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.

https://i.imgur.com/Vrs6apv.png" alt="">

Context

There is a well-documented phenomenon of increased suicide rates among United States military veterans. One recent analysis, published in 2016, found the suicide rate amongst veterans to be around 20 per day. The widespread nature of the problem has resulted in efforts by and pressure on the United States military services to combat and address mental health issues in and after service in the country's armed forces.

In 2013 News21 published a sequence of reports on the phenomenon, aggregating and using data provided by individual states to typify the nationwide pattern. This dataset is the underlying data used in that report, as collected by the News21 team.

Content

The data consists of six files, one for each year between 2005 and 2011. Each year's worth of data includes the general population of each US state, a count of suicides, a count of state veterans, and a count of veteran suicides.

Acknowledgements

This data was originally published by News21. It has been converted from an XLS to a CSV format for publication on Kaggle. The original data, visualizations, and stories can be found at the source.

Inspiration

What is the geospatial pattern of veterans in the United States? How much more vulnerable is the average veteran to suicide than the average citizen? Is the problem increasing or decreasing over time?

Version 2 (18 March 2025) includes a further 356 service itineraries. In addition, 41 entries from the previous version were updated or expanded. Currently the database covers a total of 1,858 Jewish soldiers, 421 wives and 83 children.

ORIGINAL VERSION 1 (18 September 2024)

With more than 1,500 individual entries, this is the inaugural instalment of my research database collated in the framework of the Project Forgotten Soldiers: Jewish Military Experience in the Habsburg Monarchy. This is an open access database, and everyone is welcome to use it according to their own scholarly and personal interests. In 1,189 cases we have official documented records confirming the soldiers were Jewish. In another 313 entries I was able to identify likely Jewish soldiers based on circumstantial evidence cross-referencing names and places of birth, with the presence of confirmed Jewish soldiers drafted into the same units as part of the same recruitment drive. This dataset further includes evidence for 156 spouses and 47 children. While military records do mentions these, their number suggests that the Habsburg army preferred to enlist unmarried men.

The database is structured in a similar way to an official individual entry in the Habsburg military records. These were arranged in tables, with soldiers listed by seniority. Name, place and land of birth are followed by age and religion. This latter rubric allows identifying the bulk of the Jewish soldiers. Also included in the record is marital status, profession (if any), number, names and ages of children (if any), followed by a short summary text of the soldier’s service itinerary. While not always consistent in detail, these texts mention enlistment dates, transfers between units, promotions, desertions, periods as prisoner of war and military awards (if any). I have taken the material from the personal records and added several additional parameters:

The soldiers are entered into the database according to their date of enlistment. This is followed by a colour-coded table showing their years of service. To see the meaning of the different colours employed, scroll to the legend at the end of the dataset.

Following the years of service, we see the date when the soldier left service (final year in service for incomplete service records). When known, the reason the soldier left the army is given (discharge/ death/ desertion etc).

Then come the three most important columns within the table: service record, primary sources and units. At first glance, these columns have only a few letters and numbers, but bring your mouse courser onto the relevant field marked with red triangles. An additional window will then open:

a. Service Record: Shows the entire service record of the soldier arranged by date. I use original German as it appears in the archival records. If you see spelling differences with modern German – they are there for a reason.

b. Primary Sources: Provides the information on all the archival records consulted to reconstruct the service itinerary. The number in the field denotes the number of the archival cartons consulted.

c. Units: Number of units in which a soldier serves. Bringing the cursor on to the field will open their list. Most Jewish soldiers served in the line infantry (IR) and the Military Transport Corps (MFWK or MFK). However, there were also Jewish sharpshooters, cavalrymen, gunners and even a few members of the nascent Austrian Navy.

The next two columns provide entries of the soldier’s conduct and medical condition, which in Habsburg military jargon was referred to rather callously as Defekten. I note the original medical diagnoses verbatim. When possible to identify, I note the modern medical term.

General database-wide parameters are then noted in the next part of the table. Among others, it provides information on enlistment type (conscript/ volunteer?), main branches of service (such as Infantry/ Cavalry/ Artillery), and roles within the military (such as non-commissioned officers/ drummers/ medics).

Concluding this part of the table are columns covering desertions, periods as prisoner of war and awards of the army cannon cross (for veterans of 1813-14) and other military awards.

The last column provides the original German outtake rubric as to how the soldier left service. In special cases, additional service notes are provides on the right.

