Émilie counil, phd ([email protected]),2).pdfstudy sample: 14 villages, people aged 18...
TRANSCRIPT
Émilie Counil, PhD ([email protected]),M-L Château-Degat, A Ferland, P Julien & É Dewailly
December 11th, 2008 Arctic Change Conference,
Québec City
36
22
9
3
30
0 10 20 30 40
Other foods
Cereal products
Fruits and vegetables
Milk products
Meat and alternatives
About 70% of Inuit people declared consuming one bad quality food at least 3 times a day
Percentage of daily energy (24h-recall)
As an introduction
Source: Nunavik Inuit Health Survey 2004
Percentage of daily energy (24h-recall)
8
12
6
5
6
0 5 10 15
Fat
Sweetbeverages
Sweets
Snacks
Other
9% soft drinks
36
22
9
3
30
0 10 20 30 40
Other foods
Cereal products
Fruits and vegetables
Milk products
Meat and alternatives
Source: Nunavik Inuit Health Survey 2004
As an introduction
George River, November 2007
Akulivik Northern Store,
March 2008
Epidemiological studies:Consumption of carbonated drinks and obesity in children and teenagers (James et al. 2004, Ludwig et al. 2001)
Sugar-sweetened beverages, weight gain, and type 2 diabetesin women (Schulze et al. 2004)
Soft drink, cardio-metabolic risk factors, and the MetS in adults(Dhingra et al. 2007)
Possible mechanisms:
Physiological effectsDietary behaviorEconomics of food choice
Does the association hold among Inuit?
Research Hypothesis
Study sample:14 villages, people aged 18 and aboveExclusions: non Inuit, pregnant, incomplete data, abnormaly high/low energy
Biochemical analysis:
Blood lipoprotein profiles, fasting glucoseFatty acids in RBC membranes
Clinical measures:
Blood pressureWeight, height, waist circumference
Questionnaires:
LifestyleQuantitative Food Frequency Questionnaire
The Circumpolar Inuit Health in Transition Cohort Study: Nunavik
Inuit Health Survey 2004(n=1006)
Study Sample (n=552)
Inuit Health inTransition Cohort
(n=929)
Study sample
International Diabetes Federation (IDF): Central obesity (abnormal waist or BMI>30 kg/m2) + at least 2 criteria:
1. Raised triglycerides (≥1.7mmol/l) or medication2. Reduced HDL-c (<1.03 and <1.29mmol/l in M and F) or medication3. Raised blood pressure (SBP ≥130 or DBP ≥85 mm Hg) or treated HTA4. Raised fasting plasma glucose (FPG ≥5.6mmol/l) or history of DM
Identify those with «incident MetS»:Central obesity (abnormal waist or BMI>30 kg/m2) + at least 2 criteria:
1. Raised triglycerides and NO MEDICATION2. Reduced HDL-c and NO MEDICATION3. Raised blood pressure and NO HISTORY OF TREATED HTA4. Raised fasting plasma glucose and NO HISTORY OF DM
IDF definition and «incident» cases
Definition of the MetS
Bootstrap (SAS callable SUDDAN 9.0)Complex sampling design and partial non response
Descriptive statistics adjusted on age and genderF-test (continuous) and Wald chi-square (categorical variables)Satterthwaite correction for degrees of freedom
Logistic regression, covariates: Model 1: age, sexModel 2: + smoking (5 class), energy (FFQ)Model 3: + SFA (FFQ), trans-, n3- & n6-FA (red blood cell)
Statistical analyses
All sweet beverages 733.8 [668.6;799.0]
+ Diet sodaAll drinks 811.2 [732.6;888.8]
Drink
So sweet
n=552Median (ml/day) 95%CI
Fruit juice 152.1 [122.0;182.2]
Regular soda 354.8 [268.3;441.4]
1 can (12 oz) = 355ml = up to 50g of sugars = 1.6 to 2.9$!
