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Albane S, Slimani H, Kheddouci H. A graph grammar and $$K_{4}$$-type tournament-based approach to detect conflicts of interest in a social network. Knowl Inf Syst 2020. [DOI: 10.1007/s10115-020-01525-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Mialon M, Fabbri A, Fooks G. Reply to the article: "What principles should guide interactions between population health researchers and the food industry? Systematic scoping review of peer-reviewed and grey literature". Obes Rev 2019; 20:1504-1506. [PMID: 31237105 DOI: 10.1111/obr.12905] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 05/14/2019] [Indexed: 11/29/2022]
Affiliation(s)
- Melissa Mialon
- Center for Epidemiological Studies in Health and Nutrition (NUPENS), Department of Nutrition, Faculty of Public Health, University of São Paulo, São Paulo, Brazil
| | - Alice Fabbri
- Charles Perkins Centre and School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia
| | - Gary Fooks
- School for Languages and Social Sciences, Aston University, Birmingham, UK
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Cullerton K, Adams J, Forouhi N, Francis O, White M. What principles should guide interactions between population health researchers and the food industry? Systematic scoping review of peer-reviewed and grey literature. Obes Rev 2019; 20:1073-1084. [PMID: 30968553 PMCID: PMC6767600 DOI: 10.1111/obr.12851] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Revised: 03/02/2019] [Accepted: 03/03/2019] [Indexed: 12/18/2022]
Abstract
There is no explicit consensus amongst population health researchers regarding what constitutes acceptable or effective interactions with the food industry. This has led to confusion and disagreements over conflicts of interest, which can undermine the integrity of science. To clarify this issue, we aimed to systematically identify the key principles developed by population health researchers to prevent or minimize conflicts of interest when interacting with the food industry. Databases of peer-reviewed literature were searched. In addition, an advanced Google search, a request to experts seeking related documents, and hand searching of references were undertaken. Thematic analysis of the extracted data was undertaken. We examined 54 eligible documents describing guidelines for population health researchers when interacting with the food industry. Fifty-six principles were identified and synthesized in five themes. There were high levels of agreement in themes relating to research governance, transparency, and publication but less agreement and guidance on how principles should be applied in relation to funding and risk assessment. There is agreement on some of the general principles for preventing and minimizing conflicts of interests for population health researchers when interacting with the food industry. However, for issues such as assessing the appropriateness of an industry partner, greater clarity and consensus are required.
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Affiliation(s)
- Katherine Cullerton
- Centre for Diet and Activity Research, MRC Epidemiology UnitUniversity of CambridgeCambridgeUK
- School of Public HealthUniversity of QueenslandHerstonAustralia
| | - Jean Adams
- Centre for Diet and Activity Research, MRC Epidemiology UnitUniversity of CambridgeCambridgeUK
| | - Nita Forouhi
- Centre for Diet and Activity Research, MRC Epidemiology UnitUniversity of CambridgeCambridgeUK
| | - Oliver Francis
- Centre for Diet and Activity Research, MRC Epidemiology UnitUniversity of CambridgeCambridgeUK
| | - Martin White
- Centre for Diet and Activity Research, MRC Epidemiology UnitUniversity of CambridgeCambridgeUK
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Schwingshackl L, Knüppel S, Schwedhelm C, Hoffmann G, Missbach B, Stelmach-Mardas M, Dietrich S, Eichelmann F, Kontopantelis E, Iqbal K, Aleksandrova K, Lorkowski S, Leitzmann MF, Kroke A, Boeing H. Perspective: NutriGrade: A Scoring System to Assess and Judge the Meta-Evidence of Randomized Controlled Trials and Cohort Studies in Nutrition Research. Adv Nutr 2016; 7:994-1004. [PMID: 28140319 DOI: 10.3945/an.116.013052] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023] Open
Abstract
The objective of this study was to develop a scoring system (NutriGrade) to evaluate the quality of evidence of randomized controlled trial (RCT) and cohort study meta-analyses in nutrition research, building upon previous tools and expert recommendations. NutriGrade aims to assess the meta-evidence of an association or effect between different nutrition factors and outcomes, taking into account nutrition research-specific requirements not considered by other tools. In a pretest study, 6 randomly selected meta-analyses investigating diet-disease relations were evaluated with NutriGrade by 5 independent raters. After revision, NutriGrade was applied by the same raters to 30 randomly selected meta-analyses in the same thematic area. The reliability of ratings of NutriGrade items was calculated with the use of a multirater κ, and reliability of the total (summed scores) was calculated with the use of intraclass correlation coefficients (ICCs). The following categories for meta-evidence evaluation were established: high (8-10), moderate (6-7.99), low (4-5.99), and very low (0-3.99). The NutriGrade scoring system (maximum of 10 points) comprises the following items: 1) risk of bias, study quality, and study limitations, 2) precision, 3) heterogeneity, 4) directness, 5) publication bias, 6) funding bias, 7) study design, 8) effect size, and 9) dose-response. The NutriGrade score varied between 2.9 (very low meta-evidence) and 8.8 (high meta-evidence) for meta-analyses of RCTs, and it ranged between 3.1 and 8.8 for meta-analyses of cohort studies. The κ value of the ratings for each scoring item varied from 0.32 (95% CI: 0.22, 0.42) for risk of bias for cohort studies and 0.95 (95% CI: 0.91, 0.99) for study design, with a mean κ of 0.66 (95% CI: 0.53, 0.79). The ICC of the total score was 0.81 (95% CI: 0.69, 0.90). The NutriGrade scoring system showed good agreement and reliability. The initial findings regarding the performance of this newly established scoring system need further evaluation in independent analyses.
