568578 research-article2015

HPQ0010.1177/1359105314568578Journal of Health PsychologyFields et al.

Article

Physical activity, sleep, and C-reactive protein as markers of positive health in resilient older men

Journal of Health Psychology 1­–11 © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1359105314568578 hpq.sagepub.com

Alison J Fields, Robert E Hoyt, Steven E Linnville and Jeffery L Moore

Abstract This study explored whether physical activity and sleep, combined with the biomarker C-reactive protein, indexed positive health in older men. Many were former prisoners of war, with most remaining psychologically resilient and free of any psychiatric diagnoses. Activity and sleep were recorded through actigraphy in 120 veterans (86 resilient and 34 nonresilient) for 7 days. Resilient men had higher physical activity, significantly lower C-reactive protein levels, and 53 percent had lower cardiac-disease risk compared to nonresilient men. Sleep was adequate and not associated with C-reactive protein. Results suggest continued study is needed in actigraphy and C-reactive protein as means to index positive health.

Keywords actigraphy, C-reactive protein, physical activity, resilience, sleep

According to the United Nations study on years or aging, older populations (aged 60  older) are “expected to more than double from 841 million people in 2013 to more than 2 billion in 2050” and will comprise 21 percent of the global populace (United Nations Department of Economic and Social Affairs (UN), 2013: xii). This older group tends to suffer from chronic illnesses such as diabetes, hypertension, and cardiovascular disease, which can negatively impact individual health and cause a burden to public health as a whole (Halter et al., 2014; Katz and Gilbert, 2008; Owen et al., 2010). In order to minimize these deleterious health outcomes, a broader definition of health has been established to include soundness of mind, body, and social well-being (World Health Organization (WHO), 1948). Positive

health is now considered more than just the absence of illness and disease; rather, it relates to a wide variety of personal factors that contribute to a healthier and longer life including biological, subjective, and functional aspects (Seligman, 2008). Research supports the concept that physical activity (PA) plays a large role in overall physical health. Long-term PA can reduce adiposity, improve insulin resistance, increase antioxidant defenses, modulate cardiovascular mortality, Robert E. Mitchell Center for Prisoner of War Studies, USA Corresponding author: Alison J Fields, Robert E. Mitchell Foundation, 220 Hovey Road, Pensacola, FL 32508, USA. Email: [email protected]

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and improve endothelial function (Kasapis and Thompson, 2005). Inactivity is “the fourth leading risk factor for global mortality,” and reducing inactivity has become a public health priority worldwide (World Health Association, 2011: 1). Physical inactivity is also a risk factor for various undesired psychological issues including depressive symptoms, phobias, alcohol and drug dependence, as well as anxiety and mood disorders (Meng and D’Arcy, 2013). PA is also a modifiable and inexpensive element that has been associated with reduced risk of developing and slowing progression of Alzheimer’s disease and dementia (Brown et al., 2013; Ruthirakuhan et al., 2012). The importance of sleep is widely recognized, and there is now a national objective to improve sleep in government programs such as Healthy People 2020 (United States Department of Health and Human Services, 2013). Sleep contributes to physical health in various ways, including undoing the damage of daily life stresses, promoting proper biological modulation of metabolic and endocrine function, stimulating both pro-inflammatory and anti-inflammatory cytokines, and prompting nocturnal waste removal from the brain (Frey et al., 2007; Hawkley et al., 2005; Spiegel et al., 1999; Xie et al., 2013). Abnormal sleep, in both chronic and acute situations, has been linked to such adverse physical conditions as coronary heart disease, hypertension, obesity, and all-cause mortality (Ayas et al., 2003; Gottlieb et al., 2006; Patel et al., 2004; Taheri et al., 2004). Poor sleep has also been associated with negative psychological aspects such as pain perception, posttraumatic stress disorder (PTSD), and major depressive disorder (Gulec et al., 2012; Pieh et al., 2011; Van Liempt, 2012). An easily obtained, readily available biomarker may provide an objective, non-verbal indication that an individual may have a health risk (either mentally or physically). One such biomarker is C-reactive protein (CRP). It is a nonspecific, acute-phase response protein widely considered to be one of the most stable, accurate, and reliable markers of heightened systemic inflammation, which is related to a broad range of negative health events,

