Interpretation of NutriGrade: a grading system to assess the quality of evidence for cohort studies on nutrition_Chinese Journal of Evidence-Based Medicine

Authors：

SHANG Xue ^1,2,3 , WU Yanan ^1,2,3 , E Fenfen ^1,2,3 , LU Cuncun ⁴ , HOU Liangying ^2,3 , GUO Kangle ^1,2,3 , WANG Yan ^1,2,3 , ZHOU Liying ^1,2,3 , XU Meng ^1,2,3 , YANG Chaoqun ^1,2,3 ,  YANG Kehu ^1,2,3 ,  LI Xiuxia ^1,2,3

1. Evidence Based Social Science Research Center/Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou 730000, P. R. China;
2. Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou 730000, P. R. China;
3. Evidence Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China;
4. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, P. R. China;

Corresponding author：

YANG Kehu, Email: kehuyangebm2006@126.com; LI Xiuxia, Email: lixiuxia@lzu.edu.cn

Keywords：

Meta-analysis; Cohort study; Evidence classification; Nutrition; NutriGrade

DOI：

10.7507/1672-2531.202205035

Video：

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In response to the specific requirements of nutrition research, Schwingshackl’s research group developed the NutriGrade grading system, which independently assessed the quality of evidence in randomized controlled trials and cohort studies in nutrition, aiming to summarize the associations or effects between different nutritional factors and outcomes and meet the specific needs of evidence users. It has the advantages of novel classification, quantifiability, independence and pertinence, and it has better consistency, fairness, reliability and feasibility. Well-designed prospective cohort studies are more feasible in the field of nutrition than randomized controlled trials. The grading of the evidence quality for cohort studies included the following eight items: a) risk of bias, study quality, and study limitations; b) precision; c) heterogeneity; d) directness; e) publication bias; f) funding bias; g) effect size; and h) dose-response. Based on the evaluation results of the above items, the evidence quality could be divided into four grades: high (8-10), moderate (<8), low (<6), and very low (<4). The purpose of this paper was to introduce the basic principles, specific contents, and application methods of the NutriGrade grading system for cohort studies and cite examples to provide references for relevant researchers.

Citation： SHANG Xue, WU Yanan, E Fenfen, LU Cuncun, HOU Liangying, GUO Kangle, WANG Yan, ZHOU Liying, XU Meng, YANG Chaoqun, YANG Kehu, LI Xiuxia. Interpretation of NutriGrade: a grading system to assess the quality of evidence for cohort studies on nutrition. Chinese Journal of Evidence-Based Medicine, 2022, 22(11): 1348-1357. doi: 10.7507/1672-2531.202205035 Copy

