Next Article in Journal
Associations Between MASLD, Ultra-Processed Food and a Mediterranean Dietary Pattern in Older Adults
Previous Article in Journal
Advancing Nutritional Science: Contemporary Perspectives on Diet’s Role in Metabolic Health and Disease Prevention
Previous Article in Special Issue
Parental Acculturation and Its Effect on Preschool-Aged Children’s Health Behaviors Among Latinos in Nevada: A Cross-Sectional Study
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Editorial

Dietary Behaviors and the Living Environment Can Explain Residual Obesity Risk

by
Demosthenes Panagiotakos
Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University, 176 76 Athens, Greece
Nutrients 2025, 17(9), 1413; https://doi.org/10.3390/nu17091413
Submission received: 2 April 2025 / Accepted: 7 April 2025 / Published: 23 April 2025
(This article belongs to the Special Issue Dietary Behaviors and Obesity Predisposition)

1. Introduction

Despite substantial advancements and extensive funding in obesity research—spanning the development of novel pharmacological and non-pharmacological treatments, as well as numerous public health initiatives—the global prevalence of obesity continues to escalate at an alarming rate.
Obesity is a complex condition influenced by both genetic and environmental factors [1]. It has been suggested that genetic predisposition accounts for approximately 40–70% of an individual’s risk of developing obesity [2,3,4]. While genetics play a critical role in obesity risk, lifestyle factors such as diet and physical activity are also well recognized for their significant impact on an individual’s body weight [5,6,7].
However, the persistent increase in obesity rates suggests that there are key factors that have been overlooked or not even considered in current obesity research, increasing the residual risk. This residual obesity risk refers to the influence of certain behavioral, psychological, and socio-environmental determinants that are not accounted for in conventional models. Factors such as stress, emotional eating, sleep deprivation, food insecurity, and cultural norms surrounding diet and physical activity can significantly impact an individual’s ability to maintain a healthy weight, even when genetic predisposition and conventional risk factors are considered. Additionally, socioeconomic status, exposure to obesogenic environments, and marketing of unhealthy foods contribute to persistent weight-related disparities.
This editorial explores how dietary behaviors, including meal timing, portion control, food choices, and eating patterns influenced by emotional and environmental cues, may contribute to residual obesity risk. It also examines why traditional obesity interventions—typically focused on calorie restriction, exercise, and behavioral modification—often fail to address these deeper, underlying factors. By recognizing the broader influences on eating behaviors, we can develop more effective and sustainable strategies for obesity prevention and management.

2. Advances in Obesity Research and Their Limitations

Over the past few decades, significant strides have been made in understanding the pathophysiology of obesity. Advances in metabolic research have identified key pathways involved in energy regulation, appetite control, and fat storage. Genetic variations can affect metabolism, appetite regulation, fat storage, and energy expenditure, making some individuals more susceptible to weight gain. Studies have identified multiple genes, such as FTO (i.e., fat mass and obesity-associated gene) and melanocortin-4 receptor gene (MC4R), that play a role in obesity by influencing hunger, satiety, and fat accumulation [3,4].
Recent research suggests that gut microbiota composition may play a pivotal role in residual obesity risk. The gut microbiome influences energy extraction from food, metabolic rate, and inflammation, factors not typically measured in standard obesity studies. Dysbiosis, or an imbalance in gut microbiota, has been linked to increased adiposity and altered energy metabolism, independent of caloric intake. Furthermore, epigenetic modifications induced by early-life nutrition and dietary exposures may predispose individuals to obesity later in life. Maternal diet, childhood eating patterns, and intergenerational influences contribute to a metabolic phenotype that traditional interventions may fail to reverse [8,9,10].
Moreover, pharmaceutical innovations, such as GLP-1 receptor agonists (e.g., semaglutide and tirzepatide), have emerged as promising treatments for obesity, demonstrating efficacy in reducing body weight. Additionally, public health initiatives have promoted dietary guidelines aimed at reducing calorie intake and improving nutrient quality [11].
However, despite these advances, obesity rates continue to climb. This paradox suggests that conventional interventions, focused on diet composition, caloric restriction, and pharmacotherapy, do not fully address the complexity of obesity. The concept of residual obesity risk acknowledges that many non-traditional factors, particularly those linked to dietary behaviors, remain unrecognized in standard epidemiological frameworks. This residual obesity risk encompasses factors that are not typically included in obesity research models but nonetheless exert a significant influence on weight regulation. These include eating behaviors and patterns, i.e., irregular meal timing, frequent snacking, and nighttime eating, which have been associated with obesity risk beyond total caloric intake, emotional eating, stress-induced overeating, and hedonic eating that contribute to weight gain independent of metabolic factors, disrupted circadian rhythms, and late-night food consumption and negatively impact metabolic homeostasis [12].

