BUENOS AIRES Inequality and health in the metropolitan ... · BUENOS AIRES II. METHODOLOGICAL...

43Environment and Urbanization, Vol. 8, No. 2, October 1996

BUENOS AIRES

Inequality and health inthe metropolitan area ofBuenos Aires

Silvina Arrossi

SUMMARY: This paper describes differences in unsatisfied ba-sic needs and in mortality rates by age group for the 20 districtswhich make up the Metropolitan Area of Buenos Aires. It alsodescribes differences in causes of death by age group betweenthe central city (Capital Federal) and the inner and outer ring ofmunicipalities that surround it. The paper ends with a discus-sion of why it is important to develop a more detailed statisticalpicture of health differences between districts in cities and ex-amines also the difficulties in doing so.

I. INTRODUCTION

THE SUBJECT OF inequality in health conditions has been in-creasingly attracting attention in the past few years. This canbe seen both in the area of design and execution of health poli-cies and in the sphere of academic research. This growing in-terest has occurred both in the world’s higher-income coun-tries and in middle and low-income countries in the South.(1)

In 1984, equity in individual health status and equality of ac-cess to health services became the first of the 38 regional goalsof the European Office of the WHO in order to achieve the objec-tive of “Health for All in the Year 2000”. In this context, numer-ous studies appeared which showed the differences betweenthe countries of Western Europe and the recently instituted coun-tries of Eastern Europe and also the differences between thevarying regions or districts within each country. Examples ofthis are the studies carried out in Belgium, Finland, Hungary,Italy, Norway, Poland and Spain, among others, for the seminaron “Inequities in Health” held in Lisbon in 1987.(2) On the otherhand, the improvement in infant mortality and life expectancyrates in the majority of countries in Latin America has beencalled into question in view of the enormous differences whichexist between the various social groups in each country.(3)

The key issue is how national or city-wide health indicatorscan mask enormous regional differences and differences be-tween various social groups within each country or city. Fromthis perspective, it is important to carry out studies which iden-tify these differences and which enable progress to be made in

Silvina Arrossi is a sociologistwith a masters degree in pub-lic health who worked in IIED-América Latina between 1990and 1996 with much of herwork concentrating on hous-ing problems faced by low in-come groups in Latin Americancities and on the health impli-cations of poor quality hous-ing. This paper is condensedfrom a longer and more de-tailed study entitledDesigualdad y Salud en El AreaMetropolitana de BuenosAires. It is one of a number ofstudies of city inequality sup-ported by the Swedish Interna-tional Development Coopera-tion Agency (SIDA). Atpresent, Silvina Arrossi isworking at the Social Develop-ment Secretariat in Argentina.This paper was translated fromSpanish by U.M. Dean. Ad-dress: c/o IIED Amèrica Latina;fax (54) 1 383 2079

44 Environment and Urbanization, Vol. 8, No. 2, October 1996

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the methodologies and instruments required for them to be iden-tified.

In Argentina, there has been a sustained improvement in ba-sic health indicators in recent decades. This is reflected mainlyin changes in life expectancy at birth and infant mortality rates,measures which place Argentina among the best positionedcountries in Latin America. From an epidemiological point ofview, Argentina is closer to the epidemiological model of West-ern Europe and North America with a prevalence of cardiovas-cular diseases, tumours, and violence and trauma as the maincauses of death.

This might indicate that Argentina is leaving behind the healthproblems typically related to poverty and is moving on to con-front problems which are usually related to conditions in richercountries. However, this improved relative position concealsthe fact that indicators which are useful for establishing inter-national comparisons and relative positions between countriescannot be used to establish the health situation of the differentsocial groups which make up the country. The national indica-tors overlook the heterogeneity of situations which make up thehealth picture of a particular population.

In this context, the objective of this work is to analyzethe differences in health between the 20 districts whichmake up the Metropolitan Area of Buenos Aires using basicmortality data by age and causes of death. This is not in-tended to be a study of development and of trends in healthconditions. Even a glance at the basic indicators of health andliving conditions shows an improvement in health and basicservice provision in the Metropolitan Area over time in line withthe progress made in the country as a whole. This work isseeking to emphasize how national or city-wide indicators canconceal important differences between different areas of a city.It is obvious, moreover, that an analysis of differences in accessto health and in living conditions should incorporate an analy-sis by social group. However, the structure of the health infor-mation system used and the quality of the recording of some ofthe variables used in this system make an analysis of this kindimpossible. It is also not possible to identify differences in ac-cess to health services and in living conditions within the 20districts analyzed here. Thus, all the districts of the Metropoli-tan Area are treated as if they were homogeneous areas whenmany are areas with marked social and spatial polarity withintheir boundaries.

The rest of this paper is divided into three parts. Section IIdescribes the methodology employed, the sources of data usedand the definitions and classifications employed. Section IIIpresents the results of the analysis. Section IV discusses theimplications of the work carried out and the limitations of themethodology and analysis, and poses some questions for thefuture.

1. Illsey, Raymond (1990), “Com-parative review of sources, meth-odology and knowledge” in So-cial Science and Medicine Vol.31,No.3, pages 229-236.

2. See special issue of SocialScience and Medicine, Vol.31,No.3, 1990.

3. Bahr J. and W. Riner (1993),“Life expectancy and infant mor-tality in Latin America” in SocialScience and Medicine Vol.36,No.10, pages 1373-1382; alsoCurto de Casas, Isabe (1993),“Geographical inequalities inmortality in Latin America” in So-cial Science and Medicine Vol.36,No.10, pages 1349-1352; andNuñez, Norma (1992), Perfiles demortalidad según condiciones devida en Venezuela (Mortality Pro-files in Accordance with LivingConditions in Venezuela),Panamerican Health Organiza-tion.


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II. METHODOLOGICAL CONSIDERATIONS

a. Indicators Employed

DIFFERENCES IN THE health conditions of the populations inthe districts which make up the Metropolitan Area of BuenosAires were evaluated by processing and calculating general andage-specific mortality rates and causes of death for 1991. Thesebasic data on mortality were supplemented with information onsocio-economic conditions, access to housing and basic serv-ices (education, drinking water, sanitation) and health insur-ance provision for the population of the different districts.

The choice of mortality rates as a measure of the population’shealth conditions has considerable limitations. The main one isthat it provides only a partial picture of the condition of people’shealth in providing evidence on how many and from what theydie. It says very little about the quality of life and the health ofthe population who does not die. These data thus underesti-mate the importance of diseases or injuries that have incapaci-tating effects and which are disproportionately high in relationto the number of deaths which they cause - as for example mentalillnesses, osteoarthritis and onchocerciasis. They also under-represent the importance of the underlying causes of death suchas diabetes and undernutrition.(4)

The other problem inherent in the use of mortality data re-lates to the limitations of data produced to link more strictlyepidemiological variables (for example cause of death) with thosewhich concern the demographic and social characteristics ofthe household to which the dead person belongs. This limitsany attempt to link the social variables with the strictly medicaland biological variables at the household level. This difficultyhas generally been resolved through the analysis of geographi-cal inequalities, combining information from different sources(censuses, health statistics), but this method has two limita-tions. First, there is the conceptual problem that this methodonly allows for general correlations related to the wholepopulations, not to individuals, and therefore it is not possibleto relate the analysis related to a specific factor with illness ordeath in the same person. Second, there is a methodologicallimitation in that, in general, the information is processed inaccordance with administrative and/or operational zoning cri-teria which do not necessarily make it possible to identify areaswhere the levels of living conditions are different.

