Personal Activity Intelligence and Mortality in Patients with Cardiovascular Disease: The HUNT Study

Physical Activity and Cause-Specific Cardiovascular Mortality Among People With and Without Cardiovascular Disease: A Cohort Study of 0.6 Million US Adults

OBJECTIVE

To assess the association of physical activity (PA) with cause-specific cardiovascular disease (CVD) mortality among people with preexisting CVD and to analyze the relationship of PA with CVD-related mortality in people without CVD as well as the association of PA with nonspecific CVD mortality in both populations.

PARTICIPANTS AND METHODS

Of the total participants in the 1997 through 2018 US National Health Interview Survey waves, 87,959 adults with CVD and 527,185 without CVD were included. Leisure-time PA was self-reported; based on frequency and duration, minutes per week in PA were calculated and subsequently classified into: (1) none: 0 min/wk, (2) insufficient: 1 to 149.9 min/wk, (3) recommended: 150 to 300 min/wk, and (4) additional: more than 300 min/wk. Mortality data were obtained through link to records from the National Death Index. Statistical analyses were performed with Cox regression adjusted for potential confounders.

RESULTS

During a mean follow-up of 8.5 years, 12,893 participants with CVD, 9943 with coronary heart disease (CHD), and 843 with stroke died of CVD mortality, diseases of heart mortality, and cerebrovascular mortality, respectively. In fully adjusted models, compared with no PA, insufficient, recommended, and additional PA were associated with 25.9%, 37.1%, and 42.0% lower risk of diseases of heart mortality among people with prior CHD, respectively. Among people with stroke, recommended and additional PA was related to 30.7% and 59.3% lower risk of cerebrovascular mortality, respectively. The protective effect of PA on cause-specific CVD mortality was greater in people with CVD than in those without prior CVD. Moreover, PA was more markedly inversely associated with cause-specific CVD mortality than with nonspecific CVD mortality in people with CVD.

CONCLUSION

Physical activity was strongly associated with lower risk of CVD-, CHD-, and stroke-related mortality among people with a history of these specific diseases. Health care professionals should emphasize the importance of a physically active lifestyle in patients with CVD.

Physical activity, cardiorespiratory fitness, and cardiovascular health: A clinical practice statement of the American Society for Preventive Cardiology Part II: Physical activity, cardiorespiratory fitness, minimum and goal intensities for exercise training, prescriptive methods, and special patient populations

The prescription of exercise for individuals with and without cardiovascular disease (CVD) should be scientifically-based yet adapted to the patient. This scientific statement reviews the clinical and physiologic basis for the prescription of exercise, with specific reference to the volume of physical activity (PA) and level of cardiorespiratory fitness (CRF) that confer significant and optimal cardioprotective benefits. Recommendations are provided regarding the appropriate intensity, frequency, and duration of training; the concept of MET-minutes per week; critical components of the exercise session (warm-up, conditioning phase, cool-down); methodologies for establishing the training intensity, including oxygen uptake reserve (V̇O2R), target heart rate derivation and rating perceived exertion; minimum and goal intensities for exercise training; and, types of training activities, including resistance training, adjunctive lifestyle PA, marathon/triathlon training, and high-intensity interval training. In addition, we discuss the rationale for and value of exercise training programs for patients with peripheral artery disease, diabetes mellitus, and heart failure.

Using Personal Activity Intelligence With Patients in a Clinic Setting

BACKGROUND

Personal Activity Intelligence (PAI) is a novel heart-rate-based metric used to assess cardiorespiratory fitness and quantify physical activity.

OBJECTIVE

The aim of this study was to examine the feasibility, acceptability, and effectiveness of PAI with patients in a clinic setting.

METHODS

Patients (n = 25) from 2 clinics underwent 12 weeks of heart-rate-monitored physical activity interfaced with aPAI Health phone app. We used a pre-post design with the Physical Activity Vital Sign and the International Physical Activity Questionnaire. Feasibility, acceptability, and PAI measures were used to evaluate the objectives.

