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The impact of work-family conflict on Chinese women’s fertility intention: the role of fertility attitude, income class, and child-rearing burden

BMC Women's Health volume 24, Article number: 557 (2024) Cite this article

Abstract

The struggle women face in balancing work and family roles is a significant factor contributing to the decline in their fertility intentions. Therefore, work-family conflict serves as a crucial determinant influencing women’s fertility intentions. This study aims to explore the internal mechanism between work-family conflict and the fertility intentions of Chinese women, using data obtained from 334 questionnaires. Data analysis was conducted using Mplus 8.0. The following conclusions were drawn: (1) There is a negative correlation between work-family conflict and women’s fertility intentions. (2) Fertility attitudes play a mediating role in the relationship between work-family conflict and women’s fertility intentions. (3) The relationship between work-family conflict and women’s fertility intentions is moderated by income class. (4) The relationship between work-family conflict and women’s fertility intentions is moderated by women’s child-rearing burden. The findings of this study provide a foundation for governments at all levels to formulate population policies.

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Introduction

According to Yang et al. [41], China is experiencing a sustained decline in fertility rates among women of childbearing age, leading to concerns over low population growth. In 2022, the number of births fell below 10 million for the first time since the establishment of the People’s Republic of China, resulting in negative population growth. The 60 + population in China is projected to reach nearly 300 million from 2021 to 2025, comprising over 20% of the total population. Moreover, Zhai and Liu [43] estimate that the working-age population, which was approximately 900 million in 2018, will decline to 830 million by 2030 and to 700 million by 2050. As the effects of the newly implemented population policy wane and the number of women of childbearing age decreases, there is a growing risk of continued birth rate decline [17]. Work-family conflict, which is defined as an inter-role conflict with incompatible pressures from work and family roles [15], can be an important factor influencing women’s fertility intention [9]. This conflict may intensify, particularly in countries with high job strain or inadequate childcare options, as well as in societies that expect women to balance both career development and family responsibilities, which in turn can impact women’s fertility intentions [30, 36]. Given this background, it is worthwhile to further explore the impact of work-family conflict on fertility intention using Chinese women as the research focus.

Currently, scholars have examined the influences of fertility policies [6], socioeconomic and cultural factors [18, 26], regional security systems [31], and housing price fluctuations [16] on fertility intentions. However, research specifically focusing on individual female and family factors remains relatively limited. Among numerous influencing factors, fertility attitude encompasses individuals’ values regarding the entirety of the fertility process [44]. Fertility attitude partly reflects fertility intention but differs in focus: while fertility attitude primarily mirrors personal motivations regarding fertility, intention centers on preferences for the number, spacing, gender, and birth order of children [44]. Influenced by societal contexts, fertility attitude may vary across life stages, potentially creating disparities between desired and actual fertility rates [14]. Women often face challenges in balancing family and work responsibilities, which impact their fertility choices [29, 42], suggesting that fertility attitude plays a role in shaping the relationship between work-family conflict and fertility intentions. In real-world scenarios, women from different income classes may perceive work-family conflict differently due to disparities in financial status, occupational demands, and societal expectations, which can consequently impact their fertility intentions in diverse ways [8]. Nevertheless, existing research on the impact of income levels on fertility intentions has yielded inconclusive findings. Some studies suggest that women in higher income brackets demonstrate stronger fertility intentions [42], while others challenge this conclusion [39]. For a long time, traditional Chinese culture has adhered to the family division of labor model, where men primarily serve as earners and women assume homemaking duties. Within such a cultural context, the influence of work-family conflict on women’s childbearing burdens significantly relates to the responsibility of childcare [30]. However, as an increasing number of modern women actively embrace their era, pursue their dreams, and advocate for their rights, women have assumed significant roles in various sectors, including economics, education, and politics. Changes have been observed in the traditional family division of labor in Chinese households, necessitating further exploration into the influence and extent of childrearing burdens on the relationship between work-family conflict and women’s fertility intentions.

Therefore, actively studying the underlying mechanisms between work-family conflict and Chinese women’s fertility intentions, and formulating policies accordingly, can yield positive implications for mitigating the ongoing decline in birth rates.

