L o n g e v i d a d , E n f e r m e d a d e s C r ó n i c a s y S i s t e m a s d e S a l u d !

D r . C a r l o s J a v i e r R e g a z z o n i

F u n d a c i ó n S a n a t o r i o G ü e m e s , S e p t i e m b r e 2 0 1 3

D E F I N I C I O N E S !

ENFERMEDADES CRÓNICAS Y SISTEMAS DE SALUD

ENFERMEDADES Y MORTALIDAD, 2010 Condición y Ranking Causa de muerte Años-vida perdidos Enfermedad Cardiovascular 1 1 ACV 2 3 Cáncer de Pulmón 3 2 Alzheimer 4 9 EPOC 5 4 Diabetes 6 7 Neumonía 7 11 Cáncer de colon 8 10 Enfermedad Renal Crónica 9 16 Otros trastornos vasculares 10 17

EE.UU., año 2010. En base a: Christopher J.L. Murray, Alan D. Lopez. Measuring the Global Burden of Disease. N Engl J Med 2013;369:448-57

ENFERMEDADES CRÓNICAS •  Hipertensión arterial •  Enfermedad coronaria •  Enfermedad cerebrovascular •  Enfermedad pulmonar obstructiva crónica •  Cáncer •  Diabetes •  Condiciones de riesgo

•  Dislipidemia •  Obesidad

ENFERMEDADES CRÓNICAS Y MORTALIDAD

Enfermedades Crónicas

60%

Infecciosas y Maternoinfantiles

31%

Violencia y Traumáticas

9%

Causas de Mortalidad, Mundo!En base a: World Health Organization. Preventing chronic diseases: a vital investment: WHO global report 2005

CAMBIO DE PATOLOGÍA

0

2000

4000

6000

8000

10000

2008 2015 2030

Mue

rtes

en

.000

s/añ

o

Causas de Muerte por grupos América Latina, WHO Traumaticas

Enfermedades no comunicables

Enfermedades comunicables, condiciones maternas y neonatales y nutricionales

CAUSAS DE MORTALIDAD, 2030

of demographic change are labelled ‘‘population growth’’ and‘‘population ageing’’ in Figure 7. The total projected changein numbers of deaths between 2002 and 2030 is the sum of thepopulation growth, population ageing, and epidemiologicalchange components.

In almost all cases, demographic and epidemiologicalfactors are operating in opposing directions in determiningmortality in 2030. The major exception is HIV/AIDS, wheredemographic and epidemiological change are acting in thesame direction to increase total HIV/AIDS deaths to 6.5million deaths in 2030 under the baseline scenario. Demo-graphic change dominates, as the majority of HIV/AIDSdeaths are in sub-Saharan Africa, where population growth is

highest and where HIV/AIDS incidence rates are assumed toremain largely constant under the baseline scenario.For Group I conditions other than HIV/AIDS for which

substantial declines in mortality rates are projected, the effectof these declines will be attenuated in most regions bydemographic change leading to an increase in the childpopulation most at risk for these conditions. Populationgrowth and population ageing act in opposite directions forGroup I mortality excluding HIV/AIDS in low-incomecountries, but not in other income groups. If future fertilityrates are higher than projected, then the higher childpopulation numbers will further offset the projected reduc-tions in death rates for Group I conditions.

Figure 5. Projections of Global Deaths (Millions) for Selected Causes, for Three Scenarios: Baseline, Optimistic, and Pessimistic, 2002–2030

doi: 10.1371/journal.pmed.0030442.g005

PLoS Medicine | www.plosmedicine.org November 2006 | Volume 3 | Issue 11 | e4422020

Projections of Global Mortality

ENFERMEDADES CRÓNICAS Y MORTALIDAD: ARGENTINA

Enfermedades Crónicas

62%

Infecciosas y Maternoinfantiles

16% Violencia y

Traumáticas 14%

Enf mal definidas 6%

Lesiones mal definidas

2%

Causas de Muerte Precoz (Años de vida perdidos por muerte prematura), Argentina!En base a: MSN. Estudio de Carga de Enfermedad, 2010

FACTORES DE RIESGO EN LA ARGENTIA

0,0 5,0

10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0

La R

ioja

T de

l Fue

go

Cha

co

San

Jua

n

Río

Neg

ro

Form

osa

Cat

amar

ca

S d

el E

ster

o

San

ta C

ruz

Men

doza

Tucu

mán

Cór

doba

Neu

quén

Cor

rient

es

La P

ampa

Bs

As

San

ta F

e

Mis

ione

s

Tota

l paí

s

Ent

re R

íos

San

Luí

s

Juju

y

Chu

but

CA

BA

Sal

ta

Prevalencia (%) de Detección de HTA, DLP, DBT "Programa de Vigilancia de la Salud y Control de Enfermedades" VIGI+A e

INDEC, Encuesta Nacional de Factores de Riesgo 2005.

