At A Glance

Noteworthy Characteristics

  • Study design permits tracking of trends in attitudes and behaviors in adolescents over time periods and age groups.
  • Annual follow-up questionnaires are mailed to a sample of each graduating class for a number of years after their initial participation.
  • Includes self-report data on leisure activities, height and weight, some dietary behaviors, and physical activity.

Website

http://www.monitoringthefuture.org/

Purpose

To collect data on a variety of subjects from secondary school students in the United States (U.S.).

Target Population

Students in the 8th, 10th, and 12th grades in public and private schools in the U.S.

Conducted

Began in 1975. Data collection for 8th and 10th grade students began in 1991. Conducted annually. Most recent year conducted was 2018.

Sponsor

National Institute on Drug Abuse, National Institutes of Health, U.S. Department of Health and Human Services

Special Note(s)

In each grade, students are randomly assigned to complete questionnaires with a subset of topical questions in addition to a set of core questions on demographics and drug use. Some topical questions collect data on diet and physical activity, but these questions vary by survey year.

Sampling

Sample Design

Cross-sectional survey.

Multi-stage random sampling is performed each year to obtain a nationally representative sample of students in each targeted grade. Learn more about the sampling design.

Sample Size

Approximately 50,000 8th, 10th, and 12th grade students in approximately 400 public and private middle schools and high schools are surveyed each year.

Special Note(s)

Within each school, up to 350 students may be included. In schools with fewer students, the usual procedure is to include all of them in the data collection. In larger schools, a subset of students is selected either by randomly sampling classrooms or by some other random method that is judged to be unbiased. Sampling weights are used to correct for unequal probabilities of selection that occurred at any stage of sampling.

Key Variables

Demographic

NameMethods of Assessment
Disability (cognitive)Interview/questionnaire
Race-ethnicity (Black/White/Hispanic)Interview/questionnaire
SexInterview/questionnaire

Diet-Related

NameMethods of Assessment
Frequency of eating breakfast, vegetables, and fruitInterview/questionnaire

Physical Activity-Related

NameMethods of Assessment
Frequency of participation in sports or exerciseSelf report
Frequency of vigorous physical activitySelf report
Participation in specific sportsSelf report

Weight-Related

NameMethods of Assessment
Height and weightSelf report

Geocode/Linkage

NameMethods of Assessment
School zip code, city, county, and state with restricted data use agreementN/A

Data Access and Cost

Data Availability

Data can be obtained from the Inter-University Consortium for Political and Social Research (ICPSR). Only investigators at ICPSR member institutions may download raw data files. Learn more about downloading data.

Cost

Free of charge.

Special Note(s)

Investigators may obtain most restricted data by signing a Restricted Data Use Agreement and submitting a Data Protection Plan. Learn more.

The most recent year for which data are available is not necessarily the most recent year this survey was conducted.

Geocode/Linkage

Geocode Variable(s)

School zip code, city, county, and state with Restricted Data Use Agreement (see Data Access and Cost).

Existing Linkages

None noted.

Special Note(s)

Metropolitan statistical areas are designated as Large, Other, and Non but are not otherwise identified.

Selected Publications

Click here for a full list of publications.

General

Auld MC, Powell LM. Economics of food energy density and adolescent body weight. Economica 2009;76(304):719-740.

O'Malley PM, Johnston LD, Delva J, Bachman JG, Schulenberg JE. Variation in obesity among American secondary school students by school and school characteristics. American Journal of Preventive Medicine 2007;33(4S):187-194.

Powell LM, Chriqui J, Chaloupka FJ. Associations between state-level soda taxes and adolescent body mass index. Journal of Adolescent Health 2009;45(3 Suppl):S57-S63.