Proteomic analysis of cardiorespiratory fitness for prediction of mortality and multisystem disease risks.

Despite the wide effects of cardiorespiratory fitness (CRF) on metabolic, cardiovascular, pulmonary and neurological health, challenges in the feasibility and reproducibility of CRF measurements have impeded its use for clinical decision-making. Here we link proteomic profiles to CRF in 14,145 individuals across four international cohorts with diverse CRF ascertainment methods to establish, validate and characterize a proteomic CRF score. In a cohort of around 22,000 individuals in the UK Biobank, a proteomic CRF score was associated with a reduced risk of all-cause mortality (unadjusted hazard ratio 0.50 (95% confidence interval 0.48-0.52) per 1 s.d. increase). The proteomic CRF score was also associated with multisystem disease risk and provided risk reclassification and discrimination beyond clinical risk factors, as well as modulating high polygenic risk of certain diseases. Finally, we observed dynamicity of the proteomic CRF score in individuals who undertook a 20-week exercise training program and an association of the score with the degree of the effect of training on CRF, suggesting potential use of the score for personalization of exercise recommendations. These results indicate that population-based proteomics provides biologically relevant molecular readouts of CRF that are additive to genetic risk, potentially modifiable and clinically translatable.

Physical Activity and Progression of Coronary Artery Calcification in Men and Women.

Importance: Prior cross-sectional studies have suggested that very high levels of physical activity (PA) are associated with a higher prevalence of coronary artery calcium (CAC). However, less is known regarding the association between high-volume PA and progression of CAC over time. Objective: To explore the association between PA (measured at baseline and during follow-up) and the progression of CAC over time. Design, Setting, and Participants: This cohort study included data from 8771 apparently healthy men and women 40 years and older who had multiple preventive medicine visits at the Cooper Clinic (Dallas, Texas), with a mean (SD) follow-up time of 7.8 (4.7) years between the first and last clinic visit. Participants with reported PA and CAC measurements at each visit during 1998 to 2019 were included in the study. Data were analyzed from March 2023 to February 2024. Exposures: PA reported at baseline and follow-up, examined continuously per 500 metabolic equivalent of task minutes per week (MET-min/wk) and categorically: less than 1500, 1500 to 2999, 3000 or more MET-min/wk. Main Outcomes and Measures: Negative binomial regression was used to estimate the rate of mean CAC progression between visits, with potential modification by PA volume, calculated as the mean of PA at baseline and follow-up. In addition, proportional hazards regression was used to estimate hazard ratios for baseline PA as a predictor of CAC progression to 100 or more Agatston units (AU). Results: Among 8771 participants, the mean (SD) age at baseline was 50.2 (7.3) years for men and 51.1 (7.3) years for women. The rate of mean CAC progression per year from baseline was 28.5% in men and 32.1% in women, independent of mean PA during the same time period. That is, the difference in the rate of CAC progression per year was 0.0% per 500 MET-min/wk for men and women (men: 95% CI, -0.1% to 0.1%; women: 95% CI, -0.4% to 0.5%). Moreover, baseline PA was not associated with CAC progression to a clinically meaningful threshold of 100 AU or more over the follow-up period. The hazard ratio for a baseline PA value of 3000 or more MET-min/wk vs less than 1500 MET-min/wk to cross this threshold was 0.84 (95% CI, 0.66 to 1.08) in men and 1.16 (95% CI, 0.57 to 2.35) in women. Conclusions and Relevance: This study found that PA volume was not associated with progression of CAC in a large cohort of healthy men and women who were initially free of overt cardiovascular disease.

Multimorbidity trajectories in early adulthood and middle age: Findings from the CARDIA prospective cohort study.

Background: Multimorbidity research has focused on the prevalence and consequences of multimorbidity in older populations. Less is known about the accumulation of chronic conditions earlier in the life course. Methods: We identified patterns of longitudinal multimorbidity accumulation using 30 years of data from in-person exams, annual follow-ups, and adjudicated end-points among 4,945 participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Chronic conditions included arthritis, asthma, atrial fibrillation, cancer, end stage renal disease, chronic obstructive pulmonary disease, coronary heart disease, diabetes, heart failure, hyperlipidemia, hypertension, and stroke. Trajectory patterns were identified using latent class growth curve models. Results: Mean age (SD) at baseline (1985-6) was 24.9 (3.6), 55% were female, and 51% were Black. The median follow-up was 30 years (interquartile range 25-30). We identified six trajectory classes characterized by when conditions began to accumulate and the rapidity of accumulation: (1) early-fifties, slow, (2) mid-forties, fast, (3) mid-thirties, fast, (4) late-twenties, slow, (5) mid-twenties, slow, and (6) mid-twenties, fast. Compared with participants in the early-fifties, slow trajectory class, participants in mid-twenties, fast were more likely to be female, Black, and currently smoking and had a higher baseline mean waist circumference (83.6 vs. 75.6 cm) and BMI (27.0 vs. 23.4 kg/m2) and lower baseline physical activity (414.1 vs. 442.4 exercise units). Conclusions: A life course approach that recognizes the heterogeneity in patterns of accumulation of chronic conditions from early adulthood into middle age could be helpful for identifying high risk subgroups and developing approaches to delay multimorbidity progression.