Hipertensión arterial Hipercolesterolemia Diabetes

FACTORES DE RIESGO EN LA ARGENTINA (25-64 AÑOS)

Table 2 Prevalence (as Percent and 95% Confidence Interval) of Major Risk Factors by City for the Overall Population and for Men and Women

Barquisimeto Bogota Buenos Aires Lima Mexico City Quito Santiago

Hypertension* 24.7 (22.7-26.8) 13.4 (11.5-15.2) 29.0 (26.9-31.1) 12.6 (11.1-14.0) 11.7 (10.3-13.1) 8.6 (7.3-10.0) 23.8 (21.6-26.1)Men 27.5 (23.7-31.3) 14.6 (11.9-17.2) 37.7 (34.3-41.1) 14.4 (12.2-16.7) 11.2 (8.9-13.6) 7.2 (5.6-8.7) 27.3 (24.1-30.5)Women 22.9 (20.6-25.2) 12.4 (10.2-14.7) 21.7 (19.0-24.4) 10.7 (8.8-12.6) 12.1 (9.9-14.2) 10.1 (7.8-12.4) 20.7 (17.8-23.5)

Hypercholesterolemia† 5.7 (4.7-6.7) 12.0 (10.5-13.5) 18.7 (16.7-20.7) 11.6 (10.1-13.1) 16.4 (14.2-18.7) 20.2 (18.0-22.3) 15.3 (13.4-17.2)Men 4.5 (3.0-6.1) 12.4 (9.9-14.9) 19.6 (16.8-22.4) 10.1 (8.2-12.1) 17.5 (14.4-20.7) 21.6 (18.2-25.0) 15.9 (13.3-18.5)Women 6.5 (5.0-7.9) 11.7 (9.5-13.8) 17.8 (15.1-20.5) 13.0 (10.8-15.2) 15.4 (12.3-18.5) 18.8 (16.0-21.6) 14.8 (12.2-17.4)

Current smoking‡ 21.8 (19.3-24.2) 22.2 (19.1-25.2) 38.6 (36.0-41.2) 26.6 (23.9-29.4) 27.3 (25.0-29.5) 29.9 (27.0-32.7) 45.4 (42.8-47.9)Men 32.2 (27.7-36.7) 31.3 (27.1-35.5) 39.7 (36.2-43.2) 38.0 (34.2-41.7) 34.4 (30.2-38.5) 49.4 (45.9-52.9) 47.7 (44.2-51.1)Women 14.9 (12.7-17.1) 15.0 (11.1-18.9) 37.7 (34.2-41.3) 15.4 (12.6-18.2) 21.0 (18.8-23.2) 10.5 (7.8-13.2) 43.3 (39.7-46.9)

Diabetes§ 6.0 (5.0-7.0) 8.1 (6.8-9.5) 6.2 (4.8-7.7) 4.4 (3.4-5.4) 8.9 (7.7-10.2) 5.9 (4.8-7.1) 7.2 (5.9-8.6)Men 5.6 (4.0-7.2) 7.4 (5.7-9.2) 7.9 (5.7-10.0) 4.3 (2.8-5.7) 8.0 (6.3-9.7) 4.6 (3.2-6.0) 6.8 (5.2-8.5)Women 6.3 (5.0-7.5) 8.7 (6.8-10.6) 4.8 (3.3-6.4) 4.6 (3.2-5.9) 9.7 (7.8-11.6) 7.3 (5.6-8.9) 7.6 (5.6-9.6)

Obesity¶ 25.1 (22.1-28.1) 18.0 (15.7-20.2) 19.7 (17.4-21.9) 22.3 (19.9-24.6) 31.0 (28.4-33.5) 16.3 (14.3-18.3) 26.6 (24.4-28.8)Men 23.5 (18.8-28.3) 12.8 (10.1-15.5) 23.1 (19.8-26.3) 21.1 (18.0-24.3) 31.7 (28.0-35.4) 10.3 (8.2-12.5) 23.6 (20.4-26.8)Women 26.1 (22.6-29.6) 22.0 (19.0-25.0) 16.8 (13.8-19.8) 23.4 (20.5-26.4) 30.4 (27.1-33.7) 22.4 (18.7-26.0) 29.4 (26.0-32.9)

Metabolic syndrome** 25.8 (23.3-28.4) 20.4 (18.2-22.5) 16.7 (14.8-18.6) 17.9 (15.9-20.0) 27.2 (24.9-29.4) 13.7 (11.9-15.6) 21.0 (18.9-23.1)Men 26.3 (22.3-30.2) 18.7 (15.8-21.6) 21.7 (19.0-24.4) 15.8 (13.0-18.6) 26.3 (22.9-29.6) 7.5 (5.6-9.3) 19.0 (16.3-21.6)Women 25.6 (22.9-28.3) 21.7 (19.0-24.4) 12.3 (9.6-15.1) 20.0 (17.3-22.8) 28.0 (24.4-31.6) 20.1 (16.9-23.4) 23.0 (20.0-26.0)

*Hypertension, blood pressure !140/90 mm Hg, or use of antihypertensive drugs.†Hypercholesterolemia, total serum cholesterol !240 mg/dL.‡Smoking, daily or occasional consumption of cigarettes, cigars, or pipe tobacco.§Diabetes, fasting blood glucose level !126 mg/dL, or self-reported diabetes.¶Obesity, body mass index !30 kg/m2.**Metabolic syndrome, presence of !3 of the following: abdominal obesity (waist !102 cm in men, !88 cm in women); triglycerides !150 mg/dL; high-density lipoprotein cholesterol "40 mg/dL in men,

"50 mg/dL in women; blood pressure !130/85 mm Hg; fasting glycemia !110 mg/dL or self-reported diabetes.

