International Journal of Health Geographics最新文献

{"title":"Spatiotemporal analysis of the effect of global development indicators on child mortality.","authors":"Prince M Amegbor,&nbsp;Angelina Addae","doi":"10.1186/s12942-023-00330-x","DOIUrl":"https://doi.org/10.1186/s12942-023-00330-x","url":null,"abstract":"<p><strong>Background: </strong>Child mortality continue to be a major public health issue in most developing countries; albeit there has been a decline in global under-five deaths. The differences in child mortality can best be explained by socioeconomic and environmental inequalities among countries. In this study, we explore the effect of country-level development indicators on under-five mortality rates. Specifically, we examine potential spatio-temporal heterogeneity in the association between major world development indicators on under-five mortality, as well as, visualize the global differential time trend of under-five mortality rates.</p><p><strong>Methods: </strong>The data from 195 countries were curated from the World Bank's World Development Indicators (WDI) spanning from 2000 to 2017 and national estimates for under-five mortality from the UN Inter-agency Group for Child Mortality Estimation (UN IGME).We built parametric and non-parametric Bayesian space-time interaction models to examine the effect of development indicators on under-five mortality rates. We also used employed Bayesian spatio-temporal varying coefficient models to assess the spatial and temporal variations in the effect of development indicators on under-five mortality rates.</p><p><strong>Results: </strong>In both parametric and non-parametric models, the results show indicators of good socioeconomic development were associated with a reduction in under-five mortality rates while poor indicators were associated with an increase in under-five mortality rates. For instance, the parametric model shows that gross domestic product (GDP) (β = - 1.26, [CI - 1.51; - 1.01]), current healthcare expenditure (β = - 0.40, [CI - 0.55; - 0.26]) and access to basic sanitation (β = - 0.03, [CI - 0.05; - 0.01]) were associated with a reduction under-five mortality. An increase in the proportion practising open defecation (β = 0.14, [CI 0.08; 0.20]) an increase under-five mortality rate. The result of the spatial components spatial variation in the effect of the development indicators on under-five mortality rates. The spatial patterns of the effect also change over time for some indicators, such as PM2.5.</p><p><strong>Conclusion: </strong>The findings show that the burden of under-five mortality rates was considerably higher among sub-Saharan African countries and some southern Asian countries. The findings also reveal the trend in reduction in the sub-Saharan African region has been slower than the global trend.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"9"},"PeriodicalIF":4.9,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10157969/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9497194","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":"Uncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policies.","authors":"André Alves,&nbsp;Nuno Marques da Costa,&nbsp;Paulo Morgado,&nbsp;Eduarda Marques da Costa","doi":"10.1186/s12942-023-00329-4","DOIUrl":"https://doi.org/10.1186/s12942-023-00329-4","url":null,"abstract":"<p><strong>Background: </strong>COVID-19 caused the largest pandemic of the twenty-first century forcing the adoption of containment policies all over the world. Many studies on COVID-19 health determinants have been conducted, mainly using multivariate methods and geographic information systems (GIS), but few attempted to demonstrate how knowing social, economic, mobility, behavioural, and other spatial determinants and their effects can help to contain the disease. For example, in mainland Portugal, non-pharmacological interventions (NPI) were primarily dependent on epidemiological indicators and ignored the spatial variation of susceptibility to infection.</p><p><strong>Methods: </strong>We present a data-driven GIS-multicriteria analysis to derive a spatial-based susceptibility index to COVID-19 infection in Portugal. The cumulative incidence over 14 days was used in a stepwise multiple linear regression as the target variable along potential determinants at the municipal scale. To infer the existence of thresholds in the relationships between determinants and incidence the most relevant factors were examined using a bivariate Bayesian change point analysis. The susceptibility index was mapped based on these thresholds using a weighted linear combination.</p><p><strong>Results: </strong>Regression results support that COVID-19 spread in mainland Portugal had strong associations with factors related to socio-territorial specificities, namely sociodemographic, economic and mobility. Change point analysis revealed evidence of nonlinearity, and the susceptibility classes reflect spatial dependency. The spatial index of susceptibility to infection explains with accuracy previous and posterior infections. Assessing the NPI levels in relation to the susceptibility map points towards a disagreement between the severity of restrictions and the actual propensity for transmission, highlighting the need for more tailored interventions.