Daily Physical Activity Patterns Research Articles

Exploring the association between daily distributional patterns of physical activity and cardiovascular mortality risk among older adults in NHANES 2003-2006

PurposeCardiovascular disease (CVD) is one of the leading causes of death worldwide. Physical activity (PA) has previously been shown to be a prominent risk factor for CVD mortality. Traditionally, measurements of PA have been self-reported and based on various summary metrics. However, recent advances in wearable technology provide continuously monitored and objectively measured physical activity data. This facilitates a more comprehensive interpretation of the implications of PA in the context of CVD mortality by considering its daily patterns and compositions. MethodsThis study utilized accelerometer data from the 2003–2006 National Health and Nutrition Examination Survey (NHANES) on 2816 older adults aged 50–85 and mortality data from the National Death Index (NDI) in December 2019. A novel partially functional distributional analysis method was used to quantify and understand the association between daily distributional patterns of physical activity and cardiovascular mortality risk through a multivariable functional Cox model. ResultsA higher mean intensity of daily PA during the day was associated with a reduced hazard of CVD mortality after adjusting for other higher order distributional summaries of PA and age, gender, race, body mass index (BMI), smoking and coronary heart disease (CHD). A higher daily variability of PA during afternoon was associated with a reduced hazard of CVD mortality, after adjusting for the other predictors, particularly on weekdays. The subjects with a lower variability of PA, despite having same mean PA throughout the day, could have a lower reserve of PA and hence could be at increased risk for CVD mortality. ConclusionsOur results demonstrate that not only the mean intensity of daily PA during daytime, but also the variability of PA during afternoon could be an important protective factor against the risk of CVD-mortality. Considering circadian rhythm of PA as well as its daily compositions can be useful for designing time-of-day and intensity-specific PA interventions to protect against the risk of CVD mortality.

Characterizing daily physical activity patterns with unsupervised learning via functional mixture models

Characterizing daily physical activity patterns with unsupervised learning via functional mixture models

Effects of physical activity patterns on myopia among children and adolescents: A latent class analysis.

The daily physical activity (PA) patterns of children and adolescents are intricate and ambiguous, with varying effects on myopia resulting from different combinations of PA. This study aims to scrutinize the spectrum of PA patterns among children and adolescents and assess their impact on myopia. Data sourced from the 2014 National Student Physical Fitness Survey (Tianjin segment) encompassed PA records and visual acuity measurements of participants. Latent Class Analysis and a generalized linear model were employed to investigate the relationship between PA categories and visual acuity across different educational stages. The study comprised 6465 primary and middle school students, among whom 50.13% were male. PA patterns were categorized into high (27.16%), medium (29.88%) and low visual acuity regulation groups (13.97%) and the nonmainstream group (28.99%). Following adjustments for sex, age, region and BMI, the medium visual acuity regulation group exhibited a lower risk of myopia (OR = 0.617, 95% CI = 0.424-0.897, p = 0.012; OR = 0.654, 95% CI = 0.438-0.976, p = 0.038) compared to the nonmainstream group among junior and senior middle school students. The efficacy of diverse PA patterns in mitigating myopia risk varies across educational stages and is influenced by sex-specific factors. It is imperative to advance myopia management strategies by emphasizing tailored PA interventions, discerning between PA patterns and delivering timely guidance and interventions tailored to distinct educational stages and sexes.

Morning physical activity may be more beneficial for blood lipids than afternoon physical activity in older adults: a cross-sectional study

BackgroundThe effect of differences in daily physical activity patterns on blood lipids has not been determined. This study examines the effects of the differences in free-living daily physical activity patterns (amount and intensity) on blood lipid levels in older adults.MethodsThis cross-sectional study included 51 older participants (71.8 ± 0.6 years, men = 8, women = 43). A triaxial accelerometer was used to assess physical activity patterns. The time from awakening to bedtime for each participant was used for group classification based on the amount (number of steps) and intensity (moderate-to-vigorous physical activity, MVPA) of physical activity. The morning step group (M Step) was defined as those who took more steps in the morning, and the afternoon step group (A Step) was defined as those who took more steps in the afternoon. The same method was used for MVPA (morning MVPA: M MVPA; afternoon MVPA: A MVPA). Blood samples were collected at the start of the study to determine blood lipid levels.ResultsNumber of steps taken showed a trend toward lower low-density lipoprotein cholesterol (LDL-C) levels in the M Step group compared with the A Step group. The LDL/high-density lipoprotein (HDL) ratio was significantly lower in the M Step group than the A Step group (p < 0.05). The M MVPA group also had higher HDL-C levels and significantly lower LDL/HDL ratios than the A MVPA group (p < 0.05).ConclusionsThese results suggest that compared with afternoon physical activity, daily morning physical activity (amount and intensity) is more effective in improving blood lipid levels.

