The birth rate in mainland China declined from 12.95‰ in 2016 to 6.39‰ in 2023, posing significant challenges to social harmony and sustainable development. To evaluate the effectiveness and impact of family planning policy adjustments, this study collected birth rate and population data for mainland China (2007 - 2023) and eight provinces, including Shanghai and Beijing (provincial-level municipalities), Xinjiang, Heilongjiang, Hunan, Hebei, Hainan, and Guangdong. Using Joinpoint regression and autoregressive integrated moving average models, we analyzed birth rate trends, assessed the stimulatory effects of four family planning policy adjustments (2011 - 2021), and projected future birth rate trajectories for both mainland China and the selected provinces. The findings show that the partial two-child policies (2011, 2013) stabilized national birth rates and triggered short-term regional increases. The universal two-child policy (2016) caused a temporary surge, followed by a continued linear decline. The three-child policy (2021) failed to reverse this trend and had a negligible impact. Key drivers include a 19% decrease in the population of women of childbearing age and a 34% decline in childbearing willingness. Projections from birth rate models (2024 - 2030) demonstrate a continued national decline, with significant regional disparities in both demographic characteristics and policy responsiveness. To address these dual challenges, China must implement comprehensive reforms to its national family planning policies to support sustainable social development, alongside province-specific interventions tailored to local demographic conditions to maintain regional balance.
Funding
This research was supported by funding from the Shunyi District for Health Improvement and Research (Grant No. Wsjkfzkyzx-2023-q-05).
Conflict of interest
The authors declare that they have no competing interests.
| [1] |
Azcorra H., Salazar-Rendón J.C., Rodríguez L., Vázquez- Vázquez A., & Mendez-Dominguez N. (2023). The impact of COVID-19 on the number of births in Yucatan, Mexico. American Journal of Human Biology, 35(4):e23849. https://doi.org/10.1002/ajhb.23849
|
| [2] |
Babu N.C., & Padma A.S. (2024). Future prediction of population, birth and fertility rates in India. Indian Journal of Community Health, 36(1):153-155. https://doi.org/10.47203/IJCH.2024.v36i01.025
|
| [3] |
Chen H., Boo H.S. & Teng K.Y. (2025). Unmet preconditions and individualism: Factors contributing to low fertility intentions and population decline in China. International Journal of Population Studies, 11(3):68-90. https://doi.org/10.36922/ijps.5124
|
| [4] |
Clegg L.X., Hankey B.F., Tiwari R., Feuer E.J., & Edwards B.K. (2009). Estimating average annual percent change in trend analysis. Statistics in Medicine, 28(29):3670-3682. https://doi.org/10.1002/sim.3733
|
| [5] |
Du Y., & Dong H. (2024). Family planning policy adjustment and family fertility response - Analysis from the perspective of social stratification. Sociological Research, 39(1):64-86.
|
| [6] |
Giglio N., Lasalvia P., Pawaskar M., Parellada C.I., Rojas Y.G., Micone P., et al. (2022). Trends in varicella burden of disease following introduction of routine childhood varicella vaccination in Argentina: A 12-year time series analysis. Vaccines, 10(7):1151. https://doi.org/10.3390/vaccines10071151
|
| [7] |
Helfenstein U. (1991). The use of transfer function models, intervention analysis and related time series methods in epidemiology. International Journal of Epidemiology, 20(3): 808-815. https://doi.org/10.1093/ije/20.3.808
|
| [8] |
Islami F., Ward E.M., Sung H., Cronin K.A., Tangka F.K.L., Sherman R.L., et al. Annual report to the nation on the status of cancer, Part 1:National cancer statistics. Journal of the National Cancer Institute, 113(12):1648-1669. https://doi.org/10.1093/jnci/djab131
|
| [9] |
Kim H.J., Fay M.P., Feuer E.J., & Midthune D.N. (2000). Permutation tests for joinpoint regression with applications to cancer rates. Statistics in Medicine. 19(3):335-351. https://doi.org/10.1002/(SICI)1097-0258(20000215)19:3<335:AID-SIM336>3.0.CO;2-Z
|
| [10] |
Liang T., & Li A. (2024). Will the adjustment of our family planning policy change people’s fertility intention?. Contemporary Economic Management. 46(10):76-87. https://doi.org/10.13253/j.cnki.ddjjgl.2024.10.007
|
| [11] |
Liu J., Ding W., & Jia H. (2016), A Study on the impact of fully relaxing the two child policy on the birth rate: A case study of Tangshan city. Contemporary Economy, 13:2-5. https://doi.org/10.3969/j.issn.1007-9378.2016.13.036
|
| [12] |
Lv T., Zhang H., Xie X., Yuan H., Huang Y., & Zou Y. (2025), Perspectives on advanced care planning of adolescent and young adult cancer patients, families, and healthcare providers: A qualitative study based on the health belief model. Asia-Pacific Journal of Oncology Nursing. 12:100635. https://doi.org/10.1016/j.apjon.2024.100635
|
| [13] |
Moreno-Agostino D., Wu Y.T., Daskalopoulou C., Hasan M.T., Huisman M., & Prina M. (2021), Global trends in the prevalence and incidence of depression: A systematic review and meta-analysis. Journal of Affective Disorders, 281:235-243. https://doi.org/10.1016/j.jad.2020.12.035
|
| [14] |