RESULTS

Twenty-two patients (88%) completed the study. There were significant improvements in International Physical Activity Questionnaire metabolic equivalent task minutes per week ( P = .046) and a decrease in sitting hours ( P = .0001). The Physical Activity Vital Sign activity increase in minutes per week was not significant ( P = .214). Patients achieved a mean PAI score of 116 ± 81.1 and 100 or greater 71% of the days. Most patients (81%) expressed satisfaction with PAI.

CONCLUSIONS

Personal Activity Intelligence is feasible, acceptable, and effective when used with patients in a clinic setting.

Temporal changes in personal activity intelligence and the risk of incident dementia and dementia related mortality: A prospective cohort study (HUNT)

BACKGROUND

The Personal Activity Intelligence (PAI) translates heart rate during daily activity into a weekly score. Obtaining a weekly PAI score ≥100 is associated with reduced risk of premature morbidity and mortality from cardiovascular diseases. Here, we determined whether changes in PAI score are associated with changes in risk of incident dementia and dementia-related mortality.

METHODS

We conducted a prospective cohort study of 29,826 healthy individuals. Using data from the Trøndelag Health-Study (HUNT), PAI was estimated 10 years apart (HUNT1 1984-86 and HUNT2 1995-97). Adjusted hazard-ratios (aHR) and 95%-confidence intervals (CI) for incidence of and death from dementia were related to changes in PAI using Cox regression analyses.

FINDINGS

During a median follow-up time of 24.5 years (interquartile range [IQR]: 24.1-25.0) for dementia incidence and 23.6 years (IQR: 20.8-24.2) for dementia-related mortality, there were 1998 incident cases and 1033 dementia-related deaths. Individuals who increased their PAI score over time or maintained a high PAI score at both assessments had reduced risk of dementia incidence and dementia-related mortality. Compared with persistently inactive individuals (0 weekly PAI) at both time points, the aHRs for those with a PAI score ≥100 at both occasions were 0.75 (95% CI: 0.58-0.97) for incident dementia, and 0.62 (95% CI: 0.43-0.91) for dementia-related mortality. Using PAI score <100 at both assessments as the reference cohort, those who increased from <100 at HUNT1 to ≥100 at HUNT2 had aHR of 0.83 (95% CI: 0.72-0.96) for incident dementia, and gained 2.8 (95% CI: 1.3-4.2, P<0.0001) dementia-free years. For dementia-related mortality, the corresponding aHR was 0.74 (95% CI: 0.59-0.92) and years of life gained were 2.4 (95% CI: 1.0-3.8, P=0.001).

INTERPRETATION

Maintaining a high weekly PAI score and increases in PAI scores over time were associated with a reduced risk of incident dementia and dementia-related mortality. Our findings extend the scientific evidence regarding the protective role of PA for dementia prevention, and suggest that PAI may be a valuable tool in guiding research-based PA recommendations.

FUNDING

The Norwegian Research Council, the Liaison Committee between the Central Norway Regional Health Authority and Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

Association Between Personal Activity Intelligence and Mortality: Population-Based China Kadoorie Biobank Study

OBJECTIVE

To prospectively investigate the association between personal activity intelligence (PAI) - a novel metabolic metric which translates heart rate during physical activity into a simple weekly score - and mortality in relatively healthy participants in China whose levels and patterns of physical activity in addition to other lifestyle factors are different from those in high-income countries.

PATIENTS AND METHODS

From the population-based China Kadoorie Biobank study, 443,792 healthy adults were recruited between June 2004 and July 2008. Participant's weekly PAI score was estimated and divided into four groups (PAI scores of 0, ≤50, 51-99, or ≥100). Using Cox proportional hazard analyses, we calculated adjusted hazard ratios (AHRs) for cardiovascular disease (CVD) and all-cause mortality related to PAI scores.

