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Obesity Management in Adults : A Review

  • 1 Department of Medicine, Division of General Internal Medicine and Clinical Innovation, New York University Grossman School of Medicine, New York, New York
  • 2 Department of Population Health, New York University Grossman School of Medicine, New York, New York
  • 3 Family Health Centers at NYU Langone, New York, New York
  • 4 Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
  • 5 Division of General Internal Medicine, University of Minnesota Medical School, Minneapolis
  • 6 Division of General Internal Medicine, University of Colorado School of Medicine, Aurora
  • 7 New York Harbor Veteran Affairs, New York, New York
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Importance   Obesity affects approximately 42% of US adults and is associated with increased rates of type 2 diabetes, hypertension, cardiovascular disease, sleep disorders, osteoarthritis, and premature death.

Observations   A body mass index (BMI) of 25 or greater is commonly used to define overweight, and a BMI of 30 or greater to define obesity, with lower thresholds for Asian populations (BMI ≥25-27.5), although use of BMI alone is not recommended to determine individual risk. Individuals with obesity have higher rates of incident cardiovascular disease. In men with a BMI of 30 to 39, cardiovascular event rates are 20.21 per 1000 person-years compared with 13.72 per 1000 person-years in men with a normal BMI. In women with a BMI of 30 to 39.9, cardiovascular event rates are 9.97 per 1000 person-years compared with 6.37 per 1000 person-years in women with a normal BMI. Among people with obesity, 5% to 10% weight loss improves systolic blood pressure by about 3 mm Hg for those with hypertension, and may decrease hemoglobin A 1c by 0.6% to 1% for those with type 2 diabetes. Evidence-based obesity treatment includes interventions addressing 5 major categories: behavioral interventions, nutrition, physical activity, pharmacotherapy, and metabolic/bariatric procedures. Comprehensive obesity care plans combine appropriate interventions for individual patients. Multicomponent behavioral interventions, ideally consisting of at least 14 sessions in 6 months to promote lifestyle changes, including components such as weight self-monitoring, dietary and physical activity counseling, and problem solving, often produce 5% to 10% weight loss, although weight regain occurs in 25% or more of participants at 2-year follow-up. Effective nutritional approaches focus on reducing total caloric intake and dietary strategies based on patient preferences. Physical activity without calorie reduction typically causes less weight loss (2-3 kg) but is important for weight-loss maintenance. Commonly prescribed medications such as antidepressants (eg, mirtazapine, amitriptyline) and antihyperglycemics such as glyburide or insulin cause weight gain, and clinicians should review and consider alternatives. Antiobesity medications are recommended for nonpregnant patients with obesity or overweight and weight-related comorbidities in conjunction with lifestyle modifications. Six medications are currently approved by the US Food and Drug Administration for long-term use: glucagon-like peptide receptor 1 (GLP-1) agonists (semaglutide and liraglutide only), tirzepatide (a glucose-dependent insulinotropic polypeptide/GLP-1 agonist), phentermine-topiramate, naltrexone-bupropion, and orlistat. Of these, tirzepatide has the greatest effect, with mean weight loss of 21% at 72 weeks. Endoscopic procedures (ie, intragastric balloon and endoscopic sleeve gastroplasty) can attain 10% to 13% weight loss at 6 months. Weight loss from metabolic and bariatric surgeries (ie, laparoscopic sleeve gastrectomy and Roux-en-Y gastric bypass) ranges from 25% to 30% at 12 months. Maintaining long-term weight loss is difficult, and clinical guidelines support the use of long-term antiobesity medications when weight maintenance is inadequate with lifestyle interventions alone.

Conclusion and Relevance   Obesity affects approximately 42% of adults in the US. Behavioral interventions can attain approximately 5% to 10% weight loss, GLP-1 agonists and glucose-dependent insulinotropic polypeptide/GLP-1 receptor agonists can attain approximately 8% to 21% weight loss, and bariatric surgery can attain approximately 25% to 30% weight loss. Comprehensive, evidence-based obesity treatment combines behavioral interventions, nutrition, physical activity, pharmacotherapy, and metabolic/bariatric procedures as appropriate for individual patients.

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Elmaleh-Sachs A , Schwartz JL , Bramante CT , Nicklas JM , Gudzune KA , Jay M. Obesity Management in Adults : A Review . JAMA. 2023;330(20):2000–2015. doi:10.1001/jama.2023.19897

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A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to predict obesity

Affiliations.

