Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-22T19:08:28.407Z Has data issue: false hasContentIssue false

Inaccurate data in meta-analysis; ‘A posteriori dietary patterns and metabolic syndrome in adults: a systematic review and meta-analysis of observational studies’

Published online by Cambridge University Press:  07 October 2019

Roberto Fabiani
Affiliation:
Department of Chemistry, Biology and Biotechnology, University of Perugia, Via del Giochetto, 06126 Perugia, Italy Email: [email protected]
Giulia Naldini
Affiliation:
School of Specialization in Hygiene and Preventive Medicine, University of Perugia, Perugia, Italy
Manuela Chiavarini
Affiliation:
Department of Experimental Medicine Section of Public Heath, University of Perugia Perugia, Italy
Rights & Permissions [Opens in a new window]

Abstract

Type
Letter to the Editor
Copyright
© The Authors 2019

Madam

We read with interest the meta-analysis by Shab-Bidar et al.(Reference Shab-Bidar, Golzarand and Hajimohammadi1) on the association of a posteriori dietary patterns (DP) and metabolic syndrome. We noticed several inaccuracies regarding the inclusion of data that need to be clarified. The authors declare that the meta-analysis was conducted with articles published up to July 2015, but many articles(Reference He, Yang and Zhang2Reference Panagiotakos, Pitsavos and Skoumas6) meeting the inclusion criteria were not selected and included in the study. We found that the food composition of the DP included in the meta-analysis not always reflected the frequency of consumed foods characterizing the categories ‘Unhealthy/Western’ and ‘Healthy/Prudent’ investigated by the authors. They classified and analysed together as ‘Healthy/Prudent’, DP whose composition differed considerably, as described in the studies by Suliga et al.(Reference Suliga, Kozieł and Cieśla7), Akter et al.(Reference Akter, Nanri and Pham8), Hong et al.(Reference Hong, Song and Lee9), Kim and Jo(Reference Kim and Jo10) and DiBello et al.(Reference DiBello, McGarvey and Kraft11). Similarly, for the analysis of the ‘Unhealthy/Western’ pattern, they combined different DP described in the studies by Gadgil et al.(Reference Gadgil, Anderson and Kandula12), Hong et al.(Reference Hong, Song and Lee9), Kim and Jo(Reference Kim and Jo10), DiBello et al.(Reference DiBello, McGarvey and Kraft11), Noel et al.(Reference Noel, Newby and Ordovas13) and Esmaillzadeh et al.(Reference Esmaillzadeh, Kimiagar and Mehrabi14). Therefore, the combination of these risk estimations seems methodologically incorrect. We summarize the misclassified DP included in the ‘Unhealthy/Western’ and ‘Healthy/Prudent’ patterns in Table 1.

Table 1 Summary and composition of the misclassified dietary patterns (DP) included in the meta-analysis

In addition, we noticed some inconsistencies regarding the risk data included in the meta-analysis. The most evident inaccuracies in the risk data for the ‘Unhealthy/Western’ pattern are the following: (i) study by Gadgil et al.(Reference Gadgil, Anderson and Kandula12), ‘Animal protein’ DP, OR = 0·69 (95 % CI 0·65, 1·10) instead of OR = 0·69 (95 % CI 0·43, 1·10); and (ii) study by Suliga et al.(Reference Suliga, Kozieł and Cieśla7), ‘Fat, meat and alcohol’ DP, OR = 1·22 (95 % CI 0·97, 1·53) instead of the risk estimate of the adjusted model OR = 1·04 (95 % CI 0·82, 1·33). The inaccuracies in the risk data for ‘Healthy/Prudent’ pattern regard the following risk estimations: (i) study by Gadgil et al.(Reference Gadgil, Anderson and Kandula12), ‘Fruits, vegetables, nuts, and legumes’ DP, OR = 0·80 (95 % CI 0·62, 1·51) instead of OR = 0·65 (95 % CI 0·38, 1·11); (ii) study by Suliga et al.(Reference Suliga, Kozieł and Cieśla7), ‘Healthy’ DP, OR = 0·68 (95 % CI 0·53, 0·92) instead of the adjusted model OR = 0·87 (95 % CI 0·68, 1·13); (iii) study by Naja et al.(Reference Naja, Nasreddine and Itani15), ‘Traditional Lebanese’ DP, OR = 1·96 (95 % CI 0·85, 4·51) instead of OR = 1·96 (95 % CI 0·82, 4·34); and (iv) study by Cho et al.(Reference Cho, Kim and Cho16), ‘Healthy’ DP, OR = 0·58 (95 % CI 0·43, 0·78) instead of OR = 0·58 (95 % CI 0·50, 0·91).

In summary, since the dietary patterns represent a complex variable reflecting specific combination of different foods which varies consistently among the studies, we believe that pooling dietary patterns on the basis of factor loadings and combining risk data referring to similar dietary patterns are essential to obtain consistent and solid evidence on the association between diet and health-related outcomes as expected in a meta-analysis.

