Cited by 1,034Physical Activity and HealthObesity, Physical Activity, DietSleep and related disorders

The DOI matches its Crossref record; 69 of the 70 references it cites were found in a registry or an index; none of the 50 sources its claims cite is checked for support yet.

Combined Effects of Time Spent in Physical Activity, Sedentary Behaviors and Sleep on Obesity and Cardio-Metabolic Health Markers: A Novel Compositional Data Analysis Approach

Open access
Chastin, Sebastien F. M., Palarea-Albaladejo, Javier, Dontje, Manon L., Skelton, Dawn A.·2015·PLOS ONE

Abstract

The associations between time spent in sleep, sedentary behaviors (SB) and physical activity with health are usually studied without taking into account that time is finite during the day, so time spent in each of these behaviors are codependent. Therefore, little is known about the combined effect of time spent in sleep, SB and physical activity, that together constitute a composite whole, on obesity and cardio-metabolic health markers. Cross-sectional analysis of NHANES 2005-6 cycle on N = 1937 adults, was undertaken using a compositional analysis paradigm, which accounts for this intrinsic codependence. Time spent in SB, light intensity (LIPA) and moderate to vigorous activity (MVPA) was determined from accelerometry and combined with self-reported sleep time to obtain the 24 hour time budget composition. The distribution of time spent in sleep, SB, LIPA and MVPA is significantly associated with BMI, waist circumference, triglycerides, plasma glucose, plasma insulin (all p<0.001), and systolic (p<0.001) and diastolic blood pressure (p<0.003), but not HDL or LDL. Within the composition, the strongest positive effect is found for the proportion of time spent in MVPA. Strikingly, the effects of MVPA replacing another behavior and of MVPA being displaced by another behavior are asymmetric. For example, re-allocating 10 minutes of SB to MVPA was associated with a lower waist circumference by 0.001% but if 10 minutes of MVPA is displaced by SB this was associated with a 0.84% higher waist circumference. The proportion of time spent in LIPA and SB were detrimentally associated with obesity and cardiovascular disease markers, but the association with SB was stronger. For diabetes risk markers, replacing SB with LIPA was associated with more favorable outcomes. Time spent in MVPA is an important target for intervention and preventing transfer of time from LIPA to SB might lessen the negative effects of physical inactivity.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Using NHANES 2005–6 data on 1,937 adults, this study applies compositional data analysis to the 24-hour time budget of sleep, sedentary behavior (SB), light activity (LIPA), and moderate-to-vigorous activity (MVPA). The overall composition is associated with most obesity and cardiometabolic markers, with MVPA generally favorable, SB detrimental, and effects of reallocating time being asymmetric.

Key findings

  • The 24-hour composition of sleep, SB, LIPA, and MVPA was significantly associated with BMI, waist circumference, triglycerides, plasma glucose, plasma insulin, HOMA, systolic blood pressure (all p<0.001), and diastolic blood pressure (p=0.003), but not HDL (p=0.121) or LDL (p=0.434).
  • Within the composition, MVPA showed the strongest favorable associations; for example, MVPA was associated with lower waist circumference (B = -2.96, p<0.001) and lower BMI (B = -0.98, p<0.001), while SB was associated with higher waist circumference (B = 2.41, p=0.023) and higher BMI (B = 1.40, p=0.002).
  • Reallocating 10 minutes was asymmetric: replacing 10 minutes of SB with MVPA was associated with 0.001% lower waist circumference, whereas displacing 10 minutes of MVPA with SB was associated with 0.84% higher waist circumference. For BMI, displacing 10 minutes of MVPA with SB changed BMI by 1.21%, while the opposite change was -0.001%.
  • For diabetes risk markers, replacing SB with LIPA was associated with more favorable outcomes; LIPA contrasted favorably with other behaviors for triglycerides (B = -0.21, p<0.001), plasma insulin (B = -0.13, p=0.033), and HOMA (B = -0.15, p=0.020).

Methods

  • Secondary cross-sectional analysis of NHANES 2005–6, including adults aged 21–64 with at least 5 valid days of accelerometry data; N=1,937 were available for analysis.
  • Sleep was self-reported; SB, LIPA, and MVPA were measured with an Actigraph 7164 accelerometer and classified using count thresholds (<100, 100–1951, and ≥1952 counts/min, respectively), then expressed as proportions of 24 hours and normalized to sum to one.
  • Compositional data analysis used isometric log-ratio transformations in linear regression models (CODA), compared with single-behavior models (SINGLE), and estimated effects of 10-minute time reallocations; confounders were retained by backward elimination if p<0.2, with analyses in R 3.1.1.

