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Do Different Brain Neurons Control Eating for Need vs. Pleasure?

Posted on April 27, 2025May 4, 2025 by CNP Staff

A study on mice published in Nature Metabolism examined how a group of GABAergic proenkephalin neurons in the diagonal band of Broca region of the brain responds to food presentation.
A subset of neurons linking to the paraventricular nucleus of the hypothalamus promoted eating when the mouse was hungry.
Another subset of neurons linking to the lateral hypothalamus inhibited eating behaviors when the mouse detected high-calorie food

Why We Eat When We Are Not Hungry

We have all probably experienced a situation where we wanted to eat something, although we knew we had recently eaten and were not hungry. This can happen when we see, smell, or taste something delicious, but also when we find ourselves in an environment where we usually eat or that we have learned to associate with eating, when we are in a social situation when eating is expected, when we feel sad or distressed, and in many other situations.

Two Types of Hunger: Homeostatic vs. Hedonic

Scientists believe there are at least two different processes responsible for hunger and the desire to eat food (Hedrih, 2023). One of these processes is homeostatic hunger, which serves the purpose of acquiring the nutrients our body needs to survive. Lack of specific nutrients triggers specific signals, leading to the experience of hunger that motivates the organism to seek and eat foods containing those nutrients.

The other process is hedonic eating. It arises primarily from the fact that our brain rewards us with pleasant experiences when we eat certain foods. For example, studies (primarily on rodents) have shown that neural pathways linking the digestive system to reward-processing areas in the brain (Hedrih, 2024a; McDougle et al., 2024) react to the presence of fat and sugar, producing pleasant experiences.

Moreover, people seem to learn to expect a certain degree of pleasure from the food they eat. If a meal they consume does not produce satiety, they will be more likely to overeat or eat more of another, more enjoyable food later (Hedrih, 2024c; Murphy et al., 2024).

How Hunger Cues and Emotional Eating Are Learned

However, the expectation of pleasant experiences from delicious food does not seem to be the only thing that triggers eating behaviors. Some researchers argue that humans learn to interpret specific signals from their body as hunger in childhood, primarily through interactions with their caregivers (Changizi et al., 2002; Hedrih, 2023).

For example, one recent study found substantial associations between the hunger experiences of young adults (Australian students participating in the study) and their caregivers (Hedrih, 2023; Stevenson et al., 2023). Another study found a substantial overlap between the broad eating patterns of children and their caregivers (Pickard et al., 2024). The results of that study showed that parents who were fussy eaters were more likely to have children who were also fussy eaters. Similarly, parents prone to emotional overeating tended to have children with similar eating behaviors.

In addition, humans can learn to anticipate eating at certain places and times so well that their bodies begin adjusting specific biochemical parameters, such as blood sugar levels, in anticipation of a meal (Isherwood et al., 2023). Many humans also learn to use food to regulate unpleasant emotions through emotional eating (Ha & Lim, 2023; Hedrih, 2024b; Ljubičić et al., 2023).

Brain Circuits Regulating Hunger and Pleasure

Study author Hailan Liu and her colleagues wanted to examine the role of a specific group of neurons called GABAergic proenkephalin (or Penk) neurons located in the diagonal band of Broca (DBB) region of the basal forebrain of male mice in regulating homeostatic and hedonic feeding (i.e., feeding to obtain the needed nutrients and feeding motivated by the expectation of rewarding experiences) (Liu et al., 2024).

The Penk neurons are neural cells that release the neurotransmitter gamma-aminobutyric acid (GABA) and the neuropeptides enkephalins. GABA is the brain’s main inhibitory neurotransmitter, meaning that it reduces the activity of neurons on which it acts. Penk neurons produce the protein proenkephalin. While still in the Penk neuron, this protein is divided into smaller protein-like signaling molecules called enkephalins. Enkephalins are released from the Penk neurons and modulate the activity of other neurons (see Figure 1).

Figure 1. GABAergic proenkephalin (Penk) neurons

Study authors conducted a series of experiments on mice using various techniques, including optogenetics. Optogenetics is a group of techniques that genetically modify targeted neural cells, enabling them to respond to specific types of light. In this study, researchers applied optogenetics to their studied DBB Penk neurons. This allowed them to switch specific groups of those neurons on and off at will. They also used advanced imaging techniques to track the activity of these neurons in real-time. The study authors monitored the activity of these neurons when mice were exposed to different types of food and under various conditions.

Separate groups of DBB Penk neurons regulate homeostatic and hedonic feeding

Results showed that the studied Penk neurons could be divided into two groups. One group of these neurons projected to the paraventricular nucleus (PVN) of the hypothalamus region in the brain. This region is involved in hunger regulation. When this group of neurons was activated, mice were more likely to eat regular mouse food. This was especially the case when they were hungry. Study authors concluded that the activity of these neurons promoted feeding driven by homeostatic hunger.

The other group of neurons projected to the lateral hypothalamus (LH) region of the brain. This region is involved in hedonic eating, which refers to eating for pleasure. When this group of Penk neurons was activated, mice decreased consumption of high-fat, high-sugar foods (high-calorie), even when these foods were freely available. Normally, mice (like humans) find food rich in both fats and sugar very appealing. This means that the group of DBB Penk neurons projecting to the lateral hypothalamus suppresses eating for pleasure (see Figure 2).

Figure 2. Penk neurons and their effects on eating behavior

Disabling DBB Penk neurons creates a preference for high-calorie food

Further experimenting revealed that the first group of neurons is very active when a mouse is presented with food after it has not eaten for some time. On the other hand, the Penk neurons linked to the lateral hypothalamus become active when a mouse is presented with high-calorie food, thereby inhibiting the drive to eat it. When all of these neurons were completely disabled, and mice had a choice between regular and high-calorie food (food rich in both fats and sugar), they consumed more of the high-calorie food, gained weight, and developed obesity (see Figure 3).

Figure 3. Penk Neurons Control Homeostatic and Hedonic Eating

Conclusion

Overall, the study identified two groups of GABAergic proenkephalin neurons located in the diagonal band of Broca region. One group projects to the area of the hypothalamus involved in hunger regulation, and their activity promotes eating when the mouse has not eaten for some time. The other group projects to the hypothalamus area involved in hedonic eating, and its activity inhibits this type of eating. Disabling these neurons makes mice prefer high-calorie food and gain weight.

This study contributes to the scientific understanding of neural mechanisms regulating food intake. These and similar findings may enable the development of more effective and targeted treatments for obesity in humans in the future.

The paper “Distinct basal forebrain-originated neural circuits promote homoeostatic feeding and suppress hedonic feeding in male mice” was authored by Hailan Liu, Jonathan C. Bean, Yongxiang Li, Meng Yu, Olivia Z. Ginnard, Kristine M. Conde, Mengjie Wang, Xing Fang, Hesong Liu, Longlong Tu, Na Yin, Junying Han, Yongjie Yang, Qingchun Tong, Benjamin R. Arenkiel, Chunmei Wang, Yang He, and Yong Xu.

References

Changizi, M. A., McGehee, R. M. F., & Hall, W. G. (2002). Evidence that appetitive responses for dehydration and food-deprivation are learned. Physiology and Behavior, 75(3), 295–304. https://doi.org/10.1016/S0031-9384(01)00660-6

Ha, O.-R., & Lim, S.-L. (2023). The role of emotion in eating behavior and decisions. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1265074

Hedrih, V. (2023). Are Hunger Cues Learned in Childhood? CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/are-hunger-cues-learned-in-childhood/

Hedrih, V. (2024a, February 19). Consuming Fat and Sugar (At The Same Time) Promotes Overeating, Study Finds. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/16563-2/

Hedrih, V. (2024b, May 6). Lonely Women Tend To Show More Maladaptive Eating Behaviors, Study Finds. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/lonely-women-tend-to-show-more-maladaptive-eating-behaviors-study-finds/

Hedrih, V. (2024c, July 9). When Our Eating Experience Falls Short, Do We Eat More to Compensate? CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/when-our-eating-experience-falls-short-of-expectations-will-we-eat-more-to-compensate/

Isherwood, C. M., van der Veen, D. R., Hassanin, H., Skene, D. J., & Johnston, J. D. (2023). Human glucose rhythms and subjective hunger anticipate meal timing. Current Biology, 33(7), 1321-1326.e3. https://doi.org/10.1016/j.cub.2023.02.005

Liu, H., Bean, J. C., Li, Y., Yu, M., Ginnard, O. Z., Conde, K. M., Wang, M., Fang, X., Liu, H., Tu, L., Yin, N., Han, J., Yang, Y., Tong, Q., Arenkiel, B. R., Wang, C., He, Y., & Xu, Y. (2024). Distinct basal forebrain-originated neural circuits promote homoeostatic feeding and suppress hedonic feeding in male mice. Nature Metabolism, 6(9), 1775–1790. https://doi.org/10.1038/s42255-024-01099-4

Ljubičić, M., Matek Sarić, M., Klarin, I., Rumbak, I., Colić Barić, I., Ranilović, J., Dželalija, B., Sarić, A., Nakić, D., Djekic, I., Korzeniowska, M., Bartkiene, E., Papageorgiou, M., Tarcea, M., Černelič-Bizjak, M., Klava, D., Szűcs, V., Vittadini, E., Bolhuis, D., & Guiné, R. P. F. (2023). Emotions and Food Consumption: Emotional Eating Behavior in a European Population. Foods, 12(4), Article 4. https://doi.org/10.3390/foods12040872

McDougle, M., de Araujo, A., Singh, A., Yang, M., Braga, I., Paille, V., Mendez-Hernandez, R., Vergara, M., Woodie, L. N., Gour, A., Sharma, A., Urs, N., Warren, B., & de Lartigue, G. (2024). Separate gut-brain circuits for fat and sugar reinforcement combine to promote overeating. Cell Metabolism. https://doi.org/10.1016/j.cmet.2023.12.014

Murphy, S. L., Van Meer, F., Van Dillen, L., Van Steenbergen, H., & Hofmann, W. (2024). Underwhelming pleasures: Toward a self-regulatory account of hedonic compensation and overconsumption. Journal of Personality and Social Psychology. https://doi.org/10.1037/pspa0000389

Pickard, A., Farrow, C., Haycraft, E., Herle, M., Edwards, K., Llewellyn, C., Croker, H., & Blissett, J. (2024). Associations between parent and child latent eating profiles and the role of parental feeding practices. Appetite, 201, 107589. https://doi.org/10.1016/j.appet.2024.107589

Stevenson, R. J., Bartlett, J., Wright, M., Hughes, A., Hill, B. J., Saluja, S., & Francis, H. M. (2023). The development of interoceptive hunger signals. Developmental Psychobiology, 65(2), 1–11. https://doi.org/10.1002/dev.22374

Does Eating Lots of Junk Food Lead to Poor Mental Health?

