Week-1 Assignment Getting Your Research Project Started

[getitdonefzzz]

My first Data Viz. Program on SAS

# 1gapminder Program:

From above Program and results, I have successfully taken variables:  Alcconsumption, HIVrate, incomeperperson, urbanrate.

I have set limit URBANRATE greater equal to 90 only so as to make short and quick result table.

From the above results I have successfully interpret output of the program and as per the objective “FREQ MISSING”, “FREQUENCY PROCEDURE”, and required variables are interpretable. 

[getitdonefzzz]

Selecting the data set:

This is my first assignment on Coursera and I am trying to give my best, so giving feedback will be highly appreciated as it will help me to improve for further assignments.

I have gone through provided data sets and finally I chose to work with GAPMINDER data set.

(Gapminder seeks to increase the use and understanding of statistics about social, economic, and environmental development at local, national, and global levels.)

 Research question:

Topic:

1)     How does consumption of alcohol, breast cancer and HIV have impact on Life expectancy?

I will include all the relevant variables in my personal code book.

 2)     Association between life expectancy and income.

Here, variables like employ rate and urban rate can be included.

 Hypothesis:

·  Does economic growth raise life expectancy?

   Can drinking alcohol shorten your life?

·  Impact of community-based HIV/AIDS treatment on household                income.

·  Is urban rate associated with life expectancy?

 Selection of variables:

           As my research topic is based on life expectancy, I will use below mentioned variables:

Alcconsumption, Breastcancer, HIVrate, incomeperperson, employrate, urbanrate and lifeexpectancy.

 Search term used to get more information on research topic:

·         Impact of alcohol on life expectancy

·         Life expectancy of people with HIV

·         Life expectancy of patients with breast cancer

·         Connection between life expectancy and income

·         Disease and development(Urbanization)

Literature survey: 

·         Alcohol-related harms

There is increasing awareness of the significant impact of harmful use of alcohol[1] not only on individuals, but also on global public health.  The harmful use of alcohol ranks among the top five risk factors for disease, disability and death throughout the world. It is a causal factor in more than 200 diseases and injury conditions. Drinking alcohol is associated with a risk of developing such health problems as alcohol dependence, liver cirrhosis, cancer and injuries and more recently linked to infectious diseases (tuberculosis, HIV/AIDS).

https://health.gov.ie/wp-content/uploads/2016/03/Alcohol-Literature-Review-2014.docx

 ·      The Effect of Life Expectancy on Economic Growth in the United States

Mechanism to Earnings per Capita The traditional mechanisms that are usually discussed when describing how health impacts economic growth are increases in savings, education, and changes in the population age structure. With extended life expectancy, populations live longer, saving more into their retirement, investing more in their education and with a large percent of the population in the working age range this can lead to large improvements in economic growth (Bloom and Canning 2000). Since the model used in this paper controls for education and age structure, the contribution from life expectancy to earnings per capita measured below is not based on either of these mechanisms. Rather, the mechanism proposed in the analysis to follow is related to morbidity and worker productivity. Life expectancy, instrumented with tobacco tax, is predicted to increase the morbidity associated with diseases related to smoking such as cardiovascular disease, cancers, and respiratory diseases. Although this mechanism has not been well researched, the author plans to investigate at the individual level the effect on worker productivity and morbidity on income levels using the Mincer wage equation and available data 16 that contain smoking levels, wage data, as well as health and morbidity data. This mechanism is measured at the county and state level in the United States in the analysis that follows.                  

http://paa2010.princeton.edu/papers/101886

Links:

Breast cancer

https://academic.oup.com/annonc/article/26/6/1263/161844  

HIV rate

https://journals.lww.com/aidsonline/Fulltext/2012/01280/Projected_life_expectancy_of_people_with_HIV.9.aspx  

Alcconsumption

https://www.sciencedirect.com/science/article/pii/S0140673600042124  

Incomeperperson

http://www.augurproject.eu/IMG/pdf/1-_WP7_2nd_deliverable_April2011.pdf  

Disease & Development

https://www.journals.uchicago.edu/doi/abs/10.1086/529000  

https://www.tandfonline.com/doi/abs/10.1080/0032472031000142776  

 Summary:

Going through provided data and references, I am able to make some good points:

Stable and high-income rate leads to proper medication of disease, hence life expectancy in this case is high.

Bad addiction like alcohol consumption and smoking of cigarettes may shorten life.

HIV or cancer treatment involves financial funding, hence income per person is important.

Also, employment results in urbanization.

Henceforth, disease and negative addiction are inversely proportional to life expectancy;

While high income rate and urbanization are directly proportional to life expectancy.

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