Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2012 Mar 7.
Published in final edited form as: Health Psychol. 2011 Oct 24;31(2):194–201. doi: 10.1037/a0025989

Post-Traumatic Stress Disorder is Associated With Poor Health Behaviors: Findings From the Heart and Soul Study

Angelica L Zen 1, Shoujun Zhao 2, Mary A Whooley 3, Beth E Cohen 4
PMCID: PMC3295904  NIHMSID: NIHMS348015  PMID: 22023435

Abstract

Objective

Posttraumatic stress disorder (PTSD) results in substantial disability, including increased risk of cardiovascular disease (CVD). Poor health behaviors are major risk factors for initial and recurrent CVD events. Therefore, this study investigated whether PTSD is associated with poor health behaviors in patients with CVD.

Method

Cross-sectional study of 1,022 men and women with CVD. PTSD was assessed with the Computerized Diagnostic Interview Schedule for DSM–IV. Physical activity, medication adherence and smoking history were determined by self-report questionnaires. Multivariate logistic and linear regression models were used to evaluate the association of PTSD with health behaviors.

Results

Of the 1,022 participants, 95 (9%) had PTSD. PTSD was associated with significantly higher rates of physical inactivity in terms of overall exercise (OR 1.6, 95% CI [1.0–2.6]; p = .049), light exercise (OR 1.7, 95% CI [1.0–2.9]; p = .045), and self-rated level of exercise compared to others of their age and sex (OR 1.8, 95% CI [1.0–3.0]; p = .047). Participants with PTSD were more likely to report medication nonadherence, including forgetting medications (OR 1.8, 95% CI [1.0–3.3]; p = .04) or skipping medications (OR 1.7, 95% CI [1.1–2.9]; p = .03). Participants with PTSD also reported a greater smoking history (β 6.4 pack years, 95% CI [1.8–10.9]; p = .006), which remained significant after adjustment for depression and income.

Conclusions

Among patients with heart disease, those with PTSD were more likely to report physical inactivity, medication nonadherence and smoking. The majority of these associations were explained by adjustment for comorbid depression and lower income.

Keywords: posttraumatic stress disorder, health behaviors, smoking, physical activity, medication adherence

Though posttraumatic stress disorder (PTSD) is an illness commonly known for its impact on mental health, it is increasingly recognized as a disorder that is associated with poor physical health as well (Heppner et al., 2009; Hoge et al., 2004; Kessler, 2000; Kross, Gries, & Curtis, 2008). Veterans with PTSD have been found to have a higher lifetime prevalence of circulatory, digestive, musculoskeletal, nervous system, respiratory and infectious diseases (Boscarino, 1996; Andersen, Wade, Possemato, Ouimette, 2010). In particular, PTSD has been shown to be a major risk factor for cardiovascular disease (CVD), with studies finding that patients with PTSD are at increased risk of myocardial infarction and CVD death (Boscarino, 2006; Kang, Bullman, & Taylor, 2006; Kubzansky, Koenen, Jones, & Eaton, 2009; Kubzansky, Koenen, Spiro, Vokonas, & Sparrow, 2007).

PTSD can impact physical health through several potential pathways. Schnurr and Green (2004) have created a conceptual framework describing psychological, biological, behavioral, and attentional mechanisms by which PTSD might lead to adverse physical health outcomes. The psychological effects of PTSD include dissociation and the development of avoidant coping strategies, which may result in delayed seeking of health care. PTSD might also act via biological mechanisms, leading to physiological changes such as excess sympathetic activity and disruption of the hypothalamic-pituitary-adrenal axis that may directly damage the cardiovascular system and cause atherosclerosis (Kubzansky & Koenen, 2009; McEwen, 2003). This study focuses on the association between PTSD and health behaviors, which plays a particularly important role in the development and progression of CVD (Whooley et al., 2008). For example, lower physical activity is one of the strongest predictors of future CVD events and death in patients with existing heart disease (Lavie, Thomas, Squires, Allison, & Milani, 2009). Medication adherence is critical for control of CVD risk factors, such as diabetes, high blood pressure, and dyslipidemia, and nonadherence predicts cardiovascular events (Gehi, Ali, Na, & Whooley, 2007). Finally, smoking causes CVD events through atherosclerosis of the coronary arteries, dyslipidemia, and increased thrombosis.

Several studies have demonstrated that patients with PTSD have increased rates of tobacco and illicit substance use, but other health behaviors have received less attention (Feldner, Babson, & Zvolensky, 2007; Jacobsen, Southwick, & Kosten, 2001). Few studies have looked at exercise patterns in patients with PTSD. Those that have been published did not compare physical activity habits of patients with PTSD to a control sample without PTSD and/or had a sample size too small to draw conclusions about the association between PTSD and exercise (Buckley, Mozley, Bedard, Dewulf, & Greif, 2004; de Assis et al., 2008). Medication adherence may also be lower in PTSD, but this has only been studied in pediatric transplant patients and patients with recent myocardial infarction (Shemesh et al., 2001; Shemesh et al., 2004). In addition, the association of PTSD with these health behaviors has not been examined in patients with stable CVD, a population at highest risk for future CVD events.

In this study, data was collected from a diverse cohort of 1,022 patients with stable CVD to investigate the association of PTSD with physical activity, medication adherence, and smoking. The hypothesis was that PTSD would be associated with a higher incidence of poor health behaviors. Understanding the association of PTSD and health behaviors can lead to new avenues to reduce CVD morbidity and mortality and improve the long-term health of the growing number of individuals living with PTSD.

Method

The Heart and Soul Study is a prospective cohort study designed to examine the association between mental health disorders and cardiovascular events in adults with stable CVD. Detailed methods of the study have been described previously (Ruo et al., 2003) and are summarized briefly below.

