HEDG Workng Paper 08/22 A comparson of the health status and health care utlsaton patterns between foregners and the natonal populaton n Span: new evdence from the Spansh Natonal Health Survey C Hernández Quevedo Dolores Jménez Rubo September 2008 ISSN 1751-1976 http://www.york.ac.uk/res/herc/research/hedg/wp.htm
A comparson of the health status and health care utlsaton patterns between foregners and the natonal populaton n Span: new evdence from the Spansh Natonal Health Survey September 2008 C Hernández Quevedo 1, Dolores Jménez Rubo 2 1 European Observatory of Health Systems and Polces, LSE Health, UK 2 Departamento de Economía Aplcada, Unversty of Granada, Span Abstract The reducton of nequaltes n health and n the access to health servces s one of the man objectves n any health care system. Varous studes have analysed the exstence of nequaltes n health and n the use of health care for the Spansh populaton. However, the emprcal evdence for the mmgrant collectve on ths ssue s as yet nsuffcent. Ths workng paper ams to provde evdence on nequaltes n health and n the access to health servces for the mmgrant populaton lvng n Span, relatve to that of the autochthonous populaton, by usng the 2003 and 2006 Spansh Natonal Health Survey. After usng a pooled ordered probt for a measure of self-assessed health and pooled probt models for several utlsaton varables, our results show that there are dfferent patterns n health status and utlsaton of health care between natonals and mmgrants n Span. Immgrants report better levels of health status than Spanards, although they face barrers of entry to health care servces. Health polces should focus on reducng legal, cultural and admnstratve barrers to access health servces. JEL codes: I12, C21 The data used for ths study has been provded by the Spansh Natonal Insttute of Statstcs (INE). Data collectors do not bear any responsblty for the analyss or nterpretatons presented here. Authors are grateful to Davd Epsten, Plar García, Alexandrna Stoyanova, Ángela Blanco and partcpants at the XXVIII Jornadas de Economía de la Salud (Salamanca, May 2008) and the 7 th European Conference on Health Economcs (Rome, July 2008), for ther comments on an earler verson of ths work. * Correspondng author: Dolores Jménez Rubo. Departamento de Economía Aplcada, Facultad de Cencas Económcas y Empresarales, Campus Unverstaro de Cartuja, 18071 Granada. E-mal: dolores@ugr.es 1
Keywords: health care utlsaton, health lmtatons, nequaltes, mmgrants, Span 1 Introducton Immgraton s a phenomenon relatvely new, but wth a growng mportance n Span. Consderng the 1998-2007-tme span, the proporton of foregners regstered n the census as a proporton of the total populaton has ncreased fve-fold (see Fgure 1.A), becomng the man recevng country of mmgraton flows n Europe 2. Immgrants tend to concentrate n Balears, Comundad Valencana and Murca, followed by Madrd and Cataluña. Extremadura and Asturas are the Autonomous Communtes (ACs) where mmgrants represent the lowest proporton of the populaton (see Fgure 2.A). By natonalty, Latn Amercans are the most numerous, followed by ctzens from the European Unon and Afrca (see Fgures 3.A and 4.A). The mportance of the phenomenon of mmgraton for the health servces s manfested n the approval of the Law 4/2000 of 11th of January about rghts and lbertes of foregners n Span, accordng to whch all ndvduals, regardless of ther natonalty, should be enttled to use health care servces wth the same condtons as Spansh ctzens. The only requste for mmgrants, whether legally accredted or not, to be able to access health care servces n the same way as Spanards s to be regstered n the local populaton census. Immgrants who are not regstered n the populaton census are only covered by emergency servces. Chldren and pregnant women have full coverage rrespectve of ther legal and admnstratve stuaton (Durán, Lara and van Waveren, 2006). In addton, the government has recently approved the Ctzenshp and Integraton Strategc Plan 2007-2010 that targets the whole populaton, and ntends to promote socal coheson through polces based on equalty of opportunty and equalty of rghts and dutes (Mladovsky, 2007). There are also Regonal Immgraton Plans n most of the Autonomous Communtes whch nclude as a prorty the reducton of nequaltes n health and n the access to health 2 Data accessed on July 2008 from the Spansh Natonal Statstcs Insttute ( Foregn populaton by natonalty, autonomous communtes, age and sex ) and Eurostat ( Net mgrant flows n Europe ). Avalable onlne at http://www.ne.es/jax/menu.do?type=pcaxs&path=/t20/e245/p05//a2007&fle=pcaxs and http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=table&nt=1&plugn=0&language=en&pcode =caa14608 2
servces. However, these polces have been formulated wthout any sound scentfc evdence that corroborates the exstence of such nequaltes. Antecedents Hgh scale mmgraton started some decades ago n the US, Canada and n many Member States n the European Unon. Ther experence as mmgraton recpent countres has allowed them to specfy the health care needs of ther mmgrant populaton and to collect representatve data about ths populaton group n ther natonal health surveys. As a consequence, there s a great deal of lterature on ths ssue for countres such as Canada and England (e.g.gravelle, Morrs and Sutton, 2006; McDonald and Kennedy, 2004; Smaje and Le Grand, 1995). In Span, however, mmgraton and specally work-related mmgraton s a relatvely new phenomenon and therefore, the studes about nequaltes n health and equty n the utlzaton of the Spansh health care system for the mmgrant populaton are as yet few. For the specfc case of Canada, McDonald and Kennedy (2004) use multple crosssectons of the Populaton Natonal Health Survey and the Canadan Communty Health Survey n order to corroborate the phenomenon known as the healthy mmgrant effect, accordng to whch the health status of recent mmgrants s superor to that of the natve populaton of the mmgrant recpent countres. Ther results pont to the exstence of the healthy mmgrant effect for chronc condtons, but not for self-assessed health. In addton, the authors show that the probablty of reportng a chronc condton by the mmgrant populaton does not seem to be a consequence of a greater use of health servces wth the number of years snce mgraton. For the Spansh case, several studes have explored the exstence of nequaltes n health and nequty n the access to health care servces for the Spansh populaton (e.g., Abásolo and Mannng 2001; Clavero and González 2005; García and López 2004; 2007). However, only a few studes have analysed nequaltes n health and health servce utlsaton of the mmgrant populaton lvng n Span. Recently, Rvera et al (2008) explot the Spansh Natonal Health Survey (SNHS), the European Survey on Income and Lvng Condtons (EU-SILC) and the European 3
