Anthropometric measures as a predictor of cephalopelvic disproportion

This study compared three body measurements, height, hip width (bitrochanteric) and foot length, in 120 Hispanic women who had their first birth by cesarean section (N = 60) or by spontaneous vaginal delivery (N = 60). The objective of the study was to see if there were differences in these measurements that could be useful in predicting cephalopelvic disproportion. Data were collected from two public hospitals in Houston Texas over a 10 month period from December 1994 to October 1995. The statistical technique used to evaluate the measures was discriminant analysis.^ Women who delivered by cesarean section were older, shorter, had shorter feet and delivered heavier infants. There were no differences in the bitrochanteric widths of the women or in the mean gestational age or Apgar scores of the infants.^ Significantly more of the mothers and infants were ill following cesarean section delivery. Maternal illness was usually infection; infant illness was primarily infection or respiratory difficulties.^ Discriminant analysis is a technique which allows for classification and prediction to which group a particular entity will belong given a certain set of variables. Using discriminant analysis, with a probability of cesarean section 50 percent, the best combination to classify who would have a cesarean section was height and hip width, correctly classifying 74.2 percent of those who needed surgery. When the probability of cesarean section was 10 percent and probability of vaginal delivery was 90 percent, the best predictor of who would need operative delivery was height, hip width and age, correctly classifying 56.2 percent. In the population from which the study participants were selected the incidence of cephalopelvic disproportion was low, approximately 1 percent.^ With the technologic assistance available in most of the developed world, it is likely that the further pursuit of different measures and their use would not be of much benefit in attempting to predict and diagnose disproportion. However, in areas of the world where much of obstetrics is "hands on", the availability of technology extremely limited, and the incidence of disproportion larger, the use of anthropometric measures might be useful and of some potential benefit. ^

Development of a rapid bioassessment method and index of biotic integrity for estuaries located along the northwest Gulf of Mexico

Recently it has been proposed that the evaluation of effects of pollutants on aquatic organisms can provide an early warning system of potential environmental and human health risks (NRC 1991). Unfortunately there are few methods available to aquatic biologists to conduct assessments of the effects of pollutants on aquatic animal community health. The primary goal of this research was to develop and evaluate the feasibility of such a method. Specifically, the primary objective of this study was to develop a prototype rapid bioassessment technique similar to the Index of Biotic Integrity (IBI) for the upper Texas and Northwestern Gulf of Mexico coastal tributaries. The IBI consists of a series of "metrics" which describes specific attributes of the aquatic community. Each of these metrics are given a score which is then subtotaled to derive a total assessment of the "health" of the aquatic community. This IBI procedure may provide an additional assessment tool for professionals in water quality management.^ The experimental design consisted primarily of compiling previously collected data from monitoring conducted by the Texas Natural Resource Conservation Commission (TNRCC) at five bayous classified according to potential for anthropogenic impact and salinity regime. Standardized hydrological, chemical, and biological monitoring had been conducted in each of these watersheds. The identification and evaluation of candidate metrics for inclusion in the estuarine IBI was conducted through the use of correlation analysis, cluster analysis, stepwise and normal discriminant analysis, and evaluation of cumulative distribution frequencies. Scores of each included metric were determined based on exceedances of specific percentiles. Individual scores were summed and a total IBI score and rank for the community computed.^ Results of these analyses yielded the proposed metrics and rankings listed in this report. Based on the results of this study, incorporation of an estuarine IBI method as a water quality assessment tool is warranted. Adopted metrics were correlated to seasonal trends and less so to salinity gradients observed during the study (0-25 ppt). Further refinement of this method is needed using a larger more inclusive data set which includes additional habitat types, salinity ranges, and temporal variation. ^

Relationship between enterotoxigenic Escherichia coli and travelers' diarrhea in Mexico, from 1992 to 1997

The purpose of this study was to examine the relationship between enterotoxigenic ETEC and travelers' diarrhea over a period of five years in Guadalajara, Mexico. Specifically, this study identified and characterized ETEC from travelers with diarrhea. The objectives were to study the colonization factor antigens, toxins and antibiotic sensitivity patterns in ETEC from 1992 to 1997 and to study the molecular epidemiology of ETEC by plasmid content and DNA restriction fragment patterns. ^ In this survey of travelers' diarrhea in Guadalajara, Mexico, 928 travelers with diarrhea were screened for enteric pathogens between 1992 and 1997. ETEC were isolated in 195 (19.9%) of the patients, representing the most frequent enteric pathogen identified. ^ A total of 31 antimicrobial susceptibility patterns were identified among ETEC isolates over the five-year period. ^ The 195 ETEC isolates contained two to six plasmids each, which ranged in size from 2.0 to 23 kbp. ^ Three different reproducible rRNA gene restriction patterns (ribotypes R-1 to R-3) were obtained among the 195 isolates with the enzyme, HindIII. ^ Colonization factor antigens (CFAs) were identified in 99 (51%) of the 195 ETEC strains studied. ^ Cluster analysis of the observations seen in the four assays all confirmed the five distinct groups of study-year strains of ETEC. Each group had a >95% similarity level of strains within the group and <60% similarity level between the groups. In addition, discriminant analysis of assay variables used in predicting the ETEC strains, reveal a >80% relationship between both the plasmid and rRNA content of ETEC strains and study-year. ^ These findings, based on laboratory observations of the differences in biochemical, antimicrobial susceptibility, plasmid and ribotype content, suggest complex epidemiology for ETEC strains in a population with travelers' diarrhea. The findings of this study may have implications for our understanding of the epidemiology, transmission, treatment, control and prevention of the disease. It has been suggested that an ETEC vaccine for humans should contain the most prevalent CFAs. Therefore, it is important to know the prevalence of these factors in ETEC in various geographical areas. ^ CFAs described in this dissertation may be used in different epidemiological studies in which the prevalence of CFAs and other properties on ETEC will be evaluated. Furthermore, in spite of an intense search in near 200 ETEC isolates for strains that may have clonal relationship, we failed to identify such strains. However, further studies are in progress to construct suitable live vaccine strains and to introduce several of CFAs in the same host organism by recombinant DNA techniques (Dr. Ann-Mari Svennerholm's lab). (Abstract shortened by UMI.)^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Disparities in foodborne illness in Harris County, Texas, 2005--2010

Using a retrospective cross-sectional approach, this study quantitatively analyzed foodborne illness data, restaurant inspection data, and census-derived socioeconomic and demographic data within Harris County, Texas between 2005 and 2010. The main research question investigated involved determining the extent to which contextual and regulatory conditions distinguish outbreak and non-outbreak establishments within Harris County. Two groups of Harris County establishments were analyzed: outbreak and non-outbreak restaurants. STATA 11 was employed to determine the average profiles of each category across both the regulatory and socioeconomic (contextual) variables. Cross tabulations of all of the non-quantitative variables were also performed, and finally, a discriminant analysis was conducted to assess how well the variables were able to allocate the restaurants into their respective categories. Contextual and regulatory conditions were found to be minimally associated with the occurrence of foodborne outbreaks within Harris County. Across both the categories (outbreak and non-outbreak establishments), variables included were extremely similar in means, and when possible to observe, distributions. The variables analyzed in this study, both regulatory and contextual, were not found to significantly allocate the establishments into their correct outbreak or non-outbreak categories. The implications of these findings are that regulatory processes and guidelines in place in Harris County do not effectively to distinguish outbreak from non-outbreak restaurants. Additionally, no socioeconomic or racial/ethnic patterns are apparent in the incidence of foodborne disease in the county. ^