An evolutionary perspective on diet and depression: the larger the evolutionary mismatch, the more depressive symptoms in students

An evolutionary perspective on diet and depression: the larger the

evolutionary mismatch, the more depressive symptoms in students

Bachelor Project, Psychobiology

Renée Robbers 10735801 24-01- ‘20 Supervisor/Examiner Annemie Ploeger Abstract

With depression being a commonly occurring disorder among students, the identification of risk factors and new targets for prevention is imperative.

According to the Mismatch Hypothesis, we suffer from depression because of an evolutionary mismatch between the present environment and the environment in which we evolved, during the hunters and gatherers period of time. With the rapidity of changes also within our diet over the past thousands of years, our digestive makeup is unable to process the Western modern diet. In addition, because of the gut-brain axis our diet and mind are closely connected. That is why the aim of this study was to examine the effect of a modern diet on

depressive symptoms in students, from an evolutionary perspective. To examine this, Dutch students completed a survey containing a Food Frequency

Questionnaire, the Mismatch Questionnaire and the University Student Depression Inventory. Interviews were conducted to get a closer look into causality and individual differences. No correlation was found between the FFQ and both the USDI and MM questionnaire. However, a correlation was found between the MM questionnaire and the USDI. This suggests a connection between the environmental mismatch and depressive symptoms among students; living in a modern- industrialized world demands certain coping mechanisms that we may not have.

Keywords: depression, evolutionary mismatch hypothesis, diet, students,

Introduction

Depression is a commonly occurring disorder, in which the functioning and the quality of life is diminished. Unfortunately, nowadays, the prevalence of the disorder among students in the western world is very high; 30.6% of the students shows major depression symptoms (Ibrahim, Kelly, Adams, & Glazebrook, 2013). Characteristics that come with the disorder are diminished concentration,

feelings of worthlessness or excessive or inappropriate guilt, fatigue, loss of energy, lack of interest in everyday experiences and recurrent thoughts of death (American Psychiatric Association, 2013; Kessler and Bromet, 2013; Koukopoulos and Sani 2014). Many risk factors and causes are globally researched, but the right intervention still has not been found. In this research project an evolutionary perspective on depression will be explored.

One hypothesis about the disorder, from an evolutionary point of view, is the Mismatch Hypothesis: people in the western world suffer from depression

because the environment in which they live is too different from the environment in which humans used to live when they evolved, during the hunters and

gatherers period of time. This seems to be a plausible explanation. However, the hypothesis has not been tested extensively. Finding a connection between this evolutionary hypothesis and the major depression rates can give an insight in why and how depression works. Furthermore, a clear insight can help to find possible interventions such as medication, or even prevention.

The mismatch hypothesis, however, is quite broad; there are many relevant factors in our environment which have changed over the past millions of years. One of these factors is our diet. In the Old Stone Age, beginning 2 million years ago and continuing until 10.000 years ago, hunters and gatherers travelled around just to find the right food sources. The current evidence of their so-called paleolithic diet is obtained from dental microwear, bone chemistry,

zooarchaeological and archaeobotanical remains (Revedin et al., 2010). For a long period of time researchers believed that the paleo diet comprises mostly lean meat, internal organs and limited uncultivated plant foods. This protein-rich diet excluded the type of foods such as dairy, legumes and grains (Frassetto,

showed that our ancestors did eat grass seeds, legumes and grains of various wild plants (Iii, Spy, Henry, Brooks, & Piperno, 2010; Revedin et al., 2010). This evidence indicates a ‘new’ kind of paleo diet, different from what we previously thought. Little to no research has been done examining these new findings about the paleodiet.

After the hunters and gatherers, the Neolithic period of time started. Humans were introduced to the agricultural revolution and food animal domestication. Food became more accessible, but that was not enough; we wanted to develop new mechanisms to make, preserve and manipulate food even more easily. So, industrialization followed. Recently another revolution has started: the fast food revolution. Now, in the Western World we have more access to food than needed. It is not the nutrients themselves anymore that are the main factors in

determining the choice on what to eat; we choose attractive, practical and durable over healthy. Fast food and other highly processed foods are way more convenient and therefore great suiters into our busy lives. They are made to be able to be consumed anywhere, anytime. However, the intake of ultra-processed food is positively correlated with the consumption of a lot of unhealthy types of fat, free sugars and salt (Monteiro et al., 2018; (Bielemann, Santos Motta, Minten, Horta, & Gigante, 2015). So not only because the convenience, but also because of our built-in appetite for fat and sugar, honed during human evolution, highly processed foods are way more appealing to us (Cummings, Mamtora, and Tomiyama, 2019).

The rapidity of the new innovations that come with agriculture and

industrialization has overreached the capacity of genetic evolution to keep up. The discordance between the modern diet and a paleo-type diet, to which evolutionary forces have adapted our digestive system and physiology, may contribute in a major way to the pathogenesis of multiple disorders. Various researches refer to the consumption of extremely processed foods as a reason for the rise in obesity and chronic diseases (Monteiro et al., 2018; Bielemann et al., 2015). However, relatively little is known about the connection between an unhealthy diet and depression, from an evolutionary perspective.

Yet, rapidly increasing amount of evidence implicates direct cell-to-cell

tract and our brain (Stilling, Dinan, and Cryan, 2014). These host-microbe

interactions are mainly possible because of the gut-brain axis (GBA). This axis is a bidirectional neurohumoral communication system that integrates

gastrointestinal and brain functions (Collins and Bercik, 2009). Because of this bidirectional communication it is important to consider the influence of behavior on our diet, but also the influence of our diet on the brain and behavior (Stilling et al., 2014). Recent discoveries suggest that gut microbiota are an important factor in how the body influences the brain, contribute to healthy homeostasis, and influence risk of several mental diseases, including mood disorders such as depression and anxiety (Foster and McVey Neufeld, 2013; Dash et al., 2015). See the Appendix to find more information on the gut-brain interaction.

As mentioned earlier, a high intake of ultra-processed foods is considered to be unhealthy because of three reasons: first, our bodies may still be adapted to a hunter-gatherer type of diet; second, because of that, our bodies may not be able to process the high amounts of sugar and fat. Third, because of this disability ultra-processed food causes a disbalance in (the variety of) the microbiome, which is a crucial component in our state of health (Stilling, Dinan, and Cryan, 2014). Taking into account these three reasons and the earlier mentioned bidirectional gut-brain interaction, ultra-processed food may contribute to

depression. Furthermore, according to the mismatch hypothesis, an environment more closely resembling a hunters and gathers environment, would be better for our (mental) health (Frassetto et al., 2009). With food being a major factor in our environment, would less highly processed food and a more paleo type diet help in a way that we can eventually cure or prevent depression?

To find this out, the objective of this study was to evaluate the consumption of (ultra-) processed food and a Paleolithic type diet in Dutch students, and to investigate whether this correlates with symptoms of depression. In addition, we studied whether a mismatch with our ancestors’ type of life is correlated with both an unhealthy diet and depression. We studied the data collected using a

the University Student Depression Inventory (USDI), among 150 Dutch students (Ocké, Bueno-de-mesquita, Goddijn, & Jansen, 1997). See the Appendix for the classification of ‘processed’ food used in this research.

A diet more closely resembling a hunter-gatherer diet is expected to go together with fewer to no depression symptoms, and a lower score on the Mismatch questionnaire. A diet containing more ultra-processed foods is expected to go together with more depression symptoms, and a high score in the Mismatch questionnaire. And at last, a lower mismatch score and fewer highly processed food is expected go together with a lower USDI score. After the data collection of the questionnaires, interviews will be conducted with some of the students who completed the questionnaire. This way, a closer look can be taken into causality and individual differences (Van Rossum, Fransen, Verkaik-Kloosterman, Buurma-Rethans, & Ocké, 2007).

