9 resultados para Non-linear multiple regression

em DigitalCommons@The Texas Medical Center


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Multiple sclerosis (MS) is the most common demyelinating disease affecting the central nervous system. There is no cure for MS and current therapies have limited efficacy. While the majority of individuals with MS develop significant clinical disability, a subset experiences a disease course with minimal impairment even in the presence of significant apparent tissue damage on magnetic resonance imaging (MRI). The current studies combined functional MRI and diffusion tensor imaging (DTI) to elucidate brain mechanisms associated with lack of clinical disability in patients with MS. Recent evidence has implicated cortical reorganization as a mechanism to limit the clinical manifestation of the disease. Functional MRI was used to test the hypothesis that non-disabled MS patients (Expanded Disability Status Scale ≤ 1.5) show increased recruitment of cognitive control regions (dorsolateral prefrontal and anterior cingulate cortex) while performing sensory, motor and cognitive tasks. Compared to matched healthy controls, patients increased activation of cognitive control brain regions when performing non-dominant hand movements and the 2-back working memory task. Using dynamic causal modeling, we tested whether increased cognitive control recruitment is associated with alterations in connectivity in the working memory functional network. Patients exhibited similar network connectivity to that of control subjects when performing working memory tasks. We subsequently investigated the integrity of major white matter tracts to assess structural connectivity and its relation to activation and functional integration of the cognitive control system. Patients showed substantial alterations in callosal, inferior and posterior white matter tracts and less pronounced involvement of the corticospinal tracts and superior longitudinal fasciculi (SLF). Decreased structural integrity within the right SLF in patients was associated with decreased performance, and decreased activation and connectivity of the cognitive control system when performing working memory tasks. These studies suggest that patient with MS without clinical disability increase cognitive control system recruitment across functional domains and rely on preserved functional and structural connectivity of brain regions associated with this network. Moreover, the current studies show the usefulness of combining brain activation data from functional MRI and structural connectivity data from DTI to improve our understanding of brain adaptation mechanisms to neurological disease.

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While numerous studies have found similar mortality rates for Hispanics compared to non-Hispanic whites, surprisingly little is known about years of potential life lost (YPLL) differentials in mortality. The primary purpose of this paper is to quantify the effect that YPLL has on Hispanics in order to determine if YPLL differs between Hispanics and non-Hispanic whites. Using YPLL may bring attention to dissimilarities that are often obscured through traditional measures. Bexar County 2000-2004 data from the Texas Department of State Health Services, Vital Statistics Unit was analyzed for the descriptive analysis and 2003 Bexar County Multiple Cause Death data was analyzed for the regression analysis. The multiple regression models were used to examine Hispanic and non-Hispanic white differences in years of potential life lost (YPLL) before age 75 from all-causes of death. For this analysis, YPLL was regressed on ethnicity, education level and marital status for men and women. The descriptive analysis found YPLL from all-causes was greater among non-Hispanic whites than Hispanics. However, the regression analysis found Hispanics lost more year of potential from all-causes of death compared to non-Hispanic whites. This indicates that the effect of ethnicity on YPLL differs for different methods of analysis. Future research efforts should keep in mind the method of analysis when using YPLL. Understanding differences in mortality among Hispanics and non-Hispanic whites is important for targeting future health policies and research to aid in eliminating Hispanic health disparities. ^

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Characteristics of Medicare-certified home health agencies in Texas and the contributions of selected agency characteristics on home health care costs were examined. Cost models were developed and estimated for both nursing and total visit costs using multiple regression procedures. The models included home health agency size, profit status, control, hospital-based affiliation, contract-cost ratio, service provision, competition, urban-rural input-price differences, and selected measures of patient case-mix. The study population comprised 314 home health agencies in Texas that had been certified at least one year on July, 1, 1986. Data for the analysis were obtained from Medicare Cost Reports for fiscal year ending between July 1, 1985 to June 30, 1986.^ Home health agency size, as measured by the logs of nursing and total visits, has a statistically significant negative linear relationship with nursing visit and total visit costs. Nursing and total visit costs decrease at a declining rate as size increases. The size-cost relationship is not altered when controlling for any other agency characteristic. The number of visits per patient per year, a measure of patient case-mix, is also negatively related to costs, suggesting that costs decline with care of chronic patients. Hospital-based affiliation and urban location are positively associated with costs. Together, the four characteristics explain 19 percent of the variance in nursing visit costs and 24 percent of the variance in total visit costs.^ Profit status and control, although correlated with other agency characteristics, exhibit no observable effect on costs. Although no relationship was found between costs and competition, contract cost ratio, or the provision on non-reimburseable services, no conclusions can be made due to problems with measurement of these variables. ^

