Disability and Rehabilitation

ISSN: 0963-8288 (Print) 1464-5165 (Online) Journal homepage: http://www.tandfonline.com/loi/idre20

Disability correlates in Canadian Armed Forces Regular Force Veterans James M. Thompson, Tina Pranger, Jill Sweet, Linda VanTil, Mary Ann McColl, Markus Besemann, Colleen Shubaly & David Pedlar To cite this article: James M. Thompson, Tina Pranger, Jill Sweet, Linda VanTil, Mary Ann McColl, Markus Besemann, Colleen Shubaly & David Pedlar (2015) Disability correlates in Canadian Armed Forces Regular Force Veterans, Disability and Rehabilitation, 37:10, 884-891, DOI: 10.3109/09638288.2014.947441 To link to this article: http://dx.doi.org/10.3109/09638288.2014.947441

Published online: 09 Sep 2014.

Submit your article to this journal

Article views: 55

View related articles

View Crossmark data

Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=idre20 Download by: [University of Pennsylvania]

Date: 06 November 2015, At: 03:40

http://informahealthcare.com/dre ISSN 0963-8288 print/ISSN 1464-5165 online Disabil Rehabil, 2015; 37(10): 884–891 ! 2014 Informa UK Ltd. DOI: 10.3109/09638288.2014.947441

RESEARCH PAPER

Disability correlates in Canadian Armed Forces Regular Force Veterans James M. Thompson1,2, Tina Pranger1,3, Jill Sweet1, Linda VanTil1, Mary Ann McColl2,4, Markus Besemann5, Colleen Shubaly6, and David Pedlar1

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

1

Veterans Affairs Canada, Charlottetown, Prince Edward Island, Canada, 2Department of Public Health Sciences, Queen’s University, Kinston, Ontario, Canada, 3Faculty of Health Sciences, School of Occupational Therapy, Dalhousie University, Halifax, NS, Canada, 4School of Rehabilitation Therapy, Queen’s University, Kinston, Ontario, Canada, 5Rehabilitation Medicine, Canadian Forces Health Services Group, Ottawa, Canada, and 6 Veterans Affairs Canada, Halifax, NS, Canada Abstract

Keywords

Purpose: This study was undertaken to inform disability mitigation for military veterans by identifying personal, environmental, and health factors associated with activity limitations. Method: A sample of 3154 Canadian Armed Forces Regular Force Veterans who were released during 1998–2007 participated in the 2010 Survey on Transition to Civilian Life. Associations between personal and environmental factors, health conditions and activity limitations were explored using ordinal logistic regression. Results: The prevalence of activity reduction in life domains was higher than the Canadian general population (49% versus 21%), as was needing assistance with at least one activity of daily living (17% versus 5%). Prior to adjusting for health conditions, disability odds were elevated for increased age, females, non-degree post-secondary graduation, low income, junior non-commissioned members, deployment, low social support, low mastery, high life stress, and weak sense of community belonging. Reduced odds were found for private/recruit ranks. Disability odds were highest for chronic pain (10.9), any mental health condition (2.7), and musculoskeletal conditions (2.6), and there was a synergistic additive effect of physical and mental health co-occurrence. Conclusions: Disability, measured as activity limitation, was associated with a range of personal and environmental factors and health conditions, indicating multifactorial and multidisciplinary approaches to disability mitigation.

Activity limitations, disability, mental health, physical health, veterans History Received 10 January 2014 Revised 15 July 2014 Accepted 18 July 2014 Published online 9 September 2014

ä Implications for Rehabilitation 

  

Consider activity limitations in all veterans with health problems, particularly women or veterans with current or lost marital relationship; post-secondary non-degree education; low income; junior non-commissioned member rank; high life stress; chronically painful conditions; musculoskeletal disorders; or mental health conditions. Comorbidity indicates the need for coordinated multidisciplinary care, especially between physical and mental health care services. Since disability is associated with psychosocial factors, service providers should be aware of the broad range of services and interventions available to mitigate disability in veterans. Do not be led astray by the absence of combat deployment history since disability occurs in former military personnel who have not deployed.

Introduction A key function of veterans’ administrations is to compensate for and mitigate disability associated with service-related health conditions in transition to civilian life [1]. In the 1990s, anecdotal evidence and studies of the minority of veterans participating in Veterans Affairs Canada (VAC) programs demonstrated a clear need for enhanced transition support for modern-day Canadian Armed Forces (CAF) veterans who were experiencing disability. This led to significant enhancement of services provided by VAC,

Address for correspondence: Dr. Jim Thompson, Veterans Affairs Canada, PO Box 7700, Room 406 DJM Bldg, 161 Grafton Street, Charlottetown, PE, Canada C1A 8M9. E-mail: research-recherche@ vac-acc.gc.ca

CAF, and the Department of National Defence (DND). CAF veterans receive health care and rehabilitation services from provincial and private health care providers; however, little has been published about correlates of disability in CAF veterans on a population basis to aid them in their work. In the ecological view of the World Health Organization’s International Classification of Health and Functioning (ICF) framework, disability is an umbrella term for impairments in body functions and structures, activity limitations, and participation restrictions owing to interactions of the person with their environment [1–7]. Health-related activity limitation, the measure of disability used in this study, occurs when a person is limited in the activities they can perform as a result of having impairments owing to a physical or mental health problem. Activity limitations are associated with restriction in employment [9,10]; a broad

