The rise in obesity in the past several decades has been dramatic worldwide, particularly in the Western world. According to data from 2016, WHO reports that the Nordic countries and the Netherlands have similar rates for overweight and obesity (people with a BMI ≥ 25 kg/m2) that vary within 4 percentage points; from Denmark with the lowest 55.4% to Iceland with the highest 59.1%. These rates are lower than many Western countries (such as Canada, USA, Australia, New Zealand, UK, France, Spain, Greece, and the Middle East). Similar are the results for obesity (lowest for Denmark with 19.7% and highest for Norway with 23.1%). These rates are also lower than many Western countries, as mentioned above (excluding France) [
Nordic countries and the Netherlands are highly regulated welfare states. They are also countries in geographical proximity with similarities in their societies such as economic and social policies. Therefore, these countries can apply similar initiatives and can be compared with each other. A regional focus allows for a more targeted analysis and provides results and conclusions that can benefit at the regional level [
Well planned, implemented, and evaluated setting-based interventions are paramount in measuring the success, future directions, and financial commitment of interventions for obesity prevention. Bottom-up approaches enable taking into account the needs of the intervention participants and the characteristics and resources of the context. This makes interventions more feasible to implement and more salient to the participants; these aspects increase the sustainability of desired outcomes. Research evidence supports the bottom-up approach since it can help overcome barriers of required change [
Multilevel approaches that involve the environment of the individual are highly significant for fighting the obesity epidemic, as environmental factors are often a root cause of obesity [
The school setting is equally important both for children and their parents, especially as this setting is where children spend a large amount of their time during the day. Schools are places where children consume one or more meals per day. They are places where canteens, vending machines, and restaurants are often available which can negatively influence children’s eating habits. In addition, children spend a lot of time sitting in school. Physical education, as well as the provision of available spaces for play and activities, can improve their PA levels. School-based interventions have provided evidence for effectiveness of childhood obesity prevention [
Similarly, the worksite setting is of high importance, due to the considerable amount of time most adults spend at work. There are also opportunities to improve the worksite with exercise facilities, such as access to gyms, and with improved access and availability of healthy food provided in restaurants, canteens, or as snacks that can encourage people towards healthier habits.
Community-based interventions are also very important because they can create a healthier environment for people to live in, through parks, policies on fast food, cycling and jogging tracks, awareness campaigns, and so on. Therefore, they can be very powerful for affecting diet and PA habits in a community [
A thorough review of community-based interventions, addressing obesity prevention in the Netherlands through an equity lens, reported that these interventions have impacted socioeconomic inequalities in health behaviour positively and negatively [
Furthermore, reviews of health promotion interventions implemented at the worksite, globally and in Nordic countries, have found that the majority of studies utilised the worksite as a convenient setting to implement interventions targeted at individual behaviour change, rather than use a setting-based, multilevel approach including changes to the worksite environment [
Different components that define the quality of a study such as representativeness, randomisation process, comparability of chosen intervention and control groups, attrition rate, and spillover effect/attributability to intervention also need to be considered. The quality of a study affects highly the outcome, and a low-quality study might obscure the impact of the intervention otherwise evidenced. Another important element in evaluating the quality of interventions and an integral part of designing and planning complex interventions is the use of theory. This has also been acknowledged by the British Medical Research Council and forms part of its guidance [
The aim of this review was to identify, synthesise, and evaluate the quality of interventions including environmental components based in the in settings from Nordic countries and the Netherlands, aimed at preventing obesity where BMI was measured and reported as an outcome.
The review of the literature was completed systematically, guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement [
Interventions targeted all age groups, living in either the Netherlands or the Nordic countries: Denmark, Finland, Iceland, Norway, and Sweden, regardless of socioeconomic status (SES). The Nordic countries were included in the review based on geographical and cultural similarities. The Netherlands were included due to the similarities of their historical welfare model to that of the Nordic countries in general [
We chose interventions in the community, school, and worksite setting with at least one environmental component. The community is considered a setting as much as the worksite and school [
No restrictions were made to length of follow-up. English language studies published in the literature up to and including April 2016 were included in the review. Hospital-based clinical interventions or those primarily based in the primary care setting were excluded. Furthermore, worksite-based interventions were excluded if the target group was deemed too specialised and not representative of the general population of employees, for example, one professional group only. If there was more than one article referring to different follow-up points, the longest follow-up was chosen as the included article.
All intervention study designs other than purely qualitative were included.
Interventions where the outcome was obesity or chronic disease prevention and where BMI was measured and reported as either a primary or secondary outcome were included. Studies that measured only behavioural outcomes including dietary or PA levels were excluded.
