Although FMF is traditionally associated with populations in the Mediterranean basin including Turks, Armenians, Arabs, Iranians, and Sephardic Jews recent epidemiological shifts indicate its increasingly global distribution due to migration patterns and improved genetic screening (3). The onset of FMF commonly occurs in childhood or adolescence, but the clinical burden continues into adulthood, shaping multiple domains of quality of life, including physical health, emotional stability, and reproductive potential (4). The reproductive implications of FMF have gained growing attention, especially as more patients reach reproductive age with better diagnostic and therapeutic strategies that prolong long‑term health and survival (5). Chronic systemic inflammation is increasingly recognized as a major determinant of reproductive dysfunction, and FMF given its episodic yet persistent inflammatory milieu may influence fertility through multiple biological pathways (6). Pro‑inflammatory cytokines such as IL‑1β and TNF‑α are known to interfere with ovarian reserve, endometrial receptivity, male spermatogenesis, and hypothalamic pituitary gonadal axis regulation, suggesting potential mechanisms linking FMF to reduced fertility (7). In addition, recurrent febrile attacks, oxidative stress, and microvascular dysfunction may negatively impact gonadal tissues and hormonal signaling, further raising the possibility of subfertility among affected individuals (8). Evidence from chronic inflammatory diseases such as rheumatoid arthritis and systemic lupus erythematosus supports the notion that systemic inflammation, even in the absence of direct urogenital pathology, may alter fertility outcomes both in men and women (9).

Colchicine therapy, the mainstay of FMF treatment, has also been implicated in discussions surrounding fertility, although results have been inconsistent and disease‑specific conclusions remain limited (10). While colchicine is essential for preventing inflammatory attacks and reducing the risk of amyloidosis, it may theoretically influence spermatogenesis through microtubule inhibition, raising concerns about reversible reductions in sperm count or motility, though robust evidence is lacking in FMF‑focused cohorts (11). Conversely, some studies suggest that infertility in FMF may stem more from chronic inflammation rather than colchicine exposure, underscoring the importance of distinguishing medication effects from disease‑related pathophysiology (12). In women, certain investigations have proposed potential associations between FMF and menstrual irregularities, ovulatory dysfunction, and higher rates of miscarriage, though findings remain heterogeneous and influenced by genetic, environmental, and cultural factors (13).

The role of MEFV genotypes in reproductive outcomes is another emerging area of interest. Variants such as M694V, V726A, E148Q, and M680I differ in penetrance, disease severity, and inflammatory activity, which may theoretically contribute to fluctuating fertility profiles (14). Severe or uncontrolled FMF phenotypes, particularly those associated with high‑risk MEFV genotypes, may increase exposure to inflammatory mediators and oxidative stress, potentially affecting both male and female reproductive physiology (15). However, genotype–fertility associations remain poorly characterized, and current literature provides only fragmentary insights, highlighting the need for systematic investigation in well‑defined clinical populations (16). Moreover, sociocultural variables, including age at marriage, parity expectations, access to reproductive healthcare, and regional demographics, may further modulate infertility rates among FMF patients, creating complex interactions between biological and contextual determinants (17).

Despite these theoretical mechanisms, the true prevalence of infertility among FMF patients remains unclear, as available studies often involve small sample sizes, heterogeneous populations, or inconsistent diagnostic tools for assessing reproductive function (18). Most previous research has focused on disease epidemiology, genotype‑phenotype relationships, or colchicine resistance, with considerably less attention devoted to long‑term reproductive health and infertility patterns in adult FMF populations (19). There is particularly limited evidence from Middle Eastern and Iranian cohorts, despite the region’s high FMF prevalence and unique genetic structure, which makes local investigations especially relevant for clinical practice and policymaking (20). As a result, clinically important questions regarding the magnitude of infertility in FMF, its demographic correlates, and its potential modifiable determinants remain inadequately answered.

Given these gaps, there is a pressing need for region‑specific research that characterizes infertility prevalence and explores its association with demographic factors among married FMF patients. Such data are valuable not only for improving clinical counseling and personalized disease management but also for shaping therapeutic decisions, reproductive planning, and public health strategies tailored to high‑risk regions. The Kowsar Clinic in Ardabil, as a major referral center for rheumatologic disorders in Northwest Iran, provides a unique setting to examine these questions in a well‑defined FMF population. By addressing these knowledge gaps, the present study aims to contribute critical, locally relevant evidence to the global understanding of reproductive outcomes in auto inflammatory diseases.

