3. cross sectional
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KNOWLEDGE FOR THE BENEFIT OF HUMANITYKNOWLEDGE FOR THE BENEFIT OF HUMANITY
PUBLIC HEALTH AND EPIDEMIOLOGY (HFS3063) Epidemiological Study Designs:
CROSS SECTIONAL
Dr. Dr. MohdMohd RazifRazif ShahrilShahril
School of Nutrition & Dietetics School of Nutrition & Dietetics
Faculty of Health SciencesFaculty of Health Sciences
UniversitiUniversiti Sultan Sultan ZainalZainal AbidinAbidin
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Topic Learning Outcomes
By the end of this lecture, students should be able to;
• describe cross sectional study design.
• explain the advantages and disadvantages of cross sectional design.
• Identify appropriate dietary assessment tools for cross sectional study design
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Cross sectional • A type of observational or descriptive study
– Researcher has no control over the exposure of interest (e.g.
diet)
• Involves identifying a defined population at a particular
time and measuring a range of variables on an
individual basis
– Can include past or current dietary intake
– Data may be explored in relation to the presence or absence of
disease or health outcomes.
• Not possible to determine whether the exposure and the
outcome are causally related
– Data represent snapshot of information at one point in time
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(cont.) Cross sectional • Also known as prevalence surveys
– Can be used to estimate prevalence of disease in a population
– Prevalence = number of cases in the population at a particular
point in time expressed as a rate.
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(cont.) Cross sectional
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Uses of cross sectional studies Prevalence Surveys
• Commonly used to describe the burden of disease in the
community and its distribution
Describe population characteristics
• Commonly used to describe population characteristics,
often in terms of person (who?) and place (where?) e.g.:
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(cont.) Uses of cross sectional studies
Migrant studies
• Give clues as to the association between genetics
background and environmental exposures on the risk of
disease
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(cont.) Uses of cross sectional studies
KAP studies
• Knowledge, Attitude and Practice (KAP) studies are
purely descriptive and help to build up a better
understanding of the behaviour of the population
– Without necessarily relating this to any disease or health
outcomes
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(cont.) Uses of cross sectional studies
Development of hypotheses
• The work has added support to other findings.
• The results have encourages further work in the area
studied.
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Limitations of cross sectional studies
• Exposure and disease/ outcome are measured at the
same time
– Not possible to identify which is cause and which is effect.
– To test the hypotheses, a cohort study would be needed.
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(cont.) Limitations of cross sectional studies
• Confounding factors may not be equally distributed
between groups being compared
– May lead to bias and subsequent misinterpretation
– Confounding factor = variable which is related both to the
exposure (diet) and the outcome (disease). E.g.: age, gender,
ethnicity
• Impact removed by stratifying the samples by the confounder at the analysis
stage
• Residual confounding (related to variables measured poorly or not at all) is
still possible
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(cont.) Limitations of cross sectional studies
• Current diet may be altered by the presence of disease
– Outcome (disease) is having influence on the exposure (diet)
variable
– Diet may change over time even when subjects are not affected
by disease
• Due to errors in recall of the exposure and possibly the
outcome
• Prevalence studies may be affected by Neyman’s bias
– Subjects are not included in the prevalence measure because
they have died early from the disease or the symptoms have
gone
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Design of cross sectional studies
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Questions to ask Steps to take Important elements
What is the problem and why should it be studied?
CHOOSE THE PROBLEM AND ANALYSE IT • Problem identification • Prioritizing problem • Problem analysis
What information is already available?
LITERATURE REVIEW
• Literature and other
available information
What do we hope to achieve?
FORMULATION OF OBJECTIVES
• General and specific
objectives • Hypothesis
What data do we need to meet out objectives? How will this be collected?
RESEARCH METHODOLOGY
(cont.)
• Sampling • Variables • Data collection
techniques • Plan for data
collection, processing, and analysis
• Ethics, pilot study
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(cont.) Design of cross sectional studies
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Questions to ask Steps to take Important elements
(cont.)
Who will do what and when?
WORK PLAN • Personnel-training • Timetable
How will the study be administered?
PLAN FOR PROJECT ADMINISTRATION
• Administration and
monitoring
What resources do we need?
RESOURCE IDENTIFICATION AND
ACQUISITION
• Money • Personnel • Material, equipment
How will we use the results?
PROPOSAL SUMMARY, PAPERS AND
PRESENTATION
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Dietary assessment in cross sectional studies
Characteristics;
• Measures an individual’s intake at one point in time
– Food balance sheet data or food sales data are not suitable
• Does not require long-term follow up or repeat measures
– Measures habitual intake
• Valid
• Reproducible
• Suitable for aim of study
• Cost within study budget
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Dietary assessment in cross sectional studies
Deciding which method to choose;
• What is already known about the population?
– Very little – a more detailed method may be required such as
weighed intake or food records.
– Some information – a FFQ may be developed.
• What are the objectives of the study?
– Detailed food and nutrient intake required – use a weighed
intake or measured food diary: some FFQs with portion size may
be suitable.
– Food intake patterns of interest – a recall, FFQ or food checklist.
– Meal patterns – recall, food list, food diary, weighed intake.
– Food knowledge and attitudes – consider using focus group
discussion, semi structured questionnaires, or interviews.
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Dietary assessment in cross sectional studies
(cont.) Deciding which method to choose;
• Who are the subjects?
– Literate – weighed intake, food records may be appropriate.
– Illiterate – recall, interviewer administered FFQ.
– Motivated – weighed intake.
– Less motivated or short of time – recall, FFQ.
• What resources are available?
– Finance limited – an FFQ or recall methods may be cheaper, or
use published/ routine data.
– Personnel limited/ inexperienced - FFQ
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Dietary assessment in cross sectional studies
(cont.) Deciding which method to choose;
• What is the level of cooperation required of the subjects?
– Weighed intake and food record methods require a high degree
of cooperation.
– FFQ and recall methods require less cooperation.
• Statistical issues
– Consider how many days of intake need to be recorded by
weighing or food record.
– In population studies, it is most efficient to maximise the sample
size and minimize the number of recording days per individual.
– All methods should be validated in a subsample against an
alternative measure of diet with independent errors, such as a
biomarker.
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Analysis of cross sectional studies
• Data checked for any errors and outliers prior to
analysis.
• Data explored graphically e.g. plot the frequency
distributions of various nutrients
– Check normality of the distribution
• Standard descriptive statistics
– Mean, median, quartiles, mode
– Range, interquartile range, standard deviation
– Standard error and confidence intervals
– Prevalence rates
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(cont.) Analysis of cross sectional studies
• Association can be explored using correlation and
regression for continuous variables
– Shows variables are associated, not necessarily imply a cause
and effect relationship.
• Means can be compared
• Complex multivariate analysis (multiple and logistics
regression) can be carried out
– to investigate how a dependent variable is related to more than
one explanatory variable.
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Recapitulate In this lecture, you have been exposed to;
• definition of cross sectional study.
• uses of cross sectional study.
• limitations of cross sectional study.
• designing a cross sectional study.
• how to decide which dietary assessment method to be
used in a cross sectional study.
• types of analysis that can be conducted in a cross
sectional study.
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Thank YouThank You
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