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Domain 1- Culturally Responsive Clinical Practice

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Domain 1- Culturally Responsive Clinical Practice

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I have developed my understanding of Domain 1.4 and the importance of family and community, and its impact on consent, treatment, and follow-up for Iraqi migrants and refugees (Culturally Responsive Clinical Practice, 2019, p. 12). Having analysed the competency standards, I now realise that as a nurse I must navigate family relationships when planning care and support their involvement in shared decision-making. (Culturally Responsive Clinical Practice, 2019, p. 14). This understanding will be essential to me in the workplace because I will be able to apply it through building trust, showing respect and asking non-leading questions to gain an understanding of the patient’s family dynamic. Throughout reading this framework and resources, I have felt that my knowledge of family and community has allowed a deeper understanding of Iraqi culture, amplifying my commitment to cultural humility.

references:

Culturally Responsive Clinical Practice: Working with People from Migrant and Refugee Backgrounds competency standards framework for clinicians, January 2019.

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Social inclusion and non-discrimination hold great significance for refugees arriving in Australia and their overall health upon resettling.

According to the findings of The Trajectories of Psychological Distress and Social Integration in Newly Resettled Refugees (P. Nguyen et al., 2023), the 5-year follow-up for refugees shows that high levels of psychological distress increased due to social integration factors such as discrimination and lower English proficiency. This same article reports that women of Middle Eastern backgrounds show higher levels of distress due to these social factors of inclusion. Another study from Frontiers in Psychiatry: Determinants of mental illness among humanitarian migrants (Cooper et al., 2019) states that high reports of mental illness, such as PTSD, remained prevalent over 3 years of resettlement, especially among people of Middle Eastern background, increasing outcomes of chronic health conditions and poor-rated health.

https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2019.00545/full

https://link.springer.com/article/10.1007/s00127-023-02528-7

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Southern Synergy, Department of Psychiatry, Monash University, Melbourne, VIC, Australia

Department of General Practice, Southern Synergy, Department of Psychiatry, Monash University, Melbourne, VIC, Australia

Centre for Mental Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia

Mental Health Program, Monash Health, Melbourne, VIC, Australia

Background: As refugee numbers grow worldwide, understanding prevalence and determinants of mental illness in this population becomes increasingly important.

Methods: We used longitudinal data to examine the initial years of resettlement in Australian refugees with a focus on ethnic-like social support. Three annual waves from a longitudinal, nationally representative cohort of 2,399 humanitarian migrants recently resettled in Australia were examined for two mental illness outcomes: post-traumatic stress disorder indicated by positive PTSD-8 screen and "high risk of severe mental illness" (HR-SMI) by Kessler Psychological Distress Scale (K6) ≥19. Generalized linear mixed models examined demographic and resettlement factors.

Findings: Contrary to predictions, high prevalence of positive screens for mental illness persisted over 3 years. At baseline, 30.3% (95% CI, 28.5-32.2) screened positive for post-traumatic stress disorder (PTSD), and 15.4% (95% CI, 14.0-16.9) had HR-SMI. Over the 3 years, 52.2% met screening criteria for mental illness. PTSD was associated with older age, females, Middle Eastern birthplace, increasing traumatic events, more financial hardships, having a chronic health condition, and poor self-rated health. HR-SMI was associated with females, Middle Eastern birthplace, unstable housing, more financial hardships, having a chronic health condition, poor self-rated health, and discrimination. Also contrary to predictions, like-ethnic social support was positively associated with PTSD (OR, 1.51; 95% CI, 1.10-2.09).

Interpretation: There is high prevalence of positive screens for mental illness throughout initial years of resettlement for refugees migrating to Australia. Our unexpected finding regarding like-ethnic social support raises future avenues for research. Predictors of mental illness in the post-migration context represent tangible opportunities for intervention and are likely relevant to similar resettlement settings globally.

Introduction

The number of forcibly displaced people worldwide has currently reached levels second only to the number shortly after World War II ( 1). The United Nations High Commissioner for Refugees (UNHCR) estimates that there were 22.5 million refugees and 2.8 million asylum seekers worldwide at the end of 2016, equating to, on average, 20 people displaced from their homes every minute ( 1). Australia's humanitarian intake represents the third highest rate of UNHCR humanitarian resettlement worldwide, behind the United States and Canada, and is committed to a programme in 2018-2019 aiming to permanently resettle 18,750 humanitarian migrants ( 1, 2). Individuals acquiring visas prior to arrival in Australia are considered as offshore humanitarian migrants and individuals acquiring visas after arriving in Australia as onshore humanitarian migrants ( 2). The Australian offshore humanitarian migrant programme resettles individuals under a Permanent Protection visa. The Australian onshore humanitarian migrant programme resettles individuals under the "Refugee" or "Special Humanitarian Programme" visa categories ( 2). The onshore and offshore migrant groups are herein described as "humanitarian migrants" for this study.

