research framework for obesity

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• Published: 27 January 2020

Epidemiology and Population Health

Evidence from big data in obesity research: international case studies

• Emma Wilkins 1 ,
• Ariadni Aravani 1 ,
• Amy Downing 1 ,
• Adam Drewnowski 2 ,
• Claire Griffiths 3 ,
• Stephen Zwolinsky 3 ,
• Mark Birkin 4 ,
• Seraphim Alvanides 5 , 6 &
• Michelle A. Morris   ORCID: orcid.org/0000-0002-9325-619X 1  

International Journal of Obesity volume  44 ,  pages 1028–1040 ( 2020 ) Cite this article

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Background/objective

Obesity is thought to be the product of over 100 different factors, interacting as a complex system over multiple levels. Understanding the drivers of obesity requires considerable data, which are challenging, costly and time-consuming to collect through traditional means. Use of ‘big data’ presents a potential solution to this challenge. Big data is defined by Delphi consensus as: always digital , has a large sample size, and a large volume or variety or velocity of variables that require additional computing power (Vogel et al. Int J Obes. 2019). ‘Additional computing power’ introduces the concept of big data analytics. The aim of this paper is to showcase international research case studies presented during a seminar series held by the Economic and Social Research Council (ESRC) Strategic Network for Obesity in the UK. These are intended to provide an in-depth view of how big data can be used in obesity research, and the specific benefits, limitations and challenges encountered.

Methods and results

Three case studies are presented. The first investigated the influence of the built environment on physical activity. It used spatial data on green spaces and exercise facilities alongside individual-level data on physical activity and swipe card entry to leisure centres, collected as part of a local authority exercise class initiative. The second used a variety of linked electronic health datasets to investigate associations between obesity surgery and the risk of developing cancer. The third used data on tax parcel values alongside data from the Seattle Obesity Study to investigate sociodemographic determinants of obesity in Seattle.

Conclusions

The case studies demonstrated how big data could be used to augment traditional data to capture a broader range of variables in the obesity system. They also showed that big data can present improvements over traditional data in relation to size, coverage, temporality, and objectivity of measures. However, the case studies also encountered challenges or limitations; particularly in relation to hidden/unforeseen biases and lack of contextual information. Overall, despite challenges, big data presents a relatively untapped resource that shows promise in helping to understand drivers of obesity.

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Acknowledgements

The ESRC Strategic Network for Obesity was funded via ESRC grant number ES/N00941X/1. The authors would like to thank all of the network investigators ( https://www.cdrc.ac.uk/research/obesity/investigators/ ) and members ( https://www.cdrc.ac.uk/research/obesity/network-members/ ) for their participation in network meetings and discussion which contributed to the development of this paper.

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Emma Wilkins, Ariadni Aravani, Amy Downing & Michelle A. Morris

Center for Public Health Nutrition, University of Washington, Seattle, WA, USA

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Engineering and Environment, Northumbria University, Newcastle, UK

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Wilkins, E., Aravani, A., Downing, A. et al. Evidence from big data in obesity research: international case studies. Int J Obes 44 , 1028–1040 (2020). https://doi.org/10.1038/s41366-020-0532-8

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Received : 23 May 2019

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DOI : https://doi.org/10.1038/s41366-020-0532-8

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Research priority setting in obesity: a systematic review

• Review Article
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• Published: 03 December 2021
• Volume 31 , pages 1285–1301, ( 2023 )

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• Halima Iqbal   ORCID: orcid.org/0000-0003-0895-1479 1 , 2 ,
• Rosemary R. C. McEachan 2 ,
• Jane West 2 &
• Melanie Haith-Cooper 1  

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Obesity research priority setting, if conducted to a high standard, can help promote policy-relevant and efficient research. Therefore, there is a need to identify existing research priority setting studies conducted in the topic area of obesity and to determine the extent to which they followed good practice principles for research priority setting.

Studies examining research priority setting in obesity were identified through searching the MEDLINE, PBSC, CINAHL, PsycINFO databases and the grey literature. The nine common themes of good practice in research priority setting were used as a methodological framework to evaluate the processes of the included studies. These were context, use of a comprehensive approach, inclusiveness, information gathering, planning for implementation, criteria, methods for deciding on priorities, evaluation and transparency.

Thirteen articles reporting research prioritisation exercises conducted in different areas of obesity research were included. All studies reported engaging with various stakeholders such as policy makers, researchers and healthcare professionals. Public involvement was included in six studies. Methods of research prioritisation commonly included both Delphi and nominal group techniques and surveys. None of the 13 studies fulfilled all nine of the good practice criteria for research priority setting, with the most common limitations including not using a comprehensive approach and lack of inclusivity and evaluating on their processes.

There is a need for research priority setting studies in obesity to involve the public and to evaluate their exercises to ensure they are of high quality.

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Introduction

Setting priorities for research helps to direct the most effective use of resources, such as research capacity, time and funds, to ensure an optimal health impact (Terry et al. 2018 ). Research priority setting in health, informed by stakeholders, can assist in the identification of topical and relevant issues, and unresolved questions regarding prevention, diagnosis and treatment of health conditions using a process that is explicit, iterative and inclusive (Rudan et al. 2010 ). There is currently no consensus on the definition of research priority setting, but there is agreement on a range of activities that centre on identifying, prioritising and reaching agreement on the research areas or questions deemed important to stakeholders (Tong et al. 2019 ). In the past, research-funding organisations and researchers developed their own research agendas without consulting key stakeholders (Graham et al. 2020 ). In recent times, however, there has been a focus on research needing to address questions that have relevance to those very people it intends to help (Dawson et al. 2017 ). It has been advocated that priority setting processes must also be fair, informed by credible evidence, of high quality and involve a broad range of stakeholders (Nasser et al. 2013 ; Sibbald et al. 2009 ; Viergever et al. 2010 ). Adopting a systematic and transparent approach to the identification of health research priorities can help to ensure that funded research has a public health benefit and make efficient and equitable use of limited resources (Bryant et al. 2014 ). Developing research agendas with target populations increases the potential for success and is more likely to be well received and relevant to their needs.

Nine common themes of good practice in research priority setting

There are currently no published guidelines for reporting priority setting for health research (Tong et al. 2019 ). In the absence of a gold standard approach, a checklist of nine common themes for good practice in health research prioritisation was developed by Viergever et al. ( 2010 ). In developing the checklist, expert consultation was initiated, and a literature review identified several methodological approaches which were combined to draw together a comprehensive outline of common views on what constituted good practice in health research priority setting (Viergever and Roderik 2010 ). The aim was to facilitate a transparent and comprehensive priority setting via this checklist and accommodate the flexibility required by different contexts.

The nine themes contained within the checklist broadly fall into three different categories: preparatory work, deciding on priorities and after priorities have been set. Each category contains corresponding practices that further identify the goals in each step. There are five related practices within preparatory work , namely context, use of a comprehensive approach (established frameworks providing structured guidance for research prioritisation), inclusiveness, information gathering and planning for implementation. There are two related practices within deciding on priorities, namely criteria and methods for deciding on priorities, and two within after priorities have been set, namely evaluation and transparency. See Table 1 for a detailed description of each theme.

The worldwide prevalence of obesity has significantly increased over the past few decades, leading the trend to be termed a ‘global epidemic’ by the World Health Organization and a serious threat to public health (World Health Organization 2017 ). Moreover, obesity is a global issue because it concerns both developed and developing countries (Cassi et al. 2017 ). The most recent available statistics from 2018/19 show that in England, a significant proportion of adults were overweight or obese, namely 67% of men and 60% of women (NHS Digital 2020 ). Of these, 26% of men and 29% of women were obese, and morbid obesity has also increased, from under 1% in 1993, to 3% in 2018 (NHS Digital 2020 ). Excess levels of fat in the body increase the risk of disease (Pollack et al. 2020 ) and obesity is a major risk factor for developing a range of conditions including cardiovascular disease, type 2 diabetes, muscular disorders, respiratory conditions and a host of psychological problems (Fruh 2017 ). A recent report by Public Health England highlights that the COVID-19 pandemic has brought to the fore the health crisis caused by overweight and obesity (Public Health England 2020 ). Both international and national research has consistently identified obesity as one of the key factors linked with severe outcomes from COVID-19 (Dietz and Santos-Burgoa 2020 ; Halvatsiotis et al. 2020 ). The direct annual costs resulting from obesity to the UK National Health Service (NHS) are reportedly estimated to reach £9.7 billion ($13.2 billion) by 2050, with wider costs to society predicted to reach just under £50 billion ($67.8 billion) per year by 2050 (Bradford Metropolitan District Council 2019 ).

Research is critical to inform prevention and treatment strategies to tackle obesity. Although there is a plethora of research examining the multitude of factors influencing obesity, research budgets are finite. Research priority setting can assist in making the most effective use of budgets by identifying the most relevant research areas according to different stakeholders. There is an emphasis on the need for research priority setting exercises to be explicit in their processes (Tong et al. 2019 ). Research priority setting guidelines and/or frameworks can help improve future research prioritisation in obesity, thus increasing the value and contribution of research aimed at reducing the obesity levels of populations.

The aim of this systematic review was to identify research priority setting exercises that have been conducted in obesity and to examine whether they had applied good practice principles in health research priority setting.

The systematic review followed the standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Shamseer et al. 2015 ).

Search strategy and process of study selection

The search was undertaken between 14–15 November 2020, using four electronic health databases, namely MEDLINE, PBSC, CINAHL and PsychINFO. The following Boolean search term combinations were used:

‘research priority setting’ [all fields] OR ‘research prioritization’ [all fields] OR ‘research prioritisation’ [all fields] OR ‘research priorities’ [all fields] OR ‘research agenda’ [all fields]

‘obesity’ OR ‘child obesity’ [all fields] OR ‘childhood obesity’ [all fields] OR ‘pediatric obesity’ [all fields] OR ‘obesity prevention’ [all fields] OR ‘obesity treatment’ [all fields]

We searched databases from their inception to November 2020. Only titles and abstracts published in English were included. The principal researcher (HI) independently conducted the article search. Searches in the grey literature included Google Scholar, Cochrane methods priority setting, the James Lind Alliance (a well-established priority-setting partnership method) and reference lists of selected articles to identify eligible papers. The search string ‘research priority setting and obesity’ was applied to Google Scholar. The first ten pages of Google Scholar were examined for additional articles. All authors contributed and refined the review’s search strategy.

Inclusion and exclusion criteria

The review included any study describing a process of conducting a research prioritisation exercise in obesity. To be included in the review, studies must have outlined participants’ characteristics, stated the methods used to obtain research and identified well-established outcomes. International studies were included provided they were written in the English language. Studies were excluded if they did not mention health research, had not described the research prioritisation process or had assessed priorities for practice and policy rather than research (quality indicators). Also excluded were studies that did not focus on obesity research prioritisation.

Across all databases, the search yielded 249 citations, of which 203 remained after duplicates were removed. After the titles and abstracts had been screened, 26 articles underwent full-text screening. Of these publications, 13 studies met our inclusion criteria and were finally included in the analysis. Of the 13 excluded studies, four did not focus mainly on research prioritisation, one was a study protocol, two did not focus on obesity, four were non-research articles and two failed to include the methods and processes. All authors discussed and agreed on the selected papers. References were managed with EndNote X9 for ease. The PRISMA flowchart is displayed in Fig. 1 .

PRISMA 2009 flow diagram

Quality assessment tool

In the absence of a gold standard approach to research priority setting, the checklist of nine common themes for good practice in health research priority setting by Viergever et al. ( 2010 ) was used to ascertain whether the research prioritisation exercises in each included study complied with good practice principles in their processes. This checklist has been previously used to evaluate or guide research prioritisation exercises (Doolan-Noble et al. 2019 ; Iqbal et al. 2021 ; Mador et al. 2016 ; Reveiz et al. 2013 ; Tong et al. 2015 ;) and has identified weaknesses prevalent in their processes. The checklist was specifically designed for health research priority setting and, as such, can identify issues that may have been otherwise overlooked by traditional quality appraisal tools.

Data synthesis and extraction

A descriptive synthesis was conducted to outline study characteristics and outcomes, and to determine how many good practice principles each study followed. Studies could score between 0 (demonstrated none of the good practice principles) to 20 (demonstrated all of the good practice principles). One researcher (HI) independently extracted study characteristics, methods and outcomes. The relevant data were inserted into comprehensive data extraction checklist forms developed specifically for the quality synthesis. The quality appraisal criteria were applied by two researchers and resolved through discussion (HI and MC).

