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      Dietary protein intake and all-cause and cause-specific mortality: results from the Rotterdam Study and a meta-analysis of prospective cohort studies

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          Abstract

          Evidence for associations between long-term protein intake with mortality is not consistent. We aimed to examine associations of dietary protein from different sources with all-cause and cause-specific mortality. We followed 7786 participants from three sub-cohorts of the Rotterdam Study, a population-based cohort in the Netherlands. Dietary data were collected using food-frequency questionnaires at baseline (1989–1993, 2000–2001, 2006–2008). Deaths were followed until 2018. Associations were examined using Cox regression. Additionally, we performed a highest versus lowest meta-analysis and a dose–response meta-analysis to summarize results from the Rotterdam Study and previous prospective cohorts. During a median follow-up of 13.0 years, 3589 deaths were documented in the Rotterdam Study. In this cohort, after multivariable adjustment, higher total protein intake was associated with higher all-cause mortality [e.g. highest versus lowest quartile of total protein intake as percentage of energy (Q4 versus Q1), HR = 1.12 (1.01, 1.25)]; mainly explained by higher animal protein intake and CVD mortality [Q4 versus Q1, CVD mortality: 1.28 (1.03, 1.60)]. The association of animal protein intake and CVD was mainly contributed to by protein from meat and dairy. Total plant protein intake was not associated with all-cause or cause-specific mortality, mainly explained by null associations for protein from grains and potatoes; but higher intake of protein from legumes, nuts, vegetables, and fruits was associated with lower risk of all-cause and cause-specific mortality. Findings for total and animal protein intake were corroborated in a meta-analysis of eleven prospective cohort studies including the Rotterdam Study (total 64,306 deaths among 350,452 participants): higher total protein intake was associated with higher all-cause mortality [pooled RR for highest versus lowest quantile 1.05 (1.01, 1.10)]; and for dose–response per 5 energy percent (E%) increment, 1.02 (1.004, 1.04); again mainly driven by an association between animal protein and CVD mortality [highest versus lowest, 1.09 (1.01, 1.18); per 5 E% increment, 1.05 (1.02, 1.09)]. Furthermore, in the meta-analysis a higher plant protein intake was associated with lower all-cause and CVD mortality [e.g. for all-cause mortality, highest versus lowest, 0.93 (0.87, 0.99); per 5 E% increment, 0.87 (0.78, 0.98), for CVD mortality, highest versus lowest 0.86 (0.73, 1.00)]. Evidence from prospective cohort studies to date suggests that total protein intake is positively associated with all-cause mortality, mainly driven by a harmful association of animal protein with CVD mortality. Plant protein intake is inversely associated with all-cause and CVD mortality. Our findings support current dietary recommendations to increase intake of plant protein in place of animal protein.

          Clinical trial registry number and website NTR6831, https://www.trialregister.nl/trial/6645

          Electronic supplementary material

          The online version of this article (10.1007/s10654-020-00607-6) contains supplementary material, which is available to authorized users.

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          Most cited references 51

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          Measuring inconsistency in meta-analyses.

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            Bias in meta-analysis detected by a simple, graphical test.

            Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews. Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution.
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              Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

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                Author and article information

                Contributors
                z.chen.1@erasmusmc.nl
                trudy.voortman@erasmusmc.nl
                Journal
                Eur J Epidemiol
                Eur. J. Epidemiol
                European Journal of Epidemiology
                Springer Netherlands (Dordrecht )
                0393-2990
                1573-7284
                19 February 2020
                19 February 2020
                2020
                : 35
                : 5
                : 411-429
                Affiliations
                [1 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Epidemiology, , Erasmus University Medical Center, ; Rotterdam, The Netherlands
                [2 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Nutrition, , Harvard T. H. Chan School of Public Health, ; Boston, MA USA
                [3 ]GRID grid.419770.c, Swiss Paraplegic Research, ; Nottwil, Switzerland
                [4 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Epidemiology, , Harvard T. H. Chan School of Public Health, ; Boston, MA USA
                [5 ]GRID grid.32224.35, ISNI 0000 0004 0386 9924, Clinical and Translational Epidemiology Unit and Division of Gastroenterology, , Massachusetts General Hospital and Harvard Medical School, ; Boston, MA USA
                [6 ]GRID grid.5645.2, ISNI 000000040459992X, Medical Library, , Erasmus MC University Medical Center, ; Rotterdam, The Netherlands
                [7 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Epidemiology, , Erasmus MC, ; Office Na-2718, PO Box 2040, 3000 CA Rotterdam, The Netherlands
                [8 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Epidemiology, , Erasmus MC, ; Office Na-2716, PO Box 2040, 3000 CA Rotterdam, The Netherlands
                Article
                607
                10.1007/s10654-020-00607-6
                7250948
                32076944
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                Categories
                Meta-Analysis
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                © Springer Nature B.V. 2020

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