However, mortality data are the only continuous source of in-formation for an unambiguous picture of the health situation.(5)

This is because the method by which it is prepared, based onthe system of recording vital facts from each country, guaran-tees data which are comparable for the whole population andwhich is produced periodically. Although important differencesbetween countries certainly exist as to the level of under-re-cording presented by the mortality data(6), a standardized meth-odology of collection and classification of the information existsas can be seen in the widespread use of the International Clas-sification of Diseases for analyzing mortality by causes.(7)

4. Feachem R. et al. (1993) TheHealth of Adults in the Develop-ing World, World Bank, Washing-ton DC.

5. See reference 4.

6. It is estimated that about 90 percent of mortality data for about 72per cent of Latin America is cov-ered - see reference 3, Curto deCasas (1993).

7. In a study published by theWorld Bank concerning adulthealth in the Third World, it wasrecognized that if countries in theSouth developed their health poli-cies using the information avail-able by causes, they would bedoing no more and no less thanwealthier countries. With the ex-ception of the incidence of can-cer and some specific notifiablediseases, wealthier countrieslack reliable data on morbidityand base their health policies ontrends and differentials in the spe-cific mortality rates by cause -see reference 4.


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In addition, the data on morbidity present insuperable con-ceptual and technical problems that are inherent in the waysthey are produced. Unlike mortality, data on morbidity refer tofacts for which there is no unambiguous definition. Thus, forexample, morbidity can be observable or perceived and the useof one or other can yield divergent results. In addition, unlikemortality, there is no system to collect morbidity data for theentire population. Countries generally record information onmorbidity relating to the illnesses or injuries that people havewho attend the public health system - and so data on morbidityare much influenced by the degree of accessibility which thedifferent population groups have to different health care pro-viders.

In Argentina, there is a good system for recording data onhealth; the vital statistics system records regular informationon health conditions. This system collects basic information ondeaths of the population as a whole and on live births. Thisallowed this study of differences between districts in mortalityalthough the limitations mentioned above should be recognized.

The specific mortality rates by age were constructed on thebasis of the classification of the population into six age catego-ries, structured in such a way that the risk is different betweeneach age group and similar within the same group:(8)

• under 1 year• between 1 and 4 years• between 5 and 14 years• between 15 and 49 years• between 50 and 64 years• 65 years and over

The analysis also divided the infant mortality rate into twocomponents, the neonatal mortality rate (the mortality rate forinfants of less than 28 days) and the post-neonatal mortalityrate (the mortality rate for infants of between 28 and 364 days).

b. Specific Mortality Rates by Cause of Death

The International Classification of Disease (9th Revision ICD-9) was used as a basis for the classification. It categorizes 999morbid conditions which were sub-divided into five large cat-egories. The classification criteria used for all the age groupswere:

• infectious diseases• tumours• cardiovascular diseases• respiratory diseases• congenital anomalies• violence• others

In the case of children under the age of one, deaths were alsoclassified in accordance with the extent to which the death could

8. Ministerio de Salud y AcciónSocial - INDEC (1994), Encuestaa población: modulo deutilización y gasto en servicios desalud - aglomerado Gran BuenosAires (Population Survey: Patternof Utilization and Expenditure inHealth Services), Buenos Aires.


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be avoided based on avoidability criteria proposed by the Minis-try for Health and Social Action(9) - see Box 1 for a summary.

c. Socio-economic Level

The socio-economic level of the different districts which makeup the Metropolitan Area was analyzed starting from the unsat-isfied basic needs indicator using the methodology developedby the National Institute of Statistics and Censuses (INDEC).This establishes that households with unsatisfied basic needsare those which do not satisfy any one of the following condi-tions:(10)

• households with more than three people to a room (Over-crowding);

• households which live in housing of an unsuitable type;(11)

• households without a flush toilet;• households with any child of school age who is not attending

school.

d. Sources of Information Used

Two information sources were used for the construction ofthe mortality rates:

• The System of Vital Statistics of the Department of HealthStatistics (DES) of the Ministry for Health and Social Action,from which the data bases on deaths and on live births,corresponding to the Metropolitan Area of Buenos Aires forthe year 1991, were obtained on magnetic archive. Data onage, sex, date of death, cause of death and residence of thedeceased were selected and also age, sex, date of birth andresidence of the mother in the case of live births.

• The 1991 National Census of Population and Housing from

Box 1: The Classification of Causes of Infant Deaths According to Whether TheyCould Have Been Avoided

A classification system was developed for all deaths of infants under the age of 28days and for infants aged between 28 and 364 days according to whether the deathwas avoidable, partly avoidable or unavoidable. For instance, for infants under theage of 28 days, there are causes of death that could have been avoided throughproper monitoring of pregnancy (eg. tetanus) or through proper care during labouror through early diagnosis and treatment (eg. septicaemia, respiratory diseasesand perinatal jaundice). Other causes of death were classified as partly avoidable(eg. nutritional deficiencies) or unavoidable (eg. congenital anomalies). A comparablesystem of classification was developed for infants aged between 28 and 364 days.For instance, among the avoidable causes are the diseases that are preventable byvaccination (eg. measles, diphtheria and whooping cough) and the diseases whichcan be addressed through early diagnosis and treatment. Others were classified aspartly avoidable, unavoidable or unknown.

9. Ministry of Health and SocialAction (1987), “Agrupamiento decausas de muerte de menores deun año basado en la aplicaciónde criterios de evitabilidad”(“Grouping of causes of death ofinfants under the age of one yearbased on the application of crite-ria of avoidability”) in Boletín delprograma nacional deestadísticas de salud No.60, No-vember 1990.

10. INDEC (1993), Necesidadesbásicas insatisfechas: evoluciónintercensal 1980-1991, Ministeriode Economía y Obras y ServiciosPúblicos, June.

11. Defective housing includescamps, huts or dangerous hous-ing, rented houses, bed andbreakfast establishments, andthose households which meet atleast one of the following condi-tions: no provision of piped wa-ter inside the house; no flush toi-let; floor of earth or other mate-rial which is not ceramic, tiles,mosaic, wood, carpet, plastic,cement or fixed brick (INDEC1993, see note 10).


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which information was obtained concerning the number ofinhabitants in each district as well as those variables whichmake it possible to measure the socio-economic and educa-tional level of the population and their level of access to basicgoods and services.

e. Areas of Investigation

The Metropolitan Area of Buenos Aires is made up of the CapitalFederal [Federal District] and Gran Buenos Aires [Great BuenosAires], or Buenos Aires Conurbation, consisting of 19 districts -see Figure 1. This, in turn, is divided into two large regions,GBA1 and GBA2, by means of a modification of the classifica-tion proposed by the National Institute of Statistics and Cen-suses. This divides Gran Buenos Aires into two, based on thefact that the quality of housing conditions and the levels of healthservices and infrastructure provision generally get worse thefurther away a district is from the Capital Federal, the later adistrict was urbanized and the less its level of consolidation.Gran Buenos Aires 1 (GBA1) is the region closest to Capital Fed-eral and is where provision of services and living conditions arebetter whilst Gran Buenos Aires 2 (GBA2) includes the districtsfurthest from Capital Federal where living conditions and ac-cess to basic services are worst. However, due to the fact that,in this study, the unsatisfied basic needs indicators are consid-ered as the principal indicator of the living conditions of thepopulation of each district, the composition of GBA1 and GBA2was altered so that two relatively homogeneous regions remainedwith regard to the percentage of the population with unsatisfiedbasic needs. In this way, the Metropolitan Area of Buenos Aireswas classified into three regions:

• Capital Federal [Federal District] which includes, within its200 square kilometres, the historic city and the port zone.

