Obesity is a major public health problem whose prevalence has been rapidly increasing in the United States (U.S), and globally. It is one of the leading causes of preventable deaths globally and contributes to the development of many diseases.
The search was limited to studies published in English and other languages involving both animal and human subjects. Articles selected included preclinical studies, randomized clinical trials RCTs, observational studies, meta-analyses, narrative and systemic reviews providing primary quantitative data with a measure of obesity or food addiction as an outcome. Over 5000 articles were found in the first round of search which was filtered to 506 articles.
Oxidative stress plays a critical role in food addiction and is both a cause and mediator of obesity. Reactive oxygen species play a direct role in adipogenesis and oxidative stress modulates all factors involved in obesity including genetics, sleep, gut microbiome, insulin, ghrelin, inflammation, adipokines, leptin, stress, HPA axis, and the hypothalamus.
The idea of thinking of combating obesity from the lens of calorie count, low carbohydrate, high or low-fat, vegetarian, vegan, plant-based, or animal-based diet is fundamentally wrong. The best way to look at obesity is through the framework of systemic redox homeostasis. Since redox homeostasis is tilted towards increased reactive oxygen species production, and excessive antioxidant intake can result in oxidative stress, an antioxidant and prooxidant food ratio of 2:3 per meal is the ideal nutritional ratio for good health and ideal weight. A ratio of 3:4 is ideal for obese individuals because of their state of chronic oxidative stress and inflammation. Physical activity, sleep quality, psychological stress, maternal prenatal diet and oxidative stress promoting disease conditions are important modulators of oxidative stress and obesity.
Happiness is a universal goal that people pursue. Studies of the relationship between obesity and happiness have shown mixed findings. It is uncertain whether an optimum BMI level exists and at what level obesity interferes or interacts with happiness. Guided by the Circle of Discontent Theory, we examined the relationship between obesity and happiness among Chinese residents using the 2014 China Family Panel Studies data. The results reveal an inverted U-shaped relationship between BMI and happiness, with obesity associated with happiness through physical appearance, health, and income. The socioeconomic conditions for the appropriate weight to achieve happiness are discussed.
Citation: Cheng, Y. J., Chen, Z. G., Wu, S. H., Mei, W. Y., Yao, F. J., Zhang, M., & Luo, D. L. (2021). Body mass index trajectories during mid to late life and risks of mortality and cardiovascular outcomes: Results from four prospective cohorts. EClinicalMedicine, 33, 100790.
Note: This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.
Our understanding of the weight-outcome association mainly comes from single-time body mass index (BMI) measurement. However, data on long-term trajectories of within-person changes in BMI on diverse study outcomes are sparse. Therefore, this study is to determine the associations of individual BMI trajectories and cardiovascular outcomes.
The present analysis was based on data from 4 large prospective cohorts and restricted to participants aged ≥45 years with at least two BMI measurements. Hazard ratios (HR) and 95% confidence intervals(95%CI) for each outcome according to different BMI trajectories were calculated in Cox regression models.
The final sample comprised 29,311 individuals (mean age 58.31 years, and 77.31% were white), with a median 4 BMI measurements used in this study. During a median follow-up of 21.16 years, there were a total of 10,192 major adverse cardiovascular events (MACE) and 11,589 deaths. A U-shaped relation was seen with all study outcomes. Compared with maintaining stable weight, the multivariate adjusted HR for MACE were 1.53 (95%CI 1.40–1.66), 1.26 (95%CI 1.16–1.37) and 1.08 (95%CI 1.02–1.15) respectively for rapid, moderate and slow weight loss; 1.01 (95%CI 0.95–1.07), 1.13 (95%CI 1.05–1.21) and 1.29 (95%CI 1.20–1.40) respectively for slow, moderate and rapid weight gain. Identical patterns of association were observed for all other outcomes. The development of BMI differed markedly between the outcome-free individuals and those who went on to experience adverse events, generally beginning to diverge 10 years before the occurrence of the events.
Our findings may signal an underlying high-risk population and inspire future studies on weight management.
National Natural Science Foundation of China, Guangdong Natural Science Foundation.
Trajectories Body mass index Cardiovascular events Mortality Mid-to-late life
Research in context
Evidence before this study
We searched Pubmed for articles published in English assessing risk of cardiovascular disease and all-cause mortality in relation to BMI and BMI trajectories, using the search terms “BMI”, “change in BMI”, “BMI trajectories”, “cardiovascular diseases”, “major adverse cardiovascular events”, “death”, “mortality”, “coronary heart disease”, “stroke”, “heart failure”, “myocardial infarction” and “risk”, from the inception to December 15, 2020. We found numerous studies discussing the associations of single time BMI measurements and cardiovascular risks, but few of them explored the associations of individual change trajectories and adverse outcomes.
Added value of this study
In this large population-based study, a U-shaped relation was observed between BMI trajectories and subsequent risk of different health outcomes. Both weight gain and weight loss conferred increased risks for cardiovascular events and all-cause mortality. In addition, we found for the first time that falling off the BMI trajectory could be a warning sign for future occurrence of adverse events.
Implications of all the available evidence
Our findings may signal an underlying high-risk population and underscore the importance of maintaining body weight over the middle to late adulthood.
In light of the obesity epidemic [1,2], it is imperative to understand the relationship of weight to the risks of mortality and cardiovascular diseases (CVD). Although this relation is well documented in previous researches, most of them were based on single-time assessment of body weight (or body mass index, BMI) , , , , , . As noted, the relation of single-time BMI measurement to adverse outcomes changed during the observation period . Specifically, the magnitude of this association weakens among middle-aged and elderly populations [10,11].
Further, using single-time BMI may fail to recognize the effect of weight change on the associated risks. Weight changes are highly variable over the life course , , , . Both weight loss and gain in middle-aged adults rendered increased risk of all-cause and CVD mortality [4,, , , ]. However, the patterns of BMI change may differ among individuals; thus, a life-course perspective is essential. Mapping the longitudinal trajectory of BMI may directly capture the within-person change in BMI, and better characterize the associated risks.