  • 1 Centre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Selangor, Malaysia.
  • 2 Centre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Selangor, Malaysia. Electronic address: [email protected].
  • 3 RIADI Laboratory, University of Manouba, Manouba, Tunisia; College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia.
  • 4 Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Selangor, Malaysia.
  • PMID: 34426171
  • DOI: 10.1016/j.compbiomed.2021.104754

Obesity is considered a principal public health concern and ranked as the fifth foremost reason for death globally. Overweight and obesity are one of the main lifestyle illnesses that leads to further health concerns and contributes to numerous chronic diseases, including cancers, diabetes, metabolic syndrome, and cardiovascular diseases. The World Health Organization also predicted that 30% of death in the world will be initiated with lifestyle diseases in 2030 and can be stopped through the suitable identification and addressing of associated risk factors and behavioral involvement policies. Thus, detecting and diagnosing obesity as early as possible is crucial. Therefore, the machine learning approach is a promising solution to early predictions of obesity and the risk of overweight because it can offer quick, immediate, and accurate identification of risk factors and condition likelihoods. The present study conducted a systematic literature review to examine obesity research and machine learning techniques for the prevention and treatment of obesity from 2010 to 2020. Accordingly, 93 papers are identified from the review articles as primary studies from an initial pool of over 700 papers addressing obesity. Consequently, this study initially recognized the significant potential factors that influence and cause adult obesity. Next, the main diseases and health consequences of obesity and overweight are investigated. Ultimately, this study recognized the machine learning methods that can be used for the prediction of obesity. Finally, this study seeks to support decision-makers looking to understand the impact of obesity on health in the general population and identify outcomes that can be used to guide health authorities and public health to further mitigate threats and effectively guide obese people globally.

Keywords: Diseases; Machine learning; Obesity; Overweight; Risk factors.

Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Publication types

  • Research Support, Non-U.S. Gov't
  • Systematic Review
  • Machine Learning
  • Metabolic Syndrome*
  • Obesity* / epidemiology
  • Risk Factors

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Complications of obesity in adults: A short review of the literature

Introduction.

Obesity, which broadly refers to excess body fat, has become an important public health problem. Its prevalence continues to increase worldwide. 1 As the prevalence of obesity increases so does the burden of its associated co-morbidities. 2 Non-communicable diseases and their risk factors including obesity are now becoming a significant problem not only in affluent societies but also in developing countries. 3 – 6

Assessing total body fat accurately requires sophisticated technology which is not readily available for purposes of the epidemiology of the disease. 7 , 8 The World Health Organisation (WHO) adopted body mass index (BMI), which is calculated by dividing the body weight in kilograms (Kg) by the square of the height in metres (m), as a surrogate measure of total body fat. 4 BMI correlates well with the percentage body fat in the young and middle aged where obesity is most prevalent. 7 , 8 With this index, obesity is defined when the value is equal to or more than 30Kg/m2. 7 , 8

However, not only does the total body fat matter but also the pattern of distribution. Excess visceral fat, also referred to as central obesity, has a stronger association with cardiovascular disease than subcutaneous fat with is deposited mainly around the hips and buttocks. Central obesity produces a characteristic body shape which resembles an apple and thus is also referred to as “apple shaped” obesity as opposed to “pear shaped” obesity in which fat is deposited on the hips and buttocks. 9 This distribution is also reflected in the waist circumference and Waist:Hip ratio (WHR), ie the ratio of the hip circumference to waist circumference.

In this review, data from different studies on complications of obesity are summarized and controversies discussed. Areas of current and future research in obesity and its complications have also been highlighted.

Current evidence linking obesity and mortality

Several large studies have demonstrated increased mortality above a certain threshold of BMI. In the Framingham heart study, a prospective cohort study, male and female non-smokers aged 40 years who were obese lived 5.8 and 7.1 years less than their non-obese counterparts. 10 Another study by Fontaine et al. which used data from the National Health and Nutrition Examination Survey (NHANES I and II) and the NHANES III Mortality Study, found a marked reduction in life expectancy in obese young adults compared to non-obese adults.

There is now evidence that not only does percentage of fat assessed by BMI matter in predicting mortality but also the distribution of fat in the body. The INTERHEART study, among other studies, showed that high hip fat distribution assessed by hip circumference had a negative predictive effect on myocardial infarction (MI) whereas high waist fat distribution again assessed by waist circumference was associated with high rates of MI. 11

The possible effect of fat distribution on mortality and morbidity cannot be ignored in view of these emerging data. Body fat distribution, assessed using magnetic resonance imaging in leading research institutions, and its effects on mortality and morbidity is currently a research topic of interest.

Morbidities related to obesity

Impaired glucose tolerance and diabetes mellitus.

