Abstract
Background
Chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD) are intimately connected. A recently developed measure called Life’s Essential 8 (LE8) is used to evaluate cardiovascular health (CVH). We aimed to investigate the relationship between LE8 and the prevalence of COPD, and the association between LE8 and all-cause mortality in individuals with COPD.
Methods
The National Health and Nutrition Examination Survey (NHANES) 2005–2018 was the source of the data used in our investigation. The participants were divided into three groups according to their LE8 scores: low (< 50), moderate (50–79), and high (≥ 80) CVH. Weighted logistic regression models and restricted cubic spline (RCS) curves were used to examine the relationship between LE8 score and the prevalence of COPD. To determine whether the results were stable, we used subgroup and sensitivity analyses. Furthermore, we evaluated the association between LE8 and all-cause mortality in COPD patients using a weighted Cox regression analysis.
Results
Weighted logistic regression analysis of the fully adjusted model indicated that a higher LE8 score was associated with a lower prevalence of COPD (OR = 0.75; 95% CI, 0.71–0.79). The RCS curves showed a linear negative association between them. LE8 score was negatively correlated with the prevalence of COPD across all subgroups, and this negative correlation was significant in those younger than 60 years old. The sensitivity analysis’s results were consistent with the primary findings. Furthermore, weighted Cox regression analysis of the fully adjusted model showed that LE8 score was negatively associated with all-cause mortality in COPD patients (HR = 0.81, 95% CI = 0.74–0.89).
Conclusions
LE8 score was negatively associated not only with the prevalence of COPD, but also with all-cause mortality in patients with COPD.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12890-025-03783-x.
Keywords: NHANES, COPD, Life’s essential 8, Cardiovascular health, All-cause mortality
Introduction
Chronic obstructive pulmonary disease (COPD) is a gradually worsening lung condition defined by ongoing respiratory symptoms and restricted airflow caused by anomalies in the airways or alveoli [1]. With an estimated 3.3 million deaths in 2019, COPD is currently the third most common cause of death worldwide [2, 3]. The global prevalence of COPD varies, but it is estimated that roughly 10% of individuals aged 40 years and above are affected by the disease [4]. The aging population and ongoing exposure to risk factors will likely cause the incidence of this illness to increase even more. Despite being a preventable and treatable condition, there is currently no cure for COPD [5]. Therefore, identifying risk factors for COPD and implementing appropriate interventions are key steps in significantly reducing the incidence and mortality associated with the disease.
Cardiovascular disease (CVD) is a condition that often coexists with COPD and also poses a significant challenge to global public health [6, 7]. The association between COPD and CVD is multifaceted and reciprocal [8]. Individuals with COPD have a much higher likelihood of acquiring CVD, while those with existing CVD may experience worsening respiratory symptoms and exacerbations of COPD [9–11]. Common risk factors are present in both illnesses, such as smoking, which is a significant trigger for both COPD and CVD [12, 13]. Other factors include advanced age, sedentary lifestyle, poor diet, and comorbid conditions such as diabetes and hypertension [14, 15]. The interrelationship between COPD and CVD gives us insight that measures to improve cardiovascular health (CVH) have the potential to be effective in preventing COPD.
In response to the growing burden of CVD, the American Heart Association (AHA) introduced the “Life’s Simple 7 (LS7)” initiative in 2010, a comprehensive framework aimed at improving CVH through manageable lifestyle modifications and risk factor control [16]. This initiative highlights seven key factors—diet, physical activity, nicotine exposure, weight management, blood pressure, cholesterol, and blood sugar—that individuals can monitor and improve to significantly reduce their risk of developing CVD [16]. As the understanding of CVH evolves, so does the need for more comprehensive approaches. In 2022, the AHA created Life’s Essential 8 (LE8) by adding sleep health to the original framework [17]. This evolution reflects an increasing amount of research that emphasizes the significant influence of sleep on CVH [18, 19]. The inclusion of sleep health in LE8 represents a significant enhancement over LS7, offering a more comprehensive and holistic approach to CVD prevention [20].
