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Social Science & Medicine 71 (2010) 1610e1619

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Social Science & Medicine

journal homepage: www.elsevier .com/locate/socscimed

Migration-related health inequalities: Showing the complex interactions betweengender, social class and place of origin

Davide Malmusi a,b,c,d,*, Carme Borrell a,c,d,e, Joan Benach c,f

aAgència de Salut Pública de Barcelona, Barcelona, Spainb Training Unit in Preventive Medicine and Public Health lMAS-UPF-ASPB, Barcelona, SpaincCIBER Epidemiología y Salud Pública (CIBERESP), Spaind Institute of Biomedical Research (IIB-Sant Pau), Barcelona, SpaineUniversitat Pompeu Fabra, Barcelona, SpainfHealth Inequalities Research Group (GREDS), Employment Conditions Network (EMCONET), Universitat Pompeu Fabra, Barcelona, Spain

a r t i c l e i n f o

Article history:Available online 6 September 2010

Keywords:Health inequalitiesMigration and healthSocio-economic conditionsSelf-rated healthSpain

* Corresponding author. Agència de Salut Pública dTel.: þ34 932027772.

E-mail addresses: dmalmusi@aspb.cat, davidemalm

0277-9536/$ e see front matter � 2010 Elsevier Ltd.doi:10.1016/j.socscimed.2010.07.043

a b s t r a c t

In this paper, we briefly review theories and findings on migration and health from the health equityperspective, and then analyse migration-related health inequalities taking into account gender, socialclass and migration characteristics in the adult population aged 25e64 living in Catalonia, Spain. On thebasis of the characterisation of migration types derived from the review, we distinguished betweenimmigrants from other regions of Spain and those from other countries, and within each group, thosefrom richer or poorer areas; foreign immigrants from low-income countries were also distinguishedaccording to duration of residence. Further stratification by sex and social class was applied. Groups werecompared in relation to self-assessed health in two cross-sectional population-based surveys, and inrelation to indicators of socio-economic conditions (individual income, an index of material and financialassets, and an index of employment precariousness) in one survey. Social class and gender inequalitieswere evident in both health and socio-economic conditions, and within both the native and immigrantsubgroups. Migration-related health inequalities affected both internal and international immigrants, butwere mainly limited to those from poor areas, were generally consistent with their socio-economicdeprivation, and apparently more pronounced in manual social classes and especially for women.Foreign immigrants from poor countries had the poorest socio-economic situation but relatively betterhealth (especially men with shorter length of residence). Our findings on immigrants from Spain high-light the transitory nature of the ‘healthy immigrant effect’, and that action on inequality in socio-economic determinants affecting migrant groups should not be deferred.

� 2010 Elsevier Ltd. All rights reserved.

Introduction

In economically advanced countries, theoretical and empiricalresearch on health inequalities and on health among migrants hasgenerally developed in parallel, with few attempts to integrate thetwo fields. Migration and health issues have only been partiallyaddressed within the health equity framework. In this paper, webriefly review theories and findings regarding migrants’ healthfrom the health equity perspective and then analyse migration-related health inequalities in Catalonia taking into accountgender, social class, and migration circumstances. The framework

e Barcelona, Barcelona, Spain.

usi@gmail.com (D. Malmusi).

All rights reserved.

of the WHO Commission on Social Determinants of Health (CSDH,2008) highlights the existence of health inequalities that aredependent on the different spheres that shape an individual’sposition in society, such as social class, gender and ethnicity (Solar& Irwin, 2007). Inequalities faced by racial and ethnic minoritieshave been widely described in countries such as the United Statesand United Kingdom, which have a very long (decades or centu-ries) history of migration, intertwined with slavery and colo-nialism, and established minorities (Nazroo, 2003). In otherwestern European countries, the study of inequalities related tomigration dynamics might be also useful, and has attractedgrowing interest. Catalonia (around 7,000,000 inhabitants), whichhas experienced a large and now established immigration flowfrom other areas of Spain, and a more recent one from abroad, canconstitute an interesting case study.

