research paper on composition of milk

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Compositional and functional properties of milk and dairy products derived from cows fed pasture or concentrate-based diets

Affiliations.

• 1 Food Chemistry and Technology, Teagasc Food Research Centre, Cork, Ireland.
• 2 School of Food and Nutritional Sciences, University College Cork, Cork, Ireland.
• PMID: 33949109
• DOI: 10.1111/1541-4337.12751

Worldwide milk production is predominantly founded on indoor, high-concentrate feeding systems, whereas pasture-based feeding systems are most common in New Zealand and Ireland but have received greater attention recently in countries utilizing conventional systems. Consumer interest in 'pasture-fed' dairy products has also increased, arising from environmental, ethical, and nutritional concerns. A substantial body of research exists describing the effect of different feeding strategies on the composition of milk, with several recent studies focusing on the comparison of pasture- and concentrate-based feeding regimes. Significant variation is typically observed in the gross composition of milk produced from different supplemental feeds, but various changes in the discrete composition of macromolecular components in milk have also been associated with dietary influence, particularly in relation to the fatty acid profile. Changes in milk composition have also been shown to have implications for milk and dairy product processability, functionality and sensory properties. Methods to determine the traceability of dairy products or verify marketing claims such as 'pasture-fed' have also been established, based on compositional variation due to diet. This review explores the effects of feed types on milk composition and quality, along with the ultimate effect of diet-induced changes on milk and dairy product functionality, with particular emphasis placed on pasture- and concentrate-based feeding systems.

Keywords: Bovine diet; concentrate; milk composition; pasture; processing.

© 2021 The Authors. Comprehensive Reviews in Food Science and Food Safety published by Wiley Periodicals LLC on behalf of Institute of Food Technologists.

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A 100-Year Review: Progress on the chemistry of milk and its components

• John A. Lucey John A. Lucey Correspondence Corresponding author Contact Affiliations Center for Dairy Research, University of Wisconsin–Madison, Madison 53706 Search for articles by this author
• Don Otter Don Otter Affiliations Center for Dairy Research, University of Wisconsin–Madison, Madison 53706 Search for articles by this author
• David S. Horne David S. Horne Affiliations Center for Dairy Research, University of Wisconsin–Madison, Madison 53706 Search for articles by this author
• milk protein
• functionality
• dairy chemistry

INTRODUCTION

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A CENTURY OF PROGRESS IN DAIRY CHEMISTRY

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SUMMARY AND FUTURE DIRECTIONS

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Article info

Publication history.

This review is part of a special issue of the Journal of Dairy Science commissioned to celebrate 100 years of publishing (1917–2017).

Identification

DOI: https://doi.org/10.3168/jds.2017-13250

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Production, composition and nutritional properties of organic milk: a critical review.

Graphical Abstract

1. Introduction

2. an introduction to organic milk production, organic milk production regulations, 3. milk production systems, 3.1. conventional systems, 3.1.1. traditional system, 3.1.2. intensive system, 3.2. organic system.

4. Impact of Production Systems on Farm Performance and Raw Milk Composition

4.1. milk yield, 4.2. udder health and somatic cell count (scc), 4.3. microbiological quality, 4.4. mastitis, 4.5. volatile organic compounds, 4.6. protein, 4.7. vitamins, 4.8. carbohydrates, 4.10. minerals and heavy metals.

5. Perceived Health Benefits of Organic and Conventional Milk

6. global market for organic milk products, 7. future challenges and perspectives, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Linehan, K.; Patangia, D.V.; Ross, R.P.; Stanton, C. Production, Composition and Nutritional Properties of Organic Milk: A Critical Review. Foods 2024 , 13 , 550. https://doi.org/10.3390/foods13040550

Linehan K, Patangia DV, Ross RP, Stanton C. Production, Composition and Nutritional Properties of Organic Milk: A Critical Review. Foods . 2024; 13(4):550. https://doi.org/10.3390/foods13040550

Linehan, Kevin, Dhrati V. Patangia, Reynolds Paul Ross, and Catherine Stanton. 2024. "Production, Composition and Nutritional Properties of Organic Milk: A Critical Review" Foods 13, no. 4: 550. https://doi.org/10.3390/foods13040550

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Composition of Milk

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• Robert Jenness  

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Milk is secreted by all species of mammals to supply nutrition and immunological protection to the young. It performs these functions with a large array of distinctive compounds. Interspecies differences in the quantitative composition of milk (Jenness and Sloan 1970) probably reflect differences in the metabolic processes of the lactating mother and in the nutritive requirements of the suckling young.

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Production and Utilization of Milk

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Jenness, R. (1988). Composition of Milk. In: Wong, N.P., Jenness, R., Keeney, M., Marth, E.H. (eds) Fundamentals of Dairy Chemistry. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-7050-9_1

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Composition of Milk of Different Farm Animal: A Review

American Journal of Pure and Applied Biosciences.

17 Pages Posted: 16 Mar 2021 Last revised: 27 May 2021

Hassen Yusuf Bekere

Haramaya University

Mohammedsham Husen

Haramaya university,college of veterinary medicine.; Tulo offices of livestock and fisheries development

Date Written: July 7, 2020

Milk is a key contributor to improving nutrition and food security particularly in developing countries. Milk composition of mammalian species varies widely with reference to genetic, physiological, nutritional factors and environmental conditions. It is necessary to know the maximum value addition in the dairy food chain as the nutrient, to not only determine the dietary value of milk for human consumption, but also help to define market strategy for various classes of consumer like; growing children, nursing mothers, young people involved in hard jobs or elderly people. The use of cow, camel, goat, buffalo milk gained worldwide acceptance and importance throughout the world, while consumption of mare milk popular only in Western Europe. Goat milk prescribed by many doctors for children, who are sensitive to cow milk, and is an alternative for people who are allergic to cow milk. Goat milk is very useful for people suffering from problems such as acidity, eczema, asthma, migraine, colitis, stomach ulcer, digestive disorder, liver and gallbladder diseases and stress-related symptoms such as insomnia, constipation and neurotic indigestion. For some people with digestive difficulties, goat’s milk can be easily digested. Camel milk is an important source of proteins for the people living in the arid lands of the world camel milk is considered to have anti-cancer, hypo-allergenic and anti- diabetic properties. Buffalo milk is a natural product that can be consumed like any other milk. It is one of the richest products from a compositional point of view and characterized by higher fat, total solids, proteins, caseins, and lactose and ash contents than cow, goat, camel and human milk. The major constituents of buffalo milk are higher in concentration than that of human, cow, goat and camel milk with respect to nutritional values. In addition to its advantage as a rich source of nutrients, a recent study indicated that subjects with cow milk allergy are able to tolerate buffalo milk. Therefore, this review is aimed to explore composition of milk of farm animals and to make awareness on availability of different sources of milks.

Keywords: Milk Composition, Farm Animal, Nutrition of Milk, Enzymes in Milk

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• Published: 26 June 2024

Exploring the impact of maternal factors and dietary habits on human milk oligosaccharide composition in early breastfeeding among Mexican women

• Víctor H. Urrutia-Baca 1 ,
• Janet A. Gutiérrez-Uribe 1 ,
• Perla A. Ramos-Parra 2 ,
• Astrid Domínguez-Uscanga 1 ,
• Nora A. Rodriguez-Gutierrez 3 ,
• Karla L. Chavez-Caraza 3 ,
• Ilen Martinez-Cano 4 ,
• Alicia S. Padilla-Garza 3 ,
• Elias G. Ruiz-Villarreal 4 ,
• Francisca Espiricueta-Candelaria 1 &
• Cristina Chuck-Hernández 1  

Scientific Reports volume  14 , Article number:  14685 ( 2024 ) Cite this article

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Human milk oligosaccharides (HMOs) promote adequate intestinal microbiota development and favor the immune system's maturation and cognitive development. In addition to non-modifiable factors, HMOs composition can be influenced by other factors like body mass index and eating habits, but the reports are discrepant. The aim of this work was to describe the correlation between maternal factors and HMOs concentration in colostrum in 70 women from northeastern Mexico categorized into women with normal weight and women with overweight or obesity. The absolute concentration of six HMOs were significantly lower in women with overweight or obesity compared to women with normal weight (LNFPI p = 0.0021, 2’-FL p = 0.0304, LNT p = 0.0492, LNnT p = 0.00026, 3’-SL p = 0.0476, 6’-SL p = 0.00041). Another main finding was that the frequency of consumption of food groups such as vegetables, fruits and meats was positively correlated to specific HMOs (Poblano chili and 2’-FL; r s  = 0.702, p = 0.0012; Orange or tangerine and 3-FL; r s  = 0.428, p = 0.0022; Chicken and 2'-FL; r s  = 0.615, p = 0.0039). This study contributes to the elucidation of how maternal factors influence the composition of HMOs and opens possibilities for future research aimed at mitigating overweight or obesity, consequently improving the quality of human milk.

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Introduction.

Health authorities around the world have recognized the nutritional, physiological, and protective benefits of breastfeeding, such as the tendency to reduce the risk of type 2 diabetes, obesity, allergies, celiac disease, necrotizing enterocolitis (NEC), gastrointestinal tract infections, and some cancers. HMOs are multifunctional glycans naturally present in human milk and are particularly interesting for their quantity and structural diversity 1 . So far, more than 200 individual molecular species of HMOs and more than 100 structures have been reported 2 . HMOs contain glucose (Glc), galactose (Gal), N -acetylglucosamine (GlcNac), fucose (Fuc), and N -acetylneuraminic acid (Neu5Ac) and are formed by a reducing lactose core that can be extended enzymatically by lacto- N -biose (Galβ-1,3-GlcNAc, type 1 LacNAc) or N-acetyllactosamine (Gal-β1,4-GlcNAc, type 2 LacNAc) motifs. These structures can be further decorated by the addition of Fuc residues in α1,2-, α1,3-, and α1,4-linkages or Neu5Ac residues in α2,3- and α2,6-linkages.

Since oligosaccharide chains can be either fucosylated or sialylated, they are usually classified into three main categories: neutral non-fucosylated, neutral fucosylated, and HMOs containing sialic acid. HMOs promote the colonization of beneficial microbes in the infant's gut, such as beneficial Bifidobacterium species, preventing the growth of other harmful bacteria and contributing to the development of the immune system 3 . HMOs have been shown to have anti-bacterial, anti-viral, and anti-inflammatory effects and have proven beneficial toward the protection from NEC 4 , 5 . The benefits of HMOs may extend beyond infancy to the development of cognitive functions, making them the focus of intense current scientific research.

