Moderate to vigorous physical activity (MVPA) is strongly associated with risk reductions of noncommunicable diseases and mortality. Cardiovascular health status may influence the benefits of MVPA. ...We compare the association between MVPA and incident major adverse cardiovascular events (MACE) and mortality between healthy individuals, individuals with elevated levels of cardiovascular risk factors (CVRF), and cardiovascular disease (CVD).
A cohort study was performed in the 3 northern provinces of the Netherlands, in which data were collected between 2006 and 2018, with a median follow-up of 6.8 years (Q25 5.7; Q75 7.9). A total of 142,493 participants of the Lifelines Cohort Study were stratified at baseline as (1) healthy; (2) CVRF; or (3) CVD. Individuals were categorized into "inactive" and 4 quartiles of least (Q1) to most (Q4) active based on self-reported MVPA volumes. Primary outcome was a composite of incident MACE and all-cause mortality during follow-up. Cox regression was used to estimate hazard ratios (HRs), 95% confidence intervals (CIs) and P values. The main analyses were stratified on baseline health status and adjusted for age, sex, income, education, alcohol consumption, smoking, protein, fat and carbohydrate intake, kidney function, arrhythmias, hypothyroid, lung disease, osteoarthritis, and rheumatoid arthritis. The event rates were 2.2% in healthy individuals (n = 2,485 of n = 112,018), 7.9% in those with CVRF (n = 2,214 of n = 27,982) and 40.9% in those with CVD (n = 1,019 of n = 2,493). No linear association between MVPA and all-cause mortality or MACE was found for healthy individuals (P = 0.36) and individuals with CVRF (P = 0.86), but a linear association was demonstrated for individuals with CVD (P = 0.04). Adjusted HRs in healthy individuals were 0.81 (95% CI 0.64 to 1.02, P = 0.07), 0.71 (95% CI 0.56 to 0.89, P = 0.004), 0.72 (95% CI 0.57 to 0.91, P = 0.006), and 0.76 (95% CI 0.60 to 0.96, P = 0.02) for MVPA Q1 to Q4, respectively, compared to inactive individuals. In individuals with CVRF, HRs were 0.69 (95% CI 0.57 to 0.82, P < 0.001), 0.66 (95% CI 0.55 to 0.80, P < 0.001), 0.64 (95% CI 0.53 to 0.77, P < 0.001), and 0.69 (95% CI 0.57 to 0.84, P < 0.001) for MVPA Q1 to Q4, respectively, compared to inactive individuals. Finally, HRs for MVPA Q1 to Q4 compared to inactive individuals were 0.80 (95% CI 0.62 to 1.03, P = 0.09), 0.82 (95% CI 0.63 to 1.06, P = 0.13), 0.74 (95% CI 0.57 to 0.95, P = 0.02), and 0.70 (95% CI 0.53 to 0.93, P = 0.01) in CVD patients. Leisure MVPA was associated with the most health benefits, nonleisure MVPA with little health benefits, and occupational MVPA with no health benefits. Study limitations include its observational nature, self-report data about MVPA, and potentially residual confounding despite extensive adjustment for lifestyle risk factors and health-related factors.
MVPA is beneficial for reducing adverse outcomes, but the shape of the association depends on cardiovascular health status. A curvilinear association was found in healthy and CVRF individuals with a steep risk reduction at low to moderate MVPA volumes and benefits plateauing at high(er) MVPA volumes. CVD patients demonstrated a linear association, suggesting a constant reduction of risk with higher volumes of MVPA. Therefore, individuals with CVDs should be encouraged that "more is better" regarding MVPA. These findings may help to optimize exercise prescription to gain maximal benefits of a physically active lifestyle.
To determine the association of resistance exercise, independent of and combined with aerobic exercise, with the risk of development of metabolic syndrome (MetS).
