The Comal County Needs Assessment Youth Survey

A crucial link in preserving and protecting the future of our communities resides in maintaining the health and well being of our youth. While every member of the community owns an opinion regarding where to best utilize monies for prevention and intervention, the data to support such opinion is often scarce. In an effort to generate data-driven indices for community planning and action, the United Way of Comal County, Texas partnered with the University Of Texas - Houston Health Science Center, School Of Public Health to accomplish a county-specific needs assessment. A community-based participatory research emphasis utilizing the Mobilization for Action through Planning and Partnership (MAPP) format developed by the National Association of City and County Health Officials (NACCHO) was implemented to engage community members in identifying and addressing community priorities. The single greatest area of consensus and concern identified by community members was the health and well being of the youth population. Thus, a youth survey, targeting these specific areas of community concern, was designed, coordinated and administered to all 9-11th grade students in the county. 20% of the 3,698 completed surveys (72% response rate) were randomly selected for analysis. These 740 surveys were coded and scanned into an electronic survey database. Statistical analysis provided youth-reported data on the status of the multiple issues affecting the health and well being of the community's youth. These data will be reported back to the community stakeholders, as part of the larger Comal County Needs Assessment, for the purposes of community planning and action. Survey data will provide community planners with an awareness of the high risk behaviors and habit patterns amongst their youth. This knowledge will permit more effective targeting of the means for encouraging healthy behaviors and preventing the spread of disease. Further, the community-oriented, population-based nature of this effort will provide answers to questions raised by the community and will provide an effective launching pad for the development and implementation of targeted, preventive health strategies. ^

Estimation of the incidence of a rare genetic disease through a two-tier mutation survey.

Recent attempts to detect mutations involving single base changes or small deletions that are specific to genetic diseases provide an opportunity to develop a two-tier mutation-screening program through which incidence of rare genetic disorders and gene carriers may be precisely estimated. A two-tier survey consists of mutation screening in a sample of patients with specific genetic disorders and in a second sample of newborns from the same population in which mutation frequency is evaluated. We provide the statistical basis for evaluating the incidence of affected and gene carriers in such two-tier mutation-screening surveys, from which the precision of the estimates is derived. Sample-size requirements of such two-tier mutation-screening surveys are evaluated. Considering examples of cystic fibrosis (CF) and medium-chain acyl-CoA dehydrogenase deficiency (MCAD), the two most frequent autosomal recessive disease in Caucasian populations and the two most frequent mutations (delta F508 and G985) that occur on these disease allele-bearing chromosomes, we show that, with 50-100 patients and a 20-fold larger sample of newborns screened for these mutations, the incidence of such diseases and their gene carriers in a population may be quite reliably estimated. The theory developed here is also applicable to rare autosomal dominant diseases for which disease-specific mutations are found.

Is Our Business Family-Centered?

Human Services agencies often claim to be family-centered, but continue to implement “Service Integration” in a way that supports their mission rather than supporting families. David Berns, guest editor for this issue of the Journal of Family Strengths, presents a framework for redefining the role of governmental agencies beyond their day-to-day delivery of services to one that prevents the need for more intrusive and more costly interventions. Under this philosophy, agencies must consider how families functioned before they requested assistance, and how they will function if services are not successful. By taking the time to truly understand a family’s needs, caseworkers often discover that they may need a service for which they are not eligible and may be eligible for services that they don’t want or need. Instead of focusing entirely on what their agency can do for the family, caseworkers should consider all types of support that might produce better results. Families often need support from friends and communities rather than, or in addition to, a formalized service. Facilitating natural supports in the community may prevent the need for a governmental program. It is only when basic supports break down that families must use ever more intensive and costly programs. The author gives examples of how this framework is guiding the redesign of the TANF Program in Washington, D.C.

The relationship of maternal low birthweight and infant low birthweight among African-American women at term delivery: Findings from the 1988 National Maternal and Infant Health Survey

