Epi Quiz 1 Notes PDF

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KINS 4300-Epidemiology Notes Module 1 Notes 

PPT 1: Intro to Exercise Epidemiology o Exercise for health is not a new idea  Traced back to 9th century BC – recommended as treatment for rheumatism  Hippocrates & Aristotle agreed  “man falls into ill health as a result of not caring for exercise” -Aristotle o History  Renewed interest in exercise during Renaissance  Greek writings of benefits of exercise were translated from Arabic  1569-Hieronymus Mercurialis wrote “The Art of Gymnastics” – urged all sedentary people to exercise  Laid foundation for rehab medicine by recommending that convalescents & older people do special exercises based on their disease  1770s-Benjamin Russ (Father of American Psychiatry) – delivered “Sermons to Gentlemen upon Temperance and Exercise”  Proposed a federal university that included exercise & sport to improve & strength o Human Longevity  James Easton – 1st person to use empirical methods to study relationship between exercise & health  Concluded exercise was a key influence upon one’s lifespan o “It is not the rich nor the great, not those who depend on medicine, who became old, but such as use much exercise” -Easton 1799 o Concluded based on exam of historical records of over 1700 people who reached 100 years of age o Coronary Heart Disease Hypothesis  1950s- modern science began to examine potential effects of physical activity on health  One of the 1st studies: London Bus Driver Study  Conducted by Jeremy Morris – 1953 o After this study - Morris considered the father of Physical Activity Epidemiology  Compared heart attack rates among relatively inactive bus drivers with the more active bus conductors (who spent day going up & down aisles/stairs/punching tickets)  Found that drivers experienced about twice as many heart attacks as conductors

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o True regardless of age o Physical Activity Epidemiology = the study of the relation between physical activity & health using epidemiologic methods  Sub-discipline of epidemiology PPT 2: Epidemiology Definition o Epidemiology = study of distribution & determinants of health-related states or events in specialized populations and the application of this study to the control of health problems  Word Parts:  “epi” = upon, among  “-demos” = the populace, people  “-ology” = study of  Key Terms in Epi Definition:  Study o Basic science of public health o Quantitative o Based on principles of statistics & research methodologies  Distribution o Study the distribution of frequencies & patterns of health events o Try to answer “who”, “what”, “where”, “when”  Who = age, sex, ethnic, socioeconomic variations in disease occurrence  Where = geographic variation in diseases  Such as urban/rural different or climate differences  When = trends & diseases occurrence over time may be looked at  Determinants = causes or factors association with risk of disease o Trying to answer “how” & why” o Disease is not randomly distributed across the population  Instead, each of us have special characteristics/histories that predispose us to/protect us against different diseases  Health-related States o Early epidemiology focused on infectious disease o Modern epidemiology is concerned with whole spectrum of health events  Ex:  chronic disease such as diabetes  environmental problems such as lead poisoning  behavioral problems such as autism

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injuries such as concussions

Populations o reflects epidemiology’s focus on community o epidemiology deals with groups of people  looks at risks in populations  focuses on public health!!  does not focus on individuals!!  Which is the focus of clinical medicine  Control o Key goal: apply knowledge gained from epidemiologic studies to control & prevent health problems o Data steers/influences public health decision making  Ex: choosing to open schools based on regional prevalence of COVID  Like PA guidelines o Development/evaluation of interventions o Objectives of Epidemiology  Descriptive Epidemiology = comprehensive overview of health of a given population  makes use of available data to examine: o Morbidity = Prevalence & incidence of disease o Mortality = incidence of death o Economic cost o Indicators of healthy living (quality, not just quantity)  Examines trends & different diseases/health events over time  Guides prevention efforts & allocation of scarce health resources  Ex: o Chart of U.S. Heart Attack Deaths in 1991  Increased with age  Higher in men than women  Info shows burden of disease overall & in different sub-groups  Can help generate hypothesis related to causes of disease  Ex: slide suggests sex hormones (estrogen) plays a role in heart attacks o Cardiovascular deaths decreased from 1982-1993 while cancer deaths increased slightly over same time period  Info is useful for monitoring effectiveness of disease prevention programs & identifying growing public health concerns o Geographic difference in prevalence of multiple sclerosis in Australia 

