SPSS - Health Study Research Project Topic: Link Between The Low Carbohydrate Diet and Cardiovascular Disease

**(Use data set for calculations)** **APA Format***

Null Hypothesis:  The null hypothesis will be: Adults (age >18) with self-reported low carbohydrate diets will not have statistically significant differences in cardio-vascular disease scores than adults who self-reported other diets. You can use a single tail test or two tail test, depending on the data chosen.

1. Summarize the 9 studies shown below (or other studies about the topic) and draft the Background section of your paper. The background section of a paper sets up the rationale for the research study. Generally, it communicates three important things: a description of the problem that will be addressed, a synthesis of the previous research on this particular topic that highlights the “gap” in the literature, and the research aim. It is common to see these ideas described in three distinct paragraphs. The first one describes the public health problem and generally includes statistics on the prevalence or incidence of your outcome and potential adverse effects associated with this topic (e.g., mortality, morbidity, costs). The next paragraph summarizes or synthesizes the previous work on the topic. The key here is to justify the research aim by highlighting a shortcoming or "gap" in the literature. For instance, the "gap" might be that previous work has not looked at your particular exposure of interest and its association with the outcome. Alternatively, it might be that the literature is inconsistent on your topic and thus more research is needed or it might be that the data examining this question is too old and needs to be updated. It might also be that no one has focused on a particular age group or examined the influence of a third variable (e.g., BMI) in the way you think it should be dealt with. These are just examples; there are lots of ways to justify your research study, but it requires you to be familiar with previous findings and sometimes requires a bit of creativity! The last paragraph of the background describes the research aim and the implications of this work. Consider why the findings will be important and how they will be used. Please work on strong scientific writing, keeping your language objective, without judgement or opinion. Please also work on using appropriate topic sentences to give the reader the main point of the paragraph so they know what to expect in the body of the paragraph. Please use double-spaced formatting throughout

2. First, identify which variables you will analyze for your study. Specify your exposure and your outcome of interest and determine potential confounders of this relationship. Remember that confounders are those “third variables” that are associated with both the exposure and the outcome. Then, indicate the variables’ type – either continuous or categorical.

· Next, in SPSS, run frequency distributions for each of the categorical variables and descriptive statistics for each of the continuous variables. Consider also creating a graph or chart in SPSS to describe these distributions. For variables that have very small frequencies in at least one category (e.g., less than 7 people in a category), think about combining that category with another if it makes conceptual sense (i.e., there are very few Native Americans, does it make sense to combine them with the Asian group?). See the instructions for recoding variables. Try the recode, give the recoded variable a new name, run a frequency of the new variable (it will be on the bottom of the list of variables), and SAVE THE DATA FILE. IF YOU RECODE OR CREATE NEW VARIABLES, YOU MUST SAVE YOUR DATA FILE TO KEEP THE NEW VARIABLES.

· Cut and paste the SPSS output to a word document. Include the frequency distributions or descriptive statistics for each variable of interest. If you have recoded a variable, please include a distribution of just the recoded data (i.e., the new variable). Then, for each distribution, graph, or statistic presented, summarize in words what the data means (i.e., “Approximately half (54%) the sample is female.”) Type the summary below the corresponding SPSS result.

3. In SPSS, run the appropriate test of the unadjusted relationship between your exposure and outcome variables. Use your recoded or computed variables if created them last week (i.e. cross-tab tables, chi-squares, correlation, and coefficient) in order to answer your research question.

Cut and paste your cross-tab tables and test statistics to a word document. Below each SPSS result, state in words the meaning of the result (e.g., Females are more likely than males to wash their hands after every visit to the washroom [Chi-square = 3.84, p=0.05]).

4. Organize the results you will be presenting (no more than 5 tables or graphs). Create new tables or graphs in Word so you can modify the formatting if needed and add descriptive titles and labels (refer to Chapter 11 of your textbook). Then, add your text from the last two weeks in paragraph form.

After organizing your findings, consider the following questions:

How do your results compare to and/or expand the results reported by studies you reviewed for your introduction?

What are the possible reasons for finding the results that you did? (Make clear that statements you make that are not backed up by your results are speculation.)

What do the results suggest for the goals of future studies on this topic?

What do the results suggest in terms of interventions, preventions, outreach, policy etc. to improve the health outcome of interest to your study?