Participants

Participants were 1,024 adults with CVD recruited from San Francisco area hospitals and clinics, including 838 men, 186 women; 615 white, 409 other ethnicities (please see Table 1 for additional sample demographics). Participants were eligible for the study if they had a history of myocardial infarction, angiographic evidence of stenosis of 50% or greater in one or more coronary vessels, evidence of prior exercise-induced ischemia by treadmill or nuclear testing, a history of coronary revascularization, or a diagnosis of coronary artery disease documented by an internist or cardiologist. Potential participants were excluded if they had a history of myocardial infarction in the past six months (treadmill test contraindicated), they were unable to walk one block (could not complete treadmill test), or they were planning to move out of the local area within three years. Recruitment was open to non-English speaking participants, and in-person oral translation of forms and interview questions was available for those who did not identify English as their primary language. All participants spoke English, but 16 participants identified a non-English language as their primary language (nine Spanish, six Russian, and one Man-darin).

Table 1.

Characteristics of Participants With PTSD vs. Participants Without PTSD

Characteristic PTSD
(n = 95)		 No PTSD
(n = 927)		 p
Age, years 61 ± 11 67 ± 11 <.001
Male, n (%) 72 (76) 766 (83) .10
White, n (%) 54 (57) 561 (61) .48
High school education, n (%) 113 (90) 778 (87) .92
Annual income under $20,000, n (%) 64 (67) 433 (47) <.001
Regular alcohol use, n (%) 25 (26) 268 (29) .56
Myocardial infarction, n (%) 55 (58) 492 (53) .34
Depression, n (%) 58 (61) 165 (18) <.001
Medication Use
 Beta blocker, n (%) 56 (59) 536 (58) .83
 Statin, n (%) 60 (63) 595 (64) .84
 Renin-angiotensin inhibitor, n (%) 46 (48) 477 (51) .57
 Aspirin, n (%) 76 (80) 715 (77) .52
Cardiovascular risk factors
 Body mass index 29 ± 5 28 ±5 .82
 Total cholesterol, mg/dL 174 ± 35 178 ± 43 .42
 LDL cholesterol, mg/dL 102 ± 27 105 ± 34 .39
 HDL cholesterol, mg/dL 47 ± 14 46 ± 14 .58
 Systolic blood pressure, mmHg 134 ± 20 133 ± 21 .71
 Diastolic blood pressure, mmHg 75 ± 12 75 ± 11 .49
 Hemoglobin A1c 5.9 ± 1.5 6.0 ± 1.1 .48
Health behaviors
 Overall physical activity: inactive, n (%) 43 (45) 330 (35) .06
 Light exercise: inactive, n (%) 28 (29) 204 (22) .09
 Moderate exercise: inactive, n (%) 49 (52) 413 (44) .18
 Heavy exercise: inactive, n (%) 82 (85) 785 (83) .69
 Compared to others: inactive, n (%) 70 (74) 544 (59) .004
 Medication nonadherence- forgot, n (%) 17 (18) 93 (10) .02
 Medication nonadherence- skipped, n (%) 25 (26) 139 (15) .004
 Medication nonadherence- as prescribed, n (%) 10 (11) 73 (8) .37
Smoking status
 Current smoker, n (%) 32 (34) 169 (18) <.001
 Former smoker, n (%) 43 (45) 463 (50) .38
 Never smoker, n (%) 20 (21) 294 (32) .03
Mean pack years smoking 27.3 ± 22 19.9 ± 21 <.001
Open in a new tab

Note. PTSD = Post-traumatic stress disorder; LDL = Low-density lipoprotein; HDL = High-density lipoprotein.

Procedures

Outpatients with documented CVD were identified from hospital and clinic administrative databases. A total of 15,438 of these patients were mailed an invitation to participate in the study, and 2,495 responded that they would be interested. After attempting to contact the respondents by phone, 596 declined to participate and 505 could not be reached. An additional 370 met the exclusion criteria described above. The remaining 1,024 patients enrolled in the study and completed baseline examinations between September 2000 and December 2002 that included a structured psychiatric interview, a questionnaire packet, fasting blood draw, echocardiogram, and exercise treadmill test. All participants provided written informed consent after reviewing detailed consent forms and having the opportunity to ask questions of the study staff. The research protocol was approved by the institutional review boards at participating institutions. Out of the 1,024 participants who completed baseline examination, two did not complete PTSD assessments, leaving a total of 1,022 participants for this analysis.

Measures

PTSD

PTSD was evaluated with the Computerized Diagnostic Interview Schedule for DSM–IV (CDIS), a validated, computer-based interview administered by trained research personnel, (Robins, Slobodyan, Marcus, et al., 1999) which assesses PTSD based on criteria outlined in the Diagnostic and Statistical Manual IV (APA, 2000). Staff attended a 4-day CDIS training session that included observed interviews to standardize administration. The CDIS has been widely used in epidemiologic studies, has shown good sensitivity compared to gold standard clinical interviews for PTSD, and has shown good concordance among clinical and lay interviewers (Breslau, Peterson, Kessler, & Schultz, 1999; Kulka et al., 1988). In our study, the CDIS PTSD symptom questions showed good internal consistency (Cronbach’s alpha = .84). Out of the 1,022 participants, 95 were classified as having current PTSD, as they had symptoms meeting PTSD criteria in the last year.

Physical activity

Physical activity was evaluated with five-items. To evaluate overall activity, participants were asked how often in the last month they performed 15–20 minutes of exercise. Participants chose from one of the following six categories: not at all active, a little active (1–2 times per month), fairly active (3–4 times per month), quite active (1–2 times per week), very active (3–4 times per week) and extremely active (5 or more times per week). Specific types of exercise were evaluated by asking how often in the last month participants engaged in 15–20 minutes of light, moderate, or heavy exercise, with examples provided for these categories. Participants chose from one of four responses: not at all, less than once per week, 1–2 times per week, and 3 or more times per week. Finally, participants were asked to rate their physical activity levels compared to others of their age and sex. Participants rated themselves as much less active, somewhat less active, about the same, somewhat more active, or much more active. These items demonstrated good internal reliability (Cronbach’s alpha = .75).

