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Children Eating Healthier Diets Tend to Have Better Mental Health, Study Finds

Posted on September 30, 2024November 3, 2024 by CNP Staff

An analysis of the Norwegian Mother, Father, and Child Cohort Study data published in Nutrients reported that children eating healthier diets tended to have lower depression and anxiety symptoms
Mothers eating healthier diets during pregnancy tended to have children with less depression and anxiety symptoms
Children eating healthier diets at 3 and 7 years tended to be more extroverted, benevolent, conscientious, and emotionally stable at 8 years of age

It is well-known that diets lacking certain nutrients can produce very serious diseases. If one does not take enough vitamin C, scurvy will develop. Similarly, a lack of vitamin D can lead to rickets in children or osteoporosis in adults. Deficiency of iron can cause anemia. There are many other examples. However, these are all very straightforward links between a very specific disease and deficiencies of specific nutrients. Many of them have been well-known for centuries.

Dietary patterns and health

In recent decades, scientists have started researching the more subtle links between overall dietary patterns and specific aspects of behavior and mental health. Results of these studies, for example, showed that eating diets based on foods containing large quantities of easily accessible fats and carbohydrates may dysregulate the body’s food intake regulation mechanisms and lead to obesity (Hedrih, 2024; Ikemoto et al., 1996; McDougle et al., 2024).

Eating large quantities of easily accessible fats and carbohydrates may dysregulate the body’s food intake regulation mechanisms and lead to obesity

Similarly, eating ultra-processed foods, foods that have undergone extensive industrial-level processing, often to the extent that makes their ingredients unrecognizable, was linked to a host of adverse health consequences, including cardiovascular disease-related mortality, type 2 diabetes, various mental disorders, and even sleep problems (Duquenne et al., 2024; Lane et al., 2024). Some researchers argue that high consumption of ultra-processed foods also leads to the development of addiction-like conditions (Gearhardt et al., 2023; Hedrih, 2023) (see Figure 1).

Figure 1. Adverse health consequences associated with consumption of ultra-processed foods

On the other hand, adherence to dietary patterns such as the Nordic diet or the Mediterranean diet has been linked to various favorable health outcomes (Adamsson et al., 2011; Camprodon-Boadas et al., 2024; Lankinen et al., 2019, 2019; Salas-Salvadó et al., 2018).

Prenatal dietary patterns and health

When a human egg cell is fertilized with a sperm cell, it transforms into a zygote. Immediately, the zygote begins a process of rapid cell division and growth, transforming itself into a blastocyst. The blastocyst implants itself into its mother’s uterus and continues rapid growth, developing into a newborn baby some nine months later. During this period, the future baby takes all the nutrients it needs from its mother’s body.

This means that the mother’s diet is crucial for the healthy development of the fetus. While it has long been known that extreme deficiencies in the mother’s diet (e.g., starvation, exposure to specific chemical agents) will have serious adverse consequences for the development of the fetus, findings about the effects of subtle changes to the mother’s diet on the offspring started are relatively new, coming mostly from studies on rodents.

For example, a recent study on rats found that insufficient quantities of omega-3 polyunsaturated fatty acids in the mother’s diet lead to more anxiety-like behaviors in the offspring (Bogachuk et al., 2024). Another study on Norwegian and English mothers (humans) found that mothers adhering to healthy dietary patterns are less likely to have children with autism and social communication problems (Friel et al., 2024).

Mothers adhering to healthy dietary patterns are less likely to have children with autism and social communication problems

The current study

Study author Kristine Vejrup and her colleagues wanted to explore the links between the dietary patterns of mothers during pregnancy and of their children during early years with children’s personality traits and symptoms of depression and anxiety at eight years of age (Vejrup et al., 2023).

They analyzed data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and merged them with the Medical Birth Registry of Norway (MBRN). MoBa is a large-scale longitudinal study conducted by the Norwegian Institute of Public Health. It enrolled 41% of pregnant Norwegian women between 1999 and 2008.

Authors of this study analyzed data from 40,556 mothers with singleton pregnancies who completed a food frequency questionnaire (asking how often they ate different types of food) at the 22nd week of pregnancy and when their child was 6 months, 18 months, 3 years, and 7 years old, and assessments of depression, anxiety, and personality traits of their children when children were 8 years old.

From the mother’s responses about food frequencies, study authors calculated their level of adherence to the New Nordic Diet, a dietary pattern considered healthy and associated with various positive health outcomes. They did the same for the children (after they were born). Based on the similarity between the reported diet and the New Nordic Diet, researchers categorized participating women and children into those highly adhering to this diet, those with medium adherence, and a group of women with low adherence to the diet. Also, they assigned them scores reflecting the level of adherence (see Figure 2).

Figure 2. Study procedure ( Vejrup et al., 2024)

Children eating healthier diets had lower anxiety and depression symptoms

Results showed that children whose mothers ate healthier diets (i.e., had higher adherence to the New Nordic diet) tended to have fewer depression symptoms. Similarly, children eating healthier diets at all examined ages tended to have lower depression symptoms. The healthiness of a child’s dietary pattern at 3 and 7 years of age was associated with fewer anxiety symptoms when it was 8.

Children whose mothers ate healthier diets (i.e., adhered more closely to the New Nordic Diet) tended to have fewer depression symptoms

Diet was associated with personality traits

Children whose mothers ate a healthier diet during pregnancy tended to be more extroverted, benevolent, conscientious, and have better imaginations. They tended to be more emotionally stable (lower neuroticism). The same associations were obtained with children’s dietary habits at 3 and 7 years but also at 18 months, with some exceptions (see Figure 3).

Figure 3. Diet association with anxiety and depression symptoms and personality traits

Conclusion

The study shows that children of mothers who follow a healthy dietary pattern during pregnancy and who themselves eat healthy during the early years of development tend to have fewer depression and anxiety symptoms later when they are 8.

Although the obtained associations were slight, they indicate that a healthy diet in childhood might contribute to protecting mental health later in life.

The paper “Diet in Early Life Is Related to Child Mental Health and Personality at 8 Years: Findings from the Norwegian Mother, Father and Child Cohort Study (MoBa)” was authored by Kristine Vejrup, Elisabet R. Hillesund, Neha Agnihotri, Christine Helle, and Nina C. Øverby.

Watch this Diet-Mental Health Break #42 on Youtube! Do Healthy Diets Improve Children’s Mental Health?

References

Adamsson, V., Reumark, A., Fredriksson, I.-B., Hammarström, E., Vessby, B., Johansson, G., & Risérus, U. (2011). Effects of a healthy Nordic diet on cardiovascular risk factors in hypercholesterolaemic subjects: A randomized controlled trial (NORDIET). Journal of Internal Medicine, 269(2), 150–159. https://doi.org/10.1111/j.1365-2796.2010.02290.x

Bogachuk, A. P., Jacobs, D. S., & Moghaddam, B. (2024). Impact of supplementation with omega-3 fatty acids after maternal dietary deficiency on adolescent anxiety and microglial morphology. Behavioral Neuroscience. https://doi.org/10.1037/bne0000584

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

Duquenne, P., Capperella, J., Fezeu, L. K., Srour, B., Benasi, G., Hercberg, S., Touvier, M., Andreeva, V. A., & St-Onge, M.-P. (2024). The association between ultra-processed food consumption and chronic insomnia in the NutriNet-Santé Study. Journal of the Academy of Nutrition and Dietetics, S2212267224000947. https://doi.org/10.1016/j.jand.2024.02.015

Friel, C., Leyland, A. H., Anderson, J. J., Havdahl, A., Brantsæter, A. L., & Dundas, R. (2024). Healthy Prenatal Dietary Pattern and Offspring Autism. JAMA Network Open, 7(7), e2422815. https://doi.org/10.1001/jamanetworkopen.2024.22815

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

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

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

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

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

Lankinen, M., Uusitupa, M., & Schwab, U. (2019). Nordic Diet and Inflammation—A Review of Observational and Intervention Studies. Nutrients, 11(6), 1369. https://doi.org/10.3390/nu11061369

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

Salas-Salvadó, J., Becerra-Tomás, N., García-Gavilán, J. F., Bulló, M., & Barrubés, L. (2018). Mediterranean Diet and Cardiovascular Disease Prevention: What Do We Know? Progress in Cardiovascular Diseases, 61(1), 62–67. https://doi.org/10.1016/j.pcad.2018.04.006

Vejrup, K., Hillesund, E. R., Agnihotri, N., Helle, C., & Øverby, N. C. (2023). Diet in Early Life Is Related to Child Mental Health and Personality at 8 Years: Findings from the Norwegian Mother, Father and Child Cohort Study (MoBa). Nutrients, 15(1), 243. https://doi.org/10.3390/nu15010243

Study Identifies Neurons Controlling Food-Seeking Behaviors in Mice

Posted on September 16, 2024September 18, 2024 by CNP Staff

A study of genetically engineered mice published in Nature Communications showed that a set of neurons in the midbrain called vesicular GABA transporter-expressing GABAergic neurons (or vgat l/vlPAG neurons for short) controls food-seeking and eating behaviors.
Activity of these neurons alone induced food-seeking behavior, including hunting and foraging for inanimate food items.
Their activation resulted in exploratory foraging and compulsive eating without altering other aspects of the studied mice’s behaviors.

Feeding is probably the most important activity for all living beings. In the wild, animals spend most of their awake time exploring their surroundings, searching for food. This typically includes studying new areas and new things in their surroundings and pursuing prey. Thanks to the easy availability of food in modern societies, most humans spend much less time searching for food. However, deciding what to eat, where to get the food from, and activities needed to obtain and eat food are an important part of human life as well.

