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Red/processed meat consumption and non-cancer-related outcomes in humans: umbrella review

Published online by Cambridge University Press:  22 December 2022

Xingxia Zhang
Affiliation:
West China Hospital, Sichuan University, Chengdu, People’s Republic of China
Shiqi Liang
Affiliation:
West China School of Nursing, Sichuan University, Chengdu 610041, People’s Republic of China
Xinrong Chen
Affiliation:
West China School of Nursing, Sichuan University, Chengdu 610041, People’s Republic of China
Jie Yang
Affiliation:
Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
Yong Zhou
Affiliation:
Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
Liang Du
Affiliation:
Chinese Evidence-based Medicine/Cochrane Center, Chengdu, People’s Republic of China
Ka Li*
Affiliation:
West China School of Nursing, Sichuan University, Chengdu 610041, People’s Republic of China
*
*Corresponding author: Ka Li, email [email protected]
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Abstract

The associations of red/processed meat consumption and cancer-related health outcomes have been well discussed. The umbrella review aimed to summarise the associations of red/processed meat consumption and various non-cancer-related outcomes in humans. We systematically searched the systematic reviews and meta-analyses of associations between red/processed meat intake and health outcomes from PubMed, Embase, Web of Science and the Cochrane Library databases. The umbrella review has been registered in PROSPERO (CRD 42021218568). A total of 40 meta-analyses were included. High consumption of red meat, particularly processed meat, was associated with a higher risk of all-cause mortality, CVD and metabolic outcomes. Dose–response analysis revealed that an additional 100 g/d red meat intake was positively associated with a 17 % increased risk of type 2 diabetes mellitus (T2DM), 15 % increased risk of CHD, 14 % of hypertension and 12 % of stroke. The highest dose–response/50 g increase in processed meat consumption at 95 % confident levels was 1·37, 95 % CI (1·22, 1·55) for T2DM, 1·27, 95 % CI (1·09, 1·49) for CHD, 1·17, 95 % CI (1·02, 1·34) for stroke, 1·15, 95 % CI (1·11, 1·19) for all-cause mortality and 1·08, 95 % CI (1·02, 1·14) for heart failure. In addition, red/processed meat intake was associated with several other health-related outcomes. Red and processed meat consumption seems to be more harmful than beneficial to human health in this umbrella review. It is necessary to take the impacts of red/processed meat consumption on non-cancer-related outcomes into consideration when developing new dietary guidelines, which will be of great public health importance. However, more additional randomised controlled trials are warranted to clarify the causality.

Type
Systematic Review and Meta-Analysis
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Nutrition Society

Red meat refers to3 all mammalian muscle meat, including, beef, veal, pork, lamb, mutton, horse and goat, which may be minced or frozen, and are usually consumed cooked(1,Reference Bouvard, Loomis and Guyton2) . Processed meat refers to any meat (including red meat and poultry, offal or meat by-products such as blood) that has been transformed through one or several of the following processes: salting, curing, fermentation, smoking or other processes to enhance flavour or improve preservation(1,Reference Bouvard, Loomis and Guyton2) . The history of meat consumption in humans may date back to the end of the last ice age, 10 000 to 12 000 years ago(Reference Smil3,Reference Potter John4) . Currently, meat is a common part of the daily diet, especially in Western countries. In developed countries such as the USA, Australia and New Zealand, people consume approximately 110–120 kg of meat/year(Reference Potter John4). Recently, a global survey of animal source food consumption across 185 countries found that between 1990 and 2018, mean unprocessed red meat and processed meat intake per person increased globally by 88·1 % and 152·8 %, respectively, and the increase of unprocessed red meat intake in China was largest by 312·5 % (equivalent to an additional 5·89 servings/week) due to increased pork consumption(Reference Miller, Reedy and Cudhea5). According to the FAO of the United Nations, world meat production is projected to double by 2050, most of which is expected in developing countries(6).

Until now, the association between red/processed meat consumption and human health has been widely documented in epidemiological studies and systematic reviews. High red/processed meat consumption was associated with a range of harmful outcomes, especially in chronic non-communicated disease, including CVD, type 2 diabetes mellitus (T2DM)(Reference Neuenschwander, Ballon and Weber7) and many types of tumors(Reference Chao, Thun Michael and Connell Cari8,Reference Ferro, Rosato and Rota9) . Recently, Huang et al. conducted an umbrella review to summarise the associations of red/processed meat intake and several cancer outcomes(Reference Huang, Cao and Chen10). However, there were few publications that overly evaluated the existing evidence of red/processed meat consumption and non-cancer-related outcomes. Considering the large consumption of red/processed meat, we conducted an umbrella review to systematically collect and evaluate data on red/processed meat consumption and non-cancer-related outcomes and provide comprehensive evidence(Reference Papatheodorou11).

Methods

Umbrella review

Umbrella review is a useful tool to help us systematically understand the knowledge of specific topics, which can provide a comprehensive overview of evidence of existing systematic reviews and meta-analyses about a topic area(Reference Aromataris, Fernandez and Godfrey12,Reference Yi, Wu and Zhuang13) . We carried out an umbrella review of red meat and processed meat consumption on diverse health-related outcomes by retrieving comprehensive evidence. The umbrella review has been registered in PROSPERO (CRD 42021218568).