The study cohort included adults ...(mean ± SD age, 46±9.5 years) who received comprehensive medical examinations at the Cooper Clinic in Dallas, Texas, between January 1, 1987, and December, 31, 2006. Exercise was assessed by self-reported frequency and minutes per week of resistance and aerobic exercise and meeting the US Physical Activity Guidelines (resistance exercise ≥2 d/wk; aerobic exercise ≥500 metabolic equivalent min/wk) at baseline. The incidence of MetS was based on the National Cholesterol Education Program Adult Treatment Panel III criteria. We used Cox regression to generate hazard ratios (HRs) and 95% CIs.
Among 7418 participants, 1147 (15%) had development of MetS during a median follow-up of 4 years (maximum, 19 years; minimum, 0.1 year). Meeting the resistance exercise guidelines was associated with a 17% lower risk of MetS (HR, 0.83; 95% CI, 0.73-0.96; P=.009) after adjusting for potential confounders and aerobic exercise. Further, less than 1 hour of weekly resistance exercise was associated with 29% lower risk of development of MetS (HR, 0.71; 95% CI, 0.56-0.89; P=.003) compared with no resistance exercise. However, larger amounts of resistance exercise did not provide further benefits. Individuals meeting both recommended resistance and aerobic exercise guidelines had a 25% lower risk of development of MetS (HR, 0.75; 95% CI, 0.63-0.89; P<.001) compared with meeting neither guideline.
Participating in resistance exercise, even less than 1 hour per week, was associated with a lower risk of development of MetS, independent of aerobic exercise. Health professionals should recommend that patients perform resistance exercise along with aerobic exercise to reduce MetS.
Physical activity and exercise training are associated with a lower risk for coronary events. However, cross-sectional studies in middle-aged and older male athletes revealed increased coronary ...artery calcification (CAC) and atherosclerotic plaques, which were related to the amount and intensity of lifelong exercise. We examined the longitudinal relationship between exercise training characteristics and coronary atherosclerosis.
Middle-aged and older men from the MARC-1 (Measuring Athlete's Risk of Cardiovascular Events 1) study were invited for follow-up in MARC-2 (Measuring Athlete's Risk of Cardiovascular Events 2) study. The prevalence and severity of CAC and plaques were determined by coronary computed tomography angiography. The volume (metabolic equivalent of task MET hours/week) and intensity (moderate 3 to 6 MET hours/week; vigorous 6 to 9 MET hours/week; and very vigorous ≥9 MET hours/week) of exercise training were quantified during follow-up. Linear and logistic regression analyses were performed to determine the association between exercise volume/intensity and markers of coronary atherosclerosis.
We included 289 (age, 54 50 to 60 years median (Q1 to Q3)) of the original 318 MARC-1 participants with a follow-up of 6.3±0.5 years (mean±SD). Participants exercised for 41 (25 to 57) MET hours/week during follow-up, of which 0% (0 to 19%) was at moderate intensity, 44% (0 to 84%) was at vigorous intensity, and 34% (0 to 80%) was at very vigorous intensity. Prevalence of CAC and the median CAC score increased from 52% to 71% and 1 (0 to 32) to 31 (0 to 132), respectively. Exercise volume during follow-up was not associated with changes in CAC or plaque. Vigorous intensity exercise (per 10% increase) was associated with a lesser increase in CAC score (β, -0.05 -0.09 to -0.01;
=0.02), whereas very vigorous intensity exercise was associated with a greater increase in CAC score (β, 0.05 0.01 to 0.09 per 10%;
=0.01). Very vigorous exercise was also associated with increased odds of dichotomized plaque progression (adjusted odds ratio aOR, 1.09 1.01 to 1.18 per 10%; aOR, 2.04 0.93 to 4.15 for highest versus lowest very vigorous intensity tertiles, respectively), and specifically with increased calcified plaques (aOR, 1.07 1.00 to 1.15 per 10%; aOR, 2.09 1.09 to 4.00 for highest versus lowest tertile, respectively).
