1
Q
Type 2 Diabetes and Physical Activity association
A
Intensity does not matter
2
Q
BMI and Physical Activity association
A
- Risk reduction is greater with no adjustment
for BMI - Both pathways (PA & BMI) are involved in
reducing the risk of T2D - Risk reduction is less after adjusting for BMI
because we can see the direct effect of PA on
T2D
3
Q
Systolic Blood Pressure
A
Max pressure the heart exerts while beating
4
Q
Diastolic Blood Pressure
A
Amount of pressure in the arteries between beats
5
Q
Is intensity associated with improvements in SBP and DBP?
A
Only diastolic blood pressure because as intensity increases, so does the reduction
6
Q
Why is the reduction in risk of incident hypertension less after adjusting for BMI?
A
- By adjusting for BMI, you remove the effect of
the shared pathway of BMI and PA - This leaves the direct effect of PA on
hypertension
7
Q
No adjustment for BMI
A
- Risk reduction is greater because we can
reduce body weight by being physically active,
which then also reduces risk of hypertension
8
Q
Adjustment for BMI
A
- Risk reduction is less because you take away
one of the ways in which PA impacts blood
pressure
9
Q
Hypertension and PA association
A
Linear inverse association
10
Q
Blood pressure and PA
A
Regardless of blood pressure level or intensity, PA is associated with benefit in a dose-response pattern
11
Q
Modifiable risk factors
A
- Diet
- Exercise
- Weight
- Radiation exposure
- Tobacco
12
Q
Non-Modifiable risk factors
A
- Heredity
- Certain viruses
- Carcinogens
13
Q
Colon cancer and PA association
A
- Dose-response relationship
- 30-45 min of PA a day is associated with the
benefit - All forms of exercise are beneficial
14
Q
Colon cancer and cardiorespiratory fitness
A
- Powerful predictor of colorectal cancer
- When we adjust for PA, the relative risk
remains the same meaning regardless of your
level of PA, if you have a high CRF, you will
reduce your risk of colon cancer
15
Q
Sitting time and cancer mortality
A
- More time you spend sitting, the greater the
risk of cancer mortality - However, performing large amounts of PA (35
MET-hr/week) the risk of sitting becomes
insignificant
16
Q
Breast cancer and PA
A
- Threshold relationship
- Must be exercising regularly at high intensity,
meeting guidelines to see a benefit (gradual
decline in risk as PA increases) - 30 min a day
- Sedentary time increases the risk
17
Q
Lung cancer and PA
A
- Smoking is a powerful predictor of lung cancer
- In smokers, there is a benefit of
performing PA - In non-smokers, there is no trend to the
benefit of PA on lung cancer - Relationship between PA and lung cancer
must not be casual - Ex. those who smoke the least tend to be
more active and health-conscious, than those
who regularly smoke, causing a reduced risk
of lung cancer
18
Q
Sitting time and PA on all-cause mortality
A
Performing more PA for the same hours of sitting, reduces the risk to insignificant
19
Q
TV-Viewing time and PA on all-cause mortality
A
- TV viewing leads to a higher risk of all-cause
mortality than sitting (due to occupations) - Still a risk of this form of sedentary time on all-
cause mortality, even at a high amount of PA - Might be because of the things one does as
they view TV (eat, drink)
20
Q
TV-Viewing
A
Residual risk even with a high amount of PA
21
Q
Screen Time
A
Sitting while doing an occupation has different effects compared to sitting when performing recreation screen time
22
Q
Indirect field methods of body composition
A
- Bioelectrical impedance (BIA)
- Skinfolds
- Ultrasounds
- Bod pod
23
Q
Skin folds
A
- Measure the skin fold on a body part
- Derive total body percent fat score
- Not accurate to assume a smaller body part
has the same amount of fat as the whole body
24
Q
Fundamental Equation
A
C = f(Q)
C = unknown component (unknown adiposity)
f = mathematical function that links c to Q
Q = measurable quantity/property (skin folds)
25
Steps to derive and validate a field method equation
1. Choose a reference (criterion) method to
measure the unknown component
(dependent variable)
2. Choose a well characterized subject group
3. Apply statistical method to derive a function
(equation) for predicting the component from
the measured property
ex. take everyone in a class and use a
direct/criterion method (MRI) to measure
actual skeletal muscle mass.
