research paper modified food

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• Published: 13 January 2022

Evaluation of adverse effects/events of genetically modified food consumption: a systematic review of animal and human studies

• Chen Shen 1 ,
• Xiang-Chang Yin 2 ,
• Bo-Yang Jiao 3 ,
• Jing Li 4 ,
• Peng Jia 5 ,
• Xiao-Wen Zhang 1 ,
• Xue-Hao Cheng 6 ,
• Jian-Xin Ren 6 ,
• Hui-Di Lan 7 ,
• Wen-Bin Hou 1 ,
• Min Fang 1 ,
• Yu-Tong Fei 1 ,
• Nicola Robinson 1 , 8 &
• Jian-Ping Liu   ORCID: orcid.org/0000-0002-0320-061X 1 , 9  

Environmental Sciences Europe volume  34 , Article number:  8 ( 2022 ) Cite this article

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A systematic review of animal and human studies was conducted on genetically modified (GM) food consumption to assess its safety in terms of adverse effects/events to inform public concerns and future research.

Seven electronic databases were searched from January 1st 1983 till July 11th 2020 for in vivo, animal and human studies on the incidence of adverse effects/events of GM products consumption. Two authors independently identified eligible studies, assessed the study quality, and extracted data on the name of the periodical, author and affiliation, literature type, the theme of the study, publication year, funding, sample size, target population characteristics, type of the intervention/exposure, outcomes and outcome measures, and details of adverse effects/events. We used the Chi-square test to compare the adverse event reporting rates in articles funded by industry funding, government funding or unfunded articles.

One crossover trial in humans and 203 animal studies from 179 articles met the inclusion criteria. The study quality was all assessed as being unclear or having a high risk of bias. Minor illnesses were reported in the human trial. Among the 204 studies, 59.46% of adverse events (22 of 37) were serious adverse events from 16 animal studies (7.84%). No significant differences were found in the adverse event reporting rates either between industry and government funding ( χ 2  = 2.286, P  = 0.131), industry and non-industry funding ( χ 2  = 1.761, P  = 0.185) or funded and non-funded articles ( χ 2  = 0.491, P  = 0.483). We finally identified 21 GM food-related adverse events involving 7 GM events (NK603 × MON810 maize, GTS 40-3-2 soybean, NK603 maize, MON863 maize, MON810 maize, MON863 × MON810 × NK603 maize and GM Shanyou 63 rice), which had all been on regulatory approval in some countries/regions.

Serious adverse events of GM consumption include mortality, tumour or cancer, significant low fertility, decreased learning and reaction abilities, and some organ abnormalities. Further clinical trials and long-term cohort studies in human populations, especially on GM food-related adverse events and the corresponding GM events, are still warranted. It suggests the necessity of labelling GM food so that consumers can make their own choice.

Introduction

Genetic modification is defined as introducing transgene(s) with desired traits into the recipient organism’s genome by recombinant deoxyribonucleic acid (DNA) technology, and therefore it does not occur naturally [ 1 , 2 , 3 ]. Genetically modified (GM) crops are thought to address food security, sustainability and climate change solutions by improving crop yields, conserving biodiversity, providing a better environment in terms of the insect-resistant and herbicide-tolerant traits, reducing CO 2 emissions and helping alleviate poverty through uplifting the economic situation [ 4 ]. Insect-resistant and herbicide-tolerant traits were first introduced into four types of crop, canola, cotton, maize and soybeans, at the beginning of GM production [ 5 ]. At present, the mainstream characteristics of new crops still pursue higher-yielding, more nutritious, pest- and disease-resistant and climate-smart to meet future demand for a yield increase of major crops such as wheat, rice and corn, due to the growing population [ 6 ].

Since 1996, the first year of commercialization of GM crops, 70 countries had adopted GM crops until 2018, including 26 countries that cumulatively planted 2.5 billion hectares of GM crops and an additional 44 countries that imported GM crops. During the 27 years (1992 to 2018), 4349 approvals for 387 GM events from 27 GM crops were granted by 70 countries involving 2063 for food (when the direct consumers are mainly humans), 1461 for feed (the products only intended for animal consumption) use and 825 for environmental release or cultivation [ 4 , 7 ]. The major agricultural product exporting countries like the U.S.A., Brazil and Argentina show over 90% adoption of biotech crops [ 4 ]. For GM animal products, biotech salmon, considered to be the first genetically engineered animal for human consumption, was approved by the United States Department of Agriculture and Food & Drug Administration in 2015 [ 8 ]. In addition, it is illegal to grow major GM food crops in China while there are substantial investments in biotechnology research and GM maize, soybeans, and canola are allowed to import and eat [ 9 ].

Genetically modified food, however, is an example of the controversial relation between the inherent uncertainty of the scientific approach and the need of consumers to use products resulting from scientific developments thought to be safe [ 10 ]. Significant health risks have not been reported in peer-reviewed studies on GM food safety/security, which may cause some publication bias [ 11 ] but with a few exceptions, like the most famous “Monarch Butterfly controversy” [ 12 ], "Pusztai case" [ 13 ] and the "Séralini case" [ 14 ]. Unexpected effects of GM crops were reported in these studies, occupying an important place in the pages of scientific journals. Nevertheless, the above controversies severely impacted the public image, leading to full or partial bans in 38 countries including the European Union [ 15 ].

The complexity of risk evaluation is shown in these conflicting results, and concerns about the citizen-consumers have been raised against GM food [ 10 ]. Of most concern, aroused from the controversial events and some research results, is the potential of carcinogenesis, teratogenesis [ 16 ], lethal effects and adverse influences on fertility. GM agriculture is now widely discussed in both positive and negative frames and currently serves as a hotbed of debate in the public and policymakers. Although there are some reports and evidence from human and animal studies on the potential health effects of GM food/feed, the evidence is not conclusive and public concerns have not been resolved.

We aimed to conduct a systematic review of animal and human studies on GM food consumption to assess its safety in terms of adverse effects/events to inform public concerns and future research.

This study was a systematic review of previously published studies, conducted and reported in adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 17 ] guideline.

Search strategy

China National Knowledge Infrastructure (CNKI), Wanfang, VIP Database, Chinese Biomedical Database (SinoMed), PubMed, the Cochrane Library and Embase databases were searched from January, 1st, 1983 till July, 11th, 2020, using a predefined search strategy (Additional file 1 : Appendix S1). Reference lists of retrieved articles were also searched.

Eligibility criteria

Based on the evidence pyramid proposed by the Medical Center of State University of New York in 2001, we determined the type of research we included in the study. For a comprehensive evaluation of the literature, all in vivo animal studies and human studies (cross-sectional studies, case reports, case series, case–control studies, case–crossover studies, cohort studies, controlled clinical trials, including randomized trials, quasi-randomized trials and non-randomized trials) in multiple languages were included. Animal studies in all fields were included, that is, they could be clinical, agricultural and animal husbandry, veterinary medicine, life sciences, etc. Field studies were excluded.

The study population in animal studies was applied with inclusion criteria based on the categorization approach that highlights the actual use of them: laboratory animals and economical animals (livestock and aquatilia) were included, with no prespecified limitations on age, population, species/races, health status or others. Interventions/exposures of the genetically modified animal/plant/microorganism products included for animal/human ingestion referred to GM food, GM food ingredients and GM feed, regardless of their dosage or duration. The GM strain (line) and GM event were not limited. There was no restriction on whether controls were or were not included. The studies were excluded if they focused on the effects of GM food/feed on secondary or multilevel consumers in the food chain where GM food/feed was only consumed by primary consumers in the predator relationships. For instance, if non-GM fishes were fed with diet containing GM ingredients and then the fish was fed to the experimental cats, the study was excluded.

Outcomes focused on the incidence of adverse effects or adverse events in GM food/feed consumption, including primary outcomes on carcinogenesis, teratogenesis, lethal effect (all-cause mortality) and reproduction and secondary outcomes on other biomarkers were included. Toxicity studies of general toxicity studies (acute, sub-acute, sub-chronic, chronic and carcinogenicity toxicity studies) and specific toxicity studies (genotoxicity, reproductive and developmental toxicity, immunotoxicity and other toxicology studies) were included. Mortality in pups before weaning was considered as an outcome of reproductive toxicity but not as a lethal effect. Outcomes of adverse events in laboratory testing would not be included only when they could indicate tissue or organ toxicity. Outcomes of adverse events in breeding performance in animal husbandry studies, which focused on the economic benefits of the animal products, were included and these indicators were regarded as reproduction biomarkers in this research.

Outcomes of adverse events on growth performance, carcass traits, meat and fur production performance and meat quality for economic benefit evaluation of live stocks were excluded, of which the indicators included final body weight, weight gain, feed to gain ratio, half-eviscerated weight, eviscerated weight, percentage of eviscerated yield and muscle lean meat, sebum rate in some parts of the body, etc. Studies on the insecticidal effect of insect-resistant GM feed and outcomes of adverse events in gene fragments residual in the digestive tract were excluded. Besides, duplicate publications, studies with duplicate statistics, or references devoid of necessary information of participants, sample size, interventions/exposures or results were excluded.

Study selection and data extraction

Titles and abstracts of the retrieved articles were reviewed by 6 researchers in pair (C Shen, XC Yin, BY Jiao, J Peng, YZ Li, XH Cheng). 6 authors (C Shen, XC Yin, BY Jiao, JX Ren, J Li and XW Zhang) independently reviewed the full texts to identify the studies meeting eligibility criteria and then 8 researchers in pair (C Shen, XC Yin, BY Jiao, J Li, P Jia, XW Zhang, XH Cheng and JX Ren) independently extracted data from the included studies according to a predesignated extraction table. The discrepancies were resolved through consensus and if necessary, arbitrated by another author (JP Liu).

We extracted the name of the periodical, author and affiliation, literature type, the theme of the study, publication year, funding, sample size, target population characteristics, type of the intervention/exposure, outcomes and outcome measures. For those studies in which adverse effects/events occurred, details of interventions/exposures and control conditions (if any), dosage, duration, number of the generation, and the results were extracted.

Quality assessment

The methodological quality for animal studies was assessed, using criteria from the SYRCLE’s risk of bias tool for animal studies. The quality of animal studies was categorized into low risk of bias, unclear risk of bias, or high risk of bias according to the risk for each important outcome within included studies, including the adequacy of generation of the sequence generation, baseline characteristics, allocation concealment, random housing, blinding (performance bias), random outcome assessment, blinding (detection bias), incomplete outcome data, selective outcome reporting, or other sources of bias. The judgment of other risk of bias was based on whether there were contamination (pooling drugs), inappropriate influence of funders, unit of analysis errors, design-specific risks of bias or new animals added to the control and experimental groups to replace drop-outs from the original population.

Statistical synthesis and analyses

Statistical analyses were carried out using Microsoft Excel 2016 and SPSS 20.0. The findings were reported mainly in two parts, characteristics of the included studies and detailed information on the studies in which adverse effects/events occurred. Initially, descriptive statistics, frequencies, and percentages were calculated to summarize the data. Subsequently, studies that evaluated similar populations, interventions, controls (if any) and outcomes were pooled using a random-effects meta-analysis, and data from other studies were presented in tables and described in a narrative summary. The incidence of adverse events reported in articles funded by industry funding, government funding or unfunded articles were, respectively, counted and the Chi-square test was used for the comparisons.

Besides, we figured the incidence of serious adverse events (SAEs) by percentage. With reference to the Food and Drug Administration’s definition [ 18 ], our study defined SAEs as death, life-threatening, hospitalization (initial or prolonged), disability or permanent change, disruption, impairment or damage in a body function or structure (including cancer or tumour), in physical activities or quality of life, congenital anomaly or birth defect in the newborn child or pups, infertility or significant low in the number of deliveries or live birth rate than the non-GM commercial, conventional or blank controls, and an event resulting in intervention/treatment to prevent permanent impairment, damage or to prevent one of the other outcomes.

Meanwhile, the adverse events which cannot be ruled out that it has nothing to do with GM food (hereinafter abbreviated as GM food-related adverse events) were identified and the percentages under each outcome were calculated.

Description of studies

The flow diagram of the literature selection is shown in Fig.  1 . A total of 9668 records were identified, including 9584 from the initial search through seven databases and 84 from other sources. After removal of duplicates and exclusion of references by reading titles and abstracts, 455 full-text articles were screened and 276 references were excluded with reasons (seen in the flow chart). Finally, 204 studies from 179 articles [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 , 195 , 196 , 197 ] (153 journal articles, 22 dissertations, 3 conference proceedings and 1 unpublished report) were included in data synthesis, since there were more than one study conducted in each of the 2 included dissertations [ 107 , 127 ], 11 journal articles [ 19 , 33 , 35 , 63 , 67 , 88 , 102 , 118 , 132 , 172 , 184 ] and 1 unpublished report [ 32 ]. The included studies were of 203 in vivo animal studies and 1 crossover trial [ 97 ] in humans.

The flow of literature search and selection of studies on the safety of GM food

Study characteristics

Of the 179 included articles, 94 were in English [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 ], 83 were published in Chinese [ 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 , 195 ], and 2 in Japanese [ 196 , 197 ]. The earliest included reference dated back to 1998 [ 153 ] (shown in Fig.  2 ), after which the remaining articles were distributed from 2000 to 2020 (45 articles in the 2000s, while 131 in the 2010s and 2 in the 2020s). The year 2012 witnessed the largest volume of publication (n = 26 articles, 14.53%). For funding sources or sponsors (Additional file 1 : Appendix S2), in addition to 57 articles not mentioning the funding/sponsor (hereinafter as non-funded articles), there were 116 articles (64.8% of the 179 articles) supported by 56 kinds of government funding from 12 countries/government organizations and, still, 9 articles (5.03%) by 10 kinds of industry/institute funding sources/sponsors from 4 countries (America, Australia, French and German). Among them, 3 articles [ 29 , 62 , 74 ] claimed to have been funded or sponsored by both government and industry. China had undertaken the most government/school-level funding projects (39 of 56 projects, 69.64%).

The publications (number of articles) on the safety of GM food by year

The periodicals that have published more than 5 included articles were Food and Chemical Toxicology (published 25 included articles), EFSA Journal (13), Regulatory Toxicology and Pharmacology (9), Journal of Hygiene Research (9) and Chinese Journal of Food Hygiene (8). 11 of 13 authors, who have published ten or more included studies, were from European Food Safety Authority and published 12 included articles as co-authors. They were Christina Tlustos (published 12 included articles), Claudia Bolognesi (12), Konrad Grob (12), Vittorio Silano (12), Andre Penninks (11), Gilles Riviere (11), Holger Zorn (11), Karl-Heinz Engel (11), Yi Liu (11), Natalia Kovalkovicova (10), Sirpa Karenlampi (10). In addition to the above 12 articles, the top 3 of the 11 authors who published five or more included studies was Yang Xiao-Guang (from Chinese Center for Disease Control and Prevention, published 11 included articles), Wang Jing (from Tianjin Centre for Disease Control and Prevention, published 10 included articles) and Zhuo Qin (from Chinese Center for Disease Control and Prevention, published 7 included articles). The top 5 affiliations which published included articles were Chinese Center for Disease Control and Prevention (published 16 included articles), Tianjin Centre for Disease Control and Prevention (12), European Food Safety Authority (12), National Chung Hsing University (10), International Rice Research Institute (9).

