IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i11p5538-d559915.html
   My bibliography  Save this article

Analysis of Effectiveness of a Supplement Combining Harpagophytum procumbens , Zingiber officinale and Bixa orellana in Healthy Recreational Runners with Self-Reported Knee Pain: A Pilot, Randomized, Triple-Blind, Placebo-Controlled Trial

Author

Listed:
  • Marcela González-Gross

    (ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, 28040 Madrid, Spain
    CIBER Physiopathology of Obesity and Nutrition (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain)

  • Carlos Quesada-González

    (ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, 28040 Madrid, Spain
    Department of Applied Mathematics to Information and Communication Technologies, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Javier Rueda

    (Biomechanical Laboratory, Faculty of Physical Activity and Sport Sciences, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Manuel Sillero-Quintana

    (Department of Sport, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Nicolas Issaly

    (Natural Origins, 69380 Lozanne, France)

  • Angel Enrique Díaz

    (ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, 28040 Madrid, Spain
    Clinical Laboratory Unit, Department of Sport and Health, Spanish Agency for Health Protection in Sport (AEPSAD), 28040 Madrid, Spain)

  • Eva Gesteiro

    (ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • David Escobar-Toledo

    (ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Rafael Torres-Peralta

    (ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Marc Roller

    (Natural Origins, 69380 Lozanne, France)

  • Amelia Guadalupe-Grau

    (ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

Abstract

Recreational running (RR) is becoming a popular way to increase physical activity for improving health, together with a higher incidence of knee injuries. The aim was to analyze the effect of a four-week supplementation with a mixture of Harpagophytum procumbens , Zingiber officinale and Bixa orellana on males, middle-aged, RR with an undiagnosed knee discomfort. A randomized triple-blind placebo-control trial was conducted among male RR aged 40–60 years suffering from self-declared knee discomfort after training. Participants were assigned to supplementation (2 g/day in 6 doses; n = 13; intervention group (IG)) or matched placebo ( n = 15; control group (CG)) for 4 weeks. At pre- and post-intervention, assessment of routine blood biomarkers, body composition, running biomechanics and body temperature was performed using standardized procedures. Machine learning (ML) techniques were used to classify whether subjects belonged to IG or CG. ML model was able to correctly classify individuals as IG or CG with a median accuracy of 0.857. Leg fat mass decreased significantly ( p = 0.037) and a deeper reduction in knee thermograms was observed in IG ( p < 0.05). Safety evaluation revealed no significant differences in the rest of parameters studied. Subjects belonging to IG or CG are clearly differentiated, pointing into an effect of the supplement of ameliorating inflammation.

Suggested Citation

  • Marcela González-Gross & Carlos Quesada-González & Javier Rueda & Manuel Sillero-Quintana & Nicolas Issaly & Angel Enrique Díaz & Eva Gesteiro & David Escobar-Toledo & Rafael Torres-Peralta & Marc Rol, 2021. "Analysis of Effectiveness of a Supplement Combining Harpagophytum procumbens , Zingiber officinale and Bixa orellana in Healthy Recreational Runners with Self-Reported Knee Pain: A Pilot, Randomized, ," IJERPH, MDPI, vol. 18(11), pages 1-18, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:5538-:d:559915
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/11/5538/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/11/5538/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hamilton H. T. Reis & Ciro J. Brito & Manuel Sillero-Quintana & Alisson G. Silva & Ismael Fernández-Cuevas & Matheus S. Cerqueira & Francisco Z. Werneck & João C. B. Marins, 2023. "Can Adipose Tissue Influence the Evaluation of Thermographic Images in Adolescents?," IJERPH, MDPI, vol. 20(5), pages 1-11, March.