Effects of multidisciplinary inpatient rehabilitation on everyday life physical activity and gait in patients with multiple sclerosis

BackgroundMultiple sclerosis is a progressive neurological disease that affects the central nervous system, resulting in various symptoms. Among these, impaired mobility and fatigue stand out as the most prevalent. The progressive worsening of symptoms adversely alters quality of life, social interactions and participation in activities of daily living. The main objective of this study is to bring new insights into the impact of a multidisciplinary inpatient rehabilitation on supervised walking tests, physical activity (PA) behavior and everyday gait patterns.MethodsA total of 52 patients, diagnosed with multiple sclerosis, were evaluated before and after 3 weeks of inpatient rehabilitation. Each measurement period consisted of clinical assessments and 7 days home monitoring using foot-mounted sensors. In addition, we considered two subgroups based on the Expanded Disability Status Scale (EDSS) scores: ‘mild’ (EDSS < 5) and ‘severe’ (EDSS ≥ 5) disability levels.ResultsSignificant improvements in fatigue, quality of life and perceived mobility were reported. In addition, walking capacity, as assessed by the 10-m walking test, two-minute walk test and timed-up-and-go test, improved significantly after rehabilitation. Regarding the home assessment, mildly disabled patients significantly increased their locomotion per day and complexity of daily PA pattern after rehabilitation, while severely disabled patients did not significantly change. There were distinct and significant differences in gait metrics (i.e., gait speed, stride length, cadence) between mildly and severely disabled patients, but the statistical models did not show a significant overall rehabilitation effect on these gait metrics.ConclusionInpatient rehabilitation showed beneficial effects on self-reported mobility, self-rated health questionnaires, and walking capacity in both mildly and severely disabled patients. However, these improvements do not necessarily translate to home performance in severely disabled patients, or only marginally in mildly disabled patients. Motivational and behavioral factors should also be considered and incorporated into treatment strategies.

Investigating young children’s physical activity through time and place

BackgroundPrevious research indicates the start of primary school (4-5-year-old) as an essential period for the development of children’s physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider variety of environmental- and social contexts and therefore their PA is influenced by more diverse factors. However, in order to understand children’s daily PA patterns and identify relevant opportunities for PA promotion, it is important to further unravel in which (social) contexts throughout the day, PA of young children takes place.MethodsWe included a cross-national sample of 21 primary schools from the Startvaardig study. In total, 248 children provided valid accelerometer and global positioning (GPS) data. Geospatial analyses were conducted to quantify PA in (social) environments based on their school and home. Transport-related PA was evaluated using GPS speed-algorithms. PA was analysed at different environments, time-periods and for week- and weekend days separately.ResultsChildren accumulated an average of 60 min of moderate-to-vigorous PA (MVPA), both during week- and weekend days. Schools contributed to approximately half of daily MVPA during weekdays. During weekends, environments within 100 m from home were important, as well as locations outside the home-school neighbourhood. Pedestrian trips contributed to almost half of the daily MVPA.ConclusionsWe identified several social contexts relevant for children’s daily MVPA. Schools have the potential to significantly contribute to young children’s PA patterns and are therefore encouraged to systematically evaluate and implement parts of the school-system that stimulate PA and potentially also learning processes. Pedestrian trips also have substantial contribution to daily MVPA of young children, which highlights the importance of daily active transport in school- and parental routines.

Differences in daily physical activity by Alzheimer's risk markers among older adults.