As responses were not normally distributed and several categories had very few responses, the physical activity items were dichotomized. For the overall activity question, those who reported being not at all active or a little active were considered “inactive,” while those who were fairly active, quite active or very active were “active.” This dichotomous classification has been used in previous Heart and Soul studies and was found to be a strong, independent predictor of further CVD events (Whooley et al., 2008). In addition, those who participated not at all or less than once per week for a particular level of exercise were categorized as “inactive” for that level of activity, while all other participants were considered “active.” Finally, participants who considered themselves much less active or somewhat less active compared to others were categorized as “inactive.” To validate these classifications, we compared exercise treadmill scores in those classified as inactive versus active. We found that inactive participants had significantly lower treadmill scores, indicating worse performance (p < .001 for each of the five physical activity questions).

Medication adherence

Medication adherence was assessed with a standardized questionnaire. Participants were asked, “In the past month, how often did you forget to take one or more of your prescribed medications?” Possible responses were never, once in the last month, 2 to 3 times in the last month, about once per week, several times per week, or nearly every day. Based on prior analyses from this cohort, we defined nonadherence as forgetting to take medications once per week or more (Gehi et al., 2007). Participants were also asked “Overall, in the past month, how often did you take your medications as the doctor prescribed?” Possible responses were less than half of the time, about half of the time (50%), most of the time (75%), nearly all of the time (90%), and all of the time. As in prior analyses, nonadherence was defined as 75% of the time or less (Gehi, Haas, Pipkin, & Whooley, 2005; Gehi et al., 2007). Finally, they were asked how often they decided to skip one or more of their prescribed medications, with possible responses being never, once in the last month, 2 to 3 times in the last month, about once per week, several times per week, and nearly every day. Participants who reported skipping medications 2 to 3 times in the last month or more were classified as nonadherent. This differs from the classification of about once per week or greater as nonadherent in a prior analyses of depression and medication nonadherence as there were too few participants in the PTSD group meeting this criteria given the relatively smaller number of participants with PTSD (Gehi et al., 2005).

Smoking

To assess current smoking, participants were asked, “Do you currently smoke cigarettes?” with possible responses being yes or no. Duration of smoking was assessed by asking participants, “How many years have you or did you smoke cigarettes?” Possible responses were 0, 1-10, 11-20, 21-30, or greater than 30. Finally, participants were asked, “How many packs of cigarettes do you or did you usually smoke during those years?” Participants could choose: less than 1/2 pack per day, more than 1/2 pack per day but less than 1 pack per day, more than 1 pack per day but less than 2 packs per day, or more than 2 packs per day. Participants were divided into three categories: current smokers, former smokers, and never smokers. Mean pack years for smoking was calculated by multiplying the mean for the number of years smoked by the mean for the number of packs smoked per day.

Covariates

A self-report questionnaire was administered to all participants to determine age, sex, ethnicity, medical history, education level, and income level. Annual income level was selected from one of six categories (less than $10,000, $10,000–19,999, $20,000–29,999, $30,000–39,999, $40,000–50,000, and greater than $50,000). As several categories had fewer than 10 responses in the PTSD group, this variable was dichotomized as annual income < $20,000 versus ≥ $20,000. This cutpoint is consistent with the U.S. Census Bureau Poverty Threshold in 2000-2002, the period during which baseline interviews were conducted (U.S. Census Bureau Poverty Thresholds, 2010). To measure alcohol use, the AUDIT-C, a validated screening questionnaire, was used (Bradley, Bush, McDonell, Malone, & Fihn, 1998; Bush, Kivlahan, McDonell, Fihn, & Bradley, 1998), which had modest internal consistency in our study (Cronbach’s alpha = .65). We measured height and weight and calculated body mass index by dividing the weight in kilograms by the square of the height in meters. Fasting total, high-density lipoprotein, and low-density lipoprotein cholesterol were measured from venous blood samples (Shlipak, Ix, Bibbins-Domingo, Lin, & Whooley, 2008). Participants brought their medications to the study visit and research assistants recorded all current medications. Medications were categorized using Epocrates Rx (San Mateo, California). The CDIS was used to measure current depression, defined as meeting DSM-IV criteria for a major depressive episode. The CDIS has been previously validated with clinical interviews (Robins et al., 1999; Robins et al., 1981) and had high internal reliability in our study (Cronbach’s alpha = .95).

Statistical Analysis

Baseline differences were compared between participants with and without PTSD using t tests for continuous variables and chi-square tests for dichotomous variables. Multivariate logistic regression models were used to evaluate the association of PTSD with physical activity, medication adherence and current smoking. Adjustments were made for potentially confounding patient characteristics that were associated with PTSD at p < .20, (age and sex). Models of PTSD and physical activity were also adjusted for current smoking as this was considered a potential confounder of the association of PTSD and current physical activity. Models were not adjusted for alcohol use because there was no significant difference in alcohol use between participants with and without PTSD. All statistical tests were two-sided with α= .05. Ordinal logistic regression models were used to calculate the association of PTSD and smoking status. Ordinal logistic regression yields a single odds ratio for the association of PTSD and each combination of higher versus lower risk outcome categories (current vs. former or never smoker and current or former vs. never smoker). To analyze the association between PTSD and the mean number of smoking pack years, multivariate linear regression models adjusted for age and sex were used. To evaluate the role of depression in the association between PTSD and health behaviors, sensitivity analyses were performed, excluding patients with depression and adjusting for depression. Finally, annual household income (defined as < $20,000 vs. ≥ $20,000) was added to the models, as this differed significantly by PTSD status and could be a mechanism leading to poor health behaviors in patients with PTSD. Based on the sample size of 1,022, a two-tailed α of 0.05, and the 9% prevalence of PTSD in the sample, the study had 80% power to detect odds ratios for the health behavior outcomes of at least 1.79–2.22 given expected outcome prevalences of 10–50%. The study had 80% power to detect a beta coefficient of at least 6.4 pack years of smoking. SAS version 9.2 (SAS Institute) was used to perform all analyses.

