Journal of Pain and Symptom Management
Volume 38, Issue 4 , Pages 533-545, October 2009

A Community Population Survey of Prevalence and Severity of Dyspnea in Adults

  • David C. Currow, MPH, FRACP

      Affiliations

    • Department of Palliative and Supportive Services, Flinders University, Adelaide, Australia
    • Corresponding Author InformationAddress correspondence to: David C. Currow, MPH, FRACP, Department of Palliative and Supportive Services, Flinders University, 700 Goodwood Road, Daw Park, South Australia 5041, Australia.
    • ,
  • John L. Plummer, PhD, AStat

      Affiliations

    • Department of Anaesthesia, Flinders Medical Centre, Bedford Park, Australia
    • ,
  • Alan Crockett, PSM, MPH, PhD, Grad Cert HE, FANZSRS

      Affiliations

    • Discipline of General Practice, University of Adelaide, Adelaide, Australia
    • ,
  • Amy P. Abernethy, MD

      Affiliations

    • Department of Palliative and Supportive Services, Flinders University, Adelaide, Australia
    • Division of Medical Oncology, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA

Accepted 19 February 2009.

Article Outline

Abstract 

Given the progress in the symptomatic treatment of breathlessness, and the physical and psychological morbidity associated with chronic breathlessness, estimates of the size of the population that may benefit from better support become imperative. Prevalence estimates have varied widely (0.9% of clinical encounters to 32%) and have largely relied only on respondents who used clinical services. Whole-of-population approaches may be able to define better the “true” prevalence of chronic breathlessness and quantify exertion limited by breathlessness. The aim of this study was to estimate population levels of chronic breathlessness, severity of limits to exercise, and demographic predictors of the presence of breathlessness. A whole-of-population face-to-face survey method (n=8,396) in South Australia was used, directly standardized for age, gender, country of birth, and rurality. Respondents were asked about breathlessness and levels of exertion causing breathlessness for at least three of the last six months using a modified Medical Research Council dyspnea scale. Univariate and multivariate analyses identify the demographic characteristics of people more likely to experience chronic breathlessness. With a participation rate of 65.3%, 8.9% of respondents had breathlessness that chronically limited exertion. Significant associations with chronic breathlessness in multivariate analysis included female sex (P<0.001), not working full time (P<0.001), low income (P=0.007), and older age (P=0.031). There are significant levels of chronic breathlessness in the community. Given the prevalence, it is feasible to explore the onset of breathlessness, the underlying etiologies and subsequent health service utilization, and health consequences.

Key Words: Dyspnea, symptom burden, symptom intensity, population health planning, prevalence survey, chronic complex disease

 

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Introduction 

The subjective somatopsychic sensation of breathlessness at rest or on minimal exertion creates significant distress for people and their caregivers across the community.1 Even after reversible causes of dyspnea are optimally treated, there are people who continue to experience shortness of breath as part of their daily life, limiting their well-being. Mechanisms for such breathlessness include a combination of pathologies encompassing chronic lung and heart diseases, malignancies, chronic infections, anemia, progressive muscle weakness, obesity, and anxiety.2

The ultimate aim of health care and health services is to optimize function3 and minimize morbidity. The prevalence and limits to exertion caused by breathlessness need to be defined across the whole population irrespective of health service utilization. This is especially the case if a person's breathlessness can be improved by: reversing or stabilizing the underlying cause(s) of breathlessness;4, 5, 6 improving function;7, 8, 9 addressing comorbidities, such as anxiety and depression, which are more commonly associated with people with severe breathlessness;10 and simultaneously relieving the subjective sensation of dyspnea using physical, cognitive, or pharmacological interventions.11, 12, 13, 14, 15 With level of breathlessness as a potential predictor of prognosis in chronic obstructive pulmonary disease (COPD), its prevalence becomes important for health planning.16

Quoted prevalence rates for dyspnea in the community vary widely (0.9%–32%), because the methods used to date have relied on respondents' having contact with health services, and therefore, may reflect the prevalence of breathlessness for that service provider, not the population as a whole.10, 17, 18, 19 Reported prevalence of breathlessness is even higher in some patient subpopulations with specific pathologies, ranging up to 100%.20 Further, levels of exertion limited by breathlessness and its chronicity have not been well explored.

