988 resultados para Biology, Biostatistics|Health Sciences, Epidemiology


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Mycoplasma hyopneumoniae is the major cause of enzootic pneumonia (EP) in domestic pigs, a disease with low mortality but high morbidity, having a great economic impact for producers. In Switzerland EP has been successfully eradicated, however, sporadic outbreaks are observed with no obvious source. Besides the possibility of recurrent outbreaks due to persisting M. hyopneumoniae strains within the pig population, there is suspicion that wild boars might introduce M. hyopneumoniae into swine herds. To elucidate possible links between domestic pig and wild boar, epidemiological investigations of recent EP outbreaks were initiated and lung samples of pig and wild boar were tested for the presence of specific genotypes by multilocus sequence typing (MLST). Despite generally different genotypes in wild boar, outbreak strains could be found in geographically linked wild boar lungs after, but so far not before the outbreak. Recurrent outbreaks in a farm were due to the same strain, indicating unsuccessful sanitation rather than reintroduction by wild boar. In another case outbreaks in six different farms were caused by the same strain never found in wild boar, confirming spread between farms due to hypothesized animal transport. Results indicate the presence of identical lineages of wild boar and domestic pig strains, and possible transmission of M. hyopneumoniae between wild boar and pig. However, the role of wild boar might be rather one as a recipient than a transmitter. More important than contact to wild boar for sporadic outbreaks in Switzerland is apparently persistence of M. hyopneumoniae within a farm as well as transmission between farms.

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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. ^

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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. ^

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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.)^

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The Federal Coal Mine Health and Safety Act of 1969 required that periodic chest radiographs be offered to underground coal miners to protect the miners from the development of Coal Workers' Pneumoconiosis (CWP) and progression of the disease to progressive massive fibrosis (PMF). These examinations are administered by the National Institute for Occupational Safety and Health (NIOSH) through the Coal Workers' Health Surveillance Program (CWHSP). The mine operator is required to provide each miner with the opportunity to have the chest radiograph at no cost to the miner.^ Three rounds of examinations have been conducted since 1969 and the fourth is underway. The decrease in participation over rounds is of great concern if the incidence and progression of CWP are to be understood and controlled.^ This study developed rates of participation for each of 558 West Virginia underground coal mines who submitted or had NIOSH assigned plans for making chest radiographs available during the third round, July 1978 through December 1980. These rates were analyzed in relation to desired levels of participation and to reinforcing, predisposing and enabling factors presumed to affect rates of participation in disease prevention and surveillance programs.^ Two reinforcing factors, size of mine and inclusion of the mine in the National Coal Study (NCS) epidemiology research program, and the enabling factor, use of an on-site radiograph facility, demonstrated highly significant relationships to participation rates.^ The major findings of the study were: (1) Participation in the CWHSP is even lower than previously estimated; (2) CWHSP program evaluation is not systematic and program data base is not complete and comprehensive; and (3) NIOSH program policy is not clear and administration of the CWHSP is fragmented and lacks adequate fiscal and personnel resources. ^

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Current statistical methods for estimation of parametric effect sizes from a series of experiments are generally restricted to univariate comparisons of standardized mean differences between two treatments. Multivariate methods are presented for the case in which effect size is a vector of standardized multivariate mean differences and the number of treatment groups is two or more. The proposed methods employ a vector of independent sample means for each response variable that leads to a covariance structure which depends only on correlations among the $p$ responses on each subject. Using weighted least squares theory and the assumption that the observations are from normally distributed populations, multivariate hypotheses analogous to common hypotheses used for testing effect sizes were formulated and tested for treatment effects which are correlated through a common control group, through multiple response variables observed on each subject, or both conditions.^ The asymptotic multivariate distribution for correlated effect sizes is obtained by extending univariate methods for estimating effect sizes which are correlated through common control groups. The joint distribution of vectors of effect sizes (from $p$ responses on each subject) from one treatment and one control group and from several treatment groups sharing a common control group are derived. Methods are given for estimation of linear combinations of effect sizes when certain homogeneity conditions are met, and for estimation of vectors of effect sizes and confidence intervals from $p$ responses on each subject. Computational illustrations are provided using data from studies of effects of electric field exposure on small laboratory animals. ^

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In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