Theoretical review and research hypotheses

Work-family conflict and women’s fertility intentions

Women facing work conflicts are confronted with a direct dilemma between their careers and childbearing, which can have adverse effects on their ability and willingness to expand their families [33, 42]. The strain and fatigue resulting from balancing work and family responsibilities can diminish women’s capacity for personal activities, such as nurturing children and planning for childbirth [41]. Job-related anxieties often manifest as impatience or irritability at home, and these negative reactions may hinder women’s fertility intentions [38]. Moreover, women experiencing work-family conflicts may reassess the value of childbirth due to the challenges they face, potentially leading to unfavorable fertility attitudes [29, 42]. Societal or professional pressures can further contribute to the postponement or abandonment of childbirth among these women [7]. Lastly, high levels of work-family conflict can diminish job satisfaction for women, which can in turn impact their decisions regarding family planning [19]. Based on these considerations, we propose the following hypothesis:

H1:

There is a negative correlation between work-family conflict and women’s fertility intentions.

The mediating role of fertility attitudes

Work-family conflicts have the potential to impact women’s attitudes toward childbirth. Firstly, the juggling of career demands and family obligations often intensifies stress levels for women. This heightened pressure can have a negative effect on their subjective well-being, which in turn can influence their eagerness to initiate or expand their families [28, 42]. Secondly, work-family conflicts disrupt the delicate balance between women’s work and family roles, creating recurring discord that can lead to familial tensions and reduced marital satisfaction [1]. Consequently, this can dampen women’s fertility intentions [42]. Lastly, work-family conflicts can give rise to disagreements between partners regarding child-rearing and fulfilling family responsibilities. Such discord can impede the establishment of consensus on fertility preferences or even result in decisions against having children [24]. At the same time, women’s fertility attitudes can also influence their fertility intentions. Research indicates that positive fertility attitudes are associated with greater intentions to have children, while negative attitudes may deter individuals from pursuing parenthood [21]. Based on these considerations, we propose the following hypothesis:

H2:

Fertility attitudes play a mediating role in the relationship between work-family conflict and women’s fertility intentions.

The moderating role of income class

Income class may also play a role in moderating the relationship between women’s work-family conflict and fertility intentions [3, 4, 8]. For women in lower-income classes, work-family conflicts have the potential to decrease fertility intentions. They may opt to delay childbirth or limit the number of children to ensure economic stability [19, 37, 38]. In contrast, women in higher-income classes enjoy more opportunities to access quality occupational benefits and social resources, as well as possess greater financial capabilities to mitigate the challenges posed by work-family conflicts [13, 22, 42]. In other words, high-income women may have more flexibility in balancing work and family life, which can influence their fertility intentions [39]. Therefore, we propose the following hypothesis:

H3:

The relationship between work-family conflict and women’s fertility intentions is moderated by income class.

The moderating role of women’s childrearing burden

In China, despite the potential for career success, women continue to shoulder the primary responsibility for childbirth and child-rearing, thereby increasing their burden in child-rearing. In societies where traditional gender roles assign the primary responsibility of child-rearing to women, the burden tends to be higher [35]. When all other factors are held equal, compared to societies where the responsibility of child-rearing is more evenly distributed, societies where mothers primarily bear the responsibility tend to have lower total fertility rates [10]. Women address the competing demands of work and family by reducing their familial responsibilities, including having fewer children [5, 27]. Especially for women with limited social support and resources, concerns about increased burdens in child-rearing can lead to a decrease in fertility intentions [2]. Therefore, we propose the following hypothesis:

H4:

The relationship between work-family conflict and women’s fertility intentions is moderated by women’s child-rearing burden.

We propose a research model and shown in Fig. 1.

Fig. 1
figure 1

Research Model

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Methods

Sample and data collection procedures

Data collection for this study took place from April to August 2023. The initial section of the questionnaire outlined the study’s purpose and provided an explanation of the requirements to complete the questionnaire items. The succeeding part comprised the measurement items for each category. All participants completed the entire questionnaire anonymously. Additionally, to minimize participants from guessing answers, the items were presented in a randomized order.

According to the theme of this study, participants must meet two criteria: being married (according to Chinese law, the legal marriage age for women is 20 years old, so married women also meet the age requirement for childbirth) and being employed. Considering the disparities in economic development levels and varying social customs across different regions of China, which may influence women’s fertility intention, efforts were made to recruit participants from diverse regions and provinces of China. Participants were invited through various social media platforms and asked to complete the survey questionnaire via provided links. A total of 400 female participants were recruited for this study. Out of the 400 questionnaires distributed, 365 completed questionnaires were received. After excluding invalid questionnaires due to logical errors or incomplete responses, we retained 334 valid responses. Among these 334 valid questionnaires, 127 participants were from eastern provinces such as Jiangsu, Zhejiang, Fujian, and Guangdong; 109 were from central regions like Shanxi, Henan, Hubei, and Hunan; and 98 were from western provinces like Ningxia, Gansu, and Qinghai. The demographic characteristics of the participants are presented in Table 1.

Table 1 Descriptive statistics of respondents
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Measurement

The measurement of work-family conflict utilized the scale developed by Netemeyer et al.[32]. This scale consists of 5 items, with one representative item being, " My work interferes with my family and home life.”

For the measurement of fertility intentions, the Fertility Intention Scale (FIS) developed by Zhu et al. [45] was referenced. This scale encompasses 21 items across 5 dimensions: social support, fertility risk, disease control, happiness, and fertility values. A representative item from this scale is, “The additional physical strain of pregnancy does not lessen my desire to have children.”

The measurement of fertility attitudes drew from the scales developed by Klobas [12, 20]. This scale comprises 6 items and assesses attitudes towards costs and benefits of fertility decisions. A representative question from this scale is, “If you were to have another child in the next three years, would your freedom to do things likely get better or worse?”

The measurement of income class was conducted using the methods outlined by Li & Zhang [25, 40]. Annual income data were averaged and categorized into seven segments in ascending order, with values assigned from 1 to 7. Higher values indicate higher income classes. Annual income data were averaged and categorized into seven segments in ascending order, with values assigned from 1 to 7, where higher values indicate higher income levels. In this study, the average income of the sample’s region was used as a reference point (equal to 4) during data collection. Specifically, incomes ranging from 70 to 99% of the local average were rated as 3, incomes from 40 to 69% were rated as 2, and incomes below 40% were rated as 1. Conversely, incomes above the local average but below 1.5 times the local average were rated as 5, incomes from 1.5 to 2 times the local average were rated as 6, and incomes exceeding 2 times the local average were rated as 7.

This study measured women’s child-rearing burden by referencing the method of Yue & Yang (2023). It extracted and appropriately revised all four relevant questions regarding women’s child-rearing burden from the 2014 CFPS questionnaire. For women who have children, the questions were: “After having children, who primarily takes care of your children during the day?“, “After having children, who primarily takes care of your children at night?“, “After having children, who primarily helps your children with their homework?“, and “After having children, who primarily takes your children to kindergarten/pre-school?” For women without children, the questions were: “After having children, who will primarily take care of your children during the day?“, “After having children, who will primarily take care of your children at night?“, “After having children, who will primarily help your children with their homework?“, and “After having children, who will primarily take your children to kindergarten/pre-school?” The response options for these questions were categorized into three types: mother, father, and others. Considering that the question about taking children to kindergarten/pre-school is only relevant to families with children aged 3–6, for families with children in this age group, women’s child-rearing burden is the weighted average of these four variables. If the surveyed household does not have children in this age group, women’s child-rearing burden is the weighted average of the first three variables. A higher value indicates a higher women’s child-rearing burden.

This study relied on the research findings of established scholars [17]; Yue & Yang, 2023) and identified control variables such as women’s age, number of children, education level and hukou status to mitigate their influence on analyzing the relationship between work-family conflict and fertility intentions.

Tools

In this study, Mplus8.0 was used for data analysis.

Results

Reliability and validity

As demonstrated in Table 2, the factor loadings of the items were above 0.60, the composite reliability (CR) values for each variable ranged from 0.80 to 0.90, and the average variance extracted (AVE) values were above 0.50. These results indicate good reliability and convergent validity. Furthermore, as shown in Table 3, the square root value of the AVE for each variable was greater than the correlation coefficient between variables. This finding suggests that the model possesses good discriminant validity.

