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. ^

Birth defects among surviving children under seven years of age in Tianjin, China

Birth defects are a leading cause of infant mortality in the developed countries. They are also of increasing concern in many developing countries, such as China. However, prevalence and causes of birth defects in China are inadequately understood.^ The purpose of the present study was to estimated prevalence of birth defects in surviving children under seven years of age in Tianjin, China and investigate determinants of birth defects in the study area.^ The present study took place in Tianjin, China in 1986, involving 22,081 surviving children under seven years of age. Children with birth defects were ascertained through physical examinations by physicians during household visits and ascertainment of birth defects was verified through multiple sources. Of 22,081 surviving children, 524 had birth defects (23.7 per 1,000). The study noted a striking discrepancy in the prevalence of birth defects between urban and rural area. The prevalence of birth defects was 16.3 per 1,000 in the urban and 33.2 per 1,000 in the rural area.^ Using cases of birth defects ascertained from surviving children, a case-control study was carried out. The study observed that first-trimester maternal flu was associated with increased risk of both major and minor birth defects in children after controlling for other maternal factors (adjusted odds ratio (OR) = 8.7, 95% confidence interval (CI) = 4.3-17.3; OR = 3.6, 95% CI = 1.7-7.5). This association could be biased by different reporting of exposure between mothers of children with birth defects and mothers of children without defects. This study indicated that maternal flu was also associated with congenital heart defects and polydactyly after controlling for other maternal factors (adjusted OR = 32.3, 95% CI = 13.3-78.3; adjusted OR = 5.5, 95% CI = 1.1-27.7). The associations remained when affected controls (children with similar birth defects other than congenital heart defects or polydactyly) were used (adjusted OR = 4.3, 95% CI = 1.2-15.3; OR = 1.4, 95% CI = 1.4-7.9). A weak association between first-trimester vaginal bleeding and selected groups of birth defects was found in this study, but the association may be confounded by other factors. Maternal smoking during pregnancy was modestly associated with cleft lip with or without cleft palate (OR = 1.4, 95% = 0.4-4.9), but the association may be due to chance. Some major limitations in this study warrant caution in interpretation of the findings, especially the causal relation. ^

Community participation in health services

This study critically analyzes and synthesizes community participation (CP) theory across disciplines, defining and beginning to map out the elements of CP according to a preliminary framework of structure, process, intermediate outcomes, and ultimate outcomes. The first study component sought to determine the impact of Sight N' Soul, a CP project utilizing neighborhood health workers (NHWs), on appointment missing in an indigent urban African-American population. It found that persons entering the vision care system through contact with an NEW were about a third less likely to miss an appointment than those persons entering the system through some other avenue. While theory in this area remains too poorly developed to hypothesize causal relationships between structure, process, and outcomes, a summary of the elements of Sight N' Soul's structure and process both developed the preliminary framework and serves as a first step to mapping these relationships. The second component of the study uncovered the elements of structure and process that may contribute to a sustained egalitarian partnership between community people and professionals, a CP program called Project HEAL. Elements of Project HEAL's structure and process included a shared belief in the program; spirituality; contribution, ownership, and reciprocation; a feeling of family; making it together; honesty, trust, and openness about conflict; the inevitability of uncertainty and change; and the guiding interactional principles of respect; love, care, and compassion; and personal responsibility. The third component analyzed the existing literature, identifying and addressing gaps and inconsistencies and highlighting areas needing more highly developed ethical analysis. Focal issues include the political, economic, and historical context of CP; the power of naming; the issue of purpose; the nature of community; the power to muster and allocate resources; and the need to move to a systems view of health and well-being, expanding our understanding of the universe of potential outcomes of CP, including iatrogenic outcomes. Intermediate outcomes might include change in community, program, and individual capacity, as well as improved health care delivery. Ultimate outcomes include increased positive interdependencies and opportunities for contribution; improved mental, physical, and spiritual health; increased social justice; and decreased exploitation. ^

Physical activity and survival after a first myocardial infarction: The Corpus Christi Heart Project

