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Background: Before pregnancy is recognized, ovulation, fertilization, and implantation must all occur. Physical activity and sedentary behavior may impact pregnancy success by altering each or all of these processes. The aim of this review was to review the association between physical activity and sedentary behavior with spontaneous female and male fertility. Method: PubMed/MEDLINE, Web of Science, CINAHL, SPORTDiscus, and Embase were searched from inception to August 9, 2021. Eligible studies included randomized controlled trials or observational studies, published in English, describing an association between physical activity or sedentary behavior (exposures) and spontaneous fertility (outcome) among women or men. Results: Thirty-four studies from 31 unique populations were included in this review (12 cross-sectional studies, 10 cohort studies, 6 case–control studies, 5 randomized controlled trials, and one case–cohort study). Of the 25 studies among women, the majority identified mixed results (n = 11) or no association (n = 9) between physical activity and female fertility. Seven studies reported on female fertility and sedentary behavior, and 2 found sedentary behavior was associated with decreased female fertility. Of the 11 studies among men, most of the studies (n = 6) found that physical activity was associated with increased male fertility. Two of the studies reported on male fertility and sedentary behavior, and neither identified an association. Conclusions: The association between spontaneous fertility and physical activity in both men and women remains unclear, and the association with sedentary behavior remains largely unexplored. [ABSTRACT FROM AUTHOR]

Background: Saudi Arabia is experiencing rapid development of the built environment and implementing policy changes to promote physical activity (PA) and reduce sedentary behavior (SB) among its population. In light of these developments, this scoping review systematically summarized population levels of PA/SB in Saudi Arabia. Methods: The authors searched 6 databases on December 13, 2021, for articles published in English or Arabic from 2018 to the search date. Studies using population-based sampling in Saudi Arabia and measuring PA/SB were included. Results: Of the 1272 records found, 797 were screened, and 19 studies (9 on children/adolescents age 6–19 y and 10 on adults age 15–75 y) were included. All studies were cross-sectional in design, and 18 studies collected data at only one point in time, ranging from 2009 to 2020. A total of 18 studies relied on self-reporting to assess PA/SB using a variety of questionnaires. Among children/adolescents, approximately 80% to 90% did not attain at least 60 minutes per day of moderate to vigorous PA and 50% to 80% engaged in ≥2 hours per day of screen time or SB. Among adults, approximately 50% to 95% had low or insufficient PA (eg, less than meeting PA guidelines) and about half had a sitting time of ≥5 hours per day. Population-based studies were not found among children <10 years and adults >75 years. Conclusions: A high proportion of participants in the reviewed studies did not meet PA recommendations and spent excessive time in SB. Ongoing surveillance efforts for all ages may help identify target populations for interventions and prioritize the national strategy on PA/SB in Saudi Arabia. [ABSTRACT FROM AUTHOR]

BackgroundThe relationship between light intensity physical activity (PA), which is common in older adults, and cardiovascular disease (CVD) risk factors is unclear. This study examined associations of accelerometer-measured PA intensity with CVD risk factors in older women of different race-ethnicities.Methods and resultsCross-sectional analyses were conducted in 4832 women (mean age 78.9 years; 52.5% white, 30.5% black, 17.1% Hispanic) who were without known CVD and wore triaxial accelerometers a minimum of 4 of 7 days with ≥10 hours/d awake wear-time. Vector magnitude counts per 15-s epoch were used to define time spent in low light (19-225 counts/15 s), high light (226-518), and moderate-to-vigorous; ≥519) intensity PA. Fasting CVD biomarkers, resting blood pressure, waist girth, body mass index, and 10-year predicted CVD risk (Reynolds Risk Score) were measured. After adjusting for age, wear time, race-ethnicity, and potential confounders, each PA measure was favorably associated with mean high-density lipoprotein, triglyceride, glucose, C-reactive protein, body mass index, waist girth, and Reynolds Risk Score (P

