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  • Published: 15 August 2020

Treatment strategies for asthma: reshaping the concept of asthma management

  • Alberto Papi 1 , 7 ,
  • Francesco Blasi 2 , 3 ,
  • Giorgio Walter Canonica 4 ,
  • Luca Morandi 1 , 7 ,
  • Luca Richeldi 5 &
  • Andrea Rossi 6  

Allergy, Asthma & Clinical Immunology volume  16 , Article number:  75 ( 2020 ) Cite this article

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Asthma is a common chronic disease characterized by episodic or persistent respiratory symptoms and airflow limitation. Asthma treatment is based on a stepwise and control-based approach that involves an iterative cycle of assessment, adjustment of the treatment and review of the response aimed to minimize symptom burden and risk of exacerbations. Anti-inflammatory treatment is the mainstay of asthma management. In this review we will discuss the rationale and barriers to the treatment of asthma that may result in poor outcomes. The benefits of currently available treatments and the possible strategies to overcome the barriers that limit the achievement of asthma control in real-life conditions and how these led to the GINA 2019 guidelines for asthma treatment and prevention will also be discussed.

Asthma, a major global health problem affecting as many as 235 million people worldwide [ 1 ], is a common, non-communicable, and variable chronic disease that can result in episodic or persistent respiratory symptoms (e.g. shortness of breath, wheezing, chest tightness, cough) and airflow limitation, the latter being due to bronchoconstriction, airway wall thickening, and increased mucus.

The pathophysiology of the disease is complex and heterogeneous, involving various host-environment interactions occurring at various scales, from genes to organ [ 2 ].

Asthma is a chronic disease requiring ongoing and comprehensive treatment aimed to reduce the symptom burden (i.e. good symptom control while maintaining normal activity levels), and minimize the risk of adverse events such as exacerbations, fixed airflow limitation and treatment side effects [ 3 , 4 ].

Asthma treatment is based on a stepwise approach. The management of the patient is control-based; that is, it involves an iterative cycle of assessment (e.g. symptoms, risk factors, etc.), adjustment of treatment (i.e. pharmacological, non-pharmacological and treatment of modifiable risk factors) and review of the response (e.g. symptoms, side effects, exacerbations, etc.). Patients’ preferences should be taken into account and effective asthma management should be the result of a partnership between the health care provider and the person with asthma, particularly when considering that patients and clinicians might aim for different goals [ 4 ].

This review will discuss the rationale and barriers to the treatment of asthma, that may result in poor patient outcomes. The benefits of currently available treatments and the possible strategies to overcome the barriers that limit the achievement of asthma control in real-life situations will also be discussed.

The treatment of asthma: where are we? Evolution of a concept

Asthma control medications reduce airway inflammation and help to prevent asthma symptoms; among these, inhaled corticosteroids (ICS) are the mainstay in the treatment of asthma, whereas quick-relief (reliever) or rescue medicines quickly ease symptoms that may arise acutely. Among these, short-acting beta-agonists (SABAs) rapidly reduce airway bronchoconstriction (causing relaxation of airway smooth muscles).

National and international guidelines have recommended SABAs as first-line treatment for patients with mild asthma, since the Global Initiative for Asthma guidelines (GINA) were first published in 1995, adopting an approach aimed to control the symptoms rather than the underlying condition; a SABA has been the recommended rescue medication for rapid symptom relief. This approach stems from the dated idea that asthma symptoms are related to bronchial smooth muscle contraction (bronchoconstriction) rather than a condition concomitantly caused by airway inflammation. In 2019, the GINA guidelines review (GINA 2019) [ 4 ] introduced substantial changes overcoming some of the limitations and “weaknesses” of the previously proposed stepwise approach to adjusting asthma treatment for individual patients. The concept of an anti-inflammatory reliever has been adopted at all degrees of severity as a crucial component in the management of the disease, increasing the efficacy of the treatment while lowering SABA risks associated with patients’ tendency to rely or over-rely on the as-needed medication.

Until 2017, the GINA strategy proposed a pharmacological approach based on a controller treatment (an anti-inflammatory, the pillar of asthma treatment), with a SABA as an additional rescue intervention. The reliever, a short-acting bronc hodilator, was merely an addendum , a medication to be used in case the real treatment (the controller) failed to maintain disease control: SABAs effectively induce rapid symptom relief but are ineffective on the underlying inflammatory process. Based on the requirement to achieve control, the intensity of the controller treatment was related to the severity of the disease, varying from low-dose ICS to combination low-dose ICS/long-acting beta-agonist (LABA), medium-dose ICS/LABA, up to high-dose ICS/LABA, as preferred controller choice, with a SABA as the rescue medication. As a result, milder patients were left without any anti-inflammatory treatment and could only rely on SABA rescue treatment.

Poor adherence to therapy is a major limitation of a treatment strategy based on the early introduction of the regular use of controller therapy [ 5 ]. Indeed, a number of surveys have highlighted a common pattern in the use of inhaled medication [ 6 ], in which treatment is administered only when asthma symptoms occur; in the absence of symptoms, treatment is avoided as patients perceive it as unnecessary. When symptoms worsen, patients prefer to use reliever therapies, which may result in the overuse of SABAs [ 7 ]. Indirect evidence suggests that the overuse of beta-agonists alone is associated with increased risk of death from asthma [ 8 ].

In patients with mild persistent disease, low-dose ICS decreases the risk of severe exacerbations leading to hospitalization and improves asthma control [ 9 ]. When low-dose ICS are ineffective in controlling the disease (Step 3 of the stepwise approach), a combination of low-dose ICS with LABA maintenance was the recommended first-choice treatment, plus as-needed SABA [ 3 , 10 ]. Alternatively, the combination low-dose ICS/LABA (formoterol) was to be used as single maintenance and reliever treatment (SMART). The SMART strategy containing the rapid-acting formoterol was recommended throughout GINA Steps 3 to 5 based on solid clinical-data evidence [ 3 ].

The addition of a LABA to ICS treatment reduces both severe and mild asthma exacerbation rates, as shown in the one-year, randomized, double-blind, parallel-group FACET study [ 11 ]. This study focused on patients with persistent asthma symptoms despite receiving ICS and investigated the efficacy of the addition of formoterol to two dose levels of budesonide (100 and 400 µg bid ) in decreasing the incidence of both severe and mild asthma exacerbations. Adding formoterol decreased the incidence of both severe and mild asthma exacerbations, independent of ICS dose. Severe and mild exacerbation rates were reduced by 26% and 40%, respectively, with the addition of formoterol to the lower dose of budesonide; the corresponding reductions were 63% and 62%, respectively, when formoterol was added to budesonide at the higher dose.

The efficacy of the ICS/LABA combination was confirmed in the post hoc analysis of the FACET study, in which patients were exposed to a combination of formoterol and low-dose budesonide [ 12 ]. However, such high levels of asthma control are not achieved in real life [ 5 ]. An explanation for this is that asthma is a variable condition and this variability might include the exposure of patients to factors which may cause a transient steroid insensitivity in the inflammatory process. This, in turn, may lead to an uncontrolled inflammatory response and to exacerbations, despite optimal controller treatment. A typical example of this mechanism is given by viral infections, the most frequent triggers of asthma exacerbations. Rhinoviruses, the most common viruses found in patients with asthma exacerbations, interfere with the mechanism of action of corticosteroids making the anti-inflammatory treatment transiently ineffective. A transient increase in the anti-inflammatory dose would overcome the trigger-induced anti-inflammatory resistance, avoiding uncontrolled inflammation leading to an exacerbation episode [ 13 , 14 , 15 ].

Indeed, symptoms are associated with worsening inflammation and not only with bronchoconstriction. Romagnoli et al. showed that inflammation, as evidenced by sputum eosinophilia and eosinophilic markers, is associated with symptomatic asthma [ 16 ]. A transient escalation of the ICS dose would prevent loss of control over inflammation and decrease the risk of progression toward an acute episode. In real life, when experiencing a deterioration of asthma control, patients self-treat by substantially increasing their SABA medication (Fig.  1 ); it is only subsequently that they (modestly) increase the maintenance treatment [ 17 ].

figure 1

Mean use of SABA at different stages of asthma worsening. Patients have been grouped according to maintenance therapy shown in the legend. From [ 17 ], modified

As bronchodilators, SABAs do not control the underlying inflammation associated with increased symptoms. The “as required” use of SABAs is not the most effective therapeutic option in controlling a worsening of inflammation, as signaled by the occurrence of symptoms; instead, an anti-inflammatory therapy included in the rescue medication along with a rapid-acting bronchodilator could provide both rapid symptom relief and control over the underlying inflammation. Thus, there is a need for a paradigm shift, a new therapeutic approach based on the rescue use of an inhaled rapid-acting beta-agonist combined with an ICS: an anti-inflammatory reliever strategy [ 18 ].

The symptoms of an exacerbation episode, as reported by Tattersfield and colleagues in their extension of the FACET study, increase gradually before the peak of the exacerbation (Fig.  2 ); and the best marker of worsening asthma is the increased use of rescue beta-agonist treatment that follows exactly the pattern of worsening symptomatology [ 19 ]. When an ICS is administered with the rescue bronchodilator, the patient would receive anti-inflammatory therapy when it is required; that is, when the inflammation is uncontrolled, thus increasing the efficiency of the anti-inflammatory treatment.

figure 2

(From [ 19 ])

Percent variation in symptoms, rescue beta-agonist use and peak expiratory flow (PEF) during an exacerbation. In order to allow comparison over time, data have been standardized (Day-14 = 0%; maximum change = 100%)

Barriers and paradoxes of asthma management

A number of barriers and controversies in the pharmacological treatment of asthma have prevented the achievement of effective disease management [ 20 ]. O’Byrne and colleagues described several such controversies in a commentary published in 2017, including: (1) the recommendation in Step 1 of earlier guidelines for SABA bronchodilator use alone, despite asthma being a chronic inflammatory condition; and (2) the autonomy given to patients over perception of need and disease control at Step 1, as opposed to the recommendation of a fixed-dose approach with treatment-step increase, regardless of the level of symptoms [ 20 ]. Other controversies outlined were: (3) a difficulty for patients in understanding the recommendation to minimize SABA use at Step 2 and switch to a fixed-dose ICS regimen, when they perceive SABA use as more effective; (4) apparent conflicting safety messages within the guidelines that patient-administered SABA monotherapy is safe, but patient-administered LABA monotherapy is not; and (5) a discrepancy as to patients’ understanding of “controlled asthma” and their symptom frequency, impact and severity [ 20 ].

Controversies (1) and (2) can both establish an early over-dependence on SABAs. Indeed, asthma patients freely use (and possibly overuse) SABAs as rescue medication. UK registry data have recently suggested SABA overuse or overreliance may be linked to asthma-related deaths: among 165 patients on short-acting relievers at the time of death, 56%, 39%, and 4% had been prescribed > 6, > 12, and > 50 SABA inhalers respectively in the previous year [ 21 ]. Registry studies have shown the number of SABA canisters used per year to be directly related to the risk of death in patients with asthma. Conversely, the number of ICS canisters used per year is inversely related to the rate of death from asthma, when compared with non-users of ICS [ 8 , 22 ]. Furthermore, low-dose ICS used regularly are associated with a decreased risk of asthma death, with discontinuation of these agents possibly detrimental [ 22 ].

Other barriers to asthma pharmacotherapy have included the suggestion that prolonged treatment with LABAs may mask airway inflammation or promote tolerance to their effects. Investigating this, Pauwels and colleagues found that in patients with asthma symptoms that were persistent despite taking inhaled glucocorticoids, the addition of regular treatment with formoterol to budesonide for a 12-month period did not decrease asthma control, and improved asthma symptoms and lung function [ 11 ].

Treatment strategies across all levels of asthma severity

Focusing on risk reduction, the 2014 update of the GINA guidelines recommended as-needed SABA for Step 1 of the stepwise treatment approach, with low-dose ICS maintenance therapy as an alternative approach for long-term anti-inflammatory treatment [ 23 ]. Such a strategy was only supported by the evidence from a post hoc efficacy analysis of the START study in patients with recently diagnosed mild asthma [ 24 ]. The authors showed that low-dose budesonide reduced the decline of lung-function over 3 years and consistently reduced severe exacerbations, regardless of symptom frequency at baseline, even in subjects with symptoms below the then-threshold of eligibility for ICS [ 24 ]. However, as for all post hoc analyses, the study by Reddel and colleagues does not provide conclusive evidence and, even so, their results could have questionable clinical significance for the management of patients with early mild asthma. To be effective, this approach would require patients to be compliant to regular twice-daily ICS for 10 years to have the number of exacerbations reduce by one. In real life, it is highly unlikely that patients with mild asthma would adhere to such a regular regimen [ 25 ].

The 2016 update to the GINA guidelines lowered the threshold for the use of low-dose ICS (GINA Step 2) to two episodes of asthma symptoms per month (in the absence of any supportive evidence for the previous cut-off). The objective was to effectively increase the asthma population eligible to receive regular ICS treatment and reduce the population treated with a SABA only, given the lack of robust evidence of the latter’s efficacy and safety and the fact that asthma is a variable condition characterized by acute exacerbations [ 26 ]. Similarly, UK authorities recommended low-dose ICS treatment in mild asthma, even for patients with suspected asthma, rather than treatment with a SABA alone [ 10 ]. However, these patients are unlikely to have good adherence to the regular use of an ICS. It is well known that poor adherence to treatment is a major problem in asthma management, even for patients with severe asthma. In their prospective study of 2004, Krishnan and colleagues evaluated the adherence to ICS and oral corticosteroids (OCS) in a cohort of patients hospitalized for asthma exacerbations [ 27 ]. The trend in the data showed that adherence to ICS and OCS treatment in patients dropped rapidly to reach nearly 50% within 7 days of hospital discharge, with the rate of OCS discontinuation per day nearly double the rate of ICS discontinuation per day (− 5.2% vs. − 2.7%; p < 0.0001 respectively, Fig.  3 ), thus showing that even after a severe event, patients’ adherence to treatment is suboptimal [ 27 ].

figure 3

(From [ 27 ])

Use of inhaled (ICS) and oral (OCS) corticosteroids in patients after hospital discharge among high-risk adult patients with asthma. The corticosteroid use was monitored electronically. Error bars represent the standard errors of the measured ICS and OCS use

Guidelines set criteria with the aim of achieving optimal control of asthma; however, the attitude of patients towards asthma management is suboptimal. Partridge and colleagues were the first in 2006 to evaluate the level of asthma control and the attitude of patients towards asthma management. Patients self-managed their condition using their medication as and when they felt the need, and adjusted their treatment by increasing their intake of SABA, aiming for an immediate relief from symptoms [ 17 ]. The authors concluded that the adoption of a patient-centered approach in asthma management could be advantageous to improve asthma control.

The concomitant administration of an as-needed bronchodilator and ICS would provide rapid relief while administering anti-inflammatory therapy. This concept is not new: in the maintenance and reliever approach, patients are treated with ICS/formoterol (fast-acting, long-acting bronchodilator) combinations for both maintenance and reliever therapy. An effective example of this therapeutic approach is provided in the SMILE study in which symptomatic patients with moderate to severe asthma and treated with budesonide/formoterol as maintenance therapy were exposed to three different as-needed options: SABA (terbutaline), rapid-onset LABA (formoterol) and a combination of LABA and ICS (budesonide/formoterol) [ 28 ]. When compared with formoterol, budesonide/formoterol as reliever therapy significantly reduced the risk of severe exacerbations, indicating the efficacy of ICS as rescue medication and the importance of the as-needed use of the anti-inflammatory reliever.

The combination of an ICS and a LABA (budesonide/formoterol) in one inhaler for both maintenance and reliever therapy is even more effective than higher doses of maintenance ICS and LABA, as evidenced by Kuna and colleagues and Bousquet and colleagues (Fig.  4 ) [ 29 , 30 ].

figure 4

(Data from [ 29 , 30 ])

Comparison between the improvements in daily asthma control resulting from the use of budesonide/formoterol maintenance and reliever therapy vs. higher dose of ICS/LABA + SABAZ and steroid load for the two regimens

The effects of single maintenance and reliever therapy versus ICS with or without LABA (controller therapy) and SABA (reliever therapy) have been recently addressed in the meta-analysis by Sobieraj and colleagues, who analysed 16 randomized clinical trials involving patients with persistent asthma [ 31 ]. The systematic review supported the use of single maintenance and reliever therapy, which reduces the risk of exacerbations requiring systemic corticosteroids and/or hospitalization when compared with various strategies using SABA as rescue medication [ 31 ].

This concept was applied to mild asthma by the BEST study group, who were the first to challenge the regular use of ICS. A pilot study by Papi and colleagues evaluated the efficacy of the symptom-driven use of beclomethasone dipropionate plus albuterol in a single inhaler versus maintenance with inhaled beclomethasone and as-needed albuterol. In this six-month, double-blind, double-dummy, randomized, parallel-group trial, 455 patients with mild asthma were randomized to one of four treatment groups: an as-needed combination therapy of placebo bid plus 250 μg of beclomethasone and 100 μg of albuterol in a single inhaler; an as-needed albuterol combination therapy consisting of placebo bid plus 100 μg of albuterol; regular beclomethasone therapy, comprising beclomethasone 250 μg bid and 100 μg albuterol as needed); and regular combination therapy with beclomethasone 250 μg and albuterol 100 μg in a single inhaler bid plus albuterol 100 μg as needed.

