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Indiana University-Purdue University Indianapolis (IUPUI) / Introduction: Increasing obesity in children leads to an increase in the risk of Type 2 diabetes (T2D). Therefore, it is important to promote healthier lifestyles in youths and encourage their caregivers(s) to provide a healthy lifestyle environment. The PowerHouse program focuses on improving food choices, increasing physical activity, and adopting behavior changes for the reduction of obesity and the prevention of T2D. Method: The aim of this study was to assess the effects of implementing the PowerHouse program on both clinical and quality of life outcomes in high-risk, low-income youth and their caregivers. Primary outcomes were BMI standard deviation and BMI percentile in youths. Secondary outcomes included physical activity of youths and quality of life for both youths and their caregivers. Attendance rates were also calculated. Linear effect mixed models were used to test for time effects for all outcomes. Results: Clinical outcomes did not improve over time, except for youth HbA1c (p-value = 0.0447). Some improvements in youth quality-of-life outcomes were noted: specifically, the Sports Index score of the Fels Physical Activity Questionnaire for Children (adjusted p-value = 0.0213) and the Physical Summary (p-value = 0.0407), Psychosocial Summary (p-value = 0.0167), and Total score (p-value = 0.0094) for the youth-reported Pediatric Quality of Life Inventory. Quality of life did not change over time for caregivers. For attendance, there was an improvement after the intervention was modified to improve access to fresh produce (p-value = 0.0002). Conclusion: HbA1c and quality of life improved over time for youth; however, there was not an improvement in caregiver outcomes over time. The data suggest that more time may be needed to see the full effects of the intervention, and/or that a booster intervention may be needed.

<p>Postpartum depression has become a major public health concern for women within a specific time period after delivery. Depression is possibly associated with some risk factors such as socioeconomic status, social support, maternal mental and physical health, and history of anxiety. TOMIS III, funded by the Canadian Institutes of Health Research, is a prospective cohort to study the associations between delivery method and health and health resource utilization.</p> <p>Clinically, we investigated the associations between mode of delivery and outcome of postnatal depression, maternal and infant health, and we implied the risk predictors for outcomes by statistical methodology of marginal model with generalized estimating equations (GEE). Statistically, a variety of regression models, namely, generalized linear mixed effect model (GLMM), hierarchical generalized linear model (HGLM) and Bayesian hierarchical model were applied for this analysis and results were compared with GEEs. Some imputation strategies, namely, mean imputation, last observation carrying forward (LOCF), hot-deck imputation and multiple imputation were employed for handling missing values in this study.</p> <p>Analysis results demonstrated that there was no statistically significant association between mode of delivery and postpartum depression [OR 0.99, 95% CI (0.73, 1.34)]. However, the development of postpartum depression was found to be associated with low income, low mental and physical health functioning, lack of social support, the low number of unmet learning needs in hospital, and English or French spoken at home. Results were consistent for all regression models but GEE provided the best fit and an excellent discriminative ability. GEE models were constructed on different datasets imputed by mean, LOCF, hot-deck and multiple imputation, and LOCF was recommended to handle the missing data in this longitudinal study.</p> <p>Analyses on the outcome of maternal health and infant health stated that method of delivery had a statistically significant influence on maternal health but no significant impact on infant health. Risks of maternal health problems were associated with cesarean delivery, good/fair/poor infant health, low maternal mental and physical health functioning, lack of care for maternal mental health, and good/fair/poor health before pregnancy. Risks of infant health problems were associated with good/fair/poor maternal health before pregnancy and after discharge, inadequate care or help for infant health, fair/poor community services after discharge, low maternal mental health functioning, non-English or non-French spoken at home, and mothers born outside of Canada.</p> / Master of Science (MSc)

The construction industry's two main certifications are Leadership in Energy and Environmental Design (LEED) and Energy Star. To achieve the triple bottom line of sustainability for these certifications, both certifications should make a positive impact individually as well as mutually, with their impact extending to the surrounding neighborhood. This research examined the spillover effect of LEED and/or Energy Star certified office buildings on the property values of other buildings in their neighborhood in Manhattan, New York City from an economic standpoint. The spatial analysis approach using the Geographic Information System and the statistical analysis approach based on the Hedonic Price Model and the Linear Mixed Effect Model were applied to identify the geographical distribution of LEED and/or Energy Star certified office buildings and their other buildings in their neighborhoods and analyze the impact of the former on the latter. The results were as follows: 1) There was a significant correlation between a LEED and/or Energy Star certified office building and the unit market values of its adjoining buildings through the unit market values of the certified office building, the LEED and/or Energy Star certification achievement, and the major features of LEED certification; 2) There was a varying spillover effect of the certified office building on the median unit market value of buildings depending on their proximities to a LEED and/or Energy Star certified office building. This research provides a firm foundation for further efforts to quantify the spillover effect of LEED and/or Energy Star certification on a neighborhood from an economic standpoint, thus supporting and encouraging growth in the local real estate market and benefitting not only the owners, developers, and investors of the certified office building but also the owners of neighboring buildings. / Ph. D.

