Evidence map›Paper›PMID 37898776›Full record

ArticleEuropean journal of medical research2023

HOMA-IR is positively correlated with biological age and advanced aging in the US adult population.

Haifang Yang, Rongpeng Gong, Moli Liu, Ying Deng, Xiaoyu Zheng, Tianyang Hu

Abstract read
In one paragraph

Article in European journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

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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

6 authors.

Haifang Yang *Medical College of Qinghai University, Xining, China.
Rongpeng Gong *Medical College of Qinghai University, Xining, China.
Moli LiuMedical College of Qinghai University, Xining, China.
Ying DengDepartment of Cardiology, The First Branch, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xiaoyu ZhengSchool of Clinical Medicine, Chongqing Medical and Pharmaceutical College, Chongqing, China. zhengxycq@126.com.
Tianyang HuPrecision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China. hutianyang@stu.cqmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInsulin resistance (IR) had been reported to be associated with age; however, few studies have explored the association between IR and biological age (BA). The HOMA-IR value is a useful indicator of the extent of IR. This cross-sectional study is to explore the relationship between HOMA-IR and BA/advanced aging in the US population.

methodsThis study is a cross-sectional analysis of National Health and Nutrition Examination Survey (NHANES) data. The survey comprised 12,266 people from the NHANES, and their full HOMA-IR data as well as BA data were extracted. Four multiple linear regressions were performed to analyze the association between HOMA-IR and BA, and four multiple logistic regression models were performed to analyze the association between HOMA-IR and advanced aging. In addition, trend tests and stratified analysis were performed and smoothed fitted curves were plotted to test the robustness of the results.

resultsHOMA-IR was positively correlated with BA [β: 0.51 (0.39, 0.63)], and it was the same to advanced aging [OR: 1.05 (1.02, 1.07)], and both showed a monotonically increasing trend. The trend tests showed that the results were stable (all P for trend < 0.0001). The smoothed fitted curves showed that there were non-linear relationships between HOMA-IR and BA/advanced aging. And the stratified analysis indicated that the relationship between HOMA-IR and BA/advanced aging remained robust in all subgroups.

conclusionThe study suggested that HOMA-IR is positively correlated with BA and advanced aging in the US adult population, with a monotonic upward trend. This is a new finding to reveal the relationship between HOMA-IR and age from new standpoint of BA rather than chronological age (CA). And it may contribute to a better understanding of human health aging and may aid future research in this field.

Indexed as

Insulin ResistanceAdultAgingCross-Sectional StudiesHumansNutrition SurveysSurveys and QuestionnairesAdvanced agingBiological ageCross-sectional studyHOMA-IRNHANES

Identifiers

PMID37898776
PMCPMC10612177

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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 OpenQuestion graph.