Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^

A comparison of worker risk of injury while working on fully automated side loaders and other residential collection trucks at a large solid waste collection company

The study aim was to determine whether using automated side loader (ASL) trucks in higher proportions compared to other types of trucks for residential waste collection results in lower injury rates (from all causes). The primary hypothesis was that the risk of injury to workers was lower for those who work with ASL trucks than for workers who work with other types of trucks used in residential waste collection. To test this hypothesis, data were collected from one of the nation’s largest companies in the solid waste management industry. Different local operating units (i.e. facilities) in the company used different types of trucks to varying degrees, which created a special opportunity to examine refuse collection injuries and illnesses and the risk reduction potential of ASL trucks.^ The study design was ecological and analyzed end-of-year data provided by the company for calendar year 2007. During 2007, there were a total of 345 facilities which provided residential services. Each facility represented one observation.^ The dependent variable – injury and illness rate, was defined as a facility’s total case incidence rate (TCIR) recorded in accordance with federal OSHA requirements for the year 2007. The TCIR is the rate of total recordable injury and illness cases per 100 full-time workers. The independent variable, percent of ASL trucks, was calculated by dividing the number of ASL trucks by the total number of residential trucks at each facility.^ Multiple linear regression models were estimated for the impact of the percent of ASL trucks on TCIR per facility. Adjusted analyses included three covariates: median number of hours worked per week for residential workers; median number of months of work experience for residential workers; and median age of residential workers. All analyses were performed with the statistical software, Stata IC (version 11.0).^ The analyses included three approaches to classifying exposure, percent of ASL trucks. The first approach included two levels of exposure: (1) 0% and (2) >0 - <100%. The second approach included three levels of exposure: (1) 0%, (2) ≥ 1 - < 100%, and (3) 100%. The third approach included six levels of exposure to improve detection of a dose-response relationship: (1) 0%, (2) 1 to <25%, (3) 25 to <50%, (4) 50 to <75%, (5) 75 to <100%, and (6) 100%. None of the relationships between injury and illness rate and percent ASL trucks exposure levels was statistically significant (i.e., p<0.05), even after adjustment for all three covariates.^ In summary, the present study shows that there is some risk reduction impact of ASL trucks but not statistically significant. The covariates demonstrated a varied yet more modest impact on the injury and illness rate but again, none of the relationships between injury and illness rate and the covariates were statistically significant (i.e., p<0.05). However, as an ecological study, the present study also has the limitations inherent in such designs and warrants replication in an individual level cohort design. Any stronger conclusions are not suggested.^

Spit & lies: Does social desirability predict smoking cessation success?

This study examines the role of socially desirable responding (SDR) on smoking cessation program success. SDR is the tendency for individuals to give responses that put themselves in what they perceive to be a socially desirable light. ^ This research is a secondary analysis of data from Project Cognition, a study designed to examine the associations between performance on cognitive assessments and subsequent relapse to smoking. Adult smokers (N=183) were recruited from the greater Houston area to participate in the smoking cessation study. In this portion of the research, participants' smoking status was assessed on their quit day (QD), one week after QD, and four weeks after QD. Primary outcome measures were self-reported relapse, true cessation determined by biological measure, discrepancies between self-reported smoking status and biological assessments of smoking, and dropping out. ^ Primary predictor measures were the Balanced Inventory of Desirable Responding (BIDR) and self-reported motivation to quit smoking. The BIDR is a 40-item questionnaire that assesses Self-deceptive Enhancement (SDE; the tendency to give self-reports that are honest but positively biased) and Impression Management (IM; deliberate self-presentation to an audience). Scores were used to create a dichotomous BIDR total score group variable, a dichotomous SDE group variable, and a dichotomous IM group variable. Participants at one standard deviation above the mean were in the "high" group, and scores below one standard deviation were in the "normal" group. In addition, age, race, and gender were analyzed as covariates. ^ The overall findings of this study suggest that in the general population BIDR informs participants' self-reports and the IM and SDR subscales inform participants' behavior. BIDR predicted self-reported relapse in the general population and trended toward indicating that a participant will claim smoking cessation success when biological measures indicate otherwise. SDE interacted with motivation to predict biologically verified cessation success. There was no main effect for BIDR, IM, or SDE predicting drop out; however, IM interacted with age to predict participants' likelihood of drop out. Used in conjunction, the BIDR, IM subscale, and SDR subscale can be used to more accurately tailor smoking cessation programs to the needs of individual participants.^

