Pub Date : 2024-05-21DOI: 10.1186/s12942-024-00374-7
Juliette F E van Beek, Laurent Malisoux, Olivier Klein, Torsten Bohn, Marion Tharrey, Frank J Van Lenthe, Mariëlle A Beenackers, Martin Dijst, Camille Perchoux
Background: Greenness exposure has been associated with many health benefits, for example through the pathway of providing opportunities for physical activity (PA). Beside the limited body of longitudinal research, most studies overlook to what extent different types of greenness exposures may be associated with varying levels of PA and sedentary behavior (SB). In this study, we investigated associations of greenness characterized by density, diversity and vegetation type with self-reported PA and SB over a 9-year period, using data from the ORISCAV-LUX study (2007-2017, n = 628).
Methods: The International Physical Activity Questionnaire (IPAQ) short form was used to collect PA and SB outcomes. PA was expressed as MET-minutes/week and log-transformed, and SB was expressed as sitting time in minutes/day. Geographic Information Systems (ArcGIS Pro, ArcMap) were used to collect the following exposure variables: Tree Cover Density (TCD), Soil-adjusted Vegetation Index (SAVI), and Green Land Use Mix (GLUM). The exposure variables were derived from publicly available sources using remote sensing and cartographic resources. Greenness exposure was calculated within 1000m street network buffers around participants' exact residential address.
Results: Using Random Effects Within-Between (REWB) models, we found evidence of negative within-individual associations of TCD with PA (β = - 2.60, 95% CI - 4.75; - 0.44), and negative between-individual associations of GLUM and PA (β = - 2.02, 95% CI - 3.73; - 0.32). There was no evidence for significant associations between greenness exposure and SB. Significant interaction effects by sex were present for the associations between TCD and both PA and SB. Neighborhood socioeconomic status (NSES) did not modify the effect of greenness exposure on PA and SB in the 1000 m buffer.
Discussion: Our results showed that the relationship between greenness exposure and PA depended on the type of greenness measure used, which stresses the need for the use of more diverse and complementary greenness measures in future research. Tree vegetation and greenness diversity, and changes therein, appeared to relate to PA, with distinct effects among men and women. Replication studies are needed to confirm the relevance of using different greenness measures to understand its' different associations with PA and SB.
背景:绿化与许多健康益处有关,例如通过提供体育活动(PA)机会的途径。除了有限的纵向研究外,大多数研究都忽略了不同类型的绿化暴露在多大程度上可能与不同水平的体育锻炼和久坐行为(SB)有关。在这项研究中,我们利用 ORISCAV-LUX 研究(2007-2017 年,n = 628)的数据,调查了 9 年间以密度、多样性和植被类型为特征的绿化与自我报告的 PA 和 SB 的关联:方法:采用国际体育活动调查问卷(IPAQ)简表收集体育活动量和运动量结果。PA以MET-分钟/周表示,并进行对数转换,SB以久坐时间(分钟/天)表示。地理信息系统(ArcGIS Pro、ArcMap)用于收集以下暴露变量:树木覆盖密度(TCD)、土壤调整植被指数(SAVI)和绿色土地利用组合(GLUM)。这些暴露变量是利用遥感和制图资源从公开来源获得的。在参与者确切居住地址周围 1000 米的街道网络缓冲区内计算绿化暴露:利用随机效应之间模型(REWB),我们发现了TCD与PA的个体内负相关(β = - 2.60,95% CI - 4.75; - 0.44),以及GLUM与PA的个体间负相关(β = - 2.02,95% CI - 3.73; - 0.32)。没有证据表明绿化暴露与 SB 之间存在显著关联。TCD与PA和SB之间的关系存在显著的性别交互效应。在1000米缓冲区内,邻里社会经济地位(NSES)不会改变绿化暴露对PA和SB的影响:讨论:我们的研究结果表明,绿度暴露与PA之间的关系取决于所使用的绿度测量类型,这强调了在未来研究中使用更多样化和互补性绿度测量的必要性。树木植被和绿度多样性及其变化似乎与PA有关,对男性和女性有不同的影响。需要进行重复研究,以确认使用不同的绿化度量来了解其与 PA 和 SB 的不同关联的相关性。
{"title":"Longitudinal study of changes in greenness exposure, physical activity and sedentary behavior in the ORISCAV-LUX cohort study.","authors":"Juliette F E van Beek, Laurent Malisoux, Olivier Klein, Torsten Bohn, Marion Tharrey, Frank J Van Lenthe, Mariëlle A Beenackers, Martin Dijst, Camille Perchoux","doi":"10.1186/s12942-024-00374-7","DOIUrl":"10.1186/s12942-024-00374-7","url":null,"abstract":"<p><strong>Background: </strong>Greenness exposure has been associated with many health benefits, for example through the pathway of providing opportunities for physical activity (PA). Beside the limited body of longitudinal research, most studies overlook to what extent different types of greenness exposures may be associated with varying levels of PA and sedentary behavior (SB). In this study, we investigated associations of greenness characterized by density, diversity and vegetation type with self-reported PA and SB over a 9-year period, using data from the ORISCAV-LUX study (2007-2017, n = 628).