research proposal on obesity

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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Obesity Research

Language switcher.

Over the years, NHLBI-supported research on overweight and obesity has led to the development of evidence-based prevention and treatment guidelines for healthcare providers. NHLBI research has also led to guidance on how to choose a behavioral weight loss program.

Studies show that the skills learned and support offered by these programs can help most people make the necessary lifestyle changes for weight loss and reduce their risk of serious health conditions such as heart disease and diabetes.

Our research has also evaluated new community-based programs for various demographics, addressing the health disparities in overweight and obesity.

NHLBI research that really made a difference

• In 1991, the NHLBI developed an Obesity Education Initiative to educate the public and health professionals about obesity as an independent risk factor for cardiovascular disease and its relationship to other risk factors, such as high blood pressure and high blood cholesterol. The initiative led to the development of clinical guidelines for treating overweight and obesity.
• The NHLBI and other NIH Institutes funded the Obesity-Related Behavioral Intervention Trials (ORBIT) projects , which led to the ORBIT model for developing behavioral treatments to prevent or manage chronic diseases. These studies included families and a variety of demographic groups. A key finding from one study focuses on the importance of targeting psychological factors in obesity treatment.

Current research funded by the NHLBI

The Division of Cardiovascular Sciences , which includes the Clinical Applications and Prevention Branch, funds research to understand how obesity relates to heart disease. The Center for Translation Research and Implementation Science supports the translation and implementation of research, including obesity research, into clinical practice. The Division of Lung Diseases and its National Center on Sleep Disorders Research fund research on the impact of obesity on sleep-disordered breathing.

Find funding opportunities and program contacts for research related to obesity and its complications.

Current research on obesity and health disparities

Health disparities happen when members of a group experience negative impacts on their health because of where they live, their racial or ethnic background, how much money they make, or how much education they received. NHLBI-supported research aims to discover the factors that contribute to health disparities and test ways to eliminate them.

• NHLBI-funded researchers behind the RURAL: Risk Underlying Rural Areas Longitudinal Cohort Study want to discover why people in poor rural communities in the South have shorter, unhealthier lives on average. The study includes 4,000 diverse participants (ages 35–64 years, 50% women, 44% whites, 45% Blacks, 10% Hispanic) from 10 of the poorest rural counties in Kentucky, Alabama, Mississippi, and Louisiana. Their results will support future interventions and disease prevention efforts.
• The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is looking at what factors contribute to the higher-than-expected numbers of Hispanics/Latinos who suffer from metabolic diseases such as obesity and diabetes. The study includes more than 16,000 Hispanic/Latino adults across the nation.

Find more NHLBI-funded studies on obesity and health disparities at NIH RePORTER.

Read how African Americans are learning to transform soul food into healthy, delicious meals to prevent cardiovascular disease: Vegan soul food: Will it help fight heart disease, obesity?

Current research on obesity in pregnancy and childhood

• The NHLBI-supported Fragile Families Cardiovascular Health Follow-Up Study continues a study that began in 2000 with 5,000 American children born in large cities. The cohort was racially and ethnically diverse, with approximately 40% of the children living in poverty. Researchers collected socioeconomic, demographic, neighborhood, genetic, and developmental data from the participants. In this next phase, researchers will continue to collect similar data from the participants, who are now young adults.
• The NHLBI is supporting national adoption of the Bright Bodies program through Dissemination and Implementation of the Bright Bodies Intervention for Childhood Obesity . Bright Bodies is a high-intensity, family-based intervention for childhood obesity. In 2017, a U.S. Preventive Services Task Force found that Bright Bodies lowered children’s body mass index (BMI) more than other interventions did.
• The NHLBI supports the continuation of the nuMoM2b Heart Health Study , which has followed a diverse cohort of 4,475 women during their first pregnancy. The women provided data and specimens for up to 7 years after the birth of their children. Researchers are now conducting a follow-up study on the relationship between problems during pregnancy and future cardiovascular disease. Women who are pregnant and have obesity are at greater risk than other pregnant women for health problems that can affect mother and baby during pregnancy, at birth, and later in life.

Find more NHLBI-funded studies on obesity in pregnancy and childhood at NIH RePORTER.

Learn about the largest public health nonprofit for Black and African American women and girls in the United States: Empowering Women to Get Healthy, One Step at a Time .

Current research on obesity and sleep

• An NHLBI-funded study is looking at whether energy balance and obesity affect sleep in the same way that a lack of good-quality sleep affects obesity. The researchers are recruiting equal numbers of men and women to include sex differences in their study of how obesity affects sleep quality and circadian rhythms.
• NHLBI-funded researchers are studying metabolism and obstructive sleep apnea . Many people with obesity have sleep apnea. The researchers will look at the measurable metabolic changes in participants from a previous study. These participants were randomized to one of three treatments for sleep apnea: weight loss alone, positive airway pressure (PAP) alone, or combined weight loss and PAP. Researchers hope that the results of the study will allow a more personalized approach to diagnosing and treating sleep apnea.
• The NHLBI-funded Lipidomics Biomarkers Link Sleep Restriction to Adiposity Phenotype, Diabetes, and Cardiovascular Risk study explores the relationship between disrupted sleep patterns and diabetes. It uses data from the long-running Multiethnic Cohort Study, which has recruited more than 210,000 participants from five ethnic groups. Researchers are searching for a cellular-level change that can be measured and can predict the onset of diabetes in people who are chronically sleep deprived. Obesity is a common symptom that people with sleep issues have during the onset of diabetes.

Find more NHLBI-funded studies on obesity and sleep at NIH RePORTER.

Learn about a recent study that supports the need for healthy sleep habits from birth: Study finds link between sleep habits and weight gain in newborns .

Obesity research labs at the NHLBI

The Cardiovascular Branch and its Laboratory of Inflammation and Cardiometabolic Diseases conducts studies to understand the links between inflammation, atherosclerosis, and metabolic diseases.

NHLBI’s Division of Intramural Research , including its Laboratory of Obesity and Aging Research , seeks to understand how obesity induces metabolic disorders. The lab studies the “obesity-aging” paradox: how the average American gains more weight as they get older, even when food intake decreases.

Related obesity programs and guidelines

• Aim for a Healthy Weight is a self-guided weight-loss program led by the NHLBI that is based on the psychology of change. It includes tested strategies for eating right and moving more.
• The NHLBI developed the We Can! ® (Ways to Enhance Children’s Activity & Nutrition) program to help support parents in developing healthy habits for their children.
• The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project standardizes data collected from the various studies of obesity treatments so the data can be analyzed together. The bigger the dataset, the more confidence can be placed in the conclusions. The main goal of this project is to understand the individual differences between people who experience the same treatment.
• The NHLBI Director co-chairs the NIH Nutrition Research Task Force, which guided the development of the first NIH-wide strategic plan for nutrition research being conducted over the next 10 years. See the 2020–2030 Strategic Plan for NIH Nutrition Research .
• The NHLBI is an active member of the National Collaborative on Childhood Obesity (NCCOR) , which is a public–private partnership to accelerate progress in reducing childhood obesity.
• The NHLBI has been providing guidance to physicians on the diagnosis, prevention, and treatment of obesity since 1977. In 2017, the NHLBI convened a panel of experts to take on some of the pressing questions facing the obesity research community. See their responses: Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents (PDF, 3.69 MB).
• In 2021, the NHLBI held a Long Non-coding (lnc) RNAs Symposium to discuss research opportunities on lnc RNAs, which appear to play a role in the development of metabolic diseases such as obesity.
• The Muscatine Heart Study began enrolling children in 1970. By 1981, more than 11,000 students from Muscatine, Iowa, had taken surveys twice a year. The study is the longest-running study of cardiovascular risk factors in children in the United States. Today, many of the earliest participants and their children are still involved in the study, which has already shown that early habits affect cardiovascular health later in life.
• The Jackson Heart Study is a unique partnership of the NHLBI, three colleges and universities, and the Jackson, Miss., community. Its mission is to discover what factors contribute to the high prevalence of cardiovascular disease among African Americans. Researchers aim to test new approaches for reducing this health disparity. The study incudes more than 5,000 individuals. Among the study’s findings to date is a gene variant in African Americans that doubles the risk of heart disease.