A thorough search of the databases Medline and Embase through the Ovid search strategy was completed for articles published until April 2016 (Table
Search strategy, medline and EMBASE via ovid.
(1) obesity.mp. |
(2) childhood obesity.mp. |
(3) overweight.mp. |
(4) exp Obesity/pc [prevention and control] |
(5) exp Cardiovascular disease/pc [Prevention & Control] |
(6) (body mass index or BMI).mp. |
(7) (Denmark or Danish or Dane$).mp. |
(8) (Sweden or Swedish or Swede$).mp. |
(9) (Norway or Norwegian$).mp. |
(10) (Finland or Finnish or Finn$).mp. |
(11) (Iceland or Icelandic or Icelander$).mp. |
(12) (Netherlands or Dutch).mp. |
(13) (Nordic or Scandinavia$).mp. |
(14) communit$.mp. |
(15) (population based or population-based).mp. |
(16) (community based or community-based)mp. |
(17) (whole of community or whole-of community).mp. |
(18) (community wide or community-wide).mp. |
(19) national.mp. |
(20) state.mp. |
(21) regio$.mp. |
(22) local.mp. |
(23) municip$.mp. |
(24) district.mp. |
(25) town$.mp. |
(26) village$.mp. |
(27) borough.mp. |
(28) precinct.mp. |
(29) (county or counties).mp. |
(30) area.mp. |
(31) province.mp. |
(32) shire.mp. |
(33) urban.mp. |
(34) rural.mp. |
(35) (city or cities).mp. |
(37) (school based or school-based).mp. |
(38) (secondary school or secondary-school).mp. |
(39) (elementary school or elementary-school or primary school or primary-school).mp. |
(40) (pre-school or preschool).mp. |
(41) pupil$.mp. |
(42) student$.mp. |
(43) kindergarten$.mp. |
(44) childcare.mp. |
(45) nurser$.mp. |
(46) daycare.mp. |
(47) worksite$.mp. |
(48) worksite$.mp. |
(49) employee$.mp. |
(50) worker$.mp. |
(52) intervention study.mp. |
(53) prevention.mp. |
(54) primary prevention.mp. |
(55) program$.mp. |
(56) (community intervention$ or community-intervention$).mp. |
(57) (community program$ or community-program$).mp. |
(58) (health promotion or promotion).mp. |
(59) (lifestyle intervention or life-style intervention).mp. |
(60) exercise intervention.mp. |
(61) (physical activity or physical actvity intervention).mp. |
(62) (diet$ intervention or healthy eating intervention).mp. |
(63) environment$ intervention.mp. |
(64) policy.mp. |
(65) policy implementation.mp. |
(66) project.mp. |
(67) study.ti. |
(68) (randomi#ed control stud$ or randomi#ed control trial or RCT).mp. |
(69) cohort stud$.mp. |
(70) longitudinal.mp. |
(71) prospective.mp. |
(72) case control stud$.mp. |
(73) case series.mp. |
(74) (cluster-randomi#ed or cluster randomi#ed or randomi#ed).mp. |
(75) quasi-experimental design.mp. |
(76) interrupted time series.mp. |
(77) pilot study.mp. |
(78) program$ evaluation.mp. |
(79) effectiveness.mp. |
(80) evaluation.mp. |
(81) (follow up or follow-up).mp. |
(82) 1 or 2 or 3 or 4 or 5 or 6 |
(83) 7 or 8 or 9 or 10 or 11 or 12 or 13 |
(84) 14 or 15 or 16 or 17 or 18 or 19 or 20 or 21 or 22 or 23 or 24 or 25 or 26 or 27 or 28 or 29 or 30 or 31 or 32 or 33 or 34 or 35 or 36 or 37 or 38 or 39 or 40 or 41 or 42 or 43 or 44 or 45 or 46 or 47 or 48 or 49 or 50 |
(85) 51 or 52 or 53 or 54 or 55 or 56 or 57 or 58 or 59 or 60 or 62 or 64 or 65 or 66 |
(86) 67 or 68 or 69 or 70 or 71 or 72 or 73 or 74 or 75 or 76 or 77 or 78 or 79 or 80 or 81 |
(87) 82 and 83 and 84 and 85 and 86 |
(88) Limit to English |
Studies meeting the inclusion criteria by full-text were classified by setting and country. Data were extracted independently by two researchers. A descriptive analysis of the studies involved extracting information including study design, participants, gender as a percentage of females, mean age (SD), total follow-up, measure of SES (education), and if a theoretical base (data not shown) was used for the intervention design and implementation. Further assessment of the outcomes of each study was reviewed with information extracted including the outcomes measured, description of the study population units, response rate and loss to follow-up, randomisation used, selection process for setting or community of choice, summary of intervention implemented, and lastly the outcome related to BMI. Where information was insufficient regarding baseline data or intervention design for a particular article, additional reference articles were sourced from respective reference lists or via a search in Pubmed by study name. Lastly, some additional estimated calculations were made by the authors for the response rate, lost to follow-up, and gender, based on the information available from the articles.
