Dr Rebecca McLoughlin

It is estimated that over 80% of the global population is exposed to unacceptably high levels of air pollution, which can have damaging health effects. In fact, according to the most recent analysis of the global burden of diseases (2015), particulate matter (PM) air pollution exposure alone is the 5th leading risk factor for mortality worldwide, accounting for approximately 4.2 million deaths (7.6% of global deaths). Common diseases associated with both acute and chronic PM exposure include asthma, chronic obstructive pulmonary disease (COPD), respiratory infections, cardiovascular, metabolic, gastrointestinal, skin and central nervous system (CNS) diseases. While the specific mechanisms leading to the development and progression of each of these diseases vary, all have a common underlying pathology of inflammation and oxidative stress. Various nutritional interventions have been assessed for their protective effect against air pollution exposure. Dietary supplementation with vitamin E is hypothesised to be beneficial due to its antioxidant and anti-inflammatory properties. Here we review the literature on the adverse health effects of air pollution on the respiratory, cardiovascular, metabolic, gastrointestinal, skin and central nervous systems and the role of vitamin E in modifying the detrimental consequences of air pollution. While there is evidence from clinical trials regarding the benefits of combined vitamin E and C in ameliorating the effects of air pollution in asthma and reducing the risk of respiratory infections, further work is needed to assess the efficacy of vitamin E supplementation in protecting against the numerous other health consequences of air pollution exposure.

Background: The management of obstructive airway diseases (OADs) is complex. The treatable traits (TTs) approach may be an effective strategy for managing OADs. Objective: To determine the effectiveness of interventions targeting TTs for managing OADs. Methods: Ovid Embase, Medline, CENTRAL, and CINAHL Plus were searched from inception to March 9, 2022. Studies of interventions targeting at least 1 TT from pulmonary, extrapulmonary, and behavioral/lifestyle domains were included. Two reviewers independently extracted relevant data and performed risk-of-bias assessments. Meta-analyses were performed using random-effects models. Subgroup and sensitivity analyses were carried out to explore heterogeneity and to determine the effects of outlying studies. Results: Eleven studies that used the TTs approach for OAD management were identified. Traits targeted within each study ranged from 13 to 36. Seven controlled trials were included in meta-analyses. TT interventions were effective at improving health-related quality of life (mean difference [MD] = -6.96, 95% CI: -9.92 to -4.01), hospitalizations (odds ratio [OR] = 0.52, 95% CI: 0.39 to 0.69), all-cause-1-year mortality (OR = 0.65, 95% CI: 0.45 to 0.95), dyspnea score (MD = -0.29, 95% CI: -0.46 to -0.12), anxiety (MD = -1.61, 95% CI: -2.92 to -0.30), and depression (MD = -2.00, 95% CI: -3.53 to -0.47). Conclusion: Characterizing TTs and targeted interventions can improve outcomes in OADs, which offer a promising model of care for OADs.

Background Whilst multidimensional assessment enables the detection of treatable traits in severe asthma and has the potential to improve patient outcomes, healthcare disparities exist, and little is known about the factors influencing optimal management in severe asthma. This study aimed to explore perceived barriers, and enablers to implementing personalised care in severe asthma, from the healthcare professionals' perspective. Methods A descriptive, qualitative study involving a single focus group (n = 7) and semi-structured interviews (n = 33) with multidisciplinary healthcare professionals involved in severe asthma care was conducted. A hybrid thematic and content analysis was undertaken to identify themes, which were then deductively mapped to the Theoretical Domains Framework (TDF). Results Overall, three emergent themes were identified: (1) Barriers- (2) Enablers- to optimal management; (3) Desired model of care. Across all TDF domains, 6 constructs influenced development and implementation of optimal care: (1) belief about consequences, (2) environmental context and resources, (3) belief about capabilities, (4) social/professional role and identity, (5) goals and (6) knowledge. Conclusion Implementation of personalised care in severe asthma is complex and non-linear. The use of a theory-based approach effectively demonstrated how a variety of behaviours could be targeted to optimise and promote personalised care in different clinical setting.