Effect of Lower Versus Higher Red Meat Intake on Cardiometabolic and Cancer Outcomes

Observational studies have reported that intake of red meat is associated with cardiometabolic disease and cancer (18). Dietary guidelines from the United States, United Kingdom, and the World Cancer Fund/American Institute for Cancer Research recomm... show more

Observational studies have reported that intake of red meat is associated with cardiometabolic disease and cancer (18). Dietary guidelines from the United States, United Kingdom, and the World Cancer Fund/American Institute for Cancer Research recommend limiting intake of red and processed meat (810). Such recommendations are primarily based on observational studies that are at high risk for confounding. Randomized trials generally provide higher-certainty evidence supporting causal relationships (11, 12). The few systematic reviews of trials addressing red meat consumption have evaluated only surrogate outcomes, such as blood pressure and lipid levels (1315). In this systematic review of randomized trials, we investigate the effect of lower versus higher red meat intake on the incidence of major cardiometabolic and cancer outcomes. The review was performed by the Nutritional Recommendations (NutriRECS) working group as part of a new initiative to develop trustworthy guideline recommendations in nutrition (16). In addition to this review, we performed 4 parallel systematic reviews that focused on observational studies addressing the effect of red and processed meat consumption on cardiometabolic and cancer outcomes (1719), and a review of health-related values and preferences related to meat consumption (20). These reviews were used to underpin guideline recommendations for consumption of red and processed meats (21). Methods We registered the systematic review protocol in PROSPERO (CRD42017074074) on 10 August 2017 (22). Data Source and Searches We searched MEDLINE, EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), CINAHL (Cumulative Index to Nursing and Allied Health Literature), and the Web of Science from inception until July 2018, and MEDLINE from inception through to April 2019, with no restrictions on language or date of publication (Section I of the Supplement). We also searched ProQuest Dissertations and Theses Global (1989 to 2018); trial registries, including ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform Search Portal, to April 2019; and bibliographies of eligible studies and relevant systematic reviews. Supplement. Supplementary Material Study Selection We included English-language and nonEnglish-language reports of randomized trials of adults allocated to consume diets that included varying quantities of unprocessed red meat (measured as servings or times/week, or as g/d) or processed meat (meat preserved by smoking, curing, salting, or adding preservatives) for 6 months or more (23). Eligible trials compared diets lower in red or processed meat with diets higher in red or processed meat that differed by a gradient of at least 1 serving per week (Table 1). If a trial reported more than 2 study groups (24, 25), we used the groups with the largest gradient in red meat intake or combined groups if red meat intake was equal. Studies in which more than 20% of the participants were pregnant or had cancer or a chronic health condition, other than cardiometabolic diseases, were excluded. Table 1. Study Characteristics Outcomes of interest, which were determined a priori and in consultation with the guideline panel, were all-cause mortality, cardiovascular mortality, adverse cardiometabolic events and major morbidity, cancer mortality and incidence, quality of life, and surrogate outcomes (weight, body mass index, blood lipid levels, blood pressure, and hemoglobin level) (22). Pairs of reviewers screened titles and abstracts for initial eligibility and reviewed the full text of potentially eligible studies, independently and in duplicate. Reviewers resolved disagreements by discussion and third-party adjudication if needed. Data Extraction and Quality Assessment Using standardized, piloted forms, pairs of reviewers conducted calibration exercises and independently extracted information on study design, participant characteristics, interventions, comparators, and outcomes of interest and resolved disagreement by discussion or, if necessary, third-party adjudication. When details related to methods or results were unavailable or unclear, we contacted study authors for additional information. Reviewers, independently and in duplicate, assessed the risk of bias of eligible trials by using a modified version of the Cochrane Collaboration's risk of bias instrument for randomized trials (2628). The modified version categorizes risk of bias as definitely low, probably low, probably high, or definitely high for each of the following domains: sequence generation, allocation sequence concealment, blinding, missing participant outcome data, selective outcome reporting, and other bias (for example, prematurely terminated studies). We resolved any disagreements by discussion or, if necessary, third-party adjudication. We collapsed ratings of probably low and definitely low into low risk of bias and ratings of probably high and definitely high into high risk of bias. Among the 8 risk of bias domains, we considered a study to be at high risk of bias if, at the outcome level, 2 or more domains were at high risk of bias (Section I of the Supplement). Data Synthesis and Analysis We reported risk ratios (RRs), hazard ratios (HRs), and mean differences (MDs) with their 95% CIs for the lowest versus highest category of red meat intake, at the last reported time point. We used the HartungKnappSidikJonkman approach to pool data (29, 30). To calculate absolute risk differences, we multiplied the effect estimate for each outcome with the population risk estimates from the Emerging Risk Factors Collaboration study for cardiometabolic outcomes (31) or from GLOBOCAN for cancer outcomes (32, 33) and, when this was not available, the control group estimate from the largest study (Section I of the Supplement). We investigated heterogeneity by using the Cochran Q test and the I 2 statistic (34). We used R Project, version 3.3.0 (R Foundation for show less