Although increasing number of studies have investigated the relationship of BMI trajectories and cardiovascular outcomes, most were assuming the population lies within a mixture of latent groups, using either growth curve model or group-based latent model [11,, , , , , , , , , ]. These models are largely based on subgroup means over a specific period of time and might be imprecise. Till now, there are at least 2 to 6 different BMI trajectory patterns being reported [11,, , , , , , , , , , ], even using the same dataset [20,26].
Therefore, in order to obtain a more precise association between BMI trajectory and cardiovascular outcomes, we here used the original BMI slope from each individual to represent individual BMI change trajectory. As far as we know, less than ten papers have reported the value of BMI slope in cardiovascular system [13,14,, , , , , , ]. Most of them investigated the association of BMI slope and change in cardiovascular risk factors [14,31,, , , ]. Only two researches illustrated its association with cardiovascular outcomes [13,32]. However, models were not fully adjusted and differences on weight change direction were not taken into consideration.
Therefore, in our current study, we separated weight gain and weight loss by different degrees of change to comprehensively illustrate the relation of individual BMI trajectory to diverse study outcomes. As a second aim, we explored and characterized the developmental paths of BMI prior to individual outcomes.
Model 1, adjusted for age, gender and race; Model 2, adjusted for age, gender, race, smoking status, current alcoholic use, education level, marital status, income, physical activity, consumption of fruits and vegetables, history of hypertension, diabetes, HF, CHD, cancer, COPD and stroke, baseline BMI, serum level of glucose, total cholesterol, LDLC, HDLC and triglyceride.
Compared with maintaining stable weight, the multivariate adjusted HRs for MACE were 1.53 (95%CI 1.40–1.66), 1.26 (95%CI 1.16–1.37) and 1.08 (95%CI 1.02–1.15) respectively for rapid, moderate and slow weight loss; 1.01 (95%CI 0.95–1.07), 1.13 (95%CI 1.05–1.21) and 1.29 (95%CI 1.20–1.40) respectively for slow, moderate and rapid weight gain. Models examining the associations with outcomes of MI and CHF yielded similar results as MACE. While for stroke, the hazard was significantly increased in participants with moderate-to-rapid weight loss and moderate weight gain, but for slow weight loss or slow weight gain, the association was insignificant (Table 2). Consistently, Fig. 1-A shows a U-shaped relation of the entire range of annual BMI change to individual cardiovascular outcomes in the cubic spline models.
3.2.2. Secondary outcomes
Similarly, the HRs for all-cause mortality were 1.98 (95%CI 1.83–2.13), 1.38 (95%CI 1.28–1.49) and 1.18 (95%CI 1.12–1.25) respectively for rapid, moderate and slow weight loss; 0.99 (95%CI 0.93–1.04), 1.08 (95%CI 1.01–1.15) and 1.29 (95%CI 1.20–1.38) respectively for slow, moderate and rapid weight gain, when compared to maintaining stable weight. Identical patterns of association were observed for CVD, non-CVD and CHD death (Table 2). Likewise, in the restricted cubic spline models, we detected a U-shaped relationship between annual BMI change and mortality risk, with a nadir around 0 kg/m2/year (Fig. 1-B).
3.3. BMI trajectories prior to different outcomes
Fig. 2 is an illustrative drawing to represent the general developmental patterns of BMI prior to different outcomes. We found that the development of BMI differed markedly between the outcome-free individuals and those who went on to experience adverse events. Trajectories appeared similar for the outcomes of MACE, all-cause, CVD and non-CVD death. The outcome-free participants followed a trajectory where the average BMI levels rise initially, remain stable or steadily decreased throughout follow-up. Those who went on to experience events generally showed lower baseline levels of BMI, steeper rise initially and faster fall before the occurrence of the events. With regards to MI and CHD death, the average BMI level was comparable in participants with or without the outcomes, but an accelerated decline was observed in those who died or experienced the events. Interestingly, although the developmental trend was identical among participants with and without CHF, those who experienced CHF had a generally higher BMI level during their life. With respect to the outcome of stroke, the BMI trajectories were less distinctive between groups.
3.4. Additional information and stratified analysis
We repeated the primary analyses in a series of sensitivity analyses. Excluding participants with missing values on baseline covariates (supplementary Table 3 in Appendix 3), with preexisting illnesses at baseline (supplementary Table 4 in Appendix 3), or with highest weight variability during follow-up (supplementary Table 5 in Appendix 3) did not appreciably change the results. In terms of percent change of BMI, the association patterns for cardiovascular outcomes were identical to our primary analysis (supplementary Table 6 in Appendix 3). But for the death outcomes, we only found significant increased risk in weight loss quintiles (quintile 1 and 2). When separating the primary analysis by individual cohort, consistent findings were observed (supplementary Table 7 in Appendix 3).
As depicted in Fig. 3, the associations of BMI trajectories and MACE were generally consistent in stratified analyses by sex, race and smoking status. It should be noted that the BMI-MACE association was significantly modified by age and borderline by baseline BMI. The hazards for MACE were significantly higher in those younger than 60 years, but lower in those who were initially with obesity. For all-cause mortality, the associations with BMI trajectories were generally consistent in white or non-white population and significantly modified by age, sex, and smoking status. It’s revealed that male and individuals younger than 60 years had higher hazards for death. But surprisingly, the hazards were lower in the smoker subgroups. Similar to the MACE outcome, the hazards for death were lower in subgroup with obesity, but the modification effect by baseline BMI was insignificant. The association of BMI trajectories and other outcomes across the predefined subgroups are provided in supplementary Table 8 and Table 9 (Appendix 3).
In our analyses of the overall cohort of 29,311 participants, a U-shaped relation was observed between BMI trajectories and subsequent risk of cardiovascular events and all-cause mortality. Significant increase of risks for MACE and all-cause death were noted for people assigned in weight loss or weight gain categories. The hazard risks for adverse outcomes were consistently lowest among individuals maintaining their body weight. Although effect modification was observed in several subgroups, our findings were generally robust in a number of sensitivity analysis. Furthermore, our study for the first time delineates the characteristics of BMI trajectories prior to different health outcomes, showing an accelerated decline in BMI almost ten years before the occurrence of the events.