</p><p><strong>Methods: </strong>The International Physical Activity Questionnaire (IPAQ) short form was used to collect PA and SB outcomes. PA was expressed as MET-minutes/week and log-transformed, and SB was expressed as sitting time in minutes/day. Geographic Information Systems (ArcGIS Pro, ArcMap) were used to collect the following exposure variables: Tree Cover Density (TCD), Soil-adjusted Vegetation Index (SAVI), and Green Land Use Mix (GLUM). The exposure variables were derived from publicly available sources using remote sensing and cartographic resources. Greenness exposure was calculated within 1000m street network buffers around participants' exact residential address.</p><p><strong>Results: </strong>Using Random Effects Within-Between (REWB) models, we found evidence of negative within-individual associations of TCD with PA (β = - 2.60, 95% CI - 4.75; - 0.44), and negative between-individual associations of GLUM and PA (β = - 2.02, 95% CI - 3.73; - 0.32). There was no evidence for significant associations between greenness exposure and SB. Significant interaction effects by sex were present for the associations between TCD and both PA and SB. Neighborhood socioeconomic status (NSES) did not modify the effect of greenness exposure on PA and SB in the 1000 m buffer.</p><p><strong>Discussion: </strong>Our results showed that the relationship between greenness exposure and PA depended on the type of greenness measure used, which stresses the need for the use of more diverse and complementary greenness measures in future research. Tree vegetation and greenness diversity, and changes therein, appeared to relate to PA, with distinct effects among men and women. Replication studies are needed to confirm the relevance of using different greenness measures to understand its' different associations with PA and SB.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"23 1","pages":"14"},"PeriodicalIF":4.9,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11110334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141076756","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}
Pub Date : 2024-05-19DOI: 10.1186/s12942-024-00371-w
Fedra Trujillano, Gabriel Jimenez, Edgar Manrique, Najat F Kahamba, Fredros Okumu, Nombre Apollinaire, Gabriel Carrasco-Escobar, Brian Barrett, Kimberly Fornace
Background: In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies.
Results: We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance.
Conclusions: Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.
背景:在不久的将来,由于气候变化引起的气温和降雨模式的变化,蚊媒疾病的发病率可能会扩大到新的地方。因此,有必要利用最新的技术进步来改进病媒监测方法。无人驾驶飞行器(UAV),通常被称为无人机,已被用于收集高分辨率图像,以绘制蚊子栖息地的详细信息,并将控制措施导向特定区域。监督分类方法在很大程度上被用于自动检测病媒栖息地。然而,人工标注数据进行模型训练限制了其在快速反应中的使用。Meta AI Segment Anything Model (SAM) 等开放源码基础模型可促进高分辨率图像的人工数字化。这种预先训练好的模型可以帮助提取各种图像中的相关特征。在此,我们通过 Samgeo 软件包(基于 Python 的地理空间数据封装器)对 SAM 的性能进行了评估,因为该软件包尚未应用于流行病学研究的遥感图像分析:我们使用无人机获取的非洲、南美洲和东南亚五个疟疾流行地区的不同图像,测试了两种相关土地覆被类别的识别:水体和人类住区。我们使用人工放置的点提示和与特定兴趣类别相关的文本提示来指导图像分割,并评估了在不同地理环境下的性能。使用点提示对建筑物进行分割的平均 Dice 系数值为 0.67,对水体进行分割的平均 Dice 系数值为 0.73。在使用文本提示时,建筑物和水体的 Dice 系数分别达到 0.72 和 0.70。然而,性能与每个对象、景观特征和所选词语密切相关,导致性能参差不齐:结论:SAM 等最新模型可协助矢量控制程序对图像进行人工数字化,在勘测感兴趣的区域时快速识别关键特征。然而,精确的分割仍然需要用户提供人工提示和修正,以获得精确的分割。有必要进行进一步的评估,尤其是在农村地区的应用。
{"title":"Using image segmentation models to analyse high-resolution earth observation data: new tools to monitor disease risks in changing environments.","authors":"Fedra Trujillano, Gabriel Jimenez, Edgar Manrique, Najat F Kahamba, Fredros Okumu, Nombre Apollinaire, Gabriel Carrasco-Escobar, Brian Barrett, Kimberly Fornace","doi":"10.1186/s12942-024-00371-w","DOIUrl":"10.1186/s12942-024-00371-w","url":null,"abstract":"<p><strong>Background: </strong>In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies.</p><p><strong>Results: </strong>We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance.</p><p><strong>Conclusions: </strong>Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"23 1","pages":"13"},"PeriodicalIF":4.9,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11102859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141065797","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}
Pub Date : 2024-05-14DOI: 10.1186/s12942-024-00373-8
T Remmers, P Koolwijk, I Fassaert, J Nolles, W de Groot, S B Vos, S I de Vries, R Mombarg, D H H Van Kann
Background: Previous research indicates the start of primary school (4-5-year-old) as an essential period for the development of children's physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider variety of environmental- and social contexts and therefore their PA is influenced by more diverse factors. However, in order to understand children's daily PA patterns and identify relevant opportunities for PA promotion, it is important to further unravel in which (social) contexts throughout the day, PA of young children takes place.
