please reference the pages I have attached below.
HLTH 501 Case Study Analysis: Summary Template Background The National Heart, Lung, and Blood Institute (NHLBI)[footnoteRef:1] created a teaching dataset that includes real but anonymized data collected as part of the Framingham Heart Study. The Framingham Heart Study is one of the most influential and longest running epidemiological studies of risk factors for cardiovascular disease ever run. The study started in 1948 and continues today to collect extensive data from original participants, their children, and their children’s children. Much of what we know about cardiovascular disease was discovered by investigators involved in the Framingham Heart Study. In fact, studies to date using data collected in the Framingham Heart study have resulted in over 3000 publications in high impact, peer-reviewed medical journals. [1: http://www.nhlbi.nih.gov/] The Framingham Heart Study has been widely discussed in the media. WGBH in Boston produced a video documentary for PBS entitled “The Hidden Epidemic: Heart Disease in America” that details the history of heart disease in this country and highlights the Framingham Heart Study.[footnoteRef:2] In 2007, CBS News did a story on the study, its participants, and its impact.[footnoteRef:3] Additionally, research results from the Framingham Heart Study are communicated widely, most recently highlighting the discovery of a gene that may promote obesity[footnoteRef:4] and new data showing declining rates of dementia.[footnoteRef:5] Interested readers can visit the Framingham Heart Study website for a detailed history of this incredible study and its many contributions to preventive medicine.[footnoteRef:6] [2: http://www.pbs.org/wgbh/takeonestep/heart/] [3: http://www.cbsnews.com/videos/landmark-heart-study/] [4: http://www.cbsnews.com/news/how-a-fat-gene-may-influence-your-weight/] [5: http://www.cbsnews.com/news/dementia-alzheimers-risk-signs-of-hope-study/] [6: https://www.framinghamheartstudy.org/about-fhs/history.php/] Datasets for Analysis NHLBI created a longitudinal teaching dataset includes clinical, laboratory, and outcome data on n = 4434 participants. Each participant has between one and three observations—which represent examinations held approximately 6 years apart. There are a total of 11,627 observations in the full dataset. A detailed description of the Framingham Heart Study dataset and other public use datasets available from NHLBI are available on the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) website.[footnoteRef:7] [7: https://biolincc.nhlbi.nih.gov/static/studies/teaching/framdoc.pdf?link_time=2016-07-06_14:21:55.514359] Two datasets are available for analysis here—one is the complete dataset with n = 11,627 observations (or person-exams), and the second includes only data collected at the first examination for each participant (n = 4434). The two datasets are available as comma separated values (.csv) files for analysis in Excel, R, or other statistical computing packages. FHS-All.csv contains n = 11,627 observations and FHS-Exam1.csv contains n = 4434 observations. Variables The following variables are available in each dataset for analysis (extracted from the complete documentation file, available on the NHLBI BioLINCC website [footnoteRef:8]). [8: https://biolincc.nhlbi.nih.gov/static/studies/teaching/framdoc.pdf?link_time=2016-07-06_14:21:55.514359] Variable Name Description Coding Details/Range RANDID Unique identification number for each participant 2248-9999312 SEX Participant sex 1 = Male, 2 = Female PERIOD Exam cycle 1, 2, 3 TIME Number of days since first (baseline) exam 0–4854 AGE Age at exam, years 32–81 SYSBP Systolic blood pressure, mmHg 83–295 DIABP Diastolic blood pressure, mmHg 30–150 BPMEDS Use of anti-hypertensive medication 0 = No, 1 = Yes CURSMOKE Currently smoking cigarettes 0 = No, 1 = Yes CIGPDAY Number of cigarettes smoked per day 0 (non-smoker)–90 TOTCHOL Total serum cholesterol, mg/dL 107–696 HDLC* High density lipoprotein cholesterol, mg/dL 10–189 LDLC* Low density lipoprotein cholesterol, mg/dL 20–565 BMI Body mass index = weight (kg)/height (m)2 14–57 GLUCOSE Serum glucose, mg/dL 39–478 DIABETES Diabetes (glucose > 200 mg/dL or on treatment) 0 = No, 1 = Yes HEARTRTE Heart rate, beats/minute 37–220 PREVAP Prevalent angina pectoris 0 = No, 1 = Yes PREVCHD Prevalent coronary heart disease (CHD) 0 = No, 1 = Yes PREVMI Prevalent myocardial infarction (MI) 0 = No, 1 = Yes PREVSTRK Prevalent stroke 0 = No, 1 = Yes PREVHYP Prevalent hypertension 0 = No, 1 = Yes The following are outcome events coded 1 if the event occurred during the follow-up (only the first event is recorded). ANGINA Angina pectoris 0 = No, 1 = Yes HOSPMI Hospitalized for MI 0 = No, 1 = Yes MI_FCHD Hospitalized for MI or fatal CHD 0 = No, 1 = Yes ANYCHD Any coronary heart disease event 0 = No, 1 = Yes STROKE Stroke 0 = No, 1 = Yes CVD Cardiovascular disease 0 = No, 1 = Yes HYPERTEN Hypertension 0 = No, 1 = Yes DEATH Death from any cause 0 = No, 1 = Yes The following are numbers of days from the first (baseline) exam to the first event during the follow-up. If no event occurred, time is end of follow-up, death, or last known contact date. TIMEAP Time from baseline to first angina TIMEMI Time from baseline to first myocardial infarction TIMEMIFC Time from baseline to first MI or fatal CHD TIMECHD Time from baseline to first CHD TIMESTRK Time from baseline to first stroke TIMECVD Time from baseline to first cardiovascular disease TIMEHYP Time from baseline to first