The role of a nursing home administrator's education in influencing quality of care in US nursing homes

Nursing home literature links poor management practices to poor quality of care and resident outcomes. Since Nursing Home Administrators (NHAs) require an array of skills to perform their role, it is important to explore what makes a NHA effective. This research fills a gap in the literature and provides a possible option to improve the quality of care in nursing homes. Purpose of the study. The study examines whether NHAs with advanced education (defined as a Masters degree or more) are associated with better quality of care in licensed nursing homes (NHs). Design and Methods. Data was derived from the CDC’s 2004 National Nursing Home Survey, which is a representative sample of NHs across the US. A Donabedian- inspired structure-process-outcomes study model was created to explain how education relates to quality of care. Quality of care was defined as onsite oral care, employee influenza vaccination rates and staff recognition programs. Statistical analyses included multivariate logistic regression; covariates included facility-level variables used in similar peer-reviewed research but also included select measures from the Area Resource File to control for county-level factors. Results. Descriptive and analytical analyses confirm that NHAs with a Bachelor’s degree, Associate degree or high school diploma perform less well than NHAs with a Masters degree or more. NHAs with advanced education are more likely to have onsite dental care and recognition programs for staff than NHAs with a Bachelor’s degree (or less). Also NHAs with less than graduate education are more likely to provide off-site dental care. Employee vaccination rates are not impacted by education. Adding certification, tenure or years of experience to a NHA with advanced education gives them an advantage. In fact, certification and experience alone do not have a positive relationship to care indicators; however adding these to advanced education produces a significant result. Implications. This research provides preliminary evidence that advanced education for the NHA is associated with better quality of care. If future research can confirm these findings, there is merit in revisiting the qualifications. Education can be a legitimate option to support quality improvement efforts in US nursing homes. ^

Rabies control in the developing world: Results of a cross-sectional study in Bohol, Philippines

Rabies remains a significant problem in much of the developed world, where canine rabies is not well controlled, and the bite of an infected dog is the most common means of transmission. The Philippines continues to report several hundred cases of human rabies every year, and many more cases go undetected. In recent years, the province of Bohol has been targeted by the Philippine government and the World Health Organization for a rabies eradication program. ^ The primary objective of this dissertation research was to describe factors associated with dog vaccination coverage and knowledge, attitudes, and practices regarding rabies among households in Bohol, Philippines. Utilizing a cross-sectional cluster survey design, we sampled 460 households and 541 dogs residing within dog-owning households. ^ Multivariate linear regression was used to examine potential associations between knowledge, attitudes, and practices (KAPs) and variables of interest. Forty-six percent of households knew that rabies was spread through the bite of an infected dog. The mean knowledge score was 8.36 (SD: ± 3.4; range: 1–24). We found that having known someone with rabies was significantly associated with an almost one point increase in the knowledge score (β = 0.88; p = 0.02). The mean attitudes score was 5.65 (SD: ± 0.63; range: 2–6), and the mean practices score was 7.07 (SD: ± 1.7; range: 2–9). Both the attitudes score and the practices score were positively and significantly associated with only the knowledge score and no other covariates. ^ Multivariate logistic regression was used to examine associations between dog vaccination coverage and variables of interest. Approximately 71% of owned dogs in Bohol were reported as vaccinated at some time during their lives. We found that a dog's age was significantly associated with vaccination, and the odds of vaccination increased in a linear fashion with age. We also found that dogs had approximately twice the odds of being vaccinated if they were confined both day and night to the household premises or if the owner was employed; however, these results were only marginally significant (p = 0.07) in the multivariate model. ^ Finally, a systematic review was conducted on canine rabies vaccination and dog population demographics in the developing world. We found few studies on this topic, especially in countries where the burden of rabies is greatest. Overall, dog ownership is high. Dogs are quite young and do not live very long due to disease and accidents. The biggest deterrent to vaccination is the rapid dog population turnover. ^ It is our hope that this work will be used to improve dog rabies vaccination programs around the world and save lives, both human and canine.^

