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We used linear regression to examine cross-sectional associations of accelerometer-measured physical activity and sedentary time with extrinsic and intrinsic epigenetic age acceleration models (EEAA and IEAA) and GrimAge measured from blood samples from Framingham Heart Study participants with accelerometry and DNA methylation data (n = 2435; mean age 54.9 ± 14.3, 46.0% men). Residuals of Hannum-, Horvath-, and GrimAge-predicted epigenetic age were calculated by regressing epigenetic age on chronological age. We took into account blood cell composition for EEAA, IEAA, and AdjGrimAge. Moderate to vigorous physical activity (MVPA) was log-transformed to normalize its distribution. Adjustment models accounted for family structure, age, sex, smoking status, cohort-laboratory indicator, and accelerometer wear time. We additionally explored adjustment for body mass index (BMI).Walking 1500 more steps/day or spending 3 fewer hours sedentary was associated with10 months lower GrimAge biological age (or ~ 1 month lower AdjGrimAge, after adjusting for blood cells, p0.05). Every 5 min/day more MVPA was associated with 19-79 days lower GrimAge (4-23 days lower using EEAA or AdjGrimAge, p0.01). Adjusting for BMI attenuated these results, but all statistically significant associations with AdjGrimAge remained.Greater habitual physical activity and lower sedentary time were associated with lower epigenetic age, which was partially explained by BMI. Further research should explore whether changes in physical activity influence methylation status and whether those modifications influence chronic disease risk.

Background Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk. Objective The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF. Methods Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals’ 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)–AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m2), as well as the relation between self-reported physical activity and predicted 5-year AF risk. Results We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a Conclusions Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation.

Background: Taking fewer than the widely promoted “10 000 steps per day” has recently been associated with lower risk of all-cause mortality. The relationship of steps and cardiovascular disease (CVD) risk remains poorly described. A meta-analysis examining the dose–response relationship between steps per day and CVD can help inform clinical and public health guidelines. Methods: Eight prospective studies (20 152 adults [ie, ≥18 years of age]) were included with device-measured steps and participants followed for CVD events. Studies quantified steps per day and CVD events were defined as fatal and nonfatal coronary heart disease, stroke, and heart failure. Cox proportional hazards regression analyses were completed using study-specific quartiles and hazard ratios (HR) and 95% CI were meta-analyzed with inverse-variance–weighted random effects models. Results: The mean age of participants was 63.2±12.4 years and 52% were women. The mean follow-up was 6.2 years (123 209 person-years), with a total of 1523 CVD events (12.4 per 1000 participant-years) reported. There was a significant difference in the association of steps per day and CVD between older (ie, ≥60 years of age) and younger adults (ie, Conclusions: For older adults, taking more daily steps was associated with a progressively decreased risk of CVD. Monitoring and promoting steps per day is a simple metric for clinician–patient communication and population health to reduce the risk of CVD.

BACKGROUND Few studies examined the association between depressive symptom trajectories and objectively measured physical activity. OBJECTIVE We aimed to investigate if antecedent depressive symptoms predict subsequent daily step counts among participants in the electronic Framingham Heart Study (eFHS). METHODS We performed group-based multi-trajectory modeling to construct depressive symptom trajectory groups using both depressive symptoms (CES-D >16) and antidepressant use in eFHS participants who attended three FHS research exams over fourteen years. At the third exam, eFHS participants were provided with a study smartwatch for measuring daily step counts. We performed linear mixed models to examine the association between depressive symptom trajectories and daily step counts over one-year follow-up adjusting for age, sex, wear-hour, body mass index, and smoking status. RESULTS We identified two depressive symptom trajectory groups from 724 eFHS participants (mean age 53 years, 60% women). The low symptom group (n=566; mean follow-up 286±111 days) consisted of ≤5% of participants with depressive symptoms and ≤1% reporting antidepressant medication use, and the high symptom group (n = 158; 269±113 days) consisted of ≥28% of participants with depressive symptoms and ≥47% reporting antidepressant medication use across the three exams. Compared to those in the low symptom group, participants in the high symptom group walked fewer daily steps during one-year follow-up (690 fewer; 95% CI: 254-1125). CONCLUSIONS Antecedent depressive symptoms/anti-depressive medication use was associated with lower subsequent daily step counts in eFHS. Our findings suggest that adding interventions to improve mood via mHealth technologies may help promote people’s daily physical activity.

BackgroundThe joint associations of total and intensity-specific physical activity with obesity in relation to all-cause mortality risk are unclear.MethodsWe included 34 492 adults (72% women, median age 62.1 years, 2034 deaths during follow-up) in a harmonised meta-analysis of eight population-based prospective cohort studies with mean follow-up ranging from 6.0 to 14.5 years. Standard body mass index categories were cross-classified with sample tertiles of device-measured total, light-to-vigorous and moderate-to-vigorous physical activity and sedentary time. In five cohorts with waist circumference available, high and low waist circumference was combined with tertiles of moderate-to-vigorous physical activity.ResultsThere was an inverse dose–response relationship between higher levels of total and intensity-specific physical activity and mortality risk in those who were normal weight and overweight. In individuals with obesity, the inverse dose–response relationship was only observed for total physical activity. Similarly, lower levels of sedentary time were associated with lower mortality risk in normal weight and overweight individuals but there was no association between sedentary time and risk of mortality in those who were obese. Compared with the obese-low total physical activity reference, the HRs were 0.59 (95% CI 0.44 to 0.79) for normal weight-high total activity and 0.67 (95% CI 0.48 to 0.94) for obese-high total activity. In contrast, normal weight-low total physical activity was associated with a higher risk of mortality compared with the obese-low total physical activity reference (1.28; 95% CI 0.99 to 1.67).ConclusionsHigher levels of physical activity were associated with lower risk of mortality irrespective of weight status. Compared with obesity-low physical activity, there was no survival benefit of being normal weight if physical activity levels were low.