How to use this dataset

This depends on what you are looking for. Firstly, download the dataset on to your computer via the link provided below. It is a simple Excel file which is easy to work with. If you wish to find out whether one of your ancestors served in the Habsburg army, use a simple keyword search. Please note that in our period there was no single accepted orthography meaning that some letters were used interchangeably (for instance B/P; D/T). There were also various patronymic suffices used in different parts of the monarchy (-witz in German/ -wicz in Polish/ -vits in Hungarian). Habsburg military clerks were mostly German speakers who often recorded the name phonetically. For instance, Jankel/ Jankl/ Jacob/ Jacobus all denote the same name. A Jewish teenager who identified himself as Moische when first reporting to duty, may have stayed so in the military records for decades, even if he was already a non-commissioned officer whose subordinates referred to as Herr Corporal.

If you study the history of concrete Jewish communities, use the keyword search and the filter option to find entries in the database where this locality is mentioned. Some places like Prague and Lublin could be identified effortlessly. In other cases (and see the above point on German-speaking clerks), place names were recorded phonetically. The military authority usually stuck to official Polish names in Galicia, and Hungarian in the Lands of the Crown of St. Stephan. In reality, a Jewish recruit from Transcarpathian Ruthenia could have his place of birth recorded in Hungarian, Romanian or Rusin. When I could not identify the place in question, I marked it with italics. Do you think you identified something I could not? Excellent! Then please write me, and I will correct the entry in the next instalment of this database.

I should stress that, currently, the database is not statistically representative. I have worked chronologically, meaning that there are disproportionally more entries for Jewish soldiers from the Turkish War, the first two Coalition Wars, and the Wars of 1805 and 1809. If you look at some of my other databases (for instance, that of the 1st Line Infantry Regiment 'Kaiser'), you will find least as many Jews who served in the wars of 1813-15. I will cover these in due course. This said, using the filter option of the Excel sheet, you can already make some individual queries. For instance, did Jewish grenadiers meet the minimal height requirement to be eligible for transfer into the elite infantry? (Hint: they did not!) If you are interested in the historical study of nutritional standards, compare the height of the soldiers with their year and place of birth. In my other project, I made calculations of the average height of Habsburg soldiers and I can already reveal that Jewish conscripts were, on average, several centimetres smaller than their non-Jewish comrades drafted in the same annual intake. Whatever stereotypes said, most Jews in the Habsburg Monarchy around 1800 were very poor and the sad fact of malnutrition as a child is reflected in their height as adults.

I should stress that this is a cumulative database. ZENODO has an excellent feature allowing updated versions to supersede earlier files while retaining the same DOI (Digital Object Identifier) and metadata. As my research progresses, I plan to upload new versions of this database bi-annually. This includes not only adding new entries, but also expanding and correcting existing ones. It might well be that the service record of a soldier covered up to 1806 will be brought to a later date, possibly even to his discharge from the army. If you have not found whom you are looking for, or if you want to work with larger samples for your research, visit this page again in a few months’ time. And if you do use this database for scholarly research (by all means, please do), do not forget to cite it as you would cite any other item in your bibliography! If you are a museum professional and you want to employ material from your database to illustrate your exhibitions, you are welcome, but please cite this resource for others to learn. Links to this database will also be appreciated.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES VETERAN STATUS - DP02 Universe - Civilian population 18 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

This dataset is designed for object detection of military aircraft. The dataset encompasses 74 different military aircraft types, with some types merged as one class along with their variants.

A-10, A-400M, AG-600, AH-64, AV-8B, An-124, An-22, An-225, An-72, B-1, B-2, B-21, B-52, Be-200, C-130, C-17, C-2, C-390, C-5, CH-47, CL-415, E-2, E-7, EF-2000, F-117, F-14, F-15, F-16, F-22, F-35, F-4, F/A-18, H-6, J-10, J-20, JAS-39, JF-17, JH-7, KC-135, KF-21, KJ-600, Ka-27, Ka-52, MQ-9, Mi-24, Mi-26, Mi-28, Mig-29, Mig-31, Mirage2000, P-3, RQ-4, Rafale, SR-71, Su-24, Su-25, Su-34, Su-57, TB-001, TB-2, Tornado, Tu-160, Tu-22M, Tu-95, U-2, UH-60, US-2, V-22, Vulcan, WZ-7, XB-70, Y-20, YF-23, Z-19.

This Dataset is in YOLO8 Format consist of Images and labels in jpg and txt files respectively.

The National Waterway Network is a comprehensive network database of the nation's navigable waterways. The data set covers the 48 contiguous states plus the District of Columbia, Hawaii, Alaska, Puerto Rico and water links between. The nominal scale of the dataset varies with the source material. The majority of the information is at 1:100,000 with larger scales used in harbor/bay/port areas and smaller scales used in open waters. Purpose: The National Waterway Network is a geographic database of navigable waterways in and around the United States, for analytical studies of waterway performance, for compiling commodity flow statistics, and for mapping purposes.