Results

Participant Characteristics

Of the 1,022 participants, 95 (9%) had PTSD. Those with PTSD were younger and more likely to have depression (see Table 1). Participants with PTSD were more likely to be inactive, to be nonadherent to their medications, to be current smokers, and to have a more extensive smoking history. In addition, participants with PTSD were more likely to have an income under $20,000. Of the 95 participants with PTSD, the distribution of Criterion A events associated with PTSD symptoms included: seeing someone seriously injured in combat or experiencing the unexpected sudden death of a close friend or relative (15 participants for each); sexual assault by a relative (seven participants); sexual assault by a nonrelative, being held captive, tortured, or kidnapped not in combat or seeing someone seriously injured or killed not in combat (five participants for each); being wounded in combat (four participants); being diagnosed with a life-threatening illness (three participants); being involved in a serious accident or being held captive or tortured in combat (two participants for each); being mugged or threatened with a weapon, being in a natural disaster, or unexpectedly discovering a dead body (one participant for each). Twenty-eight participants reported other types of events that met trauma criteria from the CDIS PTSD module.

PTSD and Physical Activity

Participants with PTSD were significantly more likely to rate themselves as being much less active (23% vs. 14%) or somewhat less active (32% vs. 20%) than others. Similarly, participants without PTSD were more likely to rate themselves as having about the same activity (24% vs. 19%), being somewhat more active (27% vs. 17%) or being much more active (14% vs. 9%) than others. After adjustment for potential confounders, participants with PTSD were more likely to be inactive in terms of overall exercise, light exercise, and level of exercise compared to others (see Table 2), although the statistical significance was marginal. Participants with PTSD were also more likely to be inactive in terms of moderate and heavy exercise, but these differences were not statistically significant.

Table 2.

Adjusted Associations of PTSD With Poor Health Behaviors

Model 1
 Model 2
 Model 3
Health behavior OR 95% CI OR 95% CI OR 95% CI
Physical activity
 Overall: inactive 1.6 [1.0–2.6]* 1.4 [0.83–2.3] 0.99 [0.63–1.6]
 Light exercise: inactive 1.7 [1.0–2.9]* 1.6 [0.96–2.8] 0.87 [0.53–1.4]
 Moderate exercise: inactive 1.4 [0.88–2.3] 1.4 [0.83–2.3] 0.99 [0.63–1.6]
 Heavy exercise: inactive 1.3 [0.63–2.7] 1.3 [0.60–2.7] 1.2 [0.60–2.3]
 Compared to others: inactive 1.8 [1.0–3.0]* 1.5 [0.83–2.6] 0.92 [0.55–1.5]
Medication nonadherence
 Forgot to take 1.8 [1.0–3.3]* 1.4 [0.79–2.7] 0.70 [0.38–1.3]
 Skipped 1.7 [1.1–2.9]* 1.4 [0.82–2.4] 1.4 [0.80–2.3]
 Overall not taking as prescribed 1.1 [0.56–2.3] 0.89 [0.42–1.9] 0.89 [0.42–1.9]
 Smoking
 Smoking statusa 1.7 [1.1–2.5]* 1.5 [0.99–2.3] 1.6 [0.90–2.9]
 Mean pack years β = 6.4b [1.8–10.9]** β = 6.7b [2.0–11.5]** β = 6.0b [1.3–10.7]*
Open in a new tab

Note. OR = odds ratio; CI = confidence interval. Model 1: Odds ratios for physical activity were adjusted for age, sex, and current smoking. Odds ratios for medication nonadherence and smoking were adjusted for age and sex. Model 2: Includes additional adjustment for depression. Model 3: Includes additional adjustment for annual income <$20,000.

a

Smoking status (current vs. former vs. never smoker) was entered into an ordinal logistic regression model.

b

These values represent β values, not odds ratios.

*

p < .05.

**

p < .01.

PTSD and Medication Adherence

After adjusting for age and sex (see Table 2), participants with PTSD had an 80% higher odds of medication nonadherence (p = .04) and 70% higher odds of skipping medications (p = .03) but no difference in report of frequency of taking medications as prescribed.

PTSD and smoking

Participants with PTSD were significantly more likely to be current or former smokers and to have a more extensive smoking history, with 6.4 more pack-years of tobacco use (see Table 2).

Depression and income

After additional adjustment for depression, PTSD remained marginally significantly associated with greater pack years of smoking (see Table 2). After excluding the 223 participants with depression and adjusting for age and sex, PTSD remained significantly associated with overall physical in-activity, light exercise inactivity, and greater pack years of smoking (see Table 3). Following additional adjustment for income, only the associations of PTSD and greater pack years of smoking remained significant (Tables 2 and 3).

Table 3.

