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. 2021 Nov 24;34(2):211–223. doi: 10.1080/08995605.2021.1987084

Movement behaviors associated with mental health among US military service members

Lilian G Perez 1,✉, Lu Dong 1, Robin Beckman 1, Sarah O Meadows 1
PMCID: PMC10013521  PMID: 38536360

ABSTRACT

Compared to the general adult population, military service members experience an excess burden of mental health problems (e.g., posttraumatic stress disorder, PTSD). Physical activity, screen time, and sleep (i.e., movement behaviors) are independently associated with mental health, but their combined effects are poorly understood, particularly in military populations. We analyzed data from active component service members in the national 2018 Health Related Behaviors Survey (N = 17,166). Weighted gender-stratified logistic regression models examined the associations of meeting recommended/healthy levels of moderate-to vigorous physical activity (MVPA), screen time, and sleep duration – separately and in combination (none, some, all) – with PTSD, suicide ideation, and serious psychological distress. In both men and women, meeting sleep recommendations was associated with reduced odds of each outcome. Meeting MVPA recommendations was associated with lower odds of serious psychological distress only in men (OR = 0.76, 95% CI: 0.58–1.00). No/low screen time was associated with lower odds of suicide ideation only in women (OR = 0.66, 95% CI: 0.45–0.95). The odds of all three outcomes were lower in those who reported some or all (vs. none) recommended/healthy movement behaviors, with the lowest odds found in the “all” group, suggesting a possible dose-response relationship. Findings can help inform multiple behavior change interventions to improve service members’ psychological fitness and military readiness.

KEYWORDS: Mental health, suicide, physical activity, sleep, military

What is the public significance of this article?— Adequate sleep among service members reduces the odds of poor mental health, independent of physical activity and sedentary behaviors. However, engaging in healthy or recommended levels of all three behaviors may provide additional benefits for mental health. Military programming may need to target multiple behavior change among service members to enhance psychological fitness and military readiness.

Introduction

In the US, one in five active duty service members has a mental health disorder diagnosis (Deployment Health Clinical Center, 2017). Although this prevalence is similar to that of the general adult population (19%) (Substance Abuse and Mental Health Services Administration, 2019), certain disorders, such as posttraumatic stress disorder (PTSD) and suicide ideation are disproportionately higher in active duty service members, particularly women (Meadows et al., 2018; Substance Abuse and Mental Health Services Administration, 2019). The risk factors for mental health disorders in active duty service members include socio-demographics (e.g., female, Latino or non-Latino black, and low SES), poor physical health, and lack of social/emotional support, among others (DiBiasio et al., 2014; Kaczkurkin et al., 2016). Several studies among military and nonmilitary samples also show that health behaviors across the movement continuum (referred to as movement behaviors hereafter) (Chaput et al., 2014; McGregor et al., 2018), such as high physical activity, particularly aerobic exercise (Fluetsch et al., 2019; Vancampfort et al., 2018; White et al., 2017); low sedentary time such as screen time (Huang et al., 2020; Mason et al., 2019); and adequate sleep (Liu et al., 2013; Mason et al., 2019) are associated with better mental health outcomes. However, these studies have largely focused on a single movement behavior, while ignoring others that occur throughout the day. Research from other topic areas such as obesity show that movement behaviors have independent and synergistic effects, where individuals who engage in a combination of high physical activity, low sedentary time, adequate sleep, have better health outcomes than those who engage in a combination of negative behaviors (Chastin et al., 2015; Saunders et al., 2016). However, only a few studies have examined the independent and combined associations of movement behaviors on mental health outcomes, with none focused on military populations (McGregor et al., 2018; Rayward et al., 2017).

The Department of Defense’s Total Force Fitness framework, which identifies eight fitness domains for military readiness and resilience (Chairman of the Joint Chiefs of Staff, 2013), posits that targeting factors in the physical or behavioral fitness domains, which include movement behaviors, can have beneficial effects on other domains such as psychological fitness. To date, only a handful of studies have examined the associations of individual movement behaviors with mental health outcomes among active duty service members (LeardMann et al., 2011; Morgan et al., 2017; Mysliwiec et al., 2013). However, none of these studies examined the combination of movement behaviors. To better understand how the mental health benefits of movement behaviors can be optimized among active duty service members, studies are needed testing multiple movement behaviors simultaneously. Studies identifying service members who engage in a combination of negative movement behaviors are needed to identify high-risk groups who could benefit from multiple behavior change interventions. Such interventions may benefit not only the health of those at risk but also overall military readiness.

The present study used data from a representative sample of active component military service members (all active duty) to examine the independent and combined associations of three movement behaviors – physical activity (PA), screen time, and sleep duration – with probable PTSD, suicide ideation, and serious psychological distress. Given the gender differences observed for mental health disorders and health behaviors in the military (Meadows et al., 2018), we stratified all analyses by gender. We hypothesized that the optimal profile (i.e., reporting all three movement behaviors at recommended or healthy levels) would be associated with the lowest risk of mental health problems, with variations by gender.

Methods

Sample population

Cross-sectional data were obtained from the active component sample of the 2018 Health Related Behaviors Survey (HRBS) of the Department of Defense (DoD). The protocol for the 2018 HRBS is described in detail in a published report (Meadows et al., 2021). In brief, the sample included active duty service members who were not enrolled as cadets in service academies, senior military colleges, or other Reserve Officers’ Training Corps programs as of September 2018. Personnel in the National Guard or reserve program (even those serving on active duty) comprised a separate reserve component sample and were not included in the present analyses. We focused only on the active component service members given their full-time status and potential to benefit from DoD-related prevention efforts.

The sampling frame was based on active component personnel’s service branch, pay grade, and gender. Of the 1,357,219 eligible active component service members in the sampling frame, 199,996 were invited to participate. Of the 19,787 who logged into the survey, 1,732 did not proceed through the front material and were therefore dropped. An additional 889 surveys were dropped due to non-usability, leaving a final analytic sample of 17,166 (men: 11,813; women: 5,353).

The weighted overall response rate was 9.6%. We created analytic weights to account for differences between respondents and the broader DoD service member population from which they were drawn. In the unweighted sample, service members in the Army were under-represented, whereas members of the Air Force and Coast Guard were over-represented. Junior enlisted were under-represented and senior enlisted and mid-grade officers were over-represented. Women were over-represented. Other under-represented groups included service members who were never married, had no children, and had a high school degree (or less). We created separate weights addressing potential population differences due to the survey design and non-response and then combined them to calculate the final analytic weights. The final weights improve the generalizability of study findings to the broader population of survey-eligible active component service members. Additional details about the weights can be found in the 2018 HRBS report (Meadows et al., 2021).

