literature review about obesity

• Etiology of Obesity (M Rosenbaum, Section Editor)
• Published: 01 September 2020

A Review of Obesity, Physical Activity, and Cardiovascular Disease

• Andrew Elagizi   ORCID: orcid.org/0000-0002-9316-4260 1 ,
• Sergey Kachur 1 ,
• Salvatore Carbone 2 ,
• Carl J. Lavie 1 &
• Steven N. Blair 3  

Current Obesity Reports volume  9 ,  pages 571–581 ( 2020 ) Cite this article

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Purpose of Review

The focus of this review is to discuss obesity, physical activity (and physical inactivity/sedentary behavior), cardiovascular disease (CVD), and their often interrelated health implications. The authors summarize the pathophysiological changes associated with obesity, which lead to the development of CVD, recommendations for interventions such as diet, increased physical activity, and weight loss according to current literature and guidelines, and the critical importance of cardiorespiratory fitness (CRF).

Recent Findings

Clinical trials continue to demonstrate improved outcomes among overweight or obese individuals who achieve a healthy weight using various methods. Increasing CRF levels appears to demonstrate the largest health improvements, regardless of underlying comorbidities or achieving weight loss.

CRF, which is perhaps the single most important predictor of overall health, seems more important than weight loss alone regarding improved CVD outcomes in the obese population. These findings are reproduced in studies involving patients with various forms of CVD and CVD risk factors. The importance of CRF is well established; future endeavors to establish specific CRF targets for various patient cohorts are needed.

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Abbreviations

American College of Cardiology

• Atrial fibrillation

American Heart Association

Body mass index

• Coronary artery disease
• Cardiorespiratory fitness

Cardiovascular

• Cardiovascular disease

Department of Health and Human Services

Diabetes mellitus

• Heart failure

Hypertension

Metabolic equivalent

Metabolic syndrome

Metabolically healthy obesity

Myocardial infarction

• Physical activity

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

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Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School-the University of Queensland School of Medicine, 1514 Jefferson Highway, New Orleans, LA, 70121-2483, USA

Andrew Elagizi, Sergey Kachur & Carl J. Lavie

Department of Kinesiology & Health Sciences, College of Humanities & Sciences, Virginia Commonwealth University, Richmond, VA, USA

Salvatore Carbone

Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA

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Salvatore Carbone is supported by a Career Development Award 19CDA34660318 from the American Heart Association.

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• Obesity and sedentary behavior are leading preventable causes of CVD and mortality.

• Increasing fitness levels appears to be the most effective way to improve outcomes in obese populations, both with and without CVD, compared with weight loss alone.

• Understanding that individuals may respond very differently to the same diet can help patients and clinicians avoid “diet centrism.”

This article is part of the Topical Collection on Etiology of Obesity

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Elagizi, A., Kachur, S., Carbone, S. et al. A Review of Obesity, Physical Activity, and Cardiovascular Disease. Curr Obes Rep 9 , 571–581 (2020). https://doi.org/10.1007/s13679-020-00403-z

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Published : 01 September 2020

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Obesity prevention and the role of hospital and community-based health services: a scoping review

• Claire Pearce   ORCID: orcid.org/0000-0003-2129-467X 1 , 2 , 3 ,
• Lucie Rychetnik 1 , 2 , 4 ,
• Sonia Wutzke 1   an1 &
• Andrew Wilson 1 , 2  

BMC Health Services Research volume  19 , Article number:  453 ( 2019 ) Cite this article

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Control of obesity is an important priority to reduce the burden of chronic disease. Clinical guidelines focus on the role of primary healthcare in obesity prevention. The purpose of this scoping review is to examine what the published literature indicates about the role of hospital and community based health services in adult obesity prevention in order to map the evidence and identify gaps in existing research.

Databases were searched for articles published in English between 2006 and 2016 and screened against inclusion and exclusion criteria. Further papers were highlighted through a manual search of the reference lists. Included papers evaluated interventions aimed at preventing overweight and obesity in adults that were implemented within and/or by hospital and community health services; were an empirical description of obesity prevention within a health setting or reported health staff perceptions of obesity and obesity prevention.

The evidence supports screening for obesity of all healthcare patients, combined with referral to appropriate intervention services but indicates that health professionals do not typically adopt this practice. As well as practical issues such as time and resourcing, implementation is impacted by health professionals’ views about the causes of obesity and doubts about the benefits of the health sector intervening once someone is already obese. As well as lacking confidence or knowledge about how to integrate prevention into clinical care, health professional judgements about who might benefit from prevention and negative views about effectiveness of prevention hinder the implementation of practice guidelines. This is compounded by an often prevailing view that preventing obesity is a matter of personal responsibility and choice.

Conclusions

This review highlights that whilst a population health approach is important to address the complexity of obesity, it is important that the remit of health services is extended beyond medical treatment to incorporate obesity prevention through screening and referral. Further research into the role of health services in obesity prevention should take a systems approach to examine how health service structures, policy and practice interrelationships, and service delivery boundaries, processes and perspectives impact on changing models of care.

Peer Review reports

Chronic diseases place a significant burden on the Australian healthcare system. They account for 90% of all deaths [ 1 ] and significantly reduce quality of life [ 2 ]. Being obese is a major risk factor for many chronic diseases including heart disease, cancer, kidney failure, pulmonary disease and diabetes [ 3 , 4 ]. Being overweight can impede the management of chronic conditions and is the second highest contributor to burden of disease. Obesity has been shown to reduce quality-adjusted life expectancy [ 5 ].

The World Health Organisation (WHO) highlights prevention of obesity as an important priority to reduce the impact of non-communicable disease. Both supporting people who are currently overweight to attain modest weight loss as well as preventing further increases in weight may eventually see a decrease in overall rates of obesity and a reduction in the rates of chronic diseases [ 6 ] and therefore a decrease in associated costs [ 7 ].

International guidelines recommend that preventive care be provided across the whole health system, integrated into ‘curative’ or disease management focused consultations, regardless of age or health status [ 8 ]. For obesity prevention, there are specific guidelines for the role of the general practitioner, for example the Royal Australian College of General Practitioners ‘Guidelines for preventive activities in general practice’ [ 9 ]. However, the prevention role of hospital and community health services is not as clearly articulated, particularly in relation to an adult population.

In this research we present a review of published literature investigating the role of hospital and community based health services in adult obesity prevention. The aim is to improve understanding of the role for hospital and community based health services in prevention as well as the potential enablers and barriers to the delivery of preventive health services in order to inform future research to support the development of obesity prevention guidelines applicable to a range of health service settings.

A scoping review [ 10 ] was conducted to map evidence and identify gaps in the extent, range, and nature of research undertaken in relation to the role of health services in obesity prevention. The focus of the review was on hospital and community based health services as unlike primary care, the roles of these services in obesity prevention are not clearly outlined in clinical guidelines.

Research question

The overarching question for this scoping study was: What does the peer reviewed literature reveal about the role of adult health services (excluding general practice) in the provision of obesity prevention and what are the key elements of implementation?

Data sources and search

Three databases (CINAHL and Medline concurrently and PubMed) were searched for references containing the words “obese” AND “prevent*” AND “healthcare/ health services” AND “adult”. Medline and CINAHL were searched concurrently to cover medical, nursing and allied health research. PubMed was searched to pick up those articles not yet assigned MESH headings. For practical reasons, the scope was limited to articles published in English between 2006 and 2016 (November). The Cochrane database was searched using the phrase “Prevention of overweight and obesity” to include systematic reviews conducted in the last 10 years.

Inclusion and exclusion criteria

As the aim of the review was to highlight clinical interventions as well as issues relating to implementation, papers were included if they fell into any of the following categories: (1) Evaluation of a specific hospital or community health based obesity prevention intervention; (2) Clinical guidelines featuring obesity prevention; (3) Systematic or scoping reviews of health service based obesity prevention or (4) Empirical description of obesity prevention within a health setting. A fifth category was identified in the process of undertaking the review: (5) Health staff or health service consumer perceptions of and beliefs about obesity and obesity prevention. For each of these categories, the focus of the intervention was on services for adults. We included primary studies as well as literature reviews.

Articles that were excluded were those that:

focused on prevention of childhood obesity;

were medical treatments aimed solely at weight loss, such as surgical or pharmaceutical interventions;

described an intervention that did not take place in a health setting or if that setting was focused solely on the role of general practitioners.

Papers were also excluded if they described obesity or associated disease but did not focus on interventions with a goal of prevention or if the focus was on population health initiatives that were not within the remit of health services, such as introducing food taxes. Opinion pieces and editorials were not included.

Data extraction

All articles were reviewed and divided into the categories described above. Information was summarised using a standardised extraction form developed for the review (see Tables  1 , 2 , 3 , 4 , 5 ) to identify the clinical areas where prevention is effective and the fundamental elements of implementation.

The primary aim of analysis was to determine the main factors in delivering adult obesity prevention within a health setting. Analysis commenced with an examination of intervention type, sample size, setting and duration. Studies were then grouped into categories that were empirically derived from the type of studies identified as summarised in Tables  1 , 2 , 3 , 4 , 5 . Analysis has been framed with the 5As framework [ 9 ] which is utilised as a preventative healthcare tool to identify risk factors for chronic disease. It originated as a smoking cessation tool but has been adapted for use with obesity.

Literature search

An initial PubMed search using the search terms “obese” AND “prevent*” AND “healthcare/ health services” AND “adult”, produced 710 articles. The first 40 of these articles were screened and found to be highly irrelevant. Subsequently, the PubMed search was changed to a title search “The Role of Health Services in the Prevention of Overweight and Obesity in Adults”. This produced 240 references, which on initial scan appeared to highlight more relevant documents. CINAHL and Medline searches using the same search terms produced 584 articles which on screening appeared to hold relevant studies. The Cochrane database search resulted in 151 references.

All references were then screened for duplicates before being assessed against the specific inclusion/ exclusion criteria. Further references were highlighted through a manual search of the reference list of those references which met the inclusion criteria. In all, 43 articles were included for review. Figure  1 presents the review flow chart.

Scoping review flow chart

Scope of literature by category

Of the 43 papers included in the review, seven were primary studies of a specific health based obesity prevention intervention (Category 1) and seven were scoping or systematic reviews of specific health based obesity prevention interventions (Category 2). Four clinical guidelines were included (Category 3); two specific to the Australian context [ 9 , 41 ], one from the United States [ 42 ] and one from the United Kingdom [ 43 ]. One guideline, the Royal Australian Council of General Practitioners (RACGP) Red Book [ 44 ] focussed on primary healthcare but was included as it does examine implementation of the 5As framework. This framework is frequently utilised in preventive care and though most commonly used in primary care, is one which is applicable to a range of health services. The other three focus on primary healthcare, but also consider other health services. A group of 12 papers (Category 4) provided general descriptions of obesity prevention interventions within health settings. Thirteen papers (Category 5) surveyed health professionals or consumers about their perceptions or knowledge of obesity and/or obesity prevention. A summary of the papers in each category, and the extracted data can be found in Tables  1 , 2 , 3 , 4 , 5 .

How the 5A framework informs obesity prevention

The specific health based obesity prevention interventions (Category 1 and 2), were examined using the 5As framework [ 44 ]. The 5As framework is used to identify risk factors for chronic disease, including obesity, and to plan interventions to take into account the behavioural and physiological elements to be addressed [ 45 ]. The 5As refer to Ask (about risk factors); Assess (level of risk factors, health literacy and readiness to change); Advise/ Agree (use motivational interviewing to agree goals); Assist (develop a plan to address goals) and Arrange (organise support to achieve goals and maintain change) [ 44 ].

Whilst not all the papers explicitly referred to the 5As, elements of the framework were noted in each of the seven primary studies and three of the six literature reviews concerned with health service based prevention interventions. In the section below we apply the 5A framework to consider different elements of obesity prevention and how these have been reported in the literature.

Ask and assess

For this review, Ask and Assess have been considered together as both focus on gathering the initial information which will determine the next step. A focus on screening is supported by evidence which shows that weighing people and discussing the risks associated with putting on excess weight has an impact on individual knowledge and readiness for change which are basic factors if obesity prevention is to be effective [ 36 , 46 ]. The US Preventive Task Force and the National Heart, Lung, and Blood Institute guidelines recommend health services screen all adults for obesity [ 42 ].

Screening should include not only identifying risk factors but also ascertaining if a person is wanting to make changes to address the risk factors and their ability to do so based on factors such as health literacy, which is an individual’s ability to understand, interpret and apply information to their own health and healthcare [ 47 ]. In the included studies, there was a focus on determining risk factors but not on establishing an individual’s health literacy. The seven evaluation based papers identified a need to assess for obesity risk factors and the potential impact of these on health but only one [ 12 ] specifically concluded that there is a need to train staff in issues such as health literacy and readiness for change. This factor was missing all together from the systematic review summarising best practice in applying the framework [ 23 ].

All the primary study papers (Category 1) concluded that there is a role for health professionals in the provision of prevention advice and five of these seven studies discussed providing specific training to support this role [ 12 , 13 , 15 , 16 , 17 ]. However, targeted training does not automatically change practice. Two studies, one with community health staff and one with mental health clinicians, found that training changed practice in terms of assessment of risk factors but did not change practice in relation to providing advice [ 16 , 17 ]. In studies which reported that clinicians did provide advice, in most cases patients could recall that advice but these papers did not report on whether the people receiving the advice changed their behaviour or on the long term retention of that advice [ 11 , 12 , 13 , 15 ]. One systematic review [ 23 ] framed ‘advise’ in terms of telling people they needed to lose weight and how they should do that on the basis that sustained weight loss has the most significant impact on health. It did not consider supporting people to set their own goals around their weight or risk factors. The remaining six literature reviews did not report on health professionals providing advice.

The next step of the 5As framework is providing intervention aimed at assisting people to set goals to self-manage lifestyle changes. The primary studies (category 1) did not address this element, instead framing the role of health services not as providing support but instead referring to other agencies to provide this support. One literature review concluded that intensive long term support was required to assist people to embed changes but did not provide specific details of what this might look like [ 23 ]. Another concluded that assisting people to set goals related to weight management achieves better outcomes than linking goals to more general improvements in health [ 20 ]. The remaining literature reviews did not address the ‘assist’ element.

The final step of the 5As framework recommends providing support to help people achieve and maintain their weight goals. Three of the Category 1 health service evaluations focussed specifically on this step. All were unsuccessful in increasing health professional’s rate of referral to support services. [ 15 , 16 , 17 ]. For example, a recent study undertaken across several community health centres focussed on supporting community health staff to incorporate assessment, brief advice and referral in relation to addressing chronic disease risk factors, including obesity risk factors. The intervention was well supported over the 12 months of implementation by a range of initiatives including pre-intervention policy change, electronic resources and staff training. The intervention was successful in getting staff to undertake more assessments for risk factors but did not change practice in relation to brief advice or referral for intervention [ 17 ] . Similar results were obtained within a community mental health setting, concluding that even when clinical guidelines explicitly direct clinicians to incorporate preventive care into interactions, rates of care given around issues such as fruit and vegetable intake or physical activity remain low [ 16 ]. The study concluded that prevention may need to be delivered within a different model of care [ 16 ]. Two of the systematic reviews concluded that successful obesity prevention needs to include the provision of or referral to intensive, multicomponent behavioural interventions which aim to support weight loss and management [ 21 , 23 ].

Clinical areas in which obesity prevention may be warranted

The National Health and Medical Research Council (NHMRC) Clinical Practice Guidelines [ 6 ] identify different life stages where there is a greater risk of weight gain. The empirical studies were therefore analysed to identify the clinical areas where prevention may have the most significant impact and the specific elements key to working with these clinical groups. Fifteen of the papers included in the review focused on a particular life stage or cohort of patients. The clinical areas identified were maternity, which has received the most focus but has not been rigorously evaluated [ 13 , 14 , 26 , 27 , 31 , 33 , 34 , 36 , 48 ] and mental health [ 37 ]. Definitive evidence of how obesity prevention should be delivered in mental health services was not available.