The rescue use of beclomethasone/albuterol in a single inhaler was as efficacious as the regular use of inhaled beclomethasone (250 μg bid ) and it was associated with a lower 6-month cumulative dose of the ICS [ 32 ].

The time to first exacerbation differed significantly among groups ( p  = 0.003), with the shortest in the as-needed albuterol and placebo group (Fig.  5 ). Figure  5 also shows equivalence between the as-needed combination therapy and the regular beclomethasone therapy. However, these results were not conclusive since the study was not powered to evaluate the effect of the treatment on exacerbations. In conclusion, as suggested by the study findings, mild asthma patients may require the use of an as-needed ICS and an inhaled bronchodilator rather than a regular treatment with ICS [ 32 ].

figure 5

(From [ 32 ])

Kaplan Meier analysis of the time to first exacerbation (modified intention-to-treat population). First asthma exacerbations are shown as thick marks. As-needed albuterol therapy = placebo bid plus 100 μg of albuterol as needed; regular combination therapy = 250 μg of beclomethasone and 100 μg of albuterol in a single inhaler bid plus 100 μg of albuterol as needed; regular beclomethasone therapy = 250 μg of beclomethasone bid and 100 μg of albuterol as needed; as-needed combination therapy = placebo bid plus 250 μg of beclomethasone and 100 μg of albuterol in a single inhaler as needed

Moving forward: a new approach to the management of asthma patients

Nearly a decade after the publication of the BEST study in 2007, the use of this alternative therapeutic strategy was addressed in the SYGMA 1 and SYGMA 2 trials. These double-blind, randomized, parallel-group, 52-week phase III trials evaluated the efficacy of as-needed use of combination formoterol (LABA) and the ICS budesonide as an anti-inflammatory reliever in patients requiring GINA Step 2 treatment, with the current reliever therapy (e.g. as-needed SABA) or with low-dose maintenance ICS (inhaled budesonide bid ) plus as-needed SABA, administered as regular controller therapy [ 33 , 34 ].

The SYGMA 1 trial, which enrolled 3849 patients, aimed to demonstrate the superiority of the as-needed use of the combination budesonide/formoterol over as-needed terbutaline, as measured by the electronically-recorded proportion of weeks with well-controlled asthma [ 34 ]. The more pragmatic SYGMA 2 trial enrolled 4215 patients with the aim to demonstrate that the budesonide/formoterol combination is non-inferior to budesonide plus as-needed terbutaline in reducing the relative rate of annual severe asthma exacerbations [ 33 ]. Both trials met their primary efficacy outcomes. In particular, as-needed budesonide/formoterol was superior to as-needed SABA in controlling asthma symptoms (34.4% versus 31.1%) and preventing exacerbations, achieving a 64% reduction in exacerbations. In both trials, budesonide/formoterol as-needed was similar to budesonide maintenance bid at preventing severe exacerbations, with a substantial reduction of the inhaled steroid load over the study period (83% in the SYGMA 1 trial and 75% in the SYGMA 2 trial). The time to first exacerbation did not differ significantly between the two regimens; however, budesonide/formoterol was superior to SABA in prolonging the time to first severe exacerbation [ 33 , 34 ].

The double-blind, placebo-controlled design of the SYGMA trials does not fully address the advantages of anti-inflammatory reliever strategy in patients who often rely on SABAs for symptom relief, so to what extent the study findings could apply to real-life practice settings was unclear.

These limitations were overcome by the results of the Novel START study, an open-label, randomized, parallel-group, controlled trial designed to reflect real-world practice, which demonstrated the effectiveness in mild asthma of budesonide/formoterol as an anti-inflammatory reliever therapy [ 35 ].

In real-world practice, mild asthma patients are treated with an as-needed SABA reliever or with daily low-dose ICS maintenance therapy plus a SABA reliever. In the Novel START study, 668 patients with mild asthma were randomized to receive either as-needed albuterol 100 µg, two inhalations (SABA reliever as a continuation of the Step 1 treatment according to the 2017 GINA guidelines), budesonide 200 µg (ICS maintenance treatment) plus as-needed albuterol (Step 2 therapy of the GINA 2017 guidelines), or 200 µg/6 µg budesonide/formoterol as anti-inflammatory reliever therapy taken as-needed for a 52-week study period.

In this study, the rate of asthma exacerbations for budesonide/formoterol was lower compared with albuterol (51%) and similar to the twice-daily maintenance budesonide plus albuterol, despite a 52% reduction in the mean steroid dose with the single combination inhaler treatment [ 35 ]. In addition, severe exacerbation rate was lower with budesonide/formoterol as compared with as-needed albuterol and regular twice-daily budesonide. These data support the findings of the SYGMA 1 and 2 trials, highlighting the need for a critical re-examination of current clinical practice. Along with the results of the SYGMA trials, they provide convincing evidence of the advantages of the anti-inflammatory reliever strategy, particularly in real-life settings.

The SYGMA 1, SYGMA 2 and the novel START studies complete the picture of the treatment strategies for asthma at any degree of severity, including mild asthma. A growing body of evidence shows that an anti-inflammatory reliever strategy, when compared with all other strategies with SABA reliever, consistently reduces the rate of exacerbations across all levels of asthma severity (Fig.  6 ) [ 28 , 29 , 34 , 36 , 37 , 38 , 39 ].

figure 6

(Data source: [ 39 ])

Risk reduction of severe asthma attack of anti-inflammatory reliever versus SABA across all levels of asthma severity. Bud = budesonide; form = formoterol; TBH = turbohaler. Data from: 1: [ 36 ]; 2: [ 37 ]; 3: [ 38 ]; 4: [ 28 ]; 5: [ 29 ]; 6: [ 30 ]; 7: [ 34 ]

This evidence set the ground (Fig.  7 ) for the release of the 2019 GINA strategy updates. The document provides a consistent approach towards the management of the disease and aims to avoid the overreliance and overuse of SABAs, even in the early course of the disease. The 2019 GINA has introduced key changes in the treatment of mild asthma: for safety reasons, asthmatic adults and adolescents should receive ICS-containing controller treatment instead of the SABA-only treatment, which is no longer recommended.

figure 7

Timeline of key randomized controlled trials and meta-analyses providing the supporting evidence base leading to the Global Initiative for Asthma (GINA) 2019 guidelines. GINA global initiative for asthma, MART maintenance and reliever therapy, SMART single inhaler maintenance and reliever therapy

In Step 1 of the stepwise approach to adjusting asthma treatment, the preferred controller option for patients with fewer than two symptoms/month and no exacerbation risk factors is low-dose ICS/formoterol as needed. This strategy is indirectly supported by the results of the SYGMA 1 study which evaluated the efficacy and safety of budesonide/formoterol as needed, compared with as-needed terbutaline and budesonide bid plus as-needed terbutaline (see above). In patients with mild asthma, the use of an ICS/LABA (budesonide/formoterol) combination as needed provided superior symptom control to as-needed SABA, resulting in a 64% lower rate of exacerbations (p = 0.07) with a lower steroid dose (17% of the budesonide maintenance dose) [ 34 ]. The changes extend to the other controller options as well. In the 2017 GINA guidelines, the preferred treatment was as-needed SABA with the option to consider adding a regular low-dose ICS to the reliever. In order to overcome the poor adherence with the ICS regimen, and with the aim to reduce the risk of severe exacerbations, the 2019 GINA document recommends taking low-dose ICS whenever SABA is taken, with the daily ICS option no longer listed.

Previous studies including the TREXA study in children and adolescents [ 40 ], the BASALT study [ 41 ] and research conducted by the BEST study group [ 32 ] have already added to the evidence that a low-dose ICS with a bronchodilator is an effective strategy for symptom control in patients with mild asthma. A recently published study in African-American children with mild asthma found that the use of as-needed ICS with SABA provides similar asthma control, exacerbation rates and lung function measures at 1 year, compared with daily ICS controller therapy [ 42 ], adding support to TREXA findings that in children with well controlled, mild asthma, ICS used as rescue medication with SABA may be an efficacious step-down strategy [ 40 ].

In Step 2 of the stepwise approach, there are now two preferred controller options: (a) a daily low-dose ICS plus an as-needed SABA; and (b) as-needed low-dose ICS/formoterol. Recommendation (a) is supported by a large body of evidence from randomized controlled trials and observations showing a substantial reduction of exacerbation, hospitalization, and death with regular low-dose ICS [ 7 , 8 , 9 , 24 , 43 ], whereas recommendation (b) stems from evidence on the reduction or non-inferiority for severe exacerbations when as-needed low-dose ICS/formoterol is compared with regular ICS [ 33 , 34 ].

The new GINA document also suggests low-dose ICS is taken whenever SABA is taken, either as separate inhalers or in combination. This recommendation is supported by studies showing reduced exacerbation rates compared with taking a SABA only [ 32 , 40 ], or similar rates compared with regular ICS [ 32 , 40 , 41 ]. Low-dose theophylline, suggested as an alternative controller in the 2017 GINA guidelines, is no longer recommended.

Airway inflammation is present in the majority of patients with asthma, and although patients with mild asthma may have only infrequent symptoms, they face ongoing chronic inflammation of the lower airways and risk acute exacerbations. The GINA 2019 strategy recognizes the importance of reducing the risk of asthma exacerbations, even in patients with mild asthma (Steps 1 and 2) [ 4 ]. In this regard, the new recommendations note that SABA alone for symptomatic treatment is non-protective against severe exacerbation and may actually increase exacerbation risk if used regularly or frequently [ 4 ].

The reluctance by patients to regularly use an ICS controller means they may instead try and manage their asthma symptoms by increasing their SABA reliever use. This can result in SABA overuse and increased prescribing, and increased risk of exacerbations.

As part of the global SABINA (SABA use IN Asthma) observational study programme, a UK study examined primary care records to describe the pattern of SABA and ICS use over a 10-year period in 373,256 patients with mild asthma [ 44 ]. Results showed that year-to-year SABA prescribing was more variable than that of ICS indicating that, in response to fluctuations in asthma symptom control, SABA use was increased in preference to ICS use. Furthermore, more than 33% of patients were prescribed SABA inhalers at a level equivalent to around ≥ 3 puffs per week which, according to GINA, suggests inadequate asthma control.

The problem of SABA overuse is further highlighted by two studies [ 45 , 46 ], also as part of the SABINA programme. These analysed data from 365,324 patients in a Swedish cohort prescribed two medications for obstructive lung disease in any 12-month period (HERA).

The first study identified SABA overuse (defined as ≥ 3 SABA canisters a year) in 30% of patients, irrespective of their ICS use; 21% of patients were collecting 3–5 canisters annually, 7% were collecting 6–10, and 2% more than 11 [ 45 ]. Those patients who were overusing SABA had significantly more asthma exacerbations relative to those using < 3 canisters (20.0 versus 12.5 per 100 patient years; relative risk 1.60, 95% CI 1.57–1.63, p < 0.001). Moreover, patients overusing SABA and whose asthma was more severe (GINA Steps 3 and 4) had greater exacerbation risk compared with overusing patients whose asthma was milder (GINA Steps 1 and 2).

The second study found those patients using three or more SABA reliever canisters a year had an increased all-cause mortality risk relative to patients using fewer SABA canisters: hazard ratios after adjustment were 1.26 (95% CI 1.14–1.39) for 3–5 canisters annually, 1.67 (1.49–1.87) for 6–10 canisters, and 2.35 (2.02–2.72) for > 11 canisters, relative to patients collecting < 3 canisters annually [ 46 ].

The recently published PRACTICAL study lends further support to as-needed low-dose ICS/formoterol as an alternative option to daily low-dose ICS plus as-needed SABA, outlined in Step 2 of the guidelines [ 47 ]. In their one-year, open-label, multicentre, randomized, superiority trial in 890 patients with mild to moderate asthma, Hardy and colleagues found that the rate of severe exacerbations per patient per year (the primary outcome) was lower in patients who received as-needed budesonide/formoterol than in patients who received controller budesonide plus as-needed terbutaline (relative rate 0.69, 95% CI 0.48–1.00; p < 0.05). Indeed, they suggest that of these two treatment options, as-needed low-dose ICS/formoterol may be preferred over controller low-dose ICS plus as-needed SABA for the prevention of severe exacerbations in this patient population.

Step 3 recommendations have been left unchanged from 2017, whereas Step 4 treatment has changed from recommending medium/high-dose ICS/LABA [ 3 ] to medium-dose ICS/LABA; the high-dose recommendation has been escalated to Step 5. Patients who have asthma that remains uncontrolled after Step 4 treatment should be referred for phenotypic assessment with or without add-on therapy.

To summarise, the use of ICS medications is of paramount importance for optimal asthma control. The onset and increase of symptoms are indicative of a worsening inflammation leading to severe exacerbations, the risk of which is reduced by a maintenance plus as-needed ICS/LABA combination therapy. The inhaled ICS/bronchodilator combination is as effective as the regular use of inhaled steroids.

The efficacy of anti-inflammatory reliever therapy (budesonide/formoterol) versus current standard-of-care therapies in mild asthma (e.g. reliever therapy with a SABA as needed and regular maintenance controller therapy plus a SABA as-needed) has been evaluated in two randomized, phase III trials which confirmed that, with respect to as-needed SABA, the anti-inflammatory reliever as needed is superior in controlling asthma and reduces exacerbation rates, exposing the patients to a substantially lower glucocorticoid dose.

Conclusions

A growing body of evidence shows that anti-inflammatory reliever strategy is more effective than other strategies with SABA reliever in controlling asthma and reducing exacerbations across all levels of asthma severity. A budesonide/formoterol therapy exposes asthma patients to a substantially lower glucocorticoid dose while cutting the need for adherence to scheduled therapy.

Availability of data and materials

Not applicable.

Abbreviations

Global Initiative for Asthma

Inhaled corticosteroids

Long-acting beta-agonists

Oral corticosteroids

Short-acting beta-agonists

Single inhaler maintenance and reliever treatment

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Acknowledgements

The Authors thank Maurizio Tarzia and Gayle Robins, independent medical writers who provided editorial assistance on behalf of Springer Healthcare Communications. The editorial assistance was funded by AstraZeneca.

No funding was received for this study. The editorial assistance was funded by AstraZeneca.

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Alberto Papi & Luca Morandi

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Francesco Blasi

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Giorgio Walter Canonica

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Luca Richeldi

Respiratory Section, Department of Medicine, University of Verona, Verona, Italy

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LM and AR reports no conflicts of interest in the last 3 years.

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Papi, A., Blasi, F., Canonica, G.W. et al. Treatment strategies for asthma: reshaping the concept of asthma management. Allergy Asthma Clin Immunol 16 , 75 (2020). https://doi.org/10.1186/s13223-020-00472-8

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Asthma Research

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Over the years, and as part of our broader commitment to research on lung diseases, the NHLBI has led and supported asthma research to discover better prevention and treatment options. Research supported by the NHLBI has also helped us understand what leads to and affects asthma, and it has provided doctors with information about what treatments work best for people who have asthma. 

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NHLBI research that really made a difference

For nearly 20 years, the NHLBI  Severe Asthma Research Program (SARP)  has transformed our knowledge of severe asthma. Research supported through the program has identified  secondhand smoke, pneumonia, and obesity as key risk factors for asthma . Studies have also found genetic variations linked with severe asthma and biomarkers for asthma severity. Researchers can  request access to the data on dbGaP .

Research funded by the NHLBI

Our  Division of Lung Diseases  and its  Airway Biology and Disease Branch  oversee much of the research on asthma we fund. The Asthma Program supports research related to asthma, including the role of inflammation in the development of asthma, genetics and asthma, and clinical management of asthma in adults and children.

Find  funding opportunities  and  program contacts  for asthma research.

Current research on asthma treatment

  • How ventilators may lead to asthma: The NHLBI-funded Post-Vent study will use data collected from the Prematurity-Related Ventilatory Control (Pre-Vent): Role in Respiratory Outcomes NHLBI Collaborative Program to study long-term health outcomes of premature birth and intermittent low oxygen levels shortly after babies are born prematurely. These babies often develop asthma. This study will try to predict which premature babies are most likely to develop asthma. 
  • Why medicines work: An NHLBI-funded study is assessing how an antibiotic called azithromycin (AZ) reduces severe wheezing in preschool children seen in the emergency room. While prior studies have shown that AZ benefits these children, it is unclear if the beneficial effects are because of the antibacterial activity of AZ or because of the anti-inflammatory activity of AZ. To help answer this question, this study will compare whether children with bacteria growing in their throats get more benefit from AZ treatment than children who do not have bacteria growing in their throats at the time they go to the emergency room with severe wheezing.
  • Personalized medicine: The  Precision Interventions for Severe and/or Exacerbation Prone Asthma Network (PrecISE) is conducting clinical trials to identify personalized medicine approaches that treat severe asthma more effectively. It has established 30 locations nationwide that will test new and approved treatments based on each patient’s specific biology and biomarkers.

Find more NHLBI-funded studies on asthma treatment at NIH RePORTER. 

An illustration of lungs

Learn about one PrecISE study that is looking at treatments that may help support people with severe asthma or asthma that hasn’t responded to traditional treatments: Personalizing treatment for severe asthma .

Current research on asthma biology

The different bacteria in a person’s body can affect the immune system. We support studies to figure out whether different bacteria play a role in developing certain types of asthma.

  • Airway cells and asthma: NHLBI-funded research will look at how genes are regulated in airway epithelial cells to better understand how they affect the development of asthma. Epithelial cells line the lung’s airways. As researchers learn more about how changes in the cells lead to asthma, they hope to develop treatments to reprogram the epithelium and prevent or cure asthma and other lung diseases.
  • Bacteria in the airways: An AsthmaNet  study found  different bacteria in the airways of people with asthma compared to those without asthma. Some of the observed differences could help predict the response to inhaled steroids. Researchers can  request the data  through our Biologic Specimen and Data Repository Information Coordinating Center.
  • Targeted treatments for severe asthma: NHLBI-supported researchers are developing new and personalized approaches to treating severe asthma . The study builds on earlier research which led the researchers’ discovery of three mechanisms that are relevant to severe asthma.

Find more NHLBI-funded studies on asthma biology at NIH RePORTER.

Researchers have identified a key role for the circadian system — the biological clock that controls your sleep/wake cycle: Study of biological clock may explain why asthma worsens at night .

Current research on asthma disparities

African Americans are more likely to develop asthma and three times more likely to die from asthma-related causes than white Americans. Research on this topic is part our broader commitment to addressing  health disparities and inequities . 

  • Genetic factors: The  Consortium on Asthma among African-Ancestry Populations in the Americas (CAAPA)  aims to discover genes that confer asthma risk among individuals of African ancestry and to study genetic diversity in populations of African descent. Read  some of the results here  or  request access to the data on dbGaP .
  • Comprehensive care for at-risk children: We also fund the  Asthma Empowerment Collaborations to Reduce Childhood Asthma Disparities . We support clinical trials to evaluate programs that provide comprehensive care for children at high risk of poor asthma outcomes, such as low-income minority children. 
  • Race, sex, and socioeconomic factors: The NHLBI recently launched the DECIPHeR program to study differences in heart and lung diseases among groups defined by race and ethnicity, sex and/or gender, and socioeconomic status. The first projects began in September 2020, with one project focused on asthma in children in Colorado.  Working with communities across the state, from rural to urban areas in Colorado, researchers will work with school-based asthma navigators and nurses to test a team approach to asthma control in school children in low-income areas.

Find more NHLBI-funded studies on  asthma and health disparities .

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An NHLBI-funded study found that African-American boys, but not girls, with higher levels of BPA (Bisphenol A) tended to have more asthma symptoms: Study links exposure to higher levels of BPA plasticizer to more asthma symptoms in black boys .

Asthma research labs at the NHLBI

The  Laboratory of Asthma and Lung Inflammation , located within the  Pulmonary Branch , is focused on developing new treatment approaches for people with severe asthma. Headed by Stewart J. Levine, M.D., the lab’s researchers found a new biological pathway that leads to asthma. They continue to study this pathway, as well as an important molecule in it called apolipoprotein E (ApoE).

“By studying the pathways of the disease, we identified a new biological mechanism that leads to asthma,” explained Stewart J. Levine, M.D. Read the research feature: Disease pathways lead to possible new treatment for severe asthma .

Learn about research opportunities in the lab:

  • Post-doctoral Fellowship on Apolipoprotein Pathways in Asthma  
  • Graduate Medical Education (GME): NHLBI/UMD Pulmonary-Critical Care Fellowship  

Related asthma programs and guidelines

  • The NAEPP’s  Expert Panel Report 4 (EPR-4) Working Group  was established in 2018 to update the 2007  Guidelines for the Diagnosis and Management of Asthma (EPR-3) in focused topic areas. The working group members reviewed the latest research to update the guidelines on treatments and management of asthma, including the role of immunotherapy, the effectiveness of indoor allergen reduction, and the use of fractional exhaled nitric oxide (FeNO). Read  Asthma Management Guidelines: Focused Updates 2020 .
  • Learn More Breathe Better®  is a national health education program for asthma, COPD, and other lung and respiratory diseases. The program raises awareness about asthma and other lung conditions and supports the promotion, implementation, and adoption of evidence-based care.  Learn More Breathe Better® Asthma offers a  series of asthma handouts  to patients and caregivers, including tips for talking to your doctor. 
  • Since 1989, the  National Asthma Education and Prevention Program (NAEPP)  has worked with medical associations, voluntary health organizations, and community programs to educate patients, healthcare professionals, and the public about asthma.
  • The Lung Tissue Research Consortium (LTRC)  provides human lung tissues to qualified investigators for use in their research. The program enrolls patients who are planning to have lung surgery, collects blood and other clinical data from these donors, and stores donated tissue that otherwise would be discarded after the lung surgery. The LTRC provides tissue samples and data at no cost to approved investigators.

Explore more NHLBI research on asthma

The sections above provide you with the highlights of NHLBI-supported research on asthma. You can explore the full list of NHLBI-funded studies on the NIH RePORTER .

To find more studies:

  • Type your search words into the  Quick Search  box and press enter. 
  • Check  Active Projects  if you want current research.
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Asthma Research and Practice

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  • Published: 21 October 2019

A systematic review of psychological, physical health factors, and quality of life in adult asthma

  • Sabina Stanescu   ORCID: orcid.org/0000-0003-0792-8939 1 ,
  • Sarah E. Kirby 1 , 2 ,
  • Mike Thomas   ORCID: orcid.org/0000-0001-5939-1155 2 , 3 ,
  • Lucy Yardley 1 &
  • Ben Ainsworth 4  

npj Primary Care Respiratory Medicine volume  29 , Article number:  37 ( 2019 ) Cite this article

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  • Outcomes research
  • Quality of life

Asthma is a common non-communicable disease, often characterized by activity limitation, negative effects on social life and relationships, problems with finding and keeping employment, and poor quality of life. The objective of the present study was to conduct a systematic review of the literature investigating the potential factors impacting quality of life (QoL) in asthma. Electronic searches were carried out on: MEDLINE, EMBASE, PsycINFO, the Cochrane Library, and Web of Science (initial search April 2017 and updated in January 2019). All primary research studies including asthma, psychological or physical health factors, and quality of life were included. Narrative synthesis was used to develop themes among findings in included studies in an attempt to identify variables impacting QoL in asthma. The search retrieved 43 eligible studies that were grouped in three themes: psychological factors (including anxiety and depression, other mental health conditions, illness representations, and emotion regulation), physical health factors (including BMI and chronic physical conditions), and multifactorial aspects, including the interplay of health and psychological factors and asthma. These were found to have a substantial impact on QoL in asthma, both directly and indirectly, by affecting self-management, activity levels and other outcomes. Findings suggest a complex and negative effect of health and psychological factors on QoL in asthma. The experience of living with asthma is multifaceted, and future research and intervention development studies should take this into account, as well as the variety of variables interacting and affecting the person.

Introduction

Over 235 million people worldwide are living with asthma, which is one of the leading non-communicable diseases worldwide. 1 , 2 Symptoms, exacerbations, and triggers in asthma are associated with lower quality of life (QoL), tiredness, activity limitation, negative effects on social life and relationships, problems with finding and keeping employment, and reduced productivity. 3 , 4 , 5 , 6 , 7 People with asthma are up to six times more likely than the general population to have anxiety or depression, 8 and 16% of people with asthma in the UK have panic disorder, 9 compared to 1% in the general population. 10 People with brittle asthma (difficult-to-control asthma with severe, recurrent attacks) demonstrate even greater comorbidity and maladaptive coping styles. 11 Psychological dysfunction is often unrecognized in primary care, despite being significantly associated with poor asthma outcomes, including asthma control and QoL. 8 , 12 , 13 Indeed, the European Asthma Research and Innovation Partnership has identified understanding the role of psychological factors as an unmet need in improving asthma outcomes. 14 , 15 They propose that anxiety and depression are present at all three stages of the experience of asthma: onset, progression, and exacerbation. 14

A recent meta-analysis found that asthma diagnoses significantly increased the risk of psychological and health conditions (such as cardiovascular/cerebrovascular diseases, obesity, hypertension, diabetes, psychiatric and neurological comorbidities, gut and urinary conditions, cancer, and respiratory problems other than asthma). 16 In addition, studies have pointed towards an impact on QoL in people with asthma of additional health and psychological factors, such as comorbid anxiety or depression, higher body mass index(BMI), professional status, and feelings of lack of control over health (for example, refs 17 , 18 ). Such evidence reinforces the argument that the needs of people with asthma should be approached in conjunction with these additional factors, rather than using a single-illness approach, aiming to reduce the adversity of people’s experience. However, the extent to which psychological and physical health factors interact and impact asthma outcomes is yet to be systematically explored. This systematic review aims to provide a narrative synthesis of the literature exploring psychological and physical health factors that influence QoL in adults with asthma.

Study characteristics

The search and screening process identified 43 eligible papers, published between 2003 and 2019 (see Fig. 1 for PRISMA flowchart 19 ). The characteristics of each study are summarized below in Table 1 . Twelve studies were conducted in Europe, 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 17 in North America, 12 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 7 in Australia, 17 , 48 , 49 , 50 , 51 , 52 , 53 4 in Asia, 54 , 55 , 56 , 57 and 3 in Africa. 58 , 59 , 60 All papers employed a quantitative approach comprising 2 longitudinal studies 31 , 44 and 41 cross-sectional studies. Only 4 studies included a control group. 21 , 28 , 29 , 31 Overall, the majority of papers had a large sample size (ranging between 40 and 39,321 participants; 30 papers included a sample size of >100). The majority of studies recruited from primary care or the general population, using self-report to confirm a diagnosis of asthma. Only a few studies recruited from secondary and tertiary asthma clinics. 12 , 27 , 36 , 41 , 44 , 48 , 60 There was a high occurrence ( n  = 14) of exclusion criteria relating to specific demographic or asthma characteristics, as well as mental health conditions and comorbidities, which restricted the study sample without a reason being given. Most studies used self-report measures, 17 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 32 , 33 , 34 , 35 , 36 , 37 , 39 , 41 , 42 , 43 , 44 , 45 , 46 , 48 , 49 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 with a small proportion using psychiatric interviews to screen for mental health conditions. 12 , 31 , 38 , 40 , 50 The majority of studies used asthma-specific QoL measures ( n  = 29), 12 , 21 , 23 , 25 , 27 , 28 , 30 , 32 , 33 , 34 , 35 , 36 , 37 , 39 , 40 , 41 , 42 , 44 , 48 , 49 , 50 , 51 , 54 , 55 , 56 , 58 , 59 , 60 , 61 17 included an health-related QoL measure ( n  = 18), 17 , 20 , 22 , 23 , 24 , 25 , 28 , 30 , 31 , 34 , 35 , 36 , 38 , 43 , 50 , 51 , 52 , 55 and 4 used general measures of QoL ( n  = 7); 26 , 35 , 45 , 46 , 47 , 57 , 62 11 papers used >1 measure of QoL. 23 , 25 , 28 , 30 , 34 , 35 , 36 , 37 , 50 , 51 , 55 The average age across included studies was 42.1 years (and 61.57% were female). Papers report prevalence rates of between 16.8% and 48.9% for depression and between 13.3% and 44.4% for anxiety, 20 , 27 , 33 , 38 , 50 , 56 , 58 , 60 with an average of 28.31% for a diagnosis of anxiety or depression. Across several studies, the prevalence of other mental health conditions was 28.31% on average (ranging between 28% and 80%). 12 , 37 , 38 , 40 , 42 Between 72% and 86.9% of people with asthma had at least one additional physical condition and between 21% and 26.3% had ≥2; 25 , 34 , 56 26.36% had, on average, at least one other physical health condition. On average, people with asthma were significantly more likely to have a BMI of >30 (and between 61% and 75.1% had a BMI >25). 26 , 45 , 59 The quality assessment identified that most studies were of a reasonable quality; however, it should be noted that some measures used could be considered inappropriate for the research aim or the population under investigation. Examples include measuring general QoL with an asthma-specific measure or administering a geriatric depression questionnaire to a young adult population.

figure 1

PRISMA statement of included and excluded papers

Narrative synthesis

Narrative synthesis generated three overarching themes: psychological factors, health factors, and multifactorial aspects (see Table 2 for themes and subtheme descriptions). Overall, patients with asthma demonstrated impaired QoL, which was further decreased by psychological factors (e.g. anxiety, depression, emotion regulation, illness perceptions), health risk factors (such as an increased BMI), and the presence of a co-existing mental health or physical condition (such as rhinitis, cardiovascular disease, diabetes, etc.). Having more than one co-existing condition or psychological factor impacted overall QoL even more substantially. Results for each of the aspects found are presented below.

Psychological factors

Within this first theme, four subthemes were generated. These comprised ‘anxiety and depression’, ‘other mental health conditions’, ‘emotional regulation’, and ‘illness representations’.

Anxiety and depression were notably the most commonly considered factors ( n  = 30). A high prevalence of people with asthma showed symptoms of or clinical diagnoses of anxiety or depression, which appeared to play a key role in understanding the relationship between asthma and QoL. Overall, having a diagnosis of anxiety or depression was associated with poorer QoL across all dimensions (e.g. activity limitation, physical or mental wellbeing, social or role functioning, etc.), as well as health perceptions. 24 , 36 , 46 , 50 , 54 In particular, one study (of undergraduate students aged 18–25 years, with childhood-onset asthma) found that anxiety was significantly associated with asthma QoL, as was the interaction between anxiety and depression, 32 while others found that generally anxiety and depression both predicted worse QoL independently (refs 12 , 29 , 33 , 38 , 42 , 44 , 56 , 60 ). One study found that the average asthma-related QoL scores for people with asthma and depression were 1.4 times lower compared to people with asthma and no depression. 33 Having current depression or anxiety was associated with worse QoL than was having a lifetime diagnosis; this was in turn was greater than having no depression or anxiety. 45 Having a history of major depression was also significantly associated with worse physical and mental functioning, compared to those with asthma and no depression. 38 There was considerable variability across variance explained, with depression found to account for between 3% 40 and 56% 30 of the variance in QoL, whereas anxiety was found to account for between 2% 40 and 68%. 21

In contrast, one study found that having either a depressive or an anxiety disorder significantly impacted asthma QoL but having both was not significantly different than only having one, 40 which is dissonant with other studies. Another study of 90 people with difficult asthma found that having anxiety or depression had no significant effect on QoL. 48 In addition, although depression was associated with poorer QoL, it did not inflate the relationship between asthma severity and QoL. 29 All other studies were significant but showed only small-to-moderate effect sizes. Having a full clinical diagnosis of anxiety or depression was not significantly worse (in terms of QoL) than having only some symptoms of anxiety and depression.

Studies also considered the impact of anxiety and depression on specific subdomains of QoL and asthma-specific QoL. Having anxiety was not associated with physical functioning, mental health or health perception, 38 or the physical component of QoL. 20 Depression, however, was associated with significantly poorer QoL on physical dimensions and activity limitation, 20 , 21 , 23 , 30 , 38 , 45 , 53 , 55 , 58 although one study found significant results only for participants with uncontrolled asthma. 22 In relation to asthma-specific QoL, depression and anxiety were significantly associated with decreased asthma-specific QoL. 17 , 21 , 23 , 27 , 28 , 32 , 33 , 36 , 37 , 40 , 50 , 54 , 55 , 58 , 61

Nine studies looked at other mental health conditions, such as panic disorder with or without agoraphobia, 24 , 38 , 44 , 57 personality disorders, 31 alexithymia, 23 somatization, 38 mood disorders, 12 , 40 , 57 schizophrenia, eating disorders, substance use disorders, 38 and general occurrence of any psychiatric disorder. 12 , 17 The results in this subtheme were mixed, but overall they suggest that the presence of an additional mental health condition is significantly associated with a decrease in QoL in patients with asthma. 12 , 17 Panic disorder was also shown to be both significantly 24 and non-significantly 57 associated with poorer mental and physical components of QoL. Alexithymia in people with asthma was not associated with poorer QoL. 23 Having asthma and a personality disorder was associated with lower general QoL, 31 as well as lower scores for physical health, vitality, pain, general health, social function, mental health, and emotional role (physical function was not significant). This association was not found for people without asthma, suggesting that it is the combination of conditions (asthma and co-existing mental health conditions) that may lead to the negative impact on QoL. 31

The emotion regulation subtheme included studies that explored the relationship between emotional states, negative affect (not related to anxiety, depression, or other mental health conditions), or coping and QoL in people with asthma. QoL in asthma was found to be influenced by affect and a predisposition to negative states, as found by four studies. 28 , 39 , 41 , 51 For instance, a model of age, gender, negative affect, and medical problems accounted for 20% of symptoms and 23% of activity limitation. 39 This was supported by findings that negative mood is associated with poor scores on both the mental and physical components of the Asthma Quality of Life Questionnaires (AQLQ), 28 as well as a positive correlation between active coping and asthma QoL. 51 Despite heterogeneity, the impaired QoL was associated with impulsive-careless coping 41 and avoidant coping. 51 Overall, the presence of psychological distress seemed to affect people with asthma more than people without asthma in terms of QoL.

Illness-related cognitions are people’s patterns of beliefs about the characteristics of their conditions, which in turn influence their appraisal of severity and can determine future behaviours. 63 A number of illness-related cognitions and perceptions significantly predicted QoL in seven studies. 26 , 34 , 37 , 42 , 43 , 51 , 60 For instance, asthma self-efficacy 42 was positively associated with QoL. However, decreased QoL was significantly predicted by a series of varied illness perceptions: subjective illness severity, uncertainty in illness, illness intrusiveness, 43 perceived disability, 60 health beliefs and attitudes, 34 perceived severity, 34 level of confidence or self-efficacy in managing asthma, 51 satisfaction with illness, 51 anxiety sensitivity for physical concerns, 39 and satisfaction with life. 37 In addition, a model of subjective and objective illness severity accounted for 24% of the variance in QoL, further supporting the effect of illness perceptions on QoL. 34

Physical health factors

Two subthemes were generated in the physical health factors theme: additional physical conditions and BMI.

