Evidence map›Paper›PMID 39224205›Full record

ArticleBMJ open sport & exercise medicine2024

Physical activity modification over time according to socioeconomic position: results from the EPIC-Italy cohort study.

Matteo Franco, Luigi Facchini, Carlotta Sacerdote, Giovanna Masala, Luca Manfredi, Lucia Dansero, Benedetta Bendinelli, Melania Assedi, Valentina Vitale, Valeria Pala and 2 more

Abstract read
In one paragraph

Article in BMJ open sport & exercise medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Understanding barriers and facilitators of adherence to lifestyle changes in prediabetes: a qualitative study.International journal of qualitative studies on health and well-being · 2026
    Observational
  2. 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

12 authors.

Matteo FrancoDepartment of Clinical and Biological Sciences, University of Turin, Orbassano, Turin, Italy.ORCID 0009-0004-1687-4893
Luigi FacchiniInstitute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy.
Carlotta SacerdoteUnit of Cancer Epidemiology, Città Della Salute e Della Scienza University-Hospital and Center for Cancer Prevention (CPO), Città della Salute, Turin, Italy.
Giovanna MasalaInstitute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy.
Luca ManfrediDepartment of Clinical and Biological Sciences, University of Turin, Orbassano, Turin, Italy.
Lucia DanseroDepartment of Clinical and Biological Sciences, University of Turin, Orbassano, Turin, Italy.
Benedetta BendinelliInstitute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy.
Melania AssediInstitute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy.
Valentina VitaleDepartment of Research, Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Valeria PalaDepartment of Research, Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Saverio CainiInstitute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy.
Fulvio RicceriDepartment of Clinical and Biological Sciences, University of Turin, Orbassano, Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Our study aimed to investigate how physical activity (PA) changes over an 11-year follow-up among adults from different socioeconomic positions (SEP) near retirement age. Moreover, an analysis of different PA types is considered. Methods: We used data from the EPIC-Italy cohort. We evaluated PA using the Cambridge Physical Activity Index (CPAI) and the metabolic equivalent of tasks (MET) per hour of activity for recreational PA and household PA. Educational level was assessed using the Relative Index of Inequality (RII). Occupational classes were classified according to LIFEPATH Consortium knowledge. Logistic regression was used to analyse PA among SEP and changes during follow-up. Analyses were also conducted separately for sex. Results: The higher educated were more prevalent in the higher quartile of recreational PA than the lower educated both at baseline and follow-up (37% vs 28% and 37% vs 27%, respectively). At the baseline, the lower educated had a higher risk of being physically inactive than the higher educated based on recreational PA (overall OR: 1.50, 95% CI 1.40 to 1.60). Manual workers did not show a higher risk of less PA than professionals/managers (overall OR: 1.03, 95% CI 0.91 to 1.16).At follow-up, the lower educated and manual workers showed a higher risk of being physically inactive (lower educated OR: 1.46, 95% CI 1.37 to 1.56; manual worker OR: 1.33, 95% CI 1.18 to 1.50). The analyses of changes in PA showed that those who were less educated or manual workers had a higher risk of worsening their PA during the follow-up period, particularly women in recreational PA and men in CPAI measurement. Conclusion: Individuals who had a disadvantaged SEP showed a higher risk of performing less PA over time.

Indexed as

EducationExercisePhysical activityPublic health

Identifiers

PMID39224205
PMCPMC11367325

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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.