epi1 - Epidemiology I Epidemiology I What is epidemiology...

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Unformatted text preview: Epidemiology I Epidemiology I What is epidemiology? What common measures are used in the field of epidemiology? What are the subject areas studied by epidemiologists? How has epidemiology evolved over time? What is the current focus of epidemiology? What are the health challenges of modern medicine (and focus of epidemiology)? Definition of Epidemiology Definition of Epidemiology Study of the distribution and determinants of diseases and injuries in human populations Concerned with frequencies and types of injuries and illness in groups of people Focus is not on the individual Concerned with factors that influence the distribution of illness and injuries Background Background Relatively new science – emerged in 19th century In strictest terms – study of epidemics Today: Concerned with epidemic disease and all other forms of illness and bodily injury Cancer, heart disease HIV/AIDS Alcoholism, drug addiction Suicide Automobile accidents … Relationship Between Clinical Relationship Between Clinical Medicine and Epidemiology Focus in medicine is the individual patient Community replaces the individual patient in epidemiology Fundamental Assumptions in Fundamental Assumptions in Epidemiology Disease doesn’t occur at random Disease has causal and preventive factors ∗ Disease is not randomly distributed throughout a population Epidemiology uses systematic approach to study the differences in disease distribution in subgroups Allows for study of causal and preventive factors Components of Epidemiology Components of Epidemiology Measure of disease frequency Quantification of existence or occurrence of disease Distribution of disease ­ three questions Who is getting disease? Where is disease occurring? When is disease occurring? Formulation of hypotheses concerning causal and preventive factors Determinants of disease Hypothesis are tested using epidemiologic studies Progression of Epidemiologic Progression of Epidemiologic Reasoning 1. Suspicion that a factor may influence occurrence of disease ­ Observations in clinical practice ­ ­ Examination of disease patterns ­ ­ ­ ­ Are HC providers seeing unexpected illness patterns in their patients? Do subpopulations have higher or lower rates? Are disease rates increased in the presence of certain factors? Observations in laboratory research Theoretical speculation ­ What theories can be generated from existing knowledge of disease prevention and causation models? Progression of Epidemiologic Progression of Epidemiologic Reasoning (Cont.) 2. Formulation of specific hypotheses ­ Based on suspicions concerning influence of a particular factor on disease occurrence 3. Conduct study ­ Hypotheses are tested to determine if statistical associations between factors and disease occurrence exist ­ Study population is assembled from individuals with disease or outcome of interest and an appropriate comparison group ­ Data is collected and analyzed Progression of Epidemiologic Progression of Epidemiologic Reasoning (Cont.) 4. Assess validity of association ­ Does the observed association really exist? ­ ­ Is the association valid? Are there alternative explanations for the association? ­ ­ ­ Chance Bias Confounding Progression of Epidemiologic Progression of Epidemiologic Reasoning (Cont.) 5. Make a judgement of whether a cause­ effect relation between factor (exposure) exists ­ ­ ­ ­ What is the magnitude of the association? Are the findings consistent with previous studies (or conflicting)? Are the findings biologically credible? Can underlying biological mechanisms that support the association be identified? Historical Perspective Historical Perspective Hippocrates ­ 5th century Association between external environment and personal characteristics and health “Whoever wishes to investigate medicine properly should proceed thus: in the first place consider the seasons of the year, and what effects each of them produces. Then the winds, the hot and the cold, especially such are as common to all countries, and then such as are peculiar to each locality. In the same manner, when one comes into a city to which he is a stranger, he should consider its situation, how it lies as to the winds and the rising of the sun; for it influence is not the same whether it lies to the north or the south, to the rising or to the setting sun. One should consider most attentively the waters which the inhabitants use, whether they be marshy and soft, or hard and running form elevated and rocky situations, and then if saltish and unfit for cooking; and the ground, whether it be naked and deficient in water, or wooded and well watered, and whether it lies in a hallow, confined situation, or is elevated and cold; and the mode in which the inhabitants live, and what are their pursuits, whether they are fond of drinking and eating to excess, and given to indolence, or are fond of exercise and labor.” (Hippocrates, “On airs, waters and places” Medical Classics 