Determinants of chronic physical health conditions in Canadian Veterans
Publication: Journal of Military, Veteran and Family Health
Volume 1, Number 2
Abstract
Abstract
Introduction: Limited information is available about the determinants of chronic health conditions of Veterans despite the increasingly perilous nature of military engagements in recent decades. Methods: Econometric analysis, using probit and negative binomial models, was conducted on the basis of data from a cross-sectional self-reported health survey of Canadian Veterans to investigate the determinants of musculoskeletal, respiratory, gastrointestinal, and cardiovascular health conditions; pain; and diabetes. Results: The results stress the role of military service–related factors in the increased likelihood of chronic physical health conditions in Canadian Veterans. Army Veterans had an increased probability of musculoskeletal (0.08, p ≤ 0.001) and gastrointestinal (0.05, p ≤ 0.001) conditions and pain (0.07, p ≤ 0.01). Veterans who were deployed had an increased risk of musculoskeletal conditions (0.08, p ≤ 0.001) and pain (0.06, p ≤ 0.001). In terms of non–service-related factors, the results confirm the role of obesity as a statistically significant determinant of chronic musculoskeletal, respiratory, and cardiovascular conditions; pain; and diabetes. Female Veterans were also at higher risk of respiratory and gastrointestinal conditions. Low-income Veterans have increased probability of musculoskeletal, gastrointestinal, pain, and cardiovascular conditions, and the risk decreased with rising income level. Finally, Veterans with mental health conditions had increased odds of musculoskeletal (OR = 2.79, p ≤ 0.001), respiratory (OR = 2.40, p ≤ 0.001), gastrointestinal (3.66, p ≤ 0.001), pain (OR = 2.61, p ≤ 0.001), and cardiovascular (OR = 1.45, p ≤ 0.01) conditions and diabetes (OR = 1.37, p ≤ 0.05). Discussion: The findings have important clinical and health resource use implications as Veterans seek treatment in community settings once they transition from military to civilian life. They also serve to advance the research agenda on the health of Veterans, an understudied population in Canada.
Résumé
Introduction: L’information disponible concernant les déterminants des problèmes chroniques de la santé des vétérans est limitée malgré l’augmentation du niveau de danger des engagements militaires dans les dernières décennies. Méthode: Une analyse économétrique avec des modèles binomial et probit a été utilisée à partir des données transversales d’un sondage sur la santé des vétéran(e)s canadien(ne)s. Cette analyse a été effectuée afin d’étudier les facteurs déterminants des conditions de santé tels que les problèmes musculosquelettiques, respiratoires, gastro-intestinaux, et cardiovasculaires, en plus des problèmes de douleur et de diabète. Résultats: Les résultats démontrent le rôle des facteurs reliés au service militaire pour l’augmentation probable des problèmes chroniques de la santé des vétéran(e)s canadien(ne)s. Les membres de la Force terrestre ont une plus grande probabilité de problèmes musculosquelettiques (0.08, p ≤ 0.001), gastro-intestinaux (0.05, p ≤ 0.001) et de douleurs (0.07, p ≤ 0.01). Pour les facteurs non-relié au service, les résultats confirment le rôle de l’obésité comme étant un facteur important pour les problèmes musculosquelettiques, respiratoires, de douleur, de diabète et cardiovasculaires chroniques. Les vétéranes sont par ailleurs plus à risque élevé de problèmes respiratoires et gastro-intestinaux. Les vétéran(e)s à revenu faible sont à grande probabilité de problèmes musculosquelettiques, gastro-intestinaux, cardiovasculaires et de douleurs. Les probabilités baissent lorsque le revenu monte. Pour terminer, les vétérans avec un problème de santé mentale sont à risque plus élevé pour les problèmes musculosquelettiques (OR = 2.788, p ≤ 0.001), respiratoires (OR = 2.397, p ≤ 0.001), gastro-intestinaux (3.656, p ≤ 0.001), de douleur (OR = 2.608, p ≤ 0.001), diabètes (OR = 1.374, p ≤ 0.05) and cardiovasculaires (OR = 1.448, p ≤ 0.01). Discussion: Les résultats ont des implications importantes pour les clinicien(ne)s et pour les ressources utilisées par les vétéran(s) dans leur communauté lorsqu’ils ont terminé la transition entre la vie militaire et la vie civile. Ils seront utilisés comme guide lors des prochaines recherches dans le domaine de la santé des vétéran(e)s, une population qui n’est pas assez étudiée au Canada.
