Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MA, USA; Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MA, USA.
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MA, USA.
Sci Total Environ. 2024 May 1;923:171511. doi: 10.1016/j.scitotenv.2024.171511. Epub 2024 Mar 5.
Studies using data from the National Health and Nutrition Examination Survey-III (NHANES-III) have demonstrated significant prospective associations between blood lead levels and increased mortality. Bone lead represents cumulative lead burden and thus is a better biomarker for assessing chronic impacts, but its in vivo assessment requires special K-x-ray fluorescence (KXRF) instrumentation. Our team recently developed an algorithm predicting bone lead levels from a combination of blood lead levels, age and other socioeconomic and behavioral variables. We examined the associations of our algorithm-estimated bone lead levels and mortality in NHANES-III.
We included 11,628 adults followed up to December 31, 2019. Estimated tibia lead and patella lead levels were calculated using our prediction algorithms. We used survey-weighted Cox proportional hazards models to compute hazard ratios (HRs) and 95 % confidence intervals (CIs).
During the median follow-up of 26.8 years, 4900 participants died (mortality rate = 1398 per 100,000 adults/year). Geometric means (95 % CIs) of blood lead, predicted tibia lead, and predicted patella lead were 2.69 μg/dL (2.54, 2.84), 6.73 μg/g (6.22, 7.25), and 16.3 μg/g (15.9, 16.8), respectively. The associations for all-cause mortality were similar between blood lead and bone lead. However, the associations for cardiovascular mortality were much greater with predicted bone lead markers compared to blood lead: for comparing participants at the 90th vs. 10th percentiles of exposure, HR = 3.32 (95 % CI: 1.93-5.73) for tibia lead, 2.42 (1.56-3.76) for patella lead, 1.63 (1.25-2.14) for blood lead. The population attributable fractions for cardiovascular disease mortality if everyone's lead concentrations were declined to the 10th percentiles were 45.8 % (95 % CI: 28.1-59.4) for tibia lead, 33.1 % (18.1-45.8) for patella lead, and 22.8 % (10.4-33.8) for blood lead.
These findings suggest that risk assessment for cardiovascular mortality based on blood lead levels may underestimate the true mortality risk of lead exposure.
使用来自国家健康和营养检查调查 III（NHANES-III）的数据进行的研究表明，血液铅水平与死亡率增加之间存在显著的前瞻性关联。骨铅代表累积的铅负担，因此是评估慢性影响的更好生物标志物，但体内评估需要特殊的 K-射线荧光（KXRF）仪器。我们的团队最近开发了一种算法，可以根据血液铅水平、年龄和其他社会经济及行为变量来预测骨铅水平。我们研究了我们的算法估计的骨铅水平与 NHANES-III 中死亡率之间的关联。
我们纳入了 11628 名成年人，随访至 2019 年 12 月 31 日。使用我们的预测算法计算胫骨铅和髌骨铅的估计值。我们使用调查加权 Cox 比例风险模型计算风险比（HR）和 95%置信区间（CI）。
在中位随访 26.8 年期间，有 4900 名参与者死亡（死亡率=每 100000 名成年人/年 1398 人）。血液铅、预测胫骨铅和预测髌骨铅的几何均数（95%CI）分别为 2.69μg/dL（2.54，2.84）、6.73μg/g（6.22，7.25）和 16.3μg/g（15.9，16.8）。全因死亡率的相关性在血液铅和骨铅之间相似。然而，与血液铅相比，预测的骨铅标志物与心血管死亡率的相关性要大得多：对于比较暴露于第 90 百分位和第 10 百分位的参与者，胫骨铅 HR=3.32（95%CI：1.93-5.73），髌骨铅 HR=2.42（1.56-3.76），血液铅 HR=1.63（1.25-2.14）。如果每个人的铅浓度都降至第 10 百分位，那么心血管疾病死亡率的人群归因分数分别为胫骨铅 45.8%（95%CI：28.1-59.4）、髌骨铅 33.1%（18.1-45.8）和血液铅 22.8%（10.4-33.8）。
这些发现表明，基于血液铅水平的心血管死亡率风险评估可能低估了铅暴露的真实死亡风险。