• Gran Buenos Aires 1, made up of those districts with up to 15per cent of their population with unsatisfied basic needs andwhich are concentrated just to the North and to the South ofthe Federal District: Avellaneda, General San Martin, Lanús,Morón, San Isidro, Tres de Febrero and Vicente López.

• Gran Buenos Aires 2, made up of those districts which havemore than 15 per cent of their population with unsatisfiedbasic needs: Almirante Brown, Berazategui, EstebanEcheverría, Florencio Varela, General Sarmiento, Lomas deZamora, La Matanza, Merlo, Moreno, Quilmes, San Fernandoand Tigre.

Although each district is made up of localities and quarterswhich, in turn, have considerable differences in terms of livingand health conditions, the data from the data base of deaths donot permit a level of disaggregation below the district level. Thismeans that the lowest level of disaggregation used for the analysisis the municipality (district).


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III. LIVING AND HEALTH CONDITIONS IN THEMETROPOLITAN AREA OF BUENOS AIRES

THE METROPOLITAN AREA of Buenos Aires is located in theprovince of Buenos Aires at the mouth of the Rio Plata (literallythe Silver River, although usually known in English as the RiverPlate). It is the principal urban agglomeration in Argentina bothbecause of its role in the economic structure of the country andbecause of the population concentrated there. It is also one ofthe world’s largest cities with 10.9 million inhabitants in 1991.The Metropolitan Area is made up of the Capital Federal and 19districts (see Figure 1) and these hold some 34 per cent of Ar-gentina’s total population in an area of 3,880 square kilome-tres.


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District Total Area Densitypopulation (sq. km.) (inhabitants

per sq.km.)

TOTAL for Argentina

TOTAL for Buenos AiresMetropolitan Area

Capital Federal

-------------------------------------Gran Buenos Aires (GBA) 1

AvellanedaGeneral San MartinLanúsMoronSan IsidroTres de FebreroVicente Lopez-------------------------------------

Gran Buenos Aires (GBA) 2

Almirante BrownBerazateguiEsteban EcheverriaFlorencio VarelaGeneral SarmientoLomas de ZamoraLa MatanzaMerloMorenoQuilmesSan FernandoTigre

The Metropolitan Area can be divided into the Capital Federalwith 27.1 per cent of the population in 1991, and two largeregions, GBA1 (with 25.6 per cent) and GBA2 (with 47.3 perent). Table 1 gives the distribution of the population betweenthe Capital Federal and each of the districts which make upthese regions.

In socio-economic terms, these three regions are well differ-entiated, Capital Federal being the district with the best livingconditions. Table 2 gives details of the proportion of the popu-lation by district with unsatisfied basic needs and includes fur-ther details of the percentage living in inadequate housing, inhousing without flush toilets and without health insurance.Figure 2 shows the percentage of the population in each districtwith unsatisfied basic needs and the distribution of populationwith unsatisfied basic needs. This indicates that it is not neces-sarily the districts with the lowest proportion of people withunsatisfied basic needs that have the lowest concentration of

32615528 2780400 11.7

10934727 3880 2818.2

2965403 200 14827.0

2801818 420 6671.0

344991 55 6722.6 406809 56 7264.5 468561 45 10412.6 643553 131 4912.6 299023 48 6229.7 349376 46 7595.2 289505 39 7423.2

5167506 3260 2165.6

450698 122 3694.2 244929 188 1302.8 275793 377 731.6 254997 206 1237.9 652969 196 3331.5 574330 89 6453.1 1121298 323 3471.5 390858 170 2299.2 287715 180 1598.4 511234 125 4089.9 144763 924 156.7 257922 360 716.5

Table 1: Metropolitan Area of Buenos Aires: TotalPopulation, Area and Density by District, 1991

SOURCE: National Census of Population and Housing, 1991. INDEC.


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people with unsatisfied basic needs. For instance, the CapitalFederal has among the lowest percentages of households andamong the highest concentration of households with unsatis-fied basic needs.

Figure 3 shows the variation between districts for some of theindicators used to make up the unsatisfied basic needs index.These show the different conditions in these three regions withGBA2 being the region which clearly has worse living condi-tions and worse levels of health insurance provision. The Capi-tal Federal and the two municipalities to its North (Vicente Lopezand San Isidro) have among the lowest proportions of house-holds with unsatisfied basic needs in aggregate and with regardto the indicators shown in Figure 3.

IV. MORTALITY IN THE METROPOLITAN AREAOF BUENOS AIRES

a. General Mortality

THE GENERAL MORTALITY rate of the Metropolitan Area ofBuenos Aires for 1991 was 8.7 per 1,000, a figure close to thenational rate of 7.8 per 1,000. However, this figure concealsconsiderable differences between the three regions: the CapitalFederal had a general mortality rate of 12.1 per 1,000 whileGBA1 and GBA2 had rates of 9.3 and 6.5 per 1,000 respectively- see Table 3.

Figure 4 shows the distribution of general and age specificmortality rates by district (per 1,000 inhabitants) in 1991. The


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map of the general mortality rate shows how the rate withinGBA1 varies between 7 and 9.7 per 1,000, with the exception ofAvellaneda which has a rate of 14.3 per 1,000. In GBA2, thefigures range from 5 to 6.5 per 1,000. In this region, the casesof San Fernando, Lomas de Zamora and Quilmes stand out withgeneral mortality rates of 10, 8.3 and 7 per 1,000 respectively.

The analysis of general mortality according to causes of deathshows a predominance of cardiovascular diseases in the Metro-politan Area - see Table 4. In second place come tumours fol-lowed by diseases which are classified as “other causes”, respi-ratory diseases, violence, infectious disease and, lastly, congeni-tal anomalies. The distribution of the causes of death is main-tained when each of the regions which make up the Metropoli-tan Area is analyzed separately although some differences doexist as to the weight of each group of causes within each region- see Box 2.

Table 2: The Proportion of the Population in the Metropolitan Area of Buenos Aireswith Unsatisfied Basic Needs by District

Percentage ofthe population

without coveragefor health services

36.4

36.1

19.5

30.335.533.732.725.133.420.1

40.438.944.247.543.336.943.244.749.434.638.743.2

District

TOTAL for Argentin

TOTAL for Buenos AiresMetropolitan Area

Capital Federal----------------------------------Gran Buenos Aires (GBA) 1

AvellanedaGeneral San MartinLanúsMoronSan IsidroTres de FebreroVicente Lopez----------------------------


Almirante BrownBerazateguiEsteban EcheverriaFlorencio VarelaGeneral SarmientoLomas de ZamoraLa MatanzaMerloMorenoQuilmesSan FernandoTigre

Percentage of thepopulation with

unsatisfiedbasic needs

29.0

25.5

5.1

12.717.515.016.69.7

10.55.5

32.724.646.153.243.628.133.843.548.624.728.436.2

Percentage ofthe population

with inadequatehousing

7.0

5.9

2.0

3.54.84.23.42.83.21.5

7.78.7

10.513.09.76.97.49.1

11.16.96.88.3

Percentageof housing

withoutflush toilets

14.20

7.20

2.20

4.205.303.704.003.003.401.80

9.006.70

13.0016.9011.007.907.809.90

12.206.90

11.7010.00

SOURCE: SIEMPRO on the basis of the National Census of Population and Housing, 1991, INDEC.