Humanitarian migrants appear to be at a greater risk of mental illness, especially post-traumatic stress disorder (PTSD), when compared with wider host and non-refugee migrant populations ( 3- 5). Authors of a meta-analysis considering conflict exposed populations and refugees showed prevalence of PTSD as 30.6% (95% CI, 26.3-35.6%) and depression as 30.8% (95% CI, 26.3-35.6%) ( 6). Forced migration involves major transitions in cultural and socioeconomic systems and the reconstruction of social networks ( 7). Additionally, the stresses of premigration trauma, intra-migration voyages, and socioeconomic instability in the post-migration context may contribute to the high prevalence of mental illness found in refugee populations ( 6, 8, 9). While the predictors of mental illness may appear similar to non-refugee populations, it is likely they obtain extra significance in the refugee context. This may be true for social support, which appears beneficial for mental health, yet may be dependent on the source of the support received. Schweitzer et al. ( 10) found only like-ethnic social support was significantly negatively associated with PTSD, whereas support received from the wider host population was not. These results are similar to other studies, both quantitative ( 11) and qualitative ( 12, 13), which suggest a greater benefit of like-ethnic support when compared with outside sources of support. Conversely, other studies provide evidence that longer time spent with like-ethnic community confers a greater risk for mental illness ( 14). Understanding the predictors of mental illness is essential for directing interventions in the post-migration context, as mental illness has been shown to negatively impact many aspects of resettlement.

Additionally, prevalence of mental illness throughout the initial resettlement period seems high among humanitarian migrants ( 15). Over the long term, the prevalence of mental illness appears determined by the degree of trauma exposure and post-migration socioeconomic context ( 16). However, whether this prevalence declines ( 11, 17) or persists ( 18) over the course of early resettlement is unclear, particularly in the Australian context.

Studying refugee populations has proven difficult given the inherent cultural and linguistic diversity of these "hidden" populations, making them difficult to engage at a population level ( 21). Past studies considering the prevalence, course, and predictors of mental illness in humanitarian migrant populations have been limited by cross-sectional design, opportunistic sampling techniques, and small sample sizes. Additionally, the bulk of the previous literature does not reflect the current distribution of nationalities seen displaced globally today. As a result, the conclusions that can be drawn from previous nonrepresentative cohorts and cross-sectional data are limited.

Our study considered data from the largest, nationally representative, longitudinal cohort survey of refugee populations to date: the Building a New Life in Australia survey ( 22). We examined the first three annual waves of data, which encompass the initial 3 years of permanent resettlement in an Australian humanitarian migrant population. Our study aimed to explore the prevalence, course, and predictors of mental illness in this population through time. The study was exploratory in nature but had two a priori hypotheses: firstly, prevalence of mental illness would decrease over time, and secondly, the presence of like-ethnic social support would be negatively associated with mental illness.

Methods

Data Source

We used the first three annual waves of the BNLA study, a nationally representative, longitudinal cohort study examining the first 5 years of resettlement in a humanitarian migrant population ( 22). The population studied were onshore and offshore humanitarian migrants who first settled in Australia from May to October 2013. The first annual wave occurred between October 2013 and March 2014, the second between October 2014 and February 2015, and the third between October 2015 and February 2016.

Participants

A census approach was used to sample participants from the Australian Department of Border Protection and Immigration (DIBP) settlement database, which contained demographic and contact details for all individuals granted Australian humanitarian migrant visas during the selected study dates.

Eligible study participants fulfilled the inclusion criteria:

● Over 15 years old

● Onshore humanitarian migrant who was granted a permanent residence visa between May and December 2013 (6 months before fieldwork dates of BNLA study)

or

Offshore humanitarian migrant that arrived in Australia between May and December 2013 (6 months before fieldwork dates of BNLA study)

● Living in 1 of 11 deemed-confidential study locations around Australia

● Written consent given to participate in study

Principal applicants (PA) are the primary adults listed on the visa application and were the initial individuals contacted for participation and were considered as the lead participants for the study. Invitations to participate were sent via mail, followed by a phone call and subsequent home visits by researchers ( 22). Secondary applicants (SAs) are other members of the migrating unit noted on the PA visa application, for example, a spouse or child. If a PA was recruited for the study, invitations to participate in study were extended to SAs. This migrating unit was considered as the primary sampling unit for the study. Individuals aged 15 years and above were included in the study in order to maximize the available data points with the view that individuals at age 15 years in wave 1 would be 18+ over the course of the study. We were able to examine the effect of age by including age variables in our multivariate models.

Outcome Measures

Questionnaires were administered to participants using multiple methods, to accommodate responses from individuals who had poor reading literacy ( 19, 22). Waves 1 and 3 were mostly administered via computer-assisted self-interview, whereas wave 2 was mostly computer-assisted telephone interview. Interpreters and interviewers were available for both methods upon participant request ( 22). Given the diversity of national and ethnic groups within the cohort, the written questionnaire was translated into 14 languages for wave 1 and with the availability of interpreters; 19 languages were covered in total for the study ( 22).