Posted on April 14, 2025June 17, 2025 by CNP Staff

A meta-analysis published in BMC Psychiatry examined the results of 17 studies and found that high junk food consumption is associated with poorer mental health.
Junk food consumption was associated with 15% higher odds of having depression and experiencing stress.
Odds of developing mental health disorders were 16% higher in individuals consuming lots of junk food.

Not all foods and beverages are equally healthy. Some foods are rich in essential nutrients, minerals, fibers, and other ingredients our body needs to function well. These foods generally support our long-term health. Other types of food tend to be rich in ingredients used solely to increase their palatability and to make them more appealing to people. These unhealthy foods often have large quantities of refined sugars added, causing blood sugar spikes and crashes after consumption. They also tend to contain various artificial additives to increase their taste and improve chemical or mechanical properties. These ingredients typically have no nutritional value and are linked to increased risks of health problems (e.g., Huang et al., 2023; Lane et al., 2024).

Junk food

One important category of foods typically considered unhealthy is junk food. Junk food is the name coined in the 1970s to refer to foods that are energy-dense (i.e., high in calories), but have low nutritional value. These foods contain refined sugar, white flour, trans fat, polyunsaturated fat, salt, and numerous food additives. They tend to lack protein, minerals, and fiber (Rajveer & Monika, 2012). A rule of thumb is that if a food item has a long list of ingredients with many names of chemical compounds or artificial ingredients, it is likely junk food.

Junk food is easy to produce (industrially), tastes good, and typically has a long shelf life without requiring refrigeration. Most often, junk food is ultra-processed, meaning it is made mostly or entirely from substances derived from foods and additives with few or no unprocessed components (Monteiro et al., 2018).

Junk food and health

Junk food is made highly palatable by combining high concentrations of easily digestible fats and sugar. When fats and sugars enter the human digestive system, they trigger separate neural pathways linking to reward areas of the brain. When they are digested simultaneously, both pathways are triggered, producing a very strong rewarding experience (Hedrih, 2024; McDougle et al., 2024). This is the likely mechanism behind the extreme pleasure we feel when we eat chocolate, for example.

When fats and sugars enter the human digestive system, they trigger separate neural pathways linking to reward areas of the brain.

Studies have shown that these experiences also promote overeating and may, in time, dysregulate the brain’s food intake mechanism to control how much food a person eats (Hedrih, 2024). This leads to obesity. In studies on rodents, when researchers want to make animals obese, they feed them food rich in easily digestible fats and sugar (Ikemoto et al., 1996). This is called an obesogenic diet.

Junk food, particularly ultra-processed foods, also tends to contain additives, many of which are added to make the food even more palatable and produce effects similar to those found in addictions (Gearhardt et al., 2023; Hedrih, 2023a). Many studies have linked regular consumption of junk food or its main components, such as refined sugar, with increased risk of various adverse health conditions (Hedrih, 2023b; Huang et al., 2023; Zhang et al., 2024).

Junk food contains additives, many of which are added to make the food even more palatable and produce effects similar to those found in addictions

The current study

Study author Hanieh-Sadat Ejtahed and her colleagues conducted a meta-analytic study to integrate existing scientific findings about the links between junk food consumption and mental health disorders in adults (Ejtahed et al., 2024). They searched multiple databases of scientific publications for studies reporting on this link. The search yielded 17 such studies conducted on data from 159,885 participants.

As studies about junk food often do not use the term junk food, these authors considered a study to be about junk food if it was about one of the following types of foods, beverages, or food/beverage components (see Figure 1):

Sweet drinks: fruit-flavored drinks, sweetened coffee, fruit juice drinks, sugared coffee and tea, energy drinks, cola drinks, beverages, soft drinks, lemonade, and soda.
Sweet snacks: total sugars, added sugars, sweetened desserts, fatty/sweet products, ice cream, chocolate, artificial sweeteners, sweet snacks, dessert, sauces and dressings, candy, patterns of consumption of sweet, high fat and sugary foods, biscuits and pastries, cakes, pie/cookies, and baked goods),
Snacks: Including snacks, sauces/added fats, fast food, fast-food pattern, western diet pattern, snacking and convenience pattern, fried foods, fried potato, crisps, salty snacks, convenience pattern, instant foods), and;
Total junk foods: Different types of junk food are considered together. These were either studies on junk food or studies focusing on multiple categories of junk food.

Figure 1. Junk foods included in Ejtahed et al. (2024)

Junk food consumption is associated with higher mental health symptoms

The results showed that all studies reported at least some associations between mental health symptoms and junk food consumption. However, it sometimes happened that one study found a specific mental health issue to be associated with junk food consumption, but another did not.

Overall, studies indicated that individuals consuming junk food tend to have 15% higher odds of having heightened stress and depression symptoms. Two studies focused on stress showed that individuals consuming junk food had a 31% higher risk of experiencing heightened stress symptoms compared to those not consuming junk food or eating it less.

Results of longitudinal studies, studies that followed groups of participants over time, indicated that individuals consuming junk food regularly have 16% higher odds of developing mental health disorders compared to those who do not eat junk food or eat it less. Frequent consumers of junk food developed depression 30% more often than individuals consuming it less often or not at all (see Figure 2).

Figure 2. Junk food is associated with Depression symptoms

Conclusion

Overall, the study showed that individuals consuming high amounts of junk food regularly tend to have poorer mental health compared to those consuming it less often or not at all. In particular, they were somewhat more likely to develop mental health disorders, have heightened depressive symptoms, and experience stress.

The study showed that individuals consuming high amounts of junk food regularly tend to have poorer mental health compared to those consuming it less often or not at all.

The cause of this association remains insufficiently clear. Studies have identified some possible mechanisms through which junk food could affect mental health. These include neuroinflammation and changes in the body’s functioning that result from obesity. However, it also remains possible that mental health problems make it harder for individuals to maintain a healthy diet, leaving them with the easier and, most often, more accessible option, which is junk food.

Note: Mechanisms through which consumption of junk food influences depression and mental health symptoms can be found in NP 150 Parts I and II.

The paper “Association between junk food consumption and mental health problems in adults: a systematic review and meta-analysis” was authored by Hanieh-Sadat Ejtahed, Parham Mardi, Bahram Hejrani, Fatemeh Sadat Mahdavi, Behnaz Ghoreshi, Kimia Gohari, Motahar Heidari-Beni, and Mostafa Qorbani.

References

Ejtahed, H.-S., Mardi, P., Hejrani, B., Mahdavi, F. S., Ghoreshi, B., Gohari, K., Heidari-Beni, M., & Qorbani, M. (2024). Association between junk food consumption and mental health problems in adults: A systematic review and meta-analysis. BMC Psychiatry, 24(1), 438. https://doi.org/10.1186/s12888-024-05889-8

Gearhardt, A. N., Bueno, N. B., DiFeliceantonio, A. G., Roberto, C. A., Jiménez-Murcia, S., & Fernandez-Aranda, F. (2023). Social, clinical, and policy implications of ultra-processed food addiction. BMJ, e075354. https://doi.org/10.1136/bmj-2023-075354

Hedrih, V. (2023a). 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. (2023b, June 6). Health Consequences of High Sugar Consumption. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/health-consequences-of-high-sugar-consumption/

Hedrih, V. (2024, February 19). Consuming Fat and Sugar (At The Same Time) Promotes Overeating, Study Finds. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/16563-2/

Huang, Y., Chen, Z., Chen, B., Li, J., Yuan, X., Li, J., Wang, W., Dai, T., Chen, H., Wang, Y., Wang, R., Wang, P., Guo, J., Dong, Q., Liu, C., Wei, Q., Cao, D., & Liu, L. (2023). Dietary sugar consumption and health: Umbrella review. BMJ (Clinical Research Ed.), 381, e071609. https://doi.org/10.1136/bmj-2022-071609

Lane, M. M., Gamage, E., Du, S., Ashtree, D. N., McGuinness, A. J., Gauci, S., Baker, P., Lawrence, M., Rebholz, C. M., Srour, B., Touvier, M., Jacka, F. N., O’Neil, A., Segasby, T., & Marx, W. (2024). Ultra-processed food exposure and adverse health outcomes: Umbrella review of epidemiological meta-analyses. BMJ, e077310. https://doi.org/10.1136/bmj-2023-077310

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

Monteiro, C. A., Cannon, G., Moubarac, J.-C., Levy, R. B., Louzada, M. L. C., & Jaime, P. C. (2018). The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutrition, 21(1), 5–17. https://doi.org/10.1017/S1368980017000234

Rajveer, B., & Monika, O. (2012). Junk Food: Impact on health. Journal of Drug Delivery & Therapeutics, 2(3), 67–73.

Zhang, L., Sun, H., Liu, Z., Yang, J., & Liu, Y. (2024). Association between dietary sugar intake and depression in US adults: A cross-sectional study using data from the National Health and Nutrition Examination Survey 2011–2018. BMC Psychiatry, 24(110), 1–10. https://doi.org/10.1186/s12888-024-05531-7

Do Parents and Children Tend to Have Similar Eating Habits?

Posted on March 31, 2025April 4, 2025 by CNP Staff

A U.K. study published in Appetite compared children’s eating patterns to those of their parents
Parents who really enjoyed their food and were prone to emotional overeating had an increased likelihood of having children with similar eating behaviors and a lower likelihood of having children who were fussy eaters
Parents who were fussy eaters, quick to become satiated, and who showed comparatively little enjoyment in food had an increased chance of having children with these characteristics.

When children are very young, they generally eat whatever their caregivers (most often parents) give them. What that is depends on what is available in the area where they live, their parents’ culture, and their personal preferences. For example, a recent study reported that newborns in Taiwan are, on average, breastfed for only 2 months (Chen et al., 2024), switching to various rice-based foods afterward. In contrast, the average breastfeeding duration in Greece is around 4 months (Tavoulari et al., 2016), and the first solid foods given to babies are not based on rice. These differences between families and cultures persist in later years of life as well, creating specific food environments that individuals live in.