Disability correlates in CAF Veterans

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

DOI: 10.3109/09638288.2014.947441

range of adverse health and well-being factors including physical and mental health problems, quality of life, social support, and stress [5,6,8,11–20]; and, in US veterans, suicide [21]. Activity limitations play a role in the assessment for veterans’ disability benefits [1]. There are no published reports of disability prevalence and associated factors for Canadian veterans. There is evidence that activity limitations, poorer physical health, and associated chronic conditions such as arthritis are more common in US veterans than non-veterans [19,21–23]. A contradictory study found that activity limitations were not more prevalent in US veterans than non-veterans, but were more prevalent in veterans with war service than those without [24]. It is unclear whether these associations are related to military service or non-service factors [25,26] and most of the studies did not include recent-era veterans. Associations of disability and psychosocial factors are well established, but there have been few studies that considered multiple factors simultaneously in veterans [12]. Owing to cultural differences, it cannot be assumed that findings in other nations apply to Canadian veterans. The 2010 Survey on Transition to Civilian Life (STCL) was the first comprehensive national study of CAF veterans living in the Canadian general population [27–29]. The STCL included Regular Force Veterans (at least 1 d of service) who had released in 1998–2007 and were surveyed in 2010. The mean age of the veterans was 44 years (range 20–67, standard deviation [SD] 11.2) and they enrolled in the military from the 1960s to the 2000s. They had varied experiences in training, domestic disaster response, international missions primarily in Cyprus, the Balkans, and the 1990–1991 Persian Gulf War, and 7% served in Afghanistan after 2000. This paper adds to the understanding of disability in modern CAF veterans by exploring associations of health-related activity limitations with various factors. The goal was to inform disability mitigation through both individual rehabilitation and populationlevel policy and programming. The objectives were to estimate the prevalence of disability measured as activity limitations and to assess the relative roles of personal and environmental factors, individual chronic health conditions and comorbidity.

Methods Sample The STCL was a cross-sectional computer-assisted telephone interview survey and data linkage study of health, disability, and determinants of health of CAF veterans [27–29]. The survey questionnaire was designed by VAC and DND and administered by Statistics Canada. The STCL sampled 4721 of 32 015 former CAF Regular Force personnel who released from service during January 1998 to December 2007; had not re-enrolled in the CAF; and were not living in institutions, the northern Territories or outside of Canada. A random stratified design was used to oversample those receiving services from VAC (VAC clients). Ethical approval was provided by Statistics Canada. Of the 4721 former CAF Regular Force personnel sampled, the response rate was 71%: 84% for VAC clients and 59% for nonclients. Of these, 3154 (94%) agreed to share their data with VAC and DND. Sample sizes for the adjusted multivariable models varied 2647–2866 owing to missing data; however, Chi-squared testing and frequency distribution inspection of this did not create significant bias. The veterans were surveyed 2–12 years (mean 6.8, SD 3.0 years) after release and a third (34%) were VAC clients. The majority (80%) was in the labor force in the week prior to the survey (74% employed, 6% unemployed), 3% were permanently unable to work and 18% were not in the labour force. Additional population characteristics are shown in Table 1.

885

Dependent variable Health-related activity limitation Disability was assessed in two ways (Table 1) using questions borrowed from the Canadian Community Health Survey (CCHS): (1) whether a long-term physical or mental condition or health problem reduced the amount or kind of activity at home, school, work, or other sometimes or often (some disability) and (2) need for assistance with at least one basic or instrumental activity of daily living (high disability). These measures were combined into a 3-category ordinal-dependent variable reflecting degree of disability: no, some, and high. Most with high disability also had some disability (98%). Independent variables We grouped independent variables into personal and environmental factors and health conditions, consistent with the core concepts of the ICF framework [2,29]. Personal and environmental factors In the ICF framework, personal factors include age, gender, education and coping; and environmental factors include family, work, and cultural factors (2). We identified personal and environmental covariates of interest that were available in the STCL dataset by exploring unadjusted bivariable associations with Chi-squared tests [29], considering collinearity and potential causal relationships with disability [5,9,11,16,20,25,30–34]. Bivariable correlations were assessed using SPSS (SPSS Inc., Chicago, IL). Age, sex, and military rank at release were ascertained from the DND human resources database. Other variables were self-reported using questions borrowed from Statistics Canada surveys. Income adequacy was measured using quintiles of the ratio of household income to Statistics Canada’s 2009 Low Income Measure for number of people [35]. Respondents were asked if they had deployed outside Canada for 30 d or more for combat, peacekeeping, humanitarian aid, or nonroutine sea deployments, excluding training. Social support was a summary of 21 questions ranging 19–95 low to high and mastery was a summary of seven questions ranging 0–28 low to high [27]. Ranks were grouped into senior officer (Major, Colonel, Captain Navy, General, Commodore, and Admiral), junior officer and cadet (Officer Cadet, Naval Cadet, Lieutenant, and Captain), senior non-commissioned member ([NCM] Sergeant, Warrant Officer, Master Warrant Officer, Chief Warrant Officer, Petty Officer, and Chief Petty Officer), junior NCM (Corporal, Master Corporal, Leading, and Master Seaman) and Private and Recruit. Health conditions Using questions borrowed from the CCHS, respondents were asked whether they had chronic health conditions diagnosed by a health professional that had lasted or were expected to last 6 months or more. Physical health conditions (PHC) were grouped into musculoskeletal conditions (arthritis or back problems excluding fibromyalgia); cardiovascular conditions (high blood pressure, heart condition, or effects of stroke); respiratory conditions (asthma, emphysema, chronic bronchitis, or chronic obstructive pulmonary disease); gastrointestinal conditions (intestinal or stomach ulcers, or bowel disorder such as Crohn’s Disease, ulcerative colitis, irritable bowel syndrome, or bowel incontinence); hearing problem; obesity; diabetes; cancer and chronic pain or discomfort. Mental health conditions (MHC) were assessed using four questions about mood disorder, anxiety disorder, anxiety or depression, and posttraumatic stress disorder that were not mutually exclusive, so they were combined into any MHC.

