Income-Related Health Inequalities in France between 1998 and 2002: Comparing Trends with Alternative Health Indicators

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1 Income-Related Health Inequaltes n France between 1998 and 2002: Comparng Trends wth Alternatve Health Indcators by Florence Jusot a, Lse Rochax a,b and Sandy Tubeuf* a,b Sept 2005 Work n progress * Correspondng author tubeuf@rdes.fr. IRDES 10, rue Vauvenargues PARIS Tel.: a IRDES (Insttut de Recherche et de Documentaton en Econome de la Santé) b IDEP(Insttut d Econome Publque), GREQAM(Groupement de Recherche en Econome Quanttatve d Ax-Marselle II) Abstract : The objectve of ths paper s to characterze the evoluton of ncome-related health nequaltes (IRHI) n France between 1998 and 2002, computng concentraton ndexes and decomposng them n explanatory factors. Two complementary approaches are offered here. The frst follows other European IRHI analyses, where self-assessed health s re-scaled and made contnuous, usng the 1994 Canadan HUI dstrbuton. The second uses an ndcator whch has been constructed specfcally for ths study and whch s based on addtonal health data from the same source as the SAH measure. Ths global health ndcator (GHI) uses, beyond SAH, a set of sem-contnuous varables measurng the number of dseases at ndvdual level together wth the mnmal vtal rsk and the dsablty that they generate. Changes nduced n ncome-related health nequaltes over tme wll be analysed usng both ndcators. The data comes from the 1998 and 2002 IRDES Health and Health Insurance Survey (HHIS) and s representatve of French households (about 20,000 ndvduals n 7,338 households). The decomposton method proposed by Wagstaff et al. (2001) s frst used to measure the respectve contrbuton of each IRHI explanatory factor on French data. The man contrbuton of ths paper, however, s a senstvty analyss performed by comparng the results under two alternatve health ndcators. The 2002 results show that, rrespectve of the health ndcator used, health s unequally dstrbuted. Yet the contrbuton of each IRHI determnant vares wth the ndcator. Ths s partcularly marked for actvty status and CMU-beneft. As for the evoluton between 1998 and 2002, rrespectve of the year or of the health ndcator used, health s unequally dstrbuted, favourng the rchest ndvduals, wth a stablty of the gradent over tme. Ths analyss leads to the concluson that the use of that or that other health ndcator s of consequence on the underlyng ncome-related health nequalty. Furthermore, ths analyss concludes that ncome s by far the most mportant factor explanng changes n IRHI, but the nature of ts contrbuton also dffers accordng to the health ndcator used. For the HUI-scaled ndcator, t s related to ts own dstrbuton wthn the populaton and not to the strong relatonshp that exsts between health and ncome, whereas the opposte result holds wth the second ndcator. In the same way, the contrbuton of factors (other than ncome) to the changes n IHRI vares accordng to the health ndcator used. Keywords: Self-assessed health Dseases severty ndex Inequalty Concentraton ndex Decomposton 1

2 1. Introducton The French health care system s based on the prncple of horzontal equty, accordng to whch ndvduals wth equal need should have dentcal access to care regardless of ther soco-economc status. But lower socoeconomc groups are known to have hgher rates of morbdty and mortalty than hgher socoeconomc groups. Moreover, health nequaltes between groups seem to ncrease over tme. For nstance, n France, whle over the perod , the mortalty of blue collar men aged was 1.8 hgher than that of ther whte collar counterparts, the rato ncreased to 1.9 between 1983 and 1991, to reach 2.1 between 1991 and 1999 (Montel & Robert-Bobée 2005). A seres of changes n the French health care system over the last ten years has gven rse to a new concern for health nequalty. Although the great majorty -98% of the French populaton- s covered by nsurance, ndvduals out of the labour market (unemployed wth no benefts, homeless ) were excluded from medcal nsurance cover untl Furthermore, the compulsory natonal health nsurance fund only covers between 70% and 80% of total health care cost. The remanng part s covered by a supplementary medcal health nsurance taken out voluntarly by ndvduals or n most cases by ther employers. Thus, 10% of the French populaton, most promnently the poorest-off, was stll uncovered by a supplementary health nsurance n Consequently, one of the most strkng polcy changes n that year has been the extenson by Law of free access to medcal care to a larger number of ndvduals wth low ncome, through a unversal healthcare coverage, called the Couverture Malade Unverselle (CMU). Besdes grantng access to compulsory medcal nsurance, ths reform provdes the poorest 4.5 mllon ndvduals wth a free supplementary health nsurance and exempts them from out-of-pocket payments and Avance de fras 1 for ther health care consumpton (Bosguérn, 2005). Pror to the mplementaton of CMU, a lmted cover was granted to the poorest and sckest-off through AMG (Ade Médcale Gratute) but t vared substantally across French départements. Its extent was, however, farly lmted, manly exemptng ndvduals from havng to pay the tcket modérateur 2 whle offerng no cover for balance-bllng by provders or for optcal or dental care. Ths reform has reduced dfferences n health care consumpton. For an equvalent state of health, CMU benefcares use of healthcare s comparable n level to the populaton wth a supplementary health nsurance, even though some dfferences reman n the actual mx of care (Raynaud, 2003 ; Grgnon & Perronnn, 2003). However, the effcacy of ths program n reducng socal nequaltes n health has not yet been fully assessed. The only outcome measure s that by the end of 2000, CMU benefcares declared more frequently than non-benefcares that ther health status had mproved durng that year (Raynaud, 2003). By concentratng on the perod before and after CMU mplementaton ( ), one of the objectves of ths paper s to analyse the evoluton n ncome-related health nequaltes (IRHI) n 1 In France, doctors consultatons and drugs must be pad n full (wth exceptons) at the tme of use and reclamed afterwards (the so-called Avance de fras ) 2 The tcket modérateur s the copayment, after refundng by the French Natonal Health Insurance fund. It s a mnmum partcpaton of the person nsured to hs/her health expenses. It can however, be partly or fully refunded by a supplementary ndvdual health nsurance. See Rochax L. and Hartmann L. for a presentaton of recent changes n the French health care system. 2