An analysis of the methodological quality of the studies was then completed using a quality assessment tool [
Finally, comparability was difficult to determine, especially if some but not all baseline characteristics were similar. Available data were assessed when a study included BMI in their baseline description and were deemed noncomparable if there were differences in BMI, even if there were no differences in other characteristics. In addition, we considered the baseline characteristics comparable, if the intervention and control group were matched or selected based on similar characteristics, such as SES.
Data is presented by setting in the following order: whole of community, worksite, and school. Data were not pooled or regrouped based on specific characteristics but are presented and discussed as separate settings. Pooling or regrouping of the data was not possible due to the heterogeneity of the studies.
The literature screening process is presented in Figure
Study identification, screening, and eligibility, guided by PRISMA.
Table
Descriptive characteristics and assessment of setting-based interventions.
Author |
Study design |
Participants | Gender as % of females |
Number of participants, settings, or communities/randomisation units/response rate/baseline/lost to follow-up | Choice of setting/community | Intervention implemented | Changes in BMI as % or mean ( |
---|---|---|---|---|---|---|---|
|
|||||||
Jenum et al. [ |
Quasiexperimental changes in PA, smoking, BMI, BP, lipids, and glucose 3 yrs. (cohort) | (I) Whole of community (30–67 yrs.) |
I: 57.2% |
(I) One district |
(I) District selected as disadvantaged, with a high population of low-income, multiethnic residents |
3-year intervention (same as follow-up) |
Proportion with net increase in BMI (difference of proportion with increase and proportion with decrease) |
|
|||||||
Lupton et al. [ |
Quasiexperimental changes in PA, diet, smoking, BMI, BP, and cholesterol 6 yrs. (cohort) | (I) Whole of community (20–62 yrs.) |
I: 48.9% |
(I) One municipality |
(I) Municipality selected based on high CVD mortality in Finnmark county |
3-year intervention (shorter than follow-up) |
Mean BMI change |
Kumpusalo et al. [ |
Quasiexperimental changes in PA, diet, smoking, alcohol, BMI, BP, and lipids 3 yrs. (cohort + cross-sectional samples) | (I) Whole of community (20–64 yrs.) |
I: 46.0% |
(I) Four villages |
Villages selected due to similar characteristics of rural villages associated with population, age, trades and services |
3-year intervention (same as follow-up) |
Mean BMI before-after |
|
|||||||
Isacsson et al. [ |
Pre- and post-intervention (No control group) changes in smoking, BMI, BP, cholesterol, and glucose 4 yrs. (cohort + cross-sectional samples) | (I) Whole of community (30–64 yrs. and children) | 49.2% |
One municipality |
Municipality selected based on high CVD mortality | 5-year intervention (longer than follow-up) |
Mean BMI for every cross-sectional survey |
Lingfors et al. [ |
Pre- and postintervention (no control group) changes in BMI, BP, and cholesterol 8 yrs. (cohort + cross-sectional samples) | (I) Whole of community (30 and 35 yrs.) | 51.8% |
One county |
County selected based on high CVD mortality | 8-year intervention (same as follow-up) |
Mean BMI before-after for age groups 30 and 35 years |
Weinehall et al. [ |
Quasiexperimental changes in smoking, BMI, BP, and cholesterol 4 yrs. (cohort + cross-sectional samples) | (I) Whole of community (30, 40, 50 and 60 yrs.) |
I: 50.7% |
(I) One municipality |
Municipality selected due to high CVD incidence and mortality | 4-year intervention (same as follow-up) |
Mean BMI for every cross-sectional survey for (I) and (C) groups |
Schuit et al. [ |
Quasiexperimental |
(I) Whole of community (20–59 yrs.) |
I: 49.6% |
(I) One province |
Province selected as a demonstration project and from previous national monitoring studies | 5-year Intervention (same as follow-up) |
Mean BMI change |
|
|||||||
|
|||||||
Engbers et al. [ |
Quasiexperimental, Changes in PA, diet, alcohol, smoking, BMI, BP, and lipids 1 yr. (cohort) | (I) Office workers from a governmental company with BMI > 23 kg/m2 |
I: 37.4% |
