Prolonged bouts of sedentary time and cardiac autonomic function in midlife
Abstract
Excessive sedentary time (SED) and long SED bouts are associated with cardiovascular diseases (CVD) and increased mortality. Low heart rate variability (HRV), indicating autonomic dysfunction, increases mortality and CVD morbidity. Information about the association between prolonged SED and HRV is lacking. The aim was to assess the relationship between SED bouts and HRV. Physical activity (PA), SED, HRV, and cardiorespiratory fitness (CRF) were collected from a birth-cohort sample (n = 4150) at 46 years. PA and SED were measured for 14 days with an activity monitor (Polar Active, Polar Electro, Finland). SED accumulating in bouts of at least 30 and 60 minutes (SED30, SED60) was calculated. Linear regression was used to study the relationship between prolonged SED and HRV accounting for CRF, PA, and health covariates. Higher SED60 and in women SED30 were associated with higher root mean square of differences in R-R intervals (rMSSD) after adjustments (β = .082-.104). In women, higher SED60 was associated with lower ratio between low- and high-frequency powers (β = −.060). Sedentary bouts were not associated with resting HR or post-exercise HR recovery. A positive relationship between SED bouts and rMSSD independent of PA and CRF was found, prolonged SED being positively associated with cardiac parasympathetic activity in midlife.
1 INTRODUCTION
Sedentary behavior is defined as any waking behavior with low energy expenditure (≤1.5 Metabolic Equivalents) in sitting, reclining, or lying posture.1 The association among high sedentary time (SED), impaired cardio metabolic health, and increased mortality independent of physical activity (PA) has been well documented.2-4 Almost half of the SED has been reported to accumulate in rather long periods (≥30 minutes bouts) among those of middle age.5 Individuals having higher sedentary bout durations in addition to high total SED have been reported to have higher mortality and CVD risk.6, 7 Furthermore, many experimental studies have reported detrimental effects of prolonged SED especially on glucose metabolism.8-10
Cardiac autonomic function is regulated by the autonomic nervous system, including sympathetic and parasympathetic systems, former being associated with the mobilization of energy and latter being responsible for restorative functions. The balance between these systems can be analyzed non-invasively by measuring heart rate variability (HRV), defined as oscillation in the interval between consecutive heartbeats.11 Autonomic dysfunction, often characterized by predominance of sympathetic system, is associated with lower resting HRV, which is a risk factor for all-cause mortality12 and cardiovascular diseases (CVD).13 Decline in HRV with advancing age occurs because of the normal aging process which causes a decline in cardiac vagal modulation reducing the parasympathetic activity.14-16 Higher levels of PA, especially moderate to vigorous PA (MVPA), and better cardiorespiratory fitness (CRF) have been found associated with higher HRV, lower resting heart rate (HR), and better heart rate recovery (HRR) after exercise.17-20 In addition, it has been suggested that PA has a protective role in the age-related decline of HRV.21, 22
Unfavorable changes in autonomic regulation, which can be assessed with HRV,11 might be attributable to cardiovascular effects resulting from too much sitting.13, 23 The previous evidence on the association between SED, independently of PA, and HRV is limited. Only few studies have examined the association between objectively measured SED and HRV with inconsistent results, and no previous study has included accumulation patterns of SED.24, 25 High occupational sitting time has been found to be associated with reduced HRV, but the same association was not found for sitting during leisure time.24 A more recent study found no association between HRV and occupational or leisure time sitting after adjusting for potential confounders.25
The aim of this population-based study was to investigate the relationship between the total SED, accumulated daily SED in bouts of at least 30 and 60 minutes of uninterrupted SED, and HRV among middle-aged people.