The 2018 HRBS was approved by Institutional Review Boards of the RAND Corporation, Westat, and the Coast Guard as well as the Office of People Analytics, the Office of the Under Secretary of Defense for Personnel and Readiness’s Research Regulatory Oversight Office, the Office of the Assistant Secretary of Defense for Health Affairs and the Defense Health Agency’s Human Research Protection Office, and the DoD Security Office.

Measures

Data collection for the 2018 HRBS was conducted between October 22, 2018 through March 1, 2019. After providing informed consent, participants completed an anonymous web-based survey. The survey assessed measures relevant to the Total Force Fitness framework (Chairman of the Joint Chiefs of Staff, 2013) including mental health, behavioral, physical, and medical factors. Socio-demographic factors obtained from the Defense Manpower Data Center were linked to the survey responses using the unique survey ID codes.

Mental health outcomes

Posttraumatic stress disorder (PTSD) symptoms were assessed using the Primary Care PTSD screen for DSM 5 (PC-PTSD-5) (Prins et al., 2016). The first question asked whether the respondent had ever experienced a traumatic event (yes/no). Those who responded “yes” were then instructed to answer five additional items on whether specific symptoms were experienced in the past 30-days (yes/no). Responses on the five items were used to create a binary variable categorizing respondents with probable PTSD (≥3 symptoms) and those without (<3 symptoms) (Prins et al., 2016).

Suicide ideation was assessed with a single item from the National Survey on Drug Use and Health (NSDUH) (Miller et al., 2015). The item asked respondents whether they had seriously thought about trying to kill themselves in the past 12 months (yes/no).

Psychological distress was assessed using the Kessler-6 (K6) scale (Kessler et al., 2002). The six-item scale assesses the frequency of experiencing nonspecific psychological distress in the past 30-days. Responses on the six items were summed and the total score was dichotomized to categorize respondents with serious psychological distress (score of ≥13) and those without (<13) (Kessler et al., 2003).

Movement behaviors

PA was assessed using questions from the National Health and Nutrition Examination Survey (NHANES). Two questions assessed the frequency with which respondents engaged in moderate-intensity aerobic PA (MPA) and vigorous-intensity aerobic PA (VPA) in the past 30-days. Two follow-up questions assessed the typical amount of time spent per day in MPA and VPA in the past 30-days. The reported frequencies and duration were combined to estimate minutes/week in MPA and VPA. We estimated adherence to the 2018 national PA recommendations for adults (US Department of Health and Human Services, 2018), which also represent the Healthy People 2020 goal for PA: ≥150 minutes/week of MPA or ≥75 minutes/week of VPA, or an equivalent combination of moderate-to vigorous PA (MVPA). We created a binary variable categorizing respondents who met the MVPA recommendations vs. did not meet the MVPA recommendations.

Screen time was assessed with a single item asking respondents to indicate the average number of hours per day in the past 30-days they spent using a device with a screen for activities other than for work or school, similar to items from the NHANES. Although no screen time recommendations are available, one review found that more than 2 hours/day was consistently associated with increased risk of depression (Wang et al., 2019). Thus, we created a binary variable to categorize respondents who reported no/low screen time (≤2 hours/day) vs. high (>2 hours/day).

Sleep duration was assessed with a single item asking respondents to indicate the average number of hours of sleep they got over a 24-hour period, as assessed in the Behavioral Risk Factor Surveillance System (Jungquist et al., 2016), except we limited the timeframe to the past 30-days. We used the National Sleep Foundation’s recommendations for adults to create a binary variable categorizing respondents who reported meeting the sleep recommendations (7–9 hours/night) vs. short/long sleep (<7 or >9 hours/night) (Hirshkowitz et al., 2015), consistent with a previous study on psychological distress (Liu et al., 2013).

We also created a variable that indicated the combined number of positive movement behaviors reported (met MVPA recommendations, no/low screen time, and met sleep recommendations): none, some (any two behaviors), and all.

Covariates

Individual characteristics assessed include socio-demographics (i.e., self-identified gender, race/ethnicity, education, marital status, age, service branch, and pay grade); body mass index (computed using self-reported weight and height); self-rated overall physical health (ranging on a 5-point scale from “excellent” to “poor”); medication use for emotional, mental health, or substance use problems in the past 12 months (yes/no); and any tobacco use in the past month (yes/no).

Analyses

Among the variables used in the present analyses, missing data were largely due to drop-off, which occurs when a respondent stops completing the survey before they get to the end, and non-response. Data missingness due to drop-off ranged from 0–7% (with the higher percent for items toward the end of the survey) and missingness due to non-response ranged from 0–0.5%. Missing data in the survey were imputed using the mice package in R (Van Buuren & Groothuis-Oudshoorn, 2011). We specified the predictive mean matching imputation method for binary, ordinary, and continuous variables, and the polytomous regression method to impute categorical data. All statistical analyses were performed in SAS version 9.4 (SAS Institute Inc., Cary, NC). The procedure surveylogistic with the Taylor series linearization method was used to estimate standard errors that correct for the sampling design. To account for oversampling and non-response, we included analytic weights in all models.

We estimated descriptive statistics (weighted proportions or means) for the overall sample and stratified by gender. For the main analyses, we computed a series of gender-stratified logistic regression models for each binary mental health outcome. First, we examined the bivariate associations of each positive movement behavior and the combined positive movement behavior variable with probable PTSD, suicide ideation, and serious psychological distress. Multivariate models estimated the independent associations of all three positive movement behaviors, adjusting for the covariates. Separate adjusted models were conducted for the combined positive movement behavior variable.

Results

Sample characteristics

The sample was predominantly male, non-Hispanic white, young- or middle-aged, and had a high school education or less (Table 1). The prevalence of the mental health outcomes was lowest for suicide ideation (8.3%), followed by serious psychological distress (9.6%), and highest for probable PTSD (10.4%) (Table 1). Women had a higher prevalence of all three outcomes compared to men. For the movement behaviors, most of the sample (71.8%) met the MVPA recommendations, though women were less physically active than men (Table 1). Approximately a third of the sample reported no/low screen time and another third met the sleep recommendations. No differences by gender were observed for screen time or sleep. About three-fourths of the sample reported at least two positive movement behaviors, only 9.9% reported all three.

Table 1.

