Abstract
This study investigated whether sedentary behaviour and different activity levels have an independent association with carotid intima-media thickness (IMT) and with the 3-year IMT progression in different carotid segments.
The study population included 614 healthy men and women (mean age = 44 ± 8 years) without carotid atherosclerosis and without increased coronary heart disease risk, who underwent B-mode carotid ultrasound and objective physical activity assessment by accelerometer (mean monitoring time = 5.7 ± 1.5 days). Time spent in sedentary (57.6 ± 9.1%), light (41.0 ± 9.2%), moderate and vigorous activities was determined. Sedentary behaviour was expressed as the ratio of time spent in sedentary and light activity (sedentary/light ratio) as these two activities occupied the majority of waking time. In 495 subjects, the carotid ultrasound was repeated 3 years after the baseline examination. After adjustment for age and the established risk factors that were independent determinants of carotid wall thickness in our population, sedentary/light ratio was independently associated only with the common carotid artery (CCA) IMT. The 3-year increase in CCA IMT was significantly lower in subjects with periods of vigorous activity (7 ± 40 µm) when compared with those with light activity only or with periods of moderate activity (22 ± 51 and 19 ± 46 µm, respectively, P < 0.05).
The healthy, young-to-middle age population of this study spent more than half of their waking time in sedentary activities. The proportion of time spent in sedentary activities was directly associated with baseline CCA IMT, independently of age and established atherosclerotic risk factors. In the longitudinal analysis, period of vigorous activity influenced the 3-year IMT progression in CCA.
Introduction
Population-based studies have demonstrated1–3 a generalized shift towards sedentary lifestyle, due to an increase in work-related sedentary activities (working at a computer, studying) as well as in time spent driving a car or watching TV.4 Sedentary behaviour is associated with obesity, diabetes mellitus, metabolic syndrome,4–7 and an increased risk of cardiovascular morbidity and mortality8 and it is also considered a major risk factor for clinical atherosclerosis.9 However, in the only study7 that evaluated a relationship between carotid intima-media thickness (IMT, used as a marker of preclinical atherosclerosis) and television watching (used as a measure of sedentary behaviour), TV viewing time was not independently associated with carotid IMT despite its unfavourable effect on several atherosclerotic risk factors. The lack of association could be explained by the fact that TV watching, although a major leisure-time sedentary activity,3 may not describe accurately the total sedentary time.
Guidelines from the American College of Sport Medicine and the American Heart Association10 recommend a minimum of 30 min of moderate-intensity activity 5 days per week or 20 min of vigorous-intensity activity 3 days per week to maintain health and reduce overall mortality.11 Indeed, results from the Los Angeles Atherosclerosis Study12 as well as those from the Amsterdam Growth and Health Longitudinal Study13 have demonstrated that vigorous habitual activity attenuates progression of carotid IMT and has a favourable impact on carotid stiffness. However, physical activity (PA) in these studies was estimated through self-reported data (questionnaires or structured interviews) that might introduce errors due to imprecise questions, misunderstanding of questions, and misclassification.14
An objective estimate of free-living activity during occupation and leisure, by means of small accelerometers that can continuously monitor human ambulatory movements, may provide better insight into the possible role of sedentary behaviour and PA intensity in cardiovascular disease risk and in the development of atherosclerosis.2,15 Therefore, the main purpose of the present study was to investigate the possible association of carotid IMT and 3-year IMT progression with the time spent in sedentary activities and with different activity levels, objectively assessed by accelerometer monitoring, in a cohort of apparently healthy subjects without carotid atherosclerosis and without increased coronary heart disease risk.16 The effect of sedentary time and PA levels on carotid wall thickness was assessed in different carotid segments, as each segment has its distinct anatomy and haemodynamic environment and consequently, established cardiovascular risk factors and lifestyle habits might influence the common carotid artery (CCA), carotid bulb, and the origin of internal carotid artery (ICA) in different ways.17 Beside the main objective, this study also provides insight into the pattern of daily free-living activity in a healthy, young-to-middle age population.
Methods
The study population is a subgroup of the RISC (Relationship between Insulin Sensitivity and Cardiovascular risk) study cohort (www.egir.org). The design and protocol of the RISC study has been reported elsewhere.18 Briefly, >1200 apparently healthy Caucasian subjects (age 30–60 years) were recruited in 19 centres in 14 European countries. Blood pressure (BP), plasma cholesterol, triglycerides, fasting, and 2 h glucose were within established limits. Exclusion criteria were the presence of chronic and overt cardiovascular diseases, carotid stenosis >40%, and treatment for hypertension, obesity, diabetes, or dyslipidaemia. Local Ethics Committee approval was obtained by each centre, and written consent was obtained from all participants. A standardized examination protocol18 included anthropometry, BP measurements, resting ECG, fasting blood test, oral glucose tolerance test, euglycaemic hyperinsulinaemic clamp, high-resolution ultrasound of extracranial carotid arteries. Monitoring of habitual PA was performed in a subset of subjects who consented to wear an accelerometer. Information regarding medical history, drug use, alcohol and cigarette consumption, and the subjective perception of PA were collected using standardized questionnaires. Clinical cardiovascular disease was excluded on the basis of medical history and a resting ECG. The 10-year absolute risk for total coronary heart disease endpoints was estimated with the Framingham Heart Study prediction score sheet.16 All above listed examinations, except the euglycaemic hyperinsulinaemic clamp and accelerometer monitoring were repeated after a 3-year period.
