37 datasets found
  1. d

    Eating Disorders in Military Connected People

    • catalog.data.gov
    • data.mo.gov
    • +1more
    Updated Feb 7, 2025
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    data.mo.gov (2025). Eating Disorders in Military Connected People [Dataset]. https://catalog.data.gov/dataset/eating-disorders-in-military-connected-people
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    Dataset updated
    Feb 7, 2025
    Dataset provided by
    data.mo.gov
    Description

    Information about the types of eating disorders, some reasons why the military community are at risk, warning signs and how to get help. The Missouri Eating Disorders Council (MOEDC) created this document so support service members, veterans and their families.

  2. Children and Young People Eating Disorder Collection Q4 2022/23

    • gov.uk
    Updated May 11, 2023
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    NHS England (2023). Children and Young People Eating Disorder Collection Q4 2022/23 [Dataset]. https://www.gov.uk/government/statistics/children-and-young-people-eating-disorder-collection-q4-202223
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    Dataset updated
    May 11, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    NHS England
    Description

    The data collection is an interim aggregate data collection which will run until data of sufficient quality are available from the Mental Health Services dataset (MHSDS). The dataset has been approved by the data control board to run until the MHSDS is considered to be of sufficient completeness and quality.

    The Strategic Data Collection Service (SDCS) collection for Children and Young People with Eating Disorders (CYP ED) will be retired at the end of the 2022-23 reporting period. Information for activity for 2022-23 quarter 3 (October-December 2022) and quarter 4 (January – March 2023) will continue to be collected via SDCS. Following the completion of the quarter 4 collection (final submission date will be mid-April 2023) and publication the SDCS collection will be retired. The CYP ED access and waiting time standard will be monitored using the MHSDS data only from 2023-24 onwards. Services wholly or partly funded by the NHS (including the private and voluntary sector) are contractually bound to record accurate data on their services under the NHS Standard Contract.

    Official statistics are produced impartially and free from political influence.

  3. f

    Motivational interviewing and anorexia nervosa dataset

    • open.flinders.edu.au
    • researchdata.edu.au
    Updated May 31, 2023
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    Tracey Wade; Anna Frayne; Sally-Anne Edwards; Therese Robinson; Peter Gilchrist (2023). Motivational interviewing and anorexia nervosa dataset [Dataset]. http://doi.org/10.25451/flinders.16881934.v1
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    Dataset updated
    May 31, 2023
    Dataset provided by
    Flinders University
    Authors
    Tracey Wade; Anna Frayne; Sally-Anne Edwards; Therese Robinson; Peter Gilchrist
    License

    https://library.unimelb.edu.au/Digital-Scholarship/restrictive-licence-templatehttps://library.unimelb.edu.au/Digital-Scholarship/restrictive-licence-template

    Description

    This dataset comprises survey and interview results from an investigation into the efficacy of motivational interviewing in engaging individuals with anorexia nervosa in treatment. Responses from 47 participants (2 male and 45 female aged between 16 and 37 years) are arranged in a database.Participants were part of an inpatient anorexia nervosa population, assessed over three waves; at admission to hospital (baseline), and at 2 and 6 week follow up. Assessment were conducted face to face for participants in hospital and via the telephone for those who had been discharged.The Anorexia Nervosa Stages of Change Questionnaire (ANSOCQ) was used for the study.Date coverage: 2005-10-01 - 2008-08-01Location: Adelaide, South Australia, Australia

  4. Children and Young People Eating Disorder Collection

    • gov.uk
    Updated May 10, 2018
    + more versions
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    NHS England (2018). Children and Young People Eating Disorder Collection [Dataset]. https://www.gov.uk/government/statistics/children-and-young-people-eating-disorder-collection
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    Dataset updated
    May 10, 2018
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    NHS England
    Description

    The data collection is an interim aggregate experimental data collection which will run until data of sufficient quality are available from the Mental Health Services dataset (MHSDS). The dataset has been approved to run up until the end of 2016/17. The MHSDS will collect data that allows the calculation of CYP ED waiting times from April 2017, however there are likely to be issues around the quality of the initial data.