62The

AmericanJournalofMedicine,Vol121,No

1,January2008

Schargrodsky H, Hernández-Hernández R, Marcet Champagne B, et al. : Assessment of Cardiovascular Risk in Seven Latin American Cities. Am J Med 2008; 121: 58-65

ENFERMEDADES CRÓNICAS

•  Crónicas!

•  No contagiosas!

•  Multi-morbilidad!

•  Factores de riesgo!

•  Complejidad!

D E M O G R A F Í A !

ENFERMEDADES CRÓNICAS Y SISTEMAS DE SALUD

27/08/13 07:06The Problems of a Graying Population - NYTimes.com

Página 1 de 3http://www.nytimes.com/2011/07/29/world/americas/29iht-letter29.html?_r=0&ref=world&pagewanted=print

Reprints

This copy is for your personal, noncommercial use only. You can order presentation-ready copies for distributionto your colleagues, clients or customers here or use the "Reprints" tool that appears next to any article. Visitwww.nytreprints.com for samples and additional information. Order a reprint of this article now.

July 28, 2011

The Problems of a Graying PopulationBy CHRYSTIA FREELAND | REUTERS

It’s the demography, stupid.

There are a lot of different reasons this is turning out to be such a politically hot summer in so

much of the Western world. But one way to understand this season’s acrimony — from the

protests of the indignati in Spain and Greece, to the budget deadlock in Washington and even to

the tragedy in Norway — is as diverse symptoms of a shared condition: The West is getting old.

That demographic fact is becoming a generational war, and there is every reason to believe that

in the coming decades it will get worse.

The heart of the problem is arithmetical: The post-World War II social welfare state, created at a

moment when the baby boom was still gestating, is built on a generational Ponzi scheme. As life

expectancy increases and fertility declines, that population pyramid is being inverted — and in

some countries, that is causing the entire economy to topple.

That’s true in Greece and Spain, where the young are taking to the streets partly because state

pension commitments have become so heavy they are suffocating the economy and depriving

the seniors’ grandchildren of any chance of a job. Likewise in the United States, where,

notwithstanding the national self-image as a laissez-faire land that has eschewed Europe’s

lavish social safety net, the budget battle is really a fight about the old: Programs for the elderly

constitute almost half of non-interest government spending, about $1.6 trillion in 2010, of a

$3.3 trillion total. That figure will swell as the baby boomers retire.

According to a paper by political economist Nicholas Eberstadt, who has done extensive

research on the issue, “costs associated with population aging are estimated to account for about

half the public-debt run-up of the O.E.C.D. economies over the past 20 years.”

It is not just at home that graying societies are creating wrenching political and economic

tensions: The demographic squeeze may be contributing to one of today’s biggest dangers in

international finance: the threat of sovereign default. Ali Alichi, an economist at the

International Monetary Fund, argues in an essay published by the fund last month that “old

folks may be less willing to repay sovereign debt.” According to Mr. Alichi, “As the number of

older voters relative to younger ones increases around the globe, the creditworthiness of

DEMOGRAFÍA Y CRÓNICAS

•  Longevidad   Aumenta la incidencia de crónicas.   Sin embargo la mayoría es en pacientes jóvenes.   Causan mortalidad precoz.

•  Fertilidad dual   Crecen más las poblaciones más pobres.   Las más alcanzadas por las crónicas.

•  Urbanización   Concentra la pobreza y el problema de las crónicas.   Hábitos no saludables.

LONGEVIDAD: VIDA DESPUÉS DE LOS 65’

00

05

10

15

20

25

Año

s de

exp

ecta

tiva

de v

ida

a lo

s 65

añ

os

Esperanza de vida a los 65 años, OECD, Mujeres Australia Austria Belgium France Germany Hungary Japan Mexico Netherlands New Zealand Norway Poland Portugal Slovak Republic Sweden Switzerland Turkey United States

LONGEVIDAD: SOBREVIDA A LOS 75 AÑOS

9,5

10

10,5

11

11,5

12

Año

s de

vid

a pr

omed

io a

par

tir

de lo

s 75

año

s de

eda

d

EE.UU. Expectativa de vida a los 75 años CDC. Health, United States 2009 Web Update

DUALIDAD: EJEMPLO CABA

140.000 145.000 150.000 155.000 160.000 165.000 170.000 175.000 180.000 185.000 190.000

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Población en Comunas 8 y 2, CABA, Elaboración propia en base a sensos 2001 y 2010

Comuna 8

Comuna 2

1,5%/año

-0,2%/año

CRÓNICAS: MUERTE PRECOZ

0

4000

8000

12000

16000

20000

Def

unci

ones

cad

a 10

0.00

0

Defunciones, ambos sexos, cada 100.000, a partir de los 35 años.

