Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

Metabolic syndrome in Mexican American females---prevalence and impact of age, socioeconomic status, and family history of type II diabetes

This thesis presents an analysis of data from Molecular Epidemiology of Type II Diabetes Mellitus in Mexican Americans. The study included 294 families. Among the participating families were 500 Mexican American females aged 19 to 86 who provided information on characteristics such as height, weight, and a variety of biochemical indicators. The research questions for this thesis are: (1) How strong is the association between indicators of the metabolic syndrome in study participants and their family histories of type II diabetes; and (2) How is an individual's family history of type II diabetes, age and socioeconomic status associated with the metabolic syndrome? In this thesis education status of the participants is used as an indicator of socioeconomic status. Answers to these questions are provided through the analysis of women's responses to written questionnaires and biochemical data. ^

Gene-gene interaction and gene-pathway analysis of genome-wide association for schizophrenia

Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^

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. ^

A comparison of adherence with minocycline treatment in Parkinson's disease and rheumatoid arthritis clinical trials

Background: Little is known about the effects on patient adherence when the same study drug is administered in the same dose in two populations with two different diseases in two different clinical trials. The Minocycline in Rheumatoid Arthritis (MIRA) trial and the NIH Exploratory Trials in Parkinson's disease (NET-PD) Futility Study I provide a unique opportunity to do the above and to compare methods measuring adherence. This study may increase understanding of the influence of disease and adverse events on patient adherence and will provide insights to investigators selecting adherence assessment methods in clinical trials of minocycline and other drugs in future.^ Methods: Minocycline adherence by pill count and the effect of adverse events was compared in the MIRA and NET-PD FS1 trials using multivariable linear regression. Within the MIRA trial, agreement between assay and pill count was compared. The association of adverse events with assay adherence was examined using multivariable logistic regression.^ Results: Adherence derived from pill count in the MIRA and NET-PD FS1 trials did not differ significantly. Adverse events potentially related to minocycline did not appear useful to predict minocycline adherence. In the MIRA trial, adherence measured by pill count appears higher than adherence measured by assay. Agreement between pill count and assay was poor (kappa statistic = 0.25).^ Limitations: Trial and disease are completely confounded and hence the independent effect of disease on adherence to minocycline treatment cannot be studied.^ Conclusion: Simple pill count may be preferred over assay in the minocycline clinical trials to measure adherence. Assays may be less sensitive in a clinical setting where appointments are not scheduled in relation to medication administration time, given assays depend on many pharmacokinetic and instrument-related factors. However, pill count can be manipulated by the patient. Another study suggested that self-report method is more sensitive than pill count method in differentiating adherence from non-adherence. An effect of medication-related adverse events on adherence could not be detected.^

Identification of genetic risk factors for cerebellar mutism in pediatric brain tumor patients

Following posterior fossa surgery for resection of childhood medulloblastoma and primitive neuroectodermal tumor (M/PNET), cerebellar mutism (CM) may develop. This is a condition of absent or diminished speech in a conscious patient with no evidence of oral apraxia, which can be accompanied by other symptoms of the posterior fossa syndrome complex, which includes ataxia and hypotonia. Little is known about the etiology. Therefore, we conducted a SNP, gene, and pathway-level analysis to assess the role of host genetic variation on the risk of CM in M/PNET subjects following treatment. Cases (n= 20) and controls (n= 53) were recruited from the Childhood Cancer Epidemiology and Prevention Center, in Houston, TX. DNA samples were genotyped using the Illumina Human 1M Quad SNP chip. Ten pathways were identified from logistic regression used to identify the marginal effect of each SNP on CM risk. The minP test was conducted to identify associations between SNPs categorized to genes and CM risk. Pathways were assessed to determine if there was a significant enrichment of genes in the pathway compared to all other pathways. There were 78 genes that reached the threshold of min P ≤0.05 in 948 genes. The Neurotoxicity pathway was the most significant pathway after adjusting for multiple comparisons (q=0.040 and q=0.005, using Fisher's exact test and a test of proportions, respectively). Most genes within the Neurotoxicity pathway that reached a threshold of minP ≤0.05 were known to have an apoptosis function, possibly inducing neuronal apoptosis in the dentatothalamocortical pathway, and may be important in CM etiology in this population. This is the first study to assess the potential role of genetic risk factors on CM. As an exploratory study, these results should be replicated in a larger sample. ^

Identification of genes associated with quantitative traits involved in cardiovascular disease and lipoprotein metabolism