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While clinical studies have shown a negative relationship between obesity and mental health in women, population studies have not shown a consistent association. However, many of these studies can be criticized regarding fatness level criteria, lack of control variables, and validity of the psychological variables.^ The purpose of this research was to elucidate the relationship between fatness level and mental health in United States women using data from the First National Health and Nutrition Examination Survey (NHANES I), which was conducted on a national probability sample from 1971 to 1974. Mental health was measured by the General Well-Being Schedule (GWB), and fatness level was determined by the sum of the triceps and subscapular skinfolds. Women were categorized as lean (15th percentile or less), normal (16th to 84th percentiles), or obese (85th percentile or greater).^ A conceptual framework was developed which identified the variables of age, race, marital status, socioeconomic status (education), employment status, number of births, physical health, weight history, and perception of body image as important to the fatness level-GWB relationship. Multiple regression analyses were performed separately for whites and blacks with GWB as the response variable, and fatness level, age, education, employment status, number of births, marital status, and health perception as predictor variables. In addition, 2- and 3-way interaction terms for leanness, obesity and age were included as predictor variables. Variables related to weight history and perception of body image were not collected in NHANES I, and thus were not included in this study.^ The results indicated that obesity was a statistically significant predictor of lower GWB in white women even when the other predictor variables were controlled. The full regression model identified the young, more educated, obese female as a subgroup with lower GWB, especially in blacks. These findings were not consistent with the previous non-clinical studies which found that obesity was associated with better mental health. The social stigma of being obese and the preoccupation of women with being lean may have contributed to the lower GWB in these women. ^

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Background. Public schools are a key forum in the fight for child health because of the opportunities they present for physical activity and fitness surveillance. However, because schools are evaluated and funded on the basis of standardized academic performance rather than physical activity, empirical research evaluating the connections between fitness and academic performance is needed to justify curriculum allocations to physical activity. ^ Methods. Analyses were based on a convenience sample of 315,092 individually-matched standardized academic (TAKS™) and fitness (FITNESSGRAM®) test records collected by 13 Texas school districts under state mandates. We categorized each fitness result in quintiles by age and gender and used a mixed effects regression model to compare the academic performance of the top and bottom fitness groups for each fitness test and grade level combination. ^ Results. All fitness variables except BMI showed significant, positive associations with academic performance after sociodemographic covariate adjustments, with effect sizes ranging from 0.07 (95% CI: 0.05,0.08) in girls trunklift-TAKS reading to 0.34 (0.32,0.35) in boys cardiovascular-TAKS math. Cardiovascular fitness showed the largest inter-quintile difference in TAKS score (32-75 points), followed by curl-ups. After an additional adjustment for BMI and curl-ups, cardiovascular associations peaked in 8th-9 th grades (maximum inter-quintile difference 142 TAKS points; effect size 0.75 (0.69,0.82) for 8th grade girls math) and showed dose-response characteristics across quintiles (p<0.001 for both genders and outcomes). BMI analysis demonstrated limited, non-linear association with academic performance after adjustment for sociodemographic, cardiovascular fitness and curl-up variables. Low-BMI Hispanic high school boys showed significantly lower TAKS scores than the moderate (but not high) BMI group. High-BMI non-Hispanic white high school girls showed significantly lower scores than the moderate (but not low) BMI group. ^ Conclusions. In this study, fitness was strongly and significantly related to academic performance. Cardiovascular fitness showed a distinct dose-response association with academic performance independent of other sociodemographic and fitness variables. The association peaked in late middle to early high school. The independent association of BMI to academic performance was only found in two sub-groups and was non-linear, with both low and high BMI posing risk relative to moderate BMI but not to each other. In light of our findings, we recommend that policymakers consider PE mandates in middle-high school and require linkage of academic and fitness records to facilitate longitudinal surveillance. School administrators should consider increasing PE time in pursuit of higher academic test scores, and PE practitioners should emphasize cardiovascular fitness over BMI reduction.^