Exercise intensity but not volume was associated with progression of coronary atherosclerosis during 6-year follow-up. It is intriguing that very vigorous intensity exercise was associated with greater CAC and calcified plaque progression, whereas vigorous intensity exercise was associated with less CAC progression.
To determine the relationship between lifelong exercise dose and the prevalence of cardiovascular morbidity.
From June 1, 2011, through December 31, 2014, 21,266 individuals completed an online ...questionnaire regarding their lifelong exercise patterns and cardiovascular health status. Cardiovascular disease (CVD) was defined as a diagnosis of myocardial infarction, stroke, or heart failure, and cardiovascular risk factors (CVRFs) were defined as hypertension, hypercholesterolemia, or type 2 diabetes. Lifelong exercise patterns were measured over a median of 32 years for 405 patients with CVD, 1379 patients with CVRFs, and 10,656 controls. Participants were categorized into nonexercisers and quintiles (Q1-Q5) of exercise dose (metabolic equivalent task MET minutes per week).
The CVD/CVRF prevalence was lower for each exercise quintile compared with nonexercisers (CVD: nonexercisers, 9.6% vs Q1: 4.4%, Q2: 2.8%, Q3: 2.4%, Q4: 3.6%, Q5: 3.9%; P<.001; CVRF: nonexercisers, 24.6% vs Q1: 13.8%, Q2: 10.2%, Q3: 9.0%, Q4: 9.4%, Q5: 12.0%; P<.001). The lowest exercise dose (Q1) significantly reduced CVD and CVRF prevalence, but the largest reductions were found at 764 to 1091 MET-min/wk for CVD (adjusted odds ratio=0.31; 95% CI, 0.20-0.48) and CVRFs (adjusted odds ratio=0.36; 95% CI, 0.28-0.47). The CVD/CVRF prevalence did not further decrease in higher exercise dose groups. Exercise intensity did not influence the relationship between exercise patterns and CVD or CVRFs.
These findings demonstrate a curvilinear relationship between lifelong exercise patterns and cardiovascular morbidity. Low exercise doses can effectively reduce CVD/CVRF prevalence, but engagement in exercise for 764 to 1091 MET-min/wk is associated with the lowest CVD/CVRF prevalence. Higher exercise doses do not yield additional benefits.
Subjective measures of sedentary behaviour (SB) (i.e. questionnaires and diaries/logs) are widely implemented, and can be useful for capturing type and context of SBs. However, little is known about ...comparative validity and reliability. The aim of this systematic review and meta-analysis was to: 1) identify subjective methods to assess overall, domain- and behaviour-specific SB, and 2) examine the validity and reliability of these methods.
The databases MEDLINE, EMBASE and SPORTDiscus were searched up to March 2020. Inclusion criteria were: 1) assessment of SB, 2) evaluation of subjective measurement tools, 3) being performed in healthy adults, 4) manuscript written in English, and 5) paper was peer-reviewed. Data of validity and/or reliability measurements was extracted from included studies and a meta-analysis using random effects was performed to assess the pooled correlation coefficients of the validity.
The systematic search resulted in 2423 hits. After excluding duplicates and screening on title and abstract, 82 studies were included with 75 self-reported measurement tools. There was wide variability in the measurement properties and quality of the studies. The criterion validity varied between poor-to-excellent (correlation coefficient R range - 0.01- 0.90) with logs/diaries (R = 0.63 95%CI 0.48-0.78) showing higher criterion validity compared to questionnaires (R = 0.35 95%CI 0.32-0.39). Furthermore, correlation coefficients of single- and multiple-item questionnaires were comparable (1-item R = 0.34; 2-to-9-items R = 0.35; ≥10-items R = 0.37). The reliability of SB measures was moderate-to-good, with the quality of these studies being mostly fair-to-good.
