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PsychoNutritional Education Within Nutritional Psychology: A Study Linking Sugar Consumption with Adverse Health Outcomes

Posted on June 6, 2023November 10, 2023 by CNP Staff

Within nutritional psychology, we explore the dietary and nutritional elements influencing the diet-mental health relationship. This involves identifying the processes and mechanisms through which our diet and dietary intake patterns influence our brain, behavior, and experience. Sugar intake is a substantial and increasing part of the human diet. Understanding its influence on our diet-mental health relationship is important within nutritional psychology. Let’s look at a recent study published in the BMJ that explores the sugar-health connection.

This umbrella review by Huang and colleagues (2023) reviewed 73 meta-analytic articles exploring the connection between sugar consumption and adverse health outcomes. In this study, findings reported that sugar consumption is associated with many adverse health outcomes. Specifically, this study identified associations between sugar consumption and eighteen harmful metabolic issues, ten harmful cardiovascular conditions, seven types of cancer, and ten other types of adverse medical conditions. The best quality evidence was for links between sugar consumption and increased body weight (Huang et al., 2023).

Studies have shown an association between sugar consumption and certain metabolic and cardiovascular issues, cancer, obesity, and other adverse medical conditions.

Sugars and carbohydrates

Carbohydrates are a type of molecule that provides the body with energy. Alongside protein and fat, carbohydrates are considered macronutrients, nutrients the human body requires in large quantities. The three main types of carbohydrates are sugars, starches, and fibers (Slavin, 2013) (see Figure 1).

Figure 1. Three types of carbohydrates

Fibers and starches are called complex carbohydrates, made of many simple carbohydrates strung together to form large molecules. They need to be broken down by the body into simple carbohydrates to be used. The human body can break down and digest starches, such as those found in bread, cereals, or pasta, but it cannot digest most fibers. However, eating foods containing fiber can help an individual feel full (satiated) and be less likely to overeat (Cho et al., 2010; Samra & Anderson, 2007).

Eating foods containing fiber can help one feel satiated and be less likely to overeat.

Sugars

Sugars are called simple carbohydrates because their molecules are the smallest and the simplest. The three most common sugars are glucose (the primary source of energy for the cells of our body), fructose (the naturally occurring sugar found in fruits, honey, and vegetables), and sucrose (the substance sold in supermarkets as “sugar,” a combination of glucose and fructose, also naturally occurring).

Sugars are naturally found in various fruits, vegetables, and animal products (e.g., honey, milk, meat). However, sugars are also very often added to food and drinks, either by the cook or the manufacturer, during food production and preparation, or directly by the consumer, before consumption. This is done to increase the sweetness of food, thus making it tastier. Researchers refer to sugars added to food and beverages in this way as “added sugars” (Huang et al., 2023).

Added sugars

Generally, sugar-sweetened beverages are the largest source of added sugars. These include soft drinks (both carbonated and non-carbonated), fruit drinks, and sports and energy drinks. Milkshakes, smoothies, and similar sweetened drinks also contain added sugar.

Foods with lots of added sugar include various desserts, candies, cakes, sweet snacks, ice cream, granola and energy bars, milk chocolate, candied dried fruits, canned fruits, sweetened flavored yogurts, many condiments (such as ketchup), most cereals, cocoa spreads, creamers, jams, and many others (see Figure 2).

Figure 2. Foods containing lots of added sugars

What are the health consequences of high sugar consumption?

Although the Dietary Guidelines for Americans by the United States Department of Agriculture recommend that between 45% and 65% of calories in our diet should come from carbohydrates, they also suggest that the intake of added sugars should be very limited or altogether avoided. Sources such as the Harvard T.H. Chan School of Public Health website specify that the body needs no carbohydrates from added sugar. Despite this, foods and drinks with added sugars represent a large share of people’s dietary intake worldwide, with consumption increasing in many developing countries. This is particularly true with sugar-sweetened beverages such as soft drinks (Huang et al., 2023).

The body does not need carbohydrates from added sugar. Yet, foods and drinks with added sugars represent a large share of the dietary intake of people worldwide.

Numerous studies have linked a high intake of sugars with an increased risk of various adverse health outcomes. These include obesity, diabetes, cardiovascular disease, dental caries, and abnormal fat accumulation in tissues where fat is not normally stored, such as the liver, muscles, pancreas, heart, and others.

The current study

Study author Yin Huang from the Sichuan University in Chengdu, China, and his colleagues wanted to evaluate the quality of evidence, potential biases, and validity of all available studies on dietary sugar consumption and health outcomes.

The number of scientific studies exploring links between the consumption of sugars and health runs in hundreds of thousands worldwide, and new ones are conducted and published daily. These researchers conducted an umbrella review.

The number of scientific studies exploring links between the consumption of sugars and health runs in hundreds of thousands worldwide.

What is an umbrella review?

When a certain topic attracts a lot of research interest, many studies are conducted to explore that topic further. Studies are conducted by different researchers. They use more or less different methodologies and can also conceptualize key factors they explore in ways that are not completely identical.

Scientists need ways to integrate the multitudes of findings produced in this way. To do this, they can conduct systematic reviews, evaluating the findings of different studies and discussing similarities and differences between their methodologies and findings. When there are many studies (e.g., more than a dozen) that explore the same link between certain factors or the same aspect of some phenomenon, a meta-analysis can be conducted to map the strength of the links observed and make quantitative inferences about tendencies in the findings of these studies.

Finally, when the number of studies on a topic is really large, and their study methodologies and factors are diverse (i.e., there are many systematic reviews and meta-analyses), the type of study that can integrate their results is called the umbrella review. An umbrella review is a type of systematic review that combines evidence from a multitude of systematic reviews and meta-analyses on a certain topic (see Figure 3).

It starts with a rigorous process of searching and selecting relevant systematic reviews and meta-analyses to include in the study. Assessing the quality of the included studies and integrating the findings of different reviews follows. Its very name indicates a study incorporating the results of many integrating studies (see Figure 3).

Figure 3. Set-up of an umbrella review

The procedure

The authors searched publicly available databases of research publications for systematic reviews and meta-analyses that studied the health outcomes of sugar consumption. They considered studies of sugar consumption that measured the specific proportion of sugars in foods, the percentage of total energy derived from sugars, or combinations of these two. They searched PubMed, Embase, Web of Science, and the Cochrane Database of Systematic Reviews from inception through January 2022. They looked for papers written in English.

They used “sugars” or “sugar” and “systematic review” or “meta-analysis” as keywords for their searches. Two of the authors conducted the searches separately. A third author resolved any discrepancies between their literature screening results.

Search results

The search yielded 8601 research papers—2184 of those turned out to be duplicates and were excluded. Of the remaining 6417 papers, 6221 were excluded from further analysis for various reasons. This left 196 papers with eligible titles and abstracts. Of these, researchers excluded a further 124 because data on sugar could not be extracted from them, because they were reviewed without meta-analyses, or due to various methodological issues. 4 turned out not to be in English and were thus excluded.

In the end, 73 scientific articles contained results of meta-analyses and met all the inclusion criteria set by the researchers. These papers were included in the umbrella analysis.

The quality of evidence

An important aspect these researchers considered when analyzing was the quality of evidence presented for the claims made in the analyzed papers. Not all scientific findings are the same. Some findings are obtained on large samples that are likely to be representative of studied populations. They describe strong and clear effects of one studied factor on another or strong associations between phenomena. Such studies are considered to provide strong evidence. When the physical mechanism creating the claimed effects is known, or at least when researchers have a plausible idea of what it might be, the evidence is even stronger.

However, studies are sometimes done on small samples that are or might be quite different from the population. They might report associations between studied phenomena without any further knowledge or idea about the physical mechanism creating the reported link. And the links reported might be very weak, sometimes so weak that one might suspect they are simply due to chance. The evidence quality provided by such studies is considered to be much worse.

In the case of this study, researchers classified meta-analytic studies they analyzed into five categories based on the strength of the evidence. The highest evidence strength was assigned to studies conducted on very large samples (over 1000 cases or over 20,000 participants, depending on the features of the studied phenomena) and reported strong effects or associations similar across different studies covered by the meta-analysis analyzed. On the other hand, studies that reported results that were near zero or were very weak were considered to provide weak evidence for the associations reported. Sample sizes were taken into account because it is much, much easier to obtain small samples that are unusual and thus provide unusual results than large samples (Hedrih & Hedrih, 2022).

They assigned these evidence classes numbers ranging from 1 (best quality evidence) to 4 (weakest evidence) and N.S. (no association at all, N.S. stands for non-significance).

Figure 4. Quality of evidence

High sugar consumption is associated with four beneficial and 45 harmful health outcomes.

Results showed that most of the meta-analyses included in the study studied associations between the consumption of sugar and endocrine/metabolic diseases (such as diabetes, 28 such studies), cancer (25 studies), and cardiovascular diseases (17) (see Figure 5).

Figure 5. The contents of this umbrella review

These studies reported four beneficial associations between high sugar consumption and medical outcomes and 45 harmful ones. Thirty-four studies reported no associations between sugar consumption and the health outcomes they examined.

Children who consume more sweetened beverages have a 55% higher chance of being obese.

