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Abstract
Background Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) is a condition characterised by the simultaneous presence of features of both asthma and COPD. The study aims to investigate the association between ACO and frailty among middle-aged and elderly populations, and identify the risk factors for frailty in individuals with ACO.
Methods We conducted a cross-sectional study with 34 403 eligible participants (aged ≥40 years) from the National Health and Nutrition Examination Survey 1999–2018 cycles. Participants were stratified into four groups: ACO, asthma, COPD and non-asthma/COPD. Frailty assessment was based on frailty index, generating frail and non-frail group. Univariate and multivariate survey-weighted logistic regression analysis were used to determine the association between ACO and frailty, and to identify the risk factors for frailty in ACO.
Results The frailty prevalence in participants with ACO was 60.2%, significantly higher than that in those with asthma (32.3%) and COPD (40.6%). In the unadjusted model, participants with ACO exhibited six-fold higher odds of frailty (OR 6.30, 95% CI 5.29 to 7.49), which was significantly greater than those with COPD (OR 2.84, 95% CI 2.46 to 3.28) and asthma (OR 1.99, 95% CI 1.80 to 2.18), using the non-asthma/COPD group as a reference. After adjusting for all confounders, participants with ACO had over four times higher odds of frailty (OR 4.48, 95% CI 3.53 to 5.71), still higher than those with asthma and COPD. The findings remained robust in sensitivity and subgroup analyses. Furthermore, hypertension, cancer, cardiovascular disease, chronic kidney disease and cognitive disorders were identified as risk factors for frailty among ACO participants, while higher income and education levels were protective factors.
Conclusion Patients (aged ≥40 years) with ACO were at a higher risk of frailty, regardless of age or sex, compared with those with asthma or COPD alone. Greater attention should be paid to patients with ACO, regardless of their age.
- Asthma
- Inflammation
- Pulmonary Disease, Chronic Obstructive
Data availability statement
Data are available in a public, open access repository.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
The prevalence of frailty is higher in those with chronic respiratory diseases and is associated with increased hospitalisation and mortality. Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO), an important subgroup of chronic respiratory diseases with characteristics of both asthma and COPD, bears a higher disease burden. While both asthma and COPD could increase the risk of frailty, the association between ACO and frailty has not yet been investigated.
WHAT THIS STUDY ADDS
Patients (aged ≥40 years) with ACO were at a higher risk of frailty, regardless of age or sex, compared with those with asthma or COPD alone. Hypertension, cancer, cardiovascular disease, chronic kidney disease and cognitive disorders were identified as risk factors for frailty among ACO participant, while higher income and education levels were protective factors.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
To the best of our knowledge, this is the first cross-sectional study to investigate the association between ACO and frailty, with the asthma, COPD and non-asthma/COPD as comparison. The study suggested that greater attention should be paid to patients with ACO, regardless of their age. Furthermore, identifying risk factors for frailty in ACO assists in risk stratification and early intervention, which could contribute to reducing the disease burden and reversing the frailty state.
Introduction
Frailty, which is characterised by loss of function in multiple systems, serves as an indicator of biological ageing.1 2 It encompasses cognitive, psychological and social dimensions beyond its physical aspect.3 A systematic review revealed that the pooled prevalence of physical frailty in community-dwelling older adults was 19.1%.4 There has been evidence that frailty contributes to the risk of falls, malnutrition, dementia and disability, associated with higher risk of hospitalisation and mortality.2 5 Noteworthily, frailty is dynamic, preventable and reversible to some extent,6 and may begin during middle age.7 Therefore, the International Conference of Frailty and Sarcopenia Research strongly recommended early identification, assessment and management of frailty to maximise the length and quality of survival.8 However, there is currently no consensus on the standardised measurement of frailty. Frailty index, which quantified frailty in the cumulative deficit model, is commonly used for assessment.9
Chronic obstructive pulmonary disease (COPD) and asthma have frequently been studied in the researches on frailty. The prevalence of frailty is higher in people with chronic respiratory diseases, ranging from 2.6% to 80.9% in COPD.10 Emerging evidence has demonstrated that the odds of frailty is approximately twofold higher in patients with COPD11; furthermore, the copresence of frailty and COPD is associated with a higher risk of exacerbation, hospitalisation, major adverse cardiovascular event and all-cause mortality.12 Landré et al found that patients with asthma were also more likely to be frail13; and the higher prevalence among asthmatic over 60 years old was associated with cumulative lifetime oral corticosteroid exposure.14 Although COPD and asthma are unique diseases with distinct characteristics, they can coexist in a given individual, which is more common in middle-aged and elderly populations (aged ≥40 years).15
