Intensity or volume: the role of physical activity in longevity.

AIMS: To investigate how physical activity (PA) volume, intensity, duration, and fragmentation are associated with the risk of all-cause and cardiovascular disease mortality. To produce centile curves for PA volume and intensity representative of US adults. METHODS: This study is based on the observational 2011-2014 National Health and Nutrition Examination Survey (NHANES). Adults (age ≥20) with valid accelerometer, covariate, and mortality data were included. Average acceleration (AvAcc), intensity gradient (IG), and total PA served as proxies for volume, intensity, and duration of PA, respectively. Weighted Cox proportional hazard models estimated associations between outcome and PA metrics. RESULTS: In 7518 participants (52.0% women, weighted median age 49), there were curvilinear inverse dose-response relationships of all-cause mortality risk (81-month follow-up) with both AvAcc (-14.4% [95% CI -8.3 to -20.1%] risk reduction from 25th to 50th percentile) and IG (-37.1% [95% CI -30.0 to -43.4%] risk reduction from 25th to 50th percentile), but for cardiovascular disease mortality risk (N=7016, 82-month follow-up) only with IG (-41.0% [95% CI -26.7 to -52.4%] risk reduction from the 25th to 50th percentile). These relationships plateau at AvAcc: ∼35-45 mg and IG: -2.7 to -2.5. Associations of PA with all-cause and cardiovascular disease mortality are primarily driven by intensity and secondary by volume. Centile curves for volume and intensity were generated. CONCLUSION: Intensity is a main driver of reduced mortality risk suggesting that the intensity of PA rather than the quantity matters for longevity. The centile curves offer guidance for achieving desirable PA levels for longevity.

This study shows that the distribution of the intensity of physical activity accumulated across the day may be more important for mortality reduction than the quantity (volume), underscoring the relevance of integrating physical activity of higher intensity into daily routines for health optimisation.Higher physical activity intensity is more closely associated with reduced mortality risk than physical activity volume, particularly for cardiovascular disease mortality.We provide initial evidence suggesting health benefits when accumulating intense physical activity in continuous bouts rather than sporadically across the day.

Associations between Aircraft Noise, Sleep, and Sleep-Wake Cycle: Actimetric Data from the UK Biobank Cohort near Four Major Airports.

BACKGROUND: Nighttime aircraft noise may affect people's sleep, yet large-scale evidence using objective and subjective measures remains limited. OBJECTIVE: Our aim was to investigate associations between nighttime aircraft noise exposure and objectively measured sleep disturbance using a large UK cohort. METHODS: We used data from 105,770 UK Biobank cohort participants exposed and unexposed to aircraft noise who lived in 44 local authority districts near 4 international airports in England. We used a generalized linear regression model to examine cross-sectional associations between aircraft noise Lnight (23:00 hours-07:00 hours) and 7-d actimetric measures collected 2013-2015 (n=22,102). We also used Logit and generalized estimating equations models to examine associations between Lnight and self-reported sleep measures at enrollment (2006-2010) and follow-up (2012-2013). This approach allowed us to compare and contrast the results and support potential future meta-analyses on noise-related sleep disturbance. RESULTS: Cross-sectional analyses of actimetric data suggested sleep disturbance associated with Lnight, showing higher level of movements during the least active continuous 8-h time period [ß: 0.12 milligravitational units; 95% confidence interval (CI): 0.013, 0.23]. We also saw disrupted sleep-wake cycles as indicated by index scores of lower relative amplitude (ß: -0.006; 95% CI: -0.007, -0.005), poorer interdaily stability (ß: -0.010; 95% CI: -0.014, -0.006), and greater intradaily variability (ß: 0.021; 95% CI: 0.019, 0.023), comparing Lnight ≥55 dB with <45 dB. Repeated cross-sectional analyses found a 52% higher odds of more frequent daytime dozing [odds ratio (OR) =1.52; 95% CI: 1.32, 1.75] for Lnight ≥55 dB in comparison with <45 dB, whereas the likelihood for more frequent sleeplessness was more uncertain (OR=1.13; 95% CI: 0.92, 1.39). Higher effect sizes were seen in preidentified vulnerable groups, including individuals >65y of age and those with diabetes or dementia. CONCLUSION: Individuals exposed to higher levels of aircraft noise experienced objectively higher levels of sleep disturbance and changes in sleep-wake cycle. https://doi.org/10.1289/EHP14156.

