Obesity, Biased Mental Models, and Stigma in the Context of the Obesity COVID-19 Syndemic

By Peter S. Hovmand, Nicolaas P. Pronk, Theodore K. Kyle, Joseph Nadglowski, Patricia M. Nece, and Cypress T. Lynx
April 5, 2021 | Commentary


Introduction to Syndemics and Systems Thinking

Obesity is a complex disease associated with a multitude of genetic, behavioral, and environmental factors, and therefore addressing it effectively requires a nuanced and strategic approach that appreciates this complexity and leverages contextual factors. In January 2020, the National Academy of Sciences, Engineering, and Medicine’s Roundtable on Obesity Solutions (ROOS) used group model building [1,2,3] to support the strategic planning efforts of the Roundtable and its work to address obesity solutions and health inequities in obesity prevention, treatment, and management. During this collaboration, ROOS members generated a system map of drivers of obesity. Using the obesity system map as a discussion guide, the authors of this manuscript convened online starting in April 2020 to consider how COVID-19 might impact their work. In this commentary, the authors argue that the interaction between COVID-19 and obesity is an emergent syndemic that will significantly impact efforts to address obesity prevalence in coming years.

Syndemics are characterized as two or more interacting epidemics giving rise to an emergent pattern of disease and population health outcomes where large-scale social forces cause geographic clustering or concentration of disease [4]. The hallmark of a syndemic is the adverse interaction of epidemics, negatively affecting the mutual course of each disease trajectory, and enhancing vulnerability—outcomes made worse by experienced inequities. Efforts to clarify the concept of syndemics include the development of more explicit criteria for considering a population health phenomenon as a syndemic by calling out the specific mechanisms of interactions and the emergent patterns [5]. More recently, the concept has been extended in The Lancet to characterize obesity as part of a global syndemic that includes undernutrition and climate change [6], as well as part of a syndemic with COVID-19 through metabolic mechanisms [7]. However, in their recent review on what constitutes a syndemic, Mendenhall and Singer [4] critique efforts to restrict the interactions quantitatively. Specifically, they indicate that some approaches may systematically exclude interactions of social forces such as marginalization, oppression, and stigma that characterize disease clustering.

In this commentary, the authors of this manuscript use the ROOS system map to detail the feedback mechanisms and their interactions in population health. Specifically, this commentary focuses on the implications for prevention, treatment, and management of obesity, biased mental models, and stigma as impacted by COVID-19. Grounded in system dynamics [8,9], group model building provides a formal set of visual conventions for representing feedback systems. As ROOS focused on health inequities, the group model building effort elicited structures pre-COVID-19 that highlighted feedback mechanisms related to stigma, biased mental models, and structural racism central to the notion of a syndemic. Especially relevant to the quantified notion of interactions that Mendenhall and Singer [4] propose, this representation using system dynamics can be used to capture the shifting influence of feedback mechanisms as an emergent characteristic of syndemics [10].


Interactions Between Obesity and COVID-19

Figure 1 highlights a subset of the feedback mechanisms identified in the systems map. It was clear from early epidemiological studies [11,12,13] that obesity was a risk factor for COVID-19 complications and mortality (reinforcing loop R2 in Figure 1). More recent studies have pointed to biological mechanisms in people with obesity that may increase the incidence and severity of COVID-19 infections (reinforcing loop R1) [7]. The increased risk of complications and mortality has also influenced people seeking treatment for obesity and decreased disengagement (balancing loop B4). This led to concerns of increased stigma because of the portrayal of obesity in the media during COVID-19 [14] with potential implications for changes in payer policies in terms of coverage and reimbursement (balancing loop B2) based on biased mental models (reinforcing loop R4a).


FIGURE 1 | Subset of Feedback Mechanisms Driving the Obesity COVID-19 Syndemic
SOURCE: Developed by authors.
NOTES: The box represents prevalence as an accumulation or stock, which is disaggregated by population demographics (e.g., children and adults, gender, racial/ethnic social groups). Circles represent rates of change including obesity incidence, treatment, and mortality, which are also disaggregated by population demographics. Clouds represent population boundaries of the system as sources or sinks. Lines with arrows represent hypothesized causal relationships between key variables. Arcs with labels identify feedback mechanisms or loops where labels with “B” prefixes represent balancing feedback loops and “R” prefixes denote reinforcing feedback mechanisms.


There was already a shortage of trained obesity care providers pre-COVID-19, so the increase in demand for providers related to COVID-19, combined with increased demand to seek care related to obesity (as a means to reduce risks associated with COVID-19) conspire to limit quality of care, especially given the additive systemic effects of racism (balancing loop B5). These feedback effects are likely to have longer-term dynamic consequences that reinforce biased social norms and biased mental models (reinforcing loop R3), which influence funding (reinforcing loop R4c) that drives the availability of evidence-based interventions. Factors such as food insecurity, healthier behavior, and structural racism, as impacted by COVID-19, amplify the feedback interactions between obesity and COVID-19.

