A short introduction to epidemiologyChapter 4: More complexstudy designs
Neil Pearce
Centre for Public Health Research
Massey University
Wellington, New Zealand
Birth
End of Follow up
Death
other death
lost to follow up
“non-diseased”
symptoms
severe disease
Study Design Options
•All epidemiological studies are (or should be)based on a particular population (the sourcepopulation) followed over a particular periodof time (the risk period)
•The different study design options differ onlyin how the source population is defined andhow information is drawn from this populationand time period
Incidence and Prevalence
•Incidence is the number of new cases of thecondition over a specified period of time
•Prevalence is the number of cases of thecondition at a particular point in time
Study Design Options
Chapter 4More complex study designs
•Other axes of classification
•Continuous outcomemeasures
•Ecologic and multi-levelstudies
Other axes of classification
•Continuous exposure data
•Timing of collection of exposure data(retrospective, prospective)
•Sources of exposure information (interviews,routine records, biomarkers)
•Level of measurement of exposure(individual, population)
Chapter 4More complex study designs
•Other axes of classification
•Continuous outcomemeasures
•Ecologic and multi-levelstudies
Continuous Outcome Measures
•Lung function in a cross-sectional study (aprevalence study is a cross-sectional studywith a dichotomous outcome measure)
•Changes in lung function over time in alongitudinal study (an incidence study is alongitudinal study with a dichotomousoutcome measure)
Continuous Outcome Measures
•Tager et al (1983), longitudinal study ofpulmonary function in children aged 5-9years, followed for 7 years
•Exposures: maternal smoking
•Outcomes: annual increase in FEV1 (thiswas 28mL lower in children exposed tomaternal smoking)
Continuous Outcome Measures
•Roemer et al (1993), time series study ofwinter air pollution and respiratory health ofchildren aged 6-12 years
•Exposures: daily air pollution measures
•Outcomes: asthma symptoms, medicationuse (e.g. wheeze was more common on dayswhen particulate concentrations were high
Cross-Sectional Studies
Particularly valuable for:
•Non-fatal diseases
•Degenerative diseases with no clear point ofonset (e.G. Chronic bronchitis)
•Examining effects on physiologic variables(e.G. Liver enzyme levels, blood pressure,lung function)
Cross-Sectional Studies: Examples
•General household surveys (e.g. England andWales, Spain, New Zealand)
•National Health and Nutrition Examination Survey(USA)
•International surveys (e.g. European CommunityRespiratory Health Survey (ECRHS), InternationalStudy of Asthma and Allergies in Childhood(ISAAC)
•Pre-employment surveys
•Studies in specific populations (e.g. occupationalhealth research)
Cross-Sectional studies
•Disease is measured at one point in time
•Exposure may be measured at the same timeand/or historical exposure information maybe available
•May be difficult to know the temporalrelationship between exposure and disease
•This problem is avoided in repeated cross-sectional studies
Study Design Options
•Case series
•Incidence studies
•Incidence case-control studies
•Prevalence studies
•Prevalence case-control studies
•Cross-sectional studies (with continuousoutcome measure)
•Longitudinal studies (with continuousoutcome measure)
Chapter 4More complex study designs
•Other axes of classification
•Continuous outcomemeasures
•Ecologic and multi-levelstudies
Ecologic Studies
An ecologic study is a study in which oneor more exposures (or confounders) ismeasured at the population level ratherthan the individual level
Reasons for Ecologic Studies
•Low cost and convenience
•Measurement limitations of individual-levelstudies (e.g. diet, air pollution)
•Design limitations of individual-level studies(e.g. lack of exposure variation)
•Interest in ecologic effects
•Simplicity of analysis and presentation
Levels of Measurement
•Individual measures, e.g. smokingstatus, income
•Aggregate measures, e.g. % smokers,median family income
•Environmental measures, e.g. airpollution levels
•Global measures, e.g. smokinglegislation, income inequality, GNP, typeof health care system, populationdensity
Levels of Analysis
•Individual level, e.g. average level of air pollutionis “assigned” to each individual, and individualage, gender, ethnicity, smoking status areknown
•Partially ecologic analysis: e.g. some variablesknown for individuals (age, gender, air pollution)but others for the population (%smokers)
•Fully ecologic analysis: all information onexposure and disease only known for thepopulation
Levels of Analysis
Multilevel analysis
•First level: individual level analysis withineach group (population)
•Second level: regression parameters fromfirst level are modelled as a function ofecologic variables
•e.g. Humphreys and Carr-Hill (1991) usedmultilevel modeling to estimate the contextualeffect of living in a poor area, controlling forindividual income and other risk factors
Levels of Inference
•Individual (e.g. fat intake and breast cancer)
•Contextual (e.g. living in a poorneighbourhood)
•Ecologic (e.g. GNP, income inequality)
•The major problem is with cross-levelinferences, e.g. using ecologic data toestimate the individual risk from fat intake
12 Month Period Prevalence of Asthma Symptoms in 13-14 Yr Old Children
The Ecologic Fallacy in ISAAC:Indoor Humidity and Asthma
The Ecologic Fallacy in ISAAC:Indoor Humidity and Asthma
Example of ecologic data
Example of ecologic data
Example With No Confounding byGroup
Example With Confounding by Group
Example With Effect Modificationby Group
Problems of Ecologic Studies
Ecologic bias, in estimating effects at the individual levelmay result from:
•Within group bias: if there is confounding, selectionbias or misclassification within each group then theecologic estimate may also be biased
•Confounding by group: the “background” disease ratevaries across groups
•Effect modification by group: the “excess rate” due toexposure varies across groups
Problems of Ecologic Studies
•The major problems of “ecologic bias” arise fromattempts at cross-level inference, e.g. in studieswhere the intention is to make inferences at theindividual level
•Nevertheless, ecologic studies have played a majorrole in the development, and to some extent in thetesting, of epidemiological hypotheses
•Furthermore, some important risk factors can onlybe studied at the population level.
A short introduction to epidemiologyChapter 4: More complexstudy designs
Neil Pearce
Centre for Public Health Research
Massey University
Wellington, New Zealand