    Official statistics are produced impartially and free from political influence.

  5. f

    Neurobiology of social reward valuation in adults with a history of anorexia...

    • plos.figshare.com
    • research.repository.duke.edu
    pdf
    Updated May 30, 2023
    + more versions
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    Maggie M. Sweitzer; Karli K. Watson; Savannah R. Erwin; Amy A. Winecoff; Nandini Datta; Scott Huettel; Michael L. Platt; Nancy L. Zucker (2023). Neurobiology of social reward valuation in adults with a history of anorexia nervosa [Dataset]. http://doi.org/10.1371/journal.pone.0205085
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    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Maggie M. Sweitzer; Karli K. Watson; Savannah R. Erwin; Amy A. Winecoff; Nandini Datta; Scott Huettel; Michael L. Platt; Nancy L. Zucker
    License

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

    Description

    ObjectiveAnorexia nervosa (AN) is a disorder characterized by atypical patterns of reward valuation (e.g. positive valuation of hunger). Atypical reward processing may extend into social domains. If so, such findings would be of prognostic significance as impaired social functioning predicts worse outcome. We explore neural circuits implicated in social reward processing in individuals with a history of AN who are weight-restored relative to controls and examine the effects of illness course on the experience of social value.Method20 weight-restored individuals with a history of AN (AN-WR) and 24 healthy control (HC) participants were assessed using fMRI tasks that tapped social reward: smiling faces and full human figures that varied in attractiveness and weight.ResultsAN-WR differed from HC in attractiveness ratings by weight (negatively correlated in AN-WR). While there were no significant differences when viewing smiling faces, viewing full figures resulted in decreased activation in regions implicated in reward valuation (the right caudate) for AN-WR and this region was negatively correlated with a sustained course of the disorder. Exploratory whole brain analyses revealed reduced activation in regions associated with social reward, self-referential processing, and cognitive reappraisal (e.g., medial prefrontal cortex, striatum, and nucleus accumbens) with sustained disorder course.DiscussionThe rewarding value of full body images decreases with a sustained disorder course. This may reflect an extension of atypical reward processing documented in AN-WR, perhaps as a function of starvation dampening visceral motivational signals; the deployment of cognitive strategies that lessen the experience of reward; and/or the nature of the stimuli themselves as provocative of eating disorder symptoms (e.g., thin bodies). These findings did not extend to smiling face stimuli. Advances in technology (e.g., virtual avatars, text messaging) may provide novel means to build relationships, including therapeutic relationships, to support improved social connections without threats to symptom provocation.

  6. G

    Mental Health and Substance Use Health Services

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +1more
    csv, geojson, html +4
    Updated Jun 18, 2025
    + more versions
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    Government of British Columbia (2025). Mental Health and Substance Use Health Services [Dataset]. https://open.canada.ca/data/en/dataset/2e469ff2-dadb-45ea-af9d-f5683a4b9465
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    pdf, csv, geojson, xls, kml, wms, htmlAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Government of British Columbia
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    The HealthLink BC Mental Health and Substance Use (MHSU) data set includes the following: Programs that offer early intervention, transitional care or other services that supplement and facilitate primary and adjunctive therapies; which offer community mental health education programs; or which link people who are in need of treatment with appropriate providers. Programs that provide preventive, diagnostic and treatment services in a variety of community and hospital-based settings to help people achieve, maintain and enhance a state of emotional well-being, personal empowerment and the skills to cope with everyday demands without excessive stress or reliance on alcohol or other drugs. Treatment may include emotional support, introspection and problem-solving assistance using a variety of modalities and approaches, and medication, as needed, for individuals who have a substance use disorder involving alcohol and/or other drugs or for people who range from experiencing difficult life transitions or problems in coping with daily living to those with severe, chronic mental illnesses that seriously impact their lives. Multidisciplinary programs, often offered on an inpatient basis with post-discharge outpatient therapy, that provide comprehensive diagnostic and treatment services for individuals who have anorexia nervosa, binge-eating disorder, bulimia or a related eating disorder. Treatment depends on the specific type of eating disorder involved but typically involves psychotherapy, nutrition education, family counseling, medication and hospitalization, if required, to stabilize the patient's health. Alliance of Information & Referral Systems (AIRS) / 211 LA County taxonomy is the data classification used for all HealthLink BC directory data, including this MHSU data set (https://www.airs.org/i4a/pages/index.cfm?pageid=1). AIRS taxonomy and data definitions are protected by Copyright by Information and Referral Federal of Los Angeles County, Inc (https://211taxonomy.org/subscriptions/#agreement)