Study 1: Survey

1.1. Methods

1.1.1. Participants

Participants were considered eligible when they were student and at least 16 years old, until they were graduated from any kind of study (Masters included). The pre graduate students needed to be Dutch native speakers. A written

informed consent was obtained. 151 (40 men, 111 women) students volunteered to participate in study 1.

1.1.2. Measures

Dutch Food Frequency Questionnaire

The Dutch Food Frequency Questionnaire (FFQ) is a self-report about the average consumption frequency during 12 months, for 42 food items. The consumption of ultra-processed foods was evaluated according to the classification proposed by Monteiro et al. (2018), i.e., the NOVA classification which represented the degree

of processing, as follows; Group 1: unprocessed or minimally processed foods to processed foods used as ingredients in cooking, Group 2: preparations by the food industry and ultra-processed foods or food products. The questionnaire made by Ocké et al. (1997) was used and altered to suit this study; some food items were added or left out because of expected changes in food patterns (e.g. fast food). In the Dutch FFQ, 18 items were classified as unprocessed and 24 items were classified as processed. Subjects could indicate their answer on a 10-point scale; 1: never to 10: more than 3 times a day. Group 1 consisted of 18 items, so a minimum score of 18 and a maximum score of 180 could be achieved, regarding to unprocessed food. Group 2 consisted of 24 items, so a minimum score of 24 and a maximum score of 240 could be achieved, regarding to

processed food. Since there were not as much unprocessed foods on the FFQ as there were processed foods, the scores were converted into proportions. These proportions are the ratios processed and unprocessed food, within the total amount of food items that are noted to be consumed by the participants. The food items were selected by a data-based approach, using the Dutch National Food Consumption Survey 1987–1988 dataset (Ocké et al., 1997). The food items included in the Dutch Food Frequency Questionnaire are listed in the Appendix.

Mismatch Questionnaire

The Mismatch questionnaire (MM) is used to measure the mismatch of the

participants’ life with a hunter and gatherer kind of life (F. W. Marlowe, 2010). It is a self-report consisting of 78 questions divided into 15 subscales: sleep; this item contains questions about the participants sleep behavior, lack of exercise;

contains questions about the amount of exercise the participants gets every day, processed food; contains questions about the participants’ diet, lack of social contact; contains questions about the participants’ social contact with friends, partner and family, lack of nature; contains questions about the participants’ contact with nature (for example, does he/she own plants? Does he/she go outside often?), materialism; contains questions about the urge to own certain things and the importance of owning these things, perfectionism; contains

questions about the urge to perform and the importance of being good at things, lack of time; contains questions about the participants’ time schedule and

planning, lack of freedom; contains questions about the participants’ perspective on his/her freedom to do whatever he/she wants whenever he/she wants, lack of happiness; contains questions about participants’ joy and happiness in life, social

participants spent on social media and whether they sometimes fear to miss out on things, worrying; contains questions about whether the participant worries about his/her future for example, deviant youth; contains questions about the participants’ childhood and his/her perspective on how he/she is raised,

unhealthy habits; contains questions about unhealthy habits such as smoking, and other; contains questions about the participants religiousness, residence, diagnoses of psychological disorders, allergies, headaches and stomach pain, age and sex. The questionnaire is new and never used in previous studies. The

maximum score on the Mismatch questionnaire that could be achieved was 78, the minimum score was 0. The higher the score, the higher the mismatch with a hunter and gatherer type of life. Find the exact questions in the Appendix 4.

University Student Depression Inventory

The University Student Depression Inventory (USDI) is a self-report containing 30 items, rated on a 5-point scale; 1: not at all to 5: all the time. (Habibi, Khawaja, Moradi, Dehghani, & Fadaei, 2014). The questions were divided into three

subscales: lethargy, cognitive/emotional and academic motivation. The inventory from Habibi et al. (2014) was translated into Dutch. Its Cronbach’s alpha was α =

0.95 (Heerink, R., 2019), and the internal consistencies of the subscales of

lethargy was respectively 0.89, of cognitive/emotional was 0.84 and of academic motivation was 0.84. According to Khawaja and Bryden (2006), the English version of the USDI had good concurrent validity with a strong positive

relationship with the Depression, Anxiety, and Stress Scale. (Habibi et al., 2014).

1.1.3. Procedure

The USDI was translated into Dutch. Ethical approval was obtained by the University of Amsterdam committee. The survey was made using Qualtrics, an online survey platform. Subjects could participate whenever or wherever they wanted; on their mobile phone or on their laptop/computer. The study was advertised on social media and students were invited to make the survey. Also, the test was advertised on a survey website, where students could fill in the survey voluntarily. They were informed that their participation was completely

voluntary, and they could discontinue the test at any time. The survey contained also questions on two other topics, which were used for research: the Quick Big Five, the Highly Sensitive Person Test and the Pittsburgh Sleep Quality Index. Since these were not relevant for this current study they are not further explained. The survey design is shown in figure 1.

1.1.4. Data analysis

It took 17 days to get 151 students to complete the survey. Qualtrics collected and converted the data into Excel. After the data collection statistical analyses were done. P-values lower than 0.05 were considered statistically significant. A power analysis for multiple regression was done and at least n = 68 participants were needed.

Figure 1. The survey design of the survey in study 1.

Shown is the survey design of study 1. The online survey was made by Dutch students and started with an informed consent, followed by 3 questions about the age, sex and education of the participant. After, the Dutch Food Frequency Questionnaire (FFQ) was presented, followed by the Mismatch Questionnaire (MM), the Quick Big Five (QB5), Highly Sensitive Person Test (HSP), Pittsburgh Sleep Quality Index (PSQI) and the University Student

Depression Inventory (USDI). At last, 5 questions about the participants health were asked. After completing the survey, the participants were asked if they would want to participate in a follow-up study (study 2). It took approximately 20 minutes for the participants to complete

variances and means between males and females. Correlations were tested between the MM, FFQ and USDI scores. Also, a correlation analysis was done between all of the MM subscales and the USDI. The ‘Other’ subscale contains questions which would not fit into the other subscale themes. That is why these questions are also individually analyzed, by doing correlation tests between the USDI, FFQ and the ‘Other’ questions. This way some more knowledge can be preserved about the sample used in this study.

Two MLR analyses were done. First, a MLR analysis was done with the MM scores, processed scores and unprocessed scores being the independent variables, and the USDI scores being the dependent variable. There were not equally as much processed food items on the FFQ as there were unprocessed food items. That is why the FFQ scores were also converted into ratios, to be able to compare the scores with each other. To make sure that the FFQ had just one outcome, these two food ratios were put together and called ‘Food Ratio’. Another MLR analysis was done, with the MM scores and FFQ Food Ratio being the independent variable and the USDI being the dependent variable. For some parameters, median and range data were calculated.

1.2. Results

A total of 151 students participated. However, 45 students (29,8%) were excluded because they did not meet the inclusion criteria or had missing data.

The results of the remaining 106 participants (33 men, mean age 22,07 ± SD 2,51) were analyzed. 11 students indicated to have been diagnosed with a mental illness.

A Levene’s Test was done and no significant difference in variances was found between males and females (p=0.21). A t-test was done, and no significant difference was found between the mean USDI scores of the different sexes (p=0.56). The mean of the USDI scores of men was 62.88 ± SD 19,4. The mean of the USDI scores for women was 65.04 ± SD 16,81. Taking into account that there were no differences found between sex regarding to the responsive variable and that the men group was relatively small (31,1% was male), no analysis was done between these two groups.

