{"title":"Spatial association and modelling of under-5 mortality in Thailand, 2020.","authors":"Suparerk Suerungruang, Kittipong Sornlorm, Wongsa Laohasiriwong, Roshan Kumar Mahato","doi":"10.4081/gh.2023.1220","DOIUrl":null,"url":null,"abstract":"<p><p>Under-5 mortality rate (U5MR) is a key indicator of child health and overall development. In Thailand, despite significant steps made in child health, disparities in U5MR persist across different provinces. We examined various socio-economic variables, health service availability and environmental factors impacting U5MR in Thailand to model their influences through spatial analysis. Global and Local Moran's I statistics for spatial autocorrelation of U5MR and its related factors were used on secondary data from the Ministry of Public Health, National Centers for Environmental Information, National Statistical Office, and the Office of the National Economic and Social Development Council in Thailand. The relationships between U5MR and these factors were modelled using ordinary least squares (OLS) estimation, spatial lag model (SLM) and spatial error model (SEM). There were significant spatial disparities in U5MR across Thailand. Factors such as low birth weight, unemployment rate, and proportion of land use for agricultural purposes exhibited significant positive spatial autocorrelation, directly influencing U5MR, while average years of education, community organizations, number of beds for inpatients per 1,000 population, and exclusive breastfeeding practices acted as protective factors against U5MR (R2 of SEM = 0.588).The findings underscore the need for comprehensive, multi-sectoral strategies to address the U5MR disparities in Thailand. Policy interventions should consider improving socioeconomic conditions, healthcare quality, health accessibility, and environmental health in high U5M areas. Overall, this study provides valuable insights into the spatial distribution of U5MR and its associated factors, which highlights the need for tailored and localized health policies and interventions.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geospatial Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4081/gh.2023.1220","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Under-5 mortality rate (U5MR) is a key indicator of child health and overall development. In Thailand, despite significant steps made in child health, disparities in U5MR persist across different provinces. We examined various socio-economic variables, health service availability and environmental factors impacting U5MR in Thailand to model their influences through spatial analysis. Global and Local Moran's I statistics for spatial autocorrelation of U5MR and its related factors were used on secondary data from the Ministry of Public Health, National Centers for Environmental Information, National Statistical Office, and the Office of the National Economic and Social Development Council in Thailand. The relationships between U5MR and these factors were modelled using ordinary least squares (OLS) estimation, spatial lag model (SLM) and spatial error model (SEM). There were significant spatial disparities in U5MR across Thailand. Factors such as low birth weight, unemployment rate, and proportion of land use for agricultural purposes exhibited significant positive spatial autocorrelation, directly influencing U5MR, while average years of education, community organizations, number of beds for inpatients per 1,000 population, and exclusive breastfeeding practices acted as protective factors against U5MR (R2 of SEM = 0.588).The findings underscore the need for comprehensive, multi-sectoral strategies to address the U5MR disparities in Thailand. Policy interventions should consider improving socioeconomic conditions, healthcare quality, health accessibility, and environmental health in high U5M areas. Overall, this study provides valuable insights into the spatial distribution of U5MR and its associated factors, which highlights the need for tailored and localized health policies and interventions.
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.