Association of Cardiovascular Health in Young Adulthood with Long-Term Blood Pressure Trajectories.

BACKGROUND: Cardiovascular health (CVH) in young adulthood (YA) has been associated with cardiovascular outcomes in older age. However, little is known about the relationship between YA CVH and mid-life BP trajectories. METHODS: Baseline CVH (defined by 7 of AHA's Life's Essential 8 [LE8] metrics, excluding BP) was measured in YA with individual metrics scored and averaged as a composite LE8 score. Categorical CVH status was defined as high, moderate, and low. Latent class analysis was used to identify trajectories of mid-BP (mean of SBP and DBP) from average ages 35 to 55 years. Multinomial logistic regression was used to estimate the association of YA CVH status (continuously and categorically) with mid-life BP trajectory group membership. RESULTS: There were 3,688 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study in YA with follow-up data for mid-life BP trajectories. We observed 3 BP trajectory groups, labeled as Persistently-Low, Middle, and High-Increasing. On average, each 10-points higher baseline LE8 score (mean [SD] of 73.5 [13.1]) in YA was associated with adjusted odds ratios of 0.78 (95% CI, 0.72-0.84) for membership in the Middle and 0.65 (0.57-0.73) for membership in the High-Increasing trajectory groups. Compared with categorical low CVH status at baseline, those with high CVH were significantly less likely to be in the Middle and High-Increasing BP trajectory groups. CONCLUSIONS: Moderate or low CVH status in YA is associated with elevated mid-life BP trajectory. These data suggest that young adult CVH promotion may be important for primordial prevention of hypertension.

Transforming Big Data into AI-ready data for nutrition and obesity research.

OBJECTIVE: Big Data are increasingly used in obesity and nutrition research to gain new insights and derive personalized guidance; however, this data in raw form are often not usable. Substantial preprocessing, which requires machine learning (ML), human judgment, and specialized software, is required to transform Big Data into artificial intelligence (AI)- and ML-ready data. These preprocessing steps are the most complex part of the entire modeling pipeline. Understanding the complexity of these steps by the end user is critical for reducing misunderstanding, faulty interpretation, and erroneous downstream conclusions. METHODS: We reviewed three popular obesity/nutrition Big Data sources: microbiome, metabolomics, and accelerometry. The preprocessing pipelines, specialized software, challenges, and how decisions impact final AI- and ML-ready products were detailed. RESULTS: Opportunities for advances to improve quality control, speed of preprocessing, and intelligent end user consumption were presented. CONCLUSIONS: Big Data have the exciting potential for identifying new modifiable factors that impact obesity research. However, to ensure accurate interpretation of conclusions arising from Big Data, the choices involved in preparing AI- and ML-ready data need to be transparent to investigators and clinicians relying on the conclusions.

Validation of a Zio XT Patch Accelerometer for the Objective Assessment of Physical Activity in the Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: Combination devices to monitor heart rate/rhythms and physical activity are becoming increasingly popular in research and clinical settings. The Zio XT Patch (iRhythm Technologies, San Francisco, CA, USA) is US Food and Drug Administration (FDA)-approved for monitoring heart rhythms, but the validity of its accelerometer for assessing physical activity is unknown. OBJECTIVE: To validate the accelerometer in the Zio XT Patch for measuring physical activity against the widely-used ActiGraph GT3X. METHODS: The Zio XT and ActiGraph wGT3X-BT (Actigraph, Pensacola, FL, USA) were worn simultaneously in two separately-funded ancillary studies to Visit 6 of the Atherosclerosis Risk in Communities (ARIC) Study (2016-2017). Zio XT was worn on the chest and ActiGraph was worn on the hip. Raw accelerometer data were summarized using mean absolute deviation (MAD) for six different epoch lengths (1-min, 5-min, 10-min, 30-min, 1-h, and 2-h). Participants who had ≥3 days of at least 10 h of valid data between 7 a.m-11 p.m were included. Agreement of epoch-level MAD between the two devices was evaluated using correlation and mean squared error (MSE). RESULTS: Among 257 participants (average age: 78.5 ± 4.7 years; 59.1% female), there were strong correlations between MAD values from Zio XT and ActiGraph (average r: 1-min: 0.66, 5-min: 0.90, 10-min: 0.93, 30-min: 0.93, 1-h: 0.89, 2-h: 0.82), with relatively low error values (Average MSE × 106: 1-min: 349.37 g, 5-min: 86.25 g, 10-min: 56.80 g, 30-min: 45.46 g, 1-h: 52.56 g, 2-h: 54.58 g). CONCLUSIONS: These findings suggest that Zio XT accelerometry is valid for measuring duration, frequency, and intensity of physical activity within time epochs of 5-min to 2-h.

