1. Background
Iran's fertility transition represents one of the world's most rapid declines, with Total Fertility Rate (TFR) falling from 7.0 in 1960 to an estimated 1.6 in recent years (2024 - 2025), far below replacement level (1, 2). This demographic shift carries profound implications for population aging and socioeconomic structures. While early declines stemmed from successful family planning and female education (3), contemporary drivers reflect complex economic and cultural dynamics (4). Significant urban-rural disparities persist, with Tehran's TFR at 1.5 compared to 2.3 in some rural areas (5). Kashan, with a TFR of 1.8 (6), presents an ideal case study amid 40% youth unemployment and expanding female higher education (7, 8).
2. Objectives
This study aimed to examine the determinants of fertility desires and the associated factors among married women attending comprehensive health centers in Kashan, Iran.
3. Methods
3.1. Study Design and Setting
A cross-sectional study was conducted in 2023 at five comprehensive health centers in Kashan, Iran.
3.2. Sample Size and Sampling
The sample size was calculated as 586 using the Cochran formula for estimating a proportion. A design effect of 1.5 was applied to account for cluster sampling.
Parameters were: Z = 1.96 (95% CI), P = 0.5 (maximum variability), q = 1-P, and e = 0.05 (margin of error). A total of 578 married women were ultimately enrolled. A two-stage cluster sampling method was employed. First, five health centers were randomly selected from all comprehensive health centers in Kashan. Second, a proportional number of eligible women from each center's roster were randomly invited to participate.
3.3. Participants
Eligible participants were married women aged 18 - 49 years, attending the selected health centers for any reason, who provided informed consent. After ethical approval, 578 married women aged 18 - 49 were recruited, excluding those pregnant, infertile, or with severe psychiatric conditions.
3.4. Data Collection Tool
Data were collected using a researcher-administered, structured questionnaire with three main sections.
Socio-demographic and economic characteristics: This section included items on age, duration of marriage, education level, employment status and sector, spouse's employment, housing status (owner/renter), and perceived household economic status.
Fertility attitudes and desires: This section utilized a validated 15-item scale adapted from previous studies (8) to measure fertility intentions, desired number of children, and attitudes towards childbearing. Responses were recorded on a 5-point Likert scale (1 = Strongly disagree to 5 = Strongly agree) for attitude items. Example items include: "Having a child is essential for a complete family life", and "I worry that having (another) child would limit my personal freedom".
Perceived Barriers to Childbearing: This section consisted of a 24-item inventory developed based on a literature review and expert consultation. It covered four domains: Economic barriers (e.g., cost of education, housing), health-related barriers (e.g., maternal health concerns, previous pregnancy complications), social barriers (e.g., social pressure, lack of family support), and personal/occupational barriers (e.g., career ambitions, work-family conflict). Responses were binary (yes/no) or on a 3-point scale (e.g., not a barrier, minor barrier, major barrier).
3.5. Validity and Reliability
Content validity of the questionnaire was assessed and confirmed by a panel of ten experts in reproductive health, demography, and instrument development. The Content Validity Index (CVI) for the entire tool was 0.91. Face validity was established through a pilot study with 30 women who confirmed the clarity and relevance of the items. Internal consistency reliability was measured using Cronbach's alpha coefficient, which was 0.84 for the fertility attitude scale and 0.79 for the barrier inventory in the pilot study, indicating good reliability.
3.6. Ethical Considerations
The study protocol was reviewed and approved by the Research Ethics Committee of Kashan University of Medical Sciences (IR.KAUMS.NUHEPM.REC.1402.024). The objectives and procedures of the study were explained to all potential participants. Written informed consent was obtained from each woman before data collection. Confidentiality of all information was assured, and participants were informed of their right to withdraw at any time.
3.7. Data Analysis
Data analysis employed SPSS 26, using chi-square tests, t-tests, and multivariable logistic regression.