Analytic Epidemiology = searches for causal factors of underlying diseases/health events  Aka etiologic research  Ex of Analytic Epi Research Finding Links between: o Smoking & lung cancer o Cholesterol & CVD o Inactivity & diabetes  Relative risk between “exposed” & “unexposed” groups used to measure strength of associations o Exposed = those with potential risk factor o Unexposed = Those without potential risk factor o Relative Risk (RR) = risk of a disease/health outcome  RR = (Risk in exposed group) / (Risk in unexposed group)  If RR = 1  risk in exposed = risk in non-exposed  no association  If RR > 1  risk in exposed greater than risk in non-exposed  positive association  If RR < 1  risk in exposed less than risk in non-exposed  negative association  Ex: Smokers vs. Non-smokers  Over 10 years, 100/1000 (10%) smokers develop lung cancer & 10/1000 (1%) non-smokers develop lung cancer o RR = (risk in smokers) / (risk in non-smokers) = 10% / 1% = 10 o Interpretation: the 10-year risk of developing lung cancer among smokers is 10 times greater than the risk among non-smokers PPT 3: Epidemiological Thinking & Causal Theory o Epidemiologist’s Goal = to answer the question: Does __ (an exposure) cause ____ (an outcome) ?  Ex:  Does low sun exposure cause multiple sclerosis? o Must be clear  Does inactivity in childhood cause adult obesity?  Does smoking high tar cigarettes cause poor lung function? o Does smoking high tar cigarettes cause poorer lung function compared to low tar cigarette smokers? o Cause = an exposure or characteristic whose presence has led to one or more individuals developing this disease  General definition: That which produces an effect or brings about a change  If you do x, y always happens  But in disease, it is not like that ^  Smoking causes lung cancer yet only 10% get it 

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o We still say smoking causes cancer though  Smoking is not enough on its own to cause lung cancer so there must be other factors that have to be present/certain conditions met for a smoker to develop lung cancer  Theoretically only 1 person needs to get outcome in order for it to be a cause  Non-smokers develop cancer by having a different risk factor for cancer  Multiple factors result in cancer o Theory of Causal Mechanisms = all pieces of pie must be present for disease to occur through this mechanism  by definition, disease begins when last mechanism has acted  if any piece of the pie can be prevented, the disease cannot occur through that mechanism  can stop disease from happening!  Single component cause = 1 piece of pie  Necessary Component Cause = it has to be present in order for disease to occur  Ex: A in slide 8  Ex: Covid pneumonia: must have Covid exposure to get it, AIDSmust have HIV  Sufficient Component Cause = something causes disease by itself  Would be 1 pie with 1 slice

o Implications of Causal Model  Strength of Causes - common to think that some component causes play a more important role than others  Ex: smoking & lung cancer -RR ~10% but smoking and MI (heart attack) – RR ~2%  For individual cases, no such thing as strong/weak cause  Can define a “strong cause” to be a component causes that plays a causal role in large proportion of cases  Defined this way, strength depends on the prevalence of other causal factors that produce the disease & Is not a universally accurate description of any cause o Ex: smoking & Radon Gas causing lung cancer

If we get rid of smoking, radon gas prevalence of causing cancer will probably go up  Radon gas now causing a greater proportion of lung cancer Interaction Between Causes – model posits that several causal components act in concert to produce an effect (not necessarily at same time)  Provides biological basis for concept of interaction: o Effect of 1 factor is dependent on presence of another  Ex: exposure to H1N1 & immune status, exposure to UV light & skin tone 