The obesity COVID-19 syndemic is likely to have three major dynamic consequences on persons living with obesity:

  1. access and barriers to treatment for obesity;
  2. societal bias and stigma; and
  3. obesity prevention over the longer term along with their financial well-being.


Figure 2 highlights some of the additional feedback mechanisms identified by ROOS tied to prevention, including challenges related to existing inequities in healthy food and activity systems, healthier behavior, adverse childhood experiences, and food insecurity—all issues tied to significant existing health inequities that have been impacted and exacerbated by COVID-19.


FIGURE 2 | Overall System Map of Obesity Prevalence from the ROOS Group Model Building Workshop in January 2020
SOURCE: Developed by authors.


In already resource-constrained systems—with shortages of a trained workforce, biased mental models and stigma, barriers to implementing evidence-based policy, and environmental prevention strategies—multiple systems may fall into a set of nested capability traps [15]. These limitations, in turn, create a greater effort needed to fight multiple crises without the resources available to address the underlying systems perpetuating health inequities in the obesity COVID-19 syndemic. Furthermore, as obesity and COVID-19 form a syndemic, intersectionality demands that multiple oppressed identities (such as race, gender, sexual orientation, and geographic origin) also interact
with obesity, and thus cannot be ignored [16].



It has been 26 years since Singer first identified syndemics and 13 years since obesity was recognized as a complex system [17]. It is possible to identify multiple leverage points for action using systems thinking to examine the complexity driving the obesity COVID-19 syndemic. There is no need to wait any longer to respond to the obesity COVID-19 syndemic and work to prevent the resulting health inequities. Unlike the past, today we have tools available to halt the structural harms [18] inflicted by the obesity COVID-19 syndemic.


Join the conversation!

Tweet this!  A new #NAMPerspectives commentary uses the frame of a syndemic, or interacting epidemics, to explore how #COVID19 has made treatment of obesity more challenging and stigma more prevalent: https://doi.org/10.31478/202104a

Tweet this!  The authors of our newest #NAMPerspectives commentary discuss how the interaction between #COVID19 and obesity has impacted access to treatment, increased societal bias and stigma, and may impact obesity prevention over the long-term: https://doi.org/10.31478/202104a

Tweet this!  Existing health inequities, including those for people with obesity, have been impacted and exacerbated by COVID-19. This #NAMPerspectives commentary focuses on the implications of #COVID19 for the prevention, treatment, and management of obesity: https://doi.org/10.31478/202104a

Download the graphics below and share them on social media!





  1. Vennix, J. A. M. 1996. Group model building: Facilitating team learning using system dynamics. New York, NY: John Wiley & Sons.
  2. Richardson, G. P., and D. F. Andersen. 1995. Teamwork in group model building. System Dynamics Review 11(2):113-137. https://doi.org/10.1002/sdr.4260110203
  3. Hovmand, P. S. 2014. Community-based system dynamics. New York, NY: Springer.
  4. Mendenhall, E., and M. Singer. 2020. What constitutes a syndemic? Methods, contexts, and framing from 2019. Current Opinion in HIV and AIDS 15(4):213-217. https://doi.org/10.1097/COH.0000000000000628
  5. Tsai, A. C., and B. F. O. Burns. 2015. Syndemics of psychosocial problems and HIV risk: A systematic review of empirical tests of the disease interaction concept. Social Science & Medicine 139:26-35. https://doi.org/10.1016/j.socscimed.2015.06.024
  6. Swinburn, B. A., V. I. Kraak, S. Allender, V. J. Atkins, P. I. Baker, J. R. Bogard, H. Brinsden, A. Calvillo, O. De Schutter, R. Devarajan, M. Ezzati, S. Friel, S. Goenka, R. A. Hammond, G. Hastings, C. Hawkes, M. Herrero, P. S. Hovmand, M. Howden, L. M. Jaacks, A. B. Kapetanaki, M. Kasman, H. V. Kuhnlein, S. K. Kumanyika, B. Larijani, T. Lobstein, M. W. Long, V. K. R. Matsudo, S. D. H. Mills, G. Morgan, A. Morshed, P. M. Nece, A. Pan, D. W. Patterson, G. Sacks, M. Shekar, G. L. Simmons, W. Smit, A. Tootee, S. Vandevijvere, W. E. Waterlander, L. Wolfenden, and W. H. Dietz. 2019. The global syndemic of obesity, undernutrition, and climate change: The Lancet commission report. The Lancet 393(10,173):791-846. https://doi.org/10.1016/S0140-6736(18)32822-8
  7. Hill, M. A., J. R. Sowers, and C. S. Mantzoros. 2021. Commentary: COVID-19 and obesity pandemics converge into a syndemic requiring urgent and multidisciplinary action. Metabolism 114:154408. https://doi.org/10.1016/j.metabol.2020.154408
  8. Richardson, G. P. 2011. Reflections on the foundations of system dynamics. System Dynamics Review 27(3):219-243. https://doi.org/10.1002/sdr.462
  9. Sterman, J. 2018. System dynamics at sixty: The path forward. System Dynamics Review 34(1-2):5-47. https://doi.org/10.1002/sdr.1601
  10. Hovmand, P. S., and C. Nishesh. 2015. Simultaneous linear estimation using structural equation modeling. In H. Rahmandad, R. Oliva, and N. D. Osgood (Eds.) Analytical Methods for Dynamic Modelers (71-94). Cambridge, MA: The MIT Press.
  11. Hajifathalian, K., S. Kumar, C. Newberry, S. Shah, B. Fortune, T. Krisko, S. Ortiz-Pujols, X. K. Zhou, A. J. Dannenberg, R. Kumar, and R. Z. Sharaiha. 2020. Obesity is associated with worse outcomes in COVID-19: Analysis of early data from New York City. Obesity 28(9):1606-1612. https://doi.org/10.1002/oby.22923
  12. Klang, E., G. Kassim, S. Soffer, R. Freeman, M. A. Levin, and D. L. Reich. 2020. Severe obesity as an independent risk factor for COVID-19 mortality in hospitalized patients younger than 50. Obesity 28(9): 1595-1599. https://doi.org/10.1002/oby.22913
  13. Pettit, N. N., E. L. MacKenzie, J. P. Ridgway, K. Pursell, D. Ash, B. Patel, and M. T. Pho. 2020. Obesity is associated with increased risk for mortality among hospitalized patients with COVID-19. Obesity 28(10):1806-1810. https://doi.org/10.1002/oby.22941
  14. Flint, S. W. 2020. Stigmatizing media portrayal of obesity during the coronavirus (COVID-19) pandemic. Frontiers in Psychology 11. https://doi.org/10.3389/fpsyg.2020.02124
  15. Repenning, N. P., and J. D. Sterman. 2002. Capability traps and self-confirming attribution errors in the dynamics of process improvement. Administrative Science Quarterly 47(2):265-295. https://doi.org/10.2307/3094806
  16. Walby, S. 2007. Complexity theory, systems theory, and multiple intersecting social inequalities. Philosophy of the Social Sciences 37(4):449-470. https://doi.org/10.1177/0048393107307663
  17. Vandenbroeck, P., J. Goossens, and M. Clemens. 2018. Foresight Tackling Obesities: Future Choices—Building the Obesity System Map. Government Office for Science, UK Government’s Foresight Programme. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/fi le/295154/07-1179-obesity-building-system-map.pdf (accessed December 18, 2020).
  18. Galtung, J. 1969. Violence, peace, and peace research. Journal of Peace Research 6(3):167-91. https://doi.org/10.1177/002234336900600301