Table 2 Results of CFA and reliability and validity tests (excluding income class)
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Table 3 Variables’ correlation coefficient and the square root of AVE (excluding income class)
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Model fit

The model fit indices were χ2/df = 2.87, CFI = 0.94, TLI = 0.91, RMSEA = 0.06, and SRMR = 0.07, indicating that the model had a good fit.

Direct and indirect effects

As presented in Table 4, the total effect of work-family conflict on fertility intentions was − 0.42 (p < 0.001). The direct effect was − 0.34 (p < 0.001), supporting H1. Additionally, the indirect effect was − 0.09 (p < 0.001). The bootstrap analysis, conducted 5000 times, illustrated that the 95% confidence interval of the indirect effect did not include 0, providing support for H2.

Table 4 Test of mediating effect
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Moderating effect

Table 5 reveals that the interaction effect between work-family conflict and income class is 0.09 with a standard error of 0.02 (p < 0.01), suggesting that income class played a moderating role in the relationship between work-family conflict and fertility intentions, endorsing H3. Similarly, the interaction effect between work-family conflict and child-rearing burden is -0.07, with a standard error of 0.02 (p < 0.01), indicating that child-rearing burden also acts as a moderator in this relationship, confirming H4.

Figure 2 shows the moderating role of income class, with a flatter slope for those in the higher income class suggesting a diminished negative effect of work-family conflict on fertility intentions as income increases. In contrast, Fig. 3 shows the moderating effect of the child-rearing burden, where a sharper slope for those with a heavier burden indicates a stronger negative influence of work-family conflict on fertility intentions with rising child-rearing burden.

Table 5 Test of moderating effect
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Fig. 2
figure 2

The moderating effect of income class (IC)

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Fig. 3
figure 3

The moderating effect of child-rearing burden (CRB)

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Discussion

Theoretical contributions

Firstly, this study further substantiates the impact of work-family conflict on female fertility intentions, aligning with the perspectives of previous scholars [9, 33, 42]. Notably, cultural norms have been identified as a significant factor. Various cultures encourage larger families, while others prioritize smaller families for economic reasons [11]. This suggests that the negative correlation between work-family conflict and female fertility intentions holds true across different social and cultural contexts.

Secondly, there is ongoing debate among scholars regarding the moderating effect of income class on the relationship between work-family conflict and female fertility intentions [39, 42]. The findings of this study support the perspectives of certain scholars [19, 37, 38, 42].

Lastly, this study delves into the significance of individual factors, such as fertility attitudes and childcare burdens. This exploration offers a fresh perspective for better comprehending the underlying mechanisms of work-family conflict and female fertility intentions.

Practical implications

The first strategy involves fostering a family-friendly corporate environment. This includes promoting flexible working hours and remote work options to accommodate employees’ familial needs. Moreover, companies can offer childcare services and lactation rooms for parents. It is essential to enhance maternity and paternity leave policies, ensuring adequate time off for bonding with newborns. Providing workplace retraining and career development support facilitates a smooth return to work post-childbirth and promotes career advancement. Strengthening internal communication, fostering inclusivity, and creating an environment that values work-life balance are also critical.

The second strategy focuses on reshaping young people’s attitudes toward reproduction. Establishing specialized fertility education institutions or departments to deliver comprehensive reproductive education and guidance services is crucial. Supporting young individuals in understanding the importance of fertility through mediums like social media and interactive activities is effective. This approach aims to boost confidence and readiness among young people of childbearing age.

The third strategy involves implementing inclusive tax policies. The government could consider reducing or exempting taxes related to childcare expenses, such as education and childcare costs, to ease the financial burden of raising children. Establishing a maternity allowance scheme to cover childbirth-related expenses would provide much-needed financial support. Allowing families to deduct childcare expenses as pre-tax deductions could make childbearing economically viable. Extending paid maternity leave would further alleviate financial pressures during the childbearing period and encourage childbirth.

Lastly, the fourth strategy proposes establishing a robust public childcare network. Many European countries have implemented comprehensive public childcare services, significantly reducing the childcare burden on mothers and boosting women’s motivation to have children [23, 34]. While China’s current fertility support policies extend maternity leave and increase maternity allowances, these measures may inadvertently reinforce women’s role as primary caregivers, potentially discouraging childbirth.