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In The Woodlands, Texas, 346 students in grades 9-12, age 14-18 participated in a screening examination for cardiovascular risk factors. The relationships between blood pressure with Type-A-behavior and its components were evaluated. Type-A-behavior was measured using the Hunter-Wolf Type-A-behavior scale.^ The following results refer to the current 24-item version of the Hunter-Wolf Type-A-behavior scale and subscales derived in the Bogalusa study which thereafter were applied to The Woodlands population.^ No significant differences in blood pressure were observed among children in the highest vs. lowest quintile of the Type-A-behavior score or subscales scores. The correlation coefficients of blood pressure with the Type-A-behavior and its components were small and non-significant in both boys and girls. Multiple regression analyses conducted by sex, showed that after adjustment for age, weight and height, the addition of the total Type-A-behavior score or subscale scores did not increase significantly the amount of the variability explained for any of the blood pressure components.^ These analyses were repeated with results from the original 17-item version of the Hunter-Wolf Type-A-behavior scale and subscales derived in Bogalusa. Similarly, no relationship was observed between the 17-item Type-A-behavior score or subscales scores with blood pressure levels in The Woodlands population.^ Finally, it was important to determine whether subscales derived within The Woodlands population would differ from those described in Bogalusa and would relate differently to blood pressure among students in The Woodlands. The corresponding analyses showed that the subscales derived from the two studies were different, but in fact neither set of subscales was importantly related with blood pressure in The Woodlands population.^ The results of this study are largely consistent with those obtained by Hunter and Wolf in Bogalusa, who among the white population found only the factor "Eagerness-Energy" to be associated with fourth phase diastolic blood pressure among girls. Even this relationship which they observed was weak and inconsistent across sex-race groups and blood pressure components. This study does not support even this positive finding. In conclusion, evidence indicates that blood pressure is not associated with Type-A-behavior or its components as measured by the Hunter-Wolf Type-A-behavior scale among white adolescents. ^

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This study described the relationship of sexual maturation and blood pressure in a sample (n = 361) of white females, ages seven through 18, attending public schools in a defined area of Central Texas during October through December, 1984. Other correlates of blood pressure were also described for this sample.^ A survey was performed to obtain the data on height, weight, body mass, pulse rate, upper arm circumference and length, and blood pressure. Each subject self-assessed her secondary sex characteristics (breast and pubic hair) according to drawings of the Tanner stages of maturation. The subjects were interviewed to obtain data on personal health habits and menstrual status. Student age, ethnic group and place of residence were abstracted from school records. Parents or guardians of the subjects responded to a questionnaire pertaining to parental and subject health history and parents' occupation and educational attainment.^ In the simple linear regression analysis, sexual maturation and variables of body size were significantly (p < 0.001) and positively associated with systolic and fourth- and fifth-phase diastolic blood pressure. The demographic and socioeconomic variables were not sufficiently variant in this population to have differential effects on the relation between blood pressure and maturation. Stepwise multiple regression was used to assess the contribution of sexual maturation to the variance of blood pressure after accounting for the variables of body size. Sexual maturation (breast stage) along with weight, height and body mass remained in the multiple regression models for fourth- and fifth-phase diastolic blood pressure. Only height and body mass remained in the regression model for systolic blood pressure; sexual maturation did not contribute more to the explanation of the systolic blood pressure variance.^ The association of sexual maturation with blood pressure level was established in this sample of young white females. More research is needed first, to determine if this relationship prevails in other populations of young females, and second, to determine the relationship of sexual maturation sequence and change with the change of blood pressure during childhood and adolescence. ^

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Ovarian cancer is the leading cause of cancer-related death for females due to lack of specific early detection method. It is of great interest to find molecular-based biomarkers which are sensitive and specific to ovarian cancer for early diagnosis, prognosis and therapeutics. miRNAs have been proposed to be potential biomarkers that could be used in cancer prevention and therapeutics. The current study analyzed the miRNA and mRNA expression data extracted from the Cancer Genome Atlas (TCGA) database. Using simple linear regression and multiple regression models, we found 71 miRNA-mRNA pairs which were negatively associated between 56 miRNAs and 24 genes of PI3K/AKT pathway. Among these miRNA and mRNA target pairs, 9 of them were in agreement with the predictions from the most commonly used target prediction programs including miRGen, miRDB, miRTarbase and miR2Disease. These shared miRNA-mRNA pairs were considered to be the most potential genes that were involved in ovarian cancer. Furthermore, 4 of the 9 target genes encode cell cycle or apoptosis related proteins including Cyclin D1, p21, FOXO1 and Bcl2, suggesting that their regulator miRNAs including miR-16, miR-96 and miR-21 most likely played important roles in promoting tumor growth through dysregulated cell cycle or apoptosis. miR-96 was also found to directly target IRS-1. In addition, the results showed that miR-17 and miR-9 may be involved in ovarian cancer through targeting JAK1. This study might provide evidence for using miRNA or miRNA profile as biomarker.^

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Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^