They are often used to assess the prevalence of acute or chronic conditions, but cannot be used to answer questions about the causes of disease or the results of intervention.
[citation needed] The use of routinely collected data allows large cross-sectional studies to be made at little or no expense.
In a cross-sectional survey, a specific group is looked at to see if an activity, say alcohol consumption, is related to the health effect being investigated, say cirrhosis of the liver.
For example, past alcohol consumption may be incorrectly reported by an individual wishing to reduce their personal feelings of guilt.
[citation needed] Cross-sectional studies can contain individual-level data (one record per individual, for example, in national health surveys).
However, in modern epidemiology it may be impossible to survey the entire population of interest, so cross-sectional studies often involve secondary analysis of data collected for another purpose.
Major sources of such data are often large institutions like the Census Bureau or the Centers for Disease Control in the United States.
[citation needed] In economics, cross-sectional analysis has the advantage of avoiding various complicating aspects of the use of data drawn from various points in time, such as serial correlation of residuals.
The cross-sectional study has the advantage that it can investigate the effects of various demographic factors (age, for example) on individual differences; but it has the disadvantage that it cannot find the effect of interest rates on money demand, because in the cross-sectional study at a particular point in time all observed units are faced with the same current level of interest rates.