D. Malmusi et al. / Social Science & Medicine 71 (2010) 1610e1619 1611

Immigrants’ health trajectory and its explanations

Previous work on migrants’ health generally compares thehealth of international migrants to that of the native population inthe destination country. Most findings are consistent with the so-called “healthy immigrant effect”: recently arrived immigrants(usually from poor areas) have generally better health than thenative population, or at least better than expected for their socio-economic characteristics; this health advantage is frequentlyobserved to deteriorate more rapidly than among natives, despitea relative socio-economic improvement (Newbold, 2005;Ronellenfitsch & Razum, 2004; Uretsky & Mathiesen, 2007;Vissandjee, Desmeules, Cao, Abdool, & Kazanjian, 2004). Apossible explanation for this pattern, proposed in several USstudies on Hispanic immigrants (Abraído-Lanza, Chao, & Flórez,2005; Escobar, Hoyos Nervi, & Gara, 2000; Hosper, Nierkens,Nicolaou, & Stronks, 2007; Lutsey et al., 2008), suggests thatculture-based healthier lifestyles, stronger social bonds andsupport from the country of origin initially exert a protectiveeffect on immigrants’ health; but that these factors are progres-sively lost as immigrants undergo a process of “acculturation”, i.e.assimilate dominant culture and habits, and in their offspring.However, in these studies acculturation was not measureddirectly, but simply as a function of the duration or number ofgenerations of residence; also, searching for a culture-basedexplanation might divert attention from structural constraints(Viruell-Fuentes, 2007, p. 1525). In fact, there is evidence thatimmigrants also have better levels of health than the population intheir place of origin, and this is especially true for young migrantswhose primary goal is to find work; this has been attributed toa labour-related positive health selection due to the high physicaldemands of the manual jobs that most occupy (Lu, 2008; Marmot,Adelstein, & Bulusu, 1984; Redstone Akresh & Frank, 2008). Also,many studies show that less privileged social class and poorersocio-economic conditions account partly or totally for the poorerhealth outcomes of individuals from low-income countries (Hjern,Wicks, & Dalman, 2004; Levecque, Lodewyckx, & Vranken, 2007;Lindström, Sundquist, & Östergren, 2001; Rasch et al., 2008;Reijneveld, 1998; Tinghog, Hemmingsson, & Lundberg, 2007;van der Wurff et al., 2004); additional, specific mechanisms ofinequality creation have also been postulated such as discrimi-nation (Gee, Ryan, Laflamme, & Holt, 2006) and “othering” (beingtreated as ‘the other’: Viruell-Fuentes, 2007). Together, thesefindings e positive health selection, rapid decline in healthdespite a parallel socio-economic improvement, and socio-economic explanations of inequality e make sense if we attributethis accelerated health decline as the late-effect of cumulativeinequality, both in the place of origin, with poorer socio-economicenvironment in childhood and growth (Ronellenfitsch & Razum,2004), and in the place of destination, with chronic exposure towork hazards, poor living conditions, hardship and discrimina-tion, mechanisms that are well recognized as causal factors ofracial and ethnic inequalities in health (Harris et al., 2006; Krieger,2003; Nazroo, 2003). The psychobiological impacts of a forcedmigration, such as separation from friends and relatives and lossof social status, may add to these mechanisms.

Characterising migration: advantaged and disadvantaged, internaland international

Another recurrent characteristic in recent studies on immigra-tion and health is the distinction between immigrants from‘Western’, ‘high-income’ or ‘developed’ countries, and those from‘other’, ‘low-income’ or ‘developing’ countries: a distinction whichis empirically supported by data, but rarely accompanied by

theoretical discussion (Hjern et al., 2004; Hosper et al., 2007;Levecque et al., 2007; Lindström et al., 2001; Pudaric, Sundquist,& Johansson, 2003; Rasch et al., 2008). In our view, this distinc-tion makes sense, in that emigration from deprived areas is usuallya forced choice, shared by a wide sector of the population, as theresult of broad imbalances in economic and social well-beingbetween the countries of origin and destination (Castles, 2003);this often implies entry to the host society in a subordinate posi-tion, with little negotiating power, and increased vulnerability todiscrimination and exploitation. This type of migration e based onlabour movement from impoverished to advantaged and expand-ing economies e is the predominant or most increasing type inboth internal and international migration flows (Lu, 2008; UnitedNations, 2009) and is the most important for analyses of healthinequalities based on power relations. The minority of immigrantswho move between wealthy areas are more likely to do so forindividual circumstances and opportunities, and do not share thecharacteristics mentioned above. In this sense, migration isa reflection of global, geographical inequalities between countries,territories and populations.

Finally, the vast majority of studies on health inequalitiesbetween natives and immigrants have focused on internationalmigration. However, internal migrants e those who have movedwithin the same country e are at least four times as many asinternational ones (UNDP, 2009, p. 1). Most theoretical workmakes little distinction between internal and internationalmigration but often suggests that the basic underlying mecha-nisms and challenges (adaptation to a new life, economic hard-ship) apply equally to both groups (Lu, 2008). Legal restrictionsand greater geographical and cultural distance are the additionalbarriers (related both to health selection and hazards) faced byinternational migrants (Lu, 2008). Some of the studies on healthinequalities between natives and immigrants from other regionsof the same or an adjacent country described poorer health forFinns in Sweden (Pudaric et al., 2003; Westman, Martelin,Härkänen, Koskinen, & Sundquist, 2008), higher mortalityamong Irish and Scottish immigrants in England (Marmot et al.,1984; Raftery, Jones, & Rosato, 1990; Wild & McKeigue, 1997),but less hypertension and overweight than non-migrants foremployment-related internal migrants in Croatia (Kolci�c &Polasek, 2009).

Our study area, Catalonia, is a relatively wealthy region withinSpain, with its own language, customs, and national identity, withthe interesting characteristic of having experienced in the last 50years two separate waves of interregional and internationalimmigration, in both cases mainly (but not exclusively) fromdisadvantaged areas. The last decade has seen a rapid increase inforeign immigration, which increased the foreign-born populationinmunicipal continuous registers from 4% in the year 2000 to 14,8%in 2007 (Idescat, 2008). For this reason, good quality data on thehealth of this sector of the population are just becoming available.12.6% of the adult immigrant population were born in the highlydeveloped EU-15 countries, while the rest includes 41.1% fromCentral and South America (from various countries, being Ecuador,7.9%, the most common); 23.5% from Africa (mostly Morocco,17.4%); 13.2% from the rest of Europe (Romania, 6%); and 8.8% fromAsia. On the other hand, several different waves arrived from otherregions of Spain during the second half of last century, especially inthe 1950s and 1960s, when the rapidly expanding Catalan economyrequired workers and the areas of the south and west of Spainwereaffected by unemployment and poverty. At present in Cataloniathere are more people born in other Spanish regions than in Cat-alonia itself in some age cohorts, such as those aged 55e74 (Idescat,2008). This heterogeneity has been largely omitted in healthstudies. Recently, the only study of immigration and health status

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was published, as far as we are aware, that includes in a separategroup Spanish individuals born outside Catalonia (Borrell et al.,2008).

