Comparing the Strength of Associations Between Male Genital Problems and Mental Illnesses and Sleep Disorders.
Ray M MerrillDajeong SongMcKay K AshtonPublished in: American journal of men's health (2024)
This study compares the rate of selected types of mental illnesses (stress, anxiety, depression) and sleep disorders (insomnia, sleep apnea) according to the status of eight male genital problems. Analyses utilize medical claims data for male employees aged 18 to 64 years of a large corporation, 2017 to 2021. Approximately 1,076 (7.3%) men per year have one or more genital problems. The most common being benign prostatic hyperplasia (BPH; 3.8%) and then erectile dysfunction (ED; 1.7%). For BPH patients, the rate experiencing stress, anxiety, depression, or a combination of these is 0.96%, 6.2%, 5.3%, and 5.1%, respectively. Corresponding rates for ED are 1.5%, 7.2%, 5.9%, and 7.5%. For BPH patients, the rate experiencing insomnia, sleep apnea, or both is 3.1%, 22.7%, and 2.0%, respectively. Corresponding rates for ED are 1.2%, 20.6%, and 2.2%. Male genital problems positively associate with having one or more mental illnesses (stress, anxiety, depression), except for hydrocele, with ED and penis disorder having the strongest associations. Male genital problems also positively associate with having insomnia and/or sleep apnea, except for infertility and orchitis, with BPH and ED having the strongest associations. The positive associations involving BPH and ED with mental illnesses are each more pronounced in the younger age group (18-49 vs. 50-64). Similar results are seen in the models involving sleep disorders. Thus, comorbid male genital problems, mental illnesses, and sleep disorders exist, with the strength of associations unique to the male genital problem and sometimes modified by age.
Keyphrases
- sleep quality
- mental health
- sleep apnea
- benign prostatic hyperplasia
- lower urinary tract symptoms
- emergency department
- depressive symptoms
- end stage renal disease
- positive airway pressure
- obstructive sleep apnea
- physical activity
- ejection fraction
- chronic kidney disease
- prognostic factors
- peritoneal dialysis
- healthcare
- patient reported outcomes
- machine learning
- health insurance
- artificial intelligence
- big data
- deep learning
- middle aged