A Comparison of Subjective and Objective Measures of Physical Activity and Fitness in Identifying Associations with Cardiometabolic Risk Factors

https://doi.org/10.1016/j.annepidem.2008.01.005Get rights and content

Purpose

To compare the ability of alternative measures of physical activity and fitness to quantify associations with health outcomes.

Methods

Associations between a range of subjective and objective physical activity and fitness measures and cardiometabolic risk factors were examined using data from 1,631 Australians aged 26–36 years. Anthropometry, fitness, blood pressure, and fasting blood glucose, insulin, and lipids were measured at study clinics. Participants completed the International Physical Activity Questionnaire (IPAQ) and 7-day pedometer diaries; they also reported sedentary behavior (sitting, television viewing).

Results

In men and women, associations were strongest for fitness, with those in the highest (vs. lowest) fitness quarter having a 75% to 80% lower prevalence of two or more primary risk factors (waist circumference, high-density lipoprotein cholesterol, and insulin resistance). In men, a 60% to 70% reduced prevalence of two or more risk factors was observed across extreme quarters of IPAQ leisure, IPAQ vigorous, sitting duration, and pedometer measures. Similar reductions in prevalence were observed only across extreme quarters of pedometer activity and television viewing in women.

Conclusions

Associations between alternative measures and cardiometabolic risk were relatively independent, suggesting that a range of physical activity and fitness measures may be needed to most accurately quantify associations between physical activity and health.

Introduction

Population-based studies have typically relied on self-report measures of physical activity, given their low cost, feasibility, and ability to characterize physical activity by frequency, intensity, duration, and type (1). Despite their widespread use, self-reported activity measures may be subject to unreliable recall and bias, may miss most nonstructured activity, and result in large amounts of random error 1, 2, 3. These limitations may substantially attenuate observed associations with health outcomes, potentially leading to erroneous null findings, and make it difficult to characterize dose-response relationships where they exist.

Objective measures of physical activity such as pedometers are becoming more commonly used in large population studies 4, 5. These relatively low-cost instruments are able to capture lower intensity activities, such as walking and incidental activity, which are difficult to accurately quantify using survey methods (3). However, pedometers are unable to distinguish activity intensity which may be an important limitation where the relationship between physical activity and a health outcome is intensity dependent. Other motion sensors, such as accelerometers, have the ability to quantify activity intensity, but their higher cost has largely prohibited their use in population studies.

Rather than measure physical activity directly, some population-based studies have measured different facets of physical fitness, such as cardiorespiratory fitness. While the facets of physical fitness are known to be influenced by genetic factors, they can be objectively measured and are considered to be acceptable surrogate measures of fitness-related physical activity patterns in adults 6, 7, 8.

Despite the growing choice of measurement options, few studies have directly compared the usefulness of a range of both subjective and objective physical activity measures in quantifying associations with health outcomes. Such data are needed to make informed decisions in selecting the most appropriate measure of physical activity for a given health outcome. Toward this end, this study compared associations between physical activity and cardiovascular risk factors across a range of physical activity and fitness measures.

Section snippets

Study Sample

Data for these cross-sectional analyses were collected in the period 2004–2006 from Australian adults (aged 26–36 years) as part of the Childhood Determinants of Adult Health Study, a follow-up of the 1985 Australian Schools Health and Fitness Survey (N = 8,498; age 7–15 years). Details of the 1985 sampling strategies have been described elsewhere (9). At follow-up, 6,840 (80.5%) of the original participants were successfully traced and 5,170 (60.8%) were enrolled and provided data to the

Results

Summary measures of physical activity, fitness, and cardiometabolic health are described in Table 1. The interrelationship between the alternative measures of physical activity and fitness are presented by sex in Table 2. IPAQ total activity was more strongly associated with self-reported sitting time and pedometer steps than with other non-IPAQ measures of physical activity. In men, IPAQ work activity was more strongly associated with objectively measured pedometer steps and self-reported time

Discussion

Results from this study are useful in evaluating several important issues related to the measurement of physical activity in epidemiological studies. One key issue addressed was the comparative strength of associations using subjective versus objective measures of physical activity. Prior studies have consistently reported weaker associations between self-reported physical activity and cardiovascular health outcomes than those observed using objective measures of aerobic fitness (6). A common

References (27)

  • W.E. Siri

    The gross composition of the body

    Adv Biol Med Phys

    (1956)
  • K.G. Alberti et al.

    The metabolic syndrome—a new worldwide definition

    Lancet

    (2005)
  • J.F. Sallis et al.

    Assessment of physical activity by self-report: status, limitations, and future directions

    Res Q Exerc Sport

    (2000)
  • S.A. Adams et al.

    The effect of social desirability and social approval on self-reports of physical activity

    Am J Epidemiol

    (2005)
  • R.J. Shephard

    Limits to the measurement of habitual physical activity by questionnaires

    Br J Sports Med

    (2003)
  • T. Dwyer et al.

    The inverse relationship between number of steps per day and obesity in a population-based sample: the AusDiab study

    Int J Obes (Lond)

    (2007)
  • K.F. Janz

    Physical activity in epidemiology: moving from questionnaire to objective measurement

    Br J Sports Med

    (2006)
  • S.N. Blair et al.

    Is physical activity or physical fitness more important in defining health benefits?

    Med Sci Sports Exerc

    (2001)
  • C. Bouchard et al.

    Genetics of aerobic and anaerobic performances

    Exerc Sport Sci Rev

    (1992)
  • R.S. Paffenbarger et al.

    Measurement of physical activity to assess health effects in free-living populations

    Med Sci Sports Exerc

    (1993)
  • J.E. Pyke

    Australian Health and Fitness Survey 1985

    (1987)
  • D.R. Matthews et al.

    Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man

    Diabetologia

    (1985)
  • C.L. Craig et al.

    International physical activity questionnaire: 12-country reliability and validity

    Med Sci Sports Exerc

    (2003)
  • Cited by (81)

    • Lifestyle Interventions

      2018, Chronic Coronary Artery Disease: A Companion to Braunwald's Heart Disease
    View all citing articles on Scopus
    View full text