Bidirectional 10-year associations of accelerometer-measured sedentary behavior and activity categories with weight among middle-aged adults

Identification of potential mediators of the relationship between body mass index and colorectal cancer: a Mendelian randomization analysis

BACKGROUND

Colorectal cancer (CRC) is the third-most-common cancer worldwide and its rates are increasing. Elevated body mass index (BMI) is an established risk factor for CRC, although the molecular mechanisms behind this association remain unclear. Using the Mendelian randomization (MR) framework, we aimed to investigate the mediating effects of putative biomarkers and other CRC risk factors in the association between BMI and CRC.

METHODS

We selected as mediators biomarkers of established cancer-related mechanisms and other CRC risk factors for which a plausible association with obesity exists, such as inflammatory biomarkers, glucose homeostasis traits, lipids, adipokines, insulin-like growth factor 1 (IGF1), sex hormones, 25-hydroxy-vitamin D, smoking, physical activity (PA) and alcohol consumption. We used inverse-variance weighted MR in the main univariable analyses and performed sensitivity analyses (weighted-median, MR-Egger, Contamination Mixture). We used multivariable MR for the mediation analyses.

RESULTS

Genetically predicted BMI was positively associated with CRC risk [odds ratio per SD (5 kg/m2) = 1.17, 95% CI: 1.08-1.24, P-value = 1.4 × 10-5] and robustly associated with nearly all potential mediators. Genetically predicted IGF1, fasting insulin, low-density lipoprotein cholesterol, smoking, PA and alcohol were associated with CRC risk. Evidence for attenuation was found for IGF1 [explained 7% (95% CI: 2-13%) of the association], smoking (31%, 4-57%) and PA (7%, 2-11%). There was little evidence for pleiotropy, although smoking was bidirectionally associated with BMI and instruments were weak for PA.

CONCLUSIONS

The effect of BMI on CRC risk is possibly partly mediated through plasma IGF1, whereas the attenuation of the BMI-CRC association by smoking and PA may reflect confounding and shared underlying mechanisms rather than mediation.

Distilling causality between physical activity traits and obesity via Mendelian randomization

BACKGROUND

Whether obesity is a cause or consequence of low physical activity levels and more sedentary time has not yet been fully elucidated. Better instrumental variables and a more thorough consideration of potential confounding variables that may influence the causal inference between physical activity and obesity are needed.

METHODS

Leveraging results from our recent genome-wide association study for leisure time moderate-to-vigorous intensity (MV) physical activity and screen time, we here disentangle the causal relationships between physical activity, sedentary behavior, education-defined by years of schooling-and body mass index (BMI), using multiple univariable and multivariable Mendelian Randomization (MR) approaches.

RESULTS

Univariable MR analyses suggest bidirectional causal effects of physical activity and sedentary behavior with BMI. However, multivariable MR analyses that take years of schooling into account suggest that more MV physical activity causes a lower BMI, and a higher BMI causes more screen time, but not vice versa. In addition, more years of schooling causes higher levels of MV physical activity, less screen time, and lower BMI.

CONCLUSIONS

In conclusion, our results highlight the beneficial effect of education on improved health and suggest that a more physically active lifestyle leads to lower BMI, while sedentary behavior is a consequence of higher BMI.

Paradoxical Associations of Occupational and Nonoccupational Sedentary Behavior With Cardiovascular Disease Risk Measures in Desk Workers

OBJECTIVES

We assessed sedentary behavior (SB) patterns and examined its associations, by domain, with cardiovascular disease (CVD) risk measures in desk workers ( N = 273).

METHODS

Sedentary behavior was measured by activPAL3 and partitioned into occupational and nonoccupational SB. Cardiovascular disease risk measures included blood pressure, pulse wave velocity, heart rate, and heart rate variability. Paired t tests evaluated patterns of SB across domains. Linear regressions estimated associations of occupational and nonoccupational SB with CVD risk measures.

RESULTS

Participants spent 69% of their time in SB; higher proportions were accumulated during occupational versus nonoccupational time. Higher all-domain SB was only associated with higher pulse wave velocity. Paradoxically, greater nonoccupational SB unfavorably associated with CVD risk measures, while higher occupational SB favorably correlated to CVD risk measures.

