Midterm Review Flashcards

1
Q

1 Contrast between PH with medicine

A

Ph focuses on prevention
– Achievements may be more difficult to recognize
– Less attention and funding
– Less than 5% of U.S. health spending is on public health

  • Yet public health programs clearly save lives and medical costs
    – U.S. life expectancy ↑ by ~30 years over 20th cent
    – Only ~5 of the 30 years can be attributed to medical care
    – Public health: nutrition, sanitation, housing, occupational safety, etc.
    – What was one of the biggest changes to health/disease over the 20th
    century? Cleaner air and water!
  • Politics:
    – $ How much “health” are we willing to fund?
    – What are we willing to give up?
  • Individual liberties, corporate profits, etc.
    – Is our emphasis on curing disease rather than preventing it out of
    control?

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2
Q

What was one of the biggest changes to health/disease over the 20th
century? Cleaner air and water!

A
  • British Cholera Epidemic
    1848-1849:
    – 616 deaths prompted
    Snow (and others) to
    investigate causes
    – Based on his clinical
    experience and review of
    epidemiologic
    characteristics of cholera,
    Snow formulated a theory
    of causation and
    transmission of the disease

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3
Q

John Snow Cholera Epidemic

A

Snow’s hypothesis
* Observations:
– A gastrointestinal disease, therefore causal agent was likely
ingested
– Diarrhea as most prominent symptom, therefore causal
agent likely left the body by this route
– If cholera excretions contaminated rivers from which
drinking water was taken, then the disease could be widely
disseminated
* Causal Hypothesis:
– Sewage-contaminated drinking water was a causal agent
for the cholera epidemic

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4
Q

Layers of Prevention and Intervention

A
  • Primary prevention
    – Prevent illness/injury from occurring
    – Discourage risk behaviors (e.g., smoking)
  • Secondary prevention
    – Minimize severity or damage after event has occurred
    – Screening for early stages
  • Tertiary prevention
    – Further minimize overall disability
    – Not always a huge distinction from “secondary”
    – Medical treatment and rehabilitation

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5
Q

Why is Public Health Controversial?

A
  • Moral and religious opposition
    – Sex education
    – Provision of contraception
    – Clean needle programs
    – Safe and legal abortions
  • Political interference with science and research funding
    – E.g., stem cell research, HIV research, climate change
  • Companies and private businesses are not always motivated to help their customers. They seek to earn profits.

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6
Q

Powers and Responsibilities of Government

A
  • U.S Constitution states that the fundamental purpose of the government is “to promote the general welfare”

-Reserve clause: health care is not mentioned in the Constitution so the responsibility for public health belongs to the states

-Interstate commerce provision justifies the activities of the Food and Drug Administration (FDA)

-Power to tax and spend is widely used by federal government to control public health policy (The federal government provides 65% of the funding for Medicaid)

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7
Q

A word about global health governance

A
  • World Health Organization (WHO)
    – Serves as a clearinghouse for science that informs public health at global and regional levels.

– Can issue policy recommendations, but does not have a “jurisdiction” and therefore cannot enforce rules.

– Coordinates efforts at a global level – especially useful in pandemic response.

– Useful to think of WHO’s role as one of health diplomacy.

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8
Q

“Descriptive” epidemiology

A
  • Who, Where, When (and how many)
  • Understand the state of population health and how it is changing
    – E.g., Are we making progress in CVD, cancer?
    – E.g., Are some diseases on the rise (or new)?
    – Prompts questions of: WHY?
  • Interventions (e.g., screening, etc.), treatments, changes to
    environment or behavior.
  • Understand disparities (e.g., by race-ethnicity, age, gender/sex, SES)

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9
Q

Endemic vs Epidemic

A
  • Endemic = the usual and expected rate of a
    disease in a population
  • Epidemic = an increase in the frequency of a
    disease above the usual and expected rate

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10
Q

Analytic epi (How)

A
  • We already know person, place, time because of the descriptive epi so we need to look at relationships to learn HOW epidemics occur:
    – Explain why and how a health problem occurs
    – Describe association between exposure and outcome
    – Test a hypothesis about the cause of disease by studying how exposures relate to the outcome
  • These studies look at:
    – Hosts
    – Environments
    – Agents

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11
Q

Epidemiology

A

The study of the distribution, causes, and effects of health and disease in defined populations
* Distribution
* Causes (and effects)
– Really difficult to prove “causation”
– We are attempting to find/show associations
* E.g., HRT is associated with an increased risk of heart disease
* Correlation does not imply causation
– Also investigating risk factors (might not refer to as a “cause” per se
– Sometimes we say “disease.” Sometimes we say “health outcome.” These terms are often used interchangeably.