Of the 204 included studies, one was a double-blind crossover trial ( n  = 36) in humans and the others were all animal studies. Individual sample sizes of the total 54,392 study population ranged from 4 (cats) [ 153 ] to 21,000 (Atlantic salmon) [ 23 ]. The studies involved 14 different kinds of animals (see Table 1 ). Apart from the most commonly used rats/mice (in 160 studies, 78.82%), pigs and chicks were two of the most extensively studied animals (in 23 studies, 11.33%). For themes of the 178 included animal studies, 158 were on clinical and 20 were on agricultural and animal husbandry. For the ones on clinical, 117 were on general toxicity (8 on acute, 6 sub-acute, 84 sub-chronic, 16 chronic toxicity, and still 3 on both acute, sub-acute and sub-chronic toxicity), 35 on specific toxicity (15 on reproductive and developmental toxicity, 16 on immunotoxicity, 3 on teratogenic effect and 1 on mutagenicity), 3 on allergenicity, 1 on learning and memory ability, 1 on athletic ability and 1 on both sub-chronic toxicity and allergenicity.

For interventions/exposures, 31 kinds of GM food were identified, including 18 kinds of GM plant food, 7 kinds of GM animal food and 6 kinds of GM microorganism food. Each included study covered one intervention/exposure, except for one study, Chen [ 29 ], that involved two kinds of GM products (sweet pepper and tomato) modified with the same gene (coat protein gene of cucumber mosaic virus), respectively, in two experimental groups. Maize, rice and soybean were the three most popular kinds of GM plant food (taken 79.38%) in research while milk/milk powder and animal-derived protein occupied the top two in GM animal food (56.25%). As for GM microorganism products, 5 kinds of food/feed enzyme derived from 5 different kinds of GM fungi or bacteria as well as 1 kind of microorganism-derived protein were among included studies.

Methodological quality of the animal studies

According to our predefined quality assessment criteria, all of the studies were identified as being unclear or having a high risk of bias (Fig.  3 ). None of the studies were reported to blind researchers from knowing which intervention each animal received. None of the studies reported prior sample-size calculation, 31 studies (15.27%) described wrong randomization procedures or did not mention the method of “randomization”, and 12 studies (5.91%) did not report adequate allocation concealment. 28 studies (13.79%) described that the groups were similar at baseline and 76 studies (37.44%) claimed that the housing conditions of animals from the various experimental groups were identical. 10 studies (4.93%) described randomly pick an animal during outcome assessment while 7 studies (3.45%) failed to select animals at random for outcome assessment. 88 studies (43.35%) completely used objective outcome indicators for outcome measurement. 185 studies (91.13%) reported consistent outcomes in the method and result sections while 5 studies did not, but none of the study protocols were available.

Risk of bias of the included animal studies

Incidence of adverse events/effects

No meta-analysis was conducted due to the significant heterogeneity of the primary studies. Among the 204 studies, a total of 29 studies (14.22%) from 23 articles reported 37 adverse events, involving 13 on mortality, 6 on reproductive toxicity, 3 on carcinogenesis and 15 on other biomarkers (including one human trial). It is worth noting that when, in one study, there were multiple aspects of adverse events on “other biomarkers”, we recorded it as 1 adverse event. Then, 22 serious adverse events (59.46% of adverse events) were identified in 16 studies (7.84% of the included studies and 55.17% of the studies reporting adverse events, marked in the tables with double asterisks). The SAEs mainly rested on mortality (13 studies), tumour or cancer (3), significant low in the number of pup deliveries (2), decreased learning and reaction abilities (1), severe stomach inflammation (1), intestinal adenoma lesions (1), and other pathology abnormalities (1) as hypertrophies and hyperplasia in mammary glands and pituitary, liver congestions and necrosis as well as severe chronic progressive nephropathies.

The incidence of adverse events reporting in government funding, industry funding and non-funded articles were 10.34% (12 of 116), 33.33% (3 of 9) and 15.79% (9 of 57), respectively. When comparing the adverse event reporting rates using the Chi-square test, we found that there were no significant differences either between industry funding and government funding ( χ 2  = 2.286, P  = 0.131), industry funding and non-industry funding ( χ 2  = 1.761, P  = 0.185) or funded and non-funded articles ( χ 2  = 0.491, P  = 0.483).

Incidence of adverse events/effects in human trial

As for the human trial [ 97 ], shown in Table 2 , a randomized double-blind crossover design was conducted for acute consumption of two single breakfasts, with a 14-day washout period, containing either seed oil generated from transgenic Camelina sativa plants or commercially blended fish oil. 36 healthy people were randomly allocated into two groups and venous blood samples were collected after the postprandial session, 8 h after each meal. No follow-up was reported. No major adverse symptoms or health effects were reported but some unrelated minor illnesses for the 72 postprandial sessions from 36 participants, such as minor upper respiratory tract infections (2.78%), minor nose bleed (1.39%), pyelonephritis (1.39%) and headaches (8.33%).

Incidence of adverse events/effects in animal studies

For the 203 animal studies, 28 studies (13.79%) from 22 articles reported 36 adverse events, including 13 on mortality (Table 3 , 36.11%), 6 on reproductive toxicity ( Table 4 , 16.67%), 3 on carcinogenesis (Table 5 , 8.33%) and 14 on other biomarkers (Additional file 1 : Appendix S3, 38.89%).

All causes of death were included in this analysis and 11 of the 13 studies claimed that the mortality was not significantly different between the groups or had nothing to do with GM food. One study (Ermakova [ 37 ]) reported higher pup mortality in the Roundup-Ready soya (40.3.2 line) group compared with the controls. In Séralini [ 74 ] , the general cause of death was large mammary tumours in females and other organ problems in males. Besides, rats in the Roundup-tolerant GM NK603 maize groups were 2–3 times more likely to die than controls, and more rapidly.

With respect to effects on reproduction, 5 animal feeding studies were reported to trigger reproductive toxicity but one study (Cisterna [ 31 ]) claimed to have no substantial impact on fertility. The reproductive toxicity manifested in the significant low in the number of deliveries, survival rate (from birth to weaning), litter weight, litter size and weight of some organs in the pups. For example, in Ermakova I 2005, the rats fed with Roundup-Ready soya had a 55.6% pup mortality rate during lactation periods compared to 9% in the control of traditional soya and 6.8% in the reference group. The pups kept dying during the lactation period while pups from the control group only died during the first week. Cyran N 2008 a and Cyran N 2008 c [ 32 ] were two rat feeding studies reported in one article, both given NK603 × MON810 maize. A multi-generation study was conducted as Cyran N 2008 a while Cyran N 2008 c did a continuous breeding study. Both of them indicated that fewer sum of pups was born and weaned in the GM groups. Pup losses, in Cyran N 2008 a, overall generations were about twice as many pups lost as compared to the control group (14.59% vs 7.4%) but was not significantly different and significantly lower litter weight was also reported in Cyran N 2008 c.

Three mouse/rat feeding studies reported triggering cancers/tumours when Tang [ 156 ] attributed the incidence of the tumour to the elder age of rats. Séralini 2014 (on Roundup-tolerant GM maize) found that females in the treatment groups almost always developed large mammary tumours more often than and controls. As for males, 4 times larger palpable tumours than controls were presented which emerged up to 600 days earlier. Cyran 2008 b [ 32 ] revealed a life term study where mice in the three groups were fed with transgenic maize NK603xMON810 (from 33.0% in the diet), control isoline diet and GM-free Austrian corn reference diet, respectively. The survival rate was not significantly different while cancer (leucosis) was the common cause of death.

GM food-related adverse events

Among the 37 adverse events reported, 16 of them claimed to have nothing to do with GM food, while the rest 21 (from 17 studies) did not, still leaving the question open. The GM food-related adverse events existed in mortality (2 studies), reproductive toxicity (5), carcinogenesis (2), and other biomarkers (12).

By gathering evidence, we identified 3 kinds of GM food associated with adverse events, GM soybean, GM maize as well as GM rice. For the 17 studies involved in the GM food-related adverse events, 4 studies were absent of information on the GM event of their test substance and the remainder concentrated on 7 GM events (3 studies on NK603 × MON810 maize, 2 on GTS 40-3-2 soybean, 2 on NK603 maize, 2 on MON863 maize, 2 on MON810 maize, 1 on maize mixed with MON863 × MON810 × NK603, NK603 × MON810 and NK603 and 1 on GM Shanyou 63 rice). When searching in the GM Approval Database on the ISAAA website, we found that all of the first 6 GM events listed, all developed by Monsanto Company, had been on regulatory approval for food, feed and cultivation in multiple countries/regions, including the European Union. GM -39 Shanyou 63 was developed in China and given approval for food, feed, and cultivation only by China in 2009.

Summary of findings

We included 203 in vivo animal studies and 1 human trial, and all of the studies were identified as being unclear or having a high risk of bias. Overall, we reported two main findings. First, we identified 37 adverse events for GM food consumption while 22 of them (59.46%) were serious adverse events extracted from 16 animal studies (7.84%). SAEs were mortality, tumour or cancer, significantly low in the number of pup deliveries, decreased learning and reaction abilities, severe stomach inflammation, intestinal adenoma lesions, and other pathological abnormalities in the mammary glands, pituitary, liver and kidney.

Second, there were 21 GM food-related adverse events indicating that GM food may have effects on increased mortality (2 studies), reproductive toxicity (5 studies), which referred to significantly low fertility in parental generation and low survival rate, litter weight, litter size and weight of some organs in the pups, carcinogenesis (2 studies) and other biomarkers (12 studies). The effect-related GM food included 7 GM events (NK603 × MON810 maize, GTS 40-3-2 soybean, NK603 maize, MON863 maize, MON810 maize, MON863 × MON810 × NK603 maize and GM Shanyou 63 rice), which had all been on regulatory approval for food, feed and cultivation in some countries/regions.

Agreements and disagreements with other reviews

To our knowledge, there have been 3 previous systematic reviews (SRs) [ 198 , 199 , 200 ] and 6 conventional reviews [ 16 , 201 , 202 , 203 , 204 , 205 ] addressing similar research questions on the unexpected effects of GM food consumption. Keshani et al. [ 198 ], searching in 4 English databases, included experimental studies on GM crops’ potential effects on sperm parameters. The study finally included 7 rat feeding studies, which were all identified in our study, and indicated no harm to GM plants consumers. Edge et al. [ 199 ] addressed 30 review questions for including human studies, published in recent 20 years (1994–2014), on health effects of genetically engineered (GE) food crops, but found no human study on 25 questions. The remaining 5 questions, related to allergenicity and nutrient adequacy, were answered based on 21 human studies. The human studies were all excluded in our research because of no direct ingestion of GE food in the allergenicity assessment studies or no targeted outcomes in the nutrient assessment trial. To illustrate, the above-mentioned nutrient assessment clinical trial evaluated the effect of carrots containing twofold higher calcium content on calcium absorption and we thought it was not on outcome related to adverse events/effects. The conclusion of the research also supported that there were no clear adverse health effects associated with the consumption of GE food. Moreover, Dunn et al. [ 200 ] included both human and animal studies for examining the allergenicity of GM organisms and finally found 34 human studies and 49 animal studies eligible. In addition to 32 human studies which involved human serum for IgE binding or inhibition studies and not direct consumption of GM product, the rest 2 [ 206 , 207 ]studies were on actual ingestion of a GM food. However, they were not included in our research because of not targeted study type and unrelated outcomes. The conclusion agreed with the first two SRs that GM foods did not appear to be more allergenic than their conventional counterparts.

As for conventional reviews, Domingo showed special attention to the safety of GM food and published four literature reviews in 2000 [ 203 ], 2007 [ 204 ], 2011 [ 205 ] and 2016 [ 16 ]. Domingo searched two databases, PubMed and Scopus, to assess adverse/toxic effects of GM plants. In the latest updated review, he addressed the conclusion that GM soybeans, rice, corn/maize and wheat would be as safe as the parental species of these plants. However, our results may not be consistent with Domingo’s conclusion: we focus on a summarization of adverse events for GM food consumption through a systematic search in 7 databases; we identified 37 adverse events, 22 serious adverse events and 21 GM food-related adverse events; GM maize, soybean and rice with some specific GM events were all related to GM food-related adverse events. In addition, Domingo found a notable advance of studies published in scientific journals by biotechnology companies. Coincidentally, we did a Chi-square test to compare the adverse event reporting rates and found no significant differences between industry funding, government funding and non-funded articles. Besides, our systematic review validated Domingo’s findings that some GM plants were studied scarcely in recent years including GM potatoes discussed in the controversy of Pusztai case.

Strengths and limitations

In this review, a systematic search of major databases was conducted to identify all available studies in all languages on the adverse effects/events of GM food consumption. To make the inclusion and data synthesis comprehensive, both in vivo human and animal studies in all fields were included, with no limitations on the type of participant, type of intervention/exposure or whether control was included. The terms used for searching, containing all kinds of names of GM food, were based on a basic search on the internet by the researchers and the list was perfected as much as possible. With respect to additional searching, we went through multifarious news which reported controversy of GM food and thus we identified several hot studies by following the clue. In order to trace the potential conflicts of interest, we performed a Chi-square test for comparing adverse events report rates in articles funded by industry funding, government funding or unfunded articles, but found no statistical significance. Nevertheless, it was hard to conduct a quantitative data synthesis for the effects of GM food consumption on the adverse events because of the significant heterogeneity of the primary studies.

There are several limitations in this review. The methodological quality of the included studies is generally poor, which indicates a high or unclear risk of bias resulting from insufficient reporting of methodological components in the studies. Methodological quality may not be fully reflected based solely on the reporting of the manuscript. There were unclear descriptions of randomization procedures and a lack of blinding in all of the studies, which may have created potential performance biases and detection biases, as researchers might have been aware of the effects of interventions. The ability to perform meta-analysis was limited because of the heterogeneity of the participants, interventions (GM food in various GM events), comparisons, feeding doses, administration time, other exposure factors, and the variance of composite outcome measures used in the 204 included studies. When we did the manual search, we found that related publications were retracted sometimes, under the name of inadequate experimental designs or statistical analysis. For example, Séralini 2012 was retracted by Food and Chemical Toxicology , but subsequently republished in another journal [ 14 , 74 ]. This indicates that it was hard for us to find the original full-text papers of the retracted publications and articles provided by databases still have some unavoidable publication bias. The retraction on controversial researches may also cause the controversy for the public to doubt the reality of the studies published and to concern the safety of GM food. In addition, the lack of human studies is another key limitation of this research. As for the searching strategy, we did not include publication types as newspaper articles and comments. This was thought to be a limitation of this research because these sources may give us clues of related researches and can help us to do a manual search comprehensively. It is also an implication for future systematic reviews.

