1. Identify an existing at-risk population. Using aggregated statistics, include
ID: 3297566 • Letter: 1
Question
1. Identify an existing at-risk population. Using aggregated statistics, include identified criteria and data that substantiates why this population is at risk.
2. Using analyzed population data, identify a health risk within this population that nursing science can impact. Describe the specific variables. Provide SPSS data that correlates population to the identified health risk.
3. Identify potential obstacles that may hinder the implementation of the prevention and health promotion activities.
4. Identify stakeholders, individuals, and agencies with whom you may need to collaborate.
My questions are How do I display the population by female and male gender
1=female
2=male
How do I display the for age groups for each county
1=18-29
2=30-44
3=45-54
4=65 and older
How do I display the marital status for each county?
1=married
2=single
3=divorced
4=widowed
Also how to display race/ethnicity for each county
1=Caucasian
2=African American
3=Hispanic
4=Other/Multiracial
How do I display mortality by gender for each county?
The variables for each are above
How do I display mortality by race for each county?
The variables for each are above
I was just going to run frequencies on this data. Do you think that is sufficient?
Should I run frequencies for each variable?
The mortality numbers by race for Diabetes are by prevalence %
Dallas=10.2 Caucasians
African Americans=17.1%
Hispanic=12.2%
Other=7.1%
Baxter
Caucasians-7.0%
African Americans= 12.5%
Hispanic=20%
Other=2%
Bell
Caucasians=12.0
African Americans=22.0
Hispanic=15.0
Other=0
Hidalgo
Caucasians=13%
African Americans=30%
Hispanic=26%
Other=7.1%
Johnson
Caucasians=20%
African Americans=42%
Hispanic=30%%
Other=0%
Terrant
Caucasians=12.0
African Americans=49%
Hispanic=12.0
Other=6.0
Travis
Caucasians=13%
African Americans=17.1%
Hispanic=25%
Other=5.0%%
Midland
Caucasians=22%
African Americans=27.1%
Hispanic=22.2%
Other=4.1%
Lubbock
Caucasians=18%
African Americans=33.1%
Hispanic=20.2%
Other=6%
Brazos
Caucasians=25%
African Americans=47.1%
Hispanic=10.0%
Other=17.1%
The mortality numbers by sex for Diabetes are by prevalence
Dallas
Female:=19.3%
Male:=24.6%
Baxter
Female:=15.0%
Male:= 32.7%
Bell
Female:=25%
Male:=30%
Hidalgo
Female:= 15%
Male:=28%
Johnson
Female:=11%
Male:=28%
Terrant
Female:=32%
Male:=24%
Travis
Female:=10%
Male:=22%
Midland
Female:=12%
Male:=15%
Lubbock
Female:=28%
Male:=33%
Brazos
Female:=22%
Male:=18%
Citrix Viewer View Devices Epidemiology Part 2 EMJ_2.sav [DataSet1]- IBM SPSS Statistics Data Editor ile Edt YewData TransformAnayze Graphs tities Estensions Window Heb Type Width Decimals Label ValuesMissin Numeric Name Measure Role Align Right Center Unknown Input Right Unknown Center Nominal Input Center Center /Scale input Center NominalInput Center Center Nominal Input Center NominalInput CountyName 2 Population Texas County Name Population of County Age Group of Individual Race_Ethnicity Marital Status Presence of Risk Factors CVD Present Heart Disease Present Stroke Present HTN Present Overwight and Obese Present1, Yes Family History Present 1, Dallas.. None 3 Age 4 Race_Ethnicity Numeric Numeric Numeric Numeric Numeric Numeric Numeric Numeric7 1.00,18-29. None 1, Caucasi... None (1. Married. None (1, Yes) None [1. Yes.. None 1,Yes).None 1, Yes None 1. Yes) None None (1, Yes.. None None Input 14 13 13 Marital_Status Scale Input 6 Risk Factor CVD Heart Dz Nominal input 10 11 Ovenvieght_Obese Numeric 12 FamilyHistony 13 MortalityRatebyRace Numeric8 14 MortalityRatebyGender Numeric8 15 15 Center Nominal Input Center db Nominal Input Center / Scale center Scale input Numeric7 Texas Mortality Rate by Race for D..1 Input Texas Mortality Rate by Sex for Di (1, Men-24 None 17 : 19Explanation / Answer
Running frequencies on this data set is fine. But given that you need to find the correlations and what variables work & which of them could be obstacles, you should analyze the overall frequencies test result and then re-run the frequencies on the variables that seem out-of-touch with the data set to confirm the hypothesis that you develop from the result.
Incase you need the complete anaylsis on this, provide a sample dataset or even the population to run this on and we will get the results run on it and explain it to you.
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