25 datasets found
  1. UNHCR Population Reference Points (PRP)

    • data.amerigeoss.org
    api +4
    Updated Jun 18, 2025
    + more versions
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    UN Humanitarian Data Exchange (2025). UNHCR Population Reference Points (PRP) [Dataset]. http://data.amerigeoss.org/dataset/unhcr-population-reference-points-prp
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    kmz, api, html, qgis, esri arcmap project fileAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    United Nationshttp://un.org/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Point layer that represents populated places locations (e.g., capitals/ cities/ towns) and of administrative units (Level 1, 2 and 3 depending on availability).

  2. Populations, abbreviations, sample sizes (n), mean number of IBD blocks...

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Peter Ralph; Graham Coop (2023). Populations, abbreviations, sample sizes (n), mean number of IBD blocks shared by a pair of individuals from that population (“self”), and mean IBD rate averaged across all other populations (“other”), sorted by regional groupings described in the text. [Dataset]. http://doi.org/10.1371/journal.pbio.1001555.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Peter Ralph; Graham Coop
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Populations, abbreviations, sample sizes (n), mean number of IBD blocks shared by a pair of individuals from that population (“self”), and mean IBD rate averaged across all other populations (“other”), sorted by regional groupings described in the text.

  3. UNHCR Population Reference Areas

    • data.humdata.org
    api +3
    Updated Jun 4, 2025
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    UNHCR - The UN Refugee Agency (2025). UNHCR Population Reference Areas [Dataset]. https://data.humdata.org/dataset/98b61b16-702a-4945-9543-3aa3d31b7fb6?force_layout=desktop
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    kmz, api, esri arcmap project file, htmlAvailable download formats
    Dataset updated
    Jun 4, 2025
    Dataset provided by
    United Nations High Commissioner for Refugeeshttp://www.unhcr.org/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Polygon layer that represent the areas of Population Reference Points. Available only for the main People of Concern locations.

  4. a

    Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy

    • africageoportal.com
    Updated Aug 20, 2020
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    Africa GeoPortal (2020). Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy [Dataset]. https://www.africageoportal.com/items/ffd1b8a7ffbf4b758fc15dcc0a6060c3
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    Dataset updated
    Aug 20, 2020
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    (by Joseph Kerski)This map is for use in the "What is the spatial pattern of demographic variables around the world?" activity in Section 1 of the Going Places with Spatial Analysiscourse. The map contains population characteristics by country for 2013.These data come from the Population Reference Bureau's 2014 World Population Data Sheet.The Population Reference Bureau (PRB) informs people around the world about population, health, and the environment, empowering them to use that information to advance the well-being of current and future generations.PRB analyzes complex demographic data and research to provide the most objective, accurate, and up-to-date population information in a format that is easily understood by advocates, journalists, and decision makers alike.The 2014 year's data sheet has detailed information on 16 population, health, and environment indicators for more than 200 countries. For infant mortality, total fertility rate, and life expectancy, we have included data from 1970 and 2013 to show change over time. This year's special data column is on carbon emissions.For more information about how PRB compiles its data, see: https://www.prb.org/

  5. f

    High-Accuracy HLA Type Inference from Whole-Genome Sequencing Data Using...

    • plos.figshare.com
    png
    Updated Jun 3, 2023
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    Alexander T. Dilthey; Pierre-Antoine Gourraud; Alexander J. Mentzer; Nezih Cereb; Zamin Iqbal; Gil McVean (2023). High-Accuracy HLA Type Inference from Whole-Genome Sequencing Data Using Population Reference Graphs [Dataset]. http://doi.org/10.1371/journal.pcbi.1005151
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    pngAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS Computational Biology
    Authors
    Alexander T. Dilthey; Pierre-Antoine Gourraud; Alexander J. Mentzer; Nezih Cereb; Zamin Iqbal; Gil McVean
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Genetic variation at the Human Leucocyte Antigen (HLA) genes is associated with many autoimmune and infectious disease phenotypes, is an important element of the immunological distinction between self and non-self, and shapes immune epitope repertoires. Determining the allelic state of the HLA genes (HLA typing) as a by-product of standard whole-genome sequencing data would therefore be highly desirable and enable the immunogenetic characterization of samples in currently ongoing population sequencing projects. Extensive hyperpolymorphism and sequence similarity between the HLA genes, however, pose problems for accurate read mapping and make HLA type inference from whole-genome sequencing data a challenging problem. We describe how to address these challenges in a Population Reference Graph (PRG) framework. First, we construct a PRG for 46 (mostly HLA) genes and pseudogenes, their genomic context and their characterized sequence variants, integrating a database of over 10,000 known allele sequences. Second, we present a sequence-to-PRG paired-end read mapping algorithm that enables accurate read mapping for the HLA genes. Third, we infer the most likely pair of underlying alleles at G group resolution from the IMGT/HLA database at each locus, employing a simple likelihood framework. We show that HLA*PRG, our algorithm, outperforms existing methods by a wide margin. We evaluate HLA*PRG on six classical class I and class II HLA genes (HLA-A, -B, -C, -DQA1, -DQB1, -DRB1) and on a set of 14 samples (3 samples with 2 x 100bp, 11 samples with 2 x 250bp Illumina HiSeq data). Of 158 alleles tested, we correctly infer 157 alleles (99.4%). We also identify and re-type two erroneous alleles in the original validation data. We conclude that HLA*PRG for the first time achieves accuracies comparable to gold-standard reference methods from standard whole-genome sequencing data, though high computational demands (currently ~30–250 CPU hours per sample) remain a significant challenge to practical application.