Food environments

A food environment is created by the physical, economic, and social conditions that shape people’s access to and choices of food. These include factors such as the availability of grocery stores, farmers’ markets, restaurants, food prices, advertising, and cultural norms. A well-developed food environment with affordable fresh produce and diverse options supports healthy eating, while an environment dominated by processed and fast food can lead to poor nutrition (Cooksey-Stowers et al., 2017; Samuthpongtorn et al., 2023).

An environment dominated by processed and fast food can lead to poor nutrition.

For example, a food desert is an area where people have limited access to fresh and affordable food. These areas can develop due to a lack of grocery stores, but they can also result from logistics difficulties. For example, stores on small remote islands often have canned food only. In contrast, a food swamp is an area where unhealthy food options, such as fast food chains and convenience stores, significantly outnumber healthier alternatives (Cooksey-Stowers et al., 2017). School cafeterias and workplace canteens are also food environments, influencing eating habits through meal options, portion sizes, and nutrition policies.

A food desert is an area where people have limited access to fresh and affordable food.

Understanding food environments is crucial for addressing obesity, food insecurity, and diet-related diseases. For example, a relatively recent study found that food swamps predict obesity rates in the U.S. (Cooksey-Stowers et al., 2017), while living in food deserts was associated with an increased risk of cardiovascular events in individuals with coronary artery disease (Kelli et al., 2019).

Latent eating profiles

People in general have very diverse menus. They tend to eat different things on different days and at different times. Even dietary intake patterns of people with very similar eating habits almost always show some differences. Their food environments differ as well. Because of this, it is not easy to analyze similarities and differences in eating patterns of different individuals in a way that would allow generalizations.

One way to make such analyses is to group eating patterns of individuals into latent eating profiles (Pickard et al., 2024). Latent eating profiles are broad patterns of eating behaviors within a population used to group individuals based on their dietary habits, preferences, or psychological drivers of food consumption. They are typically identified using statistical methods like latent class analysis.

The current study: Intergenerational transmission of eating behaviors

Study author Abigail Pickard and her colleagues wanted to study the intergenerational transmission of eating behaviors (Pickard et al., 2024). For this purpose, they examined associations between the latent eating profiles of a group of children and their parents.

The study participants were 785 parents and primary caregivers from the U.K. who had provided survey data on their 3-6-year-old child’s eating behavior seven months before this study. This time, the study authors asked them to complete an assessment of their own eating behavior patterns (the Adult Eating Behavior Questionnaire) and feeding practices they apply to their children (the Comprehensive Feeding Practices Questionnaire). Study authors paired this with the eating behavior data of participants’ children they already had (see Figure 1).

Figure 1. Study procedure (Pickard et al., 2025).

Eating profiles of parents and children

Study authors analyzed participants’ responses to these eating behavior assessments to organize them into categories, i.e., latent eating profiles. Analysis of children’s responses resulted in 4 categories (latent eating profiles). These were:

Avid Eating – 22% of children – children who enjoy food, are slow to become satiated, and are prone to emotional overeating,
Happy Eating – 18% of children – children who also enjoy food, but are less prone to food fussiness, slow eating, and emotional over- or undereating,
Typical Eating – 44% of children – approximately average proneness to all studied eating behaviors, and
Avoidant Eating – 16% of children – these children are highly prone to food fussiness and emotional undereating, they quickly become satiated, eat slowly, and enjoy food less than the other three groups.

Parents’ and caregivers’ eating profiles were similar with some differences – 41% were in the Typical Eating category, 37% were in the Avid eating profile, and 6% were in the Avoidant eating group. The adults did not have the Happy Eating profile; instead, the 4th adult profile was called Emotional Overeating. 16% of adult participants were in this profile, characterized by the highest proneness to overeating of all four groups, and with lower enjoyment of food than the typical and avid eating profiles (see Figure 2).

Figure 2. Eating profiles of parents and children.

Eating profiles of parents and their children showed similarities

Further analysis revealed that parents in the Avid eating profile and those in the Emotional Overeating profile were more likely to have children in the Avid Eating or Happy Eating Profiles and less likely to have children who were Avoidant eaters. Statistical analysis showed that this association could be partially mediated by proneness to use food to regulate emotions and the shared food environment. In other words, parents who are avid eaters or prone to emotional overeating would use food to regulate emotions. Their children would pick up on this habit and, in turn, also become avid eaters. The situation was similar for Happy Eaters children, but with the food environment, parents and children shared also being a mediator.

Similarly, statistical analysis showed that parents who were in the Avoidant Eating profile had an increased likelihood of having children who were in the Avoidant Eating category as well.

Conclusion

Overall, the study showed that parents who are avid or highly prone to overeating tend to have children who are also avid or happy eaters. It is possible that this link is partly caused by children learning from their parents (who are in these eating categories) to use food for regulating emotions, but also by their shared food environments. Similarly, parents who were avoidant eaters tended to have children who are avoidant eaters.

These findings highlight the importance of home food environments for the transmission of eating behaviors across generations, particularly less favorable ones.

The paper “Associations between parent and child latent eating profiles and the role of parental feeding practices” was authored by Abigail Pickard, Claire Farrow, Emma Haycraft, Moritz Herle, Katie Edwards, Clare Llewellyn, Helen Croker, and Jacqueline Blisset.

References

Chen, C., Shih, P., Su, C., Cheng, C., Lee, M., & Lane, H. (2024). Association between infant feeding and ADHD development in childhood: A birth cohort study in Taiwan. Journal of Child Psychology and Psychiatry, jcpp.14100. https://doi.org/10.1111/jcpp.14100

Cooksey-Stowers, K., Schwartz, M., & Brownell, K. (2017). Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States. International Journal of Environmental Research and Public Health, 14(11), 1366. https://doi.org/10.3390/ijerph14111366

Kelli, H. M., Kim, J. H., Samman Tahhan, A., Liu, C., Ko, Y., Hammadah, M., Sullivan, S., Sandesara, P., Alkhoder, A. A., Choudhary, F. K., Gafeer, M. M., Patel, K., Qadir, S., Lewis, T. T., Vaccarino, V., Sperling, L. S., & Quyyumi, A. A. (2019). Living in Food Deserts and Adverse Cardiovascular Outcomes in Patients With Cardiovascular Disease. Journal of the American Heart Association, 8(4), e010694. https://doi.org/10.1161/JAHA.118.010694

Samuthpongtorn, C., Nguyen, L. H., Okereke, O. I., Wang, D. D., Song, M., Chan, A. T., & Mehta, R. S. (2023). Consumption of Ultraprocessed Food and Risk of Depression. JAMA Network Open, 6(9), e2334770. https://doi.org/10.1001/jamanetworkopen.2023.34770

Tavoulari, E.-F., Benetou, V., Vlastarakos, P. V., Psaltopoulou, T., Chrousos, G., Kreatsas, G., Gryparis, A., & Linos, A. (2016). Factors affecting breastfeeding duration in Greece: What is important? World Journal of Clinical Pediatrics, 5(3), 349–357. https://doi.org/10.5409/wjcp.v5.i3.349

Lifestyle Therapy Is as Effective as Psychotherapy for Mental Health Outcomes and Costs

Posted on March 15, 2025March 27, 2025 by CNP Staff

Lifestyle therapy for depression is gaining attention as an effective alternative to psychotherapy. An experimental study published in the LANCET Regional Health Western Pacific compared the effectiveness of psychotherapy and online videoconferencing lifestyle therapy (focused on diet and exercise)
Results showed that participants’ depression symptoms were reduced to a similar extent in both types of therapy
Lifestyle therapy was cheaper per participant, but there were no differences in the total costs of the two types of therapy

Depression is one of the most common mental health disorders worldwide. It is among the top 25 causes of global disease burden, along with conditions such as cancer, cardiovascular diseases, and others (O’Neil et al., 2024).

What is depression?

Depression is characterized by persistent feelings of sadness, hopelessness, and a loss of interest or pleasure in daily activities. It can affect how a person thinks, feels, and behaves, often leading to physical and emotional problems that interfere with daily functioning. Untreated depression can also lead to suicidal ideas. Individuals with depression are at a more than 20-fold higher risk of suicide compared to the general population (Briley & Lépine, 2011).

Mainstream treatments for depression include psychotherapy and antidepressant drugs. However, in many individuals, these treatments do not result in improvement, leading to a condition called treatment-resistant depression. Estimates state that at least 30% of cases of depression represent treatment-resistant depression (De Carlo et al., 2016; McIntyre et al., 2023). Additionally, up to 15% of patients show only partial improvement (Fava, 2003).

Lifestyle Therapy and new treatments for depression

Because mainstream treatments are limited in effectiveness, scientists are constantly seeking new approaches. Studies have demonstrated certain effects produced by therapies organized around physical exercise, hiking, and sports activities (Kvam et al., 2016; Noetel et al., 2024; Sturm et al., 2012). Researchers have also examined the effectiveness of art therapy, particularly in suicidal patients (Abdulah & Abdulla, 2020).

Novel studies are examining the effectiveness of psychedelic drugs such as MDMA and psilocybin in treating treatment-resistant depression and report very promising results (Barone et al., 2019; Goldberg et al., 2020). Ketamine, a traditionally used general anesthetic substance, also shows promise (Zavaliangos-Petropulu et al., 2023).

One more novel approach to treatment is lifestyle changes. Studies have suggested that certain lifestyle changes might also be beneficial for individuals with depression. This includes the previously mentioned exercises and dietary changes (Araste et al., 2024; Fatahi et al., 2021; Lu et al., 2024). Working with patients to implement these practices in their lives became known as lifestyle therapy.

How Lifestyle Therapy for Depression Compares to Psychotherapy

Study author Adrienne O’Neil and her colleagues wanted to compare the effectiveness of lifestyle therapy delivered via Zoom to cognitive-behavioral therapy for depression (O’Neil et al., 2024). Cognitive-behavioral therapy is currently considered the gold-standard psychotherapy approach for treating depression. These researchers aimed to explore whether lifestyle therapy is less effective than cognitive-behavioral therapy for treating depression or not.