Cardiovascular disease (CVD) is a threat to public health. It has been reported to be the leading cause of death in United States. The invention of next generation sequencing (NGS) technology has revolutionized the biomedical research. To investigate NGS data of CVD related quantitative traits would contribute to address the unknown etiology and disease mechanism of CVD. NHLBI's Exome Sequencing Project (ESP) contains CVD related phenotypes and their associated NGS exomes sequence data. Initially, a subset of next generation sequencing data consisting of 13 CVD-related quantitative traits was investigated. Only 6 traits, systolic blood pressure (SBP), diastolic blood pressure (DBP), height, platelet counts, waist circumference, and weight, were analyzed by functional linear model (FLM) and 7 currently existing methods. FLM outperformed all currently existing methods by identifying the highest number of significant genes and had identified 96, 139, 756, 1162, 1106, and 298 genes associated with SBP, DBP, Height, Platelet, Waist, and Weight respectively. ^

Circadian rhythm profiles in porcine ICU subjects

Purpose: To explore the natural trajectory of circadian rhythms of sedation requirement, core body temperature (CBT), pulmonary mechanics (PM), and gas exchange (GE) in mechanically ventilated swine, as these variables affect the duration of mechanical ventilation. ^ Design: A secondary analysis to describe and compare circadian rhythms of study variables in swine mechanically ventilated for ≤ 7 days. ^ Setting: Porcine Intensive Care Unit (ICU).^ Sample: Six male swine. ^ Methods: Sedation requirements were recorded hourly and the CBT, PM and GE variables were sampled every 1 s – 1 min for ≤ 7 days. The data sets for each pig with > 5 days ICU length of stay were divided into one section representing the first 3 days and one section representing subsequent days. The Lomb periodogram was used to estimate the circadian time period for each variable, and cosinor analysis with the estimated time period to obtain amplitude and mesor. Circadian to ultradian bandpower ratio to assess rhythm quality and stability over time and goodness-of-fit index to describe biological significance of a rhythm were used. Together, these two parameters were used to define rhythm robustness over time. The masking effect of sedation as a potential confounder of the circadian rhythms of CBT, PM, and GE was explored, and circadian rhythm profiles of CBT of pigs in the ICU setting were compared with those of the same pigs in the ambulatory setting. ^ Results: All pigs had significant rhythms in CBT, respiratory rate, and peripheral oxygen saturation across ICU data sets. Healthier pigs had more robust rhythms of study variables over time. Sedation did not appear to mask the circadian rhythms of CBT, PM, and GE. The circadian rhythm of CBT was less robust in the ICU setting than in the ambulatory setting. ^ Conclusions: Individual subject observations provided preliminary evidence that robustness of rhythms varies with subject acuity. Comparison of profiles of circadian rhythms among ICU subjects with similar acuity and disease processes is warranted to determine if the profiles in the present study are reproducible. Identification of consistent patterns may provide insight into subject morbidity and timing of such therapeutic interventions as weaning from mechanical ventilation. ^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

Developing the follow-up schedules for women with breast cancer

Background: The follow-up care for women with breast cancer requires an understanding of disease recurrence patterns and the follow-up visit schedule should be determined according to the times when the recurrence are most likely to occur, so that preventive measure can be taken to avoid or minimize the recurrence. Objective: To model breast cancer recurrence through stochastic process with an aim to generate a hazard function for determining a follow-up schedule. Methods: We modeled the process of disease progression as the time transformed Weiner process and the first-hitting-time was used as an approximation of the true failure time. The women's "recurrence-free survival time" or a "not having the recurrence event" is modeled by the time it takes Weiner process to cross a threshold value which represents a woman experiences breast cancer recurrence event. We explored threshold regression model which takes account of covariates that contributed to the prognosis of breast cancer following development of the first-hitting time model. Using real data from SEER-Medicare, we proposed models of follow-up visits schedule on the basis of constant probability of disease recurrence between consecutive visits. Results: We demonstrated that the threshold regression based on first-hitting-time modeling approach can provide useful predictive information about breast cancer recurrence. Our results suggest the surveillance and follow-up schedule can be determined for women based on their prognostic factors such as tumor stage and others. Women with early stage of disease may be seen less frequently for follow-up visits than those women with locally advanced stages. Our results from SEER-Medicare data support the idea of risk-controlled follow-up strategies for groups of women. Conclusion: The methodology we proposed in this study allows one to determine individual follow-up scheduling based on a parametric hazard function that incorporates known prognostic factors.^

Retrospective analysis of Methicillin-Resistant Staphylococcus Aureus (MRSA) skin and Soft-Tissue Infections (SSTI) in a university hospital emergency department (ED)

