Abstract
Background
Declining fertility rates have emerged as a major demographic and socioeconomic challenge worldwide, including in Iran. Understanding the role of family conditions in shaping women’s reproductive attitudes is essential for informing effective fertility-related policies and interventions.This study aimed to examine the relationship between family conditions and attitudes toward childbearing among married women in Sarab, Iran.
Methods
Data were collected using a demographic questionnaire, the Family Conditions Questionnaire, and a researcher-developed Attitudes Toward Childbearing Questionnaire. The researcher-developed questionnaire demonstrated good validity and reliability (overall Cronbach’s alpha = 0.886), while the Family Conditions Questionnaire had previously established psychometric properties. Data were analyzed using SPSS version 27 using descriptive statistics, ANOVA, independent t-tests, Pearson’s correlation, and hierarchical regression analysis.
Results
Participants had a mean age of 31.4 years. Housewives reported more positive attitudes toward childbearing compared to employed women (p < 0.001). Significant differences were also observed across educational and financial groups (p < 0.001). Family conditions were strongly correlated with childbearing attitudes (r = 0.833, p < 0.01). Regression analysis showed that while demographic variables explained 13.1% of the variance in attitudes, inclusion of family conditions increased explained variance to 70.4%. Among family dimensions, educational (β = 0.270), economic (β = 0.266), and parenting interactions (β = 0.220) were the strongest predictors.
Conclusion
Family conditions, particularly the educational and economic dimensions, were more strongly associated with married women’s attitudes toward childbearing than demographic characteristics. In addition, favorable family conditions attenuated the statistical associations between education, employment status, and childbearing attitudes in the regression models. These findings highlight the importance of considering family dynamics, spousal communication, and intergenerational support when developing policies and counseling strategies aimed at promoting positive attitudes toward childbearing in Iran.
Keywords: Childbearing, Fertility, Family conditions, Attitudes, Married women, Iran
Plain language summary
In recent years, the number of children that families in Iran choose to have has decreased. This trend is important because it can affect the balance of the population, leading to fewer young people and more elderly individuals in the future. Such changes can create social and economic challenges for families and society.This study looked at how family situations influence women’s attitudes toward having children. We worked with 380 married women living in Sarab, Iran, and asked them about their family conditions such as financial situation, education, cultural background, emotional support, and parenting roles and their feelings about childbearing.We found that women’s family conditions had a stronger effect on their attitudes toward having children than their personal characteristics such as age, education, or job. For example, women who felt supported by their family, had better financial stability, or received encouragement in education and parenting were more positive about having children. On the other hand, women with less support or more financial pressure were less likely to view childbearing positively.The results show that strong and supportive families can help women feel more confident and motivated about having children, even when education and employment might make it more difficult. This means that improving family support and communication is just as important as government policies for encouraging childbearing.
Background
One of the most significant global changes with increasingly profound effects is the decline in fertility rates [1]. Iran has not been an exception to this trend and is also experiencing a decrease in fertility [2]. According to the 2011 census, the fertility rate in Iran had dropped to 1.6 children per woman. If this trend continues, the country’s population could decrease to approximately 31 million over the next 80 years, with a large proportion consisting of elderly individuals [3]. The continuation of this trend could pose numerous economic challenges, including reduced labor force and youth population, negatively affecting investment and consumption [4]. It may also impose substantial economic burdens on society and alter family structures [5]. Consequently, declining willingness to have children has become an issue of significant societal concern requiring targeted interventions.
Childbearing is crucial for sustaining the economic and social equilibrium of nations. By maintaining population replacement and workforce capacity, fertility contributes to economic development, social cohesion, and sustainable development [6, 7]. It also plays an important role in strengthening family stability and facilitating the transmission of cultural values across generations [8]. Therefore, promoting positive attitudes toward childbearing may contribute to both family well-being and broader societal development.
Knowing the determinants of attitudes toward fertility can help fertility counselors and policymakers develop interventions that are better aligned with the needs of married couples [9]. Learning from the experience of advanced nations discloses that changes in marital arrangements, family formation processes and intergenerational and gender interactions in the previous two centuries led to declining fertility [10]. These findings highlight the important role of cultural and social values in shaping reproductive attitudes, which have evolved considerably with ongoing social and demographic changes [11]. Building on this evidence, prior studies have generally categorized the determinants of childbearing attitudes into demographic, socioeconomic, cultural, and policy-related domains [12, 13].