The papers which focussed on maternity based services highlight the immediate consequences of maternal obesity including higher rates of gestational diabetes, high blood pressure and pre-eclampsia and higher risk births. Excess weight gain in pregnancy combined with not losing the weight after pregnancy are predictors of long-term maternal obesity and increases the risk of the child developing obesity whilst mothers with gestational diabetes are more likely to develop type 2 diabetes later in life [ 36 ]. Along with the individual risks to mother and child, there is an increased demand for services and a requirement for more specialised services to support woman and baby both during and after the birth [ 18 , 26 , 30 , 31 , 33 , 34 ].

Only one of the papers targeting obesity prevention in maternity care settings reported on a specific intervention. This found that women at risk of gestational diabetes who receive advice in relation to limiting weight gain during pregnancy are less likely to develop diabetes despite no significant difference in weight gain compared with a control group [ 13 ]. The other maternity focussed papers were more descriptive, providing a broad overview of implementation factors including the need for a multidisciplinary approach to reinforce the benefits of diet and physical activity beyond weight management. For example, obese pregnant women who are physically active have been shown to experience less depressive symptoms and report higher quality of life to obese women who are not physically active in pregnancy [ 14 ]. Two papers stated that discussions about safe weight gain and weight management needs to be done in a way that does not stigmatise or cause feelings of shame [ 27 , 33 ].

Only one paper looked at a life stage other than child bearing years, namely older adults [ 29 ]. This paper summarised the results of a large survey, focussing specifically on older persons’ perceptions of receiving weight management advice. As with similar studies looking at the adult population more generally [ 28 ], it was found that older adults were more likely to receive lifestyle advice if they were already obese or had a number of chronic conditions [ 29 ]. The disadvantage of many of the survey based studies was the reliance on self-reported weight and height.

In terms of specific clinical areas, studies have been conducted in mental health and community health services. It was reported that it is very difficult to change the practice of mental health staff to include a focus of physical health risk factors [ 16 ] with mental health clinicians not necessarily seeing this as their role [ 37 ] despite the fact that people with mental illness do want to reduce their risk factors [ 40 ]. Similarly in services delivering general community health care, despite the presence of risk factors and an openness by clients to receive preventive advice, community health staff do not deliver opportunistic prevention, particularly in relation to diet [ 8 , 17 ].

Perceptions and beliefs towards obesity prevention in health services

This review found that along with practical barriers to changing practice including a lack of time, resources or clinical guidelines [ 34 , 38 , 39 , 49 ], a key barrier to healthcare based obesity prevention is the perceptions and beliefs of health professionals towards obesity. As well as lacking confidence or knowledge about how to integrate prevention into clinical care, health professionals may simply not see it is their role [ 37 ]. There is also an issue with judgements being made in relation to who might benefit from prevention along with a negative view of the effectiveness of prevention, compounded by a view that preventing obesity is a matter of personal responsibility and choice [ 25 , 38 ].

The 13 studies which specifically looked at this issue are summarised in Category 5 of Tables  1 , 2 , 3 , 4 , 5 . These papers used a range of methods to ascertain attitudes, including questionnaires or surveys [ 8 , 32 , 36 , 37 , 39 , 40 , 46 , 49 , 50 ] and semi-structured interviews or focus groups [ 33 , 34 , 35 , 38 ] and were conducted with health professionals [ 33 , 34 , 35 , 37 , 38 , 39 , 49 , 50 ] and consumers [ 8 , 32 , 36 , 40 , 46 ]. Due to the range of methods and small numbers of many of the studies the results are not necessarily generalisable but a recurrence of themes indicates that perceptions and beliefs should be considered when incorporating obesity prevention into health care services.

The view of health professionals, that prevention is not their role, may be reinforced by the fact that they will probably not have had specific training in assessment and advice [ 16 ]. They may make judgements on who would benefit from preventive advice and tend to only raise the issue of weight if they know the patient [ 38 ]. Whilst health professionals are aware of the health implications of excess weight there may be a perception that they cannot be effective in their role due to a lack of patient motivation to enact change [ 25 ]. Other studies have shown that patients may not be told they are overweight or have the health consequences of being overweight discussed [ 21 , 32 ]. This is despite evidence to suggest that being told firstly they are overweight and secondly the health risks of excess weight can impact on an individual’s readiness to make changes to diet and levels of physical activity [ 28 ]. When discussions do occur, they are more likely to be with people who are already obese [ 24 , 28 ] or who have more frequent health encounters indicating that they have more complex health problems [ 29 ]. By clinicians not discussing weight and lifestyle with people before it becomes a significant problem there is a missed opportunity to prevent illness development based on known risk factors.

The uptake of prevention may also be impacted by a view that obesity is an issue of lifestyle choice and personal responsibility and therefore not the responsibility of health services unless linked to the treatment of a specific clinical condition [ 35 , 38 ]. Clinical guidelines may not be consistently followed because of a lack of knowledge of the guidelines existence or a belief that the guidelines will be ineffective due to pre-conceived ideas about the group of clients being targeted or a lack of confidence in the guidelines [ 19 , 35 ] . Specific to maternity services, clinicians acknowledge that weight gain in pregnancy is an issue but do not perceive that their patients see it as a problem [ 30 ]. In some instances, health professionals don’t feel confident talking to their patients about excess weight [ 35 , 38 , 39 , 51 ]. These findings occur even in areas where policy is in place directing clinicians to incorporate prevention, highlighting the need for more comprehensive, multi component change management strategies to enable health professionals to develop their practice to incorporate prevention routinely into interventions [ 8 ].

Without further training, baseline knowledge on appropriate interventions to support obesity prevention is generally poor [ 39 ] and advice may be given based on the clinicians own experience of weight management [ 38 ]. Educating staff about prevention may lead to an increase in assessment of risk but not a significant increase in brief advice or referral to other services for prevention intervention [ 15 , 17 ]. Both of these later elements are key to impacting on an individual’s chronic disease risk profile [ 16 ]. Training of staff may need to extend beyond principles of prevention and also include training on communicating complex information to people with low health literacy. This should include teaching techniques to ensure health professionals clarify their patient has understood information, [ 12 ] as this is a significant element in someone being able to adopt and follow preventive care advice [ 45 ].

However, the evidence of what education strategies are most effective, particularly in relation to increasing assessment and referral across all risk factors, is limited [ 52 ]. A systematic review of interventions to change the behaviour of health professionals found just six randomised control trials and the combined results of these were ambiguous [ 19 ]. When specifically looking at factors influencing health professionals decision to provide counselling regarding physical activity, the health professionals own levels of physical activity, whether or not they have specific training, knowing the patient well and the patient having risk factors for chronic disease were all influencing factors [ 22 ].

This review examined the literature in order to ascertain the role of hospital and community- based health services in adult obesity prevention as well as the potential enablers and barriers to the delivery of preventive health services. Whilst it is acknowledged that the health care system alone is not the answer to reducing the population impact of obesity [ 53 ], there is evidence that health services can significantly contribute to obesity prevention commencing with screening all patients for risk factors and providing brief advice. This should be followed up with referral to a service which provides long term follow-up with a focus on lifestyle change rather than just weight loss and should include consideration of an individual’s health literacy [ 41 , 42 , 43 , 44 ].

However, the reviewed evidence indicates that existing clinical guidelines, including the application of the 5As framework, are not being fully implemented. Where training and resources have focussed on prevention, there is an increase in the rate of screening provided but only a limited change in the rates of brief advice or referral to an intervention service [ 12 , 15 , 16 , 17 ]. Whilst assessment of risk factors may offer some benefits, greater change is achieved when this is followed up by advice and clear, individualised input to assist people to apply the advice to their own circumstances [ 54 ].

In taking a scoping approach to the role of health services, this review was able to draw out that a significant barrier to the implementation of prevention guidelines are the perceptions of health professionals. They may not see prevention as their role [ 16 ], make judgements about the causes of and responsibility for an individual’s weight, or make subjective decisions about who will benefit from their advice [ 25 , 35 , 38 ]. Health professionals may also not feel sufficiently confident to raise the issue of weight because of the social meanings attached or lack of knowledge [ 35 , 38 , 39 , 51 ]. Our review reveals these issues are common to nursing, allied health and medical staff.

Health care is predominantly delivered within a reactive model of care which is at odds with the concept of prevention [ 55 ]. Whilst there are obesity prevention guidelines which highlight the need to apply a framework such as the 5As, this fundamentally linear tool is designed to work within a traditional health care approach which focusses on the diagnosis and treatment of acute disease. As has been shown by this review, health professionals’ willingness or ability to change practice may be influenced by a range of factors, including their personal perceptions of obesity and of the potential value of prevention. So, whilst at a macro level policy and guidelines may be in place, implementation is hindered at a meso level by the mismatch between the medical model and the multifactorial causes of obesity and at a micro level by the impact of personal beliefs on patient interaction. Each of the factors dynamically influence the others so need should not be considered in isolation [ 53 ].

Changing the health system to implement effective action for the prevention of obesity therefore calls for an examination of the issues through a systems lens rather than taking a simple problem-solution driven approach. Health services are a complex system, constituted of a range of people, processes, activities, settings and structures. The interrelationships, boundaries, processes and perspectives connect in dynamic and non-linear ways which may result in emergent self-organised behaviour [ 56 ]. Importantly it should be acknowledged that systems are often nested within other systems with their own dynamics at play. Consequently, a search for solutions means identifying multiple causes as well as multiple points for intervention and being aware of unintended consequences [ 2 , 57 ]. The studies identified by this review focussed on a linear approach to implementing guidelines or examined the perspectives of just one clinical team or group within a system. There is a need for research to be undertaken which, using a systems approach, examines the opportunities and threats to prevention from the perspective of a range of players within the system and considers how these perspectives might be influenced by policy and guidelines, as well as each other. This could include looking at moving beyond traditional structural boundaries to look at alternative models of care to the medical model including the use of support roles outside of those typically considered to be health professionals, particularly in the role of ongoing support [ 56 , 58 ].

Obesity is often described as a ‘wicked’ problem due to the multifactorial causes requiring complex solutions. Whilst a population health approach is important to address this complexity, it is important that the remit of health services is extended beyond medical treatment to incorporate obesity prevention. [ 59 ]. Though this scoping review has demonstrated that there is evidence for incorporating obesity prevention into clinical care, research to date has taken a linear approach to the implementation of guidelines without explicitly factoring in the impact of the perceptions of clinicians and managers to the prevention role or addressing the individual responsibility discourse. Further research into the role of health services in obesity prevention should take a systems approach to examine the impacts of changing models of care whilst also taking into account the perceptions of health staff towards obesity and obesity prevention and the breadth of issues impacting on each individual’s ability to make lifestyle changes.

Strengths and limitations of the reviews

This review contributes to an understanding of the role of health services in obesity prevention by specifically focussing on services outside of primary health. The use of a scoping review allowed for broad coverage of the literature in order that the main issues could be highlighted in order to inform health policy, clinical practice and future research. The broad aims of the review may impact on attempts to replicate the review. Limiting the review to English language references may have excluded some evidence.

Availability of data and materials

Not applicable

Abbreviations

National Health and Medical Research Council

Royal Australian College of General Practitioners

World Health Organisation

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Acknowledgements

The primary author, Claire Pearce, receives a scholarship from the Australian Prevention Partnership Centre (TAPPC) to support her PhD candidacy. The co-authors all have an affiliation with TAPPC. The funding body was not involved directly in the design or completion of the study or in the writing of the manuscript.

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Claire Pearce, Lucie Rychetnik, Sonia Wutzke & Andrew Wilson

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CP conceived the study, screened citations and full-text articles, analysed and interpreted the data, and wrote and edited the manuscript. LR reviewed the analysis.

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The lived experience of people with obesity: study protocol for a systematic review and synthesis of qualitative studies

• Emma Farrell   ORCID: orcid.org/0000-0002-7780-9428 1 ,
• Marta Bustillo 2 ,
• Carel W. le Roux 3 ,
• Joe Nadglowski 4 ,
• Eva Hollmann 1 &
• Deirdre McGillicuddy 1  

Systematic Reviews volume  10 , Article number:  181 ( 2021 ) Cite this article

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Obesity is a prevalent, complex, progressive and relapsing chronic disease characterised by abnormal or excessive body fat that impairs health and quality of life. It affects more than 650 million adults worldwide and is associated with a range of health complications. Qualitative research plays a key role in understanding patient experiences and the factors that facilitate or hinder the effectiveness of health interventions. This review aims to systematically locate, assess and synthesise qualitative studies in order to develop a more comprehensive understanding of the lived experience of people with obesity.

This is a protocol for a qualitative evidence synthesis of the lived experience of people with obesity. A defined search strategy will be employed in conducting a comprehensive literature search of the following databases: PubMed, Embase, PsycInfo, PsycArticles and Dimensions (from 2011 onwards). Qualitative studies focusing on the lived experience of adults with obesity (BMI >30) will be included. Two reviewers will independently screen all citations, abstracts and full-text articles and abstract data. The quality of included studies will be appraised using the critical appraisal skills programme (CASP) criteria. Thematic synthesis will be conducted on all of the included studies. Confidence in the review findings will be assessed using GRADE CERQual.

The findings from this synthesis will be used to inform the EU Innovative Medicines Initiative (IMI)-funded SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) study. The objective of SOPHIA is to optimise future obesity treatment and stimulate a new narrative, understanding and vocabulary around obesity as a set of complex and chronic diseases. The findings will also be useful to health care providers and policy makers who seek to understand the experience of those with obesity.

Systematic review registration

PROSPERO CRD42020214560 .

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Obesity is a complex chronic disease in which abnormal or excess body fat (adiposity) impairs health and quality of life, increases the risk of long-term medical complications and reduces lifespan [ 1 ]. Operationally defined in epidemiological and population studies as a body mass index (BMI) greater than or equal to 30, obesity affects more than 650 million adults worldwide [ 2 ]. Its prevalence has almost tripled between 1975 and 2016, and, globally, there are now more people with obesity than people classified as underweight [ 2 ].

Obesity is caused by the complex interplay of multiple genetic, metabolic, behavioural and environmental factors, with the latter thought to be the proximate factor which enabled the substantial rise in the prevalence of obesity in recent decades [ 3 , 4 ]. This increased prevalence has resulted in obesity becoming a major public health issue with a resulting growth in health care and economic costs [ 5 , 6 ]. At a population level, health complications from excess body fat increase as BMI increases [ 7 ]. At the individual level, health complications occur due to a variety of factors such as distribution of adiposity, environment, genetic, biologic and socioeconomic factors [ 8 ]. These health complications include type 2 diabetes [ 9 ], gallbladder disease [ 10 ] and non-alcoholic fatty liver disease [ 11 ]. Excess body fat can also place an individual at increased cardiometabolic and cancer risk [ 12 , 13 , 14 ] with an estimated 20% of all cancers attributed to obesity [ 15 ].

Although first recognised as a disease by the American Medical Association in 2013 [ 16 ], the dominant cultural narrative continues to present obesity as a failure of willpower. People with obesity are positioned as personally responsible for their weight. This, combined with the moralisation of health behaviours and the widespread association between thinness, self-control and success, has resulted in those who fail to live up to this cultural ideal being subject to weight bias, stigma and discrimination [ 17 , 18 , 19 ]. Weight bias, stigma and discrimination have been found to contribute, independent of weight or BMI, to increased morbidity or mortality [ 20 ].