Communty and Health Survey (ECHP) wth the am of comparng the patterns of health status and utlsaton of health care servces for the natonal and foregn populaton. The authors conclude that the epdemologcal profle and the utlsaton of health servces of Spanards and foregners do not dffer substantally. Jménez Rubo (2008) employs the 2003 Spansh Natonal Health Survey to explore whether non-spanards, for the same level of need, use health care servces at the same rate as natonal ctzens. For vsts to hosptal emergency servces, the study corroborates prevous results for Catalona whch suggest that emergency care s an mportant mechansm of access to health servces by mmgrants. The results of the study also show that the mmgrant populaton have a hgher probablty of beng hosptalsed, and a lower probablty of vstng a specalst doctor, than the Spansh populaton wth the same health and socoeconomc characterstcs. On the other hand, a study by Torres-Cantero et al (2007) analyses the utlsaton level by llegal mmgrants n Span as a consequence of the law ntroduced n 2002 that allowed llegal mmgrants free access to health servces n smlar terms than the legal mgrants or the Spansh populaton. The study concludes that there are no mportant dfferences n use of health servces between legal and llegal mmgrants. Fnally, a natonal level study based on the 2003 Spansh Natonal Health Survey (Carrasco- Garrdo et al, 2007), explores the health status, lfe style and utlzaton of health care servces for the mmgrant populaton n Span. Ther fndngs show that, as compared to the Spansh populaton, mmgrants present better parameters related to lfestyle than the ones of the natonal populaton, such as a lower consumpton of alcohol and tobacco. As for the use of health care servces, mmgrants report hgh rates of hosptalsaton. However, the study does not fnd evdence for an excessve or napproprate use of health servces. Regardng regonal level studes, García Gómez (2007) explores the dfferences n the access to health care servces and the health status between mmgrants and the Catalan populaton usng data from the 2006 Catalan Health Survey. For self-assessed health, the fndngs show that mmgrants are less lkely to report bad physcal health status, but are more lkely to report bad mental health levels. Wth respect to the use of health servces, the results of ths study suggest that mmgrants have a lower probablty of vstng a 4
specalst doctor and a hgher probablty of vstng hosptal emergency servces than Spansh-born ndvduals, other factors equal. Snce the dfferences n utlsaton are reduced wth the mmgrants number of years of resdence n Catalona, the study concludes that the dfferent utlsaton patterns between the natve and the mmgrant populaton mght be due to a lmted knowledge of the functonng of the Spansh health care system by mmgrants. Usng data from hosptal admssons at Hosptal del Mar n Barcelona, Cots et al. (2002) fnd that mmgrants have dfferent needs than the Spansh populaton gven ther dfferent age structure and ther hgher fertlty rate. The analyss also shows that low ncome mmgrants tend to access health care servces prmarly through the emergency department. In a more recent study, Cots et al. (2007) analysed hosptal emergency vsts at Hosptal del Mar n Barcelona by the mmgrant and Spanard populaton. They fnd that mmgrants tend to use hosptal emergency servces as a substtute for other health care servces. The emprcal lterature presented n ths secton has two mportant lmtatons. On the one hand, the studes usng natonal level data are constraned by the small sample szes for the mmgrant populaton. On the other hand, the studes wth suffcently large sample szes are based on data for Catalona. Ths paper ams at contrbutng to the research lterature about the health status and health care utlsaton of mmgrants n Span usng recently avalable naton-wde data. The data used corresponds to the 2003 and 2006 waves of the Spansh Natonal Health Survey that n 2003 started collectng health-related nformaton about foregners lvng n Span. Poolng the 2003 and 2006 waves of the SNHS wll allow us to maxmse the usable sample sze for the mmgrant populaton n Span. In partcular, the objectve of ths paper s to use regresson estmaton technques to explore how the patterns of health and health care utlsaton compare between Spanards and non Spanards. In addton, we compute ncome related measures of nequalty n health and nequty n health care use for our samples of autochthonous and mmgrant populatons to analyse whether there are dfferences n health or health care utlsaton that can be attrbuted to dfferences n ncome levels n the two groups. The next secton provdes an overvew of the methodology that we have followed n the estmatons, whle secton 3 presents the data used. Secton 4 dscusses the results, dstngushng between the health and health care use specfcatons. Fnally, secton 5 concludes. 5
2 Methods 2.1 Emprcal specfcaton For the purpose of our study, we apply dfferent estmaton technques to our data, makng a dstncton between the self-reported health specfcaton and the model specfcaton for the utlsaton varables. Specfcaton for modellng self-assessed health For self-assessed health, we run an ordered probt model to explan a four-category measure of health status. Probt models assume normalty and present a symmetrc functon, assumng that the error term s dstrbuted normally, wth zero mean and varance equal to one. We consder here a pooled specfcaton for both years 2003 and 2006, applyng the standard cross-secton estmator. The log-lkelhood used for the pooled model assumes that the observatons are ndependent across waves and uses the product of ther margnal dstrbutons (Jones, 2000). Our ordered probt specfcaton presents a measurement model, n whch a latent varable (h * ) s mapped to an observed varable (h ), through the thresholds τ s. The structural model, s gven by the followng expresson: h * = α + β ln nc + γ k xk, k + ε, wth = 1,..., N (1) * In (5), h represents a latent varable representaton of the observed level of health lmtatons; lnnc s the logarthm of the equvalsed net household ncome, x k, s a vector of socoeconomc and demographc varables and ε reflects the ndvdual error term. In our data, the latent outcome h * s not observed. Instead, we observe a categorcal measure of health n whch the latent ndcator falls (h ). The mechansm of observaton (measurement model) s the followng: 6
h * 1, f h < τ 1 * 2, f τ 1 h < τ 2 = * 3, f τ 2 h < τ 3 * 4, f τ 3 h < (2) Specfcaton for modellng health care use Assumng a lnear model, the utlsaton of health servces can be explored by regressng medcal care use (y ) on ncome, a vector of k medcal need ndcator varables (x k ), and a set of p non-need varables (z p ) usng the equaton: (3) y = α + β*ln( nc ) + γ x + δ z + ε k k, p p, k p Need varables are those that ought to affect the use of health care, whereas non-need varables are those that ought not to affect current health care use. In spte of the substantal debate on the meanng of need and the value judgements nvolved n dstngushng between need and non-need varables (Gravelle, Morrs, and Sutton, 2006), we follow the standard approach n the emprcal lterature and use morbdty varables (proxed by health status and health lmtatons) as need ndcators, and varables such as ncome, educaton, AC of resdence (as a proxy for avalablty of care), tenure of prvate nsurance, and natonalty, as non-need ndcators. Because health care use varables are dscrete and non-normally dstrbuted, lnear (OLS) estmaton methods are n general not approprate for the regresson specfed n equaton (3), and non-lnear methods are requred n order to obtan effcent estmatons and approprate predctons (Wooldrdge, 2006). For modellng health care utlsaton we run pooled probt regressons collapsng 2003 and 2006 SNHS data. Assumng that y n equaton (3) above s a latent varable (y*), the probt model can be wrtten as: 7
y * 1f y > 0 = 0, otherwse (4) We estmated the pooled probt regresson models for our health and health care use varables usng STATA 9.0. Indvdual weghts (provded by the SNHS) were used n all computatons n order to make the results representatve for the Spansh populaton. Also, a year dummy for 2006 was ncluded n the estmatons to take nto account the possblty that the 2003 and 2006 samples are ndependent. 2.2 Socoeconomc nequaltes n health and nequtes n the use of health care: the Concentraton Index Methods based on concentraton curves and concentraton ndces have been extensvely used for measurng nequaltes and nequtes (Wagstaff and van Doorslaer, 2000). The health concentraton curve (CC) and concentraton ndex (CI) provde measures of relatve ncome-related health nequalty (Wagstaff, Van Doorslaer and Pac, 1989). Wagstaff, Pac and van Doorslaer (1991) have revewed and compared the propertes of the concentraton curves and ndces wth alternatve measures of health nequalty. They argue that the man advantages are that: they capture the socoeconomc dmenson of health nequaltes; they use nformaton from the whole ncome dstrbuton rather than just the extremes; that they gve the possblty of vsual representaton through the concentraton curve, and fnally, they allow checks of domnance relatonshps. The concentraton ndex (CI) s derved from the concentraton curve (CC). Ths s llustrated n Fgure 1 for a measure of ll-health. The sample of nterest s ranked by socoeconomc status. So, f ncome s used as the relevant rankng varable, the horzontal axs begns wth the poorest ndvdual and progresses through the ncome dstrbuton up to the rchest ndvdual. Ths relatve ncome rank s then plotted aganst the cumulatve proporton of llness on the vertcal axs. Ths assumes that a cardnal measure of llness s avalable, that can be compared and aggregated across ndvduals. The 45-degree lne shows the lne of perfect equalty, along whch the populaton shares of llness are proportonal to ncome, such that the poorest 20% of ndvduals experence 20% of the llness n the populaton. Pro-poor nequalty s llustrated by the concave curve n the fgure whch corresponds to the concentraton curve. In the example shown, the poorest 20% of ncome earners experence more than 20% of llnesses. The sze of nequalty can 8
be summarsed by the health concentraton ndex, whch s gven by twce the area between the concentraton curve and the 45-degree lne. Fgure 1: Concentraton curve for ll-health Cum. Prop. ll-health 0.2.4.6.8 1 0.2.4.6.8 1 Cum. Prop. sample ranked by ncome There are varous ways of expressng the CI algebracally. The one that s most convenent for our purposes s: t ( h R ) 2 = (5) µ t CI cov t, Ths shows that the value of the concentraton ndex s equal to the covarance between ndvdual health (h ) and the ndvdual s relatve rank (R ), scaled by the mean of health n the populaton (µ). Then the whole expresson s multpled by 2, to ensure the concentraton ndex ranges between -1 and +1. Equaton (5) ndcates that the CI s a measure of the degree of assocaton between an ndvdual s level of health and ther relatve poston n the ncome dstrbuton. Together wth the CI for our measure of health lmtatons, we calculate a CI of the needstandardsed use for health care (HI), whch measures the degree of horzontal nequty n 9
health care (van Doorslaer, Massera et al, 2004). When HI equals zero, there s horzontal equty. Postve values of the HI measure ndcate pro-rch nequty, whle negatve values of the HI measure ndcate pro-poor nequty. Assumng a lnear model, need-standardsed use can be calculated by ndrect standardsaton as the dfference between actual utlsaton (y ) and need-expected utlsaton ( x ŷ ), plus the sample mean (y m ): y ˆ = y yˆ + IS X y m (6) x The computaton of the need-predcted values of utlsaton ( ŷ ) requres two steps. Frstly, we run a regresson of medcal care use (y ) on (the logarthm of) ncome, a vector of k medcal need ndcator varables (x k ), and a set of p non-need varables (z p ), usng the followng equaton: y γ k xk, + δ p z + p = α + β ln nc +, ε, (7) k p Secondly, we combne the coeffcents from the OLS estmatons wth actual values of the x k varables the need varables for whch we want to standardse- and sample means of the ncome and z p varables -the non-need varables for whch we do not want to standardse, but for whch we want to control n the estmaton of the coeffcents-, usng the needpredcton equaton: X m m yˆ = ˆ α + ˆ β ln nc ˆ, δ z, (8) + ˆ γ k xk + k p p p x where ŷ ndcates the amount of medcal care an ndvdual would have receved f he had been treated as others wth the same need characterstcs, on average. To compute need-standardsed use we employ standard OLS models (see, e.g. Van Doorslaer et al., 2004; García and López, 2007). Although non lnear models have certan advantages over standard OLS modellng technques, calculaton of equaton (6) would nvolve a re-lnearzaton by usng ether the margnal or average effects of each ndependent varable treated as fxed parameters and evaluated at the mean (or some other parameter). The dsadvantage of ths procedure s that the standardsaton holds only 10
approxmately, and s contngent on the values used for the evaluaton. In addton, prevous research shows that horzontal nequty measures calculated by standard OLS technques hardly dffer to those obtaned by non lnear methods (Van Doorslaer et al., 2000). 3 The data 3.1 Spansh Natonal Health Survey In ths study we use the 2003 and 2006 waves of the Spansh Natonal Health Survey. The Spansh Natonal Health Survey (hereafter SNHS) s a representatve survey of the Spansh populaton. It s dssemnated every two years and t s coordnated by the Mnstry of Health and Consumpton. The samplng of the data follows a three-stage stratfed desgn. The unts of the frst stage are the census sectons. The unts of the second stage are the man famly households. Wthn each household, an adult (16 or older) s selected to fll all the questonnares. The SNHS ncludes a wde varety of nformaton about health and socoeconomc condtons of Spansh resdents and t contans ndvdualsed samples for adults and chldren. For the purpose of ths work, we restrct attenton to the adult samples of the 2003 and 2006 waves of the SNHS. Prevous waves of ths survey (1987, 1991, 1993, 1997, 2001) do not allow us to dentfy the natonalty or the country of brth of the respondent. Snce 2003, the SNHS ncludes a varable related to the natonalty of the respondents and n the last wave correspondng to 2006, nformaton on the country of brth s ncluded. In addton, the SNHS for both the 2003 and 2006 waves ncludes nformaton about vsts to hosptal emergency servces, a varable whch s not usually ncluded n other health surveys (e.g. Spansh sample from the ECHP). Ths nformaton wll allow us to corroborate wth recent Spansh naton-wde data the fndngs of prevous studes suggestng that hosptal emergency servces are an mportant mechansm of access to the health system by mmgrants n Span (ej. Cots et al. 2007; García Gómez 2007; Jménez Rubo 2008). 3.2 Sample and varables 11
We use an unbalanced sample of respondents, ncludng all the ndvduals aged 16 years or older ntervewed n each wave. Table 1 shows the sample sze for our dataset splt by natonalty our proxy for mmgrant status- and gender. Table 1. Sample szes for 2003 and 2006 SNHS 2003 2006 Total 2003-2006 All 21,650 29,478 51,128 Men 9,875 11,645 21,520 Women 11,755 17,833 29,608 Natonals 21,000 27,381 48,381 Men 9,580 10,747 20,327 Women 11,420 16,634 28,054 Immgrants 650 2,055 2,705 Men 295 878 1,173 Women 355 1,177 1,532 The SNHS ncludes several ndcators of health status, together wth varables related to the respondents utlsaton of health care servces. In addton, a wde set of demographc and socoeconomc varables, ncludng lfestyle varables, can be found n the SNHS for both years. Health status varables We use self-assessed health (SAH) as our dependent varable n the health status model. Although the SNHS ncludes several measures of health status, SAH s our preferred one as t s the most extensvely used measure of health n the research lterature and t has been shown to be a strong predctor of subsequent use of health care servces (van Doorslaer et al., 2000) and mortalty (Idler and Kasl, 1995). For measurng ndvdual s self perceved health status, ndvduals are asked: In the last twelve months, would you say that your health state has been: very good, good, far, poor, very poor?. From ths orgnal SAH varable, we construct a varable wth four categores, collapsng the two lowest categores (poor and very poor) nto one category (Hernández-Quevedo et al, 2008). 12