Adjusted Associations of PTSD With Poor Health Behaviors Excluding Participants With Depression

Model 1
 Model 2
Health behavior OR 95% CI OR 95% CI
Physical activity
 Overall: inactive 3.0 [1.4–6.4]** 0.71 [0.38–1.3]
 Light exercise: inactive 2.5 [1.2–5.4]* 0.68 [0.34–1.4]
 Moderate exercise: inactive 2.0 [0.91–4.2] 0.87 [0.47–1.5]
 Heavy exercise: inactive 1.1 [0.38–3.3] 1.1 [0.47–2.5]
 Compared to others: inactive 1.5 [0.69–3.4] 1.2 [0.64–2.2]
Medication use
 Forgot to take 2.1 [0.82–5.2] 0.61 [0.25–1.5]
 Skipped 1.4 [0.59–3.3] 1.4 [0.58–3.2]
 Overall not taking as prescribed 1.5 [0.78–3.0] 1.5 [0.77–3.0]
 Smoking
 Smoking statusa 1.6 [0.88–2.8] 1.5 [0.71–3.3]
 Mean smoking pack years β = 8.9b [1.9–15.9]** β = 8.9b [1.9–15.9]**
Open in a new tab

Note. OR = odds ratio; CI = confidence interval. Model 1: Odds ratios for physical activity were adjusted for age, sex, and current smoking. Odds ratios for medication nonadherence and smoking were adjusted for age and sex. Model 2: Includes additional adjustment for annual income < $20,000.

a

Smoking status (current vs. former vs. never smoker) was entered into an ordinal logistic regression model.

b

These values represent β values, not odds ratios.

*

p < .05.

**

p < .01.

Discussion

The findings from this study suggest that PTSD may be associated with poor health behaviors that play a role in the relationship between PTSD and increased CVD risk, but that this association may be due to other psychosocial factors. To the best knowledge of the authors, this is the only controlled study of PTSD and physical activity. A study of 826 male veterans seeking treatment at a PTSD clinic found that the majority (58%) exercised at levels below national guidelines (Buckley et al., 2004). In another uncontrolled study of 50 patients with PTSD, 52% reported being initially physically active, but only 22% remained active after developing PTSD (de Assis et al., 2008). In this study, activity levels in patients with PTSD were compared to a control sample without PTSD by examining a large, ethnically and socioeconomically diverse cohort of patients with CVD. This study showed that participants with PTSD had higher rates of inactivity, especially in terms of light exercise and that the majority of participants, with and without PTSD, exercised at rates below guidelines set forth by the American Heart Association and the American College of Sports Medicine (Haskell et al., 2007). The high rate of inactivity in these patients with a history of heart disease is concerning as studies show that exercise has substantial benefits in secondary prevention of CHD and in reducing CV morbidity and mortality (Lavie et al., 2009; O’Connor et al., 1989).

Several studies have found that patients with psychological stressors are less likely to adhere to treatment recommendations but few have examined the association of PTSD and medication adherence (Shemesh et al., 2000; Shemesh et al., 2001; Shemesh et al., 2004). In an examination of 56 patients six months after myocardial infarction, Shemesh and colleagues found those with PTSD were more likely to be nonadherent to aspirin and to be readmitted for cardiovascular problems (Shemesh et al., 2004). An earlier study in a similar group of postmyocardial infarction patients also found that those with PTSD were more likely to be nonadherent to captopril and that patients with nonadherence suffered more adverse outcomes. The association of PTSD and smoking has been more widely studied, and lifetime and current smoking rates have been found to be twice as high among patients with PTSD (Feldner et al., 2007). This study highlights the fact that even in a group of patients with existing CVD, who theoretically would have received extensive counseling about risk factor modification, PTSD was associated with medication nonadherence and greater tobacco use, behaviors that could substantially increase CVD risk (Gehi et al., 2005; Gehi et al., 2007).

The data from this study fits into Schnurr and Green’s (2004) conceptual framework describing how PTSD leads to adverse physical outcomes. Focusing on the behavioral component, these results demonstrate that patients with PTSD had both greater adoption of high risk behaviors (smoking) and lower uptake of preventive behaviors (exercise). There are several possible explanations for why patients with PTSD may show alterations in these health behaviors.

The study by de Assis et al. (2008) found that 71% of patients with PTSD reported a lack of motivation to exercise. Following the development of PTSD, an increasing number also reported fear that exercise could cause health problems. In addition, avoidance symptoms seen in PTSD, such as a sense of foreshortened future might make patients feel it is unnecessary to engage in healthful preventive behaviors. This sense of foreshortened future may also increase participation in risky behaviors like smoking. The emotional distress and hyperarousal symptoms of PTSD can also cause patients to “self-medicate” with substances like nicotine to decrease their anxiety levels (Feldner et al., 2007; Jacobsen et al., 2001). These same hyperarousal symptoms may make quitting smoking more difficult by increasing withdrawal symptoms (Jacobsen et al., 2001). Finally, the psychosocial impact of PTSD could contribute to poor health behavior patterns. Many patients with PTSD have a lower socioeconomic status, as was reflected in our study by the fact that participants with PTSD were significantly more likely to have income levels under $20,000. Economic concerns could decrease medication adherence or prevent patients from joining a gym or participating in organized sports (Kessler, 2000). Patients living in neighborhoods with lower socioeconomic status also have decreased access to safe areas for exercise (Rundle et al., 2008). In our models, income did appear to play an important role in the associations of PTSD and health behaviors. In addition to economic issues, patients with PTSD may have difficulties with interpersonal relationships that could reduce the social support that often motivates and facilitates healthy behaviors (Kessler, 2000).

