Table 2. Baseline Heart Rate Variability (rMSSD) Characteristics by Ethnicity, Smoking Habitus, and Medication Use. Ethnicity Caucasian African–American Hispanic or Other Smoking Never Past Current Antihypertensive Not taking Taking Thyroid Not taking Taking Antidepressant Not taking Taking Hyperlipidemic Not taking Taking Hormone Replacement Therapy Not taking Taking n 248 102 23 218 134 21 268 104 314 58 302 71 315 57 196 170 Mean (SD) P 21.14 (10.2) 27.13 (13.4) 24.09 (13.9) 23.37 (12.1) 22.03 (11.0) 24.52 (11.3) 23.32 (11.9) 21.87 (11.1) 23.09 (11.4) 21.94 (12.9) 23.85 (11.5) 19.14 (11.6) 23.04 (11.5) 22.21 (12.8) 23.54 (11.3) 22.03 (12.1) ,0.0001* ,0.0001{ 0.47 0.26 0.47 0.6 0.16 ,0.002* *Significant overall statistical effect. {Significantly different than Caucasian. Abbreviation: rMSSD; Root mean square successive difference of RR intervals. doi:10.1371/journal.pone.0002288.t002 Table 3. Baseline Relationship between Physiologic Characteristics and Indices of Heart Rate Variability. Physiologic Characteristic Baseline Age, y VO2max, L/min Weight, kg BMI, kg/m2 Indices of Heart Rate Variability Time Domain Frequency Domain rMSSD 20.19* 0.04 20.02 0.02 SDNN 20.15{ 0.07 20.04 0.00 HF 20.22{ 0.05 20.02 0.02 LF 0.08 0.02 20.111 20.07 20.18// 20.02 20.04 20.03 VLF Total 0.0003 0.06 20.04 0.01 Data represent Spearman correlation coefficients. Statistical notations are: (*) P,0.0002, ({) P,0.003, ({) P,0.001, (1) P,0.03), (//) P,0.0004. Abbreviations: SDNN, standard deviation of RR intervals; rMSSD, Root mean square successive difference of RR intervals; HF, log high frequency spectral power (0.15–0.40 Hz); LF, log low frequency spectral power (0.04–0.15 Hz); VLF, log very low frequency spectral power (0.0033–0.04 Hz); PT, log total spectral power frequency. doi:10.1371/journal.pone.0002288.t003 Exercise & HRV After Menopause interpretation of this index more difficult. These findings have important implications for women entering into and completing menopause. Normal aging influences a variety of indices related to CV circulation including the adrenoreceptor responsiveness and baroflex sensitivity [20,21]. As it pertains to HRV, parasympa- thetic tone shifts to a lower range [22,23]. Though parasympa- thetic tone is generally higher in women than men, aging reduces the difference between the two genders whereby changes in HRV begin approximately at menopause [7,24,25]. A hallmark feature of exercise training is an improvement in CV dynamics, inclusive of an improvement in the neuroregulatory aspects of cardiac regulation through the sinoatrial node [26,27,28,29]. Further, high levels of cardiorespiratory fitness are associated with higher HRV characteristics in endurance-exercise training young and older men as denoted by various indices including LF, HF total power, SDNN, and rMSSD [30,31,32,33]. However, this relationship is not as clear in older women where some studies show no difference in HRV characteristics, while others report an improvement in women exhibiting higher physical activity levels [14,15,34]. This is important clinically as a moderate level of physical activity is recommended for an aging population during a time when physiologic function and physical activity levels are waning [35,36]. Our findings affirm the theory that physical activity facilitates improvements HRV in older women and that the quantity of exercise training necessary to affect such an improvement is relatively modest. Previous cross-sectional studies helped to define the question evaluated our the current study. In a recent report, Reland et al. categorized older women into three groups: low activity (1000 kcal/week), moderate activity (.1000–2000 kcal/week), and high activity (.2000 kcal/week) and found that women in the high activity group who participated in chronic physical activity demonstrated an increase in parasympathetic indices of HRV [15]. A recent prospective study by Britton et al. also found that women who avoided being placed in the lowest/adverse quartile of HRV function and HR during 5.6 years of follow-up are most strongly influenced by baseline exercise training, body mass index, cholesterol, and blood pressure [37]. While these investigations support the concept that physical activity improves HRV, they do not adequately reflect the efficacy of using exercise training as an intervention to improve HRV. Earlier literature describing the use of exercise training to modulate HRV in women is limited and difficult to interpret due to variances in study protocol participant age, length, small sample sizes and the exercise training intensity used for the intervention. Davy et al reported that 12 weeks of aerobic exercise at 70% of maximal heart rate (,50–55% VO2max) was insufficient to improve HRV in eight postmenopausal women [12]. In contrast, Ito et al observed a significant improvement in HRV character- istics following 8 weeks of exercise training in mildly obese younger women (45.964 y; [38]) In the only study we are aware of using a longer exercise training intervention, Stein et al observed an improvement in HRV characteristics for older women (6664 y) exercising at 70% of VO2max (,80–85% HRmax). From these studies, one could surmise that intensity and study length are important factors for examining HRV changes in women; however, the results of these trials may create confusion regarding the effectiveness of exercise training for improving HRV in women. Perhaps the most simplistic explanation surrounding previous findings is that these trials were performed with small sample sizes and may have been statistically underpowered to adequately identify changes in HRV relative to exercise training. In our PLoS ONE | www.plosone.org 5 June 2008 | Volume 3 | Issue 6 | e2288