886

J. M. Thompson et al.

Disabil Rehabil, 2015; 37(10): 884–891

Table 1. Prevalence of activity limitations compared to the Canadian general population. Veteransa Indicator

Sample size and population estimate (95% CI)

Canadian populationb Population estimate (95% CI)

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

A long-term physical condition or mental condition or health problem reduced amount or the kind of activity (sometimes or often) At home 1814 43% (41–44%) 16% (11–21%) At school in those at school 71 22% (17–28%) –d At work in those working 944 35% (33–37%) 13% (7–19%) Leisure and other activities 1820 44% (42–46%) 16% (11–21%) Some disability: reduction of activity in the life domains of home, work, school, and other activities: Often 1110 24% (22–25%) Sometimes 888 25% (24–27%) Never 1138 51% (49–52%)

9% (6–12%)c 13% (9–17%)c 78% (71–85%)

Because of any physical or mental condition or health problem, needed the help of another person with: Preparing meals 238 5% (4–5%) Getting to appointments and running errands 419 8% (8–9%) Doing everyday housework 714 14% (13–15%) Personal care such as washing, dressing, eating, or taking medication 186 4% (3–4%) Moving about inside house 136 3% (2–3%) Looking after personal finances 214 5% (4–5%)

–d 3% (1–5%)c 4% (2–6%)c –d –d –d

High disability: needs help with at least one activity of daily living (ADL) Yes No

835 2307

17% (16–18%) 83% (82–84%)

5% (3–7%) 95% (90–100%)

CI, confidence interval. a Survey on Transition to Civilian Life 2010. b Canadian Community Health Survey 2008, age, and sex adjusted to the study population. c Estimate considered marginal quality by Statistics Canada guidelines (a coefficient of variation 11.6–33.3%). d Estimate does not meet Statistics Canada’s quality standards (coefficient of variation433.3%).

Statistical analysis Weighted population estimates and their associated 95% confidence intervals (CI) are expressed as percentages calculated from individual respondent weights provided by Statistics Canada to account for sampling stratification by VAC client status, age, sex, and non-response. General population prevalence rates and confidence intervals were calculated from the 2007 to 2008 CCHS public use microdata file after age- and sex-adjusting to the STCL population [36]. Disability odds ratios (OR) were calculated by ordinal logistic regression using Stata version 11.1 and weighted data. Stata conducted tests of proportionality for no disability versus any disability and for no or some disability versus high disability at the p ¼ 0.01 level, calculating two different ORs if the proportionality test was not met. Analyses were conducted on respondents with complete data. Taylor series linearization was used to calculate confidence intervals. Adjusted odds ratios (AOR) were calculated using three multivariable models adjusted for all the personal and environmental variables: one without health conditions (Table 2), one with the individual health conditions (Table 3), and an additive comorbidity model (Table 4). The synergy index was calculated as {AORMHC+PHC1}/{[AORMHC– 1] + [AORPHC1]} where a result of 1 indicates no interaction between physical and mental health conditions, less than 1 indicates a subadditive effect, and greater than 1 indicates an additive synergistic effect [37]. The proportion of disability odds attributable to the interaction was calculated as {AORMHC+PHCAORMHC–AORPHC + 1}/AORMHC+PHC.

Results The prevalence of some disability was about double the Canadian general population adjusting for age and sex (49% versus 21%) and the prevalence of a high degree of disability was about triple (17% versus 5%) (Table 1).

In bivariable regression analysis, all the personal and environmental covariates, health conditions, and comorbidity categories had significantly elevated unadjusted odds of disability (Table 2). In the first multivariable model (Table 2), prior to adjusting for health conditions, at least one category of every personal and environmental factor had elevated odds of disability. Junior NCM was the only rank group with elevated odds of disability, was the largest rank category at 30% of the population, and had the highest rate of release owing to health problems limiting CAF employability (54%). AOR proportionality was met for all covariates except mastery, where the AOR for some or high disability relative to none (AOR ¼ 0.93; 0.91–0.95; p50.001) was higher than high disability relative to none or some; and female sex, where that AOR was not significant (AOR ¼ 1.27; 0.93–1.72; p ¼ 0.131). In the second model (Table 3), adjusted for all the health conditions at once, the personal and environmental factors remained significant except age, education, rank, and deployment. Among individual conditions, chronic pain/discomfort had the strongest association with disability (AOR ¼ 10.9) followed by any mental health condition (AOR ¼ 2.7) and musculoskeletal conditions (AOR ¼ 2.6). Gastrointestinal, cardiovascular and respiratory conditions, and hearing problems had weaker independent associations with disability. AOR proportionality was met for all conditions except hearing problems, where the AOR for no or some disability relative to high disability (AOR ¼ 2.37; 1.763.19; p50.001) was higher than for high disability relative to none or some. In the third model (Table 4), adjusted for comorbidity, only deployment was no longer significant. Co-occurrence of physical conditions in those with mental conditions was very high at 95%, while 28% with physical conditions had mental conditions. Disability was predominant in those with higher comorbidity measured as both the number of conditions and the co-occurrence

Disability correlates in CAF Veterans

DOI: 10.3109/09638288.2014.947441

887

Table 2. Regression results for personal and environmental factors prior to adjusting for health conditions. Degree of activity limitation

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

Variables Total Sex Male Female Age, mean (SD) Marital status Single/never married Widowed/separated/divorced Married/common law Highest attained education University degree Post-secondary other High school Less than high school Income adequacy quintiles 1 – highest 2 3 4 5 – lowest Rank Senior Officer Junior Officer and Cadet Senior NCM Junior NCM Private and recruit Deployed No Yes Social support, mean (SD) Mastery, mean (SD) Life stress Not at all Not very A bit Quite a bit Extremely Sense of community belonging Very strong Somewhat strong Somewhat weak Weak