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Thus, if we take general mortality, we observe a similar distri-bution pattern of causes of death in the three regions with per-centage differences with respect to the specific weight of eachgroup of causes in each region. However, the analysis of thedifferences in general mortality says little about differences inthe health situation in each district. When all deaths corre-sponding to all age groups are combined in a single measure-ment, the general mortality rate tends to be higher in those popu-lation groups with greater socio-economic development due tothe larger relative proportion of persons in the highest agegroups. This fact means that - with the classification of causesof death used in this study - causes of death corresponding tothe higher age groups are over-represented in the general mor-tality rate.

Box 2: Differences in the Most Common Causes of Death between the CapitalFederal, the Inner Ring of Gran Buenos Aires 1 and the Outer Ring of GranBuenos Aires 2

Cardiovascular diseases carry greater weight within GBA1 (52.1 per cent) and lessweight in GBA2 (46.3 per cent).

The percentage corresponding to tumours is higher in Capital Federal (19.3 percent) and lower in GBA2 (18.8 per cent).

Respiratory diseases have the greatest weight in Capital Federal (7.1 per cent)and the lowest in GBA1 (5.7 per cent).

Violence (which includes traffic accidents) presents dissimilar figures in eachregion, with a difference of more than three points between GBA2 (7.9 per cent)and Capital Federal (3.6 per cent). GBA1 has an intermediate figure, with 6.2 percent.

Infectious diseases show homogeneous figures in the three areas, fluctuating around3 per cent.

Congenital anomalies are most frequent in GBA2 (1.7 per cent) and lowest in CapitalFederal, with 0.4 per cent.

Table 3: General Mortality Rates for the Three RegionsThat Make Up the Metropolitan Area of Buenos Aires(per thousand inhabitants, 1991)

Area Deaths in 1991 Population Generalmortality rate

Capital Federal



SOURCE: Own analysis on the basis of data from Ministry of Health and Social Action.

35,888

25,938

32,934

2,965,403

2,801,818

5,167,506

12.1

9.3

6.4


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Tab

le 4

: G

ener

al M

ort

alit

y b

y C

ause

s o

f D

eath

(in

per

cen

tag

es)

by

area

s, 1

991

232

0

.9

564

1

.7

133

0

.4

796

0

.8

1351

6

52.1

1526

0

46.3

1794

2

49.9

4671

8

49.3

732

2.8

996

3.0

1126

3.1

2854

3.0

1471

5

.7

2057

6

.2

2561

7

.1

6089

6

.4

4885

18.8

5647

17.1

6933

19.3

1746

518

.4

1343

5.2

2589

7.9

1303

3.6

5235

5.5

3530

13.

6

5526

16.

8

5890

16.

4

1494

6 1

5.8

2570

910

0.0

3263

910

0.0

3588

810

0.0

9410

310

0.0

SO

UR

CE

: O

wn

anal

ysis

on

basi

s of

info

rmat

ion

supp

lied

by t

he M

inis

try

of H

ealth

and

Soc

ial A

ctio

n.

Are

a

Con

geni

tal

%

Car

dio-

%

Infe

ctio

us

%

Res

pira

tory

%

Tum

ours

%

V

iole

nce

%

Oth

ers

%

To

tal

%

anom

alie

s

vasc

ular

d

isea

ses

dise

ases

dis

ease

s

Gra

n B

ueno

sA

ires

(G

BA

) 1

Gra

n B

ueno

sA

ires

(G

BA

) 2

Cap

ital F

eder

al

TO

TAL

(fo

r th

e w

hole

met

ropo

litan

are

a)


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The different states of health can be analyzed in greater depthfrom the analysis of the age-specific rates because, in this way,it is possible to analyze the differential situations of the differ-ent at-risk groups. An analysis of specific mortality rate by ageand cause of death is presented below.

b. Infant Mortality

The basic indicator for analyzing mortality among infants (thoseunder one) is the infant mortality rate (IMR). This is also recog-nized as one of the best indicators for showing up situations ofpoverty and poor living conditions as poor housing conditions,lack of basic services and inadequate incomes which result ininadequate food for infants show up in higher IMRs.

In Argentina, the trend in the IMR has been a continuous im-provement in the last few decades, from a rate of 33 per 1,000live births in 1980 to 24.7 per 1,000 in 1991. The IMR forBuenos Aires Metropolitan Area in 1991 was 22.1 per 1,000live births, a figure close to the provincial average (24.2 per1,000) and that of the country (24.7 per 1,000). However, ananalysis of the IMRs broken down to the level of each of thethree large regions which make up the Metropolitan Area showsgreat differences between these (see Table 5). Whilst the Capi-tal Federal has the lowest IMR for the whole area (15.2 per 1,000),the rates for GBA1 and GBA2 are considerably higher with 21.6and 24.7 per 1,000, respectively. In two of the districts in GBA2(San Fernando to the North and Florencio Varela to the South),the rate exceeded 30 per 1,000 live births which is almost twicethe rate in the Capital Federal - see map in Figure 4.

The differentiation of the IMR into neonatal and post-neonatalmortality rates shows in greater detail the inter-district differ-ences in infant health. Neonatal mortality is generally linked toproblems of pregnancy, delivery and/or newborn infant, whereasenvironmental and quality of life problems of the households towhich the infant belongs are considered to be the main influ-ences on post-neonatal mortality.(12)

The neonatal mortality rate (NMR) is roughly the same for GBA1and GBA2, but 40 per cent higher than for the Capital Federal.However, in both GBA2 and Capital Federal, neonatal mortalityrepresents approximately 60 per cent of the deaths of childrenunder the age of one whilst in GBA1 this percentage is almost70 per cent.

However, the post-neonatal mortality rate (PMR) is lower inCapital Federal with 5.7 per 1,000. The greatest difference canbe found between this district and GBA2 which has a rate thatis 80 per cent higher than that in Capital Federal.

An analysis of the IMR by causes classified in accordance withcriteria of avoidability (see Box 1) shows that GBA2 has the high-est IMR figure for avoidable causes (12.5 per 1,000), 140 percent higher than in Capital Federal which has the lowest level,with 5.2 per 1,000. This is evident in Figure 5. Likewise, GBA2has the highest mortality rate for partly avoidable causes (seeFigure 5) although differences with the other two regions arenot great. If we combine the mortality rate corresponding to

12. Ministerio de Salud y AcciónSocial (Ministry of Health andSocial Action) (1992), Módulo deutilización y gasto en servicios desalud. Aglomerado Gran BuenosAires, situación sanitaria de losmenores de un año. Cifrasdefinitivas (Pattern of use andexpenditure in health services.Greater Buenos Aires Agglom-eration, Health Circumstances ofthe Under one-year olds. Defini-tive figures), Series 10, No.5,Buenos Aires, December.


BUENOS AIRES


BUENOS AIRES

avoidable causes and partly avoidable causes, GBA2 is againthe region with the highest figure, 100 per cent higher than thatin Capital Federal and almost 50 per cent higher than that inGBA1 (16.5, 8.5 and 11.5 per 1,000 respectively).

It is thus obvious that GBA1 and GBA2 are the two regionswith the worst levels of infant mortality compared to CapitalFederal although there are differences between these two re-gions, GBA1 being generally better positioned than GBA2. How-ever, the analysis of IMRs within each district shows great dif-ferences between the districts - see Figure 5.

c. Gran Buenos Aires (GBA) 1

The districts in this region present IMRs with figures whichfluctuate around the overall IMR for the region, the gap betweenthe highest rate (Lanús) and the lowest (San Isidro and VicenteLópez) being approximately 25 per cent. Lanús shows a figurecloser to the average for GBA2 and, likewise, has the highest

District Population Live births Deaths IMR Deaths NMR PMR< 1 year < 28 days


AvellanedaGeneral San MartinLanúsMoronSan IsidroTres de FebreroVicente Lopez--------------------------


Almirante BrownBerazateguiEsteban EcheverriaFlorencio VarelaGeneral SarmientoLomas de ZamoraLa MatanzaMerloMorenoQuilmesSan FernandoTigre----------------------------

Capital Federal

Table 5: Infant, Neonatal, and Post-neonatal Mortality Rates by District, 1991.

2801818

344991406809468561643553299023349376289505

5167506

450698257922244929390858574330652969511234275793

1121298287715144763254997

2965403

44967

601569937605

10310472256113711

108768

93485946501488249982

14225100866181

23190695829506064

39703

973

13815318721693

11373

2704

18517611322024137125915752318889

182

605

21.64

22.9421.8824.5920.9519.7020.1419.67

24.86

19.7929.6022.5424.9324.1426.0825.6825.4022.5527.0230.1730.01

15.24

658

94111125146607646

1585

11112670

13714721915090

26910855

103

358

14.63

15.6315.8716.4414.1612.7113.5412.40

14.57

11.8721.1913.9615.5314.7315.4014.8714.5611.6015.5218.6416.99

9.02

7.01

7.326.018.156.796.996.597.28

10.29

7.928.418.589.419.42

10.6910.8110.8410.9511.5011.5313.03

5.71

SOURCE: Own analysis based on data from the Ministry of Health and the 1991 CNPV.


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post-neonatal mortality with 16.4 per 1,000 live births. How-ever, it should be noted that some districts present a high per-centage of unknown causes of death, which has to be consid-ered when drawing any conclusions.

The analysis of IMR by cause of death classified in accord-


BUENOS AIRES

ance with criteria of avoidability (see Figure 5) reveals that allthe districts of GBA1 have IMR figures for avoidable causes whichfluctuate around the average for the region with the exceptionof Lanús and General San Martin which, with rates of 9.6 and10.3 per 1,000 respectively, are approximately 20 per cent higherthan the average. The latter district also has the highest IMRfor avoidable and partly avoidable causes (13.7 per 1,000) to-gether with Avellaneda which has a rate of 13.1 per 1,000 livebirths.

On the other hand, the neonatal mortality rate for criteria ofavoidability shows again that the worst positioned districts areLanús and General San Martin, followed by Avellaneda. SanIsidro has the lowest NMR for avoidable and partly avoidablecauses and also the lowest for avoidable causes only.

In the districts which belong to GBA1, the Post-neonatal Mor-tality Rate (PMR) for avoidable and partly avoidable causes ishalf that in GBA2. The same difference remains if only thePMRs corresponding to avoidable causes are considered, as thevery low figure for the district of Tres de Febrero shows (two,while the rate for most districts in GBA2 is over five).

d. Gran Buenos Aires (GBA) 2

In this region there is a big difference between the figures inthe different districts which can be grouped together in fourranks:

• IMR less than 20 per 1,000; Almirante Brown, with 19.8 per1,000, falls into this category;

• IMR between 22 and 24.9 per 1,000; four districts fall intothis category, namely Berazategui, La Matanza, Lomas deZamora and Merlo;

• IMR between 25 and 27 per 1,000; four districts fall into thiscategory, namely E. Echeverría, Quilmes, General Sarmientoand Moreno; and

• the districts with a higher IMR, namely Tigre, Florencio Varelaand San Fernando with 29.6, 30.0, and 30.2 per 1,000, re-spectively.

Between the district with the lowest IMR (Almirante Brown)and San Fernando, with the highest IMR, there is a gap of nearly52 per cent. Furthermore, Florencio Varela and San Fernandohave the highest PMR, together with the district of Moreno, with13.0, 11.5 and 11.5 per 1,000, respectively. Tigre has the highestNMR in the region (21.2 per 1,000) followed by San Fernando(18.6 per 1,000) and Florencio Varela (17 per 1,000). The otherdistricts fluctuate approximately around the rate for the region.The IMR from avoidable and partly avoidable causes shows thatFlorencio Varela is the district with the worst conditions, with arate of 16.7 per 1,000 for avoidable causes and 20.3 per 1,000for avoidable and partly avoidable causes. San Fernando andTigre, two of the districts with a higher IMR, have relatively lowfigures (13.9 and 11.9) which can, to a large extent, be explainedby the high proportion of deaths which fall into the “unknown”


BUENOS AIRES

category, revealing that these districts have serious problemswith the recording of information on causes of death. The factthat the district with the lowest rate of avoidable deaths, LaMatanza (8.7 per 1,000), has nearly half the rate of FlorencioVarela (16.7 per 1,000) shows the enormous inequality whichexists within GBA2. Tigre and La Matanza are the districts whichreflect better conditions since they have the lowest IMRs for cri-teria of avoidability with 9.4 and 8.6 per 1,000 (avoidable) and11.9 and 11.8 per 1,000 (avoidable and partly avoidable), re-spectively.

With regard to neonatal mortality by avoidable and partly avoid-able causes, differences between districts for avoidable causesare not great, with the exception of Florencio Varela which hasthe highest figure, and with a very small rate corresponding topartly avoidable causes. San Fernando and Tigre have low fig-ures which are explained by the large proportion of unknowncauses, as already mentioned. Merlo, Moreno and Lomas deZamora have the highest NMR for avoidable and partly avoid-able causes mainly on account of avoidable mortality. LaMatanza and Almirante Brown have low figures in all three ratecategories.

In conclusion, for neonatal mortality from avoidable and partlyavoidable causes, differences between the average rate by crite-ria of avoidability are not large in GBA1 and GBA2 but there areimportant differences within each region. The following groupsof districts can be drawn up (the districts of Tigre and SanFernando are not included in this classification, because of thehigh proportion of unknown causes):

• Districts with low NMRs for avoidable and for partly avoid-able causes: Vicente López, Tres de Febrero and San Isidroin GBA1, and Almirante Brown and La Matanza in GBA2.