A whole-of-population survey is a tool which can define prevalence and severity of a problem independent of health service access. The annual South Australian Health Omnibus survey has been used to assess a range of health needs, behaviors, and beliefs across the whole South Australian community since 1991.21 The survey provides robust data from a representative cross-section of the population (metropolitan and rural), and has the advantage that it includes people who may not use health services or whose symptom burden remains unrecognized by health professionals. Data obtained from the Health Omnibus have been used also to investigate the use of prescribed medications,22 long-term caregiver outcomes,23 and service utilization.24

The aim of this study was to define the prevalence and severity of chronic breathlessness across the whole community and, through this, to understand better the demographic characteristics of people who may face ongoing dyspnea irrespective of their contact with health services. The null hypothesis was that there would be no identifiable group within the community with higher levels of chronic breathlessness.

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Methods 

The South Australian Health Omnibus is an annual, face-to-face, cross-sectional, whole-of-population, multistage, systematic area-sampling survey. Originally, a state government population health planning tool, Omnibus is now run by a commercial research organization that employs trained interviewers and provides consolidated deidentified data. All respondents provide basic demographic data, which are supplied to the researchers in addition to the researchers' own questions.

Questions in the Health Omnibus 

On average, more than 200 questions about health beliefs and behaviors (spanning smoking to child care, arthritis to exercise habits) are included each year in interviews lasting between 60 and 90 minutes. There are no “core” questions. The questions included each year are generated from researchers and service providers around the state on a user-pays system. Researchers can purchase the “space” for any number of questions within the health survey each year.

Before the main survey, a pilot study of 50 interviews was conducted to test questions, validate the survey instrument, and assess survey procedures each year. No changes were made to the question on breathlessness as a result of the pilot.

The Breathlessness Question 

The same question on breathlessness was included in the 2006 and 2007 surveys. The definition of chronicity was adapted from a similar pain question25 (Table 1) and the responses drawn from the Medical Research Council (MRC) dyspnea scale.26, 27 The first possible response substituted “breathlessness on strenuous exertion” with “none” (Table 1). No changes were made based on the pilot.

Table 1. South Australian Health Omnibus Survey, 2006 and 2007—Question on Breathlessness

Have you experienced breathlessness most days for more than 3 months in the last 6 months?
•No.

•Yes, I get short of breath when hurrying on the level or up a slight hill.

•Yes, I have to stop for breath when walking at my own pace on the level.

•Yes, I stop for breath after walking 100m or after a few minutes on the level.

•Yes, I am too breathless to leave the house.


Sampling Schema 

The survey was carried out between September and December (Spring) 2006 and 2007, drawing 75% of the sample from the Adelaide metropolitan area, with the remainder being drawn from country centers. Each year, more than 5,000 properties are approached seeking a resident to participate in the interview (Fig. 1). (Of note, not all properties were necessarily residential. Properties may have been vacant land or businesses [retail, light industrial, or warehouses]). Participation rates are, therefore, calculated on the number of relevant potential participants contacted in a dwelling, not the number of properties approached.

In metropolitan areas, 340/2041 Australian Bureau of Statistic's Census collector's districts (CD) were randomly selected and then a starting point in each CD randomly selected. A map numbered all corners, and the SPSS random number generator then selected the starting point. Each collector used a set algorithm to move from the starting point in approaching properties. In nonmetropolitan areas, properties to be approached were selected using a further 100 randomly selected starting points statewide with a minimum of two Census Collector Districts per town; eight towns with more than 10,000 people were included, and towns with populations of 1,000–10,000 were randomly selected, with the probability of selection proportional to the size of the town. This brings a total of more than 440 starting points systematically defined geographically across the state to ensure adequately representative sampling. Having randomly defined starting points, a skip pattern of every fourth property was approached for each cluster. Where contact could not be made with a household (in distinction to a property), a further five attempts were undertaken to make contact at different times of the day and different days of the week (Fig. 1).