Limitations

  • The paper states that objective sleep data were unavailable, sleep was self-reported only for week/workdays while accelerometry was averaged over the whole week, and this likely introduced random error.
  • The paper states that accelerometer thresholds are less accurate for distinguishing SB from LIPA, that different thresholds might lead to different results, and that data loss from the full NHANES sample was around 50%, affecting representativity.
  • The paper states that cross-sectional analysis limits causal inference and that estimated effects reflect population shifts in time distribution rather than actual individual effects; it also notes that absolute estimates depend on confounding-variable values, though trends remained similar.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0139984

Cites

69 of 69 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 50 cited sources checked · 0 supported · 0 flagged

Show all 62 claims

  • It may state two separate claims as one. 51
  • Probably not a substantial claim. 13
59 of 59
  • The paper relies on this without support.

    The absolute values of the time re-allocation estimates will vary if computed around a different starting composition, but the direction and relative size of the effects should be the same.

    “The absolute values of these estimates will vary if the time re-allocation is computed around a different starting composition, but the direction and relative size of the effects should be the same.”
  • The paper relies on this without support.

    Self-reported sleep duration accurately reflects actual sleep time.

    “Sleep duration was self-reported as an integer from 1 to 24 hours in response to the question “How much sleep do you actually get at night on weekdays or workdays”.”
  • The paper relies on this without support.

    This study is the first to use compositional analysis to investigate associations between the relative distribution of time in physical behaviors and cardiometabolic health markers.

    “This study is the first to our knowledge to use a compositional analysis to provide a statistically sound and comprehensive investigation of the associations between the relative distribution of time spent in different physical behaviors that make up the day and cardio-metabolic health markers.”
  • The paper relies on this without support.

    Humans cannot perform MVPA all day.

    “Humans cannot perform MVPA all day, therefore, although LIPA might be detrimental, spending the rest of the day in LIPA might be better than sitting (SB).”
  • The paper relies on this without support.

    Activity patterns can be different at weekends or non-working days.

    “It is known that activity patterns can be different at weekends or non-working days.”
  • The paper relies on this without support.

    Sleep duration varies at weekends or non-working days depending on chronotypes.

    “Similarly sleep duration varies at weekends or non-working days depending on chronotypes.”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Claimed detrimental SB effect on CRP reverses the table's direction

    Major

    The text describes a negative health effect on CRP when SB replaces MVPA. In Table 4, that replacement changes Log(CRP) by -0.950, indicating lower CRP.

  • BMI plot is cited as Fig 6B instead of Fig 16B

    Minor

    The cited reciprocal BMI plot is described as panel B of Fig 16. Fig 6 concerns LDL concentration groups.

  • BMI coefficient for MVPA differs from Table 3

    Minor

    The results text gives the CODA coefficient for MVPA as -0.098, while Table 3 reports -0.98-a tenfold difference.

3 of 3

Citations

Cites

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1 of the 70 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Zeljko Pedisic, 2014, Measurement issues and poor adjustments for physical activity and sleep undermine sedentary behaviour research, Kinesiology, 46, 135

Cited by

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Metadata

Authors
Chastin, S. F. M., Palarea-Albaladejo, J., Dontje, M. L., & Skelton, D. A.
Affiliations
Glasgow Caledonian University (GB)
Corresponding author
Chastin, Sebastien F. M.
Venue
PLOS ONE
Published
2015-10-13
Volume
10
Issue
10
Pages
e0139984
ISSN
1932-6203 (ISSN-L)
OpenAlex
W1818552750
Cited by
1,034
References
70
Citations by year
2026: 81 · 2025: 115 · 2024: 124 · 2023: 108 · 2022: 90 · 2021: 109 · 2020: 140 · 2019: 90 · 2018: 72 · 2017: 67 · 2016: 36
FWCI
42.99
Type
journal article
Language
en
Open access
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • ResearchOnline (Glasgow Caledonian University) (acceptedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • Rural and Environment Science and Analytical Services Division
  • Scottish Government
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
Keywords
physical activity, sedentary behavior, sleep, time budget, compositional data analysis, obesity, cardiometabolic health, waist circumference, blood pressure, insulin, triglycerides, light physical activity, moderate-to-vigorous physical activity, time displacement, diabetes risk, NHANES
MeSH terms
Adult, Behavior, Blood Glucose, Blood Pressure, C-Reactive Protein, Diastole, Fasting, Humans, Insulin, Lipids, Middle Aged, Motor Activity, Obesity, Sleep, Statistics as Topic, Systole, Time Factors, Body Mass Index, Linear Models, Waist Circumference, Young Adult, Sedentary Behavior

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