Skip to main content
Download PDF

Associations between sarcopenia with asthmatic prevalence, lung function and comorbidity

BMC Geriatrics volume 22, Article number: 703 (2022) Cite this article

Abstract

Background

Sarcopenia is listed as a treatment trait in behavioral/risk factors for severe asthma, but studies on asthma and sarcopenia are lacking. This study aimed to determine the associations between sarcopenia with asthmatic prevalence, symptoms, lung function and comorbidities.

Methods

Fifteen thousand four hundred four individuals from the China Health and Retirement Longitudinal Study(CHARLS) and 10,263 individuals from the Study on global AGEing and adult health(SAGE) in China were included in this study. Four components of this study were used to assess the bidirectional association in the prevalence between sarcopenia with asthma, and estimate the relationships between sarcopenia with asthmatic symptoms, lung function and comorbidities via generalized additive models. The 10-item Center for Epidemiological Studies–Depression Scale ≥ 12 scores was classified as depression.

Results

In the CHARLS and SAGE, the prevalence of sarcopenia in asthmatics was higher than those without asthma. Asthmatics with sarcopenia had a significantly increased prevalence of severe shortness of breath(sarcopenia yes vs. no, adjusted OR = 3.71, 95%CI: 1.43–9.60) and airway obstruction in the SAGE(sarcopenia yes vs. no, adjusted OR = 6.82, 95%CI: 2.54–18.34) and an obvious reduction of PEF in the CHARLS and SAGE(sarcopenia yes vs. no, adjusted RR = 0.86, 95%CI: 0.82–0.91) compared to asthmatics without sarcopenia. The presence of sarcopenia was positively associated with the prevalence of chronic obstructive pulmonary disease(sarcopenia yes vs no, adjusted OR = 5.76, 95%CI:2.01–16.5) and depression(sarcopenia yes vs no, adjusted OR = 1.87, 95%CI:1.11–3.14) in asthmatics.

Conclusions

Our findings indicated that sarcopenia partakes in the development of asthma by affecting lung function and comorbidities and maybe considered a treatable trait of asthma management.

Peer Review reports

Introduction

In 2018, approximately 339 million individuals suffered from asthma with respiratory symptoms and sudden episodes of airflow limitation worldwide [1]. Frequent exacerbations of asthma place a substantial physiological and economic burden on patients and their families and can even lead to disability and mortality. Worsening lung function and comorbidities (such as depression and chronic lung diseases) are two independent risk factors for asthmatic exacerbations [1]. In recent years, treatable traits have been regarded as a new paradigm for asthma management, with one key paradigm involving the early identification of pulmonary, extrapulmonary, and behavioral/risk factors related to asthmatic exacerbations [2,3,4,5]. A recent study demonstrated that targeting treatable traits may reduce acute exacerbations, and improve the quality of life and asthma control in individuals with severe asthma [2].

Sarcopenia is defined as an age-related loss of skeletal muscle mass plus loss of muscle strength and/or reduced physical performance with the age cut-off values at either 60- or 65-years-old in the Asian Working Group for Sarcopenia (AWGS) 2019 [6]. The diagnosis of sarcopenia requires to have the measurement of appendicular skeletal muscle mass(ASM), muscle strength and physical performance. According to the AWGS 2014 criteria, the prevalence of sarcopenia ranges from 5.5% to 25.7% with a male predominance. The AWGS 2019 criteria recommended that the cut-off value of gait speed has increased from 0.8 m/s to < 1.0 m/s [6], which may increase the prevalence of sarcopenia. Sarcopenia with muscle fiber atrophy may cause immune senescence [7], the deterioration of respiratory force generation [8] and pulmonary function [9], frailty [10], depression and mortality [10] in the general population. In the study of McDonald et al., sarcopenia was regarded as a treatment trait in behavioral/risk factors for severe asthma. However, studies about the associations between sarcopenia with asthmatic prevalence, lung function and comorbidities are lacking.

It can be hypothesized that muscle fiber atrophy and weakness secondary to sarcopenia can potentially lead to the impairment of respiratory function, physical activity limitations and the increasing risk of developing depression or comorbidities in individuals with asthma. By using two national population-based studies in China, we evaluated the associations in the prevalence between sarcopenia with asthma. Subsequently, this study determined whether sarcopenia and its severity are associated with the reduction of lung function in elderly individuals with asthma. Finally, we investigated whether sarcopenia has significant relationships with comorbidities via generalized additive models.

