1. Key findings and recommendations

Overweight, which includes obesity,1 is a key public health issue facing countries across the world. Advances in technology, globalisation, urbanisation and the expansion of food retail have changed the way people eat. Consequently, diets today are increasingly comprised of foods associated with weight gain (e.g. added fats and sugar) at the expense of those with healthy dietary elements (e.g. fruit and vegetables). Concurrently, people today have fewer reasons to be physically active with the rising use of less active modes of transport and sedentary jobs. Given changes in body weight are primarily due to imbalances between energy intake from diet and energy output through physical activity, it is not surprising that rates of overweight, which includes obesity, are high: as of 2019, 64% of men and 56% of women in the OECD live with overweight (OECD, 2019[1]). For further details on overweight risk factors and trends, see Chapter 2.

Overweight places both a health and economic toll on countries. Adults who live with overweight are at greater risk of developing certain non-communicable diseases (NCDs) such as type 2 diabetes and several cancers. High NCD rates, in turn, lead to a greater number of premature deaths: over the period 2020-50, overweight is estimated to reduce average life expectancy in the OECD by 2.7 years, with this figure increasing to 3.2 years when considering healthy life years (OECD, 2019[2]). Given people living with overweight are more likely have one or multiple NCDs, demand and costs for health care are also likely to be higher among this group of people. For example, OECD estimates the cost of treating overweight and its related conditions at USD PPP (purchasing power parity) 209 per year, per person, which translates into 8.4% of total health expenditure.

OECD countries have responded to the obesity epidemic with a mixture of policy interventions. Across the OECD, over 90% of countries have implemented a national action plan to address unhealthy diets and physical inactivity (WHO, 2019[3]; WHO, 2019[4]). Action plans at the national level complement and align with those developed by the international community such as WHO’s Global Action Plan on Physical Activity, which aims to reduce the global prevalence of physical inactivity by 15% by 2030. Action plans typically include a range of interventions such as those that aim to widen the availability of healthy choices (see Chapter 2 for further details).

To assist policy makers address rising rates of overweight, this report examines a selection of strategically important prevention interventions implemented within OECD and EU27 countries. Given the significant health and economic impact of overweight, policy makers have implemented a range of interventions targeting key risk factors – i.e. unhealthy diets and physical inactivity. To assist policy makers select and transfer interventions considered “best practice”, this report details key findings and aligning policy recommendations following a review of 12 interventions submitted by OECD policy makers or selected from the EU’s Public Health Best Practice Portal (see Table 1.1 for a high-level overview of each intervention) (European Commission, 2021[5]). Due to this process, selected interventions typically target individual lifestyle behaviours. In reality, tackling overweight requires a multifaceted approach, including policies to change economic, social and physical environments. Further, the chosen interventions do not cover all overweight risk factors, but instead focus on the two predominant risk factors – diet and physical activity. Despite these limitations, selected interventions represent some of those that are of key strategic interest, therefore, countries are considering transferring them to their local context.

Each intervention was assessed against a standard methodology – namely an assessment of the intervention against five best practice criteria including effectiveness, efficiency and equity, as well as an assessment of the intervention’s transferability potential. For further methodological details, see Annex A.

Selected interventions evaluated using OECD’s microsimulation model estimate large declines in disease incidence. OECD’s Strategic Public Health Planning for non-communicable diseases (SPHeP-NCD) model estimated changes in disease incidence for five of the twelve interventions following an improvement in overweight risk factors: the Multimodal Training Intervention, Nutri-Score, the Combined Lifestyle Intervention, Young People at a Healthy Weight (JOGG) and Physical Activity on Prescription (see Table 1.1 for a high-level overview of interventions). Results from the model estimate that if all interventions were to be scaled-up simultaneously by 2050, 18.4 and 5.9 million cases of disease would be avoided across analysed OECD and EU27 countries, respectively. The majority of these disease cases are either musculoskeletal disorders (MSDs) or cardiovascular diseases (CVDs) (Figure 1.1).2 To put these figures into perspective, in the EU each year there are approximately CVD 6 million cases (Institute for Health Metrics and Evaluation, 2019[6]). Nutri-Score – a healthy food labelling scheme first established in France – is estimated to have the greatest impact, which is largely due its wide reach (covering everyone aged 1 year and over). Conversely, the Multimodal Training Intervention – a healthy living programme in Iceland – despite having a large health impact at the individual level, would have a relatively low impact across the population as it targets those aged 65+. A reduction in disease incidence has a subsequent positive impact on life years (LYs) and disability adjusted life years (DALYs) gained as summarised in Figure 1.2.