Elaboración propia en base a WHO (Japón 2009)

Argentina 2009

Japón

•  La Argentina tiene un exceso de muertes en jóvenes

DEFUNCIONES HASTA LOS 75 AÑOS

(%) de defunciones a los 75 años Argentina 50 Pcia de Buenos Aires 64 Canadá 25 Japón 21 Angola 75

URBANIZACIÓN: ARGENTINA

8.64

4

9.79

0

10.9

40

9.27

8

8.53

0

19.6

96

21.0

93

22.3

12

26.1

33

27.7

68

0

5.000

10.000

15.000

20.000

25.000

30.000

35.000

40.000

1990 1995 2000 2005 2007

Población urbana en

miles, Argentina. UN-

HABITAT

Urbano formal

Villas

MULTI-MORBILIDAD: EDAD

Articles

www.thelancet.com Published online May 10, 2012 DOI:10.1016/S0140-6736(12)60240-2 3

ResultsWe analysed data from 1 751 841 patients (about a third of the Scottish population) from 314 Scottish medical practices. Table 1 shows the demographic characteristics of the study population, the proportion of those with multimorbidity, and the proportion with physical and mental health comorbidity. Men and women were equally represented, as were all deprivation deciles. 42·2% (95% CI 42·1–42·3) of the population had one or more chronic morbidities, 23·2% (23·1–23·2) had multimorbidity, and 8·3% (8·3–8·4) had physical and mental health comorbidity. Of people with at least one morbidity, 54·9% (54·8–55·0) had multimorbidity and 19·8% (19·8–19·9) had physical and mental health comorbidity. Most people with common chronic mor-bidities had at least two, and frequently more, other disorders (appendix).

The number of morbidities and the proportion of people with multimorbidity increased substantially with age (table 1). By age 50 years, half of the population had at least one morbidity, and by age 65 years most were multimorbid (fi gure 1). However, in absolute terms, more people with multimorbidity were younger than 65 years than 65 years and older (210 500 vs 194 966), although older people had more morbidities on average (table 1).

The crude prevalence of multimorbidity increased modestly with the deprivation of the area in which patients lived (19·5%, 95% CI 19·3–19·6, in the most a! uent areas vs 24·1%, 23·9–24·4, in the most deprived; di" erence 4·6%, 95% CI 4·3–4·9; table 1). However, this fi nding should be interpreted with caution because the population in more deprived areas was, on average, younger (median age 37 years [IQR 21–53] in the most deprived areas vs 42 years [IQR 22–58] in the most a! uent areas). People living in more deprived areas were more likely to be multimorbid than were those living in the most a! uent areas at all ages, apart from those aged 85 years and older (fi gure 2). Young and middle-aged adults living in the most deprived areas had rates of multimorbidity equivalent to those aged 10–15 years older in the most a! uent areas (fi gure 2 and appendix).

8·3% (95% CI 8·3–8·4) of all patients, and 36·0% (35·9–36·2) of people with multimorbidity, had both a physical and a mental health disorder. The prevalence of physical and mental health comorbidity was higher in women than in men, and was substantially higher in older people than in younger people (table 1). Although older people were much more likely to have physical–mental health comorbidity, the absolute numbers were greater in younger people (90 139 people <65 years vs 55 912 people #65 years). The crude socioeconomic gradient in physical–mental health comorbidity was greater than that for any multimorbidity, with a near doubling in prevalence in the most deprived versus the most a! uent areas (table 1; di" erence 5·1%, 95% CI 4·9–5·3). In the logistic regres-sion analysis with the presence of any mental health

disorder as the outcome (table 2), we noted a non-linear association with age, so we included an age-squared term in the model. The predicted probability of having a mental health disorder increased with age up until about age 60 years, and then decreased (data not shown). Men were less likely to have a mental health disorder than were women, and those in the most deprived decile were more than twice as likely to have a mental health disorder than were those in the most a! uent decile (adjusted OR 2·28, 95% CI 2·21–2·32). The presence of a mental health disorder was strongly associated with the number of physical disorders that an individual had—eg, people with fi ve or more disorders had an OR of 6·74 (95% CI

0 disorders1 disorder2 disorders3 disorders4 disorders5 disorders6 disorders7 disorders!8 disorders

100

0–4 5–910–14

15–1920–24

25–2930–34

35–3940–4

445–4

950–54

55–5960–6

465–6

970–74

75–7980–8

485+

Age group (years)

Patie

nts (

%)

90

80

70

60

50

40

30

20

10

0

Figure !: Number of chronic disorders by age-group

90

80

70

60

50

40

30

20

10

3·0

4·08·0

12·0

16·821·2

26·8

36·8

45·4

54·2

64·1

70·6

76·579·4

80·6

82·9

76·6

69·1

58·3

46·5

34·8

9·813·4

18·3

26·8

7·96·34·8

0

0–4 5–910–14

15–1920–24

25–2930–34

35–3940–4

445–4

950–54

55–5960–6

465–6

970–74

75–7980–8

4!8

5

Age group (years)

Patie

nts w

ith m

ultim

orbi

didt

y (%

)

Socioeconomicstatus

10987654321

Figure ": Prevalence of multimorbidity by age and socioeconomic status On socioeconomic status scale, 1=most a! uent and 10=most deprived.