• Districts with high NMRs for avoidable and for partly avoid-able causes: Lanús, General San Martin and Avellaneda inGBA1 and Florencio Varela in GBA2.

• Districts with NMRs for avoidable and for partly avoidablecauses close to the zonal average for both rates: Morón inGBA1, Berazategui, Esteban Echeverría and Quilmes in GBA2.

• Districts with NMRs close to the average for the region butwith relatively higher figures for criteria of avoidability duemainly to a higher rate for partly avoidable causes; Lomas deZamora, Merlo and Moreno in GBA2.

On the other hand, post-neonatal mortality by criteria ofavoidability shows substantial differences between the threeregions with rates of 1.8, 3.5 and 6.1 per 1,000 for Capital Fed-eral, GBA1 and GBA2, respectively although the high propor-tion of unknown causes in the Capital Federal has to be noted.These differences remain if we consider avoidable deaths sepa-rately from partly avoidable ones.

In GBA1, the high figure for the rate of avoidable causes forSan Isidro is striking when compared to the other districts. Theother districts have figures around the average with the excep-tion of Tres de Febrero which has a rate slightly higher than


BUENOS AIRES

that of Capital Federal. The figures for the rates for partly avoid-able causes are practically negligible.

Again, in GBA2, great differences can be seen between thebetter and worse positioned districts. Florencio Varela has thehighest rate, both for avoidable causes and for partly avoidablecauses, which means that the combined rate is much higherthan that for the remaining districts. Esteban Echeverría, Gen-eral Sarmiento, Moreno and San Fernando have figures higherthan the average for the region and the other districts have ratesbelow this figure.

In this sense, in relation to mortality in children under theage of one, a large gap can be seen between the situation inCapital Federal, which has the lowest IMR figures, and in GBA1and GBA2. Children in GBA2, under the age of one, have agreater risk of death before the end of their first year of life thanthose in GBA1. This difference between regions remains if oneanalyzes IMRs for avoidable and partly avoidable causes andthe distribution of the neonatal and post-neonatal rates althoughthe differences between GBA1 and GBA2 for neonatal mortalityare not significant. Within GBA1 and GBA2, the gap betweenthe districts is generally more marked in the case of GBA2.

e. Children Aged between One and Four Years

The mortality rate for children of aged between one and fourshows that the risk of death for this age group - called “theadolescents of paediatrics”(13) - is lower for GBA1 (6.7 per 10,000)in comparison with Capital Federal (8.0 per 10,000) and GBA2(8.4 per 10,000). This implies that the risk of death in this agegroup is least in GBA1.

Within GBA1, Avellaneda and Lanús are the districts with thehighest levels (8.5 and 8.0 per 10,000, respectively, 50 per centmore than Tres de Febrero and Vicente López, the districts withthe lowest figures (4.6 and 4.5 per 10,000, respectively).

In GBA2, one can see a large gap between the lowest rate, forBerazategui (5.3 per 10,000), and Esteban Echeverría with 10.5per 10,000. Other districts with high levels are Lomas deZamora, La Matanza and San Fernando with 9.3, 9.8 and 9.9per 10,000 respectively. Florencio Varela, one of the districtswith a very high IMR, has one of the lowest mortality rates forchildren between the ages of one and four (5.8 per 10,000).

The analysis of mortality by causes(14) (see Table 6) shows that,both in GBA1 and in GBA2, “violence” predominates as the firstcause of death(15) although GBA2 has a higher rate than GBA1.In the latter, “respiratory diseases” have a somewhat greaterweight than “cardiovascular disease” (second and third causesof death) but the relative figures are similar and do not appearto mark a significant difference. In Capital Federal, on the otherhand, cardiovascular diseases take first position followed bythose classified as “others”, leaving “violence” in third place.

It is clear that the differences observed between these threeregions for mortality in this age group contradict the figuresexpected, given their socio-economic characteristics. With Capi-tal Federal having higher figures than GBA1, and being closer

13. This description is due to thefact that children of this age areexperiencing a stage of transitionwhich runs from complete de-pendence on those who look af-ter them to environmental riskfactors since they are exposed tonumerous injuries (accidents,contact with contaminating mate-rials, ingestion of toxic sub-stances) and without the rigorousprotection which they received attheir previous stage.

14. Some of the differences be-tween the total rates for each re-gion are due to the fact that casesfor which the cause of death wasa “missing value” (i.e. not known)were not considered for theanalysis.

15. Although the analysis carriedout does not make it possible todifferentiate between types of dis-ease within each group ofcauses, a study carried out by theHealth Statistics Division of theMinistry of Health and Social Ac-tion showed that, in 1989, for chil-dren in this age group, traffic anddomestic accidents accountedfor 45 per cent of violence inCapital Federal, 35 per cent inGBA1 and 38 per cent in GBA2.


BUENOS AIRES

to GBA2, one might suppose that living conditions exist in thefirst district which have a direct effect on the age group residentthere (e.g. traffic accidents). However, analysis of mortality bycause shows that the difference between these two areas re-sides basically in the greater proportion of deaths from cardio-vascular diseases which are not directly linked to living condi-tions; according to the classification of criteria of avoidability forchildren of this age, they come within the category of non-avoid-able deaths.(16) One may assume that there are probably prob-lems of recording of the mortality data for this age group whichwould mean that deaths of children living in GBA1 and/or GBA2,but who attended hospitals in Capital Federal where they died,were recorded as residents of Capital Federal(17) causing an over-estimate of mortality in this age group in this region.

f. Population Aged between Five and 14 Years

The mortality rate in the population of five to 14-year olds forthe Metropolitan Area of Buenos Aires was 28.0 per 100,000 in1991, a figure five points lower than that for the whole countryfor the same year (which was 33.4 per 100,000) and two points

GBA1 Deaths Rate % Population

TotalViolenceRespiratory diseases.Cardiovascular diseasesOthersInfectious diseasesCongenital anomaliesTumours

GBA2 Deaths Rates % Population

TotalViolenceCardiovascular diseasesRespiratory diseasesOthersInfectious diseasesCongenital anomaliesTumours

CAPITAL FEDERAL Deaths Rates % Population

TotalCardiovascular diseasesOthersViolenceRespiratory diseasesInfectious diseasesTumoursCongenital anomalies

SOURCE: Own analysis on the basis of data supplied by the Ministry of Health and Social Action.

Table 6: Mortality by Causes for the Population Aged Between 1 and 4 Years in 1991

1162621202013115

36999605653373430

116342616131188

6.551.471.191.131.130.730.620.28

8.232.211.341.251.180.830.760.67

7.992.341.791.100.890.760.550.55

100.0022.4118.1017.2417.2411.219.484.31

100.0026.8316.2615.1814.3610.039.218.13

100.0029.3122.4113.7911.219.486.906.90

176979

448191

145252

16. See Ministry of Health (1994)for more details of the classifica-tions of death in children betweenthe ages of one and four years inaccordance with criteria ofavoidability.

17. The mortality rate is calcu-lated by place of residence and,therefore, any alteration in therecording of this variable pro-duces differences in the result-ing rates.


BUENOS AIRES

below the figure for the province of Buenos Aires. Of the threeregions which make up the Metropolitan Area, GBA1 and Capi-tal Federal have the highest figures with 29.8 and 28.9 per100,000, respectively against a rate of 26.9 for GBA2.