Deciding what to eat, where to get the food from, and the activities needed to obtain and eat food are also important parts of human life

Foraging for food

At the turn of the century, scientific evidence pointed to the fact that living organisms have distinct “modes of operation” characterized by specific emotions, accompanying motives, and resulting behavior. The famous neuroscientist Jakk Panksepp proposed seven such biologically determined primary emotional systems (Panksepp, 2004, 2011). He named one of them Seeking.

Panksepp’s Seeking system drives the urge to explore, investigate, and make sense of the environment, motivating goal-directed behaviors. It is associated with the feeling of anticipation and excitement when pursuing desired outcomes, such as finding food, resources, or novel experiences. It is linked to the activity of the mesolimbic dopamine pathway in the brain, which plays a crucial role in reward and motivation.

Neurobiology of seeking food

Panksepp’s theory brought a very global understanding of how food-seeking behavior works. However, many details are still not well understood. A recent study demonstrated that activating a set of neurons located in the arcuate nucleus of the brain’s hypothalamus region initiates consumption of the available food (in rodents). These neurons are called Agouti-related peptide or AgRP neurons (Hedrih, 2024; Sternson & Atasoy, 2014), but they are also known as hunger neurons (see Figure 1).

Figure 1. Neurons in the hypothalamus that initiate food consumption

However, food-seeking is a much broader set of behaviors than just food consumption. It can include a detailed exploration of the environment and hunting prey (Reis et al., 2024). Hunting behaviors in humans and animals can be very complex and involve even the most complex cognitive processes.

Older studies have already established that food-seeking is not solely triggered by a lack of nutrients in the body but that a wide array of factors and circumstances can trigger it. These include current mood, habits, available food cues, current environment, and many others (Hayashi et al., 2023; Hedrih, 2023a, 2023b; Thanarajah et al., 2023; Zhang et al., 2023).

The current study
Study author Fernando M. C. V. Reis and his colleagues wanted to examine the role of a group of neural cells found in the midbrain region of mice in food-seeking behaviors – exploration, foraging, and hunting. These cells are called vesicular GABA transporter-expressing GABAergic neurons or vgat l/vlPAG cells, for short. They are located in the midbrain’s lateral and ventrolateral periaqueductal gray subregions (see Figure 2).

Figure 2. Neural cell group in the midbrain involved in food-seeking behaviors

These authors note that previous studies established that exploratory behaviors in mice can be reduced by inactivating zona incerta neurons, a group of heterogeneous neurons located in the zona incerta region of the subthalamus region of the brain. On the other hand, their activation causes mice to explore novelties, hunt prey (e.g., crickets), and eat non-pray food. There is another group of cells located in the medial preoptic area of the brain that also causes pursuit and following of both pray (crickets) and inedible objects (camk2a cells), and both of these groups of cells connect to the periaqaductal gray part of the midbrain. This brought the attention of study authors to the vgat l/vlPAG neurons.

The study was conducted on male and female Vgat-Cre mice aged between 2 and 6 months. Vgat-Cre mice are genetically engineered mice modified to allow researchers to target their GABAergic neurons. By activating and deactivating specific neurons in this way, researchers are able to observe the effects these neurons have on their behavior.

The study authors conducted a series of behavioral tests on these mice to examine the activity of vgat l/vlPAG neurons and study the behavior of mice when the activity of these neurons is inhibited or stimulated.

Vgat l/vlPAG neurons are more active prior to eating

Results showed that vgat l/vlPAG neurons are more active when mice engage in food-seeking behaviors (hunting, foraging, eating). This was the case both when mice hunted crickets and when they ate inanimate food. Further experiments showed that these cells are more active prior to eating than during eating.

Vgat l/vlPAG neuron activity is necessary and sufficient to activate food foraging and consumption behaviors

When the study authors used genetic manipulation to inhibit vgat l/vlPAG neurons, mice reduced their activities in hunting crickets (in one experiment), their consumption of inanimate food (walnuts in this case), and their time to start hunting crickets.

Figure 3. Vgat l/vlPAG neurons activity and food-seeking behaviors

On the other hand, when study authors used the same technique to stimulate the activity of these neurons, mice increased both their hunting activities and consumption of inanimate food. While these genetic manipulations affected hunting, foraging, and eating behaviors, the mice’s general activity level (how much they move) was not affected.

Further investigations showed that these cells are bidirectionally connected to several other groups of cells involved in feeding, exploration, and investigation, including the already mentioned group of cells in zona incerta.

Conclusion

Overall, the study used a series of experiments on mice to demonstrate that vgat l/vlPAG neurons are crucial in initiating and controlling hunting, foraging, and eating behaviors in mice. While humans and mice are very different species, they share many physiological similarities. Discoveries like this bring science closer to fully understanding the workings of neural circuits controlling food-seeking behaviors and likely the Seeking system in humans.

The paper “Control of feeding by a bottom-up midbrainsubthalamic pathway” was authored by Fernando M. C. V. Reis, Sandra Maesta-Pereira, Matthias Ollivier, Peter J. Schuette, Ekayana Sethi, Blake A. Miranda, Emily Iniguez, Meghmik Chakerian, Eric Vaughn, Megha Sehgal, Darren C. T. Nguyen, Faith T. H. Yuan, Anita Torossian, Juliane M. Ikebara, Alexandre H. Kihara, Alcino J. Silva, Jonathan C. Kao, Baljit S. Khakh, and Avishek Adhikari.

References

Hayashi, D., Edwards, C., Emond, J. A., Gilbert-Diamond, D., Butt, M., Rigby, A., & Masterson, T. D. (2023). What Is Food Noise? A Conceptual Model of Food Cue Reactivity. Nutrients, 15(22), Article 22. https://doi.org/10.3390/nu15224809

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

Hedrih, V. (2023b). Food and Mood: Is the Concept of ‘Hangry’ Real? CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/food-and-mood-is-the-concept-of-hangry-real/

Hedrih, V. (2024, March 4). Researchers Identify Neural Pathways Transmitting Anti-Inflammatory Effects of Hunger. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/researchers-identify-neural-pathways-transmitting-anti-inflammatory-effects-of-hunger/

Panksepp, J. (2004). Affective Neuroscience: The Foundations of Human and Animal Emotions (1st edition). Oxford University Press.

Panksepp, J. (2011). The basic emotional circuits of mammalian brains: Do animals have affective lives? Neuroscience & Biobehavioral Reviews, 35(9), 1791–1804. https://doi.org/10.1016/j.neubiorev.2011.08.003

Reis, F. M. C. V., Maesta-Pereira, S., Ollivier, M., Schuette, P. J., Sethi, E., Miranda, B. A., Iniguez, E., Chakerian, M., Vaughn, E., Sehgal, M., Nguyen, D. C. T., Yuan, F. T. H., Torossian, A., Ikebara, J. M., Kihara, A. H., Silva, A. J., Kao, J. C., Khakh, B. S., & Adhikari, A. (2024). Control of feeding by a bottom-up midbrain-subthalamic pathway. Nature Communications, 15(1), Article 1. https://doi.org/10.1038/s41467-024-46430-5

Sternson, S. M., & Atasoy, D. (2014). Agouti-related protein neuron circuits that regulate appetite. Neuroendocrinology, 100, 95–102. https://doi.org/10.1159/000369072

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

Zhang, X., Wang, H., Kilpatrick, L. A., Dong, T. S., Gee, G. C., Labus, J. S., Osadchiy, V., Beltran-Sanchez, H., Wang, M. C., Vaughan, A., & Gupta, A. (2023). Discrimination exposure impacts unhealthy processing of food cues: Crosstalk between the brain and gut. Nature Mental Health, 1(11), Article 11. https://doi.org/10.1038/s44220-023-00134-9

A Vicious Cycle Between Memory and Food Intake Regulation Likely Maintains Obesity

Posted on September 2, 2024September 5, 2024 by CNP Staff

A paper published in Neuroscience and Biobehavioral Reviews shows that humans have a bidirectional relationship between memory and eating
Memory of recent meals limits subsequent food intake, and this memory is impaired in obese individuals
Excessive food intake likely disrupts the functioning of the part of the hippocampus that plays a role in food-related memory, forming a vicious cycle that promotes further increased food intake

Many factors influence our decisions about when and what to eat. To a degree, these decisions depend on our subjective feelings of hunger and fullness. Still, they also depend on whether food is available and what kind, our eating habits, desires and plans, food cues, and many other things.

One often overlooked but also important factor is the memory of recent meals. In the most basic scenario, if we remember that we just had lunch, we will not have it again. However, these decisions are part of a complex behavioral pattern regulating our food intake behaviors.

How do we regulate food intake?

Scientists believe that our food intake behaviors are primarily regulated by the activities of neurons located in the hypothalamus region of the brain. For example, studies on rodents identified a set of neurons called agouti-related protein neurons that, when artificially triggered, make a rodent start eating (Hedrih, 2024; Sternson & Atasoy, 2014). These neurons are part of a complex system that involves hormones like leptin and ghrelin and various neural pathways that react to the presence or absence of nutrients in our body.

Our food intake decisions do not depend solely on the presence or absence of specific nutrients. Most individuals living in organized societies with sufficient food availability have established habits of having meals at specific times of day. Studies indicate that our bodies anticipate those times and prepare for food intake, e.g., by modifying glucose levels in the blood (Isherwood et al., 2023). We also tend to feel hungry when our usual meal time arrives (see Figure 1). For example, food anticipation can trigger a preparatory response in the body, leading to a mild increase in glucose levels as the brain signals the pancreas to release insulin. This response helps the body manage the expected influx of nutrients from the upcoming meal (Teff, 2011).

