Evidence map›Paper›PMID 39223616›Full record

ArticleLipids in health and disease2024

10-year trajectory of Life's Essential 8 and incident hypertension: a community-based cohort study.

Jiwen Zhong, Jinguo Jiang, Liang Guo, Yang Liu, Shouling Wu, Xinyi Peng, Shuohua Chen, Xueying Qin, Shaohong Dong, Ruijun Huang and 1 more

Abstract read
In one paragraph

Article in Lipids in health and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Jiwen Zhong *Department of Critical Care Medicine, Zhuhai People's Hospital (Zhuhai Clinical Medical College of Jinan University), Zhuhai, 51900, Guangdong, China.
Jinguo Jiang *Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical University, Shenyang, Liaoning, China.
Liang GuoDepartment of Cardiology, Renmin Hospital of Wuhan University, 430060, Wuchang, Wuhan, China.
Yang LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38# Xueyuan Road, Haidian District, 100191, Beijing, China.
Shouling WuDepartment of Cardiology, Kailuan General Hospital, No.57 Xinhua East Road, 063000, Tangshan, Hebei Province, China.
Xinyi PengHypertension Center, State Key Laboratory of Cardiovascular Disease of China, National Center for Cardiovascular Diseases of China, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100037, Beijing, China.
Shuohua ChenDepartment of Cardiology, Kailuan General Hospital, No.57 Xinhua East Road, 063000, Tangshan, Hebei Province, China.
Xueying QinDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38# Xueyuan Road, Haidian District, 100191, Beijing, China.
Shaohong DongDepartment of Cardiology, Shenzhen Cardiovascular Minimally Invasive Medical Engineering Technology Research and Development Center, The Second Clinical Medical College, The First Affiliated Hospital, Shenzhen People's Hospital, Jinan University, Southern University of Science and Technology), 518020, Shenzhen, Guangdong, China.
Ruijun HuangDepartment of Critical Care Medicine, Zhuhai People's Hospital (Zhuhai Clinical Medical College of Jinan University), Zhuhai, 51900, Guangdong, China. laizahuang@163.com.
Wei ZhengDepartment of Critical Care Medicine, Zhuhai People's Hospital (Zhuhai Clinical Medical College of Jinan University), Zhuhai, 51900, Guangdong, China. zhzhengwei@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe health effects of Life's Essential 8 (LE8) on chronic diseases have been disclosed, but its association with hypertension remains unknown. The current study aimed to explore the potential link between 10-year LE8 trajectory and the incidence of hypertension.

methodsLE8 was constructed from four behaviors and four metabolic factors, ranging from 0 to 100. Latent mixture models were used to identify trajectories of LE8 scores during 2006 to 2016. Incident hypertension was diagnosed based on self-reported clinical diagnoses and physical examinations from 2016 to 2020. Cox models were employed to assess the association of LE8 trajectories with hypertension. In addition to incorporating the mean hs-CRP levels from 2006 to 2016, age, sex, monthly income, educational level, and occupation at recruitment were adjusted for as confounding factors.

results7500 participants aged 40.28 ± 10.35 years were included in the study, of whom 2907 (38.76%) were women. Five LE8 trajectory patterns were identified. After around four-year follow-up, 667 hypertension events were observed. Compared to the Low-Stable trajectory, the hazard ratios and 95% confidence intervals for the Moderate-Increasing, Moderate-Decreasing, Moderate-Stable, and High-Stable trajectories were 0.51 (0.40, 0.65), 0.81 (0.64, 1.02), 0.45 (0.36, 0.58), 0.23 (0.16, 0.33), respectively. The risk of incident hypertension decreased as participants improved their LE8 status. The robustness of the primary results was confirmed through several sensitivity analyses.

conclusionsLE8 trajectories were associated with the incident hypertension. People who improved their LE8 scores over time experienced a decreased risk of hypertension, even if they started with lower LE8 scores initially.

Indexed as

HypertensionAdultCohort StudiesFemaleHumansIncidenceMaleMiddle AgedProportional Hazards ModelsRisk FactorsHypertensionLife’s essential 8Trajectory analysis

Identifiers

PMID39223616
PMCPMC11368014

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.