Methods: We included a cross-national sample of 21 primary schools from the Startvaardig study. In total, 248 children provided valid accelerometer and global positioning (GPS) data. Geospatial analyses were conducted to quantify PA in (social) environments based on their school and home. Transport-related PA was evaluated using GPS speed-algorithms. PA was analysed at different environments, time-periods and for week- and weekend days separately.
Results: Children accumulated an average of 60 min of moderate-to-vigorous PA (MVPA), both during week- and weekend days. Schools contributed to approximately half of daily MVPA during weekdays. During weekends, environments within 100 m from home were important, as well as locations outside the home-school neighbourhood. Pedestrian trips contributed to almost half of the daily MVPA.
Conclusions: We identified several social contexts relevant for children's daily MVPA. Schools have the potential to significantly contribute to young children's PA patterns and are therefore encouraged to systematically evaluate and implement parts of the school-system that stimulate PA and potentially also learning processes. Pedestrian trips also have substantial contribution to daily MVPA of young children, which highlights the importance of daily active transport in school- and parental routines.
背景:以往的研究表明,小学阶段(4-5 岁)是儿童体育锻炼(PA)模式发展的关键时期,因为从这一时期开始,最常观察到的是与年龄相关的体育锻炼下降。在这一时期,幼儿会接触到更多的环境和社会背景,因此他们的 PA 会受到更多不同因素的影响。然而,为了了解儿童的日常 PA 模式并确定促进 PA 的相关机会,有必要进一步了解幼儿在一天中的哪些(社会)环境中进行 PA:我们从 Startvaardig 研究中选取了 21 所小学作为跨国样本。共有 248 名儿童提供了有效的加速度计和全球定位系统(GPS)数据。我们进行了地理空间分析,以学校和家庭为基础,对(社会)环境中的 PA 进行量化。使用 GPS 速度算法评估了与交通相关的 PA。分别对不同环境、不同时间段以及工作日和周末的 PA 进行了分析:结果:儿童在工作日和周末日平均积累了 60 分钟的中度至剧烈活动时间(MVPA)。平日里,学校约占每天 MVPA 的一半。在周末,离家 100 米以内的环境以及家庭与学校附近以外的地点都很重要。行人出行占每日 MVPA 的近一半:我们发现了与儿童日常 MVPA 相关的几种社会环境。学校有可能对幼儿的 PA 模式做出重大贡献,因此我们鼓励学校系统地评估和实施学校系统中能促进 PA 并有可能促进学习过程的部分。行人出行对幼儿的日常 MVPA 也有很大贡献,这突出了日常积极交通在学校和家长日常活动中的重要性。
{"title":"Investigating young children's physical activity through time and place.","authors":"T Remmers, P Koolwijk, I Fassaert, J Nolles, W de Groot, S B Vos, S I de Vries, R Mombarg, D H H Van Kann","doi":"10.1186/s12942-024-00373-8","DOIUrl":"10.1186/s12942-024-00373-8","url":null,"abstract":"<p><strong>Background: </strong>Previous research indicates the start of primary school (4-5-year-old) as an essential period for the development of children's physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider variety of environmental- and social contexts and therefore their PA is influenced by more diverse factors. However, in order to understand children's daily PA patterns and identify relevant opportunities for PA promotion, it is important to further unravel in which (social) contexts throughout the day, PA of young children takes place.</p><p><strong>Methods: </strong>We included a cross-national sample of 21 primary schools from the Startvaardig study. In total, 248 children provided valid accelerometer and global positioning (GPS) data. Geospatial analyses were conducted to quantify PA in (social) environments based on their school and home. Transport-related PA was evaluated using GPS speed-algorithms. PA was analysed at different environments, time-periods and for week- and weekend days separately.</p><p><strong>Results: </strong>Children accumulated an average of 60 min of moderate-to-vigorous PA (MVPA), both during week- and weekend days. Schools contributed to approximately half of daily MVPA during weekdays. During weekends, environments within 100 m from home were important, as well as locations outside the home-school neighbourhood. Pedestrian trips contributed to almost half of the daily MVPA.</p><p><strong>Conclusions: </strong>We identified several social contexts relevant for children's daily MVPA. Schools have the potential to significantly contribute to young children's PA patterns and are therefore encouraged to systematically evaluate and implement parts of the school-system that stimulate PA and potentially also learning processes. Pedestrian trips also have substantial contribution to daily MVPA of young children, which highlights the importance of daily active transport in school- and parental routines.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"23 1","pages":"12"},"PeriodicalIF":4.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11092161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140921186","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}
Pub Date : 2024-05-13DOI: 10.1186/s12942-024-00372-9
Oluwafemi John Ifejube, Sekhar L Kuriakose, T S Anish, Cees van Westen, Justine I Blanford
A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurrences in Kerala, India. Leptospirosis data were obtained for three years: 2017 (non-flood year) and two years with flooding-2018 (heavy flooding) and 2019 (moderate flooding). We considered the severity of flood events using the discharge, duration and extent of each flooding event and compared them with the leptospirosis cases. The distribution of cases regarding flood discharge and duration was assessed through descriptive and spatiotemporal analyses, respectively. Furthermore, cluster analyses and spatial regression were completed to ascertain the relationship between flood extent and the postflood cases. This study found that postflood cases of leptospirosis can be associated with flood events in space and time. The total cases in both 2018 and 2019 increased in the post-flood phase, with the increase in 2018 being more evident. Unlike the 2019 flood, the flood of 2018 is a significant spatial indicator for postflood cases. Our study shows that flooding leads to an increase in leptospirosis cases, and there is stronger evidence for increased leptospirosis cases after a heavy flood event than after a moderate flooding event. Flood duration may be the most important factor in determining the increase in leptospirosis infections.
