Evidence map›Paper›PMID 30817711›Full record

ArticleMedicine and science in sports and exercise2019

Development and Testing of an Integrated Score for Physical Behaviors.

Sarah Kozey Keadle, Eli S Kravitz, Charles E Matthews, Marilyn Tseng, Raymond J Carroll

Abstract read
In one paragraph

Article in Medicine and science in sports and exercise, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Validity and reliability of self-reported methods for assessment of 24-h movement behaviours: a systematic review.The international journal of behavioral nutrition and physical activity · 2024
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sarah Kozey KeadleDepartment of Kinesiology and Public Health, California Polytechnic State University, San Luis Obispo, CA.
Eli S KravitzDepartment of Statistics, Texas A&M University, College Station, TX.
Charles E MatthewsMetabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.
Marilyn TsengDepartment of Kinesiology and Public Health, California Polytechnic State University, San Luis Obispo, CA.
Raymond J CarrollDepartment of Statistics, Texas A&M University, College Station, TX.

Funding

Prospective Studies of Diet and Cancer in the AARP CohortZIACP010196 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI SINHA, RASHMI · 2009 to 2025
$21.0M
Physical Activity, Energy Balance, and CancerZIACP010197 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALBANES, DEMETRIUS · 2009 to 2025
$17.5M
Measurement Error, Nutrition, Physical Activity and CancerU01CA057030 · NCI · TEXAS A&M UNIVERSITY · PI CARROLL, RAYMOND J. · 2015 to 2019
$2.8M
MEASUREMENT ERROR, NUTRITION AND BREAST/COLON CANCERR01CA057030 · NCI · TEXAS A&M UNIVERSITY SYSTEM · PI CARROLL, RAYMOND J. · 1992 to 2004
$1.3M
Intramural NIH HHS Z99 CA999999Intramural NIH HHS ZIA CP010196NCI NIH HHS R01 CA057030NCI NIH HHS U01 CA057030
6 · The paper itself

Abstract

purposeInterest 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).

methodsNational 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.

resultsIn 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.

conclusionsWe 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.

Indexed as

MortalitySedentary BehaviorActivities of Daily LivingAgedExerciseFemaleHealth StatusHumansMaleMiddle AgedProspective StudiesRisk AssessmentSitting PositionSleepSurveys and QuestionnairesTelevision

Identifiers

PMID30817711
PMCPMC6629509

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.