Intro and Evaluating Evidence

Question 1

What is the importance of chronic disease prevention?

Answer 1

Question 2

What is chronic disease?

Answer 2

• Diseases of long duration and slow progression
• May be non-communicable (non-infectious)
• Examples: cancer, heart disease, diabetes
• Accounts for >60% of all deaths globally

Question 3

Today in Canada, 84% of males and 90% of females reach at least age 65.
Why this change? [5]

Answer 3

• Sanitation
• Improved medical care
• Vaccinations
• Improved social safety net
• Nutrition (decreased prevalence of deficiency diseases; however, current diets are increasing risk of chronic diseases)

Question 4

Will today’s children die earlier than their parents?

Answer 4

Maybe not, but their quality of life in later years is decreasing due to chronic disease.

Question 5

What is a risk factor?

Answer 5

• Any substance or condition that increases one’s risk (likelihood) for developing the condition.
• Modifiable = can be altered (e.g., smoking, diet, physical activity, sleep patterns)
• Non-modifiable = cannot be altered (e.g., age, genetics)

Question 6

What are some dietary risk factors? [10]

Answer 6

• High sodium
• Low nuts/seeds
• High processed meats
• Low seafood omega-3 fats
• Low vegetables
• Low fruits
• High sugar-sweetened beverages
• Low whole grains
• Low PUFAs replacing CHO or saturated fats
• High red meats, unprocessed

Question 7

What are the Bradford Hill Causal Criteria? [5] + [4 bonus]

What are concerns of the first 5?

Answer 7

1. Consistency of association: relationship observed repeatedly
   
   • concerns: consistent errors across studies; inability to find consistent relationships due to methodological differences across studies (different tools used to collect information, different populations studied)
2. Strength of association: effect size
   
   • concerns: often only weak associations in nutrition studies
3. Dose response: statistically significant linear trend
   
   • concerns: threshold effects → nutrient/outcome relationships are not always linear; misclassification → food records vs. food frequency questionnaire
4. Biological plausibility: theoretical explanation/mechanism
   
   • concerns: unknown mechanism for effects of nutrients on diseases; foods vs. nutrients (complex systems); what part of the food is responsible for the effect?
5. Temporality: exposure precedes the outcome
   
   • concerns: did diet cause disease? Or did disease cause a change in the diet?

Bonus:

• Specificity: exposure causes a specific outcome
• Analogy: comparison to a similar biological system can be made
• Coherence: fits in with existing knowledge
• Experiment: true experimental study finds the association

Question 8

What are 5 challenges is measuring change?

Answer 8

1. The level of original measurement matters.
2. There may be a minimal detectable difference (i.e., can only detect differences greater than the measurement error of the instrument used)
3. Starting points matter → floor/ceiling (i.e., already as high/low as it can get, outcome won’t differ) effects; regression to the mean)
4. Variables change naturally over time (e.g., blood pressure)
5. Tools of measurement must be both reliable and valid.

Question 9

What are some advantages of survey research? [3]

Answer 9

• Cheap and convenient
• Can survey a broad geographic area and large number of subjects
• Relatively inexpensive compared to other research methods
• May serve as a basis for hypothesis development and future research ideas.

Question 10

What are limitations of survey research? [4]

Answer 10

• Non-response bias
• Interviewer bias
• Misreporting
• Poorly designed questions (may be misunderstood / might be asking the wrong thing)

Question 11

Compare cross-sectional, cohort, and case-control studies regarding the timing of outcome and exposure.

Answer 11

Cross-sectional: O + E

Cohort: E (follow over time) O

Case-control: O (look back for) E

Question 12

What are advantages of case-control studies? [4]

Answer 12

Useful for studying: ­

• Rare conditions ­
• Conditions with a very long lag between exposure and outcome
• Usually requires fewer subjects than cohort or cross-sectional studies
• Generally quicker and cheaper than cohort studies

Question 13

What are limitations of case-control studies? [6]

Answer 13

1. Difficult to establish temporality ­

Did exposure precede disease OR did diet/lifestyle change because of disease?

2. How far back?

Must determine appropriate time period in the past in terms of biological plausibility

E.g. For folic acid and neural tube defect – appropriate to ask about intake from 1 year ago BUT for ω-3 fatty acids and heart disease, how far back to ask about? – 1 year, 5 years, 10?