3. Why Traditional Approaches Fall Short

Conventional dietary interventions for obesity often focus on nutrient composition and calorie reduction. However, these approaches do not fully address the behavioral and environmental contributors to obesity risk. It is worth noting that most intervention studies have been meticulously and thoughtfully designed to achieve their objectives and funding from national and international organizations; however, their long-term sustainability remains uncertain. Key shortcomings include failure to address certain behavioral triggers. Many weight loss programs neglect the role of emotional eating and stress-induced dietary behaviors. Cognitive and behavioral interventions, such as mindfulness-based eating strategies, are underutilized in obesity management. Moreover, public health recommendations often assume equal access to healthy foods, ignoring disparities in food availability and affordability. Stress, work schedules, and cultural factors shape dietary behaviors in ways that standard interventions fail to consider [13,14].
The food environment also plays a significant role in shaping dietary behaviors and obesity risk. The availability, affordability, and accessibility of healthy versus unhealthy foods can greatly influence an individual’s eating patterns and overall caloric intake. In many urban settings, highly processed, energy-dense foods are more convenient and cost-effective than fresh, nutrient-rich options, making it challenging for individuals, especially those from lower socioeconomic backgrounds, to maintain a balanced diet. Additionally, aggressive marketing strategies by the food industry, particularly targeting children and low-income populations, further contribute to unhealthy eating habits. Factors such as portion sizes, food deserts, workplace and school meal options, and cultural norms around eating also shape long-term dietary behaviors. As a result, even individuals who are aware of healthy eating principles may struggle to make healthier choices in environments that continuously promote overconsumption of unhealthy foods. Addressing these systemic influences through policy changes, urban planning, and educational initiatives is essential for reducing obesity risk at the population level [15,16,17].

4. Strategies to Mitigate Residual Obesity Risk

To effectively combat obesity, interventions must integrate a broader understanding of dietary behaviors and their interactions. Urban planning initiatives can increase access to healthy food options in underserved communities. School-based nutritional programs can instill lifelong healthy eating habits in children. Behavioral interventions should be incorporated into obesity management strategies. Dietary modifications should extend beyond calorie reduction. Emphasizing whole foods, fiber-rich diets, and gut microbiome-friendly nutrition can promote better long-term outcomes. Public health and policy initiatives must also be strengthened. Food labeling regulations should be improved to enhance consumer awareness of food quality. Urban planning initiatives should focus on increasing access to healthy food options in underserved communities. School-based nutritional programs should aim to instill lifelong healthy eating habits in children.

