetened cereals and sweet products) compared with those with children in control schools (Figure 2). Significant differences between children in intervention and control schools were found for high-fat dairy products (P=0.001), sweetened cereals (P=0.02) and sweet products (P=0.002). No differences were observed for consumption of bread (P=0.09), fast food (P=0.43), crisps/nuts (P=0.16), drinks (P=0.75), and fruit and vegetables (P=0.47). There were no differences between families from intervention and control schools regarding breakfast and dinner eating habits, and the dinner and breakfast scores were similar (data not shown).

Figure 2

Difference in proportions between intervention and control families in unhealthy eating habits. Negative values denote lower prevalence of unhealthy eating habits in intervention.

Eating behaviour varied partly with the parental educational background. The proportion of families who reported an unhealthy consumption of fast food was higher in the families with parents who had lower educational background, P<0.001.

Breakfast and dinner scores appeared to differ between the two parental education groups. The proportion of children with maximum breakfast score (=9) was 28% in families with lower and was 43% in families with a higher parental educational background (P=0.01). Proportions of maximum dinner scores were 90% compared with 94% in the two groups, respectively (P=0.20).

A significant interaction effect was observed between parental education and intervention for reported intake of dairy products and fast food. For children in families with low parental education background, the odds ratio (OR) was 3.58 with regard to healthy choice behaviour for dairy products in the intervention group compared with the control group, (OR=1.0), whereas for children in families with high parental education background the corresponding ORs for the intervention group and the control group were 1.65 and 1.18, respectively (P for interaction=0.02). The same patterns were observed for the OR for healthy choice behaviour for fast food products where ORs were 2.5 in the intervention group compared with 1.0 in the control group in children in families with low parental education, whereas in families with a high parental education background the corresponding ORs were 2.1 and 3.2, respectively (P for interaction=0.0005).

There was no difference between children from intervention and control schools with respect to eating attitudes assessed by the ChEAT questionnaire.


This study evaluated the efficacy of a school and after school care-based obesity prevention programme, STOPP, focused on healthy eating, including modification of school lunches and afternoon snack, increased PA during school time and a reduction of sedentary activities during time spent at after school care. The programme was designed to be an integrated, sustainable part of the ordinary school curriculum, possible to maintain within the ordinary school budget. After 4 years of intervention, the prevalence of overweight and obesity in grades 2, 3 and 4 children in the intervention schools was significantly reduced compared with an increase in control schools.

In analyses including all children who participated in the study for at least 1 school year, the difference between intervention and controls in the change in BMIsds did not show statistical significance after adjustment for cluster by school. However, the proportion of children who were initially overweight or obese and who reached normal weight was larger in the intervention schools.

The effect of intervention was more pronounced in boys than in girls, which is in contrast to what has been observed in more education-based obesity prevention programmes.36 Recent epidemiological data from Sweden have indicated a reduced prevalence of overweight and obesity among girls but not among boys6 and it is possible that this secular trend has attenuated the study effect among girls.

Although results are difficult to compare due to variations in methodology, duration and social setting, the results in this study were better than expected from earlier studies.36, 25, 26, 37 A possible factor of importance might be that we succeeded in creating a school and after school care environment with restricted access to sweetened products and beverages.

In an attempt to evaluate the different aspects of the intervention, PA was measured objectively throughout the 4 years. The results from these measurements suggest that the PA intervention probably only contributed to a minor extent to the observed change in overweight prevalence between the intervention and control schools. Overall, PA tended to be higher in intervention schools compared with control schools. However, this difference was attenuated after further adjustment for cluster by school, indicating variation by school. Physical activity during school time did not differ between intervention and control schools even though all teachers in the intervention schools reported that they implemented 30 min of additional PA per day during school time. It is possible that schoolteachers did not report this part of the intervention correctly and this was also difficult to supervise for the STOPP research staff. However, it is also plausible that children in intervention schools compensated by being less physically active during other parts of the school day or a combination of both. The interest in implementing the programme varied considerably among the teachers, and some teachers reported it was difficult to integrate PA in their ordinary lessons. Reducing sedentary time during after school care time appeared to be partly successful. A statistically significant higher PA level was observed in intervention schools at this time of the day, although this difference did not persist after cluster adjustment.

Random documented school visits by the study staff indicate that the implementation of the intervention including healthy school lunches and afternoon snacks was, with minor divergences, successful in all intervention schools. Removal of all types of sweets was more difficult to accept for the school staff and required frequent reminders from the STOPP staff. The control schools were instructed not to change their health-promoting policies during the study period. However, due to the public interest in the childhood obesity epidemic, some of the control schools performed minor changes in their school lunches and afternoon snacks during the intervention period. These changes were out of control for the researchers but are unavoidable in any type of public intervention and may have affected the results, reducing differences between intervention and control schools.

