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Can Broccoli Sprouts Alleviate Symptoms of Bowel Inflammation?

Posted on January 15, 2024January 17, 2024 by CNP Staff

A study published in mSystems found that feeding mice a diet consisting of 10% steamed broccoli sprouts alleviated the symptoms of experimentally induced bowel inflammation
These mice gained more weight during the study period
The mice showed lower inflammation indicators and richer bacterial communities in all parts of the gut compared to mice with induced bowel inflammation but on a regular diet

Inflammatory bowel diseases

Inflammatory bowel diseases constitute a group of chronic, inflammatory disorders primarily affecting the gastrointestinal tract. The two main types of these diseases are Crohn’s and ulcerative colitis. Both conditions arise from an abnormal immune response in which the immune system mistakenly attacks healthy cells lining the digestive tract, leading to chronic inflammation (see Figure 1).

Figure 1. Two main inflammatory bowel diseases

Symptoms of inflammatory bowel diseases can include abdominal pain, diarrhea, weight loss, fatigue, and sometimes rectal bleeding. These diseases are complex conditions usually caused by multiple factors. Genetic predisposition, environmental factors, and immune system dysregulation play a role in their development (Ramos & Papadakis, 2019). While there is currently no cure for inflammatory bowel diseases, various treatments such as medications, dietary modifications, and, in some cases, surgery can help manage symptoms and improve the quality of life for individuals suffering from them (Holman et al., 2023).

Could inflammatory bowel disease symptoms be improved through diet?

Studies indicate that between 0.3% and 0.5% of people in Europe and North America suffer from inflammatory bowel diseases (Ng et al., 2017). While these percentages might seem small, they represent millions of individuals worldwide. Considering that these diseases’ symptoms are often devastating, it is quite understandable that finding ways to treat inflammatory bowel diseases has attracted much research attention.

A significant portion of this research focused on identifying dietary elements that could alleviate the symptoms of these diseases because changing a diet is considered an easy way to address symptoms if a viable dietary approach existed. In this regard, cruciferous vegetables are seen as a promising avenue of research, as their consumption is associated with reduced inflammation and a lower risk of cancer (Holman et al., 2023; Tilg, 2015). Some common cruciferous vegetables include broccoli, cauliflower, cabbage, Brussels sprouts, kale, and collard greens.

Broccoli sprouts

Broccoli sprouts are young, edible shoots that grow from germinated broccoli seeds. They are known for their high nutritional value, particularly for being rich in glucosinolates –compounds that can be converted into bioactive substances with potential health benefits, including antioxidant and anti-inflammatory properties. The presence of glucosinolates is particularly high in immature broccoli sprouts.

One of these bioactive substances is sulforaphane. Studies have shown that sulforaphane inhibits the action of certain immune factors responsible for the upregulation of proinflammatory proteins in the body, known as cytokines.

However, when broccoli is eaten raw, enzymes in it will convert most glucosinolates into an inactive substance. Steaming or cooking fresh broccoli sprouts alters these plant enzymes’ activity and leaves glucosinolates intact. This allows a specific type of gut bacteria to convert glucosinolates into sulforaphane (Holman et al., 2023) (see Figure 2).

Figure 2. Broccoli sprout properties

The current study

Study author Johanna M. Holman and her colleagues aimed to investigate whether adding steamed broccoli sprouts to mice’s diets could improve chronic, relapsing colitis symptoms. Simultaneously, they wanted to see how these sprouts affect gut microbiota composition under the same conditions.

Gut microbiota, also known as gut flora or gut microbiome, is the diverse community of microorganisms, including bacteria, viruses, fungi, and archaea, that inhabit the gastrointestinal tract of humans and other animals. They play a crucial role in digestion and metabolism, being also involved in several other bodily functions (Carbia et al., 2023; Leclercq et al., 2020).

The procedure

The study was conducted on 40 mice divided into 2×2 groups. Researchers fed one group of mice a regular diet while adding steamed broccoli sprouts to the other group’s diet. Researchers chemically induced bowel inflammation (colitis) in one-half of the mice from each group, while the other half did not undergo this induction. In that way, there were four groups, with ten mice in each – the group fed a regular diet with induced colitis, the group fed a regular diet without induced colitis, the group fed a diet with broccoli sprouts without induced colitis, and the group fed a diet with broccoli sprouts with induced colitis. The study started when the mice were seven weeks old and continued for 34 days.

Researchers prepared the broccoli sprouts for 10 minutes in a double boiler. They then cooled the steamed broccoli sprouts down and stored them in a -80oC freezer until they freeze-dried. Researchers then ground the freeze-dried broccoli sprouts into a fine powder and added the powder to the regular mice food, constituting 10% of the food by weight (see Figure 3.1).

Figure 3.1. Study Procedure (Part I)

Dextran sodium sulfate (DSS) in water

The study authors added dextran sodium sulfate (DSS) to the water two groups (group I & group 3) of mice drank to induce colitis. When consumed, dextran sodium sulfate disrupts the expression of certain proteins in the cells lining the intestines. This disruption causes the cells lining the intestine walls to become permeable, leading to a leaky barrier. The leakiness of this barrier triggers a host of events that result in inflammation and symptoms similar to colitis in humans.

Researchers started putting dextran sodium sulfate in the water the mice drank starting from the 7th day of the study. Its concentration in water was 2.5%. They gave mice water with dextran sodium sulfate for five days. This was followed by a recovery period of 5-7 days (no dextran sodium sulfate in water), after which they repeated the procedure. There were three cycles during which water with dextran sodium sulfate was given to mice (Figure 3.2).

Figure 3.2. Study procedure Part II (Dextran sodium sulfate consumption cycles)

Assessments

The study authors assessed the severity of symptoms caused by the treatment through a combination of factors, including the mice’s body weight, fecal consistency, and the presence of blood in feces. They collected fecal samples of these mice every 2-3 days and every day during periods when mice drank water with dextran sodium sulfate.

After the study period, mice were euthanized, and researchers studied gut microbiota contents in various places in mice’s digestive tracts using genetic techniques. They also determined various inflammation indicators (cytokines) levels from their blood (see Figure 4).

Figure 4. Research Assessment

Broccoli sprouts alleviated the symptoms of colitis

Results showed that, during the study period, mice with induced colitis who ate a diet with broccoli sprouts gained more weight than mice with induced colitis on the regular diet. Although mice were still in their growth phase and expected to gain weight naturally, the first two cycles of dextran sodium sulfate treatments led to weight loss. However, mice on the broccoli sprout diet regained the lost weight by the beginning of the next cycle, while mice on the regular diet did not. At the end of the study, mice fed a regular diet with induced colitis had the lowest weight of all groups.

Mice with induced colitis who were fed a diet with broccoli sprouts had less pronounced symptoms of colitis and lower levels of some of the inflammation markers (proinflammatory cytokines IL-1 beta, IL-6, and tumor necrosis factor-alpha (TNF-α) compared to mice with induced colitis on the regular diet (see Figure 5).

Figure 5. Result analysis (Holman et al., 2023)

Broccoli sprouts protected against changed to bacterial community induced by colitis

Mice on a broccoli sprout diet with induced colitis had significantly more bacterial richness in their colon contents and on the colon walls (materials scraped from the colon) compared to mice with induced colitis on the regular diet. Comparing all four groups, results showed that the two groups that consumed diets with broccoli sprouts had higher bacterial richness in all gut locations, with the most notable difference observed in the colon.
Further analysis showed that the gut bacterial community of mice with induced colitis that consumed a diet with broccoli sprouts differed in which bacterial species were present from those of mice with induced colitis that consumed the regular diet. This indicated that broccoli sprouts strongly protected against changes to bacterial communities induced by dextran sodium sulfate.

Conclusion

Overall, the study results show that adding steamed broccoli sprouts to the diet of mice alleviates the effects of chemically induced bowel inflammation – colitis, but also protects microbial communities in their guts from changes induced by the treatment designed to induce colitis. Bacterial richness in various locations in the gut was similar between mice with induced colitis consuming broccoli sprouts and mice without colitis on a regular diet.

Although these findings were obtained on mice using chemically induced bowel inflammation, similarities with human biochemistry and inflammatory bowel diseases might be sufficient for similar effects. Since broccoli sprouts are widely available and affordable food items, adding them to a diet might be an easily implementable way to reduce symptoms of inflammatory bowel diseases and protect the gut microbiome. Of course, further study is needed to confirm that the effects observed in this study would also be present in humans with inflammatory bowel diseases. However, adding broccoli sprouts to the diet is a promising strategy.

Since broccoli sprouts are widely available and affordable food items, adding them to a diet might be an easily implementable way to reduce symptoms of inflammatory bowel diseases and protect the gut microbiome

The paper “Steamed broccoli sprouts alleviate DSS-induced inflammation and retain gut microbial biogeography in mice” was authored by Johanna M. Holman, Louisa Colucci, Dorien Baudewyns, Joe Balkan, Timothy Hunt, Benjamin Hunt, Marissa Kinney, Lola Holcomb, Allesandra Stratigakis, Grace Chen, Peter L. Moses, Gary M. Mawe, Tao Zhang, Yanyan Li, and Suzanne L. Ishaq.

References
Carbia, C., Bastiaanssen, T. F. S., Iannone, F., García-cabrerizo, R., Boscaini, S., Berding, K., Strain, C. R., Clarke, G., Stanton, C., Dinan, T. G., & Cryan, J. F. (2023). The Microbiome-Gut-Brain axis regulates social cognition & craving in young binge drinkers. EBioMedicine, (In press), 104442. https://doi.org/10.1016/j.ebiom.2023.104442

Holman, J. M., Colucci, L., Baudewyns, D., Balkan, J., Hunt, T., Hunt, B., Kinney, M., Holcomb, L., Stratigakis, A., Chen, G., Moses, P. L., Mawe, G. M., Zhang, T., Li, Y., & Ishaq, S. L. (2023). Steamed broccoli sprouts alleviate DSS-induced inflammation and retain gut microbial biogeography in mice. MSystems. https://doi.org/10.1128/msystems.00532-23

Leclercq, S., Le Roy, T., Furgiuele, S., Coste, V., Bindels, L. B., Leyrolle, Q., Neyrinck, A. M., Quoilin, C., Amadieu, C., Petit, G., Dricot, L., Tagliatti, V., Cani, P. D., Verbeke, K., Colet, J. M., Stärkel, P., de Timary, P., & Delzenne, N. M. (2020). Gut Microbiota-Induced Changes in β-Hydroxybutyrate Metabolism Are Linked to Altered Sociability and Depression in Alcohol Use Disorder. Cell Reports, 33(2). https://doi.org/10.1016/J.CELREP.2020.108238

Ng, S. C., Shi, H. Y., Hamidi, N., Underwood, F. E., Tang, W., Benchimol, E. I., Pannacione, R., Ghosh, S., Wu, J. C. Y., Chan, F. K. L., Sung, J. J. Y., & Kaplan, G. G. (2017). Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies. The Lancet, 390(10114), 2769–2778.

Ramos, G. P., & Papadakis, K. A. (2019). Mechanisms of Disease: Inflammatory Bowel Diseases. Mayo Clinic Proceedings, 94(1), 155–165. https://doi.org/10.1016/j.mayocp.2018.09.013

Tilg, H. (2015). Cruciferous vegetables: prototypic anti-inflammatory food components. Tilg Clinical Phytoscience, 1(10). https://doi.org/10.1186/s40816-015-0011-2

Do the Quality and Timing of Your Snacks Affect Your Cardiometabolic Health?

Posted on December 30, 2023January 12, 2024 by CNP Staff

A study published in the European Journal of Nutrition found that individuals consuming poor-quality snacks tend to have poorer cardiometabolic health indicators

Individuals snacking late in the evening, after 9 pm, tended to have poorer cardiometabolic health indicators than those not snacking late

The number of consumed snacks per day was not associated with cardiometabolic health indicator levels

Snacking
Snacking is consuming small, often casual, food portions between regular meals. Individuals typically do this to curb hunger, satisfy cravings, ease stress/boredom/nerves, or provide a quick energy boost. Snacks can vary widely in terms of their nutritional content and may range from healthy options like fruits and nuts to less nutritious choices like chips and candy.

A study in the U.S. indicated that 97% of people practiced snacking in 2006. The same study reported that the share of snack calories in the total daily energy intake stood at 24%. This was a substantial increase compared to findings in previous years. Not only did snacking become more widespread, but the energy density of snacks consumed increased (Piernas & Popkin, 2010). This increase in snacking coincided with the worldwide obesity pandemic (Wong et al., 2022).

A study in the U.S. in 2006 indicated that 97% of people practiced snacking and the share of snack calories in their total daily energy was 24%

Cardiometabolic blood markers
When studying the effects of various dietary patterns or differences between groups of individuals practicing different dietary patterns, researchers rely on various indicators of the functioning of study participants’ metabolisms and various physiological parameters to estimate possible links between dietary patterns and health. One very frequently used group of indicators is cardiometabolic blood markers, a group of indicators that can be derived from a blood sample.

Cardiometabolic blood markers are a group of specific substances found in the bloodstream that provide information about an individual’s cardiovascular and metabolic health. These markers include cholesterol levels, particularly low-density lipoprotein (LDL) cholesterol (“bad” cholesterol), which is associated with an increased risk of heart disease when elevated. Additionally, triglycerides (TGs), a type of fat in the blood, and blood glucose levels are important indicators of metabolic health. Elevated markers can signify an increased risk of diabetes, obesity, and heart disease, making them crucial for assessing and managing overall health and wellness (see Figure 1).

Figure 1. Cardiometabolic blood markers and associated health risks

Snacking and health
On the general level, snacking can be beneficial for health. It distributes energy and nutrient intake across multiple occasions in a day. Frequent snacks also present more opportunity for an individual to consume specific nutrients required by the body, thereby completing main meals (Marangoni et al., 2019)

On the general level, snacking can be beneficial for health

However, this largely depends on what the snacks are, i.e., their quality. For example, a recent study showed that snacking on a high-quality snack, i.e., whole almonds for six weeks, improved endothelial function, i.e., the ability of a thin layer of cells lining the inner surface of blood vessels to regulate various physiological processes in the cardiovascular system. These snacks also reduced concentrations of LDL cholesterol (also known as “bad“ cholesterol) in the blood (Dikariyanto et al., 2020).

On the other hand, consuming low-quality snacks, snacks consisting of ultra-processed foods, and foods with poor nutritional values can have opposite effects. Studies have linked frequent consumption of ultra-processed foods to adverse health outcomes (Monteiro et al., 2019; Samuthpongtorn et al., 2023), and it makes little difference whether these foods are perceived as snacks or as the main meals.

Frequent consumption of ultra-processed foods leads to adverse health outcomes

The current study
Study author Kate M. Bermingham and her colleagues wanted to explore the relationship between snacking habits – frequency of snacks, their quality, and timing with cardiometabolic blood markers, body measures, and the gut microbiome. They analyzed data from the ZOE PREDICT 1 study.

ZOE PREDICT 1 was a diet intervention study conducted between June 2018 and May 2019 that examined interactions between diet and cardiometabolic markers. The study participants were 967 healthy individuals from the UK. They were between 18 and 65 years of age. 73% of the participants were females. The study lasted for two weeks. Participants visited the clinic on the first day to take measurements and logged their dietary behavior for the next 13 days.

