International Journal of Health Geographics最新文献

{"title":"Using spatial video and deep learning for automated mapping of ground-level context in relief camps.","authors":"Jayakrishnan Ajayakumar, Andrew J Curtis, Felicien M Maisha, Sandra Bempah, Afsar Ali, Naveen Kannan, Grace Armstrong, John Glenn Morris","doi":"10.1186/s12942-024-00382-7","DOIUrl":"10.1186/s12942-024-00382-7","url":null,"abstract":"<p><strong>Background: </strong>The creation of relief camps following a disaster, conflict or other form of externality often generates additional health problems. The density of people in a highly stressed environment with questionable safe food and water access presents the potential for infectious disease outbreaks. These camps are also not static data events but rather fluctuate in size, composition, and level and quality of service provision. While contextualized geospatial data collection and mapping are vital for understanding the nature of these camps, various challenges, including a lack of data at the required spatial or temporal granularity, as well as the issue of sustainability, can act as major impediments. Here, we present the first steps toward a deep learning-based solution for dynamic mapping using spatial video (SV).</p><p><strong>Methods: </strong>We trained a convolutional neural network (CNN) model on a SV dataset collected from Goma, Democratic Republic of Congo (DRC) to identify relief camps from video imagery. We developed a spatial filtering approach to tackle the challenges associated with spatially tagging objects such as the accuracy of global positioning system and positioning of camera. The spatial filtering approach generates smooth surfaces of detection, which can further be used to capture changes in microenvironments by applying techniques such as raster math.</p><p><strong>Results: </strong>The initial results suggest that our model can detect temporary physical dwellings from SV imagery with a high level of precision, recall, and object localization. The spatial filtering approach helps to identify areas with higher concentrations of camps and the web-based tool helps to explore these areas. The longitudinal analysis based on applying raster math on the detection surfaces revealed locations, which had a considerable change in the distribution of tents over space and time.</p><p><strong>Conclusions: </strong>The results lay the groundwork for automated mapping of spatial features from imagery data. We anticipate that this work is the building block for a future combination of SV, object identification and automatic mapping that could provide sustainable data generation possibilities for challenging environments such as relief camps or other informal settlements.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536618/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584562","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 influence of malaria control interventions and climate variability on changes in the geographical distribution of parasite prevalence in Kenya between 2015 and 2020.","authors":"Bryan O Nyawanda, Sammy Khagayi, Eric Ochomo, Godfrey Bigogo, Simon Kariuki, Stephen Munga, Penelope Vounatsou","doi":"10.1186/s12942-024-00381-8","DOIUrl":"10.1186/s12942-024-00381-8","url":null,"abstract":"<p><strong>Background: </strong>The burden of malaria in Kenya was showing a declining trend, but appears to have reached a plateau in recent years. This study estimated changes in the geographical distribution of malaria parasite risk in the country between the years 2015 and 2020, and quantified the contribution of malaria control interventions and climatic/ environmental factors to these changes.</p><p><strong>Methods: </strong>Bayesian geostatistical models were used to analyse the Kenyan 2015 and 2020 Malaria Indicator Survey (MIS) data. Bivariate models were fitted to identify the most important control intervention indicators and climatic/environmental predictors of parasitaemia risk by age groups (6-59 months and 5-14 years). Parasitaemia risk and the number of infected children were predicted over a 1 × 1 km² grid. The probability of the decline in parasitaemia risk in 2020 compared to 2015 was also evaluated over the gridded surface and factors associated with changes in parasitaemia risk between the two surveys were evaluated.</p><p><strong>Results: </strong>There was a significant decline in the coverage of most malaria indicators related to Insecticide Treated Nets (ITN) and Artemisinin Combination Therapies (ACT) interventions. Overall, there was a 31% and 26% reduction in malaria prevalence among children aged < 5 and 5-14 years, respectively. Among younger children, the highest reduction (50%) and increase (41%) were in the low-risk and semi-arid epi zones, respectively; while among older children there was increased risk in both the low-risk (83%) and semi-arid (100%) epi zones. Increase in nightlights and the proportion of individuals using ITNs in 2020 were associated with reduced parasitaemia risk.