Asthma was more commonly reported by Indigenous than non-Indigenous Australians in this nationally representative study, but the prevalence of asthma was not associated with most traditional indicators of SES - education, employment, income, home ownership and area-level disadvantage - in the Indigenous population. In the non-Indigenous population, associations between these traditional SES indicators and asthma were generally significant, although modest in size. In both populations, main language, along with place of residence and food insecurity, appeared to be more strongly associated with current asthma than traditional SES indicators.
The lack of an association between traditional SES variables and asthma among Indigenous Australians contrasts sharply with results of previous studies of other chronic conditions such as diabetes and kidney disease. In two recent studies, diabetes prevalence was strongly inversely associated with a wide range of SES measures among Indigenous Australians [11, 12]. The higher rates of diabetes among Indigenous Australians were not completely explained by their relative disadvantage, however, as Indigenous people of high SES still had higher rates of diabetes than did non-Indigenous people of low SES . Similarly, Cass and colleagues showed a strong gradient in regional rates of Indigenous Australian end-stage renal disease according to an index of social disadvantage . Even in the least disadvantaged regions, however, age- and sex-standardised incidence of end-stage renal disease was generally significantly higher for Indigenous Australians than for the total Australian population [9, 10].
Few studies have focused on the relationship between SES and asthma in indigenous populations in other developed countries. In one large American study using 2004 data from the Behavioral Risk Factor Surveillance System (BRFSS), the higher prevalence of asthma among Native American adults compared with non-Hispanic Whites was due in large part to their lower SES . Although direct comparison was not possible in the present study, age-adjusted asthma prevalence was higher for Indigenous than non-Indigenous people of the same SES category across all variables examined, which suggests that the higher asthma prevalence of Indigenous Australians is not explained by SES differences.
The results for the non-Indigenous population are largely consistent with studies from other populations in developed countries. Among adults in 24 US states in 2004, education, income and employment status were all independently associated with asthma prevalence . Using US NHANES data for 2001-2004, another study found that males and females living below the poverty line were more likely to report current asthma than those living at or above it . In an analysis of 2005 BRFSS data, low household income (<$25,000 versus ≥$50,000) was significantly associated with asthma . In a study of adults aged 20-44 years in 32 study centres in Europe, North America and Australasia, low social class (based on occupation) and low age at completion of full-time studies were associated with current asthma prevalence after adjustment for other individual level factors, and area-level educational level was associated with asthma prevalence, regardless of atopic status . In California, higher education was associated with higher levels of asthma with hay fever (a marker of atopic status), but lower levels of asthma without hay fever .
The significantly lower prevalence of self-reported asthma among Indigenous and non-Indigenous people whose main language was not English is consistent with the higher rates of asthma in English-speaking countries generally . Language may be a marker for lower levels of exposure to asthma risk factors, lower genetic susceptibility, lower access to and/or use of health services that would result in a diagnosis of asthma, or a combination of these and other factors. Differences in access to and use of health services may also help explain the lower prevalence of asthma in Indigenous people living in remote areas. Although main language varied by place of residence, these two variables were independently associated with asthma prevalence.
Food insecurity was associated with asthma in both populations after adjustment for other factors including SES. Food insecurity, which was more common in lower SES groups but was reported across the SES spectrum, may be a more salient measure of financial stress than traditional SES measures. Although not directly comparable, the results are consistent with data from the 2004 and 2005 US BRFSS indicating a significantly higher prevalence of asthma, even after adjusting for SES, among those who reported they couldn't see a doctor because of cost in the past 12 months [5, 6].
The main strengths of the current study are the use of nationally representative data, comparisons between Indigenous and non-Indigenous populations, and identical SES measures with comparable scales in the two populations. The main limitations relate to the cross-sectional nature of the study and the potential misclassification of asthma, SES and other relevant factors.
Because information on SES and asthma were collected at the same time, the temporal relationships between SES indicators and asthma are not always certain. For example, employment status may change as a result of having a serious chronic disease such as severe asthma. This may explain why asthma was more common among those not in the labour force, at least in the non-Indigenous population.
Although the definition of asthma was limited to those who said they had been diagnosed by a health practitioner, it is possible that some people who reported asthma did not actually have it, or did not currently have it, while others who did have asthma did not report it (in some cases because they had never received a diagnosis), or reported that it was not current. It is possible that the higher prevalence of asthma in the Indigenous population, particularly in older age groups, may be explained in part by misdiagnosis of other chronic respiratory diseases as 'asthma', but other factors, such as inadequate treatment and greater lifelong exposure to tobacco smoke and respiratory infections, are likely to play an important role . Conversely, factors such as lack of access to and/or use of diagnostic services may have resulted in an under-estimate of asthma prevalence. If this was more common among those of low SES, it could explain, at least in part, the lack of observed associations between traditional SES variables and asthma in the Indigenous population. It is worth noting, however, that other factors likely to be associated with low SES, such as food insecurity, remote area residence, and speaking a language other than English, were all significantly associated with asthma.
Information used to determine SES may have been incorrectly reported by (or on behalf of) some participants, and only limited detail was available on the SES indicators examined here. Data on housing tenure was not available in the NATSIHS CURF for the non-Indigenous population. Despite the use of comparable scales, the equivalence of a given level of SES may not be guaranteed across individuals or population groups. For example, the meaning of a certain level of education may vary over time and place, and years of education do not necessarily reflect the quality of education received, nor its social or economic value [23, 24]. Similarly, the use of SEIFA quintiles based on the whole population may not adequately capture the socioeconomic position of population subgroups such as Indigenous Australians . No information was available about other potentially important SES measures, such as total household assets. An area-based measure of disadvantage was included, but no other information was available about neighbourhood/area characteristics. Although equivalised household income is intended to adjust for household size and economies of scale, the dynamic nature of Indigenous households  can make it difficult to assess both Indigenous household income and household size, both of which are required to calculate equivalised income. This analysis assessed the associations between adult SES and current asthma in adults. No information was available about childhood SES for adult participants, even though their asthma may have first occurred during childhood. The factors associated with asthma in children may be different from those in adults. Although information about asthma was available for participating children in the NATSIHS and NHS, there were few SES data available for those under 18 years.
No information was available about a number of other factors that can affect asthma risk, including air quality, occupational exposures, family history of asthma, childhood infections, domestic exposures such as mould and dust mites, passive smoking, diet, and access to care. Despite these limitations, the NATSIHS data provide the best available information on asthma in Indigenous Australian adults.
While traditional SES variables do not appear to explain the patterns of asthma in Indigenous Australians, other factors that operate across the socioeconomic spectrum, including racism and discrimination, marginalization and dispossession, chronic stress, and exposure to violence [3, 27–29], may play a role in asthma expression through a range of plausible biological pathways . The episodic nature of asthma, and the well-known challenges in diagnosing it, may also be important, especially among people with limited health literacy and/or limited access to health care, both of which are more likely in the Indigenous population.