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This study describes the incidence and mortality of uterine cervical cancer among Texas Anglo and Hispanic women, compares these data with respective data from the U.S. SEER Program, and determines factors which explain observed differences between the Texas ethnic groups and between Texas and SEER women. A total of 1,052 invasive and 1,852 in situ cervical cancer cases diagnosed during 1976-1985 among Texas residents were identified from the Texas Cancer Registry for study.^ The effect of ethnicity on the incidence of cervical cancer was found to be strongly modified by age. Texas Hispanic women 35 years and older were found to be at significantly greater risk (two- to four-fold) of invasive cervical cancer than Texas Anglos, and the risk was greatest among women 55-69 years. Compared with SEER females, both Texas ethnic groups exhibited excess risks of invasive cancer, but the magnitude varied with age. In contrast, Texas females were diagnosed less frequently with in situ cervical cancer than SEER females, and Hispanics had the largest differentials.^ As an indicator of differences in screening utilization between Texas and SEER ethnic groups, comparisons of in situ with invasive rates revealed both Texas ethnic groups in all age groups to have lower ratios than respective SEER females. Texas Hispanics had the lowest ratios. A larger percentage of squamous cell tumors were diagnosed among SEER females compared with Texas females, also supporting the finding of less screening. Texas invasive cases did not differ by ethnic group in the distribution of cell types. Hispanics 35-54 years had higher rates than Texas Anglos and SEER Hispanics for all four cell types.^ Declines in the incidence of invasive tumors over time were seen among Texas Anglos 35-54 years and Hispanics 55+ years. The mortality of cervical cancer also declined among Texas Anglo and Hispanic females 55+ years, but the rates still remained highest among these groups.^ In summary, these data indicate increased risks of invasive cervical cancer and less screening among subgroups of Texas females. Prevention efforts should be directed toward these Texas women at high risk of invasive cervical tumors. ^

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Diarrhea is a major public health problem in developing countries among infants and young children. Not all episodes of diarrhea are confirmed as infectious, suggesting alternate mechanisms. One such is immunoglobulin E (IgE) mediated or allergic diarrhea that can be seen in food allergy. In order to determine the relation between allergic gastroenteritis and feeding practice, a cohort of 152 infants were followed from birth to one year age in a rural community of Egypt between October, 1987 to April, 1988 were analyzed. In multivariate analysis of the data, statistically conclusive higher risk had been observed with presence of factors, like consumption of milk pudding (RR = 7.4, CI = 1.5-36.2 and p = 0.01), infant's age 3-6 months (RR = 7.7, CI = 1.3-45.9 and p = 0.02), infants whose mothers were vaccinated antenatally (RR = 3.1, CI = 1.3-7.0 and p = 1.3-7.0, p = 0.0) and wet-nursed infants (RR = 2.7, CI = 1.1-6.5 and p = 0.02). In contrast, infants who were completely breast-fed (RR = 0.13, CI = 0.02-0.6 and p = 0.01), and infants family owning a television set (RR = 0.29, CI = 0.1-0.6 and p = 0.0) were less likely to develop allergic gastroenteritis. The role of IgE on development of persistent diarrhea was also examined in a nested case-control design. Multivariate analysis revealed a significant association between detection of fecal IgE and development of persistent diarrhea compared to acute diarrhea (OR = 3.32, CI = 1.0-10.9 and p = 0.04) and health or non diarrhea (OR = 4.8, CI = 1.07-21.7 and p = 0.03) controls. ^

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The objective was to study knowledge, attitudes, practice (KAP) and needs regarding infection control measures using two cross-sectional surveys from 1999 and 2010 conducted in India. Both data collection instruments had only about 35 comparable variables in common. In 1999, there were 456 respondents (dentists) who completed a self-administered survey instrument compared to 272 respondents in 2010. Both the 1999 and 2010 samples were mutually independent with no overlap, had regional differences, and therefore, were not completely comparable for changes in KAP over time. While almost all respondents from both surveys felt that education in dental safety was needed and wanted mandatory dental safety curriculum in dental schools, severe inadequacies in dental safety knowledge, protection against immunizable diseases, and practice of universal precaution were noted. Data from the study demonstrated that there is a substantial opportunity to improve the knowledge, attitude and practice of dental infection control and occupational safety in India. Few respondents (27%) reported that the infectious disease status of a patient is always known and a significant number reported that they had the right to refuse care for patients of known infectious disease status. This indicates that Stigma in treating HIV/AIDS patients remains a concern, which in turn suggests that a stronger focus on educating dentists about dental safety and on stigma and infectious disease is needed. Information obtained from this study could be utilized for developing policies oriented towards increasing dental safety educational efforts, in both dental schools as curriculum, and for practicing dentists through professional updates or continuing dental education.^

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The Work Limitations Questionnaire (WLQ) is used to determine the amount of work loss and productivity which stem from certain health conditions, including rheumatoid arthritis and cancer. The questionnaire is currently scored using methodology from Classical Test Theory. Item Response Theory, on the other hand, is a theory based on analyzing item responses. This study wanted to determine the validity of using Item Response Theory (IRT), to analyze data from the WLQ. Item responses from 572 employed adults with dysthymia, major depressive disorder (MDD), double depressive disorder (both dysthymia and MDD), rheumatoid arthritis and healthy individuals were used to determine the validity of IRT (Adler et al., 2006).^ PARSCALE, which is IRT software from Scientific Software International, Inc., was used to calculate estimates of the work limitations based on item responses from the WLQ. These estimates, also known as ability estimates, were then correlated with the raw score estimates calculated from the sum of all the items responses. Concurrent validity, which claims a measurement is valid if the correlation between the new measurement and the valid measurement is greater or equal to .90, was used to determine the validity of IRT methodology for the WLQ. Ability estimates from IRT were found to be somewhat highly correlated with the raw scores from the WLQ (above .80). However, the only subscale which had a high enough correlation for IRT to be considered valid was the time management subscale (r = .90). All other subscales, mental/interpersonal, physical, and output, did not produce valid IRT ability estimates.^ An explanation for these lower than expected correlations can be explained by the outliers found in the sample. Also, acquiescent responding (AR) bias, which is caused by the tendency for people to respond the same way to every question on a questionnaire, and the multidimensionality of the questionnaire (the WLQ is composed of four dimensions and thus four different latent variables) probably had a major impact on the IRT estimates. Furthermore, it is possible that the mental/interpersonal dimension violated the monotonocity assumption of IRT causing PARSCALE to fail to run for these estimates. The monotonicity assumption needs to be checked for the mental/interpersonal dimension. Furthermore, the use of multidimensional IRT methods would most likely remove the AR bias and increase the validity of using IRT to analyze data from the WLQ.^