Daily physical activity patterns differ by Alzheimer's disease (AD) status and might signal cognitive risk. It is critical to understand whether patterns are disrupted early in the AD pathological process. Yet, whether established AD risk markers (β-amyloid (Aβ) or APOE-ε4) are associated with differences in objectively measured activity patterns among cognitively unimpaired older adults is unclear. Wrist accelerometry, brain Aβ (+/-), and APOE-ε4 genotype were collected in 106 (Aβ) and 472 (APOE-ε4) participants [mean age 76 (SD: 8.5) or 75 (SD: 9.2) years, 60% or 58% women] in the BLSA. Adjusted linear and function-on-scalar regression models examined whether Aβ or APOE-ε4 status was cross-sectionally associated with activity patterns (amount, variability, or fragmentation) overall and by time-of-day, respectively. Differences in activity patterns by combinations of Aβ and APOE-ε4 status were descriptively examined (n=105). There were no differences in any activity pattern by Aβ or APOE-ε4 status overall. Aβ+ was associated with lower total amount and lower within-day variability of physical activity overnight and early evening, and APOE-ε4 carriers had higher total amount of activity in the evening and lower within-day variability of activity in the morning. Diurnal curves of activity were blunted among those with Aβ+ regardless of APOE-ε4 status, but only when including older adults with MCI/dementia. Aβ+ in cognitively unimpaired older adults might manifest as lower amount and variability of daily physical activity, particularly during overnight/evening hours. Future research is needed to examine changes in activity patterns in larger samples and by other AD biomarkers.

Cross-sectional associations between patterns and composition of upright and stepping events with physical function: insights from The Maastricht Study

IntroductionAge-related declines in physical functioning have significant implications for health in later life. Physical activity (PA) volume is associated with physical function, but the importance of the pattern in which PA is accumulated is unclear. This study investigates associations between accelerometer-determined daily PA patterns, including composition and temporal distribution (burstiness) of upright and stepping events, with physical function.MethodsData was from participants who wore an activPAL3 accelerometer as part of The Maastricht Study. Exposures included a suite of metrics describing the composition and the temporal distribution (burstiness) of upright and sedentary behaviour. Physical function outcomes included the six-minute walk test (6MWT), timed chair-stand test (TCST), grip strength (GS), and SF-36 physical functioning sub-scale (SF-36pf). Multivariable linear regression models were used to assess associations, adjusting for covariates including overall PA volume (daily step count).ResultsParticipants(n = 6085) had 6 or 7 days of valid data. Upright and stepping event metrics were associated with physical function outcomes, even after adjusting PA volume. Higher sedentary burstiness was associated with better function (6MWT, TCST, and SF-36pf), as was duration and step volume of stepping events (6MWT, TCST, GS, and SF-36pf), step-weighted cadence (6MWT, TCST, and SF-36pf). Number of stepping events was associated with poorer function (6MWT, GS, and SF-36pf), as was upright event burstiness (SF-36pf). Associations varied according to sex.ConclusionOur study reveals that diverse patterns of physical activity accumulation exhibit distinct associations with various measures of physical function, irrespective of the overall volume. Subsequent investigations should employ longitudinal and experimental studies to examine how changing patterns of physical activity may affect physical function, and other health outcomes.

Exploring the Application of Force Intelligent Wearable Devices in Quantitative Management of Daily Physical Activity

This study looks into how force-intelligent wearable devices can be used to quantitatively manage daily physical activity levels. The study intends to investigate the effectiveness of these devices in measuring various physical activity metrics such as step count, distance walked, calories burned, and exercise intensity. A thorough methodology is used, which includes device selection, participant recruiting, data collecting, and analysis methods. Participants wear the selected wearable devices continuously for a set amount of time, enabling longitudinal tracking of daily physical activity patterns. The acquired data is evaluated using statistical analysis approaches such as descriptive statistics, correlation analysis, and cross-demographic group comparisons. The findings provide insights into participants' activity levels, device accuracy, user engagement, and relationships between various physical activity measures. The study's findings help to better understand the usefulness of force-intelligent wearable devices in promoting physical activity and improving health outcomes. Further research in this area could help to inform programs aimed at increasing physical activity and general well-being.

Patterns of Physical Activity of Adolescents With ADHD in the School Context: A Cross-Sectional Study for Clinical Practice

Objectives: To describe the daily Physical Activity (PA) patterns of adolescents with Attention-deficit/hyperactivity disorder (ADHD), to analyze the differences in terms of PA patterns between adolescents with ADHD and those without ADHD, and to study the factors associated with achieving the daily PA recommendations. Methods: The sample was composed of 778 adolescents who provided complete information on their PA patterns through the Physical Activity Questionnaire for Adolescents (PAQ-A). Of these, 97 had ADHD according to DSM-5 criteria. Results: The results show that being a girl or being of foreign origin and having ADHD have an impact on the achievement of the recommended amount of daily PA. Conclusions: When promoting PA in adolescents with ADHD within the school environment, it is necessary to consider different domains and specific contexts of a school day, paying special attention to girls and adolescents with ADHD of immigrant origin.

