A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

Detecting spatiotemporal clusters of accidental poisoning mortality among Texas counties, U.S., 1980 – 2001

Background Accidental poisoning is one of the leading causes of injury in the United States, second only to motor vehicle accidents. According to the Centers for Disease Control and Prevention, the rates of accidental poisoning mortality have been increasing in the past fourteen years nationally. In Texas, mortality rates from accidental poisoning have mirrored national trends, increasing linearly from 1981 to 2001. The purpose of this study was to determine if there are spatiotemporal clusters of accidental poisoning mortality among Texas counties, and if so, whether there are variations in clustering and risk according to gender and race/ethnicity. The Spatial Scan Statistic in combination with GIS software was used to identify potential clusters between 1980 and 2001 among Texas counties, and Poisson regression was used to evaluate risk differences. Results Several significant (p < 0.05) accidental poisoning mortality clusters were identified in different regions of Texas. The geographic and temporal persistence of clusters was found to vary by racial group, gender, and race/gender combinations, and most of the clusters persisted into the present decade. Poisson regression revealed significant differences in risk according to race and gender. The Black population was found to be at greatest risk of accidental poisoning mortality relative to other race/ethnic groups (Relative Risk (RR) = 1.25, 95% Confidence Interval (CI) = 1.24 – 1.27), and the male population was found to be at elevated risk (RR = 2.47, 95% CI = 2.45 – 2.50) when the female population was used as a reference. Conclusion The findings of the present study provide evidence for the existence of accidental poisoning mortality clusters in Texas, demonstrate the persistence of these clusters into the present decade, and show the spatiotemporal variations in risk and clustering of accidental poisoning deaths by gender and race/ethnicity. By quantifying disparities in accidental poisoning mortality by place, time and person, this study demonstrates the utility of the spatial scan statistic combined with GIS and regression methods in identifying priority areas for public health planning and resource allocation.

Physician and patient determinants of the treatment of sleep difficulties in U.S. outpatient settings

The prevalence of sleep difficulties among the patients seen in the primary care settings is about 30%. This problem increases with age and is more common among females than males. Variations are noticed in prescription choices for different patients with sleep difficulties. Many factors affect a physician's prescription decision while chosen from a wide array of available medications. Both pharmacological and behavioral therapies are available for the treatment of sleep difficulties. It is important to know the impact of use of different types of prescriptions on health outcomes related to sleep difficulties. Thus the knowledge of prescription patterns among different types of patients (e.g. age, gender, race, insurance type etc.) becomes important for determining a clinical guideline. This study is designed to assist in evidence-based policymaking on understanding the variations in physician prescriptions for sleep difficulties and reasons for such variations. ^ A modified version of the model suggested by Eisenberg was used as a theoretical framework for this study to predict the factors influencing treatment of sleep difficulties. Multivariate logistic regression methods were used to analyze the 1996–2001 National Ambulatory Medical Care Survey data. ^ This study found that increased age, female gender, white race, established patients, and mental comorbidity were associated with significantly increased likelihood for prescription of some type of therapy for sleep difficulties in US outpatient settings. Patients with private insurance were associated with lower likelihood of receipt of many therapies. Psychiatrists were more likely to prescribe some kind of treatment as well as more expensive therapies for sleep difficulty as compared to other physician specialties. HMO enrolled patient visits were more likely to be associated with receipt of behavioral therapy. This study also found that 32% of patients with sleep difficulties received no type of therapy during their visits. Only 5% of the patients received behavioral therapy only. Almost three-quarters of the patients receiving some kind of medication prescription were prescribed benzodiazepines. The study results also suggest a need for wider coverage of behavioral therapy by payers in US outpatient settings. ^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