Studies were conducted in research priority setting in the area of obesity for childhood obesity (Botchwey et al. 2018 ; Byrne et al. 2008 ; Curtin et al. 2017 ; Gallagher et al. 2010 ; Hennessy et al. 2018 ; McPherson et al. 2016 ; Ramirez et al. 2011 ; Taylor et al. 2013 ; Ward et al. 2013 ), adult obesity (Hill et al. 2019 ; Hill et al. 2020 ; Mama et al. 2014 ), and obesity more generally (McKinnon et al. 2009 ). Studies were conducted in the areas of childhood obesity prevention or treatment (Byrne et al. 2008 ; Gallagher et al. 2010 ; Hennessy et al. 2018 ; Taylor et al. 2013 ), youth physical activity and healthy weight (Botchwey et al. 2018 ), healthy weight among youth with autism spectrum disorder and other developmental disabilities (Curtin et al. 2017 ), preconception priorities for maternal obesity prevention (Hill et al. 2019 ), pregnancy priorities for maternal obesity prevention (Hill et al. 2020 ), obesity reduction (Mama et al. 2014 ), obesity in children with physical disabilities (McPherson et al. 2016 ), obesity in Latino children (Ramirez et al. 2011 ), obesity policy (McKinnon et al. 2009 ) and obesity prevention in early care and education settings (Ward et al. 2013 ). The prioritisation exercises were all conducted in high income countries, namely Australia (4), the UK (1) and the US (8).

Seven studies did not include any patient or public involvement in their establishment of research priorities, yet involved a wide range of other stakeholders such as researchers, policy makers/leaders and healthcare professionals (Botchwey et al. 2018 ; Byrne et al. 2008 ; Gallagher et al. 2010 ; Hennessy et al. 2018 ; McKinnon et al. 2009 ; Taylor et al. 2013 ; Ward et al. 2013 ). One study solely involved the public in identifying priorities (Mama et al. 2014 ) and the remaining five studies involved the public alongside other stakeholders (Curtin et al. 2017 ; Hill et al. 2019 ; Hill et al. 2020 ; McPherson et al. 2016 ; Ramirez et al. 2011 ). Frequently cited methods used to identify priorities were surveys, Delphi techniques and the nominal group technique.

The main outcome of the studies was the generation of research priorities relevant to the topic and scope of each study. The priorities were described as prioritised research ideas/gaps/areas, prioritised lists, research priorities and prioritised themes. All 13 studies are displayed in Table 2 below.

When matched against the checklist of good practice principles in research priority setting as defined by Viergever et al. ( 2010 ), none of the studies adhered to all the principles outlined in the checklist (see Table 3 ).

Summary of the comprehensiveness of studies in reporting good practice principles

Theme 1: context.

The focus of the exercise was made clear in all studies, as were the underlying values and principles of each study. These included the need to engage the community in identifying obesity research priorities (Mama et al. 2014 ), or to foster collaboration amongst interdisciplinary research experts in the field of healthy weight, prevention of weight gain and maintenance of healthy weight (Gallagher et al. 2010 ; Hennessy et al. 2018 ; Taylor et al. 2013 ), or to develop a research agenda leveraging the collective expertise of a range of stakeholders (McPherson et al. 2016 ). However, the resources used for the exercises were made explicit in very few studies. Where information was provided, these included the use of materials used during the exercise such as cards to write knowledge gaps on (McPherson et al. 2016 ), flipcharts and numbered stickers for ranking (Hennessy et al. 2018 ), the use of audio-recorders (Mama et al. 2014 ) and the use of facilitators (Gallagher et al. 2010 ; Hennessy et al. 2018 ; Hill et al. 2020 ; Hill et al. 2019 ; McKinnon et al. 2009 ; McPherson et al. 2016 ) and project staff members to take notes and capture details around the issues raised (Ward et al. 2013 ), as well as the use of a statistician, data analyst and administrative support staff (Curtin et al. 2017 ). In one study, the use of a transcription service was disclosed (Mama et al. 2014 ). The economic/financial and political environment in which the prioritisation exercise took place was not disclosed in any of the studies.

Theme 2: Use of a comprehensive approach

None of the studies reported the use of established, structured, step-by-step frameworks specifically designed for research priority setting to guide their prioritisation processes, such as the James Lind Alliance (JLA) methodology (JLA 2020 ), the Essential National Health Research (ENHR) strategy (COHRED 2009 ), the Combined Approach Matrix (CAM) (Ghaffar 2009 ) and the Child Health and Nutrition Research Initiative (CHNRI) (Rudan 2016 ). None of the studies developed their own frameworks to guide their exercises.

Theme 3: Inclusiveness

Across prioritisation exercises, participants comprised a diverse range of stakeholders. Samples were inclusive of health service managers, medical practitioners, healthcare practitioners, academics, interdisciplinary researchers, dietitians, scientists, government agencies, policy leaders and experts in the field of child obesity more generally. Two studies solely involved researchers in the process (Gallagher et al. 2010 ; Taylor et al. 2013 ). Public involvement in the exercise was made explicit in six studies only (Curtin et al. 2017 ; Hill et al. 2020 ; Hill et al. 2019 ; Mama et al. 2014 ; McPherson et al. 2016 ; Ramirez et al. 2011 ). Although all studies discussed participant characteristics, some were more detailed in their descriptions by disclosing the sex of participants (Hennessy et al. 2018 ; Mama et al. 2014 ; Ramirez et al. 2011 ), with women overwhelmingly outnumbering men in two studies (Hennessy et al. 2018 ; Ramirez et al. 2011 ). An appropriate representation of regional participation was included in most studies that did not involve the public, as well as the incorporation of relevant sectors.

Theme 4: Information gathering

In some studies, a core planning group or committee suggested initial priorities to direct the process (Gallagher et al. 2010 ; Ramirez et al. 2011 ; Ward et al. 2013 ), or researchers identified the initial areas and other stakeholders prioritised the selected areas (Botchwey et al. 2018 ; Byrne et al. 2008 ). The use of technical data was reported in most studies. These included reviews of guidelines and recommendations (Hill et al. 2020 ; Hill et al. 2019 ), as well as literature searches, reports and systematic reviews (Botchwey et al. 2018 ; Hill et al. 2020 ; Ramirez et al. 2011 ). Surveys were conducted to obtain broad input on the selected topic areas (Botchwey et al. 2018 ; Byrne et al. 2008 ; Curtin et al. 2017 ), as were questionnaires (Ramirez et al. 2011 ; Taylor et al. 2013 ). Workshops (Gallagher et al. 2010 ; Hennessy et al. 2018 ; Hill et al. 2019 ; Hill et al. 2020 ; McPherson et al. 2016 ), group meetings (Curtin et al. 2017 ; McPherson et al. 2016 ; Ward et al. 2013 ) and brainstorming sessions were also reported as a means of generating information (Curtin et al. 2017 ), as well as presentations (McPherson et al. 2016 ; Ward et al. 2013 ).

Theme 5: Planning for implementation

Most of the studies did not report their plans for implementing identified priorities. Several community projects were established from two research priority setting studies (Gallagher et al. 2010 ; Ramirez et al. 2011 ). Plans for implementing pilot studies were established from a research agenda (Ramirez et al. 2011 ). Ongoing activities influenced by the identified priorities were reported in two studies (Hill et al. 2019 ; Hill et al. 2020 ). The research agenda shaped four initial projects in another study (Botchwey et al. 2018 ) and finally, one study secured a large team grant to address some items on their research agenda (McPherson et al. 2016 ).

Theme 6: Criteria

Criteria to focus discussion on research priorities were mentioned in six studies (Botchwey et al. 2018 ; Hill et al. 2020 ; Hill et al. 2019 ; McKinnon et al. 2009 ; McPherson et al. 2016 ; Ramirez et al. 2011 ). Cited criterion included research priorities that had the greatest long-term impact, and what would have the most immediate impact (Botchwey et al. 2018 ), prevalence or burden attributable to the proposed problem (Hill et al. 2019 ), provision, potential and proposed transformation attributable to the problem (Hill et al. 2020 ), preventative effect with respect to obesity development, and implementation feasibility (Hill et al. 2020 ), and the most appropriate and feasible methods for initiating research efforts (McPherson et al. 2016 ).

Theme 7: Methods for deciding on priorities

Studies either adopted a metrics approach (Botchwey et al. 2018 ; Byrne et al. 2008 ; Curtin et al. 2017 ; Gallagher et al. 2010 ; Taylor et al. 2013 ; Ward et al. 2013 ), a consensus approach (McPherson et al. 2016 ; Ramirez et al. 2011 ) or a combination of both (Hennessy et al. 2018 ; Hill et al. 2019 ; Hill et al. 2020 ). Likert scales were utilised in one study for ranking priorities (Ramirez et al. 2011 ), as were numbered stickers (Hennessy et al. 2018 ). The Delphi method was the most used method for deciding on priorities, both in its original form (Byrne et al. 2008 ; Ramirez et al. 2011 ; Taylor et al. 2013 ) and adapted versions, followed by the nominal group technique (Hennessy et al. 2018 ). In two studies, the Delphi technique was combined with the nominal group technique (Hill et al. 2019 ; Hill et al. 2020 ). One study used a modified nominal group technique to determine priorities (McKinnon et al. 2009 ). Another study did not use ranking and/or consensus to determine priorities, and instead searched for themes in the data and described these as the priorities (Mama et al. 2014 ).

Theme 8: Evaluation

There were no reported plans to update the priorities. One study mentioned that the research agenda would be reviewed, re-evaluated and refined (Curtin et al. 2017 ).

Theme 9: Transparency

Most of the studies were explicit in their priority setting processes, despite not using a well-established framework, although some were more transparent than others (Gallagher et al. 2010 ; Hennessy et al. 2018 ; Hill et al. 2020 ; Hill et al. 2019 ; Ramirez et al. 2011 ). The majority of studies outlined how the priorities were set. In most cases, it was clear which stakeholders identified initial topics, which stakeholders added generated additional input and who exactly prioritised.

Some studies also highlighted the limitations of their prioritisation exercise, such as acknowledging the lack of public involvement altogether (Hennessy et al. 2018 ), the possibility of unequal representation of disciplines (Hill et al. 2019 ; Hill et al. 2020 ), the lack of participation in person by children or youth (McPherson et al. 2016 ) and the lack of men that participated (Hennessy et al. 2018 ). Further highlighted limitations were around the issue of generalisability. This included the small sample size (Taylor et al. 2013 ), method of sample recruiting (Mama et al. 2014 ) and the possibility of selection bias due to the participants not being randomly selected (Ramirez et al. 2011 ). Other challenges were also highlighted, such as issues encountered in achieving consensus during the prioritisation phases (Hennessy et al. 2018 ), and the steps taken to reduce potential limitations when using the nominal group technique (Hennessy et al. 2018 ; Hill et al. 2019 ). One study reported pilot testing the questionnaire used to elicit priorities utilising a survey instrument, and subsequently revising it for improvement (Ramirez et al. 2011 ).

This review provides an assessment of research priority setting initiatives in the area of obesity. Most of the prioritisation exercises focussed on obesity topics including causes, prevention and management. Of the 13 identified studies, ten concentrated on child obesity, three on adult obesity and one focussed on obesity more generally. The application of a checklist of good practice principles in research priority setting identified the strengths and weaknesses inherent in each study. None of the studies fulfilled all the good practice principles as outlined by the checklist. It is clear that more effort needs to be made in studies examining obesity research priority setting to ensure that their processes are of a high quality. It is important to note however, that two studies (Byrne et al. 2008 ; McKinnon et al. 2009 ) were conducted before the checklist of nine common themes of good practice was published in 2010. In addition, literature advocating the need for research priority setting to be fair, legitimate, informed by credible evidence, include a wide range of stakeholders and be transparent, has only more recently been strongly advocated (Bhaumik et al. 2015 ; Nasser et al. 2013 ; Tong et al. 2019 ; Viergever et al. 2010 ) which may be as a result of the increase in research prioritisation exercises in the past two decades. Our findings suggest that the greatest limitations of studies when applied to the checklist of good practice concerned the criteria use of comprehensive approach, inclusiveness and evaluation.

None of the studies used comprehensive well-established research priority setting frameworks such as the JLA methodology, the ENHR strategy, the CAM and the CHNRI initiative. These established schemata were all developed before the studies were undertaken and provide step-by-step guidance for the entire process, while covering many of the points on the checklist (Viergever et al. 2010 ). It is argued by Viergever et al. ( 2010 ) that the use of these structurally well-defined tools and methods should at least be considered, and that they will gradually replace commonly used methods such as the Delphi method (Yoshida 2016 ), which was a frequently used method used to establish obesity priorities in the identified studies.