Government policies on population and family planning also significantly determine attitudes and behaviors toward fertility [14]. In Iran, a range of support and incentive policies has been put in practice in support of higher fertility and family support [15]. These policies will only be successful when compatible with the attitudes and needs of society in the present era [16]. Research has found that incompatibility between policy interventions and the social order has the effect of diminishing them. Hence, an accurate awareness of attitudes and determinants of childbearing among married females has the ability to aid in the refinement and development of population policies [17, 18]. Yet, while demographic, socioeconomic, and policy-related determinants of childbearing attitudes have been relatively well documented, the role of family conditions has received comparatively less systematic attention.
Family circumstances represent one such underexamined predictor of attitudes toward childbearing. Family relationships are central in the formation and adjustment of fertility attitudes [19]. Family interactions and behaviors directly determine fertility decisions [20]. For example, families with high emotional attachment and supporting relationships might be more inclined to bear children because of the strength of attachment and responsibility [21]. Moreover, family patterns in the form of the numbers of children in neighboring families and the experience of the parents also determine the attitudes of individuals [22]. Pressure from the family and society at large may also raise or lower the desire to bear children [23]. Families that face societal demand for larger family size or are greatly affected by the cultural demand may take differing attitudes toward fertility [24]. Hence, family circumstances and internal behavior patterns form a central determinant of attitudes and fertility decisions.
Although previous studies have identified demographic, socioeconomic, cultural, and policy-related factors associated with fertility attitudes, the multidimensional role of family conditions has received comparatively limited attention, particularly in the Iranian context. Moreover, few studies have simultaneously examined whether different dimensions of family conditions—including educational, economic, cultural, emotional, and parenting-related characteristics—remain associated with attitudes toward childbearing after accounting for demographic characteristics. Addressing this gap may provide a more comprehensive understanding of the factors associated with childbearing attitudes and generate evidence to inform family-centered reproductive and population policies. Therefore, the present study aimed to investigate the associations between multiple dimensions of family conditions and attitudes toward childbearing while quantifying their relative contributions beyond demographic characteristics.
Methods
This study employed a descriptive-analytical, cross-sectional design to examine the relationship between family conditions and attitudes toward childbearing among married women residing in Sarab, Iran. Sarab is a city in East Azerbaijan Province, northwestern Iran, with a predominantly Azerbaijani (Turkish-speaking) population. The study was conducted in comprehensive health centers that provide primary maternal, reproductive, and family health services to women from diverse socioeconomic backgrounds.Data were collected between October and December 2024. A cross-sectional design was chosen to simultaneously assess variables and identify existing patterns and correlations at a specific point in time. Findings from this approach can provide a basis for longitudinal research and inform the design of targeted interventions in the fields of population and reproductive health. The study was conducted following approval from the Ethics Committee of Sarab University of Medical Sciences (Ethics code: IR.SARAB.REC.1402.015). All participant information remained confidential, and data were used solely for research purposes.
Sample size and sampling method
The sample size was calculated using Cochran’s formula for finite populations:
 |
corresponding to the desired confidence level (1.96 for a 95% confidence level), p is the estimated proportion (0.50), q is calculated as 1 − p (0.50), and d is the margin of error (0.05). Based on these assumptions (N = 52,203, Z = 1.96, p = 0.50, q = 0.50, and d = 0.05), the required sample size was calculated to be 381 participants.
A multi-stage cluster random sampling method was employed. In the first stage, a list of all comprehensive health centers in Sarab was compiled and divided into four clusters based on geographic location. In the second stage, one or more centers were randomly selected from each cluster. Subsequently, eligible married women were randomly selected from the records of the selected centers. Finally, participants were invited to join the study after screening for inclusion criteria. To ensure ethical compliance, participants received complete information regarding the study’s objectives, procedures, benefits, and data confidentiality, and informed consent was obtained.
Inclusion and exclusion criteria
Inclusion criteria
Married women residing in Sarab.
Aged 18–45 years.
At least one year of marriage.
Ability to understand and respond to questionnaires.
Willingness to participate voluntarily.
Exclusion criteria
Diagnosis of severe psychiatric disorders or confirmed cognitive impairment.
Incompletion of more than 20% of the questionnaire.
Withdrawal from participation at any stage of the study.