The term ‘Asthma-COPD overlap (ACO)’ refers to a clinical condition characterised by the simultaneous presence of features of both asthma and COPD,16 which is a group of clinical characteristics not a single entity definition.17 18 Nevertheless, a widely accepted definition has not been established due to the complex pathophysiological mechanisms and multiple phenotypes in ACO.18 19 Based on data from North America, Europe and Asia, it was estimated that 2.0% of the general population, 26.5% of patients with asthma, and 29.6% of patients with COPD were diagnosed with ACO.20 Notably, patients with ACO experience more frequent symptoms of dyspnoea and exacerbations leading to hospitalisations, which are associated with higher healthcare costs and mortality rates compared with those with asthma or COPD alone.21–23 However, the association between ACO and frailty has not been extensively studied yet, and it is also unclear whether this association significantly differs from that of COPD and asthma. Given the dynamic reversible nature of frailty and its association with adverse outcomes, early identification and intervention of high-risk individuals who may develop frailty in patients with ACO is warranted.
Therefore, we predict that middle-aged and elderly patients with ACO are at a greater risk of frailty than those with asthma and COPD alone. To validate the hypothesis, a study was conducted on frailty and ACO among individuals aged 40 years and above, using data from the National Health and Nutrition Examination Survey (NHANES) database. The aims are as follows: (1) to describe the prevalence of frailty in participants with ACO, COPD, asthma and non-asthma/COPD; (2) to investigate the association of frailty with ACO and compare it with that with COPD and asthma and(3) to identify the risk factors of frailty in those with ACO.
Methods
Study population
The NHANES database uses a complex and multistage probability sampling design to represent the health and nutritional status of the population in the USA through personal interviews, physical examinations and laboratory tests. It covers demographic variables, lifestyle factors, anthropometric variables and medical comorbidities.24
The study used data from the NHANES 1999–2018 cycles (n=1 01 316), as the 2019–2020 cycle was incomplete due to the COVID-19 pandemic. Considering the prevalence of overlapping symptoms of both asthma and COPD was reported higher among individuals aged 40 and above,15 we included all participants in this age group (n=36 252). After excluding samples with a weight of 0, a total of 34 403 eligible participants were ultimately enrolled for the current analysis.
Definitions of asthma, COPD and ACO
Asthma was diagnosed if any of the following criteria were met: (1) participants were told to have asthma by a doctor or other health professional; (2) participants used antiasthmatic drugs; (3) participants with no history of smoking, chronic bronchitis and emphysema, aged younger than 40, used drugs including selective phosphodiesterase-4 inhibitors, mast cell stabilisers, leukotriene modifiers or inhaled corticosteroids.
COPD was diagnosed if any of the following criteria were met: (1) participants had a forced expiratory volume in 1 s/forced vital capacity (FVC) ratio <0.70 after inhaling β2-adrenergic bronchodilator medication; (2) participants were told to have emphysema by a doctor or other health professional and (3) participants with history of smoking and chronic bronchitis, aged 40 or over, used drugs including selective phosphodiesterase-4 inhibitors, mast cell stabilisers, leukotriene modifiers, inhaled corticosteroids.
Participants who met the at least one criterion from the definition of asthma and COPD were diagnosed as ACO. And those without a diagnosis of either asthma or COPD were diagnosed as non-asthma/COPD.
Diagnosis of frailty
We quantified frailty through the frailty index following the procedure and principle presented by Searle et al.25 The frailty index contained 49 variables in multiple systems, including cognition, dependence, depressive symptoms, comorbidities, general health condition and hospital utilisation, physical performance and anthropometry, and laboratory test values.26 The 49 variables were health deficits that generally increase with age but do not saturate too early. All deficits (ordinal, continuous and binary) were denoted as a value between 0 (not present) and 1 (maximally present), according to the severity. The frailty index was finally calculated by dividing the actual scores of the deficits by 49 (the total number of included deficits). A frailty index score of 0.21 has been established as the threshold for identifying ‘frail’ individuals who are at an increased risk of hospital-related events.27 28 The 49 variables in the frailty index and their respective values were shown in online supplemental table 1.