Thomas et al. [ 21 ] highlighted, more than a decade ago, the need to rethink how we approach obesity so as not to perpetuate damaging stereotypes at a societal level. Obesity research then, as now, largely focused on measurable outcomes and quantifiable terms such as body mass index [ 22 , 23 ]. Qualitative research approaches play a key role in understanding patient experiences, how factors facilitate or hinder the effectiveness of interventions and how the processes of interventions are perceived and implemented by users [ 24 ]. Studies adopting qualitative approaches have been shown to deliver a greater depth of understanding of complex and socially mediated diseases such as obesity [ 25 ]. In spite of an increasing recognition of the integral role of patient experience in health research [ 25 , 26 ], the voices of patients remain largely underrepresented in obesity research [ 27 , 28 ].

Systematic reviews and syntheses of qualitative studies are recognised as a useful contribution to evidence and policy development [ 29 ]. To the best of the authors’ knowledge, this will be the first systematic review and synthesis of qualitative studies focusing on the lived experience of people with obesity. While systematic reviews have been carried out on patient experiences of treatments such as behavioural management [ 30 ] and bariatric surgery [ 31 ], this review and synthesis will be the first to focus on the experience of living with obesity rather than patient experiences of particular treatments or interventions. This focus represents a growing awareness that ‘patients have a specific expertise and knowledge derived from lived experience’ and that understanding lived experience can help ‘make healthcare both effective and more efficient’ [ 32 ].

This paper outlines a protocol for the systematic review of qualitative studies based on the lived experience of people with obesity. The findings of this review will be synthesised in order to develop an overview of the lived experience of patients with obesity. It will look, in particular, at patient concerns around the risks of obesity and their aspirations for response to obesity treatment.

The review protocol has been registered within the PROSPERO database (registration number: CRD42020214560) and is being reported in accordance with the reporting guidance provided in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement [ 33 , 34 ] (see checklist in Additional file  1 ).

Information sources and search strategy

The primary source of literature will be a structured search of the following electronic databases (from January 2011 onwards—to encompass the increase in research focused on patient experience observed over the last 10 years): PubMed, Embase, PsycInfo, PsycArticles and Dimensions. There is no methodological agreement as to how many search terms or databases out to be searched as part of a ‘good’ qualitative synthesis (Toye et al. [ 35 ]). However, the breadth and depth of the search terms, the inclusion of clinical and personal language and the variety within the selected databases, which cover areas such as medicine, nursing, psychology and sociology, will position this qualitative synthesis as comprehensive. Grey literature will not be included in this study as its purpose is to conduct a comprehensive review of peer-reviewed primary research. The study’s patient advisory board will be consulted at each stage of the review process, and content experts and authors who are prolific in the field will be contacted. The literature searches will be designed and conducted by the review team which includes an experienced university librarian (MB) following the methodological guidance of chapter two of the JBI Manual for Evidence Synthesis [ 36 ]. The search will include a broad range of terms and keywords related to obesity and qualitative research. A full draft search strategy for PubMed is provided in Additional file  2 .

Eligibility criteria

Studies based on primary data generated with adults with obesity (operationally defined as BMI >30) and focusing on their lived experience will be eligible for inclusion in this synthesis (Table  1 ). The context can include any country and all three levels of care provision (primary, secondary and tertiary). Only peer-reviewed, English language, articles will be included. Studies adopting a qualitative design, such as phenomenology, grounded theory or ethnography, and employing qualitative methods of data collection and analysis, such as interviews, focus groups, life histories and thematic analysis, will be included. Publications with a specific focus, for example, patient’s experience of bariatric surgery, will be included, as well as studies adopting a more general view of the experience of obesity.

Screening and study selection process

Search results will be imported to Endnote X9, and duplicate entries will be removed. Covidence [ 38 ] will be used to screen references with two reviewers (EF and EH) removing entries that are clearly unrelated to the research question. Titles and abstracts will then be independently screened by two reviewers (EF and EH) according to the inclusion criteria (Table  1 ). Any disagreements will be resolved through a third reviewer (DMcG). This layer of screening will determine which publications will be eligible for independent full-text review by two reviewers (EF and EH) with disagreements again being resolved by a third reviewer (DMcG).

Data extraction

Data will be extracted independently by two researchers (EF and EH) and combined in table format using the following headings: author, year, title, country, research aims, participant characteristics, method of data collection, method of data analysis, author conclusions and qualitative themes. In the case of insufficient or unclear information in a potentially eligible article, the authors will be contacted by email to obtain or confirm data, and a timeframe of 3 weeks to reply will be offered before article exclusion.

Quality appraisal of included studies

This qualitative synthesis will facilitate the development of a conceptual understanding of obesity and will be used to inform the development of policy and practice. As such, it is important that the studies included are themselves of suitable quality. The methodological quality of all included studies will be assessed using the critical appraisal skills programme (CASP) checklist, and studies that are deemed of insufficient quality will be excluded. The CASP checklist for qualitative research comprises ten questions that cover three main issues: Are the results of the study under review valid? What are the results? Will the results help locally? Two reviewers (EF and EH) will independently evaluate each study using the checklist with a third and fourth reviewer (DMcG and MB) available for consultation in the event of disagreement.

Data synthesis

The data generated through the systematic review outlined above will be synthesised using thematic synthesis as described by Thomas and Harden [ 39 ]. Thematic synthesis enables researchers to stay ‘close’ to the data of primary studies, synthesise them in a transparent way and produce new concepts and hypotheses. This inductive approach is useful for drawing inference based on common themes from studies with different designs and perspectives. Thematic synthesis is made up of a three-step process. Step one consists of line by line coding of the findings of primary studies. The second step involves organising these ‘free codes’ into related areas to construct ‘descriptive’ themes. In step three, the descriptive themes that emerged will be iteratively examined and compared to ‘go beyond’ the descriptive themes and the content of the initial studies. This step will generate analytical themes that will provide new insights related to the topic under review.

Data will be coded using NVivo 12. In order to increase the confirmability of the analysis, studies will be reviewed independently by two reviewers (EF and EH) following the three-step process outlined above. This process will be overseen by a third reviewer (DMcG). In order to increase the credibility of the findings, an overview of the results will be brought to a panel of patient representatives for discussion. Direct quotations from participants in the primary studies will be italicised and indented to distinguish them from author interpretations.

Assessment of confidence in the review findings

Confidence in the evidence generated as a result of this qualitative synthesis will be assessed using the Grading of Recommendations Assessment, Development and Evaluation Confidence in Evidence from Reviews of Qualitative Research (GRADE CERQual) [ 40 ] approach. Four components contribute to the assessment of confidence in the evidence: methodological limitations, relevance, coherence and adequacy of data. The methodological limitations of included studies will be examined using the CASP tool. Relevance assesses the degree to which the evidence from the primary studies applies to the synthesis question while coherence assesses how well the findings are supported by the primary studies. Adequacy of data assesses how much data supports a finding and how rich this data is. Confidence in the evidence will be independently assessed by two reviewers (EF and EH), graded as high, moderate or low, and discussed collectively amongst the research team.

Reflexivity

For the purposes of transparency and reflexivity, it will be important to consider the findings of the qualitative synthesis and how these are reached, in the context of researchers’ worldviews and experiences (Larkin et al, 2019). Authors have backgrounds in health science (EF and EH), education (DMcG and EF), nursing (EH), sociology (DMcG), philosophy (EF) and information science (MB). Prior to conducting the qualitative synthesis, the authors will examine and discuss their preconceptions and beliefs surrounding the subject under study and consider the relevance of these preconceptions during each stage of analysis.

Dissemination of findings

Findings from the qualitative synthesis will be disseminated through publications in peer-reviewed journals, a comprehensive and in-depth project report and presentation at peer-reviewed academic conferences (such as EASO) within the field of obesity research. It is also envisaged that the qualitative synthesis will contribute to the shared value analysis to be undertaken with key stakeholders (including patients, clinicians, payers, policy makers, regulators and industry) within the broader study which seeks to create a new narrative around obesity diagnosis and treatment by foregrounding patient experiences and voice(s). This synthesis will be disseminated to the 29 project partners through oral presentations at management board meetings and at the general assembly. It will also be presented as an educational resource for clinicians to contribute to an improved understanding of patient experience of living with obesity.

Obesity is a complex chronic disease which increases the risk of long-term medical complications and a reduced quality of life. It affects a significant proportion of the world’s population and is a major public health concern. Obesity is the result of a complex interplay of multiple factors including genetic, metabolic, behavioural and environmental factors. In spite of this complexity, obesity is often construed in simple terms as a failure of willpower. People with obesity are subject to weight bias, stigma and discrimination which in themselves result in increased risk of mobility or mortality. Research in the area of obesity has tended towards measurable outcomes and quantitative variables that fail to capture the complexity associated with the experience of obesity. A need to rethink how we approach obesity has been identified—one that represents the voices and experiences of people living with obesity. This paper outlines a protocol for the systematic review of available literature on the lived experience of people with obesity and the synthesis of these findings in order to develop an understanding of patient experiences, their concerns regarding the risks associated with obesity and their aspirations for response to obesity treatment. Its main strengths will be the breadth of its search remit—focusing on the experiences of people with obesity rather than their experience of a particular treatment or intervention. It will also involve people living with obesity and its findings disseminated amongst the 29 international partners SOPHIA research consortium, in peer reviewed journals and at academic conferences. Just as the study’s broad remit is its strength, it is also a potential challenge as it is anticipated that searchers will generate many thousands of results owing to the breadth of the search terms. However, to the best of the authors’ knowledge, this will be the first systematic review and synthesis of its kind, and its findings will contribute to shaping the optimisation of future obesity understanding and treatment.

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Abbreviations

Body mass index

Critical appraisal skills programme

Grading of Recommendations Assessment, Development and Evaluation Confidence in Evidence from Reviews of Qualitative Research

Innovative Medicines Initiative

Medical Subject Headings

Population, phenomenon of interest, context, study type

Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy

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Acknowledgements

Any amendments made to this protocol when conducting the study will be outlined in PROSPERO and reported in the final manuscript.

This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 875534. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and T1D Exchange, JDRF and Obesity Action Coalition. The funding body had no role in the design of the study and will not have a role in collection, analysis and interpretation of data or in writing the manuscript.

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Emma Farrell, Eva Hollmann & Deirdre McGillicuddy

University College Dublin Library, Dublin, Ireland

Marta Bustillo

Diabetes Complications Research Centre, University College Dublin, Dublin, Ireland

Carel W. le Roux

Obesity Action Coalition, Tampa, USA

Joe Nadglowski

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Contributions

EF conceptualised and designed the protocol with input from DMcG and MB. EF drafted the initial manuscript. EF and MB defined the concepts and search items with input from DmcG, CleR and JN. MB and EF designed and executed the search strategy. DMcG, CleR, JN and EH provided critical insights and reviewed and revised the protocol. All authors have approved and contributed to the final written manuscript.

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Correspondence to Emma Farrell .

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Supplementary Information

Additional file 1:..

PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) 2015 checklist: recommended items to address in a systematic review protocol*.

Additional file 2: Table 1

. Search PubMed search string.

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Farrell, E., Bustillo, M., le Roux, C.W. et al. The lived experience of people with obesity: study protocol for a systematic review and synthesis of qualitative studies. Syst Rev 10 , 181 (2021). https://doi.org/10.1186/s13643-021-01706-5

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Received : 28 October 2020

Accepted : 14 May 2021

Published : 21 June 2021

DOI : https://doi.org/10.1186/s13643-021-01706-5

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Effectiveness of weight management interventions for adults delivered in primary care: systematic review and meta-analysis of randomised controlled trials

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• Peer review
• Claire D Madigan , senior research associate 1 ,
• Henrietta E Graham , doctoral candidate 1 ,
• Elizabeth Sturgiss , NHMRC investigator 2 ,
• Victoria E Kettle , research associate 1 ,
• Kajal Gokal , senior research associate 1 ,
• Greg Biddle , research associate 1 ,
• Gemma M J Taylor , reader 3 ,
• Amanda J Daley , professor of behavioural medicine 1
• 1 Centre for Lifestyle Medicine and Behaviour (CLiMB), The School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
• 2 School of Primary and Allied Health Care, Monash University, Melbourne, Australia
• 3 Department of Psychology, Addiction and Mental Health Group, University of Bath, Bath, UK
• Correspondence to: C D Madigan c.madigan{at}lboro.ac.uk (or @claire_wm and @lboroclimb on Twitter)
• Accepted 26 April 2022

Objective To examine the effectiveness of behavioural weight management interventions for adults with obesity delivered in primary care.

Design Systematic review and meta-analysis of randomised controlled trials.

Eligibility criteria for selection of studies Randomised controlled trials of behavioural weight management interventions for adults with a body mass index ≥25 delivered in primary care compared with no treatment, attention control, or minimal intervention and weight change at ≥12 months follow-up.

Data sources Trials from a previous systematic review were extracted and the search completed using the Cochrane Central Register of Controlled Trials, Medline, PubMed, and PsychINFO from 1 January 2018 to 19 August 2021.

Data extraction and synthesis Two reviewers independently identified eligible studies, extracted data, and assessed risk of bias using the Cochrane risk of bias tool. Meta-analyses were conducted with random effects models, and a pooled mean difference for both weight (kg) and waist circumference (cm) were calculated.

Main outcome measures Primary outcome was weight change from baseline to 12 months. Secondary outcome was weight change from baseline to ≥24 months. Change in waist circumference was assessed at 12 months.

Results 34 trials were included: 14 were additional, from a previous review. 27 trials (n=8000) were included in the primary outcome of weight change at 12 month follow-up. The mean difference between the intervention and comparator groups at 12 months was −2.3 kg (95% confidence interval −3.0 to −1.6 kg, I 2 =88%, P<0.001), favouring the intervention group. At ≥24 months (13 trials, n=5011) the mean difference in weight change was −1.8 kg (−2.8 to −0.8 kg, I 2 =88%, P<0.001) favouring the intervention. The mean difference in waist circumference (18 trials, n=5288) was −2.5 cm (−3.2 to −1.8 cm, I 2 =69%, P<0.001) in favour of the intervention at 12 months.

Conclusions Behavioural weight management interventions for adults with obesity delivered in primary care are effective for weight loss and could be offered to members of the public.

Systematic review registration PROSPERO CRD42021275529.

Introduction

Obesity is associated with an increased risk of diseases such as cancer, type 2 diabetes, and heart disease, leading to early mortality. 1 2 3 More recently, obesity is a risk factor for worse outcomes with covid-19. 4 5 Because of this increased risk, health agencies and governments worldwide are focused on finding effective ways to help people lose weight. 6

Primary care is an ideal setting for delivering weight management services, and international guidelines recommend that doctors should opportunistically screen and encourage patients to lose weight. 7 8 On average, most people consult a primary care doctor four times yearly, providing opportunities for weight management interventions. 9 10 A systematic review of randomised controlled trials by LeBlanc et al identified behavioural interventions that could potentially be delivered in primary care, or involved referral of patients by primary care professionals, were effective for weight loss at 12-18 months follow-up (−2.4 kg, 95% confidence interval −2.9 to−1.9 kg). 11 However, this review included trials with interventions that the review authors considered directly transferrable to primary care, but not all interventions involved primary care practitioners. The review included interventions that were entirely delivered by university research employees, meaning implementation of these interventions might differ if offered in primary care, as has been the case in other implementation research of weight management interventions, where effects were smaller. 12 As many similar trials have been published after this review, an updated review would be useful to guide health policy.

We examined the effectiveness of weight loss interventions delivered in primary care on measures of body composition (weight and waist circumference). We also identified characteristics of effective weight management programmes for policy makers to consider.