The study participants were 182 adults with depression recruited from a tertiary mental health service in Victoria, Australia. The study authors randomly divided them into two groups. One group underwent lifestyle psychotherapy, while the other completed a set of cognitive behavioral psychotherapy sessions, both delivered via Zoom.

The lifestyle psychotherapy treatment consisted of six 90-minute sessions delivered over eight weeks. A dietitian and an exercise physiologist conducted sessions. They targeted nutrition and physical activity but could integrate alcohol, smoking, substance use, and/or sleep hygiene. Two psychologists delivered the cognitive-behavioral psychotherapy program, which consisted of six group sessions delivered over eight weeks.

The study authors tracked changes in depression symptoms using the Patient Health Questionnaire-9, a tool for assessing depressive symptoms over the preceding two weeks. Participants also completed short clinical interviews and other questionnaires (see Figure 1).

Figure 1. Study Procedure (O’Neil et al., 2024)

Lifestyle therapy was not less effective than cognitive-behavioral psychotherapy

80% of participants who started the treatments completed 3 or more of the 6 sessions. The two groups did not differ in how many participants attended the sessions. Engagement checks showed that participants were “mostly engaged” or “very engaged” around 80% of the time.

Analyses showed that both groups of participants displayed reductions in depressive symptoms after their respective treatments. These reductions were of similar magnitude, indicating that lifestyle therapy was not worse than cognitive-behavioral psychotherapy. Participants who had more severe depression symptoms at baseline tended to report a stronger decrease in symptoms after treatment in both therapy types.

Additionally, lifestyle therapy participants reported improved diet quality and greater self-reported stool consistency. However, they reported fewer improvements in social support compared to psychotherapy participants (see Figure 2).

Figure 2. Lifestyle and cognitive-behavioral psychotherapy findings

Looking at the economic aspect of these two types of treatment, study authors found that the cost of delivering lifestyle therapy was marginally lower for lifestyle therapy (482 AUD ≈ 304 USD) per participant compared to psychotherapy (503 AUD ≈ 317 USD). However, the cost difference disappeared when additional costs of delivering and receiving these therapies were considered.

Conclusion

Overall, the study found that group lifestyle therapy delivered via Zoom is not less effective than cognitive-behavioral therapy of the same length delivered in the same way. When all relevant costs were considered, it was also not more expensive.

Given the increasing burden of depression and that a substantial percentage of individuals with depression remain untreated or without access to psychotherapy, these findings suggest that trained dietitians and exercise physiologists may be well-placed to provide remote mental health care and help alleviate the current burden on mental health services.

The paper “Clinical and cost-effectiveness of remote-delivered, online lifestyle therapy versus psychotherapy for reducing depression: results from the CALM non-inferiority, randomised trial” was authored by Adrienne O’Neil, Joahna Perez, Lauren M. Young, Tayla John, Megan Turner, Dean Saunders, Sophie Mahoney, Marita Bryan, Deborah N. Ashtree, Felice N. Jacka, Courtney Bruscella, Megan Pilon, Mohammadreza Mohebbi, Megan Teychenne, Simon Rosenbaum, Rachelle Opie, Meghan Hockey, Lucija Peric, Samantha De Araugo, Khyati Banker, India Davids, Monica Tembo, Jessica A. Davis, Jerry Lai, Tetyana Rocks, Melissa O’Shea, Niamh L. Mundell, Grace McKeon, Murat Yucel, Pilvikki Absetz, Vincent Versace, Sam Manger, Mark Morgan, Anna Chapman, Craig Bennett, Jane Speight, Michael Berk, Steve Moylan, Lara Radovic, and Mary Lou Chatterton.

References

Abdulah, D. M., & Abdulla, B. M. O. (2020). Suicidal ideation and attempts following a short-term period of art-based intervention: An experimental investigation. The Arts in Psychotherapy, 68, 101648. https://doi.org/10.1016/J.AIP.2020.101648

Araste, A., Moghadam, M. R. S. F., Mohammadhasani, K., Fard, M. V., Khorasanchi, Z., Latifi, M., Hasanzadeh, E., Talkhi, N., Sharifan, P., Asadiyan-Sohan, P., Bidokhti, M. K., Ghassemi, A., Darban, R. A., Ferns, G., & Ghayour-Mobarhan, M. (2024). Adherence to the Nordic diet is associated with anxiety, stress, and depression in recovered COVID-19 patients, a case-control study. BMC Nutrition, 10(1), 38. https://doi.org/10.1186/s40795-024-00845-x

Barone, W., Beck, J., Mitsunaga-Whitten, M., & Perl, P. (2019). Perceived Benefits of MDMA-Assisted Psychotherapy beyond Symptom Reduction: Qualitative Follow-Up Study of a Clinical Trial for Individuals with Treatment-Resistant PTSD. Journal of Psychoactive Drugs, 51(2), 199–208. https://doi.org/10.1080/02791072.2019.1580805

Briley, M. & Lépine. (2011). The increasing burden of depression. Neuropsychiatric Disease and Treatment, 3. https://doi.org/10.2147/NDT.S19617

De Carlo, V., Calati, R., & Serretti, A. (2016). Socio-demographic and clinical predictors of non-response/non-remission in treatment resistant depressed patients: A systematic review. Psychiatry Research, 240, 421–430. https://doi.org/10.1016/j.psychres.2016.04.034

Fatahi, S., Matin, S. S., Sohouli, M. H., Găman, M.-A., Raee, P., Olang, B., Kathirgamathamby, V., Santos, H. O., Guimarães, N. S., & Shidfar, F. (2021). Association of dietary fiber and depression symptom: A systematic review and meta-analysis of observational studies. Complementary Therapies in Medicine, 56, 102621. https://doi.org/10.1016/j.ctim.2020.102621

Fava, M. (2003). Diagnosis and Definition of Treatment-Resistant Depression. Biol Psychiatry, 53, 649–659. https://doi.org/10.1016/S0006-3223(03)00231-2

Goldberg, S. B., Pace, B. T., Nicholas, C. R., Raison, C. L., & Hutson, P. R. (2020). The experimental effects of psilocybin on symptoms of anxiety and depression: A meta-analysis. Psychiatry Research, 284, 112749. https://doi.org/10.1016/j.psychres.2020.112749

Kvam, S., Lykkedrang Kleppe, C., Nordhus, I. H., & Hovland, A. (2016). Exercise as a treatment for depression: A meta-analysis. Journal of Affective Disorders, 202, 67–86. https://doi.org/10.1016/j.jad.2016.03.063

Lu, X., Wu, L., Shao, L., Fan, Y., Pei, Y., Lu, X., Borné, Y., & Ke, C. (2024). Adherence to the EAT-Lancet diet and incident depression and anxiety. Nature Communications, 15(1), 5599. https://doi.org/10.1038/s41467-024-49653-8

McIntyre, R. S., Alsuwaidan, M., Baune, B. T., Berk, M., Demyttenaere, K., Goldberg, J. F., Gorwood, P., Ho, R., Kasper, S., Kennedy, S. H., Ly-Uson, J., Mansur, R. B., McAllister-Williams, R. H., Murrough, J. W., Nemeroff, C. B., Nierenberg, A. A., Rosenblat, J. D., Sanacora, G., Schatzberg, A. F., … Maj, M. (2023). Treatment-resistant depression: Definition, prevalence, detection, management, and investigational interventions. World Psychiatry, 22(3), 394–412. https://doi.org/10.1002/wps.21120

Noetel, M., Sanders, T., Gallardo-Gómez, D., Taylor, P., Del Pozo Cruz, B., Van Den Hoek, D., Smith, J. J., Mahoney, J., Spathis, J., Moresi, M., Pagano, R., Pagano, L., Vasconcellos, R., Arnott, H., Varley, B., Parker, P., Biddle, S., & Lonsdale, C. (2024). Effect of exercise for depression: Systematic review and network meta-analysis of randomised controlled trials. BMJ, e075847. https://doi.org/10.1136/bmj-2023-075847

O’Neil, A., Perez, J., Young, L. M., John, T., Turner, M., Saunders, D., Mahoney, S., Bryan, M., Ashtree, D. N., Jacka, F. N., Bruscella, C., Pilon, M., Mohebbi, M., Teychenne, M., Rosenbaum, S., Opie, R., Hockey, M., Peric, L., De Araugo, S., … Chatterton, M. L. (2024). Clinical and cost-effectiveness of remote-delivered, online lifestyle therapy versus psychotherapy for reducing depression: Results from the CALM non-inferiority, randomised trial. The Lancet Regional Health – Western Pacific, 49, 101142. https://doi.org/10.1016/j.lanwpc.2024.101142

Sturm, J., Plöderl, M., Fartacek, C., Kralovec, K., Neunhäuserer, D., Niederseer, D., Hitzl, W., Niebauer, J., Schiepek, G., & Fartacek, R. (2012). Physical exercise through mountain hiking in high-risk suicide patients. A randomized crossover trial. Acta Psychiatrica Scandinavica, 126(6), 467–475. https://doi.org/10.1111/j.1600-0447.2012.01860.x

Zavaliangos-Petropulu, A., McClintock, S. M., Khalil, J., Joshi, S. H., Taraku, B., Al-Sharif, N. B., Espinoza, R. T., & Narr, K. L. (2023). Neurocognitive effects of subanesthetic serial ketamine infusions in treatment resistant depression. Journal of Affective Disorders, 333, 161–171. https://doi.org/10.1016/j.jad.2023.04.015

Can Positive Emotions Boost Healthy Eating?

Posted on March 3, 2025June 17, 2025 by CNP Staff

Participants of a qualitative study of individuals with metabolic syndrome published in Health Psychology Open indicated that eating healthfully increases their positive emotions and psychological experiences.
It also prevents negative emotions, they reported.
These individuals also believed that positive feelings lead to eating healthfully, creating an upward positive spiral between positive feelings and healthy eating.

In recent years, the number of people with obesity has increased worldwide. This led many authors to speak about an obesity epidemic (e.g., Wong et al., 2022). While people differ in their weight and how much fat their body has, there seems to be a specific point after which the risk of various diseases increases exponentially with further fat accumulation. Represented by body mass index (BMI), the ratio of weight in kilograms, and the square of height in meters, this cutoff point is the BMI value of 30. The World Health Organization declared this BMI the cutoff point for diagnosing obesity (Wilding, 2001). Obesity, paired with several other medical conditions that often co-occur with it, creates what is known as metabolic syndrome.