3 France over that perod, computng concentraton ndexes and decomposng them n explanatory factors. Although assessng the mpact of ths reform on health nequaltes would requre a longer tme horzon than just two years, the present analyss also provdes a useful step n the evaluaton of ths reform, nasmuch as CMU benefts n 2002 are lkely to be mportant determnants of changes n ncome-related health nequalty. Consderng that the level of ncome-related health nequalty evdenced n emprcal studes may depend on the health ndcator used (Couffnhal et al., 2004), the second contrbuton of ths paper s to carry out a senstvty analyss, by comparng results from two alternatve health ndcators. The frst s the wdespread cardnalsed self-assessed health (SAH). The second uses an ndcator whch has been constructed specfcally for ths study and whch s based on addtonal health data from the same source as the SAH measure. Ths global health ndcator (GHI) uses, beyond SAH, a set of semcontnuous varables measurng the number of dseases at ndvdual level together wth the mnmal vtal rsk and the dsablty that they generate. The frst secton focuses on methodology, and presents the two alternatve IRHI ndcators. The second presents the data and varables defnton. The emprcal results are analysed n the thrd secton. Dfferences n IRHI n 2002 accordng to the health ndcator used are frst analysed before turnng to changes n IRHI between 1998 and 2002 and comparng trends wth alternatve health ndcators. The last secton concludes wth a dscusson of these results. 2. Methods 2.1. Measurng health Most of the recent nternatonal health nequalty studes rely on the noton of self-assessed health (SAH) or ndcators constructed on SAH nformaton as a measure of health (Van Doorslaer & Koolman, 2005). Ths wdespread use of SAH can be partly attrbuted to the ease wth whch such nformaton can be collected. The two health ndcators that wll be used n the followng analyss are also derved from SAH nformaton. In the IRDES 1998 and 2002 HHIS, self-assessed health s collected usng the followng queston: Could you grade your health status from 0 to 10? (wth 0 beng the lowest health status). Ths analogcal scale s slghtly dfferent from the more wdespread SAH queston promoted by the European Offce of WHO, whch conssts n categores rangng from very good to very poor 3. The SAH dstrbuton n the HHIS surveys s hghly skewed as a great majorty report a level of health hgher than 7. The skewness s also manfest n the nter-category dstances, much smaller between levels 7 to 10 than between 0 and 6. Ths health measure varable beng ordnal and categorcal, t must be changed nto one of two polar cases to measure nequaltes adequately: ether a dchotomous or a cardnal varable. A contnuous health ndcator s generally preferred to a dchotomous one, n order to avod both nformaton losses and cut-off pont dependency (Van Doorslaer & Jones, 2003). The method used to cardnalse SAH conssts n assumng that the 3 In the IRDES 2002 HHSI, ths 5-pont scale s ncluded for one half of the sample, along wth the orgnal 10- pont scale. A comparson of the two scales has been performed and shows that a score between 8 and 10 appears to be equvalent to categores good and very good grouped together ( Jusot et al., 2005a). 3

4 categorcal ordnal varable reflects a contnuous latent varable, whch descrbes the populaton s health status, and then choosng ether an arbtrary or a known health dstrbuton on whch to scale the dfferent categores of the varable Cardnalsaton of SAH wth an arbtrary dstrbuton In the lterature two arbtrary dstrbutons for the latent health varable are used: the lognormal dstrbuton (Wagstaff & Van Doorslaer, 1994) and the normal one consstng n an ordered Probt regresson (Cutler & Rchardson, 1997). The former s often encountered n the ncome-related health nequaltes lterature and reles on the assumpton that a contnuous health varable underles the ordnal categorcal health varable. Ths latent varable s dstrbuted accordng to the opposte of a lognormal dstrbuton. In the same way, n the second case, t s assumed that there exsts an underlyng contnuous health varable to the categorcal varable but t s estmated usng an ordered Probt and then rescaled onto the [0,1] nterval, usng the hghest and the lowest predcton. These two methods have been crtcsed for the arbtrarness of the choce of dstrbuton (Van Doorslaer & Jones, 2003). Indeed, n the same way that concentraton ndces, for example, depend on the shape of the dstrbuton, the health nequalty measure wll also be arbtrary. Moreover, the self-assessed health varable s assumed to be contnuous but the underlyng nformaton s stll categorcal. Also, an ordnary least square regresson cannot be used and ntra-categorcal dfferences are not consdered Cardnalsaton of SAH wth a health dstrbuton In vew of these lmtatons, Van Doorslaer & Jones (2003) have advocated rescalng SAH by a health dstrbuton. A frst applcaton of the nterval regresson method was defned on Canada, usng a health dstrbuton derved from the Canadan Natonal Populaton Health Survey (CNPHS), namely the Health Utlty Index (HUI), to rescale the Canadan SAH (Van Doorslaer & Jones, 2003). In ths context, the cumulatve dstrbuton functon of the HUI was used as the benchmark, from whch the thresholds defnng the HUI ntervals correspondng to each SAH level are derved. The same thresholds were then used for all European countres (Van Doorslaer & Koolman, 2005), assumng that dstrbutons of health were comparable to the Canadan one. The authors conclude that ths s the best procedure n terms of ablty to represent both the dstrbuton of generc health from SAH categores and the set of covarates used n the nterval regresson model. In the end, a predcton of each ndvdual s level of health utlty s computed from the observed SAH level. We wll frst apply ths method to our data and use the emprcal dstrbuton of the HUI n the 1994 CNPHS to cardnalse the French SAH varable n both surveys. In so dong, we assume that there s a stable mappng from ths HUI dstrbuton to the latent health varable that determnes SAH and that t can be appled to the French populaton. As noted before, there are also eleven thresholds to consder snce SAH s collected on a 10-pont scale n France: 0 (the worse possble status), 0.293, 0.335, 0.35, 0.394, 0.428, 0.696, 0.756, 0.852, 0.926, 0.947, and 1 (the best possble status). 4

