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Appetite 109 (2017) 100e107

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Appetite

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Eating behaviour of university students in Germany: Dietary intake, barriers to healthy eating and changes in eating behaviour since the time of matriculation

Jennifer Hilger a, b, *, Adrian Loerbroks b, Katharina Diehl a

a Mannheim Institute of Public Health, Social and Preventive Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany b Institute of Occupational Medicine and Social Medicine, Centre for Health and Society, Faculty of Medicine, University of Düsseldorf, Düsseldorf, Germany

a r t i c l e i n f o

Article history: Received 8 June 2016 Received in revised form 13 October 2016 Accepted 11 November 2016 Available online 15 November 2016

Keywords: Nutrition Healthy eating University students Barriers Germany

* Corresponding author. Mannheim Institute of Pub Preventive Medicine, Medical Faculty Mannheim, Hei Ludolf-Krehl-Straße 7-11, D-68167 Mannheim, Germa

E-mail address: Jennifer.Hilger@medma.uni-heide

http://dx.doi.org/10.1016/j.appet.2016.11.016 0195-6663/© 2016 Elsevier Ltd. All rights reserved.

a b s t r a c t

A healthy diet plays a key role in preventing obesity and non-communicable diseases such as type 2 diabetes. This is true for all age groups, including young adults. While unhealthy eating habits among young adults, in particular university students, have been identified in former studies, this group has been neglected in existing health promotion strategies. Our aim was to explore baseline dietary intake, common barriers to healthy eating, and changes in eating behaviour among university students since the time of matriculation. We used data from the quantitative part of the Nutrition and Physical Activity Study (NuPhA), a cross-sectional online survey (data collection: 2014/10/31e2015/01/15). Students were recruited from all over Germany. Overall, 689 university students (30.5% male; mean age: 22.69) from more than 40 universities across Germany participated. We found that there is room for improvement with regard to the consumption of specific food groups, for example, fruits and vegetables. The main barriers to healthy eating were lack of time due to studies, lack of healthy meals at the university canteen, and high prices of healthy foods. Cluster analysis revealed that barriers to healthy eating might affect only specific subgroups, for instance freshmen. Changes in eating behaviour since matriculation were found in the consumption of meat, fish, and regular meals. Future qualitative studies may help to explore why university students change their eating behaviour since the time of matriculation. Such knowledge is necessary to inform health promotion strategies in the university setting.

© 2016 Elsevier Ltd. All rights reserved.

1. Introduction

A healthy diet is widely recognized as a main factor in pre- venting obesity and non-communicable diseases such as type 2 diabetes and cardiovascular disease (World Health Organisation, 2016). Therefore, following a healthy diet should be promoted across all age groups. According to the WHO (2016) a healthy diet should include, for instance, high consumption of fruits, vegetables, and whole grains, in addition to low consumption of saturated fats, salt, and refined carbohydrates. The transition from adolescence to young adulthood may be a particularly important time for health promotion strategies, including the promotion of healthy eating, because many health behaviours are developed and established

lic Health, Social and delberg University, ny. lberg.de (J. Hilger).

during this period (Nelson, Story, Larson, Neumark-Sztainer, & Lytle, 2008; Poobalan, Aucott, Clarke, & Smith, 2014). However, current studies indicate that poor dietary habits seem to be com- mon among this age group. Former studies report, for example, high levels of fast food consumption, low intake of fruits and veg- etables, and breakfast skipping (N. Larson, Laska, Story, & Neumark- Sztainer, 2012; Niemeier, Raynor, Lloyd-Richardson, Rogers, & Wing, 2006). Furthermore, excessive weight gain has been observed among young adults (Gordon-Larsen, Adair, Nelson, & Popkin, 2004; Mensink, Schienkiewitz, Haftenberger, Lampert, Ziese, & Scheidt-Nave, 2013; Nelson Laska, Larson, Neumark- Sztainer, & Story, 2010), particularly university students (Mihalopoulos, Auinger, & Klein, 2008; Racette, Deusinger, Strube, Highstein, & Deusinger, 2005).