  7. f

    Data Sheet 1_Gender differences in eating disorders.docx

    • figshare.com
    docx
    Updated Jun 2, 2025
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    Elena Ilaria Capuano; Angela Ruocco; Beatrice Scazzocchio; Giulia Zanchi; Camilla Lombardo; Annalisa Silenzi; Elena Ortona; Rosaria Varì (2025). Data Sheet 1_Gender differences in eating disorders.docx [Dataset]. http://doi.org/10.3389/fnut.2025.1583672.s001
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    docxAvailable download formats
    Dataset updated
    Jun 2, 2025
    Dataset provided by
    Frontiers
    Authors
    Elena Ilaria Capuano; Angela Ruocco; Beatrice Scazzocchio; Giulia Zanchi; Camilla Lombardo; Annalisa Silenzi; Elena Ortona; Rosaria Varì
    License

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

    Description

    Eating disorders (EDs) are characterized by disturbances in eating behavior and occur worldwide, with a lifetime prevalence of 2 to 5%. Their etiology is complex and multifactorial, involving a complex interplay between genetic, biological, psychological, sociocultural, and environmental factors. They are more common among females than males and may be associated with medical and psychiatric complications, impaired functioning, and decreased quality of life. This narrative review aims at providing an updated contribution to the current understanding of gender differences in eating disorders (EDs) focusing on male population to foster more targeted and effective clinical interventions. A comprehensive review of the scientific literature was conducted by analyzing several major databases, including PubMed, PsycINFO, and Google Scholar. Only in recent years, there has been increased attention on the male population, revealing multiple differences between genders in terms of prevalence, onset, phenomenology, diagnosis, comorbidities, and outcomes of EDs. Moreover, the relationship between different sexual orientations and/or gender identities and EDs is an emerging field of study. Data suggest an increase in eating disorders (EDs) also among the male population underlines the importance that healthcare personnel of all specialties acquire basic competencies for adequately tackling these disorders in a gender perspective. In particular, prevention and early intervention, especially during critical developmental periods like puberty and adolescence, are crucial to avoid permanent damage. Future research and public health initiatives involving schools and families and targeting males should be addressed to promote a healthy relationship with food and body image, reduce stigma, and encourage people to seek help when needed.

  8. o

    Binge Eating Disorder Prevalence in a University-Based Obesity Clinic

    • osf.io
    Updated Apr 5, 2023
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    Cindy Ho (2023). Binge Eating Disorder Prevalence in a University-Based Obesity Clinic [Dataset]. https://osf.io/ts6q5
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    Dataset updated
    Apr 5, 2023
    Dataset provided by
    Center For Open Science
    Authors
    Cindy Ho
    Description

    No description was included in this Dataset collected from the OSF

  9. d

    Health and Care of People with Learning Disabilities

    • digital.nhs.uk
    Updated Dec 7, 2023
    + more versions
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    (2023). Health and Care of People with Learning Disabilities [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/health-and-care-of-people-with-learning-disabilities
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    Dataset updated
    Dec 7, 2023
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Apr 1, 2022 - Mar 31, 2023
    Description

    The aim of this publication is to provide information about the key differences in healthcare between people with a learning disability and those without. It contains aggregated data on key health issues for people who are recorded by their GP as having a learning disability, and comparative data about a control group who are not recorded by their GP as having a learning disability. Six new indicators were introduced in the 2022-23 reporting year for patients with and without a recorded learning disability. These relate to: • Patients with an eating disorder • Patients with both an eating disorder and autism diagnosis • Patients with a diagnosis of autism who are currently treated with antidepressants More information on these changes can be found in the Data Quality section of this publication. Data has been collected from participating practices using EMIS and Cegedim Healthcare Systems GP systems.