Supplemental material
Covariates
Covariates, including age, sex, ethnicity, education level, family income-to-poverty ratio (PIR), smoking, alcohol intake, physical activity and comorbidities, were self-reported through standardised questionnaires in household interviews. Body weight and height were measured through physical examinations at a mobile examination centre; and body mass index (BMI) was calculated by dividing weight in kilograms by height in metres squared. Blood eosinophils count (BEC), the result of laboratory tests, was divided into two groups according to the cut-off value of 300 cells/µL.29
Age was expressed as a continuous variable. Sex (male and female), ethnicity (Hispanic, non-Hispanic white, non-Hispanic black and other), education level (below high school, high school and above high school) and BMI (<25 kg/m2, 25–29.9 kg/m2, ≥30 kg/m2) were presented as categorical variables. In addition, the PIR, calculated as family income divided by the poverty guidelines,30 was categorised into three levels: low income (PIR<1.3), medium income (1.3≤PIR<3.5) and high income (PIR≥3.5).31 Corresponding to the NCHS classification standard, smoking status was divided into never (less than 10 cigarettes during lifetime), former (equal to or more than 100 cigarettes but did not smoke at the time of the survey) and now (equal to or more than 100 cigarettes and smoked cigarettes at the time of the survey). Base on the frequency, alcohol intake was divided into never, mild (≥1 drinks per day for females, ≥2 drinks per day for males), moderate (≥2 drinks per day for females, ≥3 drinks per day for males, or binge drinking (≥4 drinks on same occasion for females, ≥5 drinks on same occasion for males) ≥2 days per month), heavy (≥3 drinks per day for females, ≥4 drinks per day for males or binge drinking).32 According to the International Physical Activity Questionnaire, physical activity was classified as 0 to <600 metabolic equivalent task minutes per week (MET-min/week), 600 to <1200 MET-min/week and ≥1200 MET-min/week, representing low, medium and high, respectively.33 However, due to over 30% missing data on physical activity, this variable was removed from multiple imputation. More detailed explanation for covariate acquisition process is accessible on the official website of NHANES.
Statistical analysis
Statistical analysis was conducted with the application of recommended NHANES sample weights to ensure the representativeness of results. The missing values were imputed by multiple imputation based on five replications to maximise statistical power and minimise bias caused by data excluded from analyses34 (online supplemental table 2).
According to the results of normality test, mean±SD was used to depict continuous variables that followed a normal distribution; while median (Q1, Q3) was used for those that did not follow a normal distribution. Categorical variables are presented in terms of frequency (n) and proportion (%). We employed one-way analysis of variance for continuous variables and χ2 test for categorical variables in order to compare the baseline characteristics among different groups (ACO, asthma, COPD and non-asthma/COPD).
We initially created a stacked bar chart to illustrate the differences in the distribution of frailty in groups (ACO, asthma, COPD and non-asthma/COPD). The frailty assessment was conducted following frailty index and participants were categorised as non-frail (score <0.21) and frail (score ≥0.21). Furthermore, survey-weighted logistic regression analysis was employed to infer the effects (OR) and 95% CI of ACO on frailty, in comparison with asthma, COPD and non-asthma/COPD. To eliminate potential confounding effects, three models were built in multivariate logistic regression. Model 1 adjusted for age, sex, ethnicity, educational level, PIR, smoking, and alcohol intake. Model 2 adjusted for covariates in model 1 plus BMI and BEC. Model 3 adjusted for all covariates, including that in Model 2 plus comorbidities (hypertension, diabetes, cancer, cardiovascular disease (CVD), chronic kidney disease (CKD), and cognitive disorders). To ensure the robustness of the results, we conducted a sensitivity analysis on the complete dataset (n=17 842) through excluding participants with missing data. In addition, we assessed the association in different subgroups, including age (<65 and ≥65 years) and sex (male and female).
To identify the population at high risk of developing frailty among the participants with ACO, potential risk factors were explored through survey-weighted logistic regression analysis to determine their cross-sectional associations with frailty. The potential risk factors, including age, sex, ethnicity, education level, PIR level, smoking status, alcohol intake, BMI, BEC and comorbidities (hypertension, diabetes, cancer, CVD, CKD and cognitive disorders), were compared between frail and non-frail groups among participants with ACO (n=992). We used a univariate regression model with all the variables to eliminate non-significant factors. Subsequently, a multivariate analysis was conducted using variables that were statistically significant in univariate logistic regression to identify the risk factors associated with frailty in ACO participants.
