Red meat consumption in higher healthy eating index diets is associated with brain health critical nutritional adequacy, and fecal microbial diversity

Individuals consuming high HEI-diet, regardless of red meat intake, maintained healthy BMI

Participants in the HH-R group were older with a mean age of 55.47 ± 13.92 years, marginally higher than those in the HH-NR group, who had a mean age of 53.10 ± 15.14 years (p < 0.05). In the low-HEI groups, LH-R participants averaged 52.88 ± 13.95 years, compared to 50.59 ± 14.07 years in LH-NR (p < 0.05, Fig. 2). Participants in the HH-R group had a higher mean BMI (23.76 ± 3.73 kg/m²) compared to those in the HH-NR group (22.98 ± 4.08 kg/m², p = 0.001). In the low-HEI groups, LH-R group also had a higher mean BMI (25.17 ± 4.91) compared to LH-NR (23.80 ± 5.34, p < 0.001). High-HEI participants collectively had lower BMI than low-HEI groups (p < 0.001), with only the LH-R group exceeding recommended BMI thresholds. Additionally, while female participants outnumbered males in all diet groups, high-HEI groups showed a similar sex distribution regardless of red meat consumption (34.9% male in HH-NR vs 36.7 in HH-R, Fig. 2). Higher imbalances appeared between low groups.

Age, BMI, and weight by diet quality and red meat intake. The bar graph illustrates the mean (± SD) values for age, BMI, and weight in the following groups: high-HEI (≥ 80) with red meat (HH-R), high-HEI without red meat (HH-NR), low-HEI (< 80) with red meat (LH-R), and low-HEI without red meat (LH-NR). Statistical significance is based on t-tests, denoted by asterisks: *p < 0.05, **p < 0.01, ***p < 0.001.

High-HEI diets, with or without red meat, preserve healthier macronutrient profiles

Among individuals adhering to high-HEI diets, macronutrient profiles were distinct between red meat consumers and non-consumers (Fig. 3). Energy intake did not differ significantly (p = 0.24) between the HH-R group (1838.69 ± 558.03 kcal) and the HH-NR group (1791.3 ± 630.52 kcal). Whereas energy intake was significantly higher in the LH-R group (1910.72 ± 769.58 kcal) compared to the LH-NR group (1688.45 ± 685.19 kcal, p < 0.001). Total carbohydrate intake was lower among red meat consumers (HH-R: 187.24 ± 62.63 g; LH-R: 162.57 ± 90.43 g) compared to non-consumers (HH-NR: 195.6 ± 74.22 g; LH-NR: 172.86 ± 87.7 g; both, p < 0.05), though all the values were within the acceptable macronutrient distribution ranges for carbohydrates. The protein intake on the other hand was higher (p < 0.001) in both HH-R (77.58 ± 26.84 g) and LH-R (80.74 ± 35.8 g) compared to HH-NR (67.35 ± 26.85 g) and LH-NR (62.99 ± 29.56 g), suggesting the contribution of red meat. Dietary fiber intake across all four groups was below adequate intake level of 25-38 g/day. Both red meat groups had lower fiber intake: HH-R (21.87 ± 8.99 g) and LH-R (17.6 ± 11.17 g) compared to HH-NR (24.78 ± 11.45 g) and LH-NR (19.24 ± 11.89 g); however, HH-R still exceeded both Low-HEI groups. Saturated fatty acid consumption was different between groups: in the high-HEI group, HH-R (19.88 ± 8.32 g) had significantly higher saturated fatty acid intake (p < 0.001) than HH-NR: 16.89 ± 8.84 g, corresponding to 9.73% vs. 8.49% of total calories—both remained below the DGA threshold of 10%. This suggests that red meat inclusion in overall high-quality diets does not inherently exceed SFA recommendations. By contrast, in the low-HEI group, LH-R (28.69 ± 14.76 g; 13.51% of calories) and LH-NR (20.67 ± 12.77 g; 11.02% of calories), both exceeded this 10% recommendation threshold. While LH-NR’s intake represents a modest improvement overall, both low-HEI groups remain at higher SFA consumption than DGA recommendations.

A lollipop plot showing differential nutrient intake associated with red meat consumption in High- and Low- HEI diets. Lollipop chart illustrating log₂ fold changes (FC) in macro- and micronutrient intakes between red meat consumers and non-consumers, stratified by diet quality (high-HEI [blue] vs. low-HEI [red]). Fold differences were capped at ± 0.5 for visualization clarity. Lollipops extending to the left denote reduced nutrient intake in consumers, while those to the right indicate increased intake relative to non-consumers. Dot size corresponds to the -log₁₀(p-value), with larger dots representing greater statistical significance (p < 0.05). HEI healthy eating index.

