Non-Alcoholic Beer Influences Glucose and Lipid Metabolism and Changes Body Composition in Healthy, Young, Male Adults

Abstract

Background and Aims: Non-alcoholic beers (NABs) are gaining popularity as alternatives to alcoholic beverages, yet their metabolic and health effects compared to no consumption of these drinks remain unclear. Material and Methods: The investigator-blinded, single-center, randomized study compares the effects on the metabolism, health, and gut microbiome of the daily consumption of different NABs-pilsener, mixed beer, and wheat beer-on glucose and fat metabolism, body composition, and liver function in 44 healthy young men. The participants consumed 660 mL of one of these beers or water daily for 4 weeks. We measured indicators of glucose and lipid metabolism, liver enzymes, body composition, and the composition of the gut microbiota. Results: The findings revealed that mixed beer increased fasting glucose and triglycerides, and wheat beer increased insulin, C-peptide, and triglycerides. The intake of pilsener and water decreased cholesterol and LDL levels without significantly affecting glucose metabolism. Biomarkers of liver damage such as M30 lowered in water and pilsener, while ALT and AST lowered in mixed beer. The pattern of the gut microbiota also changed, as pilsener lowered Firmicutes and increased Actinobacteria. Conclusions: In summary, consumption of NABs, especially mixed and wheat beers, exerts an unfavorable metabolic impact on glucose and fat, while pilsener and water are more favorable from a metabolic perspective. We concluded that the metabolic alterations seen are probably due to the caloric and sugar content in NABs, rather than polyphenols. The chronic effects of NABs on health should be evaluated in future studies.

Keywords: fat metabolism; glucose metabolism; liver; microbiome; non-alcoholic beer.

Figure 1

Non-alcoholic beer consumption alters glucose and lipid metabolism in healthy, young men. Markers of glucose and fat metabolism were measured in healthy young men at baseline and after 4 weeks consumption of 660 mL daily of either pilsener (PI; n = 11), wheat beer (WB; n = 11), or mixed beer (MB; n = 10). Water consumption (WA; n = 12) was included as a control group. Estimated marginal means and error bars (95% confidence interval) are plotted in in the foreground and raw data are plotted in the background. Significance was calculated using two-way repeated measures ANOVA. Significant difference between time points using pairwise comparison of estimated marginal means is marked in the plot (* p < 0.05; ** p < 0.01). (A) Insulin (WA: p = 0.58, PI: p = 0.36, WB: p = 0.014, MB: p = 0.36), (B) C-peptide (WA: p = 0.68, PI: p = 0.81, WB: p = 0.134, MB: p = 0.14), (C) fasting glucose (WA: p = 0.99, PI: p = 0.44, WB: p = 0.24, MB: p = 0.027), (D) HbA1c (WA: p = 0.08, PI: p = 0.0016, WB: p = 1, MB: p = 0.15), (E) triglycerides (WA: p = 0.52, PI: p = 0.23, WB: p = 0.32, MB: p = 0.32), (F) cholesterol (WA: p = 0.65, PI: p = 0.24, WB: p = 0.91, MB: p = 0.2), (G) LDL cholesterol (WA: p = 0.77, PI: p = 0.49, WB: p = 0.8, MB: p = 0.12), and (H) HDL cholesterol (WA: p = 0.05, PI: p = 0.7, WB: p = 0.37, MB: p = 0.78). LDL = low-density lipoprotein and HDL = high-density lipoprotein.

Figure 2

Non-alcoholic beer consumption alters liver damage markers and changes body composition. Markers of liver damage were measured, and bioelectrical impedance analysis (BIA) was performed in healthy young men at baseline and after 4 weeks. Estimated marginal means and error bars (95% confidence interval) are plotted in the foreground and raw data are plotted in the background. Significance was calculated using two-way repeated measures ANOVA. Significant difference between time points using pairwise comparison of estimated marginal means is marked in the plot (* p < 0.05). (A) M30 (WA: p = 0.0162, PI: p = 0.0373, WB: p = 0.9563, MB: p = 0.69), (B) ALT (WA: p = 0.11, PI: p = 0.46, WB: p = 0.82, MB: p = 0.03), (C) AST (WA: p = 0.31, PI: p = 0.24, WB: p = 0.78, MB: p = 0.013), (D) FAST (WA: p = 0.075, PI: p = 0.086, WB: p = 0.77, MB: p = 0.032), (E) Body fat (WA: p = 0.24, PI: p = 0.076, WB: p = 0.0026, MB: p = 0.21), (F) BCM (WA: p = 0.58, PI: p = 0.52, WB: p = 0.1, MB: p = 0.23), and (G) BCM ECM Ratio. ALT = alanine transaminase, AST = Aspartate transaminase, FAST = Fibroscan-AST Score, and BCM = body cell mass.

Figure 3

Non-alcoholic beer consumption changes alpha diversity and alters microbiota composition at the phyla level. Fecal samples were collected at baseline and after 4 weeks. Significance was calculated with Wilcoxon signed rank test on paired samples (* p < 0.05; ** p < 0.01; *** P < 0.001) (A–C) We detected 7237 species among all groups. Microbial diversity based on the (A) Shannon, (B) Chao 1, and (C) inverse Simpson indices. (D) Relative abundance of bacteria per group and time point summarized at the phylum level.

Figure 4

Non-alcoholic beer consumption changes microbiota composition on the genera level. Fecal samples were collected at baseline and after 4 weeks. Significance was calculated with Wilcoxon signed rank test on paired samples (* p < 0.05; ** p < 0.01; *** p < 0.001). (A) Relative abundance of bacteria per group and time point summarized at the genera level. Relative abundance for (B) Firmicutes, (C) Actinobacteriota, (D) Bifidobacterium, and (E) Bacteroides at baseline and after 4 weeks for each group. WA = water, PI = pilsener, WB = wheat beer, and MB = mixed beer.

Figure 5

Changes in the parameters are clustered differently among groups. For each included parameter, the difference between week 4 and baseline was calculated and correlated with each other separately for each group ((A): Water, (B): pilsener, (C): wheat beer, (D): mixed beer) using Pearson’s correlation and hierarchical clustering (* p < 0.05; ** p < 0.01; *** p < 0.001). Clusters indicate similarity of changes in the parameter per group. B/F ratio: Bacteroides–Firmicutes ratio, BCM: body cell mass, CAP: controlled attenuation parameter, E: liver stiffness, HDL: high-density lipoprotein, LDL: low-density lipoprotein, and TG: triglycerides.