No disability, N, Wt%

Some disability, N, Wt%

High disability, N, Wt%

Total, N, Wt%

Unadjusted odds ratioa

Adjusted odds ratiob

–

–

1124, 50.2

1179, 33.3

818, 16.5

3121, 100

1003, 89.3 121, 10.7 43.2 (12.1)

1066, 89.2 113, 10.8 47.4 (9.1)

981, 82.5 137, 17.5 47.1 (7.3)

2750, 88.1 371, 11.9 45.8 (10.1)

1.00 1.76*** 1.03***

1.00 2.21*** (1.60–3.05) 1.03*** (1.02–1.04)

197, 21.2 72, 5.6 854, 73.3

112, 10.7 146, 12.1 921, 77.3

52, 7.1 117, 13.5 649, 79.4

361, 15.3 335, 9.0 2424, 75.6

1.00 4.42*** 2.39***

1.00 1.54* (1.05–2.27) 1.49* (1.09–2.04)

235, 21.0 360, 33.7 451, 38.9 78, 6.4

1545, 14.8 434, 38.4 514, 40.8 75, 6.0

51, 6.7 323, 39.3 366, 44.5 77 9,56

440, 16.6 1117, 36.2 1331, 40.5 230, 6.8

1.00 3.05*** 3.10*** 4.21***

1.00 1.71** (1.21–2.41) 1.29 (0.91–1.83) 0.95 (0.60–1.50)

22.0 21.4 19.1 19.1 18.5

1.00 1.49** 1.44** 2.60*** 3.55***

1.00 1.28 (0.99–1.67) 1.07 (0.82–1.41) 1.33* (1.00–1.78) 1.73*** (1.28–2.33)

281, 2258, 214, 191, 154,

25.8 21.2 19.3 18.0 15.7

216, 250, 244, 218, 195,

21.2 23.5 20.4 18.0 16.8

85, 128, 120, 193, 251,

11.6 17.6 15.8 24.7 30.3

582, 606, 578, 578, 600,

119, 8.9 170, 16.9 310, 22.7 247, 19.8 278, 31.8

109, 9.4 90, 9.4 432, 32.9 451, 36.6 97, 11.7

23, 2.9 38, 5.2 291, 35.7 420, 48.9 46, 7.3

251, 8.1 298, 12.5 1033, 28.2 1118, 30.2 421, 21.1

1.00 1.16 4.16*** 5.74*** 0.96

1.00 0.90 (0.59–1.38) 1.27 (0.86–1.88) 1.70* (1.12–2.56) 0.56* (0.33–0.97)

508, 52.1 600, 47.9 82.4 (12.9) 21.5 (12.9)

297, 31.2 863, 68.8 76.5 (16.6) 19.9 (16.6)

168, 23.1 633, 76.9 68.7 (18.5) 15.3 (18.5)

973, 40.3 2096, 59.7 78.2 (16.0) 20.0 (16.0)

1.00 2.70*** 0.96*** 0.88***

1.00 1.39** (1.14–1.70) 0.99*** (0.98–0.99) 0.88*** (0.86–0.90)

184, 15.7 337, 29.9 459, 41.4 131, 11.9 13, 1.1

119, 9.9 270, 23.4 522, 43.9 232, 19.6 34, 3.2

44, 6.3 88, 11.3 335, 39.6 255, 32.2 93, 10.6

347, 12.2 695, 24.7 1316, 42.0 618, 17.8 140, 3.4

1.00 1.18, 0.79 1.85*** 3.85*** 10.17***

1.00 1.10 (0.79–1.52) 1.59** (1.16–2.18) 2.43*** (1.70–3.46) 3.70*** (2.19–6.26)

134, 12.2 615, 54.2 293, 26.7 69, 6.9

104, 7.9 546, 48.1 351, 30.5 160, 13.5

49, 7.2 269, 34.7 262, 30.8 230, 27.3

287, 1430, 906, 459,

1.00 1.05 1.78*** 4.35***

1.00 0.98 (0.73–1.32) 1.19 (0.87–1.64) 1.74** (1.21–2.51)

10.0 48.9 28.7 12.4

N, unweighted sample sizes; Wt%, weighted percent of those with the characteristic except where mean and standard deviation are shown. a Individual unadjusted regressions. b Single multivariable ordinal logistic model; sample size ¼ 2866. *p50.05, **p50.01, ***p50.001.

of physical and mental health conditions: of those with some limitations 65% had 3 or more physical conditions and of those with high limitations 76% had 3 or more physical conditions (Figure 1). In the comorbidity model, the synergy index was 2.3 (95% CI 1.6–3.3), indicating a synergistic additive effect of the co-occurrence of physical and mental health conditions. Although only 22.8% had co-occurrence of physical and mental conditions, the proportion of disability odds attributable to this comorbidity was 55% (39–71%).

measured as activity limitations. Multiple personal and environmental factors and health conditions were associated with disability independently of other factors. The predominant associated health conditions were chronic pain or discomfort, musculoskeletal conditions, and mental health conditions. The majority of activity limitation was attributable to the co-occurrence of physical and mental health conditions. Deployment was associated with disability before but not after adjusting for chronic health conditions.