Figure 1. Body changes in anticipation and preparation of food intake

Often, we can develop a desire to eat if we see, smell, or taste delicious food. Sometimes, even thinking about food can make us want to eat it. In scientific terms – food cues can motivate us to eat (Hedrih, 2023). People also tend to eat when they feel bad. This is called emotional eating (Dakanalis et al., 2023; Ljubičić et al., 2023).

We can develop a desire to eat if we see, smell, or taste delicious food

Memory and food intake regulation

One of the factors important for regulating food intake is memory. Classic studies of patients with amnesia revealed that their memory dysfunction also affects appetite (Parent et al., 2022). In simple words, individuals who are unable to remember whether they had their regular meal or not might decide to have it again.

More recent studies indicate that impaired memory might play a role in the development of obesity and that specific diets known to lead to obesity also tend to produce memory impairments (Hayes et al., 2024; Hsu et al., 2015).

One of the most important factors for regulating food intake is memory

The current review

Marise B. Parent and her colleagues reviewed a series of studies on humans and rodents examining the links between memory and eating behaviors (Parent et al., 2022). They aimed to demonstrate a bidirectional relationship between memory functions and eating behaviors. Bidirectional, in this case, means that memory affects eating behaviors and that eating habits affect memory.

Disrupted memory and food intake

They start by reiterating the findings of classic case studies of patients with amnesia. For example, in the 1980s, a group of researchers conducted an experiment on a patient, H.M., who suffered from memory loss after undergoing brain surgery to treat epilepsy. This patient hardly ever mentioned being hungry or thirsty, even after not eating or drinking anything for quite some time. At one point, researchers offered him a meal 1 minute after he had just eaten and forgotten the previous meal. He readily accepted it and ate it. Twenty minutes after this, he could not remember having eaten anything.

However, this one patient might have been specific. His hunger ratings did not seem to depend on whether he had just eaten. In studies by these same researchers, 3 out of 4 patients with similar amnesia would report lower hunger levels after a meal. On the other hand, a different experiment a decade later reported about a patient with amnesia who would refuse an additional meal only after eating two 3-course meals one after another. Other researchers reported similar findings in later years, indicating that this link between memory of the previous meal and eating might be a somewhat general occurrence.

Studies in the 21st century tested the link between memory and food intake by diverting participants’ attention from the meal with a secondary activity while eating (e.g., playing games or watching TV) in the hope that this will prevent them from memorizing the food eaten. Results showed that after eating while being distracted, participants tended to take more snacks in a later test. On the other hand, studies that had participants focus on the food they eat showed that they take less food later (see Figure 2).

Figure 2. Distracted eating vs. focused eating

Studies on rodents showed that a group of neurons in the brain’s hippocampus region (dorsal hippocampal glutamatergic neurons) likely mediates the ability of memories about previous meals to stop later intake. Their activity immediately after a meal seems to be critical for this.

Obesity is associated with impaired memory

The authors of this review note that many studies in both rodents and humans report specific aspects of cognition to be impaired in obese individuals. This is particularly the case with certain memory functions. This association is present even in young, otherwise healthy adults. The authors also cite research findings that link obesity with changes in areas of the brain known to play a role in memory processes. There is also a finding that obese individuals tend to have lower global brain volume.

Looking at possible mechanisms through which obesity might lead to changes in the brain and memory impairments, the authors of this review propose that these might be inflammation of the brain and insulin resistance.

Conclusion – the vicious cycle

Based on all the findings, the authors of this review propose that there is a vicious cycle between memory and obesity. Obesity likely leads to memory and other cognitive impairments by stimulating inflammatory processes in the brain and insulin resistance. On the other hand, impaired memory disrupts the food intake regulation mechanism, leading to increased food intake, maintaining or even exacerbating obesity (see Figure 3).

Figure 3. Memory-obesity vicious cycle

Because of this, future research and obesity prevention programs need to be aware of this bidirectional relationship and devise ways to break the vicious cycle if they are to prevent or treat obesity successfully.

The paper “Memory and eating: A bidirectional relationship implicated in obesity” was authored by Marise B. Parent, Suzanne Higgs, Lucy G. Cheke, and Scott E. Kanoski.

References

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

Hayes, A. M. R., Lauer, L. T., Kao, A. E., Sun, S., Klug, M. E., Tsan, L., Rea, J. J., Subramanian, K. S., Gu, C., Tanios, N., Ahuja, A., Donohue, K. N., Décarie-Spain, L., Fodor, A. A., & Kanoski, S. E. (2024). Western diet consumption impairs memory function via dysregulated hippocampus acetylcholine signaling. Brain, Behavior, and Immunity, 118, 408–422. https://doi.org/10.1016/j.bbi.2024.03.015

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

Hsu, T. M., Konanur, V. R., Taing, L., Usui, R., Kayser, B. D., Goran, M. I., & Kanoski, S. E. (2015). Effects of sucrose and high fructose corn syrup consumption on spatial memory function and hippocampal neuroinflammation in adolescent rats. Hippocampus, 25(2), Article 2. https://doi.org/10.1002/hipo.22368

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), Article 7. https://doi.org/10.1016/j.cub.2023.02.005

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

Parent, M. B., Higgs, S., Cheke, L. G., & Kanoski, S. E. (2022). Memory and eating: A bidirectional relationship implicated in obesity. Neuroscience & Biobehavioral Reviews, 132, 110–129. https://doi.org/10.1016/j.neubiorev.2021.10.051

Sternson, S. M., & Atasoy, D. (2014). Agouti-related protein neuron circuits that regulate appetite. Neuroendocrinology, 100, 95–102. https://doi.org/10.1159/000369072

Teff, K. L. (2011). How neural mediation of anticipatory and compensatory insulin release helps us tolerate food. Physiology & Behavior, 103(1), 44. https://doi.org/10.1016/j.physbeh.2011.01.012

Chronic Insomnia Is Associated With Higher Ultraprocessed Food Consumption

Posted on July 22, 2024July 23, 2024 by CNP Staff

A large epidemiological study published in the Journal of the Academy of Nutrition and Dietetics reported an association between the consumption of ultra-processed food and chronic insomnia
Overall, 19.4% of individuals had symptoms of chronic insomnia, and ultra-processed foods were 16% of participants’ daily food intake
However, increasing ultra-processed food intake by 10% was associated with 9% higher odds of suffering from chronic insomnia among men and 5% higher odds among women

We have all experienced situations when we have trouble getting good sleep. This can happen when we are excited, when something troubles us, when our sleeping arrangements are uncomfortable, and under many other circumstances. However, some people have constant difficulties with getting good sleep. This is called chronic insomnia.

What is chronic insomnia?

Chronic insomnia is a sleep disorder characterized by difficulty falling asleep, staying asleep, or waking up too early, occurring at least three nights per week for three months or more (Insomnia – What Is Insomnia? 2022). Common causes of chronic insomnia include stress, anxiety, depression, chronic pain, and certain medications or substances.

This condition leads to chronically poor sleep quality and insufficient rest, which can significantly impair daytime functioning, including concentration, mood, and overall productivity (Drake et al., 2003; Roberts et al., 2008). Chronic insomnia is also associated with an increased risk of developing other health problems, such as cardiovascular disease or diabetes (Sofi et al., 2014; Vgontzas et al., 2009).

Insomnia and diet

Diet is an important determinant of health and chronic disease risk. Many studies report links between dietary habits and risks of specific diseases or adverse health outcomes (Camprodon-Boadas et al., 2024; Hedrih, 2024; Huang et al., 2023).

Diet is an important determinant of health and chronic disease risk.

Recently, industrially processed foods have started attracting researchers’ interest. This is especially the case with ultra-processed foods. 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, or humectants. 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 (Hedrih, 2023) (see Figure 1).

Figure 1. Examples of ultra-processed foods

Many studies linked the consumption of ultra-processed foods with increased risks of various health conditions, including cardiovascular diseases, type 2 diabetes, depression, anxiety, and general risk of death from different causes (e.g., Lane et al., 2024). Some even propose that ultra-processed foods be classified as addictive substances (Gearhardt et al., 2023; Hedrih, 2023)

The current study

Study author Pauline Duquenne and her colleagues wanted to assess the association between the consumption of ultra-processed food and chronic insomnia. They hypothesized that a greater intake of ultra-processed foods would be associated with increased insomnia symptoms (Duquenne et al., 2024).

These authors analyzed data from NutriNet-Santé, an ongoing online study that started in France in 2009. NutriNet-Santé participants are adults who can comprehend written French. The data used in this analysis came from 38,570 participants. Their average age was 50 years, and 77% were females.

When they are included in the study and at regular intervals thereafter, NutriNet-Santé participants complete a battery of questionnaires about their lifestyle profiles, body measurements, physical activity, and health status.

Participants provided their dietary intake data every six months. On these occasions, the study asks them to complete three 24-hour dietary records over a two-week period. The days when dietary intake was recorded were not on consecutive days (see Figure 2).

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

Aside from this, the current analysis utilized assessments of participants’ chronic insomnia symptoms and their sociodemographic data.

Chronic insomnia is associated with anxiety, depression, and female gender

Results showed that 19.4% of participants had symptoms of chronic insomnia. These individuals were also more likely to show symptoms of depression and anxiety. Participants with chronic insomnia were more often females. Females were 84% of the chronic insomnia group and 75% of participants without chronic insomnia.

Because the sample was very large, associations with many other demographic and lifestyle factors were also detected, but these associations tended to be very small.

Individuals suffering from chronic insomnia tended to consume more ultra-processed foods

Ultra-processed foods constituted 16% of participants’ daily food intake. However, participants with chronic insomnia tended to consume more of this type of food. Statistical analysis showed that a 10% increase in daily intake of ultra-processed food corresponded to a 6% higher odds of suffering from chronic insomnia.

Participants with chronic insomnia tended to consume more ultra-processed foods.

