An Age-Period-Cohort Analysis of Cardiovascular Disease Mortality in the United States from 1999 to 2018.

BACKGROUND: Although cardiovascular disease mortality rates in the United States declined from the 1970s to 2010s, they have now plateaued. The independent effects of age, period, and birth year (cohort) on cardiovascular disease mortality have not previously been defined. METHODS: We used data from the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research to examine the effects of age, period, and cohort on cardiovascular disease mortality among individuals aged 20-84 years from 1999 to 2018, prior to the onset of the coronavirus disease 2019 pandemic. Age effects were described as cardiovascular disease-related mortality rates in each 5-year age group adjusted for year of death (period) and year of birth (cohort). Period and cohort effects were quantified as adjusted rate ratios (RRs) comparing cardiovascular disease mortality rates in each period and cohort to the reference periods and reference cohort (ie, 1919 birth cohort), respectively. RESULTS: Between 1999 to 2018, there were 10,404,327 cardiovascular disease deaths among US adults. In each individual birth cohort, the age-specific cardiovascular disease mortality rates were stable between ages 20 through 39 years. Age-specific rates were higher for each year older between ages 40 through 84 years adjusting for period effects. The period cardiovascular disease mortality rates were lower in later periods (2004-2008 period RR 0.87, 95% confidence interval [CI] 0.85 to 0.88; 2009-2013 period RR 0.78, 95% CI 0.76 to 0.80) compared with the reference period (1999 to 2003) and plateaued thereafter. The cohort cardiovascular disease mortality rates were progressively lower in more recent birth cohorts (1924 birth cohort RR 0.85, 95% CI 0.83 to 0.87; 1974 birth cohort RR 0.29, 95% CI 0.27 to 0.32) compared with the reference cohort (1919 cohort) and plateaued thereafter. CONCLUSION: Although cardiovascular disease mortality rates declined rapidly among those born between 1919 and 1974, improvements plateaued in birth cohorts thereafter even adjusted for period effects.

Cardiac Structure and Function Phenogroups and Risk of Incident Heart Failure (from the Multi-ethnic Study of Atherosclerosis).

Indices of cardiac structure and function, such as left ventricular (LV) mass and ejection fraction, have been associated with risk of incident heart failure (HF), but the clinical relevance of data-driven grouping of a comprehensive set of cardiac parameters is unclear. In Multi-Ethnic Study of Atherosclerosis participants, latent class analysis was applied in the sample stratified by gender to define phenogroups on the basis of cardiovascular magnetic resonance imaging parameters of right ventricular and LV structure and function at baseline. Cox proportional hazard models in gender-stratified analyses were used to assess the association between phenogroup membership and risk of HF subtypes adjusting for potential confounders. In the 4,204 participants (mean age 61 ± 10 years, 53% women), the mean follow-up time was 14 ± 4 years for men and 15 ± 4 years for women. For both genders, 4 distinct phenogroups were identified: (1) ideal cardiac mechanics; (2) higher output/hypertrophied LV; (3) impaired ejection fraction/dilated LV; and (4) higher output/hyperdynamic (LV). Men in phenogroups 4 (hazard ratio [HR] 2.91, 95% confidence interval [CI] 1.60 to 5.31, p = 0.0005), 3 (HR 3.52, 95% CI 1.90 to 6.53, p <0.0001), and 2 (HR 3.49, 95% CI 1.94 to 6.28, p <0.0001) had higher rates of incident HF than did men in phenogroup 1, in fully adjusted models. No significant associations were found between phenogroup membership and incident HF in women. In conclusion, phenogroup membership based on cardiac structure and function in men was significantly associated with incident HF. Integration of cardiac magnetic resonance imaging variables may help identify differential risk for HF in men.

Attendance at Supervised Exercise Sessions and Walking Outcomes in Peripheral Artery Disease: Results From 2 Randomized Clinical Trials.

