The$evolution$ofhealth$in$time:$ Do$we$have$a$Health ...cefup.fep.up.pt/uploads/eco...

The evolution of health in time: Do we have a Health version of

the Easterlin Paradox?

Pilar García-‐Gómez (Erasmus University Rotterdam ) Manuel García-‐Goñi (Universidad Complutense de Madrid)

Juan Oliva (Universidad de Castilla la Mancha) Ángel López (Universidad de Cartagena)

February 1, 2013

The evolution of health in time: Do we have a Health version of the Easterlin Paradox?

1. Motivation

2. Data

3. Estimation Methods

4. Results

5. Discussion

Manuel García-‐Goñi [email protected]


Motivation

"   Relationship between health and income "   Causality "   Different challenges in different countries "   Chronics, patient-‐centred care and perceived quality of life

"   What data says for Catalonia: "   A period of great economic growth from 1994-‐2006 "   Increased in life expectancy and health expenditures "   But decrease in self-‐reported health status

"   ???



Motivation

"   What happened? "   Real decrease in health status? "   Better diagnostics and detection… and relationship with

SRHS? "   Changes in reporting behaviour? "   Bago d’Uva (HE2008): SRHS and meaning of health, expectations, use, or comprehension (cross section)

"   Johnston et al (JHE 2009): income related with objective HS but not with SRHS…



Motivation

"   Easterlin paradox: The income-‐happiness relationship "   In time, neither rich nor poor people increased their level of happiness even if income of both groups increased

"   Critiques "   Within or across countries? "   Time series? Short run or long run?

"   Explanation "   Adaptation "   Rivalry

"   Do we have something similar with self-‐reported health status?



Motivation

"   Close relationship health-‐happiness

"   Do we have something similar with self-‐reported health status? "   Reporting heterogeneity? (different trend between objective and self-‐reported measures) … due to adaptation?



1. Motivation

2. Data


4. Results

5. Discussion



Data: Catalonia 1994-‐2006


2000

2001

2002

2003

2004

2005

2006

2007

2008 Catalonia 118,5 119,6 121,8 121,5 120,8 120,7 123,3 123,0 120,9

Spain 97,0 98,0 100 101,0 101,0 102,0 (

b) 105,0 105,0 104

Euro Zone 112,0 112,0 111 110,0 109,0 109,0 (

b) 109,0 109,0 109

European Union 100,0 100,0 100 100,0 100,0 100,0 (

b) 100,0 100,0 100

Data for Catalonia 1994 2006 Life expectancy at birth 78,4 81,39 Infant Mortality 5,2 2,8 Life expectancy at 60 22,6 24,21

Relative to EU GDPpc



"  What about SRHS? "   ESCA (Catalonia Health Survey) waves (1994,2002,2006) measuring the Health Related Quality Of through EQ-‐5 D "   Questions on mobility (dimension 1), personal care

(dimension 2), daily activities (dimension 3), pain/ discomfort (dimension 4) and anxiety/depression (dimension 5). Choice between: ‘absence of problems’, ‘moderate problems’ and ‘incapacity to perform the activity or severe problems’.

"   representative samples of the Catalonian populations by sex, age groups and each one of the 37 health areas existing in Catalonia with a maximum estimation error of ± 5%


ESCA 1994 ESCA 2002 ESCA 2006 Quality of life related to health No problems in any of the 5 dimensions in the EQ-5D 65,09% 61,91% 57,08% One reported problem in one of the dimeniosn in the EQ-5D 16,22% 16,82% 17,51% Several reported problem in at least one of the dimensions in the EQ-5D (moderate or severe) 18,68% 21,27% 25,42% Reported problems (moderate or severe) in dimension 1 of the EQ-5D 12,86% 12,32% 17,09% Reported problems (moderate or severe) in dimension 2 of the EQ-5D 3,23% 4,12% 6,33% Reported problems (moderate or severe) in dimension 3 of the EQ-5D 5D 8,62% 10,23% 13,05% Reported problems (moderate or severe) in dimension 4 of the EQ-5D 27,65% 31,72% 34,27% Reported problems (moderate or severe) in dimension 5 of the EQ-5D 13,58% 17,25% 20,34% Socioeconomic variables Mean age 46,42 45,7 47,67 Age in the range 16-44 48,67% 50,64% 49,11% Age in the range 45-64 29,96% 28,98% 28,29% Older than 65 21,37% 20,38% 22,59% Females (%) 53,38% 51,39% 50,58% Males (%) 46,62% 48,61% 49,42% Single (%) 26,87% 29,41% 29,84% Married (%) 62,55% 60,58% 57,57% Widowed (%) 8,76% 6,33% 8,35% Separated (%) 1,82% 3,69% 4,24% Born in Catalonia (%) 67,71% 69,68% 70,43% Born in Spain but not in Catalonia (%) 30,91% 26,89% 21,95% Born out of Spain (%) 1,38% 3,43% 7,62% With no level of education (%) 14,51% 18,36% 14,86% Primary education (%) 56,25% 25,39% 23,41% Secondary education (%) 21,28% 44,28% 46,48% University degree (%) 7,96% 11,96% 15,24% Employed (%) 41,90% 49,89% 56,06% Unemployed (%) 8,11% 5,94% 4,28% Situación de baja laboral 3,57% 3,10% 4,42% Inactive population (%) 46,42% 41,06% 35,24% Socioeconomic class I 4,06% 8,86% 8,84% Socioeconomic class II 16,88% 8,86% 10,22% Socioeconomic class III 16,67% 23,85% 26,04% Socioeconomic class IV 52,61% 46,01% 42,21% Socioeconomic class V 9,77% 10,03% 12,70%

