Poverty, Educational Attainment and Health Among America’s Children: Current and Future Effects of Population Diversification and Associated Socioeconomic Change

A complex of interrelated factors including minority status, poverty, education, health status, and other factors determine the general welfare of children in America, particularly in heavily diverse states such as Texas. Although racial/ethnic status is clearly only a concomitant factor in that determination it is a factor for which future projections are available and for which the relationships with the other factors in the complex can be assessed. After examining the nature of the interrelationships between these factors we utilize direct standardization techniques to examine how the future diversification of the United States and Texas will affect the number of children in poverty, the educational status of the householders in households in which children in poverty live and the health status of children in 2040 assuming that the current relationships between minority status and these socioeconomic factors continue into the future. In the results of the analyses, data are compared with the total population of the United States and Texas in 2040 assumed in the first simulation scenario, to have the race/ethnicity characteristics of 2008 and in the second those projected for 2040 by the U.S. Census Bureau for the nation and by the Texas State Data Center for Texas in 2040. The results show that the diversification of the population could increase the number of children in poverty in the United States by nearly 1.8 million more than would occur with the lower levels of diversification evident in 2008. In addition, poverty would become increasingly concentrated among minority children with minority children accounting for 76.2 percent of all children in poverty by 2040 and with Hispanic children accounting for nearly half of the children in poverty by 2040. Results for educational attainment show an increasing concentration of minority children in households with householders with very low levels of education such that by 2040, 85.2 percent of the increase in the number of children in poverty would be in households with a householder with less than a high school level of education. Finally, the results related to several health status factors show that children in poverty will have a higher prevalence of nearly all health conditions. For example, the number of children with untreated dental conditions could increase to more than 4 million in the United States and to nearly 500,000 in Texas. The results clearly show that improving the welfare of children in America will require concerted efforts to change the poverty, educational, and health status characteristics associated with minority status and particularly Hispanic status. Failing to do so will lead to a future in which America’s children are increasingly impoverished, more poorly educated, and less healthy and which, as a result, is an America with a more tentative future.

The effects of population density on the spread of disease

The objective of this study is to identify the relationship between population density and the initial stages of the spread of disease in a local population. This study proposes to concentrate on the question of how population density affects the distribution of the susceptible individuals in a local population and thus affects the spread of the disease, measles. Population density is measured by the average of the number of contacts with susceptible individuals by each individual in the population during a fixed-length time period. The term “contact with susceptible individuals” means sufficient contact between two people for the disease to pass from an infectious person to a susceptible person. The fixed-length time period is taken to be the average length of time an infected person is infectious without symptoms of the disease. For this study of measles, the time period will be seven days. ^ While much attention has been given to modeling the entire epidemic process of measles, attempts have not been made to study the characteristics of contact rates required to initiate an epidemic. This study explores the relationship between population density, given a specific herd immunity rate in the population, and initial rate of the spread of the disease by considering the underlying distribution of contacts with susceptibles by the individuals in the population. ^ This study does not seek to model an entire measles epidemic, but to model the above stated relationship for the local population within which the first infective person is introduced. This study describes the mathematical relationship between population density parameters and contact distribution parameters. ^ The results are displayed in graphs that show the effects of different population densities on the spread of disease. The results support the idea that the number of new infectives is strongly related to the distribution of susceptible contacts. The results also show large differences in the epidemic measures between populations with densities equal to four versus three. ^

Procedure for the identification of population characteristics for targeting intervention services on the basis of outcome-goal priorities: Case management services for the chronic mentally ill