The transition from school to university coincides changing living arrangements, which might also result in a reorientation of eating behaviours (El Ansari, Stock, & Mikolajczyk, 2012). However, only a few studies have focused on potential changes in eating

J. Hilger et al. / Appetite 109 (2017) 100e107 101

behaviour since matriculation (Lupi, Bagordo, Stefanati, Grassi, Piccinni, Bergamini, et al., 2015; Nelson Laska et al., 2010; Wengreen & Moncur, 2009). In addition, little is known about the reasons which may prevent university students from following a healthy diet. Thus, we aimed to a) describe the baseline dietary intake of university students, b) identify potential barriers to healthy eating and c) explore potential changes in their eating behaviour since the time of matriculation.

2. Material and methods

2.1. Study design and sample

The analyses are based on data from the quantitative part of the Nutrition and Physical Activity Study (NuPhA), a cross-sectional online survey among university students conducted across Ger- many from October 2014 to January 2015. University students were recruited via fliers, mailing lists, social networks, and advertising the study during classes and lectures. Students received informa- tion on the study aims and data security regulations; they were informed that participation was voluntary and withdrawal from the study possible at any point in time. Participants provided informed consent by selecting the “agreement button” during the online survey, which then directed them to the first question of the survey. As an incentive we randomly awarded gift certificates to 40 stu- dents who completed the online survey. The study was approved by the Medical Ethics Committee of the Medical Faculty Mannheim, Heidelberg University (2013-634N-MA).

2.2. Measures

2.2.1. Dietary assessment Dietary intake was assessed using a brief food frequency ques-

tionnaire (FFQ). The original FFQ consisted of 17 food items and was developed by the Max Rubner Institute (2016), the German Federal Research Institute of Nutrition and Food. The FFQ was originally designed as a parental questionnaire to evaluate the dietary intake of children. We slightly adapted this FFQ to fit the population of young adults. Our final FFQ consisted of 22 food items, and the frequency of consumption was assessed by the following response categories: never, less than once a week, once a week, two to three times a week, four to five times a week, six to seven times a week, or several times a day. For further analyses we grouped the categories once a week and two to three times a week, as well as the categories four to five times a week and six to seven times a week. Based on a food pyramid developed by the German state-funded Agency for Consumer Information (Koelsch & Brueggemann, 2012; von Ruesten, Illner, Buijsse, Heidemann, & Boeing, 2010), the 22 food items were grouped into six food groups: 1. Vegetables, salad; 2. Fruits; 3. Bread, grains, side dishes; 4. Dairy products; 5. Meat, sausages, fish, eggs; 6. Sweets and snacks.

2.2.2. Assessment of barriers to healthy eating We used a questionnaire applied and validated in previous

research among adolescents and young adults (Andajani-Sutjahjo, Ball, Warren, Inglis, & Crawford, 2004; Musaiger, Al-Mannai, Tayyem, Al-Lalla, Ali, Kalam, et al., 2014; Musaiger, Al-Kandari, Al- Mannai, Al-Faraj, Bouriki, Shehab, et al., 2013) to identify potential barriers to healthy eating. The questionnaire was translated into German and slightly modified by adapting and adding items to fit the population of university students. Participants could choose one of the following response options for each of the 22 barrier items: “Not a barrier, a somewhat important barrier, a very important barrier”. For further analysis, we combined the two categories “important barrier” and “very important barrier” into

one barrier category based on sensitivity analysis.

2.2.3. Assessment of changes in eating behaviour Changes in eating behaviour since matriculation were examined

by asking, “Has your eating behaviour changed since matricula- tion?” (response categories: yes/no/unknown). A second question enquired after changes in the frequency of food consumption: “Since matriculation, do you consume: more, less, or as many as before of the following foods”. We assessed changes in the con- sumption of ten food items, eight of which were also included in the FFQ and two additional ones (total calories; regular meals). These questions were adapted from the Campbell Survey on Well- Being in Canada (Canadian Fitness and Lifestyle Research Institute, 1988).