(I) One company located in one building (employees with BMI > 23 kg/m2 invited) |
Worksites selected based on comparability of working environments | 1-year Intervention (same as follow-up) |
Mean BMI change |
|
|||||||
Kwak et al. [ |
Quasiexperimental changes in body composition 2 yrs. (cohort) | (I) Blue collar and white collar workers employed by local government, hospital, factories, energy company, and university (<40 yrs.) |
I: 50.7% |
(I) Six worksites |
Worksites matched for SES selected based on size (100 employees +) and staff access to a canteen | 1-year intervention (shorter than follow-up) |
Mean BMI change |
|
|||||||
Hedberg et al. [ |
Quasiexperimental changes in PA, diet, smoking, BMI, BP, lipids and stress 1½ yrs. (cohort) | (I) Professional drivers, |
No females |
(I) Drivers within 50 km from one town (51 drivers invited) |
Participants selected from previous participation in a CVD screening program of professional drivers |
1-year intervention (shorter than follow-up) |
Mean BMI before-after |
|
|||||||
Ask et al. [ |
Quasiexperimental (pilot study) |
(I) 10th grade students (15 yrs.) from a secondary school |
I: 42.3% |
(I) One school, one class |
School selected due to request from teachers concerned about antisocial behaviour and poor attendance | 4-month intervention (same as follow-up) |
Median (range) BMI before and after |
|
|||||||
Ask et al. [ |
Quasiexperimental (pilot study) changes in diet and BMI |
(I) 9th grade students from a secondary school |
NA |
(I) One school |
Schools selected as their syllabus for the 9th grade included lunch preparation in the home economics class, provided 3 times per week | 4-month intervention (same as follow-up) |
Mean BMI before-after |
Bere et al. 2014 [ |
Cluster randomised changes in diet and BMI |
(I) 6th and 7th grade children (10–12 yrs.) from schools from one county |
I: 49% |
(I) Nine schools |
(I) Schools selected from one county participating in the “fruit and vegetables make the marks project” (FVMM) |
1-year intervention (shorter than follow-up) |
Mean BMI (95% CI) |
|
|||||||
Grydeland et al. [ |
Cluster Randomised changes in body composition 20-months (cohort) | (I) 6th grade children (11 yrs.) from schools in the largest towns/ |
I: 50% |
(I) Twelve schools |
Schools selected from large municipalities located in 7 counties from the same region with greater than 40 students in 6th grade | 20-month intervention (same as follow-up) |
Mean BMI change (95% CI) |
Resaland et al. [ |
Quasiexperimental changes in BMI, BP, lipids, and glucose 2 yrs. (cohort) | (I) 4th grade children (9 yrs.) from a school in a municipality |
I: 49.6% |
(I) One school |
Schools selected from municipalities located within the same region, 105 km apart and had a similar SES, similar size, and similar number of children | 2-year intervention (same as follow-up) |
Mean BMI change |
|
|||||||
Bugge et al. [ |
Quasiexperimental |
(I) 1st-3rd grade children (6-7 yrs.) from schools from one local authority (suburb) |
I: 45.6% |
(I) Ten schools |
(I) Schools selected due to an interest by one of the local authorities, in measuring the effect of recently upgraded PA opportunities for young school children |
3-year intervention (shorter than follow-up) |
Mean BMI change |
|
|||||||
Klakk et al. [ |
Quasiexperimental changes in body composition 2 yrs. (cohort) | (I) 2nd–4th grade children (8–13 yrs.) from schools within one municipality |
NA | (I) Six schools |
(I) Schools selected based on an initiative by a community to increase PE lessons in local primary schools for improved health of students |
2-year intervention (same as follow-up) |
Mean BMI before-after |
Puska et al. [ |
Quasiexperimental changes in diet, smoking, BMI, BP, cholesterol, health knowledge, attitude, and emotional problems 2 yrs. (cohort) | (II)d 7th grade students (13 yrs.) from schools from one county |
II: 44.8% |
(II) Two schools |
(II) (CI) The Intervention county (North Karelia) was selected as it was the setting of an established ‘whole of community’ intervention, of which this school-based intervention was a component |
2-year intervention (same as follow-up) |
Mean BMI change |
Magnusson et al. [ |