Weighted characteristics of the active component sample

  Men
 Women
 Overall
Characteristic Weighted % (95% CI) Weighted % (95% CI) Weighted % (95% CI)
Mental health outcome      
Probable PTSD, in the past 30 days 9.6 (8.8– 10.5) 13.9 (12.5– 15.3) 10.4 (9.6– 11.1)
Suicide ideation, in the past 12 months 7.9 (7.0– 8.8) 10.1 (8.8– 11.5) 8.3 (7.5– 9.0)
Serious psychological distress, in the past 30 days 9.1 (8.1– 10.0) 12.0 (10.6– 13.4) 9.6 (8.7– 10.4)
Movement behavior      
MVPA, in the past 30 days      
Met recommendations 73.3 (72.1– 74.5) 64.3 (62.3– 66.2) 71.8 (70.8– 72.9)
Did not meet recommendations 26.7 (25.5– 27.9) 35.7 (33.8– 37.7) 28.2 (27.1– 29.2)
Screen time, in the past 30 days      
No/low 35.1 (33.8– 36.4) 34.8 (32.9– 36.6) 35.0 (33.9– 36.1)
High 64.9 (63.6– 66.2) 65.2 (63.4– 67.1) 65.0 (63.9– 66.1)
Sleep duration, in the past 30 days      
Met recommendations 34.3 (33.0– 35.6) 38.4 (36.4– 40.3) 35.0 (33.9– 36.1)
Short/long sleep 65.7 (64.4– 67.0) 61.6 (59.7– 63.6) 65.0 (63.9– 66.1)
Combined positive movement behaviorsa      
None 11.8 (10.9– 12.7) 15.4 (13.8– 17.0) 12.4 (11.6– 13.2)
Some (any two behaviors) 78.3 (77.2– 79.4) 74.8 (73.0– 76.6) 77.7 (76.8– 78.7)
All 9.9 (9.1– 10.6) 9.8 (8.7– 10.9) 9.9 (9.2– 10.5)
Individual characteristics      
Gender      
Male - - 83.3 (82.6– 84.0)
Female - - 16.7 (16.0– 17.4)
Age, years      
18–24 34.7 (33.1– 36.2) 40.2 (38.0– 42.3) 35.6 (34.3– 36.9)
25–34 41.1 (39.7– 42.4) 40.8 (38.9– 42.6) 41.0 (39.8– 42.2)
35–44 19.8 (19.0– 20.6) 15.9 (14.8– 16.9) 19.2 (18.5– 19.9)
45+ 4.4 (4.1– 4.7) 3.2 (2.7– 3.7) 4.2 (4.0– 4.5)
Race/ethnicity      
Non-Hispanic white 60.2 (58.8– 61.6) 47.1 (45.2– 49.1) 58.0 (56.8– 59.3)
Non-Hispanic black 14.7 (13.6– 15.8) 24.2 (22.2– 26.1) 16.3 (15.3– 17.3)
Hispanic 15.8 (14.7– 16.9) 17.6 (16.0– 19.2) 16.1 (15.2– 17.0)
Non-Hispanic Asian 5.6 (5.0– 6.2) 5.7 (4.9– 6.5) 5.6 (5.1– 6.1)
Other 3.7 (3.2– 4.1) 5.4 (4.5– 6.2) 3.9 (3.5– 4.4)
Education      
High school or less 65.9 (64.8– 67.1) 61.4 (59.6– 63.2) 65.2 (64.2– 66.2)
Some college 12.9 (12.2– 13.7) 13.3 (12.2– 14.4) 13.0 (12.3– 13.6)
Bachelor’s degree or more 21.2 (20.3– 22.0) 25.3 (23.9– 26.7) 21.9 (21.1– 22.6)
Marital status      
Married 55.6 (54.1– 57.0) 45.1 (43.1– 47.1) 53.8 (52.6– 55.1)
Cohabiting 7.5 (6.7– 8.4) 8.9 (7.8– 10.1) 7.8 (7.1– 8.5)
Never married 31.6 (30.1– 33.0) 34.8 (32.8– 36.9) 32.1 (30.9– 33.4)
Separated, divorced, or widowed 5.3 (4.7– 5.9) 11.1 (10.0– 12.2) 6.3 (5.7– 6.8)
Service branch      
Air force 23.3 (22.4– 24.2) 27.8 (26.4– 29.2) 24.1 (23.3– 24.9)
Army 34.8 (33.3– 36.3) 33.0 (30.9– 35.1) 34.5 (33.2– 35.8)
Marine Corps 15.1 (14.2– 16.0) 8.0 (7.1– 8.9) 13.9 (13.1– 14.7)
Navy 23.6 (22.3– 24.8) 28.3 (26.3– 30.3) 24.4 (23.3– 25.4)
Coast Guard 3.2 (3.0– 3.5) 2.9 (2.6– 3.2) 3.2 (3.0– 3.4)
Pay grade      
E1–E4 41.3 (39.8– 42.8) 48.0 (45.9– 50.0) 42.4 (41.1– 43.7)
E5–E6 30.6 (29.4– 31.8) 25.9 (24.2– 27.5) 29.8 (28.8– 30.8)
E7–W5 12.0 (11.3– 12.6) 8.1 (7.4– 8.9) 11.3 (10.8– 11.9)
O1–O3 9.8 (9.2– 10.4) 12.0 (11.1– 12.9) 10.1 (9.6– 10.7)
O4–O6 6.4 (6.1– 6.8) 6.1 (5.5– 6.6) 6.3 (6.0– 6.6)
Body mass index (kg/m2), mean 26.5 (26.4– 26.6) 25.3 (25.1– 25.4) 26.3 (26.2– 26.4)
Used medication for mental health in the past year 7.5 (6.7– 8.2) 13.4 (12.2– 14.6) 8.5 (7.8– 9.1)
Currently uses tobacco 40.4 (39.0– 41.8) 24.8 (23.0– 26.6) 37.8 (36.6– 39.0)
Self-reported overall physical health      
Excellent 15.3 (14.2– 16.4) 11.3 (10.1– 12.5) 14.6 (13.7– 15.5)
Very good 38.2 (36.9– 39.6) 35.3 (33.4– 37.2) 37.7 (36.6– 38.9)
Good 35.5 (34.2– 36.9) 39.6 (37.6– 41.6) 36.2 (35.0– 37.4)
Fair 9.2 (8.4– 10.1) 12.2 (10.8– 13.5) 9.7 (9.0– 10.5)
Poor 1.7 (1.3– 2.2) 1.7 (1.0– 2.3) 1.7 (1.4– 2.1)
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CI = Confidence Interval. MVPA = moderate-to vigorous-physical activity. PTSD = posttraumatic stress disorder.

aTotal number of movement behaviors reported at the recommended or healthy levels (met MVPA recommendations, no/low screen time, and met sleep recommendations).

Bivariate associations between the movement behaviors and mental health outcomes

Correlations among the movement behaviors and mental health variables are presented as supplementary tables (Appendices A, B). Bivariate models showed that for both men and women, the positive movement behaviors were each associated with reduced odds of the mental health outcomes, except probable PTSD (Appendix C). Further, men and women who reported some or all positive movement behaviors had lower odds of all three mental health outcomes than those who reported none (Appendix C).

