Abstract
BACKGROUND:
Childbearing is one of the most important determinants of population fluctuations. Identifying factors affecting childbearing is necessary for the proper implementation of population programs. This study aimed to determine the factors affecting childbearing intention among women employees in Birjand based on the theory of planned behavior.
MATERIALS AND METHODS:
In this descriptive-correlational study, 405 women employees in the offices of Birjand city in 2022 were selected by stratified random sampling and completed a two-part questionnaire including demographic information and questions related to the theory of planned behavior. The data were analyzed using SPSS v19 and Pearson's correlation, logistic regression, independent t-test, and ANOVA.
RESULTS:
The mean age of the participants in the study was 37.82 ± 6.39 years and the mean number of current children was 1.77 ± 0.92. The mean score of childbearing intention was 8.80 ± 3.06, the attitude was 66.04 ± 11.50, the subjective norm was 27.03 ± 6.95, and perceived behavioral control was 32.90 ± 7.80. Also, there was a significant negative and direct relationship between all the constructs of the theory of planned behavior and childbearing intention (P < 0.01). The variables of age, the number of current children, and the ideal number of children were predictors of childbearing intention. According to the standardized beta coefficients, the strongest predictor of intention was the number of current children (β = −0.464).
CONCLUSION:
The findings showed that various demographic factors are efficient in childbearing intention. The findings of this study can provide a picture of the current situation of factors affecting childbearing intention in society and be used as a guide for policymakers in fertility planning.
Keywords: Attitude, fertility, intention, women
Introduction
In recent years, significant demographic changes have occurred worldwide, and fertility and having children are the major determinants of demographic fluctuations.[1] With a decrease in the fertility rate and the transformation of natural fertility into controlled fertility, the population has gradually shifted from young to old age.[2] Iran currently has the lowest fertility rate in the Middle East.[3]
The national census in 2015 showed that while the birth rate has increased, the population growth rate has decreased compared to 2015, and the total fertility rate (TFR) in Iran is 2.[4] According to the current trend, TFR will reach less than the replacement rate in 2020–2025. This has led researchers to focus on increasing fertility rates.[2]
The desire for childbearing is one of the main issues in the field of demography, which is related to different quantitative and qualitative factors and is influenced by different demographic, economic, and social factors.[5,6] Among the factors affecting the reduction of childbearing are lifestyle changes, increasing individualism, changing attitudes from childbearing to parenting, rethinking the values of children, not wanting to be parents, and changing women's attitudes toward marriage and roles of wife and mother.[7,8,9] The results of studies on the impressive factors of childbearing show that age, education level, and economic status are the main determinants of childbearing intention among women, and women who have higher social participation, economic situation, and marital satisfaction have a lower tendency to childbearing.[10,11] The ideal number of children, sexual preferences, and gender socialization are other factors that affect women's desire to have children.[7] Women play a more active role than men in deciding and taking action in family planning. These are the main determinants of childbearing intention.[12] The duties of women in society and their ability to make decisions in family affairs and autonomy are essential factors for controlling their fertility. Social participation plays a decisive role in explaining childbearing intention.[13] Studies have shown that employed women have intra-occupational and extra-occupational challenges regarding childbearing, which move them towards having few children as a lifestyle method, and reducing childbearing is a price for acquiring social skills such as education, job, and income.[14]
Recent studies in the field of childbearing show that female employees follow the patterns of childlessness and delay in childbearing more than others.[14,15,16] Considering the influence of this group of women on other social groups in terms of fertility regulation methods and family formation patterns, they can spread their reproductive behavior to other social groups.[15] Various studies have been conducted on women and the factors affecting childbearing, but there is little information on the factors affecting childbearing in employed women. According to demographic policies, appropriate programs are needed to improve fertility levels. Health education needs to know the factors affecting behavior to make programs effective. Consequently, the roles of models and theories have been determined.[16] They can answer the questions of planners in this field about the reasons for not performing the desired behavior and how to change people's behaviors.[17] Studies have shown that the theory of planned behavior (TPB) is a suitable theoretical framework for determining factors affecting behavior.[18] According to this theory, an individual's behavioral intentions predict their behavior.[19] It is determined by attitude (desirability or undesirability of performing the behavior), subjective norm (perceived social pressure by the individual to perform the behavior), and perceived behavioral control (perceived difficulty or ease of performing the behavior).[20]
Having children is multifactorial, and it is affected by various individual, psychological, economic, social, cultural, demographic, and biological factors. Identifying the factors affecting childbearing is necessary for implementing population policies and programs. Therefore, this study was conducted to determine the factors affecting the intention to have children among working women in Birjand based on the TPB.