Higher consumption of sugar-sweetened beverages was associated with higher body weight and a higher risk of gout (class 4 evidence). Gout is arthritis characterized by a buildup of uric acid crystals in the joints that cause inflammation and pain.

Children who consumed high quantities of sugar-sweetened beverages had a 55% higher likelihood of being obese compared to children who did not consume such beverages (class 2 evidence). The more frequently children consumed such beverages, the higher their body mass was.

Children who consumed high quantities of sugar-sweetened beverages had a 55% higher likelihood of being obese than children who did not.

Sugar consumption, coronary heart disease, and cancer

One study linked a higher intake of sugar-sweetened beverages with the risk of coronary heart disease. They reported that every additional glass of sugar-sweetened beverages (250 mL) per day was associated with a 17% increase in the risk of coronary heart disease (class 2 evidence). Another study linked higher consumption of these beverages with an increased likelihood of myocardial infarction (class 3 evidence).

Every additional glass of sugar-sweetened beverages (250 mL) per day was associated with a 17% increase in the risk of coronary heart disease.

One meta-analysis reported that participants who consumed sugar-sweetened beverages the most had a two times higher risk of developing hepatocellular carcinoma (a type of liver cancer, class 4 evidence). Another meta-analysis linked higher fructose intake with a higher risk of pancreatic cancer (class 3 evidence).

Other health outcomes

A recent meta-analysis reported that every additional glass (250 mL) of sugar-sweetened beverages per day was associated with a 4% increase in death from all causes (class 3 evidence). Another study reported a link between higher consumption of these drinks and depression (class 2 evidence).

Researchers also reported several other health outcomes linked to sugar consumption, but the evidence for those associations was very weak (class 4). These included links between increased consumption of sugar-sweetened beverages and hypertension, death from cardiovascular disease, prostate cancer, death from breast cancer, overall risk of death from cancer, risk of asthma, fatty liver disease, bone mineral density, and others.

Health outcomes not associated with sugar include the risk of colorectal cancer, ovarian cancer, and death from cardiovascular disease. Fructose intake was not associated with type 2 diabetes, risk of hypertension, and uric acid concentrations in the serum. Consumption of sugar of sugar-sweetened beverages was not found to be associated with the risk of chronic kidney disease. Do remember that all the studies conducted are meta-analyses.

Conclusion

The analysis showed that high dietary sugar intake is associated with various harmful health outcomes. Although evidence was strongest for the effects of high intake of sugars on increased body weight, particularly in children, the evidence for other adverse health effects is also considerable. These findings come from a series of meta-analyses, each of which integrated findings of multitudes of individual studies conducted in different places and on different people worldwide, giving extra weight to the reported results.

The insights from these studies can help better educate the general population about health outcomes related to nutritional choices, particularly consuming food and beverages with extreme quantities of added sugars. They can also be useful to manufacturers of food and beverages as a guide to make future food products healthier.

The paper “Dietary sugar consumption and health: umbrella review” was authored by Yin Huang, Zeyu Chen, Bo Chen, Jinze Li, Xiang Yuan, Jin Li, Wen Wang, Tingting Dai, Hongying Chen, Yan Wang, Ruyi Wang, Puze Wang, Jianbing Guo, Qiang Dong, Chengfei Liu, Qiang Wei, Dehong Cao, and Liangren Liu.

Figure 6. Study findings of the umbrella review

References

Cho, S., Case, I., & Nishi, S. (2010). Fiber and Satiety. In Weight Control and Slimming Ingredients in Food Technology (pp. 227–276). Blackwell Publishing Ltd.

Hedrih, V., & Hedrih, A. (2022). Interpreting statistics for beginners : a guide for behavioural and social scientists. Routledge, Taylor&Francis Group. https://doi.org/10.4324/9781003107712

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

Samra, R. A., & Anderson, G. H. (2007). Insoluble cereal fiber reduces appetite and short-term food intake and glycemic response to food consumed 75 min later by healthy men. The American Journal of Clinical Nutrition, 86(4), 972–979. https://doi.org/10.1093/AJCN/86.4.972

Slavin, J. L. (2013). Carbohydrates, dietary fiber, and resistant starch in white vegetables: Links to health outcomes. Advances in Nutrition, 4(3), 3515–3555. https://doi.org/10.3945/AN.112.003491

The Western Diet and How it Weakens the Interoceptive Signals that Control our Appetitive Behavior

Posted on May 9, 2022January 29, 2025 by CNP Staff

In terms of the global dietary landscape, the Western diet provides a rich diversity and abundance of highly processed foods and beverages that are easy to consume. Although highly palatable, this availability also provides us with a steady stream of external cues that can heighten feeding behaviors. Obesogenic environments (those prevalent with cues that promote excessive weight gain) are pervasive across Western societies and are hypothesized to overwhelm the internal cues that normally regulate our dietary intake (Sample et al., 2016).

Obesogenic environments (those prevalent with cues that promote excessive weight gain) are pervasive across Western societies and are hypothesized to overwhelm the internal cues that normally regulate our dietary intake.

These internal cues, which are perceived by the brain through neural circuits in a process known as interoception, are critical in maintaining proper appetites and, ultimately, a healthy physical and mental body. Interoception refers to the process of identifying and listening to internal bodily signals, which may be a modifiable determinant of appetite regulation and weight gain (Robinson et al., 2018). Research is exploring the mechanisms by which interoceptive sensations mediate our nutritional health.

Interoception: our body’s communication network to eating regulation

Interoception is considered one of the six foundational elements within nutritional psychology and is defined as “our internal awareness of the body’s state.” Encompassing conscious and subconscious physiological signals, we sense a variety of internal cues that inform our brain about our heartbeat, breathing, and hunger. A growling stomach, a desire for certain foods, fatigue from a lack of food, and even emotions associated with eating are all examples of internal sensations that can further drive feeding and appetitive behaviors.

The study of interoception is increasing in the field of neuroscience, and there is compelling evidence demonstrating the links between awareness of one’s internal state (called interoceptive awareness) and the regulation of emotion (Price & Hooven, 2018).

Considering the diet-mental health relationship (DMHR), the regulation of food intake—and, perhaps, bodyweight—partially depends on the brain’s capability to respond to internal physiological signals arising from external food-related cues in our environment (Sample et al., 2016). In other words, the ability of environmental food cues to evoke appetitive and dietary intake behavior is held in check by interoceptive satiety signals that inhibit those behaviors (Sample et al., 2016).

There is compelling evidence demonstrating the links between awareness of one’s internal state (called interoceptive awareness) and the regulation of emotion.

Western diets impair the interoceptive signals that control our eating.

In this 2016 study, Sample and her colleagues conducted experiments to investigate how food-related external cues may overwhelm interoceptive internal cues that normally regulate dietary intake. They hypothesized that food-related external cues could promote overeating by attenuating the brain’s hippocampal function, which processes interoceptive satiety signals.

The authors examined the role of a Western diet (WD) (consisting of highly processed, low nutrient foods) and its obesogenic effect on the internal sensations that mediate our appetite. Rodents were trained to use internal cues (i.e., feelings of hunger) and external cues (i.e., food) and then assigned to two distinct groups: a regular chow or WD chow. Both groups then removed external cues to assess the different diets’ direct impact on interoceptive signals that mediate feeding. Interestingly, the study found that the WD group failed to distinguish between internal and external cues (Figure 1).

Figure 1. Western diets (WD) impact the internal interoceptive signals used by the hippocampus to regulate appetite and dietary intake. The positive sign indicates the addition of either regular or WD food and the negative sign indicates the removal of food-related external cues.

The inability to parse between interoceptive deprivation (i.e. “I am hungry”) and external signals (i.e. “the food looks delicious”) is a function that has been characterized by the hippocampus, with previous studies demonstrating how the WD could interfere with homeostatic feeding behaviors (Jacka, 2015; Attuquayefio, 2016; Stevenson, 2020).

Indeed, the authors noticed that inhibiting the hippocampus (through surgical injections of a neurotoxin) in a cohort of rodents led to increased weight gain and reduced sensitivity to satiety hormones like cholecystokinin, which normally tells the body you are full and slows digestion (Figure 1). Ultimately, the study suggests that the WD impairs the interoceptive energy state signals that the hippocampus relies on to regulate feeding behavior.

Current research further validates this connection. In a recent study by Robinson, Marty, Higgs, and Jones (2022) exploring the connection between interoception, eating behavior, and body weight in over a thousand human adults, these researchers found that poorer self-reported ability to detect interoceptive signals (deficits in interoceptive accuracy) was, in fact, predictive of higher BMI.

The findings are certainly food for thought as we navigate the choices of food available to us in our day-to-day lives—especially for those living in regions characterized by a high intake of the Western diet. Knowing the options and alternatives of nutritious foods is essential to maintaining proper feeding behaviors that will keep one healthy.