Acknowledgements

Acknowledgements: The work was completed at the University of Perugia, Italy. The authors thank their home institution for financial support. Financial support: This study was supported by Perugia University, Perugia, Italy. Perugia University had no role in the design, analysis or writing of this article. Conflict of interest: The authors declared no personal or financial conflicts of interest. Authorship: R.F., G.N. and M.C. contributed to the manuscript drafting. Ethics of human subject participation: Not applicable.

References

Shab-Bidar, S, Golzarand, M, Hajimohammadi, Met al. (2018) A posteriori dietary patterns and metabolic syndrome in adults: a systematic review and meta-analysis of observational studies. Public Health Nutr 21, 16811692.10.1017/S1368980018000216CrossRefGoogle ScholarPubMed
He, DH, Yang, M, Zhang, RHet al. (2015) Dietary patterns associated metabolic syndrome in Chinese adults. Biomed Environ Sci 28, 370373.Google ScholarPubMed
Aekplakorn, W, Satheannoppakao, W, Putwatana, Pet al. (2015) Dietary pattern and metabolic syndrome in Thai adults. J Nutr Metab 2015, 468759.10.1155/2015/468759CrossRefGoogle ScholarPubMed
Baik, I, Lee, M, Jun, N-Ret al. (2013) A healthy dietary pattern consisting of a variety of food choices is inversely associated with the development of metabolic syndrome. Nutr Res Pract 7, 233241.10.4162/nrp.2013.7.3.233CrossRefGoogle ScholarPubMed
Bian, S, Gao, Y, Zhang, Met al. (2013) Dietary nutrient intake and metabolic syndrome risk in Chinese adults: a case–control study. Nutr J 12, 106.10.1186/1475-2891-12-106CrossRefGoogle ScholarPubMed
Panagiotakos, DB, Pitsavos, C, Skoumas, Yet al. (2007) The association between food patterns and the metabolic syndrome using principal components analysis: the ATTICA study. J Am Diet Assoc 107, 979987.10.1016/j.jada.2007.03.006CrossRefGoogle ScholarPubMed
Suliga, E, Kozieł, D, Cieśla, Eet al. (2015) Association between dietary patterns and metabolic syndrome in individuals with normal weight: a cross-sectional study. Nutr J 14, 55.10.1186/s12937-015-0045-9CrossRefGoogle ScholarPubMed
Akter, S, Nanri, A, Pham, NMet al. (2013) Dietary patterns and metabolic syndrome in a Japanese working population. Nutr Metab (Lond) 10, 30.10.1186/1743-7075-10-30CrossRefGoogle Scholar
Hong, S, Song, Y, Lee, KHet al. (2012) A fruit and dairy dietary pattern is associated with a reduced risk of metabolic syndrome. Metabolism 61, 883890.10.1016/j.metabol.2011.10.018CrossRefGoogle ScholarPubMed
Kim, J & Jo, I (2011) Grains, vegetables, and fish dietary pattern is inversely associated with the risk of metabolic syndrome in South Korean adults. J Am Diet Assoc 111, 11411149.10.1016/j.jada.2011.05.001CrossRefGoogle ScholarPubMed
DiBello, JR, McGarvey, ST, Kraft, Pet al. (2009) Dietary patterns are associated with metabolic syndrome in adult Samoans. J Nutr 139, 19331943.10.3945/jn.109.107888CrossRefGoogle ScholarPubMed
Gadgil, MD, Anderson, CAM, Kandula, NRet al. (2015) Dietary patterns are associated with metabolic risk factors in South Asians living in the United States. J Nutr 145, 12111217.10.3945/jn.114.207753CrossRefGoogle ScholarPubMed
Noel, SE, Newby, PK, Ordovas, JMet al. (2009) A traditional rice and beans pattern is associated with metabolic syndrome in Puerto Rican older adults. J Nutr 139, 13601367.10.3945/jn.109.105874CrossRefGoogle ScholarPubMed
Esmaillzadeh, A, Kimiagar, M, Mehrabi, Yet al. (2007) Dietary patterns, insulin resistance, and prevalence of the metabolic syndrome in women. Am J Clin Nutr 85, 910918.10.1093/ajcn/85.3.910CrossRefGoogle ScholarPubMed
Naja, F, Nasreddine, L, Itani, Let al. (2013) Association between dietary patterns and the risk of metabolic syndrome among Lebanese adults. Eur J Nutr 52, 97105.10.1007/s00394-011-0291-3CrossRefGoogle ScholarPubMed
Cho, YA, Kim, J, Cho, ERet al. (2011) Dietary patterns and the prevalence of metabolic syndrome in Korean women. Nutr Metab Cardiovasc Dis 21, 893900.10.1016/j.numecd.2010.02.018CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Summary and composition of the misclassified dietary patterns (DP) included in the meta-analysis