Enhancing clinical and public health interpretation of accelerometer-assessed physical activity with age-referenced values based on UK Biobank data.

BACKGROUND: Higher accelerometer-assessed volume and intensity of physical activity (PA) have been associated with a longer life expectancy but can be difficult to translate into recommended doses of PA. We aimed to: (a) improve interpretability by producing UK Biobank age-referenced centiles for PA volume and intensity; (b) inform public-health messaging by examining how adding recommended quantities of moderate and vigorous PA affect PA volume and intensity. METHODS: 92,480 UK Biobank participants aged 43-80 years with wrist-worn accelerometer data were included. Average acceleration and intensity gradient were derived as proxies for PA volume and intensity. We generated sex-specific centile curves using Generalized Additive Models for Location Scale and Shape (GAMLSS) and modeled the effect of adding moderate (walking) or vigorous (running) activity on the combined change in the volume and intensity centiles (change in PA profile). RESULTS: In men, volume was lower as age increased while intensity was lower after age 55; in women, both volume and intensity were lower as age increased. Adding 150 min of moderate PA weekly (5 × 30 min walking) increased the PA profile by 4 percentage points. Defining moderate PA as brisk walking approximately doubled the increase (9 percentage points) while 75 min of vigorous PA weekly (5 × 15 min running) trebled the increase (13 percentage points). CONCLUSION: These UK Biobank reference centiles provide a benchmark for interpretation of accelerometer data. Application of our translational methods demonstrate that meeting PA guidelines through shorter duration vigorous activity is more beneficial to the PA profile (volume and intensity) than longer duration moderate activity.

Interplay between physical activity volume and intensity with modeled life expectancy in women and men: A prospective cohort analysis.

BACKGROUND: There is a lack of research examining the interplay between objectively measured physical activity volume and intensity with life expectancy. METHODS: Individuals from UK Biobank with wrist-worn accelerometer data were included. The average acceleration and intensity gradient were extracted to describe the physical activity volume and intensity profile. Mortality data were obtained from national registries. Adjusted life expectancies were estimated using parametric flexible survival models. RESULTS: 40,953 (57.1%) women (median age = 61.9 years) and 30,820 (42.9%) men (63.1 years) were included. Over a median follow-up of 6.9 years, there were 1719 (2.4%) deaths (733 in women; 986 in men). At 60 years, life expectancy was progressively longer for higher physical activity volume and intensity profiles, reaching 95.6 years in women and 94.5 years in men at the 90th centile for both volume and intensity, corresponding to 3.4 (95% confidence interval (95%CI): 2.4-4.4) additional years in women and 4.6 (95%CI: 3.6-5.6) additional years in men compared to those at the 10th centiles. An additional 10-min or 30-min daily brisk walk was associated with 0.9 (95%CI: 0.5-1.3) and 1.4 (95%CI: 0.9-1.9) years longer life expectancy, respectively, in inactive women; and 1.4 (95%CI: 1.0-1.8) and 2.5 (95%CI: 1.9-3.1) years in inactive men. CONCLUSION: Higher physical activity volumes were associated with longer life expectancy, with a higher physical activity intensity profile further adding to a longer life. Adding as little as a 10-min brisk walk to daily activity patterns may result in a meaningful benefit to life expectancy.

Device-measured physical activity and cardiac structure by magnetic resonance.