RESULTS

During a median follow-up of 8.2 (interquartile range, 7.3 to 9.1) years, there were 21,901 deaths, including 9466 CVD deaths. Compared with the inactive group (0 PAI score), a baseline weekly PAI score greater than or equal to 100 was associated with a lower risk of CVD mortality, an AHR of 0.87 (95% CI, 0.81 to 0.94) in men, and an AHR of 0.84 (95% CI, 0.78 to 0.92) in women, after adjusting for multiple confounders. Participants with a weekly PAI score greater than or equal to 100 also had a lower risk of all-cause mortality (AHR, 0.93; 95% CI, 0.89 to 0.97 in men, and AHR, 0.93; 95%, 0.88 to 0.98 in women). Moreover, this subgroup gained 2.7 (95% CI, 2.4 to 3.0) years of life, compared with the inactive cohort.

CONCLUSION

Among relatively healthy Chinese adults, the PAI metric was inversely associated with CVD and all-cause mortality, highlighting the generalizability of the score in different races, ethnicities, and socioeconomic strata.

Personal Activity Intelligence e-Health Program in People with Type 2 Diabetes: A Pilot Randomized Controlled Trial

INTRODUCTION

Innovative strategies are needed to enable people with type 2 diabetes (T2D) to self-manage physical activity (PA). Personal Activity Intelligence (PAI) is a new metric that uses the heart rate response to PA to inform the user as to whether they are doing enough PA to reduce the risk of premature mortality. The PAI score reflects PA over the previous 7 d with the goal to maintain a score ≥100. The aim of this study was to investigate the feasibility, acceptability, and efficacy of the PAI e-Health Program in people with T2D.

METHODS

Thirty participants with T2D who were not meeting PA guidelines were randomly assigned to 12 wk of either 1) PAI e-Health Program or 2) PA attention control. The PAI e-Health Program consisted of receiving a wrist-worn heart rate monitor and an app with the PAI metric, and attending 4 × 2 h·wk-1 sessions of exercise and counseling. Feasibility and acceptability of the program were evaluated by achievement of a PAI score ≥100 and participant feedback. Efficacy was determined from changes in glycemic control, cardiorespiratory fitness, exercise capacity (time-on-test), body composition, sleep time, and health-related quality of life.

RESULTS

Program participants in the PAI e-Health Program had a mean ± SD PAI score of 119.7 ± 60.6 and achieved ≥100 PAI on 56.4% of the days. The majority of participants (80%) intended to continue to use PAI monitoring. Compared with control, the PAI group significantly improved their exercise capacity (mean difference, 95% confidence interval) (63 s, 17.9-108.0 s), sleep time (67.2 min, 7.2-127.1 min), total percent body fat (-1.3%, -2.6% to -0.1%), and gynoid fat percent (-1.5%, -2.6 to -0.5).

CONCLUSIONS

The PAI e-Health Program is feasible, acceptable, and efficacious in people with T2D.

Effect of personal activity intelligence (PAI) monitoring in the maintenance phase of cardiac rehabilitation: a mixed methods evaluation

BACKGROUND

Personal activity intelligence (PAI) is a single physical activity metric based upon heart rate responses to physical activity. Maintaining 100 PAI/week is associated with a 25% risk reduction in cardiovascular disease mortality and 50 PAI/week provides 60% of the benefits. The effect of utilising this metric within a cardiac population has not been previously investigated. The aim of this study was to determine the effect of PAI monitoring on the amount and/or intensity of physical activity for people in the maintenance phase of cardiac rehabilitation and to explore participants' perceptions of this approach.

METHODS

A concurrent mixed methods approach was undertaken. Participants in the maintenance phase of cardiac rehabilitation monitored PAI for six weeks via a wearable physical activity monitoring device (WPAM). In the first three weeks participants were blinded to their PAI score. A quality-of-life questionnaire (EQ-5D-5L) was completed, and semi-structured interviews conducted to investigate attitudes to PAI monitoring. Daily PAI data was collected throughout the 6-week period.