Ten papers examined additional physical conditions in relation to QoL in asthma; 25 , 27 , 34 , 39 , 46 , 47 , 48 , 49 , 52 , 53 most only referred to ‘comorbidity’ or ‘medical problems’ as a measure of frequency of additional conditions. 34 , 36 , 39 Some studies looked at both general and individual co-existing conditions 25 , 48 , 52 and others counted chronic conditions but did not include them in further analyses. 33 , 36 , 56 , 59 Of the ones that did explore individual conditions, the highest impact seemed to be provoked by musculoskeletal conditions. 25 Similarly, statistically and clinically significant decreases in activity levels were also found for people with asthma and multimorbid conditions. 52 Other conditions investigated included respiratory conditions, 47 diabetes, 25 , 48 obesity, 48 hypertension, 25 , 39 gastro-oesophageal reflux disorder, 48 rhinitis, 48 , 49 vocal cord dysfunction, 48 sleep apnoea, 48 musculoskeletal disorders, 25 , 39 arthritis, 39 , 52 heart disease, 25 stroke, 39 , 52 cancer, 39 , 52 osteoporosis, 52 dysfunctional breathing, 48 headaches, 39 and allergic status. 27 , 39 The consensus was that having an additional physical condition significantly decreased QoL in asthma, the effect being amplified with the addition of further conditions.

Eleven papers exploring BMI found that it consistently influenced QoL for people with asthma both directly as a multimorbid factor and indirectly by increasing the chance of additional conditions and activity limitation. 25 , 26 , 28 , 29 , 35 , 42 , 44 , 45 , 48 , 56 , 59 In particular, one study found that generic health status decreased for overweight and obese patients with asthma. People with asthma with obesity had on average 5.05 more restricted activity days than people without obesity or without asthma. 35 Other studies found that increased BMI was an independent factor in predicting poorer QoL 48 and that QoL was two times worse in overweight and three times worse in obese people with asthma. 59 In contrast, one study found that overweight BMI made no difference; however, being obese did. 27 Almost ½ of obese patients and 25% overweight patients had problems with mobility, pain, discomfort, self-care, and usual activities (compared to <15% people with asthma of normal weight). 26

Multifactorial aspects

Seven studies included statistical analyses to explore potential mechanisms for the relationship between asthma QoL and additional physical conditions, BMI, and psychological factors. 17 , 35 , 42 , 45 , 50 , 56 , 59 Results from studies in this group are complex, indicating that people with asthma are at a higher risk of adverse outcomes (such as exacerbated symptoms or decreased QoL) if they also have a high BMI and depression. 35 , 42 , 56 , 59 People with current depression and asthma are more likely to be obese and 3.9 times more likely to report fair or poor general health. 45 A few of these studies have explored the relationship between these factors further. For example, people with asthma and obesity were more likely to have additional physical comorbidities and poorer QoL. 59 Significant increases in major depression were associated with dyspnoea, 50 and depression and perceived control of asthma significantly mediated between BMI and QoL. 35 Higher BMI has also been associated with worse asthma-specific self-efficacy, which was in turn associated with decreased QoL. 42

The aim of the present review was to synthesise the literature exploring health and psychological factors that influence QoL in adults with asthma. Previous evidence shows that QoL is generally lower in people with asthma and compounded by poor asthma control and severity. 13 The narrative synthesis in the present study builds on this by identifying three themes, encompassing a number of factors that substantially explain further impairment in QoL for people with asthma. These were not limited to individual components but also combinations of co-existing conditions, risk factors, and health and psychological factors, which consistently showed a negative impact on QoL.

Anxiety and depression were the most commonly reported psychological factors associated with impaired QoL, but effects were also found for other mental health conditions, illness representations, and emotion regulation. These results are generally consistent with previous research showing not only that among people with asthma there are more people with depression than without 8 but also with an increase in depression, the risk of asthma increased. 64 Although the relationship between anxiety and depression and asthma-specific QoL were not further considered in the primary sources, they point towards either a link with activity limitation or a cumulative impact of the interaction between these psychological factors, which in turn affect the QoL of people with asthma. In addition, it is argued that people with asthma use more emotion-focused, and generally maladaptive, coping strategies, such as avoidance. 65 Despite this, psychotherapy, such as cognitive-behavioural therapy and counselling has had limited effectiveness in improving asthma outcomes. 66

Physical health factors, such as high BMI and co-occurring health conditions, were extremely common in people with asthma, consistent with existing literature. 16 This affects QoL both directly and indirectly, affecting self-management and illness perceptions. As such, non-pharmacological treatments such as lifestyle change and activity promotion could prove effective. For instance, a higher proportion of people with asthma seem to have overweight or obese BMI 67 and weight loss intervention studies have been associated with improvements in asthma symptoms. 68

One of the fundamental components of reduced QoL is activity limitation, which is especially relevant to people with asthma, with or without additional conditions or psychological risk factors. This has been widely acknowledged by previous research, to the extent that it has been included as one of the components of asthma-related QoL measures, such as the AQLQ. 69 Furthermore, it is not surprising that decreased QoL in adults with asthma is associated with depression or high BMI, both of which have been consistently associated with activity limitation (e.g. refs 70 , 71 ). In addition, depression was found to affect QoL on the physical components as well as the mental ones, which has interesting implications for future research and clinical practice.

It is important to note the high prevalence of anxiety, depression, and chronic conditions, despite frequent exclusion of comorbid psychiatric conditions. This was found throughout the included papers and is consistent with previous research (e.g. refs 8 , 16 ). This does not only mean that psychological and health factors significantly add to the burden of living with asthma but also that the occurrence of psychological dysfunction and health risk factors seem to be common in people with asthma. In addition, the complex nature of patients with chronic diseases such as asthma, with factors interacting, adds to the negative experience of living with asthma. Results are similar to previous meta-analyses and reviews, 8 , 72 pointing towards conclusive evidence that additional factors (physical or psychological) decrease QoL and functionality in asthma. Finally, these effects were consistent, regardless of the measure of QoL used (asthma specific, health related, or general). This suggests that the identified factors may affect people with asthma more than people without asthma or that the cumulative impact of comorbidities is greater than arithmetically assumed.

The quality of the present review needs to be discussed in relation to the methodology and robustness of the synthesis, determined by the quantity and quality of individual studies included. 73 The quality assessment identified that most studies were of a reasonable quality overall, although all papers had one or two elements that were of a slightly lower quality (this included aspects such as recruitment from only one hospital reducing generalizability or self-report vs objective measurement of weight for BMI calculations). However, this was not problematic for the purposes of this review as the focus was to identify potential factors considered in research rather than classify the methodological quality used to measure their impact on QoL. In addition, the search terms in this review could have limited the number and kind of studies included. For instance, not every potential comorbid condition was listed. This could be a focus for future research. Socio-demographic factors were not included, which can be considered a limitation; however, the breadth of the area was deemed too much for the scope of the present review and could also be the focus of future research. The majority of included studies were observational and as such could not be used to determine causal mechanisms. However, the aim of this review was only to identify potential factors involved in decreased QoL in asthma, rather than build a causal model. Similarly, the impact of individual factors was not measured and could be explored in future research.

A strength of the present review is that it uses a novel approach to QoL in asthma, by systematically taking into account additional aspects that influence the experience of living with asthma and impact QoL. Results suggest both a direct association of the identified aspects, as well as indirectly through interactions with other aspects of living with asthma, such as overarching illness perceptions and activity limitation. The present review emphasizes some interesting and novel findings for asthma and QoL research. Three main implications for future research and practice are proposed. First, for future research, the findings of this review should be used to further explore and understand the factors impacting QoL in people with asthma. It is crucial to explore the needs and experience of patients with complex medical problems, in order to unpick the different factors impacting on QoL. Second, the results are relevant for practitioners, particularly in primary care, as they draw attention to the prevalence of various physical and mental health factors that can interact and affect asthma outcomes. This could influence training or guidelines on potential factors to consider during appointments and consultations. Finally, most current non-pharmacological interventions for patients with chronic conditions tend to overlook the complex needs of patients in a multimorbidity context. As such, it is suggested that future intervention development should use a personalized, tailored approach that aims to address the needs of patients with complex medical problems in the wider context of their experience of living with asthma.

This review demonstrates that the themes and factors identified through inductive narrative synthesis illustrate that QoL in asthma cannot be determined in a simplistic way. The findings suggest a complex experience in living with asthma, one that has a stronger impact on QoL than the sum its of parts. People with asthma and their QoL cannot be viewed separately from the psychological and other health elements that they experience. Future research is encouraged to take a function-oriented approach to QoL in asthma, including management of multimorbid conditions when planning studies; clinical practice should also acknowledge the additional and complex needs of people with asthma by offering relevant, person-based tailored interventions.

Search strategy

The initial search was carried out in April 2017 and was updated in January 2019. Databases searched included MEDLINE, EMBASE, PsycINFO, the Cochrane Library, and Web of Science. Search terms used comprised a combination of the following key terms: asthma (MESH term), psychological/psychosocial and factor/determinant/predictor, comorbid, multimorbid, anxiety, depression, illness perception, illness cognition, illness representation, locus of control, self-efficacy, risk factor, quality of life, health-related quality of life, wellbeing, distress, health status, burden. In addition, a hand search of all the references of included papers was performed as well as a grey literature search on Google Scholar.

Study selection

Studies were included if they investigated psychological or physical health factors and included QoL in adults with asthma as primary or secondary outcome. Psychological factors were considered any modifiable factors, including thoughts, beliefs, attitudes, or emotions of people with asthma, as well as the presence of any co-occurring mental health condition. Physical health factors were defined as any physical comorbid or multimorbid condition or risk factor. These were chosen to allow as much inclusivity as possible and to reflect the exploratory nature of this review. Intervention studies were excluded, as they rarely considered the impact of health or psychological factors on QoL but rather investigated how interventions improved asthma outcomes. Studies were excluded if they were conference abstracts, reviews, or not primary research or the full text not in English, German, or Spanish language.

Data extraction and quality appraisal

Data extracted comprised authors, year of publication, study sample, predictors, QoL measurement (outcome), and findings. The AXIS tool 74 was used to assess the quality of included papers. This contains questions on study design, sample size justification, target population, sampling frame, sample selection, measurement validity and reliability, and overall methods and does not offer a numerical scale. No papers were excluded or weighted based on the quality assessment.

Data synthesis

Owing to heterogeneity of QoL measures and the range of variables used in the included studies, narrative synthesis was used to describe and group similar findings, explore patterns identified in the literature, and develop a narrative account of the results. 73 This is an approach to systematic reviews involving the synthesis of findings from multiple sources and relies primarily on word and text to summarise the findings.

All data generated or analysed during this study are included in this published article.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

World Health Organization. Chronic Respiratory Diseases - Asthma http://www.who.int/respiratory/asthma/en/ (2018).

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Stanescu, S., Kirby, S.E., Thomas, M. et al. A systematic review of psychological, physical health factors, and quality of life in adult asthma. npj Prim. Care Respir. Med. 29 , 37 (2019). https://doi.org/10.1038/s41533-019-0149-3

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research paper about asthma

ORIGINAL RESEARCH article

Dietary factors and risk for asthma: a mendelian randomization analysis.

Wenwen Yang&#x;

  • 1 The First Clinical Medical College, Lanzhou University, Lanzhou, Gansu, China
  • 2 Qilu hospital of Shandong University, Shandong University, Jinan, Shandong, China
  • 3 Department of Thoracic Surgery, the First Hospital of Lanzhou University, Lanzhou, Gansu, China
  • 4 Gansu Province International Cooperation Base for Research and Application of Key Technology of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China

Background: Previous research has found a link between dietary factors and asthma. However, few studies have analyzed the relationship between dietary factors and asthma using Mendelian randomization. Methods: The IEU Open GWAS project ( https://gwas.mrcieu.ac.uk/ ) was the source of exposure and outcome datasets. The exposure datasets included Alcoholic drinks per week, Alcohol intake frequency, Processed meat intake, Poultry intake, Beef intake, Non-oily fish intake, Oily fish intake, Pork intake, Lamb/mutton intake, Bread intake, Cheese intake, Cooked vegetable intake, Tea intake, Fresh fruit intake, Cereal intake, Salad/raw vegetable intake, Coffee intake, and Dried fruit intake. The weighted median, MR-Egger, and Inverse Variance Weighted methods were used as the main methods of Mendelian randomization analysis. Heterogeneity and pleiotropic analysis were performed to ensure the accuracy of the results.

Results: Alcohol intake frequency (after removing outliers OR: 1.217; 95% CI: 1.048-1.413; p=0.00993) was related to an increased risk of Asthma. Fresh fruit intake (OR: 0.489; 95% CI: 0.320-0.748; p=0.000954) and Dried fruit intake (after removing outliers OR: 0.482; 95% CI: 0.325-0.717; p= 0.000312) were discovered as protective factors. Other dietary intakes found no causal relationship with asthma.

Conclusion: This study found that dried fruit intake and fresh fruit intake were associated with a reduced risk of asthma, and alcohol intake frequency was associated with an increased risk of asthma. This study also found that other factors included in this study were not associated with asthma.

1. Introduction

As a common chronic disease, asthma is a major health problem worldwide ( 1 ). The incidence of asthma has increased rapidly over the past few decades ( 2 – 4 ). The goal of asthma treatment is to minimize both symptoms and the risk of adverse outcomes ( 5 ). The increase in asthmatic patients has increased the medical burden worldwide. In Western countries, the financial burden for an individual asthma patient ranges from US$300 to US$1,300 per year ( 6 ). Asthma patients in developing countries face both a financial burden and a higher risk of adverse outcomes due to appropriate treatment is deficient. Dietary factors may play an important role in this increase in asthma ( 7 ). In adults, the causes of asthma include environmental and lifestyle factors. A previous study has reported the critical role of diet in the development of allergic diseases ( 8 ). Dietary factors may be directly related to asthma pathogenesis ( 9 ). Knowing whether dietary changes benefit patients with asthma has important implications for both clinicians and patients with asthma. Previous studies have found that alcohol intake ( 10 ), fruit intake ( 11 ), vegetable intake ( 12 ), dairy intake ( 13 ), fish intake ( 14 ), and meat intake ( 15 ) were associated with asthma or asthma symptoms. Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs), which has advantages over other research methods ( 16 ). However, there are few MR studies on the causal relationships between dietary factors and asthma. We, therefore, performed this MR analysis to explore the relationships between dietary factors and asthma.

The following basic assumptions constitute the premise of MR analysis. First, IVs must be intensely associated with the exposure factor(s). Second, IVs cannot be directly correlated to the outcome. Third, IVs were not related to any potential confounding factors. The GWAS summary-level data used in this study was issued by the IEU open GWAS project. This project, supported by the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, collated and analyzed GWAS data from UK Biobank, published articles, and FinnGen biobank. This study was exempt from the approval of the Ethical Review Authority because the data used in this study was public, anonymized, and de-identified.

2.1. Data sources

Diet-Related Exposure factors used in this study included vegetable intake (Salad/raw vegetable intake and Cooked vegetable intake), meat intake (Processed meat intake, Poultry intake, Beef intake, Non-oily fish intake, Oily fish intake, Pork intake, and Lamb/mutton intake), staple food intake (Bread intake and Cereal intake), beverage intake (Alcoholic drinks per week, Alcohol intake frequency, Tea intake, and Coffee intake), fruit intake(Dried fruit intake and Fresh fruit intake), and another food intake (Cheese intake). These GWAS summary-level data were extracted directly or indirectly from UK Biobank by the IEU open GWAS project. The GWAS summary-level data of asthma was extracted from FinnGen biobank by the IEU open GWAS project. We did not use proxy SNPs when finding SNPs from the outcome, mainly because the FinnGen biobank contained enough SNPs (16,380,176 SNPs in the dataset of asthma). More information about the exposure and outcome datasets is presented in Table 1 and Supplementary Table 1 .

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Table 1 Information of the exposures and outcome datasets.

2.2. The selection of IVs

In MR analysis, IVs were utilized as mediators between exposure factors and outcomes to explore the causal relationship between exposure and outcomes. IVs are generally genetic variations, among which Single nucleotide polymorphisms (SNPs) are the most commonly used. SNPs associated with dietary factors were extracted from the IEU open GWAS project ( https://gwas.mrcieu.ac.uk/ ). we screened the SNPs intensely related with exposures at the genome-wide significance level (p < 5×10 –8 ), clumping window > 10,000 kb, and the linkage disequilibrium level (r2 < 0.001). More information is shown in Table 1 . The F statistic was used to ensure the strong association between IVs and exposure, The F statistic greater than 10 was generally considered to meet the requirements of strong association ( 17 ).

2.3. Statistical analysis

We conducted the inverse variance weighted (IVW) method as the primary method for calculating the causal effect. The IVW model is the method with the strongest ability to detect causation in the two-sample MR analysis ( 18 ). We contrasted the consequences of the IVW method with the weighted median and the MR-Egger methods. The weighted median method allows no more than 50% of invalid IVs, and the MR-Egger method allows all IVs to be voided. Therefore, it will be more convincing when the three models are consistent. The heterogeneity of the IVW model was assessed by Cochran’s Q test. Cochran’s Q-test p<0.05 indicated heterogeneity. However, the existence of heterogeneity does not mean that the IVW model is necessarily invalid. The MR-Egger method allows for the existence of non-zero intercepts and was used to detect directional pleiotropy. Leave-one-out analysis was performed to assess whether there was a significant effect on the results after the removal of a single SNP. We use the MR-PRESSO method to detect outliers. Once outliers were found, they will be removed immediately. After removing outliers, the MR analysis will be performed again. All analyses were performed in R software (version 4.2.0) using the TwoSampleMR package ( 19 ).