Barnett K, Mercer Sw, et al. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet May 10, 2012 DOI:10.1016/S0140- 6736(12)60240-2

MULTI-MORBILIDAD: POBREZA

Barnett K, Mercer Sw, et al. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet May 10, 2012 DOI:10.1016/S0140- 6736(12)60240-2

Articles

www.thelancet.com Published online May 10, 2012 DOI:10.1016/S0140-6736(12)60240-2 3

ResultsWe analysed data from 1 751 841 patients (about a third of the Scottish population) from 314 Scottish medical practices. Table 1 shows the demographic characteristics of the study population, the proportion of those with multimorbidity, and the proportion with physical and mental health comorbidity. Men and women were equally represented, as were all deprivation deciles. 42·2% (95% CI 42·1–42·3) of the population had one or more chronic morbidities, 23·2% (23·1–23·2) had multimorbidity, and 8·3% (8·3–8·4) had physical and mental health comorbidity. Of people with at least one morbidity, 54·9% (54·8–55·0) had multimorbidity and 19·8% (19·8–19·9) had physical and mental health comorbidity. Most people with common chronic mor-bidities had at least two, and frequently more, other disorders (appendix).

The number of morbidities and the proportion of people with multimorbidity increased substantially with age (table 1). By age 50 years, half of the population had at least one morbidity, and by age 65 years most were multimorbid (fi gure 1). However, in absolute terms, more people with multimorbidity were younger than 65 years than 65 years and older (210 500 vs 194 966), although older people had more morbidities on average (table 1).

The crude prevalence of multimorbidity increased modestly with the deprivation of the area in which patients lived (19·5%, 95% CI 19·3–19·6, in the most a! uent areas vs 24·1%, 23·9–24·4, in the most deprived; di" erence 4·6%, 95% CI 4·3–4·9; table 1). However, this fi nding should be interpreted with caution because the population in more deprived areas was, on average, younger (median age 37 years [IQR 21–53] in the most deprived areas vs 42 years [IQR 22–58] in the most a! uent areas). People living in more deprived areas were more likely to be multimorbid than were those living in the most a! uent areas at all ages, apart from those aged 85 years and older (fi gure 2). Young and middle-aged adults living in the most deprived areas had rates of multimorbidity equivalent to those aged 10–15 years older in the most a! uent areas (fi gure 2 and appendix).

8·3% (95% CI 8·3–8·4) of all patients, and 36·0% (35·9–36·2) of people with multimorbidity, had both a physical and a mental health disorder. The prevalence of physical and mental health comorbidity was higher in women than in men, and was substantially higher in older people than in younger people (table 1). Although older people were much more likely to have physical–mental health comorbidity, the absolute numbers were greater in younger people (90 139 people <65 years vs 55 912 people #65 years). The crude socioeconomic gradient in physical–mental health comorbidity was greater than that for any multimorbidity, with a near doubling in prevalence in the most deprived versus the most a! uent areas (table 1; di" erence 5·1%, 95% CI 4·9–5·3). In the logistic regres-sion analysis with the presence of any mental health

disorder as the outcome (table 2), we noted a non-linear association with age, so we included an age-squared term in the model. The predicted probability of having a mental health disorder increased with age up until about age 60 years, and then decreased (data not shown). Men were less likely to have a mental health disorder than were women, and those in the most deprived decile were more than twice as likely to have a mental health disorder than were those in the most a! uent decile (adjusted OR 2·28, 95% CI 2·21–2·32). The presence of a mental health disorder was strongly associated with the number of physical disorders that an individual had—eg, people with fi ve or more disorders had an OR of 6·74 (95% CI

0 disorders1 disorder2 disorders3 disorders4 disorders5 disorders6 disorders7 disorders!8 disorders

100

0–4 5–910–14

15–1920–24

25–2930–34

35–3940–44

45–4950–54

55–5960–6

465–6

970–74

75–7980–8

485+

Age group (years)

Patie

nts (

%)

90

80

70

60

50

40

30

20

10

0

Figure !: Number of chronic disorders by age-group

90

80

70

60

50

40

30

20

10

3·0

4·08·0

12·0

16·821·2

26·8

36·8

45·4

54·2

64·1

70·6

76·579·4

80·6

82·9

76·6

69·1

58·3

46·5

34·8

9·813·4

18·3

26·8

7·96·34·8

0

0–4 5–910–14

15–1920–24

25–2930–34

35–3940–44

45–4950–54

55–5960–6

465–6

970–74

75–7980–8

4!8

5

Age group (years)

Patie

nts w

ith m

ultim

orbi

didt

y (%

)

Socioeconomicstatus

10987654321

Figure ": Prevalence of multimorbidity by age and socioeconomic status On socioeconomic status scale, 1=most a! uent and 10=most deprived.

E F E C T O S S O B R E E L S I S T E M A D E S A L U D !