Multivariate associations between the movement behaviors and mental health outcomes

For both men and women, the multivariate models with all three movement behaviors showed consistent inverse associations between meeting the sleep recommendations and each mental health outcome, independent of MVPA and screen time (Table 2; full model shown in Appendix D). Compared to those who reported short/long sleep, those who met the sleep recommendations had a significantly lower odds of probable PTSD [men: OR = 0.24, 95% CI: 0.19–0.32; women: OR = 0.53, 95% CI: 0.39–0.72]; suicide ideation [men: OR = 0.37, 95% CI: 0.27–0.52; women: OR = 0.60, 95% CI: 0.40–0.90]; and serious psychological distress [men: 0.35, 95% CI: 0.25–0.49; women: OR = 0.30, 95% CI: 0.19–0.46]. No/low screen time was associated with reduced odds of suicide ideation only among women (OR = 0.66, 95% CI: 0.45–0.95). Meeting the MVPA recommendations was associated with reduced odds of serious psychological distress only among men (OR = 0.76, 95% CI: 0.58–1.00).

Table 2.

Multivariate associationsa between the movement behaviors and mental health outcomes among active component service members, by gender

Movement behavior Probable posttraumatic stress disorder, in the past 30 days
 Suicide ideation, in the past 12 months
 Serious psychological distress, in the past 30 days
Men
 Women
 Men
 Women
 Men
 Women
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Met MVPA recommendations (ref: did not meet) 0.99 (0.79– 1.25) 1.00 (0.77– 1.29) 0.95 (0.72– 1.25) 0.91 (0.63– 1.33) 0.76 (0.58– 1.00) 0.85 (0.61– 1.20)
No/low screen time (ref: high) 1.03 (0.84– 1.26) 0.99 (0.74– 1.31) 0.83 (0.63– 1.09) 0.66 (0.45– 0.95) 0.83 (0.63– 1.08) 0.85 (0.60– 1.20)
Met sleep recommendations (ref: short/long sleep) 0.24 (0.19– 0.32) 0.53 (0.39– 0.72) 0.37 (0.27– 0.52) 0.60 (0.40– 0.90) 0.35 (0.25– 0.49) 0.30 (0.19– 0.46)
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Bolded values are statistically significant (p < .05). CI = Confidence Interval. MVPA = moderate-to vigorous-physical activity. OR = Odds Ratio.

aAdjusted for age, race/ethnicity, education, marital status, service branch, pay grade, BMI, past-year medication use for mental health, current tobacco use, and self-reported overall physical health.

The multivariate models with the combined positive movement behavior variable showed that men and women who reported some or all three positive behaviors had a lower odds of each mental health outcome than those who reported none, with one exception – probable PTSD in women (Table 3; full model shown in Appendix E). The odds were lowest for those reporting all three positive movement behaviors. We also conducted separate analyses comparing those reporting all three positive movement behaviors with those reporting some (reference) (Appendix F). Results showed that reporting all three behaviors at recommended/healthy levels compared to some was associated with a lower odds of each outcome among men. In contrast, among women, those who reported all three behaviors at recommended/healthy levels compared to some did not differ significantly in their mental health outcomes.

Table 3.

Multivariate associationsa between the combination of positive movement behaviorsb and mental health outcomes among active component service members, by gender

  Probable posttraumatic stress disorder, in the past 30 days
 Suicide ideation, in the past 12 months
 Serious psychological distress, in the past 30 days
  Men
 Women
 Men
 Women
 Men
 Women
  OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
None Ref Ref Ref Ref Ref Ref
Some 0.71 (0.53– 0.95) 0.77 (0.56– 1.05) 0.63 (0.46– 0.87) 0.60 (0.38– 0.95) 0.58 (0.42– 0.79) 0.51 (0.34– 0.77)
All 0.32 (0.20– 0.51) 0.66 (0.32– 1.37) 0.30 (0.15– 0.60) 0.34 (0.12– 0.97) 0.11 (0.05– 0.22) 0.35 (0.11– 1.06)
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Bolded values are statistically significant (p < .05). CI = Confidence Interval. MVPA = moderate-to vigorous-physical activity. OR = Odds Ratio.

aAdjusted for age, race/ethnicity, education, marital status, service branch, pay grade, BMI, past-year medication use for mental health, current tobacco use, and self-reported overall physical health.

bTotal number of movement behaviors reported at the recommended or healthy levels (met MVPA recommendations, no/low screen time, and met sleep recommendations).

Discussion

This is one of the first studies to examine the independent and combined associations of multiple movement behaviors (MVPA, screen time, and sleep duration) with mental health outcomes in a US military sample. Findings showed that among active component service men and women, sleep duration was the most consistent correlate of all three mental health outcomes (probable PTSD, suicide ideation, serious psychological distress), independent of MVPA and screen time. Unexpectedly, few associations were found for MVPA and screen time. We also found that those who reported some or all movement behaviors at recommended/healthy levels (vs. none) had a lower odds of each mental health outcome. The odds of each outcome were lowest for those reporting all three behaviors at recommended/healthy levels, suggesting a possible dose-response relationship.

Overall, the prevalence of mental health problems in our sample was high, particularly when compared to the prevalence reported in other studies with the general adult population. For example, the prevalence of suicide ideation was 8.3% in our sample but only 4.3% in the NSDUH (Substance Abuse and Mental Health Services Administration, 2019). Consistent with those other studies, we found a higher prevalence of mental health problems in women compared to men.

Other studies have also shown a higher prevalence of mental health problems in military service members, particularly women, compared to the general population (Crum-Cianflone et al., 2016; Kessler et al., 2014; Nock et al., 2014). Military members can experience more severe stressors, such as combat exposure during deployment, than civilians, which can contribute to their excess burden of mental health problems. The observed gender differences may be explained by differences in exposure to different types of stressors and reactions to those stressors, gender-based discrimination, sexual harassment and assault, and social support, among other factors (Hourani et al., 2015, 2016; Luxton et al., 2010). Although our study did not examine these other risk factors, they may be critical drivers of the observed gender differences in mental health outcomes.

Findings from the multivariate model with all three movement behaviors showed that meeting the sleep recommendations was consistently associated with reduced odds of probable PTSD, suicide ideation, and serious psychological distress compared to short/long sleep, independent of MVPA and screen time. These associations were statistically significant across men and women. In contrast to our finding, a different study among Canadian adults found that relative to other movement behaviors (PA and sedentary time), time spent sleeping was not associated with a self-report general mental health measure (McGregor et al., 2018). However, a different study among trauma-exposed individuals found that poor sleep quality was positively associated with PTSD symptom severity, independent of PA and sitting time (Mason et al., 2019). Overall, our finding suggests that meeting the sleep recommendations is one of the most important correlates of mental health problems among active component service men and women, independent of their MVPA or screen time.

Although previous studies have shown that aerobic PA is related to a lower risk of mental health problems (Fluetsch et al., 2019; Vancampfort et al., 2018; White et al., 2017) and sedentary time is related to a higher risk (Huang et al., 2020; Mason et al., 2019), those studies were limited to one movement behavior. When we modeled all three movement behaviors, we found few significant associations for MVPA and screen time.

