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Interactive association of metals and Life’s Essential 8 with mortality in U.S. adults: a prospective cohort study from the NHANES dataset

BMC Public Health volume 24, Article number: 3073 (2024) Cite this article

Abstract

Background

Life’s Essential 8 (LE8) is a novel assessment of cardiovascular health (CVH) by evaluating lifestyle, and reports of the associations between LE8 and urinary metals on mortality have been very limited. This study aimed to conduct a prospective cohort study and investigate the combined effects of metals and LE8 on mortality in U.S. adults.

Methods

This study enrolled participants with complete information on urinary metals, LE8, mortality status, and confounders from the National Health and Nutrition Examination Survey (2005–2018). The Cox regression model, adaptive lasso penalized regression, and restricted cubic spline were used to analyze the individual effects of metals and LE8 on all-cause mortality. The additive and multiplicative interaction scales and quantile g-computation were used to evaluate the interaction and combined effects. Stratified analyses were performed to clarify whether metals and LE8 interacted with other variables to influence all-cause mortality.

Results

A total of 8017 participants were included in this study. The concentrations of cadmium, cobalt, lead, antimony, and thorium were greater in the low CVH group than in the high CVH group [median (µg/L): 0.29 vs. 0.19, 0.36 vs. 0.35, 0.48 vs. 0.39, 0.05 vs. 0.04, and 0.07 vs. 0.06]. The interaction between cadmium and LE8 was statistically significant, with a synergy index of 1.169 (95% CI: 1.004, 1.361). The stratified analyses showed that the interaction between age and LE8 had an impact on all-cause mortality (P for interaction = 0.004).

Conclusions

In this representative sample of the U.S. population, we found that the combined effect of cadmium, lead, thallium, and LE8 was positively associated with all-cause mortality. Furthermore, the interaction between cadmium and LE8 influenced all-cause mortality. So people should adopt healthy behaviors and reduce heavy metal exposure to minimize the risk of adverse health outcomes.

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Introduction

Mortality in humans is influenced by a multitude of factors, among which daily dietary habits, physical activity, smoking, and alcohol consumption play pivotal roles. Poor dietary choices, characterized by high intake of processed foods, trans fats, and sugars, coupled with insufficient physical activity, significantly increase the risk of chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer, all of which contribute to higher all-cause mortality [1]. CVD, in particular, remains one of the leading causes of death globally, with lifestyle factors playing a key role in its development and progression. Conversely, a balanced diet rich in fruits, vegetables, whole grains, and lean proteins, alongside regular exercise, can substantially lower the risk of CVD and other life-threatening conditions by promoting overall health [2]. Moreover, lifestyle choices such as smoking and excessive alcohol consumption have been unequivocally linked to increased all-cause and CVD mortality. Smoking is a major contributor to respiratory diseases, CVD, and various cancers, while excessive alcohol intake is associated with liver disease, accidents, and a host of other health complications [3]. Collectively, these factors underscore the critical importance of healthy lifestyle practices in reducing all-cause mortality and CVD mortality, ultimately improving longevity. In 2010, the American Heart Association launched a project to provide care for the cardiovascular health (CVH) of individuals. The key to this project was to set a credible indicator, including information on nutrition, exercise, cigarette use, body mass index (BMI), total cholesterol, blood pressure, and blood glucose [4]. In 2022, sleeping conditions were added to this indicator, forming Life’s Essential 8 (LE8) [5]. According to Sun et al., the risk of all-cause mortality and CVD mortality decreased as the LE8 score increased [6]. By exploring the relationships between LE8 scores and all-cause death, Xing et al. reported that baseline and long-term LE8 scores were negative with the prevalence of all-cause and CVD mortality in young adults [7].