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12
Q

Investigating Associations:
4 Types of Study Designs in Epi

A
  1. Cross-sectional
  2. Prospective cohort (longitudinal) – observational*
  3. Case-control – observational*
  4. Experimental/Interventional**

*Observational studies pose the least risk of harm.
**Experimental studies can potentially cause harm.

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13
Q

Prospective Cohort Study

A
  • Start with a defined population (cohort)…
  • Some are exposed and some unexposed …
  • Follow up and compare on development of disease
  • Text examples
    – Framingham Heart Study
  • CVD risk factors (BP, cholesterol, smoking) and heart disease
  • But we didn’t know they were risk factors!
  • There was no concept of “high” blood pressure (“hypertension”); considered a normal process of aging

– Nurses’ Health Study
* Oral contraceptives and breast cancer
* Regular consumption of alcohol increases risk of breast
cancer by 10% to 40%

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14
Q

Case-Control Study

A
  • Again, examine relation of an exposure to a disease
  • Identify people with the disease (cases) match to people w/o the disease (controls) and …
  • Start with two groups: disease (cases) and no disease (controls), and compare their prior exposure status
  • Text examples
    – EMS and L-tryptophan
    – Reye’s syndrome and aspirin use in children
  • A primary distinction from cohort study is starting with cases rather than a cohort (pre-defined pop)
  • Selection of cases
    – Sources: hospitals, physician practices, disease registries, etc. (Be mindful of generalizability!)
  • Case-control study saves time over cohort. WHY?
    – What if you’re waiting around for incident cases?
  • Advantages of over cohort designs
    – Inexpensive
    – Shorter time
    – Requires smaller sample (good when disease rare)
  • Limitations
    – Recall bias
    – Difficulties selecting controls
    – Cannot estimate disease incidence or prevalence.
    WHY?

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15
Q

Case study diagram

A

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16
Q

Experimental/Interventional:
Randomized controlled trials (RCTs)

A
  • Gold standard in research
    – Control group
    – Randomization
  • Planned experiment where investigators assign study participants to either an intervention or control group
  • Trials are designed to test efficacy of intervention or clinical treatment
  • They are often blinded to protect against breaches in ethics
    – Blind – the participants don’t know treatment status, researchers know treatment status
    – Double blind – neither participants nor researchers know treatment status

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17
Q

Measuring Disease
Prevalence vs. Incidence

A
  • Prevalence: # people who currently have a condition
    – Often expressed as a proportion
    – Implies a population at risk (the denominator)
    – Sometimes called frequency
    – E.g., 5%, or 50/1000 persons
  • Incidence: # of new cases/diagnoses
    – Usually includes a time dimension – WHY?
    – Also incorporates dimensions used/implied in prevalence
    (i.e., 3 dimensions)
    – E.g., 50/year, 50/1000 persons/year

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18
Q

Prevalence

A
  • Number of existing cases of disease in a
    population
  • Can be expressed as a percentage or number of cases per unit size of population
  • Indication of extent of health problem; helps us determine need and allocation of resources

Prevalence = Number of all cases (new + old)/Total population

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19
Q

Incidence

A
  • Rate of development of disease in a population over a certain time period
  • Can help identify emerging diseases, reemerging diseases, or outbreaks

Incidence = Number of new cases/Total population at risk

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20
Q

Prevalence vs. Incidence

A

Can be very different depending on the outcome

  • Chronic and incurable (e.g., HIV/AIDS, arthritis, diabetes)
    – Prevalence > incidence
  • Common and short-lived (e.g., STDs)
    – Incidence > prevalence
  • Rapidly fatal (e.g., pancreatic cancer, acute
    leukemia, Ebola, Dengue Hemorrhagic Fever)
    – Incidence > prevalence

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21
Q

Example of Incidence:
Disease Mortality

A
  • Death rate/mortality rate = incidence of death
    – E.g., 400 deaths/100,000/year
  • Note difference with prevalence: why do we not measure a “prevalence” for death?