  10. o

    Prevalence and correlates of bipolar disorders in patients with eating...

    • odportal.tw
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    Prevalence and correlates of bipolar disorders in patients with eating disorders. [Dataset]. https://odportal.tw/dataset/jxsq-efV
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    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    "BACKGROUND: To investigate the prevalence and correlates of bipolar disorders in patients with eating disorders (EDs), and to examine differences in effects between major depressive disorder and bipolar disorder on these patients. METHODS: Sequential attendees were invited to participate in a two-phase survey for EDs at the general psychiatric outpatient clinics. Patients diagnosed with EDs (n=288) and controls of comparable age, sex, and educational level (n=81) were invited to receive structured interviews for psychiatric co-morbidities, suicide risks, and functional level. All participants also completed several self-administered questionnaires assessing general and eating-related pathology and impulsivity. Characteristics were compared between the control, ED-only, ED with major depressive disorder, and ED with bipolar disorder groups. RESULTS: Patients with all ED subtypes had significantly higher rates of major depressive disorder (range, 41.3-66.7%) and bipolar disorder (range, 16.7-49.3%) than controls did. Compared to patients with only EDs, patients with comorbid bipolar disorder and those with comorbid major depressive disorder had significantly increased suicidality and functional impairments. Moreover, the group with comorbid bipolar disorder had increased risks of weight dysregulation, more impulsive behaviors, and higher rates of psychiatric comorbidities. LIMITATIONS: Participants were selected in a tertiary center of a non-Western country and the sample size of individuals with bipolar disorder in some ED subtypes was small. CONCLUSION: Bipolar disorders were common in patients with EDs. Careful differentiation between bipolar disorder and major depressive disorder in patients with EDs may help predict associated psychopathology and provide accurate treatment."

  11. f

    Additional file 4 of Eating disorder symptomatology among transgender...

    • springernature.figshare.com
    xlsx
    Updated Aug 13, 2024
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    Sofie M. Rasmussen; Martin K. Dalgaard; Mia Roloff; Mette Pinholt; Conni Skrubbeltrang; Loa Clausen; Gry Kjaersdam Telléus (2024). Additional file 4 of Eating disorder symptomatology among transgender individuals: a systematic review and meta-analysis [Dataset]. http://doi.org/10.6084/m9.figshare.26592008.v1
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    xlsxAvailable download formats
    Dataset updated
    Aug 13, 2024
    Dataset provided by
    figshare
    Authors
    Sofie M. Rasmussen; Martin K. Dalgaard; Mia Roloff; Mette Pinholt; Conni Skrubbeltrang; Loa Clausen; Gry Kjaersdam Telléus
    License

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

    Description

    Additional file 4. Title: Data used for meta-analysis of prevalence. Description: Data used for meta-analysis of prevalence.

  12. u

    Mental Health and Substance Use Health Services - Catalogue - Canadian Urban...

    • beta.data.urbandatacentre.ca
    • data.urbandatacentre.ca
    Updated Sep 13, 2024
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    (2024). Mental Health and Substance Use Health Services - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://beta.data.urbandatacentre.ca/dataset/gov-canada-2e469ff2-dadb-45ea-af9d-f5683a4b9465
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    Dataset updated
    Sep 13, 2024
    Description