The findings from this study should be interpreted in light of several limitations. First, this study sample consisted mostly of urban men with existing CVD. While this is an important group to study given their high risk for recurrent CVD events and mortality, these results may not generalize to other populations. Second, cross-sectional data was used for this study; therefore, it cannot be determined whether the association between PTSD and altered health behaviors is causal. Third, the CDIS is a validated measure of PTSD, but it does not include detailed information on the duration or severity of PTSD symptoms. Fourth, health behaviors were measured by self-report and no objective measures were available to confirm responses. Self-report of health behaviors may be inaccurate and participants may have been subject to many biases, including recall bias (Newell, Girgis, Sanson-Fisher, & Savolainen, 1999), social desirability, and demand characteristics. The findings from this study may represent differences in the perception or reporting of health behaviors, and differences in actual levels of smoking, adherence, or activity cannot be confirmed. It is possible, for example, that a patient with PTSD could report lower than actual activity levels because they view themselves as having functional limitations. In addition, measures such as physical activity levels compared to others are subjective, and a person’s view of their peers’ activity levels could be influenced by their PTSD status as well as their own exercise habits. It is somewhat reassuring that in prior studies using this cohort, self-report of medication nonadherence and physical activity were important predictors of future CVD events and mortality (Gehi et al., 2007; Whooley et al., 2008). In addition, prior studies have found that self-report is a reliable method of assessing physical activity (Ainsworth, Jacobs, & Leon, 1993; Bowles, FitzGerald, Morrow, Jackson, & Blair, 2004; Jackson, Morrow, Bowles, FitzGerald, & Blair, 2007) and medication adherence (Blumberg et al., 2005; Gehi et al., 2007). Finally, given the high rate of comorbidity between PTSD and depression, there was limited power to fully examine the independent effects of these psychiatric disorders on health behaviors.

The findings from this study support the hypothesis that poor health behaviors are associated with PTSD and may be involved in the high risk of adverse CVD events in patients with PTSD. This study highlights the importance of counseling patients with PTSD about making healthy lifestyle choices. Patients with PTSD may need targeted interventions for smoking cessation, adherence to their medication regimens, and formulation of an exercise plan. These goals are particularly important in patients with PTSD and a past history of CVD, as they are at high risk of having another adverse CVD event. Future studies should evaluate the prospective association of PTSD and health behaviors as well as further examine the potential causal mechanisms, such as depression and socioeconomic disparities, linking PTSD to poor health behaviors. In addition, studies should examine whether healthy lifestyle modifications can decrease the incidence of adverse cardiovascular events in patients with PTSD and whether they can perhaps help alleviate symptoms of PTSD itself.

Acknowledgments

Dr. Cohen was supported by NIH/NHLBI grant K23 HL 094765-01, Department of Defense/NCIRE grant DAMD17-03-1-0532, W81XWH-05-2-0094, and a grant from the Irene Perstein Foundation. The Heart and Soul Study was funded by the Department of Veterans Affairs, Washington, DC, the National Heart Lung and Blood Institute (R01 HL079235), Bethesda, MD, the American Federation for Aging Research (Paul Beeson Scholars Program), New York, NY, the Robert Wood Johnson Foundation (Faculty Scholars Program), Princeton, NJ, the Ischemia Research and Education Foundation, South San Francisco, CA, and the Nancy Kirwan Heart Research Fund, San Francisco, CA. The contents of this work are solely the responsibility of the authors and do not necessarily represent the official views of any of these funding agencies. The funding organizations were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.

Footnotes

The authors do not have any conflicts of interest.

Preliminary data for this article was presented as an abstract at the American Geriatrics Society, 2010 meeting.

Contributor Information

Angelica L. Zen, Department of Medicine, University of California, Los Angeles

Shoujun Zhao, Department of Radiology, University of California, San Francisco.

Mary A. Whooley, Section of General Internal Medicine, Department of Veterans Affairs Medical Center, San Francisco VA Medical Center, San Francisco, California and Department of Medicine University of California, San Francisco

Beth E. Cohen, Section of General Internal Medicine, Department of Veterans Affairs Medical Center, San Francisco VA Medical Center, San Francisco, California and Department of Medicine University of California, San Francisco