Logs and diaries are recommended to validly and reliably assess self-reported SB. However, due to time and resources constraints, 1-item questionnaires may be preferred to subjectively assess SB in large-scale observations when showing similar validity and reliability compared to longer questionnaires.
CRD42018105994.
The minimal and optimal daily step counts for health improvements remain unclear.
A meta-analysis was performed to quantify dose-response associations of objectively measured step count metrics in ...the general population.
Electronic databases were searched from inception to October 2022. Primary outcomes included all-cause mortality and incident cardiovascular disease (CVD). Study results were analyzed using generalized least squares and random-effects models.
In total, 111,309 individuals from 12 studies were included. Significant risk reductions were observed at 2,517 steps/d for all-cause mortality (adjusted HR aHR: 0.92; 95% CI: 0.84-0.999) and 2,735 steps/d for incident CVD (aHR: 0.89; 95% CI: 0.79-0.999) compared with 2,000 steps/d (reference). Additional steps resulted in nonlinear risk reductions of all-cause mortality and incident CVD with an optimal dose at 8,763 (aHR: 0.40; 95% CI: 0.38-0.43) and 7,126 steps/d (aHR: 0.49; 95% CI: 0.45-0.55), respectively. Increments from a low to an intermediate or a high cadence were independently associated with risk reductions of all-cause mortality. Sex did not influence the dose-response associations, but after stratification for assessment device and wear location, pronounced risk reductions were observed for hip-worn accelerometers compared with pedometers and wrist-worn accelerometers.
As few as about 2,600 and about 2,800 steps/d yield significant mortality and CVD benefits, with progressive risk reductions up to about 8,800 and about 7,200 steps/d, respectively. Additional mortality benefits were found at a moderate to high vs a low step cadence. These findings can extend contemporary physical activity prescriptions given the easy-to-understand concept of step count. (Dose-Response Relationship Between Daily Step Count and Health Outcomes: A Systematic Review and Meta-Analyses; CRD42021244747)
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To examine the associations of resistance exercise, independent of and combined with aerobic exercise, with the risk of development of hypercholesterolemia in men.
This study used data from the ...Aerobics Center Longitudinal Study, which is a cohort examining the associations of clinical and lifestyle factors with the development of chronic diseases and mortality. Participants received extensive preventive medical examinations at the Cooper Clinic in Dallas, Texas, between January 1, 1987, and December 31, 2006. A total of 7317 men aged 18 to 83 years (mean age, 46 years) without hypercholesterolemia at baseline were included. Frequency (times per week) and total amount (min/wk) of resistance and aerobic exercise were determined by self-report. Hypercholesterolemia was defined as a total cholesterol level of 240 mg/dL or higher or physician diagnosis.
During a median (interquartile range) follow-up of 4 (2 to 7) years, hypercholesterolemia developed in 1430 of the 7317 men (20%). Individuals meeting the resistance exercise guidelines (≥2 d/wk) had a 13% lower risk of development of hypercholesterolemia (hazard ratio HR, 0.87; 95% CI, 0.76-0.99; P=.04) after adjustment for general characteristics, lifestyle factors, and aerobic exercise. In addition, less than 1 h/wk and 2 sessions per week of resistance exercise were associated with 32% and 31% lower risks of hypercholesterolemia (HR, 0.68; 95% CI, 0.54-0.86; P=.001; and HR, 0.69; 95% CI, 0.54-0.88; P=.003), respectively, compared with no resistance exercise. Higher levels of resistance exercise did not provide benefits. Meeting both resistance and aerobic exercise guidelines (≥500 metabolic equivalent task min/wk) lowered the risk of development of hypercholesterolemia by 21% (HR, 0.79; 95% CI, 0.68-0.91; P=.002). compared with meeting none of the guidelines.
