- Research
- Open access
- Published:
Influence of perceived stress on fertility intention among women of childbearing age without children: multiple mediating effect of anxiety, family communication and subjective well-being
Reproductive Health volume 21, Article number: 135 (2024)
Abstract
Background
In recent years, there has been a significant decrease in the desire to have children among Chinese women of childbearing age, particularly for the first child. This trend has sparked a growing interest in understanding the underlying factors. Although perceived stress has been speculated as an important factor in decreasing fertility intention, the precise mechanism is unclear. The current study, therefore, aims to investigate the psychological mechanisms linking perceived stress to fertility intentions among women of childbearing age without children, a topic of significant relevance and importance.
Methods
Data were sourced from Chinese residents' psychology and behavior investigation (PBICR-2022). A multistage random sampling method was applied to recruit eligible participants. The Mplus8.3 software constructed a chain path model among the variables.
Results
The median fertility intention was 30(3–60) on a scale of 0 to 100. The mediation analysis revealed a significant negative influence of perceived stress on fertility intention (β = − 0.076, P < 0.001). Additionally, a more intricate pattern of chain-mediating effect was observed involving perceived stress, anxiety (β = 0.037, P < 0.05), family communication (β = 0.106, P < 0.001), subjective well-being (β = 0.088, P < 0.001) and fertility intention.
Conclusions
Perceived stress not only directly suppressed fertility intention but also indirectly affected it through anxiety, family communication, and subjective well-being. Effective family communication and favorable subjective well-being emerged as factors that could augment fertility intentions among women of childbearing age without children.
Introduction
Over the past three decades, one of the most notable demographic shifts has been the marked decline in global fertility rates, except for a few in impoverished rural areas [1]. A research article published in the Lancet in July 2020 projected that by 2100, the global total fertility rate could drop to 1.7, meaning an average of only 1.7 children per woman during her reproductive lifespan [2]. This projection aligns with trends in China, where, by the end of 2023, the total fertility rate had fallen to about 1.0—well below the critical threshold of 1.5 [3]. Such a decline in fertility poses substantial challenges to workforce sustainability, accelerates population aging, and impacts demographic structures, fundamental welfare, and societal progress [4].
China has discontinued the original family planning policy to address this issue and implemented various supportive measures to stimulate fertility. Nevertheless, the outcomes have fallen short of the policy's anticipated effects.
To clarify the phenomenon of low fertility, scholars have conducted extensive research and identified low fertility intention as a reliable birth predictor [5]. Fertility intention refers to an individual's expectations and attitudes toward having children within a specific timeframe [6]. It comprises tempo intentions, which relate to the timing of childbirth, and quantum intentions, which refer to the desired total number of children [7]. Micro and macro-level factors, including individual characteristics, family circumstances, socioeconomic status (SES), and sociocultural environment, can influence fertility intentions [8]. Previous studies have shown that some external stressors, such as labor pains, economic burdens [9], workplace competition [10], and conflicts between work and family [11], are also associated with one's fertility intention. While being a mother is generally a joyful experience for most women, it can also induce stress, which in turn influences their reproductive decisions [12]. However, the specific psychological mechanisms through which perceived stress affects fertility intention remain unclear.
The psychological stress theory posits that perceived stress, by disrupting individuals' equilibrium or exceeding their coping capacity, often triggers anxiety [13]. Anxiety can significantly influence individuals' behaviors and decision-making processes, including their fertility intentions [14]. A study examining China's universal two-child policy revealed that the pressures associated with childbirth led to significant anxiety about having a child among young women, subsequently inhibiting their fertility behaviors [15]. Similarly, another research on the decision to have a third child found that anxiety related to childbirth and parenthood was inversely associated with fertility intentions [16]. These findings implied that anxiety may serve as a mediating variable between perceived stress and fertility intentions; however, this has not yet been verified. Consequently, we hypothesize that acting as an independent mediator, anxiety will demonstrate a positive correlation with perceived stress and a negative impact on fertility intentions. (Hypothesis 1).
In 1980, Skinner et al. proposed the theory of process model of family functioning. This theory posits that the primary objective of a family is to manage various daily tasks, and effective communication within families is crucial for completing these tasks [17]. Having children is regarded as one of the family's fundamental functions and critical tasks. Previous studies demonstrated that under favorable economic conditions, families with effective communication are more likely to be close and express a desire for an expanded family size [18]. However, under unfavorable conditions or when facing significant pressures, whether effective family communication can still influence women's decisions to have children requires further exploration. In light of this, we hypothesize that as an independent mediator, family communication will negatively correlate with perceived stress and positively impact fertility intentions (Hypothesis 2).