Explore more NHLBI research on overweight and obesity

The sections above provide you with the highlights of NHLBI-supported research on overweight and obesity . You can explore the full list of NHLBI-funded studies on the NIH RePORTER .

To find more studies:

• Type your search words into the  Quick Search  box and press enter. 
• Check  Active Projects  if you want current research.
• Select the  Agencies  arrow, then the  NIH  arrow, then check  NHLBI .

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Bridging the Evidence Gap in Obesity Prevention: A Framework to Inform Decision Making (2010)

Chapter: 10 conclusions and recommendations, 10 conclusions and recommendations.

D ecisions about prevention are complex, not only for the obesity problem but also for other problems with multiple types and layers of causation. Recognition of the need to emphasize population-based approaches to obesity prevention, the urgency of taking action, and the desire of many decision makers to have evidence on which actions to take have created a demand for evidence with which to answer a range of questions. In reality, the evidence approaches that apply to decision making about the treatment of obesity or other clinical problems are inadequate and sometimes inappropriate for application to decisions about public health initiatives. The need to work around evidence gaps and the limitations of using evidence hierarchies that apply to medical treatment for assessing population-based preventive interventions have been faced by the developers of several prior Institute of Medicine (IOM) reports on obesity prevention (focused on child and adolescent obesity). These evidence issues are not new and have already been the focus of many efforts in the field of public health in relation to other complex health problems. However, they are far from resolved. Considering these issues in relation to obesity prevention has the potential to advance the field of public health generally while also meeting the immediate need for clarity on evidence issues related to addressing the obesity epidemic.

The IOM’s Food and Nutrition Board formed the Committee on an Evidence Framework for Obesity Prevention Decision Making, with funding from Kaiser Permanente, the Robert Wood Johnson Foundation, and the Centers for Disease Control and Prevention. This committee was asked to develop a framework for evidence-informed decision making in obesity prevention, focused on approaches for assessing policy, environmental, and community interventions designed to influence diet and physical activity. The committee was tasked to:

provide an overview of the nature of the evidence base for obesity prevention as it is currently construed;

identify the challenges associated with integrating scientific evidence with broader influences on policy and programmatic considerations;

provide a practical and action-oriented framework of recommendations for how to select, implement, and evaluate obesity prevention efforts;

identify ways in which existing or new tools and methods can be used to build a useful and timely evidence base appropriate to the challenges presented by the epidemic, and describe ongoing attempts to meet these challenges;

develop a plan for communicating and disseminating the proposed framework and its recommendations; and

specify a plan for evaluating and refining the proposed framework in current decision-making processes.

CONCLUSIONS

Recognition is increasing that overweight and obesity are not only problems of individuals, but also societywide problems of populations. Acting on this recognition will require multifaceted, population-based changes in the socioenvironmental variables that influence energy intake and expenditure. There exist both a pressing need to act on the problem of obesity and a large gap between the type and amount of evidence needed to act and the type and amount of evidence available to meet that need. A new framework is necessary to assist researchers and a broad community of decision makers in generating, identifying, and evaluating the best evidence available and in summarizing it for use in decision making. This new framework also is important for researchers attempting to fill important evidence gaps through studies based on questions with program and policy relevance. However, the methods used and the evidence generated by traditional research designs do not yield all the types of evidence useful to inform actions aimed at addressing obesity prevention and other complex public health challenges. An expanded approach is needed that emphasizes the decision-making process and contextual considerations.

The Framework

To meet this need, the committee developed the L.E.A.D. ( L ocate Evidence, E valuate Evidence, A ssemble Evidence, and Inform D ecisions) framework, designed to facilitate a systematic approach to the identification, implementation, and evaluation of promising, reasonable actions to address obesity prevention and other complex public health challenges (see Figure 10-1 ). The framework is designed to help identify the nature of the evidence that is needed and clarify what changes in current approaches to generating and evaluating evidence will facilitate meeting those needs. This section describes the main components of the framework and issues related to these components.

Obesity prevention has not been addressed successfully by traditional study designs, which are generally linear and static. A systems approach is needed to develop more complex, interdisciplinary strategies. Accordingly, the L.E.A.D. framework

FIGURE 10-1 The L ocate Evidence, E valuate Evidence, A ssemble Evidence, Inform D ecisions (L.E.A.D.) framework for obesity prevention decision making.

recommends taking a systems perspective. In other words, it is necessary to use an approach that encompasses the whole picture, highlighting the broader context and interactions among levels, to capture the complexity of obesity prevention and other multifactorial public health challenges.

Addressing such challenges first requires specifying the question(s) being asked to guide the identification of evidence that is appropriate, inclusive, and relevant. Core to the framework is the orientation of the user. A variety of decisions have to be made to address obesity prevention. To capture the resulting mix of evidence needs, the framework adopts a typology that differentiates three broad categories of interrelated questions of potential interest to the user: Why should we do something about this problem? What specifically should we do? and How do we implement this information for our situation? This “Why,” “What,” “How” typology stresses the need for multiple types of evidence to support decisions on obesity prevention.

Once the question(s) of interest have been specified, locating useful evidence requires clear knowledge of the types of information that may be useful and an awareness of where that information can be found. The framework calls for the use of

diverse approaches to gather and synthesize information from other disciplines that address issues similar to those faced in obesity prevention and public health generally. Evidence identified and gathered to inform decision making for obesity prevention and other complex public health challenges should be assessed based on both its generalizability and level of certainty (i.e., its external and internal validity, respectively). The L.E.A.D. framework addresses these two key aspects of the evidence through the nature of the question(s) being asked, established criteria for the value of evidence, and the context in which the question(s) arise. Results of the overall evaluation of evidence should provide answers on what to do, how to do it, and how strongly the action is justified.

When decision makers are coming to a decision on obesity prevention actions, it is important for them to understand the state of the available knowledge relevant to that decision. This knowledge includes evidence on the specific problem to be addressed, the likely effectiveness and impact of proposed actions, and key considerations involved in their implementation. Successful evidence gathering, evaluation, and synthesis for use in obesity prevention usually require the involvement of a number of disciplines using a variety of methodologies and technical languages. The framework incorporates a standardized approach using a uniform language and structure for summarizing the relevant evidence in a systematic, transparent, and transdisciplinary way that is critical for communicating the process and conclusions clearly.

With an emergent problem such as obesity, decisions to act often must be made in the face of a relative absence of evidence, or evidence that is inconclusive, inconsistent, or incomplete. Evidence gathered from a particular intervention implemented in a closely controlled manner within a specific population with its own unique characteristics is often difficult to apply to a similar intervention with another population. The typical way of presenting results of obesity prevention efforts in journals often adds to the problem of incomplete evidence because useful aspects of the research related to its generalizability are not reported. If obesity prevention actions must be taken when evidence is limited, this incomplete evidence can be blended with theory, expert opinion, experience, and local wisdom to make the best decision possible. The actions taken then should undergo critical evaluation, the results of which should be used to build credible evidence for use in decision making about future efforts. Important alternatives to waiting for the funding, implementation, and publication of formal research on obesity prevention are natural experiments as sources of practice-based evidence, “evaluability assessment” of emerging innovations (defined as assessing whether a program is ready for full-scale evaluation), and continuous quality assessment of ongoing programs. The L.E.A.D. framework process leads to knowledge integration, or the incorporation of new knowledge gained through the process of applying the framework into the context of the organization or system where decisions are made.

The evidence base to support the identification of effective obesity prevention interventions is limited in many areas. Opportunities to generate evidence may occur

at any phase of the evidence review or decision-making process. The L.E.A.D. framework guides the generation of evidence related to “What,” “Why,” and “How” questions and supports the use of multiple forms of evidence and research designs from a variety of disciplines. In obesity prevention–related research, the generation of evi dence from evaluation of ongoing and emerging initiatives is a particular priority.

Researchers, decision makers, and intermediaries working on obesity prevention and other complex multifactorial public health problems are the primary audiences for communicating and disseminating the L.E.A.D. framework. With sufficient information, they can apply the framework as a guide for generating needed evidence and supporting decision making. It is important to understand the settings, communication channels, and activities of these key audiences to engage and educate them effectively on the purpose and adoption of the framework. To support the development of a communication and dissemination plan, it is critical to create partnerships, make use of existing activities and networks, and tailor the messages and approaches to each target audience.