Limitations and future directions

First of all, this study utilized cross-sectional data, which provides valuable insights into the current status of the variables under investigation. However, future research can further strengthen the understanding of cause-and-effect relationships between variables by utilizing longitudinal data which captures changes over time.

Secondly, this study focuses on the impact of women’s fertility attitudes on fertility intentions. According to the theory of planned behavior, subjective norms and perceived behavioral control significantly influence individual behavioral intentions. Scholars such as Hu et al. [17] have extensively studied these aspects, offering new perspectives on women’s fertility intentions. Future research can further explore these insights.

Thirdly, to enhance the generalizability of the findings given the study’s focus, the sample was drawn from diverse regions and provinces of China. However, factors such as regional economic levels, social customs, cultural traditions, and fertility beliefs can all influence women’s fertility intentions. Therefore, it is important to explore whether the sample includes different subgroups based on these factors, whether these subgroups lead to varying conclusions, and whether there is mobility among individuals across these subgroups. To address these questions, effective collection of longitudinal data is needed, followed by further exploration using latent profile analysis and latent transition analysis.

Finally, it is essential to acknowledge that female fertility intention can be influenced by a wide array of factors, traditional family values, culture background, education level, and other societal factors. Considering the impact of additional variables in future studies can help broaden our understanding and provide a more comprehensive analysis of the results.

Data availability

Data is provided within the manuscript.

References

  1. Balbo N, Arpino B. The role of family orientations in shaping the effect of fertility on subjective well-being: a propensity score matching approach. Demography. 2016;53(4):1–24. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s13524-016-0480-z.

    Article  Google Scholar 

  2. Baxter J, Hewitt B, Haynes M. Life course transitions and housework: marriage, parenthood, and time on housework. J Marriage Family. 2008;70(2):259–72. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1741-3737.2008.00479.x.

    Article  Google Scholar 

  3. Bijlsma MJ, Wilson B. Modelling the socio-economic determinants of fertility: a mediation analysis using the parametric g-formula. J Royal Stat Soc Ser A- Stat Soc. 2020;183(2):493–513. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/rssa.12520.

    Article  Google Scholar 

  4. Bollen KA, Glanville JL, Stecklov G. Socio-economic status, permanent income, and fertility: a latent-variable approach. Popul Stud. 2007;61(1):15–34. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/00324720601103866.

    Article  Google Scholar 

  5. Brinton MC, Oh E. Babies, work, or both? Highly educated women’s employment and fertility in east Asia. Am J Sociol. 2019;125(1):105–40. https://doiorg.publicaciones.saludcastillayleon.es/10.1086/704369.

    Article  Google Scholar 

  6. Cai Y. China’s below-replacement fertility: government policy or socioeconomic development? Popul Dev Rev. 2010;36(3):419. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1728-4457.2010.00341.x.

    Article  PubMed  Google Scholar 

  7. Chen G, Zhang J, Hu Y, Gao Y. Gender role attitudes and work-family conflict: a multiple mediating model including moderated mediation analysis. Front Psychol. 2022;13. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fpsyg.2022.1032154.

  8. Cooke LP. Gender-class equality in political economies. Am J Sociol. 2013;119(1):281–3. https://doiorg.publicaciones.saludcastillayleon.es/10.1086/670387.

    Article  Google Scholar 

  9. Cukrowska-Torzewska E, Matysiak A. The motherhood wage penalty: a meta-analysis. Soc Sci Res. 2020;88–89. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ssresearch.2020.102416.

  10. Doepke M, Kindermann F. Bargaining over babies: theory, evidence, and policy implications. Am Econ Rev. 2019;109(9):3264–306. https://doiorg.publicaciones.saludcastillayleon.es/10.1257/aer.20160328.

    Article  Google Scholar 

  11. Domar AD, Clapp D, Slawsby E, Kessel B, Orav J, Freizinger M. The impact of group psychological interventions on distress in infertile women. Health Psychol. 2000;19(6):568–75. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/0278-6133.19.6.568.

    Article  PubMed  CAS  Google Scholar 

  12. Dommermuth L, Klobas J, Lappegard T. Realization of fertility intentions by different time frames. Adv life Course Res. 2015;24:34–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.alcr.2015.02.001.