5 The Global Health Indcator (GHI) We propose an alternatve method to derve a contnuous health ndcator. Rather than usng a contnuous health dstrbuton wth whch to rescale the SAH ndcator, we use addtonal nformaton avalable at ndvdual level n order to estmate a latent varable of true health (Perronnn, Rochax & Tubeuf, 2005). Indeed, even f SAH s now recognzed as a good ndcator of true health (Idler & Benyamn, 1997), t stll suffers from varous reportng bases related, among other factors, to age, gender and socoeconomc characterstcs. Therefore, n order to better capture true health, t seems mportant to correct SAH from these reportng bases by usng avalable nformaton n the survey beyond SAH. In partcular, we consder the total number of self-reported dseases, each one weghted by a severty ndex based both on the dsablty level and on the vtal rsk t generates. The vtal rsk ndcator captures the dsutlty from lfe expectancy loss whereas, the dsablty ndcator evaluates the dsutlty due to the presence of a dsablty and the assocated loss of lfe qualty For years, researchers from the IRDES have developed successve tests methods, n close cooperaton wth doctors and statstcans to generate mnma levels of vtal rsk and dsablty for each dsease. Ther work conssts n assgnng a vtal rsk and a dsablty level for each reported dsease n reference to the Internatonal Classfcaton of the Dseases and n the absence of other nformaton. It s assumed that other dseases from whch the ndvdual could suffer, could only ncrease the vtal rsk and the dsablty level, but n no case reduce them. Each dsease s thus postoned on a mnmum vtal rsk scale of sx ponts and a mnmum dsablty level scale of seven ponts. These two scores provde an ndcaton of a dsease s severty. Beyond, snce ndvduals lvng n the same household are lkely to assess ther health status n comparable ways, takng nto account potental clusters effects seems relevant. Thus, a random effect model s used to estmate health determnants wth equvalent health statuses. subj Formally, the procedure to generate ths global health ndcator conssts n defnng h, namely SAH and a latent varable of true health subj * h as h = h = g( f ( h *, X, u, u ; α, β ) * D j (1bs) where j=1,,j s the degree of severty, defned on the bass of the scores on both dsablty and vtal rsk ndces, D j, s the number of dseases of severty j that the ndvdual has reported n the survey, ; α ) X s a vector of ndvdual characterstcs that may nduce reportng bases, namely age, gender and socoeconomc characterstcs, u s an ndvdual dosyncratc error term and u HH s a household dosyncratc error term HH (1) 5

6 The model generates an estmate of the true health and the parameter estmates αˆ j are also used as weghts to obtan robust SAH ndcators, as proposed n Lndeboom & Van Doorslaer (2004). In the end, the cardnal health ndcator s constructed for each ndvdual by multplyng the number of declared dseases (weghted by the severty-nduced level of dseases) by the estmated parameters. Thus, the GHI s gven by j GHI = αˆ D j j j= 1 (2) Ths new ndcator s contnuous 4. We consdered two defntons of GHI: n the frst verson, we only correct for age and gender whle n the second we further correct for socoeconomc characterstcs. Indeed, whle the lterature on SAH unambguously shows the exstence of reportng bases due to gender and age (Baron-Epel & Kaplan, 2001; Van Doorslaer & Gerdtham, 2003), the exstence of a potental reportng bas nduced by socoeconomc characterstcs s stll debated (Kerkhofs & Lndeboom, 1995; Shmuel, 2003; Van Doorslaer et Gerdtham, 2003). As a result, we compare the changes n the evoluton of IRHI between 1998 and 2002, usng HUI and verson 1 of GHI Explanng health nequalty Some of the work on nequaltes n health s concerned wth pure nequaltes n health -.e. defned on a sngle dmenson- (Gakdou et al. 2000), but the present research focuses on multdmensonal nequaltes n health, n partcular, the varaton n health whch s systematcally related to socoeconomc status. In the ncome-related health nequalty lterature, concentraton ndces and curves were frst ntroduced by Wagstaff et al. (1989) and have snce been successfully used to descrbe and measure the degree of nequalty n varous measures of health, health care or n health care payments. The concentraton ndex provdes a measure of socoeconomc nequalty n health, ntutvely comparable to the Gn ndex whch s commonly used n pure health nequalty measurement. The two measures dffer n the rankng varable used: n the two-dmensonal case, ncome s used rather than health n the Gn of health (Le Grand, 1987). The concentraton ndex compares the cumulatve proporton of the populaton ranked by ncreasng ncome on the X-axs wth the cumulatve proporton of health on the Y-axs. It ranges between 1 and 1. The CI s 1 (resp. +1) when all health s concentrated n the poorest (resp. the rchest) person. A value of 0 s nterpreted as an equal dstrbuton of health over ncome,.e. for any p, a p proporton of ndvduals ranked accordng to ther ncome receves a p proporton of health. 4 For practcal reasons, GHI s re-scaled to be used on a [0;1] nterval. Thus, ' GHI mn( GHI ) GHI = mn( GHI ) 6

