Certainty of the Global Burden of Disease 2019 Modelled Prevalence Estimates for Musculoskeletal Conditions: A Meta-Epidemiological Study

Javier Muñoz Laguna; Milo A Puhan; Fernando Rodríguez Artalejo; Robby De Pauw; Grant M A Wyper; Brecht Devleesschauwer; João V Santos; Cesar A Hincapié

doi:10.3389/ijph.2023.1605763

Certainty of the Global Burden of Disease 2019 Modelled Prevalence Estimates for Musculoskeletal Conditions: A Meta-Epidemiological Study

Int J Public Health. 2023 May 31:68:1605763. doi: 10.3389/ijph.2023.1605763. eCollection 2023.

Authors

Javier Muñoz Laguna^{1

2

3

4}, Milo A Puhan², Fernando Rodríguez Artalejo^{1

5

6}, Robby De Pauw^{7

8}, Grant M A Wyper^{9

10}, Brecht Devleesschauwer^{7

11}, João V Santos^{12

13

14}, Cesar A Hincapié^{2

3

4}

Affiliations

¹ Department of Preventive Medicine, Public Health and Microbiology, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain.
² Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
³ University Spine Centre Zurich (UWZH), Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
⁴ EBPI-UWZH Musculoskeletal Epidemiology Research Group, University of Zurich and Balgrist University Hospital, Zurich, Switzerland.
⁵ CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain.
⁶ IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain.
⁷ Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
⁸ Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium.
⁹ School of Health & Wellbeing, University of Glasgow, Glasgow, United Kingdom.
¹⁰ Place and Wellbeing Directorate, Public Health Scotland, Glasgow, United Kingdom.
¹¹ Department of Translational Physiology, Infectiology and Public Health, Ghent University, Merelbeke, Belgium.
¹² MEDCIDS-Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal.
¹³ CINTESIS-Centre for Health Technology and Services Research, Porto, Portugal.
¹⁴ Public Health Unit, ACES Grande Porto V - Porto Ocidental, ARS Norte, Porto, Portugal.

Abstract

Objectives: To describe and assess the risk of bias of the primary input studies that underpinned the Global Burden of Disease Study (GBD) 2019 modelled prevalence estimates of low back pain (LBP), neck pain (NP), and knee osteoarthritis (OA), from Australia, Brazil, Canada, Spain, and Switzerland. To evaluate the certainty of the GBD modelled prevalence evidence. Methods: Primary studies were identified using the GBD Data Input Sources Tool and their risk of bias was assessed using a validated tool. We rated the certainty of modelled prevalence estimates based on the GRADE Guidelines 30-the GRADE approach for modelled evidence. Results: Seventy-two primary studies (LBP: 67, NP: 2, knee OA: 3) underpinned the GBD estimates. Most studies had limited representativeness of their study populations, used suboptimal case definitions and applied assessment instruments with unknown psychometric properties. The certainty of modelled prevalence estimates was low, mainly due to risk of bias and indirectness. Conclusion: Beyond the risk of bias of primary input studies for LBP, NP, and knee OA in GBD 2019, the certainty of country-specific modelled prevalence estimates still have room for improvement.

Keywords: GRADE approach; epidemiology; global burden of disease; knee osteoarthritis; low back pain; musculoskeletal disorders; neck pain; prevalence.

Publication types

Review

MeSH terms

Kanada
Global Burden of Disease*
Humans
Prevalence
Spain / epidemiology
Switzerland / epidemiology

Grants and funding

This work was supported, in part, by the European Cooperation in Science and Technology (COST Action CA18218 virtual mobility grant No CA18218-6a68cbf4). The funder had no role in study conceptualisation and design, or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the manuscript for publication.