Introduction
Bovine dairy foods provide a wide range of essential nutrients, including bioavailable amino acids, fats, calcium, phosphorus, and several vitamins (Haug et al., Reference Haug, Høstmark and Harstad2007). These nutrients contribute significantly to musculoskeletal growth and maintenance, and general well-being (Thorning et al., Reference Thorning, Raben, Tholstrup, Soedamah-Muthu, Givens and Astrup2016). A recent data modelling study demonstrated that milk (bovine) is the main contributing food item to the global nutrient availability of calcium, vitamin B2, lysine, and dietary fat, emphasising the role of dairy in the modern diet (Smith et al., Reference Smith, Fletcher, Hill and McNabb2022). Dairy foods are widely accessible, and a wide variety of food types are available, including milk, butter, cream, and fermented dairy foods such as cheese, yogurt, and kefir (Haug et al., Reference Haug, Høstmark and Harstad2007). Fermented dairy foods are produced through the desirable action of microorganisms (Marco et al., Reference Marco, Sanders, Gänzle, Arrieta, Cotter, De Vuyst, Hill, Holzapfel, Lebeer, Merenstein, Reid, Wolfe and Hutkins2021). This process can enhance the nutritional quality of dairy foods, potentially providing probiotics (live microorganisms), prebiotics (substrates for desirable gut microbes), and additional bioactive compounds (Hill et al., Reference Hill, Guarner, Reid, Gibson, Merenstein, Pot, Morelli, Canani, Flint, Salminen, Calder and Sanders2014; Davani-Davari et al., Reference Davani-Davari, Negahdaripour, Karimzadeh, Seifan, Mohkam, Masoumi, Berenjian and Ghasemi2019). These attributes have the potential to increase gut microbial diversity and improve aspects of digestive, cardiovascular, and metabolic health, thus, fermented dairy foods can provide health benefits beyond the scope of non-fermented dairy (Leeuwendaal et al., Reference Leeuwendaal, Stanton, O’Toole and Beresford2022).
Gastrointestinal complications are widely experienced, with a 2021 study showing approximately 40% of the global population experience at least one symptom associated with functional gastrointestinal disorders (FGIDs) (Sperber et al., Reference Sperber, Bangdiwala, Drossman, Ghoshal, Simren, Tack, Whitehead, Dumitrascu, Fang, Fukudo, Kellow, Okeke, Quigley, Schmulson, Whorwell, Archampong, Adibi, Andresen, Benninga, Bonaz, Bor, Fernandez, Choi, Corazziari, Francisconi, Hani, Lazenbnik, Lee, Mulak, Rahmann, Santos, Setshedi, Syam, Vanner, Wong, Lopez-Colombo, Costa, Dickman, Kanazawa, Keshteli, Khatun, Maleki, Poitras, Pratap, Stefanyuk, Thompson, Zeevenhooven and Palsson2021). FGIDs cover a range of gastrointestinal tract disorders, encompassing symptoms such as constipation, diarrhoea, bloating, and abdominal pain (Sperber et al., Reference Sperber, Bangdiwala, Drossman, Ghoshal, Simren, Tack, Whitehead, Dumitrascu, Fang, Fukudo, Kellow, Okeke, Quigley, Schmulson, Whorwell, Archampong, Adibi, Andresen, Benninga, Bonaz, Bor, Fernandez, Choi, Corazziari, Francisconi, Hani, Lazenbnik, Lee, Mulak, Rahmann, Santos, Setshedi, Syam, Vanner, Wong, Lopez-Colombo, Costa, Dickman, Kanazawa, Keshteli, Khatun, Maleki, Poitras, Pratap, Stefanyuk, Thompson, Zeevenhooven and Palsson2021). Irritable bowel syndrome (IBS) is a common FGID, with a 2021 study showing worldwide prevalence (as per Rome III criteria) is approximately 10% (Sperber et al., Reference Sperber, Bangdiwala, Drossman, Ghoshal, Simren, Tack, Whitehead, Dumitrascu, Fang, Fukudo, Kellow, Okeke, Quigley, Schmulson, Whorwell, Archampong, Adibi, Andresen, Benninga, Bonaz, Bor, Fernandez, Choi, Corazziari, Francisconi, Hani, Lazenbnik, Lee, Mulak, Rahmann, Santos, Setshedi, Syam, Vanner, Wong, Lopez-Colombo, Costa, Dickman, Kanazawa, Keshteli, Khatun, Maleki, Poitras, Pratap, Stefanyuk, Thompson, Zeevenhooven and Palsson2021). FGIDs and associated symptoms can severely affect quality of life and are burdensome on healthcare systems (Sperber et al., Reference Sperber, Bangdiwala, Drossman, Ghoshal, Simren, Tack, Whitehead, Dumitrascu, Fang, Fukudo, Kellow, Okeke, Quigley, Schmulson, Whorwell, Archampong, Adibi, Andresen, Benninga, Bonaz, Bor, Fernandez, Choi, Corazziari, Francisconi, Hani, Lazenbnik, Lee, Mulak, Rahmann, Santos, Setshedi, Syam, Vanner, Wong, Lopez-Colombo, Costa, Dickman, Kanazawa, Keshteli, Khatun, Maleki, Poitras, Pratap, Stefanyuk, Thompson, Zeevenhooven and Palsson2021). Gastrointestinal symptoms associated with FGIDs (e.g., diarrhoea, abdominal pain) are also experienced in clinically defined gastrointestinal diseases. Specifically, inflammatory bowel disease (IBD) is a chronic condition primarily affecting the lower gastrointestinal tract (Xavier and Podolsky, Reference Xavier and Podolsky2007). IBD encompasses both Crohn’s disease (CD) and ulcerative colitis (UC), which are characterised by chronic gastrointestinal inflammation (Xavier and Podolsky, Reference Xavier and Podolsky2007). UC is localised to the colon, while inflammation can occur anywhere along the GI tract in CD (Gohil and Carramusa, Reference Gohil and Carramusa2014). A 2017 review reported global IBD prevalence as over 6.8 million (95% UI 6.4–7.3) cases (Wang et al., Reference Wang, Li, Liu and Zhang2023). In 2020, global CD and UC prevalence were reported as 3 to 20 and 1 to 24 cases per 100,000, respectively (Feuerstein and Cheifetz, Reference Feuerstein and Cheifetz2017; Du and Ha, Reference Du and Ha2020). Gastrointestinal symptoms can be managed through medical strategies and lifestyle modifications in FGIDs and IBD, and thus, it is important to understand how dietary intake can influence the parameters of gastrointestinal health in these cohorts (Fikree and Byrne, Reference Fikree and Byrne2021).
The gut microbiome plays an important role in human health, wherein the combined microbial community, or specific components thereof, can, depending on the composition and/or function, benefit the host (Ogunrinola et al., Reference Ogunrinola, Oyewale, Oshamika and Olasehinde2020). The gut microbiome is involved in the maintenance of gastrointestinal health as well as aspects of immune, metabolic, and mental functions (Valdes et al., Reference Valdes, Walter, Segal and Spector2018). The gut microbial environment is influenced by a wide range of factors including age, lifestyle, and genetics (Ogunrinola et al., Reference Ogunrinola, Oyewale, Oshamika and Olasehinde2020). Dietary intake is a strong predictor of gut microbial composition, and therefore understanding gut microbial responses to foods is important (Hasan and Yang, Reference Hasan and Yang2019). Gut microbial dysbiosis is defined as perturbations to the structure of complex commensal communities in the gut (Petersen and Round, Reference Petersen and Round2014). Dysbiosis in the gut microbiota is characterised by reduced diversity, expansion of pathobionts (organisms that can be harmful under certain conditions), and loss of beneficial microbes (Petersen and Round, Reference Petersen and Round2014; Jochum and Stecher, Reference Jochum and Stecher2020).