CONCLUSIONS

Observed paradoxical associations suggest that domain should be considered in efforts to improve cardiovascular health by reducing SB.

Device-measured physical activity and sedentary time in a national sample of Luxembourg residents: the ORISCAV-LUX 2 study

BACKGROUND

Existing information about population physical activity (PA) levels and sedentary time in Luxembourg are based on self-reported data.

METHODS

This observational study included Luxembourg residents aged 18-79y who each provided ≥4 valid days of triaxial accelerometry in 2016-18 (n=1122). Compliance with the current international PA guideline (≥150 min moderate-to-vigorous PA (MVPA) per week, irrespective of bout length) was quantified and variability in average 24h acceleration (indicative of PA volume), awake-time PA levels, sedentary time and accumulation pattern were analysed by linear regression. Data were weighted to be nationally representative.

RESULTS

Participants spent 51% of daily time sedentary (mean (95% confidence interval (CI)): 12.1 (12.0 to 12.2) h/day), 11% in light PA (2.7 (2.6 to 2.8) h/day), 6% in MVPA (1.5 (1.4 to 1.5) h/day), and remaining time asleep (7.7 (7.6 to 7.7) h/day). Adherence to the PA guideline was high (98.1%). Average 24h acceleration and light PA were higher in women than men, but men achieved higher average accelerations across the most active periods of the day. Women performed less sedentary time and shorter sedentary bouts. Older participants (aged ≥55y) registered a lower average 24h acceleration and engaged in less MVPA, more sedentary time and longer sedentary bouts. Average 24h acceleration was higher in participants of lower educational attainment, who also performed less sedentary time, shorter bouts, and fewer bouts of prolonged sedentariness. Average 24h acceleration and levels of PA were higher in participants with standing and manual occupations than a sedentary work type, but manual workers registered lower average accelerations across the most active periods of the day. Standing and manual workers accumulated less sedentary time and fewer bouts of prolonged sedentariness than sedentary workers. Active commuting to work was associated with higher average 24h acceleration and MVPA, both of which were lower in participants of poorer self-rated health and higher weight status. Obesity was associated with less light PA, more sedentary time and longer sedentary bouts.

CONCLUSIONS

Adherence to recommended PA is high in Luxembourg, but half of daily time is spent sedentary. Specific population subgroups will benefit from targeted efforts to replace sedentary time with PA.

Compositional analysis of movement behaviors' association on high-sensitivity c-reactive protein: the Jackson heart study

PURPOSE

Movement behaviors (i.e. physical activity [PA], sedentary behavior [SB], and sleep) are intrinsically codependent, an issue resolved using compositional data analysis (CoDA). High-sensitivity C-reactive protein (hs-CRP) is a nonspecific inflammatory marker positively associated with cardiovascular diseases and affected by movement behaviors. Examine the relation between movement behaviors using CoDA and how time reallocation between two movement behaviors was associated with hs-CRP concentration.

METHODS

The Jackson Heart Study was designed to investigate cardiovascular disease risk factors among African American participants in the Jackson, MS area. PA and sleep were self-reported with SB calculated as the remaining time in the day.

RESULTS

The median untransformed hs-CRP concentration was 0.28 mg·dL^-1 (interquartile range; 0.11, 0.61). Reallocating 15 minutes of PA with SB, the hypothetical change in log hs-CRP concentration was 0.08 mg·dL^-1 (95% CIs; 0.04, 0.11) greater than the average log hs-CRP concentration. Substituting 15 minutes of SB or sleep with PA was associated with a hypothetical change in log hs-CRP concentration difference of -0.05 mg·dL^-1 (-0.08, -0.03) and -0.06 mg·dL^-1 (-0.08, -0.03), respectively. Reallocations between SB and sleep were not associated with the hypothetical difference in log hs-CRP concentration.

CONCLUSIONS

Modeling estimates suggest replacing 15 minutes of SB with PA is associated with lower inflammation.

Ten-Year Changes in Television Viewing and Physical Activity Are Associated With Concurrent 10-Year Change in Pericardial Adiposity: The Coronary Artery Risk Development in Young Adults Study

BACKGROUND

Longitudinal association of television (TV) viewing and moderate- to vigorous-intensity physical activity (MVPA) with pericardial adipose tissue (PAT) is unclear.