Recent studies have shown that the risk of CVD decreases as the LE8 score increases [21–23]. Xing et al. [22] followed 16,011 participants aged 18–40 for 13 years and found that the risk of CVD was inversely connected to the LE8 score. Li et al. [23] also noted that a decreased risk of CVD was linked to a higher LE8 score. To date, the LE8 score has been used to evaluate conditions other than CVD, including depression, periodontitis, and chronic kidney disease [24–26]. And yet, our understanding of the relationship between LE8 and COPD remains limited. Using data from the National Health and Nutrition Examination Survey (NHANES) 2005–2018, this research explored the link between LE8 and the risk of COPD. Among individuals with COPD, we also examined the impact of LE8 on all-cause mortality.
Methods
Data sources and participant
NHANES is an all-encompassing survey that gathers important nutritional and health data from a cross-section of the US population. Incorporating complex survey design and weights into sampling is an important step in NHANES. Using these weights in the analysis helps to produce valid national estimates and ensures that the results are generalizable to the entire U.S. population [27]. NHANES 2005–2018 contained 70,190 individuals in all, as Fig. 1 illustrated. After excluding those under 40 years old, pregnant women, and individuals with incomplete COPD and LE8 data, 20,756 participants met the criteria and were enrolled in our study.
Fig. 1.
Flowchart for selecting eligible participants in the cross-sectional study from NHANES 2005–2018. NHANES, National Health and Nutrition Examination Survey; COPD, Chronic obstructive pulmonary disease; LE8, Life’s Essential 8
Diagnosis of COPD
COPD was diagnosed when any of the following conditions were fulfilled: (1) Participants were given an COPD diagnosis by a doctor or other medical specialist; (2) Following the administration of the bronchodilator, the individuals had a ratio of forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) below 0.70; (3) Participants were given an emphysema diagnosis by a doctor or other medical specialist; (4) Participants who had a record of chronic bronchitis were required to be over 40 years of age, have a history of smoking, and be currently using medications like inhaled corticosteroids, leukotriene modifiers, mast cell stabilizers, and selective phosphodiesterase-4 inhibitors.
Definition of LE8
CVH is measured using the LE8, which includes four health behaviors and four health factors. Health behaviors encompass a wide range of practices, including diet, nicotine exposure, physical activity, and sleep quality. Several components of health factors include body mass index (BMI), blood pressure, blood sugar, and non-high-density lipoprotein cholesterol. To evaluate dietary status, we used the Healthy Eating Index-2015 (HEI-2015) [28]. Employing the first 24-hour total nutrient intake recall interview from the NHANES database, the thirteen components of the HEI-2015 were evaluated (Table S1). The data required to assess the other seven indicators of the LE8 can be directly obtained from NHANES. A more comprehensive explanation of the scoring methodology for each LE8 component was provided in Table S2. The LE8 score is calculated by averaging eight indicators, each with a score ranging from 0 to 100. The following is the classification of CVH based on the LE8 score: High CVH is indicated by an LE8 score of 80 or more, moderate CVH by a score of 50 to 79, and low CVH by a score of less than 50 [17].
Demographic characteristics
Information on demographic characteristics was collected through the home interviews. Gender and race information can be obtained directly from the database. Age was categorized into the following two groups: <60 years and ≥ 60 years. The number of years of schooling was used to classify educational level into three groups: under high school, high school or equivalent, and college or above. Poverty-income ratio (PIR) fell into three categories: <1.3, 1.3–3.5, and > 3.5. Depending on whether or not they were partnered, participants’ marital status was categorized into two groups.
Mortality outcome
By linking to the National Death Index, we were able to obtain matched mortality data for each participant. The period between the date of the interview and the death, or December 31, 2019, was used to calculate the length of follow-up. The primary mortality outcome of our investigation was all-cause mortality in the COPD patients, which is defined as deaths from any cause.
Statistical analysis
Statistical analysis was performed with R software (version 4.3.1). To ensure that the sample represents the entire U.S. population, we applied weights in our data analysis. Continuous variables were represented using means with 95% confidence intervals (CI), and groups were compared using a weighted t-test. To compare categorical variables, which were presented as weighted percentages (%) and actual frequencies, a weighted chi-square test was used. We tested three weighted logistic regression models to see whether there was a correlation between greater LE8 scores and a reduced prevalence of COPD. Crude model was not adjusted; Model 1 was adjusted for age (continuous), gender, and race; Model 2 expanded upon Model 1 by including additional adjustments for factors such as educational level, PIR, and marital status.