{"title":"Analysing the outbreaks of leptospirosis after floods in Kerala, India.","authors":"Oluwafemi John Ifejube, Sekhar L Kuriakose, T S Anish, Cees van Westen, Justine I Blanford","doi":"10.1186/s12942-024-00372-9","DOIUrl":"10.1186/s12942-024-00372-9","url":null,"abstract":"<p><p>A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurrences in Kerala, India. Leptospirosis data were obtained for three years: 2017 (non-flood year) and two years with flooding-2018 (heavy flooding) and 2019 (moderate flooding). We considered the severity of flood events using the discharge, duration and extent of each flooding event and compared them with the leptospirosis cases. The distribution of cases regarding flood discharge and duration was assessed through descriptive and spatiotemporal analyses, respectively. Furthermore, cluster analyses and spatial regression were completed to ascertain the relationship between flood extent and the postflood cases. This study found that postflood cases of leptospirosis can be associated with flood events in space and time. The total cases in both 2018 and 2019 increased in the post-flood phase, with the increase in 2018 being more evident. Unlike the 2019 flood, the flood of 2018 is a significant spatial indicator for postflood cases. Our study shows that flooding leads to an increase in leptospirosis cases, and there is stronger evidence for increased leptospirosis cases after a heavy flood event than after a moderate flooding event. Flood duration may be the most important factor in determining the increase in leptospirosis infections.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"23 1","pages":"11"},"PeriodicalIF":4.9,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11092194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140916413","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}
Pub Date : 2024-05-09DOI: 10.1186/s12942-024-00369-4
Yasemin Inaç, Suzannah D'Hooghe, Delfien Van Dyck, Sarah Dury, Stefanie Vandevijvere, Benedicte Deforche, Eva M De Clercq, Nico Van de Weghe, Karin De Ridder
Obesity, a significant public health concern, disproportionately affects people with lower socioeconomic status (SES). Food environments have been identified as part of the causal chain of this disparity. This study investigated variations in the food environment across groups with different SES profiles residing in peri-urban municipal settings. In addition, it examined the association of the perceived and objective food environments with eating behaviour and assessed if these associations were moderated by SES. Utilizing GIS and survey data (n = 497, aged 25-65), results showed differences in the objective and perceived food environments based on SES. Respondents with higher SES perceived their food environments as better but resided farther from all food outlets compared to respondents with lower SES. However, there was no difference in outlet density or mRFEI between SES groups. SES moderated associations between the objective and perceived food environments and most eating behavior outcomes except fast food consumption frequency. For fruits and vegetables, SES moderated the association between neighborhood availability and consumption frequency (β0.23,CI0.03;0.49). Stratified analysis revealed a positive association for both lower (β0.15, CI0.03;0.27) and higher (β0.37, CI 0.12;0.63) SES groups. For snack foods, SES moderated the association between healthy outlet density and consumption frequency (β-0.60, CI-0.94; -0.23), showing statistical significance only for respondents with higher SES (β0.36,CI 0.18;0.55). Similarly, for sugar-sweetened beverages, a statistically significant interaction was observed between unhealthy outlet density in the 1000m buffer and consumption frequency (β 0.06, CI 0.02; 0.11). However, this association was only statistically significant for respondents with higher SES (β-0.02,CI -0.05;-0.0002). These results emphasize the significance of SES as a crucial element in comprehending the connection between the food environment and eating behaviour. Indicating the need for policymakers to take SES into account when implementing food environment interventions, particularly when focusing on the neighborhood food environment without considering residents' SES and their perceptions.