Using a trained interviewer, one interview was conducted per household with the person above the age of 15 years who most recently had a birthday. If the person selected by the algorithm declined to participate, he or she could not be replaced by another member of the household, and the potential respondent was categorized as a nonparticipant.

Data Quality 

All data were double entered. The few missing responses were followed up by telephone by a research supervisor. For quality assurance, 10% of each interviewer's respondents were selected randomly by a research supervisor, recontacted, and asked to confirm their eligibility and answer a subset of questions. Aggregated data were anonymized before release to researchers.

Overall, all these processes apply to the whole survey, are unchanged since the inception of the survey in 1991, and were not able to be modified at the discretion of the researchers.

Setting 

South Australia has a population of 1.6 million people (7% of the Australian population), most of whom live in one metropolitan center, Adelaide (1.1 million people), and the rest in small regional centers (maximum population: 30,000).28

Power Calculation 

Based on previously published figures, it was anticipated that the prevalence of breathlessness would be far lower than the disease-specific estimates and was set at 3%.20, 29, 30, 31, 32, 33, 34, 35 A sample size of 5,500 respondents would allow the estimation of this proportion with a 95% confidence interval [CI] of ±0.5%. A hypothesis test comparing prevalence of breathlessness in two subgroups of equal size would have 85% power at a two-tailed Type 1 error of 0.05 to detect a difference in prevalence of 2.3% vs. 3.7%. Allowing for a 60% participation rate, at least 9,200 people needed to be approached.

Statistical Analysis 

Initially, data were weighted by the inverse of the respondent's probability of selection for the survey, adjusted for participation rates in metropolitan and rural areas and then reweighted and directly standardized against the population of South Australia (2006) for gender, 10-year age group, country of birth, and region of residence (urban, suburban, outer metropolitan, regional, rural, and remote).23, 28 Before combining the data set for the two years, each annual data set was compared. There were no statistically significant differences between the years in demographics or the symptom question. Direct standardization36 macros appropriate for combining more than one survey year were applied.15 Each respondent was assigned a standardized weight, and only weighted data were analyzed.

All available demographic data have been used in the analysis. Descriptive statistics were used for respondents' demographic characteristics. The demographic characteristics for the subgroup most affected by breathlessness were defined using logistic regression, and severity of breathlessness using proportional odds ordinal logistic regression by incorporating all the plausible variables collected.37 The validity of the proportional odds assumption was assessed by examining coefficients of a generalized ordinal logistic regression model, which did not incorporate the constraint of proportional odds. Analyses used Stata version 9.2 software (Stata Corporation, College Station, TX, 2005).

Given the patterns of breathlessness, particularly in the younger age group where no one experienced the most severe level of breathlessness, and with small numbers in many other cells, analyses used a dichotomization of “no breathlessness” and “any breathlessness” for the prevalence of breathlessness. The severity of breathlessness was separately analyzed for each demographic factor using all five responses that a person could potentially make (Table 1).

Sensitivity Analyses 

To confirm the direction and magnitude of the findings, all analyses were rerun with the unweighted data, and reanalyzed using other key dichotomizations.

Ethics and Consent 

The survey receives annual South Australian Department of Health Research Ethics Committee approval. Given that this was a community survey of people in their own homes, verbal consent was obtained from all participants before interview, and continued participation accepted as continued consent.

