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OCR for page 487
CLinking DHS Surveys to
United Nations City Data
Until 2000, the city population data published in the United Nations Demographic
Yearbook were not computerized in any publicly accessible form. Thanks to the
efforts of Alice Clague of the United Nations, the panel was able to secure a
new database (United Nations, 2000) containing a prepublication version of the
city population data that appear in the 1998 Demographic Yearbook. Although
our computer file lacked some of the detail of the published table, it supplied
the framework we needed to construct the merged city population dataset used
throughout this report. To lengthen the time span of these data, we supplemented
the computer file by keying in city population data from three earlier years of the
Demographic Yearbook (United Nations, 1987, 1992, 1998a).
Drawing on these data and another computer file (United Nations, 2001) con-
taining the statistical annexes to a recent volume of World Urbanization Prospects,
we assembled a composite city database that includes the following:
· Raw population counts and estimates for capital cities and agglomerations
of 100,000 population and above, taken from four recent volumes of the
United Nations Demographic Yearbook
· Extrapolated data series from World Urbanization Prospects (United Na-
tions,2001) for cities of 750,000 population and above, covering the period
1950 to 2000 at 5-year intervals
· Recent population estimates for capital city urban agglomerations, also taken
from United Nations (2001) and earlier years of this publication
For cities of under 750,000 population (other than capital cities), only the
Demographic Yearbook population counts are available.
487
OCR for page 488
488
CITIES TRANSFORMED
The panel then faced a problem in linking the United Nations city-level data
to survey data on individuals and households from the Demographic and Health
Surveys (DHS). Until recently the DHS program did not release information on
the geographic locations of its sampling clusters, evidently to protect the confi-
dentiality of the survey respondents. In the surveys available to the panel, not
even the city name is provided for urban residents. This restriction means that if
the DHS data are to be linked to data on cities, the only option is to forge the link
using whatever geographic indicators are reported in the surveys.)
Most DHS surveys provide information on the region of the country in which
a sampling cluster is located, although the surveys vary greatly in the extent of
regional detail, with some countries specifying regions very broadly in geograph-
ical terms. All DHS surveys contain information on whether the sampling cluster
is urban or rural in character, presumably following the definitions used by the
country's national statistics office. Unfortunately, the population size of the urban
area in which a cluster is located is not given; rather, its size is loosely character-
ized in broad, almost qualitative terms. In Round 1 of the DHS program, urban
areas were characterized as being either large or small cities. Since Round 2,
three categories have been used: capitals and large cities, small cities, and towns.
Large cities are defined as those with populations of 1 million or more; the small
city category contains all cities in the wide range from 50,000 to 1 million pop-
ulation; and towns are the residual category for urban areas below 50,000 in size
(Demographic and Health Surveys, 1994, 2001~.
THE MATCHING PROCEDURE
Faced with these difficulties, the panel undertook to match the DHS data on region
and city size, as broadly and qualitatively defined, to the United Nations estimates
of the population sizes of specific individual cities.2 Using the available DHS data
and reports, together with geographic atlases (e.g., Cohen, 1998b), we found that
we could link the data in two ways. Often enough information was available for
us to match a sampling cluster to a specific city. Sometimes, however, we lacked
sufficiently detailed geographic variables from the DHS to identify a specific city
of residence, but were able to winnow the possibilities to a set of cities. The latter
type of linkage occurred more often in the Round 1 DHS surveys (whose urban
characterizations were cruder than those in Rounds 2 and 3) and in more populous
countries and those with higher levels of urbanization (which usually have more
. . . . . .
caches In any given geographic regions.
iWe are indebted to Narayan Sastry of RAND Corporation for providing us with sampling cluster
identifiers for the 1986 Brazilian DHS, a survey undertaken in an era in which the DHS program
supplied such identifiers. Of the 90 DHS surveys used in our analyses, this is the only one allowing a
precise match between sampling clusters and residence in particular cities.
2Edward Hui (Brown University) made a major contribution to this effort.
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LINKING DHS SURVEYS TO UNITED NATIONS CITY DATA
489
In the case of the unique matches, the panel assigned a city size value taken
from the merged United Nations database described above. Our aim was to use
a city population estimate for 1990 a year roughly midway in the course of the
DHS program or the nearest available year. In deciding among the different
United Nations population estimates, we gave first preference to the World Urban-
ization Prospects estimate, but if this was unavailable turned to the Demographic
Yearbook estimate for the urban agglomerations or, if necessary, to the Yearbook
estimate for the city proper.