This systematic review was registered on PROSPERO and is reported according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. 13 14

Eligibility criteria

We considered studies to be eligible for inclusion if they were randomised controlled trials, comprised adult participants (≥18 years), and evaluated behavioural weight management interventions delivered in primary care that focused on weight loss. A primary care setting was broadly defined as the first point of contact with the healthcare system, providing accessible, continued, comprehensive, and coordinated care, focused on long term health. 15 Delivery in primary care was defined as the majority of the intervention being delivered by medical and non-medical clinicians within the primary care setting. Table 1 lists the inclusion and exclusion criteria.

Study inclusion and exclusion criteria

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We extracted studies from the systematic review by LeBlanc et al that met our inclusion criteria. 11 We also searched the exclusions in this review because the researchers excluded interventions specifically for diabetes management, low quality trials, and only included studies from an Organisation for Economic Co-operation and Development country, limiting the scope of the findings.

We searched for studies in the Cochrane Central Register of Controlled Trials, Medline, PubMed, and PsychINFO from 1 January 2018 to 19 August 2021 (see supplementary file 1). Reference lists of previous reviews 16 17 18 19 20 21 and included trials were hand searched.

Data extraction

Results were uploaded to Covidence, 22 a software platform used for screening, and duplicates removed. Two independent reviewers screened study titles, abstracts, and full texts. Disagreements were discussed and resolved by a third reviewer. All decisions were recorded in Covidence, and reviewers were blinded to each other’s decisions. Covidence calculates proportionate agreement as a measure of inter-rater reliability, and data are reported separately by title or abstract screening and full text screening. One reviewer extracted data on study characteristics (see supplementary table 1) and two authors independently extracted data on weight outcomes. We contacted the authors of four included trials (from the updated search) for further information. 23 24 25 26

Outcomes, summary measures, and synthesis of results

The primary outcome was weight change from baseline to 12 months. Secondary outcomes were weight change from baseline to ≥24 months and from baseline to last follow-up (to include as many trials as possible), and waist circumference from baseline to 12 months. Supplementary file 2 details the prespecified subgroup analysis that we were unable to complete. The prespecified subgroup analyses that could be completed were type of healthcare professional who delivered the intervention, country, intensity of the intervention, and risk of bias rating.

Healthcare professional delivering intervention —From the data we were able to compare subgroups by type of healthcare professional: nurses, 24 26 27 28 general practitioners, 23 29 30 31 and non-medical practitioners (eg, health coaches). 32 33 34 35 36 37 38 39 Some of the interventions delivered by non-medical practitioners were supported, but not predominantly delivered, by GPs. Other interventions were delivered by a combination of several different practitioners—for example, it was not possible to determine whether a nurse or dietitian delivered the intervention. In the subgroup analysis of practitioner delivery, we refer to this group as “other.”

Country —We explored the effectiveness of interventions by country. Only countries with three or more trials were included in subgroup analyses (United Kingdom, United States, and Spain).

Intensity of interventions —As the median number of contacts was 12, we categorised intervention groups according to whether ≤11 or ≥12 contacts were required.

Risk of bias rating —Studies were classified as being at low, unclear, and high risk of bias. Risk of bias was explored as a potential influence on the results.

Meta-analyses

Meta-analyses were conducted using Review Manager 5.4. 40 As we expected the treatment effects to differ because of the diversity of intervention components and comparator conditions, we used random effects models. A pooled mean difference was calculated for each analysis, and variance in heterogeneity between studies was compared using the I 2 and τ 2 statistics. We generated funnel plots to evaluate small study effects. If more than two intervention groups existed, we divided the number of participants in the comparator group by the number of intervention groups and analysed each individually. Nine trials were cluster randomised controlled trials. The trials had adjusted their results for clustering, or adjustment had been made in the previous systematic review by LeBlanc et al. 11 One trial did not report change in weight by group. 26 We calculated the mean weight change and standard deviation using a standard formula, which imputes a correlation for the baseline and follow-up weights. 41 42 In a non-prespecified analysis, we conducted univariate and multivariable metaregression (in Stata) using a random effects model to examine the association between number of sessions and type of interventionalist on study effect estimates.

Risk of bias

Two authors independently assessed the risk of bias using the Cochrane risk of bias tool v2. 43 For incomplete outcome data we defined a high risk of bias as ≥20% attrition. Disagreements were resolved by discussion or consultation with a third author.

Patient and public involvement

The study idea was discussed with patients and members of the public. They were not, however, included in discussions about the design or conduct of the study.

The search identified 11 609 unique study titles or abstracts after duplicates were removed ( fig 1 ). After screening, 97 full text articles were assessed for eligibility. The proportionate agreement ranged from 0.94 to 1.0 for screening of titles or abstracts and was 0.84 for full text screening. Fourteen new trials met the inclusion criteria. Twenty one studies from the review by LeBlanc et al met our eligibility criteria and one study from another systematic review was considered eligible and included. 44 Some studies had follow-up studies (ie, two publications) that were found in both the second and the first search; hence the total number of trials was 34 and not 36. Of the 34 trials, 27 (n=8000 participants) were included in the primary outcome meta-analysis of weight change from baseline to 12 months, 13 (n=5011) in the secondary outcome from baseline to ≥24 months, and 30 (n=8938) in the secondary outcome for weight change from baseline to last follow-up. Baseline weight was accounted for in 18 of these trials, but in 14 24 26 29 30 31 32 44 45 46 47 48 49 50 51 it was unclear or the trials did not consider baseline weight. Eighteen trials (n=5288) were included in the analysis of change in waist circumference at 12 months.

Studies included in systematic review of effectiveness of behavioural weight management interventions in primary care. *Studies were merged in Covidence if they were from same trial

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Study characteristics

Included trials (see supplementary table 1) were individual randomised controlled trials (n=25) 24 25 26 27 28 29 32 33 34 35 38 39 41 44 45 46 47 50 51 52 53 54 55 56 59 or cluster randomised controlled trials (n=9). 23 30 31 36 37 48 49 57 58 Most were conducted in the US (n=14), 29 30 31 32 33 34 35 36 37 45 48 51 54 55 UK (n=7), 27 28 38 41 47 57 58 and Spain (n=4). 25 44 46 49 The median number of participants was 276 (range 50-864).

Four trials included only women (average 65.9% of women). 31 48 51 59 The mean BMI at baseline was 35.2 (SD 4.2) and mean age was 48 (SD 9.7) years. The interventions lasted between one session (with participants subsequently following the programme unassisted for three months) and several sessions over three years (median 12 months). The follow-up period ranged from 12 months to three years (median 12 months). Most trials excluded participants who had lost weight in the past six months and were taking drugs that affected weight.

Meta-analysis

Overall, 27 trials were included in the primary meta-analysis of weight change from baseline to 12 months. Three trials could not be included in the primary analysis as data on weight were only available at two and three years and not 12 months follow-up, but we included these trials in the secondary analyses of last follow-up and ≥24 months follow-up. 26 44 50 Four trials could not be included in the meta-analysis as they did not present data in a way that could be synthesised (ie, measures of dispersion). 25 52 53 58 The mean difference was −2.3 kg (95% confidence interval −3.0 to −1.6 kg, I 2 =88%, τ 2 =3.38; P<0.001) in favour of the intervention group ( fig 2 ). We found no evidence of publication bias (see supplementary fig 1). Absolute weight change was −3.7 (SD 6.1) kg in the intervention group and −1.4 (SD 5.5) kg in the comparator group.

Mean difference in weight at 12 months by weight management programme in primary care (intervention) or no treatment, different content, or minimal intervention (control). SD=standard deviation

Supplementary file 2 provides a summary of the main subgroup analyses.

Weight change

The mean difference in weight change at the last follow-up was −1.9 kg (95% confidence interval −2.5 to −1.3 kg, I 2 =81%, τ 2 =2.15; P<0.001). Absolute weight change was −3.2 (SD 6.4) kg in the intervention group and −1.2 (SD 6.0) kg in the comparator group (see supplementary figs 2 and 3).

At the 24 month follow-up the mean difference in weight change was −1.8 kg (−2.8 to −0.8 kg, I 2 =88%, τ 2 =3.13; P<0.001) (see supplementary fig 4). As the weight change data did not differ between the last follow-up and ≥24 months, we used the weight data from the last follow-up in subgroup analyses.

In subgroup analyses of type of interventionalist, differences were significant (P=0.005) between non-medical practitioners, GPs, nurses, and other people who delivered interventions (see supplementary fig 2).

Participants who had ≥12 contacts during interventions lost significantly more weight than those with fewer contacts (see supplementary fig 6). The association remained after adjustment for type of interventionalist.

Waist circumference

The mean difference in waist circumference was −2.5 cm (95% confidence interval −3.2 to −1.8 cm, I 2 =69%, τ 2 =1.73; P<0.001) in favour of the intervention at 12 months ( fig 3 ). Absolute changes were −3.7 cm (SD 7.8 cm) in the intervention group and −1.3 cm (SD 7.3) in the comparator group.

Mean difference in waist circumference at 12 months. SD=standard deviation

Risk of bias was considered to be low in nine trials, 24 33 34 35 39 41 47 55 56 unclear in 12 trials, 25 27 28 29 32 45 46 50 51 52 54 59 and high in 13 trials 23 26 30 31 36 37 38 44 48 49 53 57 58 ( fig 4 ). No significant (P=0.65) differences were found in subgroup analyses according to level of risk of bias from baseline to 12 months (see supplementary fig 7).

Risk of bias in included studies

Worldwide, governments are trying to find the most effective services to help people lose weight to improve the health of populations. We found weight management interventions delivered by primary care practitioners result in effective weight loss and reduction in waist circumference and these interventions should be considered part of the services offered to help people manage their weight. A greater number of contacts between patients and healthcare professionals led to more weight loss, and interventions should be designed to include at least 12 contacts (face-to-face or by telephone, or both). Evidence suggests that interventions delivered by non-medical practitioners were as effective as those delivered by GPs (both showed statistically significant weight loss). It is also possible that more contacts were made with non-medical interventionalists, which might partially explain this result, although the metaregression analysis suggested the effect remained after adjustment for type of interventionalist. Because most comparator groups had fewer contacts than intervention groups, it is not known whether the effects of the interventions are related to contact with interventionalists or to the content of the intervention itself.

Although we did not determine the costs of the programme, it is likely that interventions delivered by non-medical practitioners would be cheaper than GP and nurse led programmes. 41 Most of the interventions delivered by non-medical practitioners involved endorsement and supervision from GPs (ie, a recommendation or checking in to see how patients were progressing), and these should be considered when implementing these types of weight management interventions in primary care settings. Our findings suggest that a combination of practitioners would be most effective because GPs might not have the time for 12 consultations to support weight management.

Although the 2.3 kg greater weight loss in the intervention group may seem modest, just 2-5% in weight loss is associated with improvements in systolic blood pressure and glucose and triglyceride levels. 60 The confidence intervals suggest a potential range of weight loss and that these interventions might not provide as much benefit to those with a higher BMI. Patients might not find an average weight loss of 3.7 kg attractive, as many would prefer to lose more weight; explaining to patients the benefits of small weight losses to health would be important.

Strengths and limitations of this review

Our conclusions are based on a large sample of about 8000 participants, and 12 of these trials were published since 2018. It was occasionally difficult to distinguish who delivered the interventions and how they were implemented. We therefore made some assumptions at the screening stage about whether the interventionalists were primary care practitioners or if most of the interventions were delivered in primary care. These discussions were resolved by consensus. All included trials measured weight, and we excluded those that used self-reported data. Dropout rates are important in weight management interventions as those who do less well are less likely to be followed-up. We found that participants in trials with an attrition rate of 20% or more lost less weight and we are confident that those with high attrition rates have not inflated the results. Trials were mainly conducted in socially economic developed countries, so our findings might not be applicable to all countries. The meta-analyses showed statistically significant heterogeneity, and our prespecified subgroups analysis explained some, but not all, of the variance.

Comparison with other studies

The mean difference of −2.3 kg in favour of the intervention group at 12 months is similar to the findings in the review by LeBlanc et al, who reported a reduction of −2.4 kg in participants who received a weight management intervention in a range of settings, including primary care, universities, and the community. 11 61 This is important because the review by LeBlanc et al included interventions that were not exclusively conducted in primary care or by primary care practitioners. Trials conducted in university or hospital settings are not typically representative of primary care populations and are often more intensive than trials conducted in primary care as a result of less constraints on time. Thus, our review provides encouraging findings for the implementation of weight management interventions delivered in primary care. The findings are of a similar magnitude to those found in a trial by Ahern et al that tested primary care referral to a commercial programme, with a difference of −2.7 kg (95% confidence interval −3.9 to −1.5 kg) reported at 12 month follow-up. 62 The trial by Ahern et al also found a difference in waist circumference of −4.1 cm (95% confidence interval −5.5 to −2.3 cm) in favour of the intervention group at 12 months. Our finding was smaller at −2.5 cm (95% confidence interval −3.2 to −1.8 cm). Some evidence suggests clinical benefits from a reduction of 3 cm in waist circumference, particularly in decreased glucose levels, and the intervention groups showed a 3.7 cm absolute change in waist circumference. 63

Policy implications and conclusions

Weight management interventions delivered in primary care are effective and should be part of services offered to members of the public to help them manage weight. As about 39% of the world’s population is living with obesity, helping people to manage their weight is an enormous task. 64 Primary care offers good reach into the community as the first point of contact in the healthcare system and the remit to provide whole person care across the life course. 65 When developing weight management interventions, it is important to reflect on resource availability within primary care settings to ensure patients’ needs can be met within existing healthcare systems. 66

We did not examine the equity of interventions, but primary care interventions may offer an additional service and potentially help those who would not attend a programme delivered outside of primary care. Interventions should consist of 12 or more contacts, and these findings are based on a mixture of telephone and face-to-face sessions. Previous evidence suggests that GPs find it difficult to raise the issue of weight with patients and are pessimistic about the success of weight loss interventions. 67 Therefore, interventions should be implemented with appropriate training for primary care practitioners so that they feel confident about helping patients to manage their weight. 68

Unanswered questions and future research

A range of effective interventions are available in primary care settings to help people manage their weight, but we found substantial heterogeneity. It was beyond the scope of this systematic review to examine the specific components of the interventions that may be associated with greater weight loss, but this could be investigated by future research. We do not know whether these interventions are universally suitable and will decrease or increase health inequalities. As the data are most likely collected in trials, an individual patient meta-analysis is now needed to explore characteristics or factors that might explain the variance. Most of the interventions excluded people prescribed drugs that affect weight gain, such as antipsychotics, glucocorticoids, and some antidepressants. This population might benefit from help with managing their weight owing to the side effects of these drug classes on weight gain, although we do not know whether the weight management interventions we investigated would be effective in this population. 69

What is already known on this topic

Referral by primary care to behavioural weight management programmes is effective, but the effectiveness of weight management interventions delivered by primary care is not known

Systematic reviews have provided evidence for weight management interventions, but the latest review of primary care delivered interventions was published in 2014

Factors such as intensity and delivery mechanisms have not been investigated and could influence the effectiveness of weight management interventions delivered by primary care

What this study adds

Weight management interventions delivered by primary care are effective and can help patients to better manage their weight

At least 12 contacts (telephone or face to face) are needed to deliver weight management programmes in primary care

Some evidence suggests that weight loss after weight management interventions delivered by non-medical practitioners in primary care (often endorsed and supervised by doctors) is similar to that delivered by clinician led programmes

Ethics statements

Ethical approval.

Not required.

Data availability statement

Additional data are available in the supplementary files.