3:19, 1938). Historical Perspective Historical Perspective John Graunt – 1662 (Hennekins and Buring 1987) The Nature and Political Observations Made Upon the Bills of Mortality Systematic statistical approach Analyzed births and deaths in London Excess of males born, higher mortality for males Infant mortality is very high Seasonal variation for mortality Importance of routinely collected information for study of human illness William Farr ­ 1839 Examined mortality and occupation and marital status Identified important issues in epidemiological investigations Use of comparison population, influence of multiple factors on disease Historical Perspective Historical Perspective John Snow (1854) – Father of modern epidemiology Established modern epidemiologic methods Cholera epidemic in London Plotted geographical location of all cases – deaths from cholera From The Visual Display of Quantitative Data , Edward R. Tufte John Snow (cont) John Snow (cont) Went door to door, collecting information on daily habits Suspected water supply as source of epidemic Broad street pump closed, epidemic stopped Mode of investigation – “shoe leather” Practical application of epidemiology – use epidemiological investigation to impact a health problem How the Epidemiologist Works How the Epidemiologist Works Studies origin and distribution of a health problem Collection of data Constructs a logical chain of inferences to explain the various factors in a society or segment of society that cause a health problem to exist Likened to a detective investigating the scene of a crime looking for clues Starts with examination of sick person(s) Extends investigation to the setting where illness is occurring Looks for common denominator that links all the affected so that the cause of the problem can be eliminated or controlled Epidemiologic Analyses – Areas of Epidemiologic Analyses – Areas of Study Causal agents related to disease: 1. 2. 3. 4. 5. Biological agents – bacteria, viruses, insects Nutritional agents – diet (fats, carbohydrates, food nutrients) Chemical agents – gases, toxic agents Physical agents – climate, vegetation, chemical pollutants (air, water, food) Social agents – occupation, stress, social class, lifestyle, location of residence Epidemiologist studies: Epidemiologist studies: Host characteristics: Biological factors Age, sex, degree of immunity, other physical attributes that promote resistance or susceptibility Behavioral factors Habits, culture, lifestyle Social environment Living conditions such as poverty, crowding Norms, values and attitudes Socially prescribed standards of living Use of food and water, food handling practices Household and personal hygiene Eras of Epidemiology Eras of Epidemiology 1. 2. 3. 4. Sanitary era – early 19th century Infectious disease era – between late 19th century and early 20th century Chronic disease era – 2nd half of 20th century Eco­epidemiology era – 21st century Definitions Case Case Episode of disorder, illness, or injury affecting an individual Case of measles Cancer case TB case Food poisoning event Various sources provide case information Interviews or surveys Medical providers Institutions or agencies Incidence Incidence Measure of new cases of disease (or other events of interest) that develop in a population during a specified period of time E.g. Annual incidence, five­year incidence Measure of the probability that unaffected persons will develop the disease Used when examining an outbreak of a health problem Prevalence Prevalence Number of existing cases of disease or other condition Proportion of individuals in a population with disease or condition at a specific point of time Diabetes prevalence, smoking prevalence Provides estimate of the probability or risk that one will be affected at a point in time Provides an idea of how severe a problem may be – measures overall extent Useful for planning health services (facilities, staff) Epidemic, Endemic and Pandemic Epidemic, Endemic and Pandemic Epidemic Endemic Any significant increase in the number of persons affected by a disease The first occurrence of a new disease A disease that is established within a population that remain at a fairly stable prevalence Pandemic Widespread, universal disease penetration over a wide geographic area More Terms More Terms Morbidity – illnesses, symptoms, impairments Mortality ­ deaths Acute disease – diseases that strike and disappear quickly, within a month or so (chicken pox, colds) Chronic disease – long term or lifelong diseases, incurable More Terms More Terms Birth cohort Persons born in a given year Life expectancy (LE) Average number of years of life remaining to a person at a particular age Based on mortality rates and personal characteristics (e.g. gender, race) Years of potential life lost (YPLL) Measure of premature mortality Death before age 75 Epidemiologic Measures Ratio Ratio Used to compare two quantities 1:1.1 ratio of female to male births Used to show quantity of disease in a population cases population Proportion Proportion A specific type of ratio in