The trend of COPD risk with changes in the LE8 score was evaluated using restricted cubic splines (RCS). Furthermore, we conducted subgroup analyses and interaction tests to examine the link between LE8 scores and COPD in different subgroups, as well as any differences between them. Following the exclusion of individuals with preexisting CVD, we reanalyzed the link between LE8 and COPD risk in the sensitivity analysis to assess the robustness of our findings. In the weighted logistic regression, the risk of developing COPD was expressed as odds ratios (ORs) for each 10-point increase in the LE8 score.
To examine the connection between the LE8 score and all-cause mortality in COPD patients, we used weighted Cox regression analysis. The survival probability of the low, moderate, and high CVH groups was assessed using the log-rank test and the Kaplan-Meier survival curve. The risk of all-cause mortality in COPD patients was reported as hazard ratios (HRs) for each 10-point rise in the LE8 score, based on the weighted Cox regression findings. P < 0.05 was considered statistically significant.
Results
Baseline characteristics
Included in this research were 20,756 participants with a weighted mean age of 57.9 (57.6,58.2) years. The weighted proportion of men to females was 46.6% and 53.4%, respectively. The COPD group included 1,551 people, with a prevalence incidence of 7.3% (weighted). For all individuals, the weighted mean LE8 score was 65.3 (64.8,65.8), with low, moderate, and high CVH weighted proportions of 14.5%, 68.8%, and 16.7%, respectively. Compared to the non-COPD group, the COPD group had a higher proportion of elderly individuals, males, non-Hispanic Whites, those with lower education levels, those living in poverty, and those without a partner (P < 0.05) (Table 1). Individuals without COPD showed higher LE8 scores and a larger percentage of high CVH than those with COPD. Except for BMI and blood lipids scores, which showed no statistical difference between the two groups, the scores for the other six components were higher in participants without COPD (Table 1).
Table 1.
Weighted clinical features of the participants
| Variables | Total (n = 20,756) |
COPD group (n = 1,551) |
Non-COPD group (n = 19,205) | P |
|---|---|---|---|---|
| Age, years, mean (95% CI) | 57.9 (57.6,58.2) | 62.6 (61.9,63.3) | 57.5 (57.2,57.9) | < 0.001 |
| Age strata, years, n (%) | < 0.001 | |||
| < 60 | 10,183 (58.4) | 503 (40.6) | 9,680 (59.8) | |
| ≥ 60 | 10,573 (41.6) | 1,048 (59.4) | 9,525 (40.2) | |
| Gender, n (%) | < 0.001 | |||
| Male | 9,988(46.6) | 907 (54.2) | 9,081 (46.0) | |
| Female | 10,768 (53.4) | 644 (45.8) | 10,124 (54.0) | |
| Race, n (%) | < 0.001 | |||
| Mexican American | 2,809 (5.7) | 70 (1.5) | 2,739 (6.1) | |
| Other Hispanic | 1,920 (4.2) | 82 (1.9) | 1,838 (4.4) | |
| Non-Hispanic White | 9,678 (74.1) | 1,038 (83.2) | 8,640 (73.4) | |
| Non-Hispanic Black | 4,577 (10.2) | 264 (7.0) | 4,313 (10.4) | |
| Other races | 1,772 (5.8) | 97 (6.4) | 1,675 (5.7) | |
| Educational level, n (%) | < 0.001 | |||
| Under high school | 5,240 (15.4) | 476 (22.7) | 4,764 (14.8) | |
| High school or equivalent | 4,847 (23.9) | 427 (29.8) | 4,420 (23.4) | |
| College or above | 10,669 (60.7) | 648 (47.5) | 10,021(61.8) | |
| PIR, n (%) | < 0.001 | |||
| < 1.3 | 5,260 (15.4) | 556 (25.6) | 4,704 (14.6) | |
| 1.3–3.5 | 7,334 (32.9) | 553 (35.6) | 6,781 (32.7) | |
| > 3.5 | 6,370 (44.8) | 326 (32.0) | 6,044 (45.8) | |