While the pathogenesis of FGIDs and IBD is complex, gut microbial dysbiosis appears to be intertwined with such gastrointestinal diseases and disorders (Xavier and Podolsky, Reference Xavier and Podolsky2007; Holtmann et al., Reference Holtmann, Ford and Talley2016). In comparison to healthy individuals, FGID and IBD cohorts have been shown to have different gut microbial characteristics (Duan et al., Reference Duan, Zhu, Wang and Duan2019; Pittayanon et al., Reference Pittayanon, Lau, Leontiadis, Tse, Yuan, Surette and Moayyedi2020; Wang et al., Reference Wang, Alammar, Singh, Nanavati, Song, Chaudhary and Mullin2020; Clooney et al., Reference Clooney, Eckenberger, Laserna-Mendieta, Sexton, Bernstein, Vagianos, Sargent, Ryan, Moran, Sheehan, Sleator, Targownik, Bernstein, Shanahan and Claesson2021; Abdel-Rahman and Morgan, Reference Abdel-Rahman and Morgan2022; Kim et al., Reference Kim, Lee and Shim2023). A 2019 systematic review of 16 studies showed IBS patients had lower faecal bacterial alpha diversity, compared to healthy controls (Duan et al., Reference Duan, Zhu, Wang and Duan2019). A 2020 meta-analysis of 23 case–control studies showed IBS patients had lower faecal Lactobacillus and Bifidobacterium, and higher Escherichia coli, relative to healthy controls (Wang et al., Reference Wang, Alammar, Singh, Nanavati, Song, Chaudhary and Mullin2020). However, a more recent review of 16 studies focusing on longitudinal omics studies only, showed significant heterogeneity across gut microbial characteristics in IBS cohorts across studies, concluding that defining uniform gut microbial characteristics of an IBS-related gut microbiota is challenging (Ng et al., Reference Ng, Yau, Yaow, Chong, Chong, Teoh, Lim, Soh, Ng and Thumboo2023). However, while clearer characterisation of IBS-related gut microbial characteristics is needed, overall, gut microbial dysbiosis is prevalent in this cohort (Wang et al., Reference Wang, Alammar, Singh, Nanavati, Song, Chaudhary and Mullin2020; Kim et al., Reference Kim, Lee and Shim2023; Ng et al., Reference Ng, Yau, Yaow, Chong, Chong, Teoh, Lim, Soh, Ng and Thumboo2023). In IBD patients, a recent meta-analysis of 13 studies showed faecal bacterial alpha diversity was lower compared to healthy controls, and this was more pronounced in CD compared to UC (Abdel-Rahman and Morgan, Reference Abdel-Rahman and Morgan2022). Similarly to studies in IBS cohorts, studies comparing gut microbial taxa of healthy cohorts to IBD cohorts also had heterogenous methods and results, although Pittayanon et al. (Reference Pittayanon, Lau, Leontiadis, Tse, Yuan, Surette and Moayyedi2020) reported some notable differences in bacterial taxa between healthy, CD and UC cohorts, based on a review of 45 studies. Thus, overall, gut microbial dysbiosis is prevalent among FGID and IBD cohorts, but it should be noted that further studies are needed to determine distinctive gut microbial characteristics in such cohorts (Duan et al., Reference Duan, Zhu, Wang and Duan2019; Pittayanon et al., Reference Pittayanon, Lau, Leontiadis, Tse, Yuan, Surette and Moayyedi2020; Wang et al., Reference Wang, Alammar, Singh, Nanavati, Song, Chaudhary and Mullin2020; Clooney et al., Reference Clooney, Eckenberger, Laserna-Mendieta, Sexton, Bernstein, Vagianos, Sargent, Ryan, Moran, Sheehan, Sleator, Targownik, Bernstein, Shanahan and Claesson2021; Abdel-Rahman and Morgan, Reference Abdel-Rahman and Morgan2022; Kim et al., Reference Kim, Lee and Shim2023).
Dairy foods provide a range of nutrients, with certain fermented dairy foods also providing probiotics, prebiotics, and bioactive compounds (Haug et al., Reference Haug, Høstmark and Harstad2007). Therefore, dairy has the potential to influence the gut microbiome and gastrointestinal health, particularly in individuals with gastrointestinal complications. Identification of dairy foods that could improve common gastrointestinal symptoms and ameliorate gut microbial dysbiosis among FGID and IBD cohorts would be beneficial, as dairy consumption may be an accessible method of improving gastrointestinal health in such cohorts. This review aims to provide a comprehensive synthesis of intervention studies examining the effects of bovine dairy consumption on the gut microbiome and gastrointestinal health outcomes in human and animal (porcine and murine) cohorts with FGIDs, IBD, and associated symptoms.
Methods
Literature search
The protocol for this review was registered on PROSPERO (Registration ID: CRD42023392814) and follows PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines (Moher et al., Reference Moher, Liberati, Tetzlaff and Altman2010). A search strategy was developed based on population, intervention, comparator, and outcome (PICO) parameters. Inclusion criteria for the types of participants, interventions, controls, and outcomes are outlined in the PICO framework (Table 1). Populations included were human adults with gastrointestinal diseases or symptoms, and equivalent porcine and murine models. Gastrointestinal disease refers to IBD (UC and CD), FGIDs, and their associated gastrointestinal symptoms. Gastrointestinal symptoms refer to any symptoms related to the lower gastrointestinal tract, such as bloating, gas, diarrhoea, and constipation. The scope of this review focuses on gastrointestinal symptoms (e.g., diarrhoea, abdominal pain, bloating) and disease status in IBD. Many of the gastrointestinal symptoms associated with IBD are also experienced in FGIDs and therefore, these populations were also included to extend the search. Animal models were included as they allow more invasive methods of gastrointestinal analysis, which adds to the review by providing non-subjective measures of gastrointestinal health. Animal models were restricted to porcine and murine as they are considered physiologically relevant to humans, with respect to gastrointestinal research (Mizoguchi, Reference Mizoguchi2012; Gonzalez et al., Reference Gonzalez, Moeser and Blikslager2015). Interventions included dairy intake, which includes bovine dairy in any form (e.g., whole-milk, yogurt, whey). Comparators accepted were alternative dairy foods, dairy restriction, standard diets, or healthy cohorts. The outcomes included changes in gastrointestinal disease status, gastrointestinal symptoms, gut microbial characteristics (bacterial diversity and relative bacterial abundance), and faecal short-chain fatty acid (SCFA) concentrations. Inclusion criteria also included studies published in English, randomised-controlled dietary intervention trials, and controlled dietary intervention trials for human and animal studies, respectively. The search strategy was then used in three databases to identify relevant studies: PubMed, Embase, and Web of Science (from journal inception to December 2022). See supplementary material for the extended search strategy.
Table 1. PICO criteria
Abbreviations: PICO, population, intervention, control, outcome; SCFA, short-chain fatty acid.
* Refers to inflammatory bowel disease, functional gastrointestinal disorders, and their associated gastrointestinal symptoms.