As the target audiences begin to use the framework, assessing its use in selected settings will be essential so it can be improved and refined. Evaluation of the impact of the L.E.A.D. framework is also important for determining its relevance to current evidence-generation and decision-making processes. To this end, key outcome measures—utilization, adoption, acceptance, maintenance, and impact—should be defined and data collected on these measures. It will be important to develop or adopt data collection tools and utilize methods and existing initiatives that will best serve this purpose, as well as to systematically integrate the feedback thus obtained to sustain and improve the framework’s applicability and utilization.

RECOMMENDATIONS

The United States has made progress toward translating science into practice in the brief time since the obesity epidemic was officially recognized. But the pace of this translation has been slow relative to the scope and urgency of the problem and the associated harms and costs. As discussed above, moreover, the evidence emerging from applied research on obesity prevention can be inconclusive, incomplete, and inconsistent. A systematic process is needed to improve the use of available evidence and increase and enhance the evidence base to inform decisions on obesity prevention and other complex public health problems. Commitment to such a process is needed from both decision makers and those involved in generating evidence, including public and private policy makers and their advisors, scientific and policy think tanks, advocacy groups and stakeholders, program planners, practitioners in public health and other sectors, program evaluators, public health researchers and research scientists, journal editors, and funders. With this in mind, the committee makes the following recom-

mendations for assisting decision makers and researchers in using the current evidence base for obesity prevention and for taking a systems-oriented, transdisciplinary approach to generate more, and more useful, evidence.

Utilize the L.E.A.D. Framework

Recommendation 1: Decision makers and those involved in generating evidence, including researchers, research funders, and publishers of research, should apply the L.E.A.D. framework as a guide in their utilization and generation of evidence to support decision making for complex, multifactorial public health challenges, including obesity prevention.

Key assumptions that should guide the use of the framework include the following:

A systems perspective can help in framing and explaining complex issues.

The types of evidence that should be gathered to inform decision making are based on the nature of the questions being asked, including Why? (“Why should we do something about this problem in our situation?”), What? (“What specifically should we do about this problem?”), and How? (“How do we implement this information for our situation?”). A focus on subsets of these questions as a starting point in gathering evidence explicitly expands the evidence base that is typically identified and gathered.

The quality of the evidence should be judged according to established criteria for that type of evidence.

Both the level of certainty of the causal relationship between an intervention and the observed outcomes and the intervention’s generalizability to other individuals, settings, contexts, and time frames should be given explicit attention.

The analysis of the evidence to be used in making a decision should be summarized and communicated in a systematic, transparent, and transdisciplinary manner that uses uniform language and structure. The report on this analysis should include a summary of the question(s) asked by the decision maker; the strategy for gathering and selecting the evidence; an evidence table showing the sources, types, and quality of the evidence and the outcomes reported; and a concise summary of the synthesis of selected evidence on why an action should be taken, what that action should be, and how it should be taken.

If action must be taken when evidence is limited, this incomplete evidence can be blended carefully and transparently with theory, expert opinion, and collaboration based on professional experience and local wisdom to support making the best decision.

Sustained commitments will be needed from both the public and private sectors to achieve successful utilization of the various elements of the L.E.A.D. framework in future evidence-informed decision making and evidence generation. This respon-

sibility lies with the academic and research community, as well as with government and private funders and the leadership of journals that publish research in this area. Necessary supports will include increasing understanding of systems thinking and incorporating it into research-related activities, creating and maintaining resources to support the utilization of evidence, establishing standards of quality for different types of evidence, and supporting the generation of evidence, each of which is described in more detail below. Finally, it will be necessary to communicate, disseminate, evaluate, and refine the L.E.A.D. framework.

Incorporate Systems Thinking

Recommendation 2: Researchers, government and private funders, educators, and journal editors should incorporate systems thinking into their research-related activities.

To implement this recommendation:

Researchers should use systems thinking to guide the development of environmental and policy interventions and study designs.

Government and private funders should encourage the use of systems thinking in their requests for proposals and include systems considerations in proposal evaluations.

Universities, government agencies such as the U.S. Centers for Disease Control and Prevention, and public health organizations responsible for educating public health practitioners and related researchers should establish training capacity for the science and understanding of systems thinking and the use of systems mapping and other quantitative or qualitative systems analysis tools.

Journal editors should encourage the use of systems thinking for addressing complex problems by developing panels of peer reviewers with expertise in this area and charging them with making recommendations for how authors could use systems thinking more effectively in their manuscripts.

Build a Resource Base

Recommendation 3: Government, foundations, professional organizations, and research institutions should build a system of resources (people, compendiums of knowledge, registries of implementation experience) to support evidence-based public policy decision making and research for complex health challenges, including obesity prevention.

The Secretary of Health and Human Services, in collaboration with other public- and private-sector partners, should establish a sustainable registry of reports on evidence for environmental and policy actions for obesity prevention.

Integral to this registry should be the expanded view of evidence for decision making on obesity prevention proposed in this report and the sharing of experiences and innovative programs as the evidence evolves. A service provided by this registry should be periodic synthesis reviews based on mixed qualitative and quantitative methods.

The Secretary of Health and Human Services, in collaboration with other public- and private-sector partners, should develop and fund a resource for compiling and linking existing databases that may contain useful evidence for obesity prevention and related public health initiatives. This resource should include links to data and research from disciplines and sectors outside of obesity prevention and public health and to data from nonacademic sources that are of interest to decision makers.

Establish Standards for Evidence Quality

Recommendation 4: Government, foundations, professional organizations, and research institutions should catalyze and support the establishment of guidance on standards for evaluating the quality of evidence for which such standards are lacking.

Government and private funders should give priority to funding for the development of guidance on standards for evaluating the quality of the full range of evidence types discussed in this report that are useful in making obesity prevention decisions, especially those for which the scientific literature is limited.

Professional organizations and research institutions should encourage and bring attention to efforts by faculty, researchers, and students to establish guidance in this area.

Support the Generation of Evidence

Recommendation 5: Obesity prevention research funders, researchers, and publishers should consider, wherever appropriate, the inclusion in research studies of a focus on the generalizability of the find ings and related implementation issues at every stage, from conception through publication.

Those funding research in obesity prevention should give priority to support for studies that include an assessment of the limitations, potential utility, and applicability of the research beyond the particular population, setting, and circumstances in which the studies are conducted, including by initiating requests for applications and similar calls for proposals aimed at such studies. Additional ways in which this recommendation could be implemented include adding crite-

ria related to generalizability to proposal review procedures and training reviewers to evaluate generalizability.

Obesity prevention researchers and program evaluators should give special consideration to study designs that maximize evidence on generalizability.

Journal editors should provide guidelines and space for authors to give richer descriptions of interventions and the conditions under which they are tested to clarify their generalizability.

Recommendation 6: Research funders should increase opportunities for those carrying out obesity pre vention initiatives to measure and share their outcomes so others can learn from their experience.

Organizations funding or sponsoring obesity prevention initiatives—including national, regional, statewide, or local programs; policy changes; and environmental initiatives—should provide resources for obtaining practice-based evidence from innovative and ongoing programs and policies in a more routine, timely, and systematic manner to capture their processes, implementation, and outcomes. These funders should also encourage and support assessments of the potential for evaluating the most innovative programs in their jurisdictions and sponsor scientific evaluations where the opportunities to advance generalizable evidence are greatest.

Research funders, researchers, and journal editors should assign higher priority to studies that test obesity prevention interventions in real-world settings in which major contextual variables are identified and their influence is evaluated.

Recommendation 7: Research funders should encourage collaboration among researchers in a variety of disciplines so as to utilize a full range of research designs that may be feasible and appropriate for evaluating obesity prevention and related public health initiatives.

As part of their requests for proposals on obesity prevention research, funders should give priority to and reward transdisciplinary collaborations that include the creative use of research designs that have not been extensively used in prevention research but hold promise for expanding the evidence base on potential environmental and policy solutions.

Communicate, Disseminate, Evaluate, and Refine the L.E.A.D. Framework

Recommendation 8: A public–private consortium should bring together researchers, research funders, publishers of research, decision makers, and other stakeholders to discuss the practical uses of the

L.E.A.D. framework, and develop plans and a timeline for focused experimentation with the frame work and for its evaluation and potential refinement.