The distribution data of the different questionnaires and age are shown in table 1. The average age of the participants was 22,07 years old (range >16). The mean score of the MM questionnaire was 31,04 (range 0-78), the mean score of the USDI was 64,67 (range 30-150).

Table 1. Age, MM and USDI data distribution.

Shown are the means, standard deviation (SD), minimum and

maximum of the age, the Mismatch questionnaire scores and the USDI questionnaire scores. Age MM USDI Mean 22,07 31,04 64,67 SD 2,51 6,13 17,41 Min 17 19 33 Max 30 46 111

1.2.1. FFQ

On average participants scored 88,81 (± SD 13,77, range 24-240) on processed food, and 85,04 (± SD 9,99, range 18-180) on unprocessed food of the FFQ (Table 2). A paired t-test was performed, and a significant difference was found between the scores of processed and unprocessed foods (p<0.001). Since there were not as much unprocessed food on the FFQ as there were processed foods, the scores were converted into proportions (Table 3). These proportions show the ratios processed and unprocessed food, within the total amount of food items that are noted to be consumed by the participant. An average of 43,84% (± SD 4,19%) was attributed to the consumption of processed foods. The majority (56,16% ± SD 4,19%) of food items was attributed to unprocessed food. A non-parametrical Spearman correlation was done, and no significant correlation was found between the MM questionnaire and the FFQ scores on processed food and unprocessed food. Also, no significant correlation was found between the FFQ and the USDI (Table 4).

Table 4. Correlation between MM, USDI and FFQ.

No significant correlation was found between the MM

questionnaire and the FFQ scores on both processed food and unprocessed food. No significant correlation was found between the FFQ and the

Processe d Ratio Unproces sed Ratio Mean 43,84% 56,16% SD 4,19% 4,19% Min 29,93% 44,44% Max 55,56% 70,07% Table 3. FFQ proportions of

processed and unprocessed food. Shown are the mean, standard deviation (SD), minimum and maximum of the proportions processed and unprocessed food, within the total amount of food that are noted to be consumed by the participants. Processe d Unproces sed Mean 88,81 85,04 SD 13,77 9,99 Min 45 56 Max 140 110

Table 2. FFQ scores distribution, on processed and unprocessed food.

Shown are the mean, standard deviation (SD), minimum and maximum of the scores on the FFQ performed by the participants. A score within the range of 24-240 could be performed on the

processed food items, and a score within the range of 18-180 could be performed on the unprocessed food items of the FFQ. A total score could be performed within the range of 42-420.

Correlatio n Processed p-value Correlation Unprocessed p-value MM 0,10 0,31 -0,13 0,19 USDI 0,07 0,45 -0,18 0,07

1.2.2. MM

For every scale of the Mismatch questionnaire (Cronbach’s alpha α = 0.58) the mean and standard deviation was calculated. These are shown in table 5 and figure 2. Participants scored the highest on the subscale ‘Lack of time’, with a mean of 3,54 (± SD 1,49). The lowest was scored on the ‘Deviant youth’ subscale, with a mean of 0,77 (± SD 0,97). The USDI was not normally distributed, so a non-parametrical Spearman correlation was done between the USDI and every subscale of the MM questionnaire (Table 5). The ‘Lack of freedom’ item showed the highest correlation with the USDI (0,47), with p<0.001. The second highest correlation was found for the ‘Lack of time’ subscale (0,27), with p<0.05. The MM data of all the subscales

together was normally distributed, so a Pearson correlation test and regression analysis were done between the total Mismatch score and the USDI. A significant p-value (p<0.001) was found, with a correlation of 0,47 and regression coefficient 1,34 (Figure 3).

The ‘Other’ subscale of the MM questionnaire contains questions that are individually analyzed. Find the exact questions in the Appendix 4. No significant correlation was found between any of the questions and the FFQ or USDI.

Sleep Lack of exercise Processe d food Lack of social contact Lack of Nature Materialis m Perfectionis m Lack of time Min 1 0 0 0 0 0 0 0 Max 5 5 4 4 5 4 5 5 Mean 2,58 3,09 1,13 1,72 2,21 1,8 4,02 3,54 SD 0,94 1,28 1,03 1,04 1,05 1,25 1,27 1,49 Correlatio n 0,24 -0,19 0,25 0,03 0,13 0,08 0,23 0,27 p-value 0,01* 0,33 0,01* 0,76 0,17 0,39 0,02* 0,01* Lack of freedom Lack of happines s Social media /FOMO Worrying Deviant youth Unhealthy habits Other Min 0 0 0 0 0 0 0 Max 4 4 5 5 4 4 3 Mean 1,01 1,05 2,7 2,58 0,77 0,83 2,18 SD 1 1,44 1,79 1,29 0,97 0,92 0,9 Correlatio n 0,47 0,18 0,12 0,26 0,18 0.05 -0.08 p-value 0,00* 0,07 0,21 0,01* 0,10 0,63 0,42

Table 5. Mean, standard deviation (SD) and correlation with USDI and corresponding p-values of every item on the Mismatch questionnaire.

1.2.4. USDI

Cronbach’s alpha of the USDI was α = 0.92. A Spearman correlation test was done, and no significant correlation was found between the MM questionnaire and the FFQ scores on processed food and unprocessed food. No significant correlation was found between the FFQ and the USDI.

Figure 2. Mismatch subscale distribution boxplot

Shown is the boxplot of the scores on the subscales of the Mismatch questionnaire. From left to right: sleep, lack of exercise, processed food, lack of social contact, lack of nature, materialism,

perfectionism, lack of time, lack of freedom, lack of happiness, social media/FOMO, worrying, deviant youth, unhealthy habits and other.

Figure 3. Correlation and regression between the USDI and MM.

Shown is a scatter plot of the correlation analysis between the USDI and MM data, and the regression line between the USDI data (y-axis) and the MM data (x-axis) (p<0.001, r = 0.47, regression coefficient = 1,34, SE = 0,25).

1.2.5. MLR

Two multiple linear regression (MLR) analyses were done, with USDI as dependent variable and FFQ and MM as independent variables. First, a MLR was done to analyze the processed and unprocessed food scores. The homoscedasticity of this model was tested, and it was found that the variation of observations around the regression line was constant. A significant regression was found between the MM and USDI (p<0.001, regression coefficient = 1,26, SE = 0,25). No significant regression was found for both the processed and unprocessed scores. The Adjusted R-squared showed that 21,89% of the variation within the USDI can be attributed to the differences between the MM, processed and unprocessed scores (Table 6).

Second, a MLR was done taking processed and unprocessed food together as one variable, called ‘Food Ratio’. Food Ratio was the ratio processed-unprocessed food within the total amount of food items that are noted to be consumed by the participant, as the processed and unprocessed scores were converted into

proportions. The residuals of the USDI were not normally distributed. The homoscedasticity of this second model was tested, and it was found that the variation of observations around the regression line was constant. A significant regression was found between MM and USDI (p<0.001, regression coefficient = 1,27, SE = 0,26). The Adjusted R-square showed that 21,04% of the variation within the USDI can be attributed to the differences within the MM, since no significant p-value was found for either processed or unprocessed food (Table 7). No significant regression was found between the FFQ Food Ratio and the USDI (Table 6).