    The HealthLink BC Mental Health and Substance Use (MHSU) data set includes the following: Programs that offer early intervention, transitional care or other services that supplement and facilitate primary and adjunctive therapies; which offer community mental health education programs; or which link people who are in need of treatment with appropriate providers. Programs that provide preventive, diagnostic and treatment services in a variety of community and hospital-based settings to help people achieve, maintain and enhance a state of emotional well-being, personal empowerment and the skills to cope with everyday demands without excessive stress or reliance on alcohol or other drugs. Treatment may include emotional support, introspection and problem-solving assistance using a variety of modalities and approaches, and medication, as needed, for individuals who have a substance use disorder involving alcohol and/or other drugs or for people who range from experiencing difficult life transitions or problems in coping with daily living to those with severe, chronic mental illnesses that seriously impact their lives. Multidisciplinary programs, often offered on an inpatient basis with post-discharge outpatient therapy, that provide comprehensive diagnostic and treatment services for individuals who have anorexia nervosa, binge-eating disorder, bulimia or a related eating disorder. Treatment depends on the specific type of eating disorder involved but typically involves psychotherapy, nutrition education, family counseling, medication and hospitalization, if required, to stabilize the patient's health. Alliance of Information & Referral Systems (AIRS) / 211 LA County taxonomy is the data classification used for all HealthLink BC directory data, including this MHSU data set (https://www.airs.org/i4a/pages/index.cfm?pageid=1). AIRS taxonomy and data definitions are protected by Copyright by Information and Referral Federal of Los Angeles County, Inc (https://211taxonomy.org/subscriptions/#agreement)

  13. D

    Data from: Negative Body Image is Not Related to Spontaneous Body-Scaled...

    • dataverse.nl
    • narcis.nl
    Updated Mar 5, 2019
    + more versions
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    Klaske A. Glashouwer; Charlotte Meulman; Peter de de Jong; Klaske A. Glashouwer; Charlotte Meulman; Peter de de Jong (2019). Negative Body Image is Not Related to Spontaneous Body-Scaled Motoric Behavior in Undergraduate Women [Dataset]. http://doi.org/10.34894/JG33QO
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    application/x-spss-sav(96605)Available download formats
    Dataset updated
    Mar 5, 2019
    Dataset provided by
    DataverseNL
    Authors
    Klaske A. Glashouwer; Charlotte Meulman; Peter de de Jong; Klaske A. Glashouwer; Charlotte Meulman; Peter de de Jong
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Body image disturbance is a core characteristic of anorexia nervosa which might be grounded in distortions in schematic body representations. In line with this, several studies showed that when walking through door-like apertures of different widths individuals with anorexia nervosa move as if their bodies are larger than they actually are. They turn their body at a higher aperture/shoulder width ratio than healthy individuals. We examined whether oversized body-scaled motoric behaviors may not be restricted to anorexia nervosa but concern a general feature of negative body image attitudes. Therefore, we investigated the relation between negative body image as assessed with shape and weight concerns subscales of the Eating Disorder Examination Questionnaire and aperture/shoulder width turning ratios in women with a healthy weight (N = 62). We found that a more negative body image was unrelated to higher aperture/shoulder width turning ratios. Bayes analysis provided moderate evidence for the null hypothesis that spontaneous body-scaled motoric behaviors are not involved in negative body image. Future studies should disentangle whether being underweight per se is related to distinctive spontaneous body-scaled motoric behaviors or whether an ‘oversized’ body schema is a unique characteristic of anorexia nervosa, potentially contributing to the persistence of this disorder.

  14. f

    Table_1_White Matter Abnormalities in Anorexia Nervosa: Psychoradiologic...

    • frontiersin.figshare.com
    docx
    Updated Jun 7, 2023
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    Simin Zhang; Weina Wang; Xiaorui Su; Lei Li; Xibiao Yang; Jingkai Su; Qiaoyue Tan; Youjin Zhao; Huaiqiang Sun; Graham J. Kemp; Qiyong Gong; Qiang Yue (2023). Table_1_White Matter Abnormalities in Anorexia Nervosa: Psychoradiologic Evidence From Meta-Analysis of Diffusion Tensor Imaging Studies Using Tract Based Spatial Statistics.docx [Dataset]. http://doi.org/10.3389/fnins.2020.00159.s001
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    docxAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    Frontiers
    Authors
    Simin Zhang; Weina Wang; Xiaorui Su; Lei Li; Xibiao Yang; Jingkai Su; Qiaoyue Tan; Youjin Zhao; Huaiqiang Sun; Graham J. Kemp; Qiyong Gong; Qiang Yue
    License

