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QUESTION
critical thinking assignment
Module 00: Critical Thinking
1) Using the Framingham Heart Study dataset
2) you will compare the risk factors in men and women where you will use the following patient characteristics: age, systolic blood pressure, diastolic blood pressure, use of anti-hypertensive medication, current smoker, total serum cholesterol, mg/dL, body mass index (BMI), and diabetes,
3) by determining the means for each risk factor.
4) Create a table that summarizes your results.
- H0 The risk factors for heart disease listed as patient characteristics are not related to if the patient is male or female in the Framingham Heart Study. (Null Hypothesis)
- H1 The risk factors for heart disease listed as patient characteristics are related to if the patient is male or female in the Framingham Heart Study. (Alternative Hypothesis)
5) Steps of R Studio Analysis shown on page 67 in Introductory Statistics with R.
6) Steps of Excel Analysis
7) To conduct your analysis of the data sort the data by the Sex/Gender variable and sort by smallest to largest.
8) Compute the means and standard deviations for continuous variables using AVERAGE range) and STDEV (range) functions – Compute n (%) for dichotomous variables using COUNT (range) and COUNTIF (range, criteria) functions modifying ranges accordingly.
9) Present your findings by cutting and pasting your results table in a Word document that includes the following:
a) introduction,
b) a discussion where you interpret the meaning of the table and a conclusion should be included.
c) Your submission should be 2-3 pages to discuss and display your findings.
d) Provide support for your statements with in–text citations from a minimum of 5 scholarly, peer–reviewed articles. One of these sources may be from the class readings, textbook, or lectures, but the others must be external.
e) The Saudi Digital Library is a good place to find these sources and should be your primary resource for conducting research.- Using the Framingham Heart Study dataset
- you will compare the risk factors in men and women where you will use the following patient characteristics: age, systolic blood pressure, diastolic blood pressure, use of anti-hypertensive medication, current smoker, total serum cholesterol, mg/dL, body mass index (BMI), and diabetes,
- by determining the means for each risk factor.
- Create a table that summarizes your results.
- H0The risk factors for heart disease listed as patient characteristics are not related to if the patient is male or female in the Framingham Heart Study. (Null Hypothesis)
- H1The risk factors for heart disease listed as patient characteristics are related to if the patient is male or female in the Framingham Heart Study. (Alternative Hypothesis)
- Steps of R Studio Analysisshown on page 67 in Introductory Statistics with R.
- Steps of Excel Analysis
- To conduct your analysis of the data sort the data by the Sex/Gender variable and sort by smallest to largest.
- Compute the means and standard deviations for continuous variables using AVERAGE range) and STDEV (range) functions – Compute n (%) for dichotomous variables using COUNT (range) and COUNTIF (range, criteria) functions modifying ranges accordingly.
- Present your findings by cutting and pasting your results table in a Word document that includes the following:
- introduction,
- a discussion where you interpret the meaning of the table and a conclusion should be included.
- Your submission should be 2-3 pages to discuss and display your findings.
- Provide support for your statements with in–text citations from a minimum of 5 scholarly, peer–reviewed articles. One of these sources may be from the class readings, textbook, or lectures, but the others must be external.
- The Saudi Digital Library is a good place to find these sources and should be your primary resource for conducting research.
| Subject | Nursing | Pages | 5 | Style | APA |
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Answer
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Risk Factors between Males and Females
Introduction
Gender variation in terms of cardiovascular diseases has been established by previous research, with inclination of incidences of this category of diseases being towards the male gender (Wakabayashi, 2017). De Smedt, et al. (2016) further authenticated the sentiments of gender differences in risk factor control and management of patients with coronary heart diseases (CHD) and critically identified that female patients with CHD are more predisposed to having more adverse cardiovascular risk factor profile. These factors have often been adjusted by age, among other factors, and it is established that age is a significant confounder in assessing risk factor differences between males and females. This paper presents a comparative examination of risk factors between men and women, using patient characteristics like age, systolic blood pressure, body mass index (BMI), diastolic blood pressure, use of anti-hypertensive medication, current smoker, total serum cholesterol, and diabetes.