Data collection
Data were collected via face-to-face interviews by two trained research assistants who had completed comprehensive training on study objectives, proper interview techniques, ethical principles, and bias reduction strategies. Due to the absence of standardized instruments suitable for the study population, researcher-developed questionnaires were used to assess family conditions and attitudes toward childbearing.
Measurement instruments
Demographic Questionnaire: A structured questionnaire was used to collect demographic information, including age, education, and income. This instrument provided essential data for controlling potential confounding variables.
Family Conditions Questionnaire: To assess family conditions, a 22-item questionnaire developed by Nourbakhsh(2012) was used. The instrument comprised five main components: economic status, educational level, cultural factors, emotional relationships, and parenting interactions. Responses were scored on a 5-point Likert scale ranging from “strongly disagree” to “strongly agree,” with higher scores indicating more favorable family conditions. Cronbach’s alpha for the subscales ranged from 0.59 to 0.71, and face validity was confirmed by experts [25]. Although the Family Conditions Questionnaire was originally developed for a different research purpose, it assesses core dimensions of the family environment, including educational, economic, cultural, emotional, and parenting-related characteristics. These dimensions have been identified in previous studies as important factors associated with reproductive attitudes and fertility decision-making. Therefore, the questionnaire was considered conceptually appropriate for assessing family conditions in relation to attitudes toward childbearing in the present study.
Attitudes toward Childbearing Questionnaire (Researcher-Developed): A 23-item questionnaire was designed to evaluate married women’s attitudes toward childbearing, based on literature review, previous studies, and theoretical frameworks related to fertility attitudes and behaviors. The instrument covered three main components:
Cognitive attitudes toward childbearing (8 items).
Negative or inhibiting attitudes toward childbearing (10 items).
Parental readiness and identity (5 items).
Responses were scored using a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Items assessing negative attitudes (items 9–18) were reverse-coded to ensure consistency, with higher scores reflecting more positive attitudes toward childbearing. Face validity and qualitative content validity were assessed by a panel of five experts in reproductive health, demography, and research methodology, who evaluated the questionnaire for clarity, relevance, comprehensiveness, and representativeness of the construct. The questionnaire was revised according to their recommendations before administration. A pilot study with 20 participants from the target population was conducted to assess reliability, and the results are presented in Table 1. Cronbach’s alpha coefficients were 0.771 for cognitive attitudes, 0.882 for negative/inhibiting attitudes, 0.827 for parental readiness/identity, and 0.886 for the overall questionnaire. Split-half reliability indicated a Spearman-Brown coefficient of 0.770 and Guttman coefficient of 0.776, demonstrating high internal consistency and excellent reliability. Construct validity was further examined using exploratory factor analysis (EFA) with principal axis factoring and Promax rotation, followed by confirmatory factor analysis (CFA) using AMOS version 24. Sampling adequacy was assessed using the Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity. Model fit in the CFA was evaluated using the chi-square/degrees of freedom ratio (χ²/df), Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Incremental Fit Index (IFI), Goodness-of-Fit Index (GFI), Adjusted Goodness-of-Fit Index (AGFI), and the Root Mean Square Error of Approximation (RMSEA).
Table 1.
Reliability and internal consistency of the attitudes toward childbearing questionnaire and its subscales
| Component / Total Questionnaire | Number of Items | Cronbach’s Alpha | Split-Half (Spearman-Brown) | Guttman |
|---|---|---|---|---|
| Cognitive attitudes toward childbearing | 8 | 0.771 | - | - |
| Negative or inhibiting attitudes | 10 | 0.882 | - | - |
| Parental readiness and identity | 5 | 0.827 | - | - |
| Total questionnaire | 23 | 0.886 | 0.770 | 0.776 |
Data analysis
Data were analyzed using SPSS version 27. Initially, descriptive statistics (frequency, percentage, mean, and standard deviation) were calculated to describe the demographic characteristics and main study variables.To compare attitudes toward childbearing across groups, mean comparison tests were conducted. Specifically, ANOVA was used to assess differences across educational levels and financial status, Homogeneity of variances was evaluated using Levene’s test. Because the assumption of equal variances was violated (p < 0.05), Games–Howell post hoc comparisons were performed following significant ANOVA results. An independent t-test was performed to compare housewives with employed women. Effect sizes were reported using Eta² and Cohen’s d. Linear associations among continuous variables (age, family conditions, and attitudes toward childbearing) were assessed using Pearson’s correlation coefficients.