Interventions result in both health expenditure savings and improvements in workforce productivity. The impact of the same five interventions on efficiency was also measured using OECD’s SPHeP-NCD model. Results from the analysis indicate savings ranging from 0.02% (Combined Lifestyle Intervention) to 0.06% (Young People at Healthy Weight) of total health expenditure per year over the period 2021-50. On a per capita basis, this translates into annual savings of EUR 0.41 to EUR 1.28 across OECD countries (see Figure 1.3). Interventions accrue additional savings as a result of improvements to workforce productivity – i.e. a reduction in absenteeism, presenteeism and early retirement as well as a higher employment rate. Gains in workforce productivity are also shown in Figure 1.3, which covers all interventions except the Multimodal Training Intervention given it targets those aged 65 and over and who are presumed to have already left the workforce.

Many interventions are cost-effective, and for several countries, even cost-saving. For each of the selected case studies, the cost per DALY gained (over the period 2021-50) revealed interventions were in many instances not only cost-effective but also cost-saving (see Figure 1.4).3 Nutri-Score, in particular, is viewed as a good financial investment as it is cost-saving across all OECD and EU27 countries. More intensive interventions such as the Multimodal Training Intervention, which offers participants access to fitness classes under the supervision of a qualified personal trainer, are more expensive and therefore, although highly effective, may not being cost-effective against standard thresholds. It is important to note that the Multimodal Training Intervention and the Combined Lifestyle Intervention (CLI) have a relatively low extent of coverage, indicating there is room to improve economies of scale and therefore possibly reduce the cost per targeted individual. For example, previous analyses by OECD (2019[2]) found physical activity prescription programmes similar to CLI are cost-effective when scaled-up to the whole population. In addition, the Multimodal Training Intervention targets older people, therefore, compared to interventions that target young people or the general population, there is limited time to see an improvement in health outcomes.

Overweight is a complex health issue for which there is no “silver bullet” solution. Changes in modifiable overweight risk factors such as diet, physical activity, sleep and stress are complex and multifaceted. Therefore, it is not surprising that individual interventions, alone, are limited in their ability to markedly reverse trends in overweight and obesity. This aligns with findings among selected interventions, which often recorded small changes to key health outcomes. For instance, the StopDia Pilot – a diabetes prevention programme targeting Finland’s Somali population – recorded a statistically significant improvement in vegetable consumption and non-significant changes among remaining indicators (e.g. step count). Similarly, another diabetes prevention programme in Europe (DE-PLAN) led to a statistically significant drop in consumption of sugars and sweets but no significant change in fruit and vegetable consumption or physical activity levels. One notable exception was the Multimodal Training Intervention, a healthy living programme in Iceland for the elderly, which reported statistically significant, favourable changes across all outcome measures (see Box 1.1).

Countries must address the obesity epidemic using a mixture of interventions targeting both the individual and society. Policy packages comprised of several interventions can address the multiple causes of overweight. This report outlines several interventions policy makers can draw upon to create a comprehensive policy package targeting overweight. Selected interventions cover a range of settings (e.g. schools, primary care, and community facilities) and populations (e.g. younger children all the way up to the older population). However, due to the selection process based on submissions by countries (see Annex A), the majority are “downstream” interventions that focus on changing the behaviour of individuals. “Upstream” structural interventions that aim to change the environment in which people live should complement downstream ones (see Box 1.2 for information on how Australia incorporates both down and upstream policies). For example, food reformulation, food procurement, restrictions on unhealthy food purchases, changes in the urban environment, and increases in green spaces and bike/walking paths (these types of interventions will be reviewed in future best practice reports). Structural interventions are important for deconstructing the obesogenic environment by “making the healthy choice the easy choice”. Strategies to tackle overweight should also cover lesser-known risk factors such as sleep and stress.