Interested funders should bring together a consortium of representatives of key stakeholders (including decision makers, government funders, private funders, academic institutions, professional organizations, researchers, and journal editors) who are committed to optimizing the use of the current obesity prevention evidence base and developing a broader and deeper base of evidence.

This consortium should develop an action-oriented plan for funding and implementing broad communication, focused experimentation, evaluation, and refinement of the L.E.A.D. framework. This plan should be based on the major purposes of the framework: to significantly improve the evidence base for obesity prevention decision making on policy and environmental solutions, and to assist decision makers in using the evidence base.

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

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• Funding Opportunities

NIH Obesity Research Funding Opportunities

NIH funding opportunities for obesity-related research appear below. We encourage you to discuss your proposed research with an NIH program director before applying.

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Obesity Research Proposals Samples For Students

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Childhood obesity is actually a condition that is currently a severe public health concern. It is a situation where the excess body fats negatively affect the wellbeing or health of our children. This situation has some effects on health of a child and for that reason it is crucial for parents to take the necessary precautionary measures or else we will not have future generations. These effects include psychological or emotional effects and diseases like high blood pressure, cancer, diabetes, sleep problems, heart disease, and other disorders. For that reason, this paper centers on the research proposal for this problem.

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Child obesity is rising around the world. Obesity is being observed at a younger age of children than in the past. There are many factors that have led to this trend. This paper seeks to examine one of these factors; parents’ connection to child obesity. It seeks to establish whether there is a substantive relationship and if it is there, to what extent does it cause obesity in children. The paper uses various data collection methods and analysis techniques to cover the issue.

Keywords: Child Obesity, Parents, BMI

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Childhood obesity..

More than one-third of children and adolescents are overweight or obese.

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Child obesity is out of control in the United States when one out of five children

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Summary The literature review covers the challenge faced by McDonalds in the increasing opposition to marketing its products to children and having an image for producing unhealthy foods. The research objective is to find solutions for the company to implement so that it can change this perception about the company and reduce opposition to its business practices.

Section 1: Summary of Business Problem and Research Objectives 2 Section 2: Literature Search and Review 2 Analysis of the Literature Review 5 Section 3: Research Objectives and Methodology 6

References 7

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Clinical Question What would be the effect of competitive food and beverage (CF&B) policies on student weight outcomes in comparison to the students who have not followed the CF&B policies and those who have followed some other policy according to which some of the competitive foods are available to students?

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Obesity has become a perennial problem for the modern world. The costs involving obesity in the United States alone have surpassed the 100 billion mark. Though recent studies have shown that the prevalence of obesity in children and young adults have stagnated in both the United States and Australia, the rates remain relatively high. This has raised the concern for the overweight and obesity problems for later generations in Australia and the United States.

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Research Proposal Childhood Obesity

Valery Delgado

Prof. Elisabeth von Uhl

ENGL 21002 M

Research Proposal

December 11, 2018

Childhood Obesity: A Hidden Issue Within Public Schools

THE PROBLEM:

Obesity has become a nationwide health epidemic that continues to expand from children to adults. Indeed, being overweight poses a higher risk for many other health problems to arise including but not limited to diabetes, high blood pressure, high cholesterol, and heart disease. Moreover, studies such as the one proposed by Roger et al. illustrates the increase frequency of childhood obesity observed in low-income neighborhoods due to the of lack resources in regards  health risk associated with obesity. With this in mind, this growing issue is a prevalent concern that continues to not be fully address in many public schools in the Bronx county. Being a former student i n the Mohegan Public School 67 and having the opportunity to observe the continuous disregard of health science information to young students is problematic.

Furthermore, some of these students continue to be exposed to easily accessible sugary and unhealthy food within and outside the perimeters of the school. Additionally, these children are not encourage to participate in different physical activity in school. On the other hand, many of these students already suffer from excess amount of weight causing them to lack motivation to perform any form of physical activities. In addition, it was observe that many of these students avoid interacting or playing with other children in the playground, but prefer consuming unhealthy snacks. Therefore, all public schools should provide new alternatives to teach children and parents the importance of a healthy meals, negative effects of unhealthy snacks and the risk associated with obesity.

BACKGROUND:

Certainly, childhood obesity continues in being a growing problem in the United States among children and adolescents leading to greater health risk among the youth. According to the CDC (2018), “obesity is prevalent among children and adolescents between the ages of 2 to 19 years old.” In addition, the CDC(2018) reported that “obesity prevalence was 13.9% for 2 to 5 year olds, 18.4% for 6 to 11 years old and 20.6% for 12 to 19 years old.” The data illustrates a positive correlation between the older ages and higher obesity which indicates that as these children become older they also become less aware of the possible issues associated with obesity. Additionally, Cynthia et al (2010) proposed a study that emphasizes the long term effects of childhood obesity lingering into adulthood. As a result, obesity can lead to higher probability of developing cardiovascular complications including high blood pressure, high cholesterol and diabetes. Interesting, the study also reveal that obesity was prevalent among low-income population compared to population in higher socioeconomic status. Therefore, one can expect that the lack of resources like money and access to nutritional food to be contributing factors towards higher obesity levels in children.

Moreover, another study reveals that “there seems to be a relationship between certain ethnic groups and their low socioeconomic status” (Rogers et al, 2015). The study states that childhood obesity is a common disease in low-income communities among Hispanic and non-Hispanic Black populations. Additionally, the CDC data demonstrates that there is a higher prevalence of childhood obesity among Hispanic and non-Hispanic Black  population with a prevalence rate of up 25.8% and 22% respectively, while the childhood obesity rate of non-Hispanic white is much lower at 14.1% (2018). Such discrepancies in obesity rates possibly suggest that children and parents in minority communities lack health related information. Another consideration can be attributed to low income neighborhoods which are predominantly African American and Hispanic so the obesity rate could be expected to be much higher in these communities. Rogers et al study also states that “African American and Hispanics children within the low socioeconomic status are most likely to be in the overweight or obese category“(2015).

LITERATURE REVIEW:

These studies demonstrates that childhood obesity is not just present in low-income populations but emphasises additional factors that increases the likelihood of these children developing obesity as a long term health problem. Public schools in the city usually allow students to purchase inexpensive unhealthy meals from vending machines or fast food stands that are easily accessible throughout the neighborhood. As a result, these students have a higher consumption rate of sugary snacks which limits their physical motivation to participate in any physical activity. For instance, “33% of children and 41% of adolescents on average had consumed meals from a fast food restaurant”(Poti et al, 2014). The reason why majority of  children pick unhealthy meals is primarily due to the inexpensive prices of unhealthy snacks like chips, cookies and candy as “most likely, the availability of unhealthy sustenances are predominant in low income neighborhoods” (Rogers et al, 2015). Moreover, the price convenience outweighs the nutritious options not only in the eyes of the children but also the parents as “fast food intake is correlated with dietary preferences, access to fast food places and income constraints, influence how individuals eat throughout the day (Poti et al, 2014). However, parents are not noticing the poorer eating habits being taught to their children.

Interestingly, the average amount of calories intake continues to increase among children and adolescents. The environmental factors of nearby fast food places and limited budget is a influencing factor for fast food consumption. In addition, “fast food are higher in solid fat then in food consumed from retail stores or schools and few items on children menu align with national nutrition standards or dietary guidelines” (Poti et al, 2014). Children are not meeting the daily requirement of nutrition because fast foods have a higher concentration of fat which contributes to weight gain. Therefore, public schools can be used as the intermediate for children and parents to acknowledge the risk associated with obesity and unhealthy eating.  

Additionally, “obesity severely affects children in low income households with 18.9% of children and adolescents between 2 to 19 years old being classified as obese” (CDC,2018). Consequently, “obesity prevalence increased by 23 to 33% for children in low income families” (Rogers et al, 2015). In addition, “23.7% of African Americans between the ages of 12 to 19 were considered obese, while whites within the same age group had 16.1% of obesity prevalence”(Rogers et al, 2015). African Americans live in low income area compared to Caucasians that are part of the high socioeconomic status. Indeed, these children that grow up in low-income population have a higher possibility of developing obesity due to the limitations not only within their communities but also the public schools they attend..