Our findings showed that meeting the MVPA recommendations was associated with reduced odds of serious psychological distress, independent of screen time and sleep, only among men. In line with our finding, a study among university students found a significant inverse association between MVPA and depression, independent of sleep (sedentary time was not examined), only among men (Cahuas et al., 2019). Although women in our study reported less MVPA than men, they may have engaged in higher amounts of light-intensity PA (e.g., yoga or slow walking), which has been linked to lower psychological distress, independent of MVPA and sedentary time (Hamer et al., 2014). The HRBS did not assess light PA, thereby limiting our ability to test its associations with mental health.

Our findings also showed that no/low screen time was associated with reduced odds of suicide ideation, independent of MVPA and sleep, only among women. Similar to our finding, a study with youth reported that no/low screen time (≤2 hrs/day) was associated with reduced odds of suicide ideation in girls but not boys, independent of PA and sleep (Sampasa-Kanyinga et al., 2020). In our study, women with high screen time may have had greater exposure to negative content that increased their risk of suicide ideation, such as cyberbullying or online sexual harassment. Given the HRBS’s screen time measure was focused on duration, we were unable to examine the role of screen content. Nevertheless, a report from the DoD shows that female active duty members report higher online sexual harassment (via social media) than males (Office of People Analytics, 2019). To our knowledge, no published study has examined gender differences in online risk factors of suicide ideation among active duty members. However, evidence from other studies with the general population point to an association between exposure to online victimization and an increased odds of suicide ideation, with a stronger association in females than males (Kim et al., 2019).

Our final models showed that among both men and women, reporting some or all positive movement behaviors, compared to none, was related to reduced odds of the mental health outcomes (except probable PTSD in women). The lowest odds were in those reporting all three positive behaviors, suggesting a possible dose-response relationship. Findings from the models comparing those reporting some and all positive movement behaviors also showed that engaging in all three behaviors compared to only two may provide additional mental health benefits among men. However, for women, no additional benefit was observed for those reporting all versus some positive movement behaviors.

Only a few studies have examined how combinations of health behaviors are related to mental health outcomes (Loprinzi & Mahoney, 2014; Rayward et al., 2017; Sampasa-Kanyinga et al., 2020), though none have been conducted in military populations. Overall, those studies provide support for the mental health benefits of engaging in multiple positive movement behaviors, consistent with our findings. For example, one study that examined different combinations of sleep and PA found a significantly lower prevalence of psychological distress among the excellent sleepers/mixed activity group (i.e., slightly over half met or exceeded the PA recommendations) compared to poor sleepers (who were less physically active) (Rayward et al., 2017). That study did not include a sedentary time measure. A different study with adolescents found that those who met all three recommendations (vs. none) for PA, screen time, and sleep had reduced odds of suicide ideation (Sampasa-Kanyinga et al., 2020).

The gender difference in the association between the combined movement behavior variable and probable PTSD warrants further investigation. To our knowledge, no published study has examined the combination of movement behaviors in relation to PTSD. It is possible that men’s high MVPA may have enhanced the other movement behaviors, particularly sleep, thus providing a stronger protective effect against probable PTSD. There is evidence that MVPA is associated with favorable sleep duration and quality (Loprinzi & Cardinal, 2011; McClain et al., 2014). Thus, sleep may be playing a mediating role between MVPA and probable PTSD in men. Testing mediators was beyond the scope of this paper, but future work is needed testing the pathways by which the three movement behaviors influence one another and mental health outcomes.

Our study had several limitations. Given the cross-sectional design, causal inferences cannot be drawn from our findings. The female sample size was significantly smaller than that of males, which may have reduced power to detect associations in the female-specific models. However, the gender distribution in the 2018 HRBS is similar to that of past HRBS samples and the general armed forces population (Meadows et al., 2018; Office of the Under Secretary of Defense, 2020). Our findings are specific to active component service members and are not generalizable to the reserve component or the general US adult population.

The response rate for the 2018 HRBS was low but slightly higher than that of the 2015 HRBS (6.8% for the active component sample). We used weights in all our analyses to address potential survey and non-response bias and thereby improve the generalizability of findings to the population of survey-eligible service members. Another limitation is that our analyses relied on self-report data, which are subject to respondent bias. Objective measures such as accelerometry may produce a more accurate picture of activity at various intensities in a 24-hr period than self-report measures. Further, our sedentary time measure was limited to non-school/work screen time, but sedentary time throughout the day may have different effects.

Despite these limitations, our study had several strengths. The large sample size of the HRBS was critical for performing analyses on “rare” events, i.e., where the prevalence is <20%, and testing the gender-stratified models. The survey also included members across five services branches, which provided greater heterogeneity in population and health characteristics.

Conclusions

Overall, our findings provide support for the Total Force Fitness Framework for military readiness by showing that multiple movement behaviors (PA, screen time, and sleep) are related to the psychological fitness of active component service members. Although health behavior programs targeting individual movement behaviors are becoming increasingly available across the service branches (Baker et al., 2015; Piche et al., 2014; Troxel et al., 2015), none have tested the effects of changing multiple movement behaviors in relation to mental health. Given multiple positive movement behaviors may provide benefits beyond mental health, such as improved physical health outcomes (Chastin et al., 2015; Colley et al., 2018) and work performance (Guertler et al., 2015), service branches may consider shifting their intervention efforts from targeting individual behaviors to multiple movement behaviors. Collectively, these movement behaviors have the potential to strengthen the psychological fitness of service members as well as their overall health, well-being, and military readiness.

Appendix A. Pearson correlations among movement behaviors and mental health outcomes for women.

  Number of positive movement behaviors Probable PTSD Suicide ideation Serious psychological distress Meets MVPA recommendations No/low screen time Meets sleep recommendations
Number of positive movement behaviors (0 = none, 1 = some, 2 = all) 1 −0.12 *** −0.13 *** −0.18 *** 0.56 *** 0.49 *** 0.49 ***
Probable PTSD (score ≥3)   1 0.27 *** 0.33 *** −0.06 *** −0.02 −0.16 ***
Suicide ideation (yes)     1 0.39 *** −0.05 ** −0.07 *** −0.11 ***
Serious psychological distress (score ≥13)       1 −0.11 *** −0.05 ** −0.19 ***
Meets MVPA recommendations (yes)         1 0.03 * 0.05 **
Screen time (no/low)           1 0.02 *
Meets sleep recommendations (yes)             1
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PTSD = posttraumatic stress disorder; MVPA = moderate-to vigorous physical activity.

*** p < 0.0001

** p < 0.05

* 0.05 ≤ p < 0.10

Appendix B. Pearson correlations among movement behaviors and mental health outcomes for men.