Discussion

Prevalence of activity limitations

This is the first study of activity limitations in Canadian veterans living in the general population. While the great majority of these CAF Regular Force Veterans who released from service in 1998– 2007 were participating in the civilian labour force and not retired, they had significant prevalence rates of disability

In this first report of disability prevalence in Canadian veterans, both types of activity limitations were significantly more prevalent than in the general Canadian population, adjusting for age and sex. There have been mixed findings in cross-sectional studies of US veterans, where health-related

888

J. M. Thompson et al.

Disabil Rehabil, 2015; 37(10): 884–891

Table 3. Multivariable regression model adjusted for chronic health conditions. Degree of activity limitation Chronic health conditions

Some disability, N, Wt%

High disability, N, Wt%

Total, N, Wt%

Unadjusted odds ratioa

435, 35.5 104, 8.0 291, 23.4 216, 14.5 10, 0.8 50, 4.1 184, 13.8 46, 4.3 52, 3.7 264, 22.5

1095, 92.0 376, 28.6 845, 69.2 517, 39.2 17, 1.3 168, 14.0 324, 26.5 111, 10.6 73, 5.6 386, 32.5

803, 97.5 526, 61.7 715, 85.3 399, 45.7 16, 2.2 227, 26.7 276, 33.5 118, 14.2 88, 11.2 315, 38.1

2333, 64.5 1006, 23.7 1848, 48.9 1132, 27.9 43, 1.2 445, 11.1 784, 21.2 275, 8.0 213, 5.5 965, 28.4

27.33*** 7.9*** 9.30*** 2.61*** 2.20* 4.57*** 2.40*** 2.61*** 2.39*** 1.77***

Adjusted odds ratiob 10.90*** 2.65*** 2.61*** 1.30* 1.80 1.65** 1.48** 1.49** 1.17 1.15

(7.93–14.98) (2.09–3.36) (2.08–3.26) (1.01–1.67) (0.67–4.87) (1.23–2.22) (1.17–1.89) (1.11–1.99) (0.76–1.82) (0.93–1.41)

N, unweighted sample sizes; Wt%, weighted percent of those with the characteristic. a Individual unadjusted regressions, reference category is without the condition. b Single multivariable ordinal logistic regression model adjusted for the personal and environmental factors; reference category is without the condition; sample size ¼ 2647. *p50.05, **p50.01, ***p50.001. Table 4. Multivariable regression model adjusted for comorbidity of physical and mental health conditions. Degree of activity limitation Variables Neither PHC nor MHC MHC only PHC only Both PHC and MHC

No disability, N, Wt%

Some disability, N, Wt%

High disability, N, Wt%

Total, N, Wt%

Unadjusted odds ratioa

Adjusted odds ratiob

311, 32.5 17, 1.7 684, 59.3 87, 6.5

7, 1.1 8, 0.7 782, 70.5 367, 27.8

1, 0.4 1, 0.2 287, 37.9 524, 61.6

319, 16.7 26, 1.1 1753, 59.45 978, 22.8

1.00 10.7*** 38.3*** 249.1***

1.00 8.98*** (2.63–30.64) 24.7*** (11.8–51.7) 73.40*** (34.3–156.8)

PHC, physical health conditions; MHC, mental health conditions. N, unweighted sample sizes; Wt%, weighted percent of those with the characteristic. a Individual unadjusted regressions. b Single multivariable ordinal logistic regression model adjusted for the personal and environmental factors; sample size ¼ 2826. ***p50.001.

20%

Figure 1. Disability prevalence (degree of activity limitations) by comorbidity category. PHC, physical health condition; MHC, mental health condition.

No Disability

Some Disability

High Disability

15% Disability Prevalence

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

Pain or discomfort Any mental health condition Musculoskeletal condition Hearing problem Cancer Gastrointestinal condition Cardiovascular condition Respiratory condition Diabetes Obesity

No disability, N, Wt%

10%

5%

0% 0 PHC

1 PHC

2 PHCs

3+ PHCs

-

0 PHC

No MHC

1 PHC

2 PHCs

3+ PHCs

With MHC

PHC = Physical health condition, MHC = mental health condition.

activity limitations and work limitations were more common than non-veterans in some studies but not all [21–23,38]. It is difficult to compare studies owing to differing populations and methodologies. In a longitudinal study, Second World War, Korean War, and Vietnam War US veterans more often had chronic physical and mental conditions but less often had

ADL limitations compared with non-veterans when adjusting for a variety of potential confounders [24]. Veterans with service in those wars had more ADL limitations than veterans without. These findings point to the importance of policies and services for preventing and mitigating disability in military veterans.

Disability correlates in CAF Veterans

DOI: 10.3109/09638288.2014.947441

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

Chronic health conditions The increased prevalence of disability in these veterans probably was due in large part to the significant prevalence of pain and discomfort (65%) and the higher prevalence rates compared with the general Canadian population of back problems (40% versus 21%) and arthritis (23% versus 11%) after adjusting for age and sex [28]. These findings are consistent with civilian and military studies [8,32,33,39]. Activity limitations have been associated with high occupational physical demand in civilian studies [8]. In US military populations, musculoskeletal conditions and disability in serving personnel were associated with military occupations and female sex; veterans were more likely than nonveterans to have arthritis after adjusting for sociodemographics and to have activity limitations after adjusting for age and sex; veterans with arthritis were more likely to have activity limitations than those without; and back conditions had the highest cumulative risk of disability [11,12,22,37,40]. These findings reinforce the importance of identifying and managing painful physical conditions in disability mitigation; however, it is important to consider the wide range of other physical conditions that also contribute. Hearing problems were prevalent (28%) in these relatively young veterans and were significantly associated with disability after adjusting for other health conditions. Although hearing loss has been associated with ADL limitations in prior research, we found no other studies that assessed hearing problems and our measure of some disability or that adjusted for the presence of comorbid conditions. Noise-induced hearing loss and tinnitus are well-recognized risks of military service and are the most common diagnoses in VAC disability entitlement after musculoskeletal disorders [41]. This finding reinforces the importance of assessing hearing in veterans with disability, and asking about disability in those with hearing problems. Comorbidity and chronic mental health conditions The findings of this study demonstrate the importance of considering comorbidity in rehabilitation; identifying and managing both physical and mental health in persons experiencing disability; and encouraging collaboration and communication among multidisciplinary providers. In this study, disability was concentrated in veterans with multiple physical conditions, consistent with prior evidence of the importance of multimorbidity [39,42]. However, this study also found that mental conditions were associated with disability independently of physical conditions, disability predominated in those with co-occurring physical and mental health conditions, and there was a synergistic additive effect of the co-occurrence of physical and mental conditions. Although the importance of physical and mental health co-occurrence is well established from studies in civilian Canadian and international populations [9,13–16,20,30,39,43], this study extends the finding to military veterans. In rehabilitation, it is important to understand how mental health relates to disability. A high degree of disability was predominant in those with co-occurring physical and mental health conditions while some disability was predominant in those who only had physical health conditions. This is consistent with prior evidence that physical and mental health conditions appear to act differently to produce disability [15,30]. Mental conditions can arise secondary to chronic physical health problems and related disability [44,45]. However, mental conditions can also directly confer disability through distinct emotional, cognitive, and behavioral mechanisms. While it is well documented that mental health problems significantly contribute to disability

