Background This study examined the associations between accelerometer-derived sedentary time (ST), lower intensity physical activity (LPA), higher intensity physical activity (HPA) and the incidence of depressive symptoms over 4 years of follow-up. Methods We included 2082 participants from The Maastricht Study (mean ± s.d. age 60.1 ± 8.0 years; 51.2% men) without depressive symptoms at baseline. ST, LPA and HPA were measured with the ActivPAL3 activity monitor. Depressive symptoms were measured annually over 4 years of follow-up with the 9-item Patient Health Questionnaire (PHQ-9). Cox regression analysis was performed to examine the associations between ST, LPA, HPA and incident depressive symptoms (PHQ-9 ⩾ 10). Analyses were adjusted for total waking time per day, age, sex, education level, type 2 diabetes mellitus, body mass index, total energy intake, smoking status and alcohol use. Results During 7812.81 person-years of follow-up, 203 (9.8%) participants developed incident depressive symptoms. No significant associations [Hazard Ratio (95% confidence interval)] were found between sex-specific tertiles of ST (lowest v. highest tertile) [1.13 (0.76–1.66], or HPA (highest v. lowest tertile) [1.14 (0.78–1.69)] and incident depressive symptoms. LPA (highest v. lowest tertile) was statistically significantly associated with incident depressive symptoms in women [1.98 (1.19–3.29)], but not in men (p-interaction <0.01). Conclusions We did not observe an association between ST or HPA and incident depressive symptoms. Lower levels of daily LPA were associated with an increased risk of incident depressive symptoms in women. Future research is needed to investigate accelerometer-derived measured physical activity and ST with incident depressive symptoms, preferably stratified by sex.
The aim of this systematic review and meta‐analysis was to identify the genetic variants of (inter)national competing long‐distance runners and road cyclists compared with controls. The Medline and Embase databases were searched until 15 November 2021. Eligible articles included genetic epidemiological studies published in English. A homogenous group of endurance athletes competing at (inter)national level and sedentary controls were included. Pooled odds ratios based on the genotype frequency with corresponding 95% confidence intervals (95%CI) were calculated using random effects models. Heterogeneity was addressed by Q‐statistics, and I2. Sources of heterogeneity were examined by meta‐regression and risk of bias was assessed with the Clark Baudouin scale. This systematic review comprised of 43 studies including a total of 3938 athletes and 10 752 controls in the pooled analysis. Of the 42 identified genetic variants, 13 were investigated in independent studies. Significant associations were found for five polymorphisms. Pooled odds ratio [95%CI] favoring athletes compared with controls was 1.42 [1.12–1.81] for ACE II (I/D), 1.66 [1.26–2.19] for ACTN3 TT (rs1815739), 1.75 [1.34–2.29] for PPARGC1A GG (rs8192678), 2.23 [1.42–3.51] for AMPD1 CC (rs17602729), and 2.85 [1.27–6.39] for HFE GG + CG (rs1799945). Risk of bias was low in 25 (58%) and unclear in 18 (42%) articles. Heterogeneity of the results was low (0%–20%) except for HFE (71%), GNB3 (80%), and NOS3 (76%). (Inter)national competing runners and cyclists have a higher probability to carry specific genetic variants compared with controls. This study confirms that (inter)national competing endurance athletes constitute a unique genetic make‐up, which likely contributes to their performance level.
There is little agreement on the factors influencing endurance performance. Endurance performance often is described by surrogate variables such as maximum oxygen consumption, lactate threshold, and running economy. However, other factors also determine success and progression of high-level endurance athletes. Therefore, the aim was to identify the relevant factors for endurance performance assessed by international experts by adhering to a structured communication method (i.e., Delphi technique). Three anonymous evaluation rounds were conducted initiated by a list of candidate factors (n = 120) serving as baseline input variables. The items that achieved ≥70% of agreement in round 1 were re-evaluated in a second round. Items with a level of agreement of ≥70% in round 2 reached consensus and items with a level of agreement of 40–69% in round 2 were re-rated in a third round followed by a consensus meeting. Round 1 comprised of 27 panellists (n = 24 male) and in round 2 and 3 18 (n = 15 male) of the 27 panellists remained. Thus, the final endurance expert panel comprised of 18 international experts (n = 15 male) with 20 years of experience on average. The consensus report identified the following 26 factors: endurance capacity, running economy, maximal oxygen consumption, recovery speed, carbohydrate metabolism, glycolysis capacity, lactate threshold, fat metabolism, number of erythrocytes, iron deficiency, muscle fibre type, mitochondrial biogenesis, hydrogen ion buffering, testosterone, erythropoietin, cortisol, hydration status, vitamin D deficiency, risk of non-functional overreaching and stress fracture, healing function of skeletal tissue, motivation, stress resistance, confidence, sleep quality, and fatigue. This study provides an expert-derived summary including 26 key factors for endurance performance, the “FENDLE” factors (FENDLE = Factors for ENDurance Level). This consensus report may assist to optimize sophisticated diagnostics, personalized training strategies and technology.
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