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

(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

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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