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Results 

Of the 10,600 properties approached, contact could not be made with 2,204 (Fig. 1). Interviews were conducted with 5,480 people in the 8,396 contactable properties, of which 5,473 were evaluable (no breathlessness scores were available for three respondents, and no data for calculating weights for four respondents). There was an overall participation rate of 65.3%, which meant that the reduced number of properties with which contact was made (8,396) still ensured adequate overall power. There were 2,794 female respondents (51.0%). Almost two-thirds of people (62.1%) were married or in a de facto relationship.

Overall, 8.9% of the population sampled reported breathlessness (Fig. 1 and Table 2). More marked impairment from breathlessness was seen in 2.6% of the total population—from breathlessness while walking at one's own pace to an inability to leave the house because of breathlessness (Table 2).

Table 2. Severity of Breathlessness Daily for at Least Three of the Last Six Months Using a Modified MRC Scale for a Population-Based Sample of the South Australia Population Collected in 2006 and 2007
Episodes of Breathlessness Every Day for More than 3 of the Last 6 MonthsNumber of PeopleaPercentage
No breathlessness4,99091.17
Breathless when hurrying on level or up a slight hill3396.19
Stop for breath when walking at my own pace on the level731.13
Stop for breath after 100m or after few minutes on the level540.99
Too breathless to leave the house170.31
Not stated3<0.1
Total5,476100.00

aWeighted for the population of South Australia using gender, age, rurality, and country of birth.

Predictors of Breathlessness 

Predictors of dyspnea were explored in both single-factor (Table 3) and multifactor (Table 4) analyses.

Table 3. Results of Single-Factor Analyses of Demographic Factors Associated With Prevalence of Breathlessness (Present/Not Present) in the Community From the 2006, 2007 South Australian Health Omnibus Survey
FactorLevelsCompared With Reference Category
Odds RatioP Value
Gender, P<0.001Male, n=2,6821
Female, n=2,7941.9<0.001

Age (years), P<0.001<35, n=1,7421
35–49, n=1,4620.70.05
50–64, n=1,2441.50.008
≥65, n=1,0282.8<0.001

Highest education, P<0.001Still at school, n=3131.70.16
School, n=2,0262.8<0.001
Still studying, n=2841.30.39
Trade/diploma, n=1,9241.90.001
Bachelor+, n=9171

Marital status, P<0.001Married, n=2,9221
De facto, n=4770.90.60
Separated/divorced, n=4731.7<0.001
Widowed, n=2973.0<0.001
Never married, n=1,2940.90.36
Not stated, n=142.40.19

Lives alone, P<0.001Live with others, n=4700
Lives alone, n=7761.9<0.001

Geography, P=0.35Metro, n=4,0411
Country, n=1,4350.90.35

Income, P<0.001<$30K, n=1,2461
$30–59K, n=1,2590.4<0.001
$60–79K, n=6210.2<0.001
$80K+, n=1,2760.2<0.001
Not stated, n=1,0720.5<0.001

Work status, P<0.001Full time, n=2,0301
Part time, n=1,0221.50.49
Home duties, n=5293.5<0.001
Unemployed, n=1572.90.001
Retired, n=1,0814.8<0.001
Student, n=4331.90.026
Other, n=1226.7<0.001
Work-related injury, n=605.6<0.001
Not stated, n=424.00.067

Counts are weighted data.

Table 4. Results of Multifactor Analyses of Demographic Factors That Help to Predict Prevalence of Breathlessness (Present/Not Present) in the Community From the 2006, 2007 South Australian Health Omnibus Survey
FactoraLevelsCompared With Reference Category
Odds Ratio (95% CI)P Value
Gender, P<0.001Male1
Female1.8 (1.4–2.3)<0.001

Age (years), P=0.031<351
35–490.7 (0.5–1.1)0.10
50–641.2 (0.8–1.8)0.30
≥651.2 (0.8–1.9)0.44

Income, P=0.007<$30K1
$30–59K0.7 (0.5–1.0)0.032
$60–79K0.4 (0.3–0.7)0.001
≥$80K0.5 (0.3–0.8)0.003
Not stated0.8 (0.6–1.1)0.20

Work status, P<0.001Full time1
Part time1.0 (0.6–1.5)0.87
Home duties1.7 (1.1–2.6)0.022
Unemployed1.9 (1.0–3.7)0.06
Retired2.0 (1.3–3.1)0.002
Student1.8 (0.9–3.6)0.11
Other3.9 (2.3–6.6)<0.001
Work-related injury3.5 (1.6–7.7)0.002
Not stated3.9 (0.7–21)0.12

Counts are weighted data.

aOther factors included in the analysis were as follows: highest level of education (P=0.18); marital status (P=0.35); and single-occupant households (P=0.82).

