Association of Physical Inactivity with MRI Markers of Brain Aging: Assessing Mediation by Cardiometabolic and Epigenetic Factors.

INTRODUCTION: Cardiometabolic risk factors and epigenetic patterns, increased in physically inactive individuals, are associated with an accelerated brain aging process. OBJECTIVE: To determine whether cardiometabolic risk factors and epigenetic patterns mediate the association of physical inactivity with unfavorable brain morphology. METHODS: We included dementia and stroke free participants from the Framingham Heart Study Third Generation and Offspring cohorts who had accelerometery and brain MRI data (n = 2,507, 53.9% women, mean age 53.9 years). We examined mediation by the 2017-revised Framingham Stroke Risk Profile (FSRP, using weights for age, cardiovascular disease, atrial fibrillation, diabetes and smoking status, antihypertension medications, and systolic blood pressure) and the homeostatic model of insulin resistance (HOMA-IR) in models of the association of physical inactivity with brain aging, adjusting for age, age-squared, sex, accelerometer wear time, cohort, time from exam-to-MRI, and season. We similarly assessed mediation by an epigenetic age-prediction algorithm, GrimAge, in a smaller sample of participants who had DNA methylation data (n = 1,418). RESULTS: FSRP and HOMA-IR explained 8.3-20.5% of associations of higher moderate-to-vigorous physical activity (MVPA), higher steps, and lower sedentary time with higher brain volume. Additionally, FSRP and GrimAge explained 10.3-22.0% of associations of physical inactivity with lower white matter diffusivity and FSRP explained 19.7% of the association of MVPA with lower free water accumulation. CONCLUSION: Our results suggest that cardiometabolic risk factors and epigenetic patterns partially mediate the associations of physical inactivity with lower brain volume, higher white matter diffusivity, and aggregation of free water in the extracellular compartments of the brain.

Characterizing longitudinal change in accelerometry-based moderate-to-vigorous physical activity in the Hispanic Community Health Study/Study of Latinos and the Framingham Heart Study.

BACKGROUND: Physical activity promotes health and is particularly important during middle and older age for decreasing morbidity and mortality. We assessed the correlates of changes over time in moderate-to-vigorous physical activity (MVPA) in Hispanic/Latino adults from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL: mean [SD] age 49.2 y [11.5]) and compared them to a cohort of primarily White adults from the Framingham Heart Study (FHS: mean [SD] 46.9 y [9.2]). METHODS: Between 2008 and 2019, we assessed accelerometry-based MVPA at two time points with an average follow-up of: 7.6 y, SD 1.3 for HCHS/SOL, and 7.8 y, SD 0.7 for FHS. We used multinomial logistic regression to relate socio-demographic and health behaviors with changes in compliance with 2018 US recommendations for MVPA from time 1 to time 2 (remained active or inactive; became active or inactive) across the two cohorts. RESULTS: In HCHS/SOL mean MVPA was 22.6 (SD, 23.8) minutes at time 1 and dropped to 16.7 (19.0) minutes at time 2. In FHS Mean MVPA was 21.7 min (SD, 17.7) at time 1 and dropped to 21.3 min (SD, 19.2) at time 2. Across both cohorts, odds of meeting MVPA guidelines over time were about 6% lower in individuals who had lower quality diets vs. higher, about half in older vs. younger adults, about three times lower in women vs. men, and 9% lower in individuals who had a higher vs. lower BMI at baseline. Cohorts differed in how age, gender, income, education, depressive symptoms, marital status and perception of general health and pain associated with changes in physical activity. High income older Hispanics/Latino adults were more likely to become inactive at the follow-up visit as were HCHS/SOL women who were retired and FHS participants who had lower levels of education and income. Higher depressive symptomology was associated with becoming active only in HCHS/SOL women. Being male and married was associated with becoming inactive in both cohorts. Higher perception of general health and lower perception of pain were associated with remaining active only in FHS adults. CONCLUSIONS: These findings highlight potentially high-risk groups for targeted MVPA intervention.

Association of Depressive Symptom Trajectory With Physical Activity Collected by mHealth Devices in the Electronic Framingham Heart Study: Cohort Study.

