Health-Related Values and Preferences Regarding Meat Consumption

People need to choose from a wide range of foods on a daily basis to meet their nutritional requirements (1). Consumption of different foods may yield both desirable and undesirable health effects (2). In light of recent studies showing an association between consumption of unprocessed red meat and processed meat and adverse health consequences, including increased risk for cancer (3), all-cause (4) and cardiovascular mortality (5), and stroke (6), dietary guidelines have generally endorsed limiting meat intake (79). However, these guidelines have neglected to identify and incorporate their target populations' values and preferences on meat consumption (1013), which are major influences on what foods people eat (1416). Understanding people's health-related values and preferences on meat consumption may improve the trustworthiness of dietary recommendations (17). Therefore, we conducted a systematic review addressing people's health-related values and preferences on meat consumption. This review was done as part of Nutritional Recommendations and Accessible Evidence Summaries Composed of Systematic Reviews (NutriRECS), an initiative that aims to develop trustworthy nutritional recommendations (18). We performed 4 parallel systematic reviews addressing the following: experimental (19) and observational evidence (20) on the effect of red and processed meat on cancer and cardiometabolic outcomes, observational studies on the effect of red and processed meat on cancer outcomes (21), and the effect of varying red and processed meat dietary patterns on cardiometabolic and cancer outcomes (22). On the basis of these reviews, we developed recommendations for red and processed meat and health outcomes (23). Methods We registered the protocol with PROSPERO (CRD42018088854) (24) and adhered to the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) statement (25). Data Sources and Searches We designed and conducted a search in MEDLINE (via PubMed), EMBASE (via Ovid), Web of Science (Institute for Scientific Information), Centre for Agriculture and Biosciences Abstracts (via CABI), International System for Agricultural Science and Technology, and Food Science and Technology Abstracts from inception to July 2018, and an updated search of MEDLINE and EMBASE through June 2019. We combined search terms related to meat consumption, consumer behavior, and values and preferences with the controlled vocabulary from each database. We did not restrict our search by publication status, language, or date of publication (Supplement Table 1). We also reviewed reference lists of the included articles and relevant systematic reviews. Supplement. Supplementary Material* Study Selection We included studies exploring health-related values and preferences on meat consumption if more than 80% of participants were adults (aged 18 years). We considered quantitative (that is, cross-sectional design), qualitative (that is, participant interviews, focus groups), and mixed-methods studies. If studies did not report the participants' ages, we assumed that more than 80% were aged 18 years or older. We included only studies done in Europe, Australia, Canada, the United States, and New Zealand because we considered them to be homogeneous countries reflecting similar socioeconomic characteristics and values. We excluded studies that focused on meat alternatives (for example, cultured, in vitro, functional products, or genetically modified), types (for example, organic), quality (composition, sensory quality or palatability factors, or origin), safety (for example, food handling, chemical hazards or contamination, or storing or preserving), industry (for example, market research to inform or meet consumers' demands), consumption trends, and specific populations (for example, cancer survivors or pregnant women). Before beginning each aspect of the review process, we conducted calibration exercises in which reviewers assessed the same articles and discussed any disagreement, leading to a clarification and a common understanding of criteria and process. After calibration, teams of 2 reviewers independently screened titles and abstracts of all retrieved references. Subsequently, teams of 2 reviewers independently reviewed the full text of articles deemed potentially eligible during title and abstract screening. In cases of disagreement, reviewers reached consensus with assistance from a third reviewer. Data Extraction and Quality Assessment We used 2 ad hoc data extraction forms for quantitative and qualitative research (Supplement Tables 2 and 3). After calibration exercises similar to the ones described earlier, teams of reviewers independently abstracted information from each study, including study identification, objectives or research questions, population characteristics, design and methods, risk of bias or methodological limitations, and findings. In cases of disagreement, reviewers