</p><p><strong>Conclusions: </strong>This article argues that NPI to contain COVID-19 spread should consider the spatial variation of the susceptibility to infection. The findings highlight the importance of customising interventions to specific geographical contexts due to the uneven distribution of COVID-19 infection determinants. The methodology has the potential for replication at other geographical scales and regions to better understand the role of health determinants in explaining spatiotemporal patterns of diseases and promoting evidence-based public health policies.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"8"},"PeriodicalIF":4.9,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10078027/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9434336","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":"Characterization of prehospital time delay in primary percutaneous coronary intervention for acute myocardial infarction: analysis of geographical infrastructure-dependent and -independent components.","authors":"Keisuke Oyatani,&nbsp;Masayuki Koyama,&nbsp;Nobuaki Himuro,&nbsp;Tetsuji Miura,&nbsp;Hirofumi Ohnishi","doi":"10.1186/s12942-023-00328-5","DOIUrl":"https://doi.org/10.1186/s12942-023-00328-5","url":null,"abstract":"<p><strong>Background: </strong>Prehospital delay in reaching a percutaneous coronary intervention (PCI) facility is a major problem preventing early coronary reperfusion in patients with ST-elevation myocardial infarction (STEMI). The aim of this study was to identify modifiable factors that contribute to the interval from symptom onset to arrival at a PCI-capable center with a focus on geographical infrastructure-dependent and -independent factors.</p><p><strong>Methods: </strong>We analyzed data from 603 STEMI patients who received primary PCI within 12 h of symptom onset in the Hokkaido Acute Coronary Care Survey. We defined onset-to-door time (ODT) as the interval from the onset of symptoms to arrival at the PCI facility and we defined door-to-balloon time (DBT) as the interval from arrival at the PCI facility to PCI. We analyzed the characteristics and factors of each time interval by type of transportation to PCI facilities. In addition, we used geographical information system software to calculate the minimum prehospital system time (min-PST), which represents the time required to reach a PCI facility based on geographical factors. We then subtracted min-PST from ODT to find the estimated delay-in-arrival-to-door (eDAD), which represents the time required to reach a PCI facility independent of geographical factors. We investigated the factors related to the prolongation of eDAD.</p><p><strong>Results: </strong>DBT (median [IQR]: 63 [44, 90] min) was shorter than ODT (median [IQR]: 104 [56, 204] min) regardless of the type of transportation. However, ODT was more than 120 min in 44% of the patients. The min-PST (median [IQR]: 3.7 [2.2, 12.0] min) varied widely among patients, with a maximum of 156 min. Prolongation of eDAD (median [IQR]: 89.1 [49, 180] min) was associated with older age, absence of a witness, onset at night, no emergency medical services (EMS) call, and transfer via a non-PCI facility. If eDAD was zero, ODT was projected to be less than 120 min in more than 90% of the patients.</p><p><strong>Conclusions: </strong>The contribution of geographical infrastructure-dependent time in prehospital delay was substantially smaller than that of geographical infrastructure-independent time. Intervention to shorten eDAD by focusing on factors such as older age, absence of a witness, onset at night, no EMS call, and transfer via a non-PCI facility appears to be an important strategy for reducing ODT in STEMI patients. Additionally, eDAD may be useful for evaluating the quality of STEMI patient transport in areas with different geographical conditions.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"7"},"PeriodicalIF":4.9,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10064653/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10643838","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":"Geographic accessibility and hospital competition for emergency blood transfusion services in Bungoma, Western Kenya.","authors":"Eda Mumo, Nathan O Agutu, Angela K Moturi, Anitah Cherono, Samuel K Muchiri, Robert W Snow, Victor A Alegana","doi":"10.1186/s12942-023-00327-6","DOIUrl":"10.1186/s12942-023-00327-6","url":null,"abstract":"<p><strong>Background: </strong>Estimating accessibility gaps to essential health interventions helps to allocate and prioritize health resources. Access to blood transfusion represents an important emergency health requirement. Here, we develop geo-spatial models of accessibility and competition to blood transfusion services in Bungoma County, Western Kenya.