METHODS

We studied Coronary Artery Risk Development in Young Adults Study participants transitioning from early to middle age at Coronary Artery Risk Development in Young Adults (CARDIA) exam years 15 (2000-2001; N = 1975, mean age = 40.4, 55.4% women, 45.3% Black) and 25 (2010-2011). TV viewing (in hours per day) and MVPA (in exercise units) were measured using a self-report questionnaire. PAT volume (in milliliters) was measured using computed tomography. Multivariable linear regression was used to examine the associations of tertiles of 10-year change (years 25-15) in TV viewing and MVPA with a concurrent change in PAT with adjustments for covariates.

RESULTS

Participants in the highest tertile of 10-year increase in TV viewing had a greater increase in PAT (β = 2.96 mL, P < .01). Participants in both middle (β = -3.93 mL, P < .01) and highest (β = -6.22 mL, P < .01) tertiles of 10-year changes in MVPA had smaller mean increases in PAT over 10 years when compared with the lowest tertile in fully adjusted models.

CONCLUSIONS

Reducing or maintaining early-midlife levels of TV viewing and increasing MVPA may be associated with less PAT accumulation with age.

Patterns of Accelerometer-Measured Physical Activity and Health Outcomes in Adults: A Systematic Review

PURPOSE

The aim of this study was to systematically review the literature on accelerometer-measured physical activity and health outcomes in adults.

METHODS

Eight electronic databases were searched for relevant articles published up to March 2021. Only population-based studies of adults (age ≥18 yr) that directly compared two or more categories of physical activity (i.e., bout duration, intensity, and daily/weekly frequency) with a health outcome (e.g., mortality, cardiometabolic, healthy aging, depression, sleep, and brain structure) were included.

RESULTS

Of the 15,923 publications retrieved, 52 articles were included. Twenty-eight studies directly compared the associations between physical activity accumulated in different bout durations, 31 studies directly compared the associations between physical activity accumulated in different intensities, and 9 studies directly compared the associations between the effects of varying daily and weekly frequencies of physical activity, with health outcomes. Most showed no differences in relationships with health outcomes when physical activity was accumulated in short (<10-min) or long (≥10-min) bouts. Overall, there were no differences in the relationships with most health outcomes when different intensities and daily/weekly frequencies were compared. However, in most studies, researchers did not adjust their analyses for total volume of physical activity. Moreover, variations in researcher-driven decisions about data collection and processing methods made it difficult to compare study findings.

CONCLUSIONS

These findings suggest that physical activity accumulated in many patterns of bout duration, intensity, or daily/weekly frequency is associated with a range of beneficial health outcomes in adults. Lack of adjustment for total volume of physical activity in most studies and inconsistent methods for defining components of physical activity prevent firm conclusions about which specific patterns of bout duration, intensity, and daily/weekly frequency are most important for health benefits.

Integrating a physical activity coaching intervention into diabetes care: a mixed-methods evaluation of a pilot pragmatic trial

Physical activity (PA) counseling is under-utilized in primary care for patients with type 2 diabetes mellitus (T2D), despite improving important health outcomes, including physical function. We adapted evidence-based PA counseling programs to primary care patients, staff, and leader's needs, resulting in "Be ACTIVE" comprised of shared PA tracker data (FitBit©), six theory-informed PA coaching calls, and three in-person clinician visits. In a pilot randomized pragmatic trial, we evaluated the feasibility, acceptability, and effectiveness of Be ACTIVE. Sedentary patients with T2D were randomized to Be ACTIVE versus an enhanced control condition. Mixed methods assessments of feasibility and acceptability included costs. Objective pilot effectiveness outcomes included PA (primary outcome, accelerometer steps/week), the Short Physical Performance Battery (SPPB) physical function measure, and behavioral PA predictors. Fifty patients were randomized to Be ACTIVE or control condition. Acceptability was >90% for patients and clinic staff. Coaching and PA tracking costs of ~$90/patient met Medicare reimbursement criteria. Pre-post PA increased by ~11% (Be ACTIVE) and ~6% in controls (group difference: 1574 ± 4391 steps/week, p = .72). As compared to controls, Be ACTIVE participants significantly improved SPPB (0.9 ± 0.3 vs. -0.1 ± 0.3, p = .01, changes >0.5 points prevent falls clinically), and PA predictors of self-efficacy (p = .02) and social-environmental support (p < .01). In this pilot trial, Be ACTIVE was feasible and highly acceptable to stakeholders and yielded significant improvements in objective physical function consistent with lower fall risk, whereas PA changes were less than anticipated. Be ACTIVE may need additional adaptation or a longer duration to improve PA outcomes.