INTRODUCTION
The military has undergone major operational changes in the past few decades.1 After World War II, the Armed Forces were engaged primarily as peacekeepers and observers in United Nations–sponsored missions. Since the 1990s, however, the Canadian Armed Forces have taken on combat roles in various conflict zones, including the Balkans and Afghanistan. Many members of the Armed Forces who served in these conflicts have since retired. Information on the determinants of their health status is limited, despite the increasingly perilous nature of their military engagements. Such information would help provide valuable information on the identification of high-risk Veterans and the reintegration of Veterans into civilian life and generate testable research hypotheses that can spur further research on the health of Veterans.2–5
In this study, we used data from a comprehensive 2010 survey of the health of Canadian Veterans who were released over 1998 to 2007. The research question entailed the determination of risk correlates of six major chronic health conditions (musculoskeletal, cardiovascular, respiratory, and gastrointestinal conditions; pain; and diabetes). We further investigated the determinants associated with overall health status as determined by the number of chronic health conditions reported by Veterans. As far as we are aware, this is the first detailed, systematic analysis of the overall health status of a nationally representative sample of Canadian Veterans.
A scoping literature review showed a significant gap in literature on the identification of physical health risk factors in the Canadian Veteran population. Some of the relevant background findings showed the lower health-related quality-of-life scores of Veterans compared with age- and sex-adjusted Canadian averages,6 with the lowest scores reported for non-commissioned ranks, the youngest cohort, and widowed or divorced Veterans. Veterans with the greatest odds of disability were those who had chronic pain and musculoskeletal health conditions.7 Risks that were found to be associated with post-military adjustment to civilian life included lower rank, with Army Veterans facing greater difficulty. Deployment was not considered a significant risk factor8 for this cohort.
Research before the availability of this new survey data set showed a significant relationship between educational achievement and the markers of transition to civilian life, which included being employed and having a sufficient income base.9 A detailed 2012 scoping review10 identified general health conditions faced by US, Canadian, and other Veterans, which included musculoskeletal disorders, infections, hearing loss, stomach conditions, neurologic conditions, and cardiovascular diseases. However, this review found no studies identifying risk factors of physical health for Canadian Veterans. There is also a recent growing literature on the association of physical and mental health in Canadian Veterans. Physical health was shown to be associated with suicidal ideation after controlling for socio-demographic characteristics.11 Anxiety disorder was shown to be associated with higher rates of cardiovascular, gastrointestinal, respiratory, and musculoskeletal conditions; diabetes; and chronic pain in Canadian Veterans.12
For US Veterans, most of the existing related health risk literature focused on Gulf War Veterans. A systematic review of these Gulf War Veterans found that deployment was most strongly associated with chronic fatigue syndrome.13 A population-based survey of 30,000 Veterans showed that deployed Veterans had a higher prevalence of functional impairment, health care utilization, symptoms, and medical conditions than non-deployed Veterans.14 Moreover, mortality rates among US Veterans with multiple chronic conditions were found to rise with the increased number of health conditions.15
The literature review confirmed the significant gap in the determinants of chronic health conditions in the Canadian Veteran population. This study attempts to bridge this gap through the use of the first high-quality, comprehensive health survey data set. It also contributes to the literature by identifying risk factors related to the preponderance of health conditions in Veterans, since nearly half of the Veterans reported having more than one chronic condition.
STUDY POPULATION AND FRAMEWORK
The data set for this study was derived from the Survey on Transition to Civilian Life that was commissioned by Veteran Affairs Canada (VAC) in 2010 to fill the health information gap on military to civilian transitions.16 Using this survey data set for the study had several distinct advantages. First, it is derived from the first and only comprehensive survey in Canada to gather information on chronic health conditions of Veterans irrespective of their deployment status and their client status with VAC. Second, the survey population represented a wide range of former military personnel in terms of socio-demographics and military service–related factors. Third, at 71% the response rate was considered high, providing a nationally representative sample of whom 94% agreed to share the responses with VAC and the Department of National Defence.
The survey was conducted by Statistics Canada using computer-assisted telephone interviews from February 3, 2010, to March 19, 2010. In the survey, Veterans were defined as former Canadian Forces personnel who had been discharged from the military, regardless of the length of the service. Regular Force personnel are those who worked full time with the Canadian Armed Forces and exclude those who worked part time in the Reserve Forces.
