A spatial-temporal approach to surveillance of prostate cancer disparities in population subgroups

BACKGROUND: Prostate cancer mortality disparities exist among racial/ethnic groups in the United States, yet few studies have explored the spatiotemporal trend of the disease burden. To better understand mortality disparities by geographic regions over time, the present study analyzed the geographic variations of prostate cancer mortality by three Texas racial/ethnic groups over a 22-year period. METHODS: The Spatial Scan Statistic developed by Kulldorff et al was used. Excess mortality was detected using scan windows of 50% and 90% of the study period and a spatial cluster size of 50% of the population at risk. Time trend was analyzed to examine the potential temporal effects of clustering. Spatial queries were used to identify regions with multiple racial/ethnic groups having excess mortality. RESULTS: The most likely area of excess mortality for blacks occurred in Dallas-Metroplex and upper east Texas areas between 1990 and 1999; for Hispanics, in central Texas between 1992 and 1996: and for non-Hispanic whites, in the upper south and west to central Texas areas between 1990 and 1996. Excess mortality persisted among all racial/ethnic groups in the identified counties. The second scan revealed that three counties in west Texas presented an excess mortality for Hispanics from 1980-2001. Many counties bore an excess mortality burden for multiple groups. There is no time trend decline in prostate cancer mortality for blacks and non-Hispanic whites in Texas. CONCLUSION: Disparities in prostate cancer mortality among racial/ethnic groups existed in Texas. Central Texas counties with excess mortality in multiple subgroups warrant further investigation.

The coordinated approach to child health in underserved population (CATCH UP) curriculum: A quantitative evaluation of an innovative preschool obesity prevention program

Obesity has been on the rise in the United States over the last 30 years for all populations, including preschoolers. The purpose of the project was to develop an observation tool to measure physical activity levels in preschool children and use the tool in a pilot test of the CATCH UP curriculum at two Head Start Centers in Houston. Pretest and posttest interobserver agreements were all above 0.60 for physical activity level and physical activity type. Preschoolers spent the majority of their time in light physical activity (75.33% pretest, 87.77% posttest), and spent little time in moderate to vigorous physical activity (MVPA) (24.67% pretest, 12.23% posttest). Percent time spent in MVPA decreased significantly pretest to posttest from (F=5.738, p=0.043). While the pilot testing of the CATCH UP curriculum did not show an increase in MVPA, the SOFIT-P tool did show promising results as being a new method for collecting physical activity level data for preschoolers. Once the new tool has undergone more reliability and validity testing, it could allow for a more convenient method of collecting physical activity levels for preschoolers. ^

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.

Sequential updating via dynamic hierarchical models: A Bayesian approach to longitudinal data analysis

Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^

Development and validation of the Neuro Symptom Inventory in the primary brain tumor patient population

Symptoms has been shown to predict quality of life, treatment course and survival in solid tumor patients. Currently, no instrument exists that measures both cancer-related symptoms and the neurologic symptoms that are unique to persons with primary brain tumors (PBT). The aim of this study was to develop and validate an instrument to measure symptoms in patients who have PBT. A conceptual analysis of symptoms and symptom theories led to defining the symptoms experience as the perception of the frequency, intensity, distress, and meaning that occurs as symptoms are produced, perceived, and expressed. The M.D. Anderson Symptom Inventory (MDASI) measures both symptoms and how they interfere with daily functioning in patients with cancer, which is similar to the situational meaning defined in the analysis. A list of symptoms pertinent to the PBT population was added to the core MDASI and reviewed by a group of experts for validity. As a result, 18 items were added to the core MDASI (the MDASI-BT) for the next phase of instrument development, establishing validity and reliability through a descriptive, cross-sectional approach with PBT patients. Data were collected with a patient completed demographic data sheet, an investigator completed clinician checklist, and the MDASI-BT. Analysis evaluated the reliability and validity of the MDASI-BT in PBT patients. Data were obtained from 201 patients. The number of items was reduced to 22 by evaluation of symptom severity as well as cluster analysis. Regression analysis showed more than half (56%) of the variability in symptom severity was explained by the brain tumor module items. Factor analysis confirmed that the 22 item MDASI-BT measured six underlying constructs: (a) affective; (b) cognitive; (c) focal neurologic deficits; (d) constitutional symptoms; (e) treatment-related symptoms; and (f) gastrointestinal symptoms. The MDASI-BT was sensitive to disease severity and if the patient was hospitalized. The MDASI-BT is the first instrument to measure symptoms in PBT patients that has demonstrated reliability and validity. It is the first step in a program of research to evaluate the occurrence of symptoms and plan and evaluate interventions for PBT patients. ^