889

[14,17,20,32,42,43,46], the role of mental conditions and directions of causality between both types have been less clear owing to the use of variable measures, cross-sectional methodologies, and the high comorbidity of physical conditions in those with mental conditions. Personal and environmental factors The findings in this study support the importance of addressing self-efficacy and providing social support to mitigate disability [33]. All the personal and environmental factors were associated with health-related activity limitations in the multivariable model prior to adjusting for health conditions. The association was strongest for increasing degrees of life stress. This cross-sectional study does not shed light on the sources of life stress or direction of causality, but it is noteworthy that related personal factors (mastery, social support, and sense of community belonging) also remained significant after adjusting for health conditions, similar to findings in a Canadian civilian study [9]. The finding that women appear to be a potentially vulnerable subgroup will be of interest to service providers and supports preventive strategies. This study found an independent association between female sex and a high degree of activity limitations. Canadian studies found that women in the general population were more likely to have some limitations as well as arthritis, back problems, mood, and anxiety disorders [5,18]. A large study of US serving military personnel found that women had higher rates of musculoskeletal occupational disability and speculated on as yet unproven explanatory factors [11]. While further research is needed to clarify the potential role of occupational demands on post-service disability, these findings identify junior non-commissioned members as a potentially vulnerable veteran subgroup for service providers and population-level interventions. Nearly a third (30%) of these Regular Force Veterans were in this rank category (Corporal, Master Corporal, Leading, and Master Seaman), which had the highest rate of medical release and significant odds of disability. One hypothesis is that the disproportionate rate of chronic health conditions in former junior NCMs, especially painful musculoskeletal conditions, might be attributable to higher occupational physical demands. The association with post-secondary education other than university degree, which includes trade certification in physically demanding military and civilian occupations, supports this hypothesis. US studies have reported similar gradients in selfreported health by rank and higher odds of disability discharge in veterans with high physical demand occupations [11,12,26,47]. Service providers should be aware of veterans’ military experiences but should not be led astray by the absence of deployment history. This is the first study we are aware of exploring prior deployment and activity limitations in military veterans. Deployment was significant after adjusting for health conditions, consistent with a growing body of evidence in Canada and elsewhere that factors other than merely having deployed play key roles in later-life health-related adverse outcomes such as physical and mental health conditions, unemployment, and suicide [10,48–50]. While chronic physical and mental conditions causing later life functional impairments and activity limitations obviously can arise from deployment-related illnesses and injuries, they can also arise through other occupational and nonoccupational life course factors. Strengths This study is unique in examining factors associated with a range in degree of activity limitation in Canadian veterans. Veteran identity and some sociodemographic and military characteristics were objectively determined through data linkage. The response

890

J. M. Thompson et al.

rate was good and the sample was statistically representative of CAF Regular Force personnel who released during 1998–2007 and were living in the general Canadian population. The lower response rate for those not receiving VAC benefits was due largely to lack of contact information, but sampling weights provided by Statistics Canada accounted for age and sex differences between responders and non-responders. Owing to the high consent-to-share rate (94%), small differences that might exist between those who agreed to share and those who did not were thought to be insignificant.

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

Limitations Activity limitation is not a direct measure of disability experienced as difficulty in participating in roles such as employment or family life; however, the survey identified factors associated with two degrees of health-related activity limitation, which is a risk factor for role participation disability [3,7,43]. In this study, 17% with health-related activity limitations had none of the chronic health conditions asked about in the survey; however, the survey captured conditions most commonly associated with morbidity or mortality. The non-exclusive mental health questions used in this survey did not permit exploration of associations between specific mental conditions and disability but did allow for assessment of their role relative to physical conditions with an additive regression approach used in other studies [13,16]. The study was cross-sectional so associations cannot be presumed to imply causality; however, the findings identify subgroups of veterans more likely to experience disability and support hypotheses about causal factors. While the study did not have a direct measure of exposure to occupational factors that might predispose to post-service disability, the use of military rank enables hypotheses about the possible role of occupational stressors. Finally, while it is not known whether the findings are representative of the much larger CAF veteran population of older veterans and reservists, they are representative of modern-day veterans exposed to the increased operational tempo of CAF operations since 1990. Further research Further research is needed to determine how activity limitations affect military veterans in role participation in work, family, and community life, for example, the degree to which activity limitations affect civilian labour force participation. More research is needed to understand how mental health relates to disability and to produce evidence for effective rehabilitation measures in persons with co-occurring mental and physical health conditions. Reasons for the higher odds of disability in women veterans are unclear. Prospective life course studies using more precise clinical measures and measures of military service exposures are needed to determine the relationship between military service and disability after transition to civilian life.

