Statistical methods for analyzing physical activity data

Physical activity is any bodily movement that results in caloric expenditure. One important aspect of physical activity research is the assessment of usual (i.e., long-term average) physical activity in the population, in order to better understand the links between physical activity and health outcomes. Daily or weekly measurements of physical activity taken from a sample of indivuals are prone to measurement errors and nuisance effects, which can lead to biased estimates of usual physical activity parameters. Fortunately, statistical models can be used to account and adjust for these errors in order to give more accurate estimates of usual physical activity parameters. In this dissertation we develop statistical methods for estimating parameters of usual physical activity. In Chapter 1 we outline metrics and instruments used for physical activity assessment, and review current approaches for modeling usual physical activity and usual dietary intake for regularly consumed food components. In Chapter 2 we develop a model for physical activity data from the National Health and Nutrition Examination Survey (NHANES). A linear regression is defined to model objective monitor-based physical activity as a function of self reported physical activity variables and demographic variables. The fitted model is used to estimate mean daily physical activity levels for demographic groups in the population. In Chapter 3 we develop a method for estimating usual daily energy expenditure parameters from data collected using a self-report instrument and an objective monitoring device. Our method is an extension of existing methods that utilize measurement error models. We illustrate our method with preliminary data from the Physical Activity Measurement Survey (PAMS) collected using a SenseWear Pro armband monitor and a 24-hour physical activity recall

Statistical methods for analyzing physical activity data

Physical activity is any bodily movement that results in caloric expenditure. One important aspect of physical activity research is the assessment of usual (i.e., long-term average) physical activity in the population, in order to better understand the links between physical activity and health outcomes. Daily or weekly measurements of physical activity taken from a sample of indivuals are prone to measurement errors and nuisance effects, which can lead to biased estimates of usual physical activity parameters. Fortunately, statistical models can be used to account and adjust for these errors in order to give more accurate estimates of usual physical activity parameters. In this dissertation we develop statistical methods for estimating parameters of usual physical activity. In Chapter 1 we outline metrics and instruments used for physical activity assessment, and review current approaches for modeling usual physical activity and usual dietary intake for regularly consumed food components. In Chapter 2 we develop a model for physical activity data from the National Health and Nutrition Examination Survey (NHANES). A linear regression is defined to model objective monitor-based physical activity as a function of self reported physical activity variables and demographic variables. The fitted model is used to estimate mean daily physical activity levels for demographic groups in the population. In Chapter 3 we develop a method for estimating usual daily energy expenditure parameters from data collected using a self-report instrument and an objective monitoring device. Our method is an extension of existing methods that utilize measurement error models. We illustrate our method with preliminary data from the Physical Activity Measurement Survey (PAMS) collected using a SenseWear Pro armband monitor and a 24-hour physical activity recall.</p

Expanding the Scope of Pyclen-Picolinate Lanthanide Chelates to Po-Tential Theranostic Applications

A family of three picolinate pyclen based ligands, previously investigated for the complexation of Y3+ and some lanthanide ions (Gd3+, Eu3+), was studied with 161Tb and 177Lu in view of potential radiotherapeutic applications. The set of six Tb3+ and Lu3+ complexes was synthesized and fully characterized. The coordination properties in the solid state and in solution were thoroughly studied. Potentiometric titrations, corroborated by DFT calculations, showed the very high stability constants of the Tb3+ and Lu3+ complexes, which are associated to remarkable kinetic inertness. A complete radiolabeling study performed with both 161Tb and 177Lu radionuclides, including experiments with regard to the stability with and without scavengers and kinetic inertness using challenging agents, proved that the ligands could reasonably compete with the DOTA analogue. To conclude, the potential of using the same ligand for both radiotherapy and optical imaging was highlighted for the first time

Expanding the Scope of Pyclen-Picolinate Lanthanide Chelates to Po-Tential Theranostic Applications

A family of three picolinate pyclen based ligands, previously investigated for the complexation of Y3+ and some lanthanide ions (Gd3+, Eu3+), was studied with 161Tb and 177Lu in view of potential radiotherapeutic applications. The set of six Tb3+ and Lu3+ complexes was synthesized and fully characterized. The coordination properties in the solid state and in solution were thoroughly studied. Potentiometric titrations, corroborated by DFT calculations, showed the very high stability constants of the Tb3+ and Lu3+ complexes, which are associated to remarkable kinetic inertness. A complete radiolabeling study performed with both 161Tb and 177Lu radionuclides, including experiments with regard to the stability with and without scavengers and kinetic inertness using challenging agents, proved that the ligands could reasonably compete with the DOTA analogue. To conclude, the potential of using the same ligand for both radiotherapy and optical imaging was highlighted for the first time