The PTSD-8 is a screening questionnaire that assesses the three symptom clusters in the Diagnostic and Statistical Manual of Mental Disorders, version IV (DSM-IV) diagnosis for PTSD ( 24). It is derived from the Harvard Trauma Questionnaire, which has shown good performance in cross-cultural populations ( 25). Participants with responses of "Sometimes" or "Most of the time" in at least one of each of the PTSD symptom clusters were considered as screening positive for PTSD. In our study, internal consistency of the PTSD-8 in wave 1 was 0.96.

A secondary aggregate outcome variable of "any mental illness" was included if either HR-SMI or PTSD was present at a given wave. As this aggregate outcome did not present any new information, it is not presented in results.

Statistical Analyses

We used Stata/SE 14.2 for Windows for all analyses ( 26). Population sample weights provided by the AIFS were used for all analyses, unless otherwise stated ( 22). Sociodemographic characteristics of the baseline cohort were summarized. Categorical data were described using frequency, percentage, and 95% confidence intervals (CIs). Continuous data were described using median and IQR, as data were not normally distributed. The prevalence of outcome variables at the population level were represented graphically with 95% CIs and significance of prevalence change across waves assessed using binomial tests.

A variable selection process with four stages (see Appendix) was used to identify the final independent variables used in the final generalized linear mixed models (GLMM). Firstly, univariate ordinal regressions were used to examine associations between baseline candidate variables and primary outcome variables, with variables retained at p < 0.1. Second, correlated variables were examined using Pearson's correlation coefficients, and one candidate variable was selected from two or more variables when r > 0.5. Selection was influenced on clinical and statistical relevance as well as amount of missing data. This step was conducted by two authors (SC and JE) so that highly correlated variables were removed from the final models. Third, we analyzed the outcomes in the panel data using GLMM via xtlogit in stata ( 26) (as dichotomous outcomes) with migrating (family) unit and individuals specified as random effects and a variable denoting "wave" as fixed. Variables at p < 0.1 and time and social support variables were retained for a second iteration of the logit model. Social support and time variables were then only retained at p < 0.1 in a third iteration of the model. Variables relating to social support and time were retained until this stage regardless of their significance, as they were directly related to the hypotheses. In the last variable selection stage, candidate variables were modeled using xtlogit over 1,000 bootstrap samples at 95% resampling of the original data set. The number of times each candidate variable achieved significance ( p < 0.05) was recorded. Candidate variables were selected for use as independent variables in final models if they were identified as significant in 1,000 bootstraps over 50% of the time. The results of this variable selection process are shown in the Supplementary Appendix.

The final models examined associations between the outcomes and independent variables selected in the four-stage process previously discussed, with migrating unit and individuals specified as random and other variables as fixed effects in the GLMM ( 27). To ensure robustness, our final models are based on 200 bootstrap samples drawn with 95% resampling. A sensitivity analysis was run by removing those variables with more than 10% missing data across all three waves and comparing the results with those of the final model. Final "Akaike's information criteria" (AIC) and "Bayesian information criteria" (BIC) were used to compare the relative "goodness of fit" for each model ( 28).

Forest plots were used to graphically represent significant findings from final models.

Missing Data

A missing data analysis was done to evaluate the potential effects of response bias. To do this, we examined potential associations between missing data and outcome measures over three waves using logistic regression. Demographic variables examined were age, gender, region or birth, and trauma. There were no significant associations between demographic variables and nonresponse to K6 or PTSD-8 over all three waves, including nonresponse due to attrition. This supported the assumption that the data appeared to be missing at random and no imputation for missing values was done.

Ethics Approval

The original BNLA study was approved by the Australian Institute of Family Studies ethics committee, which is registered with the National Health and Medical Research Council. Names of participants and potentially identifying information were withheld from the data source, meaning no individual can be identified by researchers.

Ethics exemption for secondary analysis of the data was granted by Monash University Human Research Ethics Committee.

Results

Participants

There were 1,509 principal respondents and 890 secondary respondents who completed interviews at baseline ( Figure 1) (19, 22). A total of 2,399 completed interviews at baseline, 2,009 at wave 2, and 1,894 at wave 3. The overall response rate between baseline to wave 3 was 79.0% ( Table 1).

Demographics

Table 2 shows that the majority of baseline participants were male (54.0%), originating from the Middle East (44.8%), married or partnered (57.4%), and unemployed (92.4%) with 6-12 years of pre-arrival schooling (48.8%).

Onshore and offshore migrants differed significantly by gender ( p < 0.001), region of birth ( p < 0.001), employment ( p < 0.0001), pre-arrival education ( p < 0.0001), and time since arrival ( p < 0.0001).