More than 38.9% of US adults have obesity ; however, much of our understanding of the BMI-mortality association comes from single-time BMI measurement, without considering within-person variation over the long term. Since weight change is highly variable across adulthood, more studies are now focusing on BMI trajectories and different health outcomes [11,13,, , , , , , , , , , ,32]. However, most of these studies were grouping people using growth curve model or group-based latent model [11,, , , , , , , , , ]. Using the above models, one can identify individuals with distinct BMI trajectories from the available data [25,48]. However, class membership is not determined with certainty for each individual since it relies on the selected models (linear, curvilinear, cubic and other forms) and probability of belonging [20,49]. Thus, misclassification is possible and the associated risk of adverse outcomes could be invalid. In articles published by Zeng H.et al. and Zajacova et al., the authors used the same data but identified different patterns of BMI trajectory [20,26]. As of now, at least two to six patterns of BMI trajectories have been reported in the general population and majority of them were depicting an ascending trend or paralleling with each other [21,26,28,, , ]. It is unrealistic that all participants were going the same way over the life course. There must be some groups of individuals experiencing gradual weight loss or even rapid loss in their weight. Furthermore, most of the existing studies differentiate the curves by studying changes in pre-defined BMI categories: defining a change within normal weight as “normal-stable” , or a change from overweight category to category with obesity as “overweight obesity” trajectory . This crude categorization of BMI trajectories would probably yield over- or under-deterministic results. It should be noted that a variety of changes could occur within the same categories; even a small change in BMI would pose a significant deleterious effect on health . Furthermore, the rate of change, the direction of change, or the slope of the trajectory was all likely to make a difference in the negative outcomes [13,53].
Thus, from the current study, we derived an overall BMI trajectory (annul change in BMI or BMI slope) for each individual, giving further support to the associations of long term trajectories and diverse health outcomes. In our study, the slope of BMI throughout middle and older age, either positive or negative, rendered increased risks of MACE and mortality: the larger the changes the greater the risk. More specifically, BMI falling faster than 0.1 kg/m2 per year resulted in at least 8% higher risks of MACE and 18% of death. On the other hand, increasing BMI by 0.3 kg/m2 per year was associated with at least 13% higher hazards for MACE and 8% for death. Although several prior studies were conducted with a similar method, findings were mixed and inconsistent. As demonstrated in Framingham Heart Study, BMI slopes were inversely associated with the outcome of total mortality and morbidity due to CHD. On the contrary, in the study of Chicago Western Electric Company, weight loss slope was significantly associated with total and cardiovascular mortality, while the weight gain slope showed nonsignificant increased risk of each endpoint for 25-year follow-up . These inconsistencies may result from inadequate adjustment for potential cofounders and not considering the weight change direction.
Identical pattern of association was noted in subgroups of the population, after stratification for age, sex, race, smoking status and baseline BMI. However, effect modification of these stratification variables varied with respect to different outcomes. Generally, the hazardous effects of weight change and adverse outcomes were more pronounced in male participants and at younger age (<60 years). Two additional results should be noted. First, although previous studies have suggested that smoking status is a crucial modifier on the association of BMI and cardiovascular risks, we reveal that the hazards of cardiovascular outcomes were generally consistent in the three categories of smoking status. While for all-cause and non-CVD death, the association with weight loss were inconclusively modified by smoking status. The inconsistent observed relation could be the result of diverse weight change patterns associated with smoking or accounted for the unmeasured confounders [12,33]. Second, decreased weight in individuals with higher BMI (overweight or with obesity) may result in a better outcome when compared to those with normal weight at baseline, which could partially explain the phenomenon of “obesity paradox” . The risk differences for weight gain among normal, overweight or individuals with obesity were less obvious.
In this study, we not only captured the characteristics of individual BMI change trajectory, but also directly evaluated the average BMI trajectories for those with and without specific outcomes. We found for the first time that patterns of change in BMI prior to different outcomes were different. Overall, the BMI trajectories appeared similar for most of the study outcomes: the outcome-free participants followed a trajectory where the average BMI levels remained relatively stable, while for those who went on to experience adverse events, the trajectories began to fall 10 years before the event. Although it’s unclear whether the observed weight loss was the antecedent cause or the consequence of the outcome, these findings may signal an underlying high-risk population and underscore the importance of maintaining body weight over the middle to late adulthood.
The major strengths of this study include the availability of multiple BMI measurements within identical time interval and using the linear mixed model, which entails a more accurate assessment of individual BMI trajectory. Furthermore, although distinguishing intentional and unintentional weight loss is challenging, we try to separate them by using weight variability, in which the highest variability subgroup represents intentional weight loss subcategory. As a result, in weight loss participants with high weight variability, moderate and rapid weight loss was not significantly correlated with increased risk of cardiovascular events. But likewise, we did not observe a beneficial effect in this group of population. One possible explanation for this is that weight rebound following intentional weight loss may offset the positive effect brought by losing weight. Therefore, for weight loss individuals, it is imperative to first examine the reasons for weight loss: intentional or unintentional. If someone is losing weight intentionally, avoiding weight regain or achieving sustained weight loss may be the cornerstone of the accrued benefits brought by losing weight from a high BMI.
Despite of the strengths provided above, several limitations should be noted. Firstly, our findings relate solely to changes in BMI while the changes of fat mass, muscle mass and the general change of the body composition were unknown. In addition, since majority of the study participants were white US people, the results could not be generalized to more heterogeneous populations. Secondly, although we are trying to distinguish whether weight loss was intentional or unintentional in our sensitivity analysis, data on the causes of weight loss were unavailable in the current study. And thus, we could not confirm the above speculation and further studies are warranted.