Although the intervention was focused on eating habits at school and not on health education per se, we observed in three of eight food domains a more healthy food intake in the families from intervention schools at the end of the intervention. It is most likely that this is an effect of the intervention, as other aspects such as breakfast and dinner habits not dealt with in the intervention programme did not differ. These results might suggest that changes in school lunches and after school care snacks, strict rules and attitudes against unhealthy eating among professional caretakers facilitate parental selection of more healthy food alternatives.

We found a social gradient with a less healthy eating pattern among families with less educated parents. This is in agreement with a higher prevalence of obesity in children from families with lower education.6 Interestingly, the difference between intervention and control families were more pronounced among families with a low education indicating that the STOPP programme might predominantly influence the behaviour in high-risk families.

With rising prevalence of overweight and obesity in the population increased risk for body dissatisfaction might also be the case.38 Earlier studies have shown that young children are influenced by the extreme ideal for thinness, particularly in women, and that weight concerns start at the early age.39, 40 As recently suggested,41 obesity interventions should take these issues into account, including an evaluation whether these programmes increase the risk of unhealthy food restraint and subsequently eating disorders. We found no signs of negative effects of the intervention as measured by self-report. There was no effect of the intervention on BMI in lean children (BMIsds >0), and the ChEAT results were almost identical in intervention and control schools. Thus, the type of intervention here presented seems not to be harmful.


The study has several limitations. The children in the study were exposed to the intervention anywhere between 1 and 4 years and therefore only 311 children participated for the full duration of the intervention. Almost one-third of the children participated for only 1 year and that time period might have been insufficient to detect a change in BMIsds. We did not have any control on PA and dietary behaviours during the summer holidays and this might negatively affect the long-term effect of the intervention. The summer periods have been shown to be associated with an increase of body fat in children who have improved their body composition during a school-based intervention.42

The family food questionnaire has not been validated, which could have implications on the results, and the questionnaire was only answered at the end of the study. Physical activity and ChEAT were measured continuously during the study period. Thus, we have no comparable data obtained before the intervention. However, environmental characteristics were very similar for intervention and control schools, and there were no differences in the socioeconomic or educational status of the parents. Therefore it is unlikely that the observed differences were present before the initiation of the intervention.


A school-based intervention including healthy school lunches and after school care snacks as well as strict rules against unhealthy eating can reduce the prevalence of overweight and positively influence eating habits at home. It is unlikely that the PA intervention contributed substantially to the result as no difference in PA levels between intervention and control schools was observed despite the school level intervention. Thus, it remains to be established whether successful PA intervention can further improve the outcome of this type of intervention.


  1. 1

    Lobstein T, Baur L, Uauy R . Obesity in children and young people: a crisis in public health. Obes Rev 2004; 5: S4–104.

    Article  Google Scholar 

  2. 2

    Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM . Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA 2004; 291: 2847–2850.

    CAS  Article  Google Scholar 

  3. 3

    Petersen S, Brulin C, Bergstrom E . Increasing prevalence of overweight in young schoolchildren in Umea, Sweden, from 1986 to 2001. Acta Paediatr 2003; 92: 848–853.

    CAS  Article  Google Scholar 

  4. 4

    Rasmussen F, Johansson M, Hansen HO . Trends in overweight and obesity among 18-year-old males in Sweden between 1971 and 1995. Acta Paediatr 1999; 88: 431–437.

    CAS  Article  Google Scholar 

  5. 5

    Asp N-G, Björntorp P, Britton M, Carlsson P, Kjellström T, Marcus C et al. Treating obesity in children and adolescents. In: Östman J, Britton M, Jonsson E (eds). Treating and Preventing Obesity. Wiley-VCH Verlag GmbH & Co KgaA: Weinheim, 2004, pp 227–259.

    Google Scholar 

  6. 6

    Sundblom E, Petzold M, Rasmussen F, Callmer E, Lissner L . Childhood overweight and obesity prevalences levelling off in Stockholm but socioeconomic differences persist. Int J Obes 2008; 32: 1525–1530.

    CAS  Article  Google Scholar 

  7. 7

    Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH . Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med 1997; 337: 869–873.

    CAS  Article  Google Scholar 

  8. 8

    Freedman DS, Dietz WH, Srinivasan SR, Berenson GS . The relation of overweight to cardiovascular risk factors among children and adolescents: the Bogalusa Heart Study. Pediatrics 1999; 103: 1175–1182.

