High prevalence of asthma in five remote indigenous communities in Australia

Australian children have some of the highest known prevalence rates of asthma, ranging 17–19.5% 1. Amongst Aboriginal and Torres Strait Islander children, who comprise ∼2% 2 of the Australian indigenous children, data on asthma prevalence are sparse and controversial. Indeed, the prevalence of asthma in indigenous communities in Australia was thought to be extremely low (0–3.3%) 3, 4. Specifically in the Torres Strait region, using an interviewer-administered questionnaire, Veale et al. 3 found that the overall prevalence of wheeze in the last 12 months in those aged 5–19 yrs was 4.6%. However, more recent reports from different regions of Australia showed higher prevalences (up to 24%) 5. Indeed, the team from the Indigenous Health Paediatric Respiratory Outreach Program, as part of their clinical service in the Torres Strait region, diagnosed asthma in many children referred by local health workers 6. Notwithstanding that there was a wide range of methods used in previous studies (different questionnaires, wide range of age groups, and the use of different tests), the reason for this apparent variation in asthma rates between communities and over time, as well as the effect of asthma in terms of morbidity and mortality, is open to conjecture.

In view of this, it was hypothesized that the prevalence of asthma symptoms in the Torres Strait and the Northern Peninsula Area may be higher than previously reported. Therefore, a study of childhood asthma in the Torres Strait and the Northern Peninsula Area was carried out to document the prevalence of asthma symptoms in children and adolescents living in five communities in the Torres Strait and the Northern Peninsula Area, Australia.

Methods

Results

Of a total of 1,120 buildings listed, 565 were included in the study and 510 either did not have any eligible children in the house or were business or government premises. The remaining 45 (4%) were refusals or empty households at the time of the interviewer's visit. There were 1,682 eligible children aged 0–17 yrs identified, with 1,650 children participating in the study (98.1%). The participation rates in Thursday Island, Saibai Island, Warraber Island, Bamaga and Umagico were 97.3%, 99.3%, 100.0%, 99.4% and 97.9%, respectively. Interviewer consistency (between two interviewers) ranged from 92–100%.

Selected demographic characteristics of the study population are shown in table 1⇓. The male to female ratio was 1:1. The majority of children were aged <10 yrs (62.7%). However, there was considerable intercommunity variation. Thursday Island had the highest proportion of children aged >10 yrs, while Umagico had the highest proportion of children aged <10 yrs (p-value=0.007). Most of the children included in the study (89.4%) were indigenous. Thursday Island had the highest proportion of Caucasian children (8.6%), Saibai Island had the highest proportion of South Sea Islanders (13.2%) and Umagico and Warraber had the highest proportion of Indigenous children, 100% and 98.1%, respectively (p-value <0.001).

There were considerable variations in the education and employment status across the communities as well (p-value<0.001 and p-value<0.001, respectively). Thursday Island had the highest proportion of carers in the higher education category (66.8%) and Umagico had the lowest (14.3%). Of the total group, more than half of caregivers (53.8%) had completed high school or had done further tertiary studies, 15.5% had not completed high school but had additional training, such as apprenticeship or had a certificate, and 30.7% had not completed high school or further training. Thursday Island had the lowest level of unemployment, whilst Umagico had the highest. When nonindigenous children were excluded from the analysis, the demographic characteristics were very similar to the aforementioned.

The overall self-reported prevalence of ever wheezing was 20.6%, 12.4% reported wheezing in the previous 12 months, 8.9% reported that they tired more easily than other children, 8.5% became more short of breath than other children, 7.8% reported wheezing after exercise and 15.8% reported ever having asthma (table 2⇓). When the prevalence of symptoms were compared across different communities, there was considerable intercommunity variation (table 2⇓) with most of these being statistically significant (crude p-values ranged 0.001–0.074). When sociodemographic differences between communities were taken into account, self-report of ever wheezing, ever having asthma or taking asthma medication in the last 12 months remained significant (adjusted p-values were 0.048, 0.012 and 0.028, respectively). The main confounding factors effecting variation in asthma symptoms across the communities were age and sex. For wheezing in the last 12 months, employment status and carer's education were also influential confounding factors and for the question “More short of breath than other children?” carer's education was also a confounding factor. Bamaga had the highest proportions of asthma symptoms (ever wheezing, ever had asthma and taken asthma medication), while Saibai Island and Umagico had the lowest (Umagico scored lowest for ever wheezing, and taken asthma medication, while Saibai Island scored lowest for ever having asthma).

For those children who reported wheezing in the last 12 months, 120 reported wheezing that was severe enough to disturb their sleep (65.3%) and 43 (23.4%) reported that it affected their speech. When these symptoms were stratified across demographic factors (table 3⇓), only the number of asthma attacks in the last 12 months was significantly different across different levels of education of the carer, with those reporting 1–3 asthma attacks having the highest proportion of carers with the lowest education attainment.

