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Differences in Physical Activity Prevalence and Trends From 3 U.S. Surveillance Systems: NHIS, NHANES, and BRFSS

Susan A. Carlson, Dianna Densmore, Janet E. Fulton, Michelle M. Yore, and Harold W. Kohl III

Background:

Three U.S. surveillance systems—National Health Interview Survey (NHIS), National Health and Nutrition Examination Survey (NHANES), and Behavioral Risk Factor Surveillance System (BRFSS)—estimate physical activity prevalence.

Methods:

Survey differences were examined qualitatively. Prevalence estimates by sex, age, and race/ethnicity were assessed for comparable survey periods. Trends were examined from NHIS 1998 to 2007, NHANES 1999 to 2006, and BRFSS 2001 to 2007.

Results:

Age-adjusted prevalence estimates appeared most similar for NHIS 2005 (physically active: 30.2%, inactive: 40.7%) and NHANES 2005 to 2006 (physically active: 33.5%, inactive: 32.4%). In BRFSS 2005, prevalence of being physically active was 48.3% and inactive was 13.9%. Across all systems, men were more likely to be active than women; non-Hispanic whites were most likely to be active; as age increased, overall prevalence of being active decreased. Prevalence of being active exhibited a significant increasing trend only in BRFSS 2001 to 2007 (P < .001), while prevalence of being inactive decreased significantly in NHANES 1999 to 2006 (P < .001) and BRFSS 2001 to 2007 (P < .001).

Conclusions:

Different ways of assessing physical activity in surveillance systems result in different prevalence estimates. Before comparing estimates from different systems, all aspects of data collection and data analysis should be examined to determine if comparisons are appropriate.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 6 (2009): Issue s1 (Jan 2009): Physical Activity Surveillance and Assessment

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Physical Activity Patterns Associated With Weight-Control Status: Differences by Race and Sex

Judy Kruger, Michelle M. Yore, Barbara E. Ainsworth, and Caroline A. Macera

Background:

Physical activity (PA) plays a major role in maintaining energy balance. We examined the patterns of occupational activity, strength training, and lifestyle PA (low, medium, high) by sex and race among persons trying to control their weight (lose weight, stay about the same, not trying to lose/not trying to stay about the same).

Methods:

Population data (N = 9258) from a nationwide telephone survey were collected to examine PA patterns. Domains of PA were analyzed by sex and race.

Results:

Of those trying to control their weight, approximately 24.0% engaged in strengthening activities 2 to 3 d/wk. Among those trying to lose weight, 48.2% versus 42.2% of men (White and non-White, respectively) and 40.4% versus 35.1% of women (White and non-White, respectively) reported high volumes of PA.

Conclusions:

PA patterns among persons trying to control their weight vary by sex and race. Adults trying to control their weight are encouraged to increase levels of PA.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 5 (2008): Issue 3 (May 2008)

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Occupational Physical Activity: Reliability and Comparison of Activity Levels

Michelle M. Yore, Sandra A. Ham, Barbara E. Ainsworth, Caroline A. Macera, Deborah A. Jones, and Harold W. Kohl III

Background:

In 2001, the Behavioral Risk Factor Surveillance System (BRFSS) included a new occupational physical activity (PA) question. This article evaluates the reliability of this survey question.

Methods:

Forty-six subjects were followed for 3 wk, answered 3 PA surveys by telephone, and completed daily PA logs for 1 wk. Kappa statistics determined the reliability of occupational activities (sitting/standing, walking, and heavy lifting). A descriptive analysis compared the time in specific occupational activities.

Results:

Eighty percent of the respondents reported “mostly sitting or standing” at work; and test–retest reliability was moderate (k = 0.40 to 0.45). The occupationally inactive sat/stood for 85% (mean hours = 5.6) of the workday, whereas the occupationally active sat/stood for 53% (mean hours = 3.9) of the workday.

Conclusions:

The BRFSS occupational activity question has moderate reliability, distinguishes between occupationally active and inactive persons, and can be used in surveillance systems to estimate adult occupational PA.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 2 (2005): Issue 3 (Jul 2005)

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Single Versus Multiple Item Questions on Occupational Physical Activity

Michelle M. Yore, Heather R. Bowles, Barbara E. Ainsworth, Caroline A. Macera, and Harold W. Kohl III

Background:

In 2002, the National Physical Activity and Weight Loss Survey asked two sets of questions on occupational physical activity—one question from the Behavioral Risk Factor Surveillance System (BRFSS) and eight detailed questions from the occupational physical activity questionnaire (OPAQ). This study compares the responses.

Methods:

On the basis of percentage of occupational physical activity reported on OPAQ, 5847 respondents were classified by three levels (sitting or standing, walking, and heavy labor). Kappa, MET-min per day, and median hours worked at the three levels were calculated to compare the two sets of questions.

Results:

Levels of occupational physical activity reported on the BRFSS question agreed with OPAQ (kappa = 0.56). Hours of heavy labor per day reported on OPAQ increased among the three activity levels on BRFSS.

Conclusions:

The BRFSS question and OPAQ classify respondents similarly by occupational physical activity. The BRFSS question is useful for overview and OPAQ, for more detailed analyses.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 3 (2006): Issue 1 (Jan 2006)

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Television Viewing, Computer Use, and BMI Among U.S. Children and Adolescents

Janet E. Fulton, Xuewen Wang, Michelle M. Yore, Susan A. Carlson, Deborah A. Galuska, and Carl J. Caspersen

Background:

To examine the prevalence of television (TV) viewing, computer use, and their combination and associations with demographic characteristics and body mass index (BMI) among U.S. youth.

Methods:

The 1999 to 2006 National Health and Nutrition Examination Survey (NHANES) was used. Time spent yesterday sitting and watching television or videos (TV viewing) and using the computer or playing computer games (computer use) were assessed by questionnaire.

Results:

Prevalence (%) of meeting the U.S. objective for TV viewing (≤2 hours/day) ranged from 65% to 71%. Prevalence of no computer use (0 hours/day) ranged from 23% to 45%. Non-Hispanic Black youth aged 2 to 15 years were less likely than their non-Hispanic White counterparts to meet the objective for TV viewing. Overweight or obese school-age youth were less likely than their normal weight counterparts to meet the objective for TV viewing

Conclusions:

Computer use is prevalent among U.S. youth; more than half of youth used a computer on the previous day. The proportion of youth meeting the U.S. objective for TV viewing is less than the target of 75%. Time spent in sedentary behaviors such as viewing TV may contribute to overweight and obesity among U.S. youth.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 6 (2009): Issue s1 (Jan 2009): Physical Activity Surveillance and Assessment