Inclusion of red meat in a diet improves micronutrient adequacy

In both the high- and low-HEI categories, participants consuming red meat consistently demonstrated higher intakes of some brain-health critical micronutrients than their non-red-meat counterparts (Fig. 3). Vitamin B12 levels among red meat consumers (5.04 ± 2.91 mcg in HH-R; 5.55 ± 4.35 mcg in LH-R) exceeded those of non-consumers (3.63 ± 2.96 mcg in HH-NR; 3.45 ± 3.24 mcg in LH-NR). The higher absolute intake also translated to a much greater proportion meeting the Estimated Average Requirement (EAR)—over 93% in both red meat groups (HH-R and LH-R) compared to just 65–71% of non-consumers (Figure S2). Zinc intake followed a similar pattern, with red meat groups (11.82 ± 5.06 mg in HH-R; 11.22 ± 5.36 mg in LH-R) exceeding non-consumers (10.65 ± 5.08 mg in HH-NR; 8.93 ± 4.35 mg in LH-NR). Higher percentage of participants in the red meat groups meeting the EAR (HH-R: 84.9%; LH-R: 72.0%) than in the non-red meat groups (HH-NR: 71.9%; LH-NR: 61.6%). Selenium intake ranged from 114.27 ± 40.28 mcg (HH-R) to 112.03 ± 52.79 mcg (LH-R), compared to 100.89 ± 44.39 mcg (HH-NR) and 90.48 ± 48.33 mcg (LH-NR) While selenium adequacy was high for all participants, red meat groups still showed the highest proportion meeting the EAR, with over 97% achieving the threshold. Calcium levels were below the recommended levels, but the HH-R group (994.74 ± 447.68 mg) came closest overall. Vitamin D intake was significantly higher among red meat consumers, but remained below the recommended level as well as the EAR in all groups. On the other hand, while over 79% of the high-HEI consumers (HH-R) and 64% of the low-HEI consumers (LH-R) meeting the EAR, folate intake was lower in both the high-HEI with red meat group (519.86 ± 244.14 mcg) and the low-HEI with red meat group (457.38 ± 218.98 mcg) compared to the high-HEI without red meat (549.01 ± 270.5 mcg) and low-HEI without red meat (488.75 ± 238.45 mcg) groups. Importantly, despite higher intakes of certain nutrients in the red meat groups, consumption remained safely below the Tolerable Upper Intake Level (UL) for virtually all participants. Less than 3% of any group exceeded the UL for calcium or zinc. Overall, the findings suggest that integrating red meat into a high-HEI diet elevates intake of some micronutrients essential for cognitive and mental health and increases the probability of meeting or exceeding the EAR level.

Higher HEI scores associated with reduced mental and neurodevelopmental disorders, independent of red meat intake

Higher HEI scores showed inverse association with the prevalence of nearly all mental health and neurodevelopmental disorders examined (Table 1). Higher HEI scores were significantly associated with reduced log odds of depression (log odds = −2.22, p < 0.001), bipolar disorder (log odds = −5.903, p < 0.001), PTSD (log odds = −3.80, p < 0.001), and migraines (log odds = -1.47, p < 0.001). Within individuals with high HEI scores, depression prevalence was 9.8% (36/367) in HH-NR vs 10.8% (42/388) in HH-R and the difference was not statistically significant. Similarly, red meat consumption was not associated with statistically significant differences in the prevalence of bipolar disorders, PTSD, non-specified mental illnesses, and migraines. These findings suggest that adherence to a high-quality diet is important for mental health disorders, but the impact may be largely independent of red meat consumption. In the analysis of neurodevelopmental conditions, a higher HEI score was significantly associated with lower odds of attention deficit disorder/attention-deficit/hyperactivity disorder (log odds = −3.4042, p < 0.001 and autism spectrum disorder diagnoses (log odds = −4.7185, p =  < 0.001). Red meat consumption showed a borderline significant increase in attention deficit disorder/attention-deficit/hyperactivity disorder odds (log odds = 0.6648, p = 0.07584), it did not significantly affect autism spectrum disorder risk (p = 0.89). These findings raise the possibility of reverse causality, which means neurodevelopmental conditions may influence dietary patterns, complicating the ability to maintain high quality diets. The cross-sectional nature of the data limits us from making temporal interpretations and observed associations could reflect the adaptations that is secondary to the mentioned conditions.