  Number of positive movement behaviors Probable PTSD Suicide ideation Serious psychological distress Meets MVPA recommendations No/low screen time Meets sleep recommendations
Number of positive movement behaviors (0 = none, 1 = some, 2 = all) 1 −0.11 *** −0.12 *** −0.15 *** 0.55 *** 0.48 *** 0.48 ***
Probable PTSD (score ≥3)   1 0.24 *** 0.27 *** −0.05 *** −0.0007 −0.18 ***
Suicide ideation (yes)     1 0.44 *** −0.05 *** −0.06 *** −0.13 ***
Serious psychological distress (score ≥13)       1 −0.09 *** −0.06 *** −0.15 ***
Meets MVPA recommendations (yes)         1 0.01 0.02 *
Screen time (no/low)           1 0.04 ***
Meets sleep recommendations (yes)             1
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PTSD = posttraumatic stress disorder; MVPA = moderate-to vigorous physical activity.

*** p < 0.0001

** p < 0.05

* 0.05 ≤ p < 0.10

Appendix C. Bivariate associations of the individual and combined movement behaviors with each mental health outcome among active component service members, by gender.

Movement behavior Probable PTSD, in the past 30 days
 Suicide ideation, in the past 12 months
 Serious psychological distress, in the past 30 days
Men
 Women
 Men
 Women
 Men
 Women
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Met MVPA recommendations a (ref: did not meet) 0.70 (0.57– 0.86) 0.70 (0.55– 0.88) 0.66 (0.51– 0.85) 0.72 (0.53– 0.99) 0.52 (0.41– 0.65) 0.52 (0.39– 0.68)
No/low screen time b (ref: high) 1.00 (0.82– 1.21) 0.90 (0.71– 1.14) 0.60 (0.47– 0.76) 0.61 (0.43– 0.85) 0.63 (0.49– 0.80) 0.73 (0.54– 0.97)
Met sleep recommendations c (ref: short/long sleep) 0.16 (0.12– 0.21) 0.33 (0.25– 0.45) 0.25 (0.18– 0.35) 0.43 (0.29– 0.63) 0.23 (0.17– 0.32) 0.21 (0.14– 0.32)
Combined positive movement behaviors d (ref: none)            
Some (any two behaviors) 0.52 (0.40– 0.67) 0.49 (0.37– 0.65) 0.40 (0.30– 0.55) 0.45 (0.31– 0.65) 0.38 (0.29– 0.49) 0.32 (0.23– 0.44)
All 0.16 (0.10– 0.25) 0.25 (0.13– 0.47) 0.12 (0.06– 0.23) 0.18 (0.07– 0.47) 0.04 (0.02– 0.08) 0.11 (0.04– 0.30)
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Bolded values are statistically significant (p < .05). CI = Confidence Interval. MVPA = moderate-to vigorous-physical activity. OR = Odds Ratio. PTSD = posttraumatic stress disorder.

aMeeting the MVPA recommendations was defined as ≥150 minutes/week of moderate-intensity or ≥75 minutes/week of vigorous-intensity physical activity, or an equivalent combination of moderate-to vigorous-intensity physical activity.

bScreen time other than for work or school. No/low screen time was defined as ≤2 hours/day; high screen time was defined as >2 hours/day.

cMeeting the sleep recommendations was defined as 7–9 hours/night; short/long sleep was defined as <7 or >9 hours/night.

dTotal number of movement behaviors reported at the recommended or healthy levels (met MVPA recommendations, no/low screen time, and met sleep recommendations).

Appendix D. Multivariate associations between the movement behaviors and mental health outcomes among active component service members, by gender.