An epidemiologic evaluation of a worksite based intervention

The healthcare industry spends billions on worker injury and employee turnover. Hospitals and healthcare settings have one of the highest rates of lost days due to injuries. The occupational hazards for healthcare workers can be classified into biological, chemical, ergonomic, physical, organizational, and psychosocial. Therefore, interventions addressing a range of occupational health risks are needed to prevent injuries and reduce turnover and reduce costs. ^ The Sacred Vocation Program (SVP) seeks to change the content of work, i.e., the meaningfulness of work, to improve work environments. The SVP intervenes at both the individual and organizational level. First the SVP attempts to connect healthcare workers with meaning from their work through a series of 5 self-discovery group sessions. In a sixth session the graduates take an oath recommitting them to do their work as a vocation. Once motivated to connect with meaning in their work, a representative employee group meets in a second set of five meetings. This representative group suggests organizational changes to create a culture that supports employees in their calling. The employees present their plan in the twelfth session to management beginning a new phase in the existing dialogue between employees and management. ^ The SVP was implemented in a large Dallas hospital (almost 1000 licensed beds). The Baylor University Medical Center (BUMC) Pastoral Care department invited front-line caregivers (primarily Patient Care Assistants, PCAs, or Patient Care Technicians, PCTs) to participate in the SVP. Participants completed SVP questionnaires at the beginning and following SVP implementation. Following implementation, employer records were collected on injury, absence and turnover to further evaluate the program's effectiveness on metrics that are meaningful to managers in assessing organizational performance. This provided an opportunity to perform an epidemiological evaluation of the intervention using the two sources of information: employee self-reports and employer administrative data. ^ The ability to evaluate the effectiveness of the SVP on program outcomes could be limited by the strength of the measures used. An ordinal CFA performed on baseline SVP questionnaire measurements examined the construct validity and reliability of the SVP scales. Scales whose item-factor structure was confirmed in ordinal CFA were evaluated for their psychometric properties (i.e., reliability, mean, ceiling and floor effects). CFA supported the construct validity of six of the proposed scales: blocks to spirituality, meaning at work, work satisfaction, affective commitment, collaborative communication, and MHI-5. Five of the six scales confirmed had acceptable measures of reliability (all but MHI-5 had α>0.7). All six scales had a high percentage (>30%) of the scores at the ceiling. These findings supported the use of these items in the evaluation of change although strong ceiling effects may hinder discerning change. ^ Next, the confirmed SVP scales were used to evaluate whether the intervention improved program constructs. To evaluate the SVP a one group pretest-posttest design compared participants’ self-reports before and after the intervention. It was hypothesized that measurements of reduced blocks to spirituality (α = 0.76), meaning at work (α = 0.86), collaborative communication (α = 0.67) and SVP job tasks (α = 0.97) would improve following SVP implementation. The SVP job tasks scale was included even though it was not included in the ordinal CFA analysis due to a limited sample and high inter-item correlation. Changes in scaled measurements were assessed using multilevel linear regression methods. All post-intervention measurements increased (increases <0.28 points) but only reduced blocks to spirituality was statistically significant (0.22 points on a scale from 1 to 7, p < 0.05) after adjustment for covariates. Intensity of the intervention (stratifying on high participation units) strengthened effects; but were not statistically significant. The findings provide preliminary support for the hypothesis that meaning in work can be improved and, importantly, lend greater credence to any observed improvements in the outcomes. (Abstract shortened by UMI.)^

Enlarged tracheoesophageal puncture: A systematic review and retrospective analysis

Background. An enlarged tracheoesophageal puncture (TEP) results in aspiration around the voice prosthesis (VP) and may lead to pneumonia. The aims of this research were: (1) to conduct a systematic review and meta-analysis on enlarged TEP; (2) to analyze preoperative, perioperative, and postoperative risk factors for enlarged TEP; and (3) to evaluate control of leakage around the VP using conservative treatments and adverse events in patients with enlarged TEP.^ Methods. A systematic review was conducted (1978-2008). A summary risk estimate was calculated using a random-effects meta-analysis model. A retrospective cohort study was completed. Patients who underwent total laryngectomy and TEP at The University of Texas M. D. Anderson Cancer Center (MDACC) were included. Multiple logistic regression methods were used to assess risk factors for enlargement. Descriptive and bivariate statistics were calculated to evaluate outcomes and adverse events. Results: Twenty-seven manuscripts were included in the systematic review. The summary risk estimate of enlarged TEP/leakage around the VP was 7.2% (95% CI: 4.8%-9.6%). Temporary VP removal and TEP-site injections were the most commonly reported treatments. Neither prosthetic diameter (p=0.076) nor timing of TEP (p=0.297) significantly increased risk of enlargement per stratified analyses of published outcomes. The cumulative incidence of enlarged TEP was 18.6% (36/194, 95% CI: 13.0%-24.1%) in the MDACC cohort. Enlarged TEP occurred exclusively in irradiated patients. Adjusting for length of follow-up and timing of TEP, advanced nodal disease (ORadjusted: 4.3, 95% CI: 1.0-19.1), stricture (ORadjusted : 3.2, 95% CI: 1.2-8.6), and locoregional recurrence/distant metastasis after laryngectomy (ORadjusted: 6.2, 95% CI: 2.3-16.4) increased risk of enlarged TEP. At last follow-up, conservative methods controlled leakage around the VP in 81% (29/36) of patients. Unresolved leakage was associated with recurrent cancer (p=0.081) and TEP-site irregularity (p=0.003). Relative to those without enlargement, enlarged TEP patients had significantly higher risk of pneumonia (RR: 3.4, 95% CI: 1.9-6.2).^ Conclusions. These data establish that enlarged TEP poses serious health risks, and provide insight into medical and oncologic factors that may contribute to development of this complication. In addition, this research supports the use of conservative treatments to address leakage after enlarged TEP in lieu of complete TEP closure.^