Genetic variants associated with metastatic prostate cancer

Introduction. Distant metastasis remains the leading cause of death among prostate cancer patients. Several genetic susceptibility loci associated with Prostate cancer have been identified by the Genome Wide Association Studies (GWAS). To date, few studies have explored the ability of these SNPs to identify metastatic prostate cancer. Based on the identification of genetic variants as predictors of aggressive disease, a case comparison study of prostate cancer patients was designed to explore the association of 96 GWAS single nucleotide polymorphisms (SNPs) with metastatic disease. ^ Method. 1242 histologically confirmed prostate cancer patients, with and without metastatic disease, were enrolled into the study. Data were collected from personal interviews, hospital database and abstraction of medical records. Ninety six SNPs identified from GWAS studies based on their associations with prostate cancer risk were genotyped in the study population. Univariate and multivariate logistic regression analyses were used to explore the relationships of the variants with metastatic prostate cancer in Whites and African American men. ^ Results. Four SNPs showed independent associations with metastatic prostate cancer (rs721048 in EHBP1 (2p15), rs3025039 in VEGF (6p12), rs11228565 in Intergenic(11q13.2) and rs2735839 in KLK3(19q13.33)) in the White population. For SNP rs2735839 in KLK3, genotype GA was 1.71 times as likely to be associated with metastatic prostate cancer diagnosis as genotype AA after adjusting for other significant SNPs and covariates (95% CI, 1.12-2.60; p=0.012). In men of African descent, three SNPs: rs1512268 in NKX3-1(8p21.2), rs12155172 in intergenic (7p15.3) & rs10486567 in JAZF1 (7p15.2) were positively associated with metastatic disease in the multivariate analysis. The strongest SNP was rs1512268 heterozygous genotype AG in NKX3-1(8p21.2) which was associated with 3.97-fold increased risk of metastatic prostate cancer diagnosis (95% CI, 1.69-9.34; p =0.002). ^ Conclusion. Genetic variants associated with metastatic prostate cancer were different in Whites and African American men. Given the high mortality rate recorded in men diagnosed with metastatic prostate tumor, further studies are needed to validate associations and establish their clinical application.^

Trastuzumab use and risk of congestive heart failure in older breast cancer patients

Trastuzumab is a humanized-monoclonal antibody, developed specifically for HER2-neu over-expressed breast cancer patients. Although highly effective and well tolerated, it was reported associated with Congestive Heart Failure (CHF) in clinical trial settings (up to 27%). This leaves a gap where, Trastuzumab-related CHF rate in general population, especially older breast cancer patients with long term treatment of Trastuzumab remains unknown. This thesis examined the rates and risk factors associated with Trastuzumab-related CHF in a large population of older breast cancer patients. A retrospective cohort study using the existing Surveillance, Epidemiology and End Results (SEER) and Medicare linked de-identified database was performed. Breast cancer patients ≥ 66 years old, stage I-IV, diagnosed in 1998-2007, fully covered by Medicare but no HMO within 1-year before and after first diagnosis month, received 1st chemotherapy no earlier than 30 days prior to diagnosis were selected as study cohort. The primary outcome of this study is a diagnosis of CHF after starting chemotherapy but none CHF claims on or before cancer diagnosis date. ICD-9 and HCPCS codes were used to pool the claims for Trastuzumab use, chemotherapy, comorbidities and CHF claims. Statistical analysis including comparison of characteristics, Kaplan-Meier survival estimates of CHF rates for long term follow up, and Multivariable Cox regression model using Trastuzumab as a time-dependent variable were performed. Out of 17,684 selected cohort, 2,037 (12%) received Trastuzumab. Among them, 35% (714 out of 2037) were diagnosed with CHF, compared to 31% (4784 of 15647) of CHF rate in other chemotherapy recipients (p<.0001). After 10 years of follow-up, 65% of Trastuzumab users developed CHF, compared to 47% in their counterparts. After adjusting for patient demographic, tumor and clinical characteristics, older breast cancer patients who used Trastuzumab showed a significantly higher risk in developing CHF than other chemotherapy recipients (HR 1.69, 95% CI 1.54 - 1.85). And this risk is increased along with the increment of age (p-value < .0001). Among Trastuzumab users, these covariates also significantly increased the risk of CHF: older age, stage IV, Non-Hispanic black race, unmarried, comorbidities, Anthracyclin use, Taxane use, and lower educational level. It is concluded that, Trastuzumab users in older breast cancer patients had 69% higher risk in developing CHF than non-Trastuzumab users, much higher than the 27% increase reported in younger clinical trial patients. Older age, Non-Hispanic black race, unmarried, comorbidity, combined use with Anthracycline or Taxane also significantly increase the risk of CHF development in older patients treated with Trastuzumab. ^