Implications for research

Future research should be conducted in humans, especially observational cohort studies. High-quality animal studies according to the ARRIVE reporting standard focusing on reproductive toxicity and carcinogenesis are still needed. Trials or studies should be registered prospectively, and be accessible. Furthermore, to address public concerns, future studies should focus on SAEs and GM food-related adverse events reported in this research such as NK603 maize, MON863 maize and MON810 maize. Meanwhile, some implications of findings still could be explored such as how GM food affects people’s eating habits, labelling of GM food and public choice. Some of the included studies conducted an intergenerational or multigenerational evaluation of the safety of GM food, but only two studies (Cyran N 2008 a and Cyran N 2008 c) in one article reported adverse events related to fertility. The differences in the results may be due to different interventions/exposures (GM food in certain GM events), laboratory animals, intervention/exposure time, experiment environment, etc. Therefore, it is necessary for subsequent studies to start with intergenerational or multigenerational research to verify the safety of GM food in terms of study design.

Serious adverse events accounted for 59.46% of the total 37 identified adverse events of GM consumption, which include: mortality, tumour or cancer, significantly lower number of pup deliveries, decreased learning and reaction abilities, and organ abnormalities in the stomach, intestinal adenoma, mammary glands, pituitary, liver and kidney. The interventions/exposures in the adverse event related studies emphasized on GM soybean, maize and rice in specific GM events. Animal studies occupy the lowest hierarchy of evidence, and there are flaws in study design and is not convincing enough. The evidence on the effect of GM consumption on humans is still insufficient. Further clinical trials and long-term cohort studies in human populations, especially on GM food-related adverse events and the corresponding GM events, are still warranted. It is better to prove the safety before they are approved for food consumption and it also suggests the necessity of labelling on GM food so that consumers can make their own choice.

Availability of data and materials

All data generated or analysed during this study are included in this published article.

Abbreviations

Genetically modified

Deoxyribonucleic acid

China National Knowledge Infrastructure

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Serious adverse event

Camelina sativa Seed oil

Blended fish oil

Body weight

Systematic reviews

Genetically engineered

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Acknowledgements

We appreciate Yi-Zhen Li for participating in screening the titles and abstracts .

This work was supported by Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (ZYYCXTD-C-202006). Prof. Nicola Robinson (visiting professor of Beijing University of Chinese Medicine) was funded by the International development and capacity enhancement of evidence-based Chinese medicine Project, Ministry of Science and Technology of the People's Republic of China, G20200001187.

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Chen Shen, Xiao-Wen Zhang, Wen-Bin Hou, Min Fang, Xun Li, Yu-Tong Fei, Nicola Robinson & Jian-Ping Liu

Beijing Institute of Radiation Medicine, Beijing, China

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All work was done by the authors. JPL and YTF conceived the study and revised the manuscript. CS contributed to data searching, screening and extraction, analysis of the data, drafted and revised the paper and approved the final version to be submitted. XCY, BYJ, JP, XHC, JXR, JL, XWZ, HDL, WBH and MF participated in identifying or screening the titles, abstracts and full-text screening and data extraction. XL, NR and JPL advised on the analysis of the data and revised the manuscript. All authors read and approved the final manuscript.

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Additional file 1: appendix s1..

Search strategy applied in English language databases. Appendix S2. Funding sources or sponsors. Appendix S3. Adverse events/effects—other biomarkers.

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Shen, C., Yin, XC., Jiao, BY. et al. Evaluation of adverse effects/events of genetically modified food consumption: a systematic review of animal and human studies. Environ Sci Eur 34 , 8 (2022). https://doi.org/10.1186/s12302-021-00578-9

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Crop biotechnology and the future of food

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• Agriculture
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The global population continues to rise, as does the likelihood of reduced yields of major food crops due to the changing climate, thus making the development of genetically improved, stress-resilient crops a research priority. The convergence of low-cost genome sequencing with improved computational power and high-throughput molecular phenotyping technologies has accelerated the identification of genes underlying important agronomic traits relevant to food production and quality. Here, we discuss the evolution of plant improvement, and how researchers leverage genomic analyses and revolutionary new plant breeding technologies like site-directed nucleases to enhance food crop traits through agricultural biotechnology. Deployment of these products from the laboratory to the field remains hindered by biological and regulatory bottlenecks that require further development.

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Advancing crop genomics from lab to field

A CRISPR way for accelerating improvement of food crops

Genetic strategies for improving crop yields

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Acknowledgements

We apologize to those authors whose research could not be cited due to space limits. We thank H. Bartram for a careful reading of the manuscript. M.A.S. was supported by the Corteva Agriscience Open Innovation programme grant entitled “Gene Editing for Organic Agriculture.” P.C.R. was supported by grants from the US National Science Foundation (award no. 1237975), the Crary Social Ecology Fund, the Foundation for Food and Agricultural Research (award no. 534683) and the National Institutes of Health (GM122968).

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Steinwand, M.A., Ronald, P.C. Crop biotechnology and the future of food. Nat Food 1 , 273–283 (2020). https://doi.org/10.1038/s43016-020-0072-3

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Genetically Modified Food Research Paper

This sample genetics research paper on genetically modified food features: 4000 words (approx. 13 pages) and a bibliography with 14 sources. Browse other research paper examples for more inspiration. If you need a thorough research paper written according to all the academic standards, you can always turn to our experienced writers for help. This is how your paper can get an A! Feel free to contact our writing service for professional assistance. We offer high-quality assignments for reasonable rates.

The topic of genetic modification of food has raised various ethical concerns among the consumers, environmentalist, farmers, scientists, and common citizens. The camps for and against the use of the modern technology in our food productions tend to base their arguments either on strict deontological moral principles or on the utilitarian calculation of overall harms and benefits. In this research paper the different ethical viewpoints are introduced and their feasibility analyzed.

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This research paper discusses genetic modification of food. As the topic has raised many ethical concerns and points of view, it will examine different ethical issues as well as frameworks related to genetically modified organisms (GMOs) locally, regionally, and globally. The paper will introduce the methods of genetic modification and their history and current situation. Then it will discuss the various ethical approaches for and against genetic modification – including a discussion on known and potential benefits and harms of the genetic modification of organisms meant for human and animal consumption.

Conceptual Clarification

Genetic modification (GM) of food involves deliberate altering of the genetic material of plants and animals. It is an old agricultural practice carried on by farmers since early historical times. Recently, however, it has been improved by technology, i.e., genetic engineering and molecular biology. The term genetically modified foods (GMF) or genetically modified organisms is currently most commonly used to refer to crop plants created for human or animal consumption using these latest technologies.

Genetic modification in general describes the process by which scientists are able to pinpoint the individual gene which produces desired outcome, extract it, copy it, and insert it into another organism. Genetically engineered plants or animals are then generated by altering their genetic makeup. Usually genetically modified plants are tested in the laboratories for desired qualities. This testing is done by adding one or more genes to a plant’s genome using genetic engineering techniques (Freedman 2013; Fridovich-Kiehl and Diaz 2014).

Most direct genetic modification is done either by gene addition (cloning) or gene subtraction (genes are removed or inactivated). An example would be to isolate a gene responsible for drought tolerance and insert that gene into a different plant. Thus, the engineered organisms are sometimes also referred to as “transgenic organisms.”

History And Development

To some extent, humans have been involved in genetic modification for centuries. For example, larger cattle which produce more milk were bred to produce even larger offspring. Seeds from cereals and other crops that were more resilient and grew better were selected for planting the following year to produce better yields. This traditional process, however, has been slow and somewhat unreliable and inaccurate. The new technology that allows the scientists to take a gene from one living thing and put it directly into another plant or animal makes the desired changes more precise and happen in a much shorter time period. Currently the new technologies have created crops that are pest proof; disease, fungal, viral, and herbicide resistant; and weather (drought, cold, or hot) tolerant. It is also used to improve the nutritional content of crops and expand their storage. Also genetic modification has been used to improve taste, size, and color of food products. For example, so-called Golden Rice has been modified so that it gets an extra boost of vitamin A from a daffodil gene so that it produces almost 20 times the beta-carotene of previous varieties. This rice was intended for Asia, and the justification for this modification is that in this way, people who might have poor or restricted diet and cannot get enough vitamin A otherwise could get it directly from rice (FDA 2014, Fridovich-Kiel and Diaz 2014).

The discovery in 1946 that DNA can be transferred between organisms brought new elements to food production. The first genetically modified plant was produced in 1983 by using an antibiotic resistant tobacco plant. In 1994 the transgenic Flavr Savr tomato was approved by the US Food and Drug Administration (FDA) for marketing and commercial use in the USA. This genetic modification allowed the tomato to delay ripening after picking. Commercial sale of genetically modified crops began when Calgene first marketed its Flavr Savr tomato in 1996 (Fridovich-Kieh and Diaz 2014).

To date, most genetic modifications of foods have primarily focused on cash crops in high demand by farmers – such as soybean, corn, canola, and cottonseed oil. These have been engineered for resistance pathogens and herbicides as well as better nutrient profiles, as noted above. The most genetically modified food organisms are currently corn and soya. Corn that is used for food has been genetically modified to be resistant to various herbicides and to express a protein from Bacillus thuringiensis that kills certain insects. Nevertheless, it should be noted that since corn is used in various ways and processed into grits, meal and flour which for their part can be used in breakfast cereals, snack foods, baking mixes, etc.; genetic modification can be found in many different food products. Similarly soybeans are processed to different products that are used in a variety of foods, such as salad dressings soups, meat analogues, cheeses, nondairy creamer, desserts, infant formulas, breads, pasta, pet foods, etc.

According to various statistics, up to 90 % of the corn and soya beans grown in the USA have been genetically modified, and up to 60 % of all products on supermarket shelves could contain at least some GM soya (Freedman 2013; FridovichKieh and Diaz 2014). The percentage is lower in Europe, in Asia, and in Africa, but in reality it is very difficult to know exactly how far the genetic modification has spread across the globe.

GM livestock have also been experimentally developed. However, as of September 2014, there were no genetically modified animals approved for use as food, though GM salmon was still awaiting regulatory approval. In general according to FDA in the USA, many kinds of GE animals are currently in development. The largest class of GE animals is being developed for biopharm purposes – that is, they are intended to produce substances (e.g., in their milk or blood) that can be used as human or animal pharmaceuticals. Another group of GE animals are under development for use as sources of scarce cells, tissues, or organs for transplantation into humans (xenotransplant sources). Yet, others are intended for use as food and may be disease resistant or have improved nutritional or growth characteristics. Other developments include animals that produce high-value industrial or consumer products, such as highly specific antimicrobials against human and animal pathogens (e.g., E. coli 0157 or Salmonella). In general animals (e.g., goat) that are usually used for food production (e.g., milk) have already been genetically modified and approved by the FDA to produce nonfood products. (For details see FDA 2014; FridovichKiehl and Diaz 2014).

Currently, about only a tenth of world’s cropland includes GM plants. Four countries the USA, Canada, Brazil, and Argentina grow approximately 90% of the planet’s GM crops. Other Latin American countries are pushing away from the plants. In Africa there are test farms in some countries but not wide production. For example, Mauritius, South Africa, and Egypt are developing virus and pest-resistant transgenic sugarcane technologies. Other crops are tested also elsewhere in Africa (Freedman 2013).

Ethical Dimensions

From the point of view of global bioethics, genetic modification of food is an issue of central interest. After all, GM food has various transnational worldwide ethical dimensions. Firstly, GM has a global context, and many debates on its benefits and risks, whether health or environment related or economic, reach beyond national borders. Secondly, the responses to the use of genetic engineering in food production reach beyond borders as the movements for or against the GMF are not only national but also regional and international. Thirdly, many regulations that are set to control and test GMOs need to be based on international agreements.

Philosophical Ethics

In the philosophical ethics, the arguments for and against GM food vary often depending on the theoretical ethical starting point. Some deontological arguments may see the act of genetic modification to be wrong per se. This view is usually based on ideological or religious commitments. Genetic engineering may be seen, for example, as unnatural and, thus, immoral. In religious deontology, it could be seen as a human attempt to take the place of God – and thus, work against God’s will. These positions could be easily defeated by counter argumentation that points out that has God created human beings and gave them the ability to find scientific ways to improve and change nature. Consequently, the development of genetic engineering is in tandem with the God-given mandate to humankind to have dominion over other lesser creatures. Indeed, without fundamental theological assumptions, there do not seem to be strong categorical arguments against genetic modification. This is partly because genetic engineering has existed in one way or another for centuries if not thousands of years, for instance, the biblical account of Jacob “creating” cattle of rings raked, speckled, and spotted fleeces (Genesis 30:27:42).

On the other hand, reasoning along the lines of utilitarian ethics yields quite opposite conclusions on the rightness or wrongness of the overall consequences of genetic modification. Depending on whose utility we focus on and whether we calculate economic aspects, risks, or benefits and based on what information, we may get very different views on the moral desirability of GMF. Thus, while risks and benefits are at the core of the GMO debates, utilitarianism cannot currently provide very solid ethical argumentation either for or against genetic engineering – especially before all risks and benefits could be scientifically more accurately proven. Finally the tradition of Aristotelian virtue ethics may again see that human beings are changing the intrinsic telos of living organisms in a manner that prevents these organisms from flourishing naturally. Lastly, virtue ethics may also be interpreted to promote human beings realizing their full rational potential as inventors of these new technologies that merely enhance evolutionary tendencies of the nature (On philosophical ethical theories see for example Singer 1993).

Actual And Potential Harms And Benefits

As noted above, traditional moral theories do not necessarily provide a particularly solid or feasible framework for ethical argumentation for or against genetic modification of food. Thus, it is productive also to consider the actual benefits and risks that concern people in relation to the GMF.

The promoters of genetic modification of food appeal to the advantages that are achieved: better taste, larger sizes, better nutritional value, as well as economic benefits when the crops become resistant to pests, weeds, extreme weather conditions, etc. The overall benefit is mentioned to be the improved food production that would help to feed the poor across the world by providing more resistant crops with better nutritional values in places where the traditional farming techniques have not produced the needed results (WHO 2014).

Despite these benefits, there is still much opposition toward GMF. Politicians, administrators, “traditional” farmers, environmental movements, and just ordinary concerned consumers have raised several issues of concern. These vary from general concerns on environmental pollution, unintentional gene transfer to wild plants, possible creation of new viruses and toxins, etc. Below these risks are listed in more detail.