Data collection and screening
Search results from each database were downloaded and exported into Endnote (Clarivate Analytics, PA, USA). References from each database were merged and duplicates were removed. Studies were then imported into Covidence for screening against selection criteria by title, abstract, and then full text (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia). Two authors (CNC, CG) independently completed the screening process to select the final studies meeting the inclusion criteria. Where discrepancies arose, a third author (ERG) was introduced to resolve disagreements.
Data extraction and analysis
A data extraction form was used to collect study data. Variables considered for extraction included study design, study setting, population characteristics (e.g., human IBD cohort, murine IBD model), test food (e.g., fermented milk, yogurt), control (e.g., PBS, healthy cohort), intervention dose (e.g., grams per day, grams per kg body weight), intervention duration, analysis methods (e.g., questionnaire, faecal metagenomic analysis) and results (e.g., gut microbial composition, diarrhoea frequency). One author completed the data extraction process independently (CNC) and the second author (CG) cross-checked the data extraction form.
Risk of bias assessment
The Cochrane ‘Risk of bias’ 2.0 tool was used to assess the risk of bias (RoB) in the human studies meeting inclusion criteria (Sterne et al., Reference Sterne, Savović, Page, Elbers, Blencowe, Boutron, Cates, Cheng, Corbett, Elridge, Emberson, Hernán, Hopewell, Hróbjartsson, Junqueira, Jüni, Kirkham, Lasserson, Li, McAleenan, Reeves, Shepperd, Shrier, Stewart, Tilling, White, Whiting and Higgins2019). This tool assesses RoB based on five domains: risk of bias arising from randomisation, deviations from the intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. For the animal studies meeting inclusion criteria, SYRCLE’s RoB tool was used to assess bias (Hooijmans et al., Reference Hooijmans, Rovers, de Vries, Leenaars, Ritskes-Hoitinga and Langendam2014). The tool assesses RoB based on five domains: risk of bias arising from selection, performance, detection, attrition, and reporting (Hooijmans et al., Reference Hooijmans, Rovers, de Vries, Leenaars, Ritskes-Hoitinga and Langendam2014). Risk of bias assessments were carried out by two reviewers (CNC, CG), and discrepancies were addressed through discussion.
The studies meeting inclusion criteria were grouped by population type (human or animal) to synthesise the results. Within population types, studies were further grouped by outcome (gut microbiome/SCFAs or gastrointestinal health parameters/symptoms). A narrative synthesis of the respective results from each group of studies was then conducted.
Results
The search strategy identified a total of 2646 de-duplicated studies. After the overall screening process, 26 studies were considered eligible for the review and were included in the data synthesis. See Figure 1 for the PRISMA flow diagram providing further details of the search results and screening process. Most studies (n = 2420) were excluded at the title screening phase. The primary reasons for exclusion at the title screening phase were test foods (e.g., non-bovine milks including sheep’s milk and human milk, probiotic strains alone, prebiotics alone), outcomes (e.g., effects on hypertension, adiposity, inflammatory response, colon cancer) or population groups which were out of scope (e.g., diabetic cohorts, lactose intolerant cohorts, paediatric cohorts, non-murine/porcine animal cohort). The main reason for exclusion at the full-text screening phase was due to test foods that were out of scope (n = 30), followed by outcomes (n = 18) and population types (n = 9) that failed to meet inclusion criteria (Figure 1).
Figure 1. PRISMA flow diagram.
Study details
Fifteen studies within human populations were identified (Supplementary Table S1), with a total of 1550 participants across the studies (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Studies were conducted from 2003 to 2021 with the majority taking place in Asia (n = 7) (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021) and Europe (n = 7) (Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019). Sample sizes ranged from 20 to 530 participants and ages ranged from 18 to 94 years (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Seven studies involved participants with FGIDs (diarrhoea, constipation, or general digestive symptoms) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020), five studies included IBS patients (Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021) and three studies included IBD patients (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019). Gastrointestinal symptoms and disease criteria included both clinical diagnosis (e.g., Rome criteria) and self-reported digestive health problems (e.g., self-reported mild constipation) (Supplementary Table S1) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021).
Eleven studies within animal populations were identified, with a total of 627 subjects reported across the studies (Supplementary Table S2) (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Studies were conducted between 2005 and 2022 with the majority, like the human studies reported above, taking place in Asia (n = 6) (Uchida and Mogami, Reference Uchida and Mogami2005; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022) and Europe (n = 3) (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020). Sample sizes ranged from 31 to 144 animal participants, aged between 1 to 18 weeks (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Seven studies included mice (Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022) and four studies included rats (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). Of these, ten standard murine species including Wistar rats or C57BL6 mice were used (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Gastrointestinal complications in these animals were chemically induced by the administration of dextran sodium sulphate (n = 6), trinitrobenzene sulfonic acid (n = 2), loperamide (n = 1) or antibiotics (n = 1) (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Alternatively, Veiga et al. (Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010) used TRUC mice species (TNFR1/p55−/−), a genetic model for UC (Supplementary Table S2).
Study design and methods
Table 2 outlines the study design and methods used in human studies. The majority (n = 11) of test foods were fermented milk (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021), three studies examined yogurt consumption (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003;Liu et al., Reference Liu, Xu, Han and Guo2015; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020), and Yilmaz et al. (Reference Yilmaz, Dolar and Ozpinar2019) investigated kefir consumption. Thus, all test foods included were fermented dairy foods. No study with a non-fermented dairy food (e.g., whole milk) met the study inclusion criteria. Of the fermented milk, seven studies investigated mixed-strain fermented milk, three studies investigated Lactobacillus casei strain Shirota fermented milk, and one study investigated Lactobacillus fermented milk (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Controls were mostly non-fermented or acidified milk (n = 9) (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019), or deprivation (i.e., meaning the removal of a dairy food from the diet) (n = 3) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019). Three studies provided nutritional information for test foods (n = 2 fermented milk, n = 1 yogurt), which is outlined in Supplementary Table S3 (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Liu et al., Reference Liu, Xu, Han and Guo2015). Fat contents ranged from <0.01 g to 2.91 g per 100 g, protein contents ranged from 1.25 to 2.73 g per 100 g and carbohydrate contents ranged from 11.75 to 18.00 g/100 g (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Liu et al., Reference Liu, Xu, Han and Guo2015). Li et al. (Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020) and Mokhtar et al. (Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021) included healthy cohorts free of gastrointestinal disease as control groups. Trial duration ranged from 1 week to 1 year and test food quantities consumed per day ranged from 65 mL to 500 mL (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Gastrointestinal disease status and symptoms were assessed through self-reported symptom questionnaires and disease-specific questionnaires (e.g., IBS Symptom Severity Scale) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). In addition to questionnaires, Ishikawa et al. (Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003) and Kato et al. (Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004) performed colonoscopies to determine gastrointestinal disease status. Gut microbiota was assessed using polymerase chain reaction (PCR) based techniques (n = 4) (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019), DNA or 16S rRNA sequencing (n = 2) (Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Liu et al., Reference Liu, Xu, Han and Guo2015) or culturing methods (n = 2) (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004). SCFAs were analysed by high-performance liquid chromatography (n = 3) (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010) gas chromatography (n = 2) (Liu et al., Reference Liu, Xu, Han and Guo2015; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020), or in vitro methods (n = 1) (Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014). Eleven of 15 studies specified their primary outcome (n = 3) (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019) or had just one outcome (n = 8) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015). Of these, most stated gastrointestinal symptoms (n = 8) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019) or gastrointestinal disease status (n = 2) (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004) as their primary outcome. Veiga et al. (Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014) stated changes in gut microbial characteristics as their primary outcome. Four studies with multiple outcomes did not specify a primary outcome (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021).