The study population were Veterans who were released between January 1, 1998, and December 31, 2007 (a 10-year period). The responders were Regular Force Veterans of the Canadian Armed Forces who enrolled from the 1960s to the 2000s and included those who were deployed to Cyprus, the Balkans, the first Gulf War, and Afghanistan. The survey yielded 3,154 unique observations. A random stratified design was used to oversample Veterans who received VAC benefits, which include disability pensions, disability awards, rehabilitation earnings loss, career transition services, and income support and health insurance. To adjust for the stratified random sampling design that enabled oversampling of the VAC client groups, individual sampling weights were used to compute weighted population estimates and used in the regression analysis.
METHODS
Probit model specification
Both probit and logit models are used extensively in binary response models, and the models provide very similar results, with the logit model using a logistic function and the probit model using a cumulative distribution function. The use of probit models to estimate risk factors for chronic conditions in a natural setting is well established in the economics literature.17 In this analysis, a series of probit equations were run for each chronic condition. The dependent variable in each equation was the chronic physical condition, which had a binary response – it was equal to 1 if the condition existed and 0 if it did not. Probit models were estimated for the likelihood that a specific physical health condition was present as a function of a set of individual socio-economic and demographic characteristics and service-oriented variables that described participants’ military service (rank, deployment status, and branch of service)
Negative binomial model specification
The negative binomial specification accommodates over-dispersion of the survey cross-sectional data. In the survey sample, close to half (49%) had two or more chronic health conditions, with conditional variance exceeding conditional mean. To investigate risk factors that affect Veterans’ overall health irrespective of the type of chronic disease condition, the total number of chronic health conditions reported was used as the dependent variable in negative binomial regression to obtain incident rate ratios (IRRs). This method is considered a valid alternative to logistic regression.18
Study variables
The dependent variables include the following chronic conditions:
•
Musculoskeletal – arthritis (including osteoarthritis and rheumatoid arthritis) and back problems (excluding fibromyalgia)
•
Cardiovascular – heart disease, high blood pressure, and the effects of stroke
•
Respiratory – asthma and chronic obstructive pulmonary disease (COPD); COPD included both emphysema and chronic bronchitis
•
Gastrointestinal – bowel disorders (Crohn’s disease, ulcerative colitis, irritable bowel syndrome, bowel incontinence) and stomach and intestinal ulcers
•
Diabetes
•
Pain or discomfort (either one time or recurring).
The independent variables were grouped into the following categories on the basis of health risk determinants taken from the public health literature on chronic health conditions:
•
Demographic characteristics – These characteristics included age, marital status, and sex. Age was grouped into three categories: younger than 40 years (base case), between 40 and 60 years old, and older than 60 years. The age grouping was based on identifying determinants for different working-age categories – from early career to mid-career to retirement. Marital status was divided into married or common law, widowed or divorced, and single (base case).
•
Early childhood – Height was used a proxy for early life well-being.
•
Behavioural characteristics – Smoking was categorized into daily smoker, occasional smoker, and former smoker or never smoked (base case).
•
Military status – Military status captured three main variables: branch, rank, and deployment outside Canada. Veterans were in the Air Force (base case), Army, or Navy branches of the Armed Forces. Two indicators were used to identify a Veteran’s deployment status: First, they had to have been deployed outside Canada at least once and, second, the deployment period had to last more than 30 days.
•
Educational attainment levels – Education was grouped into categories of increasing levels of formalized education: (1) up to high school, (2) trade, (3) college, and (4) university (base case).
•
Wealth – Home ownership and income levels were the economic variables of wealth. The highest income bracket (#_gt_#$150,000) was the base case.
•
Intermediate conditions – All respondents with a body mass index (BMI) of more than 30 were categorized as obese. BMI categories were adopted from a body weight classification system recommended by Health Canada and the World Health Organization (WHO).19
RESULTS
Descriptive analysis
Descriptive statistics
The entire sample consisted of 3,154 Veterans and was 88% male. As seen in Table 1, nearly half of the Veterans in the study population were from the Army with a third from the Air Force. Sixty percent had been deployed outside Canada at least once for a period of 30 days or more. Fifty-eight percent were aged 40 to 60 years. More than half had at least 20 years of service, andTable 1 Characteristics of Veterans
the majority had enrolled in the 1970s and 1980s. The educational rank of these Veterans ranged from less than high school to a postgraduate degree, with 17% having attained at least a bachelor’s degree, nearly a quarter having college degree below the bachelor’s level, and 10% having a trade certificate. Nearly half (47%) had either a high school diploma or equivalent or less than a high school education. Fifty-three percent of Veterans with up to a high school education were in the Army compared with 33% of those with a university education. Of those with a university education, 82% were in the officer ranks.