The physical activity health paradox and risk factors for cardiovascular disease: A cross-sectional compositional data analysis in the Copenhagen City Heart Study

Background

Studies indicate that physical activity during leisure and work have opposite associations with cardiovascular disease (CVD) risk factors, referred to as the physical activity health paradox. We investigated how sedentary behaviour and physical activity types during leisure and work are associated with systolic blood pressure (SBP), waist circumference (WC), and low-density lipoprotein cholesterol (LDL-C) in an adult general population sample using compositional data analysis.

Methods

Participants wore accelerometers for 7 days (right thigh and iliac crest; 24 h/day) and had their SBP, WC, and LDL-C measured. Accelerometer data was analysed using the software Acti4 to derive daily time spent in sedentary behaviour and physical activity types. The measure of association was quantified by reallocating time between sedentary behaviour and 1) walking, and 2) high-intensity physical activity (HIPA; sum of climbing stairs, running, cycling, and rowing), during both domains.

Results

In total, 652 participants were included in the analyses (median wear time: 6 days, 23.8 h/day). During leisure, the results indicated that less sedentary behaviour and more walking or more HIPA was associated with lower SBP, while during work, the findings indicated an association with higher SBP. During both domains, the findings indicated that less sedentary behaviour and more HIPA was associated with a smaller WC and lower LDL-C. However, the findings indicated less sedentary behaviour and more walking to be associated with a larger WC and higher LDL-C, regardless of domain.

Conclusions

During leisure, less sedentary behaviour and more walking or HIPA seems to be associated with a lower SBP, but, during work, it seems to be associated with a higher SBP. No consistent differences between domains were observed for WC and LDL-C. These findings highlight the importance of considering the physical activity health paradox, at least for some risk factors for CVD.

Mendelian randomization suggests a bidirectional, causal relationship between physical inactivity and adiposity

Physical inactivity and increased sedentary time are associated with excess weight gain in observational studies. However, some longitudinal studies indicate reverse causality where weight gain leads to physical inactivity and increased sedentary time. As observational studies suffer from reverse causality, it is challenging to assess the true causal directions. Here, we assess the bidirectional causality between physical inactivity, sedentary time, and adiposity by bidirectional Mendelian randomization analysis. We used results from genome-wide association studies for accelerometer-based physical activity and sedentary time in 91,105 individuals and for body mass index (BMI) in 806,834 individuals. We implemented Mendelian randomization using CAUSE method that accounts for pleiotropy and sample overlap using full genome-wide data. We also applied inverse variance-weighted, MR-Egger, weighted median, and weighted mode methods using genome-wide significant variants only. We found evidence of bidirectional causality between sedentary time and BMI: longer sedentary time was causal for higher BMI [beta (95% CI) from CAUSE method: 0.11 (0.02, 0.2), p = 0.02], and higher BMI was causal for longer sedentary time (0.13 (0.08, 0.17), p = 6.3 x 10^-4). Our analyses suggest that higher moderate and vigorous physical activity are causal for lower BMI (moderate: –0.18 (-0.3,–0.05), p = 0.006; vigorous: –0.16 (-0.24,–0.08), p = 3.8 × 10^-4), but indicate that the association between higher BMI and lower levels of physical activity is due to horizontal pleiotropy. The bidirectional, causal relationship between sedentary time and BMI suggests that decreasing sedentary time is beneficial for weight management, but also that targeting adiposity may lead to additional health benefits by reducing sedentary time.