References

  1. Ainsworth BE, Jacobs DR, Jr., Leon AS. Validity and reliability of self-reported physical activity status: The Lipid Research Clinics questionnaire. Medicine and Science in Sports and Exercise. 1993;25:92–98. doi: 10.1249/00005768-199301000-00013. doi:10.1249/00005768-199301000-00013. [DOI] [PubMed] [Google Scholar]
  2. Andersen J, Wade M, Possemato K, Ouimette P. Association between posttraumatic stress disorder and primary care provider-diagnosed disease among Iraq and Afghanistan veterans. Psychosomatic Medicine. 2010;72:498–504. doi: 10.1097/PSY.0b013e3181d969a1. [DOI] [PubMed] [Google Scholar]
  3. APA, editor. text revision. 4th ed. American Psychiatric Association; Washington, DC: 2000. Diagnostic and Statistical Manual of Mental Disorders. [Google Scholar]
  4. Blumberg EJ, Hovell MF, Kelley NJ, Vera AY, Sipan CL, Berg JP. Self-report INH adherence measures were reliable and valid in Latino adolescents with latent tuberculosis infection. Journal of Clinical Epidemiology. 2005;58:645–648. doi: 10.1016/j.jclinepi.2004.11.022. doi:10.1016/j.j-clinepi.2004.11.022. [DOI] [PubMed] [Google Scholar]
  5. Boscarino JA. Diseases among men 20 years after exposure to severe stress: implications for clinical research and medical care. Psychosomatic Medicine. 1997;59:605–614. doi: 10.1097/00006842-199711000-00008. [DOI] [PubMed] [Google Scholar]
  6. Boscarino JA. Posttraumatic stress disorder and mortality among U.S. Army veterans 30 years after military service. Annals of Epidemiology. 2006;16:248–256. doi: 10.1016/j.annepidem.2005.03.009. doi:10.1016/j.annepidem.2005.03.009. [DOI] [PubMed] [Google Scholar]
  7. Bowles HR, FitzGerald SJ, Morrow JR, Jr., Jackson AW, Blair SN. Construct validity of self-reported historical physical activity. American Journal of Epidemiology. 2004;160:279–286. doi: 10.1093/aje/kwh209. doi: 10.1093/aje/kwh209. [DOI] [PubMed] [Google Scholar]
  8. Bradley KA, Bush KR, McDonell MB, Malone T, Fihn SD. Screening for problem drinking: Comparison of CAGE and AUDIT. Journal of General Internal Medicine. 1998;13:379–388. doi: 10.1046/j.1525-1497.1998.00118.x. doi: 10.1046/j.1525-1497.1998.00118.x. [DOI] [PubMed] [Google Scholar]
  9. Breslau N, Peterson EL, Kessler RC, Schultz LR. Short screening scale for DSM-IV posttraumatic stress disorder. American Journal of Psychiatry. 1999;156:908–911. doi: 10.1176/ajp.156.6.908. [DOI] [PubMed] [Google Scholar]
  10. Buckley TC, Mozley SL, Bedard MA, Dewulf AC, Greif J. Preventive health behaviors, health-risk behaviors, physical morbidity, and health-related role functioning impairment in veterans with post-traumatic stress disorder. Military Medicine. 2004;169:536–540. doi: 10.7205/milmed.169.7.536. [DOI] [PubMed] [Google Scholar]
  11. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Archives of Internal Medicine. 1998;158:1789–1795. doi: 10.1001/archinte.158.16.1789. doi: 10.1001/archinte.158.16.1789. [DOI] [PubMed] [Google Scholar]
  12. de Assis MA, de Mello MF, Scorza FA, Cadrobbi MP, Schooedl AF, da Silva SG, Arida RM. Evaluation of physical activity habits in patients with posttraumatic stress disorder. Clinics (Sao Paulo) 2008;63:473–478. doi: 10.1590/S1807-59322008000400010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Feldner MT, Babson KA, Zvolensky MJ. Smoking, traumatic event exposure, and post-traumatic stress: A critical review of the empirical literature. Clinical Psychology Review. 2007;27:14–45. doi: 10.1016/j.cpr.2006.08.004. doi: 10.1016/j.cpr.2006.08.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gehi A, Haas D, Pipkin S, Whooley MA, Findings from the Heart and Soul Study Depression and medication adherence in outpatients with coronary heart disease. Archives of Internal Medicine. 2005;165:2508–2513. doi: 10.1001/archinte.165.21.2508. doi:10.1001/archinte.165.21.2508. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Gehi AK, Ali S, Na B, Whooley MA. Self-reported medication adherence and cardiovascular events in patients with stable coronary heart disease: The heart and soul study. Archives of Internal Medicine. 2007;167:1798–1803. doi: 10.1001/archinte.167.16.1798. doi:10.1001/archinte.167.16.1798. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, Bauman A. Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation. 2007;116:1081–1093. doi: 10.1161/CIRCULATIONAHA.107.185649. doi:10.1161/CIRCULATIONAHA.107.185649. [DOI] [PubMed] [Google Scholar]
  17. Heppner PS, Crawford EF, Haji UA, Afari N, Hauger RL, Dashevsky BA, Baker D. The association of posttraumatic stress disorder and metabolic syndrome: A study of increased health risk in veterans. BMC Medicine. 2009;7:1. doi: 10.1186/1741-7015-7-1. doi:10.1186/1741-7015-7-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Hoge CW, Castro CA, Messer SC, McGurk D, Cotting DI, Koffman RL. Combat duty in Iraq and Afghanistan, mental health problems, and barriers to care. New England Journal of Medicine. 2004;351:13–22. doi: 10.1056/NEJMoa040603. doi:10.1056/NEJMoa040603. [DOI] [PubMed] [Google Scholar]
  19. Jackson AW, Morrow JR, Jr., Bowles HR, FitzGerald SJ, Blair SN. Construct validity evidence for single-response items to estimate physical activity levels in large sample studies. Research Quarterly for Exercise and Sport. 2007;78:24–31. doi: 10.1080/02701367.2007.10599400. [DOI] [PubMed] [Google Scholar]
  20. Jacobsen LK, Southwick SM, Kosten TR. Substance use disorders in patients with posttraumatic stress disorder: A review of the literature. American Journal of Psychiatry. 2001;158:1184–1190. doi: 10.1176/appi.ajp.158.8.1184. doi: 10.1176/appi.ajp.158.8.1184. [DOI] [PubMed] [Google Scholar]
  21. Kang HK, Bullman TA, Taylor JW. Risk of selected cardiovascular diseases and posttraumatic stress disorder among former World War II prisoners of war. Annals of Epidemiology. 2006;16:381–386. doi: 10.1016/j.annepidem.2005.03.004. doi:10.1016/j.annepidem.2005.03.004. [DOI] [PubMed] [Google Scholar]