Table 2. Methods (human studies)
Abbreviations: AM, acidified milk; GC, gas chromatography; GID, gastrointestinal disease; GIS, gastrointestinal symptoms; GM, gut microbiota; GM FC, gut microbial functional capacity; ITT, intestinal transit time; LcS, Lactobacillus casei strain Shirota; LFM, Lactobacillus fermented milk; MSFM, mixed-strain fermented milk; NFM, Non-fermented milk; NGS, next-generation sequencing; PCR, polymerase chain reaction; RT-qPCR, reverse-transcription polymerase chain reaction; SCFAs, short-chain fatty acids; qPCR, quantitative polymerase chain reaction.
* Bold denotes primary research outcome.
** Placebo fermented milk prepared without live bacteria.
Table 3 outlines the study design and methods used in animal studies (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Test foods included fermented milk (n = 5) (Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022), yogurt (n = 2) (Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022), cheese (n = 1) (Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020), cheese whey protein (n = 1) (Sprong et al., Reference Sprong, Schonewille and van der Meer2010), milk whey culture (n = 1) (Uchida and Mogami, Reference Uchida and Mogami2005) and kefir (n = 1) (Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019). In line with the human studies, all test foods included were fermented dairy foods. No study with a non-fermented dairy food (e.g., whole milk) met the study inclusion criteria. Of the fermented milk, three studies investigated mixed-strain fermented milk, one study investigated fermented milk with L. casei strains and one study investigated fermented milk with Bacillus subtilis strains (Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). A range of controls were used including water or saline, phosphate-buffered saline (PBS), and acidified or non-fermented dairy among others (Table 3) (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Trial duration ranged from 5 days to 4 weeks in length, and test food quantities were provided based on g/kg body weight or measurements ranging from 300uL to 4 mL per day (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). A range of measures were used to assess gastrointestinal disease status, including histology, ulcer analysis, caecal analysis, colitis score, gut barrier function, and faecal analysis (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). GI symptoms were determined by disease activity analysis, stool analysis (e.g., bleeding, consistency), and intestinal transit time (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Gut microbiota was assessed using DNA or 16S rRNA sequencing (n = 5) (Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022) or PCR-based methods (n = 3) (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015), SCFA concentrations were measured by gas chromatography (n = 2) (Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017) or UPLC-MS/MS analysis (n = 1) (Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). Most studies (n = 9) had several outcomes and did not specify which was their primary outcome (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). Uchida and Mogami (Reference Uchida and Mogami2005) investigated one outcome, which was gastrointestinal disease status. Yang et al. (Reference Yang, Zhan, Wan, Li, Hu and Liu2022) investigated several outcomes and stated gut microbial compositional and diversity changes as their primary outcome.
Table 3. Methods (animal studies)
Abbreviations: AL, ad libitum; AM, acidified milk; B. subtilis; Bacillus subtilis strain B. subtilis JNFE0126; BB12, mixed-strain fermented milk containing Bifidobacterium animalis subsp. lactis BB12; BT, bifid triple viable capsules; DAI, disease activity index; GC, gas chromatography; GID, gastrointestinal disease; IT, intestinal transit; LB, lacidophilin tablets; L.cas, Lactobacillus casei; MSFM, mixed-strain fermented milk; NFM, non-fermented milk; PB, probiotic; PBS, phosphate buffer solution; PFM, pasteurised ordinary fermented milk; PPFM, pasteurised probiotic fermented milk (mixed-strain); RT-Thr/Cys, Threonine and Cysteine; SL, mixed-strain fermented milk containing S.thermophiles and Lactobacillus delbrueckii subsp. bulgaricus; qPCR, reverse-transcription polymerase chain reaction; UC, ulcerative colitis; UPLC-MS/MS, ultra-high-performance liquid chromatography-mass spectrometry; YS108R; mixed-strain fermented milk containing Bifidobacterium longum YS108R.
* Bold denotes primary research outcome.
** Six intervention arms, two probiotic strain yogurt and three probiotic strain yogurt each administered at 1, 2, and 4 mL per day.
Gut microbiota and SCFAs
Eight studies with human participants investigated changes in gut microbiota, reporting results as relative bacterial abundance at the order, family, genus, and species levels of the taxonomic hierarchy (Table 4) (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020). Gut microbiota alterations were also reported as changes in bacterial alpha diversity (Chao1 index) and bacterial counts by Matsumoto et al. (Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010) and Li et al. (Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020 ), respectively. These found increases in bacterial alpha diversity and total bacterial counts, relative to baseline measures within experimental groups (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020). At the genus level, Matsumoto et al. (Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010) and Li et al. (Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020) saw increases in Bifidobacterium, relative to baseline measures within their experimental groups. Both Liu et al. (Reference Liu, Xu, Han and Guo2015) and Yilmaz et al. (Reference Yilmaz, Dolar and Ozpinar2019) saw increases in Lactobacillus at the genus level, relative to control and within experimental group, respectively. Kato et al. (Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004) and Veiga et al. (Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014) identified increases in several Bifidobacterium species (Bifidobacterium breve, Bifidobacterium pseudocatenulatum, Bifidobacterium animalis), relative to baseline measures within experimental group and to control, respectively. Six studies investigated SCFA concentrations and reported results as total and/or individual SCFA concentrations (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Liu et al., Reference Liu, Xu, Han and Guo2015; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020). Kato et al. (Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004) and Matsumoto et al. (Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010) demonstrated increases in total SCFA concentrations within experimental group and relative to control. Most (n = 4) of the studies demonstrated increases in butyrate, propionate, and acetate concentrations compared within experimental groups (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014) or relative to controls (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Liu et al., Reference Liu, Xu, Han and Guo2015). However, both Ishikawa et al. (Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003) and Li et al. (Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020) reported decreases in butyrate concentrations, with Li et al. (Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020) also reporting decreases in acetate and propionate concentrations, relative to baseline concentrations within experimental groups.
Table 4. Gut microbiota and short-chain fatty acid results (human)
Note: All effects reported are statistically significant (p < 0.05).
Abbreviations: FGID, functional gastrointestinal disorder; FM, fermented milk; GID, gastrointestinal disease; IBD, inflammatory bowel disease; IBD, irritable bowel syndromeLcS FM, Lactobacillus casei strain Shirota fermented milk; MSFM, mixed-strain fermented milk; N, number of participants; NR, not reported; SCFAs, short-chain fatty acids.
a Effect within group (comparing pre-intervention and post-intervention).
b Effect between groups (comparing difference between intervention and control groups).
* Bold denotes primary research outcome.
** In high H2 producers only.
A total of eight studies analysed gut microbiota and SCFAs in animal subjects, reporting results as bacterial diversity (alpha) and relative abundance at the phylum, family, genus and species levels (Table 5) (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). The Shannon Index, Richness Index (operational taxonomic unit count), and Chao1 index were used to measure alpha diversity (Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). Bacterial alpha diversity consistently increased across four studies, relative to controls (Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). At the phylum level, Liu et al. (Reference Liu, Tang, Yu, Zhang and Li2017) and Yang et al. (Reference Yang, Zhan, Wan, Li, Hu and Liu2022) reported increased abundances of Bacteroidetes and decreased abundance of Firmicutes, relative to controls. At the family level, Veiga et al. (Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010) and Yan et al. (Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020) found that fermented milk decreased Enterobacteriaceae, relative to controls. Consistent increases among Lactobacillus at the genus level and increases among several Lactobacillus species, relative to controls, were identified in four studies (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). Fewer animal studies analysed SCFA concentrations compared to human studies, and the results were variable (Table 5). Both Veiga et al. and Feng et al. saw increases in butyrate in response to fermented milk consumption, whereas Liu et al. saw a decrease in butyrate in response to yogurt consumption, relative to controls (Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). Veiga et al. identified an increase in acetate in response to fermented milk, whereas Liu et al. saw a decrease in acetate in response to yogurt consumption, compared with their respective control groups (Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017).