15

Table 6. Multiple Linear Regression output

Mismatch, processed food, unprocessed food and USDI. Shown is the multiple regression output, with the Mismatch score, processed food (Pro) score and the unprocessed food (Unpr) score on the FFQ as

independent variables, and the USDI as the dependent variable. No significant p-value was found for the FFQ. A

MLR Estim

ate Std. Error t-valu e p-value Intercept 43,74 16,96 2,58 0,01 MM 1,26 0,25 4,96 0,00** Pro 0,06 0,12 0,49 0,63 Unpr -0,28 0,16 -1,72 0,09 Residual standard error 15,5 5 R Squared 0,24 Adjusted R 0,22

1.2.6. Principal component analysis subscales Mismatch Questionnaire

A principal component analysis (PCA) was done to transform possibly correlated variables of the MM questionnaire into a set of values of linearly uncorrelated variables. First a scree plot was made to determine how many components were relevant. The number of components above the scree was 13 with Eigenvalue 2 (Figure 4). An Orthogonal Varimax rotation was used, because the relevant

components were considered to be uncorrelated. Find the exact PCA outcome in the Appendix 7.

The MM questionnaire consisted out of 15 subscales. However, 13 components were considered to be relevant according to the PCA. There are 9 components which can be explained by its variables (Table 8).

Table 7. Multiple Linear Regression output

Mismatch, FFQ and USDI. Shown is the multiple

regression output, with the Mismatch and FFQ scores as independent variables and the USDI as the dependent

variable. No significant p-value was found for the FFQ. A significant p-value was found for the MM questionnaire. **,

MLR Estim

ate Std. Error t-valu e p-value Intercept 14,3 10,80 1,325 0,19 MM 1,27 0,26 4,98 0,00** Food Ratio FFQ 13,31 11,80 1,13 0,26 Residual standard error 15.6 0 R Squared 0.23 Adjusted R 0.21 p-value 0,00* *

Variables (questions of the MM questionnaire) Component Heb je (bijna) altijd het gevoel dat je het te druk hebt? 1

Voel je je minstens één keer per week opgejaagd? Timing

Heb je minstens één keer per week het gevoel dat je tijdgebrek hebt? Maak je je minstens één keer per week zorgen over deadlines? Wil je minstens één keer per week meer doen dan past in de beschikbare tijd? Heb je het gevoel dat je altijd kunt vertrekken als dingen je tegen gaan staan?

Krijg je minder werk/studie gedaan omdat je wordt afgeleid door sociale media? 2

Blijf je ’s avonds laat langer actief op sociale media dan je zou willen? Social media

Ben je meer tijd kwijt dan je zou willen aan sociale media? Heb je het gevoel dat je verslaafd bent aan sociale media? Zit je minstens vijf keer per week nog minstens een uur voor het slapen gaan op je telefoon/tablet/computer?

Heb je minstens één keer per week het gevoel dat je kunt gaan en staan waar je wilt? 3

Heb je minstens één keer per week het gevoel dat je de vrijheid hebt om te doen wat je wilt? Freedom & Happiness

Heb je minstens één keer per week een sociale activiteit buiten de deur? Heb je momenteel alle spullen die je nodig hebt om van het leven te kunnen genieten? Moet je minstens één keer per dag hard lachen om iets leuks? Heb je minstens één keer per week het gevoel dat je je tijd zelf kunt indelen? Dans je minstens één keer per week (thuis of elders)?

Vind je het belangrijk om (bijna) altijd goed te presteren? 4

Heb je de neiging om (bijna) altijd goed je best te doen? Perfectionism

Wil je graag dat dingen in het leven gaan zoals je van tevoren had gepland? Heb je de neiging om (bijna) altijd te streven naar perfectie? Heb je de neiging om je agenda vol te plannen? Heb je moeite om dingen los te laten?

Heb je als kind veel warmte ontvangen van je ouder(s)? 5 Heb je een hechte band met het gezin waar je uit komt? Family

connections

Hebben je ouders je al op jonge leeftijd zelfstandigheid bijgebracht? Ben je als kind door je ouder(s) vrijgelaten om te doen wat je wilde? Heb je één of meer kinderen of heb je een kinderwens?

Drink je gemiddeld meer dan twee koppen koffie per dag? 6

Gebruik je minstens één keer per maand drugs? Unhealthy habits

Drink je minstens één keer per dag een drank met suiker? Drink je gemiddeld meer dan zeven glazen alcohol per week? Rook je gemiddeld meer dan vijf sigaretten per dag? Eet je minstens één keer per dag gefrituurde ingrediënten en/of producten met veel zout?

Woon je bij je ouder(s)/verzorger(s)? 7

Woon je bij of dichtbij je familie? Residence

Woon je in de stad?

Vind je het belangrijk om in je leven veel bezittingen te vergaren? 8

Heb je bewondering voor mensen die dure huizen, auto’s en kleding bezitten? Materialism

Houd je van veel luxe in je leven? Heb je het gevoel dat je dingen mist als je geen toegang hebt tot sociale media?

Kom je minstens één keer per dag in de natuur (park, bos, duinen, etc.)? 9

Ben je gemiddeld vier uur per dag of meer in de buitenlucht? Exercise & Nature Ben je gemiddeld vier uur per dag of meer in beweging?

Is er in jouw buurt veel groen (bomen, struiken, etc.) te vinden? Sommige mensen zijn beweeglijk. Denk bijvoorbeeld aan jonge kinderen; die zitten bijna nooit stil. In vergelijking met het gemiddelde van jouw leeftijd, ben jij een beweeglijk persoon? Zit je vaak op je stoel te wiebelen en/of te friemelen met je handen?

Six time indicating questions, such as ‘Heb je bijna altijd het gevoel dat je het te druk hebt?’, loaded onto component 1. This component is labelled Timing. Five social media questions, such as ‘Krijg je minder werk/studie gedaan omdat je wordt afgeleid door social media?’, loaded onto component 2. This component is called Social Media. Seven freedom and happiness related questions, such as ‘Heb je minstens één keer per week het gevoel dat je kunt gaan en staan waar je wilt?’ loaded onto component 3. This component is labelled Freedom and Happiness. Six perfectionism related questions, such as ‘Vind je het belangrijk om (bijna) altijd goed te presteren?’, loaded onto component 4. This component is labelled Perfectionism. Five parents and youth related questions, such as ‘Heb je als kind veel warmte ontvangen van je ouders?’, loaded onto component 5. This component is labelled Family connections. Six unhealthy habits questions and some questions about processed food, such as ‘Drink je gemiddeld meer dan twee koppen koffie per dag?’, loaded onto component 6. This component is labelled Unhealthy habits. Three residence related questions, such as ‘Woon je bij je ouder(s)/verzorger(s)?’, loaded onto component 7. This

component is labelled Residence. Four materialism questions loaded onto component 9, such as “Vind je het belangrijk om in je leven veel bezittingen te vergaren?”. This component is labelled Materialism. Six nature and exercise related questions, such as

Table 8. Components and its corresponding variables of the Principal Component Analysis (PCA) of the MM questionnaire.

Shown are 9 components of the PCA of the MM questionnaire: timing, social media, freedom & happiness, perfectionism, family connections, unhealthy habits, residence, materialism, exercise & nature. The components can be explained by their corresponding variables.

‘Kom je minstens één keer per dag in de natuur (park, bos, duinen, etc.)?’, loaded onto component 11. This component is labelled Exercise & Nature.

