TEST 1 Flashcards

1
Q

what is epidemiology

A

-disease states and events in objective, scientific and controlled manner
-screening, intervention, preventing bad health outcomes
-prevalence and incidence
-answers questions

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2
Q

prevalence

A

-portion of people who have the condition of interest in a population
-how is disease distributed in population (group with common characteristic)
-person, place, time

-point prevalence- # of cases at specific point in time
-period prevalence- # of cases over defined period
-lifetime prevalence- proportion of people who have had disorder at any time during life

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3
Q

incidence rate

A

-the rapidity with which newly dx cases of disease develop

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4
Q

2 principles epidemiology is based on

A

-1. disease doesnt occur at random -> things that increase and decrease likelihood
-2. these factors can be identified by systematic investigation of population

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5
Q

sample, sample error

A

-subgroup within a population
-sample error- natural variability in a population
-ex. measuring bus capacity on a middle school bus -> everyone weighs slightly different

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6
Q

selection bias

A

-sample is not random -> sample is chosen with subconscious bias
-ex. testing sugar on diabetics but all the diabetics are members from your church
-ex. more female pts in groups bc they reminded the researcher of his mother

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7
Q

validity vs reliability

A

-validity- accuracy
-reliability- repeatability of test

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8
Q

nominal vs ordinal vs interval data

A

-nominal- data that has no order -> name
-ex. blood type, eye color

-ordinal data- has a particular order
-ex. pain scale 1-5

-interval data- clear order data point -> mean, mode, median -> precise measurements

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9
Q

sub-disciplines of epidemiology

A

-disease- cancer, cvd, infectious
-exposure- environmental, genetic, nutritional
-population- clinical, geriatric, pregnant

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10
Q

sequence of epidemiologic investigation

A

-1. suspect exposure influences a disease (DESCRIPTIVE)
-2. hypothesis (DESCRIPTIVE)
-3. investigation to measure relationship (ANALYTIC/SCIENTIFIC)
-4. judge if relationship is significant -> chance, bias, confounding variables (ANALYTIC/SCIENTIFIC)
-5. evaluate preventions and tx (ANALYTIC/SCIENTIFIC)

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11
Q

confounding variable

A

-a variable that could also be causing a disease process in addition to the independent variable
-lead to paradoxical results
-ex. giving a drug to deadly cancer pts -> the drug looks like its working poorly but the pts were just really sick
-ex. coffee drinkers have a higher likelihood of CVD -> but coffee drinkers also have a higher likelihood of smoking
-not clear which is causing the result

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12
Q

hypothesis

A

-1. project the expected assoc between two or more measurable variables
-2. state clear implications for testing stated relations

-advance research
-guide study, variables, sample, analysis, interpretation
-fundamental hypothesis -> operational hypothesis

-ex.Caregivers to relatives with dementia will have a higher incidence of high blood pressure than non-caregivers, mediated through higher levels of stress-related symptoms

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13
Q

2 types of epidemiology

A

-descriptive -> monitor public health and hypothesizes about causes of disease -> identify and count cases of disease and conduct studies
-case report, case series, cross-sectional study
-ex. is this an outbreak?
-ex. framingham
-surveys- qualitative
-DESCRIBE PATTERNS

-analytic/scientific -> eval hypothesis about causes of disease and eval success of intervention -> compare groups and determine association
-clinical trial, experimental, case-control, cohort
-SEARCH FOR CAUSES AND PREVENTION

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14
Q

framingham study

A

-5,000
-MA
-1947
-50 years
-every 2 years fu
-nicotine, alcohol, conditions, dietary intake, emotional stress
-3rd generations

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15
Q

sources of data

A

-WHO- government, NGOs, HMOs, hospitals, researchers

-WHAT- US census, surveys, death certificates, birth certificates, cancer registries, discharge reports, etc.