morbidity, and mortality in older adults (Bassuk et al., 2004; Pepys and Hirschfield, 2003; Willerson and Ridker, 2004). CRP exhibits little variability within stable patients, appears comparable among healthy men and women, displays little circadian variability, and is not affected by short-term factors such as eating (Meier-Ewert et al., 2001; Mohsin and Ahmad, 2011; Rifai and Ridker, 2003). CRP values may possibly be more accurate at diagnosing inflammation and physical damage than plasma viscosity or erythrocyte sedimentation rate (Pepys and Hirschfield, 2003). There has been some debate on the effect PA has on CRP. It has been reported that PA is inversely associated with levels of CRP even when adjusting for suspected confounders such as age, smoking, and body mass index (BMI) while other studies have not shown any significant relationship (Church et al., 2010; Ford, 2002; Kasapis and Thompson, 2005). In population studies of middle-aged men and women, CRP concentrations reduced with increasing levels of PA (Aronson et al., 2004). Exploration of CRP levels and PA in older populations is important as there is a greater likelihood of reduced PA and increased sedentary behavior due to age-related infirmities, putting the older population at a greater health risk (Milanovic et al., 2013). A clear relationship between quantity and quality of sleep and CRP in healthy populations has not been established either. Some researchers have found that sleep quality was associated with CRP in males, and others have found the correlation in females only (Liu et al., 2014; Meier-Ewert et al., 2004; Miller et al., 2009). Grandner et al. (2013) reported that CRP has shown to be significantly elevated in long sleephours), but not in short sleepers ers (>9  ( 3.0 mg/L) increases over twofold in those with symptoms of anxiety disorder, while Pitsavos et al. (2006) reported male participants in the upper tertile of the Spielberger State Anxiety Inventory (STAI) had 22 percent higher levels of CRP. Among females, the associations between CRP and psychological states have not been as consistent (Liukkonen et al., 2011; Pitsavos et al., 2006). Other psychological constructs have also been linked to CRP levels. Burnout is a “chronic affective state comprised of emotional exhaustion, physical fatigue, and cognitive weariness” and has been associated with increased CRP in women (Toker et al., 2005). Shirom et al. (2010) define vigor as a “moderately aroused positive affect of physical strength, cognitive liveliness, and emotional energy.” They found high levels of vigor were associated with reduced levels of CRP in both men and women. Also Stephan et al. (2014) reported for every standard deviation (SD) decrease in self-perceived age, there was a decrease in CRP between 8 and 15 percent and that subjective age was a stronger predictor of CRP than was actual chronological age. While CRP has previously been employed as an indicator of acute physical issues, its application across a broader spectrum of positive health concepts may be salient in the overall health of aging adults. CRP measurements correlate so highly with “severity, extent, and progression of many different pathologies,” that it has great potential use in the identification of patients who might be in need of further medical evaluation, more frequent or detailed monitoring, lifestyle risk education and modifications, or even pharmacological therapies for underlying causes of the increased CRP (Pepys and Hirschfield, 2003: 1811). Thus, this is a biomarker which could potentially index “tip-ofthe-iceberg” underlying physical and/or psychological issues impacting an individual. The impact of PTSD is of great concern as the United States has experienced a number of

traumas at a national scale in recent years (9/11 terrorist attacks, Boston Marathon bombings, Iraq/Afghanistan wars, and major national disasters—Hurricane Katrina, etc.). According to Bonanno (2004), 50–60 percent of the US population has experienced a traumatic event, thus increasing the likelihood of developing PTSD and making them susceptible to various health risks (e.g. disorders of depression, anxiety, and substance abuse). However, only 5–10 percent of those individuals exposed to trauma are later diagnosed with PTSD. Therefore, a number of people are resilient to traumatic experiences and exhibit intact psychological functioning (Bonanno, 2004; Smith et al., 2010). One such group who experienced extreme trauma is the Vietnam-era repatriated US prisoners of war (RPWs). These individuals suffered from years of wartime imprisonment, torture, and starvation; yet, a number of them were resilient to these experiences. Most of these same individual’s sleep quality improved significantly at the time of repatriation (ca 1973). Specifically, sleep issues before, during, and after captivity were assessed upon repatriation from a sample of 440 Vietnam RPWs by Segovia et al. (2013). In that study, psychiatric disorders were assessed at repatriation (ca 1973), and assessments were continued annually by a psychiatrist or clinical psychologist. Odds ratios examining the presence of sleepdisturbance symptoms (i.e. early morning awakenings, nightmares) showed “resilient” RPWs (i.e. those free of psychiatric diagnoses) reporting fewer sleep-disturbance symptoms compared to “nonresilient” RPWs before, during, and after captivity. Particularly interesting were the repatriates who seemed to have “bounced back” from the captivity experience. Those reporting fewer sleep complaints at repatriation were nearly 2½ times more likely to be resilient than the groups reporting sleep difficulties at repatriation. Reporting fewer sleep complaints, but not necessarily an absence of them before, during, and after the trauma could predict psychological and physical resilience over time (Segovia et al., 2013).

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One valuable tool recognized by many to be both reliable and valid in sleep and PA research is wrist actigraphy (Mathie et al., 2004; Sadeh, 2011). Benefits of actigraphy include reasonable comparability to the gold standard sleep test of polysomnography (PSG), cost effectiveness, small size and light weight, practicality in participants’ natural environments, and allowance for long-term monitoring over multiple days and nights (De Souza et al., 2003; Martin and Hakim, 2011). Another added benefit is that actigraphy, unlike self-reported data, is not subject to recall or reporting bias, which could undermine the accuracy of activity classification. Given the potential to prevent, reduce, or reverse damage from adverse conditions associated with poor PA or sleep quality, we sought to examine a cohort of older men using actigraphy to measure levels of PA and sleep and correlate these results with the CRP biomarker as a factor to measure positive health. Furthermore, since these men had been survivors of a long-term prisoner-of-war experience, we also looked at group differences of resiliency in their state of health.