ENFERMEDADES CRÓNICAS Y SISTEMAS DE SALUD

E. CRÓNICAS: IMPACTO

Enfermedades Crónicas •  Muerte precoz •  Vida con discapacidad

Económico Sanitario

Menor ingreso

Insustentabilidad

Mayor costo

Complejidad

CRÓNICAS: IMPACTO SANITARIO: COSTOS

0

10

20

30

40

50 109 U$S

Gasto Total, 10 primeras causas, Adultos, US 2008 Center for Financing, Access, and Cost Trends, AHRQ, Household Component of the

Medical Expenditure Panel Survey, 2008

Mujeres Hombres

GASTO RELATIVO EN SALUD Y EDAD

0

1

2

3

4

5

6

0-5 6-14 15-24 25-34 35-44 45-54 55-64 65-74 75+

Gasto relativo

Gasto relativo per cápita en salud, por grupo etario, EE.UU 1999 Edad 35-44 años=1

Meara E, White C, Cutler DM, 2003

PREDICTORES DE RIESGO

25,3

36,6

13,2

45,1 35,1

26,8

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

100%

Población General Top 5% Top 6-10% Top 11-25%

Porc

enta

je d

e po

blac

ión

segú

n gr

upo

etar

io

Percentilo de Gasto

Participación en el Gasto en Salud, según Edad. US, población, 2005-2006; MEPS (Cohen, Rohde, 2009)

65 y más 45-64 30-44 18-29 0-17

22,7%

50,2%

65,5% 74,4%

80,6%

96,5%

3,5% 0%

20%

40%

60%

80%

100%

Top 1% Top 5% Top 10% Top 15% Top 20% Top 50% Bottom 50%

Porc

enta

je d

el g

asto

to

tal e

n sa

lud

Porcentaje de la población rankeada según nivel de gasto Note: Dollar amounts in parentheses are the annual expenses per person in each percentile. Population is the civilian noninstitutionalized population, including those without any health care spending. Health care spending is total payments from all sources (including direct payments from individuals, private insurance, Medicare, Medicaid, and miscellaneous other sources) to hospitals, physicians, other providers (including dental care), and pharmacies; health insurance premiums are not included. Source: Kaiser Family Foundation calculations using data from U.S. Department of Health and Human Services, Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey (MEPS), 2005.

Concentración del gasto en salud, USA 2005

IMPACTO DE ENFERMEDADES CRÓNICAS

EC Años productivos Aporte Social Costo en salud

-

+

CALIDAD DE ATENCIÓN EN ADULTOS

•  6.712 personas •  Adultos •  12 ciudades

USA •  Contacto tel. •  Acceso a

Historias clínicas

30 Condiciones seleccionadas

agudas y crónicas

439 indicadores de calidad de atención

Tratamientos y medidas

preventivas 1998 2000

PARA CADA CONDICIÓN: •  Medición de tratamiento

recibido •  Comparación con tratamiento

recomendado

RAND RESEARCH AREAS

THE ARTS

CHILD POLICY

CIVIL JUSTICE

EDUCATION

ENERGY AND ENVIRONMENT

HEALTH AND HEALTH CARE

INTERNATIONAL AFFAIRS

NATIONAL SECURITY

POPULATION AND AGING

PUBLIC SAFETY

SCIENCE AND TECHNOLOGY

SUBSTANCE ABUSE

TERRORISM ANDHOMELAND SECURITY

TRANSPORTATION ANDINFRASTRUCTURE

WORKFORCE AND WORKPLACE

The Health Insurance ExperimentA Classic RAND Study Speaks to the Current Health Care Reform Debate

After decades of evolution and experiment, the U.S. health care system has yet to solve a funda-mental challenge: delivering quality

health care to all Americans at an a! ordable price. In the coming years, new solutions will be explored and older ideas revisited. One idea that has returned to prominence is cost sharing, which involves shifting a greater share of health care expense and responsibil-ity onto consumers. Recent public discussion of cost sharing has often cited a landmark RAND study: the Health Insurance Experi-ment (HIE). Although it was completed over two decades ago, in 1982, the HIE remains the only long-term, experimental study of cost sharing and its e! ect on service use, quality of care, and health. " e purpose of this research brief is to summarize the HIE’s main fi ndings and clarify its relevance for today’s debate. Our goal is not to conclude that cost sharing is good or bad but to illuminate its e! ects so that policymakers can use the information to make sound decisions.

Learning from Experiment: Conducting the HIE In the early 1970s, fi nancing and the impact of cost sharing took center stage in the national health care debate. At the time, the debate focused on free, universal health care and whether the benefi ts would justify the costs. To inform this debate, an interdisciplinary team of RAND researchers designed and car-ried out the HIE, one of the largest and most comprehensive social science experiments ever performed in the United States.

" e HIE posed three basic questions: • How does cost sharing or membership in

an HMO a! ect use of health services com-pared to free care?

• How does cost sharing or membership in an HMO a! ect appropriateness and quality of care received?

• What are the consequences for health?

" e HIE was a large-scale, randomized experiment conducted between 1971 and 1982. For the study, RAND recruited 2,750 families encompassing more than 7,700 indi-viduals, all of whom were under the age of 65. " ey were chosen from six sites across the

This product is part of the RAND Corporation research brief series. RAND research

briefs present policy-oriented summaries of individual

published, peer-reviewed documents or of a body of

published work.

Corporate Headquarters 1776 Main Street

P.O. Box 2138 Santa Monica, California

90407-2138 TEL 310.393.0411

FAX 310.393.4818

© RAND 2006

www.rand.org

Key fi ndings:

• In a large-scale, multiyear experiment, participants who paid for a share of their health care used fewer health services than a comparison group given free care.

• Cost sharing reduced the use of both highly effective and less effective services in roughly equal proportions. Cost sharing did not signifi cantly affect the quality of care received by participants.

