Since 1990, the United Nations Development Programme has been tracking the socioeconomic performance of nations using the Human Development Index (HDI), a composite indicator that measures education, health and living standards. In order to better understand the dynamics of health and well-being at the metropolitan level (rather than at the national level), LSE Cities has recalibrated available data for 129 urban areas. The map above shows how metropolitan regions perform in terms of health, indicating life expectancy figures where they are available, while the dataset on the facing page ranks the regions in order of performance across all three dimensions of development – health, education and wealth
Given that most publically available data on health is not based at the official municipal or metropolitan level, the new LSE Cities index has been calculated using ‘extended metropolitan regions’ (EMR) to ensure a degree of geographical comparability across the sample of metropolitan areas (see p. 14) and their available datasets. To compensate for regional imbalances, each metropolitan area has been compared to its country’s performance and ‘pegged’ against internationally comparable data at the national level. In relation to health scores, for example, most weight was given to life expectancy and infant mortality rate. When only one or neither of these was available, child immunisation rates or the number of doctors or hospital beds per person were taken into account. A full description of the methodology and data sources is available online.
The data suggests that almost all of the 129 metropolitan regions analysed outperform their national contexts. Only 19 under-perform in health, ten in education and 14 in wealth. Metropolitan regions tend to outperform their national contexts most in the wealth dimension, followed by education and then health, but there is a considerable range of performances across all dimensions. The table on the adjacent page reveals that many regions in the sample do not score equally well on all three dimensions. High-income Asian and West European areas achieve their highest scores in health – with Hong Kong at the top – while Sydney and North American areas tend to score higher in education and wealth than in health. Chinese and Indian metropolitan regions tend to score much lower in education than they do in either health or wealth, while this trend is reversed in Sub-Saharan Africa, where the large majority score lowest in health. These patterns indicate that the level of performance of metropolitan regions is tightly linked to the level of development and welfare regime of the nation in which they exist.
The map demonstrates how high-income Asian regions do better than all others (with a score of 0.87 out of 1 on average), while West European areas and Sydney come second (0.81), followed by their North American counterparts (0.76). Eastern European and Mexican metropolitan regions share a score of 0.65 on average, while those in China (0.61) score marginally higher than their South American peers (0.60). The lower end of the distribution is made up of North African and Middle-Eastern city regions (0.57 on average), South East Asia (0.55), South Asia cities (0.49) and, trailing even further behind, those in Sub-Saharan Africa (0.27).
Despite these strong regional patterns, the data suggests that metropolitan regions with significantly different health scores exist in very close proximity to each other. The largest gap is in South America, between Santiago in Chile (0.76) and Bolivia’s La Paz (0.47), followed by the difference between the high-scoring Hong Kong (0.88) and Singapore (0.86) and their respective neighbours, South Guangdong in mainland China (0.60) and Jakarta in Indonesia (0.58). Within the European continent there are wide discrepancies, with Stockholm in Sweden performing very well at 0.85 while Moscow in nearby Russia falls to 0.60, and relatively close cities like Athens and Istanbul score respectively 0.77 and 0.57. In Asia, even though Ho Chi Minh City in Vietnam and Phnom Penh in Cambodia are only just over 200 kilometres (124 miles) apart, there is a substantial score difference of 0.22. Major variations also exist at the lower end of the scale in Africa, where Dar es Salaam in Tanzania fares twice as well as Lusaka in Zambia (0.36 versus 0.18) , while India’s Chennai’s outperforms Faisalabad in Pakistan, with a score of 0.57 compared to 0.41.
The performance of a number of selected case studies is discussed in detail overleaf.
Sources: UN Development Programme (2011). Human Development Report Database. [hdr.undp.org/en/statistics/data/] UN Population Division (2011). World Population Prospects: The 2010 Revision Population Database. [esa.un.org/wpp]. Various international, regional and national statistical sources were used to calculate the Extended Metropolitan Region health, education and wealth indices. A full list is available at urban-age.net. The population of the Extended Metropolitan Regions were based on national statistical sources and the UN World Urbanisation Prospects, 2009 Revision.