There is currently no controversy that obesity is associated with impaired glucose tolerance or type 2 diabetes mellitus. The underlying mechanism is thought to be due to insulin resistance. However, there is currently limited data accurately quantifying insulin resistance using the standard hyperinsulinemic euglycemic clamp, 12 largely because the invasive nature of the procedure makes it unsuitable for general epidemiological studies. 12

The association of obesity with diabetes has been shown in several studies. In one of the biggest cohort studies, in which 84,941 female nurses were followed up for 16 years, there were 3,300 new cases of diabetes mellitus. Importantly, the study revealed that overweight or obesity was the main predictor of type 2 diabetes mellitus. 13 In men, there were similar findings from the Health Professional follow-up study. An age adjusted relative risk of 60.9 for developing diabetes was found in those with a BMI ≥35Kg/m2 in comparison to those with BMI <23Kg/m2. 14

In Malawi, the prevalence of diabetes in adults aged 25– 64 years is estimated at 5.6%. 3 However, there is limited data on obesity attributable diabetes in Malawian adults.

Hypertension

Data available shows a strong association between obesity and hypertension. In one large cohort study of 82,473 participants, BMI was positively associated with hypertension at age 18 and midlife. There was also marked increase in risk of hypertension with weight gain. 15 In the Framingham study, the relative risk of hypertension in overweight men and women were 1.46 and 1.75, respectively, after adjusting for age. 16 In the same study, reduction of weight in obese women at age 18 reduced the risk of hypertension.

In older populations, hypertension and obesity continue to relate in a predictable manner as has been shown in the Honolulu Heart Program and Japanese data survey. 17 , 18

Recently, waist circumference (WC) has been shown to be important in assessing obesity and the risk of hypertension. When WC and BMI were compared as continuous variables in the same regression model, WC was found to be a better predictor for obesity related risk, including hypertension, than BMI. 19 However, when WC was used as a categorical variable (normal or high), BMI was a better predictor. WC may be a valuable means of quantifying the risk of hypertension in the obviously obese individuals as it is cheap, easier and faster to apply than BMI which, in addition to a stadiometer, requires a weighing scale and calculation of the index.

Following a recent survey in Malawi, hypertension was estimated at 32.9% in adults aged 25–64 years. 3 The survey also found that 29% of the population in this age range were either overweight or obese possibly indicating that obesity may have played a role in hypertension. However, the association of obesity and hypertension was not interrogated in this survey.

Heart Disease

There is unequivocal evidence that there is an increased risk of coronary artery disease (CAD) in obesity. In the Asian Pacific Cohort Collaboration study in which more than 300,000 participants were followed, there was a 9 percent increase in events of ischaemic heart disease for a unit change in BMI. Increased risk of CAD was has also been found in the Framingham and Nurses Health Studies. 16 , 20

When the risk of heart failure (HF) was evaluated in the Framingham study, the risk of HF was found to be 2-fold in the obese group than in the non-obese group. 21 However, it appears that having a higher BMI improves survival in patients with congestive heart failure (CHF). In a retrospective analysis of 7,767 patients with CHF who were categorised into 4 BMI ranges including obesity (BMI>30kg/m2), there was reduced crude all case mortality with consecutively higher BMI groups in an almost linear fashion. After further analysis, overweight and obese patients had a hazard ratio of 0.88 compared to healthy weight patients (taken as the reference group) whereas underweight patients with stable CHF had a 1.21 risk of death when they were compared to the same reference group. 22

The reason for this is not clear. The authors argue that other cardiovascular morbidities associated with obesity and overweight may have lead to the diagnosis of HF in its earlier stages in the obese group than in the group with lower BMI, therefore, reducing the risk of death from CHF.22 However, the cardiopulmonary testing results of overweight and healthy weight patients, with CHF have been found to be similar. 23 , 24 Therefore, the foregoing argument is unlikely to account for this difference.

Clearly, with the known adverse effects of obesity and in the absence of knowledge on the mechanism of this ‘paradox’, recommending overweight or obesity for purposes of reduction of CHF associated mortality is not an option. Elucidating the mechanism of this paradox is currently an area of research interest.

Dyslipidaemia

Dyslipidaemia, manifested by reduced high density lipoprotein (HDL) and increased triglycerides, is associated with obesity. 25 The underlying mechanism is largely due to insulin resistance. Very low density lipoprotein (VLDL) clearance in plasma is dependent on the rate of hepatic synthesis and catabolism by lipoprotein lipase, an enzyme which is also involved in formation of HDL. 25 , 26 In obesity, insulin resistance is associated with increased hepatic synthesis of VLDL and impaired lipoprotein lipase. 26 , 27 There is evidence that dyslipidaemia can still occur in the absence of insulin resistance in obesity. In 1998, a study by Gary et al. showed a significant association between obesity, particularly central obesity, and dyslipidaemia after adjusting for insulin resistance.

