Evidence map›Paper›PMID 42312227›Full record

ArticleDepression and anxiety2026

Association Between Intergenerational Relationship With Adult Children and Anxiety-Depression Comorbidity Symptoms in Older Women in China: A National Study Using Latent Profile Analysis.

Zishuo Huang, Jiaoqi Ren, Hanlei Tang, Gonghang Qiu, Borui Yang, Ying Wang, Houguang Zhou

Abstract read
In one paragraph

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

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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

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2 · The registry

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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

7 authors.

Zishuo HuangDepartment of Geriatrics, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China, fudan.edu.cn.ORCID 0009-0008-3112-1717
Jiaoqi RenDepartment of Geriatrics, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China, fudan.edu.cn.ORCID 0009-0008-4891-5150
Hanlei TangThe School of Public Health, Fudan University, Shanghai, 200032, China, fudan.edu.cn.ORCID 0009-0007-8543-7744
Gonghang QiuThe School of Public Health, Fudan University, Shanghai, 200032, China, fudan.edu.cn.ORCID 0009-0009-5689-3112
Borui YangThe School of Public Health, Fudan University, Shanghai, 200032, China, fudan.edu.cn.ORCID 0009-0000-0150-3839
Ying WangDepartment of Geriatrics, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China, fudan.edu.cn.ORCID 0000-0003-4757-1364
Houguang ZhouDepartment of Geriatrics, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China, fudan.edu.cn.ORCID 0000-0002-5550-1166

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The phenomenon of global aging is becoming increasingly salient, and the mental health of older women requires greater attention. However, there is a conspicuous paucity in the exploration of anxiety-depression comorbidity patterns among Chinese older women, as well as the correlation between intergenerational relationships with adult children and these comorbid conditions. Methods: About 20,153 older women aged 65 years or above from the China Aging and Health Survey (CAHS) were included in the study. Depression and anxiety were assessed using the Patient Health Questionnaire-9 (PHQ-9) and the 7-item Generalized Anxiety Disorder (GAD-7) Questionnaire, respectively. Latent profile analysis (LPA) was utilized to identify subgroups of older women exhibiting similar patterns of symptoms. To examine the association between intergenerational relationships with adult children and the comorbid patterns of anxiety and depression, multinomial logistic regression was employed. Finally, stratified analyses were conducted to perform sensitivity testing. Results: LPA revealed three profiles: low ( Conclusion: Anxiety-depression comorbidity patterns in older women can be classified into three categories: low, moderate, and high comorbidity. Moreover, intergenerational relationships with adult children are associated with these comorbid patterns, with more frequent interactions corresponding to lower levels of comorbidity.

Indexed as

Adult ChildrenAnxietyAnxiety DisordersDepressionDepressive DisorderIntergenerational RelationsAgedAged, 80 and overChinaComorbidityFemaleHumansLatent Class Analysisanxiety-depression comorbidity symptomsintergenerational relationshiplatent profile analysisolder women

Identifiers

PMID42312227
PMCPMC13269846

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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.