BACKGROUND AND AIMS: Although extreme cardiac adaptions mirroring phenotypes of cardiomyopathy have been observed in endurance athletes, adaptions to high levels of physical activity within the wider population are under-explored. Therefore, in this study, associations between device-measured physical activity and clinically relevant cardiac magnetic resonance volumetric indices were investigated. METHODS: Individuals without known cardiovascular disease or hypertension were included from the UK Biobank. Cardiac magnetic resonance data were collected between 2015 and 2019, and measures of end-diastolic chamber volume, left ventricular (LV) wall thickness, and LV ejection fraction were extracted. Moderate-to-vigorous-intensity physical activity (MVPA), vigorous-intensity physical activity (VPA), and total physical activity were assessed via wrist-worn accelerometers. RESULTS: A total of 5977 women (median age and MVPA: 62 years and 46.8 min/day, respectively) and 4134 men (64 years and 49.8 min/day, respectively) were included. Each additional 10 min/day of MVPA was associated with a 0.70 [95% confidence interval (CI): 0.62, 0.79] mL/m2 higher indexed LV end-diastolic volume (LVEDVi) in women and a 1.08 (95% CI: 0.95, 1.20) mL/m2 higher LVEDVi in men. However, even within the top decile of MVPA, LVEDVi values remained within the normal ranges [79.1 (95% CI: 78.3, 80.0) mL/m2 in women and 91.4 (95% CI: 90.1, 92.7) mL/m2 in men]. Associations with MVPA were also observed for the right ventricle and the left/right atria, with an inverse association observed for LV ejection fraction. Associations of MVPA with maximum or average LV wall thickness were not clinically meaningful. Results for total physical activity and VPA mirrored those for MVPA. CONCLUSIONS: High levels of device-measured physical activity were associated with cardiac remodelling within normal ranges.

Capturing How the Accelerometer Measured Physical Activity Profile Differs in People with Diabetic Foot Ulceration.

Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, with treatment requiring offloading. This study aimed to capture how the accelerometer-assessed physical activity profile differs in those with DFUs compared to those with diabetes but without ulceration (non-DFU). Participants were requested to wear an accelerometer on their non-dominant wrist for up to 8days. Physical activity outcomes included average acceleration (volume), intensity gradient (intensity distribution), the intensity of the most active sustained (continuous) 5-120 min of activity (MXCONT), and accumulated 5-120 min of activity (MXACC). A total of 595 participants (non-DFU = 561, DFU = 34) were included in the analysis. Average acceleration was lower in DFU participants compared to non-DFU participants (21.9 mg [95%CI:21.2, 22.7] vs. 16.9 mg [15.3, 18.8], p < 0.001). DFU participants also had a lower intensity gradient, indicating proportionally less time spent in higher-intensity activities. The relative difference between DFU and non-DFU participants was greater for sustained activity (MXCONT) than for accumulated (MXACC) activity. In conclusion, physical activity, particularly the intensity of sustained activity, is lower in those with DFUs compared to non-DFUs. This highlights the need for safe, offloaded modes of activity that contribute to an active lifestyle for people with DFUs.

Footwear fit as a causal factor in diabetes-related foot ulceration: A systematic review.

AIMS: Incorrectly fitting footwear (IFF) poses a risk of trauma to at-risk feet with diabetes. The aim of this systematic review was to summarise and assess the evidence that IFF is a statistically significant cause of ulceration. METHODS: We searched PubMed, Scopus, Web of Science and Google Scholar for English-language peer-reviewed studies reporting the number or percentage of people with diabetes-related foot ulceration (DFU) attributed to wearing IFF and included a physical examination of the footwear worn. Two independent reviewers assessed the risk of bias using the Newcastle-Ottawa scale. RESULTS: 4318 results were retrieved excluding duplicates with 45 studies shortlisted. Ten studies met the inclusion criteria with most rated as fair (n = 6) or good (n = 3). There is some evidence that DFU is significantly associated with IFF, but this is limited: only 3 of 10 included studies found a statistically significant percentage of those with DFU were wearing IFF or inappropriate footwear which included fastening, material, type or fit (15.0%-93.3%). Risk of bias in these three studies ranged from 'fair' to 'poor'. IFF definitions were often unreported or heterogeneous. Only one study reported IFF-related ulcer sites: 70% were at plantar hallux/toes and 10% at plantar metatarsal heads. CONCLUSIONS: There is some evidence that IFF is a cause of DFU, but further research is needed, which defines IFF, and methodically records footwear assessment, ulcer location and physical activity. Researchers need to uncover why IFF is worn and if this is due to economic factors, a need for footwear education or other reasons.

Improving the identification of bone-specific physical activity using wrist-worn accelerometry: A cross-sectional study in 11-12-year-old Australian children.

Physical activity (PA) during childhood and adolescence is important for the accrual of maximal peak bone mass. The precise dose that benefits bone remains unclear as methods commonly used to analyze PA data are unsuitable for measuring bone-relevant PA. Using improved accelerometry methods, this study identified the amount and intensity of PA most strongly associated with bone outcomes in 11-12-year-olds. Participants (n = 770; 382 boys) underwent tibial peripheral quantitative computed tomography to assess trabecular and cortical density, endosteal and periosteal circumference and polar stress-strain index. Seven-day wrist-worn raw acceleration data averaged over 1-s epochs was used to estimate time accumulated above incremental PA intensities (50 milli-gravitational unit (mg) increments from 200 to 3000 mg). Associations between time spent above each 50 mg increment and bone outcomes were assessed using multiple linear regression, adjusted for age, sex, height, weight, maturity, socioeconomic position, muscle cross-sectional area and PA below the intensity of interest. There was a gradual increase in mean R2 change across all bone-related outcomes as the intensity increased in 50 mg increments from >200 to >700 mg. All outcomes became significant at >700 mg (R2 change = 0.6%-1.3% and p = 0.001-0.02). Any further increases in intensity led to a reduction in mean R2 change and associations became non-significant for all outcomes >1500 mg. Using more appropriate accelerometry methods (1-s epochs; no a priori application of traditional cut-points) enabled us to identify that ∼10 min/day of PA >700 mg (equivalent to running ∼10 km/h) was positively associated with pQCT-derived measures of bone density, geometry and strength in 11-12-year-olds.

Greater hepatic lipid saturation is associated with impaired glycaemic regulation in men with metabolic dysfunction-associated steatotic liver disease but is not altered by 6 weeks of exercise training.

AIMS: To examine the impact of impaired glycaemic regulation (IGR) and exercise training on hepatic lipid composition in men with metabolic dysfunction-associated steatotic liver disease (MASLD). MATERIALS AND METHODS: In Part A (cross-sectional design), 40 men with MASLD (liver proton density fat fraction [PDFF] ≥5.56%) were recruited to one of two groups: (1) normal glycaemic regulation (NGR) group (glycated haemoglobin [HbA1c] < 42 mmol∙mol-1 [<6.0%]; n = 14) or (2) IGR group (HbA1c ≥ 42 mmol∙mol-1 [≥6.0%]; n = 26). In Part B (randomized controlled trial design), participants in the IGR group were randomized to one of two 6-week interventions: (1) exercise training (EX; 70%-75% maximum heart rate; four sessions/week; n = 13) or (2) non-exercise control (CON; n = 13). Saturated (SI; primary outcome), unsaturated (UI) and polyunsaturated (PUI) hepatic lipid indices were determined using proton magnetic resonance spectroscopy. Additional secondary outcomes included liver PDFF, HbA1c, fasting plasma glucose (FPG), homeostatic model assessment of insulin resistance (HOMA-IR), peak oxygen uptake (VO2 peak), and plasma cytokeratin-18 (CK18) M65, among others. RESULTS: In Part A, hepatic SI was higher and hepatic UI was lower in the IGR versus the NGR group (p = 0.038), and this hepatic lipid profile was associated with higher HbA1c levels, FPG levels, HOMA-IR and plasma CK18 M65 levels (rs ≥0.320). In Part B, hepatic lipid composition and liver PDFF were unchanged after EX versus CON (p ≥ 0.257), while FPG was reduced and VO2 peak was increased (p ≤ 0.030). ΔVO2 peak was inversely associated with Δhepatic SI (r = -0.433) and positively associated with Δhepatic UI and Δhepatic PUI (r ≥ 0.433). CONCLUSIONS: Impaired glycaemic regulation in MASLD is characterized by greater hepatic lipid saturation; however, this composition is not altered by 6 weeks of moderate-intensity exercise training.

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality.

Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. We developed a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry. After exclusion, 1448 participant nights of data were used for training. The difference between polysomnography and the model classifications on the external validation was 34.7 min (95% limits of agreement (LoA): -37.8-107.2 min) for total sleep duration, 2.6 min for REM duration (95% LoA: -68.4-73.4 min) and 32.1 min (95% LoA: -54.4-118.5 min) for NREM duration. The sleep classifier was deployed in the UK Biobank with 100,000 participants to study the association of sleep duration and sleep efficiency with all-cause mortality. Among 66,214 UK Biobank participants, 1642 mortality events were observed. Short sleepers (<6 h) had a higher risk of mortality compared to participants with normal sleep duration of 6-7.9 h, regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.58; 95% confidence intervals (CIs): 1.19-2.11) or high sleep efficiency (HRs: 1.45; 95% CIs: 1.16-1.81). Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

Waking Up to the Importance of Sleep in Type 2 Diabetes Management: A Narrative Review.