Nine questions loaded onto the 9 components in table 8 but did not match the theme of the component (these questions are not shown in table 8). For example ‘Maak je je minstens één keer per week zorgen over de vraag of je je studie wel gaat halen?’ loaded onto component 6, which is about unhealthy habits. Altogether, the two subscales ‘Lack of freedom’ and ‘Lack of happiness’, could be combined as one factor in further research using the MM questionnaire. Also, ‘Processed food’ and ‘Unhealthy Habits’ could be considered as one factor. At last, subscales ‘Lack of social contact’ and ‘Deviant youth’ could be combined in one factor. One new subscale could be added; ‘Residence’. The remaining 4 components seem to consist out of random variables, mostly containing questions of subscales ‘Worrying’, ‘Processed food’, ‘Sleep’ and ‘Other’.

1.3. Conclusion

The aim of study 1 was to find a correlation between the FFQ, MM and USDI. However, a significant correlation was found only between the USDI and the MM. Also, a correlation test was done between the scores of every subscale of the MM questionnaire and the USDI scores. The highest correlation was found for ‘Lack of freedom’, and the second highest correlation was found for ‘Lack of time’.

A principal component analysis was done to transform possibly correlated variables of the MM questionnaire into a set of values of linearly uncorrelated variables.

Thirteen components were found. Nine of the components contained variables which would logically fit together. These components were labelled as follows: Timing, Social Media, Freedom& Happiness, Perfectionism, Family connection, Unhealthy habits, Residence, Materialism and Exercise & Nature. The remaining 4 components seem to consist out of random variables, mostly containing questions of subscales ‘Worrying’, ‘Processed food’, ‘Sleep’ and ‘Other’.

Study 2: Interview

2.1. Methods

2.1.1. Sampling and participant information

In-depth semi-structured interviews (n = 5) were conducted with Dutch students, aged 22-27. Two of the interviewees were Master’s students, the three others were finishing their Bachelor’s. They completed the survey from study 1 and agreed to participate in a follow-up study. The interviewees were recruited in person or online, via e-mail. One student did not reply to the e-mail, so another student was approached. The students were chosen to participate, based on their scores on the FFQ, MM and USDI. Participants 1 and 4 were male and female and scored relatively low on the MM. Also, they both noted to eat relatively much unprocessed food. Participant 2 and 3 scored quite high on the USDI and noted to eat relatively much processed food. Participant 5 scored very low on the MM. Two of the interviewees were living at their parents. There were no dropouts during the interview process. The students were informed that their participation was completely voluntary and that they could discontinue the interview at any time. Participant characteristics (age, gender, scores on the different questionnaires) are presented in table 9 and 10.

2.1.2. Data collection

Only the researcher and the participant were present during the interview. All students consented to their interview being audio recorded. Additional notes were maintained in a research diary. The interviews took place at the participants home or at university premises. Some of the interviews were conducted by video-message, due to long distance. The interview was semi-structured, with 4 main themes to guide but not direct the interviews. The questions in the interview were yielded into 4 themes: (1) students’ diets and their opinion about what they

eat, (2) their overall mood, are they happy in life or not, (3) the influence of their mood on their diet and the influence of their diet on their mood, and at last (4) students’ individual differences in Mismatch scores. All the participants were asked these same main questions but received different follow-up questions, depending on their answers and their scores on the questionnaire of study 1.

2.1.3. Data analysis

Transcripts were first coded line by line and then systematically sorted under the relevant themes. The interviews were transcribed verbatim, but except from the main questions, some of the irrelevant follow-up questions were left out. The descriptive themes were then compared between the participants. Differences, patterns and similarities were identified to generate a consistent interpretation of the dataset. To make sure the transcription was done thoroughly, and no details were left out the interviewer did the analysis herself, as soon as possible after the interviews were taken.

2.2. Results MM Mean SD Participa nt 1 Participa nt 2 Participa nt 3 Participa nt 4 Participa nt 5 Sleep 2,58 0,94 1 3 4 3 2 Lack of exercise 3,09 1,28 5 0 1 1 3 Processed food 1,13 1,03 0 1 4 1 1 Lack of Social contact 1,72 1,04 1 2 1 2 0 Lack of Nature 2,21 1,05 1 3 0 0 3 Materialism 1,8 1,25 2 1 2 0 1 Perfectionis m 4,02 1,27 4 4 4 5 5 Lack of time 3,54 1,49 2 4 4 5 1 Lack of freedom 1,01 1 0 1 0 1 0 Lack of happiness 1,05 1,44 2 1 1 0 0 Social Media /FOMO 2,7 1,79 1 5 1 4 2 Worrying 2,58 1,29 3 5 5 2 4 Deviant youth 0,77 0,97 0 1 0 0 0 Unhealthy 0,83 0,92 1 4 2 1 0

Habits

Other 2,18 0,9 3 3 3 2 1

Analysis yielded four intersecting key themes: (1) students’ diets and their opinion about what they eat, (2) their overall mood, are they happy in life or not, (3) the influence of their mood on their diet and the influence of their diet on their mood, and at last (4) students’ individual differences in Mismatch scores regarding to the quantitative research done in this study. The findings below include quotations. This way a rich description of the experiences of the

interviewees is provided. The data of the participants is shown in table 9 and 10.

2.2.1. Students’ diets and their opinion about what they (should) eat.

Every interviewee described their eating behavior very much differently. 3 of the 5 students noted to be quite conscious about what they ate; they tried to eat healthy, but were not too hard on themselves (“Ik volg niet echt een bepaald

dieet. Ik eet ook soms erg ongezond, maar na een ongezonde periode probeer ik dat te balanceren door weer een periode gezond te eten. Ik ben me bewust van wat goed voor me is en wat niet.” – Female, aged 22, USDI 56, MM 23, Pro. Ratio

38,41, Unpr. Ratio 61,59). One of the students noted to eat healthy but not because he was being conscious about it, but because he simply did not like unhealthy foods (“Ik ben er niet echt bewust mee bezig, maar het gaat een

beetje vanzelf. Ik vind het zelf gewoon het lekkerste om gezond te eten.” – Male,

aged 24, USDI 93, MM 38, Pro. Ratio 46,13, Unpr. Ratio 53,88). One of the students was aware of the meaning of processed food, in addition to his

awareness of his quite unhealthy eating behavior, but noted to just not have the Table 9. MM scores of the participants of study 2. Shown are the MM scores of the different subscales of the participants in study 2. Also, the mean scores and the standard deviation (SD) of the MM data of all the participants of study 1 is shown.

Table 10. Data of the participants of study 2. Shown are the age, sex, USDI score, MM score, the amount of processed and unprocessed items from the FFQ and the processed and unprocessed food ratios.

Partici pant

Age Sex USDI MM Proces

sed Unproce ssed Pro. Ratio Unpr. Ratio 1 27 Male 60 26 66 98 33,56 66,44 2 24 Male 93 38 97 85 46,13 53,88 3 25 Male 91 32 115 87 49,78 50,22 4 22 Female 54 26 86 110 36,96 63,04 5 22 Female 56 23 79 95 38,41 61,59

veel geblowd en gaf vaak de schuld van mijn ‘minder gezonde’ gevoel aan het feit dat ik blow.” “Ik vergeet soms ook avond te eten, door mijn werk. En soms vind ik het lastig om inspiratie op te doen voor wat ik ga eten” “Ik denk dat als ik meer structuur in mijn leven had, dat ik dan wel wat gezonder en beter zou eten.” – Male, aged 25, USDI 91, MM 32, Pro. Ratio 49,78, Unpr. Ratio 50,22). The

other students who knew about processed and unprocessed food, and its high amounts of sugar and fat, said that they tried not to eat too much processed products. One of the students did not know about processed and unprocessed food at all. Just one of the interviewees ate only vegetarian meals (“Ik ben al 12

jaar vegetariër. Ik eet heel soms vis, omdat dat goed is voor bepaalde vetten. Dus ik eet eigenlijk best wel gezond. Dat heb ik vanuit huis meegekregen.” –

Female, aged 22, USDI 54, MM 26, Pro. Ratio 36,96, Unpr. Ratio 63.04). Every interviewee had a healthy eating behavior when living at their parents before leaving for college (“Mijn moeder zorgde er altijd voor dat we thuis goed aten.