RESULTS

Twenty participants completed the trial. PAI earned/day was increased after participants could view their data (mean difference: 2.1 PAI/day (95% CI 0.3, 4.0), p = 0.027). The median change in percentage of days participants achieved a Total PAI score of 25 (p = 0.023) and 50 (p = 0.015) were also increased. The mean change in total scores for the EQ-5D-5L and EQVAS were improved after 6 weeks (0.6 ± 1.05; 95% CI (0.11-1.09); p = 0.019); (5.8/100; 95% CI (2.4-9.2); p = 0.002 respectively). Thematic framework analysis identified three global themes (perceptions on the WPAM, PAI and factors affecting exercise). Most participants stated motivation to exercise increased after they could view their PAI data. Many of the participants believed they would continue to use PAI long-term. Others were undecided; the latter primarily due to technical issues and/or preferring devices with greater functionality and attractiveness. All participants would recommend PAI.

CONCLUSION

This exploratory study showed monitoring PAI via a WPAM increased the amount and/or intensity of physical activity within the cardiac population. Participants found PAI interesting, beneficial, and motivating. If technical issues, aesthetics, and functionality of the WPAM were improved, participants may continue to use the approach long-term. PAI may be a viable strategy to assist people with cardiac disease maintain physical activity adherence.

Association between Personal Activity Intelligence (PAI) and body weight in a population free from cardiovascular disease - The HUNT study

BACKGROUND

Personal Activity Intelligence (PAI) is a new metric for physical activity tracking, and is associated with reduced risk of all-cause and cardiovascular mortality. We prospectively investigated whether PAI is associated with lower body weight gain in a healthy population.

METHODS

We included 85,243 participants (40,037 men and 45,206 women) who participated in at least one of three waves of the Trøndelag Health Study (HUNT1: 1984-86, HUNT2: 1995-97, and HUNT3: 2006-08). We used questionnaires to estimate PAI, and linear mixed models to examine body weight according to PAI levels at three study waves. We also conducted regression analyses to assess separate relationships between change in PAI and the combined changes in PAI and physical activity recommendations, according to body weight from HUNT1 to HUNT3.

FINDINGS

Compared with HUNT1, body weight was 8.6 and 6.7 kg higher at HUNT3 for men and women, respectively, but was lower among those with ≥200 PAI at HUNT3. For both sexes, a change from inactive (0 PAI) at HUNT1 to ≥100 weekly PAI-score at HUNT2 and HUNT3, and a ≥100 PAI-score at all three occasions were associated with lower body weight gain, compared with the reference group (0 PAI at all three waves). Importantly, among both sexes, obtaining ≥100 weekly PAI at HUNT1 and HUNT3 was associated with lower body weight gain regardless of adhering to physical activity guidelines.

INTERPRETATION

Adhering to a high PAI over time may be a useful tool to attenuate excessive body weight gain in a population free from cardiovascular disease.

FUNDING

Norwegian Research Council and the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and technology.

Temporal changes in personal activity intelligence and mortality: Data from the aerobics center longitudinal study

BACKGROUND

Personal activity intelligence (PAI) is a metric developed to simplify a physically active lifestyle for the participants. Regardless of following today's advice for physical activity, a PAI score ≥100 per week at baseline, an increase in PAI score, and a sustained high PAI score over time were found to delay premature cardiovascular disease (CVD) and all-cause mortality in a large population of Norwegians. However, the association between long-term temporal change in PAI and mortality in other populations have not been investigated.

OBJECTIVE

To test whether temporal change in PAI is associated with CVD and all-cause mortality in a large population from the United States.

METHODS

We studied 17,613 relatively healthy participants who received at least two medical examinations in the Aerobics Center Longitudinal Study between 1974 and 2002. The participant's weekly PAI scores were estimated twice, and adjusted hazard ratios (AHR) and 95% confidence intervals (CI) for CVD and all-cause mortality related to changes in PAI between baseline and last examination were assessed using Cox proportional hazard regression analyses.