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

Point of decision signs and stair use in a university worksite setting: General versus specific messages

Point-of-decision signs to promote stair use have been found to be effective in various environments. However, these signs have been more consistently successful in public access settings that use escalators, such as shopping centers and transportation stations, compared to worksite settings, which are more likely to contain elevators that are not directly adjacent to the stairs. Therefore, this study tested the effectiveness of two point-of-decision sign prompts to increase stair use in a university worksite setting. Also, this study investigated the importance of the message content of the signs. One sign displayed a general health promotion message, while the other sign presented more specific information. Overall, this project examined whether the presence of the point-of-decision signs increases stair use. In addition, this research determined whether the general or specific sign promotes greater stair use. ^ Inconspicuous observers measured stair use both before the signs were present and while they were posted. The study setting was the University of Texas School of Nursing, and the target population was anyone who entered the building, including employees, students, and visitors. The study was conducted over six weeks and included two weeks of baseline measurement, two weeks with the general sign posted, and two weeks with the specific sign posted. Each sign was displayed on a stand in the decision point area near the stairs and the elevator. Logistic regression was used to analyze the data. ^ After adjustment for covariates, the odds of stair use were significantly greater during the intervention period than the baseline period. Furthermore, the specific sign period showed significantly greater odds of stair use than the general sign period. These results indicate that a point-of-decision sign intervention can be effective at promoting stair use in a university worksite setting and that a sign with a specific health information message may be more effective at promoting stair use than a sign with a general health promotion message. These findings can be considered when planning future worksite and university based stair promotion interventions.^

Association of processed red meat and prostate cancer stage in Mexican-Americans: A population based case-control study

Objective: The objective of this study is to investigate the association between processed and unprocessed red meat consumption and prostate cancer (PCa) stage in a homogenous Mexican-American population. Methods: This population-based case-control study had a total of 582 participants (287 cases with histologically confirmed adenocarcinoma of the prostate gland and 295 age and ethnicity-matched controls) that were all residing in the Southeast region of Texas from 1998 to 2006. All questionnaire information was collected using a validated data collection instrument. Statistical Analysis: Descriptive analyses included Student's t-test and Pearson's Chi-square tests. Odds ratios and 95% confidence intervals were calculated to quantify the association between nutritional factors and PCa stage. A multivariable model was used for unconditional logistic regression. Results: After adjusting for relevant covariates, those who consume high amounts of processed red meat have a non-significant increased odds of being diagnosed with localized PCa (OR = 1.60 95% CI: 0.85 - 3.03) and total PCa (OR = 1.43 95% CI: 0.81 - 2.52) but not for advanced PCa (OR = 0.91 95% CI: 1.37 - 2.23). Interestingly, high consumption of carbohydrates shows a significant reduction in the odds of being diagnosed with total PCa and advanced PCa (OR = 0.43 95% CI: 0.24 - 0.77; OR = 0.27 95% CI: 0.10 - 0.71, respectively). However, consuming high amounts of energy from protein and fat was shown to increase the odds of being diagnosed with advanced PCa (OR = 4.62 95% CI: 1.69 - 12.59; OR = 2.61 95% CI: 1.04 - 6.58, respectively). Conclusion: Mexican-Americans who consume high amounts of energy from protein and fat had increased odds of being diagnosed with advanced PCa, while high amounts of carbohydrates reduced the odds of being diagnosed with total and advanced PCa.^

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

Is H. pylori infection associated with diarrhea in a cohort of 3- to 8-year-old Colombian children?