Cluster Randomised changes in body composition and cardiorespiratory fitness 2 yrs. (cohort) | (I) 2nd grade children (7 yrs.) from schools from the same city |
I: 50.8% |
(I) Three schools |
(I) Schools in this region were selected based on a national concern of a decline in aerobic fitness of children and adolescents |
2-year intervention (same as follow-up) |
Mean BMI before-after |
Elinder et al. [ |
Quasiexperimental changes in PA, diet, BMI, and self-esteem 2 yrs. (cohort) | (I) 2nd, 4th, and 7th grade children and students (6–16 yrs.) from schools in a municipality |
Grade 2: 49.2% |
(I) Nine schools |
(I) Schools located in a middle-class municipality were selected for the study due to a request by representatives from the municipality |
2-year intervention (same as follow-up) |
|
Marcus et al. [ |
Cluster randomised changes in PA, diet, and BMI 4 yrs. (cohort) | (I) Children (6–10 yrs.) from schools in one county area |
49% |
(I) Five schools |
Selected schools had a population of students from families of middle and working class | 4-year intervention (same as follow-up) |
NA |
|
|||||||
Nyberg et al. [ |
Cluster randomised changes in PA, diet, BMI, health behaviours, and parental self-efficacy 1 yr. (cohort) | (I) Children (6 yrs.) and their parents from preschools in a municipality |
I: 47.3% |
(I) Seven preschool classes |
Schools selected from a municipality with low to medium SES due to the higher prevalence of obesity in lower SES communities in Sweden | 6-month intervention (shorter than follow-up) |
NA |
De Henauw et al. [ |
Quasiexperimental changes in diet, body composition, well being, screen time, and sleep 2 yrs. (cohort) | (I) Children (2–9.9 yrs.) from kindergartens and primary schools from one region |
48.8% |
All the schools in the region were invited |
(I) Community selected as one of eight European countries as part of the IDEFICS cross-cultural childhood obesity and prevention study |
2-year intervention (same as follow-up) |
Mean BMI-z score before-after |
|
|||||||
Sollerhed and Ejlertsson 2008 [ |
Quasiexperimental |
(I) Children (6–9 yrs.) from a school from a rural location |
I: 39.7% |
(I) One school |
Schools selected based on similarities of rural location, size, appearance, structure, and SES of the children | 3-year intervention (same as follow-up) |
Mean BMI change |
|
|||||||
Stenevi-Lundgren et al. [ |
Quasiexperimental changes in PA and body composition |
(I) 1st and 2nd grade girls (7–9 yrs.) from a school from a middle-class area in a municipality |
I: 100% |
(I) One school |
(I) School selected that did not have a high level of PA in the curriculum |
1-year intervention (same as follow-up) |
Mean annual BMI change (95% CI) |
Busch et al. [ |
Quasiexperimental |
(I) Students from high schools from suburbs of middle-large cities |
NA | (I) Two schools |
(I) Schools selected to implement the Utrecht Health School (UHS) program |
2-year intervention (same as follow-up) |
School A |
Busch et al. [ |
Pre- and Postintervention historical control group (pilot study for Busch et al.) [ |
(I) 4th grade students (15–16 yrs.) from a secondary school |
I: 47% |
(I) One school |
(I) School selected to implement the Utrecht Health School (UHS) program in 4th graders in 2010 |
3-year intervention (same as follow-up) |
NA |
de Greeff et al. [ |
Cluster randomised changes in BMI and fitness |
(I) 2nd or 3rd grade children (7–8 yrs.) from schools in one region |
I: 55.2% |
(I) Six 2nd grade and six 3rd grade classes |
Schools were selected as they were part of the project “Fit en Vaardig op school,” a randomised trial with the aim to improve academic performance | 22-week intervention (same as follow-up) |
Mean BMI before-after |
|
|||||||
Kocken et al. [ |
Cluster randomised changes in PA, diet, BMI, sedentary behaviour, and behavioural determinants |
(I) 4th–6th grade children (9–11 yrs.) from schools |
I: 52.0% |
(I) Twenty-three schools |
(I) Children aged 9–11 yrs. were selected due to their ability to participate in the study questionnaires and the restricted budget for the study |
2-year intervention (same as follow-up) |
Mean BMI z-score before-after |
de Meij et al. [ |
Quasiexperimental |
(I) 3rd–8th grade children (6–12 yrs.) from schools in 2 city districts |