For the first time, the latest American Diabetes Association/European Association for the Study of Diabetes (ADA/EASD) consensus guidelines have incorporated a growing body of evidence linking health outcomes associated with type 2 diabetes to the movement behavior composition over the whole 24-h day. Of particular note, the importance of sleep as a key lifestyle component in the management of type 2 diabetes is promulgated and presented using three key constructs: quantity, quality, and timing (i.e., chronotype). In this narrative review we highlight some of the key evidence justifying the inclusion of sleep in the latest consensus guidelines by examining the associations of quantity, quality, and timing of sleep with measures of glycemia, cardiovascular disease risk, and mortality. We also consider potential mechanisms implicated in the association between sleep and type 2 diabetes and provide practical advice for health care professionals about initiating conversations pertaining to sleep in clinical care. In particular, we emphasize the importance of measuring sleep in a free-living environment and provide a summary of the different methodologies and targets. In summary, although the latest ADA/EASD consensus report highlights sleep as a central component in the management of type 2 diabetes, placing it, for the first time, on a level playing field with other lifestyle behaviors (e.g., physical activity and diet), the evidence base for improving sleep (beyond sleep disorders) in those living with type 2 diabetes is limited. This review should act as a timely reminder to incorporate sleep into clinical consultations, ongoing diabetes education, and future interventions.

Feasibility of Using a GENEActiv Accelerometer with Triaxial Acceleration and Temperature Sensors to Monitor Adherence to Shoulder Sling Wear Following Surgery.

BACKGROUND: Self-reported adherence to sling wear is unreliable due to recall bias. We aim to assess the feasibility and accuracy of quantifying sling wear and non-wear utilising slings pre-fitted with a GENEActiv accelerometer that houses triaxial acceleration and temperature sensors. METHODS: Ten participants were asked to wear slings for 480 min (8 h) incorporating 180 min of non-wear time in durations varying from 5-120 min. GENEActiv devices were fitted in sutured inner sling pockets and participants logged sling donning and doffing times. An algorithm based on variability in acceleration in three axes and temperature change was developed to identify sling wear and non-wear and compared to participants' logs. RESULTS: There was no significant difference between algorithm detected non-wear duration (mean ± standard deviation = 172.0 ± 6.8 min/participant) and actual non-wear (179.7 ± 1.0 min/participant). Minute-by-minute agreement of sensor-detected wear and non-wear with participant reported wear was 97.3 ± 1.5% (range = 93.9-99.0), with mean sensitivity 94.3 ± 3.5% (range = 86.1-98.3) and specificity 99.1 ± 0.8% (range = 93.7-100). CONCLUSION: An algorithm based on accelerometer-assessed acceleration and temperature can accurately identify shoulder sling wear/non-wear times. This method may have potential for assessing whether sling wear adherence after shoulder surgeries have any bearing on patient functional outcomes.

Twenty-four-hour physical behaviour profiles across type 2 diabetes mellitus subtypes.

AIM: To investigate how 24-h physical behaviours differ across type 2 diabetes (T2DM) subtypes. MATERIALS AND METHODS: We included participants living with T2DM, enrolled as part of an ongoing observational study. Participants wore an accelerometer for 7 days to quantify physical behaviours across 24 h. We used routinely collected clinical data (age at onset of diabetes, glycated haemoglobin level, homeostatic model assessment index of beta-cell function, homeostatic model assessment index of insulin resistance, body mass index) to replicate four previously identified subtypes (insulin-deficient diabetes [INS-D], insulin-resistant diabetes [INS-R], obesity-related diabetes [OB] and age-related diabetes [AGE]), via k-means clustering. Differences in physical behaviours across the diabetes subtypes were assessed using generalized linear models, with the AGE cluster as the reference. RESULTS: A total of 564 participants were included in this analysis (mean age 63.6 ± 8.4 years, 37.6% female, mean age at diagnosis 53.1 ± 10.0 years). The proportions in each cluster were as follows: INS-D: n = 35, 6.2%; INS-R: n = 88, 15.6%; OB: n = 166, 29.4%; and AGE: n = 275, 48.8%. Compared to the AGE cluster, the OB cluster had a shorter sleep duration (-0.3 h; 95% confidence interval [CI] -0.5, -0.1), lower sleep efficiency (-2%; 95% CI -3, -1), lower total physical activity (-2.9 mg; 95% CI -4.3, -1.6) and less time in moderate-to-vigorous physical activity (-6.6 min; 95% CI -11.4, -1.7), alongside greater sleep variability (17.9 min; 95% CI 8.2, 27.7) and longer sedentary time (31.9 min; 95% CI 10.5, 53.2). Movement intensity during the most active continuous 10 and 30 min of the day was also lower in the OB cluster. CONCLUSIONS: In individuals living with T2DM, the OB subtype had the lowest levels of physical activity and least favourable sleep profiles. Such behaviours may be suitable targets for personalized therapeutic lifestyle interventions.