4. Derive an equation that can predict skeletal
muscle mass from the BIA resistance (Ht2/R)
26
Derivation and validation of a BIA skeletal muscle prediction equation
1. Derive/develop the prediction equation
2. Cross-validate the prediction equation
- reference group used to develop the
equation must be similar in characteristics in
the other population to properly predict body
composition in the other group (ex. gender,
age, activity level)
27
Cross validation example
- An equation based on second-year kin
students at queens using MRI to develop the
equation is created
- this equation would be optimized and specific
to that population, if this equation works on
second-year kin students at Western, it has
been cross-validated
28
Deriving an equation
- Some don't always have access to money
for MRI technology
- Can locate an equation in the literature
(academic journals)
- Must resemble the population of interest
- Do not measure BMI with an equation that is
not specific for the population
29
Applying field methods of body composition
- No exercise or sauna for 8 hours before
measurement
- The body must be properly hydrated to
achieve an accurate impedance value
- No alcohol within 12 hours
- Height and weight are accurately measured
30
BMI and Obesity-related morbidity and mortality
BMI alone is not optimal for identifying obesity-related mortality
31
BMI and waist circumference
These two variables together are a better indicator of obesity-related mortality than either one alone
32
Ectopic fat accumulation
Visceral, liver fat accumulation of this may be why BMI and WC together are strong predictors of obesity mortality
33
Gender and location of excess adiposity
- Men: abdominal region grows (apple)
- Women: pre-menopause, lower body region
grows (hips and thighs) (pear)
34
Issues with use of BMI and WC to identify risk
1. BMI is only positively related to health risk
(causes of risk) after consideration of WC
2. We base risk off of BMI categories where they
could be individuals at the extremes of each
category who undergo a different risk
(assuming that all people with a certain BMI
have the same risk)
3. When BMI and WC are considered as
individual continuous variables, WC is a
positive predictor of risk, whereas BMI is
unrelated or negatively related to health risk
35
Mortality risk in adults (BMI and WC)
- The relationship between WC and mortality
risk is improved when BMI is adjusted for (take
out BMI effect on mortality risk)
- When we adjust for WC, a higher BMI
decreases the risk
- BMI masks the effects of WC
36
Low BMI
- At greater risk
- For a given WC, a lower BMI means the
individual has greater visceral fat and
therefore a greater health risk
37
Healthy cardio-metabolic profile
- Functional adipocytes store excess fat so it
does not go to unwanted places
- Ex. Subcutaneous adipose tissue going to the
heart or liver
38
Cardio-metabolic risk profile
- Dysfunctional adipocytes cant store excess fat
and therefore fat goes to unwanted places
- Ex. subcutaneous adipose tissue
39
Obesity management
It is said that one must achieve a weight loss of greater than 5% of body mass in order to deem the treatment as successful
40
Clinically significant weight loss
5% or more
41
Maintaining weight
3% or less
42
A revised approach to obesity management
- Change focus from the bathroom scale to
adaption of healthy behaviours
- Target the casual behaviours (diet & exercise)
- Must go upstream and look at causes of
obesity
43
Public interpretation of weight loss
- Weight loss is required for the benefit
- Ex. I will see no benefit to diet and exercise if i
do not lose weight
- No weight loss or limited weight loss is a
failure
44
Desired health outcomes related to obesity risk
- Improve CRF
- Decrease total adiposity
- Decrease visceral/abdominal adiposity
- Maintain/increase skeletal muscle mass
- Improve cardio-metabolic risk factors
- Weight loss is not a prerequisite for any of
these
45
Exercise and weight loss
- Exercise will improve cardio-metabolic risk
factors, skeletal muscle mass and CRF
regardless of weight loss
- Exercise without weight loss is not a failure
- Even exercise without weight loss causes a
decrease in WC, due to an increase in skeletal
muscle mass
KNPE 255
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