Secondary data analysis of lead screening compliance in high-risk children

Introduction. Despite the ban of lead-containing gasoline and paint, childhood lead poisoning remains a public health issue. Furthermore, a Medicaid-eligible child is 8 times more likely to have an elevated blood lead level (EBLL) than a non-Medicaid child, which is the primary reason for the early detection lead screening mandate for ages 12 and 24 months among the Medicaid population. Based on field observations, there was evidence that suggested a screening compliance issue. Objective. The purpose of this study was to analyze blood lead screening compliance in previously lead poisoned Medicaid children and test for an association between timely lead screening and timely childhood immunizations. The mean months between follow-up tests were also examined for a significant difference between the non-compliant and compliant lead screened children. Methods. Access to the surveillance data of all childhood lead poisoned cases in Bexar County was granted by the San Antonio Metropolitan Health District. A database was constructed and analyzed using descriptive statistics, logistic regression methods and non-parametric tests. Lead screening at 12 months of age was analyzed separately from lead screening at 24 months. The small portion of the population who were also related were included in one analysis and removed from a second analysis to check for significance. Gender, ethnicity, age of home, and having a sibling with an EBLL were ruled out as confounders for the association tests but ethnicity and age of home were adjusted in the nonparametric tests. Results. There was a strong significant association between lead screening compliance at 12 months and childhood immunization compliance, with or without including related children (p<0.00). However, there was no significant association between the two variables at the age of 24 months. Furthermore, there was no significant difference between the median of the mean months of follow-up blood tests among the non-compliant and compliant lead screened population for at the 12 month screening group but there was a significant difference at the 24 month screening group (p<0.01). Discussion. Descriptive statistics showed that 61% and 56% of the previously lead poisoned Medicaid population did not receive their 12 and 24 month mandated lead screening on time, respectively. This suggests that their elevated blood lead level may have been diagnosed earlier in their childhood. Furthermore, a child who is compliant with their lead screening at 12 months of age is 2.36 times more likely to also receive their childhood immunizations on time compared to a child who was not compliant with their 12 month screening. Even though there was no statistical significant association found for the 24 month group, the public health significance of a screening compliance issue is no less important. The Texas Medicaid program needs to enforce lead screening compliance because it is evident that there has been no monitoring system in place. Further recommendations include a need for an increased focus on parental education and the importance of taking their children for wellness exams on time.^

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. ^

HEALTH MAINTENANCE ORGANIZATION ENVIRONMENT: AN EMPIRICAL STUDY OF THE RELATIONSHIP OF EXTERNAL CONTEXT AND PERFORMANCE

The research project is an extension of a series of administrative science and health care research projects evaluating the influence of external context, organizational strategy, and organizational structure upon organizational success or performance. The research will rely on the assumption that there is not one single best approach to the management of organizations (the contingency theory). As organizational effectiveness is dependent on an appropriate mix of factors, organizations may be equally effective based on differing combinations of factors. The external context of the organization is expected to influence internal organizational strategy and structure and in turn the internal measures affect performance (discriminant theory). The research considers the relationship of external context and organization performance.^ The unit of study for the research will be the health maintenance organization (HMO); an organization the accepts in exchange for a fixed, advance capitation payment, contractual responsibility to assure the delivery of a stated range of health sevices to a voluntary enrolled population. With the current Federal resurgence of interest in the Health Maintenance Organization (HMO) as a major component in the health care system, attention must be directed at maximizing development of HMOs from the limited resources available. Increased skills are needed in both Federal and private evaluation of HMO feasibility in order to prevent resource investment and in projects that will fail while concurrently identifying potentially successful projects that will not be considered using current standards.^ The research considers 192 factors measuring contextual milieu (social, educational, economic, legal, demographic, health and technological factors). Through intercorrelation and principle components data reduction techniques this was reduced to 12 variables. Two measures of HMO performance were identified, they are (1) HMO status (operational or defunct), and (2) a principle components factor score considering eight measures of performance. The relationship between HMO context and performance was analysed using correlation and stepwise multiple regression methods. In each case it has been concluded that the external contextual variables are not predictive of success or failure of study Health Maintenance Organizations. This suggests that performance of an HMO may rely on internal organizational factors. These findings have policy implications as contextual measures are used as a major determinant in HMO feasibility analysis, and as a factor in the allocation of limited Federal funds. ^

Progressive regression of left ventricular hypertrophy two years after bariatric surgery.

