ASSOCIATION BETWEEN HEALTH-RELATED COMPONENTS AND BODY DISSATISFACTION IN WOMEN

Katherine Sullivan, Jacob Broeckel, Casey J. Metoyer, Andrew D. Fields, Madelyn K. Simmang, Michael R. Esco, FACSM, Michael V. Fedewa. University of Alabama, Tuscaloosa, AL. BACKGROUND: Body dissatisfaction refers to a negative perception or evaluation of one’s body or physical appearance. Higher body dissatisfaction negatively impacts self-esteem, perceived quality of life, and can increase the risk of disordered eating, substance abuse, anxiety, and depression. PURPOSE: To examine the association between body dissatisfaction and health-related components among women. METHODS: A convenience sample of 29 female adults were included in our analysis (90% Caucasian, 24.8±9.2 yrs., 24.9±3.6 kg/m2). Body mass and height were measured and used to calculate body mass index (BMI). Body dissatisfaction scores (BDS) were calculated using the body dissatisfaction subscale of the eating disorder inventory II (EDI-BD). Where applicable, EDI-BD items were reverse scored such that, higher BDS scores indicate greater body dissatisfaction. Health-related components included waist and hip circumference (cm), number of push-ups completed until exhaustion, average dominant and non-dominant hand-grip strength (kg), participant’s perceived functional ability to walk, jog, or run a one-mile and three-mile distance, BMI (kg/m2), physical activity (MET-minutes/week) derived from the short form International Physical Activity Questionnaire, and relative adiposity (%Fat) derived from Dual X-ray Absorptiometry. Bivariate correlations were used to examine the direction and strength of the association between BDS and health-related components. The strength of each r value was considered weak (r=0.2), moderate (r=0.5), or strong (r=0.8). Data are presented as mean±standard deviation, with p\u3c0.05 used to determine statistical significance. RESULTS: No statistically significant correlations (p\u3e.05 for all) were observed between BDS and waist or hip circumference (r=.144, r=.282, respectively), push-ups (r=-.215), dominant or non-dominant hand-grip strength (r=-.121, r=-.086, respectively), perceived ability to complete one-mile or three-miles (r=-.289, r=-.258), BMI (r=.240), or physical activity (r=.094). Significant, moderate correlations were observed between BDS and %Fat (r=.426, p=.021). CONCLUSIONS: Our results indicate a moderate, linear relationship between %Fat and body dissatisfaction. Given the relatively homogenous age, race, and BMI characteristics of the current study, the association between body dissatisfaction and health-related components should be further examined within a larger and more diverse sample

RELIABILITY OF LIGHTING CONDITIONS FOR MEASURING BODY FAT PERCENTAGE VIA IMAGE CAPTURE

Madelyn K. Simmang, Katherine Sullivan, Casey J. Metoyer, Jacob Broeckel, Andrew D. Fields, Mary Lovelady, Maddy Schwing, Michael V. Fedewa, Michael R. Esco, FACSM. University of Alabama, Tuscaloosa, AL. BACKGROUND: A smartphone application has been previously validated to estimate metrics of body composition (%Fat) from a full-body digital image. However, the reliability of the automated image analysis program has not been extensively examined under varying lighting conditions. PURPOSE: The aim of this study was to evaluate the reliability of %Fat estimates measured under Low(LL) Ambient(AL), Moderate(ML), and Bright-Light(BL) conditions. METHODS: A convenience sample of participants were included in the study (n=12, 83.3% female, 83.3% Caucasian, 31.25±10.49 yrs, 24.82±2.85 kg/m2). Age, gender, and race were assessed via self-report. Full-body digital images were taken in front of a white photography backdrop under LL, AL, ML, and BL lighting conditions (\u3c50 Lux, 300-400 Lux, 600-800 Lux, and \u3e900 Lux, respectively). Images were taken from the posterior view and were captured using an iPad Air 2 (Apple Inc., Cupertino, CA). A light meter (MT-912, Shenzhen Flus Technology Co., Ltd., Shenzhen China) was used to measure the level of illuminance in Lux. Images were analyzed using an automated smartphone application (made Health and Fitness LLC, Birmingham AL. version 1.1.3), which provided estimates of %Fat using a proprietary algorithm. A repeated measures ANOVA was used to assess potential mean differences in %Fat across the four lighting conditions, with the reliability assessed using a 2-way ICC with absolute agreement. The strength of the ICC value was considered weak, moderate, strong, or near-perfect (r=0.2, 0.5, 0.8, and 0.9 respectively). Data are presented as mean±standard deviation, with statistical significance set at p\u3c.05. RESULTS: Significant differences were observed across conditions (p=.047), such that %FatLL (27.62±4.95 %Fat) was slightly higher than the %FatBL (26.94±5.44 %Fat) (p=.018), but not different than the %FatAL (27.16±5.08 %Fat) or %FatML (27.31±5.23 %Fat) conditions (both p\u3e.05). No other differences were observed between conditions (all p\u3e.05). Near-perfect agreement between %FatLL and the %FatAL, %FatML, and %FatBL conditions (ICC=0.984, 0.985 0.991, respectively; all p\u3c.001) was observed. CONCLUSION: Based on the results of the study, a small difference was observed between %Fat estimates obtained under LL and BL conditions. However, the agreement between all conditions was near-perfect. These results suggest that %Fat can be estimated from a single digital image using a smartphone application across various lighting conditions with acceptable reliability