In addition to daily lifestyles associated with human death, environmental factors around human surroundings also play an important role. As industrialization accelerates and urbanization progresses, environmental pollution has become increasingly severe. In particular, the widespread presence of heavy metals in the environment poses a long-term and serious threat to global public health. Heavy metals, such as cadmium (Cd) [8, 9], lead (Pb) [10], and mercury (Hg) [11], are widely distributed in water resources and soils in the United States. These heavy metals enter the human body through drinking water, food, and air, accumulating over time and exhibiting toxic effects that can lead to various health issues, including CVD, cancer, and neurological disorders. They can cause endothelial dysfunction, lipid peroxidation, and inflammation by enhancing oxidative stress in the body, leading to tissue and organ damage [12]. A study by Rhee et al. revealed an association between Pb and lung cancer mortality, mainly in females [13]. A cohort study showed that mixed metal exposure was positively associated with all-cause mortality in the population, with Cd contributing the most [14]. Importantly, Cd and other metals have also been implicated in the progression of cardiovascular diseases, further linking environmental exposure to both all-cause and CVD mortality. With the emphasis on health, maintaining a healthy lifestyle, reducing exposure to hazards, and decreasing mortality have become critical areas of research.

However, current research predominantly focuses on the individual effects of lifestyle or environmental exposure on health, with relatively few studies examining their combined impact on all-cause and CVD mortality. Given that heavy metal exposure and daily lifestyle factors may influence health through shared biological mechanisms such as oxidative stress [15, 16] and chronic inflammation [17, 18], exploring their combined effects is crucial for a comprehensive understanding of their role in all-cause and CVD mortality risk. By studying the interaction between these factors, we can uncover additional potential health risk factors and further identify which lifestyle adjustments can effectively mitigate the negative health impacts of heavy metal exposure. This, in turn, provides a scientific basis for the development of individual and public health policies. Ultimately, this research will help optimize population health management strategies, reduce premature deaths related to environmental and lifestyle factors, particularly from CVD, and enhance overall human health. Therefore, in this study, we used the data from seven cycles of the National Health and Nutrition Examination Survey (NHANES) (2005–2018) and the most recent follow-up mortality data to explore the potential interaction between metals and LE8 on mortality.

Materials and methods

Study population

We extracted data from the NHAENS database, a survey of selected representative populations designed to investigate the health and nutritional status of different ethnic groups in the U.S. [19]. Messages about the NHANES study design, data collection process, ethics, and informed consent of participants were mentioned in our previous study [20]. The current study combined data from the 2005–2006, 2007–2008, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2017–2018 NHANES cycles. The schematic diagram of participant selection is shown in Fig. 1. Initially, 70,190 subjects were enrolled, with participants < 20 years (n = 30,441) and missing information on urinary metals (n = 27,325), components of LE8 (n = 2,712), mortality status (n = 30), and confounders (n = 665) excluded from the study. Based on previous studies [5], we also excluded individuals who were pregnant or breastfeeding at the time of the examination (n = 165), as well as individuals who self-reported coronary heart disease, angina, heart attack, or stroke (n = 835). Finally, this study included 8017 individuals with complete information on urinary metals, LE8, survival status, and other covariates.

Fig. 1
figure 1

Flow Chart of the research subjects selection in the NHANES 2005–2018

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Urinary metal assessment and quantification of CVH