| Independent variable | Weighted % |
|---|---|
| Age, y | |
| <40 | 34.1 |
| 40–60 | 57.9 |
| >60 | 7.9 |
| Sex | |
| Male | 88.2 |
| Female | 11.9 |
| Branch | |
| Air Force | 31.1 |
| Army | 48.8 |
| Navy | 15.7 |
| Deployment | |
| Yes | 59.7 |
| No | 40.3 |
| Income, $ | |
| <50,000 | 17.2 |
| 50,000–100,000 | 40.1 |
| 100,000–150,000 | 25.6 |
| >150,000 | 17.2 |
| Obese | 28.0 |
| Military rank | |
| Senior officers | 8.0 |
| Junior officers | 12.4 |
| NCM (senior) | 28.2 |
| NCM (junior) | 30.2 |
| Recruits | 21.2 |
| Homeownership | |
| Yes | 83.3 |
| No | 16.6 |
| Marital status | |
| Married or common law | 75.6 |
| Divorced or separated | 8.6 |
| Single | 15.3 |
NCM = non-commissioned member.
Across all chronic conditions, Veterans with up to a high school education reported the highest rate of musculoskeletal, cardiovascular, and gastrointestinal conditions; pain; and diabetes. In total, 49% of all survey Veterans had a musculoskeletal condition, 8% had a respiratory condition, 11% had a gastrointestinal condition, 41% had pain, 6% had diabetes, and 21% had a cardiovascular condition.
Regression
Key findings of the probit model
The marginal probit effects for each probit regression model related to the chronic conditions are shown in Table 3. Income was found to be a significant negative risk factor for musculoskeletal, gastrointestinal, pain, and cardiovascular health conditions. The occurrence of each of these conditions fell as income increased. Veterans with an income level of less than $50,000 faced a greater probability of musculoskeletal (0.16, p ≤ 0.001), gastrointestinal (0.08, p ≤ 0.001), pain (0.21, p ≤ 0.001), and cardiovascular (0.1, p ≤ 0.001) conditions than the highest income earners (#_gt_#$150,000). At less than a 1% level of significance, the results show a strong association between lower income levels and the occurrence of these chronic physical conditions.
In terms of military rank, the results showed that that non-officers (senior non-commissioned members [NCMs], privates, and recruits) had the strongest association with musculoskeletal and pain conditions. These findings were similar to those found for lower income Veterans.
An important finding of the study was that across all the military branches, Army Veterans had a significantly higher risk of musculoskeletal (0.08, p ≤ 0.001), gastrointestinal (0.05, p ≤ 0.001), and pain (0.07, p ≤ 0.01) conditions than Air Force members. The magnitude of risk was higher for Army Veterans than for those in any other branch of the military.
A key finding was that Veterans who were deployed outside Canada (60% of the sample) showed increased risk for musculoskeletal (0.08, p ≤ 0.001) and pain (0.06, p ≤ 0.001) conditions. Previous studies have shown the negative implications of deployment on health in US Veterans,20–22 but this study is the first that supports this relationship in Canadian Veterans.
Obesity remained a significant determinant for all health conditions except gastrointestinal ones. The associations between obesity and musculoskeletal conditions (0.07, p ≤ 0.01), respiratory conditions (0.03, p ≤ 0.01), pain (0.07, p ≤ 0.001), diabetes (0.05, p ≤ 0.001), and cardiovascular conditions (0.13, p ≤ 0.001) were highly statistically significant. No other determinant in this study showed significance across this many health conditions. Daily smoking (0.07, p ≤ 0.05) and formerly smoking (0.05, p ≤ 0.05) also had a strong association with musculoskeletal conditions. The association between smoking status and musculoskeletal conditions is a new finding for the Veteran population.
