Evidence map›Paper›PMID 31906177›Full record

ArticleInternational journal of environmental research and public health2019

A Large Sample Survey of Tibetan People on the Qinghai-Tibet Plateau: Current Situation of Depression and Risk Factors.

Jiazhou Wang, Yueyue Zhou, Yiming Liang, Zhengkui Liu

Abstract read
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Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

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26citing papers in PubMed, 1 pooled it
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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

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  20. Symptom Structure of Depression in Older Adults on the Qinghai-Tibet Plateau: A Network Analysis.International journal of environmental research and public health · 2022
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jiazhou WangCAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China.
Yueyue ZhouCAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China.
Yiming LiangCAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China.
Zhengkui LiuCAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA depressive state is a negative emotional state characterized by abnormal dejection and unpleasant mood. Long-term depressive symptoms can result in psychological disorders such as depression. However, little is known about the depression status and risk factors of the Tibetan people on the Qinghai-Tibet Plateau.

objectiveThis study explores the depression status of the Tibetan people to better promote ethnic minorities' physical and mental health. PARTICIPANTS AND

settingThe Center for Epidemiologic Studies Depression Scale (CES-D) was administered to 24,141 Tibetan people from Yushu Prefecture; the average age was 34.33 years (SD = 9.18, range = 18-94 years). MATERIALS AND

methodsParticipants completed questionnaires collecting demographic information and evaluating symptoms of depression.

resultsThe depression prevalence was higher at high altitudes, and there may be a significant positive correlation between depression rates and altitude. Significant differences were found for each demographic variable. Participants with depressive symptoms (scores ≥8) accounted for 52.3% of the total sample, and participants with depression (scores ≥14) accounted for 28.6%. The binary logistic regression results showed that alcohol drinkers, unmarried participants, participants with high self-assessed socioeconomic status, participants with a high income level, and those with a middle-school education were more likely to be depressed.

conclusionsThe results provide the first evidence that the prevalence of depression in Tibetans of the Qinghai-Tibet Plateau is higher than that in the general Chinese population and that reported in Western studies, a finding that may be related to cultural differences and chronic hypoxia caused by the high altitude. This paper offers insight into the mental health status of people living in plateau areas and provides a basis for formulating pertinent mental health policy.

Indexed as

AdolescentAdultAgedAged, 80 and overCross-Sectional StudiesDepressionFemaleHumansMaleMiddle AgedPrevalencePsychiatric Status Rating ScalesRisk FactorsTibetYoung Adultdepressionhigh altitudemental healthQinghai–Tibet plateauTibetan people

Identifiers

PMID31906177
PMCPMC6981986

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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.