Behavior reallocations within 24-h movement profiles and change in cardiometabolic biomarkers during pregnancy.

OBJECTIVE: The goal of this study was to investigate associations of reallocations within 24-h movement profiles and changes in cardiometabolic biomarkers from early to late pregnancy. METHODS: In 137 individuals with prepregnancy overweight/obesity, waking movement was measured using wrist-worn accelerometers, sleep was self-reported, and biomarkers were measured in fasting serum samples at 12 and 32 weeks' gestation. We used compositional isotemporal substitution models. RESULTS: On average, biomarkers increased 21%-83% across pregnancy. For those with guideline-recommended moderate/vigorous-intensity physical activity (MVPA) in early pregnancy, reallocating 30 min from MVPA to sleep, sedentary behavior, or light-intensity physical activity (LPA) was associated with a 0.6 mmol/L greater increase in total cholesterol (95% CI: -0.1 to 1.2) and a 0.7 mmol/L greater increase in low-density lipoprotein (LDL) cholesterol (95% CI: 0.1 to 1.3) from early to late pregnancy. For those with low MVPA in early pregnancy, reallocating 30 min from sleep, sedentary behavior, or LPA to MVPA was associated with a 0.6 mmol/L lower increase in total cholesterol (95% CI: -1.3 to 0.1) and a 0.8 mmol/L lower increase in LDL cholesterol (95% CI: -1.4 to -0.1) from early to late pregnancy. There were no associations with change in glucose, insulin, homeostatic model assessment for insulin resistance, very low-density lipoprotein, or high-density lipoprotein cholesterol, triglycerides, or free fatty acids. CONCLUSIONS: Maintaining or achieving a 24-h movement profile with guideline-recommended amounts of MVPA may be beneficial for reducing pregnancy-induced increases in total and LDL cholesterol.

Social and Behavior Factors of Alzheimer's Disease and Related Dementias: A National Study in the U.S.

INTRODUCTION: Considerable research has linked many risk factors to Alzheimer's Disease and Related Dementias (ADRD). Without a clear etiology of ADRD, it is advantageous to rank the known risk factors by their importance and determine if disparities exist. Statistical-based ranking can provide insight into which risk factors should be further evaluated. METHODS: This observational, population-based study assessed 50 county-level measures and estimates related to ADRD in 3,155 counties in the U.S. using data from 2010 to 2021. Statistical analysis was performed in 2022-2023. The machine learning method, eXtreme Gradient Boosting, was utilized to rank the importance of these variables by their relative contribution to the model performance. Stratified ranking was also performed based on a county's level of disadvantage. Shapley Additive exPlanations (SHAP) provided marginal contributions for each variable. RESULTS: The top three ranked predictors at the county level were insufficient sleep, consuming less than one serving of fruits/vegetables per day among adults, and having less than a high school diploma. In both disadvantaged and non-disadvantaged counties, demographic variables such as sex and race were important in predicting ADRD. Lifestyle factors ranked highly in non-disadvantaged counties compared to more environmental factors in disadvantaged counties. CONCLUSIONS: This ranked list of factors can provide a guided approach to ADRD primary prevention strategies in the U.S., as the effects of sleep, diet, and education on ADRD can be further developed. While sleep, diet, and education are important nationally, differing prevention strategies could be employed based on a county's level of disadvantage.

Plasma Neuronal Growth Regulator 1 May Link Physical Activity to Reduced Risk of Type 2 Diabetes: A Proteome-Wide Study of ARIC Participants.