Literature research

We searched PubMed, Embase, Web of Science and the Cochrane Library for related studies from inception to February 2022. The search strategy was as follows: (red meat OR processed meat OR beef OR veal OR pork* OR lamb OR mutton OR ham OR sausage* OR bacon OR frankfurter*) AND (systematic review* OR meta-analys*), and the terms were truncated for all fields. The references included in each eligible meta-analysis were also searched by hand. The search strategies are shown in Supplementary Table 1. The processes of literature retrieval were performed by two authors independently following predefined eligibility criteria. Any discrepancies were resolved by consensus or involved in the third one.

Eligibility criteria

Whether a meta-analysis was eligible for our umbrella review or not depended on the following criteria: (1) Systematic reviews with meta-analysis (quantitative analysis) of observational studies or interventional studies evaluated the associations of red and/or processed meat with non-cancer-related outcomes in human beings; (2) the pooled relative risk, hazard risk and odds risk for observational studies and the mean difference and weight mean difference for meta-analyses of interventional studies were reported and (3) published in English language. Meta-analysis with total red meat (refers to no processed red meat and processed red meat), red meat (refers to no processed red meat) and processed meat intake (refers to processed red meat or white meat such as chicken) was included, while meta-analysis with mixed types of meat consumption (for example, red meat and white meat were not discussed separately) was excluded. Meta-analyses on biological indicators such as blood lipids rather than health-related outcomes were excluded. Systematic reviews without quantitative analysis were excluded as well. Any disagreements were resolved by discussion.

Data extraction

Two researchers extracted the data independently. The following information in each eligible meta-analysis was recorded: health-related outcomes, mane of first author, publication year, types of meat (red/processed), number and designs (randomised controlled trial/cohort/case–control/cross-section) of studies included in each meta-analysis, number of total participants in each meta-analysis, population, dose–response analysis, period of follow-up, effects model (random/fixed), metric, the pooled estimates and 95 % confidential interval (95 % CI), heterogeneity of each outcome and publication bias. When a meta-analysis reported more than one outcome, or a meta-analysis included various meats, we extracted them one by one. If two or more meta-analyses investigated the same health outcome, the one with the highest quality was included.

Assessment of methodological quality and quality of evidence of included meta-analysis

We used the AMSTAR 2 (Revised AMSTAR: A Measurement Tool to Access Systematic Reviews) to assess the methodological quality of each involved meta-analysis, which was a critical appraisal tool for systematic review of observational or interventional study consisting of sixteen items including seven critical domains and grades the methodological quality of each meta-analysis as ‘high’, ‘moderate’, ‘low’ and ‘critically low’ based on detailed and specific explanations of bias(Reference Shea, Reeves and Wells14,15) . The Nutri-GRADE (Grading of Recommendations Assessment, Development and Evaluation, GRADE) system was used to assess the quality of evidence for the included meta-analysis, which was modified from GRADE by Lukas et al. (Reference Schwingshackl, Knüppel and Schwedhelm16) to rate the certainty of meta-evidence from nutritional studies(Reference Tobias, Wittenbecher and Hu17). It assorts the quality of meta-evidence from cohort studies as ‘high’ (8–10 points), ‘moderate’ (6–7·99 points), ‘low’ (4–5·99) and ‘very low’ (0–3·99) according to eight items including risk of bias, precision, heterogeneity, directions, publication bias, funding bias, effect size and dose–response(Reference Schwingshackl, Knüppel and Schwedhelm16).

Data analysis

The summary estimates and 95 % CI of each related outcome were extracted and calculated by fixed or random effects methods. We extracted the I 2 metric and Egger’s test or Begg’s test to measure the heterogeneity and publication bias if they were available. A P < 0·1 for Egger’s regression test was regarded as statistically significant publication bias. If the total estimate effects were not reported, we chose the outcomes derived from cohort rather than case–control or cross-sectional studies because of the strengths of the study design. We did not reanalyse other data or primary studies included in the meta-analysis.

Results

Characteristics of the meta-analyses

We searched PubMed, Embase, Web of Science and the Cochrane Library to identify data investigating the association of red and/or processed meat consumption and non-cancer-related outcomes in humans. The search yielded forty-two meta-analyses related to the topic. The other two meta-analyses(Reference O’Connor, Kim and Campbell18,Reference Guasch-Ferre, Satija and Blondin19) of randomised controlled trials were excluded in the main text because the outcome indicators were blood lipids (online Supplementary Table 2). Finally, forty meta-analyses of observational studies with fifty-four unique outcomes were included in the umbrella review. The processes and results of systematic selection are shown Fig. 1. Thirteen meta-analyses exploring the associations of meat consumption and health outcome were excluded because all of them failed to specify the kinds of meat. The associations between red/processed meat and all non-cancer-related outcomes are available in Supplementary Table 2. The map of outcomes associated with red/processed meat consumption is shown in Fig. 2.

Fig. 1. The flow chart of selection process.

Fig. 2. Map of outcomes associated with red/processed meat consumption.