Female Veterans exhibited a significantly greater risk of respiratory and gastrointestinal conditions. Compared with female Veterans, male Veterans had a lower risk of respiratory (−0.06, p ≤ 0.01) and gastrointestinal (−0.08, p ≤ 0.01) conditions. Veterans who were married or divorced were equally at higher risk of pain than their single counterparts, although the divorced Veterans exhibited a higher magnitude of risk than the married Veterans. The divorced Veterans also showed a significant association with cardiovascular conditions (0.09, p ≤ 0.05).
| No. of health conditions | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Income level, $ | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | Total |
| 0–<50,000 | 4.4 | 3.4 | 3.2 | 3.0 | 2.3 | 0.8 | 0.1 | 0.0 | 17.2 |
| 50,000–<100,000 | 11.4 | 7.8 | 9.5 | 6.6 | 3.2 | 1.2 | 0.3 | 0.1 | 40.1 |
| 100,000–<150,000 | 7.6 | 5.8 | 6.4 | 3.8 | 1.5 | 0.4 | 0.1 | 0.0 | 25.6 |
| >150,000 | 7.6 | 4.1 | 2.9 | 1.7 | 0.6 | 0.0 | 0.0 | 0.0 | 17.2 |
| Total | 30.9 | 21.0 | 22.0 | 15.2 | 7.6 | 2.6 | 0.7 | 0.1 | 100.0 |
Finally, Veterans aged 40 years and older exhibited a significantly greater risk for all conditions with the exception of respiratory illness. The risk increased for Veterans aged 60 years and older, especially for cardiovascular conditions (0.35, p ≤ 0.001), diabetes (0.08, p ≤ 0.001), and musculoskeletal conditions (0.19, p ≤ 0.001).
Key findings of the negative binomial model
The negative binomial model was used to investigate the associations between risk factors and the number of chronic health problems reported by Veterans. As seen in Table 2, 52% of the sample had at least one chronic condition, 22% reported two conditions, and 26% reported more than two chronic conditions.
The results of the negative binomial model using IRRs are shown in Table 4. The results show that the significant factors affecting the total number of chronic conditions are age, sex, branch, deployment, income, obesity, lower rank, marital status, and smoker status. Education and home ownership were not related to the total number of reported health conditions.
Army Veterans had an IRR that was 1.16 times that for Air Force Veterans. Those who were deployed overseas had an IRR that was 1.15 times that of those who were not deployed. As income levels increased, the IRR decreased from 1.70 to 1.24, with the IRR of the highest earners showing the health-protective effect of income. Obese Veterans had an IRR of 1.29 compared with non-obese Veterans. Veterans of lower rank (NCM seniors and recruits) had significantly higher IRRs than higher ranking Veterans (1.54 and 1.63, respectively). Daily smokers had a higher IRR (1.19) than non-smokers, but former smokers had a lower IRR than non-smokers (1.10). Those who were married or divorced or separated had higher IRRs than those who were single (1.26 and 1.29, respectively).
DISCUSSION
The analysis of risk factors for multiple chronic conditions is complex, given the different levels of severity, comorbidity, and possible complex pathways between chronic conditions and other factors. The key findings highlight the role of service-related factors in a subset of chronic conditions in Veterans. Notably, the study showed that overseas deployment and being in the Army were major contributory determinants of many of the chronic physical conditions. Being in the Army was a significant determinant of musculoskeletal and gastrointestinal conditions and pain. The reasons for the strong association between Army Veterans (who accounted for 49% of the Veteran population) and chronic conditions could be the nature of work undertaken by Army personnel or the socio-economic background of Army Veterans. A quarter of all Army Veterans attained only up to high school education compared with 15% of Air Force and 7% of Navy Veterans. The selection of recruits into the different branches as well as self-selection could confound these results because different branches require different aptitudes in the placement of recruits. However, there is a paucity of publicly available information on how applicants are initially selected into the Armed Forces and into the different branches of the military.
Deployment was shown to be a significant determinant of musculoskeletal conditions and pain. The location of deployment matters in this context, as demonstrated by literature that focuses on health status of Veterans deployed to a specific theatre (e.g., the Gulf War). However, the survey neither collected this information nor asked how many times a Veteran was deployed, the location of each deployment, and the actual duration of each deployment. In addition, lower ranking Veterans were also found to be at higher risk for musculoskeletal, gastrointestinal, and pain health conditions.