2.3. Data analysis

Descriptive analyses like frequency distributions and cross classifications were performed to characterise the sample's base- line dietary intake, barriers to a healthy eating, and changes in eating behaviour since matriculation. In addition, we conducted Chi2 tests to explore if eating behaviour differs between male and female university students. To combine similar barriers to healthy eating into one dimension, we conducted an explorative factor analysis using SPSS FACTOR with Varimax rotation. After excluding eight of the primarily 22 barrier items with factor loadings <0.6, we obtained a five-factor solution (Kaiser-Meyer-Olkin-Measure: 0.685; Bartlett-Test: <0.001; supplement 1): factor 1: Personal motivation/attitudes; factor 2: Lack of knowledge/information; factor 3: Environmental barriers; factor 4: Lack of social support; factor 5: Lack of time. The five factors identified were subsequently incorporated in a hierarchical cluster analysis (Ward's method, squared Euclidian distance). The cluster analysis was conducted to group university students affected by the same barriers to healthy eating. To detect differences between the clusters identified, Chi2

tests were applied to discrete variables and Kruskal-Wallis H test to continuous variables.

All statistical analyses were performed using IBM SPSS Statistics 22 (IBM Corporation, Armonk, USA). The pre-defined level of sig- nificance for all tests was p < 0.05.

3. Results

The sample included 689 university students (30.5% male; Table 1) aged 16e29 years from more than 40 universities across Germany. Approximately 35% of them were undergraduate stu- dents in the first to third semesters. The majority of the students (74.2%) had left their hometown to enrol at university.

3.1. Baseline dietary intake

A minority of the students reported eating cooked vegetables (3.2%) as well as raw vegetables and salad (3.6%) several times a day. Fresh fruits were consumed by 26.9% of students several times a day (Fig. 1). Brown bread was eaten by 10.3% less than once a week. While 18.0% of the students reported that they never ate red meat,12.6% stated that they consumed it 4e7 times per week. More than half of the students (55.4%) ate poultry 1e3 times a week, and 43.1% consumed fish 1e3 times a week. Chocolate was eaten by 4.5% several times per day. More than half (52.5%) of the university students reported consuming fast food less than once a week, and a minority (1.9%) reported eating fast food frequently (4e7 times a week).

Gender differences in the frequency of food consumption were also identified: While females were more likely to consume cooked

Table 1 Characteristics of university students in the NuPhA Study (n ¼ 689).

Characteristics n (%)/m (SD)

Gender Male 210 (30.5) Female 479 (69.5)

Age 22.69 (2.73) BMI 22.14 (2.93) Migration background 96 (13.9) Number of semesters studied 1e3 semesters 234 (34.9) 4e5 semesters 127 (18.9) 6e9 semesters 187 (27.9) 10 þ semesters 123 (18.3)

Subject of studies Medicine/health care 369 (53.6) Political sciences/social sciences 86 (12.5) Law/business sciences 46 (6.7) Sport sciences 42 (6.2) Other subjects 146 (21.2)

Marital status Married 28 (4.1) In a partnership 360 (52.2) Not in a partnership 301 (43.7)

Left hometown to start studies 511 (74.2) Money available per month 766.69 (516.54) Getting support from parents 585 (85.7) Getting support from the German Federal Assistance Act 127 (18.6) Having a side job 426 (62.4)

m: mean; SD: standard deviation; BMI: body mass index.

J. Hilger et al. / Appetite 109 (2017) 100e107102

vegetables (p ¼ 0.01), salad/raw vegetables, fresh fruits, and curd-/ cream cheese/yoghurt (all: p < 0.001), consumption of red meat, poultry, sausages, fish (all: p < 0.001), and hard/soft cheeses (p ¼ 0.02) was more common among male students. In addition, males ate fast food (p < 0.001) and side dishes like pasta/rice (p ¼ 0.01) and fried potatoes/chips (p < 0.001) more frequently than females. Gender differences were also seen in the frequency of chocolate consumption, with females consuming chocolate more often than males (p < 0.001). Within the total sample, 15.8% re- ported to adhere to a vegetarian diet (13.8% vegetarians, 2.0% vegans). Significantly more females (19.6%) than males (7.1%) re- ported to be vegetarians (p < 0.001).