Habitual physical activity (PA) impacts the plasma proteome and reduces the risk of developing type 2 diabetes (T2D). Using a large-scale proteome-wide approach in Atherosclerosis Risk in Communities study participants, we aimed to identify plasma proteins associated with PA and determine which of these may be causally related to lower T2D risk. PA was associated with 92 plasma proteins in discovery (P < 1.01 × 10-5), and 40 remained significant in replication (P < 5.43 × 10-4). Eighteen of these proteins were independently associated with incident T2D (P < 1.25 × 10-3), including neuronal growth regulator 1 (NeGR1; hazard ratio per SD 0.85; P = 7.5 × 10-11). Two-sample Mendelian randomization (MR) inverse variance weighted analysis indicated that higher NeGR1 reduces T2D risk (odds ratio [OR] per SD 0.92; P = 0.03) and was consistent with MR-Egger, weighted median, and weighted mode sensitivity analyses. A stronger association was observed for the single cis-acting NeGR1 genetic variant (OR per SD 0.80; P = 6.3 × 10-5). Coupled with previous evidence that low circulating NeGR1 levels promote adiposity, its association with PA and potential causal role in T2D shown here suggest that NeGR1 may link PA exposure with metabolic outcomes. Further research is warranted to confirm our findings and examine the interplay of PA, NeGR1, adiposity, and metabolic health.

Chronic Stress and Cardiovascular Events: Findings From the CARDIA Study.

INTRODUCTION: Higher levels of perceived stress are associated with adverse cardiovascular health. It is plausible that these associations are attenuated among individuals with positive psychological factors such as social support and health-enhancing behaviors. Therefore, this study examined longitudinal associations of chronic stress with cardiovascular disease (CVD) events, and whether social support and physical activity (PA) modify these associations. METHODS: Data from 3,401 adults (mean age 40.2 years; 46.7% Black; 56.2% women) from the Coronary Artery Risk Development in Young Adults (CARDIA) study, with no prior CVD event in 2000-2001 were analyzed. Chronic stress lasting ≥6 months across 5 life domains (work, financial, relationships, health of self, and health of close other) was self-reported. Adjudicated CVD events (fatal/or nonfatal CVD event) were ascertained yearly through 2020. PA and social support were self-reported via questionnaires. Statistical analyses were conducted in 2023 using multivariable stepwise Accelerated Failure Time analysis to assess associations between key study variables. RESULTS: The mean chronic stress score was 1.30±1.33 stressors and, by 2020, 220 participants had experienced a CVD event. Chronic stress was associated with lowered survival (time ratio: 0.92; 95% CI: 0.854-0.989), when adjusted for sociodemographic and lifestyle variables but no longer significant when adjusting for clinical factors. Neither PA nor social support were significant modifiers (all ps>0.05). CONCLUSIONS: Chronic stress was associated with the risk of having a CVD event among middle-aged adults, due at least in part to clinical mediators. Studies should continue exploring positive psychosocial and behavioral factors that may modify this association.

Breaking Up Sedentary Time Reduces Recurrent Fall Risk, but Not Incident Fracture Risk in Older Men.

Apart from physical activity volume, frequent breaks from sedentary bouts and active bouts may differentially reduce fall and fracture risk. We assessed the longitudinal relationship between frequency of breaks from time spent sedentary and frequency of active bouts with recurrent falls and fractures. The sample included 2918 men aged 79.0 ± 5.1 years with free-living activity (SenseWear Armband) at the Osteoporotic Fractures in Men Study (MrOS) year 7 (2007-2009) visit. Men were divided into quartiles by the number of breaks from sedentary bouts (sedentary bout: 5+ minutes sedentary; <1.5 metabolic equivalents of task [METS]) and separately by active bout frequency (active bout: 5+ minutes of activity; ≥1.5 METS). Recurrent falls (2+ falls/year) and fractures were ascertained by self-report; fractures were radiographically confirmed. Generalized estimating equations estimated the recurrent fall odds, with restricted cubic splines applied to assess nonlinear relationships. Cox proportional hazards models estimated fracture risk. Over 4 years of follow-up after year 7, 1025 (35.1%) men were fallers. Over 8.40 ± 4.10 years of follow-up, 640 (21.9%) men experienced a fracture. There was a significant nonlinear U-shaped relationship between number of breaks from sedentary bouts and recurrent falls (p < 0.001); compared with men with few breaks from sedentary bouts (1.4-<13.6), the odds of recurrent falls were lower with a moderate number (13.6-<17.0, odds ratio [OR] = 0.82, 95% confidence interval [CI] 0.66, 1.01; 17.0-<20.4, OR = 0.79, 95% CI 0.64, 0.99), but not with the highest number of breaks from sedentary bouts (20.4-34.6, OR = 1.01, 95% CI 0.81, 1.27). Results remained borderline significant after adjusting for total sedentary time. Men with the highest compared with the lowest number of breaks from sedentary bouts had a lower fracture risk, but the association was attenuated after adjustment for total sedentary time. No associations were observed for active bout frequency. In conclusion, breaking up extended periods of sedentary time reduces fall risk regardless of total sedentary time. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.

Young Adult Physical Activity Trajectories and Midlife Nonalcoholic Fatty Liver Disease.