For explanng health care utlsaton, we nclude self-assessed health and three other measures of health as a proxy for the need of health care use. The frst s based on the queston Do you have any dffculty n carryng out your daly actvtes?, wth four possble answers: 1. No lmtatons, 2. Moderate lmtatons, 3. Severe lmtatons. The second need varable employed s based on the queston: ''Dd you have to reduce or lmt your man actvty durng the last two weeks?'' (no, yes). The last health status ndcator employed n the study of health care utlsaton s an ndcator of whether the ndvdual suffered an accdent of any knd, ncludng ntoxcaton or burnt, durng the twelve months prevous to the survey. Health care utlsaton varables The use varables that we consder are dfferent ndcators of whether the ndvdual has vsted: the GP, the specalst, hosptal servces and hosptal emergency servces. Measurement of the utlsaton of the general practtoner (GP) and medcal specalst servces s based on the queston: "Durng the last two weeks (four weeks n the 2006 SNHS), about how many tmes have you vsted: (a) a famly doctor or general practtoner and (b) a medcal specalst?". Hosptal utlsaton s measured on the bass of the queston: "How many tmes n the past 12 months have you (a) been a patent overnght n a hosptal and (b) vsted hosptal emergency servces?. The dfferent recall perods for utlsaton of a GP and a specalst doctor n the 2003 and 2006 surveys mply that we wll not be able to make predctons of use for each type of servce. However, we can provde some nsghts from the sgn of the estmated coeffcents. Socoeconomc varables Several varables have been ncluded n the econometrc estmatons to reflect both the demographc and socoeconomc characterstcs of the ndvdual. Age and gender have been ncluded n the specfcatons, where age s captured by the fve dummy varables, that reflect the age nterval that characterses the ndvdual (age 16-34, 35-44, 45-64, 65-74 and over 75 years). We allow for the nteracton between age and sex varables. 16-34 year old males are the reference category. 13
Income s used as the rankng varable when calculatng the concentraton ndces, but t s also ncluded as an explanatory varable n the econometrc specfcaton of both models that explan health lmtatons and utlsaton of health servces by the Spansh populaton. In the SNHS, ncome s measured as a categorcal varable wth 8 possble response categores that provde us wth an estmate of the aggregate monthly ncome, after taxes and deductons, of all household members from all sources. Gven the hgh proporton of mssng values for ncome n the SNHS (25% n the 2003 wave and 11% n the 2006 wave), we have mputed household ncome by regressng the lower and upper bounds of each ncome nterval on a set of varables related to the household, such as regon of resdence, number of chldren and number of adults and the mean age of adults, together wth several varables related to the man earner of the household, such as educaton, actvty and socoeconomc poston (Álvarez, 2001; Jones, 2000). In addton to ncreasng the sample sze, the use of an nterval regresson has allowed us to convert the categorcal ncome values nto contnuous ones, a transformaton whch s partcularly useful for the purpose of computng the CI. We have ncluded non-response dummes n the estmatons to allow for the possblty that tems were not mssng at random (Morrs, Sutton and Gravelle, 2003). Equvalent ncome has been computed by usng the modfed OECD equvalence scale that takes nto account dfferences n the sze and composton of the famles 3. Other socoeconomc varables used n ths study for both specfcatons of health lmtatons and use of health care are: AC of resdence, job status, level of educaton and natonalty of the respondents. We have ncluded a dummy varable for each AC, except for the base category, Comundad de Madrd, to allow for cultural and geographcal dfferences n the dstrbuton of health and use of health servces among Spansh regons. Gven ther dfferent status, Ceuta and Mellla have been excluded from the analyss, and nstead, restrcted attenton has been devoted to the seventeen Spansh ACs. For educaton, we use four levels: no educaton, prmary and secondary (frst cycle) studes, secondary (second cycle) and post-secondary studes, and unversty studes (reference category). Job status s measured by sx dummy varables that descrbe the actvty status of the respondents: employed (base category), unemployed, retred, student, housework and other. In ths study 3 The modfed OECD scale assgns a weght of 1.0 to the frst adult household member, 0.5 to the second adult household member and 0.3 to chldren, beng calculated as: Equvalent ncome = ((ncome)/(1+0.5*(householdsze 1 number of chldren) + 0.3*chldren)) 14
we have used natonalty as a proxy for mmgrant status. Natonalty s captured by the followng dummy varables: Span (reference category), European Unon, other European country, Canada or USA, Latn Amerca, Asa, Afrca and Oceana. Table 2 shows the number of ndvduals correspondng to the dfferent categores of natonalty ncluded n the 2003 and the 2006 waves of the SNHS. After Spanards, natonals from Central and South Amerca are the most numerous, followed by European Unon ctzens, Afrcans and Europeans (from non European Unon countres). Asan, Australasan and North Amercan are the less representatve natonaltes n the survey. Table 2. Number of mmgrants by natonalty Total 2003-2006 2003 2006 Natonalty N % N % N % Latn Amerca 1,250 46 281 43 969 47 European Unon 742 28 144 22 598 29 Afrca 446 17 127 20 319 16 Europe 150 6 70 11 80 4 Asa 76 3 24 4 52 3 North Amerca 24 1 3 0,5 21 1 Oceanía 8 0.3 1 0.2 7 0.3 Non Spanards 2,705 5 650 3 2,055 7 Spanards 48,381 95 21,000 97 27,381 93 Other ndvdual characterstcs There are addtonal varables that have been ncluded n the dfferent specfcatons. In the self-reported health model, three ndcators of lfestyle have been ncluded. These are: whether the ndvdual smokes, an ndcator of whether the ndvdual practces physcal exercse and whether the respondent consumes alcohol regularly. For the specfcaton of the models of health care utlsaton, we have ncluded an ndcator of whether the ndvdual has prvate health nsurance. Gven that the type of health nsurance may have an mportant effect on the length of tme an ndvdual has to wat to 15
receve health care assstance, we have ncluded a dummy varable takng the value one f the ndvdual has prvate coverage for health care servces, rrespectvely of whether he has purchased the nsurance hmself, or the state or a prvate company has contracted t on hs behalf 4. The fact that the tenure of a prvate nsurance s not always an ndvdual s choce but s based on the ndvdual s occupaton, mples that endogenety n ths context s less lkely to be an ssue. 4 Results 4.1 Descrptve statstcs Table 3 shows the mean statstcs of the key (dependent) health status and health care use varables used n the estmatons. Accordng to Table 3, there are dfferences n the proporton of ndvduals reportng good or very good health and usng health care servces between Spansh natonals and non-natonals 5. Non Spanards report better level of health than Spanards, a hgher use of hosptal emergency servces, and a lower use of specalsed care as compared to Spansh populaton. The next secton explores whether these dfferences persst after controllng for all those factors that are known to affect health care use. Table 3. Sample means of key health status and health care use varables 2003 2006 All Spanard Non Spanard All Spanard Non Spanard Good or very good health 0.65 0.64 0.77 0.62 0.61 0.72 GP vsts 0.24 0.25 0.15 0.84 0.84 0.85 Specalst vsts 0.07 0.07 0.05 0.41 0.41 0.38 Hosptal vsts 0.11 0.10 0.12 0.10 0.10 0.08 Hosptal emergency vsts 0.27 0.26 0.29 0.29 0.29 0.31 4 In Span, cvl servants have the possblty to opt out between the Natonal Health Servce or prvate nsurance companes (WHO, 2006). 5 Sample means reported n Table 3 are for a bnary measure of beng n good or very good health and ndcators of whether the ndvdual has vsted at least once any of the health servces consdered n ths study. Detaled sample means for self-assessed health categores can be found n Table 1A. 16
Sample means of the ndependent varables ncluded n the regresson models are presented n Table 1A of the Appendx. Accordng to the sample descrptves, non-spanard ndvduals report hgher levels of educaton compared to Spansh ctzens. Further, there are relatvely more non-spanards employed, n the workng age and n the mddle ncome categores. The socoeconomc characterstcs of mmgrants, and n partcular ther smlar dstrbuton by ncome level to the Spansh populaton, and ther hgh proporton n the upper ncome nterval, suggest that the non Spanard sample mght be capturng to a great extent mmgraton of wealthy ndvduals for non economc reasons such as retrng, rather than mmgraton of ndvduals movng to Span n search for work. Regardng lfestyle varables, there s a hgher proporton of natonal ndvduals who smoke and consume alcohol, whle the proporton of ndvduals who practce physcal actvtes s relatvely hgher for Spanards than for non-spanards. 4.2 Regresson results for econometrc models of health status and health care use 4.2.1 Health status The estmated coeffcents of the probt models for health and health care use for the mmgrant categores employed n the estmatons are presented n Tables 4 to 6. Regresson results for the remanng control varables used n the econometrc estmatons are presented n Tables 3A to 5A n the Appendx. Table 4 shows that after controllng for a set of socoeconomc and demographc varables, beng mmgrant s stll statstcally sgnfcant n explanng health status and t s negatvely related to reportng low categores of health. Hence, mmgrants are more lkely to report the hghest categores of selfassessed health. Regardng the socoeconomc varables, Table 3A shows that for all specfcatons of SAH, there s a gradent for age, wth ndvduals reportng worse levels of health as the ndvdual gets older. The margnal effects for female ndvduals are greater than for male ndvduals, hence, reportng worse health. For level of educaton, t s also possble to see a gradent, wth ndvduals wth hgher level of educaton reportng better levels of health than those wth lower levels of educaton. Regardng actvty status, those retred and nactve are the ndvduals more lkely to report the lower categores of SAH. Students are more lkely to report hgher categores of SAH than the employed ndvduals. 17
Table 4. Results for the pooled probt analyss: coeffcents for non Spanards Self-assessed Hosptal Hosptal GP vsts Specalst vsts health vsts emergency vsts Natonalty Coef. z Coef. Z Coef. z Coef. z Coef. z Non Spanard -0.02*** -2.8 0.04** 2.4-0.03*** -4.6 0.02*** 2.9 0.02*** 2.6 Pseudo R 2 0.1 0.3 0.2 0.1 0.2 Log-L -32,920-14,947-11,405-13,792-24,407 N 31,101 32,829 32,646 49,123 49,123 Note: The astersks ndcate sgnfcance at the 1% level (***) 5% level (**) and 10% level (*) Table 6. Results for the pooled probt analyss: coeffcents for non Spanard natonaltes Natonalty Selfassessed health GP vsts Specalst vsts Hosptal vsts Hosptal emergency vsts Latn Amerca 0.001 (0.2) 0.05** (2.4) -0.03*** (-3.4) 0.02*** (3.1) 0.07*** (5.8) European Unon -0.05*** (-3.3) 0.07** (2.2) -0.05*** (-4.3) -0.002 (-0.2) -0.04** (-2.4) Afrca -0.03* (0.2) 0.04 (1.2) -0.02 (-0.9) 0.05*** (3.6) 0.04* (1.9) Europe -0.03 (-1.6) -0.16*** (-3.3) 0.04 (0.9) -0.02 (-1.0) -0.08*** (-2.6) Asa -0.01 (-0.4) 1.0 (1.4) -0.01 (-0.4) 0.04 (1.4) -0.02 (-0.5) North Amerca -0.08 (-1.0) -0.35*** (-12.1) 0.04 (0.3) -0.07*** (-4.2) -0.1 (-1.4) Oceana 0.34* (1.7) -0.30* (-1.9) -0.03 (-0.2) 0.08 (0.6) -0.16 (-1.4) Pseudo R 2 0.1 0.3 0.2 0.1 0.2 Log-L -32,904-14,935 11,404-13,779-24,384 N 31,101 32,830 32,649 49,124 49,124 Note: The astersks ndcate sgnfcance at the 1% level (***) 5% level (**) and 10% level (*) 18
Table 5 ndcates that beng an European Unon mmgrant s statstcally sgnfcant n explanng health status at any conventonal sgnfcance level, whle beng an mmgrant ether from Afrca or Oceana s statstcally sgnfcant at a 10% sgnfcance level, ceters parbus. Immgrants from the European Unon tend to report hgher categores of selfassessed health status, whle those from Afrca and Oceana tend to report worse levels of health than the natonals. Table 7. Results for the pooled probt analyss, ncludng nteractons between ncome and non-spanards Self-assessed Health GP vsts Specalst vsts Hosptal vsts Hosptal emergency vsts Coef. z Coef. z Coef. z Coef. z Coef. Z Non- Spanard* Income (ln) -0.004*** -2.9 0.04 1.1-0.03-1.1-0.10*** -7.3-0.06** -2.3 Pseudo R 2 0.1 0.3 0.2 0.1 0.2 Log-L -32,885-14,946-11,405-13,765-24,405 N 31,101 32,829 32,646 49,123 49,123 Note: The astersks ndcate sgnfcance at the 1% level (***) 5% level (**) and 10% level (*) In order to analyse whether the dfferences n health or utlsaton of health care are systematcally assocated to ncome, we have ntroduced a thrd model ncludng an nteracton term between ncome and beng non Spanard. For the SAH model, n Table 6, we can see that the nteracton between beng mmgrant and level of ncome s statstcally sgnfcant and negatvely assocated wth health status. Ths means that the gap n health status between mmgrants and non mmgrants ncreases wth the level of ncome (Wooldrdge, 2006). 4.4.2. Health care utlsaton The regresson results n Tables 4A and 5A n the Appendx show that need s the most mportant determnant of health care use. Overall, the estmated coeffcents on the need varables have the expected sgn. For nstance, relatve to beng n very good health, beng n very bad health ncreases the probablty of usng every type of health servce consdered n ths study. In general, the coeffcents for the varable self-assessed health also show the 19
expected gradent. Also, an nterestng result ndcates that 16-34 years old females have a hgher probablty of contactng a GP, a specalst doctor, and beng hosptalzed than ther male counterparts, possbly ndcatng the use of maternty related servces by healthy women. However, other non-need factors were also found to be mportant determnants of health care utlsaton, ncludng the natonalty of an ndvdual. As found n prevous research usng Spansh data (García and López, 2007), ncome s postvely assocated wth the probablty of contactng a specalst, whle negatvely assocated wth the probablty of a GP vst. However, nterestngly, our results suggest that hgher ncome ndvduals have a hgher probablty of vstng emergency medcal attenton. The tenure of a prvate nsurance ncreases as expected the probablty of payng a vst to the specalst doctor and of beng hosptalsed, and reduces the probablty of vstng the GP. The mpact of the natonalty of an ndvdual on health care use across natonaltes and types of health care s descrbed n more detal below. GP vsts Accordng to the results Latn Amercan and European Unon ndvduals report a hgher probablty of a GP vst than a Spanard, whle natonals from Europe, North Amerca and Oceana report a lower probablty of vstng the GP. In partcular, Latn Amercans have a probablty 0.05 greater of contactng a GP than a Spanard ndvdual wth the same soco economc and health characterstcs. Specalst vsts In general, non Spanards have a lower probablty of vstng a specalst physcan than Spansh ndvduals. By natonalty, the analyss reveals that Latn Amercans and ctzens from the European Unon have a lower probablty of contactng a specalst. For European Unon ctzens for example the probablty of a vst s 0.05 lower than for a Spansh ndvdual wth the same level of need. Inpatent stays For non-natonal ndvduals the results reveal a hgher probablty to spend a nght n a hosptal as compared to a Spansh ctzen. Among non Spanards, the probablty of beng 20
hosptalsed s larger for Latn Amercans and Afrcans. For Latn Amercans for example the probablty of an npatent stay s 0.02 greater than for a Spanard, holdng all other factors equal. However, North Amercans report a lower probablty of an npatent stay relatve to a Spanard ndvdual. Hosptal emergency servces Accordng to the results presented n Table 4 non Spanards have a hgher probablty of usng hosptal emergency servces. In partcular, the results show that Latn Amercans and Afrcans have hgher probabltes of an emergency vst as compared to Spanards, whle ctzens from the European Unon and Europe report lower probabltes of vstng hosptal emergency servces. These results corroborate the prevous fndngs suggestng that emergency servces are an mportant mechansm of access to hosptal servces by mmgrants, and are n lne wth prevous research for Catalona (Cots, Castells, García, Ru, Felpe, and Vall 2007; García Gómez 2007). In sum, the results for health care use ndcate that relatve to Spanards, mmgrants report hgher probabltes of contactng a GP, a hosptal, and hosptal emergency servces, and a lower probablty of vstng a specalst doctor. However, accordng to the results presented n Table 7, the dfferent pattern of hosptal utlsaton between Spanards and non Spanards tend to dmnsh as the level of ncome ncreases. 4.3 Socoeconomc nequaltes n health outcomes and utlsaton Table 2.A shows the results for the Concentraton Indces of our measure of health, together wth the CI of the need-standardsed use for health care, ths s, our measure of Horzontal Inequty. Ths has been calculated for both years and both natonal and nonnatonal ndvduals. Fgures 2, 3 and 4 show smlar results for self-assessed health and utlsaton varables, presentng the 95% confdence nterval of the concentraton ndces. 21
Fgure 2. CI for SAH for 2003 and 2006 0.1 0.08 0.06 0.04 0.02 0-0.02 All All Spanard Non-Spanard Spanard Non-Spanard 2003 SAH 2006 SAH Fgure 3. CI of the need-standardsed use for health care for 2003 0,50 0,40 0,30 0,20 0,10 0,00-0,10 All All All All Span. Non Span. Span. Non Span. Span. Non Span. Span. Non Span. -0,20-0,30-0,40-0,50 Gp vsts Specalst vsts Hosptal vsts Hosptal emergency vsts 22
Fgure 4. CI of the need-standardsed use for health care for 2006 0,200 0,150 0,100 0,050 0,000-0,050 All All All All Span. Non Span. Span. Non Span. Span. Non Span. Span. Non Span. -0,100-0,150-0,200-0,250-0,300 Gp vsts Specalst vsts Hosptal vsts Hosptal emergency vsts The results n Table 2A and Fgure 2 show that all concentraton ndces for self-assessed health are postve, mplyng the exstence of ncome-related nequaltes n health for both natonals and mmgrants. These nequaltes favour rch ndvduals, so that rcher ndvduals tend to report hgher categores of health than the poor ndvduals. Ths prorch nequalty n health s greater for natonals than for mmgrants, for both perods, although mmgrants show lower nequalty n 2006 whle natonals concentrate more nequaltes n 2006 than n 2003. For health care utlsaton, the results corroborate prevous studes for Span (e.g. García and López, 2007; Van Doorslaer et al., 2004), n that the dstrbuton of need-standardsed hosptal vsts and specalst care s pro-rch, whle the dstrbuton of need-standardsed GP vsts s pro-poor. However, our results reveal some nterestng dfferences for the nequty measures between Spanards and non Spanards. Frstly, for GP vsts and specalst medcal attenton, the fndngs show that for mmgrants ncome does not lead to substantal dfferences n utlzaton for the same level of need. Secondly, for non Spanards ncome related nequtes n the use of hosptal servces are much more concentrated on the poor than for Spanards, especally for the year 2003. These results are consstent wth our 23
prevous fndngs shown n Table 7, and ndcate that only for hosptal servces the dfferences n the patterns of utlsaton between Spanards and autochthonous populaton are assocated wth ncome. 5 Dscusson The reducton of nequaltes n health and n the access to health servces s one of the man objectves n any health care system. Economsts have developed emprcal methods that allow to quantfy the degree of nequalty n the dstrbuton of health measures and health care utlsaton, and compare nequaltes over tme and space, dentfyng those factors that lead to nequaltes, beng able to provde some evdence to polcymakers. Varous studes have analysed the exstence of nequaltes n health and n the use of health care for the Spansh populaton. However, the emprcal evdence for the mmgrant collectve on ths ssue s as yet nsuffcent. Ths workng paper ams to provde evdence on nequaltes n health and n the access to health servces for the mmgrant populaton lvng n Span, relatve to that of the autochthonous populaton, by usng recent naton wde data from the Spansh Natonal Statstcs Insttute. In order to analyse any dfferences n health outcomes for the natonal and mmgrant populaton, we focus on a measure of self-reported health that s avalable n the Spansh Natonal Health survey. The man objectve s to fnd the relatonshp between socoeconomc and demographc varables on the level of reported health and check weather the pattern s sgnfcantly dfferent for mmgrant ndvduals. Results show that reportng worse health s related to lower levels of educaton, beng retred or nactve, gettng older, whle those wth hgher levels of ncome tend to report hgher categores of self-perceved health. For the specfc case of mmgrants, we fnd that foregners tend to report better levels of self-assessed health than natonals. In partcular, those ndvduals from the European Unon tend to report hgher level of health than the natonal populaton. In the analyss of the dfferences n the health care utlsaton patterns by natonalty groups attenton s drawn to whether, after havng controlled for need varables (proxed by 24
morbdty varables), utlsaton of a GP, a specalst doctor, npatent and hosptal emergency servces vary accordng to the natonalty of the respondents. Other non-need varables ncluded n the study are: ncome, educaton, Autonomous Communty of resdence, tenure of prvate health nsurance and economc status. Utlsaton of health care servces s analysed usng probt regresson models. The results ndcate that need s the most mportant predctor of the probablty of usng any of the health care servces analysed n ths study. However, other non-need factors were found to be statstcally sgnfcant n predctng ndvdual utlsaton of health servces, ncludng the natonalty of the respondent. The results for our health care utlsaton varables reveal that mmgrants are more lkely to be treated n a hosptal than Spanards are, and they are more lkely to contact a GP and emergency medcal servces. For specalst vsts the fndngs ndcate that foregners are less lkely to contact a specalst doctor than natonal ctzens. Snce under utlsaton of specalst care servces does not appear to be caused by a reluctance to seek an ntal contact wth the GP, these results may be taken to mply the exstence of nequty n the access to specalst care wth respect to natonalty. Regardng emergency vsts, the fndngs suggest that mmgrants have a hgher probablty of contactng hosptal emergency servces as compared to Spanards. As suggested by prevous research for Catalona, ths result may reflect a lmted understandng of the functonng of the Spansh health care system by mmgrants, and a potental substtuton of specalsed care by hosptal emergency servces. In addton, we have calculated measures of ncome related nequalty n health and nequty n health care utlsaton based on the Concentraton Index to explore whether the observed dfferences n our key health and health care related varables are systematcally assocated wth ncome. For self assessed health, we found evdence of ncome-related nequaltes n health for both natonals and mmgrants, favourng the rchest ndvduals. Natonals concentrate hgher levels of health than mmgrants for the two perods consdered, although mmgrants show lower ncome related nequalty n 2006 whle natonals concentrate more ncome related nequaltes n 2006 than n 2003. 25
For health care utlsaton our results show that only for hosptal vsts the dfferences found n the dstrbuton of the need standardsed probablty of use between Spanards and non Spanards are related to ncome. In partcular, accordng to our fndngs, the dstrbuton of the probablty of vstng a hosptal s much more pro-poor than for Spanards. For the remanng use varables ncome does not appear to lead to substantal dfferences n the probablty of utlzaton for the same level of need. Overall, our fndngs ndcate that mmgrants n Span have dfferent health and health care utlsaton patterns than Spansh populaton. Whle mmgrants report better levels of health status than Spanards, our results suggest that non Spanards face substantal barrers of entry to health care servces. Our results mply that health polces should focus on mprovng mmgrants knowledge of the system by reducng legal, cultural and admnstratve barrers to access health servces. Further understandng of the nature of these barrers (demand related: culture, language command, soco economc context or legal status; supply related: accessblty, staff atttudes), would help to target resources better to populaton needs and therefore ensure more effectve health polces. References Abásolo, I., Mannng, R. (2001). Equty n utlzaton of and access to publc sector GPs n Span. Appled Economcs, 33, 349-364. Álvarez, B (2001). La demanda atendda de consultas médcas y servcos urgentes en España. Investgacones Económcas, volumen XXV(1): 93-138 Carrasco Garrdo, P., Gl de Mguel, A., Hernández Barrera, V., Jménez García, R. (2007). Health profles, lfestyles and use of health resources by the mmgrant populaton resdent n Span. European Journal of Publc Health, Vol. 17, No. 5:503-507. Clavero, A., González, M. L. (2005). La demanda de asstenca santara en España desde la perspectva de la decsón del pacente. Estadístca Española, 158, 55-87. Cots, F., Castells, X., García, O., Ru, M., Felpe, A., Vall, O. (2007). Impact of mmgraton on the cost of emergency vsts n Barcelona (Span). BMC Health Servces Research, 7, 9-17. 26
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APPENDIX Fgure 1A. Proporton of foregn populaton on total populaton, 1998-2007 14,0 12,0 10,0 8,0 6,0 4,0 2,0 2,9 3,1 1,6 1,9 3,6 2,3 4,8 3,3 6,2 4,7 7,7 6,2 8,6 7,0 10,0 8,5 10,8 9,3 11,6 10,0 Non Spansh natonals/total populaton Non Spansh born/total populaton 0,0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Source: Own calculatons from Spansh Natonal Statstcs Insttute data Fgure 2A. Proporton of foregn populaton on total populaton by Autonomous Communtes, 2007 25,0 20,0 15,0 10,0 5,0 0,0 Extremadura Galca Asturas Pas Vasco Cantabra Castlla y León Andaluca Castlla La Mancha Navarra Aragon La Roja Canaras Cataluña Madrd Murca Valenca Balears Non Spansh natonals/total populaton Non Spansh born/total populaton Source: Own calculatons from Spansh Natonal Statstcs Insttute data 30
Fgure 3A. Foregn populaton classfed by natonalty group, 2007 North Amerca 1,0% Asa 4,9% Oceana 0,1% Central and South Amerca 34,3% European Unon (27) 37,8% Afrca 17,9% Europe 4,1% Source: Own calculatons from Spansh Natonal Statstcs Insttute data Fgure 4A. Foregn populaton classfed by country of brth, 2007 Central and South Amerca 37,9% North Amerca 1,4% Asa 4,7% Oceana 0,1% European Unon (27) 34,7% Afrca 16,4% Europe 4,7% Source: Own calculatons from Spansh Natonal Statstcs Insttute data 31
Table 1A. Sample means of key varables Average 2003-2006 2003 2006 Income All Spanards Non Spanards All Spanards Non Spanards All Spanards Non Spanards < 360 euros 0.021 0.021 0.016 0.026 0.027 0.018 0.017 0.017 0.016 361-600 euros 0.143 0.147 0.070 0.184 0.185 0.114 0.118 0.123 0.058 601-900 euros 0.171 0.171 0.174 0.201 0.199 0.263 0.152 0.153 0.151 901-1200 euros 0.203 0.200 0.260 0.199 0.198 0.237 0.205 0.201 0.266 1201-1800 euros 0.236 0.234 0.262 0.213 0.213 0.210 0.250 0.248 0.276 1801-3600 euros 0.192 0.193 0.182 0.152 0.153 0.132 0.217 0.219 0.195 3601-6000 euros 0.030 0.030 0.028 0.021 0.021 0.016 0.036 0.036 0.031 > 6000 euros 0.004 0.004 0.007 0.004 0.004 0.009 0.005 0.004 0.007 Self-reported health Very good 0.121 0.116 0.203 0.093 0.091 0.152 0.141 0.135 0.221 Good 0.512 0.511 0.534 0.556 0.554 0.618 0.480 0.478 0.505 Far 0.266 0.268 0.219 0.254 0.256 0.191 0.274 0.278 0.229 Bad 0.078 0.080 0.035 0.076 0.077 0.035 0.079 0.083 0.034 Very bad 0.024 0.025 0.009 0.021 0.022 0.003 0.026 0.027 0.011 Lmtatons man actvty (prevous 2 weeks) Lmted 0.147 0.148 0.129 0.133 0.134 0.102 0.157 0.158 0.138 Non lmted 0.853 0.852 0.871 0.867 0.866 0.898 0.843 0.842 0.862 Lmtatons n daly actvtes Severe 0.044 0.046 0.014 0.033 0.034 0.008 0.053 0.055 0.017 Moderate 0.150 0.152 0.099 0.065 0.066 0.015 0.212 0.218 0.128 None 0.806 0.802 0.887 0.902 0.900 0.977 0.735 0.726 0.855 Accdent 0.102 0.103 0.084 0.101 0.102 0.094 0.103 0.104 0.081 Age and sex 16 to 34 years old male 0.107 0.101 0.218 0.121 0.117 0.235 0.097 0.088 0.212 35 to 44 years old male 0.092 0.090 0.126 0.102 0.102 0.117 0.084 0.080 0.130 45 to 64 years old male 0.122 0.125 0.074 0.126 0.128 0.080 0.119 0.122 0.072 32
65 to 74 years old male 0.054 0.057 0.013 0.061 0.062 0.015 0.049 0.052 0.012 > 75 years old male 0.046 0.048 0.007 0.046 0.047 0.006 0.046 0.049 0.007 16 to 34 years old female 0.127 0.118 0.291 0.125 0.121 0.274 0.128 0.116 0.297 35 to 44 years old female 0.109 0.108 0.132 0.097 0.096 0.123 0.118 0.116 0.134 45 to 64 years old female 0.170 0.173 0.116 0.144 0.145 0.115 0.189 0.194 0.116 65 to 74 years old female 0.088 0.092 0.012 0.093 0.095 0.015 0.084 0.089 0.011 > 75 years old female 0.086 0.090 0.011 0.084 0.086 0.018 0.086 0.092 0.008 Educaton None 0.143 0.147 0.080 0.148 0.149 0.105 0.139 0.145 0.071 Prmary and secondary (cycle 1) 0.483 0.490 0.365 0.509 0.514 0.352 0.463 0.471 0.369 Secondary (cycle 2) and 0.229 0.220 0.378 0.205 0.201 0.329 0.246 0.235 0.395 postsecondary Unversty 0.146 0.143 0.177 0.137 0.135 0.214 0.152 0.150 0.164 Actvty status Employed 0.439 0.427 0.659 0.423 0.417 0.618 0.450 0.434 0.674 Retred 0.250 0.261 0.050 0.247 0.252 0.072 0.252 0.268 0.043 Unemployed 0.063 0.061 0.089 0.063 0.062 0.082 0.063 0.060 0.092 Student 0.050 0.050 0.041 0.061 0.062 0.057 0.042 0.042 0.035 Housework 0.188 0.191 0.149 0.199 0.200 0.166 0.181 0.183 0.143 Other 0.010 0.010 0.012 0.007 0.007 0.005 0.013 0.012 0.014 Health nsurance Prvate health nsurance 0.145 0.146 0.117 0.131 0.131 0.125 0.155 0.158 0.114 Compulsory health nsurance 0.997 0.998 0.969 0.996 0.997 0.966 0.997 0.999 0.970 Lfestyle varables Smoke 0.468 0.469 0.455 0.463 0.464 0.423 0.472 0.473 0.467 Physcal actvty 0.589 0.591 0.556 0.572 0.571 0.615 0.603 0.607 0.534 Alcohol consumpton 0.440 0.445 0.331 0.557 0.558 0.541 0.187 0.192 0.123 33
Table 2A: Concentraton Index for health status and utlsaton of health care 2003 2006 All Spanard Non Spanard All Spanard Non Spanard Very good/good health GP vsts Specalst vsts Hosptal vsts Hosptal emergency vsts 0.07*** (20.9) -0.10*** (-11.7) 0.16*** (8.5) 0.06*** (4.1) 0.003 (0.4) 0.07*** (20.3) -0.10*** (-11.7) 0.16*** (8.5) 0.07*** (5.1) 0.004 (0.6) 0.05*** (3.33) -0.08 (-1.4) 0.11 (0.7) -0.26*** (-3.6) -0.05 (-1.2) 0.07*** (22.8) -0.04*** (-10.9) 0.09*** (10.4) 0.01 (0.7) 0.01 (1.0) 0.08*** (24.2) -0.04*** (-10.9) 0.09*** (10.3) 0.03** (2.2) 0.01 (1.5) 0.016 (1.3) -0.02* (-1.8) 0.07 (1.5) -0.13* (-1.9) -0.02 (-0.7) Note: The astersks ndcate sgnfcance at the 1% level (***) 5% level (**) and 10% level (*) Table 3A. Margnal effects for pooled probt specfcaton for SAH, ncludng dfferent defntons of mmgrant Self assessed health (1) (2) (3) Income (ln) -0.047*** -0.048*** -0.047*** Imputed ncome dummy -0.004-0.003-0.003 Non-Spanard * Income (ln) -0.004 Age and sex 35 to 44 years old male 45 to 64 years old male 65 to 74 years old male over 75 years old male 16 to 34 years old female 35 to 44 years old female 45 to 64 years old female 65 to 74 years old female Over 75 years old female Educaton Prmary and secondary (cycle 1) Secondary (cycle 2) and postsecondary Unversty Actvty status Retred Unemployed Student Housework Other 0.019*** 0.054*** 0.028*** 0.055*** 0.008** 0.036*** 0.097*** 0.129*** 0.143*** -0.051*** -0.074*** -0.085*** 0.105*** 0.022*** -0.0241*** 0.027*** 0.119*** 0.012*** 0.031*** 0.029*** 0.056*** 0.008** 0.036*** 0.099*** 0.131*** 0.145*** -0.052*** -0.075*** -0.087*** 0.107*** 0.022*** -0.024*** 0.029*** 0.122*** 0.019*** 0.054*** 0.029*** 0.054*** 0.008** 0.036*** 0.097*** 0.128*** 0.142*** -0.051*** -0.073*** -0.085*** 0.104*** 0.021*** -0.023*** 0.027*** 0.119*** 34