| Not record | 1,792 (6.9) | 116 (6.8) | 1,676 (6.9) | |
| Marital status, n (%) | < 0.001 | |||
| Married/ Living with partner | 12,943 (68.4) | 860 (62.0) | 12,083 (68.9) | |
| Widowed/ Divorced/ Separated/ Never married | 7,813 (31.6) | 691 (38.0) | 7,122 (31.1) | |
| LE8 score, mean (95% CI) | 65.3 (64.8,65.8) | 58.3 (57.2,59.3) | 65.8 (65.3,66.3) | < 0.001 |
| HEI-2015 diet score, mean (95% CI) | 42.3 (41.5,43.2) | 36.3 (34.2,38.4) | 42.8 (41.9,43.7) | < 0.001 |
| Physical activity score, mean (95% CI) | 66.6 (65.5,67.7) | 59.0 (55.8,62.2) | 67.2 (66.0,68.3) | < 0.001 |
| Nicotine exposure score, mean (95% CI) | 72.7 (71.7,73.7) | 43.5 (40.4,46.6) | 74.9 (74.1,75.8) | < 0.001 |
| Sleep health score, mean (95% CI) | 83.1 (82.5,83.6) | 77.9 (75.9,79.8) | 83.5 (82.9,84.1) | < 0.001 |
| BMI score, mean (95% CI) | 58.0 (57.2,58.8) | 59.6 (57.4,61.8) | 57.9 (57.0,58.8) | 0.133 |
| Blood lipids score, mean (95% CI) | 59.2 (58.6,59.8) | 59.4 (57.4,61.5) | 59.2 (58.5,59.9) | 0.823 |
| Blood glucose score, mean (95% CI) | 80.7 (80.1,81.3) | 74.8 (72.8,76.8) | 81.2 (80.6,81.8) | < 0.001 |
| Blood pressure score, mean (95% CI) | 60.8 (60.0,61.5) | 57.5 (55.3,59.7) | 61.0 (60.2,61.8) | 0.003 |
| CVH, n (%) | < 0.001 | |||
| Low (LE8 < 50) | 3,716 (14.5) | 506 (28.6) | 3,210(13.4) | |
| Moderate (50 ≤ LE8 < 80) | 14,372 (68.8) | 977 (66.1) | 13,395 (69.0) | |
| High (LE8 ≥ 80) | 2,668 (16.7) | 68 (5.3) | 2,600 (17.6) |
COPD, Chronic obstructive pulmonary disease; PIR, poverty-income ratio; LE8, Life’s Essential 8; CI, confidence interval; HEI-2015, Healthy Eating Index-2015; BMI, body mass index; CVH, cardiovascular health
Association between LE8 score and COPD
After accounting for all covariates, the weighted logistic regression analysis revealed that each 10-point increase in LE8 score was associated with a 25% reduction in the risk of developing COPD (P < 0.05). Both the moderate (OR = 0.52, 95% CI = 0.45–0.60, P < 0.001) and high (OR = 0.19, 95% CI = 0.14–0.27, P < 0.001) CVH groups demonstrated a notable decrease in the risk of COPD when compared to the low CVH group, according to the weighted logistic regression analysis of the fully adjusted model executed after LE8 scores were categorized according to the CVH. Also, the High CVH group had the lowest incidence of COPD (P for trend < 0.001) (Table 2). A linear negative association between LE8 scores and COPD was found in the RCS analysis (P for nonlinear = 0.475), with an elevating LE8 score corresponding to a lowering probability of COPD (Fig. 2).
Table 2.
Weighted logistic regression analysis of the correlation between LE8 scores and the prevalence of COPD
| Crude model | Model 1 | Model 2 | ||||
|---|---|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | |
| LE8 score (per 10 points) |
0.70 (0.67,0.74) |
< 0.001 |
0.71 (0.68,0.75) |
< 0.001 |
0.75 (0.71,0.79) |
< 0.001 |
| LE8 score categories | ||||||
| Low (LE8 < 50) | Reference | Reference | Reference | |||
| Moderate (50 ≤ LE8 < 80) | 0.45 (0.39,0.52) | < 0.001 |
0.46 (0.40,0.53) |
< 0.001 |
0.52 (0.45,0.60) |
< 0.001 |
| High (LE8 ≥ 80) |
0.14 (0.10,0.19) |
< 0.001 |
0.16 (0.11,0.22) |
< 0.001 | 0.19 (0.14,0.27) | < 0.001 |
| P for trend | < 0.001 | < 0.001 | < 0.001 | |||
Crude model, not adjusted; Model 1, adjusted for age (continuous), gender, race; Model 2, additionally adjusted for educational level, PIR and marital status. OR, odds ratio; CI, confidence interval; LE8, Life’s Essential 8
Fig. 2.