  6. Z

    3D cranial landmark coordinates from the Athens Collection. A modern Greek...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jul 25, 2024
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    Bertsatos Andreas (2024). 3D cranial landmark coordinates from the Athens Collection. A modern Greek population reference dataset for testing 3D-ID software [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_2553691
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    Dataset updated
    Jul 25, 2024
    Dataset provided by
    Chovalopoulou Maria-Eleni
    Bertsatos Andreas
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Area covered
    Athens
    Description

    The present dataset comprises the landmark coordinates of 158 intact crania (80 males and 78 females) of adult individuals from the Athens Collection. The 3D coordinates of up to 34 landmarks have been extracted from high quality textured 3D models produced with photogrammetry. The dataset aims to evaluate the correct classification performance of 3D-ID software. Hence, the dataset contains the landmark 3D coordinates both in Meshlab's PickedPoints files (.pp) but also in 3D-ID's input text format (.3did). The dataset is accompanied by certain GNU Octave scripts and functions used for data conversion and integrity check. For more details see the Dataset Description pdf.

  7. f

    HRQOL scores of MSMW and the Chinese general population reference group.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Jiang-Peng Chen; Ming-Ming Han; Zi-Jun Liao; Zhen-Zhen Dai; Liang Liu; Hua Chen; Xiao-Yan Wen; Shan Hu; Ping Que; Wen Wen; Bin Peng (2023). HRQOL scores of MSMW and the Chinese general population reference group. [Dataset]. http://doi.org/10.1371/journal.pone.0118651.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jiang-Peng Chen; Ming-Ming Han; Zi-Jun Liao; Zhen-Zhen Dai; Liang Liu; Hua Chen; Xiao-Yan Wen; Shan Hu; Ping Que; Wen Wen; Bin Peng
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data are shown as the mean±SD; Reference group: Chinese general population reference group.HRQOL scores of MSMW and the Chinese general population reference group.

  8. c

    The Occupational Therapy Software Market will grow at a CAGR of 5.6% from...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated May 7, 2025
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    Cognitive Market Research (2025). The Occupational Therapy Software Market will grow at a CAGR of 5.6% from 2023 to 2030! [Dataset]. https://www.cognitivemarketresearch.com/occupational-therapy-software-market-report
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    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    May 7, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    The Occupational Therapy Software market is valued at USD 2388.7 Million in 2022 and will be USD 3686.7 Million by 2030 with a CAGR of 5.6% during the forecast period. Factors Affecting Occupational Therapy Software Market Growth

    One of the main factors fuelling the market expansion is the increase in elderly population:
    

    As per the Population Reference Bureau, there has been a significant surge in the elderly population around the world. This demographic shift has led to a marked increase in the prevalence of chronic diseases, which is expected to further fuel the growth of the market. Furthermore, the aging population of the nation has created a substantial patient base that requires occupational and physical therapy services. It is worth noting that the likelihood of suffering from various chronic diseases rises with age, making this a critical issue that demands attention. As per the Population Reference Bureau, there has been a significant surge in the elderly population around the world. This demographic shift has led to a marked increase in the prevalence of chronic diseases, which is expected to further fuel the growth of the market. Furthermore, the aging population of the nation has created a substantial patient base that requires occupational and physical therapy services. It is worth noting that the likelihood of suffering from various chronic diseases rises with age, making this a critical issue that demands attention.