Acknowledgements We are grateful for the assistance of Mr. Alain Poirier, Senior Statistics Officer, Research Directorate, Veterans Affairs, Canada.

Declaration of interest Drs. Thompson, Pranger, VanTil, and Pedlar, Ms. Sweet, and Ms. Shubaly were employees of Veterans Affairs Canada and LCol Besemann was a Canadian Armed Forces member. Dr. McColl had no potential conflicts of interest. Veterans Affairs Canada and the Department of National Defence funded this study.

Disabil Rehabil, 2015; 37(10): 884–891

References 1. McGeary M, Ford MA, McCutchen SR, Barnes DK. A 21st century system for evaluating veterans for disability benefits. Washington (DC): Committee on Medical Evaluation of veterans for Disability Compensation, Board on Military and Veterans Health, Institute of Medicine (US); National Academies Press; 2007. 2. World Health Organization. How to use the ICF: a practical manual for using the International Classification of Functioning, Disability and Health (ICF). Exposure draft for comment. October 2013. Geneva: WHO. Available from: http://www.who.int/classifications/ drafticfpracticalmanual2.pdf [last accessed 28 Jun 2014]. 3. Altman BM, Ng E, Berthelot J-M. A comparative analysis of four disability/functional limitation modules in the 2003 Joint Canada/ United States Survey of Health. Presented at Toronto meeting of the American Statistical Association Section on Research Methods; 2004; 7 p. Electronic Citation. Available from: http://www.amstat.org/sections/srms/Proceedings/y2004/files/Jsm2004-000574.pdf [last accessed 23 Dec 2013]. 4. Stucki G, Kostanjsek N, Ustun B, et al. Chapter 11. Applying the ICF in rehabilitation medicine. Chapter 11. In: Frontera WR, ed. Delisa’s physical medicine & rehabilitation: principles and practice, 5th ed. Lippincott Williams and Wilkins; 2010:301–24. 5. Goodridge D, Lawson J, Marciniuk D, Rennie D. A populationbased profile of adult Canadians living with participation and activity limitations. CMAJ 2011;183:E1017–24. 6. Resnik L, Reiber G. Long-term disabilities associated with combat casualties: measuring disability and reintegration in combat veterans. J Am Acad Orthop Surg 2012;20:S31–4. 7. Lederer V, Loisel P, Rivard M, Champagne F. Exploring the diversity of conceptualizations of work (dis)ability: a scoping review of published definitions. J Occup Rehabil 2014;24:242–67. 8. Cole DC, Ibrahim SA, Shannon HS, et al. Work correlates of back problems and activity restriction due to musculoskeletal disorders in the Canadian national population health survey (NPHS) 1994–5 data. Occup Environ Med 2001;58:728–34. 9. Dewa CS, Lin E, Kooehoorn M, Goldner E. Association of chronic work stress, psychiatric disorders, and chronic physical conditions with disability among workers. Psychiatry Serv 2007;58:652–8. 10. Horton JL, Jacobson IG, Wong CA, et al. The impact of prior deployment experience on civilian employment after military service. Occup Environ Med 2013;70:408–17. 11. Feuerstein M, Berkowitz SM, Peck CA Jr. Musculoskeletalrelated disability in US Army personnel: prevalence, gender, and military occupational specialties. J Occup Environ Med 1997;39: 68–78. 12. Lincoln AE, Smith GS, Amoroso PJ, Bell NS. The natural history and risk factors of musculoskeletal conditions resulting in disability among US Army personnel. Work 2002;18:99–113. 13. Schmitz N, Wang J, Malla A, Lesage A. Joint effect of depression and chronic conditions on disability: results from a population-based study. Psychosom Med 2007;69:332–8. 14. McKnight-Eily LR, Elam-Evans LD, Strine TW, et al. Activity limitation, chronic disease, and comorbid serious psychological distress in U.S. adults – BRFSS 2007. Int J Public Health 2009;54: 111–19. 15. Druss BG, Hwang I, Petukhova M, et al. Impairment in role functioning in mental and chronic medical disorders in the United States: results from the National Comorbidity Survey Replication. Mol Psychiatry 2009;14:728–37. 16. Scott KM, Von Korff M, Alonso J, et al. Mental-physical co-morbidity and its relationship with disability: results from the World Mental Health Surveys. Psychol Med 2009;39:33–43. 17. Mausbach BT, Chattillion EA, Moore RC, et al. Activity restriction and depression in medical patients and their caregivers: a metaanalysis. Clin Psychol Rev 2011;31:900–8. 18. Crompton S. Women with activity limitations: women in Canada, a gender-based statistical report. Ottawa: Social and Aboriginal Statistics Division, Statistics Canada; December 2011. Catalogue no. 89-503-X. 19. Luncheon C, Zack M. Health-related quality of life among US veterans and civilians by race and ethnicity. Prev Chronic Dis 2012; 9:E108. 20. Bedard K, Deschenes O. The long-term impact of military service on health: evidence from World War II and the Korean War. Am Econ Rev 2006;96:176–94.