Toxics Release Inventory facilities and childhood cancer: Geographic information systems based approach

Purpose. To examine the association between living in proximity to Toxics Release Inventory (TRI) facilities and the incidence of childhood cancer in the State of Texas. ^ Design. This is a secondary data analysis utilizing the publicly available Toxics release inventory (TRI), maintained by the U.S. Environmental protection agency that lists the facilities that release any of the 650 TRI chemicals. Total childhood cancer cases and childhood cancer rate (age 0-14 years) by county, for the years 1995-2003 were used from the Texas cancer registry, available at the Texas department of State Health Services website. Setting: This study was limited to the children population of the State of Texas. ^ Method. Analysis was done using Stata version 9 and SPSS version 15.0. Satscan was used for geographical spatial clustering of childhood cancer cases based on county centroids using the Poisson clustering algorithm which adjusts for population density. Pictorial maps were created using MapInfo professional version 8.0. ^ Results. One hundred and twenty five counties had no TRI facilities in their region, while 129 facilities had at least one TRI facility. An increasing trend for number of facilities and total disposal was observed except for the highest category based on cancer rate quartiles. Linear regression analysis using log transformation for number of facilities and total disposal in predicting cancer rates was computed, however both these variables were not found to be significant predictors. Seven significant geographical spatial clusters of counties for high childhood cancer rates (p<0.05) were indicated. Binomial logistic regression by categorizing the cancer rate in to two groups (<=150 and >150) indicated an odds ratio of 1.58 (CI 1.127, 2.222) for the natural log of number of facilities. ^ Conclusion. We have used a unique methodology by combining GIS and spatial clustering techniques with existing statistical approaches in examining the association between living in proximity to TRI facilities and the incidence of childhood cancer in the State of Texas. Although a concrete association was not indicated, further studies are required examining specific TRI chemicals. Use of this information can enable the researchers and public to identify potential concerns, gain a better understanding of potential risks, and work with industry and government to reduce toxic chemical use, disposal or other releases and the risks associated with them. TRI data, in conjunction with other information, can be used as a starting point in evaluating exposures and risks. ^

Youth population's health issues in Comal County, Texas

This study assesses adolescent's health issues in Comal County, TX. Adolescents are defined as youth between the ages of 12 to 17 years of age, who resided in Comal County during the time period of 2000 to 2007. The analysis focused on high risk behaviors including use of gateway drugs—tobacco and alcohol; illegal substance use; and reproductive health related indicators, including sexual activity, sexually transmitted diseases, and pregnancy. This study is based on the primary and secondary data collected as part of the 2008 Comal County Community Assessment. It compares findings from the primary data sources to extant data from four secondary data sources including: (1) The Centers for Disease Control & Prevention (national) Healthy People 2010; (2) The Centers for Disease Control & Prevention, Youth Risk Behavior Surveillance Survey, 2007; (3) The Texas Department of State Health Services, 2000 to 2007; and The Pride Survey (Local and Statewide). The methods are drawn from the literature on "rapid epidemiologic appraisal" (Annett H. & Rifkin S. B., 1988). The study focus on corroborating the perceptions, subjective concerns, opinions and beliefs of the Comal County key stakeholders and community participants with qualitative and quantitative indicators of health and well being. The value of this approach is to inform community leaders using a public health perspective and evidence in their decisions about priority setting and resources allocation activities for prevention of high risk behaviors and promotion of adolescent health and well being. ^