310 Digital Physical Activity Phenotype before Cerebrovascular Disease: A Retrospective Study of Accelerometer-Measured Behavior in UK Biobank Observational Cohort

OBJECTIVES/GOALS: To investigate digital behavior patterns before cerebrovascular disease (CeVD), we compared accelerometer-measured physical activity (PA) phenotypes of future CeVD patients versus controls in UK Biobank. METHODS/STUDY POPULATION: Accelerometer data from 76,525 eligible participants monitored for 7-days (Jan. 2013-Dec. 2015) was classified into four categories: sedentary, light PA (LPA), moderate-to-vigorous PA (MVPA), and sleep. Covariables and diagnoses were defined using baseline data and patient records. Daily PA patterns associated with incident CeVD were compared to controls using negative binomial regression models. RESULTS/ANTICIPATED RESULTS: Adult participants with future CeVD (n = 2,163) spent 4.4% less time in MVPA (Incident Rate-Ratio (IRR) 0.956; 95% CI = 0.923-0.992; p = 0.016) compared to controls. During 0:00-5:59h (midnight to 5:59AM), future CeVD patients were less likely to sleep (IRR = 0.985; 95% CI = 0.977-0.992; p &lt;0.001) but more likely to be sedentary (IRR = 1.189; 95% CI = 1.098-1.290; p &lt;0.001) or in LPA (IRR = 1.108; 95% CI = 1.015-1.211; p &lt;0.001). In subgroup analyses, decreased MVPA was observed in current/former smokers (IRR = 0.887; 95% CI = 0.819-0.963), males (IRR = 0.931; 95% CI = 0.870-0.997), and the unemployed/retired (IRR = 0.923; 95% CI = 0.856-0.998), an effect more pronounced in depressed patients (p for interaction = 0.044) and prolonged (&gt; 2 hr/day) screen users (p for interaction = 0.018). DISCUSSION/SIGNIFICANCE: The digital phenotype of PA prior to CeVD is characterized by less sleep during 0:00-5:59h and less daily MVPA, demonstrating the utility of accelerometer data in identifying candidates for preventative intervention.

Abstract P217: Directionality of Associations Between Daily Physical Activity and Cognition Among Older Adults in the Baltimore Longitudinal Study of Aging

Physical activity is a modifiable risk factor for dementia. Associations between physical activity and cognition are likely bidirectional, as cognitive functions are required to initiate and perform activities. Understanding the directionality of these associations has potential implications for both dementia prevention and physical activity engagement. Yet, the directionality between cognitive function and free-living physical activity patterns is unclear. This study included 237 cognitively unimpaired older adults in the BLSA with cognitive test performance and ≥ 3 valid days of wrist accelerometry measured at 2 visits over an average of 1.8 (0.9-4.0) years. Cognitive domain factor scores were derived using confirmatory factor analysis. Accelerometry data were used to calculate daily physical activity patterns: 1) total activity counts (TAC), 2) time spent active, 3) time spent non-active, 4) active-to-sedentary-transition probability (ASTP), 5) mean active bout length, 6) sedentary-to-active transition probability (SATP), 7) mean non-active bout length. Bivariate latent change score models estimated directionality of associations between changes in cognitive factor scores and changes in daily physical activity patterns. Models were adjusted for age, sex, race, education, and number of comorbidities. Participants were on average 77 (60-96) years, 48% women, and 22% Black. After covariate adjustment, one SD higher in baseline TAC was associated with less memory decline (estimate = 0.089, SE = 0.045). One SD higher in baseline time spent non-active was associated with greater declines in language (estimate = -0.068, SE = 0.035), visuospatial processing (estimate = -0.079 SE = 0.034), and global cognition (estimate = -0.058, SE = 0.024). One SD higher in baseline ASTP was associated with greater declines in memory (estimate = -0.114, SE = 0.047) and visuospatial processing (estimate = -0.074, SE = 0.034), whereas mean active bout length was associated with less decline in these domains (memory: estimate = 0.121, SE = 0.046; visuospatial processing: estimate = 0.081, SE = 0.033). There were no associations with time spent active, SATP, or mean non-active bout length and changes in any cognitive factor score. Cognitive factor scores were not associated with changes in any activity pattern. Patterns relating to amount of daily activity, time spent sedentary, and probability of transitioning from active-to-sedentary states were primarily associated with changes in memory and visuospatial processing. This suggests increasing free-living movement or decreasing sedentary behavior might be related to short-term changes in cognition among older adults. Future studies are needed to determine causality of these associations and to evaluate directionality over longer periods of time.