References

Attuquayefio, T., Stevenson, R. J., Boakes, R. A., Oaten, M. J., Yeomans, M. R., Mahmut, M., & Francis, H. M. (2016). A high-fat high-sugar diet predicts poorer hippocampal-related memory and a reduced ability to suppress wanting under satiety. Journal of experimental psychology. Animal learning and cognition, 42(4), 415–428. https://doi.org/10.1037/xan0000118

Jacka, F. N., Cherbuin, N., Anstey, K. J., Sachdev, P., & Butterworth, P. (2015). Western diet is associated with a smaller hippocampus: a longitudinal investigation. BMC medicine, 13, 215. https://doi.org/10.1186/s12916-015-0461-x

Price, C. J., & Hooven, C. (2018). Interoceptive Awareness Skills for Emotion Regulation: Theory and Approach of Mindful Awareness in Body-Oriented Therapy (MABT). Frontiers in psychology, 9, 798. https://doi.org/10.3389/fpsyg.2018.00798

Robinson, E., Marty, L., Higgs, S., & Jones, A. (2021). Interoception, eating behaviour and body weight. Physiology & behavior, 237, 113434. https://doi.org/10.1016/j.physbeh.2021.113434

Sample, C. H., Jones, S., Hargrave, S. L., Jarrard, L. E., & Davidson, T. L. (2016). Western diet and the weakening of the interoceptive stimulus control of appetitive behavior. Behavioural brain research, 312, 219–230. https://doi.org/10.1016/j.bbr.2016.06.020

Stevenson, R. J., Francis, H. M., Attuquayefio, T., Gupta, D., Yeomans, M. R., Oaten, M. J., & Davidson, T. (2020). Hippocampal-dependent appetitive control is impaired by experimental exposure to a Western-style diet. Royal Society open science, 7(2), 191338. https://doi.org/10.1098/rsos.191338

The “Diet-Sleep” Relationship: Is there A Connection?

Posted on May 13, 2022January 29, 2025 by CNP Staff

With growing recognition of the link between mental health and sleep, many of us want to know if making lifestyle changes, including what we eat, can impact our sleep habits and potentially improve our overall psychological well-being.

Recent research by Rostami et al. (2022) examines the link between sleep quality and sleep-related outcomes and a newly proposed hybrid diet, referred to as the Mediterranean-DASH Diet Intervention for Neurodegenerative Delay, or MIND diet. The MIND diet combines the Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets, which have both been previously studied for their impact on various aspects of psychological health (Bayes et al., 2022; Salari-Moghaddam et al., 2019) respectively).

Rostami and colleagues set out to explore the relationship between the MIND diet and psychological function, including depression, anxiety/stress, and sleep.

The MIND diet includes 10 “brain-healthy food groups” (green leafy vegetables, other vegetables, nuts, berries, beans, whole grains, fish, poultry, olive oil, and wine) and identifies 5 “brain-unhealthy food groups” (red meats and processed red meat products, butter and stick margarine, cheese, pastries, fast fried foods, and sweets).

In this study, Rostami and colleagues set out to explore the relationship between the MIND diet and psychological function, including depression, anxiety/stress, and sleep.

This is the first study to explore the relationship between adherence to the MIND diet and sleep.

400 Iranian adult males with a mean age of 38.67 years working in healthcare centers were randomly selected to participate. They had no history of chronic disease. Using a food frequency questionnaire (FFQ) consisting of 168 foods and their standard serving sizes, participants reported how often they consumed each food. The research team then calculated an overall MIND diet score of 0-14 for participants based on intake of both the “brain-healthy food groups” of the MIND diet and the specified “brain-unhealthy food groups” (Note: wine was not included in the calculated MIND diet score since it was not on the FFQ). A higher MIND diet score indicated greater adherence to the MIND diet.

Additional information obtained from participants consisted of demographics (i.e., age, smoking status, marital status, education), height and weight measurements for calculation of Body Mass Index (BMI), and frequency of physical activity. The researchers used the Depression Anxiety and Stress Scale (DASS-21) to look for depression, anxiety, and stress and included questionnaires to examine sleep quality (Pittsburgh Sleep Quality Index), daytime sleepiness (Epworth Sleepiness Scale), and insomnia (Insomnia Severity Index).

Greater adherence to the MIND diet was linked to better sleep quality and fewer reports of daytime sleepiness and insomnia.

According to Rostami et al., this is the first study to explore the relationship between adherence to the MIND diet and sleep. They found that greater adherence to the MIND diet was linked to better sleep quality and fewer reports of daytime sleepiness and insomnia. The authors suggest that the anti-inflammatory and antioxidant properties of the MIND diet likely contribute to the observed positive impact on sleep.

The anti-inflammatory and antioxidant properties of the MIND diet likely contribute to the observed positive impact on sleep.

No significant effect between MIND-diet adherence and depression, anxiety, or stress was observed in this study.

Limitations of these findings include lack of generalizability of results to other populations and possible misreporting from participants on self-report measures. The nature of the study design (cross-sectional) prevents findings related to causality. The authors recommend further investigation to address these factors and verify their results.

References:

Bayes, J., Schloss, J., & Sibbritt, D. (2022). The effect of a Mediterranean diet on the symptoms of depression in young males (the “AMMEND” study): A Randomized Control Trial. The American journal of clinical nutrition, nqac106. Advance online publication. https://doi.org/10.1093/ajcn/nqac106

Rostami, H., Parastouei, K., Samadi, M., Taghdir, M., & Eskandari, E. (2022). Adherence to the MIND dietary pattern and sleep quality, sleep related outcomes and mental health in male adults: A cross-sectional study. BMC Psychiatry, 22(167). https://doi.org/10.1186/s12888-022-03816-3

Salari-Moghaddam, A., Keshteli, A. H., Mousavi, S. M., Afshar, H., Esmaillzadeh, A., & Adibi,(2019). Adherence to the MIND diet and prevalence of psychological disorders in adults. Journal of affective disorders, 256, 96–102. https://doi.org/10.1016/j.jad.2019.05.056

Are You What Your Gut-Microbiome Wants You To Eat?

Posted on May 3, 2022January 30, 2025 by CNP Staff

We’ve all heard the saying “you are what you eat,” but new microbiome research is shedding light on this old adage, with a more modern-day update being “you are what your gut-microbiome wants you to eat.” Let’s look at why this is the case.

First, we know that our food choices significantly impact our physical and mental health. As far back as the 1800s and 1900s, scientists hypothesized an apparent correlation between our food intake and the subsequent effects on appetite, body image, and brain function (Tzameli, 2013). Though biomedical research has already established the endocrine responses that regulate hunger and satiety in the gut-brain axis signaling, little attention has been paid to the mechanisms that influence an individual’s choice of food and nutrition.

Microorganisms that live in our gut may influence what we eat!

A growing body of evidence indicates that our gut microbiome may be one of the factors influencing our food choices. From Nutritional Psychology conceptualization, we are beginning to understand that eating behavior and food preferences are dependent on many aspects of the diet-mental health relationship (DMHR), such as our psychosocial environment, interoceptive experiences, sensory perception, cognitive processes, and psychological state. However, emerging research in the Microbiota-Gut Brain Axis (MGBA) suggests that the microorganisms residing within our gut may also influence what we eat. Therefore, the classic expression, “you are what you eat,” may soon be reframed as “you are [also] what your microbiome wants you to eat.”

A feedback loop between our gut microbiome, brain, and food choices.

To explore the influence of the gut microbiome on diet selection behavior, Trevelline and Kohl conducted an experiment in 2022 to study the influence of gut microbes on the diet selection behaviors in mice.

The classic expression, “you are what you eat,” may soon be reframed as “you are [also] what your microbiome wants you to eat.”

To achieve this, intestinal microbiota from three “donor” mouse species, each with distinct foraging behavior, were transplanted into germ-free “host” mice to colonize their intestinal tracts.

Following that, the donor germ-free mice were randomly divided into three treatment groups, each based on the donor species:

Carnivore (i.e., predatory-based)
Herbivore (i.e., plant-based)
Omnivore (i.e., inclusive-based)

The mice were then given a choice between a low protein-carbohydrate (LPC) diet and a high protein-carbohydrate (HPC) diet, and their diet preferences were tracked for 11 days. To assess the impact of the donor microbiome on host diet selection behavior, the researchers compared the microbiomes of mice in three treatment groups: predatory (carnivores), inclusive (omnivores), and plant-based (herbivores) (Fig 1A).

Figure 1A. Experimental design to assess host diet selection behaviors across different microbiomes. From Trevelline and Kohl, Proceedings of the National Academy of Sciences, 2022.

Strikingly, the authors discovered that when mice have given a choice of selected diets varying in macronutrient composition, each microbiome had a distinct effect on food choice behavior (Fig 1B). For example, host mice that received microbiota from herbivorous donors voluntarily ate fewer carbohydrates, evidenced by a higher protein:carbohydrate (P:C) ratio diet intake. On the other hand, omnivore and carnivore treatment groups chose a lower P:C ratio diet intake.

Given that these host mice had no microbiome prior to transplantation, the change in diet selection behavior is evidence of the microbiome influencing food choice (Alcock, 2014). Moreover, through an in-depth analysis of blood and fecal samples, the authors discovered the microbial release of essential amino acids (EAAs) from the gut microbiome of host mice, including tryptophan. Tryptophan is an important food choice driver because it is a precursor to serotonin, the happiness hormone that has been shown to regulate feeding behavior, metabolism, and diet selection (Harrold, 2012; Cryan, 2019; Kaur & Bose, 2019; Yabut, 2019; Gao, 2020; Trevelline & Kohl, 2022). Together, these findings show that the gut microbiome can influence host diet selection behavior by mediating the availability of essential amino acids (EAAs).