Within GBA1, the situation in Avellaneda is striking: there isa rate of 50.8 per 100,000 which is more than three times therate of Vicente López, the district with the lowest rate (16.4 per100,000). Tres de Febrero, Morón and Lanús also have rela-tively low rates, lower in every case than the average for theregion. The rates for San Isidro and General San Martin areapproximately twice that for Vicente López but not as high asthat for Avellaneda. Given that Avellaneda is one of the districtswith better living conditions, this fact may be explained by thehypothesis that this district is taking people from other districtsand that, because of problems in recording the residence ofpersons who have died, a rise occurs in that particular rate.

In GBA2, the rates fluctuate around the regional average withthe obvious exception of Esteban Echeverría, which has the low-est rate in GBA2 (11.3 per 100,000), and Moreno which, with arate of 45.4 per 10,000, has the highest figure, four times higherthan the lowest. In this case, what has been hypothesized forthe case of Avellaneda is valid for Moreno although this districthas worse living conditions. However, the differences in mortal-ity rates depend not only on living conditions but also on factorssuch as access to health services and quality of care. For exam-ple, a district with a low socio-economic level but a good healthservices infrastructure might have high mortality levels if it takespeople from other districts and if problems exist in the record-ing of mortality data. It is obvious that, on the basis of the dataavailable, it is very difficult to reach any conclusion. But it isimportant to note the need to supplement the analysis of mor-tality indicators with studies of provision and accessibility ofhealth services in each district so as to be able to establish inthe different cases the contribution of the movement of the popu-lation seeking attention between the different providers existingin each region.

With regard to causes of death(18) (see Table 7), both in CapitalFederal and in GBA1 and GBA2, “violence” predominates as thefirst cause of death (with similar rates in all three cases butslightly higher in GBA1). However, GBA2 is the region whichhas the highest proportion of violent deaths in relation to thetotal (41 per cent). “Tumours” are the second cause althoughthere is practically a two point difference between Capital Fed-eral (6.5 per 100,000) and GBA2 (4.8 per 100,000). Similarly,in Capital Federal, cardiovascular diseases occupy third placewhilst in GBA1 and GBA2 this position is occupied by diseaseswhich come under the “others” category. Respiratory and in-fectious diseases do not appear to be an important problem atthis level of disaggregation although the “infectious diseases”rate is comparatively higher in GBA1 than in the other two re-gions and “respiratory diseases” are of greater importance inCapital Federal, with a rate approximately twice that of GBA1and GBA2 (2.4, 1.9 and 1.2 per 100,000, respectively).

The five to 14 year age group includes two clearly differenti-

18. Some of the differences be-tween the total rates for each re-gion are due to the fact that casesfor which the cause of death wasa missing value were not consid-ered for the analysis.


BUENOS AIRES

ated age groups: the one which corresponds to the school pe-riod (five to 12 years) and the one that is the beginning of ado-lescence (13 and 14 years). However, it was not possible todiscern patterns of mortality for these two groups since process-ing of this kind would have exceeded the capacity of the presentstudy. However, it is possible to determine some of the moststriking characteristics of each of these groups through theanalysis carried out for 1989 by the National Health StatisticsDirectorate.(19) In this study, the data have been processed atthe level of the three regions (Capital Federal, GBA1 and GBA2)so data disaggregated at district level are not provided. Themost striking conclusions from this study are:

• There are no differences between the specific mortality ofschool-children (five-12 years) and of adolescents (13 and 14years) in Capital Federal (32 per 100,000 in both cases). How-ever, both in GBA1 and in GBA2, mortality in adolescents ishigher than in school children (25 and 37 per 100,000 inGBA1 and 26 and 49 per 100,000 for GBA2, respectively).

• Violent deaths are more common among adolescents thanamong school-children.

19. Ministry of Health and SocialAction (1994).


14154262519944

290119524338131312

11142251615931

472189

1092668

383550


TotalViolenceRespiratory diseases.Cardiovascular diseasesOthersInfectious diseasesCongenital anomaliesTumours






29.8611.445.515.294.021.910.850.85

26.5410.894.763.943.481.191.191.10

28.9410.956.524.173.912.350.780.26

100.0038.3018.4417.7313.486.382.842.84

100.0041.0317.9314.8313.104.484.484.14

1000.0037.8422.5214.4113.51

8.112.700.90


BUENOS AIRES

• Among violent deaths, deaths from accidents predominate inall three regions and among these those caused by motorvehicles predominate.

g. Population Aged between 15 and 49 Years

The mortality rate for the population aged between 15 and 49years in the Metropolitan Area of Buenos Aires was 17.6 per10,000 for 1991. The rate does not differ greatly between thethree regions, with Capital Federal, GBA1 and GBA2 having ratesof 17.6, 17.9 and 17.4 per 10,000 respectively.

Differences between maximum and minimum rates are great-est in GBA1. Avellaneda, with 29.3 per 10,000, has a rate al-most 100 per cent higher than that for Vicente López and Lanús,the districts with the lowest mortality rate.

In GBA2, the gap between the highest and lowest rates is notas marked, that for San Fernando being almost 65 per centgreater than that for Berazategui, the district in GBA2 with thelowest mortality for this age group. The remaining districts fluc-tuate around the average for the region.

Mortality by cause(20) (see Table 8) shows that “cardiovasculardiseases” are the first cause of death in all three regions. “Vio-lence” is the second cause in GBA1 and GBA2 followed by “tu-mours” and those classified as “others”. In Capital Federal, onthe other hand, the second cause of death is tumours whilstviolence comes third. What is striking is that the rate for respi-ratory diseases is double that for GBA1 and GBA2.

This age group can also be divided into two sub-groups withdifferent characteristics. On the one hand, there is the 15 to 19year age group which makes up the adolescent population and,on the other hand, the 20 to 49 year age group which makes upthe already adult population. As the processed data do notmake it possible to analyze mortality with respect to these twogroups, the main conclusions with reference to them will betaken from the study carried out by the National Health Statis-tics Directorate(21) for the three regions of the Metropolitan Areain 1989.

Population Aged between 13 and 19 Years:

• Specific mortality for this age group was highest in GBA2(7.1 per ten thousand) followed by GBA1 and finally CapitalFederal with 5.6 and 4.3 per 10,000, respectively.

• Violence was the first cause of death, the proportion beinghighest in GBA2 (58.6 per cent of all deaths). In GBA1 andCapital Federal, the figures are 57.1 and 49.6 per cent, re-spectively.

• Within violence, accidents predominate (63.1, 55.1, and 59.6per cent for Capital Federal, GBA1 and GBA2, respectively).In GBA1 and GBA2 homicides occupy second place (35.9 and35.4 per cent against 6.2 per cent in Capital Federal). Thehigh proportion of suicides in Capital Federal compared toGBA1 and GBA2 is striking (30.7, 9 and 5.1 per cent of totaldeaths by violence).


21. Ministry of Health and SocialAction (1994).


BUENOS AIRES

Population Aged between 20 and 49 Years:

• Specific mortality was higher in GBA2 than in Capital Fed-eral and GBA1 (18.4, 1.8 and 2.2 per 10,000, respectively).

• Mortality among males was higher (almost double) than infemales in all three regions.

