Interdisciplinary Case Study for the Core Curriculum
We are in the process of creating a series of integrated case studies to be used in all of the core courses to demonstrate the contributions each core course can make to addressing public health problems.
One interdisciplinary case study that we are developing focuses on efforts to improve health in Weymouth, MA (based on a real case).
The working draft of the case can be accessed at:
http://sphweb.bumc.bu.edu/otlt/MPH-Modules/Weymouth/
The online module begins by giving a brief history of the development of Weymouth from its colonial origins to the present day.
In 2003-2004 Weymouth conducted a town-wide health survey, the results of which raised concerns about the general health of the residents. The data set below is a subset of the actual data that was collected and analyzed by JSI.
Import the data set Weymouth_Adult_Part.csv.
Begin a new script in the RStudio editor with the following code:
### Part 1###
# The first command below creates a data frame object called 'wey'.
# The "na.omit" part asks R to omit missing data points, i.e., those for which data is "not available."
wey<-na.omit(Weymouth_Adult_Part)
# Next, attach the data set
attach(wey)
# Create a derived variable for the respondent's age in 2002 (when the data was collected) based on their reported birth year.
age=(2002-birth_yr)
# Compute body mass index (BMI) as shown below.
bmi=weight/(hgt_inch)^2*703
# Compute the mean and standard deviation of bmi and quantiles
mean(bmi)
[1] 26.03121
sd(bmi)
[1] 5.393322
quantile(bmi)
0% 25% 50% 75% 100%
10.96235 23.23926 25.84559 29.69308 54.54867
summary(bmi)
Min. 1st Qu. Median Mean 3rd Qu. Max.
10.96 23.26 25.85 26.94 29.70 54.55
The next page continues the exercise with code that produces histograms and boxplots.