Single-Factor Analyses—Dichotomous Prevalence (Present/Not Present) 

Analyses focused on predictors of individuals with reported breathlessness of any level (n=483) compared with those without reported breathlessness (n=4,990).

Gender. In single-factor analysis, prevalence of any breathlessness was significantly greater in women (316 of 2,794; 11.3%) than men (169 of 2,682; 6.3%; P<0.001; odds ratio [OR]=1.9; 95% CI=1.5–2.4).

Age. Prevalence of breathlessness was 6.7%, 4.9%, 9.8%, and 16.9% for individuals aged less than 35, 35–49, 50–64, and 65 years or above, respectively. Logistic regression demonstrated significant variation in breathlessness across the age groups (P<0.001). The two older-age categories had significantly higher rates of breathlessness than the youngest age group (50–64 vs. <35 years: OR=1.5, P=0.008; ≥65 vs. <35 years: OR=2.8, P<0.001).

Marital Status. Logistic regression demonstrated heterogeneity in the prevalence of breathlessness by marital status (P<0.001). Breathlessness varied across the relationship categories explored: married (8.0% of 2,922); de facto (7.2% of 477); separated or divorced (13.0% of 473); widowed (20.6% of 297); never married (7.0% of 1,294); and relationship status not stated (17.4% of 14). Breathlessness was more prevalent in people who were separated or divorced (OR=1.7; P<0.001; 95% CI=1.3–2.3) and those who were widowed (OR=3.0; P<0.001; 95% CI=2.2–4.0).

Household Size. People who lived alone (n=776) were much more likely to report having breathlessness (14.2%) than people who lived in households with more than one person (7.9%; OR=1.9; P<0.001; 95% CI=1.6–2.3). The severity of breathlessness was also significantly worse in people living in single-occupant households for each of the four categories of breathlessness (Table 1).

Highest Level of Education. Omitting the 11 people who did not state their highest level of education, logistic regression demonstrated significant heterogeneity of breathlessness when compared by educational level (P<0.001). For people with university education as their highest level of education, prevalence of breathlessness was significantly lower (4.5%; P<0.001) than the other educational groups (trade or diploma: 8.1% [OR=1.9; 95% CI=1.3–2.7]; school only: 11.7% [OR=2.8; 95% CI=2.0–4.0]).

Household Income. A large number of respondents did not identify their household income (9.7%). Logistic regression revealed significant heterogeneity in breathlessness across respondent groups (P<0.001). For the lowest income bracket (<AU$30,000; n=1,246), 16.9% of respondents reported chronic breathlessness, significantly higher than each of the other income groups (P<0.001 for all groups). Only 3.8% of the population in the highest household income bracket (≥AU$80,000) reported chronic breathlessness (OR=0.5; 95% CI=0.4–0.7 when compared with people in households with <AU$30,000).

Work Status. There was significant heterogeneity of the prevalence of breathlessness by category of work status (P<0.001). Prevalence was lowest in those working full time (4.0% of 2,030) and students (7.3% of 433), and highest in those not working because of work-related injury (19.1% of 60), retired (16.8% of 1,081), with home duties (13.0% of 527), or unemployed (11.0% of 157).

Rural/Metropolitan. There was no statistically significant difference between prevalence of breathlessness for people living in metropolitan settings and those in nonmetropolitan settings (9.1% vs. 8.1%; P=0.35).