Dynamic population coding in primary visual cortex

More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this 'connectome' approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. ^ First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex's functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. ^ Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy. ^

A categorical data analysis approach to estimation of demographic characteristics for Texas county populations

The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

Thrombolytic therapy for acute myocardial infarction: A cohort study to evaluate a selective approach to invasive diagnosis and therapy. The Corpus Christi Heart Project

Coronary perfusion with thrombolytic therapy and selective reperfusion by percutaneous transluminal coronary angioplasty (PTCA) were examined in the Corpus Christi Heart Project, a population-based surveillance program for hospitalized acute myocardial infarction (MI) patients in a biethnic community of Mexican-Americans (MAs) and non-Hispanic whites (NHWs). Results were based on 250 (12.4%) patients who received thromobolytic therapy in a cohort of 2011 acute MI cases. Out of these 107 (42.8%) underwent PTCA with a mean follow-up of 25 months. There were 186 (74.4%) men and 64 (25.6%) women; 148 (59.2%) were NHWs, 86 (34.4%) were MAs. Thrombolysis and PTCA were performed less frequently in women than in men, and less frequently in MAs than in NHWs.^ According to the coronary reperfusion interventions used, patients were divided in two groups, those that received no-PTCA (57.2%) and the other that underwent PTCA (42.8%) after thrombolysis. The case-fatality rate was higher in no-PTCA patients than in the PTCA (7.7% versus 5.6%), as was mortality at one year (16.2% versus 10.5%). Reperfusion was successful in 48.0% in the entire cohort and (51.4% versus 45.6%) in the PTCA and no-PTCA groups. Mortality in the successful reperfusion patients was 5.0% compared to 22.3% in the unsuccessful reperfusion group (p = 0.00016, 95% CI: 1.98-11.6).^ Cardiac catheterization was performed in 86.4% thrombolytic patients. Severe stenosis ($>$75%) obstruction was present most commonly in the left descending artery (52.8%) and in the right coronary artery (52.8%). The occurrence of adverse in-hospital clinical events was higher in the no-PTCA as compared to the PTCA and catheterized patients with the exception of reperfusion arrythmias (p = 0.140; Fisher's exact test p = 0.129).^ Cox regression analysis was used to study the relationship between selected variables and mortality. Apart from successful reperfusion, age group (p = 0.028, 95% CI: 2.1-12.42), site of acute MI index (p = 0.050) and ejection-fraction (p = 0.052) were predictors of long-term survival. The ejection-fraction in the PTCA group was higher than (median 78% versus 53%) in the no-PTCA group. Assessed by logistic regression analysis history of high cholesterol ($>$200mg/dl) and diabetes mellites did have significant prognostic value (p = 0.0233; p = 0.0318) in long-term survival irrespective of treatment status.^ In conclusion, the results of this study support the idea that the use of PTCA as a selective intervention following thrombolysis improves survival of patients with acute MI. The use of PTCA in this setting appears to be safe. However, we can not exclude the possibility that some of these results may have occurred due to the exclusion from PTCA of high risk patients (selection bias). ^