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

    Description

    Background: Anorexia nervosa (AN) is a debilitating illness whose neural basis remains unclear. Studies using tract-based spatial statistics (TBSS) with diffusion tensor imaging (DTI) have demonstrated differences in white matter (WM) microarchitecture in AN, but the findings are inconclusive and controversial.Objectives: To identify the most consistent WM abnormalities among previous TBSS studies of differences in WM microarchitecture in AN.Methods: By systematically searching online databases, a total of 11 datasets were identified, including 245 patients with AN and 246 healthy controls (HC). We used Seed-based d Mapping to analyze fractional anisotropy (FA) differences between AN patients and HC, and performed meta-regression analysis to explore the effects of clinical characteristics on WM abnormalities in AN.Results: The pooled results of all AN patients showed robustly lower FA in the corpus callosum (CC) and the cingulum compared to HC. These two regions preserved significance in the sensitivity analysis as well as in all subgroup analyses. Fiber tracking showed that the WM tracts primarily involved were the body of the CC and the cingulum bundle. Meta-regression analysis revealed that the body mass index and mean age were not linearly correlated with the lower FA.Conclusions: The most consistent WM microstructural differences in AN were in the interhemispheric connections and limbic association fibers. These common “targets” advance our understanding of the complex neural mechanisms underlying the puzzling symptoms of AN, and may help in developing early treatment approaches.

  15. f

    Patient characteristics (n = 180) at inclusion and global scores on...

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Melissa Rizk; Christophe Lalanne; Sylvie Berthoz; Laurence Kern; Nathalie Godart (2023). Patient characteristics (n = 180) at inclusion and global scores on psychological scales. [Dataset]. http://doi.org/10.1371/journal.pone.0143352.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Melissa Rizk; Christophe Lalanne; Sylvie Berthoz; Laurence Kern; Nathalie Godart
    License

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

    Description

    BMI: Body mass index. BSQ: Body Shape Questionnaire score. BVAQ-B: Bermond—Vorst alexithymia questionnaire-form B. Duration PA: Total duration of physical activity. EAT-26 bulimia: 26-item Eating Attitudes Test bulimia and food preoccupation subscale score. EAT-26 dieting: 26-item Eating Attitudes Test dieting subscale score. EDE-Q compulsive: Item 18 of the EDE-Q. HAD anx.dep: Hospital anxiety and depression scale composite score. Intensity PA: Mean intensity of physical activities. MOCI: Maudsley obsessive-compulsive inventory total score. RSES: Rosenberg self-esteem scale score.Patient characteristics (n = 180) at inclusion and global scores on psychological scales.

  16. f

    Table_2_Anorexia and bulimia in relation to ulcerative colitis: a Mendelian...

    • frontiersin.figshare.com
    xlsx
    Updated Jul 10, 2024
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    Qiang Su; Jian Li; Yun Lu; Min Wu; Jiang Liang; Zhenxiang An (2024). Table_2_Anorexia and bulimia in relation to ulcerative colitis: a Mendelian randomization study.xlsx [Dataset]. http://doi.org/10.3389/fnut.2024.1400713.s002
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    xlsxAvailable download formats
    Dataset updated
    Jul 10, 2024
    Dataset provided by
    Frontiers
    Authors
    Qiang Su; Jian Li; Yun Lu; Min Wu; Jiang Liang; Zhenxiang An
    License