Single-Factor Analyses—Severity of Breathlessness From Categories in Table 1 

Using the graded responses of the MRC scale, differences in severity of breathlessness for each of the individual demographic factors were of note in six analyses.

Gender. Although overall prevalence of breathlessness was greater for women (OR=1.9), using generalized ordinal logistic regression the severity of breathlessness between genders disappeared at the two most severe levels of breathlessness (breathlessness at 100m along the level [OR=1.2; 95% CI=0.7–1.9] and too breathless to leave the house [OR=0.7; 95% CI=0.3–1.8]), but numbers in these cells are small.

Age. The severity of breathlessness was most marked in the oldest age group for every gradation of breathlessness, with 1.2% of people aged 65 years or above too breathless to leave the house, and 2.7% having to stop because of breathlessness at 100m along the level. Ordinal logistic regression confirms that severity of breathlessness is much worse for people aged 65 years or above (OR=2.9; P<0.001), and for people aged 50–64 years (OR=1.5; P<0.001).

Marital Status. Having noted that people who are separated/divorced and those who are widowed have more breathlessness, these people are also confirmed to have more severe breathlessness in each of the categories of breathlessness offered in the responses using ordinal logistic regression (separated/divorced: OR=1.7, P<0.001; widowed: OR=3.2, P<0.001).

Household Size. The severity of breathlessness was significantly worse in people living in single-occupant households for each of the four categories of breathlessness offered (OR=1.9, P<0.001).

Household Income. Respondents in households with an income of less than AU$30,000 per annum had significantly higher levels of breathlessness at every level of possible response (P<0.001 for each level).

Work Status. For people fulfilling home duties, retired or unemployed, all had more severe breathlessness at every level of breathlessness than people in full-time work using generalized ordinal logistic regression. (P<0.001 for all levels in each of the three respondent categories.)

Multifactor Analysis—Prevalence of Breathlessness (Present/Not Present) 

As a result of the single-factor analyses, place of residence (rural/metropolitan) was omitted from the multifactor analysis. All other demographic factors were included in the analysis.

Using multivariable logistic regression, significant predictors of breathlessness included gender (P<0.001), work status (P<0.001), income (P=0.007), and age (P=0.031). Highest level of education, marital status, and living alone were not significant predictors in the model. The Archer-Lemeshow F-adjusted mean residual goodness-of-fit test confirmed adequacy of the model (P=0.25).38 A multifactor analysis for severity of breathlessness was not performed given the size of the cells with more severe breathlessness.

Sensitivity Analyses 

All analyses were also run without the population-standardized weightings. The direction and magnitude of the unweighted analyses confirmed the weighted results.

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Discussion 

The population prevalence of adults with dyspnea that has the potential to chronically limit exertion on a daily basis is 8.9%. Women, people not working, people living alone, and those without a university education were at highest risk.

This is, to our knowledge, the only population survey encompassing all adult ages in rural and metropolitan settings dealing with prevalence and severity of chronic breathlessness embedded in a whole-of-population face-to-face survey. It identifies that it is feasible, given this prevalence, to explore a range of factors that may predispose to breathlessness (smoking) or demonstrate consequences of breathlessness (inability to work) in subsequent surveys. Importantly, the study identifies that there is a substantial population which can be identified to be more at risk for dyspnea, and for which targeted programs for early recognition and assessment may be of value.

Prior studies have been limited by their methodologies, leading to an over- or underrepresentation of the population prevalence of breathlessness (Figure 2). For example, prior estimates of the prevalence of breathlessness were derived from studies of metropolitan populations only,18, 26 of patients of health services with specific diagnoses,6, 20, 29, 30, 31, 32, 33, 34, 35, 39, 40 of primary care health service users,19 of specific age groups,10, 18, 41 or of respondents to questionnaires that identified they were about respiratory issues before the respondents engaged in the survey.17, 18, 28, 41, 42, 43 A survey specifically and exclusively on respiratory symptoms presented to people who identify themselves as wanting to participate may overestimate the true prevalence because of a positive response bias in people who are symptomatic.18 Because the current study had questions embedded in a general health and social survey, it potentially more accurately reflects the underlying “true” prevalence of chronic breathlessness.