Red meat with a high-HEI diet preserves favorable microbial phyla profile

At the phylum level, HH-R (6.3) had the highest phylum diversity among the four groups and LH-NR (5.83) had the lowest. HH-NR, HH-R, and LH-R (6.2) all had a significantly higher mean diversity compared to LH-NR group (5.83, p < 0.01) (Fig. 4a). Similar outcome was also observed when using Shannon diversity measures (Fig. 4a). Among major phyla, Firmicutes showed the highest abundance across all groups, with a mean abundance of 36.59%. Proteobacteria was the second most abundant phylum overall (31.48%), with the highest levels observed in the HH-NR group (36.59%) and the lowest in the LH-R group (27.61%). Bacteroidetes followed as the third most abundant phylum, with relatively stable levels across groups. Regarding differences, Actinobacteria showed significantly lower relative abundance in the HH-R compared with the HH-NR group (p = 0.02); Bacteroidetes was significantly higher in the LH-R relative to the HH-R (p = 0.016); Firmicutes was lower in the LH-NR than the HH-NR (p = 0.038) and higher in LH-R than LH-NR (p = 0.0018) (Fig. 4b). At the OTU level, No difference was observed within the High-HEI groups as HH-R and HH-NR were not different for both alpha diversity and Shannon index measures. However, at the Low-HEI levels, both metrics of alpha diversity were significantly higher in LH-R compared to LH-NR (Fig. 4c).

Alpha diversity and relative abundance of microbial communities across dietary groups. (A) Phylum-level alpha diversity: Boxplots of phylum richness (left) and Shannon diversity index (right) across dietary groups. Significant differences were assessed using Kruskal–Wallis tests (B) Alpha diversity at the OTU level, represented by OTU richness (left) and Shannon diversity index (right), highlighting additional diversity patterns among groups. (C) Stacked bar plots of dominant bacterial phyla, showing group-specific variations in the composition. High-HEI (≥ 80) with red meat (HH-R), high-HEI without red meat (HH-NR), low-HEI (< 80) with red meat (LH-R), and low-HEI without red meat (LH-NR); Statistical significance is denoted where applicable, with group-specific comparisons annotated within the plots.

Several key bacterial species were different between the groups

No significant differences in beta-diversity composition were detected via principal coordinate analysis (PCoA) using the Jaccard dissimilarity metric (PERMANOVA, p > 0.05; Fig. 5a,b) and Bray–Curtis distance (Figure S1)When looking at the individual species, we observed several differences in the relative abundance of specific bacterial species Fig. 5c). B. adolescentis showed a significantly lower abundance in HH-R compared to HH-NR (log₂FC = −1.3957, p_adj < 0.001) as well as LH-R compared to LH-NR (log₂FC = −0.5895, p_adj < 0.001). Within the genus Bacteroides, B. caccae was significantly higher in HH-R compared to HH-NR (log₂FC = 0.7457, p_adj = 0.003), with no significant differences observed between low-HEI groups. B. eggerthii showed a consistent and significantly lower abundance across both: HH-R (log₂FC = −1.0163, p_adj < 0.001), LH-R (log₂FC = −0.5337, p_adj < 0.001), and overall (log₂FC = -0.6174, p_adj < 0.001). Similarly, B. fragilis was less abundant in HH-R (log₂FC = −0.8234, p_adj = 0.003) compared to HH-NR but showed no significant changes in low groups. And B. ovatus showed a significantly lower abundance in both HH-R (log₂FC = −0.5306, p_adj = 0.009) compared to HH-NR and LH-R (log₂FC = −0.3134, p_adj = 0.001) compared to LH-NR. Furthermore, within the genus Blautia, both B. obeum and B. producta were significantly less abundant among the red meat consumers across all comparisons. B. obeum was lower in HH-R (log₂FC = −0.6163, p_adj < 0.001) and LH-R (log₂FC = −0.1856, p_adj = 0.017). Similarly, B. producta was lower in HH-R (log₂FC = −0.4692, p_adj = 0.021), LH-R (log₂FC = −0.8112, p_adj < 0.001). Butyricoccus pullicaecorum was another species that showed significantly less abundance across all comparisons: HH-R (log₂FC = −0.6036, p_adj = 0.001) and LH-R (log₂FC = −0.3479, p_adj < 0.001).

Microbial community composition and differential abundance across dietary groups. (A) Principal Coordinate Analysis (PCoA) plot at the genus level based on the Jaccard index, illustrating microbial community clustering across dietary groups. (B) PCoA plot at the OTU level using the Jaccard index, showing distinct microbial community structures among groups. (C) Log₂ fold change (log₂FC) plot depicting differential abundance of microbial species, comparing HH-R vs. HH-NR and LH-R vs. LH-NR groups. Positive values indicate higher abundance in the red meat group, while negative values represent higher abundance in the no-red-meat group. Significant differences are annotated within the plot; high-HEI (≥ 80) with red meat (HH-R), high-HEI without red meat (HH-NR), low-HEI (< 80) with red meat (LH-R), and low-HEI without red meat (LH-NR).

Among the species from Clostridium genus, C. clostridioforme also showed a consistent lower abundance in red meat consumers: HH-R (log₂FC = -0.3864, p_adj = 0.018) and LH-R (log₂FC = −0.2290, p_adj = 0.004). Whereas C. colinum and C. ramosum both were higher significantly in HH-R (C. colinum: log₂FC = 0.5799, p_adj = 0.003; C. ramosum: log₂FC = 0.7271, p_adj = 0.001), but was lower significantly in LH-R (C. colinum: log₂FC = −0.8000, p_adj < 0.001; C. ramosum: log₂FC = -0.6078, p_adj < 0.001). C. hathewayi was higher in HH-R (log₂FC = 2.9310, p_adj < 0.001) but did not show difference between low-HEI groups. C. saccharogumia was significantly less abundant in LH-R (log₂FC = −1.1328, p_adj < 0.001) but was not statistically significant between high-HEI groups. Furthermore, C. spiroforme was lower significantly in HH-R (log₂FC = −0.4873, p_adj = 0.004), while C. symbiosum was lower in LH-R (log₂FC = −0.2484, p_adj = 0.005).

Within the genus Coprococcus, C. catus showed a significant lower abundance in HH-R compared to HH-NR (log₂FC = -0.4532, p_adj = 0.001), with no significant difference between low-HEI groups. Conversely, C. eutactus showed a significant lower abundance in LH-R (log₂FC = −0.5739, p_adj < 0.001) but not in HH-R. Among others, Dorea formicigenerans showed a significant lower abundance in HH-R (log₂FC = −0.4146, p_adj = 0.002) and not in low-HEI groups. Eggerthella lenta was consistently less abundant across all red meat consumer groups: HH-R (log₂FC = −0.6128, p_adj = 0.001), LH-R (log₂FC = -0.1946, p_adj = 0.017), and overall (log₂FC = −0.2108, p_adj = 0.003). Collinsella aerofaciens was significantly higher in red meat consumers compared to non-consumers in the overall analysis (log₂FC = 0.1489, p_adj = 0.043). Eubacterium biforme was less abundant in HH-R compared to HH-NR (log₂FC = –0.6855, p_adj = 0.003) but was significantly higher in LH-R compared to LH-NR (log₂FC = 0.2512, p_adj = 0.030). Eubacterium dolichum, was significantly less abundant among LH-R (log₂FC = −0.5451, p_adj < 0.001), while no significant difference was observed in HH-R.

Ruminococcus, Ruminococcus callidus was significantly less abundant in HH-R (log₂FC = −0.5619, p_adj = 0.010), but significantly more abundant in LH-R (log₂FC = 1.3757, p_adj < 0.001) compared to respective non-consumers. R. flavefaciens was significantly less abundant in LH-R (log₂FC =  −0.5331, p_adj < 0.001), but not in HH-R. R. gnavus was significantly less abundant in LH-R (log₂FC = −0.4056, p_adj < 0.001), but no significant difference was seen in HH-R. R. lactaris was more abundant in LH-R (log₂FC = 0.1868, p_adj = 0.046), but no significant changes were observed in HH-R, and R. torques was higher in LH-R (log₂FC = 0.8395, p_adj < 0.001), but not in HH-R.

Several other species showed differential responses to diet quality and red meat consumption, which are shown in (Fig. 5c). A few more important differences include: Roseburia faecis showed a consistent and significantly lower abundance among red meat consumers across all comparisons (p_adj < 0.001 in all comparisons). Gemmiger formicilis was significantly less abundant in HH-R (log₂FC = -0.4911, p_adj = 0.007), but no significant difference was seen in LH-R. Haemophilus parainfluenzae showed a divergent pattern: it was significantly less abundant in HH-R (log₂FC = −1.1420, p_adj < 0.001) compared to HH-NR, but significantly more abundant in LH-R (log₂FC = 0.6370, p_adj < 0.001) compared to LH-NR. Parabacteroides distasonis showed a significantly higher abundance among HH-R (log₂FC = 0.4329, p_adj = 0.018), but no significant difference was seen in LH-R. Prevotella copri was significantly less abundant in LH-R (log₂FC = -0.6686, p_adj < 0.001), but no difference was observed in HH-R. Veillonella dispar, both HH-R (log₂FC = −0.7551, p_adj = 0.007) and LH-R (log₂FC = −0.5314, p_adj < 0.001) had significantly lower abundance. Conversely, Veillonella parvula was significantly more abundant in HH-R (log₂FC = 0.5388, p_adj = 0.029) and LH-R (log₂FC = 1.6065, p_adj < 0.001).