7 More formally, let us defne y as the measure of health of ndvdual, wth R the cumulatve proporton of the populaton ranked by ncreased ncome. The concentraton ndex of ncome-related health nequalty s gven by: where y = E y ). ( 2 C = cov(y, R ) y (3) The decomposton method Concern has been expressed wth respect to the economc ntuton behnd concentraton ndces. As a result, research has focused on the decomposton of the concentraton ndex nto ts varous determnants. A decomposton method was then ntroduced to observe nequalty and to dentfy ts sources (Wagstaff et al., 2003). Let us assume that the followng lnear regresson model defnes the measure of health of ndvdual accordng to the k regressors: K 0 + β k k + ε k = 1 y = β x (4) whereε s a random error term assumed to have expected mean value equal to zero and constant varance and K, the number of regressors. The β k are assumed constant for every ndvdual. By substtutng n the prevous concentraton ndex equaton, we obtan: x K k C = β k C k + cov, k = 1 y y (5) The concentraton ndex s also assumed to be made up of two components: an explaned one, equal to a weghted sum of the concentraton ndces of the k regressors and a resdual component. The weght represents the estmated health elastcty wth respect to regressor k, as: η k = β k (6) The estmated health nequalty s also expressed as a sum of nequalty n each of ts determnants, each weghted by hs own health elastcty. Ths decomposton method emphaszes the contrbuton of each regressor to the explanaton of IRHI and gves each regressor s respectve mpact on health and also the degree of nequalty of ts own dstrbuton wth respect to ncome. x k y 2 ( ε R ) 7

8 Decomposton of nequalty over tme The decomposton of the changes over tme between the two concentraton ndces reles on the Oaxaca decomposton methodology (Oaxaca, 1973) and on the approach proposed by Wagstaff et al. (2001). It conssts n wrtng the dfference between the concentraton ndces of the populaton at the two tme perods: CI 1998 k2002 k2002 k1998 k1998 k2002 k1998 k k (7) Not only can the dfference n measurement of the ncome-related health nequalty be decomposed but the contrbuton of each regressor to these changes may also be evaluated, thus: CI k = η k η ( CI CI ) + CI ( η = CI CI = η 2002 ( CI CI ) + CI ( η η k1998 k2002 k1998 As the decomposton of the changes s also expressed n elastcty parameters, the dfference between the two perods s explaned by two terms: the nequalty n the dstrbuton of the regressor (dfferences between the two CI) and the nequalty related to the regressor s specfc lnk wth health (dfferences between elastctes). Moreover, the relatve mportance of the nequalty compared to the health elastcty component n the contrbuton of each varable can be assessed by computng both the relatve excess elastcty and the relatve excess nequalty over tme. ) ) (8) 3. Data and varable defnton The data comes from the 1998 and 2002 IRDES Health and Health Insurance Survey. The IRDES- HHIS s representatve of French households, covers about 20,000 ndvduals (about 7,338 households) and s carred out every two years. Although half of the sample s re-ntervewed every four years, we treat each wave separately to carry out cross-secton analyses. Surveys were conducted wth some degree of varaton n the questonnare wordng and scope, but the sample selected compares populatons wth smlar characterstcs over tme. It provdes nformaton on soco-economc and demographc characterstcs, as well as on health status and health nsurance coverage. Each household flls a medcal consumpton record durng a month. All pharmaceutcal expendtures, hosptal and ambulatory consultatons are also reported. The analyss s restrcted to the workng-age populaton.e. ndvduals aged 16 to 60. The lower bound s also justfed by the fact that ndvduals under 16 do not assess ther own health. Fnally, ndvduals wth ncomplete health questonnares and those who dd not answer some of the socodemographc questons were also excluded. In the end, the sample contans 8,699 ndvduals n 1998 and 6,837 ndvduals n Samples are corrected to account for the under-representaton of the severely ll and the elderly n the surveys. The rankng varable s the equvalent household ncome, usng the OECD scale. In the IRDES-HHIS, ndvduals are asked for a detaled set of questons on ncome ncludng an ncome bracket and a 8

9 contnuous value. When ths value s unknown, the medan of the bracket s used to compute the equvalent household ncome. Detaled socal, health and demographc varables are also avalable at ndvdual level. Ten agegender categores are created for men and women aged 16-25, 26-35, 36-45, 46-55, and lastly, Three levels of educaton are consdered (low, medum, hgh). Employment status has sx modaltes: employed, unemployed, nactve, lookng after famly/home, retred and student. Health nsurance varables are also recorded, ndcatng whether the ndvdual s covered by prvate health nsurance beyond compulsory nsurance or by the AMG n 1998 or the CMU complementary nsurance n The omtted reference ndvdual s a young man, less educated, wth no prvate nsurance and n employment. 4. Results: Dfferences n ncome-related health nequalty n 2002 accordng to the health ndcator We frst present the estmated coeffcents of the regresson. Second, the varous concentraton ndces for both dependent and ndependent varables are computed and dscussed. Thrd, health nequalty contrbutons are analysed for each year usng both ndcators to test for senstvty What are the relatonshps between the determnants of health and the health varables? The estmated parameters explan the relatonshps between socoeconomc characterstcs and the measurement of the health varable. These relatonshps are comparable n terms of sgns -when sgnfcant- for both health ndcators and for the two years (Table 1). Besdes, the estmated parameters of the two GHI versons (verson1 when correctng for age and gender only and verson 2 when correctng for age, gender and socoeconomc condtons) are smlar n the same year. Thus, we do not dstngush between them n the followng paragraph. As ndvduals become older, ther health status deterorates. Ths relatonshp s slghtly stronger for women for both HUI and GHI. Both ndcators ncrease wth equvalent ncome. As for the relatonshp between health and educaton, we fnd that both prmary/secondary and hgh school levels have a sgnfcant and postve nfluence on health status. There s an nverse relatonshp between voluntary health nsurance and health (although t s nsgnfcant for 1998, usng HUI). The scker appear to take out supplementary health nsurance more readly, a fndng whch could tentatvely be nterpreted n terms of adverse selecton. There s also a negatve relatonshp between health and beng a CMU benefcary over tme but t s only sgnfcant for GHI. Intuton on the sgn of these estmated parameters can be found n the CMU elgblty condtons,.e. very low ncomes often mplyng low health statuses too. A smlar concluson s found n a recent analyss (Bosguérn, 2005), whch showed that ndvduals tend to apply for CMU-beneft f they antcpate health care needs. Lastly, parameters on the actvty status varable provde us wth nformaton on the relatonshp between health and socal characterstcs. 9

