Temporal changes in the nature of disability: US Army soldiers discharged with disability, 1981--2005 Nicole S. Bell, ScD, MPH Carolyn E. Schwartz, ScD.

Slides:



Advertisements
Similar presentations
Associations between Obesity and Depression by Race/Ethnicity and Education among Women: Results from the National Health and Nutrition Examination Survey,
Advertisements

Meet the Author Webcast Public Health Reports Meet the Author Webcast Socioeconomic Status and Risk of Diabetes-Related Morality in the United States With.
Syphilis and HIV screening initiatives in North Carolina jails Lynne A. Sampson PhD, MPH HIV/STD Update September 25, 2008.
Concurrent Tobacco Use: A Study of Socio-demographic Correlates Nasir Mushtaq, MPH Laura A Beebe, PhD University of Oklahoma Health Sciences Center.
Disabilities due to Injury in the U.S. Armed Forces Thomas Songer Ronald LaPorte.
Gender and the use of Veterans Health Administration homeless services programs among Iraq/Afghanistan Veterans Oni J. Blackstock, MD Yale RWJF Clinical.
Racial Differences in Quality of Care for Bipolar Disorder Center for Health Equity Research and Promotion Departments of Medicine and Psychiatry, University.
Cancer scanning and seeking is associated with knowledge, lifestyle choices and screening behavior Minsun Shim, MA Bridget Kelly, MPH Robert C. Hornik,
 Increasing age was associated with more time in sleep & leisure, & less in productive activity.  Females averaged less time in leisure & more time in.
* Includes Marine Corps Active Duty Demographic Profile Assigned Strength, Gender, Race, Marital, Education and Age Profile of Active Duty Force September.
Readmissions for Medicaid Patients: State-Level Benchmarks and Initiatives AHRQ Annual Conference September 10, 2012 David Kelley, M.D., M.P.A. Office.
Veterans Using and Uninsured Veterans Not Using VA Health Care Karin Nelson, MD, MSHS Gordon A. Starkebaum, MD Gayle E. Reiber, PhD, MPH VA Puget Sound.
Disease Burden, Utilization and Costs of Care Among Women Using Veterans Health Administration HERC Cyber Seminar May 25, 2005 Presented by Ciaran Phibbs.
Disparities for Latino Children in the Receipt of Timely Medical Care David Brousseau MD, MS, Jennifer Yauck MS, Raymond Hoffmann PhD, Ann Nattinger MD,
Shane Lloyd, MPH 2011, 1,2 Annie Gjelsvik, PhD, 1,2 Deborah N. Pearlman, PhD, 1,2 Carrie Bridges, MPH, 2 1 Brown University Alpert Medical School, 2 Rhode.
Addressing Racial/Ethnic Differences in ADHD Diagnosis and Treatment Among Medicaid-insured Youth in California Dinci Pennap, MPH, 1 Mehmet Burcu, MS,
The Role of Residential Segregation in Disparity Research: A Case Example of ADHD Diagnosis and Treatment Dinci Pennap, MPH, 1 Mehmet Burcu, MS, 1 Daniel.
Do veterans with spinal cord injury and diabetes have greater risk of macrovascular complications? Ranjana Banerjea, PhD 1, Usha Sambamoorthi, PhD 1,2,3,
Disability, Cigarette Smoking And Health-Related Quality Of Life: NYS Adult Tobacco Survey Harlan R. Juster, PhD Larry L. Steele, PhD Theresa M. Hinman,
Copyright restrictions may apply JAMA Pediatrics Journal Club Slides: Discharges to Home Health and Postacute Care Berry JG, Hall M, Dumas H, et al. Pediatric.
Hope M. Tiesman, PhD, MSPH Centers for Disease Control & Prevention NIOSH Division of Safety Research Division of Safety Research Gender Differences in.
SSDS Inc. The changing profile of disability in the U.S. Army: Nicole S. Bell, ScD, MPH Carolyn E. Schwartz, ScD Thomas C. Harford, PhD Ilyssa.
Gimeno D 1, Betancourt J 1, Tucker D 2, Cooper S 1, Alamgir A 1, Whitworth K 1, Gorrell N 2, Delclos G 1, Hammill T 3, Senchak A 4, Packer M 3, Sagiraju.
Adolescent Vaccination: Taking It to the Schools Immunization Site Preferences Among Primarily Hispanic Middle School Parents Amy B. Middleman, MD, MSEd,
Musculoskeletal Disorders among Dentists in Alexandria Prof. Dr. Samy A. Nassif PhD, PT Dean of Faculty of Physical Therapy - PUA Professor of Physical.
* Includes Marine Corps Active Duty Demographic Profile Assigned Strength, Gender, Race, Marital, Education and Age Profile of Active Duty Force September.
SSDS Inc. Intentional injury in the U.S. Army: Is a college education the answer? Nicole S. Bell, ScD, MPH Thomas C. Harford, PhD Social Sectors Development.
* Includes Marine Corps Active Duty Demographic Profile Assigned Strength, Gender, Race, Marital, Education and Age Profile of Active Duty Force September.
Then and Now Dr. B.D. Maxfield Office of Army Demographics Hispanics in the U.S. Army April 2004.
Then and Now Dr. B.D. Maxfield Office of Army Demographics Asians in the U.S. Army April 2004.
Program Application SANTA ANA COLLEGE Funded by a grant from the
Measures of the health status of Australians
Diabetes Care Among Medicaid Psychiatric Patients
Adverse Childhood Experiences, Traumatic Brain Injury, and Disruptive Behavior Disorders: Results From the 2011 National Survey of Children's Health Timothy.
Bruce B. Cohen, PhD Massachusetts Department of Public Health
Gender disparities in self-reported fear of an intimate partner
Prevalence of Self-Reported Diabetes and Exposure to Organochlorine Pesticides among Mexican-Americans: Hispanic Health and Nutrition Examination Survey.
Mesfin S. Mulatu, Ph.D., M.P.H. The MayaTech Corporation
Disparities in process and outcome measures among adults with persistent asthma David M. Mosen, PhD, MPH; Michael Schatz, MD, MS; Rachel Gold, PhD; Winston.
Age at First Measles-Mumps-Rubella Vaccination in Children with Autism and School-Matched Control Subjects William W. Thompson, PhD Presented at the.
Falls in a Working-Age Population: The U.S. Army Experience
UCSF Fresno Family and Community Medicine Dept.
Associations between Depression and Obesity: Findings from the National Health and Nutrition Examination Survey, Arlene Keddie, Ph.D. Assistant.
When Military Fitness Standards No Longer Apply
Aparna Jain, PhD, MPH Laura Reichenbach, PhD
Women returning from Operation Iraqi Freedom/Operation Enduring Freedom: Comparison of Healthcare Utilization among Women & Men Veterans Mona Duggal MD.
Lancet. 2017 Aug 5;390(10094): doi: /S (17) Epub 2017 May 25.
Clinical differences between freestanding and hospital-based emergency departments May 18, 2017 Ryan C. Burke, MPH.
Claire Dye, MSPH Dawn Upchurch, PhD
H azardous Drinking, Drinking Expectancies And Risky Sexual Behaviors In A Community Sample Of Adult Sexual Minority Women 33rd Annual Research.
Age at First Measles-Mumps-Rubella Vaccination in Children with Autism and School-matched Controls: A Population-Based Study in Metropolitan Atlanta F.
Cognitive Impacts of Ambient Air Pollution in the National Social Health and Aging Project (NSHAP) Cohort Lindsay A. Tallon MSPH1, Vivian C. Pun PhD1,
University of Massachusetts Medical School
Outcome Based Prescribing of Citalopram
FY03 Profile of Marine Corps Then and Now in the Marine Corps
ARMY DEMOGRAPHICS FY00 Soldier Demographics Family Demographics 1
STDs among Sexually Active Female College Students: Does Sexual Orientation or Gender of Sex Partner(s) Make a Difference? Lisa L. Lindley, DrPH, MPH,
Jessina C. McGregor, PhD; Miriam R. Elman, MPH; David T
FY04 Profile of Marine Corps Then and Now in the Marine Corps
M Javanbakht, S Guerry, LV Smith, P Kerndt
State of the Gap: By the Numbers
FY03 Profile of Air Force Then and Now in the Air Force
THE ESSENCE OF AMERICA'S ARMY”
Alzheimer’s Disease in New Mexico
ARMY DEMOGRAPHICS FY01 Soldier Demographics Family Demographics 1
FY04 Profile of Navy Then and Now in the Navy
FY04 Profile of Air Force Then and Now in the Air Force
Lucy Annang, PhD, MPH Diane M. Grimley, PhD
FY03 Profile of Navy Then and Now in the Navy
Recent Incidences and Trends of the Top Cancers in Northeast Tennessee Appalachian Region Adekunle Oke1, Sylvester Orimaye2, Ndukwe Kalu1, Dr. Faustine.
Presentation transcript:

Temporal changes in the nature of disability: US Army soldiers discharged with disability, 1981--2005 Nicole S. Bell, ScD, MPH Carolyn E. Schwartz, ScD Tom C. Harford, Ph.D. Ilyssa E. Hollander, MPH Paul J. Amoroso, MD Social Sectors Development Strategies, Inc.

Background Disability increasing at almost 10% per year among US Army soldiers. In FY 2005, the DoD paid disability-retired military service members $1.25 billion, $474 million of which was for disabled Army retirees Few studies published describe the nature of these disabilities, risk factors or disposition

Study Goals Document major types of disability discharges from 1981-2005 Describe the population at risk for different types of disability Document and describe the type of compensation (an indicator of severity) awarded for different types of disability as well as temporal changes in these associations

Total Army Injury and Health Outcomes Database (TAIHOD) Methods: The Data Total Army Injury and Health Outcomes Database (TAIHOD) US Army Physical Disability Agency DMDC (personnel files)

Methods – Study Population All Active Duty Army discharged with a permanent disability between 1981-2005 N = 108,119

VASRD System for classifying disability VASRD codes categorized into 15 body/organ systems Musculoskeletal Respiratory Neurological Cardiovascular Mental health Digestive Endocrine Hemic/lymphatic Ear/other sensory organs Eye Infectious/immune/nutritional Skin Gynecological Genitourinary Dental and oral

VASRD Dispositions (compensation awards) Eligibility dependent upon tenure in the Army and whether condition caused, or aggravated, by Army service Separation without benefits Separation with severance pay Retirement with permanent disability

Demographic Factors Gender Age Rank Time in service Race/ethnicity Marital status Education

Methods -- Analyses Frequency distributions Multiple Logistic Regression analysis Adjusted (standardized) and unadjusted rates Autoregressive Time Series Analysis

Results

Results 91% all disability captured in top 5 conditions Musculoskeletal (72%, n = 77,418) Neurological (6%, n = 6,896) Mental health (5%, n = 5,075) Cardiovascular (4%, n = 4429) Respiratory (4%, n = 4202)

Risk factors for different types of disability Musculoskeletal Respiratory Cardiovascular Neurological Mental Health OR (95% C.I.) Gender Male 0.86* (0.82-0.88) 0.82* (0.76-0.89) 1.01 (0.92-1.10) 1.24* (1.15-1.33) 1.31* (1.22-1.42) Female (referent) 1.00 Age <21 (referent) 21-25 1.12* (1.07-1.17) 1.03 (0.92-1.16) 0.57* (0.51-0.64) 1.06 (0.92-1.14) 1.05 (0.96-1.15) 26-30 (1.17-1.31) 0.80 *(0.70-0.92) 0.53* (0.46-0.61) 1.02 (0.92-1.13) 1.22* (1.09-1.37) 31-35 1.27* (1.19-1.36) 0.71* (0.61-0.84) 0.54* (0.46-0.64) (0.88-1.13) 1.54* (1.35-1.76) 36-40 (0.97-1.15) 0.80+ (0.66-0.97) 0.88 (0.74-1.06) (0.86-1.17) 2.09* (1.76-2.47) >40 0.76* (0.68-0.85) 0.91 (0.71-1.16) 1.55* (1.25-1.91) 0.98 (0.81-1.20) 2.37* (1.90-2.96)

Risk factors for different types of disability Musculoskeletal Respiratory Cardiovascular Neurological Mental Health OR (95% C.I.) Race/ethnicity White (referent) 1.00 Black 0.77* (0.75-0.80) 1.62* (1.51-1.74) 1.11* (1.03-1.19) 0.88* (0.83-0.94) 1.04 (0.97-1.12) Hispanic 1.01 (0.94-1.07) 1.21* (1.05-1.41) 0.61* (0.51-0.74) 0.91 (0.80-1.02) 0.99 (0.86-1.13) Other 0.97 (0.90-1.04) 1.07 (0.91-1.26) 0.79* (0.67-0.94) 0.92 (0.81-1.05) 1.24* (1.09-1.42) Marital status Single 0.82* (0.80-0.85) 0.86* (0.80-0.93) 1.05 (0.96-1.14) (0.94-1.06) 1.80* (1.68-1.93) Married (referent) Previously married 0.89 (0.76-1.05) 0.86 (0.73-1.01) 0.96 0.84-1.10) 1.26* (1.08-1.46)

Risk factors for different types of disability Musculoskeletal Respiratory Cardiovascular Neurological Mental Health OR (95% C.I.) Education <High school or equivalent (referent) 1.00 Some college 0.74* (0.70-0.79) 1.13 (0.99-1.29) 1.34* (1.21-1.50) 1.07 (0.96-1.19) 1.35* (1.20-1.52) >College degree 0.91* (0.85-0.98) 0.93 (0.77-1.11) 0.95 (0.82-1.11) 0.94 (0.82-1.08) 1.29* (1.12-1.48) Rank E1-E4 (referent) E5-E6 (0.87-0.95) 0.99 (0.90-1.09) 1.05 (0.94-1.17) 0.97 (0.90-1.05) 1.09 (0.99-1.21) E7-E9 0.50* (0.46-0.55) (0.87-1.28) 2.06* (1.76-2.43) 1.12 (0.96-1.31) 2.10* (1.72-2.56) Officer 0.52* (0.47-0.57) 1.23 (0.97-1.55) 1.58* (1.28-1.94) 1.44* (1.21-1.71) 1.70* (1.41-2.04) Time in service yrs 0.97* (0.97-0.98) 1.03* (1.01-1.04) 1.04* (1.03-1.05) 1.02* (1.01-1.03) 0.93* (0.91-0.94)

Results

Results Separation with Severance pay 77% Permanent Disability Retirement 15% Separation without benefits 8%

Results: Disability compensation varies by disability type Musculoskeletal disability cases were more likely to be discharged with severance pay Mental disorders and respiratory disorder disabilities more likely to be discharged with no benefits Cardiovascular disorders more likely to be retired with a permanent disability discharge Neurological disorders more likely to be either discharged with no benefits or retired with permanent disability discharge.

Conclusion Disability is increasing among active duty army and this is primarily driven by musculoskeletal disorders. This is by far the largest and fastest growing cause of disability Women, 21-25 year old, white, lower ranking enlisted, short tenured soldiers with high school degree or less at greatest risk for musculoskeletal Demographic shifts in Army population composition do not explain increasing musculoskeletal disability rates Separation with lump sum fastest growing compensation group & is associated with musculoskeletal disability

Recommendations More research needed to understand occupational exposures and health behavior risk factors for all disability, especially musculoskeletal disorder More research clarifying the clinical significance of musculoskeletal disability