which the numerator is included in the denominator, usually presented as a percentage Calculation of proportion: Males undergoing bypass surgery at Hospital A Total patients undergoing bypass surgery at Hospital A 352 males undergoing bypass surgery = 539 total patients undergoing bypass surgery 65.3% Rate Rate Special form of proportion that includes a specification of time Most commonly used in epidemiology because it most clearly expresses probability or risk of disease or other events in a defined population over a specified period of time 3 major types Crude rates Specific rates (age­specific, infant mortality) Adjusted rates Crude rates Crude rates Unadjusted, simple ratios cases in defined period of time population in defined period of time x K (k denotes units 100’s, 1,000, etc.) Crude mortality rate: Total deaths in 2003 x 1,000 = U.S. death rate Estimated U.S. pop in 2003 Calculation of rates: Number of events in a specified time period Xk Population at risk of these events in a specified time period k is used to denote the units of population such as per 1,000 or per 100,000 9,981 deaths in Detroit in 2000 951,270 total population in Detroit 2000 = 10.49 per 1,000 1049 per 100,000 Detroit Population Detroit Population N=951,270 in 2000 9981 deaths 15,892 births 7,181 to single “named” parent Is Detroit population declining, stable or increasing? Specific Rates Specific Rates Capture effects of specific variables or social characteristics Age­specific, gender­specific, gender and race­ specific Example – infant mortality – deaths within the 1st year of life Total # of deaths in 2003 among persons age less than 1 year x 1,000 = 2003 infant Number of live births during 2003 mortality rate Adjusted or Standardized Rates Adjusted or Standardized Rates Allow for comparison of populations with different characteristics Statistically constructed summary rates allow for appropriate comparisons by taking into account differences in populations (age, gender, etc.) Example of use: Population in Arizona is much older than population in Alaska, so it would be inappropriate to compare mortality rates. Standardization allows for meaningful comparisons. Calculating prevalence: Number of existing cases of disease P= at a given point in time Total population at risk P= 2176 DNW pts with asthma encounter = .07 31005 DNW pts = 7 asthmatics per 100 pts =7% Prevalence calculation exercise: Pediatric Asthma at DNW Number of existing cases of disease P= at a given point in time Total population at risk P= = 2159 DNW pts < 19 with asthma encounter = 9173 DNW pts < 19 Types of Prevalence Types of Prevalence Point prevalence: number of cases that exist at a given point in time Lifetime prevalence: proportion of the population that has a history of a given disorder at some point in time Period prevalence: number of cases that exist in a population during a specified period of time Cumulative Incidence Cumulative Incidence The proportion of individuals who become diseased during a specified time period. Time period can be a calendar year, 6 months, 3 years, 5 years, etc. Formula for cumulative incidence: Number of new cases of disease during a given time period CI = Total population at risk 70 new cases of breast cancer in a 5 year period CI = 3,000 women at risk = 0.023 = 23 cases per 1,000 women during 5 years Incidence Rate Incidence Rate Also known as incidence density Measure of incidence that is able to handle varying observation periods Denominator is sum of person­time at risk Formula for incidence rate or incidence density: Number of new cases of disease during a given time period ID = Total person-time at risk 70 new cases of breast cancer ID = 13,000 women-years of observation = 0.0054 = 5.4 cases / 1,000 women years Relationship Between Incidence Relationship Between Incidence and Prevalence Prevalence varies directly with both incidence and duration. If incidence is low, but duration is long (chronic), prevalence will be large in relation to incidence. If prevalence is low because of short duration (due to recovery, migration or death), prevalence will be small in relation to incidence. Special Types of Incidence Special Types of Incidence Rates Morbidity rate ­ number of nonfatal cases in Morbidity rate ­ number of nonfatal cases in the population at risk during a specified period of time Mortality rate ­ number of deaths in a population at risk during a specified period of time Cause­specific mortality ­ death from a specific cause Case fatality rate ­ number of deaths from a disease divided by all case of the disease Attack rate ­ cumulative incidence expressing the risk of disease among a population observed for a specified period of time Special types of incidence and Special types of incidence and prevalence measures Rate Type Numerator Denominator Morbidity rate Incidence New cases of nonfatal disease Total population at risk Mortality rate Incidence Number of deaths from Total population a disease or all causes Case­fatality rate Incidence Number of deaths from Number of cases of a disease that