Association between body fat variation rate and risk of diabetic nephropathy - a posthoc analysis based on ACCORD database

医学 生物统计学 糖尿病 流行病学 肾病 环境卫生 内科学 数据库 内分泌学 计算机科学
作者
Shuai Li,Lin Li,Xiaoyue Chen,Siyu Liu,Ming Gao,Xunjie Cheng,Chuanchang Li
出处
期刊:BMC Public Health [BioMed Central]
卷期号:24 (1)
标识
DOI:10.1186/s12889-024-20317-y
摘要

Weight control has consistently been regarded as a significant preventive measure against diabetic nephropathy. however, the potential impact of substantial fluctuations in body fat during this process on the risk of diabetic nephropathy remains uncertain. This study aimed to investigate the association between body fat variation rate and diabetic nephropathy incident in American patients with type 2 diabetes. The study used data from the Action to Control Cardiovascular Risk in diabetes (ACCORD) trial to calculate body fat variation rates over two years and divided participants into Low and High groups. The hazard ratio and 95% confidence interval were estimated using a Cox proportional hazards model, and confounding variables were addressed using propensity score matching. Four thousand six hundred nine participants with type 2 diabetes were studied, with 1,511 cases of diabetic nephropathy observed over 5 years. High body fat variation rate was linked to a higher risk of diabetic nephropathy compared to low body fat variation rate (HR 1.13, 95% CI 1.01–1.26). Statistically significant interaction was observed between body fat variation rate and BMI (P interaction = 0.008), and high level of body fat variation rate was only associated with increased risk of diabetic nephropathy in participants with BMI > 30 (HR 1.34 and 95% CI 1.08–1.66). Among participants with Type 2 Diabetes Mellitus, body fat variation rate was associated with increased risk of diabetic nephropathy. Furthermore, the association was modified by BMI, and positive association was demonstrated in obese but not non-obese individuals. Consequently, for obese patients with diabetes, a more gradual weight loss strategy is recommended to prevent drastic fluctuations in body fat. Clinical Trials. gov, no. NCT000000620 (Registration Date 199909).

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
YTT发布了新的文献求助10
1秒前
APTX4869完成签到,获得积分10
1秒前
大知闲闲应助科研通管家采纳,获得10
1秒前
orixero应助科研通管家采纳,获得30
1秒前
cdercder应助科研通管家采纳,获得20
1秒前
orixero应助breeze采纳,获得10
2秒前
田様应助科研通管家采纳,获得10
2秒前
2秒前
顾矜应助沐泫采纳,获得10
2秒前
2秒前
我是老大应助科研通管家采纳,获得10
2秒前
2秒前
cdercder应助科研通管家采纳,获得10
2秒前
传奇3应助科研通管家采纳,获得10
3秒前
今后应助科研通管家采纳,获得10
3秒前
xuxu213发布了新的文献求助10
3秒前
4秒前
5秒前
5秒前
王琰完成签到,获得积分20
6秒前
沃耀珐艺区完成签到,获得积分10
6秒前
oqhg完成签到,获得积分10
8秒前
8秒前
墨曦发布了新的文献求助10
8秒前
今后应助辛夷采纳,获得10
9秒前
111发布了新的文献求助10
9秒前
上官若男应助酷炫的海云采纳,获得10
9秒前
gj发布了新的文献求助10
9秒前
csu化学人发布了新的文献求助10
10秒前
忧夏完成签到,获得积分10
10秒前
@@发布了新的文献求助10
10秒前
曾经不言发布了新的文献求助10
10秒前
12秒前
Sg完成签到,获得积分10
12秒前
12秒前
哈哈哈哈哈完成签到,获得积分10
14秒前
xh发布了新的文献求助10
15秒前
靓丽的如冬应助yang采纳,获得10
16秒前
17秒前
18秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Analytical Separation Science 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7548092
求助须知:如何正确求助?哪些是违规求助? 9131477
关于积分的说明 19510393
捐赠科研通 7141676
什么是DOI,文献DOI怎么找? 3259762
关于科研通互助平台的介绍 2426508
邀请新用户注册赠送积分活动 2248407