    The Restraining Factor of Occupational Therapy Software:

    Software issues obstruct the market growth:
    

    For small and medium-sized healthcare practices, one of the main challenges they might face is the cost associated with implementing and maintaining occupational therapy software. This can include not just the initial investment, but also ongoing expenditures related to updates, upgrades, and technical support. For many practices, these expenses can be a significant barrier to adopting new technology that could improve their operations and patient care.

    Impact of the COVID-19 Pandemic on the Anti Plagiarism Software for the Education Sector Market:

    The COVID-19 pandemic had an unexpected impact on the field of occupational therapy, as the software used to assist patients in their treatment proved to be especially beneficial during this time. With many patients being discharged from hospitals to prevent the spread of the virus, it became crucial for occupational therapists to continue providing care remotely. Through the use of electronic information and telecommunication technology, therapists were able to teach patients how to manage their exhaustion and gradually resume their normal activities. This innovative approach allowed for a safe and effective way to continue treatment amidst the pandemic. Introduction of Occupational Therapy Software

    Software for occupational therapy aids in streamlining finances, lightening the load, and increasing patient care, all of which contribute to better patient outcomes. Occupational therapy aids people with physical, mental, and sensory issues in regaining their independence in all facets of everyday living. These treatments are beneficial for people with illnesses like dementia, and Alzheimer's disease, amputations, and children with developmental disorders. The therapists give them care plans that enable them to carry out everyday activities on their own. Since these conditions are becoming more common, it is anticipated that during the forecast period, demand for these software solutions will increase. Due to the increasing prevalence of medical issues in this group, the market is expected to be driven by the world's growing elderly population. For instance, the Alzheimer's Association estimates that 6 million Americans over 65 had Alzheimer's in 2021 It is projected that the increased use of digital healthcare solutions will increase demand for occupational therapy software and positively affect market expansion.

  9. f

    FlexTyper search times for WGS samples.

    • plos.figshare.com
    xlsx
    Updated May 31, 2023
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    Phillip Andrew Richmond; Alice Mary Kaye; Godfrain Jacques Kounkou; Tamar Vered Av-Shalom; Wyeth W. Wasserman (2023). FlexTyper search times for WGS samples. [Dataset]. http://doi.org/10.1371/journal.pcbi.1008815.s005
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    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS Computational Biology
    Authors
    Phillip Andrew Richmond; Alice Mary Kaye; Godfrain Jacques Kounkou; Tamar Vered Av-Shalom; Wyeth W. Wasserman
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The operation (either Cytoscan search or Ancestry search), number of queries, sample id, max RAM used for search, wall time, and time in seconds. Parameter settings for search found in main text. (XLSX)

  10. f

    An exploration of parameter settings for the recovery of pathogen reads in...

    • figshare.com
    xlsx
    Updated Jun 3, 2023
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    Phillip Andrew Richmond; Alice Mary Kaye; Godfrain Jacques Kounkou; Tamar Vered Av-Shalom; Wyeth W. Wasserman (2023). An exploration of parameter settings for the recovery of pathogen reads in pure simulated viral samples. [Dataset]. http://doi.org/10.1371/journal.pcbi.1008815.s003
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    xlsxAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS Computational Biology
    Authors
    Phillip Andrew Richmond; Alice Mary Kaye; Godfrain Jacques Kounkou; Tamar Vered Av-Shalom; Wyeth W. Wasserman
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Indexed samples include EBV, HIV-1, FR751039, U21941, and ERR2322364 (human RNA-seq sample). The viral samples are simulated to a depth of 100x genomic coverage. Each subsection of the table is the analysis for an individual sample, which has been searched with specified parameters. An example parameter string: k100s1m2000u_UniqRead, can be interpreted as k-mer length 100, step size 1, maximum occurrence 2000, uniqueKmer parameter turned on, and unique read flag turned on. For each of the queries (EBV, HIV-1, FR751039, U21941), the FlexTyper count in Single-end mode is listed. Last, the search time for retrieving k-mers from the index is listed in seconds. (XLSX)

  11. f

    Social-demographic characteristics of study population.

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Jiang-Peng Chen; Ming-Ming Han; Zi-Jun Liao; Zhen-Zhen Dai; Liang Liu; Hua Chen; Xiao-Yan Wen; Shan Hu; Ping Que; Wen Wen; Bin Peng (2023). Social-demographic characteristics of study population. [Dataset]. http://doi.org/10.1371/journal.pone.0118651.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jiang-Peng Chen; Ming-Ming Han; Zi-Jun Liao; Zhen-Zhen Dai; Liang Liu; Hua Chen; Xiao-Yan Wen; Shan Hu; Ping Que; Wen Wen; Bin Peng
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data are shown as the number (%)#Wilcoxon rank tests were used*Chi-square tests were used.Social-demographic characteristics of study population.

