François L Thériault1,2, R A Hawes3, B G Garber3,4, F Momoli4,5,6, W Gardner4,5, M A Zamorski3,7, I Colman4. 1. Canadian Forces Health Services Group, Department of National Defence, Ottawa, Canada. francois.theriault3@forces.gc.ca. 2. School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada. francois.theriault3@forces.gc.ca. 3. Canadian Forces Health Services Group, Department of National Defence, Ottawa, Canada. 4. School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada. 5. Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada. 6. Ottawa Hospital Research Institute, Ottawa, Canada. 7. Department of Family Medicine, University of Ottawa, Ottawa, Canada.
Abstract
PURPOSE: Major depression is a leading cause of morbidity in military populations. However, due to a lack of longitudinal data, little is known about the rate at which military personnel experience the onset of new episodes of major depression. We used a new source of clinical and administrative data to estimate the incidence of major depression diagnoses in Canadian Armed Forces (CAF) personnel, and to compare incidence rates between demographic and occupational factors. METHODS: We extracted all data recorded in the electronic medical records of CAF Regular Force personnel, at every primary care and mental health clinical encounter since 2016. Using a 12-month lookback period, we linked data over time, and identified all patients with incident diagnoses of major depression. We then linked clinical data to CAF administrative records, and estimated incidence rates. We used multivariate Poisson regression to compare adjusted incidence rates between demographic and occupational factors. RESULTS: From January to December 2017, CAF Regular Force personnel were diagnosed with major depression at a rate of 29.2 new cases per 1000 person-years at risk. Female sex, age 30 years and older, and non-officer ranks were associated with significantly higher incidence rates. CONCLUSIONS: We completed the largest study to date on diagnoses of major depression in the Canadian military, and have provided the first estimates of incidence rates in CAF personnel. Our results can inform future mental health resource allocation, and ongoing major depression prevention efforts within the Canadian Armed Forces and other military organizations.
PURPOSE: Major depression is a leading cause of morbidity in military populations. However, due to a lack of longitudinal data, little is known about the rate at which military personnel experience the onset of new episodes of major depression. We used a new source of clinical and administrative data to estimate the incidence of major depression diagnoses in Canadian Armed Forces (CAF) personnel, and to compare incidence rates between demographic and occupational factors. METHODS: We extracted all data recorded in the electronic medical records of CAF Regular Force personnel, at every primary care and mental health clinical encounter since 2016. Using a 12-month lookback period, we linked data over time, and identified all patients with incident diagnoses of major depression. We then linked clinical data to CAF administrative records, and estimated incidence rates. We used multivariate Poisson regression to compare adjusted incidence rates between demographic and occupational factors. RESULTS: From January to December 2017, CAF Regular Force personnel were diagnosed with major depression at a rate of 29.2 new cases per 1000 person-years at risk. Female sex, age 30 years and older, and non-officer ranks were associated with significantly higher incidence rates. CONCLUSIONS: We completed the largest study to date on diagnoses of major depression in the Canadian military, and have provided the first estimates of incidence rates in CAF personnel. Our results can inform future mental health resource allocation, and ongoing major depression prevention efforts within the Canadian Armed Forces and other military organizations.
Authors: Lindsey A Hines; Laura Goodwin; Margaret Jones; Lisa Hull; Simon Wessely; Nicola T Fear; Roberto J Rona Journal: Psychiatr Serv Date: 2014-01-01 Impact factor: 3.084
Authors: J P Bonde; N Utzon-Frank; M Bertelsen; M Borritz; N H Eller; M Nordentoft; K Olesen; N H Rod; R Rugulies Journal: Br J Psychiatry Date: 2016-02-18 Impact factor: 9.319
Authors: François L Thériault; Bryan G Garber; Franco Momoli; William Gardner; Mark A Zamorski; Ian Colman Journal: Can J Psychiatry Date: 2018-07-17 Impact factor: 4.356
Authors: Anne M Gadermann; Charles C Engel; James A Naifeh; Matthew K Nock; Maria Petukhova; Patcho N Santiago; Benjamin Wu; Alan M Zaslavsky; Ronald C Kessler Journal: Mil Med Date: 2012-08 Impact factor: 1.437
Authors: François L Thériault; Franco Momoli; Robert A Hawes; Bryan G Garber; William Gardner; Ian Colman Journal: Soc Psychiatry Psychiatr Epidemiol Date: 2021-08-10 Impact factor: 4.328