Evidence map›Paper›PMID 40017861›Full record

ArticleBMJ public health2023

Menopausal status, age at menopause and risk of all-cause mortality among Chinese women: findings from a 10-year prospective study.

Sha Huang, Ruofan Gongye, Siyu Zou, Jia Yi Hee, Kun Tang

Abstract read
In one paragraph

Article in BMJ public health, 2023. 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.

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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

5 authors.

Sha HuangSchool of Life and Health Sciences, Hainan University, Haikou, China.
Ruofan GongyeVanke School of Public Health, Tsinghua University, Beijing, China.
Siyu ZouVanke School of Public Health, Tsinghua University, Beijing, China.
Jia Yi HeeVanke School of Public Health, Tsinghua University, Beijing, China.
Kun TangVanke School of Public Health, Tsinghua University, Beijing, China.ORCID 0000-0002-5444-186X

Funding

Wellcome Trust
6 · The paper itself

Abstract

Introduction: Menopause characteristics (menopausal status and age at menopause) have been implicated in future health consequences. However, evidence of the impact on menopause on total mortality has been inconsistent. The present study aimed to investigate the associations of menopausal status and age at menopause with the risk of all-cause mortality in Chinese women. Methods: We used prospective data from the China Kadoorie Biobank cohort study that recruited over 300 000 women aged 30-79 years from 10 regions across China between 2004 and 2008. All participants were prospectively followed up, with a median follow-up of 10.20 years. Cox proportional hazard regression was used to examine HRs with 95% CIs for all-cause mortality associated with menopausal status and age at menopause. Results: Compared with premenopausal women, postmenopausal women were at higher risk of all-cause mortality with adjusted HR of 1.11 (95% CI 1.03 to 1.20). Among postmenopausal women, the HRs of total mortality were 1.25 (95% CI 1.14 to 1.36), 1.09 (95% CI 1.03 to 1.15), 0.98 (95% CI 0.94 to 1.02) and 0.97 (95% CI 0.91 to 1.04) for menopause at ages less than 40, 40-44, 50-53 and 54 years or older, respectively, relative to 45-49 years. In addition, for each 1-year increase in age at menopause was associated with a 1% decreased risk of death from all causes (95% CI 0.98 to 0.99). Conclusions: Women with postmenopausal status had a higher risk of all-cause mortality than premenopausal women, particularly for ages at menopause younger than 45 years.

Indexed as

EpidemiologyFemalePublic Health

Identifiers

PMID40017861
PMCPMC11816857

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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.