Methods

Study population

The China Health and Retirement Longitudinal Study(CHARLS) was initiated between June 2011 and March 2012 and involved 17,708 individuals aged more than 45 years, which represented a national population-based health, social and economic status with encompassing 450 urban or rural areas in 28 provinces of China. The CHARLS used a face-to-face computer-assisted personal interview (CAPI) with physical measurements, blood sample collection, and depression assessments. Follow-ups were conducted every 2 years with the participation of new individuals in the CHARLS. The Biomedical Ethics Review Committee of Peking University approved the CHARLS. Written informed consent was collected at the National School of Development of Peking University. More detailed description of the CHARLS has been reported elsewhere [11] and can be found via the following link: https://charls.charlsdata.com/pages/Data/2018-charls-wave4/zh-cn.html (accessed on 30 May 2022).

The Study on global AGEing and adult health(SAGE) was designed by the World Health Organization(WHO), and this initiative planed to assess and compare the health status and socioeconomic consequences of adult populations and the ageing process in six countries(China, Ghana, India, Mexico, Russian Federation and South Africa) worldwide. The SAGE in China wave 1 was conducted between 2007 and 2010, involved 15,050 individuals and covered the eight provinces. In 2012, the data involving 19 districts in Shanghai and 9524 individuals were included in the SAGE. The WHO Ethical Review Committee and local ethics research review boards approved ethical and obtained written informed consent. ALL of the information and data can be found in a previous study [12] and via the following link: https://apps.who.int/healthinfo/systems/surveydata/index.php/catalog/sage (accessed on 30 May 2022).

Definition of asthma, sarcopenia and depression

The diagnosis of asthma was based on a positive answer of the following question: “Have you ever been diagnosed with asthma by a doctor”. In the WHO SAGE, we collected the relevant data about asthmatic medication treatments and symptoms (attacks, awakening, and severe shortness of breath) in the past 12 months. Severe shortness of breath was based on a positive answer of the following question: “Have you had an attack of shortness of breath that came on without obvious cause when you were not exercising or doing some physical activity?”.

According to the recommendation of the AWGS 2019 [6], muscle strength and physical performance in the diagnosis of sarcopenia were measured by using handgrip strength (< 28.0 kg for men and < 18.0 kg for women) and gait speed (< 1.0 m/s) in the CHARLS and WHO SAGE. In addition, the CHARLS also provided 5-time chair stand test to measure low physical performance(≥ 12 s). The following anthropometric equation for the height-adjusted muscle mass (ASM/Ht2) can be used to determine whether low ASM existed in the Chinese population [6, 13]: ASM/Ht2 = (0.193*body weight + 0.107* height- 4.157* gender -0.037*age-2.631)/ height2. Similar to previous studies [14,15,16], the cut-off value for defining low muscle mass was based on the ASM/Ht2 of the lowest 20th percentile of the study population. Therefore, ASM/Ht2 < 6.92 for men and < 5.14 for female were regarded as low ASM. The age cut-off value of sarcopenia was set at 60-years-old [6]. Low ASM with low muscle strength or physical performance were defined as sarcopenia, meanwhile patients with severe sarcopenia were associated with low ASM, muscle strength and physical performance [6].

The CHARLS assessed whether depression existed by using the 10-item Center for Epidemiological Studies–Depression Scale (CES-D10). The 10 items with 4 four answer options were used to estimate the depressive feelings and behaviors of individuals over one week, and a value of 0–3 was assigned to each answer. Previous studies identified that the CES-D10 harbors adequate reliability and validity in the assessment of depression for the community-dwelling older Chinese population [17]. The CES-D10 ≥ 12 scores with total scores ranging from 0 to 30 scores were considered to indicate depression [17, 18].

Variables

In the CHARLS, this study included the following demographic characteristics as adjusted confounding factors: sex, age, region, urban/rural, marital status, alcohol use, smoking, body mass index(BMI), night sleep duration and thirteen physician- diagnosed comorbidities (hypertension, dyslipidemia, hyperglycemia, cancers, chronic lung diseases, liver diseases, heart diseases, stroke, kidney diseases, digestive diseases, emotional or psychiatric problems, memory-related diseases, and arthritis or rheumatism). Lung function was measured through peak expiratory flow(PEF) in the CHARLS.

In the WHO SAGE, the following variables were used to adjust the associations between asthma and sarcopenia: sex, age, region, urban/rural, married status, alcohol, smoking, vigorous-intensity activity, moderate-intensity activity, BMI, night sleep duration, hypertension, diabetes, angina, stroke, chronic lung diseases and arthritis. This study evaluated lung function in individuals with asthma through the following variables: forced expiratory volume in the first second (FEV1), FEV1/forced vital capacity(FVC), PEF, forced expiratory flow rate, mid-exhalation (FEF25%–75%). FEV1/FVC < 0.7 was regarded as airway obstruction. Individuals with chronic lung diseases and FEV1/FVC < 0.7 were diagnosed as having chronic obstructive pulmonary disease (COPD).