Interventions that target children are of particular importance when designing policy packages to tackle overweight. Tackling overweight in children is of critical importance given its link to obesity in adulthood, which is associated with more complex health issues. In addition, overweight is connected with high levels of stigma among children leading to poor mental health and well-being (see Box 1.3 for further details). Despite the well-established link between overweight in childhood and poor physical and mental health, some interventions targeting children may be overlooked given the lack of evidence on their long-term impact. For example, compared to interventions targeting adults, those based in schools may look unfavourable given diseases associated with overweight (e.g. cardiovascular diseases) do not usually appear until middle adulthood, and are therefore not captured within usual evaluation timelines (OECD, 2022[10]). This is supported by previous OECD analyses which showed school-based overweight interventions are effective once a sufficient number of children exposed to the intervention are adults who are susceptible to developing chronic diseases (OECD, 2019[2]). The importance of evaluating prevention interventions targeting children and teenagers is highlighted in Switzerland, where it is a top priority within the Federal Office of Public Health.

Policy packages covering individual and structural overweight prevention interventions can have a greater than additive effect on health outcomes and be cost saving. As outlined above, policy packages are necessary for addressing the multiple causes of overweight and for ensuring the whole population is reached. Policy packages are also attractive given their potential to have a more than additive effect on health outcomes. As an example, interventions to boost physical activity, such as through lifestyle programmes, will be more effective among people living in environments that promote exercise, such as those with green spaces and walking paths. Similarly, interventions to improve health literacy regarding nutrition will be more effective if people have better access to healthy food that is affordable.

Only two of the twelve selected interventions targeted a disadvantaged group in an effort to reduce health inequalities – the StopDia Pilot and SI!. The StopDia Pilot is an adaption of the nationwide Finnish diabetes prevention programme, StopDia. Specifically, StopDia was adapted to suit the needs of Finland’s Somali population who are at greater risk of developing diabetes. For example, participants were recruited from their local mosque and group education sessions were run by a health professional with a Somali background. Regarding SI! – a school-based obesity prevention intervention – the process for recruiting schools ensured children with an immigrant background and/or in a low-income area were included.

In addition to the StopDia Pilot, four interventions reported outcomes specific to a disadvantaged group, which found mixed results:

  • StopDia Pilot: initial evidence from a before-and-after evaluation of the StopDia Pilot indicate the intervention achieved small improvements in lifestyle-related diabetes risk factors such as increased vegetable consumption and physical activity, as well as weight loss (Hussein et al., 2020[12]).

  • Young People at a Healthy Weight (JOGG): a review of JOGG, a community-based intervention for those aged 0-19, found the intervention had a greater impact on reducing overweight prevalence in low-SES municipalities compared to middle- to high-SES municipalities. Further, the results were only significant for low-SES municipalities (Kobes, Kretschmer and Timmerman, 2021[13]).

  • Nutri-Score: a study of Nutri-Score, a healthy food labelling scheme, found people with a lower education level were more likely than higher educated people to change purchasing behaviours (Sarda, Ducrot and Serry, 2020[14]). The same study, however, found Nutri-Score was more likely to change the behaviour of middle-income people relative to those on low-incomes.

  • ToyBox: an evaluation of ToyBox, a kindergarten based overweight prevention intervention, found it had a greater impact on reducing sedentary behaviour among children attending kindergartens in high-SES areas (De Craemer et al., 2014[15]).

  • SI!: a randomised control trial (RCT) of SI!, another kindergarten based overweight prevention intervention, found larger observed effects among children whose parents had at least a high school education and a relatively high income – specifically, in terms of changes in knowledge, attitude and habits in relation to diet and physical activity (Peñalvo et al., 2015[16]).

Literature reviews of similar interventions were the basis for assessing equity among those that neither targeted nor reported outcomes for disadvantaged population groups. Findings are summarised in Box 1.4.

