Evidence map›Paper›PMID 40770308›Full record

ArticleBMC public health2025

Fertility intentions among Chinese adults: a cross-sectional study using a national survey.

Mingyan Hao, Chenxiao Zhang, Haofeng Fu, Jingting Zhang, Ziyi Zhang, Baotong Ma, Ruitong Xia, Yuanwei Lu, Jingwen Liu, Hanjia Xin and 20 more

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

30 authors.

Mingyan HaoShanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, School of Public Health, Shanxi Medical University, Taiyuan, 030013, China. mingyan.hao@duke.edu.
Chenxiao ZhangSchool of Social and Behavioral Sciences, Nanjing University, Nanjing, 210000, China.
Haofeng FuSchool of Infectious Diseases and Public Health, City University of Hong Kong, Kowloon, Hong Kong, 999077, China.
Jingting ZhangSchool of Public Health, Hebei Medical University, Shijiazhuang, 050017, China.
Ziyi ZhangSchool of Stomatology, North Sichuan Medical College, Nanchong, 637100, Sichuan, China.
Baotong MaSchool of Management, Hainan Medical University, Haikou, 571199, China.
Ruitong XiaSchool of Humanities and Foreign Languages, Qingdao University of Technology, Qingdao, 266525, China.
Yuanwei LuSchool of Management, North Sichuan Medical College, Nanchong, 637100, China.
Jingwen LiuSchool of Nursing, Shanxi Medical University, Taiyuan, 030001, China.
Hanjia XinSchool of Nursing, Nanchang University, Nanchang, 330031, China.
Yumeng CaoDepartment of Stomatology, Jitang College of North China University of Science and Technology, Tangshan, 063202, China.
Saier YangSchool of Geriatric Nursing and Wellness, Tianfu College of Southwestern, University of Finance and Economic, Chengdu, 611130, China.
Runqing LiSchool of Philosophy and Social Development, Shandong University, Jinan, 250100, China.
Ji ZhaoSchool of Medical, Tibet University, Lhasa, 850000, China.
Jin ZhangSchool of Journalism and Communication, Jinan University, Guangzhou, 510632, China.
Zheng GaoMedical School, Nanjing University, Nanjing, 210093, China.
Yaxin ZengSchool of Economics & Management, Nanchang University, Nanchang, 330031, China.
Yixiao DingSchool of Teachers College, Shihezi University, Shihezi, 832003, China.
Zhuolun RenSchool of Journalism and Communication, Renmin University of China, Beijing, 100872, China.
Yan GuanSchool of Health Management, Guangzhou Medical University, Guangzhou, 511436, China.
Na ZhangSchool of Nursing, Health Science Center, Xi'an Jiaotong University, Xi'an, 710049, China.
Jia LiSchool of Literature and Communication, Yunnan Minzu University, Kunming, 650500, China.
Yan MaSchool of First Clinical Medical College, Inner Mongolia Medical University, Hohhot, 010107, China.
Pei WeiSchool of Accounting and Audit, Guangxi University of Finance and Economics, Guangxi, 530007, China.
Jingjing DongSchool of Nursing, Henan University of Science and Technology, Luoyang, 471023, China.
Chen ChenSchool of Journalism and Communication, Lanzhou University, Lanzhou, 730000, China.
Yajing ZhouSchool of Nursing, North Sichuan Medical College, Nanchong, Sichuan, 637100, China.
Jianzhong ZhengShanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China. zjzhong4183@163.com.
Wei LiuShanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China. lyglge666@163.com.
Lizheng WangSchool of Public Health, Shanxi Medical University, Taiyuan, 030001, China. 435646547@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe decline in fertility intentions has emerged as a critical demographic and policy challenge within China, particularly in light of the introduction of the three-child policy. This situation necessitates a thorough examination of the multiple underlying factors that contribute to individuals' decisions regarding family size. By analyzing these diverse influences, policymakers and stakeholders will be better equipped to design effective interventions aimed at addressing this urgent issue. A nuanced comprehension of the complexities surrounding low fertility intentions is essential for promoting family growth and fostering stability within the nation. Ultimately, a targeted approach informed by these insights will be vital for encouraging a cultural shift towards larger families and ensuring the long-term demographic health of China.

methodsIn our research, we performed a cross-sectional analysis using data gathered in 2022 from the Psychology and Behavior Investigation of Chinese Residents (PBICR), which encompassed 21,916 participants aged 18 to 49 years. We assessed fertility intention scores for respondents based on their preferences for having a first, second, and third child, employing a scoring system that ranged from 0 to 100. To investigate the impact of various factors on fertility intentions, we organized the independent variables into three primary domains: socio-demographic characteristics, lifestyle and health behaviors, and family structure. We utilized domain-specific multivariate linear regression analyses, along with gender-stratified models, and examined interaction effects. The explanatory capacity of each model was evaluated by calculating R² values, which offered insights into the variance accounted for by the independent variables.

resultsOur research indicated that men demonstrated significantly higher scores for fertility intention than women, with a meaningful statistical difference (β = 7.63, p < 0.001). Various factors were recognized as positive indicators of fertility intention, such as being younger, residing in rural areas, having a favorable self-evaluation of health, and marital status. Moreover, behaviors like smoking and current alcohol use showed significant associations with fertility intentions. In our examination of family-related factors, we discovered that dual-income households without children (DINK) and nuclear family setups were linked to lower fertility intentions, whereas those living with parents expressed greater intentions to parent. Importantly, the interaction effects suggested that women faced a more pronounced decline in fertility intentions as age increased. Among the factors studied, socio-demographic characteristics explained the largest proportion of variance in fertility intentions (R² = 0.086).

conclusionsFertility intentions in China are shaped by various factors, such as differences between genders, individual health, and family structure. To tackle the challenge of decreasing fertility rates effectively, it is essential that interventions focus on younger women and highlight the advantages of living with multiple generations. In addition, reproductive policies ought to consider health and lifestyle factors, establishing a more comprehensive strategy to encourage family expansion in urban settings. Through the adoption of these approaches, stakeholders can strive to counteract the patterns of low fertility intentions and create an environment that supports family growth.

Indexed as

FertilityIntentionAdolescentAdultChinaCross-Sectional StudiesEast Asian PeopleFamily CharacteristicsFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultFertility intentionsInfluencing factorsLifestyle factors

Identifiers

PMID40770308
PMCPMC12326872

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.