Study population
The population of the present study was selected according to the following criteria: (i) accelerometer monitoring for at least 3 days and 10 h per day; (ii) far-wall IMT well defined in at least CCA and carotid bulb; (iii) absence of carotid plaque (IMT in any carotid segment below 1.5 mm); (iv) low, below average or average 10-year coronary heart disease risk.16 Six hundred and fourteen subjects fulfilled the selection criteria (Figure 1); in 495 subjects, carotid ultrasound was repeated 3 years (±2 months) after the baseline examination.
Selection of study population from the RISC population.
Selection of study population from the RISC population.
Body composition assessment
Height was measured on a stadiometer. Body weight and fat-free mass were measured by electrical bioimpedance using a Body Composition Analyzer Model TB-300 (TANITA, Tokyo, Japan); fat mass was obtained as the difference between body weight and fat-free mass. Waist circumference was measured as the narrowest circumference between the lower rib margin and anterior superior iliac crest.
Oral glucose tolerance test and insulin clamp
A 2-h, 75-g oral glucose tolerance test and a euglycaemic hyperinsulinaemic clamp were performed on separate days, within 1 month, following previously described procedures standardized across centers.18 Insulin sensitivity was expressed as the ratio of the glucose disposal rate (M-value) averaged over the final 40 min of the 2 h clamp and normalized by fat-free mass to the mean plasma insulin concentration measured during the same interval (M/I, µmol/min/kgffm/mM).
Analytical procedures
Plasma glucose was measured centrally by the glucose oxidase technique (Glucose Analyzer, Beckman, Fullerton, CA, USA), and the serum concentration of insulin was measured by radioimmunoassay using a kit specific for human insulin (Linco Research, St Louis, MO, USA). Serum total and HDL cholesterol and triglycerides were assayed in a central laboratory by standard methods.
Carotid artery ultrasound imaging and analysis
High resolution B-mode ultrasound of extracranial carotid arteries was performed in each centre by trained and certified technicians following a standardized protocol.18–19 Carotid images were analysed in a centralized reading centre (Pisa) by a single reader (M.K.) using the computer-driven image analysis system MIP (Medical Image Processing; Institute of Clinical Physiology, CNR, Pisa, Italy). Far-wall IMT was measured bilaterally in digitized end-diastolic frames, for a single view of the CCA and for three different views of carotid bulb and ICA. The IMT in different segments were calculated as the mean of all IMT measurements available in the specific segment (two for CCA and up to six for bulb and ICA). Minimum luminal diameter of the left CCA was measured in three consecutive cardiac cycles as the distance between the lumen–intima interfaces of the near and far walls,19 ∼10–20 mm before the flow divider. In the RISC study, intra-observer variability of CCA measurements was tested in 140 randomly chosen scans. The mean differences between two readings were 4.6 ± 2.8 and 3.8 ± 2.3% for IMT and luminal diameter, respectively. Inter-test variability evaluated in 45 examinations repeated 1–2 weeks apart was 8.1 ± 3.5%.
Physical activity estimation
Habitual PA and sedentary behaviour were estimated by both objective and subjective methods, i.e. by accelerometer monitoring and by the International Physical Activity Questionnaire (IPAQ).20 A single-axis accelerometer (Computer Science Applications Model AM7164, Manufacturing Technology, Inc., FL, USA)6,15 was used to monitor ambulatory movements. The accelerometer was secured by a belt at the small of the back from waking up until going to sleep. Subjects were asked to wear the monitor for 7 days if possible, weekend included, and to behave in their usual manner. In the final analysis, only those days when the accelerometer was worn for at least 10 h were included. Non-wearing periods were identified as 60 min or more of continuous zero counts.
Accelerometer data were processed with custom software developed for this project and were checked for spurious recording: high counts >20 000 counts/min or repeated recording of the same number of counts;6,21 the days with spurious data were excluded. Data were summarized as the minutes and percentage of monitoring time spent in each of the different intensity levels—sedentary, light, moderate, and vigorous. A cut-off of <100 counts/min was used to categorize sedentary activity,3 and the widely utilized Freedson's cut-offs15 were used to differentiate light-intensity (100–1952 counts/min), moderate-intensity (1952–5724 counts/min), and vigorous-intensity (>5724 counts/min) activity. For moderate and vigorous activity, at least 10 min of this activity was required, in line with current PA recommendations that refer to ‘bouts lasting 10 min or more’.10 Minutes of moderate- or vigorous-intensity activity that were not in 10 min bouts were included in the light intensity time. The average intensity of daily PA was expressed as the average number of accelerometer counts per 1 min of monitoring time.
The IPAQ long-form questionnaire was used to assess the subjective perception of PA. The time during the last 7 days that had been spent walking or performing moderate-intensity or vigorous-intensity activities was recorded. On the basis of the scoring system described elsewhere (www.ipaq.ki.se), the subjects were divided into three categories of self-reported PA—low, moderate, and high PA levels. The IPAQ also estimates a sedentary behaviour calculating (minutes per week) the time spent in sitting activities during a typical weekday, weekend day, and during travel (total sitting time).20 The IPAQ self-reported PA and sitting time have been previously validated against accelerometry.14,22
Statistical analysis
Quantitative data are expressed as mean ± SD, categorical data as percentages. Skewed variables are given as median [inter-quartile range] and were log-transformed for statistical analyses. Analysis of variance was used to compare continuous variables. Relations between the outcome variables and continuous variables were evaluated by univariate Pearson correlation coefficients. Multiple linear regression analyses, adjusted for centre and sex (in women also for menopause), were used to test the independence of the associations of outcome variables with their significant correlates in univariate models. Statistical tests were two-sided and significance was set at a value of P < 0.05. Statistical analysis was performed by JMP software, version 3.1 (SAS Institute, Inc., Cary, NC, USA).
