Letters

Table 2. Mean Sedentary Behavior Among Women in the Women's Health Study, 2011-2013 Sedentary Behavior, Mean (SD)a Bout Duration, min

No. of Bouts/d

Bouts, %

>1

85.9 (16.1)

100

≥5

29.8 (4.7)

35.5 (6.7)

≥10

15.9 (3.2)

19.4 (5.9)

65.5 (10.1)

≥20

7.0 (2.2)

8.7 (4.1)

44.5 (12.5)

≥30

3.8 (1.6)

4.8 (2.9)

31.5 (12.4)

≥40

2.2 (1.2)

2.9 (2.1)

22.7 (11.3)

≥50

1.4 (0.9)

1.8 (1.6)

16.5 (10.0)

≥60

0.9 (0.7)

1.2 (1.2)

11.9 (8.6)

time spent in sedentary behavior was 65.5% (9.0%), equivalent to a mean (SD) of 9.7 (1.5) hours per day (Table 1). The mean (SD) number of sedentary bouts per day was 85.9 (16.1), with 9.0 (2.4) breaks per sedentary hour. Adjusting for wear time and smoking status, total sedentary time increased and the number of bouts and breaks per sedentary hour decreased as age and BMI increased (P < .001). Most sedentary time occurred in bouts of shorter duration (Table 2). Among the total number of sedentary bouts, the mean (SD) percentage of bouts of at least 30 minutes was 4.8% (2.9%), representing 31.5% (12.4%) of total sedentary time. Discussion | This study provides a detailed analysis of sedentary behavior patterns among a large sample of older women, more than 6 times the size of previous similar studies.6 We found that older women spent about two-thirds of waking time in sedentary behavior, most of which occurred in bouts lasting less than 30 minutes. Previous studies have shown a similar proportion of time spent in sedentary behavior; however, these did not report on patterns.4,6 Even though accelerometers provide objective measures, they cannot convey postural information (ie, sitting vs standing). However, these older women are unlikely to be standing still for long periods. These data are limited to women from the Women’s Health Study, who are primarily white and of higher socioeconomic status; however, total sedentary time was similar to a national sample.4 If future studies confirm the health hazards of sedentary behavior and guidelines are warranted, these data may be useful to inform recommendations on how to improve such behavior. Eric J. Shiroma, MEd, MS Patty S. Freedson, PhD Stewart G. Trost, PhD I-Min Lee, MBBS, ScD

Sedentary Time, % 100 81.6 (6.4)

a

A bout of sedentary behavior is defined as consecutive minutes recorded on the accelerometer in which counts per minute was less than 100.

Study concept and design: Shiroma, Freedson, Lee. Acquisition of data: Shiroma, Lee. Analysis and interpretation of data: All authors. Drafting of the manuscript: Shiroma, Trost, Lee. Critical revision of the manuscript for important intellectual content: Freedson, Lee. Statistical analysis: Shiroma, Lee. Obtained funding: Lee. Administrative, technical, or material support: All authors. Study supervision: Lee. Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Drs Freedson and Trost are members of the Actigraph scientific advisory board. No other disclosures were reported. Funding/Support: This research was supported by research grants CA154647, CA047988, CA121005, HL099557, HL043851, HL080467, HL099355, and HL007575 from the National Institutes of Health. Role of the Sponsor: The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Additional Contributions: We are grateful to the staff of the Women’s Health Study (Brigham and Women’s Hospital), particularly Ara Sarkissian, MM, Bonnie Church, BA, Colby Smith, and Jane Jones, MEd. None of the persons named were compensated. 1. Thorp AA, Owen N, Neuhaus M, Dunstan DW. Sedentary behaviors and subsequent health outcomes in adults a systematic review of longitudinal studies, 1996-2011. Am J Prev Med. 2011;41(2):207-215. 2. Ridker PM, Cook NR, Lee IM, et al. A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. N Engl J Med. 2005;352(13):1293-1304. 3. Choi L, Liu Z, Matthews CE, Buchowski MS. Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc. 2011;43(2):357-364. 4. Matthews CE, George SM, Moore SC, et al. Amount of time spent in sedentary behaviors and cause-specific mortality in US adults. Am J Clin Nutr. 2012;95(2):437-445. 5. Tudor-Locke C, Camhi SM, Troiano RP. A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003-2006. Prev Chronic Dis. 2012;9:113.