RESULTS

During a median follow-up time of 9.3 years [interquartile range, 2.6-16.6; 181,765 person-years], there were 1144 deaths, including 400 CVD deaths. We observed an inverse linear association between change in PAI and risk of CVD mortality (P=0.007 for linear trend, and P=0.35 for quadratic trend). Compared to participants with zero PAI at both examinations, multivariable-adjusted analyses demonstrated that participants who maintained high PAI scores (≥100 PAI at both examinations) had a 51% reduced risk of CVD mortality [AHR, 0.49: 95% CI, 0.26-0.95)], and 42% reduced risk of all-cause mortality [AHR, 0.58: 95% CI, 0.41-0.83)]. For participants who increased their PAI scores over time (PAI score of zero at first examination and ≥100 at last examination), the AHRs were 0.75 (95% CI, 0.55-1.02) for CVD mortality, and 0.82 (95% CI, 0.69-0.99) for all-cause mortality. Participants who maintained high PAI score had 4.8 (95% CI, 3.3-6.4) years of life gained. For those who increased their PAI score over time, the corresponding years gained were 1.8 years (95% CI, 0.1-3.5).

CONCLUSION

Among relatively healthy participants, an increase in PAI and maintaining a high PAI score over time was associated with reduced risk of CVD and all-cause mortality.

CONDENSED ABSTRACT

Our objective was to investigate the association between temporal changes in PAI and mortality in a large population from the United States. In this prospective cohort study of 17,613 relatively healthy participants at baseline, maintaining a high PAI score and an increase in PAI score over an average period of 6.3 years was associated with a significant reduction in CVD and all-cause mortality. Based on our results, clinicians can easily recommend that patients obtain at least 100 PAI for most favourable protection against CVD- and all-cause mortality, but can also mention that significant benefits also occur at maintaining low-to-moderate PAI levels.

Personal activity intelligence and mortality - Data from the Aerobics Center Longitudinal Study

IMPORTANCE

Personal activity intelligence (PAI) is a novel activity metric that can be integrated into self-assessment heart rate devices, and translates heart rate variations during exercise into a weekly score. Previous studies relating to PAI have been conducted in the same populations from Norway where the PAI metric has been derived, limiting generalizability of the results.

OBJECTIVE

To test whether PAI is associated with total and cause-specific mortality in a large cohort from the United States.

DESIGN

Aerobics Center Longitudinal Study (ACLS) - a prospective cohort between January 1974 and December 2002 with a mean follow-up of 14.5 years.

SETTING

Population-based.

PARTICIPANTS

56,175 relatively healthy participants (26.5% women) who underwent extensive preventive medical examinations at Cooper Clinic (Dallas, TX).

EXPOSURE

Personal activity intelligence (PAI) score per week was estimated and divided into 4 groups (PAI scores of 0, ≤50, 51-99, and ≥100).

MAIN OUTCOMES AND MEASURES

Total and cause-specific mortality.

RESULTS

During a median follow-up time of 14.9 (interquartile range, 6.7-21.4) years, there were 3434 total deaths including 1258 cardiovascular (CVD) deaths. Compared with the inactive (0 PAI) group, participants with a baseline weekly ≥100 PAI had lower risk of mortality: adjusted hazard ratio (AHR), 0.79: 95% CI, 0.71-0.87 for all-cause mortality, and AHR, 0.72: 95% CI, 0.60-0.87 for CVD mortality among men; AHR, 0.85: 95% CI, 0.64-1.12 for all-cause mortality, and AHR, 0.48: 95% CI, 0.26-0.91 for CVD mortality among women. For deaths from ischemic heart disease (IHD), PAI score ≥100 was associated with lower risk in both men and women (AHR, 0.70: 95% CI, 0.55-0.88). Obtaining ≥100 weekly PAI was also associated with significantly lower risk of CVD mortality in pre-specified age groups, and in participants with known CVD risk factors. Participants with ≥100 weekly PAI gained 4.2 (95% CI, 3.5-4.6) years of life when compared with those who were inactive at baseline.

CONCLUSIONS AND RELEVANCE

PAI is associated with long-term all-cause, CVD, and IHD, mortality. Clinicians and the general population can incorporate PAI recommendations and thresholds in their physical activity prescriptions and weekly physical activity assessments, respectively, to maximize health outcomes.