    Article  PubMed  Google Scholar 

  13. Dribe M, Breschi M, Gagnon A, Gauvreau D, Hanson HA, Maloney TN. Socio-economic status and fertility decline: insights from historical transitions in Europe and North America. Popul Stud. 2017;71(1):3–21. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/00324728.2016.1253857.

    Article  Google Scholar 

  14. Gauthier AH. The impact of family policies on fertility in industrialized countries: a review of the literature. Popul Res Policy Rev. 2007;26(3):323–46. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11113-007-9033-x.

    Article  Google Scholar 

  15. Greenhaus JH, Beutell NJ. Sources of conflict between work and family roles. Acad Manage Rev. 1985;10(1):76–88. https://doiorg.publicaciones.saludcastillayleon.es/10.5465/AMR.1985.4277352.

    Article  Google Scholar 

  16. Hou J, Yue N, Zhang L. Housing price and the willingness of floating populations to reproduce: a perspective of social integration. J Hunan Univ (Social Sciences) (Chinese). 2023;37(5):54–63. https://doiorg.publicaciones.saludcastillayleon.es/10.16339/j.cnki.hdxbskb.2023.05.008.

    Article  Google Scholar 

  17. Hu A, Yang M, Bao Y. The impacts of work-family conflict on the second-child fertility intention among Chinese urban employees: a study based on the theory of planned behavior. Popul Dev (Chinese). 2023;29(3):34–48.

    Google Scholar 

  18. Iwata S, Naoi M. The asymmetric housing wealth effect on childbirth. Rev Econ Househ. 2017;15(4):1373–97. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11150-016-9355-8.

    Article  Google Scholar 

  19. Jiang M, Wu Z, He B, Tu A, Wu Y. Effect of work–family conflict on three-child fertility intention of working women of reproductive age under the background of active reproductive support: the moderating and mediating effects of anxiety disorders and life stress. Sustainability. 2022;14(21). https://doiorg.publicaciones.saludcastillayleon.es/10.3390/su142114615.

  20. Klobas J. Social psychological influences on fertility intentaons: A study of eight countries in different social, economic and policy contexts (Report to the European Commission within the Project Reprodudecisioncision-makingmacro-micro-perspectiveective. Issue: REPRO); 2010.

    Google Scholar 

  21. Kohan S, Gholami M, Shaghaghi F, Mohebbi-Dehnavi Z. Investigating the relationship between attitudes toward fertility and childbearing and the value of children with attitudes toward fertility control in married women aged 15–45 in Isfahan. J Educ Health Promotion. 2022;11(1). https://doiorg.publicaciones.saludcastillayleon.es/10.4103/jehp.jehp_1858_21.

  22. Lappeg RT, Klüsener S, Vignoli D. Why are marriage and family formation increasingly disconnected across Europe? A multilevel perspective on existing theories. Popul Space Place. 2017. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/psp.2088.

    Article  Google Scholar 

  23. Laroque G, Salanié B. Identifying the response of fertility to financial incentives. J Appl Econom. 2014;29(2):314–32. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/jae.2332.

    Article  Google Scholar 

  24. Latshaw BA, Yucel D. Work-family conflict and partners’ agreement on fertility preferences among dual-earner couples: does women’s employment status matter? J Family Res. 2022;34(4):1151–74. https://doiorg.publicaciones.saludcastillayleon.es/10.20377/jfr-689.

    Article  Google Scholar 

  25. Li P, Zhang Y. The scope, identity and social attitudes of the middle class in China. Soc (Chinese). 2008;28(2):1–19. https://doiorg.publicaciones.saludcastillayleon.es/10.15992/j.cnki.31-1123/c.2008.02.003.

    Article  Google Scholar 

  26. Lin P, Chang C, Sing T. Do housing options affect child birth decisions? Evidence from Taiwan. Social Sci E- lectronic Publishing. 2015;53(16):3527–46. https://doiorg.publicaciones.saludcastillayleon.es/10.1177/0042098015615742.

    Article  Google Scholar 

  27. Liu S, Hynes K. Are difficulties balancing work and family associated with subsequent fertility? Fam Relat. 2012;61(1):16–30. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1741-3729.2011.00677.x.

