Evidence map›Paper›PMID 34348705›Full record

ArticleBMC women's health2021

Association between sleep quality and central obesity among southern Chinese reproductive-aged women.

Bingbing Li, Nan Liu, Donghui Guo, Bo Li, Yan Liang, Lingling Huang, Xiaoxiao Wang, Zhenzhen Su, Guozeng Zhang, Peixi Wang

Open access · goldAbstract read
In one paragraph

Article in BMC women's health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

8 citing papers in PubMed, 19 citations in OpenAlex.

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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

10 authors at 7 institutions in 1 country.

Bingbing LiInstitute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, 475004, China.
Nan LiuInstitute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, 475004, China.
Donghui GuoThe People's Hospital of Longhua.Shenzhen, Shenzhen, 518109, China.
Bo LiInstitute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, 475004, China.
Yan LiangThe Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, China.
Lingling HuangInstitute of Nursing and Health, Shanghai Lida University, Shanghai, 201609, China.
Xiaoxiao WangNursing Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei Province, China.
Zhenzhen SuInstitute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, 475004, China.
Guozeng ZhangInstitute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, 475004, China. zhanggz@henu.edu.cn.
Peixi WangInstitute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, 475004, China. peixi001@163.com.
Henan University · CNHuazhong University of Science and Technology · CNSanda University · CNShenZhen People’s Hospital · CNThird Affiliated Hospital of Southern Medical University · CNTongji Hospital · CNXuzhou Medical College · CN

Funding

the Henan key R&D and promotion program 2019510the National Natural Science Foundation of China 81872584
6 · The paper itself

Abstract

backgroundThe connections between sleep quality and central obesity among reproductive-aged women are not clear. The study aimed to explore the association between sleep quality and central obesity among Chinese reproductive-aged women and identify the independent contributions of sociodemographic characteristics, health-related factors, and sleep quality to central obesity.

methodsIn this cross-sectional survey, the minimal sample sizes were 2404 subjects; 2449 Chinese women aged 18-49 participated in this study. Sleep quality was assessed by the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Central obesity as the outcome of interest was a binary variable; women were categorized as with versus without central obesity measured by waist circumference (WC). The independent contribution of sociodemographic characteristics (Cluster 1), health-related variables (Cluster 2), and sleep quality (Cluster 3) to central obesity was derived from the corresponding R

resultsThe risk of central obesity increased significantly with poor sleep quality (assessed by global PSQI score) [adjusted odds ratio (OR) = 2.20 per SD increase; 95% confidence interval (CI) = 1.28-3.78; P = 0.004], increased sleep disturbance score (adjusted OR = 1.11 per SD increase; 95% CI = 1.01-1.22; P = 0.042) and decreased subjective sleep quality score (adjusted OR = 0.81 per SD increase; 95% CI = 0.73-0.90; P < 0.001). The independent contribution of sleep quality was 9.9%, less than those of sociodemographic (73.3%) and health-related (16.8%) variables. Among complaints related to sleep disturbance, the inability to breathe comfortably, and having bad dreams showed significant associations with central obesity.

conclusionsThere exists some degree of correlation between sleep quality and central obesity among Chinese reproductive-aged women. These findings underscore the need for future public health guidelines to formulate some detailed strategies to improve sleep quality, such as preventing and intervening risk factors that influence sleep quality and suggesting optimal sleep duration, which might effectively reduce the incidence of central obesity in this population group.

Indexed as

Obesity, AbdominalSleep Wake DisordersAdultChinaCross-Sectional StudiesFemaleHumansSleepCentral obesityChinesePittsburgh Sleep Quality IndexReproductive-aged womenSleep quality

Identifiers

PMID34348705
PMCPMC8336247
OpenAlexW3191601234

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.