OBJECTIVES:

The long term goal of this research is to develop an educational program within public schools that would teach children and parents of the benefits of healthy eating, promoting physical activity and risks associated with the constant consumption of unhealthy eating habits. The information gathered from multiple studies can be used to develop an outline with the contributing factors that can potentially caused health related problems such as obesity among children and adolescents.

For the study under Cynthia L.Ogden et al (2010) examined the relationship of obesity and socioeconomic status among children and adolescents. Indeed, the study illustrated the correlation between childhood obesity and income status of the household head. One of the results found that children and adolescents living with the head of a household with a college degree are less obese than those without an education. As stated before, low income children and adolescents had a higher obesity rate compared to those of a higher economic status. Therefore, both of these findings demonstrated that the prevalence of obesity decrease as income increases which can suggest that limitation of knowledge is possible cause of unhealthy eating habits.

In addition, Rogers et al (2015) study further examined the relationship of obesity between ethnic groups and socioeconomic status. The results indicated a higher rate of obesity present in children of  African Americans and Hispanics in low income status compared to their Caucasian counterpart. Alternatively, families of low income status were less likely to notice their children being overweight. Therefore, lower household income is associated with higher prevalence of obesity among children.

Furthermore, the Jennifer M. Poti et al (2014) study demonstrated the association of fast food intake with poor diet is abundant pattern among obese children. The results concluded that half of  U.S children consumed fast food on a daily basis. From previous observation during a field site view of the Mohegan Public school, such findings are relevant with the eating habits present among the students. As a result, fast food consumption was correlated with obesity or overweight among children.

The Center for Disease Control (2018) provided a national representative sample about the prevalence of childhood obesity in the United States. The results provided the percentage of obesity for each of the three age groups such as 2 to 5 year olds, 6 to 11 years old and 12 to 19 years old. In addition, children within minority communities like Hispanic and African Americans had a higher obesity prevalence compared to their Asian and White counterpart. Furthermore, obesity prevalence was higher in low income group and families that lacked a education. Overall, ethnicity and socioeconomic status are the contributing factors of childhood obesity.

In order to develop a guideline of prevalent information for public schools to use as in outline for parents and students, a study will be developed to test whether the information provided can expand awareness of health risk associated with unhealthy lifestyle activities. The focus group will include a sample size consisted of children between the ages of elementary and middle school and if possible the parents could participate. Participants will be randomly selected from the Mohegan Public School 67. Next, A educational program will be provided to inform the participants about healthy eating, the benefits of physical activities and risk of unhealthy eating.

Afterward, each participant will completed a 20 question survey. The questionnaire will contain a series of questions focusing on various topics expanding from preference in physical activities, eating habits, knowledge of health risk issues. The answers will be recorded as an scale that will range from strongly agree to strongly disagree. Furthermore, through data analysis the most important prevalent information will be gathered depending on the common answers among the subjects. At this point, an educational outline could be provided to the school for further testing with a larger sample size. The final outline will need to be tested on multiple trials to condense the information into a format that is understandable for both children and parents.

CONCLUSION:

Overall, many students within public schools  are constantly exposed to unhealthy eating habits that also prevents from participation in physical activities. These children and adolescents can or will be consider overweight and obese which would most likely continue to negatively affect them during adulthood. Indeed, obesity can lead to further health complications. There are certain factors that contribute to childhood obesity such as ethnicity, income and education. However, there is a possible solutions to reducing obesity among the youth. As a recommendation, a continuous program can be develop to educate these young minds about healthy eating and positive thinking as this should be a standard application within public schools in order to prevent and hopefully lower the cases pertaining health related issues from childhood obesity.

Works Cited

“Childhood Obesity” CDC,  August 13, 2018 https://www.cdc.gov/obesity/data/childhood.html

Cynthia L.Ogden, Ph.D.; Molly M.Lamb, Ph.D.; Margaret D. Carroll, M.S.P.H.; and Katherine

• Flegal, Ph.D ( December 2010) Obesity and Socioeconomic Status in Children and Adolescents: United States. 2005-2008. U.S Department of Health and Human Services. No.51

Jennifer M. Poti, Kiyah J Duffey, and Barry M. Popkin (2014). The association of fast food consumption with poor dietary outcomes and obesity among children: is is the fast food or the remainder of the diet. The American Journal of Clinical Nutrition   99(1):162-71.

Robert Rogers, BA, Taylor F. Eagle, BS, Anne Sheetz, MPH, Alan Woodland, MD, Robert Leibowitz, PhD, Minkyoung Song, PhD, RN, FNP-BC, Rachel Sylvester, BS, Nicole Corriveau, BS, Eva Kline- Rogers, MS, RN, Qingmei Jiang, MA, MS, Elizabeth A. Jackson, MD, MPH, and Kim Eagle, MD ( Dec 1. 2015)  The Relationship between Childhood Obesity, Low Socioeconomic Status, and Race/Ethnicity: Lessons from Massachusetts. 11(6): 691–695.

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Adult obesity complications: challenges and clinical impact

Saleem ansari.

Clinical Biochemistry, King’s College Hospital, Denmark Hill, London, England SE5 9RS, UK

Hasan Haboubi

Department of Gastroenterology, Guy’s & St Thomas’ Foundation trust, London, England, UK

Nadim Haboubi

Consultant Physician, University of South Wales, Pontypridd, Rhondda Cynon Taff, UK

The complications associated with adult obesity are overwhelming national healthcare systems. No country has yet implemented a successful population-level strategy to reverse the rising trends of obesity. This article presents epidemiological data on the complications of adult obesity and discusses some of the challenges associated with managing this disease at a population and individual level.

Introduction

Adult obesity [body mass index (BMI) >30 kg/m 2 ] was estimated to affect 10.8% of men (266 million) and 14.9% of women (375 million) worldwide in 2014. This has more than doubled when compared with worldwide figures in 1975 where 3.2% of men and 6.4% of women were obese. If this trend persists, by 2025, 18% of men and 21% of women will be obese. 1 Since 2006, the rise in adult obesity has remained stable in many developed countries except for morbid obesity (BMI > 40 kg/m 2 ), which continues to rise 2 ; in developing countries obesity prevalence is rising towards levels seen in the Western world. 3 Indeed, the World Health Organisation (WHO) has set governments across the world the challenge of preventing further rises in obesity by 2025 to meet the overarching aim of preventing premature death from the four most common non-communicable diseases – cardiovascular disease (CVD), diabetes, cancer and chronic respiratory disease. 4

The current review presents epidemiological data pertaining to the complications of adult obesity and some of the challenges associated with managing this disease at a population and individual level.

Obesity, mortality and BMI

Obesity, as defined by BMI ( Table 1 ), is associated with an increased risk of all-cause mortality, with CVD and malignancy being the most common causes of death. 5 – 8 A meta-analysis of 239 prospective studies involving 10.6 million individuals from Asia, Australia, New Zealand, Europe and North America found that all-cause mortality was lowest between a BMI of 20–25 kg/m 2 but increased significantly just below this range and throughout the overweight/obese categories, 8 which suggests a J-shaped relationship between BMI and mortality. Ethnic differences for BMI ranges defining overweight and obesity exist, especially between Caucasian and Asian populations, reflecting the higher risk of cardiometabolic complications at a lower BMI in the latter population ( Table 1 ). 9 Although BMI is the simplest and most common anthropometric method for diagnosing obesity, waist circumference (WC) or waist-to-hip ratio (WHR) may better predict cardiometabolic disease because they are better measures of abdominal obesity. 10 , 11 Combining BMI and WC or WHR will capture total body fat distribution better than BMI alone and may help identify individuals with metabolic syndrome ( Table 2 ) at an earlier stage. Given that individuals frequently know their waist size, this may be a more practical measure to self-report compared with height and weight, which can often be misreported. 12

Adult BMI classification. 13

BMI, body mass index.

Risk factors used in the clinical diagnosis of the metabolic syndrome. 15

Three risk factors from Table 2 are required for a diagnosis of the metabolic syndrome.

HDL, high-density lipoprotein; IDF, International Diabetes Federation; WC, waist circumference.

Mechanisms by which obesity causes complications

The excess adiposity that characterises obesity can cause complications through anatomical and metabolic effects.