Studies exploring the relationship between subjective well-being and fertility behavior have gradually grown over the past two decades. Luppi found that both experienced and anticipated well-being played influential roles in individuals' fertility decision-making [19]. Additionally, subjective well-being has also been linked to perceived stress [20]. When individuals perceive threats to their resources and struggle to adapt to their work environment, their happiness can be adversely affected [21]. However, the potential mediating role of subjective well-being in the relationship between perceived stress and fertility intentions remains uncertain. Therefore, we hypothesize that as an independent mediator, subjective well-being will negatively correlate with perceived stress and positively influence fertility intentions (Hypothesis 3).
In summary, existing studies and theories have identified several critical variables associated with decreased fertility intentions; however, the interaction of these variables with specific mechanisms remains ambiguous. Consequently, we propose that perceived stress will influence fertility intentions through a complex interplay chain of mediating effects involving anxiety, family communication, and subjective well-being. (Hypothesis 4). The complete hypothetical model is depicted in Fig. 1.
Methods
Participants
Since the implementation of China's new birth policy, many studies have shifted focus to the birth of second or third children. However, efforts to increase the birth rates of second or third children in the context of low first-child fertility incur significant costs and result in limited effectiveness and unsustainability. Consequently, this study aims to investigate the first baby fertility intentions of women of childbearing age who do not yet have children. Our data are derived from a large-scale cross-sectional survey, “Psychology and Behavior Investigation of Chinese Residents in 2022” (PBICR 2022) [22]. This extensive survey was conducted in China (excluding Hong Kong, Macau, and Taiwan) from June to August 2022, employing a multistage random sampling approach consisting of two stages. Initially, a total of 148 cities, 202 districts and counties, 390 townships/towns/sub-districts, and 780 communities/villages from 23 provinces, five autonomous regions, and four municipalities were selected as the first stratification [23]. Subsequently, respondents from each community and village were chosen in the second stage using non-equal probability sampling (quota sampling). The quota criteria include gender and age, with a required gender ratio of 1:1 and an age distribution generally following the Population Pyramid as per the “Seventh National Census in 2020” of China
A pre-tested structured questionnaire was used to collect information through a one-on-one and face-to-face interview by trained investigators. When face-to-face investigation was not feasible, the investigator resorted to online video interviews and directly provided electronic questionnaires to the participants. In total, 31,480 questionnaires were disseminated, collecting 30,505 valid questionnaires, yielding an overall response rate of 96.9%. The present study utilized data from the PBICR 2022 survey. The inclusion criteria comprised the following: (1) participants held Chinese nationality; (2) women aged between 20 and 49 years old without children and not currently pregnant. Although China's family planning regulations explain that women's reproductive age is 15–49 [24], considering the legal age of marriage for women in China is 20 years old, this study selected data related to women aged 20–49. (3) volunteered to participate in the research and completed a consent form; (4) could understand the content of each item in the questionnaire. The exclusion criteria included (1) participants with unconsciousness or severe mental disorders and (2) those unwilling to cooperate or be involved in similar projects. Ultimately, according to the inclusion and exclusion criteria (Fig. 2), we obtained a valid sample of 4872 for this study after deleting data with missing values and outliers.
Measures
Fertility intention
To accurately measure fertility intention, a single question was included on the scale: “What is the strength of your desire to have your first child?” Respondents recorded their responses by moving a slider, which ranged from 0 (No desire) to 100 (Strong desire), with higher scores signifying a heightened level of fertility intention.
Perceived stress scale (PSS-4)
The PSS-4 is a 4-item instrument to assess the perceived psychological stress experienced over the preceding month [25]. Questions 1 and 4 were coded from 0 (Never) to 4 (Very often), and Questions 2 and 3 were reverse-coded. The total score is the sum of each item, ranging from 0 to 16 points, with higher scores indicating a more pronounced stress level. This scale has demonstrated reliability and validity in Chinese [26]. The Cronbach's α for PSS-4 was 0.668.
Generalized anxiety disorder scale-7 (GAD-7)
The GAD-7 was applied to assess the self-reported severity of anxiety. This scale contains seven items, each rated on a scale ranging from 0 (Not at all) to 3 (Almost every day), resulting in a total score ranging from 0 to 21. The classification of scores is as follows: 0–4 indicates no symptoms, 5–9 suggests mild symptoms, 10–14 means moderate symptoms, and 15–21 signifies severe symptoms [27]. The Chinese version of the GAD-7 has been validated and demonstrated strong reliability and validity [28]. In this study, the Cronbach's α coefficient was 0.944.