To identify predictors of attitudes toward childbearing, a hierarchical regression analysis was performed. This method was chosen because it allows stepwise examination of predictors, making it possible to evaluate the unique contribution of demographic characteristics and family conditions separately. It also enables assessment of the incremental variance explained (ΔR²) by adding new predictors at each step.In Model 1, demographic variables (age, education, employment status, and financial status) were entered to determine their independent predictive value. In Model 2, the total family conditions score was added to examine its contribution beyond demographics. In Model 3, the five components of family conditions (economic, educational, cultural, emotional, and parenting interactions) were included instead of the total score to evaluate the relative predictive strength of each dimension. For each model, R², ΔR², F change, and both unstandardized (B) and standardized (β) coefficients were reported. A significance level of p < 0.05 was adopted for all analyses. Before interpreting the regression models, the underlying assumptions were evaluated. Multicollinearity was assessed using tolerance values and variance inflation factors (VIF). Tolerance values ranged from 0.376 to 0.806, and VIF values ranged from 1.24 to 2.66, indicating no evidence of problematic multicollinearity. Independence of residuals was confirmed by a Durbin–Watson statistic of 1.765. The assumptions of normality and homoscedasticity were evaluated through visual inspection of the histogram of standardized residuals, the normal probability (P–P) plot, and the scatterplot of standardized residuals versus standardized predicted values. These diagnostic plots demonstrated an approximately normal distribution of residuals and a random dispersion of residuals around zero, indicating that the assumptions of normality and homoscedasticity were satisfactorily met. A two-sided p value < 0.05 was considered statistically significant for all analyses. Because all study variables were collected using self-reported questionnaires at a single time point, common method variance was assessed using Harman’s single-factor test. The first unrotated factor accounted for 18.18% of the total variance, indicating that common method bias was not a significant concern.
Results
Psychometric evaluation of the attitudes toward childbearing questionnaire
The construct validity of the researcher-developed Attitudes toward Childbearing Questionnaire was evaluated using exploratory and confirmatory factor analyses. As shown in Table 2, the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.827, indicating that the data were suitable for factor analysis. Bartlett’s test of sphericity was statistically significant (χ² = 699.77, df = 253, p < 0.001), supporting the factorability of the correlation matrix. Exploratory factor analysis using principal axis factoring with Promax rotation supported the proposed three-factor structure consisting of cognitive attitudes, negative/inhibiting attitudes, and parental readiness and identity. The three-factor measurement model was subsequently evaluated using confirmatory factor analysis. The model demonstrated an excellent fit to the data (χ² = 231.02, df = 227, χ²/df = 1.02, p = 0.413, CFI = 0.995, TLI = 0.995, IFI = 0.995, GFI = 0.951, AGFI = 0.940, and RMSEA = 0.007). Standardized factor loadings ranged from 0.26 to 0.52. Together with the excellent global model fit indices, these findings supported the adequacy of the proposed three-factor measurement model.
Table 2.
Construct validity and model fit indices of the attitudes toward childbearing questionnaire
| Index | Value |
|---|---|
| KMO | 0.827 |
| Bartlett’s χ² | 699.77 |
| df | 253 |
| p-value | < 0.001 |
| χ² | 231.02 |
| χ²/df | 1.02 |
| CFI | 0.995 |
| TLI | 0.995 |
| IFI | 0.995 |
| GFI | 0.951 |
| AGFI | 0.940 |
| RMSEA | 0.007 |
A total of 381 married women were initially recruited. One questionnaire was excluded because of incomplete data; therefore, the final analyses were conducted on 380 participants. Table 3 presents the demographic characteristics of the participants. The majority of the participants had a bachelor’s degree, while the fewest had a doctoral degree. Half of the participants were housewives, and half worked outside the home. Regarding economic status, the largest proportion reported that their income was equal to their expenses, whereas the smallest proportion reported an income below their expenses. These results show sufficient diversity in the educational, occupational, and economic characteristics of the sample.
Table 3.