In addition to genetic factors, environmental factors such as geographical location, season of delivery, and maternal diet and maternal characteristics such as age, ethnicity, parity, mode of delivery, and maternal nutritional status affects HMOs concentration and composition 6 , 7 , 8 , 9 . Body mass index (BMI) at the beginning of pregnancy has been related to differences in the concentration of HMOs. Some studies have reported that overweight and obesity may positively or negatively correlate with the concentration of specific oligosaccharides 7 , 8 , 10 , 11 , 12 . McGuire et al. 7 , in 410 breastfeeding women from an international cohort (Spanish, Swedish, Peruvian, North American, Ethiopian, Gambian, Ghanaian, and Kenyan) found that maternal weight and BMI were positively associated with 2′-FL and fucosyl-lacto- N -hexaose (FLNH); maternal weight was positively correlated with lacto- N -fucopentaose III (LNFP III) and difucosyl-lacto- N -tetraose (DFLNT). Conversely, maternal weight and BMI were inversely correlated with LNnT and disialyl-lacto-N-tetraose (DSLNT). Azad et al. 8 , observed that lacto- N -hexaose (LNH) was lower in women with overweight compared to women with normal weight while DFLNT was higher in women with obesity. Isganaitis et al. 12 , found that three HMOs along with other seven metabolites concentrations were significantly different in the milk of one month infant mothers from Oklahoma (USA) with overweight or obesity compared to normal weight at one month after delivery; particularly Lacto- N -fucopentaose-I (LNFP-I) and 2’-FL contents were reduced by 62% and 38%, respectively, while Lacto-N-fucopentaose-II (LNFP-II) or Lacto- N -fucopentaose-III (LNFP-III) increased by 65% 12 .

In another study in a European cohort, women with overweight had significantly higher concentrations of 3’-SL, 6’-galactosyl-lactose (6’-GL) and DSLNT at day 2; 6’-SL at day 17; and lacto-N-fucopentaose-V (LNFP-V) at day 90 and 120 than women with normal weight. In addition, lower concentrations of LNnT (at day 2 postpartum), lacto-N-tetraose (LNT; at day 30 and 90 postpartum), and LNFP-V (at day 60 postpartum) were observed in women with overweight or obesity compared to women with normal weight 10 . Ferreira et al. 11 , in 101 Brazilian mothers reported a direct correlation between LNnT and prepregnancy weight and BMI and an inverse correlation with 3-fucosyllactose (3-FL), LNFP-III and DFLNH at 2–8 days. However, a study reported that prepregnancy BMI was not associated with the concentration of HMOs in Hispanic mothers living in Los Angeles, CA, USA 13 .

To understand the influence of obesity on the breast milk composition, Saben et al. 14 , were the first to evaluate the relationship between obesity-associated maternal factors (as hyperglycemia, hyperinsulinemia, and insulin resistance) and HMOs in 136 US mothers. They observed a negative association between third trimester fasting plasma glucose and insulin with total HMO-bound sialic acid and concentrations of the sialylated HMOs 3’-SL and DSLNT in non-secretors (women who are unable to produce 2’-FL and LNFPI in breast milk) at two months postpartum. In secretors, difucosyllactose and LNFP-II concentrations increased, and sialyllacto- N -tetraose c (LSTc) and sialyllacto- N -tetraose b (LSTb) decreased as insulin sensitivity increased 14 .

A recent study discovered significant associations with changes in maternal food intake during lactation. Higher cheese, egg, fruits and vegetables consumption has been positively correlated with HMO concentrations in secretory mothers (for example, 2'-FL and LNT + LNnT), while fish consumption has been negatively associated with LNFP-V 15 . Previous studies have also demonstrated the association of food consumption with HMOs composition with contradictory results between them 8 , 15 , 16 , 17 .

Undoubtedly, the discrepancy between the different reports invites new research on the influence of modifiable factors on HMOs. The aim of the present study was to describe the correlation between maternal factors and HMOs concentrations at the beginning of breastfeeding.

Participant demographics, medical history, and anthropometrics: mother–child pairs

In the present study, 70 mothers and their newborn children were recruited. Of the participating mothers, 94.3% were secretors (HMOs production status). They had an average age of 23.0 ± 5.2 years at delivery (Table 1 ). Regarding their demographics, 80% resided in the Monterrey N.L. Mexico metropolitan area, 60% had middle school as their highest level of completed education, and 90% of the mothers were employed in various unspecified occupations. Medically, 10% had a history of high blood pressure and 5.7% of cholesterolemia or dyslipidemia; none had a history of kidney disease. Cholesterolemia or dyslipidemia was found to be associated with overweight or obesity in mothers (p = 0.05); the four women who had this medical history were in the overweight or obesity group, as detailed in Table 1 .

Regarding the data associated with pregnancy and childbirth, 67.1% of births were spontaneous at the beginning, and 77.1% of the deliveries were eutocic. According to their conclusion, each delivery resulted in the birth of a single child. The average number of previous births compared to the current was 1.3 ± 1.4 children. Based on the anthropometric data in all participants, the prepregnancy BMI was 24.5 ± 5.9 kg m -2 , and the BMI at delivery was 28.3 ± 5.7 kg m -2 with a total weight gain of 9.8 ± 7.1 kg. The prepregnancy BMI and BMI at delivery were significantly higher in women with overweight or obesity compared to the women with normal weight, as expected (Table 1 ). Furthermore, the diastolic and systolic blood pressures in all participants were 69.4 ± 11.1 mm Hg and 113.0 ± 11.2 mm Hg, respectively. Systolic blood pressure was significantly higher (p = 0.01) in women with overweight or obesity (116.4 ± 9.4 mm Hg) compared to women with normal weight (109.7 ± 11.8 mm Hg). However, 4/36 (11.1%) and 3/34 (8.8%) showed a diastolic blood pressure above 80 mm Hg in women with normal weight and women with overweight or obesity, respectively. On the other hand, 6/36 (16.6%) and 9/34 (26.5%) showed a systolic blood pressure above 120 mm Hg in women with normal weight and women with overweight or obesity, respectively. Regarding to another maternal factors such as age at delivery, residence, maximum level of studies, occupation, high blood pressure medical history, mode of delivery, parity, diastolic blood pressure and weight gain, no differences were found between the groups (women with overweight or obesity vs. women with normal weight; p > 0.05), as shown in Table 1 .

Data were obtained from all participating mothers' newborns, 60% were female, and 95.7% did not show congenital anomalies. The weight and height at birth were 3.2 ± 0.4 kg and 49.2 ± 2.1 cm, respectively. Of newborns, 68.6% were normal weight, and 81.4% were normal height. The weight of the newborns was significantly higher in women with overweight or obesity compared to women with normal weight (p = 0.024). In addition, the average birth head circumference was 33.6 ± 1.3 cm. Regarding neonatal screening, APGAR and Silverman-Andersen scores were normal in most newborns, and hearing screening was positive (a positive result indicates correct hearing at birth) in 45.7% (Table 1 ). Regarding birth height, birth head circumference, sex, congenital anomalies, APGAR and Silverman-Andersen scores, and hearing screening, no differences were found between the groups (p > 0.05).

HMOs profiling and individual concentrations between the study groups

The total HMOs content was significantly lower in the group of women with overweight or obesity with 11.7 ± 3.4 g L −1 compared to women with normal weight with 15.9 ± 4.7 g L −1 (p < 0.001). These concentrations were based on the sum of 2'-FL, 3-FL, LNT, LNnT, LNFPI, 3'-SL, and 6'-SL, as the most representative HMOs (about 90%) in breast milk (Fig.  1 and Supplementary Table 2 ). In all participants, about 63% of the total HMOs were fucosylated neutrals (Fig.  1 a), followed by 21.9% non-fucosylated neutrals (Fig.  1 b) and 15.1% acidic (Fig.  1 c).

Comparison of HMO concentrations in colostrum samples from Mexican mothers with normal weight and overweight/obesity. ( a ) Neutral fucosylated, ( b ) neutral no fucosylated and ( c ) acidic. The data is displayed in a grouped boxplot with connect mean line and the p values were obtained using the non-parametric Mann–Whitney U test. Significance levels are denoted as * for p < 0.05, ** for p < 0.01 and *** for p < 0.001; n.s. not significant. NW women with normal weight, OW/OB women with overweight/obesity, 2’-FL 2’-fucosyllactose, 3’-SL 3’-sialyllactose, 6’-SL 6’-sialyllactose, 3-FL 3-fucosyllactose, LNFPI lacto- N -fucopentaose I, LNnT lacto- N -neotetraose, LNT lacto- N -tetraose.

There was a significant decrease in the concentration of six of the seven HMOs in women with overweight or obesity compared to women with normal weight. For the neutral fucosylated HMOs, the concentrations of 2’-FL were 5.2 ± 1.8 g L −1 , and LNFPI were 2.7 ± 1.9 g L −1 in women with normal weight compared to women with overweight or obesity with 4.4 ± 1.4 g L −1 and 1.7 ± 0.9 g L −1 , respectively (Fig.  1 a). In addition, the acidic HMOs 3’-SL and 6’-SL showed concentrations of 1.9 ± 1.3 g L −1 and 1.1 ± 0.5 g L −1 in women with normal weight compared to women with overweight or obesity with 1.2 ± 1.5 g L −1 and 0.5 ± 0.3 g L −1 , respectively (Fig.  1 c). In the case of non-fucosylated neutral HMOs, the concentrations of LNT and LNnT were 2.7 ± 1.8 g L −1 and 0.8 ± 0.5 g L −1 in women with normal weight compared to women with overweight or obesity with 1.8 ± 1.5 g L −1 and 0.5 ± 0.3 g L −1 , respectively (Fig.  1 b).

Correlations between HMOs concentrations and maternal factors

Three main horizontal clusters were observed among maternal factors in the hierarchical analysis (Fig.  2 ). The first was composed of age, parity, prepregnancy weight and BMI, and weight and BMI at delivery, while the second was composed of prepregnancy height, height at delivery and weight gain, and the third group composed by diastolic and systolic blood pressure. Only the factors grouped in the first cluster showed correlations with HMOs. HMOs were arranged in two main vertical clusters; the first formed by LNT, 3-FL and 2'-FL while the second by LNFPI, LNnT, 6'-SL, total HMOs and 3'-SL. Negative correlations associated with age, previous births, prepregnancy weight, prepregnancy BMI, weight at delivery, and BMI at delivery were observed with HMOs concentrations at the beginning of lactation.