Family communication scale (FCS-10)
We used the FCS-10 to assess the quality of communication among family members, encompassing aspects such as idea exchange, information sharing, degree of concern, openness, confidence, and emotional expression [29]. Respondents rated ten items on a scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). The overall score ranged from 10 to 50, with higher scores indicating more excellent family communication. The scale has demonstrated reliability and validity in previous application studies [30]. In our study, the Cronbach’s α coefficient of FCS-10 was 0.970.
World Health Organization well-being index (WHO-5)
The WHO-5 is a 5-item assessment tool to evaluate respondents' subjective psychological well-being over the past two weeks [31]. Participants provided numerical responses on a scale ranging from 0 (None of the time) to 5 (All of the time) for each item. The raw score was multiplied by 4 to yield a final score that ranged from 0 to 100, representing the individuals’ perceived level of well-being. The Chinese version of the WHO-5 has been proven reliable and valid in previous application studies [32]. In our study, the Cronbach's α coefficient of WHO-5 was 0.954.
Statistical analysis
We used Excel software for real-time data input and SPSS 25.0 to conduct descriptive statistics, difference tests, and correlation analysis between variables for data analysis. We applied the Kolmogorov–Smirnov normality test to assess the normality of the measurement data. Baseline characteristics were summarized using frequencies and percentages. Due to the non-normal distribution of fertility intention data, we use the median (Interquartile range, IQR) to describe it. The Mann–Whitney U test and Kruskal–Wallis test were respectively used to evaluate differences among binary variables (Permanent Residence, Marital status, and Debt) and multi-class variables (Age, Education, Number of houses, Housing area, and Family per capita monthly income), within demographic sociology indicators. Spearman correlation was used to analyze the correlation between variables.
We utilized Mplus8.3 to construct a chain path model. The goodness of model fit was assessed based on criteria such as a root-mean-square error of approximation (RMSEA) < 0.05 and comparative fit index (CFI) and Tucker Lewis Index (TLI) > 0.95, χ2/df < 3; SRMR < 0.05 indicating a well-fitting model [33, 34].
Results
Sociodemographic characteristics and fertility intention
Our study included 4,872 women of childbearing age without children, as presented in Table 1. The majority of the participants were unmarried (89.9%), falling within the age range of 20 to 29 years (88.1%), and residing in urban areas (79.1%). In terms of education, 73.0% of participants had completed college, 18.2% had received senior high school education, 7.0% had obtained a master's or doctoral degree, and 1.8% had an educational background of junior high school or below. Approximately half of the participants (52.2%) reported that their family owned only one house. Concerning housing area, 60.2% of participants lived in spaces ranging from 90 to 150m2. Family per capita monthly income was divided into four categories: ≤ 3000 CNY, 3001–6000 CNY, 6001–12000 CNY, and ≥ 12,000 CNY, with proportions of 31.2%, 41.3%, 19.0%, and 8.5%, respectively. Moreover, 64.2% of participants reported that their families had incurred debt in the past year.
The median fertility intention score is 30 (3–60), as shown in Table 2. Notably, significant variations in fertility intentions were observed among different age groups, displaying an inverted U-shaped trend as age increased. Specifically, the 30–39 age group exhibited the highest fertility intention, with a median score of 50 (ranging from 20 to 75) (P < 0.001). Furthermore, married women tended to express higher fertility intentions than their single counterparts (P < 0.001). Additionally, there were notable differences in fertility intention among different educational groups (P < 0.001). As education levels progressed from junior high school to master and above, a U-shaped curve emerged in the pattern of fertility intention with a bottom in the high school education group. In contrast, the relationship between income and fertility intention displayed an inverted U-shaped trend, with fertility intentions peaking among women with a per capita household income of 6000–12000 CNY (P < 0.001). Significant differences in fertility intention were also observed among women with one property and other groups (P < 0.001). Furthermore, variations in fertility intention were observed among groups with different housing areas. Women residing in homes ranging from 90 to 150 square meters reported the highest fertility desires (P < 0.001). Notably, permanent residence status and debt did not significantly influence fertility intentions (Table 1).
Correlation
We conducted pairwise correlation analyses to examine the relationships between fertility intention and other variables in the hypothesized model. As indicated in Table 2, there are significant correlations between all variables. Perceived stress (r = − 0.158, P < 0.01) and anxiety (r = − 0.069, P < 0.01) exhibit negative correlations with fertility intention. Conversely, family communication (r = 0.168, P < 0.01) and subjective well-being (r = 0.175, P < 0.01) display positive associations with fertility intention.
