Monday, April 21
Grant Miller: Managerial Incentives in Public Service Delivery
Alvarez, Gerardo, Francisco Lara, Sioban D. Harlow, and Catalina Denman. 2009. "Infant mortality and urban marginalization: a spatial analysis of their relationship in a medium-sized city in northwest Mexico." Revista Panamericana De Salud Publica-Pan American Journal of Public Health, 26(1): 31-38.
Objective. To identify areas with high risk of infant mortality and any possible correlation with the population's socioeconomic status through the use of a geographic information system and spacial analysis techniques.
Methods. An exploratory ecologic study was conducted in Hermosillo, the capital of Sonora, Mexico, in 2000-2003. The urban marginalization index (UMI) and the infant mortality rate (IMR) were determined for each of the city's basic geostatistical areas (BGA). The UMI and IMR were statistically calculated to identify geographic areas in which they were concentrated and to determine the degree of spatial correlation between these indicators. To determine the general spatial autocorrelation and spatial clustering of UMIs and IMRs within the city and the BGAs, Morans I index, Ipop statistics, and Besag and Newell's method were employed.
Results. The mean IMR was 14.3 per 1000 live births, higher in the BGAs with greater social marginalization (16.2 per 1000) and lower in those with less (11.7 per 1000). The UMI range was -3.1-6.6 (maximum: 4.3; minimum: -2.7). Autocorrelation was found among the UMI (Moran I = 0.62), with significant clustering in the city's northwest, northeast, and southeast parts. Local clustering of high IMRs was found in Hermosillo's central and western areas, albeit without autocorrelation ( Moran I = -0.007). High risk areas (high IMR and high UMI) were found in the city's northwestern section.
Conclusions. Spatial clusters with high IMR were found in socially marginalized areas in the northwestern part of Hermosillo, a city of medium size located in northwestern Mexico. These results, reached through a combination of spatial analysis techniques and geographic information tools can help guide interventions specifically designed for these high risk residential areas.
Country of focus: Mexico.