Evidence map›Paper›PMID 35932038›Full record

ArticleBMC endocrine disorders2022

Correlation of obesity, dietary patterns, and blood pressure with uric acid: data from the NHANES 2017-2018.

Jia Yao, Yuan Zhang, Jia Zhao, Yu-Ping Lin, Qi-Yun Lu, Guan-Jie Fan

Open access · goldAbstract read
In one paragraph

Article in BMC endocrine disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 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

6 authors at 1 institution in 1 country.

Jia Yao *School of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
Yuan Zhang *School of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
Jia ZhaoSchool of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
Yu-Ping LinDepartment of Endocrinology, Guangdong Provincial Hospital of Chinese Medicine, 111 Dade Road, Yuexiu District, Guangzhou, 510120, China.
Qi-Yun LuDepartment of Endocrinology, Guangdong Provincial Hospital of Chinese Medicine, 111 Dade Road, Yuexiu District, Guangzhou, 510120, China.
Guan-Jie FanDepartment of Endocrinology, Guangdong Provincial Hospital of Chinese Medicine, 111 Dade Road, Yuexiu District, Guangzhou, 510120, China. fanguanjiegz@163.com.
Guangzhou University of Chinese Medicine · CN

Funding

Guangdong Provincial Hospital of Traditional Chinese Medicine No. 2021DB02the Chinese Government, the Ministry of Science, and Technology of the People's Republic of China through the National Science and Technology Support Program No. 2015BAI04B09
6 · The paper itself

Abstract

backgroundPrevalence rates of hyperuricemia and gout are increasing. Clinical investigations of hyperuricemia-related risk factors aid in the early detection, prevention, and management of hyperuricemia and gout. Ongoing research is examining the association of obesity, dietary patterns, and blood pressure (BP) with serum uric acid (sUA).

methodsA cross-sectional study was conducted based on the National Health and Nutrition Examination Survey. The exposures included body mass index (BMI), dietary patterns, and BP. The outcome variable was sUA level. The weighted multivariate linear regression models and smooth curve fittings were used to assess the association of BMI, dietary patterns, and BP with sUA.

resultsThere was a significantly positive correlation between BMI and sUA (β = 0.059, 95% CI: 0.054 to 0.064, P < 0.00001). Overweight and obese individuals had higher sUA levels than those with the normal BMI (β = 0.451, 95% CI: 0.357 to 0.546, P < 0.00001; β = 0.853, 95% CI: 0.760 to 0.946, P < 0.00001; respectively). Dietary energy intake was positively correlated with sUA (β = 0.000, 95% CI: 0.000 to 0.000, P = 0.01057). Dietary intake of carbohydrate and fiber were negatively correlated with sUA (β = - 0.001, 95% CI: - 0.002 to - 0.000, P < 0.00001; β = - 0.008, 95% CI: - 0.011 to - 0.004, P = 0.00001; respectively). Moreover, systolic BP was positively correlated with sUA (β = 0.006, 95% CI: 0.003 to 0.009, P = 0.00002). However, no statistical differences were found about the associations of dietary intake of total sugars, protein, total fat, cholesterol, and diastolic BP with sUA.

conclusionsThe current cross-sectional investigation of a nationally representative sample of US participants showed that BMI, dietary energy intake, and systolic BP were positively correlated with sUA levels; dietary carbohydrate and fiber intake were negatively correlated with sUA levels. The findings might be helpful for the management and treatment of hyperuricemia and gout.

Indexed as

GoutHyperuricemiaBlood PressureCross-Sectional StudiesHumansNutrition SurveysObesityRisk FactorsUric AcidUric AcidBlood pressureDietNHANESObesityUric acid

Identifiers

PMID35932038
PMCPMC9354319
OpenAlexW4289889113

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.