Li Wanlu, Wen Chi Pang, Li Wenyuan, Ying Zhijun, Pan Sai, Li Yizhan, Zhu Zecheng, Yang Min, Tu Huakang, Guo Yi, Song Zhenya, Chu David Ta-Wei, Wu Xifeng
Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
National Institute for Data Science in Health and Medicine, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, Zhejiang, China.
Diabetol Metab Syndr. 2023 Aug 13;15(1):169. doi: 10.1186/s13098-023-01146-2.
Higher fasting plasma glucose (FPG) levels were associated with an increased risk of all-cause mortality; however, the associations between long-term FPG trajectory groups and mortality were unclear, especially among individuals with a normal FPG level at the beginning. The aims of this study were to examine the associations of FPG trajectories with the risk of mortality and identify modifiable lifestyle factors related to these trajectories.
We enrolled 50,919 individuals aged ≥ 20 years old, who were free of diabetes at baseline, in the prospective MJ cohort. All participants completed at least four FPG measurements within 6 years after enrollment and were followed until December 2011. FPG trajectories were identified by group-based trajectory modeling. We used Cox proportional hazards models to examine the associations of FPG trajectories with mortality, adjusting for age, sex, marital status, education level, occupation, smoking, drinking, physical activity, body mass index, baseline FPG, hypertension, dyslipidemia, cardiovascular disease or stroke, and cancer. Associations between baseline lifestyle factors and FPG trajectories were evaluated using multinomial logistic regression.
We identified three FPG trajectories as stable (n = 32,481), low-increasing (n = 17,164), and high-increasing (n = 1274). Compared to the stable group, both the low-increasing and high-increasing groups had higher risks of all-cause mortality (hazard ratio (HR) = 1.18 (95% CI 0.99-1.40) and 1.52 (95% CI 1.09-2.13), respectively), especially among those with hypertension. Compared to participants with 0 to 1 healthy lifestyle factor, those with 6 healthy lifestyle factors were more likely to be in the stable group (OR = 0.61, 95% CI 0.51-0.73; OR = 0.20, 95% CI 0.13-0.32).
Individuals with longitudinally increasing FPG had a higher risk of mortality even if they had a normal FPG at baseline. Adopting healthy lifestyles may prevent individuals from transitioning into increasing trajectories.
空腹血糖(FPG)水平升高与全因死亡风险增加相关;然而,长期FPG轨迹组与死亡率之间的关联尚不清楚,尤其是在初始FPG水平正常的个体中。本研究的目的是探讨FPG轨迹与死亡风险的关联,并确定与这些轨迹相关的可改变生活方式因素。
我们在MJ前瞻性队列中纳入了50919名年龄≥20岁、基线时无糖尿病的个体。所有参与者在入组后6年内至少完成了4次FPG测量,并随访至2011年12月。通过基于组的轨迹模型确定FPG轨迹。我们使用Cox比例风险模型来检验FPG轨迹与死亡率的关联,并对年龄、性别、婚姻状况、教育水平、职业、吸烟、饮酒、身体活动、体重指数、基线FPG、高血压、血脂异常、心血管疾病或中风以及癌症进行了调整。使用多项逻辑回归评估基线生活方式因素与FPG轨迹之间的关联。
我们确定了三种FPG轨迹,分别为稳定型(n = 32481)、低增长型(n = 17164)和高增长型(n = 1274)。与稳定组相比,低增长组和高增长组的全因死亡风险均较高(风险比(HR)分别为1.18(95%置信区间0.99 - 1.40)和1.52(95%置信区间1.09 - 2.13)),尤其是在高血压患者中。与具有0至1个健康生活方式因素的参与者相比,具有6个健康生活方式因素的参与者更有可能处于稳定组(优势比(OR)= 0.61,95%置信区间0.51 - 0.73;OR = 0.20,95%置信区间0.13 - 0.32)。
即使基线FPG正常,但FPG呈纵向升高的个体死亡风险更高。采用健康的生活方式可能会阻止个体转变为升高轨迹。