IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i3p1136-d488338.html
   My bibliography  Save this article

Reliability of a Risk-Factor Questionnaire for Osteoporosis: A Primary Care Survey Study with Dual Energy X-ray Absorptiometry Ground Truth

Author

Listed:
  • Maria Radeva

    (Institute of Diagnostic and Interventional Radiology, Jena University Hospital—Friedrich Schiller University Jena, Am Klinikum 1, 07747 Jena, Germany)

  • Dorothee Predel

    (Institute of Radiology, Suedharz Hospital Nordhausen, Dr.-Robert-Koch-Str. 39, 99734 Nordhausen, Germany
    Current address: Department for Nuclear Medicine, Central Hospital Bad Berka, Robert-Koch-Allee 9, 99437 Bad Berka, Germany.)

  • Sven Winzler

    (Institute of Radiology, Suedharz Hospital Nordhausen, Dr.-Robert-Koch-Str. 39, 99734 Nordhausen, Germany)

  • Ulf Teichgräber

    (Institute of Diagnostic and Interventional Radiology, Jena University Hospital—Friedrich Schiller University Jena, Am Klinikum 1, 07747 Jena, Germany)

  • Alexander Pfeil

    (Department of Internal Medicine III, Jena University Hospital—Friedrich Schiller University Jena, Am Klinikum 1, 07747 Jena, Germany)

  • Ansgar Malich

    (Institute of Radiology, Suedharz Hospital Nordhausen, Dr.-Robert-Koch-Str. 39, 99734 Nordhausen, Germany)

  • Ismini Papageorgiou

    (Institute of Diagnostic and Interventional Radiology, Jena University Hospital—Friedrich Schiller University Jena, Am Klinikum 1, 07747 Jena, Germany
    Institute of Radiology, Suedharz Hospital Nordhausen, Dr.-Robert-Koch-Str. 39, 99734 Nordhausen, Germany)

Abstract

(1) Purpose: Predisposing factors to osteoporosis (OP) as well as dual-source x-ray densitometry (DXA) steer therapeutic decisions by determining the FRAX index. This study examines the reliability of a standard risk factor questionnaire in OP-screening. (2) Methods: n = 553 eligible questionnaires encompassed 24 OP-predisposing factors. Reliability was assessed using DXA as a gold standard. Multiple logistic regression and Spearman’s correlations, as well as the confounding influence of age and body mass index, were analyzed in SPSS (IBM Corporation, Armonk, NY, USA). (3) Results: Our study revealed low patient self-awareness regarding OP and its risk factors. One out of every four patients reported a positive history for osteoporosis not confirmed by DXA. The extraordinarily high incidence of rheumatoid arthritis and thyroid disorders likely reflect confusion with other diseases or health anxiety. FRAX-determining risk factors such as malnutrition, liver insufficiency, prior fracture without trauma, and glucocorticoid therapy did not correlate with increased OP incidence, altogether demonstrating how inaccurate survey information could influence therapeutic decisions on osteoporosis. (4) Conclusions: Contradictive results and a low level of patient self-awareness suggest a high degree of uncertainty and low reliability of the current OP risk factor survey.

Suggested Citation

  • Maria Radeva & Dorothee Predel & Sven Winzler & Ulf Teichgräber & Alexander Pfeil & Ansgar Malich & Ismini Papageorgiou, 2021. "Reliability of a Risk-Factor Questionnaire for Osteoporosis: A Primary Care Survey Study with Dual Energy X-ray Absorptiometry Ground Truth," IJERPH, MDPI, vol. 18(3), pages 1-14, January.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:3:p:1136-:d:488338
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/3/1136/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/3/1136/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shaanthana Subramaniam & Soelaiman Ima-Nirwana & Kok-Yong Chin, 2018. "Performance of Osteoporosis Self-Assessment Tool (OST) in Predicting Osteoporosis—A Review," IJERPH, MDPI, vol. 15(7), pages 1-22, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wen-Yu Ou Yang & Cheng-Chien Lai & Meng-Ting Tsou & Lee-Ching Hwang, 2021. "Development of Machine Learning Models for Prediction of Osteoporosis from Clinical Health Examination Data," IJERPH, MDPI, vol. 18(14), pages 1-12, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:3:p:1136-:d:488338. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.