Toen ik op kamers ging veranderde mijn dieet dus.” – Male, aged 25, USDI 91,

MM 32, Pro. Ratio 49,78, Unpr. Ratio 50,22. “Mijn ouders kookte altijd en bestelde

nooit.” – Male, aged 24, USDI 93, MM 38, Pro. Ratio 46,13, Unpr. Ratio 53,88).

2.2.2. Overall mood

4 of the 5 students noted to be quite happy in life. One student did not feel happy at the time of the interview. (“Over het algemeen ben ik denk ik niet heel erg

gelukkig geweest de afgelopen jaren. Ik ben best ambitieus maar ik ben niet echt bezig geweest met mijn ambitie de afgelopen jaren. En dat maakt me wel

ongelukkig.” – Male, aged 25, USDI 91, MM 32, Pro. Ratio 49,78, Unpr. Ratio

50,22”). All of the interviewees felt it was important to do what you love and to have good and enough social contact with family and friends (“Plezier hebben in

wat je doet. Ik kom graag uit bed elke dag.” – Male, aged 27, USDI 60, MM 26,

Pro. Ratio 33,56, Unpr. Ratio 66,55. “Ja ik ben op dit moment wel gelukkig. Wat

mij gelukkig maakt zijn sociale contacten, me bezighouden met dingen die ik leuk vind.” – Male, aged 24, USDI 93, MM 38, Pro. Ratio 46,13, Unpr. Ratio 53,88.

“Ja, ik ben op dit moment wel gelukkig ja! Dat komt vooral doordat het nu goed

gaat met mijn familie, en met mijn vriend.” – Female, aged 22, USDI 56, MM 23,

Pro. Ratio 38,41, Unpr. Ratio 61,59). Most of the interviewees felt that arguing and complicated social contacts had a big negative impact on their happiness (“Als het niet lekker loopt tussen mij en mijn vriendin weegt dat wel zwaar, dat

kan mijn dag verpesten.” – Male, aged 27, USDI 60, MM 26, Pro. Ratio 33,56,

Unpr. Ratio 66,55). Most of the students thought that they got a lot of positive energy out of their study, especially later throughout their studies (“Ja ik ben op

dit moment wel gelukkig. Wat mij gelukkig maakt … mijn studie, ik vind het echt niet erg om heel veel tijd te stoppen in geschiedenis. Ik vond de middelbare school bijvoorbeeld veel erger, maar nu ik heb gevonden wat ik leuk vind en wat bij mij past maakt me dat heel erg gelukkig.” – Male, aged 24, USDI 93, MM 38,

Pro. Ratio 46,13, Unpr. Ratio 53,88). Some students felt a bit stressed during the beginning of college, mostly because they were a bit overwhelmed or because they felt like they did not make the right choice on what to study (“Tevens weegt

mijn studie erg zwaar; voor mijn huidige studie studeerde ik iets wat ik helemaal niet leuk vond en dat zorgde ervoor dat ik me niet gelukkig voelde.” – Female,

aged 22, USDI 54, MM 26, Pro. Ratio 36,96, Unpr. Ratio 63.04. “Tijdens mijn

bachelor was ik meer in het moment bezig en meer aan het zoeken. Ik wist nog niet wat ik precies leuk vond.” – Male, aged 27, USDI 60, MM 26, Pro. Ratio 33,56,

Unpr. Ratio 66,55). 4 of the interviewees knew how to cheer themselves up during times of unhappiness, mostly by talking to friends and family or by exercising.

2.2.3. The influence of mood on diet and the influence of diet on mood

2 of the interviewees, the two females, felt that their eating behavior had an impact on their mood. They noted a unhealthy feeling after times of eating unhealthy, and that caused unhappy feelings (“Stel ik heb een weekend erg

ongezond gegeten, dan merk ik dat wel aan hoe ik me voel. Ik zit dan minder lekker in mijn vel.” – Female, aged 22, USDI 54, MM 26, Pro. Ratio 36,96, Unpr. Ratio 63.04. “Als ik een tijd heel ongezond eet voel ik me niet lekker in mijn lijf.

Dus dat heeft wel invloed op hoe ik me voel.” – Female, aged 22, USDI 56, MM

23, Pro. Ratio 38,41, Unpr. Ratio 61,59). One student experienced a big impact of his eating behavior on his mood. He could use this connection to alter his mood when he wanted or needed (“Als ik me door niet eten moe voel, dan heeft dat

effect op mijn humeur. Dan weet ik dat dat komt doordat ik niet goed heb gegeten. Ik heb bijvoorbeeld een periode gehad waarin ik een heel strak dieet volgde. En in die periode wist ik dan ook gewoon dat ik me zo voelde door mijn eten en dat ik dus minder energie had. Ik kon het goed terugkoppelen; ik wist dat

dan hou ik me aan wat ik normaal eet en weet ik wat ik nodig hebt, dus dan ben ik zeker dat het wat dat betreft goed komt en dat maakt me ook meer zeker in de situatie.” – Male, aged 27, USDI 60, MM 26, Pro. Ratio 33,56, Unpr. Ratio

66,55). However, he did not experience an impact of his mood on his behavior. The remaining students felt no connection between their diet and mood.

2.2.4. Individual differences in Mismatch scores

All of the interviewees found it difficult to imagine how life would be if they did not have to study (“Poeh, dan heb ik echt geen leven meer. Ik stop nu zo veel tijd

in mijn studie, ik ben bijna met niets anders bezig.” – Female, aged 22, USDI 56,

MM 23, Pro. Ratio 38,41, Unpr. Ratio 61,59). Most of them thought that they would have to find something else to focus on. (“Als ik niet zou studeren had ik

andere dingen gezocht om me op te focussen. Werken. Maar ik vind het lastig om dat in te beelden.” – Male, aged 24, USDI 93, MM 38, Pro. Ratio 46,13, Unpr.

Ratio 53,88). One of the students noted to experience a liberating feeling when she thought of not having to study. (“Het gevoel dat ik niet meer zou hoeven

studeren geeft me wel een bevrijdend gevoel moet ik zeggen.” – Female, aged

22, USDI 54, MM 26, Pro. Ratio 36,96, Unpr. Ratio 63.04). 2 of the interviewees lived at their parents’. Both moved back in after a period of living away from their parents. They experienced a more relaxed overall feeling after moving back in. They thought it was convenient to not have the struggle of cooking for

themselves every day, and to have someone to talk to when they came home after a long day (“Ik kom nu thuis en dan is er iemand waarmee ik gezellig kan

eten en kletsen. Op kamers deed iedereen toch meer zijn eigen ding. Ook kan ik nu lekker mee eten met mijn moeder en hoef ik niet te stressen over eten.” –

Female, aged 22, USDI 56, MM 23, Pro. Ratio 38,41, Unpr. Ratio 61,59. “Toen ik

weer bij mijn moeder ging wonen viel er namelijk een druk, van dat ik op allemaal plekken tegelijk moest zijn, weg. Een fijne thuisbasis is voor mij echt heel erg belangrijk.” – Female, aged 22, USDI 54, MM 26, Pro. Ratio 36,96, Unpr. Ratio 63.04). One of the interviewees thought it would have been better for his eating behavior and mood if he would have lived at his parents a little longer than he did (“Ik denk dat ik wel wat snel op kamers ben gegaan. Ik moest wel

want ik ging in een andere stad studeren maar ik denk dat ik eigenlijk wel meer tijd had kunnen gebruiken om nog op te groeien. Ook als ik me vergelijk met andere culturen, want dat doe ik, dan denk ik dat onze cultuur zo niet persé bij mij past. Ik had nog wel langer bij mijn ouders willen blijven wonen.” – Male, aged

25, USDI 91, MM 32, Pro. Ratio 49,78, Unpr. Ratio 50,22).