3. Reliance on Memory

Difficult to recall past practices accurately

4. RECALL BIAS

Cases more motivated than controls to search their memory to make sense of why they have the condition

Thus, cases may be more likely to report past exposure

5. Misclassification

Misclassification of cases

Misclassification of exposure status

6. Cannot calculate disease incidence or prevalence

Proportions of cases in the study sample ≠ proportions with the outcome in the population

Question 14

What is the difference between an odds ratio and risk?

Answer 14

Risk (Probability) = likelihood of event of event A /total number of events

Odds = likelihood of event A /likelihood of alternate event

Example: Risk vs. Odds of rolling a 6 on a die

Risk = 1/6

Odds = 1/5

Question 15

How is an odds ratio interpreted?

Answer 15

OR > 1 → exposure more likely in cases than controls (There is a positive association between the exposure and outcome)

OR < 1 → exposure is less likely in cases than controls (There is a negative association between the exposure and outcome OR there is a protective effect of the exposure)

OR = 1 → no difference in odds of exposure between cases and controls

Question 16

When is an odds ratio considered statistically significant?

Answer 16

An OR is considered statistically significant when the confidence interval (CI) excludes 1.0

The Confidence Interval is the range of values within which the true population value likely exists

Eg. 95% CI ­

95% chance that the true value for the population lies within the CI

Eg. 99% CI ­

99% chance that the true value for the population lies within the CI

For α = 0.05 (Type I error), a 95% (1 – α) CI is used

Eg. OR 3.01 (95% CI 1.86-4.85) ­

Sample odds ratio = 3.01 ­

95% chance that the true population value lies somewhere between 1.86 and 4.85

Generally, the larger the sample size, the smaller (and more precise) the CI

Question 17

What three questions should you ask yourself when you interpret an odds ratio?

Answer 17

Is the OR >1 or <1?

Does the CI include 1?

Is the CI very wide or very small?

Question 18

What is considered a ‘strong’ odds ratio?

Answer 18

>4 or <0.25 = strong

2-4 or 0.25-0.5 = moderate

1.5-2 or 0.5-0.67 = possible but weak

<1.50 or >0.7 = possible but very weak

Question 19

Which of the Bradford Hill Criteria for Causation cannot be shown with case-control or cross-sectional studies?

Answer 19

Temporality

Question 20

Describe the advantages of prospective cohort studies. [5]

Answer 20

• Can establish timing and directionality of events
• Can calculate incidence (new cases)
• Avoid potential for recall bias
• May be easier (or at least more feasible) than a randomized controlled trial
• If well designed, can assess many outcomes

Question 21

Describe limitations of prospective cohort studies. [4]

Answer 21

1. Confounding: Exposure may be related to another (unknown) factor that is associated with the outcome
2. Level of exposure may change over time
3. Loss to follow up: Particularly problematic if people who withdraw from the study have different characteristics than those who remain involved
4. Large sample size is needed if outcome of interest is rare

Question 22

How is relative risk interpreted?

Answer 22

RR < 1 → outcome less likely to occur in exposed group than non-exposed group

(Negative association between exposure and outcome)

RR >1 → outcome more likely to occur in exposed group than non-exposed group

(Positive association between exposure and outcome)

RR = 1 → no relationship between exposure and outcome

With RR can say:

“Exposed are x times as likely to have the outcome”

Eg. RR = 0.70, Subjects who took Vitamin C supplements were 0.70 times (or 70%) as likely to get heart disease

Eg. RR = 2.2 Subjects who drink milk were 2.2 times as likely to have strong bones compared to those who did not drink milk

Question 23

When is relative risk statistically significant?

Answer 23

RR is statistically significant when the confidence interval does NOT include 1

Question 24

What type of studies can odds ratios be calculated for?

What about relative risks?

Answer 24

Odds Ratios may be calculated for cohort studies, case-control studies or experimental studies

Relative Risks are used in cohort studies and experimental studies (where risk is compared between treatment group/control group)

RR should NOT be calculated for case-control studies

Question 25

Describe advantages and limitations of cross-over design.

Answer 25

**Advantage**: Subjects serve as their own control, therefore, no differences between treatment and control group; Can use smaller sample size **Limitation**: Can not use crossover design if treatment leads to a permanent change (Eg. education program)

Question 26

What are advantages of randomized controlled trials? [5]

Answer 26

* Controls for possible confounders → aims to have comparable groups by randomization * Level of exposure controlled/manipulated by researcher * Control group for comparison (ensure effects are due to treatment) * If blinded, reduces bias * Provides evidence about temporality of associations

Question 27

What are limits to randomized controlled trials? [5]

Answer 27

* Cost * Feasibility → ethical implications * Large sample size needed for statistical power * Poor compliance and drop outs * External validity/generalizability

Question 28

What are 5 nutrition RCT challenges?

