Evidence map›Paper›PMID 39741514›Full record

ArticleFrontiers in medicine2024

Analyzing lipid profiles and dyslipidemia prevalence in hypertensive patients: a cross-sectional study from primary community health institutions.

Wenxin Wang, Xinmin Li, Deliang Lv, Xiaobing Wu, Fengzhu Xie, Wei Xie, Jinxiao Wang, Zhiguang Zhao

Abstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Effects of aged black garlic (ABG10+Frontiers in nutrition · 2026
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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

8 authors.

Wenxin Wang *School of Public Health/Institute of Local Government Development, Shantou University, Shan-Tou, China.
Xinmin LiSchool of Public Health, Shantou University, Shan-Tou, China.
Deliang Lv *Shenzhen Center for Chronic Disease Control, Shenzhen, China.
Xiaobing WuShenzhen Center for Chronic Disease Control, Shenzhen, China.
Fengzhu XieShenzhen Center for Chronic Disease Control, Shenzhen, China.
Wei XieShenzhen Center for Chronic Disease Control, Shenzhen, China.
Jinxiao WangSchool of Public Health, Shantou University, Shan-Tou, China.
Zhiguang ZhaoShenzhen Center for Chronic Disease Control, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: A significant proportion of hypertensive patients also suffer from comorbid dyslipidemia, which critically influences their treatment outcomes and overall prognosis. Given its implications, the lipid profiles of hypertensive individuals warrant increased attention for more effective clinical management. Methods: We analyzed data from 92,443 hypertensive patients registered at primary community health institutions in 2021. Employing a cross-sectional study design, we assessed the distribution of lipid levels and the prevalence of various dyslipidemia subtypes. Stepwise forward logistic regression was used to identify factors associated with dyslipidemia, adjusting for gender, age, body size, and other relevant characteristics. Results: According to the 2023 Chinese Guidelines for the Management of Lipids, the overall prevalence of dyslipidemia was 37.5%. Subtype analysis revealed prevalence of high total cholesterol (TC) at 11.2%, high triglycerides (TG) at 16.0%, low high-density lipoprotein cholesterol (HDL-C) at 16.0%, and high low-density lipoprotein cholesterol (LDL-C) at 10.2%. TG abnormalities were more common among males (16.8%), whereas TC abnormalities predominated in females (14.4%). Notably, hypertensive patients with diabetes had higher levels of TG compared to non-diabetics ( Conclusion: Our study underscores the necessity of rigorous lipid monitoring and analysis of dyslipidemia-influencing factors for the development of effective health management strategies within the community. There is a critical need to examine lipid profiles comprehensively and implement targeted therapeutic interventions aimed at managing hyperlipidemia, a modifiable risk factor for cardiovascular disease.

Indexed as

associated factorsdyslipidemiadyslipidemia componentepidemiologylipid levelprevalence

Identifiers

PMID39741514
PMCPMC11685003

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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.