Author Affiliations: Harvard School of Public Health, Boston, Massachusetts (Shiroma); University of Massachusetts, Amherst (Freedson); University of Queensland, Brisbane, Australia (Trost); Harvard Medical School, Boston, Massachusetts (Lee). Corresponding Author: Eric J. Shiroma, MEd, MS, Harvard School of Public Health, 900 Commonwealth Ave, Third Floor, Boston, MA 02215 (ericshiroma @mail.harvard.edu). Author Contributions: Mr Shiroma and Dr Lee had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

6. Arnardottir NY, Koster A, Van Domelen DR, et al. Objective measurements of daily physical activity patterns and sedentary behaviour in older adults: Age, Gene/Environment Susceptibility-Reykjavik Study. Age Ageing. 2013;42(2):222-229.

COMMENT & RESPONSE

Suicides Among Military Personnel To the Editor The study by Ms LeardMann and colleagues1 evaluated 83 suicides occurring among 151 560 military personnel over 707 493 person-years for predictors of suicide risk.

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The Millennium Cohort Study (MCS), on which the analysis of LeardMann et al was based, is not a representative sample of recent US military personnel and has a significant sampling bias relative to risk factors for suicide. Phase 1 had a 36% response rate and its enrollees “were demographically older, more educated, married, and in the officer ranks, compared with individuals in the invited sample or the military population at large.”2 Of the approximately 350 000 personnel invited to enroll in phases 2 and 3, only 21% and 22% enrolled, respectively. Compared with invitees, enrollees in phases 2 and 3 had 77% to 91% higher odds of being female and 57% to 90% higher odds of being in noncombat military specialties.3 In contrast to the negative finding of LeardMann et al,1 a population study examining 255 suicides among Army personnel occurring over 1 million person-years of active duty follow-up during 2007-2008 found a 30% increased risk of suicide among soldiers who had deployed.4 Neither the discussion by LeardMann et al nor the accompanying Editorial5 cited this relevant study. Although the unique role of deployment exposures and of deployment-related mental disorders in contributing to risk of suicide requires further investigation, the possibility cannot be excluded that the failure of LeardMann et al1 to find an association between deployment and suicide in their study is accounted for by sampling bias. This possibility seems particularly likely given that in phases 2 and 3 of the MCS, “[m]ental disorders and hospitalization for more than two days within the past year were associated with reduced odds of enrollment,”3 and that the earlier population study found that 50% of suicides had a previous ambulatory visit for a mental health disorder and 17% had a prior hospitalization during the study period.4 Even though the study by LeardMann et al has internal validity, caution is warranted in generalizing its conclusions to recent US military populations because a substantial proportion of male combat personnel with prior hospitalization and diagnosed mental health problems were excluded. Remington L. Nevin, MD, MPH Elspeth Cameron Ritchie, MD, MPH Author Affiliations: Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (Nevin); District of Columbia Department of Mental Health, Washington, DC (Ritchie). Corresponding Author: Remington L. Nevin, MD, MPH, Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, Room 782, Baltimore, MD 21205 ([email protected]). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Nevin reported receiving consulting fees from attorneys representing clients alleging harm from their exposure to the antimalarial drug mefloquine; being retained as an expert witness in criminal and civil cases involving civilians and military personnel exposed to the drug, including a case of suicide in the US Marine Corps; being employed by the US Army; receiving a grant from the US Army to study suicides and mefloquine; and receiving travel expenses from the James Kirk Bernard Foundation to attend a suicide risk conference. Dr Ritchie reported being retired from the US Army.

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3. Horton JL, Jacobson IG, Littman AJ, Alcaraz JE, Smith B, Crum-Cianflone NF. The impact of deployment experience and prior healthcare utilization on enrollment in a large military cohort study. BMC Med Res Methodol. 2013;13(1):90. 4. Bachynski KE, Canham-Chervak M, Black SA, Dada EO, Millikan AM, Jones BH. Mental health risk factors for suicides in the US Army, 2007--8. Inj Prev. 2012;18(6):405-412. 5. Engel CC. Suicide, mental disorders, and the US military: time to focus on mental health service delivery. JAMA. 2013;310(5):484-485.