Demographic characteristics of the study participants
| Variable | Category | Frequency (n) | Percentage (%) |
|---|---|---|---|
| Education | Middle school | 75 | 19.7 |
| High school diploma | 102 | 26.8 | |
| Bachelor’s degree | 104 | 27.4 | |
| Master’s degree | 70 | 18.4 | |
| Doctorate | 29 | 7.6 | |
| Employment status | Homemaker | 186 | 48.9 |
| Employed | 194 | 51.1 | |
| Financial status | Income less than expenses | 115 | 30.3 |
| Income equal to expenses | 126 | 33.2 | |
| Income greater than expenses | 139 | 36.6 |
Table 4 presents the descriptive statistics of the continuous variables. The mean age of the participants was 31.4 years. The mean scores for family conditions and attitude toward childbearing were 70.48 (SD = 13.94) and 70.63 (SD = 13.76), respectively, reflecting moderate-to-high family conditions and an overall positive attitude toward childbearing. The relatively similar dispersion of these variables indicates a comparable level of variability in family conditions and attitudes toward childbearing among the participants.
Table 4.
Descriptive statistics of continuous variables
| Variable | N | Minimum | Maximum | Mean | Standard Deviation (SD) |
|---|---|---|---|---|---|
| Age (years) | 380 | 18 | 45 | 31.39 | 6.24 |
| Family Conditions | 380 | 40 | 104 | 70.48 | 13.94 |
| Attitudes Toward Childbearing | 380 | 36 | 113 | 70.63 | 13.76 |
Table 5 presents the group comparisons examining the associations between demographic factors and attitudes toward childbearing. Educational level was significantly associated with attitudes toward childbearing (F = 5.477, p < 0.001, Eta² = 0.055). Women with a high school diploma had significantly more positive attitudes than those with bachelor’s degrees (mean difference = 5.93, p = 0.008), master’s degrees (mean difference = 6.97, p = 0.001), and doctoral degrees (mean difference = 10.73, p = 0.003). No other pairwise comparisons reached statistical significance. Employment status also influenced attitudes; housewives had significantly higher scores than employed women (t = 4.122, p < 0.001, Cohen’s d = 0.42). Financial status was significantly associated with attitudes toward childbearing (F = 10.024, p < 0.001, Eta² = 0.050). Games–Howell post hoc analysis showed that women whose income equaled their expenses had significantly more positive attitudes than both women whose income was lower than their expenses (mean difference = 7.62, p < 0.001) and those whose income exceeded their expenses (mean difference = 4.87, p = 0.003). No significant difference was observed between the latter two groups (p = 0.308). These findings indicate that educational level, employment status, and financial status were significantly associated with attitudes toward childbearing.
Table 5.
Comparison of attitudes toward childbearing across demographic groups
| Variable | Group | Mean | Std. Deviation | Test | F / t | Sig. | Effect Size |
|---|---|---|---|---|---|---|---|
| Education | Middle School | 71.84 | 17.28 | ANOVA | 5.477 | 0.000 | Eta² = 0.055 |
| Diploma | 74.97 | 12.59 | |||||
| Bachelor | 69.04 | 12.83 | |||||
| Master | 68.00 | 10.67 | |||||
| Doctoral | 64.24 | 13.25 | |||||
| Employment Status | Housewife | 73.54 | 13.87 | Independent T-test | 4.122 | 0.000 | Cohen’s d = 0.42 |
| Employed | 67.84 | 13.10 | |||||
| Financial Status | Income < Expenses | 67.10 | 16.16 | ANOVA | 10.024 | 0.000 | Eta² = 0.050 |
| Income = Expenses | 74.71 | 10.90 | |||||
| Income > Expenses | 69.84 | 13.06 |
Table 6 presents the results of the correlation analysis. A strong and statistically significant positive correlation was observed between family conditions and attitudes toward childbearing (r = 0.833, p < 0.01), suggesting that better family conditions are associated with more positive attitudes toward childbearing. In contrast, age showed weak and non-significant correlations with both family conditions (r = 0.075) and attitudes toward childbearing (r = 0.073), indicating that age is not an important determinant in this context.
Table 6.