Results
Characteristics of study population
Clinical characteristics of the study population are shown in Table 1. Baseline far-wall IMT in CCA, carotid bulb, and ICA were 597 ± 83, 762 ± 145, and 611 ± 133 µm, respectively. After a 3-year period, the mean IMT changes in the corresponding segments were 17 ± 48, 56 ± 100, and 52 ± 110 µm. ICA IMT was measured in 92% of subjects at baseline and in 90% at follow-up.
Characteristics of study population
| Mean/mediana/% | Range | |
|---|---|---|
| Men/women | 244/370 | |
| Age (years) | 44 ± 8 | (30–60) |
| Weight (kg) | 72.3 ± 13.6 | (42–119) |
| Waist girth (cm) | 85.5 ± 12.0 | (59–121) |
| Fat mass (kg) | 19.8 ± 8.0 | (4.7–60.2) |
| Body mass index (kg/m2) | 24.8 ± 3.6 | (16.8–40.2) |
| Office systolic BP (mmHg) | 116 ± 12 | (79–139) |
| Office diastolic BP (mmHg) | 74 ± 7 | (52–89) |
| HDL cholesterol (mmol/L) | 1.50 ± 0.39 | (0.32–2.88) |
| LDL cholesterol (mmol/L) | 2.85 ± 0.78 | (0.9–5.7) |
| Triglycerides (mmol/L)a | 0.89 [0.54] | (0.30–4.56) |
| Fasting glucose (mmol/L) | 5.1 ± 0.5 | (2.9–6.8) |
| Fasting insulin (pmol/L)a | 28 [21] | (7–115) |
| M/I-value (µmol/min/kgffm/mM)a | 142 [89] | (32–389) |
| Smoking (never:current:ex) (%) | 48:28:24 |
| Mean/mediana/% | Range | |
|---|---|---|
| Men/women | 244/370 | |
| Age (years) | 44 ± 8 | (30–60) |
| Weight (kg) | 72.3 ± 13.6 | (42–119) |
| Waist girth (cm) | 85.5 ± 12.0 | (59–121) |
| Fat mass (kg) | 19.8 ± 8.0 | (4.7–60.2) |
| Body mass index (kg/m2) | 24.8 ± 3.6 | (16.8–40.2) |
| Office systolic BP (mmHg) | 116 ± 12 | (79–139) |
| Office diastolic BP (mmHg) | 74 ± 7 | (52–89) |
| HDL cholesterol (mmol/L) | 1.50 ± 0.39 | (0.32–2.88) |
| LDL cholesterol (mmol/L) | 2.85 ± 0.78 | (0.9–5.7) |
| Triglycerides (mmol/L)a | 0.89 [0.54] | (0.30–4.56) |
| Fasting glucose (mmol/L) | 5.1 ± 0.5 | (2.9–6.8) |
| Fasting insulin (pmol/L)a | 28 [21] | (7–115) |
| M/I-value (µmol/min/kgffm/mM)a | 142 [89] | (32–389) |
| Smoking (never:current:ex) (%) | 48:28:24 |
Mean ± SD, median [inter-quartile range] or percentage, and range.
aSkewed variables expressed as median [inter-quartile range].
Physical activity measures
Physical activity measures obtained by accelerometer were summarized as percentage of accelerometer-monitored time spent in sedentary, light, moderate, and vigorous activity (Table 2). The great majority of monitored time (98.6 ± 2.2%) was spent either in sedentary or in light-intensity PA. Therefore, subjects who spent more time in sedentary activity spent less time in light-intensity activity. The ratio of time (minutes) spent in sedentary and light-intensity activity (sedentary/light ratio) is used as an index of sedentary behaviour. One hundred and ninety-six subjects spent their monitored time only in light activity, 321 subjects had some bouts of moderate activity, and 97 subjects had some bouts of vigorous activity (Table 2).