Cerebrovascular Disease

Currently available evidence shows that the risk of haemorrhagic and ischaemic stroke, in relation to obesity, is increased in men. In women this relation is true with ischaemic stroke but not haemorrhage stroke. In the Korean prospective study involving 234,863 men who were followed up for 9 years, a significant positive association was found between BMI and the risk of ischemic stroke whereas, with haemorrhagic stroke, a J-shaped association was found showing that the risk increased more than that of ischaemic stroke at the upper and lower extremes of BMI. 28 Controlling for confounding factors attenuated the association but still yielded significant association.

In a prospective study of 39,053 participants (all women) followed up for an average of ten years, 432 strokes occurred. Three hundred and seven were ischaemic, 81 hemorrhagic and 4 undefined. In obese subjects (BMI > 30kg/m2), the hazard ratios (95% CI) for total stroke, ischaemic stroke and hemorrhagic stroke were 1.5 (1.16 to 1.94), 1.72 (1.30 to 2.28) and 0.82 (0.43 to 1.58), respectively. This was in comparison with the group of women with BMI less than 25kg/m2. 29

The reason for the discrepancy in risks of hemorrhagic stroke between men and women is not clear. Following findings from other studies that have shown higher incidence of hemorrhagic stroke in Asian populations in the setting of low cholesterol and lean body weight, 30 , 31 the authors argue that these factors (low cholesterol and lean body weight) may explain the observed findings in the latter studies. However, this still remains a hypothesis which needs investigating. Further, with this hypothesis one would expect men in the Korean and Physicians' studies to have shown increased risk of hemorrhagic stroke as well with the group with BMI towards lean body weight who presumably would have had low cholesterol levels. 28 , 32

Lately, central obesity (where fat is preferentially distributed around the trunk) has been shown to be important in predicting stroke mortality. In the Israel heart disease study, stroke mortality was predicted by trunk obesity alone independent of BMI, hypertension, diabetes and socioeconomic status. 37 , 33

Metabolic syndrome

According to the National Cholesterol Education Program's Adult Treatment Panel III (NCEP: ATP III), the metabolic syndrome is defined when an individual has any 3 of the following 5 features: (i) waist circumference above 40 inches for men and >35 inches for women, (ii) Triglycerides above 150mg/dl, (iii) HDL cholesterol above 40mg/dl for men and 50mg/dl for women, (iv) Blood pressure above 130/85 mmHg, (v) Fasting glucose above 100mg/dl.

Central obesity and insulin resistance, which leads to altered lipid and glucose metabolism, appear to be the basis for the features seen in metabolic syndrome. 34 The syndrome was originally intended for prediction of the risk of cardiovascular disease, however, this has recently been questioned as the sum of the combined risk factors appears not to offer more than the sum of individual factors. 35

Pulmonary abnormalities

Several studies have linked obesity and obstructive sleep apnea (OSA). In the Wisconsin Sleep Cohort study, obesity had a strong association with OSA. 36 In another study, increased neck circumference, which was also shown to correlate very well with obesity, had been shown to correlate with obstructive sleep apnea. 37 There have been two mechanisms that have been thought to contribute to OSA. Firstly, is the direct effect of increased fat tissue along the airway which impinges on the lumen. 38 Secondly, increased fat tissue has been implicated in increasing the collapsibility of the airway. 39

Asthma is another condition that may occur as a complication of obesity. There is evidence that obesity increases the risk of asthma. In one prospective multicentre study, the prevalence of asthma was observed to increase in obese patients. Seventy five per cent that presented with an asthmatic emergency were either obese or overweight. 40 Further prospective studies have shown that obesity predicts asthma. 41 The mechanism linking obesity and asthma includes increased airway hyper-responsiveness, decreased functional and tidal volumes, chronic systemic inflammation driven by increased inflammatory cytokines and chemokines, adipocytes derived factors leptin, adiponectin and plasminogen activator inhibitor. 42

Gastrointestinal abnormalities

Most epidemiological studies have found an association between obesity and increased risk of Gastroesophageal reflux disease (GORD). In one large cross-sectional population study, which was part of a randomized trial, involving 10, 537 subjects, the adjusted odds ratios for heart burn and acid regurgitation occurring once in a week in obese patients were 2.91 (95% CI 2.07 – 4.08) and 2.23 (95% 1.44–1.99) respectively, compared with those with normal BMI.46 Recent evidence from a meta-analysis involving data from studies between 1966 and 2004 has shown obesity to be significantly associated with GORD, esophageal cancer and erosive esophagitis and that these disorders appear to increase with increasing weight. 43

