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Basic Concepts in Epidemiology

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Basic Concepts in Epidemiology Basic concepts in Epidemiology An introduction to principles of epidemiology for psychiatric trainees Updated 2012 Module 1 Descriptive Epidemiology Introduction to epidemiology Descriptive studies Association and causation Measures of frequency • Prevalence • Incidence Case definition Standardisation What is epidemiology? study of the distribution, frequency and determinants of disease in human populations a basic science which is the foundation of all population based research disciplines • health economics, health service research, clinical research Characteristics of epidemiology Concerned with populations, not individuals Comparative Quantifiable – numeric, statistics Human populations a group of persons sharing one or more variables in common variable could be age, sex, location, disease, exposure ….. or any combination Aims of epidemiology describe disease in populations determine aetiology of disease describe natural history of disease predict outcomes identify preventative measures assist health service planning Epidemiology and clinicians roots are in non-clinical sciences may not be direct relevance to clinician or patient may point to socio-political interventions rather than clinical/medical interventions clinical epidemiology Clinical epidemiology the application by a physician who provides direct patient care of epidemiological and biometric methods to the study of the diagnostic and therapeutic processes. [It does not] constitute a distinct or isolated discipline but reflects an orientation arising from both clinical medicine & epidemiology (Sackett 1969) Epidemiological studies distribution and frequency • descriptive, prevalence, cross sectional studies • correlational studies determinants • case-control • cohort interventions • experimental Descriptive studies also called prevalence or cross sectional study disease status and exposure status ascertained at the same point uses survey techniques to examine populations cannot determine causal relationships useful for formulating hypothesis Correlational studies compare entire populations comparison between different places at same time - - or same place at different times useful to form hypotheses for further testing Discussion point Association In Denmark there is a correlation between the number of children born in a local area and the number of storks in that area Do storks really deliver children to the Danish? Storks and birth rates in 17 European countries Association and causality Assessing association Bradford Hill criteria • consistency • strength • specificity • dose-response relationship • temporality • biological plausibility • coherence • experimental evidence Measures of frequency Measuring disease frequency crude count rates • prevalence • incidence role of standardisation Measures of frequency What is a rate? allows comparisons between populations of different sizes and/or at different times comprises two components - • the number of events, or numerator • the number of people, or denominator Strictly speaking a rate expresses a time interval e.g per year Measures of frequency Calculating a rate no. of events in population (numerator) rate = no. of people in population (denominator) numerator and denominator must refer to the same population either numerator or denominator may not be available numerator and denominator must be comparable across all populations Measures of frequency Prevalence a measure of the occurrence of all cases of disease in a population existing cases of disease in population prevalence = number of people in population case definition ascertainment (registers, surveys) point v period v lifetime prevalence suitable for chronic disease Discussion point Case definition How would you define a case of dementia? How would you define a case of schizophrenia? Case definition Most diseases exist as continua rather than discrete phenomena Comparisons require consistent definitions of caseness Particular problem for psychiatry Also consistency in social and environmental variables e.g. smoking rates, social class Case definition state or categorical • dichotomous variables - ill or not ill • ICD 10, DSM IV trait or dimensional • continuous variables - degrees of illness • MMSE, GHQ • often cut-offs used to convert to state Case ascertainment structured interviews • used to collect standardised data • PSE, SADS, DIS, CIS-R, GMS diagnostic rules • used to establish consistent diagnoses • CATEGO, RDC, AGECAT International classifications • ICD10, DSMIVR Measures of frequency Types of prevalence Point prevalence • The proportion of the population with a disease at any specific point in time Period prevalence • The proportion of the population with a disease at any point during a defined period Lifetime prevalence • The proportion of the population who have, or have had, a disease during their lifetime • Better measure for chronic, relapsing conditions Measures of frequency Incidence measures frequency of new cases of disease in a population over time new cases of disease over time period incidence = number of people at risk case definition ascertainment (registries, surveys) “at risk” suitable for acute disease Relationship between incidence & prevalence for a disease at a steady state in a population prevalence incidence duration Discussion point Prevalence and incidence Year 1 2 3 Special types of incidence & prevalence prevalence • congenital malformation rates • smoking amongst teenagers incidence • teenage conceptions • hospital admission rates • mortality rates Endemic and epidemic Conditions which exist at usually low levels over time are said to be endemic Periodically peaks of incidence occur – often seasonally – forming epidemics Occasionally very high peaks occur – associated with rapid spread – forming pandemics Measures of mortality mortality rates often used as proxy for disease occurrence routinely counted and readily available poor proxy for diseases with great morbidity but little mortality • chronic diseases • infectious diseases Crude and age specific rates age specific rates may reveal diversity lost in calculating total death rates age specific rates are used in calculating age standardised death rates total number of deaths crude death rate = size of population number of deaths in age range age specific death rate = size of population in age range Standardisation Age standardisation crude rates allow comparisons between populations of different sizes populations also differ in age and sex structure age (sex) standardisation modifies crude rates to account for these differences SMRs and ASDRs Standardisation Direct standardisation age/sex-specific rates from the index population(s) are applied to the age/sex structure of a standard population the weighted average represents the rate which would have occurred in the index population(s) if they had the age/sex structure of the standard population the age standardised death rate ASDR Standardisation Direct methods - limitations the age/sex specific rates of the index population must be known often small numbers of deaths in index populations leading to instability in rates often the indirect method is preferred Standardisation Indirect standardisation the age/sex specific rates from a standard population are applied to the age/sex structure of the index population the number of deaths expected in the index population is calculated the standardised mortality ratio (SMR) is observed deaths 100% expected deaths Standardisation Standardised Mortality Ratio The ratio of the number of events observed in the study population to the number that would be expected if the study population had the same age-sex specific rates as the standard population Break for 15 minutes Module 2 Epidemiological studies Case control studies • Odds ratio Cohort studies • Relative risk Bias Confounding Sampling Screening • Specificity, sensitivity • Likelihood ratios Case-control study Case and control status determined by the presence or absence of disease at the start of the study period e.g. cases have dementia and controls don’t have dementia Exposure status determined retrospectively e.g. did they smoke or not in the past Case control studies Advantages quick and inexpensive good for rare diseases good if there is a long latent period from exposure to disease Good for investigating multiple exposures for a single disease Case control studies Disadvantages poor for rare exposures cannot usually calculate incidence rates poor for establishing temporal relationships prone to bias - selection and recall DEFINITION Odds the ratio of the probability of occurrence of an event to that of non occurrence Of 100 people with a cough (cases), 60 people are smokers and 40 are not - the odds of someone with a cough being a smoker is 60:40 or 1.5 (i.e. 60/40) DEFINITION Odds ratio the ratio of the odds in favour of exposure among the cases to the odds in favour of exposure in the controls measure of association derived from case-control study estimates relative risk if disease is rare OR > 1 indicates positive association DEFINITION Odds ratio example Of 100 people with a cough (cases), 60 are smokers and 40 are not - the odds of someone with a cough being a smoker is 60:40 or 1.5 (i.e. 60/40) Of 100 people without a cough (controls), 20 are smokers and 80 are not – the odds of someone without a cough being a smoker is 20:80 or 0.25 (i.e. 20/80) The odds ratio is 1.5 / 0.25 = 6 Odds
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