When the main three asthma symptoms were stratified by demographic factors (table 4⇓), there were small differences between the ethnic groups although these were not statistically significant. For most questions, prevalence of symptoms did not vary greatly across age groups, except for wheezing in the last 12 months where there were higher proportions of children in the lower age groups reporting this symptom (p-value=0.003). Self-reports of “ever had wheezing?” and “wheezing in the last 12 months?” varied across sex, levels of carer's education and employment status. In general, males were more likely to report symptoms than females. Those living in households with most people employed and whose carers were more educated were more likely to have ever wheezed and have wheezed in the last 12 months (p-values ranged 0.003–0.013).

Discussion

This cross-sectional survey, which utilized an indigenous health model where local health workers have an important role in healthcare, has shown that the prevalence of asthma symptoms in Aboriginal and Torres Strait Islander children living in the Torres Strait region is as high as 20.6%. This is much higher than previously reported 3, higher than black American children (13.4%), similar to Hispanic American children (20.1%) 10 and to nonindigenous Australians who have one of the highest prevalence rates in the world 11, 12.

The differences between this study and that which Veale et al. 3 have undertaken in this locality could be attributed to several factors: those related to epidemiological study methods (different questionnaires, delivery method, participation rates, definition of asthma) and those related to true difference in prevalence (period and time effect, possible intra-regional variations in prevalence). This study utilized a questionnaire validated by the ISAAC 13, modified to suit the local idiom and delivered by local health workers who were trained for the purpose of the study. It is believed that all of these factors contributed to an extremely high participation rate (97–100%). In contrast, Veale et al. 3 used a questionnaire which was not previously validated, not translated to indigenous languages, partially delivered by nonindigenous workers, with participation rates ranging from 51–80%. Given the methodological differences between the two studies, it would not be possible to determine if the different findings between the two studies reflect community or methodological differences or the passage of time.

The present study randomly sampled communities within the Torres Strait region; the children included in the study represented ∼39% of the 0–17-yr-old population for the entire Torres Strait region 2, and based on an expected prevalence of 15%, the study sample size was sufficient to estimate within 1.7% of the true population value (95% confidence interval). In addition, while the Torres Strait and the Northern Peninsula Area are geographically remote, there are considerable intercommunity differences in levels of development or Westernization of life style, as well as differences in racial mix, and these could have also accounted for the inconsistency between this study and that of Veale et al. 3.

The difference in the definition of asthma may also account for some of the disparity in prevalence between the two studies. Veale et al. 3 defined asthma as the presence of symptoms and airway hyperresponsiveness (AHR) 3. However, the presence of AHR in paediatric asthma is controversial 14, 15 and is generally reported as being of limited value in population studies in all age ranges 16. While asthmatics must be hyperresponsive on some occasions, AHR is not synonymous with asthma 16–18 and Pearce et al. 17 argue that clinical asthma, rather than AHR, should be the focus of population surveys, particularly as the sensitivity and specificity of AHR in defining asthma is low. While the direction of differences that may have occurred by including AHR in the definition cannot be resolved, it is believed that this considerable body of evidence against the use of AHR in prevalence studies suggests that the inclusion of AHR would not have provided support for estimating prevalence of asthma in the present study.

While it might be argued that the prevalence of asthma symptoms is high, there is indirect supportive evidence of the high prevalence of asthma in other indigenous communities. In an indigenous rural community in Western Australia, Bremner et al. 5 described a high prevalence (24%) of wheeze in female patients <18 yrs of age. Williams et al. 18 reported that in Western Australia, where indigenous status has been collected as part of the hospital record for several years, the admission rate for asthma was higher for indigenous than nonindigenous children (rate ratios for indigenous versus nonindigenous children ranged 1.4–5.3). While hospitalization data are not good proxy for prevalence and accuracy is questionable, at the very least, the Western Australian data suggest that serious asthma requiring hospitalization is more common among indigenous children. This is consistent with overseas studies which found the prevalence of asthma to be higher in economically disadvantaged groups 19. However, on the contrary, data from the Northern Territory suggests higher annual hospitalization rates per 1,000 population for nonindigenous children with a principal diagnosis of asthma: 2.6–4.7 for indigenous children and 5.5 for nonindigenous 20. Remoteness of the indigenous children in this latter study may have lead to bias with an underestimation with respect to hospitalization of indigenous children. Its results are also limited by the retrospective nature of the study and the gross calculation of rates. In addition, the belief that asthma in indigenous children is nonexistent 3 and infectious disease is the dominant illness, may have lead to an underestimation of asthma diagnosis 21.