Multiple mediating analysis
Given the significant differences in fertility intentions observed across various demographic groups—distinguished by age, education levels, marital status, number of properties, housing area, and per capita monthly income—we incorporated these variables as control variables in the chain path model. The model demonstrated excellent fit indices: RMSEA = 0.017, P = 1.000; CFI = 0.993, TLI = 0.985; χ2/df = 2.36; SRMR = 0.013. As shown in Table 3 and Fig. 3, perceived stress significantly and negatively affected fertility intention (β = − 0.076, P < 0.001). Anxiety significantly and positively affected fertility intention (β = 0.037, P < 0.05). Additionally, family communication (β = 0.106, P < 0.001) and subjective well-being (β = 0.088, P < 0.001) both had substantial and positive influences on fertility intention. Furthermore, perceived stress (β = − 0.324, P < 0.001) and anxiety (β = − 0.094, P < 0.001) had significant and negative effects on subjective well-being, respectively. Family communication significantly and positively impacted subjective well-being (β = 0.288, P < 0.001). Additionally, perceived stress (β = − 0.255, P < 0.001) and anxiety (β = − 0.107, P < 0.001) were both significantly and negatively associated with family communication. Finally, perceived stress (β = 0.504, P < 0.001) significantly and positively affected anxiety.
All the direct and indirect paths between perceived stress and fertility intention are shown in Table 4. It was found that the mediating effects of anxiety (β = 0.019, Boot SE = 0.008, Boot 95%CI [0.003, 0.035]), family communication (β = − 0.027, Boot SE = 0.004, Boot 95%CI [− 0.036, − 0.019]), and subjective well-being (β = − 0.029, Boot SE = 0.006, Boot 95%CI [− 0.041, − 0.018]) were all statistically significant. Additionally, the chain mediation effects were also significant for all four mediators (β = − 0.006, Boot SE = 0.001, Boot 95%CI [− 0.009, − 0.004]), (β − 0.004, Boot SE = 0.001, Boot 95%CI [− 0.007, − 0.002]), (β = − 0.007, Boot SE = 0.001, Boot 95%CI [− 0.010, − 0.004]), (β = − 0.001, Boot SE = 0.000, Boot 95%CI [− 0.002, − 0.001]).
Discussion
Based on the national cross-sectional data, this study investigated the fertility intentions of childbearing-age women without children. We examined the complex interrelations among perceived stress, anxiety, family communication, subjective well-being, and fertility intentions. Additionally, path analysis clarified the psychological mechanisms by which perceived stress impacts fertility intentions. The results demonstrated that perceived stress adversely affected fertility intentions both directly and indirectly through anxiety, family communication, and subjective well-being. The findings offer deeper insights into the factors contributing to declining fertility rates.
The prevalence of fertility intention
Our findings indicate that the median fertility intention score among childbearing-aged Chinese women without children is 30 (3 to 60). This data suggests that half of the participants reported a relatively low level of fertility desire, as evidenced by a score of 30 points. These findings suggest a prevailing low fertility intention among childbearing-aged women without children in contemporary China.
Perceived stress as an indicator of fertility intention
We discovered that perceived stress is a non-negligible indicator of fertility intentions. It was observed that perceived stress directly and negatively impacted fertility intention, accounting for approximately 58.02% of the total effect (Table 4). This outcome aligns with the findings of previous studies [35]. Due to physiological and psychological changes, childbirth is considered a significant stressor for women. Moreover, the decision to have children involves a complex interplay of factors, including the financial burdens of child-rearing, potential loss of personal freedom, and challenging work-family conflicts [36]. When these pressures and risks overwhelm, parent–child companionship is often reduced, leading to a substantial emotional burden [37]. Consequently, women may reevaluate their decisions regarding parenthood [38].
Anxiety as the mediator between perceived stress and fertility intention
Recent research increasingly highlights the growing prevalence of fertility-related anxiety as parenting stress intensifies. Some young women even experience what is colloquially termed “childbearing phobia” [39]. Consistent with prior studies, our findings confirm that perceived stress significantly and positively influences anxiety. Notably, while anxiety was established as a mediator between perceived stress and fertility intentions, its effect is unexpectedly positive (β = 0.037; P < 0.05), contrary to our initial hypotheses. This indicates the presence of a masking effect within the relationship between perceived stress, anxiety, and fertility intentions. Hypothesis 1 was not entirely supported.
A plausible explanation for this inconsistency can be made from several aspects. First, fertility is significantly influenced by physiological factors such as age. Women's fecundity gradually declines after age 32 and more rapidly after 37 years [40]. For women who have not yet experienced childbirth, increasing age may intensify anxiety related to fecundity and health concerns, prompting more severe consideration of fertility-related issues. Our findings, which indicate an inverted U-shaped relationship between age and fertility intentions, with the highest intentions observed in the 30–39 age group, support this perspective. Additionally, the entrenched cultural emphasis on family and the pressure from parents to have grandchildren in China may heighten anxiety among young women, compelling them to prioritize childbirth in their life plans.
