Evidence map›Paper›PMID 31431681›Full record

ArticleJournal of human hypertension2020

Association of long-term sleep habits and hypertension: a cross-sectional study in Chinese adults.

Hao Zhao, Wei Gui, Hongjuan Huang, Yue Liu, Hui Ding, Wenyan Fan, Shaoxin Huang, Wanshui Yang, Xin Wang, Guangdi Chen

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of human hypertension, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
3.2field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Correlation between sleep duration and prevalence of hypertension: the China Health and Nutrition Survey.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Sleep status and hypertension: a risk assessment.Sleep & breathing = Schlaf & Atmung · 2021
    Article
  13. Article
  14. Review
  15. Napping in Older Adults: A Review of Current Literature.Current sleep medicine reports · 2020
    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

10 authors at 3 institutions in 1 country.

Hao Zhao *Department of Public Health, and Department of Reproductive Endocrinology of Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Wei Gui *Department of Pediatric, The Affiliated Hospital of Jiujiang University, Jiujiang, China.
Hongjuan HuangDepartment of Pediatric, The Affiliated Hospital of Jiujiang University, Jiujiang, China.
Yue LiuDepartment of Social Medicine and Public Health, School of Basic Medicine, Jiujiang University, Jiujiang, China.
Hui DingDepartment of Social Medicine and Public Health, School of Basic Medicine, Jiujiang University, Jiujiang, China.
Wenyan FanDepartment of Social Medicine and Public Health, School of Basic Medicine, Jiujiang University, Jiujiang, China.
Shaoxin HuangDepartment of Social Medicine and Public Health, School of Basic Medicine, Jiujiang University, Jiujiang, China.
Wanshui YangDepartment of Nutrition, School of Public Health, Anhui Medical University, Hefei, China. wanshuiyang@gmail.com.
Xin WangDepartment of Social Medicine and Public Health, School of Basic Medicine, Jiujiang University, Jiujiang, China. wangxin0072@126.com.
Guangdi ChenDepartment of Public Health, and Department of Reproductive Endocrinology of Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China. chenguangdi@zju.edu.cn.
Jiujiang University · CNWomen's Hospital, School of Medicine, Zhejiang University · CNAnhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Poor sleep has been associated with risk of hypertension, but previous studies were limited by treating one or two sleep factors as predictor. Our previous study has developed a sleep factor questionnaire (SFQ) to comprehensively assess wide range of sleep characteristics including sleep duration, sleep quality, light at night (LAN) exposure, night/shift work, daytime napping, and frequency of nighttime waking, insomnia, and snoring. In this cross-sectional study we used the SFQ to evaluated the associations between these sleep domains and hypertension. Comparing with the subjects who slept 7-8 h, subjects with sleep duration 6-7 h (OR = 1.42, 95% CI: 1.01, 2.00), 8-9 h (OR = 1.60, 95% CI: 1.07, 2.40), and over 9 h (OR = 2.39, 95% CI: 1.60, 3.58) had an increased prevalence of hypertension. The associations were significant among individuals under 45 years sleeping 6-7 h and those over 45 years sleeping over 8 h. The OR of prevalent hypertension was 0.80 (95% CI: 0.62, 0.97) for habitual daytime napping compared with never napping, and the association was also significant among individuals over 45 years old. Moreover, among subjects with sleep duration 7-8 h, habitual daytime napping may decrease prevalent hypertension (OR = 0.635, 95% CI: 0.437, 0.924). In conclusion, our data suggested a positive association between both short (6-7 h) and long sleep duration and hypertension, and a preventive pattern for habitual daytime napping among over 45 years old and hypertension. Moreover, interaction analysis indicated that habitual midday nap may decrease prevalent hypertension among subjects with sleep duration 7-8 h.

Indexed as

HypertensionSleepAdultChinaCross-Sectional StudiesHumansMiddle AgedRisk Factors

Identifiers

PMID31431681
OpenAlexW2969667416

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.