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

    Description

    BackgroundEvidence for anorexia and bulimia in relation to the risk of ulcerative colitis (UC) is limited and inconsistent. The objective of this research was to utilize bi-directional, two-sample Mendelian randomization (MR) analysis to predict the causal association between anorexia nervosa and bulimia nervosa with UC.MethodsThe genome-wide association studies (GWAS) provided data for anorexia and bulimia from the UK Biobank, utilizing single-nucleotide polymorphisms (SNP) as instrumental variables. Additionally, genetic associations with UC were collected from various sources including the FinnGen Biobank, the UK Biobank and the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC). The main analytical approach utilized in this study was the inverse-variance-weighted (IVW) method. To evaluate horizontal pleiotropy, the researchers conducted MR-Egger regression and MR-PRESSO global test analyses. Additionally, heterogeneity was assessed using the Cochran’s Q test.ResultsThis study found a negative association between genetically predicted bulimia (OR = 0.943, 95% CI: 0.893–0.996; p = 0.034) and the risk of UC in the IIBDGC dataset, indicating that individuals with bulimia have approximately a 5.7% lower risk of developing UC. No association was observed in the other two datasets. Conversely, genetically predicted anorexia was not found to be causally associated with UC. In bi-directional Mendelian randomization, UC from the IIBDGC dataset was negatively associated with the risk of anorexia (OR = 0.877, 95% CI: 0.797–0.965; p = 0.007), suggesting that UC patients have approximately a 12.3% lower risk of developing anorexia, but not causally associated with bulimia.ConclusionGenetically predicted bulimia may have a negative association with the onset of UC, while genetically predicted anorexia does not show a causal relationship with the development of UC. Conversely, genetically predicted UC may have a negative association with the development of anorexia.

  17. f

    Descriptive statistics of treatment received within three months after...

    • figshare.com
    xls
    Updated Jun 30, 2023
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    Kathrin Schopf; Silvia Schneider; Andrea Hans Meyer; Julia Lennertz; Nadine Humbel; Nadine-Messerli Bürgy; Andrea Wyssen; Esther Biedert; Bettina Isenschmid; Gabriella Milos; Malte Claussen; Stephan Trier; Katherina Whinyates; Dirk Adolph; Tobias Teismann; Jürgen Margraf; Hans-Jörg Assion; Bianca Überberg; Georg Juckel; Judith Müller; Benedikt Klauke; Simone Munsch (2023). Descriptive statistics of treatment received within three months after admission (therapist-report). [Dataset]. http://doi.org/10.1371/journal.pone.0280402.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kathrin Schopf; Silvia Schneider; Andrea Hans Meyer; Julia Lennertz; Nadine Humbel; Nadine-Messerli Bürgy; Andrea Wyssen; Esther Biedert; Bettina Isenschmid; Gabriella Milos; Malte Claussen; Stephan Trier; Katherina Whinyates; Dirk Adolph; Tobias Teismann; Jürgen Margraf; Hans-Jörg Assion; Bianca Überberg; Georg Juckel; Judith Müller; Benedikt Klauke; Simone Munsch
    License

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

    Description

    Descriptive statistics of treatment received within three months after admission (therapist-report).

  18. f

    Table_1_Anorexia and bulimia in relation to ulcerative colitis: a Mendelian...

    • frontiersin.figshare.com
    xlsx
    Updated Jul 10, 2024
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    Qiang Su; Jian Li; Yun Lu; Min Wu; Jiang Liang; Zhenxiang An (2024). Table_1_Anorexia and bulimia in relation to ulcerative colitis: a Mendelian randomization study.XLSX [Dataset]. http://doi.org/10.3389/fnut.2024.1400713.s001
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    xlsxAvailable download formats
    Dataset updated
    Jul 10, 2024
    Dataset provided by
    Frontiers
    Authors
    Qiang Su; Jian Li; Yun Lu; Min Wu; Jiang Liang; Zhenxiang An
    License

