Objectives Research shows that students in healthcare fields have distorted perceptions of their bodies, specifically regarding their weight status. Nutrition majors are important to consider, given their future careers require them to assess others’ weight statuses and provide relevant diet recommendations. The main aims of this secondary analysis were to compare accuracy of nutrition versus non-nutrition majors’ body weight perception to their measured body mass index (BMI) and body fat percentage (BFP). It was hypothesized that nutrition majors will more accurately classify their weight relative to their BMI and BFP compared to non-nutrition majors due to their knowledge of weight classifications. Methods In this cross-sectional study, 188 non-nutrition (77% female; BMI 24.14 ± 5.46; BFP 26.30 ± 9.70) and 108 nutrition (83% female; BMI 23.78 ± 3.75; BFP 25.45 ± 8.39) majors enrolled in a general nutrition class and completed a nutrition assessment survey that included the multiple-choice question: “How would YOU describe your current weight?”. Categories were underweight, healthy weight, or overweight. Height was measured by a calibrated stadiometer. Weight and body composition were assessed by In-Body 770. BMI and BFP were categorized as underweight, healthy weight, or overweight according to the In-Body reference guidelines. Difference in accuracy of nutrition versus non-nutrition majors’ body weight perceptions were analyzed by independent t-tests. Data are expressed as means ± standard deviations. Results Of the 296 students, 28% misperceived their weight status relative to BMI and 40% misperceived their weight status relative to BFP. Of the 28%, 55 students perceived their weight as lower than (30% nutrition) and 25 students perceived their weight as higher than (52% nutrition) their measured BMI. Of the 40%, 86 students perceived their weight as lower than (24% nutrition) and 31 students perceived their weight as higher than (48% nutrition) their measured BFP. Nutrition majors had more accurate perceptions of their weight status relative to measured BFP than non-majors (−0.06 ± 0.58; −.27 ± 0.62; P = 0.004). Conclusions When perceptions were inaccurate, most students perceived themselves as a healthier weight than their measured BMI and BFP indicated. Nutrition majors’ perceptions relative to BFP were more accurate than non-majors. Funding Sources None.
Objectives Young adults tend to consume western diets with low microbe-accessible carbohydrates (MACs), which are fermentable carbohydrates that may reduce the risk of developing non-communicable diseases. The importance of dietary fiber (only one type of MAC) in the prevention of chronic diseases led to recommendations for increasing fiber intake. However, a reference to other MACs such as resistant starches, non-starch polysaccharides, polyols (lactitol, sorbitol, etc.), and oligosaccharides (fructo-oligosaccharides, etc.) is still lacking and their relationship with diet quality is far less understood. The healthy eating index (HEI) score is a measure of diet quality, independent of quantity, and is useful to assess compliance with U.S. Dietary Guidelines for Americans. The primary aim of this study was to determine the MACs consumption in healthy US college students and their association with dietary quality as indicated by the HEI-2015. Methods For this cross-sectional study, data were collected from consenting students (≥ 18years old) in an introductory nutrition course (n = 592, age (mean ± standard deviation) 19.5 ± 3.5; 83.7% white; 78.4% female). Dietary intake was measured via a web-based dietary history questionnaire (DHQ-II), which is able to quantify the consumption of MAC's and subclasses such as polyols and soluble dietary fibers. DHQ website provided step by step instructions to calculate HEI in SAS (SAS enterprise guide 7.4). Linear regression was run to determine the association between the average daily intake of MACs and the HEI-2015 score. Results Average MAC intake was 7.7 ± 4.4 grams with most of the amounts coming from soluble dietary fibers (6.6 ± 3.8). The mean HEI-score of this population was 64.9 ± 10.8. Average daily consumption of MAC was significantly associated with HEI score, F(1,590) = 65.22, P = 0.000, accounting for 10% of the variation in HEI-score with adjusted R2 = 9.8%, a medium-size effect according to Cohen (1988). An extra gram of daily average intake of MAC led to a 0.78 (95% CI, 0.59 to 0.97) increase in HEI-score. Conclusions MAC intake was associated with an increase in HEI-2015 score; however, the total MAC intake was low in this population of college students. Therefore, more efforts are needed to increase the consumption of MACs not just dietary fibers in college students. Funding Sources None.
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