The limited impact of selected interventions on health equity aligns with the broader literature. For example, Brown and colleagues’ (2019[22]) systematic review of overweight prevention interventions for children found studies “rarely” reported on outcomes by factors that affect equity (e.g. by socio-economic or migrant status). Further, for studies that did report by different population groups, results were mixed and often found more favourable outcomes among privileged populations.

Policy makers should prioritise and support overweight interventions that promote healthy equity. Specifically, interventions that target disadvantaged population groups or have processes in places to ensure the needs of these groups are addressed, for example by:

  • Adapting the intervention to the needs of the disadvantaged, employing a diversified recruitment and communication strategy, as well as stratifying evaluation indicators by different population groups (see Box 1.5 for further details).

  • Making funding conditional on proving how the intervention promotes health equity and/or prioritise scaling-up/transfer efforts for interventions with a proven impact on reducing health inequalities.

  • Providing additional financial resources given the difficulties in accessing, engaging and retaining disadvantaged population groups in public health interventions. For example, extra funding may be necessary to recruit a sufficiently large number of participants, which is important for rigorous evaluations (Bonevski et al., 2014[23]). Similarly, additional funding may be necessary to ensure participants with a low SES have equal access to interventions, in particular among those that require participants to pay a proportion of fees out-of-pocket (such as the Multimodal Training Interventions and Physical Activity on Prescription).

  • Improving levels of health literacy (HL), which refers to an individual’s knowledge, motivation and skills to access, understand, evaluate and apply health information (Stormacq, Wosinski and Van den Broucke, 2016[24]). Levels of HL are low in the population (HLS‐EU Consortium, 2012[25]; Moreira, 2018[26]), in particular among disadvantaged population groups. For example, a nation-wide study of HL in Denmark found immigrants and individuals with a basic education and below average income had lower levels of HL (Svendsen et al., 2020[27]). Higher levels of HL among disadvantaged groups will ultimately improve population health and reduce inequalities. See Box 1.6 for an overview of policy options to boost HL rates.

Uptake and retention issues limit the effectiveness of overweight prevention interventions. Changing people’s behaviour is complex, particularly in relation to behaviours that affect rates of overweight given they are shaped by cultural, socio-economic and environmental factors (Rogers et al., 2016[32]). Therefore, it is not surprising that weight loss interventions suffer from recruitment and retention issues (Lam, Partridge and Allman-Farinelli, 2015[33]), including interventions in this report. For example, the Combined Lifestyle Intervention in the Netherlands, which offers participants advice on diet and physical activity, has a GP referral rate of 1.03% (it is important to note that this intervention is in its infancy). Further, only half of all people prescribed physical activity as part of Sweden’s Physical Activity on Prescription intervention followed-up after six months.

There are various reasons explaining low rates of uptake and retention. These include, but are not limited to: issues with making initial contact, particularly for certain groups such as ethnic minorities, a lack of interest and time among eligible participants, poor intervention design, and limited confidence in the intervention (Lam, Partridge and Allman-Farinelli, 2015[33]). Failing to improve uptake and retention ultimately has a negative impact on an intervention’s long-term effectiveness.

To improve uptake and retention in overweight prevention interventions, policy makers should use a multi-pronged evidence-based approach. Several strategies are available to policy makers to increase uptake and retention in overweight prevention interventions, including those outlined in Box 1.7.

Several countries transferred selected interventions to their local setting. Over half of all selected interventions have been transferred from their original “owner” country to another “target” country (Table 1.2). The majority of transfers took place among European countries. Of these interventions, only two reported changes in outcomes in the target country, which is largely due to the infancy of several transfer projects, many of which were delayed due to COVID-19. One further intervention – StopDia, a diabetes prevention intervention in Finland – was adapted and transferred to the country’s Somali population. The remaining four interventions exist only in the owner country.

