Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

ENVI 165 Long Exam 2 > Epidemiology 2 > Flashcards

Epidemiology 2 Flashcards

1
Q

Define

Observational Studies

A
  • Uncontrolled studies/natural experiments
  • Viewed as less definitive than clinical trials
  • By the end of experiment, cohort might flake → your sample size will be lower
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What can/can’t you control in observational studies?

A
  • Only thing you control is finding the boundary in which you will observe
  • Cannot control certain factors (or confounders)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

List

Types of Observational Studies

3

A
  1. Cohort studies
  2. Case-control studies
  3. Cross-sectional studies
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Define

Cohort Study

A
  • Starts with exposed & non-exposed group, both w/o disease
  • Follow groups to observe disease incidence or mortality rates
  • How many people develop the disease based on who are & who are not exposed?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

In Cohort Studies, how are disease rates in both groups compared?

A

rate ratio or rate difference(??) lol

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

List

Types of Cohort Study

2

A
  1. Retrospective (past to present)
  2. Prospective (present to future)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Define

Retrospective studies

A
  • Faster & cheaper
  • Getting people now, and asking their past lifestyle
  • Info on exposure & confounders from historical information
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Define

Issues w/ Retrospective Studies

A
  • Bias, will they tell you accurately? Or too much/too little/incorrect info?
  • Di ka sure if your medical records are accurate
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Define

Prospective Studies

A
  • Take longer, more expensive
  • Measure exposure levels & confounding variables at baseline
  • Good when biological samples are required
  • Unreasonable to keep historical biological samples
  • To study diseases difficult to ascertain in retrospect
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Define

Issues w/ Prospective Studies

A
  • Lifestyle can change throughout the study: Takes longer, can be multifactorial
  • Inconsistent statistically
  • Tip: get too much at first, para kung umonti u arent screwed
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

List

What can cohort studies consider?

2

A

Cumulative incidence or risk (disease events per person)
* This person had disease event, this person didn’t

Incidence rates or mortality
rates (disease events per person per time)
* Over a month, x people had this disease

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Cohort studies are good for ____ exposures & ____ diseases

A

rare exposures & common diseases

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Define

Case Control Studies

A
  • Start: diseased & non-diseased groups
  • Look backward in time
  • More subject to bias than cohort
  • Case: has disease
  • Control: no disease
  • Compares odds of exposure in each group
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Define

Recall bias

A
  • Cases recall past exposures more often than controls
  • typical of retrospective exposure assessment
  • some people may recall more, some less
  • no such thing as perfect recall
  • Results biased towards finding association
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Case Control studies are good for ____ exposures & ____ diseases.

why?

A

common exposures & rare diseases

  • Since ure starting with a bias looking into the rare disease, might as well look into those patients
  • Cohorting a rare disease needs a huuuge cohort
  • Unicorn disease: hard to catch
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Proportion Exposed vs Odds of Exposure

A

Proportion exposed = a / (a+b)
Odds of exposure = a / b

a is no. of exposed
b is no. of non-exposed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

What conclusion can we draw when comparing odds of exposure and control?

A

odds of exposure > control → exposure is associated with disease

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Describe

Cross-sectional Studies (Prevalence Studies)

A
  • Measures exposure & disease at the same time
  • Done when outcome of interest is subclinical/asymptomatic disease
  • Difficult to determine whether exposure DID precede disease
  • looking at 1 point in time & getting samples (bio & envi) in that point in time
  • Tend to be weaker in design (compared to cohort & case-control)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Define

subclinical disease

A

illness that is staying below the surface of clinical detection

  • “under” the clinic, Clinic doesn’t see it bc you don’t go to the hospital bc it’s not that bad
  • Ex. blood has the lead due to low exposure, but won’t show disease associated with high exposure (neurotoxicity)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Relationship bet. Cross sectional studies vs. cohort or case-control studies

A

Cross-sectional is Often only possible design
* Can be confirmed in cohort or case-control studies
* Often first step before cohort or case-control studies

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Define

bias

A

Distortion of the true relationship bet. exposure & disease

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

List

Kinds of bias

3

A

Selection Bias
Confounding Bias
Information Bias

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Define

Selection bias

A
  • Selecting a study population not representative of general population
  • Cannot be corrected during analysis
  • Easy to do, but difficult to correct
  • Once you selected your sample, kahit anong sample test won’t explain why you selected your samples
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Describe

Healthy Worker Effect

A
  • Workers compared to general population
  • Results based against finding adverse health effects among workers
  • Typically ‘labour’ work (physical work)
  • What representation means may be different based on what you’re looking at
25
Q

Explain

how did the study on ethylene oxide & breast cancer obtain selection bias?

A
  • Only 20% of individuals in target pop answered questionnaire on how breast cancer occurs
  • Bc of how they designed where/how the interview will be, nagkakaselection bias agad
26
Q

Describe

Confounding Bias

A

Distortion of exposure-disease relationship by a third variable association with both exposure & disease
* Ex. Age, smokers

  • Adjustment for effect can be made during analysis
  • Might show association even when there isn’t
  • Influences both independent and dependent variables – will show association even if there isn’t
  • Even if you select your cohort really well, there can still be confounding bias – important to always talk to your cohort
27
Q

Describe

How does Confounding Bias impact results?

A
  • Might show association even when there isn’t
  • Influences both independent and dependent variables – will show association even if there isn’t
  • Can change positively or negatively(???? what)
28
Q

How can the error of confounding bias be adjusted during analysis?