2 MATERIALS AND METHODS
2.1 Study population
The Northern Finland Birth Cohort 1966 study includes all newborns whose date of birth was expected in the year 1966 in the two northernmost provinces in Finland (n = 12 058 live births). Information about these individuals has been recorded regularly since their birth through healthcare records, questionnaires, and clinical examinations.26 Most recent follow-up procedures—at which time participants were 46 years old (n = 10 321)—included questionnaires, laboratory tests, a CRF test, HRV measurement, and objective PA measurement with a wrist-worn activity monitor. The study was approved by the Ethical Committee of the Northern Ostrobothnia Hospital District in Oulu, Finland (94/2011), and has been performed in accordance with the Declaration of Helsinki. The subjects provided written consent for the study. Personal identity information was encrypted and replaced with identification codes to provide full anonymity.
2.2 Questionnaire
Postal questionnaires were sent to all participants with known addresses in the years 2012-2014 (response rate 67%, n = 6851). Questionnaires included items on health, health behavior, and social background. Each participant's education, employment status, and prevalence of diagnosed diseases were inquired. Smoking status and alcohol consumption (g/day) were composed based on multiple questions about drinking and smoking habits.
2.3 Clinical examination
Participants (n = 5852) attended clinical examinations where their medical conditions were widely examined by trained nurses. Body fat percent (fat%) was analyzed with bioelectrical impedance measurement device InBody 720 (InBody). In the laboratory, venous blood samples were drawn after overnight fasting for the analysis of triglycerides, serum low-density lipoprotein (LDL), and high-density lipoprotein (HDL) cholesterol levels, which were determined using an enzymatic assay method (Advia 1800; Siemens Healthcare Diagnostics Inc). The samples were analyzed in NordLab Oulu, a testing laboratory (T113) accredited by Finnish Accreditation Service (FINAS) (EN ISO 15189). Systolic (SBP) and diastolic blood pressures (DBP) were measured thrice in seated position (the two latter measurements averaged; Omron M10, Omron 124 Healthcare) after 15 min of rest.
2.4 Cardiorespiratory fitness
Cardiorespiratory fitness was measured by a submaximal 4-min single-step test (based on the Åstrand-Ryhming step test) without shoes on a bench with an adjusted height of 33/40 cm for women and men, respectively. A metronome was used to pace the stepping rate for 23 ascents/min. Heart rate was measured continuously during the step test and transformed into moving 10-beat median data. HR was reported as peak HR (HRpeak, bpm) during the submaximal step test and recovery HR value 60 seconds after the test (HRrec, bpm) measured in a seated position (RS800CX, Polar Electro Oy). Heart rate recovery 60 seconds after the step test was calculated (HRR60, HRpeak – HRrec, bpm). Also, the steepest 30-seconds slope during the first 60 seconds of recovery was calculated (HRslope, bpm s−1).18 Peak HR obtained from a submaximal exercise test can be used to evaluate somewhat reliably an individual's aerobic capacity (VO2max).27 Correlation between directly measured maximal oxygen uptake during a maximal cycle ergometer test and peak HR obtained from the step test was −0.52 in a sub study (n = 123) of the NFBC1966 31-year follow-up.28 Participants were excluded if they terminated the test because of exhaustion or some other reason (n = 277), if they did not perform the test because of impaired health status or unwillingness (n = 534), or if there were technical problems with HR measurement (n = 31).