Correlation matrix of study variables
| Variable | 1 | 2 | 3 |
|---|---|---|---|
| 1. Age | 1 | ||
| 2. Family Conditions | 0.075 | 1 | |
| 3. Attitudes Toward Childbearing | 0.073 | 0.833** | 1 |
** Correlation is significant at the 0.01 level (2-tailed)
Table 7 presents the results of the hierarchical regression analysis examining the predictive role of demographic variables and family conditions. Model 1, including only demographic variables (age, education, employment, and financial status), explained 13.1% of the variance in attitudes (R² = 0.131, p < 0.001). In this model, age (β = 0.115, p = 0.029) and financial status (β = 0.350, p < 0.001) were significant positive predictors, while education (β = − 0.285, p < 0.001) and employment status (β = − 0.214, p = 0.002) were significant negative predictors. Model 2 incorporated the total family conditions score alongside demographic variables, resulting in a substantial improvement. This model explained 70.4% of the variance (R² = 0.704, ΔR² = 0.573, p < 0.001), with family conditions showing the strongest standardized association (β = 0.801, p < 0.001). After adjustment for family conditions, the regression coefficients of the demographic variables became smaller, and several were no longer statistically significant. In Model 3, the five dimensions of family conditions (economic, educational, cultural, emotional, and parenting interactions) were included individually. This model explained 70.6% of the variance (R² = 0.706, ΔR² = 0.575, p < 0.001). All family condition dimensions were positively associated with attitudes toward childbearing. The educational (β = 0.270, p < 0.001) and economic (β = 0.266, p < 0.001) dimensions showed the largest standardized coefficients, followed by the parenting interaction (β = 0.220, p < 0.001) and cultural (β = 0.207, p < 0.001) dimensions. The emotional dimension was also significantly associated with attitudes toward childbearing, although its standardized coefficient was comparatively smaller (β = 0.084, p = 0.011).
Table 7.
Hierarchical regression analysis predicting attitudes toward childbearing
| Model | Variables | B | SE B | Beta | T | p | R² | ΔR² | ΔF |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Age | 0.253 | 0.115 | 0.115 | 2.20 | 0.029 | 0.131 | 14.13*** | |
| Education | -3.259 | 0.824 | − 0.285 | -3.95 | 0.000 | ||||
| Employment Status | -5.892 | 1.879 | − 0.214 | -3.14 | 0.002 | ||||
| Financial Status | 5.896 | 1.048 | 0.350 | 5.62 | 0.000 | ||||
| 2 | Total Family Conditions | 0.791 | 0.029 | 0.801 | 26.89 | 0.000 | 0.704 | 0.573 | 723.04*** |
| Age | 0.056 | 0.068 | 0.025 | 0.827 | 0.409 | ||||
| Education | − 0.856 | 0.490 | − 0.075 | -1.746 | 0.082 | ||||
| Employment Status | -1.871 | 1.109 | − 0.068 | -1.688 | 0.092 | ||||
| Financial Status | 1.449 | 0.635 | 0.086 | 2.283 | 0.023 | ||||
| 3 | Components of Family Conditions: | 0.706 | 0.575 | 144.94*** | |||||
| Economic Dimension | 0.883 | 0.121 | 0.266 | 7.32 | 0.000 | ||||
| Educational Dimension | 0.942 | 0.126 | 0.270 | 7.45 | 0.000 | ||||
| Cultural Dimension | 0.712 | 0.128 | 0.207 | 5.55 | 0.000 | ||||
| Emotional Dimension | 0.544 | 0.212 | 0.084 | 2.57 | 0.011 | ||||
| Parenting Interaction Dimension | 0.740 | 0.119 | 0.220 | 6.23 | 0.000 | ||||
| Age | 0.057 | 0.068 | 0.026 | 0.835 | 0.404 | ||||
| Education | − 0.845 | 0.492 | − 0.074 | -1.717 | 0.087 | ||||
| Employment Status | -1.761 | 1.114 | − 0.064 | -1.580 | 0.115 | ||||
| Financial Status | 1.285 | 0.644 | 0.076 | 1.995 | 0.047 | ||||
*** p-value < 0.001
Overall, these results indicate that family conditions, particularly the educational and economic dimensions, showed the strongest associations with married women’s attitudes toward childbearing. After accounting for family conditions, demographic variables exhibited comparatively weaker statistical associations, suggesting that family-related factors may be more closely associated with attitudes toward childbearing in this study.
Discussion
The present study examined the relationship between familial conditions and attitudes toward childbearing among married women in Sarab, Iran. The findings indicate that while demographic factors such as age, education, employment status, and financial situation were significantly associated with women’s attitudes toward childbearing, family conditions—particularly educational, economic, and cultural dimensions—showed even stronger associations. Initial analyses indicated that higher educational attainment and employment status were associated with more negative attitudes towards childbearing, which is consistent with the evidence that educated women might report lower fertility intentions due to career aspirations and opportunity costs [26, 27]. However, when family factors were added to the model, the associations of education and employment status with childbearing attitudes were substantially attenuated. This finding suggests that family conditions may partially explain the statistical associations between education, employment, and childbearing attitudes. However, given the cross-sectional design, these relationships should be interpreted as associations rather than causal pathways.
