Evidence map›Paper›PMID 40918191›Full record

ArticleFrontiers in cardiovascular medicine2025

Patterns and characteristics of dyslipidemia subtypes among community-dwelling elderly in Eastern China: a cross-sectional study.

Xiaomeng Mi, Suting Xiong, Wenguo Xu, Fang Yao, Jie Huang, Lan Cui, Yu Qin, Jian Su, Wenchao Xu, Ran Tao and 1 more

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xiaomeng Mi *Chronic Non-Communicable Disease Prevention and Control Section, Changzhou Center for Disease Control and Prevention, Changzhou Institute for Advanced Study of Public Health, Nanjing Medical University, Changzhou, China.
Suting Xiong *Chronic Non-Communicable Disease Prevention and Control Section, Changzhou Center for Disease Control and Prevention, Changzhou Institute for Advanced Study of Public Health, Nanjing Medical University, Changzhou, China.
Wenguo XuChronic Non-Communicable Disease Prevention and Control Section, Changzhou Center for Disease Control and Prevention, Changzhou Institute for Advanced Study of Public Health, Nanjing Medical University, Changzhou, China.
Fang YaoChronic Non-Communicable Disease Prevention and Control Section, Changzhou Center for Disease Control and Prevention, Changzhou Institute for Advanced Study of Public Health, Nanjing Medical University, Changzhou, China.
Jie HuangChronic Non-Communicable Disease Prevention and Control Section, Nantong Center for Disease Control and Prevention, Nantong, China.
Lan CuiChronic Non-Communicable Disease Prevention and Control Section, Jiangsu Center for Disease Control and Prevention, Nanjing, China.
Yu QinChronic Non-Communicable Disease Prevention and Control Section, Jiangsu Center for Disease Control and Prevention, Nanjing, China.
Jian SuChronic Non-Communicable Disease Prevention and Control Section, Jiangsu Center for Disease Control and Prevention, Nanjing, China.
Wenchao Xu *Chronic Non-Communicable Disease Prevention and Control Section, Changzhou Center for Disease Control and Prevention, Changzhou Institute for Advanced Study of Public Health, Nanjing Medical University, Changzhou, China.
Ran Tao *Chronic Non-Communicable Disease Prevention and Control Section, Jiangsu Center for Disease Control and Prevention, Nanjing, China.
Jinyi Zhou *Chronic Non-Communicable Disease Prevention and Control Section, Jiangsu Center for Disease Control and Prevention, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Identifying and understanding different dyslipidemia patterns is crucial for maintaining the cardiovascular health of older adults. Therefore, this study aimed to investigate the dyslipidemia profiles of the elderly population from communities in an Eastern Chinese province, focusing on dyslipidemia subtypes and patterns, and exploring the associated demographic and health-related factors. Methods: A cross-sectional survey was conducted in communities in an Eastern Chinese province. Dyslipidemia patterns were defined using 4-digit binary codes for abnormal TC, TG, LDL-C, and HDL-C. Correspondence analysis explored subtype-pattern associations to reveal common combinations. Binary and multinomial logistic regressions, with Bonferroni correction, examined relationships between factors and dyslipidemia patterns. Results: Among 44,304 participants (31.5% dyslipidemia), correspondence analysis delineated patterns across Hyper_TC, Hyper_TG, Hyper_LDL, and Hypo_HDL subtypes, including Hyper_TC/LDL co-occurrence and Hyper_TG/Hypo_HDL independence, varying by gender. Multifactorial analyses revealed gender-based effects of age, education, income, and lifestyle, but consistent risks from comorbidities and urban-rural factors. Dyslipidemia subtype patterns and risk factor associations are thus gender- and pattern-specific. Conclusion: This study provided an in-depth analysis of dyslipidemia subtype patterns among community-dwelling elderly in Eastern China. The findings emphasized that considering gender- and pattern-specific risk factors is crucial in the prevention and management of dyslipidemia among older adults.

Indexed as

community-dwelling elderly Chinesedyslipidemiadyslipidemia patternsdyslipidemia subtypesgender differences

Identifiers

PMID40918191
PMCPMC12411541

What Socratic holds

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LicenceCC BY
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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 Socratic graph.