  • View full-size image.
  • Fig. 2 

    Conceptual outline of the population that is breathless and limitations in survey work to define the “true” level of breathlessness accounting for under- and overestimates.

What Other Studies Do These Current Data Support? 

There is a marked gender difference in dyspnea prevalence, which at first may be counterintuitive. Predisposing factors, such as tobacco smoke and occupational exposure, are less frequently encountered in females in the generations spanned in this survey. Previous studies have found increased rates of breathlessness in women compared with an apparently similar population of men,44, 45, 46 including people with COPD. 47, 48 This gender difference in symptom reporting is the subject of ongoing conjecture, but should be taken to be a true difference in prevalence.44 Likewise, pain is reported more frequently by women in the chronic setting across the population.25

A key demographic association with breathlessness is living alone. A population survey does not define causal relationships and it is not clear whether a person's breathlessness is such that they choose to live alone or, as a consequence of breathlessness, people find that others choose not to live with them. Similarly, breathlessness rates increase as workforce participation diminishes; again, the initiating cause cannot be ascribed.

In specific subpopulations of people who already have contact with health services, there are high rates of both prevalence and severity. The study by Ho et al. identified high levels of breathlessness in a community population aged over 70 years, randomly sourced through general practice in a single town with 62,000 inhabitants.10 The prevalence rates were more than double those reported in this study in people above 65 years of age, and the differences may relate to lifestyle, including differing rates of tobacco use, occupational factors, including any unique local industrial exposures, and the way in which participants were sourced for the survey.

What Are the Strengths of the Study? 

This current study used a new method to explore the background rate and day-to-day exertional limitations caused by chronic breathlessness in a whole population level using a questionnaire, and had a sufficiently large sample to allow confidence in the findings. The community rate of chronic breathlessness is central to designing interventions to better identify and manage long-term symptomatic breathlessness. The sampling measures used by the Health Omnibus allow a representative sample of the state to be obtained. As a direct result, the estimates derived by only assessing participants who access clinicians or health services are avoided.

The choice of measurement tools is also important. Breathlessness is a somatopsychic experience incorporating stimulus, transmission, meaning, and response; its measurement is complex. As a multidimensional construct with differing underlying pathologies, widely differing domains49, 50 are captured in a large number of validated measures.51 The best measure to use in a brief population survey is open to debate. The MRC scale26, 27 was chosen because it is categorical, incorporates the concept of exertional capability increasingly limited by breathlessness, and can be used quickly and simply by trained interviewers. The MRC scale has been validated in populations including people with COPD and idiopathic pulmonary fibrosis.26, 52

By using a categorical scale for breathlessness, one is also able to infer information about the functional status of the respondents, particularly those with more severe breathlessness. Ho et al. have shown that increasing breathlessness is directly correlated with diminishing ability to perform basic activities of daily living in a cohort study of people above 70 years of age, a subgroup of whom was interviewed about daily activities.10 There was a strong and statistically significant relationship between worsening breathlessness scores and diminishing function.

The worst level of breathlessness on the MRC scale directly correlates with a level of the life space measure that assesses the mobility of people living in the community.53 One level of life space looks at the ability to leave the house. There are direct correlations between diminishing life space and the ability to carry out activities of daily living, functional status, and global measures of health. Such measures reflect the diminishing environment in which a person operates as one facet of overall functional status and correlates with a number of health consequences.

What Are the Limitations of the Study? 

