Abstract:
Background: Despite recent experiments and interventions in the field of reproductive health,
male subfertility has emerged as a serious global problem. Studies focusing on the causes of male
sub-fertility in Sri Lanka are extremely scarce.
Objectives: To investigate the relationships between various etiologies and male sub-fertility in a
tertiary care centre in Southern Sri Lanka
Methods: A cross-sectional study was conducted among subfertile males who attended the sub-
fertility clinics in Teaching Hospital Mahamodara, Sri Lanka, from the 01st of July to the 31st of
December 2023. A convenience sampling technique was used to enrol 50 subfertile men in the
study. A self-developed, validated questionnaire was used to collect data. Semen samples were
collected from each participant after 3-5 days of abstinence, and basic semen analysis was
performed according to the WHO laboratory manual for the examination and processing of human
semen, 6th edition (2021). In addition, 5 mL of blood was collected from each participant, and
fasting blood sugar (FBS), lipid profile, and HbA1c were performed. A bioelectrical impedance
analysis (BIA) scan was performed on each participant for the measurement of body fat. Data
were analysed using SPSS version 21.0.
Results: The age distribution of the study participants was ranged from 26 to 45 years. Of the
total, 56.0% (n=28) were presented with a BMI above the normal range. BIA analysis revealed
very high body fat levels in 48.0% (n=24) study participants, while 28.0% (n=14) were presented
with high visceral fat levels. Among the study participants, 20.0% (n=10) were presented with
high FBS levels and high HbA1C results, while 66.0% (n=33) were presented with high total
cholesterol. Moreover, 44.0% (n=22) were reported using mobile phones for more than four hours
per day, and 10% (n=5) were reported using laptops for more than two hours per day. However, a
statistically significant correlation could not be observed between sperm parameters (motility,
morbidity, and viability) and FBS, HbA1c, and lipid parameters.
Conclusions: Any correlation between sperm parameters and FBS, HbA1c, and lipid parameters
of the study participants could not be observed using Pearson correlation