For Chinese adults, BMI was divided into four groups: underweight (< 18.5 kg/m2), normal (18.5 to < 24.0 kg/m2), overweight (24.0 to < 28.0 kg/m2), and obesity (≥ 28.0 kg/m2) [19]. Age was divided into three groups: 60–69 years, 70–79 years, and 80 years and above. More detailed groups of all the variables are shown in Tables 1 and 2.

Table 1 The characteristics of study population in the China Health and Retirement Longitudinal Study
Full size table
Table 2 The characteristics of study population in the Study on global AGEing and adult health from China
Full size table

Statistical analysis

Study populations were categorized into three groups: no sarcopenia, non-severe sarcopenia and severe sarcopenia. SPSS described the categorical variables by counts and percentages (%), subsequently compared the difference among the three groups via a chi-square test. Continuous variables are presented as means and standard deviations with the Mann–Whitney U test for skewed continuous variables and Student’s t test or one-way ANOVA for normally distributed continuous variables. The chi-square goodness-of-fit method was used to test the normality of the distribution of the data. The first component of the study assessed the associations in the prevalence between sarcopenia and asthma via three generalized additive models with binomial regression.The adjusted variables of each model were shown in each table. Model 1 included patient demographic characteristics, Model 2 added physical/behavioral factors, and Model 3 added physical/behavioral factors and comorbidities. In the CHARLS, the least absolute shrinkage and selection operator (LASSO) [20] and multivariate logistic analyses with binomial regression were used to screen the independent risk factors for sarcopenia in asthmatics. We also evaluated the relationships between sarcopenia with asthmatic symptoms in the second component. Model 4 also included lung function on the basis of model 3 in Table 3. The third component was that three generalized additive models with Poisson regression were used to compare the differences in lung function among the three sarcopenia groups in asthmatics. In the WHO SAGE, model 4 added the adjustments of asthmatic medications and symptoms. Finally, three generalized additive models with binomial regression were used to evaluate the associations between sarcopenia with depression and COPD in asthmatics. All statistical analyses were done in SPSS, Empower(R) (www. empowerstats.com; X&Y solutions, Inc., Boston MA). Odds ratios (ORs) for binomial regression analysis and rate ratios (RRs) for Poisson regression analysis with 95% confidence intervals (CIs) represented the strength of associations, meanwhile a two tailed P < 0.05 was considered statistically significant.

Table 3 The associations between sarcopenia and asthma-related symptoms in the Study on global AGEing and adult health from China
Full size table

Results

Characteristics of the CHARLS and WHO SAGE

In three cycles of the CHARLS (2011, 2013 and 2015), a total of 15,404 individuals aged 67.6 ± 6.2 years (range, 60–103 years) were included in this present study. More than half (51.9%) of individuals were male with predominantly rural (62.4%), never alcohol and smoking. The overall prevalence of sarcopenia was 21.1% with 5.8% representing severe sarcopenia. The prevalence of sarcopenia showed an upwards trend with increasing age: 14.4%, 31.8%, and 51.2% in the 60–69, 70–79 and ≥ 80 years groups, respectively. A total of 659 (4.3%) individuals reported physician- diagnosed asthma. In addition, a total of 4433 (28.7%) individuals were classified as depressive group (CES-D10 ≥ 12 scores).

A total of 10,263 individuals aged 69.5 ± 7.2 years(range, 60–102 years) were selected from the WHO SAGE. About 47% of individuals came from rural. Predominantly female (51.1%) with high proportions of never drinking alcohol and never smoking were shown in the WHO SAGE. The overall prevalence of sarcopenia was 12.3% with 10.2% among male and 14.4% among female. A total of 512(5%) individuals were diagnosed with severe sarcopenia. Moreover, the prevalence of sarcopenia in the three age groups also significantly increased and varied by 6.0%, 16.4% and 32.5%. A total of 2104 (20.5%) individuals had airway obstruction (FEV1/FVC < 0.7). Additionally, the prevalence of asthma was 3.1% (316 individuals). A total of 301 asthmatics provided the information about medication treatment (73.4%) and asthma-related symptoms. Furthermore, the proportions of asthma-related attacks, awakening, and severe shortness of breath were 68.1%, 27.2% and 42.2%, respectively. More detailed data were shown in Tables 1 and 2.

Associations in the prevalence between sarcopenia with asthma

In the CHARLS, the prevalence of non-severe and severe sarcopenia among asthmatics were 18.5% and 7.4%, respectively (see Fig. 1). A total of 4.0% of individuals with sarcopenia had a diagnosis of asthma, which was higher than that of individuals without sarcopenia (2.9%, P = 0.036). Model 3 indicated that sarcopenia and asthma had no significant bidirectional association in the prevalence (see Table S1). In asthmatics, the LASSO (see S1 Figure) and multivariate logistic regression analyses indicated that aged with rural (rural vs. unban, adjusted OR = 0.41, 95%CI: 0.23–0.75) and depression (CES-D10 < 12 scores vs. ≥ 12 scores, adjusted OR = 1.95, 95%CI: 1.16–3.27) harbored relatively high prevalence of sarcopenia.