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Background and Objective. Ever since the human development index was published in 1990 by the United Nations Development Programme (UNDP), many researchers started searching and corporative studying for more effective methods to measure the human development. Published in 1999, Lai’s “Temporal analysis of human development indicators: principal component approach” provided a valuable statistical way on human developmental analysis. This study presented in the thesis is the extension of Lai’s 1999 research. ^ Methods. I used the weighted principal component method on the human development indicators to measure and analyze the progress of human development in about 180 countries around the world from the year 1999 to 2010. The association of the main principal component obtained from the study and the human development index reported by the UNDP was estimated by the Spearman’s rank correlation coefficient. The main principal component was then further applied to quantify the temporal changes of the human development of selected countries by the proposed Z-test. ^ Results. The weighted means of all three human development indicators, health, knowledge, and standard of living, were increased from 1999 to 2010. The weighted standard deviation for GDP per capita was also increased across years indicated the rising inequality of standard of living among countries. The ranking of low development countries by the main principal component (MPC) is very similar to that by the human development index (HDI). Considerable discrepancy between MPC and HDI ranking was found among high development countries with high GDP per capita shifted to higher ranks. The Spearman’s rank correlation coefficient between the main principal component and the human development index were all around 0.99. All the above results were very close to outcomes in Lai’s 1999 report. The Z test result on temporal analysis of main principal components from 1999 to 2010 on Qatar was statistically significant, but not on other selected countries, such as Brazil, Russia, India, China, and U.S.A.^ Conclusion. To synthesize the multi-dimensional measurement of human development into a single index, the weighted principal component method provides a good model by using the statistical tool on a comprehensive ranking and measurement. Since the weighted main principle component index is more objective because of using population of nations as weight, more effective when the analysis is across time and space, and more flexible when the countries reported to the system has been changed year after year. Thus, in conclusion, the index generated by using weighted main principle component has some advantage over the human development index created in UNDP reports.^

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This study compared initial year trends in prenatal care and birth outcomes of women enrolled in the Texas Children's Health Insurance Program (CHIP) Perinatal program to trends in Medicaid program women. The study utilized claims data from Community Health Choice (CHC), a health plan in Harris County, Texas that provides coverage to both populations. Quarterly data was analyzed and compared for the first two years of the CHIP Perinatal program (2007-2008) to determine if outcome trends for the CHIP program improved over the outcome trends seen with those enrolled in Medicaid. Study findings indicate an increase in the quarterly prenatal care utilization for the CHIP Perinatal population from 2007 to 2008 and the associated birth weights of babies delivered also had marginal improvements during the same timeframe. Enrollees in Medicaid continued to have overall better outcomes than those enrolled within the CHIP Perinatal program. However, the study showed that the rate of improvement in both prenatal care utilization and birth outcomes were greater for the CHIP Perinatal enrollees than those enrolled in Medicaid. ^ The majority of these improvements were significant when comparing each coverage program and from year to year. Lastly, the study showed that there was a correlation between prenatal care utilization and birth outcomes. However, further analysis of the data could not conclusively indicate that access to prenatal care services provided by the CHIP Perinatal program contributed to the increases observed in utilization and birth outcomes for the study's sample population.^

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Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

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Studies suggest that slim infants (low weight-for-height) experienced higher mortality rates than average or high weight-for-height infants (Miller and Hassanein, 1973; Hoffman, Meirik, and Bakketeig, 1984). In this study, the 1980 National Natality Survey and the National Fetal Mortality Survey were used to examine the association of weight, height and perinatal mortality. All singleton births to white married mothers, between 18 and 34 years of age and of parity less than 4, for whom both mother's and hospital questionnaires were completed in those two surveys (3796 live births and 2043 fetal deaths) were selected for analysis. Overall, low weight and height infants had excess mortality rates. However, after adjustment for low birthweight and preterm birth status, low weight and height infants had only slightly higher mortality rates than their medium or high weight and height counterparts. The current study consists of relatively well-educated white married mothers of optimal reproductive age and low parity. Therefore, lower than expected mortality rates for slim infants may be attributed to these favorable demographic factors in this sample as compared with previous studies, or because of advances in perinatal medicine, slim infants may be prevented from achieving the high mortality seen in earlier studies. ^