Evidence map›Paper›PMID 40951382›Full record

ArticleFrontiers in public health2025

Effect of "universal two-child" policy on population changes in Shandong province, China: an interrupted time series analysis.

Keqing Shi, Wenhui Cui, Shuyu Chen, Xueli Zhang, Xin Wang, Mengjun Cao, Hang Gao, Qiang Wang

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Keqing Shi *College of Public Health, Shandong Second Medical University, Weifang, China.
Wenhui Cui *College of Public Health, Shandong Second Medical University, Weifang, China.
Shuyu Chen *College of Public Health, Shandong Second Medical University, Weifang, China.
Xueli Zhang *Department of Histology and Embryology, College of Basic Medical Sciences, Shandong Second Medical University, Weifang, China.
Xin WangCollege of Public Health, Shandong Second Medical University, Weifang, China.
Mengjun CaoCollege of Public Health, Shandong Second Medical University, Weifang, China.
Hang GaoCollege of Clinical Medical Sciences, Shandong Second Medical University, Weifang, China.
Qiang WangDepartment of Epidemiology, Shandong Second Medical University, Weifang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As population aging intensifies and women's fertility levels decline continuously, the improvement of fertility policies has emerged as a pivotal concern for most governments. This study aimed to evaluate the effect of the "universal two-child" policy implementation on the birth population trend. Methods: A quasi-experimental interrupted time series (ITS) study was conducted to analyze the collected data. Data on the birth population of Shandong province from 2000 to 2022 were collected to observe trend changes before and after the intervention. Results: The birth rate increased immediately in the first year after the intervention ( Conclusion: The policy implementation helped to boost the population growth in the short term, but the long-term effect of the policy was not optimistic. More targeted incentive strategies should be considered to reverse the continuous decline in fertility rates.

Indexed as

Birth RateFamily Planning PolicyPopulation DynamicsAdultChinaFemaleHumansInterrupted Time Series Analysisbirthsfertility ratesinterrupted time seriessegmented regression analysisthe universal two-child policy

Identifiers

PMID40951382
PMCPMC12423096

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.