Cross sectional study overview


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Cross sectional study overview

  1. 1. Cross-sectional study
  2. 2. Definition <ul><li>A cross-sectional studies </li></ul><ul><ul><li>a type of observational or descriptive study </li></ul></ul><ul><ul><li>the research has no control over the exposure of interest (e.q. diet). </li></ul></ul><ul><li>It involves </li></ul><ul><ul><li>identifying a defined population at a particular point in time </li></ul></ul><ul><ul><li>measuring a range of variables on an individual basis </li></ul></ul><ul><ul><li>include past and current dietary intake </li></ul></ul>1.
  3. 3. Uses of cross-sectional studies <ul><li>Prevalence survey: The studies are commonly used to describe the burden of disease in the community and its distribution. </li></ul><ul><li>D escribe population characteristics: They are also commonly used to describe population characteristics, often in terms of person (who?) and place (where?) </li></ul><ul><ul><li>.e.q. </li></ul></ul><ul><ul><li>The British National Diet and Nutrition Survey or Nutrition and Health Survey in Taiwan </li></ul></ul><ul><ul><li>To describe various age groups in the population in terms of food and nutrient intake and range of other personal and lifestyle characteristics. </li></ul></ul>
  4. 5. <ul><li>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. </li></ul><ul><ul><li>e.q. A study of the prevalence (percentage) of coronary heart disease </li></ul></ul><ul><ul><li>among men of Japanese ancestry living in Japan, Honolulu and the San Francisco Bay area </li></ul></ul><ul><ul><li>showed the highest rates among those who had migrated to the United States. </li></ul></ul>
  5. 7. <ul><li>KAP (knowledges, attitudes, and practices ) study: </li></ul><ul><ul><li>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. </li></ul></ul><ul><li>Management tool : health service managers and planners may make use of cross-sectional survey to assess utilization and effectiveness of service. </li></ul><ul><li>Development of hypothesis : Hypotheses on the causes of disease may be developed using data from cross-sectional study survey. </li></ul>
  6. 8. Limitation of cross-sectional study <ul><li>It is not possible to say exposure or disease/outcome is cause and which effect.( 不能判定因果關係 ) </li></ul><ul><li>Confounding factors may not be equally distributed between the groups being compared and this unequal distribution may lead to bias and subsequent misinterpretation. </li></ul><ul><li>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. </li></ul><ul><li>A further limitation of cross-sectional studies may be due to errors in recall of the exposure and possibly outcome. </li></ul>
  7. 9. Design of cross-sectional survey <ul><li>The problem to be studied must be clearly described and a thorough literature review undertaken before starting the data collection. </li></ul><ul><li>Specific objectives need to be formulated. </li></ul><ul><li>The information has to be collected and data collection techniques need to be decided. </li></ul><ul><li>Sampling is a particularly important issue to ensure that the objectives can be met in the most efficient way. </li></ul>
  8. 10. <ul><li>Fieldwork needs planning: </li></ul><ul><ul><li>Who is available to collect the data ? </li></ul></ul><ul><ul><li>Do they need training ? </li></ul></ul><ul><ul><li>If more than one is to collect the data then it is necessary to assess between-observer variation. </li></ul></ul><ul><li>The collection, coding and entry of data need planning. </li></ul><ul><li>A pilot study is essential to test the proposed methods and make any alternations as necessary. </li></ul><ul><li>* The steps are summarized in Fig 13.5* </li></ul>
  9. 13. Dietary assessment in cross-sectional studies <ul><li>Some characteristics of dietary assessment methods for cross-sectional studies </li></ul><ul><ul><li>Measures an individual’s intake at one point in time. </li></ul></ul><ul><ul><li>Does not require long-term follow up or repeat measures </li></ul></ul><ul><ul><li>Valid </li></ul></ul><ul><ul><li>Reproducible </li></ul></ul><ul><ul><li>Suitable </li></ul></ul><ul><ul><li>Cost within study budget </li></ul></ul>
  10. 14. Dietary method application <ul><li>Food records using household measures have been used in cross-sectional studies. </li></ul><ul><li>The recall method attempts to quantify diet over a defined period in the past usually 24 hours. </li></ul><ul><li>The most commonly used dietary assessment method which attempts to measure usual intake is the food frequency questionnaire (FFQ). </li></ul>
  11. 17. Analysis of cross-sectional study <ul><li>Before starting any formal analysis, the data should be checked for any errors and outlines. </li></ul><ul><ul><li>Obvious error must be corrected. </li></ul></ul><ul><ul><li>The records of outliners should be examined excluded </li></ul></ul><ul><ul><li>Checking normality of data distribution. </li></ul></ul><ul><ul><ul><li>e.q. using the Kolmogorov-Smirnov Goodness of Fit Test. </li></ul></ul></ul>
  12. 18. <ul><li>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. </li></ul><ul><li>Mean can be compared using t-tests or analysis of variance (ANOVA). </li></ul><ul><li>More complex multivariate analysis can be carried out such as multiple and logistic regression. </li></ul>