Integrating migration with other inequality mechanisms

Themigration dimension cannot be understood independently ofsocial class and gender, as all three are key intertwined mechanismsof power relations in society (Anthias, 2001). Through processessuch as exploitation, domination and discrimination, power deter-mines the extent to which an individual or group can influence theirsurrounding environment, and it entails privileges, opportunities,access to resources and health-damaging exposures (the so-calledintermediary determinants of health in the CSDH framework)throughout life. Studies describing health inequalities by both socialclass and gender are increasing, and in Catalonia women in disad-vantaged classes have the worst indicators of morbidity and self-assessed health (Borrell, Benach, & CAPS-FJ Bofill Working Group,2006). As described, several studies have simultaneously exploredsocio-economic position andmigration status (Levecque et al., 2007;Marmot et al., 1984; Reijneveld, 1998), and others socio-economicposition and race/ethnicity (see Davey Smith, 2000; Krieger, 2003).However, only a few studies have attempted to analyse inequality inthree dimensions simultaneously, usually with gender, socio-economic position and race/ethnicity (Almeida-Filho et al., 2004;Clarke, O’Malley, Johnston, & Schulenberg, 2009; Pamuk, Makuc,Heck, Reuben, & Lochner, 1998; Schulz & Mullings, 2006), but alsowith migration status (Borrell et al., 2008). A recent study in Cal-ifornia showed that body mass index among immigrants increaseswith length of residence, and the pace of increase is higher amongwomen, those with the lowest education level, and Hispanics(Sanchez-Vaznaugh, Kawachi, Subramanian, Sánchez, & Acevedo-Garcia, 2008). Pamuk et al. (1998) found that a stable racialminority such as Black people in the US had poorer self-rated healththan Whites at each level of income, whereas the Hispanic (a largeproportion of whom were immigrants) had equal or better health;and that women had worse health than men among Black andHispanic, but not among Whites.

In summary, it seems reasonable that an analysis of migration-related health inequalities requires a classification of migrationtype that takes into account the duration of residence and char-acteristics of the place of origin, i.e. its grade of economic devel-opment, and localization within or outside the receiving country.The aim of the next section is to test empirically the relevance ofthis classification and to explore the intersections of migration typewith gender and social class in the analysis of social inequalities inhealth status in Catalonia. Also, we will look at the distribution, inthe same dimensions, of socio-economic assets and privilegese theintermediary determinants e and at their contribution to therelationship between migration type and health.

Methods

Study population, sample and data collection

The population context was the 2006 non-institutionalisedpopulation of Catalonia, Spain. Two cross-sectional surveys carriedout on the same population were used: the Enquesta de Condicionsde Vida i Hàbits de la Població (which we will refer to as the LivingConditions Survey, LCS) and the Enquesta de Salut de Catalunya (theHealth Interview Survey, HIS). Both surveys are part of the regionalgovernment’s official statistical plan, and share the followingcharacteristics: a random sampling method stratified by territory,age and sex, individuals selected from the continuous populationregister (response rates for eligible subjects were 72.7% in the LCS

and 84% in the HIS; non-responders were replaced by subjects withthe same characteristics), and information collected during face-to-face interviews at home.

In this study, we restricted the analysis to the adult populationaged 25e64, in order to ensure an acceptable comparability inwork-related and economic circumstances of social classes andmigrant groups with quite different age structures. This comprisesa sample of 10,408 individuals in the HIS and 7107 in the LCS. Wemainly focused on the LCS, due to its more extensive socio-economic information, but HIS data were also used for validatingresults for the health variable.

Indicators and variables

The dependent variable was derived from a single question onself-assessment of general health. Studies of health inequalitieshave made extensive use of this simple question, which not onlyhas predictive power for mortality and morbidity, but also reflectsthe global judgement of the individual, combining evaluation ofdisease, symptoms, functional abilities and general well-being. Thisquestion has demonstrated reasonable validity in comparisonacross socio-economic positions (Bago-d’Uva, O’Donnell, & vanDoorslaer, 2008; Quesnel-Vallée, 2007). The following question(not age-comparative) was used: ‘‘Would you say your overallhealth is.” with 5 possible answers, ranging from ‘excellent’ to‘poor’ in the HIS, and ‘very good’ to ‘very poor’ in the LCS. Adichotomous outcome variable was used (Poor health ¼ less thangood; Good health¼ good or better), which has been shown to givevery similar results to ordinal methods (Manor, Matthews, & Power,2000). Poor health was reported by comparable proportions of thepopulation in the two surveys: 21.7% of LCS subjects (three possibleanswer categories below ‘good’) and 19.5% of the HIS subjects (twocategories below ‘good’).

Social class is based on the current or last occupation of thesubject, or in its absence, the occupation of the partner or house-hold reference person. The Spanish adaptation of the BritishRegistrar General classification was used (Domingo-Salvany,Regidor, Alonso, & Alvarez-Dardet, 2000):

- Class I (higher-level professionals, administrative managers,directors of large companies);

- II (medium-level professionals and directors of smallcompanies);

- III, which we further separated into III-non-manual (adminis-trative workers, clerks, safety and security workers) and III-manual (self-employed and supervisors in manualoccupations);

- IV (skilled and semi-skilled manual occupations);- and V (unskilled manual occupations).

