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英国生物银行研究中健康生活方式指数与MRI衍生的身体成分测量之间的关联。

The association between the healthy lifestyle index and MRI-derived body composition measurements in the UK Biobank study.

作者信息

Peila Rita, Rohan Thomas E

机构信息

Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue Belfer, Rm1301, Bronx, NY, 10461, USA.

出版信息

Sci Rep. 2025 Jan 6;15(1):1010. doi: 10.1038/s41598-024-84406-z.

Abstract

A high healthy lifestyle index (HLI) score, which reflects an adequate amount of sleep, no alcohol consumption, no smoking, a moderate to high physical activity level, a high quality diet, and a normal body mass index (BMI), has been associated with reduced risk of morbidity and mortality. We examined the relationship between the HLI and measurements of adipose and lean tissue volumes measured using magnetic resonance imaging (MRI). We studied 33,002 participants in the UK Biobank study, aged 40-69 years at enrolment. Information on lifestyle components was obtained at the baseline examination (2006-2010), while MRI was performed at a later exam (2014-2020). A multilevel HLI score, constructed by assigning individual scores to each HLI component, was categorized into quartiles in multivariable linear regression analyses. Higher HLI levels were associated with lower levels of body composition parameters (visceral and subcutaneous adipose tissue, total adipose tissue, total lean tissue, muscle fat infiltration, abdominal fat ratio, weight to muscle ratio) in a dose-dependent manner (tests-for-trend p-value < 0.001 for all parameters). When BMI was excluded from the HLI score and included separately in the model, a direct association between HLI score and total lean tissue volume was observed. Higher HLI scores were associated with a better body composition profile.

摘要

较高的健康生活方式指数(HLI)得分,反映了充足的睡眠、不饮酒、不吸烟、中等至高体力活动水平、高质量饮食以及正常的体重指数(BMI),与发病率和死亡率风险降低相关。我们研究了HLI与使用磁共振成像(MRI)测量的脂肪组织和瘦组织体积之间的关系。我们在英国生物银行研究中对33002名参与者进行了研究,这些参与者在入组时年龄为40 - 69岁。生活方式组成部分的信息在基线检查(2006 - 2010年)时获取,而MRI在后续检查(2014 - 2020年)时进行。通过为每个HLI组成部分分配个体得分构建的多级HLI得分,在多变量线性回归分析中被分为四分位数。较高的HLI水平与较低水平的身体成分参数(内脏和皮下脂肪组织、总脂肪组织、总瘦组织、肌肉脂肪浸润、腹部脂肪比率、体重与肌肉比率)呈剂量依赖性相关(所有参数的趋势检验p值<0.001)。当BMI从HLI得分中排除并单独纳入模型时,观察到HLI得分与总瘦组织体积之间存在直接关联。较高的HLI得分与更好的身体成分特征相关。

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