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Improving Statistics for Improving Statistics for Measuring Development Measuring Development Outcomes Outcomes The need to accommodate rapid The need to accommodate rapid urbanization in the national urbanization in the national statistical plan statistical plan UN-HABITAT, Nairobi UN-HABITAT, Nairobi 26 May, 2003 26 May, 2003

UN-HABITAT, Nairobi 26 May, 2003

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Improving Statistics for Measuring Development Outcomes The need to accommodate rapid urbanization in the national statistical plan. UN-HABITAT, Nairobi 26 May, 2003. World Population Growth Will Be Mainly Urban. Almost All Growth Will Take Place in Cities of Poor Countries. - PowerPoint PPT Presentation

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Improving Statistics for Measuring Improving Statistics for Measuring Development OutcomesDevelopment Outcomes

The need to accommodate rapid The need to accommodate rapid urbanization in the national statistical planurbanization in the national statistical plan

UN-HABITAT, NairobiUN-HABITAT, Nairobi

26 May, 200326 May, 2003

World Population GrowthWorld Population Growth Will Be Mainly Urban Will Be Mainly Urban

Almost All Growth Will Take Place in Cities of Poor CountriesAlmost All Growth Will Take Place in Cities of Poor Countries

Especially in Their Smaller CitiesEspecially in Their Smaller Cities

Developing Country Rapid Urbanizaton Leads to an Increase in Informal Settlements

• Urban growth in developing countries comes primarily from Urban growth in developing countries comes primarily from individuals migrating from the rural areas (Nairobi: 90% of recent individuals migrating from the rural areas (Nairobi: 90% of recent arrivals to the slum areas came from rural Kenya).arrivals to the slum areas came from rural Kenya).

• In the cities of developing countries there is restricted access to In the cities of developing countries there is restricted access to formal serviced land by the urban poor (limited formal land market formal serviced land by the urban poor (limited formal land market activities, and limited access to credit)activities, and limited access to credit)

• The urban irregular informal land market meets the demand of the The urban irregular informal land market meets the demand of the urban poor (and is apparently both more profitable and easier to urban poor (and is apparently both more profitable and easier to develop) Smolka, Lincoln Institute, ref Latin America.develop) Smolka, Lincoln Institute, ref Latin America.

• The result has been a rapid increase in the informal or slum areas. The result has been a rapid increase in the informal or slum areas. The formal serviced land market is not responding to the demand. The formal serviced land market is not responding to the demand.

Need to sample the slum areas

• Slum areas are home health risks equivalent to Slum areas are home health risks equivalent to those in the rural areas.those in the rural areas.

• National statistical practice and planning has National statistical practice and planning has been masking the problems of the urban poor.been masking the problems of the urban poor.

• Poverty is still regarded as a predominantly rural Poverty is still regarded as a predominantly rural problem.problem.

• Sample sizes in the urban areas have been too Sample sizes in the urban areas have been too small to disaggregate into slum areas .small to disaggregate into slum areas .

Where intra-city differentials have been possible the differences are stark.

• In Accra it was estimated that mortality rates were 3 to 5 In Accra it was estimated that mortality rates were 3 to 5 times higher in high density poor areas (Songsore and times higher in high density poor areas (Songsore and McGranahan 1993). However, the perception by national McGranahan 1993). However, the perception by national planners is that those living in Accra are uniformly better planners is that those living in Accra are uniformly better off.off.

• DiDifferentials in malnutrition are consistently larger in fferentials in malnutrition are consistently larger in urban than in rural areas according to a ten country study urban than in rural areas according to a ten country study using the DHS data.using the DHS data.

• There are similar examples from Bangladesh, Philippines, There are similar examples from Bangladesh, Philippines, Kenya.Kenya.

SOCIOECONOMIC DIFFERENTIALS IN CHILD STUNTING ARE CONSISTENTLY LARGER IN URBAN THAN IN RURAL AREAS

Purnima Menon, Marie T. Ruel, and Saul S. MorrisFood Consumption and Nutrition Division

International Food Policy Research Institute

• “Our study showed that children living in urban areas might be up to 10 times more at risk of being stunted if they are from poor households compared to children from households of higher socioeconomic status. The fact that there are consistently such strong socioeconomic gradients in urban areas of developing countries implies that reliance on global average statistics to allocate resources between rural and urban areas could be dangerously misleading, a point originally made by Basta (1977). We have previously shown that the “average” urban child is consistently less likely to suffer from stunting than the “average” rural child (Ruel et al. 1998), yet in virtually every case studied in the present analysis, there was a distinct group of highly vulnerable urban children that should be high on the list of national priorities for nutrition-oriented interventions.”

• “This piece of research demonstrates the dire need for program and policy attention to ameliorate the nutrition situation of the population living in poor urban areas.”

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National Rural Urban Urban Slum

Infant Mortality Higher in Dhaka Slum than in Rural Bangladesh, 1991

SOME URBAN FACTS OF LIFE: IMPLICATIONS FORRESEARCH AND POLICY

Marie T. Ruel, Lawrence Haddad, and James L. Garrett

• “The prevalence of diarrhea among the urban low SES group was also greater than among the rural low SES group in 7 of the 11 countries studied. Thus, overall diarrhea prevalence rates in urban areas rival those found in rural areas, and poor urban dwellers are often worse off than the rural poor in that regard.”

SOME URBAN FACTS OF LIFE: IMPLICATIONS FORRESEARCH AND POLICY

Marie T. Ruel, Lawrence Haddad, and James L. Garrett

Rapid urbanization requires that we begin to routinely provide data on intra-city differentials

• Nearly all the projected urban growth for the next decades Nearly all the projected urban growth for the next decades will be in developing countries. (WUP 2001)will be in developing countries. (WUP 2001)

• The current estimated 924 million slum dwellers could The current estimated 924 million slum dwellers could increase to 1.5 billion by 2020. Almost all of the increase increase to 1.5 billion by 2020. Almost all of the increase in the urban areas of developing countries. in the urban areas of developing countries.

• The current estimate of the percentage of slum dwellers in The current estimate of the percentage of slum dwellers in Sub-Saharan Africa is more that 70%Sub-Saharan Africa is more that 70%

• We have no evidence that this proportion is decreasing; to We have no evidence that this proportion is decreasing; to the contrary the evidence seems to point to an increase in the contrary the evidence seems to point to an increase in the number of urbanthe number of urban poor.poor.

SummarySummary

• Slum dwellers are paying in lives for urbanization that is Slum dwellers are paying in lives for urbanization that is not being addressed by national and local authorities. not being addressed by national and local authorities. (mortality, morbidity, malnutrition)(mortality, morbidity, malnutrition)

• We need to advocate for and ensure that the urban We need to advocate for and ensure that the urban differentials inform policy.differentials inform policy.

• Statistically this means that we must expand urban Statistically this means that we must expand urban coverage and include “slum” strata in the sample design coverage and include “slum” strata in the sample design and encourage national statistical offices also to do this. and encourage national statistical offices also to do this.

• Urgent Need for Spatially-Disaggregated Urban DataUrgent Need for Spatially-Disaggregated Urban Data