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采用时依 Cox 回归模型和限制立方样条的健康检查数据 U 型链接与护理需求。

U-shaped link of health checkup data and need for care using a time-dependent cox regression model with a restricted cubic spline.

机构信息

Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, 461-8673, Japan.

Department of Advanced Medicine, Nagoya University Hospital, Nagoya, 466-8560, Japan.

出版信息

Sci Rep. 2023 May 22;13(1):7537. doi: 10.1038/s41598-023-33865-x.

Abstract

We explored risk indicators likely to result in older adults needing certified long-term care in Japan and ascertained whether this relationship forms a U-shaped link. We analyzed a community-based cohort of residents in Kitanagoya City, Aichi Prefecture, Japan. Participants were 3718 individuals aged 65 years and above who underwent health examinations between April 1, 2011 and March 31, 2012. For continuous clinical variables, we applied a time-dependent Cox regression model. Two types of models were applied-a linear and nonlinear model with restricted cubic splines-to assess the U-shaped association. Statistical significance (set at 0.05) for the nonlinearity was tested by comparing the spline and linear models. Among the participants, 701 were certified as needing Level 1 care or higher during a follow-up. Among the continuous clinical variables, the nonlinear model for body mass index, systolic blood pressure, high-density lipoprotein cholesterol, alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transpeptidase revealed significant U-shaped associations as compared with the linear model in which the outcome was a certification of the need for nursing care. These results provide an important insight into the usefulness of nonlinear models for predicting the risk of such certification.

摘要

我们探索了可能导致日本老年人需要认证的长期护理的风险指标,并确定了这种关系是否形成 U 型关联。我们分析了日本爱知县北名古屋市的一个基于社区的居民队列。参与者为 3718 名年龄在 65 岁及以上的人,他们在 2011 年 4 月 1 日至 2012 年 3 月 31 日期间接受了健康检查。对于连续的临床变量,我们应用了时间依赖性 Cox 回归模型。我们应用了两种类型的模型-线性和非线性模型与限制立方样条-来评估 U 型关联。通过比较样条和线性模型来检验非线性的统计学意义(设定为 0.05)。在参与者中,有 701 人在随访期间被认证为需要 1 级或更高水平的护理。在连续的临床变量中,与线性模型相比,非线性模型对于体重指数、收缩压、高密度脂蛋白胆固醇、丙氨酸氨基转移酶、天冬氨酸氨基转移酶和γ-谷氨酰转肽酶的结果呈现出显著的 U 型关联,提示需要护理认证。这些结果为预测此类认证风险的非线性模型的有用性提供了重要的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a57f/10203122/97e9c73c2dff/41598_2023_33865_Fig1_HTML.jpg

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