3 resultados para Noninstitutionalized

em DigitalCommons@The Texas Medical Center


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The association between Social Support, Health Status, and Health Services Utilization of the elderly, was explored based on the analysis of data from the Supplement on Aging to the National Health Interview Survey, 1984 (N = 11,497) using a modified framework of Aday and Andersen's Expanded Behavioral Model. The results suggested that Social Support as operationalized in this study was an independent determinant of the use of health services. The quantity of social activities and the use of community services were the two most consistent determinants across different types of health services use.^ The effects of social support on the use of health services were broken down into three components to facilitate explanations of the mechanisms through which social support operated. The Predisposing and Enabling component of Social Support had independent, although not uniform, effects on the use of health services. Only slight substitute effects of social support were detected. These included the substitution of the use of senior centers for longer stay in the hospital and the substitution of help with IADL problems for the use of formal home care services.^ The effect of financial support on the use of health services was found to be different for middle and low income populations. This differential effect was also found for the presence of intimate networks, the frequencies of interaction with children and the perceived availability of support among urban/rural, male/female and white/non-white subgroups.^ The study also suggested that the selection of appropriate Health Status measures should be based on the type of Health Services Utilization in which a researcher is interested. The level of physical function limitation and role activity limitation were the two most consistent predictors of the volume of physician visits, number of hospital days, and average length of stay in the hospital during the past year.^ Some alternative hypotheses were also raised and evaluated, when possible. The impacts of the complex sample design, the reliability and validity of the measures and other limitations of this analysis were also discussed. Finally, a revised framework was proposed and discussed based on the analysis. Some policy implications and suggestions for future study were also presented. ^

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A conceptual framework based on the Health Belief Model was proposed which identified those factors most significant in the prediction of compliance behavior. The hypothesized model was applied to analyze the effects of sociodemographic characteristics, self-assessed health status, and social support networks on compliance with antihypertensive regimens, focusing on black adults.^ The study population was selected from the National Health and Examination Survey II (NHANES II) which produced a sample of 3,957 eligible persons 35-74 years of age.^ The study addressed the following research questions: (a) what is the relationship between demographic variables and self-assessed health status, (b) what is the relationship between social support network and self-assessed health status, (c) what is the compliance, (d) what factors, e.g., demographic characteristics, social support network, self-assessed health status, are most related to compliance, and (e) does the effect of these factors on compliance differ between black and white adults?^ The results of the study found that blacks: (a) had poorer health than whites, and education and income were significantly related to self-assessed health status, (b) the stronger social support networks of blacks, the better their health status, and (c) older blacks and those in poorer health were more likely to comply with recommended treatment. The hypothesized conceptual model for the prediction of compliance behavior was partially substantiated for both blacks and whites.^ Implications for the application of the conceptual model are also discussed. ^

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The purpose of this study was to understand the role of principle economic, sociodemographic and health status factors in determining the likelihood and volume of prescription drug use. Econometric demand regression models were developed for this purpose. Ten explanatory variables were examined: family income, coinsurance rate, age, sex, race, household head education level, size of family, health status, number of medical visits, and type of provider seen during medical visits. The economic factors (family income and coinsurance) were given special emphasis in this study.^ The National Medical Care Utilization and Expenditure Survey (NMCUES) was the data source. The sample represented the civilian, noninstitutionalized residents of the United States in 1980. The sample method used in the survey was a stratified four-stage, area probability design. The sample was comprised of 6,600 households (17,123 individuals). The weighted sample provided the population estimates used in the analysis. Five repeated interviews were conducted with each household. The household survey provided detailed information on the United States health status, pattern of health care utilization, charges for services received, and methods of payments for 1980.^ The study provided evidence that economic factors influenced the use of prescription drugs, but the use was not highly responsive to family income and coinsurance for the levels examined. The elasticities for family income ranged from -.0002 to -.013 and coinsurance ranged from -.174 to -.108. Income has a greater influence on the likelihood of prescription drug use, and coinsurance rates had an impact on the amount spent on prescription drugs. The coinsurance effect was not examined for the likelihood of drug use due to limitations in the measurement of coinsurance. Health status appeared to overwhelm any effects which may be attributed to family income or coinsurance. The likelihood of prescription drug use was highly dependent on visits to medical providers. The volume of prescription drug use was highly dependent on the health status, age, and whether or not the individual saw a general practitioner. ^