KEY POINTS

Question: What is the association between personal activity intelligence (PAI), a novel activity metric, and mortality in a large cohort from the United States?

FINDINGS

In this prospective study of 56,175 healthy participants at baseline, followed-up for a mean of 14.5 years, ≥100 PAI score/week was associated with significant 21% lower risk of all-cause and 30% lower risk of CVD mortality in comparison with inactive people. Participants with ≥100 PAI/week lived on average 4.2 years longer compared with inactive. Meaning: PAI is associated with long-term all-cause and CVD mortality. Clinicians and general population may incorporate PAI recommendations into weekly physical activity assessments to maximize CVD prevention.

High-Intensity Training Reduces CVD Risk Factors among Rotating Shift Workers: An Eight-Week Intervention in Industry

Rotating shift work is associated with risk factors for cardiovascular disease (CVD). We have studied the effect of 17 min high-intensity training three times a week over eight weeks on CVD risk factors among shift workers. Sixty-five shift workers from two plants were recruited. They were all deemed healthy at the initial health screening and in 100% work. From plant A, 42 workers, and plant B, 23 workers participated. After the intervention, 56 workers were retested. The intervention group consisted of 19 participants from plant A who had participated in at least 10 sessions. Twenty workers from plant B and 17 workers from plant A that not had taken part in the training were included in the control group. All workers reported physical activity (PA) by questionnaires before and after the training intervention. We measured blood pressure, heart rate, lipids, glycated hemoglobin (HbA1c), and C-reactive protein (CRP) and arterial stiffness. Maximal oxygen uptake (V.O_2max) was assessed by bicycle ergometry. The intervention group favorably differed significantly from the control group in improvement of systolic and diastolic blood pressure and glycated hemoglobin (HbA1c). Short training sessions with 4 min of high-intensity PA, three times a week, for eight weeks among rotating shift workers reduced some CVD risk factors. PA interventions in occupational settings may thus decrease coronary heart disease and stroke incidences in this vulnerable group of workers.

Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial

BACKGROUND

Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improve clinical results. We aim to demonstrate the feasibility of combining machine learning (ML) with PGHD in TJA to predict patient-reported outcome measures (PROMs).

METHODS

Twenty-two TJA patients were recruited for this pilot study. Three activity trackers collected 35 features from 4 weeks before to 6 weeks following surgery. PROMs were collected at both endpoints (Hip and Knee Disability and Osteoarthritis Outcome Score, Knee Osteoarthritis Outcome Score, and Veterans RAND 12-Item Health Survey Physical Component Score). We used ML to identify features with the highest correlation with PROMs. The algorithm trained on a subset of patients and used 3 feature sets (A, B, and C) to group the rest into one of the 3 PROM clusters.

RESULTS

Fifteen patients completed the study and collected 3 million data points. Three sets of features with the highest R² values relative to PROMs were selected (A, B and C). Data collected through the 11th day had the highest predictive value. The ML algorithm grouped patients into 3 clusters predictive of 6-week PROM results, yielding total sum of squares values ranging from 3.86 (A) to 1.86 (C).

CONCLUSION

This small but critical proof-of-concept study demonstrates that ML can be used in combination with PGHD to predict 6-week PROM data as early as 11 days following TJA surgery. Further study is needed to confirm these findings and their clinical value.

Personal Activity Intelligence (PAI): A new standard in activity tracking for obtaining a healthy cardiorespiratory fitness level and low cardiovascular risk