Although potential errors existed in different NHANES cycles, measurements of arsenic (As), barium (Ba), Cd, cobalt (Co), cesium (Cs), Hg, molybdenum (Mo), Pb, antimony (Sb), thallium (Tl), and tungsten (Tu) were made in all seven cycles from 2005 to 2018. Finally, we included urinary As, Ba, Cd, Co, Cs, Hg, Mo, Pb, Sn, Tl, and Tu in this study. Urinary metals were detected using inductively coupled plasma dynamic reaction cell mass spectrometry and the unit was µg/L. Limits of detection (LOD) for urinary metals and the percent of samples below the LOD were presented in Table S1. The metal levels below LOD were estimated by dividing the LOD by the root sign 2 [20]. The quantification tables for the LE8 scores are provided in the previous study [5] for the quantified NHANES data. As shown in Table S2, the LE8 assessment included four health behaviors, including diet, physical activity, smoking, and sleep, as well as four health factors, including BMI, non-high-density lipoprotein (HDL) cholesterol, blood glucose, and blood pressure [5]. Dietary indicators were evaluated using the Dietary Approaches to Stop Hypertension (DASH)-style eating pattern. Self-report questionnaires were used to gather data on physical activity, smoking status, daily sleep, blood glucose, and medication history. Data on height, weight, and blood pressure were collected by physical examination, and BMI was calculated by dividing weight by the square of height. Data on non-HDL cholesterol, plasma glucose, and hemoglobin A1c were collected from fresh blood [21]. Venous blood samples from participants were collected and analyzed following the NHANES laboratory protocol. All standard biochemical parameters were measured using a Roche Cobas 6000 (c501 module) analyzer. For further details on the methods used for each analyte, as well as the rationale and operating procedures, please refer to the Laboratory Methods document available at https://wwwn.cdc.gov/Nchs/Nhanes/ [22].

Mortality

The mortality data were collected as of December 31, 2019, and were extracted via linkage to the National Death Index. The primary endpoint was all-cause mortality, and the secondary endpoints included CVD mortality (ICD I00-I09, I11, I13, I20-I51, I60-I69), cancer mortality (C00-C97), and others [23]. The specific study identifiers were used to match NHANES data to determine participants’ baseline data and mortality status.

Other covariates

Other covariates included age, sex, marriage, ethnicity, education, poverty income ratio (PIR), alcohol use, and NHANES cycle. The stratification of age, marital status, ethnicity, and education was described in our previous study [20]. Drinking status was categorized as never drinker (less than 12 alcohol drinks/lifetime), ever drinker (had at least 12 alcohol drinks/1 year and no drink alcohol over past 12 months), current drinker (drink alcohol over past 12 months). Smoking was categorized as never smoker (smoked less than 100 cigarettes in life), ever smoker (smoked at least 100 cigarettes in life and no smoke now), and current smoker (smoked at least 100 cigarettes in life and smoke now) [24]. PIR was categorized as < 2 or ≥ 2. We also included depression as a covariate, based on the study by Lloyd et al. [5]. The Patient Health Questionnaire-2 was used to assess the level of depression in participants aged 18 years and older. Subjects were asked, “Over the last 2 weeks, how often have you been bothered by the following problems (feeling down, depressed, hopeless, or little interest or pleasure in doing things)?”, and response options “not at all”, “a few days”, “more than half a day” and “almost every day” were scored 0, 1, 2 or 3 points, respectively [5]. Scores ≥ 3 out of 6 were the validated threshold for evaluating the potential condition of depression, so depression was categorized as < 3 or ≥ 3.