Place of birth and duration of residence were used to define themigration type. People born in Catalonia (native Catalans) consti-tute the reference category. Migrants were first separated intointernal (people born in the rest of Spain) and international (peopleborn abroad). To further divide internal migrants according to thesocio-economic situation of their place of origin, we retrieved anestimation of the Human Development Index (HDI) by Spanishregions for the year 1981 (Herrero, Soler, & Villar, 2005), which weexpected to be more related to migration decisions in the peakperiod of the internal immigration wave than a current estimation.We grouped the 16 regions (excluding Catalonia) into thirds: anupper third of 5 regions with an HDI range of 0.857e0.846 (Cata-lonia had 0.851), a medium third of 5 regions (range 0.841e0.825)and a bottom third of 6 (0.811e0.763), which we respectivelynamed ‘Spain-wealthy’, ‘Spain-average’ and ‘Spain-poor’.

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The same division among foreign immigrants was based on theHDI elaborated by the United Nations Development Programme inthe year of the surveys (UNDP, 2006, p. 283). EU-15 countries andother countries with similar HDI were coded as ‘Foreign-advanced’and the rest as ‘Foreign-poor’. The cut-off was set at the level ofthe EU-15 country with lowest HDI, Portugal, which was 0.904that year. In its last report (2009, p. 171), UNDP has set a cut-off at0.900 above which lie countries with “very high humandevelopment”.

Immigrants from poorer countries were also classified as recentand long-term according to duration of residence. Other migrantgroups were not separated into recent and long-term categoriesbecause of the low number of recent internal immigrants andimmigrants from richer countries. Categories in previous studieswere alternatively set at 5, 10 or 20 years, with evidence ofprogressive health deteriorationwithout a preferrable cut-off point(Newbold & Danforth, 2003; Ronellenfitsch & Razum, 2004;Uretsky & Mathiesen, 2007). Therefore, and taking into accountthe sample size limitations, we separated recent and long-term onthe basis of the median year of arrival in both of our samples, 2000,i.e. 6 years before the survey date. Those who arrived before 2000were classified as long-term, and those arrived afterward, as recent.

As for the intermediary determinants of health, we focused onthree dimensions of living and working conditions. Three variableswere extracted from the LCS, and treated as dependent or adjust-ment variables depending on the analysis:

- economic and material conditions of the household: the availableitems were all dichotomised and an index was created byadding the 10 items giving the highest internal consistency(Cronbach’s alpha: 0,76). These were: savings capacity, nodifficulty in making it through the month, active financialinvestments, spending for leisure, having a hired person forhousehold labour, and availability of some items: dishwasher,vacuum cleaner, personal computer, internet connection,landline phone. The index was used as continuous variable inlogistic models, and dichotomised in descriptive analysis, withthe lowest tertile (4 or less items) coded as materialdeprivation;

- individual income: the respondent could place her/himself inone of 12 possible ranges of monthly net income. Descriptiveanalyses were restricted to workers with valid responses,dichotomising income at the lower third of the sample distri-bution: below or above 900 euros/month, coded as low income(yes/no). In logistic models, the categories “no individualincome” and “non-response or irregular income” (12.3% of thesubjects) were added;

- employment conditions: for those employed, we selected sixitems related to the concept of ‘precariousness’ (Vives et al.,2010): type of contract (permanent versus temporary or nocontract), time in current job (more or less than 5 years),unemployment during last 5 years (yes/no), unions’ represen-tation in the firm (yes/no), paid holidays (more or less than 30days) and self-perceived job insecurity. The resulting index(Cronbach’s alpha: 0,58) was dichotomised with subjects withthree or more of the “insecure” characteristics coded asprecarious employment. In logistic models, those not employedwere added as a separate category.

Statistical analysis

All analyses were carried out using the Stata 9 package, andincluded weights derived from the complex sample design. Resultswere stratified by sex.

First, we described the demographic characteristics, socio-economic conditions and health status of the six social classes andthe seven migration-based groups, separately. Due to the largedifferences in age distribution between groups, we directlydescribed the variables of interest adjusted byage. Thiswasmadebycomparing all the groups, for each dependent variable, in a logisticregression adjustedbyage. For the sake of interpretability, predictedprevalences (e.g. of poor health) at 45 years of agewere obtained foreach group using the logistic regression post-estimation function.

Thereafter, two separate approaches were used to describe andexplain migration-related inequalities in a framework of genderand social class. One consisted of describing once again socio-economic conditions and health status in a matrix of sex, socialclass and migration at a time, after simplifying both the migrationand social class classifications. The other was to compare by meansof logistic regression the health status of migration-based groups,adjusting for age; and then, adding as potential mediators,sequentially, social class, material conditions of the household,individual income, and employment status and conditions.

Results

Socio-demographic description of the samples

A total of 3510 women and 3597men composed the LCS sample,and 5086 women and 5322 men composed the HIS sample. Table 1displays the distribution of the samples by sex and social class andby sex and origin; and for each category, mean age, and age-adjusted socio-economic situation and health status.

Social class IV was the largest group in both sexes and bothsurveys. In both surveys, women inmanual classes (III-m to V) weregenerally older than in non-manual classes, whereas no suchpattern was observed in men. With regard to origin, 64.6% of theLCS subjects were Catalans, 22.8% were born in the rest of Spain and12.6% were born abroad. Corresponding figures in the HIS were70%, 20.8% and 9.2%. In both surveys, the majority of internalimmigrants were from the poorest regions group, and the majorityof foreign immigrants were from the poor countries group. Internalimmigrants were older than the native Catalans, with ageincreasing from the richest to the poorest regions group, whereasrecent immigrants from poor countries were younger.