Despite all the evidence of health benefits related to physical activity (PA) and cardiorespiratory fitness (CRF), low levels of PA have reached pandemic proportions, and inactivity is the fourth leading cause of death worldwide. Lack of time, and inability to self-manage are often cited as main barriers to getting adequate PA. Recently, a new personalized metric for PA tracking named Personal Activity Intelligence (PAI) was developed with the aim to make it easier to quantify how much PA per week is needed to reduce the risk of premature mortality from non-communicable diseases. PAI can be integrated in self-assessment heart rate devices and defines a weekly beneficial heart rate pattern during PA by considering the individual's sex, age, and resting and maximal heart rates. Among individuals ranging from the general population to subgroups of patients with cardiovascular disease (CVD), a PAI score ≥100 per week at baseline, an increase in PAI score, and a sustained high PAI score over time were found to delay premature death from CVD and all causes, regardless of whether or not the current PA recommendations were met. Importantly, a PAI score ≥100 at baseline, maintaining ≥100 PAIs and an increasing PAI score over time was associated with multiple years of life gained. Moreover, obtaining a weekly PAI ≥100 attenuated the deleterious association between CVD risk factor clustering and prolonged sitting time. PAI and objectively measured CRF (as indicated by VO_2peak) were positively associated in a graded fashion, and individuals with a PAI score between 100 and 150 had expected age and sex specific average VO_2peak values. A PAI score ≥100 was associated with higher VO_2peak in both men (4.1 mL·kg^-1·min^-1; 95% CI, 3.5 to 4.6) and women (2.9 mL·kg^-1·min^-1; 95% CI, 2.4 to 3.3), compared to the reference group of <100 PAI. The combined analysis of PAI, PA and VO_2peak demonstrated that a PAI score ≥100 was associated with high VO_2peak values regardless of meeting or not meeting the current PA recommendations. Collectively, these findings suggest that PAI has the potential to be a useful tool to motivate people to become and stay physically active by quantifying the amount of PA needed to produce significant health benefits.

An Update on the Role of Cardiorespiratory Fitness, Structured Exercise and Lifestyle Physical Activity in Preventing Cardiovascular Disease and Health Risk

The cardiovascular disease (CVD) pandemic has placed considerable strain on healthcare systems, quality of life, and physical function, while remaining the leading cause of death globally. Decades of scientific investigations have fortified the protective effects of cardiorespiratory fitness (CRF), exercise training, and physical activity (PA) against the development of CVD. This review will summarize recent efforts that have made significant strides in; 1) the application of novel analytic techniques to increase the predictive utility of CRF; 2) understanding the protective effects of long-term compliance to PA recommendations through large cohort studies with multiple points of assessment; 3) and understanding the potential harms associated with extreme volumes of PA.

Triglyceride-Rich Lipoproteins and Novel Targets for Anti-atherosclerotic Therapy

Although elevated serum low-density lipoprotein-cholesterol (LDL-C) is without any doubts accepted as an important risk factor for cardiovascular disease (CVD), the role of elevated triglycerides (TGs)-rich lipoproteins as an independent risk factor has until recently been quite controversial. Recent data strongly suggest that elevated TG-rich lipoproteins are an independent risk factor for CVD and that therapeutic targeting of them could possibly provide further benefit in reducing CVD morbidity, events and mortality, apart from LDL-C lowering. Today elevated TGs are treated with lifestyle interventions, and with fibrates which could be combined with omega-3 fatty acids. There are also some new drugs. Volanesorsen, is an antisense oligonucleotid that inhibits the production of the Apo C-III which is crucial in regulating TGs metabolism because it inhibits lipoprotein lipase (LPL) and hepatic lipase activity but also hepatic uptake of TGs-rich particles. Evinacumab is a monoclonal antibody against angiopoietin-like protein 3 (ANGPTL3) and it seems that it can substantially lower elevated TGs levels because ANGPTL3 also regulates TGs metabolism. Pemafibrate is a selective peroxisome proliferator-activated receptor alpha modulator which also decreases TGs, and improves other lipid parameters. It seems that it also has some other possible antiatherogenic effects. Alipogene tiparvovec is a nonreplicating adeno-associated viral vector that delivers copies of the LPL gene to muscle tissue which accelerates the clearance of TG-rich lipoproteins thus decreasing extremely high TGs levels. Pradigastat is a novel diacylglycerol acyltransferase 1 inhibitor which substantially reduces extremely high TGs levels and appears to be promising in treatment of the rare familial chylomicronemia syndrome.