Date of Award

2014-12-08

Degree Name

PhD Nursing

Dissertation Committee

Ann M. Mayo, RN, DNSc, FAAN, Chairperson; Cynthia D. Connelly, RN, PhD, FAAN; Linda D. Urden, RN, DNSc, CNS, NE-BC, FAAN

Keywords

demographics, Diabetic registry, Cardiovascular risk factors, clinical characteristics, nursing

Abstract

Background: Cardiovascular disease is the leading cause of death in the United States. There were over 18 million people diagnosed with diabetes in 2002. These disease processes together combine for significant health burden on society (American Diabetes Association, 2008). The purpose of the study was to describe the relationship between select demographics, and clinical characteristics to determine risk factors for cardiovascular disease in a diabetic population. Methods: A retrospective descriptive study was conducted using a diabetic registry database containing patients diagnosed with diabetes from January 1, 2011 to December 31, 2012. Study variables included age, gender, socio-economic status, glycosylated hemoglobin levels (HgbAlc), micro-albumin levels, and low density lipoprotein levels (LDL). Descriptive and inferential statistics were conducted using SPSS Windows version 22. Results: For the total cases (N=292) age ranging 35 years to 97 years, 57% female, the analysis revealed only one independent variable, gender, demonstrated a relationship with the dependent variable, LDL (r =.138; p =>0.009). For the regression analysis, combined variability of the independent variables (age, gender, socio-economic status, HgbAlc, and micro-albumin) accounted for only three percent variance in the dependent variable (p =0.134). The overall model was not a good fit to the sample data. Conclusions: The diabetic registry used for this study was designed to meet regulatory and accreditation requirements and as such had limited categories of data. The practicality of using a database for research has benefits, but can also impose significant limitations. In this study the data categories were limited, possibly accounting for the lack of model fit. However, the findings did indicate a premise for future research using a diabetic registry if changes could be made to collect more categories of data such that the findings could provide full characterization of the sample and generalizability of the findings.

Document Type

Dissertation: Open Access

Department

Nursing

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Nursing Commons

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