  12. f

    Genomic Insights into the Ancestry and Demographic History of South America

    • plos.figshare.com
    pdf
    Updated Jun 1, 2023
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    Julian R. Homburger; Andrés Moreno-Estrada; Christopher R. Gignoux; Dominic Nelson; Elena Sanchez; Patricia Ortiz-Tello; Bernardo A. Pons-Estel; Eduardo Acevedo-Vasquez; Pedro Miranda; Carl D. Langefeld; Simon Gravel; Marta E. Alarcón-Riquelme; Carlos D. Bustamante (2023). Genomic Insights into the Ancestry and Demographic History of South America [Dataset]. http://doi.org/10.1371/journal.pgen.1005602
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS Genetics
    Authors
    Julian R. Homburger; Andrés Moreno-Estrada; Christopher R. Gignoux; Dominic Nelson; Elena Sanchez; Patricia Ortiz-Tello; Bernardo A. Pons-Estel; Eduardo Acevedo-Vasquez; Pedro Miranda; Carl D. Langefeld; Simon Gravel; Marta E. Alarcón-Riquelme; Carlos D. Bustamante
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    South America, Americas
    Description

    South America has a complex demographic history shaped by multiple migration and admixture events in pre- and post-colonial times. Settled over 14,000 years ago by Native Americans, South America has experienced migrations of European and African individuals, similar to other regions in the Americas. However, the timing and magnitude of these events resulted in markedly different patterns of admixture throughout Latin America. We use genome-wide SNP data for 437 admixed individuals from 5 countries (Colombia, Ecuador, Peru, Chile, and Argentina) to explore the population structure and demographic history of South American Latinos. We combined these data with population reference panels from Africa, Asia, Europe and the Americas to perform global ancestry analysis and infer the subcontinental origin of the European and Native American ancestry components of the admixed individuals. By applying ancestry-specific PCA analyses we find that most of the European ancestry in South American Latinos is from the Iberian Peninsula; however, many individuals trace their ancestry back to Italy, especially within Argentina. We find a strong gradient in the Native American ancestry component of South American Latinos associated with country of origin and the geography of local indigenous populations. For example, Native American genomic segments in Peruvians show greater affinities with Andean indigenous peoples like Quechua and Aymara, whereas Native American haplotypes from Colombians tend to cluster with Amazonian and coastal tribes from northern South America. Using ancestry tract length analysis we modeled post-colonial South American migration history as the youngest in Latin America during European colonization (9–14 generations ago), with an additional strong pulse of European migration occurring between 3 and 9 generations ago. These genetic footprints can impact our understanding of population-level differences in biomedical traits and, thus, inform future medical genetic studies in the region.

  13. f

    Social support and HRQOL scores of the two groups.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Jiang-Peng Chen; Ming-Ming Han; Zi-Jun Liao; Zhen-Zhen Dai; Liang Liu; Hua Chen; Xiao-Yan Wen; Shan Hu; Ping Que; Wen Wen; Bin Peng (2023). Social support and HRQOL scores of the two groups. [Dataset]. http://doi.org/10.1371/journal.pone.0118651.t003
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jiang-Peng Chen; Ming-Ming Han; Zi-Jun Liao; Zhen-Zhen Dai; Liang Liu; Hua Chen; Xiao-Yan Wen; Shan Hu; Ping Que; Wen Wen; Bin Peng
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data are shown as the mean±SD.Social support and HRQOL scores of the two groups.

  14. f

    Details of the birds inducted into the study.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Tamsyn Fourie; Duncan Cromarty; Neil Duncan; Kerri Wolter; Vinny Naidoo (2023). Details of the birds inducted into the study. [Dataset]. http://doi.org/10.1371/journal.pone.0141419.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tamsyn Fourie; Duncan Cromarty; Neil Duncan; Kerri Wolter; Vinny Naidoo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Details of the birds inducted into the study.

  15. f

    Health Related Quality of Life in a Dutch Rehabilitation Population:...