Furthermore, it is widely recognized that a moderate level of anxiety can enhance alertness and consciousness, potentially benefiting certain behaviors. Our data, indicating a median anxiety score of 5 (on a scale from 1 to 7), suggest a mild level of anxiety among the participants. It is plausible that this level of anxiety could stimulate fertility intentions. However, it is worth noting that our study exclusively focused on women of childbearing age without children. Future research should explore whether the impact of anxiety on fertility intentions varies among women who have already given birth.
Family communication as the mediator between perceived stress and fertility intention
Effective communication within the family plays a crucial role in task distribution and completion. The process model of family functioning suggests that adequate family communication is essential for women of childbearing age to manage anxiety and stress, enhance subjective well-being, and better engage in family fertility tasks. Deep and meaningful family communication gives women respect, compassion, love, and support, significantly influencing their reproductive decision-making [41]. However, stress can increase an individual's psychological burden and adversely affect their interpersonal relationships and ability to utilize social support [42]. Previous research has indicated that daily stressors and hassles are negatively associated with the quality of family communication and couple relationships [43]. Our results align with these studies, revealing a significant negative correlation between family communication and perceived stress and a positive correlation between family communication and fertility intentions. Moreover, family communication acts as a mediator between perceived stress and fertility intentions, thus confirming Hypothesis 2. This finding underscores the role of open and supportive family communication in the negative impacts of stress and positively affecting fertility intentions.
Subjective well-being as the mediator between perceived stress and fertility intention
Numerous studies have demonstrated the constructive impact of subjective well-being on an individual's reproductive behavior and decision-making, with these findings held across different countries [44]. However, the accumulation of stress could diminish an individual's perception of happiness and has been linked to their future fertility choices [45]. In accordance with these previous findings, our data indicates that subjective well-being negatively correlates with perceived stress and positively influences fertility intentions. Notably, subjective well-being was a significant mediator in the relationship between perceived stress and fertility intentions, thus affirming Hypothesis 3.
The chain mediating role of anxiety and family communication on perceived stress and fertility intention
Our findings confirmed that anxiety and family communication act as chain mediators between perceived stress and fertility intentions. The quality of communication within a family and how its members express their thoughts and feelings are widely recognized as critical factors affecting their mental health and family functioning [46]. Effective family communication, serving as a stress buffer, can mitigate the effects of negative emotions and empower young women with the courage and confidence to handle pressures and challenges [47]. This dynamic is likely to lead to an enhancement in fertility intention.
The chain mediating role of anxiety and subjective well-being on perceived stress and fertility intention
Furthermore, the chain mediating role of anxiety and subjective well-being between perceived stress and fertility intentions was also established. Subjective well-being, a positive emotional and cognitive evaluation of one's life, influences childbearing behavior [48]. Enhanced subjective well-being is often considered as a prerequisite for a greater inclination to have children [49]. However, when women of reproductive age frequently encounter various stressors, they are more susceptible to experiencing anxiety [50], which in turn leads to diminished happiness and a reduced desire to have children.
The chain mediating role of family communication and subjective well-being on perceived stress and fertility intention
Our results confirmed the chain-mediated effect of family communication and subjective well-being on the relationship between perceived stress and fertility intentions. Couples experiencing relationship issues are more likely to suffer reduced happiness and face significant obstacles when planning for childbirth [51]. Conversely, effective family communication, acting as a buffer against stress, can enhance women's subjective well-being and promote their fertility intentions [52].
The chain mediating role of anxiety, family communication, and subjective well-being on perceived stress and fertility intention
Our study also identified that anxiety, family communication, and subjective well-being play a more complex chain-mediated role in the relationship between perceived stress and fertility intentions among women of childbearing age without children. Anxiety is linked to behaviors such as reassurance-seeking and avoidance [53]. Suppose an anxious woman successfully receives adequate comfort and support from her spouse or family. In that case, she is likely to feel happier and more energized, thereby bolstering her belief in the value and meaning of childbirth. Conversely, in the absence of practical support from family members and effective psychological relief, a woman's emotions may remain entrenched in stress, diminishing her subjective well-being and life satisfaction and reinforcing her reluctance towards fertility [54]. This is also consistent with the principles of the process model of family functioning theory. Hypothesis 4 was all confirmed.
