Evidence map›Paper›PMID 38420444›Full record

ArticleHeliyon2024

Association between a body shape index and Parkinson's disease: A large cross-sectional study from NHANES.

Wei Huang, Yingqi Xiao, Li Zhang, Hu Liu

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. The obesity pandemic and its impact on non-communicable disease burden.Pflugers Archiv : European journal of physiology · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
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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

4 authors.

Wei HuangDepartment of Orthopaedics, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, China.
Yingqi XiaoDepartment of Pulmonary and Critical Care Medicine, Dongguan Tungwah Hospital, Dongguan, China.
Li ZhangDepartment of Pulmonary and Critical Care Medicine, Dongguan Tungwah Hospital, Dongguan, China.
Hu LiuDepartment of Orthopaedics, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To further evaluate the connection between obesity and Parkinson's disease, we utilized A body shape index which normalizes waist circumference for Body mass index. Derived from the National Health and Nutrition Examination Survey. Methods: Based on National Health and Nutrition Examination Survey data from 2005 to 2018, this study included 31,933 adult participants in total. First, all the participants were divided into the Parkinson's disease group and non-Parkinson's disease group, respectively. Next, according to their quartiles of A body shape index levels, they were further classified into Q1 group (0.058-0.077), Q2 group (0.078-0.081), Q3 group (0.082-0.084), and Q4 group (0.085-0.117). A body shape index was the primary exposure, while Parkinson's disease was the primary outcome. A body shape index is defined by waist circumference divided by Body mass index Results: According to the unadjusted multivariate logistic analysis, the Q4 group had a greater likelihood of acquiring Parkinson's disease than the Q1 group [OR = 4.519, 95% CI: 3.094-6.600; Conclusions: There is a non-linear positive correlation between the adult A body shape index and the risk of Parkinson's disease. Adults are at a greater risk of getting Parkinson's disease as A body shape index rises, and the link is particularly strong among men aged 20 to 59.

Indexed as

A body shape indexCross-sectional studyNational health and nutrition examination surveyParkinson's disease

Identifiers

PMID38420444
PMCPMC10900994

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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.