Contributors: CDM and AJD conceived the study, with support from ES. CDM conducted the search with support from HEG. CDM, AJD, ES, HEG, KG, GB, and VEK completed the screening and full text identification. CDM and VEK completed the risk of bias assessment. CDM extracted data for the primary outcome and study characteristics. HEJ, GB, and KG extracted primary outcome data. CDM completed the analysis in RevMan, and GMJT completed the metaregression analysis in Stata. CDM drafted the paper with AJD. All authors provided comments on the paper. CDM acts as guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: AJD is supported by a National Institute for Health and Care Research (NIHR) research professorship award. This research was supported by the NIHR Leicester Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. ES’s salary is supported by an investigator grant (National Health and Medical Research Council, Australia). GT is supported by a Cancer Research UK fellowship. The funders had no role in considering the study design or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: This research was supported by the National Institute for Health and Care Research Leicester Biomedical Research Centre; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.

The lead author (CDM) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported, and that no important aspects of the study have been omitted.

Dissemination to participants and related patient and public communities: We plan to disseminate these research findings to a wider community through press releases, featuring on the Centre for Lifestyle Medicine and Behaviour website ( www.lboro.ac.uk/research/climb/ ) via our policy networks, through social media platforms, and presentation at conferences.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ .

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• v.17(8); 2020 Aug

Obesity and Depression: Its Prevalence and Influence as a Prognostic Factor: A Systematic Review

Beatriz villagrasa blasco.

1 Psychogeriatry Area, Benito Menni CASM, Barcelona, Spain

Jesús García-Jiménez

2 Psychiatry Service, Hospital General Básico Santa Ana, Motril, Granada, Spain

Isabel Bodoano

3 Psychiatry Service, Virgen de las Nieves Hospital, Granada, Spain

Luis Gutiérrez-Rojas

4 Department of Psychiatry, University of Granada, Granada, Spain

5 CTS-549 Research Group, Institute of Neurosciences, University of Granada, Granada, Spain

6 Psychiatry Service, San Cecilio University Hospital, Granada, Spain

Depression and obesity are two conditions with great impact over global health. This is mainly due to their high prevalence and the morbidity and mortality associated to both. The main aim of the present systematic review is to study the association between obesity and depression and the prognostic implications derived from it.

A literature review was performed in the PUBMED database. 18 articles were found (9 cross-sectional studies, 6 longitudinal studies and 3 clinical trials), which were reviewed by critical reading after which a summary of the main conclusions was written.

These selected articles confirmed that there is indeed a link between depression and obesity, although there are doubts as to the significance of this relationship. Depression is a risk factor for obesity, especially atypical depression and in African-American adolescent males. Obesity is a risk factor for depression, especially in women and for recurrent depressive disorder. The comorbidity between obesity and depression is a risk factor for a bad prognosis illness.

The relationship between both disorders has been analysed in scientific literature, obtaining significant associations but also contradictory results. The most current data demonstrates that there is a relationship between both entities, although there is no unanimity when it comes to establishing the meaning of this association.

INTRODUCTION

Obesity and depression are considered notorious health problems, not only because of their significant prevalence but also because of their high morbidity mortality rates. According to recent data from the World Health Organization (WHO) in 2014 it was estimated that more than 600 million people were affected with obesity whilst at least 2.6 million people die from obesity every year. 44% of global cases of diabetes, 23% of ischemic heart diseases and 7–41% of certain cancers are attributable to overweight and obesity [ 1 ]. When it comes to depression the figures are no less alarming, it is estimated that depression affects 350 million people in the world, making it one of the main causes of disability and morbidity worldwide. In addition, depression is also an important cause of premature mortality, primarily due to suicide [ 2 ].

The probable association between obesity and depression has been studied repeatedly over time in scientific literature. This is mainly due to the fact that they both carry a high prevalence and an increased risk of cardiovascular disease [ 3 ]. While many cross-sectional studies have documented this relationship its significance still remains unclear.

Prospective studies have revealed inconsistent findings regarding the sequence in the onset of depression and obesity [ 4 ]. This discrepancy could be due to the methodological variation of the different studies (including variations in the sample selection) the duration of the follow-up and/or the evaluation and diagnosis of depression and obesity. The relationship between obesity and depression has also been studied in childhood and adolescence. A prospective study [ 5 ] determined that adolescent women affected with obesity predicted an increased risk of major depression (up to almost 4 times more). However this risk was not significant for men. A meta-analysis that included 8 longitudinal studies [ 6 ], concluded that there was a bidirectional relationship between depression and obesity. Thus he determined that people with obesity had a 55% increased risk of developing depression over time, and that depressed people had a 58% increased risk of obesity. In addition, the relationship between obesity and depression was stronger than the relationship between overweight and depression, which reflected a dose-response gradient.

The main objectives of this review will be three; 1) to define the methodological quality of those more recent studies that analysed the association between depression and obesity, 2) to determine whether there is indeed an association between both conditions and 3) to clarify what influence they may have over each other. Additionally it will examine the importance of certain socio-demographic, clinical and therapeutic variables in the relation between obesity and depression.

A literature review was conducted of those articles published in the PUBMED database with an inclusion deadline from January 1, 2012 to December 31, 2017, using the following MeSH terms: “obesity” AND “depressive disorder.” The filters applied were those of studies published in the last 6 years and carried out in humans. 179 articles were obtained and the main researcher (BV) made an exhaustive reading of the abstracts, selected the publications based on the inclusion criteria and was responsible for the successive stages. We follow the international recommendations for systematic reviews as Preferred Items for Reporting of Systematic Reviews and Meta-Analyses (PRISMA) [ 7 ].

The following inclusion criteria was applied: available abstract, English written articles, already established diagnostic criteria for both conditions (obesity according to body mass index (BMI) and depression according to major depression criteria in the DSM IV or ICD-10, studies of prevalence in both pathologies and finally, the evaluation of the possible prognostic association between these conditions when they affect the same person simultaneously. The exclusion criteria where the following: no available abstract, articles written in a non-English language, articles of very low quality according to the GRADE system (Grading of Recommendations, Assessment, Development and Evaluation) [ 8 , 9 ], and the failure to fulfil the objectives of the study.

The GRADE system initially classifies the evidence into high or low, coming from experimental or observational studies; subsequently and following a series of considerations (risk/benefit balance, values and preferences of the patients and professionals, and the use of resources or costs), the evidence is classified into high, moderate, low or very low [ 9 ]. In comparison with other systems, the advantages of GRADE classification includes a clear separation between quality of evidence and strength of recommendations, provide comprehensive criteria and acknowledgment of values and preferences and explicit evaluation of the importance of outcomes of alternative management strategies [ 8 ]. Finally studies which main objective was the evaluation of interventions aimed at reducing the frequency of these conditions were also excluded.

By reading the abstracts, a total of 39 articles were selected, which were then thoroughly revised, eventually discarding 21 of them for not complying with the inclusion criteria. Most of these articles were discarded for failing to adapt to the international diagnostic standards rendering it difficult to draw clear conclusions. The third stage corresponded to the critical reading of the 18 selected articles. Figure 1 summarizes each of these stages. Subsequently, the methodological quality of the 18 selected works was evaluated, for which the GRADE classification was used [ 8 , 9 ]. This system is a rigorous and transparent instrument that classifies scientific publications according to their level of evidence and determines the strength of their conclusions. There are 4 levels of quality, so that initially the publications are classified as high or low quality, depending on whether they are experimental or observational studies. In the final phase, a series of characteristics are analysed (limitations, biases and possible confusion biases among others) that allow us to sort the final classification in high, moderate, low or very low evidence level.

Flow chart of the literature search.

Different types of studies and methodological quality

Of the 18 selected studies, 15 were observational and 3 were experimental clinical trials. Within the observational group (15), 6 had a longitudinal design (one retrospective and five prospective) and the other 9 were cross-sectional. The main features as well as the evaluation of the quality of these studies are summarized in Tables 1 , ​ ,2 2 and ​ and3. 3 . The heterogeneity in the ages of the selected samples should be noted, so that four of the studies were performed in adolescents aged 11 to 17 years [ 10 - 13 ] and the other two [ 14 , 15 ] in patients aged 65 and over.

Clinical trials studying treatment of patients with obesity and depression

Longitudinal studies in patients suffering from depression and obesity

OR: odds ratio, CI: confidence interval, BMI: body mass index, RR: relative risk

Cross-sectional studies performed in patients with obesity and depression

Methodological quality of the studies ( Tables 1 , ​ ,2 2 and ​ and3) 3 ) varied between the low gradation (in the observational studies) and the moderate gradation (in the experimental ones), none of these studies reached the maximum score for they contained important methodological errors.

Depression as a risk factor for obesity

In this section we will focus on those 10 studies that studied depression as a risk factor for obesity. The conclusions here obtained were not uniform. Three of these studies [ 15 - 17 ] concluded that only atypical depression (DSM subtype) was a risk factor for obesity. However, there was no correlation between the other subtypes such as classic or melancholic depression and obesity. Others studies found an association between depressive symptoms and obesity. A higher OR was found for abdominal obesity compared to BMI >30 [ 18 ] whilst there was a higher OR in patients with obesity in comparison than those with overweight [ 19 ].

Another study focused on age and ethnicity [ 13 ], concluding that in the selected sample (African-American adolescent males), depression was a risk factor for the development of obesity. It found no association between obesity and the rest of the sample. Finally, 3 of the studies in this first section [ 13 , 20 , 21 ] did not obtain significant differences, concluding that depression was not a risk factor for obesity in the selected sample ( Figure 2 ).

Depression as a risk factor for obesity.

Obesity as a risk factor for depression

In this second section, we discovered 5 studies that concluded that obesity was a risk factor for depression. Only one of the articles could not establish a relationship between both disorders, although the conclusions must be adjusted [ 11 ]. The group of Nigatu et al. [ 20 ] selected a sample with recurrent depressive disorder and another group of participants who had suffered a single depressive episode. They found that that obesity acted as a risk factor for depression only for the group with recurrent depressive episodes. Another group analysed the association between obesity, body image and depression in a sample of more than 4,000 adolescents [ 12 ]. Although it was initially established that obesity and depression were indeed associated, this was not maintained when adjusting the results for other factors such as sociodemographic and clinical variables. Regarding sex, there is data that suggests a different obesity-depression relationship between men and women, since it was only in woman that obesity increased the risk of depression [ 22 ]. Finally, in a different work on the same sample of 4,000 adolescents [ 11 ], the authors concluded that adolescents affected with obesity did not have higher depression rates, although they did detect an increased risk of future obesity in the group of adolescents with depression ( Figure 3 ).

Obesity as a risk factor for depression.

Obesity-depression association. Prognostic implications

An overall of four articles viewed this subject. The first article [ 10 ], studied the response to fluoxetine in patients admitted to an acute care unit when diagnosed with a depressive episode. The results concluded that those participants who did not reach symptomatic remission had a higher BMI at the beginning of the treatment. A second article [ 23 ] analysed the association between obesity, depression and bipolar disorder in a population sample. They observed that patients affected with obesity that had suffered a mayor depressive episode were more likely to suffer from bipolar disorder in the future than those patients that had depression but did not suffer from obesity. The association between obesity and the response to antidepressant treatment was also studied in one of the clinical trials [ 24 ]. Patients with depression where randomly assigned to take different therapeutic options. All patients had their BMI calculated at the beginning and end of the clinical trial. There were no significant differences in the response to treatment when classified by BMI yet there was disparity in the relationship between the BMI and comorbidities. This association was studied leading to the conclusion that BMI in this sample was related to the clinical presentation of depression, with those patients with higher BMI being more prone to suffer from comorbid pathologies (medical and psychiatric, such as social phobia and bulimia). Finally, the results of a multidisciplinary and intensive treatment for depression were not related to the BMI baseline of participants according to data from another study [ 25 ].

Our chief aim when undertaking this systematic review has been to clarify the association between obesity and depression, two diseases with great impact over global health. In none of the three sections in which the selected articles have been divided (depression>risk factor>obesity, obesity>risk factor> depression and prognosis when depression and obesity are associated) have we observed unanimity in the conclusions.

In the first group (depression as risk factor for obesity) 8 out of the 11 selected articles presented data in favour of this association. We highlight the results of a clinical trial [ 26 ] in which patients with depression who took a high-fat diet had higher rates of obesity than those patients with the same diet but without depressive disorder diagnosis. However, the subtype of depression must be taken into account in order to be able to relate it to obesity. Data derived from this clinical trial revealed that it is only the subtype of atypical depression that has been statistically associated. These findings support the current trends that suggest that within the depressive syndrome there would be different entities with different features that would be influenced in different ways by other variables. Regarding this subject, one of the selected articles [ 13 ] analysed if there was an association between depression and obesity in adolescents when divided according to ethnic group and sex. They found that it was only in African-American males that depression was a risk factor for obesity; however this did not occur in the rest of the sample.

We also analysed articles that could not demonstrate a correlation between obesity and depression [ 20 ]. However, here we must point out that the methodological quality of these studies was not very high, for they did not take into account, for example, the considerable number of losses. They also failed to monitor the influence of certain important variables such as the antidepressant treatment.

In the second section there is a greater consensus when it comes to affirming that obesity increases the risk of depression. Out of the six selected articles, five concluded that there is an association between both factors. Once again, the depressive subtype, the average age of the sample and sex are variables that influenced the results. For example, according to Nigatu et al. [ 20 ] obesity would only act as a risk factor for depression in case of recurrent major depressive disorder, however for a sample of adolescents that were followed in time, there was no association between both factors [ 11 ].

In the third section we analysed the influence on the prognosis of the obesity-depression combination in the same patient. We found two clinical trials [ 10 , 24 ] that analysed this issue. There was no homogeneity in the samples, since Lin selected hospitalized patients whilst Toups worked with an ambulatory sample with comorbid anxiety disorder. While in the first article the results show that in patients affected with obesity the response to the antidepressant treatment was significantly worse, in the second article no significant associations were obtained.

It has been suggested that the association between depression and obesity is probably due to the action of certain genes involved in both pathologies. For example the genes that encode glucocorticoids, leptin and dopamine receptors. The role of environmental factors should also be noted, especially all those situations that contribute to maintaining a situation of chronic stress. The results of a study conducted on twins by Afari et al. [ 27 ] concluded that only 12% of the genetic component of depression was shared by obesity, so that environmental factors are fundamental to understand how both pathologies are related [ 28 ]. The current etiopathogenic model states that chronic stress sets in motion a series of mechanisms involving the central nervous system, the hypothalamic-pituitary-adrenal axis and the autonomic nervous system [ 29 ]. These mechanisms would then generate a pro-inflammatory state through peripheral resistance to the glucocorticoid action, intestinal bacterial translocation, increase of catecholamines and the secretion of cytokines (TNF-α and IL-6). This pro-inflammatory environment would act over white fat adipocytes leading to an inappropriate local activation, with an increase in the production of leptin and a decrease of adiponectin, causing inflammation and the accumulation of fatty tissue [ 30 ]. In addition to these local changes, inflammatory cytokines act over the central nervous system, inducing changes in synaptic plasticity and in neurogenesis that would be similar to those that occur in depression.

As previously explained, the wide methodological variety of the studies included in this review hampered the conclusion of unequivocal results. This is seen in the heterogeneity of the sample size, the design of the studies or the different instruments used to measure obesity and depression, all which could significantly influence the results. However, it can be stated that a high percentage of the analysed bibliography, demonstrates that both pathologies are associated, although in some cases it is difficult to determine the significance of this association.

Another strong point in this study is that it highlights the importance of the subtypes of depression, a feature that is not generally taken into account although there is increasing evidence that depressive disorder will bring different entities together, each with their own clinical and therapeutic characteristics. Furthermore, the influence of age, sex or ethnicity over depressive symptomatology validates the change in diagnostic manuals towards a more dimensional perspective, as well as the inclusion of sub-threshold forms of presentation associated with clinical and functional discomfort. These results highlight that the reality of the great psychiatric syndromes is probably much more complex than what it was initially believed to be.

