This document discusses cross-sectional study designs for epidemiological research. A cross-sectional study involves identifying a population at a single point in time and collecting data on exposures and outcomes without influencing either. Key advantages are allowing estimates of disease prevalence and descriptions of population characteristics. Limitations include inability to determine causality and potential for confounding biases. The document outlines appropriate dietary assessment tools, study design considerations, and analytical methods for cross-sectional research.

1. 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 & DieteticsSchool of Nutrition & Dietetics
Faculty of Health SciencesFaculty of Health Sciences
UniversitiUniversiti SultanSultan ZainalZainal AbidinAbidin
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2. 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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3. 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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4. (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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5. (cont.) Cross sectional
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6. 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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7. (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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8. (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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9. (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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10. 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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11. (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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12. (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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13. 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

14. (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

15. 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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16. 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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17. 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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18. 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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19. 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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20. (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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21. 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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22. Thank YouThank You
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