Material and methods

Study Design

This descriptive cross‑sectional study was conducted at Kosar clinic of Ardabil University of Medical Sciences, to evaluate infertility prevalence and its demographic determinants among married patients diagnosed with FMF. The study focused on individuals attending routine rheumatology follow‑ups during the designated study period. A cross‑sectional framework was selected to capture real‑world patterns of reproductive outcomes and associated factors in a defined clinical population, enabling quantitative assessment of demographic influences within a single time window.

Sampling and Sample Size Estimation

A sample size of 63 participants was estimated using the standard single‑population proportion formula, assuming a conservative infertility prevalence of 0.5, a 95% confidence level, and a marginal error of 0.12. The formula applied was:

n = Z² × p × (1−p) / d²

where n is the sample size, Z (1.96) corresponds to the 95% confidence level, p is the estimated prevalence (0.5), and d is the acceptable margin of error (0.12). Following substitution, the calculated sample size was 63 participants, considered adequate for the targeted precision and variability. Sampling was performed through a convenience sampling approach, recruiting all eligible married FMF patients who presented to the rheumatology clinic of Kosar clinic of Ardabil during the study period and met the predefined inclusion criteria. This method ensured timely enrollment and feasibility within the study’s operational constraints while maintaining a representative spectrum of disease severity, treatment exposure, and demographic diversity among the FMF population routinely managed in the center.

 Inclusion Criteria

Eligible participants were married adults diagnosed with FMF based on clinical criteria and confirmed by expert rheumatologic assessment. Individuals were required to have a minimum of one year of disease history, regular follow‑up at Kosar clinic of Ardabil, and the ability to provide informed consent. Only patients with complete demographic and reproductive history data were included to ensure accurate evaluation of infertility patterns and associated variables.

Exclusion Criteria

Patients with known non‑FMF causes of infertility, including structural reproductive abnormalities, endocrine disorders, or prior gonadotoxic treatments, were excluded. Individuals with incomplete medical records, unclear reproductive histories, or documented non‑adherence to colchicine therapy were removed to avoid confounding. Those unwilling to participate or unable to provide reliable information were also excluded to preserve data integrity and ensure consistency in clinical and demographic assessment.

 Procedures

All eligible patients were evaluated through a structured interview and medical record review conducted by trained clinical researchers. Demographic data including age, sex, marital duration, education, socioeconomic status, and lifestyle variables were collected systematically. Detailed FMF‑related information, such as age at diagnosis, attack frequency, colchicine dosage, adherence, and MEFV genotype (if available), was extracted from clinical records. Infertility was defined as the inability to achieve pregnancy after at least 12 months of unprotected intercourse, consistent with international reproductive health guidelines.

A standardized infertility assessment checklist was applied, documenting reproductive history, prior pregnancies, miscarriages, duration of attempted conception, and any previous fertility evaluations. For male participants, information on semen analysis if previously performed was recorded, while female participants provided information on menstrual regularity, ovulatory symptoms, and prior gynecological evaluations. Cases with ambiguous fertility histories were clarified through follow‑up interviews. All collected data were verified by a rheumatologist to ensure clinical accuracy and minimize reporting errors.

 Statistical Analysis

Data were analyzed using SPSS software. Continuous variables were examined for normality using the Kolmogorov Smirnov test and were normally distributed. Descriptive statistics were reported as means and standard deviations for quantitative variables and frequencies with percentages for categorical variables. Group comparisons were performed using independent t‑tests for continuous variables and chi‑square tests for categorical variables. Multivariable logistic regression was conducted to assess the relationship between infertility and demographic predictors, adjusting for clinically relevant covariates. A p‑value <0.05 was considered statistically significant.

Ethical Considerations

The study was approved by the Ethics Committee of Ardabil University of Medical Sciences under the code IR.ARUMS.MEDICINE.REC.1402.104. All participants received detailed information regarding study objectives, confidentiality protections, and voluntary participation rights before providing written informed consent. Data were anonymized prior to analysis, and no identifiable information was stored or disclosed. The study adhered to the principles of the Declaration of Helsinki, ensuring respect for autonomy, privacy, and scientific integrity throughout all stages of data collection and reporting.