It is concerning that only six of the 13 studies in this review involved the public as stakeholders and even then, the public were significantly underrepresented in the sample (Hill et al. 2020 ; Hill et al. 2019 ; McPherson et al. 2016 ; Ramirez et al. 2011 ), with another study not making clear how many public stakeholders were involved in the process (Curtin et al. 2017 ). Interestingly, of the seven studies that scored the highest in this review, six of them involved the public in the generation of priorities. It is well established in the literature that community engagement in research priority setting is crucial for establishing research questions that are relevant to them. Previous studies have demonstrated that the research priorities of other stakeholders do not align with those of the public (Brady et al. 2020 ; Manikam et al. 2017 ; Owens et al. 2008 ; Tallon et al. 2000 ; Voigt et al. 2010 ). A 2014 report systematically reviewed research priority setting studies from the period 1966 to 2014 and found that in the 91 studies, researcher and government involvement was strong, yet involvement of other key stakeholders was limited (McGregor et al. 2014 ). To ensure the incorporation of public and patients in the process, guidelines are available such as the Guidance for Reporting Involvement of Patients and the Public (GRIPP) checklist (Staniszewska et al. 2017 ), which was developed to aid in improving the quality, consistency and transparency of reporting the inclusion of patients and the public in research. The checklist offers a comprehensive list of issues that require consideration when reporting activities in relation to public and patient involvement. It must be noted, however, that it fails to offer information on how the public and patient contributors are to be recruited (Dawson et al. 2017 ). Additionally, it does not offer explicit consideration for representing the diversity of the population relevant to the topic area (Dawson et al. 2017 ). It is unclear in the current review whether public stakeholders were representative of the community at large, i.e. whether there was inclusion of Black and minority ethnic stakeholders in the samples. In addition to ensuring the inclusion of the public in research priority setting exercises, it is recommended that key characteristics of the sample are recorded and reported so that issues in relation to inclusion and diversity can be understood.

With regard to evaluation, a small number of studies in this review described strategies for the implementation of identified priorities, yet none measured the impact of the prioritisation. This can be done, for example, by performing an impact assessment reviewing the research performed (Viergever and Roderik 2010 ). The authors of a 2014 report (McGregor et al. 2014 ) argued that many of the exercises failed to translate the result of the prioritisation process into implementation of projects. It was further highlighted that the exercises were rarely repeated due to the lack of follow-up. The authors of the current review would strongly endorse the use of good practice guidelines, such as the one used to critically appraise the studies in this review, or the Reporting Guideline for Priority Setting of Health Research (REPRISE) by Tong et al. ( 2019 ).

In summary, one can say that while research priority setting studies in the topic area of obesity do exist, they vary in scope and in quality. Although a wide range of stakeholders were involved in the prioritisation processes, public involvement was either non-existent or limited. The use of a comprehensive approach in research priority setting and/or adherence to good practice guidelines could enrich obesity priority setting processes to ensure the identified obesity priorities are relevant, transparent and can assist in implementation efforts. It is imperative that the public be involved in the obesity research priority setting process, resulting in research agendas that have incorporated their unmet needs. This can improve the relevance and legitimacy of research and ultimately achieve better health outcomes in obesity.

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This work was supported by the National Institute for Health Research (NIHR) under its Applied Research Collaboration (ARC) Yorkshire and Humber in the form of Ph.D. funding to HI [NIHR200166], the UK Prevention Research Partnership (UKPRP) in the form of funding to JW and RM [MR/S037527/1], the NIHR Clinical Research Network in the form of funding to JW, and the NIHR ARC Yorkshire and Humber in the form of funding to RM

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Conceptualisation: Halima Iqbal, Melanie Haith-Cooper, Rosie McEachan, Jane West; Methodology: Halima Iqbal; Formal analysis and investigation: Halima Iqbal, Melanie Haith-Cooper; Writing – original draft preparation: Halima Iqbal; Writing – review and editing: Halima Iqbal, Melanie Haith-Cooper, Rosie McEachan, Jane West; Resources: Halima Iqbal; Supervision: Halima Iqbal

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Iqbal, H., McEachan, R.R.C., West, J. et al. Research priority setting in obesity: a systematic review. J Public Health (Berl.) 31 , 1285–1301 (2023). https://doi.org/10.1007/s10389-021-01679-8

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Bridging the Evidence Gap in Obesity Prevention: A Framework to Inform Decision Making

• PMID: 25032376
• Bookshelf ID: NBK220184
• DOI: 10.17226/12847

To battle the obesity epidemic in America, health care professionals and policymakers need relevant, useful data on the effectiveness of obesity prevention policies and programs. Bridging the Evidence Gap in Obesity Prevention identifies a new approach to decision making and research on obesity prevention to use a systems perspective to gain a broader understanding of the context of obesity and the many factors that influence it.

Copyright 2010 by the National Academy of Sciences. All rights reserved.

• THE NATIONAL ACADEMIES
• COMMITTEE ON AN EVIDENCE FRAMEWORK FOR OBESITY PREVENTION DECISION MAKING
• 1. Introduction
• 2. Obesity Prevention Strategies in Concept and Practice
• 3. Rationale for and Overview of the L.E.A.D. Framework
• 4. Defining the Problem: The Importance of Taking a Systems Perspective
• 5. Specifying Questions and Locating Evidence: An Expanded View
• 6. Evaluating Evidence
• 7. Assembling Evidence and Informing Decisions
• 8. Opportunities to Generate Evidence
• 9. Next Steps
• 10. Conclusions and Recommendations
• A Acronyms and Glossary
• B Other Evidence Projects
• C Review of Existing Reviews on Obesity Prevention
• D Information Sources for Locating Evidence
• E An In-Depth Look at Study Designs and Methodologies
• F Agendas from Two Workshops
• G Committee Member Biographical Sketches

Publication types

• Research article
• Open access
• Published: 16 April 2015

Successful behavior change in obesity interventions in adults: a systematic review of self-regulation mediators

• Pedro J Teixeira 1 ,
• Eliana V Carraça 1 ,
• Marta M Marques 1 ,
• Harry Rutter 2 ,
• Jean-Michel Oppert 3 , 4 ,
• Ilse De Bourdeaudhuij 5 ,
• Jeroen Lakerveld 6 &
• Johannes Brug 7  

BMC Medicine volume  13 , Article number:  84 ( 2015 ) Cite this article

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Relapse is high in lifestyle obesity interventions involving behavior and weight change. Identifying mediators of successful outcomes in these interventions is critical to improve effectiveness and to guide approaches to obesity treatment, including resource allocation. This article reviews the most consistent self-regulation mediators of medium- and long-term weight control, physical activity, and dietary intake in clinical and community behavior change interventions targeting overweight/obese adults.

A comprehensive search of peer-reviewed articles, published since 2000, was conducted on electronic databases (for example, MEDLINE) and journal reference lists. Experimental studies were eligible if they reported intervention effects on hypothesized mediators (self-regulatory and psychological mechanisms) and the association between these and the outcomes of interest (weight change, physical activity, and dietary intake). Quality and content of selected studies were analyzed and findings summarized. Studies with formal mediation analyses were reported separately.

Thirty-five studies were included testing 42 putative mediators. Ten studies used formal mediation analyses. Twenty-eight studies were randomized controlled trials, mainly aiming at weight loss or maintenance (n = 21). Targeted participants were obese (n = 26) or overweight individuals, aged between 25 to 44 years (n = 23), and 13 studies targeted women only. In terms of study quality, 13 trials were rated as “strong”, 15 as “moderate”, and 7 studies as “weak”. In addition, methodological quality of formal mediation analyses was “medium”. Identified mediators for medium-/long-term weight control were higher levels of autonomous motivation, self-efficacy/barriers, self-regulation skills (such as self-monitoring), flexible eating restraint, and positive body image. For physical activity, significant putative mediators were high autonomous motivation, self-efficacy, and use of self-regulation skills. For dietary intake, the evidence was much less clear, and no consistent mediators were identified.

Conclusions

This is the first systematic review of mediational psychological mechanisms of successful outcomes in obesity-related lifestyle change interventions. Despite limited evidence, higher autonomous motivation, self-efficacy, and self-regulation skills emerged as the best predictors of beneficial weight and physical activity outcomes; for weight control, positive body image and flexible eating restraint may additionally improve outcomes. These variables represent possible targets for future lifestyle interventions in overweight/obese populations.

Peer Review reports

Lifestyle treatment interventions for obesity typically target changes in diet and physical activity through strategies like setting adequate goals and enhancing patients’ motivation, changing their beliefs and expectations, and providing guidance in the use of a variety of self-regulation skills (such as self-monitoring), all of which are thought to influence behavior change and maintenance [ 1 - 4 ]. A wide variety of health behavior change theories has been employed to provide conceptual organization of these determinants, including social cognitive theories such as the theory of planned behavior [ 5 ], theories of motivation such as self-determination theory [ 6 ], theories distinguishing between motivational and post-motivational or volitional phases [ 7 ] such as the health action process approach (HAPA) [ 8 ], and self-regulation models such as control theory [ 9 ]. Since all these theories address the regulation of a person’s behavior in the service of some goal or desired outcome, through intrapersonal factors, in this paper we broadly refer to intervening variables in this process as self-regulation factors .

Behavior modification in general, and “comprehensive lifestyle interventions” in particular [ 10 ] are currently the first recommended step in obesity management. However, so far, randomized controlled trials evaluating the effectiveness of programs that target lifestyle behavior have shown mixed effects and, if effective, they have generally resulted in only small changes in target behaviors [ 11 - 15 ]. In addition, the evidence shows that relatively little if any weight loss accomplished in treatment programs is maintained over the long term [ 16 ]. Furthermore, few studies have analyzed why, or by which mechanisms, interventions are successful for some individuals and not for others. Clearly, there is a need for research that identifies causal predictors of long-term weight control, including successful weight loss and maintenance [ 17 ].

Despite the limited success of available interventions in reversing the current trends in obesity prevalence, approaches focusing on individual behavior change remain an important topic of interest in obesity research. Several reasons justify this assertion. First, these interventions typically focus on behaviors (for example, diet and physical activity), which have widespread consequences for health, with or without weight loss. Second, if and when individuals are able to successfully self-regulate their behaviors, these effects tend to be sustainable, which is essential for having a lasting impact on health; moreover, this successful self-regulation may also “transfer” to, and help change, other health behaviors [ 18 ]. Third, although some interventions targeting individuals may be ineffective on their own, they might be able to contribute to the effectiveness of strategies that integrate multiple levels (that is, strategies that include individual-level and environmental-level approaches) [ 19 ]. Finally, the potential for dissemination of individual-level intervention approaches is considerable, given that a sizable number of overweight and obese persons will seek professional help at some point in their lives. Consequently, improving the efficacy of such interventions has substantial clinical as well as public health relevance.

One recent development in studies testing lifestyle interventions for obesity is their ability to identify the mechanisms or processes by which interventions induce meaningful and lasting change in their (most successful) participants. These mechanisms can generally be named predictors (or determinants ) of success, and some studies have gone one step further to evaluate the extent to which they may be causal mediators of intervention effects. Testing of mediation, using appropriate methods, is a critical step in this field; it provides the strongest possible inference for the identification of elements in interventions which are causally “responsible” for achieving desired outcomes [ 20 ].

Success and failure in the self-regulation of health behaviors involve multiple psychological and behavioral aspects. The aim of this review was to identify and summarize psychological self-regulation mediators of successful weight change, or change in energy balance-related behavior (physical activity and diet), in clinical and community behavior change obesity interventions. Because eventual weight regain is frequent after behavior and/or weight change interventions, particular attention was given to studies reporting long-term outcomes, that is, one year or more after the beginning of the intervention.

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [ 21 ].

Eligibility criteria

Studies were included in this review if they were intervention studies published since 2000 in the English language, used experimental designs, and referred to clinical or community behavior change interventions with overweight/obese adults (≥18 years old) aiming to reduce overweight/obesity. This review was limited to “lifestyle interventions” defined as interventions that promote change in energy balance-related behaviors (such as diet and physical activity, as the outcomes) and self-regulatory factors (such as motivation and self-monitoring, as the potential mediators) relevant for overweight/obesity treatment, typically in settings involving personal contact between interventionists and participants. There were no restrictions with respect to the format and duration of the intervention. To be eligible, studies should also report outcomes assessed at least 6 months after the start of the intervention; include a quantitative assessment of change in weight/BMI, physical activity (for example, self-reported or accelerometer-derived minutes of moderate and vigorous physical activity, daily pedometer steps, attendance to PA sessions), or dietary intake (for example, energy intake, fat intake, fruit and vegetable intake) as well as a quantitative assessment of potential mediators of successful behavior change. We decided not to distinguish predictors of weight loss and predictors of weight loss maintenance, choosing instead to divide the studies according to the length of measurement periods (shorter versus longer than 12 months). While it is possible that predictors of those two processes differ, to appropriately evaluate predictors of weight loss maintenance, we would have to rely on studies of successful weight losers, and preferably including psychological measures before and after the maintenance period. Only one intervention study fit both criteria.

An a priori list of mediators was used for study inclusion/exclusion, based on previous work in this area (for example, [ 2 , 22 ]). Only mediators representing individual-level self-regulatory processes were considered (that is, those related to skills, motivation, competence , coping mechanisms, beliefs, physical self-perceptions, and eating regulation factors such as disinhibition, restraint, and perceived hunger). Mediators associated with personality factors, social support, and health-related outcomes (such as psychological distress, quality of life, and well-being) were excluded. Finally, eligible studies were required to report the effect of the intervention on hypothesized mediator(s) and the association of the putative mediator with the outcomes of interest.