Social class and gender inequalities in socio-economic conditionsand health

All socio-economic indicators in the LCS, as well as the healthindicator in both surveys, showed increasing levels of deprivationwith decreasing social classes (Table 1). In all social classes andmigration groups, women were more likely than men to reportpoor health and to have a low incomewhen employed.Women alsohad worse employment conditions than men in some groups:manual social classes, immigrants from average and poorestregions of Spain, and recent immigrants from poor countries.‘Spain-average’ and ‘Spain-poor’ were also the only groups wherewomen experienced greater material/financial deprivation.

Migration-related inequalities in socio-economic conditions andhealth

People from both the wealthiest and average regions of Spainhad similar or better socio-economic indicators compared to thoseof the native population, with the exception of women from ‘Spain-average’ regions, who had slightly poorer indicators. Health levelsin these groups were also similar to those of the reference

Table 1Socio-economic conditions and health status according to social class and migration type, stratified by sex, in the two surveys.

Living Conditions Survey Health Interview Survey

N Age mean Materialdeprivation %b

Lowincome %c,b

Precariousemployment %c,b

Poorhealth %b

N Age mean Poorhealth %b

Social classa

Women I 319 38.6 7.4 7.9 15.8 11.8 467 39.1 12.3II 425 40.2 15.8 20.2 17.5 21.2 522 39.9 11.8III-nm 751 37.8 17.1 30.5 19.6 21.3 1010 40.1 17.7III-m 187 43.0 33.8 41.3 41.4 29.2 332 45.6 23.5IV 1316 41.6 49.4 67.2 40.1 32.2 2054 43.7 27.7V 492 44.0 64.1 81.8 62.0 41.6 636 46.5 40.2

Men I 389 40.7 3.8 3.0 13.2 9.3 550 41.6 7.8II 451 39.4 14.1 7.4 19.8 14.2 479 40.8 10.9III-nm 500 40.5 17.4 8.7 17.0 14.1 661 42.3 11.1III-m 335 43.6 28.8 12.4 25.6 16.8 655 44.1 14.3IV 1651 40.4 45.8 17.4 30.5 26.4 2468 42.0 19.3V 263 38.4 69.6 35.4 42.4 26.2 462 40.9 20.1

OriginWomen Natives 2254 38.7 27.2 39.0 26.2 23.4 3562 40.5 19.9

Spain-wealthy 61 42.4 29.1 22.5 15.0 25.6 56 44.2 42.7Spain-average 168 46.0 33.1 34.7 35.0 29.4 210 50.4 23.2Spain-poor 596 49.0 50.2 63.4 37.9 40.4 819 50.8 33.9Foreign-advanced 53 41.3 18.8 36.0 28.5 18.7 81 39.8 16.8Foreign-poor, less recent 159 38.8 69.0 57.3 51.6 27.4 153 39.7 39.8Foreign-poor, recent 219 33.6 70.4 77.1 82.9 33.4 205 35.6 31.7

Men Natives 2333 38.3 25.0 12.5 26.7 18.7 3728 39.8 14.2Spain-wealthy 48 43.6 35.4 3.7 13.1 13.1 62 43.9 10.0Spain-average 152 46.9 23.9 4.2 12.4 18.1 213 48.7 13.6Spain-poor 597 49.2 39.1 11.9 23.7 24.7 801 51.4 22.0Foreign-advanced 46 37.9 24.0 14.9 46.0 16.9 77 38.7 12.5Foreign-poor, less recent 182 37.3 71.0 25.6 52.5 23.5 186 40.9 18.4Foreign-poor, recent 239 33.1 79.0 38.8 67.0 20.9 255 35.0 8.1

a Social class could not be coded in 20 women and 8 men in the LCS, and in 65 women and 47 men in the HIS.b Predicted probabilities at age 45 obtained from logistic regression models.c Restricted to subjects in paid job.

Table 2

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population, except for a high proportion of poor health reportedamong the 56 women from rich regions in the HIS sample.

‘Spain-poor’ women were markedly more disadvantaged thannatives for all socio-economic and health indicators. Men also hadpoorer health in both surveys, and a relative excess of deprivation,whereas they were similar to the reference population in terms ofincome and employment conditions.

‘Foreign-advanced’ immigrants had similar, if not better, socio-economic and health indicators than the native population.Conversely, ‘foreign-poor’ immigrants had by far the worst situa-tion in all socio-economic indicators, especially in the more recentgroup. Their health situation differed by gender: women reportedworse health than natives, and the pattern according to duration ofresidence was opposite in the two surveys. Men’s prevalence ofpoor health was more similar to natives’ levels, and even lower inrecent immigrants in the HIS sample.

Sampledistribution in thematrixof sex/social class/migration type. LivingConditionsSurvey.

Non-manual III-m IV Unskilled

N Column % N Column % N Column %

WomenNatives 1192 79.7 880 58.5 171 34.8Spain-rich 108 7.2 88 5.9 33 6.7Spain-poor 102 6.8 342 22.8 146 29.7Foreign-advanced 33 2.2 17 1.1 3 0.6Foreign-poor 60 4.0 176 11.7 139 28.3

MenNatives 1025 76.5 1186 59.7 117 44.5Spain-rich 98 7.3 94 4.7 6 2.3Spain-poor 141 10.5 406 20.4 50 19.0Foreign-advanced 21 1.6 24 1.2 1 0.4Foreign-poor 55 4.1 276 13.9 89 33.8

Socio-economic and health inequalities in a matrix of sex, socialclass and migration type

The next step consisted of the simplification of social classgrouping and migration type classification, taking into account thedifferences and similarities described, as well as the sample sizelimitations. Because of the low proportion of immigrant subjectsin the non-manual social classes (I, II and III-nm) and the conse-quent difficulty in making the groups big enough, these weregrouped into one. Class III-m was also small and was thereforegrouped with class IV, to which it was more similar than theaggregated non-manual classes. Finally class V, which was clearlythe least advantaged in most indicators, especially in women, wasmaintained separate. Migration type classification was simplified

first by combining immigrants from the wealthiest and interme-diate Spanish regions, which were two small and fairly similargroups, into ‘Spain-rich’; and second, ‘foreign-poor’ immigrantswere considered together regardless of duration of residence. Thesample distribution in the resulting groups is shown in Table 2,and socio-economic and health indicators are displayed in Fig. 1.Note that figures for immigrants from advanced countries wereultimately removed, as they comprised only 1e40 subjects in eachsubgroup.

Fig. 1 shows that the social class gradient and the gender gap insocio-economic conditions and health generally persist within boththe native population and the different immigrant groups.Conversely, differences between migrant types are more inconsis-tent, depending on social class, gender and the measured outcome.

Fig. 1. Socio-economic conditions and health status according to the matrix of sex/social class/migration type.Predicted probabilities at age 45 obtained from logistic regression models. In less than good health, the two columns of the same colour represent data from the HIS and the LCS forthe same group. Estimations of low income and precarious employment are restricted to subjects in paid job.

D. Malmusi et al. / Social Science & Medicine 71 (2010) 1610e1619 1615

Health inequalities affecting ‘Spain-poor’ immigrants persist ineach class among women, but disappear among men, except in theIIIm-IV group. In the case of deprivation, inequality persists withineach social class grouping and gender. The gap in income betweennative and ‘poor Spain’women persists in manual classes only, andthe gap in employment conditions disappears.

‘Foreign-poor’ men and women have still the highest levels ofmaterial deprivation and precariousness within each class.‘Foreign-poor’ men continue to have an equal or better healthstatus than natives in their class (clearly better in class V),whereas women have worse health among the unskilled groupand inconsistent results between the two surveys in other socialclasses.

In the caseof ‘Spain-rich’ immigrants, stratificationbysocial classuncovers some relative disadvantage for manual women, namelya higher prevalence ofmaterial deprivation and poor health. Amongmen the sample size is inadequate to interpret findings.

Migration-related health inequalities: the role of socio-economicposition and conditions

Table 3 shows the results of the alternative approach, that isthe analysis of migration-related health inequalities stratified bysex, and adjusted for social class and indicators of living andworking conditions, considered as potential mediators. Fig. 2illustrates how the risk (measured with odds ratios) of poorhealth of certain migrant groups is attenuated by the intro-duction of these variables in the models.

Models adjusted only by age show a significant excess risk ofpoor health for ‘Spain-poor’ migrants among male (OR 1.48) andespecially among female (OR 2.11), compared to the Catalan-borngroup. The excess risk among men is clearly reduced and no longersignificant when adjusted for social class and the material andeconomic assets index. Among women, the risk is partially reducedbut still significant after these adjustments.

Table 3Odds ratio of fair/poor health according to migration type, adjusted by potential mediators (logistic regression models). LCS survey.

Sex and origin N Model 1 Model 2 Model 3 Model 4 Model 5

Adjusted by age þSocial class þMaterial assets þIncome þJob

OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI

WomenNatives 2254 1 1 1 1 1Spain-rich 229 1.27 (0.93e1.72) 1.25 (0.91e1.71) 1.21 (0.87e1.67) 1.23 (0.89e1.70) 1.17 (0.85e1.62)Spain-poor 596 2.11*** (1.73e2.59) 1.67*** (1.35e2.06) 1.49*** (1.20e1.86) 1.50*** (1.21e1.86) 1.48*** (1.19e1.85)Foreign-advanced 53 0.76 (0.36e1.58) 0.84 (0.40e1.76) 0.90 (0.43e1.89) 0.89 (0.42e1.88) 0.85 (0.40e1.79)Foreign-poor, less recent 159 1.25 (0.85e1.85) 0.90 (0.60e1.34) 0.64* (0.42e0.98) 0.65* (0.43e0.99) 0.67 (0.44e1.02)Foreign-poor, recent 219 1.70*** (1.19e2.42) 1.19 (0.82e1.73) 0.84 (0.57e1.23) 0.83 (0.56e1.22) 0.88 (0.60e1.30)MenNatives 2333 1 1 1 1 1Spain-rich 200 0.91 (0.62e1.32) 0.88 (0.60e1.30) 0.83 (0.56e1.23) 0.89 (0.59e1.33) 0.84 (0.56e1.26)Spain-poor 597 1.48*** (1.19e1.84) 1.20 (0.96e1.51) 1.07 (0.85e1.35) 1.15 (0.91e1.46) 1.17 (0.92e1.48)Foreign-advanced 46 0.89 (0.38e2.08) 0.89 (0.37e2.10) 0.88 (0.37e2.10) 0.87 (0.36e2.07) 0.85 (0.35e2.03)Foreign-poor, less recent 182 1.30 (0.86e1.96) 1.00 (0.66e1.52) 0.60* (0.39e0.93) 0.59* (0.38e0.93) 0.60* (0.38e0.95)Foreign-poor, recent 239 1.10 (0.73e1.67) 0.81 (0.53e1.24) 0.49** (0.32e0.76) 0.44*** (0.28e0.68) 0.45** (0.29e0.71)

*p < 0,05. **p < 0,01. ***p < 0.001.Model 1: Adjusted by age (5-years categories). Model 2: Model 1þ social class (I, II, III-nm, III-m, IV, V, not coded). Model 3: Model 2þmaterial index (linear). Model 4: Model3þ individual monthly income (>900V,<900V, no income, irregular or non-response). Model 5: Model 4þ employment status and conditions (Secure job, precarious job, notemployed).

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Immigrant men and women from advanced countries, as well as‘Spain-rich’ men, showed a non-significant tendency to lower riskof poor health. Only ‘Spain-rich’ women had a slight, non-signifi-cant, excess risk of poor health (OR 1.27), hardly modified by socio-economic adjustments.

The ‘foreign-poor’were disaggregated into more and less recentmigrants. More recent immigrant women had a significantly higherrisk of poor health (OR 1.70), which was reversed (OR 0.84) afteradjustment for social class and economic assets. All other ‘foreign-poor’ groups (less recent immigrant women, more and less recentimmigrant men) had a slight, non-significant, excess risk of poorhealth, which was significantly reversed by socio-economicadjustments.

Discussion

This study analyses inequalities in socio-economic determinantsand self-assessed health status according to gender, social class andmigration type, defined on the base of sociological theory, historical

Fig. 2. Risk of fair/poor health according to migration type, adjusted by potential mediatorSource: Living Conditions Survey.Odds Ratio (OR) and 95% confidence intervals (CI) obtained from logistic regression modelModel 1: Adjusted by age (5-years categories). Model 2: Model 1 þ social class (I, II, III-nmmodified the associations.

context and literature review. As discussed below, the findingsshow that this migration type classification helps to detect andunderstand migration-related health inequalities, which:

- affect both internal and international immigrants, but aremainly limited to immigrants from poor areas, as a reflection ofglobal inequities between countries and regions;

- seem to affect women more than men;- are largely consistent with immigrants’ socio-economicdeprivation compared with natives. The ‘healthy immigranteffect’ might explain the relative health advantage of recentforeign immigrants and especially men.

In addition, the magnitude and strength of inequalities by socialclass and gender stand out independently of birthplace. Social classand gender are fundamental drivers of living and working condi-tions and health status, not only among natives but also within allimmigrant groups. Also, social class and gender may act as medi-ators or effect modifiers of some of the associations between

s. Left: women, right: men.

s., III-m, IV, V). Model 3: Model 2 þ material index (linear). Further adjustments hardly

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migration type and health status. Therefore, in Catalonia, as alsodemonstrated in research elsewhere, studies on migration andhealth must take these two dimensions of inequality into account.

Health inequalities by migration type, and the contribution of socio-economic factors

Fundamental differences were observed as a function of thelevel of economic development of the place of origin, among bothinternal and international migrants. Immigrants from affluentregions and countries were not dissimilar to the native Catalanpopulation in terms of socio-economic characteristics and healthoutcomes. Inequalities were only evident for those who hadmigrated from clearly poorer areas. This result is in line withstudies from other countries (such as Pudaric et al., 2003), and withthe hypothesis we made of two clearly distinct types of migration,one which is assumed to be more likely to be the result of freechoices or individual opportunities, and another which we inter-pret as part of large population movements resulting from markedeconomic inequalities between territories. These geographicalinequities are reproduced by the lower social position that theseimmigrants attain in the host society.

Thus, it is not unexpected that a large proportion of migration-related health inequalities are “explained” after adjustment forsocial class and the material and financial situation, as observed inother studies cited above (e.g. Reijneveld, 1998). We expected thatthe cumulative ‘embodiment’ of more adverse conditions both pre-(early life) and post-migration (living and working conditions inthe first periods in the host country) would result in excess risk ofpoor health beyond the present social and economic situation,particularly for a long-term immigrant population, such as thatfrom within Spain. This hypothesis was supported to some extentfor women, but not for men. It is likely that these cumulative effectsare still partly counterbalanced by health-related selectionprocesses, which have influenced the likelihood of migration aswell as of returning. Also, the capacity of the material assets indexto add further explanatory power to health differences than socialclass alone should be noted. Davey Smith (2000) and Nazroo (2003)have pointed out the insufficiency of a single measure of socio-economic position to control for the social disadvantage experi-enced by ethnic minorities in the US and UK. In this case especially,the assets index might have acted as marker of accumulatedwealth, as shown by the fact that, while the gap in income andcurrent employment conditions between natives and ‘poor Spain’immigrants was eliminated within the same social class, the gap indeprivation persisted.

Another important finding is that, despite the focus in mostother studies on international migrants, internal migration may bealso very relevant to a health inequalities analysis, and that in thespecific case studied, due to differences in migrationwave period, itmay also be indicative of future developments in foreign immi-grants’ health. Foreign immigrants from poor countries reportedthe worst socio-economic conditions, but relatively good health,a pattern attributable to the “healthy immigrant effect” that wasexpected for the most recent immigrants only but also partlyextended to those having lived in Spain for longer. In our analysis,‘less recent’ foreign immigrants had a median length of stay inCatalonia (15 years) which was far shorter than for internalimmigrants (37 years). In the long term, foreign migrants’ healthmay deteriorate to a level similar to (or possibly worse than)internal migrants, since as already pointed out (Lu, 2008), inter-national migrants face the same social and economic challenges asinternal migrants, and additional legal and cultural barriers (Solé,2000).

The modifying effect of social class and gender on migration-relatedinequalities

In some cases, inequalities between natives and migrants frompoor areas were wider in, or limited to, manual social classes andespecially women. If one looks at health data in Fig. 1, among theunskilled manual group, male and female patterns vary: amongwomen, all immigrant groups (from both poor and rich regions ofSpain, and from poor countries) showed excess risk of poor health,whereas among men, immigrant groups had better health thannatives in the same social class. Possible explanations could includethe following:

- family migration is usually in favour of man’s employment(Boyle, Cooke, Halfacree, & Smith, 2001). This implies botha greater health-related selection and consequent “healthyimmigrant effect” among men, and a detrimental effect onwoman’s health;

- wider gender inequalities in immigrants’ societies of origin dueto strong patriarchal systems, where the “traditional”(submissive) role of women is enhanced. This was the case inSpain, particularly outside Catalonia, under Franco’s dictator-ship (Borrell et al., 2008), and is also likely in most of the lesseconomically advanced countries, as shown by indicators suchas the Gender Empowerment Measure (UNDP, 2006, p. 367);

- as indicatedby Lohan (2007), patriarchymaybe reinforced in lessfavoured social classes where men may appeal to hierarchies ofmasculinity rather than hierarchies of social class, in order toregain social status. On theother side,manual immigrantwomenare exposed to the cumulative burden of socio-economic andgender-related disadvantages and disempowerments, togetherwith their experience of marginalisation (Lynam, 2004).

Limitations

One of this study’s innovations lies in the simultaneousdescription of three complex dimensions of inequality, althoughthis was made difficult by insufficient sample size, particularly insome subgroups that had to be excluded or aggregated in someanalyses. Also, due to sample size, we ruled out further splitting“foreign-poor” immigrants by country or continent of origin. Astudy on self-assessed health of foreigners in Spain found somevariability between continents, but did not stratify by sex and socialclass (Hernández-Quevedo & Jiménez-Rubio, 2009). While waitingfor data that make possible this analysis, wemay speculate that thephenomena described in our study are common to all immigrantpopulations from poor backgrounds e as the case of the rest ofSpain demonstrates e more than a specificity of some peculiar“ethnic minorities”. The representativeness of the foreign pop-ulation is another issue. Since 2000, foreign immigrants can beregistered in the municipal population registries (the base for thesurvey) regardless of whether they have residence authorization,and this is a prerequisite to freely register and access to publicservices, including healthcare. However, there is some evidence ofunder-representation from the lower proportion of foreign immi-grants in the surveys than in population data. This might especiallyconcern those more recently arrived and/or with residentialinstability: groups probably affected by higher deprivation, but alsoenjoying the “healthy immigrant effect”.

Language and cultural differences have been raised as possiblesources of bias in self-assessed health comparison between ethnicgroups, or between natives and immigrants. This should not applyto the larger immigrant group in our study, the one from withinSpain. In respect of foreign immigrants, we lack data in our context;

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nevertheless, such a bias is not evident in studies on Asian immi-grants in the US (Erosheva, Walton & Takeuchi, 2007), ethnicminorities in the UK (Chandola & Jenkinson, 2000), or in a Dutchstudy, where the poorer health rating of Turkish and Moroccanswas consistent with their greater global burden of diseases and useof healthcare (Agyemang, Denktas, Bruijnzeels, & Foets, 2006).Conversely, self-assessed health may be considered a sensitive andprecocious marker of health deterioration among immigrants:health selection is stronger for chronic and severe conditions, andseveral studies found relatively better health outcomes for immi-grants on indicators such as mortality, chronic conditions orimpaired activity than with self-assessed health (Leung, Luo, So, &Quan, 2007; Lu, 2008; Puigpinós, 2008; Vissandjee et al., 2004).With the HIS data too, we found that the foreign-poor performedrelatively better on an indicator of chronic limitation than on self-assessed health, and equal or worse on mental health measuredwith the GHQ-12 (data not shown). In summary, the use of self-assessed health to compare natives’ and immigrants’ health seemsreasonable, even though adding other, not necessarily more valid(Quesnel-Vallée, 2007), health indicators to the analysis could helpto give a more complete picture.

In conclusion, the present study shows how disadvantagedmigration emerges as a health inequality mechanism, in addition toand interacting with gender and social class, and especially evidentin women. These inequalities are in line with existing geographicalinequities that affect some (not all) immigrant groups. Evidence isgiven from a large immigrant group such as the one from withinSpain, with long duration of residence, so lessening the influence ofthe healthy immigrant effect, and quite similar cultural background,so making acculturation an unlikely cause. Future research andpolicies on thehealthof new immigrants cannot ignore class, genderand territorial inequality and the health trajectory perspective, andshould make surveillance of socio-economic conditions asa predictor of future health and a target of policies for health equity.

Acknowledgement

This work was undertaken as part of Davide Malmusi’s doctoraldissertation at the Universitat Pompeu Fabra. Davide Malmusi waspartially supported by the IV grant for young epidemiologists“Enrique Nájera” awarded by the Sociedad Española de Epi-demiología and sponsored by the Escuela Nacional de Sanidad.

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