The aim of this study is to identify dietary patterns within Jordan University students. Three dietary patterns were identified named: snacking, healthy and the accessible. Dietary habits at this life stage are influential for quality of life and future health. The number of studies that identified the dietary patterns of the university students is limited; the approach of identifying dietary intake patterns instead of food or food group intakes is still little investigated. Most of the studies identified 3–5 dietary patterns in this group of population [16–19, 32, 33]; moreover, these patterns received different names including: snacking, Westernized, processed, unhealthy traditional, convenience, the dairy products pattern, and traditional Westernized. The differences in identified patterns between different studies and settings may be due to many factors including cultural food variations; the availability and affordability of certain foods; and nutrition transition status of the countries. In addition to, age gender, nutrition and health awareness of the studied groups.
In this study, “Snacking” dietary pattern comprised the highest percentage of variance (13.2%), while, the total dietary intake variance percentage of the three patterns was (23.3%), this pattern is commonly defined by high intakes of sugar, fat and processed products. These findings were consistent with the results of Sprake, et al [16] in five UK universities, where the total variance explained by four components was (21.7%). It should be pointed out that the variance explained by the components is set by the number of components that are selected to be retained by the investigator [5, 31, 34].
The second dietary pattern identified in the current study was “healthy”. A dietary pattern was similar to this one has already been observed in a cross sectional study on healthcare professionals and students from the University of Guadalajara (Mexico) accounted for 8.78% of the variance [33]. Whereas, this pattern accounted for 5.9% of variance in the current study.
The differences between the food items in the patterns that have been identified in our study and patterns from the literature come from the fact that factor analysis is a data driven analysis method; which means that the amount of food groups/items that you enter will affect the item in the patterns that will be retained [31, 34, 35].
The third patterns which named as “Accessible” pattern, it enclosed some food items that were on the snacking pattern as well as some items from the healthy pattern.
We have found some associations between the dietary patterns and some lifestyle and socio-demographic factors. Among the three dietary patterns identified for the university students, the snacking pattern was significantly associated with BMI (obese or underweight) as well as smoking and not being physically active. Other studies have also found that a high fat and sugar pattern is also linked with unhealthy lifestyle choices [18, 36, 37]. On the other hand, the healthy pattern was associated with physical activity and considering breakfast as the main meal of the day, as well as having more than three meals per day. This finding supports that the dietary pattern and lifestyle choices go hand in hand [33]. As for the traditional pattern it had a significant association with consuming three or more meals per day.
In our study, males had higher factor scores for the healthy pattern, which could be because of the higher number of males that are physically active compared to females. Contrary to other studies [16, 18, 37], Females were always linked to healthier lifestyle and eating habits as they were more concerned about dieting and physical activity in order to achieve certain a body image desired [38]. Some factors may have played a role in the BMI distribution in our study sample as the highest percentage was normal weight individuals (65.3%). The participation in the study was voluntary among the students, so obese/overweight students might have refrained from participating because of the fear of stigma or not wanting to be weighed [39].
As most of our students sample lived with their families (90.1%), their dietary choices may be influenced by that, as the living situation has shown direct effect on the dietary choices to university students in our study as well as another study in our country [26]. In the Middle Eastern region, young adults still depend in their families financially. So, the foods they eat are usually the most convenient to them, whether it was the food available at home or it was fast /junk food. So the eating pattern may also reflect the eating habits of the household to some extent [15]. Other than that, the food options available at the university campus do not offer that much variety for the students to choose from. A lot of factors play a role in the choices of university students as they are in a provisional phase of their life and they are easily influenced by others and what the media reflects on them [12, 14].
Strength and Limitations
The present study has a number of limitations and strengths that should be addressed. Studying dietary patterns gives an insight about the whole diet instead of focusing on single nutrient which made it easier to interpret with different factors. It’s also important to mention that the dietary data collection method through the food frequency questionnaire (FFQ) was optimal for this study, as it allowed covering a longer period of time which gave us a broader idea of food intake of the study sample. For the anthropometric measurements (weight &height) we relied on the measured data instead of the reported one which adds to the accuracy of the data.
The cross-sectional design of the study allows the examination of associations rather than causations, which makes it unclear if obesity is a result of following unhealthy pattern or they follow an unhealthy pattern because of their obesity. Also, the food frequency questionnaire (FFQ) relies on memory hence the dietary intake information might not be accurate.
The analysis method is data driven so the patterns we identified are specific to the study populations; so different data generates different patterns. The results of this study may not be representative of all university students in Jordan because we included only one university for the study.