Search strategy and study selection

A comprehensive search of peer-reviewed articles published between January 2000 and February 2014 (including online ahead of print publication) was conducted in six electronic databases (Pubmed, MEDLINE, PsycINFO, the Cochrane Library, Web of Knowledge, and SPORTDiscus). The decision to restrict the selection to studies published since 2000 is based on the fact that recent development in studies testing the effectiveness of lifestyle interventions for obesity makes older studies less externally valid. For instance, in 1995, Friedman and Brownell [ 23 ] alerted for the need of a “third generation” of obesity treatment studies analyzing causal mechanisms between psychosocial variables and weight change. Despite this, one decade later, it has been observed that very few studies had investigated such mechanisms, and even fewer looked into long-term changes [ 2 ].

Searches included various combinations of four sets of terms: i) terms concerning the health condition or population of interest (overweight/obesity); ii) terms concerning the intervention(s)/exposure(s) evaluated (for example, behavior change/lifestyle obesity interventions); iii) terms respecting the outcomes of interest (weight change, physical activity, and dietary intake); iv) terms concerning the predictors/mediators of interest (psychological, self-regulation); and v) terms concerning the type of analyses of relevance (for example, mediation, correlates, predictors). (See Additional file 1 for a search example; complete search strategies can be obtained from the authors). Other sources included manual cross-referencing of bibliographies cited in previous reviews [ 2 , 22 , 24 - 26 ] and included studies, as well as manual searches of the content of key scientific journals ( Obesity Reviews; International Journal of Obesity; Obesity (Silver Spring); International Journal of Behavioral Nutrition and Physical Activity; Journal of the American Dietetic Association; Psychology of Sports and Exercise; Health Psychology; Journal of Behavioral Medicine; Preventive Medicine ).

Titles, abstracts, and references of potential articles were reviewed by two authors (EVC, MM) to identify studies that met the eligibility criteria. Duplicate entries were manually removed. Relevant articles were then retrieved for a full read. The same two authors reviewed the full text of potential studies, and decisions to include or exclude studies in the review were made by consensus.

Data coding and extraction

A data extraction form was developed, informed by the PRISMA statement for reporting systematic reviews [ 21 ] and the Cochrane Collaboration’s tool for assessing risk of bias [ 27 ]. Data extraction included information about study details (authors, year, country of publication, affiliations, and funding), participants (characteristics, recruitment, setting, attrition, compliance, and blinding), study design and setting, outcomes of interest, mediators/predictors (in/out list), intervention length and characteristics, psychosocial instruments, and statistical analysis, including mediation techniques (a complete coding form can be obtained from the authors). Authors of included studies were contacted when necessary to retrieve missing data in published reports.

Considering that the main focus of this review was the identification of mediators, data extraction was performed separately, starting with the studies formally testing mediation (see Additional file 2 ), followed by those that reported both the effect of the intervention on hypothesized mediators ( path a ) and the association of the putative mediator with the outcomes of interest ( path b ), but did not test mediation (see Additional file 3 ). Regarding mediation and specifically in studies with formal mediation tests, researchers could use Baron and Kenny’s approach [ 28 ] and check whether the main effects were reduced in the presence of the mediator, or employ more sophisticated techniques to directly test the significance of the indirect effect through the mediator (for instance, by following MacKinnon’s approach [ 29 ], and using Preacher and Hayes mediation procedures or structural equation modeling). Additional file 4 presents a detailed description of the mediation analyses procedures and estimates for each study. In the latter (that is, predictor studies), we generally looked at a) whether significant intervention-control differences existed for a given variable (or pre-post change in non-controlled designs); b) whether there was an association between these changes (in intervention group only) and changes in the outcome (weight/PA/diet) in this group. If both were present, results were deemed consistent with mediation.

Quality assessment

The quality of included studies was assessed using an adapted version of the Quality Assessment Tool for Quantitative Studies, developed by the Effective Public Health Practice Project [ 30 ], and recommended for use by the Cochrane Public Health Review Group [ 27 ]. The current adaptation was based on recommendations from several authors [ 31 , 32 ], and has been used in a previous systematic review conducted as part of the SPOTLIGHT project [ 33 ]. This tool was adapted to allow the evaluation of both experimental and observational studies and contains 19 items, guiding the assessment of eight key methodological domains – 1) study design, 2) blinding, 3) representativeness (selection bias), 4) representativeness (withdrawals/dropouts), 5) confounders, 6) data collection, 7) data analysis, and 8) reporting. Each domain is classified as Strong (low risk of bias/high methodological quality), Moderate , or Low (high risk of bias/low methodological quality) methodological quality. A global rating is determined based on the scores of each component (see Additional file 5 for a full description of the Assessment Tool components and scoring system). Two researchers independently rated each of the eight domains and overall quality (EVC, MM). Discrepancies were resolved by consensus.

For studies employing formal tests of mediation, assessment of methodological quality was complemented with a checklist tool developed specifically for mediation analysis by Lubans, Foster, and Biddle [ 34 ], and subsequently adapted by Rhodes and Pfaeffli [ 35 ]. This tool includes 11 questions answered with a yes (1) or no (0) format, whose scores are added to generate a global score. High quality is represented by scores between 9 and 11, moderate quality ranges between 5 and 8, and low quality is considered when scores are below 5 (see Additional file 5 for a full description of the Checklist components and scoring system). Methodological quality of the mediation analyses was also rated by two authors (EVC, MM), with conflicting judgments discussed to reach agreement. Inter-rater agreement was good (Cohen’s kappa = 0.78).

Data synthesis

This review analyzed psychological and self-regulation mediators and predictors of change in body weight or BMI (primary outcome), physical activity, and dietary intake, separately (Note: we will use the term predictors when studies did not test for formal mediation, and mediators when they did). Intervention effects on the outcomes of interest were included in Additional files 2 and 3 . Results were divided according to the length of assessment of the outcomes, into short-term (<12 months from the start of the intervention) and long-term (≥12 months), so that those variables mediating/predicting more sustainable outcomes (the main focus of this review) could be more easily identified. Twelve months has been indicated by an expert panel on obesity as an appropriate threshold between weight loss and the maintenance of the weight lost [ 10 ]. In the synthesis of data derived from studies formally testing mediation, only controlled trials were included, to further strengthen inference regarding intervention effects on mediators and outcomes. In the case of prediction studies (not formally testing mediation), we included both controlled and uncontrolled trials, to capitalize on the (relatively) larger number of studies available, which would otherwise be excluded using the more stringent criteria. Table  1 describes the 35 included studies. In Tables  2 , 3 , 4 , 5 , 6 , and 7 , mediation-specific results are discriminated from the general results, provided that the main goal of this review was the identification of self-regulation mediators in behavior change obesity interventions. The overall results (considering multivariate, bivariate/correlational, and mediation analyses) are also presented in each table (Tables  2 , 3 , 4 , 5 , 6 , and 7 ). A total of 42 mediators/predictors were identified across outcomes. To facilitate data interpretation, considering the very large number of individual variables, these were grouped together by similarity into categories. Categorization was done through the extraction of information from primary studies on the definition and operationalization of the constructs. The following 12 categories were formed: Self-regulatory skills use, Processes of change, Coping mechanisms, Self-efficacy/barriers, Autonomous motivation, Controlled motivation, Decisional balance, Outcomes expectations/beliefs, Body image/physical self-worth, Cognitive restraint, Eating disinhibition, Perceived hunger. Please refer to Additional file 6 for full details regarding the mediators/predictors identified per outcome.

Finally, Tables  2 , 3 , 4 , 5 , 6 , and 7 show, separately for each mediator/predictor, the number of studies that have analyzed it, the number of times it was tested (some of them within the same study), and the number of times a significant effect was found. Results are presented for mediation-specific results and for the overall results.

Study selection

The literature search yielded a total of 1,394 potentially relevant records. Eight additional articles that were identified through manual searches and cross-referencing were added, bringing the total number of potential articles to 1,404. Of these, 770 abstracts were assessed for eligibility (634 duplicates removed). After the initial screening of titles and abstracts, 692 articles were excluded (Figure  1 ). Some articles were excluded for multiple reasons. Thirty-five articles describing 32 unique lifestyle interventions met the eligibility criteria and were therefore included [ 36 - 70 ]. Papers reporting on the same intervention are identified in Additional files 2 and 3 .

Flow diagram of studies.

Study characteristics

The characteristics of included studies are summarized in Table  1 (for further details, see Additional files 2 and 3 ). Most studies (n = 28) were randomized controlled trials, mainly aiming at weight loss or weight loss maintenance (n = 21). Most interventions took place in university (n = 15) or fitness club settings (n = 12), and most lasted more than 6 months (n = 29). However, only 11 trials included a follow-up assessment period and, of these, more than half were shorter than 12 months. Most studies were based on, or at least informed by, one or more theories of behavior change; the most frequent being social cognitive theory (n = 23), the transtheoretical model (n = 5), and self-determination theory (n = 3). Eight interventions were grounded in other theories, including group dynamics theory, problem solving model, theory of planned behavior, health belief model, and self-regulation theory. Four studies did not report using any theoretical framework. Samples were mostly composed of obese individuals (n = 26), aged between 25 to 44 years old (n = 23), and 13 studies targeted women only.

Twenty-six studies evaluated mediators/predictors of weight change, of which 17 reported medium/long-term outcomes; 19 studies evaluated mediators/predictors of physical activity, with 8 of them reporting medium/long-term outcomes; finally, 11 studies investigated dietary intake as the outcome measure, 4 of them in the medium/long-term. Weight-related measurements were performed with calibrated digital scales, and weight changes were expressed in weight change percent from baseline (n = 9), in kilograms (n = 10), as residualized scores regressed on the baseline scores (n = 6), or as BMI changes (n = 3). Regarding physical activity, objective measures were employed in 4 studies (for example, accelerometry, pedometry) and self-reported instruments in 17 studies; of these, 6 used the Seven-Day Physical Activity Recall [ 71 ] and 6 studies used the Godin Leisure-Time Exercise Questionnaire [ 72 ]. Dietary and caloric intake, indirectly assessed through the number of servings, was collected with the Food Intake Questionnaire in most studies (n = 5), followed by the Three-Day Food Records in most of the studies (n = 3), and the Block Food-Frequency Questionnaire (n = 1).

The overall results of the quality assessment can be found in Table  1 and the total quality score for each study in Additional files 2 and 3 (for a detailed classification of each item and study see Additional file 7 ). Regarding the overall methodological quality of the studies, 13 studies were rated as ”strong”, 15 were classified as ”moderate”, and 7 were rated as ”weak”. All included studies scored strong on the Study design , as they were experimental. Thirteen studies were rated as weak regarding Blinding of participants (during recruitment) and outcome assessors, 13 were rated as moderate, 8 as strong, and 1 did not receive a rating, as it was a non-randomized trial. All studies except two (one scored weak and the other scored strong) scored moderate regarding Representativeness (selection bias). Regarding reporting of Withdrawals and dropouts , 5 studies were rated as weak, 16 as moderate, and 14 as strong. Four studies scored weak in the adjustment of analysis for Confounders , 10 scored moderate, and 21 strong. In terms of Data collection tools, 4 studies were rated as weak as they did not provide information on the validity or reliability of the measures used, 11 were classified as moderate, and 17 as strong. Three studies were not rated as they used a larger dataset for which information on psychometric properties of the measures is already provided. All studies scored strong in the use of Appropriate statistical analyses . In terms of Reporting, 30 studies were rated as strong, and 5 studies as moderate.

In addition, studies including formal tests of mediation (n = 10) were classified as of moderate (n = 10) quality on the mediation analysis checklist. None of the studies reported conducting pilot studies to test mediation, and in all except two studies, there was no specific information regarding the power of the analysis to detect mediation. In only six studies were the outcomes controlled for baseline values.

Mediators/predictors tested in studies with weak methodological quality are identified in Tables  2 , 3 , 4 , 5 , 6 , and 7 . Overall, there appeared to be no association between the methodological quality of the studies and the results of the mediation analyses. Only 2 out of the 7 studies with a global weak score reported significant results for all mediator/predictors.

Mediators/predictors of weight control

Of the total number of studies investigating mediators/predictors of weight control (n = 26), 9 looked into short-term outcomes (<12 months) [ 47 - 49 , 51 , 52 , 54 , 57 , 62 , 70 ]. Twenty-one variables, grouped into nine categories, were tested as mediators/predictors of short-term weight control (Table  2 ). None of the studies performed formal tests of mediation. In the overall analyses (in this case, all were multivariate), self-regulation skill use emerged as the most consistent predictor of short-term weight control (consistent with mediation in 92% of the times it was tested [12 times in 6 studies]). Other variables that appear promising as mediators of short-term weight control were higher self-efficacy (and/or lower perceived barriers) and more positive body image, both consistent with mediation in 67% of the times they were tested (a total of 9 and 6 times, respectively). In the case of self-efficacy, 2 (out of 6) studies presented with low methodological quality. Although lower eating disinhibition also appears to find empirical support in non-formal mediation analyses, these results come from a single, weak quality study, and are correlational in nature. There were no other consistent mediators/predictors of short-term weight control.