4. Results
4.1. Socio-demographic Characteristics
Participants averaged 32.5 ± 6.8 years. Education levels included 28.2% college graduates and 37.7% with less than high school education; 41.8% were employed. Detailed participant characteristics are presented in Table 1.
| Characteristic and Category | No (%) |
|---|---|
| Age (y) | |
| 18 - 29 | 142 (24.6) |
| 30 - 34 | 158 (27.3) |
| 35 - 39 | 165 (28.5) |
| ≥ 40 | 113 (19.6) |
| Education level | |
| Less than high school | 98 (17.0) |
| High school diploma | 120 (20.8) |
| Associate/bachelor's degree | 296 (51.2) |
| Master's degree or higher | 64 (11.1) |
| Employment status | |
| Homemaker | 336 (58.1) |
| Employed | 242 (41.9) |
| Housing status | |
| Homeowner | 347 (60.0) |
| Renter | 231 (40.0) |
| Perceived economic status | |
| Low | 151 (26.1) |
| Middle | 289 (50.0) |
| High | 138 (23.9) |
| Marital satisfaction | |
| High | 245 (42.4) |
| Moderate | 221 (38.2) |
| Low | 112 (19.4) |
4.2. Fertility Desires and Intentions
Fertility reluctance prevalence was 68.2% (394/578). Among reluctant women, 42.3% considered their family complete while 25.9% rejected childbearing entirely. Of the 31.8% desiring children, most (18.7%) wanted one child, with only 13.1% seeking ≥ 2 children (Table 1).
4.3. Predictors of Fertility Reluctance: Multivariable Analysis
Multivariable analysis identified key predictors: Age ≥ 40 years (OR = 4.2, 95% CI: 2.8 - 6.3), economic constraints (OR = 3.2, 95% CI: 2.1 - 4.9), and employment (OR = 2.4, 95% CI: 1.6 - 3.6). The model explained 28% of variance (AUC = 0.78). A significant age-financial interaction (P = 0.021) indicated stronger economic effects on younger women (Table 2).
| Predictor Variable and Category | aOR b | 95% CI | P-Value |
|---|---|---|---|
| Age (y) | |||
| 18 - 29 (Ref) | 1.00 | - | - |
| 30 - 34 | 1.80 | 1.20 - 2.70 | 0.008 |
| 35 - 39 | 3.10 | 1.90 - 5.05 | < 0.001 |
| ≥ 40 | 4.20 | 2.80 - 6.30 | < 0.001 |
| Education level | |||
| ≤ High school (Ref) | 1.00 | - | - |
| University degree | 1.90 | 1.30 - 2.80 | 0.012 |
| Employment status | |||
| Homemaker (Ref) | 1.00 | - | - |
| Employed | 2.40 | 1.60 - 3.60 | 0.002 |
| Financial constraints | |||
| No (Ref) | 1.00 | - | - |
| Yes | 3.20 | 2.10 - 4.90 | < 0.001 |
| Marital satisfaction | |||
| High (Ref) | 1.00 | - | - |
| Moderate | 1.40 | 0.90 - 2.10 | 0.112 |
| Low | 2.10 | 1.50 - 3.00 | < 0.001 |
| Housing status | |||
| Homeowner (Ref) | 1.00 | - | - |
| Renter | 2.10 | 1.40 - 3.10 | 0.001 |
| Daily work hours | |||
| ≤ 5 h (Ref) | 1.00 | - | - |
| > 5 h | 1.80 | 1.20 - 2.70 | 0.015 |
| Prior pregnancy complications | |||
| No (Ref) | 1.00 | - | - |
| Yes | 1.70 | 1.10 - 2.50 | 0.022 |
Abbreviation: aOR, adjusted odds ratio.
a AUC = 0.78. Interaction: Age, financial constraints (P = 0.021).
b The model demonstrated good fit (Hosmer-Lemeshow test, P = 0.32).