The causal relationship between dietary factors and asthma were analyzed using 18 different exposure factors. The amounts of SNPs used in this study ranged from 7 to 92. The F-statistics are all greater than 10 (range: 15.502 to 112.254). The number of European-descent individuals included in the exposures ranged from 335,394 to 462,346. The outcome included 20 629 European-descent asthma cases and 135 449 European-descent controls from the FinnGen biobank, and there was little overlap between the populations involved in exposures and outcome. See Table 1 for more information on exposures and results. The number of SNPs used for different exposures in this study ranged from 7 to 92, and the range after removing outliers was between 5 and 90 (the number of outliers found in different exposures ranged from 0 to 2). See Table 2 for more information. As shown in Table 1 , the F statistic (after removing outliers) ranges from 15.502 to 112.254, which indicates that IVs used in our study satisfies the requirements of strong association with exposures.

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Table 2 The results of Mendelian randomization analyses.

In this study, a total of 3 causalities were identified (p < 0.05 by IVW method). We found that alcohol intake frequency (after removing outliers OR: 1.217; 95% CI: 1.048-1.413; p=0.00993) was related to an increased risk of Asthma. This discovery was further verified by the consequences of the MR-Egger (after removing outliers OR: 1.624; 95% CI: 1.010-2.610; p= 0.0483) and weighted median (after removing outliers OR: 1.270; 95% CI: 1.046-1.542; p=0.0157) model. Fresh fruit intake (OR: 0.489; 95% CI: 0.320-0.748; p=0.000954) and Dried fruit intake (after removing outliers OR: 0.482; 95% CI: 0.325-0.717; p= 0.000312) were discovered as protective factors. And we have reached the same conclusion in the Weighted median model (Fresh fruit intake OR: 0.462; 95% CI: 0.255-0.838; p=0.011; Dried fruit intake OR: 0.477; 95% CI: 0.284-0.801; p=0.0051). However, there were no significant results in the MR-Egger model (P>0.05). Cereal intake showed a positive result before the outliers were not removed, and the positive result disappeared after the outlier was removed (P= 0.0256 VS 0.0508). This study also found that Alcoholic drinks per week (OR: 0.903; 95% CI: 0.599-1.359; p=0.624; Outliers excluded: OR:0.804; 95% CI:0.577-1.120; p=0.196), Processed meat intake (OR: 1.315; 95% CI: 0.797-2.168; p=0.284; Outliers excluded: OR:1.136; 95% CI:0.721-1.790; p=0.583), Poultry intake (OR: 1.101; 95% CI: 0.151-8.051; p= 0.924; Outliers excluded: OR:1.827; 95% CI:0.565-5.906; p=0.314), Beef intake (OR: 0.807; 95% CI: 0.307-2.124; p= 0.664; Outliers excluded: OR:0.479; 95% CI:0.227-1.012; p=0.0538), Non-oily fish intake (OR: 0.957; 95% CI: 0.302-3.029; p= 0.940; Outliers excluded: OR:0.648; 95% CI:0.219-1.923; p=0.435), Oily fish intake (OR: 0.739; 95% CI: 0.501-1.091; p= 0.128; Outliers excluded: OR:0.751; 95% CI:0.543-1.038; p=0.0831), Pork intake (OR: 1.287; 95% CI: 0.429-3.863; p= 0.653; Outliers excluded: OR:1.225; 95% CI:0.498-3.013; p=0.658), and Lamb/mutton intake (OR: 1.127; 95% CI: 0.564-2.251; p= 0.735; Outliers excluded: OR:0.875; 95% CI:0.454-1.687; p=0.691), Bread intake(OR: 0.942; 95% CI: 0.615-1.442; p= 0.784; No outliers), Cheese intake(OR: 0.876; 95% CI: 0.678-1.132; p= 0.310; No outliers), Cooked vegetable intake(OR: 1.230; 95% CI: 0.558-2.710; p= 0.607; Outliers excluded: OR:0.982; 95% CI:0.475-2.031; p= 0.962), Tea intake(OR: 0.827; 95% CI: 0.621-1.101; p= 0.192; Outliers excluded: OR:0.793; 95% CI:0.608-1.034; p=0.0865), Salad/raw vegetable intake(OR: 0.810; 95% CI: 0.287-2.284; p= 0.691; Outliers excluded: OR:1.026; 95% CI:0.396-2.660; p=0.957), and Coffee intake(OR: 0.947; 95% CI: 0.676-1.328; p= 0.754; No outliers) were not associated with asthma either before or after exclusion of outliers. More MR analysis results are in Table 2 . Although heterogeneity was discovered in a considerable number of exposures (Cochrane’s Q test P<0.05), the consequences of the MR-Egger intercept suggested that no directional pleiotropy was discovered ( Table 2 ). Leave-one-out analysis indicated that the causalities of the positive results were very robust ( Figure 1 ). As shown in Table 2 , the results of the MR-PRESSO analysis were greatly consistent with the results of the IVW model (causal relationships were only shown in Alcohol intake frequency, Fresh fruit intake, and Dried fruit intake).

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Figure 1 The results of Leave-one-out analyses (A) Fresh fruit intake (B) Alcohol intake frequency (C) Dried fruit intake.

4. Discussion

The most important finding of this MR analysis is that Alcohol intake frequency, Fresh fruit intake, and Dried fruit intake were associated with asthma. Other findings are also noteworthy. First of all, a causal relationship between Cereal intake and asthma cannot be completely ruled out. In our analysis, if there were any outliers, we repeated the MR analysis and used the new results of the IVW model as a basis for determining whether there was a causal relationship. When we analyzed whether there was a causal relationship between grain intake and asthma, we found no causal relationship after excluding outliers (OR: 0.671; 95% CI: 0.450-1.001; p=0.0508). And a causal relationship was shown in the IVW model (OR: 0.617; 95% CI: 0.404-0.943; p= 0.0256) and the weighted median model (OR: 0.607; 95% CI: 0.373-0.987; p= 0.0442) before excluding outliers. We, therefore, think that the 95% confidence intervals and p-values at critical value have limited convincing power. Secondly, Alcoholic drinks per week, meat intake (Processed meat intake, Poultry intake, Beef intake, Non-oily fish intake, Oily fish intake, Pork intake, and Lamb/mutton intake), Bread intake, Cheese intake, Cooked vegetable intake, Tea intake, Salad/raw vegetable intake, and Coffee intake were not associated with asthma. To our knowledge, there have been many MR studies on the risk or protective factors of asthma ( 20 , 21 ). However, there are few studies involving meat intake, staple food intake, fruit and vegetable intake, and beverage intake. Asthma imposes a heavy economic burden on the world every year. Asthma and asthma complications also seriously affect the quality of life of patients with asthma. The conclusions of our study can help clinicians to improve their health education for patients with asthma, and encourage patients with asthma to change their eating habits (such as reducing the frequency of alcohol intake and increasing fruit intake). For those at high risk for asthma, adjusting dietary habits also reduces the risk of developing asthma. Therefore, this study has important implications for deepening the understanding of the risk and protective factors of asthma.

Alcohol can affect the human immune system ( 22 , 23 ). Numerous studies have shown that heavy drinking is associated with higher immunoglobulin E (IgE) levels ( 24 – 26 ). Alcohol consumption is also associated with the development of allergic diseases, such as allergic rhinitis and atopic dermatitis ( 27 , 28 ). A prospective study found a U-shaped association between alcohol consumption and the risk of asthma, with moderate alcohol consumption having the lowest asthma risk ( 10 ). However, Mendelian randomization analysis did not find a causal relationship between alcohol intake and asthma ( 29 , 30 ). Unlike observational studies, MR studies using genetic variations (primarily SNPs) as instrumental variables are immune to confounding factors and reverse causality. This study found no causality between Alcoholic drinks per week and asthma, however, there was a causal relationship between the frequency of alcohol intake and asthma. We believe that the possible reasons for the differences between MR studies and observational studies in the relationship between alcohol intake and asthma are as follows: First, although possible confounding factors have been adjusted, observational studies may still be affected by other confounding factors. Second, there is indeed a U-shaped association between alcohol intake and asthma, which was not detected by the MR study. Therefore, more observational studies and more ingenious MR studies are needed in the future to further reveal the relationship between alcohol intake and asthma. Our study indicated that there may indeed be a causal relationship between alcohol intake and asthma, and this causal relationship is more about the frequency of alcohol intake than the amount of alcohol intake.

The airway is particularly vulnerable to oxidative damage. In experiments, oxidants can induce many symptoms of asthma by inducing the release of pro-inflammatory mediators including cytokines and chemokines ( 31 ). Vegetables and fruits contain many antioxidants. Studies in children showed that asthma symptoms were inversely correlated with fish, vegetable, and fruit intake ( 14 , 32 ). Several studies in adults have linked high fruit and vegetable intake to a lower risk of asthma ( 33 – 36 ). However, not all studies have shown an association between vegetable intake and asthma. However, not all studies have shown an association between vegetable intake and asthma. A study found no association between vegetable intake and asthma ( 37 ). This study used the MR analysis method to find a causal relationship between fruit intake and asthma, but not vegetable intake. There have been many studies on the relationship between fish intake and asthma ( 38 – 41 ). Most of these studies supported an association between fish intake and a reduced risk of asthma ( 38 – 41 ). A Japanese study found that the risk of childhood asthma increased with the frequency of fish intake ( 42 ). However, our study showed no causal relationship between fish intake (including Oily fish intake and Non-oily fish intake) and asthma. This study provides powerful new evidence for insights into the relationship between fish intake and asthma. A study from Singapore suggested that a diet rich in meats may increase the risk of cough with phlegm ( 15 ). A study from Australia found a positive association between meat/cheese intake, poultry/seafood intake and asthma or hayfever ( 43 ). However, this study found no causal relationship between either meat intake or poultry intake and asthma. A study from South Korea found coffee intake had a protective effect on asthma ( 44 ). A prospective cohort study from the UK Biobank has found that coffee and tea intake may be protective against asthma ( 45 ). This study found coffee and tea intake were not associated with asthma. We must correctly understand the relationship between MR and randomized controlled trials (RCTs). On the one hand, MR can effectively overcome the bias caused by confounding ( 16 ). on the other hand, As a powerful supplement to randomized controlled trials, MR is not a substitute for RCTs. Therefore, this conclusion must be viewed with caution.

The mechanisms by which dietary factors affect asthma are not fully understood. Antioxidants and lipids may play an important role ( 46 ). Another possible pathway is through the gut microbiome. The intake of different foods can affect the composition of bacteria in the gut, which will affect the metabolism of nutrients ( 47 , 48 ). A link between changes in the gut microbiome and improvements in airway hyperresponsiveness was found in a mouse model ( 49 ).

Although this MR analysis suggested associations between Fresh fruit intake, Dried fruit intake, and alcohol intake and asthma, the MR analysis should be interpreted with more caution. First, the causality found by the MR analysis reflected the effects of long-term exposure to associated factors. Therefore, short-term exposures may not be of clinical significance. Second, another notable problem is that MR cannot distinguish causal relationships between different periods. For example, an MR study found a causality between vitamin D and multiple sclerosis ( 50 ). However, this effect was only present in childhood or earlier ( 51 ). Third, Univariate MR analyses revealed only overall effects between exposures and outcomes, not direct effects between them. There can be extremely complex mechanisms between exposures and outcomes.

This study has some strengths and limitations. MR uses genetic variation as IVs to infer the causality, which can effectively overcome the bias caused by reverse causality and confounding ( 16 ). In order to ensure the accuracy of MR analysis, we performed sensitivity and pleiotropic analysis. We used European populations from different countries in exposures and outcome to avoid unnecessary bias. Of course, the limitations of this study cannot be ignored. First, the F-statistics indicated that the IVs used in this study satisfied the requirement of strong associations with exposure (F-statistics>10). however, a considerable part of the F-statistics is lower than 100, so this may affect the accuracy of the consequences. Second, we cannot further subdivide different types of dietary intake, nor can we distinguish the effects of different dietary combinations. Third, we were unable to conduct a sex-stratified analysis due to the lack of summary-level GWAS data for different sexes.

5. Conclusion

This study found that dried fruit intake and fresh fruit intake were associated with a reduced risk of asthma, and alcohol intake frequency was associated with an increased risk of asthma. This study also found that alcoholic drinks per week, processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, cereal intake, salad/raw vegetable intake, and coffee intake were not associated with asthma.

Data availability statement

Publicly available datasets were analyzed in this study. This data can be found here: All GWAS data used in this study are available in the IEU open GWAS project ( https://gwas.mrcieu.ac.uk/ ).

Ethics statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent was not provided because All GWAS data used in this study are available in the IEU open GWAS project ( https://gwas.mrcieu.ac.uk/ ). This study was exempt from the approval of the Ethical Review Authority because the data used in this study was public, anonymized, and de-identified.

Author contributions

The study was designed by WY and BH. Statistical analyses were performed by WY, LH, MZ, SS, FW and YY. The manuscript was written by WY and YY. All authors contributed to the interpretation of data and commented on the manuscript. All authors read and approved the manuscript. All authors contributed to the article and approved the submitted version.

Supported by Natural Science Foundation of Gansu Province (21JR1RA118) and Gansu Provincial Youth Science and Technology Fund (21JR1RA107, 18JR3RA305).

Acknowledgments

Special thanks to the IEU open GWAS project developed by The MRC Integrative Epidemiology Unit (IEU) at the University of Bristol. Thank them for extracting relevant GWAS summary-level data from published articles, UK Biobank, and FinnGen biobank.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2023.1126457/full#supplementary-material

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Keywords: Mendelian randomization, dietary intake, asthma, alcohol intake, fruit intake

Citation: Yang W, Yang Y, He L, Zhang M, Sun S, Wang F and Han B (2023) Dietary factors and risk for asthma: A Mendelian randomization analysis. Front. Immunol. 14:1126457. doi: 10.3389/fimmu.2023.1126457

Received: 17 December 2022; Accepted: 09 February 2023; Published: 22 February 2023.

Reviewed by:

Copyright © 2023 Yang, Yang, He, Zhang, Sun, Wang and Han. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Biao Han, [email protected]

†These authors share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Diagnosis and Management of Asthma in Adults: A Review

Affiliations.

  • 1 Division of Allergy and Clinical Immunology, University of Texas Medical Branch, Galveston.
  • 2 Department of Preventive Medicine and Community Health, University of Texas Medical Branch, Galveston.
  • 3 Division of Pulmonary Critical Care and Sleep, Department of Internal Medicine, University of Texas Medical Branch, Galveston.
  • PMID: 28719697
  • DOI: 10.1001/jama.2017.8372

Importance: Asthma affects about 7.5% of the adult population. Evidence-based diagnosis, monitoring, and treatment can improve functioning and quality of life in adult patients with asthma.

Observations: Asthma is a heterogeneous clinical syndrome primarily affecting the lower respiratory tract, characterized by episodic or persistent symptoms of wheezing, dyspnea, and cough. The diagnosis of asthma requires these symptoms and demonstration of reversible airway obstruction using spirometry. Identifying clinically important allergen sensitivities is useful. Inhaled short-acting β2-agonists provide rapid relief of acute symptoms, but maintenance with daily inhaled corticosteroids is the standard of care for persistent asthma. Combination therapy, including inhaled corticosteroids and long-acting β2-agonists, is effective in patients for whom inhaled corticosteroids alone are insufficient. The use of inhaled long-acting β2-agonists alone is not appropriate. Other controller approaches include long-acting muscarinic antagonists (eg, tiotropium), and biological agents directed against proteins involved in the pathogenesis of asthma (eg, omalizumab, mepolizumab, reslizumab).

Conclusions and relevance: Asthma is characterized by variable airway obstruction, airway hyperresponsiveness, and airway inflammation. Management of persistent asthma requires avoidance of aggravating environmental factors, use of short-acting β2-agonists for rapid relief of symptoms, and daily use of inhaled corticosteroids. Other controller medications, such as long-acting bronchodilators and biologics, may be required in moderate and severe asthma. Patients with severe asthma generally benefit from consultation with an asthma specialist for consideration of additional treatment, including injectable biologic agents.

Publication types

  • Administration, Inhalation
  • Adrenal Cortex Hormones / adverse effects
  • Adrenal Cortex Hormones / therapeutic use
  • Adrenergic beta-Agonists / adverse effects
  • Adrenergic beta-Agonists / therapeutic use
  • Airway Obstruction / physiopathology
  • Anti-Asthmatic Agents / adverse effects
  • Anti-Asthmatic Agents / therapeutic use*
  • Asthma / diagnosis*
  • Asthma / drug therapy*
  • Asthma / physiopathology
  • Biological Products / therapeutic use
  • Bronchial Hyperreactivity / physiopathology
  • Drug Therapy, Combination
  • Inflammation
  • Muscarinic Antagonists / therapeutic use
  • Adrenal Cortex Hormones
  • Adrenergic beta-Agonists
  • Anti-Asthmatic Agents
  • Biological Products
  • Muscarinic Antagonists

Grants and funding

  • UL1 TR000071/TR/NCATS NIH HHS/United States

Clinical Trials

Asthma studies.