MEASURING THE EFFECT OF ILLNESS ON THE EXPECTED REMAINING SERVICE TIME FOR THE ACTIVE DUTY ARMY: A LIFE TABLE APPROACH

A life table methodology was developed which estimates the expected remaining Army service time and the expected remaining Army sick time by years of service for the United States Army population. A measure of illness impact was defined as the ratio of expected remaining Army sick time to the expected remaining Army service time. The variances of the resulting estimators were developed on the basis of current data. The theory of partial and complete competing risks was considered for each type of decrement (death, administrative separation, and medical separation) and for the causes of sick time.^ The methodology was applied to world-wide U.S. Army data for calendar year 1978. A total of 669,493 enlisted personnel and 97,704 officers were reported on active duty as of 30 September 1978. During calendar year 1978, the Army Medical Department reported 114,647 inpatient discharges and 1,767,146 sick days. Although the methodology is completely general with respect to the definition of sick time, only sick time associated with an inpatient episode was considered in this study.^ Since the temporal measure was years of Army service, an age-adjusting process was applied to the life tables for comparative purposes. Analyses were conducted by rank (enlisted and officer), race and sex, and were based on the ratio of expected remaining Army sick time to expected remaining Army service time. Seventeen major diagnostic groups, classified by the Eighth Revision, International Classification of Diseases, Adapted for Use In The United States, were ranked according to their cumulative (across years of service) contribution to expected remaining sick time.^ The study results indicated that enlisted personnel tend to have more expected hospital-associated sick time relative to their expected Army service time than officers. Non-white officers generally have more expected sick time relative to their expected Army service time than white officers. This racial differential was not supported within the enlisted population. Females tend to have more expected sick time relative to their expected Army service time than males. This tendency remained after diagnostic groups 580-629 (Genitourinary System) and 630-678 (Pregnancy and Childbirth) were removed. Problems associated with the circulatory system, digestive system and musculoskeletal system were among the three leading causes of cumulative sick time across years of service. ^

The application of principal component analysis on human development indicators: Temporal approach from 1999 to 2010

Background and Objective. Ever since the human development index was published in 1990 by the United Nations Development Programme (UNDP), many researchers started searching and corporative studying for more effective methods to measure the human development. Published in 1999, Lai’s “Temporal analysis of human development indicators: principal component approach” provided a valuable statistical way on human developmental analysis. This study presented in the thesis is the extension of Lai’s 1999 research. ^ Methods. I used the weighted principal component method on the human development indicators to measure and analyze the progress of human development in about 180 countries around the world from the year 1999 to 2010. The association of the main principal component obtained from the study and the human development index reported by the UNDP was estimated by the Spearman’s rank correlation coefficient. The main principal component was then further applied to quantify the temporal changes of the human development of selected countries by the proposed Z-test. ^ Results. The weighted means of all three human development indicators, health, knowledge, and standard of living, were increased from 1999 to 2010. The weighted standard deviation for GDP per capita was also increased across years indicated the rising inequality of standard of living among countries. The ranking of low development countries by the main principal component (MPC) is very similar to that by the human development index (HDI). Considerable discrepancy between MPC and HDI ranking was found among high development countries with high GDP per capita shifted to higher ranks. The Spearman’s rank correlation coefficient between the main principal component and the human development index were all around 0.99. All the above results were very close to outcomes in Lai’s 1999 report. The Z test result on temporal analysis of main principal components from 1999 to 2010 on Qatar was statistically significant, but not on other selected countries, such as Brazil, Russia, India, China, and U.S.A.^ Conclusion. To synthesize the multi-dimensional measurement of human development into a single index, the weighted principal component method provides a good model by using the statistical tool on a comprehensive ranking and measurement. Since the weighted main principle component index is more objective because of using population of nations as weight, more effective when the analysis is across time and space, and more flexible when the countries reported to the system has been changed year after year. Thus, in conclusion, the index generated by using weighted main principle component has some advantage over the human development index created in UNDP reports.^