Variable Probable PTSD, in the past 30 days
 Suicide ideation, in the past 12 months
 Serious psychological distress, in the past 30 days
Men
 Women
 Men
 Women
 Men
 Women
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Movement behavior            
Met MVPA recommendations (ref: did not meet) 0.99 (0.79– 1.25) 1.00 (0.77– 1.29) 0.95 (0.72– 1.25) 0.91 (0.63– 1.33) 0.76 (0.58– 1.00) 0.85 (0.61– 1.20)
No/low screen time (ref: high) 1.03 (0.84– 1.26) 0.99 (0.74– 1.31) 0.83 (0.63– 1.09) 0.66 (0.45– 0.95) 0.83 (0.63– 1.08) 0.85 (0.60– 1.20)
Met sleep recommendations (ref: short/long sleep) 0.24 (0.19– 0.32) 0.53 (0.39– 0.72) 0.37 (0.27– 0.52) 0.60 (0.40– 0.90) 0.35 (0.25– 0.49) 0.30 (0.19– 0.46)
Covariates            
Age (ref: 18–24)            
25–34 1.12 (0.74– 1.69) 1.46 (1.00– 2.12) 0.92 (0.61– 1.38) 0.77 (0.50– 1.19) 1.10 (0.73– 1.65) 1.31 (0.85– 2.01)
35–44 1.56 (0.99– 2.47) 1.37 (0.85– 2.20) 0.73 (0.43– 1.23) 0.77 (0.43– 1.38) 0.74 (0.44– 1.23) 0.68 (0.38– 1.21)
45+ 2.10 (1.27– 3.47) 1.39 (0.75– 2.60) 0.54 (0.28– 1.02) 0.57 (0.25– 1.31) 0.64 (0.35– 1.17) 0.56 (0.23– 1.33)
Race/ethnicity (ref: Non-Hispanic white)
Non-Hispanic black 1.03 (0.77– 1.39) 0.94 (0.67– 1.32) 0.77 (0.53– 1.13) 0.53 (0.34– 0.83) 0.62 (0.41– 0.94) 0.72 (0.48– 1.07)
Hispanic 1.13 (0.85– 1.49) 0.82 (0.58– 1.17) 0.79 (0.54– 1.13) 0.92 (0.58– 1.46) 0.85 (0.61– 1.18) 0.87 (0.55– 1.36)
Non-Hispanic Asian 0.87 (0.57– 1.34) 0.77 (0.47– 1.27) 0.82 (0.48– 1.41) 0.45 (0.24– 0.86) 1.35 (0.89– 2.05) 0.77 (0.43– 1.35)
Other 0.98 (0.64– 1.49) 1.86 (1.13– 3.05) 1.06 (0.63– 1.76) 0.58 (0.31– 1.08) 0.77 (0.48– 1.25) 0.61 (0.34– 1.11)
Education (ref: Bachelor’s degree or more)
High school or less 1.26 (0.96– 1.64) 1.12 (0.77– 1.63) 1.03 (0.72– 1.48) 1.38 (0.86– 2.20) 1.29 (0.89– 1.85) 1.67 (0.99– 2.80)
Some college 1.16 (0.87– 1.54) 1.08 (0.73– 1.59) 1.13 (0.74– 1.73) 1.23 (0.74– 2.05) 1.23 (0.80– 1.89) 1.57 (0.92– 2.69)
Marital status (ref: Married)            
Cohabiting 1.65 (1.09– 2.48) 1.28 (0.84– 1.95) 1.62 (1.01– 2.60) 1.18 (0.69– 2.00) 1.40 (0.88– 2.21) 1.10 (0.64– 1.89)
Never married 0.79 (0.57– 1.09) 1.21 (0.89– 1.65) 1.22 (0.88– 1.69) 1.48 (0.98– 2.23) 1.26 (0.91– 1.75) 0.90 (0.61– 1.34)
Separated, divorced, or widowed 1.40 (0.99– 1.97) 1.33 (0.93– 1.91) 2.06 (1.27– 3.34) 1.64 (1.01– 2.65) 2.19 (1.43– 3.36) 1.02 (0.66– 1.58)
Service branch (ref: Army)            
Air force 0.60 (0.47– 0.78) 0.70 (0.51– 0.96) 0.77 (0.55– 1.07) 0.41 (0.28– 0.62) 0.58 (0.42– 0.81) 0.46 (0.31– 0.68)
Marine Corps 1.20 (0.87– 1.65) 1.96 (1.26– 3.04) 1.13 (0.77– 1.66) 0.79 (0.47– 1.34) 1.27 (0.89– 1.82) 1.11 (0.65– 1.92)
Navy 0.86 (0.64– 1.16) 1.13 (0.76– 1.67) 1.40 (0.96– 2.03) 0.81 (0.49– 1.34) 1.26 (0.88– 1.81) 1.20 (0.77– 1.88)
Coast Guard 0.58 (0.40– 0.83) 0.99 (0.64– 1.52) 0.70 (0.42– 1.16) 0.56 (0.25– 1.23) 0.79 (0.50– 1.26) 0.64 (0.37– 1.09)
Pay grade (ref: E1-E4)            
E5–E6 1.22 (0.84– 1.77) 1.03 (0.70– 1.51) 0.58 (0.40– 0.85) 0.86 (0.54– 1.37) 0.68 (0.47– 0.98) 0.66 (0.44– 1.00)
E7–W5 1.66 (1.10– 2.50) 1.41 (0.88– 2.26) 0.56 (0.35– 0.89) 0.39 (0.20– 0.77) 0.46 (0.29– 0.73) 0.70 (0.38– 1.27)
O1–O3 0.84 (0.53– 1.35) 0.71 (0.43– 1.17) 0.63 (0.39– 1.00) 1.32 (0.77– 2.26) 0.80 (0.48– 1.34) 0.93 (0.51– 1.66)
O4–O6 1.26 (0.78– 2.05) 0.64 (0.35– 1.15) 0.48 (0.27– 0.86) 0.54 (0.25– 1.18) 0.58 (0.32– 1.04) 0.46 (0.21– 1.01)
BMI (kg/m2) 1.01 (0.98– 1.04) 1.00 (0.96– 1.03) 1.01 (0.98– 1.05) 1.01 (0.96– 1.07) 0.98 (0.95– 1.02) 1.03 (0.98– 1.08)
Used medication for mental health in the past year (ref: no) 4.39 (3.40– 5.67) 4.52 (3.43– 5.94) 4.68 (3.38– 6.49) 4.86 (3.49– 6.77) 5.06 (3.71– 6.89) 5.42 (3.94– 7.46)
Currently uses tobacco (ref: no) 1.28 (1.04– 1.57) 1.85 (1.42– 2.42) 1.64 (1.29– 2.10) 1.55 (1.09– 2.21) 1.21 (0.95– 1.54) 1.55 (1.11– 2.16)
Self-reported overall physical health 1.69 (1.47– 1.95) 1.55 (1.33– 1.80) 1.50 (1.28– 1.76) 1.29 (1.05– 1.60) 2.13 (1.81– 2.51) 2.16 (1.75– 2.67)
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Bolded values are statistically significant (p < .05). CI = Confidence Interval. MVPA = moderate-to vigorous-physical activity. OR = Odds Ratio. PTSD = posttraumatic stress disorder.

Appendix E. Multivariate associations between the combination of positive movement behaviors a and mental health outcomes among active component service members, by gender.