肥胖症是一个重大的公共健康问题,对社会经济地位(SES)较低的人群影响尤为严重。食品环境被认为是造成这种差异的原因之一。本研究调查了居住在城市周边地区的不同社会经济地位群体的饮食环境差异。此外,研究还考察了感知到的和客观的食物环境与饮食行为之间的关联,并评估了这些关联是否会受到社会经济地位的影响。利用地理信息系统和调查数据(n=497,年龄在 25-65 岁之间),结果显示了基于社会经济地位的客观和感知食物环境的差异。与社会经济地位较低的受访者相比,社会经济地位较高的受访者认为他们的食品环境更好,但居住地距离所有食品店都更远。然而,不同社会经济地位群体之间的食品店密度或 mRFEI 并无差异。除快餐消费频率外,社会经济地位调节了客观和感知的食品环境与大多数饮食行为结果之间的关系。就水果和蔬菜而言,社会经济地位调节了邻里可用性与消费频率之间的关系(β0.23,CI0.03;0.49)。分层分析表明,较低(β0.15, CI0.03;0.27)和较高(β0.37, CI 0.12;0.63)社会经济地位群体之间均存在正相关。就休闲食品而言,社会经济地位缓和了健康销售点密度与消费频率之间的关系(β-0.60,CI-0.94; -0.23),仅对社会经济地位较高的受访者具有统计学意义(β0.36,CI 0.18;0.55)。同样,就含糖饮料而言,1000 米缓冲区内的不健康销售点密度与消费频率之间存在统计学意义上的显著交互作用(β 0.06,CI 0.02;0.11)。然而,这种关联仅对社会经济地位较高的受访者具有统计学意义(β-0.02, CI -0.05;-0.0002)。这些结果表明,社会经济地位是理解饮食环境与饮食行为之间关系的重要因素。这表明政策制定者在实施食品环境干预措施时需要考虑到社会经济地位,尤其是在关注社区食品环境而不考虑居民的社会经济地位及其看法时。
{"title":"Associations between the objective and perceived food environment and eating behavior in relation to socioeconomic status among adults in peri-urban settings: results from the CIVISANO study in Flanders, Belgium.","authors":"Yasemin Inaç, Suzannah D'Hooghe, Delfien Van Dyck, Sarah Dury, Stefanie Vandevijvere, Benedicte Deforche, Eva M De Clercq, Nico Van de Weghe, Karin De Ridder","doi":"10.1186/s12942-024-00369-4","DOIUrl":"10.1186/s12942-024-00369-4","url":null,"abstract":"<p><p>Obesity, a significant public health concern, disproportionately affects people with lower socioeconomic status (SES). Food environments have been identified as part of the causal chain of this disparity. This study investigated variations in the food environment across groups with different SES profiles residing in peri-urban municipal settings. In addition, it examined the association of the perceived and objective food environments with eating behaviour and assessed if these associations were moderated by SES. Utilizing GIS and survey data (n = 497, aged 25-65), results showed differences in the objective and perceived food environments based on SES. Respondents with higher SES perceived their food environments as better but resided farther from all food outlets compared to respondents with lower SES. However, there was no difference in outlet density or mRFEI between SES groups. SES moderated associations between the objective and perceived food environments and most eating behavior outcomes except fast food consumption frequency. For fruits and vegetables, SES moderated the association between neighborhood availability and consumption frequency (β0.23,CI0.03;0.49). Stratified analysis revealed a positive association for both lower (β0.15, CI0.03;0.27) and higher (β0.37, CI 0.12;0.63) SES groups. For snack foods, SES moderated the association between healthy outlet density and consumption frequency (β-0.60, CI-0.94; -0.23), showing statistical significance only for respondents with higher SES (β0.36,CI 0.18;0.55). Similarly, for sugar-sweetened beverages, a statistically significant interaction was observed between unhealthy outlet density in the 1000m buffer and consumption frequency (β 0.06, CI 0.02; 0.11). However, this association was only statistically significant for respondents with higher SES (β-0.02,CI -0.05;-0.0002). These results emphasize the significance of SES as a crucial element in comprehending the connection between the food environment and eating behaviour. Indicating the need for policymakers to take SES into account when implementing food environment interventions, particularly when focusing on the neighborhood food environment without considering residents' SES and their perceptions.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"23 1","pages":"10"},"PeriodicalIF":4.9,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11080110/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140900101","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}
Pub Date : 2024-04-13DOI: 10.1186/s12942-024-00368-5
Shuangming Zhao, Yuchen Fan, Pengxiang Zhao, Ali Mansourian, Hung Chak Ho
Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability. This study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers’ exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers’ activities. The taxi drivers’ weekday and weekend 24-h PM2.5 exposure was 83.60 μg/m3 and 55.62 μg/m3 respectively, 3.4 and 2.2 times than the WHO’s recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the “Inner Ring Road”, while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the “Third Ring Road”. These findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.