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22
Q

Types of Results

A
  • True results:
    – True positive: a test indicates disease when there is disease present
    – True negative: a test indicates NO disease when there is NO disease present
  • False results:
    – False positive: a test indicates disease when there is NO disease present
    – False negative: test indicates NO disease when there is disease present

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23
Q

SENSITIVITY

A
  • The ability of a test to correctly identify those
    who have the disease
  • Sensitive tests are good at finding positive results
    – A sensitive test may be too good at finding positive results that it give false positive results
    – A test with high sensitivity will have few false
    negatives

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24
Q

SPECIFICITY

A
  • The ability of a test to correctly identify those
    who do not have the disease
  • Specific tests are good at finding negative results
    – A specific test may be too good at finding negative
    results that it give false negative results
    – A test that has high specificity will have few false
    positives
25
RR vs OR
* Relative Risk (Risk Ratio) (RR) – Used when comparing outcomes of those who were exposed to something to those who were not exposed – Calculated in cohort studies – Cannot be calculated in case-control studies because the entire population at risk is not included in the study * Odds Ratio (OR) – Odds of exposure among cases divided by odds of exposure among controls – Used in case-control studies – Provides a rough estimate of the risk ratio slide 52
26
Relative Risk (RR)
* Relative Risk (RR) = the ratio of the incidence for persons exposed to the factor to the incidence for persons in the unexposed group. * Used in prospective cohort studies slide 53
27
Strength of an Association Table 5-1: Relative Risk of Lung Cancer by Smoking Status
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Odds Ratio
* Odds Ration (OR) = a measure of the strength of an association between an exposure and a disease. – OR is a ratio of two ratios. – The numerator of the odds ratio is the ratio of exposed subjects to nonexposed subjects in the case group; the denominator is the ratio of exposed subjects to nonexposed subjects in the control group. * Odds Ratio used in case-control studies slide 55
29
OR: Reye Syndrome case-control study
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30
Why can’t we use RR in case-control study?
* It is not possible to calculate the relative risk in a case-control study because this calculation requires knowing the rate of new cases in the exposed versus the unexposed groups – but the starting point of a case-control study is a group that already has the disease, which does not directly reveal the rate of new cases in a broader population. slide 57
31
Sources of Error
1. Random variation = association merely due to chance 2. Confounding variables 3. Bias slide 58
32
Confounding
* Associations may not reflect causation because of confounding * We think (or hypothesize) that X causes Y * We conduct an epidemiological study and observe that X and Y are, indeed, correlated (associated) – YAY! * BUT what could lead to this observation? – It might truly be the case that X causes Y (XàY) – Or is it due to the relationships of X and Y to other variables (Z) slide 59-60
33
Bias
* Bias = systematic error that can be introduced into a study in a number of ways. * Bias may be introduced: – in the selection of cases or controls (“selection bias”) – in the reporting of exposures or outcomes (e.g., recall bias; and purposeful suppression of data) – in the disproportionate loss to follow-up of exposed or unexposed groups (e.g., attrition) slide 61
34
Ethics in Epi
* Abuses by Dr. Mengele, who conducted medical experiments on concentration camp prisoners during WWII * Tuskegee syphilis experiment * Tonsillectomies * Institutional Review Boards (IRB) – Big improvement over no ethics review – But who do they really protect? The subjects or the institutions? * E.g., male genital cutting (circumcision) RCTs in African countries to prevent HIV infection – Conflicts of interest (pharmaceutical companies may profit from favorable results of clinical trials) slide 62
35
P-value
* The probability that the observed result could have occurred by chance alone – I.e., that there really is no association or no difference – What does “chance alone” mean? – Typical threshold for “statistically significant” is 5%, or p<0.05 * Example: sex balance is really 50-50, but you take a sample and compare %F vs. %M – By chance alone, you might find a difference – p = chance that difference = 0 (i.e., no difference) slide 63
36
Epidemiologic Transitions
1. Rise of infectious disease (urbanization) – e.g., from rural life with death due to old age, to high-density cities with death due to cholera and tuberculosis 2. “Conquest” of infectious disease followed by rise of chronic disease – e.g., from communicable diseases (plague) to “lifestyle” diseases in rich countries (cancer) 3. Chronic disease rejoined by infectious disease – e.g., while chronic disease remains (CVD), old infectious diseases re-emerge (yellow fever, dengue fever, measles) and novel pathogens emerge (SARS-CoV-2) slide 64
37
The “Conquest” of Infectious Diseases
* Public health measures + antibiotics 1940s * Means of transmission * Chain of infection – Pathogen, reservoir, method of transmission, susceptible host * Examples: rabies, smallpox (eradicated), measles (new outbreaks), polio, malaria, dengue fever * Fear of vaccinations * Herd immunity slide 65
