Lara Weed

All Publications

• An umbrella review of systematic reviews of the impact of wrist-worn wearables on health outcomes. Physiological reviews Glisic, M., Llane, A., Stojic, S., Llanaj, E., Roa-Díaz, Z. M., Raguindin, P. F., Kastrati, L., Weed, L., Turakhia, M. P., Ashley, E., Muka, T., Ioannidis, J. P. 2025

  Abstract

  We conducted an umbrella review to synthesize the evidence on the effectiveness of interventions incorporating wrist-worn wearables* feedback on diverse health outcomes including health promotion (i.e., health behaviors and disease risk perception) morbidity, mortality, functioning, and other health-related metrics in humans. We searched in MEDLINE, Web of Science, Embase and Cochrane Library until 18th March 2025 for eligible systematic reviews. After screening 9 487 citations, we identified 39 systematic reviews, which included 98 original studies (one observational study, 95 randomized controlled trials, and two pre-post studies). The reviews primarily focused on adult populations, individuals with cardiometabolic conditions, and cancer survivors. The original interventional studies mainly included Fitbit (40.2%), Polar (12.4%), and ActiGraph (10.3%) devices. Over 80% of the clinical trials involved complex behavioral interventions with wearable-based feedback, and the control groups varied. Most systematic reviews were rated as low confidence, with common flaws including inadequate considerations for risk-of-bias and heterogeneity. Interventions incorporating wrist-worn activity trackers increased physical activity in diverse populations. The effect of interventions incorporating wrist-wearables' feedback on cardiometabolic risk markers, quality of life, depression/anxiety and pain was limited and remained inconsistent. Our findings rely on existing systematic reviews, which may vary in quality, review methodologies and comprehensiveness. There is also potential for missing more recent evidence not yet captured in these reviews. These limitations should be considered when interpreting our results. Acknowledging these caveats, wrist-worn wearables seem to increase physical activity, and may have also additional benefits that require further study.

  View details for DOI 10.1152/physrev.00049.2024

  View details for PubMedID 41460208

• Circadian Phase Estimation From Ambulatory Wearables With Particle Filtering: Accuracy Depends on Initialization, Recording Duration, and Light Exposure. Journal of biological rhythms Weed, L., Jamgochian, A., St Hilaire, M. A., Cheng, P., Kochenderfer, M. J., Zeitzer, J. M. 2025: 7487304251392289

  Abstract

  While current mathematical models of human circadian rhythms accurately predict circadian phase responses to light in controlled laboratory experiments, they show reduced performance in the real world, especially among shift workers with irregular schedules and downstream erratic light diets. The source of the discrepancy between in-laboratory and ambulatory performance remains unclear. We evaluate the impact of initialization strategy, recording duration, and light exposure characteristics on model performance using wearable data from both individuals on regular schedules and shift workers. We implement a probabilistic initialization framework to account for unknown starting phase and assess model performance in prediction of phase from light input data against an in-lab measure of circadian phase (dim light melatonin onset). In participants with regular schedules, accuracy improved with longer recordings, while shift workers show no accuracy gains when having more nights of data. Light exposure patterns differed significantly between groups, with brighter and more regular day-to-day light exposure being weakly to moderately associated with improved model estimates, whereas fragmented patterns of light exposure increased uncertainty. These findings suggest that current models require adaptation, particularly in light sensitivity, to generalize to free-living, irregular conditions and support robust, scalable circadian tracking in real-world populations.

  View details for DOI 10.1177/07487304251392289

  View details for PubMedID 41342262

• Circadian-informed modeling predicts regional variation in obesity and stroke outcomes under different permanent US time policies. Proceedings of the National Academy of Sciences of the United States of America Weed, L., Zeitzer, J. M. 2025; 122 (38): e2508293122

  Abstract

  Seasonal changes in time policy, such as switching between Standard Time (SDT) and Daylight Saving Time (DST), have been adopted by many countries, including the United States. While transitioning between SDT and DST has notable acute negative population health impacts, the chronic impact of these time policies on health has not been well evaluated. To estimate the impact of permanent SDT or DST on health, we modeled the circadian impact of SDT, DST, and Biannual Shifting (BAS) across a year in the contiguous, continental United States. We find that BAS produces a greater burden on the circadian system as compared to either permanent SDT or DST. Chronotype as well as location (latitude and location within time zones) impact this burden. Analyzing these data relative to county-level health data (Centers for Disease Control and Prevention Places dataset), we find that, under idealized light exposure conditions and after controlling for health and socioeconomic factors, there would be a decrease in the prevalence of both obesity [[Formula: see text]0.78% ([Formula: see text]0.06% to [Formula: see text]1.49%)] and stroke [[Formula: see text]0.09% ([Formula: see text]0.04% to [Formula: see text]0.14%)] under SDT compared with the current policy. The prevalence of both obesity [[Formula: see text]0.51% ([Formula: see text]0.09% to [Formula: see text]0.93%)] and stroke [[Formula: see text]0.07% ([Formula: see text]0.04% to [Formula: see text]0.09%)] would also decrease under permanent DST, though to a lesser degree. Our data, reflecting the impact of time policy on circadian burden and subsequent health benefits, support the cessation of BAS.

  View details for DOI 10.1073/pnas.2508293122

  View details for PubMedID 40953265

• Adverse effects of late sleep on physical health in a large cohort of community-dwelling adults. European journal of internal medicine Lok, R., Weed, L., Winer, J., Zeitzer, J. M. 2024

  Abstract

  Sleep timing, influenced by chronotype, behavior, and circadian rhythms, is critical for human health. While previous research has linked chronotype to various health outcomes, the impact of aligning sleep timing with chronotype on physical health remains underexplored. The objective of this study is to investigate the association between chronotype, actual sleep timing, and their alignment with a spectrum of physical health outcomes.Objective sleep timing (actigraphy, categorized as early, intermediate, or late) and chronotype (self-reported, categorized as morning, intermediate, or evening types) were derived from the UK Biobank (n=73,888 middle-aged and older adults) and used in cross-sectional and longitudinal analyses. Physical health outcomes included metabolic disorders, diabetes, obesity, hypertension, circulatory disorders, digestive disorders, respiratory disorders, and all-cause cancer based on ICD10 codes. Analyses were adjusted for demographic factors, sleep duration and sleep timing stability.As compared to morning types with early behavior (aligned), morning types with late behavior (misaligned) had an increased risk of all included physical health disorders (p's<0.001). As compared to evening-types with late behavior (aligned), however, evening-types with early behavior (misaligned) had a decreased risk of diabetes, obesity, hypertension, circulatory disorders, and respiratory disorders (p < 0.01). Longitudinal analyses, in which the likelihood of developing de novo physical health disorders was associated with chronotype, behavioral timing, and alignment between the two, confirmed cross-sectional findings.Late sleep timing across chronotypes was consistently associated with adverse physical health outcomes. These findings underscore the importance of going to sleep early, regardless of preference.

  View details for DOI 10.1016/j.ejim.2024.12.031

  View details for PubMedID 39743471

• Impact Of Time Of Day On Neuromuscular Performance Of The Star Excursion Balance Test In Young Women Weed, L., Thompson, S., Kraus, E., Delp, S., Zeitzer, J. LIPPINCOTT WILLIAMS & WILKINS. 2024: 257-258

  View details for Web of Science ID 001315123201146

• How many days are enough? Sleep-wake timing regularity and fragmentation scores change with the number of days included. Journal of sleep research Lok, R., Suh, S., Rue, S., Weed, L., Zeitzer, J. M. 2024: e14332

  Abstract

  The duration of sleep data collection from actigraphy is often influenced by practical factors (e.g. workdays versus non-workdays), but the impact of the variation of duration on outcome measures of interest has not been well explored. This study investigates the effect of the duration of actigraphy measurement on non-parametric measures of 24-hr sleep-wake rhythms. We examined regularity inter-daily stability and fragmentation intra-daily variation over 14 days or the first 7 days in participants (n = 41) undergoing evaluation for sleep disorders. Bland-Altman plots assessed the impact of fewer than 14 or 7 days, respectively, on inter-daily stability and intra-daily variation scores. Intra-daily variation values were also calculated for each day and compared with the 14-day intra-daily variation. Compared with the entire 14-day period, using shorter durations (< 7 days) led to a higher estimated bias and increased variance in the limits of agreement for inter-daily stability. Intra-daily variation values showed increased variation in the limits of agreement with fewer days. Similar trends were observed when comparing shorter actigraphy periods 3 or 5 days-7 days. Daily intra-daily variation calculations indicate that individuals with higher daily fragmentation experienced more pronounced day-to-day fragmentation and greater variability in the degree of fragmentation, in a linear association between daily intra-daily variation standard deviation and 14-day intra-daily variation values. Our data indicate that a minimum of 7 full days of actigraphy is recommended to reduce measurement errors, and intra-daily variation and inter-daily stability derived from less than 7 days cannot be compared with those from more than 7 days without significant error.

  View details for DOI 10.1111/jsr.14332

  View details for PubMedID 39317644

• Perils of the nighttime: Impact of behavioral timing and preference on mental health in 73,888 community-dwelling adults. Psychiatry research Lok, R., Weed, L., Winer, J., Zeitzer, J. M. 2024; 337: 115956

  Abstract

  Mental health is independently influenced by the inclination to sleep at specific times (chronotype) and the actual sleep timing (behavior). Chronotype and timing of actual sleep are, however, often misaligned. This study aims to determine how chronotype, sleep timing, and the alignment between the two impact mental health. In a community-dwelling cohort of middle- and older-aged adults (UK Biobank, n = 73,888), we examined the impact of chronotype (questionnaire-based), the timing of behavior (determined with 7-day accelerometry), and the alignment between the two on mental, behavioral, neurodevelopmental disorders (MBN), depression, and anxiety, as assessed through ICD-10 codes. As compared to morning types with early behavior (aligned), morning types with late behavior (misaligned) had an increased risk of having MBN, depression, and anxiety (p's<0.001). As compared to evening-types with late behavior (aligned), however, evening-types with early behavior (misaligned) had a decreased risk of depression (p < 0.01), with a trend for MBN (p = 0.04) and anxiety (p = 0.05). Longitudinal analyses, in which the likelihood of developing de novo mental health disorders was associated with chronotype, behavioral timing, and alignment between the two, confirmed cross-sectional findings. To age healthily, individuals should start sleeping before 1AM, despite chronobiological preferences.

  View details for DOI 10.1016/j.psychres.2024.115956

  View details for PubMedID 38763081

• Impaired 24-h activity patterns are associated with an increased risk of Alzheimer's disease, Parkinson's disease, and cognitive decline. Alzheimer's research & therapy Winer, J. R., Lok, R., Weed, L., He, Z., Poston, K. L., Mormino, E. C., Zeitzer, J. M. 2024; 16 (1): 35

  Abstract

  Sleep-wake regulating circuits are affected during prodromal stages in the pathological progression of both Alzheimer's disease (AD) and Parkinson's disease (PD), and this disturbance can be measured passively using wearable devices. Our objective was to determine whether accelerometer-based measures of 24-h activity are associated with subsequent development of AD, PD, and cognitive decline.This study obtained UK Biobank data from 82,829 individuals with wrist-worn accelerometer data aged 40 to 79 years with a mean (± SD) follow-up of 6.8 (± 0.9) years. Outcomes were accelerometer-derived measures of 24-h activity (derived by cosinor, nonparametric, and functional principal component methods), incident AD and PD diagnosis (obtained through hospitalization or primary care records), and prospective longitudinal cognitive testing.One hundred eighty-seven individuals progressed to AD and 265 to PD. Interdaily stability (a measure of regularity, hazard ratio [HR] per SD increase 1.25, 95% confidence interval [CI] 1.05-1.48), diurnal amplitude (HR 0.79, CI 0.65-0.96), mesor (mean activity; HR 0.77, CI 0.59-0.998), and activity during most active 10 h (HR 0.75, CI 0.61-0.94), were associated with risk of AD. Diurnal amplitude (HR 0.28, CI 0.23-0.34), mesor (HR 0.13, CI 0.10-0.16), activity during least active 5 h (HR 0.24, CI 0.08-0.69), and activity during most active 10 h (HR 0.20, CI 0.16-0.25) were associated with risk of PD. Several measures were additionally predictive of longitudinal cognitive test performance.In this community-based longitudinal study, accelerometer-derived metrics were associated with elevated risk of AD, PD, and accelerated cognitive decline. These findings suggest 24-h rhythm integrity, as measured by affordable, non-invasive wearable devices, may serve as a scalable early marker of neurodegenerative disease.

  View details for DOI 10.1186/s13195-024-01411-0

  View details for PubMedID 38355598

  View details for PubMedCentralID 4163039

• Fatigued but not sleepy? An empirical investigation of the differentiation between fatigue and sleepiness in sleep disorder patients in a cross-sectional study. Journal of psychosomatic research Suh, S., Lok, R., Weed, L., Cho, A., Mignot, E., Leary, E. B., Zeitzer, J. M. 2024; 178: 111606

  Abstract

  Sleepiness and fatigue are common complaints among individuals with sleep disorders. The two concepts are often used interchangeably, causing difficulty with differential diagnosis and treatment decisions. The current study investigated sleep disorder patients to determine which factors best differentiated sleepiness from fatigue.The study used a subset of participants from a multi-site study (n = 606), using a cross-sectional study design. We selected 60 variables associated with either sleepiness or fatigue, including demographic, mental health, and lifestyle factors, medical history, sleep questionnaires, rest-activity rhythms (actigraphy), polysomnographic (PSG) variables, and sleep diaries. Fatigue was measured with the Fatigue Severity Scale and sleepiness was measured with the Epworth Sleepiness Scale. A Random Forest machine learning approach was utilized for analysis.Participants' average age was 47.5 years (SD 14.0), 54.6% female, and the most common sleep disorder diagnosis was obstructive sleep apnea (67.4%). Sleepiness and fatigue were moderately correlated (r = 0.334). The model for fatigue (explained variance 49.5%) indicated depression was the strongest predictor (relative explained variance 42.7%), followed by insomnia severity (12.3%). The model for sleepiness (explained variance 17.9%), indicated insomnia symptoms was the strongest predictor (relative explained variance 17.6%). A post hoc receiver operating characteristic analysis indicated depression could be used to discriminate fatigue (AUC = 0.856) but not sleepiness (AUC = 0.643).The moderate correlation between fatigue and sleepiness supports previous literature that the two concepts are overlapping yet distinct. Importantly, depression played a more prominent role in characterizing fatigue than sleepiness, suggesting depression could be used to differentiate the two concepts.

  View details for DOI 10.1016/j.jpsychores.2024.111606

  View details for PubMedID 38359639

• PERILS OF THE NIGHTTIME: IMPACT OF BEHAVIORAL TIMING AND PREFERENCE ON MENTAL AND PHYSICAL HEALTH Zeitzer, J., Lok, R., Weed, L., Winer, J. OXFORD UNIV PRESS INC. 2023

  View details for Web of Science ID 001008232900019

• Brief structured respiration practices enhance mood and reduce physiological arousal. Cell reports. Medicine Balban, M. Y., Neri, E., Kogon, M. M., Weed, L., Nouriani, B., Jo, B., Holl, G., Zeitzer, J. M., Spiegel, D., Huberman, A. D. 2023: 100895

  Abstract

  Controlled breathwork practices have emerged as potential tools for stress management and well-being. Here, we report a remote, randomized, controlled study (NCT05304000) of three different daily 5-min breathwork exercises compared with an equivalent period of mindfulness meditation over 1 month. The breathing conditions are (1) cyclic sighing, which emphasizes prolonged exhalations; (2) box breathing, which is equal duration of inhalations, breath retentions, and exhalations; and (3) cyclic hyperventilation with retention, with longer inhalations and shorter exhalations. The primary endpoints are improvement in mood and anxiety as well as reduced physiological arousal (respiratory rate, heart rate, and heart rate variability). Using a mixed-effects model, we show that breathwork, especially the exhale-focused cyclic sighing, produces greater improvement in mood (p < 0.05) and reduction in respiratory rate (p < 0.05) compared with mindfulness meditation. Daily 5-min cyclic sighing has promise as an effective stress management exercise.

  View details for DOI 10.1016/j.xcrm.2022.100895

  View details for PubMedID 36630953

• The Impact of Missing Data and Imputation Methods on the Analysis of 24-Hour Activity Patterns. Clocks & sleep Weed, L., Lok, R., Chawra, D., Zeitzer, J. 2022; 4 (4): 497-507

  Abstract

  The purpose of this study is to characterize the impact of the timing and duration of missing actigraphy data on interdaily stability (IS) and intradaily variability (IV) calculation. The performance of three missing data imputation methods (linear interpolation, mean time of day (ToD), and median ToD imputation) for estimating IV and IS was also tested. Week-long actigraphy records with no non-wear or missing timeseries data were masked with zeros or 'Not a Number' (NaN) across a range of timings and durations for single and multiple missing data bouts. IV and IS were calculated for true, masked, and imputed (i.e., linear interpolation, mean ToD and, median ToD imputation) timeseries data and used to generate Bland-Alman plots for each condition. Heatmaps were used to analyze the impact of timings and durations of and between bouts. Simulated missing data produced deviations in IV and IS for longer durations, midday crossings, and during similar timing on consecutive days. Median ToD imputation produced the least deviation among the imputation methods. Median ToD imputation is recommended to recapitulate IV and IS under missing data conditions for less than 24 h.

  View details for DOI 10.3390/clockssleep4040039

  View details for PubMedID 36278532

• SLEEP-WAKE STABILITY AND VARIABILITY IN THE MIDDLE-AGED ADULT POPULATION: A UK BIOBANK STUDY Lok, R., Weed, L., Chawra, D., Winer, J., Zeitzer, J. OXFORD UNIV PRESS INC. 2022: A73-A74

  View details for Web of Science ID 000838094800159

• Gait instability and estimated core temperature predict exertional heat stroke BRITISH JOURNAL OF SPORTS MEDICINE Buller, M., Fellin, R., Bursey, M., Galer, M., Atkinson, E., Beidleman, B. A., Marcello, M. J., Driver, K., Mesite, T., Seay, J., Weed, L., Telfer, B., King, C., Frazee, R., Moore, C., Williamson, J. R. 2022

  Abstract

  Exertional heat stroke (EHS), characterised by a high core body temperature (Tcr) and central nervous system (CNS) dysfunction, is a concern for athletes, workers and military personnel who must train and perform in hot environments. The objective of this study was to determine whether algorithms that estimate Tcr from heart rate and gait instability from a trunk-worn sensor system can forward predict EHS onset.Heart rate and three-axis accelerometry data were collected from chest-worn sensors from 1806 US military personnel participating in timed 4/5-mile runs, and loaded marches of 7 and 12 miles; in total, 3422 high EHS-risk training datasets were available for analysis. Six soldiers were diagnosed with heat stroke and all had rectal temperatures of >41°C when first measured and were exhibiting CNS dysfunction. Estimated core temperature (ECTemp) was computed from sequential measures of heart rate. Gait instability was computed from three-axis accelerometry using features of pattern dispersion and autocorrelation.The six soldiers who experienced heat stroke were among the hottest compared with the other soldiers in the respective training events with ECTemps ranging from 39.2°C to 40.8°C. Combining ECTemp and gait instability measures successfully identified all six EHS casualties at least 3.5 min in advance of collapse while falsely identifying 6.1% (209 total false positives) examples where exertional heat illness symptoms were neither observed nor reported. No false-negative cases were noted.The combination of two algorithms that estimate Tcr and ataxic gate appears promising for real-time alerting of impending EHS.

  View details for DOI 10.1136/bjsports-2021-104081

  View details for Web of Science ID 000744332300001

  View details for PubMedID 35022161

• A Preliminary Investigation of the Effects of Obstacle Negotiation and Turning on Gait Variability in Adults with Multiple Sclerosis SENSORS Weed, L., Little, C., Kasser, S. L., McGinnis, R. S. 2021; 21 (17)

  Abstract

  Many falls in persons with multiple sclerosis (PwMS) occur during daily activities such as negotiating obstacles or changing direction. While increased gait variability is a robust biomarker of fall risk in PwMS, gait variability in more ecologically related tasks is unclear. Here, the effects of turning and negotiating an obstacle on gait variability in PwMS were investigated. PwMS and matched healthy controls were instrumented with inertial measurement units on the feet, lumbar, and torso. Subjects completed a walk and turn (WT) with and without an obstacle crossing (OW). Each task was partitioned into pre-turn, post-turn, pre-obstacle, and post-obstacle phases for analysis. Spatial and temporal gait measures and measures of trunk rotation were captured for each phase of each task. In the WT condition, PwMS demonstrated significantly more variability in lumbar and trunk yaw range of motion and rate, lateral foot deviation, cadence, and step time after turning than before. In the OW condition, PwMS demonstrated significantly more variability in both spatial and temporal gait parameters in obstacle approach after turning compared to before turning. No significant differences in gait variability were observed after negotiating an obstacle, regardless of turning or not. Results suggest that the context of gait variability measurement is important. The increased number of variables impacted from turning and the influence of turning on obstacle negotiation suggest that varying tasks must be considered together rather than in isolation to obtain an informed understanding of gait variability that more closely resembles everyday walking.

  View details for DOI 10.3390/s21175806

  View details for Web of Science ID 000694535000001

  View details for PubMedID 34502697

  View details for PubMedCentralID PMC8434341

• Estimating Sedentary Breathing Rate from Chest-Worn Accelerometry From Free-Living Data Telfer, B. A., Williamson, J. R., Weed, L., Bursey, M., Frazee, R., Galer, M., Moore, C., Buller, M., Friedl, K. E., IEEE IEEE. 2020: 4636-4639

  Abstract

  Breathing rate was estimated from chest-worn accelerometry collected from 1,522 servicemembers during training by a wearable physiological monitor. A total of 29,189 hours of training and sleep data were analyzed. The primary purpose of the monitor was to assess thermal-work strain and avoid heat injuries. The monitor design was thus not optimized to estimate breathing rate. Since breathing rate cannot be accurately estimated during periods of high activity, a qualifier was applied to identify sedentary time periods, totaling 8,867 hours. Breathing rate was estimated for a total of 4,179 hours, or 14% of the total collection and 47% of the sedentary total, primarily during periods of sleep. The breathing rate estimation method was compared to an FDA 510(K)-cleared criterion breathing rate sensor (Zephyr, Annapolis MD, USA) in a controlled laboratory experiment, which showed good agreement between the two techniques. Contributions of this paper are to: 1) provide the first analysis of accelerometry-derived breathing rate on free-living data including periods of high activity as well as sleep, along with a qualifier that effectively identifies sedentary periods appropriate for estimating breathing rate; 2) test breathing rate estimation on a data set with a total duration that is more than 60 times longer than that of the largest previously reported study, 3) test breathing rate estimation on data from a physiological monitor that has not been expressly designed for that purpose.

  View details for Web of Science ID 000621592204236

  View details for PubMedID 33019027