Almost all of the interviewees exercised quite often and 2 of them noted to think it was very important also for their mindsets. (“Een keer in de zoveel tijd heb ik

het echt nodig; als mijn hoofd bijvoorbeeld heel erg vol zit moet ik even tijd vrij maken om te gaan sporten. Het is echt mijn uitlaatklep. Sporten is voor mij echt een natural high.” – Male, aged 24, USDI 93, MM 38, Pro. Ratio 46,13, Unpr. Ratio

53,88).

One of the interviewees spent a lot of time on social media. According to him, that was due to the many hours he spent at the university (“Het is echt een

automatisme; ik open soms Instagram en wil niet eens weten wat er staat, maar toch besteed ik er veel tijd aan. Het is erg idioot, maar toch doe ik het. Ik ben er thuis veel minder mee bezig. Ik scrol echt het meeste tijdens lesuren, uit

verveling.” – Male, aged 24, USDI 93, MM 38, Pro. Ratio 46,13, Unpr. Ratio 53,88).

2.3. Conclusion

The aim of study 2 was to get an insight into the individual differences (in mismatch, depression and diet) between the interviewees and to find out more about causality. The majority of the interviewees was really conscious about his/her diet and tried not to eat too much unhealthy foods. However, 1 of these students did not know about the meaning of processed and unprocessed food. Just 1 of the 5 students noted to eat quite a lot of processed foods, despite the fact that she was conscious about the unhealthy amounts of fat and sugar in it. The majority of the students felt happy and thought studying gave them more energy and a purpose in life. However, some noted that the first year of college was quite tough. Mostly because they were unsure whether they had chosen the right study. Also, most of the interviewees felt that social contact with family, partner and friends and doing the things you love was really important for their overall happiness. 3 of the interviewees were conscious about a connection between their diet and their mood. Most of them thought that this was a

bidirectional connection. All of the students found it difficult to imagine how life would be if they did not have to study. At last, most of the interviewees noted that living at their parents might positively influence their diet and overall

happiness. The one of the interviewees with a rather unhealthy diet noted not to be completely happy in life. However, he did not attribute these feelings to his

3. Discussion

The aim of this study was to evaluate the consumption of processed food and unprocessed food in Dutch students, and whether this is correlated with

symptoms of depression. In addition, we studied whether a mismatch with our ancestors’ environment correlates with an unhealthy diet and symptoms of depression. No significant correlation was found between the University Student Depression Inventory and the Food Frequency Questionnaire, for both the

consumption of processed and unprocessed food. Also, no correlation was found between the FFQ and the Mismatch questionnaire. A significant correlation was found between the MM questionnaire and the USDI. The greatest correlation with the USDI was found for MM subscales ‘Lack of time’ and ‘Lack of freedom’. Also, a significant regression was found with the independent variable being the MM score and the dependent variable being the USDI score; the bigger the mismatch, the more symptoms of depression. An interview was conducted with 5

participants, who completed the survey. All of the interviewees noted that social contacts and doing the things you love were very important for their overall happiness.

Plausible mechanisms

A plausible explanation for the absence of correlation between the FFQ and the MM and USDI, could be that food has a relatively small effect on depression in comparison to other environmental aspects, such as social contacts or lack of freedom. Also, the gut-brain interaction is an unconscious mechanism. The experience of having too little time, too much stress and perfectionism are conscious processes and might therefore have a bigger, conscious impact on humans’ happiness. Moreover, most of the interviewees noted to experience a connection between diet and mood. However, they did not mention food when they were asked what environmental aspects had the largest impact on their happiness.

In this research we studied the correlation between food and depression in students. Previous findings show that long-term psychosocial stress and

components of the modern-day diet challenge our stress systems (De Punder & Pruimboom, 2015) (Appendix 2). Read ‘long-term’. Stress and processed food do

not have to cause depression right away: it might be a long-term process. In addition, earlier research shows that processed food is a risk factor for depression five years later in a middle-aged population (Akbaraly et al., 2009). Even though this study was conducted within a middle-aged (age 30-35) British sample (so not in Dutch students), these findings indicate a long-term effect of processed food as well. Further research could be done taking the FFQ scores of the sample from this current study, and conducting the USDI in 5 years.

The positive association between the MM and the USDI indicates a negative effect of having a too big mismatch with a hunters and gatherers life on

depression among students. There are several plausible mechanisms underlying this association. Evolutionary psychology considers human cognition, behavior and emotion as a product of underlying physiological mechanisms, which have evolved to increase survival or reproductive prospects in ancestral environments. However, humans have begun living in environments diverging extremely from those in which they evolved thousands of years ago. A certain mismatch arises through natural sources, but also through human-induced changes; the rapidity of the new innovations that come with agriculture and industrialization has overreached the capacity of genetic evolution to keep up (Li et al., 2018). It makes us less able to cope with aspects from our ‘new’ environment, and might therefore result in ‘diseases of modern civilization’, such as depression (Hahn-Holbrook & Haselton, 2014). Students these days have a huge mismatch: unlike hunters and gatherers most of the students are not living with their parents, and because of their busy study schedule they might have a lack of time or feel like they have a lack of freedom. During the interviews conducted in study 2, one of the interviewees noted that the experience of having a lack of time or a lack of freedom gives rise to a certain feeling of helplessness. Helplessness has an aggravating effect on depression (Seligman, 1972).

Limitations of this study

Quite some participants noted to experience a lack of time, according to the survey in study 1. It sounds plausible that because of busy study schedules students might feel that they have a lack of time or freedom. However, just one of the interviewees in study 2 attributed these feelings to her study. This might be because of several reasons. First, we may have interviewed too few students. A bigger sample would have given a more representing outcome and maybe

of college. Most of them noted to have experienced more stress at the beginning of their Bachelor. Following research could to be done, interviewing more first year students. Third, the interviewees in study 2 might have experienced a lack of time due to their study, but they did not think it contributed in a major way to their unhappy feelings. Other aspects could have been more relevant for them, such as social difficulties.

Another limitation to this study is reversed causation, with depression effecting certain aspects of mismatch rather than the other way around. For example, due to depressive feelings students might feel that they have a lack of time or

freedom, remains an alternative interpretation of the observed associations. To test this issue interviews were conducted. This way a clearer insight into causality was expected. However, as mentioned earlier, the interviews were conducted with too few students to get a real representative view on the 151 students who filled in the survey in study 1. More interviews would have possibly given a better perspective on causality.

In the present study the correlation for every subscale of the MM with the USDI was calculated. Six of the 15 subscales showed a significant correlation with the USDI. Also, a total MM score was calculated and a MLR was done, to find the effect of the FFQ score and the MM score on the USDI score. A significant

regression between the MM score and the USDI was found. Altogether, the total MM score had a significant effect on the USDI, even though just 6 of the MM subscales showed a significant correlation with the USDI. In addition, the

subscales are heterogeneous variables and uncorrelated with each other. This all suggests that we have to be careful with our conclusions; the effect of the MM may be mainly determined by just some of the subscales. Therefore, it is tricky to say that the overall MM score has an effect on USDI score. An ‘evolutionary mismatch’ is such a broad concept and therefore difficult to analyze. Future research should be done, analyzing all of the subscales individually and more thoroughly. This could provide an insight into whether we can speak about a general MM, or whether we have to analyze all the subscales separately.