Transferring interventions is a complex task that requires an in-depth understanding of contextual factors. Public health interventions, such as those targeting overweight risk factors, are complex given they involve several interacting components and multiple stakeholders in areas such as health, education, community and environment. They also target heterogeneous populations and have outcomes influenced by various direct and indirect factors (Craig et al., 2008[37]; Norris et al., 2019[38]). Transferring validated interventions is therefore complex as it requires an in-depth understanding of the owner and target setting. This information is often missing leading to a “significant gap between research, practice and transfer” (Barnfield, Savolainen and Lounamaa, 2020[39]). For example, transferring the kindergarten based healthy living intervention, ToyBox, to Malta was “much harder to implement in practice than it look[ed] on paper” for various reasons including a resistance from teachers to “excessively regulate” the school environment as well as an unwillingness among teachers and parents “to act as role models” (Stegeman et al., 2020[40])

Policy makers are providing increasing support to assist the spread of best practice interventions. Policy makers are eager to transfer interventions supported by a strong evidence base. Given the complexity of transferring an intervention, it is increasingly common for policy makers to implement multi-year projects designed to assist the transfer process. For example, as part of the Joint Action (JA) CHRODIS-PLUS (a European JA on Chronic Diseases), the following interventions were transferred to other European countries over a period of three years (2017-20): the Multimodal Training Intervention, ToyBox and Young People at a Healthy Weight (JOGG). Further details on JA CHRODIS-PLUS and other European JAs and projects related to intervention transfers are in Box 1.8. In general, these JAs and projects promote extensive mapping of contextual factors as well as building close ties between individuals responsible for implementation in the owner and target setting.

OECD’s transferability analysis revealed several good transfer candidate countries for selected interventions. OECD developed a methodology to cluster countries based on their potential to transfer selected interventions to their own countries. High-level methodological details are in Annex A, with further details available in an upcoming Health Working Paper. The points below, as well as Box 1.9, summarise key findings from an analysis of transferability results for all 12 interventions:

  • Several countries have population, sector specific, political and economic arrangements in place that are likely to increase the transferability potential of selected interventions including Austria, Finland, Belgium, Germany, the United Kingdom and Ireland. Details on good transfer candidate countries according to the type of intervention are provided in Table 1.3, which covers school-based, primary care based and nutrition labelling interventions.

  • Countries such as Hungary and Greece should consider undertaking further analysis to ensure interventions align with overarching political priorities, which is a key transfer facilitator. For example, these countries do not have a national plan to address unhealthy diets, which is a key overweight risk factor.

  • Prior to transferral, several countries should ensure whether selected interventions are affordable in the long term, in particular, for interventions that require participants to pay out-of-pocket (i.e. Iceland’s Multimodal Training Intervention and Sweden’s Physical Activity on Prescription).

It is important to note that there are limitations with this analysis, most importantly:

  • It should not be assumed that selected interventions will fail in countries where it is recommended that the political and/or economic feasibility be ensured. Instead, the results indicate areas these countries should pay particular attention to, but are not necessarily pre-requisites for transferral.

  • The analysis relied on publically available data that covered a large number of OECD and EU27 countries. Therefore, the data is high level and does not capture all relevant indicators for assessing transferability. Further, the data covers information at the national level, and therefore does not take into account regional differences.

Policy makers can help spread best practice interventions targeting overweight by dedicating resources to the transfer and/or scaling-up process. Given the effort needed to transfer an intervention, policy makers should provide dedicated support to this process. In Europe, this is increasingly common with the European Commission funding multi-year projects dedicated to transferring one or multiple public health interventions to several countries (see Box 1.8 for example projects). Projects that support the transfer process should ultimately depend on factors such as the size, significance and complexity of the intervention, as well as the number of countries adopting the intervention. However, for any transfer project, it is important to promote the following transfer “facilitators”:

  • Close ties between implementers in the owner and target setting. A review of health promotion and disease prevention intervention transfers as part of JA CHRODIS-PLUS found building a “strong relationship between the good practice owner and implementer” was a key transfer facilitator (Stegeman et al., 2020[40]). For example, by organising visits to the owner setting to understand the “ins and outs” of the intervention and meeting with stakeholders face-to-face.