This percentage differed somewhat between the sexes. Among men, a 10% higher daily intake of ultra-processed foods corresponded to a 9% higher odds of suffering from chronic insomnia. The increase in odds was 5% among women (see Figure 3).

Figure 3. Study findings (Duquenne et al., 2024)

Conclusion

Using a very large sample from the French-speaking population, this study demonstrates a link between ultraprocessed food consumption and the risk of chronic insomnia. Although the increased risk reported in this study is only slight, this finding adds to the growing body of evidence associating the consumption of ultra-processed foods with adverse health outcomes.

However, it should be noted that the design of this study does not allow any cause-and-effect conclusions to be drawn from the results. While it is possible that increased consumption of ultra-processed food increases the risk of chronic insomnia, it is also possible that chronic insomnia or factors leading to chronic insomnia make a person more likely to consume ultra-processed foods (e.g., because they are readily available or highly palatable). Further studies are needed to clarify the nature of the observed links.

The paper “The association between ultra-processed food consumption and chronic insomnia in the NutriNet-Santé Study” was authored by Pauline Duquenne, Julia Capperella, Léopold K. Fezeu, Bernard Srour, Giada Benasi, Serge Hercberg, Mathilde Touvier, Valentina A. Andreeva, and Marie-Pierre St-Onge.

References

Drake, C. L., Roehrs, T., & Roth, T. (2003). Insomnia causes, consequences, and therapeutics: An overview. Depression and Anxiety, 18(4), 163–176. https://doi.org/10.1002/da.10151

Hedrih, V. (2024, March 4). Researchers Identify Neural Pathways Transmitting Anti-Inflammatory Effects of Hunger. Nutritional Psychology. https://www.nutritional-psychology.org/researchers-identify-neural-pathways-transmitting-anti-inflammatory-effects-of-hunger/

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

Insomnia – What Is Insomnia? | NHLBI, NIH. (2022, March 24). https://www.nhlbi.nih.gov/health/insomnia

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. Public Health Nutrition, 22(5), 936–941. https://doi.org/10.1017/S1368980018003762

Roberts, R. E., Roberts, C. R., & Duong, H. T. (2008). Chronic Insomnia and Its Negative Consequences for Health and Functioning of Adolescents: A 12-Month Prospective Study. Journal of Adolescent Health, 42(3), 294–302. https://doi.org/10.1016/j.jadohealth.2007.09.016

Sofi, F., Cesari, F., Casini, A., Macchi, C., Abbate, R., & Gensini, G. (2014). Insomnia and risk of cardiovascular disease: A meta-analysis. European Journal of Preventive Cardiology, 21, 57–64. https://doi.org/10.1177/2047487312460020

Vgontzas, A. N., Liao, D., Pejovic, S., Calhoun, S., Karataraki, M., & Bixler, E. O. (2009). Insomnia With Objective Short Sleep Duration Is Associated With Type 2 Diabetes. Diabetes Care, 32(11), 1980–1985. https://doi.org/10.2337/dc09-0284

People Choose Healthier Food After Experiencing Nature

Posted on July 14, 2024July 16, 2024 by CNP Staff

A series of five experiments published in Communications Psychology found that individuals exposed to or imagining natural environments tend to choose healthier foods.
The effects were present across various foods and beverages and 3 different countries.
They were detectable both when individuals were walking in a park and when they were looking at photos of nature and imagining the scenery.

People enjoy being in natural environments. Of course, most still like to be comfortable in those environments, but many will also accept different levels of hardship to enjoy nature. Many people travel regularly just to visit nature. Providing opportunities to experience delightful natural environments is also important to tourism.

Nature and health

Not only is nature enjoyable, but studies show that time spent in nature or living near areas of natural vegetation, such as parks, gardens, or forests (particularly urban forests within cities), i.e., so-called green spaces, is associated with better health. It is even associated with a lower risk of dying, particularly of cardiovascular diseases (Gascon et al., 2016). Children living near green spaces tend to have better cognitive development. Studies indicate that the overall well-being of individuals living near green spaces or experiencing them often is better (Dadvand et al., 2015; Ma et al., 2019; van den Berg et al., 2015)

Living near bodies of water, such as rivers, lakes, seas, and oceans, is also associated with similar benefits (Gascon et al., 2017).

Studies indicate that spending time in nature may also improve or help improve mental health.

Studies indicate that spending time in nature may also improve or help improve mental health. For example, one study found that hiking in nature reduced suicidal tendencies in individuals with high tendencies. Another study found that group walks in nature can buffer against the effects of a stressful lifestyle and protect one’s mental health (Marselle et al., 2019; Mitten et al., 2018; Sturm et al., 2012). This is just a selection of such studies.

The current studies

Study authors Maria Langlois and Pierre Chandon note that some studies indicate that experiencing nature might also benefit food choices. However, the quality of these studies was limited (Langlois & Chandon, 2024). To overcome this, they conducted a series of 5 experiments.

Their hypothesis was that experiencing nature outdoors or through a virtual nature scene would lead people to make healthier food choices than they normally make while experiencing urban environments. More precisely, their expectation was that nature exposure increases the feelings of connectedness to nature, leading to healthier attitudes and increased respect for one’s body. This, and not just the desire to lose weight, might be what leads to healthier dietary choices. Previous studies already reported a link between nature-relatedness and food choices (Miliron et al., 2015).

The procedure

In the first study, 39 Paris, France, residents took a 20-minute walk either through a large local park (the nature environment group) or nearby city streets (the urban environment group). The experiment was conducted with one participant at a time. After the walk, participants accessed a snack buffet offering 4 healthy snacks (bananas, apples, dried fruits, and mixed nuts) and four unhealthy snacks (strawberry cookies, apricot cookies, potato chips, and brownies). The study authors recorded which participants selected which snack.

Participants of the second study were 698 U.S. residents recruited through Prolific. Their task was to imagine being in a hotel room. They were randomly assigned to imagine that from their imagined hotel room, they could either view a scene of nature, an urban scene or that the window curtains were closed. They were shown photos to illustrate these situations. Participants would then write a sentence describing the scene and choose what they would like to eat from a food service menu containing 12 items of different healthiness.

In the third study, 883 U.S. residents viewed a photo of an urban environment or nature used in study 2 (without window frames). They would imagine being in that environment and selecting food they would take as a packed lunch. Afterward, they rated the healthiness of that food. Study 4 was similar but included additional steps to ensure participants paid attention to the photo. Also, instead of picking specific foods, they were selecting between “a natural, healthy snack,” “a tasty, indulgent snack,” or “a diet, light snack”.

In the 5th study, 913 U.K. participants imagined being in a hotel with a window through which they could see the scene in the photo they viewed. The photos showed either a waterfront view with green cliffs or a modern building in a clean city without people. After imagining the scene, participants selected food and beverages they would like (see Figure 1).

Figure 1. Study procedure (Langlois and Chandon, 2024)

Nature experiences lead to healthier food choices

In the first study, participants who walked through the park chose healthy snacks more often than participants who went on an urban walk. The two groups of participants did not differ in the quantity of snacks they ate.

In the second study, participants in the group that imagined viewing a nature scene from the hotel window tended to make much healthier food choices. Participants who imagined closed curtains and those imagining that they viewed an urban scene did not differ in the healthiness of their choices.

Participants who walked through the park chose healthy snacks more often than participants who went on an urban walk.

The link between nature experiences and healthy food choices held across countries and situations
The other 3 studies mirrored the results of the first two. Participants of the third study who imagined being in nature more often chose healthier lunch options compared to those who imagined being in an urban environment. The group that imagined nature was more likely to select lunch options they viewed as healthier.

In the fourth study, participants who viewed nature were likelier to select a healthy snack and less likely to select both a tasty and a diet snack. Participants of the fifth study who viewed the waterfront with green cliffs (nature) were also more likely to select healthy food than those who viewed the urban scene (see Figure 2).

Figure 2. Results

Conclusion

Across 5 studies and 3 countries, the link between nature experiences and healthy food choices persisted. Participants who walked through nature, imagined it, and/or viewed pictures of it were likelier to choose healthier food choices.

Additionally, these choices seem to be driven by food healthiness and not the desire to lose weight, given that, in a study that explicitly offered a choice between a diet snack and a healthy snack, participants who experienced nature more often opted for the healthy one.

These healthier food choices are driven by food healthiness and not the desire to lose weight.

The findings indicate that weight-loss interventions and other programs aimed at promoting healthy dietary habits should consider individuals’ environments and everyday experiences with nature.

The paper “Experiencing nature leads to healthier food choices” was authored by Maria Langlois and Pierre Chandon.