2.5 Cardiac autonomic function
The measurement of resting cardiac autonomic function has been described in detail elsewhere.18 A description of the protocol was provided to each participant while they sat on a chair having the instrumentation they needed attached. In order to record R-R intervals (RRi), a heart rate monitor (RS800CX) was used. Before recordings, a rest period of at least one minute was held to allow for stabilization of HR. This short stabilization period has been reported to provide robust HRV measurements from even as short as a 1-minute recording.29 HR was recorded for three minutes in a seated position followed by three minutes of standing. The participants were allowed to breathe spontaneously. Spontaneous breathing was allowed because it requires less familiarization from the participant and breathing frequency has been reported to have only a small impact on one of the main HRV variable, the root mean square of successive differences in RRi (rMSSD).30 The first 150 seconds of recording in a seated position was analyzed and the last 150 seconds in standing. Artifacts and ectopic beats were removed and replaced by the local average (Hearts 1.2, University of Oulu, Oulu, Finland), and sequences with ≥10 consecutive beats of noise or ectopic beats were deleted. The RRi series with ≥80% accepted data were included in the analyses.18 A total of 5679 subjects took part in the RRi recordings, and of those, 5473 (96%) had eligible HRV data. Mean heart rate (HRrest), rMSSD describing the cardiac vagal activity, and the ratio between low- and high-frequency power (LF/HF) describing the balance between sympathetic and parasympathetic activation were analyzed from measurements in seated position. Participants with antihypertensive medication with β-blockers (n = 766) or type I or II diabetes (n = 235) were excluded from the analysis.
2.6 Physical activity and sedentary time
Physical activity and SED were objectively measured with a wrist-worn waterproof accelerometer-based activity monitor (Polar Active, Polar Electro Oy). The activity monitor was blinded, giving no feedback to the user. Polar Active provides MET (Metabolic Equivalent) values every 30 seconds and applies the user's height, weight, sex, and age as predefined inputs.31 Polar Active has been shown to correlate (R = .86) with the double-labeled water technique, assessing energy expenditure during exercise training.32 Participants were asked to wear the activity monitor 24 hours/d for at least 14 days, also while sleeping, in the wrist of the non-dominant hand. The first day when the activity monitor was given to the participant was excluded from the analysis. Participants with four or more eligible days (wear time of at least 600 minutes/d during waking hours) were included in the analyses.33
Volume of light PA was analyzed including all activity with intensity 2-3.49 METs and calculated by multiplying each MET value with its duration (vLPA, MET minutes/d). Similarly, volume of MVPA was analyzed including all activity with intensity of at least 3.5 METs and calculated by multiplying each MET value with its duration (vMVPA, MET minutes/d). The term SED corresponds here to all activity between 1 and 2 METs (total SED, minutes/d), and the amount of prolonged SED was analyzed as accumulated time in bouts of at least 30 and 60 min (SED30 and SED60, minutes/d) of consecutive MET values between 1 and 2 METs (not allowing any higher MET values in between). All PA variables were averaged over the number of valid measurement days for each participant. In our earlier comparison of different accelerometry-based methods, the threshold <2 MET for Polar Active provided similar results as threshold <100 cpm for ActiGraph, and the mean difference between methods was 7.0 minutes/d (95% confidence interval from −17.8 to 31.7 minutes/d).34
2.7 Statistics
The descriptive data are presented in counts and proportions, means and standard deviations (SD), or medians, and 25th and 75th percentiles for skewed data. Univariate associations between continuous variables and sexes were analyzed using the independent-sample t test, with Tukey's post-hoc test for normally distributed variables and with the independent-sample Mann-Whitney U test for skewed data. Differences in categorical variables between sexes were analyzed using the chi-square (χ2) test, and the Z test with Bonferroni correction was used for post-hoc analysis. rMSSD, LF/HF ratio, alcohol consumption, triglycerides, and daily accumulated time in sedentary bouts were natural-log-transformed to obtain normal distribution. Since bout variables obtained several zero values, a constant value of 1 was added to each measured value before natural-log transformation. The correlation between total SED and sedentary bouts and autonomic function variables (rMSSD, LF/HF ratio, HRrest, HRR60, HRslope) was calculated using the Pearson correlation coefficient (r). All HRV variables significantly associated with sedentary bouts in univariate analyses were entered in the multivariate linear regression analysis. The models were adjusted for potential confounders (independent variables) which had linear relationship with outcome variables, including HRpeak (bpm), fat%, SBP (mmHg), HDL and LDL cholesterol and triglycerides (mmol/L), alcohol consumption (composed from self-reports, g/d), smoking (self-reported; yes/no), and vLPA and vMVPA (MET minutes/d). Diastolic BP was highly correlated with SBP and was therefore excluded. All confounders were selected based on previous literature and have been found to be associated with HRV.13 The models were first adjusted for all these covariates in block 1 (stepwise method). Afterward, the total SED and sedentary bout variables were each separately added to the model in block 2 (enter method). No significant collinearity was observed between covariates or sedentary variables (variance inflation factor <5). No significant autocorrelation (Durbin-Watson statistic 1.5 < d < 2.5) or heteroscedasticity based on the distribution and variance of residuals was observed. The statistical significance was set to P < .05. All statistical analyses were performed with IBM SPSS Statistics for Windows, version 24.0 (IBM Corp.).