Fig. 1
figure 1

The prevalence of sarcopenia. A In the China Health and Retirement Longitudinal Study; B In the Study on global AGEing and adult health from China

Full size image

In the WHO SAGE, 9.2% and 7% of individuals with asthma could be diagnosed with non-severe and severe sarcopenia, which were higher than those in individuals without asthma (see Fig. 1). The prevalence of asthma was 4.0% in individuals with sarcopenia. Three models observed no significant association in the prevalence between asthma and sarcopenia (see Table S2). The LASSO (see S1 Figure) and multivariate logistic regression analyses suggested that female, rural, aged and airway obstruction were independent risk factors for sarcopenia among asthmatics.

Sarcopenia and asthma-related symptoms

Four models also showed that asthma-related attacks and awakening had no significant associations with the presence of sarcopenia (see Table 3). However, sarcopenia was associated with a significantly higher prevalence of asthma-related severe shortness of breath after adjusting for demographic characteristics, physical/behavioral factors, comorbidities and lung function (adjusted OR = 3.71, 95%CI: 1.43–9.60). The prevalence of sarcopenia demonstrated a rising tendency with the increasing numbers of asthma-related symptoms (see Fig. 2).

Fig. 2
figure 2

The associations between the prevalence of sarcopenia with the number of asthma-related symptoms in asthmatics from the Study on global AGEing and adult health from China

Full size image

Sarcopenia and lung function in asthmatics

In the CHARLS, Poisson regression analyses suggested that the adjusted mean value of PEF was significantly declined in asthmatics with non-severe (adjusted RR = 0.926, 95%CI: 0.910–0.934) and severe sarcopenia (adjusted RR = 0.759, 95%CI: 0.739–779) compared to no sarcopenia (see Table S3).

In the WHO SAGE, four Poisson regression analyses demonstrated that the more severe sarcopenia in asthmatics, the more obvious was lung function impairment (see Table 4 and Fig. 3). Asthmatics with sarcopenia (adjusted RR = 6.82, 95%CI: 2.54–18.34 in model 4) were associated with a significantly higher prevalence of airway obstruction than those without sarcopenia. Sarcopenia had a significantly negative correlation with the adjusted mean value of PEF in asthmatics (adjusted RR = 0.86, 95%CI: 0.82–0.91 in model 4).

Table 4 The associations between sarcopenia and lung function of asthmatics in the Study on global AGEing and adult health from China
Full size table
Fig. 3
figure 3

The associations between different grade of sarcopenia with lung function in asthmatics from the Study on global AGEing and adult health from China. A FEV1; B FEV1/FVC < 0.7; C PEF; D FEF 25%-75%

Full size image

Sarcopenia and comorbidities in asthmatics

In the CHARLS, adjusted OR values in the prevalence of depression respectively were 1.82(95%CI: 1.04–3.18) in nonsevere sarcopenia and 2.02 (95%CI: 1.01–4.10) in severe sarcopenia compared with no sarcopenia after adjusting for demographic characteristics, physical/behavioral factors, and thirteen comorbidities (see Table S3). The presence of sarcopenia was associated with a significantly higher prevalence of depression (adjusted OR = 1.87, 95%CI:1.11–3.14 in model 3).

In the WHO SAGE, sarcopenia was an independent risk factor of COPD in individuals with asthma(adjusted OR = 5.76, 95%CI:2.01–16.5 in model 4). When model 3 added the adjustments of asthmatic medication and symptoms, the prevalence of COPD in the non-severe sarcopenia group (adjusted OR = 9.11, 95%CI:2.69–30.8 in model 4) was significantly higher than that in the no sarcopenia group (see Table S4).

Discussion

This study used two national population-based surveys to determine the associations between sarcopenia with asthma and found the following results: Firstly, the prevalence of sarcopenia and severe sarcopenia defined by the AWGS 2019 criteria was 12.3–21.3% and 5–5.8% in Chinese older asthmatics. There was no significantly bidirectional association in the prevalence between asthma and sarcopenia, but an upwards trend of sarcopenia was associated with the increasing numbers of asthma-related symptoms. Secondly, the presence of sarcopenia, especially severe sarcopenia, was accompanied by a significantly increased risk of airway obstruction and an obvious reduction of PEF. Thirdly, sarcopenia was positively associated with the prevalence of depression and COPD in terms of asthmatic comorbidity.

