International Journal of Health Geographics最新文献

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"title":"Socioeconomic and geographic variations of disabilities in India: evidence from the National Family Health Survey, 2019-21.","authors":"Rashmi Rashmi, Sanjay K Mohanty","doi":"10.1186/s12942-024-00363-w","DOIUrl":"10.1186/s12942-024-00363-w","url":null,"abstract":"<p><strong>Background: </strong>Increasing disability is of global and national concern. Lack of evidence on disability across socioeconomic groups and geographic levels (especially small areas) impeded interventions for these disadvantaged subgroups. We aimed to examine the socioeconomic and geographic variations in disabilities, namely hearing, speech, visual, mental, and locomotor, in Indian participants using cross-sectional data from the National Family Health Survey 2019-2021.</p><p><strong>Methods: </strong>Using data from 27,93,971 individuals, we estimated age-sex-adjusted disability rates at the national and sub-national levels. The extent of socioeconomic variations in disabilities was explored using the Erreygers Concentration Index and presented graphically through a concentration curve. We adopted a four-level random intercept logit model to compute the variance partitioning coefficient (VPC) to assess the significance of each geographical unit in total variability. We also calculated precision-weighted disability estimates of individuals across 707 districts and showed their correlation with within-district or between-cluster standard deviation.</p><p><strong>Results: </strong>We estimated the prevalence of any disability of 10 per 1000 population. The locomotor disability was common, followed by mental, speech, hearing, and visual. The concentration index of each type of disability was highest in the poorest wealth quintile households and illiterate 18 + individuals, confirming higher socioeconomic variations in disability rates. Clusters share the largest source of geographic variation for any disability (6.5%), hearing (5.8%), visual (24.3%), and locomotor (17.4%). However, States/Union Territories (UTs) account for the highest variation in speech (3.7%) and mental (6.5%) disabilities, where the variation at the cluster level becomes negligible. Districts with the highest disability rates were clustered in Madhya Pradesh, Maharashtra, Karnataka, Tamil Nadu, Telangana, and Punjab. Further, we found positive correlations between the district rates and cluster standard deviations (SDs) for disabilities.</p><p><strong>Conclusions: </strong>Though the growing disability condition in India is itself a concerning issue, wide variations across socioeconomic groups and geographic locations indicate the implementation of several policy-relevant implications focusing on these vulnerable chunks of the population. Further, the critical importance of small-area variations within districts suggests the design of strategies targeting these high-burden areas of disabilities.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10874552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139900662","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}