2 resultados para accounting change

em DigitalCommons@The Texas Medical Center


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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.

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A historical prospective study was designed to assess the man weight status of subjects who participated in a behavioral weight reduction program in 1983 and to determine whether there was an association between the dependent variable weight change and any of 31 independent variables after a 2 year follow-up period. Data was obtained by abstracting the subjects records and from a follow-up questionnaire administered 2 years following program participation. Five hundred nine subjects (386 females and 123 males) of 1460 subjects who participated in the program, completed and returned the questionnaire. Results showed that mean weight was significantly different (p < 0.001) between the measurement at baseline and after a 2 year follow-up period. The mean weight loss of the group was 5.8 pounds, 10.7 pounds for males and 4.2 pounds for females after a 2 year follow-up period. A total of 63.9% of the group, 69.9% of males and 61.9% of females were still below their initial weight after the 2 year follow-up period. Sixteen of the 31 variables assessed utilizing bivariate analyses were found to be significantly (p (LESSTHEQ) 0.05) associated with weight change after a 2 year follow-up period. These variables were then entered into a multivariate linear regression model. A total of 37.9% of the variance of the dependent variable, weight change, was accounted for by all 16 variables. Eight of these variables were found to be significantly (p (LESSTHEQ) 0.05) predictive of weight change in the stepwise multivariate process accounting for 37.1% of the variance. These variables included: Two baseline variables (percent over ideal body weight at enrollment and occupation) and six follow-up variables (feeling in control of eating habits, percent of body weight lost during treatment, frequency of weight measurement, physical activity, eating in response to emotions, and number of pounds of weight gain needed to resume a diet). It was concluded that a greater amount of emphasis should be placed on the six follow-up variables by clinicians involved in the treatment of obesity, and by the subjects themselves to enhance their chances of success at long-term weight loss. ^