The gut microbiome can influence host diet selection behavior by mediating the availability of Essential Amino Acids (EAAs).

Finally, the findings discussed here are of great interest to Nutritional Psychology. Together with other studies, they show us that what we eat can be influenced by our microbiota’s ‘bottom up’ connection. And in turn, this connection affects our food choices and dietary intake, which cycles back to influence our microbiota.

Figure 1B. Gut microbiome of donor mice altering feeding choices in host mice.

This reciprocal feedback loop is partly caused by the gut microbiome’s ability to synthesize essential amino acids (EAAs), which interact with the gut-brain axis and, in turn, influence dietary habits. Depending on the food choices made, the body’s response to those choices can be beneficial or detrimental. Therefore, increasing awareness of the factors influencing dietary intake may help us to impact both our physical and mental health positively.

References

Alcock, J., Maley, C. C., & Aktipis, C. A. (2014). Is eating behavior manipulated by the gastrointestinal microbiota? Evolutionary pressures and potential mechanisms. BioEssays : news and reviews in molecular, cellular and developmental biology, 36(10), 940–949. https://doi.org/10.1002/bies.201400071

Cryan, J. F., O’Riordan, K. J., Cowan, C., Sandhu, K. V., Bastiaanssen, T., Boehme, M., Codagnone, M. G., Cussotto, S., Fulling, C., Golubeva, A. V., Guzzetta, K. E., Jaggar, M., Long-Smith, C. M., Lyte, J. M., Martin, J. A., Molinero-Perez, A., Moloney, G., Morelli, E., Morillas, E., O’Connor, R., … Dinan, T. G. (2019). The microbiota-gut-brain axis. Physiological reviews, 99(4), 1877–2013. https://doi.org/10.1152/physrev.00018.2018

Gao, K., Mu, C. L., Farzi, A., & Zhu, W. Y. (2020). Tryptophan metabolism: A link between the gut microbiota and brain. Advances in nutrition (Bethesda, Md.), 11(3), 709–723. https://doi.org/10.1093/advances/nmz127

Harrold, J. A., Dovey, T. M., Blundell, J. E., & Halford, J. C. (2012). CNS regulation of appetite. Neuropharmacology, 63(1), 3–17. https://doi.org/10.1016/j.neuropharm.2012.01.007

Kaur, H., Bose, C., & Mande, S. S. (2019). Tryptophan metabolism by gut microbiome and gut-brain-axis: An in silico analysis. Frontiers in Neuroscience, 13, 1365. https://doi.org/10.3389/fnins.2019.01365

Trevelline, B. K., & Kohl, K. D. (2022). The gut microbiome influences host diet selection behavior. Proceedings of the National Academy of Sciences of the United States of America, 119(17), e2117537119. https://doi.org/10.1073/pnas.2117537119

Tzameli I. (2013). Appetite and the brain: You are what you eat. Trends in Endocrinology and Metabolism: TEM, 24(2), 59–60. https://doi.org/10.1016/j.tem.2012.12.001

Yabut, J. M., Crane, J. D., Green, A. E., Keating, D. J., Khan, W. I., & Steinberg, G. R. (2019). Emerging roles for serotonin in regulating metabolism: New implications for an ancient molecule. Endocrine reviews, 40(4), 1092–1107. https://doi.org/10.1210/er.2018-00283

Are You What Your Gut-Microbiome Wants You To Eat?

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

We’ve all heard the saying “you are what you eat,” but new microbiome research is shedding light on this old adage, with a more modern-day update being, “you are what your gut-microbiome wants you to eat.” Let’s look at why this is the case.

Is Your Gut Microbiome Telling You What To Eat?

Though biomedical research has already established the endocrine responses that regulate hunger and satiety in the gut-brain axis signaling, little attention has been paid to the mechanisms that influence an individual’s choice of food and nutrition.

Microorganisms that live in our gut may influence what we eat!

A feedback loop between our gut microbiome, brain, and food choices

The classic expression, “you are what you eat,” may soon be reframed as “you are [also] what your microbiome wants you to eat.”

To achieve this, intestinal microbiota from three “donor” mouse species, each with distinct foraging behavior, were transplanted into germ-free “host” mice to colonize their intestinal tracts.

Following that, donor germ-free mice were randomly divided into three treatment groups, each based on the donor species:

A carnivore (i.e., predatory-based)
An herbivore (i.e., plant-based)
An omnivore (i.e., inclusive-based)

Figure 1A. Experimental design to assess host diet selection behaviors across different microbiomes. From Trevelline and Kohl, Proceedings of the National Academy of Sciences, 2022.

The gut microbiome can influence host diet selection behavior by mediating the availability of Essential Amino Acids (EAAs)

Figure 1B. Gut microbiome of donor mice altering feeding choices in host mice.

This reciprocal feedback loop is partly caused by the gut microbiome’s ability to synthesize EAAs, which interact with the gut-brain axis and, in turn, influence dietary habits. Depending on the food choices made, the body’s response to those choices can be beneficial or detrimental. Therefore, increasing awareness of the factors influencing dietary intake may help us to impact both our physical and mental health positively.

References

Harrold, J. A., Dovey, T. M., Blundell, J. E., & Halford, J. C. (2012). CNS regulation of appetite. Neuropharmacology, 63(1), 3–17. https://doi.org/10.1016/j.neuropharm.2012.01.007

Tzameli I. (2013). Appetite and the brain: You are what you eat. Trends in Endocrinology and Metabolism: TEM, 24(2), 59–60. https://doi.org/10.1016/j.tem.2012.12.001

Do Artificial Sweeteners Affect Eating Habits and The Diet-Mental Health Relationship?

Posted on April 27, 2022March 4, 2025 by CNP Staff

Artificial sweeteners—sugar substitutes that satisfy our cravings for sugar but contain low calories—have become a popular alternative to reduce the risks associated with high-sugar consumption and means of bodyweight management. Yet, the long-term effects of these nonnutritive sweeteners (NNS) have yet to be determined, particularly how our brain responds differently to NNS and nutritive sweeteners (NSW), and consequently, the effects they have on our eating behaviors. While previous clinical trials have investigated the impact of NNS and NSW on neurobehavioral states, these studies were limited as they focused on mostly male cohorts within normal body mass index (BMI).

The long-term effects of these NNS and their effects on eating behaviors have yet to be determined.

To create more generalizable data, Yunker et al. (2021), investigators from the University of Southern California, led a randomized crossover trial that aimed to elucidate the role of gender and BMI status on eating after ingesting NNS compared to NSW.

The authors designed a longitudinal study, in which all participants received a complete sequence of interventions in random order across three separate visits and utilized functional MRI imaging (fMRI) and an ad libitum (Latin for “at one’s pleasure”) buffet meal for evaluation.

Through fMRI, the authors measured the blood oxygen level-dependent (BOLD) signals, which reflect neural activity, in various brain areas as participants responded to different types of food cues after ingesting either the sucrose (an NSW), sucralose (an NSS), or water (a control) interventions. At defined intervals, participants also had their blood sampled to assess changes in endocrine response across these interventions (Fig. 1). Caloric intake was measured through the buffet meal for each participant to compare differences in appetitive and feeding behaviors across interventions.

Figure 1. Study design from Yunker et al., JAMA Network Open, 2021.

Artificial Sweeteners May Cause Overeating

BOLD signals were greater in the medial frontal (MFC) and orbitofrontal cortices (OFC) in obese individuals when presented with food cues after ingesting sucralose compared to non-food cues. However, this difference was not observed in participants who’s BMIs were categorized as healthy or overweight, suggesting a distinct intersectional effect of BMI status on one’s neurobehavioral response to food upon ingesting artificial sweeteners. Furthermore, as opposed to male counterparts, BOLD signals were greater in the MFC and OFC of females and were heightened when the participants were females with obesity during the sucralose intervention in the food cue tasks.

The significant increase in BOLD signals within the MFC area/region of the brain is intriguing because previous studies have shown this brain region to be responsible for conditioned motivation for eating in mice (Petrovich, 2007). Likewise, as the region houses higher cognitive function, the higher BOLD signals suggest that participants may have thought more about eating when exposed to food cues after taking artificial sweeteners (Jobson, 2021).

The higher BOLD signals suggest that participants may have thought more about eating when exposed to food cues after taking artificial sweeteners.

The increase in BOLD OFC signal is another interesting result as studies have correlated this brain area with processing the perception of food value, taste reward, and even smell in humans (Small, 2007; Seabrook, 2020). The primary concern concluded by this study is the possibility of overeating—and, in turn, obesity and its comorbidities—when individuals turn to sugar substitutes, especially for women who are already obese.

Although the authors conclude there was minimal effect on endocrine response between NSS and NSW, this study found reduced suppression of ghrelin–the “hunger hormone”–after ingesting sucralose, which suggests that artificial sweeteners may impair the normal homeostatic signaling that regulates feeding behaviors. As such, this would result in a longer period of “feeling hungry” which can contribute to overeating. This is evident in the study in which participants consumed more calories after ingesting sucralose, and this effect was more pronounced in females (no interaction/influence of BMI status found).

Artificial sweeteners may impair the normal homeostatic signaling that regulates feeding behaviors.