Materials and Methods
Study Design and Setting
This descriptive correlation study (cross-sectional type) was conducted in 2022 on women employees in the government offices of Birjand city.
Study Participants and Sampling
The sample size in this study was 405, which was calculated using the results of Bandehelahi et al.[21] with a 95% confidence level and 90% power. The women were selected using stratified random sampling. Offices based on the number of working women, in the form of classes under ten people, 10–20, 20–30, 30–40, 40–50, 50–60, 60–70, 70–80, 100–200 and more than 200 people (at a distance of 80–100 offices did not exist) were classified. The sample size was assigned to each category based on the volume of each floor. The inclusion criteria were women willing to participate in the study, employed in one of the offices of Birjand city, married, 18–49 years old, having a maximum of three children, no contraindications for pregnancy, no infertile, and no menopause.
Data collection tool and technique
The data collection tool was a demographic questionnaire and questionnaire on the intention to have children, designed based on the TPB and using brainstorming, study sources, and the existing questionnaire.[22] The questionnaire on childbearing intention included 43 items (childbearing intention (3 items), attitude (20 items), subjective norm (10 items), perceived behavioral control (10 items)), with a five-point Likert scale (from strongly disagree to strongly agree) and a score of 1 to 5 for each question. Obtaining a higher score in the construct of intention indicated a greater childbearing intention, and the constructs of attitude, subjective norm, and perceived behavioral control indicated an undesirable situation. The face and content validity of the questionnaire was confirmed by ten experts and professors of health education and midwifery with CVR > 0.62 according to the Lawshe table and CVI > 0.79. Reliability was evaluated using the method of internal consistency and test-retest. Finally, Cronbach's alpha was calculated. Cronbach's alpha and intraclass correlation coefficients (ICCs) for the intention construct (α = 0.74, ICC = 0.88), attitude (α = 0.79, ICC = 0.88), subjective norm (α = 0.70, ICC = 0.85), and perceived behavioral control (α = 0.78, ICC = 0.77) were calculated. After informed consent was obtained, a questionnaire was administered to the participants.
The data were analyzed using SPSS software v19 (SPSS Inc. Chicago, IL, USA). Quantitative variables were described by means and standard deviations, and qualitative variables using numbers and percentages. The Kolmogorov-Smirnov test was used to determine the normality of quantitative variables. The mean childbearing intention according to demographic variables was compared using an independent t-test and ANOVA with Tukey's post hoc test. Investigation of the relationship between variables was performed using the Pearson correlation coefficient and determining the predictors of the TPB constructs with logistic regression. The best model was selected based on the stepwise method with variable inclusion criteria at the alpha level of 0.1 and exclusion of 0.05, with the highest determination coefficient.
Ethical Consideration
Birjand University of Medical Sciences approved this study with the code of ethics (IR.BUMS.REC.1400.353). All information about the participants was kept confidential by the researchers and participants in the study were voluntary.
Results
A total of 405 female employees were surveyed. The mean age of the participating women and their spouses was 37.82 ± 6.39 and 40.71 ± 6.99 years, respectively. Most participants (43.2%) had two children. In addition, 57.3% of the participants had an undergraduate degree. The distributions of other demographic variables are presented in Table 1.
Table 1.
