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Obesity, metabolic dysfunction, and risk of kidney stone disease: a national cross-sectional study.
Ye, Zhenyang; Wu, Changjing; Xiong, Yang; Zhang, Fuxun; Luo, Jinyang; Xu, Lijing; Wang, Jia; Bai, Yunjin.
Afiliação
  • Ye Z; Department of Urology, West China Xiamen Hospital of Sichuan University, Xiamen, P.R. China.
  • Wu C; Department of Urology, West China Hospital, Sichuan University, Chengdu, P.R. China.
  • Xiong Y; Andrology Laboratory, West China Hospital, Sichuan University, Chengdu, P.R. China.
  • Zhang F; Department of Urology, West China Hospital, Sichuan University, Chengdu, P.R. China.
  • Luo J; Andrology Laboratory, West China Hospital, Sichuan University, Chengdu, P.R. China.
  • Xu L; Department of Urology, West China Hospital, Sichuan University, Chengdu, P.R. China.
  • Wang J; Andrology Laboratory, West China Hospital, Sichuan University, Chengdu, P.R. China.
  • Bai Y; Department of Urology, West China Xiamen Hospital of Sichuan University, Xiamen, P.R. China.
Aging Male ; 26(1): 2195932, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37038659
ABSTRACT

BACKGROUND:

This study aimed to investigate the association between different metabolic syndrome-body mass index (MetS-BMI) phenotypes and the risk of kidney stones. MATERIALS AND

METHODS:

Participants aged 20-80 years from six consecutive cycles of the NHANES 2007-2018 were included in this study. According to their MetS status and BMI, the included participants were allocated into six mutually exclusive groups metabolically healthy normal weight (MHN)/overweight (MHOW)/obesity (MHO) and metabolically unhealthy normal weight (MUN)/overweight (MUOW)/obesity (MUO). To explore the association between MetS-BMI phenotypes and the risk of kidney stones, binary logistic regression was used to determine the odds ratios (ORs).

RESULTS:

A total of 13,589 participants were included. It was revealed that all the phenotypes with obesity displayed higher risks of kidney stones (OR = 1.38, p < 0.01 for MHO & OR = 1.80, p < 0.001 for MUO, in the fully adjusted model). The risk increased significantly when metabolic dysfunction coexisted with overweight and obesity (OR = 1.39, p < 0.05 for MUOW & OR = 1.80, p < 0.001 for MUO, in the fully adjusted model). Of note, the ORs for the MUO and MUOW groups were higher than those for the MHO and MHOW groups, respectively.

CONCLUSIONS:

Obesity and unhealthy metabolic status can jointly increase the risk of kidney stones. Assessing the metabolic status of all individuals may be beneficial for preventing kidney stones.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cálculos Renais / Síndrome Metabólica / Obesidade Tipo de estudo: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cálculos Renais / Síndrome Metabólica / Obesidade Tipo de estudo: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2023 Tipo de documento: Article