I: 51.2% |
(I) Nine schools |
Schools were selected from socially and economic deprived areas which met the criteria of a certified PE teacher, high enrolment of students with a low SES, and access by school to a gymnasium | 2-year intervention (same as follow-up) |
Mean BMI before-after |
|
|||||||
Jansen et al. [ |
Cluster randomised changes in BMI and fitness 2 yrs. (cohort) | (I) 3rd–8th grade children (6–12 yrs.) from schools from an inner-city area |
Grades 3–5 |
(I) Ten schools |
Primary schools were selected as located in deprived inner-city neighbourhoods, with low SES, and a high proportion of immigrant children | 2-year intervention (same as follow-up) |
Mean BMI before-after |
Singh et al. [ |
Cluster randomised changes in PA, diet and body composition |
(I) 1st grade students (12–14 yrs.) from schools |
I: 53.2% |
(I) Ten schools |
NA | 8-month intervention (shorter than follow-up) |
Mean BMI before-after |
Naul et al. [ |
Quasiexperimental changes in BMI and fitness 1 yr. (cohort) | (I) Children (6–10 yrs.) from Dutch schools |
Gender: NA |
(I) Thirteen schools |
Schools were selected from a sample of 39 primary schools that had implemented an intervention in their school | 1st year (4-year intervention) |
Mean BMI before-after |
SD: standard deviation; SES: socioeconomic status; PA: physical activity; BMI: body mass index; BP: blood pressure; yrs.: years; yr.: year; I: intervention; C: control; n: number; NA: not available; CVD: cardiovascular disease; NS: non-significant; NGO: non-governmental organizations; MONICA: multinational monitoring of trends and determinants in Cardiovascular disease; PE: physical education; II: intense direct intervention; CI: county-wide intervention; IDEFICS: the identification and prevention of dietary- and lifestyle-induced health Effects in children and infants approach. aAdditional references (e.g., design article) for further information on baseline data and design. bDoes not apply for mean age when all children are at the same grade (same age). cMean years of education or SES for schools where we refer to the years of education of the parents and not of the children or adolescents. dHigh refers to high education as defined as university education [
Summary of key characteristics of setting-based interventions.
Setting | Study type | Total follow-up | Gender as percentage (%) of females | Outcome measures | Intervention components | Theory based | BMI change |
---|---|---|---|---|---|---|---|
Community-based, |
Pre-post studies (no control), |
3–8 years |
46.0% to 57.2%. Female | CVD risk factors, |
Multicomponent, |
Explicitly theory-based, |
Positive, |
|
|||||||
Worksite-based, |
Quasiexperimental, |
1–2 years |
37.4% to 50.7% female (2/3) |
CVD risk factors, |
Multicomponent, |
Theory-based and built upon a multilevel approach, |
No effect, |
|
|||||||
School-based, |
Cluster randomised, |
4 months-8 years |
39.7% to 60.1% female (22/23) |
Obesity, |
Multicomponent, |
Explicitly theory-based using a multilevel approach; like intervention mapping and whole school participation, n = 10 | Negative, |
Weight prevention was a secondary outcome in five out of the 33 studies: changes in dietary habits [
Among the whole of community interventions, two were pre-post studies without a control group [
All whole of community interventions focused on risk factors for cardiovascular disease (CVD) and involved individual and environmental components in the interventions. Five studies were multicomponent studies (three components and above) [
Changes in BMI for the interventions are presented in Table
All three worksite-based interventions were quasiexperimental and measured BMI change for adults. The percentage of female participants in two of the studies was 37.4% to 50.7%, whilst one intervention included 100% male drivers [
Two of the interventions had an individual component [
Nine of the school-based interventions were cluster randomised [
Fourteen school-based interventions were multicomponent studies [
Ten [
Finally, two studies showed a decrease in BMI in the I group [
Table
Quality assessment of setting-based interventions.