Mortality

Red meat consumption was related to an 11 % accession in CVD mortality risk (95 % CI (1·09, 1·14))(Reference Zeraatkar, Han and Guyatt20). Processed meat consumption was associated with a higher risk of all-cause mortality (1·09; 95 % CI (1·04, 1·10))(Reference Zeraatkar, Han and Guyatt20), CVD mortality (1·11; 95 % CI (1·03, 1·19))(Reference Zeraatkar, Han and Guyatt20) and cancer mortality (1·08; 95 % CI (1·06, 1·11))(Reference Wang, Lin and Ouyang21). Dose–response analysis showed that one serving/d consumption of processed meat was related to a 15 % higher risk of all-cause mortality (95 % CI (1·11, 1·19))(Reference Wang, Lin and Ouyang21). The associations of red/processed meat consumption and mortality are shown in Table 1.

Table 1. Associations between red/processed meat consumption and mortality

MA, meta-analysis; RMT, red meat; PMT, processed meat; RR, risk ratio; HR, hazard ratio; NR, not report; VS, verse.

Cardiovascular outcomes

High red meat intake was related to an increased risk of ischaemic heart disease (1·09; 95 % CI (1·06, 1·12)(Reference Papier, Knuppel and Syam22), CHD (1·16; 95 % CI (1·08, 1·24)(Reference Bechthold, Boeing and Schwedhelm23), stroke (1·16; 95 % CI (1·08, 1·25)(Reference Bechthold, Boeing and Schwedhelm23), hypertension (1·15; 95 % CI (1·02, 1·28)(Reference Schwingshackl, Schwedhelm and Hoffmann24) and heart failure (1·12; 95 % CI (1·04, 1·21))(Reference Bechthold, Boeing and Schwedhelm23). In the dose–response analysis, each additional daily 100 g red meat was positively associated with a 15 % increased risk of CHD, 14 % of hypertension(Reference Schwingshackl, Schwedhelm and Hoffmann24), 12 % of stroke and 8 % of heart failure(Reference Bechthold, Boeing and Schwedhelm23).

Processed meat consumption was associated with an increased risk of CVD, with an estimated relative risk of 1·23; 95 % CI (1·07, 1·41)(Reference Cui, Liu and Zhu25) for heat failure, 1·18; 95 % CI (1·12, 1·25)(Reference Papier, Knuppel and Syam22) for ICH, 1·16; 95 % CI (1·07, 1·26)(Reference Bechthold, Boeing and Schwedhelm23) for stroke and 1·12; 95 % CI (1·02, 1·23)(Reference Zhang and Zhang26) for hypertension. Dose–response analysis revealed that more than 50 g processed meat intake/d was associated with a higher risk of CHD (1·27; 95 % CI (1·09, 1·49)(Reference Bechthold, Boeing and Schwedhelm23), stroke (1·17; 1·02, 1·34)(Reference Bechthold, Boeing and Schwedhelm23), heart failure (1·12; 95 % CI (1·05, 1·19)(Reference Bechthold, Boeing and Schwedhelm23) and hypertension (1·12; 95 % CI (1·00, 1·26))(Reference Schwingshackl, Schwedhelm and Hoffmann24). The associations between red/processed meat consumption and CVD are shown in Table 2.

Table 2. Associations between red/processed meat consumption and cardiovascular outcomes

MA, meta-analysis; IHD, ischaemic heart disease; HF, heart failure; RR, risk ratio; HR, hazard ratio; NR, not report; VS, verse.

Metabolic outcomes

High red meat consumption was related to a higher risk of metabolic syndrome (1·32; 95 % CI (1·14, 1·54))(Reference Guo, Ding and Liang27), abdominal obesity (1·18; 95 % CI (1·06, 1·32))(Reference Schlesinger, Neuenschwander and Schwedhelm28), T2DM (1·15; 95 % CI (1·08, 1·23))(Reference Zhang, Fu and Moore29) and non-alcoholic fatty liver disease (1·12, 95 % CI (1·04, 1·21))(Reference He, Li and Guo30). Dose–response showed that a 100 g/d increase in red meat was associated with a 17 % increased risk of T2DM (95 % CI (1·08, 1·26))(Reference Schwingshackl, Hoffmann and Lampousi31), a 10 % higher risk of abdominal obesity(Reference Schlesinger, Neuenschwander and Schwedhelm28) and a 14 % increased risk of weight gain(Reference Schlesinger, Neuenschwander and Schwedhelm28).

Processed meat intake was associated with a higher risk of metabolic syndrome (1·48; 95 % CI (1·11, 1·97)(Reference Guo, Ding and Liang27), T2DM (1·27; 95 % CI (1·15, 1·40)(Reference Zhang, Fu and Moore29), obesity (1·82; 95 % CI (1·69, 1·97)(Reference Daneshzad, Askari and Moradi32) and abdominal obesity (8·8; 95 % CI (1·20, 64·28))(Reference Schlesinger, Neuenschwander and Schwedhelm28). Dose–response analysis found that the risk of T2DM increased by 37 %, 95 % CI (1·22, 1·55))(Reference Schwingshackl, Hoffmann and Lampousi31) for each 50 g/d increment in processed meat consumption. The associations between red/processed meat consumption and metabolic outcomes are shown in Table 3.

Table 3. Associations between red/processed meat consumption and metabolic and other outcomes

MA, meta-analysis; BE, Barrett’s oesophagus; WG, weight gain; T2DM, type 2 diabetes mellitus; MS, metabolic syndrome; COPD, chronic obstructive pulmonary disease; IBD, Inflammatory bowel disease; WC, waist circumference; AO, abdominal obesity; NAFLD, non-alcoholic fatty liver disease; RR, risk ratio; HR, hazard ratio; MD, mean difference; NR, not report.