NEIGHBORHOOD QUALITY AND WEEKLY PATTERNS OF PHYSICAL ACTIVITY AMONG BLACK AND WHITE ADULTS

Abstract Engaging in regular moderate to vigorous physical activity across the week is recommended for maintaining health. This analysis examined whether objective and subjective neighborhood quality was associated with different patterns of weekly physical activity across the week among middle and older Black and white adults. We leveraged data from the National Study of Daily Experiences (NSDE), in which 833 Black and white American adults (Mage = 62.65; n Black = 167) reported their daily moderate to vigorous physical activity across eight consecutive days. The objective and subjective measures of neighborhood quality were the area deprivation index (ADI) and personal belief in the neighborhood, respectively. Hypotheses were tested using the latent class analysis (LCA) framework. Weekly patterns of daily physical activity were classified into four different groups: Active Every Day (group size = 35.75%), Active on Weekdays (26.63%), Active on the Weekend (11.76%), and Less Active (15.85%). Lower ADI rankings, but not personal beliefs about one’s neighborhood, were associated with a higher probability of being in the three more active relative to the Less Active group, an association stronger among white adults. Finally, the three more active groups showed higher self-rated physical health than the Less Active group. Within-race analyses showed that this association was only evident among white adults. Neighborhood deprivation is an important structural context that may strongly limit adults’ engagement in daily physical health.

PHYSICAL ACTIVITY AND DEMENTIA IN THE NATIONAL HEALTH AND AGING TRENDS STUDY (NHATS)

Abstract Individuals living with dementia exhibit disrupted sleep/wake rhythms; however, whether daily physical activity volume and patterns are worse among those living with dementia is not well established. We examined the cross-sectional association between dementia classification and accelerometry-derived patterns of daily physical activity in NHATS. Wrist-worn accelerometry was collected using the Actigraph Centrepoint Insight Watch in a subset of Round 11 (2021) participants. Dementia status, including possible and probable dementia, was determined using the NHATS dementia algorithm. We characterized daily physical activity patterns using: most active 10-hours/day (M10), time of M10, least active 5-hours/day (L5), time of L5, relative amplitude (RA), intra-daily variability (IV), inter-daily stability (IS), and activity fragmentation using the active-to-sedentary transition probability (ASTP). We used separate linear regression models to study the association between dementia and each actigraphy feature, adjusting for relevant demographic features including age, gender, race, BMI, and education. 721 participants had ≥3 days of valid accelerometry data, dementia status, and complete covariate data (40% aged ≥80 years, 54% women). Compared to cognitively normal participants, those living with dementia averaged fewer activity counts/day (beta: -382K counts/day p&amp;lt;0.0001), lower M10 (beta: -261K counts, p&amp;lt;0.0001), lower IS (beta: -0.04; p= 0.0066), and higher ASTP (beta: 7.1%; p&amp;lt;0.0001). Participants with and without dementia did not differ in terms of IV, L5, or RA (p&amp;gt;0.05 for all). These results suggest important differences in volume and patterns of daily movement by dementia status. Future studies should investigate whether similar differences exist in earlier stages of cognitive impairment to enhance preventative efforts.

Temporal Patterns of Diet and Physical Activity and of Diet Alone Have More Numerous Relationships With Health and Disease Status Indicators Compared to Temporal Patterns of Physical Activity Alone.