    Article  Google Scholar 

  28. Luppi F, Mencarini L. Parents’ subjective well-being after their first child and declining fertility expectations. Demographic Res. 2018;39:285–314. https://doiorg.publicaciones.saludcastillayleon.es/10.4054/DemRes.2018.39.9.

    Article  Google Scholar 

  29. Matysiak A, Mencarini L, Vignoli D. Work–family conflict moderates the relationship between childbearing and subjective well-being. Eur J Popul. 2016;32(3):355–79. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10680-016-9390-4.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Mills M, Mencarini L, Tanturri ML, Begall K. Gender equity and fertility intentions in Italy and the Netherlands. Demographic Res. 2008;18:1–26. https://doiorg.publicaciones.saludcastillayleon.es/10.4054/DemRes.2008.18.1.

    Article  Google Scholar 

  31. Mohabir N, Jiang Y, Ma R. Chinese floating migrants: rural- urban migrant labourers’ intentions to stay or return. Habitat Int. 2017;60:101–10. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.habitatint.2016.12.008.

    Article  Google Scholar 

  32. Netemeyer RG, Boles JS, Mcmurrian R. Development and validation of work-family conflict and family-work conflict scales. J Appl Psychol. 1996;81(4):400–10. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/0021-9010.81.4.400.

    Article  Google Scholar 

  33. Nilsen W, Skipstein A, Ostby KA, Mykletun A. Examination of the double burden hypothesis—a systematic review of work–family conflict and sickness absence. Eur J Pub Health. 2019;29(3):465–71. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/eurpub/ckx054.

    Article  Google Scholar 

  34. Raute AC. Can financial incentives reduce the baby gap? Evidence from a reform in maternity leave benefits. J Public Econ. 2019;169:203–22. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jpubeco.2018.07.010.

    Article  Google Scholar 

  35. Sayer LC. Gender, time and inequality: trends in women’s and men’s paid work, unpaid work and free time. Soc Forces. 2005;84(1):285–303. https://doiorg.publicaciones.saludcastillayleon.es/10.1353/sof.2005.0126.

    Article  Google Scholar 

  36. Schieman S, Glavin P, Milkie MA. When work interferes with life: work-nonwork interference and the influence of work-related demands and resources. Am Sociol Rev. 2009;74(6):966–88. https://doiorg.publicaciones.saludcastillayleon.es/10.1177/000312240907400606.

    Article  Google Scholar 

  37. Schneider D, Hastings OP. Socioeconomic variation in the effect of economic conditions on marriage and nonmarital fertility in the United States: evidence from the great recession. Demography. 2015;52(6):1893–915. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s13524-015-0437-7.

    Article  PubMed  Google Scholar 

  38. Shreffler KM, PirrettiRobert AE, Drago R. Work–family conflict and fertility intentions: does gender matter? J Fam Econ Issues. 2010;31(2):228–40. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10834-010-9187-2.

    Article  Google Scholar 

  39. Tarca V, Tarca E, Luca FA. The impact of the main negative socio-economic factors on female fertility. Healthc (Basel). 2022;10(4). https://doiorg.publicaciones.saludcastillayleon.es/10.3390/healthcare10040734.

  40. Trapeznikova I. Measuring income inequality. IZA World Labor. 2019;462. https://doiorg.publicaciones.saludcastillayleon.es/10.15185/izawol.462.

  41. Yang X, Li W, Li R. Examining the influence of fertility policy adjustments on gender equality in China during the period of exceptionally slow population growth. China CDC Wkly. 2023;5(27):605–8. https://doiorg.publicaciones.saludcastillayleon.es/10.46234/ccdcw2023.116.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Zeng Z, Ma J, Ma Y, Li D, Sun Y. Born or not: A moderated mediation model of the relationship between work-family conflict and female employees’ wellbeing based on fertility intention during the COVID-19 pandemic. Front Public Health. 2023;11. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fpubh.2023.1093048.

  43. Zhai Z, Liu W. Data quality of the 7th population census and new developments of China’s population. Popul Res. 2021;45(3):46–56. kns.cnki.net/kcms/detail/detail.aspx?dbname = DKFX. 2021&filename = RKYZ202103004&dbcode = DKFX.