 Results

Among 63 married FMF patients attending Kowsar Clinic in Ardabil, four individuals met the clinical definition of infertility, corresponding to a prevalence of 6.3%, while 59 patients (93.7%) were fertile. This relatively low but clinically relevant rate suggests that, in this cohort, FMF and its treatments do not appear to be strongly associated with overt infertility. However, the small number of infertile cases limits statistical power for subgroup analyses (figure 1).

Figure 1. Prevalence of Infertility Among Married Patients with Familial Mediterranean Fever

The combined demographic profile of the 63 married FMF patients shows a middle‑aged cohort with a mean age of 45.54 years and a relatively wide age range spanning from 17 to 76 years, indicating considerable variability in the age distribution of affected individuals. The standard deviation of 12.04 years further reflects this dispersion. Sex distribution demonstrates a predominance of female participants, with women representing 63.5% of the study population compared to 36.5% men. This imbalance mirrors the real‑world referral pattern observed in rheumatology outpatient settings, where women more frequently seek evaluation for chronic, recurrent inflammatory symptoms. Collectively, these demographic findings help contextualize the subsequent analysis of infertility outcomes, allowing for more accurate interpretation of age and sex‑related trends within the FMF population.

In this cohort, patients were stratified into two age groups below and above 45 years to assess the relationship between age and infertility. Among individuals younger than 45 years, 2 of 33 patients (6.1%) were infertile, while in the group aged 45 years and older, infertility was observed in 2 of 30 patients (6.7%). The near-identical proportions across the two strata indicate that age did not meaningfully influence infertility rates in this population, a finding supported by the lack of statistical significance (P=0.92). This suggests that, within the studied cohort, infertility appears to be independent of age distribution.

In this cohort of married FMF patients, the comparative age distribution between fertile and infertile individuals reveals a modest but non‑significant upward shift in the infertile group. While the box‑plot demonstrates slightly higher central age values in infertile participants, substantial overlap in the interquartile ranges and dispersions indicates that age is not a distinguishing factor for fertility outcomes in this population. The broad distribution observed in both groups, combined with the absence of statistically meaningful separation, aligns with the reported non‑significant P‑value (0.39) and suggests that fertility impairment in FMF is unlikely to be age‑driven within the studied range. This distribution pattern further underscores the multifactorial nature of reproductive outcomes in FMF and highlights the need for evaluation of non‑age‑related biological and clinical determinants in future investigations (figure 2).

Figure 2. Age‑Related Patterns of Fertility Status Among Married FMF Patients: A Comparative Distribution Analysis

The 100% stacked bar visualization illustrates the proportional distribution of fertility status across male and female FMF patients, offering a clear comparison of relative frequencies rather than absolute counts. Both bars show a dominant fertile segment approximately 95.7% in men and 92.5% in women while the infertile portions remain small and closely aligned between the two sexes. The substantial overlap in proportional patterns, despite minor numerical differences, indicates that the likelihood of infertility is nearly equivalent in men and women within this cohort. This visual consistency mirrors the statistical results, where the absence of a significant association between sex and infertility (P=0.62) suggests that gender-related differences do not meaningfully influence fertility outcomes among FMF patients (figure 3).

Figure 3. Sex-Based Proportional Distribution of Fertility Status in Married FMF Patients

  The stacked bar chart illustrates the absolute distribution of fertility status across urban and rural residents within the cohort of married FMF patients. Urban residents represent the vast majority of the sample, showing 52 fertile and 4 infertile individuals, whereas all seven rural participants are fertile with no documented infertility. Although the urban group appears to contain more infertile cases, this difference is driven almost entirely by the large imbalance in group size rather than a true disparity in fertility outcomes. The parallel height of the fertile segments across both bars, coupled with the absence of infertility among rural residents, underscores a pattern consistent with the statistical analysis, which revealed no significant association between residence and infertility (P = 0.46). Overall, these findings suggest that place of residence does not meaningfully influence reproductive outcomes in FMF patients (figure 4).

Figure 4. Residential Distribution of Fertility Status Among Married FMF Patients