Increasing physical activity (PA) at the population level requires appropriately targeting intervention development. Identifying the locations in which participants with various sociodemographic, body weight, and geographic characteristics tend to engage in varying intensities of PA as well as locations these populations underutilize for PA may facilitate this process. A visual location-coding protocol was developed and implemented in Google Fusion Tables and Maps using data from participants (N = 223, age 18-85) in five states. Participants concurrently wore ActiGraph GT1M accelerometers and Qstarz BT-Q1000X GPS units for 3 weeks to identify locations of moderate-to-vigorous (MVPA) or vigorous (VPA) bouts. Cochran-Mantel-Haenzel general association tests examined usage differences by participant characteristics (sex, age, race/ethnicity, education, body mass index (BMI), and recruitment city). Homes and roads encompassed >40% of bout-based PA minutes regardless of PA intensity. Fitness facilities and schools were important for VPA (19 and 12% of bout minutes). Parks were used for 13% of MVPA bout minutes but only 4% of VPA bout minutes. Hispanics, those without a college degree, and overweight/obese participants frequently completed MVPA bouts at home. Older adults often used roads for MVPA bouts. Hispanics, those with ≤high school education, and healthy/overweight participants frequently had MVPA bouts in parks. Applying a new location-coding protocol in a diverse population showed that adult PA locations varied by PA intensity, sociodemographic characteristics, BMI, and geographic location. Although homes, roads, and parks remain important locations for demographically targeted PA interventions, observed usage patterns by participant characteristics may facilitate development of more appropriately targeted interventions.

Using data from the Multi-Ethnic Study of Atherosclerosis (MESA), we evaluated associations of neighborhood crime and safety with changes in adiposity (body mass index (BMI) and waist circumference). MESA is a longitudinal study of cardiovascular disease among adults aged 45-84 years at baseline in 2000-2002, from 6 US sites, with follow-up for MESA participants until 2012. Data for this study were limited to Chicago, Illinois, participants in the MESA Neighborhood Ancillary Study, for whom police-recorded crime data were available, and who had complete baseline data (n = 673). We estimated associations of individual-level safety, aggregated neighborhood-level safety, and police-recorded crime with baseline levels and trajectories of BMI and waist circumference over time using linear mixed modeling with random effects. We also estimated how changes in these factors related to changes in BMI and waist circumference using econometric fixed-effects models. At baseline, greater individual-level safety was associated with more adiposity. Increasing individual- and neighborhood-level safety over time were associated with decreasing BMI over the 10-year period, with a more pronounced effect observed in women for individual-level safety and men for neighborhood-level safety. Police-recorded crime was not associated with adiposity. Neighborhood-level safety likely influences adiposity change and subsequent cardiovascular risk in multiethnic populations.

IntroductionDetermining locations of physical activity (PA) is important for surveillance and intervention development, yet recommendations for using location recording tools like global positioning system (GPS) units are lacking. Specifically, no recommendation exists for the number of days study participants should wear a GPS to reliably estimate PA time spent in locations.MethodsThis study used data from participants (N = 224, age = 18-85 yr) in five states who concurrently wore an ActiGraph GT1M accelerometer and a Qstarz BT-Q1000X GPS for three consecutive weeks to construct monitoring day recommendations through variance partitioning methods. PA bouts ≥10 min were constructed from accelerometer counts, and the location of GPS points was determined using a hand-coding protocol.ResultsMonitoring day recommendations varied by the type of location (e.g., participant homes vs parks) and the intensity of PA bouts considered (low and medium cut point moderate to vigorous PA [MVPA] bouts or high cut point vigorous PA [VPA] bouts). In general, minutes of all PA intensities spent in a given location could be measured with ≥80% reliability using 1-3 d of GPS monitoring for fitness facilities, schools, and footpaths. MVPA bout minutes in parks and roads required longer monitoring periods of 5-12 d. PA in homes and commercial areas required >19 d of monitoring.ConclusionsTwelve days of monitoring was found to reliably estimate minutes in both low and medium threshold MVPA as well as VPA bouts for many important built environment locations that can be targeted to increase PA at the population level. Minutes of PA in the home environment and commercial locations may be best assessed through other means given the lengthy estimated monitoring time required.