Firstly, there is a fear that genetic modification can lead to a loss of biodiversity if genetically modified organisms could have the potential to do unexpected harm to other plants and animals. The concern is that plants with new genes imported to them will accidentally crossbreed with wild plants and create harmful and unnatural effects in nontarget organisms (e.g., pesticideresistant super weeds or kill insects which are not pest but have a useful role in protecting plants). At worst, this could even lead to certain animal and wild plant species effectively being rendered extinct. This is not a fully unfounded concern as some laboratory tests have shown that pollen from GM maize in the USA damaged the caterpillars of the monarch butterfly. The studies on this case, however, are still highly controversial (see for details Winston 2002; Pewtrust 2003).

Secondly, where test crops have been planted in a country, there can be a definite danger of cross contamination with wild or non-GM plant strains. Many people are afraid that genetically modified foods may end up harming not only individual human beings but the environment at large. Even with very strict controls in place, it is impossible to prevent pollen from traveling on the wind from GM crops to other possible organic version of the same crop being grown nearby. Pollen could also be carried by insects. This could mean that in the end, all our food crops could contain a proportion of genetically modified elements. As consumers we would then lose our rights to choose GM food or not as it would be impossible to tell whether our food has been genetically modified at one stage or the other.

Thirdly, while the countries that are most affected by harsh weather conditions, arid lands, and famine could potentially be the greatest beneficiaries of GM foods, many regions with poverty and famine have not shown great enthusiasm for the newly developed crops.

In Africa there has been continuing resistance against adopting genetic modification in farming as many African governments warn that gene technologies will not help the local farmers. Instead they may destroy the diversity, the local knowledge, and the traditionally more sustainable agricultural systems. If these countries become dependent on the multinational companies who provide the seeds and related fertilizers and pesticides, the capacity to feed people in developing countries will diminish rather than increase. This feat may not be unfounded as multinational companies are there to make profits rather than feed the world and, thus, tend to have conditions for the commercial use of their seeds and crops. Multinational Monsanto that produces genetically modified crops, for example, is said to have had a terminator gene build in to them to prevent farmers from keeping seeds produced by their crops for the following year. Only recently this company was pressured to agree not to use this terminator technology in its crops (see, for example, Winston 2002).

Fourth, some of the specific fears expressed by opponents of GM technology include physical health risks such as alteration of nutritional quality of foods, potential toxicity and poisoning, possible antibiotics resistance, allergic reactions, etc. (Helferich and Winter 2010; Pusztai et al. 2003). The results on the actual and potential harms and benefit seem to be sometimes very contradictory, and it is difficult to know what we really should believe in.

Local, Regional, And Global Attitudes Toward GMF

In general, there appears to be a broad scientific consensus that food on the market derived from GM crops poses no greater risk to human health than conventional food. However, it is also fair to note that it might be too early to know for certain whether or not GM foods are harmful to human health or to the environment in the long run. This technology has been in use for too short a time to be able to assess and predict all possible unwanted side effects. What makes an accurate assessment even more difficult is the fact that the research reports on the safety of genetic modification produce contradictory results. It appears that their results depend on who is sponsoring the research and where the information comes from. While most available studies claim that GM foods have not harmed anyone directly, there are also reports that reveal harmful effects that have occurred.

Another ethical dimension of the research and studies on GMF is that the results may sometimes depend on the background politics and interests of certain involved parties. Thus, fully impartial information is still hard to get as the companies involved in genetic modification or distribution of genetically modified foods produce their own research and studies that focus on the benefits of GM technology and may undermine the risks. On the other hand, the opponents to the use of these technologies emphasize the risks and may exaggerate the potential harms.

Also, different countries and different regions across the world tend to have divided views on the GMF. They also focus on different ethical, political, and economic concerns. Governments in different countries have taken diverse approaches to assess and manage the risks associated with the use of genetic engineering technology in relation to genetically modified organisms. There are different regulations between countries and again particularly big difference between the USA and Europe. The European Commission has funded high number of research projects on the safety of GM crops. And while these studies have not found any high risk from GM group, the EU ministers are very cautious of letting new GM products in commercial markets and general consumption. The opinion, however, are split also within the EU. Particularly Germany, France, and Hungary have led the opposition, while other countries have been more favorable toward GMF. Traditionally Europe has been more conservative and has stronger opposition to the use of GMF than the USA. In the USA the big multinational companies located there, such as Monsanto, have produced genetically modified organisms and GM food for a long time for wide markets, and the consumers for the most part have welcomed the used technology and are willing to buy products with enhanced qualities. In Europe the markets are more reluctant to accept GMOs, and there are strict regulations to clearly label products “contaminated” with genetic modifications. Some critics say that many of the objections to GM food stem from politics rather than science, and they are motivated by an objection to large multinational corporations having enormous influence over the food production and distorting the agricultural markets and creating dependencies (see, e.g., Noussain et al. 2004, pp. 102–120; Pollack 2009, and also Monsanto 2014). From the point of view of global bioethics, many of these differences in views are related to the wider questions of (global and local) distributive justice. For example, African states and developing countries in general are particularly concerned about the economic dependency on multinational corporations. They also do not want to be used as testing grounds as they worry about the unknown health and environmental effects (Qaim 2009, pp. 667–669). However, institutionally they have not been able to follow up the implementation of regulations to control-related issues. Thus, while there is political resistance against the GMF, in many African and Asian countries, the general policy is not fully clear and GM products are not yet well regulated.

Country-specific regulations also often depend on the intended use of the products of the genetic engineering process. Countries which have legislation in place focus primarily on assessment of risks for consumer health and consumer rights. However, a crop not intended for food use is generally not reviewed by authorities responsible for food safety, and its use is followed as carefully as for food crops.

Legislation, Testing, And Labeling

In order to avoid any harmful effects of genetic modification of food, the safety assessment of GM foods usually investigates the following (1) direct health effect (toxicity), (2) tendencies to provoke allergic reaction (allergen city), (3) specific components thought to have nutritional or toxic properties, (4) the stability of the inserted gene, (5) nutritional effects associated with genetic modifications, and (6) any unintended effects which could result from the gene insertions.

One way to give the consumer at least a choice is the power to choose whether or not to buy GM products. Indeed the argument over the development, marketing, and selling GM foods has become a fierce political debate in recent years. Currently labeling can be mandatory up to a threshold GM content level (which varies between countries) or voluntary. In Canada and the USA, labeling GM food is voluntary, while in Europe all food including processed food or fee which contains greater than 0.9 % of GM contents is required to be labelled. Big companies that promote GM of foods such as Monsanto, General Mills, Pepsico, DuPont, Hershey, Cargill, Kellogg, Hormel, Kraft, Mars, Goya, Ocean Spray, and Nestle, as well as industrial food marketers, spend million on advertising to convince people to vote against labeling, while in many countries the consumer and environmental movements have pressured the government to make sure the GM products are clearly labeled (WHO 2014). Other ethical dilemmas may arise: [If the safety of GMFs is not a clear-cut issue, what are the ethical concerns associated with the power of choice? For instance, is it ethical for a government to allow its citizens to choose to buy products of uncertain risks and benefits? The non-labeling movement of GMFs tends to raise the question of trust.

In relation to international trade, according to WHO no specific international regulatory systems are currently in place. Several international organizations, however, are involved in developing protocols for GMOs. The Codex Alimentarius Commission (Codex) is the joint FAO/WHO body responsible for compiling the standards, codes of practice, guidelines, and recommendations. Codex is developing principles for the human health risk analysis of GM foods. The premise of these principles dictates a premarket assessment, performed on a case-by-case basis and including an evaluation of both direct effects (from the inserted gene) and unintended effects (that may arise as a consequence of inserting of the new gene). Codex principles do not have a binding effect on national legislation but are referred to specifically in the Sanitary and Phytosanitary Agreement of the World Trade Organization (SPS agreement) and can be used as a reference in case of trade disputes. The Cartagena Protocol on Biosafety (CPB), an environmental treaty legally binding for its parties, regulates trans-boundary movements of living modified organisms (MLOs). The cornerstone of the CPB is a requirement that exporters seek consent from importers before the first shipment of LMOs intended for release into the environments (WHO 2014).

From the point of view of global bioethics, many different ethical questions can be found in the debate for and against GMF: individual rights and health, environmental ethical issues, questions of distributive justice, issues of different worldviews and belief systems, etc. As GMF is a very complex issue and relatively little is known of its long-term consequences, it is important that we indeed learn more about the risks and benefits of the new technologies and their application. More studies needs to be carried out and preferably by independent research bodies rather than biotech companies or movement that are in principle against the GM technology. This is important in order to learn through impartial research about both short and long-term effects.

It is unlikely that GM products will be taken off the shelves or that the development of new GM organism would be stopped. Neither will the planting of crops cease. Thus, it is essential to continue testing the safety on new GM crops and follow any side effects of the current ones. The debate on GMF will likely continue, shaped by different views presented by governments, companies, and consumers. In this debate, clarity is often hindered when arguments are based on partial scientific evidence, on partial interests, on moral values, on politics, or on mere rhetoric.

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• Fridovich-Keil, J. L, & Diaz, J. M. (2014). Genetically modified organism. Encyclopaedia Britannica. https://www.britannica.com/science/genetically-modified-organism .
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CDER Emerging Drug Safety Technology Program (EDSTP)

Introducing the emerging drug safety technology program (edstp).

The EDSTP is specifically focused on the use of artificial intelligence (AI) and other emerging technologies in pharmacovigilance (PV) and is part of the Center for Drug Evaluation and Research’s (CDER) multifaceted approach to enhance mutual learning of where and how specific innovations, such as AI, can best be used across the drug product lifecycle.  

Emerging Technology's Potential in PV and Safety Surveillance

FDA has a longstanding commitment to ensure medicines marketed in the United States are safe through continued surveillance and research following approval. In the postmarket setting, regulated industry (per 21 CFR 314.80, 314.98, and 600.80) is obligated to review all adverse drug experience information received or otherwise obtained and submit reports to FDA. Both industry and regulatory authorities face challenges with timely and efficient collection, processing, and evaluation of single and aggregate patient safety data compounded by ever-increasing case volumes. Advances in emerging technology have the potential to address some of these challenges by creating more efficiencies within a PV system. For example, early adopters of AI are leveraging these emerging technologies to automate fundamental tasks (e.g., adverse event intake, data entry, and processing) with the intention to drive down associated administrative burden and costs. These technologies can also make safety surveillance more efficient and effective by capturing, aggregating, and analyzing larger and more diverse data sets. 

Goals of the EDSTP

CDER recognizes industry’s interest in dialogue around AI capabilities that advance PV. Industry may have concerns that using such technologies could create uncertainties regarding satisfying regulatory obligations for PV. This is especially true while CDER familiarizes itself with new technologies (e.g., assessing their performance characteristics and efforts to validate and verify models) to determine how they may be evaluated within our regulatory framework. 

In this context, CDER established the EDSTP with three goals: 

• Serve as the central point of contact for discussion between industry and CDER on the use of AI and other emerging technologies in PV 
• Enable knowledge management and knowledge transfer within FDA specific to the context of AI or other emerging technologies used in PV
• Understand the context of use of AI and other emerging technologies in PV to inform potential regulatory and policy approaches within PV

To help further these goals, CDER created the Emerging Drug Safety Technology Meeting (EDSTM) program , which will be administered by the EDSTP. FDA expects that increased communication with the broader pharmaceutical industry during EDSTMs will accelerate FDA’s understanding of how AI enabled tools and other emerging technologies are being used for PV, their performance characteristics, their associated risks and benefits, efforts to validate and verify relevant models, and barriers to implementation. 

Questions and Answers

What is the purpose of the emerging drug safety technology meeting (edstm).

The EDSTM is a means by which eligible participants (see Eligibility Criteria ) can meet with CDER to share information about their use of AI and other emerging technologies and its potential application in PV. The goal of the meeting is to facilitate mutual learning and discussion on the opportunities and challenges with using such technologies in PV. Those selected for a meeting will meet with CDER to discuss their research, development, and/or use of AI and other emerging technologies in PV.

Which FDA representatives will be involved in the EDSTMs?

EDSTMs will be attended by members of CDER’s Emerging Drug Safety Technology Program, which includes representatives from CDER staff with experience in emerging drug safety technologies, pharmacovigilance activities, policy, and relevant inspection programs (e.g., Postmarketing Adverse Drug Experience (PADE) Compliance Program). The relevant interdisciplinary experts attending an EDSTM will depend on the nature of the topic proposed by the meeting requester. Additional experts from other centers or offices may participate as resources and time permit.

What topics are of interest to CDER for EDSTMs?

CDER is interested in a deeper understanding of AI and other emerging technologies that industry is exploring or has applied to PV activities. CDER is also interested in additional safety-related use cases involving emerging technology in PV, including but not limited to, signal detection and evaluation. The FDA AI/ML for Drug Development Discussion Paper references common uses of AI in PV, particularly for postmarket safety surveillance such as for the processing, evaluation, and submission of individual case safety reports (ICSRs) (see pages 8 – 9).

When exploring use cases of AI and other emerging technologies in PV with industry in EDSTMs, CDER is also interested in understanding how industry establishes the credibility and trustworthiness of AI models, including the following areas of consideration:

• Human-led governance, accountability, transparency, and explainability
• Data quality, reliability, representativeness, and bias mitigation
• Model development, performance, monitoring, and validation.

These areas of consideration are noted in the AI/ML for Drug Development Discussion Paper (see pages 17 – 23).

When is CDER accepting requests for EDSTMs? When are the submission deadlines?

CDER is now accepting requests for EDSTMs. Refer to the Submission Timeline and Process for quarterly submission deadlines. Requests will be reviewed on a quarterly basis for a total of up to nine participants in a 12-month period for the initial phase of the EDSTM.

For more information regarding CDER’s Emerging Drug Safety Technology Program (EDSTP), email [email protected] and include the subject line “EDSTP – General Inquiry”

In this Section

Emerging Drug Safety Technology Meeting (EDSTM) Program

Related information, focus area: artificial intelligence.

FDA aims to improve its understanding of AI’s potential and limitations. Learn more.

Artificial Intelligence and Machine Learning (AI/ML) for Drug Development

FDA recognizes the increased use of AI/ML throughout the drug development life cycle. Learn more.

Artificial Intelligence and Medical Products

Learn more about how the FDA is shaping the future of health care through the responsible and innovative integration of AI.

FDA Discussion Papers on AI/ML in Drug Development and Manufacturing

FDA recognizes the potential for AI/ML to enhance drug development in many ways. Learn more.

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Ultra-Processed Foods and Health Outcomes: A Narrative Review

Leonie elizabeth.

1 School of Exercise and Nutrition Science, Deakin University, Geelong 3217, Australia; ua.ude.nikaed@ebazilel (L.E.); [email protected] (P.M.); [email protected] (P.B.)