For the cases in which a DHS sampling cluster could be linked only to a set of
cities, we constructed the weighted average of the 1990 populations for the cities
in the set, using the city populations themselves as weights, and assigned this
weighted average to the DHS sampling cluster. The idea was to assign the city
population value that would be expected if a person were to be drawn at random
from the set of cities.
THE RESULT: CITY SIZE RANGES
Clearly there is much room for subjective errors and imprecision in the final re-
sults of this matching procedure. It is unfortunate that until recently the DHS
program has had no mechanism in place to allow its survey clusters to be linked
directly to city identifiers; having such a mechanism would have eliminated one
source of error (see Appendix F for the panel's recommendation for meeting this
need). As we have discussed, the United Nations population estimates are them-
selves subject to errors and substantial differences in definitions. In view of the
many uncertainties involved, all city sizes are classified in ranges of population
size in the panel's analyses using DHS data, rather than being expressed as point
estimates. We chose ranges that appeared to be narrow enough to be informative,
yet broad enough to mitigate the effects of matching and other errors. In our anal-
yses of DHS data, we do not make use of population growth rates for cities and
sets of cities, although that possibility deserves further research attention.
DHS SURVEYS USED IN THIS REPORT
The following tables provide information on the DHS surveys examined in this
report, which are limited to those datasets that had been released and were avail-
able to the panel as of the beginning of 2000. (Many more DHS surveys have
been made available since then, but they could not be included.) Table C-1 lists
the countries whose surveys were examined by the panel, with the year of the sur-
vey indicated. Table C-2 gives each country's urban definition precisely as it is
recorded by the United Nations. Table C-3 lists the cities of these countries whose
populations fell into the 1-5 million range in 1990 or the closest year to it for
which a calculation was possible, and also lists the cities with more than 5 million
population.
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490
CITIES TRANSFORMED
TABLE C-1 Countries with a Demographic and Health Survey Included in the Panel's
Dataset, by Region (survey year in parentheses)
Region Countries Surveyed
North Africa Egypt (1988, 1992, 1995), Morocco (1987, 1992), Tunisia
(1988)
Sub-Saharan Africa Benin (1996), Botswana (1988), Burkina Faso (1993),
Burundi (1987), Cameroon (1991, 1998), Central African
Republic (1994-95), Chad (1996-97), Comoros (1996),
Cole d'Ivoire (1994), Ghana (1988, 1993, 1998-99),
Kenya (1989, 1993, 1998), Liberia (1986),
Madagascar (1992, 1997), Malawi (1992, Mali (1987,
1995-96), Mozambique (1997), Namibia (1992),
Niger (1992, 1998), Nigeria (1990), Rwanda (1992),
Senegal (1986, 1992-93, 1997), Sudan (1989-90),
Tanzania (1991-2, 1996), Togo (1988, 1998),
Uganda (1988-89, 1995), Zambia (1992, 1996),
Zimbabwe (1988, 1994)
South-East Asia Indonesia (1987, 1991, 1994, 1997), Philippines (1993,
1998), Thailand (1987)
South and West Asia Bangladesh (1993-94, 1996-97), India (1992), Kazakhstan
(1995), Republic of Kyrgyzstan (1997), Nepal (1996),
Pakistan (1990-91), Sri Lanka (1987), Turkey (1993),
Uzbekistan (1996), Yemen (1991)
Latin America Bolivia (1989, 1994, 1998), Brazil (1986, 1996),
Colombia (1986, 1990, 1995), Dominican Republic (1986,
1991, 1996), Ecuador (1987), E1 Salvador (1985),
Guatemala (1987, 1995, 1999), Haiti (1994-95), Mexico
(1987), Nicaragua (1998), Paraguay (1990), Peru (1986,
1991-92, 1996), Trinidad and Tobago (1987)
TABLE C-2 Urban Definitions in the Countries with a DHS Survey in the Panel's
Dataset, as Recorded by the United Nations
Country Definition
Bangladesh
Benin
Bolivia
Botswana
Brazil
Burkina Faso
Burundi
Places having a municipality (pourashava), a town
committee (shahar committee), or a cantonment board.