Daily temporal patterns of energy intake (temporal dietary patterns [TDPs]) and physical activity (temporal physical activity patterns [TPAPs]) have been independently and jointly (temporal dietary and physical activity patterns [TDPAPs]) associated with health and disease status indicators. The aim of this study was to compare the number and strength of association between clusters of daily TDPs, TPAPs, and TDPAPs and multiple health and disease status indicators. This cross-sectional study used 1 reliable weekday dietary recall and 1 random weekday of accelerometer data to partition to create clusters of participants representing the 3 temporal patterns. Four clusters were created via kernel-k means clustering algorithm of the same constrained dynamic time warping distance computed over the time series for each temporal pattern. From the National Health and Nutrition Examination Survey (2003-2006), 1,836 US adults aged 20 through 65 years who were not pregnant and had valid diet, physical activity, sociodemographic, anthropometric, questionnaire, and health and disease status indicator data were included. Health status indicators used as outcome measures were body mass index, waist circumference, fasting plasma glucose, hemoglobin A1c, triglycerides, high-density lipoprotein cholesterol, total cholesterol, and systolic and diastolic blood pressure; disease status indicators included obesity, type 2 diabetes mellitus, and metabolic syndrome. Multivariate regression models determined associations between the clusters representing each pattern and health and disease status indicators, controlling for confounders and adjusting for multiple comparisons. The number of significant differences among clusters and adjusted R2 and Akaike information criterion compared the strength of associations between clusters of patterns and continuous and categorical health and disease status indicators. TDPAPs showed 21 significant associations with health and disease status indicators, including body mass index, waist circumference, obesity, and type 2 diabetes; TDPs showed 19 significant associations; and TPAPs showed 8 significant associations. TDPAPs and TDPs had stronger and more numerous associations with health and disease status indicators compared with TPAPs. Patterns representing the integration of daily dietary habits hold promise for early detection of obesity.

Functional proportional hazards mixture cure model with applications in cancer mortality in NHANES and post ICU recovery.

We develop a functional proportional hazards mixture cure model with scalar and functional covariates measured at the baseline. The mixture cure model, useful in studying populations with a cure fraction of a particular event of interest is extended to functional data. We employ the expectation-maximization algorithm and develop a semiparametric penalized spline-based approach to estimate the dynamic functional coefficients of the incidence and the latency part. The proposed method is computationally efficient and simultaneously incorporates smoothness in the estimated functional coefficients via roughness penalty. Simulation studies illustrate a satisfactory performance of the proposed method in accurately estimating the model parameters and the baseline survival function. Finally, the clinical potential of the model is demonstrated in two real data examples that incorporate rich high-dimensional biomedical signals as functional covariates measured at the baseline and constitute novel domains to apply cure survival models in contemporary medical situations. In particular, we analyze (i) minute-by-minute physical activity data from the National Health And Nutrition Examination Survey 2003-2006 to study the association between diurnal patterns of physical activity at baseline and all cancer mortality through 2019 while adjusting for other biological factors; (ii) the impact of daily functional measures of disease severity collected in the intensive care unit on post intensive care unit recovery and mortality event. Our findings provide novel epidemiological insights into the association between daily patterns of physical activity and cancer mortality. Software implementation and illustration of the proposed estimation method are provided in R.

Identifying the sociodemographic and work-related factors related to workers’ daily physical activity using a decision tree approach

BackgroundThe social and behavioural factors related to physical activity among adults are well known. Despite the overlapping nature of these factors, few studies have examined how multiple predictors of physical activity interact. This study aimed to identify the relative importance of multiple interacting sociodemographic and work-related factors associated with the daily physical activity patterns of a population-based sample of workers.MethodsSociodemographic, work, screen time, and health variables were obtained from five, repeated cross-sectional cohorts of workers from the Canadian Health Measures Survey (2007 to 2017). Classification and Regression Tree (CART) modelling was used to identify the discriminators associated with six daily physical activity patterns. The performance of the CART approach was compared to a stepwise multinomial logistic regression model.ResultsAmong the 8,909 workers analysed, the most important CART discriminators of daily physical activity patterns were age, job skill, and physical strength requirements of the job. Other important factors included participants’ sex, educational attainment, fruit/vegetable intake, industry, work hours, marital status, having a child living at home, computer time, and household income. The CART tree had moderate classification accuracy and performed marginally better than the stepwise multinomial logistic regression model.ConclusionAge and work-related factors–particularly job skill, and physical strength requirements at work–appeared as the most important factors related to physical activity attainment, and differed based on sex, work hours, and industry. Delineating the hierarchy of factors associated with daily physical activity may assist in targeting preventive strategies aimed at promoting physical activity in workers.