The majority of university students (74.3%) reported regularly eating breakfast on weekdays (4e5 times), while 8.7% stated they seldom/never ate breakfast on weekdays. Most students (77.9%) had breakfast on their own. Lunch was eaten by 73.6% on weekdays, and 66.6% reported having lunch together with colleagues/friends. More than half of the university students (51.8%) reported having lunch at the university canteen. As the main reasons for eating there, students mentioned eating together with fellow students/ friends (78.4%), saving time (75.1%), proximity to university (74.8%), and wanting a warm meal (58.0%). During the week, 83.0% of stu- dents ate dinner on 4e5 days and slightly more than half (50.5%) reported having dinner on their own.

3.2. Barriers to healthy eating

The majority of the university students (90.9%) reported trying to eat healthily, including 92.3% of female and 87.6% of male stu- dents. Overall, 66.1% found it easy to follow a healthy diet, however significantly more females (69.2%) than males (58.7%; p ¼ 0.01) agreed on this.

The two most important barriers to healthy eating were lack of time to prepare a healthy meal due to university commitments and lack of healthy meals at the university canteen (Fig. 2). Gender differences were observed for several barriers with significantly more males (very important barrier 3.3%; important barrier 21.0%)

than females (very important barrier 2.5%; important barrier: 12.3%) reporting a lack of motivation (p ¼ 0.010). In addition, more males (very important barrier: 5.8%; important barrier: 18.6%) than females (very important barrier: 2.7%, important barrier: 7.4%) stated that they did not enjoy eating healthy food (p ¼ 0.001). Fe- males mentioned “healthy food doesn't taste good” as a barrier to healthy eating (very important: 2.1%; important: 8.6%) less frequently than males did (very important: 3.8%, important: 17.7%; p ¼ 0.001). Males reported a lack of time due to hobbies and other interests (very important: 4.8%, important: 25.4%) as a reason for not following a healthy diet more often than females did (very important: 3.5%, important: 17.7%; p ¼ 0.04).

The cluster analysis resulted in five barrier clusters to healthy eating which we defined as follows: Cluster 1: Non-supported/non- motivated; Cluster 2: Lack of time; Cluster 3: Lack of knowledge/ information; Cluster 4: No barriers; Cluster 5: Environmental bar- riers. We did not find gender differences among the five clusters identified (Table 2). Students in the “Lack of knowledge/informa- tion” cluster were slightly younger than those in the four other clusters. More than 90% of students in clusters 2 (“Lack of time”), 4 (“No barriers”) and 5 (“Environmental barriers”) “tried to follow” a healthy diet but this was true for only 81.8% in the “Non-supported/ non-motivated” cluster and for 79.5% in the “Lack of knowledge/ information” cluster. In addition, fewer students in the latter clus- ters reported “finding it easy” to follow a healthy diet (41.7% and 39.7%, respectively) compared to those in the “No barriers” cluster (91.2%). Clusters did not differ with regard to meal patterns, such as having regular breakfast or having lunch at the university canteen. However, fewer than 40% of students in clusters 1 (“Non-sup- ported/non-motivated”), 2 (“Lack of time”), and 4 (“No barriers”) mentioned “lack of cooking skills/cooking is too time consuming” as reason for eating at the university canteen compared to 58.3% in the “Lack of knowledge/information” cluster and 59.4% in the ”Environmental barriers” cluster. In the latter group, more than 80% of students reported having left their hometown to start their studies. Within this group, the majority (73.2%) mentioned that their eating behaviour had changed since entering university. Clusters did not differ with regard to the amount of money available per month or the level of financial support from parents or the German Federal Training Assistance Act. However, more than 60% of students in the “Non-supported/non-motivated” cluster (73.5%) and in the “Lack of knowledge/information” cluster (63.0%) re- ported having a side job.

