Office of Surveillance, Epidemiology, and Laboratory Services

1. Socioeconomic status and anxiety/stress/depression are associated with suicidal thoughts among adults who served in the U.S. military: A latent class analysis Xiao Jun (John) Wen, MD; Chaoyang Li, MD, PhD; Guixiang Zhao, MD, PhD; Alexander E. Crosby, MD, Matthew M. Zack, MD, MPH; Lina Balluz, Sc.D. MPH Centers for Disease Control and Prevention Presented on June 11, 2013, CSTE Annual Conference 2013, Pasadena, CA Office of Surveillance, Epidemiology, and Laboratory Services Public Health Surveillance Program Office

2. Background Data source: VA http://www.va.gov/opa/docs/Suicide-Data-Report-2012-final.pdf. Death per 100,000 Suicide mortality among veterans and active military in the U.S has been a national concern in recent years

3. Background Predictors for suicide death among veterans and active military in the U.S: • Being male, white, single, unemployed, and depressed • Risk factor assessments are usually done by multivariate logistic regression models

4. Background Limitations of single-indicator modeling: • It does not fully account for the correlation and overlap among individual suicide risk factors • Examples • Social economic status: employment and annual income level • Mental health status: depressive disorders, depression, anxiety, post-traumatic stress disorder • A risk factor may include multiple indicators, or it is a class of multiple factors in the same domain. Such risk factor can be very difficulty to handle by a single-indicator modeling approach

5. Background To identify class variables in the domains of socioeconomic status and mental health status as potential correlates of suicidal thoughts

6. Methods Data source • Behavioral Risk Factor Surveillance System (BRFSS) 2011 data • Optional model • Sample used in the analysis -6,884 adult respondents who had served in the U.S. military (did not include those in training for the Reserves or National Guard and also excluded those who refused or answered “do not know” to the question about suicide thoughts) -Both landline and cell phone -Nine states participations (Alaska, Kansas, Louisiana, Maine, Nebraska, Nevada, New Jersey, North Carolina, and Tennessee)

7. Methods Outcome variable: suicidal thoughts • Question asked about it: “Has there been a time in the past 12 months when you thought of taking your own life?”

8. Methods Questions asked about the economic status: • Employment: “Are you currently…? (multiple choices on employment)” • Annual income: “(How much) is your annual household income from all sources?” • Home ownership: “Do you own or rent your home?”

9. Methods • Questions about mental health and treatment: • “(Ever told) you have a depressive disorder (including depression, major depression, dysthymia, or minor depression)?” (core questionnaire) • “Has a doctor or other health professional ever told you that you have depression, anxiety, or post traumatic stress disorder (PTSD)?” • “In the past 12 months, did you receive any psychological or psychiatric counseling or treatment?”

10. Methods Domains Indicators Outcome Covariates • Age • Sex • Marital status • Health insurance coverage • Smoking • Physical activities • Self-rated health • Disability • Traumatic brain injury • Employment • Annual income • Home ownership Social economic Suicidal thoughts Latent class variables • Depression/anxiety • Depression/anxiety/ • PTSD • Received counseling treatment Mental health Modeling of the Latent class variables

11. Methods • Probabilities of being at the low socioeconomic class by latent class analysis

12. Methods Probabilities of high risk of mental health by latent class analysis

13. Methods Table 1 Fit of latent class models using Bayesian information criterion (BIC) and quality of models for health-related domains, Behavioral Risk Factor Surveillance System (BRFSS), 2011

14. Results Table 2 Prevalence of self-reported suicidal thoughts by demographics, socioeconomic and mental health status, and risk factors among adults who served in the military, from nine states in U.S., 2011

15. Results Table 2 Prevalence of self-reported suicidal thoughts by demographics, socioeconomic and mental health status, and risk factors among adults who served in the military, from nine states in U.S., 2011

16. Results Table 2 Sample descriptive statistics by demographics, socioeconomic and mental health status, and risk factors among adults who served in the military, from nine states in U.S., 2011

17. Results Table 2 Prevalence of self-reported suicidal thoughts by demographics, socioeconomic and mental health status, and risk factors among adults who served in the military, from nine states in U.S., 2011

18. Results Table 3 Adjusted Prevalence ratios of self-reported suicidal thoughts by latent classes of socioeconomic and mental health determinants among adults served in the military, from nine states in U.S., 2011

19. Discussions We identified two latent class variables that are associated with suicidal thoughts • Being a member of lower socioeconomic class • Being a member of mentally unhealthy class

20. Discussions We also identified several individual risk factors that are associated with suicidal thoughts: • No healthcare coverage • Self-rated poor/fair health status Based on our knowledge, they have not been reported in the literature.

21. Discussions • Strength of the analysis: • Examined the likelihood of being a member of lower socioeconomic class and mentally unhealthy class • Using these valid latent class variables as independent variables to identify potential indicators of the suicidal thoughts • Modeling results indicate that being a member of lower socioeconomic class or of mentally unhealthy class is more likely to report suicidal thoughts

22. Discussions • Strength of the analysis: • Latent class variable modeling approach counted for the correlation and overlap among individual suicide risk factors • Overcame some of the limitations from the single-indicator modeling approaches • Filled some information gaps about suicidal thoughts among old-aged veterans and active military: • Majority of the respondents (60%) in this analysis were aged 55 years old or above and recent publications only focused on younger veterans and active military

23. Discussions Limitations of the analysis: • selection bias: -Those with no phone were not included -Those who were institutionalized due to very poor mental health status • Recall bias: -Self-reported data • Social desirability bias -Very sensitive question was asked • Cross sectional analysis: - Cause-effects relationship should not be inferred

24. Conclusions • Our latent-class modeling approach has identified that socioeconomic and mentally unhealthy status among adults are strongly associated with suicidal thoughts. Suicide prevention programs should focus on adults in this group. • It may also be useful in identifying other potential risk factors that are difficult to do so by the conventional single-indicator modeling approaches.

25. Thanks • To your attention • To all of my coauthors: • Chaoyang Li, MD, PhD • Guixiang Zhao, MD, PhD • Alexander E. Crosby, MD • Matthew M. Zack, MD, MPH • Lina Balluz, Sc.D. MPH

26. Contact Information John Wen Environmental Health Tracking Branch Division of Hazards and Health Effects National Center for Environment Health Centers for Disease Control and Prevention 770-488-3984 tzw4@cdc.gov