Social Support

Table 3 shows that approximately half of the baseline participants had received at least some support from their "national or ethnic" community (51.3%) and religious community (46.9%); a smaller proportion had received at least some support from other community groups (33.5%). A substantial minority of participants had received no support from ethnic, religious, or other community groups (41.4%).

Prevalence of Mental Illness

Figure 2 Prevalence of mental illness over time. (A) PTSD, post-traumatic stress disorder and; HR-SMI, high risk of severe mental illness. (B) HR-SMI for onshore and offshore participants. (C) PTSD or onshore and offshore participants.

Between waves 1 and 2, there was a significant decrease in the prevalence of PTSD and severe mental illness ( p = 0.001). There was no significant overall decrease between waves 1 and 3 for severe mental illness; however, for PTSD, there was ( p = 0.021) (see Supplementary Appendix).

GLMM Results

Tables 6 and 7 show the results of GLMMs with positive screen for HR-SMI and PTSD as binary outcomes after 200 bootstrap replications. Figures 3 and 4 represent forest plots of significant results from these final models. Model 1 included all variables arising from the variable selection process. Model 2 was a sensitivity analysis that excluded variables with >10% missing data across all waves. Both models detected the same independent variables reaching significance, which demonstrates robust model outputs. Model 2 reported more significant categories within the independent variables and has smaller AIC and BIC scores. However, model 1 includes variables with >10% missing data across all waves and subsequently maximizes the number of data points used in the model.

Table 6 GLMM high risk of severe mental illness. Results from generalized linear mixed models using " High risk of severe mental illness" as positive outcome.

No social support variables were significantly associated with any study outcomes in multivariate analysis stages (see Supplementary Appendix), except like-ethnic support, which was significantly positively associated with PTSD ( Table 7). Loneliness was significantly positively associated with all study outcomes ( Tables 6 and 7).

Other variables showing a significant positive association with HR-SMI were female gender, Middle Eastern region of birth, unstable housing contract, increasing financial hardship, increasing poor self-rated health, having a chronic health condition, experiencing discrimination, and financial stress ( Table 6).

Other variables showing a significant positive association with PTSD were older age, female gender, Middle Eastern region of birth, increasing number of traumatic events, increasing financial hardship, presence of a chronic health condition, and increasing poor self-rated health ( Table 7).

Discussion

Our study considers three waves of data from the largest, nationally representative, prospective cohort study of refugees conducted to date ( n = 2,399). Our study considers data from the largest prospective, population level, cohort study of refugee populations to date. The nationally representative nature of the cohort is rarely seen with research considering refugee populations. Our study is the first to use all three waves of data from the total BNLA cohort. We show the predictors of mental illness in this cohort and examine the relationship of like-ethnic social support and mental illness.

The most important finding from this study is that there was a high prevalence of mental illness that persisted over the first 3 years of resettlement in Australian humanitarian migrant populations. Although there was a significant decrease in prevalence of all primary study outcomes at wave 2, there was no significant decrease of HR-SMI from waves 1 to 3. There was a statistically significant yet perhaps clinically insignificant decrease in prevalence of PTSD from waves 1 to 3. These findings do not support our first hypothesis, and this trough in mental illness prevalence may be due to interview mode effects at wave 2, which mainly consisted of computer-assisted telephone interviews.

Our results agree with the findings from the meta-analysis of Steel et al. who showed prevalence of PTSD as 30.6% (95% CI, 26.3-35.6%) and depression as 30.8% (95% CI, 26.3-35.6%) in refugees and conflict-exposed populations ( 6). Our results also agree with Hauff and Vaglum, who showed no decline in general psychological distress and depression over the first 3 years of resettlement in a small sample ( n = 145) of Vietnamese refugees in Norway ( 18). Our findings diverge from those of other authors who have shown a decrease in prevalence of mental illness as time in host country increased in Australian ( 17) and Canadian ( 11) resettlement contexts. As our results are taken from a large, representative, longitudinal sample of the current Australian refugee population, we argue that they hold particular significance for the humanitarian migrant populations resettled both in Australia and worldwide today.

Contrary to our second hypothesis, like-ethnic support showed a positive association with PTSD. We failed to detect statistically significant multivariate associations between other social support variables and all outcome measures during our variable selection process. This is an unexpected finding and diverges from results from past authors of qualitative ( 12, 13) and quantitative ( 10) studies, who have shown the beneficial effects of like-ethnic support for mental health. Rarely have authors shown that a greater degree of support from a like-ethnic community is positively associated with mental illness ( 14). Given that our findings show an associative relationship, it may be that individuals suffering from PTSD symptomatology may be receiving greater degrees of like-ethnic support or may be reluctant to seek external sources of support due to avoidant symptoms typical of PTSD. Alternatively, given that discrimination also emerged as a predictor for PTSD and severe mental illness, it may also be that the positive association of like-ethnic support and mental illness reflects a disenfranchisement of individuals from the wider Australian society. This appears similar to findings from Beiser ( 29), who showed that the negative effects of discrimination on depression were amplified among those with greater attachment to their ethnic identity. Reminders of premigration trauma upon interaction with members of a like-ethnic community, causing PTSD symptomatology may also be a factor in this unexpected finding. Further research, including qualitative research and subgroup analysis, particularly of adolescents within the cohort, is needed to examine the nature of like-ethnic social support through resettlement in relation to mental health. Future research using trajectory modeling techniques would also allow an examination on individual illness trajectory within the BNLA cohort.

