Evidence map›Paper›PMID 38835721›Full record

ArticleThe annals of applied statistics2023

A RIEMANN MANIFOLD MODEL FRAMEWORK FOR LONGITUDINAL CHANGES IN PHYSICAL ACTIVITY PATTERNS.

Jingjing Zou, Tuo Lin, Chongzhi Di, John Bellettiere, Marta M Jankowska, Sheri J Hartman, Dorothy D Sears, Andrea Z LaCroix, Cheryl L Rock, Loki Natarajan

Abstract read
In one paragraph

Article in The annals of applied statistics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Jingjing ZouHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego.
Tuo LinHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego.
Chongzhi DiDivision of Public Health Sciences, Fred Hutchinson Cancer Cente.
John BellettiereHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego.
Marta M JankowskaDepartment of Population Sciences, Beckman Research Institute, City of Hope.
Sheri J HartmanHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego.
Dorothy D SearsCollege of Health Solutions, Arizona State University.
Andrea Z LaCroixHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego.
Cheryl L RockDepartment of Family Medicine, University of California, San Diego.
Loki NatarajanHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego.

Funding

UCSD Biorepository Shared ResourceU54CA155435 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PATTERSON, RUTH E · 2011 to 2015
$9.1M
Sedentary Behaviour Interrupted: Acute, medium and long-term effects on biomarkers of healthy aging, physical function and mortalityP01AG052352 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LACROIX, ANDREA Z. · 2017 to 2022
$9.0M
Novel computational techniques to detect the relationship between sitting patterns and metabolic syndrome in existing cohort studies.R01DK114945 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NATARAJAN, LOKI · 2018 to 2021
$2.6M
NCI NIH HHS U54 CA155435NIA NIH HHS P01 AG052352NIDDK NIH HHS R01 DK114945
6 · The paper itself

Abstract

Physical activity (PA) is significantly associated with many health outcomes. The wide usage of wearable accelerometer-based activity trackers in recent years has provided a unique opportunity for in-depth research on PA and its relations with health outcomes and interventions. Past analysis of activity tracker data relies heavily on aggregating minute-level PA records into day-level summary statistics in which important information of PA temporal/diurnal patterns is lost. In this paper we propose a novel functional data analysis approach based on Riemann manifolds for modeling PA and its longitudinal changes. We model smoothed minute-level PA of a day as one-dimensional Riemann manifolds and longitudinal changes in PA in different visits as deformations between manifolds. The variability in changes of PA among a cohort of subjects is characterized via variability in the deformation. Functional principal component analysis is further adopted to model the deformations, and PC scores are used as a proxy in modeling the relation between changes in PA and health outcomes and/or interventions. We conduct comprehensive analyses on data from two clinical trials: Reach for Health (RfH) and Metabolism, Exercise and Nutrition at UCSD (MENU), focusing on the effect of interventions on longitudinal changes in PA patterns and how different modes of changes in PA influence weight loss, respectively. The proposed approach reveals unique modes of changes, including overall enhanced PA, boosted morning PA, and shifts of active hours specific to each study cohort. The results bring new insights into the study of longitudinal changes in PA and health and have the potential to facilitate designing of effective health interventions and guidelines.

Indexed as

accelerometerActivity trackersfunctional data analysisfunctional principal component analysislongitudinal analysisRiemann manifold

Identifiers

PMID38835721
PMCPMC11149895

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Registered trials

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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.