This data set illustrates the number of active troops by active service, reserve force, paramilitary, total troops, and active troops per thousand people across the globe. http://en.wikipedia.org/wiki/List_of_countries_by_number_of_active_troops August 27, 2007

This comprehensive report chronicles the history of women in the military and as Veterans, profiles the characteristics of women Veterans in 2009, illustrates how women Veterans in 2009 utilized some of the major benefits and services offered by the Department of Veterans Affairs (VA), and discusses the future of women Veterans in relation to VA. The goal of this report is to gain an understanding of who our women Veterans are, how their military service affects their post-military lives, and how they can be better served based on these insights.

Services and Support Programs for Military Service Members and Veterans, 2012-13 (PEQIS 19), is a study that is part of the Postsecondary Education Quick Information System (PEQIS) program; program data is available since 1997-98 at . PEQIS 19 (https://nces.ed.gov/peqis/) is a cross-sectional survey that collected information on the services and support programs available to students who are military service members and veterans at the institution. The study was conducted using self-administered paper-and-pencil questionnaires of a person at the postsecondary institution that is familiar with the institution programs for military service members and veterans. Key statistics produced from PEQIS 19 were services and support programs for military members and veterans.

Abstract copyright UK Data Service and data collection copyright owner.The European State Finance Database (ESFD) is an international collaborative research project for the collection of data in European fiscal history. There are no strict geographical or chronological boundaries to the collection, although data for this collection comprise the period between c.1200 to c.1815. The purpose of the ESFD was to establish a significant database of European financial and fiscal records. The data are drawn from the main extant sources of a number of European countries, as the evidence and the state of scholarship permit. The aim was to collect the data made available by scholars, whether drawing upon their published or unpublished archival research, or from other published material. The ESFD project at the University of Leicester serves also to assist scholars working with the data by providing statistical manipulations of data and high quality graphical outputs for publication. The broad aim of the project was to act as a facilitator for a general methodological and statistical advance in the area of European fiscal history, with data capture and the interpretation of data in key publications as the measurable indicators of that advance. The data were originally deposited at the UK Data Archive in SAS transport format and as ASCII files; however, data files in this new edition have been saved as tab delimited files. Furthermore, this new edition features documentation in the form of a single file containing essential data file metadata, source details and notes of interest for particular files. Main Topics: The files in this dataset relate to the data files held in the Leicester database in the directory /armies/.. The interest of this data in the longer term is to build up a run of statistics for the period of the so-called military revolution'. This was a decisive factor in the increase of state expenditure on war and the creation of the so-calledfiscal military state'. It may also be possible to build up, in the longer term, calculations of a relative state efficiency (expenditure in terms of army size), relative state mobilization (army size in terms of overall population levels) and an index of state expenditure in real terms (via the cost of payment of armies). File Information g103ded1. Size and cost of Danish and Norwegian armies, 1680-1765 g103ded2. Size and cost of Danish and Norwegian armies, 1771-1813 g103ded3. Contributions towards the Danish and Norwegian armies from provincial chambers, 1771-1813 g103ded4. Cost of the Danish and Norwegian army, 1814-1896 g103dem1. Total manpower and composition of the Danish and Norwegian armies, 1680-1813 g103dem2. Total cost of the Danish and Norwegian armies in cash, 1680-1810 g103ned1. Strength of the Dutch army, 1595-1793 g103nem1. Total manpower of the Danish/Norwegian and Dutch armies, 1680-1769? Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research. No sampling (total universe)

The Levada Center has been conducting omnibus surveys of the Russian population on a regular basis. This data collection includes questions about the attitude towards compulsory military conscription vs. a contract-based professional army plus a question about the capability of the Russian army - together with standard socio-demographic and political data about all respondents. This data collection contains the raw data from a total of 32 opinion polls conducted from 1997 to 2021.

The documentation of data collection documents the questions included in the dataset and provides information about the random-sample questionnaire-based nationally representative polls conducted as omnibus surveys. The original data file is in Russian, but the documentation lists all questions and answer options with an English translation.

Included in this data collection are the relevant questions from the Levada omnibus surveys copied into one file. The SPSS file (.sav) is the original files provided by the Levada Center. It has been exported into an Excel file. The content of the respective xlsx-file should be identical with the original sav-file. An overview of some selected results is included in the data collection as separate file.

In this version the technical description and the documentation of data collection have been corrected, as they included a reference to the wrong dataset. The actual dataset has not be changed.