Participants logged food intake through an app
Researchers running the ZOE PREDICT 1 study trained study participants to accurately record their food intake using photos, product barcodes, portion sizes, and weighing food items on digital scales. Participants used a specially developed app called ZOE to record their food intake data throughout the study. Researchers collected data on the nutrient compositions of food from a nutrient database, while data on the contents of branded food items came from supermarket websites.

Participants reported the meal type (i.e., snack, breakfast, lunch, dinner, or drink), when they had it, and the food items consumed. A meal was when a participant consumed food or drinks separated by at least 30 minutes from a previous occasion. All food and drinks taken within 30 minutes of each other were considered a single meal. Participants consumed standardized meals on multiple study days to allow researchers to test their effects, but data from those days were not included in these analyses (see Figure 2).

Figure 2. Recording data on food consumption

Snacking habits and other data
Study authors considered snacks to be food or drinks consumed between main meals. They could consist of a single or multiple types of foods. However, the study authors did not count drinks of up to 50 kcal (e.g., drinking a glass of water) as snacks (if nothing else was consumed along with those drinks).

From the snacking data, researchers assessed the quality of snacks and inferred typical consumption times. The quality of snacks was related to the level of processing. Poor-quality snacks were ultra-processed, while unprocessed or minimally processed foods were considered high-quality.

Participants reported their hunger levels daily through the ZOE app. They did this at the time of the first logging into the app of the day and at regular intervals later. There were up to 7 hunger ratings per day. Participants also self-reported their general activity levels over the past year (“In the past year, how frequently have you typically engaged in physical exercises that raise your heart rate and last for 20 min at a time?”). They provided stool samples to allow researchers to examine their gut microbiome composition and gave blood samples at the start of the study for measuring cardiometabolic markers.

People who snack have 2.28 snacks per day on average

Results showed that 95% of participants snacked. On average, participants who snacked had 2.28 snacks per day: 19% had one snack per day, 47% had two snacks/day, and 29% had more than 2. The more snacks an individual had, the higher the share of snacks in their total daily energy intake was. Participants with larger shares of sugar and fats in their diets tended to consume more daily snacks, and their snacks tended to be higher in energy. Compared to main meals, snacks had higher shares of fats and sugars but lower protein contents (see Figure 3).

Figure 3. Snacking and snack vs. main meals

Cakes, pies, cereals, and ice cream were snacks with the highest contribution to energy intake
The most popular foods consumed as snacks were drinks (milk, tea, coffee, fruit drinks), candy, cookies and brownies, nuts, seeds and fruits (apples, bananas, citrus fruits), crisps, bread, cheese and butter, cakes and pies, and granola or cereal bars.

However, snacks with the highest contributions to total daily energy intakes were cakes and pies (14% of energy intake), cereals (13%), ice cream and frozen dairy products (12%), donuts and pastries (11%), candies, cookies and brownies (11%), nuts and seeds (11%) and corn snacks, chips and puffs (11%). There were no differences between genders on the average share of energy derived from snacks. The same was true with different age groups and people with different overall physical activity levels (see Figure 4).

Figure 4. Snacks with the highest contributions to total daily energy intake

People who eat better-quality snacks tend to have more favorable cardiometabolic blood marker levels

There were no differences in cardiometabolic blood marker levels between people who ate different numbers of snacks per day, nor between those who ate and those who did not eat snacks. There was also no association between the quantity of energy derived from snacks and cardiometabolic marker levels. Gut microbiota composition was not associated with snacking habits.

The number of snacks in a day and the quantity of energy derived from them were not associated with cardiometabolic blood markers (the quality of snacks was)

However, the quality of snacks was associated with cardiometabolic marker levels. Analysis showed that, on average, individuals who eat lower-quality snacks have higher levels of cardiometabolic markers than those who eat better-quality snacks. More specifically, these individuals had higher triglyceride levels and were more likely to show insulin resistance. They also had higher average levels of self-reported hunger. Participants eating high-quality snacks tended to have lower body weight, body mass index values, and body fat (see Figure 5).

Figure 5. Effect of snack quality on cardiometabolic marker levels

Late-evening snackers had poorer cardiometabolic blood marker levels
Analysis of the time of snack consumption showed that 13% of participants tended to mostly snack before noon (up to 50% of calories from snacks in that period), 39% were afternoon snackers (12 pm – 6 pm), and 31% were evening snackers (after 6 pm). 17% ate snacks equally throughout the day – there was no specific period when they ate more snacks. Additionally, researchers found that 32% of individuals tend to eat snacks (at least one) late in the evening – after 9 p.m. They referred to these individuals as late-evening snackers (see Figure 6).

Figure 6. Snacking times

Statistical analyses showed that late-evening snackers tend to have poorer cardiometabolic marker levels than those who do not snack after 9 p.m. Notably, these individuals had heightened blood glucose and triglyceride levels after meals and higher glycated hemoglobin levels compared to those who ate their snacks during the day. These differences were even higher in late-evening snackers prone to consuming poor-quality snacks (see Figure 7).

Figure 7. Effect of late-evening snacking on cardiometabolic markers

Conclusion
The study showed that the number of snacks eaten throughout the day is not associated with cardiometabolic blood marker levels. The same was the case with the share of energy derived from snacks. However, these health indicators are related to the quality of snacks and the time of day consumed. Consuming poor-quality snacks, particularly late in the evening, was associated with poorer cardiometabolic health indicators.

These findings could be used to inform the general public, as well as metabolic and cardiovascular disease prevention programs, about the possible health effects of snacking habits. Although the study design does not allow any cause-and-effect conclusions to be drawn, i.e., it remains unknown whether changing snacking habits would affect cardiometabolic indicator levels, there is a possibility that simply switching to better-quality snacks and avoiding late-evening snacking might indeed improve cardiometabolic health indicators and reduce the risk of serious metabolic diseases by at least some extent.

The paper “Snack quality and snack timing are associated with cardiometabolic blood markers: the ZOE PREDICT study” was authored by Kate M. Bermingham, Anna May, Francesco Asnicar, Joan Capdevila, Emily R. Leeming, Paul W. Franks, Ana M. Valdes, Jonathan Wolf, George Hadjigeorgiou, Linda M. Delahanty, Nicola Segata, Tim D. Spector, and Sarah E. Berry.

References

Bermingham, K. M., May, A., Asnicar, F., Capdevila, J., Leeming, E. R., Franks, P. W., Valdes, A. M., Wolf, J., Hadjigeorgiou, G., Delahanty, L. M., Segata, N., Spector, T. D., & Berry, S. E. (2023). Snack quality and snack timing are associated with cardiometabolic blood markers: the ZOE PREDICT study. European Journal of Nutrition. https://doi.org/10.1007/s00394-023-03241-6

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

Marangoni, F., Martini, D., Scaglioni, S., Sculati, M., Donini, L. M., Leonardi, F., Agostoni, C., Castelnuovo, G., Ferrara, N., Ghiselli, A., Giampietro, M., Maffeis, C., Porrini, M., Barbi, B., & Poli, A. (2019). Snacking in nutrition and health. International Journal of Food Sciences and Nutrition, 70(8), 909–923. https://doi.org/10.1080/09637486.2019.1595543

Monteiro, C. A., Cannon, G., Levy, R. B., Moubarac, J. C., Louzada, M. L. C., Rauber, F., Khandpur, N., Cediel, G., Neri, D., Martinez-Steele, E., Baraldi, L. G., & Jaime, P. C. (2019). Ultra-processed foods: What they are and how to identify them. In Public Health Nutrition (Vol. 22, Issue 5, pp. 936–941). Cambridge University Press. https://doi.org/10.1017/S1368980018003762

Piernas, C., & Popkin, B. M. (2010). Snacking Increased among U.S. Adults between 1977 and 2006, ,. The Journal of Nutrition, 140(2), 325–332. https://doi.org/10.3945/JN.109.112763

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

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

Intake of Micronutrients May Quicken Recovery From Anxiety and Depressive Symptoms

Posted on December 16, 2023January 12, 2024 by CNP Staff

An experimental study published in the Journal of Affective Disorders reports that intake of micronutrients might accelerate the improvement of depression and anxiety symptoms
Symptoms of the group taking micronutrients improved more quickly than those of the placebo group
The effect of the micronutrients was greater in younger participants, men, those from lower socioeconomic groups, and participants who had previously tried psychiatric medication

Everyone occasionally experiences situations in which they feel low, sad, or not interested in doing anything in particular, having difficulty gathering the motivation to perform daily activities. Similarly, we all feel anxious from time to time, particularly before important events, but the outcome of which is uncertain. However, in some individuals, these feelings become so persistent and frequent that they begin to impair their daily functioning. These are conditions that we refer to as depression (or major depressive disorder) and anxiety disorder.

What are depression and anxiety disorders?
Depression is a mental health disorder characterized by persistent feelings of sadness, hopelessness, and a lack of interest or pleasure in activities. Symptoms may include changes in appetite and sleep patterns, fatigue, difficulty concentrating, and thoughts of death or suicide. It significantly impacts a person’s emotional well-being and daily functioning.
Anxiety, on the other hand, is a condition marked by excessive worry, fear, or apprehension about future events. It can manifest in various forms, such as generalized anxiety disorder, panic disorder, social anxiety disorder, or various phobias. Physical symptoms like restlessness, muscle tension, and increased heart rate often accompany anxiety (see Figure 1).

Figure 1. Depression Vs. Anxiety

Epidemiological studies indicate that the number of people suffering from anxiety and depression has been increasing across many world countries in recent decades. Analyses indicate that these increases are likely not solely the consequence of better diagnostics and propose that changes to the way we live our lives might have adverse mental health consequences as well (Baxter et al., 2014; Steffen et al., 2020; Weinberger et al., 2018).

The number of people suffering from anxiety and depression has been increasing across many world countries in recent decades

What causes depression and anxiety disorders?
Researchers currently believe that neither depression nor anxiety have a single cause. Available data indicate that they can stem from various factors, including genetics, imbalances in brain chemistry, trauma, and environmental stressors. Recent studies also linked these disorders to certain dietary habits and changes in gut microbiota (Craiovan, 2015; Hedrih, 2023; Leclercq et al., 2020; Samuthpongtorn et al., 2023; Valles-Colomer et al., 2019).

How are these disorders treated?
Currently, psychiatric medications are an accessible treatment option for many people with depression and anxiety disorders (Blampied et al., 2023). Medications are often combined with psychotherapy. However, the effectiveness of these treatments is far from 100%. In many individuals, standard treatment protocols do not result in the withdrawal of symptoms. They sometimes fail to produce even a reduction of symptoms. This has given rise to concepts such as treatment-resistant depression (Fava, 2003). Also, it motivates researchers to seek alternative treatment options (e.g., Zavaliangos-Petropulu et al., 2023) or additions to the existing protocols that could improve their effectiveness.

Among other things, researchers proposed lifestyle changes and physical exercise as potential ways to improve symptoms of depression and anxiety. However, studies of the effectiveness of such treatments indicate mixed results (Kvam et al., 2016; Serrano Ripoll et al., 2015).

Studies conducted in recent decades identified associations between depression and mental health in general with dietary habits and properties of the gut microbiota (Hedrih, 2023a, 2023b; Leclercq et al., 2020; Valles-Colomer et al., 2019). This opened another possible venue for developing potential mental health disorder treatments – dietary intervention.

The current study
Study author Meredith Blampied and her colleagues wanted to explore the potential of dietary intervention in treating anxiety and depression. They note that poverty of diet is a well-established characteristic of people with these two types of disorders. These researchers considered adding micronutrients to patients’ diets as a promising option for a dietary intervention (Blampied et al., 2023).

Some previous studies already established that dietary interventions might effectively improve mental health symptoms. However, to be truly effective, dietary changes introduced through dietary interventions need to be maintained long-term. This is an issue in many patients (Blampied et al., 2023).

Poverty of diet is a well-established characteristic of people with anxiety and depression

What are micronutrients?
Micronutrients are essential nutrients the body requires in relatively small amounts to maintain proper physiological functions. These include vitamins and minerals, each playing unique roles in supporting various bodily processes. Vitamins such as A, B, C, D, E, and K are organic compounds that contribute to immune support, bone health, and energy metabolism. Minerals, including calcium, iron, zinc, and magnesium, are inorganic elements vital for bone formation, oxygen transport, and enzyme function (see Figure 2).

Figure 2. Impact of micronutrients on Bodily functions

There are several possible mechanisms for how micronutrients might benefit mental health. Some micronutrients are necessary components for the production of neurotransmitters. Other micronutrients help reduce inflammation and oxidative stress or maintain the balance of microbes in the digestive tract. Due to all this, the authors of this study believed that adding a broad spectrum of micronutrients to the diets of individuals suffering from depression or anxiety might lead to a greater reduction of symptoms during treatment (compared to placebo) (Blampied et al., 2023).

There are several possible mechanisms for how micronutrients might benefit mental health

Study participants
Study participants were 150 adults from Canterbury, New Zealand, reporting functionally impairing symptoms of anxiety and/or depression. Functionally impairing symptoms are symptoms that adversely affect their relationships, ability to work and/or engage in meaningful activity, and/or that prevent them from engaging in activities of daily living. Researchers recruited these participants between 2018 and 2020 via referrals from general practitioners and through self-referrals.

Study procedure
The study’s authors divided participants randomly into two groups of equal size. Both groups received pills that they were supposed to take over a ten-week study period. The pills and their packaging looked identical. Researchers sent participants the packages with pills for the study period via courier service. There were 12 pills participants had to consume each day, in three doses, four pills per dose.

However, pills delivered to one group (the micronutrient group) contained essential micronutrients, while those delivered to the other group contained maltodextrin (a carbohydrate derived from starch), fiber acacia gum (a natural thickening agent), and very small amounts of cocoa and riboflavin powders (for flavor) (see Figure 3).

Figure 3. Study Procedure (Blampied et al., 2023)

A full daily dose of micronutrient pills contained vitamins A, C, D, E, B6, B12, thiamin, riboflavin, niacin, biotin, pantothenic acid, calcium, iron, phosphorous, iodine, magnesium, zinc, selenium, copper, manganese, chromium, molybdenum, potassium, and several other ingredients.

Of all the individuals involved in the study procedure, only the pharmacist who prepared the pills had access to the group membership list, i.e., knew which participant was in which group. No one else knew this, including the study participants themselves. This was necessary to ensure that participants in both groups remained uncertain whether they were taking micronutrient capsules or a placebo.

Once per week, participants completed online assessments of depression (the Patient Health Questionnaire – 9 item scale, PHQ-9), anxiety (the Generalized Anxiety Disorder-7 question Scale, GAD-7), and a modified questionnaire used to assess side-effects of antidepressants (the Antidepressant Side-Effect Checklist, ASEC). Additionally, a clinical psychologist monitored the participants’ condition during the trial. This included assessment phone calls at the start and the end of the study and weekly text message reminders to complete the online assessments.

Symptoms improved faster in the micronutrient group
Results showed that anxiety and depression symptom severity decreased in both groups as the study progressed. However, the pace of decrease was faster in the group that consumed micronutrients. This was the case with both symptoms of depression and anxiety (See Figure 4).

Figure 4. Symptoms improved faster in the micronutrient group

To verify that these are the effects of micronutrients (and not, e.g., of participants’ expectations), study authors asked participants to report which group they think they are in. Results showed that 62% of participants in the placebo group and 55% from the micronutrient group believed they were in the placebo group. The small difference in percentages indicated to the researchers that their attempt to not let participants know which group they were in was successful. It also increased the likelihood that the observed differences between groups are the effects of micronutrient supplements (and not some other uncontrolled factor).