In this large population-based study, a U-shaped relation was observed between BMI trajectories and subsequent risk of different health outcomes. Both weight gain and weight loss conferred increased risks for cardiovascular events and all-cause mortality. In addition, we found for the first time that patterns of change in BMI prior to different outcomes were different. Falling off the BMI trajectory could be a warning sign for future occurrence of adverse events; thus, maintaining body weight during the middle to late adulthood may be essential. Despite the observational nature of the current study, the trajectories and risk patterns identified here may inspire future studies on the cause and potentially weight management guidelines.
The ARIC, CHS, MESA and FHS studies are carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts. The study was also financially supported by the grants from National Natural Science Foundation of China (81600260), Guangdong Natural Science Foundation (2016A030313210), the Science and Technology Planning Project of Guangdong Province (2017A020215174), the Fundamental Research Funds for the Central Universities in Sun Yat-Sen University (18ykpy08), and the project of Kelin new star of the First Affiliated Hospital of Sun Yat-Sen University (Y50186).
Declaration of Competing Interest
We declare no competing interests.
All authors contributed to the study concept and design. YC, CZ and WS contributed equally to this work. DL and YC are senior and corresponding authors who also contributed equally to this study. DL, YC, CZ and WS have full access to all the data in this study and take full responsibility as guarantors for the integrity of the data and the accuracy of the data analysis. CY, LD, CZ and WS contributed to the study design. CZ and WS contributed to analysis and data interpretation. CY and LD drafted the manuscript and contributed to the final approval of the manuscript. MW, YF and ZM contributed to critical revision of the manuscript for important intellectual content.
Data sharing statement
The cohort data sets were obtained from the NIH Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) and could be applied to the corresponding author upon reasonable request.
Appendix. Supplementary materials
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The world is full of contradictions, inconsistencies and inequities. On the one hand, it has been reported by the Food and Agriculture Organization of the United Nations (FAO, 2015) that 805million people are estimated to be chronically undernourished. Yet, it has been estimated that the volume of food produced is more than one and a half times what is needed to provide everybody on the planet with a nutritious diet (Weis, 2007). It is not about lack, it is about inequity. While 805 million starve, we also know that 1460 million are overweight or obese, and that number is increasing.
There is also water scarcity with 1.2 billion people lacking access to clean drinking water and 2.5 billion people having no access to a toilet, less than the number of people with a mobile phone (United Nations, 2015). As the world population increases from 7.3 billion today to around 9.6 billion in 2050 (+31.5%), the supply of fresh drinking water available will remain about the same. Yet, around 70 per cent of the world’s water is used in agriculture. Annual grain crops are planted on about 70 per cent of the world’s cropland and provide 80per cent of the world’s food (Pimentel et al., 2012), 70 per cent of which is stock feed for farm animals, which in turn produce dairy and meat.
Over the next 25 years, a lot more food will be needed for the extra 31.5 per cent and the only way it can be produced is through agriculture, creating a vicious circle. The FAO (2015) predicts that the global demand for livestock products will increase by 70 per cent by 2050 with an estimated 1 billion poor depending on livestock for food and income. The livestock sector contributes to human-induced Greenhouse Gas emissions for 14.5 per cent and is a large user of natural resources, especially water.
As Father Time waves his sickle over the remaining decades of this century, there will be a worsening water scarcity. Thanks in part to a ready supply of beef burgers, fried chicken, milk, eggs and cola. Many recent editorials in medical and scientific journals have addressed issues relating to food, diets and dieting (e.g. Drewnowski, 2014; Edmonds and Templeton, 2013; Fitzgerald, 2014; Gold and Graham, 2011; Ndisang et al., 2014; Pagadala and McCullough, 2012; Potenza, 2014; Sniehotta et al., 2014; Stuckler and Basu, 2013; The PLoS Medicine Editors, 2012; Yanovski, 2011).
The Special Issue on ‘Food, Diets and Dieting’ provides a state-of-the-art overview of psychological studies by international researchers on this topic area. The Call for Papers for a Special Issue on ‘Food, Diets and Dieting’ was timely; we received unprecedented interest with many high-quality submissions. Following peer review, the number of accepted papers finally reached the total of 42. The contributions have been divided into two sets for publication in the May and June 2015 issues of Special Issue: Food, diets and dieting. These publications in Journal of Health Psychology are complemented in our companion, open access journal, Health Psychology Open, by a theoretical review paper and a series of commentary papers (Marks, 2015).
According to the McKinsey Global Institute (2014) obesity is responsible for around 5 per cent of global deaths and the global economic impact is US$2.0trillion, or 2.8per cent of global gross domestic product (GDP), roughly equivalent to the impact from smoking or armed violence, war and terrorism. In the United States, in 2004, direct and indirect health costs associated with obesity were US$98 billion. That figure probably has doubled by now.
Depending on the source, it is reported that the direct medical cost of overweight and obesity combined has been estimated to be 5–10per cent of the US health care spend. 42million children under the age of 5 were overweight or obese in 2013. Prevalence of overweight or obesity in adults doubled from 6 per cent in 1980 to 12 per cent in 2008. By 2050, it is predicted that obesity will affect 60 per cent of adult men, 50 per cent of adult women and 25per cent of children making the United States, Britain and much of Europe a mainly obese society.
Globalization is Driver
The main driver of the obesity epidemic and increased prevalence of other non-communicable diseases is unregulated corporate globalization (Swinburn et al., 2011). From the point of view of human health, globalization flies a banner of progress and freedom yet brings illness and an early death to millions of people with non-communicable ‘diseases of affluence’. Transnational corporations are scaling up their promotion of tobacco, alcohol, cola and other sugary beverages, ultra-processed food and unhealthy commodities generally throughout low- and middle-income countries. Moodie et al. (2013) have observed that sales of unhealthy commodities across 80 low- and middle-income countries are strongly interrelated. They argue that wherever there are high rates of tobacco and alcohol consumption, there are also a high intake of snacks, soft drinks, processed foods and other unhealthy food commodities. Moodie et al. (2013) argued that the alcohol and ultra-processed food and drink industries are using similar strategies to the tobacco industry to undermine effective public health policies and programmes. Furthermore, it is suggested that unhealthy commodity industries should have no role in the formation of national or international policy for non-communicable disease policy. Therefore, it follows that the only evidence-based mechanisms that can prevent harm caused by unhealthy commodity industries are public regulation and market intervention.