3 RESULTS
A total of 4150 participants had valid PA, HRV, and CRF data. Participants were on average 46.6 years old (age range 45.3-48.1 years). The characteristics of the study population are presented in Table 1. Women had, on average, higher vLPA, lower vMVPA, and less SED compared with men (P < .001), but no differences in terms of cumulative bouts of SED30 or SED60 were found between sexes (P > .05). Women had also lower cholesterol and triglyceride levels and lower blood pressure compared with men (P < .001). Women had higher rMSSD and lower LF/HF ratio than men (P < .001). Higher HRpeak (P < .001) and HRR (P < .001) were found in women. Significant linear association was found between HRV and SED variables in both sexes (Table 2).
| Men (n = 1855) | Women (n = 2295) | |
|---|---|---|
| Height | 178.7 (6.2) | 164.9 (5.9)** |
| Weight | 85.8 (13.4) | 69.9 (12.7)* |
| Fat% | 22.6 (6.7) | 32.0 (8.0)** |
| Education | ||
| No professional education, n (%) | 68 (4%) | 41 (2%)* |
| Vocational/college-level education, n (%) | 1288 (71%) | 1441 (65%)* |
| Polytechnic/university degree, n (%) | 455 (25%) | 729 (33%)* |
| Employment status | ||
| Employed, n (%) | 1597 (90%) | 1970 (90%) |
| Studying, n (%) | 18 (1%) | 46 (2%)* |
| Unemployed, n (%) | 115 (7%) | 88 (4%)* |
| Other, n (%) | 36 (2%) | 84 (4%)* |
| Smoking | ||
| Non-smoker, n (%) | 895 (49%) | 1372 (60%)* |
| Former smoker, n (%) | 571 (31%) | 544 (24%)* |
| Current smoker, n (%) | 368 (20%) | 357 (16%)* |
| Alcohol consumption | ||
| Alcohol consumption, g/day | 8.20 (2.33-20.30) | 3.00 (0.70-8.10)** |
| Heavy users (men ≥ 40 g/day, women ≥ 20 g/day), n (%) | 150 (8%) | 171 (8%) |
| Objective PA monitoring | ||
| vLPA (MET min/day) | 704 (190) | 742 (191)** |
| vMVPA (MET min/day) | 436 (232) | 341 (179)** |
| Total SED (min/day) | 642 (93) | 617 (87)** |
| SED30 (min/day) | 62 (35-106) | 64 (38-97) |
| SED60 (min/day) | 7 (0-20) | 9 (0-20) |
| Clinical measurements | ||
| HDL cholesterol (mmol/L) | 1.4 (0.3) | 1.7 (0.4)** |
| LDL cholesterol (mmol/L) | 3.8 (0.9) | 3.2 (0.9)** |
| Triglycerides (mmol/L) | 1.2 (0.9-1.7) | 0.9 (0.7-1.2)** |
| Systolic blood pressure (mmHg) | 130 (14) | 120 (15)** |
| Diastolic blood pressure (mmHg) | 86 (10) | 82 (10)** |
| Cardiac autonomic function measurement | ||
| HRrest, sit (bpm) | 71 (12) | 72 (10) |
| rMSSD, sit (ms) | 20 (13-30) | 24 (16-36)** |
| LF/HF, sit | 2.3 (1.3-4.2) | 1.2 (0.7-2.3)** |
| CRF measurement | ||
| HRpeak (bpm) | 146 (16) | 149 (15)** |
