
Mapping
How Statistics Canada measures the nation’s obesity
Data on each province's obesity rates affects public policy. How accurate is it?
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Over the past 10 years, Jason Gilliland and his team at the Human Environments Analysis Laboratory (HEAL) at Western University have been conducting studies into what causes obesity in southern Ontario. They have created maps, such as those pictured here, to help them do so.
Gilliland, director of HEAL, explains how his research is being used to identify the geographic and socioeconomic links to healthy eating.
Map 1: Access to Healthy Foods in southwestern Ontario
Created in 2012, this map shows which areas have the easiest or most difficult access to healthy foods in southwestern Ontario. For the purposes of the study associated with this map, Gilliland categorized any supermarket as a source of healthy food.
He points out that there are many areas on the map (in red) that can be up to 35 kilometres away from a supermarket. These are called food deserts and are typically small towns or hamlets.
Gilliland says that public health officials from counties in southwestern Ontario are using this map in the development of policies and strategies that will improve the access to supermarkets in some regions. In London, Ont., for example, his research will be used to help achieve the city’s goal of eradicating food deserts by 2020.
Map 2: Access to Recreational Opportunities in Middlesex County
Gilliland and his team looked at how far Middlesex County homes were from parks, arenas and other public facilities to determine the recreational opportunities in the region.
He says that the importance of this map — one of 400 similar maps he and his team have created — is that it shows where child obesity is more likely to be present. He hypothesizes that people in the darker green areas and within the yellow lines (closest to recreational spaces) are more likely to be physically active and less likely to be overweight.
But Gilliland also notes that although the recreational spaces are there, it does not mean that they will be used. “Just because you build it doesn’t mean they will come,” he says. “However, if it isn’t there, they can’t come.”
Map 3: Density of Junk Food Around Elementary Schools in London
For this map, Gilliland used census data released in 2012 to illustrate the differences in the number of junk-food sites (which he classified as convenience stores or fast food restaurants) in low- to high-income neighbourhoods and to show the socio-economic factors that may affect obesity.
The black circles on the map represent schools. The bigger the circle, the greater the number of junk-food sites within a 500-metre-walk.
“It does appear from just looking at the map that the largest circles are in the orange areas — in the poorest areas,” Gilliland says, adding that it is “scary” how some of these schools are within range of 11 to 23 junk-food sites.
Gilliland has found that children who attend schools near junk-food sites are more likely to be associated with greater numbers of junk-food purchases before and after school, poor overall diet quality, and the increased likelihood of being overweight or obese.
This story is from the April 2015 Issue
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