Other significant associations highlight the importance of socioeconomic stability in the post-migration context. Significant associations in this post-migration context represent modifiable factors. The dose-response-like relationship with financial hardship and mental illness appears strong, as was a similar dose-response with premigration trauma and PTSD, and self-rated health and mental illness.

Middle Eastern region of birth emerged as a significant predictor of PTSD and HR-SMI (see Figures 3 and 4) when compared with other nationalities. This agrees with recent studies showing high prevalence of PTSD and depression among Middle Eastern populations and has clinical significance given the current Middle Eastern refugee crisis ( 33, 34).

Limitations

Given this inherent heterogeneity however, it is likely our results apply to similar resettlement contexts worldwide, as our population is nationally representative of Australia's contemporaneous refugee intake and the populations currently displaced globally.

Implications of the Findings

Humanitarian migrant populations remain at a high risk for mental illness over the first 3 years of resettlement. Post-migration variables represent modifiable targets for intervention and highlight the importance of post-migration socioeconomic stability. Given the limitations considered, our results show that refugees who recently resettled in Australia are a cohort at high risk of mental illness given that the majority (52.4%) of the participants screened positive for PTSD or HR-SMI at some point in the study. Persisting high prevalence of mental illness over the first 3 years shows a possible unmet need for trauma-informed mental health service provision to newly arrived humanitarian migrants extending beyond the first year of resettlement.

The results imply that screening for mental illness may be necessary over the first 3 years of resettlement and could be a valuable part of resettlement services. Given that perceived physical health is an important positive predictor, primary care clinics could be an important point of screening. This is also echoed in the previous literature concerning somatization of mental illness in culturally diverse populations.

The positive association between like-ethnic social support and mental illness was an unexpected finding, and further mixed-methods research is needed to help illuminate the association between PTSD and ethnic-like support. At present, the conclusions that can be drawn from it are limited, and as this finding has rarely been documented in the past literature, it raises interesting avenues for future research. Further subgroup analysis is another important avenue of future research for this heterogenous population. This could include qualitative studies among culturally diverse humanitarian migrant populations to enable a greater interpretation of our results and their applicability to guiding evidenced-based interventions.

Finally, other predictors including perceived loneliness arising from our results add to the prior body of evidence highlighting the importance of stability in the post-migration context. The significant post-migration predictors shown in our results represent modifiable factors for intervention by government and mental health service providers.

Author Contributions

SC: Literature search, figures, study design, data analysis, data interpretation, writing. JE: Study design, data analysis, data interpretation, writing. FS: Study design, data interpretation, writing. GM: Study design, data interpretation, data interpretation, writing.

Conflict of Interest Statement

The 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.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2019.00545/full#supplementary-material

References

9. Priebe S, Giacco D, El-Nagib R. WHO Health Evidence Network Synthesis Reports. Public Health Aspects of Mental Health Among Migrants and Refugees: A Review of the Evidence on Mental Health Care for Refugees, Asylum Seekers and Irregular Migrants in the WHO European Region. Copenhagen: WHO Regional Office for Europe (c) World Health Organization 20; 2016.
Google Scholar
26. StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.
Google Scholar

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Frontiers | Determinants of Mental Illness Among Humanitarian Migrants: Longitudinal Analysis of Findings From the First Three Waves of a Large Cohort Study

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Background:As refugee numbers grow worldwide, understanding prevalence and determinants of mental illness in this population becomes increasingly important. ...

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As stated by the community profiles for healthcare providers- Iraqi profile, Refugees from Iraq are linked to having chronic health conditions, such as latent tuberculosis infection (P. 2 QLD Health).

Having analysed the Australian Refugee Health Practice Guide under Common Health Concerns, Tuberculosis is acknowledged as a common concern for refugees. According to this guide, LTBI is mostly asymptomatic and non-infectious unless active (History and Examination, J. Denholm et al., 2025).

Managing Tuberculosis should start with referring the patient to a clinician with experience in Tuberculosis to determine if the infection is current or dormant. Following the guide, patients should be prescribed isoniazid for 6-9 months. (Management and Referral J. Denholm et al., 2025). Other, shorter treatments such as rifamycins are also sufficient.