Suggested Citation

Hovmand, P. S., N. P. Pronk, T. K. Kyle, J. Nadglowski, P. M. Nece, and C. T. Lynx. 2021. Obesity, Biased Mental Models, and Stigma in the Context of the Obesity COVID-19 Syndemic. NAM Perspectives. Commentary, National
Academy of Medicine, Washington, DC. https://doi.org/10.31478/202104a

Author Information

Peter S. Hovmand, PhD, MSW, is Pamela B. Davis, MD, PhD, Professor of Medicine in the Center for Community Health Integration at Case Western Reserve University. Nicolaas P. Pronk, PhD, MA, is President of the HealthPartners Institute. Theodore K. Kyle, RPh, MBA, is Principal and Founder of ConscienHealth. Joseph Nadglowski is President and CEO of the Obesity Action Coalition. Patricia M. Nece, JD, is Vice Chair of the Obesity Action Coalition. Cypress T. Lynx, MPH, is Research Associate in the Food and Nutrition Board at the National Academies of Science, Engineering, and Medicine.

Peter S. Hovmand served as a consultant to the Roundtable on Obesity Solutions from January 2020–June 2020. Nicolaas P. Pronk is the current chair of the Roundtable on Obesity Solutions, and Theodore K. Kyle, Joseph Nadglowski, and Patricia M. Nece are members.


The authors would like to acknowledge the members of the Roundtable on Obesity Solutions for their input on the system map. The authors would also like to thank Leslie Sim, MPH, of the National Academies of Science, Engineering, and Medicine for her leadership as the Director of the Roundtable on Obesity Solutions.

Conflict-of-Interest Disclosures

Theodore K. Kyle receives personal fees from Gelesis, Novo Nordisk Inc., and Nutrisystem. Patricia M. Nece receives personal fees from Novo Nordisk Inc.


Questions or comments should be directed to Cypress Lynx at CLynx@nas.edu.


The system map was developed by individual members of the Roundtable on Obesity Solutions in collaboration with Peter S. Hovmand. The systems map does not necessarily represent the views of any one organization,
the Roundtable, or the National Academies and has not been subjected to the review procedures of, nor is it a product of, the National Academies.

The views expressed in this paper are those of the authors and not necessarily of the authors’ organizations, the National Academy of Medicine (NAM), or the National Academies of Sciences, Engineering, and Medicine (the National Academies). The paper is intended to help inform and stimulate discussion. It is not a report of the NAM or the National Academies. Copyright by the National Academy of Sciences. All rights reserved.

Read more by topic:
, ,

Join Our Community

Sign up for NAM email updates