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Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions
BACKGROUND: Late antenatal care and smoking during pregnancy are two important factors that are amenable to intervention. Despite the adverse health impacts of smoking during pregnancy and the health benefits of early first antenatal visit on both the mother and the unborn child, substantial proport...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016259/ https://www.ncbi.nlm.nih.gov/pubmed/24152599 http://dx.doi.org/10.1186/1476-072X-12-46 |
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author | Chong, Shanley Nelson, Michael Byun, Roy Harris, Liz Eastwood, John Jalaludin, Bin |
author_facet | Chong, Shanley Nelson, Michael Byun, Roy Harris, Liz Eastwood, John Jalaludin, Bin |
author_sort | Chong, Shanley |
collection | PubMed |
description | BACKGROUND: Late antenatal care and smoking during pregnancy are two important factors that are amenable to intervention. Despite the adverse health impacts of smoking during pregnancy and the health benefits of early first antenatal visit on both the mother and the unborn child, substantial proportions of women still smoke during pregnancy or have their first antenatal visit after 10 weeks gestation. This study was undertaken to assess the usefulness of geospatial methods in identifying communities at high risk of smoking during pregnancy and timing of the first antenatal visit, for which targeted interventions may be warranted, and more importantly, feasible. METHODS: The Perinatal Data Collection, from 1999 to 2008 for south-western Sydney, were obtained from the New South Wales Ministry of Health. Maternal addresses at the time of delivery were georeferenced. A spatial scan statistic implemented in SaTScan was then used to identify statistically significant spatial clusters of women who smoked during pregnancy or women whose first antenatal care visit occurred at or after 10 weeks of pregnancy. RESULTS: Four spatial clusters of maternal smoking during pregnancy and four spatial clusters of first antenatal visit occurring at or after 10 weeks were identified in our analyses. In the maternal smoking during pregnancy clusters, higher proportions of mothers, were aged less than 35 years, had their first antenatal visit at or after 10 weeks and a lower proportion of mothers were primiparous. For the clusters of increased risk of late first antenatal visit at or after 10 weeks of gestation, a higher proportion of mothers lived in the most disadvantaged areas and a lower proportion of mothers were primiparous. CONCLUSION: The application of spatial analyses provides a means to identify spatial clusters of antenatal risk factors and to investigate the associated socio-demographic characteristics of the clusters. |
format | Online Article Text |
id | pubmed-4016259 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40162592014-05-11 Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions Chong, Shanley Nelson, Michael Byun, Roy Harris, Liz Eastwood, John Jalaludin, Bin Int J Health Geogr Research BACKGROUND: Late antenatal care and smoking during pregnancy are two important factors that are amenable to intervention. Despite the adverse health impacts of smoking during pregnancy and the health benefits of early first antenatal visit on both the mother and the unborn child, substantial proportions of women still smoke during pregnancy or have their first antenatal visit after 10 weeks gestation. This study was undertaken to assess the usefulness of geospatial methods in identifying communities at high risk of smoking during pregnancy and timing of the first antenatal visit, for which targeted interventions may be warranted, and more importantly, feasible. METHODS: The Perinatal Data Collection, from 1999 to 2008 for south-western Sydney, were obtained from the New South Wales Ministry of Health. Maternal addresses at the time of delivery were georeferenced. A spatial scan statistic implemented in SaTScan was then used to identify statistically significant spatial clusters of women who smoked during pregnancy or women whose first antenatal care visit occurred at or after 10 weeks of pregnancy. RESULTS: Four spatial clusters of maternal smoking during pregnancy and four spatial clusters of first antenatal visit occurring at or after 10 weeks were identified in our analyses. In the maternal smoking during pregnancy clusters, higher proportions of mothers, were aged less than 35 years, had their first antenatal visit at or after 10 weeks and a lower proportion of mothers were primiparous. For the clusters of increased risk of late first antenatal visit at or after 10 weeks of gestation, a higher proportion of mothers lived in the most disadvantaged areas and a lower proportion of mothers were primiparous. CONCLUSION: The application of spatial analyses provides a means to identify spatial clusters of antenatal risk factors and to investigate the associated socio-demographic characteristics of the clusters. BioMed Central 2013-10-24 /pmc/articles/PMC4016259/ /pubmed/24152599 http://dx.doi.org/10.1186/1476-072X-12-46 Text en Copyright © 2013 Chong et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Chong, Shanley Nelson, Michael Byun, Roy Harris, Liz Eastwood, John Jalaludin, Bin Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions |
title | Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions |
title_full | Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions |
title_fullStr | Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions |
title_full_unstemmed | Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions |
title_short | Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions |
title_sort | geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016259/ https://www.ncbi.nlm.nih.gov/pubmed/24152599 http://dx.doi.org/10.1186/1476-072X-12-46 |
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