A cohort study study design was used to study the relationship of maternal low birthweight and infant low birthweight among African American women delivering full term infants. The cohort consisted of 3,157 mother-infant pairs drawn from the 1988 National Maternal and Infant Health Survey conducted by the National Center for Health Statistics. The objectives of the study were (1) to determine if low birthweight, African American mothers delivering term infants experienced higher rates of infant low birthweight and (2) to examine the role of selected contributory variables in the relationship of maternal low birthweight and infant low birthweight. Contributory risk factors examined included maternal marital status, maternal age, maternal education, maternal height, maternal prepregnant weight, birth order, history of a prior low birthweight delivery, timing of prenatal care, number of prenatal visits, gestational length, infant gender, and behavioral factors of smoking, alcohol, and illicit drug use during pregnancy.^ Using logistic regression analysis, risk of infant low birthweight among maternal low birthweight mothers increased after controlling for less than a high school education, less than 20 years of age, prepregnant weight less than 100 lbs, history of a prior low birthweight delivery, birth order, smoking during pregnancy, and use of alcohol and illicit drugs during pregnancy, but was not statistically significant. Loss of statistical significance was attributed to a large reduction in cases available for analysis after including illicit drug use in the model.^ This study demonstrated a consistent pattern of increased rates of infant low birthweight among low birthweight mothers. The force of history remains, hence women with this trait should be carefully monitored and advised during pregnancy to decrease risk of a low birthweight infant, in order to decrease the chain of events leading to future generations of low birthweight mothers. ^

Attitudes, stress and use of force in selected areas of Texas law enforcement

This research aimed to explore the extent to which police use of force was related to attitudes towards violence, agency type, and racism. Previous studies have found a culture of honor in the psychology of violence in the Southern United States. Were similar attitudes measurable among Texas professional line officers? Are there predictors of use of force?^ A self reported anonymous survey was administered to Texas patrol officers in the cities of Austin and Houston, and the Counties of Harris and Travis. A total of seventy-four questionnaires were used in the statistical analyses. Scales were developed measuring use of force, attitudes towards violence, and feelings on racism. Their relationship was examined.^ A regression model shows a strong and significant relationship between the officers' attitudes towards violence and the self-reported use of force. Further, agency type, municipal versus sheriff, also predicts use of force. Attitudes regarding race or racism, as measured by this study, were not predictive of use of force. ^

For-profit business safety interventions: A systematic, descriptive review of the literature

The purpose of this research was to determine if principles from organizational theory could be used as a framework to compare and contrast safety interventions developed by for-profit industry for the time period 1986–1996. A literature search of electronic databases and manual search of journals and local university libraries' book stacks was conducted for safety interventions developed by for-profit businesses. To maintain a constant regulatory environment, the business sectors of nuclear power, aviation and non-profits were excluded. Safety intervention evaluations were screened for scientific merit. Leavitt's model from organization theory was updated to include safety climate and renamed the Updated Leavitt's Model. In all, 8000 safety citations were retrieved, 525 met the inclusion criteria, 255 met the organizational safety intervention criteria, and 50 met the scientific merit criteria. Most came from non-public health journals. These 50 were categorized by the Updated Leavitt's Model according to where within the organizational structure the intervention took place. Evidence tables were constructed for descriptive comparison. The interventions clustered in the areas of social structure, safety climate, the interaction between social structure and participants, and the interaction between technology and participants. No interventions were found in the interactions between social structure and technology, goals and technology, or participants and goals. Despite the scientific merit criteria, many still had significant study design weaknesses. Five interventions tested for statistical significance but none of the interventions commented on the power of their study. Empiric studies based on safety climate theorems had the most rigorous designs. There was an attempt in these studies to address randomization amongst subjects to avoid bias. This work highlights the utility of using the Updated Leavitt's Model, a model from organizational theory, as a framework when comparing safety interventions. This work also highlights the need for better study design of future trials of safety interventions. ^

Factors associated with smoking cessation using the 2005 National Health Interview Survey

Objectives. The objective of this study is to compare the socio-demographic, behavioral, and access to care characteristics of smokers who have quit smoking for one or more years and current smokers who have made an attempt to quit smoking within the last year. ^ Methods. Data from the 2005 National Health Interview Survey (NHIS) were used to compare current smokers who have tried to quit (n=2747) and former smokers who have quit for one or more years (n=6194). The data was analyzed using STATA 9.0 to perform statistical calculations. ^ Results. Age, education, race and income were associated with smoking status. Respondents aged 65 and older were 36 times more likely to have quit smoking. Education and income had higher odds ratios among quitters (OR=1.27 and OR=1.21) and Non-Hispanic Whites were the most likely to have quit smoking compared to Hispanics and Blacks. Adults with health insurance coverage were 3.44 times more likely to have quit smoking. ^ Discussion. Existing research suggests that individual factors relating to demographics behavior and access to care can impact a smoker's ability to quit smoking. This paper discusses the factors that affect cessation and which populations would benefit from additional research and targeted smoking cessation programs. ^

