1. Urban Health and Disparities: A Comparison of 57 Cities
Christine Stauber*, Ellis Adams, Dajun Dai, Richard Rothenberg, John Heath
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2. Outline Overview of the Urban Health Index Toolkit and Methods
Description of data source
Selection of Indicators
Results
Ranking, comparison and correlation
Discussion and other applications

3. The Urban Health Index Approach
We adopted a method used by the Human Development Index1 to examine health disparities for small geographic areas.
We standardized indicators for small area units on a (0, 1) interval and combined them using their geometric mean to form an Urban Health Index (UHI).2
The method uses the ratio of the highest and lowest deciles of the UHI and the linear slope of the middle 80% to assess disparities.

4. Urban Health Index Approach
Health indicators
Health determinants
Area boundaries
Demographic base
Standardization
Combination
Distribution
Processing
Mapping
Graphing
Disparity Slope = θ θ A B
Disparity Ratio = A/B

5. 2 3 5 4 6 7

6. Application of the UHI for cities
Selected publicly available datasets from the Demographic and Health Surveys – – most recent dataset available
Identified set of 9 indicators from three domains – environment, women’s education and childhood immunizations
Identified major urban centers and selected data for 57 cities for calculation and comparison

7. Nine indicators used for analysis
Environment -
% of households with access to water piped onto premises
% of households with access to improved sanitation
% of households not using solid fuels
Women’s Education -
% of women (15-49 y.o.) who completed secondary education or higher
% of women (15-49 y.o.) who believe that condom use decrease HIV risk
% of women (15-49 y.o.) that believe having only one partner can decrease HIV risk
Health -
% of children (1-4 y.o.) who have received 3 doses of the DPT vaccine
% of children (1-4 y.o.) who have received 3 doses of the polio vaccine
% of children (1-4 y.o.) who have received the measles vaccine

8. Results
Indicators oriented in positive direction so a higher UHI score indicates higher access to determinants of health
Tirana, Albania had the highest UHI score and therefore the highest rank
Port-Au Prince, Haiti and Monrovia, Liberia had the two lowest scores and were ranked the lowest
Regions presented a broad range of UHI scores with cities in Europe presenting on average the highest scores while cities in Sub-Saharan Africa presenting the lowest but broad variation existed within regions
UHI score appeared to be positively correlated with GNI but there were some important exceptions that deserve more attention

14. Discussion
Cities in the African Region had the lowest UHI scores, followed by those in the Western Pacific and Southeast Asia, the Americas and the European Region.
Cities in the African Region may still be struggling to achieve coverage of the 9 indicators we examined.
As countries and their cities (principally their capital cities) develop economically, they begin to allocate more resources to improve coverage of service such as water and sanitation and access to health services and education as evident in our analysis of log-linear GNI and UHI scores.
However, there are important positive and negative deviations from this trend that deserve consideration.

18. As shown in the bag plot in Figure 22 (and discussed earlier regarding Figure 8), six cities have lower than mean GNI while achieving a high UHI score (>0.6). These cities have demonstrated that they are capable of providing high service coverage while combating a lower gross domestic product. Importantly, they are not all isolated to one region of the world but are from Africa (Nairobi), Europe (Bishkek, Dushanbe, Osh), South East Asia (Kathmandu) and the Western Pacific (Phnom Penh). Tegucigalpa is also highlighted as a city from the Americas that is achieving a relatively high UHI even though the country (Honduras) has a low GNI.

19. Conclusion
The UHI is a flexible measure that can examine a variety of direct indicators, social determinants, and demographic measures in conjunction with other data (e.g., GNI, Gini) and lends itself well to visualization.
A similar analysis for a sub-city level might be of greater value to identify “hot spots” and prioritize areas for remediation
When visualized in conjunction with measures of income or income disparity, the UHI identifies countries that:
Make better use of limited resources (high UHI with low GNI and Gini)
Maintain better resources yet whose problems in health and health disparities persist (low UHI with higher GNI and Gini)
Revisions in the cluster sampling methods used by DHS or similar surveys would provide much improved data sources for this type of city-level analysis, and especially for intra-city analysis

20. References
1 - Human Development Index – Rothenberg et al., – Rothenberg et al., – Bortz et al., 2015 – 5 – Weaver et al., – Stauber et al., – Dai et al.,

21. Thank you! Questions? Acknowledgements: Funding provided in part by WHO Kobe Center