  • An understanding of the context in the owner and target setting, and how the two differ. The owner and target setting will differ, in particular for cross-country transfers – e.g. differences in cultural diversity, regulations, and workforce skills. It is important to understand these differences at the outset and adapt the intervention accordingly. OECD’s Transferability Framework (see Annex A) provides guidance on what types of contextual factors to consider when undertaking this assessment. Further information is in OECD’s Guidebook on Best Practices in Public Health (OECD, 2022[10]), including publically available indicators and databases to assess differences in contexts. It is unlikely publically available data can fully describe the two contexts, which reinforces the importance of establishing close ties between the owner and target setting to fill in any knowledge gaps.

  • Practical materials and guides that assist transfers across multiple settings. Such information will help spread the intervention to multiple settings in an efficient manner. For example, as part of WholEUGrain – a project to transfer the Danish Whole Grain Partnership to several European countries – administrators of the Partnership developed a systematic implementation guide (i.e. the “Toolbox”). See Box 1.10 for further details and for other publically available transfer material.

  • Provide evidence supporting the impact of the intervention in a different setting. Securing buy in from policy makers and stakeholders is necessary when transferring best practice interventions to other countries. One way to secure buy in is to show evidence of the intervention’s estimated impact in the target setting. Such an analysis was carried out for a selection of interventions in this report using OECD’s SPHeP-NCD model (see Box 1.11). Where such information is not available, it is possible to draw upon evidence from previous transfers to similar countries.

Several selected interventions employed gold standard evaluation designs, which are not commonplace in public health. In various fields, randomised control trials (RCTs) are the gold standard in evaluation given their potential to reduce many sources of bias (Deconinck et al., 2021[43]). RCTs, however, are not always appropriate when evaluating public health interventions such as those targeting overweight risk factors. For example, it may not be ethical or possible to exclude certain groups from accessing an intervention, further, given the high cost associated with RCTs, they are not always affordable. For these reasons, overweight prevention interventions are frequently evaluated using other study designs such as observational studies (Barnish and Turner, 2017[44]). Among selected interventions, 55% relied on findings from prospective or retrospective cohort studies (observational studies), while the remaining 45% employed a RCT.

Other factors used to assess the quality of evidence show selected interventions performed well in several areas. Evaluations that use the same study design aren’t necessarily of the same quality. For this reason, the quality of evidence supporting selected interventions was assessed against the Quality Assessment Tool for Quantitative Studies (Effective Public Health Practice Project, 1998[45]). This tool evaluates the internal validity of studies using six criteria: selection bias; study design; controlling for confounders; blinding; data collection methods; and withdrawals and dropouts. For each criterion, a study is awarded either a “strong”, “moderate” or “weak” score. Results across the 12 interventions are summarised in Figure 1.5, which show positive results in several areas. In particular, the majority of studies used strong data collection methods to measure outcomes and recorded low levels of withdrawal and dropout, thereby reducing bias. Conversely, studies infrequently controlled for all confounding factors or blinded participants and researchers. This is not surprising given overweight is a complex issue influenced by many factors for which there is not always readily available data (e.g. socio-economic status), further, participants must often be made aware of the intervention in order to participate.

Despite the use of relatively strong evaluation methods, there is room to improve the quality of evidence base supporting the effectiveness and efficiency of overweight prevention interventions, as outlined below. Ultimately, a strong evidence base helps policy makers make better decisions on which interventions to support.

Incentives to encourage rigorous evaluations will improve the quality of evidence supporting overweight prevention interventions. Types of incentives may include:

  • Requiring applicants to submit an evaluation study when applying for funding. At a minimum, the evaluation study should include a logic model, proposed evaluation indicators, chosen study design and data collection methods. Developing an evaluation study is an important first step for any new intervention.

  • Setting minimum evidence standards when deciding which interventions to scale-up and transfer. For example, the Irish Physical Activity Research Collaboration developed a standardised evaluation framework to help funders and policy makers make evidence-based decisions on whether to continue or discontinue publically funded interventions. It is important to note that it is not plausible to rigorously evaluate all public health interventions, further, it is not always ethically feasible to apply gold standard evaluation designs, such as RCTs. For this reason, minimum evidence standards should depend on intervention characteristics such as their overall priority, risk and evidence to date. See Box 1.12 for an example of where this principle is applied.