Statistical and methodological challenges for disaster preparedness and medical needs assessment in Rio Grande Valley of Texas

In recent years, disaster preparedness through assessment of medical and special needs persons (MSNP) has taken a center place in public eye in effect of frequent natural disasters such as hurricanes, storm surge or tsunami due to climate change and increased human activity on our planet. Statistical methods complex survey design and analysis have equally gained significance as a consequence. However, there exist many challenges still, to infer such assessments over the target population for policy level advocacy and implementation. ^ Objective. This study discusses the use of some of the statistical methods for disaster preparedness and medical needs assessment to facilitate local and state governments for its policy level decision making and logistic support to avoid any loss of life and property in future calamities. ^ Methods. In order to obtain precise and unbiased estimates for Medical Special Needs Persons (MSNP) and disaster preparedness for evacuation in Rio Grande Valley (RGV) of Texas, a stratified and cluster-randomized multi-stage sampling design was implemented. US School of Public Health, Brownsville surveyed 3088 households in three counties namely Cameron, Hidalgo, and Willacy. Multiple statistical methods were implemented and estimates were obtained taking into count probability of selection and clustering effects. Statistical methods for data analysis discussed were Multivariate Linear Regression (MLR), Survey Linear Regression (Svy-Reg), Generalized Estimation Equation (GEE) and Multilevel Mixed Models (MLM) all with and without sampling weights. ^ Results. Estimated population for RGV was 1,146,796. There were 51.5% female, 90% Hispanic, 73% married, 56% unemployed and 37% with their personal transport. 40% people attained education up to elementary school, another 42% reaching high school and only 18% went to college. Median household income is less than $15,000/year. MSNP estimated to be 44,196 (3.98%) [95% CI: 39,029; 51,123]. All statistical models are in concordance with MSNP estimates ranging from 44,000 to 48,000. MSNP estimates for statistical methods are: MLR (47,707; 95% CI: 42,462; 52,999), MLR with weights (45,882; 95% CI: 39,792; 51,972), Bootstrap Regression (47,730; 95% CI: 41,629; 53,785), GEE (47,649; 95% CI: 41,629; 53,670), GEE with weights (45,076; 95% CI: 39,029; 51,123), Svy-Reg (44,196; 95% CI: 40,004; 48,390) and MLM (46,513; 95% CI: 39,869; 53,157). ^ Conclusion. RGV is a flood zone, most susceptible to hurricanes and other natural disasters. People in the region are mostly Hispanic, under-educated with least income levels in the U.S. In case of any disaster people in large are incapacitated with only 37% have their personal transport to take care of MSNP. Local and state government’s intervention in terms of planning, preparation and support for evacuation is necessary in any such disaster to avoid loss of precious human life. ^ Key words: Complex Surveys, statistical methods, multilevel models, cluster randomized, sampling weights, raking, survey regression, generalized estimation equations (GEE), random effects, Intracluster correlation coefficient (ICC).^

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.^

Association of ALLHAT investigator characteristics with participant recruitment

Clinical trials are often not successful because of the inability to recruit a sufficient number of patients. The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), the largest antihypertensive trial ever conducted, provided highly generalized results and successful recruitment of over 42,000 participants. The overall purpose of this study was to examine the association of investigator characteristics with anti-hypertensive (AHT) participant recruitment in ALLHAT. This secondary data analyses collected data from the ALLHAT investigator profile survey and related investigator characteristics to recruitment success. The sample size was 502 investigators, with recruitment data from 37,947AHT participants. Recruitment was dichotomized by categorizing all sites with recruitment numbers at or above the overall median recruitment number of 46 as "Successful Recruitment". Frequency distributions and univariate and multivariate logistic regression were conducted. When adjusting for all other factors, Hispanic ethnicity, suburban setting, Department of Veterans Affairs Medical Centers (VAMC) site type, number of clinical site staff working on the trial, study coordinator hours per week, medical conference sessions attended, the investigator's primary goal and the likelihood that a physician will convince a patient to continue on randomized treatment, have significant impacts on the recruitment success of ALLHAT investigators. Most of the ALLHAT investigators described their primary commitment as being towards their patients and not to scientific knowledge alone. However, investigators that distinguished themselves as leaders in research had greater recruitment success than investigators who were leaders in clinical practice. ALLHAT was a highly successful trial that proved that community based cardiovascular trials can be implemented on a large scale. Exploring characteristics of ALLHAT investigators provides data that can be generalized to sponsors, sites, and others interested in maximizing clinical trial recruitment numbers. Future studies should further evaluate investigator and study coordinator factors that impact cardiovascular clinical trial recruitment success.^