  22. Kessler RC. Posttraumatic stress disorder: The burden to the individual and to society. Journal of Clinical Psychiatry. 2000;61(Suppl 5):4–12. discussion 13-14. [PubMed] [Google Scholar]
  23. Kross EK, Gries CJ, Curtis JR. Posttraumatic stress disorder following critical illness. Critical Care Clinics. 2008;24:875–887. doi: 10.1016/j.ccc.2008.06.002. ix-x. doi:10.1016/j.ccc.2008.06.002. [DOI] [PubMed] [Google Scholar]
  24. Kubzansky LD, Koenen KC. Is posttraumatic stress disorder related to development of heart disease? An update. Cleveland Clinic Journal of Medicine. 2009;76(Suppl, 2):S60–65. doi: 10.3949/ccjm.76.s2.12. doi:10.3949/ccjm.76.s2.12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Kubzansky LD, Koenen KC, Jones C, Eaton WW. A prospective study of posttraumatic stress disorder symptoms and coronary heart disease in women. Health Psychology. 2009;28:125–130. doi: 10.1037/0278-6133.28.1.125. doi: 10.1037/0278-6133.28.1.125. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Kubzansky LD, Koenen KC, Spiro A, 3rd, Vokonas PS, Sparrow D. Prospective study of posttraumatic stress disorder symptoms and coronary heart disease in the Normative Aging Study. Archives of General Psychiatry. 2007;64:109–116. doi: 10.1001/archpsyc.64.1.109. doi:10.1001/archpsyc.64.1.109. [DOI] [PubMed] [Google Scholar]
  27. Kulka RA, Schlenger WE, Fairbank JA, Hough RL, Jordan B, Marmar CR, Weiss D. Executive summary, description of findings, and technical appendices. Vol. 1. Research Triangle Park Institute; Research Triangle Park, NC: 1988. Contractual report of findings from the National Vietnam Veterans Readjustment Study. [Google Scholar]
  28. Lavie CJ, Thomas RJ, Squires RW, Allison TG, Milani RV. Exercise training and cardiac rehabilitation in primary and secondary prevention of coronary heart disease; Mayo Clinic Proceedings; 2009; pp. 373–383. doi:10.4065/84.4.373. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. McEwen BS. Mood disorders and allostatic load. Biological Psychiatry. 2003;54:200–207. doi: 10.1016/s0006-3223(03)00177-x. doi:10.1016/S0006-3223(03)00177-X. [DOI] [PubMed] [Google Scholar]
  30. Newell SA, Girgis A, Sanson-Fisher RW, Savolainen NJ. The accuracy of self-reported health behaviors and risk factors relating to cancer and cardiovascular disease in the general population: A critical review. American Journal of Preventive Medicine. 1999;17:211–229. doi: 10.1016/s0749-3797(99)00069-0. doi:10.1016/S0749-3797(99)00069-0. [DOI] [PubMed] [Google Scholar]
  31. O’Connor GT, Buring JE, Yusuf S, Goldhaber SZ, Olmstead EM, Paffenbarger RS, Jr., Hennekens CH. An overview of randomized trials of rehabilitation with exercise after myocardial infarction. Circulation. 1989;80:234–244. doi: 10.1161/01.cir.80.2.234. doi:10.1161/01.CIR.80.2.234. [DOI] [PubMed] [Google Scholar]
  32. Robins LN, Cottler LB, Bucholz KK, Compton WM, North CS, Rourke KM. Diagnostic Interview Schedule for the DSM-IV (DIS-IV) Washington University; St Louis, MO: 2000. [Google Scholar]
  33. Robins LN, Helzer JE, Croughan J, Ratcliff KS. National Institute of Mental Health Diagnostic Interview Schedule. Its history, characteristics, and validity. Archives of General Psychiatry. 1981;38:381–389. doi: 10.1001/archpsyc.1981.01780290015001. [DOI] [PubMed] [Google Scholar]
  34. Rundle A, Field S, Park Y, Freeman L, Weiss CC, Neckerman K. Personal and neighborhood socioeconomic status and indices of neighborhood walk-ability predict body mass index in New York City. Social Science and Medicine. 2008;67:1951–1958. doi: 10.1016/j.socscimed.2008.09.036. doi:10.1016/j.socscimed.2008.09.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Ruo B, Rumsfeld JS, Hlatky MA, Liu H, Browner WS, Whooley MA. Depressive symptoms and health-related quality of life: The Heart and Soul Study. Journal of the American Medical Association. 2003;290:215–221. doi: 10.1001/jama.290.2.215. doi:10.1001/jama.290.2.215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Schnurr PP, Green BL. Understanding relationships among trauma, post-tramatic stress disorder, and health outcomes. Advances in Mind-Body Medicine. 2004;20:18–29. [PubMed] [Google Scholar]
  37. Shemesh E, Lurie S, Stuber ML, Emre S, Patel Y, Vohra P, Shneider BL. A pilot study of posttraumatic stress and nonadherence in pediatric liver transplant recipients. Pediatrics. 2000;105:E29. doi: 10.1542/peds.105.2.e29. doi:10.1542/peds.105.2.e29. [DOI] [PubMed] [Google Scholar]
  38. Shemesh E, Rudnick A, Kaluski E, Milovanov O, Salah A, Alon D, Cotter G. A prospective study of posttraumatic stress symptoms and nonadherence in survivors of a myocardial infarction (MI) General Hospital Psychiatry. 2001;23:215–222. doi: 10.1016/s0163-8343(01)00150-5. doi:10.1016/S0163-8343(01)00150-5. [DOI] [PubMed] [Google Scholar]
  39. Shemesh E, Yehuda R, Milo O, Dinur I, Rudnick A, Vered Z, Cotter G. Posttraumatic stress, nonadherence, and adverse outcome in survivors of a myocardial infarction. Psychosomatic Medicine. 2004;66:521–526. doi: 10.1097/01.psy.0000126199.05189.86. doi:10.1097/01.psy.0000126199.05189.86. [DOI] [PubMed] [Google Scholar]
  40. Shlipak MG, Ix JH, Bibbins-Domingo K, Lin F, Whooley MA. Biomarkers to predict recurrent cardiovascular disease: The Heart and Soul Study. American Journal of Medicine. 2008;121:50–57. doi: 10.1016/j.amjmed.2007.06.030. doi:10.1016/j.amjmed.2007.06.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. United States Census Bureau United States Census Bureau Poverty Thresholds. 2010 Retrieved from http://www.census.gov/hhes/www/poverty/data/threshld/index.html.
  42. Whooley MA, de Jonge P, Vittinghoff E, Otte C, Moos R, Carney RM, Browner WS. Depressive symptoms, health behaviors, and risk of cardiovascular events in patients with coronary heart disease. Journal of the American Medical Association. 2008;300:2379–2388. doi: 10.1001/jama.2008.711. doi:10.1001/jama.2008.711. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES