Evidence map›Paper›PMID 35476038›Full record

ArticleJMIR cardio2022

Relations Between BMI Trajectories and Habitual Physical Activity Measured by a Smartwatch in the Electronic Cohort of the Framingham Heart Study: Cohort Study.

Michael M Hammond, Yuankai Zhang, Chathurangi H Pathiravasan, Honghuang Lin, Mayank Sardana, Ludovic Trinquart, Emelia J Benjamin, Belinda Borrelli, Emily S Manders, Kelsey Fusco and 7 more

Abstract read
In one paragraph

Article in JMIR cardio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
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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

17 authors.

Michael M HammondBoston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.ORCID https://orcid.org/0000-0002-0157-4458
Yuankai ZhangDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID https://orcid.org/0000-0002-2318-7539
Chathurangi H PathiravasanDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID https://orcid.org/0000-0003-2170-1247
Honghuang LinDivision of Clinical Informatics, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States.ORCID https://orcid.org/0000-0003-3043-3942
Mayank SardanaCardiology Division, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-9465-1047
Ludovic TrinquartDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID https://orcid.org/0000-0002-3028-4900
Emelia J BenjaminBoston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.ORCID https://orcid.org/0000-0003-4076-2336
Belinda BorrelliDepartment of Health Policy & Health Services Research, Henry M Goldman School of Dental Medicine, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0002-0859-796X
Emily S MandersBoston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.ORCID https://orcid.org/0000-0001-9508-1541
Kelsey FuscoBoston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.ORCID https://orcid.org/0000-0002-8805-2520
Jelena KornejBoston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.ORCID https://orcid.org/0000-0003-3551-1145
Nicole L SpartanoSection of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, MA, United States.ORCID https://orcid.org/0000-0002-0724-8629
Vik KheterpalCare Evolution, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0002-4752-4229
Christopher NowakCare Evolution, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0003-1796-9558
David D McManusCardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States.ORCID https://orcid.org/0000-0002-9343-6203
Chunyu LiuDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID https://orcid.org/0000-0002-9160-0153
Joanne M MurabitoBoston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.ORCID https://orcid.org/0000-0002-0192-7516

Funding

The Center for Advancing Point of Care in Heart, Lung, Blood and Sleep DiseasesU54HL143541 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI BRYAN O BUCHHOLZ, Nathaniel Scott Hafer · 2018 to 2026
$141.0M
FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · 2019 to 2024
$29.8M
IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
ConProject-006U54HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BHATNAGAR, ARUNI, ROBERTSON, ROSE MARIE · 2018 to 2022
$18.8M
CAPSITE: Community Assessment of Pain and Sensitization in the ElderlyR01AG066010 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BENJAMIN, EMELIA J., EDWARDS, ROBERT R · 2020 to 2025
$3.3M
Detecting bleeding events using EHRs for prediction in AfibR01HL137794 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI MCMANUS, DAVID D., YU, HONG · 2018 to 2021
$3.3M
Systematic Assessment of Geriatric Elements in Atrial Fibrillation (SAGE-AF)R01HL126911 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI MCMANUS, DAVID D., SACZYNSKI, JANE STEELE · 2016 to 2019
$3.2M
Smartwatch Monitoring for Atrial Fibrillation After StrokeR01HL137734 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI CHON, KI H, MCMANUS, DAVID D. · 2018 to 2021
$3.1M
FHS-NEXT - Framingham Novel EXam using TechnologyR01HL141434 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BENJAMIN, EMELIA J., MCMANUS, DAVID D. · 2019 to 2022
$2.5M
NHLBI NIH HHS 75N92019D00031NHLBI NIH HHS R01 HL092577NHLBI NIH HHS R01 HL126911NHLBI NIH HHS R01 HL137734NHLBI NIH HHS R01 HL137794NHLBI NIH HHS R01 HL141434NHLBI NIH HHS U54 HL120163NHLBI NIH HHS U54 HL143541NIA NIH HHS R01 AG066010
6 · The paper itself

Abstract

backgroundThe prevalence of obesity is rising. Most previous studies that examined the relations between BMI and physical activity (PA) measured BMI at a single timepoint. The association between BMI trajectories and habitual PA remains unclear.

objectiveThis study assesses the relations between BMI trajectories and habitual step-based PA among participants enrolled in the electronic cohort of the Framingham Heart Study (eFHS).

methodsWe used a semiparametric group-based modeling to identify BMI trajectories from eFHS participants who attended research examinations at the Framingham Research Center over 14 years. Daily steps were recorded from the smartwatch provided at examination 3. We excluded participants with <30 days or <5 hours of smartwatch wear data. We used generalized linear models to examine the association between BMI trajectories and daily step counts.

resultsWe identified 3 trajectory groups for the 837 eFHS participants (mean age 53 years; 57.8% [484/837] female). Group 1 included 292 participants whose BMI was stable (slope 0.005; P=.75), group 2 included 468 participants whose BMI increased slightly (slope 0.123; P<.001), and group 3 included 77 participants whose BMI increased greatly (slope 0.318; P<.001). The median follow-up period for step count was 516 days. Adjusting for age, sex, wear time, and cohort, participants in groups 2 and 3 took 422 (95% CI -823 to -21) and 1437 (95% CI -2084 to -790) fewer average daily steps, compared with participants in group 1. After adjusting for metabolic and social risk factors, group 2 took 382 (95% CI -773 to 10) and group 3 took 1120 (95% CI -1766 to -475) fewer steps, compared with group 1.

conclusionsIn this community-based eFHS, participants whose BMI trajectory increased greatly over time took significantly fewer steps, compared with participants with stable BMI trajectories. Our findings suggest that greater weight gain may correlate with lower levels of step-based physical activity.

Indexed as

BMIcardiologycardiovascular diseasesdigital healthmHealthmobile healthmobile health appsphysical activitysmartwatch

Identifiers

PMID35476038
PMCPMC9096636

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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.