Statistical analyses were conducted with R software (V.4.2.1); and p values <0.05 were deemed statistically significant.
Patient and public involvement
Patients were not involved in the planning and conduct of this research.
Results
Baseline characteristics
The study ultimately comprised 34 403 eligible participants (aged ≥40 years), among whom 992 individuals were diagnosed with ACO (see flow chart in figure 1). Baseline characteristics of all participants were presented in table 1. The mean age of participants diagnosed with ACO was 61 years, which was comparatively lower than that of those diagnosed with COPD (63.1 years), but relatively higher than that of individuals diagnosed with asthma (56 years) and those without a diagnosis of either asthma or COPD (57.5 years). Compared with participants with a sole diagnosis of asthma or COPD, as well as those without either condition, individuals diagnosed with ACO exhibited a higher prevalence of low-income status (32.0%), overweight/obesity (76.1%), BEC≥300 cells/µL (38.7%), hypertension (66.8%), diabetes (23.0%), CVD (33.8%) and cognitive disorders (18.2%).
Flow chart of data collection and processing. ACO, asthma-COPD overlap; COPD, chronic obstructive pulmonary disease; NHANES, National Health and Nutrition Examination Survey.
Baseline characteristics of participants (n=34 403)
The prevalence of frailty and cross-sectional association of ACO with frailty
As illustrated in figure 2 using a stacked bar chart, the distribution of frailty was significantly different among ACO, asthma, COPD and non-asthma/COPD (p<0.0001). 60.2% of participants with ACO fulfilled the diagnostic criteria of frailty, as determined by the frailty index, higher than participants with COPD (40.6%), asthma (32.3%) and non-asthma/COPD (19.4%).
Prevalence of frailty in ACO, Asthma, COPD and non-asthma/COPD. Frailty was defined using frailty index: non-frail (<0.21) and frail (≥0.21). ACO, asthma-COPD overlap; COPD, chronic obstructive pulmonary disease.
As presented in table 2, the logistic regression results indicated that participants with ACO had a higher risk of frailty compared with those with COPD, asthma and non-asthma/COPD. In the unadjusted model, participants with ACO exhibited sixfold higher odds of frailty (OR 6.30, 95% CI 5.29 to 7.49; p<0.0001), which was significantly greater than those with COPD (OR 2.84, 95% CI 2.46 to 3.28; p<0.0001) and asthma (OR 1.99, 95% CI 1.80 to 2.18; p<0.0001), using the non-asthma/COPD group as a reference. After adjusting for potential confounders, the association persisted. In model 3, with all covariates adjusted, participants with ACO had over four times higher odds of frailty (OR 4.48, 95% CI 3.53 to 5.71; p<0.0001) compared with the non-asthma/COPD group, which was higher than those with asthma (OR 1.78, 95% CI 1.55 to 2.03; p<0.0001) and COPD (OR 2.12, 95% CI 1.76 to 2.55; p<0.0001), indicating a greater risk of frailty associated with ACO.
Associations of frailty with ACO, COPD and Asthma (n=33 403)
Sensitivity analysis and subgroup analysis
To ensure the robustness of our findings, we performed a sensitivity analysis on the complete dataset (n=17 842) by eliminating the participants with missing data on covariates. Distribution of frailty in the four groups (ACO, asthma, COPD and non-asthma/COPD) followed the same trend when using two approaches to manage missing data (see online supplemental figure 1). The prevalence of frailty was significantly higher in ACO participants compared with those with asthma, COPD and non-asthma/COPD. The survey-weighted multivariate logistic regression results in online supplemental table 3 indicated that ACO was associated with a higher risk of frailty than asthma or COPD alone, regardless of whether multiple imputation or complete data were used (see online supplementary appendix).
As demonstrated in online supplemental table 4, the positive association of ACO with frailty remained robust across age (<65 and ≥65 years) and sex (male and female) subgroups. Furthermore, consistent with the findings of the overall population analysis, participants with ACO still had a higher risk of frailty than those with COPD and asthma alone within various subpopulations.
Risk factors for frailty in those with ACO
The differences between frail and non-frail participants with ACO were shown in online supplemental table 5. After univariate logistic regression, ethnicity, PIR level, education level, smoking, alcohol intake, hypertension, diabetes, cancer, CVD, CKD and cognitive disorders were included in multivariable logistic regression model (table 3). Combining univariate and multivariate logistic regression, the frail participants with ACO exhibited positive associations with hypertension (adjusted OR (aOR): 1.868, 95% CI 1.164 to 2.996; p=0.010), cancer (aOR 2.094, 95% CI 1.185 to 3.697; p=0.011), CVD (aOR 5.431, 95% CI 3.401 to 8.672; p<0.0001), CKD (aOR 2.233, 95% CI 1.365 to 3.655; p=0.002) and cognitive disorders (aOR 12.655, 95% CI 5.447 to 29.401; p<0.0001). The high-income group was almost 76% less likely to be frail (aOR 0.244, 95% CI 0.133 to 0.446; p<0.0001) and the medium-income group was almost 50% less likely to be frail (aOR 0.500, 95% CI 0.309 to 0.811; p=0.005), compared with those in the low-income group (table 3). Moreover, ACO participants with education above high school exhibited a 53% lower risk of frailty (aOR 0.470, 95% CI 0.223 to 0.993; p=0.048) compared with those with education below high school (table 3).
Analysis of risk factors related to frailty in ACO (n=33 403)
Discussion
Research basis, findings and significance
ACO is an important subgroup of chronic respiratory diseases with characteristics of asthma and COPD, bearing a higher disease burden.35 The loss of muscle mass, muscle strength14 36 and nutrient intake,4 as well as many other extrapulmonary complications that may occur in asthma and COPD, are all components of frailty. Regarding frailty measurement, we have opted for the cumulative deficit model and employ the frailty index to identify frail individuals. Compared with another commonly used frailty scale (the phenotype model), the frailty index defines frailty not only by physical limitations, but also by the accumulation of clinical indicators, psychological disorders and social impairments.
Based on the NHANES database, the study revealed a frailty prevalence of 60.2% in participants with ACO, which was significantly higher than that observed in those with asthma and COPD. The prevalence of frailty varied greatly from previous studies due to different diagnostic criteria and study population.37 Consistent with previous studies, asthma (aOR 1.78, 95% CI 1.55 to 2.03; p<0.0001)13 and COPD (aOR 2.12, 95% CI 1.76 to 2.55; p<0.0001)11 were found to increase the risk of frailty. Notably, ACO was significantly more strongly associated with frailty than either asthma or COPD (aOR 4.48, 95% CI 3.53 to 5.71; p<0.0001). By eliminating the participants with missing data on covariates, the association remained stable in the sensitivity analysis on the complete dataset. Moreover, according to the results of subgroup analysis, the association had clinical significance not only in adults over 65 years old (aOR 4.05, 95% CI 2.85 to 5.76; p<0.0001) but also in middle-aged adults (aOR 5.00, 95% CI 3.66 to 6.84; p<0.0001). Furthermore, among the ACO participants, hypertension, cancer, CVD, CKD and cognitive disorders were identified as risk factors for frailty. Additionally, higher income and education levels were found to be protective factors.
To the best of our knowledge, this is the first cross-sectional study to investigate the association between ACO and frailty, with the asthma, COPD and non-asthma/COPD as comparison. In addition, previous research on frailty has primarily concentrated on the older adults aged above 65 years old, with less emphasis placed on those in middle age. As the prevalence of ACO was reported higher among individuals aged 40 and above,15 we limited the study population to those who were 40 years old or older. The finding that the risk of frailty is greatly increased in participants with ACO than those with asthma or COPD alone enriches the understanding of ACO and frailty. This supports the previous notion that patients diagnosed with ACO carry a heavier disease burden, highlighting the importance of identifying patients exhibiting features of both asthma and COPD. Furthermore, early identification of ACO patients in a frail state aids in risk stratification and management, thereby reducing the disease burden according to the risk factor analysis in ACO participants.