Risk factors relate to the variability of health outcomes as well as the mean: A GAMLSS tutorial

Background:

Risk factors or interventions may affect the variability as well as the mean of health outcomes. Understanding this can aid aetiological understanding and public health translation, in that interventions which shift the outcome mean and reduce variability are typically preferable to those which affect only the mean. However, most commonly used statistical tools do not test for differences in variability. Tools that do have few epidemiological applications to date, and fewer applications still have attempted to explain their resulting findings. We thus provide a tutorial for investigating this using GAMLSS (Generalised Additive Models for Location, Scale and Shape).

Methods:

The 1970 British birth cohort study was used, with body mass index (BMI; N = 6007) and mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale; N = 7104) measured in midlife (42–46 years) as outcomes. We used GAMLSS to investigate how multiple risk factors (sex, childhood social class, and midlife physical inactivity) related to differences in health outcome mean and variability.

Results:

Risk factors were related to sizable differences in outcome variability—for example males had marginally higher mean BMI yet 28% lower variability; lower social class and physical inactivity were each associated with higher mean and higher variability (6.1% and 13.5% higher variability, respectively). For mental wellbeing, gender was not associated with the mean while males had lower variability (–3.9%); lower social class and physical inactivity were each associated with lower mean yet higher variability (7.2% and 10.9% higher variability, respectively).

Conclusions:

The results highlight how GAMLSS can be used to investigate how risk factors or interventions may influence the variability in health outcomes. This underutilised approach to the analysis of continuously distributed outcomes may have broader utility in epidemiologic, medical, and psychological sciences. A tutorial and replication syntax is provided online to facilitate this (https://osf.io/5tvz6/).

Funding:

DB is supported by the Economic and Social Research Council (grant number ES/M001660/1), The Academy of Medical Sciences / Wellcome Trust (“Springboard Health of the Public in 2040” award: HOP001/1025); DB and LW are supported by the Medical Research Council (MR/V002147/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Contributions of changes in physical activity, sedentary time, diet and body weight to changes in cardiometabolic risk

Background

Increased physical activity (PA), reduced time spent sedentary (SED), healthier diet and reduced body weight may all have a positive impact on cardiometabolic risk. The relative importance of change in each of these variables on cardiometabolic risk, however, is unclear. We therefore sought to investigate the relative contributions of changes in PA, SED, diet and body weight on cardiometabolic risk.

Methods

This is a secondary analysis of data collected from the EuroFIT randomised controlled trial, which was a 12-week group-based lifestyle intervention for overweight middle-aged men delivered by coaches in football club stadia aiming to improve PA, SED, diet, and body weight. PA and SED were assessed by accelerometry, diet using the Dietary Instrument for Nutrition Education (DINE). An overall cardiometabolic risk score was derived from combining z-scores for glucose, HbA1c, insulin, lipids and blood pressure. In total, 707 men (from the overall cohort of 1113) with complete data for these variables at baseline and 12-month follow-up were included in the multivariable linear regression analyses.

Results

In multivariable analyses, change in number of steps (explaining 5.1% of R²) and dietary factors (less alcohol, fatty and sugary food, and more fruit and vegetables) (together explaining 4.5% of R²), but not changes in standing time or SED, were significantly associated with change in body weight. Changes in number of steps (R² = 1.7%), fatty food score (R² = 2.4%), and sugary food score (R² = 0.4%) were significantly associated with change in cardiometabolic risk score in univariable models. However, in multivariable models which included changes in weight as well as changes in steps and dietary variables, change in weight explained a substantially larger proportion of the change in cardiometabolic risk score, explaining 14.1% of R² (out of an overall model R² of 19.0%). When baseline (as well as change) values were also included in the model, 38.8% of R² for change in cardiometabolic risk score was explained overall, with 14.1% of R² still explained by change in weight.

Conclusion

Change in body weight, together with baseline cardiometabolic risk explained most of the change in cardiometabolic risk. Thus, the benefits of increasing physical activity and improving diet on cardiometabolic risk appear to act largely via an effect on changes in body weight.

Trial registration

International Standard Randomised Controlled Trials, ISRCTN-81935608. Registered 06052015. https://www.isrctn.com/ISRCTN81935608?q=&filters=recruitmentCountry:Portugal&sort=&offset=7&totalResults=92&page=1&pageSize=10&searchType=basic-search

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-021-01237-1.