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

    Description

    BackgroundEvidence for anorexia and bulimia in relation to the risk of ulcerative colitis (UC) is limited and inconsistent. The objective of this research was to utilize bi-directional, two-sample Mendelian randomization (MR) analysis to predict the causal association between anorexia nervosa and bulimia nervosa with UC.MethodsThe genome-wide association studies (GWAS) provided data for anorexia and bulimia from the UK Biobank, utilizing single-nucleotide polymorphisms (SNP) as instrumental variables. Additionally, genetic associations with UC were collected from various sources including the FinnGen Biobank, the UK Biobank and the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC). The main analytical approach utilized in this study was the inverse-variance-weighted (IVW) method. To evaluate horizontal pleiotropy, the researchers conducted MR-Egger regression and MR-PRESSO global test analyses. Additionally, heterogeneity was assessed using the Cochran’s Q test.ResultsThis study found a negative association between genetically predicted bulimia (OR = 0.943, 95% CI: 0.893–0.996; p = 0.034) and the risk of UC in the IIBDGC dataset, indicating that individuals with bulimia have approximately a 5.7% lower risk of developing UC. No association was observed in the other two datasets. Conversely, genetically predicted anorexia was not found to be causally associated with UC. In bi-directional Mendelian randomization, UC from the IIBDGC dataset was negatively associated with the risk of anorexia (OR = 0.877, 95% CI: 0.797–0.965; p = 0.007), suggesting that UC patients have approximately a 12.3% lower risk of developing anorexia, but not causally associated with bulimia.ConclusionGenetically predicted bulimia may have a negative association with the onset of UC, while genetically predicted anorexia does not show a causal relationship with the development of UC. Conversely, genetically predicted UC may have a negative association with the development of anorexia.

  19. Children and Young People Eating Disorder Collection Q2 2018/2019

    • gov.uk
    Updated Nov 8, 2018
    + more versions
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    NHS England (2018). Children and Young People Eating Disorder Collection Q2 2018/2019 [Dataset]. https://www.gov.uk/government/statistics/children-and-young-people-eating-disorder-collection-q2-20182019
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    Dataset updated
    Nov 8, 2018
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    NHS England
    Description

    The data collection is an interim aggregate experimental data collection which will run until data of sufficient quality are available from the Mental Health Services dataset (MHSDS). The dataset has been approved to run up until the end of 2016/17. The MHSDS will collect data that allows the calculation of CYP ED waiting times from April 2017, however there are likely to be issues around the quality of the initial data.

    Official statistics are produced impartially and free from political influence.

  20. f

    Predictors and long-term health outcomes of eating disorders

    • plos.figshare.com
    docx
    Updated Jun 4, 2023
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    Katie M. O’Brien; Denis R. Whelan; Dale P. Sandler; Janet E. Hall; Clarice R. Weinberg (2023). Predictors and long-term health outcomes of eating disorders [Dataset]. http://doi.org/10.1371/journal.pone.0181104
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    docxAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Katie M. O’Brien; Denis R. Whelan; Dale P. Sandler; Janet E. Hall; Clarice R. Weinberg
    License

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

    Description

    Anorexia and bulimia nervosa may have long-term effects on overall and reproductive health. We studied predictors of self-reported eating disorders and associations with later health events. We estimated odds ratios (ORs) for these associations in 47,759 participants from the Sister Study. Two percent (n = 967) of participants reported a history of an eating disorder. Risk factors included being non-Hispanic white, having well-educated parents, recent birth cohort (OR = 2.16, 95% confidence interval [CI]: 2.01–2.32 per decade), and having a sister with an eating disorder (OR = 3.68, CI: 1.92–7.02). As adults, women who had experienced eating disorders were more likely to smoke, to be underweight, to have had depression, to have had a later first birth, to have experienced bleeding or nausea during pregnancy, or to have had a miscarriage or induced abortion. In this descriptive analysis, we identified predictors of and possible long-term health consequences of eating disorders. Eating disorders may have become more common over time. Interventions should focus on prevention and mitigation of long-term adverse health effects.

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data.mo.gov (2025). Eating Disorders in Military Connected People [Dataset]. https://catalog.data.gov/dataset/eating-disorders-in-military-connected-people

Eating Disorders in Military Connected People

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Dataset updated
Feb 7, 2025
Dataset provided by
data.mo.gov
Description

Information about the types of eating disorders, some reasons why the military community are at risk, warning signs and how to get help. The Missouri Eating Disorders Council (MOEDC) created this document so support service members, veterans and their families.

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