Restricted cubic spline curve (3 knots) to identify the relationship between LE8 scores and COPD. Solid red curves are multivariable-adjusted OR, with light red area showing 95% CI. The reference line for no association is indicated by horizontal dashed black line at a OR of 1.0. The vertical dashed black line represents the minimum threshold for beneficial associations. The association was adjusted for age (continuous), gender, race, educational level, PIR and marital status. OR, odds ratios; CI, confidence interval; LE8, Life’s Essential 8
LE8 components and COPD
As shown in Table 3, there were significant negative correlations between the HEI-2015 diet, physical activity, nicotine exposure, sleep health, blood glucose and blood pressure scores and the prevalence of COPD in the fully adjusted multivariate logistic regression model. For every 10-point increase in the scores of the above components, the ORs for COPD were 0.94, 0.98, 0.82, 0.94, 0.96, and 0.98, respectively (P < 0.05).
Table 3.
Associations between components of LE8 and COPD
| LE8 components (per 10 points) | OR (95% CI) | P |
|---|---|---|
| HEI-2015 diet score | 0.94 (0.92,0.96) | < 0.001 |
| Physical activity score | 0.98 (0.96,0.99) | 0.016 |
| Nicotine exposure score | 0.82 (0.80,0.84) | < 0.001 |
| Sleep health score | 0.94 (0.91,0.96) | < 0.001 |
| BMI score | 1.02 (1.00,1.04) | 0.091 |
| Blood lipids score | 1.00 (0.97,1.02) | 0.903 |
| Blood glucose score | 0.96 (0.94,0.99) | 0.007 |
| Blood pressure score | 0.98 (0.96,0.99) | 0.021 |
The association was adjusted for age (continuous), gender, race, educational level, PIR and marital status. LE8, Life’s Essential 8; OR, odds ratio; CI, confidence interval; HEI-2015, Healthy Eating Index-2015; BMI, body mass index
Subgroup analysis and interaction test
All subgroup analyses showed a negative association between LE8 scores and the risk of COPD (P < 0.05). A formal interaction test was conducted by including a multiplicative interaction term between LE8 score and age group (< 60 vs. ≥60 years) in the multivariable logistic regression model, which showed a statistically significant interaction (P for interaction = 0.009), suggesting age may modify the association between LE8 and COPD. In the stratified analysis, higher LE8 scores were significantly associated with lower odds of COPD among participants younger than 60 years (OR = 0.70, 95% CI: 0.64–0.76), while the association was weaker but still present in those aged 60 and above (OR = 0.79, 95% CI: 0.74–0.85) (Fig. 3).
Fig. 3.
Forest plot of the relationship between LE8 scores and COPD in subgroups. The association was adjusted for age (continuous), gender, race, educational level, PIR and marital status. OR was calculated as per 10-point increase in LE8 score. OR, odds ratios; CI, confidence interval; PIR, poverty-income ratio
Sensitivity analysis
2,588 individuals with a history of CVD (heart attack, angina, congestive heart failure, and coronary heart disease) were not included in the sensitivity analysis. The results of the weighted logistic regression model, which controlled for all covariates, were in agreement with the primary findings following the exclusion of individuals with a preexisting CVD (Table 4).
Table 4.
Sensitivity analysis of the association between LE8 scores and COPD
| Excluding participants with CVD history | |||
|---|---|---|---|
| Cases/participants | OR (95% CI) | P | |
| LE8 score (per 10 points) | 1,106/18,168 | 0.77 (0.72,0.81) | < 0.001 |
| LE8 score categories | |||
| Low (LE8 < 50) | 322/2,921 | Reference | |
| Moderate (50 ≤ LE8 < 80) | 728/12,713 | 0.54 (0.45,0.65) | < 0.001 |
| High (LE8 ≥ 80) | 56/2,534 | 0.21 (0.15,0.30) | < 0.001 |
| P for trend | < 0.001 | ||
The association was adjusted for age (continuous), gender, race, educational level, PIR and marital status. CVD, cardiovascular disease; OR, odds ratio; CI, confidence interval; LE8, Life’s Essential 8
To assess the robustness of our findings and minimize potential misclassification bias due to the composite definition of COPD, we conducted an additional sensitivity analysis restricting the outcomes to spirometry-confirmed COPD cases (FEV1/FVC < 0.70). The results remained consistent with the main analysis: higher LE8 scores were significantly associated with lower odds of spirometry-defined COPD (Table S3).