Study Objective: Identify the most frequent risk factors of Community Acquired-MRSA (CA-MRSA) Skin and Soft-tissue Infections (SSTIs) using a case series of patients and characterize them by age, race/ethnicity, gender, abscess location, druguse and intravenous drug-user (IVDU), underlying medical conditions, homelessness, treatment resistance, sepsis, those whose last healthcare visit was within the last 12 months, and describe the susceptibility pattern from this central Texas population that have come into the University Medical Center Brackenridge (UMCB) Emergency Department (ED). ^ Methods: This study was a retrospective case-series medical record review involving a convenience sample of patients in 2007 from an urban public hospital's ED in Texas that had a SSTI that tested positive for MRSA. All positive MRSA cultures underwent susceptibility testing to determine antibiotic resistance. The demographic and clinical variables that were independently associated with MRSA were determined by univariate and multivariate analysis using logistic regression to calculate odds ratios (OR), 95% confidence intervals, and significance (p≤ 0.05). ^ Results: In 2007, there were 857 positive MRSA cultures. The demographics were: males 60% and females 40%, with the average age of 36.2 (std. dev. =13) the study population consisted of non-Hispanic white (42%), Hispanics (38%), and non-Hispanic black (18.8%). Possible risk factors addressed included using recreational drugs (not including IVDU) (27%) homelessness (13%), diabetes status (12.6%) or having an infectious disease, and IVDU (10%). The most frequent abscess location was the leg (26.6%), followed by the arm and torso (both 13.7%). Eighty-three percent of patients had one prominent susceptibility pattern that had a susceptibility rate for the following antibiotics: trimethoprim/sulfamethoxazole (TMP-SMX) and vancomycin had 100%, gentamicin 99%, clindamycin 96%, tetracycline 96%, and erythromycin 56%. ^ Conclusion: The ED is becoming an important area for disease transmission between the sterile hospital environment and the outside environment. As always, it is important to further research in the ED in an effort to better understand MRSA transmission and antibiotic resistance, as well as to keep surveillance for the introduction of new opportunistic pathogens into the population. ^

Instrumental variable method for the causal relationship between soluble receptor for advanced glycation end-products (sRAGE) and risk of pancreatic cancer

This thesis project is motivated by the potential problem of using observational data to draw inferences about a causal relationship in observational epidemiology research when controlled randomization is not applicable. Instrumental variable (IV) method is one of the statistical tools to overcome this problem. Mendelian randomization study uses genetic variants as IVs in genetic association study. In this thesis, the IV method, as well as standard logistic and linear regression models, is used to investigate the causal association between risk of pancreatic cancer and the circulating levels of soluble receptor for advanced glycation end-products (sRAGE). Higher levels of serum sRAGE were found to be associated with a lower risk of pancreatic cancer in a previous observational study (255 cases and 485 controls). However, such a novel association may be biased by unknown confounding factors. In a case-control study, we aimed to use the IV approach to confirm or refute this observation in a subset of study subjects for whom the genotyping data were available (178 cases and 177 controls). Two-stage IV method using generalized method of moments-structural mean models (GMM-SMM) was conducted and the relative risk (RR) was calculated. In the first stage analysis, we found that the single nucleotide polymorphism (SNP) rs2070600 of the receptor for advanced glycation end-products (AGER) gene meets all three general assumptions for a genetic IV in examining the causal association between sRAGE and risk of pancreatic cancer. The variant allele of SNP rs2070600 of the AGER gene was associated with lower levels of sRAGE, and it was neither associated with risk of pancreatic cancer, nor with the confounding factors. It was a potential strong IV (F statistic = 29.2). However, in the second stage analysis, the GMM-SMM model failed to converge due to non- concaveness probably because of the small sample size. Therefore, the IV analysis could not support the causality of the association between serum sRAGE levels and risk of pancreatic cancer. Nevertheless, these analyses suggest that rs2070600 was a potentially good genetic IV for testing the causality between the risk of pancreatic cancer and sRAGE levels. A larger sample size is required to conduct a credible IV analysis.^

External validation study of a clinical prediction rule for ambulation outcomes after traumatic spinal cord injury

The main objective of this study was to determine the external validity of a clinical prediction rule developed by the European Multicenter Study on Human Spinal Cord Injury (EM-SCI) to predict the ambulation outcomes 12 months after traumatic spinal cord injury. Data from the North American Clinical Trials Network (NACTN) data registry with approximately 500 SCI cases were used for this validity study. The predictive accuracy of the EM-SCI prognostic model was evaluated using calibration and discrimination based on 231 NACTN cases. The area under the receiver-operating-characteristics curve (ROC) curve was 0.927 (95% CI 0.894 – 0.959) for the EM-SCI model when applied to NACTN population. This is lower than the AUC of 0.956 (95% CI 0.936 – 0.976) reported for the EM-SCI population, but suggests that the EM-SCI clinical prediction rule distinguished well between those patients in the NACTN population who were able to achieve independent ambulation and those who did not achieve independent ambulation. The calibration curve suggests that higher the prediction score is, the better the probability of walking with the best prediction for AIS D patients. In conclusion, the EM-SCI clinical prediction rule was determined to be generalizable to the adult NACTN SCI population.^