Distribution and comparison of childbearing intention based on demographic characteristics (n=405)
| Variables | Population distribution n (%) | Childbearing intention |
||
|---|---|---|---|---|
| Mean±SD | P | Post hoc | ||
| Education | ||||
| Underdiploma and diploma | 11 (2.7) | 8.36±2.46 | 0.389 | |
| Undergraduate | 232 (57.3) | 8.65±2.98 | ||
| Master and doctoral | 162 (40) | 9.05±3.21 | ||
| Spouse’s education | ||||
| Underdiploma and diploma | 78 (19.3) | 8.91±2.96 | 0.524 | |
| Undergraduate | 192 (47.4) | 8.62±3.11 | ||
| Master and doctoral | 135 (33.3) | 9±3.07 | ||
| Spouse’s occupation | ||||
| Employee (1) | 258 (63.7) | 8.60±3.04 | 0.001* | (2), (3) P=0.014 |
| Worker and self-employed (2) | 124 (30.6) | 9.36±3.11 | (4), (3) P=0.011 | |
| Retired (3) | 18 (4.4) | 7.05±1.92 | ||
| Unemployed (4) | 5 (1.2) | 11.80±2.16 | ||
| Type of employment | ||||
| Permanent (1) | 229 (56.5) | 8.46±3.07 | 0.038* | (1), (2) P=0.026 |
| Agreement (2) | 83 (20.5) | 9.02±2.82 | ||
| Contractual (3) | 68 (16.8) | 9.64±3.17 | ||
| Corporate (4) | 25 (6.2) | 8.92±3.13 | ||
| Place of residence | ||||
| Homeowner | 299 (73.8) | 8.66±3.03 | 0.242 | |
| Rental | 88 (21.7) | 9.12±3.12 | ||
| With family | 18 (4.4) | 9.61±3.32 | ||
| Economic self-assessment | ||||
| Good | 157 (38.8) | 8.68±3.18 | 0.559 | |
| Medium | 230 (56.8) | 8.93±3.03 | ||
| Bad | 18 (4.4) | 8.27±2.39 | ||
| Type of delivery | ||||
| Vaginal (1) | 151 (37.3) | 8.85±3.11 | >0.001* | (1), (4) P=0.014 |
| Cesarean section (2) | 163 (40.2) | 8.55±2.70 | (2), (4) P=0.002 | |
| Both (3) | 42 (10.4) | 7.78±3.05 | (3), (4) P<0.001 | |
| No history of delivery (4) | 49 (12.1) | 10.34±3.56 | ||
| Marital satisfaction | ||||
| Yes | 386 (95.3) | 8.80±3.07 | 0.896 | |
| No | 19 (4.7) | 8.89±3.14 | ||
*P≤0.05
There was a significant relationship between childbearing intention and spouse's occupation, type of employment, and type of delivery (P < 0.05). Using post hoc tests, it was found that childbearing intention was higher in women with unemployed spouses. Additionally, women with contractual employment status had more childbearing intentions than those with permanent employment status. Women without a history of delivery also had greater childbearing intentions [Table 1].
Table 2 presents the mean and standard deviation scores for childbearing intention, attitude, subjective norms, and perceived behavioral control. There was a significant negative and direct relationship between the TPB constructs and childbearing intention (P < 0.01). Also, perceived behavioral control has the highest relation with childbearing intention (r = −0.478).
Table 2.
Mean, standard deviation, and Pearson correlation between constructs of the theory of planned behavior
| Variables | Mean±SD | Pearson correlation |
|||
|---|---|---|---|---|---|
| Childbearing intention | Attitude | Subjective norm | Perceived behavioral control | ||
| Childbearing intention | 8.8±3.06 | 1 | |||
| Attitude | 66.04±11.5 | −0.276** | 1 | ||
| Subjective norm | 27.03±6.95 | −0.426** | 0.497** | 1 | |
| Perceived behavioral control | 32.9±7.8 | −0.487** | 0.576** | 0.465** | 1 |
**Significant Pearson correlation (P≤0.001)
Figure 1 shows the relationship between demographic variables and TPB constructs. There was a significant negative and direct relationship between childbearing intention and age (r = −0.321, P < 0.001), spouse's age (r = −0.331, P < 0.001), number of current children (r = −0.354, P < 0.001), number of female children (r = −0.189, P < 0.001), number of male children (r = −0.211, P < 0.001) and the age of the last child (r = −0.299, P < 0.001). So, with the increased mean of the mentioned variables, the mean childbearing intention decreased. Also, there was a significant positive and direct relationship between childbearing intentions and marriage age (r = 0.118, P = 0.017), the ideal number of children (r = 0.215, P < 0.001), and the frequency of sexual activity per month (r = 0.104, P = 0.041).
Figure 1.
Display of Pearson correlation coefficients between demographic variables and constructs of the theory of planned behavior. *P ≤ 0.05 **P ≤ 0.01
Regression analysis showed that age, the number of current children, and the ideal number of children are predictors of childbearing intention. According to the standardized beta coefficients, the strongest predictor of intentions was the number of present children (β = −0.464). So, for each child's birth, the tendency to have children decreases by 0.464 units [Table 3].
Table 3.