Statistical analysis

In this study, we followed the NHANES guidelines and accounted for complex survey design factors, including sample weights, clustering, and stratification [19]. The study population was divided into high and low groups according to the median LE8 score of 63.13. Categorical variables were shown as percentages and for skewed variables, they were shown as P50 (P25, P75). Chi-square tests, nonparametric tests, and correlation tests were used to compare the differences in fundamental information. Then urinary metal concentrations were grouped by quartiles. The Cox regression model and adjusted restricted cubic spline (RCS) were used to analyze the relationships between metals, LE8, and all-cause mortality. Trend tests were further used to analyze the trend relationship between different groups regarding their impact on the outcome. To determine the metals included in subsequent analyses, we used adaptive lasso penalized regression (LASSO), combined with the results of Cox regressions, to identify the optimal independent variables. LASSO can be applied to various types of regression models and is particularly well-suited for high-dimensional data, as it can select a subset of relevant variables without overfitting, even when the number of predictors exceeds the number of observations. LASSO helps mitigate multicollinearity issues by selecting one variable from a group of highly correlated variables, effectively reducing the model’s complexity while retaining predictive power. By imposing an L1 penalty on the regression coefficients, LASSO tends to shrink the coefficients of less important variables to exactly zero, effectively eliminating irrelevant or redundant variables [25, 26]. Generalized linear regression and additive and multiplicative interaction scales were used to calculate the interaction effects of Cd, Pb, Tl, and LE8 on all-cause mortality, and the multiplicative interaction index (ORint) and additive interaction indices [relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), synergy index (SI)] were computed. The Delta method, an approximation based on the asymptotic normal distribution, estimates the interaction effect and its standard error (SE) from the fitted model parameters. The confidence interval is then constructed using the formula: \(\:CI=\:Estimate\:\pm\:\:1.96\:\times\:\:SE\) [27]. The concentrations of Cd, Pb, and Tl were divided into high and low groups according to the median 0.23 µg/L, 0.43 µg/L, and 0.155 µg/L, respectively. To explore the effects of multiple factors on all-cause mortality, a quantile g-computation analysis was performed. Quantile g-computation is a novel statistical method for analyzing co-exposures to pollutants, suggesting an estimate of the effect of a simultaneous increase in all exposures by a single quartile, which is useful for studying multiple pollutant exposures [28]. We further performed stratified analyses to clarify whether Cd, Pb, Tl, and LE8 interacted with other variables to influence all-cause mortality. Sensitivity analyses were performed to test the robustness of the results. The outcome was changed from all-cause mortality to CVD mortality, and Cox regression, quantile g-computation, etc., were used to compare differences in CVD mortality between metal subgroups. The reasons for replacing all-cause mortality with CVD mortality were primarily as follows: First, CVD was one of the leading causes of death in this population. Second, by examining whether the trend in CVD aligns with the trend in all-cause mortality, it could be determined whether the study results were less likely to be biased by specific disease types, thereby enhancing the robustness of the findings. All urinary metal concentrations and LE8 were log-transformed in all models. All the statistical descriptions and analyses were performed with SPSS 24.0 and R 4.2.0. In this study, we used R language packages such as “compareGroups”, “rms”, “qgcomp”, etc. A two-sided test was applied with a test level of α = 0.05.

Results

Study population characteristics

The basic information of the study subjects and the distribution of urinary metal concentrations in different CVH groups are shown in Table 1. Of the total population, the proportions of males and females were 51.1% and 48.9%, respectively. 75.6% of the subjects in the study were non-Hispanic. More than 50% of the subjects were married. 77.1% of the subjects had a high school diploma or higher, which was greater in the high CVH group than in the low CVH group. The percentages of participants with PIR < 2.0, depression ≥ 3.0, and current alcohol consumption were 58.0%, 12.9%, and 64.8%, respectively, in the low CVH group and 42.3%, 5.3%, and 72.6%, respectively, in the high CVH group. Over a median follow-up period of 89 months (IQR: 50–130 months), a total of 803 all-cause deaths occurred, of which 199 (24.8%) were CVD deaths and 208 (25.9%) were cancer deaths. As shown in Table 1, the total LE8 score in the total population was 62.9 (SE, 0.17). The DASH diet, physical activity, tobacco or nicotine exposure, sleep health, BMI, blood lipid (non-HDL cholesterol), blood glucose, and BP scores were 62.9 (SE, 0.17), 42.6 (SE, 0.34), 42.6 (SE, 0.34), 71.1 (SE, 0.43), 81.2 (SE, 0.28), 59.0 (SE, 0.38), 64.3 (SE, 0.35), 78.8 (SE, 0.31), and 64.3 (SE, 0.38), respectively. The concentrations of Cd, Co, Pb, Sb, and Tu were greater in the low CVH group than in the high CVH group [median (µg/L): 0.29 vs. 0.19, 0.36 vs. 0.35, 0.48 vs. 0.39, 0.05 vs. 0.04, and 0.07 vs. 0.06], while the results for As, Hg, and Tl were opposite [median (µg/L): 7.00 vs. 7.92, 0.26 vs. 0.34, and 0.15 vs. 0.16]. Fig. S1 shows the correlation between the LE8 score and metals. LE8 was positively correlated with As, Hg, and Tl and negatively correlated with Ba, Cd, Co, Cs, Mo, Pb, Sb, and Tu. Table S3 shows the distribution of metal concentrations in different NHANES cycles. The concentrations of certain metals showed slight variations across different years, with urinary levels of As, Hg, Mo, and Pb exhibiting a decreasing trend. Considering the fluctuations in urinary metal concentrations over the years, we included the cycle as an adjustment factor in all models.