References

Dadvand, P., Nieuwenhuijsen, M. J., Esnaola, M., Forns, J., Basagaña, X., Alvarez-Pedrerol, M., Rivas, I., López-Vicente, M., De Castro Pascual, M., Su, J., Jerrett, M., Querol, X., & Sunyer, J. (2015). Green spaces and cognitive development in primary schoolchildren. Proceedings of the National Academy of Sciences, 112(26), 7937–7942. https://doi.org/10.1073/pnas.1503402112

Gascon, M., Triguero-Mas, M., Martínez, D., Dadvand, P., Rojas-Rueda, D., Plasència, A., & Nieuwenhuijsen, M. J. (2016). Residential green spaces and mortality: A systematic review. Environment International, 86, 60–67. https://doi.org/10.1016/j.envint.2015.10.013

Gascon, M., Zijlema, W., Vert, C., White, M. P., & Nieuwenhuijsen, M. J. (2017). Outdoor blue spaces, human health and well-being: A systematic review of quantitative studies. International Journal of Hygiene and Environmental Health, 220(8), 1207–1221. https://doi.org/10.1016/j.ijheh.2017.08.004

Langlois, M., & Chandon, P. (2024). Experiencing nature leads to healthier food choices. Communications Psychology, 2(1), 24. https://doi.org/10.1038/s44271-024-00072-x

Ma, B., Zhou, T., Lei, S., Wen, Y., & Htun, T. T. (2019). Effects of urban green spaces on residents’ well-being. Environment, Development and Sustainability, 21(6), 2793–2809. https://doi.org/10.1007/s10668-018-0161-8

Marselle, M. R., Warber, S. L., & Irvine, K. N. (2019). Growing Resilience through Interaction with Nature: Can Group Walks in Nature Buffer the Effects of Stressful Life Events on Mental Health? International Journal of Environmental Research and Public Health, 16(6), Article 6. https://doi.org/10.3390/ijerph16060986

Milliron, B. J., Ward, D., Granche, J., Mensinger, J., Stott, D., Chenault, C., Montalto, F., & Ellis, E. V. (2022). Nature Relatedness Is Positively Associated With Dietary Diversity and Fruit and Vegetable Intake in an Urban Population. American journal of health promotion : AJHP, 36(6), 1019–1024. https://doi.org/10.1177/08901171221086941

Mitten, D., Overhold, J., Haynes, F., D’Amore, C., & Ady, J. (2018). Hiking: A Low-Cost, Accessible Intervention to Promote Health Benefits. American Journal of Lifestyle Medicine, 12(4), 302–310. https://doi.org/10.1177/1559827616658229

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

van den Berg, M., Wendel-Vos, W., van Poppel, M., Kemper, H., van Mechelen, W., & Maas, J. (2015). Health benefits of green spaces in the living environment: A systematic review of epidemiological studies. Urban Forestry & Urban Greening, 14(4), 806–816. https://doi.org/10.1016/j.ufug.2015.07.008

When Our Eating Experience Falls Short, Do We Eat More to Compensate?

Posted on July 9, 2024July 9, 2024 by CNP Staff

People have expectations about how much they will enjoy their food and other enjoyable activities
A new study published in the Journal of Personality and Social Psychology: Attitudes and Social Cognition proposes that when they do not experience the expected joy due to distraction, people will want to eat more to compensate
They may snack more or more often in the afternoon to compensate for insufficient enjoyment of lunch

People do many things for joy. We take walks because we enjoy them. We play sports or video games just for the joy of it. We often talk to friends just because we enjoy the exchanges. Eating food is also partly done for enjoyment. When we visit a restaurant or eat a meal, aside from nutrition, we also have an expectation that we will enjoy the experience.

This is called hedonic consumption – consumption of experiences “by an affective and sensory experience of aesthetic or sensual pleasure, fantasy, and fun” (Dhar & Wertenbroch, 2000). Hedonic consumption is a critical aspect of everyday life. It is crucial for our psychological well-being.

Hedonic consumption refers to the consumption of experiences “by an affective and sensory experience of aesthetic or sensual pleasure, fantasy, and fun.”

Hedonic overconsumption

However, hedonic consumption sometimes becomes too excessive and even problematic. A person can eat too much of the food he/she likes, leading to health problems. He/She may spend too much time playing games while neglecting other obligations. A person may decide to stay late at night to do so, impairing his/her functioning the following day. If staying late happens often and disrupts sleep patterns, in time, such behavior can dysregulate various systems of the body, leading to different health problems (Brondel et al., 2010; Cappuccio et al., 2008; Hillman & Lack, 2013)

This excessive consumption of goods and services for pleasure and enjoyment rather than necessity is called hedonic overconsumption.

The excessive consumption of goods and services for pleasure and enjoyment rather than necessity is called hedonic overconsumption.

A theoretical model of hedonic overconsumption

Why do people engage in hedonic overconsumption? Hedonic overconsumption is often ascribed to one’s lack of self-control. This lack of self-control can happen for a variety of reasons. A tempting environment, a strong short-term desire, a lack of motivation and effort investment, a lack of control capacity or situational constraints on action, or ill-chosen strategies are just a few of the reasons mentioned in the literature (Murphy et al., 2024).

However, Stephen L. Murphy and his colleagues propose that hedonic overconsumption is often about regulating the joy level we expect from experiences. They propose that if we experience “hedonic shortfalls,” i.e., if we do not experience the amount of joy we expected to derive from hedonic consumption, we will want to consume more to compensate for this shortfall (Murphy et al., 2024).

If we do not experience the amount of joy we expect to derive from hedonic consumption, we will want to consume more to compensate for this shortfall.

For example, if something distracts us while watching a movie and our minds wander from the movie, we will not experience the joy we expected. This will make us more likely to re-watch the movie, or at least the part we missed. That way, we will spend more time watching the movie in total.

The current studies

To test their hypotheses, these researchers conducted two studies and a meta-analysis. The meta-analysis focused on published scientific studies that reported associations between being distracted from joyful activities and the amount of joy experienced. It confirmed the study authors’ expectations—when people were distracted from a joyful activity, they tended to report lower levels of enjoyment.

In the first study, researchers asked 122 young people between 18 and 24 years of age to participate in an online survey. The instructions were to start the survey before lunch. At this point, among other things, they reported on how much they expected to enjoy their lunch.

Then, they were randomly allocated into three groups. Researchers told one group to eat lunch without distractions (“No distraction”), the second group to watch an online video while they ate (“Mild distraction”), and the third group to play Tetris during their lunch (“High distraction”).

After lunch, participants reported how much they ate, how much they enjoyed lunch, how much they were distracted, and how much they desired further gratification. Before dinner, on the same day, participants reported how many snacks they consumed since lunch and on how many occasions (see Figure 1).

Figure 1. The first study (Murphy et al., 2024)

The second study utilized the experience sampling approach. Over a 7-day period, study authors would send surveys (7 per day) to 220 adult participants on their mobile devices, asking them to report on their hedonic consumption activities since the previous survey. The activities included eating, drinking, smoking, gambling, drug use, gaming, use of media/audio devices for leisure, leisure reading, sport, and exercise. Participants reported various details of such activities, such as how much they expected to enjoy the activity and how much they enjoyed it.

Insufficient enjoyment leads to further consumption

Results of the first study showed that distraction during lunch was not consistently linked with the enjoyment of lunch. Although there was a very weak tendency for those experiencing more distraction to report less enjoyment, it was so weak that authors could not be sure they were not simply looking at random variations in data.

However, participants who enjoyed their lunch less tended to feel a greater need for further gratification. Participants who felt a greater need for further gratification tended to snack more frequently and consume higher amounts of snacks afterward.

Participants who enjoyed their lunch less tended to feel a greater need for further gratification.

Distraction during hedonic consumption is associated with less enjoyment

Results of the second study showed that individuals who experienced more distraction during a hedonic activity tended to report less enjoyment in the activity. When participants experienced less joy than they expected from the hedonic consumption they engaged in, they tended to be less satisfied with it. As expected, when they were not satisfied with the hedonic consumption they experienced, participants were more likely to engage in overconsumption, i.e., do more of the hedonic activity in question (see Figure 2).

Figure 2. The second study (Murphy et al., 2024)

Conclusion

This set of studies provides initial support for the idea that hedonic overconsumption can result from insufficient joy derived from hedonic activities.

If people derive insufficient enjoyment from their meals, they will be more likely to overeat if it is less than what they expected. This seems to apply to all hedonic consumptions, i.e., to all activities we conduct for pleasure. These findings point to a new aspect that weight loss programs and programs aiming to tackle other forms of excessive overconsumption (e.g., excessive betting, gambling, drinking…) need to be taken into account.

The paper “Underwhelming Pleasures: Toward a Self-Regulatory Account of Hedonic Compensation and Overconsumption” was authored by Stephen L. Murphy, Floor van Meer, Lotte van Dillen, Henk van Steenbergen, and Wilhelm Hofmann.

References

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

Cappuccio, F. P., Taggart, F. M., Kandala, N.-B., Currie, A., ChB, M., Peile, E., & Miller, M. A. (2008). Meta-Analysis of Short Sleep Duration and Obesity in Children and Adults. 31(5).

Dhar, R., & Wertenbroch, K. (2000). Consumer Choice between Hedonic and Utilitarian Goods. Journal of Marketing Research, 37(1), 60–71. https://doi.org/10.1509/jmkr.37.1.60.18718

Hillman, D. R., & Lack, L. C. (2013). Public health implications of sleep loss: The community burden. Medical Journal of Australia, 199(8), S7–S10. https://doi.org/10.5694/mja13.10620

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

Chronic Stress Alters Gut Microbiome Composition by Reducing the Production of a Protein Called Mucin 13

Posted on July 1, 2024July 9, 2024 by CNP Staff

A series of experiments published in Brain Behavior and Immunity revealed that exposing mice to chronic stress reduced the levels of a protein called mucin 13.
Deleting the gene that encodes mucin 13 was sufficient to create the changes in the gut microbiome seen after exposure to chronic stress and to produce and produce depression-like symptoms.
Mice without the gene that encodes mucin 13 were more susceptible to stress.

Depression and anxiety affect millions of people worldwide. Despite this, treatments for these disorders are often not very effective. Estimates state that at least 30% of individuals suffering from depression do not experience symptom withdrawal even after multiple treatment procedures (McIntyre et al., 2023). The situation is similar to anxiety – only about 60% of patients respond to treatments to any significant degree (Bystritsky, 2006).

One of the reasons for the low effectiveness of treatments for these widespread disorders probably lies in the fact that their causes are not fully understood by researchers. However, the recent discovery of the microbiota-gut-brain axis (MGBA) and studies of the biochemical pathways involved in depression and anxiety show promise to change this situation (Bonaz et al., 2018; Hedrih, 2023).