3.3. Changes in eating behaviour since matriculation

Most of the students (65.3%) reported that their eating behav- iour had changed since matriculation, with more males (69.0%) than females (63.7%; p ¼ 0.35) indicating this. In addition, more students who had moved away from home to enrol at university (70.6%) reported a change in eating behaviour than those who had stayed in their hometown (50.0%; p < 0.001).

Considering changes in the consumption of specific food groups, 40.5% of the university students reported eating more vegetables and 38.2% reported eating more fruits since matriculation (Table 3). On the other hand students reported consuming less red meat (53.5%), poultry (43.4%), and fish (37.3%). More than half of the university students (55.2%) reported that they no longer eat as many regular meals as before matriculation. Gender differences for changes in the consumption of specific food groups since matric- ulation were found for poultry, fish, fast food, and sugar/sweets (Table 3).

Fig. 1. Baseline dietary intake of university students in Germany (n ¼ 689; NuPhA Study). Reading support: The single food items are grouped into six food groups based on the German Food Pyramid developed by the German state-founded Agency for Consumer In- formation (von Ruesten et al., 2010).

J. Hilger et al. / Appetite 109 (2017) 100e107 103

Fig. 2. The top 15 barriers to healthy eating reported by university students in Germany (n ¼ 689; NuPhA Study). Reading support: sorted by: no barrier; * Indicates gender differences (determined by Chi2-tests; p < 0.05).

Table 2 Characteristics of the five barriers-to-healthy-eating clusters of students at German universities (NuPhA Study).

Cluster 1 “Non-supported/non- motivated”

Cluster 2 “Lack of time”

Cluster 3 “Lack of knowledge/ information”

Cluster 4 “No barriers”

Cluster 5 “Environmental barriers”

p value

n (%) 170 (25.5) 216 (32.4) 73 (10.9) 152 (22.8) 56 (8.4) Female [n (%)] 112 (65.9) 160 (74.1) 51 (69.9) 106 (69.7) 35 (62.5) NS Age [m (SD)] 22.7 (2.7) 22.6 (2.6) 21.8 (2.6) 23.2 (2.9) 22.7 (2.4) 0.012 BMI [m (SD)] 22.7 (3.2) 21.8 (2.5) 22.9 (3.2) 21.7 (2.9) 22.3 (2.9) 0.001 Number of semesters studied [m (SD)] 5.9 (3.4) 6.1 (3.6) 4.7 (3.6) 6.1 (3.6) 6.3 (3.5) 0.027 Migration background [n (%)] 25 (14.7) 33 (15.3) 9 (12.3) 12 (7.9) 13 (23.2) NS Try to follow a healthy diet [n (%)] 139 (81.8) 209 (96.8) 58 (79.5) 147 (96.7) 51 (91.1) <0.001 Find it easy to follow a healthy diet [n (%)] 58 (41.7) 154 (73.7) 23 (39.7) 134 (91.2) 32 (62.7) <0.001 Changes in eating behaviour since matriculation [n (%)] 110 (64.7) 151 (69.9) 46 (63.0) 89 (58.1) 41 (73.2) NS Have lunch at the university canteen [n (%)] 87 (51.2) 120 (55.6) 36 (49.3) 69 (45.4) 32 (57.1) NS Have a partner [n (%)] 100 (58.8) 121 (56.0) 41 (56.2) 87 (57.2) 28 (50.0) NS Left hometown to enrol at university [n (%)] 122 (71.8) 164 (75.9) 52 (71.2) 110 (72.4) 46 (82.1) NS Money available per month [m (SD)] 756.2 (440.7) 792.3 (726.5) 680.4 (381.5) 770.1 (314.8) 756.9 (363.0) NS Receive financial support from parents [n (%)] 147 (86.5) 184 (85.2) 65 (89.0) 127 (85.8) 44 (81.5) NS Receive financial support from Federal Training Assistance Act [n (%)] 31 (18.2) 43 (19.9) 13 (17.8) 25 (16.9) 11 (20.4) NS Have a side job [n (%)] 125 (73.5) 129 (59.7) 46 (63.0) 86 (58.1) 27 (50.0) 0.006

n: number of cases; m: mean; SD: standard deviation; BMI: body mass index; Kruskal-Wallis H tests were applied to: age, BMI, number of semesters studied, money available per month; Chi2 tests were applied to: all other variables.