One of the subscales of the MM questionnaire was ‘Processed Food’. Even though this subscale showed quite an interesting significant correlation with the USDI, no significant correlation was found between processed food on the FFQ and the USDI. This might be because of several reasons. First, on the MM subscale more

general questions about participants food intake were presented, while on the FFQ specific food items were shown. These FFQ food items may not have been representative for students’ dietary patterns. Second, the FFQ contained

questions about the participants’ food intake over the past 12 months. To answer accurately, a memory of food patterns in the past is required. In addition, actual intake may impact the reporting of intake in the past. Because of poor estimation of recall portions, limited possibilities for food specification and the quantification of food intake may be imprecise (Osuna, 2014). Third, we did not take portion size into account. This may have caused an error in collecting the food intake data as well. Altogether, it is quite hard to really define someone’s diet with just the FFQ. At last, a previous study found that the current FFQ seemed to be

adequate (Ocké et al., 1997). This study, however, was conducted over 20 years ago. Food consumption might have changed over the past few years. All of these factors (together) may have led to a different outcome of both questionnaires. This logically leads to a different correlation with the USDI.

Sometimes the interviewees indicated different experiences from what was expected based on their data from study 1. For example, some of the

interviewees scored high on the USDI, but noted to be quite happy in life during the interview. An explanation for that could be that everybody interprets

questionnaire differently, and therefore give other answers. Also, some might experience the same amount of depressive feelings but put these feelings in another perspective. Another explanation could be that some students find it hard to tell how they honestly feel face to face. Talking about depression is very personal, and it might be hard to talk about those feelings to someone they don’t really know.

In this study, a modern diet was compared to a paleo- type diet. Processed food was considered to be ‘modern’ food, and unprocessed food was considered to represent paleo- type food. However, almost all of our unprocessed food is

genetically modified nowadays (Costa-Font, Gil, & Traill, 2008). In addition, animal milk is unprocessed, but it only became part of our diet during food

domestication. This means that hunters and gatherers had totally different food to their disposal, so it is impossible for us to consume a real paleodiet now. However, since we do not have the same lives as hunters and gatherers 10.000 years ago, we could say we do not have to eat the exact same things to stay

ancestors had a lot more physical exertion in comparison to the modern human (Eaton & Konnor, 1985); sugars, protein and fats were much more important then, in comparison to now. We have to take this all into account when comparing these kinds of diets and be careful terms like ‘paleodiet’ or ‘paleo-type diet’.

Future research

We failed to show a clear connection between diet and depression from an evolutionary point of view. Even though no correlation was found between the FFQ and the USDI in this study, that does not mean processed food does not have anything to do with depression. Further research should be done examining the impact of processed food on depression while conducting a better dietary

assessment. This can be realized by compiling a more accurate questionnaire for students. In addition, the portion size needs to be reported. To prevent over- or underestimation and to make the portion size more specific, photographs of the portions can to be used (Osuna, 2014).

In the present study questionnaires were conducted to report students’ food intake. However, considering the gut-brain interaction (Appendix 2), it would be interesting to take a closer look into the biological background as well. By

examining the students’ exact nutrient intake, the effect of certain fats and sugars on the brain can be examined. Such an experiment should be done with a group of students consuming their ‘normal’ diet, and a group of students

consuming a diet closely resembling a hunter and gathers diet. Their exact food intake needs to be reported, for example by using a 24h dietary recall or a

dietary record (Osuna, 2014), and a USDI needs to be conducted. Also, interviews should be done to clarify any uncertainties about causality. By repeating this experiment 5 years later, a closer look can be taken into long term effects. Conducting such experiments in a larger sample could provide a better

understanding of how diet, depression and the evolutionary mismatch process influence each other. On top of that, this understanding could provide an insight into how we can prevent or cure depression, among students but also among others who suffer from this mental disease.

Conclusion

The correlation between the MM and USDI indicates a connection between

depressive symptoms and students living in an environment diverging extremely from our ancestors’. If a mismatch between modern and ancient lifestyles

adequately explains the large depression rates in students, then depression should be considered a disease of modernity as well (Hidaka, 2012). The results in this study together with earlier research suggest that living in such a modern- industrialized world demands certain coping mechanisms which we do not have. Students have to handle a lot of stress, while being in such an important time of their lives; they have to make decisions which have a huge impact on their future. While experiencing symptoms of depression students might have unwanted and unneeded difficulties with those decisions. However, more research needs to be done, as an ‘evolutionary mismatch’ is a very broad concept. The findings of this study show the cruciality of not putting too much pressure on students, and the necessity of doing more research into this field as a potential target for prevention of depressive disorders.

References

American Psychiatric Association, 2013. “Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.”

Akbaraly, T. N., Brunner, E. J., Ferrie, J. E., Marmot, M. G., Kivimaki, M., & Singh-Manoux, A. (2009). Dietary pattern and depressive symptoms in middle age.

https://doi.org/10.1192/bjp.bp.108.058925

Bailey, M. T., & Coe, C. L. (1999). Maternal separation disrupts the integrity of the intestinal microflora in infant rhesus monkeys. Developmental Psychobiology,

35(2), 146–155.

https://doi.org/10.1002/(sici)1098-2302(199909)35:2<146::aid-dev7>3.3.co;2-7

Bailey, M. T., Dowd, S. E., Galley, J. D., Hufnagle, A. R., Allen, R. G., & Lyte, M. (2011). Exposure to a social stressor alters the structure of the intestinal microbiota: Implications for stressor-induced immunomodulation. Brain,

Behavior, and Immunity, 25(3), 397–407.

https://doi.org/10.1016/j.bbi.2010.10.023

Bercik, P., Collins, S. M., & Verdu, E. F. (2012). Microbes and the gut-brain axis.

Neurogastroenterology and Motility, 24(5), 405–413.

https://doi.org/10.1111/j.1365-2982.2012.01906.x

Bielemann, R. M., Santos Motta, J. V., Minten, G. C., Horta, B. L., & Gigante, D. P. (2015). Consumption of ultra-processed foods and their impact on the diet of young adults. Revista de Saude Publica, 49. https://doi.org/10.1590/S0034-8910.2015049005572

Collins, S. M., & Bercik, P. (2009). The Relationship Between Intestinal Microbiota and the Central Nervous System in Normal Gastrointestinal Function and Disease. Gastroenterology, 136(6), 2003–2014.

https://doi.org/10.1053/j.gastro.2009.01.075

Costa-Font, M., Gil, J. M., & Traill, W. B. (2008). Consumer acceptance, valuation of and attitudes towards genetically modified food: Review and implications for food policy. Food Policy, 33(2), 99–111.

https://doi.org/10.1016/j.foodpol.2007.07.002

Cummings, J. R., Mamtora, T., & Tomiyama, A. J. (2019). Non-food rewards and highly processed food intake in everyday life. Appetite, 142(May), 104355. https://doi.org/10.1016/j.appet.2019.104355

Dash, S., Clarke, G., Berk, M., & Jacka, F. N. (2015). The gut microbiome and diet in psychiatry: Focus on depression. Current Opinion in Psychiatry, 28(1), 1–6. https://doi.org/10.1097/YCO.0000000000000117