Knowing the prevalence of diseases is extremely important for the clinical management of patients. However, extending this knowledge to the local setting not only impacts on the clinical care but also on public health management, such that better planning and management of medical care needs can be undertaken 22. Also, exploration of intercommunity differences may contribute to the understanding of changing prevalence of asthma and possible causative links, in particular the influence of socioeconomic factors. Significant intercommunity differences in prevalence of asthma symptoms even in neighbouring communities were found, some of these being partially explained by variations in sex, age, education and employment status. Mainland communities, Bamaga and Umagico, are only separated by 3 km, the former community being made up of Torres Strait Islander racial groups while the latter is predominantly Australian Aboriginal. Their socioeconomic profiles were significantly different, with Umagico having the highest unemployment and incomplete schooling rates, yet the prevalence of asthma symptoms was significantly lower than Bamaga. On the contrary, Warraber Island which had a higher unemployment rate than Saibai Island had a higher prevalence of asthma symptoms. While there are studies reporting the association between asthma and poverty, Rona 23 pointed out that to date there is a lack of consistent evidence that some aspects of poverty cause asthma. However, there is overwhelming evidence that poverty is a contributor to asthma exacerbations and severity. Different research groups also argue that cultural differences 24 (cultural barriers to self-care), communication difficulties 25 (different ethnic groups use different words to describe symptoms) and doctor/patient interactions can also help to explain why asthma affects different minority groups differently. Socioeconomic factors could not, however, explain all of the differences between communities studied; they also have diverse landscape and climate conditions affecting the prevailing air particles 26, and these factors could also have contributed to the findings. This study cannot fully explain the reasons for the differences observed, but further exploration within these communities would be beneficial to many aspects of healthcare and management.

Although the standardized ISAAC questionnaire was used, which is generally accepted as being a good epidemiological tool, ensuring comparable information between centres and countries 11, it is not known how the ISAAC data relate to clinical asthma or to true prevalence in indigenous groups. In addition, there are inherent difficulties with the diagnosis of asthma in children <3 yrs of age 16 and the ISAAC questionnaire was not designed for younger children. While it is the intention to carry out a longitudinal assessment of this age range, only 23% of 0–3-yr-olds reported ever wheezing and 15% reported ever having asthma. When data were stratified across demographic factors, there were some variations between the different age groups; however, chance could not be ruled out for age variations of most questions. While this does not exclude “diagnostic drift” across age ranges, that is, bronchiolitis symptoms becoming asthma symptoms, the relatively high rates of symptoms in the past year tends to affirm that the present results have not been influenced by the inclusion of this age range. Indeed, it could be that all studies of children using ISAAC protocols are influenced by “diagnostic drift”.

It is concluded that the prevalence of asthma symptoms in these remote indigenous communities is much higher than previously reported, and is comparable to nonindigenous urban centres. Furthermore, significant intercommunity variation exists and exploration of this may contribute to the understanding of paediatric asthma. This paper highlights some of the difficulties in making comparisons and of understanding the extent of the problems and the true prevalence of asthma in indigenous communities. Because of the plight of many indigenous communities/groups, and the potential for misdiagnosis from questionnaire data, these results exemplify the need for further studies designed to measure true prevalence of clinically diagnosed childhood asthma.

Appendix

Questions for wheezing and asthma (* these questions are part of the core questionnaire wheezing module for 6–7-yr-olds from the ISAAC protocol 8). Creole words added or modifications made to the questionnaire are in bold.

• *Q1- Has your child ever had wheezing or whistling sound in the chest at any time in the past? □ Yes □ No □ Not sure If No or Not sure, than go to Q6

• *Q2- Has your child had wheezing or whistling sound in the chest in the last 12 months? □ Yes □ No □ Not sure If No or Not sure, then go to Q6

• *Q3- How many attacks of wheezing sound has your child had in the last 12 months? □ None □ 1 to 3 □ 4 to 12 □ More than 12 □ Not sure

• *Q4- In the last 12 months, how often, or how many times, has your child's sleep been disturbed due to wheezing sound? □ Never wake up with wheezing sound □ Less than one night per week □ One or more nights per week □ Not sure

• *Q5- In the last 12 months, has wheezing sound ever been big enough to limit your child's speech to only 1 or 2 words at a time between breaths? □ Yes □ No □ Not sure

• *Q6- Has your child ever had short wind? (asthma) □ Yes □ No □ Not sure

• *Q7- In the last 12 months, has your child's chest sounded wheezy during or after exercise? □ Yes □ No □ Not sure

• Q8- When your child is playing does she/he become more short of breath compared to other children? □ Yes □ No □ Not sure

• Q9- Does your child tire more easily than other children do? □ Yes □ No □ Not sure

• Q10- In the last 12 months, has your child taken any medication (mersin, pills or puffers) for wheezing sound or short wind? □ Yes □ No □ Not sure (SHOW MEDICINE CARD)

• *Q11- In the last 12 months, has your child had a dry cough at night, when she/he hasn't got a cold or chest infection? □ Yes □ No □ Not sure