The distribution of mountain permafrost is generally modeled using a combination of statistical techniques and empirical variables. Such models, based on topographic, climatic and geomorphological predictors of permafrost, have been widely used to estimate the spatial distribution of mountain permafrost in North America and Europe. However at present, little knowledge about the distribution and characteristics of mountain permafrost is available for the Andes. In addition, the effects of climate change on slope stability and the hydrological system, and the pressure of mining activities have increased concerns about the knowledge of mountain permafrost in the Andes. In order to model permafrost distribution in the semi-arid Chilean Andes between ~29°S and 32°S, an inventory of rock glaciers is carried out to obtain a variable indicative of the presence and absence of permafrost conditions. Then a Linear Mixed-Effects Model (LMEM) is used to determine the spatial distribution of Mean Annual Air Temperature (MAATs), which is then used as one of the predictors of permafrost occurrence. Later, a Generalized Additive Model (GAM) with a logistic link function is used to predict permafrost occurrence in debris surfaces within the study area. Within the study area, 3575 rock glaciers were inventoried. Of these, 1075 were classified as active, 493 as inactive, 343 as intact and 1664 as relict forms, based on visual interpretation of satellite imagery. Many of the rock glaciers (~60-80%) are situated at positive MAAT, and the number of rock glaciers at negative MAAT greatly decreases from north to south. The results of spatial temperature distribution modeling indicated that the temperature changes by -0.71°C per each 100 m increase in altitude, and that there is a 4°C temperature difference between the northern and southern part of the study area. The altitudinal position of the 0°C MAAT isotherm is situated at ~4250 m a.s.l. in the northern (29°S) section and drops latitudinally to ~4000 m a.s.l. in the southern section (32°S) of the study area. For permafrost modeling purposes, 1911 rock glaciers (active, inactive and intact forms) were categorized into the class indicative of permafrost presence and 1664 (relict forms) as non-permafrost. The predictors MAAT and Potential Incoming Solar Radiation (PISR) and their nonlinear interaction were modeled by the GAM using LOESS smoothing function. A temperature offset term was applied to reduce the overestimation of permafrost occurrence in debris surface areas due to the use of rock glaciers as permafrost proxies. The dependency between the predictor variables shows that a high amount of PISR has a greater effect at positive MAAT levels than in negative ones. The GAM for permafrost distribution achieved an acceptable discrimination capability between permafrost classes (area under the ROC curve ~0.76). Considering a permafrost probability score (PPS) ≥ 0.5 and excluding steep bedrock and glacier surfaces, mountain permafrost can be potentially present in up to about 6.8% (2636 km2) of the study area, whereas with a PPS ≥ 0.75, the potential permafrost area decreases to 2.7% (1051 km2). Areas with the highest PPS are spatially concentrated in the north section of the study area where altitude rises considerably (the Huasco and Elqui watersheds), while permafrost is almost absent in the southern section where the topography is considerably lower (Limarí and Choapa watersheds). This research shows that the potential mountain permafrost distribution can be spatially modeled using topoclimatic information and rock glacier inventories. Furthermore, the results have provided the first local estimation of permafrost distribution in the semi-arid Chilean Andes. The results obtained can be used for local environmental planning and to aid future research in periglacial topics.

The migratory birds stop at different stopover sites during migration. The presence of resources in these stopover sites is essential to regain the energy of these birds. This thesis aims to compare the resource abundance and intake at the two stopover sites: Reda and Wisla river estuaries. How a bird's mass changes during its stay at an estuary is considered as a proxy for the resource abundance of a site. The comparison is made on different subsets, including those which has incomplete data, i.e. next day is not exactly one day after the previous capture. Multiple linear regression, Generalized additive model and Linear mixed effect model are used for analysis. Expectation maximization and an iterative predictive process are implemented to deal with incomplete data. We found that Reda has higher resource abundance and intake as compared to that of Wisla river estuary.