Regression model for predicting constructs of the theory of planned behavior based on demographic variables
| Constructs | Predictor variables | Unstandardized coefficient |
β | P | |
|---|---|---|---|---|---|
| B | S.E | ||||
| Childbearing intention | Age | −0.067 | 0.026 | −0.139 | 0.010 |
| Number of current children | −1.535 | 0.192 | −0.464 | <0.001 | |
| The ideal number of children | 1.282 | 0.135 | 0.449 | <0.001 | |
| Attitude | The ideal number of children | −4.000 | 0.496 | −0.380 | <0.001 |
| Marriage age | −0.311 | 0.136 | −0.107 | 0.023 | |
| Subjective norm | Number of current children | 2.105 | 0.386 | 0.282 | <0.001 |
| The ideal number of children | −2.481 | 0.335 | −0.384 | <0.001 | |
| The rank of spouse among siblings | −0.461 | 0.168 | −0.031 | <0.001 | |
| Perceived behavioral control | Number of current children | 3.217 | 0.425 | 0.381 | <0.001 |
| The ideal number of children | −2.568 | 0.357 | −0.362 | <0.001 | |
Discussion
This study investigated the factors affecting childbearing intention among female employees in Birjand based on the TPB. Demographic variables such as the age of the woman and her husband, the sex of the children, the age of the last child, the age of marriage, the number of current children, the ideal number of children, and the frequency of sexual activity were impressive on the desire to have children. Examining the relationship between the constructs of the TPB (attitude, subjective norm, and perceived behavioral control) with the childbearing intention showed a direct correlation between them. Improving the attitude toward having children increased the childbearing intent among women employees. The subjective norm construct was also efficient in the decision to have children, which indicates the influence of important people in life on the level of behavior compliance. Regression analysis showed that age, number of current children, and number of ideal children predict the intent to have children, and the number of present children is the strongest predictor.
In the present study, as the age of the woman and her husband increased, the desire to have children decreased, which is consistent with the results of other studies.[23,24,25,26] More aged people have less desire to have children, probably they have reached the ideal number of children with increasing age.
The findings showed that the sex of children affected childbearing, which is consistent with Bandehelahi's study.[21] Having children of the same sex has increased the intent to have children, which can be justified by the tendency to have both girls and boys in Iranian couples.
Our results show a direct and positive relationship between the age of marriage and the intention to have children. In other words, a decrease in the age of marriage reduces it, and marrying at an older age increases the chances of fertility, which is not similar to the results of other studies.[27,28] This contrast is probably due to the low marriage age of the women included in the present study, with an average of about 24 years. Women with a lower marriage age still have enough opportunity to have children; however, people with a higher marriage age will have a greater desire to have children due to approaching the end of their reproductive age. Also, young women may have less childbearing intentions due to the characteristics of the new generation.
According to the results of the present study, with the increase in the number of present children, the desire to have children decreased, which is consistent with other studies.[13,23,29] Similarly, Dommermuth et al. showed that people without children intended to have children more than people with children.[30] There was a direct and positive relationship between the ideal number of children and the intention to have children, meaning that the participants considering more children to be ideal had a greater desire to have children.
According to the results of this study, the participants who intended to have children had more sexual intercourse during the month and vice versa, which was similar to the findings of Heywood et al.[31]
No relationship was observed between the education level of couples, and economic status to childbearing intention, which conflicted with the findings of other studies.[32,33,34] The high education of the participants in this study can be the reason for this inconsistency because the significant majority of women had academic education. Regarding economic status, some studies have shown that people with higher income have less desire to have children[32]; however, in other studies, the improvement in the economic situation increased the intention to have children.[33] That can be due to the unrealistic answer of the participants about their economic status.
The results showed that the attitude toward having children, subjective norms, and perceived behavioral control are the factors that determine the intention to have children, which is consistent with the results of other studies. Perceived behavioral control had the highest correlation with the desire to have children, so behavioral intention increased with the improvement of perceived behavioral control, as in Erfani's study.[35] Similar to Bandehelahi's study, the average score of intention to have children increased with the improvement of the subjective norm.[21] The relationship between the intent and the subjective norm shows the influence of important people in life in following the behavior. Also, there was a direct relationship between the attitude and the intention to have children, in such a way that with a more positive attitude towards having children, the intention to have children increased, which was in line with the results of Khorram's study.[28] Based on these results, the TPB is suitable for investigating the intention to have children.
Conclusions
The findings showed that demographic factors such as the age of the woman and her husband, the sex of the children, the age of the last child, the age of marriage, the number of current children, the ideal number of children, and the frequency of sexual activity are efficient in childbearing intention. The findings of this study provide a picture of the current situation of factors affecting childbearing intent in society and can be used as a guide for the authorities in fertility planning.
Limitation and Recommendation
One of the limitations of this study was the target population, who were merely women employees in government offices. It is suggested to conduct more research on housewives and women employees in private institutions.
Financial support and sponsorship
This study was financially supported by Birjand University of Medical Sciences, Birjand, Iran.
Conflicts of interest
There are no conflicts of interest.
Acknowledgments
We thank the participants in the study and all those who helped us in this research.
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