</p><p><strong>Conclusion: </strong>Increased nightlights and ITN use could have led to the reduction in parasitaemia risk. However, the reduction is heterogeneous and there was increased risk in northern Kenya. Taken together, these results suggest that constant surveillance and re-evaluation of parasite and vector control measures in areas with increased transmission is necessary. The methods used in this analysis can be employed in other settings.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514743/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142511033","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":"Understanding Ixodes ricinus occurrence in private yards: influence of yard and landscape features.","authors":"Anna Mazaleyrat, Jonas Durand, Irene Carravieri, Christophe Caillot, Cyril Galley, Sandrine Capizzi, Franck Boué, Pascale Frey-Klett, Laure Bournez","doi":"10.1186/s12942-024-00380-9","DOIUrl":"10.1186/s12942-024-00380-9","url":null,"abstract":"<p><strong>Background: </strong>Lyme borreliosis is the most frequent zoonotic disease in the northern hemisphere and is transmitted by ticks of the genus Ixodes. Although many people are bitten by ticks in private yards, our understanding of the factors associated with their presence in these areas remains limited. To address this gap, we used a citizen science approach to identify the local and landscape features associated with tick presence in yards.</p><p><strong>Methods: </strong>This study was conducted near Nancy, a city in northeastern France, from 2020 to 2022. Citizen scientists collected ticks in their yard on a single event (n = 185) and measured 13 yard features. Additionally, we computed 11 features related to the landscape composition and spatial configuration surrounding these yards. Using generalized linear mixed models, we determined the yard and landscape features associated with the presence of ticks and nymphal Ixodes ricinus (hereafter nymphs), the life stage, and species that mostly bite humans.</p><p><strong>Results: </strong>Despite a low density, ticks were found in 32% of the yards, including yards in urbanized areas. At the transect level, the likelihood of finding a nymph was nearly three times higher in transects shaded by vegetation compared to those in open areas, with no relationship between nymph occurrence and transect location or grass height. At the yard level, the occurrence of ticks and nymphs was related to both yard and landscape characteristics. Nymph and tick occurrence were more than twice as high in yards with signs of deer and a wood/brush pile compared to those without these characteristics, and increased with the connectivity of vegetation areas and the percentage of forest areas in the landscape.</p><p><strong>Conclusions: </strong>Our study reveals that private yards across an urbanization gradient are locations of tick exposure with tick presence linked to both yard and landscape factors. These findings emphasize the importance of public awareness regarding tick exposure in yards and provide crucial insights for future public health prevention campaigns.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11468097/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142401678","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":"Accessibility, neighborhood socioeconomic disadvantage and expenditures on electronic gambling machines: a spatial analysis based on player account data.","authors":"Jani Selin, Pasi Okkonen, Susanna Raisamo","doi":"10.1186/s12942-024-00379-2","DOIUrl":"10.1186/s12942-024-00379-2","url":null,"abstract":"<p><strong>Background: </strong>Gambling and its harmful effects on human health and well-being represent a significant public health concern in many countries, with electronic gambling machines (EGMs) recognized as one of the most detrimental forms of gambling. Previous research has established an association between EGM accessibility, expenditure, gambling harm, and the socioeconomic status (SES) of neighborhoods. However, there is limited understanding of the direct impact of SES and EGM accessibility on individual player expenditures. Prior estimations of expenditure often rely on self-reported data or venue-level revenue statistics. This study uses high spatial resolution socioeconomic data together with individual-level account-based location and expenditure (point of sales) data (71,669 players, 745 EGM venues) to explore the association between EGM accessibility and neighborhood SES and to examine whether the EGM expenditure of neighborhood residents is associated with EGM accessibility and neighborhood SES.