{"title":"意大利城市可持续发展目标 3 指数分析","authors":"","doi":"10.1016/j.puhe.2024.08.014","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>Improving health at global and local scales is one of the 17 Sustainable Development Goals (SDGs) set by the United Nations (UN) for the period 2015–2030, specifically defined by SDG3, which includes 13 targets described by 28 indicators. In this context, the aim of the current study was to propose a protocol to infer SDG3 values at municipality level with the current openly available data.</p></div><div><h3>Study design</h3><p>The study incorporated a quantitative research.</p></div><div><h3>Methods</h3><p>To calculate the SDG3 index, defined as the average of all 13 target scores, official Italian data at five geographical granularities covering the period 2018–2022 were used, and a spatial downscaling strategy was implemented. The quality of matching between original and inferred indicators was assessed applying a specific standard (International Organisation for Standardisation [ISO]/TS 21564) that matches quality between terminology resources with regards to health care. The significance of regional/provincial differences was assessed by the Kruskal–Wallis test with Bonferroni correction, and the Moran's index with queen contiguity method was applied to evaluate clustering tendency.</p></div><div><h3>Results</h3><p>The geographical distribution of scores varied considerably (and with statistical significance) across the targets, with municipalities in the central part of the country achieving relatively good overall performance. Matching quality also varied consistently across targets. Clustering tendency was observed and was likely due to regional differences in data collection protocols.</p></div><div><h3>Conclusions</h3><p>The SDG3 index, as an internationally standardised measure of health, can be used to validate urban health indices; however, considerable improvement by official data providers in Italy is required to guarantee access to data at the municipal level.</p></div>","PeriodicalId":49651,"journal":{"name":"Public Health","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0033350624003615/pdfft?md5=331244318aaf08bbf662ddfd032648ff&pid=1-s2.0-S0033350624003615-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Analysis of the Sustainable Development Goal 3 index for Italian municipalities\",\"authors\":\"\",\"doi\":\"10.1016/j.puhe.2024.08.014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>Improving health at global and local scales is one of the 17 Sustainable Development Goals (SDGs) set by the United Nations (UN) for the period 2015–2030, specifically defined by SDG3, which includes 13 targets described by 28 indicators. In this context, the aim of the current study was to propose a protocol to infer SDG3 values at municipality level with the current openly available data.</p></div><div><h3>Study design</h3><p>The study incorporated a quantitative research.</p></div><div><h3>Methods</h3><p>To calculate the SDG3 index, defined as the average of all 13 target scores, official Italian data at five geographical granularities covering the period 2018–2022 were used, and a spatial downscaling strategy was implemented. The quality of matching between original and inferred indicators was assessed applying a specific standard (International Organisation for Standardisation [ISO]/TS 21564) that matches quality between terminology resources with regards to health care. The significance of regional/provincial differences was assessed by the Kruskal–Wallis test with Bonferroni correction, and the Moran's index with queen contiguity method was applied to evaluate clustering tendency.</p></div><div><h3>Results</h3><p>The geographical distribution of scores varied considerably (and with statistical significance) across the targets, with municipalities in the central part of the country achieving relatively good overall performance. Matching quality also varied consistently across targets. Clustering tendency was observed and was likely due to regional differences in data collection protocols.</p></div><div><h3>Conclusions</h3><p>The SDG3 index, as an internationally standardised measure of health, can be used to validate urban health indices; however, considerable improvement by official data providers in Italy is required to guarantee access to data at the municipal level.</p></div>\",\"PeriodicalId\":49651,\"journal\":{\"name\":\"Public Health\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0033350624003615/pdfft?md5=331244318aaf08bbf662ddfd032648ff&pid=1-s2.0-S0033350624003615-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Public Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0033350624003615\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Public Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0033350624003615","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Analysis of the Sustainable Development Goal 3 index for Italian municipalities
Objectives
Improving health at global and local scales is one of the 17 Sustainable Development Goals (SDGs) set by the United Nations (UN) for the period 2015–2030, specifically defined by SDG3, which includes 13 targets described by 28 indicators. In this context, the aim of the current study was to propose a protocol to infer SDG3 values at municipality level with the current openly available data.
Study design
The study incorporated a quantitative research.
Methods
To calculate the SDG3 index, defined as the average of all 13 target scores, official Italian data at five geographical granularities covering the period 2018–2022 were used, and a spatial downscaling strategy was implemented. The quality of matching between original and inferred indicators was assessed applying a specific standard (International Organisation for Standardisation [ISO]/TS 21564) that matches quality between terminology resources with regards to health care. The significance of regional/provincial differences was assessed by the Kruskal–Wallis test with Bonferroni correction, and the Moran's index with queen contiguity method was applied to evaluate clustering tendency.
Results
The geographical distribution of scores varied considerably (and with statistical significance) across the targets, with municipalities in the central part of the country achieving relatively good overall performance. Matching quality also varied consistently across targets. Clustering tendency was observed and was likely due to regional differences in data collection protocols.
Conclusions
The SDG3 index, as an internationally standardised measure of health, can be used to validate urban health indices; however, considerable improvement by official data providers in Italy is required to guarantee access to data at the municipal level.
期刊介绍:
Public Health is an international, multidisciplinary peer-reviewed journal. It publishes original papers, reviews and short reports on all aspects of the science, philosophy, and practice of public health.