Photo of hand holding an inhaler

NIAID supports targeted research to understand the underlying immune responses that lead to asthma. NIAID research focuses on understanding how environmental exposures interact with a person’s genetic makeup to cause immune responses that contribute to the development of asthma or increase its severity.

Current Clinical Research Studies Seeking Volunteers

The following are some of the selected clinical trials supported by NIAID and investigating various aspects of asthma. The links lead to full study descriptions, eligibility criteria, and contact information.

Sorting and Expression Profiling of Airway Cells From Humans (The SEARCH Study) (NCT02791542)

Healthy and asthmatic participants ages 18 to 70 years may be eligible to participate in this study that seeks to identify enhancers that are important in regulating key airway epithelial cell genes, to determine how enhancer activity changes in asthma, and to develop approaches for targeting the activity of these enhancers.

Preventing Asthma in High Risk Kids (PARK) (NCT02570984)

This clinical trial is designed to test whether a treatment aimed at blocking IgE (ant-IgE or omalizumab) can prevent the progression to childhood asthma in high risk 2 to 4-year-old children. IgE is critical in the development of allergic diseases and asthma.  Other outcomes include the development or persistence of other allergies, including food allergy and atopic dermatitis. Participants will be treated with anti-IgE (omalizumab) for two years, and then observed off treatment for two years.

Lung-Resident Memory Th2 Cells in Asthma (NCT03455959)

People ages 18 to 55 years who have a clinical history of allergic symptoms to an indoor allergen present in their home environment (e.g., cat, dog, dust mite) and confirmed skin reactivity may be eligible to participate in this study that has the potential to change the therapeutic approach to allergic asthma.

See All Open NIAID-Supported Asthma Studies

Several of our studies need healthy volunteers to participate.

Asthma Research at NIAID

Read more about NIAID’s research on asthma .

What's It Like To Participate?

Find out what it's like to volunteer on our Participant’s Guide to Clinical Trials .

Read some  Participant Testimonials  to see more about what its like to participate.

For questions about participating in this clinical study, contact

    Office of Patient Recruitment     Toll Free: 1-800-411-1222     TTY: 1-866-411-1010

  • Research Article
  • Open access
  • Published: 09 January 2023

Development of a real-world database for asthma and COPD: The SingHealth-Duke-NUS-GSK COPD and Asthma Real-World Evidence (SDG-CARE) collaboration

  • Sean Shao Wei Lam   ORCID: orcid.org/0000-0002-0898-5858 1 , 2 , 3 , 4 ,
  • Andrew Hao Sen Fang 5 ,
  • Mariko Siyue Koh 6 , 7 ,
  • Sumitra Shantakumar 7 , 8 ,
  • See-Hwee Yeo 8 ,
  • David Bruce Matchar 7 , 9 , 10 ,
  • Marcus Eng Hock Ong 1 , 2 , 3 , 11 ,
  • Ken Mei Ting Poon 12 ,
  • Liming Huang 12 ,
  • Sudha Harikrishan 2 ,
  • Dominique Milea 8 ,
  • Des Burke 8 ,
  • Dave Webb 8 ,
  • Narayanan Ragavendran 2 , 7 ,
  • Ngiap Chuan Tan 5 , 7 &
  • Chian Min Loo 6 , 7  

BMC Medical Informatics and Decision Making volume  23 , Article number:  4 ( 2023 ) Cite this article

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The SingHealth-Duke-GlaxoSmithKline COPD and Asthma Real-world Evidence (SDG-CARE) collaboration was formed to accelerate the use of Singaporean real-world evidence in research and clinical care. A centerpiece of the collaboration was to develop a near real-time database from clinical and operational data sources to inform healthcare decision making and research studies on asthma and chronic obstructive pulmonary disease (COPD).

Our multidisciplinary team, including clinicians, epidemiologists, data scientists, medical informaticians and IT engineers, adopted the hybrid waterfall-agile project management methodology to develop the SingHealth COPD and Asthma Data Mart (SCDM). The SCDM was developed within the organizational data warehouse. It pulls and maps data from various information systems using extract, transform and load (ETL) pipelines. Robust user testing and data verification was also performed to ensure that the business requirements were met and that the ETL pipelines were valid.

The SCDM includes 199 data elements relevant to asthma and COPD. Data verification was performed and found the SCDM to be reliable. As of December 31, 2019, the SCDM contained 36,407 unique patients with asthma and COPD across the spectrum from primary to tertiary care in our healthcare system. The database updates weekly to add new data of existing patients and to include new patients who fulfil the inclusion criteria.

Conclusions

The SCDM was systematically developed and tested to support the use RWD for clinical and health services research in asthma and COPD. This can serve as a platform to provide research and operational insights to improve the care delivered to our patients.

Peer Review reports

Introduction

Real-world data (RWD) in healthcare refers to data that are routinely collected as part of the care delivery process, rather than through clinical trial settings. RWD can be used to generate real-world evidence (RWE) [ 1 ]. The potential uses of RWE are broad, ranging from clinical guidelines development to enabling precision medicine in clinical practice [ 2 , 3 , 4 ]. With the adoption of electronic health records (EHR) and recent legislations such as the 21st Century Cures Act [ 5 ], there has been an increasing interest in using real-world evidence (RWE) to satisfy the needs of the evolving healthcare industry [ 5 , 6 ]. Various initiatives have been organized around the use of RWE, such as the Duke-Margolis Centre for Health Policy RWE Collaborative, to advance policy development related to regulatory acceptability of RWE [ 7 ]. RWE has successfully been used by the US Food and Drug Administration in its approval of a cancer therapy drug label expansion in April 2019 [ 8 ].

Obtaining RWD from information systems can be done manually or automatically. Manual extraction entails visual inspection of patient records and manual transcription. Such methods are laborious and vulnerable to transcription errors [ 9 ]. Given these issues, researchers have increasingly relied on the automated methods for data collection [ 10 , 11 , 12 ]. This allows for efficient, near real-time research on clinical practice, while minimizing the risk of data entry errors.

There have been a number of well-reported large-scale RWD for various clinical care domains, for example, the Clinical Practice Research Datalink (CPRD) which is a primary care database of anonymized medical records [ 13 ], European Severe Heterogeneous Asthma Registry, Patient-centred (SHARP) Clinical Research Collaboration [ 14 ], UK Severe Asthma Registry (UKSAR) [ 15 ], US Advancing the Patient EXperience (APEX) in Chronic Obstructive Pulmonary Disease (COPD) [ 16 ] registry amongst others.

In Singapore, a public–private sector collaboration—the SingHealth-Duke-GlaxoSmithKline COPD and Asthma Real-World Evidence (SDG-CARE) collaboration—was formed in 2017 to accelerate the use of RWD. With the above in mind, the collaboration aimed to develop a near real-time integrated RWD database—the SingHealth COPD and Asthma Data Mart (SCDM). The RWD is updated every 24 h, thereby providing a near real-time basis for effectively querying updated clinical and operational data. This is the first large-scale registry in Singapore to fully realize the potential of RWD to improve the care of patients with COPD and asthma. The SCDM is intended to be sufficiently robust to support the conduct of most clinical and health services research trials surrounding asthma and COPD, while ensuring minimal intrusion via the electronic medical record (EMR) systems. This study describes the development of the SCDM and provides an overview of its contents.

Setting, systems and stakeholders

SingHealth is the largest of the three public health systems in Singapore, and consists of public hospitals, community hospitals, national specialty centers and a network of eight primary care clinics (polyclinics). Singhealth provides medical care to over 2 million patients in this city-state of 5.8 million population and attracts patients from all over the country [ 17 , 18 ]. For this collaboration, two SingHealth clinical sites, Singapore General Hospital (SGH) and SingHealth Polyclinics (SHP) were involved. SGH is a tertiary multispecialty academic hospital with 1,785 beds and provides specialist care to over 1 million patients a year, and SHP is a primary care network of 8 clinics that caters to about 2 million patient attendances a year [ 17 ].

Over the years, SingHealth has established a comprehensive integrated enterprise information technology (IT) system that supports a broad range of functions ranging from administrative to clinical and operational functions. A core component of the SingHealth IT and data infrastructure is her enterprise data warehouse (EDW)—SingHealth Electronic Health Intelligence System (eHints) [ 19 ]. Data from various clinical, operations and research sources are ingested into eHints automatically through an Informatica-based [ 20 ] Extract-Transform-Load (ETL) layer. Data in eHints can be organized into data marts to orientate to specific domains (e.g. finance) and subject areas. Once the data is consolidated in the EDW, it can then be consumed through the Oracle Business Intelligence Enterprise Edition (OBIEE) analytics platform [ 21 , 22 ] to support advanced, near real-time user reporting, dash-boarding and other important enterprise business intelligence functions (Fig.  1 ).

figure 1

Overview of analytics support infrastructure in SingHealth. Note Electronic Health Intelligence System (eHints) [ 19 ] is the enterprise data warehouse for SingHealth. It integrates data from various IT systems and feeds them into analytics tools for research and clinical care

Prior to the development of the SCDM, mainly the administrative and operational systems were integrated with eHints. For the development of the SCDM, various standalone clinical systems had to be newly integrated. One of the key clinical systems used in SingHealth is Sunrise Clinical Manager™ (SCM) [ 23 ], a commercial electronic medical records (EMR) system by Allscripts (Allscripts Healthcare LLC).

The administration and maintenance of most IT systems for the public healthcare system is under the purview of Integrated Health Information System (IHiS) [ 24 ]. This includes the OBIEE platform. IHiS is a distinct IT organization who engages in a client-vendor relationship with SingHealth. Given the engagement framework, there is a need to predict the manpower capacity that is required, and clear metrics for monitoring project progress (via planned milestones) [ 25 ]. However, the dynamic and uncertain requirements inherent in the design of a registry which leverages on clinical and operational data requires flexibility in requirement changes. There is thus a need for short feedback cycles with close stakeholder engagement. The organizational setup and project requirements dictate the need for a hybrid project management methodology which leverages on well-planned waterfall methodologies coupled with sub-modules which are executed in an agile approach with close stakeholder engagement across each of the sub-modules [ 26 , 27 ]. The submodules ensured that correct data sources are ingested into the data warehouse and properly transformed and standardized prior to each milestone.

The SCDM was designed and developed with the involvement from clinicians, medical informaticians, IT engineers and project managers from SingHealth, IHiS and GlaxoSmithKline (GSK). It was built within the SingHealth eHints platform [ 19 ] and governed in compliance to all existing cybersecurity and privacy laws for the healthcare sector in Singapore [ 28 ]. SCDM is under the ownership of SingHealth, and the custodianship of the SDG-CARE Steering Committee.

In developing the SCDM, the team complied with all applicable laws regarding patient privacy. Ethics board approval was obtained as part of the SDG-CARE collaboration, prior to developing the SCDM (SingHealth Centralized Institutional Review Board Ref No. 2017/2950).

A study protocol was also produced to clearly define the objectives and deliverables of the SDG-CARE collaboration. The SCDM was developed in accordance with this study protocol.

Development of the SCDM ETL algorithm

To ensure a comprehensive and systematic approach, the team adopted a hybrid waterfall-agile methodology in developing the SCDM. Waterfall methodology is a linear project management approach where stakeholder and customer requirements are gathered at the beginning of the project, and a sequential project plan is then created to accommodate those requirements. The agile methodology was used for rapid reviews with frequent stakeholders’ engagement sessions to derive the unified data model within the design and development phase. The following details the broad phases.

Requirement gathering

This was a critical step in the waterfall aspect of the hybrid methodology where requirements were gathered, allowing other phase to be planned. To do this, the task of data profiling was undertaken. Data profiling involved first listing down the source IT systems that captured asthma and COPD relevant data (e.g. EMR, radiology information system, outpatient administration system) and then reviewing the list of variables captured in each of these systems. Face-to-face requirement gathering sessions with the various stakeholders (i.e. clinicians, researchers, medical informaticians and IT engineers) were conducted to frame the high level scope of work followed by deep diving into detailed data requirements. Clinicians and medical informaticians reviewed screen shots of each end user EMR screen to select required front-end data fields. Based on these requirements, IT engineers then identified the matching back-end data sources and assessed the feasibility of extracting the data. At the end of this phase, a detailed user requirements document (URD) was compiled to formalise the business requirements for IT implementation. The URD specified clearly the initial data elements to be captured in the SCDM.

Design and development

The purpose of the design phase was to define the data mart schema and to create an ETL specification document. The overall SCDM ETL mechanism was designed as a two-step process to mirror typical research study protocols. The first ETL step involved identifying a cohort of patients who have asthma and COPD based on a set of pre-defined inclusion criteria, followed by importing their pre-selected data elements. To identify patients for inclusion in the SCDM, the team used a Place-Diagnosis-Time framework to define a multidimensional inclusion criterion. The “Place” component refers to the visit location (i.e. SGH or SHP). The “Diagnosis” component refers to the diagnosis for the visit (e.g. asthma or COPD), and the “Time” component refers to the date of the visit (i.e. whether it falls within a specified time window). In the interest of keeping the SCDM robust, no exclusion criteria were used.

The selected data elements to import were captured in the URD. As there were common data elements captured in SGH and SHP that were labelled and stored differently in the back-end databases, the agile method was also used across several scrum cycles to resolve the data differences with the stakeholders. These were mapped into unified data elements in the SCDM.

The developers translated the ETL document to actual Informatica ETL codes. The OBIEE subject areas were also developed. Test cases and scripts were then created to facilitate system integration testing by the IT engineers. Upon the completion of the SCDM, the SCDM ETL mechanism design was compiled into an ETL document to provide developers with a lineage of each data element. The design of the user interface based on the OBIEE platform was also documented.

User acceptance test (UAT)

In this phase, the business stakeholders (i.e. clinicians, researchers and medical informaticians) reviewed the system to ensure that it met the requirements laid out at the beginning of the project. This was done by releasing a completed product for testing and verification.

A UAT briefing was conducted by the system developers to guide users on how to access the SCDM via OBIEE. A UAT test plan and test cases were also mutually agreed between SingHealth and IHiS to ensure all stakeholders were aligned on the project exit criteria. UAT was conducted in two phases to adhere with organizational policy which directed that production data should not be used for testing purposes in test environment. Phase 1 was a functional test where users focused on testing that front-end interfaces were in accordance with requirements in test environments. Phase 2 focused on data verification where users compared data from SCDM and source systems in the production environments.

For Phase 2 of the UAT, three team members from SingHealth verified the data extracted from SCDM with data in the EMR systems. There were two testing sub-components, which mirrored the two steps in the ETL mechanism. In the first step, the testers would check that the cohort extracted from SCDM matched the cohort extracted from the EMR database using identical extraction criteria. In the next step, all data elements of a 100 patients sample from the SCDM were extracted. These were then manually checked against their data in the HER system. Finally, aggregated data from SCDM was computed and compared with published data from the same population.

Once the UAT was complete, the testers signed off on a UAT document and a deployment checklist was prepared for system go-live.

Implementation and post-implementation support

Upon user acceptance, the SCDM was deployed in a production environment with the necessary rectification identified during UAT. Subsequently, IHiS provided technical support to users. A data dictionary was produced to facilitate understanding of the various data elements in the SCDM. A user manual was also produced to explain to users the SCDM’s applicability and to provide step-by-step instructions for data extraction.

The SCDM is a unified data repository within eHints which integrates data from various source systems. Data in SCDM is updated in batches on a weekly basis, where data of existing patients is updated and new patients are added. It is accessible via OBIEE which has a friendly user interface to supporting drag-and-drop to enable reporting and analysis for business intelligence (Fig.  2 ).

figure 2

Screen capture of SingHealth COPD and Asthma Data Mart (SCDM) user interface in eHints. Note The Oracle Business Intelligence Enterprise Edition (OBIEE) analytics platform is the front-end of Electronic Health Intelligence System (eHints), allows users to drag-and-drop columns for data extraction, instead of having to write SQL codes. It is meant to support self-service data extraction

SCDM’s cohort definition is based on patients having at least one of the pre-defined diagnosis codes recorded in the SCM clinical document when they visit the SGH Department of Respiratory and Critical Care Medicine (RCCM) or SHP on or after January 1, 2015 up to current date.

The pre-defined diagnosis codes (with SNOMED-CT Description ID) are listed below:

Allergic bronchopulmonary aspergillosis (63349014)

Aspirin exacerbated respiratory disease (3038385014)

Asthma (301485011)

Asthma-COPD overlap syndrome (ACOS) (3046475015)

Bronchiectasis (21163015)

Chronic bronchitis (105519017)

Chronic obstructive pulmonary disease (475431013)

Churg-Strauss syndrome (136476013)

COPD—Chronic obstructive pulmonary disease (475427019)

Severe asthma (1208972017)

There are a total of 199 data elements organized into 28 folders within a single subject area. Table 1 lists the 28 folders, while the list of 199 data elements can be found in the Additional file 1 : Table 1. In some cases where the same elements were available from both SGH and SHP, these elements were mapped and reconciled.

Data verification

For Phase 2 UAT, a retrospective data extraction was performed from both the EMR and SCDM using the following extraction criteria: (1) At least one visit to SGH RCCM specialist clinics and/or SHP, and (2) for asthma or COPD, and (3) between January 1, 2019 and December 31, 2019.