* Number of cases.

Other outcomes

The highest red meat intake was associated with a higher risk of inflammatory bowel disease (2·37; 95 % CI (1·40, 3·99))(Reference Ge, Han and Liu33). In addition, there was a significant association between processed red meat consumption and the risk of COPD (hazard risk: 1·40; 95 % CI (1·21, 1·62))(Reference Salari-Moghaddam, Milajerdi and Larijani34). Linear dose–response analysis showed that each 50 g/week increase in processed red meat intake was associated with an 8 % higher risk of COPD (1·08; 95 % CI (1·03, 1·13))(Reference Salari-Moghaddam, Milajerdi and Larijani34) (Table 3).

Heterogeneity

In all the included studies, approximately 23·3 % of the meta-analyses had lower heterogeneity, with I 2 < 25 %; approximately 28·4 % of the meta-analyses had moderate heterogeneity, with I 2 between 25 % and 75 %; and 23·3 % of meta-analyses had high heterogeneity, with I 2 > 75 %. In addition, approximately 5 % of the results were derived from a single study; therefore, heterogeneity does not apply. However, 20 % of studies did not report heterogeneity, and we could not reanalyse because of the unavailability of information. The heterogeneity of each meta-analysis may be influenced by geographical and demographic factors, the difference in parades, the measurement of meat consumption, the volume of meat consumption and the time of follow-up and the evaluation of the results (online Supplementary Table 2).

Publication bias

Funnel plots, Egger’s test and Begg’s test were used in this umbrella. Approximately 58·3 % of studies reported that there were no publication biases. Two meta-analyses found significant evidence for publication biases in studies of meat consumption and metabolic syndrome(Reference Guo, Ding and Liang27) (P = 0·07) and waist circumference(Reference Rouhani, Salehi-Abargouei and Surkan35) (P = 0·052). The other meta-analysis did not report the outcomes of publication bias due to the insufficient number of studies.

The methodological quality of included meta-analyses

The results of the methodological quality assessment are shown in Table 4 (AMSTAR-2). The retrieved meta-analyses were rated as four levels: 45·0 % were rated as ‘high’, approximately 2·5 % were rated as ‘moderate’, approximately 32·0 % were rated as ‘low’ and 20·0 % were classified as ‘critically low’. The reason was that most studies failed to report the funding sources of the single article included in each meta-analysis (Item 10 of AMSTA-2).

Table 4. Results of AMSTAR-2 and Nutri-GRADE

AMSTAR, a measurement tool to access systematic reviews; Nutri-GRADE, the grading of recommendations assessment, development, and evaluation for nutrition research; ICH, ischaemic heart disease; NAFLD, non-alcoholic fatty liver disease; COPD, chronic obstructive pulmonary disease; IBD, Inflammatory bowel disease.

The quality of the meta-evidence

The results of quality of the meta-evidence are shown in Table 4 (Nutri-GRADE), and the detail scores of items in Nutri-GRADE are shown in Supplementary Table 3. Approximately 47·5 % were graded as ‘moderate’, 17·5 % were graded as ‘low’ and 35·0 % were graded as ‘very low’. None of the associations was stratified as ‘high’. The main reason was that many of those outcomes came from sub-group analysis with a limited number of studies and resulted in 0 points in the items 3 and 5. In addition, many meta-analyses failed to conduct dose–response analysis, and the effect size was limited.

Discussion

Main findings of the umbrella review

A total of forty meta-analyses of observational studies with forty unique health-related outcomes were included in our umbrella review. Red and processed meat consumption likely did more harm than benefits for a variety of non-cancer-related outcomes in this umbrella review. Red meat, especially processed meat consumption, was associated with an increased risk of all-cause mortality, CVD and metabolic outcomes.

Red/processed meat consumption was associated with an increased risk of all-cause mortality and cause-specific mortality in our umbrella review, which is consistent with the risk of CVD and cancer. Recently, a cohort study(Reference Zhong, Van Horn and Greenland36) with 29 682 participants found that red meat and processed meat consumption was significantly associated with all-cause mortality (adjusted hazard risk, 1·03 (95 % CI (1·01, 1·05); adjusted hazard risk, 1·03 (95 % CI (1·02, 1·05), respectively). This may be because the major cause of all-cause mortality is likely to be a combination of CVD and cancer aetiology(Reference Kwok, Gulati and Michos37). The carcinogenic effects of red and processed meat have been well investigated in both epidemiological and laboratory studies(Reference Huang, Cao and Chen10,Reference Gamage, Dissabandara and Lam38Reference Soladoye, Shand and Dugan41) . The International Agency for Research on Cancer classified the consumption of processed meat as ‘carcinogenic to humans’ (Group 1) and red meat as ‘probably carcinogenic to humans’ (Group 2A) in 2015(Reference Bouvard, Loomis and Guyton42).