The work of Drewnowski and others has demonstrated a strong relationship between affordability of food and beverages and their energy density measured in terms of fat and sugar (Drewnowski, 2014; Drewnowski and Specter, 2004). A systematic review of 27 studies across 10 countries showed that a healthful diet costs around US$550 per year more than an unhealthy one (Rao et al., 2013). In England, another study suggested that the healthiest dietary pattern costs double the price of the least healthy, costing £6.63/day and £3.29/day, respectively (Morris et al., 2014). That is a difference of £1219 per annum.
The inverse relationship between income and prevalence of overweight and obesity follows from two related facts: (a) cheaper foods and drinks are energy-dense and (b) a healthful diet is unaffordable for the majority of people. In 2008, an estimated 1.46 billion adults worldwide had a body mass index (BMI) of 25kg/m2 or greater, and of these, 205million men and 297million women were obese. Taking into account, the rate of increase in obesity, this half-billion figure is projected to increase at least 30 per cent by 2050. The World Health Organization (WHO) (2014) estimates that around 3.4million adults die each year as a result of overweight or obesity. The WHO (2013) published a plan to halt the rise in diabetes and obesity as a part of a vision: ‘A world free of the avoidable burden of noncommunicable diseases’. WHO interventions revolve around ‘mobilizing sustained resources Marks 471 … in coordination with the relevant organizations and ministries’ which consists of high-level meetings between governmental representatives and publishing position statements.
Evidence and logic suggest that economic prosperity is the enabler for obesity and, furthermore, leading authorities have concluded that Obesity is the result of people responding normally to the obesogenic environments they find themselves in. Support for individuals to counteract obesogenic environments will continue to be important, but the priority should be for policies to reverse the obesogenic nature of these environments. (Swinburn et al., 2011) Policy reversals to reduce obesogenicity by regulation face robust resistance from the food and drinks industry. Yet without regulation to change the price imbalance between unhealthful and healthful foods, the obesity epidemic is unlikely to go away. In the meantime, hundreds of millions of individuals continue inexorably along the path of overweight and obesity, with the associated unpleasant illnesses and an early death. It follows that health care systems must be competent to offer effective interventions to prevent, treat and ameliorate the impact of overweight or obesity. Authorities decree that a ‘balanced diet’ with regular physical activity is of crucial importance to a healthy body. Yet, in spite of thousands of studies, hundreds of campaigns and scores of dedicated institutes and journals based on this creed, there are currently no validated public health interventions able to achieve sustained long-term weight loss. Today, the muchtouted idea of the ‘balanced diet’ seems little more than worn out myth. Some basic questions require answers: What is causing the obesity epidemic? What can be done about it? and What is the role of health psychologists (if any)? (Marks et al., 2015; Marks, in press). The obesity epidemic is comparable in importance to the smoking epidemic. Arguably, it will prove to be even more significant in human history than smoking. It took 50 years of consolidated pressure to reduce the prevalence of smoking related diseases. Progress has been frustratingly slow. Still, in 2015, only one industrialized country in the world has plain or standard packaging of cigarettes (Australia) with a second one planning to follow next year (England). With no significant interventions on the horizon for obesity prevention, for example, unhealthful food taxation, the obesity epidemic can continue unabated to run its course, until food and water shortages have their ultimate impact on human society.
Enough Knowledge Now to Tackle Obesity
There is enough knowledge now to tackle the obesity epidemic. Unfortunately our political leaders lack the spine to do what is necessary. Our market-led governance is in the pocket of the paymasters who influence the election of our presidents and prime ministers. If the food chain could be rationally developed, the food and water crises could be curbed within two decades from now. This Special Issue contains a collection of in-depth psychological studies on food, diets and dieting. These studies are relevant to the issue of why certain foods are eaten or avoided by individual consumers and how the choices of consumers are influenced by family, social and economic conditions. Diets and dietary changes involve complex systems of variables which operate on a mass scale. Improved understanding of psychological functioning around food, diets and dieting holds one key to improving nutritional health. A better understanding of behaviour alone is not enough; changes to the food environment are also necessary. Our governmental leaders need to wake up, loosen their ties to their industrial paymasters and take effective action.
Drewnowski A (2014) Healthy diets for a healthy planet. The American Journal of Clinical Nutrition 99(6): 1284–1285.
Drewnowski A and Specter SE (2004) Poverty and obesity: The role of energy density and energy costs. The American Journal of Clinical Nutrition 79(1): 6–16.
Edmonds EW and Templeton KJ (2013) Childhood obesity and musculoskeletal problems: Editorial Clinical Orthopaedics and Related Research 471(4): 1191–1192.
Fitzgerald DA (2014) Mini-symposium: Childhood obesity and its impact on respiratory wellbeing: Editorial title: Childhood obesity is the global warming of healthcare. Paediatric Respiratory Reviews 15(3): 209–284.
Food and Agriculture Organization of the United Nations (FAO) (2014) The State of Food Insecurity in the World: Strengthening the Enabling Environment for Food Security and Nutrition. Rome: FAO. Available at: http:// http://www.fao.org/3/a-i4030e.pdf
Food and Agriculture Organization of the United Nations (FAO) (2015) Livestock and the environment. Available at: http://www.fao.org/ livestock-environment/en/
Gold MS and Graham NA (2011) Editorial: Hot topic: Food Addiction & Obesity Treatment Development (Executive Guest Editors: Mark S Gold and Noni A Graham). Current Pharmaceutical Design 17(12): 1126–1127.
