Supplement-driven iron overload accelerates phenotypic aging via inflammatory biomarkers: Potential counteraction through anti-inflammatory or antioxidant diets

Abstract

Given the dual effects of iron on health, we carried out this study to explore its relationship with phenotypic age (PhenoAge) and to evaluate the roles of inflammation and oxidative stress in this regard. Since these associations are still poorly understood, elucidating them is vital for understanding aging-related health outcomes. A cross-sectional study was conducted using NHANES 2017-2018 data, involving 8692 participants aged 20 years or older. The nonlinear relationships between iron intake and PhenoAge acceleration (PhenoAgeAccel) were assessed using weighted restricted cubic splines (RCS). Multivariable-adjusted analyses were performed using weighted generalized linear models (GLMs). K-means clustering was employed to identify patterns of iron co-exposure. Interaction effects were assessed using likelihood ratio tests, while mediation analyses were conducted to quantify the contributions of inflammation and oxidative stress markers. This study identified a U-shaped relationship between total iron intake and PhenoAgeAccel (breakpoint: 18.441 mg/day). Below this threshold, higher iron intake was protective against aging (β = -0.126); above it, aging accelerated (β = 0.021). Notably, dietary iron derived solely from food was not associated with any harmful effects on aging. In contrast, supplemental iron intake showed a positive association with PhenoAgeAccel (β = 0.017), highlighting the potential risks of excessive supplement use. Moreover, the aforementioned associations showed no gender differences. Cluster analysis split participants into two groups: dietary iron reference (DIR), mostly below the UL (45 mg/day) with minimal supplemental iron; and supplement-driven iron overload (SDIO), all exceeding the UL, with supplemental iron comprising 83.44 % of total intake on average. SDIO showed significantly faster phenotypic aging (β = 1.774) than DIR. However, anti-inflammatory or antioxidant diets were able to counteract this detrimental effect (P for interaction = 0.025). Inflammation-related markers partially mediated SDIO-associated aging acceleration (mediation proportion: 15.53 %-25.63 %). The results stayed robust even after adjusting for variables related to anemia and post-menstrual status. This study suggests that excessive use of supplements, resulting in iron overload, may accelerate individual aging through inflammation-related pathways. Nevertheless, a diet abundant in anti-inflammatory or antioxidant properties could counteract this heightened risk of aging.

Keywords: CDAI; DII; Diet; Inflammation; Iron; PhenoAgeAccel.

Fig. 1

Flowchart of participant selection in this study. PIR, poverty-income ratio; BMI, body mass index; WC, waist circumference; PA, physical activity.

Fig. 2

RCS curves of relationships between iron intake and PhenoAgeAccel. (a) Total iron and PhenoAgeAccel in overall population; (b) Dietary iron and PhenoAgeAccel in overall population; (c) Total iron and PhenoAgeAccel stratified by gender; (d) Dietary iron and PhenoAgeAccel stratified by gender. The solid line denotes the value of β, while the shaded region illustrates the 95 % confidence interval. Fully adjusted for age, gender, race, total energy intake, HEI-2020 score, education level, PIR, marital status, BMI, waist circumference, physical activity, sedentary time, smoking, current alcohol drinking, CVD, cancer, hypertension, diabetes, and dyslipidemia.

Fig. 3

Analysis of iron co-exposure patterns in 8692 participants. (a) Heatmap depicting the correlations among total iron, dietary iron, and supplemental iron, based on Pearson correlation analysis; (b) Determination of the optimal cluster number (k) for K-means analysis using the silhouette method; (c) Visualization of K-means clustering using PCA dimensionality reduction; (d) Stratified comparison of iron source distributions between clusters. Cluster 1, SDIO group; Cluster 2, DIR group.

Fig. 4

Anti-inflammatory or antioxidant diets counteract SDIO-associated PhenoAgeAccel. (a) Associations between SDIO and PhenoAgeAccel (vs. DIR group); (b) Modulatory effects of anti-inflammatory or antioxidant diets on SDIO-related PhenoAgeAccel; (c) GO-BP enrichment analysis of overlapping targets (Top15 presented). PIPOD, Pro-inflammatory and pro-oxidative diet; AIPOD, Anti-inflammatory and pro-oxidative diet; PIAOD, Pro-inflammatory and antioxidant diet; AIAOD, Anti-inflammatory and antioxidant diet.

Fig. 5

The mediating effects and proportions of inflammatory biomarkers in the association between SDIO and PhenoAgeAccel. Fully adjusted for age, gender, race, total energy intake, HEI-2020 score, education level, PIR, marital status, BMI, waist circumference, physical activity, sedentary time, smoking, current alcohol drinking, CVD, cancer, hypertension, diabetes, and dyslipidemia. The arrow indicates promotion. ACME, average causal mediation effects; ADE, average direct effects.

Fig. 6

Stratified analyses of the associations between SDIO and PhenoAgeAccel.