Can Weight Loss Reduce Risk-Taking Behaviors?

• A study in Germany published in Clinical Nutrition found that individuals’ proneness to risk-taking behavior decreased after a 10-week weight loss intervention
• Before the intervention, participants’ decisions depended on their mood
• After participants lost weight, their decisions no longer depended on mood but became associated with glycated hemoglobin levels, i.e., with long-term blood sugar levels

Obesity is an important health problem in the modern world. The number of overweight and obese individuals and their share in the global population has increased drastically in recent decades. This prompted many researchers to declare that the world is facing an obesity epidemic (Wong et al., 2022).

Many researchers declare that the world is facing an obesity epidemic.

What is obesity, and what causes it?

Obesity is a medical condition characterized by excessive body fat accumulation that can negatively impact health. It is typically measured using the body mass index (BMI), with a BMI of 30 or higher indicating obesity. A BMI of 30 was chosen as the cutoff because that is the point at which the risk of several obesity-related diseases, including type 2 diabetes, starts to rise exponentially (Wilding, 2001).

While it is obvious that obesity develops when the body consumes more food than it needs, the question remains why that happens. The human body has an intricate food intake regulation mechanism that makes us feel satiated and stop eating when we have had enough. In obesity, this mechanism becomes dysregulated.

While it is obvious that obesity develops when the body consumes more food than it needs, the question remains why that happens.

There seem to be many different ways in which this dysregulation can happen, including various genetic variants predisposing individuals to obesity, tumors, or changes in specific brain structures (e.g., thalamus) (Wilding, 2001), and certain dietary patterns seem also to be able to induce obesity. For example, there is a well-established protocol for studies on rodents where feeding them food that is rich in easily digestible fats and carbohydrates at the same time will dysregulate food intake control mechanisms in their brains, leading to the development of obesity (e.g., Ikemoto et al., 1996). Researchers call this feeding pattern the obesogenic diet.

Feeding them food rich in easily digestible fats and carbohydrates simultaneously will dysregulate food intake control mechanisms.

Similarly, foods rich in easily digestible fats, sugars, and other additives that make the food more palatable and appealing have been linked to the development of obesity in humans. This is particularly the case with many ultraprocessed foods. Researchers argue that frequent consumption of such foods can lead to a condition they refer to as food addiction. Food addiction shows marked similarities with other types of recognized substance addictions (Gearhardt et al., 2011; Hedrih, 2023; Schulte et al., 2019).

Frequent consumption of ultra-processed foods can lead to food addiction.

How does the functioning of the brain change in obesity?

It is fairly obvious that for a person to develop obesity, changes in the brain’s functioning need to occur, which will cause the person to eat more food than his/her body needs (e.g., Pujol et al., 2021). Research into these changes is ongoing, but it seems likely that changes in neural functioning that develop in obesity are not limited to food intake.

For a person to develop obesity, changes in the brain’s functioning need to occur, which will cause the person to eat more food than his/her body needs.

For example, research indicates that sleep patterns of obese individuals tend to differ from those of non-obese individuals (Bacaro et al., 2020), but also that sleep deprivation seems to change individuals’ eating patterns (Brondel et al., 2010; Greer et al., 2013). There is evidence of increased inflammation in the hypothalamus region of the brain in obesity (Thaler et al., 2013), and that energy use patterns in the brains of obese and non-obese individuals differ (Hedrih, 2024; Wang et al., 2020).

The current study

Study author Beatrix Keweloh and her colleagues note that previous studies reported that individuals with higher body mass indexes tend to be more prone to risk-taking. They wondered whether risk-taking would decrease if the body mass index decreased, i.e., if individuals lost weight (Keweloh et al., 2024). These authors hypothesized that metabolic and psychological factors would change participants’ decision patterns after weight loss and that this would depend on their blood glucose levels.

The study participants were 62 individuals with severe obesity, 41 of whom were women. Their average body mass index was 46-47, and their average age was 45. They completed two assessment procedures: a computerized economic risk task to assess their proneness to taking risks and a mood assessment (the Positive and Negative Affect Scale, PANAS). Participants also gave blood samples, allowing researchers to measure their glycated hemoglobin levels. These procedures were 10 weeks apart.

In between, participants completed a clinically supervised 10-week weight loss intervention in which their food intake was reduced to 800 kcal/day, more than two to three times lower than their normal daily food intake. During the intervention, participants consumed micronutrient-balanced, very low-calorie diet products with around 33% protein—carbohydrates comprised around 50% and fat around 17% of participants’ total energy consumption. After completing the calorie-reduced intervention, participants gradually switched to meals based on a Mediterranean diet (see Figure 1).

 

 

Figure 1. Study Procedure (Keweloh et al., 2024)

 

Risk-taking behavior decreased after participants lost weight

The results showed that participants lost an average of 49 pounds (22 kilograms), lowering their average body mass index to 36. The concentration of glycated hemoglobin in their blood, which indicates long-term glucose levels, also decreased significantly after the weight loss intervention. Participants’ moods improved substantially compared to before the intervention.

The concentration of glycated hemoglobin in their blood, which indicates long-term glucose levels, decreased significantly after the weight loss.

After losing weight, participants became less prone to taking risks. The likelihood that they will choose the risky option in the economic game decreased by 19%. The magnitude of the decrease in risk-taking was associated with the change in body mass index. Individuals whose body mass index reduced more (i.e., who lost more weight) tended to show a stronger decrease in risk-taking (Figure 2).