Previous studies have demonstrated that habitual physical activity is associated with a reduced risk of incident coronary heart disease (CHD). However, the role of physical activity in lowering the risk of all-cause mortality, CHD mortality, reinfarction, or receipt of a revascularization procedure after a first myocardial infarction (MI) remains unresolved, particularly in minority populations. To investigate the associations between physical activity and risk of all-cause mortality, CHD mortality, reinfarction, and receipt of a revascularization procedure, this study was conducted among Mexican-American and non-Hispanic white women and men who survived a first MI. The Corpus Christi Heart Project, a population-based cardiovascular surveillance study, provide data which included vital status, survival time, medical history, CHD risk factor information, including level of physical activity among Mexican-American and non-Hispanic white adults who had experienced a first MI between May, 1988 and April, 1990. MI patients were interviewed at baseline and annually thereafter until their death or through May, 1995. A categorical variable was created to reflect change in level of physical activity following the first MI; categories included (1) sedentary with no change, (2) decreased activity, (3) increased activity, and (4) moderate activity with no change (the referent group). Proportional hazards regression analyses were used to assess the relationship of level of physical activity and risk of death, reinfarction, or receipt of a revascularization procedure adjusting for age, sex, ethnicity, severity of MI, and CHD risk factor status. Over a 7-year follow-up period, the relative risk (95% confidence intervals) of all-cause mortality was 4.67 (2.27, 9.60) for the sedentary-no change group, 2.33 (0.96, 5.67) for the decreased activity group, and 0.52 (0.11, 2.41) for the increased activity group. The relative risk of CHD mortality was 6.92 (2.05, 23.34) for the sedentary-no change group, 2.40 (0.55, 10.51) for the decreased activity group, and 1.58 (0.26, 9.65) for the increased activity group. The relative risk for reinfarction was 2.50 (1.52, 4.10) for the sedentary-no change group, 2.26 (1.24, 4.12) for the decreased activity group, and 0.52 (0.21, 1.32) for the increased activity group. Finally, the relative risk for receipt of a revascularization procedure was 0.65 (0.39, 1.07) for the sedentary-no change group, 0.45 (0.22, 0.92) for the decreased activity group, and 1.01 (0.51, 2.02) for the increased activity group. No interactions were observed for ethnicity or severity of first MI. These results are consistent with the hypothesis that moderate physical activity is independently associated with a lower risk of all-cause mortality, CHD mortality, and reinfarction, but not revascularization, among Mexican-American and non-Hispanic white, female and male, first MI patients. These results also support the current recommendation that physical activity plays an important role in the secondary prevention of CHD. ^

A comparison of Markov and generalized linear models of hospital mortality

This paper reports a comparison of three modeling strategies for the analysis of hospital mortality in a sample of general medicine inpatients in a Department of Veterans Affairs medical center. Logistic regression, a Markov chain model, and longitudinal logistic regression were evaluated on predictive performance as measured by the c-index and on accuracy of expected numbers of deaths compared to observed. The logistic regression used patient information collected at admission; the Markov model was comprised of two absorbing states for discharge and death and three transient states reflecting increasing severity of illness as measured by laboratory data collected during the hospital stay; longitudinal regression employed Generalized Estimating Equations (GEE) to model covariance structure for the repeated binary outcome. Results showed that the logistic regression predicted hospital mortality as well as the alternative methods but was limited in scope of application. The Markov chain provides insights into how day to day changes of illness severity lead to discharge or death. The longitudinal logistic regression showed that increasing illness trajectory is associated with hospital mortality. The conclusion is reached that for standard applications in modeling hospital mortality, logistic regression is adequate, but for new challenges facing health services research today, alternative methods are equally predictive, practical, and can provide new insights. ^

Design and implementation of a multicriteria medical decision support system for diagnosis and treatment