BACKGROUND: Few studies have examined the association between depressive symptom trajectories and physical activity collected by mobile health (mHealth) devices. OBJECTIVE: We aimed to investigate if antecedent depressive symptom trajectories predict subsequent physical activity 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 (Center for Epidemiological Studies-Depression [CES-D] scores) and antidepressant medication use in eFHS participants who attended 3 Framingham Heart Study research exams over 14 years. At the third exam, eFHS participants were instructed to use a smartphone app for submitting physical activity index (PAI) surveys. In addition, they were provided with a study smartwatch to track their daily step counts. We performed linear mixed models to examine the association between depressive symptom trajectories and physical activity including app-based PAI and smartwatch-collected step counts over a 1-year follow-up adjusting for age, sex, wear hour, BMI, smoking status, and other health variables. RESULTS: We identified 3 depressive symptom trajectory groups from 722 eFHS participants (mean age 53, SD 8.5 years; n=432, 60% women). The low symptom group (n=570; mean follow-up 287, SD 109 days) consisted of participants with consistently low CES-D scores, and a small proportion reported antidepressant use. The moderate symptom group (n=71; mean follow-up 280, SD 118 days) included participants with intermediate CES-D scores, who showed the highest and increasing likelihood of reporting antidepressant use across 3 exams. The high symptom group (n=81; mean follow-up 252, SD 116 days) comprised participants with the highest CES-D scores, and the proportion of antidepressant use fell between the other 2 groups. Compared to the low symptom group, the high symptom group had decreased PAI (mean difference -1.09, 95% CI -2.16 to -0.01) and the moderate symptom group walked fewer daily steps (823 fewer, 95% CI -1421 to -226) during the 1-year follow-up. CONCLUSIONS: Antecedent depressive symptoms or antidepressant medication use was associated with lower subsequent physical activity collected by mHealth devices in eFHS. Future investigation of interventions to improve mood including via mHealth technologies to help promote people's daily physical activity is needed.

Physical Activity Over the Lifecourse and Cardiovascular Disease.

Despite improvements in cardiovascular care in recent decades, cardiovascular disease (CVD) remains a leading cause of death worldwide. At its core, CVD is a largely preventable disease with diligent risk factor management and early detection. As highlighted in the American Heart Association's Life's Essential 8, physical activity plays a central role in CVD prevention at an individual and population level. Despite pervasive knowledge of the numerous cardiovascular and noncardiovascular health benefits of physical activity, physical activity has steadily decreased over time and unfavorable changes in physical activity occur throughout people's lives. Here, we use a lifecourse framework to examine the evidence reporting on the association of physical activity with CVD. From in utero to older adults, we review and discuss the evidence detailing how physical activity may prevent incident CVD and mitigate CVD-related morbidity and death across all life stages.

Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis.

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 <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk. 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.

Increasing Engagement in the Electronic Framingham Heart Study: Factorial Randomized Controlled Trial.

BACKGROUND: Smartphone apps and mobile health devices offer innovative ways to collect longitudinal cardiovascular data. Randomized evidence regarding effective strategies to maintain longitudinal engagement is limited. OBJECTIVE: This study aimed to evaluate smartphone messaging interventions on remote transmission of blood pressure (BP) and heart rate (HR) data. METHODS: We conducted a 2 × 2 × 2 factorial blinded randomized trial with randomization implemented centrally to ensure allocation concealment. We invited participants from the Electronic Framingham Heart Study (eFHS), an e-cohort embedded in the FHS, and asked participants to measure their BP (Withings digital cuff) weekly and wear their smartwatch daily. We assessed 3 weekly notification strategies to promote adherence: personalized versus standard; weekend versus weekday; and morning versus evening. Personalized notifications included the participant's name and were tailored to whether or not data from the prior week were transmitted to the research team. Intervention notification messages were delivered weekly automatically via the eFHS app. We assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification after randomization. Outcomes were adherence to BP and HR transmission at 3 months (primary) and 6 months (secondary). RESULTS: Of the 791 FHS participants, 655 (82.8%) were eligible and randomized (mean age 53, SD 9 years; 392/655, 59.8% women; 596/655, 91% White). For the personalized versus standard notifications, 38.9% (126/324) versus 28.8% (94/327) participants sent BP data at 3 months (difference=10.1%, 95% CI 2.9%-17.4%; P=.006), but no significant differences were observed for HR data transmission (212/324, 65.4% vs 209/327, 63.9%; P=.69). Personalized notifications were associated with increased BP and HR data transmission versus standard at 6 months (BP: 107/291, 36.8% vs 66/295, 22.4%; difference=14.4%, 95% CI 7.1- 21.7%; P<.001; HR: 186/281, 66.2% vs 158/281, 56.2%; difference=10%, 95% CI 2%-18%; P=.02). For BP and HR primary or secondary outcomes, there was no evidence of differences in data transmission for notifications sent on weekend versus weekday or morning versus evening. CONCLUSIONS: Personalized notifications increased longitudinal adherence to BP and HR transmission from mobile and digital devices among eFHS participants. Our results suggest that personalized messaging is a powerful tool to promote adherence to mobile health systems in cardiovascular research. TRIAL REGISTRATION: ClinicalTrials.gov NCT03516019; https://clinicaltrials.gov/ct2/show/NCT03516019.

