For the attention of: Donors funding urban health and NCD projects, smart city leaders in India, and researchers collecting NCD data
The problem: Health data are often collected in a way that suits national and international needs, not in a way that informs municipal decision-making on health programs in a practical way.
What we did and why: The Building Healthy Cities project collected representative city data and disaggregated it by sub-population. Cross referencing this with spatial geographic data we are better able to understand not only who is really most at risk in the city of Indore, but also where in the city they live.
What our study adds: This analysis adds nuance to the urban health equity discussion, adds to best practices for urban data collection, and is a starting point for discussion of intra-city risk groups in the Indian context.
Implications for city policy and practice: We already know that urbanization can increase health inequities, but important data can be hidden within average prevalence rates. This approach can be used in cities to identify sub-groups at risk of ill health.
In doing this we found that disease risk factors can be compounded, especially on those residents with multiple disadvantages. Our analysis can inform Indore City planners on how to target scarce health resources to decrease disparities. At an international level, a similar approach could be used in many other cities.
Links to other resources and support:
USAID-funded Building Healthy Cities project: Testing healthy urban planning approaches in Indore, India; Makassar, Indonesia; Kathmandu, Nepal; and Da Nang, Vietnam.
Indore Smart City: website
Twitter handles to follow: @JSIHealth, @USAIDAsiaHQ, @IndoreSmartCity
Full research article: Exploring urban health inequities: the example of non-communicable disease prevention in Indore
Authors: @apomeroystevens
Editor: Marcus Grant (@MarcusxGrant)
