Associations of multiple metals with bone mineral density: A population-based study in US adults

骨矿物 全国健康与营养检查调查 电感耦合等离子体质谱法 百分位 线性回归 人口 体质指数 Mercury(编程语言) 环境化学 环境卫生 动物科学 化学 质谱法 医学 骨质疏松症 内分泌学 色谱法 数学 统计 有机化学 程序设计语言 生物 计算机科学 机器学习
作者
Muhong Wei,Yuan Cui,Hao‐Long Zhou,Wenjing Song,Dongsheng Di,Ruyi Zhang,Qin Huang,Junan Liu,Qi Wang
出处
期刊:Chemosphere [Elsevier]
卷期号:282: 131150-131150 被引量:34
标识
DOI:10.1016/j.chemosphere.2021.131150
摘要

Epidemiologic studies focus on combined effects of multiple metals on bone mineral density (BMD) are scarce. Therefore, this study was conducted to examine associations of multiple metals exposure with BMD. Data of adults aged ≥20 years (n = 2545) from the US National Health and Nutrition Examination Survey (NHANES, 2011–2016) were collected and analyzed. Concentrations of metals were measured in blood (cadmium [Cd], lead [Pb], mercury [Hg], and manganese [Mn]) and serum (copper [Cu], selenium [Se], and zinc [Zn]) using inductively coupled plasma mass spectrometry and inductively coupled plasma dynamic reaction cell mass spectrometry, respectively. The weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) models were performed to determine the joint effects of multiple metals exposure on lumbar and total BMD. The linear regression analyses showed Pb was negatively associated with BMDs. The WQS regression analyses revealed that the WQS index was inversely related to lumbar (β = −0.022, 95% CI: −0.036, −0.008) and total BMD (β = −0.015, 95% CI: −0.024, −0.006), and Se, Mn, and Pb were the main contributors for the combined effects. Additionally, nonlinear dose–response relationships between Pb, Mn, and Se and BMD, as well as a synergistic interaction of Pb and Mn, were found in the BKMR analyses. Our findings suggested co-exposure to Cd, Pb, Hg, Mn, Cu, Se, and Zn (above their 50th percentiles) was associated with reduced BMD, and Pb, Mn, and Se were the main contributors driving the overall effects.

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
刚刚
1秒前
晴天小土豆完成签到 ,获得积分10
1秒前
1秒前
王强完成签到,获得积分10
2秒前
2秒前
李健应助William采纳,获得10
2秒前
积极的邪欢完成签到,获得积分10
2秒前
二十二应助御风采纳,获得10
2秒前
2秒前
量子星尘发布了新的文献求助10
2秒前
萌&完成签到,获得积分10
3秒前
kento给鱿鱼的求助进行了留言
3秒前
4秒前
4秒前
4秒前
5秒前
刘47发布了新的文献求助10
5秒前
皮蛋solo粥完成签到,获得积分20
5秒前
称心的猫咪完成签到,获得积分10
6秒前
Owen应助Lorain采纳,获得10
6秒前
机灵语雪完成签到,获得积分10
6秒前
7秒前
jia完成签到,获得积分20
7秒前
Xu完成签到,获得积分20
8秒前
Lumos发布了新的文献求助10
8秒前
8秒前
8秒前
白开水发布了新的文献求助10
8秒前
wuyuzegang发布了新的文献求助10
8秒前
9秒前
小x完成签到,获得积分20
9秒前
烟花应助paulhsy采纳,获得10
9秒前
skycrygg521发布了新的文献求助10
9秒前
6640发布了新的文献求助10
10秒前
10秒前
BowieHuang应助kk采纳,获得10
10秒前
歪歪大王完成签到,获得积分10
11秒前
tiantian完成签到,获得积分10
12秒前
12秒前
高分求助中
(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
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Russian Foreign Policy: Change and Continuity 800
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
Superabsorbent Polymers 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5709862
求助须知:如何正确求助?哪些是违规求助? 5196870
关于积分的说明 15258745
捐赠科研通 4862555
什么是DOI,文献DOI怎么找? 2610161
邀请新用户注册赠送积分活动 1560499
关于科研通互助平台的介绍 1518208