Taken together, the findings presented here emphasize the importance of considering biological factors when it comes to assessing the use and efficacy of artificial sweeteners for health-related concerns and body weight management.

References

Jobson, D. D., Hase, Y., Clarkson, A. N., & Kalaria, R. N. (2021). The role of the medial prefrontal cortex in cognition, ageing and dementia. Brain communications, 3(3), fcab125. https://doi.org/10.1093/braincomms/fcab125

Petrovich, G. D., Ross, C. A., Holland, P. C., & Gallagher, M. (2007). Medial prefrontal cortex is necessary for an appetitive contextual conditioned stimulus to promote eating in sated rats. The Journal of neuroscience : the official journal of the Society for Neuroscience, 27(24), 6436–6441. https://doi.org/10.1523/JNEUROSCI.5001-06.2007

Small, D. M., Bender, G., Veldhuizen, M. G., Rudenga, K., Nachtigal, D., & Felsted, J. (2007). The role of the human orbitofrontal cortex in taste and flavor processing. Annals of the New York Academy of Sciences, 1121, 136–151. https://doi.org/10.1196/annals.1401.002

Seabrook, L. T., & Borgland, S. L. (2020). The orbitofrontal cortex, food intake and obesity. Journal of psychiatry & neuroscience : JPN, 45(5), 304–312. https://doi.org/10.1503/jpn.190163

Yunker, A. G., Alves, J. M., Luo, S., Angelo, B., DeFendis, A., Pickering, T. A., Monterosso, J. R., & Page, K. A. (2021). Obesity and Sex-Related Associations With Differential Effects of Sucralose vs Sucrose on Appetite and Reward Processing: A Randomized Crossover Trial. JAMA network open, 4(9), e2126313. https://doi.org/10.1001/jamanetworkopen.2021.26313

Development of “Sport and Disordered Eating” Research Category In Nutritional Psychology

Posted on April 20, 2022March 2, 2025 by CNP Staff

Athletes are under immense pressure. Athletes feel the pressure to perform their best to win, attain coveted scholarships, be selected in a draft, and even to look a certain way (i.e. achieve perfection). As we’ve seen within the sporting culture, this pressure can compel athletes to engage in tactics that may improve their chances in sport, but can be detrimental to their overall health.

Athletes may use drugs to deal with the mounting pressure they feel to succeed. Lance Armstrong used in the Tour de France and Sha’Carri Richardson and Kamila Valieva used at the Olympics. Some athletes may resort to other behaviors that can have detrimental effects on both health and athletic performance, such as dieting, disordered eating, and binge eating. Let’s explore, in depth, the eating disorder prevalence in athletes, risk factors associated with these disorders, and important treatment considerations for all at-risk athletes.

Athletes may resort to behaviors that can have detrimental effects on health and athletic performance such as dieting, disordered eating, and binge eating.

Eating Disorders in Athletes
According to research, elite athletes are at higher risk for developing an eating disorder (ED) than the general population (Mancine et al., 2020; Martinsen & Sundgot-Borgen, 2013). This risk is high for youth and adolescent athletes, but these practices can also be carried into college. One study found that 32.5% of the collegiate female athletes had eating disorders (Canbolat & Cakiroglu, 2020). EDs that are developed during adolescence can even be carried into adulthood sport participation (Sundgot-Borgen, 1994). Unfortunately, these practices are not abandoned once the athletes “retire” from their sport, as ED may continue to appear within a retired athletes’ life (DeZiel & DeBeliso, 2020).

Elite athletes are at higher risk for developing an eating disorder (ED) than the general population.

ED are defined as “behavioral conditions characterized by severe and persistent disturbance in eating behaviors and associated distressing thoughts and emotions” (American Psychiatric Association, 2021). Whereas the prevalence of EDs in the general population is 5% (American Psychiatric Association, 2021), the prevalence is higher in athletes with 6-45% of female athletes suffering from this type of disorder (Bratland-Sanda & Sundgot-Borgen, 2013). Male athletes have a higher rate of ED compared to male non-athletes as well (Karrer et al., 2020).

Why (i.e., Risk Factors)
Why are athletes at greater risk for ED than the general population? They embody certain personality characteristics that put them at risk for developing an ED. For example, perfectionism, achievement motivation, and competitiveness are necessary traits for improvement in one’s sport. These same characteristics, especially perfectionism, make athletes vulnerable to developing disordered eating (Prnjak et al., 2019). Female athletes are at a greater risk for developing ED than male athletes.

Perfectionism is the greatest risk factor for disordered eating among female athletes.

The type of sport that females participate in might also increase their risk of developing an ED. Gymnastics and figure skating emphasize leanness, flexibility and balance; cross country running emphasizes low body weight and percentage body fat. The female athletes who compete in any of these sports may be at higher risk for developing disordered eating or obsessive dieting as compared to athletes who compete in a sport like soccer (de Oliveira et al., 2017). This may be due to the notion that being thin in these sports leads to greater success (Aleksic Veljkovic et al., 2020). According to UK Sport, the sports with the highest risk of ED for both female and male athletes are swimming, running, gymnastics, diving, synchronized swimming, wrestling, judo, and lightweight rowing (Bashforth, 2022).

The type of sport that females participate in might also increase their risk of developing an ED.

There are several risk factors relating to this idea of thinness equals success. It can depend on whether or not someone else is “judging” their performance (as in a gymnastics routine), whether or not there is a competitive advantage in having a smaller body mass for the sport, dominant aesthetic patterns, and the size of the uniforms used in competition (Aleksic Veljkovic et al., 2020).

Some argue that the sporting environment may actually encourage or normalize these disorders through certain usual and customary practices. Daily or weekly weigh-ins or weight-monitoring practices that are common in sports, such as wrestling, may promote an over-fixation on weight which can result in EDs (Bashforth, 2022). Athletes are also encouraged to remain “healthy” and adhere to strict diet and training practices, which may also cause an over-fixation on eating behaviors. Some athletes such as Olympic diver Tom Daley have explained that a drive for thinness or the pressure to achieve a lower weight was “hammered into him” in order to perform optimally (Bashforth, 2022).

Consequences of ED in Athletes
ED are serious conditions that can have severe detrimental effects on one’s physical and mental health. The term “Female Athlete Triad” was previously used to explain the consequences of ED or disordered eating among female athletes. These consequences included loss of menstrual cycles (amenorrhea), and decreased levels of endogenous oestrogen and other hormones which together resulted in a loss of bone density and a higher risk for osteoporosis (Mountjoy et al., 2014).

The term “Female Athlete Triad” was previously used to explain the consequences of ED or disordered eating among female athletes.

It has since been recognized that the consequences of ED reach far beyond this “triad” and affect both male and female athletes with low energy availability. A new term called Relative Energy Deficit in Sport (RED-S) has been established to reflect these developments (Mountjoy et al., 2014).

Relative Energy Deficit in Sport (RED-S) has since replaced “Female Athlete Triad” to recognize that these consequences are broader than a “triad,” and that male athletes can be affected as well.

RED-S is a term used to describe the physiological consequences that are associated with athletes consuming too little calories for their activity levels (Mancine et al., 2020). These consequences can include: reduced hormone levels such as T3, insulin, leptin, and testosterone, and an increase in cortisol and cholesterol levels (Torstveit et al., 2018). More consequences include a disruption in menstrual cycles in females, impaired bone health, decreased resting metabolic rate, iron deficiency, impaired growth and development in adolescents, early atherosclerosis, impaired gastrointestinal functioning, and impaired immune system functioning (Mountjoy et al., 2018).

ED or RED-S can result in psychological challenges as well, including mood, anxiety, and substance abuse disorders (Mancine et al., 2020). It is important to note that while ED can result in psychological consequences, it can also be preceded by these factors as well (Mountjoy et al., 2014). For example, stress and depression might increase the risk of developing ED, but can also be a result of having low energy available (Mountjoy et al., 2014).

Athletes have much higher energy demands than nonathletes, so the consequences of low-calorie intake resulting from ED or disordered eating can be detrimental to both their health and athletic performance. The International Olympic Committee (IOC) releases regular consensus statements with recent developments, hoping to spread awareness of the risk factors, consequences, and treatment options for athletes who are suffering from such disorders.

EDs have the highest fatality rate of any mental health disorder, regardless of whether someone is an athlete or not. The fatality rate is higher in men than women, and one in five people struggling with anorexia die by suicide (Markey, 2022).

In Conclusion
Eating disorders are just one piece of a larger picture of overall mental health concerns of athletes. This has been a hot topic lately, as we are seeing more elite athletes, like Simone Biles in the 2020 Summer Olympics, willing to open up about their own personal mental health challenges. Athletes may be at high risk for developing ED, along with other mental health disorders, due to the intense physical and mental demands placed on them, increased public scrutiny resulting from social media, team dynamics, and potential for injury (Rice et al., 2016).

The Nutritional Psychology Research Library Sport and Disordered Eating Research Category has been developed as a tool to help coaches, trainers, parents of youth athletes, and athletes themselves, to gain a better awareness of these disorders. This increased awareness, along with knowledge of the risk factors and treatment options available, will help those who work with athletes to gain a better understanding of the mental health challenges facing them. This insight can help to support their physical and mental well-being.