• Cardiovascular diseases predominated as first cause of death(approximately 38 per cent of deaths for the three regions).In Capital Federal tumours came second whilst in GBA1 andGBA2 this place was occupied by violence with 25.6 and 28.6per cent of the total of corresponding deaths.

• In relation to maternal mortality rates, the figures reachedare low in relation to the rate for the whole country (5.2 per10,000 live births) with 3.3, 2.3, and 3.9 per 10,000 live birthsin Capital Federal, GBA1 and GBA2, respectively. Accordingto this study, these rates would indicate substantial under-recording. The lower rates for GBA1 than for Capital Federalare due certainly to the fact that they are recorded in theplace where death occurred and not in the place of habitualresidence.


TotalViolenceRespiratory diseasesCardiovascular diseasesOthersInfectious diseasesCongenital anomaliesTumours







239377755053537287648

43961362121081866917414815

24997145724944751726210

1349288

2555150

1418701

17.745.764.083.972.760.640.470.06

17.205.334.743.202.620.680.580.06

17.615.034.033.483.351.210.440.07

100.0032.4722.9822.3615.553.642.670.33

100.0030.9827.5318.6115.223.963.370.34

100.0028.5722.8919.7719.016.882.480.40


BUENOS AIRES

24. See reference 22.

25. Some of the differences be-tween the total rates for each re-gion are due to the fact thatcases for which the cause ofdeath was a missing value werenot considered for the analysis.

h. Population Aged between 50 and 64 Years

The Metropolitan Area has a mortality rate for this age groupof 11 per 1,000, a figure similar to that observed in the provinceof Buenos Aires for the same year (11.3 per 1,000).(22) CapitalFederal, GBA1 and GBA2 do not show any differences with re-gard to this average with rates of 11.0, 11.0 and 11.1 per 1,000,respectively.

The districts which make up GBA1 do not reveal great differ-ences from the average for the region with the exception ofAvellaneda where the rate is nearly 50 per cent higher than theaverage.

In GBA2, San Fernando, with a rate of 14.3 per 1,000, andMerlo, with 12.2 per 1,000, are the districts which present highermortality for this age group. The others fluctuate around theaverage.

Mortality by cause(23) shows that cardiovascular diseases, tu-mours, those classified as “others” occupy first, second and thirdplaces as causes of death in all three regions. Respiratory andinfectious diseases are not preponderant in any of the threeregions. The rate for violence in GBA2 is double that for CapitalFederal and GBA1.

i. Population aged 65 Years and Over

The mortality rate in the Metropolitan Area for the populationaged 65 years and over was 54.8 per 1,000 in 1991, a level verysimilar to that of the province of Buenos Aires for the same pe-riod (53.4 per 1,000).(24) Both Capital Federal, and GBA1 andGBA2 have similar rates although the rate for GBA2 is slightlylower.

Within GBA1, Avellaneda stands out with a rate of 81.8 per1,000, nearly 100 per cent more than that for Tres de Febrerowith a rate of 43.01 per 1,000. The remaining districts fluctu-ate within a range of 48 to 60 per 1,000.

In GBA2, San Fernando has the highest mortality rate with65.4 per 1,000, followed by Lomas de Zamora (58.7 per 1,000)and Merlo (57.8 per 1,000). Quilmes and La Matanza have thelowest figures (47.2 and 48.6 per 1,000) and the other districtsfluctuate with rates around the average.

Again, cardiovascular diseases are the first cause of death inthis population, followed by tumours, those diseases classifiedas “others” and “respiratory diseases(25)”

22. Ministerio de Salud y AcciónSocial (1993), Estadisticasvitales: información básica 1991(Life and death statistics: basicinformation for 1991), BuenosAires.



BUENOS AIRES

IV. CONCLUSIONS

THE DATA PRESENTED here show how, as the data aredisaggregated to lower geographical levels, the different situa-tions in relation to living conditions and health which the peo-ple in different city areas face become apparent. They reveal aheterogeneity which is concealed when only indicators for citiesor metropolitan regions are considered. In this way, geographi-cal inequality is useful as a tool to identify inequalities whichexist between different social groups.

From this perspective, the study shows how, for the differentage groups considered, the distribution of mortality reveals greatdifferences between the three regions within the MetropolitanArea and among the districts in each region. Moreover, infantmortality - the best indicator for detecting situations of socialvulnerability - appears to be clearly related to the distributionof the indicators for unsatisfied basic needs and access to edu-cation, housing and sanitation.

The analysis of causes of death shows different situations ineach district according to the age group considered. It is obvi-ous that the distribution of causes of death tends to be similarwhen one analyzes the older age groups; it is infant mortalitywhich most clearly marks the relation between socio-economiclevels and levels of access to services and conditions of health.This is due to a large extent to the fact that the classificationused to categorize the adult age groups corresponds to the groupof causes fixed in the International Classification of Diseases(ICE), 9th Revision, and this appears to be somewhat inadequatefor the detection of the health problems facing these groups.Problems such as drug addiction, alcoholism, depression, anxi-ety, stress, family violence, AIDS, problems related to environ-mental pollution, etc. are very difficult to detect using the clas-sification methodology proposed in the ICE.

In this sense the whole picture of the health status of the popu-lation is influenced not only by the actual health-disease expe-rience of individuals but also by the analytical and conceptualframework that is used to apprehend and understand reality.Thus, the final “diagnosis” of how people live and die will be theresult of a combination of different factors.

• The design of national health information systems: the vari-ables included the methodology for the collection of the popu-lation statistics and the classification systems used to analyzethe resulting information.

• The reliability of the information collected: the levels of un-der-recording, the quality of information gathering, the levelof training of those entrusted with recording the data at pri-mary level (e.g., doctors in the case of death certificates).

• How different factors related to living conditions of the popu-lation interact and impact the health situation of the differentsocial groups which will be reflected in the data, dependingon the ability of the systems to detect these processes.

• Access to the health services and the quality of care which


BUENOS AIRES

these provide, which determines that certain situations of so-cial and environmental vulnerability affecting specificpopulations can be overcome and attenuated by accessibleand efficient services.

Future studies on inequality in health should be supplementedby more detailed studies for the aspects mentioned so that thediagnosis can address the problems of both poor living condi-tions and inadequate access to health services, and the designand quality of the information systems used to evaluate thesesituations.

Finally, what has been said above brings out the real problemfacing both research workers and policy makers: the methodo-logical difficulties inherent in health data. This situation, widelyrecognized, produces the paradox of a kind of information defi-ciency in contexts where a large amount of data is produced.On the one hand, those who are working in research make clearthe limitations of the existing data for the production of aca-demically valid information for comparison between differentpopulations which will make it possible to show the complexpicture of health in the population. On the other hand, thosewho are working in local environments, taking decisions on thedistribution of resources, the implementation of policies of pre-vention, the management of critical situations, etc. come upagainst the fact that existing data are not valid at low levels ofdisaggregation and are out of date. Both groups, in turn, arefacing the common problem that conventional health informa-tion systems are highly inefficient in identifying the new healthproblems which urban societies are facing.

From what has been said above, in the study of inequality inhealth it is essential that progress be made in the developmentof health information systems starting from a fundamental de-bate on the interrelation between social and epidemiological dataand which makes it possible to incorporate the complex prob-lems facing people who live in today’s cities.

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