Impact of chronic stress exposure on cognitive performance incorporating the active and healthy aging (AHA) concept within the cross-sectional Bern Cohort Study 2014 (BeCS-14)

Overall, 624 subjects were included in the BeCS-14. Of those, 147 subjects (37.4% male, 62.6% female) took part in subgroup “cognition” (supplementary table 1). Mean age was 38.0 ± 15.3 years. About one-third (31.3%) had a degree from university or advanced technical college, respectively. Most participants reported being employees (54.5%), 16.1% being in leading positions and 22.4% being students. The monthly gross income was less than 5000 CHF for 50.0%. The majority (80.1%) of the participants reported a regular alcohol consumption at least twice a month, 35.9% at least twice a week, and 23.1% had at least one drink per day. The majority were never-smoker (63.9%), physically active (till sweating) at least once a week (75.5%) and most participants reported sleeping between 7 and 8 h a night (72.1%). When comparing age-based subpopulations, there were statistically significant differences within the categories education, job status, monthly gross income and physical activity. Age group 2 (26–49 years) showed the highest percentage of participants with a degree from the university or advanced technical college. In general, job status and monthly gross income were higher in participants aged ≥ 26 years, whereas physical activity was significantly lower in participants aged ≥ 50 years.

Personal history

Life-threatening events were reported by two participants (1.4%; stroke n = 1, myocardial infarction n = 1). The prevalence of cardiovascular risk factors was 7.2% for hypertension, 8.6% for dyslipidemia, and 0.7% for diabetes mellitus. Five participants (3.7%) suffered from a malignant disease, 14.2% from depression. The prevalence of musculoskeletal disease was 13.6% (muscular disease n = 1, rheumatoid arthritis n = 1, arthrosis n = 12, osteoporosis n = 5). Comparison of age-based subpopulations showed statistically significant differences for sleep apnea, dyslipidemia, malignant disease, arthrosis and osteoporosis with a higher prevalence in subjects aged ≥ 50 years.

Bio-functional status (BFS) and bio-functional age (BFA)

Table 2 presents the results for individual BFS items. Of those above age 35 years, the mean difference between the chronological and bio-functional age (Age-BFA-index) was 7.8 ± 7.8 years, indicating that the bio-functional age of the participants was about 8 year-equivalents below their chronological age (Table 2).

Cognitive performance was assessed by the BFS cognitive-mental function subdomain (M1–M12) (Table 2) and the IGD (subtests A1-A12, subdomains total, ST/WM, L, VeM, ViM, DR) (supplementary table 3), respectively. According to the IGD, the age-adjusted mean performance percentile rank was 52.9 ± 27.7 (range 0–100). The results of the BFS cognitive-mental function subdomain and the IGD subdomains were then adjusted for age, sex and education (supplementary tables 2, 4).

When adjusting the BFS cognitive-mental function subdomain for age, there were significant differences between age groups for all subdomains. In general, age group 3 (≥ 50 years) performed significantly worse than age group 1 (≤ 25 years) (M2, M4 -M12) and age group 2 (26–49 years) (M1, M2, M4, M5, M6, M7, M9, M11, M12). In contrast, differences between age group 1 (≤ 25 years) and 2 (26–49 years) were mostly non-significant (M2–M12). Similarly, the IGD showed significant differences between age group 3 (≥ 50 years) and age group 2 (26–49 years) resp. age group 1 (≤ 25 years) in subtests A1–A7, A9–A12 and all subdomains (Total, ST/WM, L, VeM, ViM, DR), while differences between age group 1 (≤ 25 years) and 2 (26–49 years) were mostly non-significant.

When adjusting the BFS cognitive-mental function subdomain for education level, there were significant group differences for verbal reaction time (M4), cognitive reaction time (M5), cognitive switching capability (M6), ability to concentrate (M8) and strategic thinking (M9), respectively. In general, subjects with the highest education level (university/federal institute of technology (ETH)/college of higher education) performed best, while subjects with the lowest education level (secondary school/district school) showed the worst results. In the IGD a similar pattern was observed. For all but one subdomain (prospective memory (A1)), educational level had a significant impact on IGD subdomains.

When adjusting the BFS cognitive-mental function subdomain for sex, there were almost no differences. Only for pursuing reaction time (M2), women performed significantly better than men. Similarly, sex only had a minor impact on IGD subdomains.

Correlation analysis between the BFS cognitive-mental function subdomain and a validated cognitive performance test battery (IGD)

To prove the presentation of cognitive performance by the cognitive-mental BFS subdomain, a correlation analysis between the BFS and the validated IGD was performed, analogous to our preliminary study but with an expansion of the study population (Table 3). We found a significant inverse correlation between optical reaction time (M1), optical pursuing reaction time (M2), verbal reaction time (M4), cognitive reaction time (M5), cognitive switching capability (M6), strategic thinking (M9), changeover capability (M12), Stroop Test (M4–M6) and Stepping-stone-maze test (M9–M12) with total IGD and all IGD subdomains. This suggests that a person with better total memory (Total), short-term and working memory (ST/WM), learning ability (L), verbal memory (VeM), visual memory (ViM) and delayed recall (DR) performed better in these BFS cognitive-mental function subdomains. For the ability to concentrate (M7, M8), respectively, the Landolt test (M7–M8), memory performance (M10) and orientation capability (M11), all results of the total study population, correlated inversely with the IGD subdomains; however, some of these were non-significant; participants with a higher ability to concentrate (M7, M8) showed significantly better total memory (T), short-term and working memory (ST/WM), learning capacity (L) and visual memory (ViM), whereas for verbal memory (VeM) and delayed recall (DR), the correlation was inverse but not significant. In contrast, acoustic reaction time (M3) did not or positively correlated with IGD subdomains.

In a second step, correlation analysis between the BFS cognitive-mental function subdomain and IGD was performed for three age subgroups (≤ 25 years, 26–49 years, ≥ 50 years) (supplementary table 5). For subjects aged ≤ 25 years, the correlation between the BFS cognitive-mental function subdomain and IGD was weakest with five BFS subdomain items being significantly correlated to IGD subdomains. In detail, acoustic reaction time (M3), cognitive switching capability (M6), strategic thinking (M9), orientation capability (M11) and the Stroop test (M4–M6) were significantly correlated to most IGD subdomains (Total, ST/WM, L, VeM, ViM).

For subjects aged 26–49 years, the correlation between the BFS cognitive-mental function subdomain and IGD was stronger with seven BFS subdomain items showing significant correlations: optical pursuing reaction time (M2), acoustic reaction time (M3), cognitive switching capability (M6), strategic thinking (M9), memory performance (M10), Stroop test (M4–M6) and Stepping-stone-maze test (M9–M12). The strongest correlation was found for subjects aged ≥ 50 years. Here, ten BFS cognitive-mental function subdomain items showed significant correlations to IGD subdomains, with optical reaction time (M1), optical pursuing reaction time (M2), strategic thinking (M9) and changeover capability (M12) being significantly correlated to all IGD subdomains. Similarly, cognitive switching capability (M6), Stroop test (M4–M6) and Stepping stone-maze test (M9–M12) were significantly correlated to all IGD subdomains except for VeM. Acoustic, verbal and cognitive reaction time (M3, M4, M5) were significantly correlated to at least one IGD subdomain (Table 3).

Chronic stress exposure

Table 4 presents the results for chronic stress exposure assessed by TICS. The chronic stress level overall (SSCS) of the BeCS-14 subgroup “cognition” was comparable to the mean values (T50) of the TICS reference population, as well as the stress levels in the subdomains work overload, work discontent, lack of social recognition, social isolation and social tensions. However, chronic stress exposure by chronic worrying and pressure to perform were lower, whereas excessive demands at work and social overload were higher in the BeCS-14 subgroup “cognition”.

The TICS’ results (SSCS, subdomains) were then adjusted for age, sex and education (supplementary table 6). With respect to age, there were significant differences for chronic stress exposure overall (TICS-SSCS) and for the subdomains work overload, work discontent, pressure to perform, lack of social recognition and social overload. In general, chronic stress exposure was highest in age group 2 (26–49 years). Compared to their older counterparts (≥ 50 years), they had a significantly higher chronic stress level in the TICS subdomains work overload, work discontent, pressure to perform and lack of social recognition. Compared to their younger counterparts (≤ 25 years), chronic stress level was significantly higher in the TICS subdomain pressure to perform. On the contrary, chronic stress exposure was highest for the youngest age group (≤ 25 years) in the TICS subdomain work overload. Interestingly, sex did not have an impact on chronic stress exposure (SSCS, subdomains). For education, we found significant differences for chronic stress exposure overall (TICS-SSCS) and the subdomains excessive demands at work, work discontent, pressure to perform and social isolation with higher educated participants (Matura or university-degree/advanced technical college degree) showing higher chronic stress levels (Table 4).

Correlation analysis between the BFS cognitive-mental function subdomain and chronic stress exposure (TICS)

A correlation analysis between the BFS cognitive-mental function subdomain and TICS was performed to assess the impact of chronic stress exposure on cognitive function (Table 5). None but one (acoustic reaction time, M3) of the BFS cognitive-mental function subdomain items showed a significant correlation to overall chronic stress exposure (SSCS-TICS). When differentiating for TICS subdomains, this was also true for the subdomains lack of social recognition, social overload, social isolation and social tensions, respectively.

However, three TICS subdomains (work overload, work discontent, pressure to succeed) showed significant negative correlations to some BFS cognitive-mental function subdomains. In detail, work overload significantly negatively correlated with verbal and cognitive reaction time (M4, M5), cognitive switching capability (M6), ability to concentrate (M7) and the Stroop test (M4–M6), respectively. Work discontent showed the strongest negative correlation to the BFS with pursuing reaction time (M2), verbal reaction time (M4), cognitive switching capability (M6), strategic thinking (M9), changeover capability (12), Stroop test (M4–M6) and Stepping-stone-maze test (M9–M12) being significantly negatively correlated. Pressure to succeed showed a significant negative correlation to pursuing reaction time (M2), verbal and cognitive reaction time (M4, M5), cognitive switching capability (M6), strategic thinking (M9) as well as Stroop test (M4–M6) and Stepping-stone-maze test (M9–M12). This indicates that participants with higher chronic stress level, especially in the subcategories work overload, work discontent and pressure to succeed, i.e., predominantly work-related stress subdomains, showed a significantly negative correlation with the BFS cognitive-mental function subdomain and thus worse results than their less stressed counterparts.

Surprisingly, the BFS subdomains’ optical response (M1) and acoustic reaction time (M3) showed a significantly positive correlation with the TICS subdomains chronic worrying and excessive demands at work, work overload and work discontent, respectively. A higher chronic stress level in these subdomains is thus associated with a faster visual and optical reaction time.

TICS-SSCS and the difference between chronological and bio-functional age (Age–BFA index) were negatively (but not significantly) correlated (Pearson correlation − 0.12; p = 0.176). This was also true for the correlation between TICS subdomains and the age–BFA index. This finding indicates that higher chronic stress exposure was associated with bio-functional pro-aging in both sexes and thus underlines the results of our previous investigations [7] (Table 5).