Correlates of screen-based behaviors among adults from the 2019 Brazilian National Health Survey

We aimed to investigate correlates of TV viewing and other types of screen-based behaviors in a nationally representative sample of Brazilian adults. In the 2019 Brazilian National Health Survey (including 88,509 adults), TV viewing time and other types of screen behaviors (computer, tablet, and cellphone use) were self-reported and different geographical, sociodemographic, behavioral, and health status factors were investigated as potential correlates. Multinomial logistic regression models were used for the main analyses. Living in capital cities, urban areas, being unemployed, high consumption of soft drinks, obesity, and elevated depressive symptoms were each associated with more TV viewing and more time using other types of screens. There were differential associations between TV viewing and the use of other types of screen across age and socioeconomic variables. For instance, younger adults have a more diverse portfolio of screen time than older adults. To conclude, levels of screen-based behaviors vary by geographical, sociodemographic, behavioral, and health status characteristics. Interventions should focus on high-risk population groups and may benefit from targeting specific sedentary behaviors of interest.

Non-linear interaction between physical activity and polygenic risk score of body mass index in Danish and Russian populations

Body mass index (BMI) is a highly heritable polygenic trait. It is also affected by various environmental and behavioral risk factors. We used a BMI polygenic risk score (PRS) to study the interplay between the genetic and environmental factors defining BMI. First, we generated a BMI PRS that explained more variance than a BMI genetic risk score (GRS), which was using only genome-wide significant BMI-associated variants (R² = 13.1% compared to 6.1%). Second, we analyzed interactions between BMI PRS and seven environmental factors. We found a significant interaction between physical activity and BMI PRS, even when the well-known effect of the FTO region was excluded from the PRS, using a small dataset of 6,179 samples. Third, we stratified the study population into two risk groups using BMI PRS. The top 22% of the studied populations were included in a high PRS risk group. Engagement in self-reported physical activity was associated with a 1.66 kg/m² decrease in BMI in this group, compared to a 0.84 kg/m² decrease in BMI in the rest of the population. Our results (i) confirm that genetic background strongly affects adult BMI in the general population, (ii) show a non-linear interaction between BMI genetics and physical activity, and (iii) provide a standardized framework for future gene-environment interaction analyses.

Bidirectional associations of accelerometer-derived physical activity and stationary behavior with self-reported mental and physical health during midlife

Background

Moderate-to-vigorous intensity physical activity (MVPA) is associated with favorable self-rated mental and physical health. Conversely, poor self-rated health in these domains could precede unfavorable shifts in activity. We evaluated bidirectional associations of accelerometer-estimated time spent in stationary behavior (SB), light intensity physical activity (LPA), and MVPA with self-rated health over 10 years in in the CARDIA longitudinal cohort study.

Methods

Participants (n = 894, age: 45.1 ± 3.5; 63% female; 38% black) with valid accelerometry wear and self-rated health at baseline (2005–6) and 10-year follow-up (2015–6) were included. Accelerometry data were harmonized between exams and measured mean total activity and duration (min/day) in SB, LPA, and MVPA; duration (min/day) in long-bout and short-bout SB (≥30 min vs. < 30 min) and MVPA (≥10 min vs. < 10 min) were also quantified. The Short-Form 12 Questionnaire measured both a mental component score (MCS) and physical component score (PCS) of self-rated health (points). Multivariable linear regression associated baseline accelerometry variables with 10-year changes in MCS and PCS. Similar models associated baseline MCS and PCS with 10-year changes in accelerometry measures.

Results

Over 10-years, average (SD) MCS increased 1.05 (9.07) points, PCS decreased by 1.54 (7.30) points, and activity shifted toward greater SB and less mean total activity, LPA, and MVPA (all p < 0.001). Only baseline short-bout MVPA was associated with greater 10-year increases in MCS (+ 0.92 points, p = 0.021), while baseline mean total activity, MVPA, and long-bout MVPA were associated with greater 10-year changes in PCS (+ 0.53 to + 1.47 points, all p < 0.005). In the reverse direction, higher baseline MCS and PCS were associated with favorable 10-year changes in mean total activity (+ 9.75 cpm, p = 0.040, and + 15.66 cpm, p < 0.001, respectively) and other accelerometry measures; for example, higher baseline MCS was associated with − 13.57 min/day of long-bout SB (p < 0.001) and higher baseline PCS was associated with + 2.83 min/day of MVPA (p < 0.001) in fully adjusted models.