Noted in this Practice guide under Management and referral is the importance of clinicians to provide language and or visual information on treatment, and reassurance that their Asylum status will not change if they choose to start treatment.

https://refugeehealthguide.org.au/tuberculosis-tb/

https://refugeehealthguide.org.au/

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Written by on . Posted in Communicable diseases and immunisation, General population

Justin Denholm, Marion Bailes, Josh Francis

Recommendations

Offer tests for latent TB infection (LTBI) to all people aged ≤35 years. Children 2-10 years may have had tests for LTBI as part of pre-departure screening.

Screening and preventive treatment for LTBI people >35 years will depend on individual risk factors and jurisdictional requirements in the particular state or territory.

Offer LTBI testing with the intention to offer preventive treatment and follow up.

Use either the Tuberculin Skin Test (TST) or blood Interferon Gamma Release Assay (IGRA) to screen for LTBI.

TST is preferred over IGRA for children <5 years of age.

A positive TST is induration of ≥10mm in adults and children from refugee-like backgrounds; or ≥5mm in the setting of severe malnutrition, HIV infection, immunosuppression, or in children who are recent contacts of active TB cases.

Ensure that a CXR has been performed during the migration process for those aged ≥11 years as per screening guidelines. If so, a post-arrival CXR is not required unless TST or IGRA are positive, or there are respiratory symptoms suggestive of active pulmonary TB disease.

Refer individuals with a positive TST or IGRA to specialist TB services for assessment and exclusion of active TB, and consideration of treatment for LTBI.

[accordion tag=h3 clicktoclose=true autoclose=false][accordion-item title="+ Overview" state=closed]

Tuberculosis is a relatively uncommon infection in Australia. In 2013, the overall incidence of active TB was 5.5/100,000 population per year; however, nearly 90% of cases occur in overseas-born Australians, with a rate of 18.4/100,000 compared to 0.7/100,000 in non-indigenous Australian-born people. Although people born in India, the Philippines, China and Nepal make up more than half of the overseas-born cases of active TB in Australia, the highest rates are in people born in humanitarian source countries.

Immigrants born in high-incidence countries, including people from refugee-like backgrounds, are identified as high priority candidates for screening and treatment for LTBI. Post-arrival screening and LTBI treatment in those from a refugee-like background can prevent TB transmission in the community and limit the numbers of cases and deaths from TB. Australia's National TB Advisory Committee (NTAC) supports this approach.

Transmission of TB occurs through inhalation exposure of aerosolised droplets from people with active respiratory TB. Often this is a household contact or family member, but often no specific exposure is identified. In most exposed people, infection is contained locally, without progression to active TB, with the organism remaining in a state of latency - LTBI. Active TB may be primary disease (occurring directly after initial infection) or reactivation disease (occurring after a latent period that may last many years). Primary disease is more common in children; reactivation disease is more common in adolescents and adults. For people with LTBI, the lifetime risk of active TB is 5-10%. The lifetime risk of TB reactivation for immigrant children less than 5 years of age has been estimated to be 17% and the lifetime risk of those with untreated HIV infection is estimated to be 100%. ³⁷ The risk of developing active TB following exposure is greatest in the 12-18 months following exposure. ³⁸ Thus if TB infection has been acquired in the period immediately prior to travel (e.g. in crowded living conditions, including refugee camps), people are at greatest risk of progressing to active TB soon after arrival in Australia. Australian data from 2003-2012 show 85% of active TB in overseas-born children was diagnosed within 5 years of arrival; however, other population data have found nearly 50% of cases of active TB occur more than 5 years after arrival.

Although pulmonary disease is the most common presentation of active TB in adults and children, non-pulmonary active TB represents a higher proportion of all TB cases in immigrants compared to Australian-born people and active TB can present in almost any organ.

LTBI is common in children and adults from a refugee-like background in Australia. Australian studies of resettled refugee cohorts have reported prevalence figures for LTBI ranging from 7-71%. Australian data suggest the prevalence of active TB is generally <2% in adults from a refugee-like background, 43,48,50 and 0-5% in children (for more information see prevalence tables). [/accordion-item]

[accordion-item title="+ History and examination" state=closed]

Review the migration pathway, previous TB screening, and any past history of TB, TB treatment, or contact with active TB. Clarify the DHC in offshore arrivals, as the DHC includes live viral vaccines (LVV), which may influence the timing and interpretation of the TST if this test is used for screening.

Offshore humanitarian arrivals and those who have been in detention centres aged 11 years and older (at the time of arrival/detention) will have had a CXR, and children aged 2-10 years applying for humanitarian or onshore protection visas, or, from high TB prevalence countries will have had an IGRA or TST and further investigations if positive (from 2016). Asylum seekers arriving by plane are unlikely to have had a CXR and may not have had screening for active TB or LTBI.
LTBI is by definition asymptomatic and non-infectious.
Classic clinical symptoms of active pulmonary TB include chronic cough and haemoptysis. However, active TB may present with non-specific symptoms, including fever, malaise and weight loss or failure to thrive/poor growth in children, night sweats and lymphadenopathy. In the early stages of active pulmonary TB, respiratory symptoms may be absent.