Disability correlates in CAF Veterans

Downloaded by [University of Pennsylvania] at 03:40 06 November 2015

DOI: 10.3109/09638288.2014.947441

21. Kaplan MS, Huguet N, McFarland BH, Newsom JT. Suicide among male veterans: a prospective population-based study. J Epidemiol Commun Health 2007;61:619–24. 22. Dominick KL, Golightly YM, Jackson GL. Arthritis prevalence and symptoms among US non-veterans, veterans, and veterans receiving Department of veterans Affairs Healthcare. J Rheumatol 2006;33: 348–54. 23. Kramarow EA, Pastor PN. Percentage of Men Aged 25–64 Years with Activity Limitation by Age Group and Veteran Status, United States, National Health Interview Survey (NHIS), 2007–2010. QuickStats. Atlanta (GA): Centers for Disease Control and Prevention. MMWR Morb Mortal Wkly Rep. 2012;61(41);845. Available from: http://www.cdc.gov/mmwr/pdf/wk/mm6141.pdf [last accessed 12 Oct 2013]. 24. Wilmoth JM, London AS, Parker WM. Military service and men’s health trajectories in later life. J Gerontol B Psychol Sci Soc Sci 2010;65:744–55. 25. MacLean A. The things they carry: combat, disability and unemployment among U.S. men. Am Sociol Rev 2010;75:563–85. 26. Maclean A, Edwards RD. The pervasive role of rank in the health of U.S. veterans. Armed Forces Soc 2010;36:765–85. 27. MacLean MB, Van Til L, Thompson JM, et al. Life after service study: data collection methodology for income linkage and transition to civilian life survey. Charlottetown: Veterans Affairs Canada Research Directorate Technical Report; 2010. 28. Thompson JM, MacLean MB, Van Til L, et al. Survey on transition to civilian life: report on regular force veterans. Research Directorate, Veterans Affairs Canada, and Director General Military Personnel Research and Analysis, Department of National Defence. Charlottetown: Veterans Affairs Canada Research Directorate Technical Report; 2011. 29. Thompson JM, Pranger T, Sweet J, et al. Disability findings from the 2010 survey on transition to civilian life. Charlottetown: Veterans Affairs Canada Research Directorate Technical Report; 2013. 30. Alonso J, Angermeyer MC, Bernert S, et al. Disability and quality of life impact of mental disorders in Europe: results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project. Acta Psychiatr Scand Suppl 2004;(420):38–46. 31. Lillie E, Alvarado BE, Stuart H. Unemployment among Canadians with physical and a co-morbid mental disability: an examination of the 2006 Participation and Activity Limitation Survey (PALS). Disabil Health J 2013;6:352–60. 32. Statistics Canada. Participation and Activity Limitation Survey 2006: Technical and Methodological Report. Ottawa: Social and Aboriginal Statistics Division, Statistics Canada; 2007. Catalogue no. 89-628-XIE No. 002. 33. Weigl M, Cieza A, Cantista P, et al. Determinants of disability in chronic musculoskeletal health conditions: a literature review. Eur J Phys Rehabil Med 2008;44:67–79. 34. Churcher L, Chan CH, Badley EM. Chronic back problems and labor force participation in a national population survey: impact of comorbid arthritis. BMC Public Health 2013;13:326. 35. Tjepkema M, Wilkins R, Long A. Cause-specific mortality by income adequacy in Canada: a 16-year followup study.

36. 37. 38.

39.

40. 41.

42.

43. 44. 45.

46.

47.

48. 49.

50.

891

Ottawa: Statistics Canada; Health Reports; July 2013. Catalogue no. 82-003-X. Statistics Canada. Canadian Community Health Survey (CCHS) Annual Component, User Guide 2007–2008 Microdata User Files. Ottawa: Health Statistics Division, Statistics Canada; 2009. Andersson T, Alfredsson L, Kallberg H, et al. Calculating measures of biological interaction. Eur J Epidemiol 2005;20:575–9. Kramarow EA, Pastor PN. The health of male veterans and nonveterans age 25–64: United States, 2007–10. Washington (DC): U.S. Department of Health and Human Services, Centers for Disease Control; August 2012. NCHS Data Brief No. 101. Slater M, Perruccio AV, Badley EM. Musculoskeletal comorbidities in cardiovascular disease, diabetes and respiratory disease: the impact on activity limitations; a representative population-based study. BMC Public Health 2011;11:77. Blanck P, Linares C, Song C. Evolution of disability in late 19th century America: civil War pensions for Union Army veterans with musculoskeletal conditions. Behav Sci Law 2002;20:681–97. Pedlar DJ, Thompson JM. Research in the life courses of Canadian military veterans and their families. Chapter 2. In: Aiken A, Be´langer SAH, eds. Shaping the future, military and veteran health research. Kingston: Canadian Defence Academy Press; 2011:15–31. Egede LE. Major depression in individuals with chronic medical disorders: prevalence, correlates and association with health resource utilization, lost productivity and functional disability. Gen Hosp Psychiatry 2007;29:409–16. Bruffaerts R, Vilagut G, Demyttenaere K, et al. Role of common mental and physical disorders in partial disability around the world. Br J Psychiatry 2012;200:454–61. Patten SB. Long-term medical conditions and major depression in a Canadian population study at waves 1 and 2. J Affect Disord 2001; 63:35–41. Sanderson K, Nicholson J, Graves N, et al. Mental health in the workplace: using the ICF to model the prospective associations between symptoms, activities, participation and environmental factors. Disabil Rehabil 2008;30:1289–97. Whiteford HA, Degenhardt L, Rehm J, et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet 2013;382:1575–86. Gubata ME, Piccirillo AL, Packnett ER, Cowan DN. Military occupation and deployment: descriptive epidemiology of active duty U.S. Army men evaluated for a disability discharge. Mil Med 2013; 178:708–14. Garber BG, Zamorski MA, Jetly R. Mental health of Canadian Forces members while on deployment to Afghanistan. Can J Psychiatry 2012;57:736–44. Boulos D, Zamorski MA. Deployment-related mental disorders among Canadian Forces personnel deployed in support of the mission in Afghanistan, 2001–2008. CMAJ 2013;185: E545–52. LeardMann CA, Powell TM, Smith TC, et al. Risk factors associated with suicide in current and former US military personnel. JAMA 2013;310:496–506.