Lastly, it is worth noting that although all the hypotheses have been validated, the regression coefficients for fertility intentions and the remaining variables are relatively small. Firstly, this may be attributed to the complexity of fertility intentions, which are influenced by multiple macro/micro and subjective/objective factors. Perceived stress is just one such factor, explaining the modest size of its regression coefficient. This underscores the importance of considering other influential variables in future research. Secondly, the small coefficients may also be related to the large sample size in the study. A larger sample size increases the sensitivity of hypothesis testing, enabling the detection of minor differences. This factor necessitates caution in interpreting these results. Moving forward, we plan to conduct further experiments to validate these findings more robustly.
Strengths and limitations
This study utilized a large, nationwide sample, enhancing the representativeness and reliability of our results for the general population. Additionally, we conducted complex chain mediation analyses, clarifying the mechanisms by which perceived stress influences fertility intentions and rendering our findings more comprehensive and conclusive. However, this study is not without limitations. Firstly, its cross-sectional design constrains our ability to determine temporal sequences or establish causal relationships. Consequently, future longitudinal studies are essential to ascertain causality. Secondly, while significant relationships were identified between fertility intentions and other variables, the weak effects observed necessitate a cautious interpretation of the results. In future studies, it is crucial to determine whether these findings genuinely reflect reality or are influenced by the large sample size. Thirdly, this research focused solely on women of childbearing age without children. Whether the model is valid among other groups of women is unknown and needs further verification in future studies.
Conclusions
The fertility intentions of Chinese women of childbearing age without children are generally low. Perceived stress has been identified as a non-negligible variable that not only directly suppressed fertility intentions but also indirectly affected it through anxiety, family communication, and subjective well-being. In light of this, multiple measures are needed to foster a fertility-friendly environment for young women. The government should actively monitor and mitigate key stress factors impeding young women's fertility intentions, such as financial constraints, workplace challenges, and parenting concerns. The implementation of favorable birth policies and the establishment of a robust child-rearing services system could significantly enhance fertility rates. Anxiety, serving as a mediator between perceived stress and fertility intentions, underscores the need for improved psychological and social support to help women of reproductive age prepare mentally and emotionally for parenthood. Obstetricians, gynecologists, and family planning professionals should prioritize women's mental health and provide reproductive psychology education and support. Additionally, family communication and subjective well-being are significant factors in enhancing fertility intentions among women of childbearing age without children. Family members are encouraged to enhance communication and offer diverse support to improve women's well-being and decision-making regarding childbirth.
Availability of data and materials
The datasets used during the current study are available from the corresponding author on reasonable request.
References
Aassve A, Cavalli N, Mencarini L, Plach S, Bacci ML. The COVID-19 pandemic and human fertility. Science. 2020;369(6502):370–1.
Vollset SE, Goren E, Yuan CW, Cao J, Smith AE, Hsiao T, et al. Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the global burden of disease study. Lancet. 2020;396(10258):1285–306.
Wang P. National Bureau of Statistics China. The total population has decreased, and high-quality development of the population has achieved results.2024. https://www.stats.gov.cn/xxgk/jd/sjjd2020/202401/t20240118_1946711.html. Accessed 24 Jan 2024.
Tatum M. China’s three-child policy. Lancet. 2021;397(10291):2238.
Morgan SP, Taylor MG. Low fertility at the turn of the twenty-first century. Annu Rev Sociol. 2006;32:375–99.
Jing WZ, Liu J, Ma QY, Zhang SK, Li YY, Liu M. Fertility intentions to have a second or third child under China’s three-child policy: a national cross-sectional study. Hum Reprod. 2022;37(8):1907–18.
Balbo N, Billari FC, Mills M. Fertility in advanced societies: a review of research: La Fécondité Dans Les Sociétés Avancées: Un Examen Des Recherches. Eur J Popul. 2013;29:1–38.
Preis H, Tovim S, Mor P, Grisaru-Granovsky S, Samueloff A, Benyamini Y. Fertility intentions and the way they change following birth- a prospective longitudinal study. BMC Pregnancy Childbirth. 2020;20:228.
Zhang TT, Cai XY, Shi XH, Zhu W, Shan SN. The effect of family fertility support policies on fertility, their contribution, and policy pathways to fertility improvement in OECD Countries. Int J Environ Res Public Health. 2023;20(6):4790.
Xu B, Pak M. Child-raising cost and fertility from a contest perspective. Public Choice. 2021;186:9–28.
Lan X, Liang Y, Wu G, Ye HY. Relationships among job burnout, generativity concern, and subjective well-being: a moderated mediation model. Front Psychol. 2021;12: 613767.