Although the processes involved in rational patient targeting may be obvious for certain services, for others, both the appropriate sub-populations to receive services and the procedures to be used for their identification may be unclear. This project was designed to address several research questions which arise in the attempt to deliver appropriate services to specific populations. The related difficulties are particularly evident for those interventions about which findings regarding effectiveness are conflicting. When an intervention clearly is not beneficial (or is dangerous) to a large, diverse population, consensus regarding withholding the intervention from dissemination can easily be reached. When findings are ambiguous, however, conclusions may be impossible.^ When characteristics of patients likely to benefit from an intervention are not obvious, and when the intervention is not significantly invasive or dangerous, the strategy proposed herein may be used to identify specific characteristics of sub-populations which may benefit from the intervention. The identification of these populations may be used both in further informing decisions regarding distribution of the intervention and for purposes of planning implementation of the intervention by identifying specific target populations for service delivery.^ This project explores a method for identifying such sub-populations through the use of related datasets generated from clinical trials conducted to test the effectiveness of an intervention. The method is specified in detail and tested using the example intervention of case management for outpatient treatment of populations with chronic mental illness. These analyses were applied in order to identify any characteristics which distinguish specific sub-populations who are more likely to benefit from case management service, despite conflicting findings regarding its effectiveness for the aggregate population, as reported in the body of related research. However, in addition to a limited set of characteristics associated with benefit, the findings generated, a larger set of characteristics of patients likely to experience greater improvement without intervention. ^

Population amalgamation and genetic variation: observations on artificially agglomerated tribal populations of Central and South America.

The interpretation of data on genetic variation with regard to the relative roles of different evolutionary factors that produce and maintain genetic variation depends critically on our assumptions concerning effective population size and the level of migration between neighboring populations. In humans, recent population growth and movements of specific ethnic groups across wide geographic areas mean that any theory based on assumptions of constant population size and absence of substructure is generally untenable. We examine the effects of population subdivision on the pattern of protein genetic variation in a total sample drawn from an artificial agglomerate of 12 tribal populations of Central and South America, analyzing the pooled sample as though it were a single population. Several striking findings emerge. (1) Mean heterozygosity is not sensitive to agglomeration, but the number of different alleles (allele count) is inflated, relative to neutral mutation/drift/equilibrium expectation. (2) The inflation is most serious for rare alleles, especially those which originally occurred as tribally restricted "private" polymorphisms. (3) The degree of inflation is an increasing function of both the number of populations encompassed by the sample and of the genetic divergence among them. (4) Treating an agglomerated population as though it were a panmictic unit of long standing can lead to serious biases in estimates of mutation rates, selection pressures, and effective population sizes. Current DNA studies indicate the presence of numerous genetic variants in human populations. The findings and conclusions of this paper are all fully applicable to the study of genetic variation at the DNA level as well.

Population genetics of VNTR loci and their applications in evolutionary studies

Variable number of tandem repeats (VNTR) are genetic loci at which short sequence motifs are found repeated different numbers of times among chromosomes. To explore the potential utility of VNTR loci in evolutionary studies, I have conducted a series of studies to address the following questions: (1) What are the population genetic properties of these loci? (2) What are the mutational mechanisms of repeat number change at these loci? (3) Can DNA profiles be used to measure the relatedness between a pair of individuals? (4) Can DNA fingerprint be used to measure the relatedness between populations in evolutionary studies? (5) Can microsatellite and short tandem repeat (STR) loci which mutate stepwisely be used in evolutionary analyses?^ A large number of VNTR loci typed in many populations were studied by means of statistical methods developed recently. The results of this work indicate that there is no significant departure from Hardy-Weinberg expectation (HWE) at VNTR loci in most of the human populations examined, and the departure from HWE in some VNTR loci are not solely caused by the presence of population sub-structure.^ A statistical procedure is developed to investigate the mutational mechanisms of VNTR loci by studying the allele frequency distributions of these loci. Comparisons of frequency distribution data on several hundreds VNTR loci with the predictions of two mutation models demonstrated that there are differences among VNTR loci grouped by repeat unit sizes.^ By extending the ITO method, I derived the distribution of the number of shared bands between individuals with any kinship relationship. A maximum likelihood estimation procedure is proposed to estimate the relatedness between individuals from the observed number of shared bands between them.^ It was believed that classical measures of genetic distance are not applicable to analysis of DNA fingerprints which reveal many minisatellite loci simultaneously in the genome, because the information regarding underlying alleles and loci is not available. I proposed a new measure of genetic distance based on band sharing between individuals that is applicable to DNA fingerprint data.^ To address the concern that microsatellite and STR loci may not be useful for evolutionary studies because of the convergent nature of their mutation mechanisms, by a theoretical study as well as by computer simulation, I conclude that the possible bias caused by the convergent mutations can be corrected, and a novel measure of genetic distance that makes the correction is suggested. In summary, I conclude that hypervariable VNTR loci are useful in evolutionary studies of closely related populations or species, especially in the study of human evolution and the history of geographic dispersal of Homo sapiens. (Abstract shortened by UMI.) ^