Background Supervised exercise therapy (SET) is the first-line therapy for walking impairment in peripheral artery disease (PAD). This study evaluated the association between attendance at SET and improved walking performance, compared with a control group, in PAD. Methods and Results Data from 2 randomized clinical trials of SET for PAD were combined. In each trial, participants were randomized to 3 times weekly supervised treadmill exercise or an attention control group for 6 months (maximum, 77 exercise sessions). Participants randomized to SET were categorized into tertiles, according to the proportion of exercise sessions they attended. Results adjusted for age, sex, race, baseline walking performance, comorbidities, and other potential confounders. A total of 272 participants with PAD (mean age, 67.9±9.3 years; 44% women; 61% Black race) were included. For participants randomized to SET, tertiles of attendance rates at exercise sessions were as follows: 11% to 68% (N=45), 69% to <85% (N=46), and ≥85% (N=46). Compared with control, mean improvement in 6-minute walk was significantly greater in each SET tertile: mean (95% CI) for tertile 1, 27.9 m (1.3-54.4 m; P=0.04), tertile 2, 38.2 m (12.2-64.2 m; P=0.001), and tertile 3, 56.9 m (29.9-83.8 m; P<0.0001). Among participants randomized to SET, greater SET attendance was associated with greater improvement in 6-minute walk distance (overall P for trend=0.025). Compared with control, improvement in maximal treadmill walking time was greater in each SET attendance tertile: tertile 1 (3.3 minutes [95% CI, 1.7-4.8 minutes]; P<0.0001), tertile 2 (3.8 minutes [95% CI, 2.3-5.3 minutes]; P<0.0001), and tertile 3 (5.4 minutes [95% CI, 3.9-7.0 minutes]; P:<0.0001). Among participants randomized to SET, greater attendance at SET was not significantly associated with greater improvement in maximal treadmill walking time (overall P for trend=0.064). Conclusions Among people with PAD randomized to SET, better attendance at exercise sessions was associated with significantly greater 6-minute walk improvement. Among all participants with PAD, even relatively low SET attendance was associated with significantly greater improvement in walking performance, compared with a control group who did not exercise. Registration URL: https://clinicaltrials.gov/ct2/show/NCT01408901. URL: https://clinicaltrials.gov/ct2/show/NCT00106327.

Effects of Walking Exercise at a Pace With Versus Without Ischemic Leg Symptoms on Functional Performance Measures in People With Lower Extremity Peripheral Artery Disease: The LITE Randomized Clinical Trial.

Background In people with peripheral artery disease, post hoc analyses of the LITE (Low Intensity Exercise Intervention in Peripheral Artery Disease) randomized trial were conducted to evaluate the effects of walking exercise at a pace inducing ischemic leg symptoms on walking velocity and the Short Physical Performance Battery, compared with walking exercise without ischemic leg symptoms and compared with a nonexercising control group. Methods and Results Participants with peripheral artery disease were randomized to: home-based walking exercise that induced ischemic leg symptoms; home-based walking exercise conducted without ischemic leg symptoms; or a nonexercising control group for 12 months. Outcomes were change of walking velocity over 4 m and change of the Short Physical Performance Battery (0-12, with 12=best) at 6- and 12-month follow-up. A total of 264 participants (48% women, 61% Black race) were included. Compared with walking exercise without ischemic symptoms, walking exercise that induced ischemic symptoms improved change in usual-paced walking velocity over 4 m at 6-month (0.056 m/s [95% CI, 0.019-0.094 m/s]; P<0.01) and 12-month follow-up (0.084 m/s [95% CI, 0.049-0.120 m/s]; P<0.01), change in fast-paced of walking velocity over 4 m at 6-month follow-up (P=0.03), and change in the Short Physical Performance Battery at 12-month follow-up (0.821 [95% CI, 0.309-1.334]; P<0.01). Compared with control, walking exercise at a pace inducing ischemic symptoms improved change in usual-paced walking velocity over 4 m at 6-month follow-up (0.066 m/s [95% CI, 0.021-0.111 m/s]; P<0.01). Conclusions In people with peripheral artery disease, those who walked for exercise at a comfortable pace without ischemic leg symptoms slowed their walking speed during daily life and worsened the Short Physical Performance Battery score, a potentially harmful effect, compared with people who walked for exercise at a pace inducing ischemic leg symptoms. Compared with a control group who did not exercise, home-based walking exercise at a pace inducing ischemic leg symptoms significantly improved change of walking velocity over 4 m at 6-month follow-up, but this benefit did not persist at 12-month follow-up. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02538900.