reached consensus with assistance from a third reviewer. For quantitative studies, we used an adapted version of the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach to assess risk of bias of studies on importance of outcomes or values and preferences (26). We considered 5 items grouped in 3 domains: selection of participants, missing outcome data, and measurement instruments' validity. We rated studies as having high risk of bias if the measurement instrument was not validated or was unclear, and as having moderate risk if it was validated but 2 or more items had high risk of bias. For qualitative studies, we used the Critical Appraisal Skills Programme qualitative research checklist, which consists of the following items: aim of the research, qualitative methodology appropriateness, research design, appropriate recruitment strategy, data collection, investigator and participants' relationship, ethical issues, data analysis, findings, and value of the research (27). We rated studies as having serious methodological limitations if more than 2 items had serious concerns and as having moderate methodological limitations if they had 2 items with serious concerns. Reviewers independently assessed risk of bias or methodological limitations. In cases of disagreement, reviewers reached consensus with assistance from a third reviewer. Data Synthesis and Analysis We synthesized results from studies using a 4-step approach that involved simultaneous quantitative and qualitative data collection and analysis. First, we selected 2 to 3 eligible articles per study design, identified key themes, and coded them in categories. Second, we used these categories to design ad hoc data extraction forms. Third, using an iterative process, we compared the key themes of the categories identified across all studies and developed analytic themes. Fourth, we applied the critical meta-narrative synthesis to transform the quantitative data into qualitative data (28, 29). For the last step, we used 4 systematic profiles and several critical questions to extract the identified narratives and to guide our synthesis of data (Supplement Table 4). We synthesized and narratively reported the findings according to participants' meat consumption. We defined those who consumed meat as omnivores and analyzed them separately from persons who typically avoided meat, whom we defined as vegetarians, including lacto-ovo vegetarians or low-meat consumers. For quantitative studies, we assessed the certainty of evidence for each review finding according to GRADE domains (risk of bias, imprecision, inconsistency, indirectness, and publication bias) (30, 31). For qualitative studies, we assessed the certainty of evidence according to GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative Research) domains (methodological limitations, relevance, coherence, and adequacy) (32). Findings were initially considered as high certainty and were downgraded (from high to very low) by 1 or more levels if serious or several minor or moderate concerns were detected in 1 or more domains. Role of the Funding Source The study received no funding. Results The search yielded 19172 articles, of which 456 were deemed potentially eligible on the basis of title and abstract. We excluded 402 studies (Supplement Table 5). After full-text appraisal, we included 41 quantitative (3373) and 13 qualitative studies (7486). The Figure presents the flow diagram with the search results and selection of studies. Figure. Evidence search and selection. AGRIS = International System for Agricultural Science and Technology; CAB = Centre for Agriculture and Biosciences; FSTA = Food Science and Technology Abstracts. Study Characteristics Table 1 presents the characteristics of the 54 included studies. Of the 41 quantitative studies, 21 were done in Europe, 11 in the United States, 7 in Australia, 1 in Canada, and 1 in New Zealand. Eighteen studies were done between 1988 and 2009, and 23 were done between 2011 and 2019. Of the 13 qualitative studies, 7 were done in Europe, 3 in the United States, and 3 in Australia. Six were done between 1991 and 2010, and 7 were done between 2011 and 2018. The number of participants ranged from 100 to 22935 (aged 18 to >65 years) in the quantitative studies and from 19 to 460 (aged 16 to >75 years) in the qualitative studies. Among the included studies, 41 reported data on meat in general, 6 reported data on both meat in general and red meat, and 7 reported data on red meat only. Table 1. Characteristics of the Included Studies Table 1Continued Findings We identified 2 main themes: reasons for meat consumption (38 quantitative [62963 participants] and 10 qualitative [419 participants]) and willingness to reduce meat consumption in the face of undesirable health effects (5 quantitative [8983 participants] and 4 qualitative [616 participants]). Table 2 shows the main findings and their certainty (Supplement Tables 6 and 7). Of the quantitative studies, 23 of 38