    CAS  Article  Google Scholar 

  9. 9

    Strauss RS . Childhood obesity and self-esteem. Pediatrics 2000; 105: e15.

    CAS  Article  Google Scholar 

  10. 10

    Baker JL, Olsen LW, Sorensen TI . Childhood body-mass index and the risk of coronary heart disease in adulthood. N Engl J Med 2007; 357: 2329–2337.

    CAS  Article  Google Scholar 

  11. 11

    Fontaine KR, Redden DT, Wang C, Westfall AO, Allison DB . Years of life lost due to obesity. JAMA 2003; 289: 187–193.

    Article  Google Scholar 

  12. 12

    Olshansky SJ, Passaro DJ, Hershow RC, Layden J, Carnes BA, Brody J et al. A potential decline in life expectancy in the United States in the 21st century. N Engl J Med 2005; 352: 1138–1145.

    CAS  Article  Google Scholar 

  13. 13

    Daniels SR . The consequences of childhood overweight and obesity. Future Child 2006; 16: 47–67.

    Article  Google Scholar 

  14. 14

    Tucker DM, Palmer AJ, Valentine WJ, Roze S, Ray JA . Counting the costs of overweight and obesity: modeling clinical and cost outcomes. Curr Med Res Opin 2006; 22: 575–586.

    Article  Google Scholar 

  15. 15

    Asp NG, Björntorp P, Britton M, Carlsson P, Kjellström T, Marcus C et al. Treating and Preventing Obesity. Wiley-VCH Verlag GmbH & Co KgaA: Weinheim, 2004.

    Google Scholar 

  16. 16

    Whitlock EP, Williams SB, Gold R, Smith PR, Shipman SA . Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. Pediatrics 2005; 116: e125–e144.

    Article  Google Scholar 

  17. 17

    Berkowitz RI, Wadden TA, Tershakovec AM, Cronquist JL . Behavior therapy and sibutramine for the treatment of adolescent obesity: a randomized controlled trial. JAMA 2003; 289: 1805–1812.

    CAS  Article  Google Scholar 

  18. 18

    Godoy-Matos A, Carraro L, Vieira A, Oliveira J, Guedes EP, Mattos L et al. Treatment of obese adolescents with sibutramine: a randomized, double-blind, controlled study. J Clin Endocrinol Metab 2005; 90: 1460–1465.

    CAS  Article  Google Scholar 

  19. 19

    Berkowitz RI, Fujioka K, Daniels SR, Hoppin AG, Owen S, Perry AC et al. Effects of sibutramine treatment in obese adolescents: a randomized trial. Ann Intern Med 2006; 145: 81–90.

    CAS  Article  Google Scholar 

  20. 20

    Daniels SR, Long B, Crow S, Styne D, Sothern M, Vargas-Rodriguez I et al. Cardiovascular effects of sibutramine in the treatment of obese adolescents: results of a randomized, double-blind, placebo-controlled study. Pediatrics 2007; 120: e147–e157.

    Article  Google Scholar 

  21. 21

    Garcia-Morales LM, Berber A, Macias-Lara CC, Lucio-Ortiz C, Del-Rio-Navarro BE, Dorantes-Alvarez LM . Use of sibutramine in obese mexican adolescents: a 6-month, randomized, double-blind, placebo-controlled, parallel-group trial. Clin Ther 2006; 28: 770–782.

    CAS  Article  Google Scholar 

  22. 22

    Van Mil EG, Westerterp KR, Kester AD, Delemarre-van de Waal HA, Gerver WJ, Saris WH . The effect of sibutramine on energy expenditure and body composition in obese adolescents. J Clin Endocrinol Metab 2007; 92: 1409–1414.

    CAS  Article  Google Scholar 

  23. 23

    Butland B, Jebb S, Kopelman P, McPherson K, Thomas S, Mardell J et al. The Tackling Obesities: Future Choices. In: UGsF (ed). Programme 2nd edn, Government Office for Science, Department of Innovation, University and Skills: London, 2007. pp 1–164.

    Google Scholar 

  24. 24

    Asp N-G, Björntorp P, Britton M, Carlsson P, Kjellström T, Marcus C et al. Prevention of childhood obesity. Preventing Obesity in Children and Adolescents. In: Östman J, Britton M, Jonsson E (eds). Treating and Preventing Obesity. Wiley-VCH Verlag GmbH & Co KgaA: Weinheim, 2004, pp 75–92.

    Google Scholar 

  25. 25

    Flodmark CE, Marcus C, Britton M . Interventions to prevent obesity in children and adolescents: a systematic literature review. Int J Obes 2006; 30: 579–589.

