During the COVID-19 pandemic, having more money or a stable job did not necessarily mean stronger fertility intentions. The most stable influence came from pandemic-related changes in marriage and delayed pregnancy preparation after vaccination. The study examines fertility intention among Chinese married youth during the COVID-19 pandemic, using childbearing survey data from Hubei Province collected in March 2022.

Fertility intention is operationalized in two ways: the ideal number of children and the short-term fertility plan. The average ideal number was 1.652, below the population replacement level, and only 16.4 percent had a short-term fertility plan. The analysis finds that COVID-19-induced factors had a more stable effect, especially on short-term fertility planning, while parenting perceptions mattered more for the ideal number of children.

China entered a period of extremely low fertility: the total fertility rate of women of childbearing age fell to 1.3 by the end of 2020. The government introduced selective two-child, universal two-child, and three-child policies, but these pro-birth policies did not produce the expected population growth.

During the pandemic, stay-at-home quarantine increased family economic pressures and work–family conflicts, while vaccination raised concerns about side effects in pregnant women. Earlier research often used the Theory of Planned Behavior to study fertility intentions as life choices constrained by personal and contextual life chances.

That literature considered socioeconomic status, including income, education, and employment quality, as well as subjective parenting perceptions. The study identifies gaps: research usually focused on the general childbearing population, understated COVID-19 effects in non-Western contexts, and lacked comparisons of the relative importance of different determinants.

The central gap is not simply whether different factors matter, but how important they are relative to one another. The study also emphasizes that childbearing decisions differ across fertile stages, so determinants should be examined separately for different family sizes.

That leads to a research design comparing childless, one-child, and two-child families during the pandemic. The first research question asks whether socioeconomic status, parenting perceptions, and COVID-19-induced factors significantly influence fertility intentions among Chinese married youth.

It also asks which type of factor matters more. The study uses the Childbearing Survey in Hubei Province, organized by Zhongnan University of Economics and Law and the Yichang Municipal Health Commission. The survey randomly selected people aged twenty to forty-five in Yichang, and covered the entire Yichang area.

A total of 32,248 fertile-age samples were collected online in March 2022. The dependent variable is fertility intention, measured through the ideal number of children and the short-term fertility plan. For the ideal number of children, answers ranged from zero to more than three, then were recoded as wanting two or more children versus wanting one or none.

Short-term plans asked whether childless respondents planned a child this year, or whether parents planned another child this year, separating first-, second-, and third-child plans. Socioeconomic status includes education, employment status, and household economic status.

The two economic measures were combined with principal component analysis, then transformed to a zero-to-one-hundred continuous score. COVID-19-induced factors were measured with changes in the marital relationship and the perceived appropriate waiting time to become pregnant after vaccination.

The vaccination question offered four response categories: more than twelve months, six to twelve months, three to six months, or less than three months. The statistical analysis had three steps: descriptive methods, binary logit regression models, and a comparison of relative contributions across factor types.

Table one summarizes fertility structure among thirteen thousand seven hundred ninety-four married young people, with childless, one-child, and two-child families accounting for fifteen point three percent, sixty-five point seven percent, and nineteen percent. It also breaks these shares down by age, household registration, ethnicity, education, and economic status.

The reported chi-square tests indicate statistically significant differences across every listed characteristic, highlighting how fertility structure varies across demographic and socioeconomic groups. Table two summarizes two fertility-intention measures among married youth: the mean ideal number of children and the share reporting a short-term fertility plan.

Across all samples, the mean was one point six five two, while sixteen point four percent had such a plan. The table also reports subgroup differences and significance tests, including patterns by gender, age, education, employment, economic status, and perceived advantages of multi-child families, helping the authors examine possible inducers of low fertility intention.

The descriptive results show that fertility intention indicators were higher among male and minority respondents than among their counterparts. Respondents with worse marital relationships and concerns about vaccination side effects tended to have lower fertility intentions.

Higher socioeconomic status was associated with a short-term fertility plan, while parenting perceptions also showed associations with fertility intention. Table three uses binary logit regression models to examine the study’s outcomes.

Model one predicts the ideal number of children, while models two through four predict short-term plans in childless, one-child, and two-child families. Table three reports binary logistic regression results for fertility intention among Chinese married youth.

Model one predicts the ideal number of children, while Models two through four examine short-term plans among childless, one-child, and two-child families. The table groups predictors into socioeconomic status, parenting perceptions, COVID-induced factors, and controls, showing odds ratios and significance markers—for example, perceiving advantages in multi-child families is associated with an odds ratio of 2.995 in Model one.

Table Three reports odds ratios from four binary logit models: ideal family size, and short-term fertility plans among childless, one-child, and two-child families. The continuation focuses on children’s gender composition and time since the last birth, while also reporting model fit and sample sizes; for example, having both a boy and a girl has an odds ratio of five point three seven five in Model One.

These estimates matter because they show how fertility intentions are examined across distinct family structures. After controlling for other variables, each additional year of schooling decreased the likelihood of wanting more children by approximately 4.8 percent, and reduced the short-term birth probability of childless families by 9.5 percent.

Education did not affect short-term fertility plans for families with one or two children. Household economic status increased the chance of wanting at least two children by 3.5 percent, and increased the chance of a second child among one-child families by 9.4 percent.

Stable-job respondents did not show evidently higher fertility intentions than respondents with no job, so low fertility intentions cannot simply be attributed to unaffordability. Table Four uses sheaf coefficients to compare the relative effects of socioeconomic status, parenting perception, and COVID-induced factors across four fertility-intention outcomes.

The reported coefficients include standard errors in parentheses, with three asterisks indicating significance below zero point zero one; control variables are included in every model. This matters because the approach treats each factor group as a latent variable, allowing the authors to compare its contribution within the same model and identify which domains deserve policy attention.

Figure one partitions the explanatory contribution of three latent variables across different fertility intentions. COVID-induced factors account for seventy point twenty-eight percent of the first-kid plan and sixty-eight point twenty-five percent of the second-kid plan, while parenting perception accounts for fifty-nine point fifty-seven percent of the ideal number of children.

This matters because it shows that fertility intention is multidimensional: short-term plans and the desired family size are associated with different patterns of contribution. Because the sheaf coefficients are standardized, the effect sizes of latent variables can be compared within the same model, with the effects constrained to sum to one.

Figure one shows that COVID-19-induced factors are very important, explaining approximately 70 percent of the total variation in fertility plans caused by the three latent variables. Among Chinese married youth, fertility intentions were low, and COVID-19-induced factors were especially important for short-term fertility planning.

The results suggest that fertility policy must address relationship and pandemic-related constraints, not affordability alone.