Residential buffers are frequently used to assess built environment characteristics relevant to physical activity (PA), yet little is known about how well they represent the spatial areas in which individuals undertake PA. We used System for Observing Play and Recreation in Communities data for 217 adults from five US states who wore an accelerometer and a GPS for three weeks to create newly defined PA-specific activity spaces. These PA spaces were based on PA occurring in bouts of ≥10min and were defined as 1) the single minimum convex polygon (MCP) containing all of a participant's PA bout minutes and 2) the combination of many MCPs constructed using each PA bout independently. Participants spent a large proportion of their PA bout time outside of 0.5, 1, and 5 mile residential buffers, and these residential buffers were a poor approximation of the spatial areas in which PA bouts occurred. The newly proposed GPS-based PA spaces can be used in future studies in place of the more general concept of activity space to better approximate built environments experienced during PA.

Background: Patterns of physical activity and sedentary behavior among postmenopausal women are not well characterized. Objectives: To describe the patterns of accelerometer-assessed physical activity and sedentary behavior among postmenopausal women. Design: Cross-sectional study. Methods: Women 63–97 years (n = 6126) wore an ActiGraph GT3X + accelerometer on their hip for 1 week. Latent class analysis was used to classify women by patterns of percent of wake time in physical activity and sedentary behavior over the week. Results: On average, participants spent two-thirds of their day in sedentary behavior (62.3%), 21.1% in light low, 11.0% in light high, and 5.6% in moderate-to-vigorous physical activity. Five classes emerged for each single-component model for sedentary behavior and light low, light high, and moderate-to-vigorous physical activity. Six classes emerged for the multi-component model that simultaneously considered the four behaviors together. Conclusion: Unique profiles were identified in both single- and multi-component models that can provide new insights into habitual patterns of physical activity and sedentary behavior among postmenopausal women. Implications: The multi-component approach can contribute to refining public health guidelines that integrate recommendations for both enhancing age-appropriate physical activity levels and reducing time spent in sedentary behavior. [ABSTRACT FROM AUTHOR]

BackgroundFew studies have comprehensively evaluated the effectiveness of multi-faceted interventions intended to improve pedestrian safety. "Watch for Me NC" is a multi-faceted, community-based pedestrian safety program that includes widespread media and public engagement in combination with enhanced law enforcement activities (i.e., police outreach and targeted pedestrian safety operations conducted at marked crosswalks) and low-cost engineering improvements at selected crossings. The purpose of this study was to estimate the effect of the law enforcement and engineering improvement components of the program on motor vehicle driver behavior, specifically in terms of increased driver yielding to pedestrians in marked crosswalks.MethodsThe study used a pre-post design with a control group, comparing crossing locations receiving enforcement and low-cost engineering treatments (enhanced locations) with locations that did not (standard locations) to examine changes in driver yielding over a 6-month period from 2013 to 2014. A total of 24,941 drivers were observed in 11,817 attempted crossing events at 16 crosswalks in five municipalities that were participating in the program. Observations of real pedestrians attempting to use the crosswalks ("naturalistic" crossing) were supplemented by observations of trained research staff attempting the same crossings following an established protocol ("staged" crossings). Generalized estimating equations (GEE) were used to model driver yielding rates, accounting for repeated observations at the crossing locations and controlling other factors that affect driver behavior in yielding to pedestrians in marked crosswalks.ResultsAt crossings that did not receive enhancements (targeted police operations or low-cost engineering improvements), driver yielding rates did not change from before to after the Watch for Me NC program. However, yielding rates improved significantly (between 4 and 7 percentage points on average) at the enhanced locations. This was true for both naturalistic and staged crossings.ConclusionsThis study provides evidence that enhanced enforcement and low-cost engineering improvements, as a part of a broader program involving community-based outreach, can increase driver yielding to pedestrians in marked crosswalks. These data are important for the staff and decision-makers involved in pedestrian safety programs to gain a better understanding of the different engineering and behavioral mechanisms that could be used to improve driver yielding rates.

We used data from 3227 older adults in the Multi-Ethnic Study of Atherosclerosis (2004-2012) to explore cross-sectional and longitudinal associations between walkability and cardiometabolic risk factors. In cross-sectional analyses, linear regression was used to estimate associations of Street Smart Walk Score® with glucose, triglycerides, HDL and LDL cholesterol, systolic and diastolic blood pressure, and waist circumference, while logistic regression was used to estimate associations with odds of metabolic syndrome. Econometric fixed effects models were used to estimate longitudinal associations of changes in walkability with changes in each risk factor among participants who moved residential locations between 2004 and 2012 (n=583). Most cross-sectional and longitudinal associations were small and statistically non-significant. We found limited evidence that higher walkability was cross-sectionally associated with lower blood pressure but that increases in walkability were associated with increases in triglycerides and blood pressure over time. Further research over longer time periods is needed to understand the potential for built environment interventions to improve cardiometabolic health.

Accelerometers have been widely deployed in public health studies in recent years. While they collect high-resolution acceleration signals (e.g., 10-100 Hz), research has mainly focused on summarized metrics provided by accelerometers manufactures, such as the activity count (AC) by ActiGraph or Actical. Such measures do not have a publicly available formula, lack a straightforward interpretation, and can vary by software implementation or hardware type. To address these problems, we propose the physical activity index (AI), a new metric for summarizing raw tri-axial accelerometry data. We compared this metric with the AC and another recently proposed metric for raw data, Euclidean Norm Minus One (ENMO), against energy expenditure. The comparison was conducted using data from the Objective Physical Activity and Cardiovascular Health Study, in which 194 women 60-91 years performed 9 lifestyle activities in the laboratory, wearing a tri-axial accelerometer (ActiGraph GT3X+) on the hip set to 30 Hz and an Oxycon portable calorimeter, to record both tri-axial acceleration time series (converted into AI, AC, and ENMO) and oxygen uptake during each activity (converted into metabolic equivalents (METs)) at the same time. Receiver operating characteristic analyses indicated that both AI and ENMO were more sensitive to moderate and vigorous physical activities than AC, while AI was more sensitive to sedentary and light activities than ENMO. AI had the highest coefficients of determination for METs (0.72) and was a better classifier of physical activity intensity than both AC (for all intensity levels) and ENMO (for sedentary and light intensity). The proposed AI provides a novel and transparent way to summarize densely sampled raw accelerometry data, and may serve as an alternative to AC. The AI's largely improved sensitivity on sedentary and light activities over AC and ENMO further demonstrate its advantage in studies with older adults.

BackgroundSome accelerometer studies ask participants to document in a daily log when the device was worn. These logs are used to inform the window of consecutive days to extract from the accelerometer for analysis. Logs can be missing or inaccurate, which can introduce bias in the data. To mitigate this bias, we developed a simple computer algorithm that used data within the accelerometer to identify the window of consecutive wear days. To evaluate the algorithm's performance, we compared how well it agreed to the window of days identified by visual inspection and participant logs.FindingsParticipants were older women (mean age 79 years) in a cohort study that aimed to examine the relationship of objective physical activity on cardiovascular health. The study protocol requested that participants wear an accelerometer 24 h per day over nine calendar days (to capture seven consecutive wear days) and to complete daily logs. A stratified sample with (n = 75) and without (n = 100) participant logs were selected. The Objective Physical Activity and Cardiovascular Health (OPACH) algorithm was applied to the accelerometer data to identify a window of up to seven consecutive wear days. Participant logs documented dates the device was first put on, worn, and removed. Using pre-established guidelines, two independent raters visually reviewed the accelerometer data and characterized the dates representing up to seven consecutive days of 24-h wear. Average agreement level between the two raters was 90%. The percent agreement was compared between the three methods. The OPACH algorithm and visual inspection had 83% agreement in identifying a window with the same total number of days, if one or more shifts in calendar dates were allowed. For visual inspection vs. logs and algorithm vs. logs, this agreement was 81 and 74%, respectively.ConclusionThe OPACH algorithm can be efficiently and readily applied in large-scale accelerometer studies for the identification of a window of consecutive days of accelerometer wear. This algorithm was comparable to visual inspection and participant logs and might provide a quicker and more cost-effective alternative to selecting which data to extract from the accelerometer for analysis.Trial registrationclinicaltrials.gov identifier: NCT00000611.

We examined the influence of the built environment on pedestrian route selection among adolescent girls. Portable global positioning system units, accelerometers, and travel diaries were used to identify the origin, destination, and walking routes of girls in San Diego, CA and Minneapolis, MN. We completed an inventory of the built environment on every street segment to measure the characteristics of routes taken and not taken. Route-level variables covering four key conceptual built environment domains (Aesthetics, Destinations, Functionality, and Safety) were used in the analysis of route choice. Shorter distance had the strongest positive association with route choice, while the presence of a greenway or trail, higher safety, presence of sidewalks, and availability of destinations along a route were also consistently positively associated with route choice at both sites. The results suggest that it may be possible to encourage pedestrians to walk farther by providing high quality and stimulating routes.

ObjectiveWe conducted a laboratory-based calibration study to determine relevant cutpoints for a hip-worn accelerometer among women ≥60 years, considering both type and filtering of counts.MethodsTwo hundred women wore an ActiGraph GT3X+ accelerometer on their hip while performing eight laboratory-based activities. Oxygen uptake was measured using an Oxycon portable calorimeter. Accelerometer data were analyzed in 15-second epochs for both normal and low frequency extension (LFE) filters. Receiver operating characteristic (ROC) curve analyses were used to calculate cutpoints for sedentary, light (low and high), and moderate to vigorous physical activity (MVPA) using the vertical axis and vector magnitude (VM) counts.ResultsMean age was 75.5 years (standard deviation 7.7). The Spearman correlation between oxygen uptake and accelerometry ranged from 0.77 to 0.85 for the normal and LFE filters and for both the vertical axis and VM. The area under the ROC curve was generally higher for VM compared to the vertical axis, and higher for cutpoints distinguishing MVPA compared to sedentary and light low activities. The VM better discriminated sedentary from light low activities compared to the vertical axis. The area under the ROC curves were better for the LFE filter compared to the normal filter for the vertical axis counts, but no meaningful differences were found by filter type for VM counts.ConclusionThe cutpoints derived for this study among women ≥60 years can be applied to ongoing epidemiologic studies to define a range of physical activity intensities.

ObjectiveWe conducted a laboratory-based calibration study to determine relevant cutpoints for a hip-worn accelerometer among women ≥60 years, considering both type and filtering of counts.MethodsTwo hundred women wore an ActiGraph GT3X+ accelerometer on their hip while performing eight laboratory-based activities. Oxygen uptake was measured using an Oxycon portable calorimeter. Accelerometer data were analyzed in 15-second epochs for both normal and low frequency extension (LFE) filters. Receiver operating characteristic (ROC) curve analyses were used to calculate cutpoints for sedentary, light (low and high), and moderate to vigorous physical activity (MVPA) using the vertical axis and vector magnitude (VM) counts.ResultsMean age was 75.5 years (standard deviation 7.7). The Spearman correlation between oxygen uptake and accelerometry ranged from 0.77 to 0.85 for the normal and LFE filters and for both the vertical axis and VM. The area under the ROC curve was generally higher for VM compared to the vertical axis, and higher for cutpoints distinguishing MVPA compared to sedentary and light low activities. The VM better discriminated sedentary from light low activities compared to the vertical axis. The area under the ROC curves were better for the LFE filter compared to the normal filter for the vertical axis counts, but no meaningful differences were found by filter type for VM counts.ConclusionThe cutpoints derived for this study among women ≥60 years can be applied to ongoing epidemiologic studies to define a range of physical activity intensities.

Steps per day were measured by accelerometer for 7 days among 5,545 women aged 63–97 years between 2012 and 2014. Incident falls were ascertained from daily fall calendars for 13 months. Median steps per day were 3,216. There were 5,473 falls recorded over 61,564 fall calendar-months. The adjusted incidence rate ratio comparing women in the highest versus lowest step quartiles was 0.71 (95% confidence interval [0.54, 0.95]; ptrend across quartiles =.01). After further adjustment for physical function using the Short Physical Performance Battery, the incidence rate ratio was 0.86 ([0.64, 1.16]; ptrend =.27). Mediation analysis estimated that 63.7% of the association may be mediated by physical function (p =.03). In conclusion, higher steps per day were related to lower incident falls primarily through their beneficial association with physical functioning. Interventions that improve physical function, including those that involve stepping, could reduce falls in older adults. [ABSTRACT FROM AUTHOR]

Background: Describing correlates of physical activity (PA) and sedentary behavior (SB) among postmenopausal cancer survivors can help identify risk profiles and can be used to support development of targeted interventions to improve PA and reduce SB in this population. Objective: To describe PA/SB and identify correlates of PA/SB among cancer and cancer-free post-menopausal women. Methods: Women from the Women's Health Study (N = 16,629) and Women's Health Initiative/Objective Physical Activity and Cardiovascular Health Study (N = 6,079) were asked to wear an accelerometer on the hip for 7 days. Multiple mixed-effects linear regression models were used to identify sociodemographic-, health-, and chronic condition-related correlates (independent variables) associated with PA and SB (dependent variables) among women with (n = 2,554) and without (n = 20,154) a history of cancer. All correlates were mutually adjusted for each other. Results: In unadjusted analyses, women with a history of cancer took fewer mean daily steps (4,572 (standard deviation 2557) vs 5,029 (2679) steps/day) and had lower mean moderate-to-vigorous PA (74.9 (45.0) vs. 81.6 (46.7) minutes/day) than cancer-free women. In adjusted analyses, for cancer and cancer-free women, age, diabetes, overweight, and obesity were inversely associated with all metrics of PA (average vector magnitude, time in moderate-to-vigorous PA, step volume, time at ≥40 steps/minutes, and peak 30-minute step cadence). In unadjusted analyses, mean SB was similar for those with and without cancer (529.7 (98.1) vs. 521.7 (101.2) minutes/day). In adjusted analyses, for cancer and cancer-free women, age, diabetes, cardiovascular disease, current smoking, overweight, and obesity were positive correlates of SB, while Black or Hispanic race/ethnicity, weekly/daily alcohol intake, and excellent/very good/good self-rated health were inverse correlates of SB. Conclusion: Several sociodemographic, health, and chronic conditions were correlates of PA/SB for postmenopausal women with and without cancer. Future studies should examine longitudinal relationships to gain insight into potential determinants of PA/SB. [ABSTRACT FROM AUTHOR]

Aim: Secondary analyses were conducted from a randomized trial of an adaptive behavioural intervention to assess the relationship between protein intake (g and g/kg) consumed within 4 h before moderate‐to‐vigorous physical activity (MVPA) bouts and glycaemia during and following MVPA bouts among adolescents with type 1 diabetes (T1D). Materials and Methods: Adolescents (n = 112) with T1D, 14.5 (13.8, 15.7) years of age and 36.6% overweight/obese, provided measures of glycaemia using continuous glucose monitoring [percentage of time above range (>180 mg/dl), time in range (70‐180 mg/dl), time below range (TBR; <70 mg/dl)], self‐reported physical activity (previous day physical activity recalls), and 24 h dietary recall data at baseline and 6 months post‐intervention. Mixed effects regression models adjusted for design (randomization assignment, study site), demographic, clinical, anthropometric, dietary, physical activity and timing covariates estimated the association between pre‐exercise protein intake on percentage of time above range, time in range and TBR during and following MVPA. Results: Pre‐exercise protein intakes of 10‐19.9 g and >20 g were associated with an absolute reduction of −4.41% (p =.04) and −4.83% (p =.02) TBR during physical activity compared with those who did not consume protein before MVPA. Similarly, relative protein intakes of 0.125‐0.249 g/kg and ≥0.25 g/kg were associated with −5.38% (p =.01) and −4.32% (p =.03) absolute reductions in TBR during physical activity. We did not observe a significant association between protein intake and measures of glycaemia following bouts of MVPA. Conclusions: Among adolescents with T1D, a dose of ≥10 g or ≥0.125 g/kg of protein within 4 h before MVPA may promote reduced time in hypoglycaemia during, but not following, physical activity. [ABSTRACT FROM AUTHOR]

Background 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. Methods 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. Results 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). Conclusions 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. [ABSTRACT FROM AUTHOR]