Evidence map›Paper›PMID 39024620›Full record

Observational studyJournal of global health2024

Burden of multiple high-risk factors in pregnancy before and after the universal two-child policy in Chinese women: An observational study.

Yue Zhang, Weijie Ding, Xiaochen Dai, Hui Wang, Yangyang Cheng, Jiyue Dai, Xiaoqin Zhu, Xiaolin Xu

Abstract readObservational Study
In one paragraph

Observational study in Journal of global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

8 authors.

Yue Zhang *School of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
Weijie Ding *Health Care Department, Huai'an Maternal and Child Health Care Hospital Affiliated to Yangzhou University, Huai'an City, Jiangsu Province, China.
Xiaochen DaiDepartment of Health Metrics Science, School of Medicine, University of Washington, Seattle, Washington, USA.
Hui WangSchool of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
Yangyang ChengSchool of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
Jiyue DaiHealth Care Department, Huai'an Maternal and Child Health Care Hospital Affiliated to Yangzhou University, Huai'an City, Jiangsu Province, China.
Xiaoqin ZhuHealth Care Department, Huai'an Maternal and Child Health Care Hospital Affiliated to Yangzhou University, Huai'an City, Jiangsu Province, China.
Xiaolin XuSchool of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prevalence of high-risk pregnancy increased after the implementation of two-child policy in China, but the impact of this policy change on the burden and profile of multiple high-risk factors in pregnancy (MHFP) has been insufficiently explored. We hypothesised that the profile of MHFP might have changed after the two-child policy was implemented and aimed to estimate the prevalence, intercorrelation, and outcomes of MHFP before and after its introduction. Methods: We obtained data on the population of pregnant women before (2015) and after (2020/2021) the implementation of universal two-child policy in Huai'an. We then included 33 risk factors in our analysis based on the Five-Colour Management framework and defined MHFP as an individual having two or more of these factors. We also estimated the changes of the prevalence of each single factor and their coexistence. Lastly, we performed a network analysis to assess the intercorrelations across these factors and used logistic regression models to evaluate MHFP-related pregnancy outcomes. Results: We observed an increase in the prevalence of MHFP after the implementation of the universal two-child policy (25.8% in 2015 vs 38.4% in 2020/2021, P < 0.01). Chronic conditions (e.g. gestational diabetes mellitus, abnormal body mass index) had the largest increase among the included factors, while cardiovascular disease and hypertensive disorders were central factors of the network structures. The correlations of advanced maternal age with abnormal pregnancy histories and scarred uteri increased significantly from 2015 to 2020/2021. MHFP was associated with multiple pregnancy outcomes, including preterm birth (adjusted odds ratio (aOR) = 2.57; 95% confidence interval (CI) = 2.39-2.75), low birthweight (aOR = 2.77; 95% CI = 2.54-3.02), low Apgar score (aOR = 1.41; 95% CI = 1.19-1.67), perinatal death (aOR = 1.75; 95% CI = 1.44-2.12), and neonatal death (aOR = 1.76; 95% CI = 1.42-2.18). Moreover, an increasing number and certain combinations of MHFP were associated with higher odds of pregnancy outcomes. For example, the aOR of preterm birth increased from 1.67 (95% CI = 1.52-1.87) for one risk factor to 8.03 (95% CI = 6.99-9.22) for ≥4 risk factors. Conclusions: Chinese women experienced a higher burden of multiple high-risk factors after the introduction of the two-child policy, particularly those with advanced maternal age, obesity, and chronic conditions. Strategies targeting chronic conditions for women with MHFP should be prioritised and a shift to a multiple-factor-oriented framework is needed in the expanding Chinese maternal health care system.

Indexed as

Family Planning PolicyPregnancy ComplicationsAdultChinaEast Asian PeopleFemaleHumansPregnancyPregnancy, High-RiskPregnancy OutcomePrevalenceRisk FactorsYoung Adult

Identifiers

PMID39024620
PMCPMC11257705

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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.