Table 1 Characteristics of the study population in the NHANES 2005–2018 (n = 8017)
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Association of LE8 with the occurrence of all-cause mortality

The relationship between LE8 and all-cause mortality is shown in Table 2. LE8 was negatively associated with all-cause mortality in the unadjusted and adjusted models (all P for trend < 0.001). In Model 3, after adjusting for age, sex, ethnicity, marital status, education, PIR, depression status, drinking status, and NHANES cycles, the highest quartile group had a hazard ratio (HR) of 0.73 (95% CI: 0.58, 0.94) compared to the lowest quartile group, indicating a subsequent decrease in the occurrence of all-cause mortality as LE8 increased. The same result was observed for LE8 as a continuous variable.

Table 2 The relationship between LE8 and all-cause mortality, NHANES (2005–2018)
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Associations between metals and all-cause mortality

The Cox regression analyses between metals and all-cause mortality are shown in Table 3. After adjusting for all covariates, high Cd levels significantly increased the risk of all-cause mortality, with the HR of 1.67 (95% CI: 1.30, 2.13), and high levels of Ba, Cs, and Tl significantly decreased the risk of all-cause mortality [HR: 0.60 (95% CI: 0.49, 0.74), 0.67 (95% CI: 0.55, 0.82), and 0.61 (95% CI: 0.48, 0.76)]. The trend tests suggested a negative relationship between Ba, Cs, Tl, and all-cause mortality, while a positive association existed between Cd and all-cause mortality. According to the LASSO analysis in Fig. S2, Cd, Pb, and Tl were identified when the minimal value of λ (log-λ=-3.63) was chosen, with coefficients of 0.263, 0.010, and − 0.177, respectively. Based on the results of the Cox regression and the LASSO, Cd, Pb, and Tl were included in the RCS analysis. As shown in Fig. 2, RCS analyses revealed a nonlinear association between Pb and all-cause mortality. The overall associations between Cd, Pb, Tl, and all-cause mortality were statistically significant (all P values for overall < 0.05).

Table 3 Relationships between metals and all-cause mortality, NHANES (2005–2018)
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Fig. 2
figure 2

Dose-response association between log-Cd, log-Pb, log-Tl, and risk of all-cause mortality based on restricted cubic splines. The adjusted covariates were age, sex, ethnicity, marital status, education, PIR, depression status, drinking status, NHANES cycles, and the other 10 metals

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Interacting and combined effects

Table 4 shows the interaction effects of Cd, Pb, Tl, and LE8 on all-cause mortality. The percentage of all-cause deaths increased with decreasing LE8 and increasing Cd or Pb concentrations compared with those in the control group (3.8% vs. 20.6%; 4.1% vs. 19.8%), with HRs of 2.35 (95% CI: 1.82, 3.03) and 1.71 (95% CI: 1.31, 2.23), respectively. The interaction between Cd and LE8 was statistically significant, with an SI of 1.169 (95% CI: 1.004, 1.361). As shown in Fig. 3, the quartile g-computation demonstrated an increase in all-cause mortality due to the combined effects of Cd, Pb, Tl, and LE8, of which Cd and Pb played a positive role, while Tl and LE8 played a negative role. The HR for the total effect of Cd, Pb, Tl, and LE8 on all-cause mortality was 0.146 (95% CI: -0.021, 0.312, P = 0.086).