{"title":"How do taxi drivers expose to fine particulate matter (PM2.5) in a Chinese megacity: a rapid assessment incorporating with satellite-derived information and urban mobility data","authors":"Shuangming Zhao, Yuchen Fan, Pengxiang Zhao, Ali Mansourian, Hung Chak Ho","doi":"10.1186/s12942-024-00368-5","DOIUrl":"https://doi.org/10.1186/s12942-024-00368-5","url":null,"abstract":"Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability. This study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers’ exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers’ activities. The taxi drivers’ weekday and weekend 24-h PM2.5 exposure was 83.60 μg/m3 and 55.62 μg/m3 respectively, 3.4 and 2.2 times than the WHO’s recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the “Inner Ring Road”, while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the “Third Ring Road”. These findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"185 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570184","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}
Pub Date : 2024-04-04DOI: 10.1186/s12942-024-00367-6
Sara Mazzilli, Gianluca Paparatto, Antonio Chieti, Anna Maria Nannavecchia, Lucia Bisceglia, Pier Luigi Lopalco, Domenico Martinelli, Lara Tavoschi
It has been shown that COVID-19 affects people at socioeconomic disadvantage more strongly. Previous studies investigating the association between geographical deprivation and COVID-19 outcomes in Italy reported no differences in case-hospitalisation and case-fatality. The objective of this research was to compare the usefulness of the geographic and individual deprivation index (DI) in assessing the associations between individuals' deprivation and risk of Sars-CoV-2 infection and disease severity in the Apulia region from February to December 2020. This was a retrospective cohort study. Participants included individuals tested for SARS-CoV-2 infection during the study period. The individual DI was calculated employing polychoric principal component analysis on four census variables. Multilevel logistic models were used to test associations between COVID-19 outcomes and individual DI, geographical DI, and their interaction. In the study period, 139,807 individuals were tested for COVID-19 and 56,475 (43.5%) tested positive. Among those positive, 7902 (14.0%) have been hospitalised and 2215 (4.2%) died. During the first epidemic wave, according the analysis done with the individual DI, there was a significant inversely proportional trend between the DI and the risk of testing positive. No associations were found between COVID-19 outcomes and geographic DI. During the second wave, associations were found between COVID-19 outcomes and individual DI. No associations were found between the geographic DI and the risk of hospitalisation and death. During both waves, there were no association between COVID-19 outcomes and the interaction between individual and geographical DI. Evidence from this study shows that COVID-19 pandemic has been experienced unequally with a greater burden among the most disadvantaged communities. The results of this study remind us to be cautious about using geographical DI as a proxy of individual social disadvantage because may lead to inaccurate assessments. The geographical DI is often used due to a lack of individual data. However, on the determinants of health and health inequalities, monitoring has to have a central focus. Health inequalities monitoring provides evidence on who is being left behind and informs equity-oriented policies, programmes and practices. Future research and data collection should focus on improving surveillance systems by integrating individual measures of inequalities into national health information systems.
研究表明,COVID-19 对社会经济处境不利的人群影响更大。此前在意大利进行的关于地理贫困与 COVID-19 结果之间关系的研究报告显示,在病例住院和病死率方面没有差异。这项研究的目的是比较地理和个人贫困指数(DI)在评估 2020 年 2 月至 12 月阿普利亚地区个人贫困程度与 Sars-CoV-2 感染风险和疾病严重程度之间的关联方面的实用性。这是一项回顾性队列研究。参与者包括在研究期间接受过 SARS-CoV-2 感染检测的人。通过对四个普查变量进行多变量主成分分析,计算出个人 DI。多层次逻辑模型用于检验 COVID-19 结果与个人 DI、地域 DI 及其交互作用之间的关联。在研究期间,139807 人接受了 COVID-19 检测,其中 56475 人(43.5%)呈阳性。其中,7902 人(14.0%)住院治疗,2215 人(4.2%)死亡。在第一次流行病浪潮中,根据对个人 DI 的分析,DI 与检测呈阳性的风险之间呈显著的反比趋势。在 COVID-19 结果与地域 DI 之间未发现任何关联。在第二轮调查中,发现 COVID-19 结果与个人 DI 之间存在关联。未发现地域 DI 与住院和死亡风险之间存在关联。在两个波次中,COVID-19 结果与个人和地域 DI 之间的交互作用没有关联。这项研究的证据表明,COVID-19 大流行的影响是不平等的,最弱势的社区承受着更大的负担。这项研究的结果提醒我们,在使用地域 DI 作为个人社会劣势的代表时要谨慎,因为这可能导致评估不准确。由于缺乏个人数据,地域 DI 经常被使用。然而,在健康和健康不平等的决定因素方面,监测必须有一个核心重点。对健康不平等现象的监测为了解哪些人被落在后面提供了证据,并为以公平为导向的政策、计划和实践提供了信息。今后的研究和数据收集工作应侧重于改进监测系统,将对不平等现象的个别衡量纳入国家卫生信息系统。
{"title":"Comparison of geographical and individual deprivation index to assess the risk of Sars-CoV-2 infection and disease severity: a retrospective cohort study","authors":"Sara Mazzilli, Gianluca Paparatto, Antonio Chieti, Anna Maria Nannavecchia, Lucia Bisceglia, Pier Luigi Lopalco, Domenico Martinelli, Lara Tavoschi","doi":"10.1186/s12942-024-00367-6","DOIUrl":"https://doi.org/10.1186/s12942-024-00367-6","url":null,"abstract":"It has been shown that COVID-19 affects people at socioeconomic disadvantage more strongly. Previous studies investigating the association between geographical deprivation and COVID-19 outcomes in Italy reported no differences in case-hospitalisation and case-fatality. The objective of this research was to compare the usefulness of the geographic and individual deprivation index (DI) in assessing the associations between individuals' deprivation and risk of Sars-CoV-2 infection and disease severity in the Apulia region from February to December 2020. This was a retrospective cohort study. Participants included individuals tested for SARS-CoV-2 infection during the study period. The individual DI was calculated employing polychoric principal component analysis on four census variables. Multilevel logistic models were used to test associations between COVID-19 outcomes and individual DI, geographical DI, and their interaction. In the study period, 139,807 individuals were tested for COVID-19 and 56,475 (43.5%) tested positive. Among those positive, 7902 (14.0%) have been hospitalised and 2215 (4.2%) died. During the first epidemic wave, according the analysis done with the individual DI, there was a significant inversely proportional trend between the DI and the risk