Heatmap and dendrogram of Spearman’s correlation coefficients between HMOs concentrations and factors including age, anthropometrics, and previous births. Red squares indicate negative correlations, while blue squares indicate positive correlations. Significance levels are denoted as * for p < 0.05, ** for p < 0.01 and *** for p < 0.001. PP prepregnancy, BP blood pressure.

Age showed a weak negative correlation with LNnT ( r s  = −0.254; p < 0.05) and 3’-SL ( r s  = −0.242; p < 0.05). The number of previous births showed a weak negative correlation with LNnT ( r s  = −0.295; p < 0.05), 3’-SL ( r s  = −0.397; p < 0.001), and 6’-SL ( r s  = −0.268; p < 0.05), but a weak positive correlation with LNT ( r s  = 0.266; p < 0.05), as shown in Fig.  2 .

Pre-pregnancy weight and BMI were weak negatively correlated with total HMOs ( r s  = −0.349 and ρ = −0.347; p < 0.01 both), 6’-SL (pre-pregnancy weight: r s  = −0.391; p < 0.001) and moderate negatively correlated 6’-SL (pre-pregnancy: r s  = −0.407; p < 0.001) and LNnT ( r s  = −0.407 and r s  = −0.426; p < 0.001 both). In addition, weight and BMI at delivery were moderate negatively correlated with total HMOs ( r s  = −0.444 and r s  = −0.451; p < 0.001 both), 6'-SL (ρ = −0.462 and ρ = −0.487; p < 0.001 both) and LNnT (ρ = −0.458 and ρ = −0.491; p < 0.001 both), and weak negatively correlated with 3’-SL ( r s  = −0.298 and r s  = −0.302; p < 0.05 both) and LNFPI ( r s  = −0.284 and r s  = −0.312; p < 0.05 and p < 0.01), as shown in Fig.  2 .

Correlations between HMOs and frequency of food group consumption

The foods with the highest total weekly consumption frequencies of each food group were whole milk (7.4 ± 6.1), orange or tangerine (7.4 ± 10.0), onion (10.3 ± 9.2), egg-warm or boiled (7.0 + 8.1), fresh fish (2.3 ± 3.0), beans prepared at home-cooked (5.8 ± 6.0), breakfast cereal: fruit flavor—froot loops (8.5 ± 7.8), corn atole—with milk (3.3 ± 5.7), water (24.0 ± 12.4), pasta soup—broth (3.4 ± 4.2), Tortilla (purchased) or factory-made tortilla (29.0 ± 23.3), and salt or seasoning with salt added to the foods (14.1 ± 8.5). In addition, some differences in the total weekly consumption frequencies of specific foods between the study groups were observed, as shown in Supplementary Table 3 .

In the dairy foods group, a strong and very strong positive correlation was only observed between the natural drinkable yogurt consumption and two HMOs: LNnT ( r s  = 0.756) and 6’-SL ( r s  = 0.850). On the other hand, strong negative correlations of the natural whole yogurt ( r s  = −0.624) and whole yogurt with fruits ( r s  = −0.647) with LNT concentrations were observed. Panela or fresh or cottage cheese consumption was moderate negatively associated with the concentration of acidic HMOs 3-SL ( r s  = −0.421) and 6’-SL ( r s  = −0.404). In addition, semi or ripened cheese consumption was weak negatively correlated to LNnT ( r s  = −0.323) and total HMOs ( r s  = −0.317) concentrations, and moderate negatively correlated to 6’-SL ( r s  = −0.443), as shown in Table 2 .

In the fruit group, we found that the consumption of seven different types of fruits was associated with changes in the concentration of HMOs. Guava consumption showed a moderate negative correlation with the level of LNT ( r s  = −0.551), whereas from weak to strong positive correlations were: (1) orange or tangerine with LNFPI and 3-FL; (2) apple or pear with LNnT, 3’-SL, 6’-SL, and total HMOs; (3) mango with LNnT, 3’-SL and 6’-SL; (4) strawberries with LNFPI, LNnT, 6’-SL and total HMOs; (5) grapes with 3-FL; and (6) crystallized or dried fruits with 3-FL (Table 2 ).

Results like those previously described were observed in the vegetable group, seven different vegetables showed positive correlations with the concentrations of specific HMOs. The consumption of frozen vegetables moderate negatively correlated with the LNFPI concentrations ( r s  = −0.498). From weak to strong positive correlations are described as follows: (1) green leaves with LNnT; (2) carrot with 3-FL; (3) lettuce with up to four HMOs (LNFPI, LNnT, 3’-SL, and 6’-SL) and total HMOs; (4) nopales (cactus) with up to four HMOs (LNFPI, LNnT, 3’-SL, and 6’-SL); (5) cucumber with 3-FL; (6) avocado with LNFPI and LNnT; and (7) poblano chili with LNnT, 6’-SL, 3-FL and total HMOs.

The consumption of beef, pork, turkey or mixed sausage, pork or turkey ham or mortadella and egg were weak positively associated with the concentrations of total HMOs ( r s  = 0.269), 3-FL ( r s  = 0.256), and LNnT ( r s  = 0.311), respectively. Chicken was moderate postively correlated with 2’-FL ( r s  = 0.615). Pork meat consumption was weak positively correlated to LNFPI ( r s  = 0.391) and total HMOs ( r s  = 0.382), and moderate positively correlated to 2’-FL ( r s  = 0.432).

In the fish group, tuna or sardine showed a weak positive correlation with the concentrations of LNnT ( r s  = 0.374), whereas that some seafood showed a moderate positive correlation with LNT ( r s  = 0.453).

Beans prepared at home, cooked, and refried showed a weak ( r s  = 0.366) and moderate ( r s  = 0.597) positive correlations with 3-FL concentrations, respectively).

In the cereals and tubers groups, whole grain bread and sweet bread both showed a moderate ( r s  = 0.515) and weak ( r s  = 0.342) positive correlation with 3-FL, respectively; whereas that potatoes ( r s  = −0.389; half fried piece or half a potato pancake) showed a weak negative correlation and breakfast cereal ( r s  = −0.912; fruit flavor; froot loops) showed a very strong negative correlation with 3-FL.

In the corn food, appetizers with vegetables (such as sopes, quesadillas, tlacoyos, gorditas, and enchiladas; not tacos) fried and without frying were moderate positively correlated with 3-FL ( r s  = 0.509) and strong negatively correlated with 6’-SL ( r s  = −0.660), respectively.

In the beverages group, the consumption of natural fruit waters with sugar was strong positively correlated with 3-FL ( r s  = 0.708) and total HMOs ( r s  = 0.664), unsweetened industrialized flavored beverages with 6’-SL ( r s  = 0.673), and fruit nectars or fruit pulp industrialized with sugar were moderate positively associated with LNnT ( r s  = 0.405) and 3’-SL ( r s  = 0.443), while weak positively correlated to 6’-SL ( r s  = 0.328) concentrations.

Soups with pasta (pasta soup) and tortilla (corn flour tortilla) groups were weak and strong positively correlated to 3’-SL ( r s  = 0.369) and LNnT ( r s  = 0.712) concentrations, respectively.

In the miscellaneous group, dried chili was strong and very strong positively associated with LNFPI ( r s  = 0.7127) and 3-FL ( r s  = 0.81742) concentrations, respectively; soy sauce, Worcestershire sauce, or liquid food seasonings were very strong positively associated with 3’-SL ( r s  = 0.84515). The correlations between all food groups and HMOs are shown in Supplementary Table 4 .

In addition, a statistical difference (p = 0.008) was observed in total daily calories between women with normal weight (4133.1 ± 1142.4 kCal) and women with overweight or obesity (3391.1 ± 1038.8 kCal). However, total daily calories and concentrations of each of the HMOs were not correlated.

The focus of the study was to describe the correlation between maternal factors and HMO concentration in colostrum samples. The absolute concentrations of LNFPI, 2’-FL, LNT, LNnT, 3’-SL, and 6’-SL were significantly lower in women with overweight or obesity compared to women with normal weight. In addition, from weak to moderate correlations between maternal age, previous births, prepregnancy weight, prepregnancy BMI, weight at delivery, and BMI at delivery, and HMOs concentrations at the beginning of lactation were observed. The frequency of consumption of food groups such as vegetables (poblano chili and 2’-FL; rs = 0.702, p = 0.0012), fruits (orange or tangerine and 3-FL; rs = 0.428, p = 0.0022) and meats (chicken and 2'-FL; rs = 0.615, p = 0.0039) was positively correlated to specific HMOs from moderate to strong correlations.

During pregnancy, many studies suggest that a medical history of diseases associated with lipid metabolism is linked to increased BMI 18 . Hernández-Higareda et al. 19 , conducted a study on 600 Mexican women from Guadalajara, Jalisco to identify pregnancy-related diseases associated with obesity. Like the present study, they observed a significant association between a medical history of cholesterolemia or dyslipidemia and overweight or obesity in the participating women. Although the size of the samplein the present study is limited, the average systolic blood pressure was also significantly higher in women with overweight or obesity. Studies in other countries and continents have previously reported this association 20 , 21 , 22 .

Being overweight or obese during pregnancy not only increases the risk of health complications in the woman but also affects the perinatal health of the newborn. Taoudi et al. 23 , studied 90 participants from Témara, Morocco, aged between 18 and 43 years and found a significant positive correlation between gestational BMI and newborn birth weight ( r s  = 0.29; p < 0.001). A recent study in 1,112 Mexican women, reported that overweight marginally decreased the probability of having a low birth weight. In the present study, we observed that children born to women with overweight or obesity have a significant increase in birth weight compared to children born to women with normal weight 24 , 25 .

Approximately 15–20% of women worldwide do not express the FUT2 gene and are considered non-secretors related to a lower diversity and concentration of fucosylated HMOs such as 2’-FL and LNFPI 26 , 27 . In the present study, we observed a low prevalence (5.7%) of the non-secretor state of mothers. The proportion of non-secretors and secretor women vary between each report and geographic location. A proportion of 0%, 32%, 36%, and 37% of non-secretors has been reported in Bolivia, USA, Gambia, and South Africa, respectively 28 , 29 , 30 , 31 . However, this can vary significantly in different regions within the same country due to the diversity of ethnic origins 15 .