Table 5. Gut microbiota and short-chain fatty acid results (animal)
Note: All effects reported are statistically significant (p < 0.05).
* Bold denotes primary research outcome.
a Effect within group (comparing pre-intervention and post-intervention).
b Effect between groups (comparing difference between intervention and control groups).
Abbreviations: AAD, antibiotic-associated diarrhoea; BB12, mixed-strain fermented milk containing Bifidobacterium animalis subsp. lactis BB12; B. subtilis; Bacillus subtilis strain B. subtilis JNFE0126; CWP, cheese whey protein; FC, functional constipation; FM, fermented milk; IBD, inflammatory bowel disease; L.cas, Lactobacillus casei; MSFM, mixed-strain fermented milk; N, number of participants; NR, not reported; OTU, operational taxonomic units; PB, probiotic; PFM, probiotic fermented milk; SL, mixed-strain fermented milk containing S.thermophiles and Lactobacillus delbrueckii subsp. bulgaricus; Thr/Cys, Threonine and Cysteine; UC, ulcerative colitis; Y2, yogurt with two probiotic strains; Y3 yogurt with three probiotic strains; YS108R; mixed-strain fermented milk containing Bifidobacterium longum subsp. longum YS108R.
Gastrointestinal health
A total of 14 studies investigated gastrointestinal symptoms and disease status response to dairy consumption in humans (Table 6) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Overall, improvements in gastrointestinal health, individual symptoms (e.g., bloating, flatulence), and defecation parameters in response to fermented milk, kefir, or yogurt consumption were reported (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Five studies found that fermented milk and yogurt intakes regulated defecation frequency, comparing intervention groups at baseline and post-intervention (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Liu et al., Reference Liu, Xu, Han and Guo2015; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021), whereas Beniwal et al. reported effects relative to control (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003). Three studies found that fermented milk and yogurt consumption improved stool consistency, comparing baseline and post-intervention measures within intervention groups (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Liu et al., Reference Liu, Xu, Han and Guo2015), or relative to control (Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014). Improvements in gastrointestinal symptoms and gut comfort were reported across five studies (Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Within these, Mokhtar et al. and Søndergaard et al. found that fermented milk improved gastrointestinal symptoms, comparing baseline and post-intervention symptoms within intervention groups (Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Improved gut comfort in response to fermented milk consumption was demonstrated, relative to control, by Le Néve et al., and within intervention group by Thijssen et al. (Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019). Yilmaz et al. found kefir consumption improved bloating, relative to control (Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019). Kato et al. and Gomi et al. saw improvements in self-reported disease status among UC and FGID patients, respectively, in response to fermented milk intake (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015). These effects were shown by comparing disease status between intervention and control groups by Kato et al., and within intervention group by Gomi et al. (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015). Additionally, Kato et al. saw significantly lower endoscopic activity index and histological scores from baseline to post-intervention within the experimental group (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004). No study reported a deterioration in gastrointestinal disease status or symptoms in response to dairy consumption.
Table 6. Gastrointestinal disease status and symptoms (human)
Note: All effects reported are statistically significant (p < 0.05).
* Bold denotes primary research outcome.
** At long-term follow-up only.
*** Groups stratified by H2 exhalation levels (high vs low) with reported effect identified in high H2 group only.
a Effect within group (comparing pre-intervention and post-intervention).
b Effect between groups (comparing difference between intervention and control groups).
Abbreviations: AAD, antibiotic-associated diarrhoea; AM, acidified milk; FD, functional diarrhoea; FGID, functional gastrointestinal disorder; FM, fermented milk; GID, gastrointestinal disease; GI, gastrointestinal; IBD, irritable bowel syndrome; IBS-C, IBS with constipation; ITT, intestinal transit time; LcS FM, Lactobacillus casei strain Shirota fermented milk; MSFM, mixed-strain fermented milk; N, number of participants; NR, not reported; UC, ulcerative colitis.
Ten studies analysed gastrointestinal symptoms and disease status in response to dairy intake in animal cohorts (Table 7) (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Four studies identified a reduction in disease activity index in response to dairy in the form of cheese (Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020) or fermented milk (Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022), relative to controls. Mucosal healing and reduction in colonic damage in response to fermented milk consumption were demonstrated in four studies, relative to controls (Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022) and within the intervention group (Uchida and Mogami, Reference Uchida and Mogami2005). Sevencan et al. saw a decreased colonic weight/length ratio in response to kefir intake (Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019). Yan et al. and Sprong et al. saw increased MUC2 expression and increased faecal mucin excretion in response to fermented milk and cheese whey protein, respectively, relative to controls (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020). Four studies overall saw reduced diarrhoea prevalence in response to fermented dairy intake (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Within these, three studies saw a reduction in diarrhoea relative to controls for fermented milk (Lee et al., Reference Lee, Yin, Griffey and Marco2015), kefir (Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019), and yogurt intakes (Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Sprong et al. saw that cheese whey protein reduced diarrhoea, comparing changes from baseline to post-intervention within the intervention group (Sprong et al., Reference Sprong, Schonewille and van der Meer2010). Sprong et al. and Lee et al. found cheese whey protein and fermented milk reduced faecal blood loss and rectal bleeding, respectively, relative to controls (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015). Additional findings for individual studies are reported in Table 7.
Table 7. Gastrointestinal disease status and symptoms (animal)
Note: All effects reported are statistically significant (p < 0.05).
* Bold denotes primary research outcome.
a Effect within group (comparing pre-intervention and post-intervention).
b Effect between groups (comparing difference between intervention and control groups).
Abbreviations: AAD, antibiotic-associated diarrhoea; BT, bifid triple viable capsules; BB12, mixed-strain fermented milk containing Bifidobacterium animalis subsp. lactis BB12; CWP, Cheese whey protein; DAI, disease activity index; FC, functional constipation; FM, fermented milk; GI, gastrointestinal; IBD, inflammatory bowel disease; ITT, intestinal transit time; LB, lacidophilin tablets; MSFM, mixed-strain fermented milk; N, number of participants; NR, not reported; PBS, phosphate buffered saline; PB, probiotic strains; PFM; Probiotic fermented milk; SL, mixed-strain fermented milk containing S.thermophiles and Lactobacillus delbrueckii subsp. bulgaricus; B. subtilis; Bacillus subtilis strain B. subtilis JNFE0126; Thr/Cys, Threonine and Cysteine; YS108R; mixed-strain fermented milk containing Bifidobacterium longum YS108R; UC, ulcerative colitis.
Risk of bias
Risk of bias in most studies with human participants was rated as ‘some concerns’ (n = 13) (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). The main sources of potential bias were deviations from intended interventions, measurement of the outcome, and selection of the reported result (Figure S1). Missing information required for thorough bias assessment also influenced these results. Tilley et al. and Le Neve et al. were considered to have low risk of bias in their study designs (Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019). Risk of bias in studies with animal participants were mostly rated as ‘some concerns’ (n = 9) (Uchida and Mogami, Reference Uchida and Mogami2005; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022), whereas Liu et al. and Rabah et al. were rated as ‘low with some concerns’ (Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020). The main sources of potential bias across the studies were within the allocation concealment, random housing, and blinding domains. This was primarily due to a lack of information provided on these study design parameters.