Prospective Association of Daily Steps With Cardiovascular Disease: A Harmonized Meta-Analysis.

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, <60 years of age). For older adults, the HR for quartile 2 was 0.80 (95% CI, 0.69 to 0.93), 0.62 for quartile 3 (95% CI, 0.52 to 0.74), and 0.51 for quartile 4 (95% CI, 0.41 to 0.63) compared with the lowest quartile. For younger adults, the HR for quartile 2 was 0.79 (95% CI, 0.46 to 1.35), 0.90 for quartile 3 (95% CI, 0.64 to 1.25), and 0.95 for quartile 4 (95% CI, 0.61 to 1.48) compared with the lowest quartile. Restricted cubic splines demonstrated a nonlinear association whereby more steps were associated with decreased risk of CVD among older adults. 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.

Association of Accelerometer-Measured Physical Activity and Sedentary Time with Epigenetic Markers of Aging.

INTRODUCTION/PURPOSE: Physical activity may influence chronic disease risk, in part, through epigenetic mechanisms. Previous studies have demonstrated that an acute bout of physical activity can influence DNA methylation status. Few studies have explored the relationship between habitual, accelerometer-measured physical activity or sedentary time with epigenetic markers of aging. METHODS: We used linear regression to examine cross-sectional associations of accelerometer-measured physical activity and sedentary time with extrinsic and intrinsic epigenetic age acceleration (EEAA and IEAA) models 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 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). RESULTS: Walking 1500 more steps per day or spending 3 fewer hours sedentary was associated with >10 months lower GrimAge biological age (or ~1 month lower AdjGrimAge, after adjusting for blood cells, P < 0.05). Every 5 min·d -1 more moderate to vigorous physical activity was associated with 19-79 d of lower GrimAge (4-23 d lower using EEAA or AdjGrimAge, P < 0.01). Adjusting for BMI attenuated these results, but all statistically significant associations with AdjGrimAge remained. CONCLUSIONS: 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.

Factors associated with long-term use of digital devices in the electronic Framingham Heart Study.

Long-term use of digital devices is critical for successful clinical or research use, but digital health studies are challenged by a rapid drop-off in participation. A nested e-cohort (eFHS) is embedded in the Framingham Heart Study and uses three system components: a new smartphone app, a digital blood pressure (BP) cuff, and a smartwatch. This study aims to identify factors associated with the use of individual eFHS system components over 1-year. Among 1948 eFHS enrollees, we examine participants who returned surveys within 90 days (n = 1918), and those who chose to use the smartwatch (n = 1243) and BP cuff (n = 1115). For each component, we investigate the same set of candidate predictors for usage and use generalized linear mixed models to select predictors (P < 0.1, P value from Z test statistic), adjusting for age, sex, and time (app use: 3-month period, device use: weekly). A multivariable model with the predictors selected from initial testing is used to identify factors associated with use of components (P < 0.05, P value from Z test statistic) adjusting for age, sex, and time. In multivariable models, older age is associated with higher use of all system components. Female sex and higher education levels are associated with higher completion of app-based surveys whereas higher scores for depressive symptoms, and lower than excellent self-rated health are associated with lower use of the smartwatch over the 12-month follow-up. Our findings show that sociodemographic and health related factors are significantly associated with long-term use of digital devices. Future research is needed to test interventional strategies focusing on these factors to evaluate improvement in long-term engagement.

Body mass index across adulthood and the development of airflow obstruction and emphysema.

BACKGROUND: Low body mass index (BMI) is associated with COPD, but temporal relationships between airflow obstruction (AO) development and emphysematous change are unclear. We investigated longitudinal changes in BMI, AO, and lung density throughout adulthood using data from the Framingham Offspring Cohort (FOC). METHODS: BMI trajectories were modelled throughout adulthood in 4587 FOC participants from Exam 2 (mean age = 44), through Exam 9 (mean age = 71), in AO participants and non-AO participants (AO n = 1036), determined by spirometry, using fractional polynomial growth curves. This process was repeated for low lung density (LLD) and non LLD participants (LLD n = 225) determined by Computed Tomography. Spirometry decline was compared separately between tertiles of BMI in those aged <40 years and associations between fat and lean mass (measured using Dual Energy X-ray Absorptiometry, DEXA) and development of AO and LLD were also assessed. Additional analyses were performed with adjustment for smoking volume. RESULTS: The BMI trajectory from 30 years of age was visually lower in the AO group than both non-AO smokers (non-

The association of sedentary behaviour and physical activity with periodontal disease in NHANES 2011-2012.

