Evidence map›Paper›PMID 33372896›Full record

ArticleJMIR mHealth and uHealth2020

Comparison of the Physical Activity Measured by a Consumer Wearable Activity Tracker and That Measured by Self-Report: Cross-Sectional Analysis of the Health eHeart Study.

Alexander J Beagle, Geoffrey H Tison, Kirstin Aschbacher, Jeffrey E Olgin, Gregory M Marcus, Mark J Pletcher

Abstract readComparative Study
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Observational
  13. Article
  14. Article
  15. Article
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

6 authors.

Alexander J BeagleDepartment of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0002-2291-2612
Geoffrey H TisonDivision of Cardiology, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0002-0310-3326
Kirstin AschbacherDivision of Cardiology, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0001-6191-6432
Jeffrey E OlginDivision of Cardiology, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0003-1684-9327
Gregory M MarcusDivision of Cardiology, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0001-5197-7696
Mark J PletcherDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0002-6966-1312

Funding

ZIDOVUDINE &LAMIVUDINE &NEVIRAPINE COMBINATION THERAPY IN HIV 1 INFM01RR001271 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KESSLER, DAVID A · 1985 to 2006
$22.7M
UCSF Nutrition Obesity Research CenterP30DK098722 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHRISTIAN VAISSE · 2015 to 2026
$14.6M
NCRR NIH HHS M01 RR001271NIDDK NIH HHS P30 DK098722
6 · The paper itself

Abstract

backgroundCommercially acquired wearable activity trackers such as the Fitbit provide objective, accurate measurements of physically active time and step counts, but it is unclear whether these measurements are more clinically meaningful than self-reported physical activity.

objectiveThe aim of this study was to compare self-reported physical activity to Fitbit-measured step counts and then determine which is a stronger predictor of BMI by using data collected over the same period reflecting comparable physical activities.

methodsWe performed a cross-sectional analysis of data collected by the Health eHeart Study, a large mobile health study of cardiovascular health and disease. Adults who linked commercially acquired Fitbits used in free-living conditions with the Health eHeart Study and completed an International Physical Activity Questionnaire (IPAQ) between 2013 and 2019 were enrolled (N=1498). Fitbit step counts were used to quantify time by activity intensity in a manner comparable to the IPAQ classifications of total active time and time spent being sedentary, walking, or doing moderate activities or vigorous activities. Fitbit steps per day were computed as a measure of the overall activity for exploratory comparisons with IPAQ-measured overall activity (metabolic equivalent of task [MET]-h/wk). Measurements of physical activity were directly compared by Spearman rank correlation. Strengths of associations with BMI for Fitbit versus IPAQ measurements were compared using multivariable robust regression in the subset of participants with BMI and covariates measured.

resultsCorrelations between synchronous paired measurements from Fitbits and the IPAQ ranged in strength from weak to moderate (0.09-0.48). In the subset with BMI and covariates measured (n=586), Fitbit-derived predictors were generally stronger predictors of BMI than self-reported predictors. For example, an additional hour of Fitbit-measured vigorous activity per week was associated with nearly a full point reduction in BMI (-0.84 kg/m

conclusionsFitbit-measured physical activity was more strongly associated with BMI than self-reported physical activity, particularly for moderate activity, vigorous activity, and summary measures of total activity. Consumer-marketed wearable activity trackers such as the Fitbit may be useful for measuring health-relevant physical activity in clinical practice and research.

Indexed as

ExerciseFitness TrackersSelf ReportAdultBody Mass IndexCross-Sectional StudiesFemaleHumansMaleMiddle AgedWalkingadultbody mass indexcardiovascular diseasesexercisefitness trackersmHealthobesityoverweightpublic healthself-report

Identifiers

PMID33372896
PMCPMC7803477

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.