#hivrate

I reviewed all code books and found that Gap Minder has information of interest to me. The variable which I am interested in is HIV Rate as my country and region is heavily affected by it. There are a number of variables which I believe contributes to the spread of HIV. For example, alcohol consumption, employment rate, urban rate. There are also some variables which are consequences of HIV such as life expectancy, suicide rate.

From what I have observed in my area and from reading about the HIV rate from other parts of the world, HIV seem to be common among people as young as 20 years old up to 50 years. I have observed through social media that young girls are mostly at risk of early infection because they interact with older, working men. This is because through the working men they can easily afford things such as luxury clothes, phones, laptops, entertainment. They end up putting themselves at risk of HIV infection.

I have decided that I would like to see if there is any association between HIV rate and Alcohol consumption. Is HIV rate higher in countries where there is high alcohol consumption?

I have designed my cookbook to include HIV rate and alcohol consumption which are the variables I would like to study.

I have consulted some literature to see what research has been done on HIV rate and alcohol consumption. The sources that I reviewed are the following:

1.       Drug and Alcohol Consumption and Trade and HIV in the Caribbean: A Review of the Literature

http://www.jscholaronline.org/full-text/JAID/203/Drug-and-alcohol-consumption-and-trade-and-HIV-in-the-caribbean-a-review-of-the-literature.php

 2.       Integrating HIV/AIDS and Alcohol Research

http://pubs.niaaa.nih.gov/publications/arh333/167-178.htm

 3.       Alcohol Use and Sexual Risk Behaviour: A Cross-Cultural Study in Eight Countries

http://www.who.int/substance_abuse/publications/alcohol_sexual_risk_crosscultural.pdf

 4.       REVIEW OF RESEARCH ON ALCOHOL AND HIV IN SUB-SAHARAN AFRICA

http://www.mrc.ac.za/policybriefs/AlcoholSubSaharan.pdf

From the literature reviews, young people who consume alcohol are more likely to engage in sex, mostly at a younger age and with multiple partners. This increases the risk of HIV infection. Women working in hotels, restaurants, bars, night clubs seem to be at risk of engaging in alcohol related sexual behavior. Heavy drinkers are also at risk of HIV infection. People who drink alcohol may delay seeking treatment for HIV

So managed to finish Week 3 today and do both quiz and of course submit the Assignments.

For Assignment 5 I find that my explanatory variable is employment and my response variables are ) Breast Cancer incidence, 2) HIV prevalence and 3) suicide rate. As my response variable is quantitative, I have made scatterplots:

In the Scatterplot with Employment rate on the X-axis and Breast Cancer incidebce on Y-axis, I am not sure, if I can say if there is a relationship yet. I didnt figure out, how to make a regression line, which would allow to decide, how strong the relationship is in the case of one. I had predictided that there would be a positive relationship because studies have showed that incidence of the disease is highest in industrial countries (except Japan). I make an assumption that employment rate is higher in industrial countries then non-industrial (dont know if I can say that :oI ) countries. I will need to wait till I am tought how to examine for relationship. 

This Scatterplot with Employment rate on X-axis and HIV Prevalence on the Y-axis is a bit difficult to conclude something for. I therefore decided to do a bar chart, where I group employment rate. I will use the previous groups I have used according to percentiles (Q1, median, Q3). With this I had following results.

Surprise! I expected that there would be a negative relationship, as I believe that a country with high unemployment would have citizens with more risky behaviour. So I expected that the number would steadily decrease with higher rate of employment. But we cant really conclude anything before we make further analysis and calculate a p value that lets us know if the results are results of coincidence :)!

Yeah, I am eager to continue with lectures so that I can make some further analysis and find out, weather there is an association.

I wonder, how I can best describe this histogram? Hmmm...gotta come back to this.

Ungrouped Frequency Table

Grouped Frequency Table

Hi there,

Finally back and writing another post. The Gapminder includes a lot of data on variables related to development and MDG – just my cup of tea. But I of course had difficulties making a choice on what variables to work with. I have now decided to focus on employmentrate and morbidity (that is breatscancer, HIV and suicide). 

Employment is essential not only to maintain an income but also to have appropriate living conditions. Unemployment contributes to social health inequalities and is found to be an independent predictor of morbidity (Bartley M et.al., 2004) and mortality from suicide and external causes (Moser KA, 1984; Sorlie PD, 1990).

So I decided that my first research questions should be:

1. Is employment status associated with morbidity (breatscancer, HIV and suicide) 

My second research question is 

2. Is the Internetusage associated with morbidity (HIV and suicide)?