A

Stratification of groups or multivariate analysis
* Can see odds ratio/incidence go down when your remove a confounder

However, you need to actively correct it
* Be aware that you have a confounding variable present
* pag di mo alam na may confounding variable, edi di mo maadjust sa stat

29
Q

Define

Effect modification

A

Third variable modifies the effect of the exposure variable of interest

30
Q

Define

Information Bias

A
  • Occurs when information obtained about either exposure or disease is incorrect
  • Mismeasurement or misclassification
31
Q

How does information bias impact results?

Towards what

A

Usually to bias results towards no association

32
Q

List

Kinds of Data Analysis Variables

2

A
  1. Categorical variable (or dichotomous variable)
  2. Continuous variable (on a spectrum)
33
Q

How do we analyze data when both exposure & disease variables are categorical?

A
  • Calculate rate ratio & odds ratio
  • Can be stratified to control for confounding
34
Q

How do we analyze data when both exposure & disease variables are continuous?

A

Regression analysis

35
Q

What are the implications of regression (R)?
What is an acceptable R?

A

R coefficient significantly different from 0 = exposure is significant predictor of disease

  • Acceptable R: usually +- 0.8, depends on nature of study
  • Minsan nga .5 relationship is strong enough eh (wtf)
36
Q

How do we analyze data when exposure & disease variables area mix of cat & cont?

A

Linear regression for outcome
* Can be used w/ categorized exposure in regression

Logistic regression - measure of interest is odds ratio
* Even when disease variable is categorical
* Either categorical or continuous variables can be included among disease predictors

37
Q

Why does epidemiology use a lot of regression analysis?

A

kasi you’re always looking at correlation, and regression analysis shows the quantitative relationship bet 2 variables

38
Q

____ sample sizes = ____ statistical power

A

Large sample sizes = greater statistical power

39
Q

Define

Confidence Interval
What is the usual CI set?

A

Range of plausible values for measure of effect
Usually 95%, if more sure edi 99%

40
Q

Idk this maica edit before long exam

Precision of estimate = reflection of random error
* Error likely to result form choosing sample of total population of interest
* Error from biases etc.

A
41
Q

Why does epidemiology have the risk of being less precise/accurate?
How do we account for the lower precision/accuracy?

A

nature of data collection makes precision difficult
* So your stat has to remove/control your data
* But also don’t overly control your data

42
Q

List

Other Aspects of Epidemiology

2

A
  1. Environmental Epidemiology
  2. Occupational Epidemiology
43
Q

What does Environmental Epidemiology include and exclude?

A

Includes environmental agents
* Large number of people are exposed involuntarily
* Looks at explicit connection w/ environment

Excludes voluntary exposures

44
Q

Describe
Environmental Epidemiology exposure

A
  1. Exposure is usually low level and homogenous
  2. Difference in risk bet. more & less exposure is usually small
    * Needs large sample size to see the small differences
45
Q

Differentiate

Pandemic vs Epidemic vs Endemic

A

Pandemic: global
Epidemics: unusual outbreaks of disease significantly above normal levels
regional
* Sudden urge in incidences
* Often caused by known agents

Endemic: exist at constant, low or bg levels
* Always there
* COVID is endemic: it’ll be there for a long time

46
Q

Define

Occupational Epidemiology & nature of its exposure

A

Studies of illness or iniury associated w/ workplace exposures

Relatively high exposures in relatively small numbers of people
* Often geographically isolated in a worksite

47
Q

How were we able to discover carcinogens in Occupational Epidemiology?

A

Historical studies - needed time to identify long term effects

48
Q

T/F

Current workplace exposures to suspected toxins lower than in past

A

T

49
Q

What is the goal of measuring exposure?

A
  • Detecting and quantifying dose-response relationship
  • Support a causal relationship
50
Q

What do we measure when measuring exposure?

A
  1. External exposures (the actual thing)
  2. Biomarkers (ex. Proteins produced by antigens)
51
Q

What is the impact of a mismeasured exposure?

A
  • Skews true dose-response to a weaker(?) relationship
  • Which is why we need to understand which biomarker to get to definitively measure exposure & disease
52
Q

What is the impact of Misclassification of an exposure?

A
  • severely bias toward null hypothesis (no relationship)
  • Part of information/selection bias
53
Q

Describe

Job-Exposure Matrix (JEM)

A

Cross classification of jobs and exposure levels across time

54
Q

How are jobs on JEM categorized?

A

Categorized based on presumably same exposure level
* Workers in all jobs in one category assigned same exposure level at any given point in time

55
Q

Describe

Biomarkers

A

Some are measure of internal dose
* Can account for variation in absorption and metabolism
* Estimate of biologically relevant dose

56
Q

T/F

Many Biomarkers persist long enough for use in retrospective studies
Why/why not?

A

F

few persist long enough for use in retrospective studies
* Bc we can metabolize hooray
* Ex. opioid addict who doesnt take opioids for a week will pass the drug test

57
Q

Define

Quantitative Meta-analysis

A
  • Combine results from different study designs
  • Provides weighted average of results across studies
  • Studies with the most weight = lowest variance
  • Do not need access to raw data (can access from other papers)
58
Q

Define

Pooled Analysis

A
  • Raw data from several studies obtained and re-analyzed
  • More time consuming
  • More flexibility for analysis
59
Q

Differentiate

Quantitative Meta-analysis vs Pooled Analysis

A
  • Quanti: combine results, weighted average lang (easier, no need for raw data)
  • Pooled: literally re-analyze raw data (more time-consuming, but also more flexibility for analysis)

ENVI 165 Long Exam 2 (4 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions