den Braber Niala, Vollenbroek-Hutten Miriam M, Kappert Kilian D R, Laverman Gozewijn D
Biomedical Signal and Systems, University of Twente, Enschede, The Netherlands
Internal Medicine, Ziekenhuisgroep Twente, Almelo, Overijssel, The Netherlands.
BMJ Open. 2024 Dec 3;14(12):e082059. doi: 10.1136/bmjopen-2023-082059.
To analyse variance in accelerometer-based physical activity (PA) measures in patients with type 2 diabetes, identify the most distinctive PA measures and classify patients into different PA clusters based on these measures.
DIAbetes and LifEstyle Cohort Twente (DIALECT), an observational cohort study.
Secondary care in the Netherlands.
253 patients, with three excluded due to insufficient data. The cohort was predominantly male (66%) with an average age of 64.7 years.
The primary outcomes of DIALECT were all-cause mortality, microvascular and macrovascular diseases. The secondary outcomes are blood pressure levels, kidney function indicators and albuminuria levels RESULTS: Principal component analysis (PCA) was applied to 53 accelerometer-derived PA measures. Principal components were identified using a scree plot, key measures determining the principal components were derived and mean cluster analysis was applied to the components. The main PA measures were steps/day, active time, zero steps, total sedentary behaviour (SB) bout duration and total moderate to vigorous physical activity (MVPA) bout duration. Based on three PCA components, three clusters were identified. The inactive cluster had a higher BMI, diabetes duration, age and SB bout duration, and lower steps/day and MVPA bout duration compared with the other clusters (p<0.05). The active cluster still scores low on MVPA bout duration (18 min/week) and high on SB bout duration (5.0 hours/day).
PA behaviour in patients can be categorised into three distinct clusters. The identified PA measures and behaviour clusters offer promising opportunities for tailored lifestyle treatment. However, further studies are needed to determine which PA measures are clinically most relevant, validate the usefulness of this classification and evaluate whether tailoring lifestyle advice according to these clusters adds clinical value.
NTR5855.
分析2型糖尿病患者基于加速度计的身体活动（PA）测量值的差异，确定最具特色的PA测量值，并根据这些测量值将患者分为不同的PA集群。
特温特糖尿病与生活方式队列研究（DIALECT），一项观察性队列研究。
荷兰的二级医疗保健机构。
253名患者，3名因数据不足被排除。该队列主要为男性（66%），平均年龄64.7岁。
DIALECT的主要结局为全因死亡率、微血管和大血管疾病。次要结局为血压水平、肾功能指标和蛋白尿水平。结果：对53项加速度计得出的PA测量值进行主成分分析（PCA）。使用碎石图确定主成分，得出决定主成分的关键测量值，并对这些成分进行均值聚类分析。主要的PA测量值为每日步数、活动时间、零步数、久坐行为（SB）总时长和中度至剧烈身体活动（MVPA）总时长。基于三个PCA成分，确定了三个集群。与其他集群相比，不活动集群的体重指数、糖尿病病程、年龄和SB总时长更高，每日步数和MVPA总时长更低（p<0.05）。活跃集群的MVPA总时长（每周18分钟）仍然较低，SB总时长（每天5.0小时）较高。
患者的PA行为可分为三个不同的集群。确定的PA测量值和行为集群为量身定制的生活方式治疗提供了有希望的机会。然而，需要进一步研究以确定哪些PA测量值在临床上最相关，验证这种分类的有用性，并评估根据这些集群量身定制生活方式建议是否增加临床价值。
NTR5855。