Exploration of genetic susceptibility to pancreatic cancer: A GWAS approach

Pancreatic cancer is the 4th most common cause for cancer death in the United States, accompanied by less than 5% five-year survival rate based on current treatments, particularly because it is usually detected at a late stage. Identifying a high-risk population to launch an effective preventive strategy and intervention to control this highly lethal disease is desperately needed. The genetic etiology of pancreatic cancer has not been well profiled. We hypothesized that unidentified genetic variants by previous genome-wide association study (GWAS) for pancreatic cancer, due to stringent statistical threshold or missing interaction analysis, may be unveiled using alternative approaches. To achieve this aim, we explored genetic susceptibility to pancreatic cancer in terms of marginal associations of pathway and genes, as well as their interactions with risk factors. We conducted pathway- and gene-based analysis using GWAS data from 3141 pancreatic cancer patients and 3367 controls with European ancestry. Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Using the logistic kernel machine (LKM) test, we analyzed 17906 genes defined by University of California Santa Cruz (UCSC) database. Using the likelihood ratio test (LRT) in a logistic regression model, we analyzed 177 pathways and 17906 genes for interactions with risk factors in 2028 pancreatic cancer patients and 2109 controls with European ancestry. After adjusting for multiple comparisons, six pathways were marginally associated with risk of pancreatic cancer ( P < 0.00025): Fc epsilon RI signaling, maturity onset diabetes of the young, neuroactive ligand-receptor interaction, long-term depression (Ps < 0.0002), and the olfactory transduction and vascular smooth muscle contraction pathways (P = 0.0002; Nine genes were marginally associated with pancreatic cancer risk (P < 2.62 × 10−5), including five reported genes (ABO, HNF1A, CLPTM1L, SHH and MYC), as well as four novel genes (OR13C4, OR 13C3, KCNA6 and HNF4 G); three pathways significantly interacted with risk factors on modifying the risk of pancreatic cancer (P < 2.82 × 10−4): chemokine signaling pathway with obesity ( P < 1.43 × 10−4), calcium signaling pathway (P < 2.27 × 10−4) and MAPK signaling pathway with diabetes (P < 2.77 × 10−4). However, none of the 17906 genes tested for interactions survived the multiple comparisons corrections. In summary, our current GWAS study unveiled unidentified genetic susceptibility to pancreatic cancer using alternative methods. These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer, once confirmed, will shed promising light on the prevention and treatment of this disease. ^

Something real: A social marketing approach to smoking prevention among Montevideo youth

Uruguay has some of the strictest tobacco-control laws in Latin America. Despite this, youth smoking rates in Uruguay are amongst the highest in South America. Thus, it is important to identify strategies to prevent youth smoking in Uruguay. The current qualitative research study sought to identify intrapersonal and socioenvironmental factors that are associated with smoking among middle school youth in Uruguay. It also sought to develop potential prevention strategies and media messages that would resonate with youth for a social media campaign. The study was grounded in social cognitive theory and the theory of reasoned action/planned behavior, among other behavioral science theories; anthropological perspectives were also considered. To achieve these goals, 29 group and individual structured interviews were conducted in two private middle schools catering to lower and higher SES youth in Montevideo, Uruguay during the summer of 2012. One hundred and three study participants, including students, parents, and teachers, were interviewed. The structured interviews were recorded, transcribed, translated, back translated, coded and analyzed. The study findings show that positive attitudes towards smoking (i.e. to be seen, to increase status, to ensure women's equality, to looking old, and to service as a rite of passage), delinquent behavior (i.e. transgression/deviant behavior), social norms that support smoking (i.e. peer pressure and modeling, group membership/sense of belonging, parental modeling, and family support), easy access and availability to tobacco (i.e. retails stores) were factors associated with youth smoking. Potential protective factors may include parental support, negative attitudes towards smoking, sports/music, and smoke-free environments. Because study participants are accustomed to government-sponsored strong countermarketing graphic imaging, study participants selected even stronger images and messages as the preferred way to receive tobacco prevention messages. Something Real ("Algo Real") was a theme that resonated with the participants and chosen as the name for the proposed campaign. This campaign was designed as a multiple component intervention that included mass, school base, and family based strategies to prevent tobacco use. Some intervention materials specific to these intervention components were developed to target relevant intrapersonal and socioenvironmental factors identified above. These materials will be tested in future pilot studies and larger scale evaluation with this population, outside the scope of this dissertation. ^