| HRR60 (bpm) | 38 (11) | 44 (11)** |
| HRslope (bpm s−1) | −0.95 (0.32) | −1.10 (0.34)** |
- Abbreviations: CRF, cardiorespiratory fitness; HDL, high-density lipoprotein; HF, high-frequency power; HRpeak, peak heart rate during submaximal exercise test; HRR60, heart rate recovery during 60 s after submaximal exercise test; HRrest, resting heart rate; HRslope, steepness of heart rate recovery after submaximal exercise test; LDL, low-density lipoprotein; LF, low-frequency power; rMSSD, root mean square of successive differences in R-R intervals; SED30, accumulated daily time in bouts of at least 30 min of consecutive MET values in between 1 and 2 METs; SED60, accumulated daily time in bouts of at least 60 min of consecutive MET values in between 1 and 2 METs; total SED, total time obtained in between 1 and 2 METs intensity; vLPA, total volume of light physical activity; vMVPA, total volume of moderate to vigorous physical activity.
- * P < .05 compared with men
- ** P < .001 compared with men.
| Men (n = 1855) | Women (n = 2295) | |||||
|---|---|---|---|---|---|---|
| total SED | SED30 | SED60 | Total SED | SED30 | SED60 | |
| rMSSD | −0.046 (−0.091 to −0.001) | 0.027 (−0.018 to −0.072) | 0.063 (0.018-0.108)* | −0.012 (−0.052 to 0.028) | 0.077 (0.037-0.117)** | 0.084 (0.044-0.124)** |
| HRrest | 0.095 (0.05-0.139)** | 0.00 (−0.045 to 0.045) | −0.045 (−0.09 to 0.00) | 0.071 (0.031-0.111)* | −0.025 (−0.065 to 0.015) | −0.030 (−0.07 to 0.01) |
| HRR60 | −0.121 (−0.165 to −0.076)** | −0.041 (−0.086 to 0.004) | −0.011 (−0.056 to 0.034) | −0.118 (−0.158 to −0.078)** | −0.036 (−0.076 to 0.004) | −0.014 (−0.054 to 0.026) |
| HRslope | 0.163 (0.119-0.206)** | 0.069 (0.024-0.114)** | 0.041 (−0.004 to 0.086) | 0.156 (0.116-0.195)** | 0.065 (0.025-0.105)** | 0.032 (−0.008 to 0.072) |
| LF/HF | 0.010 (−0.035 to 0.055) | −0.020 (−0.065 to 0.025) | −0.035 (−0.08 to 0.01) | −0.035 (−0.075 to 0.005) | −0.065 (−0.105 to −0.025)* | −0.079 (−0.119 to −0.039)** |
- Abbreviations: HF, high-frequency power; HRR60, heart rate recovery at 60 s after submaximal exercise test; HRrest, resting heart rate; HRslope, steepness of heart rate recovery after submaximal exercise test; LF, low-frequency power; rMSSD, root mean square of successive differences in R-R intervals; SED30, duration of at least 30-min sedentary bouts; SED60, duration of at least 60-min sedentary bouts.
- * Significant correlation at level P < .05.
- ** Significant correlation at level P < .001.