McKinsey Global Institute (2014) Overcoming obesity: An initial economic analysis. Discussion paper. London. Available at: http://www. munideporte.com/imagenes/documentacion/ ficheros/025183D9.pdf
Marks DF (2015) Homeostatic theory of obesity. Health Psychology Open. Marks DF, Murray M, Evans B, et al. (2015) Health Psychology: Theory, Research and Application (4th edn). London: SAGE.
Moodie R, Stuckler D, Monteiro C, et al. (2013) Profits and pandemics: Prevention of harmful effects of tobacco, alcohol, and ultraprocessed food and drink industries. The Lancet 381(9867): 670–679.
Morris MA, Hulme C, Clarke GP, et al. (2014) What is the cost of a healthy diet? Using diet data from the UK Women’s Cohort Study. Journal of Epidemiology and Community Health 68(11): 1043–1049.
Ndisang JF, Vannacci A and Rastogi S (2014) Oxidative stress and inflammation in obesity, diabetes, hypertension, and related cardiometabolic complications. Oxidative Medicine and Cellular Longevity 2014: 506948.
Pagadala MR and McCullough AJ (2012) Editorial: Non-alcoholic fatty liver disease and obesity: Not all about BMI. The American Journal of Gastroenterology 107: 1859–1861.
Pimentel D, Cerasale D, Stanley RC, et al. (2012) Annual vs. perennial grain production. Agriculture, Ecosystems & Environment 161: 1–9.
Potenza MN (2014) Obesity, food, and addiction: Emerging neuroscience and clinical and public health implications. Neuropsychopharmacology 39(1): 249–250.
Rao M, Afshin A, Singh G, et al. (2013) Do healthier foods and diet patterns cost more than less healthy options? A systematic review and metaanalysis. BMJ Open 3: e004277.
Sniehotta FF, Simpson SA and Greaves CJ (2014) Weight loss maintenance: An agenda for health psychology. British Journal of Health Psychology 19: 459–464.
Stuckler D and Basu S (2013) Getting serious about obesity. BMJ: British Medical Journal 346: f1300.
Swinburn BA, Sacks G, Hall KD, et al. (2011) The global obesity pandemic: Shaped by global drivers and local environments. The Lancet 378(9793): 804–814.
The PLoS Medicine Editors (2012) PLoS Medicine series on Big Food: The food industry is ripe for scrutiny. PLoS Medicine 9(6): e1001246.
Weis T (2007) The Global Food Economy. London: Zed Books. World Health Organisation (WHO) (2014) Obesity and overweight. Fact Sheet No 311. Available at: http://www.who.int/mediacentre/factsheets/ fs311/en/http://www.who.int/mediacentre/ factsheets/fs311/en/
World Health Organization (WHO) (2013) Global Action Plan for the Prevention and Control of Noncommunicable Diseases 2013–2020. Geneva: WHO.
Yanovski SZ (2011) Obesity treatment in primary care – Are we there yet. New England Journal of Medicine 365(21): 2030–2031.
Here I introduce a powerful new explanation of the obesity ‘epidemic’. I reveal some surprising but brutal truths about the condition. For example, obesity is unavoidable for the majority of people in contemporary living conditions. Without radical change, the ‘epidemic’ will get much, much worse.
Obesity an ‘Epidemic’?
Notice I put the word ‘epidemic’ in single quote marks. This is because the word can only really be applied to infectious diseases. Obesity is not a disease. It’s not infectious. Obesity is a bodily condition of being overweight. It is defined loosely as having a body mass index (BMI) above 30. This places people at increased risk for a variety of chronic conditions. Unpleasant things like diabetes Type 2, cardiovascular diseases, cancer and obstructive sleep apnea. [As a scientific measure the BMI is a bit of a joke, by the way, but we’ll leave that for another post.]
Two billion people alive today are overweight or living with obesity. There is no sign that the obesity epidemic is slowing down or that medical science has an understanding of the problem. A universal feature of living beings called ‘homeostasis’ is linked to obesity. Its disruption, dyshomeostasis, is a contributory cause of overweight and obesity.
Obesity is an unavoidable human response to contemporary conditions of living. ‘Blaming and shaming’ individual sufferers is oppressive and is a part of the problem, not part of the solution. Blame and shame makes matters far, far worse. Only by reversing this form of prejudice, and the chronically stressful living conditions of hundreds of millions of people, is there any hope that we can stop the ‘epidemic’.
This book is not for the faint-hearted. It cuts through the ‘shock-horror’ narrative of obesity with brutal truths about the serious and intransigent nature of obesity. Once the causes are fully understood, the obesity epidemic can be stopped. And about time too! This book is a step towards that goal.
“When I first read David Marks brilliant new book Obesity, there was a story on Radio New Zealand that two thirds of Auckland adults were now over weight or obese and the statistic for children was not much better. You don’t have to be an epidemiological genius to see that this will become a major problem for us and for other Western countries which are in the throes of an obesity epidemic.
David Marks presents a fresh, clear-eyed analysis of the complex causes of this epidemic: social, economic and psychological. He discusses the role of neoliberal capitalism in the promotion of poor, calorie rich food and animal products. The psychologist’s discussion of a person’s ‘circle of discontent’ which undermines homeostasis and then ‘feeds’ the spiral of unhealthy eating is fascinating and rings true. And he provides a refreshing solution including the adoption of veganism. The book is lucid and courageous and is the best analysis of a harrowing problem in the world, and a call to action, which I have read.
In an environment that promotes widespread body dissatisfaction, angst and depression, homeostatic feedback loops are producing excessive consumption of unhealthy processed foods that over a protracted period causes obesity in large numbers of vulnerable people. Multiple clinical studies in different areas of medicine demonstrate the primary role of homeostasis in healthy functioning and the consequences of dyshomeostasis. Homeostasis can be overloaded or overridden with too strong a flow of inputs or outputs that disrupt its normal functioning: ‘The homeostatic behaviour of inflow controllers breaks down when there are large uncontrolled inflows, whereas outflow controllers lose their homeostatic behaviour in the presence of large uncontrolled outflows’ (Drengstig et al., 2012). Homeostasis can be disrupted anywhere, and perturbations will inevitably occur in normal functioning (Richards, 1960).