BACKGROUND: Obesity is a systemic disorder associated with an increase in left ventricular mass and premature death and disability from cardiovascular disease. Although bariatric surgery reverses many of the hormonal and hemodynamic derangements, the long-term collective effects on body composition and left ventricular mass have not been considered before. We hypothesized that the decrease in fat mass and lean mass after weight loss surgery is associated with a decrease in left ventricular mass. METHODS: Fifteen severely obese women (mean body mass index [BMI]: 46.7+/-1.7 kg/m(2)) with medically controlled hypertension underwent bariatric surgery. Left ventricular mass and plasma markers of systemic metabolism, together with body mass index (BMI), waist and hip circumferences, body composition (fat mass and lean mass), and resting energy expenditure were measured at 0, 3, 9, 12, and 24 months. RESULTS: Left ventricular mass continued to decrease linearly over the entire period of observation, while rates of weight loss, loss of lean mass, loss of fat mass, and resting energy expenditure all plateaued at 9 [corrected] months (P <.001 for all). Parameters of systemic metabolism normalized by 9 months, and showed no further change at 24 months after surgery. CONCLUSIONS: Even though parameters of obesity, including BMI and body composition, plateau, the benefits of bariatric surgery on systemic metabolism and left ventricular mass are sustained. We propose that the progressive decrease of left ventricular mass after weight loss surgery is regulated by neurohumoral factors, and may contribute to improved long-term survival.

ALTERATIONS IN HYPOTHALAMIC CONTENT OF LUTEINIZING HORMONE RELEASING HORMONE AND PITUITARY RESPONSIVENESS ASSOCIATED WITH TESTICULAR REGRESSION INDUCED BY PINEAL RELATED TREATMENTS IN THE GOLDEN HAMSTER

The adult male golden hamster, when exposed to blinding (BL), short photoperiod (SP), or daily melatonin injections (MEL) demonstrates dramatic reproductive collapse. This collapse can be blocked by removal of the pineal gland prior to treatment. Reproductive collapse is characterized by a dramatic decrease in both testicular weight and serum gonadotropin titers. The present study was designed to examine the interactions of the hypothalamus and pituitary gland during testicular regression, and to specifically compare and contrast changes caused by the three commonly employed methods of inducing testicular regression (BL,SP,MEL). Hypothalamic LHRH content was altered by all three treatments. There was an initial increase in content of LHRH that occurred concomitantly with the decreased serum gonadotropin titers, followed by a precipitous decline in LHRH content which reflected the rapid increases in both serum LH and FSH which occur during spontaneous testicular recrudescence. In vitro pituitary responsiveness was altered by all three treatments: there was a decline in basal and maximally stimulatable release of both LH and FSH which paralleled the fall of serum gonadotropins. During recrudescence both basal and maximal release dramatically increased in a manner comparable to serum hormone levels. While all three treatments were equally effective in their ability to induce changes at all levels of the endocrine system, there were important temporal differences in the effects of the various treatments. Melatonin injections induced the most rapid changes in endocrine parameters, followed by exposure to short photoperiod. Blinding required the most time to induce the same changes. This study has demonstrated that pineal-mediated testicular regression is a process which involves dynamic changes in multiply-dependent endocrine relationships, and proper evaluation of these changes must be performed with specific temporal events in mind. ^

An analysis of two methods for the classification of stage of readiness to obtain repeat mammography screening

Background and purpose: Breast cancer continues to be a health problem for women, representing 28 percent of all female cancers and remaining one of the leading causes of death for women. Breast cancer incidence rates become substantial before the age of 50. After menopause, breast cancer incidence rates continue to increase with age creating a long-lasting source of concern (Harris et al., 1992). Mammography, a technique for the detection of breast tumors in their nonpalpable stage when they are most curable, has taken on considerable importance as a public health measure. The lifetime risk of breast cancer is approximately 1 in 9 and occurs over many decades. Recommendations are that screening be periodic in order to detect cancer at early stages. These recommendations, largely, are not followed. Not only are most women not getting regular mammograms, but this circumstance is particularly the case among older women where regular mammography has been proven to reduce mortality by approximately 30 percent. The purpose of this project was to increase our understanding of factors that are associated with stage of readiness to obtain subsequent mammograms. A secondary purpose of this research was to suggest further conceptual considerations toward the extension of the Transtheoretical Model (TTM) of behavior change to repeat screening mammography. ^ Methods. A sample (n = 1,222) of women 50 years and older in a large multi-specialty clinic in Houston, Texas was surveyed by mail questionnaire regarding their previous screening experience and stage of readiness to obtain repeat screening. A computerized database, maintained on all women who undergo mammography at the clinic, was used to identify women who are eligible for the project. The major statistical technique employed to select the significant variables and to examine the man and interaction effects of independent variables on dependent variables was polychotomous stepwise, logistic regression. A prediction model for each stage of readiness definition was estimated. The expected probabilities for stage of readiness were calculated to assess the magnitude and direction of significant predictors. ^ Results. Analysis showed that both ways of defining stage of readiness for obtaining a screening mammogram were associated with specific constructs, including decisional balance and processes of the change. ^ Conclusions. The results of the present study demonstrate that the TTM appears to translate to repeat mammography screening. Findings in the current study also support finding of previous studies that suggest that stage of readiness is associated with respondent decisional balance and the processes of change. ^

