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Background: Previous research suggests associations between energy balance, eating frequency, macronutrient content, and macronutrient distribution with body composition. In particular, energy balance and protein intake have been conventionally evaluated in 24-hr time blocks, consistent with dietary recommendations and general public understanding. However, there is a potential benefit to investigating energy balance and protein intake in smaller increments of time to account for dynamic changes that occur within-day.Objective: The purpose of this study was to evaluate protein intake/distribution relative to energy balance fluctuations during the day and body composition in collegiate female basketball players.Methods: Subjects provided information on dietary intake and expenditure. Body composition was assessed by multi-current bioelectrical impedance. Energy balance (EB) and related protein distribution variables were determined with a Computerized Time-Line Energy Analysis procedure. Data were analyzed for associations between energy balance, protein intake and distribution, and body composition. Data are displayed as either traditional 24-hr EB and total protein intake or dynamic protein variables in relation to real-time EB (ingestion within ± 400 kcal EB or > 0 kcal EB).Results: There was no relationship between net 24-hr energy balance and percentage body fat. A statistically significant positive relationship was observed between total protein intake and body fat mass (R = .597; p = .031). No relationship was observed between protein distribution variables (g in ± 400 kcal EB, g in > 0 kcal EB) and percentage body fat. Protein eating occurrences (>10g, ± 400 kcal EB) was inversely correlated with BMI (R = -.650; p = .016). Subjects with the greatest energy deficits presented with lower lean body mass (R= -.736; p = .004).Conclusion: These data suggest that within-day protein distribution relative to energy balance are associated with BMI, but not with percentage body fat. Those with the highest protein intake had the highest body fat mass, with no correlation between protein intake and total energy intake detected. In this group, no association between 24hr intake net values or within-day intake values were found to be related to body fat percentage. However, the greatest energy balance deficit during the day was strongly inversely associated with lean body mass, indicative of potentially deleterious effects of energy restriction.

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This thesis includes one qualitative literature review, three empirical studies and one meta-analysis examining the measurement of physical activity in children. Previous research has highlighted the difficulties inherent in measuring children's habitual activity. This has lead to confusion regarding the relationships between physical activity and health in children. Recently a new type of activity monitor has been developed. Uniaxial (WAM, Computer Science Applications, Shalimar, Florida, USA) and triaxial (Tritrac, Professional Products, a division of Reining International, Madison, WI, USA) accelerometers that record temporal, frequency and intensity information of movement are now commercially available. The aims of this thesis were to evaluate the validity of these and other measures of physical activity in children, to examine the relationship between physical activity and body fat in children and to investigate the effect the mode of activity measurement has on this relationship. The main findings were: a) The Tritrac provided a significantly better estimate of scaled oxygen consumption during typical children's activities than the WAM, heart rate or pedometry; b) Physical activity, measured by the Tritrac or the pedometer, was inversely correlated with body fat and positively correlated with aerobic fitness; c) Heart rate measures of physical activity did not correlate significantly with body fat or aerobic fitness; d) Meta-analytic procedures showed a small to moderate relationship between activity levels and body fat in children; e) The strength of this relationship was heavily dependent on the method used to assess activity levels. Observation methods produced an effect size significantly higher than questionnaire or heart rate methods, though not significantly different to motion counter methods. In conclusion it appears that heart rate methods are inappropriate for the assessment of habitual activity in children. The use of motion counters or observation methods for assessing activity are recommended. Motion counter methods are particularly appropriate for medium to large sample sizes.

This study was conducted to determine the extent to which changes in dietary fiber consumption affect weight and body fat percentage (BF%) over time. An auxiliary objective was to examine the influence of age, total caloric intake, and physical activity (PA) on the relationship between changes in fiber intake and changes in body composition over time. Design/ Subjects: Prospective cohort design with baseline and follow-up assessments 20 months apart and 252 middle-aged women (40.1±3.0 y). Diet, particularly caloric and fiber intake, was measured using 7-day weighed food records. Body fat was assessed via the Bod Pod, and PA was measured objectively using MTI accelerometers over seven consecutive days. Statistical Analysis: Changes in weight, BF%, and fiber intake were calculated by subtracting baseline measurements from those taken at 20 months. Regression analysis was used to determine the extent to which baseline fiber intake/1000 kcal and changes in fiber intake/1000 kcal were predictive of changes in body weight and BF%. Partial correlation was employed to ascertain the effect of controlling for each of the potential confounding variables on the fiber and body composition associations. Results: Across the study, there were significant changes in all variables. For every increase of one gram of fiber/1000 kcal consumed, weight decreased by 0.55 lb (P=0.0061) and BF% decreased by 0.25 percentage point (P=0.0052). Baseline fiber intake/1000 kcal was not predictive of changes in body weight or BF% over the 20 month period. Conclusions: Increasing dietary fiber intake may be an effective means of weight management in middle-aged women.