Studies on sarcopenia and asthma did not obtain enough attention and are very scant. This was the first study to estimate the prevalence of sarcopenia in Chinese population with asthma by using the AWGS 2019 criteria. Our study demonstrated that approximately 17.6% and 5.5% of asthmatics may be diagnosed with sarcopenia and severe sarcopenia. The prevalence of sarcopenia in the CHARLS was higher than that in WHO SAGE. A possible explanation was that more individuals (62.6%) came from rural in the CHARLS compared with the WHO SAGE (47%). Two analyses based on the CHARLS and WHO SAGE suggested that rural is an independent risk factor of sarcopenia. Previous studies have fully explored the adverse effects of sarcopenia on chronic obstruction pulmonary diseases [21, 22] and health status in the general population [23, 24]. Our study suggested that the prevalence of sarcopenia among asthmatics was higher than that among individuals without asthma. The screening and study of sarcopenia in asthmatics should not be neglected, especially for ageing individuals with rural, depression and airway obstruction.

Persistent airway obstruction and lung function impairment are two important hallmarks of asthmatic deterioration [1]. Airway obstruction and declined lung function not only augment the risk of asthmatic exacerbations and reduce the quality of life, but also increase the difficulty of asthmatic medication treatment. 1 Short-term and long-term PEF monitoring may identify expiratory airflow limitations and contribute to early detection of asthmatic exacerbations and the assessment of asthma control levels. In our study, sarcopenia was found to have a positive correlation with the prevalence of airway obstructive and the decline of PEF. We also observed that asthmatics with sarcopenia were more prone to developing COPD than those without sarcopenia. It is reasonable to expect that sarcopenia along with systemic muscle fiber atrophy and weakness will inevitably lead to the functional disability of respiratory muscles. The crosstalk between sarcopenia and adverse health consequences is mediated through complex mechanisms and pathways, including microRNAs, inflammatory processes, oxidative stress and etc. [25,26,27]. The onset and development of asthma are known to involve the regulation of microRNAs and inflammatory processes [28, 29]. In asthmatics, the expression levels of miR-21 and miR-34 had strongly negative associations with handgrip strength and ASM, whereas miR-133 and miR-206 showed significantly positive correlations with handgrip strength and ASM [30]. Sarcopenia along with low handgrip strength and ASM potentially reduces the levels of miR-133 and miR-206 in asthmatics. The decreasing miR-133a could up-regulate RhoA expression of bronchial smooth muscle in an asthma model, which may lead to an augmentation of bronchial smooth muscle contraction and induce airway hyperresponsiveness (AHR) in individuals with asthma [31]. In a 4,4′-methylene diphenyl diisocyanate induced asthma model, the reduction of miR-206-3p might increase inducible nitric oxide synthase transcription expression by targeting calcineurin/NFAT signaling, in turn leading to AHR. Increasing the level of miR-21 not only promotes the differentiation of T cells towards Th2 in eosinophilic asthma, but also restrains HDAC2 levels and results in glucocorticoids insensitivity by up-regulating PI3K-mediated phosphorylation and nuclear translocation of pAKT in neutrophilic asthma [28]. Multiple studies have shown that sarcopenia is associated with a significant increase in pro-inflammatory cytokines, including TNF-α, IL-6, and C-reactive protein [32]. Taken together, the microRNAs regulatory network and inflammatory processes can be considered the underlying pathophysiology linking sarcopenia with asthma.

Depression is classified as an important independent risk factor of asthma onset, exacerbations and mortality [1]. Our study suggested a bidirectional association between depression and sarcopenia in asthmatics, similar to the results in the general population [33, 34]. Sarcopenia, especially severe sarcopenia, was associated with a significant increase of depression compared with no sarcopenia. Sarcopenia and depression harbor common pathophysiological pathways with regard to inflammatory processes, neurotrophins and oxidative stress [33]. In addition, the onset of sarcopenia and depression may attribute to some same lifestyle behaviors, such as low physical activity, smoking, and malnutrition [33]. Depression caused by sarcopenia is likely to participate in the occurrence and development of asthma.

The main strength of this study was that we assessed the relationships between sarcopenia and asthmatic prevalence, lung function and comorbidities in the Chinese population for the first time by using two national population-based studies. However, several limitations also existed in our study. Firstly, the diagnoses of asthma and some comorbidities depended on the questionnaire's results, which may have resulted in a potential selection bias. Secondly, an anthropometric equation, instead of Dual X-ray absorpometry (DXA) or Bioelectrical impedance analysis(BIA), was used to evaluate ASM. However, this equation has previously been validated in the Chinese population [13]. Our cut-off value of low ASM was substantially identical to that in the study of Wu and the colleagues [16]. Besides, the use of anthropometric equation to assess low ASM may obtain a cost-effective alternative to BIA or DXA for improving the diagnosis of sarcopenia, especially in large-sample population-based studies [35]. Thirdly, the cross-sectional nature of the two studies restrains the capability to infer interactional causation between asthma and sarcopenia.