For dependent variables with linear relationships with total SED, SED30, and/or SED60, multivariate linear regression analysis was performed separately for men and women (Table 3). Higher time spent in prolonged sedentary bouts was associated with higher rMSSD in both sexes, SED30 in women (β = .104) and SED60 in men and women (β = .082 and .094, respectively) (all P < .001). Total SED or SED30 was not associated with resting HR, heart rate recovery, or its steepness (HRrest, HRRslope, and HRR60) (all P > .05). Higher duration spent in SED60 was associated with lower LF/HF ratio in women (β = −.060, P = .013).
| Men | R 2 | β | P | Women | R 2 | β | P |
|---|---|---|---|---|---|---|---|
| rMSSD, sit | rMSSD, sit | ||||||
| Covariates | .178 | Covariates | .087 | ||||
| CRF (HRpeak) | −.250 | <.001 | CRF (HRpeak) | −.202 | <.001 | ||
| SBP | −.101 | <.001 | SBP | −.095 | <.001 | ||
| LDL cholesterol | −.065 | .005 | HDL cholesterol | −.050 | .024 | ||
| triglycerides | −.109 | <.001 | triglycerides | −.135 | <.001 | ||
| smoking | −.068 | .002 | |||||
| fat% | −.100 | <.001 | |||||
| SED60 | .082 | <.001 | SED30 | .104 | <.001 | ||
| Covariates + SED60 | .185 | SED60 | .094 | <.001 | |||
| Covariates + SED30 | .098 | ||||||
| Covariates + SED60 | .096 | ||||||
| HRrest, sit | HRrest, sit | ||||||
| Covariates | .367 | Covariates | .284 | ||||
| CRF (HRpeak) | .514 | <.001 | CRF (HRpeak) | .526 | <.001 | ||
| SBP | .087 | <.001 | SBP | .061 | .001 | ||
| smoking | .078 | <.001 | triglycerides | .117 | <.001 | ||
| triglycerides | .091 | <.001 | fat% | −.096 | <.001 | ||
| LDL cholesterol | .041 | .040 | |||||
| fat% | .053 | .021 | |||||
| vLPA | .040 | .045 | |||||
| total SED | −.037 | .168 | Total SED | −.017 | .378 | ||
| Covariates + total SED | .368 | Covariates + total SED | .285 | ||||
| HRslope | HRslope | ||||||
| Covariates | .224 | Covariates | .158 | ||||
| CRF (HRpeak) | .214 | <.001 | CRF (HRpeak) | .171 | <.001 | ||
| smoking | .085 | <.001 | triglycerides | .143 | <.001 | ||
| triglycerides | .113 | <.001 | LDL cholesterol | .050 | .024 | ||
| LDL cholesterol | .095 | <.001 | fat% | .096 | <.001 | ||
| fat% | .148 | <.001 | vMVPA | −.138 | <.001 | ||
| alcohol consumption | .046 | .034 | |||||
| vMVPA | −.111 | <.001 | |||||
| total SED | .005 | .846 | total SED | .009 | .707 | ||
| SED30 | −.016 | .492 | SED30 | −.026 | .201 | ||
| Covariates + total SED | .224 | Covariates + total SED | .159 | ||||
| Covariates + SED30 | .224 | Covariates + SED30 | .159 | ||||
| HRR60 | HRR60 | ||||||
| Covariates | .182 | Covariates | .118 | ||||
| CRF (HRpeak) | −.151 | <.001 | CRF (HRpeak) | −.124 | <.001 | ||
| SBP | −.081 | <.001 | SBP | −.060 | .005 | ||
| smoking | −.123 | <.001 | triglycerides | −.159 | <.001 | ||
| triglycerides | −.116 | <.001 | LDL cholesterol | −.051 | .022 | ||
| LDL cholesterol | −.094 | <.001 | vMVPA | .154 | <.001 | ||
| fat% | −.108 | <.001 | |||||
| vMVPA | .119 | <.001 | |||||
| total SED | .019 | .460 | total SED | .017 | .463 | ||
| Covariates + total SED | .182 | Covariates + total SED | .118 | ||||
| LF/HF | |||||||
| Covariates | .020 | ||||||
| CRF (HRpeak) | .056 | .024 | |||||
| fat% | .089 | <.001 | |||||
| vLPA | .089 | <.001 | |||||
| SED30 | −.037 | .212 | |||||
| SED60 | −.060 | .013 | |||||
| Covariates + SED30 | .021 | ||||||
| Covariates + SED60 | .023 |
- Abbreviations: HDL, high-density lipoprotein; HF, high-frequency power; HRpeak, peak heart rate during submaximal exercise test; HRR60, heart rate recovery at 60 s after submaximal exercise test; HRrest, resting heart rate; HRslope, steepness of heart rate recovery after submaximal exercise test; LDL, low-density lipoprotein; LF, low-frequency power; rMSSD, root mean square of successive differences in R-R intervals; SBP, systolic blood pressure; SED30, accumulated daily time in bouts of at least 30 min of consecutive MET values in between 1 and 2 METs; SED60, accumulated daily time in bouts of at least 60 min of consecutive MET values in between 1 and 2 METs; total SED, total time obtained in between 1 and 2 METs intensity; vLPA, total volume of light physical activity; vMVPA, total volume of moderate to vigorous physical activity.
Better CRF (lower HRpeak) was associated with higher rMSSD, better HR recovery (HRslope and HRR60), and lower resting HR in men and women and in lower LF/HF ratio in women. Lower SBP was associated with higher rMSSD, lower resting HR, and better HR recovery (HRR60) in men and women. Volume of PA was not associated with rMSSD. Higher vMVPA was associated with better HR recovery (HRslope and HRR60). Some other covariates—HDL and LDL cholesterol, smoking, alcohol consumption, and vLPA—were not as strongly associated with most of the dependent variables. After adding total SED to model, the association between HRrest and vLPA became non-significant in men. For other dependent variables, after adding sedentary variables in block 2, beta coefficients of covariates did not change notably.
4 DISCUSSION
The aim of this population-based study was to investigate the relationship between the total SED, accumulation of prolonged sedentary bouts, and cardiac autonomic function in midlife. To our knowledge, this is the first population-based study investigating the association between accumulation patterns of SED and HRV. Prolonged sedentary bouts but not total SED were significantly associated with rMSSD, after adjustments for health, CRF, and behavioral covariates. Higher accumulated SED in 60 minutes bouts was associated with higher rMSSD, describing higher parasympathetic (vagal) activity, in both sexes. Additionally, in women also SED30 was positively associated with rMSSD.
Only few previous studies have examined the association between objectively measured SED and HRV. Hallman et al24 reported higher sitting time at work being associated with lower nocturnal rMSSD but no relationship was found between rMSSD and leisure-related sitting time among blue-collar workers (n = 126). However, in their recent study with larger study population (n = 490, blue-collar workers) they reported a small negative association between nocturnal rMSSD and leisure time sitting in crude model (no association between rMSSD and occupational sitting) but after controlling for age, body mass index, smoking, and leisure MVPA time, no significant association was found between rMSSD (or other HRV indexes) and leisure or occupational or sitting times.25 These findings are in line with the present study reporting no association between total SED and HRV indexes after adjusting for confounders, although the study designs were slightly different. Hallman et al used HRV measured during sleep, and their study sample consisted solely of individuals with physically active work.24, 25
To our knowledge, no previous study has examined the association of accumulation patterns of SED and cardiac autonomic function. The possibly complex explanation for the positive association between prolonged SED and rMSSD in this study includes both physiological factors and underlying confounders. Bodily stress (mental, physical) decreases HRV because of increased sympathetic activity and the withdrawal of parasympathetic activity.13, 35 Presumably, the amount and type of stressors occurring during leisure time compared with work differ and partly affect this discrepancy. Measuring HRV in the laboratory might have induced additional stress to the participants and affected HRV measurement results. Possible confounders not accounted for in this study could include socioeconomic factors like occupation. In addition to sedentary bouts, better CRF, lower SBP, lower levels of triglycerides and in men lower fat%, LDL cholesterol, abstinence of smoking, and in women lower HDL cholesterol were associated with higher rMSSD.
