Chronic obstructive pulmonary disease (COPD) is a heterogeneous lung disease characterized by persistent respiratory symptoms and airflow obstruction caused by abnormalities in the airways or alveoli (1). With high morbidity and disability rates, COPD has become the third leading cause of death globally (2), In 2019, there were 212 million cases of COPD worldwide, posing a serious burden on patients’ quality of life and public health (3, 4). Studies have shown that the etiology of COPD is complex, and in addition to genetic factors, environmental factors, especially lifestyle factors, play a crucial role in its development and progression (5, 6). Traditionally, smoking has been recognized as a major odds factor for COPD (7), but increasing evidence suggests that other lifestyle factors, such as an unhealthy diet (8, 9), physical inactivity (10), and obesity (11), may also be closely associated with the development of COPD. While COPD is treatable, it is not completely curable.

The American Heart Association introduced “Life’s Simple 7” and expanded it to “Life’s Essential 8” (LE8) and “Life’s Crucial 9” (lc9) to promote Cardiovascular health (12–14). The “lc9” builds on the American Heart Association’s “le8” by adding psychological health as an extra component (12). The nine elements of lc9 are Eat Better, Be More Active, Manage Weight, Manage Blood Sugar, Control Cholesterol, Manage Blood Pressure, Quit Tobacco, Get Healthy Sleep, and Address Psychological Health (15). These lifestyle indicators’ protective benefits for cardiovascular health are widely acknowledged in academia, and they have been demonstrated to lessen the odds of a variety of chronic illnesses. While the associations between LC9 scores and cardiometabolic conditions are well documented (16), their linkages to respiratory system disorders—especially COPD remain systematically underexplored in population-based studies.

LBM (LBM) is a reliable body measurement tool that incorporates data such as height, age, weight, and waist circumference (17). In recent years, it has gradually attracted the attention of researchers. LBM is not only associated with metabolic health, but it also plays a significant role in the prevention and management of chronic diseases (18). According to studies, those with more LBM typically have superior lung function, and they may also be at a lower odds of developing respiratory disorders (19, 20), particularly COPD. LBM has thus been identified as a possible protective factor against developing and progression of COPD. However, the potential mediating of LBM between lc9 and COPD has not been thoroughly investigated in the literature to date.

The aim of this study was to explore the relationship between lc9 and COPD using the National Health and Nutrition Examination Survey (NHANES) database, as well as to analyze the potential mediating of LBM in it. We hypothesize that high levels of lc9 score are associated with a lower odds of COPD, while LBM may play an suggestive mediating role in this relationship. This study analyzes the link between lc9, LBM, and COPD, providing a scientific basis for prevention and management. It also contributes to a better understanding of the role of LBM and lifestyle factors in chronic disease prevention and control, and serves as a reference for public health intervention strategies.

This study is a continuous cross-sectional study based on 7 cycles of NHANES data 2007-2020. There were 3 important findings. First, the lc9 score was negatively associated with the odds of COPD, and LBM had a suggestive mediating potential. Second, compared to the non-COPD group, the COPD group had lower levels of variables including health behaviors healthy (smoking, Sleep), health factors (non-HDL-C, blood glucose, blood pressure) and mental health (Depression). Additionally, White people had the highest percentage in the COPD group. Additionally, lc9 had interaction with race and was more protective for White people.

We observed that the levels of Smoking, Sleep, non-HDL-C, blood glucose, blood pressure, and Depression in the COPD group at baseline were lower than those in the normal group. Furthermore, white people accounted for the highest proportion within the COPD group. Prior studies have examined the correlation between le8 and COPD, noting that compared with the non-COPD group, the levels of physical activity, smoking, sleep health, blood lipids, blood glucose, and blood pressure in the COPD group were significantly lower (28). Moreover, the COPD group with higher levels of smoking and depression exhibited a higher odds of mortality (29). Additionally, a 3-month cohort study discovered that among COPD patients, the majority were male (94%) and white (91%), with a relatively higher proportion of white COPD patients (30, 31). These findings are analogous to ours. lc9 is a measure of CVH (12). The association between COPD and CVH has been well documented (26, 28). The possible reasons for the high proportion of white participants in the NHANES study are shown below. NHANES utilizes a complex stratified multistage probability cluster sampling design, which, although designed to ensure representativeness, may result in a higher proportion of white participants if certain minority neighborhoods are underrepresented in selected clusters or strata (32). Second, it is more difficult for low-income groups to coordinate time to participate in on-site inspections. Further, such as language barriers, cultural differences, and distrust of medical research. These factors may contribute to lower participation rates among minorities. A similar imbalance in racial distribution was found (33).