Seventeen studies investigated potential mediators/predictors of long-term (≥12 months) weight outcomes, the main focus of the review [ 36 , 39 , 40 , 43 - 45 , 55 , 56 , 58 , 59 , 63 - 66 ]. Of these, six were RCTs that included formal tests of mediation [ 36 , 39 , 40 , 43 - 45 ]. Thirty variables, grouped in 12 categories, were tested as potential mediators/predictors (Table  3 ). The variables with stronger empirical support in formal mediation studies were body image, which was significant in all the times it was tested (3 times), and self-regulation skills, which was identified as a mediator in 67% of the times it was tested (2 times out of 3 studies). Self-efficacy was a significant mediator in 2 of the 3 times it was tested. For autonomous motivation and flexible eating restraint, results appear promising but derive from a single study in each case. Results observed in non-mediation analyses were consistent with the most stringent analyses, especially those concerning self-regulation skill use, autonomous motivation, and self-efficacy. For self-regulation skill use, significant effects were found in 83% of the 6 times it was tested, and every time in multivariate analyses. For autonomous motivation, results were consistent with mediation in all cases, but they originate from only two studies. On the other hand, empirical support from non-mediation analyses for other variables like body image and self-efficacy appears comparatively weaker and correlation-based; yet, the number of times each of these variables was tested is substantially higher (34 and 28 times, respectively). Eating disinhibition, which appeared to be an additional predictor in the short-term, does not seem to be consistent in the long-term provided that it was significant only in 38% of the 16 times it was tested. There were no other consistent mediators/predictors of long-term weight control.

Mediators/predictors of physical activity

Of the total number of studies investigating mediators/predictors of physical activity (n = 19), 11 looked into short-term outcomes (less than 6 months beyond the start of the intervention) [ 37 , 46 , 51 - 53 , 60 , 61 , 67 - 70 ]. Of these, only one formally tested mediation [ 37 ]. Fourteen variables, grouped in seven categories, were tested as mediators/predictors of short-term weight control (Table  4 ). Regarding mediation-specific results, body image emerged as a significant mediator only in one of the two times it was tested. In non-mediation studies, stronger empirical support was found for self-regulation skill use, which was significant in 11 of the 13 times it was tested (corresponding to 7 different studies). Body image and self-efficacy appear to be promising as mediators of short-term physical activity, showing significant results in 4 (out of 6) and 10 (out of 15) times they were tested, respectively. No other consistent mediators/predictors of short-term physical activity were identified.

Eight studies analyzed mediators/predictors of long-term physical activity [ 36 , 38 , 41 - 43 , 50 , 64 , 65 ], of which five used formal tests of mediation [ 36 , 38 , 41 - 43 ]. Twenty-three variables, grouped in nine categories, were tested as predictors (Table  5 ). The main predictors of long-term physical activity were autonomous motivation and self-efficacy, considering both mediation-specific analyses and the overall analyses. For autonomous motivation, results from two studies showed that mediation analyses were significant in 83% of the times and overall analyses showed consistency with mediation in 93% of the times (out of 14). For self-efficacy, results originated from 6 different studies. Mediation analyses were significant in 67% of the times self-efficacy was tested (6 times); and in the overall analyses, results were consistent with mediation in 75% of the times (out of 12). Controlled motivation was also consistently unrelated with physical activity outcomes, independent of the type of analyses performed. Finally, self-regulation skill use appears to mediate long-term physical activity in one out of two (formal mediation) and two out of the three (all analyses) times tested, but these results derive from two studies with low methodological quality.

Mediators/predictors of dietary intake

Of the total number of studies (n = 11) investigating mediators/predictors of dietary intake, seven looked into short-term outcomes [ 46 , 53 , 61 , 67 - 70 ] and four into long-term outcomes [ 41 , 50 , 64 , 65 ]. Only one study formally tested mediation [ 41 ]. Seven variables (grouped in three categories) were tested as mediators/predictors of short-term dietary intake, while 12 variables (grouped in seven categories) were tested in the long-term (Tables  6 and 7 ). Self-efficacy/barriers and self-regulation skill use appear promising as mediators of dietary intake in the short-term, both showing results consistent with mediation in 75% of the times they were tested (12 times out of 6 studies for self-efficacy, and 12 times out of 5 studies for self-regulation skills). No consistent mediators/predictors were identified in the longer time frame. Yet, self-efficacy was consistently unrelated with long-term dietary intake, looking less promising as a mediator (results were consistent with mediation only in 2 of the 8 times it was tested).

This review sought to identify the most consistent individual-level mediators of weight change, physical activity, and obesity-related dietary variables, in the context of lifestyle obesity interventions aimed at overweight and obese adults. These mediators or predictors of intervention effects were assessed by self-report, and are thought to represent psychological mechanisms or processes by which interventions affect body weight, through changes in energy-balance related behaviors. Note that this review did not focus on the efficacy of the interventions’ main effects per se. However, mediation mechanisms can be evaluated even in the absence of main significant effects of interventions, particularly in controlled trials [ 20 ].

Special emphasis was given to variables tested as formal mediators of changes in the outcomes of interest, as this provides the best possible inferences regarding causal determinants of behavior change [ 73 ]; to the extent a consistent mediator is identified, it can more confidently be targeted in future interventions of comparable characteristics. Moreover, because it is unlikely that any single factor (self-regulatory or otherwise) by itself will explain a large share of variance of change in complex behaviors such as physical activity and diet (as a result of an intervention), the identification of groups of significant predictors, which can be then discussed in the context of current theories of behavior change, can additionally contribute to understanding the role of theory in health behavior change [ 74 , 75 ].

As in many systematic reviews of behavior change interventions, the diversity of studies available - reflected on a similarly diverse set of independent (and dependent) variables, study designs, measurement methods, populations represented, and so forth - is a substantial limitation. In the present review, the large number of predictors per study, combined with substantial heterogeneity in study length, type and format of interventions (for example, web-based, face to face, group-based), and assessments employed for each variable made the task at hand especially difficult. In this scenario, the fact that several variables were identified as predictors or, in some cases, actual mediators of intervention-related change in weight control and physical activity is encouraging. Specifically, the present review shows that positive changes in body image, in autonomous motivation for physical activity, in self-efficacy (and fewer perceived barriers), and in the use of self-regulation skills (such as self-monitoring) are promising aspects that may explain the variability of results in current lifestyle obesity treatment interventions. Increases in flexible restraint could also be in this group with respect to weight outcomes, but with lower inference. Therefore, these are currently the best evidence-based candidates to target in future individual-level, real-world interventions in this domain.

Some qualifications to the previous conclusions are of note. First, for short-term results, formal tests of mediation were only reported for one of the outcomes of interest (physical activity) and taking into account only two mediators (body image/self-worth and self-efficacy/barriers). Second, there are currently too few studies using dietary variables as outcomes to allow us to draw meaningful conclusions, and only one study tested formal mediation for both time frames. Third, the external validity of some of the reported findings, such as regarding self-regulation skills and autonomous motivation, may be limited, because these findings were derived from few studies conducted by a small number of research groups, using similar study designs.

Body image appeared important as a mechanism leading to change in body weight in several studies. Body image is a multidimensional concept [ 76 ] that depicts attitudes, perceptions, and in some cases behaviors associated with mental representations of one’s body (or some of its parts) [ 77 , 78 ]. Poor body image often reflects a high level of concern with body weight or shape, what is known as dysfunctional investment in body image, when body esteem occupies an excessive role as a determinant of overall self-esteem [ 79 ]. Previous reviews [ 2 , 22 ] have identified poor body image as a predictor of less success at body weight loss (or, conversely, better body image as a positive factor in obesity treatment interventions). Potential reasons for this association range from excessive psychological pressure leading to more rigid and inconsistent eating regulation [ 80 - 82 ] - poor body image being associated with a history of failed attempts and thus being a marker for other physiological, psychological, or socio-environmental risk factors for weight gain/regain [ 83 , 84 ] - to motivational factors in which external pressures and goals predominate but tend not to produce behavior change in consistent or healthy ways (for example, wanting to be thin for reasons related to social comparison and perceived desirability) [ 85 - 87 ].

Autonomous motivation, a concept derived from self-determination theory (SDT, [ 88 ]), generally indicates the degree to which individuals self-endorse, feel that they have a choice about, and attribute deeply reflected value to a certain behavior. In contrast with the most common quantitative view of motivation (how much?), the level of autonomy represents a qualitative analysis of people’s psychological energy to act, which is perceived as internal (reflecting a sense of “ownership” over the behavior). Autonomous motivation is often associated with goals such as pursuing positive personal challenges, attaining/preserving health and well-being, social affiliation, personal development, and self-expression [ 89 ]. Additionally, because self-determined, well-internalized behaviors are associated with the satisfaction of the needs for autonomy, competence, and relatedness - and with the feelings of internal coherence and well-being that are thought to emerge from those experiences - this provides an explanation for the behavior to be pursued consistently [ 89 ]. A recent meta-analysis [ 90 ] and other reviews provide empirical support for both the SDT motivation model and the association of autonomous motivation with health behavior change in different areas [ 91 ].

Self-efficacy and perceived barriers are common variables in several theoretical frameworks concerned with health behaviors [ 92 , 93 ]. Self-efficacy measures one’s confidence to successfully implement a course of action by successfully organizing internal and external resources [ 94 ]. Although efficacy can be assessed towards other aspects of behavior regulation, it is commonly conceptualized and assessed as “barriers efficacy” or confidence to overcome internal or external obstacles that may stand in the way of one’s actions. Indeed, the correlation between self-efficacy and perceived barriers is usually high [ 56 ] (which explains our decision to group these variables in the same category). Although conceptual differences exist, self-efficacy is often equated to the concept of perceived behavior control (from the theory of planned behavior) or perceived competence (as used in self-determination theory). In practical and simple terms, enhancing confidence and competence about a given health behavior appears to be helpful in overcoming barriers - namely in initial stages of adoption - and is often a first step to increase and improve motivation for change.

Flexible eating restraint involves regulating one’s food intake so that no particular behavior is forbidden and thus subject to rigid control and scrutiny [ 95 ]. Flexible restraint is generally associated with less internal pressure to diet and a more gradual understanding of the diet’s impact on energy balance. It stands in opposition to rigid restraint [ 96 ]. Although, in the past, cognitive restraint was measured as a unified concept, its separation into flexible and rigid dimensions is increasingly frequent in obesity studies and has proven useful in understanding diet and weight regulation, particularly in the long-term. For example, we found that flexible, but not rigid or total restraint, mediated 24-month weight loss in overweight women [ 39 ] and, in the present review, results for the total restraint scale and the flexible scale also differed, as in other studies [ 97 ]. More broadly, psychological flexibility appears to predict health and psychological well-being [ 97 ], is thought to reflect more committed, values-based goal pursuit [ 98 , 99 ] and is considered a hallmark of self-determination [ 89 ], factors which may help explain successful health behavior self-regulation.

Finally, the use of certain self-regulation skills, for instance, monitoring weight, diet, and activity, as well as employing goal setting and planning techniques, was also identified as a relatively consistent predictor of successful outcomes, most especially in the shorter-term analyses. In brief, some of these skills may be important for people to ultimately act on their positive intentions. Sometimes associated with self-regulation theories ( cf . [ 100 ]) these variables are more skill-based (in some cases, they are discrete behaviors in themselves) and somewhat different than the previous set of predictors, more intrapsychic. Notably, recent behavior change models focusing on the “intention-behavior gap” (see, for example, [ 7 , 101 , 102 ]) make the distinction between motivational and implementation phases (sometimes referred to as “volitional” or “post-motivational”), with self-regulation skills reviewed in the present study falling in the latter phase [ 103 ]. Results from the present review suggest that some combination of motivational and implementation factors is important. Although this needs confirmation, there is some indication that the latter may be especially useful in early stages of behavioral adoption, whereas motivational factors may be operative along the entire continuum from adoption to maintenance, as highlighted recently in a separate study [ 104 ].

In looking at the collective findings from the present analysis, the temptation to interpret them in an integrative way is unavoidable. In principle, there should be “a logic” as to why this set of predictors emerged and not a different one, even considering the intrinsic limitations of the available data (see below). In this exercise, we are informed by our own research, for instance, linking improved eating regulation, including flexible eating, with improved body image [ 105 ] and with exercise autonomous motivation [ 18 ] and also by other studies. For example, recently, in a large dataset of women in New Zealand, autonomous motivation for eating was associated with less binge eating and slower speed of eating (and a much healthier diet), indicative of improved eating self-regulation [ 106 ]. The literature looking at relations between body image and eating behavior is also fertile in suggesting a close association between improved body image, improved eating regulation, and better weight control (see, for example, [ 55 , 87 ]). In this respect, an attempt was recently made to provide an integrative view of eating regulation and weight maintenance, which also includes an explanation for the etiology and role of body image concerns and disordered eating, while considering motivational and self-regulatory aspects [ 80 ]. It links goals (such as appearance versus health focus) and the predominant approach to eating regulation (such as rigid versus flexible restraint; focus on quality versus quantity) with the satisfaction of the needs for competence, autonomy, and relatedness, resulting in more or less adaptive diet and weight regulation (see Figures one and two in [ 80 ] for more details). The evidence from other recent systematic reviews and meta-analyses, showing that more autonomous forms of health behavior regulation, in physical activity [ 91 ], weight control [ 2 ], and in health more generally [ 90 ] are predictive of better adherence and improved outcomes, is also consistent with the relationships found in the present study.

