Cross sectional study overview
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Cross sectional study overview






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Cross sectional study overview Cross sectional study overview Presentation Transcript

  • Cross-sectional study
  • Definition
    • 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
  • Uses of cross-sectional studies
    • Prevalence survey: The studies are commonly used to describe the burden of disease in the community and its distribution.
    • D escribe 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.
    • 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.
    • 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.
  • Limitation of cross-sectional study
    • It is not possible to say exposure or disease/outcome is cause and which effect.( 不能判定因果關係 )
    • 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.
  • 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.
    • 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*
  • Dietary assessment in cross-sectional studies
    • Some characteristics of dietary assessment methods for cross-sectional studies
      • Measures an individual’s intake at one point in time.
      • Does not require long-term follow up or repeat measures
      • Valid
      • Reproducible
      • Suitable
      • Cost within study budget
  • 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).
  • 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.
    • 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.