Relationship of LE8 score with all-cause mortality in people with COPD
Among the 1,551 COPD patients, one was excluded due to missing survival data, and ultimately, 1,550 were included in the survival analysis. To determine if the LE8 scores in COPD patients were connected to all-cause mortality, we used weighted Cox regression models. The findings demonstrated that the LE8 score (per 10 points) and all-cause mortality had a negative connection after controlling for all covariates (HR = 0.81, 95% CI = 0.74–0.89, P < 0.001) (Table 5). Compared to the low CVH group, all-cause mortality was significantly reduced in the moderate (OR = 0.74, 95% CI = 0.56–0.97, P < 0.001) and high (OR = 0.30, 95% CI = 0.16–0.58, P < 0.001) CVH groups, with the high CVH group having the lowest all-cause mortality (P for trend < 0.001) (Table 5). There were significant differences in the three groups’ survival probabilities as shown by the Kaplan-Meier curves, with the high CVH group having the highest probability of surviving (P < 0.001) (Fig. 4).
Table 5.
Weighted Cox regression analysis of the correlation between LE8 scores and all-cause mortality among individuals with COPD
| Crude model | Model 1 | Model 2 | ||||
|---|---|---|---|---|---|---|
| HR (95%CI) | P | HR (95%CI) | P | HR (95%CI) | P | |
| LE8 score (per 10 points) |
0.78 (0.72,0.85) |
< 0.001 |
0.80 (0.73,0.87) |
< 0.001 |
0.81 (0.74,0.89) |
< 0.001 |
| LE8 score categories | ||||||
| Low (LE8 < 50) | Reference | Reference | Reference | |||
| Moderate (50 ≤ LE8 < 80) |
0.65 (0.49,0.87) |
0.004 |
0.69 (0.53,0.91) |
0.009 |
0.74 (0.56,0.97) |
0.032 |
| High (LE8 ≥ 80) | 0.29 (0.15,0.54) | < 0.001 |
0.29 (0.15,0.56) |
< 0.001 |
0.30 (0.16,0.58) |
< 0.001 |
| P for trend | < 0.001 | < 0.001 | < 0.001 | |||
Crude model, not adjusted; Model 1, adjusted for age (continuous), gender, race; Model 2, additionally adjusted for educational level, PIR and marital status. HR, hazard ratio; CI, confidence interval; LE8, Life’s Essential 8
Fig. 4.
Kaplan-Meier survival curves of all-cause mortality among different CVH groups in the COPD patients. CVH, cardiovascular health; LE8, Life’s Essential 8
Discussion
We found a linear negative connection between the LE8 score and the probability of COPD. Subgroup analysis indicated that this negative correlation was more pronounced in individuals under 60 years of age. Furthermore, among COPD patients, there was a negative correlation between the LE8 score and all-cause mortality.
Several studies have investigated the link between LS7 and COPD, as far as we are aware. A multiethnic cohort study conducted in the US included 6,506 participants aged 45–84 years. On average, they followed people for 10.2 years before determining that people with higher LS7 scores were less likely to develop COPD [29]. To explore the relationship between LS7 and lung function as well as COPD, Fan et al. [30] analyzed clinical data from 6,352 adults over 20 years old and found that decreased risk of COPD and improved lung function were associated with higher LS7 scores. Our study found results consistent with the aforementioned research after replacing LS7 with LE8. To make sure the data was representative of the country as a whole, we used weighted analysis. The fully adjusted model’s weighted logistic regression analysis demonstrated an inverse correlation between LE8 score and the prevalence of COPD. RCS analysis also found a linear negative correlation between the two. After categorizing LE8 scores based on CVH, we discovered that the high CVH group had the lowest incidence of COPD. LE8 enhances health evaluation by incorporating more health factors, updating and refining existing metrics, and addressing modern health behaviors. These improvements over the LS7 make the LE8 an excellent tool for promoting and maintaining CVH [17].