In terms of non–service-related factors, economic factors, notably income, were shown to be significant determinants. Veterans who were in the low income brackets had a statistically significant association with musculoskeletal, pain, and cardiovascular conditions, with risk rising as income levels fell. Veterans with higher income have better opportunities to produce health through either better nutrition or increased ability to spend time improving their health through various means. Although educational attainment was not found to be a determinant of any of the investigated health conditions, those who were in the lower ranks were found to be at higher risk of musculoskeletal, gastrointestinal, and pain conditions.
Other non–service-related factors included demographic factors such as age, sex, and marital status. Female Veterans were found to be at higher risk for respiratory conditions. Women are becoming an important demographic group within the Armed Forces, and as their numbers have increased over time, they have taken on expanded roles within the military, including activeTable 3 Probit Analysis – Marginal Effects
Table 4 Negative binomial model results
deployment. Targeted research on this cohort may need to be undertaken to understand the different health pathways of men and women in the military.
| Independent variable | Musculoskeletal | Respiratory | Gastrointestinal | Pain | Diabetes | Cardiovascular |
|---|---|---|---|---|---|---|
| Age | ||||||
| 40–60 y | 0.1163* | 0.0035 | 0.0727* | 0.1344* | 0.0629* | 0.1765* |
| >60 y | 0.1959* | 0.0235 | 0.0847† | 0.1164† | 0.0779* | 0.3531* |
| Male | −0.0089 | −0.0602† | −0.076† | −0.0516 | 0.0058 | 0.0024 |
| Branch | ||||||
| Army | 0.0737* | −0.0064 | 0.0459* | 0.0682† | 0.0058 | 0.0149 |
| Navy | 0.0001 | −0.0090 | 0.0190 | −0.0113 | 0.0048 | 0.0222 |
| Unknown | 0.184* | 0.0284 | 0.0542 | 0.0369 | −0.0122 | −0.0602 |
| Height | ||||||
| Below average | −0.0088 | −0.0028 | −0.0162 | −0.0562† | −0.0181§ | −0.0141 |
| Average | 0.0101 | −0.0067 | −0.0043 | −0.0243 | −0.0017 | 0.0467‡ |
| Education | ||||||
| High school | −0.0146 | −0.0171 | −0.1319* | 0.0112 | 0.0212§ | 0.0204 |
| Trade | −0.0211 | 0.0314 | −0.0932‡ | 0.1164† | 0.0280 | 0.0225 |
| College or diploma | 0.0457 | −0.0163 | −0.0966† | 0.0859† | 0.0245‡ | 0.0098 |
| Deployment | 0.0833* | 0.0105 | −0.0005 | 0.0649† | −0.0183 | −0.0169 |
| Income, $ | ||||||
| <50,000 | 0.1575* | 0.0270 | 0.0752* | 0.2074* | 0.0278 | 0.0992* |
| 50,000–100,000 | 0.1098* | 0.0066 | 0.0484† | 0.112* | 0.0062 | 0.0489‡ |
| Obese | 0.0661† | 0.0266† | 0.0168 | 0.0685* | 0.0478* | 0.1239* |
| Military rank | ||||||
| Senior officers | 0.0391 | −0.0300 | −0.0387 | 0.0301 | 0.0534§ | 0.0237 |
| Junior officers | 0.0720 | −0.0110 | −0.0442‡ | −0.0117 | −0.0022 | −0.0180 |
| NCM (senior) | 0.1712* | 0.0212 | 0.0514‡ | 0.1447* | 0.0245 | 0.0429 |
| Recruits | 0.2229* | 0.0191 | 0.0463§ | 0.1981* | 0.0082 | −0.0132 |
| Home ownership | 0.0066 | −0.0282 | −0.0270 | −0.0145 | −0.0153 | 0.0347 |
| Marital status | ||||||
| Unknown | 0.0764 | −0.0422‡ | 0.2100 | 0.0691 | −0.0224 | 0.4513* |
| Married or common law | 0.0538 | 0.0188 | −0.0006 | 0.1258* | −0.0092 | 0.0420 |
| Divorced or separated | 0.0488 | 0.0107 | −0.0021 | 0.1337* | −0.0209 | 0.085‡ |
| Smoker | ||||||
| Daily | 0.0704‡ | 0.0177 | 0.0249 | 0.0331 | 0.0072 | 0.0124 |
| Occasional | −0.0057 | 0.0492§ | −0.0144 | −0.0103 | −0.0146 | −0.0229 |
| Former | 0.0474‡ | 0.0224§ | 0.0120 | −0.0086 | 0.0085 | 0.0273 |
*
p ≤ 0.001.