Importance: Physical activity (PA) is recommended for preventing and treating nonalcoholic fatty liver disease (NAFLD). Yet, how long-term patterns of intensity-based physical activity, including moderate-intensity PA (MPA) and vigorous-intensity PA (VPA), might affect the prevalence of NAFLD in middle age remains unclear. Objective: To identify distinct intensity-based PA trajectories from young to middle adulthood and examine the associations between PA trajectories and NAFLD prevalence in midlife. Design, Setting, and Participants: This population-based cohort of 2833 participants used the Coronary Artery Risk Development in Young Adults study data. The setting included field clinics in Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and Oakland, California. Data analysis was completed in March 2023. Exposures: PA was self-reported at 8 examinations over 25 years (1985-1986 to 2010-2011) and separately scored for MPA and VPA. Main Outcomes and Measures: NAFLD was defined as liver attenuation values less than 51 Hounsfield units after exclusion of other causes of liver fat, measured using computed tomography in year 25 (2010-2011). Results: Among a total of 2833 participants included in the sample, 1379 (48.7%) self-identified as Black, 1454 (51.3%) as White, 1206 (42.6%) as male, and 1627 (57.4%) as female from baseline (1985-1986) (mean [SD] age, 25.0 [3.6] years) to year 25 (2010-2011) (mean [SD] age, 50.1 [3.6] years). Three MPA trajectories were identified: very low stable (1514 participants [53.4%]), low increasing (1096 [38.7%]), and moderate increasing (223 [7.9%]); and 3 VPA trajectories: low stable (1649 [58.2%]), moderate decreasing (1015 [35.8%]), and high decreasing (169 [6.0%]). After adjustment for covariates (sex, age, race, study center, education, smoking status, and alcohol consumption), participants in the moderate decreasing (risk ratio [RR], 0.74; 95% CI, 0.54-0.85) and the high decreasing (RR, 0.59; 95% CI, 0.44-0.80) VPA trajectories had a lower risk of NAFLD in middle age, relative to participants in the low stable VPA trajectory. Adjustments for baseline body mass index and waist circumference attenuated these estimates, but the results remained statistically significant. The adjusted RRs across the MPA trajectories were close to null and not statistically significant. Conclusions and Relevance: This cohort study of Black and White participants found a reduced risk of NAFLD in middle age for individuals with higher levels of VPA throughout young to middle adulthood compared with those with lower VPA levels. These results suggest the need for promoting sustainable and equitable prevention programs focused on VPA over the life course to aid in lowering NAFLD risk.

Aerobic and Muscle-Strengthening Physical Activity, Television Viewing, and Nonalcoholic Fatty Liver Disease: The CARDIA Study.

BACKGROUND: The prevalence of non-alcoholic fatty liver disease (NAFLD) in U.S. adults is over 30%, yet the role of lifestyle factors in the etiology of NAFLD remains understudied. We examined the associations of physical activity, by intensity and type, and television viewing with prevalent NAFLD. METHODS: Cross-sectional analysis of a population-based sample of 2726 Black (49%) and White (51%) adults (Mean (SD) age, 50 (3.6) years; 57.3% female) from the CARDIA study. Exposures were aerobic activity by intensity (moderate, vigorous; hours/week); activity type (aerobic, muscle-strengthening; hours/week); and television viewing (hours/week), examined concurrently in all models and assessed by validated questionnaires. Our outcome was NAFLD (liver attenuation < 51 Hounsfield Units), measured by non-contrast computed tomography, after exclusions for other causes of liver fat. Covariates were sex, age, race, study center, education, diet quality, smoking status, alcohol consumption, and body mass index or waist circumference. RESULTS: 648 participants had NAFLD. In the fully adjusted modified Poisson regression model, the risk ratios per interquartile range of each exposure were moderate-intensity aerobic activity, 1.10 (95% CI, 0.97-1.26); vigorous-intensity aerobic activity, 0.72 (0.63-0.82); muscle-strengthening activity, 0.89 (0.80-1.01); and television viewing, 1.20 (1.10-1.32). Relative to less active participants with higher levels of television viewing, those who participated in ≥2 h/week of both vigorous-intensity aerobic and muscle-strengthening activity and <7 h/week of television viewing had 65% lower risk of NAFLD (risk ratio = 0.35, 95% CI = 0.23-0.51). CONCLUSION: Adults who follow public health recommendations for vigorous-aerobic and muscle-strengthening activity, as well as minimize television viewing, are considerably less likely to have NAFLD than those who do not follow the recommendations and who have relatively high levels of television viewing.

Method for Activity Sleep Harmonization (MASH): a novel method for harmonizing data from two wearable devices to estimate 24-h sleep-wake cycles.