10 Unsurprsngly, the effect of beng a student s the only factor wth a postve relatonshp wth health, students health status beng better than other employed because of an age effect. Compared to the employed, nactvty, unemployment and retrement statuses have a negatve and sgnfcant correlaton wth health, rrespectve of the health ndcator. Compared to the general populaton, unemployment or nactvty s assocated wth an excess mortalty for both men and women. Ths result s n lne wth recent fndngs whch show that n the fve years followng unemployment, the annual rsk of death for an unemployed s, at comparable age, approxmately three tmes hgher than that of the general populaton (Mesrne, 2000). Moreover, before the age of 60, a bad health status has been found a good predctor of nactvty, retrement and unemployment, four years later (Jusot et al., 2005b) How unequal s each dependent or ndependent varable dstrbuton compared to that of ncome? The frst step of the decomposton method allows to analyse the concentraton ndces of each dependent and ndependent varables over the ncome dstrbuton (Table 2). The two frst lnes show the dstrbuton of the two health ndcators over ncome. Irrespectve of the year or of the health ndcator used, health s unequally dstrbuted, favourng the rchest ndvduals, wth a stablty of the gradent over tme. The concentraton ndces for the determnants of health are dentcal for both HUI and the two versons of GHI as the nequalty s measured over the same rankng varable, whch s ndependent of the health dmenson. The target varable here, namely the equvalent ncome, nduces an nequalty obvously n favour of the rch, whch decreases over tme. The concentraton ndex obtaned for ncome s n fact a Gn ndex. As expected, ncome nequalty and ncome-related health nequalty have the same sgn, the ncome one beng larger. Wth respect to the age-gender categores, t s clear that the youngest and the mddle-aged women are concentrated n lower ncome groups, although nequalty generally decreases over tme. Older women are concentrated n the hgher ncome groups, although nequalty decreases over tme. The same pattern s observed for both oldest men and others age groups wth a stronger decrease n the two mddle-aged groups. Besdes, an ncome nequalty favorng men s observed but decreases over tme. The most-educated ndvduals are hghly concentrated n the rchest ncome groups, and the ncome nequalty nduced slghtly decreases over tme. The prmary/secondary school level s concentrated n the rchest n 1998, but ts mpact decreases over tme and s concentrated n the poorest n Unemployed, ndvduals undertakng famly/home care and the nactve are hghly concentrated n the lower ncome groups. Unlke those n nactvty for whom concentraton ndces are stable, the concentraton ndex n unemployment slghtly decreases over tme. Concernng retred people, an nequalty favourng the rchest-off s observed. As the sample only ncludes ndvduals between 16 and 60, most of those who have retred before 60 have ether done so for ther bad health (whch would explan at least partly the postve concentraton ndex) or for general economc reasons. 10

11 Fnally, concentraton ndces concernng health nsurance accord wth prmary ntuton. The supplementary health nsurance mples a pro-rch ncome nequalty, whch s stable over tme. The CMU hghly favours the poorest-off snce t s means-tested. The concentraton of CMU benefcares n the lowest ncome groups decreases over the tme perod How does each regressor contrbute to the yearly health nequalty and how does ths vary accordng to the health ndcator used? Irrespectve of the health ndcator used, each regressor contrbutes n the same way to the health nequalty (the contrbutons values have dentcal sgns). For both years however, CMU-benefcary, nactvty, retrement and gender show mportant dfferences accordng to the health ndcator used. Indeed, the postve contrbuton of beng a CMU-benefcary s more marked usng GHI n 2002, whether under verson 1 or 2. Clearly new CMU benefcares have a better access to health care so that ther dseases are better dagnosed and therefore better declared. As for gender t appears that both for 1998 and 2002, contrbutons to health nequalty are hgher for men under HUI and for women under GHI. An explanaton s that GHI s based on the number of reported dseases and there s some evdence of a hgher tendency for women to report dseases more (Auvray et al., 2003). Because of ther hgher number of doctors consultatons, women are more lkely to know exactly the dseases they suffer from (Auvray et al., 2003). Dfferences n the contrbuton of nactvty status are sgnfcant n 1998 and are more marked usng HUI. Ths dfference may be due to the fact that because GHI corrects for reportng bas due to age, t reduces the contrbuton of nactvty to health nequalty. Dfferences n the contrbuton of retrement are also of nterest and t appears to be more marked n 2002, wth hgher values under both versons of GHI compared to HUI. One nterpretaton of ths effect may be that t s those n poor health and dagnosed dseases who tend to leave the labour market earler. Alternatvely, ths result could be explaned consderng Bound s (1990) pont of vew accordng to whch workers are n fact encouraged to take earler retrement and they justfy ther behavour by declarng health lmtatons or dseases. Income mples very slght dfferences n 1998 as n 2002 and ts contrbuton to health nequalty s hgher wth HUI. The contrbuton of educaton remans unchanged whchever health ndcator used. 5. Results: Income-related health nequaltes n France between 1998 and 2002: comparng trends usng HUI and GHI Changes between varables over tme n terms of means n the two surveys are frst reported. We then turn to changes n ncome-related health nequaltes over tme. Results concernng dfferences between health ndcators are systematcally reported. 11