The LE8 score is a composite measure that integrates eight metrics to provide a comprehensive assessment of an individual’s CVH. To date, there has also been much research on the relationship between these metrics and COPD. Scoditti et al. [31] pointed out that a Mediterranean diet, which is primarily based on vegetables and fruits, could maintain normal lung function and prevent the occurrence of COPD. A cohort study in Denmark found that smokers who were physically active had a decreased chance of acquiring COPD and a slower pace of lung function deterioration [32]. According to research by Baugh et al. [33], a lack of good quality sleep speeds up the worsening of COPD. Nicotine exposure has been widely established as the primary risk factor for COPD [12]. We separately investigated the relationship between each of the eight components of LE8 and COPD. After controlling for all covariates, we found that the above four health behaviors were negatively correlated with the prevalence of COPD. As for the association between the remaining four health factors and COPD, relevant studies have also provided answers. A study by Su et al. [34] followed 452,680 participants for 12.3 years and found that diabetes raised the likelihood of developing COPD. Rao et al. [35] noted that patients with COPD had the best prognosis and fewest cardiovascular events when blood pressure control was optimal. We also found a negative correlation between COPD risk and blood pressure and glucose scores. Verberne et al. [36] pointed out that being overweight or obese led to more metabolic complications in COPD patients. However, an umbrella review noted that low BMI was a COPD risk driver [37]. Although in our study, participants with COPD had higher BMI score compared to those without COPD, the difference was not statistically significant. As for the blood lipids score, there was no difference between individuals with or without COPD. Furthermore, we acknowledge the possibility of reverse causation in our findings, particularly in the cross-sectional model. For example, individuals with COPD may experience reduced physical activity and impaired sleep due to disease burden, which could in turn influence the observed associations [38, 39]. Therefore, we caution against drawing causal conclusions from these results, and recommend that future longitudinal or interventional studies further explore the directionality of these relationships.
We used subgroup analysis to find out how different populations’ LE8 scores were associated with COPD. The findings showed that the LE8 score and COPD incidence were negatively correlated in all subgroups, and this association was more pronounced among individuals under 60 years of age. Thus, it is evident that individuals aged 40–60 should maintain better CVH. Because a history of CVD might potentially influence the LE8 score and the findings of the research, we conducted a reanalysis after excluding people with a CVD history. This reanalysis confirms our study’s findings are stable and trustworthy, as they remain constant. A survey by Crisan et al. [40] examined the link between LS7 and mortality in COPD patients over 40 years old in the US. They discovered that reduced all-cause mortality was related to higher LS7 scores. The same conclusion was reached in our study. Individuals with COPD had a negative connection between LE8 score and all-cause mortality, according to the weighted Cox regression analysis of the fully adjusted model. The Kaplan-Meier curve also demonstrated that the group with high CVH had the highest survival probability. Therefore, even for individuals who have already developed COPD, maintaining good CVH is crucial as it can reduce all-cause mortality.
Although our study focused on the epidemiological association between LE8 and COPD, several biological mechanisms may underlie this relationship. Poor CVH is often accompanied by systemic inflammation, oxidative stress, and immune dysregulation, factors known to contribute to both cardiovascular and pulmonary diseases [41]. For example, elevated inflammatory markers such as CRP and IL-6 have been associated with reduced lung function, while oxidative stress may promote airway remodeling and alveolar damage [42, 43]. Dysregulated immune responses can further impair lung repair and increase susceptibility to respiratory insults [44]. These shared pathways may partly explain how maintaining ideal CVH could reduce COPD risk. Further studies incorporating biomarker data are needed to validate these mechanistic links. Breaking down LE8 into its individual components can also provide us with some insights. Intestinal flora creates short-chain fatty acids (SCFAs) while fermenting foods rich in fiber, such as vegetables and fruits. Reducing the likelihood of COPD, SCFAs control mucosal homeostasis and keep the lung immunological environment stable [45, 46]. In addition, dietary patterns rich in antioxidants and anti-inflammatory nutrients (e.g., fruits, vegetables, omega-3 fatty acids) may reduce lung inflammation and support immune homeostasis, whereas diets high in processed foods and saturated fats may exacerbate systemic and airway inflammation [31]. Insufficient physical exercise easily leads to persistent systemic inflammation, which may increase the risk of COPD [47]. Melatonin modulates the immune system, reduces inflammation, and acts as an antioxidant. The risk of COPD may be exacerbated by reduced melatonin production, which can be induced by poor sleep quality [48]. Moreover, sleep disturbances may trigger activation of the sympathetic nervous system and the hypothalamic-pituitary-adrenal axis, resulting in elevated oxidative stress. This heightened oxidative environment can cause injury to the airway epithelium and promote structural changes in lung tissue, thereby contributing to the pathogenesis of chronic respiratory diseases such as COPD [49]. Exposure to nicotine raises the risk of COPD by increasing the production of inflammatory cytokines, which in turn cause mucosal inflammation and oxidative stress [50]. Diabetes may promote COPD through chronic inflammation and pro-inflammatory factors [51]. Patients with hypertension who use beta-2 receptor blockers may suffer from COPD symptoms due to bronchial smooth muscle constriction [52].