</p><p><strong>Methods: </strong>Hospitals providing blood transfusion services in Bungoma were identified from an up-dated geo-coded facility database. AccessMod was used to define care-seeker's travel times to the nearest blood transfusion service. A spatial accessibility index for each enumeration area (EA) was defined using modelled travel time, population demand, and supply available at the hospital, assuming a uniform risk of emergency occurrence in the county. To identify populations marginalized from transfusion services, the number of people outside 1-h travel time and those residing in EAs with low accessibility indexes were computed at the sub-county level. Competition between the transfusing hospitals was estimated using a spatial competition index which provided a measure of the level of attractiveness of each hospital. To understand whether highly competitive facilities had better capacity for blood transfusion services, a correlation test between the computed competition metric and the blood units received and transfused at the hospital was done.</p><p><strong>Results: </strong>15 hospitals in Bungoma county provide transfusion services, however these are unevenly distributed across the sub-counties. Average travel time to a blood transfusion centre in the county was 33 min and 5% of the population resided outside 1-h travel time. Based on the accessibility index, 38% of the EAs were classified to have low accessibility, representing 34% of the population, with one sub-county having the highest marginalized population. The computed competition index showed that hospitals in the urban areas had a spatial competitive advantage over those in rural areas.</p><p><strong>Conclusion: </strong>The modelled spatial accessibility has provided an improved understanding of health care gaps essential for health planning. Hospital competition has been illustrated to have some degree of influence in provision of health services hence should be considered as a significant external factor impacting the delivery, and re-design of available services.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"6"},"PeriodicalIF":4.9,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041813/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9593366","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":"Cyclists' exposure to air pollution, noise, and greenery: a population-level spatial analysis approach.","authors":"Elias Willberg,&nbsp;Age Poom,&nbsp;Joose Helle,&nbsp;Tuuli Toivonen","doi":"10.1186/s12942-023-00326-7","DOIUrl":"https://doi.org/10.1186/s12942-023-00326-7","url":null,"abstract":"<p><p>Urban travel exposes people to a range of environmental qualities with significant health and wellbeing impacts. Nevertheless, the understanding of travel-related environmental exposure has remained limited. Here, we present a novel approach for population-level assessment of multiple environmental exposure for active travel. It enables analyses of (1) urban scale exposure variation, (2) alternative routes' potential to improve exposure levels per exposure type, and (3) by combining multiple exposures. We demonstrate the approach's feasibility by analysing cyclists' air pollution, noise, and greenery exposure in Helsinki, Finland. We apply an in-house developed route-planning and exposure assessment software and integrate to the analysis 3.1 million cycling trips from the local bike-sharing system. We show that especially noise exposure from cycling exceeds healthy thresholds, but that cyclists can influence their exposure by route choice. The proposed approach enables planners and individual citizens to identify (un)healthy travel environments from the exposure perspective, and to compare areas in respect to how well their environmental quality supports active travel. Transferable open tools and data further support the implementation of the approach in other cities.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"5"},"PeriodicalIF":4.9,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921333/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10737167","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":"Spatiotemporal evolution of COVID-19 in Portugal's Mainland with self-organizing maps.","authors":"Igor Duarte, Manuel C Ribeiro, Maria João Pereira, Pedro Pinto Leite, André Peralta-Santos, Leonardo Azevedo","doi":"10.1186/s12942-022-00322-3","DOIUrl":"10.1186/s12942-022-00322-3","url":null,"abstract":"<p><strong>Background: </strong>Self-Organizing Maps (SOM) are an unsupervised learning clustering and dimensionality reduction algorithm capable of mapping an initial complex high-dimensional data set into a low-dimensional domain, such as a two-dimensional grid of neurons. In the reduced space, the original complex patterns and their interactions can be better visualized, interpreted and understood.</p><p><strong>Methods: </strong>We use SOM to simultaneously couple the spatial and temporal domains of the COVID-19 evolution in the 278 municipalities of mainland Portugal during the first year of the pandemic. Temporal 14-days cumulative incidence time series along with socio-economic and demographic indicators per municipality were analyzed with SOM to identify regions of the country with similar behavior and infer the possible common origins of the incidence evolution.