12 5.1. What are the changes n the determnants of health between 1998 and 2002? The mean value of the health measure, whether n HUI or GHI terms, slghtly decreases between 1998 and 2002 (table 4). An explanaton for ths health status deteroraton s the hgher number of older ndvduals n the 2002 survey. The mean value of equvalent ncome ncreases over the same perod. If we compare to overall French statstcs, we fnd that the mean value of equvalent ncome for the ncome class n 1998 was about 16,208 euros per year and 17,879 euros per year n The value of equvalent ncome s therefore underestmated n the two surveys: n 1998, ts value s 1,167 euros per month and 1,382 n The proporton of hghly educated ndvduals between the two surveys ncreases. Concernng supplementary health nsurance, the proporton of ndvduals wthout supplementary health nsurance reduces from 10% n 1998 to 6.4% n Regardng employment status, the data shows that the modalty beng n employment s that whch changes most (64.5% n 1998 and almost 70% n 2002). The number of unemployed slghtly decreases over tme whle unemployment rates have fallen more markedly n France over that perod (from 11,3% n December 1998 to 9.1% n December respectvely from 13.84% to 10.10% for women, and from 10.20% to 7.80% for men). The proporton of ndvduals lookng after famly/home as well as that of retred and nactves are the same over tme. As for students, the proporton reduces by 4 ponts n 2002, whch s consstent wth the ageng of the populaton n 2002 prevously mentoned How do the changes n the determnants of health explan the change n ncomerelated health nequalty over tme? The decomposton method prevously presented gves the contrbuton of each determnant of health to the changes n ncome-related health nequalty between 1998 and The last lne n table 5 gves the value of the total change n the ncome-related health nequalty over tme both wth HUI or wth GHI (verson 1).Ths total change s postve both wth HUI and GHI, so that IRHI slghtly ncreases from 1998 to By far, the two regressors whch explan most of the changes n IRHI over tme are ncome and nactvty. Concernng the former, ts strong contrbuton s explaned both by a decrease n the concentraton ndex of nequalty n ncome over tme and by a change n the elastcty of health whch s dfferent accordng to the health ndcator. Wth HUI, ts contrbuton s also due to an ncrease n the elastcty of health wth respect to ncome, whereas for GHI, ts stronger effect s rather drven by a reducton n the elastcty of health wth respect to ncome. These results are hardly surprsng. Intutvely, the mpact of CMU may ncrease the poorest s health satsfacton by ncreasng access to care. As HUI contans a more subjectve dmenson than GHI, we therefore expect a hgher ncome elastcty of health measured on a sole subjectve assessment (HUI) than on GHI whch adds a more objectve dmenson: the number of dseases. As to the contrbuton of nactvty, rrespectve of the health ndcator, t s by far much more explaned by an ncrease n the elastcty of health wth respect to nequalty than changes n ts ncome-related nequalty. A smlar result s found n Montel & Robert- 12

13 Bobée (2005). Agan, ncreases n elastcty are dfferent under the two health ndcators, wth that of GHI beng more szeable. Irrespectve of the health ndcator, the other actvty status categores, except retrement, contrbute to a reducton of IRHI. Although the contrbuton of lookng after famly/home s almost the same for both health ndcators, others actvty statuses dffer from one to another. Unemployment decreases the ncome-related health nequalty especally when health s measured wth HUI. Its mpact s explaned more by an ncrease n the elastcty of health wth respect to unemployment than by a change n nequalty over the dstrbuton of ncome. The contrbuton of retrement s also mportant wth HUI health varable and due to changes n elastcty. As a matter of fact, when health s measured by the HUI, actvty strongly contrbutes toward explanng the ncrease n the IRHI. On the other hand, contrbutons of the health nsurance to the changes n nequalty over tme are also of nterest. Concernng supplementary health nsurance, ts contrbuton to changes s relevant wth both HUI and GHI but hgher wth the former. In both cases, the reducton of IRHI s exclusvely explaned by changes n the elastcty of health wth respect to havng a prvate nsurance coverage. Whereas the changes n the elastcty of health under HUI are drven by a reducton (the relatve change n the elastcty of health s negatve), those of the other health ndcator concern an ncrease(the relatve change n the elastcty of health s postve). As for the CMU-coverage, ts mpact on the changes dffers from one ndcator to the other. In the HUI case, access to a unversal cover contrbutes to reducng the changes (a negatve contrbuton). Ths reducton s drven by the change n the CMU-benefcares nequalty over the dstrbuton of ncome. In the GHI case, the CMU regressor contrbutes postvely to the changes n the IRHI over tme, dsplayng a marked postve partal assocaton wth health. The level of educaton has a lower mpact, though apprecable, on changes n IRHI, compared to the varables prevously analysed. Irrespectve of the health ndcator, educaton contrbutes to a reducton n IRHI. Ths reducton s more marked, whatever the level of educaton, when health s measured by HUI and wth hgher educaton level only when health s measured by GHI. Observng these results, one may note that generally, elastcty dfferences are more lkely to domnate concentraton ndces dfferences. 6. Summary and conclusons In ths paper, we have analysed nter-ndvdual ncome-related health dfferences n France. Yet the orgnalty of the paper les manly n the comparson n nequalty measurement offered by two alternatve health ndcators, wth evdence of some varatons n the results. Actvty status, namely nactvty and retrement, contrbutes dfferently to health nequalty. These results tend to hghlght the fact that the choce of the health ndcator s not trval and the comparson also contrbutes towards testng the robustness of the results to the choce of a health ndcator. Wth respect to tme changes, the results show that there s ndeed an ncome-related health nequalty favourng the hgher ncome group n France, wth a stablty of the gradent over tme. The decomposton analyss leads to the concluson that ncome and actvty status are by far the most mportant factors explanng these changes n ncome-related health nequaltes. Dependng on the 13

14 health ndcator used, we fnd that t s more related to the strong ncreasng relatonshp that exsts between health and ncome n the case of the new global health ndcator (GHI) whle t s manly attrbutable to the own dstrbuton of ncome wthn the populaton under HUI. In the same way, other socal factors contrbute to the ncrease n nequalty, n partcular, nactvty. However, the changes observed n ths analyss were not statstcally tested. In effect, t could be useful n the future to apply a bootstrap method to assess samplng varablty and obtan standard errors for the estmates of both the whole of concentraton ndces and elastctes. References Baron-Epel O. & Kaplan G., (2001), General subjectve health status or age-related subjectve health status: does t make a dfference?, Socal Scence and Medcne, 53, Bosguérn B. (2005), Les bénéfcares de la CMU au 31 décembre 2003, Etudes et Résultats, 381. Couffnhal A., Dourgnon P. a,d Tubeuf S., (2004), Outls de mesure des négaltés de santé : quelques débats d actualté, n Inégaltés socales de santé, Santé, Socété et Soldarté, n 2 Gakdou EE., Murray CJ. and Frenk J., (2000), Defnng and measurng health nequalty: an approach based on the dstrbuton of health expectancy. Bulletn of the World Health Organzaton, 78(1): Grgnon & Perronnn, (2003), Impact de la couverture malade unverselle complémentare sur les consommatons de sons. Questons d'économe de la santé n 74. Sére "Analyses". Novembre Jusot F., Khlat M., Rochereau T., Sermet C. (2005a), "Les tnérares professonnels en relaton avec la santé : une explotaton longtudnale de l enquête ESPS de l IRDES", ntermedate report (Health and Labor program, MIRE, DARES, DREES, La Poste). Jusot F., Khlat M., Rochereau T., Sermet C. (2005b), "The role of ll-health as a precursor of unemployment n France", 5th World Congress of the Internatonal Health Economcs Assocaton, July , Barcelona. LeGrand J., (1987), Inequaltes n health. Some nternatonal comparsons. European Economc Revew;31: Kerkhofs M. & Lndeboom M., (1995), Subjectve health measures and state dependent reportng errors. Health Economcs 4, Lndeboom M. and Van Doorslaer E., (2004), Cut-pont shft and ndex-shft n the self-reportng of health, Journal of Health Economcs, Forthcomng Mesrne A., (2000), La surmortalté des chômeurs : un effet catalyseur du chômage?, Econome et Statstque, N : Montel C., Robert-Bobée I.(2005), «Les dfférences socales de mortalté : en augmentaton chez les hommes, stables chez les femmes», Insee Premère, 1025 Perronnn M., Rochax L. & Tubeuf S., (2005), Measurng health: Constructon of a key ndcator on health status, Poster presented at the XXV th Internatonal Populaton Conference organzed by the Internatonal Unon for the Scentfc Study of Populaton, Tours (France), July Rochax L. and L. Hartmann, The French Publc-Prvate Mx, n The Publc-Prvate Mx for Health Care, ed. A.K. Maynard, Radclffe,

15 Shmuel A., (2003), Soco-economc and demographc varaton n health and n ts measures : the ssues of reportng heterogenety. Van Doorslaer E. et Gerdtham U. G., (2003), Does nequalty n self-assessed health predct nequalty n survval by ncome? - Evdence from Swedsh data. Socal Scence and Medecne, 57, 9 Van Doorslaer E. and Jones AM., (2003), Inequaltes n self-reported health: valdaton of a new approach to measurement, publshed n Journal of Health Economcs, Volume 22, Issue 1, Van Doorslaer E, Koolman X., (2005), Explanng the dfferences n ncome-related health nequaltes across European countres, Health Economcs, Forthcomng Wagstaff A., Pac P. and Van Doorslaer E., (1991), On the measurement of nequaltes n health, Socal Scence and Medcne, 33, 5, Wagstaff A. and Van Doorslaer E., (1994), Measurement of health nequaltes n the presence of multple-category morbdty ndcators, Health Economcs, 3, Wagstaff A., van Doorslaer E., Watanabe N., (2001), On Decomposng the Causes of Health Sector Inequaltes wth an Applcaton to Malnutrton Inequaltes n Vetnam, World Bank. Polcy Research Workng Paper n

16 Emprcal results Table 1: Estmated regresson parameters accordng to the health ndcator used Interval Regresson Coeffcents Regresson Coeffcents GHI AgeSex Regresson Coeffcents GHI AgeSexSES Interval Regresson Coeffcents Regresson Coeffcents GHI AgeSex Regresson Coeffcents GHI AgeSexSES Constant 0,843 0,921 0,917 Constant 0,812 0,934 0,931 lnnc 0,012 0,004 0,004 lnnc 0,012 0,002 0,002 male26_35-0,005 0,010 0,011 male26_35 0,006 0,020 0,021 male36_45-0,028-0,009-0,010 male36_45-0,018 0,001 0,001 male46_55-0,055-0,034-0,036 male46_55-0,056-0,039-0,040 male56_60-0,067-0,073-0,076 male56_60-0,071-0,060-0,061 fem16_25-0,007-0,011-0,012 fem16_25 0,000 0,000 0,000 fem26_35-0,012-0,013-0,014 fem26_35-0,010-0,014-0,014 fem36_45-0,030-0,033-0,036 fem36_45-0,026-0,031-0,032 fem46_55-0,073-0,086-0,091 fem46_55-0,063-0,082-0,085 fem56_60-0,072-0,132-0,139 fem56_60-0,088-0,116-0,119 edu_2 0,012 0,007 0,007 edu_2 0,017 0,013 0,013 edu_3 0,012 0,005 0,005 edu_3 0,013 0,003 0,004 sh_prvate 0,004-0,008-0,009 sh_prvate 0,000-0,016-0,016 sh_cmu -0,013-0,008-0,008 sh_cmu -0,010-0,037-0,037 act_nactve -0,189-0,116-0,119 act_nactve -0,188-0,170-0,171 act_housewk -0,014-0,004-0,004 act_housewk -0,017 0,002 0,003 act_retred -0,051-0,059-0,062 act_retred -0,020-0,071-0,072 act_unempld -0,027-0,015-0,016 act_unempld -0,022-0,019-0,020 act_student 0,006 0,012 0,013 act_student 0,019 0,021 0,021 Sgnfcatvty n bold type, p<0.05 Sgnfcatvty n bold type, p< Table 2: Concentraton ndces of regressors n 1998 an 2002 Concentraton ndces of dependent & ndependent varables predcted HUI 0,0061 0,0064 predcted GHI AgeSex 0,0005 0,0014 predcted GHI AgeSexSES 0,0004 0,0015 lnnc 0,048 0,037 male26_35 0,070 0,039 male36_45 0,017-0,041 male46_55 0,142 0,073 male56_60 0,154 0,138 fem16_25-0,219-0,118 fem26_35-0,002 0,023 fem36_45-0,054-0,052 fem46_55 0,120 0,063 fem56_60 0,175 0,155 edu_2 0,003-0,021 edu_3 0,280 0,196 sh_prvate 0,066 0,054 sh_cmu -0,762-0,619 act_nactve -0,384-0,331 act_housewk -0,229-0,255 act_retred 0,215 0,190 act_unempld -0,376-0,302 act_student -0,170-0,112 16