The current systematic review has several limitations. Firstly, the articles were only reviewed by a single researcher and most of these studies were cross-sectional, rendering it impossible to obtain causality relationships from them. Following the type of design, a high percentage of the studies presented a low to moderate methodological quality according to the GRADE scale [ 8 , 9 ]. Finally, the search was carried out only in Pubmed, and although it is one of the most powerful databases to day, it is possible that additional publications collected in other bibliographic sources were not detected.

CONCLUSIONS

Obesity and depression are disorders with a high prevalence and an extraordinary effect over global morbidity and mortality. The relationship between both disorders has been analysed in scientific literature, obtaining significant associations but also contradictory results. The most current data demonstrates that there is a relationship between both entities, although there is no unanimity when it comes to establishing the meaning of this association. Certain variables such as the subtype of atypical depression, female sex, and African-American ethnicity could influence the relationship between depression and obesity thus it is advised that they be examined in future studies. The limited methodological quality of the articles included in this review, with a large proportion of cross-sectional studies that are very heterogeneous in their design has influence the difficulty to draw clear conclusions. In the future it is recommended to include a larger number follow up of studies that are based on unified criteria.

Acknowledgments

The authors would like to gratefully acknowledge the collaboration of Department of Psychiatry members in the University of Granada.

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Luis Gutiérrez-Rojas, Beatriz Villagrasa Blasco. Data curation: Luis Gutiérrez-Rojas, Beatriz Villagrasa Blasco. Formal analysis: Luis Gutiérrez-Rojas, Beatriz Villagrasa Blasco. Funding acquisition: Luis Gutiérrez-Rojas, Beatriz Villagrasa Blasco. Investigation: Luis Gutiérrez-Rojas, Beatriz Villagrasa Blasco. Methodology: Luis Gutiérrez-Rojas, Beatriz Villagrasa Blasco. Project administration: all authors. Resources: all authors. Software: all authors. Supervision: all authors. Validation: all authors. Visualization: all authors. Writing—original draft: all authors. Writing—review & editing: all authors.

School-based obesity interventions: a literature review

Affiliation.

• 1 Center on Drugs and Public Policy, Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, MD 21201, USA. [email protected]
• PMID: 18336677
• DOI: 10.1111/j.1746-1561.2008.00285.x

Background: Childhood obesity is an impending epidemic. This article is an overview of different interventions conducted in school settings so as to guide efforts for an effective management of obesity in children, thus minimizing the risk of adult obesity and related cardiovascular risk.

Methods: PubMed and OVID Medline databases were searched for school-based obesity interventions with anthropometric measures in children and adolescents between the ages of 7 and 19 years from June 1986 to June 2006. Studies were reviewed by duration, type of intervention, and defined qualitative and quantitative measures, resulting in a yield of 51 intervention studies.

Results: The interventions ranged from 4 weeks in length to as long as 8 continuing years. In total, 15 of the intervention studies exclusively utilized physical activity programs, 16 studies exclusively utilized educational models and behavior modification strategies, and 20 studies utilized both. In addition, 31 studies utilized exclusively quantitative variables like body mass indices and waist-to-hip ratios to measure the efficacy of the intervention programs, and another 20 studies utilized a combination of quantitative and qualitative measures that included self-reported physical activity and attitude toward physical activity and the tested knowledge of nutrition, cardiovascular health, and physical fitness. A total of 40 studies achieved positive statistically significant results between the baseline and the follow-up quantitative measurements.

Conclusions: No persistence of positive results in reducing obesity in school-age children has been observed. Studies employing long-term follow-up of quantitative and qualitative measurements of short-term interventions in particular are warranted.

Publication types

• Behavior Therapy
• Health Education
• Motor Activity
• Obesity / prevention & control
• Obesity / therapy*
• Risk Factors
• School Health Services*

• Open supplemental data
• Reference Manager
• Simple TEXT file

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Systematic review article, pharmacoeconomic evaluation of anti-obesity drugs for chronic weight management: a systematic review of literature.

• 1 State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, Macao SAR, China
• 2 School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, China
• 3 School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, China
• 4 Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China

Introduction: Pharmacological therapy is recommended as a second-line alternative to reverse obesity. Currently, five anti-obesity drugs (AODs) have been approved by the U.S. Food and Drug Administration (FDA) for chronic weight management. The aim of this paper is to investigate the pharmacoeconomic evaluation of AODs through a systematic review with a special focus on methodological considerations.

Methods: We searched the general and specific databases to identify the primary pharmacoeconomic evaluation of AODs.

Results: A total of 18 full-text articles and three conference abstracts were included in this review. Most of the economic assessments were still about Orlistat. And the observations we could make were consistent with the previous systematic review. A few studies were on the combined therapies (i.e. PHEN/TPM ER and NB ER) compared to different comparators, which could hardly lead to a generalized summary of the cost-effectiveness. Most recently, pharmacoeconomic evidence on the newest GLP 1 RA approved for the indication of obesity or obesity with at least one comorbidity emerged gradually. Modelling-based cost-utility analysis is the major type of assessment method. In the modelling studies, a manageable number of the key health states and the state transitions were structured to capture the disease progression. In particular, the principal structure of the decision model adopted in the three studies on the newly approved drug was nearly the same, which enables more in-depth comparisons and generalizations of the findings.

Conclusion: This study provided an up-to-date overview of the strengths and areas for improvement in the methodological design of the pharmacoeconomic evaluation of the licensed drugs for chronic weight management. Future modelling evaluations would benefit from a better understanding of the long-term weight loss effects of the current therapeutic options and the weight rebound process after the discontinuation of treatment.

Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022302648 , identifier CRD42022302648.

1 Introduction

The world has been experiencing an obesity crisis ( 1 – 4 ). According to the latest statistics of the World Health Organization, more than 1.9 billion adults (aged or older than 18 years) were overweight and around 650 million were obese. Between 1980 and 2015, a mounting prevalence of obesity was recorded at the global level ( 5 ). In the United States, more than 42% of adults were estimated to have obesity in 2018 ( 6 ). In China, the prevalence of obesity in adults was 16.4% from 2015 to 2019 according to recent national-wide nutrition surveys ( 7 – 9 ). The worldwide childhood and adolescent obesity issue is also worrying with consideration of its strong connection with adulthood obesity and other conditions in the long run ( 4 , 10 ).

The elevated prevalence and incidence of obesity and overweight have been pressurizing the healthcare systems worldwide with complicated and serious health outcomes as well as multiplicatively unfavorable economic consequences. The linkage between obesity and overweight with increased occurrence of premature deaths, cardiovascular diseases, hypertension, type 2 diabetes, several types of cancers, as well as mental illnesses has been substantiated in various studies ( 5 , 11 – 15 ). Besides the cosmetic concerns, undesirable health-related quality of life (HRQOL) has been consistently observed in the population with obesity ( 16 – 18 ). More recently, high-quality evidence was pooled to prove that the population group with obesity is vulnerable to COVID-19 in terms of incidence, morbidity and mortality, and is subject to compromised effectiveness of COVID-19 vaccines ( 19 , 20 ). Financially, obesity and its related conditions lead to not only reduction and even loss of personal or family incomes, but also an increase in healthcare expenditure and other social costs ( 11 , 21 – 23 ). Within the OECD countries, overweight and obesity were estimated to be responsible for 8% of their overall health budgets impacting 0.5%-1.6% of GDP ( 24 ).

Despite the profound implications of excessive weight, obesity remains an undertreated chronic disease and is often treated merely as a risk factor for other conditions ( 25 – 28 ). To reverse the trend of the obesity epidemic, both preventative and treatment interventions for weight normalization are needed ( 28 – 31 ). Life-style management has been prioritized for weight loss mainly by controlling energy intake from diets or boosting energy consumption with physical activities ( 32 , 33 ). Bariatric surgeries are the recommended procedures for severe obesity with comorbidities owing to their proven effectiveness in sizeable weight reduction ( 34 , 35 ). Pharmacological therapies are still categorized as a second-line auxiliary approach to treat obesity at designated obese stages or body mass index (BMI) levels with consideration of the occurrence of comorbidities ( 32 , 33 , 35 – 37 ).

The Food and Drug Administration (FDA) in the U.S. currently approves a handful of general anti-obesity drugs for long-term use, namely, orlistat, phentermine/topiramate extended-release (PHN/TPM ER), naltrexone/bupropion extended-release (NB ER), liraglutide (LIRA) 3.0 mg, and semaglutide (SEMA) 2.4 mg ( 38 ). In the latest network meta-analysis of the relevant randomized controlled trials, these pharmaceutical options could reduce 2.78 to 12.54% of the original weight ( 39 ) (please see details in Supplementary Table S1 ). Safety concerns pertaining to anti-obesity drugs (AODs), which are typified by high-profile market withdrawals due to severe adverse events of sibutramine, rimonabant, and the more recent lorcaserin, have led to more discretion in the approval of new drugs for weight loss purposes ( 40 , 41 ). Orlistat (Xenical ® ) has been available on the market for more than 20 years and is the only one among the five long-term AODs approved by different major drug regulatory authorities including the U.S. FDA, the European Medicines Agency (EMEA), and the National Medical Products Administration (NMPA) in China. Notably, the recent discovery of novel treatment targets opened up new anticipated possibilities in pharmaceutical therapies for obesity with improved effectiveness and safety ( 42 – 44 ). In 2021, semaglutide 2.4 mg (Wegovy ® ) was approved to be on the American and European markets, which is the first drug authorized for chronic weight normalization since 2014 ( 38 , 42 , 45 ).

Cost-effectiveness evaluation is not only essential for pharmaceutical companies to prove the value for money of their innovative products to the regulatory authorities but also enables the manufacturers to predict the returns of their investment in a specific product ( 46 ). The pharmacoeconomic evidence on anti-obesity drugs has been emerging in several reviews which primarily focused on either pharmacologic treatment or various interventions ( 47 , 48 ). Some of the drugs covered in those reviews have been de-licensed due to severe adverse events, e.g. sibutramine, rimonabant, lorcaserin while emerging studies on the cost-effectiveness of the two Glucagon-like peptide-1 Receptor Agonists (GLP-1 RAs) approved in 2014 and 2021 respectively have yet been included in any of the previous reviews. Therefore, it would be meaningful to pool the up-to-date relevant pharmacoeconomic studies together to obtain a more comprehensive overview of the currently available anti-obesity drugs for long-term use with a primary focus on the understanding of the pharmacoeconomic evaluation methods.

The aim of this paper is to investigate the published pharmacoeconomic evaluation of AODs through a systematic review with a special focus on methodological considerations. In particular, we aim to evaluate the model-based cost-effectiveness studies on their potential impact on the estimation of economic outcomes and discuss the possible structural uncertainty in the modelling approaches in the pharmacoeconomic evaluations of the drugs for chronic weight management.

The whole process of screening and selection of studies for inclusion according to the predefined eligibility criteria followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement ( 49 ) (see Supplementary Table S2 ). The study protocol outlining the study design has been previously registered on the international prospective register of systematic reviews PROSPERO (reg. no. CRD42022302648).

2.1 Data sources and search strategy

The search for relevant studies was conducted in the mainstream electronic databases PubMed and EMBASE, as well as on the specific databases including ISPOR, Centre for Reviews and Dissemination (CRD) Databases (Database of Abstracts of Reviews of Effects (DARE), the National Health Service Economic Evaluation Databases (NHS EED), Health Technology Assessment Database (HTA). In addition, a snowball manual search was also performed by scanning the citation of eligible studies or relevant reviews. Both free texts and subject headings were adopted for searching the key concepts about obesity, anti-obesity drugs approved by the FDA for long-term use, as well as pharmacoeconomic evaluation. Zotero (5.0) and EndNote 9 (20.0 version) were employed for recording and managing the de-duplication and screening of articles retrieved from various sources, as well as reference management in writing the manuscript. We conducted the search on 23 January 2023 and no time limitation was set in the search. The language of studies was limited to English. See the Supplementary Table S3 for the detailed search strategies used on different databases.

2.2 Eligibility criteria

Based on our study scope and aims, the eligibility criteria were predefined as outlined in Table 1 . We primarily considered the original full pharmacoeconomic evaluations on any pharmacotherapy for chronic weight management currently approved by the FDA.

Table 1 Eligibility Criteria for Selecting the Included Studies.

2.3 Study selection

Based on the eligibility criteria, two reviewers first screened the titles and abstracts independently for initial inclusion. Then, full texts of articles considered eligible were reviewed by the two reviewers for the final inclusion. In both steps, reasons for exclusion were noted. And consensus between the two reviewers was reached over the final inclusion of studies by discussion.

2.4 Data extraction

An Excel form for data was designed and piloted by the main reviewer. The information to be extracted from the selected articles included the basic information of the study, the economic outcomes and conclusions on the cost-effectiveness, and the design of the pharmacoeconomic evaluations. The extraction of data was first performed by one reviewer, while the extracted data was later confirmed by another reviewer to ensure no omission or mistakes.

2.5 Quality assessment

The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) Checklist ( 50 ) was employed for assessing the quality of the included studies on the 28 items. The full-text articles were evaluated against the 28 items with “yes” if they reported the relevant information and “no”, if not. The percentages of the studies reporting the items were calculated to obtain a general view of the completeness and quality of the studies.

3.1 Selection of the included studies

A total of 1314 titles and abstracts were obtained initially for examination of their potential relevance to the current research focus based on the preset search strategy as illustrated in the previous section. After the removal of duplications, 1029 records were found valid for further screening. With a closer study of the titles and abstracts, a total of 179 records were identified as relevant to our research questions as outlined in the PRISMA Flowchart Figure 1 . Thereafter, the full-text articles were retrieved and examined, and four additional research articles were found from the core references that fit with the eligibility criteria. Finally, 18 full-text published articles were included for the systematic review. Considering that only a limited number of primary pharmacoeconomic studies on some drugs could be searched, three conference abstracts with relatively sufficient information on their methodological design were also incorporated into the synthesis of information in the current study.

Figure 1 PRISMA flowchart of the study selection process.

3.2 Quality assessment of the included studies

The quality of the 18 full-text articles included in the review was evaluated according to the CHEERS Checklist. The percentages of the studies reporting the 28 items were calculated and presented in Supplementary Table S4 . All the included studies depicted their study context and settings, the objectives of conducting the economic evaluation, interventions or strategies for investigation, the baseline characteristics, and time horizon. Moreover, the measurement and estimation of health outcomes, resources, and costs were specified in all the full-text articles. However, the explanation of the reason for selecting a particular model structure and a very detailed description of the model were only seen in 2/3 of the studies. In the report of the results, the major study parameters and the main review findings were summarized. The effect of uncertainty was also included and discussed in all the studies. The limitations and generalizability of all the full-text studies were clarified. Notably, none of the studies have included any explicit efforts to engage patients or other stakeholders who are affected by the study, which is a new focus reflected in the latest version of the CHEERS checklist. All the studies in full text either reported their funding sources or disclosed conflicts of interest. Details of the quality assessment are presented in the Supplementary Table S5 .