Localities with 10,000 or more inhabitants.
Localities with 2,000 or more inhabitants.
Agglomerations of 5,000 or more inhabitants where 75
percent of economic activity is nonagricultural.
Area internal to the urban perimeter of towns and cities as
defined by municipal law.
The sum of 14 towns.
Commune of Bujumbura.
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LINKING DHS SURVEYS TO UNITED NATIONS CITY DATA
TABLE C-2 continued
Country Definition
Cameroon
Central African Republic
Chad
Colombia
Comoros
491
Cole d'Ivoire
Dominican Republic
Ecuador
Egypt
E1 Salvador
Ghana
Guatemala
Haiti
India
Indonesia
Kazakhstan
Kenya
Kyrgyzstan
Urban centers.
Twenty principal centers with a population of over 3,000.
Administrative centres of prefectures, sous-pre'fectures and
administrative posts.
Population living in a nucleus of 1,500 or more inhabitants.
Administrative centers of prefectures and localities with
5,000 or more inhabitants.
Urban agglomerations containing more than 10,000
inhabitants; agglomerations of from 4,000 to 10,000
persons with more than 50 percent of households engaged
in nonagricultural activities; and the administrative centers
of Grand Lahoun and Dabakala. Excludes the milieux
urbain of Bouna, which has a population of 11,000.
Administrative centers of comunas and municipal districts.
Capitals of provinces and cantons.
Governorates of Cairo, Alexandria, Port Said, Ismailia, and
Suez; frontier governorates; and capitals of other
governorates and district capitals (markaz).
Administrative centers of municipios.
Localities with a population of 5,000 or more.
Municipio of Guatemala Department; officially recognized
centers of other departments and municipalities. Urban
population for 1981 is officially adjusted to include the
urbanized suburbs bordering the municipio of Guatemala,
consistent with the previous census.
Administrative centers of communes.
Towns (places with municipal corporation, municipal area
committee, town committee, notified area committee, or
cantonment board); and all places having 5,000 or more
inhabitants, a density of not fewer than 1,000 persons per
square mile or 390 per square kilometer, pronounced urban
characteristics, and at least three-fourths of the adult male
population employed in pursuits other than agriculture.
Municipalities (kotamadya), regency (kabupaten) capitals
and other places with urban characteristics.
Cities and urban-type localities, officially designated as
such, usually according to the criteria of number of
inhabitants and predominance of agricultural or
nonagricultural workers and their families.
Towns with 2,000 or more inhabitants.
Cities and urban-type localities, officially designated as
such, usually according to the criteria of number of
inhabitants and predominance of agricultural or
nonagricultural workers and their families.
(continued)
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492
TABLE C-2 continued
Country Definition
Liberia
Madagascar
Malawi
Mali
CITIES TRANSFORMED
Mexico
Morocco
Mozambique
Namibia
Nepal
Nicaragua
Niger
Nigeria
Pakistan
Paraguay
Peru
Philippines
Rwanda
Senegal
Sri Lanka
Localities with 2,000 or more inhabitants.
Centers with more than 5,000 inhabitants.
All townships, town planning areas, and district centers.
Localities with 5,000 or more inhabitants and district
centers.
Localities with 2,500 or more inhabitants.
Urban centers.
Conselho of Maputo and Beira.
The censuses are thought to be underenumerated, but the
underenumeration is almost solely in the rural areas.
Hence, the census population counts for urban areas (1951
and 1960) and for Windhoek (1951, 1960, 1981) are
accepted, but the 1992 Revision for the total population is
used to estimate the "true" census count for all three dates.
The 1951 and 1960 percentage urban is estimated by
dividing the census count of urban population by the
above-estimated "true" census counts. To obtain the urban
population at the time of the 1981 census, it was noted that
in 1951 and 1960, 30 percent of the urban population lived
in Windhoek. Therefore for 1981, the census-counted
Windhoek population was accepted and was divided by 0.30
to obtain an estimated urban population.
Localities with 9,000 or more inhabitants (panchayats).
Administrative centers of departments and municipios.
Urban centers (27 towns).
Towns with 20,000 or more inhabitants whose occupations
are not mainly agrarian.
Places with municipal corporation, town committee, or
cantonment.
