Abstract
Objective
Arterial stiffness and exposure to psychosocial work-related factors increase the risk of developing cardiovascular disease. However, little is known about the relationship between psychosocial work-related factors and arterial stiffness. We aimed to examine this relationship.
Design
Prospective cohort study.
Setting
Public organisations in Quebec City, Canada.
Participants
The study included 1736 white-collar workers (women 52%) from 19 public organisations.
Primary and secondary outcome measures
Association between psychosocial work-related factors from the job strain and effort–reward imbalance (ERI) models assessed at study baseline (1999–2001) with validated instruments and arterial stiffness assessed using carotid–femoral pulse wave velocity at follow-up, on average 16 years later (2015–2018). Generalised estimating equations were used to estimate differences in arterial stiffness between exposed and unexposed participants. Subgroup analyses according to sex, age, blood pressure (BP), cardiovascular risk score and employment status were conducted.
Results
Among participants with high diastolic BP (≥90 mm Hg) at baseline, aged 47 on average, those exposed to high job strain had higher arterial stiffness (1.38 m/s (95% CI: 0.57 to 2.19)) at follow-up, 16 years later, following adjustment for a large set of potential confounders. The trend was similar in participants with high systolic BP (≥140 mm Hg) exposed to high job strain (0.84 m/s (95% CI: −0.35 to 2.03)). No association was observed for ERI in the total sample and counterintuitive associations were observed in subgroup analyses.
Conclusions
Job strain may have a long-term deleterious effect on arterial stiffness in people with high BP. Interventions at midlife to reduce job strain may mitigate arterial stiffness progression.
Keywords: epidemiology, risk factors, occupational & industrial medicine, occupational stress
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This study has a long follow-up period of 16 years.
Arterial stiffness was measured using carotid–femoral pulse wave velocity, the gold standard.
Psychosocial work-related factors were assessed using validated instruments.
This study examines the effect of psychosocial work-related factors measured at a single point in time.
Introduction
Cardiovascular disease (CVD) is a major public health problem. CVD develops over several years across a continuum initiated by one or several risk factors, which can progress to atherosclerosis, cardiovascular events and end-stage organ disease.1 The main modifiable risk factors for CVD include dyslipidaemia, high blood pressure (BP), smoking, diabetes and adiposity. Additional factors such as psychosocial work-related factors can contribute to increase the risk of CVD.2 In Organisation for Economic Co-operation and Development countries, 20%–25% of workers are exposed to adverse psychosocial work-related factors.3
Arterial stiffness describes the reduced ability of large proximal arteries to dilate and retract. Carotid–femoral pulse wave velocity (cfPWV), the gold standard method for assessing aortic stiffness, is linearly associated with CVD risk.4 An increase in aortic pulse wave velocity of 1 m/s corresponds to an adjusted risk increase of 14% in fatal or non-fatal cardiovascular events.4 Adverse psychosocial work-related factors may be associated with high arterial stiffness. Results of prior studies differ according to types of exposure and sex, suggesting deleterious,5–9 beneficial10 or no effect11 of psychosocial work-related factors on arterial stiffness. All prior studies are limited by their cross-sectional design. None used the gold standard measure for arterial stiffness.
The objective of the present study was to examine the association between psychosocial work-related factors and arterial stiffness in a prospective cohort study of men and women from Quebec City, Canada. Men and women were considered separately since the prevalence of psychosocial work-related factors and their effects differ by sex.2 Elevated midlife BP is associated with increased arterial stiffness.12 The relationship between midlife psychosocial work-related factors and arterial stiffness might therefore vary between people with and without elevated BP. This potential effect modification was examined.
Methods
Population and study design
We used data from a prospective cohort study. This cohort was initiated in 1991–1993 among 9188 white-collar workers (participation proportion: 75%) from 19 public organisations in Quebec City with two subsequent phases of data collection (1999–2001 and 2015–2018).13 The current study baseline was set in 1999–2001, since effort–reward imbalance (ERI) exposure was first assessed at that time. Arterial stiffness was assessed at follow-up (2015–2018). Among the 9188 participants in the original cohort initiation, 8120 (88.4 %) and 6707 (73 %) participated in 1999–2001 and 2015–2018, respectively. Arterial stiffness was measured in 1/3 of participants randomly selected. For the present study, baseline corresponds to the 1999–2001 period and follow-up time to 2015–2018. The study sample included 1736 participants with employee status at baseline (figure 1).
Figure 1.
Flow chart. The start of the original cohort: 1991–1993. Baseline: the baseline for the current study in 1999–2001. Follow-up: the follow-up for the current study in 2015–2018. The current study investigates the association between psychosocial work-related factors measured at baseline (1999–2001) and arterial stiffness measured at follow-up (2015–2018), adjusted for covariates measured at follow-up. Covariates measured at the start of the original cohort (1991–1993) were used to compute inverse probability of censoring weights (used in order to minimise potential selection bias due to non-response and lost to follow-up).
Data collection
At each wave, workers completed a self-administered questionnaire on risk factors for hypertension and CVD, demographic, occupational and social characteristics. Trained staff measured BP (using the mercury sphygmomanometer at baseline and the automated BP-TRU device (VSM MedTech, Coquitlam, Canada) at follow-up), height, weight and waist circumference. Arterial stiffness was measured at follow-up.
Psychosocial work-related factors
Job strain and ERI exposures were assessed at baseline (1999–2001). Components of job strain (psychological demands and job control) were measured using 18 items from the Job Content Questionnaire.14 Psychological demands include the quantity of work, time constraints and level of intellectual effort. Job control includes opportunities for learning, autonomy and participation in the decision-making process. The theoretical model postulates that the greatest health risk occurs in workers combining high demands and low control. The psychometric properties of the original English15 and French16 questionnaires have been demonstrated. We classified workers with demands scores≥24 (the median in the Quebec working population) in the high demands group and those with control scores≤72 (the median in the Quebec working population) in the low control group. The low strain group included workers combining low demands and high control. The passive, active and high strain groups included respectively people combining low demands and low control, high demands and high control and high demands and low control.
The ERI model states that efforts should be rewarded with income, respect and esteem, and occupational status control. Workers are in a state of deleterious imbalance when high efforts are accompanied by low reward and are more susceptible to health problems. The modified French version of the questionnaire was used to assess ERI. Reward at work was measured by nine original questions from the French version17 of the ERI scale. Effort was measured by nine items from the validated French version of the psychological demand scale of the Job Content Questionnaire.18 The psychometric qualities of this ERI scale version have been demonstrated.19 Effort and reward scores were computed with the sum of items. A ratio efforts/reward>1 indicated an imbalance. The ratio was also used in its continuous form.
Arterial stiffness as cfPWV (m/s)
Arterial stiffness was measured at follow-up using the Complior Analyse device (Alam Medical, Saint-Quentin-Fallavier, France). The transit time between the carotid and the femoral pulse was measured two times in each participant. cfPWV was calculated by dividing the carotid–femoral transit distance (calculated using the difference in body surface measurements from the suprasternal notch to the femoral and carotid sites) by the carotid–femoral transit time delay. A third measurement was taken if the difference between the two measurements was >0.5 m/s. Interobserver and intraobserver reproducibility of this measurement has been reported as excellent.20
Covariates
Potential confounders included the following risk factors for arterial stiffness: demographic characteristics (age, sex, education, household income, marital status and having children); biological factors (BP, body mass index (BMI), waist circumference, diabetes, hypercholesterolaemia and personal history of cardiovascular event), lifestyle factors (daily smoking, alcohol abuse and leisure time physical activity); family history of CVD at ≤60 years of age; psychological distress (Psychiatric Symptom Index); other work factors (hours worked for the organisation, hours worked for another organisation).
Statistical analyses
Continuous data were expressed as the mean along with the SD. Categorical data were expressed as number and percentages. Generalised estimating equations were used to estimate differences in arterial stiffness means between the exposed and unexposed groups, with their 95% CI.21 Regression models accounted for the correlation between employees of the same organisation. The models were sequentially adjusted for sets of covariates given that biological factors, psychological distress and lifestyle factors potentially mediate the associations (figure 2). As job strain and ERI models provide distinct information, we assessed the independent effect of job strain and ERI by adjusting for job strain when measuring the association with ERI and vice versa. In order to assess effect modification, we conducted subgroup analyses by sex and BP (systolic, diastolic and pulse pressure) at baseline. Sensitivity analyses were also conducted (1) with and without individuals with personal history of CVD since they may have increased arterial stiffness; (2) according to risk factors for arterial stiffness at baseline (age and Gaziano’s cardiovascular risk score22) since they may increase the deleterious effects of psychosocial work-related factors23; (3) according to job status at follow-up since retirement may attenuate the effects of psychosocial work-related factors.24 Multiple imputations25 and inverse probability weighting26 were performed to minimise potential selection bias due to non-response and/or loss to follow-up. Covariates measured at the initiation of the original cohort (in 1991–1993) were used in the calculation of the weights that were used for inverse probability weighting in order to minimise the potential selection bias resulting from losses to follow-up between cohort initiation and subsequent time points.
Figure 2.
Possible sequences of events between chronic exposure to psychosocial work-related factors and the development of arterial stiffness, hypertension and cardiovascular diseases, based on the cardiovascular continuum. *Adiposity, smoking, alcohol abuse, excessive salt intake, physical inactivity, dyslipidaemia, diabetes, mental health, chronic inflammation.
Analyses were performed with SAS V.9.4 software. The level of statistical significance was set at 0.05.
Participant and public involvement
Participants or the public were not involved in the study design, conduct, reporting or dissemination plans.
Results
The mean follow-up time between exposure (baseline) and arterial stiffness assessment (follow-up) was 16.8 (SD: 1.3) years. At baseline, participants were on average 45 years old. More women (23%) than men (17%) were exposed to high job strain. As many men as women were exposed to ERI (24%). At follow-up, participants were on average 62 years old (table 1).
Table 1.
Population characteristics at baseline (1999–2001) (unless otherwise stated) by sex
| Missing | All 1736 (100.0%) | Missing | Men 839 (48.3%) | Missing | Women 897 (51.7%) | |
| Age, year, mean (SD), cohort initiation (1991–1993) | 0 | 37.3 (6.6) | 0 | 38.6 (6.9) | 36.2 (6.1) | |
| Age, year, mean (SD), baseline (1999–2001) | 0 | 44.9 (6.7) | 0 | 46.2 (7.0) | 0 | 43.8 (6.2) |
| Age, year, mean (SD), follow-up (2015–2018) | 0 | 61.7 (6.1) | 0 | 63.0 (6.4) | 60.6 (5.6) | |
| Job strain | 16 | 7 | 9 | |||
| Low strain | 298 (17.3) | 174 (20.9) | 124 (14.0) | |||
| Passive | 592 (34.4) | 237 (28.5) | 355 (40.0) | |||
| Active | 486 (28.3) | 280 (33.7) | 206 (23.2) | |||
| High strain | 344 (20.0) | 141 (17.0) | 203 (22.9) | |||
| Effort–reward imbalance | 47 | 24 | 23 | |||
| Yes | 408 (24.2) | 197 (24.2) | 211 (24.1) | |||
| No | 1281 (75.8) | 618 (75.8) | 663 (75.9) | |||
| Completed education | 12 | 3 | 9 | |||
| Secondary or less | 334 (19.4) | 67 (8.0) | 267 (30.1) | |||
| College | 530 (30.7) | 238 (28.5) | 292 (32.9) | |||
| University | 860 (49.9) | 531 (63.5) | 329 (37.1) | |||
| Household income $C* | 11 | 4 | 7 | |||
| 0–49 999 | 426 (24.7) | 144 (17.3) | 282 (31.7) | |||
| 50 000–79 999 | 681 (39.5) | 362 (43.4) | 319 (35.8) | |||
| ≥80 000 | 618 (35.8) | 329 (39.4) | 289 (32.5) | |||
| Marital status | 4 | 2 | 2 | |||
| Partnered | 1328 (76.7) | 695 (83.0) | 633 (70.7) | |||
| Unpartnered | 404 (23.3) | 142 (17.0) | 262 (29.3) | |||
| Having children | 2 | 1 | ||||
| One or more | 652 (77.9) | 625 (69.8) | ||||
| No | 185 (22.1) | 271 (30.3) | ||||
| Diabetes† | 0 | 0 | 0 | |||
| Yes | 34 (2.0) | 16 (1.9) | 18 (2.0) | |||
| No | 1702 (98.0) | 823 (98.1) | 879 (98.0) | |||
| Hypercholesterolaemia‡ | 1 | 1 | 0 | |||
| Yes | 493 (28.4) | 320 (38.2) | 173 (19.3)) | |||
| No | 1242 (71.6) | 518 (61.8) | 724 (80.7) | |||
| Systolic blood pressure, mm Hg, mean (SD) | 48 | 118.2 (13.7) | 16 | 123.4 (12.9) | 32 | 113.2 (12.6)) |
| Systolic blood pressure≥140 mm Hg | 48 | 16 | 32 | |||
| Yes | 111 (6.6) | 89 (10.8) | 22 (2.5) | |||
| No | 1577 (93.4) | 734 (89.2) | 843 (97.5) | |||
| Diastolic blood pressure, mm Hg, mean (SD) | 48 | 76.7 (9.5) | 16 | 80.1 (9.0) | 32 | 73.4 (8.8) |
| Diastolic blood pressure≥90 mm Hg | 48 | 16 | 32 | |||
| Yes | 169 (10.0) | 122 (14.8) | 47 (5.4) | |||
| No | 1519 (90.0) | 701 (85.2) | 818 (94.6) | |||
| Hypertension status§ | 22 | 13 | 9 | |||
| Yes | 298 (17.4) | 206 (24.9) | 92 (10.4) | |||
| No | 1416 (82.6) | 620 (75.1) | 796 (89.6) | |||
| Pulse pressure, mm Hg, mean (SD) | 48 | 41.5 (8.7) | 16 | 43.3 (9.2) | 32 | 39.8 (7.8) |
| Pulse pressure≥60 mm Hg | 48 | 16 | 32 | |||
| Yes | 46 (2.7) | 34 (4.1) | 12 (1.4) | |||
| No | 1642 (97.3) | 789 (95.9) | 853 (98.6) | |||
| Waist circumference, cm, mean (SD) | 50 | 84.4 (12.3) | 17 | 92.2 (9.5) | 33 | 76.9 (9.6) |
| High waist circumference¶ | 50 | 17 | 33 | |||
| Yes | 229 (13.6) | 124 (15.1) | 105 (12.2) | |||
| No | 1457 (86.4) | 698 (84.9) | 759 (87.9) | |||
| Body mass index, kg/m2, mean (SD) | 18 | 25.3 (3.9) | 8 | 26.2 (3.4) | 10 | 24.4 (4.2) |
| Body mass index≥25 kg/m2 | 18 | 8 | 10 | |||
| Yes | 843 (49.1) | 520 (62.6) | 323 (36.4) | |||
| No | 875 (50.9) | 311 (37.4) | 564 (63.6) | |||
| Alcohol abuse** | 4 | 1 | 3 | |||
| Yes | 106 (6.1) | 61 (7.3) | 45 (5.0) | |||
| No | 1626 (93.9) | 777 (92.7) | 849 (95.0) | |||
| Daily smoking | 4 | 1 | 3 | |||
| Yes | 200 (11.6) | 91 (10.9) | 109 (12.2) | |||
| No | 1532 (88.5) | 747 (89.1) | 785 (87.8) | |||
| Physical activity†† | 4 | 1 | 3 | |||
| Yes | 898 (51.9) | 465 (55.5) | 433 (48.4) | |||
| No | 834 (48.2) | 373 (44.5) | 461 (51.6) | |||
| Psychological distress score, mean (STD) | 6 | 15.3 (11.4) | 7 | 19.0 (12.5) | ||
| High psychological distress score‡‡ | 13 | 6 | 7 | |||
| Yes | 381 (22.1) | 143 (17.2) | 238 (26.7) | |||
| No | 1342 (77.9) | 690 (82.8) | 652 (73.3) | |||
| Hours worked per week for the organisation | 24 | 13 | 11 | |||
| ≤40 | 1601 (93.5) | 748 (90.6) | 853 (96.3) | |||
| >40 | 111 (6.5) | 78 (9.4) | 33 (3.7) | |||
| Hours worked per week for another organisation | 30 | 10 | 20 | |||
| 0 | 1477 (86.6) | 698 (84.2) | 779 (88.8) | |||
| ≥1 | 229 (13.4) | 131 (15.8) | 98 (11.2) | |||
| Employee status, follow-up (2015–2018) | 2 | 1 | 1 | |||
| Yes | 507 (29.2) | 230 (27.5) | 277 (30.9) | |||
| No | 1222 (70.5) | 606 (72.3) | 616 (68.8) | |||
| Imprecise | 5 (0.3) | 2 (0.24) | 3 (0.33) | |||
| Personal history of cardiovascular disease§§ | 8 | 1 | 7 | |||
| Yes | 101 (5.8) | 54 (6.4) | 47 (5.3) | |||
| No | 1627 (94.2) | 784 (93.6) | 843 (94.7) | |||
| Family history of cardiovascular disease¶¶ | 34 | 15 | 19 | |||
| Yes | 784 (46.1) | 356 (43.2) | 428 (48.8) | |||
| No | 897 (52.7) | 460 (55.8) | 437 (49.8) | |||
| Don’t know | 21 (1.23) | 8 (1.0) | 13 (1.5) | |||
| Gaziano’s predicted cardiovascular risk score | 53 | 18 | 35 | |||
| Low | 1453 (86.3) | 639 (77.8) | 814 (94.4) | |||
| Moderate or high | 230 (13.7) | 182 (22.2) | 48 (5.6) |
*Canadian dollars.
†Diabetes was measured by the item ‘has a doctor ever told you that you have diabetes?’.
‡Hypercholesterolaemia was measured by the item ‘has a doctor, nurse or other healthcare professional ever told you that your cholesterol level is too high?’.
§Hypertension status refers to participants who had high blood pressure or those who reported taking medication to lower their blood pressure.
¶High waist circumference≥88 cm (in women) or ≥102 cm (in men).
**10 or more drinks a week in women or 15 or more drinks a week in men.
††Performed leisure physical activity for 20–30 min per session at least two times per week.
‡‡Psychological distress score greater than or equal to the highest quintile (score>26.19).
§§Personal history of angina pectoris, unstable angina, acute myocardial infarction, coronary bypass surgery, percutaneous coronary intervention, stroke.
¶¶A member of the immediate family (father, mother, brother or sister) has had a cardiac medical problem (angina, myocardial infarction, coronary bypass) or a stroke (paralysis, embolism, haemorrhage, thrombosis) under the age of 60 years.
Table 2 presents mean arterial stiffness at follow-up in men and women according to main risk factors for CVDs and psychosocial work-related factor at baseline. Arterial stiffness (mean:8.1±1.7 m/s) was higher in men, in older participants and among those with high BP, diabetes, hypercholesterolaemia, high waist circumference, high BMI and moderate or high cardiovascular risk score.
Table 2.
Arterial stiffness at follow-up (2015–2018) in men and women according to main cardiovascular diseases risk factors and psychosocial work-related factor at baseline (1999–2001)
| All, 1736 | Men, 839 | Women, 897 | ||||
| N* | 8.1 (1.7) | N* | 8.6 (1.9) | N* | 7.7 (1.4) | |
| Age, years | ||||||
| <55 | 1602 | 8.0 (1.5) | 750 | 8.4 (1.7) | 852 | 7.7 (1.3) |
| ≥55 | 134 | 9.7 (2.3) | 89 | 10.0 (2.6) | 45 | 9.1 (1.5) |
| Systolic blood pressure, mm Hg | ||||||
| <140 | 1625 | 8.1 (1.6) | 750 | 8.5 (1.8) | 875 | 7.7 (1.4) |
| ≥140 | 111 | 9.2 (1.9) | 89 | 9.4 (1.9) | 22 | 8.7 (1.7) |
| Diastolic blood pressure mm Hg | ||||||
| <90 | 1567 | 8.1 (1.7) | 717 | 8.5 (1.9) | 850 | 7.7 (1.4) |
| ≥90 | 169 | 8.9 (1.7) | 122 | 9.1 (1.7) | 47 | 8.4 (1.5) |
| Hypertension status† | ||||||
| Yes | 298 | 8.9 (1.9) | 206 | 9.2 (2.0) | 92 | 8.4 (1.6) |
| No | 1416 | 8.0 (1.6) | 620 | 8.4 (1.8) | 796 | 7.7 (1.3) |
| High pulse pressure‡ (>60 mm Hg) | ||||||
| Yes | 46 | 9.4 (2.3) | 34 | 9.43 (2.4) | 12 | 9.2 (2.0) |
| No | 1642 | 8.1 (1.7) | 789 | 8.5 (1.8) | 853 | 7.7 (1.4) |
| Diabetes§ | ||||||
| Yes | 34 | 9.7 (3.0) | 16 | 11.3 (3.5) | 18 | 8.3 (1.6) |
| No | 1702 | 8.1 (1.6) | 823 | 8.5 (1.8) | 879 | 7.7 (1.4) |
| Hypercholesterolaemia¶ | ||||||
| Yes | 493 | 8.5 (1.8) | 320 | 8.8 (1.9) | 173 | 7.9 (1.4) |
| No | 1242 | 8.0 (1.6) | 518 | 8.4 (1.8) | 724 | 7.7 (1.4) |
| High waist circumference** | ||||||
| Yes | 229 | 8.6 (1.8) | 124 | 9.0 (2.1) | 105 | 8.0 (1.3) |
| No | 1457 | 8.1 (1.7) | 715 | 8.5 (1.8) | 792 | 7.7 (1.4) |
| Body mass index, kg/m2, mean (SD) | ||||||
| <25 | 893 | 7.9 (1.5) | 319 | 8.4 (1.7) | 574 | 7.7 (1.4) |
| ≥25 | 843 | 8.4 (1.8) | 520 | 8.7 (1.9) | 323 | 7.9 (1.4) |
| Daily smoking | ||||||
| Yes | 200 | 8.3 (1.7) | 91 | 8.7 (1.9) | 109 | 7.9 (1.4) |
| No | 1532 | 8.1 (1.7) | 747 | 8.5 (1.8) | 785 | 7.7 (1.4) |
| Physical activity†† | ||||||
| Yes | 898 | 8.1 (1.7) | 465 | 8.5 (1.8) | 433 | 7.6 (1.4) |
| No | 834 | 8.2 (1.7) | 373 | 8.7 (1.9) | 461 | 7.8 (1.4) |
| Gaziano’s predicted cardiovascular risk score | ||||||
| Low | 1453 | 7.9 (1.5) | 639 | 8.3 (1.6) | 814 | 7.7 (1.3) |
| Moderate or high | 230 | 9.5 (2.1) | 182 | 9.6 (2.2) | 48 | 9.1 (1.6) |
| Number of accumulated cardiovascular risk factors | ||||||
| 0–1 | 1489 | 8.0 (1.6) | 690 | 8.4 (1.7) | 799 | 7.7 (1.4) |
| 2+ | 194 | 9.1 (2.1) | 131 | 9.4 (2.3) | 63 | 8.4 (1.6) |
| Family history of cardiovascular disease‡‡ | ||||||
| Yes | 784 | 8.2 (1.7) | 356 | 8.6 (1.9) | 428 | 7.8 (1.4) |
| No | 897 | 8.1 (1.6) | 460 | 8.5 (1.8) | 437 | 7.6 (1.3) |
| Don’t know | 21 | 7.7 (1.8) | 8 | 8.4 (2.5) | 13 | 7.3 (1.2) |
| Job strain | ||||||
| Low strain | 298 | 8.3 (1.8) | 174 | 8.7 (1.9) | 124 | 7.8 (1.4) |
| Passive | 592 | 8.1 (1.7) | 237 | 8.6 (1.8) | 355 | 7.7 (1.5) |
| Active | 486 | 8.2 (1.8) | 280 | 8.4 (2.0) | 206 | 7.8 (1.4) |
| High strain | 344 | 8.0 (1.4) | 141 | 8.5 (1.6) | 203 | 7.6 (1.2) |
| Effort–reward imbalance | ||||||
| Yes | 408 | 8.2 (1.7) | 197 | 8.6 (1.9) | 211 | 7.8 (1.4) |
| No | 1281 | 8.1 (1.7) | 618 | 8.6 (1.9) | 663 | 7.7 (1.4) |
Arterial stiffness (m/s) in different subgroups are presented as mean and SD.
*The number of observations used.
†Hypertension status refers to participants who had high blood pressure or those who reported taking medication to lower their blood pressure.
‡Pulse pressure = systolic blood pressure – diastolic blood pressure.
§Diabetes was measured by the item ‘has a doctor ever told you that you have diabetes?’.
¶Hypercholesterolaemia was measured by the item ‘has a doctor, nurse or other health care professional ever told you that your cholesterol level is too high?’.
**High waist circumference: ≥88 cm (in women) or ≥102 cm (in men).
††Performed leisure physical activity for 20–30 min per session at least two times per week
‡‡A member of the immediate family (father, mother, brother or sister) has had a cardiac medical problem (angina, myocardial infarction, coronary bypass) or a stroke (paralysis, embolism, haemorrhage, thrombosis) under the age of 60 years.
Table 3 presents the association between psychosocial work-related factors at baseline and arterial stiffness at follow-up. In men, arterial stiffness was slightly higher in those with passive jobs. In women, arterial stiffness was higher in participants exposed to ERI. All differences were modest and not statistically significant, with CIs including the null value.
Table 3.
Arterial stiffness (m/s) mean differences at follow-up (2015–2018) and 95% CIs according to psychosocial work-related factors at baseline (1999–2001) in men and women
| Modele I | Modele II | Modele III | Modele IV | |
| Job strain in men | ||||
| Missing values/785 observations read | 6 | 28 | 55 | 79 |
| Low strain | Ref. | Ref. | Ref. | Ref. |
| Passive | 0.04 (−0.26 to 0.33) | 0.11 (−0.19 to 0.41) | 0.16 (−0.15 to 0.47) | 0.19 (−0.13 to 0.51) |
| Active | 0.11 (−0.51 to 0.29) | 0.14 (−0.50 to 0.23) | 0.14 (−0.51 to 0.23) | 0.05 (−0.42 to 0.31) |
| High job strain | 0.07 (−0.68 to 0.53) | 0.04 (−0.50 to 0.58) | 0.05 (−0.61 to 0.51) | 0.02 (−0.55 to 0.50) |
| Job strain in women | ||||
| Missing values/850 observations read | 9 | 44 | 86 | 110 |
| Low strain | Ref. | Ref. | Ref. | Ref. |
| Passive | 0.09 (−0.35 to 0.18) | 0.21 (−0.44 to 0.02) | 0.20 (−0.42 to 0.03) | 0.23 (−0.47 to 0.00) |
| Active | 0.03 (−0.31 to 0.24) | 0.06 (−0.31 to 0.18) | 0.03 (−0.30 to 0.24) | 0.11 (−0.39 to 0.16) |
| High job strain | 0.14 (−0.47 to 0.20) | 0.25 (−0.54 to 0.03) | 0.20 (−0.53 to 0.13) | 0.27 (−0.59 to 0.06) |
| ERI in men | ||||
| Missing values/785 observations read | 22 | 44 | 68 | 79 |
| ERI (categorical variable) | ||||
| No | Ref. | Ref. | Ref. | Ref. |
| Yes | 0.13 (−0.22 to 0.47) | 0.02 (−0.27 to 0.31) | 0.07 (−0.39 to 0.24) | 0.04 (−0.35 to 0.28) |
| ERI (continuous variable) | 0.21 (−0.75 to 1.17) | 0.06 (−0.89 to 0.76) | 0.27 (−1.19 to 0.66) | 0.16 (−1.20 to 0.89) |
| ERI in women | ||||
| Missing values/850 observations read | 21 | 53 | 94 | 110 |
| ERI | ||||
| No | Ref. | Ref. | Ref. | Ref. |
| Yes | 0.13 (−0.14 to 0.39) | 0.05 (−0.16 to 0.27) | 0.13 (−0.10 to 0.36) | 0.18 (−0.08 to 0.43) |
| ERI (continuous form) | 0.17 (−0.36 to 0.69) | 0.04 (−0.46 to 0.38) | 0.12 (−0.25 to 0.49) | 0.18 (−0.28 to 0.64) |
Model I: unadjusted.
Model II: I+age, education, income, marital status, children, familial history of cardiovascular disease at baseline.
Model III: II+systolic blood pressure (mm Hg), diastolic blood pressure (mm Hg), diabetes, hypercholesterolaemia, body mass index (kg/m2), waist circumference (cm), lifestyle (alcohol abuse, daily smoking, physical activity), psychological distress score at baseline.
Model IV: III+hours worked per week for the organisation, hours worked per week for another organisation, effort–reward imbalance (when studying the effect of job strain) or job strain (when studying the effect of effort–reward imbalance) at baseline.
Models are restricted to people with no personal history of cardiovascular disease at baseline.
ERI, effort–reward imbalance.
Table 4 presents the association between psychosocial work-related factors and arterial stiffness according to BP at baseline. The high job strain group had higher arterial stiffness (1.38 m/s (95% CI: 0.57 to 2.19)) among participants with high diastolic BP (DBP) (≥90 mm Hg) and lower arterial stiffness (−0.25 (95% CI: −0.48 to −0.02)) among those with lower DBP (<90 mm Hg). The same trend was observed for systolic BP. The high job strain group had higher arterial stiffness (0.84 m/s (95% CI: −0.35 to 2.03), p=0.17) among those with systolic BP≥140 mm Hg. Arterial stiffness was also higher in the high job strain (3.00 (95% CI: 1.18 to 4.76)) and the passive (2.06 (95% CI: 0.69 to 3.44)) groups among participants with pulse pressure˃60 mm Hg. However, only 43 participants had high pulse pressure. ERI was associated with lower arterial stiffness in participants with systolic BP≥140 mm Hg (−1.17 (95% CI: −2.12 to −0.22)), in those with DBP≥90 mm Hg (−0.48 (95% CI: −1.10 to 0.14)) and with pulse pressure˃60 mm Hg (−2.06 (95% CI: −3.33 to −0.79)) (table 4).
Table 4.
Arterial stiffness (m/s) mean differences at follow-up (2015–2018) and 95% CIs according to psychosocial work-related factors at baseline (1999–2001) stratified by blood pressure at the time of exposure
| Systolic blood pressure, mm Hg | Diastolic blood pressure, mm Hg | Pulse pressure, mm Hg | ||||
| <140 | ≥140 | <90 | ≥90 | ≤60 | >60 | |
| Missing/observations read | 174/1529 | 15/106 | 166/1476 | 23/159 | 139/1546 | 4/43 |
| Job strain | ||||||
| Low strain | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Passive | 0.02 (−0.23 to 0.19) | 0.27 (−1.28 to 0.74) | 0.05 (−0.28 to 0.18) | 0.03 (−0.72 to 0.79) | 0.06 (−0.27 to 0.14) | 1.54 (−0.47 to 3.55) |
| Active | 0.05 (−0.28 to 0.18) | 0.13 (−1.05 to 0.80) | 0.08 (−0.33 to 0.16) | 0.43 (−0.18 to 1.04) | 0.09 (−0.31 to 0.13) | 2.06 (0.69 to 3.44) |
| High job strain | 0.17 (−0.40 to 0.07) | 0.84 (−0.35 to 2.03) | 0.25 (−0.48 to −0.02) | 1.38 (0.57 to 2.19) | 0.16 (−0.40 to 0.08) | 3.00 (1.18 to 4.76) |
| Missing/observations read | 174/1529 | 15/106 | 166/1476 | 23/159 | 139/1546 | 4/43 |
| ERI | ||||||
| No | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Yes | 0.13 (−0.08 to 0.34) | 1.17 (−2.12 to −0.22) | 0.11 (−0.12 to 0.35) | 0.48 (−1.10 to 0.14) | 0.08 (−0.10 to 0.27) | 2.06 (−3.33 to −0.79) |
| ERI (continuous form) | 0.02 (−0.55 to 0.50) | 0.66 (−1.44 to 2.77) | 0.04 (−0.57 to 0.50) | 0.34 (−1.99 to 1.31) | 0.04 (−0.56 to 0.48) | 0.43 (−4.69 to 5.55) |
Models are adjusted for sex and covariates at baseline (age, education, income, marital status, children, systolic blood pressure (mm Hg), diastolic blood pressure (mm Hg), diabetes, hypercholesterolaemia, body mass index (kg/m2), waist circumference (cm), alcohol abuse, daily smoking, physical activity, familial history of cardiovascular disease, psychological distress, hours worked per week for the organisation, hours worked per week for another organisation, ERI (when studying the effect of job strain) or job strain (when studying the effect of ERI).
Models are restricted to people with no personal history of cardiovascular disease at baseline.
Pulse pressure = systolic blood pressure – diastolic blood pressure.
ERI, effort–reward imbalance.
Supplementary analyses showed that arterial stiffness tended to be higher in participants exposed to job strain who were≥55 years old or had a moderate or high CVD risk score. The ERI group had higher arterial stiffness in the 55+ age stratum (0.52 (95% CI: −0.67 to 1.71) (online supplemental table S1). Psychosocial work-related factors were not associated with arterial stiffness when stratifying according to employment status and duration of retirement (online supplemental table S2a and S2b). The findings were similar with and without participants with history of CVD (online supplemental table S3) and before and after multiple imputation and inverse probability weighting (online supplemental table S4).
bmjopen-2023-073649supp001.pdf (226.7KB, pdf)
Discussion
In the present study, arterial stiffness was not significantly higher in men and women exposed to high job strain and ERI overall. However, among participants with higher DBP at midlife, high job strain was associated with higher arterial stiffness 16 years later. This association was robust to adjustment for sociodemographics, lifestyle-related risk factors, CVD risk factors and other factors from the work environment.
Prior studies assessing the relationship between psychosocial work-related factors and arterial stiffness were cross-sectional.5–11 Most suggest a deleterious effect.5–9 Studies suggesting a protective10 or no effect11 involved relatively young participants (≤40 years). Studies showing deleterious associations included people aged over 40 years on average,5–7 9 a high proportion of smokers (>40%)5 6 or targeted workers in professions at higher risk of developing CVD such as firefighters.9 Given their cross-sectional design, previous studies do not inform on different aspects of the temporal relationship between psychosocial work-related factors and arterial stiffness, including the optimal time window and follow-up period. The time required between exposure to psychosocial work-related factors and arterial stiffness may vary according to the position of individuals on the cardiovascular continuum. A longer follow-up time could be required for participants who are at an earlier stage than for those who are at a more advanced stage of progression. In the present study, high job strain was associated with increased arterial stiffness 16 years later (1.38 m/s), in participants with high DBP at time of exposure assessment (baseline). The mean age of participants with high DBP at baseline was 47 years old. Given that diastolic hypertension predominates in relatively young individuals, at a relatively early stage of the cardiovascular continuum and that CVD develops over at least a decade, it is reasonable to postulate that the follow-up period used in the present study was appropriate for measuring the association between midlife work-related factors and arterial stiffness in participants with high DBP at midlife.12 27
Increased arterial stiffness was also observed among participants with high systolic BP. This association was however of smaller magnitude and did not reach statistical significance. This is consistent with the natural history of systolic/DBP progression and its link with CVD diseases onset.27 On the contrary, high job strain was associated with reduced arterial stiffness in participants who did not have high BP. Measuring the association between midlife stressors and arterial stiffness among people who do not have high BP may require a longer follow-up, which could explain the presence of this counterintuitive protective association. This is consistent with a previous cross-sectional study which showed a protective association between job strain index and brachial–ankle PWV (−1.38 m/s, p<0.01). This previous study included young participants (median age: 31 years) with diastolic (median: 79 mm Hg) and systolic (median: 110 mm Hg) BP in the normal range.10 Further studies are needed to confirm these results.
Due to limited statistical power, caution should be exercised in interpreting the trends of increased arterial stiffness among participants exposed to job strain in moderate to high cardiovascular risk score and older participants’ strata. These results should be regarded as hypothesis generating. In our study, the participants who remained actively employed at follow-up were relatively young (on average 39 years old) and had a low cardiovascular risk score (98%) at baseline. Younger age combined with low cardiovascular risk score may contribute to the absence of observed association. Indeed, among this younger subgroup, the timeframe for arterial stiffness assessment could have been suboptimal. ERI was associated with lower arterial stiffness in participants with high systolic BP, DBP and high pulse pressure. This is counterintuitive and needs to be replicated.
In normotensive people without additional cardiovascular risk factors aged 60–69, the reference value for arterial stiffness is on average 10.3 m/s.28 29 In the present study, the average value (8.3 m/s) of participants in this age group (n=930) is lower. The attrition due to non-response and loss to follow-up may have contributed to these finding given the loss of individuals who may be sicker than those who participated, as demonstrated in this cohort.30 As expected, participants at higher risk of CVD (men, older age, high BP, diabetes, hypercholesterolaemia, high waist circumference, high BMI, moderate or high cardiovascular risk score) generally had higher arterial stiffness than those at lower risk. The observed association between psychosocial work-related factors and cfPWV can be translated into vascular age. For example, among participants with elevated DBP, those exposed to job strain (mean age: 63.1) had a mean cfPWV of 9.4 m/s, which is compatible with a vascular age of 50–59 years.28 29 However, participants with elevated DBP in the low strain category (mean age: 64.9) had a mean cfPWV=7.9 m/s, which is compatible with a vascular age of 30–39 years.28 29 The observed difference in cfPWV among participants exposed to job strain within this subgroup is therefore compatible with a decade discrepancy in vascular age.
Chronic stress accelerates ageing of arteries by incompletely understood mechanisms. Chronic stress can on one hand activate the sympathetic nervous system interconnected with the renin-angiotensin-aldosterone system and endothelin-1 activity and on the other hand promote risky lifestyle.31 32 This leads to changes in vascular cell phenotypes and to thickening of the arterial innermost and intermediate layers, stiffness and increase in systolic and pulse pressure later on.31 Increased arterial stiffness causes excessive transmission of pulse pressure that can damage the microcirculation of target organs, which increases the risk of cardiovascular events.33 Older subjects or those with cardiovascular risk factors could have decreased endothelial regeneration capacity due to a reduced number of circulating progenitor endothelial cells.31 34 A reduced regenerative capacity could explain a deleterious effect of job strain in people with an increased risk of developing a cardiovascular event given their age, cardiovascular risk score or high BP. Al Mheid et al observed significant interactions (p≤0.005) between age and the burden of cardiovascular risk factors (smoking, diabetes mellitus, hypertension or hyperlipidemia), such that for younger subjects (<40 years), cardiovascular risk factors were associated with increased progenitor cells counts, whereas for older subjects (>60 years), cardiovascular risk factors and CVD were associated with lower progenitor cells counts.34
Our study has several strengths. To our knowledge, this is the first study to examine the association between psychosocial work-related factors assessed at midlife and arterial stiffness assessed at older age, using a prospective cohort. The 16-year follow-up allowed exploration of long-term effects. Other strengths are the use of a gold standard arterial stiffness measurement and validated psychosocial work-related factors models, sequential adjustment by several potentially confounding factors, inverse probability weighting to minimise the potential for selection bias and subgroup analyses based on a priori evidence.
Our study also has limitations. First, the potential for selection bias due to a high proportion of missing values (40% (approximately 1048) out of 2621 participants) and losses to follow-up (19% (approximately 500) out of 2621) may underestimate associations.30 However, the associations were similar before and after accounting for potential selection bias using multiple imputations and inverse probability weighting, suggesting that this potential bias could not have explained our results. Second, the use of a single measure of exposure limits the capacity to capture fluctuations in exposure and can lead to non-differential misclassification of exposure that may underestimate the association. Third, measuring arterial stiffness in 1/3 of participants combined with attrition reduced statistical power. Fourth, the study population was entirely composed of white-collar workers. Caution is therefore advised in generalising to other types of occupations. The fact that our sample is composed exclusively of white-collar employees limits potential confounding by occupational physical burden (repetitive movements, lifting heavy loads, long walking distance …). Fifth, arterial stiffness was measured at a single time point (at follow-up only). Therefore, stiffness progression over time could not be assessed limiting the possibility to draw causal inferences. However, data on several other major cardiovascular risk factors (age, BP, cholesterol, smoking, etc) were controlled for, which minimised the possibility for participants in compared group to substantially differ regarding their overall cardiovascular profile at baseline.
Conclusion
Job strain exposure combined with high BP at midlife may have long-term deleterious effects on arterial stiffness. Interventions at midlife to reduce job strain may be considered as a potential way to manage CVD risk.
Supplementary Material
Acknowledgments
We thank all the participants of the study.
Footnotes
Contributors: VKM conceptualised and designed the study, performed the statistical analysis, drafted, reviewed and edited the manuscript. CB was responsible for the study concept, supervised the data collection and the methodological aspects, reviewed and edited the manuscript. DT supervised the analytical approach, revised the statistical analysis program, reviewed and edited the manuscript. AM supervised aspects related to arterial stiffness, blood pressure and other cardiovascular risk factors, reviewed and edited the manuscript. XT supervised the methodological aspects, reviewed and edited the manuscript and is
responsible for the overall content as the guarantor. MV, CED, BM, MG-O, GRD and NP reviewed and edited the manuscript.
Funding: This work was supported by the Canadian Institutes of Health Research (grant number MA-11364). VKM was the recipient of a research award from the FRQS and the CERSSPL-UL. DT was supported by a Junior-2 career award from the FRQS.
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request. Data cannot be shared publicly due to privacy concerns of study participants. However, data will be shared following a justified request to the corresponding author, conditional on permission from the Centre Hospitalier Universitaire de Québec—Université Laval (CHUdeQc-UL) ethical research committee.
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
This study involves human participants and was approved by The Centre Hospitalier Universitaire de Québec—Université Laval (CHUdeQc-UL) ethical research committee (2012-1674; DR-002-1409; F9H-63202). Participants gave informed consent to participate in the study before taking part.
References
- 1.O’Rourke MF, Safar ME, Dzau V. The cardiovascular continuum extended: aging effects on the aorta and microvasculature. Vasc Med 2010;15:461–8. 10.1177/1358863X10382946 [DOI] [PubMed] [Google Scholar]
- 2.Belkic KL, Landsbergis PA, Schnall PL, et al. Is job strain a major source of cardiovascular disease risk. Scand J Work Environ Health 2004;30:85–128. 10.5271/sjweh.769 [DOI] [PubMed] [Google Scholar]
- 3.Allan R, Fisher J. Work-related Psychosocial factors and heart disease. In: Heart and Mind: The Practice of Cardiac Psychology, 2nd edn. Washington: American Psychological Association, 2011: 269–85. 10.1037/13086-000 [DOI] [Google Scholar]
- 4.Vlachopoulos C, Aznaouridis K, Stefanadis C. Prediction of cardiovascular events and all-cause mortality with arterial stiffness: a systematic review and meta-analysis. J Am Coll Cardiol 2010;55:1318–27. 10.1016/j.jacc.2009.10.061 [DOI] [PubMed] [Google Scholar]
- 5.Michikawa T, Nishiwaki Y, Nomiyama T, et al. Job strain and arteriosclerosis in three different types of arteries among male Japanese factory workers. Scand J Work Environ Health 2008;34:48–54. 10.5271/sjweh.1163 [DOI] [PubMed] [Google Scholar]
- 6.Utsugi M, Saijo Y, Yoshioka E, et al. Relationship between two alternative occupational stress models and arterial stiffness: a cross-sectional study among Japanese workers. Int Arch Occup Environ Health 2009;82:175–83. 10.1007/s00420-008-0319-z [DOI] [PubMed] [Google Scholar]
- 7.Xiu JF, Zheng L, Wang G, et al. The relationship between chronic occupational stress and arterial stiffness: a cross-sectional study in Chinese workers. Heart 2012;98:E286. 10.1136/heartjnl-2012-302920ab.4 [DOI] [Google Scholar]
- 8.Kaewboonchoo O, Sembajwe G, Li J. Associations between job strain and arterial stiffness: a large survey among enterprise employees from Thailand. Int J Environ Res Public Health 2018;15:659. 10.3390/ijerph15040659 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Yook Y-S. Firefighters' occupational stress and its correlations with cardiorespiratory fitness, arterial stiffness, heart rate variability, and sleep quality. PLoS One 2019;14:e0226739. 10.1371/journal.pone.0226739 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Nomura K, Nakao M, Karita K, et al. Association between work-related psychological stress and arterial stiffness measured by brachial-ankle pulse-wave velocity in young Japanese males from an information service company. Scand J Work Environ Health 2005;31:352–9. 10.5271/sjweh.918 [DOI] [PubMed] [Google Scholar]
- 11.Chou L-P, Li C-Y, Hu SC. Work-related psychosocial hazards and arteriosclerosis a cross-sectional study among medical employees in a regional hospital in Taiwan. Int Heart J 2015;56:644–50. [DOI] [PubMed] [Google Scholar]
- 12.Webb AJS. Progression of arterial stiffness is associated with midlife diastolic blood pressure and transition to late-life hypertensive phenotypes. J Am Heart Assoc 2020;9:e014547. 10.1161/JAHA.119.014547 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Trudel X, Gilbert-Ouimet M, Milot A, et al. Cohort profile: the prospective Québec (PROQ) study on work and health. Int J Epidemiol 2018;47:693–693i. 10.1093/ije/dyy026 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Karasek R, Brisson C, Kawakami N, et al. The job content questionnaire (JCQ): an instrument for internationally comparative assessments of psychosocial job characteristics. J Occup Health Psychol 1998;3:322–55. 10.1037//1076-8998.3.4.322 [DOI] [PubMed] [Google Scholar]
- 15.Karasek R, Schwartz J, Pieper C. Validation of a survey instrument for job-related cardiovascular illness. New York, NY: Department of Industrial Engineering and Operations Research, Columbia University, 1983. [Google Scholar]
- 16.Brisson C, Blanchette C, Guimont C, et al. Reliability and validity of the French version of the 18-item karasek job content questionnaire. Work & Stress 1998;12:322–36. 10.1080/02678379808256870 [DOI] [Google Scholar]
- 17.Niedhammer I, Siegrist J, Landre M, et al. Étude des Qualités Psychométriques de la version Française Du Modèle Du Déséquilibre efforts/Récompenses. Revue d’épidémiologie et de Santé Publique 2000;48:419–37. [PubMed] [Google Scholar]
- 18.Karasek R, Gordon G, Pietrokovsky C, et al. Job Content Questionnaire: Questionnaire and Users’ Guide. Lowell: University of Massachusetts, 1985. [Google Scholar]
- 19.Aboa-Éboulé C, Brisson C, Blanchette C, et al. Effort-reward imbalance at work and psychological distress: a validation study of post-myocardial infarction patients. Psychosom Med 2011;73:448–55. 10.1097/01.psy.0000399790.82499.d7 [DOI] [PubMed] [Google Scholar]
- 20.Di Iorio BR, Cucciniello E, Alinei P, et al. Reproducibility of regional pulse-wave velocity in uremic subjects. Hemodial Int 2010;14:441–6. 10.1111/j.1542-4758.2010.00471.x [DOI] [PubMed] [Google Scholar]
- 21.Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes. Biometrics 1986;42:121–30. [PubMed] [Google Scholar]
- 22.Gaziano TA, Young CR, Fitzmaurice G, et al. Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: the NHANES I follow-up study cohort. Lancet 2008;371:923–31. 10.1016/S0140-6736(08)60418-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Kivimäki M, Pentti J, Ferrie JE, et al. Work stress and risk of death in men and women with and without Cardiometabolic disease: a Multicohort study. Lancet Diabetes Endocrinol 2018;6:705–13. 10.1016/S2213-8587(18)30140-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Kivimäki M, Theorell T, Westerlund H, et al. Job strain and ischaemic disease: does the inclusion of older employees in the cohort dilute the association? The Wolf Stockholm study. J Epidemiol Community Health 2008;62:372–4. 10.1136/jech.2007.063578 [DOI] [PubMed] [Google Scholar]
- 25.White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med 2011;30:377–99. 10.1002/sim.4067 [DOI] [PubMed] [Google Scholar]
- 26.Robins JM, Finkelstein DM. Correcting for noncompliance and dependent censoring in an AIDS clinical trial with inverse probability of censoring weighted (IPCW) log-rank tests. Biometrics 2000;56:779–88. 10.1111/j.0006-341x.2000.00779.x [DOI] [PubMed] [Google Scholar]
- 27.Franklin SS, Larson MG, Khan SA, et al. Does the relation of blood pressure to coronary heart disease risk change with aging? the Framingham heart study. Circulation 2001;103:1245–9. 10.1161/01.cir.103.9.1245 [DOI] [PubMed] [Google Scholar]
- 28.Laurent S, Boutouyrie P. Arterial stiffness and hypertension in the elderly. Front Cardiovasc Med 2020;7. 10.3389/fcvm.2020.544302 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Mattace-Raso F, Hofman A, Verwoert G. Determinants of pulse wave velocity in healthy people and in the presence of cardiovascular risk factors: establishing normal and reference values. Eur Heart J 2010;31:2338–50. 10.1093/eurheartj/ehq165 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Massamba VK, Talbot D, Milot A, et al. Assessment of the healthy worker survivor effect in the relationship between psychosocial work-related factors and hypertension. Occup Environ Med 2019;76:414–21. 10.1136/oemed-2018-105460 [DOI] [PubMed] [Google Scholar]
- 31.Wang M, Monticone RE, McGraw KR. Proinflammatory arterial stiffness syndrome: a signature of large arterial aging. J Vasc Res 2018;55:210–23. 10.1159/000490244 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.LaRocca TJ, Martens CR, Seals DR. Nutrition and other lifestyle influences on arterial aging. Ageing Res Rev 2017;39:106–19. 10.1016/j.arr.2016.09.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Vasan RS, Short MI, Niiranen TJ, et al. Interrelations between arterial stiffness, target organ damage, and cardiovascular disease outcomes. J Am Heart Assoc 2019;8:e012141. 10.1161/JAHA.119.012141 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Al Mheid I, Hayek SS, Ko Y-A, et al. Age and human egenerative capacity impact of cardiovascular risk factors. Circ Res 2016;119:801–9. 10.1161/CIRCRESAHA.116.308461 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
bmjopen-2023-073649supp001.pdf (226.7KB, pdf)
Data Availability Statement
Data are available upon reasonable request. Data cannot be shared publicly due to privacy concerns of study participants. However, data will be shared following a justified request to the corresponding author, conditional on permission from the Centre Hospitalier Universitaire de Québec—Université Laval (CHUdeQc-UL) ethical research committee.