Health care providers face the problem of trying to make decisions with inadequate information and also with an overload of (often contradictory) information. Physicians often choose treatment long before they know which disease is present. Indeed, uncertainty is intrinsic to the practice of medicine. Decision analysis can help physicians structure and work through a medical decision problem, and can provide reassurance that decisions are rational and consistent with the beliefs and preferences of other physicians and patients. ^ The primary purpose of this research project is to develop the theory, methods, techniques and tools necessary for designing and implementing a system to support solving medical decision problems. A case study involving “abdominal pain” serves as a prototype for implementing the system. The research, however, focuses on a generic class of problems and aims at covering theoretical as well as practical aspects of the system developed. ^ The main contributions of this research are: (1) bridging the gap between the statistical approach and the knowledge-based (expert) approach to medical decision making; (2) linking a collection of methods, techniques and tools together to allow for the design of a medical decision support system, based on a framework that involves the Analytic Network Process (ANP), the generalization of the Analytic Hierarchy Process (AHP) to dependence and feedback, for problems involving diagnosis and treatment; (3) enhancing the representation and manipulation of uncertainty in the ANP framework by incorporating group consensus weights; and (4) developing a computer program to assist in the implementation of the system. ^

Evaluation of the accuracy of multilevel analysis parameter estimates for intra-cluster correlation in correlated binary data

Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^

A nonparametric method of comparing the partial areas under two correlated receiver operating characteristic curves

A non-parametric method was developed and tested to compare the partial areas under two correlated Receiver Operating Characteristic curves. Based on the theory of generalized U-statistics the mathematical formulas have been derived for computing ROC area, and the variance and covariance between the portions of two ROC curves. A practical SAS application also has been developed to facilitate the calculations. The accuracy of the non-parametric method was evaluated by comparing it to other methods. By applying our method to the data from a published ROC analysis of CT image, our results are very close to theirs. A hypothetical example was used to demonstrate the effects of two crossed ROC curves. The two ROC areas are the same. However each portion of the area between two ROC curves were found to be significantly different by the partial ROC curve analysis. For computation of ROC curves with large scales, such as a logistic regression model, we applied our method to the breast cancer study with Medicare claims data. It yielded the same ROC area computation as the SAS Logistic procedure. Our method also provides an alternative to the global summary of ROC area comparison by directly comparing the true-positive rates for two regression models and by determining the range of false-positive values where the models differ. ^

Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

Multilevel analysis for a longitudinal clinical trial

This study applies the multilevel analysis technique to longitudinal data of a large clinical trial. The technique accounts for the correlation at different levels when modeling repeated blood pressure measurements taken throughout the trial. This modeling allows for closer inspection of the remaining correlation and non-homogeneity of variance in the data. Three methods of modeling the correlation were compared. ^

Analysis of recurrent failure times: A time-dependent Yule process approach

Analysis of recurrent events has been widely discussed in medical, health services, insurance, and engineering areas in recent years. This research proposes to use a nonhomogeneous Yule process with the proportional intensity assumption to model the hazard function on recurrent events data and the associated risk factors. This method assumes that repeated events occur for each individual, with given covariates, according to a nonhomogeneous Yule process with intensity function λx(t) = λ 0(t) · exp( x′β). One of the advantages of using a non-homogeneous Yule process for recurrent events is that it assumes that the recurrent rate is proportional to the number of events that occur up to time t. Maximum likelihood estimation is used to provide estimates of the parameters in the model, and a generalized scoring iterative procedure is applied in numerical computation. ^ Model comparisons between the proposed method and other existing recurrent models are addressed by simulation. One example concerning recurrent myocardial infarction events compared between two distinct populations, Mexican-American and Non-Hispanic Whites in the Corpus Christi Heart Project is examined. ^

Forecasting cost based on a stochastic utilization plan and a fixed cost function

The application of Markov processes is very useful to health-care problems. The objective of this study is to provide a structured methodology of forecasting cost based upon combining a stochastic model of utilization (Markov Chain) and deterministic cost function. The perspective of the cost in this study is the reimbursement for the services rendered. The data to be used is the OneCare database of claim records of their enrollees over a two-year period of January 1, 1996–December 31, 1997. The model combines a Markov Chain that describes the utilization pattern and its variability where the use of resources by risk groups (age, gender, and diagnosis) will be considered in the process and a cost function determined from a fixed schedule based on real costs or charges for those in the OneCare claims database. The cost function is a secondary application to the model. Goodness-of-fit will be used checked for the model against the traditional method of cost forecasting. ^

