Obesity and Overweight among Black American Adolescent Females: The Role of Social Influences in Everyday Dietary Practices

Obesity and overweight disproportionately impact Black American adolescent females—placing them at a lifetime of elevated physical health risks. Despite this burden, the literature that explores the contributors to obesity and overweight among Black American adolescent females remains limited and unclear. This dissertation aims to develop knowledge related to obesity and overweight in Black American adolescent females, by appraising the current understanding of factors that contribute to their obesity and overweight, and explicating the everyday social influences on dietary practices. The primary study conducted for this dissertation used a mixed method, multiple case study design to examine the mother, daughter, and other household contributors to Black American adolescent daughters’ everyday practices of food consumption, acquisition, preparation, and planning. Findings reveal the importance of understanding the complex and dynamic ways mothers and other household members contribute to a holistic view of everyday dietary practices among adolescent daughters. By deeply examining the nuanced ways the multiple cases varied, context-dependent knowledge essential to understanding the complicated health challenge of obesity was produced. Subsequently, recommendations are provided for health providers and scholars to more holistically approach and examine obesity—particularly among populations who are disproportionately affected.

Parental Bereavement: Looking Beyond Grief - Challenges and Health

For most parents there is no imaginable event more devastating than the death of their child. Nevertheless, while bereaved parents grieve they are also expected to carry on with their life. The day-to-day activities that were once routine for these parents may now be challenging due to the emotional turmoil they are experiencing. To date parental bereavement has been described as complex, intense, individualized, and life-long and their grief responses are interwoven with their daily activities, but the nature of their daily life challenges are not known.

This dissertation highlights the significance of how parents respond to their bereavement challenges because bereaved parents have higher morbidity and mortality rates than non-bereaved parents or adults who have lost their spouse or parents. Many bereaved parents in their daily routines include activities that allow them to maintain a relationship with their deceased child. These behaviors have been described as “continuing bonds”, but with this dissertation the continuing bonds concept is analyzed to provide a clear conceptual definition, which can be used for future research.

Using the Adaptive Leadership Framework as the theoretical lens and a mixed method, multiple case study design, the primary study in this dissertation aims to provides knowledge about the challenges parents face in the first six months following the death of their child, the work they use to meet these challenges, and the co-occurrence of the challenges, and work with their health status. Bereaved parents challenges are unique to their individual circumstances, complex, interrelated and adaptive, as they have no easy fix. Their challenges were pertaining to their everyday life without their child and classified as challenges related to: a) grief, b) continuing bonds, c) life demands, d) health concerns, f) interactions, and g) gaps in the health care system. Parents intuitively responded to the challenges and attempted to care for themselves. However, the role of the healthcare system to assist bereaved parents during this stressful time so that their health is not negatively impacted was also recognized. This study provides a foundation about parental bereavement challenges and related work that can lead to the development and testing of interventions that are tailored to address the challenges with a goal of improving bereaved parents health outcomes.

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.