Title

A comparative analysis of wellness in Canadian cities: More alike than different

Streaming Media

Type of Proposal

Oral presentation

Start Date

31-3-2017 9:00 AM

End Date

31-3-2017 10:20 AM

Faculty

Faculty of Arts, Humanities and Social Sciences

Faculty Sponsor

Dr. Ken Cramer

Abstract/Description of Original Work

The present study examined the Moneysense 2016 rankings of 219 Canadian cities to further test the empirical derivation of Canada’s “best cities” based on 30 indices – covering climate, financial information, crime, and wealth— as derived from a principle axis factor analysis, and explained 47% of urban rankings: Climate (13% explained variance – consisting of amount of rainfall, number of days above 24°C); Financial (12% -- income, net-worth, taxes); Crime (11% -- crime rate and severity); and Wealth (11% -- car and luxury car ownership). A stepwise multiple regression predicted overall urban rank based on 10 significant indices: Rank scores were higher (like place finished in a race, so that worse cities performed worse) when individuals encountered greater unemployment (both in general and within the arts), when individuals drove older and lower quality vehicles, or relied greatly on walking in order to get to work, when household net-worth was low, when housing was less affordable, and when both crime rate and severity were high. Finally, a cluster analysis (examining how cities were similar according to comparable indices) uncovered three different types of Canadian city: Less populated cities; mid to large sized urban centres; and Mega-cities, with populations above 3 million residents, including West Vancouver, Toronto, Calgary, and Montreal. Mid/large cities were typically found in the penumbra of Mega-cities (e.g., the greater Toronto area). Of note, those cities in the largest cluster were more alike than they were different. The examinations into these cities may not explain which cities are populated with the happiest individuals, but it does offer insight into why people will flock to certain cities, perceiving them to be better places to live.

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Mar 31st, 9:00 AM Mar 31st, 10:20 AM

A comparative analysis of wellness in Canadian cities: More alike than different

The present study examined the Moneysense 2016 rankings of 219 Canadian cities to further test the empirical derivation of Canada’s “best cities” based on 30 indices – covering climate, financial information, crime, and wealth— as derived from a principle axis factor analysis, and explained 47% of urban rankings: Climate (13% explained variance – consisting of amount of rainfall, number of days above 24°C); Financial (12% -- income, net-worth, taxes); Crime (11% -- crime rate and severity); and Wealth (11% -- car and luxury car ownership). A stepwise multiple regression predicted overall urban rank based on 10 significant indices: Rank scores were higher (like place finished in a race, so that worse cities performed worse) when individuals encountered greater unemployment (both in general and within the arts), when individuals drove older and lower quality vehicles, or relied greatly on walking in order to get to work, when household net-worth was low, when housing was less affordable, and when both crime rate and severity were high. Finally, a cluster analysis (examining how cities were similar according to comparable indices) uncovered three different types of Canadian city: Less populated cities; mid to large sized urban centres; and Mega-cities, with populations above 3 million residents, including West Vancouver, Toronto, Calgary, and Montreal. Mid/large cities were typically found in the penumbra of Mega-cities (e.g., the greater Toronto area). Of note, those cities in the largest cluster were more alike than they were different. The examinations into these cities may not explain which cities are populated with the happiest individuals, but it does offer insight into why people will flock to certain cities, perceiving them to be better places to live.