Median consumption exceeds 2 cans per day
Consumption of sweet beverages
+ Tang, Punch, …Soft drinks 399.3 [349.1;449.5]
0
200
400
600
800
1000
1200
1400
1600All
18-29y
30-39y
40-49y
50-59y
60-89y
Fruit JuiceRegular Soda
Consumption of different types of sweet beverages by age group
0
200
400
600
800
1000
1200
1400
1600All
18-29y
30-39y
40-49y
50-59y
60-89y
Fruit JuiceRegular SodaSoft Drink
Consumption of different types of sweet beverages by age group
0
200
400
600
800
1000
1200
1400
1600All
18-29y
30-39y
40-49y
50-59y
60-89y
Fruit JuiceRegular SodaSoft DrinkAll sweet beverages
Consumption of different types of sweet beverages by age group
Consumption of different types of sweet beverages by age group
0
200
400
600
800
1000
1200
1400
1600All
18-29y
30-39y
40-49y
50-59y
60-89y
Fruit JuiceRegular SodaSoft DrinkAll sweet beveragesAll drinks
More than 17% of participants were defined as having the MetS
«Prevalence» of the Metabolic Syndrome
Mets/component Frequency (n) 95%CIMets (IDF) 17.4 (96) [14.7;20.6]
Mets (new) 6.0 (35) [4.3;8.2]
Mets (known) 11.4 (61) [9.2;14.1]38.3y56.4y
50.2y
22.0% HTA4.5% DM
Central obesity 58.3 (340) [54.1;61.6]
Abnormal TRIG 20.8 (115) [17.5;24.5]
Abnormal HDL-c 20.4 (109) [17.3;23.9]
Abnormal BP 31.4 (167) [27.7;35.4]
Abnormal GLU 9.9 (55) [7.8;12.6]
p
Age 47.1 36.6 29.9 <10-5
Energy (kcal/d) 1731.7 2133.4 2672.1 <10-5
Carbohydrates (g/d) 227.9 304.2 422.4 <10-5
Total fat (g/d) 54.6 64.7 69.9 0.0001
Saturated fat (g/d) 19.8 23.1 24.8 0.001
Caffeine (mg/d) 232.3 282.6 384.7 <10-5
Tertile 1 Tertile 2 Tertile 3
0.0-1.3 can 1.3-3.4 can >3.4 can
Participants intakes by tertiles of all beverages consumption
Other patients characteristics
Triglycerides (mmol/l) 1.04 1.17 1.27 0.008
Waist circumf. (cm) 90.7 91.9 93.4 0.14
Non smokers (%) 34.7 22.1 17.5 <10-5
Data are reported as least square means (adjusted on age and sex) except for smoking
Model 1AgeSex
Model 2+ Energy
+ Smoking
Model 3+ SFA
+ trans-FA+ n3-FA+ n6-FA
Tertile 2 Tertile 3 Tertile 2 Tertile 3 Tertile 2 Tertile 3
All Cases of Metabolic Syndrome
2,19[0,97;4,93]1,13
[0,56;2,29]
2,39[1,06;5,39]1,15
[0,58;2,28]
1,58[0,78;3,22]0,88
[0,48;1,60]
-1
1
3
5
7
9
11
13
15
OR
Results:Odds Ratio
Newly diagnosed cases of Metabolic Syndrome
7,12[1,54;32,9]
3,51[0,99;12,48]
7,00[1,53;32,00]
3,44[1,01;11,37]
4,52[1,36;15,00]
2,69[0,96;7,51]
-1
1
3
5
7
9
11
13
15
OR
Model 1 Model 2 Model 3
Tertile 2 Tertile 3 Tertile 2 Tertile 3 Tertile 2 Tertile 3
Results:Odds Ratio
Model 1 Model 2 Model 3
Tertile 2 Tertile 3 Tertile 2 Tertile 3 Tertile 2 Tertile 3
Results:Odds Ratio Cases of Metabolic Syndrome with previous knowledge
1,12[0,32;3,90]
0,77[0,28;2,14]
1,23[0,38;4,02]0,82
[0,31;2,11]0,81
[0,28;2,39]0,57
[0,25;1,30]
-1
1
3
5
7
9
11
13
15
OR
Limitations & Discussion
Lower consumption of SSB reported by people with known risk factors for MetS:
True lower consumption: concern about diet and/or age (taste)?Or under-report (social desirability)?
Stratification on prior knowledge about risk factor(s):Reduces sample size and powerCannot fully overcome limitations of cross-sectional design
Still, strong associations are reported in relatively young Inuit: Clinical significance of the definition based on other populationsClustering of deleterious life-style habits
November 2008, Nunavik
Marie-Ludivine Château-Degat
Annie Ferland
Éric Dewailly
My co-authors at the
Public Health Research Unit
Lipid Research Centre
Pierre Julien
Aknowledgements
Financial support
Nasivvik, Arctic Net, IPY2007-2008
Nunavik
All Inuit participants!
Thank you for your
attention!