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4. Discussion

In our nationwide NuPhA Study we found that there is room for improvement with regard to the intake of specific food groups like

fruits and vegetables. The main barriers to healthy eating were iden- tified as lack of time due to studies, lack of healthy food at the uni- versitycanteen,andhighcostsofhealthyfoods.Inaddition,mostof the students reported changes in eating behaviour since matriculation.

Table 3 Changes in food consumption since matriculation among university students at German universities (NuPhA Study).

Change in food consumption

Total sample (n ¼ 689) Males (n ¼ 210) Females (n ¼ 479) P value Food group No change % Increased% Decreased% No change % Increased % Decreased% No change % Increase % Decrease %

Vegetables 42.7c 40.5c 16.8a 42.9c 40.5c 16.6a 42.6c 40.5c 16.9a 1.00 Fruits 44.8c 38.2c 17.0a 44.8c 35.7c 19.0a 44.6c 39.3c 16.1a 0.53 Whole grain products 46.7c 38.4c 14.8a 44.8c 44.2c 11.0a 47.6c 35.8c 16.6a 0.05 Milk/dairy products 53.1d 27.8b 19.1a 53.8d 29.5b 16.7a 52.8d 27.0b 20.1b 0.53 Red meat 40.0c 6.4a 53.6d 40.0c 9.0a 51.0d 40.0c 5.3a 54.7d 0.17 Poultry 37.9c 19.7b 42.4c 34.2b 32.9b 32.9b 39.5c 13.9a 46.6c <0.001 Fish 41.6c 21.1b 37.3c 35.4c 30.1b 34.4b 44.3c 17.1a 38.6c 0.001 Sugar/Sweets 43.6c 25.4b 31.0b 35.9c 18.2a 45.9c 47.0c 28.6b 24.4b <0.001 Fast Food 40.6c 27.2b 32.2b 34.8b 33.8b 31.4b 43.2c 24.3b 32.5b 0.02 Total calories 51.8d 22.0b 26.1b 52.2d 26.5b 21.3b 51.7d 20.0b 28.3b 0.64 Regular meals 34.2b 10.7a 55.2d 35.4c 14.4a 50.2d 33.6b 9.0a 57.4d 0.07

Gender differences were determined by Chi2 tests. a <20.0%. b 20.0%e34.9%. c 35.0%e49.9%. d >50.0%.

J. Hilger et al. / Appetite 109 (2017) 100e107 105

According to the WHO (2016) a healthy diet includes the con- sumption of at least five portions of fruits and vegetables a day. In relation to this recommendation the intake of fruits and vegetables in our sample was quite low with less than 30% of all students reporting to eat fruit and vegetables several times a day. This finding is in line with other studies focusing on university students from various countries, including the USA (Yahia, Wang, Rapley, & Dey, 2015), Spain (Moreno-Gomez, Romaguera-Bosch, Tauler- Riera, Bennasar-Veny, Pericas-Beltran, Martinez-Andreu, et al., 2012), Italy (Lupi, Bagordo, Stefanati, Grassi, Piccinni, Bergamini, et al., 2015; Teleman, de Waure, Soffiani, Poscia, & Di Pietro, 2015), and Germany (Keller, Maddock, Hannover, Thyrian, & Basler, 2008). Making fruits and vegetables more accessible and appealing to students may be one strategy for increasing con- sumption among students.