Obesity, paired with several other medical conditions that often co-occur with it, creates what is known as metabolic syndrome.

What is metabolic syndrome?

Metabolic syndrome is a cluster of conditions that includes obesity, elevated blood pressure, and abnormal cholesterol levels—that together increase the risk of heart disease, stroke, and type 2 diabetes (Carrillo et al., 2022). This syndrome currently affects around 35% of U.S. adults (Hirode & Wong, 2020).

Healthy behaviors, such as following a healthy diet or maintaining a healthy weight, are critical for preventing the progression of chronic diseases. However, most people with metabolic syndrome struggle to follow and maintain a healthy lifestyle. Dietary recommendations for people with metabolic syndrome emphasize the consumption of fruits, vegetables, and lean proteins while avoiding sugar-sweetened beverages and processed and fried foods. In contrast, only 1.7% of people with chronic conditions that could be affected by diet consume high-quality diets, and the share of people without these conditions following such diets is even lower – 1.1% (Chen et al., 2011) (see Figure 1).

Figure 1. Metabolic Syndrome & Dietary Challenges

What makes people follow healthy diets?

Whether a person will eat a healthy diet depends on many factors. For some people, such diets might not be easily available or beyond what they can afford. For others, following a healthy diet would require a drastic lifestyle change and daily routine. In many cases, cultural factors such as traditional cuisine, eating habits, and even gender norms differ from the requirements of a healthy diet. In the context of socializing and celebrations, people also tend to eat more (Carrillo et al., 2022) and even engage in binge eating, i.e., eating large amounts of food in a short period of time.

In the context of socializing and celebrations, people tend to eat more.

In addition to these wider factors, an individual’s current mood also plays a role. Scientists have identified a type of behavior called emotional eating, which occurs when people eat not because their bodies need nutrients but to cope with negative emotions and stress (Dakanalis et al., 2023; Ljubičić et al., 2023). People tend to prefer highly palatable but unhealthy foods when practicing emotional eating.

Emotional eating occurs when people eat not because their bodies need nutrients but to cope with negative emotions and stress.

The current study

Study author Alba Carrillo and her colleagues wanted to expand scientific knowledge about how positive moods and feelings are associated with a healthy diet in adults with metabolic syndrome (Carrillo et al., 2022). They conducted a qualitative study with the expectation that study participants would share their views about links between a healthy diet and positive psychological experiences and be able to talk about emotion-based motivation for healthy eating.

Study participants were primary care patients from academic medical center outpatient clinics who were willing to be contacted about research studies. They were required to be English-speaking adults with at least three metabolic syndrome risk factors and not meet the U.S. physical activity recommendations of moderate to vigorous activity for at least 150 minutes per week.

Ultimately, searching for participants resulted in 21 individuals completing the study interviews. They were mostly older adults with a mean age of 63 years. 62% were female, and all of them were obese.

The principal investigator of the study conducted semi-structured interviews in which study participants reported on their perceptions of health behaviors and diet, various positive psychological constructs (e.g., feelings of gratitude, optimism, etc.), and healthy eating (e.g., “Does healthy eating lead to an increase in PP constructs?”, “Do PP constructs lead to following a healthier diet?”). All interviews were conducted via phone between June and November 2017.

Eating a healthy diet leads to positive psychological experiences

Four main themes emerged from the interviews: (1) eating a healthy diet leads to more positive psychological experiences, (2) positive psychological experiences lead to eating more healthfully, (3) eating a healthy diet prevents negative emotions, (4) healthy behaviors (weight management and exercise) that participants associate with diet can help participants follow a healthy diet (see Figure 2).

Figure 2. Main themes of healthy diet and psychological experience

This indicated that participants believed there was an upward healthy spiral of behaviors where following a healthy diet led to more positive psychological experiences and emotions. These positive experiences, in turn, helped participants follow a healthy diet. When discussing healthy eating, participants noted that they experience what study authors referred to as behavioral bundling. Their lifestyle improvements happened together to allow them to continue to eat in a way that can improve their health.

‘Behavioral bundling’ is when participants’ lifestyle improvements happen together to allow them to continue to eat in a way that could improve their health

Exercising improved participants’ mood, leading to a healthier diet

Some participants noted that the relationship between diet and emotions was mediated or co-occurred with exercise. They reported feeling more positive as a consequence of doing exercises. This, in turn, led them to follow a healthier diet.

“I need to eat better to lose weight’. […] I tend to eat better when I do some form of exercise regularly. I even crave different kinds of food. So, I will crave salads more. I’ll look for a piece of fish and not a piece of steak just from doing the exercise,” one participant said.

Conclusion

Overall, participants in this qualitative study clearly stated that positive emotions and psychological experiences motivated them to follow healthy eating patterns, which in turn made them feel more positive.

This indicates that helping people at high risk of developing chronic diseases recognize and cultivate positive emotions may help them improve their adherence to a healthy diet.

The paper “The role of positive psychological constructs in diet and eating behavior among people with metabolic syndrome: A qualitative study” was authored by Alba Carrillo, Emily H Feig, Lauren E Harnedy, Jeff C Huffman, Elyse R Park, Anne N Thorndike, Sonia Kim, and Rachel A Millstein.

References

Carrillo, A., Feig, E. H., Harnedy, L. E., Huffman, J. C., Park, E. R., Thorndike, A. N., Kim, S., & Millstein, R. A. (2022). The role of positive psychological constructs in diet and eating behavior among people with metabolic syndrome: A qualitative study. Health Psychology Open, 9(1), 20551029211055264. https://doi.org/10.1177/20551029211055264

Chen, X., Cheskin, L. J., Shi, L., & Wang, Y. (2011). Americans with Diet-Related Chronic Diseases Report Higher Diet Quality Than Those without These Diseases12. The Journal of Nutrition, 141(8), 1543–1551. https://doi.org/10.3945/jn.111.140038

Dakanalis, A., Mentzelou, M., Papadopoulou, S. K., Papandreou, D., Spanoudaki, M., Vasios, G. K., Pavlidou, E., Mantzorou, M., & Giaginis, C. (2023). The Association of Emotional Eating with Overweight/Obesity, Depression, Anxiety/Stress, and Dietary Patterns: A Review of the Current Clinical Evidence. Nutrients, 15(5), 1173. https://doi.org/10.3390/nu15051173

Hirode, G., & Wong, R. J. (2020). Trends in the Prevalence of Metabolic Syndrome in the United States, 2011-2016. JAMA, 323(24), 2526–2528. https://doi.org/10.1001/jama.2020.4501

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

Can Weight Loss Reduce Risk-Taking Behaviors?

Posted on February 15, 2025March 4, 2025 by CNP Staff

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/

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

Does Listening to Music You Dislike Make You Feel Hungrier?

Posted on February 1, 2025February 19, 2025 by CNP Staff

An experimental study published in Food Research International found that people become hungrier when they listen to music they dislike
Disliked music evoked more negative emotions as well
In contrast, listening to music they like made participants rate their food as more pleasant and satisfying

We can all probably recall some situations when we were very hungry and how good the food we ate tasted at that time. On the other hand, we were all likely in situations where we did not really feel like eating food we normally like very much. Sometimes, this happens because we have too much of it, while other times, it can happen because we are not in the mood or something else reduces our motivation to eat. Many different factors can temporarily change our taste and motivation related to food (e.g., Brondel et al., 2010; Cummings et al., 2021, 2023). One of them is music.

Many different factors can temporarily change our taste and motivation related to food. One of them is music.

Music and emotions

Music is an art form that combines sounds and silence to create patterns that evoke emotions, tell stories, or express ideas. It can be described in terms of melody, harmony, rhythm, and timbre, but probably the most important thing about music is how it makes us feel. Music serves as a universal language, connecting people and enriching human experiences.

Humans have long known that music can induce emotions. Since ancient times, humans have used music to evoke different types of emotions and to increase group cohesion or coordinate activities. For example, sailors in the 18th and 19th centuries used songs called sea shanties to coordinate their ship-related activities, which often required much coordinated physical effort (e.g., Atkinson, 2016). Since ancient times, people sang songs while doing agricultural work to maintain rhythm and morale and create a feeling of unity, creating a bond between individuals working on a task. Harvest songs, songs people sang during harvests, are particularly well-known (Karanika, 2014).

People also play and listen to music for fun because they enjoy it, when bored, and in many other situations.

Music and food

Many people like to listen to music while they eat, and restaurants and eating places often play music. They can do this to attract customers and make meals and their guests’ overall experience more enjoyable. However, the choice of music can also be a way a restaurant communicates its identity to its customers (e.g., by playing traditional vs. modern music or focusing on a specific music genre).

Studies have shown that music influences consumer behaviors in restaurants. For example, a study found that slow-paced music significantly increased consumer spending at a restaurant compared to fast-tempo music (Caldwell & Hibbert, 2002). This is the reason why expensive restaurants often play slow-paced music. In contrast, fast food places can often be heard playing fast loud music aimed at attracting customers (as the loud music can be heard from afar) but also getting them to pick up their food and leave quickly. Another study found that drinking songs increased the time and money people spent in a bar compared to cartoon songs (Jacob, 2006).

Studies have shown that music influences consumer behaviors in restaurants.

The current study

Study author Phatharachanok Siangphloen and his colleagues wanted to explore how listening to music varying in liking while viewing food can influence hunger levels, liking, and overall satisfaction (Siangphloen et al., 2024). They hypothesized that listening to music one likes would evoke emotions that would influence hunger levels and improve satisfaction with food items. They experimented.

The study participants were 50 young adults. Their average age was 26 years. 33 of them were women. First, each participant compiled a playlist containing 3 songs he/she likes and 3 songs he/she dislikes. After that, they completed three experimental trials in random order. Each trial was on a different day, with a maximum of 7 days between trials.

Trials were organized roughly at lunchtime—between 11:00 a.m. and 3:00 p.m. Participants were instructed to have breakfast in the morning and refrain from eating at least one hour before the start of the experiment. When they arrived at the lab, participants rated their current hunger, fullness, and desire to eat. Next, they were seated in the lab, and the study authors took various electrophysiological measurements of their bodies (heart rate, skin conductance, respiration rate) (see Figure 1).

Figure 1. Study procedure (Siangphloen et al., 2024).

