Nativity, duration of residence and chronic health conditions in Australia: Do trends converge towards the native-born population?
Introduction
Examining differences in chronic conditions between immigrants and native born people, and how this difference changes over time, is an important policy issue in countries for whom migrants make up a significant proportion of the population, such as Australia, Canada, New Zealand, the UK and the USA. For example, in Australia an estimated 26% of the total population is born overseas, and net overseas migration is the major contribution to population growth (Australian Bureau of Statistics, 2012a, Australian Bureau of Statistics, 2012b). As the number of immigrants in these countries continues to rise, it has become increasingly important to know how health profiles differ between foreign born and native born individuals, and how those health profiles change over time, since this will help identify vulnerable immigrant populations.
A large body of research has acknowledged the presence of a ‘healthy immigrant effect’ (HIE), whereby foreign-born (FB) people have better health status than their native-born (NB) counterparts upon arrival in the host country, and that this health advantage narrows significantly over time leading to a convergence towards the health of the host population (see Anikeeva et al., 2010, Argeseanu Cunningham et al., 2008, De Maio, 2010, Friis et al., 1998, Hyman, 2007, Lassetter and Callister, 2009, McKay et al., 2003, Messias and Rubio, 2004 for a review of the HIE in various continents).
However, there is little consensus about the universality of the HIE and the effect of duration of residence across all health measures and immigrant groups (Razum et al., 1998). There is some evidence to suggest that these effects are sensitive to how health is measured, which immigrant group is considered and where they migrate from or to (McKay et al., 2003). For example, McDonald and Kennedy (2004) and Newbold (2005) found mixed or no evidence for the HIE in terms of the probability that an individual rates his or her health as ‘fair’ or ‘poor’. In contrast, Newbold (2006) found strong evidence of the HIE with respect to chronic conditions in a cross-sectional analysis, but no significant difference between the NB and FB with respect to the risk of developing a chronic condition post-migration in a longitudinal analysis using a proportional hazards model. Further, researchers have also observed that immigrants of non-European origin (Ng et al., 2005) and visible minority immigrants are most likely to experience a decline in self-reported health status (De Maio and Kemp, 2010), thus emphasising the importance of heterogeneity within immigrant groups. Additionally, some studies have shown that immigrants come to their host countries with a health disadvantage compared to the majority population in the host country, implying a higher risk of disease in their country of origin and the absence of any healthy migrant effect (Albin et al., 2005, Gadd et al., 2003, Harding et al., 2008, Jamrozik et al., 2001). On the whole, previous research found a considerable variation in the association between nativity, duration of residence (DoR), and health.
A limitation of much of the published work on immigrant health is that until very recently, the literature has been dominated by studies based on a single (or repeated) cross-sectional dataset(s) which provide only snapshot(s) in time of differences in the outcome between migrants and non-migrants (Abraido-Lanza et al., 2006, Biddle et al., 2003, McDonald and Kennedy, 2004, McKay et al., 2006). While such studies are informative and have made an important contribution to the health inequality literature, it has been shown that interpretation of their findings is problematic because of confounding by time and cohort effects (Beiser, 2005). Developing a better understanding of differences in health between immigrants and non-immigrants requires detailed data on both migration and health events over time at an individual level. Longitudinal studies provide data rich enough to improve understanding of immigrant health trajectories.
A growing body of literature has started using longitudinal data to determine the health dynamics of immigrants (Chiswick et al., 2004, Chiswick et al., 2008, De Maio and Kemp, 2010, Fuller-Thomson et al., 2011, Kennedy and McDonald, 2006, Kim et al., 2013, Newbold, 2005, Newbold, 2009, Setia et al., 2011, Setia et al., 2009, Setia et al., 2012, So and Quan, 2012). However, these longitudinal studies of the determinants of migrant health also have methodological limitations. First, most of the existing studies have used balanced panels and have ignored potential biases caused by panel attrition. Second, most longitudinal studies have focused on health transitions within various immigrant groups and do not compare changes in the health of immigrants relative to native-born people (Chiswick et al., 2004, Chiswick et al., 2008, De Maio and Kemp, 2010, Fuller-Thomson et al., 2011, Kennedy and McDonald, 2006, Kim et al., 2013, Newbold, 2009, Setia et al., 2011). Without this comparison, the different immigrant health trajectories cannot be attributed to immigrant status. Moreover, the follow-up period of these analyses ranges between 3 and 3.5 years and may not be long enough for health changes to fully emerge.
Third, studies that compared immigrants and the native-born using longitudinal data with few exceptions (So and Quan, 2012) have focussed on transitions to poor health status (by selecting a cohort of ‘healthy’ respondents) and evaluated the risk of transitioning from good health to poor health utilising the Cox proportional hazards model (Newbold, 2005, Newbold, 2006, Ng et al., 2005). However these regression techniques have limited ability to handle the complexity of longitudinal dynamics, and selecting only healthy individuals may considerably reduce sample size. Additionally, the selected ‘healthy’ individuals may have different health risk behaviours than the discarded ‘unhealthy’ individuals, which may lead to inconsistent and biased results.
Fourth, while some studies such as those by Setia et al. (2009) have advanced the field by using mixed effects models for health outcomes in several waves of panel data (Setia et al., 2009, Setia et al., 2012), those mixed effects models can be significantly biased since they do not account for unmeasured confounding or mediation. Moreover, Setia et al. compared white and non-white immigrants with the Canadian-born population, and the effect of time since immigration for immigrants only, but did not measure the change in health over time of various immigrant groups vis-à-vis the Canadian born. Fifth, most of the existing research examines immigrant health based upon subjective measurement of health such as self-reported health. Researchers have questioned the validity (De Maio, 2007) and reliability (Crossley and Kennedy, 2002) of self-reported health status measures. Newbold (2006) suggested that the use of self-reported health as a ‘gold standard’ metric for need of care may be misleading, and that chronic conditions may be a better indicator of health within the immigrant population.
The present study overcomes some of these data and methodological limitations by (i) using longitudinal data with six years of follow-up (ii) reducing bias from loss to follow up (iii) using native-born people as a reference group to ensure differences in health are related to migration effects (iv) using longitudinal methods that can reduce bias from unmeasured confounding (v) using a more objective measure of health. It provides the first estimates of the nativity health gap (changes in the health of migrants vis-à-vis the Australian-born), based on an analysis of a nationally representative longitudinal dataset. Data from waves 3, 7 and 9 of the Household, Income and Labour Dynamics in Australia survey and group-mean-centred multilevel mixed models were used to investigate differences in the reporting of any chronic condition (including cancer, CVD, arthritis, diabetes and respiratory disease), and in the total number of chronic conditions, between NB and FB people from English speaking (ES) and non-English speaking (NES) countries. Differences in the persistence of self-reported chronic conditions post-migration were also examined after adjusting for potentially important covariates.
We address the following specific research questions:
- (1)
Do FB people from English speaking and non-English speaking countries have a health advantage relative to the NB in terms of reporting any chronic condition and in terms of the total number of chronic conditions reported?
- (2)
If the FB have a health advantage in terms of reporting any chronic condition, and total number of chronic conditions reported, does it decline as DoR increases and for all FB groups?
Section snippets
Data and methods
The data for this study come from the Household, Income and Labour Dynamics in Australia (HILDA) survey, a nationally representative panel survey of Australian people occupying private dwellings. The survey commenced in 2001 with a large sample of 7682 households having at least one eligible person aged 15 years and above. All members of these households aged 15 years and over form the basis of the panel to be interviewed in subsequent waves. In addition, some non-respondents in wave 1 were
Characteristics of the study respondents
Base-line (wave 3) characteristics of the respondents are shown in Table 1. A total of 6321 respondents aged 35 years or above with non-missing CoB information responded in wave 3 and in either or both of waves 7 and 9 of HILDA. Of those, 4742 (75%) were NB, 834 (13.2%) were born in ES countries, and the remaining 745 (11.8%) were born in NES countries. There were more females (n = 3404; 53.9%) in the sample than the men (n = 2917; 46.1%). NB respondents are relatively younger than the FB
Discussion and conclusion
Using HILDA longitudinal survey data we examined whether immigrants in Australia had a health advantage relative to the NB and, if existent, whether this relative health advantage was different for different immigrant subgroups. We also examined whether any initial health advantage of immigrants, if existent, declined as duration of residence increased and for all immigrant groups. Unlike many previous studies which examined immigrant health based upon self-assessed health, our analysis were
Acknowledgement
This paper is based on research being conducted as part of the research project ‘Investigating the dynamics of migration and health in Australia: A Longitudinal study’. It is supported by an Australian Research Council Discovery Grant (DP120104604) to the lead author. The paper uses the unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, which is funded by the Commonwealth Department of Families, Housing, Community Services and Indigenous Affairs
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