The microbiota-gut-brain axis and mental health

The gut microbiota is a community of trillions of microorganisms living in our gut. These organisms help us digest the food we eat, allowing us to extract nutrients from foods that we would not be able to use without their help. However, their role in our organisms far exceeds these digestive processes.

Researchers discovered a bidirectional communication pathway that allows the gut microbiota to influence processes in the brain and vice versa (Valles-Colomer et al., 2019). This pathway was named the microbiota-gut-brain axis. Studies show that individuals with specific mental health issues have altered gut microbiota composition.

Studies show that individuals with specific mental health issues have altered gut microbiota composition

Additionally, studies on rodents revealed that it is possible to transfer serious mental health symptoms, such as those of social anxiety or even cognitive deficits associated with Alzheimer’s disease, by simply transplanting gut microbiota from humans suffering from these disorders into rodents (Hedrih, 2024; Kim et al., 2021; Ritz et al., 2024). Recent studies also identified specific biochemicals regulated by gut microbiota that affect processes such as inflammation in the brain or that induce changes in the brain, resulting in behavioral alterations (Heiss et al., 2021; Ritz et al., 2024). An important finding was that exposure to chronic stress alters gut microbiota composition (Ritz et al., 2024; Rivet-Noor et al., 2024).

It is possible to transfer serious mental health symptoms by simply transplanting gut microbiota from humans suffering from these disorders into rodents

These results created hope that novel ways to treat anxiety and depression, as well as other mental health issues, might be developed after we better understand the interplay between gut microbiota and processes in the brain.

The current study

Study author Courtney R. Rivet-Noor and her colleagues noted that the mucus layer in the gut is crucial for regulating microbiome composition. This mucus layer is a protective barrier that covers the gut lining, preventing damage from digestive enzymes, pathogens, and mechanical stress. The main component of this layer is a class of proteins called mucins.

The authors of this study hypothesized that exposure to chronic stress alters this mucus layer, thus initiating microbiome changes (see Figure 1). To test this, they conducted a study on mice.

Figure 1. The mucus layer of the gut

The study procedure

The study was conducted on two widely used strains of inbred laboratory mice (C57BL/6J and BALB/cJ). Mice were divided into two groups – one was exposed to chronic mild restraint stress by keeping them restrained in conical tubes for 2 hours and exposing them to one overnight stressor per day. The overnight stressors were 45-degree cage tilt, wet bedding, or 2x cage change. After a certain period, this treatment produces symptoms akin to depression and anxiety in humans. Mice not exposed to stress were used as controls.

The authors conducted a series of behavioral tests to test whether the stress treatment produced the expected effects (the forced swim, tail suspension, sucrose preference, open field, elevated plus maze, and nestlet shred tests). They also analyzed the tissues of these mice and conducted microbiota transfer experiments (see Figure 2).

Figure 2. Study Procedure (Rivet-Noor et al., 2024)

Chronic stress modified microbiome composition and reduced mucin 13 levels

As expected, exposing mice to chronic stress increased depression and anxiety-like behaviors in exposed mice. It also altered their gut microbiota composition. These mice had reduced expression of the Muc13 gene, resulting in lower levels of one of the mucin proteins – mucin 13. Other mucin proteins were unaffected.

Transferring gut microbiota from stressed mice to mice not exposed to chronic stress did not affect mucin 13 levels in the recipient mice. However, transplanting gut microbiota from stressed mice into mice without gut microbiota made the latter group of mice develop depression and anxiety-like symptoms, although they were not exposed to stress. This meant that mucin 13 reductions were not driven by changes in gut microbiota, but gut microbiota changes did lead to depression- and anxiety-like symptoms (see Figure 3).

Figure 3. Chronic stress modified microbiome composition and reduced mucin 13 levels

Deleting the Muc13 gene leads to microbiome changes similar to those resulting from chronic stress

The reduction in the expression of the Muc13 gene was caused by a protein called hepatocyte nuclear factor 4 or HNF4. This protein regulates the expression of specific genes by binding to particular DNA sequences. Analysis showed that chronic stress reduced the production of HNF4, leading to lower expression of the Muc13 gene. This was independent of changes to the microbiome.

Finally, the study authors created a line of mice without the Muc13 gene. Without being exposed to chronic stress, these mice had microbiota composition resembling regular mice exposed to chronic stress. This suggested that reductions in mucin 13 protein drive the changes in microbiota after experiencing chronic stress.

Behavioral tests showed that mice without the Muc13 gene displayed depression-like but not anxiety-like behaviors without being exposed to stress. However, after being exposed to stress, mice without the Muc13 gene developed anxiety-like symptoms much faster (after only one week) than regular mice. This indicated that the lack of this gene and the consequent lack of mucin 13 made them more susceptible to the effects of stress (see Figure 4).

Figure 4. Effects of absence of Muc13 gene in Mice

Conclusion

The study showed that chronic stress’s effects on behavior are mediated by a protein in the mucus layer of the gut called mucin 13. Although the study was done on mice, mucin 13 also exists in the human gut. This discovery could potentially open new ways to treat the consequences of chronic stress by targeting the production or level of mucin 13 in the gut.

The paper “Stress-induced mucin 13 reductions drive intestinal microbiome shifts and despair behaviors” was authored by Courtney R. Rivet-Noor, Andrea R. Merchak, Caroline Render, Naudia M. Gay, Rebecca M. Beiter, Ryan M. Brown, Austin Keeler, G. Brett Moreau, Sihan Li, Deniz G. Olgun, Alexandra D. Steigmeyer, Rachel Ofer, Tobey Phan, Kiranmayi Vemuri, Lei Chen, Keira E. Mahoney, Jung-Bum Shin, Stacy A. Malaker, Chris Deppmann, Michael P. Verzi, and Alban Gaultier.

References

Bonaz, B., Bazin, T., & Pellissier, S. (2018). The vagus nerve at the interface of the microbiota-gut-brain axis. Frontiers in Neuroscience, 12(FEB). https://doi.org/10.3389/fnins.2018.00049

Bystritsky, A. (2006). Treatment-resistant anxiety disorders. Molecular Psychiatry, 11(9), 805–814. https://doi.org/10.1038/sj.mp.4001852

Hedrih, V. (2023, September 2). Gut Microbiota’s Role in Mental Health: The Positives and Negatives. CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/how-your-gut-microbiota-is-linked-to-both-positive-and-negative-aspects-of-mental-health/

Hedrih, V. (2024, March 12). Can Social Anxiety From Humans be Transmitted to Mice? CNP Articles in Nutritional Psychology. https://www.nutritional-psychology.org/can-social-anxiety-from-humans-be-transmitted-to-mice/

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

Kim, N., Jeon, S. H., Ju, I. G., Gee, M. S., Do, J., Oh, M. S., & Lee, J. K. (2021). Transplantation of gut microbiota derived from Alzheimer’s disease mouse model impairs memory function and neurogenesis in C57BL/6 mice. Brain, Behavior, and Immunity, 98, 357–365. https://doi.org/10.1016/J.BBI.2021.09.002

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

Ritz, N. L., Brocka, M., Butler, M. I., Cowan, C. S. M., Barrera-Bugueño, C., Turkington, C. J. R., Draper, L. A., Bastiaanssen, T. F. S., Turpin, V., Morales, L., Campos, D., Gheorghe, C. E., Ratsika, A., Sharma, V., Golubeva, A. V., Aburto, M. R., Shkoporov, A. N., Moloney, G. M., Hill, C., … Cryan, J. F. (2024). Social anxiety disorder-associated gut microbiota increases social fear. Proceedings of the National Academy of Sciences, 121(1), e2308706120. https://doi.org/10.1073/pnas.2308706120

Rivet-Noor, C. R., Merchak, A. R., Render, C., Gay, N. M., Beiter, R. M., Brown, R. M., Keeler, A., Moreau, G. B., Li, S., Olgun, D. G., Steigmeyer, A. D., Ofer, R., Phan, T., Vemuri, K., Chen, L., Mahoney, K. E., Shin, J.-B., Malaker, S. A., Deppmann, C., … Gaultier, A. (2024). Stress-induced mucin 13 reductions drive intestinal microbiome shifts and despair behaviors. Brain, Behavior, and Immunity, 119, 665–680. https://doi.org/10.1016/j.bbi.2024.03.028

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

Elderly Individuals Eating a Balanced Diet have Better Mental Health and Cognitive Functioning

Posted on June 24, 2024June 26, 2024 by CNP Staff

An analysis of UK Biobank data published in Nature Mental Health revealed that elderly individuals eating a balanced diet tended to have better mental health and cognitive abilities than individuals with other types of dietary preferences.
Study authors identified three additional dietary types – vegetarian, starch-free or reduced starch, and high protein-low fiber.
The study identified structural differences in specific areas of the brain between individuals eating a balanced diet and those preferring other diet types.

Food preferences are determined by many different factors. In modern societies, individual food choices are primarily defined by food preferences. In other words, people tend to eat the foods they like.

Dietary patterns and health

The link between food and health is very straightforward – if we do not eat, we will eventually die. Our body needs lots of different substances to continue functioning. We need some of them, such as proteins, fats, and carbohydrates, in large quantities. These substances are called macronutrients. Our bodies need many other types of substances in much smaller quantities. These micronutrients include vitamins, minerals, specific essential fatty acids, and many other substances.

In modern societies, individual food choices are primarily defined by food preferences. In other words, people tend to eat the foods they like.

However, a growing body of evidence indicates that specific patterns of consuming foods that our body needs can also lead to adverse health effects (for example, fats, sugars, and proteins are all substances our body needs, but eating too much or focusing on just one can produce adverse effects). Studies indicate that prolonged consumption of a diet rich in foods abundant both in fats and sugars can dysregulate our food intake control system, make us prone to overeating, and eventually lead to overweight and obesity (Hedrih, 2024; Ikemoto et al., 1996; Thanarajah et al., 2023; Wilding, 2001).