Physical activity measured by accelerometer and self-reported physical activity in IPAQ long-form questionnaire, mean ± SD, median [inter-quartile range] and range
| Mean/medianc | Range | |
|---|---|---|
| Accelerometer measures | ||
| Days of accelerometer monitoring | 5.7 ± 1.5 | (3–8) |
| Time accelerometer worn (min/day) | 873 ± 75 | (692–1040) |
| Average intensity of PA (counts/min) | 393 ± 160 | (145–1438) |
| Sedentary/light ratio | 1.53 ± 0.57 | (0.45–3.34) |
| % Time at each activity level while accelerometer worn | ||
| Sedentary activity | 57.6 ± 9.1 | (28–78) |
| Light-intensity activity | 41.0 ± 9.2 | (22–69) |
| Moderate-intensity activitya | 1.4 ± 1.5 | (0.1–11.7) |
| Vigorous-intensity activityb | 1.2 ± 1.0 | (0.2–5.4) |
| Activity intensity groups (%) | ||
| Light only:some moderate:some vigorous | 32:52:16 | |
| IPAQ—self-reported activity | ||
| IPAQ categorical score (%) | ||
| Low:moderate:high | 20:43:37 | |
| Total sitting time (min/week)c | 2500 [1680] | (240–7920) |
| Mean/medianc | Range | |
|---|---|---|
| Accelerometer measures | ||
| Days of accelerometer monitoring | 5.7 ± 1.5 | (3–8) |
| Time accelerometer worn (min/day) | 873 ± 75 | (692–1040) |
| Average intensity of PA (counts/min) | 393 ± 160 | (145–1438) |
| Sedentary/light ratio | 1.53 ± 0.57 | (0.45–3.34) |
| % Time at each activity level while accelerometer worn | ||
| Sedentary activity | 57.6 ± 9.1 | (28–78) |
| Light-intensity activity | 41.0 ± 9.2 | (22–69) |
| Moderate-intensity activitya | 1.4 ± 1.5 | (0.1–11.7) |
| Vigorous-intensity activityb | 1.2 ± 1.0 | (0.2–5.4) |
| Activity intensity groups (%) | ||
| Light only:some moderate:some vigorous | 32:52:16 | |
| IPAQ—self-reported activity | ||
| IPAQ categorical score (%) | ||
| Low:moderate:high | 20:43:37 | |
| Total sitting time (min/week)c | 2500 [1680] | (240–7920) |
aOnly 321 subjects with 10 min bouts of moderate activity.
bOnly 97 subjects with 10 min bouts of vigorous activity.
cSkewed variables expressed as median [inter-quartile range].
The average intensity of PA as well as the sedentary/light ratio showed a Gaussian distribution with 77 and 71% of values within 1 SD of the mean and with 95 and 96% of values within 2 SD of the mean.
Self-reported IPAQ categorical score and total sitting time are shown in Table 2. One hundred and twenty-two, 265, and 227 subjects belonged to low, moderate, and high self-reported PA levels, respectively. The IPAQ categorical score classed individuals differently from activity groups derived from accelerometry. The correlation between average daily time spent in sedentary activity as assessed by accelerometer and self-reported total sitting time was weak (r = 0.19; P < 0.0001).
Carotid intima-media thickness and atherosclerotic risk factors
The cross-sectional associations between baseline IMT in different carotid segments and atherosclerotic risk factors are described in Table 3. In multivariate models, age, weight, office systolic BP, fasting plasma glucose, and current smoking were independent correlates of CCA far-wall IMT (Table 4). Intima-media thickness in the carotid bulb was independently associated with sex, age, systolic BP, LDL cholesterol, and current smoking (cumulative R2 = 0.29) and ICA IMT with sex, age, LDL cholesterol, and current smoking (cumulative R2 = 0.22). Three-year IMT changes in CCA and carotid bulb correlated only with age (r = 0.16 and 0.17; P = 0.0005 and P = 0.0002), whereas IMT changes in ICA correlated with age and baseline systolic BP (r = 0.22 and 0.16, P < 0.0001 and P= 0.003, respectively).