Answer 28

1. **Duration** 1. Longer interventions → difficult to have compliance with dietary interventions over long term 2. Shorter interventions → long enough to have impact? 2. **Controlling exposure** 1. Difficult to completely ‘control’ intake of a nutrient 2. Difficult to have good compliance with nutrition interventions 3. **Level of exposure** 1. Cannot have zero intake group of essential nutrient 2. Typically comparing ‘some’ intake with ‘more’ → how to define ‘some’ and ‘more’; ‘some’ may already be enough for outcome of interest → threshold effects 4. **Nutrients vs. food** 1. Will supplement of omega-3 fatty acid produce the same effect as obtaining omega-3 fatty acid from eating fish? 5. **Difficult to accurately measure nutrient intake** 1. Rely on memory and subject's ability to accurately recall foods consumed & portion sizes 2. Foods consumed vary meal-to-meal and day-to-day 3. Similar foods may vary in nutrient content.

Question 29

When is OR, RR, or mean difference significant?

Answer 29

OR, RR → significant if CI does not cross/include 1 Mean difference → significant if CI does not cross/include 0

Question 30

What are advantages of systematic reviews? [3]

Answer 30

* Summarizes current research * Systematic methods for data retrieval limits potential for bias * Considered to be evidence of the highest level in the hierarchy of research designs.

Question 31

What are limitations of systematic reviews? [4]

Answer 31

* Limited by publication bias * Differences in methods for selecting and assessing quality of papers that may affect results * Averages may miss effects in certain groups * Systematic reviews may not always be updated → to ensure information is up to date: * Check publication date * Look for new papers published after that date → *Results from systematic reviews and meta-analyses still need to be interpreted critically.*

Question 32

One of the issues when trying to find a dose-response relationship in nutrition is that nutrient-outcome relationships […].

Answer 32

Generally do not have linear relationships

Question 33

What are some limitations of cross-sectional studies? [4]

Answer 33

**Limitations**: Non-response bias; misreporting, cannot show disease incidence or temporality

Question 34

Describe the complexity of identifying diet-disease relationships. [5]

Answer 34

* Multiple factors may contribute to disease risk * Possible confounding factors in diet-disease relationships * Long latency period (time between exposure & disease appearance) * For prospective studies & RCT, need large sample size and long follow-up * Difficult to assess nutrient intake

Question 35

A confounding factor influences only the outcome. True or False?

Answer 35

False. Confounding factors influence both the exposure and the outcome.

Question 36

A confounding factor influences both the outcome and the exposure. True or False?

Answer 36

True.

Question 37

What is meant by clinical significance?

Answer 37

Statistical significance = not likely due to chance alone Clinical significance = meaningful conclusions

Question 38

How is nutrient intake assessed? What are 2 challenges associated with these methods?

Answer 38

* Diet assessment tools (FFQ; 24 recall; diet records) * Potential for misreporting or forgetting foods * Require accurate nutrient database of food composition

Question 39

What are the 3 steps in evaluation of evidence?

Answer 39

1. Consider the **totality** of the evidence (ecological studies; cross control; case control; cohort; experiments) 2. Consider whether the evidence is **convincing** (consistent evidence from good quality studies) 3. Consider whether the evidence show **causation** (consider Hill criteria for causation)

Question 40

What is an ecological study?

Answer 40

In epidemiology, ecological studies are used to understand the relationship between outcome and exposure at a population level, where 'population' represents a group of individuals with a shared characteristic such as geography, ethnicity, socio-economic status of employment.

Question 41

Compare cross sectional, case-control and cohort study designs. ## Footnote These are observational study designs.

Answer 41

Cross sectional = E + O measured concurrently Case-control = Start with O; look 'backwards' for E Cohort = Start with E; follow over time for outcome

Question 42

Describe experimental study design.

Answer 42

* Independent variable manipulated by researcher * Randomization controls for confounding effects * Can be 'blinded' or 'double-blinded' * Can show 'causation'

Question 43

What distinguishes a TRUE experimental study from a QUASI experimental study?

Answer 43

Participants are randomly assigned to groups in a true experimental study.

Question 44

What is the 'gold-standard'?

Answer 44

Double blind, placebo controlled, randomized controlled trial (RCT) ## Footnote Neither subject nor researcher is aware of group assignment; minimizes potential for bias and confounding.