    Article  Google Scholar 

  26. 26

    Sharma M . School-based interventions for childhood and adolescent obesity. Obes Rev 2006; 7: 261–269.

    CAS  Article  Google Scholar 

  27. 27

    Kubik MY, Lytle LA, Story M . Schoolwide food practices are associated with body mass index in middle school students. Arch Pediatr Adolesc Med 2005; 159: 1111–1114.

    Article  Google Scholar 

  28. 28

    James J, Thomas P, Cavan D, Kerr D . Preventing childhood obesity by reducing consumption of carbonated drinks: cluster randomised controlled trial. BMJ 2004; 328: 1237.

    Article  Google Scholar 

  29. 29

    van Sluijs EM, McMinn AM, Griffin SJ . Effectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials. BMJ 2007; 335: 703.

    Article  Google Scholar 

  30. 30

    Cole TJ, Bellizzi MC, Flegal KM, Dietz WH . Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000; 320: 1240–1243.

    CAS  Article  Google Scholar 

  31. 31

    de Vries SI, Bakker I, Hopman-Rock M, Hirasing RA, van Mechelen W . Clinimetric review of motion sensors in children and adolescents. J Clin Epidemiol 2006; 59: 670–680.

    Article  Google Scholar 

  32. 32

    Nyberg G, Ekelund U, Marcus C . Physical activity in children measured by accelerometry: stability over time. Scand J Med Sci Sports 2008; 19: 30–35 e-pub ahead of print 2 February, PMID 18248540.

    Article  Google Scholar 

  33. 33

    Edlund B, Hallqvist G, Sjoden PO . Attitudes to food, eating and dieting behaviour in 11 and 14-year-old Swedish children. Acta Paediatr 1994; 83: 572–577.

    CAS  Article  Google Scholar 

  34. 34

    Lundstedt G, Edlund B, Engstrom I, Thurfjell B, Marcus C . Eating disorder traits in obese children and adolescents. Eat Weight Disord 2006; 11: 45–50.

    CAS  Article  Google Scholar 

  35. 35

    Rolland-Cachera MF, Sempe M, Guilloud-Bataille M, Patois E, Pequignot-Guggenbuhl F, Fautrad V . Adiposity indices in children. Am J Clin Nutr 1982; 36: 178–184.

    CAS  Article  Google Scholar 

  36. 36

    Kropski JA, Keckley PH, Jensen GL . School-based obesity prevention programs: an evidence-based review. Obesity (Silver Spring) 2008; 16: 1009–1018.

    Article  Google Scholar 

  37. 37

    Sharma AM . The value of current interventions for obesity. Nat Clin Pract Cardiovasc Med 2008; 5: S3–S9.

    CAS  Article  Google Scholar 

  38. 38

    Robinson TN, Chang JY, Haydel KF, Killen JD . Overweight concerns and body dissatisfaction among third-grade children: the impacts of ethnicity and socioeconomic status. J Pediatr 2001; 138: 181–187.

    CAS  Article  Google Scholar 

  39. 39

    Wardle J, Watters R . Sociocultural influences on attitudes to weight and eating: results of a natural experiment. Int J Eat Disord 2004; 35: 589–596.

    Article  Google Scholar 

  40. 40

    Halvarsson K, Lunner K, Sjoden PO . Assessment of eating behaviours and attitudes to eating, dieting and body image in pre-adolescent Swedish girls: a one-year follow-up. Acta Paediatr 2000; 89: 996–1000.

    CAS  Article  Google Scholar 

  41. 41

    Carter FA, Bulik CM . Childhood obesity prevention programs: how do they affect eating pathology and other psychological measures? Psychosom Med 2008; 70: 363–371.

    Article  Google Scholar 

  42. 42

    Gutin B, Yin Z, Johnson M, Barbeau P . Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project. Int J Pediatr Obes 2008; 3: S3–S9.

    Article  Google Scholar 

Download references


We thank all participating schools for their efforts. The study was supported by grants from Stockholm County Council, Swedish Council for working life and social research, Swedish Research Council, Freemason's in Stockholm Foundation for Children's Welfare and Signhild Engkvist Foundation.

Author information



Corresponding author

Correspondence to C Marcus.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Marcus, C., Nyberg, G., Nordenfelt, A. et al. A 4-year, cluster-randomized, controlled childhood obesity prevention study: STOPP. Int J Obes 33, 408–417 (2009). https://doi.org/10.1038/ijo.2009.38

Download citation


  • childhood obesity
  • prevention
  • physical activity
  • school intervention
  • healthy eating

Further reading