†
p ≤ 0.01.
‡
p ≤ 0.05.
§
p ≤ 0.1.
NCM = non-commissioned member.
| Independent variable | IRR | SE | t | p > |t| | SE | 95% CI |
|---|---|---|---|---|---|---|
| Age, y | ||||||
| 40–60 | 1.513* | 1.086 | 1.050 | 1.000 | 1.090 | 1.347–1.699 |
| >60 | 1.674* | 1.130 | 1.090 | 1.000 | 1.133 | 1.432–1.957 |
| Male | 1.814* | 1.049 | −1.320 | 1.021 | 1.047 | 1.727–0.912 |
| Branch | ||||||
| Army | 1.157* | 1.041 | 1.410 | 1.001 | 1.045 | 1.073–1.248 |
| Navy | 1.021 | 1.050 | 1.920 | 1.359 | 1.052 | 1.924–1.128 |
| Unknown | 1.264‡ | 1.129 | 1.620 | 1.009 | 1.133 | 1.030–1.553 |
| Height | ||||||
| Below average | 1.908‡ | 1.036 | −1.640 | 1.100 | 1.036 | 1.840–0.982 |
| Average | 1.006 | 1.040 | 1.470 | 1.636 | 1.042 | 1.927–1.092 |
| Education | ||||||
| High school | 1.955 | 1.072 | −1.210 | 1.836 | 1.074 | 1.820–1.112 |
| Trade | 1.118 | 1.094 | 1.940 | 1.348 | 1.102 | 1.936–1.336 |
| College or diploma | 1.092 | 1.078 | 1.930 | 1.352 | 1.085 | 1.938–1.272 |
| Deployment | 1.146† | 1.047 | 1.750 | 1.006 | 1.005 | 1.053–1.248 |
| Income, $ | ||||||
| <50,000 | 1.699* | 1.096 | 1.100 | 1.000 | 1.117 | 1.485–1.944 |
| 50,000–100,000 | 1.395* | 1.073 | 1.330 | 1.000 | 1.085 | 1.238–1.573 |
| 100,000–150,000 | 1.235* | 1.073 | 1.280 | 1.001 | 1.078 | 1.091–1.399 |
| Obese | 1.290* | 1.038 | 1.110 | 1.000 | 1.043 | 1.208–1.376 |
| Military rank | ||||||
| Senior officers | 1.187 | 1.132 | 1.240 | 1.217 | 1.142 | 1.940–1.501 |
| Junior officers | 1.037 | 1.111 | 1.260 | 1.798 | 1.114 | 1.837–1.286 |
| NCM (senior) | 1.544* | 1.133 | 1.480 | 1.000 | 1.138 | 1.296–1.841 |
| Recruits | 1.631* | 1.130 | 1.100 | 1.000 | 1.137 | 1.384–1.924 |
| Home ownership | 1.917 | 1.054 | 1.060 | 1.949 | 1.049 | 1.825–1.018 |
| Marital status | ||||||
| Unknown | 1.731* | 1.197 | 1.130 | 1.000 | 1.236 | 1.326–2.262 |
| Married or common law | 1.259* | 1.081 | 1.800 | 1.005 | 1.085 | 1.102–1.438 |
| Divorced or separated | 1.286* | 1.091 | 1.870 | 1.004 | 1.096 | 1.112–1.489 |
| Smoker | ||||||
| Daily | 1.184* | 1.056 | 1.600 | 1.009 | 1.061 | 1.072–1.310 |
| Occasional | 1.019 | 1.077 | 1.280 | 1.781 | 1.079 | 1.876–1.187 |
| Former | 1.100 | 1.044 | 1.040 | 1.041 | 1.047 | 1.012–1.196 |
| _cons | 1.478† | 1.050 | −1.340 | 1.000 | 1.068 | 1.361–0.632 |
| /ln α | −4.452 | |||||
| α | 1.012 | |||||
Obesity was shown to be a significant determinant across the chronic health conditions investigated (except gastrointestinal conditions), validating its role as a major contributing cause of non-communicable disease.23 Obesity was also analyzed as a chronic health condition on its own. The probit results, however, showed that only age (Veterans aged 40–60 years; 0.295, p ≤ 0.01), sex (men; 0.212, p ≤ 0.05), and education (trade or college; 0.413, p ≤ 0.01) were major risk correlates of obesity.
