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Topic: Diabetes Principles of Sociology Quantitative Analysis Assignment

Principles of Sociology

Quantitative Analysis Assignment
Background
This course carries a Quantitative Reasoning flag, which means that at least 10% of the total grade must based on work demonstrating proficiency in quantitative reasoning skills. Courses flagged for quantitative reasoning must include content and/or assignments that demonstrate how quantitative, mathematical, statistical and/or computational methods can be applied to problems in a discipline. In this class, you will use quantitative reasoning skills to help explain social phenomena.

Overview
For many decades, social scientists have demonstrated that health, illness, and death are the products of social conditions. For this assignment, you will use existing sources to examine county-level differences (in a state of your choice) in death rates for a cause of death you select. You will then look at demographic differences in the counties to help explain factors that might contribute to the different death rates. Finally, you will use sociological literature, concepts, and/or frameworks to further frame your analysis. In order to complete the assignment, you will need to gather data from two databases: CDC WONDER and Census Quick Facts. You will also need to consult the CDC’s publication on ICD 10 codes to identify a cause of death. Once you have selected a cause of death, you will use CDC WONDER to identify the two counties with the highest rates and the two counties with the lowest rates. Then, you will consult Census Quick Facts to gather information on social factors that might be responsible for the different death rates in the different counties. You will create tables with the data you gather and provide a narrative description and interpretation of what you find.

Steps to Complete this Assignment

STEP 1: Think about causes of death you find interesting or telling about our society.

STEP 2: Consult the CDC’s publication on ICD 10 codes. ICD stands for International Classification of Diseases. You can find the pdf here: https://www.cdc.gov/nchs/data/dvs/im9_2002.pdf.pdf

STEP 3: Once you have identified a cause of death, you will go to the CDC WONDER database to gather county-level data on death rates per 100,000 people. You can access the WONDER data here: https://wonder.cdc.gov/cmf-ICD10.html

STEP 4: In WONDER, you will identify the two counties with the highest death rates per 100,000 and the two counties with the lowest death rates per 100,000.

IMPORTANT: For causes of death that are gendered or affect specific age groups, you should not rely only on the “crude rate per 100,000,” but also the “age-adjusted” rate. You can also break out the rates by gender and race if you would like to examine the data more carefully.

STEP 5: Once you have identified the two counties with the highest death rates and the two with the lowest death rates, you will go to Census Quick Facts to gather information on characteristics of each county’s population. You can access this database here: https://www.census.gov/quickfacts/fact/table/US/PST045217

STEP 6: Makes notes about any key characteristics of the county’s population that you think might help explain the high or low death rates. This can include things like median income, education, owner-occupied housing, population density. You are also welcome to search for other data using other databases that might also shed light on the death rates. This can include things like unemployment rates, pollution, and obesity rates.

STEP 7: Once you have gathered all of your data, you will create tables showing the data you gathered. You can organize these tables in a variety of ways, but they should be clear and include the death data along with any other data you think is significant.

STEP 8: Thinking more sociologically. Once you have gathered all of your data and created tables, you are ready to think about sociological concepts or frameworks that might help explain your data. Select one or two concepts or a specific theoretical framework. You can also search for sociological literature on your topic. Try to limit your use of articles to one or two.

STEP 9: Writing it up. The last step is writing the narrative. Your paper should be approximately 5 pages long.

Sections of the paper:

I. Introduction (1-2 paragraphs):
Describe your topic. What is the ICD-10 definition? How many people die from this cause in the U.S. per year (to answer this question, you might need to search the CDC’s website)? How many people in the state you selected die from this cause (for these data, you can use WONDER and not select a specific county)? Are death rates going up or down? Is it costly? Provide a roadmap for your paper.

II. Methods (2-3 paragraphs):
How did you select your cause of death? How did you collect your data? What databases did you use to collect the data? What additional questions/issues did you examine? What surprised you? Were your preconceived ideas confirmed?
III. Findings (1-2 pages):
What did you find? Include your tables in this section. Describe the counties with the highest and lowest death rates. Are there similarities between the counties with highest death rates and lowest death rates? If so, what are these? Here you will want to rely on the Census Quick Facts data. Describe any other data you collected to help explain the different death rates and the counties.

IV. Analysis (2 pages):
How do you make sense of the social factors that might have contributed to the different death rates you found? For example, how might higher poverty rates contribute to higher suicide rates? Is there research on some of the relationships you identified? If so, briefly describe that here. Are there sociological concepts and/or frameworks that might help to explain the links between some of the social indicators of the county and death rates? If so, provide a description.

V. Conclusion (2 paragraphs):
Summarize your major findings and your analysis. You can also describe areas of needed future research or interventions to lower death rates.

Using the CDC WONDER database:

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