Isganaitis et al. 12 , analyzed the relationships between maternal obesity and human milk metabolites in 31 mothers from Oklahoma, USA and found that LNFPI was reduced by about 62% in the breast milk of women with overweight or obesity compared to women with normal weight at one month of breastfeeding (p = 0.007). In the present study we observed a similar percentage reduction in LNFPI (63%) in the colostrum of women with overweight or obesity compared to women with normal weight although in the previous study their HMOs quantifications were relative by untargeted metabolomics. However, our results differ from the previous study in that no significant reduction in 2'-FL was observed compared to the 38% they observed 12 . Another study in 78 Brazilian mothers, observed that secretor women with overweight (BMI 25–29.9 kg m −2 ) had a significantly higher concentration of 2'-FL (p = 0.030) and lower 3'-FL concentration (p = 0.011) than secretor women with normal weight (BMI 18.5–24.9 kg m −2 ) about one month postpartum 32 . The results of that study, using a similar LC–MS analytical platform, were consistent with the present study in which 3-FL was found to be significantly reduced in women with overweight or obesity (p = 0.011). A fact to highlight is that the HMO content is highest in colostrum and tends to decrease over the course of lactation. These two studies were conducted in women at one month of lactation where 2’-FL can be reduced by close to 68% and 3-FL may be increased by around 215%.

In a study conducted by McGuire et al. 7 , maternal weight and BMI were negatively correlated with LNnT ( r s  = −0.16 and r s  = −0.21, respectively) and positively correlated with 2′-fucosyllactose ( r s  = 0.20 for both) in 410 healthy women from different countries at about three months postpartum. In addition, Samuel et al. 10 , found that women with overweight had significantly higher concentrations of 3′-SL (at day 2; colostrum), 6′-SL (at day 17) while lower concentrations of LNnT (at day 2; colostrum) and LNT (at day 30 and 90) compared to women with normal weight (p < 0.05 for all) in 370 women from seven European countries. These two reports were consistent with results found in the present study, where the concentrations of LNT and LNnT were lower in women with overweight or obesity compared to women with normal weight, although McGuire et al. 7 used LC coupled to a duo ion-trap mass spectrometer for quantitative analysis. However, the increase of 3’-SL) concentration observed in women with overweight at day 2 of lactation by Samuel et al. 10 disagrees with those found in the present study; LNnT was reduced in overweight women as was in the present study. Another study in 322 women from Brazil, prepregnancy BMI was moderate negatively correlated with 3-FL ( r s  =  − 0.5), consistent with our study but discrepant in that prepregancy BMI was moderate positively correlated with LNnT ( r s  = 0.4) at 2–8 days of lactation 11 .

The impact of other maternal factors (maternal age, mode of delivery, parity, and blood pressure) on the composition of HMOs remains unclear. Austin et al. 33 , conducted a cross-sectional study of 446 Chinese women in different stages of lactation (from 0–4 days to 4–8 months) and observed that the mode of delivery had no impact on HMOs composition. However, the study conducted by Samuel et al. 10 , observed that women giving birth through cesarean section (dystocic) had significantly higher concentrations of LNT (colostrum; at day 2) and 6′-SL (at day 30), and significantly lower concentrations of 2′-FL, 3′-SL, 6′-GL, LNFP III, LNnDFH and LNFP II (colostrum; at day 2) compared to those giving birth by vaginal delivery (eutocic). The present study is consistent only with those reported with Austin et al. 33 in colostrum samples (< 48 h). Ferreira et al. 11 , reported that parity was moderate positively correlated with LNFP II ( r s  = 0.4), DFLNT ( r s  = 0.4), LNH ( r s  = 0.4) and FDSLNH ( r s  = 0.4) in colostrum samples at 2–8 days of lactation. Unlike the present study where parity showed a weak positive correlation with LNT and a weak negative correlation with 3'-SL, 6'-SL and LNnT.

McGuire et al. 7 , found that maternal age was weak negatively correlated with concentrations of LNnT, LSTc, and DSLNH ( r s  =  − 0.14, r s  =  − 0.17, and r s  =  − 0.15, respectively) and was weak positively correlated with the concentration of FLNH ( r s  = 0.15) from two weeks to five months of lactation. In the present study, maternal age was also weak negatively associated with LNnT concentrations at < 48 h of lactation.

In another studies, Fan et al. 15 , studied 468 pregnant women from Illinois USA and found that maternal age was weak positively correlated with relative abundances of 3-FL ( r s  = 0.12, p = 0.019), DFLNHb ( r s  = 0.11, p = 0.034), and IFLNH III ( r s  = 0.1, p = 0.046), and weak negatively correlated with abundances of p-LNH ( r s  =  − 0.13, p = 0.011) and IFLNH I ( r s  =  − 0.13, p = 0.012) at 6 week of lactation. A study in 3,407 Canadian mothers conducted by Azad et al. 8 , lower concentrations of DFLNT and higher concentrations of LNnT and LNT in older mothers, while lower concentrations of 3-FL were observed in multiparous mothers and the mode of delivery was not associated with HMOs concentrations at 3–4 month of lactation 8 . In a longitudinal study of 116 Chinese mothers conducted by Wang et al. 34 , maternal age was weak negatively correlated with LNT + LNnT ( r s  =  − 0.29), LNFPI ( r s  =  − 0.21), but was weak positively correlated with 2′-FL ( r s  = 0.22) only in secretor women at 1–5 days of lactation. In addition, they found a weak negative correlation between parity and LNFPI ( r s  =  − 0.20) at 1–5 days of lactation. Tonon et al. 32 , observed a strong positive correlation between parity and LNT + LNnT ( r s  = 0.79) and LNFPI ( r s  = 0.79) levels and a strong negative correlation between parity and 3′-FL ( r s  =  − 0.79) concentrations in secretor mothers (Se+) from 17 to 76 days of lactation.

Our results were consistent with the obtained by McGuire et al. 7 , and Wang et al. 34 , who observed a negative correlation between maternal age and LNnT concentrations. Regarding parity and composition of HMOs, our results are aligned with those obtained by Tonon et al. 32 , where parity showed a positive correlation with LNT concentrations. In addition, like Azad et al. 8 and Samuel et al. 10 , no statistical differences were observed between the delivery mode and the concentrations of each of the HMOs evaluated in the present study.

Only a few studies investigated the impact of maternal diet on HMOs composition. Hallam et al. 35 , evaluated the effect of high-protein and high-prebiotic-fiber maternal diets on the composition of oligosaccharides in breast milk in maternal rats and observed an increase in both neutral and acidic oligosaccharides. Although the previous study is an animal model, our results show that the frequency of consumption of foods rich in fiber such as vegetables and legumes (beans) were positively correlated with the concentrations of HMOs.

In an interventional study using two different cohorts from Baylor, Texas tested the effect of glucose or galactose-enriched diet for 30–57 h (n = 7) or a high-fat or high-carbohydrate diets for 8 days (n = 7) on HMOs. HMO-bound fucose concentration was reduced with the glucose-enriched diet 16 . These results contrast with those found in the present study where we observed that the frequency of consumption of beverages rich in sugar increases the concentrations of fucosylated HMOs such as LNFPI and 3-FL.

Nutmeg is the richest in myristic acid (a food not typical in the Mexican diet), but we can find it in quantities 30–50 times lower in dairy products (such as yogurt), fish (such as tuna or sardines) and eggs 36 . This could explain the positive correlations observed in the present study between foods containing myristic acid and concentrations of LNT or LNnT. A source of stearic acid of plant origin is cereals (corn, rice, and others) which could be related to the findings of this study where negative correlations of 2'-FL and 6'-SL in consumers of breakfast cereal (fruit flavor) and appetizers with vegetables (such as sopes, quesadillas, tlacoyos, gorditas, and enchiladas; corn-based), respectively were observed.

Another study by Seppo et al. 37 , showed that supplementation with probiotics ( Lactobacillus rhamnosus GG, Lactobacillus rhamnosus LC705, Bifidobacterium breve Bb99, and Propionibacterium freudenreichii subspecies shermanii JS) during the last three weeks of pregnancy increased the concentrations of 3-FL and 3′-SL in colostrum from 1223 pregnant mothers from Helsinki, Finland. In the present study, foods containing probiotics such as natural yogurt showed a positive correlation with LNnT and 6'-SL concentrations. However, the probiotic bacteria contained in this dairy food were not specified in the present study.

Fan et al. 15 , reported that higher cheese consumption was correlated with a higher amount of 2′-FL (p = 0.046) in breast milk at six weeks postpartum. In that same study, increased egg consumption was associated with greater LNT + LNnT abundance (p = 0.012). These results were contrary to those found in the present study, where the consumption of panela, fresh or cottage cheese, and semi or ripened cheeses showed a negative correlation with 3’-SL, 6’-SL, and LNnT concentrations. However, egg consumption was positively correlated with LNnT concentrations, consistent with what was reported by Fan et al. 15 . Quin et al. 38 , found that ingested carbohydrates (simple sugars and dietary fiber) were positively correlated with the relative levels of Galactose and Fucose present in HMOs with the decrease of Neu5Ac and Neu5Gc. Furthermore, they observed similar correlations for the total amount of fruit ingested, an important dietary source of sugars and fiber (a known source of Fucose). They observed significant positive correlations for Galactose and Fucose, while Neu5Ac levels were significantly lower in HMOs biosynthesized by women consuming large amounts of fruit. They observed that only cheese intake was positively associated with Neu5Gc levels and HMOs concentrations. These results are consistent with those found in the present study, showed that the consumption of different types of fruit was positively associated with the concentrations of all HMOs studied except 2'-FL.

Quin et al. 38 demonstrated that Neu5Ac obtained from the diet from red meat and products derived from cow's milk (such as cheese) positively influences the concentrations of HMOs. Those above could explain the positive correlation observed in the present study between the consumption of red meat (pork meat and beef) and the concentrations of total HMOs.

Our study has some limitations, with the main restriction being the small sample size, which limits the power to detect differences between groups. Despite this, we found very revealing statistical differences consistent with those reported in the literature. In addition, the study was a single-center study, limiting the generalizability to other settings. However, regional studies where overweight and obesity are very prevalent among women and school-age children are necessary to improve our understanding of the influence of dietary habits, BMI, and other maternal factors on the composition of breast milk. The present study is the first to be carried out in Mexico, a country where about 30% of adults have obesity with a greater impact on women. The results of the present study show the impact of obesity on the composition of breast milk is significative, which would suggest consequences for the infant from birth.

In conclusion, the influence of overweight and obesity as a modifiable factor associated with lower concentrations of 2’-FL, LNFPI, 3’-SL, 6’-SL, LNT and LNnT at the beginning of lactation could affect the quality of breast milk and deprive the newborn of its associated health benefits. The frequency of consumption of certain food groups, such as fruits, vegetables, and meats, can increase the concentrations of specific HMOs. The present study opens the possibility of new research aimed to improve the quality of breast milk through nutritional intervention based on healthy eating and BMI control for overweight/obesity prevention.

Study design

The present was a cross-sectional, descriptive, prospective, and single-center study that was carried out at the Hospital Regional Materno Infantil de Alta Especialidad (HRMIAE) in Monterrey, Nuevo León, Mexico, over nine months from February 2023 to October 2023.

Ethical approval

This study was conducted according to the ethical principles for medical research involving human subjects outlined in the Helsinki Declaration. Institutional review board approval (approval number: DEISC-PR-190122074; Hospital Regional Materno Infantil de Alta Especialidad) was obtained, and the participants provided written informed consent before participating in the study.

Recruitment, eligibility criteria, and study groups

In the present study, 70 mothers from 18 to 49 years of age were recruited, and a signed written informed consent was previously obtained. Recruitment was in the rooming-in area (where recovering mothers and newborns stay together until their hospital discharge) at the HRMIAE, where the first contact was established with the participants. Then, the resident doctor or social service intern evaluated compliance with the following eligibility:

Inclusion criteria: (a) women with a full-term pregnancy (≥ 38 weeks); (b) Mexican nationality; (c) healthy; (d) 18 to 49 years of age; (e) that the weight and height record is in the pregnancy control record from the first trimester; (f) patient without a history of any diabetes.

Exclusion criteria: (a) history of antibiotic use in the three months before delivery; (b) prolonged exposure to antibiotics (> 3 weeks) during pregnancy; (c) immunosuppressive or immunomodulatory therapy with corticosteroids; (d) history of vegan, lacto-ovo-vegetarian or exclusion diet (for example ketogenic diet); (e) history of bariatric surgery; (f) exposure to antineoplastic drugs; (g) histamine-H2 receptor antagonists or proton pump inhibitors or monoclonal antibodies; (h) history of mental illness (those that make it impossible to take the sample); (i) history of alcohol, tobacco or drug use during pregnancy; j) neonates with fetal distress or contact with meconium; (k) neonates who were administered an antibiotic at birth; (l) patients who do not have reliable weight and height information during prenatal care; (m) patient with a history of metabolic diseases (gestational diabetes, diabetes mellitus type 1 and 2).

Elimination criteria: (a) antibiotics for more than 24 h after delivery; (b) intensive care (mother or baby) or any condition that prevents the collection of breast milk. (c) Patients who are unable for some reason to continue breastfeeding.

Mothers were categorized into two study groups (1: women with normal weight and 2: women with overweight or obesity) based on their pre-pregnancy BMI.The permanence in the study group until the conclusion of pregnancy was determined by total weight gain. This classification followed the 2009 IOM/NRC guidelines, which detail weight gain recommendations for women with singleton and twin fetuses in Table 2 39 . For example, women who had the diagnosis of normal weight (18.5–24.9 kg m −2 ), based on prepregnancy BMI and gained normal weight during pregnancy (11.3–15.9 kg) were classified as "women with normal weight", but if gained excessive weight during pregnancy was classified as "women with overweight or obesity." On the other hand, women who had the diagnosis of overweight (25.0–29.9 kg m −2 ) or obesity (≥ 30.0 kg m −2 ), based on prepregnancy BMI, but if gained normal weight during pregnancy (6.8–11.3 kg for overweight and 5–9 kg for obesity) remained classified as "women with overweight or obesity".

In addition, women were categorized according to their secretory status based on the ability to produce 2’-FL and LNFPI in breast milk.

Data and sample collection

Socio-demographic data (age, residence, maximum level of studies, occupation), medical history, and anthropometric data were collected from all participants, and a food consumption frequency questionnaire was applied, which is a validated tool for the Mexican population within the nutritional evaluation that allows measuring caloric consumption and the portion consumed according to the frequency of consumption of food groups; total weekly frequency of food group consumption was calculated by multiplying the daily by the weekly frequency. Food consumption frequency data were collected at the same time as the colostrum sample collection and reflect the frequency in the last week (7 days).

In addition, relevant data associated with the delivery and newborn data were collected, such as anthropometrics, basic metabolic screening, and hearing screening routinely performed on all newborns. All information was collected using a data collection instrument .

About sample collection, 1 mL of breast milk samples (colostrum; < 48 h postpartum) were collected from all participating women with the help of medical personnel from the HRMIAE Human Milk Bank. After collection, the samples were immediately stored frozen at −20 °C. Finally, the samples were transported to the Centro de Biotecnología FEMSA of the Tecnologico de Monterrey and stored under the same freezing conditions until processing.

Absolute quantification of human milk oligosaccharides

Sample preparation.

The samples were prepared following the methodology previously validated in our laboratory by Urrutia Baca et al. 40 . 50 µL of each colostrum sample was diluted with 150 µL water and vortex mixed. Next, 50 µL of the mixture was transferred to 1.5 mL new tubes and mixed with 450 µL of water, and the mixture was centrifuged at 12,000× g for 30 min at 4 °C. Then, 300 µL of the lower aqueous phase was transferred to 1.5 mL tubes and mixed with 900 µL of acetonitrile. The mixture was sonicated for 10 min, incubated for 60 min at 4 °C, centrifuged at 12,000× g for 30 min at 4 °C, and the supernatant was recovered. For removal of residual protein, 500 µL of the supernatant was ultracentrifuged using tubes with a 3 kDa molecular weight cut-off membrane (Vivaspin 500, 3 kDa MWCO; GE28-9322-18; Sartorius, Stonehouse, UK) for 50 min at 7500× g , 4 °C. In this step, a carbohydrate fraction was obtained and filtered through a 0.22 μm nylon before UPLC–MS/MS analysis.

UPLC–MS/MS analysis

Calibration curves were made to establish the concentration ranges for quantification. For 2’-FL, 3-FL, and LNFPI, there were seven concentration points from 1 µg to 100 µg mL −1 , and for 6’-SL, 3’-SL, LNT, and LNnT there were six concentration points from 1 to 50 µg mL −1 . The linearity equations and the determination coefficient were obtained for both calibration curves.

The experiments were performed using an Acquity UPLC system (Waters, Milford, MA) equipped with Micromass Quattro Premier XE Mass Spectrometer (Waters, Milford, MA). An ACQUITY UPLC BEH Amide Column (Waters; 1.7 μm, 2.1 × 100 mm) coupled to an ACQUITY UPLC BEH Amide pre-column (Waters; 1.7 μm, 2.1 × 5 mm) was used for chromatographic separation adjusted at 40 °C using a binary gradient. The mobile phase A and B consisted of 10 mM ammonium formate in water and 99.9% acetonitrile, respectively. The following UPLC gradient was used: 0 − 2 min from 98 to 95% B, 2–3 min to 65% B, 3–8.5 min to 55% A, 8.5–11 min to 55% A, 11–11.2 min to 98% A, 11.2–14 min to 98% B. The flow rate was set to 0.4 mL min −1 .

Mass spectrometric analyses were performed with a triple quadrupole spectrometer equipped with an electrospray ionization source (ESI). ESI conditions were as follows: Capillary 4 kV, Cone 50 V, Extractor 3 V, RF Lens 0 V, Source temperature 150 °C, desolvation temperature 300 °C, gas flow desolvation 720 L h −1 , gas flow cone 300 L h −1 . High-purity argon was used as collision gas. The mass spectrometer was operated in negative-ion, multiple reaction monitoring (MRM) mode. Our work team previously optimized MRM conditions (Supplementary Table 1 ) and carried out the validation of the method applied in the present study 40 .

Statistical analysis

The distribution of data was determined for each study variable by Kolmogorov–Smirnov test. Next, associations were established between the mother and the newborn variables based on the study groups. Student’s t-test and Chi-square with Fisher’s Exact Test were used for continuous and categorical variables, respectively. The concentration values of each HMOs, total, and profile showed no normal distribution; therefore, a non-parametric Mann–Whitney U test was used to explore the differences between the study groups. The correlation between HMOs concentrations and factors including age, anthropometrics, previous births, and frequency of food group consumption were calculated by Spearman's correlation test; Spearman's correlation coefficient > 0 indicates a positive correlation and < 0 indicates a negative correlation. The maternal variables were organized into clusters on the X axis and the concentrations of each specific HMOs were organized on the Y axis by hierarchical cluster analysis based on ρ values. Finally, the total frequency of consumption of each food group was calculated and then correlated with the concentrations of each HMOs by Spearman's correlation test. For all statistical tests, a p-value less than 0.05 was considered significant. Finally, the box charts, heatmaps, and dendrograms were generated using Origin v2023.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors thank the Integrative Biology Unit (IBU) and the Healthy Food Unit (HFU) of the Institute for Obesity Research (IOR), Centro de Investigación y Desarrollo de Proteinas (CIDPRO) and Centro de Biotecnología FEMSA of the Tecnologico de Monterrey, and Hospital Regional Materno Infantil de Alta Especialidad (HRMIAE) of the Secretaria de Salud, Nuevo Leon, Mexico for supporting the development of this study. The authors thank Dr. Ana Lucía Araujo (Resident of Pediatrics) for her support in obtaining Institutional Review Board approval for this study (HRMIAE and Secretaria de Salud, Nuevo León, México). The authors also thank and recognize the incredible contribution of the HRMIAE Human Milk Bank health personnel during the collection of colostrum samples in the present study.

This work was supported by the Challenge-Based Research Funding 2022 of Tecnologico de Monterrey [I008-IOR001-C6-T1-E, November 3, 2022].

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Authors and affiliations.

Tecnologico de Monterrey, Institute for Obesity Research, Ave. Eugenio Garza Sada 2501, 64849, Monterrey, NL, Mexico

Víctor H. Urrutia-Baca, Janet A. Gutiérrez-Uribe, Astrid Domínguez-Uscanga, Francisca Espiricueta-Candelaria & Cristina Chuck-Hernández

Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, 64849, Monterrey, NL, Mexico

Perla A. Ramos-Parra

Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Ave. Ignacio Morones Prieto 3000, 64710, Monterrey, NL, Mexico

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V.H.U.B., C.C.H., J.G.U., and P.A.R.P. contributed to the conception and design of the study, the interpretation of the results, and the drafting of the manuscript. A.D.U., N.A.R.G., K.L.C.C., A.S.P.G., I.M.C., E.G.R.V., and F.E.C. conducted the acquisition of data. V.H.U.B. conducted the statistical analyses. All authors have read and approved the final version of the manuscript.

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Urrutia-Baca, V.H., Gutiérrez-Uribe, J.A., Ramos-Parra, P.A. et al. Exploring the impact of maternal factors and dietary habits on human milk oligosaccharide composition in early breastfeeding among Mexican women. Sci Rep 14 , 14685 (2024). https://doi.org/10.1038/s41598-024-63787-1

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Milk and dairy products: good or bad for human health? An assessment of the totality of scientific evidence

Tanja kongerslev thorning.

1 Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark

Tine Tholstrup

Sabita s. soedamah-muthu.

2 Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands

3 Centre for Food, Nutrition and Health, University of Reading, Reading, UK

Arne Astrup

There is scepticism about health effects of dairy products in the public, which is reflected in an increasing intake of plant-based drinks, for example, from soy, rice, almond, or oat.

This review aimed to assess the scientific evidence mainly from meta-analyses of observational studies and randomised controlled trials, on dairy intake and risk of obesity, type 2 diabetes, cardiovascular disease, osteoporosis, cancer, and all-cause mortality.

The most recent evidence suggested that intake of milk and dairy products was associated with reduced risk of childhood obesity. In adults, intake of dairy products was shown to improve body composition and facilitate weight loss during energy restriction. In addition, intake of milk and dairy products was associated with a neutral or reduced risk of type 2 diabetes and a reduced risk of cardiovascular disease, particularly stroke. Furthermore, the evidence suggested a beneficial effect of milk and dairy intake on bone mineral density but no association with risk of bone fracture. Among cancers, milk and dairy intake was inversely associated with colorectal cancer, bladder cancer, gastric cancer, and breast cancer, and not associated with risk of pancreatic cancer, ovarian cancer, or lung cancer, while the evidence for prostate cancer risk was inconsistent. Finally, consumption of milk and dairy products was not associated with all-cause mortality. Calcium-fortified plant-based drinks have been included as an alternative to dairy products in the nutrition recommendations in several countries. However, nutritionally, cow's milk and plant-based drinks are completely different foods, and an evidence-based conclusion on the health value of the plant-based drinks requires more studies in humans.

The totality of available scientific evidence supports that intake of milk and dairy products contribute to meet nutrient recommendations, and may protect against the most prevalent chronic diseases, whereas very few adverse effects have been reported.

Several media stories and organisations claim that dairy increases risk of chronic diseases including obesity, type 2 diabetes, cardiovascular disease, osteoporosis, and cancer. Therefore, there is an increasing scepticism among the general consumers about the health consequences of eating dairy products. This is reflected in an increasing consumption of plant-based drinks, for example, based on soy, rice, almond, or oats. Dairy is an essential part of the food culture in the Nordic countries; thus, inclusion of milk and dairy products in the diet may be natural for many Nordic individuals. The major causes of loss of disease-free years in the Nordic countries today are type 2 diabetes, cardiovascular diseases, and cancers. Moreover, the increasing prevalence of obesity greatly increases the risk of these chronic diseases. Given the increasing prevalence of these chronic diseases, it is critically important to understand the health effects of milk and dairy products in the diet. Accordingly, this narrative review presents the latest evidence from meta-analyses and systematic reviews of observational studies and randomised controlled trials on dairy intake (butter excluded) and risk of obesity, type 2 diabetes, cardiovascular disease, osteoporosis, and cancer as well as all-cause mortality.

We aim to answer the key questions: 1) For the general consumer, will a diet with milk and dairy products overall provide better or worse health, and increase or decrease risk of major diseases and all-cause mortality than a diet with no or low content of milk and dairy products? 2) Is it justified to recommend the general lactose-tolerant population to avoid consumption of milk and dairy products? 3) Is there scientific evidence to substantiate that replacing milk with plant-based drinks will improve health?

Obesity and type 2 diabetes

A large share of the on-going increase in prevalence of type 2 diabetes is driven by the obesity epidemic ( 1 , 2 ), and it is therefore relevant to assess the role of milk and dairy products for body weight control. Childhood overweight and obesity worldwide is a major contributor to the current obesity epidemic, and childhood obesity frequently tracks into adulthood ( 3 ). Therefore, early prevention of childhood obesity is important. A meta-analysis showed that among children in the pre-school and school age, there was no association between dairy intake and adiposity ( 4 ). However, there was a modestly protective effect in adolescence. A recent meta-analysis by Lu et al. ( 5 ) found that children in the highest dairy intake group were 38% less likely to be overweight or obese compared to those in the lowest dairy intake group. An increase in dairy intake of one serving per day was associated with a 0.65% lower body fat and a 13% lower risk of overweight or obesity.

Milk and dairy products are good sources of high-quality protein. Protein is important during weight loss and subsequent weight maintenance due to the high satiating effect which helps to prevent over-consumption of energy and thereby reduces body fat stores ( 6 , 7 ). Furthermore, dairy protein is a good source of essential amino acids for muscle protein synthesis and thus helps to maintain the metabolically active muscle mass during weight loss ( 8 ). Meta-analyses support that in adults, dairy products facilitate weight loss and improve body composition, that is, reduce body fat mass and preserve lean body mass during energy restriction and in short-term studies ( 9 – 11 ). The effect of an increased dairy consumption on body weight in long-term studies (>1 year) and in energy balance studies is less convincing ( 10 , 11 ). This is likely due to the opposing effects of dairy on body composition, that is, reduction of fat mass and preservation of lean body mass.

Meta-analyses assessing the role of intake of milk and dairy products on risk of type 2 diabetes have consistently found no or a slight beneficial effect of dairy intake on diabetes risk ( 12 – 15 ). This is consistent with a Mendelian randomisation study using genetic polymorphisms for the lactase gene, which showed that milk intake assessed by lactose tolerance was not associated with risk of type 2 diabetes or obesity ( 16 ). The most recent meta-analysis on dairy intake and diabetes incidence included 22 cohort studies with a total of 579,832 subjects and 43,118 type 2 diabetes cases ( 17 ). An inverse association between total dairy and yoghurt intake and risk of type 2 diabetes was reported although there was no association with milk intake. The benefits of fermented dairy products (cheese and yoghurt) in relation to type 2 diabetes may be due to their effect on the gut microbiota ( 18 , 19 ). Other studies have identified that whey protein (primarily in milk and yoghurt) can reduce postprandial plasma glucose concentration in type 2 diabetic subjects ( 20 ). This effect may be due to the branched chain amino acids in the whey protein fraction, particularly leucine which has been shown to induce a greater stimulation of glucose-dependent insulinotropic polypeptide (GIP), but not glucagon like peptide 1 (GLP-1), compared to other amino acids ( 21 ). The GIP response is possibly a key factor in the higher insulin response and the subsequent lowering of blood glucose seen after whey ingestion, at least in healthy subjects. In addition to the insulinotropic effect of milk, a recent study has indicated that dairy may also improve insulin sensitivity ( 22 ).

Conclusion on obesity and type 2 diabetes

A diet high in milk and dairy products reduces the risk of childhood obesity and improves body composition in adults. This likely contributes to lower the risk of developing type 2 diabetes. Additionally, dairy product consumption during energy restriction facilitates weight loss, whereas the effect of dairy intake during energy balance is less clear. Finally, there is increasing evidence suggesting that especially the fermented dairy products, cheese and yoghurt, are associated with a reduced risk of type 2 diabetes.

Cardiovascular disease

Low-fat, calcium-rich dairy products are generally considered to lower blood pressure. This was supported by a meta-analysis of six observational studies, whereas no association was found with intake of high-fat dairy products ( 23 ). High-fat dairy products are known to increase high density lipoprotein (HDL)- and low density lipoprotein (LDL)-cholesterol concentrations. The latter normally predicts risk of cardiovascular disease ( 24 ), but this may depend on the size of the LDL-cholesterol particles. Small, dense LDL particles are more atherogenic than their larger counterparts ( 25 – 28 ) due to their lower affinity for the LDL-receptor and higher susceptibility to oxidation ( 29 ). In agreement, some of the fatty acids typically found in milk and dairy products have been associated with less small, dense LDL particles (4:0–10:0 and 14:0 in the diet, and 15:0 and 17:0 in serum phospholipids) ( 30 ). In addition, the minerals in milk and dairy products have been shown to attenuate the LDL-response to high-fat dairy intake ( 31 , 32 ).

Among high-fat dairy products, cheese in particular does not seem to increase LDL-cholesterol to the extent expected, based on the high content of saturated fat ( 33 ). When compared to habitual diet with a lower total and saturated fat content ( 33 ), or compared to diets with lower total fat content but higher content of high-GI carbohydrates ( 34 , 35 ), a high intake of cheese was found not to increase LDL-cholesterol. A meta-analysis of randomised controlled trials studying the effect of cheese consumption compared with other foods on blood lipids and lipoproteins showed that cheese caused lower total cholesterol, LDL-cholesterol, and HDL-cholesterol concentrations compared with butter ( 36 ). Compared with milk, however, there was no statistically significant difference in blood lipids ( 32 , 37 ). Several meta-analyses have been conducted on the relationship between intake of milk and dairy products and risk of developing cardiovascular disease. There was no consistent association between milk or dairy intake and cardiovascular disease, coronary heart disease or stroke in a meta-analysis by Soedamah-Muthu et al. ( 38 ). In a recent update, including a higher number of prospective cohort studies, there was a significant inverse association between milk intake and stroke, with a 7% lower risk of stroke per 200 ml milk/day, but considerable heterogeneity. Further, stratification for Asian and Western countries showed a more marked reduction in risk in Asian than in Western countries. This is consistent with a previous meta-analysis by Hu et al. ( 39 ) showing a non-linear dose–response relationship between milk intake and risk of stroke, with the highest risk reduction of 7–8% with a milk intake of 200–300 ml/day. Also, the meta-analyses by Hu et al. ( 39 ) and de Goede et al. ( 40 ) both showed an inverse association between cheese intake and stroke, however only borderline significant in the latter. Accordingly, another meta-analysis on dairy and cardiovascular disease found that intake of cheese and milk as well as yoghurt was inversely associated with cardiovascular disease risk ( 41 ). A later meta-analysis by Qin et al. ( 42 ) found that dairy intake was associated with a 12% lower risk of cardiovascular disease, and 13% lower risk of stroke as compared to individuals with no or a low dairy consumption ( 42 ). Likewise, a recent and comprehensive meta-analysis, including 31 cohort studies, suggested that a high dairy intake was associated with a 9% lower risk of stroke, whereas no association was found with total cardiovascular disease or coronary heart disease ( 43 ). Moreover, a high intake of cheese was associated with an 8% lower risk of coronary heart disease and a 13% lower risk of stroke. In addition, high plasma levels of the saturated fatty acid C 17:0, which primarily originates from dairy, were found to be associated with a reduced risk of coronary heart disease ( 44 ). Finally, a meta-analysis by O'Sullivan et al. ( 45 ) found no indication of total dairy intake or any specific dairy product being associated with an increased cardiovascular mortality. Studies are emerging showing that dairy products, particularly the low-fat types, cluster within a healthy dietary pattern ( 46 ), and therefore, the risk of residual confounding in the observational studies cannot be ruled out.

In accordance with the latest meta-analyses presented above, the latest Nordic Nutrition Recommendations have concluded that high consumption of low-fat milk products is associated with reduced risk of hypertension and stroke ( 47 ).

Conclusion on cardiovascular disease

The overall evidence indicates that a high intake of milk and dairy products, that is, 200–300 ml/day, does not increase the risk of cardiovascular disease. Specifically, there is an inverse association with risk of hypertension and stroke.

Bone health and osteoporosis

Milk and dairy products contain a number of nutrients that are required for building strong bones in childhood and for their maintenance during adulthood with the aim to reduce osteoporosis and bone fractures in older age ( 48 ). The European Commission has concluded that protein, calcium, phosphorus, magnesium, manganese, zinc, vitamin D, and vitamin K are necessary for maintaining normal bones (European Commission regulation 2012). With the exception of vitamin D, these nutrients are all present in significant amounts in milk and dairy products.

Osteoporosis has been described as a ‘paediatric disease with geriatric consequences’ as low milk, and hence, low mineral intake during childhood and adolescence has been associated with significantly increased risk of osteoporotic fractures in middle and older age, particularly in women ( 49 , 50 ). A recent study indicated that in children and adolescents, except for those with very low calcium intakes, magnesium intake may be more important than calcium in relation to bone development ( 51 ). Calcium intake was found not to be significantly associated with total bone mineral content or density, whereas intake of magnesium and the amount absorbed were key predictors of bone mass. The extent to which these results can be extrapolated to the general population is uncertain, but milk and dairy products are important sources of magnesium and hence important supporters of bone growth during adolescence. In a meta-analysis by Huncharek et al. ( 52 ), dairy products, with or without vitamin D supplementation, increased total body and lumbar spine bone mineral content in children with low baseline dairy intake, whereas no effect was found for children with a high baseline dairy intake. Thus, there may be a threshold above which increasing intake of dairy products or dairy-calcium does not additionally benefit bone mineral content or density in children.

In adults, interactions between calcium, phosphorus, protein and vitamin D reduce bone resorption and increase bone formation, thereby attenuating age-related bone loss ( 53 ). Possibly due to the complex interaction between nutrients and the multifactorial nature of bone fractures, it has been difficult to establish whether or not a low intake of milk and dairy in adulthood increases the risk of osteoporosis and bone fractures. Hence, to date, meta-analyses have not supported a protective effect of milk and dairy intake in adulthood on risk of osteoporosis and bone fractures ( 54 , 55 ). Nevertheless a recent systematic review concluded that calcium and dairy are important contributors to bone health in adults ( 56 ).

In the 2015–2020 Dietary Guidelines for Americans, it was stated that ‘Healthy eating patterns include fat-free and low-fat (1%) dairy, including milk, yoghurt, cheese, or fortified soy beverages (commonly known as “soymilk”). Those who are unable or choose not to consume dairy products should consume foods that provide the range of nutrients generally obtained from dairy, including protein, calcium, potassium, magnesium, vitamin D, and vitamin A (e.g. fortified soy beverages)’. Although the focus is on achieving the nutrient requirements by foods rather than supplements, plant-based beverages typically contain inorganic chemical forms of calcium, which may actually increase cardiovascular risk ( 56 , 57 ). As calcium in dairy is organic, milk and dairy products should still be considered the superior sources of calcium ( 58 ). Yet, future studies need to address whether or not vitamin D fortification of dairy products is crucial for these to have a positive effect on bone fracture risk.

Conclusion on bone health and osteoporosis

The present evidence suggests a positive effect of milk and dairy intake on bone health in childhood and adolescence, but with only limited evidence on bone health in adulthood and on the risk of bone fractures in older age.

In population studies, dairy has been associated positively and negatively with various cancers, but most have been based on limited evidence and very few findings remain robust. Dairy products contain a variety of bioactive compounds that could exert both positive and negative effects on carcinogenesis. The positive effects may be related to the content of calcium, lactoferrin, and fermentation products, whereas the negative effects could be linked to the content of insulin-like growth factor I (IGF-1) ( 59 ). The World Cancer Research Fund (WCRF) continuously and systematically reviews the evidence on diet and physical activity in relation to prevention of cancer, and specific areas are updated when new evidence has emerged.

Colorectal cancer is the second most common cause of death among cancers in developed countries. Even though colorectal tumourigenesis is a complex process, epidemiological and experimental data indicate that milk and dairy products have a chemopreventive role in the pathogenesis. In the 2011 WCRF report on colorectal cancer, it was concluded that consumption of milk and calcium probably reduces the risk of this cancer ( 60 ). Likewise, in meta-analyses, dairy intake has consistently been associated with a decreased risk of colorectal cancer ( 61 , 62 ) and colon cancer ( 63 ). The most recent meta-analysis by Ralston et al. ( 64 ) reported 26% lower colon cancer risk in males consuming 525 g of milk per day, whereas no association was found in females.

The link between dairy intake and colorectal cancer is considered to be mainly due to the calcium derived from dairy, with a 24% risk reduction with a dairy-calcium intake of 900 mg/day ( 65 ). The proposed mechanisms behind this are calcium binding to secondary bile acids and ionised fatty acids, thereby reducing their proliferative effects in the colorectal epithelium ( 66 ). Also, calcium may influence multiple intracellular pathways leading to differentiation in normal cells and apoptosis in transformed cells ( 67 ). Accordingly, a number of studies have reported reduced cell proliferation in the colon and rectum with intake of calcium and dairy products ( 68 – 72 ).

In the 2010 WCRF report on breast cancer, it was concluded that the evidence for dairy intake and risk of breast cancer is non-conclusive ( 73 ). In accordance with a meta-analysis from 2011 on prospective cohort studies ( 74 ), a recent meta-analysis by Zang et al. ( 75 ), however, suggested that a high (>600 g/d) and modest (400–600 g/d) dairy intake was associated with a reduced risk of breast cancer (10% and 6%, respectively) compared with a low dairy intake (<400 g/d). Within dairy subgroups, particularly yoghurt and low-fat dairy were found to be inversely associated with the risk of developing breast cancer. As calcium and vitamin D supplementation was previously shown to reduce risk of breast cancer in the Women's Health Initiative ( 76 ), these nutrients could be involved in the underlying mechanisms.

According to the 2014 WCRF report on prostate cancer, dairy may be associated with a limited-suggestive increased risk of prostate cancer, but the current evidence is limited ( 77 ). However, this conclusion was substantiated by the most recent meta-analysis by Aune et al. ( 78 ), which suggested that a high intake of dairy products, milk, low-fat milk, cheese, and calcium were associated with a 3–9% increased risk of prostate cancer. The mechanism behind this was suggested to be an increased circulating concentration of IGF-1, which has been previously shown to be associated with an increased prostate cancer risk ( 79 ).

The 2015 WCRF report on bladder cancer suggested that the evidence for milk and dairy on bladder cancer risk was inconsistent and inconclusive ( 80 ). Two meta-analyses on milk intake and bladder cancer risk have suggested a decreased risk of bladder cancer with a high intake of milk ( 61 , 81 ). Others have found no association between milk and dairy intake and risk of bladder cancer risk ( 82 ), but none have suggested an adverse effect.

Of the cancer types for which the associations with dairy intake were not presented in the WCRF reports, recent meta-analyses have suggested no association between dairy intake and risk of ovarian cancer ( 83 ), lung cancer ( 84 , 85 ), or pancreatic cancer ( 86 ) and an inverse association between dairy intake and risk of gastric cancer in Europe and the United States ( 87 ).

Studies in lactose-intolerant individuals

In a limited number of subjects, potential differences in cancer risk and mortality between lactose-tolerant and lactose-intolerant individuals (self-reported or assessed by polymorphisms for the lactase gene) have been reported under the assumption that lactose-intolerant individuals consume less milk. However, there may also be other differences between these two groups that need to be taken into consideration, for example, genetics, ethnicity, other dietary habits, smoking, physical activity, and socio-economic factors.

Bácsi et al. ( 88 ) examined the role of genetically determined differences in the ability to degrade lactose and showed that subjects with deficiencies in the genes coding for lactase (i.e. subjects not drinking milk due to intolerance) had an increased risk of colorectal cancer. This supports the ability of dairy products to reduce colorectal cancer risk and the causality of this relation. In the European EPIC study, the hypothesis that the genetically determined lactose tolerance was associated with elevated dairy product intake and increased prostate cancer risk was examined ( 89 ). The study included 630 men with prostate cancer and 873 matched control participants. Dairy product consumption was assessed by diet questionnaires, and intake of milk and total dairy products varied significantly by lactase genotype, with an almost twofold higher intake in lactose-tolerant compared to lactose-intolerant subjects. However, the lactase variant was not found to be significantly associated with prostate cancer risk. This indicates that residual confounding may have biased the associations observed between milk and dairy intake and prostate cancer risk in the observational studies included in a previous meta-analysis ( 78 ).

Ji et al. ( 90 ) investigated Swedish subjects with self-reported lactose intolerance and found a lower risk of lung, breast, and ovarian cancers compared to lactose-tolerant subjects. Unfortunately, no information about milk intake, or other genetic, ethnic, lifestyle (diet, smoking and physical activity), and behavioural characteristics were reported. Also, self-reported lactose intolerance may not be comparable to genetically determined lactose intolerance. Due to potential bias in the design and the lack of control for known confounders, it is impossible to conclude about the relationship with dairy intake. Also, these findings are in contrast with the additional literature suggesting no or an inverse association between dairy intake and risk of breast cancer ( 74 , 75 ), ovarian cancer ( 83 , 91 ), and lung cancer ( 84 , 85 ).

Conclusion on cancer

According to WCRF reports and the latest meta-analyses, consumption of milk and dairy products probably protects against colorectal cancer, bladder cancer, gastric cancer, and breast cancer. Dairy intake does not seem to be associated with risk of pancreatic cancer, ovarian cancer, or lung cancer, whereas the evidence for prostate cancer risk is inconsistent. In women, dairy offers significant and robust health benefits in reducing the risk of the common and serious colorectal cancer and, possibly, also the risk of breast cancer. In men, the benefit of the protective effect of milk and dairy on the common and serious colorectal cancer is judged to outweigh a potentially increased risk of prostate cancer.

All-cause mortality

In medical research, the term ‘all-cause mortality’ implies all causes of death. There are many individual studies reporting that a high consumption of milk and dairy products is associated with decreased mortality ( 92 ), unchanged mortality ( 93 ), or even increased mortality ( 94 ). However, based on meta-analyses of observational cohort studies, there is no evidence to support the view that milk and dairy product intake is associated with all-cause mortality ( 45 , 95 ). In a meta-analysis, O'Sullivan et al. ( 45 ) studied whether intake of milk and dairy products as food sources of saturated fat was related to all-cause mortality, cancer mortality, and cardiovascular mortality. Neither total dairy intake nor intake of any specific dairy products was found to be associated with all-cause mortality. In the most recent meta-analysis including 12 observational studies of milk intake and mortality, there were no consistent associations between milk intake and all-cause or cause-specific mortality ( 95 ).

Conclusion on all-cause mortality

The evidence from observational studies confirms that there is no association between consumption of milk and dairy products and all-cause mortality.

Comparison of nutrient content and health aspects of milk and plant-based drinks

In recent decades, the market for milk and dairy substitute drinks based on, for example, soy, rice, oats, or almonds has expanded, and calcium-fortified plant-based drinks have become part of the nutrition recommendations as alternatives to milk in several countries, such as the United States, Sweden, Australia, and Brazil. Among the plant-based milk substitutes, soy drink dominates the market in the Western world, but the emerging of other plant-based drinks has influenced the market for soy drink ( 96 ).

The nutrient density of plant-based milk substitutes varies considerably between and within types, and their nutritional properties depend on the raw material used, the processing, the fortification with vitamins and minerals, and the addition of other ingredients such as sugar and oil. Soy drink is the only plant-based milk substitute that approximates the protein content of cow's milk, whereas the protein contents of the drinks based on oat, rice, and almonds are extremely low, and the recent review of Mäkinen et al. ( 96 ) emphasises the importance of consumer awareness of such low-protein contents. Moreover, there are now cases of severe nutritional deficiencies in children being reported as a result of inappropriate consumption of plant-based drinks ( 97 , 98 ).

Despite the fact that most of the plant-based drinks are low in saturated fat and cholesterol, some of these products have higher energy contents than whole milk due to a high content of oil and added sugar. Some plant-based drinks have a sugar content equal to that of sugar-sweetened beverages, which have been linked to obesity, reduced insulin sensitivity ( 99 ), increased liver, muscle, and visceral fat content as well as increased blood pressure, and increased concentrations of triglyceride and cholesterol in the blood ( 100 , 101 ). Analyses of several commercially available plant-based drinks carried out at the Technical University of Denmark showed a generally higher energy content and lower contents of iodine, potassium, phosphorus, and selenium in the plant-based drinks compared to semi-skimmed milk ( 102 ). Also, rice drinks are known to have a high content of inorganic arsenic, and soy drinks are known to contain isoflavones with oestrogen-like effects. Consequently, The Danish Veterinary and Food Administration concluded that the plant-based drinks cannot be recommended as full worthy alternatives to cow's milk ( 102 ), which is consistent with the conclusions drawn by the Swedish National Food Agency ( 103 ).

The importance of studying whole foods instead of single nutrients is becoming clear as potential nutrient–nutrient interactions may affect the metabolic response to the whole food compared to its isolated nutrients. As the plant-based drinks have undergone processing and fortification, any health effects of natural soy, rice, oats, and almonds cannot be directly transferred to the drinks, but need to be studied directly. Only a few studies have compared the effects of cow's milk with plant-based drinks as whole foods on disease risk markers ( 104 – 108 ). However, none of these have included commercially available drinks or disease endpoints. Therefore, the evidence is currently insufficient to conclude that plant-based drinks possess health benefits above those of milk and dairy products. Until more research has been conducted and a scientifically sound conclusion can be drawn, health authorities should be cautious about recommending plant-based drinks as acceptable substitutes to cow's milk for the general population.

Conclusion on nutrient content and health aspects of milk and plant-based drinks

Cow's milk and plant-based drinks are completely different products, both regarding nutrient content and presumably also health effects. Although there are concerns about children consuming the low-protein drinks, further evidence-based assessment of the nutritional and health value of the plant-based drinks must await more studies in humans.

Answers to the key questions

Key question 1: For the general consumer, will a diet with milk and dairy products overall provide better or worse health, and increase or decrease risk of major diseases and all-cause mortality than a diet with no or low content of milk and dairy products?

Consumption of dairy products is associated with an overall reduced risk of cardiometabolic diseases and some cancers, whereas only very few adverse effects have been reported ( Fig. 1 ). Dairy products may therefore have the potential to reduce the burden of the most prevalent chronic diseases in the population and to substantially reduce the health care costs for society ( 109 ). Consumption of dairy products is part of the dietary recommendations in several nations, for example, Sweden, Denmark, and United States. A general recommendation to reduce the intake of dairy products in individuals who actually tolerate them may be counterproductive for health and could therefore increase health care expenses. However, more emphasis should be on the foods which dairy replaces in the diet. In addition, as most of the conducted meta-analyses are on observational data, residual confounding cannot be ruled out, and it is also possible that milk and dairy intake in these studies could be just a marker of diets of higher nutritional quality.

Overall effect/association between dairy product intake and health outcomes. ↓ favourable effect/association; ↑adverse effect/association; → no effect/association.

Key question 2: Is it justified to recommend the general lactose-tolerant population to avoid the consumption of milk and dairy products?

In the Nordic countries, as few as 2% of the population has primary lactase deficiency and can be classified as lactose-intolerant individuals ( 110 ). Yet, most lactose-intolerant adults can tolerate one glass of milk or a scoop of ice cream. Cheeses have negligible lactose contents, and the lactose in yoghurt is digested more efficiently than other dairy sources due to the bacterial lactase present in yoghurt which facilitates lactose digestion ( 111 ). Therefore, fermented dairy products, that is, yoghurt and most cheeses (cottage cheese, as well as soft and hard cheeses), can be tolerated by lactose-intolerant individuals without symptoms ( 111 , 112 ).

The same applies to cow's milk protein allergy that typically occurs in 0.1–2.0% of children in the Nordic countries and Europe ( 113 ). Among children with verified cow's milk-specific IgE who were re-evaluated 1 year after diagnosis, 69% tolerated cow's milk at re-evaluation ( 114 ). Thus, the condition is generally seen to resolve in children. To warn the general population against dairy consumption based on rare milk allergies would be equivalent to warn against foods, such as peanuts or seafood due to the fact that a small subset of the population is allergic to these foods.

Key question 3: Is there scientific evidence to substantiate that replacing milk and dairy products with plant-based drinks will improve health?

Cow's milk and plant-based drinks are not nutritionally comparable foods. As only a few studies have investigated the health effects of replacing cow's milk with plant-based drinks and none have focused on commercially available drinks or on disease endpoints, the effect of this replacement can only be speculated on. There have, however, been individual cases reporting illness in children consuming low-protein plant-based drinks, but an evidence-based final assessment of the health value of plant-based drinks compared to cow's milk must await more studies in humans.

Overall conclusions regarding intake of milk and dairy products and health

Our review of the totality of available scientific evidence supports that intake of milk and dairy products contributes to meeting nutrient recommendations and may protect against the most prevalent, chronic non-communicable diseases, whereas very few adverse effects have been reported.

Conflicts of interest and funding

Tanja Kongerslev Thorning has no conflicts of interest to declare. Anne Raben is recipient of research funding from the Dairy Research Institute, Rosemont, IL, USA and the Danish Agriculture & Food Council.Tine Tholstrup is recipient of research grants from the Danish Dairy Research Foundation and the Dairy Research Institute, Rosemont, IL. The sponsors had no role in design and conduct of the studies, data collection and analysis, interpretation of the data, decision to publish, or preparation of the manuscripts. Sabita S. Soedamah-Muthu received funding from the Global Dairy Platform, Dairy Research Institute and Dairy Australia for meta-analyses on cheese and blood lipids and on dairy and mortality. The sponsors had no role in design and conduct of the meta-analyses, data collection and analysis, interpretation of the data, decision to publish, or preparation of the manuscripts. Ian Givens is recipient of research grants from UK Biotechnology and Biological Sciences Research Council (BBSRC), UK Medical Research Council (MRC), Arla Foods UK, AAK-UK (both in kind), The Barham Benevolent Foundation, Volac UK, DSM Switzerland and Global Dairy Platform. He is a consultant for The Bio-competence Centre of Healthy Dairy Products, Tartu, Estonia, and in the recent past for The Dairy Council (London). Arne Astrup is recipient of research grants from Arla Foods, DK; Danish Dairy Research Foundation; Global Dairy Platform; Danish Agriculture & Food Council; GEIE European Milk Forum, France. He is member of advisory boards for Dutch Beer Knowledge Institute, NL; IKEA, SV; Lucozade Ribena Suntory Ltd, UK; McCain Foods Limited, USA; McDonald's, USA; Weight Watchers, USA. He is a consultant for Nestlé Research Center, Switzerland; Nongfu Spring Water, China. Astrup receives honoraria as Associate Editor of American Journal of Clinical Nutrition , and for membership of the Editorial Boards of Annals of Nutrition and Metabolism and Annual Review of Nutrition . He is recipient of travel expenses and/or modest honoraria (<$2,000) for lectures given at meetings supported by corporate sponsors. He received financial support from dairy organisations for attendance at the Eurofed Lipids Congress (2014) in France and the meeting of The Federation of European Nutrition Societies (2015) in Germany.