Francisco Estupiñán-Romero, Santiago Royo-Sierra, Javier González-Galindo, Manuel Ridao-López, Enrique Bernal-Delgado
{"title":"将社会经济普查数据分配到初级保健地区:小区域分析的改进。","authors":"Francisco Estupiñán-Romero, Santiago Royo-Sierra, Javier González-Galindo, Manuel Ridao-López, Enrique Bernal-Delgado","doi":"10.1016/j.gaceta.2025.102464","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Provide a method for reusing National Institute of Statistics (INE) socioeconomic data and reconstructing the Spanish National Health System primary care areas (PCA) from INE census tracts.</p><p><strong>Method: </strong>The reconstruction of PCA boundaries entailed aligning, assigning, and integrating census tracts within the limits of the PCA using 2022 INE and 2018 Atlas VPM digital maps.</p><p><strong>Results: </strong>36,282 census tracts were assigned to 2,405 PCA. The alignment of digital maps showed a programmatic assignment of 99.7% of the census tracts within PCA; just ten census tracts must be manually assigned. The net average income per capita distribution from INE was consistent along the newly reconstructed PCA.</p><p><strong>Conclusions: </strong>We have proposed a reliable solution to integrate socioeconomic data from INE census statistics into PCA, enhancing data researchers' capacities in joint analyses of socioeconomic determinants and healthcare.</p>","PeriodicalId":94017,"journal":{"name":"Gaceta sanitaria","volume":" ","pages":"102464"},"PeriodicalIF":1.5000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Allocating socioeconomic census data to primary care areas: an improvement in small-area analyses.\",\"authors\":\"Francisco Estupiñán-Romero, Santiago Royo-Sierra, Javier González-Galindo, Manuel Ridao-López, Enrique Bernal-Delgado\",\"doi\":\"10.1016/j.gaceta.2025.102464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Provide a method for reusing National Institute of Statistics (INE) socioeconomic data and reconstructing the Spanish National Health System primary care areas (PCA) from INE census tracts.</p><p><strong>Method: </strong>The reconstruction of PCA boundaries entailed aligning, assigning, and integrating census tracts within the limits of the PCA using 2022 INE and 2018 Atlas VPM digital maps.</p><p><strong>Results: </strong>36,282 census tracts were assigned to 2,405 PCA. The alignment of digital maps showed a programmatic assignment of 99.7% of the census tracts within PCA; just ten census tracts must be manually assigned. The net average income per capita distribution from INE was consistent along the newly reconstructed PCA.</p><p><strong>Conclusions: </strong>We have proposed a reliable solution to integrate socioeconomic data from INE census statistics into PCA, enhancing data researchers' capacities in joint analyses of socioeconomic determinants and healthcare.</p>\",\"PeriodicalId\":94017,\"journal\":{\"name\":\"Gaceta sanitaria\",\"volume\":\" \",\"pages\":\"102464\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2025-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gaceta sanitaria\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.gaceta.2025.102464\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gaceta sanitaria","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.gaceta.2025.102464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Allocating socioeconomic census data to primary care areas: an improvement in small-area analyses.
Objective: Provide a method for reusing National Institute of Statistics (INE) socioeconomic data and reconstructing the Spanish National Health System primary care areas (PCA) from INE census tracts.
Method: The reconstruction of PCA boundaries entailed aligning, assigning, and integrating census tracts within the limits of the PCA using 2022 INE and 2018 Atlas VPM digital maps.
Results: 36,282 census tracts were assigned to 2,405 PCA. The alignment of digital maps showed a programmatic assignment of 99.7% of the census tracts within PCA; just ten census tracts must be manually assigned. The net average income per capita distribution from INE was consistent along the newly reconstructed PCA.
Conclusions: We have proposed a reliable solution to integrate socioeconomic data from INE census statistics into PCA, enhancing data researchers' capacities in joint analyses of socioeconomic determinants and healthcare.