The Estudio Comunitario sobre la Salud del Niño cohort study followed 326 3- to 8-year-old Colombian children for 4 years to observe the natural history of Helicobacter pylori infection and identify risk factors for acquisition, recurrence and persistence. Acute H. pylori infection during childhood may predispose to other enteric infections and therefore increase the risk of diarrheal disease. This dissertation aimed to estimate the effect of H. pylori infection on the occurrence of diarrhea and parasitic co-infections. The analysis used Generalized Estimating Equations to obtain odds ratios to estimate relative risks for diarrhea and the Zhang-Yu algorithm to estimate relative risks for on parasitic infections. Andersen-Gill models were used to estimate rate ratios for the effect of H. pylori status on the recurrence of parasitic infections. H. pylori status was classified for the entire follow-up duration in 1 of 3 categories: persistently positive, intermittently positive, and persistently negative. Multivariable models included child’s sex, age, symptoms, medication use, and socio-environmental factors. H. pylori infection was weakly and imprecisely associated with diarrheal disease, which occurred at an unexpectedly low frequency in this study. Persistently H. pylori-positive children had a somewhat higher incidence of reported diarrhea than intermittently positive or persistently negative children. Stratified analysis revealed that the presence of specific helminthes modified the effect of persistent H. pylori infection on diarrhea. The incidence of any parasitic infections was higher in children with persistent H. pylori infection relative to those with intermittent or persistently negative status, but this association did not hold when adjusted for the full set of selected covariates. The effects of H. pylori persistent status were similar for the occurrence or recurrence of Giardia duodenalis, Entamoeba histolytica, and Ascaris lumbricoides. These results show that H. pylori frequently co-exists with other parasites in Andean children and suggest that intermittently H. pylori–positive children might be at a lower risk of parasitic infections than persistently positive children. The relationship of H. pylori infection, helminthic infection and diarrheal disease should be further explored in studies that devote more intensive resources to accurate ascertainment of diarrhea.^

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.^

Associations between ambient levels of combustion pollutants and small for gestational age infants in Texas

There is scant evidence regarding the associations between ambient levels of combustion pollutants and small for gestational age (SGA) infants. No studies of this type have been completed in the Southern United States. The main objective of the project presented was to determine associations between combustion pollutants and SGA infants in Texas using three different exposure assessments. ^ Birth certificate data that contained information on maternal and infant characteristics were obtained from the Texas Department of State Health Services (TX DSHS). Exposure assessment data for the three aims came from: (1) U.S. Environmental Protection Agency (EPA) National Air Toxics Assessment (NATA), (2) U.S. EPA Air Quality System (AQS), and (3) TX Department of Transportation (DOT), respectively. Multiple logistic regression models were used to determine the associations between combustion pollutants and SGA. ^ For the first study looked at annual estimates of four air toxics at the census tract level in the Greater Houston Area. After controlling for maternal race, maternal education, tobacco use, maternal age, number of prenatal visits, marital status, maternal weight gain, and median census tract income level, adjusted ORs and 95% confidence intervals (CI) for exposure to PAHs (per 10 ng/m3), naphthalene (per 10 ng/m3), benzene (per 1 µg/m3), and diesel engine emissions (per 10 µg/m3) were 1.01 (0.97–1.05), 1.00 (0.99–1.01), 1.01 (0.97–1.05), and 1.08 (0.95–1.23) respectively. For the second study looking at Hispanics in El Paso County, AORs and 95% confidence intervals (CI) for increases of 5 ng/m3 for the sum of carcinogenic PAHs (Σ c-PAHs), 1 ng/m3 of benzo[a]pyrene, and 100 ng/m3 in naphthalene during the third trimester of pregnancy were 1.02 (0.97–1.07), 1.03 (0.96–1.11), and 1.01 (0.97–1.06), respectively. For the third study using maternal proximity to major roadways as the exposure metric, there was a negative association with increasing distance from a maternal residence to the nearest major roadway (Odds Ratio (OR) = 0.96; 95% CI = 0.94–0.97) per 1000 m); however, once adjusted for covariates this effect was no longer significant (AOR = 0.98; 95% CI = 0.96–1.00). There was no association with distance weighted traffic density (DWTD). ^ This project is the first to look at SGA and combustion pollutants in the Southern United States with three different exposure metrics. Although there was no evidence of associations found between SGA and the air pollutants mentioned in these studies, the results contribute to the body of literature assessing maternal exposure to ambient air pollution and adverse birth outcomes. ^