High red/processed meat consumption was related to an increased risk of CVD, including CHD/(ischaemic heart disease) stroke, hypertension and heart failure. Red and processed meat consumption was associated with several non-communicable diseases, including hypertension, diabetes and vascular depression(Reference Willett, Rockström and Loken43). Recently, many prospective cohort studies have shown consistent results(Reference Al-Shaar, Satija and Wang44,Reference Key, Appleby and Bradbury45) . Several mechanisms may contribute to the adverse effect of red/processed meat intake on CVD risk: (1) Red meat is high in saturated fat and cholesterol, and consumption of red meat has been linked to higher levels of LDL-cholesterol in the blood(Reference Guasch-Ferré, Satija and Blondin46). If the concentration of LDL-cholesterol in the blood increases, it will be deposited in the arterial wall of the blood vessels in the heart and brain and gradually form atherosclerotic plaques, which will block the corresponding blood vessels, and cause serious diseases such as stroke and peripheral arterial disease; (2) heme Fe, which is abundant in red meat, has been established and was associated with an increased risk of CVD. A study showed that each 1 mg/d increase in heme Fe intake was associated with a 7 % increase in the risk of CVD (95 % CI (1·01, 1·14))(Reference Fang, An and Wang47). Excess heme iron might catalyse several cellular reactions, thus increasing the levels of oxidative stress(Reference Rajpathak, Crandall and Wylie-Rosett48), and leading to enhanced lipid peroxidation, protein modification and DNA damage(Reference Rajpathak, Crandall and Wylie-Rosett48,Reference Hori, Mizoue and Kasai49) ; (3) high salt and Na were the conceived factors for hypertension(Reference He, Li and Macgregor50), and the high sodium and salt content of processed meat may increase blood pressure, which was associated with a higher risk of CVD. Studies have shown that a reduction in salt intake will likely lower population BP and, thereby, reduce cardiovascular disease(Reference He, Li and Macgregor51). The largest differences between processed and unprocessed meat are sodium and nitrates, which are 400 % and 50 % higher/g of meat, respectively(Reference Micha, Michas and Mozaffarian52); and (4) in addition, L-carnitine(Reference Koeth, Wang and Levison53), sialic acid N-glycolylneuraminic acid(Reference Kawanishi, Dhar and Do54) in red meat and preservatives in processed red meat, such as nitrates and nitrate by-products, contribute to the risk of CVD such as atherosclerosis, endothelial dysfunction and insulin resistance(Reference Al-Shaar, Satija and Wang44,Reference Förstermann55) .

High red/processed meat consumption was associated with T2DM, metabolic syndrome, obesity and other metabolic outcomes in the umbrella review. For more than a decade, epidemiological studies have shown that a Western diet characterised by high consumption of red and processed meats is related to a higher risk of T2DM both in men(Reference van Dam, Rimm and Willett56) and women(Reference Schulze, Manson and Willett57). There are several possible mechanisms: (1) Clinical trials and animal models have shown that the ingredients and metabolites of red/processed meat include saturated fatty acids (SFA), sodium, advanced glycation end products (AGEs), nitrates/nitrites, heme iron, trimethylamine N-oxide (TMAO), branched amino acids (BCAAs) and endocrine disruptor chemicals (EDCs), which play a role in the development of T2DM by increasing insulin resistance and other pathways(Reference Kim, Keogh and Clifton58); (2) Red meat is a major source of heme iron, which is a strong pro-oxidant that leads to increased levels of oxidative stress, which can lead to tissue damage, particularly pancreatic beta cells, and therefore increase the risk of T2DM(Reference Li, Wang and Lu59); (3) Several studies have shown that a high intake of dietary protein has negative effects on glucose homeostasis by facilitating insulin resistance and increasing gluconeogenesis; and (4) saturated fatty acids may contribute to the aetiology of metabolic disorders(Reference Storlien, Hulbert and Else60). The main compounds of red meat such as iron, nitrites and Na, from processed red meat have been proven to be related to the risk of MetS(Reference de Oliveira Otto, Alonso and Lee61,Reference Altamura, Müdder and Schlotterer62) . In addition, Choi et al. found an association between the presence of the minor alleles of rs662799 and high red and processed meat consumption and the incidence of MetS in Korean adults(Reference Kokkinopoulou, McGowan and Brogan63).

Strengths and limitations

The umbrella review systematically summarised the current evidence for red meat and processed meat intake and a series of non-cancer-related outcomes in humans. The AMSTAR-2 and Nutria-GRADE were used to assess the quality of methods and the evidence for each meta-analysis. However, several possible limitations should be considered. The meta-analysis with pooled analysis was included, and systematic reviews without meta-analyses were omitted, which would have impacts on the outcomes. In addition, most of the outcomes came from observational studies, which may limit the power of the association effect for each outcome due to heterogeneity and bias across studies. Besides, this umbrella review emphasised the association of red/processed meat intake and non-cancer-related health outcomes, and the cancer-related outcomes were omitted because they have been well discussed. Last but not least, we are unable to compare the differences in the effects of unprocessed red meat or processed red meat on human health at the same serving size according to existing literature because the amount of red meat consumption is mostly 100 g and that of processed meat is mostly 50 g in all of the included meta-analyses. Obviously, this is a great idea to compare the differences of the two at the same serving size in future studies.

Conclusions

Red and processed meat consumption is positively associated with a higher risk of several non-cancer-related outcomes in this umbrella review. Reduction of red meat, especially processed red meat consumption, should be taken into consideration when developing nutrition-related policies, which will be of great public health importance. However, more additional randomised controlled trials are warranted to clarify the causality.