Data Analysis
The comparison of the risk factors among males and females is presented in the tables below.
Characteristic Males
Mean (SD) Females
Mean (SD)
Total Serum Cholesterol (mg/dL) 247.10 (46.96) 234.84 (42.47)
Age 54.61 (9.54) 53.97 (9.41)
Systolic Blood Pressure 136.76 (24.32) 134.56 (20.14)
Diastolic Blood Pressure 82.41 (11.99) 83.60 (11.33)
Body Mass Index (BMI) 25.56 (4.46) 26.18 (3.40)Table 1: Mean and Standard Deviation of continuous variables/characteristics.
Characteristic Condition Females
n (%) Males
n (%)
Current Smoker No 2,036 (48%) 3,390 (64%)
Yes 2,233 (52%) 1,948 (36%)
Diabetes No 4,063 (95%) 5,138 (96%)
Yes 206 (5%) 200 (4%)
Use Of Anti-Hypertensive Medication No 4,013 (94%) 4,766 (90%)
Yes 244 (6%) 554 (10%)Table 2: Table of comparison of categorical variable risk factors between males and females.
Among the subjects in the study, males were slightly older than males based on the average age, as the male gender had a wider age range which could have influenced its distribution. Further, the males had higher serum cholesterol than females in the data, and higher systolic blood pressure, though the female gender posted a higher diastolic blood pressure average. It is also notable that women in the data have higher BMI than their male counterparts.
A higher ration of female patients were smokers than the ratio among males. As concerns diabetes, a higher share among men had diabetes than the share among women. Also, the percentage of women on anti-hypertension medication was higher than that of men.
The results from this study point to the direction of plethora of research that have examined the gender difference in cardiovascular diseases (CVD) and have consistently concluded that females are more protected from CVD than men (Maranon, & Reckelhoff, 2013). Mikkola, et al. (2015) further confirm the confounding effect of age, concluding that after menopause, the CVD predisposition trajectory changes significantly.
Conclusion
Therefore, the current findings replicate evidence that CVD risk factors have higher yield in characteristics among males than females.
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References
De Smedt, D., De Bacquer, D., De Sutter, J., Dallongeville, J., Gevaert, S., De Backer, G., ... & Clays, E. (2016). The gender gap in risk factor control: effects of age and education on the control of cardiovascular risk factors in male and female coronary patients. The EUROASPIRE IV study by the European Society of Cardiology. International journal of cardiology, 209, 284-290.
Maranon, R., & Reckelhoff, J. F. (2013). Sex and gender differences in control of blood pressure. Clinical science, 125(7), 311-318.
Mikkola, T. S., Tuomikoski, P., Lyytinen, H., Korhonen, P., Hoti, F., Vattulainen, P., ... & Ylikorkala, O. (2015). Increased cardiovascular mortality risk in women discontinuing postmenopausal hormone therapy. The Journal of Clinical Endocrinology & Metabolism, 100(12), 4588-4594.
Wakabayashi, I. (2017). Gender differences in cardiovascular risk factors in patients with coronary artery disease and those with type 2 diabetes. Journal of thoracic disease, 9(5), E503.
Huebner, M., Wolkewitz, M., Enriquez-Sarano, M., & Schumacher, M. (2017). Competing risks need to be considered in survival analysis models for cardiovascular outcomes. The Journal of Thoracic and Cardiovascular Surgery, 153(6), 1427-1431.
Khanal, S. P., Sreenivas, V., & Acharya, S. K. (2018). Cox Proportional Hazards Model for Identification of the Prognostic Factors in the Survival of Acute Liver Failure Patients in India. Nepalese Journal of Statistics, 2, 53-74.
Lee, T., & Lee, M. (2017). Analysis of stage III proximal colon cancer using the Cox proportional hazards model. Journal of the Korean Data and Information Science Society, 28(2), 349-359.
Makar, G. S., Makar, M., Obinero, C., Davis, W., Gaughan, J. P., & Kwiatt, M. (2020). Refusal of cancer-directed surgery in patients with colon cancer: risk factors of refusal and survival data. Annals of surgical oncology, 1-11.