References
Aleksić Veljković, A., ĐUrović, D., Biro, F., Stojanović, K., & Ilić, P. (2020). Eating attitudes and body image concerns among female athletes from aesthetic sports. Annales Kinesiologiae, 3–16. https://doi.org/10.35469/ak.2020.242

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

Bashforth, E. (2022, March 21). Eating disorders in athletes: how can we tackle them? Patient. https://patient.info/news-and-features/eating-disorders-in-sport-why-are-they-so-common-and-how-can-we-tackle-them

Bratland-Sanda, S., & Sundgot-Borgen, J. (2013). Eating disorders in athletes: Overview of prevalence, risk factors and recommendations for prevention and treatment. European Journal of Sport Science, 13(5), 499–508. https://doi.org/10.1080/17461391.2012.740504

Canbolat, E., & Cakiroglu, F. P. (2020). Eating Disorders and Nutritional Habits of Female University Athletes. Turkish Journal of Sports Medicine, 55(3), 231–238. https://doi.org/10.5152/tjsm.2020.181

de Oliveira, G. L., de Oliveria, T. A. P., de Pinho Goncalves, P. S., Silva, J. R. V., Fernandes, P. R., & Filho, J. F. (2017). Body Image and Eating Disorders in Female Athletes of Different Sports. Journal of Exercise Physiologyonline, 20(2).

DeZiel, J., & DeBeliso, M. (June 2020). Eating disorders in former NCAA division 1 collegiate gymnasts and their behaviors after graduating. Journal of Physical Education Research, 7(2), 35-44.

Karrer, Y., Haliousa, R., Mötteli, S., Iff, S., Seifritz, E., Jäger, M., Claussen, M.C. (2020). Disordered eating and eating disorders in male elite athletes: a scoping review. BMJ Open Sport & Exercise Medicine, 0. doi:10.1136/bmjsem-2020-000801

Mancine, R. P., Gusfa, D. W., Moshrefi, A., & Kennedy, S. F. (2020). Prevalence of disordered eating in athletes categorized by emphasis on leanness and activity type – a systematic review. Journal of Eating Disorders, 8(1). https://doi.org/10.1186/s40337-020-00323-2

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

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

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

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

Mountjoy, M., Sundgot-Borgen, J., Burke, L., Carter, S., Constantini, N., Lebrun, C., Meyer, N., Sherman, R., Steffen, K., Budgett, R., & Ljungqvist, A. (2014). The IOC consensus statement: beyond the Female Athlete Triad—Relative Energy Deficiency in Sport (RED-S). British Journal of Sports Medicine, 48(7), 491–497. https://doi.org/10.1136/bjsports-2014-093502

Prnjak, K., Jukic, I., & Tufano, J. J. (2019b). Perfectionism, Body Satisfaction and Dieting in Athletes: The Role of Gender and Sport Type. Sports, 7(8), 181. https://doi.org/10.3390/sports7080181
Rice, S. M., Purcell, R., de Silva, S., Mawren, D., McGorry, P. D., & Parker, A. G. (2016). The Mental Health of Elite Athletes: A Narrative Systematic Review. Sports Medicine, 46(9), 1333–1353. https://doi.org/10.1007/s40279-016-0492-2

Sundgot-Borgen J. (1994). Risk and trigger factors for the development of eating disorders in female elite athletes. Medicine and science in sports and exercise, 26(4), 414–419.

Special Topic in Nutritional Psychology: Factors Contributing to Food Selection Behavior

Posted on April 9, 2022March 2, 2025 by CNP Staff

Researchers continue to pursue a better understanding of how our food choices and eating behaviors are influenced by the subjective sensations we experience in relation to foods. In their 2020 study, Duerland and colleagues explored the relationship between subjective sensations and food choice.

In this study, 253 participants, ages 18-30 years, were recruited from a university in New Zealand. Participants were approached on campus, and the experiment occurred on site. They first answered background questions and indicated their degree of health consciousness by evaluating their level of agreement with the following statements: “I choose food carefully to ensure good health,” and “I think of myself as a health-conscious consumer.” Next, participants used a 0 (“not at all”) to 10 (“very much”) scale to rate their current experience of 13 food-related sensory-specific sensation variables: Energy, Concentration, Sleepiness, Fullness, Hunger, Overall Wellbeing, Physical Well-being, Mental Well-being, Desire-to-Eat, Desire-to-Snack, Sweet Desire, Salty Desire, and Fatty Desire (see Figure 1).

Figure 1. Thirteen food-related sensory-specific sensation variables (Duerlund, 2020)

Participants were then invited to choose a snack from six available options. The six snacks were divided into two categories, “healthy” and “unhealthy,” and encompassed sweet, salty, and fatty taste sensations. Grapes (sweet), nuts (salty), and dark chocolate (fatty) comprised the “healthy” options. “Unhealthy” snacks included jelly beans (sweet), potato chips (salty), and cookies (fatty). Participants’ snack choices were recorded.

Overall, grapes were chosen most often, and jellybeans the least. Sensory-specific sensations did impact snack-choice behavior. Sweet Desire, Salty Desire, and Fatty Desire demonstrated the greatest effects. Specifically, higher ratings of Salty Desire and Fatty Desire led to an increased likelihood of selecting potato chips. High Sweet Desire was associated with choosing dark chocolate. Other sensations found to impact snack choice included Hunger, Physical Well-Being, Desire-to Eat, and Desire-to-Snack.

Figure 2. Sensory-Specific Sensations and Snack Choice (Duerlund, 2020)

Background information also affected snack choice, which the authors explain is indicative of the multitude of factors contributing to food-selection behavior. In this study, high health consciousness and female gender drove the selection of “healthy” snacks, while the male gender was most associated with the “unhealthy” choices.

These findings provide new insights into how subjective sensations, health consciousness, and even gender can impact snack choice, which the authors note could contribute to a better understanding of public health issues, such as unhealthy snacking and obesity.

Editor’s Note:

While it is important to know more about people’s food choice behavior in relation to their sensations, several aspects should be taken into consideration when reading this study and its study design. Taste is one of the major contributors when it comes to a food choice (e.g., Diószegi et al., 2019) and could have influenced the results of this study; jellybeans are a good example for this as it is either liked or rather disliked by people compared to a more “neutral” food such as grapes. Thus, choosing food is also related to taste preference. Another aspect is the timing of the study. The study was conducted between 8 am and 4 pm which could have influenced food choice behavior since situational appropriateness impacts people’s food preferences (Cardello et al., 2000). The desire to eat jellybeans at 8 am might differ drastically from the desire to eat them at 3 pm, while this might not be the case for cookies or nuts. Both aspects could have been taken into consideration when conducting and analyzing this study. However, despite these limitations, the study provides an important contribution to the literature on the influence of sensations on food choice behavior.

References:

Cardello, A.V., Schutz, H.G., & Snow, C. (2000). Predictors of food acceptance, consumption and satisfaction in specific eating situations. Food Quality and Preferences, 11(3), 201-216. https://doi.org/10.1016/S0950-3293(99)00055-5

Duerland, M., Andersen, B.V., Alexi, N., Peng, M., & Byrne, D.V. (2020). Subjective sensations related to food as determinants of snack choice. Foods, 9(3): 336. https://doi.org/10.3390/foods9030336

Diószegi, J., Llanaj, E., & & Ádány, R. (2019). Genetic background of taste perception, taste preferences, and its nutritional implications: A systematic review. Frontiers in Genetics, 10, 1272. https://doi.org/10.3389/fgene.2019.01272

Does Perception of Body Weight During Adolescence Influence Dietary Intake?

Posted on March 19, 2022March 4, 2025 by CNP Staff

Adolescents seem to be vulnerable to feeling dissatisfied with their weight and body shape (Clay et al., 2005). Their perception of their body image (i.e., their Diet-Perceptual Relationship) may be shaped by the opinions of their family and friends; what they see in television, movies, and magazines (Silva et al. 2021); and all forms of social media (i.e., their Diet-Psychosocial Relationship). At the same time, it’s crucial that adolescents develop a healthy body image since it can affect mental and physical health — especially if their perception differs from their actual weight and nutritional status.

There is emerging evidence of a connection between body perception and diet.

There is emerging evidence of a connection between body perception and diet. For instance, researchers have found that Greek adolescents were less likely to be overweight or obese if they accurately guessed their weight status and adhered closely to a “healthy foods” dietary pattern, compared to those who followed a diet consisting of unhealthy/high-fat or starchy, protein-rich foods (Kanellopoulou et al., 2021). Unsurprisingly, many research papers have suggested that certain dietary patterns (typically those labeled “healthy” and/or “traditional”) can protect people against being obese/overweight.

Based on such findings, it’s purported that an accurate perception of one’s weight in conjunction with healthy dietary intake habits may play into obesity prevention strategies. Let’s take a closer look at a cross-sectional research study on this topic by Silva et al. (2021), which examined the relationship between weight misperception and dietary patterns among Brazilian adolescents.

Accurate weight perception in conjunction with healthy dietary habits could help prevent obesity.

For this study, the researchers recruited Brazilian teenagers from urban and rural schools in cities with populations larger than 100,000 across Brazil. Only adolescents deemed to be of normal weight were included. Their height and weight were measured and used to calculate their body mass index (BMI), and in turn their nutritional status (BMI relative to age).