of testing positive. No associations were found between COVID-19 outcomes and geographic DI. During the second wave, associations were found between COVID-19 outcomes and individual DI. No associations were found between the geographic DI and the risk of hospitalisation and death. During both waves, there were no association between COVID-19 outcomes and the interaction between individual and geographical DI. Evidence from this study shows that COVID-19 pandemic has been experienced unequally with a greater burden among the most disadvantaged communities. The results of this study remind us to be cautious about using geographical DI as a proxy of individual social disadvantage because may lead to inaccurate assessments. The geographical DI is often used due to a lack of individual data. However, on the determinants of health and health inequalities, monitoring has to have a central focus. Health inequalities monitoring provides evidence on who is being left behind and informs equity-oriented policies, programmes and practices. Future research and data collection should focus on improving surveillance systems by integrating individual measures of inequalities into national health information systems.","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"3 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570341","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}
Pub Date : 2024-03-07DOI: 10.1186/s12942-024-00365-8
Feifan Gao, Hanbei Cheng, Zhigang Li, Le Yu
Current research on public spaces and mental health often focuses on the independent relationship of one or more social mediators, neglecting the nuanced implications and serial mechanisms inherent in the progressive social process. Using Wuhan city, China, as a study case with multi-source data, this research applies Multilevel Generalized Structural Equation Modeling and deep learning techniques to explore the differential effects of public spaces with varying degrees of publicness (i.e., typical, semi-, and privately owned) on rural migrants’ mental health. Crucially, this study scrutinizes both explicit (social interaction) and implicit (perceived integration) social mechanisms to revisit the relationships. The findings reveal that not all public spaces equally influence mental health, with typical and privately owned public spaces conferring profound benefits. Notably, public spaces impact mental health chiefly through perceived integration instead of through direct social interaction. Social interaction improves mental health primarily by enhancing perceived integration, suggesting that meaningful connections beyond superficial encounters are critical. In particular, we observed significant social effects in typical and privately owned public spaces but limited social functionality in semi-public spaces. This evidence contributes to the knowledge required to create supportive social environments within public spaces, integral to nurturing inclusive urban development.
{"title":"Revisiting the impact of public spaces on the mental health of rural migrants in Wuhan: an integrated multi-source data analysis","authors":"Feifan Gao, Hanbei Cheng, Zhigang Li, Le Yu","doi":"10.1186/s12942-024-00365-8","DOIUrl":"https://doi.org/10.1186/s12942-024-00365-8","url":null,"abstract":"Current research on public spaces and mental health often focuses on the independent relationship of one or more social mediators, neglecting the nuanced implications and serial mechanisms inherent in the progressive social process. Using Wuhan city, China, as a study case with multi-source data, this research applies Multilevel Generalized Structural Equation Modeling and deep learning techniques to explore the differential effects of public spaces with varying degrees of publicness (i.e., typical, semi-, and privately owned) on rural migrants’ mental health. Crucially, this study scrutinizes both explicit (social interaction) and implicit (perceived integration) social mechanisms to revisit the relationships. The findings reveal that not all public spaces equally influence mental health, with typical and privately owned public spaces conferring profound benefits. Notably, public spaces impact mental health chiefly through perceived integration instead of through direct social interaction. Social interaction improves mental health primarily by enhancing perceived integration, suggesting that meaningful connections beyond superficial encounters are critical. In particular, we observed significant social effects in typical and privately owned public spaces but limited social functionality in semi-public spaces. This evidence contributes to the knowledge required to create supportive social environments within public spaces, integral to nurturing inclusive urban development.","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"25 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140053767","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}
Pub Date : 2024-03-02DOI: 10.1186/s12942-024-00364-9
Jacob Hassler, Tobias Andersson Granberg, Krisjanis Steins, Vania Ceccato
Assuring that emergency health care (EHC) is accessible is a key objective for health care planners. Conventional accessibility analysis commonly relies on resident population data. However, the allocation of resources based on stationary population data may lead to erroneous assumptions of population accessibility to EHC. Therefore, in this paper, we calculate population accessibility to emergency departments in Sweden with a geographical information system based network analysis. Utilizing static population data and dynamic population data, we investigate spatiotemporal patterns of how static population data over- or underestimates population sizes derived from temporally dynamic population data. Our findings show that conventional measures of population accessibility tend to underestimate population sizes particularly in rural areas and in smaller ED’s catchment areas compared to urban, larger ED’s—especially during vacation time in the summer. Planning based on static population data may thus lead to inequitable distributions of resources. This study is motivated in light of the ongoing centralization of ED’s in Sweden, which largely depends on population sizes in ED’s catchment areas.