Furthermore, we found gender differences in the consumption frequency of several food groups. In accordance with other studies (Lupi et al., 2015; Mikolajczyk, El Ansari, & Maxwell, 2009), males consumed in comparison to females fast food and meat products more often and fruits and vegetables less often. Reasons for such gender differences could be the generally higher health awareness (Stock, Wille, & Kramer, 2001; Wardle & Steptoe, 1991), better nutrition knowledge (Kresic, Kendel Jovanovic, Pavicic Zezel, Cvijanovic, & Ivezic, 2009), and better knowledge about what constitutes a “healthy diet” (Yahia et al., 2015) among females. A further explanation for the gender differences might be that fe- males in general are more concerned about their body weight than males (Salameh, Jomaa, Issa, Farhat, Salame, Zeidan, et al., 2014; Wardle, Haase, & Steptoe, 2006; Yahia et al., 2015). Thus, they may follow healthier eating patterns to stay slim. However, the females within our sample reported eating chocolate more frequently than the males did. Previous studies also reported that female students consumed sweet foods more frequently than their male counterparts (El Ansari, Adetunji, & Oskrochi, 2014; Mikolajczyk et al., 2009; Yahia et al., 2015). They found an associ- ation between such eating habits and higher levels of perceived stress in female students (El Ansari et al., 2014; Mikolajczyk et al., 2009). Possibly female students may eat sweet foods, especially chocolate, as a strategy to better cope with stress. Also in line with earlier studies (Mikolajczyk et al., 2009; Yahia et al., 2015), we found that female students ate fish less frequently than male stu- dents. This may be due to the higher proportion of females in our sample reporting to be vegetarians.

We identified the lack of time due to studies as one main barrier to healthy eating (Musaiger et al., 2014; Pelletier & Laska, 2012). Therefore, universities should think about strategies to overcome this important barrier like providing time management courses (Pelletier & Laska, 2012).

The perceived lack of healthy foods at the university canteen was stated as another important barrier to following a healthy diet. Intervention studies focusing on university canteens showed that providing higher food quality and greater food variety as well as reduced prices resulted in healthier eating habits (Davis, Cullen, Watson, Konarik, & Radcliffe, 2009; Guagliardo, Lions, Darmon, & Verger, 2011; Michels, Bloom, Riccardi, Rosner, & Willett, 2008). Given that more than 50% of our study sample reported having lunch regularly at the university canteen, offering healthy and low- priced meals may be a promising strategy to ensure healthy eating within the university setting.

According to our cluster analysis, most barriers to healthy eating seem to affect only specific subgroups within our sample of uni- versity students. Students in the “Lack of knowledge/information” cluster, which showed the highest proportion of students reporting difficulties in following a healthy diet, were younger and at the beginning of their studies compared to students within the other four clusters. An explanation for their difficulties might be their shorter period of independence from parents and family. Previous studies have observed an association between the decreased involvement of children and adolescents in making family meals and the current lack in cooking skills among young adults (Nelson et al., 2008). Moreover, studies have found that food preparation skills increase diet quality among young adults (Thorpe, Kestin, Riddell, Keast, & McNaughton, 2014) but also enable healthier eating habits during later life (Laska, Larson, Neumark-Sztainer, & Story, 2012). Therefore, providing nutrition information and offer- ing cooking classes within the university setting could be useful interventions to improve the nutrition knowledge and food prep- aration skills among university students.

The eating habits of students in the “Environmental barriers” cluster seemed to be affected by the opening hours of nearby grocery stores and by the lack of healthy food options in these stores. A review revealed that better access to neighborhood gro- cery stores was associated with better diet quality in adults (N. I. Larson, Story, & Nelson, 2009). In addition, individuals living in areas with a higher number of grocery stores offering healthy foods were more likely to buy a greater variety of fruits and vegetables

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(Mason, Bentley, & Kavanagh, 2013). Studies among university students indicate that on- or off-campus living seems to influence food choices, with off-campus students having greater difficulties in following a healthy diet (Kapinos & Yakusheva, 2011; Small, Bailey-Davis, Morgan, & Maggs, 2013). As a useful strategy Small et al. (2013) propose partnerships between universities and the local communities, for example, establishing farmers’ markets next to university campuses. In addition, they suggest providing trans- portation to and from local grocery stores to help students with their shopping. Although on-campus living is not common in Germany, the proposed strategies may help German university students overcome such environmental barriers.

