Male and female subjects currently participating in an ongoing study characterizing normal weight obesity in college students (Study IRB#: 17-0952), which has identical methods and outcomes, were included in this study. Based off previous literature5,29 a sample size of 54 subjects was calculated. Significant changes in %BF were detected between freshmen and juniors within each individual (18.3 ± 7.5% vs. 21.0 ± 7.4%) giving an effect size of 0.405, and significant changes were detected between freshmen and juniors within-individuals in FM (12.0 ± 8.1 kg) vs. 14.3 ± 9.1 kg) giving and effect size of 0.2975. These effect sizes were combined and averaged which gave a sample size of 54 subjects. Power was set a priori to 0.80, correlation among repeated measures to 0.6, and two-tailed analysis was employed. Sample size was
calculated using G*Power version 3.1.
In order to be included in this study, subjects were required to have a BMI between 18.5- 24.9 kg/m2. Subjects were required to be healthy and have no medical issues that would
potentially influence the results of this study, including renal, hepatic, musculoskeletal, or cardiometabolic disorders. Subjects were excluded if they had gained or lost ten pounds three months prior to enrollment or had a self-diagnosed eating disorder. Subjects were instructed to complete a three-day diet log and sign an approved informed consent from prior to enrollment.
24
Subjects were included in the study if they participated in ≤ 5 days of exercise per week and were not NCAA student-athletes.
Experimental Design
Before each visit, subjects were asked to arrive to the lab following a fast ≥8 hours. Anthropometric measurements were assessed, including weight (kg), height (cm), and BMI. Subjects completed a comprehensive assessment of body composition using DEXA. Lastly, a blood sample was taken to evaluate measures of lipids and glucose, and questionnaires were completed to assess various lifestyle factors including alcohol consumption and related
behaviors/emotional states, physical activity sleep duration and quality, and perceived stress. In a subsequent cross-sectional approach (Fall 2018), newly-enrolled subjects (n=43) were recruited to account for attrition and graduation from the previous year, as well as to further explore more detailed aspects of lifestyle habits. Questionnaires used to examine sedentary behavior, sleep quality and preferences, alcohol consumption, and mental health were included in addition to variables previously measured in the Fall and Spring assessment periods.
Body Composition
Dual-energy X-Ray absorptiometry (GE Lunar iDEXA, GE Medical Systems Ultrasound and Primary Care Diagnostics, Madison, WI, USA) was used to estimate LM, FM, %BF and VAT. All scans were performed by a trained DEXA technician. Before each scan, the trained technician entered the necessary subject information including height, weight, ethnicity, age, sex, and identification code. After ensuring the subject had removed all metal jewelry and any other
25
objects from their pockets, the technician instructed the subject to lie supine on the DEXA scanner. Once on the DEXA table, the technician adjusted the subject’s head, hips, shoulders, and limbs to center the subject within the DEXA’s measurement area. The subject’s hands lay pronated on the DEXA table next to their legs. Once in the correct position, a Velcro strap was placed around their ankles to hold the correct position. The subject was instructed to limit movement and to not alter breathing during the scan. The scan lasted between 7-13 minutes based on body size.
Cardiometabolic Health
A single blood sample was obtained during both Fall visits (Fall 2017 and Fall 2018) to assess cardiometabolic health. Blood samples were not collected in the spring of 2018. The blood sample was taken from the antecubital fossa, specifically from the median cubital, cephalic, or basilic vein. All samples were analyzed immediately post-draw using an Alere Cholestech LDX® Analyzer (Alere Inc., Waltham, MA, USA) to determine total cholesterol (TC), high- density lipoprotein (HDL), non-high-density lipoprotein (nHDL), and glucose (GLU). 40 µL of blood were aliquoted from the sample into a test cassette and placed in the device for analysis.
Questionnaires
During each visit, study participants completed multiple validated self-administered questionnaires regarding their lifestyle. The Shortened International Physical Activity
Questionnaire (IPAQ) is a 7-item survey that was used to gather data on physical activity over 7 days prior to the visit. The perceived stress scale (PSS) is a survey consisting of 14 items which was used to evaluate stress levels. Additionally, the Depression, Anxiety, and Stress Scale-21 items (DASS-21) was administered. The DASS-21 is a set of three self-report scales designed to
26
examine the emotional states of depression, anxiety and stress within individuals. The Pittsburgh Sleep Quality Index (PSQI) was given to provide an indication of subjects’ perceived sleep quality, sleep efficiency, and daily disturbances. The Morningness-Eveningness Questionnaire (rMEQ) was used to determine subjects’ diurnal preferences, sleep-wake pattern for activity, and alertness in the morning and evening. The revised College Alcohol Problems Scale (CAPS-r) and the Alcohol Use Disorders Identification Test (AUDIT) were both used to evaluate alcohol consumption and related behaviors. Sedentary behavior was assessed using the Sedentary Behavior Questionnaire (SBQ). Additionally, participants were asked about their living arrangements, including if they lived on campus or off, and how many roommates they had.
Statistical analysis
Analyses were performed using SPSS software (IBM Corp. Released 2016. IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: IBM Corp.). Repeated measures analysis of variance (ANOVA) [group (freshman vs. sophomore vs. junior vs. senior) × time (fall 2017 vs. spring 2018)] followed by Bonferroni post-hoc analysis were employed to examine changes in body composition and anthropometric outcome measures. Repeated measures analysis of variance (ANOVA) [group (freshman vs. sophomore vs. junior vs. senior) × time (fall 2017 vs. fall 2018)] followed by Bonferroni post-hoc analysis were employed to examine changes in cardiometabolic health. An additional sex (male vs. female) × group (freshman vs. sophomore vs. junior vs. senior) ANOVA was employed to assess sex-specific changes observed across class year. Pearson correlations were used to assess the direction and magnitude of relationships between nominal lifestyle factors and body composition changes observed across each academic year. Similar Pearson correlations were employed to assess the direction and magnitude of the
27
relationships between nominal lifestyle factors and observed cardiometabolic changes. A multiple regression was used to examine the relationship between categorical lifestyle factors with body composition and cardiometabolic changes observed. An alpha-level of 0.05 was employed in all statistical analyses. All data are presented as mean ± standard deviation unless noted otherwise.
28
CHAPTER IV: MANUSCRIPT