 

Figure 2. Study Findings (Keweloh et al., 2024)

 

Before the intervention, participants’ proneness to choose the risky option in the game was associated with their mood, with participants in worse moods being more prone to take risks. This association disappeared after participants lost weight. However, after the intervention, glycated hemoglobin levels became negatively associated with risk propensity, i.e., individuals with higher glycated hemoglobin levels were less prone to choosing the risky option.

After losing weight, participants became less prone to taking risks.

Conclusion

Overall, the study provides evidence that risk-taking behavior might be affected by obesity, with weight loss being accompanied by a decrease in proneness to take risks.

The knowledge gained from this study contributes to the scientific understanding of psychological changes associated with obesity. It could also help design innovative intervention strategies to support weight maintenance after weight loss.

The paper “Weight loss impacts risky decisions in obesity” was authored by Beatrix Keweloh, Damiano Terenzi, Eva Froehlich, Carol Coricelli, Paula Stürmer, Nathalie Rohmann, Perdita Wietzke-Braun, Alexia Beckmann, Matthias Laudes, and Soyoung Q. Park.

References

Bacaro, V., Ballesio, A., Cerolini, S., Vacca, M., Poggiogalle, E., Donini, L. M., Lucidi, F., & Lombardo, C. (2020). Sleep duration and obesity in adulthood: An updated systematic review and meta-analysis. Obesity Research & Clinical Practice, 14(4), 301–309. https://doi.org/10.1016/j.orcp.2020.03.004

Brondel, L., Romer, M. A., Nougues, P. M., Touyarou, P., & Davenne, D. (2010). Acute partial sleep deprivation increases food intake in healthy men. The American Journal of Clinical Nutrition, 91(6), 1550–1559. https://doi.org/10.3945/ajcn.2009.28523

Gearhardt, A. N., Yokum, S., Orr, P. T., Stice, E., Corbin, W. R., & Brownell, K. D. (2011). Neural Correlates of Food Addiction. Archives of General Psychiatry, 68(8), 808–816. https://doi.org/10.1001/ARCHGENPSYCHIATRY.2011.32

Greer, S. M., Goldstein, A. N., & Walker, M. P. (2013). The impact of sleep deprivation on food desire in the human brain. Nature Communications, 4. https://doi.org/10.1038/ncomms3259

Hedrih, V. (2023). Scientists Propose that Ultra-Processed Foods be Classified as Addictive Substances. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/scientists-propose-that-ultra-processed-foods-be-classified-as-addictive-substances/

Hedrih, V. (2024, June 10). Obese Men Need Extra Energy to Resist Food Craving. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/obese-men-need-extra-energy-to-resist-food-craving/

Ikemoto, S., Takahashi, M., Tsunoda, N., Maruyama, K., Itakura, H., & Ezaki, O. (1996). High-fat diet-induced hyperglycemia and obesity in mice: Differential effects of dietary oils. Metabolism, 45(12), 1539–1546. https://doi.org/10.1016/S0026-0495(96)90185-7

Keweloh, B., Terenzi, D., Froehlich, E., Coricelli, C., Stürmer, P., Rohmann, N., Wietzke-Braun, P., Beckmann, A., Laudes, M., & Park, S. Q. (2024). Weight loss impacts risky decisions in obesity. Clinical Nutrition, 43(6), 1270–1277. https://doi.org/10.1016/j.clnu.2024.04.002

Pujol, J., Blanco-Hinojo, L., Martínez-Vilavella, G., Deus, J., Pérez-Sola, V., & Sunyer, J. (2021). Dysfunctional Brain Reward System in Child Obesity. Cerebral Cortex, 31, 4376–4385. https://doi.org/10.1093/cercor/bhab092

Schulte, E. M., Yokum, S., Jahn, A., & Gearhardt, A. N. (2019). Food Cue Reactivity in Food Addiction: A Functional Magnetic Resonance Imaging Study HHS Public Access. Physiol Behav, 208, 112574. https://doi.org/10.1016/j.physbeh.2019.112574

Thaler, J. P., Guyenet, S. J., Dorfman, M. D., Wisse, B. E., & Schwartz, M. W. (2013). Hypothalamic Inflammation: Marker or Mechanism of Obesity Pathogenesis? Diabetes, 62(8), 2629–2634. https://doi.org/10.2337/DB12-1605

Wang, G.-J., Shokri Kojori, E., Yuan, K., Wiers, C. E., Manza, P., Wong, C. T., Fowler, J. S., & Volkow, N. D. (2020). Inhibition of food craving is a metabolically active process in the brain in obese men. International Journal of Obesity, 44(3), 590–600. https://doi.org/10.1038/s41366-019-0484-z

Wilding, J. P. H. (2001). Causes of obesity. Practical Diabetes International, 18(8), 288–292. https://doi.org/10.1002/PDI.277

Wong, M. C., Mccarthy, C., Fearnbach, N., Yang, S., Shepherd, J., & Heymsfield, S. B. (2022). Emergence of the obesity epidemic: 6-decade visualization with humanoid avatars. The American Journal of Clinical Nutrition, 115(4), 1189–1193. https://doi.org/10.1093/AJCN/NQAC005