After this, food was served (fried chicken and a cheeseburger, chunky chocolate chip cookies, a chocolate fudge brownie, a fresh chicken salad with tomatoes and cucumber, mandarins, green grapes, and a banana). While participants viewed the food, the electrophysiological measurements were taken again.

After viewing the food, participants selected the emotions they experienced from a checklist. They again rated their hunger, fullness, desire to eat, pleasantness, overall liking of the food, and satisfaction. In one trial, all this happened without any music. In the other trial, participants listened to a playlist of songs they liked, and in one, they listened to songs they disliked.

Participants were hungrier when listening to music they dislike

Participants reported being hungrier (while viewing food) when the music they disliked was playing. There were no differences in hunger ratings between the silent condition (no music) and when the music participants liked was playing.

Listening to music participants liked tended to evoke positive emotions such as relaxation, excitement, and happiness. Viewing food while disliked music was played evoked negative emotions like tiredness, loneliness, terseness, exhaustion, contempt, and others.

Participants rated individual food items lower when disliked music was playing

When participants listened to music they disliked, they rated their liking of the appearance of food and enjoyment as lower compared to the silent condition and when the liked music was playing. Similarly, when listening to music that was disliked, participants’ overall liking of food and food satisfaction were lower as well. In the condition when the disliked condition was playing, healthy food items – a banana, a salad, an orange, and grapes received lower liking ratings. In this condition, participants also rated these items as less satisfying, but they also gave a lower satisfaction rating to the chicken burger (see Figure 2).

Figure 2. Study findings (Siangphloen et al., 2024).

Conclusion

Overall, the study showed that disliked music makes individuals hungrier and affects their liking of food items. When listening to music they liked (and when there was no music), participants liked food more than they did when they disliked music. These findings can be practically applied in real-world food-eating environments to enhance positive emotions during consumption and potentially influence food choices.

The paper “Lunch melodies: Investigating the impact of music on emotions, hunger, liking, and psychophysiology while viewing a lunch meal” was authored by Phatharachanok Siangphloen, Daniel Shepherd, Kevin Kantono, and Nazimah Hamid.

This CNP summary is brought to you by The Center for Nutritional Psychology. Find out more about the Diet-Environment Relationship at www.nutritional-psycyhology.org.

References

Atkinson, D. (2016). An Introduction to English Sea Songs and Shanties. English Folk Dance and Song Society.

Caldwell, C., & Hibbert, S. A. (2002). The influence of music tempo and musical preference on restaurant patrons’ behavior. Psychology & Marketing, 19(11), 895–917. https://doi.org/10.1002/mar.10043

Cummings, J. R., Hoover, L. V., & Gearhardt, A. N. (2023). A randomized experiment of the effects of food advertisements on food-related emotional expectancies in adults. Journal of Health Psychology. https://doi.org/10.1177/13591053231168340

Cummings, J. R., Hoover, V., Turner, M. I., Glozier, K., Zhao, J., & Gearhardt, A. N. (2021). Extending Expectancy Theory to Food Intake: Effect of a Simulated Fast-Food Restaurant on Highly and Minimally Processed Food Expectancies. Clin Psychol Sci, 9(6), 1115–1127. https://doi.org/10.1177/21677026211004582

Jacob, C. (2006). Styles of background music and consumption in a bar: An empirical evaluation. International Journal of Hospitality Management, 25(4), 716–720. https://doi.org/10.1016/j.ijhm.2006.01.002

Karanika, A. (2014). Voices at Work: Women, Performance, and Labor in Ancient Greece. JHU Press.

Siangphloen, P., Shepherd, D., Kantono, K., & Hamid, N. (2024). Lunch melodies: Investigating the impact of music on emotions, hunger, liking, and psychophysiology while viewing a lunch meal. Food Research International, 192, 114825. https://doi.org/10.1016/j.foodres.2024.114825

Can Eating More Dietary Fiber Reduce Suicidal Thoughts?

Posted on January 21, 2025February 6, 2025 by CNP Staff

An analysis of data from the National Health and Nutrition Examination Survey published in the Frontiers in Nutrition found that individuals who eat very little fiber in their diet are more likely to think about suicide.
For every additional daily 1 gram of fiber per 1000 kcal of food, the risk that a person will be thinking about suicide decreased by 5%.
After dietary fiber intake reached 7.8 grams per 1000 kilocalories of food per day, further increase in fiber consumption was not associated with the risk of thinking about suicide

Editor’s Note: This article presents the results of a scientific study published in a scientific journal. It does not constitute medical advice. The presented results are correlational in nature, and they should not be interpreted as cause-and-consequence relations. The origin of the reported association is unclear. It is possible that intentionally eating more dietary fiber would not affect suicidal ideation. Dietary fiber intake or diet in general is not a replacement for appropriate medical treatment.

The desire to survive and preserve one’s own life is one of every individual’s most powerful instincts. It is deeply rooted in both biological and psychological processes developing in our bodies. This instinct, called self-preservation instinct, is what makes us prioritize the pursuit of basic needs such as food, water, shelter, or safety. It operates through our body’s stress response, the response that prepares us to flee, fight, or freeze in response to threats (Corr, 2004; Russell & Lightman, 2019), but also through our desire to avoid pain and reactions to situations that cause fear.

The self-preservation instinct makes us prioritize basic needs such as food, water, shelter, or safety and operates through our body’s stress response.

Suicide

In spite of this, more than 700,000 people worldwide intentionally end their own lives every year (Huang et al., 2024). They commit suicide. Many do it due to overwhelming emotional pain, feelings of hopelessness, or because they believe that their situation cannot improve. These feelings become so strong in these individuals that they overwhelm the self-preservation instinct.

Mental health conditions contribute significantly to the risk of suicide. Estimates state that the risk of suicide is 5-8% for individuals suffering from depression, alcoholism, or schizophrenia (Brådvik, 2018). Social factors, like isolation, financial stress, or abuse, can amplify the feelings leading to suicide. In some cases, impulsive decisions during a moment of intense distress lead to suicide.

Suicidal ideation – thinking about suicide

Committing suicide is generally not easy. Aside from the self-preservation instinct, humans design their environments and societies to preserve human well-being and prevent harm. Before committing suicide, individuals first start thinking intensely about it. This is called suicidal ideation.

It usually starts with an occasional thought of death or an imagination of life ending without any plans to act on it. As distress deepens, a person might actively start contemplating the idea of suicide. Further down the line, one might start forming a plan, deciding on the method, time, and place. In the final stage, the person will start gathering the means to commit suicide and take preparatory steps, ultimately leading to making an attempt on one’s own life. This process is described by what is now called a three-step theory of suicide (Klonsky & May, 2015).

The current study

Study author Huaying Huang and her colleagues noted that dietary interventions have shown great potential for preventing and treating affective disorders (Huang et al., 2024). This includes regulating dietary fiber intake. A recent meta-analysis showed that an increase of 1 gram in dietary fiber intake (per day) reduces the risk of depression by 24% (Fatahi et al., 2021). These authors hypothesized that dietary fiber intake might also be associated with suicidal ideation (thinking about suicide). They analyzed data from the National Health and Nutrition Examination Survey to explore this.

What is dietary fiber?

Dietary fiber is a type of carbohydrate found in plant-based foods that the body cannot digest. Although the body cannot digest it, dietary fiber serves as a food source for beneficial bacteria living in our guts. The availability of fiber helps these bacteria grow and maintain activity levels. In turn, the activity of these bacteria produces substances that interact with our body, reducing inflammation, strengthening the gut wall lining, and providing other health benefits (Takiishi et al., 2017) (see Figure 1).

Figure 1: Role of Dietary Fiber in Gut Health

Dietary fiber serves as a food source for beneficial bacteria living in our guts. These bacteria produce substances that interact with our body, reducing inflammation, strengthening the gut wall lining, and providing other health benefits.

The National Health and Nutrition Examination Survey

The National Health and Nutrition Examination Survey is a complex study program aiming to evaluate the health and nutritional condition of non-institutionalized residents of the United States. The program selects a nationally representative sample of 5000 individuals every year.

Participants of this study program complete health interviews and undergo physiological examinations. The program collects data on their demographics, socioeconomic situation, dietary habits, health, physical characteristics, and laboratory tests.

This analysis used data from 21,865 participants about dietary fiber intake, obtained through two dietary interviews asking participants to list foods and beverages they consumed in the previous 24 hours. Dietary fiber intake data used in the analysis was the average of quantities participants reported in the two interviews. Data about suicidal ideation came from answers to item nine of the Patient Health Questionnaire (PHQ-9) – “Over the last two weeks, how often have you felt that you would be better off dead or hurting yourself in some way?”. Participants’ average age was 47 years. 51% of them were females (see Figure 2).

Figure 2. Study Procedure (Huang et al., 2024).

Higher dietary fiber intake was associated with lower suicidal ideation

Results showed that 781 participants, or 3.6%, thought about suicide (i.e., had suicidal ideation). Individuals with suicidal ideation were more likely to be Hispanics, living alone, and smokers. They tended to have lower education, came from poorer families, and had lower dietary intake of unsaturated fatty acids and sodium.

The average dietary fiber intake was 7.8 grams per 1000 kilocalories of food. Individuals with higher dietary fiber intake were less likely to be thinking about suicide. However, this relationship was more complex. With each additional 1 gram of fiber per 1000 kilocalories of food (per day), the risk that a person will have suicidal ideation dropped by 5%. However, the association between higher dietary fiber intake and decreased risk of suicidal ideation was only present among individuals consuming less than 7.8 grams of fiber per 1000 kilocalories of food. Among individuals consuming more than 7.8 grams of fiber per 1000 kilocalories of food per day, fiber intake was not associated with suicidal ideation (see Figure 3).

Figure 3. Study Findings (Huang et al., 2024)

Conclusion

The study found that individuals consuming little dietary fiber were at an increased risk of suicidal ideation. Among those consuming average or above-average quantities of fiber, this association was not present. While the cause of this association remains unknown, these findings open a possibility that the risk of suicide in the general population could potentially be reduced through dietary interventions and policies.

The paper “Association between dietary fiber intake and suicidal ideation: a cross-sectional survey” was authored by Huaying Huang, Jianjiong Fu, Keyu Lu, Yaming Fu, Pan Zhuge, and Yu Yao.

References

Brådvik, L. (2018). Suicide Risk and Mental Disorders. International Journal of Environmental Research and Public Health, 15(9), 2028. https://doi.org/10.3390/ijerph15092028

Corr, P. J. (2004). Reinforcement sensitivity theory and personality. Neuroscience & Biobehavioral Reviews, 28(3), 317–332. https://doi.org/10.1016/j.neubiorev.2004.01.005

Huang, H., Fu, J., Lu, K., Fu, Y., Zhuge, P., & Yao, Y. (2024). Association between dietary fiber intake and suicidal ideation: A cross-sectional survey. Frontiers in Nutrition, 11, 1465736. https://doi.org/10.3389/fnut.2024.1465736

Klonsky, E. D., & May, A. M. (2015). The Three-Step Theory (3ST): A New Theory of Suicide Rooted in the “Ideation-to-Action” Framework. International Journal of Cognitive Therapy, 8(2), 114–129. https://doi.org/10.1521/ijct.2015.8.2.114

Russell, G., & Lightman, S. (2019). The human stress response. Nature Reviews Endocrinology, 15(9), 525–534. https://doi.org/10.1038/s41574-019-0228-0

Takiishi, T., Fenero, C. I. M., & Câmara, N. O. S. (2017). Intestinal barrier and gut microbiota: Shaping our immune responses throughout life. Tissue Barriers, 5(4), e1373208. https://doi.org/10.1080/21688370.2017.1373208

Gut Microbiota Regulates the Diet-Anxiety Relationship

Posted on January 7, 2025January 9, 2025 by CNP Staff

A new conceptual paper published in Frontiers in Nutrition examined the relationship between gut microbiota, diet, and anxiety
It suggests that gut microbiota mediate the relationship between dietary intake and anxiety
The paper also critically examined research methodologies employed in the nutritional field to investigate the interactions between diet and anxiety

Many of us have experienced situations where we’re under stress and feel some kind of strong negative emotions. We roam around thinking about what we can do about these intense emotions. Then, we might decide to eat something. Or, after experiencing stress about some aspect of our relationship with others or something we can’t resolve, we may suddenly feel the need to eat. This is called stress-induced eating. It’s an example of emotional eating, a behavior where we eat not because our body needs nutrients but because food intake would make us feel better (Konttinen, 2020; Zeeck et al., 2011).

Stress-induced eating involves eating not because our body needs nutrients but because eating makes us feel better emotionally.

What is anxiety?

Anxiety is an emotion we experience when we anticipate danger, but that danger has not yet materialized. In such a situation, we experience a sense of uncertainty as we prepare for what might happen, even if the threat is not immediate or we aren’t even sure what the nature of the threat might be. Sometimes, the threat might not even (objectively) exist. As such, anxiety is different from fear, the emotion we experience when we are faced with a clearly identified threat (Perkins et al., 2007).

The term anxiety is also used to describe a personality trait, one that makes an individual prone to experiencing anxiety. The author of the famous Reinforcement Sensitivity Theory of Personality, Jeffrey Gray, described this trait of anxiety as representing sensitivity to punishment (Pickering et al., 1995), characterizing individuals who react strongly to signals indicating that they might be punished (punishment sensitivity). The opposite pole of this trait is occupied by individuals whose reactions are stronger to signals indicating that they might receive a reward (reward sensitivity).

The term anxiety is also used to describe a personality trait, one that makes an individual prone to experiencing anxiety.

There are also clinical conditions related to experiencing anxiety called anxiety disorders. These are mental health conditions characterized by excessive and persistent feelings of worry and anxiety that are disproportionate to the actual situation and interfere with daily functioning. There are various types of anxiety disorders, including generalized anxiety disorder, panic disorder, and different phobias, each with distinct symptoms and triggers.

Anxiety disorders are one of the most prevalent types of mental health disorders, affecting up to 34% of the population. Females are affected twice as often as men. The prevalence of anxiety disorders seems to have markedly increased during the 2021-2022 COVID-19 pandemic (Basso et al., 2024)

Anxiety disorders are one of the most prevalent types of mental health disorders, affecting up to 34% of the population.

The current study

Having in mind this very high prevalence of anxiety disorders, study author Melissa Basso and her colleagues wanted to help integrate the available evidence between anxiety and diet (Basso et al., 2024). Several previous studies explored the associations between dietary intake and anxiety. These authors compiled a list of 50 such studies. The studies in the list explored the association between anxiety and specific nutrients, foods, dietary patterns, and dietary quality indices, very often reporting that specific aspects of dietary intake are associated with anxiety.

The enteric nervous system (ENS) is the part of the autonomic nervous system that governs the activities of the gastrointestinal tract independently
of the brain and the spinal cord.

Diet, anxiety, and gut microbiota

Study authors note that there is a cyclical feedback loop between emotions, including anxiety, and behavioral responses that can be reinforced by dietary content. On the one hand, food components can act on the brain and mental health by modulating brain chemistry.

There is a cyclical feedback loop between emotions, including anxiety, and behavioral responses that can be reinforced by dietary content.

This can also happen through various mechanisms that depend on the activity of the gut microbiome. These include the modulation of the autonomic and enteric nervous system (the part of the autonomic nervous system that governs the activities of the gastrointestinal tract independently of the brain and the spinal cord), the modulation of the mechanism that controls the release of hormones by gut cells (enteroendocrine signaling) and the one controlling the stress response (the hypothalamic-pituitary-adrenal (HPA) axis signaling). Potential mechanisms also include changes in the production of bacterial by-products, such as short-chain fatty acids, systemic and low-grade inflammation, and damage to the intestinal mucosal barrier, which would, in turn, change the composition of the gut microbiota (see Figure 1).

Figure 1. Mechanisms of the diet-anxiety relationship

Short-chain fatty acids produced by gut bacteria are particularly important as they promote the integrity of the intestinal barrier and support the health of the gut lining cells. However, these molecules also influence the activity of immune cells, reducing systemic inflammation. They can affect glucose metabolism and even impact the production of neurotransmitters in the brain.

Short-chain fatty acids influence the activity of immune cells, reducing systemic inflammation. They can affect glucose metabolism and even
impact the production of neurotransmitters in the brain.

On the other hand, anxiety promotes unhealthy eating habits through stimulating emotional eating behavior. While engaged in emotional eating, individuals tend to choose unhealthy products, often rich in sugars, trans-fatty acids, and various additives.

High sugar intake, in turn, activates a system in the brain involved in reward processing, motivation, and emotion regulation (the mesocorticolimbic system) in a way that is similar to what happens in substance abuse/addiction. In this way, high sugar consumption creates changes in brain function that alter emotional states (Jacques et al., 2019) (see Figure 2).

Figure 2. High sugar intake and emotional states

Trans-fatty acids (also known as artificial trans fats or industrial trans fats) contribute to low-grade chronic inflammation and gut flora alteration, changes found to increase anxiety in rats.

High sugar intake activates a system in the brain involved in reward processing, motivation, and emotion regulation in a way that is similar
to what happens in substance abuse and addiction.

Furthermore, stress, which accompanies anxiety, can cause alterations to the gut microbiome composition but also act on the integrity of the blood-brain barrier and the intestinal barrier, making it easier for molecules produced by gut microbiota to reach and affect the brain. All these mechanisms can create a feedback loop that maintains both increased anxiety and unhealthy dietary patterns associated with it, making treatment of anxiety difficult.

These authors also note that studies indicate that the intake of certain bacterial cultures in probiotics might affect anxiety, but the studies still yield mixed results.

Conclusion

Overall, reviewing the existing evidence, the authors of this paper argue that gut microbiota mediates the link between diet and anxiety in both directions. They propose a new theoretical model of this relationship listing different mechanisms through which diet-gut microbiota-anxiety influences are achieved.

Gut microbiota mediates the link between diet and anxiety in both directions.

Studies of the interactions between diet, gut microbiota, and the brain are still in their infancy. Still, they do hold promise that a new avenue for treating anxiety and other mental health disorders by influencing gut microbiota might open in the future. This is a very positive development given the less-than-perfect record of existing treatments.

Learn more about the relationship between the microbiome and psychology in CNP’s Continuing Education courses.

The paper “Diet quality and anxiety: a critical overview with focus on the gut microbiome” was authored by Melissa Basso, Irene Zorzan, Nicola Johnstone, Matteo Barberis, and Kathrin Cohen Kadosh.

References

Basso, M., Zorzan, I., Johnstone, N., Barberis, M., & Cohen Kadosh, K. (2024). Diet quality and anxiety: A critical overview with focus on the gut microbiome. Frontiers in Nutrition, 11, 1346483. https://doi.org/10.3389/fnut.2024.1346483

Jacques, A., Chaaya, N., Beecher, K., Ali, S. A., Belmer, A., & Bartlett, S. (2019). The impact of sugar consumption on stress driven, emotional and addictive behaviors. Neuroscience & Biobehavioral Reviews, 103, 178–199. https://doi.org/10.1016/j.neubiorev.2019.05.021

Konttinen, H. (2020). Emotional eating and obesity in adults: The role of depression, sleep and genes. Proceedings of the Nutrition Society, 79(3), 283–289. https://doi.org/10.1017/S0029665120000166

Perkins, A. M., Kemp, S. E., & Corr, P. J. (2007). Fear and anxiety as separable emotions: An investigation of the revised reinforcement sensitivity theory of personality. Emotion, 7(2), 252–261. https://doi.org/10.1037/1528-3542.7.2.252

Pickering, A. D., Díaz, A., & Gray, J. A. (1995). Personality and reinforcement: An exploration using a maze-learning task. Personality and Individual Differences, 18(4), 541–558. https://doi.org/10.1016/0191-8869(94)00182-R

The Center for Nutritional Psychology. (2024). Encyclopedia of Nutritional Psychology. https://www.nutritional-psychology.org/encyclopedia/anxiety/

Zeeck, A., Stelzer, N., Linster, H. W., Joos, A., & Hartmann, A. (2011). Emotion and eating in binge eating disorder and obesity. European Eating Disorders Review, 19(5), 426–437. https://doi.org/10.1002/erv.1066

The EAT-Lancet Diet Helps Lower Depression and Anxiety Risk?

Posted on November 30, 2024December 9, 2024 by CNP Staff

An analysis of UK Biobank data published in Nature Communications showed that individuals adhering to the EAT-Lancet diet have a lower risk of depression and anxiety.
The group with the highest adherence to this diet had around 20% lower risk of depression and anxiety compared to the lowest adherence group.
The EAT-Lancet diet emphasizes plant-based foods, moderate animal product consumption, and limited processed and red meat intake.

We can often read that eating certain foods might be good for our health. Studies frequently report that heightened or decreased intake of a certain type of food is associated with increased or reduced risk of certain diseases. For example, regular consumption of refined sugars, particularly sugary drinks, has been linked to a host of adverse health outcomes (Hedrih, 2023; Huang et al., 2023). On the other hand, snacking on whole almonds has been found to reduce LDL cholesterol and improve endothelial function (Dikariyanto et al., 2020) and was, therefore, beneficial for overall health.

These findings refer to individual foods or food components. However, scientists also study the effects of broad dietary patterns on health and overall well-being.

Regular consumption of refined sugars has been linked to a host of adverse health outcomes.

Dietary patterns

A dietary pattern is the overall composition and combination of foods and beverages one consumes over time. It’s not just about individual nutrients but the synergistic effects of various foods in a person’s diet. Examples of dietary patterns include the Mediterranean diet, which emphasizes whole grains, vegetables, and healthy fats, and the MIND diet, which focuses on brain health. These patterns define an individual’s long-term eating habits. Scientists have defined certain broad dietary patterns that individuals’ diets can be compared to for research purposes. These diets reflect the general dietary habits of certain groups and cultures or are created by scientists to improve health or research a certain topic.

For example, many studies explore the associations between the Western diet and health, finding that adherence to this diet is linked to various adverse health outcomes. The Western diet is characterized by a high intake of processed foods, red and processed meats, refined grains, sugars, and unhealthy fats (Hayes et al., 2024). On the other hand, studies link adherence to the Mediterranean diet and the Nordic diet with beneficial health outcomes (Adamsson et al., 2012; Araste et al., 2024; Camprodon-Boadas et al., 2024; Poulsen et al., 2014; The InterAct Consortium, 2011).

A dietary pattern is the overall combination and frequency of foods and beverages a person consumes regularly.

The EAT-Lancet diet

In January 2019, the EAT-Lancet Commission, a group of scientists and experts, developed recommendations for a sustainable and healthy diet that can support human health and environmental stability. The Commission based its diet on the best available evidence for what constitutes a healthy diet and considered food production sustainability. Their recommendations were published in the Lancet, one of the leading scientific journals in the world (Willett et al., 2019).

The EAT-Lancet diet is largely plant-based. It consists of whole grains, fruits, vegetables, nuts, legumes, unsaturated oils, low to moderate amounts of seafood and poultry, and no or low red meat, processed meat, added sugar, refined grains, and starchy vegetables. Adherence to this diet would represent a substantial dietary shift for most people. Adopting worldwide would require the global consumption of healthy foods to double, halving the consumption of less nutritious foods (Dalile et al., 2022).

The current study

Study author Xujia Lu and her colleagues wanted to explore how adherence to the EAT-Lancet diet might be associated with anxiety and depression among UK adults (Lu et al., 2024). They analyzed data from the UK Biobank, a large-scale biomedical database and research resource containing health and genetic information from half a million U.K. participants. This database is available for scientific purposes to researchers worldwide.

This study used data from 180,466 participants. At the start of the study, their average age was 56 years, and 46% were male.

These participants completed a dietary questionnaire called Oxford WebQ. This questionnaire asks participants to recall their food and drink intake in the previous 24 hours. Some participants completed it when they were included in the UK Biobank group, and all participants received invitations to complete it on multiple occasions.

Study authors used these data to calculate how much participants’ diets resembled the EAT-Lancet diet (i.e., how much participants adhered to it). There is currently no consensus about the right way to calculate adherence to the EAT-Lancet diet, so the study authors created several different scores to express this adherence. Data about depression and anxiety came from participants’ reports, hospital data, and the death registry records.

Individuals adhering to the EAT-Lancet diet were less likely to suffer from depression and anxiety

During the follow-up of around 11-12 years on average, 4548 cases of depression, 6026 cases of anxiety, and 1262 individuals with both depression and anxiety were identified.

Depending on the way adherence to the EAT-Lancet diet was calculated, participants with the strongest adherence to the EAT-Lancet diet had between 16% and 26% lower risk of developing depression or anxiety disorders compared to those with the lowest adherence to the EAT-Lancet diet. The risk reduction was the strongest for the co-occurrence of depression and anxiety, i.e., for suffering from both depression and anxiety at the same time (see Figure 1).

Figure 1. Study procedure and findings (Lu et al., 2024)

Participants with the strongest adherence to the EAT-Lancet diet had between 16% and 26% lower risk of developing depression or anxiety disorders.

Participants with higher adherence to the EAT-Lancet diet were more likely to be women, slightly older, nonsmokers, more physically active, and have lower body mass index and total energy intake.

Conclusion

Overall, the study suggests that higher adherence to the EAT-Lancet diet is associated with lower risks of depression, anxiety, and co-occurrence. Individuals adhering to this diet also tended to have healthier lifestyle habits.

The design of this study does not allow any cause-and-effect conclusions to be derived from the results. Because of this, we do not know whether this dietary pattern itself reduces the risk of anxiety and depression. It is also possible that factors producing the lowered risk of depression and anxiety make individuals more likely to adhere to a healthy diet. Still, it is possible that promoting the dietary pattern described by the EAT-Lancet diet might help prevent depression and anxiety.

The paper “Adherence to the EAT-Lancet diet and incident depression and anxiety” was authored by Xujia Lu, Luying Wu, Liping Shao, Yulong Fan, Yalong Pei, Xinmei Lu, Yan Borné, and Chaofu Ke.

References

Adamsson, V., Reumark, A., Cederholm, T., Vessby, B., Risérus, U., & Johansson, G. (2012). What is a healthy Nordic diet? Foods and nutrients in the NORDIET study. Food & Nutrition Research, 56(1), 18189. https://doi.org/10.3402/fnr.v56i0.18189

Camprodon-Boadas, P., Gil-Dominguez, A., De La Serna, E., Sugranyes, G., Lázaro, I., & Baeza, I. (2024). Mediterranean Diet and Mental Health in Children and Adolescents: A Systematic Review. Nutrition Reviews, nuae053. https://doi.org/10.1093/nutrit/nuae053

Dalile, B., Kim, C., Challinor, A., Geurts, L., Gibney, E. R., Galdos, M. V., Fata, G. L., Layé, S., Mathers, J. C., Vauzour, D., Verkuyl, J. M., & Thuret, S. (2022). The EAT–Lancet references diet and cognitive function across the life course. The Lancet Planetary Health, 6(9), e749–e759. https://doi.org/10.1016/S2542-5196(22)00123-1

Dikariyanto, V., Smith, L., Francis, L., Robertson, M., Kusaslan, E., O’Callaghan-Latham, M., Palanche, C., D’Annibale, M., Christodoulou, D., Basty, N., Whitcher, B., Shuaib, H., Charles-Edwards, G., Chowienczyk, P. J., Ellis, P. R., Berry, S. E. E., & Hall, W. L. (2020). Snacking on whole almonds for 6 weeks improves endothelial function and lowers LDL cholesterol but does not affect liver fat and other cardiometabolic risk factors in healthy adults: The ATTIS study, a randomized controlled trial. The American Journal of Clinical Nutrition, 111(6), 1178–1189. https://doi.org/10.1093/AJCN/NQAA100

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When fats and sugars enter the human digestive system, they trigger separate neural pathways linking to reward areas of the brain.

Junk food contains additives, many of which are added to make the food even more palatable and produce effects similar to those found in addictions

The study showed that individuals consuming high amounts of junk food regularly tend to have poorer mental health compared to those consuming it less often or not at all.

Food environments

Latent eating profiles

The current study: Intergenerational transmission of eating behaviors

Eating profiles of parents and children

Eating profiles of parents and their children showed similarities

Conclusion

References

Obesity, paired with several other medical conditions that often co-occur with it, creates what is known as metabolic syndrome.

In the context of socializing and celebrations, people tend to eat more.

Emotional eating occurs when people eat not because their bodies need nutrients but to cope with negative emotions and stress.

‘Behavioral bundling’ is when participants’ lifestyle improvements happen together to allow them to continue to eat in a way that could improve their health

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

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

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

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

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.

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.

Many different factors can temporarily change our taste and motivation related to food. One of them is music.

Studies have shown that music influences consumer behaviors in restaurants.

The self-preservation instinct makes us prioritize basic needs such as food, water, shelter, or safety and operates through our body’s stress response.

Dietary fiber serves as a food source for beneficial bacteria living in our guts. These bacteria produce substances that interact with our body, reducing inflammation, strengthening the gut wall lining, and providing other health benefits.

Stress-induced eating involves eating not because our body needs nutrients but because eating makes us feel better emotionally.

The term anxiety is also used to describe a personality trait, one that makes an individual prone to experiencing anxiety.

Anxiety disorders are one of the most prevalent types of mental health disorders, affecting up to 34% of the population.

The enteric nervous system (ENS) is the part of the autonomic nervous system that governs the activities of the gastrointestinal tract independently of the brain and the spinal cord.

There is a cyclical feedback loop between emotions, including anxiety, and behavioral responses that can be reinforced by dietary content.

Short-chain fatty acids influence the activity of immune cells, reducing systemic inflammation. They can affect glucose metabolism and even impact the production of neurotransmitters in the brain.

High sugar intake activates a system in the brain involved in reward processing, motivation, and emotion regulation in a way that is similar to what happens in substance abuse and addiction.

Gut microbiota mediates the link between diet and anxiety in both directions.

Regular consumption of refined sugars has been linked to a host of adverse health outcomes.

A dietary pattern is the overall combination and frequency of foods and beverages a person consumes regularly.

Participants with the strongest adherence to the EAT-Lancet diet had between 16% and 26% lower risk of developing depression or anxiety disorders.

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The enteric nervous system (ENS) is the part of the autonomic nervous system that governs the activities of the gastrointestinal tract independently
of the brain and the spinal cord.

Short-chain fatty acids influence the activity of immune cells, reducing systemic inflammation. They can affect glucose metabolism and even
impact the production of neurotransmitters in the brain.

High sugar intake activates a system in the brain involved in reward processing, motivation, and emotion regulation in a way that is similar
to what happens in substance abuse and addiction.