17 Table 3: Health nequalty contrbutons of the regressors n 2002 and 1998 accordng to the health ndcator Health nequalty contrbutons of regressors n 1998 per health ndcator predcted HUI Sum of Contrb predcted GHI AgeSex Sum of Contrb predcted GHI AgeSexSES Sum of Contrb Contrb Contrb Contrb CI pred 0,0061 0,0005 0,0004 lnnc 0,0006 0,0006 0,0002 0,0002 0,0002 0,0002 male26_35 0,000 0,001 0,001 male36_45-0,001 0,000 0,000 male46_55-0,009-0,005-0,006 male56_60-0,012-0,021-0,012-0,017-0,013-0,018 fem16_25 0,002 0,003 0,003 fem26_35 0,000 0,000 0,000 fem36_45 0,002 0,002 0,002 fem46_55-0,010-0,011-0,012 fem56_60-0,014-0,020-0,025-0,032-0,027-0,034 edu_2 0,000 0,000 0,000 edu_3 0,004 0,004 0,001 0,001 0,001 0,001 sh_prvate 0,000 0,000-0,001-0,001-0,001-0,001 sh_cmu 0,011 0,011 0,006 0,006 0,006 0,006 act_nactve 0,081 0,049 0,050 act_housewk 0,004 0,001 0,001 act_retred -0,012-0,014-0,015 act_unempld 0,011 0,006 0,007 act_student -0,001 0,082-0,002 0,040-0,002 0,041 Health nequalty contrbutons of regressors n 2002 per health ndcator Contrb predcted HUI Sum of Contrb predcted GHI AgeSex Sum of Contrb Contrb predcted GHI AgeSexSES Sum of Contrb Contrb CI pred 0,0064 0,0014 0,0015 lnnc 0,0005 0,0005 0,0001 0,0001 0,0001 0,0001 male26_35 0,000 0,001 0,001 male36_45 0,001 0,000 0,000 male46_55-0,005-0,003-0,003 male56_60-0,011-0,015-0,009-0,011-0,009-0,012 fem16_25 0,000 0,000 0,000 fem26_35 0,000 0,000 0,000 fem36_45 0,002 0,002 0,002 fem46_55-0,004-0,006-0,006 fem56_60-0,016-0,019-0,020-0,024-0,021-0,025 edu_2 0,000 0,000 0,000 edu_3 0,003 0,003 0,001 0,000 0,001 0,000 sh_prvate 0,000 0,000-0,001-0,001-0,001-0,001 sh_cmu 0,007 0,007 0,025 0,025 0,026 0,026 act_nactve 0,071 0,062 0,063 act_housewk 0,005-0,001-0,001 act_retred -0,004-0,015-0,015 act_unempld 0,008 0,006 0,007 act_student -0,002 0,077-0,003 0,050-0,003 0,051 17

18 Table 4: Means and proportons of dependent and ndependent varables Means of varables predcted HUI 0,896 0,877 predcted GHI AgeSex 0,921 0,909 predcted GHI AgeSexSES 0,913 0,905 ncome/uc ( /month) 1166, ,35 age 36,27 37,38 male 49,83 49,36 female 50,17 50,64 edu_less 47,05 44,16 edu_2 22,74 23,09 edu_3 30,21 32,75 sh_no 9,81 6,36 sh_prvate 87,55 89,66 sh_cmu 2,64 3,98 act_empl 64,46 69,74 act_housewk 6,28 5,62 act_nactve 1,89 2,46 act_retred 2,66 2,18 act_student 17,19 13,53 act_unempld 7,51 6,48 Table 5: Decomposton over tme: contrbutons of regressors to the changes n the ncomerelated health nequalty Relatve change n nequalty over the dst. of ncome Contrbuton to total change n IRHI HUI % Contrbuton Relatve change n the elastcty of health Contrbuton to total change n IRHI GHI AgeSex % Contrbuton Relatve change n the elastcty of health Change n IRHI 0,0002 0,0011 lnnc -23,7% -0, ,4% 14,2% -0, ,6% -38% male26_35-45% 0, ,4% 0, ,7% male36_45-340,3% 0, ,4% 0, ,6% male46_55-48,7% 0, ,0% 0, ,2% male56_60-10,3% -0, ,0% 0,0000 9,2% fem16_25-46,3% -0, ,3% -0, ,9% fem26_ ,9% 0, ,2% 0,0000 2,3% fem36_45-3,8% -0, ,6% 0, ,2% fem46_55-48,1% 0,0004 6,4% 0, ,9% fem56_60-11,3% -0, ,4% 59,4% 0, ,8% 14,2% edu_2-766,2% -0, ,5% 42,9% -0,0001-6,1% 81,5% edu_3-29,9% -0, ,2% 33,6% -0, ,4% -20,6% sh_prvate -18,7% -0, ,1% -87,1% -0, ,5% 108,3% sh_cmu -18,6% -0, ,4% 3,6% 0, ,7% 515,2% act_nactve -13,8% 0, ,8% 98,1% 0, ,9% 191,7% act_housewk 11,5% 0, ,5% -21,3% -0, ,4% -137,8% act_retred -12% 0, ,4% -67,9% 0,0000 4,3% -1,4% act_unempld -19,6% -0, ,3% -28,2% 0,0000-4,4% 12,3% act_student -34,2% -0, ,4% 152,5% 0,0000 1,8% 42,4% Indcatons: Relatve change n nequalty = C C 1998 /C 1998 Relatve change n the elastcty of health = η η 1998 / η