on May 16, 2011 by Georgina Moulton and pjarvis in e-Lab, Comments (0)

Exploring Obesity Atlas: a tool to analyse childhood obesity in your local region

Introduction to Obesity Atlas Presentation

Hands-on Practical Objectives

The aim of this short tutorial is to provide a hands-on experience of the Obesity Atlas software, and highlight both its benefits and limitations.

Outcomes

At the end of the tutorial you will be:

–          Able to use the web-interface of Obesity Atlas

–          Aware of why the software was commissioned and its use

–          Understand background processes used by Obesity Atlas (e.g., data cleaning)

–          Interpret the charts, graphs and statistics produced by the software

Background

This hands-on session will take up to one hour to complete.

It will walk you through the main features and some limitations of Obesity Atlas by asking you to analyse some data and interpret charts, graphs and maps produced by the software.

Please try and answer the questions (in italics) in the course material as they will help you understand how to use the software.  Remember, the presentation at the beginning will also be able to help with the questions.

Obesity Atlas URL

You will find the software at the following URL: http://www.obesityatlas.org.uk

Open a web-browser (preferably Internet Explorer) and go to the above address.

User accounts

Should you wish to register with your own details then please do so after the course (see below).

Exercise 1: Starting with Obesity Atlas

A username and password has been already been created only for the purposes for this hands-on session.  For future use of Obesity Atlas you will need to register for a username and password at: https://www.obesityatlas.org.uk/usermanager/registration.aspx .

Login to Obesity Atlas using the username and password provided.

Exercise 2: Uploading and Viewing Data

In order to use the tools and features of Obesity Atlas, you first need to upload your NCMP data.

Your data will be in excel format containing columns that represent different data-types and rows that represent separate individual records.

In Obesity Atlas, a minimum of four columns containing the following data is required:

–          Gender

–          Age

–          Height

–          Weight

In addition, the dataset can include Postcode and Ethnicity.

A test set of data for you to analyse is attached to this post.

ObesityAtlasTestData

In the menu on the left-hand side of the browser, click on the ‘Upload Data’ link.

The NCMP data you can be uploaded in two ways: interactively or standard.  The difference between the two is that the interactive mode allows you to amend the errors the data cleaning process discovers at the time of loading, whereas the standard mode will automatically remove data entries in which there are errors.

Choose the interactive mode for uploading data.

After you have uploaded your data, you should be able to view a sample of the data you have loaded.  Have a cursory glance of the data, and in particular check the column headings are correct.

Are the column headings correct?

Choose the appropriate option about the column headings.  If you have to change the column headings follow the instructions in browser.

You should not have had to change the column headings. You will now have a screen that displays the data in spreadsheet form.  Look at the summary at the top to see if there are an invalid records or scroll down the data to look for any errors.  You can if required change the errors in the data, which are highlighted in red, to the correct format etc. by clicking on the cell and changing the contents.

In this case, you do NOT need to change the cell contents.  Upload the data including errors.  Take a look at the summary of the cleaning report.  Following the guideline that 5-10% of data is usually lost during this process, you should be happy to proceed with the analysis.

Continue the data loading process, so that you can do further analysis.

Name you dataset as follows:

[your_initials]_[town]

Complete the remainder of the form with details provided:

Collection Year: 2005/2006

Denominator: Year R and Year 6

(Denominator definition: Fractions are written in the form ‘a/b’, and ‘a’ is called the numerator, and ‘b’ is called the denominator.  In epidemiology, the denominator usually represents a population group or a group of people at risk of a specific disease.)

Once your data has been successfully loaded, you can view it, by clicking on the ‘View Data’ link in the menu.

Exercise 3: Looking at Demographic Statistics

Click the ‘Demographic Statistics’ link, and proceed to have a look at first the Gender group and then School Year group statistics.

Looking at this data, what can you say about the demographics of the population?  Choose two important key messages.

Exercise 4: Looking at Obesity Statistics

Go to the Obesity Statistics form by clicking on the ‘Obesity Statistics’ link in the menu.

Look at the obesity statistics for both male and female in both school years.

Looking at the summary statistics what can you surmise about the classification schemes of the three organisations?

Exercise 5: Visual Inspection of Data using Charts and Graphs

To draw the chart/graph, choose your dataset, which gender and school year you wish to analyse, and what chart you wish to use.  Using the Charts and Graphs form, can you use and interpret the correct graphs to answer the following questions.

Which chart would you use to be able to compare the numbers of children in weight classifications between all males and females from both year R and year 6?

How would you compare the numbers of obese Males in Year R and Males in Year 6?

Is there a statistical significant different between the lowest and highest deprivation score for year 6 males?

Using the bar chart that shows proportion of obesity by ethnicity, can you tell us what the graph shows?  Hint: Comment on the differences between groups? Two key statements would be sufficient.

Is there any correlation between BMI SDS and IMD 2007 for both females and males in both school years?

Is there a correlation for any of the different groups?

If we consider just the obese population in males year R in the scatterplot, what would you expect to see?  Can you do this?

Using the stacked bar chart, what can you say about deprivation and the differences between normal, overweight, and obese for Year 6 Males?

Exercise 6: Thematic Maps

Thematic maps are implemented as static maps in Obesity Atlas.

Using different year groups and different genders, can you investigate if there are any hotspots for obesity in your population?  What are they?

Save your map onto your desktop.  You can save your map, by right-clicking on the map, choosing the ‘Save picture as’ option.

Thinking about how the thematic maps are created, is it possible to compare the outputs of different maps?  If not, why is this?

Exercise 7: Interactive Mapping

The interactive mapping option, gives users the option to create the maps interactively by allowing them to choose the demographic profile and geographical boundary (e.g., Lower Super Output Area, Middle Super Output Area and Electoral Ward).

In the ‘Interactive Mapping’ form, create the map for males, year R.  By looking at the map, and areas included what can you tell me about the data, which is used to create the map? Hint: boundary related.

If you hover over the different geographical areas, the area statistics can be viewed in the bottom right hand corner.

Look at the different areas in the map. Can you think of a limitation or an issue that a user (you) may need to be aware of when interpreting the map?

Can you look for hotspots in Males, Year 6? How does deprivation relate to this? (look at extra map provided).

Exercise 8: Obesity Profiles

Create an obesity profile for your dataset using the IMD 2007 deprivation scale.  This will take some moments, but on completion download of the profile download it to the desktop and view in Microsoft Word.

What are the differences between this and how you have interactively analysed your maps?

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