Study | Suitability of study design | Number of criteria met | Representativenessb | Randomisation | Comparabilityc | Credibility of data collection instruments | Attrition rate | Attributability to interventiond |
---|---|---|---|---|---|---|---|---|
|
||||||||
Jenum et al. [ |
Category A | 1 | NO | NO | NO | YES | NO | NO |
Jenum et al. [ |
||||||||
Lupton et al. [ |
Category A | 3 | NA | NO | YES | YES | NO | YES |
Kumpusalo et al. [ |
Category A | 3 | YES | NO | NO | YES | YES | NA |
Kumpusalo et al. [ |
||||||||
Isacsson et al. [ |
Category B | 3 | YES | E | — | YES | YES | — |
Lingfors et al. [ |
Category B | 2 | NO | — | — | YES | YES | — |
Weinehall et al. [ |
Category A/Category B | 2 | YES | NO | NA | YES | NO | NA |
Brannstrom et al. [ |
||||||||
Schuit et al. [ |
Category A | 4 | YES | NO | YES | YES | YES | NA |
|
||||||||
Engbers et al. [ |
Category A | 4 | NO | NO | YES | YES | YES | YES |
Kwak et al. [ |
Category A | 3 | NO | NO | YES | YES | YES | NA |
Hedberg et al. [ |
Category A | 4 | YES | NO | YES | YES | YES | YES |
|
||||||||
Ask et al. [ |
Category A | 3 | NO (pilot study) | YES (out of two units) | YES | YES | NA | NA |
Ask et al. [ |
Category A | 4 | NO | YES (out of three units) | YES | YES | YES | NA |
Bere et al. [ |
Category A | 3 | YES | YES | NA | YES | NO | NA |
Grydeland et al. [ |
Category A | 4 | NO | YES | YES | YES | YES | NA |
Resaland et al. [ |
Category A | 2 | NO | NO | YES | YES | NO | NA |
Bugge et al. [ |
Category A | 2 | NO | NO | YES | YES | NO | NA |
Klakk et al. [ |
Category A | 3 | NO | NO | YES | YES | YES | NA |
Puska et al. [ |
Category A | 2 | NO | NO | NA | YES | YES | NA |
Magnusson et al. [ |
Category A | 3 | NO | YES | YES | YES | NO | NA |
Elinder et al. [ |
Category A | 2 | NO | NO | NA | YES | YES | NA |
Elinder et al. [ |
||||||||
Marcus et al. [ |
Category A | 2 | NO | YES | NA | YES | NO | NA |
Nyberg et al. [ |
Category A | 4 | NO | YES | YES | YES | YES | NA |
De Henauw et al. [ |
Category A | 2 | NA | NO | NA | YES | YES | NA |
Hense et al. [ |
||||||||
Ahrens et al. [ |
||||||||
Sollerhed and Ejlertsson [ |
Category A | 3 | NO | NO | YES | YES | YES | NA |
Stenevi-Lundgren et al. [ |
Category A | 3 | NO | NO | YES | YES | YES | NA |
Busch et al. [ |
Category A | 2 | NO | NO | YES | YES | NO | NA |
Busch et al. [ |
Category C | 2 | NO (pilot study) | NO | NA | YES | NA | YES |
de Greeff et al. [ |
Category A | 3 | NO | YES | YES | YES | NA | NA |
Kocken et al. [ |
Category A | 3 | NO | YES | YES | YES | NO | NA |
de Meij et al. [ |
Category A | 3 | NO | NO | YES | YES | YES | NO |
Jansen et al. [ |
Category A | 4 | NO | YES | YES | YES | YES | NA |
Singh et al. [ |
Category A | 3 | NO | YES | NO | YES | YES | NA |
Naul et al. [ |
Category A | 2 | NO | NO | NO | YES | YES | NA |
NA: not available. aAdditional references (e.g., design article) for further information on baseline data and design. bFor the studies on schools, representativeness referred to the schools as units and not to the children/students participating. cBaseline characteristics description or matching, if baseline BMI was not mentioned we considered Na. dBased on what is discussed or reported in the article, we did not consider NO in cases where I and C were in proximity, unless a possibility of contamination is discussed. eDoes not apply, no control group.
To our knowledge, this is the first systematic review focusing on setting-based interventions on obesity prevention in Nordic countries and the Netherlands, which includes all age groups and types of settings. Results for BMI change showed no consistent direction for whole of community interventions (2/7 positive, 2/7 negative, and 3/7 no effect), no effect for worksite-based interventions (3/3), and no effect for many of the school-based interventions (1/23 negative, 3/23 positive, 15/23 no effect, 1/23 BMI significant increase for control group only, and 3/23 no data available). A quality appraisal showed that many studies poorly fulfilled criteria related to representativeness (25/33) and randomisation (20/33) or had no available information on attributability of the intervention (25/33). However, for comparability of baseline data (20/33) and attrition rates (20/33), evaluation was better.