Social capital and adolescent health risk behavior in El Salvador

An emerging body of research suggests that the social capital available in one's social environment, as defined by supportive and caring interpersonal relationships, may provide a protective effect against a number of youth risk behaviors. In exploring the potential protective effect of social capital at school and at home on adolescent health and social risk behavior, a comprehensive youth risk behavior study was carried out in El Salvador during the summer of 1999 with a sample of 984 secondary school students attending 16 public rural and urban schools. The following dissertation, entitled Social Capital and Adolescent Health Risk Behavior in El Salvador, presents three papers centered on the topics of social capital and risk behavior. ^ Paper #1. Dangers in the Adolescent River of Life: A Descriptive Study of Youth Risk Behavior among Urban and Rural presents prevalence estimates of four principal youth risk behavior domains—aggression, depression, substance use, and sexual behaviors among students primarily between the ages of 13 and 17 who attend public schools in El Salvador. The prevalence and distribution of risk behaviors is examined by gender, geographic school location, age, and subjective economic status. ^ Paper #2. Social Capital and Adolescent Health Risk Behavior among Secondary School Students in El Salvador explores the relationship between social resources (social capital) within the school context and several youth risk behaviors. Results indicated that students who perceived higher social cohesion at school and higher parental social support were significantly less likely to report fighting, having been threatened or hurt with a weapon, suicidal ideation, and sexual intercourse than students with lower perceived social cohesion at school and parental social support after adjusting for several socio-demographic variables. ^ Lastly, paper #3. School Health Environment and Social Capital : Moving beyond the individual to the broader social developmental context provides a theoretical and empirical basis for moving beyond the predominant individual-focus and physical health concerns of school health promotion to the larger social context of schools and social health of students. This paper explores the concept of social capital and relevant adolescent development theories in relation to the influence of social context on adolescent health and behavior. ^

Measurement and correlates of physical activity behavior among older minority women

Research has shown that physical activity serves a preventive function against the development of several major chronic diseases. However, studying physical activity and its health benefits is difficult due to the complexity of measuring physical activity. The overall aim of this research is to contribute to the knowledge of both correlates and measurement of physical activity. Data from the Women On The Move study were used for this study (n = 260), and the results are presented in three papers. The first paper focuses on the measurement of physical activity and compares an alternate coding method with the standard coding method for calculating energy expenditure from a 7-day activity diary. Results indicate that the alternative coding scheme could produce similar results to the standard coding in terms of total activity expenditure. Even though agreement could not be achieved by dimension, the study lays the groundwork for a coding system that saves considerable amount of time in coding activity and has the ability to estimate expenditure more accurately for activities that can be performed at varying intensity levels. The second paper investigates intra-day variability in physical activity by estimating the variation in energy expenditure for workers and non-workers and identifying the number of days of diary self-report necessary to reliably estimate activity. The results indicate that 8 days of activity are needed to reliably estimate total activity for individuals who don't work and 12 days of activity are needed to reliably estimate total activity for those who work. Days of diary self-report required by dimension for those who don't work range from 6 to 16 and for those who work from 6 to 113. The final paper presents findings on the relationship between daily living activity and Type A behavior pattern. Significant findings are observed for total activity and leisure activity with the Temperament Scale summary score. Significant findings are also observed for total activity, household chores, work, leisure activity, exercise, and inactivity with one or more of the individual items on the Temperament Scale. However, even though some significant findings were observed, the overall models did not reveal meaningful associations. ^

Risk Index Score (RISc)

The main objective of this study was to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that can be translated into a simple scoring system in order to ascertain stroke cases using hospital admission medical records data. This algorithm, the Risk Index Score (RISc), was developed using data collected prospectively by the Brain Attack Surveillance in Corpus Christ (BASIC) project. The validity of the RISc was evaluated by estimating the concordance of scoring system stroke ascertainment to stroke ascertainment accomplished by physician review of hospital admission records. The goal of this study was to develop a rapid, simple, efficient, and accurate method to ascertain the incidence of stroke from routine hospital admission hospital admission records for epidemiologic investigations. ^ The main objectives of this study were to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that could be translated into a simple scoring system to ascertain stroke cases using hospital admission medical records data. (Abstract shortened by UMI.)^