• Cost sharing in general had no adverse effects on participant health, but there were exceptions: free care led to improve-ments in hypertension, dental health, vision, and selected serious symptoms. These improvements were concentrated among the sickest and poorest patients. McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, Kerr EA. The Quality

of Health Care Delivered to Adults in the United States. N Engl J Med 2003;348:2635-45.

CALIDAD DE ATENCIÓN

35 41 42 42 45 50 55 55 60 90

0%

20%

40%

60%

80%

100%

Proporción del tratamiento teóricamente recomendado, efectivamente recibido por los pacientes.

EE.UU., 12 áreas metropolitanas, 2003 Elab propia s/RAND, The First National Report Card on Quality of Health Care in America

No recivido Recivido

RAND RESEARCH AREAS

THE ARTS

CHILD POLICY

CIVIL JUSTICE

EDUCATION

ENERGY AND ENVIRONMENT

HEALTH AND HEALTH CARE

INTERNATIONAL AFFAIRS

NATIONAL SECURITY

POPULATION AND AGING

PUBLIC SAFETY

SCIENCE AND TECHNOLOGY

SUBSTANCE ABUSE

TERRORISM ANDHOMELAND SECURITY

TRANSPORTATION ANDINFRASTRUCTURE

WORKFORCE AND WORKPLACE

The Health Insurance ExperimentA Classic RAND Study Speaks to the Current Health Care Reform Debate

After decades of evolution and experiment, the U.S. health care system has yet to solve a funda-mental challenge: delivering quality

health care to all Americans at an a! ordable price. In the coming years, new solutions will be explored and older ideas revisited. One idea that has returned to prominence is cost sharing, which involves shifting a greater share of health care expense and responsibil-ity onto consumers. Recent public discussion of cost sharing has often cited a landmark RAND study: the Health Insurance Experi-ment (HIE). Although it was completed over two decades ago, in 1982, the HIE remains the only long-term, experimental study of cost sharing and its e! ect on service use, quality of care, and health. " e purpose of this research brief is to summarize the HIE’s main fi ndings and clarify its relevance for today’s debate. Our goal is not to conclude that cost sharing is good or bad but to illuminate its e! ects so that policymakers can use the information to make sound decisions.

Learning from Experiment: Conducting the HIE In the early 1970s, fi nancing and the impact of cost sharing took center stage in the national health care debate. At the time, the debate focused on free, universal health care and whether the benefi ts would justify the costs. To inform this debate, an interdisciplinary team of RAND researchers designed and car-ried out the HIE, one of the largest and most comprehensive social science experiments ever performed in the United States.

" e HIE posed three basic questions: • How does cost sharing or membership in

an HMO a! ect use of health services com-pared to free care?

• How does cost sharing or membership in an HMO a! ect appropriateness and quality of care received?

• What are the consequences for health?

" e HIE was a large-scale, randomized experiment conducted between 1971 and 1982. For the study, RAND recruited 2,750 families encompassing more than 7,700 indi-viduals, all of whom were under the age of 65. " ey were chosen from six sites across the

This product is part of the RAND Corporation research brief series. RAND research

briefs present policy-oriented summaries of individual

published, peer-reviewed documents or of a body of

published work.

Corporate Headquarters 1776 Main Street

P.O. Box 2138 Santa Monica, California

90407-2138 TEL 310.393.0411

FAX 310.393.4818

© RAND 2006

www.rand.org

Key fi ndings:

• In a large-scale, multiyear experiment, participants who paid for a share of their health care used fewer health services than a comparison group given free care.

• Cost sharing reduced the use of both highly effective and less effective services in roughly equal proportions. Cost sharing did not signifi cantly affect the quality of care received by participants.

• Cost sharing in general had no adverse effects on participant health, but there were exceptions: free care led to improve-ments in hypertension, dental health, vision, and selected serious symptoms. These improvements were concentrated among the sickest and poorest patients.

G L O B A L !

ENFERMEDADES CRÓNICAS Y SISTEMAS DE SALUD

13/11/11 20:14How Private Companies are Transforming the Global Public Health Agenda

Página 1 de 4http://www.foreignaffairs.com/print/133936

November 9, 2011SNAPSHOT

How Private Companies are Transforming the GlobalPublic Health AgendaA New Era For the World Health Organization

Sonia ShahSONIA SHAH is a science journalist. Her most recent book is The Fever: How Malaria has Ruled Humankind for500,000 Years.

During the 1970s and 1980s, the World Health Organization and other global health leaders often strove to improvethe health of the world’s poor by targeting private sector excesses. They imposed restrictions, codes, and “ethicalcriteria” on the marketing of infant formula, pesticides, and tobacco, unnerving executives and stifling businessplans. Success hinged on the cooperation of local governments, but where policymakers implementedrecommendations they achieved real results. Breastfeeding rates rose, pesticide poisonings fell, and tobaccoconsumption declined.