Autonomous Communty Andalucía Aragón Asturas Balears Canaras Cantabra Castlla y León Castlla la Mancha Cataluña Comundad Valencana Extremadura Galca Murca Navarra País Vasco La Roja Lfestyle Smokng Physcal Actvty Consumes Alcohol Natonalty -0.006-0.0001 0.028*** 0.016* 0.029*** 0.005-0.007-0.003 0.005 0.003-0.001 0.051*** -0.01-0.001 0.005-0.014* 0.017*** 0.015*** -0.011*** -0006 0.001 0.288*** 0.016* 0.029*** 0.006-0.007-0.004 0.005 0.003-0.01 0.052*** -0.001-0.001 0.005-0.014 0.017*** 0.015*** -0.011*** -0.006-0.0003 0.028*** 0.016* 0.028*** 0.005-0.008-0.005 0.004 0.002-0.002 0.050*** -0.001-0.001 0.005-0.014* 0.016*** 0.014*** -0.010*** Non Spanard -0.023*** 0.004 Latn Amerca North Amerca European Unon Afrca Europe Asa Oceana 0.001-0.080-0.052*** -0.030* -0.031-0.0137 0.344* Year 2006 0.003 0.003 0.003 Cut-ponts Cut1 Cut2 Cut3-2.781-1.021 0.035-2.765-1.005 0.052-2.784-1.025 0.032 Pseudo R 2 0.1 0.1 0.1 Log-L -32,920-32,904-32,919 N 31,101 31,101 31,101 Note: The astersks ndcate sgnfcance at the 1% level (***) 5% level (**) and 10% level (*) 35
Table 4A. Margnal effects for pooled probt specfcaton for GP and specalst servces, ncludng dfferent defntons of mmgrant Gp vsts Specalst vsts (1) (2) (3) (1) (2) (3) Income (ln) -0.041** -0.043** -0.043*** 0.052*** 0.053*** 0.054*** Imputed ncome dummy -0.031*** -0.032*** -0.031*** -0.006-0.006-0.006 Non Spanard* Income (ln) 0.046-0.136 Self-reported health Good 0.044*** 0.045*** 0.044*** 0.020*** 0.020*** 0.020** Far 0.161*** 0.161*** 0.161*** 0.074*** 0.074*** 0.074*** Bad 0.169*** 0.169*** 0.168*** 0.156*** 0.156*** 0.156*** Very bad 0.119*** 0.119*** 0.119*** 0.179*** 0.179*** 0.180*** Lmtatons man actvty 0.233*** 0.233*** 0.233*** 0.057*** 0.057*** 0.057*** Lmtatons n daly actvtes Moderate -0.086*** -0.085*** -0.086*** 0.033** 0.031** 0.033** Severe -0.069*** -0.068*** -0.069*** 0.029*** 0.029*** 0.029*** Accdent 0.003 0.003 0.003 0.034*** 0.034*** 0.034*** Age and sex 35 to 44 years old male 0.019 0.019 0.019 0.014 0.015 0.014 45 to 64 years old male 0.061*** 0.062*** 0.061*** 0.034*** 0.034*** 0.034*** 65 to 74 years old male 0.132*** 0.133*** 0.132*** 0.013 0.013 0.013 > 75 years old male 0.201*** 0.203*** 0.201*** 0.001 0.001 0.001 16 to 34 years old female 0.054*** 0.055*** 0.054*** 0.056*** 0.056*** 0.056*** 35 to 44 years old female 0.051*** 0.051** 0.051** 0.052*** 0.053*** 0.052*** 45 to 64 years old female 0.118*** 0.119*** 0.118*** 0.031*** 0.032*** 0.032*** 65 to 74 years old female 0.170*** 0.170*** 0.170*** -0.006-0.006-0.006 > 75 years old female 0.206*** 0.207*** 0.206*** -0.040*** -0.040*** -0.040*** Educaton None 0.082*** 0.081*** 0.082*** -0.026*** -0.026*** -0.026*** Prmary and secondary (cycle 1) 0.047*** 0.046*** 0.047*** -0.016** -0.016** -0.016** Secondary (cycle 2) and postsecondary 0.030*** 0.029** 0.030*** -0.004-0.003-0.004 Actvty status Retred 0.060*** 0.061*** 0.060*** 0.034*** 0.034*** 0.035*** Unemployed 0.013 0.014 0.013 0.021** 0.021** 0.021** Student -0.022-0.021-0.022-0.015* -0.015* -0.015* Housework 0.038*** 0.039*** 0.038*** 0.018*** 0.017** 0.018*** Other 0.003 0.002 0.003 0.032 0.032 0.032 Autonomous Communty Andalucía 0.034*** 0.034*** 0.034*** -0.009-0.008-0.008 Aragón 0.032 0.032 0.032-0.006-0.006-0.006 Asturas 0.016 0.016 0.016 0.002 0.002 0.002 Balears -0.017-0.018-0.017-0.004-0.004-0.004 Canaras 0.005 0.006 0.005 0.031** 0.031** 0.031** Cantabra -0.101*** -0.101*** -0.101*** -0.011-0.011-0.011 Castlla y León 0.023 0.022 0.022-0.023*** -0.023*** -0.023*** Castlla la Mancha 0.087*** 0.088*** 0.087*** -0.014-0.013-0.014 Cataluña -0.068*** -0.068*** -0.068*** 0.019*** 0.018** 0.019*** Comundad Valencana 0.043*** 0.043*** 0.043*** 0.005 0.005 0.005 Extremadura 0.020 0.020 0.019-0.032*** -0.032*** -0.032*** 36
Galca 0.030* 0.030* 0.030* -0.011-0.011-0.011 Murca 0.054** 0.054** 0.054** -0.014-0.014-0.014 Navarra 0.007 0.008 0.007-0.004-0.004-0.004 País Vasco -0.030* -0.030* -0.029* 0.016 0.016 0.015 La Roja 0.031 0.033 0.031 0.003 0.003 0.002 Prvate health nsurance -0.084*** -0.084*** -0.084*** 0.070*** 0.071*** 0.070*** Natonalty Non Spanard 0.037** -0.225-0.033*** 0.197 Latn Amerca 0.052** -0.033*** European Unon 0.069** -0.048*** Afrca 0.041-0.017 Europe -0.164*** 0.036 Asa 0.097-0.014 North Amerca -0.351*** 0.040 Oceana -0.303* -0.027 Year 2006 0.609*** 0.608*** 0.609*** 0.292*** 0.292*** 0.292*** Pseudo-R 2 0.3176 0.3183 0.3177 0.2229 0.2231 0.2229 Log-L -14,947.1-14,934.6-14,946.5-11,405.3-11,403.9-11,404.7 N 32,829 32,830 32,829 32,646 32,649 32,646 Note: The astersks ndcate sgnfcance at the 1% level (***) 5% level (**) and 10% level (*) Table 5A. Margnal effects for pooled probt specfcaton for hosptal and hosptal emergency servces, ncludng dfferent defntons of mmgrant Hosptal vsts Hosptal emergency vsts (1) (2) (3) (1) (2) (3) Income (ln) 0.006 0.007 0.013** 0.021*** 0.024*** 0.025*** Imputed ncome dummy 0.005* 0.005* 0.005-0.009-0.008-0.009 Non Spanard*Income (ln) -0.097*** -0.056** Self-reported health Good 0.015*** 0.015*** 0.015*** 0.061*** 0.061*** 0.061*** Far 0.077*** 0.076*** 0.077*** 0.213*** 0.213*** 0.213*** Bad 0.187*** 0.187*** 0.187*** 0.373*** 0.374*** 0.373*** Very bad 0.237*** 0.236*** 0.238*** 0.385*** 0.386*** 0.385*** Lmtatons man actvty 0.031*** 0.031*** 0.031*** 0.124*** 0.124*** 0.125*** Lmtatons n daly actvtes Moderate 0.105*** 0.105*** 0.105*** 0.113*** 0.111*** 0.113** Severe 0.068*** 0.068*** 0.068*** 0.080*** 0.080*** 0.080*** Accdent 0.045*** 0.045*** 0.045*** 0.514*** 0.513*** 0.514*** Age and sex 35 to 44 years old male 0.002 0.002 0.003-0.043*** -0.043*** -0.043*** 45 to 64 years old male 0.021*** 0.022*** 0.021*** -0.083*** -0.082*** -0.083*** 65 to 74 years old male 0.042*** 0.044*** 0.042*** -0.059*** -0.059*** -0.059*** > 75 years old male 0.041*** 0.042*** 0.042*** -0.038** -0.038** -0.037** 16 to 34 years old female 0.066*** 0.066*** 0.066*** 0.070*** 0.070*** 0.070*** 35 to 44 years old female 0.017*** 0.017*** 0.017*** -0.050*** -0.051*** -0.050*** 45 to 64 years old female -0.020*** -0.019*** -0.020*** -0.107*** -0.106*** -0.106*** 65 to 74 years old female -0.012* -0.010-0.011* -0.096*** -0.096*** -0.095*** > 75 years old female -0.006-0.004-0.005-0.106*** -0.106*** -0.106*** Educaton 37
None 0.000-0.002-0.001 0.015 0.015 0.014 Prmary and secondary (cycle 1) Secondary (cycle 2) and postsecondary 0.000-0.001-0.001 0.022*** 0.021*** 0.021*** 0.000 0.000 0.000 0.026*** 0.026*** 0.026*** Actvty status Retred 0.022*** 0.023*** 0.023*** -0.016* -0.014-0.015* Unemployed 0.016*** 0.016*** 0.016*** -0.002-0.001-0.002 Student -0.041*** -0.041*** -0.041*** -0.002-0.001-0.002 Housework 0.035*** 0.034*** 0.036*** -0.001 0.000-0.001 Other 0.014 0.014 0.013-0.038* -0.037* -0.039* Autonomous Communty Andalucía -0.015*** -0.014*** -0.014*** 0.057*** 0.060*** 0.058*** Aragón 0.007 0.008 0.007 0.018 0.019 0.018 Asturas -0.017** -0.016** -0.017** 0.003 0.004 0.003 Balears 0.009 0.009 0.010 0.062*** 0.063*** 0.063*** Canaras -0.004-0.004-0.003 0.012 0.015 0.013 Cantabra 0.006 0.006 0.006 0.037* 0.039* 0.037* Castlla y León -0.003-0.003-0.002 0.007 0.009 0.007 Castlla la Mancha -0.009-0.008-0.008 0.042*** 0.045*** 0.042*** Cataluña 0.002 0.001 0.003 0.054*** 0.053*** 0.054*** Comundad Valencana -0.014*** -0.013*** -0.013*** 0.030*** 0.033*** 0.030*** Extremadura -0.011-0.010-0.009 0.055*** 0.057*** 0.056*** Galca -0.009-0.008-0.008 0.031*** 0.033*** 0.032** Murca -0.003-0.003-0.003 0.059*** 0.060*** 0.059*** Navarra -0.007-0.007-0.008 0.001 0.001 0.000 País Vasco -0.002-0.002-0.002-0.001 0.000-0.001 La Roja -0.021* -0.021* -0.022* -0.059** -0.057** -0.060** Prvate health nsurance 0.027*** 0.028*** 0.027*** -0.007-0.006-0.007 Natonalty Non Spanard 0.016*** 0.959*** 0.022*** 0.449*** Latn Amerca 0.024*** 0.071*** European Unon -0.002-0.036** Afrca 0.053*** 0.038* Europe -0.017-0.081*** Asa 0.038-0.018 North Amerca -0.067*** -0.101 Oceana 0.078-0.157* Year 2006-0.018*** -0.019*** -0.019*** 0.008* 0.008* 0.008* Pseudo-R 2 0.1203 0.1212 0.1221 0.1645 0.1653 0.1646 Log-L -13,792.6-13,779.3-13,765.5-24,407.9-24384.1-24405.2 N 49,123 49,124 49,123 49,123 49,124 49,123 Note: The astersks ndcate sgnfcance at the 1% level (***) 5% level (**) and 10% level (*) 38