19,434 patients were found in both the EMR and SCDM datasets in that period of time. 4 patients were in the EMR dataset, but absent in the SCDM dataset, while there were no patients in the SCDM dataset that were absent in the EMR dataset. The discrepancies were shared with the IT team. Thorough investigation was conducted and it was found that the discrepancies were due to residual dummy cases used for system testing. In other words, the precision and recall of the ETL mechanism in identifying patients were both 100%.

For data element verification of the 100 sample patients, data extracted from the SCDM for each patient was prepared into a structured form and then manually compared with data displayed on the EMR system. Agreement rate of the SCDM data import mechanism was computed using EMR data as the reference. The agreement rate of the data elements checked for the 100 randomly sampled patients was 100% for all 27 categories except for Problem List and Prescribed Medications (Table 2 ). These errors were deemed non-critical. They included the importing of a cancelled medication, not including the free-text remarks available for some medications and not including comorbidities data entered before year 2015.

Finally, the team cross-checked aggregated data from SCDM with published data by Zheng et al. [ 29 ] and Tay et al. [ 30 ] on the same polyclinic and tertiary care populations. Comparing the numbers, as shown in Tables 3 and 4 , found them to be largely similar.

Data contents and ETL design

The ETL extracted data from the Sunrise Clinical Manager™ system [ 23 ] across the following data sources (actual data source names have been amended for clarity):

Respiratory Medicine Consult Notes

Respiratory Medicine Follow-up Consult Notes

Respiratory Medicine Assessment Notes

Respiratory Medicine Asthma Consult Notes

Respiratory Medicine COPD Consult Notes

Family Medicine Clinical Notes

The extracted data is then loaded into pre-staging, staging and fact tables through the ETL process shown in Fig.  3 . Once the patients are recruited into the cohort based on the inclusion and exclusion criteria, retrospective data will be streamed into the ETL pipeline. For new patients who are recruited into the cohort, retrospective data will be brought into the SCDM every 24 h. For existing patients, their data will be incrementally loaded every 24 h.

figure 3

ETL Process for data sources from both SGH and SHP (target data tables are listed in the intermediate ETL steps)

A high-level cohort analysis was done to provide a summary of the data within SCDM for patients recruited into the cohort. In total, there were 36,407 patients in the SCDM as of December 31, 2019. Figure  4 illustrates how the various cohorts were composed for the analysis, while Table 5 provides a summary of the data extracted for these patients.

figure 4

Cohorts used in the preliminary analysis—Combined, SGH and SHP. Note There are some patients who would fall under both circles when the cohorts are combined, hence the lower number in the combined cohort than compared to adding the individual SGH and SHP cohorts

We described the development of a near real-time integrated RWD database that includes demographic, clinical, laboratory and radiology data of 36,407 patients (as of December 31, 2019) with asthma and COPD across the spectrum from primary to tertiary care in our healthcare system. Data verification was performed and RWD database demonstrated near perfect agreement with the clinical EMR system. Having developed this data mart within an analytics platform simplifies the access to data via a drag-and-drop interface, rather than having to write SQL codes.

While several asthma and COPD databases already exist, the strength of the SCDM is that it links RWD from primary care to tertiary care and has a rich data capture for asthma and COPD that is near real-time. Data in the RWD are refreshed with a maximum of 24 h delay as the data refresh takes place overnight when the system utilization level is low. With an intentionally broad inclusion criteria and wide range of data elements, from demographics, clinical data, laboratory results to vaccinations and unscheduled visits, we are confident that it is sufficiently robust to meet most asthma and COPD research data needs. Table 6 shows a comparison of the SCDM (asthma only) with two other asthma databases, the International Severe Asthma Registry (ISAR) and Danish National Database for Asthma (DNDA) [ 4 , 31 , 32 ].

As our health system is based on geographical regions, it allows us to serve a captive population of patients who tend to seek care within the same health system. This provides researchers with the opportunity to use relatively more complete longitudinal data to study the disease and care trajectories of asthma and COPD patients as they move across the care chain, from primary care to specialist and acute care. A previous study on this health system showed that among the patients with stable chronic diseases, there were on average approximately 1.6 times more primary care visits as compared to specialist outpatient clinics visits [ 33 ]. The registry can further serve as a basis for determining computable phenotypes [ 34 ] such as frequent exacerbators, high risk (of poor outcome) patients, fixed obstruction and type 2 high inflammatory phenotype in an Asian population.

With the heavy investments in developing the ETL pipelines, we also designed the SCDM with flexibility and sustainability in mind. For this, we deliberately chose to perform minimal transformation to preserve the raw data and minimize information loss. Unlike specific disease or national registries that combine and transform raw data to derive composite variables, our database consists of almost completely raw data in their original format. The registry adopted the same classification as the raw data, and followed the International Classification of Diseases, ICD-9 and ICD-10 [ 35 ], and the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) [ 36 ] coding standards. At the time of the study, Singapore adopted the Australian-refined Diagnosis Related Groups (AR-DRG) version 6 coding system [ 37 ]. Although not using a common data model (CDM), such as Sentinel, Observational Medical Outcomes Partnership (OMOP) and Patient Centred Outcomes Research Network (PCORNet), may make our data less linkable with data from other databases, we felt that the trade-off was in favour of generalizability of the data to meet a wide variety of definitions [ 38 , 39 , 40 , 41 ]. Amongst the various classification systems used, mappings exist between them to ensure the interpretability of results across multiple systems and globally across time. Furthermore, as the healthcare CDM space is still actively developing, we will have the option of migrating our database to a CDM [ 42 ].

Minimal filtering of the data was done as we attempted to capture the complete dataset that is available throughout the clinical processes. For example, we chose to import all medications prescribed for a patient, including non-asthma related medications, instead of filtering them based on a pre-selected list of asthma-related medications. This endowed the SCDM with the following advantages: (1) the flexibility to select medications of interest to their own study; (2) the capability to study effects and associations with non-asthma medications, and (3) the adaptability to include any new asthma and non-asthma related medications that may be prescribed in future without the need to update the underlying ETL pipelines.

Although agile methodologies are gaining in popularity in IT development space, we elected a hybrid methodology where the waterfall project plan is required to secure the resources for milestone delivery and to ensure governance requirements are duly complied. Some of the requirements to determine the cohort and data elements were well-defined and amenable to a waterfall methodology whilst within the design and development process, we have adopted the agile methodology for the refinement and implementation of the requirements [ 43 , 44 ]. The uncertain requirements inherent in the design of a registry which leverages on clinical and operational data requires flexibility in efficient requirement changes [ 25 ]. The hybrid framework also allowed us to perform robust data verification that adheres to national and organizational data security policies at the final phases of the SCDM development process. Limited by organizational and data governance constraints, whilst requiring the need for flexibility through close stakeholders’ engagement to refine the data requirements, we have adopted a hybrid waterfall-agile approach towards the development of the SCDM [ 27 ].

Our RWD database is not without its limitations. Although it currently includes patients with asthma and COPD follow-up at SGH RCCM specialist clinics in the tertiary hospital, it does not include those who are only followed-up with other departments such as Internal Medicine, Occupational Medicine, or those who only visited the Accident and Emergency Department (A&E) within the same hospital, and were not referred to the SGH RCCM. Also, although the data mart contains rich clinical details, a significant proportion of this is in free-text format which requires additional data mining tasks before the data can be analysed. One example is the smoking status data where almost half was not available from structured data input fields. With the continual effort to encourage the adoption of standardized clinical templates for asthma and COPD, we hope to improve the quality of data capture. Furthermore, the standardization of semi-structured text formats will further enable us to make use of natural language processing (NLP) algorithms to derive relevant information from the textual data. It is envisioned that we could augment the registry with NLP capabilities to improve data completeness.

Moving ahead, as the next phase in the SDG-CARE collaboration, we will leverage the SCDM in several areas. One immediate area is to develop interactive dashboards that will be able to provide a real-time overview of the key statistics in SCDM, monitor routine practice and for clinical decision support. In terms of clinical research, the team has embarked on a project using SCDM data to develop a model that uses routinely available data in primary care to predict asthma exacerbations. This will support identification of at-risk patients such that earlier and more resource-intensive interventions may be applied for this group. By working with SCDM data which is already routinely captured in the EMR, the team will be able to more easily deploy the model for use. The team also intends for the SCDM to influence public health policies, and is using the real-world data to investigate the impact of guideline non-conformance, such as yearly influenza vaccinations, on clinical outcomes, such as visits to emergency or hospitalizations for pneumonia. Findings from this may potentially result in guideline changes or lend support to tighter compliance. Further down, we also envision that the SCDM will provide the foundation for RWD collection for impactful, large-scale pragmatic clinical trials, akin to the applications from the Salford Lung Study [ 45 ].

In parallel, we will also work towards iteratively enhancing the SCDM. In the next phase, we will look toward including data from the only public paediatric and maternity tertiary hospital in Singapore—KK Women’s and Children Hospital (KKWCH). This will open up the potential to observe long-term trajectory of asthma from paediatric to adulthood and to perform more in-depth studies on determinants of poor outcomes.

We described the development of a RWD database for asthma and COPD in the largest public health care system in Singapore, spanning primary care to specialist and acute hospital care. By adopting a systematic process, we were able to ensure that it was robust, valid and applicable. This RWD database provides a unique opportunity for clinical and health services research in asthma and COPD, which can ultimately improve the care delivered to our patients.

Availability of data and materials

Data from the SingHealth COPD and Asthma Data Mart (SCDM) may be made available on reasonable request. The process for external parties to obtain the data are outlined in Additional file 1 : Annex A.

Abbreviations

Accident & Emergency Department

Asthma-COPD overlap syndrome

Asthma control test

Body mass index

Blood pressure

Common data model

COPD assessment test

Sunrise Clinical Manager clinical document

  • Chronic obstructive pulmonary disease

Clinical Practice Research Datalink

Computerized tomography

Chest X-ray

Danish National Database for Asthma

Electronic Health Intelligence System

Electronic medical records

Extract, transform and load

Forced expiratory volume in the first second

Forced vital capacity

Global Initiative for Asthma

Global Initiative for Chronic Obstructive Pulmonary Disease

GlaxoSmithKline

Hospital Episode Statistics

10Th revision of the International Classification of Diseases

Intensive care unit

Integrated Health Information System

International Severe Asthma Registry

Information technology

KK Women’s and Children Hospital

Modified Medical Research Council score

Natural language processing

Oracle Business Intelligence Enterprise Edition

Observational Medical Outcomes Partnership

Patient Centred Outcomes Research Network

Pneumococcal conjugate vaccine

Peak expiratory flow rate

Pneumococcal polysaccharide vaccine

Department of Respiratory and Critical Care Medicine

Real-world data

Real-world evidence

SingHealth COPD and Asthma Data Mart

Sunrise Clinical Manager

SingHealth-Duke-GSK COPD and Asthma Real-World Evidence

Singapore General Hospital

SingHealth Polyclinics

SNOMED Clinical Terms

User acceptance testing

User requirements document

Written asthma action plan

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Acknowledgements

The authors would like to thank Ms Usha Sankari from SingHealth Polyclinics Research Department, Mr Winston Garcia Bollas from IHiS, Ms Nancy Lew from SingHealth Medical Informatics Office, Mr Gunnar Ong formerly from SingHealth Health Services Research Centre and Mr Thomas Tan from Duke-NUS and for their efforts in this project. In addition, we would also like to acknowledge Ms Karen Tan and her team of nurses from SGH RCCM and Ms Philine Chan from the SGH RCCM Lung Function Lab.

The SGD-CARE collaboration, including the development of the SCDM, is funded by GlaxoSmithKline.

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SS had the original idea for the SDG-CARE collaboration. MSK, SS, DBM, DB, DW, EHMO, NCT, CML and DM provided the core clinical domain knowledge and statistical expertise. SWSL, HSAF, MTKP, HL, SH and NR extracted, wrangled, analyzed and implemented the SCDM. All authors contributed to the development of the SCDM. HSAF and SWSL wrote the first draft of this paper and all the authors subsequently assisted in revising the work and have approved the final version.

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This study was funded by GlaxoSmithKline plc (study number PRJ3057). SS, SHY, DM, DB and DW are full-time employees of GSK. SS, DM, DB and DW also own stocks in GlaxoSmithKline plc. SWSL, HSAF, MSK, DBM, EHMO, MTKP, HL, SH, NR, NCT and CML are full-time employees of SingHealth Duke NUS Academic Medical Centre (including SingHealth Polyclinics, Singapore General Hospital, Singapore Health Services Research Centre and Integrated Health Information Systems) and Duke-NUS Medical School. They report no conflicts of interest.

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[1] List of data elements, and; [2] Procedure for external parties to obtain data from the SingHealth COPD and Asthma Data Mart (SCDM).

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Lam, S.S.W., Fang, A.H.S., Koh, M.S. et al. Development of a real-world database for asthma and COPD: The SingHealth-Duke-NUS-GSK COPD and Asthma Real-World Evidence (SDG-CARE) collaboration. BMC Med Inform Decis Mak 23 , 4 (2023). https://doi.org/10.1186/s12911-022-02071-6

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A new perspective published in the Annals of Allergy, Asthma, and Immunology sheds light on strategies to prevent asthma exacerbations in inner-city patients. Previous research has demonstrated that living in an inner-city is an independent risk factor for Emergency Department visits and hospitalizations from asthma.

The team of physicians and researchers at Yale and Johns Hopkins commented on existing interventions for asthma management, considering whether these previous approaches were suitable in the inner-city setting. They explored a range of approaches, including environmental interventions such as allergen mitigation and pharmacologic approaches such as drug-based inhalers.

The authors assert that the most successful strategies were multilevel and should be tailored to the specific needs of the community. They concluded that policy changes should address the multiple factors that can worsen asthma to meaningfully impact health disparities.

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Environmental triggers and avoidance in the management of asthma

Clarisse gautier.

1 Department of Pulmonology and Allergy, North Hospital

Denis Charpin

2 Faculty of Medicine, Aix-Marseille University, Marseille, France

Identifying asthma triggers forms the basis of environmental secondary prevention. These triggers may be allergenic or nonallergenic. Allergenic triggers include indoor allergens, such as house dust mites (HDMs), molds, pets, cockroaches, and rodents, and outdoor allergens, such as pollens and molds. Clinical observations provide support for the role of HDM exposure as a trigger, although avoidance studies provide conflicting results. Molds and their metabolic products are now considered to be triggers of asthma attacks. Pets, dogs, and especially cats can undoubtedly trigger asthmatic symptoms in sensitized subjects. Avoidance is difficult and rarely adhered to by families. Cockroach allergens contribute to asthma morbidity, and avoidance strategies can lead to clinical benefit. Mouse allergens are mostly found in inner-city dwellings, but their implication in asthma morbidity is debated. In the outdoors, pollens can induce seasonal asthma in sensitized individuals. Avoidance relies on preventing pollens from getting into the house and on minimizing seasonal outdoor exposure. Outdoor molds may lead to severe asthma exacerbations. Nonallergenic triggers include viral infections, active and passive smoking, meteorological changes, occupational exposures, and other triggers that are less commonly involved. Viral infection is the main asthma trigger in children. Active smoking is associated with higher asthma morbidity, and smoking cessation interventions should be personalized. Passive smoking is also a risk factor for asthma exacerbation. The implementation of public smoking bans has led to a reduction in the hospitalization of asthmatic children. Air pollution levels have been linked with asthmatic symptoms, a decrease in lung function, and increased emergency room visits and hospitalizations. Since avoidance is not easy to achieve, clean air policies remain the most effective strategy. Indoor air is also affected by air pollutants, such as cigarette smoke and volatile organic compounds generated by building and cleaning materials. Occupational exposures include work-exacerbated asthma and work-related asthma.

Introduction

Over the past several years, a wide range of epidemiological, clinical, and experimental studies have led to major advances in the field of respiratory allergies. A wide array of risk factors play a multifaceted role, guiding the secondary prevention approach. In this review, we will not elaborate on potential protective factors associated with the “hygiene hypothesis”, rather we will focus on allergenic and nonallergenic triggers ( Table 1 ). 1 For each of these, after a short definition, we will review studies that suggest or prove their involvement, and when appropriate, we will then evaluate the outcomes of avoidance procedures.

Self-reported asthma triggers as ranked by the proportion of participants who have experienced the trigger and by how frequently the trigger was reported

Note: Adapted from Price D, Dale P, Elder E, Chapman KR. Types, frequency and impact of asthma triggers on patients’ lives: a quantitative study in five European countries. J Asthma . 2014;51(2):127–135. © 2014 The Author(s). Published by Taylor & Francis. 1

Allergenic triggers

Indoor allergens, house dust mite (hdm) allergens.

HDMs are ubiquitous pyroglyphidae that live in human dwellings. The mite’s gut contains potent digestive enzymes, notably proteases that persist in the feces, and these are thought to induce allergic sensitization and asthma. Their proliferation is favored by high indoor humidity and elevated temperatures. Mite allergens are classified into 33 groups, listed in the systematic World Health Organization (WHO) and the International Union of Immunologic Societies (IUIS).