Consider comorbidities that might affect risk for disease progression (e.g. low vitamin D, HIV infection), tolerance for preventive treatment (e.g. hepatitis with older age), or ability to access health services (e.g. literacy, household location, competing priorities). [/accordion-item]

[accordion-item title="+ Investigation" state=closed]

Ensure active TB has been excluded, through history, examination, and CXR and other investigations where appropriate.
If active TB is suspected refer for urgent specialist assessment and ensure appropriate infection control precautions. Neither TST nor IGRA should be used to exclude active TB in adults or children. Investigation for LTBI is completed with either the TST or (blood) IGRA. TST is preferred to IGRA for children less than 5 years of age.
All people from a refugee-like background aged ≤35 years, including children, should be screened for LTBI, ideally within one month of arrival in Australia, unless screening has been completed pre-departure. However, the risk of developing active TB persists (even decades after arrival), and screening should be offered at whatever stage individuals are identified and assessed.

Testing for LTBI should be performed with the intention to offer preventive treatment, taking into account the risks and benefits of preventive treatment; however, practice differs between different jurisdictions, and some states and territories will screen all new arrivals, including those over 35 years.

There is no indication to perform both tests. Neither test is 'gold standard' and individual factors may determine which test is preferred e.g. IGRA testing may be preferable in people with a history of BCG vaccination after infancy (BCG >1 year old) and/or people who have had the BCG vaccine more than once. In HIV-infected adults IGRA tests perform similarly to TST in identifying latent TB. Logistic factors may also influence testing decision, with IGRA requiring blood sampling, while TST requires a return visit for test reading, and should not be completed within 4 weeks of LVV. Testing may not be available outside hospitals or TB services. IGRA is not currently Medicare-rebatable unless the person is immunosuppressed.

A positive TST is considered to be induration of ≥10mm in recent immigrants from high TB prevalence countries (i.e. many adults and children from refugee-like backgrounds); or ≥5mm in the setting of severe malnutrition, HIV infection, immunosuppression or in children who are recent contacts of active TB. A positive IGRA is defined by the manufacturer's guidelines.*

* For the TST: a false negative result may occur with very recent exposure, active TB, immunosuppression, HIV, malignancy, viral infection, in older adults, and within 4 weeks of LVV (consider pre-departure screening in offshore arrivals). A false positive result may occur as a result of exposure to non-tuberculous Mycobacteria or previous BCG immunisation (particularly if given after early infancy); however, in practice, it is usually advisable to disregard the BCG when interpreting the TST.
For IGRAs: A false negative result may occur with very recent exposure, TB disease, and immunosuppression, although IGRA are less likely to be a false negative in HIV compared to the TST. A false positive result may occur with some non-tuberculous Mycobacteria. An indeterminate result can be due to a low positive control or a high negative control. In this situation the IGRA can be repeated once, and/or a TST considered. [/accordion-item]
The first line preventive treatment of LTBI is 6-9 months of isoniazid (10mg/kg up to 300mg daily, pregnancy category A).
[accordion-item title="+ Management and referral" state=closed]

People with a positive TST or IGRA should be referred to clinicians with experience in TB for assessment and repeat CXR (for radiological signs of current or past TB), unless there is a recent (within 3 months) CXR available for review. Baseline LFTs should be performed prior to commencing treatment for LTBI.

Treatment for LTBI is only undertaken after active TB has been excluded, and should be administered by experienced clinicians, in communication with a coordinated TB service. Treatment of LTBI has been shown to significantly reduce the individual risk of subsequent active TB, and LTBI treatment is recommended unless contraindicated. Relative contraindications include liver disease, older age and in patients where adherence is likely to be problematic.

Shorter course regimens, particularly those including rifamycins (pregnancy category C), are also effective.

Treatment is generally well tolerated, although adverse effects including hepatotoxicity are well described, especially in people over 35 years, and/or people with pre-existing liver conditions. A study of newly arrived refugees in Australia found high rates of LTBI treatment acceptance. When people are offered LTBI treatment, it is essential they understand the difference between LTBI and active TB, the pros and cons of treatment, and the duration of treatment. Provide language appropriate (and/or visual) information on treatment and side effects, and check patient understanding through teach-back techniques where possible.

While treatment of LTBI is recommended and should be encouraged, it is not compulsory and people should be reassured that their visa status/asylum claim will not be affected if they decide not to proceed. In this situation, advise patients to seek early review for symptoms of active TB, and consider CXR 6-12 monthly for 2 years if there is a high index of suspicion of recent exposure (within 2 years).