The scope of this review focused on significant findings and has not reported on findings where no change was identified, or where a non-significant change was identified. We recognise this is important and the data extraction file which includes non-significant and ‘no change’ findings, where reported, is provided in the Supplementary material.
Discussion
Considering the evidence presented in this review, it appears that overall, fermented dairy foods can positively influence aspects of gastrointestinal health and the gut microbiome in IBD and FGID cohorts. Gastrointestinal bacterial alpha diversity consistently increased in response to fermented dairy consumption in both human and animal studies (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). Gut microbial abundances can be reported at several levels within bacterial taxonomy (from phylum to sub-species levels), introducing limitations when comparing studies reporting results at different levels within the taxonomic hierarchy (Hugenholtz et al., Reference Hugenholtz, Chuvochina, Oren, Parks and Soo2021). However, a strong trend of increased relative Lactobacillus and Bifidobacterium abundances, and certain species within these genera, emerged (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010, Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Liu et al., Reference Liu, Xu, Han and Guo2015; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020). This was shown in studies using a range of fermented dairy test foods (fermented milks, kefir, yogurt, and cheese whey protein), providing supporting evidence that fermented dairy foods can positively influence gut microbial characteristics (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010, Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Liu et al., Reference Liu, Xu, Han and Guo2015; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020). Lactobacillus and Bifidobacterium are considered commensal gut genera, wherein increased relative abundances have been shown to benefit the host (O’Callaghan and van Sinderen, Reference O’Callaghan and van Sinderen2016; Hidalgo-Cantabrana et al., Reference Hidalgo-Cantabrana, Delgado, Ruiz, Ruas-Madiedo, Sánchez and Margolles2017; Dempsey and Corr, Reference Dempsey and Corr2022; Rastogi and Singh, Reference Rastogi and Singh2022). Thus, increasing the intake of fermented dairy foods may ultimately provide part of a solution in correcting apparent gut microbial dysbiosis in such gastrointestinal disease cohorts.
SCFAs are produced by gut microbes through colonic fermentation of fibre, and resistant starches, and certain SCFAs help to maintain gut and immune homeostasis (Tan et al., Reference Tan, McKenzie, Potamitis, Thorburn, Mackay and Macia2014). Butyrate, propionate, and acetate are beneficial SCFAs, and faecal concentrations of these SCFAs are reduced in gastrointestinal disease cohorts (Parada Venegas et al., Reference Parada Venegas, De la Fuente, Landskron, González, Quera, Dijkstra, Harmsen, Faber and Hermoso2019). Pooling human and animal data, most studies (n = 6) showed increases in total SCFAs, butyrate, propionate, and acetate in response to fermented dairy (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Veiga et al., Reference Veiga, Pons, Agrawal, Oozeer, Guyonnet, Brazeilles, Faurie, van Hylckama Vlieg, Houghton, Whorwell, Ehrlich and Kennedy2014; Liu et al., Reference Liu, Xu, Han and Guo2015; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). However, in contrast to this, three studies reported decreases in butyrate, two reported decreases in acetate and one study showed a decrease in propionate concentrations (Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020). Considering studies reporting findings relative to controls only, it is worth noting that four studies reported increases across SCFA concentrations (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Liu et al., Reference Liu, Xu, Han and Guo2015; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022), whereas just one study reported a decrease (Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017). Therefore, considering these studies only (which are more statistically robust), most studies (4 out of 5) showed fermented dairy intakes improved faecal SCFA profiles (Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Veiga et al., Reference Veiga, Gallini, Beal, Michaud, Delaney, DuBois, Khlebnikov, van Hylckama Vlieg, Punit, Glickman, Onderdonk, Glimcher and Garret2010; Bland and Altman, Reference Bland and Altman2011; Liu et al., Reference Liu, Xu, Han and Guo2015; Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). In addition, interpreting faecal SCFA concentrations in isolation is difficult, without considering fibre and resistant starch intakes, as gut microbes require these substrates to produce SCFAs (Tan et al., Reference Tan, McKenzie, Potamitis, Thorburn, Mackay and Macia2014). Therefore, dairy consumption alone cannot directly influence SCFA concentrations without fibre and resistant starch present in the colon, thus, this may explain some of the variability across findings for this outcome. It is also worth noting the heterogeneity across different methods used to analyse SCFAs (e.g., HPLC, gas chromatography, UPLC-MS/MS, in vitro analysis), which may also explain some of the variability in the results.
In human studies, gastrointestinal health parameters were primarily assessed through self-reported measures, wherein a strong trend of improved symptoms in response to fermented dairy consumption emerged (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Ishikawa et al., Reference Ishikawa, Akedo, Umesaki, Tanaka, Imaoka and Otani2003; Kato et al., Reference Kato, Mizuno, Umesaki, Ishii, Sugitani, Imaoka, Otsuka, Hasunuma, Kurihara, Iwasaki and Arakawa2004; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011; Thijssen et al., Reference Thijssen, Jonkers, Vankerckhoven, Goossens, Winkens, Clemens and Masclee2011; Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Gomi et al., Reference Gomi, Iino, Nonaka, Miyazaki and Ishikawa2015; Liu et al., Reference Liu, Xu, Han and Guo2015; Le Nevé et al., Reference Le Nevé, Derrien, Tap, Brazeilles, Portier, Guyonnet, Ohman, Störsrud, Törnblom and Simrén2019; Yilmaz et al., Reference Yilmaz, Dolar and Ozpinar2019; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). Most notably, defecation parameters (including defecation frequency, stool consistency and intestinal transit time) were consistently improved (Beniwal et al., Reference Beniwal, Arena, Thomas, Narla, Imperiale, Chaudhry and Ahmad2003; Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Liu et al., Reference Liu, Xu, Han and Guo2015; Li et al., Reference Li, Liu, Tang, Zhang, Luo, Zhang and Yang2020; Mokhtar et al., Reference Mokhtar, Jaafar, Alfian, Rathi, Rani and Ali2021). In agreement with this, animal models also demonstrated improved defecation parameters in response to fermented dairy intake, based on faecal analysis methods (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Lee et al., Reference Lee, Yin, Griffey and Marco2015; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Yang et al., Reference Yang, Zhan, Wan, Li, Hu and Liu2022). Gastrointestinal disorders significantly affect the quality of life, and patients experience considerable discomfort and distress associated with their symptoms (Hahn et al., Reference Hahn, Yan and Strassels1999). Based on these findings, fermented dairy consumption may be a useful tool to alleviate some of the gastrointestinal discomfort experienced by IBD and FGID patients. While animal studies cannot capture self-reported gastrointestinal parameters, they do facilitate more invasive measurements of gastrointestinal health, such as colonic histological analysis. Colonic histology allows in-depth analysis of the colonic environment, and is particularly important in relation to IBD in clinical practice (Kellermann and Riis, Reference Kellermann and Riis2021). In the animal studies presented, dairy interventions improved clinical gastrointestinal parameters, with notable improvements in colonic mucosal healing and reduced colonic damage, measured via colonic histology (Uchida and Mogami, Reference Uchida and Mogami2005; Sevencan et al., Reference Sevencan, Isler, Kapucuoglu, Senol, Kayhan, Kiztanir and Kockar2019; Yan et al., Reference Yan, Yang, Ross, Stanton, Zhang, Zhao and Chen2020; Zhang et al., Reference Zhang, Tong, Lyu, Wang, Wang and Yang2020; Feng et al., Reference Feng, Zhang, Zhang, Li, He, Kwok and Zhang2022). In line with these findings, one human study showed lower endoscopic activity index and histological score in response to fermented milk intake (Søndergaard et al., Reference Søndergaard, Olsson, Ohlson, Svensson, Bytzer and Ekesbo2011). Compiling mostly self-reported findings in human cohorts with colonic histological findings in animal cohorts, it appears that fermented dairy can improve a range of gastrointestinal health parameters in IBD and FGID patients.