New strategies and therapies for the prevention of heart failure in high-risk patients.

Despite declines in total cardiovascular mortality rates in the United States, heart failure (HF) mortality rates as well as hospitalizations and readmissions have increased in the past decade. Increases have been relatively higher among young and middle-aged adults (<65 years). Therefore, identification of individuals HF at-risk (Stage A) or with pre-HF (Stage B) before the onset of overt clinical signs and symptoms (Stage C) is urgently needed. Multivariate risk models (e.g., Pooled Cohort Equations to Prevent Heart Failure [PCP-HF]) have been externally validated in diverse populations and endorsed by the 2022 HF Guidelines to apply a risk-based framework for the prevention of HF. However, traditional risk factors included in the PCP-HF model only account for half of an individual's lifetime risk of HF; novel risk factors (e.g., adverse pregnancy outcomes, impaired lung health, COVID-19) are emerging as important risk-enhancing factors that need to be accounted for in personalized approaches to prevention. In addition to determining the role of novel risk-enhancing factors, integration of social determinants of health (SDoH) in identifying and addressing HF risk is needed to transform the current clinical paradigm for the prevention of HF. Comprehensive strategies to prevent the progression of HF must incorporate pharmacotherapies (e.g., sodium glucose co-transporter-2 inhibitors that have also been termed the "statins" of HF prevention), intensive blood pressure lowering, and heart-healthy behaviors. Future directions include investigation of novel prediction models leveraging machine learning, integration of risk-enhancing factors and SDoH, and equitable approaches to interventions for risk-based prevention of HF.

Relations Between BMI Trajectories and Habitual Physical Activity Measured by a Smartwatch in the Electronic Cohort of the Framingham Heart Study: Cohort Study.

BACKGROUND: The prevalence of obesity is rising. Most previous studies that examined the relations between BMI and physical activity (PA) measured BMI at a single timepoint. The association between BMI trajectories and habitual PA remains unclear. OBJECTIVE: This study assesses the relations between BMI trajectories and habitual step-based PA among participants enrolled in the electronic cohort of the Framingham Heart Study (eFHS). METHODS: We used a semiparametric group-based modeling to identify BMI trajectories from eFHS participants who attended research examinations at the Framingham Research Center over 14 years. Daily steps were recorded from the smartwatch provided at examination 3. We excluded participants with <30 days or <5 hours of smartwatch wear data. We used generalized linear models to examine the association between BMI trajectories and daily step counts. RESULTS: We identified 3 trajectory groups for the 837 eFHS participants (mean age 53 years; 57.8% [484/837] female). Group 1 included 292 participants whose BMI was stable (slope 0.005; P=.75), group 2 included 468 participants whose BMI increased slightly (slope 0.123; P<.001), and group 3 included 77 participants whose BMI increased greatly (slope 0.318; P<.001). The median follow-up period for step count was 516 days. Adjusting for age, sex, wear time, and cohort, participants in groups 2 and 3 took 422 (95% CI -823 to -21) and 1437 (95% CI -2084 to -790) fewer average daily steps, compared with participants in group 1. After adjusting for metabolic and social risk factors, group 2 took 382 (95% CI -773 to 10) and group 3 took 1120 (95% CI -1766 to -475) fewer steps, compared with group 1. CONCLUSIONS: In this community-based eFHS, participants whose BMI trajectory increased greatly over time took significantly fewer steps, compared with participants with stable BMI trajectories. Our findings suggest that greater weight gain may correlate with lower levels of step-based physical activity.

Using psycho-behavioral phenotyping for overweight and obesity: Confirmation of the 6 factor questionnaire.

