International Journal of Health Geographics最新文献

{"title":"A bootstrapping approach for generating an inverse distance weight matrix when multiple observations have an identical location in large health surveys","authors":"Sung Wook Kim, Felix Achana, S. Petrou","doi":"10.1186/s12942-019-0189-5","DOIUrl":"https://doi.org/10.1186/s12942-019-0189-5","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0189-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42492367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behavioral mapping of children’s physical activities and social behaviors in an indoor preschool facility: methodological challenges in revealing the influence of space in play","authors":"A. R. Onojeghuo, C. Nykiforuk, A. Belon, Jane Hewes","doi":"10.1186/s12942-019-0191-y","DOIUrl":"https://doi.org/10.1186/s12942-019-0191-y","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"178 ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0191-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41272976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new combination rule for Spatial Decision Support Systems for epidemiology","authors":"Luciana Moura Mendes de Lima, Laísa Ribeiro de Sá, Ana Flávia Uzeda dos Santos Macambira, Jordana de Almeida Nogueira, Rodrigo Pinheiro de Toledo Vianna, R. M. de Moraes","doi":"10.1186/s12942-019-0187-7","DOIUrl":"https://doi.org/10.1186/s12942-019-0187-7","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0187-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46723171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The population randomization observation process (PROP) assessment method: using systematic habitation observations of street segments to establish household-level epidemiologic population samples","authors":"M. Smart, R. Sadler, Alan Harris, Z. Buchalski, A. Pearson, C. Debra Furr-Holden","doi":"10.1186/s12942-019-0190-z","DOIUrl":"https://doi.org/10.1186/s12942-019-0190-z","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0190-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43960169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Google Earth™ and Geographical Information System data as method to delineate sample domains for an urban household surveys: the case of Maroua (Far North Region-Cameroon)","authors":"Ronald R. B. Ngom Vougat, Steven Chouto, Sylvain Aoudou Doua, R. Garabed, André Zoli Pagnah, B. Gonne","doi":"10.1186/s12942-019-0186-8","DOIUrl":"https://doi.org/10.1186/s12942-019-0186-8","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0186-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42121797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of the Australian Cancer Atlas: spatial modelling, visualisation, and reporting of estimates","authors":"Earl W. Duncan, S. Cramb, J. Aitken, K. Mengersen, P. Baade","doi":"10.1186/s12942-019-0185-9","DOIUrl":"https://doi.org/10.1186/s12942-019-0185-9","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0185-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41882150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A statistical downscaling approach for generating high spatial resolution health risk maps: a case study of road noise and ischemic heart disease mortality in Melbourne, Australia","authors":"I. Hanigan, T. Chaston, B. Hinze, M. Dennekamp, B. Jalaludin, Y. Kinfu, G. Morgan","doi":"10.1186/s12942-019-0184-x","DOIUrl":"https://doi.org/10.1186/s12942-019-0184-x","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0184-x","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42164101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The use of GPS data loggers to describe the impact of spatio-temporal movement patterns on malaria control in a high-transmission area of northern Zambia","authors":"M. Hast, K. Searle, M. Chaponda, J. Lupiya, J. Lubinda, J. Sikalima, Tamaki Kobayashi, T. Shields, M. Mulenga, J. Lessler, W. Moss","doi":"10.1186/s12942-019-0183-y","DOIUrl":"https://doi.org/10.1186/s12942-019-0183-y","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2019-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0183-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47545914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The linkage between the perception of neighbourhood and physical activity in Guangzhou, China: using street view imagery with deep learning techniques.","authors":"Ruoyu Wang,&nbsp;Ye Liu,&nbsp;Yi Lu,&nbsp;Yuan Yuan,&nbsp;Jinbao Zhang,&nbsp;Penghua Liu,&nbsp;Yao Yao","doi":"10.1186/s12942-019-0182-z","DOIUrl":"https://doi.org/10.1186/s12942-019-0182-z","url":null,"abstract":"<p><strong>Background: </strong>Neighbourhood environment characteristics have been found to be associated with residents' willingness to conduct physical activity (PA). Traditional methods to assess perceived neighbourhood environment characteristics are often subjective, costly, and time-consuming, and can be applied only on a small scale. Recent developments in deep learning algorithms and the recent availability of street view images enable researchers to assess multiple aspects of neighbourhood environment perceptions more efficiently on a large scale. This study aims to examine the relationship between each of six neighbourhood environment perceptual indicators-namely, wealthy, safe, lively, depressing, boring and beautiful-and residents' time spent on PA in Guangzhou, China.</p><p><strong>Methods: </strong>A human-machine adversarial scoring system was developed to predict perceptions of neighbourhood environments based on Tencent Street View imagery and deep learning techniques. Image segmentation was conducted using a fully convolutional neural network (FCN-8s) and annotated ADE20k data. A human-machine adversarial scoring system was constructed based on a random forest model and image ratings by 30 volunteers. Multilevel linear regressions were used to examine the association between each of the six indicators and time spent on PA among 808 residents living in 35 neighbourhoods.</p><p><strong>Results: </strong>Total PA time was positively associated with the scores for \"safe\" [Coef. = 1.495, SE = 0.558], \"lively\" [1.635, 0.789] and \"beautiful\" [1.009, 0.404]. It was negatively associated with the scores for \"depressing\" [- 1.232, 0.588] and \"boring\" [- 1.227, 0.603]. No significant linkage was found between total PA time and the \"wealthy\" score. PA was further categorised into three intensity levels. More neighbourhood perceptual indicators were associated with higher intensity PA. The scores for \"safe\" and \"depressing\" were significantly related to all three intensity levels of PA.</p><p><strong>Conclusions: </strong>People living in perceived safe, lively and beautiful neighbourhoods were more likely to engage in PA, and people living in perceived boring and depressing neighbourhoods were less likely to engage in PA. Additionally, the relationship between neighbourhood perception and PA varies across different PA intensity levels. A combination of Tencent Street View imagery and deep learning techniques provides an accurate tool to automatically assess neighbourhood environment exposure for Chinese large cities.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"18 1","pages":"18"},"PeriodicalIF":4.9,"publicationDate":"2019-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0182-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41216749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research.","authors":"Michelle Pasquale Fillekes,&nbsp;Eleftheria Giannouli,&nbsp;Eun-Kyeong Kim,&nbsp;Wiebren Zijlstra,&nbsp;Robert Weibel","doi":"10.1186/s12942-019-0181-0","DOIUrl":"https://doi.org/10.1186/s12942-019-0181-0","url":null,"abstract":"<p><strong>Background: </strong>GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.</p><p><strong>Methods: </strong>With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals' daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.</p><p><strong>Results: </strong>The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult's daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.</p><p><strong>Conclusion: </strong>This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals' daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"18 1","pages":"17"},"PeriodicalIF":4.9,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12942-019-0181-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41216750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}