Table 4 Interaction effects of cd, Pb, Tl, and LE8 on all-cause mortality
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Fig. 3
figure 3

Combined effect of Cd, Pb, Tl, LE8, and all-cause mortality according to the quartile g-computation model. The adjusted covariates were age, sex, ethnicity, marital status, education, PIR, depression status, drinking status, NHANES cycles, and the other 10 metals

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Fig. 4
figure 4

Subgroup analysis of the risk ratio of all-cause mortality comparing subjects with low and high LE8

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Subgroup analysis

To determine whether the associations between different levels of Cd, Pb, Tl, and LE8 and all-cause mortality were influenced by covariates, we stratified the participants by age, sex, marital status, ethnicity, education, PIR, depression status, and alcohol consumption status. As shown in Fig. S3, the interactions between Cd, Pb, Tl, and covariates were not statistically significant for all-cause death. However, we identified an interaction between age and LE8 that had an impact on all-cause mortality (P for interaction = 0.004, Fig. 4). The HRs of the < 40 years group, 40–60 years group, and > 60 years group were 0.68 (95% CI: 0.26, 1.57), 0.48 (95% CI: 0.33, 0.70), and 0.93 (95% CI: 0.78, 1.11), respectively.

Sensitivity analysis

To confirm the reliability of the results, we performed sensitivity analyses by replacing the outcome. Table S4 shows the Cox regression of the relationships between Cd, Pb, Tl, and LE8 concentrations and CVD mortality, which is consistent with the main analysis. After adjusting for covariates, Ba and LE8 had negative trend associations with CVD mortality (P for trend = 0.011 and 0.061), whereas Cd and Sb had positive trend associations with CVD mortality (P for trend = 0.052 and 0.016). Furthermore, as shown in Fig. S5, the dose-response relationship between Pb and all-cause mortality and CVD mortality is roughly consistent. The relationships of Cd and Tl with all-cause mortality and CVD mortality show slight inconsistencies. The effect of Cd on all-cause mortality increases with dose, whereas its impact on CVD mortality shows a decreasing trend at certain doses, and there is a nonlinear association between Cd and CVD mortality (P for nonlinear = 0.031). For Tl, the effect on all-cause mortality decreases as the dose increases, while the effect on CVD mortality first increases and then decreases, and the overall effect of Tl on CVD mortality shows no significant association (P for overall = 0.118). The combined effects between Cd, Pb, Tl, LE8, and CVD mortality were similar to those observed in the main analysis (Fig. S6). The HR for the total effect of Cd, Pb, Tl, and LE8 on CVD mortality was − 0.045 (95% CI: -0.376, 0.286, P = 0.789).

Discussion

To our knowledge, there has been limited research on the association between LE8 and metals. Therefore, our latest findings provide further insight into this area. Our study revealed that high levels of urinary Cd increased the risk of all-cause and CVD mortality in US adults, while Ba, Cs, Tl, and LE8 significantly decreased the risk of all-cause mortality. Additionally, we discovered that the combined effect of Cd, Pb, Tl, and LE8 was positively associated with the occurrence of all-cause mortality.

The state of human health is closely related to lifestyle, and LE8, a powerful tool for quantifying lifestyle, contains four health behaviors and four health factors. In the total population of this study, the LE8 score was 62.9, which was consistent with the results of Lloyd-Jones et al. [5]. In addition, the distribution of scores for each component of LE8 was the same as that in previous studies [29, 30]. Many studies have confirmed the strong association between LE8 and mortality. An inverse gradient association existed between baseline and long-term LE8 scores and the risk of premature all-cause mortality in young adults [7], with similar results observed in elderly study populations [31]. A comprehensive study shows that in the U.S. population, each standard deviation increase in the LE8 score reduces cancer mortality by 19%, while in the U.K. population, mortality is also reduced by 19% [32]. The results from a cross-sectional study suggested that higher LE8 scores were associated with improved cardiovascular status and a lower incidence of cerebral small-vessel disease [33]. As the burden of mortality increases due to poor lifestyles, more research will focus on LE8. In the present study, we also categorized the subjects into low and high CVH groups based on LE8 scores to explore the differences in the characteristics of the subjects in the NHANES 2005–2018. We found that the high-CVH group had a greater percentage of people who were < 40 years old, female, and had a higher education level than did the low-CVH group, which indicated that these three people are more likely to maintain a healthy lifestyle.

