4 resultados para Factor Analysis, Statistical

em DigitalCommons@The Texas Medical Center


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Teen pregnancy is a continuing problem, bringing with it a host of associated health and social risks. Alternative school students are especially at risk, but are historically under-represented in research. This is especially problematic in that instruments are needed to guide effective intervention development, but psychometrics for these instruments cannot be assumed when used in new populations. Decisional balance from the transtheoretical model offers a framework for understanding condom decision making, but has not been tested with alternative school students. Using responses from 640 subjects from Safer Choices 2 (a school-based HIV/STD/pregnancy prevention program implemented in 10 urban, southwestern alternative schools), a decisional balance scale for condom use was examined. A two-factor, mildly correlated model fit the data well. Tests of invariance examined scale functioning within gender and racial/ethnic groups. The underlying structure varied slightly based on subgroup, but on a practical level the impact on the use of scales was minimal. The structure and loadings were invariant across experimental condition. The pro scale was associated with a lower probability of having engaged in unprotected sexual behavior for sexually active subjects, and this association remained significant while controlling for demographic variables. The con scale did not show a significant association with engagement in unprotected sexual behaviors. Limitations and directions for future research were also discussed.^

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Although many family-based genetic studies have collected dietary data, very few have used the dietary information in published findings. No single solution has been presented or discussed in the literature to deal with the problem of using factor analyses for the analyses of dietary data from several related individuals from a given household. The standard statistical approach of factor analysis cannot be applied to the VIVA LA FAMILIA Study diet data to ascertain dietary patterns since this population consists of three children from each family, thus the dietary patterns of the related children may be correlated and non-independent. Addressing this problem in this project will enable us to describe the dietary patterns in Hispanic families and to explore the relationships between dietary patterns and childhood obesity. ^ In the VIVA LA FAMILIA Study, an overweight child was first identified and then his/her siblings and parents were brought in for data collection which included 24 hour recalls and food frequency questionnaire (FFQ). Dietary intake data were collected using FFQ and 24 hour recalls on 1030 Hispanic children from 319 families. ^ The design of the VIVA LA FAMILIA Study has important and unique statistical considerations since its participants are related to each other, the majority form distinct nuclear families. Thus, the standard approach of factor analysis cannot be applied to these diet data to ascertain dietary patterns. In this project we propose to investigate whether the determinants of the correlation matrix of each family unit will allow us to adjust the original correlation matrix of the dietary intake data prior to ascertaining dietary intake patterns. If these methods are appropriate, then in the future the dietary patterns among related individuals could be assessed by standard orthogonal principal component factor analysis.^

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The objective of this cross-sectional study was to examine the relationship of provincial economic development indices with incidences of child injury mortality in Thailand from 1999 - 2001. All injury deaths among children age 1-14 years were included. The independent variables included gross provincial product per capita (GPP/c), poverty and inequality indices, material and social deprivation indices, population in rural/ urban areas, and migration. Due to multicollinearity of such variables, the 76 provinces were categorized by GPP/c quartile, and means of overall injury, drowning, and transport-related mortality rates were compared among quartile groups. Spearman’s rho correlation between GPP/c and injury mortality rates was also performed. Finally, factor analysis was employed to create a set of factors to be treated as uncorrelated variables and stepwise multiple regression was carried out for the effects of the factors on injury mortality rates. A significant direct relationship was observed between GPP/c and overall injury mortality among children age 1-4 years, and 10-14 year-olds of both genders. Drowning was the main cause of this relationship among children age 1-4 years, and transport-related injury was the principle cause among children age 10-14 years. Conversely, provinces with lower GPP/c experienced higher injury mortality rates among school-age children 5-9 years old for both genders, mostly due to drowning. Factor analysis, and multiple regression results confirmed the relationships between economic development and injury mortality rates. These findings revealed that economic development had an adverse impact on injury-related mortality among children 1 to 4 and 10 to14 in Thailand.

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Despite continued research and public health efforts to reduce smoking during pregnancy, prenatal cessation rates in the United States have decreased and the incidence of low birth weight has increased from 1985 to 1991. Lower socioeconomic status women who are at increased risk for poor pregnancy outcomes may be resistant to current intervention efforts during pregnancy. The purpose of this dissertation was to investigate the determinants of continued smoking and quitting among low-income pregnant women.^ Using data from cross-sectional surveys of 323 low-income pregnant smokers, the first study developed and tested measures of the pros and cons of smoking during pregnancy. The original decisional balance measure for smoking was compared with a new measure that added items thought to be more salient to the target population. Confirmatory factor analysis using structural equation modeling showed neither the original nor new measure fit the data adequately. Using behavioral science theory, content from interviews with the population, and statistical evidence, two 7-item scales representing the pros and cons were developed from a portion (n = 215) of the sample and successfully cross-validated on the remainder of the sample (n = 108). Logistic regression found only pros were significantly associated with continued smoking. In a discriminant function analysis, stage of change was significantly associated with pros and cons of smoking.^ The second study examined the structural relationships between psychosocial constructs representing some of the levels of and the pros and cons of smoking. The cross-sectional design mandates that statements made regarding prediction do not prove causation or directionality from the data or methods analysis. Structural equation modeling found the following: more stressors and family criticism were significantly more predictive of negative affect than social support; a bi-directional relationship was found between negative affect and current nicotine addiction; and negative affect, addiction, stressors, and family criticism were significant predictors of pros of smoking.^ The findings imply reversing the trend of decreasing smoking cessation during pregnancy may require supplementing current interventions for this population of pregnant smokers with programs addressing nicotine addiction, negative affect, and other psychosocial factors such as family functioning and stressors. ^