Anatomical effects

Increased adipose tissue can place strain at various body sites leading to obstructive sleep apnoea (OSA), obesity hypoventilation syndrome (OHS) and osteoarthritis, especially of weight bearing joints. 16 – 18 Also, increased intra-abdominal pressure is associated with oesophageal disorders such as gastro-oesophageal reflux disease (GORD) and Barrett’s oesphagus. 19

Subcutaneous adipose tissue is a ‘metabolic sink’ that stores excess calories as triglycerdies through adipocyte hyperplasia and hypertrophy, which protects lean visceral organs such as the heart, kidney, liver and pancreas. However, if subcutaneous adipose tissue capacity is exceeded, hypertrophied adipocytes rupture, triggering inflammation, and triglycerdies are deposited within visceral adipose tissue 20 ; indeed obesity is associated with diastolic heart failure, chronic kidney disease (CKD), non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM). 21

Metabolic effects

Visceral adipose tissue is a potent source of proinflammatory cytokines [tumour necrosis factor alpha (TNF-α), interleukin (IL)-1 and IL-6], which are implicated in cardiometabolic diseases, malignancy and infectious diseases among patients with obesity. 20 Lipid-induced cellular insults (lipotoxicity) due to elevated free fatty acids and lipid intermediates such as ceramides are also implicated in cardiometabolic disorders (e.g. insulin resistance, NAFLD, CVD) that are associated with the metabolic syndrome. 22 Chronic inflammation and endothelial dysfunction are also key mediators linking obesity with CVD. 23

Type 2 diabetes mellitus

Diabetes mellitus affected 8.5% of the adult European population in 2013, which equates to 56.3 million people. 24 Latest figures suggest that 4.7 million people in the United Kingdom (UK) are affected by diabetes (6% of the UK population), of which 90% have T2DM. UK diabetes prevalence is expected to reach 5 million by 2025. 25 ‘Diabesity’ describes the concurrent obesity and T2DM epidemic over the past few decades because the risk of T2DM increases with BMI. A recent population study involving 2.8 million UK adults between 2000 and 2018 showed that a BMI of 30–35 kg/m 2 was associated with a five times increased risk of T2DM, which increased to a 12 times higher risk in those with a BMI of 40–45 km/m 2 . 26 One mechanism linking obesity to T2DM is related to an increase in liver and pancreatic visceral fat, 27 which is better measured by WC or WHR than BMI. Excess hepatic triglycerdies are transported in very low-density lipoproteins to all tissues, including the beta-cells of the pancreas, and over many years this results in progressive pancreatic beta-cell dedifferentiation with a subsequent relatively sudden onset of clinical diabetes. 27 Data from the Counterpoint, Counterbalance and DIRECT studies have demonstrated that remission of T2DM and improvements in liver and pancreatic fat using magnetic resonance imaging were achieved with a very low-calorie diet (600–853 kcal/day) for 8 weeks to achieve weight loss of 15 kg. 28 – 30 These studies demonstrate that remission of T2DM depended primarily on weight loss through reductions in liver and pancreatic visceral fat. 27

Cardiovascular disease

Approximately 17.9 million people die from CVD annually, which accounts for 31% of all deaths worldwide. Ischaemic heart disease and stroke are the two most common causes of mortality worldwide. 31

Coronary heart disease

A case-control study involving 27,000 participants from 52 countries demonstrated that WHR was the strongest predictor of myocardial infarction (MI), independent of age, gender, ethnicity, smoking status or CVD risk factors (hypertension, diabetes, dyslipidaemia). The relationship between BMI and MI was weaker and less consistent across ethnic groups. 32 The EPIC-Norfolk prospective cohort study involving 24,508 UK men and women followed over 9.1 years also found that WHR was more consistently and strongly predictive of coronary heart disease (CHD) after adjusting for BMI, smoking, hypertension and hypercholesterolaemia. 33 Clearly, CHD is strongly associated with obesity but indices of abdominal obesity are better predictors than BMI. 34 The distribution of fat independently mediates the risk between obesity and CHD and this is likely to be due to ectopic visceral fat promoting chronic inflammation, which participates in all stages of atherosclerosis, including acute thrombosis. 35 Indeed, abdominal obesity is the hallmark of the metabolic syndrome ( Table 2 ) which increases cardiometabolic risk. 15

Obesity is associated with an increased risk of stroke but this relationship is stronger and more consistent for ischaemic stroke. A meta-analysis of 25 studies involving 2,247,961 participants from Western and Eastern countries showed that obese individuals (BMI > 30 kg/m 2 ) had a 64% increased risk of ischaemic stroke [relative risk (RR) 1.64, 95% confidence interval (CI) 1.36–1.99] and 24% increased risk of haemorrhagic stroke, which was not significant (RR 1.24, 95% CI 0.99–1.54). 36 The association between obesity and ischaemic stroke is mediated by conventional modifiable CVD risk factors and independent mechanisms related to proinflammatory cytokines, reduced levels of adiponectin and a prothrombotic state (hyperfibrinogenaemia, hyperviscosity), which contribute to endothelial cell dysfunction and atherosclerosis. 37 , 38 The relationship between obesity and haemorrhagic stroke is less consistent. 39

Gastrointestinal complications

There are several gastrointestinal and hepatobiliary complications of obesity ( Table 3 ), many of which are common and present sooner than cardiometabolic disorders. 19 Therefore screening for obesity in patients with gastrointestinal and hepatobiliary disease should be common practice for early weight loss intervention.

Quantified risk ratios and physiological mechanism of selected gastrointestinal diseases associated with obesity. Taken and adapted from Camilleri et al. 19

CI, confidence interval; GORD, gastro-oesophageal reflux disease; NAFLD, non-alcoholic fatty liver disease; OR, odds ratio; RR, relative risk.

Non-alcoholic fatty liver disease

NAFLD has an estimated prevalence of 25.2% worldwide and 23.7% in Europe, 40 but the true incidence is difficult to characterise due to different diagnostic criteria between studies. The prevalence of NAFLD has increased over the past four decades alongside the increase in obesity. 40 A meta-analysis of 20 studies (12,065 cases, 33,693 controls), 17 from Asian countries and 3 from Western countries, demonstrated that the odds of NAFLD increased by 3–10% per 1 cm increase in WC and 13–38% per 1-unit increase in BMI. 41 Although both BMI and WC were independently associated with NAFLD, markers of abdominal obesity were stronger predictors and remained associated with NAFLD after adjusting for BMI. This may explain why some patients with a normal BMI can develop NAFLD, which is more commonly seen in rural areas of some Asian countries (25–30%) compared with the United States (US) and Europe (10–20%). 41 Therefore, both BMI and WC or WHR should be used to assess NAFLD risk. NAFLD is considered the hepatic manifestation of the metabolic syndrome, 42 whereas longitudinal studies suggest that NAFLD precedes the metabolic syndrome and T2DM. 43 NAFLD increases the risk of T2DM, hypertension, dyslipidaemia and CKD, and it is no surprise that CVD is the leading cause of mortality among this patient group. 10 , 11 Up to one-third of NAFLD patients are at risk of developing non-alcoholic steatohepatitis (NASH), 44 which can progress to liver cirrhosis, hepatocellular carcinoma (HCC), decompensated liver cirrhosis and death. 45 Therefore, individuals with NAFLD require early weight loss intervention to prevent both cardiovascular- and liver-related morbidity and mortality.

Biliary complications

Obesity increases the risk of gallbladder disease. A systematic review of 17 prospective studies involving 1,921,103 participants found a RR of 1.63 for a 5-unit increase in BMI and a RR of 1.46 for a 10 cm increase in WC. 46 There was an almost two-fold increased risk of gallbladder disease from the lower to the upper limit of the normal BMI range (18.5–24.9 kg/m 2 ), which suggests that even moderate increases in adiposity increase risk. 46 Hormone changes and gallbladder dysmotility are suggested mechanisms to explain the association between obesity and gallbladder disease ( Table 3 ). 19

Oesphageal complications

Obesity is also associated with oesophageal disorders ( Table 3 ). The prevalence of GORD increases with obesity and meta-analyses report a positive association between BMI and GORD. 47 , 48 Central obesity is an independent predictor of the consequences of GORD (oesphagitis, Barrett’s oesphagus, adenocarcinoma). 49

Respiratory

Obstructive sleep apnoea.

