Impact of Coffee/Green Tea/Soft Drink Consumption on the Risk of Hyperuricemia: A Cross-Sectional Study.


Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
08 07 2021
Historique:
received: 23 05 2021
revised: 06 07 2021
accepted: 06 07 2021
entrez: 24 7 2021
pubmed: 25 7 2021
medline: 13 8 2021
Statut: epublish

Résumé

This cross-sectional study aimed to investigate the association between hyperuricemia and the frequency of coffee, tea, and soft drink consumption, based on data from the Korean Genome and Epidemiology Study (KoGES) (2004-2016). We used the KoGES health examinee data, obtained from urban residents aged ≥ 40 years. Information on the participants' medical history, nutrition (total calorie, protein, fat, and carbohydrate intake), frequency of alcohol consumption, smoking status, household income, and frequency of coffee/green tea/soft drink intake was collected. A logistic regression model was used to analyze the data. Subgroup analyses were performed according to the participant's age and sex. Among 173,209 participants, there were 11,750 and 156,002 individuals with hyperuricemia and non-hyperuricemia controls, respectively. In an adjusted model, frequent coffee and green tea consumption did not increase the risk of hyperuricemia, compared to the "no intake" reference group. However, an adjusted odds ratio of hyperuricemia was 1.23 (95% confidence interval, 1.11-1.35,

Identifiants

pubmed: 34299750
pii: ijerph18147299
doi: 10.3390/ijerph18147299
pmc: PMC8306445
pii:
doi:

Substances chimiques

Coffee 0
Tea 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Joong Seob Lee (JS)

Department of Otorhinolaryngology-Head and Neck Surgery, Hallym University College of Medicine, Anyang 14068, Korea.

Tae Jun Kim (TJ)

Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.

Sung Kwang Hong (SK)

Department of Otorhinolaryngology-Head and Neck Surgery, Hallym University College of Medicine, Anyang 14068, Korea.

Chanyang Min (C)

Hallym Data Science Laboratory, Hallym University College of Medicine, Anyang 14068, Korea.

Dae Myoung Yoo (DM)

Hallym Data Science Laboratory, Hallym University College of Medicine, Anyang 14068, Korea.

Jee Hye Wee (JH)

Department of Otorhinolaryngology-Head and Neck Surgery, Hallym University College of Medicine, Anyang 14068, Korea.

Hyo Geun Choi (HG)

Department of Otorhinolaryngology-Head and Neck Surgery, Hallym University College of Medicine, Anyang 14068, Korea.

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Classifications MeSH