Nonlinear relationship between phenotypic age acceleration and testosterone deficiency in the US population: A cross-sectional NHANES study

Abstract Objective This study aims to assess the relationship between Phenotypic age acceleration (PhenoAgeAccel) and testosterone deficiency (TD) in US male, using National Health and Nutrition Examination Survey (NHANES) data from 2015 to 2016. Methods This study explored the relationship between PhenoAgeAccel and TD by analyzing a sample reflecting the male population of the United States (n = 1,402; NHANES 2015–2016). Phenotypic age (PA) is calculated using nine blood-based biomarkers. PhenoAgeAccel was calculated by extracting the residuals and regressing the phenotypic age on the chronological age (CA). TD was defined as serum testosterone levels below 300 ng/dL, in accordance with the criteria set forth by the AUA. This research used multivariable logistic models to examine the connection between PhenoAgeAccel and TD. Additionally, it included subgroup and interaction analyses to assess variations among different groups. Smoothed curve fitting and generalized additive modelling (GAM) were also employed to analyze the data further. Results The study included 1,402 subjects, with 293 diagnosed with TD and 1,109 without. The weighted multivariate logistic regression model indicated an 8% higher probability of TD for each unit increase in PhenoAgeAccel (OR: 1.08, 95% CI: 1.05–1.11) after accounting for all covariates. Subgroup analysis outcomes were uniform across various categories, demonstrating a significant positive relationship between PhenoAgeAccel and TD. Interaction tests showed that the positive link between PhenoAgeAccel and TD remained consistent with all interaction P-values exceeding 0.05. Also, a non-linear relationship between PhenoAgeAccel and TD was discovered, with a progressive increase in the risk of TD with elevated PhenoAgeAccel, exhibiting a J-shaped curve (inflection point: -9.26, p < 0.05). Conclusions Our study suggests that an increase in PhenoAgeAccel may be correlated with a heightened likelihood of developing TD. Consequently, PhenoAgeAccel could potentially serve as a valuable biomarker for the early identification of individuals at risk of TD, with implications for clinical management and public health nutrition strategies.