AIM: Periodontal disease is one of the most prevalent oral pathologies and a major chronic disease worldwide. Lifestyle habits such as poor nutrition and smoking have been established to contribute to the development of periodontal disease, but limited research has investigated whether physical activity and sedentary lifestyle play a role. The purpose of this study is to evaluate the association between physical activity, sedentary behaviour, and periodontal disease. MATERIALS AND METHODS: We used a nationally representative data set from the National Health and Nutrition Examination Survey (NHANES) 2011-2012. We examined the association between physical activity and sedentary behaviour and periodontal disease using multivariable logistic regression models and reported odds ratios (ORs). RESULTS: Individuals with higher total physical activity, higher leisure time physical activity, and lower amount of total sedentary behaviour had lower periodontal disease prevalence. Adjusted multivariable regression models showed that higher sedentary behaviour (more than 7.5 h/day) was associated with higher odds of periodontal disease (OR = 1.17; 95% confidence interval = 1.00-1.36; p = .045). CONCLUSIONS: The findings showed that higher sedentary behaviour is associated with higher odds of periodontal disease. Future prospective longitudinal studies and strategies are needed to investigate implications further and define the magnitude of the association between physical activity and periodontal disease.

Predictors of incident diabetes in two populations: framingham heart study and hispanic community health study / study of latinos.

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 < 0.01). Compared with full-time employment status, the multivariable-adjusted hazard ratio (HR) and 95% confidence interval (CI) for part-time employment was 0.61 (0.37,1.00) in FHS and 0.62 (0.41,0.95) in HCHS/SOL. Moderate-to-vigorous physical activity (MVPA) was an additional predictor in common observed in age- and sex-adjusted models, which did not persist after adjustment for other covariates (compared with MVPA ≤ 5 min/day, HR for MVPA level ≥ 30 min/day was 0.48 [0.31,0.74] in FHS and 0.74 [0.56,0.97] in HCHS/SOL). Additional predictors found in sex- and age-adjusted analyses among the FHS participants included male gender and lower education, but these predictors were not found to be independent of others in multivariable adjusted models, nor were they associated with diabetes risk among HCHS/SOL adults. 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.

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.

Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts.

BACKGROUND: Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support this recommendation. We aimed to determine the association between number of steps per day and stepping rate with all-cause mortality. METHODS: In this meta-analysis, we identified studies investigating the effect of daily step count on all-cause mortality in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked participating study investigators to process their participant-level data following a standardised protocol. The primary outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose-response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-variance weighted random effects models. FINDINGS: We identified 15 studies, of which seven were published and eight were unpublished, with study start dates between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10·1 per 1000 participant-years) over a median follow-up of 7·1 years ([IQR 4·3-9·9]; total sum of follow-up across studies was 297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3, and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0·60 (95% CI 0·51-0·71) for quartile 2, 0·55 (0·49-0·62) for quartile 3, and 0·47 (0·39-0·57) for quartile 4. Restricted cubic splines showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of steps per day until 6000-8000 steps per day and among adults younger than 60 years until 8000-10 000 steps per day. Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0·67 [95% CI 0·56-0·83]) and a peak of 60 min (0·67 [0·50-0·90]), but not significant for time (min per day) spent walking at 40 steps per min or faster (1·12 [0·96-1·32]) and 100 steps per min or faster (0·86 [0·58-1·28]). INTERPRETATION: Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health promotion of physical activity. FUNDING: US Centers for Disease Control and Prevention.

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.

Accelerometer-Measured, Habitual Physical Activity and Circulating Brain-Derived Neurotrophic Factor: A Cross-Sectional Study.

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 (ß= -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 (ß= -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.

Device-measured physical activity, adiposity and mortality: a harmonised meta-analysis of eight prospective cohort studies.

BACKGROUND: The joint associations of total and intensity-specific physical activity with obesity in relation to all-cause mortality risk are unclear. METHODS: We 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. RESULTS: There 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). CONCLUSIONS: Higher 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.