Evidence map›Paper›PMID 42826256›Full record

ArticleMedicine2026

The association between education level, widowhood, and depression among elderly Chinese after controlling for demographic, health, and behavioral variables.

Qingdong Ling, Yaqun Zhang

Abstract read
In one paragraph

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

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Qingdong LingSchool of Sports Medicine, Anshan Normal University, Anshan, Liaoning, China.
Yaqun Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid advancement of China's aging population, the mental health problems of the elderly, especially depression, have become an important concern in the field of public health. However, research on the combined effect of education level and widowhood on depression is still relatively limited. The aim of this study is to explore the association between education level, widowhood status, and depression symptoms among elderly people in China, and further analyze the moderating effects of health status, demographic characteristics, and behavioral variables in this association. Data from the 2018 China Health and Retirement Longitudinal Study were used. A total of 3243 participants aged 50 and above were analyzed. A simplified 10 item CES-D scale was used to assess depression. Logistic regression models were used to examine the independent and interactive effects of education level and widowhood on depression, while adjusting for demographic variables (age, gender, type of residence), health status (chronic disease, self-rated health), and behavioral factors (physical activity, smoking). Even after controlling for confounding factors, lower levels of education were significantly associated with a higher risk of depressive symptoms (odds ratio [OR] = 1.52, P < .01). Widowhood is also a strong predictor of depression (OR = 1.79, P < .01), especially in women. Interaction analysis indicates that poor self-rated health and a sedentary lifestyle exacerbate the negative impact of low education and widowhood on depression. In addition, rural residents and individuals with lower socioeconomic status face a higher risk of depression symptoms. Low education level and widowhood are independent factors contributing to the high incidence of depression among elderly people in China. Health status and lifestyle factors play a crucial mediating role in this association. These findings emphasize the necessity of targeted intervention measures, such as community-based education programs, sports promotion, and strengthening social support networks, to reduce the risk of depression among vulnerable elderly people in China.

Indexed as

DepressionEducational StatusWidowhoodAgedAged, 80 and overChinaEast Asian PeopleFemaleHealth StatusHumansLongitudinal StudiesMaleMiddle AgedRisk Factorsbehavioral factorsChinadepressioneducation levelhealth statusold agewidowhood

Identifiers

PMID42826256
PMCPMC13633002

What Socratic holds

Textmetadata
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Registered trials

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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 Socratic graph.