Prolonged consumption of a diet rich in foods abundant both in fats and sugars can dysregulate our food intake control system.

Studies also link prolonged consumption of foods rich in refined sugars with the development of type 2 diabetes, mental health conditions like depression and anxiety, and various other health issues (Hedrih, 2023; Huang et al., 2023).

The UK Biobank

Until recently, one of the challenges of studying the links between food intake and disease is that the effects of following specific dietary patterns often materialize after longer periods of time, sometimes years or even decades. Studies of diet-health relationships can be done on rodents in much shorter time periods, but the applicability of such findings to humans remains unknown without actual studies on humans. There are more and more experimental studies of the diet-mental health relationship in humans as well. Still, legal and ethical constraints usually make data collection techniques much less comprehensive.

Another issue with studying the diet-health relationship in humans is that human dietary patterns tend to be very diverse (unless experimentally controlled for research purposes). It is very difficult for a single group of researchers to have a large number of participants in a single research study. The UK Biobank helps solve this issue.

The UK Biobank is a large biomedical database containing in-depth genetic and health information from around half a million UK residents. It was established in 2006 with the aim of improving the prevention, diagnosis, and treatment of a wide range of serious and life-threatening illnesses. Data stored in the UK Biobank are available to researchers worldwide.

The current study

Study author Ruohan Zhang and his colleagues wanted to explore the associations between naturally developed dietary patterns and cognitive functions, mental health, blood and metabolic biomarkers, brain characteristics, and genetics (Zhang et al., 2024).

They analyzed data from the UK Biobank from participants who completed a food preference questionnaire. This included 182,990 elderly individuals, the average of whom was 71 years old and 57% female.

The food preference questionnaire consisted of 150 questions that assessed both the sensory qualities of food (e.g., taste) and food preferences. It also asked about health-related behaviors such as physical activity and watching TV. Participants rated how much they liked specific types of foods and beverages.

In addition, the study used data on participants’ mental health, cognitive functioning, blood and metabolic biomarkers, magnetic resonance imaging scans of participants’ brains, and genetic data related to mental disorders (see Figure 1).

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

The dietary subtypes

The study authors analyzed the structure of associations between participants’ food preference ratings to identify groups of food items that the same people tend to like or dislike. In other words, they looked for sets of food items such that if a person likes one of the items in a set, it is more likely that he/she will also like the other items and vice versa. They also looked for groups of people with similar food preferences.

In this way, they identified 4 dietary subtypes: 1) Starch-free or reduced starch, 2) vegetarian, 3) high protein and lower fiber, and 4) balanced subtype. Individuals in the first subtype showed a higher preference for fruits, vegetables, and protein foods but a lower preference for foods containing starches (e.g., grains, potatoes, cassava, beans, peas, etc.). The vegetarian subtype showed a higher preference for fruits and vegetables but a lower preference for protein foods. The third subtype had a greater preference for snacks and protein foods but a lower preference for fruits and vegetables. The balanced subtype showed balanced preferences across all food categories (see Figure 2).

Figure 2. Dietary subtypes

Individuals preferring a balanced diet had better mental health and cognitive function

Results showed that individuals with the balanced dietary subtype had better mental health results than the other 3 categories. They tended to have lower anxiety and depression symptoms, less mental distress and psychotic experiences, less prone to self-harm, reported fewer trauma experiences, and better well-being.

Participants with the balanced diet and those preferring a high protein-low fiber diet had better cognitive functioning compared to the other two groups. Magnetic resonance imaging scans showed certain differences in brain structures between the subtypes (see Figure 3).

Figure 3. Results (Zhang et al., 2024)

Conclusion

The study shed light on the links between naturally developed dietary patterns and cognitive functioning in elderly individuals. It showed that a diet with balanced preferences for various food categories is associated with better mental health and cognitive abilities than diets focusing on specific types of food while avoiding others.

While the design of this study does not allow any definitive cause-and-effect inferences to be drawn from these results, it stands to reason that a balanced diet, a diet including many different types of food, would best provide all the nutrients needed for the optimal functioning of the human body, allowing for better cognitive functioning even in advanced age.

The paper “Associations of dietary patterns with brain health from behavioral, neuroimaging, biochemical and genetic analyses” was authored by Ruohan Zhang, Bei Zhang, Chun Shen, Barbara J. Sahakian, Zeyu Li, Wei Zhang, Yujie Zhao, Yuzhu Li, Jianfeng Feng, and Wei Cheng.

References

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

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

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

Zhang, R., Zhang, B., Shen, C., Sahakian, B. J., Li, Z., Zhang, W., Zhao, Y., Li, Y., Feng, J., & Cheng, W. (2024). Associations of dietary patterns with brain health from behavioral, neuroimaging, biochemical and genetic analyses. Nature Mental Health, 2(5), 535–552. https://doi.org/10.1038/s44220-024-00226-0

Western Diet Impairs Memory in Rats. Can It Do So in Humans?

Posted on June 16, 2024June 17, 2024 by CNP Staff

A study on rats published in Brain Behavior and Immunity found that raising them from an early age on Western-style meals resulted in impaired memory function.
These impairments were dependent on the brain’s hippocampus region and persisted after rats returned to consuming healthy diets.
The memory impairment was caused by dysregulated acetylcholine signaling.

We all know that eating certain foods can temporarily make us feel bad and unwell. However, more and more studies indicate that following certain dietary patterns might have longer-lasting adverse effects (Hedrih, 2024; Zhang et al., 2024). One such pattern attracting more and more research attention is the so-called Western diet.

The Western diet

The Western diet is broadly defined as a diet high in processed foods, saturated fats, and simple sugars (Hayes et al., 2024). This diet includes many food items rich in both fats and sugars, such as donuts, chocolates, cakes, cookies, milkshakes, and many types of fast food. Studies show that consuming such foods over prolonged periods can contribute to the dysregulation of our food intake control mechanisms, leading to frequent overeating and resulting in overweight and obesity (Hedrih, 2024).

Consuming highly processed foods over prolonged periods can contribute to the dysregulation of our food intake control mechanisms.

This likely happens because our brains contain separate neural pathways that create rewarding experiences when consuming fats and when consuming sugar. A study on mice identified these pathways and found that because they are separate from each other, their simultaneous activation leads to greater rewarding experiences than the activation of just one of them (McDougle et al., 2024) (see Figure 1). In other words, foods rich in sugars and fats are needed to activate both pathways simultaneously. While humans are different from mice, these particular neural pathways are probably organized in a similar fashion in humans as well.

Figure 1. Separate neural pathways create greater rewarding experiences

Such foods are rarely found in nature but are abundant in industrial, highly processed foods (Monteiro et al., 2019). Many researchers believe that the widespread consumption of such foods is at least partly behind the obesity pandemic that has developed in large parts of the world in the past decades (Wong et al., 2022).

Many researchers believe that the widespread consumption of [industrial, highly processed foods] is at least partially behind the obesity pandemic.

Western diet and cognitive dysfunction

Studies on rats also link Western diet consumption with cognitive dysfunction. This is especially true when rats consume Western diets as juveniles (Hsu et al., 2015). One region of the brain that seems particularly vulnerable to the effects of diet during early life is the hippocampus (Hayes et al., 2024).

The hippocampus is a small, curved structure located within the brain’s temporal lobe. Its primary functions include forming and consolidating new memories, spatial navigation, and emotional regulation.

The current study

Study author Anna M.R. Hayes and her colleagues wanted to explore how consuming a Western diet in early life impairs memory function in the short and long term. In their study, they fed cafeteria-style “junk food” to young rats and examined the outcomes.

The study was conducted on male Sprague Dawley rats housed in the animal vivarium at the University of Southern California. They started their assigned experimental diets on their 26th day of life.

The study procedure

The rats were housed individually in hanging wire cages, allowing the study authors to easily collect spilled food and accurately determine how much the rats ate.

Rats were divided into two groups. Researchers prepared a junk food cafeteria-style diet consisting of 20% kcal from protein, 35% from carbohydrates, and 45% from fat. This diet represented the Western diet and was given to one group of rats. The other group of rats ate healthy rat food.

Both groups of rats had free access to their assigned food and water. The first cohort of Western diet rats ate this diet for 60 days, but the study authors shortened it to 30 days for later cohorts. After this period, the study authors started giving healthy food to these rats as well.

These researchers conducted a series of behavioral and metabolic tests on the rats and analyzed their tissues in the end.

Rats fed a Western diet ate 15% more calories during the study period. They also showed deficiencies in contextual episodic memory, which depends on the function of the brain’s hippocampus region. The lower performance of Western diet-raised rats in tasks assessing contextual episodic memory persisted even after the study authors started feeding these rats healthy food (see Figure 2).

Figure 2. Procedure (Hayes et al., 2024)

Rats fed a Western diet ate 15% more calories during the study period. They also showed deficiencies in contextual episodic memory compared to rats raised on a healthy diet.

Other types of memory were not affected. There were also no differences in anxiety markers or how much the rats moved around between the two groups. Rats raised on Western diets also tended to have altered gut microbiome composition, which was reversed after they started eating healthy.

Rats raised on a Western diet also tended to have altered gut microbiome composition, which was reversed after they started eating healthy.

Memory impairments were caused by reduced acetylcholine signaling in the hippocampus

Memory functions in the hippocampus depend on the neurotransmitter acetylcholine. Study authors found that rats fed a Western diet had lower levels of acetylcholine in the hippocampus. Their cholinergic tone, i.e., the regular, ongoing activity level of acetylcholine in the hippocampus, was lower.