Interpretation
So far, evidence fails to explain the pathophysiological mechanism behind persistent expiratory airflow limitation in patients with ACO, and whether ACO develops through a unique pathophysiological mechanism different from asthma or COPD remains to be determined.38 According to the results of three-dimensional CT analysis, ACO with consistent airway narrowing throughout the inspiratory and expiratory phases, had higher respiratory resistance, greater airway narrowing, more severe small airway dysfunction, and fewer emphysematous changes than COPD.39 This may be the structural basis for the more severe respiratory symptoms and chronic complications in ACO. Further, studies on histological features have shown that compared with COPD, ACO exhibits greater airway responsiveness, higher BEC levels and exhaled breath nitric oxide concentrations.40 41 This suggested that an inflammatory response mediated by T-helper 2 was one of the pathological features of ACO. Ferrucci and Fabbri42 found that inflammation was correlated with an increased risk of frailty and other adverse outcomes (including CVD, multimorbidity and premature death). This correlation occurs through inhibiting growth factors, increasing catabolism, and interfering with homeostatic signalling. Overall, ACO patients may be more vulnerable to frailty due to more severe airway remodelling, inflammation and multisystem complications. However, a more precise explanation remains to be explored.
Comparison with the former studies and the strengths
Previous research on frailty mainly focused on the older adults (≥65 years), among whom frailty was more common, but rarely took middle-aged adults into account.7 Besides, previous researches investigated frailty in patients with asthma or COPD; however, they ignored the association between ACO and frailty. Our analysis first demonstrated middle-aged and older ACO patients were at a higher risk of frailty, regardless of age or sex, compared with those with asthma or COPD alone.
Another strength of the current study was the use of a relatively large and nationally representative sample size data from the NHANES, facilitating generalisation of our findings. Comprehensive information about demographic characteristics, diet and lifestyle factors, anthropometric measures, and laboratory tests results enabled us to control for potential confounding factors. Furthermore, regarding the handling of missing data, multiple imputation maximised statistical power and minimise bias caused by data excluded from analyses. Sensitivity analyses on the complete data successfully verified the robustness of the results.
Limitation and future directions
The study also has limitations to be addressed in the future. First, the cross-sectional study failed to confirm the causality and inevitably generated recall bias due to the self-reported medical history and other personal information. Second, frailty is a dynamic concept, so the causal association of ACO with transition in frailty status need to be further studied. Furthermore, pulmonary function values as possible confounders were not included in the analysis, because few values were available especially those postbronchodilator. Meanwhile, the diagnosis of asthma, COPD and ACO were mainly based on questionnaire survey due to the lack of laboratory data related to respiratory function, which inevitably produces selection bias. Additionally, ACO is a heterogeneous condition with different characteristic phenotypes.29 Therefore, precise analysis of different subtypes should be performed in future studies.
Conclusion
Frailty is common in chronic respiratory diseases and requires early recognition and intervention. Patients (aged ≥40 years) with ACO were at a higher risk of frailty, regardless of age or sex, compared with those with asthma or COPD alone. Comorbidities, containing hypertension, cancer, CVD, CKD, and cognitive disorders, were identified as risk factors for frailty among ACO participants, while higher income and education levels were found to be protective factors. The study suggested that greater attention should be paid to patients with ACO, regardless of their age. Furthermore, identifying risk factors for frailty in ACO assists in risk stratification and early Intervention, which could contribute to reducing the disease burden and reversing the frailty state.
Data availability statement
Data are available in a public, open access repository.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and the NHANES programme was reviewed and approved by the Research Ethnics Review Board of the National Centre for Health Statistics. The participants provided their written informed consent to participate in this study. This analysis involving deidentified data with no direct participant contact is not considered to be human subjects research and was not subject to institutional review board review, based on National Institutes of Health policy. The Ethics Committee of the First Affiliated Hospital of Nanjing Medical University reviewed and approved the cross-sectional study (2023-QT-02). Participants gave informed consent to participate in the study before taking part.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors XW and XQ conceived the idea of the study. XW provided major contributions via performing the data analysis and finishing the manuscript. JW, SG and LZ assisted in the data analysis and confirmed the accuracy. XQ performed critical reviews of the articles. XQ is responsible for the overall content as the guarantor. All authors read and approved the final manuscript.
Funding This work was sponsored by the General Project of Jiangsu Provincial Health Commission (No. H2019029), the Jiangsu Province Six One Project (No. LGY2018054), the “Six talent peaks” high-level talents level B (No. WSN-015), and the 333 High-level personnel Training Programme.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.