Next, the researchers assessed the participants’ perception of their own weight. The students were asked questions such as “Are you satisfied with your weight?” and “In your opinion, at what level is your current weight?” If they indicated feeling “not satisfied” and “below the ideal” regarding their weight, they were placed in the underestimation group. Those who answered “not satisfied” and “above the ideal” or “far above the ideal” were assigned to the overestimation group. The participants in these groups were considered to experience weight misperception. To understand the subject further, their dietary intake patterns were examined using 24-hour dietary recalls.

34% of the study sample (over 52,000 normal-weight adolescents) misjudged their own weight.

The data showed that 34% of the 52,038 normal-weight adolescents in Brazil misjudged their own weight, with higher incidence rates reported in girls (42.6%) than boys (25.6%). In addition, a higher proportion of girls perceived themselves as heavier than they actually were (weight overestimation) compared to boys (25.7% vs. 8.2%). The authors theorized that this higher prevalence of weight overestimation in girls could be attributed to gendered social constructs — in this case, perhaps the expectation of achieving a “perfect” body. While girls tend to overestimate their weight, boys are more likely to describe themselves as too thin (Park, 2011). Nowadays many young people are concerned about their body shape and size due to social pressures to conform to a thin, ideal body (Yan et al., 2018).

The higher incidence of weight overestimation in girls may be connected to the idea of a “perfect” body.

In this study, the female students showing weight overestimation were less likely to follow the “processed meat, sandwiches, and coffee,” “ultra-processed and sweet foods,” and “traditional Brazilian” dietary patterns (the latter is characterized by rice, beans, vegetables, and meat). This suggests a sense of apprehension towards eating — of restriction. A different study in South Korea demonstrated that girls with weight overestimation tend to have poor eating habits and employ unhealthy dieting methods to lose weight (Lim et al. 2014). In short, normal-weight adolescents who perceive themselves as overweight seem to put effort into losing weight — intentions that do not exactly translate into healthy weight loss behaviors.

Similar to the girls, the normal-weight boys with weight overestimation were less inclined to adhere to a “traditional Brazilian” dietary pattern. As noted above, this “traditional” diet consists of several unprocessed or minimally processed foods, which are recommended by the Food Guide for the Brazilian Population. Worth mentioning is that this dietary guide does not recommend the intake of ultra-processed foods, warning Brazilians to avoid several of these food items found in the “ultra-processed and sweet foods” dietary pattern.

For girls who underestimated their weight, the “ultra-processed and sweet foods” and the “traditional Brazilian” dietary patterns were more likely to be adopted. In boys, weight underestimation was directly associated with greater adherence to the “processed meat, sandwiches, and coffee” and “ultra-processed and sweet foods” dietary patterns.

Weight underestimation showed correlations with the “ultra-processed and sweet foods” dietary pattern in both sexes.

Weight underestimation showed correlations with the “ultra-processed and sweet foods” dietary pattern in both sexes. Coupled with the association between weight overestimation and lower adherence to the “traditional Brazilian” dietary pattern, these results highlight that weight misperception is related to unhealthy eating habits among adolescents.

Awareness of the adolescent Diet-Perceptual Relationship in children and adolescents can be an important element for policymakers in developing and implementing intervention programs to support accurate self-perceptions of body weight. Successful efforts on this front could contribute to the adoption of better eating habits and enhanced overall general health in youth.

References

Clay, D., Vignoles, V.L. and Dittmar, H. (2005), Body image and self-esteem among adolescent girls: testing the influence of sociocultural factors. Journal of Research on Adolescence, 15: 451-477. https://doi.org/10.1111/j.1532-7795.2005.00107.x

Cuypers, K., Kvaløy, K., Bratberg, G., Midthjell, K., Holmen, J., & Holmen, T. L. (2012). Being normal weight but feeling overweight in adolescence may affect weight development into young adulthood-an 11-year followup: the HUNT Study, Norway. Journal of obesity, 2012, 601872. https://doi.org/10.1155/2012/601872

Lim, H., Lee, H. J., Park, S., Kim, C. I., Joh, H. K., & Oh, S. W. (2014). Weight misperception and its association with dieting methods and eating behaviors in South Korean adolescents. Nutrition research and practice, 8(2), 213–219. https://doi.org/10.4162/nrp.2014.8.2.213

Park, E. (2011). Overestimation and underestimation: adolescents’ weight perception in comparison to BMI-based weight status and how it varies across socio-demographic factors. The Journal of school health. 81. 57-64. 10.1111/j.1746-1561.2010.00561.x.

Silva, S., Alves, M. A., Vasconcelos, F., Gonçalves, V., Barufaldi, L. A., & Carvalho, K. (2021). Association between body weight misperception and dietary patterns in Brazilian adolescents: A cross-sectional study using ERICA data. PloS one, 16(9), e0257603. https://doi.org/10.1371/journal.pone.0257603

Yan, H., Wu, Y., Oniffrey, T., Brinkley, J., Zhang, R., Zhang, X., Wang, Y., Chen, G., Li, R., & Moore, J. B. (2018). Body Weight Misperception and Its Association with Unhealthy Eating Behaviors among Adolescents in China. International journal of environmental research and public health, 15(5), 936. https://doi.org/10.3390/ijerph15050936

Do Taste Perception, Preference, Personality, Mood, and Dietary Intake Behavior Interconnect?

Posted on February 25, 2022March 4, 2025 by CNP Staff

For hundreds of years, scientists have suspected a connection between our personality traits and taste preferences. Anton Brillat-Savarin, the famous French gastronome, is quoted saying, “Tell me what you eat, and I will tell you who you are.”

Tell me what you eat, and I will tell you who you are.

But what influences what we eat? It turns out that a symphony of elements influences our dietary intake patterns. These elements include (but are not limited to) our psychological traits (and mood states), cognitive and perceptual processes, behavioral attributes, psychosocial (including cultural) environment, and interoceptive experience. Each of these elements, in turn, is driven by physiological, biological, neuropsychological, and environmental states that are constantly at play within us (figure 1) (see the Nutritional Psychology Research Library).

Figure 1. Elements of the diet-mental health relationship (DMHR) informing nutritional psychology (NP)

Understanding the diet-mental health relationship (DMHR) involves a wealth of conceptual complexity. The burgeoning field of nutritional psychology is attempting to integrate this conceptual complexity into a singular infrastructure by which the conceptualization of the DMHR can grow (figure 1). Nutritional psychology involves understanding the myriad factors interconnecting our dietary intake with our psychological processes, functioning, and experience. A plethora of research exists (and is growing) to improve our understanding of these interconnections and is contained in the CNP Research Libraries.

What is Guiding What We Eat?

On the surface, many of us believe that what we eat is guided by what we like and want to eat (or in the current dietary intake landscape additionally, what we crave to eat and what is available to eat). In fact, what we eat goes far deeper than simply wanting and liking certain foods. A host of involuntary factors, of which we are mostly unaware, influence our daily dietary intake including our perceptions and preferences, personality, mood, behavioral attributes, and even genetics (Neuroscientist News, 2022). Let’s begin by looking at taste perception, preference, and their connection with personality traits.

Genetic Basis for Taste Perception and its Connection with Personality Traits

Perceiving taste involves complex pathways that interface with multiple cranial nerves and areas in our brain. The five taste sensations (bitter, sweet, umami, sour, and salt) arise because of the activation of specific taste receptor cells on the lingual papillae on the tongue. Specific genes encode the different taste receptors. Varieties in these genes lead to the expression of different proteins associated with different tasting abilities, preferences, and personality traits. This serves as the genetic basis for taste and the perception of taste.

Interestingly, sensory science divides people into supertasters, medium-tasters, and non-tasters. The TAS2R38 gene, located on chromosome 7, provides the genetic basis for taster status (Figure 2).

Supertasters are defined as individuals with uncommonly low gustatory thresholds and strong responses to moderate concentrations of taste stimuli (Supertaster – APA Dictionary of Psychology, n.d.). Supertasters have an unusually high number of taste buds. This gene in supertasters increases their perception of bitter flavors in foods.

Varieties in genes lead to the expression of different proteins associated with different tasting abilities, preferences, and personality traits.

For example, supertasters tend to find the taste of coffee to be very bitter. In relation to personality characteristics, studies have found that supertasters and medium-tasters tend to be more tense, apprehensive, and imaginative than non-tasters, while non-tasters are inclined to be more relaxed, placid, and practical (Mascie-Taylor et al., 1983).

Science also reveals a genetic basis for sweet liking, identified by a locus on chromosome 16 (Figure 2). Researchers divide the population into three categories related to the liking for sweetness: sweet-likers, sweet-neutral, and sweet dislikers. Regarding differences in the preferences for sweetness, studies have shown that these differences predicted intentions, prosocial personalities, and behaviors (Meier et al., 2012).

Figure 2. The five taste sensations. The genetic basis for sweet liking is identified by chromosome 16, while chromosome 7 provides the genetic basis for taster status

It is important to note that in addition to our genes, our biochemical makeup also plays a role in our food perception and preference. For example, one study showed that salivary testosterone levels correlated with the amount of spice (Tabasco in this case) that participants chose to add to their food (Bègue et al., 2015).

Now that we’re aware of the genetic (and biochemical) basis for taste perception and preference, and learned how our genes can influence personality, let’s look at how personality can influence food preference.