38
Chronic Disease Etiology
* Much more difficult to elucidate the “cause” of the following chronic diseases because their etiology is more complex than infectious diseases. – Cardiovascular disease – Cancer – Diabetes slide 66
39
Quantifying the Burden of Disease
Different measures offer varying perspectives: * Morbidity (incidence, prevalence) * Deaths (mortality rate) * Years of life lost (YLL) * Years lived with disability (YLD) * Disability-adjusted life years (DALYs) slide 67
40
What is Culture
* Culture is a concept that helps us learn how groups of people make meaning of the world. – Culture tells us what things mean, but also makes it possible for us to assign meaning to things. * A system that shapes our lived reality by organizing patterns of thoughts, beliefs, behaviors, ideas, and assumptions about the world. – Useful to think of culture as the “operating system” that runs in the background of our lives. – Shapes our ideas and guides our behaviors without us being explicitly aware that these are conditioned phenomena. slide 68
41
Culture
* Culture shapes and is shaped by: – Communication – Orientation to space and time – Social organization – Family structure – Gender roles – Sexual practices – Religion and interaction/membership in faith-based community slide 69
42
Disease v. Illness v. Sickness
* Disease = disordered physiology – pathological changes in the body which have an organic basis, can be observed biologically, and are expressed in various physical signs and symptoms * Illness = an individual’s lived experience – subjective interpretation and response to signs and symptoms * Sickness = disordered social relations – Interruption in relationships between an individual and other people (taking a “sick day” from work; moral aspersions cast when others refer to behavior that is perceived as aberrant/deviant - “they’re sick in the head”) slide 70
43
Medicalization
* “The process by which certain behaviors or conditions are defined as medical problems…, and medical intervention becomes the focus of remedy and social control” (Chang and Christakis 2002) * Medicalization occurs when human problems or experiences become defined as medical problems, usually in terms of illnesses, diseases, or syndromes. * Chang and Christakis examine changing ideas about obesity as they evolved from 1927 to 2000 in a widely-consulted medical school textbook. slide 71
44
Medicalization: Is It More Humanitarian?
* Unlike a moral or legal model, a medical model can reduce stigma and potentially lead to more humanitarian approach. – E.g., obesity – E.g., injection drug use * But is medicalization always better? – Growth of ADHD diagnoses and prescribing of stimulant drugs for millions of children and adults? slide 72
45
Socioeconomic Status (SES)
* SES (or sometimes socioeconomic position) refers to standing in the stratification system and is usually measured by education, occupation, employment, income, and wealth. * SES can reflect diverse underlying theoretical concerns such as material well-being, human capital, prestige, and productive relations. – Although these components are not interchangeable, SES is useful as a summary term what a particular measure does not have key importance. slide 73
46
RACE
* Based on biological differences (phenotypes) – “Race is the child of racism not the father” Ta-Nehisi Coates * But race is a social construct * The “One Drop” rule in the U.S. * Compare to how race has been viewed in Brazil
47
Ethnicity
* Ethnic categories: – A cultural marker or a place of origin with a shared cultural experience – Sense of community – Useful to think of as a sub-category of race, yet ethnicity can transcend more than one racial category * E.g. “Afro-Brazilian” and “African American” – OR * E.g. “Black Hispanic” and “White Hispanic" slide 75
48
RACISM & SEGREGATION
* Encompasses institutional and individual discrimination, racial prejudice and stereotypes, and internalized racism * Separated neighborhoods based on the grouping of racial or ethnic groups * Why does segregation have an impact on health? slide 76
49
WHAT IS SEX? WHAT IS GENDER?
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50
GENDER
* Refers to roles, behaviors, activities, and attributes that a society considers appropriate for men and women – Does not always imply a binary – “Third” categories (e.g., transgender, non-binary, two-spirit) * Is socially constructed: What is considered appropriate varies by society, culture, and place in history (it changes over time) * “Cisgender,” a term that recently entered the popular lexicon, refers to identifying or experiencing a gender that is the same as the sex assigned at one’s birth. slide 78
51
Why the paradox of men’s higher mortality and lower morbidity?
* Gender gap in longevity in the United States has been closing since 1980. Why? * Men’s rapid decline in smoking and decreasing mortality from cardiovascular disease (CVD) and cancer * Women’s risk for CVD increases after menopause * Men have more life-threatening chronic diseases at younger ages (CHD, cancer, cerebrovascular disease, emphysema, liver cirrhosis, kidney disease, and atherosclerosis) * Women have more chronic debilitating disorders (autoimmune diseases and rheumatologic disorders) and less life-threatening diseases (anemia, thyroid conditions, gallbladder conditions, migraines, arthritis, and eczema) slide 79