• Worsening perceived health?? • More diagnosed conditions • More education • Lower presence in lowest social classes (given occupation)

ESCA 1994 ESCA 2002 ESCA 2006

Health problems and diagnosed illnesses

Carcio Vascular disease (stroke, heart attack, heart disease) 8,11% 8,59% 10,24%

Disease / musculoskeletal problems (arthritis, osteoarthritis, back pain, neck problems, osteoporosis, ...) 34,50% 41,91% 47,17%

Respiratory Diseases 9,10% 9,25% 10,16%

Digestive Diseases 7,87% 7,90% 12,37%

Mental illness (depression / anxiety) 11,54% 13,73% 18,84%

Cardiovascular risk factors (diabetes mellitus, hypertension, high cholesterol, poor circulation) 36,63% 41,11% 47,42%

Other problems / minor illnesses 31,57% 42,32% 51,38%

Other problems / serious illness . 1,77% 5,57%

Other problems / diseases unspecified 37,86% 0,31% 13,13%

Inpatient hospitalization in the last 12 months 8,58% 9,72% 9,18%

Lifestyle

Very Sedentary 44,16% 50,42% 40,21%

Risk of alcohol use 3,67% 3,66% 4,66%

Smoker 30,19% 30,72% 28,38%

Non smoker 69,81% 69,28% 71,62%

N 11897 7062 15784



1. Motivation

2. Data


4. Results

5. Discussion



Methods

"   Our hypothesis here is that at least part of this worsening in reporting health status can be due to higher health expectations among the population, and thus changes in the reporting behavior. "   Adaptation in the Easterlin Paradox

"   Test whether there have been changes in the reporting behaviour controlling for possible changes in the underlying health status.


The evolution of health in time: Do we have a Health version of the Easterlin Paradox? Methods: change in reporting behavior?

"   Actual health status, unobserved latent variable:

"   Function of demographic characteristics , health conditions , year t (to capture any omitted variable effect varying in time as availability of technology…), and an idiosyncratic error term

"   Observed health status "   k=1: absence of problems, k=2: moderate problems, k=3:severe problems "   are cutpoints


€

Hitj* = β j Xit + γ jHit

0 +δ jTt +ε itj

€

Xit

€

Hit0

€

Hitj = k if µk−1j < Hitj

* < µkj

€

µk−1j ,µk

j

The evolution of health in time: Do we have a Health version of the Easterlin Paradox? Methods: change in reporting behavior?

"   Adaptation means that as better technology or income is available, a higher health status is needed to report good health

"   Are the cut points varying in time?

"   where Zit is a subset of Xit that can have an effect on the cut points

"   Generalized ordered probit estimated by maximum likelihood with robust standard errors.

"   Lindeboom and Van Dorslaer (JHE 2004)


€

µitkj = µk

j +ζkZit +ηkTt

€

P Hitj = k Xit ,Hit0,Tt( ) =Φ(µk

j +ζkZit +ηkTt − (β j Xit + γ jHit0 +δ jTt ))

−Φ(µk−1j +ζkZit +ηkTt − (β j Xit + γ jHit

0 +δ jTt ))


Results

"   Ordered probit models in each of the three years of analysis compared to estimation of all the years jointly

"   We reject for all 5 dimensions the null hypothesis of homogeneity of response behaviour through time



Results

"   Generalized ordered probit model for each of the five health dimensions allowing both the index and the thresholds to vary over time (reporting behaviour, while controlling for possible changes in the underlying health status)

"   δ: mainly not significant but for dimension 1 (relationship health and time)

"   η: significant and positive (relationship cutpoint and time)… easier to change from no problems to moderate, and from moderate to severe ADAPTATION.



Results

"   δ: mainly not significant but for dimension 1 (relationship health and time)

"   η: significant and positive (relationship cutpoint and time)… easier to change from no problems to moderate, and from moderate to severe ADAPTATION.


No problems

Moderate

Severe problems

2006 2002 1994


Results "   Allowing for sociodemographic variables affecting health and cutpoints

"   Education: only important changing reporting behavior for no educated individuals

"   Social class: not clear the direction… but richer complain more?

"   Only clear: heterogeneity in reporting behaviour

"   Robust estimation as we are adding all feasible controls



Results "   Estimation repeated for differences between male and female: "   Not significant differences "   health expectations have risen both for males and females, except for pain

and discomfort, where the change is only observed for males

"   And for age groups (16-‐44, 45-‐64 and 65+) "   Not significant differences "   Trying to follow cohorts…

"   16-‐44 in 1994, 22-‐52 in 2002 and 26-‐56 in 2006 … "   they do change reporting behaviour in time

"   We provide evidence of a change in reporting behaviour in time that we relate with adaptation or change in expectations about health Manuel García-‐Goñi

[email protected]


1. Motivation

2. Data


4. Results

5. Discussion



Discussion "   We find an increase in objective health measures and a decrease in self-‐

reported health status

"   We find that adaptation, as in the case of the Easterlin Paradox for Happiness, explains at least partially the heterogeneity in reporting behaviour, complaining more in a period of increasing income

"   Relevance "   Adptation and Self reported HS matters for health policy

making "   Waiting lists and priorities "   Decision of public financing new treatments through a

maximum value per QALYs "   We use constant perceived measures while they are vary in

time!!!

"   Are we getting richer and sicker? unknown



"   Thank you very much!!!!!

"   Manuel García-‐Goñi

"   [email protected]

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