5. Conclusions

The persistence of obesity despite advances in current research highlights the significance of residual obesity risk. Dietary behaviors, shaped by social and environmental factors, play a crucial role in obesity that is not adequately captured in traditional studies. Addressing residual obesity risk requires a paradigm shift in obesity prevention and management, incorporating behavioral interventions, dietary quality improvements, and systemic policy changes. A holistic approach that integrates these factors is essential to curbing the global obesity epidemic and improving long-term health outcomes.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hruby, A.; Hu, F.B. The Epidemiology of Obesity: A Big Picture. Pharmacoeconomics 2015, 33, 673–689. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  2. Bray, G.A.; Kim, K.K.; Wilding, J.P.H.; World Obesity Federation. Obesity: A chronic relapsing progressive disease process. A position statement of the World Obesity Federation. Obes. Rev. 2017, 18, 715–723. [Google Scholar] [CrossRef] [PubMed]
  3. Yang, Y.; Gao, X.; Tao, X.; Gao, Q.; Zhang, Y.; Yang, J. Combined effect of FTO and MC4R gene polymorphisms on obesity in children and adolescents in Northwest China: A case-control study. Asia Pac. J. Clin. Nutr. 2019, 28, 177–182. [Google Scholar] [CrossRef] [PubMed]
  4. Lazopoulou, N.; Gkioka, E.; Ntalla, I.; Pervanidou, P.; Magiakou, A.M.; Roma-Giannikou, E.; Chrousos, G.P.; Papassotiriou, I.; Dedoussis, G.; Kanaka-Gantenbein, C. The combined effect of MC4R and FTO risk alleles on childhood obesity in Greece. Hormones 2015, 14, 126–133. [Google Scholar] [CrossRef] [PubMed]
  5. Pot, G.K.; Hardy, R.; Stephen, A.M. Irregular consumption of energy intake in meals is associated with a higher cardiometabolic risk in adults of a British birth cohort. Int. J. Obes. 2014, 38, 1518–1524. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  6. Al Abdi, T.; Andreou, E.; Papageorgiou, A.; Heraclides, A.; Philippou, E. Personality, Chrono-nutrition and Cardiometabolic Health: A Narrative Review of the Evidence. Adv. Nutr. 2020, 11, 1201–1210. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  7. Coskun, A.K.; Oz, B.S. The Effects of Cardiometabolic Risk Factors on Dietary Behavior. Adv. Nutr. 2022, 13, 692. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  8. Bray, G.A.; Champagne, C.M. Beyond energy balance: There is more to obesity than kilocalories. J. Am. Diet. Assoc. 2005, 105 (Suppl. S1), S17–S23. [Google Scholar] [CrossRef] [PubMed]
  9. Turnbaugh, P.J.; Ley, R.E.; Mahowald, M.A.; Magrini, V.; Mardis, E.R.; Gordon, J.I. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006, 444, 1027–1031. [Google Scholar] [CrossRef] [PubMed]
  10. Liu, S.; Tao, Z.; Qiao, M.; Shi, L. The Functions of Major Gut Microbiota in Obesity and Type 2 Diabetes. Metabolites 2025, 15, 167. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  11. Zhang, J.; Wei, J.; Lai, W.; Sun, J.; Bai, Y.; Cao, H.; Guo, J.; Su, Z. Focus on Glucagon-like Peptide-1 Target: Drugs Approved or Designed to Treat Obesity. Int. J. Mol. Sci. 2025, 26, 1651. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  12. Kantilafti, M.; Chrysostomou, S.; Yannakoulia, M.; Giannakou, K. The association between binge eating disorder and weight management in overweight and obese adults: A systematic literature review. Nutr. Health 2022, 28, 189–197. [Google Scholar] [CrossRef] [PubMed]
  13. Blaustein, J.R.; Quisel, M.J.; Hamburg, N.M.; Wittkopp, S. Environmental Impacts on Cardiovascular Health and Biology: An Overview. Circ. Res. 2024, 134, 1048–1060. [Google Scholar] [CrossRef] [PubMed]
  14. Reddy, Y.U.; Ugwuja, F. Changing a Community: A Holistic View of the Fundamental Human Needs and Their Public Health Impacts. Cureus 2023, 15, e44023. [Google Scholar]
  15. Neshteruk, C.D.; Luecking, C.T.; Kracht, C.L.; Burkart, S.; Melnick, E.M.; Anderson, R.E., 3rd; Lane, H.G. Implementation strategies used in policy, systems, and environmental interventions addressing obesity-related outcomes in early childhood education settings: A systematic review. Implement. Sci. Commun. 2025, 6, 31. [Google Scholar] [CrossRef] [PubMed]
  16. Choudhury, S.; Bi, A.Z.; Medina-Lara, A.; Morrish, N.; Veettil, P.C. The rural food environment and its association with diet, nutrition status, and health outcomes in low-income and middle-income countries (LMICs): A systematic review. BMC Public Health 2025, 25, 994. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  17. Panagiotakos, D. Challenges and Opportunities in Preventing Cardiovascular Disease Within the Built Living Environment. J. Cardiovasc. Metab. Dis. Epidemiol. 2025, 1. Available online: https://www.sciltp.com/journals/jcmde/article/view/504 (accessed on 31 March 2025).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Panagiotakos, D. Dietary Behaviors and the Living Environment Can Explain Residual Obesity Risk. Nutrients 2025, 17, 1413. https://doi.org/10.3390/nu17091413

AMA Style

Panagiotakos D. Dietary Behaviors and the Living Environment Can Explain Residual Obesity Risk. Nutrients. 2025; 17(9):1413. https://doi.org/10.3390/nu17091413

Chicago/Turabian Style

Panagiotakos, Demosthenes. 2025. "Dietary Behaviors and the Living Environment Can Explain Residual Obesity Risk" Nutrients 17, no. 9: 1413. https://doi.org/10.3390/nu17091413

APA Style

Panagiotakos, D. (2025). Dietary Behaviors and the Living Environment Can Explain Residual Obesity Risk. Nutrients, 17(9), 1413. https://doi.org/10.3390/nu17091413

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop