Davor Plavec, Children’s Hospital Srebrnjak, Croatia
This is an open-access article distributed under the terms of the
Asthma and mental health problems co-occur at high rates. In context of a holistic approach to health, considering the extent to which social determinants relate to mental health in people with asthma helps identify health inequity and inform population-level preventative strategies. The aim of the current exploratory study was to examine how social determinants are associated with depression, anxiety and resilience in people with mild-moderate and severe asthma.
A cross-sectional study of 144 adults (aged ≥18 years) with a diagnosis of asthma was conducted. Participants were classified as having mild-moderate asthma or severe asthma based on international guidelines. As part of a multidimensional assessment, participants self-reported age, sex, ethnicity, country of birth, living arrangements, employment, and postcode. They also completed validated self-report questionnaires for depression and anxiety [Hospital Anxiety and Depression Scale (HADS)], and resilience [Resilience Scale (RS-25)]. Bayesian regression analyses were conducted to examine the extent to which social determinants were associated with depression, anxiety and resilience.
74 participants had mild-moderate asthma and 70 participants had severe asthma. Participants were on average 60 years old (SD = 14), 72% were female, 94% were Caucasian, 94% were Australian-born, 26% lived alone, 42% were working full- or part-time, and 83% lived in a major city of Australia. Anxiety and depression were relatively common (35% anxiety; 16% depression using HADS threshold of scores ≥8). Few social determinants were associated with depression, anxiety and/or resilience. Older age was associated with greater resilience. Females had higher levels of anxiety compared to males. Compared to participants currently working full- or part-time, those who were not working or studying due to their health had worse depressive symptoms and those who were not working for other reasons such as retirement had greater resilience.
As in the general population, age, sex and employment/student status were associated with components of mental health in people with asthma. Although limited by the small sample size and sociodemographic homogeneity, the findings of this exploratory study contribute to the large body of work fostering a holistic approach to health and striving for health equity in people with asthma, particularly those who experience mental health problems.
Mental health is a crucial aspect of quality of life in asthma. Yet, depression and anxiety are 1.5–2.4 times more common in people with asthma than people without asthma (
Multiple reasons likely explain the high prevalence of poor mental health in people with asthma. From a population perspective, one important set of reasons to consider is social determinants of health (
The aim of the current exploratory study was to examine how social determinants are associated with depression, anxiety and resilience in people with mild-moderate and severe asthma. We focused on socio-demographic determinants of age, sex, ethnicity, migrant status, living arrangements, employment status, and the neighborhood socio-economic disadvantage and geographical remoteness of participants’ residence. We hypothesized that younger age, male sex, Caucasian ethnicity, Australian birthplace, living with a partner, being employed, lower neighborhood socio-economic disadvantage and living in a major city of Australia would be associated with lower depression and anxiety symptoms and greater resilience.
This study was a secondary analysis of data collected as part of a cross-sectional, observational study of adults with mild-moderate and severe asthma in Newcastle, Australia (ACTRN12620000283976)—Understanding Breathlessness in Asthma (
The Human Research Ethics Committee of the Hunter New England Local Health District (2019/ETH12515) approved the study protocol. All participants provided written informed consent prior to completing study assessments.
Participants were recruited from the Department of Respiratory and Sleep Medicine's Ambulatory care clinics at the John Hunter Hospital, the research databases of the Department of Respiratory and Sleep Medicine and Hunter Medical Research Institute, and through general and social media advertisement.
Participants were eligible to participate if they were aged ≥18 years, with a physician confirmed diagnosis of asthma and objective evidence of variable airflow limitation within the past 10 years or assessed as part of the study. Variable airflow limitation was defined as: a change in forced expiratory volume in one second (FEV1) of ≥200 ml or ≥12% 15 min following bronchodilator administration and/or airway hyper-responsiveness (fall in FEV1 ≥15%) in response to hypertonic saline challenge and/or peak flow diurnal variation of ≥15% or >50 ml.
Eligible participants were considered to have severe asthma if they met international guideline criteria ( Asthma Control Questionnaire-7 (ACQ-7) score ≥1.5, and/or Frequent severe (≥2 systemic corticosteroids of ≥3 days each) and/or a serious (hospitalization, intensive care unit stay, mechanical ventilation) exacerbation in the previous 12 months, and/or Persistent airflow limitation [pre-bronchodilator FEV1 to forced vital capacity (FVC) ratio of <0.7 and FEV1 <80% predicted].
Criteria for study exclusion were: (1) currently pregnant; (2) high dependence on medical care, including recent intensive care unit admission; (3) significant life-limiting comorbidity; (4) current lung cancer or other blood, lymphatic or solid organ malignancy; (5) a primary diagnosis of lung disease other than asthma; or (6) cognitive impairment, poor English language skills or significant untreated hearing impairment that prevented completion of data collection forms or understanding of verbal instructions. Participants who were otherwise eligible but had experienced an asthma exacerbation (use of oral corticosteroids or an increase from maintenance dose of oral corticosteroids for ≥3 days) in the past four weeks were included but had their assessment visit postponed for four weeks.
Participants completed a comprehensive, multidimensional assessment across two in-person assessment visits, approximately two weeks apart. Participants were also provided with a questionnaire pack to take home and complete between visits. The assessment included measures of sociodemographic characteristics, pulmonary function, asthma control, mental health, breathlessness, comorbidity, exercise capacity, and physical activity. Measures relevant to the current study are described below.
For assessment of airflow limitation and reversibility, spirometry was completed (Medgraphics, CPFS/D USB Spirometer, BreezeSuite v8.5-v8.6, MGC Diagnostics) pre- and 15 min post-administration of 400 μg of salbutamol and 42 μg of ipratropium. Testing was performed according to international ATS/ERS standards, including withholding of bronchodilator medications for recommended time periods (
Participants self-reported the following data that were used to define the social determinants used for analysis: date of birth, sex (male, female, intersex), ethnicity, country of birth, living arrangements (
Depression and anxiety were measured using the two subscales of the Hospital Anxiety and Depression Scale (HADS) (
Analyses were conducted in Stata BE 17.0 (StataCorp LLC). Descriptive statistics were calculated for social determinants and mental health variables. Bayesian linear regressions were conducted to determine the relationship between each social determinant and depression, anxiety, or resilience, controlling for asthma diagnosis (mild-moderate vs. severe), using the default settings [predictor priors: normal (0,10000); MCMC iterations: 12,500; burn-in 2,500]. We tested whether including an interaction between the social determinant and asthma diagnosis improved model fit using log marginal likelihood. In all instances, the model without an interaction had the largest marginal likelihood, so these were reported. Categories with fewer than 5 participants were excluded from regression analyses. Centrality of effect sizes were reported as mean with 95% credible intervals using the highest density interval. The associations were not adjusted for confounding, as the aim was to provide measures of total effect.
There were 74 participants with mild-moderate asthma and 70 with severe asthma. Participants were on average 60 years old (SD = 14), 72% were female, 94% were Caucasian, 94% were Australian-born, 26% lived alone, 42% were working full- or part-time, and 83% lived in a major city of Australia (
Descriptive statistics for
| Total ( |
Mild-moderate asthma ( |
Severe asthma ( |
||
|---|---|---|---|---|
| Social determinants | ||||
| Age (years), mean (SD) | 59.7 (13.5) | 58.2 (13.8) | 61.3 (13.2) | |
| Sex, |
Male | 41 (28.5) | 17 (23.0) | 24 (34.3) |
| Female | 103 (71.5) | 57 (77.0) | 46 (65.7) | |
| Ethnicity, |
Caucasian | 135 (93.8) | 68 (91.9) | 67 (95.7) |
| Not Caucasian | 9 (6.3) | 6 (8.1) | 3 (4.3) | |
| Migrant status, |
Australian-born | 134 (93.7) | 69 (93.2) | 65 (94.2) |
| Overseas-born | 9 (6.3) | 5 (6.8) | 4 (5.8) | |
| Living arrangements, |
Living alone | 38 (26.4) | 19 (25.7) | 19 (27.1) |
| Living in a share house | 2 (1.4) | 1 (1.4) | 1 (1.4) | |
| Living with a spouse/partner | 57 (39.6) | 32 (43.2) | 25 (35.7) | |
| Living with family | 46 (31.9) | 22 (29.7) | 24 (34.3) | |
| Other arrangement | 1 (0.7) | 0 (0.0) | 1 (1.4) | |
| Employment status, |
Studying | 3 (2.1) | 1 (1.4) | 2 (2.9) |
| Seeking work | 1 (0.7) | 0 (0.0) | 1 (1.4) | |
| Working full- or part-time | 60 (41.7) | 39 (52.7) | 21 (30.0) | |
| Domestic duties | 3 (2.1) | 2 (2.7) | 1 (1.4) | |
| Not studying or working due to health | 19 (13.2) | 6 (8.1) | 13 (18.6) | |
| Not working for other reasons/retired | 58 (40.3) | 26 (35.1) | 32 (45.7) | |
| Neighborhood socio-economic disadvantage, mean (SD) | Index of relative economic disadvantage | 994.3 (37.1) | 1,002.5 (30.2) | 985.7 (41.8) |
| Geographical remoteness, |
Major city of Australia | 119 (82.6) | 65 (87.8) | 54 (77.1) |
| Inner regional Australia | 24 (16.7) | 9 (12.2) | 15 (21.4) | |
| Outer regional Australia | 1 (0.7) | 0 (0.0) | 1 (1.4) | |
| Mental health | ||||
| Depression (HADS), median (Q1, Q3) | 3.5 (2.0, 6.0) | 3.5 (1.0, 6.0) | 3.5 (2.0, 7.0) | |
| Possible clinically important depression (HADS depression score ≥8), |
23 (16.4) | 11 (15.7) | 12 (17.1) | |
| Anxiety (HADS), mean (SD) | 6.4 (3.9) | 6.6 (4.1) | 6.1 (3.7) | |
| Possible clinically important anxiety (HADS anxiety score ≥8), |
49 (35.0) | 29 (41.4) | 20 (28.6) | |
| Resilience (RS-25), mean (SD) | 141.4 (20.6) | 142.6 (19.2) | 140.2 (22.0) | |
| Moderately high-high resilience (RS-25 score >145), |
72 (52.1) | 37 (53.6) | 35 (50.7) | |
HADS, Hospital Anxiety and Depression Scale; 25th percentile, Q1; 75th percentile, Q3; RS-25, Resilience scale; SD, standard deviation.
High levels of anxiety and depression were common (
Social determinants predicting mental health related variables, controlling for severe asthma diagnosis.
| Social determinants | Log depression | Anxiety | Resilience | |
|---|---|---|---|---|
| Posterior mean of β (95% credible interval) | Posterior mean of β (95% credible interval) | Posterior mean of β (95% credible interval) | ||
| Age (years) | 0.006 (−0.003, 0.015) | −0.05 (−0.10, 0.00) | ||
| Sex | Male | Reference | Reference | Reference |
| Female | 0.095 (−0.154, 0.359) | −2.18 (−9.88, 5.52) | ||
| Ethnicity | Caucasian | Reference | Reference | Reference |
| Not Caucasian | 0.113 (−0.365, 0.618) | 1.62 (−0.96, 4.23) | 1.79 (−13.14, 16.55) | |
| Migrant | Australian-born | Reference | Reference | Reference |
| Overseas-born | −0.347 (−0.817, 0.153) | −0.59 (−3.09, 1.84) | −0.18 (−13.91, 13.43) | |
| Living arrangements |
Living alone | Reference | Reference | Reference |
| Living with a spouse/partner | −0.074 (−0.369, 0.239) | 0.26 (−1.48, 1.98) | 3.07 (−5.49, 11.94) | |
| Living with family | −0.024 (−0.347, 0.283) | 0.68 (−0.90, 2.38) | −2.34 (−11.58, 7.07) | |
| Employment status |
Working full- or part-time | Reference | Reference | Reference |
| Not studying or working due to health | 0.90 (−1.12, 2.89) | −0.61 (−11.28, 10.51) | ||
| Not working for other reasons/retired | 0.009 (−0.267, 0.285) | −0.90 (−2.39, 0.51) | ||
| Neighborhood socio-economic disadvantage | Index of relative economic disadvantage | −0.002 (−0.005, 0.002) | −0.02 (−0.03, 0.00) | 0.10 (−0.02, 0.21) |
| Geographical remoteness |
Major city of Australia | Reference | Reference | Reference |
| Inner regional Australia | 0.149 (−0.190, 0.478) | 0.53 (−1.25, 2.39) | −2.11 (−11.71, 7.85) | |
Reference categories are denoted with the word “Reference”. Analyses where the 95% credible interval does not include 0 are bolded.
Categories of living in a share house and other arrangements were excluded due to small cell size.
Categories of studying and domestic studies were excluded due to small cell size.
Category of outer regional Australia was excluded due to small cell size.
Overall, few social determinants were associated with mental health (
Quantifying the relationship between social determinants and mental health among people with asthma contributes to a holistic approach to health in this population. We see that age, sex and employment may be key social drivers of mental health in people with asthma. However, the reliability and generalizability of these findings are limited by the small and relatively homogenous cohort, which was biased toward better social advantage and low geographic dispersion compared with the general Australian population. Indeed, although some social determinants were associated with depression, anxiety and/or resilience, the pattern across these mental health measures was inconsistent. Person-level health or psychological determinants such as disability and interpersonal relationships may be more strongly associated with mental health at an individual-level, whereas social determinants may be observable in large-scale studies and important at a population-level.
Age and sex are often considered important social determinants of mental health, although the strength and directions of the associations vary in different contexts. In the current study, older age was associated with greater resilience. The literature is mixed in this regard, with reports of lower resilience with advancing age, likely due to cumulative life stressors or homeostatic mechanistic changes (
Not working due to health was associated with depression. This association is likely bidirectional. Depression may increase the risk of unemployment or underemployment, either directly or indirectly through another factor such as disability (
Ethnicity and migrant status, living arrangements, socio-economic disadvantage and geographic remoteness were not associated with any of the mental health variables in this study, and yet their true effect on an individual or the population may be profound. Most of our sample were Caucasian, Australian-born, and recruited from one geographic region, so our ability to detect the effect of these variables on mental health was limited. Living arrangement does not capture the quality of social relationships, which is likely to be a more influential driver of mental health. Socio-economic disadvantage and remoteness were characterized in terms of an individual's address, rather than an individual's own advantage, income, or access to healthcare or social services. Therefore, these variables likely underestimated the true effects of these social determinants on mental health.
We saw little difference in social determinants in severe compared with mild-moderate asthma, which is consistent with a previous study of a large pediatric sample that showed a similar lack of difference (
The key strength of this study was that the cohort was enriched with a large sample of individuals with severe asthma, who are typically underrepresented in asthma research. This has allowed us to characterize social determinants of mental health in this important group. Regarding study limitations, this was a cross-sectional observational study investigating simple and potentially confounded effects, so no inference on causality can be made with these data. Several potentially important socio-demographic social determinants were not captured in this study; in particular, we had no direct measures of household income or poverty, education, housing security or social inclusion. Furthermore, since participants were a convenience sample, some socially disadvantaged groups were underrepresented, which introduced bias in the sample. In particular, migrants from developing countries, homeless, job-seekers, persons with low income and rural or remote located Australians were poorly captured in this study. These groups tend to have poorer health status.
Our exploratory findings contribute to the large body of work fostering a holistic approach to health and striving for health equity in people with asthma, particularly those who experience mental health problems. Larger studies that overcome sampling limitations will help provide stronger, more actionable evidence. Screening for and intervening on social determinants of health improves outcomes for asthma and mental health (
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
The studies involving humans were approved by Human Research Ethics Committee of the Hunter New England Local Health District. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
SH: Writing – original draft, Writing – review & editing, Conceptualization, Data curation, Formal Analysis, Methodology. HL: Writing – original draft, Writing – review & editing, Conceptualization, Data curation, Methodology. VC: Writing – review & editing, Conceptualization, Methodology. AV: Writing – review & editing, Investigation. AS: Writing – review & editing, Investigation. VM: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing.
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by grants from the John Hunter Hospital Charitable Trust Research Grant Scheme, the Hunter Medical Research Institute, and The University of Newcastle. Doctors Lewthwaite and Clark are supported by the NHMRC Centre of Research Excellence in Treatable Traits.
The authors acknowledge Ms Paola Urroz Guerrero and Ms Brooke Bailey who collected participant data reported in this study and Professor Peter Gibson who is part of the Understanding Breathlessness in Asthma study management group.
HL reports consulting fees from Lung Foundation Australia; speaker fees from Lung Foundation Australia, Exercise and Sports Science Australia, and European Respiratory Society; grants from NHMRC, Diabetes Australia, and Hunter Medical Research Institute. VC reports speaker fees from Astra Zeneca. VM reports speaker and advisory board fees from AstraZeneca, GlaxoSmithKline, Boehringer Ingelheim, and grants from AstraZeneca, GlaxoSmithKline, NHMRC, and MRFF outside the submitted work. She is a board director of the Thoracic Society of Australia and New Zealand.
The remaining 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.
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.