Priscila Machado

2 Institute for Physical Activity and Nutrition, Deakin University, Geelong 3217, Australia

Marit Zinöcker

3 Department of Nutrition, Bjørknes University College, 0456 Oslo, Norway; [email protected]

Phillip Baker

Mark lawrence, associated data.

The nutrition literature and authoritative reports increasingly recognise the concept of ultra-processed foods (UPF), as a descriptor of unhealthy diets. UPFs are now prevalent in diets worldwide. This review aims to identify and appraise the studies on healthy participants that investigated associations between levels of UPF consumption and health outcomes. This involved a systematic search for extant literature; integration and interpretation of findings from diverse study types, populations, health outcomes and dietary assessments; and quality appraisal. Of 43 studies reviewed, 37 found dietary UPF exposure associated with at least one adverse health outcome. Among adults, these included overweight, obesity and cardio-metabolic risks; cancer, type-2 diabetes and cardiovascular diseases; irritable bowel syndrome, depression and frailty conditions; and all-cause mortality. Among children and adolescents, these included cardio-metabolic risks and asthma. No study reported an association between UPF and beneficial health outcomes. Most findings were derived from observational studies and evidence of plausible biological mechanisms to increase confidence in the veracity of these observed associations is steadily evolving. There is now a considerable body of evidence supporting the use of UPFs as a scientific concept to assess the ‘healthiness’ of foods within the context of dietary patterns and to help inform the development of dietary guidelines and nutrition policy actions.

1. Introduction

The concept of ultra-processed food (UPF) as a descriptor of unhealthy foods within dietary patterns is increasingly recognised in the nutrition literature [ 1 , 2 , 3 , 4 , 5 ] and authoritative reports [ 6 , 7 ]. Understanding of the contribution of UPFs to dietary quality and as a risk factor for diet-related diseases, disorders and conditions is rapidly emerging [ 8 ]. Yet, limited consideration has been given to UPF in strategies aiming to improve population health [ 9 ]. A crucial missing step in closing that gap is a review of the evidence base of the associations between UPF consumption and adverse health outcomes.

Dietary risk factors are leading contributors to the global burden of disease (GBD), responsible for an estimated 11 million deaths from non-communicable diseases (NCDs) (22% of all adult deaths) and 15% of disability life years (DALYs) lost in 2017 [ 10 ]. Leading contributors to diet-related deaths are cardiovascular disease (CVD), cancer and type 2 diabetes [ 10 ]. Contributors to DALYs from non-fatal chronic conditions include asthma, musculoskeletal conditions and mental health disorders [ 11 ].

Implicated dietary risk factors include certain nutrients, foods and dietary pattern exposures. Nutrient exposures include high amounts of sodium [ 10 , 12 ], saturated fat, trans-fat and added sugar [ 12 ]. Food exposures include low amounts of whole grains, fruit, vegetables, nuts and seeds [ 10 ] and fish [ 10 , 12 ], and high amounts of red meat, processed meat, potato chips and sugar-sweetened beverages (SSB) [ 12 , 13 ]. Dietary patterns include low scores on the Healthy Eating Index or Alternative Healthy Eating Index [ 14 ], or Mediterranean Dietary Pattern [ 15 ]; low adherence to the Dietary Approaches to Stop Hypertension diet [ 16 ]; or a high score on the Western dietary pattern [ 17 , 18 , 19 , 20 ].

In a novel approach to food categorization, NOVA (a name not an acronym) classifies foods and beverages ‘according to the extent and purpose of industrial processing’ [ 21 , 22 ], an aspect generally overlooked by public health nutrition science, policy and guidance. In 2009, a Brazilian research group, following studies on national trends over 25 years on household food acquisition and health implications [ 23 , 24 ], concluded diets containing high proportions of UPFs are intrinsically nutritionally unbalanced, harmful to health, or both [ 9 ]. This led to the development of the NOVA food classification system [ 25 ], which has since evolved [ 21 , 22 , 26 , 27 , 28 , 29 , 30 ].

The NOVA classification assigns foods to one of four groups, based on ‘the extent and purpose of industrial processing’ [ 21 ]: (1) ‘unprocessed or minimally processed foods’ (MPF), comprising edible parts of plants, animals or fungi without any processes applied to them or natural foods altered by minimal processing designed to preserve natural foods to make them suitable for storage, or to make them safe, edible or more palatable (e.g., fresh fruit, vegetables, grains, legumes, meat, milk); (2) processed culinary ingredients (PCI), which are substances extracted from group 1 (e.g., fats, oils, sugars and starches) or from nature (e.g., salt) used to cook and season MPF, not intended for consumption on their own; (3) processed foods (PF), where industrial products are made by adding PCI to MPF (e.g., canned vegetables in brine, fruit in syrup, cheese); and (4) UPFs, which are defined as ‘formulations of ingredients, mostly of exclusive industrial use, that result from a series of industrial processes (hence “ultra-processed”), many requiring sophisticated equipment and technology’ (e.g., sweet and savoury snacks, reconstituted meats, pizza dishes and confectionery, among others) [ 21 ]. Ingredients characteristic of UPFs include food substances of no or rare culinary use, including sugar, protein and oil derivatives (e.g., high-fructose corn syrup, maltodextrin, protein isolates, hydrogenated oil) and cosmetic additives (e.g., colours, flavours, flavour enhancers, emulsifiers, thickeners, and artificial sweeteners) designed to make the final product more palatable [ 21 ].

Since NOVA was established, nutrition researchers worldwide have increasingly implicated UPFs with poor dietary quality, and with adverse metabolic and health outcomes across a range of populations and country contexts [ 7 ]. Furthermore, UPFs have become dominant components in diets of populations worldwide [ 31 ], contributing up to more than 50% of energy intake in high-income countries [ 32 , 33 ], and up to 30% in middle-income countries [ 34 , 35 ], with consumption volumes rapidly increasing [ 36 , 37 , 38 ]. Because middle-income countries are home to the vast bulk of the world’s population, understanding the implications of rising UPF consumption for global human health is of utmost importance.

Several reviews have reported on UPFs and health outcomes [ 2 , 3 , 4 , 5 , 7 , 39 ]. However, despite the large and rapidly growing body of evidence linking UPFs with adverse health outcomes, the number of reviews and summarizing reports to date have been scarce, possibly delaying the inclusion of the ‘extent and purpose of industrial processing’ [ 21 ] as an independent factor for assessing the health potential of diets. As most dietary advice relies on systematic reviews and meta-analyses when reviewing evidence, a comprehensive review could be helpful in strengthening the evidence base and moving this field forward. To our knowledge, no review to date has employed a systematic search to identify all studies, without the restriction of health outcomes or study design.

The aim of this narrative review was to systematically identify and appraise the findings of studies on healthy participants (adults, adolescents and children) that have investigated associations between levels of UPF consumption and health outcomes.

2. Materials and Methods

A systematic search and narrative review method were adopted [ 40 , 41 ], involving four main steps: first, a systematic search process and application of inclusion and exclusion criteria; second, data extraction and synthesis of results; third, an analysis of key findings by narrative review; fourth, a quality appraisal procedure that included all studies. The method allowed a thorough search for extant literature, integration and interpretation of findings from diverse study types, populations, health outcomes, measurements and dietary assessments as well as quality appraisal. Checklists were used to ensure thoroughness of relevant components of the narrative review and systematic methods [ 42 , 43 , 44 ].

2.1. Search Process

The study utilised a systematic search process to ensure relevant studies were retrieved. Searches were performed in July 2019 using four databases—Medline, CINAHL, Global Health and Embase—and searching string variations of the following keywords: (ultra-process* or ultra process* or ultraprocess*) or (NOVA and “food classification”). Google Scholar citation searches and manual searches of reference lists were also conducted to identify relevant studies. A further EBSCO-host combined search was undertaken to identify any literature reviews and meta-analyses potentially missed by the initial searches. Additional searches of the electronic databases were performed in February 2020 and of Medline on 21 May 2020, to identify studies published in the interim. Records were downloaded to EndNote X8.2, and duplicates removed. Titles were first screened by title and abstract, then by full text against the inclusion and exclusion criteria given in Table 1 . Eligible articles were studies evaluating exposure (defined as ‘levels of consumption’) to ‘ultra-processed foods’ (defined as group 4 of the NOVA food classification system [ 21 ], described in Supplementary Material Table S1 ) and a ‘health outcome’ (defined as any disease, disorder or condition specified in the International Classification of Diseases, 11th Revision [ 45 ]). In this review, ‘food’ includes foods and beverages; ‘consumption’ includes national or household food availability and individual food intake. From a total of 851 papers, there were 263 identified studies on UPF and 43 for final inclusion in our review. Figure 1 presents a flow diagram adapted from PRISMA [ 43 , 44 ] of the search process.

Flow Diagram of Database Search and Article Eligibility (modified from PRISMA flow diagram [ 43 , 44 ]).

Inclusion and exclusion criteria used for screening studies.

2.2. Data Extraction, Synthesis, Analysis and Quality Appraisal

Data were extracted on study details (author, publication date, study type, country and period of study) population (subjects, sample size), UPF exposure (food data extraction level, collection method, relative exposure assessment, NOVA reference), health outcomes (definition, data collection) and key findings. Studies were organised and tabulated into three classifications by specified health outcomes: (1) overweight, obesity and cardio-metabolic risks (hereafter referred to as ‘risks’), with ‘overweight and obesity’ also encompassing BMI, weight gain and related factors such as body fat percentage, body fat distribution, waist circumference; and ‘cardio-metabolic risks’ including high blood pressure, metabolic syndrome and relevant biomarkers for cardiovascular disease or type 2 diabetes; (2) diseases including cancer, cardiovascular disease and type 2 diabetes, and mortality (hereafter, referred to as ‘diseases’); and (3) other disorders and conditions (hereafter referred to as ‘disorders’). Studies on children and adolescents were considered separately to those on adults. In one study results on adults and adolescents were reported separately.

Data were extracted for the associations adjusted for potential confounders. Crude associations were extracted when the adjusted analysis was not performed. We presented only statistically significant associations (hereafter termed ‘associations’) in the written results and the relative risk of UPF exposure. For studies with a prospective design that also presented cross-sectional data, we presented the prospective results. There were varying terminologies describing body weight in the studies. We presented authors’ terminologies in Table 2 and Table 3 . In the results and discussion, we standardised to World Health Organization (WHO) definitions and BMI (kg/m 2 ) cut-off brackets for adults—(1) ‘overweight’ (BMI ≥ 25), to clarify this includes obesity; (2) ‘overweight (BMI 25–30)’ (BMI = 25.0–29.9), to clarify this excludes obesity; and (3) ‘obesity’ (BMI ≥ 30)—and WHO BMI-for-age z-scores for children, unless otherwise stated [ 46 , 47 , 48 ]. When more than one reference was included as NOVA reference, we assumed the most recent was applied to data classification.

Overweight, obesity and cardio-metabolic risks as outcomes in studies in adults *.

Results are presented for adjusted associations for potential confounders and statistically significant associations. NOVA refers to the food classification system [ 21 ] or earlier versions, as referenced; * Includes studies on all ages; ** includes beverages; # anthropometrics; ξ reported medical diagnosis, medication, or BP readings, ‡ results for adolescents are presented in Table 3 ; UPF: ultra-processed food (includes foods and beverages); BOA: Board of Agriculture; BMI: Body Mass Index [weight (kilograms)/height (metres) 2 ]; E: energy in kilocalories or kilojoules; WHO: World Health Organisation; OR: odds ratio; CI: confidence interval; WC: waist circumference (cm); increased WC: (men ≥ 94; women ≥ 80; significantly increased WC (men ≥ 102; women ≥ 88); AO: abdominal obesity (men ≥ 102 cm; women ≥ 88 cm); FFQ: food frequency questionnaire; DGB: Dietary Guidelines for the Brazilian Population; HR: hazards ratio; RR: relative risk; MPF: unprocessed or minimally processed food; MetS: metabolic syndrome; HT: hypertension; TAG: triacylglycerol; BG: blood glucose; HDL-C: high density lipoprotein cholesterol; MPF and PF ‘pattern’: factor derived ‘pattern’ of mainly MPF and processed food (PF); CRP = C-reactive protein; BP = blood pressure.

Overweight, obesity and cardio-metabolic risks as outcome (children and adolescents).

Results are presented for adjusted associations for potential confounders and statistically significant associations. NOVA refers to the food classification system [ 21 ] or earlier versions, as referenced. * Also included in Table 2 ; ** food includes food and beverages; UPF: ultra-processed food (includes food and beverages); E: energy in kilocalories or kilojoules; WHO: World Health Organisation; BMI; Body Mass Index; FFQ; food frequency questionnaire; MetS; metabolic syndrome; WC: waist circumference; HT: hypertension; TAG: triacylglycerol; BG: blood glucose; HDL: high density lipoprotein; PR: prevalence; LDL: low-density lipoprotein; DGB: Dietary Guidelines for the Brazilian Population; TC: total cholesterol.

The analysis was addressed by a narrative review with a comprehensive exploration of general direct and negative associations in different health outcomes, associations within studies, differential effects of study types, populations and ages, exposure differences, and outcome measures. Objectivity was achieved by a quality assurance process, including group consensus; and for each article, a quality assessment was undertaken [ 49 , 50 , 51 ], as described in Supplementary Material Table S3 .

3.1. Overveiew of Identified Studies

Since the NOVA thesis was first published in 2009 [ 9 ] there have been 43 peer-reviewed studies reporting on UPF exposure and health outcomes that met this review’s eligibility criteria. The first study was published in 2012 [ 75 ] and 34 (79%) have been published since 2018. Studies were on adults ( n = 31) (six excluded elderly, two excluded adults < 45 years), children ages 3–11 ( n = 4), adolescents ages 10–19 ( n = 5), and mixed ages ( n = 3). Study types were ecological ( n = 3), cross-sectional ( n = 19), prospective cohort ( n = 19), case–control ( n = 1); and one randomised controlled trial (RCT). Studies were conducted in Brazil ( n = 16) [ 53 , 56 , 62 , 63 , 66 , 70 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 ], France ( n = 8) [ 61 , 83 , 84 , 85 , 86 , 87 , 88 , 89 ], Spain ( n = 6) [ 65 , 72 , 90 , 91 , 92 , 93 ], USA ( n = 4) [ 59 , 67 , 71 , 94 ], Canada ( n = 2) [ 57 , 68 ], UK ( n = 2) [ 55 , 60 ], and one each in Sweden [ 36 ], Lebanon [ 69 ] and Malaysia [ 64 ]. There was one study on 19 European countries [ 52 ], and one global study [ 37 ].

There were various levels at which researchers extracted food data. In the ecological studies, one study extracted at the household level and one combined household with national agriculture availability data [ 36 , 52 ] and the third, a global study on 80 countries, used national per capita sales volumes of UPF [ 37 ]. The remaining studies extracted data at the individual level, except one cross-sectional study which extracted at the household level [ 53 ]. Collection methods included sales-data ( n = 1), household purchase records (range 7 days to one month, one combined with agricultural data) ( n = 3), food-frequency questionnaire (FFQ) (range 88-880 items, one combined with 24-h recall) ( n = 17), 24hr recall ( n = 9), food intake records (from choice up to >3000 food items) ( n = 9), food diary ( n = 2), diet history interview ( n = 1); and a designed diet for the RCT ( n = 1). Relative UPF exposure was presented by per capita availability of sales by volume ( n = 1), % household energy purchased ( n = 3), % individual energy intake ( n = 18), daily energy intake ( n = 2), frequency(times/day)( n = 5), servings/day ( n = 3), % total grams ( n = 8), UPF ‘score’ ( n = 1), UPF ‘pattern’ versus MPF ‘pattern’ ( n = 1); and complete diet comparison (mainly UPF diet versus mainly MPF diet) for the RCT ( n = 1).

Health outcome data collection methods were from self-report questionnaires (on diagnoses, anthropometrics, medication use, or medical histories), measurement by trained personnel, diagnoses by medical practitioners, or extracted from national registries or statistical records.

3.2. Ultra-processed Food Consumption

In studies on adults reporting the proportion of total energy intake from UPF, Malaysia was lowest (23%) [ 64 ]. Higher levels of consumption were reported in Spain (24.4%) [ 92 ], Lebanon (27.1%) [ 69 ], Brazil (20–29.6%) [ 56 , 62 , 66 , 70 ], France (29.9–35.9%) [ 61 , 86 , 87 ], Canada (45.1–51.9%) [ 57 , 68 ], and UK (53–54.3%) [ 55 , 60 ]. The highest levels were reported in the USA (55.5–56.1%) [ 59 , 71 ]. In studies in adults reporting servings per day or frequency of UPF consumption, one study in USA reported a mean of 4 times a day [ 94 ], and one study in Spain reported 1.4–5.3 servings per day from the lowest to highest quartile of UPF intake [ 91 ]. In French studies reporting consumption by weight of food, UPF ranged from 14.4 to 18.7% of total [ 61 , 83 , 84 , 86 , 87 ].

In children and adolescents (Brazil only) the proportion of total energy intake from UPF was reported as 41.8–43.4% at ages 3–4 years, 47.7–49.2% at ages 6–8 years [ 77 , 78 , 79 ] and 50.6% in adolescents [ 73 ]. One study reported 46.2% of adolescents consumed UPF weekly (median ≥ 3 times per week) [ 76 ], and another study reported frequency intakes varied from 9.9 (private schools) to 14.5 (public schools) times per day [ 74 ].

3.3. Studies Using Overweight, Obesity and Cardio-metabolic Risks as Outcomes (Adults)

Table 2 reports the findings of studies that investigated associations of UPF exposure and overweight, obesity and cardio-metabolic risks in adults.

3.3.1. Overweight, Obesity and Related Factors

We identified 16 studies on adults investigating UPF exposure and ‘overweight’ (BMI ≥ 25), ‘overweight (BMI.25–30)’, obesity or related factors as outcomes. One study included all ages (including infants) and two studies included children or adolescents. Twelve studies reported direct associations with adverse health outcomes, one study showed no association and three studies showed mixed results (i.e., associations were not observed for all measures investigated or did not reach statistical significance).

There were three ecological studies identified: Juul et al. [ 36 ] analysed agricultural national food data and sampled approximately 4000 households. They found trends in food energy availability had risen in Sweden from 1980 to 2010, alongside a 142% increase in UPF portion in the diet. The prevalence of overweight rose in men (from 35% to 56%) and women (26% to 39%), and obesity rose in men (4.5% to 11%) and women (5% to 10%), closely tracking an increased share in food energy purchases from UPF [ 36 ]. Monteiro et al. [ 52 ] analysed budget surveys across 19 European countries. They found each percentage point increase in national household total food energy availability from UPF from 1991 to 2008 was associated with a higher national prevalence of obesity of 0.25% [ 52 ]. Vendevijvere et al. [ 37 ] investigated Euromonitor annual sales in 80 countries and found that increases in UPF volume sales were directly associated with population-level BMI trajectories. In drinks, every standard deviation increase (51 kg/capita in 2002) saw mean population BMI increase by 0.195 kg/m 2 for men ( p < 0.01) and 0.072 kg/m 2 for women ( p < 0.003). In foods, every standard deviation increase (40 kg/capita in 2002) saw mean population BMI increased by 0.316 kg/m 2 for men ( p < 0.001) with no significant association for women [ 37 ].

There were six cross-sectional studies on nationally representative samples. In Brazil, Canella et al. [ 53 ] found that household energy availability of UPF (purchased food items converted to kcal/day) was directly associated with average BMI and prevalence of excess weight or obesity. As UPF consumption rose from Quartile 1 to Quartile 4, the prevalence of excess weight rose from 34.1% to 43.9%, and prevalence of obesity rose from 9.8% to 13.1% [ 53 ]. In a second study in Brazil, Louzada et al. [ 56 ] found those in the highest quintile by percent energy intake of UPF had higher BMI and higher odds of being obese or overweight than those with the lowest quintile intake. For overweight individuals, the association was not significant [ 56 ]. In Canada, Nardocci et al. [ 57 ] found individuals in the highest quintile UPF by percent energy intake had a greater risk of obesity and overweight (BMI 25–30) compared with the lowest quintile [ 57 ]. In US adults aged 20–64 years from National Health and Nutrition Examination Survey 2005–2014 (NHANES), Juul et al. [ 59 ] found individuals in the highest quintile UPF by percent energy intake had higher BMI and waist circumference, and higher odds of overweight, obesity and abdominal obesity, with associations more pronounced in women [ 59 ]. In a UK study of 2174 adults, Adams et al. [ 55 ] found no significant association between UPF by percent energy intake and overweight or obesity. PCI was associated with the lowest odds of overweight and obesity, and MPF-CPI was associated with lower odds of being overweight [ 55 ]. In a second study in the UK on 6143 adults aged 19–96 years, Rauber et al. [ 60 ] found individuals in the highest quartile UPF by percent energy intake had higher BMI and waist circumference, and a higher odds of having obesity than those in the lowest quartile [ 60 ].

There were four cross-sectional studies on non-nationally representative samples. In Brazil, Silva et al. [ 62 ] assessed 8977 active and retired civil servants aged 35–62. They reported individuals in the highest quartile of percent energy intake compared with lowest quartile had higher BMI and waist circumference, as well as higher odds of being overweight (BMI 25–30), being obese, having increased waist circumference, or having significantly increased waist circumference [ 62 ]. In France, Julia et al. [ 61 ] studied 74,470 participants in a web-based Nutri-Santé cohort. They measured UPF intake by percent weight by quartiles and found UPF was associated with overweight (BMI 25–30), and energy-weighted quartiles were associated with overweight (BMI 25–30) and obesity [ 61 ]. In smaller studies, De Silveira et al. [ 63 ] examined vegetarians over 16 years old ( n = 503) and found overweight in high UPF consumers was 38.3% versus mean 23.5%. In Malaysia, Ali et al. [ 64 ] studied adults 18–59 years ( n = 167) and found no association between UPF and BMI or percentage body fat.

There were two prospective cohort studies. In Spain, Mendonca et al. [ 65 ] followed 8451 middle-aged graduates not overweight at baseline for a median of 8.9 years. Participants in the highest quartile of UPF intake (servings/day) had a 26% higher risk of developing overweight relative to the lowest quartile [ 65 ]. Considering those lost to follow-up, and those with repeated exposure measurement at 10-year follow-up, there remained a 24% risk and 19% risk, respectively [ 95 , 96 ]. In Brazil, Canhada et al. [ 66 ] followed 11,827 adults for 3.8 years. Participants in the highest quartile of UPF by percent energy intake had a 27% greater risk of developing ‘large weight’ and 33% risk of ‘waist gains’ than those in the lowest quintile. In those not overweight at baseline, there was a 20% risk of developing overweight compared to the lowest quartile. In crude analysis, for those overweight and not obese (BMI 25–30) at baseline there was an increased risk of developing obesity, but this did not reach significance in the fully adjusted model considering baseline BMI [ 66 ].

There was one randomised controlled crossover trial. In 20 US weight-stable adults free of disease at baseline (mean age 31.2 ± 1.6 years; mean BMI 27 ± 1.5 kg/m 2 ), Hall et al. [ 67 ] found that an a ultra-processed diet caused weight gain. Participants were provided two complete diets (either ultra-processed (81.3% energy from UPF) or unprocessed (0% UPF)) matched for calories, sugar, fat, sodium, fibre and macronutrients, in random order, in excess of daily energy requirements to consume ad libitum for 14 days each diet. Participants had a greater eating rate, consumed more energy (508 ± 106 kcal/day; p = 0.0001) and gained weight (0.9 ± 0.3 kg; p = 0.009) on the ultra-processed diet, and lost weight 0.9 ± 0.3 kg ( p = 0.007) during the unprocessed diet. Weight changes were highly correlated with energy intake ( r = 0.8, p < 0.0001) [ 67 ].

3.3.2. Cardio-Metabolic Risks

We identified five studies assessing cardio-metabolic risk factors in adults. Three showed an association of UPF exposure and adverse health outcome, one study reported mixed results, and one study had no observed association. There were four cross-sectional studies. On a representative sample of US adults, Martinez Steele et al. [ 71 ] found the highest quintile of UPF intake by percent energy was associated with 28% higher metabolic syndrome prevalence rate compared to the lowest quintile intake. Each 10% increase in consumption was associated with a 4% increase in metabolic syndrome prevalence. The association was strongest in younger adults [ 71 ]. In a study in Brazil of 8468 adults, Lopes et al. [ 70 ] found women in the highest tercile of UPF by percent energy intake had higher levels of C-reactive protein (CRP) than those in the lowest tercile. When controlling for BMI, the association was not statistically significant. No association was found in men [ 70 ]. In Canada, Lavigne-Robichard et al.’s [ 68 ] study of adults ( n = 811) found those in the highest quintile of UPF intake by percent energy had a higher prevalence of metabolic syndrome, reduced high-density lipoprotein cholesterol and elevated fasting glucose [ 68 ]. In a Lebanese study of adults ( n = 302), Nasreddine et al. [ 69 ] found those in medium/high adherence to a factor-derived MPF and PF ‘pattern’ vs. low adherence had lower odds of metabolic syndrome, hyperglycaemia and low HDL-C. No significant association was observed with metabolic syndrome and UPF ‘pattern’ [ 69 ]. There was one prospective cohort study. In Spain, Mendonca et al. [ 72 ] followed 14,790 adult graduates for a median 9.1 years. Participants in the highest tertile of UPF consumption (servings/day) had a 21% higher risk of developing hypertension than those in the lowest tertile [ 72 ].

3.4. Overweight, Obesity and Cardio-Metabolic Risks as Outcomes (Children and Adolescents)

There were eight studies on children and adolescents assessing UPF exposure and overweight, obesity body weight or cardio-metabolic risks as an outcome, which are presented in Table 3 . Three studies showed associations of UPF intake and outcomes, four showed no associations and one had mixed results. All studies were from Brazil.

There were three studies on overweight and obesity. In a nationally representative cross-sectional sample on children and adolescents aged 10–19, Louzada et al. [ 56 ] found no significant association with UPF and mean BMI, overweight/obesity or obesity. In a small cross-sectional study on adolescents aged 10–18 years ( n = 200), Enes et al. [ 73 ] found no association between UPF consumption and anthropometric indicators. In a prospective cohort study, Cunha et al. [ 74 ] followed 1035 adolescents (mean age 16 years) for three consecutive years and found no significant difference in BMI and percentage body fat trajectories.

There were five studies assessing cardio-metabolic risks. In a cross-sectional study on adolescents aged 12–19 years (n = 210), Tavares et al. [ 75 ] showed those with high UPF consumption (>Quartile 3) was associated with higher metabolic syndrome than those in the lowest quartile. In a second cross-sectional study on adolescents aged 14–19 years (n = 249), Melo et al. [ 76 ] found that while UPF was not associated with excess weight, hypertension or high waist circumference, consumption of MPF was inversely associated with excess weight. There were three prospective cohort studies. Following children aged 4–8 years ( n = 345), Rauber et al. [ 77 ] reported UPF consumption (by percent energy intake) at pre-school age was a predictor of higher total and LDL cholesterol at school age. In a follow-up of a previous RCT on 307 children aged 4–8 years, Costa et al. [ 78 ] found for every increase of 10% energy intake from UPF, delta waist circumference increased by 0.7 cm. Further, higher UPF consumption at pre-school age was a predictor of an increase in delta waist circumference from pre-school to school age. No association with fasting glucose or insulin was detected [ 78 ]. Leffer et al. [ 79 ] following young children, for three years found those children in the highest tertile of UPF energy intake at age 3 had higher levels of total cholesterol, and tri-acyl glycerol at age 6 than those in the lowest tertile [ 79 ].

3.5. Studies Using Diseases and Mortality as Outcomes

Table 4 reports the findings from studies that evaluated the association of UPF exposure and diseases and mortality as outcomes.

Diseases and mortality as outcomes.

Results are presented for adjusted associations for potential confounders and statistically significant associations. NOVA refers to the food classification system [ 21 ] or earlier versions, as referenced; UPF: ultra-processed food (includes food and beverages); E:energy in calories or kilojoules; OR: odds ratio; FFQ: food frequency questionnaire; CI: confidence interval; HR: hazards ratio; food = food and beverages; BC = breast cancer; ICD-10:International Classification of Disease; CVDL cardiovascular disease, CHD: coronary heart disease; T2D:Type 2 diabetes; ACM: all-cause mortality.

3.5.1. Cancer

In a case–control study investigating breast cancer in Brazil, Quiroz et al. [ 81 ] matched 59 women with breast cancer to 59 non-cancer controls. They found regular consumption of UPF (>5 days/week) was identified as having 2.35 times higher odds of breast cancer [ 81 ]. In a longitudinal study, Fiolet et al. [ 84 ] found a higher incident rate of cancer with UPF exposure. For every 10% increment in the proportion of UPF in the diet (by percentage grams), there was a 12% higher risk for total cancers, and 11% increased risk for breast cancer [ 84 ].

3.5.2. Cardiovascular Disease

In a prospective cohort study on 105,109 adults over a median period of 5.2 years, Srour et al. [ 83 ] found a higher incident rate of all cardiovascular disease (CVD) in those with the highest intake of UPF consumption (by percentage weight). Those in the highest quartile intake had a 12%, 13% and 11% increased risk of all CVD, coronary heart disease and cerebrovascular disease, respectively [ 83 ].

3.5.3. Type 2 Diabetes

In France, Srour et al. [ 87 ] followed 104,707 participants free of type 1 or type 2 diabetes for a median 6.0 years. Participants with a higher proportional intake (by weight) of UPF in the diet had significantly higher risk of type 2 diabetes. A 10% increase in UPF in the diet was associated with a 15% higher risk of type 2 diabetes [ 87 ].

3.5.4. Mortality

In a mortality study of US adults aged over 20 years over a median follow-up of 19 years, Kim et al. [ 94 ] found those participants with the highest quartile of consumption of UPF (frequency/day) had a 31% higher risk of all-cause mortality. There was no observed association with CVD mortality [ 94 ]. In a study of 44,551 individuals over a median period of 7.1 years in France, Schnabel et al. [ 86 ] found that participants who consumed a higher proportion of UPF (by proportion of weight in grams) had a higher risk of all-cause mortality. Each 10% increment in proportion consumed was associated with a 14% higher risk of all-cause mortality [ 86 ]. In a prospective cohort study in Spain of 19,899 individuals, Rico-Campa et al. [ 91 ] found participants in the highest quartile of UPF consumption (by servings per day) had a 62% higher risk of all-cause mortality. For each additional serve, there was an 18% higher risk. No significant associations were found with CVD and cancer mortality [ 91 ]. In a second prospective cohort study in Spain, Blanco-Rojo et al. [ 92 ] followed 11,898 individuals for 7.7 median years. They found participants in the highest quartile of consumption (by percent energy) of UPF had a 44% higher risk of all-cause mortality. Iso-caloric substitution of UPF with MPF was associated with a decrease in mortality [ 92 ].

3.6. Studies Using Other Disorders and Conditions as Outcomes

Table 5 reports the findings of studies that investigated associations of UPF exposure and other disorders and conditions as outcomes.

Disorders and conditions as outcomes.

Results are presented for adjusted associations for potential confounders and statistically significant associations. NOVA refers to the food classification system [ 21 ] or earlier versions, as referenced; food means foods and beverages; * self-report from questionnaire on condition, medical history, symptoms, medication use, and/or diagnosis by medical practitioner; ** questionnaire plus validation on sample laboratory test or interview; UPF: ultra-process food (includes food and beverages); E: energy in calories or kilojoules; OR: odds ratio; CI: confidence interval; IBS: irritable bowel syndrome; FDy: functional dyspepsia; IBD: inflammatory bowel disease; CES-D scale: Centre for Epidemiologic Studies Depression Scale; HR: hazards ratio; FFQ: food frequency questionnaire; HR: hazards ratio.

3.6.1. Gastrointestinal disorders

In a cross-sectional study in France of 33,343 adults, Schabel et al. [ 85 ] found participants in the highest quartile of UPF intake by percentage share (g/day) had a higher risk of irritable bowel syndrome (IBS)—either alone or when considering IBS and functional dyspepsia (FDy)—compared to those in the lowest quartile. There was no association of UPF intake with FDy alone [ 85 ]. In a prospective cohort study in France, Vasseur et al. [ 88 ] found no significant association with UPF intake and inflammatory bowel disease.

3.6.2. Depression

In a prospective cohort study in France, Adjiade et al. [ 89 ] followed 26,730 individuals without depressive symptoms at baseline by Centre for Epidemiological Studies Depression Scale (CES-D) scale) for mean 5.4 years. Participants in the highest quartile of UPF intake by percentage share (g/day) had a 31% increased risk of developing depression than those in the lowest quartile. An estimated 10% increase in UPF consumption was associated with a 21% increased risk of depression [ 89 ]. In Spain, Gomez-Donoso et al. [ 90 ] followed 14,907 university graduates free of depression (by diagnosis history) for a median 10.3 years. Participants in the highest quartile intake of UPF (percentage share g/day, energy-adjusted) had a 33% higher risk of developing depression than participants in the lowest quartile [ 90 ].

3.6.3. Frailty

In a prospective cohort study in Spain, Sandoval-Insausti et al. [ 93 ] followed 1822 adults >60 years free of frailty for 3.5 years. Those in the highest quartile of UPF intake (percent total energy) had 3.67 times higher odds of frailty than those in the lowest quartile [ 93 ].

3.6.4. Asthma

In a nationally representative sample of students aged 13–16 years, Melo et al. [ 80 ] found an association between a higher UPF score (based on consumption of selected sub-categories of UPF) and asthma in a dose-response manner. In a prospective cohort study in Brazil, Azerado et al. [ 82 ] followed 2190 children aged 6–11 years and found no association between UPF consumption (percent energy intake) and wheeze, asthma or severe asthma.

3.7. Quality Appraisal

The limitations and strengths found in the appraisal were used to support the critiques of studies in the discussion section. Further details are described in Supplementary Material Table S3 .

4. Discussion

This review identified 43 studies investigating associations between UPF exposure and various health outcomes and related risks, with most studies reporting more than one outcome. In 37 studies, there was at least one statistically significant association between UPF exposure and at least one adverse health outcome. No study reported an association between UPF exposure and beneficial health outcomes that reached statistical significance, were adjusted for covariates and―in prospective studies―were reported at follow-up. Beneficial outcomes were found associated with diets higher in MPF. The findings can be summarised and classified as follows: (1) in 21 studies assessing overweight, obesity and cardio-metabolic risks in adults, 15 reported significant associations and adverse health outcomes, four reported mixed associations (that is some adverse health outcomes, and some with no associations), and two found no significant associations; (2) in eight studies assessing disease or mortality, five found significant associations and adverse health outcomes, and three found mixed associations; (3) in seven studies investigating other disorders and conditions, five found only significant associations and adverse health outcomes, and two found no associations; (4) in eight studies reporting on overweight, obesity and cardio-metabolic risks in children and adolescents, three found significant associations with adverse health outcomes, two found mixed associations and three found no associations. Seven studies in adults found associations between diets high in MPF (or MPF combined with PCI or PF) and beneficial health outcomes. A study on mortality found iso-caloric substitution of UPF with MPF was associated with a decrease in mortality.

Exposure to UPF was found to be associated with population BMI trajectories, overweight and obesity prevalence as well as individual BMI, overweight including obesity (BMI ≥ 25), overweight excluding obesity (BMI 25–30), obesity, weight gain, abdominal obesity, metabolic syndrome, high blood pressure, blood lipids, blood glucose, type 2 diabetes, cardiovascular disease, coronary artery disease, cerebrovascular disease, overall cancers, breast cancer, frailty, IBS, depression and mortality (in adults), and asthma, blood lipids, metabolic syndrome and delta waist circumference (in children or adolescents). The studies that found no associations were assessing BMI, overweight, obesity, metabolic syndrome, inflammatory bowel disease, CRP (men), prostate and colorectal cancer, and mortality in CVD and cancer (in adults) or anthropometric indicators, high blood pressure, blood glucose and insulin resistance (in children). Although they showed no associations with UPF and investigated outcomes, two studies on adults and one on adolescents demonstrated that a higher intake of MPF-PCI had lower odds of overweight/obesity [ 55 ], a higher intake of MPF/PF ‘pattern’ had lower odds of metabolic syndrome [ 69 ], and MPF intake was inversely associated with overweight [ 76 ]. Three of the French studies found an association between diets higher in MPF consumption and lower risk of adverse health outcomes [ 83 , 84 , 87 ]. The RCT found participants lost weight and had improved bio-markers during the MPF diet phase [ 67 ].

4.1. Overweight, Obesity and Cardio-Metabolic Risks as Outcomes (Adults)

The majority of studies investigating UPF exposure and adverse health outcomes of overweight, obesity or cardio-metabolic risks showed associations. The WHO defines overweight and obesity as ‘abnormal or excessive fat accumulation that may impair health’ [ 48 ] and states that weight gain, at whatever the original weight, is a risk for disease [ 46 , 47 ]. Overweight and obesity are both significant risks for CVD, cancers and mortality, with body fat distribution, blood lipids, hypertension and blood glucose related risks [ 97 ]. Studies in individuals that measured only mean BMI, overweight and obesity [ 53 , 56 , 57 , 59 , 61 , 66 ] are indicative of risk. However, studies including body fat anthropometrics, abdominal obesity or biomarkers [ 59 , 60 , 62 , 67 ], the two prospective studies and RCT showing weight gain over time [ 65 , 66 , 67 ], the prospective study on hypertension [ 72 ], a study on metabolic syndrome on a nationally-presentative sample [ 71 ], and a smaller study [ 68 ] provide stronger support of the risk of UPF exposure. Moreover, the ecological studies tracing UPF purchase country comparisons [ 52 ] or time-trend analyses within [ 36 ] and between [ 37 ] countries, all showed an association with or trajectories of higher exposure to UPF and the risk to population prevalence rates or weight trajectories over time within or between countries.

The ecological studies’ strengths were the use of national obesity statistics [ 36 , 52 ], large standardised datasets [ 37 ] and nationally representative population surveys with complex sampling [ 52 ], which support an association of UPF availability and rising rates of global obesity and population mean BMIs. The strengths of the cross-sectional studies were in nationally representative samples ( n = 6) or large samples ( n = 2) with data extraction at individual intake, except one by household purchases [ 53 ] and outcome measurements by trained personnel in all studies except two [ 61 , 63 ] and partially in a third [ 57 ]. Critically, in two prospective cohort studies, Canhada et al. [ 66 ] and Mendonca et al. [ 65 ] demonstrated individuals not overweight or obese at baseline moved over time to BMI parameters of significant risk, with individuals in the highest quartile of UPF having the highest risk. The studies’ strengths were demonstrating both the risk over time for an individual, and group comparison of higher to lower UPF exposure. The Mendonca et al. study was on younger health professionals (mean age 37.6), a group who may be more motivated to follow a healthy diet pattern [ 65 ]. Results may not be applicable to the general population and in fact may be worse in those less motivated to follow a ‘healthy’ diet, which would make the association of UPF exposure and body weight gain even stronger. An interventional RCT study by Hall et al. [ 67 ] demonstrated weight gain on consumption of UPF diet and weight loss on an unprocessed diet. While whole diets are unable to be blinded, participants were blinded to glucose readings, and to weight change by wearing loose-fitting clothing.

Ecological studies were limited by methodologies unable to separate age and gender [ 36 , 52 ], the exclusion of food purchases outside the home or take-away food outlets [ 37 , 52 ], or time lags between the collection of survey data and obesity data of up to five years [ 52 ]. Ecological studies are considered a relatively weak study design due to the risk of bias in interpreting results that are observations at the population level, not necessarily translatable to individuals; and all cross-sectional studies are unable to determine causality and temporality and have the potential for confounders. In studies with mixed results, one study showed that in women (but not men), there was an association of UPF exposure with higher CRP, although not after controlling for BMI [ 70 ]. The authors posited that adiposity was driving the inflammation; however, it is also possible that inflammation could be driving adiposity [ 98 , 99 ] and that diet-induced inflammation could facilitate further pro-inflammatory events [ 98 , 100 ]. Three studies did not find any association of UPF exposure and overweight, obesity or cardio-metabolic risks. A Malaysian study on university personnel found no association with BMI or percentage body fat [ 64 ]. The study was limited by its small sample size and noted difficulties in the application of NOVA to the national food database. One study on a nationally representative sample in the UK showed no associations of UPF and body weight parameters [ 55 ]; whereas, the consumption of MPF-PCI pattern had lower odds of overweight and obesity. Likewise, in a study that showed no significant association with UPF and metabolic syndrome [ 69 ], there were lower odds of metabolic syndrome, low HDL and hyperglycaemia with higher MPF/PF intake. Both studies provide support for MPF diets over UPF. The UK study used an early NOVA classification and a more recent study found direct associations between UPF exposure and obesity [ 60 ].

4.2. Overweight, Obesity Cardio-Metabolic Risk as Outcomes (Children and Adolescents)

In investigations of cardio-metabolic risks in children and adolescents, three prospective studies following young children from ages three (or four) through to ages six (or eight) years showed a higher intake of UPF at age three (or four) predicted higher total cholesterol, LDL cholesterol, tri-acyl glycerol and/or increased delta waist circumference at age six (or eight) [ 77 , 78 , 79 ]. In cross-sectional studies, one study on adolescents showed an association of higher UPF intake and metabolic syndrome [ 75 ], and a second on adolescents showed no association with overweight, higher waist circumference and high blood pressure [ 76 ]. Three studies investigating overweight and obesity on older children and adolescents aged 10–19 years showed no association of UPF with anthropometrics measured [ 56 , 73 , 74 ]. Direct comparisons of the studies were difficult due to differing study designs, exposure measurements and outcomes and methodological weaknesses. Two of the studies reported quite high mean energy intakes of >4000 Kcal/day (>17,000 KJ) [ 73 , 74 ], and one study had a very small sample ( n = 200) with a low power of the statistical test [ 73 ]. In the prospective study there was a large drop-out rate of 43% [ 74 ]. The authors reported cross-sectional results and prospective changes were not statistically significant.

Children and adolescents have age-appropriate energy and nutrients needs for normal growth, development, cognitive advancement, physical activity and prevention of micro-nutrient deficiencies [ 101 ], in addition to consideration of risk for NCDs. The three studies on young children consistently showed a higher proportion of UPF were consumed at school age compared to preschool age and consistently showed direct associations between UPF consumption and cardio-metabolic or obesity risk. These provide strong support for an association between UPF consumption and cardio-metabolic risks in young children, and there is a concern that UPF consumption rises with age in childhood. The less strong associations in studies in older children and adolescents generally may be attributed to the role of the growth spurt in the pubertal years together with higher physical activity limiting excess weight. Nevertheless, dietary habits set in childhood and adolescence may be difficult to change, and there is a need to study post-pubertal young adults in future studies. The age bracket from post pre-school to pre-adolescence (~age 7–10) was under-represented in the studies reviewed. With the studies’ methodological differences and limitations, it is difficult to draw any firm conclusions in older children and adolescents.

4.3. Diseases and Mortality as Outcomes

There were four studies investigating UPF exposure and disease, and four studies investigating UPF and mortality. All of the studies showed a direct association with UPF intake and outcomes of breast cancer, total cancers, cardiovascular disease, coronary heart disease, cerebrovascular disease and mortality. There were no associations shown for prostate and colorectal cancer, cancer mortality and CVD mortality. Seven of the studies were prospective cohort studies and there was one case–control study in breast cancer cases compared to matched controls. Health outcome measurements were by validated scales of measure, medical records, confirmed diagnosed history and (for mortality) national death registries. All studies reported statistical analyses adjusting for appropriate covariates.

4.4. Studies that Investigated Other Disorders and Conditions as Outcomes

Seven studies investigated exposure to UPF and other disorders. Direct associations were observed with UPF intake and IBS, depression and frailty in adults [ 85 , 89 , 90 , 93 ]. Frailty, in turn, is a risk for stressors and less inclination for physical activity, and is in itself a risk for CVD [ 102 ]. One prospective study showed no association with inflammatory bowel disease. In the two studies investigating asthma, a prospective cohort study in children aged 6–11 years showed no association [ 82 ], and a cross-sectional study drawn from a representative sample of adolescents showed a direct association [ 80 ]. The studies are not directly comparable due to different study designs, age brackets and UPF definition, including 18 and 21 UPF groups in one study, and six in the other. While disorders and conditions are not considered main contributors to the global burden of death, they are main contributors to the burden of non-fatal illnesses and DALYs lost [ 11 ]. It is important to recognise the contribution diet—and in particular, UPF—is having on the reported incidence rates of these conditions.

4.5. Dietary Assessment, UPF Definitions and Confounding Variables

Most of the studies found UPF exposure was associated with one or more adverse health outcome. However, the differences in studies’ methodologies make comparisons between studies difficult.

Firstly, concerning the UPF definition, the original NOVA three-group (now four-group) food processing classification was first proposed in 2010 [ 9 , 25 ]. This was followed by development [ 26 , 27 , 29 , 54 ] and insertion into the dietary guidelines for the Brazilian population in 2014 [ 28 ]. An update occurred in 2016 [ 22 ], and further explanatory documents were published in 2018 and 2019 [ 21 , 30 ]. NOVA history has been described elsewhere [ 5 , 22 , 29 ]. The studies described in this review used these varying historical versions and additional studies on NOVA [ 33 , 58 ] as their reference for UPF definition, resulting in some differences in the foods classed as UPFs. Further details are provided in Supplementary Material Table S2 . For example, the studies using early definitions with only three food groups (‘ultra-processed food products’ contained the current groups three and four; that is, with cheese and all bread regarded as UPF and pasta regarded as PCI) [ 53 , 55 , 56 , 69 , 74 , 75 , 81 ], and artisanal bread included as UPF until 2014 [ 36 , 59 , 77 ], may not directly compare to studies using later definitions. Studies also ranged in the reporting of their application of NOVA from the provision of only a reference and brief description [ 70 , 75 ] or short food lists mismatched to reference [ 68 ] to detailed supplementary lists and/or explanations of analysis of national food databases of >3000 foods [ 61 ].

Secondly, against a broad range in the strengths and limitations of various data extraction methods [ 103 ], authors noted additional benefits or constraints of instruments in application to NOVA, and to national food databases. Food diaries (able to account for seasonal or weekly variations) [ 60 ] and 24-h recalls [ 59 , 78 ] record actual foods consumed and preparation methods, with fewer difficulties were noted in application than reported in the use of FFQs. FFQs included between 55 and 880 items and UPF ranged from 6 to >21 sub-groups, with application to NOVA constrained to foods listed. In several instances, foods were classified differently across surveys due to different food systems in country-specific contexts. For example, some FFQs do not separate the bread type and in the US and UK it is mainly UPF [ 60 , 104 ], whereas in France and Spain it is mainly artisanal [ 52 , 61 ]. Additional complexities included application to food databases with a lack of information on the differentiation of canned food into PF or UPF, databases disaggregating foods to nutrient content rather than processing type (e.g., frozen pizza disaggregated to component ingredients could inadvertently be classed as PF or PCI, and not correctly as UPF), and disaggregating handmade dishes (e.g., Bolognese pasta) into major food-items in the recipe (e.g., group 1, pasta) rather than underlying ingredients (pasta, meat, sauce, oil), which is the recommended approach [ 59 , 105 ].

Thirdly, most studies used percent energy intake as a measure of relative exposure of UPF, which is difficult to compare to studies that used frequencies (times per day), servings per day, or consumption of an UPF ‘pattern’. The French NutriNet-Santé studies used percentage weight per day, arguing the need to account for UPF that have no or less energy value (e.g., artificially sweetened beverages) than regular alternatives [ 61 , 83 , 84 , 85 , 86 , 87 , 88 ]. Ideally, prospective studies collect food data more than once, yet some studies provided no details or collected data only once [ 72 ]. Conversely, the NutriNet-Santé studies collected data by the use of three 24-h records every six months for two years to establish a baseline diet and UPF intake [ 61 , 83 , 84 , 85 , 86 , 87 , 88 ].

Lastly, adjustments for confounding variables differed among the studies. In particular, one ecological study did not have access to data on confounders [ 36 ]. Some studies did not adjust for total energy, which confounds the risk for weight gain which is in itself a risk for CVD, cancer and type 2 diabetes; or for physical activity [ 55 , 63 , 76 ] (or used proxies [ 56 ]), which confounds the risk for CVD. These factors make comparisons between studies difficult.

4.6. Consistency with Findings in Other Reviews and Studies

That UPF exposure has been found to be associated with numerous diseases and conditions across a broad range of ages, populations and settings, underlines the role of diet quality as assessed by the ‘extent and purpose of industrial processing’ (as defined by NOVA [ 21 ]) influencing human health. This finding is consistent with findings reported in other reviews [ 2 , 3 , 4 , 5 , 7 ]. An early narrative review [ 4 ] and a recent systematic review [ 5 ] investigating studies on UPF exposure and obesity and/or cardio-metabolic risks, and a systematic review investigating body fat in childhood [ 2 ], similarly found most studies showed direct associations. The recent review [ 5 ] and a systematic review of studies of children’s dietary intake in relation to Brazil’s Dietary Guidelines [ 106 ] also noted that the literature was marred by inconsistencies in study definitions and methods. However, our review found the more recent studies—particularly the French, Spanish, US and UK studies since 2018—which do not have the NOVA classification limitations as in earlier studies, have adjusted for confounders, and expert teams have evolved comprehensive processes for analysis and classification of national surveys and food-databases in the application of NOVA classification [ 37 , 59 , 60 , 61 , 65 , 67 , 71 , 72 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 ]. Our review found similar UPF consumption trends as previously reported of up to >50% in high income countries and up to 30% in middle income countries. Notably Spain (24.4%) and France (29.9–35.9%) had lower UPF intake than Canada, UK and the USA (45.1–56.1). In Brazil, children (41.4–49.2%) and adolescents (50.6%) had higher consumption rates than adults (20–29.6%). In our review, one prospective study in adolescents showed an association of UPF exposure and beneficial effects at baseline that did not reach statistical significance at follow-up [ 74 ]. In a book chapter reporting a study in Kenya, beneficial nutritional effects were found associated with UPF in children [ 107 ]. Food data, however, were extracted at the household level and estimated to individuals.

4.7. Proposed Mechanism of Effects

Evidence for the mechanisms underpinning the link between UPFs and adverse health outcomes is still emerging. Proposed mechanisms include a poor nutritional profile (i.e., UPFs are vectors for added sugars, sodium and trans-fats) and displacement of MPFs in the diet [ 33 , 34 , 35 , 58 , 108 , 109 , 110 , 111 , 112 , 113 , 114 ], higher glycaemic load and reduced gut–brain satiety signalling resulting from altered physical properties created by the processing of foods [ 115 , 116 , 117 , 118 ], carcinogens formed during high-temperature cooking (e.g., carbohydrate-rich foods with acrylamide) [ 119 , 120 ], and inflammatory responses linked with acellular nutrients and industrial food additives, gut microflora dysbiosis and increased intestinal permeability [ 98 , 121 , 122 ]. Certain properties of UPFs may promote overconsumption [ 123 ], including their often ubiquitous availability and convenience [ 124 , 125 , 126 ], palatability and quasi-addictiveness [ 127 , 128 ] and intensive marketing practices used to promote purchasing and consumption, especially among children and adolescents [ 129 , 130 , 131 ].

The NutriNet-Santé prospective studies investigating CVD and cancer found participants with high UPF exposure consumed diets higher in energy intake, sodium, lipids and carbohydrate, and participants in the CVD study had lower intakes of MPF, fruit, vegetables and fibre; in the study on type 2 diabetes, participants with higher UPF intake consumed diets higher in energy intake, sugar and sodium, and lower in wholegrain cereals, fruit, vegetables and fibre [ 83 , 84 , 87 ]. However, the studies reported associations of UPF exposure and the diseases remained even after adjusting for energy intake, salt, sugar/added sugar and Western dietary patterns (for CVD and cancer), and for a low ‘healthy’ diet pattern/diet quality (CVD and type 2 diabetes) or fibre (CVD). Those associations remained after adjustments, which suggest something other than nutritional factors may be contributing to the recorded observations. Moreover, in the CVD study, associations were observed for individual UPF food groups such as beverages, fats and sauces, meat, fish and eggs, sugary products and salty snacks; yet associations were stronger when the overall amount of UPF was considered rather than specific food groups. The authors postulated possible synergistic effects of many compounds in UPF. Similarly in other studies adjusting for overall diet ‘quality’, the associations between UPF exposure and adverse health outcomes or mortality remained [ 91 , 94 ].

In the RCT by Hall et al. [ 67 ], energy intake was greater during the UPF diet; the participants consumed more fat and carbohydrate, and gained weight and body fat. The diets were controlled for presented calories, energy density, macronutrients, sugar, sodium and fibre, providing causal evidence that something other than risk nutrients in UPFs causes energy intake and weight gain, and an increase in body fat with the consumption of a diet higher in UPFs. The study showed reduced secretion of the hunger hormone ghrelin, as well as increased levels of the satiety hormone PYY (peptide YY) with the unprocessed diet. Hence, relative to UPFs, unprocessed foods may stimulate more efficient regulation of biological mechanisms controlling hunger and satiety. The study also showed a reduction in the inflammatory bio-marker hs-CRP (highly sensitive CRP) with the unprocessed diet, and inflammation has been demonstrated to be coupled with satiety signals in animal studies [ 98 ].

Critics of NOVA have argued that ‘healthy dietary patterns’ are linked to nutrient intakes [ 132 ], and any adverse health effect seen in studies on UPF can be explained by nutritional factors [ 133 ] such as the presence of high levels of sugar, fat and salt. However, the literature indicates that the effects of ultra-processing on a food’s physical structure and chemical composition is independent of and therefore in addition to the effects of ‘risk’ or ‘positive’ nutrients present in the food [ 67 , 83 ]. Moreover, a defining characteristic of the NOVA classification is classifying added sugar, oils and fats, and salt as ingredients (Group 2). In UPF (Group 4), it is the high amount of these ingredients combined with processing techniques (deconstruction of the food matrix, removal of water) and addition of cosmetic additives, that explains the final characteristic of UPFs (high content of sugar, salt, fat; high energy density; and palatable) [ 21 ]. A further explanation of the mechanism by which UPFs influence health outcomes is that their inclusion in the diet displaces ‘protective’ MPFs, with low intakes of MPFs increasing the risk of CVD, cancer, type 2 diabetes and mortality [ 5 , 10 ].

4.8. Strength and Limitations

This is the first study to perform a systematic search for studies that have investigated UPF exposure and health outcomes, combined with a narrative review. The strengths of this review are the broad inclusion of study types, populations and health outcomes, a quality assurance process that involved a team working together and reaching consensus-based decisions, and undertaking a synthesis of the evidence to provide a coherent assessment of the role UPFs in influencing human health.

This review has limitations. We did not assess studies investigating participants with pre-existing conditions (including overweight or obesity) where UPF intake was considered an outcome. Interestingly such studies have similarly found direct associations of health conditions and UPF consumption [ 134 , 135 ]. The review was limited by the constraints within the studies under review which were mainly observational studies that cannot deduce cause and effect relationships. The smaller studies were difficult to compare to studies with national representative samples, yet were important representations of special groups or varying cultures [ 63 , 64 , 68 , 69 ].

4.9. Future Priorities for Nutrition Research and Policy Practice

With the rapidly growing number of studies reporting associations between UPFs and adverse health outcomes, and NCDs, there is an increasing need to take on board the contribution of these foods to the global burden of disease, as well as the need to act on multiple levels, including through government regulation, to improve the health prospects of current and future generations.

In the future, priority research activities to further develop the body of evidence for associations between UPF intake and health outcomes include continuing to analyse existing cohorts, conducting clinical trials, extending the cohort and clinical studies to a range of population groups, such as those in low- and middle-income countries, as well as childhood and adolescence years, to determine whether UPF influences on metabolism start before adulthood, and investigating plausible causal pathways to provide mechanistic understandings of the nature of the health associations. Further priorities include standardisation of application of the NOVA classification and analysed national databases, and a protocol for including confounder adjustment, especially weight parameters (with obesity being a known risk for CVD, cancer and type 2 diabetes) and low physical activity (a risk for CVD) [ 97 ].

With this solid evidence base the need for NOVA and UPF issues to be applied in policy practice, for example to food labelling and informing food procurement activities, is even more relevant. Food-based dietary guidelines and nutrition policy actions should consider incorporating the concept of ultra-processing to describe the healthiness of individual foods within the overall dietary pattern.

5. Conclusions

This review has shown that a high dietary intake of ultra-processed foods is associated with a range of adverse health outcomes, and non-communicable diseases, disorders and conditions, thereby bearing the potential to significantly influence the global burden of disease. Moreover, evidence suggests a higher risk of all-cause mortality with high consumption of ultra-processed foods. No study reported an association between UPF and beneficial health outcomes. The review has also shown beneficial outcomes were associated with diets higher in unprocessed and minimally processed foods. Although the majority of studies are of observational nature, the evidence base concerning plausible biological mechanisms supporting the observed associations is steadily evolving. The findings in this review support the notion that inferring health effects from individual nutrients and ingredients in foods is insufficient, and that industrial processing, and its extent and purpose, may add accuracy and reliability in predicting and explaining associations between foods and health outcomes. The considerable and growing body of evidence supporting the use of ultra-processed foods as a scientific concept to assess the ‘healthiness’ of foods within a dietary patterns context has the potential to improve future development of dietary guidelines as well as nutrition policy actions.

Abbreviations

Supplementary Materials

The following are available online at https://www.mdpi.com/2072-6643/12/7/1955/s1 , Table S1: NOVA food groups definitions according to the extent and purpose of food processing, with examples; Table S2: NOVA ultra-processed food sub-groups reported in references in studies. Table S3: Quality assurance process.

Author Contributions

Conceptualization, M.L., P.B.; methodology, M.L., L.E., P.B., M.Z.; data curation, L.E., P.M.; writing—original draft preparation, L.E.; writing—review and editing, L.E., M.Z., P.B., P.M., M.L.; supervision, M.L., P.B.; project administration, M.L. All authors have read and agreed to the published version of the manuscript.

This research was supported by an Australian Research Council Discovery Project; DP190101323, ‘Reforming evidence synthesis and translation for food and nutrition policy’.

Conflicts of Interest

P.M. was co-author of an update of the NOVA classification [ 22 ], and has been co-author of published research using the classification, including one of the studies in this review [ 80 ], and stepped aside in the appraisal process of that article. All of the authors declare no conflict of interest.