3.3 Descriptive characteristics of the included studies

The general characteristics of the included studies are presented in Table 2 . Most of the studies were conducted in the UK and the European settings ( 51 , 57 , 58 , 61 , 63 , 64 , 66 – 69 , 71 ), while 10 other studies were conducted in the US, Canada, or Australia ( 52 – 56 , 59 , 60 , 62 , 65 , 70 ). One study analyzed the cost-effectiveness of AODs in more than one country ( 68 ). 14 studies examined the costs and benefits of orlistat as an adjunct intervention to either lifestyle interventions or dietary programs relative to other interventions, placebo or no treatment ( 55 , 58 , 60 – 71 ). The cost-effectiveness of phentermine/topiramate ER (PHN/TPM ER) was evaluated in five studies ( 52 , 54 , 55 , 59 , 60 ). Three studies examined naltrexone/bupropion ER (NB ER) ( 55 , 56 , 58 ), three examined liraglutide (LIRA) 3.0 mg ( 52 , 55 , 57 ). Regarding the latest approved semaglutide (SEMA), one study in 2020 examined semaglutide (SEMA) 0.4 mg ( 54 ), while the three most recent studies investigated the cost-effectiveness of the regimen in the approved dosage 2.4mg ( 51 – 53 ). Moreover, five studies performed comparisons between various approved AODs ( 52 , 54 , 55 , 58 , 60 ). The treatment duration either modelled or implemented in most studies normally lasted for around one year.

Table 2 General Characteristics of the Included Studies.

Most of the included studies are modelling-based ( 51 – 58 , 61 – 71 ), which aimed to estimate the outcomes of weight reduction beyond the treatment duration by building mathematical models. And the baseline characteristics of the target population in these studies included the following categories: 1) obesity population with/without comorbidities, 2) overweight population with at least one obesity-related comorbidities, and 3) both conditions. Two studies exclusively focused on a gender-specific obesity group ( 65 , 70 ).

All the studies with full-text research articles either disclosed the funding sources or the conflicts of interest, or both. Except for four funded by the government ( 61 , 62 , 64 , 65 ), all the other studies involved the relevant pharmaceutical companies (e.g. Roche, Novo Nordisk, Vivus, etc.) in various forms.

Studies revealed that the general cost-effectiveness picture of the four anti-obesity drugs approved earlier for long-term use (i.e. orlistat, PHN/TPM ER, NB ER, LIRA 3.0mg) was not desirable. The cost-effectiveness of Orlistat varies largely in countries. For example, the model-based estimation of cost-effectiveness in the UK indicated that orlistat was cost-effective in the base case with an ICER of GBP 1 665 (USD 2 166/EUR 2 000) relative to placebo ( 61 ). However, in the Australian health care setting in 2003, orlistat was found to be not cost-effective with the ICER of AUD 230 000 (171 675 USD/158 482 EUR) per DALY (95% CI: 170 000 – 340 0000) in the base case in any of the costing scenarios ( 62 ). In addition, in the studies on the cost-effectiveness of orlistat, a range of cost-effectiveness thresholds was employed in the probabilistic sensitivity analysis to evaluate the impact of this threshold on the probability of cost-effectiveness of this intervention investigated. In terms of PHN/TPM ER, the ICER in a data-based CEA study turned out to be slightly below the WTP threshold of USD 50 000 per QALY, only if the benefit of the one-year treatment could be sustained for the following two years after drug cessation ( 59 ). And in another data-based study on PHN/TPM ER, the ICER was found to be at USD 54 130 per QALY and the average cost-effectiveness ratio (ACER) at USD 46 850 (32 010–69 350) per QALY with an assumed WTP threshold of USD 50 000 ( 60 ). In a more recent study, the ICER of PHN/TPM ER relative to a lifestyle management program called Weight Watcher was found to be as high as USD 117 219 per QALY ( 55 ). In the last two studies mentioned above, the ACERs of other pharmaceutical treatments including orlistat, NB ER, and LIRA 3.0mg were considerably higher than the commonly accepted WTP threshold of USD 50 000 ( 55 , 60 ). Furthermore, the selection of different comparators led to different conclusions on the cost-effectiveness of NB ER. For instance, the two CEA studies of NB ER conducted in the health care setting of Canada and the UK respectively reported NB ER to be a cost-effective weight loss option relative to standard weight management for long-term use ( 56 ) and even in a lifetime horizon ( 58 ). However, in the later study, this combination therapy was found to be not cost-effective relative to orlistat ( 58 ).

Notably, the latest three studies on SEMA with the approved dosage at 2.4mg conducted in different settings converged on the conclusions about the cost-effectiveness of this newest anti-obesity drug approved by the major drug authorities. From the UK National Health Service (NHS) and Personal Social Services perspectives, the SEMA 2.4mg injection could benefit the population with obesity and relevant comorbidities with an ICER of GBP 14 827 per QALY relative to the treatment of diet and exercise alone ( 51 ). And a series of sensitivity analyses proved the robustness of its cost-effectiveness in different scenarios under the prespecified willingness-to-pay (WTP) threshold as GBP 20 000 per QALY. In a setting of US third-party payer, this newly approved therapy also showed its cost-effectiveness against all the selected comparators including three branded AOMs under the WTP threshold of USD 150 000 per QALY ( 52 ). In another assessment of the cost-effectiveness of SEMA 2.4mg injection in a Canadian setting, the therapy showed a favorable ICER at CAD31 861 per QALY when compared with diet and exercise under the WTP threshold suggested in the relevant Canadian Guidelines (CADTH) ( 53 ). However, in an earlier CEA study on SEMA 0.4mg administered per day from the US healthcare perspective, the ICER of the same therapy option given in a daily pattern with favorable weight loss effects was found to be not cost-effective in all the projected time horizons ( 54 ).

3.4 Analysis of the pharmacoeconomic evaluation methods

3.4.1 types of cost-effectiveness analysis.

As summarized in Table 3 , cost-utility analysis (CUA) is the major type of assessment method among all the included studies, with quality-adjusted life year (QALY) as a proxy of the health outcome ( 51 – 58 , 61 – 64 , 66 – 69 ). There was one study conducted in the Australian setting that used disability-adjusted life year (DALY) as a measure of health loss ( 62 ). A few studies undertook both CUA and cost-effectiveness analysis (CEA) with QALYs and kilograms of weight reduction as the measure of health outcome, respectively ( 59 , 60 , 65 ). In addition, two early studies only adopted event-free life years gained (LYG) as the measure of health benefit ( 70 , 71 ). No cost-benefit analysis or cost-minimization analysis was observed in the economic evaluations of pharmacologic treatment for obesity.

Table 3 Details of the Included Pharmacoeconomic Evaluations.

3.4.2 Decision analytic approaches

Various decision- analytic approaches were observed in the modelling-based studies. Cohort-based Markov model was commonly applied to conceptualize a series of health states in relation to obesity and transitions between the states in most of the studies ( 51 – 53 , 61 – 64 , 67 , 68 , 70 , 71 ). In particular, the latest publications on the SEMA 2.4mg adopted the Core Obesity Model with adaptations to various extents, which is indeed a typical Markov structure ( 51 – 53 ). The individual-based state-transition Monte Carlo simulation was also employed by modelling different patient characteristics with multiple runs in the model cycle representing the state changes in a few of the studies ( 54 , 65 , 69 ). In addition, the event-driven simulation was used in three studies to capture the complex disease course of obesity ( 56 – 58 ). The modelled health states or events include discontinuation of treatment, and occurrence of obesity-related events (e.g. type 2 diabetes, primary and secondary cardiovascular events, death). 10 of the studies provided a justification for selecting a particular model and a relatively detailed account of the decision model structure ( 51 , 52 , 58 , 61 – 63 , 65 , 68 , 70 , 71 ). Moreover, the explicit model validation procedure was only mentioned briefly in two of the latest investigations on SEMA 2.4mg ( 51 , 52 ).

3.4.3 Perspective of the evaluation and cost categories

Most of the included studies specified their evaluation perspectives. The selection of cost categories also differs according to the study perspectives. Eight of the studies adopted a health-care perspective, involving the costs of the anti-obesity drugs, direct medical costs of treating obesity-related conditions, health care costs, and even the costs of the dietary programs ( 54 , 56 , 62 , 64 , 67 , 69 – 71 ). The payer perspective was undertaken in eight of the studies, which mainly considered the costs of interventions and physician visit costs, and other medication costs for reducing obesity-related conditions ( 51 , 52 , 55 – 59 , 61 ). Three studies performed their evaluation from a societal perspective ( 53 , 63 , 65 ).

3.4.4 Time horizon projected and discounting

The two data-based studies focus on the outcomes within the one-year treatment period, no discounting was performed as unnecessary ( 59 , 60 ). The modelling-based studies adopted various time horizons, among which five stretched the evaluation to a lifetime or around ( 58 , 61 , 62 , 64 , 65 ), three projected the outcomes in a period of 30 or 40 years ( 51 – 53 ), eight selected a time horizon between 10-20 years ( 56 , 57 , 63 , 67 – 71 ), while the rest used a short-term time horizon no more than five years ( 54 , 55 , 66 ). Correspondingly, for the modelling-based evaluation with more than a one-year time horizon, discount rates that followed the guideline or consensus in a specific country or setting were applied to future effects and costs in most of the studies ( 51 – 55 , 58 , 59 , 61 – 65 , 67 – 71 ). Moreover, time horizon and discount rates were estimated at values different from the base case in the sensitivity analysis to investigate the parameter uncertainty in some of the studies ( 51 , 52 , 54 , 58 , 59 , 61 , 65 , 67 , 68 , 70 , 71 ).

3.4.5 Sources of evidence and estimation of outcomes

Most of the studies reported the sources of data about effectiveness and health utility. The extrapolation of effectiveness (e.g. discontinuation data, rate of responders, mean change in body weight, risk of obesity-related sequelae, and adverse events) was mainly derived from the pivotal large-scale randomized control trials or meta-analysis ( 51 – 56 , 58 – 71 ).

The valuing of health-related utility (i.e. QALY or DALY) in some of the studies was directly informed by published literature ( 51 – 54 , 56 , 57 , 63 , 65 – 69 ). Independent computation of health utilities was also found in several studies by transforming the effectiveness data into QALY or DALY with the aid of established algorithms ( 55 , 58 , 62 , 64 ).

3.4.6 Sensitivity and uncertainty analysis

Sensitivity analysis was carried out in all the studies in full text to check the robustness of the base case estimates. More than half of these studies performed both deterministic and probabilistic sensitivity analyses ( 51 – 55 , 58 – 61 , 64 , 69 ). The covariates in the sensitivity analysis of these 18 studies fell into the following categories, namely, baseline characteristics, efficacy of interventions in comparison, natural weight increase rate, duration of weight loss benefit decay, occurrence of obesity-related conditions, costs and discount rates, valuation of health utility, and so on. However, there was no consistent inclusion of covariates among these studies. In addition, in many studies, authors solely listed specific variables or scenarios for analysis without giving detailed justification for selecting a specific parameter for the sensitivity analysis in advance. Among the evaluations on orlistat that were performed in the early 2000s, five of the studies only conducted a series of univariate sensitivity analyses by variating one of the input parameters each time ( 62 , 65 – 67 , 71 ), while the other three studies only performed probabilistic sensitivity analysis (PSA) with results displayed in scatter plots, cost-effectiveness/utility curves as well as planes as a measure of uncertainty ( 63 , 68 , 70 ).

4 Discussion

The current review comprehensively consolidated the pharmacoeconomic evidence relevant to drug options for long-term weight control. Different from the previous reviews on similar topics, the primary focus of this study rests on the methodological design of the pharmacoeconomic evaluations in the synthesis and analysis of the included studies.

Our predefined search strategy and selection process enabled us to access the relevant and up-to-date studies, of which the interventions cover all the five currently available anti-obesity drugs approved by the FDA. In general, these five AODs work on various peripheral and central pathways to regulate energy intake, suppress appetite, or increase fullness ( 72 ). Orlistat is an agent acting via peripheral pathway. It acts as an inhibitor of gastrointestinal and pancreatic lipase by preventing the catalysis of hydrolyzing triglycerides. Therefore, free fatty acids are not absorbed by the intestinal endothelium ( 45 ). Phentermine is a sympathomimetic amine anorectic acting as a norepinephrine agonist in the central nervous system, thus, decreasing the appetite. Its common anticonvulsant, topiramate, which is a gamma-aminobutyric acid agonist, glutamate antagonist and carbonic anhydrase inhibitor, shows several potential mechanisms of topiramate on weight loss ( 73 ). However, the clear mechanism of action of the combination therapy of PHN/TPM ER still awaits confirmation in animal and human studies ( 45 , 74 ). NB ER is another combination therapy for long-term weight management that makes use of the synergistic effect of two distinct agents. Naltrexone originally is an opioid receptor antagonist, while bupropion a dopamine and norepinephrine reuptake inhibitor. In the hypothalamus, bupropion enhances the effects of pro-opiomelanocortin (POMC) cells in producing melanocyte-stimulating hormone (alpha-MSH) and beta-endorphin. The alpha-MSH activates melanocortin-4 receptor; which can decrease suppress appetite, and increase energy expenditure and weight loss. Naltrexone blocks mu-opioid receptor, so preventing the inhibitory feedback from beta-endorphin on POMC cells. Therefore, bupropion and naltrexone work complementarily to reduce bodyweight ( 45 , 74 ). Lastly, both LIRA and SEMA are analogs of human glucagon like peptide (GLP-1) and act as GLP-1 receptor agonist. They stimulate pancreas to release insulin, which can regulate glucose concentration to reach euglycemia. They also inhibit the secretion of glucagon which triggers glycogenolysis and gluconeogenesis. In this approach, appetite and digestion are suppressed, thus calorie intake is reduced ( 45 , 74 , 75 ). Interestingly, the dose-dependent weight reduction effect of four among these five approved AODs (except Orlistat) was observed in the exploration of multiple sites of action and mechanisms of the therapeutic agent(s) involved, which were originally for other pathophysiological conditions ( 45 , 75 ). This development process of these critical weight loss therapies benefits from the recent advances in the understanding of the pathophysiology of obesity as a complex disease and the metabolic processes ( 74 ).

The cost-effectiveness of the four AOMs before the approval of SEMA 2.4mg was not favorable for market access in general. As orlistat has been the only pharmacotherapy option on the market for around two decades, more than half of the studies included in our review evaluated the cost-effectiveness of this AOD either as the primary intervention or as a comparator. Patients in overweight or obesity who are with or without diabetes were observed in these studies. And the evaluations were conducted in various countries from different perspectives. Both cohort-based Markov model and patient-based Monte Carlo simulations were adopted in the modelling construction. Although the generalizability of these evaluations was undesirable, it is observed that the models have evolved to capture a relatively more complex disease progression course. Specifically, the early studies adopted a shorter time horizon, while the more recent studies made efforts to extrapolate the weight loss effects to the long term by incorporating the occurrence risks of complications such as type 2 diabetes and cardiovascular events. The economic evaluations focusing on LIRA 3.0mg, NB ER and PHN/TPM ER were relatively insufficient, which makes comparisons across challenging. By contrast, the latest studies on the SEMA 2.4 mg sponsored by the manufacturer seem to alter this situation. Although the three evaluations included were conducted in different settings, the cost-effectiveness of this newly approved GLP-1 drug for long-term weight management based on the Core Obesity Model was consistently promising.

The five licensed AODs for long-term weight reduction identified in this study have been approved in North America, and four of them except NB ER are available in the European markets. This scenario is probably the main reason that nearly all the included economic evaluations were conducted in countries from these regions. There was one study that was carried out in Australia, where orlistat, phentermine, and liraglutide are officially available for weight reduction. No pharmacoeconomic evidence was generated from a Chinese setting, as orlistat has been the only approved pharmaceutical option for weight reduction in China for a long time. The emerging novel drug targets for weight loss have attracted domestic pharmaceuticals and research teams. To facilitate the research and development of AODs, the Technical Guiding Principles on the Clinical Trials of Weight Management Drugs was enacted in 2021 by the Center for Drug Evaluation (CDE) of the NMPA as a move at the institutional level to combat obesity.