Providing technical and financial support will also help strengthen the evidence base. Evaluating public health interventions, such as those targeting overweight, is a complex task that may require the development of a long-term assessment strategy. Therefore, it is necessary to involve people with experience in programme evaluations as well as ensure sufficient funding to undertake an evaluation. Some examples of how this can be achieved include:

  • Continuing to build workforce skills and competencies for example by offering short courses to workers involved in the evaluation who do not have prior experience in this area (Pettman et al., 2012[47]), as well as promoting existing material outlining the steps involved in undertaking an evaluation (Box 1.13).

  • Bridging the gap between academic and public health practice and policies by encouraging collaborative research. In Quebec, Canada, for example, a 4P Training Programme – Prevention, Promotion and Public Policies – was implemented, which partners doctoral and post-doctoral students with public health organisations to undertake applied public health research (Box 1.14) (Hamelin and Paradis, 2018[54]). Similarly, the United States promotes alliances between academic associations and the Centers for Disease Control and Prevention (CDC) via the “Academic Partnerships to Improve Health” initiative.

  • Encouraging funding agencies to dedicate a specific proportion of funds to monitor and evaluate the intervention – for example, public health agencies often set aside 15% of total funding for this purpose (Pettman et al., 2012[47]).

  • Providing funding for long-term research projects. At present, much of the research on overweight interventions focuses on short-term impacts, including those in this report. This is problematic given the benefits of overweight interventions can take years or even decades to be realised, particularly those targeting children. For this reason, policy makers are encouraged to prioritise long-term research projects. The Dutch Public Health Institute, RIVM, for example, are in the process of developing a data registry for participants of the Combined Lifestyle Intervention, which provides participants with advice on diet and physical activity. The registry is designed to assess the long-term impact of this intervention (Box 1.15).

Demonstrating efficiency is increasingly important in public health. Governments today face tight budgetary constraints concurrent with growing demand for services to meet population needs. Consequently, the health sector “competes” with itself and other sectors for funding (World Health Organization and ExpandNet, 2009[56]). Demonstrating efficiency is therefore increasingly important, particularly among prevention interventions given the low proportion of funding dedicated to this area of health – as of 2019, less than 3% of total health care expenditure in the OECD is spent on prevention (OECD, 2021[57]).

Despite the importance of demonstrating efficiency, studies related to overweight prevention interventions are limited. Economic evaluations to assess efficiency among selected interventions were rare. This finding aligns with the broader literature where the cost-effectiveness of overweight prevention interventions are “infrequently studied” (Wang et al., 2015[58]), particularly among children (Brown et al., 2019[22]). The dearth of efficiency studies is not surprising given the difficulty in choosing which costs to include, particularly for interventions targeting society as a whole.

Policies to promote efficiency studies will further enhance the evidence base for overweight prevention interventions. Similar incentives and support mechanisms to promote high-quality effectiveness evaluations can be applied to economic evaluations to demonstrate efficiency. Compared to outcome evaluations, economic evaluations typically require a greater level of expertise, therefore, it is of particular importance to bridge the gap between academia (e.g. health economists) and intervention administrators in order to promote collaborative research. For example, Australia established the ACE Obesity Policy, a priority-setting study led by academics and obesity experts to evaluate the “economic credentials” of several obesity prevention policies (Box 1.16).


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← 1. For adults, WHO define overweight and obesity as having a BMI >=25Kg/m2 and 30Kg/m2, respectively. BMI is the most widely used proxy for body adiposity to assess population-level rates of overweight, as it is easily derived from a person’s weight and height (i.e. weight (kg) divided by height in metres squared) (WHO, 2019[60]).

← 2. These figures assume interventions have a purely additive effect, which has not been verified.

← 3. An intervention is cost-effective if the cost per DALY gained falls below international thresholds used to define a country’s willingness to pay for one year of life in good health (this threshold typically ranges between EUR 22 000-80 000 (Vallejo-Torres et al., 2016[7]). An intervention is cost saving if the cost per DALY gained is negative.

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