</p><p><strong>Data and methods: </strong>Player account data include information on the home location and expenditure of the entire EGM gambling population across every EGM venue located in the Helsinki region, Finland. High-resolution (250 × 250 m) grid-level data on socioeconomic variables were used to obtain the local socioeconomic conditions of the players. EGM accessibility was estimated for every grid cell using a calibrated gravity model derived from the player account data. Statistical analyses included correlation analysis, spatial autocorrelation analysis, and regression models.</p><p><strong>Results: </strong>First, significantly higher levels of EGM accessibility were found in areas with lower local SES. Second, regression analysis revealed that both higher EGM accessibility and lower local SES were associated with higher annual losses per adult. These results, in combination with visual and spatial autocorrelation analyses, revealed that accessibility to EGM gambling is highly concentrated, especially in lower socioeconomic neighborhoods with higher levels of EGM expenditure.</p><p><strong>Conclusions: </strong>The results lay the groundwork for future spatial research on gambling harm, expenditure, accessibility, and SES utilizing detailed account data on the interaction between players and venues. The results underscore the importance of spatial restrictions when regulating EGM accessibility, particularly in areas with vulnerable populations, as a crucial measure for public health and harm prevention. The results also enable targeted gambling harm prevention actions at the local level.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11365189/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142113768","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":"Comparing mapped park and greenspace boundaries in Philadelphia: implications for exposure assessment in health studies.","authors":"Dustin Fry, Lara A Roman, Michelle C Kondo","doi":"10.1186/s12942-024-00370-x","DOIUrl":"10.1186/s12942-024-00370-x","url":null,"abstract":"<p><p>An important consideration in studies of the relationship between greenspace exposure and health is the use of mapped data to assign geographic exposures to participants. Previous studies have used validated data from municipal park departments to describe the boundaries of public greenspaces. However, this approach assumes that these data accurately describe park boundaries, that formal parks fully capture the park and greenspace exposure of residents, and (for studies that use personal GPS traces to assign participant exposures) that time spent within these boundaries represents time spent in greenspace. These assumptions are tested using a comparison and ground-truthing of four sources of mapped park and greenspace data in Philadelphia, Pennsylvania: PAD-US-AR, Philadelphia Parks and Recreation, the Delaware Valley Regional Planning Commission, and Open Street Maps. We find several important differences and tradeoffs in these data: the incorporation of highways and building lots within park boundaries, the inclusion or exclusion of formal park spaces (federal, state, and nonprofit), the exclusion of informal parks and greenspaces, and inconsistent boundaries for a linear park. Health researchers may wish to consider these issues when conducting studies using boundary data to assign park exposure.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11366133/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142113769","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":"Exploring fine-scale urban landscapes using satellite data to predict the distribution of Aedes mosquito breeding sites.","authors":"Claire Teillet, Rodolphe Devillers, Annelise Tran, Thibault Catry, Renaud Marti, Nadine Dessay, Joseph Rwagitinywa, Johana Restrepo, Emmanuel Roux","doi":"10.1186/s12942-024-00378-3","DOIUrl":"10.1186/s12942-024-00378-3","url":null,"abstract":"<p><strong>Background: </strong>The spread of mosquito-transmitted diseases such as dengue is a major public health issue worldwide. The Aedes aegypti mosquito, a primary vector for dengue, thrives in urban environments and breeds mainly in artificial or natural water containers. While the relationship between urban landscapes and potential breeding sites remains poorly understood, such a knowledge could help mitigate the risks associated with these diseases. This study aimed to analyze the relationships between urban landscape characteristics and potential breeding site abundance and type in cities of French Guiana (South America), and to evaluate the potential of such variables to be used in predictive models.</p><p><strong>Methods: </strong>We use Multifactorial Analysis to explore the relationship between urban landscape characteristics derived from very high resolution satellite imagery, and potential breeding sites recorded from in-situ surveys. We then applied Random Forest models with different sets of urban variables to predict the number of potential breeding sites where entomological data are not available.