Research article
Identifying Sedentary Subgroups: The National Cancer Institute’s Health Information National Trends Survey

https://doi.org/10.1016/j.amepre.2006.07.024Get rights and content

Background

Developing effective interventions for the 24% to 28% of U.S. adults who are sedentary requires a better understanding of the factors related to sedentary lifestyles as well as the communication channels to reach various subgroups. This study identified key sociodemographic and health communication characteristics of various subgroups with high rates of inactivity using signal detection methodology.

Methods

The sample from the nationally representative Health Information National Trends Survey 2003 (n=6369) was randomly split into two samples. Exploratory analyses (conducted 2004 and 2005) were employed on the first sample to identify various subgroups, and the stability of inactivity rates in those subgroups was examined in the second sample.

Results

Eight subgroups with varying levels of inactivity were identified. Three subgroups had inactivity levels of 40% or higher, while the lowest subgroup had a level of less than 15%. The highest inactivity subgroup consisted of individuals with at least some college education who were in fair/poor health and who watched 4 or more hours of television per day. The second-highest inactivity subgroup was composed of those without a college education who tended not to use or attend to many communication channels. The third highest inactive subgroup consisted of those without a college education who read the newspaper and were obese. Levels of inactivity in the second independent sample subgroups were not significantly different from those found in the exploratory sample.

Conclusions

This study identified empirically based, physically inactive subgroups that differed on sociodemographic and health communication characteristics. This information should be useful in creating future evidence-based, targeted, and tailored intervention strategies.

Introduction

Inactivity has been linked to increased risk of many chronic illnesses,1, 2 including increased risk and carcinogenesis for many cancers.3, 4, 5 Consequently, one of the major goals of the Institute of Medicine report in 2003, Fulfilling the Potential of Cancer Prevention and Early Detection, is the development of prevention strategies to reduce sedentary behavior and obesity.6 The importance of these prevention strategies is highlighted by national surveys indicating that 24% to 28% of adults in the United States are completely sedentary, and that levels of obesity in the nation are growing to epidemic proportions.2, 7A better understanding of the characteristics of sedentary populations is required to develop effective intervention strategies.

Those who are physically inactive (i.e., sedentary) in all likelihood do not represent just one group, but may consist of several subgroups. Yet, the identification of specific inactivity subgroups has received relatively little attention, and attempts to characterize inactive groups have typically taken a unidimensional perspective by classifying subgroups along one domain (e.g., age, gender, ethnicity) or examining multiple correlates without evaluating possible interactions among the variables.8 The characteristics of inactive groups are likely to be complex and an aggregate of various factors. Examining multiple characteristics of sedentary groups may aid in more effective health promotion intervention programs.

Identification of critical communication channels is key to developing effective programs for reaching sedentary subgroups. In addition to traditional face-to-face approaches (e.g., exercise classes), previous physical activity research has focused on either mass media campaigns to promote physical activity or smaller-scale interventions using the telephone and/or print media to provide physical activity advice and information.9 Yet, few studies have simultaneously examined the spectrum of mediated communication channels (e.g., television, newspaper, Internet) available to reach the inactive populations, and how these channels can be used to disseminate effective interventions.

The purposes of this study were to (1) identify distinct subgroups with high proportions of inactivity in a nationally derived sample using signal detection methodology (SDM), and (2) examine the stability of the inactivity patterns using an independent sample.

Section snippets

Data Source

Data came from the 2003 Health Information National Trends Survey (HINTS). This survey was developed to collect nationally representative data about the American public’s need for, access to, and use of cancer-relevant information (see http://cancercontrol.cancer.gov/hints/index.jsp).

Data Collection

Data were collected from October 2002 through April 2003. Trained interviewers used a list-assisted random-digit-dial method from all working “banks” of telephone numbers within the United States. One adult (aged

Results

Descriptive characteristics of the full sample (unweighted data) are displayed in Table 1. Overall, about 28% of respondents were sedentary. Bivariate analysis revealed that inactive respondents were older, less educated, and of lower-income strata; more likely to be women, not married, nonwhite, overweight, and have smoked ≥100 cigarettes in their lifetimes; and less likely to live in metropolitan areas, be in poorer general health, have health insurance, believe that exercise lowers cancer

Discussion and Conclusions

Approximately one quarter of the U.S. adult population remains sedentary. This study was conducted to identify empirically distinct subgroups with varying sedentary levels. Overall, results suggest that subgroups with similar levels of inactivity can have quite different defining characteristics. Furthermore, the inactivity patterns found using SDM were found to be stable in an independent sample.

Previous studies on inactivity have typically not considered the complex interactions among

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    The views presented in this paper represent those of the authors and not the National Cancer Institute.

    No financial conflict of interest was reported by the authors of this paper.

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