Evidence map›Paper›PMID 39346649›Full record

ArticleFrontiers in nutrition2024

Association between weight-adjusted-waist index and gynecologic cancers: a population-based study.

Liyuan Fang, Xiaotong Li, Yuhang Fang, Yan Wang, Runxi Wang, Yi Xie, Ying Zhang

Abstract read
In one paragraph

Article in Frontiers in nutrition, 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. Observational
  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

7 authors.

Liyuan FangDepartment of Oncology, Guang'anmen Hospital of the Chinese Academy of Traditional Chinese Medicine, Beijing, China.
Xiaotong LiDepartment of Surgery, Shanghai University of Traditional Chinese Medicine Affiliated Putuo Central Hospital, Shanghai, China.
Yuhang FangBeijing University of Chinese Medicine, Beijing, China.
Yan WangDepartment of Oncology, Guang'anmen Hospital of the Chinese Academy of Traditional Chinese Medicine, Beijing, China.
Runxi WangDepartment of Oncology, Guang'anmen Hospital of the Chinese Academy of Traditional Chinese Medicine, Beijing, China.
Yi XieBeijing University of Chinese Medicine, Beijing, China.
Ying ZhangDepartment of Oncology, Guang'anmen Hospital of the Chinese Academy of Traditional Chinese Medicine, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to analyze the association between the weight-adjusted waist index (WWI) and the risk of gynecologic cancers, using data collected from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016. Methods: We employed multiple logistic regression analysis to investigate the relationship between WWI and risk of gynecologic cancers. Subsequent subgroup analyses were performed on specific populations of interest. A restricted cubic spline model was used to explore potential non-linear relationships. Additionally, the effectiveness of WWI in predicting sarcopenia was assessed through Receiver Operating Characteristic (ROC) curve analysis. K-fold cross-validation was applied for model assessment. Results: Among the 4,144 participants, 98 self-reported having gynecologic cancers. In the fully adjusted model, WWI was significantly associated with the prevalence of gynecologic cancers (OR = 1.38, 95% CI: 1.02-1.88, Conclusion: Elevated levels of WWI were significantly associated with an increased risk of gynecologic cancers in American women, displaying a stronger association than other obesity markers. Therefore, WWI may serve as a distinct and valuable biomarker for assessing the risk of gynecologic cancers, particularly cervical and endometrial cancers.

Indexed as

gynecologic cancersNHANESnon-linearobesityweight-adjusted-waist index

Identifiers

PMID39346649
PMCPMC11437532

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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.