# Predictive model of sperm DNA fragmentation in infertile men based on lifestyle factors

## TL;DR

This study developed a predictive model to identify infertile men at risk of high sperm DNA fragmentation based on lifestyle factors like age, BMI, and stress.

## Contribution

A validated nomogram incorporating six modifiable lifestyle factors for predicting abnormal sperm DNA fragmentation in infertile men.

## Key findings

- Six lifestyle factors (age, BMI, smoking, hot spring bathing, stress, and exercise) were identified as predictors of abnormal DFI.
- The model showed strong discrimination with AUCs of 0.819 in training and 0.764 in external validation cohorts.
- The nomogram demonstrated good calibration and generalizability for clinical use in reproductive screening.

## Abstract

This study aimed to investigate the influence of lifestyle factors on the sperm DNA fragmentation index (DFI) in infertile men, and to develop and validate a predictive model for identifying individuals at risk of abnormal DFI.

A total of 746 infertile men who underwent intracytoplasmic sperm injection and embryo transfer (ICSI-ET) at the Obstetrics and Gynecology Hospital affiliated with Tongji University from June 2023 to December 2024 were included as the training cohort, while 308 infertile men treated at Xinhua Hospital affiliated with Shanghai Jiao Tong University School of Medicine from January to June 2024 served as the external validation cohort. Data were collected using structured questionnaires, including general demographic information, the Athens Insomnia Scale (AIS), and the Chinese version of the Perceived Stress Scale (CPSS). DFI values were obtained from semen analyses. Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to identify potential predictors, followed by multivariable logistic regression to determine the final independent factors. A nomogram was developed and validated internally and externally. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and the Hosmer–Lemeshow goodness-of-fit test.

Among the 746 participants, 237 (31.8%) exhibited abnormal DFI (>30%). Six independent predictors—age, body mass index (BMI), smoking, hot spring bathing, stress, and daily exercise duration—were identified as significant factors associated with abnormal DFI (all P< 0.05). The model showed excellent discrimination, with an AUC of 0.819 (95% CI: 0.771–0.867) in the training cohort and 0.814 (95% CI: 0.718–0.909) in the validation cohort. Calibration tests (Hosmer–Lemeshow P=0.798 and 0.817, respectively) indicated good model fit. In the external validation cohort, the AUC was 0.764 (95% CI: 0.707–0.821), suggesting satisfactory generalizability.

A predictive model incorporating six modifiable lifestyle factors was developed and validated for assessing the risk of abnormal sperm DFI in infertile men. This nomogram provides a simple and clinically practical tool for early screening and individualized intervention to improve reproductive outcomes.