Background: Daily 24-h sleep-wake cycles have important implications for health, however researcher preferences in choice and location of wearable devices for behavior measurement can make 24-h cycles difficult to estimate. Further, missing data due to device malfunction, improper initialization, and/or the participant forgetting to wear one or both devices can complicate construction of daily behavioral compositions. The Method for Activity Sleep Harmonization (MASH) is a process that harmonizes data from two different devices using data from women who concurrently wore hip (waking) and wrist (sleep) devices for ≥ 4 days. Methods: MASH was developed using data from 1285 older community-dwelling women (ages: 60-72 years) who concurrently wore a hip-worn ActiGraph GT3X + accelerometer (waking activity) and a wrist-worn Actiwatch 2 device (sleep) for ≥ 4 days (N = 10,123 days) at the same time. MASH is a two-tiered process using (1) scored sleep data (from Actiwatch) or (2) one-dimensional convolutional neural networks (1D CNN) to create predicted wake intervals, reconcile sleep and activity data disagreement, and create day-level night-day-night pairings. MASH chooses between two different 1D CNN models based on data availability (ActiGraph + Actiwatch or ActiGraph-only). MASH was evaluated using Receiver Operating Characteristic (ROC) and Precision-Recall curves and sleep-wake intervals are compared before (pre-harmonization) and after MASH application. Results: MASH 1D CNNs had excellent performance (ActiGraph + Actiwatch ROC-AUC = 0.991 and ActiGraph-only ROC-AUC = 0.983). After exclusions (partial wear [n = 1285], missing sleep data proceeding activity data [n = 269], and < 60 min sleep [n = 9]), 8560 days were used to show the utility of MASH. Of the 8560 days, 46.0% had ≥ 1-min disagreement between the devices or used the 1D CNN for sleep estimates. The MASH waking intervals were corrected (median minutes [IQR]: -27.0 [-115.0, 8.0]) relative to their pre-harmonization estimates. Most correction (-18.0 [-93.0, 2.0] minutes) was due to reducing sedentary behavior. The other waking behaviors were reduced a median (IQR) of -1.0 (-4.0, 1.0) minutes. Conclusions: Implementing MASH to harmonize concurrently worn hip and wrist devices can minimizes data loss and correct for disagreement between devices, ultimately improving accuracy of 24-h compositions necessary for time-use epidemiology.

Association of Parkinson's disease status with accelerometer-derived physical activity and sedentary behavior in older women: The Women's Health Study (WHS).

Evidence suggests that individuals diagnosed with Parkinson's Disease (PD) spend less time in moderate-to-vigorous intensity physical activity (MVPA) compared to those without PD. However, prior studies primarily included men and did not consider movement across the entire intensity spectrum. To address these gaps, the association of PD status with total volume physical activity and time spent in sedentary, low light-intensity physical activity (LLPA), high light-intensity physical activity (HLPA), and MVPA among older women was examined. This is a cross-sectional analysis of 17,466 ambulatory women enrolled in the Women's Health Study (WHS) with a median (IQR) age of 70 (67-75) years who were asked to wear an accelerometer for 7 days from 2011 to 2015 for the ancillary study. Reported PD status was assessed via annual mail-in questionnaires prior to device wear. Compared to those without PD (n = 16,661), PD (n = 80) was associated with 98,400 fewer vector magnitude (VM) counts per day and with spending an average of 23.2 more minutes per day sedentary and 10.5 more minutes per day in LLPA. Further, PD was associated with spending 6.4 and 27.3 fewer minutes per day in HLPA and MVPA, respectively, compared to women without PD. PD in women is associated with more daily sedentary time and less time spent in health-enhancing physical activity. Prevention strategies to promote physical activity should be emphasized to enhance health and limit progression of disability in women living with PD.

Association of leisure-time physical activity and sedentary behavior with carotid atherosclerosis morphology: The ARIC carotid-MRI study.