Kin C, Yang R, Desai P, Mueller C, Girod S. Female trainees believe that having children will negatively impact their careers: results of a quantitative survey of trainees at an academic medical center. BMC Med Educ. 2018;18(1):260.
Lazarus RS. Progress on a cognitive-motivational-relational theory of emotion. Am Psychol. 1991;46:819–34.
White L, McQuillan J. No longer intending: the relationship between relinquishedfertility intentions and distress. J Marriage Fam. 2006;68:478–90.
Zeng Y, Hesketh T. The effects of China’s universal two-child policy. Lancet. 2016;388(10054):1930–8.
Zhang C, Wei L, Zhu Y, Teng L, Zhang W, Xu J. Fertility intentions among young people in the era of China’s three–child policy: a national survey of university students. BMC Pregnancy Childbirth. 2022;22(1):637.
Skinner H, Steinhauer P, Sitarenios G. Family assessment measure (FAM) and process model of family functioning. J Fam Ther. 2000;22(2):190–210.
Parr N. Satisfaction with life as an antecedent of fertility: partner + happiness = children? Demo Res. 2010;22(21):635–62.
Luppi F, Mencarini L. Parents’ subjective well-being after their first child and declining fertility expectations. Demogr Res. 2018;39(9):285–314.
Coelhoso CC, Tobo PR, Lacerda SS, Lima AH, Barrichello CRC, Amaro-Jr E, Kozasa EH. A new mental health mobile app for well-being and stress reduction in working women: randomized controlled trial. J Med Internet Res. 2019;21(11): e14269.
Hobfoll SE. The influence of culture, community, and the nested-self in the stress process: Advancing conservation of resources theory. Appl Psychol. 2001;50(3):337–421.
Wang Y, Kaierdebieke A, Fan S, Zhang RF, Huang MJ, Li H, Sun XN, Li QY, Meng WJ, Wu WY, Lin Z, Liu JY, Wang XP, Wu YC, Tang JQ, Sun YK, Chen K, Ge P, Ming WK, Zhang C, Ma ZF, Feng L, Zhang XY, Niu YY, Yan YP, Jin YL, Gao GZ, Dai S, Li YL, Tan Y, Wu YW, Zhang Q, Gui G, Pan XL, Liao YM, Zhao XQ, Zhang YT, Chen HY, Qiu YW, Fu XM, Zhou JL, Li D, Li KH, Xu MW, Wang Z, Wang YQ, Ma Y, Sun XY, Wu YB. Study protocol: A cross-sectional study on psychology and behavior investigation of Chinese residents, PBICR. Psychosom. Med. Res. 2022;4:13–19. https://doi.org/10.53388/202219.
Wu YB, Fan SY, Liu DY, Sun XY. Psychological and behavior investigation of Chinese residents: concepts, practices, and prospects. Chinese General Practice J. 2024. https://doi.org/10.1016/j.cgpj.2024.07.006
Song J, Alimige A. Deviation between fertility desire and fertility behavior in China and the effect of family support. Popul Res. 2021;45(4):18–35.
Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health SocBehav. 1983;24(4):385–96.
Leung DY, Lam TH, Chan SS. Three versions of perceived stress scale: validation in a sample of Chinese cardiac patients who smoke. BMC Public Health. 2010;10:513.
Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalizedanxiety disorder: The GAD-7. Arch Intern Med. 2006;166(10):1092–7.
Chen SS, Sun XH, Zhu QS, Zhao Y, Tang JS, Song HD. Factors influencing the level of depression and anxiety of community-dwelling patients with schizophrenia in China during the COVID-19 pandemic. Int J Environ Res Public Health. 2023;20(5):4376.
Olson D. FACES IV and the circumplex model: validation study. J Marital Fam Ther. 2011;37(1):64–80.
Akhlaq A, Malik NI, Khan NA. Family communication and family system as the predictors of family satisfaction in adolescents. Sci J Psychol. 2012;2013:1–6.
Topp CW, Østergaard SD, Søndergaard S, Bech P. The WHO-5 well-being index: a systematic review of the literature. Psychother Psychosom. 2015;84(3):167–76.
Lin CH, Lee SM, Wu BJ, Huang LS, Sun HJ, Tsen HF. Psychometric properties of the Taiwanese version of the World Health Organization-five well-being index. Acta Psychiatr Scand. 2013;127(4):331.
Hooper D, Coughlan JMM. Structural equation modelling: guidelines for determining model fit electronic. J Bus Res Methods. 2008;6:53–60.
Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Eq Model Multidiscipline J. 1999;6(1):1–55.
Brinton MC, Babies OhE. work, or both? Highly educated women’s employment and fertility in east Asia. Am J Sociol. 2019;125(1):105–40.