hypertension TIMEDTH Time from baseline to death *Available only at period = 3 exam, missing otherwise Design, conduct and summarize results of the analyses outlined below using data collected in the Framingham Heart Study using FHS-Exam1, the dataset that includes one observation per participant. Analytic approaches and coding for solutions are detailed in the Excel file 1. Describe the study sample. Complete the following table to describe the study sample using data collected at the first examination for each participant (n = 4434). Summarize your results in three to four sentences. Patient Characteristic* Total Sample (n = 4434) Age, years Male sex Systolic blood pressure, mmHg Hypertension Use of anti-hypertensive medication Current smoker Total serum cholesterol, mg/dL Serum Glucose Stroke * Mean (Standard deviation) or n (%) 2. Compare risk factors in men and women. Complete the following table to compare men and women using data collected at the first examination for each participant (n = 4434). Summarize your results in three to four sentences. Patient Characteristic* Men (n = 1944) Women (n = 2490) Age, years Systolic blood pressure, mmHg Hypertension Use of anti-hypertensive medication Current smoker Total serum cholesterol, mg/dL Serum Glucose Stoke * Mean (Standard deviation) or n (%) 3. What characteristics are associated with serum Glucose? Use simple and multivariable linear regression analysis to complete the following table relating the characteristics listed to Glucose as a continuous variable. Before conducting the analysis, be sure that all participants have complete data on all analysis variables. If participants are excluded due to missing data, the numbers excluded should be reported. Then, describe how each characteristic is related to Glucose level. Are crude and multivariable effects similar? What might explain or account for any differences? Outcome Variable: Glucose mg/dL Characteristic Regression Coefficient Crude Models p-value Regression Coefficient Multivariable Model p-value Age, years Male sex Systolic blood pressure, mmHg Total serum cholesterol, mg/dL Current smoker Diabetes 4. Who is most likely to have prevalent coronary heart disease? Test if there are significant differences in the following risk factors between persons with and without prevalent coronary heart disease (CHD). Summarize the statistical results in the table below and then compare risk factors in persons with and without prevalent CHD. Be sure to indicate what statistical tests were used in the footnote to the table and in a brief summary of a paragraph or less. Patient Characteristic* History of CHD (n = 194) No History of CHD (n = 4240) p-value* Age, years Systolic blood pressure, mmHg Diastolic blood pressure, mmHg Total serum cholesterol, mg/dL Body mass index * Mean (Standard deviation). P-values are based on two independent samples t tests. 5. Describe the Data collection Methods used in the study 6. Please Provide a Summary of the data analysis as a whole . Summary should include pertinent information of all the questions above. This summary should not exceed 300 words. 1 HLTH 501 Case Study Analysis Assignment Instructions Overview This case study analysis utilizes the Framingham Heart Study data for analysis. Students will be able to synthesize what they’ve learned throughout the term. This case study provides a practical application of bio-statistical concepts and analysis. Instructions Case Study Analysis: Summary Assignment For this assignment, students will use Microsoft Excel to analyze selected Framingham Heart Study data. Students will perform various statistical data analysis to answer specific research questions. Students will provide appropriate tables that summarizes the analysis. After the analysis, the students will provide a summary of each statistical result tables that were created from the data. Included will be a discussion of the appropriateness of the data collection methods used in the study in comparison to other methods. The student will than summarize the data analysis to not exceed 300 words. Case Study Analysis: Interpretation Assignment For this assignment, students will utilize the information from the Case Study Analysis Summary Assignment to create an oral presentation in which they summarize and interpret selected data from the Framingham Heart Study. Interpreting data is a crucial part of practical biostatistics that shows mastery of data evaluation and implications for application. In both the summary paper and oral presentations, students will describe the study sample based on patient characteristics, compare risk factors among men and women, determine which characteristics are associated with Glucose through simple and multivariable linear regression, and determine if there are significant differences in risk factors between persons with and without prevalent coronary heart disease (CHD). Included will be a discussion of the appropriateness of the data collection methods used in comparison to other methods that could have been used. Data are to be concisely interpreted and the resulting summary paper cannot exceed 300 words in length for each question. The oral presentation may be conducted using audio, YouTube, Adobe Spark, PowerPoint, or another form of communication file. Video files are optional. The student will use the provided Case Study Analysis: Interpretation Grading Rubric to evaluate/grade the case study and report the findings in both written and oral formats. 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