Employment sector significantly influenced outcomes, with private sector employees showing higher reluctance (OR = 2.8, 95% CI: 1.9 - 4.2) than public sector counterparts (aOR = 1.9, 95% CI: 1.2 - 3.0). Other significant predictors included renting versus homeownership (aOR = 2.1), workdays > 5 hours (aOR = 1.8), and prior pregnancy complications (aOR = 1.7).
Stratified analysis revealed financial constraints had stronger effects in middle-income (aOR = 3.8) versus low-income groups (aOR = 2.1). The model demonstrated strong calibration (Hosmer-Lemeshow P = 0.32) with 72.3% sensitivity and 71.8% specificity.
Subgroup variations emerged: Marital satisfaction was more protective for nulliparous (aOR = 0.4) than multiparous women (aOR = 0.6), while education showed stronger effects among younger women (< 30 years).
5. Discussion
This study reveals high fertility reluctance (68.2%) in Kashan, aligning with national trends (9) yet exceeding rates in comparable urban centers like Yazd (10), potentially reflecting regional economic disparities or distinct cultural norms (11).
Economic factors predominated, with financial constraints emerging as the strongest predictor (aOR = 3.2), consistent with research on Iran's rising costs (12). The heightened effect among middle-income groups suggests fertility decisions are influenced by relative economic anxiety and aspirational consumption thresholds rather than absolute poverty alone. Younger women increasingly postpone childbearing to achieve lifestyle prerequisites like homeownership. This aligns with findings from qualitative research on young couples' intentions in Iran (13).
Gendered norms exacerbate economic pressures, as unequal domestic labor predicts reluctance among employed women (14, 15). Supporting this, 73% of employed mothers in Isfahan cited inadequate spousal childcare support for delaying second births (13).
The strong reluctance among women ≥ 40 reflects global delayed childbearing trends (16), yet in Iran stems from unique structural barriers. Despite the implementation of pronatalist policies in Iran, such as workplace flexibility measures and financial incentives, fertility rates continue to decline. Our analysis suggests these policies may be insufficient because they often fail to address the fundamental, structural barriers identified in this study. For instance, financial incentives are typically short-term and may not offset the lifelong economic burden of childrearing, particularly education and housing costs. Workplace flexibility policies, while important, are ineffective if not accompanied by strong anti-discrimination laws and a cultural shift towards shared domestic responsibilities. Policy measures like cash incentives (17) remain mismatched with fundamental challenges including workplace discrimination, unaffordable childcare, and high living costs (18), explaining why temporary delays often become permanent.
Employment effects varied significantly by sector, indicating that job precariousness — characterized by lacking security, maternity protections, and flexibility — rather than employment itself drives reluctance. The protective effect of marital satisfaction (40% reduced odds) underscores relational dynamics, a factor also highlighted in studies on the social determinants of reproductive health (18), while social media's dose-response relationship suggests indirect influence through exposure to alternative lifestyles.
Our findings on the multifactorial drivers of fertility reluctance are consistent with systematic reviews on factors affecting the TFR (19). Furthermore, the interaction between age and economics underscores the importance of tempo (timing) effects, as discussed in survival analyses of first birth intervals (20).
Despite robust methodology — stratified sampling, validated instruments, and advanced modeling — the cross-sectional design precludes causal inference, and urban sampling limits rural generalizability. Future longitudinal studies should establish causality, compare generational attitudes, evaluate policy impacts via quasi-experimental designs, and explore regional variations.
5.1. Conclusions
The multifaceted drivers of fertility reluctance demand integrated policy approaches combining economic support with social interventions, including subsidized childcare, family tax incentives, and paid parental leave for fathers (21). Therefore, we recommend a multi-pronged approach: (1) Long-term, substantial economic supports like direct childcare subsidies and housing assistance for young families; (2) enforced legislative protections against workplace discrimination for parents, especially mothers; and (3) nationwide educational campaigns to promote gender equity in domestic roles, encouraging active fatherhood. Effective responses must address both material constraints and the structural barriers shaping reproductive decisions in contemporary Iran.