Obesity is the most common risk factor for the development of OSA. Observational data from 2.8 million UK adults found that class I and III obesity were associated with a 5-times and 22-times increased risk of OSA, respectively, 26 which suggests that the risk of OSA increases considerably at a higher BMI. Untreated OSA can cause excessive daytime somnolence, negatively affect work performance, increase the risk of CVD and threaten vehicle licence if driving is affected. 50 , 51 Proposed mechanisms linking obesity to OSA include adipokines, upper airway adiposity and increased neck circumference causing pharyngeal collapse. 50

Obesity hypoventilation syndrome

OHS is defined as a combination of obesity (BMI > 30 kg/m 2 ), daytime hypercapnia (pCO 2  > 6 kpa) and sleep disordered breathing that are not due to other conditions associated with alveolar hypoventilation. 17 OHS has an estimated prevalence of 8.5% in patients with OSA and 19–31% among obese patients. 55 , 56 The pathophysiology of OHS may be related to leptin resistance causing central hypoventilation, impaired compensatory response to hypercapnia and impaired respiratory mechanics due to obesity. 57 The morbidity and mortality of OHS is greater than OSA. The chronic daytime hypoxia and hypercapnia increase the risk of pulmonary hypertension, right-sided heart failure and cor pulmonale. 17 Weight loss is recommended for both OSA and OHS, but adherence to lifestyle interventions can be difficult for this cohort because their exercise capacity is limited due to daytime somnolence, fatigue and chronic hypoxia, whereas poor sleep is associated with increased appetite. 16 Pharmacological therapy has not been proven to be effective in OSA and OHS. 16 Bariatric surgery is an effective treatment for OSA and parameters of sleep quality, 58 but data on OHS is limited due to the associated pulmonary and cardiac complications and therefore weight loss in this group of patients with chronic cardiorespiratory disease can be challenging. 17 Presently, no randomised control data exist to support bariatric surgery as an intervention to treat OHS. 59

Obesity increases the risk of asthma in children and adults. Over the past 40 years, there have been parallel increases in childhood obesity and asthma, with asthma prevalence doubling between 1980 and 1994. 52 A meta-analysis of seven prospective epidemiological studies involving 333,102 adult participants found that the prevalence of asthma was 38% in overweight individuals and 92% in obese individuals. 53 Two distinct asthma phenotypes have been described in obese patients; the early-onset allergic form and the late-onset non-allergic form, 54 and weight loss has been associated with improvements in lung function and asthma symptoms among obese patients. 16 The mechanism by which obesity increases asthma risk is unclear but may be related to mechanical, inflammatory and hormonal factors. 52

After smoking, obesity is the second biggest preventable cause of cancer in the UK and maintaining a normal weight could prevent 22,800 annual UK cases. 60 In 2001, the International Agency for Research on Cancer concluded that obesity accounted for 10% of post-menopausal breast cancers and 11% of colon cancers. For kidney, lower oesophageal adenocarcinoma and endometrial cancer, the risks attributed to BMI alone were 25%, 37% and 39%, respectively. 61

A population-based prospective cohort study using data from 5.24 million UK adults concluded that BMI was associated with 17 cancers. 62 Each 5 kg/m 2 increase in BMI was approximately linearly associated with cancer of the uterus, gallbladder, kidney, cervix, thyroid and leukaemia. There was a non-linear but positive association between BMI and liver, colon, ovarian and post-menopausal breast cancer. 62 The authors concluded that the heterogeneity in the effects of BMI on cancer risk suggests that there may be different mechanisms based malignancy type and patient sub-group. 62 Frequently cited mechanisms linking obesity to malignancy include systemic alterations in endogenous hormone metabolism (e.g. insulin, insulin-like growth factor, sex steroids) and chronic inflammation mediated by adipokines. 61

Obesity also impacts cancer prognosis. A meta-analysis of 82 studies involving 213,075 breast cancer patients showed that obesity (BMI > 30 kg/m 2 ) was associated with increased cancer-related mortality. 63 Similarly, the Nurses’ Health Study, which included 5204 patients with non-metastatic breast cancer, showed that weight gain after diagnosis was associated with increased risk of recurrence and breast-cancer specific mortality. 64 Weight loss by diet and physical activity has been shown to reduce the risk of postmenopausal breast cancer; however, evidence for other cancers is less robust. 65

Obesity and cognition

Cardiovascular risk factors such as T2DM, dyslipidaemia and hypertension are well-established complications of obesity that increase the risk of dementia and Alzheimer’s disease. 21 An independent relationship between mid-life obesity and dementia also exists. A meta-analysis of 39 prospective cohort studies analysing data from 1.3 million adults across the US, Europe and Asia found that a high BMI (overweight or obese range) was associated with an increased risk of dementia when BMI was measured 20 years prior to dementia diagnosis, but this relationship was reversed when BMI was measured closer to dementia diagnosis (<10 years). 66 The latter finding could be interpreted as obesity being protective; however, it is likely to be explained by reverse causation and the former finding can be explained by the fact that clinical dementia is preceded by a long (20–30 years) preclinical phase where weight loss is common. 67 , 68

Genitourinary

Obesity is an important preventable risk factor for the development CKD because it is associated with major CKD risk factors: diabetes mellitus and hypertension. 69 A large cohort study accruing over 8 million person-years found that a BMI > 25 was an independent predictor for end-stage renal disease. When compared with normal-weight controls (BMI 18.5–24.9 kg/m 2 ) the RR of end-stage renal disease for overweight individuals was 1.87 (95% CI; 1.64–2.14) and 7.07 (95% CI; 5.37–9.31) for those with class III obesity after adjusting for other CKD risk factors. 69 One proposed independent mechanism linking obesity to CKD is hyperfiltration due to the increased metabolic demands of excess body weight. 70

Between 1986 and 2000, there was a 10-fold increase in obesity-related glomerulopathy, which is characterised by proteinuria, glomerulomegaly, progressive glomerulosclerosis and renal function decline. 71 Short-term improvement is achieved with renin-angiotensin-aldosterone blockade, whereas weight loss through low-calorie dieting or bariatric surgery is associated with improvements in proteinuria and kidney function. 72 A prospective randomised control trial observed that 3 months of endurance and endurance-strength exercise among obese women (BMI 35 kg/m 2 ) was associated with an 10 ml/min/1.73 m 2 improvements in estimated glomerular filtration rate. 73

Obesity can increase the risk of kidney stones, 74 and roux-en-y gastric bypass, an operation used to treat obesity, can also increase the risk of hyperoxaluric kidney stones due to increased enteral oxalate absorption. 75 General and central obesity are both associated with urinary incontinence in men and women, overactive bladder syndrome in women and benign prostatic hyperplasia in men. 76 , 77

Musculoskeletal

Obesity is a well-recognised risk factor for the development and progression of osteoarthritis in weight-bearing joints, especially the knee. 18 There is a 36% increased risk of knee osteoarthritis with every 2 unit increase in BMI and patients with obesity suffer more severe joint degeneration. 78 Both obesity and osteoarthritis can reduce mobility, which can increase the risk of weight gain. In patients with osteoarthritis, weight loss of 10% has been associated with an improvement in joint symptoms, physical function and health related quality of life. 18

Osteoarthritis. Obesity is also associated with osteoarthritis in non-weight bearing joints such as the hands, which is linked to increased levels of adipokines. 79 Similarly, inflammatory markers observed in obesity are also associated with pre-clinical rheumatoid arthritis. 80 Prospective cohort data from the Nurses’ Health Study accruing more than 4,500,000 person-years of follow up showed that excess body weight (BMI > 24.9 kg/m 2 ) was associated with a 40–70% increased risk of rheumatoid arthritis in women, with the highest risk observed in overweight or obese women aged 18 years old. 80 Therefore, interventions that combat childhood obesity may reduce the incidence of adult rheumatoid arthritis.