Our results that lc9 was negatively associated with the odds of COPD, and this association was consistent across the overall sample, subgroup analyses, and sensitivity analyses. From the perspective of epidemiologic studies, Liu et al. concluded that CVH is negatively associated with the odds of developing COPD (28), and that maintaining an optimal CVH level is beneficial in stopping the development of COPD (28). In a population ≥40 years old, the higher the le8 score the lower the odds of COPD (26). Additionally, ls7 scores have been associated with lung function as well as the prevalence of COPD (34).The lc9 score consists of four health behaviors (diet, physical activity, nicotine exposure, and sleep), four health factors (BMI, non-HDL-C, blood glucose and blood pressure), and mental health (depression) (12).The lc9 considers the roles of sleep and mental health in COPD and may capture overlapping odds factors for COPD development.

Specifically, the lc9 component has been associated with a reduced incidence of COPD. In terms of diet, higher diet quality (e.g., adherence to a Mediterranean dietary pattern) reduces COPD odds. However, adherence to Western dietary patterns, e.g., high amounts of meat or processed meats, saturated fatty acids, increases odds (35). Genetic evidence points that exercise promotes the differentiation of lung tissue stem cells, remodeling blood vessel formation and enhancing lung ventilation (36). Additionally, smoking is the most important environmental odds factor for COPD. Chronic inflammation induced by smoking will directly contribute to COPD by reducing insulin action and elevating blood glucose levels, leading to decreased lung function (37). Additionally, sleep deprivation is associated with mildly reduced FVC (-5%) and FEV 1 (-6%) (38). It has been noted that poor sleep quality are significantly associated with the severe COPD (39). Low LBM is associated with accelerated lung function decline in COPD patients, while the opposite is true for high LBM. (40). Abdominal obesity accumulates large amounts of visceral fat and increases the odds of COPD (41). The excess visceral fat is an excellent pro-inflammatory mediator that attracts inflammatory cells and amplifies the inflammatory process, leading to alterations in the structure of the small airways (42). Mechanistic studies have shown that lipid molecules and their metabolic processes may contribute to COPD development by increasing inflammatory substances (43). Additionally, oxidative stress in which hyperlipidemia induces mitochondrial damage produces excess reactive oxygen species that impair lung function (44). Patients with type 2 diabetes have been reported to be more likely to develop COPD (45). A retrospective study showed that dyslipidemia, fasting hyperglycemia, abdominal obesity, and hypertension, were independently associated with impaired lung function (46). Epidemiologic and genetic evidence agree that depression may play an important role in the prevalence of COPD, clearly indicating that depression may be an etiologic factor in COPD (47). In addition, pro-inflammatory cytokines (e.g., IL-6 and c-reactive protein) may play a role in the relationship between depressive symptoms and lung function in older adults, causing endothelial dysfunction and reduced alveolar function (48), promoting the development of COPD. In summary, the association of lc9 with COPD may reflect the role of systemic inflammation a common pathway linking cardiovascular and pulmonary pathologies. The elevated levels of C-reactive protein and IL-6 (both of which are associated with poor CVH indices) may promote alveolar destruction and airway remodeling through activation of matrix metalloproteinases (49). Our results extend the predictive value of lc9 from cardiovascular outcomes to the domain of COPD odds, suggesting that lc9 may play a dual role in COPD prevention. The ability of lc9 to reduce the odds of COPD was stronger than that of the lc9 component alone.

Our findings suggest that lc9 may alleviate COPD odds by improving LBM. cross-sectional pathway analysis indicated a potential mediating. LBM is a key indicator of muscle mass and metabolic health (50). LBM is associated with CVH, lung function and respiratory health (51, 52). Improving lifestyle and increasing LBM (53) can reduce COPD odds. Furthermore, epidemiologic and genetic evidence agree on a negative association between LBM and COPD and also support a unidirectional causal relationship (54). This finding suggests that increasing LBM may provide additional benefits for the prevention and management of COPD beyond traditional dietary and exercise interventions.