1.	Atkins D, Best D, Briss PA, et al. Grading quality of evidence and strength of recommendations. BMJ, 2004, 328(7454): 1490.
2.	Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ, 2008, 336(7650): 924-926.
3.	Te Morenga L, Mallard S, Mann J. Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ, 2012, 346: e7492.
4.	Nestle M. Public health nutrition deserves more attention. Am J Public Health, 2021, 111(4): 533-535.
5.	Schwingshackl L, Balduzzi S, Beyerbach J, et al. Evaluating agreement between bodies of evidence from randomised controlled trials and cohort studies in nutrition research: meta-epidemiological study. BMJ, 2021, 374: n1864.
6.	Satija A, Yu E, Willett WC, et al. Understanding nutritional epidemiology and its role in policy. Adv Nutr, 2015, 6(1): 5-18.
7.	Balshem H, Helfand M, Schünemann HJ, et al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol, 2011, 64(4): 401-406.
8.	杨楠, 邓围, 陈耀龙, 等. GRADE在预后研究系统评价中应用的原理, 方法及挑战. 中国循证医学杂志, 2015, 15(9): 1112-1116.
9.	Schwingshackl L, Knüppel S, Schwedhelm C, et al. 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(6): 994-1004.
10.	Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med, 2002, 21(11): 1539-1558.
11.	Mittlböck M, Heinzl H. A simulation study comparing properties of heterogeneity measures in meta-analyses. Stat Med, 2006, 25(24): 4321-4333.
12.	Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 8. Rating the quality of evidence-indirectness. J Clin Epidemiol, 2011, 64(12): 1303-1310.
13.	Jannasch F, Kröger J, Schulze MB. Dietary patterns and type 2 diabetes: a systematic literature review and meta-analysis of prospective studies. J Nutr, 2017, 147(6): 1174-1182.
14.	Song F, Eastwood AJ, Gilbody S, et al. Publication and related biases. Health Technol Assess. 2000, 4(10): 1-115.
15.	Scherer RW, Meerpohl JJ, Pfeifer N, et al. Full publication of results initially presented in abstracts. Cochrane Database Syst Rev, 2018, (11): MR000005.
16.	杨扬, 沈志超, 靳纯桥. 发表偏倚的原因, 后果与预防研究. 编辑学报, 2002, 14(3): 170-172.
17.	Harbord RM, Egger M, Sterne JA. A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints. Stat Med, 2006, 25(20): 3443-3457.
18.	Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ, 1997, 315(7109): 629-634.
19.	Lau J, Ioannidis JP, Terrin N, et al. The case of the misleading funnel plot. BMJ, 2006, 333(7568): 597-600.
20.	Terrin N, Schmid CH, Lau J. In an empirical evaluation of the funnel plot, researchers could not visually identify publication bias. J Clin Epidemiol, 2005, 58(9): 894-901.
21.	Nestle M. Food company sponsorship of nutrition research and professional activities: a conflict of interest. Public Health Nutr, 2001, 4(5): 1015-1022.
22.	Rowe S, Alexander N, Clydesdale FM, et al. Funding food science and nutrition research: financial conflicts and scientific integrity. Am J Clin Nutr, 2009, 89(5): 1285-1291.
23.	Lesser LI, Ebbeling CB, Goozner M, et al. Relationship between funding source and conclusion among nutrition-related scientific articles. PLoS Med, 2007, 4(1): e5.
24.	Guyatt GH, Oxman AD, Sultan S, et al. GRADE guidelines: 9. Rating up the quality of evidence. J Clin Epidemiol, 2011, 64(12): 1311-1316.
25.	Hill AB. The environment and disease: association or causation. 1965. J R Soc Med, 2015, 108(1): 32-37.
26.	Galbete C, Schwingshackl L, Schwedhelm C, et al. Evaluating Mediterranean diet and risk of chronic disease in cohort studies: an umbrella review of meta-analyses. Eur J Epidemiol, 2018, 33(10): 909-931.
27.	Schwingshackl L, Missbach B, König J, et al. Adherence to a Mediterranean diet and risk of diabetes: a systematic review and meta-analysis. Public Health Nutr, 2015, 18(7): 1292-1299.
28.	Koloverou E, Esposito K, Giugliano D, et al. The effect of Mediterranean diet on the development of type 2 diabetes mellitus: a meta-analysis of 10 prospective studies and 136, 846 participants. Metabolism, 2014, 63(7): 903-911.
29.	Esposito K, Chiodini P, Maiorino MI, et al. Which diet for prevention of type 2 diabetes: a meta-analysis of prospective studies. Endocrine, 2014, 47(1): 107-116.
30.	Lucas M. Conflicts of interest in nutritional sciences: the forgotten bias in meta-analysis. World J Methodol, 2015, 5(4): 175-178.
31.	Pollock A, Farmer SE, Brady MC, et al. An algorithm was developed to assign GRADE levels of evidence to comparisons within systematic reviews. J Clin Epidemiol, 2016, 70: 106-110.
32.	Berkman ND, Lohr KN, Morgan LC, et al. Interrater reliability of grading strength of evidence varies with the complexity of the evidence in systematic reviews. J Clin Epidemiol, 2013, 66(10): 1105-1117.
33.	陈耀龙, 姚亮, Susan Norris, 等. GRADE在系统评价中应用的必要性及注意事项. 中国循证医学杂志, 2013, 13(12): 1401-1404.
34.	Schwingshackl L, Missbach B, Hoffmann G. An umbrella review of garlic intake and risk of cardiovascular disease. Phytomedicine, 2016, 23(11): 1127-1133.
35.	Schwingshackl L, Hoffmann G. Monounsaturated fatty acids and risk of cardiovascular disease: synopsis of the evidence available from systematic reviews and meta-analyses. Nutrients, 2012, 4(12): 1989-2007.