Question 45

What are 2 common feasibility issues with experimental studies?

Answer 45

* 'Placebo' group still consumes nutrient from foods * Compliance

Question 46

Describe the hierarchy of evidence for clinical decisions.

Answer 46

Question 47

What factors should you consider when evaluating the quality of a study? [5]

Answer 47

* Design * Choice of measurement tools * Sample size * Statistics * Control for confounding or other factors ## Footnote Quality Criteria Checklist. Academy of Nutrition & Dietetics. www.andeal.org/evidence-analysis-manual

Question 48

What are the Hill criteria for causation? [5]

Answer 48

* Consistency * Strength of relationship * Dose response (But be aware of sigmoid relationships between nutrition and disease!) * Biological plausibility * Temporality

Question 49

Describe sigmoid relationships and threshold effects in nutrition science.

Answer 49

* A standard dose-response does not generally appear in nutrition as it does in pharmaceutical science.

Question 50

Which observational study design(s) are unable to show temporality?

Answer 50

Cross sectional Case control

Question 51

What is considered convincing evidence according to the WCRF/AICR Third Expert Report? [6]

Answer 51

* evidence from ≥ 2 study types * ≥ 2 cohort studies * consistency of findings * biological plausibility * good quality studies * experimental evidence (human or animal)

Question 52

What is considered probable evidence according to the WCRF/AICR Third Expert Report? [4]

Answer 52

* evidence from ≥ 2 cohort or ≥ 5 case control studies * consistency * biological plausibility * good quality studies

Question 53

What is considered limited-suggestive evidence according to the WCRF/AICR Third Expert Report? [2]

Answer 53

* evidence from ≥ 2 cohort or ≥ 5 case control studies * biological plausibility

Question 54

What is considered limited-no conclusion evidence according to the WCRF/AICR Third Expert Report? [1]

Answer 54

Insufficient evidence

Question 55

How are forest plots interpreted?

Answer 55

* Each ‘black box’ shows the OR (RR or mean diff) for an individual study → the lines extending from the box shows the 95% CI * The size of the black box reflects the weight of the study in the meta-analysis (and usually, the sample size) * The clear weighted diamond is the weighted mean of all the studies

Question 56

Of all the 9 studies in this forest plot, how many showed a statistically significant effect of the treatment?

Answer 56

3

Question 57

What is a forest plot?

Answer 57

A forest plot, also known as a blobbogram (lol!), is a graphical display of estimated results from a number of scientific studies addressing the same question, along with the overall results. ## Footnote In this example, the forest-plot shows that overall, eating processed meat is associated with increased risk of colorectal cancer, and this was statistically significant.

Question 58

What is the difference between an odds ratio and risk?

Answer 58

Risk (Probability) = _likelihood of event of event A_ total number of events Odds = _likelihood of event A_ likelihood of alternate event Example: Risk vs. Odds of rolling a 6 on a die Risk = 1/6 Odds = 1/5

Question 59

If the risk is ½ (50%), what are the odds?

Answer 59

1:1

Question 60

If the odds are 3:1, then the risk is…?

Answer 60

¾ (75%)

Question 61

If the risk is 1/10 (10%), then the odds are…?

Answer 61

1:9

Question 62

If the odds are 1:99, then the risk is…?

Answer 62

1/100 (1%)

Question 63

What is an odds ratio?

Answer 63

= _Odds of exposure among cases_ Odds of exposure among controls Exposure refers to independent variable, could be nutrient intake, supplement intake etc.

Question 64

How is an odds ratio interpreted?

Answer 64

**OR \> 1** → exposure *more likely* in cases than controls (There is a positive association between the exposure and outcome) **OR \< 1** → exposure is *less likely* in cases than controls (There is a negative association between the exposure and outcome OR there is a protective effect of the exposure) **OR = 1** → no difference in odds of exposure between cases and controls

Question 65

When is an odds ratio considered statistically significant?

Answer 65

**An OR is considered statistically significant when the confidence interval (CI) excludes 1.0** The Confidence Interval is the range of values within which the true population value likely exists Eg. 95% CI ­ 95% chance that the true value for the population lies within the CI Eg. 99% CI ­ 99% chance that the true value for the population lies within the CI For α = 0.05 (Type I error), a 95% (1 – α) CI is used Eg. OR 3.01 (95% CI 1.86-4.85) ­ Sample odds ratio = 3.01 ­ 95% chance that the true population value lies somewhere between 1.86 and 4.85 Generally, the larger the sample size, the smaller (and more precise) the CI

Question 66

What three questions should you ask yourself when you interpret an odds ratio?