-STRENGTHS- already exists, established methodology, little or no cost

-WEAKNESS- can be inaccurate, not the data you want, report delays, complicated methodology

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16
Q

descriptive data sources: specific

A

-census of US population- every 10 years, demographics

-vital statistics- birth, death*, marriage, divorce, fetal death

-national survey of family growth- marriage, divorce, family planning, infertility

-national health interview survey- major health problems

-national health and nutrition exam survey- diet and health

-behavioral risk factor surveillance system- telephone

-national health care surveys- use and quality of health care

-notifiable disease surveillance system- weekly data on diseases like STDs

-national immunization survey

-national survey of drug use and health- mental health and drugs

-surveillance, epidemiology, and end results program- prevention, dx, and tx of cancer

-birth defect surveillance and research programs

17
Q

pure research

A

-abstract and general
-generating a new theory
-goal- gain new knowledge
-theory!

18
Q

clinical research

A

-in a clinical setting
-cant control variables
-ex. drug trials

-experimental research can control variables

-laboratory- done in a lab where surroundings are controlled

19
Q

applied research

A

-answers practical questions to help people do their jobs better
-ex. time use studies, eval of diff types of interventions with the same purpose
-ex. using a mouse vs using a track pad improves work speed

20
Q

4 components for measuring disease frequency

A

-1. population (which group)
-2. cases of disease (numerator)
-3. size of population (denominator)
-4. time (be explicit)

21
Q

population

A

-can be defined by area or characteristic
-FIXED- permanent -> Ex. veteran of vietnam, people born in 1982

-DYNAMIC- state or condition -> ex. residents of boston, parents of teenagers

22
Q

measuring disease frequency

A

-ratio- numbers dont need to be related

-prevalence- proportion- numbers are related, %
-people with disease/TOTAL population
-point prevalence- # with disease on a single day

-rate- time is the denominator (incidence rate)
-NEW CASES
-involves a transition- (nonsick -> sick, al mive -> dead)
-denominator - population AT RISK
-dont include immune pts, pts who already have the disease, males (if studying uterine cancer)

23
Q

prevalence vs incidence

A

-prevalence- existing disease
-assess burden of disease
-allocate resources
-administration and planning
-conditions with uncertain onset (MS, depression)

-incidence- new disease
-what is causing this disease
-eval preventions
-eval tx

-cumulative incidence- time is described in words
-incidence rate- time is part of denominator

24
Q

cumulative incidence

A

-new cases during a specified time period
-transition (not sick -> sick)
-denominator- population at risk
-critical assumption- all people have been followed for entire time period
-risk of developing disease over time period
-# new cases/# in population AT RISK at start of time period

-relevant time period does not appear in equation but is stated in WORDS

25
Q

crude mortality rate, cause specific mortality rate, age specific mortality rate

A

-Crude mortality rate: Total # of deaths from ALL causes per 100K per year
-ex. 2015- 844/100,000 in US

-Cause specific mortality rate: Total # of deaths from a SPECIFIC cause (AIDS) per 100K per year
-ex. 2015- 197/100,000 in US

-Age specific mortality rate: Total # of deaths from ALL causes among individuals in a specific AGE category (< age 1) per 100K per year
-ex. 2015- 590/100,000 in US

26
Q

risk

A

new cases/persons at risk

27
Q

incidence rate

A

-number of NEW cases of disease / PT
-PT- total disease-free observation within the source population

28
Q

population comparisons

A

-assignment- measure INCIDENCE RATE of study population and control group
-assessment- determine prevalence in study group
and control group
-results- compare prevalence of variable with the incidence rates of disease in study group and control group
-interpretation- draw conclusions
-extrapolation- draw conclusions about people that arnt in your studied population
-group association

29
Q

case control study

A

-comparing people with a disease (cases) with people without a disease (control)
-ex. women with stroke (case group) compared to women without stroke (control) -> determine who takes BC and who doesnt
-individual association

30
Q

randomized controlled trial

A

-groups are randomly assigned (case and control) and the case group is given a variable
-ex. women are randomly assigned a group -> case group gets BC and control does not -> determine who has a stroke and who does not
-altering the cause alters the effect

31
Q

cohort studies

A

-cause precedes effect
-following a population over time
-ex. framingham study