</p><p><strong>Results: </strong>Landscape analyses applied to satellite images showed that urban types can be clearly identified using texture indices. The Multiple Factor Analysis helped identify variables related to the distribution of potential breeding sites, such as buildings class area, landscape shape index, building number, and the first component of texture indices. Models predicting the number of potential breeding sites using the entire dataset provided an R² of 0.90, possibly influenced by overfitting, but allowing the prediction over all the study sites. Predictions of potential breeding sites varied highly depending on their type, with better results on breeding sites types commonly found in urban landscapes, such as containers of less than 200 L, large volumes and barrels. The study also outlined the limitation offered by the entomological data, whose sampling was not specifically designed for this study. Model outputs could be used as input to a mosquito dynamics model when no accurate field data are available.</p><p><strong>Conclusion: </strong>This study offers a first use of routinely collected data on potential breeding sites in a research study. It highlights the potential benefits of including satellite-based characterizations of the urban environment to improve vector control strategies.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11229250/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141555764","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":"An investigation of inequalities in exposure to PM_2.5 air pollution across small areas in Ireland.","authors":"Aislinn Hoy, Gretta Mohan, Anne Nolan","doi":"10.1186/s12942-024-00377-4","DOIUrl":"10.1186/s12942-024-00377-4","url":null,"abstract":"<p><p>The link between exposure to air pollution and adverse effects on human health is well documented. Yet, in a European context, research on the spatial distribution of air pollution and the characteristics of areas is relatively scarce, and there is a need for research using different spatial scales, a wider variety of socioeconomic indicators (such as ethnicity) and new methodologies to assess these relationships. This study uses comprehensive data on a wide range of demographic and socioeconomic indicators, matched to data on PM_2.5 concentrations for small areas in Ireland, to assess the relationship between social vulnerability and PM_2.5 air pollution. Examining a wide range of socioeconomic indicators revealed some differentials in PM_2.5 concentration levels by measure and by rural and urban classification. However, statistical modelling using concentration curves and concentration indices did not present substantial evidence of inequalities in PM_2.5 concentrations across small areas. In common with other western European countries, an overall decline in the levels of PM_2.5 between 2011 and 2016 was observed in Ireland, though the data indicates that almost all small areas in Ireland were found to have exceeded the World Health Organization (WHO)'s PM_2.5 annual guideline (of 5 µg/m³), calling for greater policy efforts to reduce air pollution in Ireland. The recent Clean Air Strategy contains a commitment to achieve the WHO guideline limits for PM_2.5 by 2040, with interim targets at various points over the next two decades. Achieving these targets will require policy measures to decarbonise home heating, promote active travel and the transition to electric vehicles, and further regulations on burning fossil fuels and enforcing environmental regulations more tightly. From a research and information-gathering perspective, installing more monitoring stations at key points could improve the quality and spatial dimension of the data collected and facilitate the assessment of the implementation of the measures in the Clean Air Strategy.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11227186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141538823","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":"Identifying obesogenic environment through spatial clustering of body mass index among adults.","authors":"Kimberly Yuin Y'ng Wong, Foong Ming Moy, Aziz Shafie, Sanjay Rampal","doi":"10.1186/s12942-024-00376-5","DOIUrl":"10.1186/s12942-024-00376-5","url":null,"abstract":"<p><strong>Background: </strong>The escalating trend of obesity in Malaysia is surmounting, and the lack of evidence on the environmental influence on obesity is untenable. Obesogenic environmental factors often emerge as a result of shared environmental, demographic, or cultural effects among neighbouring regions that impact lifestyle. Employing spatial clustering can effectively elucidate the geographical distribution of obesity and pinpoint regions with potential obesogenic environments, thereby informing public health interventions and further exploration on the local environments. This study aimed to determine the spatial clustering of body mass index (BMI) among adults in Malaysia.