Using GIS methods to assess the occurrence of neural tube defect births by residential proximity at conception to hazardous waste sites

In the United States, approximately 4,000 pregnancies each year are affected by the two most common birth defects, spina bifida and anencephaly. Studies have shown that exposure to environmental chemicals before and after conception may adversely affect reproduction by inducing cell death or dysfunction, which leads to infertility, fetal loss, lowered weight at birth, or birth anomalies in the offspring. The objective of the study was to evaluate the relationship between Neural Tube Defect births and residence at conception in proximity to hazardous waste sites in the Texas-Mexico border region between 1993 and 2000. ^ The study design was a nested matched case-control and utilized secondary data from a project, “The role of chemical and biological factors in the etiology of neural tube birth defects births along the Texas-Mexico Border” (Irina Cech, Principal Investigator). Geographic Information Systems (GIS) database methods were used to compare Neural Tube Defects cases to controls on status of conception residence occurring within a one-mile radius from hazardous waste sites, as compared to conception residence further away. Information on the exposures was obtained from the OnTarget Database and Environment Protection Agency website. Conditional logistic regression was used for the matched case-control study to investigate the relationship between an outcome of being a case or a control and proximity to hazardous waste sites. ^ The result of the study showed a 36 percent non-significant increased risk of having an NTD birth associated with maternal proximity to abandoned hazardous waste sites (95% CI = 0.62–3.02). In addition, there was a 24% non-significant elevated risk of having an NTD birth when living in proximity to air pollutant sites than when living further away (95% CI = 0.67–2.32). Although this study did not find statistically significant associations, it will expand on the existing knowledge of the relationship between NTD and proximity to hazardous waste sites. ^

Determining appropriate measurement methods for etiological research of computing-related musculoskeletal symptoms and disorders

Two studies among college students were conducted to evaluate appropriate measurement methods for etiological research on computing-related upper extremity musculoskeletal disorders (UEMSDs). ^ A cross-sectional study among 100 graduate students evaluated the utility of symptoms surveys (a VAS scale and 5-point Likert scale) compared with two UEMSD clinical classification systems (Gerr and Moore protocols). The two symptom measures were highly concordant (Lin's rho = 0.54; Spearman's r = 0.72); the two clinical protocols were moderately concordant (Cohen's kappa = 0.50). Sensitivity and specificity, endorsed by Youden's J statistic, did not reveal much agreement between the symptoms surveys and clinical examinations. It cannot be concluded self-report symptoms surveys can be used as surrogate for clinical examinations. ^ A pilot repeated measures study conducted among 30 undergraduate students evaluated computing exposure measurement methods. Key findings are: temporal variations in symptoms, the odds of experiencing symptoms increased with every hour of computer use (adjOR = 1.1, p < .10) and every stretch break taken (adjOR = 1.3, p < .10). When measuring posture using the Computer Use Checklist, a positive association with symptoms was observed (adjOR = 1.3, p < 0.10), while measuring posture using a modified Rapid Upper Limb Assessment produced unexpected and inconsistent associations. The findings were inconclusive in identifying an appropriate posture assessment or superior conceptualization of computer use exposure. ^ A cross-sectional study of 166 graduate students evaluated the comparability of graduate students to College Computing & Health surveys administered to undergraduate students. Fifty-five percent reported computing-related pain and functional limitations. Years of computer use in graduate school and number of years in school where weekly computer use was ≥ 10 hours were associated with pain within an hour of computing in logistic regression analyses. The findings are consistent with current literature on both undergraduate and graduate students. ^

Assessment of the effect on statistical power of regression model misspecification by using techniques of mathematical statistics and simulation study

Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^