Analysis 101, part 4: Case study

Catalogue number: 892000062020012

Release date: September 23, 2020

In this video, we will review the steps of the analytical process.

You will obtain a better understanding of how analysts apply each step of the analytical process by walking through an example. The example that we will discuss is a project that examined the relationship between walkability in neighbourhoods, meaning how well they support physical activity, and actual physical activity for Canadians

Data journey step
Analyze, model
Data competency
Data analysis
Audience
Basic
Suggested prerequisites
Length
9:01
Cost
Free

Watch the video

Analysis 101, part 4: Case study - Transcript

(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Analysis 101, part 4: Case study")

Analysis 101: part 4 - Case Study

Hi, welcome to our analysis 101 case study. Before you watch this video, make sure you've watched videos 123 so that you're familiar with the three stages of the analytical process.

Learning goals

In this video we will review the steps of the analytical process and you will obtain a better understanding of how analysts apply each step of the analytical process. By walking through an example. The example that we will discuss is a project that examined the relationship between walkability in neighborhoods, meaning how well they support physical activity. An actual physical activity of Canadians.

Steps in the analytical process

(Diagram of 6 images representing the steps involved in the analyze phase of the data journey where the first steps represent the making of an analytical plan, the middle steps represent the implementation of said plan and the final steps are the sharing of your findings.)

Throughout this video will refer back to the six steps of the analytical process and illustrate these steps through our walkability example.

What do we already know?

For analytical plan, let's start by understanding the broader context. What do we already know about the topic? Well, we already know that obesity is a problem in Canada. Insights from the Canadian health measures survey show that 29% of Canadian children and youth are overweight or obese while 60% of Canadian adults are overweight or obese. We also know that many Canadian adults and children are not active enough data from the Canadian health measures survey show that 33% of Canadian children and youth are meeting the physical activity guidelines, meaning that about 66% do not meet requirements. Likewise, 18% of Canadian adults are meeting the physical activity guidelines.

(Texte: "Without being aware of it, our neighbourhoods and how they are built influence how healthy we are.")

These challenges have led to increased attention around the idea of changing the environment in which we live to help Canadians make healthier lifestyle choices. This idea was the focus of the 2017 chief public health officers report on the state of public health in Canada, which noted that shifting behaviors is challenging. What would help Canadians become more active? More parks, better walking paths, or safer streets? Should policy makers look at crime rates? The list is endless.

What do we already know? Environments shape our health

There are a number of ways that our environment can influence our health behaviors. For example, our built environment such as how walkable our neighborhood is, or our health behaviors like how long we commute, or how many sports we participate in, can have an impact on our mental and physical health. Think about your own neighborhood. Does the design of your neighborhood make it easy or hard for you to walk to and from places or to get outside to exercise or play with your kids?

What do we already know? Knowledge gaps

Now that we understand the broader topic, let's identify the knowledge gaps. Previous studies had already demonstrated that Canadian adults living in more walkable neighborhoods are more active. However, recent findings focused on a few Canadian cities and did not provide national estimates. Likewise, previous work focus on how to get adults more active, but was limited in the analysis for children.

What is the analytical question?

Identifying a relevant analytical question is important to defining the scope of your work. For this study, the main question was does the relationship between walkability and physical activity in Canada differ by age? That's a clear, well defined question, and it's written in plain language.

Prepare and check your data

(Texte: Canadian Active Living Environments Database)

Now it's time to implement our plan. The first step is preparing and checking our data. Given that we had access to a new Canadian walkability data set, we wanted to leverage this new data source before we go any further. Let me give you some more context on walkability. Essentially, walkability means how well in neighborhoods supports physical activity. Walkability is higher in Denser neighborhoods, such as those with more people living on one block. It's also higher in neighborhoods with more amenities, like access to transit, grocery stores or schools or neighborhoods with well connected streets. Each neighborhood was assigned to walkability score from one to five. If you live in a suburban area outside the city core, your neighborhood will likely have a walkability score of three. Downtown neighborhoods will likely have a score of four or five.

Perform the analysis

(Texte: Canadian Active Living Environments; Canadian Community Health Survey (ages : 12 +years); Canadian Health Measures Survey (Ages: 3 to 79 years))

For our analysis, we linked external walkability data to two major Statistics Canada health surveys. We made use of both surveys because they use different measurements for physical activity. One survey asked respondents to self report their daily exercise while the other made use of accelerometers. Accelerometers capture minute by minute movement data. Think of it as a fancy pedometer.

Summarize and interpret your results

After some data cleaning concept, defining and lots of documenting our analytical decisions, we then started crafting a story based on our findings are main finding was that adults in more walkable neighborhoods are more active. However, different patterns were observed for children and youth. Their physical activity was pretty consistent across different levels of neighborhood walkability. When we started this work, there was a lot of evidence linking physical activity and neighborhood walkability in adults. But only a few studies examining children. Some studies found that children were more physically active in more walkable neighborhoods, while others stated the opposite. Finding we performed age specific analysis to examine this in greater detail and found that children under 12 are more active in neighborhoods with low walkability, like car oriented suburbs, which may have larger backyards, schoolyards, and parks where they can run around and play safely. But the relationship for children 12 and over with similar to that of. Adults, they were more physically active in higher walkability neighborhoods. Summarizing your results in simple terms is key to getting your message across to various audiences. As you learned in previous videos, translating complex analysis into a cohesive story is important. It's your job to digest the information and guide your reader through your story line.

Summarize and interpret your results: So what?

Interpreting the results also involves helping your audience understand the. So what factor for us. This meant highlighting that walkability is a relevant concept for adults, but we need to think differently about how to support physical activity in children. For example, what about parks, neighborhood safety, and crime rates? Explain to your reader how your findings fit within the existing body of literature. It's also a great practice to communicate what needs to be done going forward to advance our knowledge and flag any limitations to the study.

Disseminate your work

This project led to some very interesting analysis which we share it in different ways with stakeholders, policy makers and Canadians. Two major research papers were published for armor expert audience. While we also created an infographic on key points for a more general audience.

Summarize and interpret your results: So what?

(Diagram of 6 images representing the steps involved in the analyze phase of the data journey where the first steps represent the making of an analytical plan, the middle steps represent the implementation of said plan and the final steps are the sharing of your findings.)

The analytical process is a journey. It often takes much longer than you anticipate. First understand your topic and take your time to develop a clear and relevant analytical question. Make sure to check and review your data throughout the process and strive to translate your findings into a meaningful and interesting narrative. That way people will remember your work.

(The Canada Wordmark appears.)

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