While some limitations of the present work have been presented above, others need to be considered when interpreting the findings of this review. The large heterogeneity in the study-specific mediation methods and estimates reported in the primary studies prevented us from deriving a single comparable estimate for each variable and reporting on the pooled magnitude of mediation effects. This variability, as well as the limited number of studies for each mediator, did not recommend the use of meta-analytical techniques to pool data across studies. In this review, we used a narrative synthesis approach including vote counting of the number of significant mediation effects for a given variable in relation to all tests of mediation available for that variable. Although this method is not as robust as other quantitative approaches to synthesize data, it provides a reasonably good indication of whether that variable can be identified as a formal mediator (or a variable consistent with mediation) of each intervention, for each specific outcome. It should also be considered that in the primary studies included in this review, statistical significance of the mediation effects was typically the parameter used to infer that a given variable mediated the intervention effect.

Some studies were characterized by poor methodological quality, and none of the studies employing formal mediation analysis presented strong methodological quality. Nonetheless, for most mediators we did not find an association between the methodological quality of the studies and the direction/strength of the effects reported. As exceptions, we did find that in the analyses in which eating disinhibition had consistent significant effects, this was tested mostly in studies of poor quality. A similar result was found for self-regulation skills for the long-term effects in physical activity and dietary intake. Future reviews would benefit from sensitivity analyses. The diversity of outcome measures, especially for physical activity, is also a limitation, as different types of physical activity may be predicted by different factors. The fact that the coding of study characteristics was based on the description provided in the articles is also limiting, given that in many cases these descriptions did not provide enough information regarding mediation analysis, which measures were used, or the content of the interventions. Future studies should provide more detail on the content of the interventions and self-regulation factors addressed to facilitate data interpretation and inference. The choice of the year 2000 to start our search was largely arbitrary and could be seen as a limitation. Finally, the inclusion of non-controlled trials in some of the analyses could be viewed as a limiting factor; on balance, we found this an acceptable compromise (for non-mediation studies only) against the prospect of altogether excluding several studies from this review.

These limitations notwithstanding, this study identified a small number of intervention-related aspects with supporting evidence for an important role played in the difficult path of successful weight control. Since all evidence was derived from intervention studies and independent variables were analyzed as to their mediating position in the behavioral causal chain (although with variable levels of inference), we believe this is a first step leading to their formal inclusion in recommendations for lifestyle programs aiming at weight control. In practical terms, this could mean that strategies or “behavior change techniques” [ 107 ] identified as the most effective to specifically change these variables (for example, self-efficacy [ 108 ] or autonomous motivation [ 109 ]) would be integrated into future interventions in a widespread fashion, and that health professionals would be appropriately trained on how to target them regularly in their practices. It could also mean that bedside instruments (such as brief questionnaires or interview items) would be made available for professionals to quickly assess their patients for these variables (for example, to assess their body image or level of self-regulation skill use [ 1 , 110 ]) and tailor interventions to the most relevant targets for each person. In the area of motivation enhancement, the techniques and instruments used in motivational interviewing [ 111 , 112 ] are a good example of such potential application in medicine and health care.

In conclusion, based on the scientific literature to date, autonomous motivation, self-efficacy, and self-regulation skill use emerge as the most promising individual-level mediators of positive weight outcomes and increased physical activity. For long-term weight control, promoting a positive body image and flexible eating control may also be important. These aspects represent potential entry points for future lifestyle obesity interventions in adults.

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Acknowledgements

This work is part of the SPOTLIGHT project and is funded by the Seventh Framework Program (CORDIS FP7) of the European Commission, HEALTH (FP7-HEALTH-2011-two-stage), Grant agreement no. 278186. The content of this article reflects only the authors’ views, and the European Commission is not liable for any use that may be made of the information contained therein.

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Pedro J Teixeira, Eliana V Carraça & Marta M Marques

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PJT, JB, JL, JMO, HR, and IB conceived the study, and PJT and EVC developed a systematic review protocol. EVC and MM conducted the literature search and selected the studies based on the title and the abstract. EVC and MM extracted and coded the data from all studies. Study outcomes were summarized by PJT, EVC, and MM. They wrote the initial draft of the manuscript, and JB, JL, JMO, HR, and IB made significant revisions and contributions. All authors read and approved the final manuscript.

Additional files

Additional file 1:.

An Example of the Conducted Search (Medline).

Additional file 2:

Characteristics of Included Studies With Formal Mediation Analyses.

Additional file 3:

Characteristics of Included Studies Without Formal Mediation Analyses.

Additional file 4:

Indirect effects’ estimates in studies with formal mediation analysis.

Additional file 5:

EPHPP Quality Assessment Tool (adapted by the SPOTLIGHT Consortium).

Additional file 6:

Complete results for weight change, physical activity and dietary behaviors.

Additional file 7:

Consensus Ratings of Methodological Study Quality.

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Teixeira, P.J., Carraça, E.V., Marques, M.M. et al. Successful behavior change in obesity interventions in adults: a systematic review of self-regulation mediators. BMC Med 13 , 84 (2015). https://doi.org/10.1186/s12916-015-0323-6

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Volume 18 Supplement 1

My Body is Fit and Fabulous at home (MyBFF@home)

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An update on obesity research pattern among adults in Malaysia: a scoping review

• Noor Safiza Mohamad Nor 1 ,
• Rashidah Ambak 1 ,
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• Nur Shahida Abdul Aziz 1 ,
• Siew Man Cheong 1 ,
• Mohamad Aznuddin Abd Razak 1 ,
• Muslimah Yusof 1 ,
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• Azli Baharuddin 1 ,
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• Wan Nur Khairunnisa Wan Kozil 1 ,
• Intan Hafizah Ishak 1 &
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Metrics details

Obesity is a global health burden in the non-communicable diseases and much efforts have been implemented in the past decade in response to the rise of obesity prevalence among the Malaysian population. These include the development of the national policies, health programmes and research activities. The main aim of the scoping review was to identify obesity research pattern among adults in Malaysia in terms of the scopes, topics and the research designs.

The scoping review was conducted based on the framework by Arksey and O’Malley. The Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) diagram was used as a guide to record the review process. Articles from year 2008 until 2017 on overweight and obesity among adults aged 18 years and above were retrieved based on the keywords using electronic databases (Embase/Ovid, Pubmed, Cochrane library and Google Scholar). Local journals, Nutrition Research in Malaysia Biblography (2011 and 2016), online local theses databases, virtual library databases were also included in the searches. Consultations with relevant key informants from the National Institutes of Health and local universities were also conducted. Search activities were managed using Endnote software and MS Excelsheet.

The characteristics of the results were described based on the objectives of the review. A total of 2004 articles and reports were retrieved, and 188 articles related to obesity in Malaysia were included in the final review. Scopes and topics of obesity research based on the Nutrition Research Priorities in Malaysia (NRPM) for 11th Malaysia Plan were obesity prevalence, weight loss intervention, association of physical activities and dietary factors with obesity. The majority of obesity research among adults in Malaysia was cross sectional studies and only a small number of intervention studies, qualitative studies and systematic review were indentified. Research gaps were identified in order to make useful recommendations to the stakeholders.

Conclusions

In the past decade, there has been an emerging evidence on obesity research among adults in Malaysia. More obesity research needs to be conducted particularly on obesity intervention among specific gender, qualitative studies, economic cost and genetic factors of obesity.

Obesity is a global problem in both developing and developed countries, and has become a leading health burden in the Non-Communicable Diseases (NCD). In the past five years, the prevalence of obesity among adults in Malaysia showed a continuing increase of the problem, although a slower increament rate has been reported by the National Health and Morbidity Survey Malaysia (NHMS) 2011 and 2015 [ 1 , 2 ]. The NHMS reported the prevalence of overweight among adult in Malaysia was 29.4% (NHMS 2011) and 30.0% (NHMS 2015), while obesity prevalence was 15.1% and 17.7% respectively [ 1 , 2 ]. In response to the rise of obesity problem in Malaysia, various efforts and strategies have been implemented in the past decade to combat this problem. These include a new national nutrition policy and strategies, dietary guidelines, healthy lifestyle campaigns and the development of the Nutrition Research Priorities in Malaysia.

In 2014, the Institute for Public Health conducted a dialogue on obesity research to discuss the magnitude of obesity problem and categories of obesity research conducted by various institutions including from the Ministry of Health, the National Institues of Health and local universities [ 3 ]. The majority of topics for obesity research among adults in Malaysia were conducted by the researchers and students at local universities and these included risk factors of obesity, disease related with obesity, perception and body image among obese women, obesity metabolic pathway, obesity biomarkers and knowledge, attitude and practice (KAP). Issues and challenges in conducting obesity research were also highlighted in the research dialogue in terms of the research design, sub population and gap between research and practice.

Following the research dialogue activity, the National Research Priority Malaysia (NRPM) for 11th Malaysia Plan was developed in 2016 under the National Coordinating Committee on Food and Nutrition (NCCFN). Prior to this, the NRPM for 10th Malaysia Plan (2011-2015) was used by the researchers and the programme managers to address the research gap in nutrition [ 4 ]. In the latest NRPM (2016-2025), the Technical Working Group on Nutrition Research (TWGNR) has identified 14 scopes of overweight and obesity research priority area with the focus to improve understanding on the epidemiolgy of obesity, effectiveness of the intervention, management of obesity and developing new modalities. To date, evidence on obesity research conducted among adults based on the current NRPM framework is still not known. Therefore, the aims of the present review were to identify various topics of obesity research in Malaysia corresponding to the NRPM conceptual framework, and to make future recommendations on potential future research topics and research design in obesity.

Scoping review was applied for this topic with the aim to map the profile of obesity research among adults in Malaysia, which will also allows researchers to identify potential future topics on systematic review and meta analysis in obesity. Scoping review has a similar process as systematic review in identifying the literature or evidence, but scoping review seeks to map the evidence comprehensively rather than to analyse the specific outcomes based on specific questions as in the systematic review. In the present review, adults were defined as respondents aged 18 years old and above, which also include the elderly population. Obesity research was defined as any types of study related to the scope and area of overweight and obesity problems. The conduct of the scoping review utilised an established scoping review framework by Arksey and O’ Malley [ 5 ]. The systematic approach to searching, screening and reporting process of the scoping review was enhanced using the current recommendations by Levac, Colqohoun and O’ Brien [ 6 ]. Six stages in the scoping review framework were applied, which included (1) identifying the research question, (2) identifying relevant studies, (3) study selection, (4) charting the data, (5) collating, summarising and reporting the results and (6) consultation with the stakeholders and experts in obesity [ 5 ].

Identifying the research question

The present scoping review sought to answer the following research questions:

What are the characteristics of obesity research among adult in Malaysia in the past 10 years ago in terms of:

the number of research conducted in Malaysia

research design and methodology (qualitative and quantitative studies)

scope and topics of overweight and obesity research according to the purpose and scope of the NRPM for 11 th Malaysia Plan,

What are the research gap in obesity research in Malaysia and what are the future potential research in obesity?

The conceptual framework on the purpose and scope for obesity research priority area in the NRPM for 11 th Malaysia Plan was used to guide the researchers in the review process and data charting (Fig. 1 ). Fourteen scopes in the NRPM 2016 were used to map the evidence according to the topics listed in each research scope.

Conceptual framework on obesity research priorities in Malaysia for 11 th Malaysia Plan (2016-2025)

Identifying relevant studies

A comprehensive search to identify primary studies, reviews, grey literature (including technical reports) on obesity from January 2008 to December 2017 was performed using different resources. These included different electronic databases (Embase, Ovid, Pubmed, Cochrane Library, Google Scholar). Manual searches of the local journals and journal supplements related to obesity studies in Malaysia, Malaysia Nutrition Research Biblography (1985-2010 and 2011-2014), online local theses databases were conducted to maximise the search activities. The library databases and manual searching for dissertations/theses at local universities, relevant websites (World Health Organisations, Ministry of Health Malaysia Virtual Library, Malaysian Research Institute of Ageing) were also used to identify relevant studies. Subject headings, list of keywords and synonyms (obesity, overweight, obesity research, adults, Malaysia) were developed as search terms by the research team members, in order to capture potential studies in the resources (see Additional file 1 ). The search strategy was developed based on the search terms by the experienced researcher and the research librarian supported the search activities. Boolean operators (OR, AND, NOT) including adjacencies and truncations were used to combine the keywords and related terms during the literature search.

Study selection

Inclusion criteria for the search were published articles from 2008 to December 2017 related to obesity research among Malaysians aged 18 years and above (adult and elderly). These included articles from primary studies, technical reports and review articles (systematic review or narrative review). Language limit was applied whereby Malay and English language articles were selected. Selection of articles were performed in two stages. In the first stage, researchers (working in pairs) independently screened the titles and abstracts of all resources based on the inclusion criteria and search terms. The Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) diagram (2009) was used as a guide to record the review process [ 7 ]. Selected titles and abstracts were then screened and checked whether the content potentially answered the review questions. Irrelevant abstracts were excluded and the researchers then retrieved full articles of the selected abstracts.