There are many examples of dyshomeostasis in clinical medicine. Well-known to psychologists, Hans Selye reported that a persistent environmental stressor (e.g. temperature extremes), together with an associated homeostatic hormonal response, leads to tissue injury that he termed a ‘disease of adaptation’ (Selye, 1946). Intestinal homeostasis breaks down in inflammatory bowel disease (Maloy and Powrie, 2011) and in the microbial ecology of dental plaque causing dental disease (Marsh, 1994). This form of dyshomeostasis can result from local infection and inflammation and give rise to complications that affect the nervous and endocrine systems (Maynard et al., 2012). An altered balance between the two major enteric bacterial phyla, the Bacteroidetes and the Firmicutes, has been associated with clinical conditions. Within the microbiota of the gut, obesity has been associated with a decreased presence of bacteroidetes and an increased presence of actinobacteria (Ley, 2010; Turnbaugh and Gordon, 2009). Kamalov et al. (2010) proposed a dyshomeostasis theory of congestive heart failure. Craddock et al. (2012) suggested a zinc dyshomeostasis hypothesis of Alzheimer’s disease.
Homeostasis regulation within the endocrinal and central nervous systems has been associated with feeding control. Cortical areas conveying sensory and behavioural influences on feeding provide inputs to the nucleus accumbens (NAc) and the lateral hypothalamic area (LHA) is the site of homeostatic and circadian influences (Saper et al., 2002). Hormones such as leptin circulate in proportion to body fat mass, enter the brain and act on neurocircuits that govern food intake (Morton et al., 2006). Through direct and indirect actions, it is hypothesized that leptin diminishes the perception of food reward while enhancing the response to satiety signals generated during food consumption that inhibit feeding and lead to meal termination.
Another important hormone is ghrelin which is the only mammalian peptide hormone able to increase food intake. Interestingly, ghrelin also responds to emotional arousal and stress (Labarthe et al., 2014; Müller et al., 2015). During chronic stress, increased ghrelin secretion induces emotional eating by acting at the level of the hedonic/reward system. As ghrelin has anxiolytic action in response to stress, this adaptive response may contribute to control excessive anxiety and prevent depression (Labarthe et al., 2014). In obesity, studies have shown a reduced ability to mobilize ghrelin in response to stress or central ghrelin resistance at the level of the hedonic/reward system which may explain the inability to cope with anxiety and increased susceptibility to depression (Figure 1). Reciprocally, studies have shown that people with depression have increased susceptibility to obesity and eating disorders (Marks, 2015).
Figure 1. Model of hedonic/reward response to ghrelin after chronic stress in relation to anxiety and depression. Reproduced from Labarthe et al. (2014).
During chronic stress, increased ghrelin secretion induces emotional eating as hedonic reward. Ghrelin has anxiolytic actions in response to stress; this adaptive response helps to control excessive anxiety and prevent depression. In obesity, a lower ability to mobilize ghrelin in response to stress or central ghrelin resistance at the level of the hedonic/reward system may explain the inability to cope with anxiety and increased susceptibility to depression. Reciprocally, people suffering from depressed show increased susceptibility to obesity or eating disorders (due to an altered hedonic/reward response). Elevated ghrelin may also contribute to alcohol/drug craving as higher ghrelin levels correlate with greater alcohol craving.
In addition to leptin and ghrelin, other lipid messengers that modulate feeding by sending messages from the gut to the brain have been identified. For example, oleoylethanolamine has been associated with control of the reward value of food in the brain (Lo Verme et al., 2005; Tellez et al., 2013). Mice fed a high-fat diet had abnormally low levels of oleoylethanolamine in their intestines and did not release as much dopamine compared to mice on low-fat diets. Thus, alterations in gastrointestinal physiology induced by excess dietary fat may be one factor responsible for excessive eating in the obese (Tellez et al., 2013).
Health is regulated by homeostasis, a property of all living things. Homeostasis maintains equilibrium at set-points using feedback loops for optimum functioning of the organism. Long-term disruptions of homeostasis or ‘dyshomeostasis’ arise through genetic, environmental and biopsychosocial mechanisms causing illness and loss of well-being including obesity, the addictions, and chronic conditions. These and many other phenomena of Psychological Homeostasis are explained in A General Theory of Behaviour.
Obesity dyshomeostasis is associated with a self-reinforcing activity of a vicious Circle of Discontent in which hedonic reward overrides weight homeostasis in an obesogenic and chronically stressful environment. Over-consumption of processed, high-caloric, low-nutrient foods, combined with stressful living and working conditions, have caused loss of equilibrium, overweight and obesity in more than two billion people.
The prevalence of obesity is higher in women and low-income groups who are more exposed to chronic stress and low purchasing power including some ethnic minority groups.
Research on different diets suggests that a plant-based diet containing low amounts of sugar, little or no red meat and the minimum of fats promotes weight-loss and prevents obesity, diabetes, metabolic syndrome, coronary heart disease, and cancer. A vegan diet with no meat, fish or dairy is especially anti-obesogenic.
The ‘thin ideal’ pervades popular culture with narratives and images of thinness which has an entirely negative effect on youth the world over. Legislation should be enacted to ban the use of artificially enhanced images of ultra-thin models in magazines and media.
Discrimination against people who are overweight or obese causes stress and socio-economic disadvantage. Approaches to the epidemic that invoke a narrative of ‘blame-and-shame’ exacerbate the problem. There are very few people who deliberately become obese through conscious effort or who would not like to avoid it if they possibly could.
Homeostatic imbalance in obesity includes a ‘Circle of Discontent’ (COD) a system of feedback loops linking weight gain, body dissatisfaction, negative affect and over-consumption. This homeostatic COD theory is consistent with a large evidence-base of cross-sectional and prospective studies.
A preliminary model suggests that obesity dyshomeostasis is mediated by the prefrontal cortex, amygdala and HPA axis with signalling by the peptide hormone ghrelin, which simultaneously controls feeding, affect and hedonic reward.