Acknowledgements

We are highly indebted to Yuying Zhang for providing guidance in discussion.

This work was supported by National Natural Science Foundation of China (grant number 71974135).

X. Z. formulated the research question and wrote the article; K. L. and Y. Z. designed the study and improved help in interpreting the findings; D. L. gave a hand in analysing the data; S. L. and J. Y. gave help in carrying out the study.

There are no conflicts of interest.

Supplementary material

For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S0007114522003415

References

IARC Working Group on the Evaluation of Carcinogenic Risks to Humans (2018) Red Meat and Processed Meat. Lyon: International Agency for Research on Cancer.Google Scholar
Bouvard, V, Loomis, D, Guyton, KZ, et al. (2015) Carcinogenicity of consumption of red and processed meat. Lancet Oncol 16, 15991600.CrossRefGoogle ScholarPubMed
Smil, V (2002) Eating meat: evolution, patterns, and consequences. Popul Dev Rev 28, 599639.CrossRefGoogle Scholar
Potter John, D (2017) Red and processed meat, and human and planetary health. BMJ 357, j2190.CrossRefGoogle ScholarPubMed
Miller, V, Reedy, J, Cudhea, F, et al. (2022) Global, regional, and national consumption of animal-source foods between 1990 and 2018: findings from the global dietary database. Lancet Planet 6, e243e256.CrossRefGoogle ScholarPubMed
FAO (2012) Balanced feeding for improving livestock productivity – Increase in milk production and nutrient use efficiency and decrease in methane emission, by M.R. Garg. FAO Animal Production and Health Paper No. 173. Rome, Italy.Google Scholar
Neuenschwander, M, Ballon, A, Weber, K, et al. (2019) Role of diet in type 2 diabetes incidence: umbrella review of meta-analyses of prospective observational studies. BMJ 366, l2368.CrossRefGoogle ScholarPubMed
Chao, A, Thun Michael, J, Connell Cari, J, et al. (2005) Meat consumption and risk of colorectal cancer. JAMA 293, 172182.CrossRefGoogle ScholarPubMed
Ferro, A, Rosato, V, Rota, M, et al. (2019) Meat intake and risk of gastric cancer in the stomach cancer pooling (StoP) project. Int J Cancer 147, 4555.CrossRefGoogle ScholarPubMed
Huang, Y, Cao, D, Chen, Z, et al. (2021) Red and processed meat consumption and cancer outcomes: umbrella review. Food Chem 356, 129697.CrossRefGoogle ScholarPubMed
Papatheodorou, S (2019) Umbrella reviews: what they are and why we need them. Eur J Epidemiol 34, 543546.CrossRefGoogle Scholar
Aromataris, E, Fernandez, R, Godfrey, C, et al. (2015) Summarizing systematic reviews: methodological development, conduct and reporting of an umbrella review approach. Int J Evid-Based Heath 13, 132140.CrossRefGoogle ScholarPubMed
Yi, M, Wu, X, Zhuang, W, et al. (2019) Tea consumption and health outcomes: umbrella review of meta-analyses of observational studies in humans. Mol Nutr Food Res 63, e1900389.CrossRefGoogle ScholarPubMed
Shea, BJ, Reeves, BC, Wells, G, et al. (2017) AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ 358, j4008.CrossRefGoogle ScholarPubMed
AMSTAR Working Group (2017) AMSTAR Checklist. www.amstar.ca (accessed October 2021).Google Scholar
Schwingshackl, L, Knüppel, S, Schwedhelm, C, et al. (2016) Perspective: nutrigrade: a scoring system to assess and judge the meta-evidence of randomized controlled trials and cohort studies in nutrition research. Adv Nutr 7, 9941004.CrossRefGoogle ScholarPubMed
Tobias, D, Wittenbecher, C & Hu, F (2021) Grading nutrition evidence: where to go from here? Am J Clin Nutr 113, 13851387.CrossRefGoogle Scholar
O’Connor, LE, Kim, JE & Campbell, WW (2017) Total red meat intake of >/=0.5 servings/d does not negatively influence cardiovascular disease risk factors: a systemically searched meta-analysis of randomized controlled trials. Am J Clin Nutr 105, 5769.CrossRefGoogle Scholar
Guasch-Ferre, M, Satija, A, Blondin, SA, et al. (2019) Meta-analysis of randomized controlled trials of red meat consumption in comparison with various comparison diets on cardiovascular risk factors. Circulation 139, 18281845.CrossRefGoogle ScholarPubMed
Zeraatkar, D, Han, MA, Guyatt, GH, et al. (2019) Red and processed meat consumption and risk for all-cause mortality and cardiometabolic outcomes: a systematic review and meta-analysis of cohort studies. Ann Intern Med 171, 703710.CrossRefGoogle ScholarPubMed
Wang, X, Lin, X, Ouyang, YY, et al. (2016) Red and processed meat consumption and mortality: dose-response meta-analysis of prospective cohort studies. Public Health Nutr 19, 893905.CrossRefGoogle ScholarPubMed
