IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v24y2023i2d10.1007_s10198-022-01473-7.html
   My bibliography  Save this article

Mapping the obesity problems scale to the SF-6D: results based on the Scandinavian Obesity Surgery Registry (SOReg)

Author

Listed:
  • Sun Sun

    (Umeå University
    Karolinska Instiutet)

  • Erik Stenberg

    (Örebro University)

  • Yang Cao

    (Örebro University)

  • Lars Lindholm

    (Umeå University)

  • Klas-Göran Salén

    (Umeå University)

  • Karl A. Franklin

    (Umeå University)

  • Nan Luo

    (National University of Singapore)

Abstract

Background Obesity Problem Scale (OP) is a widely applied instrument for obesity, however currently calculation of health utility based on OP is not feasible as it is not a preference-based measure. Using data from the Scandinavian Obesity Surgery Registry (SOReg), we sought to develop a mapping algorithm to estimate SF-6D utility from OP. Furthermore, to test whether the mapping algorithm is robust to the effect of surgery. Method The source data SOReg (n = 36 706) contains both OP and SF-36, collected at pre-surgery and at 1, 2 and 5 years post-surgery. The Ordinary Least Square (OLS), beta-regression and Tobit regression were used to predict the SF-6D utility for different time points respectively. Besides the main effect model, different combinations of patient characteristics (age, sex, Body Mass Index, obesity-related comorbidities) were tested. Both internal validation (split-sample validation) and validation with testing the mapping algorithm on a dataset from other time points were carried out. A multi-stage model selection process was used, accessing model consistency, parsimony, goodness-of-fit and predictive accuracy. Models with the best performance were selected as the final mapping algorithms. Results The final mapping algorithms were based on OP summary score using OLS models, for pre- and post-surgery respectively. Mapping algorithms with different combinations of patients’ characteristics were presented, to satisfy the user with a different need. Conclusion This study makes available algorithms enabling crosswalk from the Obesity Problem Scale to the SF-6D utility. Different mapping algorithms are recommended for the mapping of pre- and post-operative data.