Design 

Population surveys are limited by the complexity of the questions that can be asked. Limitations in interviewer training also mean that the issues dealt with must be uncomplicated. There is always the risk of systematic underreporting of symptoms, especially if such symptoms can otherwise be rationalized: “I am getting older,” “I have put on some weight,” or “Of course I am going to be breathless.” Such underreporting may be lessened in a nonclinical setting, because no direct consequence is attached to the person's response. Further, the questions asked do not allow for chronic intermittent exacerbations of breathlessness that may be encountered, for example, in asthma. Given the prevalence data, such distinctions could be made in future use of these questions.

Sample 

A concern in the sample is the potential that the true rate of severe (MRC Grade 5) dyspnea may be underestimated. People with severe breathlessness may have been systematically excluded by being in hospital or long-term-care facilities given the severity of their physical impairment, or were overrepresented in the group of people who excluded themselves from participating, because they were too unwell to be involved in the whole survey given the time taken to administer the survey. Conversely, people who were at home may have been more likely to have limitations to their mobility, increasing the reported rate of breathlessness. Given the demonstrated limitations to life space for people as they age, there is a possibility that the more infirm are over-representing the number of people reporting more severe breathlessness. The weighting of the data by whole-of-state demographics does not overcome this difficulty. The sample is also limited by excluding people from very remote regions of the state.

Are These Results Generalizable? 

This report deals with responses from a single state and, given the geographic sampling technique and direct standardization to the Census population for key demographic features, these results can, within the limits outlined, be used in South Australia. It may be seen that this state is typical of many communities in resource rich countries with higher rates of access to clinical services. It is likely that these findings can largely be applied to other populations with similar demographics and profiles of tobacco use, chronic lung disease, heart failure, obesity, occupational exposures and lung cancer, and similar ways of delivering health services.

What Are the Implications for Future Research? 

Given that one in 11 people have breathlessness in this study, the prevalence of chronic dyspnea is high enough to allow the Health Omnibus to explore contributing lifestyle, occupational and health factors, including smoking, and define health service utilization patterns in people with chronic breathlessness in subsequent iterations. This would build on the nonclinical (demographic) factors that have been gathered in the current survey.

Future research in this area needs to validate these findings in different population settings internationally. Instead of using face-to-face techniques, computer-assisted telephone techniques could be used at a population level to replicate this study in other countries.

What Are the Implications for Practice? 

The question of what is a significant level of breathlessness arises. Such a question is context specific. The nature of breathlessness and its implications are subjective (the person with the breathlessness) and objective (issues for health and social services as breathlessness impacts on mobility and the social services that may need to be put in place as a consequence; psychological well-being; and health service utilization). The data are presented in detail to allow the significance of breathlessness to be defined across a variety of settings.

The data from this study demonstrate that there is a significant burden from dyspnea experienced over long periods of time in the community. Given this burden of symptoms, routine questions when dyspnea has been identified need to include its impact on day-to-day activities, chronicity, and psychological status (given excess levels of both anxiety and depression in people with chronic dyspnea).10 When people access services because of symptomatic dyspnea, data suggest that even skilled clinicians may underestimate the severity of dyspnea.54 The early identification of people whose exertional limitations are the cause of limiting their life space may allow potentially earlier and more effective interventions to allow people to adjust better to changing exertional limits. Defining a population where independence can potentially be maintained better by appropriate pharmacological and nonpharmacological interventions becomes a key goal of care.

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Acknowledgments 

Ms. Debbie Marriott is thanked for her attentive work in preparing the manuscript. Thanks also go to the statewide steering committee for the South Australian Health Omnibus, chaired by Dr. Anne Summers; to Harrison Health Research for their expert carriage of the survey; and to all of the men and women who gave their time to participate. Thanks to Tania Shelby-James and Bernadette Kenny for the constructive comments in reviewing the manuscript.

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 The National Health and Medical Research Grant #480459 funded this study. The authors declare no competing interests.

PII: S0885-3924(09)00634-4

doi:10.1016/j.jpainsymman.2009.01.006

Journal of Pain and Symptom Management
Volume 38, Issue 4 , Pages 533-545, October 2009

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