Background Non-genetic factors contribute to differences in diabetes risk across race/ethnic and socioeconomic groups, which raises the question of whether effects of predictors of diabetes are similar across populations. We studied diabetes incidence in the primarily non-Hispanic White Framingham Heart Study (FHS, N = 4066) and the urban, largely immigrant Hispanic Community Health Study/Study of Latinos (HCHS/SOL, N = 6891) Please check if the affiliations are captured and presented correctly. Methods Clinical, behavioral, and socioeconomic characteristics were collected at in-person examinations followed by seven-day accelerometry. Among individuals without diabetes, Cox proportional hazards regression models (both age- and sex-adjusted, and then multivariable-adjusted for all candidate predictors) identified predictors of incident diabetes over a decade of follow-up, defined using clinical history or laboratory assessments. Results Four independent predictors were shared between FHS and HCHS/SOL. In each cohort, the multivariable-adjusted hazard of diabetes increased by approximately 50% for every ten-year increment of age and every five-unit increment of body mass index (BMI), and was 50–70% higher among hypertensive than among non-hypertensive individuals (all P Conclusions The same four independent predictors – age, body mass index, hypertension and employment status – were associated with diabetes risk across two disparate US populations. While the reason for elevated diabetes risk in full-time workers is unclear, the findings suggest that diabetes may be part of the work-related burden of disease. Our findings also support prior evidence that differences by gender and socioeconomic position in diabetes risk are not universally present across populations.

Introduction: Depression is a common and serious medical illness world-wide. Studies have demonstrated a protective effect of physical activity on depression, but few studies have examined the prospective association between depressive symptoms and objectively measured physical activity. Objective: To investigate if antecedent depressive symptoms predict subsequent daily step counts among participants enrolled in the electronic Framingham Heart Study (eFHS). We hypothesize that the trajectory group with a larger proportion of participants having depressive symptoms and antidepressant use is associated with a lower level of physical activity. Methods: We used group-based multi-trajectory modeling to construct depressive symptom trajectory patterns using both depressive symptoms and antidepressant use collected from eFHS participants who attended three FHS health exams over fourteen years. The presence of depressive symptoms was defined at each exam with a Center for Epidemiological Studies-Depression (CES-D) score > 16. At the final exam, participants were provided with a study smartwatch to measure daily step counts. We excluded: a) person-day records with less than 5 hours of wear-time, or less than 1000 steps recorded in a day; b) participants who failed to return data for ≥1 day per week in the first month. We performed linear mixed effects models to examine the association between depressive symptom trajectories and average daily step counts during the first 30 days of smartwatch use and one-year of follow-up adjusting for age, sex, wear-hour, BMI, and smoking status. We used p Results: We identified two depressive symptom trajectory groups for the 724 eFHS participants (mean age 53 years, 60% women). The “low-stable” group (n=578; mean follow-up 286±110 days) consisted of n = 146; 269±114 days) consisted of >21% of participants with depressive symptoms and >46% of those with antidepressant medication use across the three exams. Compared to the low-stable trajectory group, the participants in the high-increasing depressive symptoms group walked 475 (95% CI: 24-927) fewer daily steps during the first 30 days of smartwatch use ( p = 0.04) and walked 550 (95% CI: 109-991) fewer daily steps during one-year of follow-up ( p = 0.01). Conclusion: Participants in the group with a larger proportion of antecedent depression and anti-depressant use walked significantly fewer steps compared to the group with a smaller proportion of antecedent depression and anti-depressant use. Our findings suggest that interventions via mHealth technologies that target mood may play an important role in promoting physical activity.

Background: One of the mechanisms suggested to link physical activity (PA) to favorable brain health is through stimulation of neural growth factors such as brain-derived neurotrophic factor (BDNF). Acute bouts of PA stimulate circulating BDNF levels. Objective: In this investigation, we assessed whether habitual, accelerometer-measured PA levels were related to circulating BDNF levels in a middle-aged cohort. Methods: In the Framingham Heart Study Third Generation cohort, 1,769 participants provided reliable accelerometry data and were not missing BDNF measurement or platelet counts. In a cross-sectional analysis, using multivariable regression, we related PA measures to serum BDNF levels, adjusting for age, sex, smoking status, platelet count, depression status, and accelerometer wear time. Results: Our study participants (mean age 47±9 years, 50.8% women) spent an average of 22.3 mins/day in moderate-to-vigorous (MV)PA. Most PA variables (steps, MVPA, light activity, and sedentary time) were not related to BDNF levels (p > 0.05). We observed a non-linear trend, where 15–50 mins/week vigorous activity was associated with lower BDNF compared to those with 0 min vigorous activity (β= –0.049±0.024, p = 0.05), but with no significant associations at lower or higher vigorous activity levels. In smokers, MVPA was also associated with lower BDNF levels (β= –0.216±0.079, p = 0.01). Conclusion: Our study reveals that circulating BDNF is not chronically elevated in individuals with higher levels of habitual PA in middle-aged adults from the community and may even be chronically suppressed with higher PA in subgroups, including current smokers. These results do not contradict previous studies demonstrating that circulating BDNF rises acutely after PA.