Papier, K, Knuppel, A, Syam, N, et al. (2021) Meat consumption and risk of ischemic heart disease: a systematic review and meta-analysis. Crit Rev Food Sci Nutr 63, 426–437.Google ScholarPubMed
Bechthold, A, Boeing, H, Schwedhelm, C, et al. (2019) Foood groups and risk of coronary heart disease, stroke and heart failure: a systematic review and dose-response meta-analysis of perspective studies. Crit Rev Food Sci Nutr 59, 10711090.CrossRefGoogle Scholar
Schwingshackl, L, Schwedhelm, C, Hoffmann, G, et al. (2017) Food groups and risk of hypertension: a systematic review and dose-response meta-analysis of prospective studies. Adv Nutr 8, 793803.CrossRefGoogle ScholarPubMed
Cui, K, Liu, Y, Zhu, L, et al. (2019) Association between intake of red and processed meat and the risk of heart failure: a meta-analysis. BMC Public Health 19, 354.CrossRefGoogle ScholarPubMed
Zhang, Y & Zhang, DZ (2018) Red meat, poultry, and egg consumption with the risk of hypertension: a meta-analysis of prospective cohort studies. J Hum Hypertens 32, 507517.CrossRefGoogle ScholarPubMed
Guo, H, Ding, J, Liang, J, et al. (2021) Association of red meat and poultry consumption with the risk of metabolic syndrome: a meta-analysis of prospective cohort studies. Front Nutr 8, 691848.CrossRefGoogle ScholarPubMed
Schlesinger, S, Neuenschwander, M, Schwedhelm, C, et al. (2019) Food groups and risk of overweight, obesity, and weight gain: a systematic review and dose-response meta-analysis of prospective studies. Adv Nutr 10, 205218.CrossRefGoogle ScholarPubMed
Zhang, R, Fu, J, Moore, JB, et al. (2021) Processed and unprocessed red meat consumption and risk for type 2 diabetes mellitus: an updated meta-analysis of cohort studies. Int J Environ Res Public Health 18, 20.Google ScholarPubMed
He, K, Li, Y, Guo, X, et al. (2020) Food groups and the likelihood of non-alcoholic fatty liver disease: a systematic review and meta-analysis. Br J Nutr 124, 113.CrossRefGoogle ScholarPubMed
Schwingshackl, L, Hoffmann, G, Lampousi, AM, et al. (2017) Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. Eur J Epidemiol 32, 363375.CrossRefGoogle ScholarPubMed
Daneshzad, E, Askari, M, Moradi, M, et al. (2021) Red meat, overweight and obesity: a systematic review and meta-analysis of observational studies. Clin Nutr ESPEN 45, 6674.CrossRefGoogle ScholarPubMed
Ge, J, Han, TJ, Liu, J, et al. (2015) Meat intake and risk of inflammatory bowel disease: a meta-analysis. Turk J Gastroenterol 26, 492497.CrossRefGoogle ScholarPubMed
Salari-Moghaddam, A, Milajerdi, A, Larijani, B, et al. (2019) Processed red meat intake and risk of COPD: a systematic review and dose-response meta-analysis of prospective cohort studies. Clin Nutr 38, 11091116.CrossRefGoogle ScholarPubMed
Rouhani, MH, Salehi-Abargouei, A, Surkan, PJ, et al. (2014) Is there a relationship between red or processed meat intake and obesity? A systematic review and meta-analysis of observational studies. Obes Rev 15, 740748.CrossRefGoogle ScholarPubMed
Zhong, V, Van Horn, L, Greenland, P, et al. (2020) Associations of processed meat, unprocessed red meat, poultry, or fish intake with incident cardiovascular disease and all-cause mortality. JAMA Intern 180, 503512.CrossRefGoogle ScholarPubMed
Kwok, CS, Gulati, M, Michos, ED, et al. (2019) Dietary components and risk of cardiovascular disease and all-cause mortality: a review of evidence from meta-analyses. Eur J Prev Cardiol 26, 14151429.CrossRefGoogle ScholarPubMed
Gamage, SMK, Dissabandara, L, Lam, AK, et al. (2018) The role of heme iron molecules derived from red and processed meat in the pathogenesis of colorectal carcinoma. Crit Rev Oncol 126, 121128.CrossRefGoogle ScholarPubMed
Knekt, P, Järvinen, R, Dich, J, et al. (1999) Risk of colorectal and other gastro-intestinal cancers after exposure to nitrate, nitrite and N-nitroso compounds: a follow-up study. Int J Cancer 80, 852856.3.0.CO;2-S>CrossRefGoogle ScholarPubMed
Singh, L, Varshney, JG & Agarwal, T (2016) Polycyclic aromatic hydrocarbons’ formation and occurrence in processed food. Food Chem 199, 768781.CrossRefGoogle ScholarPubMed
Soladoye, OP, Shand, P, Dugan, MER, et al. (2017) Influence of cooking methods and storage time on lipid and protein oxidation and heterocyclic aromatic amines production in bacon. Food Res Int 99, 660669.CrossRefGoogle ScholarPubMed
Bouvard, V, Loomis, D, Guyton, K, et al. (2015) Carcinogenicity of consumption of red and processed meat. Lancet Oncol 16, 15991600.CrossRefGoogle ScholarPubMed
Willett, W, Rockström, J, Loken, B, et al. (2019) Food in the Anthropocene: the EAT-Lancet Commission on healthy diets from sustainable food systems. Lancet 393, 447492.CrossRefGoogle ScholarPubMed
