Evidence map›Paper›PMID 27108078›Full record

ArticleBMC musculoskeletal disorders2016

Socioeconomic disparities in gait speed and associated characteristics in early old age.

S Plouvier, M Carton, D Cyr, S Sabia, A Leclerc, M Zins, A Descatha

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

  1. Pooled it
  2. Area Deprivation Index and Frailty Among Older People With HIV.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2025
    Article
  3. Article
  4. Article
  5. RGB-Depth Camera-Based Assessment of Motor Capacity: Normative Data for Six Standardized Motor Tasks.International journal of environmental research and public health · 2022
    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

7 authors.

S PlouvierInserm UVSQ, Population-based Epidemiologic Cohorts Unit, UMS 011, F-94807, Villejuif, France.
M CartonInserm UVSQ, Population-based Epidemiologic Cohorts Unit, UMS 011, F-94807, Villejuif, France.
D CyrInserm UVSQ, Population-based Epidemiologic Cohorts Unit, UMS 011, F-94807, Villejuif, France.
S SabiaDepartment of Epidemiology & Public Health, University College London, London, UK.
A LeclercInserm UVSQ, Population-based Epidemiologic Cohorts Unit, UMS 011, F-94807, Villejuif, France.
M ZinsInserm UVSQ, Population-based Epidemiologic Cohorts Unit, UMS 011, F-94807, Villejuif, France.
A DescathaInserm UVSQ, Population-based Epidemiologic Cohorts Unit, UMS 011, F-94807, Villejuif, France. alexis.descatha@inserm.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA few studies have documented associations between socioeconomic position and gait speed, but the knowledge about factors from various domains (personal factors, lifestyle, occupation…) which contribute to these disparities is limited. Our objective was to assess socioeconomic disparities in usual gait speed in a general population in early old age in France, and to identify potential contributors to the observed disparities, including occupational factors.

methodsThe study population comprised 397 men and 339 women, aged 55 to 69, recruited throughout France for the field pilot of the CONSTANCES cohort. Gait speed was measured in meters/second. Socioeconomic position was based on self-reported occupational class. Information on personal characteristics, lifestyle, comorbidities and past or current occupational physical exposure came either from the health examination, from interview or from self-administered questionnaire. Four groups were considered according to sex-specific distributions of speed (the two slowest thirds versus the fastest third, for each gender). Logistic regression models adjusted for health screening center and age allowed to the study of cross-sectional associations between: 1- slower speed and occupational class; 2- slower speed and each potential contributor; 3- occupational class and selected potential contributors. The association between speed and occupational class was then further adjusted for the factors significantly associated both with speed and occupational class, in order to assess the potential contribution of these factors to disparities.

resultsWith reference to managers/executives, gait speed was reduced in less skilled categories among men (OR 1.21 [0.72-2.05] for Intermediate/Tradesmen, 1.95 [0.80-4.76] for Clerks, Sale/service workers, 2.09 [1.14-3.82] for Blue collar/Craftsmen) and among women (OR 1.12 [0.55-2.28] for Intermediate/Tradesmen, 2.33 [1.09-4.97] for Clerks, 2.48 [1.18-5.24] for Sale/service workers/Blue collar/Craftsmen). Among men, occupational exposure to carrying heavy loads explained a large part of socioeconomic disparities. Among women, obesity and occupational exposure to repetitive work contributed independently to the disparities.

conclusionsThis study suggests that some potentially modifiable occupational and personal factors explain at least part of the differences in gait speed between occupational classes, and that these factors differ between men and women. Longitudinal studies are needed to confirm and complement these findings.

Indexed as

Health Status DisparitiesSocioeconomic FactorsAgedCohort StudiesCross-Sectional StudiesFemaleFollow-Up StudiesFranceHumansLife StyleMaleMiddle AgedOccupational ExposureOccupationsPilot ProjectsRisk FactorsOccupational exposureSocioeconomic positionUsual gait speed

Identifiers

PMID27108078
PMCPMC4842278

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.