Answer 66

Is the OR \>1 or \<1? Does the CI include 1? Is the CI very wide or very small?

Question 67

What is considered a ‘strong’ odds ratio?

Answer 67

\>4 or \<0.25 = strong 2-4 or 0.25-0.5 = moderate 1.5-2 or 0.5-0.67 = possible but weak \<1.50 or \>0.7 = possible but very weak

Question 68

What is absolute risk?

Answer 68

(Absolute) Risk of outcome in the whole sample = (Number with outcome) / (Total sample size)

Question 69

What is relative risk?

Answer 69

Likelihood that outcome occurs in exposed group compared to unexposed group Ratio of the risk among exposed to the risk among unexposed Null hypothesis → relative risk = 1 (no relationship) E.g., Subjects who took Vitamin C supplements were [RR] **as likely** to die from heart disease as subjects who did not take Vit C supplements

Question 70

How is relative risk interpreted?

Answer 70

**RR \< 1 →** outcome less likely to occur in exposed group than non-exposed group (Negative association between exposure and outcome) **RR \>1** → outcome more likely to occur in exposed group than non-exposed group (Positive association between exposure and outcome) **RR = 1 →** no relationship between exposure and outcome **With RR can say:** “Exposed are x times **as likely** to have the outcome” Eg. RR = 0.70, Subjects who took Vitamin C supplements were 0.70 times (or 70%) as likely to get heart disease Eg. RR = 2.2 Subjects who drink milk were 2.2 times as likely to have strong bones compared to those who did not drink milk

Question 71

Describe how relative risk may be expressed by the amount risk is increased/decreased in exposed compared to unexposed subjects.

Answer 71

**If RR is \<1, being exposed decreases the risk of having the outcome** Decreased risk = (1.00 - RR) x 100 Eg. RR = 0.70, (1.00-0.70 \* 100 = 30%) ­ exposed subjects were 30% less likely to get the outcome than unexposed subjects **If RR is \>1, being exposed increases the risk of having the outcome** Increased risk = (RR – 1.00) x 100 Eg. RR = 1.5, (1.5-1.0 \* 100 = 50%) ­ exposed subjects were 50% more likely to develop the outcome

Question 72

When is relative risk statistically significant?

Answer 72

RR is statistically significant when the confidence interval does NOT include 1

Question 73

What is risk difference?

Answer 73

Risk Difference = (Risk of outcome in exposed group) – (Risk of outcome in unexposed group) Null hypothesis: RD = 0

Question 74

What type of studies can odds ratios be calculated for? What about relative risks?

Answer 74

Odds Ratios may be calculated for cohort studies, case-control studies or experimental studies Relative Risks are used in cohort studies and experimental studies (where risk is compared between treatment group/control group) RR should NOT be calculated for case-control studies

Question 75

Answer 75

Question 76

What are 5 explanations for associations?

Answer 76

* Cause-effect * Chance/random error * Bias/systematic error * Effect-cause * Confounding

Question 77

What are explanations for associations? [5]

Answer 77

* Bias or systematic (spurious) * Effect-cause (real) * Confounding (real) * Chance/random error (spurious) * Cause-effect (real)

Question 78

What is confounding?

Answer 78

**A confounder is a 3rd factor that is:** * associated with the exposure and the outcome, and * makes the two appear related when they may not be.

Question 79

What is effect modification?

Answer 79

A 3rd variable _modifies_ (does not explain) the effect. The strength of the apparent association varies over different categories of a third variable (e.g., age, gender, genotype)

Question 80

Discern between confounding and effect modification.

Answer 80

* **Confounder** → _explains_ association * **Effect modifier** → influences association, _does not explain_ it.

Question 81

Describe the two main categories of error.

Answer 81

**Systematic** → ‘predictable’ errors of measurement (e.g., consistent under-/over-estimation); major concern for VALIDITY of measure. **Random** → due to chance; major concern for RELIABILITY of measure (i.e., there is no consistency)

Question 82

Which of the Hill Criteria for Causation are met by this evidence?

Answer 82

ALL, but strength of the relationship because RR =/= 2. However, in nutrition studies, a strength of relationship RR of 2 is not necessary to decide causality.

Question 83

Describe the relation between adult body fatness and risk of breast cancer pre- and post-menopause.

Answer 83

* Probable evidence that adult body fatness decreases risk of premenopausal breast cancer. * Convincing evidence that adult body fatness increases risk of postmenopausal breast cancer.