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Development and Testing of an Integrated Score for Physical Behaviors

KEADLE, SARAH KOZEY1; KRAVITZ, ELI S.2; MATTHEWS, CHARLES E.3; TSENG, MARILYN1; CARROLL, RAYMOND J.2,4

Medicine & Science in Sports & Exercise: August 2019 - Volume 51 - Issue 8 - p 1759–1766
doi: 10.1249/MSS.0000000000001955
SPECIAL COMMUNICATIONS: Methodological Advances
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Purpose Interest in a variety of physical behaviors (e.g., exercise, sitting time, sleep) in relation to health outcomes creates a need for new statistical approaches to analyze the joint effects of these distinct but inter-related physical behaviors. We developed and tested an integrated physical behavior score (PBS).

Methods National Institutes of Health-American Association of Retired Persons Diet and Health Study participants (N = 163,016) completed a questionnaire (2004–2006) asking about time spent in five exercise and nonexercise physical activities, two sedentary behaviors (television and nontelevision), and sleep. In half of the sample, we used shape-constrained additive regression to model the relationship between each behavior and survival. Maximum logit scores from each of the eight behavior-survival functions were summed to produce a PBS that was proportionally rescaled to range from 0 to 100. We examined predictive validity of the PBS in the other half-sample using Cox Proportional Hazards models after adjustment for covariates for all-cause and cause-specific mortality.

Results In the testing sample, over an average of 6.6 yr of follow-up, 8732 deaths occurred. We found a strong graded decline in risk of all-cause mortality across quintiles of PBS (Q5 vs Q1 hazard ratio [95% CI] = 0.53 [0.49, 0.57]). Risk estimates for the PBS were higher than any of the components in isolation. Results were similar but stronger for cardiovascular disease (Q5 vs Q1 = 0.42 [0.39, 0.48]) and other mortality (Q5 vs Q1 = 0.42 [0.36, 0.48]). The relationship between PBS and mortality was observed in stratified analyses by median age, sex, body mass index, and health status.

Conclusions We developed a novel statistical method generated a composite physical behavior that is predictive of mortality outcomes. Future research is needed to test this approach in an independent sample.

1Department of Kinesiology and Public Health, California Polytechnic State University, San Luis Obispo, CA;

2Department of Statistics, Texas A&M University, College Station, TX;

3Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD; and

4School of Mathematical and Physical Sciences, University of Technology Sydney, Sydney, AUSTRALIA

Address for correspondence: Sarah Kozey Keadle, Ph.D., M.P.H., 1 Grand Ave, San Luis Obispo, CA 93407; E-mail: skeadle@calpoly.edu.

Submitted for publication September 2018.

Accepted for publication February 2019.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.acsm-msse.org).

Online date: February 27, 2019

© 2019 American College of Sports Medicine