Results showed that anxiety and depression symptom severity decreased in both groups as the study progressed. However, the decrease pace was faster in the group that consumed micronutrients

Effects of micronutrients depend on age, previous psychiatric treatments, and socioeconomic status
Further analysis revealed that the effects of micronutrients on depressive symptoms depended on age – younger participants in the micronutrient group showed stronger improvements compared to the placebo group as time progressed.

The effects of micronutrients on depressive symptoms depended on age – younger participants in the micronutrient group showed greater improvements compared to the placebo group as time progressed.

Depression symptoms of participants in the placebo group also improved more quickly if they had not previously tried psychiatric medication. This effect was absent for anxiety symptoms. However, the effects of micronutrient intake on the pace of improvement of both depression and anxiety symptoms were greater in participants who previously used psychiatric medication. In a similar manner, depression symptoms of participants with better socioeconomic status in the placebo group improved more quickly. Still, the effects of micronutrients on the improvement of both types of symptoms were greater in participants with lower socioeconomic status.

Men’s symptoms improved slower than women’s, but micronutrients eliminated the difference
Men showed slower improvement in the placebo condition than women. However, in the micronutrient group, there was no difference in the pace of symptom improvement between men and women. This indicates that micronutrient intake accelerated the pace of symptom improvement in men specifically – men’s response to micronutrient intake was stronger.

By the end of the trial, both groups showed similar levels of improvement
Of participants who entered the study with depression symptom severity that indicated depression disorder, 61% from the micronutrient group and 49% from the placebo group achieved clinically significant symptom improvements by the end of the study.

Of participants who started the study with levels of anxiety symptoms indicating anxiety disorder, 62% from the micronutrient group and 56% from the placebo group achieved clinically significant reductions in symptoms.

In a similar fashion, males and females showed similar levels of improvement by the end of the study, and the same was the case with participants who had and those who had not used psychiatric medications earlier. Clinicians’ assessments of levels of improvement in the two groups indicated similar levels of improvement.

Conclusion
Overall, results showed that micronutrient intake might help existing treatments for anxiety and depression by accelerating the pace of recovery. The effects of this dietary intervention seem to be particularly visible in younger individuals, men, those of low socioeconomic status, and individuals with a previous history of psychiatric medication use.

Overall, results showed that micronutrient intake might help existing treatments for anxiety and depression by accelerating the pace of recovery

While it remains unclear why micronutrients showed greater effects in these categories, an important possibility is that they help alleviate dietary deficiencies in some members of these groups, producing greater overall effects in the group as a whole. This indicates that it might be useful for future depression and anxiety treatment programs, but also programs aimed at prevention, to look at the dietary habits of affected individuals along with their psychological status.

The paper “Efficacy and safety of a vitamin-mineral intervention for symptoms of anxiety and depression in adults: A randomized placebo-controlled trial “NoMAD” was authored by Meredith Blampied, Jason M. Tylianakis, Caroline Bell, Claire Gilbert, and Julia J. Rucklidge.

References
Baxter, A. J., Vos, T., Scott, K. M., Ferrari, A. J., & Whiteford, H. A. (2014). The global burden of anxiety disorders in 2010. Psychological Medicine, 44(11), 2363–2374. https://doi.org/10.1017/S0033291713003243

Blampied, M., Tylianakis, J. M., Bell, C., Gilbert, C., & Rucklidge, J. J. (2023). Efficacy and safety of a vitamin-mineral intervention for symptoms of anxiety and depression in adults: A randomised placebo-controlled trial “NoMAD.” Journal of Affective Disorders, 339, 954–964. https://doi.org/10.1016/j.jad.2023.05.077

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Hedrih, V. (2023b). Women Consuming Lots of Artificially Sweetened Beverages Might Have a Higher Risk of Depression, Study Finds. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/women-consuming-lots-of-artificially-sweetened-beverages-might-have-a-higher-risk-of-depression-study-finds/

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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

Serrano Ripoll, M. J., Oliván-Blázquez, B., Vicens-Pons, E., Roca, M., Gili, M., Leiva, A., García-Campayo, J., Demarzo, M. P., & García-Toro, M. (2015). Lifestyle change recommendations in major depression: Do they work? Journal of Affective Disorders, 183, 221–228. https://doi.org/10.1016/j.jad.2015.04.059

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Valles-Colomer, M., Falony, G., Darzi, Y., Tigchelaar, E. F., Wang, J., Tito, R. Y., Schiweck, C., Kurilshikov, A., Joossens, M., Wijmenga, C., Claes, S., Van Oudenhove, L., Zhernakova, A., Vieira-Silva, S., & Raes, J. (2019). The neuroactive potential of the human gut microbiota in quality of life and depression. Nature Microbiology, 4(4), 623–632. https://doi.org/10.1038/s41564-018-0337-x

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Can Dietary Prebiotics Reduce the Rewarding Effects of High-Calorie Foods?

Posted on November 30, 2023January 12, 2024 by CNP Staff

An experimental study of overweight young adults published in Gut demonstrated that dietary prebiotics can reduce the rewarding effects of high-calorie food
After 14 days of using prebiotics, fMRI scans showed reduced reward-related brain activation in response to high-calorie food compared to the placebo group
Occurrence of short-chain-fatty-acid-producing Bifidobacteriaceae increased in participants taking prebiotics

We are all familiar with the intense feelings of pleasure we get after consuming highly tasty and palatable food – a piece of chocolate cake, for example. We will remember these feelings and associate them with this food. When we decide what to eat in the future, we will recall the memories of that food and the feelings we experienced when eating it —and likely develop a desire to eat the same food again. That is an important part of how we create our food preferences.

Consuming highly palatable foods, especially those high in sugar and fat, can increase dopamine in the brain, creating a sense of pleasure and satisfaction

Rewarding effects of food
The feelings of pleasure we experience when eating highly palatable foods are created by our brain’s reward system. The brain’s reward system comprises a complex network of neural circuits that play a fundamental role in motivation, reinforcement, and pleasure. This process involves the release of neurotransmitters, particularly dopamine, in response to rewarding stimuli, such as food, sex, or positive social interactions. This dopamine release reinforces behaviors associated with the reward, creating a drive to seek out and repeat those behaviors (Lewis et al., 2021) (see Figure 1).

Consuming highly palatable foods, especially those high in sugar and fat, can increase dopamine in the brain, creating a sense of pleasure and satisfaction. This activation of reward neural pathways reinforces the desire to eat, making us more likely to seek those foods in the future.

Figure 1. Food and the brain’s reward system

How is the brain’s reward system linked to obesity?
Repeated exposure to highly rewarding foods, especially in excess, can lead to desensitization of the reward system. When this happens, an individual will need more and more food to achieve the expected pleasant feelings, i.e., the rewarding effects of food. This might make the individual increase the intake of the food in question, potentially leading to overeating and an increase in body weight in the long run (see Figure 2).

Figure 2. Exposure to highly rewarding foods can lead to increased food intake

The described mechanism is similar to that which occurs with addictions. This is the reason why some authors propose that an individual can develop an addiction to certain foods and that food addiction should be recognized as a distinct mental health condition. Studies these researchers carried out indicate that consumption of foods rich in both sugar and fats, such as (many types of) ultra-processed foods, is particularly likely to result in food addiction (Gearhardt et al., 2011, 2023; Hedrih, 2023; Thanarajah et al., 2023).

Studies of these neural mechanisms in humans found functional alterations in the areas of the brain involved in the reward system in overweight individuals (e.g., Pujol et al., 2021; Seabrook et al., 2023), while studies on mice clearly show that high-fat diets can indeed induce obesity by disrupting the functioning of neural mechanisms regulating food intake (e.g., Ikemoto et al., 1996).

This leads many researchers to search for methods of influencing the brain’s reward system to prevent obesity or help individuals regain healthy body mass.

The current study
Study author Evelyn Medawar and her colleagues hypothesized that consuming high doses of prebiotic fiber as a supplement would change the patterns of neural activity related to food in the brain reward system in individuals at risk for weight gain and developing diabetes. Prebiotic fiber is a type of dietary fiber that promotes the growth and activity of beneficial bacteria in the gut, supporting a healthy microbiota. While it is indigestible for humans, it serves as food for various bacteria living in the gut, promoting their growth.

The authors of this study expected that an intervention using prebiotics would alter the composition of the gut microbiome, which would, in turn, alter the food-related patterns of brain activation (Medawar et al., 2023).

The gut microbiome or gut microbiota is the community of trillions of bacteria, fungi, viruses, and other microorganisms that live in the human gut. These microorganisms are critical for digestion, allowing the human digestive system to digest substances it would not be able to digest without them. Still, they also serve a number of other metabolic roles.

High doses of prebiotic fiber as a supplement would change the patterns of neural activity related to food in the brain reward system

How can gut bacteria affect the brain reward system?
Scientists studying human life processes in recent decades discovered a system in the human body that allows communication between gut microorganisms and the brain. This bidirectional communication system is called the microbiota-gut-brain axis (MGBA). It links the gut microbiota, the gastrointestinal tract, and the central nervous system (CNS).

Aside from their role in digestion, gut microorganisms produce various signaling molecules that can influence neural, endocrine, and immune functions. These molecules enable communication between the gut and the brain through neural, hormonal, and immunological pathways. Studies have already identified various ways in which processes in the gut can affect brain functioning, but much still remains to be discovered (Qu et al., 2023; Valles-Colomer et al., 2019; Zhu et al., 2023).

Recent findings indicate that the microbiota-gut-brain axis MGBA can affect and regulate the reward system of the brain as well (Carbia et al., 2023; García-Cabrerizo et al., 2021). Given this, it is possible that gut microbiota changes could also affect the brain’s reward system (see Figure 3).

Figure 3. Signaling molecules enabling communication between the gut and brain

Recent findings indicate that the microbiota-gut-brain axis (MGBA) can affect and regulate the reward system of the brain

The procedure
Study participants were 59 overweight adults (body mass index values between 25 and 30). Their ages ranged between 18 and 42 years. Nineteen of them were females. Participants received 9-10 EUR per hour for their activities during testing days and another 30 EUR for completing the study.

The study’s authors prepared two different treatment substances for participants: a prebiotic fiber supplement and a placebo. The daily dose of prebiotic fiber consisted of 30 grams of inulin, a carbohydrate found in plants such as chicory root. Humans lack the enzymes needed to digest inulin, but many beneficial bacteria in the gut can ferment it. The product of this fermentation is short-chain fatty acids. Among other things, these substances are involved in the functioning of the MGBA (learn more about short-chain fatty acids in NP 120 Parts I and II through CNP) (see Figure 4).

Figure 4. Research procedure using prebiotic fiber vs. placebo

A daily placebo treatment substance consisted of 16g of maltodextrin, a carbohydrate used as a food additive and a thickening agent derived from starch. The placebo treatment was matched on calories with the prebiotic fiber treatment. Both substances were packed in identical sachets, so participants could not tell which substance a sachet contained. In both cases, participants were supposed to take two sachets of the treatment substance daily.

Each participant was supposed to take each of the two treatment substances for 14 days in a row, with two weeks between the treatments. The order in which each participant would take the treatments was randomized – some participants first took the prebiotic fiber for 14 days, paused for 14 days, and then took a placebo for another 14 days. Other participants would start with 14 days of placebo and finish with 14 days of using the prebiotic fiber. This was a blind study, so study participants and staff working with them did not know when they were taking a placebo and when it was prebiotic fiber.

Neuroimaging and measurements
Before and after each 14-day treatment, participants underwent functional magnetic resonance imaging (fMRI). During imaging, they viewed pictures of food and art and rated how much they wanted the item shown in the picture. Researchers told them they would receive a reward based on their ratings – either a food item that could be eaten immediately after fMRI or a carton print of an art piece.

Participants gave blood samples to assess short-chain fatty acid concentrations, gastrointestinal hormones, glucose, lipids, and inflammatory markers. They also gave stool samples for measuring gut microbiota composition and short-chain fatty acids.

Brain reactions to high-calorie foods decreased after prebiotic treatment

On average, during fMRI scans, participants wanted food more than they wanted art. The prebiotic treatment did not change the relationship between these wanting scores. However, after 14 days of taking prebiotics, participants had lower overall wanting scores than after 14 days of taking a placebo. In particular, after prebiotics treatment, participants expressed very little desire for very low and very high-calorie foods and plants (see Figure 5).

Figure 5. Brain reactions to high-calorie foods decreased after prebiotic treatment

When brain activity was examined, regional brain activity in reaction to food and art pictures remained the same. Evaluation of food pictures activated large parts of the reward network, including the ventral tegmental area, hypothalamus, nucleus accumbens, basal ganglia, and ventromedial thalamus, as well as anterior insula, amygdala, cingulate, ventromedial prefrontal cortex, and distinct parts of the orbitofrontal cortex.

However, brain reactions to pictures of wanted, high-calorie food decreased after prebiotics (compared to placebo) in three brain regions – ventral tegmental area, right and right medial the orbitofrontal cortex. Additionally, participants reported feeling less subjective hunger during fMRI after the prebiotics treatment.

Brain reactions to pictures of wanted, high-calorie food decreased after prebiotics compared to placebo

Prebiotic treatment altered gut microbiota composition
Analysis of stool samples indicated that the treatment with prebiotics led to significant shifts in gut microbiota composition. Overall richness, evenness, and diversity (the number of different species of microorganisms) decreased. The amounts of Bifidobacteria in samples increased. Increases in Bifidobacteria were associated with increases in the activity of a number of metabolic pathways.

Participants who had a more substantial decrease in Subdoligranulum bacteria after prebiotics treatment tended to show a decreased activation of the brain’s ventral tegmental area in response to high-calorie food. Participants who had a decrease in Lactiplantibacillus, a lactic acid-producing bacteria, after prebiotics treatment tended to have decreased activation in the right medial orbitofrontal cortex.

Conclusion
The study showed that intervention with a common prebiotic attenuated reactions of the brain’s reward network in response to high-calorie food. It also induced changes to the gut microbiota, through which this effect was likely achieved.

The study showed that intervention with a common prebiotic attenuated reactions of the brain’s reward network in response to high-calorie food

Since the discovery of the microbiota-gut-brain axis, scientists have considered using prebiotics or other interventions aimed at gut microbiota to achieve beneficial changes in brain activity and behavior. The results of this study indicate that this idea holds merit. While it used a common type of prebiotic, it proved that brain functioning can be affected in this way. This opens a path for future researchers to develop more effective and specific ways to achieve mental health outcomes through interventions aimed at gut microbiota.

The paper “Prebiotic diet changes neural correlates of food decision-making in overweight adults: a randomized controlled within-subject cross-over trial” was authored by Evelyn Medawar, Frauke Beyer, Ronja Thieleking, Sven-Bastiaan Haange, Ulrike Rolle-Kampczyk, Madlen Reinicke, Rima Chakaroun, Martin von Bergen, Michael Stumvoll, Arno Villringer, A Veronica Witte.

