Evidence map›Paper›PMID 36523597›Full record

ArticleFrontiers in endocrinology2022

Association of geriatric nutritional risk index with the risk of osteoporosis in the elderly population in the NHANES.

Wei Huang, Yingqi Xiao, Hongwei Wang, Kaixiang Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
9.9field-weighted citation impact, top 1% of its field
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

46 citing papers in PubMed, 58 citations in OpenAlex.

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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 at 1 institution in 1 country.

Wei HuangDepartment of Orthopaedics, Dongguan Tungwah Hospital, Dongguan, China.
Yingqi XiaoDepartment of Pulmonary and Critical Care Medicine, Dongguan Tungwah Hospital, Dongguan, China.
Hongwei WangDepartment of Orthopaedics, Dongguan Tungwah Hospital, Dongguan, China.
Kaixiang LiDepartment of Orthopaedics, Dongguan Tungwah Hospital, Dongguan, China.
Tung Wah Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Osteoporosis is common in the elderly, and malnutrition is considered a major risk factor for osteoporosis. This study investigated the relationship between the Geriatric Nutrition Risk Index (GNRI) and osteoporosis based on a large cross-sectional study of the National Health and Nutrition Examination Survey (NHANES). Methods: We included 7405 older adults from NHANES (2005 to 2018) and divided them into the High-GNRI and Low-GNRI groups based on GNRI levels to compare the prevalence of osteoporosis among the two groups. A multi-factor logistic regression analysis was used to determine whether GNRI was an independent risk factor for osteoporosis. Spearman's rank correlation coefficient was computed to investigate the linear relationship between geriatric nutritional risk index (GNRI) and bone mineral density (BMD) T-score. Finally, a generalized additive model (GAM) revealed whether there was a non-linear relationship between GNRI and osteoporosis. Results: The prevalence of osteoporosis was higher in the Low-GNRI group than those in the High-GNRI group (12.2% vs. 8.2%; Conclusion: GNRI is an independent risk factor for osteoporosis in the elderly and is negatively and non-linearly associated with the risk of osteoporosis in the elderly population.

Indexed as

MalnutritionOsteoporosisAgedCross-Sectional StudiesGeriatric AssessmentHumansNutrition Surveysgeriatric nutritional risk indexNHANESolder adultsosteoporosisrisk factors

Identifiers

PMID36523597
PMCPMC9744963
OpenAlexW4310168479

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.