Dennis CL, Prioreschi A, Brown HK, Brennenstuhl S, Bell RC, Atkinson S, et al. Medical, behavioral and social preconception and inter-conception risk factors among pregnancy planning and recently pregnant Canadian women. Fam Med Community Health. 2022;10(3): e001175.
Begall K, Mills M. The impact of subjective work control, job strain and work-family conflict on fertility intentions: a European comparison. Eur J Popul. 2011;27(4):433–56.
Matsushima M, Yamada H, Kondo N, Arakawa Y, Tabuchi T. Impact of the COVID-19 pandemic on pregnancy postponement-evidence from Japan. J Biosoc Sci. 2023;55(5):908–20.
Okine R, Hughes LM, Smith G, Bonus ML, Feinberg EC, Bernardi LA. Undergraduate students have low fertility knowledge and high anxiety regarding future fertility: an opportunity for education. Heliyon. 2023;9(3): e14623.
American College of Obstetricians and Gynecologists Committee on Gynecologic Practice and Practice Committee. Female age-related fertility decline. Committee Opinion No. 589. Fertility and Sterility.2014; 101(3): 633–634.
Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull. 1985;98(2):310–57.
Calpbinici P, Terzioglu F, Koc G. The relationship of perceived social support, personalitytraits and self-esteem of the pregnant women with the fear of childbirth. Health Care Women Int. 2021;44(10–11):1423–37.
Lavee Y, Ben-Ari A. Relationship of dyadic closeness with work-related stress: a daily diary study. J Marriage Fam. 2007;69(4):1021–35.
Le Moglie M, Mencarini L, Rapallini C. Is it just a matter of personality? On the role of subjective well-being in childbearing behavior. J Econ Behav Organ. 2015;117:453–75.
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.
Zarnaghash M, Zarnaghash M, Zarnaghash N. The relationship between family communication patterns and mental health. Procedia-Soc Behav Sci. 2013;84:405–10.
Ghazavi Z, Feshangchi S, Alavi M, Keshvari M. Effect of a family-oriented communication skills training program on depression, anxiety, and stress in older adults: a randomized clinical trial. Nurs Midwifery Stud. 2016;5(1): e28550.
Aassve A, Mencarini L, Sironi M, Aassve A, Mencarini L, Sironi M. Institutional change, happiness and fertility. Eur Sociol Rev. 2015;31(6):749–65.
Kohler HP, Billari FC. Fertility and happiness in the 21st century: institutions, preferences and their interactions. Acta Biol Colomb. 2009;10:75–94.
River LM, Borelli JL, Nelson-Coffey SK. Tolerance of infant distress among working parents: Examining the roles of attachment anxiety and work-family conflict. Parenting. 2019;19:137–59.
Rijken AJ, Liefbroer AC. The influence of partner relationship quality on fertility. Eur J Popul. 2009;25:27–44.
Zerle-Elsäßer C, Gniewosz G. Linking mothers’ well-being to a subsequent birth: the mediating role of coparenting and personal income. J Fam Psychol. 2021;35(3):366–76.
Horenstein A, Heimberg RG. Anxiety disorders and healthcare utilization: a systematic review. Clin Psychol Rev. 2020;81:101894.
Spice K, Jones SL, Hadjistavropoulos HD, Kowalyk K, Stewart SH. Prenatal fear of childbirth and anxiety sensitivity. J Psychosom Obstet Gynaecol. 2009;30(3):168–74.
Acknowledgements
We acknowledge all respondents who showed great patience in answering the questionnaires. We sincerely thank all those who have helped us.
Funding
This work was supported by the Key Program of the Social Science Foundation of Hebei Province (HB23SH003).
Author information
Authors and Affiliations
Contributions
JPZ, WJQ, and JH conceived and designed the research. JPZ, WJQ, and YBW collected and analyzed the data. JPZ wrote the manuscript. JH, WJQ, and YC revised the manuscript. RH, HYJ, YJW, MNY, and HCL contributed materials, analysis tools, tables and figures. All the authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Ethics approval and consent to participate
This study was approved by the Clinical Research Ethics Committee of the Second Xiangya Hospital of Central South University (2022-K050) on Aug 17, 2022. All participants signed informed consent forms and voluntarily participated.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Zhao, J., Qi, W., Cheng, Y. et al. Influence of perceived stress on fertility intention among women of childbearing age without children: multiple mediating effect of anxiety, family communication and subjective well-being. Reprod Health 21, 135 (2024). https://doi.org/10.1186/s12978-024-01855-5
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s12978-024-01855-5