Objective: We evaluated the prospective association of midlife leisure-time physical activity (LTPA) and sedentary behavior (SB), and their temporal patterns, with MRI-measured carotid atherosclerotic morphology. Methods: Participants enrolled in the Carotid MRI substudy (2004-2006) of the Atherosclerosis Risk in Communities (ARIC) Study and with self-reported assessments of LTPA and SB at visits 1 (1987-1989) and 3 (1993-1995) were included in this study. LTPA was ascertained using the ARIC/Baecke physical activity questionnaire and categorized according to the American Heart Association's metric of poor, intermediate, or ideal physical activity. SB, measured as TV viewing frequency, was categorized as high, medium, and low. We used multivariable adjusted linear and logistic regression models to examine the associations between midlife (visit 3 only) and persistent (visit 1 to 3) LTPA and TV viewing with carotid artery plaque burden and components. Results: Among the 1,582 (mean age: 59 years, 43% male, 18% Black) participants, 45.7%, 21.7%, and 32.6% reported ideal, intermediate, or poor LTPA, respectively. High TV viewing was reported in 33.8% of participants, with 46.4% and 19.8% reporting medium or low TV viewing, respectively. Compared to poor LTPA, ideal LTPA in midlife was not associated with total wall volume (ß=0.01, 95% CI: -0.01, 0.03), maximum carotid wall thickness (ß=0.06, 95% CI: -0.08, 0.21), normalized wall index (ß=-0.01, 95% CI: -0.03, 0.01), or maximum stenosis (ß=-0.11, 95% CI: -1.98, 1.76). Low or middle, compared to high, TV viewing was also not associated with carotid artery measures of plaque burden. Compared to poor LTPA or high TV viewing, ideal LTPA (odds ratio (OR): 0.82, 95% CI: 0.55, 1.23) and low TV viewing (OR=0.90, 95% CI: 0.56, 1.44) was not associated with odds of lipid core presence, respectively. Conclusion: Overall, this study does not provide strong evidence for an association between LTPA and SB with carotid plaque measures.

Leisure time physical activity and bone mineral density preservation during the menopause transition and postmenopause: a longitudinal cohort analysis from the Study of Women's Health Across the Nation (SWAN).

Background: Whether greater leisure time physical activity (LTPA) is associated with less bone mineral density (BMD) loss during the menopause transition (MT) remains an open question. We hypothesized that: 1) larger increases in LTPA from pre-/early perimenopause (period 1) to late perimenopause/postmenopause (period 2) would be associated with a slower period 2 BMD loss rate; and 2) greater entire-study LTPA levels would be associated with better final absolute BMD (g/cm2). Methods: Data were from of the Study of Women's Health Across the Nation (1996-2017). Exclusions were: bone beneficial medications, inability to identify start of the MT, and extreme BMD change rates. LTPA measures were a validated ordinal scale and number of metabolic equivalents per hour per week (MET hr wk-1) from sport/exercise. Multiply adjusted, linear regression models estimated: 1) BMD decline rate (annualized %) as a function of LTPA change; and 2) final BMD as a function of entire-study LTPA. Findings: Median [p25, p75] MET hr wk-1 were 4.2 [0.9, 10.1] and 4.9 [1.4, 11.2] in periods 1 and 2, respectively; walking was the commonest activity. In adjusted models (N = 875), greater increases in LTPA ordinal score and MET hr wk-1 were statistically significantly associated with a slower decline in femoral neck (FN) BMD. Larger entire-study averages of each LTPA measure were statistically significantly related to better final FN and lumbar spine BMD levels. Interpretation: Findings suggest that LTPA, at modest levels, mitigate MT-related BMD decline and even small increases in intensity, duration or frequency of common activities may lessen bone loss at the population level. Funding: US-NIH.

Association of Physical Activity and Screen Time With Body Mass Index Among US Adolescents.

Importance: The Physical Activity Guidelines Advisory Committee Scientific Report identified important research gaps to inform future guidance for adolescents, including limited evidence on the importance of sedentary behaviors (screen time) and their interactions with physical activity for adolescent health outcomes, including overweight and obesity. Objective: To identify the independent associations of physical activity and screen time categories, and the interactions between physical activity and screen time categories, with body mass index (BMI) and overweight and obesity in adolescents. Design, Setting, and Participants: This cross-sectional study used data from the Adolescent Brain Cognitive Development (ABCD) Study collected from September 10, 2018, to September 29, 2020. Data were analyzed from July 8 to December 20, 2022. A total of 5797 adolescents aged 10 to 14 years from 21 racially and ethnically diverse study sites across the US were included in the analysis. Exposures: Categories of total step count per day (with 1000 to 6000 steps per day indicating low, >6000 to 12 000 steps per day indicating medium, and >12 000 steps per day indicating high), as measured by a wearable digital device (Fitbit), and categories of self-reported screen time hours per day (with 0 to 4 hours per day indicating low, >4 to 8 hours per day indicating medium, and >8 hours per day indicating high). Main Outcomes and Measures: Participant BMI was calculated as weight in kilograms divided by height in meters squared and converted into sex- and age-specific percentiles in accordance with the Centers for Disease Control and Prevention growth curves and definitions. Individuals were classified as having overweight or obesity if their BMI was in the 85th percentile or higher for sex and age. Results: Among 5797 adolescents included in the analytic sample, 50.4% were male, 61.0% were White, 35.0% had overweight or obesity, and the mean (SD) age was 12.0 (0.6) years. Mean (SD) reported screen time use was 6.5 (5.4) hours per day, and mean (SD) overall step count was 9246.6 (3111.3) steps per day. In models including both screen time and step count, medium (risk ratio [RR], 1.24; 95% CI, 1.12-1.37) and high (RR, 1.29; 95% CI, 1.16-1.44) screen time categories were associated with higher overweight or obesity risk compared with the low screen time category. Medium (RR, 1.19; 95% CI, 1.06-1.35) and low (RR, 1.30; 95% CI, 1.11-1.51) step count categories were associated with higher overweight or obesity risk compared with the high step count category. Evidence of effect modification between screen time and step count was observed for BMI percentile. For instance, among adolescents with low screen use, medium step count was associated with a 1.55 higher BMI percentile, and low step count was associated with a 7.48 higher BMI percentile. However, among those with high screen use, step count categories did not significantly change the association with higher BMI percentile (low step count: 8.79 higher BMI percentile; medium step count: 8.76 higher BMI percentile; high step count: 8.26 higher BMI percentile). Conclusions and Relevance: In this cross-sectional study, a combination of low screen time and high step count was associated with lower BMI percentile in adolescents. These results suggest that high step count may not offset higher overweight or obesity risk for adolescents with high screen time, and low screen time may not offset higher overweight or obesity risk for adolescents with low step count. These findings addressed several research gaps identified by the Physical Activity Guidelines Advisory Committee Scientific Report and may be used to inform future screen time and physical activity guidance for adolescents.

