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Barbara Sternfeld and Lisa Goldman-Rosas

Context:

Numerous instruments to measure self-reported physical activity (PA) exist, but there is little guidance for determining the most appropriate choice.

Objective:

To provide a systematic framework for researchers and practitioners to select a self-reported PA instrument.

Process:

The framework consists of 2 components: a series of questions and a database of instruments. The questions encourage users to think critically about their specific needs and to appreciate the strengths and limitations of the available options. Instruments for the database were identified through existing literature and expert opinion.

Findings:

Ten questions, ranging from study aim and study design to target population and logistical consideration, guide the researcher or practitioner in defining the criteria for an appropriate PA instruments for a given situation. No one question on its own determines the optimal choice, but taken together, they narrow the potential field. The database currently includes 38 different self-reported PA instruments, characterized by 18 different parameters.

Conclusions:

The series of questions presented here, in conjunction with a searchable database of self-report PA instruments, provides a needed step toward the development of guiding principles and good practices for researchers and practitioners to follow in making an informed selection of a self-reported PA instrument.

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Sheila A. Dugan, Susan A. Everson-Rose, Kelly Karavolos, Barbara Sternfeld, Deidre Wesley and Lynda H. Powell

Background:

This study was done to determine whether physical activity at baseline is independently associated with musculoskeletal pain and fulfilling one’s physical role over 3 subsequent years.

Methods:

Our research involved a 3-year longitudinal study of over 2400 community-dwelling, midlife women from the Study of Women’s Health Across the Nation (SWAN). Measurements included baseline physical activity using the Kaiser Permanente Health Plan Activity Survey and SF-36 role-physical and bodily pain indices at each of 3 annual follow-up visits.

Results:

Each 1-point increase on the physical activity score was associated with a 7% greater likelihood of a high role-physical score (95% CI = 1.02– 1.13) and a 10% greater likelihood of a low bodily pain score (95% CI = 1.04–1.17) after adjusting for age, race, menopausal status, educational level, body mass index, depressive symptoms, smoking, and chronic medical conditions. The association between physical activity level and role-physical score was eliminated in the fully adjusted model after adjustment for pain level in post hoc analysis [OR = 1.04 (95% CI = 0.98–1.09)].

Conclusion:

This study demonstrates that women who are more physically active at midlife experience less bodily pain over time regardless of menopausal status, sociodemographics, and medical conditions. Higher physical activity level positively impacts fulfilling one’s physical role; however, this is mediated by pain level.

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Richard P. Troiano, Kelley K. Pettee Gabriel, Gregory J. Welk, Neville Owen and Barbara Sternfeld

Context:

Advances in device-based measures have led researchers to question the value of reported measures of physical activity or sedentary behavior. The premise of the Workshop on Measurement of Active and Sedentary Behaviors: Closing the Gaps in Self-Report Methods, held in July 2010, was that assessment of behavior by self-report is a valuable approach.

Objective:

To provide suggestions to optimize the value of reported physical activity and sedentary behavior, we 1) discuss the constructs that devices and reports of behavior can measure, 2) develop a framework to help guide decision-making about the best approach to physical activity and sedentary behavior assessment in a given situation, and 3) address the potential for combining reported behavior methods with device-based monitoring to enhance both approaches.

Process:

After participation in a workshop breakout session, coauthors summarized the ideas presented and reached consensus on the material presented here.

Conclusions:

To select appropriate physical activity assessment methods and correctly interpret the measures obtained, researchers should carefully consider the purpose for assessment, physical activity constructs of interest, characteristics of the population and measurement tool, and the theoretical link between the exposure and outcome of interest.

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Kelley Pettee Gabriel, Adriana Pérez, David R. Jacobs Jr, Joowon Lee, Harold W. Kohl III and Barbara Sternfeld

Background: Single-method assessment of physical activity (PA) has limitations. The utility and cross-validation of a composite PA score that includes reported and accelerometer-derived PA data has not been evaluated. Methods: Participants attending the Year 20 exam were randomly assigned to the derivation (two-thirds) or validation (one-third) data set. Principal components analysis was used to create a composite score reflecting Year 20 combined reported and accelerometer PA data. Generalized linear regression models were constructed to estimate the variability explained (R2) by each PA assessment strategy (self-report only, accelerometer only, composite score, or self-report plus accelerometer) with cardiovascular health indicators. This process was repeated in the validation set to determine cross-validation. Results: At Year 20, 3549 participants (45.2 [3.6] y, 56.7% female, and 53.5% black) attended the clinic exam and 2540 agreed to wear the accelerometer. Higher R2 values were obtained when combined assessment strategies were used; however, the approach yielding the highest R2 value varied by cardiovascular health outcome. Findings from the cross-validation also supported internal study validity. Conclusions: Findings support continued refinement of methodological approaches to combine data from multiple sources to create a more robust estimate that reflects the complexities of PA behavior.