Additionally, more than 80% of the individuals within the “Environmental barriers” cluster moved away from home to enrol at the university and 73% reported a change in eating behaviour since matriculation. Previous studies showed that changes in eating habits were most pronounced in students living away from home (El Ansari et al., 2012; Lupi et al., 2015; Papadaki, Hondros, J, & Kapsokefalou, 2007). One reason might be that these students are entirely responsible for food shopping and meal planning purposes for the first time in their lives (El Ansari et al., 2012; Lupi et al., 2015; Papadaki et al., 2007). In addition, they may not know where to buy healthy food close to their new place of residence.

Students belonging to the “No barriers” cluster seemed not to be affected by any barriers to healthy eating. More than 90% of stu- dents within that cluster reported finding it easy to follow a healthy diet. As the mean age of this group was slightly higher compared to the other clusters, this may indicate that students learn to cope with barriers over time. Thus, interventions that aim to enable university students to follow a healthy diet should start immedi- ately after university enrolment.

In addition, most of the students in our sample reported changes in eating behaviour since matriculation, which is in line with pre- vious research (Lupi et al., 2015). Changes in dietary intake were particularly found for meat and fish. The majority of students re- ported a decreased consumption of these food groups. Guagliardo et al. (2011) stated financial reasons as a possible explanation for a lower consumption of meat, fish, fruits, and vegetables. Although 46% of our sample mentioned high prices as a barrier to healthy eating, only a minority reported eating fewer fruits and vegetables. A reason for this might be that fruits, vegetables, meat, and fish are less expensive in Germany compared to other countries. Therefore, the decreased consumption of meat and fish might at least partly reflect the current trend in following a vegetarian or vegan diet (Leitzmann, 2014; Vegetarierbund Deutschland, 2016).

4.1. Strengths and limitations

Our study is, to the best of our knowledge, the first study to focus on eating behaviour and on barriers to healthy eating in a cross-disciplinary sample of students from different universities across Germany. Besides providing information on baseline dietary intake, we present data on the changes in eating behaviour since matriculation. Furthermore, the large sample size enabled us to conduct comprehensive statistical procedures like cluster analysis. Thus, we were able to identify specific target groups for health promotion strategies within the whole sample of university stu- dents. Therefore, our study provides valuable data on eating behaviour within young adults and the potential changes in this behaviour occurring since the time of matriculation. Nevertheless, our study has some limitations. First of all, due to the cross- sectional design of our study, no causal relationships can be drawn from our data. In addition, although the NuPhA Study recruited university students from across Germany, we cannot rule out the possibility of a participation bias, which may limit the

generalizability of our results. Furthermore, due to the self- reported variables, reporting bias and recall bias may have occurred.

5. Conclusion

The results of our study indicate that changes in eating behav- iour occur among university students since the time of matricula- tion. However, barriers to healthy eating may differ among university students and seem to affect only specific subgroups, for instance freshmen. Qualitative studies may be helpful to further explore the motives that shape the changes in eating behaviour since the time of matriculation. Such knowledge is necessary to inform health promotion strategies that enable healthy eating in the university setting.

Financial support

The NuPhA Study is partially funded by the “Institut Danone Ern€ahrung für Gesundheit e.V.”, Haar, Germany (project no: 2014/ 01). The funding organisation had no role in the design, analysis and interpretation of the data; in the writing of this manuscript; and to submit the manuscript for publication.

Conflicts of interest

none.

Authorship

Author contributions were as follows: J.H. and K.D. defined the conception and design of the study. J.H. conducted the statistical analysis. J.H. and K.D. wrote the manuscript. A.L. carefully reviewed the manuscript. All authors read and approved the final manu- script, as well as contributing to the interpretation of the findings.

Acknowledgements

We thank all university students that participated in the quan- titative part of the NuPhA Study.

Appendix A. Supplementary data

Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.appet.2016.11.016.

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