The population health performance of medical students at two medical schools

Public Health and medicine are complimentary disciplines dedicated to the health and well-being of humankind. Worldwide, medical school accreditation bodies require the inclusion of population health in medical education. In 2003, the Institutes of Medicine (IOM) recommended that all medical students receive basic public health training in population-based prevention. The purpose of this study was to (1) examine the public health clinical performance of third-year medical students at two independent medical schools, (2) compare the public health clinical practice performance of the schools, and (3) identify underlying predictors of high and low public health clinical performance at one of the medical schools. ^ This study is unique in its analysis and report of observed medical student public health clinical practices. The cohort consisted of 751 third-year medical students who completed a required clinical performance exam using trained standardized patients. Medical student performance scores on 24 consensus public health items derived from nine patient cases were analyzed.^ The analysis showed nearly identical results for both medical schools at the 60%, 65%, and 70% pass rate. Students performed poorly on items associated with prevention, behavioral science, and surveillance. Factors associated with high student performance included being from an underrepresented minority, matching to a primary care residency, and high class ranking. A review of medical school curriculum at both schools revealed a lack of training in four public health domains. Nationally, 32% of medical students reported inadequate training in public health in the year 2006.^ These findings suggest more dedicated teaching time for public health domains is needed at the medical schools represented in this study. Finally, more research is needed to assess attainment of public health knowledge and skills for medical students nationwide if we are to meet the recommendations of the IOM. ^

POPULATION ASSESSMENTS OF INFECTION WITH SCHISTOSOMA MANSONI: EFFECTS OF BIAS CAUSED BY THE RELATIVE SENSITIVITY OF DIAGNOSTIC TECHNIQUES (PUERTO RICO)

This study establishes the extent and relevance of bias of population estimates of prevalence, incidence, and intensity of infection with Schistosoma mansoni caused by the relative sensitivity of stool examination techniques. The population studied was Parcelas de Boqueron in Las Piedras, Puerto Rico, where the Centers for Disease Control, had undertaken a prospective community-based study of infection with S. mansoni in 1972. During each January of the succeeding years stool specimens from this population were processed according to the modified Ritchie concentration (MRC) technique. During January 1979 additional stool specimens were collected from 30 individuals selected on the basis of their mean S. mansoni egg output during previous years. Each specimen was divided into ten 1-gm aliquots and three 42-mg aliquots. The relationship of egg counts obtained with the Kato-Katz (KK) thick smear technique as a function of the mean of ten counts obtained with the MRC technique was established by means of regression analysis. Additionally, the effect of fecal sample size and egg excretion level on technique sensitivity was evaluated during a blind assessment of single stool specimen samples, using both examination methods, from 125 residents with documented S. mansoni infections. The regression equation was: Ln KK = 2.3324 + 0.6319 Ln MRC, and the coefficient of determination (r('2)) was 0.73. The regression equation was then utilized to correct the term "m" for sample size in the expression P ((GREATERTHEQ) 1 egg) = 1 - e('-ms), which estimates the probability P of finding at least one egg as a function of the mean S. mansoni egg output "m" of the population and the effective stool sample size "s" utilized by the coprological technique. This algorithm closely approximated the observed sensitivity of the KK and MRC tests when these were utilized to blindly screen a population of known parasitologic status for infection with S. mansoni. In addition, the algorithm was utilized to adjust the apparent prevalence of infection for the degree of functional sensitivity exhibited by the diagnostic test. This permitted the estimation of true prevalence of infection and, hence, a means for correcting estimates of incidence of infection. ^