Characteristics of a spina bifida population including North American Caucasian and Hispanic individuals.

BACKGROUND: Meningomyelocele (MM) is a common human birth defect. MM is a disorder of neural development caused by contributions from genes and environmental factors that result in the NTD and lead to a spectrum of physical and neurocognitive phenotypes. METHODS: A multidisciplinary approach has been taken to develop a comprehensive understanding of MM through collaborative efforts from investigators specializing in genetics, development, brain imaging, and neurocognitive outcome. Patients have been recruited from five different sites: Houston and the Texas-Mexico border area; Toronto, Canada; Los Angeles, California; and Lexington, Kentucky. Genetic risk factors for MM have been assessed by genotyping and association testing using the transmission disequilibrium test. RESULTS: A total of 509 affected child/parent trios and 309 affected child/parent duos have been enrolled to date for genetic association studies. Subsets of the patients have also been enrolled for studies assessing development, brain imaging, and neurocognitive outcomes. The study recruited two major ethnic groups, with 45.9% Hispanics of Mexican descent and 36.2% North American Caucasians of European descent. The remaining patients are African-American, South and Central American, Native American, and Asian. Studies of this group of patients have already discovered distinct corpus callosum morphology and neurocognitive deficits that associate with MM. We have identified maternal MTHFR 667T allele as a risk factor for MM. In addition, we also found that several genes for glucose transport and metabolism are potential risk factors for MM. CONCLUSIONS: The enrolled patient population provides a valuable resource for elucidating the disease characteristics and mechanisms for MM development.

Association of self-reported physical activity and performance in the physical fitness assessment among Airmen

The U.S. Air Force, as with the other branches of military services, has physical fitness standards imposed on their personnel. These standards ensure a healthy and fit combat force. To meet these standards, Airmen have to maintain a certain level of physical activity in their lifestyle. Objective. This was a cross sectional (prevalence) study to evaluate the association of Airmen's self-reported physical activity and their performance in the Air Force Physical Fitness Assessment in 2007. Methods. The self-reported physical activity data were obtained from the Air Force Web Health Assessment (AF WEB HA), a web-based health questionnaire completed by the Airmen during their annual Preventive Health Assessment. The physical activity levels were categorized as having met or not having met the Centers for Disease Control and Prevention (CDC) and the American College of Sports Medicine (ACSM) physical activity recommendations. Physical Fitness scores were collected from the Air Force Fitness Management System (AFFMS), a repository of physical fitness test data. Results. There were 49,029 Airmen who answered the AF WEB HA in 2007 and also took their physical fitness test. 94.4% (n = 46,304) of Airmen met the recommended physical activity guidelines and 79.9% (n = 39,178) passed the fitness test. Total Airmen who both met the physical activity recommendations and passed the fitness test was 75.6% (n = 37,088). Airmen who did not meet the activity recommendations and also failed the fitness test totaled 635 or 1.3% of the study group. The Mantel-Haenszel Chi-Square analysis of the data on the activity levels and the physical fitness test relationship was the following χ2 = 18.52, df 1, and p = <0.0001. The Odds Ratio (OR) was 1.22 (95% CI 1.12, 1.34). Conclusion. The study determined that there was a positive association between Airmen's self-reported physical activity and their performance in the physical fitness assessment.^

CLINICAL TRIAL ENROLLMENT IN A MULTIDISCIPLINARY PROSTATE CANCER

Purpose: Clinical oncology trials are hampered by low accrual rates. Less than 5% of adult cancer patients are treated on a clinical trial. We aimed to evaluate clinical trial enrollment in our Multidisciplinary Prostate Cancer Clinic and to assess if a clinical trial initiative, introduced in 2006, increased our trial enrollment.Methods: Prostate cancer patients with non-metastatic disease who were seen in the clinic from 2004 to 2008 were included in the analysis. Men were categorized by whether they were seen before or after the clinical trial enrollment initiative started in 2006. The initiative included posting trial details in the clinic, educating patients about appropriate clinical trial options during the treatment recommendation discussion, and providing patients with documentation of trials offered to them. Univariate and multivariate (MVA) logistic regression analysis evaluated the impact of patient characteristics and the clinical trial initiative on clinical trial enrollment.Results: The majority of the 1,370 men were white (83%), and lived within the surrounding counties or state (69.4%). Median age was 64.2 years. Seventy-three point five percent enrolled in at least one trial and 28.5% enrolled in more than one trial. Sixty-seven percent enrolled in laboratory studies, 18% quality of life studies, 13% novel studies, and 3.7% procedural studies. On MVA, men seen in later years (p < 0.0001) were more likely to enroll in trials. The proportion of men enrolling increased from 38.9% to 84.3% (p<0.0001) after the clinical trial initiative. On MVA, older men (p < 0.0001) were less likely to enroll in clinical trials. There was a trend toward men in the high-risk group being more likely to participate in clinical trials (p = 0.056). There was a second trend for men of Hispanic, Asian, Native American and Indian decent being less likely to participate in clinical trials (p = 0.054).Conclusion: Clinical trial enrollment in the multidisciplinary clinic increased after introduction of a clinical trial initiative. Older men were less likely to enroll in trials. We speculate we achieved high enrollment rates because 1) specific trials are discussed at time of treatment recommendations, 2) we provide a letter documenting offered trials and 3) we introduce patients to the research team at the same clinic visit if they are interested in trial participation.

Association between temperament and physical activity in a population of minority women

Physical activity has been, and remains, a significant public health issue. Thus, increasing physical activity has been identified as a top priority according to Healthy People 2010. Various behavioral variables have been associated with participation in physical activity, including the Type A behavior pattern (TABP). This study was a secondary data analysis of the Women On The Move pilot study data and examined the relationship between Type A behavior with physical activity. The study population consisted of fifty-six (56) adult minority women 40 years of age and above. The Thurstone Activity Scale was adapted for use in this study to measure TABP. Physical activity behavior was measured using an accelerometer (Computer Science Application, [CSA]) and a physical activity diary. All study questions were examined using multiple linear regression analysis. In all analyses age, household income, and level of education were entered as covariates. The results found no association with TABP and exercise or physical activity. More research involving a larger, more active study population is recommended in order to more precisely determine the relationship of TABP and physical activity. ^

Chronic volatile substance abuse among the adult Kickapoo traditional tribe of Texas: Disease and disability profiles, neuropsychosocial consequences, and social implications for treatment

The purpose of this study, based on secondary data from attendees at a substance abuse clinic for the Kickapoo Healing Grounds in Eagle Pass, Texas, is two fold: (1) to elucidate neuro-behavioral performance of volatile substance abusers in the Kickapoo tribe and (2) to determine factors associated with their treatment completion and rehabilitation as measured by their employment at follow-up. Volatile substance abuse (VSA) is associated with a host of neurological manifestations, and secondary prevention or clinical treatment and rehabilitation remains the mainstay of control efforts. Very little is known about VSA in general, and especially among Native American populations. It is anticipated that the results will help determine and assist other tribes and non-tribal substance abuse centers with treatment planning for volatile substance abusers among Native American populations. ^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^