Longitudinal trends and correlation between autism spectrum disorder prevalence and sperm quality parameters (2000-2024): a comprehensive statistical analysis.

INTRODUCTION

Over the past few decades, there has been growing concern about the concurrent trends of increasing Autism Spectrum Disorder (ASD) prevalence and declining sperm quality. These trends represent significant public health challenges that warrant thorough investigation of their underlying causes and implications.

OBJECTIVES

The primary objectives of this study are to analyze trends in ASD prevalence and sperm quality parameters from 2000 to 2024, assess the statistical significance and effect size of these trends, explore potential correlations between ASD prevalence and sperm quality parameters, and identify significant predictors among sperm quality parameters that influence ASD prevalence.

METHODS

This study employed a longitudinal approach using multiple regression, time series analysis, ANOVA, Principal Component Analysis (PCA), hierarchical clustering, logistic regression, and cross-correlation analysis. Data on ASD prevalence were sourced from the CDC Autism and Developmental Disabilities Monitoring Network, while sperm quality data were collected from various published studies.

RESULTS

The findings reveal significant negative associations between ASD prevalence and sperm quality parameters such as sperm concentration and motility, suggesting that better sperm quality is linked to lower ASD rates. Conversely, parameters like sperm DNA fragmentation (SDF), volume of ejaculate, pH level, and semen viscosity show positive associations with ASD prevalence, indicating higher values in these parameters correlate with higher ASD rates.

CONCLUSION

The study highlights the importance of maintaining reproductive health to potentially mitigate ASD risk and calls for further research to elucidate the underlying mechanisms driving these trends. These findings support the hypothesis that reproductive health factors play a crucial role in ASD etiology and suggest potential biological markers for assessing ASD risk.