  Probable PTSD, in the past 30 days
 Suicide ideation, in the past 12 months
 Serious psychological distress, in the past 30 days
  Men
 Women
 Men
 Women
 Men
 Women
Variable OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Combined positive movement behaviors a (ref: none)
Some 0.71 (0.53– 0.95) 0.77 (0.56– 1.05) 0.63 (0.46– 0.87) 0.60 (0.38– 0.95) 0.58 (0.42– 0.79) 0.51 (0.34– 0.77)
All 0.32 (0.20– 0.51) 0.66 (0.32– 1.37) 0.30 (0.15– 0.60) 0.34 (0.12– 0.97) 0.11 (0.05– 0.22) 0.35 (0.11– 1.06)
Covariates
Age (ref: 18–24)            
25–34 1.15 (0.76– 1.74) 1.46 (1.00– 2.13) 0.91 (0.61– 1.37) 0.77 (0.49– 1.19) 1.12 (0.75– 1.68) 1.36 (0.89– 2.08)
35–44 1.65 (1.04– 2.62) 1.41 (0.87– 2.26) 0.75 (0.44– 1.25) 0.73 (0.41– 1.32) 0.77 (0.46– 1.28) 0.71 (0.40– 1.26)
45+ 2.18 (1.32– 3.60) 1.43 (0.77– 2.68) 0.55 (0.29– 1.03) 0.55 (0.24– 1.26) 0.67 (0.36– 1.22) 0.60 (0.25– 1.43)
Race/ethnicity (ref: Non-Hispanic white)
Non-Hispanic black 1.07 (0.79– 1.45) 0.96 (0.68– 1.36) 0.80 (0.54– 1.17) 0.54 (0.34– 0.86) 0.64 (0.42– 0.96) 0.75 (0.50– 1.12)
Hispanic 1.11 (0.84– 1.48) 0.84 (0.59– 1.20) 0.77 (0.53– 1.12) 0.95 (0.60– 1.49) 0.82 (0.59– 1.15) 0.92 (0.60– 1.40)
Non-Hispanic Asian 0.88 (0.58– 1.33) 0.78 (0.47– 1.28) 0.82 (0.48– 1.40) 0.47 (0.24– 0.90) 1.32 (0.87– 2.00) 0.75 (0.42– 1.35)
Other 1.01 (0.67– 1.53) 1.88 (1.17– 3.02) 1.11 (0.67– 1.85) 0.59 (0.32– 1.09) 0.83 (0.52– 1.33) 0.62 (0.34– 1.13)
Education (ref: Bachelor’s degree or more)
High school or less 1.29 (0.99– 1.68) 1.14 (0.78– 1.66) 1.06 (0.74– 1.52) 1.37 (0.86– 2.19) 1.31 (0.91– 1.87) 1.69 (1.02– 2.80)
Some college 1.15 (0.87– 1.53) 1.09 (0.74– 1.61) 1.14 (0.74– 1.74) 1.21 (0.73– 2.01) 1.22 (0.80– 1.87) 1.57 (0.93– 2.65)
Marital status (ref: Married)            
Cohabiting 1.64 (1.09– 2.46) 1.26 (0.83– 1.92) 1.63 (1.02– 2.62) 1.19 (0.70– 2.02) 1.41 (0.89– 2.22) 1.09 (0.65– 1.84)
Never married 0.75 (0.54– 1.03) 1.21 (0.89– 1.64) 1.17 (0.85– 1.62) 1.48 (0.99– 2.23) 1.20 (0.87– 1.66) 0.91 (0.62– 1.34)
Separated, divorced, or widowed 1.42 (1.01– 1.98) 1.42 (0.99– 2.02) 2.11 (1.29– 3.46) 1.75 (1.09– 2.83) 2.27 (1.47– 3.49) 1.18 (0.77– 1.81)
Service branch (ref: Army)            
Air force 0.55 (0.42– 0.71) 0.67 (0.49– 0.93) 0.69 (0.50– 0.96) 0.40 (0.27– 0.60) 0.54 (0.39– 0.74) 0.44 (0.30– 0.64)
Marine Corps 1.20 (0.87– 1.64) 2.03 (1.31– 3.13) 1.11 (0.75– 1.63) 0.83 (0.49– 1.38) 1.26 (0.88– 1.80) 1.21 (0.71– 2.05)
Navy 0.82 (0.61– 1.11) 1.10 (0.74– 1.63) 1.32 (0.91– 1.92) 0.77 (0.47– 1.27) 1.22 (0.85– 1.75) 1.15 (0.75– 1.78)
Coast Guard 0.51 (0.36– 0.74) 0.94 (0.61– 1.44) 0.61 (0.37– 1.01) 0.53 (0.24– 1.18) 0.72 (0.45– 1.14) 0.59 (0.35– 1.00)
Pay grade (ref: E1-E4)            
E5–E6 1.23 (0.85– 1.78) 1.06 (0.72– 1.55) 0.58 (0.40– 0.85) 0.87 (0.54– 1.39) 0.68 (0.47– 0.98) 0.68 (0.44– 1.03)
E7–W5 1.69 (1.13– 2.54) 1.45 (0.90– 2.33) 0.56 (0.35– 0.89) 0.41 (0.21– 0.80) 0.46 (0.29– 0.74) 0.72 (0.39– 1.33)
O1–O3 0.80 (0.51– 1.28) 0.73 (0.44– 1.20) 0.59 (0.38– 0.94) 1.31 (0.76– 2.25) 0.77 (0.46– 1.26) 0.93 (0.52– 1.68)
O4–O6 1.23 (0.77– 1.98) 0.64 (0.35– 1.15) 0.46 (0.26– 0.81) 0.54 (0.25– 1.17) 0.56 (0.31– 1.00) 0.45 (0.21– 0.99)
BMI (kg/m2) 1.01 (0.98– 1.04) 1.00 (0.97– 1.04) 1.01 (0.98– 1.05) 1.02 (0.97– 1.07) 0.98 (0.95– 1.02) 1.04 (0.99– 1.09)
Used medication for mental health in the past year (ref: no) 4.37 (3.38– 5.64) 4.70 (3.59– 6.16) 4.71 (3.42– 6.49) 4.89 (3.52– 6.80) 5.12 (3.78– 6.95) 5.80 (4.25– 7.91)
Currently uses tobacco (ref: no) 1.34 (1.09– 1.64) 1.90 (1.46– 2.48) 1.72 (1.35– 2.19) 1.57 (1.11– 2.24) 1.27 (1.00– 1.61) 1.62 (1.16– 2.25)
Self-reported overall physical health 1.74 (1.52– 1.99) 1.56 (1.35– 1.82) 1.52 (1.29– 1.78) 1.27 (1.03– 1.56) 2.18 (1.85– 2.56) 2.17 (1.77– 2.66)
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Note. Bolded values are statistically significant (p < .05). CI = Confidence Interval. MVPA = moderate-to vigorous-physical activity. OR = Odds Ratio. PTSD = posttraumatic stress disorder.

aTotal number of movement behaviors reported at the recommended or healthy levels (met MVPA recommendations, no/low screen time, and met sleep recommendations).

Appendix F. Multivariate associations a between the combination of positive movement behaviors b and mental health outcomes among active component service members, by gender.

  Probable PTSD, in the past 30 days
 Suicide ideation, in the past 12 months
 Serious psychological distress, in the past 30 days
  Men
 Women
 Men
 Women
 Men
 Women
Variable OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Combined positive movement behaviors b (ref: some)
None 1.40 (1.05– 1.87) 1.31 (0.95– 1.80) 1.59 (1.15– 2.20) 1.67 (1.05– 2.65) 1.72 (1.26– 2.36) 1.95 (1.31– 2.91)
All 0.45 (0.30– 0.66) 0.87 (0.45– 1.68) 0.48 (0.25– 0.90) 0.57 (0.22– 1.45) 0.18 (0.09– 0.36) 0.68 (0.23– 1.99)
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Bolded values are statistically significant (p < .05). CI = Confidence Interval. MVPA = moderate-to vigorous-physical activity. OR = Odds Ratio. PTSD = posttraumatic stress disorder.

aAdjusted for age, race/ethnicity, education, marital status, service branch, pay grade, BMI, past-year medication use for mental health, current tobacco use, and self-reported overall physical health.

bTotal number of movement behaviors reported at the recommended or healthy levels (met MVPA recommendations, no/low screen time, and met sleep recommendations).

Funding Statement

This work was sponsored by the Office of the Secretary of Defense and conducted within the Forces and Resource Policy Center of the RAND National Security Research Division (NSRD), which operates the RAND National Defense Research Institute (NDRI), a federally funded research and development center (FFRDC) sponsored by the Office of the Secretary of Defense, the Joint Staff, the Unified Combatant Commands, the Navy, the Marine Corps, the defense agencies, and the defense intelligence enterprise.

Disclosure statement

The authors have no relevant financial or non-financial interests to disclose.

Data availability

The analyses were based on a secondary data analysis of the Department of Defense’s 2018 Health Related Behaviors Survey (HRBS), a confidential survey of active and reserve component service members. Authors were responsible for collecting the data and obtained the HRBS dataset via a data use agreement with the Defense Health Agency. Data are available upon request and with permission of the Defense Health Agency.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The analyses were based on a secondary data analysis of the Department of Defense’s 2018 Health Related Behaviors Survey (HRBS), a confidential survey of active and reserve component service members. Authors were responsible for collecting the data and obtained the HRBS dataset via a data use agreement with the Defense Health Agency. Data are available upon request and with permission of the Defense Health Agency.

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