Substance Abuse & Mental Health Services Administration

The Substance Abuse and Mental Health Services Administration (SAMHSA)

Analyzing Data

Having data does not automatically lead to effective prevention planning. A meaningful epidemiological assessment involves the next steps of interpreting the data, including analysis, comparison, synthesis, and presentation. Epidemiological profiles use this process of interpretation to assess data by the following common dimensions:

  • Size or magnitude: explores the basic question of “how big” the underlying problems are in terms of occurrence
  • Trends over time: determines the extent to which a problem is increasing or decreasing in order to detect emerging or growing problems that may warrant increased attention
  • Relative comparisons: considers how individual State, Tribe, or Jurisdiction-level estimates and trends compare with other States’, Tribes’, or Jurisdictions’ rates or national rates
  • Seriousness or severity: assesses which consumption patterns or consequences may have greater impact on individuals and society than others (for example, when comparing binge drinking to any alcohol use in the past month, we know that binge drinking places individuals at greater risk of serious consequences)
  • Economic cost: Substance abuse affects the lives of millions of people each year in the U.S., with billions of dollars in economic costs associated with mortality, morbidity, health costs, and loss of productivity.

These dimensions each provide different types of information about substance abuse problems and different ways of assessing their importance. Using multiple dimensions will often provide a more complete understanding of the extent and importance of substance abuse and related behavioral health problems in a particular setting. 

Moreover, substance use and its related consequences may not be distributed equally across members of a population; instead, they may depend upon a variety of population characteristics such as demographics (e.g., age, gender, race or ethnicity), geography (e.g., region, county), and interactions among these characteristics. Conducting subgroup analyses on the data may reveal differential patterns across subgroups in substance use and related negative consequences that are important in determining where and how to direct prevention efforts.