Matrix of univariate Pearson correlation coefficients between baseline intima-media thickness in different carotid segments, body composition, atherosclerotic risk factors, and physical activity measures
| CCA IMT | Bulb IMT | ICA IMT | Age | BMI | Weight | Fat mass | Waist | Systolic BP | LDL cholesterol | HDL cholesterol | Triglyceridesa | FPG | FPIa | M/Ia | Average PA | Sedentary/light ratio | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.0 | 0.66 | 0.54 | 0.42 | 0.24 | 0.29 | 0.20 | 0.27 | 0.29 | 0.26 | −0.11 | 0.23 | 0.25 | 0.12 | −0.15 | −0.12 | 0.19 | CCA IMT |
| 1.0 | 0.61 | 0.44 | 0.16 | 0.17 | 0.11 | 0.20 | 0.25 | 0.27 | n.s. | 0.17 | 0.22 | n.s. | n.s. | n.s. | n.s. | Bulb IMT | |
| 1.0 | 0.31 | 0.16 | 0.18 | n.s. | 0.23 | 0.22 | 0.24 | n.s. | 0.12 | 0.14 | n.s. | n.s. | −0.11 | 0.12 | ICA IMT | ||
| 1.0 | 0.15 | n.s. | 0.20 | 0.14 | 0.20 | 0.30 | n.s. | 0.16 | 0.25 | n.s. | n.s. | n.s. | n.s. | Age | |||
| 1.0 | — | — | 0.76 | 0.31 | 0.24 | −0.37 | 0.33 | 0.28 | 0.51 | −0.41 | −0.14 | n.s. | BMI | ||||
| 1.0 | 0.60 | 0.82 | 0.35 | 0.24 | −0.44 | 0.35 | 0.30 | 0.39 | −0.40 | n.s. | 0.18 | Weight | |||||
| 1.0 | 0.54 | 0.12 | 0.15 | −0.17 | 0.226 | 0.20 | 0.48 | −0.32 | −0.19 | n.s. | Fat mass | ||||||
| 1.0 | 0.35 | 0.32 | −0.45 | 0.36 | 0.29 | 0.45 | −0.44 | n.s. | n.s. | Waist | |||||||
| 1.0 | 0.14 | n.s. | 0.19 | 0.27 | 0.11 | −0.11 | n.s. | n.s. | Systolic BP | ||||||||
| 1.0 | −0.24 | 0.39 | 0.17 | 0.19 | −0.16 | −0.12 | n.s. | LDL cholesterol | |||||||||
| 1.0 | −0.41 | −0.14 | −0.33 | 0.30 | 0.11 | −0.14 | HDL cholesterol | ||||||||||
| 1.0 | 0.25 | 0.36 | −0.32 | n.s. | n.s. | Triglyceridesa | |||||||||||
| 1.0 | 0.34 | n.s. | n.s. | n.s. | FPG | ||||||||||||
| 1.0 | −0.50 | −0.20 | n.s | FPIa | |||||||||||||
| 1.0 | 0.14 | −0.14 | M/Ia | ||||||||||||||
| 1.0 | −0.36 | Average PA | |||||||||||||||
| 1.0 | Sedentary/light ratio |
| CCA IMT | Bulb IMT | ICA IMT | Age | BMI | Weight | Fat mass | Waist | Systolic BP | LDL cholesterol | HDL cholesterol | Triglyceridesa | FPG | FPIa | M/Ia | Average PA | Sedentary/light ratio | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.0 | 0.66 | 0.54 | 0.42 | 0.24 | 0.29 | 0.20 | 0.27 | 0.29 | 0.26 | −0.11 | 0.23 | 0.25 | 0.12 | −0.15 | −0.12 | 0.19 | CCA IMT |
| 1.0 | 0.61 | 0.44 | 0.16 | 0.17 | 0.11 | 0.20 | 0.25 | 0.27 | n.s. | 0.17 | 0.22 | n.s. | n.s. | n.s. | n.s. | Bulb IMT | |
| 1.0 | 0.31 | 0.16 | 0.18 | n.s. | 0.23 | 0.22 | 0.24 | n.s. | 0.12 | 0.14 | n.s. | n.s. | −0.11 | 0.12 | ICA IMT | ||
| 1.0 | 0.15 | n.s. | 0.20 | 0.14 | 0.20 | 0.30 | n.s. | 0.16 | 0.25 | n.s. | n.s. | n.s. | n.s. | Age | |||
| 1.0 | — | — | 0.76 | 0.31 | 0.24 | −0.37 | 0.33 | 0.28 | 0.51 | −0.41 | −0.14 | n.s. | BMI | ||||
| 1.0 | 0.60 | 0.82 | 0.35 | 0.24 | −0.44 | 0.35 | 0.30 | 0.39 | −0.40 | n.s. | 0.18 | Weight | |||||
| 1.0 | 0.54 | 0.12 | 0.15 | −0.17 | 0.226 | 0.20 | 0.48 | −0.32 | −0.19 | n.s. | Fat mass | ||||||
| 1.0 | 0.35 | 0.32 | −0.45 | 0.36 | 0.29 | 0.45 | −0.44 | n.s. | n.s. | Waist | |||||||
| 1.0 | 0.14 | n.s. | 0.19 | 0.27 | 0.11 | −0.11 | n.s. | n.s. | Systolic BP | ||||||||
| 1.0 | −0.24 | 0.39 | 0.17 | 0.19 | −0.16 | −0.12 | n.s. | LDL cholesterol | |||||||||
| 1.0 | −0.41 | −0.14 | −0.33 | 0.30 | 0.11 | −0.14 | HDL cholesterol | ||||||||||
| 1.0 | 0.25 | 0.36 | −0.32 | n.s. | n.s. | Triglyceridesa | |||||||||||
| 1.0 | 0.34 | n.s. | n.s. | n.s. | FPG | ||||||||||||
| 1.0 | −0.50 | −0.20 | n.s | FPIa | |||||||||||||
| 1.0 | 0.14 | −0.14 | M/Ia | ||||||||||||||
| 1.0 | −0.36 | Average PA | |||||||||||||||
| 1.0 | Sedentary/light ratio |
BMI, body mass index; FPG, fasting plasma glucose; FPI, fasting plasma insulin; M/I, index of insulin sensitivity.
aLog-transformed variable.
Regression coefficients of independent determinants of common carotid artery intima-media thickness: multiple regression model adjusted for centres and sex
| Model with established ATS risk factors | Model with established ATS risk factors and the sedentary/light ratio | |||
|---|---|---|---|---|
| β ± SE | P-value | β ± SE | P-value | |
| CCA far-wall IMT | ||||
| Sex | 0.07 ± 0.04 | 0.13 | 0.05 ± 0.04 | 0.27 |
| Age (years) | 0.41 ± 0.04 | <0.0001 | 0.41 ± 0.04 | <0.0001 |
| Weight (kg) | 0.15 ± 0.04 | 0.0005 | 0.12 ± 0.04 | 0.005 |
| Systolic BP (mmHg) | 0.13 ± 0.04 | 0.001 | 0.13 ± 0.04 | 0.001 |
| Fasting glucose (mg/L) | 0.10 ± 0.04 | 0.01 | 0.11 ± 0.04 | <0.01 |
| Current smoking (yes) | 0.14 ± 0.04 | 0.0005 | 0.15 ± 0.04 | <0.0005 |
| Sedentary/light ratio | 0.14 ± 0.03 | <0.0001 | ||
| Cumulative R2 | 0.34 | <0.0001 | 0.36 | <0.0001 |
| Model with established ATS risk factors | Model with established ATS risk factors and the sedentary/light ratio | |||
|---|---|---|---|---|
| β ± SE | P-value | β ± SE | P-value | |
| CCA far-wall IMT | ||||
| Sex | 0.07 ± 0.04 | 0.13 | 0.05 ± 0.04 | 0.27 |
| Age (years) | 0.41 ± 0.04 | <0.0001 | 0.41 ± 0.04 | <0.0001 |
| Weight (kg) | 0.15 ± 0.04 | 0.0005 | 0.12 ± 0.04 | 0.005 |
| Systolic BP (mmHg) | 0.13 ± 0.04 | 0.001 | 0.13 ± 0.04 | 0.001 |
| Fasting glucose (mg/L) | 0.10 ± 0.04 | 0.01 | 0.11 ± 0.04 | <0.01 |
| Current smoking (yes) | 0.14 ± 0.04 | 0.0005 | 0.15 ± 0.04 | <0.0005 |
| Sedentary/light ratio | 0.14 ± 0.03 | <0.0001 | ||
| Cumulative R2 | 0.34 | <0.0001 | 0.36 | <0.0001 |
Only sex and independent correlates of CCA IMT are presented.
Carotid intima-media thickness and physical activity measures
At baseline, IMT in CCA and ICA were positively associated to sedentary/light ratio and negatively to the average intensity of PA (Table 3). The independence of the association between the PA measures and IMT was tested after adjustment for those atherosclerotic risk factors that in our population were independently related to the respective IMT. The sedentary/light ratio showed an independent association with baseline CCA IMT but not with ICA IMT. The inclusion of the sedentary/light ratio into the multivariate model of CCA wall thickness did not cancel or replace established atherosclerotic risk factors and explained 2% more of the variance of CCA IMT (Table 4). To test whether other variables modified the relationship between CCA IMT and sedentary/light ratio, waist circumference, triglycerides, LDL cholesterol, and fasting plasma insulin were afterwards added into the multivariate model, without affecting the independent association between CCA wall thickness and sedentary time. The sedentary/light ratio remained independently related to CCA IMT even when the associations were tested separately for men (age, weight, current smoking, sedentary/light ratio; cumulative R2 = 0.33, P < 0.0001) and women (age, systolic BP, fasting glucose, current smoking, sedentary/light ratio; cumulative R2 = 0.37, P < 0.0001). The average intensity of PA was not independently associated with IMT in CCA or ICA.
At baseline, the IMT in all carotid segments did not differ between subjects who spent monitored time only in light activity and in subjects with some bouts of moderate or vigorous activity (596 ± 82, 594 ± 82, or 605 ± 84 µm, P = 0.55 for CCA; 760 ± 137, 763 ± 142, or 765 ± 192 µm, P = 0.94 for carotid bulb; 605 ± 128, 615 ± 138, or 610 ± 126 µm, P = 0.72 for ICA).
The 3-year changes in IMT in any carotid segment were not related to the sedentary/light ratio or to the average intensity of PA. Subjects with bouts of vigorous activity had lower 3-year increase in CCA IMT when compared with subjects with light-intensity activity only and to subjects with bouts of moderate activity (7 ± 40 vs. 22 ± 51 and 19 ± 46 µm, P < 0.05 for both), despite having a higher sedentary/light ratio (1.68 ± 0.60 vs. 1.50 ± 0.62 and 1.50 ± 0.53, P < 0.01 for both) (Figure 2). The three activity groups were similar for age (43 ± 8, 44 ± 8, 43 ± 8 years, P = 0.17).
The 3-year CCA IMT changes (mm; A) and sedentary/light ratio (B) according to accelerometer-derived activity groups. Light: only light activity during monitoring; moderate: some bouts of moderate-intensity activity; vigorous: some bouts of vigorous-intensity activity.
The 3-year CCA IMT changes (mm; A) and sedentary/light ratio (B) according to accelerometer-derived activity groups. Light: only light activity during monitoring; moderate: some bouts of moderate-intensity activity; vigorous: some bouts of vigorous-intensity activity.
Baseline CCA IMT was similar across the three IPAQ categories (606 ± 86, 596 ± 81, 592 ± 83 µm, P = 0.72) as well as across the tertiles of self-reported total sitting time (593 ± 76, 593 ± 86, 604 ± 84 µm, P = 0.86). The 3-year change in CCA IMT did not differ across the three IPAQ categories or across the tertiles of total sitting time. Similar results were observed for the IMT in carotid bulb and ICA.
Physical activity, body composition, and atherosclerotic risk factors
The associations between the sedentary/light ratio and established atherosclerotic risk factors are described in Table 3. In multivariate models, independent correlates of the sedentary/light ratio were body weight and M/I-value (β ± SE = 0.12 ± 0.04 and −0.10 ± 0.05; cumulative R2 = 0.12, P < 0.0001). Subjects with bouts of vigorous PA had significantly lower fat mass, waist circumference, LDL cholesterol, and fasting plasma insulin and higher HDL cholesterol when compared with those with light-intensity activity only (P= 0.01 to P< 0.0001) and with bouts of moderate activity (P = 0.05 to P < 0.001). Weight and systolic BP did not differ between the three activity levels.
Associations between common carotid artery wall thickness, luminal diameter, body weight, and systolic blood pressure
On the left side, CCA luminal diameter (5.65 ± 0.68 mm) was measured together with the far-wall IMT (594 ± 87 µm). Luminal diameter was positively associated with the corresponding IMT (r = 0.29, P < 0.0001) as well as with weight, BMI, systolic BP, and fasting plasma glucose (r = 0.46, 0.29, 0.27, and 0.28, respectively, P < 0.0001 for all). As expected, in a multivariate model, luminal diameter entered as an independent determinant of left CCA IMT, together with age, weight, systolic BP, glucose, and current smoking (β ± SE = 0.17 ± 0.04, 0.36 ± 0.04, 0.09 ± 0.04, 0.14 ± 0.04, 0.09 ± 0.04, and 0.11 ± 0.05; cumulative R2 = 0.31, P < 0.0001). Independent determinants of luminal diameter were sex and weight (β ± SE = 0.34 ± 0.04 and 0.27 ± 0.04, cumulative R2 = 0.34, P < 0.0001). Body weight remained independently associated to luminal diameter when analyses were performed separately for men (age and weight; cumulative R2 = 0.27, P < 0.0001) and women (weight and systolic BP; cumulative R2 = 0.17, P < 0.0001).
Discussion
This study is the first to evaluate the effect of objectively estimated sedentary time and PA levels on carotid wall thickness and its short-time progression in different carotid segments. Our cross-sectional analysis indicates that in a healthy population without increased coronary heart disease risk, the proportion of time spent in sedentary activity is directly associated with IMT in the CCA, independent of age, and established atherosclerotic risk factors. In the longitudinal analysis, subjects with short periods of vigorous PA at baseline had a lower CCA IMT progression over the following 3 years when compared with those with light-to-moderate activity.
The mechanisms underlying the cross-sectional association between sedentary time and CCA wall thickness cannot be elucidated by this study, yet we believe that our data may provide some insight into this relationship. A sedentary lifestyle was associated with higher body weight, and a larger body size is known to be associated with higher CCA luminal diameter23 and systolic BP.24 Higher luminal diameter and arterial pressure are both associated with an increase in wall tensile stress19,25 that induces a compensatory increase in wall thickness aimed to normalize wall tensile stress.25,26 Indeed, the recognized relationships between body weight and CCA luminal diameter as well as between IMT, luminal diameter, and systolic BP were confirmed in this study. The hypothesis of ‘physiological’ arterial remodelling is further supported by the observation that an independent effect of sedentary time on carotid wall thickness was demonstrated only at the CCA level, i.e. in a segment with simple ‘linear’ geometry and laminar pulsatile flow pattern, where flow- and pressure-induced changes in vascular morphology can be more easily identified.
In contrast to the sedentary/light ratio, baseline IMT in any carotid segment was not associated with average intensity of PA and did not differ according to the PA levels. However, the 3-year progression of CCA IMT was significantly lower in subjects with periods of vigorous activity than in those with only light-to-moderate activity, even though the former had higher sedentary/light ratio (Figure 2). The subjects with period of vigorous activity had lower body fat, abdominal fat, LDL cholesterol, and fasting plasma insulin as well as increased HDL cholesterol. Altogether our data imply that the effect of short periods of vigorous activity on IMT progression is independent of sedentary time and is probably mediated by the modification of atherosclerotic risk factors. These observations are in agreement with previous studies showing that body composition, lipid profile, and fasting insulin are beneficially affected with short-intermittent periods of intense activity.10–11 Furthermore, recent results from the Amsterdam Growth and Health Longitudinal Study13 have demonstrated that even the carotid artery stiffness in young adults is favourably influenced by vigorous but not by light-to-moderate habitual PA and that this positive effect could be explained by changes in cardiovascular risk factors. It is worth noting that current PA recommendations suggest at least 20 min of vigorous-intensity activity three times per week to maintain health and reduce mortality risk.10–11 The average time (median = 9 min per day) of vigorous activity that in our study was associated with lower IMT progression, meets this criterion.
Two additional observations should be briefly discussed. First, the subjective, self-reported estimates of PA and sitting time were not associated with carotid wall thickness or its progression. Furthermore, self-reported sitting time correlated poorly with sedentary time assessed by accelerometer monitoring14 and the IPAQ categorical score differed from accelerometry-derived activity groups. In fact, 37% of our subjects were included in the high-activity IPAQ group but only 16% had bouts of vigorous-intensity activity during accelerometer monitoring. These findings support the belief that self-reported PA data may introduce errors due to misunderstanding of questions and overestimation of PA level.14–15,22 However, IPAQ was developed for population-surveillance survey and not for smaller studies.22
Second, the healthy young-to-middle age population of this study spent 58% of waking time in sedentary activity, and only 68% of our subjects spent a small part of monitored time (∼2%) in moderate-to-vigorous activity. Similar results were obtained in a Swedish adult population,3 a US adult population,1 and the Australian population participating in the Australian Diabetes, Obesity and Lifestyle Study,2 a finding confirming a shift towards sedentary lifestyle.