The improvement in gastrointestinal symptom parameters seen in humans may be attributed to the mucosal healing and reduction in colonic damage demonstrated in comparable animal studies, but this association requires further research. Future human studies should investigate gastrointestinal health status via non-subjective methods. Examples of this may include gut barrier function analysis and colonic histology analysis (Grootjans et al., Reference Grootjans, Thuijls, Verdam, Derikx, Lenaerts and Buurman2010; Rosenberg et al., Reference Rosenberg, Nanda, Zenlea, Gifford, Lawlor, Falchuk, Wolf, Chiefetz, Goldsmith and Moss2013; Liu et al., Reference Liu, Ajami, El-Serag, Hair, Graham, White, Chen, Wang, Plew, Kramer, Cole, Hernaez, Hou, Husain, Jabrink-Sehgal, Kanwal, Ketwaroo, Natarajan, Shah, Velez, Mallepally, Petrosino and Jiao2019). Intestinal barrier function can be assessed by non-invasive methods, e.g., serum intestinal fatty acid binding protein concentration (Grootjans et al., Reference Grootjans, Thuijls, Verdam, Derikx, Lenaerts and Buurman2010). Although performing colonic biopsies is invasive, IBD patients undergo routine colonoscopies wherein biopsies are taken (Kellermann and Riis, Reference Kellermann and Riis2021). Thus, there is an opportunity to further explore this area through conducting colonic histological analysis in humans while adhering to ethics in clinical research settings, as demonstrated in other studies (Rosenberg et al., Reference Rosenberg, Nanda, Zenlea, Gifford, Lawlor, Falchuk, Wolf, Chiefetz, Goldsmith and Moss2013; Liu et al., Reference Liu, Ajami, El-Serag, Hair, Graham, White, Chen, Wang, Plew, Kramer, Cole, Hernaez, Hou, Husain, Jabrink-Sehgal, Kanwal, Ketwaroo, Natarajan, Shah, Velez, Mallepally, Petrosino and Jiao2019). This type of analysis would add to the body of human evidence in this area, which currently relies mostly on self-reported gastrointestinal health measures, which are subjective, and have potential inherent bias (Althubaiti, Reference Althubaiti2016).
While this review highlights improvements in gastrointestinal health in response to fermented dairy, there are several limitations and points to consider when interpreting the results. Study design parameters including test food types and their quantities, controls, analysis methods and reporting of results were widely variable across studies. This review pools evidence from the studies, irrespective of this heterogeneity, therefore, these findings should be interpreted with caution. Dairy test foods included in this review are largely variable, in terms of their physical structures (e.g., yogurt is gel/viscoelastic, milk is liquid) and their nutritional profiles (e.g., proteins content, whey/casein ratio, fat content, fat structure) (Thorning et al., Reference Thorning, Bertram, Bonjour, de Groot, Dupont, Feeney, Ipsen, Lecerf, Mackie, McKinley, Michalski, Rémond, Risérus, Soedamah-Muthu, Tholstrup, Weaver, Astrup and Givens2017). As noted by Thorning et al., these aspects of variability across dairy foods can influence the biological responses associated with consumption (Thorning et al., Reference Thorning, Bertram, Bonjour, de Groot, Dupont, Feeney, Ipsen, Lecerf, Mackie, McKinley, Michalski, Rémond, Risérus, Soedamah-Muthu, Tholstrup, Weaver, Astrup and Givens2017). For the purpose of this review, we analysed dairy foods as a whole, without delving into the apparent variability due to physical structures and nutritional matrices within and between the dairy foods. Future work in this area is needed exploring the role of dairy food matrix variables. In addition, there was large variability in outcome reporting methods within and between studies. Studies reported findings as differences within experimental groups (baseline vs post-intervention), or as differences between experimental and control groups. Reporting findings relative to control provides more statistically robust evidence, and future studies should aim to report results in this way (Bland and Altman, Reference Bland and Altman2011). Lastly, as noted in the results, half of the studies overall (n = 13) investigated several outcomes without specifying a primary research outcome, and several of the findings reported across the studies were secondary outcomes. Primary and secondary outcome findings were included in the data synthesis with equal importance, so this should be considered when interpreting the results. While this review provides a comprehensive overview of the research to date, it is important to note the significant heterogeneity across study design parameters, the study quality and validity of results reported.
Another limitation is the lack of nutritional information provided for test foods. Only three studies provided detailed nutritional information for test foods (Supplementary Table S3) (Matsumoto et al., Reference Matsumoto, Takada, Shimizu, Moriyama, Kawakami, Hirano, Kajimoto and Nomoto2010; Tilley et al., Reference Tilley, Keppens, Kushiro, Takada, Sakai, Vaneechoutte and Degeest2014; Liu et al., Reference Liu, Xu, Han and Guo2015). When foods are digested, their nutritional components (e.g., macronutrients, polyphenols, probiotics) and endogenous metabolites interact with the gastrointestinal environment, wherein food nutritional properties can influence the gut microbiome and the gastrointestinal environment in different ways (Zhang, Reference Zhang2022). Due to the lack of information available, it was not feasible to delve into the nutritional properties of test foods across different studies, to further understand their impact on gut microbiota and gastrointestinal health. Therefore, future studies should include comprehensive nutritional information of test foods to allow deeper understanding of how dairy nutritional components can influence gastrointestinal parameters. Further, very few human studies considered dietary intake as a potential cofounder in their analysis of changes in gut microbial characteristics or gastrointestinal health. Animal studies allow strict control over dietary intake (nutritional intake beyond test foods), and monitoring and controlling for this in human gastrointestinal research is a major challenge (Staudacher et al., Reference Staudacher, Yao, Chey and Whelan2022). In line with specific nutritional components within test foods, overall dietary intake (beyond test foods) is a strong predictor of gut microbial composition and gastrointestinal health, and should be considered and controlled for accordingly (Hasan and Yang, Reference Hasan and Yang2019; Staudacher et al., Reference Staudacher, Yao, Chey and Whelan2022). While most studies instructed that participants maintained their habitual diet and refrained from dairy, fermented dairy and/or probiotics, just one study out of the 15 human studies assessed dietary intake and considered it as a potential cofounder in their analysis (monitored macronutrient, micronutrient and fibre intakes at baseline and post-intervention) (Marteau et al., Reference Marteau, Guyonnet, De Micheaux and Gelu2013). Further information on controlling for dietary intake as a potential cofounder can be found in the supplementary material (data extraction form). Although it is challenging to account for dietary intake variability in free-living human cohorts, future studies should consider assessing dietary intake and specific relevant dietary components (e.g., fibre intake) in their analysis of gut microbiota alterations and changes in gastrointestinal parameters in dietary intervention studies.