</p><p><strong>Method: </strong>This study utilized information of respondents aged 18 to 59 years old from the National Health and Morbidity Survey (NHMS) 2014 and 2015 at Peninsular Malaysia and East Malaysia. Fast food restaurant proximity, district population density, and district median household income were determined from other sources. The analysis was conducted for total respondents and stratified by sex. Multilevel regression was used to produce the BMI estimates on a set of variables, adjusted for data clustering at enumeration blocks. Global Moran's I and Local Indicator of Spatial Association statistics were applied to assess the general clustering and location of spatial clusters of BMI, respectively using point locations of respondents and spatial weights of 8 km Euclidean radius or 5 nearest neighbours.</p><p><strong>Results: </strong>Spatial clustering of BMI independent of individual sociodemographic was significant (p < 0.001) in Peninsular and East Malaysia with Global Moran's index of 0.12 and 0.15, respectively. High-BMI clusters (hotspots) were in suburban districts, whilst the urban districts were low-BMI clusters (cold spots). Spatial clustering was greater among males with hotspots located closer to urban areas, whereas hotspots for females were in less urbanized areas.</p><p><strong>Conclusion: </strong>Obesogenic environment was identified in suburban districts, where spatial clusters differ between males and females in certain districts. Future studies and interventions on creating a healthier environment should be geographically targeted and consider gender differences.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11201309/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141460177","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 use of Virtual Reality (VR) to assess the impact of geographical environments on walking and cycling: a systematic literature review.","authors":"Marzieh Ghanbari, Martin Dijst, Roderick McCall, Camille Perchoux","doi":"10.1186/s12942-024-00375-6","DOIUrl":"10.1186/s12942-024-00375-6","url":null,"abstract":"<p><strong>Background: </strong>Geographical environments influence people's active mobility behaviors, contributing to their physical and mental health. The use of Virtual Reality (VR) in experimental research can unveil new insights into the relationship between exposure to geographic environments and active mobility behaviors. This systematic review aims to (1) identify environmental attributes investigated in relation with walking and cycling, using VR, (2) assess their impacts on active mobility behaviors and attitudes, and (3) identify research gaps, strengths and limitations in VR-based experimental research.</p><p><strong>Methods: </strong>Articles published between January 2010 and February 2022 within five databases (PubMed, Scopus, EBSCO, IEEE Xplore, and Cochrane Library) were explored using three keywords and their synonyms: Virtual Reality, Active mobility behavior, and Geographical environments. Studies focusing on indoor environments, driving simulation, disease-specific groups, non-relevant disciplines (e.g. military, emergency evacuation), VR methodology/software optimization, and those with static participants' involvement were excluded. The full protocol is available from PROSPERO (ID = CRD42022308366).</p><p><strong>Results: </strong>Out of 3255 articles, 18 peer-reviewed papers met the selection criteria, mostly focusing on walking (83%). Most studies used head-mounted displays (94%) and relied on convenience sampling (72% below 100 participants). Both static (33%) and dynamic (45%) environmental attributes have been investigated, with only 22% of them simultaneously in the same virtual environment. Greenness and crowd density were the most frequent attributes, rather consistently associated with emotional states and movement behaviors. Few studies have taken into account participant's previous VR experience (33%) and cybersickness (39%) while both are likely to affect an individual's perception and behavior.</p><p><strong>Conclusions: </strong>Future research should explore a broader range of environmental attributes, including static and dynamic ones, as well as a more complex integration of these attributes within a single experiment to mimic the effect of realistic environments on people's active mobility behaviors and attitudes. Larger and more diverse population samples are deemed required to improve result generalizability. Despite methodological challenges, VR emerges as a promising tool to disentangle the effect of complex environments on active mobility behaviors.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11162039/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141293850","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":"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":null,"pages":null},"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}