Conclusions

The presence of bidirectional associations between SB and activity with self-rated health suggests that individuals with low overall activity levels and poor self-rated health are at high risk for further declines and supports intervention programming that aims to dually increase activity levels and improve self-rated health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-021-01145-4.

Small Airway Dysfunction Links Asthma Severity with Physical Activity and Symptom Control

BACKGROUND

Little is known about the role of small airway dysfunction (SAD) and its complex relation with asthma control and physical activity (PA).

OBJECTIVE

To investigate the interrelations among SAD, risk factors for asthma severity, symptom control, and PA.

METHODS

We assessed SAD by impulse oscillometry and other sophisticated lung function measures including inert gas washout in adults with asthma (mild to moderate, n = 140; severe, n = 128) and 69 healthy controls from the All Age Asthma Cohort. We evaluated SAD prevalence and its interrelation with risk factors for asthma severity (older age, obesity, and smoking), type 2 inflammation (sputum and blood eosinophils, fractional exhaled nitric oxide), systemic inflammation (high-sensitivity C-reactive protein), asthma control (AC), and PA (accelerometer for 1 week). We applied a clinical model based on structural equation modeling that integrated causal pathways among these clinical variables.

RESULTS

The prevalence of SAD ranged from 75% to 90% in patients with severe asthma and from 53% to 64% in mild to moderate asthma. Severe SAD was associated with poor AC and low PA. Structural equation modeling indicated that age, obesity, obesity-related systemic inflammation, T2 inflammation, and smoking are independent predictors of SAD. Small airway dysfunction was the main determinant factor of AC, which in turn affected PA. Obesity affected AC directly and through its contribution to SAD and low PA. In addition, PA had bidirectional associations with obesity, SAD, and AC. Structural equation modeling also indicated interrelations among distal airflow limitation, air trapping, and ventilation heterogeneity.

CONCLUSIONS

Small airway dysfunction is a highly prevalent key feature of asthma that interrelates a spectrum of distal lung function abnormalities with risk factors for asthma severity, asthma control, and physical activity.

Use of Connected Technologies to Assess Barriers and Stressors for Age and Disability-Friendly Communities

Background: The benefits of engaging in outdoor physical activity are numerous for older adults. However, previous work on outdoor monitoring of physical activities did not sufficiently identify how older adults characterize and respond to diverse elements of urban built environments, including structural characteristics, safety attributes, and aesthetics.

Objective: To synthesize emerging multidisciplinary trends on the use of connected technologies to assess environmental barriers and stressors among older adults and for persons with disability.

Methods: A multidisciplinary overview and literature synthesis.

Results: First, we review measurement and monitoring of outdoor physical activity in community environments and during transport using wearable sensing technologies, their contextualization and using smartphone-based applications. We describe physiological responses (e.g., gait patterns, electrodermal activity, brain activity, and heart rate), stressors and physical barriers during outdoor physical activity. Second, we review the use of visual data (e.g., Google street images, Street score) and machine learning algorithms to assess physical (e.g., walkability) and emotional stressors (e.g., stress) in community environments and their impact on human perception. Third, we synthesize the challenges and limitations of using real-time smartphone-based data on driving behavior, incompatibility with software data platforms, and the potential for such data to be confounded by environmental signals in older adults. Lastly, we summarize alternative modes of transport for older adults and for persons with disability.

Conclusion: Environmental design for connected technologies, interventions to promote independence and mobility, and to reduce barriers and stressors, likely requires smart connected age and disability-friendly communities and cities.

Objectively Measured Sedentary Behavior and Physical Activity Across 3 Trimesters of Pregnancy: The Monitoring Movement and Health Study

BACKGROUND

Though moderate- to vigorous-intensity physical activity is recommended, limited research exists on sedentary behavior (SED) during pregnancy.