Conclusion

This study reports the prevalence of sarcopenia and severe sarcopenia in Chinese older population and asthmatics. Sarcopenia can contribute to the development of asthma by affecting lung function and comorbidity and may be considered a treatable trait of asthma management. When considering the high prevalence and significant effect of sarcopenia, it is worth designing and implementing a routine screening for asthmatics.

Availability of data and materials

The data underlying this study were obtained from open CHARLS and SAGE databases. All relevant data are within the paper.

Abbreviations

AHR:

Airway hyperresponsiveness

ASM:

Appendicular skeletal muscle mass

AWGS:

Asian Working Group for sarcopenia

BIA:

Bioelectrical impedance analysis

BMI:

Body mass index

CAPI:

Computer-assisted personal interview

CHARLS:

The China Health and Retirement Longitudinal Study

CI:

Confidence interval

DXA:

Dual X-ray absorpometry

LASSO:

Least absolute shrinkage and selection operator

OR:

Odds ratio

RR:

Rate ratio

SAGE:

Global Ageing and Adult Health

References

  1. Global Initiative for Asthma. Global Strategy for Asthma Management and Prevention, 2019. https://ginasthma.org/wp-content/uploads/2019/04/GINA-2019-main-Pocket-Guide-wms.pdf. Accessed 8 June 2019.

  2. McDonald VM, Clark VL, Cordova-Rivera L, Wark PAB, Baines KJ, Gibson PG. Targeting treatable traits in severe asthma: a randomised controlled trial. Eur Respir J. 2020;55(3):1901509.

    Article  CAS  Google Scholar 

  3. Freitas PD, Xavier RF, McDonald VM, et al. Identification of asthma phenotypes based on extrapulmonary treatable traits. Eur Respir J. 2021;57(1):2000240.

    CAS  PubMed  Google Scholar 

  4. Hiles SA, Gibson PG, Agusti A, McDonald VM. Treatable traits that predict health status and treatment response in airway disease. J Allergy Clin Immunol Pract. 2021;9(3):1255-1264.e2.

    Article  Google Scholar 

  5. Wu WW, Zhang X, Li M, et al. Treatable traits in elderly asthmatics from the Australasian severe asthma network: a prospective cohort study. J Allergy Clin Immunol Pract. 2021;9(7):2770–82.

    Article  Google Scholar 

  6. Chen LK, Woo J, Assantachai P, et al. Asian working group for sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020;21(3):300-307.e2.

    Article  Google Scholar 

  7. Nelke C, Dziewas R, Minnerup J, Meuth SG, Ruck T. Skeletal muscle as potential central link between sarcopenia and immune senescence. EBioMedicine. 2019;49:381–8.

    Article  Google Scholar 

  8. Ohara DG, Pegorari MS, Oliveira Dos Santos NL, Fatima Ribeiro Silva de C, Monteiro RL, Matos AP, et al. Respiratory muscle strength as a discriminator of sarcopenia in community-dwelling elderly: a cross-sectional study. J Nutr Health Aging. 2018;22:952–8.

    Article  CAS  Google Scholar 

  9. Landi F, Salini S, Zazzara MB, et al. Relationship between pulmonary function and physical performance among community-living people: results from Look-up 7+ study. J Cachexia Sarcopenia Muscle. 2020;11(1):38–45.

    Article  Google Scholar 

  10. Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16–31.

    Article  Google Scholar 

  11. Zhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol. 2014;43(1):61–8.

    Article  Google Scholar 

  12. Kowal P, Chatterji S, Naidoo N, et al. Data resource profile: the World Health Organization Study on global AGEing and adult health (SAGE). Int J Epidemiol. 2012;41(6):1639–49.

    Article  Google Scholar 

  13. Wen X, Wang M, Jiang CM, Zhang YM. Anthropometric equation for estimation of appendicular skeletal muscle mass in Chinese adults. Asia Pac J Clin Nutr. 2011;20(4):551–6.

    PubMed  Google Scholar 

  14. Delmonico MJ, Harris TB, Lee JS, Visser M, Nevitt M, Kritchevsky SB, et al. Alternative definitions of sarcopenia, lower extremity performance, and functional impairment with aging in older men and women. J Am Geriatr Soc. 2007;55:769–74.

    Article  Google Scholar 

  15. Yang M, Hu X, Wang H, et al. Sarcopenia predicts readmission and mortality in elderly patients in acute care wards: a prospective study. J Cachexia Sarcopenia Muscle. 2017;8:251e–258.