disease Attack rate Incidence Number of cases of a disease Disease rate at autopsy Prevalence Number of cases of a disease Birth defect rate Prevalence Number of babies with a given abnormality Total population at risk, for a limited period of observation Number of persons autopsied Number of live births Measures of Association Measures of Association Calculations used to measure disease frequency relative to other factors Indications of how more or less likely one is to develop disease as compared to another Two by Two Tables Two by Two Tables Used to summarize frequencies of disease and exposure and used for calculation of association. Disease Yes Exposure No Total Yes a b a + b No c d c + d a + c b + d a + b + c + d Total Two by Two Tables: Contents of Cells Two by Two Tables: Contents of Cells a = number of individuals who are exposed and have the disease b = number who are exposed and do not have the disease c = number who are not exposed and have the disease d = number who are both non­exposed and non­diseased *************************************************** a + b = the total number of individuals exposed c + d = the total number of unexposed a + c = the total number with the disease b + d = the total number without the disease a + b + c + d = sum of all four cells and the total sample size for the study Relative Risk Relative Risk Measure of association between incidence of disease and factor being investigated Ratio of incidence rate for persons exposed to incidence rate for those not exposed Incidence rate among exposed RR = Incidence rate among unexposed Estimate of magnitude of association between exposure and disease Formula for relative risk: Incidence rate among exposed RR = Incidence rate among unexposed a / (a + b) RR = c / (c+ d) •Risk ratio If RR calculated from cumulative incidence •Rate ratio If RR calculated from incidence rate (person units of time) RISK RATIO: Example RISK RATIO: Example Breast No Breast Cancer Cancer Total Alcohol 70 2,930 3,000 No alcohol 50 2,950 3,000 RR using Cumulative Incidence (CI): a/(a + b) 70 / 3,000 = = c/(c + d) 50 / 3,000 = 1.4 Interpretation of Relative Risk Interpretation of Relative Risk 1 = No association between exposure and disease Incidence rates are identical between groups > 1 = Positive association < 1 = Negative association or protective effect Example: .5 = half as likely to experience disease Odds Ratio Odds Ratio Breast No Breast Cancer Cancer Alcohol 70 100 No alcohol 50 140 a x d (70) (140) = OR = = 2.0 b x c (50) (100) * Used for case control studies because persons are selected based on disease status so you can’t calculate risk of getting disease Difference Measures Difference Measures Attributable risk # of cases among the exposed that could be eliminated if the exposure were removed = Incidence in exposed ­ Incidence in unexposed Population attributable risk percent = Proportion of disease in the study population that could be eliminated if exposure were removed Incidence in total population ­ Incidence in unexposed incidence in total population Impact of Modernization on Impact of Modernization on Health Infant mortality decreased Life expectancy greatly increased during 20 th century Males Females Increased from 48 to 74 years Increased from 51 to 79 years Persons living longer with multiple illnesses Chronic and degenerative diseases Illness with social causes requiring social solutions Changing Mortality Patterns Changing Mortality Patterns 1900 Pneumonia/Influenza Tuberculosis Heart disease Stroke Diarrhea/enteritis Nephritis Cancer Accidents Diphtheria 1990s Heart disease Cancer Stroke Chronic lung disease Unintentional injuries Pneumonia/influenza Diabetes mellitus HIV/AIDS Suicide U. S. Life Expectancy U. S. Life Expectancy Remaining life expectancy in years Males Females 1900 – at birth 46.3 48.7 1950 – at birth 1950 – at age 65 65.6 12.8 71.1 15.8 1999 – at birth 1999 – at age 65 1999 – at age 75 73.9 16.1 10.0 79.4 19.1 12.1 Health, United States, 2002 U.S. Infant Mortality Rate U.S. Infant Mortality Rate Deaths per 1,000 infants Significance: Measure of society’s sanitary and medical standards Health care Diet Living conditions 180 160 162 140 120 100 80 60 47 40 29.2 27 12.6 20 6.9 0 1900 1940 1950 1960 1980 2000 Factors Influencing Changing Factors Influencing Changing Pattern Improvements due to industrialization Nutrition Environmental Sanitation Water supply Housing Medical advancements Antibiotics Immunization Disease surveillance programs Factors Influencing Changing Factors Influencing Changing Patterns Problems associated with industrialization Environmental pollutants Increase in smoking Excess consumption of calories and dietary fats Lack of exercise, physical activity Stress Alcohol, drug use Challenges of Modern Medicine Challenges of Modern Medicine Behavioral aspects of health Promotion of healthy lifestyles Diet Exercise Tobacco, alcohol, drugs Sexual behavior Management of stress New diseases – AIDS, SARS, West Nile Virus, bioterrorism ...
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