Eisenberg ML, Li S, Behr B, Pera RR, Cullen MR. Relationship between semen production and medical comorbidity. Fertil Steril. 2015;103(1):66-71.
Cross-sectional study in a fertility clinic
A study cohort was identified with data from 1994 to 2011 in the Stanford Reproductive Endocrinology and Infertility semen database. The cohort included 9,387 men with a mean age of 38 years at the time of evaluation.
Participants’ initial semen samples were analyzed for sperm concentration, motility, morphology (according to Kruger Strict Criteria), and semen volume. The cohort was linked via administrative data to obtain information on patients’ comorbidities using the International Classification of Diseases-9 (ICD-9) codes. Patients were then scored on the Charlson comorbidity index (CCI). Most of the men were healthy with a CCI score of 0; however, at least 44% of the participants had 1 medical diagnosis related to infertility, and 30% had 2 or more.
When the cohort was stratified based on CCI score, differences in all measured semen parameters were identified. Men with higher CCI scores had lower semen volume, concentration, motility, total sperm count, and morphology scores. For example, the average sperm concentration for men with a CCI of 0 was 65 million per mL, compared with 46 million per mL in a man with a CCI of 3. Thirteen percent of the men with a CCI of 0 had a sperm concentration <15 million per mL, and over 30% of the men with a CCI >1 had a sperm concentration <15 million per mL. Similar trends were seen with sperm motility. Abnormal morphology was the only parameter that did not vary based on CCI score.
Further analysis failed to demonstrate disease-specific associations; however, men with diseases of the endocrine, genitourinary, and dermatological systems showed statistically significantly higher rates of semen abnormalities. Additionally, men with hypertensive disease, peripheral vascular disease, cerebrovascular disease, and nonischemic heart disease all displayed higher rates of semen abnormalities.
This article supports a naturopathic, whole-systems approach to infertility. While male infertility can exist due to a discrete, specific problem such as testicular failure, more often than not, semen quality is influenced by environment and lifestyle. This multifactorial etiology echoes that of most chronic diseases in which nutrient status, environmental exposures, and many other factors lead to development of a diagnosable illness.
Endocrine and genitourinary problems such as prostatitis or infection may directly impact fertility by impacting semen or sperm production directly. Fertility-related diagnoses such as the development of a varicocele were included in the analysis, so this data should have a strong correlation. Without further insight into the exact diagnoses seen in the cohort, it is difficult to draw conclusions, but with the connection between the skin and the microbiome (in atopic dermatitis, for example1), it is possible that the same underlying biochemistry leading to skin conditions also predisposes men to semen abnormality. Most interesting is the connection between cardiovascular disease and male fertility parameters. Data on male (and now female) gamete quality point to a few key underlying issues of importance. These include mitochondrial health, oxidative stress, and carbonyl stress, the same key drivers of chronic inflammation leading to development of cardiovascular disease.2,3 Not surprisingly, many nutrients, including carnitines, coenzyme Q10, and antioxidants, have been studied for their impact on both cardiovascular health and male fertility.
This article on comorbidities and infertility in men reinforces the importance of addressing the whole person when treating men with infertility. In addition to helping a patient develop his family, a practitioner may also help that father live longer with his family!
This study’s sample size was adequate to determine associations between comorbidities classified by bodily systems; however, a more interesting analysis would be to sort the ICD-9 codes based upon known etiologies to see if stronger associations surface: for example, diagnoses associated with inflammation, oxidative stress, histamine load, or other immune functions.