To the Editor The findings of the study reporting that deployment-related factors were not related to death by suicide among current and former US military personnel1 converge with those of previous studies,2,3 although the large sample, primary outcome of suicide death, and longitudinal design used by Ms LeardMann and colleagues address the limitations of the earlier studies. Although we agree with the study’s primary conclusions, it is important to keep in mind several limitations that were not addressed by the authors. Recent findings indicate traumatic brain injury (TBI), especially multiple TBIs, is a significant risk factor for suicidal ideation among deployed military personnel.4 Although TBIs are not incurred only when service members are deployed, many service members who have deployed to Iraq or Afghanistan have sustained 1 or more TBIs while deployed, making TBI a particularly important deployment-related risk factor. Unfortunately, LeardMann et al1 did not include this variable in their analyses. Similarly, LeardMann et al did not consider potential moderators of the relationship between deployment or combat and suicide. A recent study suggests the possibility of a moderating effect of age.5 Specifically, studies conducted with relatively younger samples of military personnel (mean age 30 years) tend to report larger effects. Combat exposure may therefore be a risk factor for older, but not younger, military personnel and veterans, which may suggest a delayed effect of deployment or combat that extends beyond the length of time considered in the study by LeardMann et al.1 We agree with the primary conclusion of LeardMann et al that early identification and treatment of psychiatric disorders among military personnel and veterans is an important part of suicide prevention in this population. However, the relationship of deployment-related variables with suicide risk is likely much more complex than what was considered. Research focused on identifying moderators of deploymentrelated variables is needed if understanding of military suicide is to advance. The question that should therefore be asked is not, “Is deployment related to suicide?” but rather, “For whom and under what circumstances is deployment related to suicide risk?” Craig J. Bryan, PsyD Tracy A. Clemans, PsyD

1. LeardMann CA, Powell TM, Smith TC, et al. Risk factors associated with suicide in current and former US military personnel. JAMA. 2013;310(5): 496-506.

Author Affiliations: National Center for Veterans Studies, Salt Lake City, Utah.

2. Ryan MA, Smith TC, Smith B, et al. Millennium Cohort: enrollment begins a 21-year contribution to understanding the impact of military service. J Clin Epidemiol. 2007;60(2):181-191.

Corresponding Author: Craig J. Bryan, PsyD, National Center for Veterans Studies, 260 S Central Campus Dr, Room 205, Salt Lake City, UT 84112 (craig [email protected]).

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ployed compared with those who did not deploy, this difference was not statistically significant (relative risk, 1.3; 95% CI, 1.0-1.7). The authors concluded that the increase in suicides paralleled an increase in mental disorder prevalence, mirroring our findings. Furthermore, the study did not control for covariates, particularly mental disorders. Suicidal behavior is extremely complex, and we agree with Drs Bryan and Clemans that other unmeasured factors may influence risk. It is important not to misinterpret our findings as suggesting that the conflicts in Iraq and Afghanistan have had no cumulative effect. Since 2005, suicide incidence in the Army increased just as sharply among soldiers who did not deploy as those who did. This corresponded to a steep increase in mental disorders in the military population overall, likely a product of intense wartime demands affecting soldiers throughout all phases of the deployment cycle. The aggregate research indicates that individuals who develop mental disorders following deployment or other military stressors unrelated to deployment will be at higher risk for suicide than individuals relatively less affected by such stressors. We agree that TBI is an important health concern requiring further study, along with other serious injuries and chronic illnesses associated with suicidal behaviors. However, the research on deployment-related TBI has been inconsistent due to definitional problems, failure to differentiate mild TBI (concussions) from more debilitating moderate or severe TBI, lack of adequate control groups (eg, non–head-injured controls), and the life-threatening context in which combat-related concussions occur, which contributes to depression, posttraumatic stress disorder, substance abuse, complex grief, and other comorbid mental and physical health problems.4-6 With regard to potential moderators, stratification by age (

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