In the second stage, full articles were screened to identify items related to the objectives of the review. Similar to the first stage, each pair (2 researchers) independently reviewed the full articles if they meet the objectives of the review. Data from both researchers were also compared to ensure the consistency of the review and any discrepencies between the reviewers were discussed. Articles were excluded if they are not relevant and did not describe the characteristics of obesity research in Malaysia and the objectives of the review. Relevant articles were then assessed in order to the answer the review questions. The results from the search were managed using the Endnote X5 software and extracted data from the full articles were documented in the Microsoft Excel spreadsheet.

Charting the data

Based on the conceptual framework on the purpose and scope for obesity research priority area in the NRPM 2016, the researchers developed a standard charting table to categorise the research topics according to the main three domains ( stated as purposes in the NRPM 2016) and these included (A) Improve understanding on the epidemiology of obesity; (B) Improve effectiveness of intervention and management of obesity; and (C) Developing new modalities. The charting table was piloted on 50 articles to ensure the standardised process of charting was applied and common understanding between the researchers on the category of the obesity research topics. General and specific information of the studies were included in the charting table such as author(s), year of publication, objectives or aims of the study, study location and settings, study population (male and/or female adult or elderly), study design and sample size. Emerging topics which was not captured in the charting process were compiled and collated into a new domain as ‘other scopes’.

Collating,summarising and reporting the results

The results of the extracted data were analysed using descriptive statistics (e.g. percentage) to provide summary characteristics of the studies based on the number and types of studies according to the scopes of obesity research. Data were presented using table of findings based on the characteristics of the studies and the NPRM 2016 framework. The quality of articles were not assessed as it is outside the scope of the present scoping review. Several limitations of the studies were also gathered in order to address the research gap and to make useful recommendations for future research in obesity.

Consultation with programme managers and experts in obesity

We also conducted consultations with relevant key informants from the Obesity Research Dialoge 2014 to provide insights and additional resources on obesity research and the direction of future research in obesity. These included researchers and experts from the local universities, National Institutes of Health (Institute for Public Heath, Institute for Medical Research, Clinical Research Centre, Institute for Behavioural Research, Institute for Health Management & Institute for Health System Research), Nutrition Division MOH, Nursing Division MOH, Allied Health Division MOH, Non-Communicable Disease Division MOH, Chairperson of the Technical Working Group for Nutrition Research (NPANM) MOH and the president of the Malaysian Association for Study of Obesity (MASO). The appraisal of the quality of each article was not included, in line with the guideline of the scoping review conduct [ 6 ].

A total of 2004 titles and abstracts were screened at Stage 1 and after screening and removal of the duplicates, 338 potentially relevant full-text papers were included (Fig. 2 ). 150 full articles were then excluded due to several reasons. These include articles not related to human studies, studies were conducted among adolescent population, studies focusing on other aspects such as cognitive or visual impairment among elderly, prevalence of underweight, dietary intake and studies on food and nutrient components. Following this, 188 documents were included in the charting process and the characteristics of the studies are shown in Table 1 . Full list of 188 articles were shown in Additional file 1 .

Details of study flow in the different stages of the review

In terms of the number of publications, there was an upward trend of publication in obesity research from year 2011 to 2014 (2011 ( n =12), 2012 ( n =29), 2013 ( n =32), 2014 ( n =34)), whereby 34 articles related to obesity were published in 2014 and there was a slight decreased trend of the number of publications from year 2015 to December 2017.Sample size of studies ranged from 50–100,000 respondents due to different methodology conducted for particular studies. Table 1 shows that the majority of studies (78.7%) were cross sectional studies and other studies included were cohort, obesity intervention, biomarkers, qualitative studies and systematic review. Almost 93% of studies conducted were among the adults and only 14 articles related to obesity among the elderly population [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ].

The National Health Morbidity Surveys (NHMS 2011, NHMS 2015) recruited a large scale of respondents around 16,800 adults and reported the prevalence of obesity and overweight among Malaysians adults by age, sex and ethnicity [ 1 , 2 ]. In the NHMS 2011 and NHMS 2015, the decline of overweight and obesity problems among elderly aged 60 years and above was also reported [ 1 , 2 ]. Under the umbrella of the NHMS the prevalence of obesity among adult was also reported in the Malaysian Adults Nutrition Survey 2014 (MANS) [ 23 ]. Another nationwide study was The Malaysian Cohort (TMC), which reported the prevalence of obesity among multi ethnic urban and rural Malaysians. This prospective study of the non-communicable diseases was initiated in 2005 by the researchers from the National University of Malaysia [ 24 ] and more than 100,000 respondents involved in this study. The baseline prevalence of obesity identified from the current cohort was 17.7%.

The majority of obesity research publication in Malaysia were quantitative studies. Out of 188, only three (3) articles on qualitative studies were retrieved (Abdul Aziz et al. [ 25 ], Muda et al. [ 26 ] and Chang et al. [ 27 ]). These studies explored different aspects of obesity problems which include perspectives among women on obesity problems, perceived barriers to weight loss, quality of life and associated factors to reduce weight among overweight and obese homemakers/housewives. Meanwhile, 22 articles related to obesity gene and biomarkers were found to be useful for future direction of obesity research. Majority of these articles were published from a single study among Malay adults in Pahang. The researchers investigated the role of Melanocortin-4 receptor (MC4R), gene variant and resistein levels with obesity [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 ]. The details of several studies and the key findings were highlighted in Table 2 .

Only five (5) review articles were identified, which inclusive of 3 systematic reviews on obesity and metabolic syndrome [ 50 , 51 , 52 ], and 2 narrative reviews [ 53 , 54 ] and Kambalia [ 50 ] described the trend of obesity and overweight among adults in Malaysia from 1996-2009, whereby women have a greater risk for overweight and obesity compared to men. Ng et al. [ 51 ] reported a national prevalence of obesity in Malaysia using a systematic analysis for the Global Burden of Disease data. They found that Malaysia has the highest prevalence of overweight and obese compared to other neighbouring countries. Meanwhile, Lim and Cheah [ 53 ] reported a review on metabolic syndrome research in Malaysia and the authors stated that there was an emerging evidence on metabolic syndrome among the Malaysian adults. The latest publication by Lim [ 54 ] in his narrative review described a comprehensive obesity research profile in Malaysia from 1999 until 2015, comprising of the prevalence of obesity according to age, sex, ethnicity, geographical variations, social and economic factors. The author also highlighted other associated risk factors of obesity, biomarkers of obesity and other diseases (metabolic syndrome, non-communicable diseases, psychiatric disorders, cancer and oral health) [ 54 ].

Two articles and 2 technical reports on the methodology and protocol related to obesity research were identified in the present review, which include the methodology of the intervention study (My Body is Fit and Fabulous at Home - MyBFF@home), the population-based longitudinal study for healthy longevity (TUA) for older adults and the dietary intervention protocol of the MyBFF@home [ 55 , 56 , 57 , 58 ].

The charting process was then continued based on 188 articles and reports using the NPRM 2016 framework table (Fig. 3 ). Based on the 3 domains of obesity research, it was found that the majority of research associated with the Domain A – Epidemiology of obesity ( n =140), followed by Domain B- Intervention and management of obesity ( n =25) and Domain C- New modalities on obesity ( n =6). There are several articles were classified as other categories ( n =17)

Number of publication on obesity research among adults in Malaysia based on the NRPM for 11 th Malaysia plan ( N =188)

Research is an important aspect of the health care system to seek answers for problems, as well as to increase the knowledge and understanding of an area or subject. The findings of the present review has several impacts on the research practice and policy. Firstly, it appears that there was an emerging trend in Malaysia on publication of obesity research in the past 10 years. Studies were conducted at different settings which include the community settings, hospital, universities and army quarters, whereby the majority of studies (more than 80%) were conducted by the researchers and the students at local universities. However, based on the NRPM framework 2016, the majority of the research conducted are related to the understanding the obesity epidemiology domain and only 22% of the publications relevant to the development of the new modalities and effectiveness of the intervention. Therefore, more research funding and support are needed to enhance the research activities related to these domains.

Secondly, researchers in Malaysia are likely to be more active in conducting cross sectional studies compared to other study designs such as RCT, case control, qualitative study including systematic reviews. It was noted that longitunidal studies reporting overweight and obesity among adults and elderly are also still very limited. Although longitudinal studies may require a bigger research fund and human resource compare to other types of study, longitundinal study is useful to set a good platform for researchers to explore various determinants and predictors related to obesity [ 59 ]. In addition, the focus of obesity research among the researchers in the MOH is more on the population-based study and one of the the studies is the NHMS, which involves a large scale of respondents in Malaysia. Since 2011, the NHMS was conducted on a yearly basis by the Institute for Public Health, MOH with different focus or health theme, whereby under the umbrella of the NHMS the Malaysian Adult Nutrition Survey (MANS) was also conducted in 2014 to focus on the nutritional status and dietary intake of the adults population in Malaysia. The obesity prevalence was captured in the Nutritional Status Module and all findings were used to support the policy makers and health programme managers in Malaysia. However, only one community- based obesity intervention study (MyBFF@home) was conducted by the MOH researchers from the Institute for Public Health. The majority of the respondents of the MyBFF@home were Malay housewives living in the low cost flats and further research on other ethnic groups are essential to evaluate the effectiveness of the weight loss intervention. There is also a need for researchers in Malaysia to focus on obesity intervention studies among different sub population especially in different ethnicity including the elderly group. Under the umbrella of the MyBFF framework, another intervention study (MyBFF@work) was also conducted and the participants were working adults (male and female workers) in the government sectors in Kelantan, Malaysia [ 60 ].

Thirdly, the present review also found that in the last 5 years, other types of obesity studies among specific group of population have emerged mainly among the indigenous group, army, university students, office workers, outpatients at the hospitals or clinics and schizophrenia patients. Despite this emerging trend, obesity research by specific gender in Malaysia is still very limited. According to Kanter and Caballero [ 61 ], global gender disparities between obese male and obese female occurred. In the developing countries, change in occupation has decreased the physical activity level among women compared to men, and underemployment may be associated to obesity problems among women [ 61 ]. Therefore research to investigate possible socioculturals factors including the occupation status among women in Malaysia are needed to support the obesity intervention programme and the national policies. Articles on narrative and systematic review have also emerged and these types of articles provide a useful insight on obesity trend in Malaysia including the prevalence of metabolic syndrome among the adult population. Based on the NRPM framework, a small number of specific research areas was identified in the past 10 years related to obesity in early life, obesity policy and novel research in obesity. These include articles on obesity intervention, perspectives on obesity, metabolic syndrome and obesity biomarkers. In the charting process, no articles were found on the impact of policies and environment on obesity, and also the economic and social cost of obesity in Malaysia. Therefore, research in these specific areas is important to be conducted in the near future. The economic cost and the health care cost of obesity is substantial and according to Wang and Brownell (2005), the indirects costs caused by the obesity problems in the United States contributed to 10% of lost in the work productivity [ 62 ]. Similar aspects should be explored by the researchers in Malaysia in order to assess the economic and social cost of obesity among the adults population.

Lastly, there were some challenges and limitations of this scoping review. The current scoping review only report the characteristics of obesity research by the number of publications but not the actual number of studies conducted by the researchers. For example, some authors published several articles based on the same study. In the present scoping review we have identified 8 articles on biomarkers from only 2 studies. This shows that although there are several publications on obesity biomarkers, the actual study conducted in Malaysia is still very limited. There were also several articles which are categorised as ‘others’, whereby these studies are not included as part of the research NRPM framework. The research team members have worked closely in the categorisation process of the topics to ensure the accurate information was gathered and included in the particular domain. The depth of the literature relevant to the context of the current review was also extensive and requires an expert in research methodology. To ensure the standardised process of data extraction, research team members with diverse experience in different areas contributed to different levels in the screening and selection process of the articles.

In the light of well established nutrition research framework for obesity in Malaysia, various research topics and publications on obesity in Malaysia have been identified over the past decade. However, focused of the studies in the last 10 years were more on the epidemiology of obesity rather than other categories of obesity research. More research funding is needed to support other research categories such as intervention study, obesity biomarker, cohort study and RCT. The present scoping review was also able to synthesise evidence based on the NRPNM framework. Based on the framework, research is warranted for 2 important research domains on the impact of policies and environment on obesity, and also the economic and social cost of obesity in Malaysia. Findings of this review could support the researchers and the policy makers to make informed decisions about the most appropriate study design on future topics related to obesity.

Abbreviations

National Health and Morbidity Survey

Ministry of Health Malaysia

Malaysian Adult Nutrition Survey

National Research Priority Malaysia

Preferred Reporting Items for Systematic Reviews and Meta Analysis

The Malaysian Cohort

Randomised Controlled Trial

My Body is Fit and Fabulous at home

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Acknowledgements

The authors would like to thank the Director General of Health Malaysia for the permission to publish this paper. The authors would also like to express their gratitude to all key informants from the Ministry of Health and local universities.