Higher SED60 was associated with lower LF/HF ratio in women but not in men. LF/HF ratio has been used to describe sympatho-vagal balance; LF power has been suggested to be generated by sympathetic nervous system and HF power by parasympathetic nervous system, and therefore, low LF/HF ratio would reflect parasympathetic dominance.36 Previously, no differences in LF and HF frequencies were reported between SED tertiles in hypertensive patients regardless of sex.37 A recent study reported a small negative association with LF and leisure time sitting but after adjustments the association became non-significant.25 The LF/HF ratio has been considered as a rather controversial measure, with the argument being that LF power would reflect sympathetic outflow only poorly.38 LF/HF ratio has also been critiqued in short-term HRV recordings because low frequencies in the signal might be insufficiently sampled.39 These limitations should be considered when drawing conclusions on the negative association in women between SED60 and LF/HF ratio obtained in this study.
After adjustments, we found no significant association between total SED or SED bouts and resting HR or heart rate recovery after exercise test. CRF was the most significant predictor of these HR metrics. Higher volume of MVPA was associated with better HR recovery (HRR60 and HRslope), and in men, higher vLPA was associated, although rather weakly, with higher resting HR.
5 STRENGTHS AND LIMITATIONS
The strengths of this study include a large population-based sample and the objective measurements of SED and PA, with a high compliance of participants wearing the activity monitor. In the analyses, we controlled for the total PA volume including all activities of at least light intensity compared with previous studies that have often used only MVPA to describe PA behavior. In addition, HRV, CRF, and covariates were measured in controlled laboratory settings.
This study also includes some limitations. The causality of the findings cannot be concluded because of the cross-sectional study design. The PA monitor might overestimate the amount of vigorous PA, which was in this study combined with moderate PA.34 The lack of posture recognition in measuring SED with wrist-worn monitors is also a limitation as the physiological consequences of sitting and standing can differ, a recent study reporting higher levels of occupational standing to be associated with higher rMSSD.25, 40 The reliability of short-term HRV recording has been argued, although its advantage in terms of fast measurement, data analysis, and low participant burden has been acknowledged.41 In addition, spontaneous breathing may confound the spectral analysis of HRV.30 Excluding participants with metabolic diseases and medications affecting autonomic function and those who were unable to carry out the CRF test might have induced selection bias to the study sample. In our previous study, we did not find significant differences in health characteristics between groups of participants with or without valid PA data.42
6 CONCLUSIONS
This large-scale population-based study evaluated the association between the total SED and time in prolonged sedentary bouts and cardiac autonomic function. Prolonged SED accumulated in 60 minutes or longer bouts was positively associated with rMSSD independent of PA and CRF suggesting prolonged SED positively associated with cardiac parasympathetic activity in midlife. Further studies are needed to explore the different SED features and their effects on HRV and to reveal underlying mechanisms of the current findings.
ACKNOWLEDGEMENTS
NFBC1966 received financial support from the University of Oulu [grant number 24000692], Oulu University Hospital [grant number 24301140], and the European Regional Development Fund (ERDF) [grant number 539/2010 A31592]. The study has been financially supported by the Ministry of Education and Culture in Finland [grant numbers OKM/86/626/2014, OKM/43/626/2015, OKM/17/626/2016, OKM/54/626/2019]; Infotech Oulu, Finland; Tauno Tönningin Säätiö; the Northern Ostrobothnia Hospital District; EU H2020 MSCA COFUND [grant number 713 645]; the Paulo Foundation; and the Finnish Foundation for Cardiovascular Research. The funders of this study did not have any role in its design, data collection, analysis, and interpretation or in writing the manuscript. We thank the participants in the 46-year study and the staff at the NFBC Project Center.
CONFLICT OF INTEREST
RA is employed by Polar Electro. The company had no role in the conduct of the study or decision to publish. For the remaining authors, none were declared.