A closer look into family components lines revealed several mechanisms. Family educational support was associated with greater confidence in parenting roles, whereas financial stability was associated with lower perceived economic pressure related to raising children. One possible explanation is that educational support within the family may improve access to reliable information about pregnancy, child health, and parenting, thereby increasing women’s confidence in their ability to manage childrearing responsibilities. Likewise, favorable economic family conditions may reduce concerns regarding the direct and indirect costs of raising children, including healthcare, education, and housing expenses. Together, these resources may create a family environment that is more supportive of positive attitudes toward childbearing [28, 29]. Spousal communication and cultural expectations were also significantly associated with childbearing attitudes, suggesting that marital and societal contexts may play an important role. These results are consistent with qualitative research conducted in Iran, which found that family and cultural norms significantly influence fertility decisions [30]. Similarly, research in other countries has shown that families with high marital satisfaction and supportive relationships are more likely to have positive fertility attitudes and behaviors [31].
Family socioeconomic status may be associated with childbearing attitudes through several interconnected pathways, including parental educational resources, financial security, and supportive gender roles such as husband involvement and shared decision-making. In Ghana, women’s empowerment and autonomy reduced the ideal family size, whereas adherence to patriarchal norms had the opposite effect. These findings are in line with our results, which show that women who live in supportive families, where they are respected and able to make informed decisions regarding their life and health, can mitigate the effects of structural barriers and economic constraints on childbearing intentions [32]. Similarly, studies from South Asia and Ethiopia showed that the shared fertility wishes and male partner involvement significantly influenced reproductive health decision-making [33, 34]. Our findings therefore suggest that promoting women’s empowerment within the family through improved spousal communication and shared decision-making may be associated with more positive childbearing attitudes. However, longitudinal studies are required to determine whether these relationships are causal.
Parental educational resources and targeted interventions matter as well. Two systematic reviews showed that higher maternal education level positively affects fertility intentions, especially when it is accompanied by good economic status and active involvement of spouses [35, 36]. Conversely, families characterized by restrictive norms, poor communication, and limited support were associated with less favorable childbearing attitudes [37, 38]. It indicates that childbearing attitudes need to be viewed not in isolation but in the context of family structure and intergenerational relationships.
Nevertheless, not all studies have reported similar findings. Several investigations conducted in high-income countries have suggested that family support alone may not be sufficient to promote positive fertility attitudes when broader structural barriers, such as unstable employment, housing costs, or limited institutional support, remain unresolved [39, 40]. These differences indicate that the relative importance of family conditions may vary across socioeconomic and policy contexts, emphasizing the need to interpret the present findings within the Iranian setting.
Intergenerational relationships and interactions further illustrate the broad impact. Studies from Nepal and other transitional societies show that the engagement of in-laws and other family members significantly influences the fertility intentions of women [41]. However, some norms like the timing of the first childbirth remain immune to change. Biological and social pathways are intertwined: maternal nutrition and childhood socioeconomic environment co-determine later life reproductive outcomes. This evidence suggests that family-related factors are closely associated with reproductive attitudes and may interact with broader social and biological processes over time.
Cross-national evidence also shows that the link between women’s education and fertility is context-specific. In the Nordic welfare states, where fertility-enhancing institutional setups such as parental leave schemes and subsidized childcare are well advanced [42, 43]. In the context of a transitional society such as Iran, where institutional support remains limited, family-level resources may help explain the observed associations between women’s educational and occupational roles and their attitudes toward childbearing. Stable economic resources, supportive cultural attitudes, and emotional support within the household may facilitate balancing educational and occupational aspirations with family life. This issue should also be considered in policy discussions on how to improve family support in Iran.
Overall, the findings suggest that family influences on childbearing attitudes are multifaceted. Educational resources, economic security, supportive spousal relationships, and positive cultural environments were all independently associated with more favorable attitudes toward childbearing. These findings highlight the importance of considering the broader family context, alongside demographic characteristics, when designing family-centered reproductive health policies and future research.