Gender difference in the effects of chronic diseases on daily physical activity patterns in older adults: analysis of objectively measured physical activity in NHATS 2021

PurposeMany chronic diseases have detrimental impact on the physical activity (PA) patterns of older adults. Often such diseases have different degrees of severity in males and females. Quantifying this gender difference would not only enhance our understanding of diseases but would also help design individual-specific PA interventions, thereby improving health outcomes for both genders. MethodsPA data for 747 participants from round 11 (2021) of the National Health and Aging Trends Study were analyzed. Multilevel functional regression models were used to study gender difference in the effects of chronic diseases on daily PA patterns while adjusting for confounders. ResultsFemales with dementia (or Alzheimer’s disease), hypertension, heart and lung disease had lower PA at different times of day compared to females without these diseases, whereas males with and without these diseases had comparable daily PA. Males with diabetes had higher midnight PA and lower noon PA compared to males without diabetes, while females’ PA with and without diabetes were similar. ConclusionsOur analysis demonstrates that although for most diseases, the daily PA patterns of individuals with the disease are negatively altered compared to healthy individuals, the extent of decline varies by gender and time of day. Designing personalized physical activity interventions considering gender and diurnal PA pattern can potentially improve quality of life across both genders.

The Association Between Ankle-Brachial Index and Daily Patterns of Physical Activity: Results From the Hispanic Community Health Study/Study of Latinos.

Peripheral artery disease (PAD) is associated with lower physical activity but less is known about its association with daily patterns of activity. We examined the cross-sectional association between ankle-brachial index (ABI) and objectively measured patterns of physical activity among Hispanic/Latino adults. We analyzed data from 7 688 participants (aged 45-74 years) in the Hispanic Community Health Study/Study of Latinos. ABI was categorized as low (≤0.90, indicating PAD), borderline low (0.91-0.99), normal (1.00-1.40), and high (>1.40, indicating incompressible ankle arteries). Daily physical activity metrics derived from accelerometer data included: log of total activity counts (LTAC), total log-transformed activity counts (TLAC), and active-to-sedentary transition probability (ASTP). Average differences between ABI categories in physical activity, overall and by 4-hour time-of-day intervals, were assessed using linear regression and mixed-effects models, respectively. In Hispanic/Latino adults, 5.3% and 2.6% had low and high ABIs, respectively. After adjustment, having a low compared to a normal ABI was associated with lower volume (LTAC = -0.13, p < .01; TLAC = -74.4, p = .04) and more fragmented physical activity (ASTP = 1.22%, p < .01). Having a low ABI was linked with more fragmented physical activity after 12 pm (p < .01). Having a high ABI was associated with lower volumes of activity (TLAC = -132.0, p = .03). Having a low or high ABI is associated with lower and more fragmented physical activity in Hispanic/Latino adults. In adults with low ABI, physical activity is more fragmented in the afternoon to evening. Longitudinal research is warranted to expand these findings to guide targeted interventions for PAD or incompressible ankle arteries.

Daily accelerometer-measured physical activity patterns and associations with cardiometabolic health among Canadian working adults.

Previous studies examining the cardiometabolic risks associated with physical activity (PA) in workers have predominantly used self-reported measures. Little is known about workers' distinct daily PA patterns and whether these are linked with cardiometabolic risks. This study examined associations between patterns of workers' accelerometer-measured daily PA and four markers of cardiometabolic health. Working adults (N=8,229; 47% women; average age: 42 years; standard deviation = 0.3) were sampled from the Canadian Health Measures Survey (five cycles: 2007 to 2017). Accelerometer devices measured daily PA, and hierarchical cluster analysis identified distinct activity patterns. Multiple linear regression analyses examined associations between activity patterns and cardiometabolic risk markers (waist circumference, systolic and diastolic blood pressure, and non-high-density lipoprotein [HDL] cholesterol). Workers were classified into six distinct activity patterns. On average, compared with workers classified in the "lowest activity" pattern, workers with the "moderate consistent activity," "fluctuating moderate activity," "high daytime activity" and "highest activity" patterns were associated with lower waist circumferences; workers with the "fluctuating moderate activity" and "highest activity" patterns were associated with lower systolic blood pressure; the "moderate evening activity" pattern was associated with lower diastolic blood pressure; and workers with the "fluctuating moderate activity," "high daytime activity" and "highest activity" patterns were associated with lower non-HDL cholesterol. "High daytime activity" was associated with lower waist circumference in women, compared with men, and the "moderate consistent activity" and "fluctuating moderate activity" patterns were associated with lower diastolic blood pressure in younger workers (40 years or younger). Workers with high daily PA levels tended to have the most optimal cardiometabolic health. Some evidence suggested that there are benefits to moderate levels of PA, particularly for lowering waist circumference and non-HDL cholesterol. Findings may assist in identifying workers for PA initiatives to promote cardiometabolic health benefits.