Another gastrointestinal condition that has been studied in relation to obesity is cholelithiasis. Data from the Nurses' study showed that females with BMI of more than 45Kg/m2 had a seven-fold increase in risk of gallstone disease compared to those with BMI of less than 24Kg/m2. 44 Men have had similar results. 45

Reproductive disease

Polycystic ovary syndrome (PCOS), characterized by anovulation, hyperandrogenism and a polycystic ovary, is associated with obesity as well as insulin resistance. It has been noted that increased visceral fat assessed by waist circumference of more than 88cm is associated with hyperandrogenemia in patients with PCOS and that reduction of insulin resistance by weight loss or drugs that increase peripheral sensitivity of insulin leads to improve hormonal aberrations and ovulation. 46

In men, abdominal obesity has been associated with impotence and infertility. In one single blinded randomised controlled trial of 110 obese men with erectile problems but no other risk factors namely diabetes, hyperlipidemia or hypertension, there was improvement of sexual function associated with decreased BMI. 47

There are other reproductive complications of obesity that occur in pregnancy and labour. These include gestational diabetes, macrosomia, dystocia and increased rates of caesarean sections. 48

Pyschosocial problems

Obesity in the affluent society has been associated with several untoward outcomes in terms of psychosocial or socioeconomic wellbeing. Obese females for example were found to be less likely to complete school, had a 20% less chance of getting married, earned less and had more household poverty in comparison to females that were not overweight. 49 However, the direction of causality can be either way since status causes obesity and obesity causes status. 50

Several psychiatric disorders have been linked to obesity. In one study involving psychiatric evaluation of 294 patients before bariatric surgery, the prevalence rates were as follows: somatization (29.3%), phobia (18%), hypochondriasis (18%) and obsessive-compulsive disorders 13.6%. Follow up of these patients after surgery showed that these psychopathologies had been reduced significantly. 51

Osteoarthritis

Osteoarthritis (OA) appears to follow obesity. In the Framingham cohort study, data from 1420 participants indicated that obesity was an important independent risk factor for OA after adjusting for age, physical activity and the levels of uric acid. 52 Other studies looking at the effect of weight reduction on obesity have shown a significant reduction in the odds of developing OA overtime, further providing evidence for this link. 53

OA involving weight bearing joints is common later in life and the prevalence is above 50% in both men and women by age 65 years. 54 The mechanism of OA has been presumed to be due to direct chronic strain on the joints related to the overweight. 55 However, there are now notions that non-mechanical mechanisms may contribute to OA in obesity as the same changes of OA seen in weight bearing joints have also been seen in non-weight bearing joints. There is growing evidence that dysregulation of adipokines (hormones from adipose tissue) such as adiponectin, visfatin and resistin may explain the link between obesity and OA - suggesting that osteoarthritis may be a systemic disease in obesity. 56

There is considerable evidence of an association between obesity and some cancers. 57 These include cancer of gallbladder, esophagus (adenocarcinoma), thyroid, kidney, uterus, colon and breast. 58 This link has further been strengthened by the observation that there is reduced incidence of cancer and mortality with weight loss. 59 , 60 However the underlying mechanism linking these cancers to obesity is not clear. For uterus and breast cancers, it is thought to be due to higher oestrogen levels synthesized from fat tissue in obese women. 61 , 62

Access to care

Obesity prevents certain medical procedures being done either due to the physical weight itself, or due to the increased risk of complications (including infections). 63 , 64 For example, most Computer Tomography scan tables and Magnetic resonance imaging machines have a weight limit of 450 Ib (204Kg). 63 Physical immobility due to obesity may also lead to restricted access to care. Surgical mortality is increased in obese patients and these patients may not be operated on purely due to surgical mortality risk associated with obesity. Obesity is also obstetric risk and is associated with increased risk of certain infectionswhich may require tertiary level care which may not always be accessible. 65

Obesity and other risk factors of non-communicable diseases (NCDs) are now emerging problems not only in affluent societies but also in developing countries like Malawi. In Malawi, the prevalence of obesity in adults is currently estimated at 4.6% (3). Obesity is predicted to rise over the coming years (4–6). Interventions to reduce the burden of obesity partly depend on recognising and understanding the complications of obesity. Clinicians are reminded to look for these complications in obese patients and institute interventions emphasizing the benefits of weight loss in obese patients.

  • Open access
  • Published: 21 June 2021

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 .

Peer Review reports

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.

Availability of data and materials

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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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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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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

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

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