Publication related to RSI or an RSI staff member
Spinal pain and major depression in a military cohort: bias analysis of dependent misclassification in electronic medical records.
BACKGROUND: Spinal pain and major depression are prevalent conditions in adult populations and are particularly impactful in the military. However, the temporal relationship between these two conditions remains poorly understood. METHODS: Using data extracted from electronic medical records, we assessed the association between incident diagnoses of spinal pain and major depression in a cohort of 48,007 Canadian Armed Forces personnel followed from January 2017 to August 2018. We used multivariate Poisson regression to measure the association between the period prevalence of these two conditions. We used probabilistic bias modelling to correct our estimates for misclassification of spinal pain and major depression. RESULTS: After correcting for misclassification with probabilistic bias modelling, subjects newly diagnosed with spinal pain during the study period were 1.41 times (95% interval 1.25, 1.59) more likely also to be diagnosed with incident major depression, and personnel newly diagnosed with major depression were 1.28 times (95% interval 1.17, 1.39) more likely also to be diagnosed with spinal pain, compared to undiagnosed counterparts of the same age and sex. Without bias corrections, we would have overestimated the magnitude of the association between major depression and spinal pain by a factor of approximately 2.0. CONCLUSION: Our results highlight a moderate and bi-directional association between two of the most prevalent disorders in military populations. Our results also highlight the importance of correcting for misclassification in electronic medical record data research.
Authors
- Theriault, Francois L, Theriault FL, Canadian Forces Health Services Group, Department of National Defence, Ottawa, Canada. Theriault.Francois@cfmws.com.; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada. Theriault.Francois@cfmws.com.
- Momoli, Franco, Momoli F, School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
- Hawes, Robert A, Hawes RA, Canadian Forces Health Services Group, Department of National Defence, Ottawa, Canada.
- Garber, Bryan G, Garber BG, Canadian Forces Health Services Group, Department of National Defence, Ottawa, Canada.; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
- Gardner, William, Gardner W, School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.; Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada.
- Colman, Ian, Colman I, School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
BACKGROUND: Spinal pain and major depression are prevalent conditions in adult populations and are particularly impactful in the military. However, the temporal relationship between these two conditions remains poorly understood. METHODS: Using data extracted from electronic medical records, we assessed the association between incident diagnoses of spinal pain and major depression in a cohort of 48,007 Canadian Armed Forces personnel followed from January 2017 to August 2018. We used multivariate Poisson regression to measure the association between the period prevalence of these two conditions. We used probabilistic bias modelling to correct our estimates for misclassification of spinal pain and major depression. RESULTS: After correcting for misclassification with probabilistic bias modelling, subjects newly diagnosed with spinal pain during the study period were 1.41 times (95% interval 1.25, 1.59) more likely also to be diagnosed with incident major depression, and personnel newly diagnosed with major depression were 1.28 times (95% interval 1.17, 1.39) more likely also to be diagnosed with spinal pain, compared to undiagnosed counterparts of the same age and sex. Without bias corrections, we would have overestimated the magnitude of the association between major depression and spinal pain by a factor of approximately 2.0. CONCLUSION: Our results highlight a moderate and bi-directional association between two of the most prevalent disorders in military populations. Our results also highlight the importance of correcting for misclassification in electronic medical record data research.