1. Atkins D, Best D, Briss PA, et al. Grading quality of evidence and strength of recommendations. BMJ, 2004, 328(7454): 1490.
2. Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ, 2008, 336(7650): 924-926.
3. Te Morenga L, Mallard S, Mann J. Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ, 2012, 346: e7492.
4. Nestle M. Public health nutrition deserves more attention. Am J Public Health, 2021, 111(4): 533-535.
5. Schwingshackl L, Balduzzi S, Beyerbach J, et al. Evaluating agreement between bodies of evidence from randomised controlled trials and cohort studies in nutrition research: meta-epidemiological study. BMJ, 2021, 374: n1864.
6. Satija A, Yu E, Willett WC, et al. Understanding nutritional epidemiology and its role in policy. Adv Nutr, 2015, 6(1): 5-18.
7. Balshem H, Helfand M, Schünemann HJ, et al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol, 2011, 64(4): 401-406.
8. 杨楠, 邓围, 陈耀龙, 等. GRADE在预后研究系统评价中应用的原理, 方法及挑战. 中国循证医学杂志, 2015, 15(9): 1112-1116.
9. Schwingshackl L, Knüppel S, Schwedhelm C, et al. 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(6): 994-1004.
10. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med, 2002, 21(11): 1539-1558.
11. Mittlböck M, Heinzl H. A simulation study comparing properties of heterogeneity measures in meta-analyses. Stat Med, 2006, 25(24): 4321-4333.
12. Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 8. Rating the quality of evidence-indirectness. J Clin Epidemiol, 2011, 64(12): 1303-1310.
13. Jannasch F, Kröger J, Schulze MB. Dietary patterns and type 2 diabetes: a systematic literature review and meta-analysis of prospective studies. J Nutr, 2017, 147(6): 1174-1182.
14. Song F, Eastwood AJ, Gilbody S, et al. Publication and related biases. Health Technol Assess. 2000, 4(10): 1-115.
15. Scherer RW, Meerpohl JJ, Pfeifer N, et al. Full publication of results initially presented in abstracts. Cochrane Database Syst Rev, 2018, (11): MR000005.
16. 杨扬, 沈志超, 靳纯桥. 发表偏倚的原因, 后果与预防研究. 编辑学报, 2002, 14(3): 170-172.
17. Harbord RM, Egger M, Sterne JA. A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints. Stat Med, 2006, 25(20): 3443-3457.
18. Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ, 1997, 315(7109): 629-634.
19. Lau J, Ioannidis JP, Terrin N, et al. The case of the misleading funnel plot. BMJ, 2006, 333(7568): 597-600.
20. Terrin N, Schmid CH, Lau J. In an empirical evaluation of the funnel plot, researchers could not visually identify publication bias. J Clin Epidemiol, 2005, 58(9): 894-901.
21. Nestle M. Food company sponsorship of nutrition research and professional activities: a conflict of interest. Public Health Nutr, 2001, 4(5): 1015-1022.
22. Rowe S, Alexander N, Clydesdale FM, et al. Funding food science and nutrition research: financial conflicts and scientific integrity. Am J Clin Nutr, 2009, 89(5): 1285-1291.
23. Lesser LI, Ebbeling CB, Goozner M, et al. Relationship between funding source and conclusion among nutrition-related scientific articles. PLoS Med, 2007, 4(1): e5.
24. Guyatt GH, Oxman AD, Sultan S, et al. GRADE guidelines: 9. Rating up the quality of evidence. J Clin Epidemiol, 2011, 64(12): 1311-1316.
25. Hill AB. The environment and disease: association or causation. 1965. J R Soc Med, 2015, 108(1): 32-37.
26. Galbete C, Schwingshackl L, Schwedhelm C, et al. Evaluating Mediterranean diet and risk of chronic disease in cohort studies: an umbrella review of meta-analyses. Eur J Epidemiol, 2018, 33(10): 909-931.
27. Schwingshackl L, Missbach B, König J, et al. Adherence to a Mediterranean diet and risk of diabetes: a systematic review and meta-analysis. Public Health Nutr, 2015, 18(7): 1292-1299.
28. Koloverou E, Esposito K, Giugliano D, et al. The effect of Mediterranean diet on the development of type 2 diabetes mellitus: a meta-analysis of 10 prospective studies and 136, 846 participants. Metabolism, 2014, 63(7): 903-911.
29. Esposito K, Chiodini P, Maiorino MI, et al. Which diet for prevention of type 2 diabetes: a meta-analysis of prospective studies. Endocrine, 2014, 47(1): 107-116.
30. Lucas M. Conflicts of interest in nutritional sciences: the forgotten bias in meta-analysis. World J Methodol, 2015, 5(4): 175-178.
31. Pollock A, Farmer SE, Brady MC, et al. An algorithm was developed to assign GRADE levels of evidence to comparisons within systematic reviews. J Clin Epidemiol, 2016, 70: 106-110.
32. Berkman ND, Lohr KN, Morgan LC, et al. Interrater reliability of grading strength of evidence varies with the complexity of the evidence in systematic reviews. J Clin Epidemiol, 2013, 66(10): 1105-1117.
33. 陈耀龙, 姚亮, Susan Norris, 等. GRADE在系统评价中应用的必要性及注意事项. 中国循证医学杂志, 2013, 13(12): 1401-1404.
34. Schwingshackl L, Missbach B, Hoffmann G. An umbrella review of garlic intake and risk of cardiovascular disease. Phytomedicine, 2016, 23(11): 1127-1133.
35. Schwingshackl L, Hoffmann G. Monounsaturated fatty acids and risk of cardiovascular disease: synopsis of the evidence available from systematic reviews and meta-analyses. Nutrients, 2012, 4(12): 1989-2007.

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