Objective: Questionnaires that assess dietary habits, eating behaviors, and relevant psychosocial constructs are routinely used in obesity research and clinical practice. The 6 factor questionnaire (6FQ) was previously developed as an assessment tool for psycho-behavioral phenotyping. The primary purpose of this study was to confirm and validate the original findings in a large diverse adult population. Methods: A total of 5399 self-selected participants (mean age of 48 ± 13 years and body mass index of 32 ± 8 kg/m2) completed the 6FQ online. The association between self-reported demographic data and 6FQ responses was assessed using linear regression models. Results: Mean factor score and odds ratio analyses consistently demonstrated a statistically significant relationship between factors and body weight even after adjusting for age, sex, and race/ethnicity. Conclusions: Although the study was correlational in design, the results demonstrate that the 6FQ, an instrument that represents multidimensional unhealthful lifestyle patterns associated with diet, physical activity, cognition, and self-perception worsen with increasing body weight. Psycho-behavioral phenotyping may be a useful approach when assessing and treating patients with obesity.

Comparison of Daily Routines Between Middle-aged and Older Participants With and Those Without Diabetes in the Electronic Framingham Heart Study: Cohort Study.

BACKGROUND: Daily routines (eg, physical activity and sleep patterns) are important for diabetes self-management. Traditional research methods are not optimal for documenting long-term daily routine patterns in participants with glycemic conditions. Mobile health offers an effective approach for collecting users' long-term daily activities and analyzing their daily routine patterns in relation to diabetes status. OBJECTIVE: This study aims to understand how routines function in diabetes self-management. We evaluate the associations of daily routine variables derived from a smartwatch with diabetes status in the electronic Framingham Heart Study (eFHS). METHODS: The eFHS enrolled the Framingham Heart Study participants at health examination 3 between 2016 and 2019. At baseline, diabetes was defined as fasting blood glucose level ≥126 mg/dL or as a self-report of taking a glucose-lowering medication; prediabetes was defined as fasting blood glucose level of 100-125 mg/dL. Using smartwatch data, we calculated the average daily step counts and estimated the wake-up times and bedtimes for the eFHS participants on a given day. We compared the average daily step counts and the intraindividual variability of the wake-up times and bedtimes of the participants with diabetes and prediabetes with those of the referents who were neither diabetic nor prediabetic, adjusting for age, sex, and race or ethnicity. RESULTS: We included 796 participants (494/796, 62.1% women; mean age 52.8, SD 8.7 years) who wore a smartwatch for at least 10 hours/day and remained in the study for at least 30 days after enrollment. On average, participants with diabetes (41/796, 5.2%) took 1611 fewer daily steps (95% CI 863-2360; P<.001) and had 12 more minutes (95% CI 6-18; P<.001) in the variation of their estimated wake-up times, 6 more minutes (95% CI 2-9; P=.005) in the variation of their estimated bedtimes compared with the referents (546/796, 68.6%) without diabetes or prediabetes. Participants with prediabetes (209/796, 26.2%) also walked fewer daily steps (P=.04) and had a larger variation in their estimated wake-up times (P=.04) compared with the referents. CONCLUSIONS: On average, participants with diabetes at baseline walked significantly fewer daily steps and had larger variations in their wake-up times and bedtimes than the referent group. These findings suggest that modifying the routines of participants with poor glycemic health may be an important approach to the self-management of diabetes. Future studies should be designed to improve the remote monitoring and self-management of diabetes.

One-Year Change in Walking Performance and Subsequent Mobility Loss and Mortality Rates in Peripheral Artery Disease: Longitudinal Data From the WALCS.

Background Associations of 1-year change in functional performance measures with subsequent mobility loss and mortality in people with lower extremity peripheral artery disease are unknown. Methods and Results Six-minute walk and 4-meter walking velocity (usual and fastest pace) were measured at baseline and 1 year later in 612 people with peripheral artery disease (mean age 71±9 years, 37% women). Participants were categorized into tertiles, based on 1-year changes in walking measures. Cox proportional hazards models were used to examine associations between 1-year change in each walking measure and subsequent mobility loss and mortality, respectively, adjusting for potential confounders. Compared with the best tertile, the worst tertile (ie, greatest decline) in 1-year change in each performance measure was associated with higher rates of mobility loss: 6-minute walk (Tertile 1 [T1] cumulative incidence rate [IR], 72/160; Tertile 3 [T3] IR, 47/160; hazard ratio [HR], 2.35; 95% CI, 1.47-3.74), usual-paced 4-meter walking velocity (T1 IR, 54/162; T3 IR, 57/162; HR, 2.21; 95% CI, 1.41-3.47), and fast-paced 4-meter walking velocity (T1 IR, 61/162; T3 IR, 58/162; HR, 1.81; 95% CI, 1.16-2.84). Compared with the best tertile, the worst tertiles in 1-year change in 6-minute walk (T1 IR, 66/163; T3 IR, 54/163; HR, 1.61; 95% CI, 1.07-2.43) and fast-paced 4-meter walking velocity (T1 IR, 63/166; T3 IR, 44/166; HR, 1.75; 95% CI, 1.16, 2.64) were associated with higher mortality. Conclusions In people with peripheral artery disease, greater 1-year decline in 6-minute walk or 4-meter walking velocity may help identify people with peripheral artery disease at highest risk for mobility loss and mortality.

Association of Habitual Physical Activity With Home Blood Pressure in the Electronic Framingham Heart Study (eFHS): Cross-sectional Study.

BACKGROUND: When studied in community-based samples, the association of physical activity with blood pressure (BP) remains controversial and is perhaps dependent on the intensity of physical activity. Prior studies have not explored the association of smartwatch-measured physical activity with home BP. OBJECTIVE: We aimed to study the association of habitual physical activity with home BP. METHODS: Consenting electronic Framingham Heart Study (eFHS) participants were provided with a study smartwatch (Apple Watch Series 0) and Bluetooth-enabled home BP cuff. Participants were instructed to wear the watch daily and transmit BP values weekly. We measured habitual physical activity as the average daily step count determined by the smartwatch. We estimated the cross-sectional association between physical activity and average home BP using linear mixed effects models adjusting for age, sex, wear time, antihypertensive drug use, and familial structure. RESULTS: We studied 660 eFHS participants (mean age 53 years, SD 9 years; 387 [58.6%] women; 602 [91.2%] White) who wore the smartwatch 5 or more hours per day for 30 or more days and transmitted three or more BP readings. The mean daily step count was 7595 (SD 2718). The mean home systolic and diastolic BP (mmHg) were 122 (SD 12) and 76 (SD 8). Every 1000 increase in the step count was associated with a 0.49 mmHg lower home systolic BP (P=.004) and 0.36 mmHg lower home diastolic BP (P=.003). The association, however, was attenuated and became statistically nonsignificant with further adjustment for BMI. CONCLUSIONS: In this community-based sample of adults, higher daily habitual physical activity measured by a smartwatch was associated with a moderate, but statistically significant, reduction in home BP. Differences in BMI among study participants accounted for the majority of the observed association.

Adherence of Mobile App-Based Surveys and Comparison With Traditional Surveys: eCohort Study.

BACKGROUND: eCohort studies offer an efficient approach for data collection. However, eCohort studies are challenged by volunteer bias and low adherence. We designed an eCohort embedded in the Framingham Heart Study (eFHS) to address these challenges and to compare the digital data to traditional data collection. OBJECTIVE: The aim of this study was to evaluate adherence of the eFHS app-based surveys deployed at baseline (time of enrollment in the eCohort) and every 3 months up to 1 year, and to compare baseline digital surveys with surveys collected at the research center. METHODS: We defined adherence rates as the proportion of participants who completed at least one survey at a given 3-month period and computed adherence rates for each 3-month period. To evaluate agreement, we compared several baseline measures obtained in the eFHS app survey to those obtained at the in-person research center exam using the concordance correlation coefficient (CCC). RESULTS: Among the 1948 eFHS participants (mean age 53, SD 9 years; 57% women), we found high adherence to baseline surveys (89%) and a decrease in adherence over time (58% at 3 months, 52% at 6 months, 41% at 9 months, and 40% at 12 months). eFHS participants who returned surveys were more likely to be women (adjusted odds ratio [aOR] 1.58, 95% CI 1.18-2.11) and less likely to be smokers (aOR 0.53, 95% CI 0.32-0.90). Compared to in-person exam data, we observed moderate agreement for baseline app-based surveys of the Physical Activity Index (mean difference 2.27, CCC=0.56), and high agreement for average drinks per week (mean difference 0.54, CCC=0.82) and depressive symptoms scores (mean difference 0.03, CCC=0.77). CONCLUSIONS: We observed that eFHS participants had a high survey return at baseline and each 3-month survey period over the 12 months of follow up. We observed moderate to high agreement between digital and research center measures for several types of surveys, including physical activity, depressive symptoms, and alcohol use. Thus, this digital data collection mechanism is a promising tool to collect data related to cardiovascular disease and its risk factors.