</p><p><strong>Results: </strong>The results show how neighbor municipalities tend to share a similar behavior of the disease, revealing the strong spatiotemporal relationship of the COVID-19 spreading beyond the administrative borders of each municipality. Additionally, we demonstrate how local socio-economic and demographic characteristics evolved as determinants of COVID-19 transmission, during the 1st wave school density per municipality was more relevant, where during 2nd wave jobs in the secondary sector and the deprivation score were more relevant.</p><p><strong>Conclusions: </strong>The results show that SOM can be an effective tool to analysing the spatiotemporal behavior of COVID-19 and synthetize the history of the disease in mainland Portugal during the period in analysis. While SOM have been applied to diverse scientific fields, the application of SOM to study the spatiotemporal evolution of COVID-19 is still limited. This work illustrates how SOM can be used to describe the spatiotemporal behavior of epidemic events. While the example shown herein uses 14-days cumulative incidence curves, the same analysis can be performed using other relevant data such as mortality data, vaccination rates or even infection rates of other disease of infectious nature.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"4"},"PeriodicalIF":3.0,"publicationDate":"2023-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10726647","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":"Comparison of static and dynamic exposures to air pollution, noise, and greenness among seniors living in compact-city environments.","authors":"Oriol Marquet,&nbsp;Jose Tello-Barsocchini,&nbsp;Daniel Couto-Trigo,&nbsp;Irene Gómez-Varo,&nbsp;Monika Maciejewska","doi":"10.1186/s12942-023-00325-8","DOIUrl":"https://doi.org/10.1186/s12942-023-00325-8","url":null,"abstract":"<p><p>GPS technology and tracking study designs have gained popularity as a tool to go beyond the limitations of static exposure assessments based on the subject's residence. These dynamic exposure assessment methods offer high potential upside in terms of accuracy but also disadvantages in terms of cost, sample sizes, and types of data generated. Because of that, with our study we aim to understand in which cases researchers need to use GPS-based methods to guarantee the necessary accuracy in exposure assessment. With a sample of 113 seniors living in Barcelona (Spain) we compare their estimated daily exposures to air pollution (PM2.5, PM10, NO2), noise (dB), and greenness (NDVI) using static and dynamic exposure assessment techniques. Results indicate that significant differences between static and dynamic exposure assessments are only present in selected exposures, and would thus suggest that static assessments using the place of residence would provide accurate-enough values across a number of exposures in the case of seniors. Our models for Barcelona's seniors suggest that dynamic exposure would only be required in the case of exposure to smaller particulate matter (PM2.5) and exposure to noise levels. The study signals to the need to consider both the mobility patterns and the built environment context when deciding between static or dynamic measures of exposure assessment.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"3"},"PeriodicalIF":4.9,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884423/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10726645","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":"Geospatial techniques for monitoring and mitigating climate change and its effects on human health.","authors":"Maged N Kamel Boulos,&nbsp;John P Wilson","doi":"10.1186/s12942-023-00324-9","DOIUrl":"https://doi.org/10.1186/s12942-023-00324-9","url":null,"abstract":"<p><p>This article begins by briefly examining the multitude of ways in which climate and climate change affect human health and wellbeing. It then proceeds to present a quick overview of how geospatial data, methods and tools are playing key roles in the measurement, analysis and modelling of climate change and its effects on human health. Geospatial techniques are proving indispensable for making more accurate assessments and estimates, predicting future trends more reliably, and devising more optimised climate change adaptation and mitigation plans.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"2"},"PeriodicalIF":4.9,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10726643","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":"The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data.","authors":"Dajana Draganic, Knut Reidar Wangen","doi":"10.1186/s12942-023-00323-w","DOIUrl":"10.1186/s12942-023-00323-w","url":null,"abstract":"<p><strong>Background: </strong>The early detection of colorectal cancer (CRC) through regular screening decreases its incidence and mortality rates and improves survival rates. Norway has an extremely high percentage of CRC cases diagnosed at late stages, with large variations across municipalities and hospital catchment areas. This study examined whether the availability of physicians related to CRC primary diagnosis and preoperative investigations, or physician density, contributes to the observed geographical differences in late-stage incidence rates.