Accelerometer Metrics: Healthy Adult Reference Values, Associations with Cardiorespiratory Fitness, and Clinical Implications.

PURPOSE: Accelerometer-assessed physical activity (PA) can be summarized using cut-point-free or population-specific cut-point-based outcomes. We aimed to 1) examine the interrelationship between cut-point-free (intensity gradient (IG) and average acceleration (AvAcc)) and cut-point-based accelerometer metrics, 2) compare the association between cardiorespiratory fitness (CRF) and cut-point-free metrics to that with cut-point-based metrics in healthy adults aged 20 to 89 yr and patients with heart failure, and 3) provide age-, sex-, and CRF-related reference values for healthy adults. METHODS: In the COmPLETE study, 463 healthy adults and 67 patients with heart failure wore GENEActiv accelerometers on their nondominant wrist and underwent cardiopulmonary exercise testing. Cut-point-free (IG: distribution of intensity of activity across the day; AvAcc: proxy of volume of activity) and traditional (moderate-to-vigorous and vigorous activity) metrics were generated. The "interpretablePA" R-package was developed to translate findings into clinical practice. RESULTS: IG and AvAcc yield complementary information on PA with both IG ( P = 0.009) and AvAcc ( P < 0.001) independently associated with CRF in healthy individuals (adjusted R2 = 73.9%). Only IG was independently associated with CRF in patients with heart failure ( P = 0.043, adjusted R2 = 38.4%). The best cut-point-free and cut-point-based model had similar predictive value for CRF in both cohorts. We produced age- and sex-specific reference values and percentile curves for IG, AvAcc, moderate-to-vigorous PA, and vigorous PA for healthy adults. CONCLUSIONS: IG and AvAcc are strongly associated with CRF and thus indirectly with the risk of noncommunicable diseases and mortality, in healthy adults and patients with heart failure. However, unlike cut-point-based metrics, IG and AvAcc are comparable across populations. Our reference values provide a healthy age- and sex-specific comparison that may enhance the translation and utility of cut-point-free metrics in clinical practice.

The potential blunting effect of metformin and/or statin therapy on physical activity-induced associations with HbA1c in type 2 diabetes.

Highlights Our analysis indicates a potential blunting effect of metformin and/or statin therapy on physical activity-induced associations with HbA1c. The benefit of daily physical activity on glycemic control in people with type 2 diabetes is potentially more apparent in those prescribed neither metformin nor statin therapy. As physical activity is rarely prescribed in isolation of other background medications used to manage type 2 diabetes, the results of this analysis may help to maximize interventions delivered through routine clinical care, while allowing for personalization in prescribed physical activity and pharmacotherapy.

Walking pace and the time between the onset of noncommunicable diseases and mortality: a UK Biobank prospective cohort study.

