Graduation Year


Document Type




Degree Name

Doctor of Nursing Practice (D.N.P.)

Degree Granting Department


Major Professor

Ponrathi Athilingam, Ph.D., ARNP

Co-Major Professor

Kevin Kip, Ph.D.

Committee Member

Carmen Rodriguez, Ph.D., ARNP

Committee Member

Skai Schwartz, Ph.D.


CES-D, Insomnia,, Sleep disorder, Interleukin-6, Diabetes



Cardiovascular disease (CVD) remains the number one killer even after years of advances and preventative measures. Identifying and reducing modifiable risk factors is a health care priority. CVD Risk assessments are calculated using several traditional risk factors including age, gender, race, blood pressure, cholesterol, history of diabetes, and smoking to estimate a persons’ risk of developing CVD (heart disease or stroke) in the next 10-years. In addition to the traditional risk factors for CVD, there is increasing evidence of metabolic disorders, depressive symptoms, inflammation and sleep quality posing a greater risk for CVD. However, these factors are not included in the current risk prediction models including the Framingham Risk Score, Reynolds Risk Score, and Pooled Cohort Risk Equations. Therefore, this study examined the effect of depressive symptoms, inflammation, and sleep quality on the independent risk for CVD.


The primary objective of this study was to evaluate the independent relationships between traditional cardiac risk factors, depressive symptoms, inflammation, and sleep quality, on long-term risk of major adverse cardiovascular events (MACE). The secondary objective was to evaluate whether gender modifies the relationships between depressive symptoms, inflammation, and sleep quality on long-term risk of MACE.


A secondary analysis was conducted on data obtained from the Longitudinal prospective cohort study Heart Strategies Concentrating on Risk Evaluation (Heart SCORE) conducted by the University of Pittsburgh. The ongoing Heart SCORE study has been prospectively examining cardiovascular disease (CVD) risk factors and CVD events on an initial cohort of 2,000 enrolled adults ages 45 to 75 at study entry. A Cox proportional-hazard model was used to evaluate the relationship between traditional risk factors as well as independently and collectively for depressive symptoms, inflammation and sleep quality and risk of MACE. Models were reanalyzed adding gender as an interaction term and in stratified analyses to evaluate whether gender modifies the relationships between sleep quality, depressive symptoms, and inflammation and long-term risk of MACE.


The participants (N= 1,895) included in this study were, 1256 females (66%), 639 males (34%), ranging from 45 to 75 years of age with a median age of 60 years, 42% Blacks, 55% Whites and 3% other race. Six percent, (n =113) of the participants experienced a major cardiac event during a mean of nearly 10 year follow up. Results indicated that men as compared with women with high levels of interleukin-6 had particularly high risk for CVD, as defined by two separate definitions of MACE, MACE1: Hazard Ratio (HR) 3.44 vs. 1.72 for males and females, respectively, MACE6: HR 2.51 vs. 1.69 for males and females, respectively. These results suggest the high inflammation in men is strongly associated with future risk of CVD. The addition of depressive symptoms to the initial traditional risk factor model was associated with a modest increase in the risk of both definitions of MACE (HR range from 1.20 to 1.68) with similar results observed by gender. Sleep quality/Insomnia was not associated with long-term risk of MACE overall or when evaluated separately by gender.


Primary prevention with early identification of potential modifiable risk factors is a key strategy in planning interventions to reduce the risk of CVD. Results from this study suggest that depression and inflammation (e.g. IL-6) should be studied in other populations to estimate their independent predictive value in risk stratification. Whereas sleep quality was not associated with long-term risk of CVD in this analysis, future studies should consider the use of objective measures of sleep quality, such as actigraphy in addition to standard use of self-report measures and sleep diaries.

Included in

Nursing Commons