{"title":"Towards more realistic measures of accessibility to emergency departments in Sweden","authors":"Jacob Hassler, Tobias Andersson Granberg, Krisjanis Steins, Vania Ceccato","doi":"10.1186/s12942-024-00364-9","DOIUrl":"https://doi.org/10.1186/s12942-024-00364-9","url":null,"abstract":"Assuring that emergency health care (EHC) is accessible is a key objective for health care planners. Conventional accessibility analysis commonly relies on resident population data. However, the allocation of resources based on stationary population data may lead to erroneous assumptions of population accessibility to EHC. Therefore, in this paper, we calculate population accessibility to emergency departments in Sweden with a geographical information system based network analysis. Utilizing static population data and dynamic population data, we investigate spatiotemporal patterns of how static population data over- or underestimates population sizes derived from temporally dynamic population data. Our findings show that conventional measures of population accessibility tend to underestimate population sizes particularly in rural areas and in smaller ED’s catchment areas compared to urban, larger ED’s—especially during vacation time in the summer. Planning based on static population data may thus lead to inequitable distributions of resources. This study is motivated in light of the ongoing centralization of ED’s in Sweden, which largely depends on population sizes in ED’s catchment areas.","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"12 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140017594","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}
Pub Date : 2024-02-28DOI: 10.1186/s12942-024-00366-7
Marie Bonal, Cindy Padilla, Guillaume Chevillard, Véronique Lucas-Gabrielli
Background: Increasing inequalities in accessibility to primary care has generated medical deserts. Identifying them is key to target the geographic areas where action is needed. An extensive definition of primary care has been promoted by the World Health Organization: a first level of contact with the health system, which involves the co-presence of different categories of health professionals alongside the general practitioner for the diagnosis and treatment of patients. Previous analyses have focused mainly on a single type of provider while this study proposes an integrated approach including various ones to define medical deserts in primary care.
Method: Our empirical approach focuses on the first point of contact with the health system: general practitioners, proximity primary care providers (nurses, physiotherapists, pharmacies, laboratories, and radiologists), and emergency services. A multiple analysis approach was performed, to classify French municipalities using the information on the evolution and needs of health care accessibility, combining a principal component analysis and a hierarchical ascending classification.
Results: Two clusters of medical deserts were identified with low accessibility to all healthcare professionals, socio-economic disadvantages, and a decrease in care supply. In other clusters, accessibility difficulties only concern a part of the health supply considered, which raises concern for the efficiency of primary care for optimal healthcare pathways. Even for clusters with better accessibility, issues were identified, such as a decrease and high needs of health care supply, revealing potential future difficulties.
Conclusion: This work proposes a multi-professional and multi-dimensional approach to medical deserts based mainly on an extensive definition of primary care that shows the relevance of the co-presence of various healthcare professionals. The classification also makes it possible to identify areas with future problems of accessibility and its potential consequences. This framework could be easily applied to other countries according to their available data and their health systems' specificities.
{"title":"A French classification to describe medical deserts: a multi-professional approach based on the first contact with the healthcare system.","authors":"Marie Bonal, Cindy Padilla, Guillaume Chevillard, Véronique Lucas-Gabrielli","doi":"10.1186/s12942-024-00366-7","DOIUrl":"10.1186/s12942-024-00366-7","url":null,"abstract":"<p><strong>Background: </strong>Increasing inequalities in accessibility to primary care has generated medical deserts. Identifying them is key to target the geographic areas where action is needed. An extensive definition of primary care has been promoted by the World Health Organization: a first level of contact with the health system, which involves the co-presence of different categories of health professionals alongside the general practitioner for the diagnosis and treatment of patients. Previous analyses have focused mainly on a single type of provider while this study proposes an integrated approach including various ones to define medical deserts in primary care.</p><p><strong>Method: </strong>Our empirical approach focuses on the first point of contact with the health system: general practitioners, proximity primary care providers (nurses, physiotherapists, pharmacies, laboratories, and radiologists), and emergency services. A multiple analysis approach was performed, to classify French municipalities using the information on the evolution and needs of health care accessibility, combining a principal component analysis and a hierarchical ascending classification.</p><p><strong>Results: </strong>Two clusters of medical deserts were identified with low accessibility to all healthcare professionals, socio-economic disadvantages, and a decrease in care supply. In other clusters, accessibility difficulties only concern a part of the health supply considered, which raises concern for the efficiency of primary care for optimal healthcare pathways. Even for clusters with better accessibility, issues were identified, such as a decrease and high needs of health care supply, revealing potential future difficulties.</p><p><strong>Conclusion: </strong>This work proposes a multi-professional and multi-dimensional approach to medical deserts based mainly on an extensive definition of primary care that shows the relevance of the co-presence of various healthcare professionals. The classification also makes it possible to identify areas with future problems of accessibility and its potential consequences. This framework could be easily applied to other countries according to their available data and their health systems' specificities.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"23 1","pages":"5"},"PeriodicalIF":3.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10900694/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139991571","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}