Arguments in support of their involvement as triggers of asthma attacks include an association between HDM allergen exposure and asthma outcomes (and in some studies, a dose–response relationship), such as asthmatic symptoms and the requirement for medication in allergic asthmatic patients. 2 , 3 The relationship with visits to the emergency department has provided conflicting results, as the association reported in earlier studies 4 was not found in a more recent one. 5

There have been numerous studies on avoidance procedures in regard to HDM and HDM allergens since their discovery in the late 1960s. These studies have led to meta-analyses. Four meta-analyses on HDM avoidance for asthma by Gotzsche and Johansen, which were published in 1998, 2001, 2004, and 2008, concluded that avoidance was of no benefit to asthmatic patients. 6 Custovic and Wijk 7 concluded that there is currently inadequate evidence to advocate allergen avoidance in adults, whereas these interventions may be of some benefit in children ( Table 2 ). Platts-Mills has criticized these meta-analyses on the basis that this analytical approach is inadequate because allergen avoidance protocols are multifaceted and personalized and are hence difficult to standardize. 8 Apart from these statistical shortcomings in the meta-analyses, there are also a number of biological issues that need to be considered. First, which biological parameter is the most representative of patient exposure? Tovey et al 9 suggest that in-bed exposure accounts for only 9% of the total exposure. Second, dust collected from the homes of patients includes many other air contaminants besides HDMs and HDM allergens, such as bacteria and endotoxins, molds, glucans originating from mold membranes, mycotoxins, and microbial volatile organic compounds ( Table 3 ). 10 Thus, avoidance procedures directly aimed at HDMs may only provide partial measures. Furthermore, being sensitized to HDMs does not per se mean that HDM allergens play a role in the clinical expression of the disease. Finally, in the context of unhealthy buildings, of which there are many, the building itself generally has one or more defects that are responsible for high indoor humidity that leads to HDMs, mold proliferation, and release of their metabolites. 10 Programs that have proven to be effective use a multifaceted approach including community health workers, 11 environmental counseling, therapeutic education, and home remediation. 12 , 13

Practical measures for reducing dust mite and pet allergen levels: effect on allergen levels and the clinical effect on symptoms of rhinitis and asthma

Notes: Evidence level graded according to the Scottish Intercollegiate Guidelines Network recommendations: Ia, evidence obtained from meta-analysis of randomized controlled trials; Ib, evidence obtained from at least one randomized controlled trials; IIb, evidence obtained from at least one other type of well-designed quasiexperimental study; III, evidence obtained from well-designed nonexperimental descriptive studies, such as comparative studies, correlation studies, and case studies; IV, evidence obtained from expert committee reports or opinions and/or clinical experience of respected authorities. Reproduced from Custovic A, Wijk PG. The effectiveness of measures to change the indoor environment in the treatment of allergic rhinitis and asthma: ARIA update (in collaboration with GA(2)LEN). Allergy . 2005;60(9):1112–1115. Copyright © Blackwell Munksgaard 2005. 7

Abbreviation: HEPA, High efficiency particulate arrestance.

Fungal components and products relevant for indoor air sciences

Note: Reproduced from Nevalainen A, Täubel M, Hyvärinen A. Indoor fungi: companions and contaminants. Indoor Air . 2015;25(2):125–156. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. 10

Abbreviations: EPS, extracellular polysaccharides; IgE, immunoglobulin E; MVOC, microbial volatile organic compounds.

Microscopic fungi, or molds, represent one of the main groups of microorganisms present in all buildings. Although there are thousands of mold species, only ~80 indoor molds are thought to be responsible for adverse health effects in humans.

There have also been a number of epidemiological surveys in regard to this topic. The results of these have been summarized in meta-analyses 14 – 17 and in reports from national 18 , 19 and international health authorities. 20 The association between dampness or mold and the impact on health is presented in Table 4 . From this, it would appear that these factors are relevant.

Association between excessive humidity/molds and health impact according to the IOM, the WHO, and the ANSES

Note: “+” means the association has been acknowledged, and “0” means that it has not.

Abbreviations: ANSES, French Agency for Food, Environment and Occupational Health & Safety; IOM, Institute of Medicine of the National Academies; WHO, World Health Organization.

There are few published interventional studies regarding dampness and mold in homes. They have been reviewed by Cox-Ganser. 21 In one study, there were significantly fewer emergency department visits and/or hospitalizations among children in the remediation group compared to those in the control group. In another randomized controlled study performed in the UK, asthma symptoms and asthma medication use declined in the intervention group. A third study involved moving participants into an “asthma friendly, Breathe-Easy Home”. Children randomized to move into these houses had more asthma-free days, and fewer of them required health care visits compared to those in the control group.

According to market research statistics published by animal food suppliers, ~50% of families in developed countries have a pet. 22 – 24 This figure is the same for families with allergies.

There are as many dogs as cats, although cats are more allergenic than dogs. 25

Pet allergy can readily be documented based on the clinical history. Skin tests for pet hair and danders (shed skin cells) are not very specific because some allergens from dogs cross-react with the major cat allergen, Fel d 1 . Allergenic particles are small, ranging from 2 to 10 µm in size, which allows them to remain airborne and to stick to surfaces and clothing. 26 , 27

Avoidance of cat allergens is hard to achieve. Patients who do not have a cat at home will nonetheless encounter cat allergens in many locations because these allergens are ubiquitous. 28 , 29 For patients who have a cat at home, the advice is generally to find a different home for the cat. Then, cat allergen levels can be reduced, although even when this advice is followed, while most families fail to adhere to this advice. 30 Other authors see little point in such measures since even low levels of cat allergens will still cause sensitized patients to react. 31 When the cat remains in the home, basic avoidance measures do not decrease cat-allergen levels. 32 , 33 Several pet companies have marketed the so-called “hypoallergenic cats”, although there is no scientific evidence to support this claim. 34

Dog allergens are found in dog hair, shed skin cells, saliva, and urine. There are no differences between breeds in terms of allergy induction. Dogs are less often responsible for allergic reaction than cats. 25 Avoidance counseling does not yield better outcomes than with cat allergies. 35

Cockroaches

Cockroach allergens are mainly found in the kitchens of low-income housing. The combination of cockroach allergen exposure and allergic sensitization contributes to asthma morbidity. 36 The environmental control of cockroaches has recently been summarized by a Joint Task Force of three major professional allergy organizations. 37 Strategies that effectively lower cockroach allergen levels result in a clinical benefit. 38 They include keeping the kitchen clean, promptly washing the dishes, putting all foods in sealed containers, frequent disposal of the garbage, avoiding leaving food to sit out, and setting roach traps.

Like cockroach allergens, mouse allergens originate from mouse urine, shed skin cells, and hair follicles, and they are mostly found in inner-city dwellings. High levels of allergens may be found in schools and homes, but their relationship with asthma morbidity is still controversial. 39 , 40 Integrative pest management has been associated with a reduction in allergen levels in the kitchen and in bedrooms. 40 Outcomes in terms of a reduction in the use of health care provisions in children are also controversial. 41 , 42 Public buildings in France have not been found to contain high levels of mouse allergens. 43

Outdoor allergens

Allergenic pollens are those that are small enough to be transported by the wind. With most patients, allergy to pollen induces rhinoconjunctivitis. Nonspecific bronchial hyperreactivity increases with grass-pollen allergy 44 as well as with Parietaria pollen allergy during pollination. 45

In the Copenhagen Allergy Study, it was estimated that a quarter of the subjects who were allergic to pollen also exhibited allergic asthma from pollen, while approximately one-half of the subjects with allergic rhinitis to animals or HDMs also exhibited asthma from animals or HDMs. 46

Pollen avoidance is only relevant during the time that the offending pollen is airborne, which underscores the importance of a precise allergologic diagnosis. During this time period, patients are advised to – if at all possible – be outdoors only early in the morning or during the late afternoon, because humidity is higher then and the pollen particles tend to stick to anthers. In addition to this, car and home windows should be kept shut. Patients may be advised to turn on their air conditioner, to wear a pollen mask and wraparound glasses, and to take a shower and to wash their hair after being outdoors for an extended period of time. These recommendations follow common sense, although they have not been validated by control experiments.

Outdoor molds

Alternaria and Cladosporium species are considered to be major outdoor allergens responsible for sensitization, development of rhinitis and asthma, and asthma exacerbation, including life-threatening exacerbations. In contrast, xerophilic species of Penicillium and Aspergillus are involved in allergic diseases as indoor allergens. In regard to indoor allergens, the diagnosis of outdoor mold allergies is difficult because allergenic extracts are not well standardized and most fungal extracts exhibit broad cross-reactivity with taxonomically unrelated fungi. 47

Nonallergenic triggers

Viral infections have been implicated in most (>80%) asthma exacerbations in children. 48 Such infections are sometimes referred to as the “September epidemic” due to their seasonal pattern. 49 Rhinoviruses are the most commonly encountered, although other viruses, such as respiratory syncytial virus, enterovirus, coronavirus, and human metapneumovirus, can also be involved. Viruses interact with allergens to induce asthma exacerbation and hospitalization. 50

Aside from keeping away from infected subjects, vaccination against the flu, and pharmacologic treatment during the first few days following contamination, there are no preventive treatments.

Active smoking

According to the Centers for Disease Control and Prevention in the USA, 21% of Americans with asthma are active smokers. 51 , 52 Asthmatics who smoke are likely to experience a higher rate of hospitalization than asthmatics who do not smoke. 53 Another study, performed with pregnant women, demonstrated poor asthma control and increased asthma exacerbations in active smokers and ex-smokers. 54 Furthermore, inhaled corticosteroids, which represent the most effective currently available treatment for treating chronic asthma, have a reduced efficacy in smokers. 55

McLeish et al 56 evaluated smoking cessation in smokers with and without asthma. They concluded that these two groups did not differ in terms of the abstinence rate and smoking relapse, although they did show that smokers with asthma exhibited a slower rate of decline in nicotine withdrawal symptoms and craving over time. Bittner et al 57 concluded that providing smoking cessation interventions during hospitalization for asthma exacerbations was an underutilized opportunity. Perret et al 58 suggested several ways to improve smoking cessation strategies in asthmatic smokers, such as individualized interventions, insisting on “lung age”, providing long-term follow-up, and, in the case of adolescents, involving older peers to deliver asthma education.

Passive smoking

The relationship between passive smoking and childhood asthma exacerbation and hospitalization is well recognized. In the USA, it is estimated that, on an annual basis, >200,000 asthma exacerbations are associated with passive smoking. 59

The implementation of a public smoking ban in Scotland has reduced the rate of asthma exacerbations. 60 A similar effect was observed in Minnesota (USA) as well as at the national level. 61 , 62 This latter survey demonstrated a lower level of second-hand smoke exposure, a decrease in the odds of current asthma symptoms, and a lower risk of visits to the doctor due to severe asthma symptoms. A meta-analysis of 11 eligible studies published between 2008 and 2013 determined that hospital attendance for asthma patients decreased by 10% following the ban. 63

Air pollution

Changes in gaseous and particulate outdoor air pollutants are associated with daily asthmatic symptoms, a decrease in lung function, 64 , 65 emergency room visits, and hospitalizations for asthma attacks. 66 The lag time amounts to 24 hours following the acute episode. In children with moderate persistent asthma, the occurrence of symptoms and the decrease in lung function are more pronounced in those patients who do not follow a maintenance therapy. 67 Avoidance of outdoor air pollution is hard to achieve because there is no realistic way of avoiding exposure. National authorities do not recommend that asthmatic subjects remain indoors during periods of elevated air pollution because indoor air pollution can in fact be more harmful. When air quality index reaches a certain level, asthmatic patients, and eventually all individuals, should reduce the time spent outdoors and, in particular, avoid exertion in the polluted air. 68 Other recommendations, such as wearing a dust mask and taking supplemental antioxidants, are unlikely to be effective. 69 Thus, as stated in this review, sustained clean air policies remain the most effective way to reduce health effects that are related to air pollution.

The impact of volatile organic compounds that are encountered as indoor air pollutants on asthma control is still a matter of debate. 70 The main indoor air pollutant is cigarette smoke. In Pittsburg, an industrial community with high outdoor air pollution, indoor activities, especially cigarette smoke, are responsible for a large part of the indoor exposure. 71 Compared to cigarette smoke, e-cigarette vapor produces very small amounts of all by-products. 72 Indoor chemical air pollution can be lowered by avoiding cooking-related pollutants, avoiding the use of sprays and other cleaning materials that generate volatile organic compounds (VOCs), choosing furniture and building material with low VOC emissions, and regular air exchange by natural or mechanical ventilation. These recommendations have been made available to the general public. 73

Meteorological changes

An increase in daily temperatures correlated with an increase in emergency room department visits for asthma, especially in patients older than 65 years. 74 However, cold temperatures also trigger asthma attacks. In general, the effect of cold weather appears to last for several weeks, whereas the effect of hot weather was more short term. 75

High altitude has traditionally been associated with a reduction in mite allergen exposure, a lower rate of mite sensitization, 76 and an improvement in the condition of asthmatics. 77 However, more recent studies have suggested that other factors could also be involved in this improvement. 78 , 79 Overall, airborne pollen grain and fungal spore concentrations are low, thus providing favorable conditions for those who suffer from pollen allergies. 80

Occupational exposures

Work-exacerbated asthma can occur when current asthma symptoms are made worse due to work; it does not refer to work as the cause of asthma. 81 This phenomenon has been reported to occur in 21.5% of asthmatics who work. Dust is the most commonly implicated agent of work-exacerbated asthma in the health care and education sectors, while for service jobs, smoke is the most common agent. Work-related asthma can be triggered by specific occupational agents. According to the French network of occupational physicians, there was a significant decrease in work-related asthma over the period 2001–2009, especially in the cases of aldehyde, latex, and isocyanates exposure, but, conversely, there was a significant increase for quaternary ammonium compounds. 82

Avoidance is mainly based on occupational hygiene and the use of personal protective equipment. It also relies on an adequate knowledge of the potential triggers of work-related asthma by asthmatic patients. A Canadian web-based educational tool has been developed and successfully tested with a group of asthmatic patients. 83

In a series originating from the Swiss Drug Monitoring Center, bronchospasm was reported in 2% of adverse drug reactions. 84 Analgesics and nonsteroidal anti-inflammatory drugs were involved in 24% of these cases, anti-infectious in 18%, cardiovascular drugs in 11%, drug formulation agents in 9%, vaccines and immunoglobulins in 5.5%, plasma volume expanders in 5.5%, and other drugs in 27%. However, bronchospastic reactions should not be equated with asthmatic bronchospastic reactions because the pathogenic mechanisms underlying these reactions remain unclear.

Stress and emotional disturbances

Stress may enhance airway inflammation by modulating immune cell function through neural and hormonal pathways. Psychological triggers have been consistently associated with exacerbations and emergency treatments. 85 In Puerto Rican children, caregiver depression, perceived stress, and child’s negative life events were associated with high trigger scores. 86 Another survey concluded that anxiety may exacerbate the effects of disrupted sleep on childhood asthma control. 87 A Cochrane Database Systematic Review only found two intervention studies, and it concluded that family therapy may be a useful adjunct to medication for asthmatic children. 88

Food reactions

Although food allergy is often associated with asthma, asthma is not, in and of itself, a strong predictor for fatal anaphylaxis. 89

Avoidance is based on not eating offending foods and, with selected patients and a suitably skilled medical team, specific hyposensitization.

Sulfites, used as preservatives and antioxidants, are found in many foods, such as pickled foods, dried fruits, and drinks such as beer, wine, and soft drinks. They can induce allergy-like symptoms such as wheezing, tightness, and cough in people with underlying asthma and allergic rhinitis. 90

Recommendations from some of the national societies and national authorities

Official recommendations regarding asthma trigger identification and management vary widely between countries. Here, we present various recommendations, sometimes contradictory, originating from national societies or national authorities. For example, the US guidelines for management of asthma exacerbations encourage “trigger identification and avoidance instructions”, without providing more detailed instructions. 91 The British Thoracic Society also recommends identification of triggers and emphasizes the role of passive smoking. 92 The French Pulmonology Society provides a list of the main triggers. 93 The American Academy of Allergy and Clinical Immunology recommends to avoid any trigger but does not mention how to do that. 94

In regard to allergen avoidance, there are large discrepancies in the recommendations from National Societies. The American College of Chest Physicians recommends decreasing exposure to passive smoking, humidity and molds, pests, and noxious gas. 95 The British Thoracic Society does not recommend the use of physical and chemical methods of reducing HDM levels in the home. It concludes that “studies of individual aeroallergen avoidance strategies show that single interventions have limited or no benefit” and suggest to implement “a multifaceted strategy more likely to be effective if it addresses all the indoor asthma triggers”. 93 The British Society on Allergy and Clinical Immunology states that HDM avoidance might be beneficial in highly motivated patients, and clinical benefits are more likely with multiple interventions. 96 The French Pulmonology Society emphasizes avoiding active and passive smoking. 93 It suggests that a home visit for environmental inspection could be useful for severe asthmatic patients who have failed to gain control of their condition despite optimum treatment. The Allergic Rhinitis and its Impact on Asthma (ARIA) group suggests “not to use single chemical or physical preventive methods or their combination” but rather “multifaceted environmental control to reduce exposure in patients with allergy to HDMs”. 97 Finally, the Global Initiative for Asthma (GINA) states that “Although allergens may contribute to asthma symptoms in sensitized patients, allergen avoidance is not recommended as a general strategy for asthma”. These strategies are often complex and expensive, and there are no validated methods for identifying those who are likely to benefit. 98 In summary, no scientific society recommends basic HDM avoidance procedures.

Many triggers, both allergenic and nonallergenic, and their interactions influence the natural history of asthma. The attending physician’s task is to list them for each individual patient and to provide avoidance counseling. Educational programs are best suited to allow patient needs to be discussed and to provide answers to any question. However, in many instances, avoiding triggers is not a guarantee of success, and a multifaceted program should be implemented.

The authors report no conflicts of interest in this work.

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