Metals are universally distributed in soils and are important industrial raw materials. Some harmful heavy metal exposure can cause damage to various systems and organs, such as the reproductive system, renal system, and cardiovascular system, resulting in adverse health effects and even death [34,35,36]. In this study, we found a positive correlation between urinary Cd concentration and all-cause mortality, with an adjusted HR of 1.67 (95% CI: 1.30, 2.13). We also discovered a negative relationship between Ba, Cs, Tl, and all-cause mortality. Our findings were consistent with the study of Shi et al., in which Tl was negatively correlated with mortality according to the multimetal model [37]. Satarug et al. explored the correlation between Cd exposure and mortality in postmenopausal women and reported that higher urinary Cd concentrations were significantly associated with increased all-cause mortality [38]. Duan et al. also reported a negative correlation between urinary Ba and CVD mortality in the NHANES population [14]. Our findings were also inconsistent with some other results. An eco-spatial study conducted in Spain showed that Tl could potentially affect human health [39]. A statistically significant association between Cs and all-cause mortality was not found in the study by Duan et al. [14]. The main reasons for this discrepancy are as follows: (1) differences in the study populations, which can lead to biased results due to age, ethnicity, tolerance level, etc.; (2) differences in the test specimens, which reflect the exposure levels of the human body at different times, which is the main reason for the discrepancy in the results. Thus, additional cohort studies are needed to explore the health effects of metals.

Cox regression and adaptive penalized LASSO regression were used to analyze the interaction and combined effects of Cd, Pb, and Tl with LE8 on all-cause mortality. Interaction analysis revealed an SI of 1.169 (95% CI: 1.004, 1.361) for Cd and LE8, suggesting a potential multiplicative interaction between Cd and LE8. The OR of the Low-LE8 + Low-Cd group was 1.94 (95% CI: 1.48, 2.56) compared to that of the High-LE8 + Low-Cd group. Unhealthy lifestyle factors like smoking [40], drinking [41], high-fat diets [42], etc. increase oxidative stress and chronic inflammation in the body, while Cd exposure similarly promotes oxidative stress and inflammation, damaging cells and tissues [43]. The lifestyle issues can weaken the immune system [44], reducing the body’s resistance to Cd exposure, leading to more severe organ damage, and thus increasing the risk of early death. Moreover, unhealthy lifestyles may impair the body’s ability to metabolize and detoxify heavy metals. Studies have shown that a healthy lifestyle, such as a balanced diet and regular exercise, can help mitigate the negative impacts of heavy metals on the body, for example, by increasing antioxidant intake to neutralize oxidative stress and enhance immunity [45]. However, a low LE8 score indicates that the individual has not benefited from these protective lifestyle factors, making them more vulnerable to the harmful effects of Cd, which leads to a higher risk of mortality. When individuals are exposed to Cd and also engage in unhealthy lifestyles, the negative effects of both factors may synergize, exacerbating bodily damage and further increasing the risk of all-cause mortality. Therefore, maintaining good lifestyle habits might reduce the harmful effects caused by Cd exposure.