The totality of evidence within current knowledge suggests that obesity is a persistent, intractable condition. Prevention and treatment efforts targeting sources of dyshomeostasis provide ways of reducing adiposity, ameliorating addiction, and raising the quality of life in people suffering chronic stress.
Vigorous and uncompromising Governmental actions are required, independent of corporate interests, at all levels of society to reduce the prevalence of obesity and related conditions. A four-armed strategy to halt the obesity epidemic is necessary.
There is an immediate need to enact anti-discrimination legislation to protect people with obesity and improve their quality of life. Anti-discrimination laws are necessary to eliminate one of the primary causes of obesity which fuels the Circle of Discontent. PLWO need legal protection from discrimination which has been shown to be detrimental to the mental health of the victims of obesity.
Legislation to enforce a mandatory code of practice is needed to resist and devalorize the thin-ideal. Precedents have been set in Israel and France to ban models with extremely low BMI, examples which should be followed in all countries. The retouching of pictures in fashion magazines to make the human subjects appear slimmer or more attractive should be controlled. Consumers should be informed when images of people have been manipulated.
Generic legislation is necessary to curb the widespread consumption of energy-dense, low nutrient foods and drinks. Mexico, France, Finland and Hungary and, most recently, the UK have set charges for a levy on sugary drinks, a step in the right direction. More generic taxation is necessary to incentivize producers and retailers to reformulate products. An ‘Unhealthy Commodities Tax’ which would yield revenue and improve the diet of a large segment of the at-risk population.
Improving the access to plant-based diets is an effective strategy for producing weight loss. The example of the WIC in the US indicates that increasing access to fruit and vegetables has a positive effect on food consumption towards a healthier diet. Following the WIC model, legislation should be considered in every state and country to improve F/V intake. Proceeds from a UCT could be used to subsidise the organic production of F/V with payments to growers and sellers to enable lower retail prices of organic F/V. Interventions to increase access and affordability of F/V would help to slow the obesity epidemic.
Huge resources have been invested on the monitoring of the epidemic and on the treatment of PLWO. The major part of future investment should be re-directed towards containment and control by legislating strategies for obesity prevention as was previously the case in tobacco control. No more kowtowing to industry. Let’s cease the “shock-horror” narrative of obesity at all levels of society and replace it by concrete actions.
We know what is required. Can our national governments show the necessary leadership and do what is necessary? The survival of the planet and the human race requires nothing less.
Inside every one us there exists a tension between comfort and discontent. When we assuage the discontent, we find comfort. When we resist comfort, the discontent builds stronger. This eternal struggle is an aspect of the human condition that creates a vicious and unforgiving circle. Within it lies a significant key to human nature, and to the nature of all sentient beings, the ‘Yin and Yang’ of life…it helps to explain the human struggle with overweight, obesity and the addictions.
Once the causes of obesity are fully understood, the obesity epidemic can be stopped. My book takes a step towards that goal. I propose an explanatory theory of an objective issue of undeniable importance to human beings – the obesity epidemic. The ideas are drawn from a range of disciplines including economics, endocrinology, epidemiology, neurobiology, nutrition, physiology, policy studies and psychology. The theory focuses on a universal feature of living beings, homeostasis, and the potential for its disruption, dyshomeostasis.
The evidence points to ‘Obesity Dyshomeostasis’ as a problematic human response to contemporary conditions of living. Similar to racism, sexism and ageism, the current trend towards ‘blaming and shaming’ individual sufferers of obesity and overweight contributes to the problem. Only by reversing this form of prejudice, and the associated environmental conditions, will the obesity epidemic have any chance of being resolved (Marks, 2015a, 2016).
Summary of argument:
Health is regulated by homeostasis, a property of all living things. Homeostasis maintains equilibrium using feedback loops for optimum functioning of the organism. Dyshomeostasis, a disturbance of homeostasis, causes overweight and obesity, is estimated to be present today in more than two billion people world-wide.
Obesity Dyshomeostasis is associated with a ‘Circle of Discontent’, a system of feedback loops connecting weight gain, body dissatisfaction, negative affect and over-consumption. The Circle of Discontent is consistent with an extensive evidence-base.
Obesity Dyshomeostasis occurs when homeostatic control of eating is overridden by hedonic reward. Appetitive hedonic reward is a natural response to an obesogenic environment containing endemic stress and easily accessible, high-energy foods and beverages. In a time of plentiful and cheap food, people eat more to comfort their discontents than purely for hunger. The comfort foods and beverages that are snacked on almost limitlessly are nutritionally deleterious to the health.
The objectives are: (i) To define, describe and discuss the concepts of psychological homeostasis and dyshomeostasis and their relevance to overweight, obesity, the addictions and chronic stress; (ii) To propose a General Theory of Well-Being founded on the construct of psychological homeostasis; (iii) Within the general theory, to specify the Obesity Dyshomeostasis Theory (ODT) of overweight and obesity; (iv) To summarize the body of evidence that is supportive of the general theory and the ODT; (v) To describe interventions for preventing overweight and obesity based on the ODT.
Obesity dyshomeostasis is mediated by the prefrontal cortex, amygdala and HPA axis with ghrelin providing the signalling for feeding dyshomeostasis, affect control and hedonic reward. Dyshomeostasis plays a causal role in obesity, the addictions and chronic conditions and is fueled by negative affect and chronic stress. Prevention and treatment efforts that target dyshomeostasis provide strategies for reducing adiposity, ameliorating the health impacts of addiction, and raising the quality of life in people suffering from chronic conditions and stress.
A four-armed strategy to halt the obesity epidemic consists of eliminating the causes of overweight and obesity: (1) Resisting and putting a stop to a culture of victim-blaming, stigma and discrimination; (2) Resisting and devalorizing the thin-ideal; (3) Resisting and reducing consumption of energy-dense, low nutrient foods and drinks; (4) Improving access to plant-based diets. If fully implemented, these interventions should be competent to restore the conditions for homeostasis in billions of people and the obesity epidemic could be halted.