Evidence map›Paper›PMID 42152118›Full record

ArticleReproductive health2026

Age at menopause and risk of sarcopenia in postmenopausal women: evidence from the China health and retirement longitudinal study.

Yachai Li, Liang Qin, Yan Wang, Shentai Li, Li Ling, Nan Jia

Abstract read
In one paragraph

Article in Reproductive health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yachai Li *Department of Gynecology, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, China.
Liang Qin *Department of Rehabilitation Medicine, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, China.
Yan Wang *Internal Medicine of Integrated Chinese and Western Medicine, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, China.
Shentai LiDepartment of Orthopaedics, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050000, China. 28704036@hebmu.edu.cn.
Li LingDepartment of Neurology, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, China. 592201535@qq.com.
Nan JiaDepartment of Neurology, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, China. gill913@sina.com.

Funding

Medical Science Research Project of Hebei 20230438
6 · The paper itself

Abstract

backgroundMenopausal age is closely associated with women's health, but research on its association with sarcopenia risk remains insufficient. Our study aimed to explore how menopausal age affects the risk of sarcopenia in postmenopausal women.

methodsBased on the China Health and Retirement Longitudinal Study (CHARLS) database, we included 3,410 postmenopausal women from 2011-2015. Participants were divided into five groups according to menopausal age: premature menopause (< 40 years), early menopause (40-44 years), intermediate menopause (45-49 years), normal menopause (50-55 years), and late menopause (> 55 years). Sarcopenia was identified using the 2019 Asian Working Group for Sarcopenia (AWGS 2019) criteria. Mixed-effects logistic regression models were used to analyze the association between menopausal age and sarcopenia.

resultsThe study included 3,410 postmenopausal women with a mean age of 64.39 ± 8.68 years and overall sarcopenia prevalence of 35.40%. Compared to the average age at menopause group (50-55 years; 1,593/3,410; 46.70%), premature menopause (127/3,410; 3.70%), early menopause (385/3,410; 11.30%), intermediate menopause (1,098/3,410; 32.20%), and late menopause (207/3,410; 6.10%) were all associated with increased sarcopenia risk. Compared to normal menopause (50-55 years), early menopause (40-44 years), intermediate menopause (45-49 years), and late menopause (> 55 years) were associated with statistically significant increased sarcopenia risk, while premature menopause (< 40 years) showed a non-significant elevated risk (OR = 1.40, 95% CI: 0.89-2.21, p = 0.1438). This association was stronger among women with late menarche, rural residence, married status, non-retirement, or low education levels.

conclusionsBoth earlier and later than average menopausal age may be associated with increased sarcopenia risk in Chinese postmenopausal women, although the association for premature menopause did not reach statistical significance in fully adjusted models.

Indexed as

MenopausePostmenopauseSarcopeniaAdultAgedAge FactorsChinaFemaleHumansLongitudinal StudiesMiddle AgedPrevalenceRisk FactorsAge at menopauseMiddle-aged and elderly womenSarcopeniaWomen's health

Identifiers

PMID42152118
PMCPMC13352640

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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.