The United States Military Installations database contains the boundaries and location information for important military installations in the United States and Puerto Rico. The database includes records for 405 military installations. Source: National Transportation Atlas Database URL: http://www.bts.gov/publications/national_transportation_atlas_database/2006/

Time series data for the statistic Armed_Forces_Percent_Of_Labor_Force and country France. Indicator Definition:Armed forces personnel are active duty military personnel, including paramilitary forces if the training, organization, equipment, and control suggest they may be used to support or replace regular military forces. Labor force comprises all people who meet the International Labour Organization's definition of the economically active population.The statistic "Armed Forces Percent Of Labor Force" stands at 1.00 percent as of 12/31/2020. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.0069 percentage points compared to the value the year prior.The 1 year change in percentage points is 0.0069.The 3 year change in percentage points is -0.008.The 5 year change in percentage points is -0.0087.The 10 year change in percentage points is -0.1446.The Serie's long term average value is 1.38 percent. It's latest available value, on 12/31/2020, is 0.381 percentage points lower, compared to it's long term average value.The Serie's change in percentage points from it's minimum value, on 12/31/2019, to it's latest available value, on 12/31/2020, is +0.0069.The Serie's change in percentage points from it's maximum value, on 12/31/1990, to it's latest available value, on 12/31/2020, is -1.12.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

The Department of Defense is keenly aware of the needs of military families whose members are serving overseas. The presentation outlines the department’s prevention programs and how they are geared to provide support to active duty and reserve component members and their children, youth, and families. Among the resources mentioned are Military OneSource, the Military and Family Life Consultant Program, and MilitaryHOMEFRONT.

Presenters: Karen Morgan and Tib Campise from the Department of Defense Family Advocacy Program

View Webinar (WMV - 58 MB)

Metadata-only record linking to the original dataset. Open original dataset below.

This infographic shows not only service members who died in battle, but all those who have served and died since their military service. It also highlights the memorial benefits VA provides to those who have served and died.

This dataset displays the number of active duty personnel and their location, by country. Included in these figures are the numbers for Army, Navy, Marine, and Air Force branches of the United States Military. Note: this data includes rounded figures for personnel involved in Operation Iraqi Freedom (OIF)and Operation Enduring Freedom (OEF). This data was collected from the department of Defense directly at: http://siadapp.dmdc.osd.mil/personnel/MILITARY/history/hst0706.pdf .

Time series data for the statistic Armed_Forces_Percent_Of_Labor_Force and country Canada. Indicator Definition:Armed forces personnel are active duty military personnel, including paramilitary forces if the training, organization, equipment, and control suggest they may be used to support or replace regular military forces. Labor force comprises all people who meet the International Labour Organization's definition of the economically active population.The statistic "Armed Forces Percent Of Labor Force" stands at 0.3511 percent as of 12/31/2020. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.005 percentage points compared to the value the year prior.The 1 year change in percentage points is 0.005.The 3 year change in percentage points is -0.0061.The 5 year change in percentage points is 0.0086.The 10 year change in percentage points is 0.0041.The Serie's long term average value is 0.41 percent. It's latest available value, on 12/31/2020, is 0.0589 percentage points lower, compared to it's long term average value.The Serie's change in percentage points from it's minimum value, on 12/31/2013, to it's latest available value, on 12/31/2020, is +0.015.The Serie's change in percentage points from it's maximum value, on 12/31/1990, to it's latest available value, on 12/31/2020, is -0.242.

The hydro polygon/arc coverages were created using TIGER/LINE 2000 shapefile data gathered from ESRI's Geography Network. The individual county hydrography line shapefiles were processed into Arc/Info coverages and then appended together to create complete state coverages. They were then edited to remove unwanted features, leaving a state-by-state database of both important and navigable water features. Attributes were added to denote navigable features and names. Also, an attribute was added to the polygons to denote which were water and which were land features. The state databases were then appended together to create a single, nationwide hydrography network containing named arcs and polygons. These features also contain a state FIPS. Because some of the hydro features are represented by lines instead of polygons, the complete hydro dataset consists of 2 shapefiles, one for lines and one for polygons. They must be used together to paint a complete picture.

This report presents findings from the 2015 National Survey on Drug Use and Health (NSDUH) with a focus on comparing estimates related to substance use and mental health for military family members (spouses and children) with general population estimates. The numbers of military family members included in the 2015 NSDUH were relatively small. As a consequence, the report focuses on wives aged 18 to 49 and children aged 12 to 17. In the general area of substance use, the report includes estimates for past year use of any illicit substances (marijuana, cocaine in any form including crack, heroin, hallucinogens, inhalants, and methamphetamine and misuse of four categories of prescription drugs -- pain relievers, tranquilizers, stimulants and sedatives), past year cigarette use, past year alcohol use (both any use and binge use), and past year treatment for substance use, including alcohol use. In the general area of mental health, the report includes estimates for any mental illness (AMI) in the past year for wives. For both wives and children, the report includes estimates for past year major depressive episode (MDE) and mental health service use. For children, estimates of mental health service are reported by general treatment setting (e.g., mental health, educational, medical). As additional years of data become available, it will be possible in future reports to include both male and female spouses and to make more detailed comparisons -- for example for more specific types of illicit substances used and for treatment received by setting, by race/ethnicity and for spouses, by employment and educational background.