Limitations
Several study limitations need to be acknowledged. First, the design is cross-sectional; therefore, one cannot ascertain whether unfavorable family conditions affect childbearing attitudes or vice versa. Second, the use of self-reported questionnaires might have caused response and social desirability biases, given the cultural sensitivity of fertility issues in Iran. Additionally, the educational dimension of the Family Conditions Questionnaire showed relatively modest internal consistency (Cronbach’s α = 0.59). Although the overall psychometric evaluation supported the use of the questionnaire, findings related to this dimension should be interpreted with caution, and further validation is recommended.Third, several potentially important reproductive characteristics, including duration of marriage, history of infertility, pregnancy history, and previous reproductive experiences, were not assessed. The absence of these variables may have resulted in residual confounding, and future studies should incorporate them to provide a more comprehensive understanding of factors associated with attitudes toward childbearing. Fourth, the Family Conditions Questionnaire did not capture some critical aspects of familial relationships such as power dynamics, generational conflicts, and extended kinship ties that are relevant to the Iranian sample. Fifth, the study was conducted only among married women attending public health centers in Sarab. Because participants were recruited exclusively from public health centers, women who do not utilize these services may have been underrepresented, introducing the possibility of selection bias. Therefore, the findings may not be generalizable to women in other regions, men, or unmarried women. Finally, although family conditions showed the strongest association with childbearing attitudes in the present study, other factors, such as policy support, childcare availability, and macroeconomic uncertainty, are also likely to be associated with these attitudes.
Conclusion
This study showed that although demographic characteristics such as age, education, employment, and financial status were associated with women’s attitudes toward childbearing, family conditions—particularly the educational, economic, and cultural dimensions—showed the strongest associations with these attitudes. Women reporting more supportive family environments also tended to report more positive childbearing attitudes, even after accounting for demographic characteristics. By highlighting the family context, this study addresses an overlooked gap in Iranian fertility research, which has primarily concentrated on macro-level and policy factors. Consequently, there is a need to appreciate that structural factors such as spousal interaction, gender equity, and parental education should be considered alongside broader structural and policy factors when designing population policies. Future studies should include men and couples to account for the interactive nature of decision-making, employ longitudinal and mixed-method designs to elucidate causal mechanisms, and examine regional as well as cultural variations across Iran. Additionally, examining how family support interplays with institutional policies like childcare, parental leave, and financial incentives could offer a more comprehensive approach to tackling the fertility issue. Overall, the findings highlight the importance of considering both family context and broader policy environments when addressing reproductive decision-making in Iran; however, causal relationships should be confirmed through longitudinal research.
Acknowledgements
The authors sincerely thank all the married women who kindly participated in this study and shared their valuable perspectives. We are also grateful to the staff of the Sarab health centers for their assistance and support during the data collection process.
Declaration of generative AI and AI-assisted technologies in the writing process
In preparing this manuscript, the authors utilized artificial intelligence (AI) tools specifically, OpenAI’s ChatGPT for support in language translation, grammar refinement, sentence structuring, and improving overall clarity. AI assistance was also used in organizing parts of the manuscript and ensuring consistency in academic tone and formatting. However, all intellectual content, scientific reasoning, data interpretation, and critical analysis were developed entirely by the authors. The AI did not generate original research ideas, draw scientific conclusions, or conduct any data analysis. All outputs from AI tools were carefully reviewed and edited by the authors to ensure accuracy and appropriateness for academic publication.
Authors' contributions
Saba Arabnezhad contributed to the study conception and design, data collection, and drafting of the initial manuscript. Amir Hossien Rostami assisted in study design, supervised data collection, and contributed to statistical analysis. Towhid Babazadeh provided methodological guidance, supported data analysis, and critically revised the manuscript for important intellectual content. Khalil Maleki Chollou assisted in literature review, data interpretation, and manuscript editing. Fatemeh Mousavinezhad contributed to participant recruitment, data collection, and preparation of tables and figures. Erfan Saeedi Tazekand conceived and supervised the study, performed statistical analyses, drafted and finalized the manuscript, and served as the corresponding author.All authors reviewed and approved the final manuscript and agree to be accountable for all aspects of the work.
Funding
This study was financially supported by Sarab Faculty of Medical Sciences.
Data availability
The datasets used during the current study are available from the corresponding author on reasonable request.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used during the current study are available from the corresponding author on reasonable request.