Evidence map›Paper›PMID 42342839›Full record

ArticleCommunications medicine2026

Observation and modeling of fertility loss attributable to natural disasters from 1990-2021.

Manman Chen, Wanzhou Wang, Din Son Tan, Zichen Ye, Yuankai Zhao, Ze Liang, Xijie Wang, Juan Juan, Chao Yang

Abstract read
In one paragraph

Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Manman Chen *School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Wanzhou Wang *Center for Digital Health and Artificial Intelligence, Peking University First Hospital, Beijing, China.
Din Son TanVanke School of Public Health, Tsinghua University, Beijing, China.
Zichen YeSchool of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yuankai ZhaoSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Ze LiangSchool of Economics and Management, Harbin Institute of Technology, Harbin, Heilongjiang, China.
Xijie WangSchool of Disaster and Emergency Medicine, Tianjin, China. xijie_wang@126.com.ORCID http://orcid.org/0000-0002-2035-4311
Juan JuanDepartment of Obstetrics & Gynecology and Reproductive Medicine, Peking University First Hospital, Beijing, China. juanjuan@bjmu.edu.cn.
Chao YangCenter for Digital Health and Artificial Intelligence, Peking University First Hospital, Beijing, China. pkuyangchao@126.com.ORCID http://orcid.org/0000-0002-9864-0510

Funding

Beijing Nova Program 20250484916National Natural Science Foundation of China (National Science Foundation of China) 82204067National Natural Science Foundation of China (National Science Foundation of China) 825B2103
6 · The paper itself

Abstract

backgroundNatural disasters have increasingly threatened population health, but their global impacts on fertility remain uncertain. This study aims to quantify global fertility loss attributable to natural disasters and its socioeconomic disparities.

methodsWe conducted a two-stage analysis using disaster records from the Emergency Events Database (EM-DAT) and total fertility rate (TFR) and net reproductive rate (NRR) data from the Global Burden of Disease (GBD) 2021 database. First, we used country-year panel data to assess exposure-response functions. Second, we estimated spatiotemporal distributions and inequalities of global, regional, and national fertility losses attributable to natural disasters.

resultsHere we show that, globally, floods and storms contribute to annual TFR losses of 103.79 and 38.75 per 100,000 women of childbearing age. Flood-attributable TFR loss is most pronounced in South Asia, particularly in low-SDI and low-income countries, whereas storm-attributable TFR loss is greater in high-SDI and middle-income countries. For NRR, epidemics, storms, floods, and earthquakes contribute to losses of 35.26, 32.36, 31.96, and 24.53 per 100,000 women of childbearing age annually. South Asia shows the highest NRR losses attributable to floods, storms, and earthquakes, whereas Sub-Saharan Africa shows the highest epidemic-attributable NRR loss. Epidemic- and flood-attributable NRR losses are higher in low-SDI and low-income countries, whereas earthquake- and storm-attributable NRR losses are higher in middle- to high-SDI and income countries.

conclusionFloods, storms, earthquakes, and epidemics contribute to significant fertility loss worldwide, with geographical and socioeconomic disparities. Regions prone to these disasters should implement local-specific reproductive health strategies to maintain sustainable demographic structures.

Identifiers

PMID42342839
PMCPMC13654928

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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.