SOCIAL AND BIOLOGICAL DETERMINANTS OF SHORT-TERM GROWTH VELOCITY AMONG PRESCHOOLERS OF RURAL GUATEMALA: A PATH ANALYSIS APPROACH (WEIGHT-GAIN, IRON DEFICIENCY, GASTROINTESTINAL SYMPTOMS)

This dissertation develops and tests through path analysis a theoretical model to explain how socioeconomic, socioenvironmental, and biologic risk factors simultaneously influence each other to further produce short-term, depressed growth in preschoolers. Three areas of risk factors were identified: child's proximal environment, maturational stage, and biological vulnerability. The theoretical model represented both the conceptual framework and the nature and direction of the hypotheses. Original research completed in 1978-80 and in 1982 provided the background data. It was analyzed first by nested-analysis of variance, followed by path analysis. The study provided evidence of mild iron deficiency and gastrointestinal symptomatology in the etiology of depressed, short-term weight gain. Also, there was evidence suggesting that family resources for material and social survival significantly contribute to the variability of short-term, age-adjusted growth velocity. These results challenge current views of unifocal intervention, whether for prevention or control. For policy formulations, though, the mechanisms underlying any set of interlaced relationships must be decoded. Theoretical formulations here proposed should be reassessed under a more extensive research design. It is suggested that studies should be undertaken where social changes are actually in progress; otherwise, nutritional epidemiology in developing countries operates somewhere between social reality and research concepts, with little grasp of its real potential. The study stresses that there is a connection between substantive theory, empirical observation, and policy issues. ^

Factors influencing participation in individuals with disability: A secondary data analysis

Individuals with disabilities face numerous barriers to participation due to biological and physical characteristics of the disability as well as social and environmental factors. Participation can be impacted on all levels from societal, to activities of daily living, exercise, education, and interpersonal relationships. This study evaluated the impact of pain, mood, depression, quality of life and fatigue on participation for individuals with mobility impairments. This cross sectional study derives from self-report data collected from a wheelchair using sample. Bivariate correlational and multivariate analysis were employed to examine the relationship between pain, quality of life, positive and negative mood, fatigue, and depression with participation while controlling for relevant socio-demographic variables (sex, age, time with disability, race, and education). Results from the 122 respondents with mobility impairments demonstrated that after controlling for socio-demographic characteristics in the full model, 20% of the variance in participation scores were accounted for by pain, quality of life, positive and negative mood, and depression. Notably, quality of life emerged as being the single variable that was significantly related to participation in the full model. Contrary to other studies, pain did not appear to significantly impact participation outcomes for wheelchair users in this sample. Participation is an emerging area of interest among rehabilitation and disability researchers, and results of this study provide compelling evidence that several psychosocial factors are related to participation. This area of inquiry warrants further study, as many of the psychosocial variables identified in this study (mood, depression, quality of life) may be amenable to intervention, which may also positively influence participation.^

Analysis of interval -censored events in hypertension studies: Evaluation of treatment of coronary heart disease

Many statistical studies feature data with both exact-time and interval-censored events. While a number of methods currently exist to handle interval-censored events and multivariate exact-time events separately, few techniques exist to deal with their combination. This thesis develops a theoretical framework for analyzing a multivariate endpoint comprised of a single interval-censored event plus an arbitrary number of exact-time events. The approach fuses the exact-time events, modeled using the marginal method of Wei, Lin, and Weissfeld, with a piecewise-exponential interval-censored component. The resulting model incorporates more of the information in the data and also removes some of the biases associated with the exclusion of interval-censored events. A simulation study demonstrates that our approach produces reliable estimates for the model parameters and their variance-covariance matrix. As a real-world data example, we apply this technique to the Systolic Hypertension in the Elderly Program (SHEP) clinical trial, which features three correlated events: clinical non-fatal myocardial infarction, fatal myocardial infarction (two exact-time events), and silent myocardial infarction (one interval-censored event). ^