    Article  Google Scholar 

  16. Hu X, Zhang L, Wang H, et al. Malnutrition-sarcopenia syndrome predicts mortality in hospitalized older patients. Sci Rep. 2017;7:3171.

    Article  Google Scholar 

  17. Cheng HG, Chen S, McBride O, Phillips MR. Prospective relationship of depressive symptoms, drinking, and tobacco smoking among middle-aged and elderly community-dwelling adults: results from the China Health and Retirement Longitudinal Study (CHARLS). J Affect Disord. 2016;195:136–43.

    Article  Google Scholar 

  18. Chen H, Xiong P, Chen L, Hao G. Childhood neighborhood quality, friendship, and risk of depressive symptoms in adults: The China health and retirement longitudinal study. J Affect Disord. 2020;276:732–7.

    Article  Google Scholar 

  19. Hu Z, Song X, Hu K, Ruan Y, Zeng F. Association between sleep duration and asthma in different weight statuses (CHNS 2009–2015). Sleep Breath. 2021;25(1):493–502.

    Article  Google Scholar 

  20. Hu Z, Li S, Yang A, et al. Delayed hospital admission and high-dose corticosteroids potentially prolong SARS-CoV-2 RNA detection duration of patients with COVID-19. Eur J Clin Microbiol Infect Dis. 2021;40(4):841–8.

    Article  CAS  Google Scholar 

  21. Bone AE, Hepgul N, Kon S, Maddocks M. Sarcopenia and frailty in chronic respiratory disease. Chron Respir Dis. 2017;14(1):85–99.

    Article  Google Scholar 

  22. Jones SE, Maddocks M, Kon SS, et al. Sarcopenia in COPD: prevalence, clinical correlates and response to pulmonary rehabilitation. Thorax. 2015;70(3):213–8.

    Article  Google Scholar 

  23. Cruz-Jentoft AJ, Sayer AA. Sarcopenia Lancet. 2019;393(10191):2636–46.

    Article  Google Scholar 

  24. Papadopoulou SK. Sarcopenia: a contemporary health problem among older adult populations. Nutrients. 2020;12(5):1293.

    Article  Google Scholar 

  25. Brown DM, Goljanek-Whysall K. microRNAs: Modulators of the underlying pathophysiology of sarcopenia? Ageing Res Rev. 2015;24(Pt B):263–73.

    Article  CAS  Google Scholar 

  26. Yanai K, Kaneko S, Ishii H, et al. MicroRNAs in sarcopenia: a systematic review. Front Med (Lausanne). 2020;7:180.

    Article  Google Scholar 

  27. Pascual-Fernández J, Fernández-Montero A, Córdova-Martínez A, Pastor D, Martínez-Rodríguez A, Roche E. Sarcopenia: molecular pathways and potential targets for intervention. Int J Mol Sci. 2020;21(22):8844.

    Article  Google Scholar 

  28. Specjalski K, Jassem E. MicroRNAs: potential biomarkers and targets of therapy in allergic diseases? Arch Immunol Ther Exp (Warsz). 2019;67(4):213–23.

    Article  CAS  Google Scholar 

  29. Zhang L, Zhang X, Zheng J, et al. Depressive symptom-associated IL-1β and TNF-α release correlates with impaired bronchodilator response and neutrophilic airway inflammation in asthma. Clin Exp Allergy. 2019;49(6):770–80.

    Article  CAS  Google Scholar 

  30. Qaisar R, Karim A, Muhammad T, Shah I. Circulating biomarkers of accelerated sarcopenia in respiratory diseases. Biology (Basel). 2020;9(10):322.

    CAS  Google Scholar 

  31. Chiba Y, Tanabe M, Goto K, Sakai H, Misawa M. Down-regulation of miR-133a contributes to up-regulation of Rhoa in bronchial smooth muscle cells. Am J Respir Crit Care Med. 2009;180(8):713–9.

    Article  CAS  Google Scholar 

  32. Fan J, Kou X, Yang Y, Chen N. MicroRNA-regulated proinflammatory cytokines in sarcopenia. Mediators Inflamm. 2016;2016:1438686.

    PubMed  PubMed Central  Google Scholar 

  33. Szlejf C, Suemoto CK, Brunoni AR, et al. Depression is associated with sarcopenia due to low muscle strength: results from the ELSA-Brasil study. J Am Med Dir Assoc. 2019;20(12):1641–6.

    Article  Google Scholar 

  34. Kirk B, Zanker J, Bani Hassan E, Bird S, Brennan-Olsen S, Duque G. Sarcopenia Definitions and Outcomes Consortium (SDOC) criteria are strongly associated with malnutrition, depression, falls, and fractures in high-risk older persons. J Am Med Dir Assoc. 2021;22(4):741–5.