Suggested Citation

  • Sun Sun & Erik Stenberg & Yang Cao & Lars Lindholm & Klas-Göran Salén & Karl A. Franklin & Nan Luo, 2023. "Mapping the obesity problems scale to the SF-6D: results based on the Scandinavian Obesity Surgery Registry (SOReg)," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(2), pages 279-292, March.
    • Handle: RePEc:spr:eujhec:v:24:y:2023:i:2:d:10.1007_s10198-022-01473-7
    DOI: 10.1007/s10198-022-01473-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-022-01473-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10198-022-01473-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. John Brazier & Yaling Yang & Aki Tsuchiya & Donna Rowen, 2010. "A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(2), pages 215-225, April.
    2. Clara Mukuria & Donna Rowen & Sue Harnan & Andrew Rawdin & Ruth Wong & Roberta Ara & John Brazier, 2019. "An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values," Applied Health Economics and Health Policy, Springer, vol. 17(3), pages 295-313, June.
    3. Jeff Round & Annie Hawton, 2017. "Statistical Alchemy: Conceptual Validity and Mapping to Generate Health State Utility Values," PharmacoEconomics - Open, Springer, vol. 1(4), pages 233-239, December.
    4. Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March.
    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. Aileen R. Neilson & Gareth T. Jones & Gary J. Macfarlane & Ejaz MI Pathan & Paul McNamee, 2022. "Generating EQ-5D-5L health utility scores from BASDAI and BASFI: a mapping study in patients with axial spondyloarthritis using longitudinal UK registry data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(8), pages 1357-1369, November.
    2. Ben F. M. Wijnen & Iris Mosweu & Marian H. J. M. Majoie & Leone Ridsdale & Reina J. A. Kinderen & Silvia M. A. A. Evers & Paul McCrone, 2018. "A comparison of the responsiveness of EQ-5D-5L and the QOLIE-31P and mapping of QOLIE-31P to EQ-5D-5L in epilepsy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(6), pages 861-870, July.
    3. Donna Rowen & John Brazier & Aki Tsuchiya & Mónica Hernández Alava, 2012. "Valuing states from multiple measures on the same visual analogue sale: a feasibility study," Health Economics, John Wiley & Sons, Ltd., vol. 21(6), pages 715-729, June.
    4. Weidong Huang & Hongjuan Yu & Chaojie Liu & Guoxiang Liu & Qunhong Wu & Jin Zhou & Xin Zhang & Xiaowen Zhao & Linmei Shi & Xiaoxue Xu, 2017. "Assessing Health-Related Quality of Life of Chinese Adults in Heilongjiang Using EQ-5D-3L," IJERPH, MDPI, vol. 14(3), pages 1-16, February.
    5. Fan Yang & Nancy Devlin & Nan Luo, 2019. "Impact of mapped EQ-5D utilities on cost-effectiveness analysis: in the case of dialysis treatments," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(1), pages 99-105, February.
    6. Wijnen, Ben F.M. & Mosweu, Iris & Majoie, Marian H.J.M. & Ridsdale, Leone & de Kinderen, Reina J.A. & Evers, Silvia M.A.A. & McCrone, Paul, 2018. "A comparison of the responsiveness of EQ-5D-5L and the QOLIE-31P and mapping of QOLIE-31P to EQ-5D-5L in epilepsy," LSE Research Online Documents on Economics 106170, London School of Economics and Political Science, LSE Library.
    7. Richard Huan Xu & Eliza Lai Yi Wong & Jun Jin & Ying Dou & Dong Dong, 2020. "Mapping of the EORTC QLQ-C30 to EQ-5D-5L index in patients with lymphomas," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(9), pages 1363-1373, December.
    8. Asrul Akmal Shafie & Irwinder Kaur Chhabra & Jacqueline Hui Yi Wong & Noor Syahireen Mohammed, 2021. "Mapping PedsQL™ Generic Core Scales to EQ-5D-3L utility scores in transfusion-dependent thalassemia patients," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 735-747, July.
    9. Fan Yang & Carlos K. H. Wong & Nan Luo & James Piercy & Rebecca Moon & James Jackson, 2019. "Mapping the kidney disease quality of life 36-item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L in patients undergoing dialysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(8), pages 1195-1206, November.
    10. Billingsley Kaambwa & Lucinda Billingham & Stirling Bryan, 2013. "Mapping utility scores from the Barthel index," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(2), pages 231-241, April.
    11. Joseph Kwon & Sung Wook Kim & Wendy J. Ungar & Kate Tsiplova & Jason Madan & Stavros Petrou, 2018. "A Systematic Review and Meta-analysis of Childhood Health Utilities," Medical Decision Making, , vol. 38(3), pages 277-305, April.
    12. Majmudar, Ishani Kartik & Mihalopoulos, Cathy & Abimanyi-Ochom, Julie & Mohebbi, Mohammadreza & Engel, Lidia, 2024. "The association between loneliness with health service use and quality of life among informal carers in Australia," Social Science & Medicine, Elsevier, vol. 348(C).
    13. Samer A. Kharroubi & Yara Beyh & Marwa Diab El Harake & Dalia Dawoud & Donna Rowen & John Brazier, 2020. "Examining the Feasibility and Acceptability of Valuing the Arabic Version of SF-6D in a Lebanese Population," IJERPH, MDPI, vol. 17(3), pages 1-15, February.
    14. Nick Bansback & Huiying Sun & Daphne P. Guh & Xin Li & Bohdan Nosyk & Susan Griffin & Paul G. Barnett & Aslam H. Anis, 2008. "Impact of the recall period on measuring health utilities for acute events," Health Economics, John Wiley & Sons, Ltd., vol. 17(12), pages 1413-1419.
    15. Natalia Hernández-Segura & Alba Marcos-Delgado & Arrate Pinto-Carral & Tania Fernández-Villa & Antonio J. Molina, 2022. "Health-Related Quality of Life (HRQOL) Instruments and Mobility: A Systematic Review," IJERPH, MDPI, vol. 19(24), pages 1-23, December.
    16. Clarke, Philip & Erreygers, Guido, 2020. "Defining and measuring health poverty," Social Science & Medicine, Elsevier, vol. 244(C).
    17. Richard Grieve & Marina Grishchenko & John Cairns, 2009. "SF-6D versus EQ-5D: reasons for differences in utility scores and impact on reported cost-utility," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 10(1), pages 15-23, February.
    18. Miguel A. Garcia-Gordillo & Daniel Collado-Mateo & Pedro R. Olivares & José C. Adsuar, 2018. "Chilean population norms derived from the health-related quality of Life SF-6D," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(5), pages 675-686, June.
    19. Admassu N. Lamu, 2020. "Does linear equating improve prediction in mapping? Crosswalking MacNew onto EQ-5D-5L value sets," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(6), pages 903-915, August.
    20. Nadja Chernyak & Heribert Sattel & Marsel Scheer & Christina Baechle & Johannes Kruse & Peter Henningsen & Andrea Icks, 2014. "Economic Evaluation of Brief Psychodynamic Interpersonal Therapy in Patients with Multisomatoform Disorder," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-4, January.

    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:spr:eujhec:v:24:y:2023:i:2:d:10.1007_s10198-022-01473-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.