Life-course body size trajectories and the progression of cardio-renal-metabolic multimorbidity: a prospective UK biobank study.

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2026-06-04 DOI:10.1186/s12986-026-01148-7

Jingjing Lang, Zhongyang Guan, Lili Li, Lu Jiang, Guanghui Mao, Guochong Chen, Mario Siervo, Xiaoyan Shi

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引用次数: 0

Abstract

Background: The influence of life-course body size on the progression of cardio-renal-metabolic multimorbidity (CRMM) is insufficiently understood.

Methods: We included 398,491 UK Biobank participants. Childhood-to-adulthood body size trajectories were defined using recalled childhood somatotype and adult body mass index (BMI). Multi-state models evaluated transition-specific hazards, state-occupation probabilities, and expected length of stay (ELOS) across body size trajectories. Progression was represented as a comorbidity-count pathway (healthy, first/double/triple CRMM, and death) and a comorbidity-pattern pathway specifying the entry disease and comorbidities among cardiovascular disease (CVD), type 2 diabetes (T2D), and chronic kidney disease (CKD). Subgroup and interaction analyses evaluated joint effects of trajectory and Life's Essential 4 (LE4). Mediation by the C-reactive protein-triglyceride-glucose index (CTI) was assessed.

Results: Trajectories culminating in obesity were associated with higher hazards along the comorbidity-count pathway and shorter healthy time (ELOS 13.08 vs. 10.59 years for Average-to-normal vs Thinner-to-obesity). Comorbidity-pattern analyses identified T2D-containing comorbidities (T2D-CKD, T2D-CVD) as hubs toward CRMM. Compared with the Average-to-normal group, hazard ratios (HRs) were highest when the destination included T2D: CVD to T2D-CVD, 3.24 (Plumper-to-obesity), and 3.85 (Thinner-to-obesity); CKD to T2D-CKD, 2.66 (Plumper-to-obesity) and 4.03 (Thinner-to-obesity). Moving from LE4-low to LE4-high attenuated the risks of CRMM associated with progressive or persistent obesity trajectories by 26.8-37.8%. CTI mediated approximately 42-54% of the associations between sustained or progressive obesity trajectories and CRMM comorbidity outcomes.

Conclusions: Progressive or persistent obesity trajectories were associated with higher CRMM progression hazards. Early adiposity prevention and sustained lifestyle improvement may slow this progression. Integrating body size trajectory and lifestyle factors with metabolic inflammation indicators may strengthen risk stratification.

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生命过程体型轨迹和心脏-肾脏-代谢多病的进展：一项前瞻性英国生物库研究。

背景：一生体型对心肾代谢多病（CRMM）进展的影响尚不清楚。方法：我们纳入了398,491名英国生物银行参与者。童年到成年的体型轨迹是通过回忆童年体型和成年体重指数（BMI）来定义的。多状态模型评估了过渡特定的危害，状态-职业概率，以及身体尺寸轨迹上的预期停留时间（ELOS）。进展表现为合并症计数途径（健康，第一次/两次/三重CRMM和死亡）和合并症模式途径，指定心血管疾病（CVD）， 2型糖尿病（T2D）和慢性肾脏疾病（CKD）的进入疾病和合并症。亚组分析和相互作用分析评估了轨迹和生命基本4 （LE4）的联合效应。评估c反应蛋白-甘油三酯-葡萄糖指数（CTI）的中介作用。结果：最终导致肥胖的轨迹与合并症计数途径上的高风险和较短的健康时间相关（平均到正常和较瘦到肥胖的ELOS分别为13.08年和10.59年）。合并症模式分析确定t2dm合并症（T2D-CKD, T2D-CVD）是CRMM的枢纽。与平均到正常组相比，当目的地包括T2D: CVD到T2D-CVD， 3.24（肥胖）和3.85（肥胖）时，风险比（hr）最高；CKD与T2D-CKD的比值为2.66（偏胖到肥胖）和4.03（偏瘦到肥胖）。从le4低到le4高，与进行性或持续性肥胖轨迹相关的CRMM风险降低了26.8-37.8%。CTI介导了持续或进行性肥胖轨迹与CRMM合并症结果之间约42-54%的关联。结论：进行性或持续性肥胖轨迹与更高的CRMM进展风险相关。早期预防肥胖和持续改善生活方式可能会减缓这一进程。将体型轨迹和生活方式因素与代谢性炎症指标相结合，可加强风险分层。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nutrition & Metabolism 医学-营养学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.