RELATIONSHIPS OF BODY COMPOSITION FACTORS WITH COMPONENTS OF PHYSICAL ACTIVITY AND MUSCULAR FITNESS

Andrew D. Fields, Katherine Sullivan, Casey Metoyer, Jacob Broeckel, Madelyn K. Simmang, Mary Lovelady, Maddy Schwing, Michael V. Fedewa, Michael R. Esco, FACSM. University of Alabama, Tuscaloosa, AL. BACKGROUND: It is commonly accepted that body composition is related to physical activity (PA) and muscular fitness (MF). However, it is not as well understood if metrics of PA and MF can explain the variance in both fat mass (FM) and fat-free mass (FFM). PURPOSE: The purpose of this investigation was to determine the extent of variation in FM and FFM that can be explained by specific components of PA and MF. METHODS: A convenience sample of participants was recruited for this study (n=37, 27.03% Female, 22.35±3.76 yrs.). All metrics were assessed during a single visit to the Exercise Physiology Lab. Body mass (BM) was measured to the nearest 0.1 kg with a calibrated digital scale (Tanita BWB-800, Tanita Corporation, Tokyo, Japan). Results from the International Physical Activity Questionnaire (IPAQ) Short-Form were converted to calculate the intensity and amount of weekly PA in MET-minutes per week (MET-min/wk). Intensities were categorized into vigorous, moderate, and walking based on IPAQ standards. FM was estimated using brightness-mode ultrasound (Philips iU22, Philips Medical Systems, Andover, MA, USA) across seven standardized sites. FFM was derived from subtracting FM from BM. Handgrip strength (HGS) was assessed on dominant hand via a hydraulic hand dynamometer (Alphamed Inc., Lakewood, NJ, USA) as a metric of muscular strength, and a maximum-rep push-up test was administered to quantify muscular endurance. The correlations between PA, MF, FM, and FFM were assessed using Pearson’s r, and described as weak, moderate, or strong (r=0.2, 0.5, or 0.8, respectively). Data are presented as mean±standard deviation, with an alpha level set to p\u3c0.05. RESULTS: There were no significant correlations found between FM and any of the PA or MF measures, (r=-0.28 to 0.24, all p\u3e0.05). FFM was moderately correlated with vigorous MET-min/wk (r=0.34, p=0.04) and walking MET-min/wk, (r=-0.37, p=0.02), and strongly correlated with and HGS (r=0.80, p\u3c0.001). Stepwise regression analysis showed that only HGS and vigorous MET-min/wk were included in the model that explained the variance in FFM (R2=0.74, p\u3c0.001). DISCUSSION: The results indicate that muscular strength and vigorous PA have stronger relationships with FFM than muscular endurance or other, lower-intensity metrics of PA. FM does not appear to be related to either MF parameters or IPAQ-derived PA