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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
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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

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