</p><p><strong>Method: </strong>Municipality-level data on CRC stage at diagnosis were obtained from the Cancer Registry of Norway for the period 2012-2020. Physician density was calculated as the number of physicians related to CRC investigations, general practitioners (GPs) and specialists per 10,000 people, using physician counts per municipality and hospital areas from Statistics Norway. The relationship was examined using a novel causal inference method for spatial data-neighbourhood adjustment method via spatial smoothing (NA approach)-which allowed for studying the region-level effect of physician supply on CRC outcome by using spatially referenced data and still providing causal relationships.</p><p><strong>Results: </strong>According to the NA approach, an increase in one general practitioner per 10,000 people will result in a 3.6% (CI -0.064 to -0.008) decrease in late-stage CRC rates. For specialists, there was no evidence of a significant correlation with late-stage CRC distribution, while for both groups, GPs and specialists combined, an increase of 1 physician per 10,000 people would be equal to an average decrease in late-stage incidence rates by 2.79% (CI -0.055 to -0.001).</p><p><strong>Conclusion: </strong>The study confirmed previous findings that an increase in GP supply will significantly improve CRC outcomes. In contrast to previous research, this study identified the importance of accessibility to both groups of physicians-GPs and specialists. If GPs encounter insufficient workforces in hospitals and long delays in colonoscopy scheduling, they will less often recommend colonoscopy examinations to patients. This study also highlighted the efficiency of the novel methodology for spatially referenced data, which allowed us to study the effect of physician density on cancer outcomes within a causal inference framework.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"22 1","pages":"1"},"PeriodicalIF":3.0,"publicationDate":"2023-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850813/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10731688","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":"Deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data for enhancing obesity estimation.","authors":"Ryan Zhenqi Zhou, Yingjie Hu, Jill N Tirabassi, Yue Ma, Zhen Xu","doi":"10.1186/s12942-022-00321-4","DOIUrl":"10.1186/s12942-022-00321-4","url":null,"abstract":"<p><strong>Background: </strong>Obesity is a serious public health problem. Existing research has shown a strong association between obesity and an individual's diet and physical activity. If we extend such an association to the neighborhood level, information about the diet and physical activity of the residents of a neighborhood may improve the estimate of neighborhood-level obesity prevalence and help identify the neighborhoods that are more likely to suffer from obesity. However, it is challenging to measure neighborhood-level diet and physical activity through surveys and interviews, especially for a large geographic area.</p><p><strong>Methods: </strong>We propose a method for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data, and examine the extent to which the derived measurements can enhance obesity estimation, in addition to the socioeconomic and demographic variables typically used in the literature. We conduct case studies in three different U.S. cities, which are New York City, Los Angeles, and Buffalo, using anonymized mobile phone location data from the company SafeGraph. We employ five different statistical and machine learning models to test the potential enhancement brought by the derived measurements for obesity estimation.</p><p><strong>Results: </strong>We find that it is feasible to derive neighborhood-level diet and physical activity measurements from anonymized mobile phone location data. The derived measurements provide only a small enhancement for obesity estimation, compared with using a comprehensive set of socioeconomic and demographic variables. However, using these derived measurements alone can achieve a moderate accuracy for obesity estimation, and they may provide a stronger enhancement when comprehensive socioeconomic and demographic data are not available (e.g., in some developing countries). From a methodological perspective, spatially explicit models overall perform better than non-spatial models for neighborhood-level obesity estimation.</p><p><strong>Conclusions: </strong>Our proposed method can be used for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone data. The derived measurements can enhance obesity estimation, and can be especially useful when comprehensive socioeconomic and demographic data are not available. In addition, these derived measurements can be used to study obesity-related health behaviors, such as visit frequency of neighborhood residents to fast-food restaurants, and to identify primary places contributing to obesity-related issues.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"21 1","pages":"22"},"PeriodicalIF":3.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10497298","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}