Browsing by Subject "socioeconomic status"
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Item Associations Between Socioeconomic Statuses and Behavioral Risk Factors and Self-Reported Health Status(2005-05-01) Wu, Gang; Daisha Cipher; Shande Chen; Sejong BaeWu, Gang, Association Between Socioeconomic Statuses and Behavioral Risk Factors and Self-Reported Health Status. Master of Public Health (Biostatistics), May 2005, 70pp., 5 figures, 4 tables, references, 58 titles. Socioeconomic statuses (SES) and behavioral risk factors determine more than 70% of overall health outcome of American population. The effects of SES and behavioral risk factors on self-reported health status (SRHS) were studied using binary logistic regression models. Age group, education level, ethnicity, physical activities, cholesterol intake, smoking status, and drinking status were identified as significant predictors (p [less than] 0.05) to SRHS based on overall model. Significant predictors for each ethnic group varied based on the same model separated by ethnicity: White (insurance coverage, physical activities, smoking status, and drinking status), Black (gender, vegetable intake, and Hispanic (cholesterol intake). Ethnic disparities in SES and behavioral risk factors were discussed. The findings may have potential importance in public health intervention.Item Racial and Ethnic Differences in Cardiovascular Disease Risk Factors in U.S. Older Women: Findings from the Behavioral Risk Factor Surveillance Survey(2006-08-01) Kurian, Anita K.; Sejong Bae; Karan Singh; Kristine LykensKurian, Anita K., Racial and Ethnic Differences in Cardiovasular Disease Risk Factors in U.S. Older Women: Findings from the Behavioral Risk Factor Surveillance Survey, 2003 & 2004. Doctor of Public Health (Clinical Research), August 2006, 118 pp., 55 tables, 14 illustrations, references, 69 titles. Objectives- The study sought to determine if there were any significant racial and ethnic differences in six modifiable cardiovascular disease risk factors in women aged 65 years and older. It also examined the dynamic relationships of race/ethnicity, socioeconomic status and cardiovascular risk factors. Methods- Data were extracted from the merged 2003 & 2004 Behavioral Risk Factors Surveillance Survey (BRFSS). Prevalence estimates and 95% of each of the six cardiovascular disease risk factors considered (Hypertension, Diabetes, Obesities, Hypercholesterolemia, Smoking, and No leisure-time physical activity) were calculated by race/ethnicity. Multinomial (for indicator outcomes) and multiple logistic regression analyses (for binary outcomes) were performed. Path analysis was performed to assess the complex pathways by which race/ethnicity and socioeconomic status (SES) were associated with cardiovascular disease risk factors. Results- Of the 77,492 survey respondents included in the sample, there were 68,251 whites, 4,912 blacks, 3,656 Hispanics and 673 AIANs. The odds of the cardiovascular risk factors were higher in race/ethnicity minority women (non-Hispanic black, Hispanic, American Indian Alaskan Native) compared to white women aged 65 years and older. Socioeconomic status was found to be a moderator rather than a mediator of the relationship between race/ethnicity and cardiovascular disease risk factors. The re-specified model with the behavioral risk factors (smoking and no leisure-time physical activity) as mediators was deemed a good fit to the data. Age, race/ethnicity, SES, smoking and leisure-time physical activity were found to have significant direct, indirect and total effects on cardiovascular disease risk factors. Conclusions- There is a need to find better ways to measure race/ethnicity, and future research should consider the impact of more fundamental determinants of CVD risk factors. Area-based measures, such as neighborhood conditions, should also be given consideration for influencing these risk factors. Identification of potential mediating and moderating factors in these pathways (for example, sense of personal control or social support) will help clinicians and public health professionals to develop culturally sensitive intervention or prevention programs specifically targeted toward risk burdens in each of these populations.Item The Use of Community Needs Assessment Data to Establish a High-Risk Profile for Negative Health Outcomes in the City of Fort Worth.(2008-12-01) Michael, SheniquaCommunity needs assessments are critical for targeting health care programs and public health policy. The relationship between socioeconomic status (SES), health behaviors and health outcomes are explored, demonstrating the use of community needs assessment data to establish a local high-risk profile. The City of Fort Worth 2003 Community Needs Assessment data was analyzed to test these hypotheses: There is a unique local relationship between SES indicators and health status; and, there is a similar relationship between health behaviors and health status. Statistical analyses demonstrated a correlation between SES and health status; however, no correlation was shown between health behaviors and health status. Recommendations include development of more reliable measurement tools.Item Unmet Health Care Needs Stratified by Socioeconomic Status: Results of the National Survey of Children with Special Health Care Needs(2006-12-01) Fulda, Kimberly G.; Kristine Lykens; Karan Singh; Sejong BaeFulda, Kimberly G., Unmet Health Care Needs Stratified by Socioeconomic Status: Results of the National Survey of Children with Special Health Care Needs. Doctor of Public Health (Clinical Research), December 2006, 200 pp., 15 tables, 4 figures, references, 73 titles. The purpose of this research study was to identify factors that affect unmet health care needs for children with special health care needs (CSHCN) and to identify how these factors vary by socioeconomic status. Data were obtained from an already existing publicly available database from the National Survey of Children with Special Health Care Needs, 2000-2002, available through the Centers for Disease Control and Prevention. Approximately 750 CSHCN from each of the 50 states and the District of Columbia were included. Survey data represented parent responses on health care and health care needs for CSHCN. Responses for 38,866 CSHCN up to 17 years of age were included in the analysis. Four hypotheses were tested: having received all needed routine, preventive care; having received all needed care from a specialist; having received all needed mental health care or counseling; and having received comprehensive, coordinated care in a medical home. Within each of the four hypotheses, four models were presented for socioeconomic status (SES): [less than] 133% of the federal poverty level (FPL); 133-199% of the FPL, 200-299$ of the FPL, and ≥ 300% of the FPL. Age, severity of the CSHCN’s condition, sex, race, ethnicity, maternal education, insurance status / type, geographical region of the household, relationship of the respondent to the CSHCN, the total number of adults in the household, and the total number of kids in the household were all significant predictors of having received all needed care in at least one SES stratum for the four hypotheses. Analyses revealed there are disparities among SES strata for unmet health care needs for CSHCN.