We found a nonlinear relationship between lc9 score and COPD odds. In other words, the OR of the lc9 score associated with COPD was significantly lower in the lower range of the corresponding score and subsequently stabilized at higher values. Although previous studies have shown a positive linear relationship between LS 7 scores and lung function (55), LE 8 showed a nonlinear negative correlation with spirometry or COPD (28). Furthermore, a NHANES study noted a linear negative association between LE 8 and odds of COPD (26). The inconsistent results may be due to the different age composition of the populations studied. When the study population was at ≥40 years old, CVH was linearly associated with the possibility of COPD. The reason is that inflammatory response is more pronounced in middle-aged and older groups, which may lead to a more direct and linear relationship between CVH indicators and disease odds (56). ROC results show low specificity and may be hindered in predicting disease. The findings suggest that LBM is an important node in the path between lc9 and COPD odds. Low-specificity models may produce a higher proportion of false-positive predictions in populations with lower disease prevalence. This may result in a discrepancy between the actual prevalence rate and the false positives that are misclassified by the model. This may be linked to inadequate subgroup sample sizes and limited inclusion of covariates.

The findings suggest a significant interaction of lc9 with race, with stronger protective associations for whites. Earlier uptake of smoking cessation interventions may result in greater gains for whites. Because higher smoking rates in other racial groups amplify the association of “nicotine exposure” indicators (e.g., smoking cessation) with protection in lc9. (57). African-American populations live in areas with higher mean annual PM2.5 concentrations than white people (57, 58), and PM2.5 is able to penetrate deep lung tissues, triggering oxidative stress and inflammatory responses that lead to mitochondrial dysfunction and lung injury (59), contributing to acute exacerbations of COPD (60). The anti-inflammatory capacity of lc9 metabolic indicators (e.g., BMI, glycemic control) may be weakened. Additionally, the assessment of depression in the lc9 (PHQ-9 scale) may underestimate the mental health burden of minorities, who are more likely to attribute psychological problems to physiological or social factors than to direct mood disorders (61). Hispanic immigrants (especially Mexicans), who are overrepresented in NHANES, may have systematically higher lc9 scores due to pre-immigrant health behavioral strengths (e.g., low processed food intake, high physical activity). This “initial health advantage” may mask the ability of lc9 scores to reduce the odds of COPD (62). This possible explanation helps to explain our findings.

This study has several strengths. First, it is a study based on coverage of different age, race, gender, and socioeconomic groups in the U.S. through stratified multistage probability sampling, and the results are generalizable to the entire country. Second, all laboratory tests were performed through a standardized process certified by the CDC, ensuring comparable and reliable data. Moreover, the study extends the predictive value of lc9 from cardiovascular outcomes to the COPD odds domain, bringing together standardized health indicators (lc9) that may play a dual role in COPD prevention. However, some limitations should not be ignored. First, this was a cross-sectional study and no causal association between lc9 and COPD could be inferred, and reverse causality cannot be ruled out in observational studies. Second, this study was based on a questionnaire, which may be subject to recall bias or social desirability bias. Some biomarkers (e.g., glucose, lipids) were based on single measurements only, which may not reflect long-term exposure levels. Additionally, the small sample sizes of some subgroups resulted in wide confidence intervals for the estimates, and the results need to be interpreted with caution. Further, NHANES excluded hospitalized patients and specific institutionalized populations, which may be subject to Newman’s bias and may lead to overrepresentation of healthy populations and underestimation of COPD odds. Moreover, this study relied on questionnaires and lacked sufficient follow-up data, thus limiting in-depth exploration of the association between lc9 and COPD. Importantly, despite adjusting for demographic and socioeconomic variables, unmeasured confounders (use of biomass fuels, air pollution, occupational history, genetic susceptibility, household pollution, environmental factors such as place of residence/zip code/geographic area, etc.) may influence the association between lc9 and COPD. Moreover, we did not consider associations with healthy migration in the NHANES study. Then, the specificity of the model in this study (49.50%, 53.70%, 56.72%) suggests that its ability to distinguish true-negative cases is limited, which may lead to an elevated false-positive rate. Finally, as the mediating potential accounted for a relatively small proportion, there may have been more important mediating potential factors explored. Notably, the results are difficult to generalize to other states and countries. The cross-sectional design precludes establishing temporal prioritization between LC9 and LBM. Although our findings are consistent with the hypothesis of experimental studies suggesting independent roles for LC9 and LBM in lung function, future longitudinal or interventional studies are needed to unravel their causal interactions.

In conclusion, our results suggest that the higher the lc9 score, the lower the odds of COPD, and that LBM plays an important mediating potential. Optimizing lifestyle factors, particularly enhancing LBM, may contribute to mitigating COPD odds. Based on cross-sectional study, the lc9 scoring system could serve as a tool to identify odds associations.