Clostridium difficile infection (CDI) in HIV-positive patients

The main aim of this study was to look at the association of Clostridium difficile infection (CDI) and HIV. A secondary goal was to look at the trend of CDI-related deaths in Texas from 1999-2011. To evaluate the coinfection of CDI and HIV, we looked at 2 datasets provided by CHS-TDSHS, for 13 years of study period from 1999-2011: 1) Texas death certificate data and 2) Texas hospital discharge data. An ancillary source of data was national level death data from CDC. We did a secondary data analysis and reported the age-adjusted death rates (mortality) and hospital discharge frequencies (morbidity) for CDI, HIV and for CDI+HIV coinfection.^ Since the turn of the century, CDI has reemerged as an important public health challenge due to the emergence of hypervirulent epidemic strains. From 1999-2011, there has been a significant upward trend in CDI-related death rates; in the state of Texas alone, CDI mortality rate has increased 8.7 fold in this time period at the rate of 0.2 deaths per year per 100,000 individuals. On the contrary, mortality due to HIV has decreased by 46% and has been trending down. The demographic groups in Texas with the highest CDI mortality rates were elderly aged 65+, males, whites and hospital inpatients. The epidemiology of C. difficile has changed in such a way that it is not only staying confined to these traditional high-risk groups, but is also being increasingly reported in low-risk populations such as healthy people in the community (community acquired C. difficile), and most recently immunocompromised patients. Among the latter, HIV can worsen the adverse health outcomes of CDI and vice versa. In patients with CDI and HIV coinfection, higher mortality and morbidity was found in young & middle-aged adults, blacks and males, the same demographic population that is at higher risk for HIV. As with typical CDI, the coinfection was concentrated in the hospital inpatients. Of all the CDI-related deaths in USA from 1999-2010, in the 25-44 year age group, 13% had HIV infection. Of all CDI-related inpatient hospital discharges in Texas from 1999-2011, in patients 44 years and younger, 17% had concomitant HIV infection. Therefore, HIV is a possible novel emerging risk factor for CDI.^

Prevalence of Staphylococcus aureus colonization among high-risk HIV populations

Staphylococcus aureus is a common microorganism in humans, typically colonizing the nasopharynx, skin and other mucosal surfaces. It is among the most frequent causes of clinically-significant bacterial infections accounting for increased morbidity and mortality among individuals with HIV/AIDS. Evidence of higher colonization rates among high-risk HIV populations have been observed however, prevalence estimates have varied. Additionally, behavioral, biological, and/or environmental factors that may account for these high colonization rates are not understood. Previous literature on clinic-based surveys were subject to considerable biases. Additionally, representative samples of high-risk HIV populations were difficult to obtain due in part to an underrepresentation of individuals who may not regularly obtain health care. ^ The main objective of this project is to determine the prevalence of methicillin-sensitive S. aureus (MSSA) and methicillin-resistant (MRSA) nasal colonization in two populations: 1) men who have sex with men (MSM) and 2) injection drug users (IDU). Both of these populations are included in the third round of the National HIV Behavioral Surveillance System (NHBS) in Houston, Texas. ^ In the NHBS-MSM3 study, logistic regression was used to report odds ratios and 95% confidence intervals (CI). For the NHBS-IDU3 study, to account for the lack of independence between samples, the method of generalized estimating equations was utilized to report adjusted odds ratios and 95% CI. The NHBS-MSM3 study enrolled 202 participants with a MSSA colonization rate of 26.7% and MRSA rate of 3%. In the NHBS-IDU3 study, 18.4% were nasally colonized with MSSA and 5.7% were nasally colonized with MRSA. Among the NHBS-MSM3 population, high-risk sexual practices were associated with colonization. For the NHBS-IDU3 population, age, marital status, employment status, and the presence of scabs, were associated with colonization status when controlling for size of recruitment network. In multivariate GEE analyses, the use of antiretroviral medications and age remained significantly associated with S. aureus nasal colonization when controlling for size of recruitment network and gender. In both studies, a significantly higher than expected S. aureus and MRSA colonization rate was observed as compared to colonization rates described for the general population. However, these estimates were moderate in comparison to reported clinic-based MSM and IDU S. aureus colonization findings. This study validates substantial prevalence differences and biases that may exist with data collected from clinic-based MSM and IDU. The prevalence of MSSA and MRSA nasal colonization did not differ significantly with respect to HIV status among NHBS-MSM3/NHBS-IDU3 participants. Continued examination on the effects of S. aureus colonization and infection should be examined longitudinally to confirm additional community-based determinants in populations that are disproportionately affected.^