Compared with no resistance exercise, less than 1 h/wk of resistance exercise, independent of aerobic exercise, is associated with a significantly lower risk of development of hypercholesterolemia in men (P=.001). However, the lowest risk of hypercholesterolemia was found at 58 min/wk of resistance exercise. This finding suggests that resistance exercise should be encouraged to prevent hypercholesterolemia in men. However, future studies with a more rigorous analysis including major potential confounders (eg, diet, medications) are warranted.
Fatigue is a common side effect of tyrosine kinase inhibitor (TKI) therapy in chronic myeloid leukemia (CML) patients. However, the prevalence of TKI-induced fatigue remains uncertain and little is ...known about predictors of fatigue and its relationship with physical activity. In this study, 220 CML patients receiving TKI therapy and 110 gender- and age-matched controls completed an online questionnaire to assess fatigue severity and fatigue predictors (Part 1). In addition, physical activity levels were objectively assessed for 7 consecutive days in 138 severely fatigued and non-fatigued CML patients using an activity monitor (Part 2). We demonstrated that the prevalence of severe fatigue was 55.5% in CML patients and 10.9% in controls (P<0.001). We identified five predictors of fatigue in our CML population: age (OR 0.96, 95% CI 0.93-0.99), female gender (OR 1.76, 95% CI 0.92-3.34), Charlson Comorbidity Index (OR 1.91, 95% CI 1.16-3.13), the use of comedication known to cause fatigue (OR 3.43, 95% CI 1.58-7.44), and physical inactivity (OR of moderately active, vigorously active and very vigorously active compared to inactivity 0.43 (95% CI 0.12-1.52), 0.22 (95% CI 0.06-0.74), and 0.08 (95% CI 0.02-0.26), respectively). Objective monitoring of activity patterns confirmed that fatigued CML patients performed less physical activity on both light (P=0.017) and moderate to vigorous intensity (P=0.009). In fact, compared to the non-fatigued patients, fatigued CML patients performed 1 hour less of physical activity per day and took 2000 fewer steps per day. Our findings facilitate the identification of patients at risk of severe fatigue and highlight the importance to set the reduction of fatigue as a treatment goal in CML care. This study was registered at The Netherlands Trial Registry, NTR7308 (Part 1) and NTR7309 (Part 2).
Studies which examined the association between sedentary behavior (SB) and cognitive function have presented equivocal findings. Mentally active/inactive sedentary domains may relate differently to ...cognitive function. We examined associations between SB and cognitive function, specifically focusing on different domains. Participants were recruited from the Nijmegen Exercise Study 2018 in the Netherlands. SB (h/day) was measured with the Sedentary Behavior Questionnaire. Cognitive function was assessed with a validated computer self-test (COST-A), and a z-score calculated for global cognitive function. Multivariate linear regression assessed associations between tertiles of sedentary time and cognitive function. Cognition tests were available from 2821 participants, complete data from 2237 participants (43% female), with a median age of 61 IQR 52–67 and a mean sedentary time of 8.3 ± 3.2 h/day. In fully adjusted models, cognitive function was significantly better in participants with the highest total sedentary time (0.07 95% CI 0.02–0.12, P = 0.01), work-related sedentary time (0.13 95% CI 0.07–0.19, P < 0.001), and non-occupational computer time (0.07 95% CI 0.02–0.12, P = 0.01), compared to the least sedentary. Leisure sedentary time and time spent sedentary in the domains TV, reading or creative time showed no association with cognitive function in final models (all P > 0.05). We found a strong, independent positive association between total SB and cognitive function in a heterogenous population. This relation was not consistent across different domains, with especially work- and computer-related SB being positively associated with cognitive function. This highlights the importance of assessing the various sedentary domains in understanding the relation between sedentary time and cognitive function.
•Higher self-rated total sedentary time is associated with better cognitive function.•Distinct sedentary domains relate differently to cognitive function.•Higher work-related sedentary times are associated with better cognitive function.•Higher computer sedentary times are associated with better cognitive function.•Leisure sedentary time is not associated with cognitive function.
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