References

Carbia, C., Bastiaanssen, T. F. S., Iannone, F., García-cabrerizo, R., Boscaini, S., Berding, K., Strain, C. R., Clarke, G., Stanton, C., Dinan, T. G., & Cryan, J. F. (2023). The Microbiome-Gut-Brain axis regulates social cognition & craving in young binge drinkers. EBioMedicine, (In press), 104442. https://doi.org/10.1016/j.ebiom.2023.104442

García-Cabrerizo, R., Carbia, C., O´Riordan, K. J., Schellekens, H., & Cryan, J. F. (2021). Microbiota-gut-brain axis as a regulator of reward processes. Journal of Neurochemistry, 157(5), 1495–1524. https://doi.org/10.1111/JNC.15284

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

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

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/

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

Lewis, R. G., Florio, E., Punzo, D., & Borrelli, E. (2021). The Brain’s Reward System in Health and Disease. In Advances in Experimental Medicine and Biology (Vol. 1344, pp. 57–69). Springer. https://doi.org/10.1007/978-3-030-81147-1_4

Medawar, E., Beyer, F., Thieleking, R., Haange, S.-B., Rolle-Kampczyk, U., Reinicke, M., Chakaroun, R., von Bergen, M., Stumvoll, M., Villringer, A., & Witte, A. V. (2023). Prebiotic diet changes neural correlates of food decision-making in overweight adults: a randomised controlled within-subject cross-over trial. Gut, gutjnl-2023-330365. https://doi.org/10.1136/gutjnl-2023-330365

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

Qu, Y., Eguchi, A., Wan, X., Ma, L., Chang, L., Shan, J., Yang, Y., Mori, C., & Hashimoto, K. (2023). Repeated use of 3,4-methylenedioxymethamphetamine is associated with the resilience in mice after chronic social defeat stress: A role of gut–microbiota–brain axis. Psychiatry Research, 320(October 2022), 0–9. https://doi.org/10.1016/j.psychres.2022.115020

Seabrook, L. T., Naef, L., Baimel, C., Judge, A. K., Kenney, T., Ellis, M., Tayyab, T., Armstrong, M., Qiao, M., Floresco, S. B., & Borgland, S. L. (2023). Disinhibition of the orbitofrontal cortex biases decision-making in obesity. Nature Neuroscience, 26(1), 92–106. https://doi.org/10.1038/s41593-022-01210-6

Thanarajah, S. E., Difeliceantonio, A. G., Albus, K., Br, J. C., Tittgemeyer, M., Small, D. M., Thanarajah, S. E., Difeliceantonio, A. G., Albus, K., Kuzmanovic, B., & Rigoux, L. (2023). Habitual daily intake of a sweet and fatty snack modulates reward processing in humans. Cell Metabolism, 35, 1–14. https://doi.org/10.1016/j.cmet.2023.02.015

Valles-Colomer, M., Falony, G., Darzi, Y., Tigchelaar, E. F., Wang, J., Tito, R. Y., Schiweck, C., Kurilshikov, A., Joossens, M., Wijmenga, C., Claes, S., Van Oudenhove, L., Zhernakova, A., Vieira-Silva, S., & Raes, J. (2019). The neuroactive potential of the human gut microbiota in quality of life and depression. Nature Microbiology, 4(4), 623–632. https://doi.org/10.1038/s41564-018-0337-x

Zhu, X., Sakamoto, S., Ishii, C., Smith, M. D., Ito, K., Obayashi, M., Unger, L., Hasegawa, Y., Kurokawa, S., Kishimoto, T., Li, H., Hatano, S., Wang, T. H., Yoshikai, Y., Kano, S. ichi, Fukuda, S., Sanada, K., Calabresi, P. A., & Kamiya, A. (2023). Dectin-1 signaling on colonic γδ T cells promotes psychosocial stress responses. Nature Immunology. https://doi.org/10.1038/s41590-023-01447-8

Does the Neighborhood You Live in Affect your Diet-Mental Health Relationship?

Posted on November 17, 2023January 12, 2024 by CNP Staff

Individuals in disadvantaged neighborhoods tend to have higher body mass index and perceived stress
fMRI scans of these individuals’ brains indicate disruptions in information processing flexibility in brain regions involved in processing rewards, regulating emotions, and higher cognitive functions
The link between neighborhood characteristics and these neural changes may be partially mediated by obesity, i.e., the body mass index, but not by stress levels (Kilpatrick et al., 2023)

When traveling through towns and cities, it’s noticeable that different areas vary significantly in their appearance and available amenities. Some neighborhoods boast well-maintained, larger, and aesthetically pleasing buildings, while others are defined by smaller, older structures showing signs of disrepair and neglect.

Affluent and disadvantaged neighborhoods
The first type of neighborhood tends to be cleaner, safer, and have better maintained public spaces. It will also have access to upscale amenities such as boutique shops, gourmet restaurants, and cultural attractions. The second type of neighborhood likely has higher crime rates and may have issues with litter and graffiti. There will be fewer local businesses and may lack various amenities. We typically call the first group affluent neighborhoods, while researchers refer to the second group as disadvantaged.

Individuals in disadvantaged neighborhoods typically have lower income levels, limited access to quality education, healthcare, employment opportunities, and substandard living conditions. These individuals often encounter systemic barriers to social mobility, resulting in a lack of access to essential services and readily available resources in more affluent areas (Woolley et al., 2008).

Living in disadvantaged neighborhoods is linked to higher health risks
Living in a disadvantaged neighborhood is linked to various adverse outcomes in the diet-mental health relationship (DMHR). Individuals living in these areas are at a higher risk of obesity due to the poor quality of foods available to them and environments that hamper physical activity (Saelens et al., 2012; Zick et al., 2009). Lower income levels among residents make them more likely to consume ultra-processed foods, a known contributor to obesity (Monteiro et al., 2019). Additionally, chronic stressors linked with living in disadvantaged neighborhoods might increase the desire for highly palatable foods, which are often unhealthy, as a coping response.

Living in a disadvantaged neighborhood is linked to various adverse outcomes in the diet-mental health relationship (DMHR)

Consequently, these factors are associated with adverse neural changes such as reduced brain volume and unfavorable changes in the structure and functioning of specific brain regions. These changes can disrupt the brain’s mechanisms for regulating food intake, leading to obesity and contributing to mental health disorders, such as depression. (Samuthpongtorn et al., 2023; Seabrook et al., 2023). The risks of health problems related to obesity, such as cardiovascular diseases, diabetes, and certain forms of cancer, are increased with the consumption of ultra-processed foods.

Figure 1. DMHR Risks of disadvantaged neighborhoods: Higher risk of obesity, increased desire, and consumption of ultra-processed foods/highly palatable foods. Changes in brain volume/structure/function, food intake regulation mechanisms, additional health problems: cardiovascular diseases, diabetes, cancer.

Area deprivation index
Whether a neighborhood is considered affluent or disadvantaged is a matter of degree. Some neighborhoods are more disadvantaged, and some are more affluent than others. It can be thought of as a continuum. Researchers use the area deprivation indices to assess a specific geographical area’s socioeconomic disadvantage or affluence (such as a neighborhood).

Whether a neighborhood is considered affluent or disadvantaged is a matter of degree

These indices can be constructed differently, but they typically consider factors such as income, education, employment, housing conditions, and essential services available in the area. Areas with wealthier, more educated residents, better employment, improved housing conditions, and good access to essential services would be considered more affluent. Those with opposite characteristics would be considered more disadvantaged (see Figure 2).

Figure 2. Area Deprivation Index features

The current study
Study author Lisa A. Kilpatrick, and her colleagues aimed to investigate the relationship between the area deprivation index (ADI) and the microstructure of the brain cortex, assessed by the T1w/T2w ratio. They also explored how body mass index and stress affect that link.

They hypothesized that individuals living in areas with worse area deprivation index values would likely have higher body mass indexes, be more prone to diets conducive to obesity, and experience higher stress levels. Consequently, these factors would negatively impact the microstructure of their brain, particularly in the areas related to processing rewards, regulating emotions, and cognition.

T1- and T2-weighted images and T1w/T2w ratio
T1-weighted (T1w) and T2-weighted (T2w) images are two types of magnetic resonance imaging (MRI) sequences used to visualize and differentiate various tissues within the human body. In neuroimaging, T1-weighted images provide excellent structural details and are used to highlight distinctions between various brain tissues, making them useful for visualizing specific areas of the brain. T2-weighted images emphasize differences in water content within the brain, making them valuable for detecting abnormalities like edema, inflammation, and lesions—areas where the brain tissue is damaged. They are also useful for assessing regions filled with cerebrospinal fluid. (see Figure 3).

Figure 3. Identifying tissue microstructure alterations on magnetic resonance imaging (MRI)

Researchers often compare signal intensities in these two types of images of the same brain area and calculate a measure called the T1w/T2w ratio. The T1w/T2w ratio can offer a more nuanced and quantitative understanding of the brain’s tissue properties, surpassing the insights provided by qualitative visual analysis alone. It can help researchers identify microstructural differences in the brain, areas where a certain disease is developing or present, regions with altered functionality, injuries, and other changes to the brain tissue.

In general, both a decrease and an increase in the T1w/T2w ratio in a brain region can indicate adverse developments in it, as it indicates that the tissue structure in that area differs from that observed in the brains of healthy individuals.

The procedure
The study involved 92 adults from the Los Angeles area, consisting of 27 men and 65 women. Between 2019 and 2022, participants underwent neuroimaging sessions encompassing T1w and T2w scanning. Details about their place of residence were also gathered. Participants were recruited using flyers and emails distributed through various channels. The mean age of participants was 28 years.

Participants underwent a stress assessment using the Perceived Stress scale and provided dietary information through the VioScreen Graphical Food Frequency System. Researchers measured their weight and height to calculate body mass index values.

Findings
Area deprivation index was linked with microstructural alterations in brain regions responsible for reward processing, emotion regulation, and higher cognition.

Participants living in more deprived areas, i.e., areas with worse area deprivation index values, had increased T1w/T2w ratios in brain regions involved in reward-related processing, emotional regulation, and higher cognition. These were observed in the medial prefrontal and cingulate regions – mainly at middle/superficial cortical levels.

They also had decreased T1w/T2w ratios in regions of the neural system involved in social interaction. The affected areas were supramarginal, middle temporal, and primary motor regions in mainly middle/deep cortical levels. Both increased and decreased T1w/T2w ratios can be interpreted as indicators of adverse changes to the microstructure of neural tissue in the affected areas. Consequently, this suggests that the functioning of these areas is not as optimal as in a healthy brain. (see Figure 4).

Figure 4. Area deprivation and brain microstructure

Body mass index mediates the link between area deprivation and altered brain microstructure
The study authors created and tested a statistical model suggesting that living in a more disadvantaged area correlates with higher body mass index values and increased stress. According to this model, these factors contribute to pronounced changes in the T1w/T2w ratios in the brain regions where alterations were observed. In other words, they proposed that body mass index (i.e., being obese or overweight) and stress mediate the relationship between area disadvantage and the extent of changes to the microstructure of specific brain areas.

They proposed that body mass index (i.e., being obese or overweight) and stress mediate the relationship between area disadvantage and the extent of changes to the microstructure of specific brain areas

Analysis showed that although individuals living in more disadvantaged neighborhoods tend to experience higher stress levels, this does not lead to changes in the brain microstructure. On the other hand, this analysis confirmed that the link between area deprivation and the microstructure of specific brain areas is mediated by body mass index. However, the body mass index did not fully account for this link, indicating that additional factors likely contribute to the association between altered brain microstructure and area deprivation level.

Conclusion
Overall, the study showed that individuals living in more disadvantaged areas tend to have altered tissue structures in brain regions responsible for reward processing, emotion regulation, and cognition. These alterations to the tissue microstructure may disrupt the flexibility of information processing in these areas. Additionally, a significant portion of these brain changes is associated with obesity and likely connected to factors that contribute to obesity.

The study showed that individuals living in more disadvantaged areas tend to have altered tissue structures in brain regions responsible for reward processing, emotion regulation, and cognition

Due to the study’s design, it remains unclear whether life in disadvantaged neighborhoods leads to obesity and adverse changes in brain microstructure or if the altered brain microstructure restricts an individual’s ability to secure resources necessary for living in more affluent neighborhoods and avoid dietary behaviors that lead to obesity. While this will have to be explored in future research, it is important for both policymakers and the general public to be aware of the connections between life in disadvantaged neighborhoods and brain health.

The paper “Mediation of the association between disadvantaged neighborhoods and cortical microstructure by body mass index” was authored by Lisa A. Kilpatrick, Keying Zhang, Tien S. Dong, Gilbert C. Gee, Hiram Beltran-Sanchez, May Wang, Jennifer S. Labus, Bruce D. Naliboff, Emeran A. Mayer, and Arpana Gupta.

References
Kilpatrick, L. A., Zhang, K., Dong, T. S., Gee, G. C., Beltran-Sanchez, H., Wang, M., Labus, J. S., Naliboff, B. D., Mayer, E. A., & Gupta, A. (2023). Mediation of the association between disadvantaged neighborhoods and cortical microstructure by body mass index. Communications Medicine, 3(1). https://doi.org/10.1038/s43856-023-00350-5

Saelens, B. E., Sallis, J. F., Frank, L. D., Couch, S. C., Zhou, C., Colburn, T., Cain, K. L., Chapman, J., & Glanz, K. (2012). Obesogenic Neighborhood Environments, Child and Parent Obesity: The Neighborhood Impact on Kids Study. American Journal of Preventive Medicine, 42(5), e57–e64. https://doi.org/10.1016/J.AMEPRE.2012.02.008

Woolley, M. E., Grogan-Kaylor, A., Gilster, M. E., Karb, R. A., Gant, L. M., Reischl, T. M., & Alaimo, K. (2008). Neighborhood Social Capital, Poor Physical Conditions, and School Achievement. Children & Schools, 30(3), 133–145. https://doi.org/10.1093/CS/30.3.133

Zick, C. D., Smith, K. R., Fan, J. X., Brown, B. B., Yamada, I., & Kowaleski-Jones, L. (2009). Running to the Store? The relationship between neighborhood environments and the risk of obesity. Social Science & Medicine, 69(10), 1493–1500. https://doi.org/10.1016/J.SOCSCIMED.2009.08.032

Scientists Propose that Ultra-Processed Foods be Classified as Addictive Substances

Posted on November 6, 2023January 12, 2024 by CNP Staff

An analysis commissioned by the BMJ argues that ultra-processed foods may be addictive
Behaviors around ultra-processed food may meet the diagnostic criteria for substance use disorder
Classifying ultra-processed foods as addictive might open novel approaches to treating food addiction and policies intended to combat it
Ultra-processed food addiction is estimated to occur in 14% of adults and 12% of children (Gearhardt et al., 2023).

We are all familiar with the devastating consequences resulting from the prolonged use of illicit drugs on an individual. In the beginning, the drugs produce pleasurable feelings by activating the brain’s reward system, and novice drug users experience euphoria, relaxation, or reduced stress. This, in turn, trains their brain to associate drug use with pleasure, reinforcing the desire to use drugs again. However, over time the body develops tolerance for the drug, and the individual needs to increase consumption to achieve the same effect continually. Ultimately, this changes the brain’s chemistry, which then becomes highly fixated on drug-induced pleasures and, consequently, less responsive to natural rewards. The desire for the drug becomes uncontrollable, and if this need is not met with more of the drug, unpleasant and difficult withdrawal symptoms occur. To avoid these symptoms, the drug user prioritizes his/her life to be exclusively focused on cycles of drug intake. This is damaging to both psychological and physical health and, in extreme cases, can lead to death. This development is what is usually referred to as addiction.

What is addiction?
A common definition of addiction is any behavior in which an individual has impaired control with harmful consequences. Individuals who recognize that the behavior is harming them or those they care about but still find themselves unable to stop engaging in that harmful behavior are considered addicted. Because addiction, in a way, violates one’s freedom of choice, it can be considered a disorder of motivation (West, 2001).

In certain types of addiction, an individual may experience withdrawal symptoms when the substance or behavior is not accessible. Withdrawal symptoms can vary depending on the specific substance involved, but common symptoms include anxiety, depression, irritability, nausea, vomiting, sweating, muscle aches, and intense cravings. Addiction can devastate an individual’s health, relationships, and overall well-being, making it a significant public health concern.
Can we become addicted to ultra-processed foods?

Although addictions to illicit drugs and alcohol get the most publicity, scientists have also recognized tobacco smoking addiction, gambling addiction, compulsive shopping addiction, smartphone addiction, internet addiction, exercise addiction, addiction to certain prescribed medications such as stimulants or benzodiazepines (medicines used to treat anxiety, sleep disorders, and seizures), pornography addiction, and many others (e.g., O’Brien, 2005; Rakić-Bajić & Hedrih, 2012; Ting & Chen, 2020) (see Figure 1).

Figure 1. Types of addictions

Many recent studies have supported the notion that individuals can display behaviors that meet the definition of addiction toward specific types of food. These behaviors include binge eating, or the inability to control food intake, strong cravings, and many other well-known characteristics of addictions (Gearhardt et al., 2011, 2023; Weingarten & Elston, 1990). Foods most often associated with food addictions are ultra-processed foods.

What are ultra-processed foods?
Almost all foods are processed to some extent. Humans process food to make it edible, preserve it, destroy harmful microorganisms, improve its taste, and for many other reasons. Some foods are not fit to eat without processing, and others would quickly spoil if left unprocessed. It is important to note that ultra-processed foods are not only processed, they have nutritionally lacking or unhealthy substances added.

Ultra-processed foods are formulations made mostly or entirely from derived substances and various additives with few intact unprocessed or minimally processed food components (Hedrih, 2023; Monteiro et al., 2019)

These foods typically contain artificial additives, preservatives, and flavor enhancers. Additives include dyes, color stabilizers, non-sugar sweeteners, de-foaming, anti-caking or glazing agents, emulsifiers, and humectants, among others. Some processes used in preparing ultra-processed foods, such as hydrogenation, hydrolyzation, or extrusion, are exclusively industrial processes that cannot be performed in a regular kitchen (see Figure 2). (Note: More about ultra-processed foods and their effects on the diet-mental health relationship can be found in NP 110: Introduction to Nutritional Psychology Methods through The Center for Nutritional Psychology).

Figure 2. Elements of ultra-processed foods

Examples of ultra-processed foods include instant noodles, artificial sweeteners, artificially sweetened beverages, sugary cereals, microwaveable meals, reconstituted meat products, sweet and savory packaged snacks, pre-prepared frozen dishes, and soft drinks (see Figure 3).

Figure 3. Examples of ultra-processed foods

Ultra-processed foods are linked to various health problems
Ultra-processed foods are often low in nutritional value, high in calories, packed with various unhealthy ingredients, attractively packaged, and marketed intensely (see Figure 3). They are usually created with the intent of having a durable product that is highly palatable but also highly profitable due to the low cost of ingredients (Hedrih, 2023).
Studies have linked the consumption of ultra-processed foods with various health problems. Research indicates that individuals regularly consuming these foods have a higher risk of obesity, type 2 diabetes, heart disease, certain types of cancer, and depression. (Monteiro et al., 2018; Samuthpongtorn et al., 2023). Despite this, the sales of these foods and their share in the dietary calorie intake are rising, both in high- and middle-income countries (Monteiro et al., 2019).

The analysis
Professor Ashley Gaerhart and her colleagues start their analysis by noting that two reviews of 281 studies from 36 different countries found that 14% of adults and 12% of children show indications of being addicted to food. These levels are similar to shares of the population addicted to tobacco and alcohol. Studies also showed that 50% of people diagnosed with binge eating disorder and 32% of people struggling with obesity who are undergoing bariatric surgery may, indeed, suffer from food addiction (Figure X).

Figure 4. Food addiction statistics

These authors then analyze what might make a food addictive. According to them, not all foods have addictive potential. Research results indicate that foods with high levels of refined carbohydrates or added fats, such as sweets and salty snacks, are the most strongly implicated in addiction behaviors, such as losing control over consumption, excessive intake, and continued use despite negative consequences.

Foods with high levels of refined carbohydrates or added fats, such as sweets and salty snacks, are the most strongly implicated in addiction behaviors

What makes food addictive?
The foods described above are all ultra-processed. Unlike natural foods, they often contain high concentrations of both fats and carbohydrates. This is unlike natural or minimally processed foods with high carbohydrate content but little or no fat (e.g., apples) or high-fat content with little or no carbohydrates (e.g., certain types of fish or meat).

Even in rare cases when natural foods do contain large amounts of both fat and carbohydrates (e.g., almonds), they typically require extensive digestion before the body can use them. For example, almond fat remains encapsulated in cell walls even after chewing, which means it is unavailable to the body at the early stages of digestion. This is important because a natural and minimally processed food item, like almonds, takes a long time to break down, so nutrients will be absorbed only in the lower intestine and, therefore, do not trigger the release of dopamine (a neurotransmitter linked to feelings of reward and pleasure). Conversely, when an ultra-processed food undergoes digestion, it readily breaks down, and nutrients rapidly enter the bloodstream through the upper intestine, thereby triggering dopamine signaling, which ultimately induces feelings of pleasure.

Unlike natural foods, fats and carbohydrates in ultra-processed foods become swiftly available to the body during digestion which affects the pleasure response of the brain, contributing to the addictive nature of these foods. The reward of obtaining both of these micronutrients simultaneously is greater than the effect that either of them, individually, can have. This alters the brain’s reward processing system and triggers the changes, leading to addiction. Various additives found in ultra-processed foods that improve their taste and mouthfeel further strengthen these effects (Figure 5).

Figure 5. Differences in body processing of ultra-processed foods and unprocessed foods

This mechanism is similar to the one determining the addictiveness of drugs. Drugs that act faster also tend to be more addictive. Studies indicate that flavor-enhancing additives in products, such as cigarettes, also increase their addictive potential (see Figure 6).

Figure 6. Relationship between flavor-enhancing additives and addictive potential

But what do the critics say?
Not all scientists agree that food addiction is a real addiction. Unlike alcohol, tobacco, or cocaine, we need food to survive. Craving for food already has a name – hunger. Fats and carbohydrates are macronutrients that are needed to fuel the body in considerable amounts. Can an intense desire to consume substances needed for survival really be considered an addiction?

The authors of this analysis note that there is also the question of the addictive chemical. All other substances are addictions to a specific chemical, but such chemical has not been identified for foods. Substances such as alcohol, nicotine, or illicit drugs activate the brain’s reward system directly, but fat and carbohydrates do not do that.

However, these researchers argue that, although fat and carbohydrates do not activate the brain’s reward system directly, they can still activate it to a magnitude similar to alcohol and nicotine. The presence of an addictive chemical might not be crucial for identifying an addiction, as the authors theorize there are many addictive chemicals with the ability to cause addiction in unknown doses and intake levels.

What should be done?
Based on all this, the authors of this analysis propose that ultra-processed foods be classified as addictive substances. They believe this would increase focus on the culpability of manufacturers of these foods, much like how classifying cigarettes as addictive helped combat smoking.

They believe that research should focus on clearly evaluating how complex features of ultra-processed foods combine to increase their addictive potential. That research can then be used to delineate between addictive and non-addictive foods based on those features. Studies should also focus on fully understanding the mechanisms linking the consumption of these foods to obesity and adverse health outcomes.

Tackling food addiction through policies
Authors of the analysis also believe that governments should combat food addiction in the same way they tackled addiction to cigarettes – through a suite of policies targeting foods with high addiction potential, notably ultra-processed foods. Examples of such policies include special taxes on ultra-processed foods and beverages, mandatory or voluntary front-of-pack or shelf labeling systems, and mandatory or voluntary reformulations of the food supply, particularly focused on banning the use of substances, increasing the addictive effects.

However, the authors also note that the consumption of ultra-processed foods tends to be particularly high in disadvantaged neighborhoods because these foods are inexpensive. There is limited if any, availability of lower-calorie, healthier foods in those areas, and those people consume the higher-calorie, ultra-processed foods instead. In light of this fact, tackling the issue of food addiction should be done with care and in a way that does not create food insecurity.

Additionally, including ultra-processed food addiction diagnosis in clinical care would improve access to support and enable the development of treatments to reduce compulsive patterns of ultra-processed food intake. Drugs already exist that show promise in helping overcome food addiction.

Conclusion
Overall, the analysis makes a strong case for the reality of ultra-processed food addiction. The ongoing obesity pandemic (Wong et al., 2022) makes what they say important. The authors propose that researchers focus on fully understanding the mechanisms through which addictive behaviors toward specific foods occur.

They also propose that policymakers approach legislation on food addiction similarly to nicotine, tobacco, and cigarette addiction – through recognizing ultra-processed food addiction as a disorder, through policies targeting the production and the sale of addictive foods, preventing the use of substances or processes that increase the addictiveness of food items, and other measures. Still, this should be done with care and in a way that does not reduce food security for anyone. Ultra-processed foods are still foods, and people need food to survive.

The analysis paper “Social, clinical, and policy implications of ultra-processed food addiction” was authored by Ashley N. Gearhardt, Nassib B. Bueno, Alexandra G. DiFeliceantonio, Christina A. Roberto, Susana Jimenez-Murcia, and Fernando Fernandez-Aranda.

References
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

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

Hedrih, V. (2023). Women Consuming Lots of Artificially Sweetened Beverages Might Have a Higher Risk of Depression, Study Finds. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/women-consuming-lots-of-artificially-sweetened-beverages-might-have-a-higher-risk-of-depression-study-finds/

Monteiro, C. A., Cannon, G., Levy, R. B., Moubarac, J. C., Louzada, M. L. C., Rauber, F., Khandpur, N., Cediel, G., Neri, D., Martinez-Steele, E., Baraldi, L. G., & Jaime, P. C. (2019). Ultra-processed foods: What they are and how to identify them. In Public Health Nutrition (Vol. 22, Issue 5, pp. 936–941). Cambridge University Press. https://doi.org/10.1017/S1368980018003762

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

O’brien, C. P. (2005). Benzodiazepine Use, Abuse, and Dependence. J Clin Psychiatry, 66(2).

Rakić-Bajić, G., & Hedrih, V. (2012). Prekomjerna upotreba interneta, zadovoljstvo životom i osobine ličnosti [Excessive use of the internet, life satisfaction and personality factors]. Suvremena Psihologija, 15(1), 119–131.

Ting, C. H., & Chen, Y. Y. (2020). Smartphone addiction. Adolescent Addiction: Epidemiology, Assessment, and Treatment, 215–240. https://doi.org/10.1016/B978-0-12-818626-8.00008-6

Weingarten, H. P., & Elston, D. (1990). The phenomenology of food cravings. Appetite, 15(3), 231–246. https://doi.org/10.1016/0195-6663(90)90023-2

West, R. (2001). Theories of addiction. Addiction, 96(1), 3–13. https://doi.org/10.1046/J.1360-0443.2001.96131.X

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

Risk Factors and Prevalence of Eating Disorders in Male Athletes

Posted on October 28, 2023November 7, 2023 by CNP Staff

There are many factors that can contribute to the breakdown of a healthy relationship between an athlete’s diet and mental health, putting them at risk for Eating Disorders (ED). In fact, ED are one of the most common psychiatric pathologies in elite athletes (Karrer et al., 2020).

ED are defined as “behavioral conditions characterized by severe and persistent disturbance in eating behaviors and associated distressing thoughts and emotions” (American Psychiatric Association, 2021). Athletes of both sexes are more likely than their non-athlete peers to develop eating disorders (Martinsen & Sundgot-Borgen, 2013; Mancine et al., 2020).

However, the prevalence of these disorders in male athletes is largely overlooked, as most research is directed towards ED in female athletes (Karrer et al., 2020), and these disorders are stereotyped as a “female problem” (Eichstadt et al., 2020). This commonly held stereotype, male gender norms, and the athletic identity of a male being “strong, stoic, and self-sacrificing” may deter male athletes who are suffering with these disorders from seeking help (Eichstadt et al., 2020).

The prevalence of these disorders in male athletes is largely overlooked, most research is directed towards ED in female athletes

There are several gender-specific differences related to the prevalence, risk factors, and potential interventions for ED in athletes. This article aims to shed light on the specificities of ED in male athletes to increase awareness and education for coaches, trainers, parents, and the athletes themselves.

Prevalence and Risk Factors
Most research assessing the risk factors of ED in athletes has been examined primarily in female athletes, but there have been a few studies looking specifically at ED in male athlete populations.

About 20% of male athletes adopt risk behaviors for eating disorders (RBED) as a means to improve their body composition (Fortes et al., 2020). Improved sport performance is the most frequently stated reason for dieting among male athletes, with between 84-91% of elite athletes believing that decreased weight could be attributed to better sport performance (Karrer et al., 2020). These risk behaviors can include long periods without food intake, using medication for appetite suppressant or diuretic effects, wearing clothing that contributes to extra dehydration, and self-induced vomiting (Fortes et al., 2020) (see Figure 1).

Figure 1. Prevalence and risk factors associated with ED in male athletes

There are several risk factors that are associated with the prevalence of ED in male athletes. For example, male athletes who participate in “weight-sensitive” sports may be at higher risk for developing ED than male athletes who participate in non-weight sensitive sports (Karrer et al., 2020). Athletes who compete in a sport, such as wrestling, that divides athletes into “weight classes” report more psychological pressure to be lean, a higher drive for thinness, higher levels of dietary constraint, and higher levels of bulimic behaviors than athletes who competed in less weight-sensitive sports, such as soccer or other team sports (Karrer et al., 2020).

Athletes who compete in sports such as wrestling, that divided into “weight classes,” reported more psychological pressure to be lean

One study found up to 50% of male athletes who participated in weight-sensitive sports had disordered eating (DE) (Rouselet et al., 2017). The pressures for these athletes to enter and remain in a specific weight class may “normalize” certain practices that would be considered DE. The male athletes who suffer from these disorders are at risk for being overlooked, and sometimes even positively reinforced, for these dangerous behaviors (Eichstadt et al., 2020).

One study found up to 50% of male athletes who participated in weight-sensitive sports had disordered eating (DE)

Psychological features of athletes may also serve as a risk factor for developing ED, DE and RBED. Whereas ED involve psychological disorders that are recognized by the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5), DE is a condition that involves behaviors similar to those found in ED to a lesser intensity or frequency, but that can still be dangerous to the individual (Fuller, 2022).

Studies show a direct linear relationship between competitive anxiety, defined as “the tendency to perceive competitive situations as threatening and to respond to them with feelings of apprehension and tension” (Martens, 1977), and risk behaviors for eating disorders (RBED) in male athletes. Specifically, the stress perception an athlete can feel both during competition, and also the negative thoughts about the competition, were associated with the “triggering” of RBED (Fortes et al., 2020). Other psychological risk factors can include low self-esteem (Dakanalis et al., 2016), depression (Grossbard et al., 2013), and the fear of negative evaluation (Dakanalis et al., 2014) (see Figure 2).

Figure 2. Psychological risk factors in athletes

Consequences of ED in Male Athletes
The literature on athlete’s health and performance consequences of ED is mainly focused on female athletes, although males also suffer health consequences. These consequences may be harder to recognize in males, as they don’t have the obvious physical symptoms of low energy availability (EA) such as amenorrhea in female athletes (Karrer et al., 2020), and are not yet well understood (Mountjoy et al., 2018).

Some health concerns that have been identified in male athletes include reduction in testosterone (Mountjoy et al., 2018) and reduced bone mineral mass (Karrer et al., 2020). In addition to the physical health challenges, low testosterone, DE, depression, and stress may affect each other reciprocally (Karrer et al., 2020). Furthermore, EDs have the highest fatality rate of any mental health disorder, which is shown to be even higher in men than it is for women. One in five patients with anorexia nervosa, a type of ED, dies by suicide (Markey et al., 2022) (see Figure 3).

Figure 3. Consequences of ED in Male Athletes

EDs have the highest fatality rate of any mental health disorder

Treatment and Prevention for ED in Male Athletes
Because of the dire consequences and outcomes that accompany EDs, it is necessary to ensure proper treatment for athletes who are suffering from these disorders. However, the ability to recognize and report these disorders in athletes, especially males, is challenging. Studies suggest that the current tools that are used to assess eating disorders among the general population are not appropriate for use with athletes for several reasons (Rousselet et al., 2017).

Current tools used to assess eating disorders among the general population are not appropriate for use with athletes for several reasons

The preoccupation with dieting and food behaviors that is generally seen as “disordered” may be part of the sporting culture, and therefore may not always point to ED (Karrer et al., 2020). Also, BMI which is often used as an indicator for ED may be skewed for athletes, as increased muscle mass will increase an athlete’s BMI, regardless of their body fat percentage (Karrer et al., 2020). In other words, an athlete with a low body fat percentage may be suffering from ED, but will not be diagnosed as such because their muscle mass gives the illusion of an elevated BMI, and therefore they will not meet the criteria. And finally, male athletes are likely to underreport their struggles with ED in self-report questionnaires (Rousselet et al., 2017).

Because of these challenges with recognizing ED in male athletes, it may be important to equip athletes with the skills necessary to appropriately confront these conditions. Some researchers are claiming that coping skills may be able to mediate the relationship between competitive anxiety and RBED in athletes. Helping athletes develop coping skills to manage their competitive anxiety under stressful conditions is a key concept of sport psychology training.

Coping skills may be able to mediate the relationship between competitive anxiety and RBED in athletes

These skills help athletes to regulate their emotions that are caused by stressors, such as a big game or competition (Pons et al., 2018). The use of coping strategies in athletes has been shown to mediate the relationship between competitive anxiety and negative emotions, and promote adaptive behaviors, in an effort to improve sport performance (Wadey et al., 2014; Pons et al., 2018). Beyond improvement in performance, coping skills may be able to be used as a tool to help athletes avoid RBED (Fortes et al., 2020).

Coping strategies in athletes mediate the relationship between competitive anxiety and negative emotions, improving sports performance

Although this may be one tool, the use of coping skills should not be the only preventative and treatment measure for athletes who are suffering from ED. The International Olympic Committee releases regular consensus statements that reflect the updated information on treatment options available for athletes who suffer from ED.

How Coaches and Sport Psychology Professionals Can Help
Despite the lack of recognition in research, male athletes are at risk for ED, DE, and RBED. By understanding certain risk factors that contribute to the development of RBED, such as sport type and psychological factors, parents, coaches, and sport psychology professionals may be able to take appropriate and necessary action to help athletes who may be at risk for developing such disorders.

References

American Psychiatric Association (2021). What Are Eating Disorders? https://www.psychiatry.org/patients-families/eating-disorders/what-are-eating-disorders

Dakanalis, A., Clerici, M., Caslini, M., Gaudio, S., Serino, S., Riva, G., & Carrà, G. (2016). Predictors of initiation and persistence of recurrent binge eating and inappropriate weight compensatory behaviors in college men. International Journal of Eating Disorders, 49(6), 581–590. https://doi.org/10.1002/eat.22535

Dakanalis, A., Timko, C. A., Favagrossa, L., Riva, G., Zanetti, M. A., & Clerici, M. (2014). Why Do Only a Minority of Men Report Severe Levels of Eating Disorder Symptomatology, When so Many Report Substantial Body Dissatisfaction? Examination of Exacerbating Factors. Eating Disorders, 22(4), 292–305. https://doi.org/10.1080/10640266.2014.898980

Eichstadt, M., Luzier, J., Cho, D., & Weisenmuller, C. (2020). Eating Disorders in Male Athletes. Sports Health: A Multidisciplinary Approach, 12(4), 327–333. https://doi.org/10.1177/1941738120928991

Fortes, L. D. S., Nascimento Junior, J. R. A. D., Freire, G. L. M., & Ferreira, M. E. C. (2020b). Does coping mediate the relationship between competitive anxiety and eating disorders in athletes? Psicologia – Teoria e Prática, 22(3). https://doi.org/10.5935/1980-6906/psicologia.v22n3p74-91

Fuller, K. (2022, June 29). Difference Between Disordered Eating and Eating Disorders. Verywell Mind. https://www.verywellmind.com/difference-between-disordered-eating-and-eating-disorders-5184548

Grossbard, J. R., Atkins, D. C., Geisner, I. M., & Larimer, M. E. (2013). Does depressed mood moderate the influence of drive for thinness and muscularity on eating disorder symptoms among college men? Psychology of Men & Masculinity, 14(3), 281–287. https://doi.org/10.1037/a0028913

Karrer, Y., Halioua, R., Mötteli, S., Iff, S., Seifritz, E., Jäger, M., & Claussen, M. C. (2020b). Disordered eating and eating disorders in male elite athletes: a scoping review. BMJ Open Sport & Exercise Medicine, 6(1), e000801. https://doi.org/10.1136/bmjsem-2020-000801

Mancine, R., Kennedy, S., Stephan, P., & Ley, A. (2020). Disordered Eating and Eating Disorders in Adolescent Athletes. Spartan Medical Research Journal. https://doi.org/10.51894/001c.11595

Markey, C. (2022). Eating Disorders Affect Boys and Men Too. U.S. & World Report News. https://health.usnews.com/health-news/blogs/eat-run/articles/eating-disorders-and-body-image-issues-in-boys-and-men

Martens, R. (1977). Sport Competition Anxiety Test. Human Kinetics Publishers.

Martisen, M., & Sundgot-Borgen, J. (2013). Higher Prevalence of Eating Disorders among Adolescent Elite Athletes than Controls. Medicine & Science in Sports & Exercise, 45(6), 1188–1197. https://doi.org/10.1249/mss.0b013e318281a939

Mountjoy, M., Sundgot-Borgen, J. K., Burke, L. M., Ackerman, K. E., Blauwet, C., Constantini, N., Lebrun, C., Lundy, B., Melin, A. K., Meyer, N. L., Sherman, R. T., Tenforde, A. S., Klungland Torstveit, M., & Budgett, R. (2018). IOC consensus statement on relative energy deficiency in sport (RED-S): 2018 update. British Journal of Sports Medicine, 52(11), 687–697. https://doi.org/10.1136/bjsports-2018-099193

Rousselet M, Guerineau B, Paruit MC, et al. Disordered eating in French high-level athletes: association with type of sport, doping behavior, and psychological features. Eat Weight Disord 2017;22:61–8

Women Consuming Lots of Artificially Sweetened Beverages Might Have a Higher Risk of Depression, Study Finds

Posted on October 13, 2023November 13, 2023 by CNP Staff

What is food processing?
Almost all foods are processed to some extent (Monteiro et al., 2019). Humans process food to preserve it so that it would not spoil, to make it edible, to destroy harmful microorganisms or chemical compounds, to improve its taste, and for many other reasons.

Many foods are not edible unless processed. For example, cassava, a root vegetable that is one of the staple foods in many parts of the world, contains large amounts of cyanogenic glycosides. If consumed raw, these compounds can release the poison cyanide. Thorough processing, which involves peeling, soaking, and cooking, is necessary to make cassava safe to eat. This thorough processing turns a poisonous plant into an important source of nutrients for humans.

Many foods are not edible unless processed

Other types of food would readily spoil without processing. For example, left on their own, meat, fish, and many fruits and vegetables would spoil very quickly in most environments. However, drying, curing, and canning allow us to preserve these foods for long periods, ensuring food is available throughout the year. Food processing such as this is crucial for creating a stable and dependable human food supply. Due to all this, it is not helpful to be critical of food processing in general. Food processing is necessary.

It is worth noting, however, that the way humans process foods – even the same food – can vary significantly depending on various factors, for example, the setting. Processing food at home (e.g., cooking a meal) differs from processing food on an industrial level (e.g., preparing the same meal industrially for mass distribution). The latter involves specific manufacturing techniques and often uses additives (e.g., colorants, flavor enhancers, preservatives, pesticides, etc.) even in relatively unprocessed foods.

With regard to food processing, researchers have developed classifications of various food items

The NOVA food classification system
With regard to processing, researchers have developed various classifications of food items. One very popular classification is the NOVA classification system (Monteiro et al., 2018), which groups foods into four categories according to the extent and purpose of processing they undergo.

The NOVA system categories are (see Figure 1):

Group 1. Unprocessed or minimally processed foods – natural foods altered only by processes that include removing inedible or unwanted parts and preparation for storage (e.g., vacuum-packaging, drying, pasteurization, refrigeration, freezing, roasting…)
Group 2. Processed culinary ingredients – derived from group 1 foods and processed to make durable products suitable for kitchens to prepare, season, and cook group 1 foods. These processes include milling, grinding, refining, pressing, and drying. Examples are oils, butter, sugar, and salt.
Group 3. Processed foods – created by adding salt, oil, sugar, or other substances from group 2 to group 1 foods. Examples include bottled vegetables, canned fish, fruits in syrup, cheeses, and freshly made bread.
Group 4. Ultra-processed foods (UPFs) are formulations made mostly or entirely from substances derived from foods and additives with little if any, intact group 1 food (Monteiro et al., 2018).

Figure 1. Nova food classification system and examples of foods in each class

Why are ultra-processed foods special?
Ultra-processed foods (UPFs) are heavily processed before consumption. They typically contain numerous artificial additives, preservatives, and flavor enhancers. These additives include dyes, color stabilizers, non-sugar sweeteners, de-foaming, anti-caking or glazing agents, emulsifiers, humectants, and many others. Some processes used in preparing these foods, such as hydrogenation, hydrolyzation, or extrusion, are exclusively industrial processes that cannot be performed in a regular kitchen (see Figure 2).

Figure 2. Elements in ultra-processed foods

Ultra-processed foods are often low in nutritional value, high in calories, and packed with unhealthy ingredients like refined sugars, trans fats, and excessive sodium. Examples of ultra-processed foods include instant noodles, artificial sweeteners, artificially sweetened beverages, sugary cereals, microwaveable meals, reconstituted meat products, sweet and savory packaged snacks, pre-prepared frozen dishes, and soft drinks. The overall purpose of ultra-processing is to create a durable product that is highly palatable but also highly profitable due to the low cost of ingredients. Ultra-processed foods usually have attractive packaging and are marketed intensely (see Figure 3).

Figure 3. Characteristics of ultra-processed foods

Ultra-processed foods and health risks
One of the concerning aspects of ultra-processed foods is their link to various health problems. Studies have linked the regular consumption of these foods with a higher risk of obesity, type 2 diabetes, heart disease, and certain types of cancer. Ultra-processed foods often lack essential nutrients like fiber, vitamins, and minerals important for overall health.

Despite these health risks, over half of the dietary energy consumed by individuals from high-income countries such as the USA, Canada, or the UK comes from ultra-processed foods. In middle-income countries such as Brazil, Mexico, and Chile, the share of dietary calories from ultra-processed foods is estimated to be between 20% and 33%. Additionally, the sales of these foods are growing by about 1% per year in high-income countries and up to 10% per year in middle-income countries (Monteiro et al., 2019) (see Figure 4).

Figure 4. Consumption of UPFs by Country.

Over half of the dietary energy consumed by individuals from high-income countries such as the USA, Canada, or the UK comes from ultra-processed foods

The current study
Study author Chatpol Samuthpongtorn and his colleagues wanted to examine whether consuming ultra-processed foods might be associated with the risk of depression. They were aware of findings linking the consumption of ultra-processed foods with many different diseases. Still, they noted that many studies that reported these findings relied only on short-term dietary data and could not account for various factors that could have influenced the results. They also wanted to know if any specific ultra-processed foods are linked to depression and whether the timing of ultra-processed food consumption might play a role.

The study participants were 31,712 females in the Nurses’ Health Study II conducted between 2003 and 2017. Participants were between 42 and 62 years old at the start of the study.

Are any specific ultra-processed foods linked to depression, and does the timing of ultra-processed food consumption play a role?

The procedure
Participants completed a food frequency questionnaire based on the NOVA classification every four years. This questionnaire asked participants to report how often they consumed various foods from the four NOVA categories. The part about ultra-processed foods included questions about the frequencies of consuming ultra-processed grain foods, sweet snacks, ready-to-eat meals, fats and sauces, ultra-processed dairy products, savory snacks, processed meat, beverages, and artificial sweeteners.

Participants reported whether they were diagnosed with depression and whether they consumed antidepressants regularly. Researchers also collected data on participants’ ages, total caloric intake, body mass index, physical activity, smoking status, menopausal hormone therapy, alcohol consumption, chronic diseases, marital status, family income, and other characteristics (see Figure 5).

Figure 5. Food Frequency Questionnaire (FFQ) every four years, and participant reports

Individuals eating more ultra-processed foods had higher body weight, smoked more, and were in poorer health

Participants who reported eating ultra-processed foods most frequently had greater body mass index, smoked more often, and suffered from diseases like diabetes, hypertension, and dyslipidemia compared to those who reported eating ultra-processed foods less often. These individuals were also less likely to exercise regularly.

Dyslipidemia is a medical condition characterized by abnormal levels of lipids (fats) in the blood, typically involving elevated cholesterol and/or triglycerides, which can increase the risk of cardiovascular diseases.

Individuals frequently consuming ultra-processed foods were more often depressive
Depending on the definition of depression used, there were 2122 (using the stricter definition) or 4840 (using the broader definition) participants suffering from depression in the study. In both cases, participants who ate ultra-processed foods most frequently (the top 20% of the sample with the highest ultra-processed food consumption) were more likely to suffer from depression compared to those who ate the ultra-processed foods the least often (the bottom 20% on ultra-processed food consumption).

Participants who ate ultra-processed foods most frequently were more likely to suffer from depression than those who ate ultra-processed foods least often

Depending on the definition of depression, the top consumers of ultra-processed foods had a 34% or 49% higher likelihood of depression compared to participants who consumed these types of food the least. This finding held when study authors considered various other factors and calculated the association between ultra-processed food consumption at one point and depression four years later (see Figure 6).

Figure 6. Research findings

The top consumers of ultra-processed foods had a higher likelihood of depression than participants who consumed these types of food the least

Sweetened beverages and artificial sweeteners are the ultra-processed foods most strongly linked with depression
Next, the study authors explored which ultra-processed foods are most linked with depression. Are all types of ultra-processed foods equally associated with depression, or is the high consumption of some specific types of ultra-processed foods linked with a higher likelihood of depression?

Analyses showed that only high consumption of artificially sweetened beverages and artificial sweeteners is associated with an increased likelihood of depression. These findings, however, don’t necessarily imply that all other UPFs consumed in the longitudinal study are exempt from having undesired effects on psychological well-being.

Analyses showed that only high consumption of artificially sweetened beverages and artificial sweeteners is associated with an increased likelihood of depression

Additional analyses indicated that individuals who reduced their intake of ultra-processed foods by at least three servings per day were at a lower risk of depression compared to individuals with a relatively stable intake of these foods in each four-year period.

Conclusion
Overall, the study results suggest that frequent intake of ultra-processed foods is associated with an increased risk of depression. This is particularly the case with high intake of artificially sweetened beverages and artificial sweeteners. While the nature of this association remains unknown, the large number of participants involved in this study and the fact that the association held across multiple years makes these findings particularly strong.

Given the current increase in the number of people suffering from depression in many world countries (e.g., Steffen et al., 2020; Weinberger et al., 2018) and also the increase in ultra-processed foods consumption (Monteiro et al., 2019; Samuthpongtorn et al., 2023), these findings could be used to inform policymakers and the general public about the importance of healthy food choices and how seemingly innocuous dietary decisions may have long-lasting health consequences.

The paper “Consumption of Ultraprocessed Food and Risk of Depression” was authored by Chatpol Samuthpongtorn, Long H. Nguyen, Olivia I. Okereke, Dong D. Wang, Mingyang Song, Andrew T. Chan, and Raaj S. Mehta.

References
Monteiro, C. A., Cannon, G., Levy, R. B., Moubarac, J. C., Louzada, M. L. C., Rauber, F., Khandpur, N., Cediel, G., Neri, D., Martinez-Steele, E., Baraldi, L. G., & Jaime, P. C. (2019). Ultra-processed foods: What they are and how to identify them. In Public Health Nutrition (Vol. 22, Issue 5, pp. 936–941). Cambridge University Press. https://doi.org/10.1017/S1368980018003762

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

Steffen, A., Thom, J., Jacobi, F., Holstiege, J., & Bätzing, J. (2020). Trends in the prevalence of depression in Germany between 2009 and 2017 based on nationwide ambulatory claims data. Journal of Affective Disorders, 271, 239–247. https://doi.org/10.1016/J.JAD.2020.03.082

Weinberger, A. H., Gbedemah, M., Martinez, A. M., Nash, D., Galea, S., & Goodwin, R. D. (2018). Trends in depression prevalence in the USA from 2005 to 2015: widening disparities in vulnerable groups. Psychological Medicine, 48(8), 1308–1315. https://doi.org/10.1017/S0033291717002781

Gut Microbiota Play Crucial Role in Mediating Effects of Western Diet

Posted on August 8, 2023January 24, 2025 by CNP Staff

Introduction

The past several decades have seen the rise of an obesity pandemic that is ongoing worldwide. While obese individuals were quite rare just a century ago, 2015-2018 estimates for the U.S. state that more than two-thirds of the adult population is overweight or obese (Wong et al., 2022). Determining the causes of this increase in obesity rates has attracted much research attention. Studies have revealed a complex interplay between diet components, environmental factors, and previously unknown psychological and physiological mechanisms resulting in overeating and obesity in the long term. These novel studies on the intersection of nutrition and psychology are part of a developing field of science called nutritional psychology (The Center for Nutritional Psychology, 2023) (see Figure 1).

Figure 1. Diet, environment, psychological, and physiological factors in nutritional psychology

There is a complex interplay between diet, environmental factors, and psychological and physiological mechanisms resulting in overeating and obesity

Gut microbiota and the microbiota-gut-brain axis

The human gut microbiome consists of trillions of microorganisms that live in the human intestinal tract. These microorganisms play a key role in digesting the food we eat. However, their influence extends beyond the gut, encompassing crucial roles in metabolic regulation, body weight maintenance, and immune system modulation.

This growing body of evidence suggests that these gut microorganisms also profoundly impact brain functions, mood, cognition, and emotional well-being (Zhu et al., 2023). This topic is explored in continuing education curricula within nutritional psychology — particularly how the gut microbiota and the gut-brain axis interconnect with the diet-mental health relationship to influence psychological functioning and experience, shedding light on its potential therapeutic implications for mental health outcomes.

This growing body of evidence suggests that gut microorganisms profoundly impact brain functions, mood, cognition, and emotional well-being

Scientists have recently discovered a communication pathway connecting the gut microbiome and the brain. This pathway is called the microbiota-gut-brain axis. It is based on small proteins called cytokines and a number of other biomolecules, including the hormone cortisol, short-chain fatty acids (SCFAs), tryptophan, and others.

The Western diet

The Western diet is a modern dietary pattern prevalent in Western societies, characterized by a high intake of processed and hyperpalatable foods with increased contents of fat, sugary snacks, and refined grains. It typically includes low consumption of fruits, vegetables, unprocessed-high-quality proteins, nuts, and seeds. This diet’s excessive reliance on added sugars and unhealthy fats has been linked to an increased risk of obesity, metabolic syndrome, and various chronic diseases.

Studies have indicated that feeding mice a Western diet causes inflammation in the region of the brain called the hypothalamus (Heiss et al., 2021; Thaler et al., 2013). Inflammation of the hypothalamus damages the neurons and leads to the formation of scars made of glial cells. This is called gliosis. Inflammation of the hypothalamus often happens before a mouse starts gaining weight. Due to this, scientists believe it might cause weight gain by causing leptin resistance.

Studies have indicated that feeding mice a Western diet causes inflammation of the region of the brain called the hypothalamus

Leptin and leptin resistance

Leptin is a hormone produced by fat cells during eating. It regulates appetite and body weight and is produced in proportion to the amount of fat in the body. Leptin concentrations inform the brain of how much fat is stored. Increased leptin concentrations (normally caused by an abundance of body fat) “tell” the brain to decrease food intake and increase energy expenditure.

Leptin is a hormone produced by fat cells that regulate appetite and body weight

Factors such as chronic inflammation or eating high-fat diets (HFDs) may cause the body to be less receptive to leptin. This is called leptin resistance. Leptin resistance results in disrupted appetite and energy regulation, i.e., the brain does not reduce food intake in spite of the abundance of body fat. This can contribute to obesity and cause difficulty controlling body weight (Thaler et al., 2013) (see Figure 2).

Figure 2. Normal leptin cycle versus leptin resistance.

Gliosis, leptin resistance, and gut microbiota

Microglia are a type of immune cell in the central nervous system that helps protect and maintain the brain and spinal cord by detecting and responding to potential threats or damage. Studies have shown that activation of microglia cells that happens during inflammation of the hypothalamus might be causing leptin resistance. Removing these microglia cells from the hypothalamus has improved sensitivity to leptin. Improved sensitivity to leptin allows the brain to recognize when enough fat is stored in the body and reduce food intake.

Studies have shown that the activation of microglia cells that happens during inflammation of the hypothalamus might be causing leptin resistance

Intriguingly, according to the scientific evidence presented in our recent NP 120 course, it has been discovered that the gut microbiota plays a significant role in regulating the development and maturation of microglia cells and influencing their function. Although the mechanism of this action remains unknown, it has led scientists to believe there might be a link between hypothalamus inflammation and gut microbiota (Heiss et al., 2021) (see Figure 3).

Figure 3. Link of Gut Microbiota in regulating development and maturation of microglia cells

There might be a link between hypothalamus inflammation and gut microbiota (Heiss et al., 2021)

The current study

Study author Christina N. Heiss and her colleagues wanted to know whether mice that lack gut microbiota are protected against diet-induced inflammation of the hypothalamus. They noted previous studies’ results showing mice with depleted gut microbiota and those treated with antibiotics to be protected from diet-induced obesity.

In other words, they noted that mice that consume a Western diet, a diet that normally leads to obesity in mice, do not become obese if microbiota are not present in their guts. This might be because the absence of microbiota prevents inflammation of the hypothalamus, which would, in turn, prevent leptin resistance from developing. If this is the case, the mechanism for preventing overeating based on leptin would remain intact, preventing mice from becoming obese. Alternatively, it could be that, without microbiota, the guts of mice could not digest complex nutrients from the food they eat, thus substantially reducing the amount of nutrition they can derive from food. In this case, obesity would be avoided because their bodies cannot use their food. But which of these is the case?

The procedure

The study authors used three groups of male mice, 10-13 weeks old – conventionally raised mice, germ-free mice, and antibiotic-fed mice. They used several genetic groups of mice, including a strain of genetically engineered mice that allow for controlled and regulated manipulation of specific genes in specific tissues (Tamoxifen-inducible Cre mice).

In the scope of the experiments, researchers fed mice either a chow diet or a Western diet. Western diet was given for either 2 days, 1 week, or 4 weeks, depending on the experiment conducted in the scope of the study.

The chow diet for mice is a nutritionally balanced and standardized diet formulated to provide essential nutrients required for the health and growth of laboratory mice. It typically consists of a combination of proteins, carbohydrates, fats, vitamins, and minerals in pellet or block form. The Western diet used in this study was high in fat and sucrose, with 40% of calories coming from fat.

All food for mice was sterilized, i.e., underwent procedures that killed all microorganisms in the food before mice ate it. The chow diet was sterilized in an autoclave, which uses high pressure and steam to kill microorganisms. The Western diet food was irradiated, i.e., radiation was used to kill microorganisms.

The mice

Conventionally raised mice were laboratory mice kept in regular conditions and fed a normal diet for laboratory mice. They have normal gut microbiota.

Germ-free mice are created through techniques that ensure they do not acquire gut microbiota from birth through their entire lifetimes. They are typically born using cesarean section deliveries of pregnant mice in a sterile environment. This is done to prevent the transfer of microbes during birth. After that, they are kept in specialized sterile isolation spaces called isolators or bubbles that maintain a controlled germ-free environment.

These isolators provide filtered air, sterile food, and autoclaved water to prevent microbial contamination. Researchers raising these mice take special care to maintain strict barrier measures, including specialized clothing and equipment, to prevent the unintentional introduction of microorganisms. They regularly monitor these mice’s bodily fluids and tissues through special techniques to ensure the absence of any detectable microorganisms. Germ-free mice are typically leaner than conventionally raised mice and, consequently, have lower leptin levels in circulation.

Antibiotic-fed mice in this study had 1g of ampicillin and 0.5g of neomycin added per liter of their drinking water. Ampicillin and neomycin are antibiotics. Researchers kept the drinking water with antibiotics added in bottles protected from light. They prepared a new solution every second day. Researchers started giving this water with antibiotics to mice three days before changing their regular diet to a Western diet.

Mice without gut microbiota are protected from diet-induced inflammation of the hypothalamus

Results showed that conventionally raised mice fed a Western diet for 1 week developed gliosis in the hypothalamus. Inflammation indicators were increased in these mice in the part of the hypothalamus called the arcuate nucleus compared to conventionally raised mice fed regular mice food (chow) (see Figure 4).

Figure 4. Conventionally raised mice fed a Western diet developed gliosis in the hypothalamus

When researchers examined germ-free mice and mice whose gut microbiota were depleted using antibiotic treatment (antibiotic-fed mice), results showed that these mice also showed no increase in inflammation indicators or the proliferation of microglia cells after eating a Western diet for a week.

Gliosis in the hypothalamus leads to greater gain in body weight and fat mass

The study authors also wanted to know whether gliosis in the hypothalamus caused by a Western diet leads, in turn, to increased body weight and fat mass accumulation in mice. To test that, they fed conventionally raised mice and antibiotic-fed mice a Western diet for 4 weeks.

Results showed that conventionally raised mice fed a Western diet gained more body weight and fat mass than antibiotic-fed mice. Compared to antibiotic-fed mice, they also had increased hypothalamus inflammation indicators and increased numbers of a specific type of microglia cells (iba1-positive microglia).

There was no association between the number of microglia in the arcuate nucleus region of the hypothalamus and changes in body weight or fat mass at the end of the 4 weeks. However, fat mass and the relative increase in fat mass during the study were associated with the number of a specific type of glial cells called astrocytes.

Further analysis showed that germ-free and antibiotic-fed mice are more sensitive to leptin than conventionally raised mice. When researchers gave them leptin injections, the first two types of mice reduced their food intake more than conventionally raised mice did.

Glucagon-like-peptide 1 (GLP-1) seems to be crucial for protection against diet-induced inflammation of the hypothalamus

Germ-free and antibiotic-fed mice had higher levels of the hormone called glucagon-like peptide 1 (GLP-1) when they were fed a regular diet. This hormone secreted in the small intestine’s intestinal lining cells (L cells) is important in regulating blood sugar levels. It also helps reduce inflammation and protect neurons.

Study authors believed it might also be crucial for the protection from inflammation of the hypothalamus induced by the Western diet. After mice were fed a Western diet for a week, antibiotic-treated and germ-free mice had higher levels of GLP-1 than conventionally raised mice. These mice did not gain weight or develop hypothalamic inflammation after this diet. However, when researchers measured these same things in antibiotic-fed and germ-free mice whose GLP-1 signaling pathway was disabled, they also gained weight and developed inflammation, similar to conventionally raised mice. This indicated that the functional signaling path of GLP-1 is crucial for countering the inflammation of the hypothalamus induced by a Western diet.

Just a week on a Western diet led to inflammation of the hypothalamus that, in turn, disrupted the body’s mechanism for regulating food intake

Conclusion

These findings in mice show that gut microbiota changes how the organism, of mice in this case, reacts to a Western diet. When gut microbiota was intact, just a week on a Western diet led to inflammation of the hypothalamus that, in turn, disrupted the body’s mechanism for regulating food intake. However, when gut microbiota was depleted or absent, this inflammation did not happen, provided that the signaling pathway of one specific hormone (GLP-1) was intact.

While the study was done on mice, similar physiological mechanisms exist in humans. Due to this, these findings on mice help scientists better understand how and through which physiological mechanisms changes in the human diet that occurred in the last century disrupted food intake regulation in the human body leading to the current obesity pandemic.

The paper “The gut microbiota regulates hypothalamic inflammation and leptin sensitivity in Western diet-fed mice via a GLP-1R-dependent mechanism” was authored by Christina N. Heiss, Louise Manneras-Holm, Ying Shiuan Lee, Julia Serrano-Lobo, Anna Hakansson Gladh, Randy J. Seeley, Daniel J. Drucker, Fredrik Backhed, and Louise E. Olofsson.

References

Heiss, C. N., Mannerås-Holm, L., Lee, Y. S., Serrano-Lobo, J., Håkansson Gladh, A., Seeley, R. J., Drucker, D. J., Bäckhed, F., & Olofsson, L. E. (2021). The gut microbiota regulates hypothalamic inflammation and leptin sensitivity in Western diet-fed mice via a GLP-1R-dependent mechanism. Cell Reports, 35(8). https://doi.org/10.1016/j.celrep.2021.109163

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

The Center for Nutritional Psychology. (2023). What is Nutritional Psychology? https://www.nutritional-psychology.org/what-is-nutritional-psychology/

Food and Mood: Is the Concept of ‘Hangry’ Real?

Posted on July 31, 2023January 24, 2025 by CNP Staff

A recent study conducted in Austria used the method of experience sampling to examine the links between hunger and mood. Researchers asked participants to report their hunger and mood five times per day. Results showed that participants reported greater anger, irritability, and decreased pleasure when hungry (Swami et al., 2022). The study was published in Plos One.

Hunger and satiety exert a very powerful influence on one’s behavior.

Nutritional psychology, as explored by The Center for Nutritional Psychology, focuses on the links between diet, psychological states, and mental health. While the significance of this research topic is widely acknowledged, it remains a relatively new field of study, with crucial findings likely to emerge in the future.

What is hunger?

From a physiological point of view, hunger is a complex biological process that primarily revolves around regulating blood glucose levels and releasing hormones that control appetite and satiety. When we eat food, our bodies break down carbohydrates into glucose, which is the primary energy source for cells. As we go without food, our blood glucose levels gradually decline.