As noted earlier, associations were found between Veterans’ mental and physical health. A further analysis was conducted using mental health as an independent variable in a logit framework. The results show that Veterans who reported any mental health condition had statistically significant higher odds of having musculoskeletal (OR = 2.79, p ≤ 0.001), respiratory (OR = 2.40, p ≤ 0.001), gastrointestinal (OR = 3.66, p ≤ 0.001), pain (OR = 2.61, p ≤ 0.001), and cardiovascular (OR = 1.45, p ≤ 0.01) conditions and diabetes (OR = 1.37, p ≤ 0.05). These results support the strong association between mental and physical health conditions in Canadian Veterans.
The study’s limitations include the following. First, all physical chronic conditions were self-reported, leading to potential measurement errors. To mitigate the potential for response bias, respondents were prompted to report only chronic health conditions that had been diagnosed by a health professional. Potential measurement error remained for the other variables, notably height, weight, and obesity level. A second limitation was the range of chronic conditions captured in the survey. Some life-threatening diseases and conditions that erode morbidity (e.g., symptoms of kidney disorders) were not covered in the survey. Third, the survey did not capture the degree or severity of each illness or health condition. Hence, it was not possible to differentiate between mild or severe chronic health conditions.
Finally, although probit models are very similar to logit models, they are considered a more novel way of estimating risk factors outside of the economics field. However, using probit models has no inherent limitations compared with other binary outcome models. For comparison purposes, logit models showed that Army Veterans had statistically significant higher odds of the following conditions: musculoskeletal (OR = 1.34, p ≤ 0.01), gastrointestinal (1.52, p ≤ 0.01), and pain (OR = 1.33, p ≤ 0.01). Veterans who were deployed had statistically significant higher odds of musculoskeletal (OR = 1.37, p ≤ 0.01) and pain (OR = 1.29, p ≤ 0.05) conditions. The lowest income earners had statistically significant higher odds of having musculoskeletal (OR = 1.68, p ≤ 0.01), gastrointestinal (1.80, p ≤ 0.05), pain (OR = 2.25, p ≤ 0.001), and cardiovascular (OR = 1.76, p ≤ 0.01) conditions. Veterans who were obese had statistically significant higher odds of having musculoskeletal (OR = 1.28, p ≤ 0.01), respiratory (OR = 1.42, p ≤ 0.01), pain (OR = 1.32, p ≤ 0.01), and cardiovascular (OR = 2.33, p ≤ 0.001) conditions and diabetes (OR = 2.68, p ≤ 0.001).
Despite the limitations, this study has several key strengths. It is a comprehensive study identifying key service-related and non–service-related determinants of chronic health conditions among all Canadian Veterans. In addition, the identification of these key determinants has important clinical implications. As Veterans reintegrate into civilian life, it is important that community physicians include this perspective in the care of their Veteran patients. Moreover, the close linkage between mental health and physical health conditions confers a higher level of disability on these Veterans, which may result in greater use of mental health services, as shown in a sample of older Canadians who have comorbid mental health and chronic health conditions.24,25
In conclusion, this study provides empirical evidence of the role of service-oriented factors (specifically deployment and Army service), low income, sex (female), and intermediate factors (obesity) as key determinants of a subset of chronic physical health conditions in Canadian Veterans. The findings may lead to further hypothesis generation to advance the research agenda for Canadian Veterans. They may also inform the design of health and social programs by Veteran Affairs Canada and the Department of National Defence that are targeted toward high-risk Armed Forces personnel as they transition from military to civilian lives.
ACKNOWLEDGEMENTS
We acknowledge J. Sweet, M. MacLean, and J. Thompson, MD, from the Research Directorate, Veteran Affairs Canada, for valuable feedback on drafts of this article.
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Journal of Military, Veteran and Family Health
Volume 1 • Number 2 • November 2015
Pages: 32 - 42
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© 2015 General Dynamics Canada, All rights reserved. For permission to share, copy, or redistribute, contact [email protected].
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Published online: 20 October 2015
Published in print: November 2015
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All authors participated in conceiving the design of the study, conducting the literature search, selecting the research questions and data set, analyzing the results, drafting the manuscript, and editing and revising the manuscript. All authors approved the final version submitted for publication.
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Journal of Military, Veteran and Family Health 2015 1:2, 32-42
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