    Google Scholar 

  44. Zheng G, An S. Intergenerational differences in Pingdi Yao’s fertility attitudes and cause analysis: based on the field work in a Pingdi Yao Village in Fuchuan, Guangxi. J Hunan Agricultural Univ (Social Sciences) (Chinese). 2021;22(1):9–17. https://doiorg.publicaciones.saludcastillayleon.es/10.13331/j.cnki.jhau(ss).2021.01.002.

    Article  Google Scholar 

  45. Zhu F, Liu C, Chen Q, Qiang W, lU Q. Revision and psychometric evaluation of a fertility intention scale for young women with breast cancer in Chinese mainland. Asia-Pacific J Oncol Nurs. 2023;10(9). https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.apjon.2023.100264.

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Funding

This manuscript is supported by the Doctoral Research Foundation of Pingdingshan University (PXY-BSQD-2022041) and the Ministry of Education’s Humanities and Social Sciences Planning Youth Project (21YJC710075).

Author information

Authors and Affiliations

  1. Henan University of Animal Husbandry and Economy, Zhengzhou, China

    Zhiwei Li

  2. School of Economics Management, Pingdingshan University, Southern Section of Weilai Road, Xincheng District, People’s Republic of China, Pingdingshan, Henan Province, China

    Jianpeng Fan & Xiaoxue Zhang

  3. Hangzhou Dianzi University, Hangzhou, China

    Yuange Xing & Ge Peng

Authors
  1. Zhiwei Li
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  2. Jianpeng Fan
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  3. Yuange Xing
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  4. Ge Peng
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  5. Xiaoxue Zhang
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Contributions

Zhiwei Li and Jianpeng Fan wrote the main manuscript text, Yuange Xing, Ge Peng and Xiaoxue Zhang prepared figures 1-3. All authors reviewed the manuscript.

Corresponding author

Correspondence to Jianpeng Fan.

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In accordance with the Declaration of Helsinki, this study was reviewed and approved by the Ethics Review Committee of the School of Economics and Management at Pingdingshan University (approval number: EA-2023127). Written consent was obtained after participants were informed about the study and expressed their willingness to participate.

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Appendix

Appendix

Items measuring fertility intentions.

  1. 1.

    I am confident in my ability to maintain good health after childbirth.

  2. 2.

    I believe I can sustain good health after giving birth.

  3. 3.

    I feel capable of effectively managing postpartum depression and other symptoms.

  4. 4.

    I think my health condition allows me to conceive.

  5. 5.

    I believe that pregnancy will not place an additional burden on my body.

  6. 6.

    I feel that I can handle pregnancy.

  7. 7.

    I believe I can take good care of a future child.

  8. 8.

    I think pregnancy will not pose any health risks.

  9. 9.

    If I were to become pregnant, I believe I would be safe.

  10. 10.

     If I were to become pregnant, I believe my child would be safe.

  11. 11.

     I feel financially prepared to support a future child.

  12. 12.

     I believe I will have support in caring for my future child.

  13. 13.

     I think I have received sufficient information about conceiving again.

  14. 14.

     I believe I will receive adequate care and support during pregnancy and in raising a child.

  15. 15.

     I think that pregnancy would make me happier.

  16. 16.

     I believe that pregnancy would bring me new hope.

  17. 17.

     I feel that a future child would bring me irreplaceable happiness.

  18. 18.

     I believe that a future child would be a source of motivation for my efforts.

  19. 19.

     I think having children represents an ideal family structure.

  20. 20.

     I believe that children can provide support for elderly parents in the future.

  21. 21.

     I feel that having multiple children would ease the future burden of supporting elderly parents.

Items measuring income class

Your household income is approximately what percentage of the local average income level?

(1) < 40% (2) 40–69% (3) 70–99% (4) Approximately 100%.

(5) 101–149% (6) 150–200% (7) > 200%.

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Li, Z., Fan, J., Xing, Y. et al. The impact of work-family conflict on Chinese women’s fertility intention: the role of fertility attitude, income class, and child-rearing burden. BMC Women's Health 24, 557 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12905-024-03401-8

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Keywords

BMC Women's Health

ISSN: 1472-6874

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