Theoretical constructs are very important in research in general, for illustrating the associations between variables, the change process, and so on thus helping understand the interventions’ mechanisms [
Participatory interventions are also very important because they engage with people whose life-world and meaningful actions are under study. The target group should play a key role in planning, implementing, and adjusting the interventions. When constructing an intervention with a participatory dimension, it entails the mobilisation of people, feeling of empowerment, and self-efficacy. In the long run, this creates a better opportunity for sustainable solutions. The participatory research methods are geared towards planning and conducting the research process consequently, which means that the aim of the inquiry and the research questions develops out of the convergence of two perspectives: of science and of practice [
This systematic review illustrates that the studies in general used theory more as a background understanding, than for guiding the interventions, or for the discussion and interpretation of the results, and implications for further research. Several studies (18/33) did not use theory explicitly [
The only available review on whole of community interventions on obesity [
Unfortunately, the vast majority of reviews on obesity and related risk factors are on children. We found only one systematic review [
Methodological issues can also reduce the strength of these studies and result in poor outcomes. One major issue is the use of a control group; without one, it is not possible to judge whether the changes are due to the project or due to other changes in that population. For the whole of community interventions, five were quasiexperimental. In addition, two of those used a cohort design, whereas the other three [
We were only able to detect three studies, where most of those excluded were studies that used individual counselling. The included studies focused largely on CVD risk factors, similarly to the whole of community interventions. It is very difficult to draw any conclusions from this limited number of studies. However, the results identify a clear need for more obesity prevention studies with an environmental component, implemented in the worksite setting. There were no changes in BMI observed in any of these interventions (3/3), and this might be partially due to relatively short follow-ups (one to two years) and no multicomponent studies, which usually reflect a serious effort for change in the environment. For example, in only one of the studies [
A review by Maes et al. [
Most of the studies showed no effect for BMI (15/23). A meta-analysis by Waters [
In some of the studies [
As for methodological issues, all school-based interventions were cohorts and had a control group but only nine were randomised studies. It is somehow reassuring that 15 studies showed comparability for baseline characteristics between I and C but that does not mean that studies should not use randomisation as a regular process. However, as mentioned previously, the process of randomisation is sometimes inhibited, as in one case where the schools participated only if they were considered as I schools [
Some major limitations of the articles included in our review are (1) very low reporting or discussion on attributability and SES, which is known to be associated with the effectiveness of a health promotion intervention, (2) unclear describing of results in some studies and some missing tests (comparison of changes in BMI between I and C which affected the way results are presented and possibly interpreted), and (3) reasons for choosing a region, municipality, worksite, or school such as practical (easy, already part of a project), with a very narrow scope in school-based interventions or initiation by local authorities which limit representativeness. Especially in the case of school-based interventions, representativeness was largely not fulfilled. However, in whole of community interventions, five were considered representative, showing most likely a more careful design view ‘heaviness’ of these projects.
All of the whole community studies included awareness campaigns but few components such as infrastructure and policies. For the schools, 19 studies made changes to the curriculum; however, fewer interventions incorporated: improved infrastructure, policies, and school-wide or community level strategies. These results show a seeming lack in creating a healthier environment through broader and vaster changes, which is considered a major component of a health promotion study. In addition, very few studies implemented or at least described a capacity building process. Across the included studies, there was “a light way” of using theory and theoretical frameworks; these were mostly only referred to, without describing if and how they were used to guide the studies, select tools or interpret the findings.
One limitation of our study was not being able to organise the studies by length of follow-up or type of intervention components. This was due to the heterogeneity of studies. However, if we had decided to restrict our studies based on follow-up time, we would have to exclude a significant amount of studies that provide valuable information. In addition, grouping based on follow-up would have created many subgroup categories especially for the community and worksite-based interventions.
This review has provided an overview of obesity prevention interventions in seven whole of community, three worksite and 23 school-based interventions, implemented in communities of Nordic countries and the Netherlands, where BMI was reported as an outcome. This review was unable to demonstrate associations with BMI outcomes among these settings. However, it is very difficult to distinguish whether these results are due to the heterogeneity of the study designs, or due to poor quality in terms of design or implementation. In addition, initiation of a project especially in the school setting was often motivated by a very narrow scope related to the schools’ needs, and not by an effort to test comprehensive strategies for obesity prevention.
There is a need to prioritise interventions that include study designs of high quality, the use of theoretical constructs to guide the studies, and a participatory approach for optimal implementation and evaluation of obesity outcomes. Use of theory at all levels of an intervention as well as promoting participatory approaches have been acknowledged to improve the effectiveness of different types of interventions, including obesity. Some suggested criteria for ‘good’ theory in the area of behavioural change are: clarity of theoretical concepts, being explanatory, describing causality, testability, and so on. [
However, the future development of a published guideline on the complete, precise reporting of theory on different levels (process, implementation, and evaluation), even if possible in the obesity field, can help improve interventions. There are no explicit guidelines for setting-based interventions compared to clinical trials and interventions on diet and PA that focus on the individual. This leads to studies with no standard of quality based on defined criteria.
Guidelines should be created with an emphasis of criteria that can affect the study quality such as the ones we used in our review. An example of such criteria is a minimum period of follow-up based on evidence that shows how long it needs for obesity interventions to show a change in BMI, not factors such as political agendas. Another example is the consistent use of representative samples and randomisation as much as possible, instead of convenient and very small samples, especially for schools and worksites. Overall, it seems that presently there is not a serious commitment in preventing obesity through setting-based interventions and in particular in worksite interventions.
Commitment to further, more advanced research of settings-based interventions in these countries remains of vital importance, to secure and direct future investment for obesity prevention interventions.
The authors declare that they have no conflicts of interest.
This work was supported by Esbjerg Municipality, Denmark.