Using the answers to these questions as your guide, draft your Discussion section. Begin by briefly describing your overall findings with respect to your research question (i.e., did you find an association between your exposure and outcome?). Next, discuss how these findings align or are consistent with the previous literature. If they are inconsistent, describe the inconsistency and add possible explanations for it. Next, discuss the strengths and limitations of your study, with respect to both internal and external validity. Consider potential biases here. Last, describe future directions for your readers, which may include policy recommendations, changes in clinical practice, and/or the need for additional research. It is also common to include a final concluding paragraph that summarizes your findings and the implications of this work.

5. Complete The Draft of the Paper

To do so, first draft the Methods section of your paper. Generally, the Methods section should include the following subsections, usually denoted with subheadings:

1. Study overview (this section is often brief - maybe a sentence or two - that includes the study design)

2. Participants and procedures (here is where you'll need the detailed information about how the study was carried out - a paragraph of approximately 4-5 sentences is usually sufficient

3. Measures (here, clearly describe your outcome, exposure, and potential confounders and how each one was measured)

4. Statistical analysis (here, include statements describing your approach to generating descriptive and inferential statistics, the statistical analysis package used, and how you treated missing data)

Please also review the articles you chose for your literature review table to see examples of how these Methods sections are written.

Second, finalize your Background, Results, and Discussion sections. Use the feedback the instructor has provided throughout the course to revise these sections accordingly.

Then, assemble the draft by including your Background, Methods, Results, and Discussion in a single document. Please also include a title page and a structured 250-word abstract on a separate page at the beginning of the document (prior to the Background section). Also include the list of your references on a separate page after your Discussion section and then insert your tables and/or graphs at the end of the document, each on a separate page. The entire paper should be in 11- or 12-point font and double-spaced using APA Format.

9 Studies:

An Epic Debunking of The Saturated Fat Myth. (2018). Healthline. Retrieved 14 May 2018, from https://www.healthline.com/nutrition/it-aint-the-fat-people

Brehm, B., Seeley, R., Daniels, S., & D’Alessio, D. (2003). A Randomized Trial Comparing a Very Low Carbohydrate Diet and a Calorie-Restricted Low Fat Diet on Body Weight and Cardiovascular Risk Factors in Healthy Women. The Journal Of Clinical Endocrinology & Metabolism, 88(4), 1617-1623. doi:10.1210/jc.2002-021480

Lee, T., & Pickard, A. (2013). Exposure Definition and Measurement. Agency For Healthcare Research And Quality (US). Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK126191/

Low-Carbohydrate-Diet Score and the Risk of Coronary Heart Disease in Women | NEJM. (2018). New England Journal of Medicine. Retrieved 14 May 2018, from https://www.nejm.org/doi/full/10.1056/nejmoa055317

Beulens, J., de Bruijne, L., Stolk, R., Peeters, P., Bots, M., Grobbee, D., & van der Schouw, Y. (2007). High Dietary Glycemic Load and Glycemic Index Increase Risk of Cardiovascular Disease Among Middle-Aged Women. Journal Of The American College Of Cardiology, 50(1), 14-21. doi:10.1016/j.jacc.2007.02.068

Liu, S., Willett, W., Stampfer, M., Hu, F., Franz, M., & Sampson, L. et al. (2000). A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. The American Journal Of Clinical Nutrition, 71(6), 1455-1461. doi:10.1093/ajcn/71.6.1455

Lasker, D., Evans, E., & Layman, D. (2008). Moderate carbohydrate, moderate protein weight loss diet reduces cardiovascular disease risk compared to high carbohydrate, low protein diet in obese adults: A randomized clinical trial. Nutrition & Metabolism, 5(1), 30. doi:10.1186/1743-7075-5-30

Keogh, J., Brinkworth, G., Noakes, M., Belobrajdic, D., Buckley, J., & Clifton, P. (2008). Effects of weight loss from a very-low-carbohydrate diet on endothelial function and markers of cardiovascular disease risk in subjects with abdominal obesity. The American Journal Of Clinical Nutrition, 87(3), 567-576. doi:10.1093/ajcn/87.3.567

Sacks, F., Carey, V., Anderson, C., Miller, E., Copeland, T., & Charleston, J. et al. (2014). Effects of High vs Low Glycemic Index of Dietary Carbohydrate on Cardiovascular Disease Risk Factors and Insulin Sensitivity. JAMA, 312(23), 2531. doi:10.1001/jama.2014.16658

Foster, G. (2010). Weight and Metabolic Outcomes After 2 Years on a Low-Carbohydrate Versus Low-Fat Diet. Annals Of Internal Medicine, 153(3), 147. doi:10.7326/0003-4819-153-3-201008030-00005