PURPOSE: To estimate time spent in various cardiovascular disease (CVD) and cancer states, according to self-reported walking pace. METHODS: In total, 391,744 UK Biobank participants were included (median age = 57 years; 54.7% women). Data were collected 2006-2010, with follow-up collected in 2021. Usual walking pace was self-defined as slow, steady, average, or brisk. Multistate modeling determined the transition rate and mean sojourn time in and across three different states (healthy, CVD or cancer, and death) upon a time horizon of 10 years. RESULTS: The mean sojourn time in the healthy state was longer, while that in the CVD or cancer state was shorter in individuals reporting an average or brisk walking pace (vs. slow). A 75-year-old woman reporting a brisk walking pace spent, on average, 8.4 years of the next 10 years in a healthy state; an additional 8.0 (95% CI: 7.3, 8.7) months longer than a 75-year-old woman reporting a slow walking pace. This corresponded to 4.3 (3.7, 4.9) fewer months living with CVD or cancer. Similar results were seen in men. CONCLUSIONS: Adults reporting an average or brisk walking pace at baseline displayed a lower transition to disease development and a greater proportion of life lived without CVD or cancer. AVAILABILITY OF DATA AND MATERIALS: Research was conducted using the UK Biobank resource under Application #33266. The UK Biobank resource can be accessed by researchers on application. Variables derived for this study have been returned to the UK Biobank for future applicants to request. No additional data are available.

Self-reported walking pace and 10-year cause-specific mortality: A UK biobank investigation.

OBJECTIVE: To investigate associations of self-reported walking pace (SRWP) with relative and absolute risks of cause-specific mortality. PATIENTS AND METHODS: In 391,652 UK Biobank participants recruited in 2006-2010, we estimated sex- and cause-specific (cardiovascular disease [CVD], cancer, other causes) mortality hazard ratios (HRs) and 10-year mortality risks across categories of SRWP (slow, average, brisk), accounting for confounders and competing risk. Censoring occurred in September 30, 2021 (England, Wales) and October 31, 2021 (Scotland). RESULTS: Over a median follow-up of 12.6 years, 22,413 deaths occurred. In women, the HRs comparing brisk to slow SRWP were 0.74 (95% CI: 0.67, 0.82), 0.40 (0.33, 0.49), and 0.29 (0.26, 0.32) for cancer, CVD, and other causes of death, respectively, and 0.71 (0.64, 0.78), 0.38 (0.33, 0.44), and 0.29 (0.26, 0.32) in men. Compared to CVD, HRs were greater for other causes (women: 39.6% [6.2, 72.9]; men: 31.6% [9.8, 53.5]) and smaller for cancer (-45.8% [-58.3, -33.2] and - 45.9% [-54.8, -36.9], respectively). For all causes in both sexes, the 10-year mortality risk was higher in slow walkers, but varied across sex, age, and cause, resulting in different risk reductions comparing brisk to slow: the largest were for other causes of death at age 75 years [women: -6.8% (-7.7, -5.8); men: -9.5% (-10.6, -8.4)]. CONCLUSION: Compared to slow walkers, brisk SRWP was associated with reduced cancer (smallest reduction), CVD, and other (largest) causes of death and may therefore be a useful clinical predictive marker. As absolute risk reductions varied across age, cause, and SRWP, certain groups may particularly benefit from interventions to increase SRWP.

Differences in Dietary Intake, Eating Occasion Timings and Eating Windows between Chronotypes in Adults Living with Type 2 Diabetes Mellitus.

Chronotype studies investigating dietary intake, eating occasions (EO) and eating windows (EW) are sparse in people with type 2 Diabetes mellitus (T2DM). This analysis reports data from the CODEC study. The Morningness-Eveningness questionnaire (MEQ) assessed chronotype preference. Diet diaries assessed dietary intake and temporal distribution. Regression analysis assessed whether dietary intake, EW, or EO differed by chronotype. 411 participants were included in this analysis. There were no differences in energy, macronutrient intake or EW between chronotypes. Compared to evening chronotypes, morning and intermediate chronotypes consumed 36.8 (95% CI: 11.1, 62.5) and 20.9 (95% CI: -2.1, 44.1) fewer milligrams of caffeine per day, respectively. Evening chronotypes woke up over an hour and a half later than morning (01:36 95% CI: 01:09, 02:03) and over half an hour later than intermediate chronotypes (00:45 95% CI: 00:21; 01:09. Evening chronotypes went to sleep over an hour and a half later than morning (01:48 95% CI: 01:23; 02:13) and an hour later than intermediate chronotypes (01:07 95% CI: 00:45; 01:30). Evening chronotypes' EOs and last caffeine intake occurred later but relative to their sleep timings. Future research should investigate the impact of chronotype and dietary temporal distribution on glucose control to optimise T2DM interventions.

Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health.

Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.