Study limitations
Accelerometer decision rules, which were written specifically for the RISC project, might affect some of our results.6,15 We assumed that the accelerometer was not worn if 60 min were recorded with no activity, and consequently, we might record longer percentages of sedentary time than other studies. For moderate or vigorous activity, we required at least 10 min bouts of this type of activity, in line with current PA recommendations.10 Therefore, the size of the population (one-third) that did not record any moderate-to-vigorous activity could be overestimated. The cut-off points used for different types of PA are rather arbitrarily chosen.2,15
Summary
The present study has demonstrated that in a healthy young-to-middle age population without cardiovascular risk, the proportion of time spent in sedentary activity was directly associated with baseline IMT in CCA. The effect of sedentary behaviour on carotid wall thickness was in addition to age and established atherosclerotic risk factors and seemed to represent ‘physiological’ arterial remodelling induced by an inactivity-related increase in body size, rather than early atherosclerotic process. In contrast to baseline IMT, the 3-year IMT progression was reduced in subjects with some bouts of vigorous-intensity activity. The beneficial effect of vigorous activity was independent of sedentary time and might be mediated by changes in atherosclerotic risk factors. Further research should be focused on the medium-high risk population where both sedentary behaviour and moderate-to-vigorous activity might differently influence body size, body composition, and risk factors.
Funding
The European Group for the Study of Insulin Resistance (EGIR) RISC study is partly supported by EU grant QLG1-CT-2001-01252. Additional support has been provided by AstraZeneca (Sweden). The EGIR is supported by Merck Santé, France.
Conflict of interest: none declared.
Appendix
RISC recruiting centres: Amsterdam, The Netherlands: R.J. Heine, J. Dekker, S. de Rooij, G. Nijpels, W. Boorsma. Athens, Greece: A. Mitrakou, S. Tournis, K. Kyriakopoulou, P. Thomakos. Belgrade, Serbia and Montenegro: N. Lalic, K. Lalic, A. Jotic, L. Lukic, M. Civcic. Dublin, Ireland: J.J.N., T.P. Yeow, M. Murphy, C. DeLong, G. Neary, M.P. Colgan, M. Hatunic. Frankfurt, Germany: T.K., H. Böhles, S. Fuellert, F. Baer, H. Zuchhold. Geneva, Switzerland: A. Golay, E. Harsch Bobbioni, V. Barthassat, V. Makoundou, T.N.O. Lehmann, T. Merminod. Glasgow, Scotland: J.R. Petrie (now Dundee), C. Perry, F. Neary, C. MacDougall, K. Shields, L. Malcolm. Kuopio, Finland: M. Laakso, U. Salmenniemi, A. Aura, R. Raisanen, U. Ruotsalainen, T. Sistonen, M. Laitinen, H. Saloranta. London, England: S.W. Coppack, N. McIntosh, J. Ross, L. Pettersson, P. Khadobaksh. Lyon, France: M. Laville, F. Bonnet, A. Brac de la Perriere, C. Louche-Pelissier, C. Maitrepierre, J. Peyrat, S. Beltran, A. Serusclat. Madrid, Spain: R. Gabriel, E.M. Sánchez, R. Carraro, A. Friera, B. Novella. Malmö, Sweden (1): P. Nilsson, M. Persson, G. Östling, (2): O. Melander, P. Burri. Milan, Italy: P.M. Piatti, L.D. Monti, E. Setola, E. Galluccio, F. Minicucci, A. Colleluori. Newcastle-upon-Tyne, England: M. Walker, I.M. Ibrahim, M. Jayapaul, D. Carman, C. Ryan, K. Short, Y. McGrady, D. Richardson. Odense, Denmark: H. Beck-Nielsen, P. Staehr, K. Hojlund, V. Vestergaard, C. Olsen, L. Hansen. Perugia, Italy: G.B. Bolli, F. Porcellati, C. Fanelli, P. Lucidi, F. Calcinaro, A. Saturni. Pisa, Italy: E. Ferrannini, A. Natali, E. Muscelli, S. Pinnola, M. Kozakova. Rome, Italy: G. Mingrone, C. Guidone, A. Favuzzi. P. Di Rocco. Vienna, Austria: C. Anderwald, M. Bischof, M. Promintzer, M. Krebs, M. Mandl, A. Hofer, A. Luger, W. Waldhäusl, M. Roden.
Project Management Board: B.B. (Villejuif, France), S.W. Coppack (London, England), J.M. Dekker (Amsterdam, The Netherlands), E. Ferrannini (Pisa, Italy), A. Mari (Padova, Italy), A. Natali (Pisa, Italy), M. Walker (Newcastle, England).
Core laboratories and reading centres: Lipids Dublin, Ireland: P. Gaffney, J.J.N., G. Boran. Hormones Odense, Denmark: C. Olsen, L. Hansen, H. Beck-Nielsen. Albumin:creatinine, Amsterdam, The Netherlands: A. Kok, J. Dekker. Genetics Newcastle-upon-Tyne, England: S. Patel, M. Walker. Stable isotope laboratory, Pisa, Italy: A. Gastaldelli, D. Ciociaro. Ultrasound reading centre, Pisa, Italy: M. Kozakova. ECG reading, Villejuif, France: M.T. Guillanneuf. Data Management, Villejuif, France: B.B., L. Mhamdi; Padova, Italy: A. Mari; Pisa, Italy: L. Mota. Mathematical modelling and website management, Padova, Italy: A Mari, G Pacini, C Cavaggion. Coordinating office, Pisa, Italy: S.A. Hills, L. Landucci, L. Mota. Further information on the RISC Study and participating centres can be found on www.egir.org.
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