In relation to test foods, although this review aimed to explore dairy foods, including both fermented and non-fermented, all test foods included in the data synthesis have a fermented aspect. Therefore, many of the test foods contained probiotics (e.g., fermented milk with probiotics). This considered, it could be argued that the positive gastrointestinal effects shown for these foods are influenced by the probiotics (e.g., Bifidobacterium strains in fermented milk), rather than the dairy foods themselves. However, while evidence shows that probiotic bacteria exert positive gastrointestinal effects, it is also important to consider the probiotic delivery matrix (Parker et al., Reference Parker, Roy, D’Adamo and Wieland2018). As shown by Liu et al., administering identical probiotic strains in different matrices (yogurt versus tablet) elicited contrasting effects, wherein gastrointestinal improvements were observed only in the yogurt group (Liu et al., Reference Liu, Tang, Yu, Zhang and Li2017). Similarly, Lee et al. also showed the benefits of L.cas BL23 were dependent on the delivery matrix, wherein significant benefits were only shown in the dairy delivery matrix (milk), compared with administration in PBS (Lee et al., Reference Lee, Yin, Griffey and Marco2015). This suggests an additive effect of the matrix in addition to the probiotic content. Further, beyond these studies, sufficient evidence shows that dairy foods, particularly milk and yogurt, are excellent matrices for probiotic delivery, in relation to preserving probiotic viability (Morelli et al., Reference Morelli, Elli, Lucido, Biolchi and Sagheddu2018; Rodrigues et al., Reference Rodrigues, Silva, Simabuco, Venema and Antunes2019). Although most test foods in this review include probiotics, the dairy delivery matrix is an additional consideration that warrants further investigation. Just two studies in this review explored the role of the dairy matrix in probiotic administration, therefore, for the majority of studies presented here, it is difficult to differentiate the effects of the dairy matrix from the probiotics themselves.
Additionally, the studies presented here highlight the effects of a range of fermented dairy food types containing probiotics on gastrointestinal health. Different dairy foods (e.g., yogurt, fermented milk, cheese) have heterogenous structural and nutritional properties, and previous studies show that the dairy matrix plays a role in the biological response to their consumption (Thorning et al., Reference Thorning, Bertram, Bonjour, de Groot, Dupont, Feeney, Ipsen, Lecerf, Mackie, McKinley, Michalski, Rémond, Risérus, Soedamah-Muthu, Tholstrup, Weaver, Astrup and Givens2017; Aguilera, Reference Aguilera2019). Thus, comparing the matrix effect across different dairy food types (e.g., fermented milk, yogurt) with respect to probiotic delivery also warrants further investigation, with respect to gastrointestinal health in IBD and FGID cohorts. There is opportunity to examine the effects of probiotics administered in dairy foods vs control, and then to also compare the dairy delivery matrix across different dairy foods.
While fermented foods and their nutritional compounds are shown to exert positive effects on gut microbial characteristics, it should be noted that current technologies may not be sensitive enough to detect small microbiota alterations (Mousa et al., Reference Mousa, Chehadeh and Husband2022; Ng et al., Reference Ng, Lim, Yaow, Ng, Thumboo and Liew2023). This considered, although foods may not significantly alter gut microbial characteristics, they can still confer benefits to the host through metabolites produced or through interaction with the host’s immune system, which are difficult to capture (Ng et al., Reference Ng, Lim, Yaow, Ng, Thumboo and Liew2023). Further advancements in gut microbiome analysis methods will allow a deeper understanding of the effects of fermented dairy foods on the gut microbial ecosystem, beyond the scope of relative bacterial abundance and diversity (Mousa et al., Reference Mousa, Chehadeh and Husband2022). In addition to this, assessing changes in gut microbial composition in conjunction with changes in gastrointestinal health (e.g., symptoms) is also important to capture the effects of fermented dairy foods on the gut microbiota, and the subsequent gastrointestinal health benefits which may be associated with gut microbial alterations.
There are also opportunities for future research to explore a wider range of dairy food types. Test foods in human studies were restricted to fermented milks, kefir, and yogurt only, whereas animal studies explored a wider range of test foods providing promising results. Notably, cheese and cheese whey protein both increased relative abundances of Bifidobacterium and Lactobacillus while also improving clinical gastrointestinal parameters (Sprong et al., Reference Sprong, Schonewille and van der Meer2010; Rabah et al., Reference Rabah, Carmo, Carvalho, Cordeiro, da Silva, Oliveira, Lemos, Cara, Faria, Garric, Harel-Oger, Le, Azevedo, Bougen and Jan2020). These findings provide a rationale to explore a wider range of dairy foods in this context in humans. Alongside yogurt, cheese is the most commonly consumed form of fermented dairy (González et al., Reference González, Fernández-Navarro, Arboleya, De Los Reyes-Gavilán, Salazar and Gueimonde2019). Thus, from a practical perspective, cheese is an important food to consider moving forward in the exploration of fermented dairy on the gut microbiome and gastrointestinal health. In addition, a deeper understanding of how fermented dairy foods influence the gut microbiome and gastrointestinal health is needed. The specific food components and the mechanisms in which they influence beneficial changes in the gut microbiome and gut symptoms warrants further investigation. Future work should expand test foods, while also considering the dairy food components influencing gastrointestinal effects, and the mechanisms by which they act.
To conclude, this review provides a basis of evidence showing fermented bovine dairy foods can improve gut microbial dysbiosis and gastrointestinal parameters in IBD and FGID cohorts. IBD and FGIDs severely affect quality of life, and while symptoms can be managed through clinical and dietary strategies, there is no cure (Zuo and Ng, Reference Zuo and Ng2018). Thus, dietary management is highly important in such cohorts. Increasing fermented dairy consumption is a practical dietary strategy that may aid the management of gastrointestinal complications. However, further well-designed large-scale human studies considering both clinical and self-reported gastrointestinal health measures and explore a wider range of test foods are now needed to extend and strengthen the existing evidence. It is worth noting that the only European Food Safety Authority approved health claim associated with fermented dairy is in relation to yogurt: ‘live yogurt cultures can improve digestion of yogurt lactose in individuals with lactose maldigestion’ (EFSA Panel on Dietetic Products N, Allergies, 2010). Future studies in this area may inform potential health claims associated with fermented dairy foods and gastrointestinal health, in relation to the gut microbiome and gastrointestinal symptoms.
Supplementary material
The supplementary material for this article can be found at http://doi.org/10.1017/gmb.2024.2.
Acknowledgements
We thank the Food for Health Ireland gut health working group for collaboration on this paper.
Disclosure statement
The authors declare none.
Author contribution
Writing – review & editing: C.E.L., D.C.S., E.R.G., E.L.F., G.A.D., N.N., P.D.C., R.S., C.N.C.; Data curation: C.G., C.N.C.; Formal analysis: C.G., C.N.C.; Investigation: C.G., C.N.C.; Validation: C.G., C.N.C.; Supervision: D.C.S., E.R.G., E.L.F.; Conceptualization: E.R.G., E.L.F., C.N.C.; Funding acquisition: E.R.G.; Project administration: E.R.G.; Resources: E.R.G.; Methodology: C.N.C.; Visualization: C.N.C.; Writing – original draft: C.N.C.
Funding
The work was funded by Food for Health Ireland (FHI). The FHI-3 project was funded by Enterprise Ireland (Dublin, Ireland) and industry [grant number: TC/2018/0025].
Research transparency and reproducibility
The data extraction form, which includes extensive study details of the papers included in this review, is provided as Supplementary material and can be made publicly available.
Open access