    Article  Google Scholar 

  35. Alexandre Tda S, Duarte YA, Santos JL, Wong R, Lebrao ML. Sarcopenia according to the European Working Group on Sarcopenia in Older People (EWGSOP) versus dynapenia as a risk factor for mortality in the elderly. J Nutr Health Aging. 2014;18:751–6.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the CHARLS research and field team and every respondent in the study for their contributions.This work was supported by the Behavioral and Social Research division of the National Institute on Aging of the National Institute of Health (grants 1-R21-AG031372-01, 1-R01-AG037031-01, and 3-R01AG037031-03S1); the Natural Science Foundation of China (grants 70773002, 70910107022, and 71130002), the World Bank (contracts 7145915 and 7159234), and Peking University.

This paper uses data from WHO's Study on Global Ageing and Adult Health (SAGE). SAGE is supported by the US National Institute on Aging through Interagency Agreements OGHA 04034785; YA1323-08-CN-0020; Y1-AG-1005-0) and through research grants R01-AG034479 and R21-AG034263.

Funding

No funding.

Author information

Authors and Affiliations

  1. Department of Respiratory and Critical Care Medicine, The First College of Clinical Medicine Science, China Three Gorges University, Yichang, 443003, People’s Republic of China

    Zhigang Hu, Xinyu Song & Fanjun Zeng

  2. Department of Respiratory and Critical Care Medicine, Yichang Central People’s Hospital at Zhijiang, NO. 183 Yiling Road, Zhijiang, 443003, People’s Republic of China

    Zhigang Hu & Ailan Yang

  3. Department of Respiratory and Critical Care Medicine, Yichang Central People’s Hospital, Yichang, 443003, People’s Republic of China

    Zhigang Hu, Xinyu Song & Fanjun Zeng

  4. Department of Academic Management, Clinical Research Center, China Three Gorges University, NO. 183 Yiling Road, Yichang, 443003, People’s Republic of China

    Yufeng Tian

Authors
  1. Zhigang Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yufeng Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xinyu Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fanjun Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ailan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Z.H. F.Z. and X.Y. wrote the main manuscript text. A.Y.and Y.T. prepared Figs. 1, 2, 3. All authors reviewed the manuscript. The author(s) read and approved the final manuscript.

Corresponding authors

Correspondence to Zhigang Hu or Xinyu Song.

Ethics declarations

Ethics approval and consent to participate

The study procedures were carried out by the Declaration of Helsinki. Written informed consents were collected in National School of Development of Peking University on the China Health and Retirement Longitudinal Study(CHARLS). WHO Ethical Review Committee and local ethics research review boards approved ethical and obtained written informed consent on Global Ageing and Adult Health (SAGE). All experiments were performed in accordance with relevant guidelines and regulations. All experimental protocols were approved by the Institutional Review Board at China, Three Gorges University. This study was deemed exempt for review by the Institutional Review Board at China, Three Gorges University.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no confict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1:

Table S1. The associations between sarcopenia and asthma in the China Health and Retirement Longitudinal Study. Table S2. The associations between sarcopenia and asthma in the Study on global AGEing and adult health from China. Table S3. The associations between sarcopenia with PEF and depression among asthmatics in the China Health and Retirement Longitudinal Study. Table S4. The associations between sarcopenia and chronic obstructive pulmonary disease among asthmatics in the Study on global AGEing and adult health from China. S1 Figure. The screen of independent risk factors of cancer specific death using the least absolute shrinkage and selection operator (LASSO) analysis with binomial regression model in in the China Health and Retirement Longitudinal Study and the Study on global AGEing and adult health from China. A. Tuning parameter selection in the LASSO model used 10-fold cross-validation via minimum criteria in the China Health and Retirement Longitudinal Study; B. LASSO coefficient profiles of potential risk factors in the China Health and Retirement Longitudinal Study; C. The area under the receiver operating characteristic curve (AUC=0.915) in the China Health and Retirement Longitudinal Study; D. Tuning parameter selection in the LASSO model used 10-fold cross-validation via minimum criteria in the Study on global AGEing and adult health from China; E. LASSO coefficient profiles of potential risk factors in the the Study on global AGEing and adult health from China; F. The area under the receiver operating characteristic curve (AUC=0.958) in the Study on global AGEing and adult health from China.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, Z., Tian, Y., Song, X. et al. Associations between sarcopenia with asthmatic prevalence, lung function and comorbidity. BMC Geriatr 22, 703 (2022). https://doi.org/10.1186/s12877-022-03394-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12877-022-03394-9

Keywords

BMC Geriatrics

ISSN: 1471-2318

Contact us