Gender-specific effects of oxidative balance score on the prevalence of diabetes in the US population from NHANES

Frontiers in Endocrinology

Endocrinology

Chenxia Ren¹  Cuiling Wu²  Xin Pang²  Lianyun Zhang²  Huifang Gao²  Yingda Song³ 

[1] Central Laboratory, Changzhi Medical College, Changzhi, China;Department of Biochemistry, Changzhi Medical College, Changzhi, China;Department of Thoracic Surgery, Shanxi Provincial People’s Hospital, Taiyuan, China;Fifth Clinical Medical College, Shanxi Medical University, Taiyuan, China;

关键词: oxidative balance score;    gender;    diabetes;    cross-sectional study;    adults;   

DOI  :  10.3389/fendo.2023.1148417

 received in 2023-01-20, accepted in 2023-03-28,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundThe relationship between oxidative balance score (OBS) and diabetes remains poorly understood and may be gender-specific. We conducted a cross-sectional study to investigate the complex association between OBS and diabetes among US adults.MethodsOverall, 5,233 participants were included in this cross-sectional study. The exposure variable was OBS, composed of scores for 20 dietary and lifestyle factors. Multivariable logistic regression, subgroup analysis, and restricted cubic spline (RCS) regression were applied to examine the relationship between OBS and diabetes.ResultsCompared to the lowest OBS quartile group (Q1), the multivariable-adjusted odds ratio (OR) (95% confidence interval (CI) for the highest OBS quartile group (Q4) was 0.602 (0.372–0.974) (p for trend = 0.007), and for the highest lifestyle, the OBS quartile group was 0.386 (0.223–0.667) (p for trend < 0.001). Moreover, gender effects were found between OBS and diabetes (p for interaction = 0.044). RCS showed an inverted-U relationship between OBS and diabetes in women (p for non-linear = 6e−04) and a linear relationship between OBS and diabetes in men.ConclusionsIn summary, high OBS was negatively associated with diabetes risk in a gender-dependent manner.

【 授权许可】

Unknown   
Copyright © 2023 Wu, Ren, Song, Gao, Pang and Zhang