Obesity has been independently associated with gout. A longitudinal community-based cohort study involving 15,533 men and women demonstrated that the relative risk of gout was almost doubled in those with a BMI > 30 kg/m 2 , and that obesity was associated with earlier onset of the disease. 81 Both gout and obesity are associated with elevated levels of serum uric acid and weight loss has been associated with reduced incidence of hyperuricaemia and gout attacks. 82

Psychosocial

Individuals with obesity are often stigmatised in education, health and employment settings. This results in obesity discrimination, 83 which has increased by 66% over the past decade with prevalence rates comparable with those of race-based discrimination. 84 Discrimination can result in low self-esteem and poor body image, which can negatively impact engagement in physical activity. 85 Obesity is also associated with psychiatric comorbidity. A cross-sectional US epidemiological survey showed that obesity (BMI > 30 kg/m 2 ) was associated with an approximately 25% increased odds of mood and anxiety disorders. 86 Similarly, another US epidemiological study involving 41,654 respondents in the National Epidemiologic Survey on Alcohol and Related Conditions showed that obesity was associated with an increased odds of alcohol use and mood, anxiety, and personality disorders, with odds ratio ranging from 1.28 to 2.08. 87 Increased BMI is also associated with an increased risk of suicidal ideation in women but not in men. 88 , 89

Obesity has a complex aetiology that requires a multifaceted strategy for prevention and treatment at a population and individual level. 90 The social ecological model can provide a framework to help identify the personal and environmental determinants of obesity which can facilitate the development of interventions. 91 Indeed, primary and secondary prevention of obesity requires input and collaboration from multiple bodies, such as the government, policy makers, legislative powers and healthcare system. Figure 1 provides an overview of selected interventions, superimposed onto a modified social ecological model, that have been implemented in different countries. No country has yet implemented a successful population-level strategy to reverse the rising trends of obesity. 1

Examples of selected interventions used by different countries to prevent and treat obesity displayed on a modified social ecological model.

UK, United Kingdom; US, United States.

The environment is obesogenic. Healthful messages from policy makers are often undermined by advertisements that promote large portions of highly palatable energy-dense processed foods and sugar-sweetened beverages, 92 which are key drivers of obesity. 93 The availability of fast-food outlets around schools may be associated with an increased risk of unhealthy eating patterns and childhood obesity, especially in deprived areas. 94 , 95 This could be curtailed by governments granting local authorities’ the power to restrict take-away outlets, especially close to schools. Furthermore, fast-foods are more readily available to both children and adults at any time of day through ordering via mobile phone applications; however, the implications of this on eating behaviour and childhood obesity remain to be elucidated. Policy makers should strongly consider implementing legislation regarding the age at which take-away foods can be purchased, and responsibility must be shared by local providers of fast-foods to enforce this legislation. 96 , 97 Clearly, labelling the calorie content of takeaway foods may also help consumers opt for more sensible food choices. 93

Obesity impacts the poorest in society. A UK study of 119,669 individuals aged 37–73 found a strong association between higher BMI and lower socioeconomic status, especially in women. 98 Similarly, a US study reported that overweight women are more likely to work in lower paying-jobs than non-overweight women and all men. 99 This health inequality is further compounded by the fact that fast-food availability is greater in areas of higher deprivation. 100 Taxation of unhealthy foods may be one strategy to limit the availability of fast-foods. Indeed, a tax on sugary-sweetened drinks in Mexico led to an average reduction of 7.6% in purchases of these beverages, 101 whilst a 21% reduction in consumption was observed amongst low-income neighbourhoods in California. 102 In the UK, the soft drinks levy has raised money from taxation to invest into physical activity and healthy eating in UK schools, 103 but whether any of these changes will prevent obesity remains to be seen.

Individuals with obesity face a pervasive form of social stigma due to their weight that subjects them to discrimination in employment, education and healthcare. In the workplace, there is a lack of legislation that protects the vast majority of individuals with obesity who experience discrimination. The UK Equality Act (2010) does not specifically prohibit discrimination against obesity 104 and in 2014, the European Court of Justice ruled that being severely overweight could be considered a disability yet obesity per se is not specified as a disabling condition in European Union (EU) employment law. 105 However, some US states have recently introduced legislation that protects against height and weight discrimination, 106 and legislation is a key step to tackling the stigma associated with obesity.

Recognising obesity as a disease rather than a lifestyle choice will address the fallacy that obesity is the fault of the individual due to laziness or gluttony and replace it with scientific knowledge that body weight is maintained within a relatively narrow individualised range by a precise subconscious homeostatic mechanism. 105 , 107 Changing this narrative is fundamental so that patients with obesity receive appropriate treatment because there is evidence that patients with obesity are not receiving appropriate referral to specialist services. Worldwide, 0.1–2% of eligible obese patients undergo bariatric or metabolic surgery. 108 In the UK, access to specialist weight management centres is variable in some areas and absent in others. Only 1% of patients who fulfil the National Institute of Clinical Excellence (NICE) eligibility for bariatric surgery are able to access this service in the UK. 109 Greater awareness of the efficacy and cost-effectiveness of surgical interventions for obesity and morbid obesity as well as pathways to access this service should be easily available for local clinicians so that their patients can receive appropriate treatment. 110 , 111

In 2012, the US Preventative Services Task Force recommended that all adults be screened for obesity and those with a BMI > 30 kg/m 2 should be offered referral for an intensive multicomponent behavioural intervention. 112 Screening may be one way to increase referral to specialist weight management centres and there is good evidence that treating patients with obesity early in their disease course, especially those with T2DM, can prevent or delay complications. 93

Patients with obesity can be challenging to manage because the causes and complications of the disease are patient specific and this requires bespoke management at a specialist multidisciplinary weight management centre. Behavioural interventions are fundamental to lifelong weight management, and unique strategies are required for weight loss, maintenance of weight loss and avoiding weight regain, all of which require motivation and commitment from patients. 93 This can be challenging because patients with obesity often have psychological, psychiatric and medical comorbidities that can negatively impact long-term adherence to behavioural interventions. 93 Data from two large randomised control trials of lifestyle interventions, the Diabetes Prevention Programme and the Look AHEAD trial, 113 , 114 suggest that frequency of patient contact, individualising patient care and face-to-face interventions were important predictors of weight loss. In a separate study, patients who attended group sessions every other week for 1 year after weight loss maintained 13 kg of their initial 13.2 kg weight loss, 115 which suggests that regular group sessions may prevent weight regain. However, implementing behavioural interventions can be difficult due to a lack of resources and time. Remotely delivered behavioural programmes via telephone or the internet are alternative approaches that may be more easily accessible and affordable. Patients who received 20 weight loss intervention phone calls over 6 months lost an average of 4.9 kg; those who received 10 calls lost 3.2 kg and those who were self-directed lost 2.3 kg. 116 In another study, patients who received 24 weekly bespoke weight loss sessions via email in addition to internet resources lost 4.4 kg after 1 year when compared with a group receiving internet resources only who lost 2.0 kg. 117 Despite their popularity, little is known about the effectiveness of smart-phone applications for weight management and therefore more research is needed.

Obesity is a multisystem disease that increases the risk of the most common non-communicable chronic diseases of the 21st century. 21 , 57 The population is developing obesity at a younger age and it is likely that these individuals will suffer morbidity for longer. 2 , 118 This will be challenging for clinicians because the symptom and disease burden from multi-organ impairment can become irreversible without timely intervention. Early identification of individuals with obesity through simple anthropometric measurements should be a priority for prompt interventions to prevent morbidity and the associated healthcare and economic costs. 119

Tackling obesity requires a whole systems approach. Governments and policy makers, rather than individuals, have the ability to change the food environment through regulation, taxation and restricting the availability of high-calorie processed foods to adults and children. Patients with obesity who face weight-based discrimination deserve policies and legislation that aim to prevent weight-based inequality. This will help change the current narrative that patients with obesity are to blame for their disease, which fuels a pervasive form of social stigma. Replacing this fallacy with scientific knowledge can prevent discrimination and facilitate referral to specialist weight management centres where a multidisciplinary team can provide bespoke patient care.

Author contribution(s): Saleem Ansari: Conceptualization; Writing-original draft; Writing-review & editing.

Nadim Haboubi: Conceptualization; Formal analysis; Supervision; Visualization; Writing-review & editing.

Conflict of interest statement: The authors declare that there is no conflict of interest.

Funding: The authors received no financial support for the research, authorship, and/or publication of this article.

Contributor Information

Saleem Ansari, Clinical Biochemistry, King’s College Hospital, Denmark Hill, London, England SE5 9RS, UK.

Hasan Haboubi, Department of Gastroenterology, Guy’s & St Thomas’ Foundation trust, London, England, UK.

Nadim Haboubi, Consultant Physician, University of South Wales, Pontypridd, Rhondda Cynon Taff, UK.