Diet and lifestyle choices play a vital role in the overall health of an individual. There are many types of diets with varying instructions on what kind and how much of a food, or food group, should be eaten. This cross sectional study focused on possible health benefits of a vegetarian diet in regards to the body composition of non-vegetarian and vegetarian women. Total meat, poultry, seafood, and fish (MPSF) intake were separated into three categories to compare low-to-very-low, moderate, and high intake. Anthropometric measurements collected included waist to hip ratio (WHR), weight, height, and percentage of body fat. No significant differences were found between the vegetarian and non-vegetarian categories BMI, body fat percentage, or WHR. Conclusions found by previous research were not supported by the results of this research. Factors including geographic location and socioeconomic status could impact the availability of healthy food for both vegetarians and non-vegetarians.

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Obesity is a heterogeneous condition that can seriously impact the degree to which one is healthy and socially accepted. It is generally considered to be greatly influenced by genetic factors. Given that we cannot change our genes, it was the purpose of this study to try to further understand the variables related to obesity that are not genetic. Specifically, the purpose of this study was to investigate the impact of certain family systems variables and childhood feeding practices on Body Mass Index (BMI). The family variables of interest were intergenerational intimacy, intergenerational differentiation, intergenerational triangulation, spousal intimacy, spousal differentiation, nuclear family triangulation, and the relationship between eating and sex. The childhood feeding variables of interest related to the use of food as a reward, coercive use of food, parental disagreement about feeding, the expression of love through food, and feeding enmeshment (i.e., the perception of parental overcontrol in feeding). Because certain eating styles have been found to be related to obesity, further investigation revolved around the impact of the family and feeding variables on eating styles. The eating styles of interest were restrained eating, emotional eating, external eating, and binge eating. The variables were studied by surveying employees of a school system in southwest Virginia. Body Mass Index was found to be significantly positively correlated with feeding enmeshment, weight as a means of sexual avoidance, and eating in response to a lack of physical affection. Restrained eating was not found to be significantly related to any family or childhood feeding variable. Emotional eating, external eating, and binge eating were all significantly negatively correlated with intergenerational intimacy, spousal differentiation, and nuclear family triangulation health, significantly positively correlated with sexual avoidance and deprivation of affection. In addition, emotional eating and binge eating were significantly negatively correlated with intergenerational differentiation, while external eating and binge eating were significantly negatively correlated with spousal intimacy. Emotional eating was positively correlated with all of the childhood feeding practices, while external eating and binge eating were correlated with four and three, respectively, of the feeding practices. While there were many significant correlational findings, there were few significant coefficients in the hierarchical regression analyses, presumably because of the high intercorrelations between the predictor variables (the family and feeding variables). In general, it can be said that family functioning and childhood feeding behaviors are relevant to overeating and overweight. The family and feeding variables are better predictors of eating styles that can lead to obesity than of obesity per se. High levels of dysfunction in families and frequent use of food in non-nutritional ways are associated with high levels of emotional, external, and binge eating. These findings may have implications for physicians and therapists. / Ph. D.

The LeanScreenTM app uses photographs and touchscreen technology of an iPad or iPhone to estimate body composition using the Department of Defense (DoD) prediction equations that use cirumference measurements of the neck, abdomen, waist, and hips. The purpose of this study was to determine the validity and reliability of the LeanScreenTM app in 148 weight-stable adults (82 men, 66 women) who were normal weight, overweight, or obese as defined by body mass index. The percent body fat (%BF) of each subject was estimated during one visit using dual-energy x-ray absorptiometery (DXA) as the criterion measure, and three field methods: the LeanScreenTM app, manually measured circumferences, and an OMRON bioelectical impedance (BIA) device. The %BF of each subject was determined once using DXA. Each of two administrators assessed the %BF of each subject twice using the LeanScreenTM app, manually measured circumferences, and the OMRON BIA device. When using the LeanScreenTM app, administrators assessed body composition using photographs they had taken and the photographs taken by the other administrator. Validity was established by comparing estimates of %BF from the LeanScreenTM app, manually measured circumferences, and the OMRON BIA device to %BF values obtained from DXA. Inter- and intrarater reliability was determined using mutliple measurements taken by each of two administrators. The three field methods were compared to DXA using mixed model ANOVA and Bland-Altman analyses. Analysis of the data revealed that the LeanScreenTM app, manually measured circumferences, and the OMRON BIA device significantly underestimated (p < 0.05) the %BF determined by DXA by an average of -3.26 ± 3.57 %BF, -4.82 ± 3.45 %BF, and -8.45 ± 3.48 %BF, respectively. Limits of agreement (LOA) for the LeanScreenTM app (6.99 %BF), manually measured circumferences (6.76 %BF), and the OMRON BIA device (6.82 %BF) were large. Slopes of the line-of-best-fit through the data in the Bland-Altman plots indicate that bias of %BF estimates using the LeanScreenTM app (slope = 0.06; p = 0.008) and the OMRON BIA device (slope = 0.15; p < 0.0001) increased as %BF increased. For each method of assessment, minimal variance could be attributed to different administrators peforming the assessment and each administrator performing multiple assessments. All inter- and intrarater reliability coefficients of the LeanScreenTM app, manually measured circumferences, and OMRON BIA estimates of %BF exceeded 0.99. The results of this study indicate that all three field methods of body composition assessments were highly reliable, however, these field measures are not recommended for use in the assessments of %BF due to a significant bias and large limits of agreements.