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Alexandre Lebel (CRAD)
The Geography of Overweight in Québec
Robert Pampalon (INSPQ)
Denis Hamel (INSPQ)
Marius Thériault (CRAD)
Halifax
June 2nd, 2008
CPHA 2008 Annual Conference
Background
Objective et methodology
Results and analyses
Presentation plan
•Why obesity is a public health concern?
•Why geography should be considered?
•Why obesity is a public health concern?
•Why geography should be considered?
•Main concepts
•Multilevel analysis
•Main concepts
•Multilevel analysis
Linked to a large number of chronic diseases•Coronary artery disease
•Stroke
•Breast cancer
•Colorectal cancer
•Hyperlipidemia
•Ostéo-arthrite
•Endometrial cancer
•Type 2 diabetes
•Pulmonary embolism
•Hypertension
•Gallbladder disease
20%Are directly
attribuable to obesity
Birmingham et al. (1999)
Life expectancy going down ?
Background:
1) Why obesity is a public health concern?
Main associations with overweight: individual characteristics
•Sex
•Age
•Marital status
•Income
•Education
•Race
•Other genetic factors
•Smoking
•Diet
•Physical activity
Lots of associations
Many interventions
Few results
2) Why geography is important?
Contextual Contextual characteristicscharacteristics
•Urban design
•Land use
•Transport system
•Rural
•Security
•Socioeconomic characteristics
Few associations!
Inconsistent resultsDifferent methodologiesHard to compareGeography given low importance
(Region definition, scale)
0
5
10
15
20
25
30
1973 1983 1993 2003
% o
bé
sit
é
Québec
Canada
Angleterre
É-U
Chine
Australie
Brésil
Mexique
France
Sources : diverses
Geographic differences in obesity prevalence
In the WorldIn the World
In QuébecIn Québec
Source : CCHS, 2003 (in Mongeau, 2005)
Overweight prevalance by health region
Québec 47 %
General objective:
To explore the spatial distribution of overweight in the Québec To explore the spatial distribution of overweight in the Québec population while taking into consideration individuals’ population while taking into consideration individuals’ characteristics, contextual indicators and an appropriate spatial characteristics, contextual indicators and an appropriate spatial frame of reference.frame of reference.
Objective and Methodology
Spatial frame of referenceSpatial frame of reference
15 Health Regions
Periphery b
Town (CA)d
Rural(MIZ)
CMA ofMontréal orQuébec City
Proximale
Remotef
City (CMA)c
Center a
Other urbanareas
Privileged or deprived 51 units
SampleSample
• CCHS 2003 (cycle 2.1)
• 20 000 Adults Living in Québec
•Dependant variable: BMI ≥ 25
• No pregnant women
• No individuals with BMI < 18,5
•Self-reported information
Men
Rank Region1 Montréal Center Privileged (a)2 Québec Rural Remote (f)3 Laval Periphery (b)4 Québec Rural Proximal (e)6 Appalachians Towns (d)8 Estrie Center (c)
40 Montérégie Towns (c)43 Lanaudière Towns (d)44 Québec Center Deprived (a)45 Gatineau City (c)47 Gatineau Rural Proximal (e)48 Abitibi Towns (d)49 Gaspésie Rural Remote (f)50 Côte-Nord Rural Proximal (e)51 Côte-Nord Towns (d)
Women
Rank Region1 Montréal Centre Privileged (a)2 Saguenay Towns (d)3 Québec Rural Proximal (e)4 Québec Center Privileged (a)5 Québec Rural Remote (f)6 Saguenay City (c)8 Estrie City (c)
13 Québec Periphery Privileged (b)40 Laurentides Towns (d)45 Montréal Periphery Privileged (b)46 Outaouais City (c)47 Mauricie Towns (d)48 Gaspésie Rural Remote (f)49 Mauricie Rural Remote (f)50 Outaouais Rural Remote (f)51 Outaouais Rural Proximal (e)
As a summary, we found that:As a summary, we found that:
Independent of individual characteristics known to be associated with overweight, many regions present significantly higher or lower odds of overweight.
These differences are not randomly distributed through space.
The geographical patterns are different between genders.
There is an important variability within rural as well as urban areas.
The contextual effect is stronger for women.
Consequently: • Geography is important
• Studying at local scale