Personality and Food Preference

Regarding food preferences, key factors of a person’s personality, including openness to experience (i.e., curiosity vs. caution), have been found to correlate with various aspects of food preference. For example, in a study by Conner et al. (2017), people with personality attributes like openness scored above average on preference for new food experiences. The controversy associated with such research, however, is that it has largely been conducted using self-rated food preferences, not in settings with actual food choices.

Key factors of a person’s personality have been found to correlate with aspects of food preference.

Many studies have addressed this issue. For example, a 2016 study analyzed participants’ willingness to try new foods. In this study, bite-sized pieces of twelve food items were placed in front of each participant (these included: octopus, hearts of palm, seaweed, soya bean milk, blood sausage, Chinese sweet rice cake, pickled watermelon rind, raw fish, quail egg, star fruit, sheep milk cheese, and black beans). Findings showed that the most anxious participants were the least willing to try new foods (Otis, 2016). This has been supported by other publications showing that anxious patients exhibit greater food aversions (Spence, 2021).

The most anxious participants were the least willing to try new foods.

Taste Perception and its Influence on Mood and Behavior

Now that we’ve explored some interconnections between genes, taste perception, and personality, let’s see how taste perception can influence our mood and behaviors. An example study by Vi and Obrist (2018) showed that those experiencing a sour taste were more likely engage in risk-taking. This was measured using the standardized Balloon Analogue Risk-Taking (BART) task, a computerized gambling task. Participants were asked to virtually pump up a balloon on a computer screen, with an accumulated monetary reward at stake. After each pump, the balloon either explodes or increases in size based on a randomized algorithm, yielding greater reward. Participants who had tasted something sour (as compared to a neutral water stimulus) were more likely to keep inflating the virtual balloon, risking the loss of the reward.

A study exploring the interrelation between taste perception and mood (Chan et al., 2013) showed that tasting something sweet made people feel temporarily more romantic. And that by having people remember an episode of romantic love, they would report some foods as being sweeter than did those who were asked to recall a jealous memory.

In another study by Ren et al., (2014), researchers exposed a group of participants to the sweet taste of Oreo cookies. This exposure resulted in a greater interest in initiating relationships with a potential partner.

A study by Greimel et al., (2006) found that prompting people to remember being mistreated at work resulted in bitter tastes being rated as more intense, while watching a joyful film clip (compared to a sad movie clip) resulted in participants rating a sweet drink as more pleasant.

Taste Perception and Clinical Disorders

Some research on taste perception in the context of mental health shows that depressed patients have differences in perception of taste. While some studies have reported no difference in taste perception in depressed patients (Arrando, 2015; Nagai, et al., 2015), researchers Hur et al. (2018) found that the prevalence of altered smell and taste among patients with major depressive disorder was 39.8% and 23.7% respectively.

These changes in taste perception are hypothesized to be due to several mechanisms, but one mechanism seems to involve neurochemical changes that happen in our brain due to either emotional or pathological processes (e.g., depression leads to elevation of inflammatory cytokines like interleukin 6). These changes can result in actual changes in the gustatory system.

It is hypothesized that changed taste thresholds could be attributed to reduced serotonin and noradrenaline levels in depressed patients, as suggested by Heath et al. (2006) (Figure 3). This proposed mechanism was supported by another study (Kim et al., 2017), which found reduced expression of 5‐HT1A receptors for serotonin in the taste cells of rats that developed anhedonia — a common symptom of depression. Case reports demonstrate that a change in taste is a neglected symptom in depressed patients that is worthy of further investigation (Miller & Naylor, 1989; Mizoguchi et al., 2012).

Figure 3. Human gustatory pathway. Variations in serotonin levels are associated with different thresholds for certain tastes like bitter and sweet (Heath, 2006).

Research also shows that patients with panic disorders can have exhibited reduced sensitivity to bitterness (DeMet et al., 1989), while anxiety levels are positively correlated with the taste thresholds for bitterness and saltiness (Heath et al., 2006).

According to Hur et al. (2018), it may be advisable for primary care providers to screen their patients for depression or other psychiatric conditions when they report changes in taste or smell.

Conclusion

In this article, we’ve had a little ‘taste’ of how our genes influence our taste perception and preferences. The DMHR plot thickens when we begin to be aware of how these perceptions and preferences can interplay with our personality, mood, and behaviors (figure 4).

Figure 4. Interconnections between genes, taste perception, and preference, behaviors, personality, and mood.

For example, we learned how anxious individuals can prefer a narrower range of food while people with personality attributes like openness typically score above average on preferences for new food experiences. Intriguingly, differences in food behavior and taste perception have been linked with circulating levels of certain neurotransmitters like serotonin and can affect taste perception in clinical disorders.

While not lending to a conclusive understanding of the factors involved in dietary intake, our goal with this article is to provide you with a new awareness of the interconnection that occurs between your genes, personality, emotions, and food-related behaviors and preferences.

To learn more, visit the CNP Diet and Personality and Diet and Sensory-Perception research categories in the NPRL.

References

Arrondo, G., Murray, G. K., Hill, E., Szalma, B., Yathiraj, K., Denman, C., & Dudas, R. B. (2015). Hedonic and disgust taste perception in borderline personality disorder and depression. The British journal of psychiatry: the journal of mental science, 207(1), 79–80. https://doi.org/10.1192/bjp.bp.114.150433

Bègue, L., Bricout, V., Boudesseul, J., Shankland, R., & Duke, A. A. (2015). Some like it hot: Testosterone predicts laboratory eating behavior of spicy food. Physiology & Behavior, 139, 375–377. https://doi.org/10.1016/J.PHYSBEH.2014.11.061

Chan, K. Q., Tong, E. M. W., Tan, D. H., & Koh, A. H. Q. (2013). What do love and jealousy taste like? Emotion (Washington, D.C.), 13(6), 1142–1149. https://doi.org/10.1037/A0033758

Conner, T. S., Thompson, L. M., Knight, R. L., Flett, J. A. M., Richardson, A. C., & Brookie, K. L. (2017). The role of personality traits in young adult fruit and vegetable consumption. Frontiers in Psychology, 8(FEB). https://doi.org/10.3389/FPSYG.2017.00119

DeMet, E., Stein, M. K., Tran, C., Chicz-DeMet, A., Sangdahl, C., & Nelson, J. (1989). Caffeine taste test for panic disorder: Adenosine receptor supersensitivity. Psychiatry Research, 30(3), 231–242. https://doi.org/10.1016/0165-1781(89)90014-0

Greimel, E., Macht, M., Krumhuber, E., & Ellgring, H. (2006). Facial and affective reactions to tastes and their modulation by sadness and joy. Physiology & Behavior, 89(2), 261–269. https://doi.org/10.1016/J.PHYSBEH.2006.06.002

Heath, T. P., Melichar, J. K., Nutt, D. J., & Donaldson, L. F. (2006). Human taste thresholds are modulated by serotonin and noradrenaline. The Journal of Neuroscience, 26(49), 12664–12671. https://doi.org/10.1523/JNEUROSCI.3459-06.2006

Hur, K., Choi, J. S., Zheng, M., Shen, J., & Wrobel, B. (2018). Association of alterations in smell and taste with depression in older adults. Laryngoscope Investigative Otolaryngology, 3(2), 94–99. https://doi.org/10.1002/LIO2.142

Kim, D., Chung, S., Lee, S. H., Koo, J. H., Lee, J. H., & Jahng, J. W. (2017). Decreased expression of 5-HT1A in the circumvallate taste cells in an animal model of depression. Archives of Oral Biology, 76, 42–47. https://doi.org/10.1016/J.ARCHORALBIO.2017.01.005

Mascie-Taylor, C. G. N., McManus, I. C., MacLarnon, A. M., & Lanigan, P. M. (1983). The association between phenylthiocarbamide (PTC) tasting ability and psychometric variables. Behavior Genetics, 13(2), 191–196. https://doi.org/10.1007/BF01065667

Meier, B. P., Moeller, S. K., Riemer-Peltz, M., & Robinson, M. D. (2012). Sweet taste preferences and experiences predict prosocial inferences, personalities, and behaviors. Journal of Personality and Social Psychology, 102(1), 163–174. https://doi.org/10.1037/A0025253

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Nagai, M., Matsumoto, S., Endo, J., Sakamoto, R., & Wada, M. (2015). Sweet taste threshold for sucrose inversely

Neuroscientist News. (2022, June 14). Do our genes determine what we eat? https://neurosciencenews.com/genetics-taste-perception-20833/

correlates with depression symptoms in female college students in the luteal phase. Physiology & behavior, 141, 92–96. https://doi.org/10.1016/j.physbeh.2015.01.003

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Every additional glass of sugar-sweetened beverages (250 mL) per day was associated with a 17% increase in the risk of coronary heart disease.

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A feedback loop between our gut microbiome, brain, and food choices.

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Is Your Gut Microbiome Telling You What To Eat?

Microorganisms that live in our gut may influence what we eat!

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Tell me what you eat, and I will tell you who you are.

Varieties in genes lead to the expression of different proteins associated with different tasting abilities, preferences, and personality traits.

Key factors of a person’s personality have been found to correlate with aspects of food preference.

The most anxious participants were the least willing to try new foods.

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