Spatial pattern analysis of the impact of community food environments on foetal macrosomia, preterm births and low birth weight.

IF 1 4区 医学 Q4 HEALTH CARE SCIENCES & SERVICES Geospatial Health Pub Date : 2024-05-07 DOI:10.4081/gh.2024.1249
Micaela Natalia Campero, Carlos Matías Scavuzzo, Carlos Marcelo Scavuzzo, María Dolores Román
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Abstract

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.

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社区食品环境对胎儿巨大儿、早产和低出生体重影响的空间模式分析。
社区食品环境(CFEs)对儿童的健康和营养有很大影响,目前在许多地区这种影响是负面的。在阿根廷共和国,还缺乏通过基于地理信息系统(GIS)的工具对社区食品环境进行区域性和综合性评估的研究。本研究旨在通过与 CFEs 三个维度(政治、个人和环境)相关的变量,描述 CFEs 的空间模式及其与阿根廷城市地区空间分布的关联。对 657 个居民人数≥ 5000 人的地区进行了 CFEs 评估。出生和 CFEs 数据来自全国公开来源数据和遥感数据。采用热点分析、纯空间分析(SaTScan)、莫兰指数、半变量图和空间约束多元聚类等方法对空间分布和集群的存在进行了评估。在该国中东部地区发现了低出生体重儿、大畸形和早产的低风险集群,而在北部、中部和南部则发现了高风险集群。在中东部地区,低风险集群与公共政策覆盖率、夜间光照充足率、社会保障覆盖率和户主受过完整中等教育的热点地区相吻合,这些地区是所研究的出生变量负面结果的低风险地区,而基本需求得不到满足的家庭以及农作物和草本植物覆盖的城郊地区的主要土地利用等级则与之相反。这些结果表明,在建立解释性模型和得出对决策有价值的新结论之前,探索出生缺陷的空间模式是一个必要的初步步骤。
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来源期刊
Geospatial Health
Geospatial Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.40
自引率
11.80%
发文量
48
审稿时长
12 months
期刊介绍: The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.
期刊最新文献
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