Since then, the global health establishment has been turned on its head. Over the last two decades, the private sectorhas emerged as the world’s top source of financing and leadership in the fight against deadly disease. The resourcesof some of the private industry players involved in global health today dwarf those of the WHO. Groups such as theGlobal Business Coalition aim to turn “business assets into disease-fighting assets”; the GBC boasts a membership ofnearly 200 companies, including multinationals such as Coca-Cola, Exxon Mobil, and Pfizer. Why the interest?Firms are responding to local demands for corporate social responsibility, but they also have come to realize, as theylook to emerging markets for future growth, that underwriting public health is a long-term investment. Asdevelopment economist Daniel Altman recently explained, in a global economy, “these people are your consumers,your workers, your investors.” Several former WHO officials now work on public health issues for private industry.Most telling is the fact that voluntary contributions from private interests and others now bankroll four out of everyfive dollars of the WHO’s budget.

The problem is that the companies most active in global health projects today hail from a narrow range of industries,many of which are under fire for their negative impact on public health. These private firms are playing a double

CONTROL ECONÓMICO FIRMAS QUE CONTROLAN EL 30% DE TODAS LAS ACCIONES CON DERECHO A VOTO DEL MUNDO

shows that many of the top actors belong to the core. This means that they do not carry out their businessin isolation but, on the contrary, they are tied together in an extremely entangled web of control. Thisfinding is extremely important since there was no prior economic theory or empirical evidence regardingwhether and how top players are connected. Finally, it should be noted that governments and naturalpersons are only featured further down in the list.

Table S1. Top 50 control-holders. Shareholders are ranked by network control (according to thethreshold model, TM). Column indicate country, NACE industrial sector code, actor’s position in thebow-tie sections, cumulative network control. Notice that NACE code starting with 65,66,67 belong tothe financial sector.

Rank Economic actor name Country NACE code Network Cumul. networkposition control (TM, %)

1 BARCLAYS PLC GB 6512 SCC 4.052 CAPITAL GROUP COMPANIES INC, THE US 6713 IN 6.663 FMR CORP US 6713 IN 8.944 AXA FR 6712 SCC 11.215 STATE STREET CORPORATION US 6713 SCC 13.026 JPMORGAN CHASE & CO. US 6512 SCC 14.557 LEGAL & GENERAL GROUP PLC GB 6603 SCC 16.028 VANGUARD GROUP, INC., THE US 7415 IN 17.259 UBS AG CH 6512 SCC 18.4610 MERRILL LYNCH & CO., INC. US 6712 SCC 19.4511 WELLINGTON MANAGEMENT CO. L.L.P. US 6713 IN 20.3312 DEUTSCHE BANK AG DE 6512 SCC 21.1713 FRANKLIN RESOURCES, INC. US 6512 SCC 21.9914 CREDIT SUISSE GROUP CH 6512 SCC 22.8115 WALTON ENTERPRISES LLC US 2923 T&T 23.5616 BANK OF NEW YORK MELLON CORP. US 6512 IN 24.2817 NATIXIS FR 6512 SCC 24.9818 GOLDMAN SACHS GROUP, INC., THE US 6712 SCC 25.6419 T. ROWE PRICE GROUP, INC. US 6713 SCC 26.2920 LEGG MASON, INC. US 6712 SCC 26.9221 MORGAN STANLEY US 6712 SCC 27.5622 MITSUBISHI UFJ FINANCIAL GROUP, INC. JP 6512 SCC 28.1623 NORTHERN TRUST CORPORATION US 6512 SCC 28.7224 SOCIETE GENERALE FR 6512 SCC 29.2625 BANK OF AMERICA CORPORATION US 6512 SCC 29.7926 LLOYDS TSB GROUP PLC GB 6512 SCC 30.3027 INVESCO PLC GB 6523 SCC 30.8228 ALLIANZ SE DE 7415 SCC 31.3229 TIAA US 6601 IN 32.2430 OLD MUTUAL PUBLIC LIMITED COMPANY GB 6601 SCC 32.6931 AVIVA PLC GB 6601 SCC 33.1432 SCHRODERS PLC GB 6712 SCC 33.5733 DODGE & COX US 7415 IN 34.0034 LEHMAN BROTHERS HOLDINGS, INC. US 6712 SCC 34.4335 SUN LIFE FINANCIAL, INC. CA 6601 SCC 34.8236 STANDARD LIFE PLC GB 6601 SCC 35.237 CNCE FR 6512 SCC 35.5738 NOMURA HOLDINGS, INC. JP 6512 SCC 35.9239 THE DEPOSITORY TRUST COMPANY US 6512 IN 36.2840 MASSACHUSETTS MUTUAL LIFE INSUR. US 6601 IN 36.6341 ING GROEP N.V. NL 6603 SCC 36.9642 BRANDES INVESTMENT PARTNERS, L.P. US 6713 IN 37.2943 UNICREDITO ITALIANO SPA IT 6512 SCC 37.6144 DEPOSIT INSURANCE CORPORATION OF JP JP 6511 IN 37.9345 VERENIGING AEGON NL 6512 IN 38.2546 BNP PARIBAS FR 6512 SCC 38.5647 AFFILIATED MANAGERS GROUP, INC. US 6713 SCC 38.8848 RESONA HOLDINGS, INC. JP 6512 SCC 39.1849 CAPITAL GROUP INTERNATIONAL, INC. US 7414 IN 39.4850 CHINA PETROCHEMICAL GROUP CO. CN 6511 T&T 39.78

17

Stefania Vitali, James B. Glattfelder and Stefano Battiston. Supporting Information: The Network of Global Corporate Control