As modelling-based economic evaluations are relatively less time- and money-consuming, the majority of the included studies constructed a mathematical model to calculate the possible costs and health outcomes of the intervention of interest. Two evaluations were data-based ( 59 , 60 ), and one of them was a typical piggyback study alongside the phase III clinical trial on Qsymia ( 59 ). State-transition decision analytical approaches including the Markov model and microsimulation were predominantly adopted in most of the studies on the AOMs approved earlier. In these models, a manageable number of the key health states and the state transitions were structured to capture the disease progression. One of the key model assumptions found in these studies was primarily about the length of weight loss decay. Studies proved the sensitivity of effect persistence in the model by assuming either a longer or shorter course of weight regain in the sensitivity analysis than in the base case scenario ( 51 , 52 , 54 , 55 , 58 – 62 , 67 , 69 , 70 ). Naturally, the longer the weight loss sustained after the treatment cessation, the better benefit was observed. And in the modelling of these studies, the decay process of the weight loss effect was normally assumed linearly after the treatment cessation. Moreover, adverse events associated with the pharmacologic treatments were seldom explicitly incorporated into the models in the included studies. The Core Obesity Model was the only one that was applied in different studies on the same AOM SEMA 2.4 mg ( 51 – 53 ). It also follows a Markov model structure, which aims to reflect the natural disease course in a real-world setting by incorporating a series of obesity-related comorbidities including the occurrence of pre-diabetes evidenced in literature or pivotal clinical studies ( 76 ). The uncertainty of the modelling evaluations on AODs would be mitigated to a greater extent if more solid evidence could be achieved in the understanding of the weight rebound process after the discontinuation of treatment.

The major evaluation technique adopted in the included studies was cost-utility evaluation. Quality of life has been proved to be negatively associated with the BMI value, so in these CUA studies, quality-adjusted-life-years (QALY) gained per weight loss effect and disability-adjusted-life-years (DALY) were used as the surrogates of health utility. The methods employed in the estimation of health utilities include direct elicitation ( 55 , 62 , 64 ), indirect measurement with self-reported questionnaires such as EQ-5D and SF-12 v2 ( 58 – 61 ), as well as extraction of reference value from previous literature ( 51 – 54 , 56 , 57 , 63 , 65 – 69 ). Although using QALYs aims to facilitate the comparison across studies, the health utility values associated with one unit reduction in BMI were found to differ considerably in these studies. The comparability between studies on the cost-effectiveness of AODs would be improved if a more in-depth understanding of the linkage between quality of life, weight reduction effect, adverse events, and side effects could be obtained through clinical and real-world studies, and correspondingly better measurement of utility value could be performed.

All the included studies made efforts to examine the uncertainty through various sensitivity analyses, which constituted the good practice of reporting ( 77 ). Future studies could provide proper justifications on the selection of parameters or inputs as the covariates in the sensitivity analysis with evidence-based consideration of the nature of the disease and statistical significance. The transparency of the model structure, parameter values, and key assumptions in the included studies were found to be improved in more recent studies to facilitate stakeholders or decision-makers to obtain a fuller understanding of the generation of evaluation results from the models ( 78 ). On the other hand, the included studies except the recent two ( 51 , 52 ) commonly were lack of explicit validation procedures to check the accuracy of the model.

Despite the effort, we managed to make, the current review still has some limitations. Firstly, as we only focused on the published studies, it is very likely that pharmacoeconomic evaluations not yet accessible to the public in any form were missed. Secondly, the heterogeneity in the methodological design of the included studies made the synthesis of information challenging. Thirdly, as inherent in the currently available evaluations, it would be difficult to make a judgment about the prediction of long-term weight loss effects and their impact on morbidity and mortality without the presence of long-term large-scale clinical trials and real-world observational studies.

5 Conclusions

This systematic review rendered a comprehensive and updated analysis of strengths and areas for improvement in the methodological design and quality of the pharmacoeconomic evaluations on the currently licensed drugs for chronic weight management. Recent CEA studies on the new-generation AOD licensed for long-term weight management indicated its great potential to better meet the clinical and market needs. More in-depth understanding of obesity and its natural trajectory as well as solid data on the long-term effectiveness and safety of AODs from future studies would facilitate the generation of pharmacoeconomic evidence with enhanced quality.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

Author contributions

YX: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing. HZ: Data curation, Formal analysis, Writing – review & editing. ZR: Investigation, Writing – review & editing. XC: Writing – review & editing. YL: Writing – review & editing. DY: Writing – review & editing. CU: Conceptualization, Writing – review & editing. HH: Conceptualization, Methodology, Supervision, Writing – review & editing.

This research is supported by the fundings of the University of Macau (MYRG2020-00230-ICMS) and The Science and Technology Development Fund, Macao SAR (001/2023/ALC).

Acknowledgments

We would like to express our gratitude to Dr Menghuan Song for her technical support.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fendo.2023.1254398/full#supplementary-material

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Keywords: obesity, anti-obesity drugs, cost-effectiveness, modeling, methodology

Citation: Xue Y, Zou H, Ruan Z, Chen X, Lai Y, Yao D, Ung COL and Hu H (2023) Pharmacoeconomic evaluation of anti-obesity drugs for chronic weight management: a systematic review of literature. Front. Endocrinol. 14:1254398. doi: 10.3389/fendo.2023.1254398

Received: 07 July 2023; Accepted: 17 October 2023; Published: 06 November 2023.

Reviewed by:

Copyright © 2023 Xue, Zou, Ruan, Chen, Lai, Yao, Ung and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Carolina Oi Lam Ung, [email protected] ; Hao Hu, [email protected]

This article is part of the Research Topic

Insights in Obesity: 2023

Thrive Patch Review 2023: What Do Nutritionists Think?

• Author: Emma Witman

The products featured in this article have been independently reviewed. When you buy something through the retail links on this page, we may earn commission at no cost to you, the reader.  Learn more here.

Key Features of Thrive:

• Thrive Patches are marketed as a weight loss patch that you wear on your skin like a sticker
• The patch and other products can be bought online, and are also sold by user recruits in an MLM structure
• The evidence for Thrive patch is inconclusive, and the skin-patch application feels gimmicky

Sometimes dieting—especially an extreme crash diet—can feel like a Band-Aid solution to weight loss. You see results for a short time, but then bounce back to your original weight or worse when you “rip the Band-Aid off,” so to speak. In many ways, the Thrive Patch feels like it could be another deceptive Band-Aid like solution to weight loss, including—but not limited to—the fact that the patch is literally stuck like a Band-Aid to the body.

But could the patch be an effective weight loss strategy ? In this Thrive Patch review, we researched the ingredients, pored over reviews from users and consulted nutritionist and weight loss coach Pete Nastasi , who is also a frequent contributor to Sports Illustrated Showcase.

Editor’s Note: This content is meant to be informative, but should not be taken as medical advice. It is not intended for use as diagnosis, prevention or treatment of health problems. Before starting any new supplement, weight loss or exercise regimen, talk with your doctor.

What Are Thrive Weight Loss Patches?

Created by the company Le-Vel, the Thrive Patch is sold two ways: online, via the company website; and peer-to-peer by recruited representatives as part of what is traditionally known as an “MLM,” or multi-level marketing. According to the U.S. Federal Trade Commission, most people who partake in an MLM selling scheme earn little to no profit , and may even lose money buying up stock of the product.

The full name of the patch is officially the THRIVE Premium Lifestyle Derma Fusion Technology, “derma fusion” referring to the fact that you apply the patch to your skin as part of Le-Vel’s eight-week program. However, we should note that studies on the following active ingredients were based on taking the supplements orally. It’s unknown how effective—if at all—the transdermal absorption of the product is via patch.

Thrive Patch Ingredients

ForsLean, an extract derived from Coleus forskohlii roots, has limited clinically-proven effectiveness for weight loss. For reference, a 2005 study of 23 women over 12 weeks published in the Journal of the International Society of Sports Nutritio n showed that Coleus forskohlii “may have helped mitigate weight gain” in overweight females , however there was no evidence that the supplement promoted actual weight loss. Furthermore, a 10-year review of literature on Coleus forskohlii indicates the supplement may cause more harm than good, citing “extreme side-effects” including liver and kidney failure .

Green coffee bean extract

The unroasted, ​​raw seeds of coffee cherries certainly won’t sate your coffee fix. But, they will supply a high amount of chlorogenic acid, a natural compound called a polyphenol that may facilitate weight loss . Indeed, the evidence behind green coffee bean extract is more promising compared to ForsLean. A 2021 study conducted in India showed that after 12 weeks, the group that was supplemented with chlorogenic acid lost more weight than those taking the placebo .

Related Post: Coffee vs. Pre Workout: Which Is Better for Your Gains?

Garcinia cambogia

A small pumpkin-shaped fruit, the peel of garcinia cambogia is high in hydroxycitric acid (HCA), which small studies have shown may help reduce fat around the midsection in men and women with a certain type of obesity. The mechanism by which HCA may prompt weight loss is not known, although it’s theorized that HCA may reduce appetite and impede fat production.

Other ingredients in the Thrive Patch

• CoQ10: Studies show that CoQ10, short for coenzyme q10, might help encourage muscle recovery , but more research is needed.
• White willow bark: According to a 2015 study overview, white willow bark may help with inflammation and joint pain .
• Cosmoperine: A derivative of piperine from black pepper, Cosmoperine is said by cosmetic brands to increase the absorption of drugs and nutrients via the skin .
• Limonene: A compound found in the essential oil of a citrus peel .
• Aloe vera : Extract from the plant that can potentially help with some skin conditions when used topically.
• L-arginine: An amino acid that helps the body build protein .

Other Thrive Products

The Thrive Patch, geared toward weight management, is only one rung of what Le-Vel calls the Thrive Experience, consisting of three recommended daily supplements: The patch, capsule supplements you swallow in the morning and a protein shake at lunch. Altogether, Thrive claims the full routine will support cognitive function, healthy joints, antioxidant intake, lean muscle and the digestive and immune systems.

Thrive vitamin supplements

Thrive has four variations of its capsule supplement, a regular and “elite” version of the capsule for men and women. Both include vitamins and minerals, however the “elite” version additionally includes ingredients found in Thrive’s weight loss supplement patches, like ForsLean. Both varieties of the vitamin supplements do however have caffeine, which has been shown to have appetite suppressing effects .

Thrive shake mixes

Called the Thrive Premium Lifestyle Mix, the shake is gluten-free with a proprietary blend of vitamins, antioxidants, minerals, plant extracts, probiotics and amino acids, the brand says. Testing information on the formulation wasn’t available. This is in contrast to many of the most popular fat burner brands , like Transparent Labs , which is Informed Choice certified. There is a Thrive vegan shake, if you’re looking for a plant-based protein powder alternative.

How The Thrive Patch Works

According to Le-Vel, the Thrive Patch delivers the active ingredients via Derma Fusion Technology. The drug, in theory, penetrates the skin at a safe pace and dosage. There are such cases of drugs being delivered transdermally, including pain medication and nicotine . Although Le-Vel says the patch was designed for “increased bioavailability” of the ingredients, there have been no studies conducted to examine the mechanism and efficacy of the Thrive patch.

Where Should You Put The Thrive Patch?

Le-Vel suggests putting the Thrive DFT Patch on clean, dry skin. The brand says you’ll yield the best results by putting the patch on “leaner,” lower fat areas, such as the biceps, shoulder, forearms or lower back. The brand also suggests rotating where you place the patch, rather than using the same spot continuously.

Thrive Patch Cost

The Thrive Experience is by no means a budget experience: It costs $300 for an eight-week supply of the supplements. Although the products are marketed as an eight-week endeavor, you can only buy the capsules, patches and shakes in two-week or four-week supplies.

Thrive Patch Reviews

Customer feedback is a bit tricky to navigate when it comes to the Le-Vel Thrive Patch: Many users are incentivized to leave positive reviews, since they also make money selling the patch and recruiting “downline” sellers to take up peddling the patch as well. I did find a solidly unbiased-sounding review in the r/supplements subreddit . The reviewer had some positive feedback, but noted that the visibility aspect of the patch appears to be “more of [a] promoter conversation starter” than a practical aspect. Most of the comments in the thread were either neutral or negative toward the patch, however, often citing the side effects as a drawback. Positive feedback cited increased energy levels.

What Do Experts Think of the Thrive Patch for Weight Loss?

Certified sports nutrition coach Pete Nastasi shared his thoughts on the Thrive patch:

“Weight loss supplements like the Thrive Patch are often marketed as quick and effortless solutions to shedding excess body fat and achieving the body of your dreams,” he tells SI Showcase. “The issue is that science and the products rarely live up to these extravagant claims.”

He noted that the Thrive patch does have “some ingredients with potential weight loss benefits,” however, he questioned the product’s overall efficacy and safety. One big reason: The studies that link the more promising ingredients to weight loss involved oral ingestion rather than transdermal application, he notes.

Another major problem in general with products like Thrive is that weight loss is too complex to be encapsulated in a pill (or patch), Nastasi says: “The major problem with the Thrive Patch and other supplements designed to promote weight loss is that weight loss is a complex and multifaceted process that is influenced by numerous factors, including diet, physical activity, genetics and your overall lifestyle,” he says. “As Le-Vel points out directly on its website, ‘meaningful weight loss requires healthy lifestyle choices, diet and exercise, and good nutritional intake.’”

He stresses that there aren’t over-the-counter weight loss pills, powders, patches or creams that will magically help you lose weight. Rather, if you truly want to promote weight loss, then you need to be in a daily caloric deficit. “Whether that’s achieved through eating less food, daily exercise or a combination of both, it’s essential for long-term sustainable results,” he says. Ultimately, his biggest concern with Thrive is that it preys on people’s insecurities to sell products at high price points. Nastasi’s math does compute: Thrive is considerably more expensive per serving than your typical pre-workout mixture for weight loss , for instance.

Thrive Patch vs. Noom

Although taking a regimen of so-called lifestyle capsules and patches might sound appealing, tools like Noom employ a more evidence-based approach. Noom is an app that helps users achieve long-term weight loss by promoting a healthy diet. You’re “tricked” into better habits via psychology and mindfulness, and education and accountability. You can also use the app for meal planning and to track your calories and weight loss progress.

Thrive Patch vs. Diet-to-Go

Diet-to-Go is a weight loss meal planning service that delivers healthy pre-prepared meals directly to your house. The program takes the guesswork out of calorie counting and recipe-finding. Instead, you get breakfast, lunch and dinner in realistic but controlled portions to help you stay on track.

FAQ About Thrive Patches

Do thrive patches expire.

I couldn’t find any information on Le-Vel.com regarding an expiration date for the Thrive patch. The company does say that the shakes are best used within five years.

Do you sleep with Thrive patches on?

Yes, the Thrive patches are meant to be worn for 24 hours, so you can sleep with them on.

Are Thrive patches safe?

The safety of the Thrive patch is impossible to decipher because of lack of testing information or short- or long-term studies on the patch. Always consult your primary care physician before starting weight loss products like Thrive.

Can Thrive patches get wet?

Yes, Thrive patches can get wet, according to Le-Vel, so they can be worn in the shower, for instance.

Final Thoughts: Are Thrive Patches Worth It?

If you’ve made it this far, you’ve probably gathered that we’re not huge fans of the Thrive patch. Our ambivalence primarily stems from both the MLM business model and the unproven nature of the transdermal delivery system. And to reiterate an important point, there’s no magic pill to help you shed pounds. As Nastasi emphasizes, a daily calorie deficit via healthy eating or physical activity is the ultimate answer. That’s true even when using the best fat burner pills out there that boast superior clinical evidence to back the ingredients and delivery method. Always consult your physician, who is best equipped to help you navigate whether the drawbacks outweigh the health benefits of taking a weight loss supplement. 

Prices are accurate and items in stock at time of publishing.

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