According to the quartile g-computation model, we found that the combined effect of Cd, Pb, Tl, and LE8 on all-cause mortality was positive, with Cd and Pb playing a positive role and LE8 and TL playing a negative role. The survival curves show a gradual decrease in survival as time progresses. Heavy metals such as Pb, Cd, and Hg can generate excessive reactive oxygen species (ROS), triggering oxidative stress in the body, which can directly damage cell membranes, proteins, and DNA, leading to cellular dysfunction and inflammatory responses, thereby inducing chronic diseases and premature death [46,47,48]. Metal exposure, especially Cd and Hg, is also associated with immunosuppression, impairing the function of immune cells [49]. Certain unhealthy lifestyle choices increase oxidative stress levels and chronic inflammation in the body, leading to metabolic disorders and weakened immune function. Under the dual effects of metal exposure and immunosuppression, organs such as the kidneys, lungs, and liver are more prone to damage [50]. The decline in organ function may lead to the worsening of chronic diseases, such as chronic kidney disease and respiratory system disorders, further increasing the risk of death. When metal exposure is combined with poor lifestyle choices, the levels of oxidative stress and chronic inflammation may intensify, exacerbating damage to cells and organs, ultimately accelerating disease progression and increasing all-cause mortality. In certain environments, individuals may be exposed to high levels of metals, and these groups are often also at high risk due to unhealthy lifestyles [51]. These lifestyle issues exacerbate the health vulnerability of individuals facing environmental exposure. Therefore, individuals should choose healthy behaviors to minimize the risk of adverse health outcomes from external contaminants. In the stratified analysis, we also found that an interaction between age and LE8 had an impact on all-cause mortality, with HRs of 0.68, 0.48, and 0.93 for the < 40 years group, 40–60 years group, and > 60 years group, respectively. The above results indicated that the 40–60 years group was healthier than the other two groups. Death is sometimes influenced by more than just a single factor, age plays a role, and studies can be performed on different age populations to better determine the effect of exposure on mortality [52].

The present study has several innovations. First, we explored the combined effect of urinary metals and LE8 on mortality for the first time. Second, we used models such as Cox regression, RCS, and stratified analysis, which are specifically designed for the relationship between exposure and outcome, making our results accurate and reliable. Moreover, sensitivity analysis also confirmed the stability of the results of this study. Ultimately, more than 8000 study subjects were included in this investigation, and more than 800 deaths occurred. This study also has several limitations. Multiple pollutants are present in the daily environment and simultaneously affect human health; thus, additional contaminants should be studied in combination. Second, this study was conducted on adults, and relevant studies on children and adolescents need to be conducted. Additionally, a portion of the study population was enrolled between 2017 and 2018, resulting in a relatively short follow-up period.

Conclusion

In conclusion, our study demonstrated that urinary Cd and Pb were associated with a high risk of all-cause mortality, while urinary Tl and LE8 could reduce all-cause mortality, and an interaction existed between Cd and LE8. Our findings emphasized the importance of adhering to healthy CVH lifestyle habits to reduce harm from heavy metal exposure and improve patient quality of life and survival.

Data availability

The datasets generated and/or analysed during the current study are available in the NHANES repository, https://www.cdc.gov/nchs/nhanes.

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Acknowledgements

The authors thank the National Center for Health Statistics of the Centers for Disease Control and Prevention for sharing the data.

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Authors and Affiliations

  1. The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, 511400, Guangdong, China

    Weipeng Zhang, Dengqiu Lu, Junfeng Nie, Zhumin Hu & Cuiyao Xian

  2. The Second Nanning People’s Hospital, Nanning, 530031, Guangxi, China

    Weiqiang Chen

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Contributions

Weipeng Zhang: Software, Data curation, Conceptualization, Writing – original draft. Weiqiang Chen, Dengqiu Lu, and Junfeng Nie: Writing – review & editing. Zhumin Hu and Cuiyao Xian: Visualization, Writing – review & editing.

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Zhang, W., Chen, W., Lu, D. et al. Interactive association of metals and Life’s Essential 8 with mortality in U.S. adults: a prospective cohort study from the NHANES dataset. BMC Public Health 24, 3073 (2024). https://doi.org/10.1186/s12889-024-20580-z

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