Cross-sectional study

1
Cross-sectional study
2
Definition
1.

• A cross-sectional studies
• a type of observational or descriptive study
• the research has no control over the exposure of
  interest (e.q. diet).
• It involves
• identifying a defined population at a particular
  point in time
• measuring a range of variables on an individual
  basis
• include past and current dietary intake

3
Uses of cross-sectional studies

• Prevalence survey The studies are commonly used
  to describe the burden of disease in the
  community and its distribution.
• Describe population characteristics They are
  also commonly used to describe population
  characteristics, often in terms of person (who?)
  and place (where?)
• .e.q.
• The British National Diet and Nutrition Survey
  or Nutrition and Health Survey in Taiwan
• To describe various age groups in the population
  in terms of food and nutrient intake and range of
  other personal and lifestyle characteristics.

4
(No Transcript)
5

• Migrant study Some migrant studies may full
  into the classification of cross-sectional
  studies. These studies give clues as to
  association between genetic background and
  environmental exposures on the risk of disease.
• e.q. A study of the prevalence (percentage) of
  coronary heart disease
• among men of Japanese ancestry living in Japan,
  Honolulu and the San Francisco Bay area
• showed the highest rates among those who had
  migrated to the United States.

6
(No Transcript)
7

• KAP (knowledges, attitudes, and practices )
  study
• KAP studies are purely descriptive and help to
  build up a better understanding of the behavior
  of the population, without necessarily relating
  this to any disease or health outcome.
• Management tool health service managers and
  planners may make use of cross-sectional survey
  to assess utilization and effectiveness of
  service.
• Development of hypothesis Hypotheses on the
  causes of disease may be developed using data
  from cross-sectional study survey.

8
Limitation of cross-sectional study

• It is not possible to say exposure or
  disease/outcome is cause and which
  effect.(????????)
• Confounding factors may not be equally
  distributed between the groups being compared and
  this unequal distribution may lead to bias and
  subsequent misinterpretation.
• Cross-sectional studies within dietary survey,
  may measure current diet in a group of people
  with a disease. Current diet may be altered by
  the presence of disease.
• A further limitation of cross-sectional studies
  may be due to errors in recall of the exposure
  and possibly outcome.

9
Design of cross-sectional survey

• The problem to be studied must be clearly
  described and a thorough literature review
  undertaken before starting the data collection.
• Specific objectives need to be formulated.
• The information has to be collected and data
  collection techniques need to be decided.
• Sampling is a particularly important issue to
  ensure that the objectives can be met in the most
  efficient way.

10

• Fieldwork needs planning
• Who is available to collect the data ?
• Do they need training ?
• If more than one is to collect the data then it
  is necessary to assess between-observer
  variation.
• The collection, coding and entry of data need
  planning.
• A pilot study is essential to test the proposed
  methods and make any alternations as necessary.
• The steps are summarized in Fig 13.5

11
(No Transcript)
12
(No Transcript)
13
Dietary assessment in cross-sectional studies

• Some characteristics of dietary assessment
  methods for cross-sectional studies
• Measures an individuals intake at one point in
  time.
• Does not require long-term follow up or repeat
  measures
• Valid
• Reproducible
• Suitable
• Cost within study budget

14
Dietary method application

• Food records using household measures have been
  used in cross-sectional studies.
• The recall method attempts to quantify diet over
  a defined period in the past usually 24 hours.
• The most commonly used dietary assessment method
  which attempts to measure usual intake is the
  food frequency questionnaire (FFQ).

15
(No Transcript)
16
(No Transcript)
17
Analysis of cross-sectional study

• Before starting any formal analysis, the data
  should be checked for any errors and outlines.
• Obvious error must be corrected.
• The records of outliners should be examined
  excluded
• Checking normality of data distribution.
• e.q. using the Kolmogorov-Smirnov Goodness of Fit
  Test.

18

• Standard descriptive statistics can then be used
  mean, median, quartiles, and mode measure of
  dispersion or variability such as standard
  deviation measure precision such as standard
  error, and confidence intervals.
• Mean can be compared using t-tests or analysis of
  variance (ANOVA).
• More complex multivariate analysis can be carried
  out such as multiple and logistic regression.