Retrospective evaluation of echocardiographic variables for prediction of heart failure hospitalization in heart failure with preserved versus reduced ejection fraction: A single center experience.

BACKGROUND: Limited data exist on the differential ability of variables on transthoracic echocardiogram (TTE) to predict heart failure (HF) readmission across the spectrum of left ventricular (LV) systolic function. METHODS: We linked 15 years of TTE report data (1/6/2003-5/3/2018) at Beth Israel Deaconess Medical Center to complete Medicare claims. In those with recent HF, we evaluated the relationship between variables on baseline TTE and HF readmission, stratified by LVEF. RESULTS: After excluding TTEs with uninterpretable diastology, 5,900 individuals (mean age: 76.9 years; 49.1% female) were included, of which 2545 individuals (41.6%) were admitted for HF. Diastolic variables augmented prediction compared to demographics, comorbidities, and echocardiographic structural variables (p < 0.001), though discrimination was modest (c-statistic = 0.63). LV dimensions and eccentric hypertrophy predicted HF in HF with reduced (HFrEF) but not preserved (HFpEF) systolic function, whereas LV wall thickness, NT-proBNP, pulmonary vein D- and Ar-wave velocities, and atrial dimensions predicted HF in HFpEF but not HFrEF (all interaction p < 0.10). Prediction of HF readmission was not different in HFpEF and HFrEF (p = 0.93). CONCLUSIONS: In this single-center echocardiographic study linked to Medicare claims, left ventricular dimensions and eccentric hypertrophy predicted HF readmission in HFrEF but not HFpEF and left ventricular wall thickness predicted HF readmission in HFpEF but not HFrEF. Regardless of LVEF, diastolic variables augmented prediction of HF readmission compared to echocardiographic structural variables, demographics, and comorbidities alone. The additional role of medication adherence, readmission history, and functional status in differential prediction of HF readmission by LVEF category should be considered for future study.

Association of Habitual Physical Activity With Cardiovascular Disease Risk.

RATIONALE: A sedentary lifestyle is associated with increased risk for cardiovascular disease (CVD). Smartwatches enable accurate daily activity monitoring for physical activity measurement and intervention. Few studies, however, have examined physical activity measures from smartwatches in relation to traditional risk factors associated with future risk for CVD. OBJECTIVE: To investigate the association of habitual physical activity measured by smartwatch with predicted CVD risk in adults. METHODS AND RESULTS: We enrolled consenting FHS (Framingham Heart Study) participants in an ongoing eFHS (electronic Framingham Heart Study) at the time of their FHS research center examination. We provided participants with a smartwatch (Apple Watch Series 0) and instructed them to wear it daily, which measured their habitual physical activity as the average daily step count. We estimated the 10-year predicted risk of CVD using the American College of Cardiology/American Heart Association 2013 pooled cohort risk equation. We estimated the association between physical activity and predicted risk of CVD using linear mixed effects models adjusting for age, sex, wear time, and familial structure. Our study included 903 eFHS participants (mean age 53±9 years, 61% women, 9% non-White) who wore the smartwatch ≥5 hours per day for ≥30 days. Median daily step count was similar among men (7202 with interquartile range 3619) and women (7260 with interquartile range 3068; P=0.52). Average 10-year predicted CVD risk was 4.5% (interquartile range, 6.1%) for men and 1.2% (interquartile range, 2.2%) for women (P=1.3×10-26). Every 1000 steps higher habitual physical activity was associated with 0.18% lower predicted CVD risk (P=3.2×10-4). The association was attenuated but remained significant after further adjustment for body mass index (P=0.01). CONCLUSIONS: In this community-based sample of adults, higher daily physical activity measured by a study smartwatch was associated with lower predicted risk of CVD. Future research should examine the longitudinal association of prospectively measured daily activity and incident CVD.