    • plos.figshare.com
    pdf
    Updated May 31, 2023
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    Leonie A. Krops; Eva A. Jaarsma; Pieter U. Dijkstra; Jan H. B. Geertzen; Rienk Dekker (2023). Health Related Quality of Life in a Dutch Rehabilitation Population: Reference Values and the Effect of Physical Activity [Dataset]. http://doi.org/10.1371/journal.pone.0169169
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    pdfAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Leonie A. Krops; Eva A. Jaarsma; Pieter U. Dijkstra; Jan H. B. Geertzen; Rienk Dekker
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    PurposeTo establish reference values for Health Related Quality of Life (HRQoL) in a Dutch rehabilitation population, and to study effects of patient characteristics, diagnosis and physical activity on HRQoL in this population.MethodFormer rehabilitation patients (3169) were asked to fill in a questionnaire including the Dutch version of the RAND-36. Differences between our rehabilitation patients and Dutch reference values were analyzed (t-tests). Effects of patient characteristics, diagnosis and movement intensity on scores on the subscales of the RAND-36 were analyzed using block wise multiple regression analyses.ResultsIn total 1223 patients (39%) returned the questionnaire. HRQoL was significantly poorer in the rehabilitation patients compared to Dutch reference values on all subscales (p

  16. Summary of findings from previous studies on association between age- and...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Arshad M. Channanath; Naser Elkum; Dalia Al-Abdulrazzaq; Jaakko Tuomilehto; Azza Shaltout; Thangavel Alphonse Thanaraj (2023). Summary of findings from previous studies on association between age- and sex-adjusted BMI z-scores and age at onset of T1D in various populations. [Dataset]. http://doi.org/10.1371/journal.pone.0175728.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Arshad M. Channanath; Naser Elkum; Dalia Al-Abdulrazzaq; Jaakko Tuomilehto; Azza Shaltout; Thangavel Alphonse Thanaraj
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summary of findings from previous studies on association between age- and sex-adjusted BMI z-scores and age at onset of T1D in various populations.

  17. f

    Odds Ratios associated with selected cardio-metabolic factors amongst the...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Christian Obirikorang; Derick Nii Mensah Osakunor; Enoch Odame Anto; Samuel Opoku Amponsah; Opei Kwafo Adarkwa (2023). Odds Ratios associated with selected cardio-metabolic factors amongst the urban population (reference: rural population). [Dataset]. http://doi.org/10.1371/journal.pone.0129494.t005
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Christian Obirikorang; Derick Nii Mensah Osakunor; Enoch Odame Anto; Samuel Opoku Amponsah; Opei Kwafo Adarkwa
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    OR: Odds ratio. Adj: adjusted. Compared using Multivariate logistic regression. p < 0.05 was considered significant.Odds Ratios associated with selected cardio-metabolic factors amongst the urban population (reference: rural population).

  18. f

    a. The contribution of the original 17 founders to the lowland-Caucasian...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
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    Karolína Machová; Pavla Štruncová; Jan Calta; Ladislav Tichý; Luboš Vostrý (2023). a. The contribution of the original 17 founders to the lowland-Caucasian lineage part of the reference population. [Dataset]. http://doi.org/10.1371/journal.pone.0277456.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Karolína Machová; Pavla Štruncová; Jan Calta; Ladislav Tichý; Luboš Vostrý
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    b. The contribution of the original 17 founders to the lowland lineage part of the reference population.

  19. f

    The relationship between blood manganese and BMD/BMC in femur.

    • plos.figshare.com
    bin
    Updated Jun 13, 2023
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    Chao Wang; Yong Zhu; Haitao Long; Mingning Ou; Shushan Zhao (2023). The relationship between blood manganese and BMD/BMC in femur. [Dataset]. http://doi.org/10.1371/journal.pone.0276551.t001
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    binAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Chao Wang; Yong Zhu; Haitao Long; Mingning Ou; Shushan Zhao
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The relationship between blood manganese and BMD/BMC in femur.

  20. f

    Association of blood manganese with total spine BMD/BMC, stratified by sex,...

    • plos.figshare.com
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    Updated Jun 13, 2023
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    Chao Wang; Yong Zhu; Haitao Long; Mingning Ou; Shushan Zhao (2023). Association of blood manganese with total spine BMD/BMC, stratified by sex, race/ethnicity and age. [Dataset]. http://doi.org/10.1371/journal.pone.0276551.t005
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Chao Wang; Yong Zhu; Haitao Long; Mingning Ou; Shushan Zhao
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Association of blood manganese with total spine BMD/BMC, stratified by sex, race/ethnicity and age.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
UN Humanitarian Data Exchange (2025). UNHCR Population Reference Points (PRP) [Dataset]. http://data.amerigeoss.org/dataset/unhcr-population-reference-points-prp
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UNHCR Population Reference Points (PRP)

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kmz, api, html, qgis, esri arcmap project fileAvailable download formats
Dataset updated
Jun 18, 2025
Dataset provided by
United Nationshttp://un.org/
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Point layer that represents populated places locations (e.g., capitals/ cities/ towns) and of administrative units (Level 1, 2 and 3 depending on availability).

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