Interventions targeting LE8 components, such as promoting physical activity, improving sleep hygiene, encouraging healthy dietary patterns, and supporting smoking cessation, may potentially be integrated into comprehensive public health strategies for the prevention and management of COPD. These modifiable lifestyle behaviors align with existing recommendations for chronic disease prevention and may offer additional benefits in reducing respiratory disease burden. However, given the cross-sectional design of our study, caution is warranted in interpreting the directionality and causality of these associations. The observed relationships between CVH and COPD do not imply a causal link, and residual confounding or reverse causation cannot be ruled out. As such, these findings should be considered hypothesis-generating, highlighting the need for future longitudinal and interventional studies to evaluate whether improving LE8 components can directly reduce COPD incidence or slow its progression.
The relationship between LE8 and COPD is being studied by us for the first time in the US population. We are also the first to examine the association between LE8 and all-cause mortality in COPD patients. New insights into the management and prevention of COPD in the US may be available from our research. However, our study is subject to certain limitations. Firstly, some components of the LE8 score, such as diet, physical activity, and sleep health, as well as COPD diagnosis, were based on self-reported data, which may lead to recall bias and misclassification. Future research should consider incorporating objective assessments (e.g., polysomnography, spirometry) to improve measurement accuracy. Secondly, Although NHANES provides nationally representative data for the U.S. population, our findings may not be directly generalizable to non-U.S. populations due to differences in genetics, environmental exposures, healthcare systems, and lifestyle factors. Thirdly, several important confounding factors were not available in our dataset, including occupational exposures, long-term air pollution exposure, early-life respiratory infections, and genetic predispositions, all of which are known to be associated with COPD risk. The absence of these variables may contribute to residual and unmeasured confounding. Fourthly, the LE8 scoring system assumes equal weighting of all eight components, which may not reflect their differential biological relevance to COPD. For example, tobacco exposure is a well-established and dominant risk factor for COPD, while other components such as blood lipids may play a less direct role. This uniform weighting may attenuate or obscure the true impact of more critical factors within the LE8 construct in relation to COPD outcomes. Lastly, due to the cross-sectional nature of our research, we were only able to determine correlations and not causations. Therefore, future longitudinal studies are necessary to validate these associations and to further investigate potential causal mechanisms.
Conclusions
This study adds to the growing evidence of an inverse association between LE8 scores and the prevalence of COPD, as well as a lower risk of all-cause mortality among COPD patients with higher LE8 scores. While these findings highlight the potential relevance of CVH to respiratory outcomes, the cross-sectional nature of the primary analysis precludes any causal inference. Therefore, the results should be interpreted as hypothesis-generating and underscore the need for future longitudinal and interventional studies to clarify the direction and mechanisms of these associations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We would like to thank the NHANES for making data publicly available.
Author contributions
Conceptualization: KW and XC. Methodology: KW and CL. Data curation: LH and CL. Writing-original draft: KW, CL and LH. Writing-review and editing: XC. Funding acquisition: XC. Supervision: XC. All authors contributed to the article and approved the submitted version.
Funding
This study received funding from the Sponsored by Science and Technology Innovation Enhancement Project of Army Medical University (STIEP 2022XQN33).
Data availability
The survey data are publicly available on the internet for data users and researchers throughout the world (https://www.cdc.gov/nchs/nhanes/index.htm).
Declarations
Ethics approval and consent to participate
The NCHS and the Centers for Disease Control and Prevention (CDC) carry out NHANES. The protocol for the NHANES study was examined and approved by the NCHS Research Ethics Review Committee. Written informed permission was signed by each participant.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Kang Wang, Chunyan Li and Lijun He contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The survey data are publicly available on the internet for data users and researchers throughout the world (https://www.cdc.gov/nchs/nhanes/index.htm).