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In-Class Exercise: Yellow Shank disease in chickens occur only in susceptible strains fed yellow corn. o What would a farmer think if you added yellow corn to the diet of a susceptible flock?  He would think feeding it yellow corn = gives yellow shank disease environmental o What would a farmer think if you added susceptible chickens to a flock fed yellow corn?  Something wrong with the chickens – all genetic Book: Chapter 1: Origins of Physical Activity Epidemiology o Ancient History of Physical Activity & Health  2080 BC – Code of Hammurabi had laws about health practices & physicians  Modern day preventive medicine & public health traced to India & Greece  Hippocrates = 1st epidemiologist  Kept records of associations between disease & climate, living conditions, & habits such as diet & exercise  Distinguished endemic diseases that differ in prevalence between places from epidemic diseases that vary in prevalence across time  Wrote that food & exercise work together to produce health & that exercise should be often & varied  1984-Allen Ryan – wrote one of 1st modern accounts of history of physical health activity  Concluded that the concept of health is older than knowledge about the causes of disease  Uses of exercise are: o 1. For evacuation of excrements o 2. Production of good condition of firm parts of the body th  9 century BC - Exercise as medicine – physical activity & exercise used as protection & rehab of health

Ayurveda recommended exercise & massage for treatment of rheumatism  480 BC-Herodicus – specialized in therapeutic gymnastics  Based therapies on vigorous exercise  Renaissance – Italy scholars renewed interest in classical Greek gymnastics  Mercurialis replaced passive exercise with vigorous exercise involving heavy breathing & physical effort  Mountain climbing, 3 types of walking, running, jumping, rope climbing, wrestling, ball games – to strengthen upper body o Modern History of Physical Activity & Health  Roots in Dr. Jeremy Morris – established epidemiologic method for collection, analysis, & interpretation of data on causes of chronic disease  Coronary Heart Disease made Dr. Morris make association between physical activity & physical fitness with reduced risk of chronic diseases  Framingham Heart Study – 1948 – data linked physical activity with reduced risk of heart disease  Soon after, discovered cigarette smoking, cholesterol, & high blood pressure = risk factors for heart disease  Tecumseh Community Health Study – 1940 – study entire community to make comprehensive summary of relationship among physical activity, fitness, & health risk factors discovered in study  Longshoremen & College Alumni Studies – helped fuel scientific & public interest in physical activity as an important component of health promotion & focused on broader fields of preventive medicine & public health on physical activity as a significant public health problem  Aerobics Center Longitudinal Study – examined impact that diet, physical activity, and other lifestyle factors have on mortality & chronic disease risk  Unique features: strength testing & treadmill tests of aerobic power  US Nurses’ Health & Health Professional Studies – longest running cohort study of women  Studies association between use or oral contraceptives & cigarette smoking & risk of chronic diseases in married registered nurses o Contemporary Physical Activity Epidemiology  AHA – 1992 – physical inactivity = independent risk factor for coronary heart disease & recommend on physical activity & public health prepared Supplement-Causation & Causal Inference in Epidemiology o Cause = antecedent event, condition, or characteristic that was necessary for occurrence of the disease at the moment it occurred, given that conditions are fixed 

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o Multicausality – a given disease can be caused by more than one casual mechanism, and every casual mechanism involves the joint action of a multitude of component causes  Most identified causes are neither necessary nor sufficient to produce disease  A cause not necessary or sufficient to for its removal to result in disease prevention  Substantial amount of disease prevented though  Over time, strength of the effect of a given factor on occurrence of a given disease may change because prevalence of its causal complements in various causal mechanisms may also change o Interaction among Causes  Several causal components act in concert to produce an effect  Don’t have to act at same time though  Any & all factors in the same causal mechanism for disease interact with one another to cause disease o Environment = nongenetic causes  100% of any disease is environmentally caused but also can be 100% inherited  Every disease has both environmental & some genetic component causes – every case can be attributed both to genes & environment  Fractions of disease attributable to genes & to environment overlap o Causal Inferences  Even the most careful & detailed mechanistic dissection of individual events cannot provide more than associations  Lab studies involve observer control that cannot be approached in epi  Only this control (not level of observation) can strengthen inferences from lab studies  Control is still not guarantee against error  Vague hypothesis have vague consequences that can be difficult to test  To cope – epidemiologists focus on testing the negation of the causal hypothesis = null hypotheses that the exposure does not have a causal relation to disease o No causal connection between study exposure & disease o Causal criteria  How epidemiologists separate out causal from noncausal explanations – inductively oriented causal criteria commonly used to make inferences  Hill’s Criteria – suggested 9 aspects of association must be considered in attempting to distinguish causal from noncausal association: o Strength – strong associations are more likely to be causal than weak associations because if they can be explained by

