Associated factors with male infertility: a case control study

Infertility affects a significant portion of the global population, with male factors contributing in many cases. Sperm analysis remains a key diagnostic tool in identifying potential causes. Prior research has shown that sperm count and motility are strong indicators of fertility potential. However, the exact relationship between lifestyle, environmental, and medical factors and male infertility remains unclear. This gap motivated the current study to explore specific variables that may influence male infertility. The study aimed to address how job-related stress or environmental exposure might affect sperm parameters. No prior work had resolved the role of geographic residence or surgical history in infertility risk. The focus was on identifying patterns in clinical and demographic data to better understand male infertility. This study contributes to the broader effort to improve diagnostic accuracy and treatment options.

The study aimed to determine factors associated with male infertility using semen analysis as a primary diagnostic tool. Researchers focused on comparing two groups: those with low sperm counts and those with normal counts. The motivation was to identify whether certain lifestyle or medical conditions correlated with infertility status. The study sought to evaluate the influence of job type, residence, and surgical history on fertility outcomes. It also aimed to assess how age and clinical infertility rates differ between the two groups. The researchers wanted to understand if specific job-related or environmental factors might contribute to infertility. They were particularly interested in the role of varicocele surgery and geographic location. The study aimed to provide evidence to guide future clinical and public health interventions.

The study included 96 men who visited infertility clinics in Ilam province, Iran, between May 2010 and May 2011. Participants were divided into two groups based on sperm count: Oligospermia (OS) and Non-Oligospermia (NOS). Semen analysis was conducted using the Weili Dynamic Sperm Analysis software, which classifies sperm based on movement and speed into categories A, B, C, or D. Age and other demographic data were collected for each participant. Clinical infertility status was assessed using standard diagnostic criteria. Researchers compared job type, residence, and surgical history between the two groups. Statistical methods were used to evaluate the odds of infertility in relation to these variables. The study design allowed for a direct comparison of risk factors between the two groups.

The study found that 62.5% of the OS group and 31.2% of the NOS group were clinically infertile, with an odds ratio of 3.6 (CI: 1.5–8.5, p=0.01). No significant age difference was observed between the two groups (OS: 29.9 ±5.1 y; NOS: 31.17 ±5.24 y, p>0.05). A significant difference in job and live ratio (A+B+C) was found in the NOS group (F=2.8, p<0.05). The main risk factors in the OS group included a history of varicocele surgery and residence location. These factors were also observed in the NOS group. The prevalence of infertility was higher in the OS group compared to the NOS group. The study highlights the potential role of environmental and medical factors in male infertility. These findings suggest that job-related and geographic variables may influence fertility outcomes.

The study suggests that men with low sperm counts (OS) have a higher likelihood of clinical infertility compared to those with normal counts (NOS). The researchers propose that job-related and residence-based factors may play a role in infertility risk. A history of varicocele surgery was identified as a potential risk factor in both groups. The findings do not confirm a causal relationship but suggest a possible association. The authors recommend further case-control studies to explore these factors in more detail. They also suggest that clinical trials may help clarify the mechanisms behind these associations. The study supports the need for more comprehensive investigations into male infertility causes. These conclusions are based on the observed patterns in the study population.