Methods Participants Participants came from the Robert E. Mitchell Center for Prisoner of War Studies who have contributed to an annual voluntary medical and psychological follow-up program within the Department of Defense since 1973. The participants were a subsection of Vietnam-era repatriates (RPWs) from all branches of service, as well as a matched comparison group (CG) of combat veterans, who had been in similar combat but never captured/imprisoned. All ranged in age from 61 to 86 years (Mean = 73 years, SD = 5 years). This study included 138 participants (105  RPW and 33 CG) who came for medical follow-up at the center between May 2012 and June 2013. Of the original 138 participants, 120 were able to supply actigraphy data (88  RPW; 32  CG). Others were excluded due to technical

problems with equipment or declination to participate. All have been evaluated psychiatrically at each medical follow-up over the past 40 years. Those who have been free of any psychiatric diagnoses over the past 40 years of medical follow-up were considered resilient (58 RPW; 28 CG); those who had been diagnosed with at least one psychiatric diagnosis were considered nonresilient (30 RPW; 4 CG) from their combat/imprisonment experiences. Details of this cohort have been published elsewhere (Segovia et al., 2013). This research was reviewed and approved by an Institutional Review Board, and all participants included in this report consented to be included in the study.

Actigraphy monitor ActiGraph™ GT3X+ monitors (ActiGraph™, LLC, Pensacola, FL, USA) were used to gather PA and sleep data continuously from our participants. These actigraphy monitors are tri-axial accelerometers that identify movement in horizontal, vertical, and diagonal planes. They are enabled with 512 MB of memory to collect activity of movement, steps, kilocalories, and positional vectors at a rate of 30–100 times per second (30–100 Hz) and ambient light (lux) measurement at a 1 Hz rate. Segments of activity were divided based upon the following activity counts per minute (CPM) cut points established by the adult algorithm included in ActiGraph software: “Sedentary” = 0–100, “Lifestyle” = 101–759, “Light” = 760–1952, “Moderate” = 1953– 5724, “Vigorous”  =  5725–9498, and “Very Vigorous” = 9499-infinity. Participants wore the monitor on their non-dominant wrist continuously for 7 days and nights. The monitor was secured by a locking band around their wrist to prevent premature removal.

Sleep diary A sleep diary designed by the American Academy of Sleep Medicine (n.d.) was used for 1 week by participants concurrently with actigraphy to

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Fields et al. augment the quantitative and qualitative sleep information. Information logged in the diary included when participants went to bed, went to sleep, took naps or prescribed medication, exercised, and drank caffeinated beverages or alcohol.

Procedures At the medical follow-up, height and current weight were collected and BMI calculated for all participants. As part of the routine clinical practice, blood samples were obtained which included high-sensitivity CRP biomarker data. Also, self-reported data were collected by clinical staff on their self-reported sleep efficiency and self-reported sleep difficulties to compare later with nighttime actigraphy data. When the participant returned home, their actigraphy monitor turned “on” and collected sleep/awake triaxial accelerometer activity for 7 days and nights. In addition, the participant maintained the 7-night sleep diary. The monitor and diary were mailed back to the research office afterward.

Data analysis Data analysis was conducted between August and December 2013 using SPSS, version 19 (IBM SPSS, Chicago, IL, USA). Spearman correlational analyses were conducted to determine whether there were any significant relationships in actigraphy and CRP biomarker for the cohort. This was followed by Mann– Whitney U analysis between the two subgroups (resilient vs nonresilient). Of the 120 participants included in this study, we collected data on 110 (92%) for a full 7 days, 8 had 6 days, 1 had 5 days, and 1 had 4 days due to forgetting to wear the device or who took it off sooner for personal reasons. Therefore, to maintain statistical power of the sample, we used average daily actigraphy as a way to normalize and include those few who had less than 7 days of actigraphy in the analyses. Nighttime sedentary data were removed from total sedentary activity to determine daytime sedentary data. Sleep efficiency was calculated by the proprietary

ActiGraph software, but was also compared with clinical and self-reported sleep efficiencies at the annual medical visit. As part of standard clinical practice in evaluating CRP levels and cardiac risk, the actigraphy data were then organized into tertiles based on CRP clinical cut points for levels of cardiac-disease risk: high risk >.3 mg/dL, medium risk .1–.3 mg/dL, and low risk 9 hours or

Physical activity, sleep, and C-reactive protein as markers of positive health in resilient older men.

This study explored whether physical activity and sleep, combined with the biomarker C-reactive protein, indexed positive health in older men. Many we...
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