November 14th, 2010
My research Project will be addressing the etiology of Cardiovascular Disease and if the prevalence of certain determined risk factors will eventually result in heart disease. My research question is stated as follows; which high risk factors are more likely to cause coronary heart disease? I will utilize the Framingham data set in conducting my analysis in addressing my research question.
Cardiovascular disease is a number of specific diseases that affect the heart itself and/or the blood vessel system, especially the veins and arteries leading to and from the heart. Research on disease dimorphism suggests that women who suffer with cardiovascular disease usually suffer from forms that affect the blood vessels while men usually suffer from forms that affect the heart muscle itself. Over 459,000 Americans die of coronary heart disease every year and coronary artery disease causes roughly 1.2 million heart attacks each year with more than forty percent of those suffering from a heart attack resulting in death. According to the American Heart Association, over 7 million Americans have suffered a heart attack in their lifetime.
There are several risk factors for heart disease in which some are controllable and others are not. Uncontrollable risk factors include; male sex, older age, family history of heart disease, post-menopausal, and race (African Americans, American Indians, and Mexican Americans are more likely to have heart disease than Caucasians). By making changes in your lifestyle, you can actually reduce your risk for heart disease. Controllable risk factors include; smoking, high LDL or bad cholesterol and low HDL or good cholesterol, uncontrolled hypertension (high blood pressure), physical inactivity, obesity (more than 20% over one's ideal body weight), uncontrolled diabetes, and uncontrolled stress and anger.
Through research identifying the risk factors for heart disease as the primary cause of heart disease, will lead to a general awareness of the consequences from adopting these risky behaviors. The results of such studies contribute to the general knowledge of the scientific community which in turn provide every day citizens with vital and life altering information useful in determining healthy decisions for themselves and their loved ones in prolonging their life expectancy.
Thomson, Honeycutt, Shaw, and Peterson (2010) conducted a research study which addressed the racial differences in long term survival among patients with coronary artery disease. The analysis was limited to patients diagnosed with CAD and the study population consisted of 19,304 (85.3%) white patients and 3,314 (14.7%) black patients. These patients were chosen utilizing a databank called DDCD where patients whose data are in the DDCD are followed routinely at 6 months, 1 year, and then annually. Using Statistical analysis, Baseline characteristics were described by medians and interquartile ranges for continuous variables and by percentages for categorical variables. The comparisons of baseline characteristics by race were analyzed using χ2 tests for categorical variables or Wilcox rank sum tests for continuous variables. Unadjusted survival results were examined using Kaplan-Meier methods, and comparisons between groups were made using the log-rank test.
After conducting these analyses, it was found that black patients with significant CAD were younger, were more often female, and had a lower socioeconomic position. Despite being younger, black patients had a higher prevalence of medical conditions including hypertension, diabetes, and cerebrovascular disease relative to white patients. Conversely, whites were more likely than blacks to have a history of angina, cigarette smoking, and hyperlipidemia. Blacks and whites had similar numbers of diseased vessels. Black patients had a lower unadjusted survival compared with white patients at 15 years of follow-up (35.3% to 45.1%). Black women had the lowest survival (30.7%), and white men had the highest (48.1%). After adjustment for clinical and treatment factors that predicted mortality, black women had lower 15-year survival compared with white women (41.5% vs 45.5%); and black men had lower survival compared with white men (43.1% vs 45.8%).
Use of the DDCD databank gave researchers accurate information in selecting their target sample and also provided them with relevant information in conducting their statistical analysis while making relevant comparisons for their findings. The appropriate statistics were utilized for the types of variables analyzed and the only discrepancy I noticed was the uneven ratio of white to black participants. Though a 50/50 split would have been more appropriate, I found it astonishing that even though blacks only made up roughly 14 percent of the study population, and whites were established to have more risk factors, the findings still had blacks with lower survival rates and higher rates of medical conditions.
Schwandt, Coresh, and Hindin (2010) conducted research exploring the relationship between African American men’s and women’s marital status and their risk of developing cardiovascular diseases and dying. A sample of 15,792 persons aged 45 to 64 years were selected from 4 locations, approximately 4,000 study participants from each study community. participants received an extensive examination that collected medical, social, and demographic data. The study participants were reexamined every 3 years from 1987 to 1998. Statistical Analyses were utilized to examine the relationship between marital status, the individual (age, gender, and education), and health status (BMI, cholesterol, physical activity score, and smoking status) using Chi-square and t tests at the p < .05 significance level to better understand how people differ by marital status at the first visit. Modeling the association between CHD and the change in marital status between Visit 1 and Visit 2, bivariate logistic and Cox proportional hazards were utilized. Finally multivariable logistic and Cox proportional hazards regression were used to assess the association of marital status or change in marital status with cardiovascular outcomes.
After conducting their analyses, for hypertension, women who stayed single (never married, divorced, separated, or widowed) were more likely to have hypertension at Visit 2 (odds ratio [OR] = 1.21) compared with women who stayed married. For CHD, women who stayed single had a slightly elevated risk (hazard ratio [HR] = 1.29, p < .10) compared with women who stayed married. In the unadjusted models, all-cause mortality was more common in men who stayed single compared with those who stayed married (HR = 1.60). For males, the only statistically significant association observed between marital status and the outcomes was mortality. Like females, males who stayed single were more likely to die during the observation period than their married counterparts.
For the sample selection, it never mentioned the ratio of African Americans to white participants which casts doubts if the sample was appropriate for making proper comparisons. In use of 4 different cities at about 4000 participants each, the likelihood of selecting a random sample was sufficient for inferential statistics. In modeling for their outcome comparisons for different amounts of variables, the proper statistics were utilized for comparing between visits.
Kim, Diez, and Kiefe (2010) conducted research to see if neighborhood deprivation and social cohesion influenced the risk of coronary heart disease. The Coronary Artery Disease Risk Development in Young Adults (CARDIA) Study was a study exploring predictors of the development of CHD risk factors in young adults. At the initial examination in 1985, the cohort consisted of 5,115 black and white men and women aged 18–30 years living in 4 US urban areas. In each area, the recruitment goal was to enroll adults in approximately equal numbers of blacks and whites, women and men, persons aged <25 years and 25 years, and persons with a high school education or less and persons with more than a high school education. Follow-up examinations took place in 1987, 1990, 1992, 1995, 2000, and 2005.
Statistical analyses have found significant relations between higher neighborhood deprivation and CHD incidence (3, 5, 23).The mean age of the overall sample in 2000 was 45.3 years (range, 32–50 years); 57.1% were female, 54.6% were white, and 45.4% were African-American. A comparison of the 2005 and 1985 baseline samples of women and men (by race/ ethnicity, income, and education) suggested greater selective erosion in men. Internal consistency reliability estimates for the neighborhood SEP and cohesion measures were high (Cronbach’s a values were 0.94 and 0.82, respectively). In the overall sample, neighborhood SEP scores were strongly inversely correlated with the percentage of black residents (r¼_0.63), weakly inversely correlated with the percentage of immigrants (r ¼ _0.13), and positively correlated with residential stability (r ¼ 0.21).
Higher neighborhood SEP and residential stability were positively correlated with neighborhood cohesion (r ¼ 0.26 and r ¼ 0.17, respectively). Being female, being white, having a higher income, being widowed, divorced, or separated, and never being married were also related to higher cohesion. In women, the highest quartile of neighborhood deprivation was associated with 2.49 times’ higher odds of CAC, controlling for covariates and perceived neighborhood cohesion (P for trend ¼ 0.03; model 2). Persons in the quartile corresponding to the lowest level of cohesion had 1.87 times’ higher adjusted odds of CAC than persons in the quartile of highest cohesion (P for trend ¼ 0.02; model 2). Associations of neighborhood deprivation and cohesion with CAC were very similar before and after adjustment for individual sociodemographic and socioeconomic characteristics. The interaction between neighborhood deprivation and cohesion was statistically significant (P ¼ 0.03).
No association between social cohesion and CAC was seen in men in nondeprived neighborhoods. For women, lower cohesion predicted higher odds in both deprived and nondeprived neighborhoods, although associations were significant only in nondeprived neighborhoods. This study was well put together, from selecting the sample in equal numbers, to the determination of testing criteria. Statistical analysis was used accurately to compare all aspects of factors that related neighborhood deprivation to prevalence of CHD and comparisons of relevant risk factors such as SES, ethnicity, environment, and marital status gave this study great credibility and accuracy.
Fuller-Thomson, Brennenstuhl, and Frank (2010) conducted a study exploring the association between childhood physical abuse and adult heart disease while controlling for established risk factors. The data source used in this study was the 2005 cycle of the Canadian Community Health Survey (CCHS) carried out by Statistics Canada. The analyses are based on a sample of 13,093 males and females from the Canadian provinces of Manitoba and Saskatchewan. Utilizing Statistical analyses, 7 consecutive logistic regression analyses were conducted with heart disease as the outcome. In the first and each subsequent model, childhood physical abuse, gender, race, childhood stressors, adult risk behaviors, adult stressors, history of mood disorder, high blood pressure, and age were adjusted for.
Using a representative, regional sample, the prevalence of self-reported childhood physical abuse was found to be 7.4% (95% CI = 6.4%, 8.4%). The prevalence of heart disease reported as diagnosed by a health professional was found to be 4.4% (95% CI = 3.6%, 5.2%).The majority of the sample was younger than 50 years (59.7%) and White (86.4%). Approximately three-quarters (73.6%) had not experienced parental unemployment, parental addiction, nor parental divorce during childhood. The majority of respondents reported current or former smoking (66.8%), an inactive physical activity level (52.9%), and abstaining from alcohol or consuming an average of zero alcoholic drinks per day (71.8%). Two-fifths were in the normal or low BMI category. Approximately 50% of the sample had postsecondary education and the majority reported no or low levels of daily stress (79.8%).
5.1% of the sample reported having diabetes, 5.8% reported having a history of a mood disorder, and 22.1% reported sometimes having high blood pressure, each as diagnosed by a health professional. Individuals who reported being physically abused as a child had 57% higher odds (O.R. = 1.57; 95% CI = 1.12, 2.20) of having a diagnosis of heart disease as compared to those not reporting abuse when adjusting for age, gender and race only. This odds ratio decreased slightly to 1.45 (95% CI = 1.01, 2.08) when the model was adjusted for the wide range of risk factors for heart disease including: childhood stressors, adult health risk behaviors, adult stressors, depression, and high blood pressure.
In selecting the sample, the analysis was restricted to two provinces in which their representative sample was selected from. This sample was only representative of the two provinces and thus was not representative of the Canadian population as a whole. The methods used were highly defined and accurate in accumulating data on their desired criteria in which to conduct analysis on. Their statistical analysis included all risk factors stated and accurate comparisons were made by utilization of regression models in accordance with proper statistical methodology.
In conducting this literature review on the association of risk factors with coronary heart dysfunction, I have learned a number of crucial facts that have clarified the distinction between a credible study and a less creditable study. Methodology; if the methods used are not accurately defined and if the samples are not truly random and representative, creditable inferences cannot be made to the population as a whole. Two, if the sample is not selected equally in accordance with the studies research question, then again creditable inferences cannot be made. I have also learned a great deal about risk factors for CHD which include the fact that minorities are at greater risk for heart disease than their white counterparts. Also that SES and neighborhood conditions can greatly increase risk for heart disease if these conditions are poor and cause the person stress. Child abuse has also been linked to greater risk of later developing heart disease and being single has been found to elevate the risk of heart disease compared to being married among older adults. In conclusion, being a minority, single at older age, child abused, live in a poor neighborhood, have a low SES, or have high levels of stress increases the risk of CHD.
(Data and Methods)
I am utilizing the Framingham heart study data set in conducting my analysis in addressing my research question. This data set includes 400 participants with 33 different variables including sex and relevant cardiovascular disease risk factors such as blood pressure, smoking history, prevalence of diabetes, body mass index, and cholesterol levels. There is an even split of males (N=200)and females (N=200) and the ratio of smokers to non smokers is 50 percent male (N=100) and 50 percent female (N=100).These data were collected during an initial examination in 1956, a follow up examination in 1968, and subsequent visits and medical records collected throughout. For determining my criteria for high risk factors for CHD I included factors such as a person who smokes, has high blood pressure, prevalence of diabetes, older age, and high cholesterol levels.
I will be comparing the data from the first examination in 1956 in which I included Age1(age at first examination), SYSBP1(systolic blood pressure), DIABP1(diabolic blood pressure), CURSMOKE1(current smoker), DIABETES1(prevalence of diabetes), TOTCHOL1(cholesterol levels), and compare it to prevalence of CHD at the third examination to see if patients with high risk factors developed CHD over the course of time. I hypothesize that due to high risk factors patients will develop some form of CHD in later life. First I will obtain frequencies of the variables I am using to see the proportion of my sample that has actually developed CHD by the third visit.
In conducting further analysis and to test if there is a positive relationship between high risk factors and the development of CHD, I will utilize Pearson’s coefficient for all variables that are at least at the interval scale level. Once a relationship is established I will conduct a hypothesis test to see if the presence of high risk factors actually can imply causing an increase in CHD development and whether this result is significant. In doing so I will conduct an anova test and a t test while utilizing a 95 percent confidence interval to further increase the accuracy of the results of the analysis.
After conducting the full analysis I found that 9 percent of the sample population developed CHD over the course of time between examination 1 and examination 3 as described by the pie chart and frequency chart above. Out of those statistics, 7 percent of women made up the 9 percent of the sample population with prevalence of CHD along with 11 percent of men as shown by the pie charts below.
After conducting an ANOVA test with a .05 alpha level on the high risk variables, I concluded that sex was a significant factor in the development of CHD f (1,306)=1.877, p=.172. Total cholesterol had no significance with f (1,299)=15.249, p=0.00, age had no significance with f (1,306)=5.929, p=.015, both systolic pressure and diastolic pressure had no significance with f (1,306)=9.443, p=.002 and f (1,306)=6.686, p=.010 respectively. Smoking has shown to be significant with f (1,306)=1.249, p=.265 along with prevalence of diabetes f (1,306)=2.520, p=.113. For this sample sex, cigarette smoking and having diabetes was associated with the development of CHD and serum cholesterol, age, and both diastolic and systolic blood pressure showed no significant association with the development of CHD.
To further validate the anova results I conducted a t-test for the high risk variables and have determined that sex t (32.703)=1.376, p=.178, Alpha level=.05 was significant, cholesterol t (30.067)=3.045, p=.005 was not significant, age t (32.392), p=.023 was also not significant. Both systolic and diastolic blood pressure was also found not to be significant with t (29.934)=2.376, p=.024 and t (30.591), p=.038 respectively. Smoking has been found to be significant with t (32.532)=1.109, p=.275 and prevalence of diabetes was found to be significant with t (28.675)=.994, p=.329 mirroring the results from the one way anova. Again sex, smoking and prevalence of diabetes have been found to be significant and age, serum cholesterol, and both systolic and diastolic blood pressure were found to have no significance.
In conclusion high risk factors associated with CHD are both avoidable and unavoidable. While we are able to control risk factors such as cholesterol levels, blood pressure, diabetes, smoking, and other health conditions caused by habits associated with our everyday lives, risk factors such as age, family history, and gender are uncontrollable factors that are unavoidable. For this study it has been determined that among the several high risk factors I have included in this study, factors such as sex, smoking, and prevalence of diabetes has been found to contribute greater to the eventual onset of a CHD condition in the patient. In contrast, risk factors such as serum cholesterol, age, and both systolic and diastolic blood pressure were found to have no significant impact on the onset of a CHD event occurring within the data collection time frame of examination 1 and 3.
Fuller-Thomson, E. , Brennenstuhl, S. , & Frank, J. (2010). The association
between childhood physical abuse and heart disease in adulthood: Findings
from a representative community sample. Child Abuse & Neglect V. 34 No. 9
(September 2010) P. 689-698.
Kim, D. , Diez Roux, A. , & Kiefe, C. (2010). Do neighborhood socioeconomic
deprivation and low social cohesion predict coronary calcification? the cardia
study. American Journal of Epidemiology V. 172 No. 3 (August 1 2010) P.
Schwandt, H. , Coresh, J. , & Hindin, M. (2010). Marital status, hypertension,
coronary heart disease, diabetes, and death among african american
women and men: Incidence and prevalence in the atherosclerosis risk in
communities (aric) study participants. Journal of Family Issues V. 31 No. 9
(September 2010) P. 1211-1229.
Thomas, K.L., Honeycutt, E. , Shaw, L.K. , & Peterson, E.D. (2010). Racial
differences in long- term survival among patients with coronary artery
disease. American Heart Journal V. 160 No. 4 (October 2010) P. 744-751