another factor, the effect of that factor would have to be even stronger than observed association & would have become evident  Weak associations explained by undetected biases  Once cofactor is identified, association is diminished by adjustment for the factor  Strong association is not necessary or sufficient for absence of causality  Strong association only serves to rule out hypotheses that association is entirely due to 1 weak unmeasured confounder/source of modest bias o Consistency = repeated observation of an association in different populations under different circumstances  Lack of consistency does not rule out causal association  Some effects are produced by their causes only under unusual circumstances  Effect of a causal agent cannot occur unless the complementary component causes act to complete a sufficient cause  Serves to rule out hypotheses that association is attributable to some factor that varies across studies o Specificity – a cause leads to a single effect, not multiple effects  Argument used to refute casual interpretation of exposures that appear to relate to myriad effects  Invalid generally o Because causes of an effect cannot be expected to lack all other effects  Existence of 1 effect of an exposure does not detract from the possibility that another effect exists  Can be used to distinguish some causal hypotheses from noncausal hypotheses when the causal hypothesis predicts a relation with 1 outcome but no relation with another o Temporality = necessity for a cause to precede an effect in time  Causation must involve the putative cause “x” preceding the putative effect “y”

If “x” followed “y” , “x” could not have caused “y” Biological gradient = presence of a unidirectional doseresponse curve  Single jump or monotonic trend – j shaped  Associations that show a monotonic trend in disease frequency with increasing levels of exposure are not necessarily causal  Con-founding can result in monotonic relation between a noncausal risk factor & disease if confounding factor demonstrates a biological gradient in its relation with disease  Existence of monotonic association is neither necessary not sufficient for a causal relation – it only refutes causal hypotheses specific enough to predict a monotonic dose-response curve Plausibility  Problem with plausibility: too often not based on logic or data, but only on prior beliefs  Approach to deal with problem: require that 1 quantify on a probability (0-1) scale the certainty that one has in prior beliefs & new hypotheses  Provides means of testing those quantified beliefs against new evidence  But plausibility still not transformed into an objective causal criterion Coherence – implies that a cause & effect interpretation for an association does not conflict with what is known of natural history & biology of the disease  Absence of coherent information from presence of conflicting information should not be taken as evidence against an association being considered causal  Presence of conflicting info may refute a hypotheseis but one must always remember that the conflicting info may be mistaken/misinterpreted Experimental Evidence  Human evidence seldom available for most epi research questions 

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Hill’s evidence - Result of removal of some harmful exposure in an intervention or prevention program instead of results of lab experiments  Lack of availability of evidence would be a pragmatic difficulty in making criterion for inference  Experimental evidence is not criterion but a test of causal hypothesis – usually unavailable  Experimental tests stronger but not as decisive as thought because difficulties in interpretation o Analogy – provides a source of more elaborate hypotheses about associations under study  Absence reflects lack of imagination or experience, not falsity of hypothesis o Criteria to Judge Validity of Scientific Evidence  Causal criteria cannot be used to establish validity of an inference  No criteria can be used to establish validity of data or evidence  Scientific evidence – form of measurement  Sources of error  No absolute criteria for assessing validity of scientific evidence but still possible to assess validity of the study  Required:  List of criteria  Apply thorough criticism – with goal of obtaining a quantified evaluation of total error that afflicts the study ...