The two key hormones involved in hunger regulation are ghrelin and leptin. Ghrelin, produced by the stomach, signals the brain to stimulate appetite when the stomach is empty. Before meals, ghrelin levels increase, and they decrease after eating. Leptin functions as an appetite suppressor and is produced by fat cells, so when body fat decreases, leptin levels drop (see Figure 1).

Figure 1. Two key hormones involved in hunger regulation are Ghrelin and Leptin

Finally, the brain integrates the input received from hormones and sensory organs (e.g., sight or smell of food) to produce the feeling of hunger or satiety. This integration of signals happens in the hypothalamus region of the brain.

The sensation of hunger

Apart from being the result of a complex physiological process, hunger is also a subjective sensation. This sensation serves to motivate the individual to seek food and ingest it. In turn, this ensures that the nutritional needs of the organism are met (McKiernan et al., 2008). When an individual feels hungry, they become more sensitive to stimuli associated with food (e.g., Lazarus et al., 1953). Individuals will pay increased attention to food items and things they have learned to associate with food (e.g., logos of restaurants or food brands, places and people they have learned to associate with food, etc.).

However, decreased levels of nutrients in the body are not the only thing that can lead to the sensation of hunger. Studies show that humans and other species of animals can eat when bored, desire sensory stimulation (McKiernan et al., 2008), or are under stress (Levine & Morley, 1981). They also learn to expect food at certain times or at certain places. Studies indicate that under regular circumstances, human daily rhythms of biological processes (circadian rhythms) are synchronized with a pattern of three meals per day. However, the body can also adapt and learn to expect meals at different times of the day. This expectation can trigger hunger at a particular time and various physiological processes preparing the body for food intake (Isherwood et al., 2023) (see Figure 2).

Figure 2. Some sources of hunger

Being “hangry” – hungry and angry

Hunger affects the behavior of both humans and animals. Observations of non-human animals show that food deprivation increases their motivation to engage in escalated and persistent aggression to acquire food. It is well-known among keepers of various animals that the animals are the most dangerous when hungry.

Studies in humans link the sensation of hunger with feelings of restlessness, nervousness, irritability, and behavioral difficulties in children. Low blood glucose levels, known to trigger the sensation of hunger, are associated with increased impulsivity, anger, and aggression (Swami et al., 2022). Studies applying the concept of ego depletion suggest that the human capacity for self-regulation and active volition is limited (Baumeister et al., 1998) and that when one is hungry, negative, high-arousal emotions are more likely to occur. This is because individuals may struggle to exercise self-regulation and self-control when their blood glucose is low (Swami et al., 2022).

Studies in humans link the sensation of hunger with feelings of restlessness, nervousness, irritability, and behavioral difficulties in children.

These findings and casual observations have given rise to the term “hangry.” A combination of “hungry” and “angry,” hangry signifies a state in which one experiences both hunger and anger due to hunger.

Coined from hungry and angry, the term “hangry” indicates a state in which one is hungry but is also angry because of hunger.

The current study

Viren Swami, the study author, and his colleagues aimed to investigate the state of being “hangry” in a natural setting more systematically.

They wanted to know the extent to which daily experiences of hunger are associated with negative emotional outcomes. They reasoned that if the sensation of hunger is indeed linked to anger and other negative emotions, this must be the case in everyday life and not only in laboratory experiments.

To examine this link, they conducted an experience sampling study in which a group of study participants reported on their daily experiences of hunger and anger over a 3-week period. Understanding that anger might not be the only emotion connected to hunger, the study authors asked participants to report on irritability, pleasure, and arousal. They expected that hunger would be associated with greater anger, irritability, and arousal but lower feelings of pleasure.

What is experience sampling?

Experience sampling (Figure 3), or ecological momentary assessment, involves collecting real-time participant data throughout their daily lives. Participants are prompted multiple times daily to report on their experiences, emotions, behaviors, or thoughts using electronic devices such as smartphones or specialized wearable devices. This method gives researchers insights into individuals’ subjective experiences in their natural settings. This approach minimizes issues related to recalling events after much time has passed, a common problem encountered in traditional research methods relying on recalling past events. Experience sampling allows for a more nuanced understanding of how various factors fluctuate over time and under different circumstances.

Figure 3. Experience sampling process

The procedure

The study initially involved 121 participants; however, it required them to respond to surveys five times daily, every day, for three weeks, resulting in a total of 105 surveys to be completed by each participant. This workload proved overwhelming for many, with only 39 participants successfully completing all 105 surveys. Seventy-six participants managed to complete at least one survey per day.

Participants were, on average, 30 years old. Their ages ranged between 18 and 60 years. 69% were from Austria, followed by Germany (20%), Switzerland, and other countries. The vast majority of the participants were women (81%). 44% lived alone, 19% were married, and 36% were in a relationship. They had an average of 14 years of education.

Daily surveys

In the survey, participants indicated on a scale of 0 to 100 how hungry they were (“How hungry are you at the moment?”), their irritability (“How irritable do you feel at the moment?”), and how angry they felt at that moment. In addition, they rated their emotional state (“How pleasant do you find your current state?”), and arousal level (“What is your current arousal level?”). They also reported the time since their last meal (“When was your last meal? [______ hours ago]”.

Participants completed the surveys using their smartphones through the ESMira software package. After installing ESMira and registering for participation in the study, participants provided their demographic data. Of the five daily surveys, study authors set three to be at fixed time points during the day, before the three main meals – at 8:00, 12:00, and 18:00. At these time points, participants received an in-app notification to complete the survey. The remaining two surveys were random, one between 9:00 and 11:00 in the morning and the other between 13:00 and 17:00 (in the afternoon) (see Figure 4).

Figure 4. Daily survey procedure

Other measures

After the three-week period of the study, participants completed the final questionnaire, in which they provided their demographic data once again. It also contained assessments of four aspects of dietary behavior – restrictive eating (e.g., “I consciously eat less so as not to gain weight”), two aspects of emotionally-induced eating behavior, with clear emotions (e.g., “When I am irritated, I have the desire to eat”) and unclear emotions (e.g., “I always want to eat something when I have nothing to do”), and externally determined eating behavior (e.g., “I eat more than usual when I see others eating”).

The final questionnaire also contained assessments of dispositional anger (the Anger subscale from the Buss and Perry Aggression Questionnaire, BPAQ) and eating motivation (the Eating Motivation Survey consists of the question “Why do you eat what you eat?” followed by 15 different motivations that the participant has to rate).

Participants rarely skipped dinner

Analysis of the responses to the final questionnaire (see Figure 5) showed that some participants often skipped meals, but not all equally. 58% reported that they usually have breakfast, 78% usually had lunch, and 84% usually had dinner. 48% snacked between main meals. 9% reported getting up at night to eat. 88% declared that their eating habits during the study were the same as usual.

53% of the participants paid close attention to maintaining a healthy diet, either very often or always, and 55% paid attention to the sensation of hunger. The main motivation for eating was hunger and because participants liked the meal. 23% of participants stated they knew when they were full and then stopped eating. 63% reported that from time to time, they would continue to eat even though they were aware that they were full. 13% said they eat when stressed, upset, angry, or bored. Less than 5% reported that they do not feel when they are full and that they orient themselves based on the size of the meal.

Figure 5. Survey Report

When hungry, participants were more often angry, irritable and felt less pleasure

The results demonstrated a strong association between hunger and heightened feelings of anger, irritability, and reduced pleasure. Surprisingly, researchers also observed that participants with higher levels of dispositional anger tended to report higher levels of hunger.

Dispositional anger is a general tendency of an individual to experience anger more frequently and intensely across various situations. In contrast, the feeling of anger refers to a temporary and transient experience of anger.

The link of hunger with irritability, anger, and lower feeling of pleasure persisted even after participants’ sex, age, body mass index, dietary behavior, and dispositional anger were considered (see Figure 6).

Figure 6. Hunger and emotions

Contrary to the study authors’ expectations, hunger was not associated with arousal.

Conclusion

Overall, the study suggests that the experience of being hangry is real. When study participants were hungry, they also tended to experience greater anger, irritability, and less pleasure. This happened in their natural environments while they were living their lives as usual, not in an artificial laboratory environment. It was also not a one-time occurrence – the findings resulted from 105 surveys taken five times daily across three weeks.

These results have important implications for understanding everyday experiences of emotions. They also help practitioners to effectively prevent interpersonal conflicts while ensuring productive behaviors and good relationships. Although the design of this study does not allow for cause-and-effect conclusions to be made, i.e., to conclude that hunger causes anger or vice versa, simply designing school or work schedules to ensure no one goes hungry could help prevent numerous interpersonal problems. Allocating sufficient time and opportunities to eat and reduce prolonged periods of hunger is an important tool for improving everyone’s well-being.

On an individual level, labeling one’s affective state as being “hangry” could allow individuals to make sense of that experience. This is very important as, unlike some other negative states, hunger can be easily resolved by simply eating something.

The paper “Hangry in the field: An experience sampling study on the impact of hunger on anger, irritability, and affect” was authored by Viren Swami, Samantha Hochstoeger, Erik Kargl, and Stefan Stieger.

References

Baumeister, R. F., Bratslavsky, E., Muraven, M., & Tice, D. M. (1998). Ego depletion: Is the active self a limited resource? Journal of Personality and Social Psychology, 74(5), 1252–1265. https://doi.org/10.1037/0022-3514.74.5.1252

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

Lazarus, R. S., Yousem, H., & Arenberg, D. (1953). Hunger and Perception. Journal of Personality, 21(3), 312–328. https://doi.org/10.1111/J.1467-6494.1953.TB01774.X

Levine, A. S., & Morley, J. E. (1981). Stress-induced eating in rats. American Journal of Physiology – Regulatory, Integrative and Comparative Physiology, 241(1), R72–R76.

McKiernan, F., Houchins, J. A., & Mattes, R. D. (2008). Relationships between human thirst, hunger, drinking, and feeding. Physiology & Behavior, 94(5), 700. https://doi.org/10.1016/J.PHYSBEH.2008.04.007

Swami, V., Hochstöger, S., Kargl, E., & Stieger, S. (2022). Hangry in the field: An experience sampling study on the impact of hunger on anger, irritability, and affect. PLOS ONE, 17(7), e0269629. https://doi.org/10.1371/JOURNAL.PONE.0269629

The Center for Nutritional Psychology. (2023). What is Nutritional Psychology? https://www.nutritional-psychology.org/what-is-nutritional-psychology/

Inflammatory bowel diseases

Could inflammatory bowel disease symptoms be improved through diet?

Broccoli sprouts

The current study

The procedure

Dextran sodium sulfate (DSS) in water

Assessments

Broccoli sprouts alleviated the symptoms of colitis

Broccoli sprouts protected against changed to bacterial community induced by colitis

Conclusion

Since broccoli sprouts are widely available and affordable food items, adding them to a diet might be an easily implementable way to reduce symptoms of inflammatory bowel diseases and protect the gut microbiome

A study in the U.S. in 2006 indicated that 97% of people practiced snacking and the share of snack calories in their total daily energy was 24%

On the general level, snacking can be beneficial for health

Frequent consumption of ultra-processed foods leads to adverse health outcomes

People who snack have 2.28 snacks per day on average

People who eat better-quality snacks tend to have more favorable cardiometabolic blood marker levels

The number of snacks in a day and the quantity of energy derived from them were not associated with cardiometabolic blood markers (the quality of snacks was)

The number of people suffering from anxiety and depression has been increasing across many world countries in recent decades

Poverty of diet is a well-established characteristic of people with anxiety and depression

There are several possible mechanisms for how micronutrients might benefit mental health

Consuming highly palatable foods, especially those high in sugar and fat, can increase dopamine in the brain, creating a sense of pleasure and satisfaction

High doses of prebiotic fiber as a supplement would change the patterns of neural activity related to food in the brain reward system

Recent findings indicate that the microbiota-gut-brain axis (MGBA) can affect and regulate the reward system of the brain

Brain reactions to high-calorie foods decreased after prebiotic treatment

Brain reactions to pictures of wanted, high-calorie food decreased after prebiotics compared to placebo

The study showed that intervention with a common prebiotic attenuated reactions of the brain’s reward network in response to high-calorie food

Living in a disadvantaged neighborhood is linked to various adverse outcomes in the diet-mental health relationship (DMHR)

Whether a neighborhood is considered affluent or disadvantaged is a matter of degree

They proposed that body mass index (i.e., being obese or overweight) and stress mediate the relationship between area disadvantage and the extent of changes to the microstructure of specific brain areas

The study showed that individuals living in more disadvantaged areas tend to have altered tissue structures in brain regions responsible for reward processing, emotion regulation, and cognition

Ultra-processed foods are formulations made mostly or entirely from derived substances and various additives with few intact unprocessed or minimally processed food components (Hedrih, 2023; Monteiro et al., 2019)

Foods with high levels of refined carbohydrates or added fats, such as sweets and salty snacks, are the most strongly implicated in addiction behaviors

The prevalence of these disorders in male athletes is largely overlooked, most research is directed towards ED in female athletes

Athletes who compete in sports such as wrestling, that divided into “weight classes,” reported more psychological pressure to be lean

One study found up to 50% of male athletes who participated in weight-sensitive sports had disordered eating (DE)

EDs have the highest fatality rate of any mental health disorder

Current tools used to assess eating disorders among the general population are not appropriate for use with athletes for several reasons

Coping skills may be able to mediate the relationship between competitive anxiety and RBED in athletes

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With regard to food processing, researchers have developed classifications of various food items

Over half of the dietary energy consumed by individuals from high-income countries such as the USA, Canada, or the UK comes from ultra-processed foods

Are any specific ultra-processed foods linked to depression, and does the timing of ultra-processed food consumption play a role?

Individuals eating more ultra-processed foods had higher body weight, smoked more, and were in poorer health

Participants who ate ultra-processed foods most frequently were more likely to suffer from depression than those who ate ultra-processed foods least often

The top consumers of ultra-processed foods had a higher likelihood of depression than participants who consumed these types of food the least

Analyses showed that only high consumption of artificially sweetened beverages and artificial sweeteners is associated with an increased likelihood of depression

There is a complex interplay between diet, environmental factors, and psychological and physiological mechanisms resulting in overeating and obesity

This growing body of evidence suggests that gut microorganisms profoundly impact brain functions, mood, cognition, and emotional well-being

Studies have indicated that feeding mice a Western diet causes inflammation of the region of the brain called the hypothalamus

Leptin is a hormone produced by fat cells that regulate appetite and body weight

Studies have shown that the activation of microglia cells that happens during inflammation of the hypothalamus might be causing leptin resistance

There might be a link between hypothalamus inflammation and gut microbiota (Heiss et al., 2021)

Mice without gut microbiota are protected from diet-induced inflammation of the hypothalamus

Gliosis in the hypothalamus leads to greater gain in body weight and fat mass

Glucagon-like-peptide 1 (GLP-1) seems to be crucial for protection against diet-induced inflammation of the hypothalamus

Just a week on a Western diet led to inflammation of the hypothalamus that, in turn, disrupted the body’s mechanism for regulating food intake

Hunger and satiety exert a very powerful influence on one’s behavior.

Studies in humans link the sensation of hunger with feelings of restlessness, nervousness, irritability, and behavioral difficulties in children.

Coined from hungry and angry, the term “hangry” indicates a state in which one is hungry but is also angry because of hunger.

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