People receiving LTBI treatment should be reviewed regularly to reinforce understanding of treatment and side effects, and to encourage adherence. They should be educated to stop their isoniazid and to contact their healthcare providers immediately if they develop adverse treatment effects (i.e. rash, anorexia, nausea, vomiting, abdominal discomfort, persistent fatigue and weakness, dark-coloured urine, pale stools or jaundice). Isoniazid can cause peripheral neuropathy in people who are malnourished. This can be prevented by concomitant administration of pyridoxine (6.25-25mg/day, by age, not per kg). People with baseline abnormal liver function should have routine periodic laboratory testing, an asymptomatic rise in LFTs is not uncommon (10-20%), and may not require treatment cessation. [/accordion-item]

[accordion-item title="+ Special considerations in children" state=closed]

Following exposure to TB, children may develop either LTBI or uncontrolled primary infection. Young children have the greatest risk of developing active TB after exposure, and also have the greatest risk of developing severe/disseminated TB, including TB meningitis.
All children with LTBI (where active TB has been excluded) should be offered preventive All children <5 years with current/recent household contact with active pulmonary TB should be discussed urgently with local TB programs, irrespective of any available screening test results. treatment for LTBI.
Clinical indicators of active TB are often subtle in children and a careful history and examination is required, including measurement of growth parameters. Symptoms include chronic cough, malaise, and weight loss/failure to thrive.

All children should be screened for LTBI and assessed for clinical features of active TB. TST is the preferred test for latent TB in children under 5 years. IGRA testing in this age group is associated with an increased proportion of indeterminate results.

New pre-departure TB screening protocols for children applying for humanitarian visas were introduced at the end of 2015 (IGRA or TST testing for children aged 2-10 years with follow-up of positive results). If screening results are available and valid (i.e. a positive or negative result for those who had IGRA testing), and children are reviewed soon after arrival, children do not need repeat LTBI testing unless there are additional clinical risk factors. Repeat testing (and ideally test using TST in those < 5 years) in children with indeterminate or failed IGRA testing. Ensure testing for LTBI in children who have not had previous LTBI screening, or where results are not available. Children <2 years will not have had pre-arrival LTBI screening and should be screened using TST on arrival.

Neither TST nor IGRA should be used to exclude active TB in children, but a positive result on either test indicates TB infection. All children with a positive TST or IGRA should be referred to clinicians with experience in TB for assessment to review/complete a CXR. Children aged <11 years who arrived before the end of 2015 will not have had a CXR as part of offshore/detention screening. From 2016, children aged 2-10 years with positive pre arrival LTBI screening will have had a CXR prior to arrival.
Translated resources for LTBI
Children who have recent contact with active TB cases should be managed by a specialist TB service. Those without previous screening will typically have a baseline TST, and if negative (after active TB is excluded) commence isoniazid until a repeat TST at 3 months ('break of contact' to look for TST conversion) when further decisions are made around ongoing management. Management of children who have had prior screening will depend on the clinical scenario.

The investigation and treatment of active TB and LTBI in children should be undertaken by specialist paediatric and TB services with experience in the management of paediatric TB. Coordinated management of all family and household contacts by the same service is recommended, and has been shown to improve treatment adherence. [/accordion-item]

[accordion-item title="+ Considerations in pregnancy and breastfeeding" state=closed]

Consider pregnancy when organising a CXR in women of childbearing age. CXR may be deferred in asymptomatic pregnant women. Neither pregnancy nor breastfeeding is a contraindication to the use of isoniazid (category A) preventive therapy in the setting of individuals at risk of progression to active TB. Infants are at significantly higher risk of developing active TB following TB exposure, and preventing active disease in women with young children is a priority. Pregnant or breastfeeding women with suspected active TB should be referred urgently to a specialist TB service. [/accordion-item]

[accordion-item title="+ Links and resources" state=closed]

Calculator to determine risks of TB reactivation versus risks of isoniazid.

Easidose, a visual prescribing aid

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Written by on . Posted in Communicable diseases and immunisation, General population Justin Denholm, Marion Bailes, Josh Francis Offer tests for latent TB infection (LTBI) to all people aged ≤35 years. Children 2-10 years may have had tests for LTBI as part of pre-departure screening.

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An article from Traditional Medicine of Karen, Nepali and Iraqi Refugees reports that the traditional beliefs of Muslim people are highly religious, and since the Iraq-Iran war, the country has lost many physicians (P. 3, J. Huang 2011).

There are said to be many practices used in their medicine, such as cumin and egg yolk heated in water, dipped into a rag and placed on the forehead to treat a fever. (P. 3, J. Huang 2011).

Another treatment used particularly for burns uses barley and butter mixed together and placed on the skin as a dressing for 48 hours. (P. 3, J. Huang 2011).

Another source from eCALD on Iraqi culture explores the spiritual beliefs of health in Iraq, one being an evil spirit known as "Jinn" who is said to cause illnesses associated with mental Health (P. 4).

https://med.virginia.edu/family-medicine/wp-content/uploads/sites/285/2017/01/Joseph-Huang-Traditional-Medicine-Karen-Nepali-Iraqi_Web.pdf

https://www.ecald.com/assets/Resources/Assets/C3-P1-S2-Iraqi-Culture.pdf