Al-Shaar, L, Satija, A, Wang, D, et al. (2020) Red meat intake and risk of coronary heart disease among US men: prospective cohort study. BMJ 371, m4141.CrossRefGoogle ScholarPubMed
Key, T, Appleby, P, Bradbury, K, et al. (2019) Consumption of meat, fish, dairy products, and eggs and risk of ischemic heart disease. Circulation 139, 28352845.CrossRefGoogle ScholarPubMed
Guasch-Ferré, M, Satija, A, Blondin, S, et al. (2019) Meta-analysis of randomized controlled trials of red meat consumption in comparison with various comparison diets on cardiovascular risk factors. Circulation 139, 18281845.CrossRefGoogle ScholarPubMed
Fang, X, An, P, Wang, H, et al. (2015) Dietary intake of heme iron and risk of cardiovascular disease: a dose-response meta-analysis of prospective cohort studies. Nutr Metab Cardiovas 25, 2435.CrossRefGoogle ScholarPubMed
Rajpathak, S, Crandall, J, Wylie-Rosett, J, et al. (2009) The role of iron in type 2 diabetes in humans. Biochim Biophys Acta Gen Subj 1790, 671681.CrossRefGoogle ScholarPubMed
Hori, A, Mizoue, T, Kasai, H, et al. (2010) Body iron store as a predictor of oxidative DNA damage in healthy men and women. Cancer Sci 101, 517522.CrossRefGoogle ScholarPubMed
He, F, Li, J & Macgregor, G (2013) Effect of longer term modest salt reduction on blood pressure: Cochrane systematic review and meta-analysis of randomised trials. BMJ 346, f1325.CrossRefGoogle ScholarPubMed
He, F, Li, J & Macgregor, G (2013) Effect of longer-term modest salt reduction on blood pressure. Cochrane Database Syst Rev 67, 1189–1195.Google Scholar
Micha, R, Michas, G & Mozaffarian, D (2012) Unprocessed red and processed meats and risk of coronary artery disease and type 2 diabetes – an updated review of the evidence. Curr Atheroscler Rep 14, 515524.CrossRefGoogle ScholarPubMed
Koeth, R, Wang, Z, Levison, B, et al. (2013) Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med 19, 576585.CrossRefGoogle ScholarPubMed
Kawanishi, K, Dhar, C, Do, R, et al. (2019) NHuman species-specific loss of CMP–acetylneuraminic acid hydroxylase enhances atherosclerosis via intrinsic and extrinsic mechanisms. PNAS 116, 1603616045.CrossRefGoogle Scholar
Förstermann, U (2008) Oxidative stress in vascular disease: causes, defense mechanisms and potential therapies. Nat Clin Pract Card 5, 338349.CrossRefGoogle ScholarPubMed
van Dam, R, Rimm, E, Willett, W, et al. (2002) Dietary patterns and risk for type 2 diabetes mellitus in U.S. men. Ann Inter Med 136, 201209.CrossRefGoogle ScholarPubMed
Schulze, M, Manson, J, Willett, W, et al. (2003) Processed meat intake and incidence of Type 2 diabetes in younger and middle-aged women. Diabetologia 46, 14651473.CrossRefGoogle ScholarPubMed
Kim, Y, Keogh, J & Clifton, P (2015) A review of potential metabolic etiologies of the observed association between red meat consumption and development of type 2 diabetes mellitus. Metab Clin Exp 64, 768779.CrossRefGoogle ScholarPubMed
Li, S, Wang, F, Lu, X, et al. (2021) Dietary iron intake and the risk of type 2 diabetes mellitus in middle-aged and older adults in urban China: a prospective cohort study. Br J Nutr 126, 10911099.CrossRefGoogle ScholarPubMed
Storlien, L, Hulbert, A & Else, P (1998) Polyunsaturated fatty acids, membrane function and metabolic diseases such as diabetes and obesity. Curr Opin Clin Nutr Metab Care 1, 559563.CrossRefGoogle ScholarPubMed
de Oliveira Otto, M, Alonso, A, Lee, D, et al. (2012) Dietary intakes of zinc and heme iron from red meat, but not from other sources, are associated with greater risk of metabolic syndrome and cardiovascular disease. J Nutr 142, 526533.CrossRefGoogle Scholar
Altamura, S, Müdder, K, Schlotterer, A, et al. (2021) Iron aggravates hepatic insulin resistance in the absence of inflammation in a novel db/db mouse model with iron overload. Mol Metab 51, 101235.CrossRefGoogle Scholar
Kokkinopoulou, A, McGowan, R, Brogan, Y, et al. (2022) Associations between Christian orthodox church fasting and adherence to the world cancer research fund’s cancer prevention recommendations. Nutrients 14.CrossRefGoogle Scholar
Figure 0

Fig. 1. The flow chart of selection process.

Figure 1

Fig. 2. Map of outcomes associated with red/processed meat consumption.

Figure 2

Table 1. Associations between red/processed meat consumption and mortality

Figure 3

Table 2. Associations between red/processed meat consumption and cardiovascular outcomes

Figure 4

Table 3. Associations between red/processed meat consumption and metabolic and other outcomes

Figure 5

Table 4. Results of AMSTAR-2 and Nutri-GRADE

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