Publication of this article was sponsored by the Ministry of Health Malaysia.

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All data generated (list of 188 articles) during the present scoping review are included in this published article [Additional file 1 ].

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NSMN, RA and TA were responsible for the concept, project development and supervision. NSMN, RA, NAMZ, CSM, NSAA, MHA, AB, MAAR, MY, MRMR, WNKWK and IHI participated in the identification of relevant studies, study selection and data charting. NSMN, NAMZ, NSAA, CSM, MRMR, WNKWK and IHI collated, summarised and reported the results. All authors contributed to preparation of the manuscript, reviewing and approving the final manuscript.

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Keywords and synonyms for search strategy and Appendix 2 List of articles. (PDF 129 kb)

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Mohamad Nor, N., Ambak, R., Mohd Zaki, N. et al. An update on obesity research pattern among adults in Malaysia: a scoping review. BMC Women's Health 18 (Suppl 1), 114 (2018). https://doi.org/10.1186/s12905-018-0590-4

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Multilevel interventions to prevent and reduce obesity

1 Northwestern University Feinberg School of Medicine, Department of Preventive Medicine, 680 N Lake Shore, Suite 1400, Chicago, IL 60611, USA;

Sandra S. Albrecht

2 Columbia University Mailman School of Public Health, Department of Epidemiology, 722 W 168 th St, Room 703, New York, NY 10032, USA;

Kiarri N. Kershaw

3 Northwestern University Feinberg School of Medicine, Department of Preventive Medicine, 680 N Lake Shore, Suite 1400, Chicago, IL 60611, USA;

The complex, multilevel causes of the ongoing obesity epidemic necessitate multilevel approaches to address the problem. Accordingly, interest in multilevel obesity interventions has expanded rapidly in recent years. We conducted an updated literature review of multilevel interventions for obesity prevention and reduction. We identified six protocols and six articles on completed studies that were published between January 2016 and September 2018. Of the completed studies, four found significant intervention effects on body mass index and/or waist circumference. Two showed significant improvements in diet and two showed significant improvements in physical activity. These studies highlight the promise multilevel interventions offer for addressing obesity at the population level.

Introduction

Global data demonstrate that obesity is a growing problem affecting countries at all development levels [ 1 , 2 ]. Obesity is a major threat to public health because it increases the risk for several chronic diseases, including diabetes and cardiovascular disease. Underlying these trends are major population level shifts in intake of less healthy, low-nutrient-density foods and sugary beverages, changes in away from-home eating and snacking, and a rise in sedentary lifestyles [ 3 – 5 ]

Although obesity has been characterized as a consequence of excess energy intake over energy expenditure, it is nevertheless a complex problem affected by the interaction of biology, behavior, social and physical environments, and government policies. Social-ecological models of health promotion ( Figure 1 ) posit that factors at multiple levels influence outcomes like obesity, and that these multi-level factors interact to impact these outcomes [ 6 ]. Specifically, they emphasize the contributions of organizations and policies to behavior, while incorporating individual and interpersonal influences. The Institute of Medicine has promoted the use of an ecological approach to understanding determinants of adverse health outcomes and for effectively promoting healthful behavior change [ 7 ]. The socialecological model serves as a framework for private and public institutions around the world [ 8 , 9 ].

Social ecological model

Obesity prevention efforts have primarily targeted a single layer of influence, usually at the individual-level, though policy-level targets are increasingly being tested. However, in recognition of the multilevel nature of obesity, interest in multi-level interventions has grown substantially over the last decade. Multilevel interventions are strategies that aim to change behaviors and address health outcomes by affecting more than one level of influence within the social-ecological model. For example, multilevel interventions can include behavioral changes at home, comprehensive health education at school, and environmental changes in the community.

Only one other review to our knowledge has summarized findings from multi-level obesity prevention interventions, and it was published in 2016 [ 10 ]. Since then there have been several commentaries and guidelines written to support efforts to conduct multilevel interventions [ 11 – 15 ]. Thus, the objective of the current review was to provide an updated synthesis of the literature on multilevel interventions to address obesity, to discuss the implications of these findings, and to identify remaining gaps in our current knowledge.

The challenge with identifying multilevel interventions is that many studies do not identify themselves in that way. Thus, we used multiple strategies to identify articles. Our primary search strategy replicated the literature search approach and terms used to identify multilevel obesity interventions in the 2016 review [ 10 ] (see Steps 1 – 3 below). This approach involved using a combination of inclusion and exclusion search terms to identify studies with intervention components at more than one of the levels illustrated in Figure 1 (i.e., multilevel) that also assessed a measure of anthropometry or body composition as the outcome. Our second strategy (Step 4) involved manually searching through articles identified from other sources. Our final strategy (Step 5) involved searching for findings from incomplete trials reported in the 2016 review.

Step 1: Initial search

In our initial search, we queried the PubMed database using a combination of Medical Subject Headings (MeSH) terms and Text Word field tags relating to: 1) obesity; 2) multilevel or multicomponent approaches; and 3) environmental influences and health behavior. We restricted our search to clinical studies that were written in English and published in journal articles between January 1, 2016 and September 30, 2018. This resulted in 236 articles.

Step 2: Application of primary exclusion criteria

We used the “NOT” option in PubMed to exclude studies outside the scope of this review. These included those that focused on testing or validating statistical methodologies, specific disease conditions or treatment, smoking, meal replacement diets, or specific single food or beverage consumption. We excluded 99 articles using these criteria, resulting in 137 articles.

Step 3: Full-text review

We manually reviewed the 137 remaining articles and coded them in Excel for two inclusion criteria: anthropometry and multilevel. Body mass index or waist circumference had to be measured and the intervention had to substantially target more than one level in the social ecological model. We discarded 122 articles because they were not multilevel, and an additional 6 articles because they did not include anthropometric measures. This left 8 articles.

Step 4: Second-pass literature search

We conducted another review of articles published between January 1, 2016 and September 30, 2018 using PubMed in order to capture articles that may have been missed in Steps 1 – 3 . In this search we used keywords that included obesity-related terms (e.g., body mass index, adiposity, waist circumference, body fat percentage), diet-related terms (e.g. eating habits, health eating, junk food, fruits, vegetables), and physical activity-related terms (e.g., exercise, walking). We also filtered results to only show articles with “multilevel interventions” or “multi-level interventions” in the title and/or abstract. An initial search resulted in 61 articles. From these, titles and abstracts were reviewed, and only studies that contained relevant data to this review were included. After excluding duplicates ( n = 27), reviews ( n = 9), and irrelevant topics ( n = 20), 5 articles not identified using Steps 1 – 3 remained for full-text review. After a full-text review of these articles, we excluded two for not including anthropometric measures as an outcome. The remaining 3 were included in this review.

Step 5: Literature search of incomplete studies from 2016 review

Six of the studies published in the 2016 review did not have results at the time that article was published. Thus, we searched the literature for follow-up articles with relevant results. Through this search we identified 1 additional study.

The articles in this review include 12 trials from countries around the world including the US (6), Brazil, China, Scotland, Germany, Australia (2), and India. Half of the included articles were recently published protocols for trials that have not completed data collection [ 16 – 21 ], and the remaining six were completed studies that published obesity-related results between 2016 and 2018 [ 22 – 27 ]. Table 1 summarizes the general characteristics of the included studies, and Table 2 summarizes the intervention components.

General characteristics of multilevel obesity prevention trial protocols and completed studies published January 2016 – September 2018

Intervention overview of multilevel obesity prevention trial protocols and completed studies published January 2016 – September 2018

Abbreviations: PA=physical activity; BMI=body mass index

Most of the trial protocols were for interventions in children (PAAPAS, STRIDE, CHIRPY DRAGON, and JolinchenKids). With the exception of STRIDE, the primary setting for those interventions was the school or daycare. The three school-based interventions included educational activities to promote healthy eating and physical activity, support to help parents promote healthful behavior change at home, and modifications to the school environment to facilitate these changes (e.g., making school lunches healthier) [ 18 , 19 , 21 ]. The STRIDE intervention is distinct from the other protocols for children in that it will be a community-based intervention that has components across 4 levels [ 17 ]. The primary individual level intervention strategy will be the distribution of two comic books annually to children. These comic books will include targeted messages around healthy eating and physical activity. At the interpersonal level, families of the children will be invited to participate in an eight-week series of workshops to support healthy eating and physical activity behaviors at home. STRIDE researchers will also collaborate with schoolteachers to add educational sessions on media literacy and to offer short PA breaks during class. They will also organize several community activities including an annual Ciclovia, an event where a permit is obtained to close down the streets and community members are encouraged to engage in a variety of physical activities. They will also establish a farmers’ marker and a series of family nights where community members share a healthy meal and learn about nutrition and PA issues in their community.

Two trial protocols focused on adults. HelpMeDoIt! will intervene at the individual and interpersonal levels in a largely online setting [ 20 ]. OPREVENT2 is the only trial protocol to intervene at all levels of influence that comprise the Social Ecological Model [ 16 ]. They will establish Community Action Committees to initiate and promote policies relating to healthy eating and PA. They will modify the worksite environment to promote water consumption and PA, and they will train schoolteachers to teach children to become agents of healthful behavior change for their parents.

Completed studies

As with the protocols, most studies (5 out of 6) focused on children and adolescents. The design of four of these studies (Active Teen Leaders Avoiding Screen-time (ATLAS) Program, Healthy Caregivers-Healthy Children (HC2), Shaping Healthy Choices Program, and School-based Lifestyle Intervention Package) was similar to the school-based protocols in terms of levels of influence and general focus of each level. The fifth study in children, the Healthy Families Study [ 22 ], focused on mother-daughter pairs living in public housing developments. The individual-level intervention centered around educational training provided by lay health advisors (Healthy Living Advocates). Healthy Living Advocates also led weekly walking groups and promoted cooking demonstrations that were offered for residents every 3 months by a Registered Dietitian. The intervention public housing developments were also provided with access to healthy foods via a Fresh Truck van that sold fruits and vegetables and monthly health screenings. The Go! Program was in hospital and clinic employees at a worksite [ 23 ]. The intervention strategies centered more on modifying the cafeteria and using influential messaging and individuals to promote healthy eating and PA.

Of the six studies, four found the intervention group had better anthropometric outcomes than the control group ( Table 3 ). The magnitude of these differences ranged across the studies. Findings for obesity-related health behaviors were largely null. PA only increased in Go! Program and Heathy Families Study trials [ 22 , 23 ]. Fruit and vegetable intake increased in the Healthy Families Study trial [ 22 ], and total energy intake decreased in the School-based Lifestyle Intervention Package trial [ 27 ].

Reported results of completed multilevel obesity prevention trials published January 2016 – September 2018

Abbreviations: BMI=body mass index; F+V=fruits and vegetables; SSB=sugar-sweetened beverages; PA=physical activity

In this updated review of the current literature on multilevel obesity prevention interventions, we found 12 trials across 5 continents. The majority of the studies were in children and took place in school settings. Findings were mixed in these studies, so it remains difficult to draw conclusions as to the utility of this approach over single-level interventions. School settings are easier environments to control than community and home environments, but there is some evidence suggesting trials that integrate approaches outside of the school and in the community have a greater impact. Further work is needed with these types of study designs such as those proposed in the STRIDE protocol [ 17 ].

Several studies showed significant reductions in BMI, but the effect sizes were rather small. This is typical of multilevel interventions, particularly in the short time frames under study. However, given these interventions occur at a population level, the potential reach is greater than that of individual-level interventions. The length of time it takes for multilevel interventions to take effect, especially those with community- and policy-level components is unclear, but it is possible that effect sizes in some of these studies will grow with longer follow-up. This was the case for the multilevel intervention in North Karelia, Finland where tobacco use declined over a ten-year period after the initiation of a communitywide multilevel intervention to reduce cardiovascular disease [ 28 ]. However, funding constraints make this type of follow-up impractical for most studies. This is evidenced by the Healthy Families Study in public housing developments which was intended to last three years but was cut to one due to a loss of funding [ 22 ].

Few of the multilevel trials we reviewed included community or policy level interventions. Policy changes are challenging to incorporate into interventions because the political processes leading up to them are often unpredictable. Uncertainty around timing makes it difficult to anticipate the opportunity to include a policy level intervention component and to secure resources to fund this type of study. In addition, policy changes cannot be randomly assigned to individuals or in many cases, communities, so they require the application of different study designs and modeling approaches than traditional RCTs.

Conclusions

In summary, while there are significant challenges to successfully implementing and evaluating multilevel interventions, this review provides some evidence that this approach has the potential to effectively reduce the burden of obesity, particularly among low-income and marginalized minority populations for whom behavioral weight loss interventions have been shown to be less effective.[ 29 , 30 ] More training and resources are needed to support the development of multi-disciplinary teams equipped to design and model the complexities underlying these types of interventions. Systems science and simulation modeling approaches have the potential to guide some of the planning of these studies, and time-sensitive funding mechanisms could help better equip researchers to design interventions around natural experiments.

Acknowledgements

This research was funded by the National Heart, Lung, and Blood Institute (NHLBI) grant number K01HL133531.

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