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Affiliation(s)
- Lukas Schwingshackl
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany;
| | - Sven Knüppel
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Carolina Schwedhelm
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Georg Hoffmann
- Department of Nutritional Sciences, University of Vienna, Vienna, Austria
| | - Benjamin Missbach
- Department of Nutritional Sciences, University of Vienna, Vienna, Austria
| | - Marta Stelmach-Mardas
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
- Department of Pediatric Gastroenterology and Metabolic Diseases, Poznan University of Medical Sciences, Poznan, Poland
| | - Stefan Dietrich
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Fabian Eichelmann
- Nutrition, Immunity, and Metabolism Start-Up Lab
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Evangelos Kontopantelis
- Centre for Primary Care, Institute of Population Health, University of Manchester, Manchester, United Kingdom
| | - Khalid Iqbal
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Krasimira Aleksandrova
- Nutrition, Immunity, and Metabolism Start-Up Lab
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Stefan Lorkowski
- Institute of Nutrition, Friedrich Schiller University Jena, Jena, Germany
- Competence Cluster of Nutrition and Cardiovascular Health, Halle-Jena-Leipzig, Germany
| | - Michael F Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany; and
| | - Anja Kroke
- Department of Nutritional, Food, and Consumer Sciences, University of Applied Sciences, Fulda, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
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Schwingshackl L, Knüppel S, Schwedhelm C, Hoffmann G, Missbach B, Stelmach-Mardas M, Dietrich S, Eichelmann F, Kontopantelis E, Iqbal K, Aleksandrova K, Lorkowski S, Leitzmann MF, Kroke A, Boeing H. Perspective: NutriGrade: A Scoring System to Assess and Judge the Meta-Evidence of Randomized Controlled Trials and Cohort Studies in Nutrition Research. Adv Nutr 2016; 7:994-1004. [PMID: 28140319 PMCID: PMC5105044 DOI: 10.3945/an.116.013052] [Citation(s) in RCA: 251] [Impact Index Per Article: 27.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The objective of this study was to develop a scoring system (NutriGrade) to evaluate the quality of evidence of randomized controlled trial (RCT) and cohort study meta-analyses in nutrition research, building upon previous tools and expert recommendations. NutriGrade aims to assess the meta-evidence of an association or effect between different nutrition factors and outcomes, taking into account nutrition research-specific requirements not considered by other tools. In a pretest study, 6 randomly selected meta-analyses investigating diet-disease relations were evaluated with NutriGrade by 5 independent raters. After revision, NutriGrade was applied by the same raters to 30 randomly selected meta-analyses in the same thematic area. The reliability of ratings of NutriGrade items was calculated with the use of a multirater κ, and reliability of the total (summed scores) was calculated with the use of intraclass correlation coefficients (ICCs). The following categories for meta-evidence evaluation were established: high (8-10), moderate (6-7.99), low (4-5.99), and very low (0-3.99). The NutriGrade scoring system (maximum of 10 points) comprises the following items: 1) risk of bias, study quality, and study limitations, 2) precision, 3) heterogeneity, 4) directness, 5) publication bias, 6) funding bias, 7) study design, 8) effect size, and 9) dose-response. The NutriGrade score varied between 2.9 (very low meta-evidence) and 8.8 (high meta-evidence) for meta-analyses of RCTs, and it ranged between 3.1 and 8.8 for meta-analyses of cohort studies. The κ value of the ratings for each scoring item varied from 0.32 (95% CI: 0.22, 0.42) for risk of bias for cohort studies and 0.95 (95% CI: 0.91, 0.99) for study design, with a mean κ of 0.66 (95% CI: 0.53, 0.79). The ICC of the total score was 0.81 (95% CI: 0.69, 0.90). The NutriGrade scoring system showed good agreement and reliability. The initial findings regarding the performance of this newly established scoring system need further evaluation in independent analyses.
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Affiliation(s)
- Lukas Schwingshackl
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany;
| | - Sven Knüppel
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Carolina Schwedhelm
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Georg Hoffmann
- Department of Nutritional Sciences, University of Vienna, Vienna, Austria
| | - Benjamin Missbach
- Department of Nutritional Sciences, University of Vienna, Vienna, Austria
| | - Marta Stelmach-Mardas
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
- Department of Pediatric Gastroenterology and Metabolic Diseases, Poznan University of Medical Sciences, Poznan, Poland
| | - Stefan Dietrich
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Fabian Eichelmann
- Nutrition, Immunity, and Metabolism Start-Up Lab
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Evangelos Kontopantelis
- Centre for Primary Care, Institute of Population Health, University of Manchester, Manchester, United Kingdom
| | - Khalid Iqbal
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Krasimira Aleksandrova
- Nutrition, Immunity, and Metabolism Start-Up Lab
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Stefan Lorkowski
- Institute of Nutrition, Friedrich Schiller University Jena, Jena, Germany
- Competence Cluster of Nutrition and Cardiovascular Health, Halle-Jena-Leipzig, Germany
| | - Michael F Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany; and
| | - Anja Kroke
- Department of Nutritional, Food, and Consumer Sciences, University of Applied Sciences, Fulda, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
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