Association Between Blood Cadmium Levels and Heart Failure Risk: Insights From NHANES 2009-2014

Heart failure (HF) is a major global public health problem, and identifying modifiable environmental risk factors is important for prevention. We evaluated the association between blood cadmium levels and the risk of HF in US adults.

We analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2009-2014. A total of 10,542 adults with complete information on blood cadmium and HF status were included. Weighted multivariable logistic regression models were used to assess the relationship between blood cadmium and self-reported HF. Restricted cubic spline (RCS) regression and two-piecewise linear models were applied to explore potential dose-response relationships.

A cohort of 10,542 US adults from the NHANES 2009-2014 dataset was analyzed, including 321 individuals diagnosed with HF. In fully adjusted, weighted logistic regression models, elevated blood cadmium levels were significantly correlated with an increased prevalence of HF. Specifically, each 1 μg/L increment in blood cadmium was associated with a 42% higher likelihood of HF (odds ratio [OR] = 1.42; 95% confidence interval [CI]: 1.18-1.72; p < 0.001). Participants in the highest quartile of blood cadmium levels exhibited more than a threefold increase in the odds of HF compared to those in the lowest quartile (OR = 3.15; 95% CI: 1.81-5.50; p < 0.001), with a significant linear trend observed across quartiles (p < 0.001). RCS analysis demonstrated a monotonic positive relationship, with an apparent inflection point at approximately 0.13 μg/L, beyond which the risk continued to escalate. This association was generally consistent across various subgroups but was notably stronger among smokers (p for interaction < 0.05).

Elevated blood cadmium is an independent risk factor for HF in the United States. These findings suggest that reducing cadmium exposure may be a novel strategy for HF prevention. Prospective studies are warranted to clarify causal relationships and underlying mechanisms.