    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. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
    2. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    3. Piaopiao Chen & Agnès H. Michel & Jianzhi Zhang, 2022. "Transposon insertional mutagenesis of diverse yeast strains suggests coordinated gene essentiality polymorphisms," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    4. Paulo Infante & Gonçalo Jacinto & Anabela Afonso & Leonor Rego & Pedro Nogueira & Marcelo Silva & Vitor Nogueira & José Saias & Paulo Quaresma & Daniel Santos & Patrícia Góis & Paulo Rebelo Manuel, 2023. "Factors That Influence the Type of Road Traffic Accidents: A Case Study in a District of Portugal," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    5. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    6. Banks, Jonathan & Rabbani, Arif & Nadkarni, Kabir & Renaud, Evan, 2020. "Estimating parasitic loads related to brine production from a hot sedimentary aquifer geothermal project: A case study from the Clarke Lake gas field, British Columbia," Renewable Energy, Elsevier, vol. 153(C), pages 539-552.
    7. Crespo, Cristian, 2020. "Two become one: improving the targeting of conditional cash transfers with a predictive model of school dropout," LSE Research Online Documents on Economics 123139, London School of Economics and Political Science, LSE Library.
    8. Alexander Wettstein & Gabriel Jenni & Ida Schneider & Fabienne Kühne & Martin grosse Holtforth & Roberto La Marca, 2023. "Predictors of Psychological Strain and Allostatic Load in Teachers: Examining the Long-Term Effects of Biopsychosocial Risk and Protective Factors Using a LASSO Regression Approach," IJERPH, MDPI, vol. 20(10), pages 1-20, May.
    9. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
    10. Daifeng Xiang & Gangsheng Wang & Jing Tian & Wanyu Li, 2023. "Global patterns and edaphic-climatic controls of soil carbon decomposition kinetics predicted from incubation experiments," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    11. Joel Podgorski & Oliver Kracht & Luis Araguas-Araguas & Stefan Terzer-Wassmuth & Jodie Miller & Ralf Straub & Rolf Kipfer & Michael Berg, 2024. "Groundwater vulnerability to pollution in Africa’s Sahel region," Nature Sustainability, Nature, vol. 7(5), pages 558-567, May.
    12. Bellotti, Anthony & Brigo, Damiano & Gambetti, Paolo & Vrins, Frédéric, 2021. "Forecasting recovery rates on non-performing loans with machine learning," International Journal of Forecasting, Elsevier, vol. 37(1), pages 428-444.
    13. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    14. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    15. Arjan S. Gosal & Janine A. McMahon & Katharine M. Bowgen & Catherine H. Hoppe & Guy Ziv, 2021. "Identifying and Mapping Groups of Protected Area Visitors by Environmental Awareness," Land, MDPI, vol. 10(6), pages 1-14, May.
    16. Marcos Rodrigues & Fermín Alcasena & Pere Gelabert & Cristina Vega‐García, 2020. "Geospatial Modeling of Containment Probability for Escaped Wildfires in a Mediterranean Region," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1762-1779, September.
    17. Natalia Pardo-Lorente & Anestis Gkanogiannis & Luca Cozzuto & Antoni Gañez Zapater & Lorena Espinar & Ritobrata Ghose & Jacqueline Severino & Laura García-López & Rabia Gül Aydin & Laura Martin & Mari, 2024. "Nuclear localization of MTHFD2 is required for correct mitosis progression," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    18. Giovanny Pillajo-Quijia & Blanca Arenas-Ramírez & Camino González-Fernández & Francisco Aparicio-Izquierdo, 2020. "Influential Factors on Injury Severity for Drivers of Light Trucks and Vans with Machine Learning Methods," Sustainability, MDPI, vol. 12(4), pages 1-28, February.
    19. Francesco Sartor & Jonathan P. Moore & Hans-Peter Kubis, 2021. "Plasma Interleukin-10 and Cholesterol Levels May Inform about Interdependences between Fitness and Fatness in Healthy Individuals," IJERPH, MDPI, vol. 18(4), pages 1-19, February.
    20. Zander S. Venter & Adam Sadilek & Charlotte Stanton & David N. Barton & Kristin Aunan & Sourangsu Chowdhury & Aaron Schneider & Stefano Maria Iacus, 2021. "Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis," IJERPH, MDPI, vol. 18(23), pages 1-12, November.

    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:11:p:5538-:d:559915. 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.