Fig 2 - uploaded by Micaela Natalia Campero
Content may be subject to copyright.
Map of the distribution of obesity cases in children aged 2 to 5 years in the localities of the province of Córdoba in 2005.
Context in source publication
Context 1
... see how the integral configuration of the environments determines the dissimilar presence of children with obesity, figure 2 shows the distribution of cases of obesity in the localities included in this study. In the south, there is a lower number of cases of obesity compared to the north-northwest of Cordoba, where there is a concentration of localities with a higher number of reported cases. ...
Similar publications
Citations
... The versatility of this model allows for the addition of characteristics not originally included in the original model (such as the environmental conditions at each location). Furthermore, the study of CFE can be conducted at various scales, both comprehensively through the three dimensions (Campero et al., 2022) and in a disaggregated manner, prioritizing specific aspects or variables based on the needs of each territory (Lytle & Sokol, 2017). ...
Community food environments (CFEs) have a strong impact on child health and nutrition and this impact is currently negative in many areas. In the Republic of Argentina, there is a lack of research evaluating CFEs regionally and comprehensively by tools based on geographic information systems (GIS). This study aimed to characterize the spatial patterns of CFEs, through variables associated with its three dimensions (political, individual and environmental), and their association with the spatial distribution in urban localities in Argentina. CFEs were assessed in 657 localities with ≥5,000 inhabitants. Data on births and CFEs were obtained from nationally available open-source data and through remote sensing. The spatial distribution and presence of clusters were assessed using hotspot analysis, purely spatial analysis (SaTScan), Moran’s Index, semivariograms and spatially restrained multivariate clustering. Clusters of low risk for LBW, macrosomia, and preterm births were observed in the central-east part of the country, while high-risk clusters identified in the North, Centre and South. In the central-eastern region, low-risk clusters were found coinciding with hotspots of public policy coverage, high night-time light, social security coverage and complete secondary education of the household head in areas with low risk for negative outcomes of the birth variables studied, with the opposite with regard to households with unsatisfied basic needs and predominant land use classes in peri-urban areas of crops and herbaceous cover. These results show that the exploration of spatial patterns of CFEs is a necessary preliminary step before developing explanatory models and generating novel findings valuable for decision-making.