Predictive validity of the personal background and preparation survey and effectiveness of targeted interventions among health science community college students

Existing data, collected from 1st-year students enrolled in a major Health Science Community College in the south central United States, for Fall 2010, Spring 2011, Fall 2011 and Spring 2012 semesters as part of the "Online Navigational Assessment Vehicle, Intervention Guidance, and Targeting of Risks (NAVIGATOR) for Undergraduate Minority Student Success" with CPHS approval number HSC-GEN-07-0158, was used for this thesis. The Personal Background and Preparation Survey (PBPS) and a two-question risk self-assessment subscale were administered to students during their 1st-year orientation. The PBPS total risk score, risk self-assessment total and overall scores, and Under Representative Minority Student (URMS) status were recorded. The purpose of this study is to evaluate and report the predictive validity of the indicators identified above for Adverse Academic Status Events (AASE) and Nonadvancement Adverse Academic Status Events (NAASE) as well as the effectiveness of interventions targeted using the PBPS among a diverse population of health science community college students. The predictive validity of the PBPS for AASE has previously been demonstrated among health science professions and graduate students (Johnson, Johnson, Kim, & McKee, 2009a; Johnson, Johnson, McKee, & Kim, 2009b). Data will be analyzed using binary logistic regression and correlation using SPSS 19 statistical package. Independent variables will include baseline- versus intervention-year treatments, PBPS, risk self-assessment, and URMS status. The dependent variables will be binary AASE and NAASE status. ^ The PBPS was the first reliable diagnostic and prescriptive instrument to establish documented predictive validity for student Adverse Academic Status Events (AASE) among students attending health science professional schools. These results extend the documented validity for the PBPS in predicting AASE to a health science community college student population. Results further demonstrated that interventions introduced using the PBPS were followed by approximately one-third reduction in the odds of Nonadvancement Adverse Academic Status Events (NAASE), controlling for URMS status and risk self-assessment scores. These results indicate interventions introduced using the PBPS may have potential to reduce AASE or attrition among URMS and nonURMS attending health science community colleges on a broader scale; positively impacting costs, shortages, and diversity of health science professionals.^

Estimates of hospital and physician costs of epilepsy in the United States for 1995 comparing the provider -based survey method and a patient -based medical charts and billing method

This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^

Population-based cross -sectional survey on intestinal helminth infections with a focus on taeniasis among residents of El Paso, Texas and Ciudad Juarez, Mexico

Few studies have been conducted on the epidemiology of enteric infectious diseases of public health importance in communities along the United States-Mexico border, and these studies typically focus on bacterial and viral diseases. The epidemiology of intestinal helminth infections along the border has not recently been explored, and there are no published reports for El Paso and Ciudad Juarez, both of which are high traffic urban areas along the Texas-Mexico border. The purpose of this research project was to conduct a cross-sectional epidemiologic survey for enteric helminths of medical importance along the Texas-Mexico border region of El Paso and Ciudad Juarez and to evaluate risk factors for exposure to these parasites. In addition, an emphasis was placed on the zoonotic tapeworm, Taenia solium. This tapeworm is especially important in this region because of the increasing incidence of neurocysticercosis, a severe disease spread by carriers of intestinal T. solium. Fecal samples were collected from individuals of all ages in a population-based cross-sectional household survey and evaluated for the presence of helminth parasites using fecal flotations. In addition, a Taenia coproantigen enzyme linked immunosorbent assay (ELISA) was performed on each stool sample to identify tapeworm carriers. A standardized questionnaire was administered to identify risk factors and routes of exposure for enteric helminth infections with additional questions to assess risk factors specific for taeniasis. The actual prevalence of taeniasis along the Texas-Mexico border was unknown, and this is the first population-based study performed in this region. Flotations were performed on 395 samples and four (1%) were positive for helminths including Ascaris, hookworms and Taenia species. Immunodiagnostic testing demonstrated a prevalence of 2.9% (11/378) for taeniasis. Based on the case definition, a 3% (12/395) prevalence of taeniasis was detected in this area. In addition, statistical analyses indicate that residents of El Paso are 8.5 times more likely to be a tapeworm carrier compared to residents of Juarez (PR=8.5, 95% CI=2.35, 30.81). This finding has important implications in terms of planning effective health education campaigns to decrease the prevalence of enteric helminths in populations along the Texas-Mexico border. ^