The association between daily sedentary and active bout frequency with mortality risk in older men using accelerometry.

BACKGROUND: Time awake with advancing age is increasingly spent sedentary and has several negative health consequences. We examined associations between the frequency of daily sedentary and active bouts with all-cause mortality. METHODS: Data are from 2816 men in the Osteoporotic Fractures in Men (MrOS) Study (mean age ± SD: 79.1 ± 5.2 years) with free-living activity monitor (SenseWear® Pro3 Armband) data (5.1 ± 0.3 days worn >90%) at the Year 7 visit (2007-2009). Sedentary bout frequency was defined as the number of sedentary bouts per day lasting 5+ min to activity of any intensity. Active bout frequency was defined as the number of active bouts per day lasting 5+ min to sedentary behavior. Sleep time was excluded from the analysis. Deaths were centrally adjudicated using death certificates. Cox proportional hazard models were used to separately examine associations between quartiles of sedentary (Q1 referent, <13.6 bouts/day) or active (Q1 referent, <5 bouts/day) bout frequency with mortality. RESULTS: After 9.3 ± 3.8 years of follow-up, 1487 (52.8%) men died. Men averaged 16.8 ± 5.1 and 8.2 ± 4.2 sedentary and active bouts/day, respectively. After full covariate adjustment, each quartile reflecting more frequent sedentary bouts (Q4 vs. Q1 HR: 0.69, 95%CI: 0.58, 0.81, p-trend <0.001) was associated with lower mortality risk. Likewise, each quartile reflecting more frequent active bouts (Q4 vs. Q1 HR: 0.58, 95%CI: 0.49, 0.70, p-trend <0.001) was associated with lower mortality risk. Results for the sedentary bouts model remained significant after adjusting for total minutes per day in sedentary behavior (Q4 vs. Q1 HR: 0.63, 95%CI: 0.61, 0.86, p-trend = 0.001). The association between active bout frequency with mortality was attenuated after adjusting for total minutes per day active. CONCLUSIONS: Regardless of total time spent sedentary, reducing duration of sedentary bouts with more frequent and shorter bouts may be a simple and feasible method to delay mortality risk among community-dwelling older men.

Pre- and Early Peri-menopausal Physical Function and Risk of Cardiovascular Events: The Study of Women's Health Across the Nation.

OBJECTIVES: To determine whether physical function (PF) before menopause is related to cardiovascular disease (CVD) risk. METHODS: Participants were N = 2950 pre-/early peri-menopausal women (median age 46, (25th-75th percentile: 43-48 years). Physical function was assessed at baseline using the Physical Function subscale of the SF-36 and scores were trichotomized (no, some, or substantial limitations). Clinical CVD events were ascertained at annual/biennial clinical assessments through the 15th follow-up visit. Risk of CVD was determined with Cox proportional hazards models. Results: Women were followed for a median of 19.1 years, during which 220 women had a CVD event. In fully adjusted models, women with substantial limitations at baseline had higher CVD risk compared to women with no limitations (hazards ratio [HR] = 1.55, 95% confidence interval [CI]: 1.12-2.33). Discussion: Substantial PF limitations in pre- and early peri-menopausal women are associated with higher risk of clinical CVD events, consistent with literature in older adults.