Nandi P., Kramer M., & Kottke M. Changing disparities in teen birth rates and repeat birth rates in Georgia: Implications for teen pregnancy prevention. Contraception, 99(3):175-178. https://doi.org/10.1016/j.contraception.2018.11.007
|
| [15] |
Pai P.F., & Lin C.S. (2005), A hybrid ARIMA and support vector machines model in stock price forecasting. Omega. 33(6):497-505. https://doi.org/10.1016/j.omega.2004.07.024
|
| [16] |
Pomar L., Favre G., Labrusse C.D., Contier A., Boulvain M., & Baud D. (2022), Impact of the first wave of the COVID-19 pandemic on birth rates in Europe: A time series analysis in 24 countries. Human Reproduction, 37(12):2921-2931. https://doi.org/10.1093/humrep/deac215
|
| [17] |
Qi M., Dai M., & Zheng Y. (2016), The impact and trend of China’s “universal two-child policy” on birth rates. Journal of Anhui University (Social Sciences Edition), 26(9):1-10. https://doi.org/10.3969/j.issn.1002-2104.2016.09.001
|
| [18] |
Rose J., Weiser T.G., Hider P., Wilson L., Gruen R.L., & Bickler S.W. (2015), Estimated need for surgery worldwide based on prevalence of diseases: A modelling strategy for the WHO global health estimate. Global Surgery, 3:S13-S20. https://doi.org/10.1016/S2214-109X(15)70087-2
|
| [19] |
Shiva H, & Mohsen R. (2024), Impact of COVID-19 pandemic on marriage, divorce, birth, and death in Kerman province, the ninth most populous province. Sci Rep.14:3980-3989. https://doi.org/10.1038/s41598-024-54679-5
|
| [20] |
Song J., Gao S., Zhao L., & Tong X. (2025), Distribution and related influencing factors of AMH level in family-planning women of childbearing age: A cross-sectional study from Beijing, China. International Journal of Women’s Health, 17:99-107. https://doi.org/10.2147/IJWH.S499220
|
| [21] |
Song Q., & Wen Q. (2015), The significance, current situation and problems of the implementation of the two-child population policy in China. Journal of Nantong University (Social Science Edition), 31(1), 122-129.
|
| [22] |
Wang M., Pan J., Li X., Li M., Liu Z., Zhao Z., et al. (2022), ARIMA and ARIMA-ERNN models for prediction of pertussis incidence in mainland China from 2004 to 2021. BMC Public Health, 22(1), 1447. https://doi.org/10.1186/s12889-022-13872-9
|
| [23] |
Wang W., Van Gelder P.H.A.J.M., Vrijling J.K., & Ma J. (005), Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes. Nonlinear Processes in Geophysics, 12(1), 55-66. https://doi.org/10.5194/npg-12-55-2005
|
| [24] |
Wang Y., & Wu S. (2023), Statistical analysis and prediction of population in China based on ARIMA model. Journal of Jilin Institute of Chemical Technology, 40(5):85-90. https://doi.org/10.16039/j.cnki.cn22-1249.2023.05.016
|
| [25] |
Weir H.K., Thompson T.D., Soman A., Møller B., & Leadbetter S. (2015), The past, present, and future of cancer incidence in the United States: 1975 through 2020. Cancer, 121(11):1827-1837. https://doi.org/10.1002/cncr.29258
|
| [26] |
Xu K., Hu D., & Liu Y. (2022), Fertility policy, cost socialization and birth rate. Journal of Guizhou University of Finance and Economics, 2:69-78. https://doi.org/10.3969/j.issn.1003-6636.2022.02.007
|
| [27] |
Yakita A. (2018), Female labor supply, fertility rebounds, and economic development. Review of Development Economics, 22:1667-1681. https://doi.org/10.1111/rode.12411
|
| [28] |
Ye T., & Zheng H. (2023), Analysis of birth rates in China with uncertain statistics. Journal of Intelligent and Fuzzy Systems, 44(6):10621-10632. https://doi.org/10.3233/JIFS-230179
|
| [29] |
Zhang G.P. (2003), Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing, 50:159-175. https://doi.org/10.1016/S0925-2312(01)00702-0
|
| [30] |
Zhang J., Ding S., & Hu X. (2022), Analysis of spatial and temporal impact differences of birth rate in mainland China. Scientific Reports, 12:1-8. https://doi.org/10.1038/s41598-022-22403-w
|
| [31] |
Zhang L., Ren L., Li H., Qiu H., Yang H., Shi X., et al. (2025), The effects of maternal health literacy, family functioning and self-efficacy on antepartum depression in pregnant women in China: A moderated mediation model. BMC Psychiatry, 25:101. https://doi.org/10.1186/s12888-025-06557-1
|
| [32] |
Zhang R., Gao X., Liu J., Xiao T. (2025), China’s fertility support policies: Current situation and prospects. Population Journal, 47(3):19-36. https://doi.org/10.16405/j.cnki.1004-129X.2025.03.002
|
| [33] |
Zhang S. (2024), The Influence Factors and Statistical Prediction of Population Birth Rate. Master’s Thesis, Nanchang University. https://doi.org/10.27232/d.cnki.gnchu.2024.000840
|
| [34] |
Zhong X. (2016), Evaluation and optimization strategy of the implementation effect of the universal two-child policy-based on the survey of the fertility desire of urban ‘double non’ couples. China Administration, 7:127-131. https://doi.org/10.3782/j.issn.1006-0863.2016.07.19
|
| [35] |
Zhu B., & Qiao X. (2018), Research on the relationship between total fertility rate and birth rate based on curve fitting model. Population and Development, 24(5):63-71.
|
| [36] |
Zhu S. (2014), Analysis of fertility desire and its influencing factors of married women of childbearing age under the background of ‘comprehensive three-child’ in Nanchang. Practical Clinical Medicine, 23(5):111-114. https://doi.org/10.13764/j.cnki.lcsy.2022.05.031
|