Administrative centers of the official districts of the
Republic.
Populated centers with 100 or more dwellings grouped
contiguously and administrative centers of districts.
All cities and municipalities with a density of at least 1,000
persons per square kilometer; administrative centers, barrios
of at least 2,000 inhabitants, and those barrios of at least
1,000 inhabitants which are contiguous to the administrative
center, in all cities and municipalities with a density of at
least 500 persons per square kilometer; and all other
administrative centers with at least 2,500 inhabitants.
Kigali; administrative centers of prefectures and important
agglomerations and their surroundings.
Agglomerations of 10,000 or more inhabitants.
Municipalities, urban councils, and towns.
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LINKING DHS SURVEYS TO UNITED NATIONS CITY DATA
TABLE C-2 continued
Country Definition
493
Sudan Localities of administrative or commercial importance or
with a population of 5,000 or more inhabitants.
Thailand Municipalities.
Togo Seven urban communes.
Trinidad and Tobago Port-of-Spain, Arima borough, and San Fernando town.
Tunisia Population living in communes.
Turkey Population of the localities within the municipality limits of
Uganda
administrative centers of provinces and districts.
Population of all settlements as small as trading centers
with as few as 100 inhabitants.
United Republic of Tanzania Gazetted townships.
Uzbekistan Cities and urban-type localities, officially designated as
such, usually according to the criteria of number of
inhabitants and predominance of agricultural or
nonagricultural workers and their families.
The entire former colony of Aden, excluding the oil refinery
and villages of Al Burayqah and Bi'r Fuqum for the former
Democratic Yemen, and six main towns for the former
Yemen.
Yemen
SOURCE: United Nations (1998b: 37-55~.
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494
CITIES TRANSFORMED
TABLE C-3 Large Cities in the Countries Covered by DHS Surveys in the Panel's
Dataset, by Region
Population circa 1990
Region
North Africa
1 to 5 Million
Egypt: Giza, Alexandria; Morocco:
Rabat, Casablanca; Tunisia: Tunis
Cameroon: Douala; Cole d'Ivoire:
Abidjan; Ghana: Accra; Kenya:
Nairobi; Mozambique: Maputo;
Nigeria: Ibadan; Senegal: Dakar;
Sudan: Omdurman, Khartoum;
Tanzania: Dar es Salaam; Zimbabwe:
Harare
Indonesia: Palembang, Tangerang,
Medan, Surabaya, Bandung;
Philippines: Quezon City
Over 5 Million
Egypt: Cairo
Sub-Saharan Africa
Southeast Asia
South, Central, West Asia Bangladesh: Chittagong; India:
Ludhiana, Varanasi, Kalyan,
Visakhapatnam, Bhopal, Ulhasnagar,
Madurai, Patna, Coimbatore, Indore,
Vadodara, Kochi, Surat, Jaipur,
Lucknow, Nagercoil, Napur, Kanpur,
Pune, Ahmedabad, Bangalore,
Hyderabad; Kazakhstan: Almaty;
Pakistan: Multan, Rawalpindi,
Peshawar, Gujranwala, Faisalabad,
Lahore; Turkey: Konya, Izmir, Ankara;
Uzbekistan: Tashkent
Bolivia: La Paz; Brazil: Santos,
Belem, Campinas, Nova Igua5cu,
Brasilia, Curitiba, Fortaleza, Salvador,
Recife, Porto Alegre, Belo Horizonte;
Colombia: Barranquilla, Cali,
Medell~n, Santa Fe de Bogota;
Dominican Republic: Santo Domingo;
Ecuador: Quito, Guayaquil; El
Salvador: San Salvador; Guatemala:
Guatemala City; Haiti: Port-au-Prince;
Mexico: Ecatepec, Netzahualcoyotl,
Puebla de Zaragoza, Monterrey,
Guadalajara,
Latin America
Nigeria: Lagos
Indonesia: Jakarta;
Philippines:
Manila; Thailand:
Bangkok
Bangladesh:
Dhaka; India:
Madras, Delhi,
Calcutta, Mumbai;
Pakistan: Karachi;
Turkey: Istanbul
Brazil: Rio de
Janeiro, Sao Paulo;
Mexico: Mexico
City; Peru: Lima
Representative terms from entire chapter:
administrative centers