Further analysis revealed that the Western diet disrupted this acetylcholine-based activity, leading to impairments of memory functions that depend on it. Researchers were able to reverse these memory impairments by administering acetylcholine receptor agonists, i.e., substances that mimic the action of acetylcholine. This confirmed that the memory impairments observed due to the Western diet were caused by reduced acetylcholine signaling (see Figure 3).

Figure 3. Memory impairments and acetylcholine signaling

Conclusion

Overall, the study demonstrated a functional connection between eating a Western diet in early life and long-lasting dysregulation of acetylcholine signaling in the hippocampus, which results in memory impairments.

While these findings were obtained on rats, it is likely that results would not be too dissimilar in humans. Therefore, they help us better understand the biochemical mechanisms linking diet and cognitive health. These and similar findings could potentially help develop programs to better protect human cognitive health.

The paper “Western diet consumption impairs memory function via dysregulated hippocampus acetylcholine signaling” was authored by Anna M.R. Hayes, Logan Tierno Lauer, Alicia E. Kao, Shan Sun, Molly E. Klug, Linda Tsan, Jessica J. Rea, Keshav S. Subramanian, Cindy Gu, Natalie Tanios, Arun Ahuja, Kristen N. Donohue, Léa Décarie-Spain, Anthony A. Fodor, and Scott E. Kanoski.

See other findings on how the Western diet impairs hippocampal functioning in humans in CNP’s Diet-Mental Health Break here.

References

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

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

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

Obese Men Need Extra Energy to Resist Food Craving

Posted on June 10, 2024June 17, 2024 by CNP Staff

A study using positronic emission tomography published in the International Journal of Obesity found that obese men need extra energy to resist the desire to eat
Just presenting men with their favorite foods increased the use of glucose in several areas of the brain, regardless of obesity
The brains of obese men required more energy to inhibit food cravings than the brains of men who were not obese

We have all experienced situations where we really, really want to eat something we shouldn’t. This experience is probably best known to individuals trying to lose weight by simply eating less. This struggle with the desire to eat might be completely invisible to outside observers. It only happens in our minds. But does that psychological struggle to avoid eating require extra energy? Most importantly, is this energy expenditure greater when the struggle is harder? A group of researchers conducted a study back in 2020 to find out.

This struggle with the desire to eat might be completely invisible to outside observers. It only happens in our minds. But does that psychological struggle to avoid eating require extra energy?

Hunger, food intake control and obesity

Our body needs food to survive. However, it is also possible to eat more than we need. Our body has a complex neuropsychological mechanism that controls this balance (Atasoy et al., 2012). This mechanism involves a complex interplay of signals from the digestion system, hormones like leptin and ghrelin (Hedrih, 2024b), and processes in the brain, primarily in the hypothalamus. The hypothalamus contains a set of neurons known as hunger neurons (agouti-related peptide neurons) that activate food-seeking and intake behaviors when triggered. On the level of subjective experiences, the described processes produce the sensation of hunger when we need food and satiety when we have eaten enough (Hedrih, 2024a) (more about neuropsychological mechanisms can be found in CNP’s NP 100 Series Introductory Certificate in Nutritional Psychology).

However, studies have shown that lack and abundance of required nutrients are not the only things that trigger feelings of hunger and satiety. Hunger can be triggered by stress, the smell or taste of delicious food, our eating habits, and many other factors (Hedrih, 2023; Isherwood et al., 2023; Swami et al., 2022).

The lack and abundance of required nutrients are not the only things that trigger feelings of hunger and satiety

This food intake regulation mechanism can also become dysregulated, making us believe that we need more food when we actually do not. When this happens, we will tend to start overeating and, in time, become overweight or obese (Ikemoto et al., 1996; Pujol et al., 2021).

This food intake regulation mechanism can also become dysregulated, making us believe that we need more food when we actually do not

Food reward system

Because food is crucial for survival, our brains have evolved to treat food as a strong natural reward. Its rewarding characteristics become particularly strong when we have not eaten for some time. Even just showing food to a person who wants to eat, it increases the activity and energy expenditure in the orbitofrontal cortex region of the brain (Wang et al., 2020), a region that plays a key role in regulating our food intake. The hungrier we are, the stronger the increase in metabolism in this part of the brain will be.

Even just showing food to a person who wants to eat it increases the activity and energy expenditure in the orbitofrontal cortex region of the brain

Studies indicate that obese individuals are more sensitive to hunger than normal-weight individuals. The regions of their brains that process rewards become more active when they see food (Devoto et al., 2018). But does this mean their brains will also be more active when they resist eating the food they like?

Obese individuals are more sensitive to hunger than normal-weight individuals

The current study

Study author Gene-Jack Wang and his colleagues hypothesized that obese individuals would have decreased activation in the orbitofrontal cortex region of the brain, in the striatum, and the insula when resisting the desire to eat appealing food. They would also have increased activity in the anterior cingulate cortex. They conducted a study to test whether this is really the case (see Figure 1).

Figure 1. Hypothesized regions of the brain in obesity

The study procedure

The study participants were 16 obese and 11 non-obese men. The authors first asked them to fill out a questionnaire related to their favorite foods and food smells and to rate a list of foods for desirability. Participants also completed an assessment of eating behaviors (the Three Factor Eating Questionnaire).

On three different days, study participants underwent positron emission tomography (PET) scans of their brains using fluorodeoxyglucose as the radiotracer. Fluorodeoxyglucose is similar to glucose but has one atom replaced by the radioactive isotope fluorine-18. This allows researchers to detect fluorodeoxyglucose using the PET scanner and assess the level of metabolic activity in the scanned brain regions – more active regions will use more glucose, hence more fluorodeoxyglucose.

On the first day, the study authors placed cotton swabs impregnated with participants’ favored foods on participants’ tongues 15 minutes before the scan began and throughout the scanning procedure. In this way, participants could taste the food but not eat it. They would also warm participants’ favorite foods and present them one after another to each study participant. At the same time, participants verbally described their favorite foods and how they like to eat them. Participants were hungry during the procedure, having not eaten anything since the previous evening.

On the second day, the study authors applied the same procedure and told participants to inhibit their food desire before the food presentation began. On the third day, participants underwent PET scans without any food presentation (see Figure 2).

Figure 2. Study procedure (Wang et al., 2020)

Food stimulation increases glucose metabolism in several brain regions

When participants from both groups were presented with food, their glucose metabolism increased in the brain’s inferior and superior frontal gyrus regions, the default mode network, and the cerebellum. Attempting to suppress the desire to eat the food reduced metabolism in the right subgenual anterior cingulate, orbitofrontal areas, bilateral insula, and temporal gyri areas (see Figure 3).

Figure 3. Food stimulation increases glucose metabolism in several brain regions

The brains of obese men use more energy to inhibit the desire to eat

When study authors instructed participants to inhibit their food desire (on day 2), this led to an increase in metabolism in the pregenual anterior cingulate cortex and caudate areas of the brains of obese men (compared to the same situation without inhibition). In the same condition, non-obese men showed decreased metabolism in these areas. Obese men who reported stronger changes in food desire after attempting to inhibit it showed lower changes in the level of metabolic activity in this brain area compared to the condition with food stimulation but with no inhibition (see Figure 4).

Figure 4. Effect of inhibiting food desire in obese men

Conclusion

When attempting to inhibit their food desire, obese men showed higher activity in two areas of the brain involved in self-regulation and emotional rewards. This shows that, in obese men, inhibiting food desire is an active process that requires extra energy.

When attempting to inhibit their food desire, obese men showed higher activity in two areas of the brain involved in self-regulation and emotional rewards

This likely means that obese individuals need to commit greater psychological effort to achieve the same level of control over eating behaviors compared to nonobese individuals. The difference in the effort required to control food intake is a factor that should be taken into account when planning weight loss programs.

The paper “Inhibition of food craving is a metabolically active process in the brain in obese men” was authored by Gene-Jack Wang, Ehsan Shokri Kojori, Kai Yuan, Corinde E. Wiers, Peter Manza, Christopher T. Wong, Joanna S. Fowler, and Nora D. Volkow.

Important note. In the original paper, figure (3b), which presented the key finding (the increase in metabolic activity in the pregenual anterior cingulate cortex and caudate areas of obese men), shows results that are the opposite of what was described in the text of the paper (i.e., it shows an increase in nonobese participants when inhibiting the desire to eat, and a decrease in the obese group). This text relied on the study authors’ textual interpretation of results and assumed that the designations of the two groups in the figure were inverted. If this was not the case, then this part of the results presented in this text is incorrect.

References

Atasoy, D., Betley, J. N., Su, H. H., & Sternson, S. M. (2012). Deconstruction of a neural circuit for hunger. Nature, 488(7410), 172–177. https://doi.org/10.1038/nature11270

Devoto, F., Zapparoli, L., Bonandrini, R., Berlingeri, M., Ferrulli, A., Luzi, L., Banfi, G., & Paulesu, E. (2018). Hungry brains: A meta-analytical review of brain activation imaging studies on food perception and appetite in obese individuals. Neuroscience & Biobehavioral Reviews, 94, 271–285. https://doi.org/10.1016/j.neubiorev.2018.07.017

Hedrih, V. (2024a, March 4). Researchers Identify Neural Pathways Transmitting Anti-Inflammatory Effects of Hunger. Nutritional Psychology. https://www.nutritional-psychology.org/researchers-identify-neural-pathways-transmitting-anti-inflammatory-effects-of-hunger/

Hedrih, V. (2024b, May 20). Do Gut Microbiota Play an Important Role in Regulating Food Intake and Satiety? Nutritional Psychology. https://www.nutritional-psychology.org/do-gut-microbiota-play-an-important-role-in-regulating-food-intake-and-satiety/

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

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

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

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

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