METHODS

The authors conducted a prospective cohort study to describe objectively measured patterns of SED and activity during each trimester of pregnancy. Women wore thigh- (activPAL3) and waist-mounted (ActiGraph GT3X) activity monitors. SED and activity were compared across trimesters using likelihood ratio tests and described using group-based trajectories. Exploratory analyses associated SED and activity trajectories with adverse pregnancy outcomes and excessive gestational weight gain.

RESULTS

Pregnant women (n = 105; mean [SD] age = 31 [5] y; prepregnancy body mass index = 26.2 [6.6] kg/m2) had mean SED of 9.7, 9.5, and 9.5 hours per day (P = .062) across trimesters, respectively. Some activities differed across trimesters: standing (increased, P = .01), stepping (highest in second trimester, P = .04), steps per day (highest in second trimester, P = .008), and moderate- to vigorous-intensity physical activity (decreased, P < .001). Prolonged SED (bouts ≥ 30 min) and bouted moderate- to vigorous-intensity physical activity (≥10 min) were stable (P > .05). In exploratory analyses, higher SED and lower standing, stepping, and steps per day trajectories were associated with increased odds of adverse pregnancy outcomes (P < .05). No trajectories were associated with excessive gestational weight gain.

CONCLUSIONS

Pregnant women exhibited stable SED of nearly 10 hours per day across pregnancy. Future research evaluating SED across pregnancy and adverse pregnancy outcome risk is warranted.

Association of sedentary time with blood pressure in women of reproductive age

While the beneficial impact of moderate-vigorous physical activity (MVPA) on blood pressure is well-understood, the relationship between sedentary time (ST) and blood pressure is less clear. We aimed to evaluate the associations between ST and BP in reproductive-age women. This cross-sectional analysis consisted of 431 women enrolled in the Placenta as a Window to Maternal Microvascular Disease Risk study at Magee-Womens Hospital. Blood pressure and self-reported physical activity and ST were collected 8-10 years after delivery at study enrollment. Logistic and linear regression models examined associations between ST and blood pressure and adjusted for MVPA. Women with the highest amount of ST were less likely to be normotensive and more likely to have elevated blood pressure and Stage II hypertension (p = 0.02). Each additional hour of ST was associated with an increased risk of Stage II hypertension (OR 1.12 [1.01-1.24]) and higher systolic blood pressure (0.45 mmHg [0.08-0.82]), diastolic blood pressure (0.29 mmHg [0.02-0.56]), and mean arterial pressure (0.34 mmHg [0.05-0.63]), after adjustment for covariates. This relationship was more apparent in women who participated in less MVPA (bottom 50th percentile) versus more MVPA (top 50th percentile). ST is associated with higher blood pressure, particularly in women who engage in less aerobic activity, and could serve as an important intervention target for reducing blood pressure and hypertension during the reproductive years.

Can we walk away from cardiovascular disease risk or do we have to 'huff and puff'? A cross-sectional compositional accelerometer data analysis among adults and older adults in the Copenhagen City Heart Study

Background

It is unclear whether walking can decrease cardiovascular disease (CVD) risk or if high intensity physical activity (HIPA) is needed, and whether the association is modified by age. We investigated how sedentary behaviour, walking, and HIPA, were associated with systolic blood pressure (SBP), waist circumference (WC), and low-density lipoprotein cholesterol (LDL-C) among adults and older adults in a general population sample using compositional data analysis. Specifically, the measure of association was quantified by reallocating time between sedentary behaviour and 1) walking, and 2) HIPA.

Methods

Cross-sectional data from the fifth examination of the Copenhagen City Heart Study was used. Using the software Acti4, we estimated daily time spent in physical behaviours from accelerometer data worn 24 h/day for 7 days (i.e., right frontal thigh and iliac crest; median wear time: 6 days, 23.8 h/day). SBP, WC, and LDL-C were measured during a physical examination. Inclusion criteria were ≥ 5 days with ≥16 h of accelerometer recordings per day, and no use of antihypertensives, diuretics or cholesterol lowering medicine. The 24-h physical behaviour composition consisted of sedentary behaviour, standing, moving, walking, HIPA (i.e., sum of climbing stairs, running, cycling, and rowing), and time in bed. We used fitted values from linear regression models to predict the difference in outcome given the investigated time reallocations relative to the group-specific mean composition.

Results

Among 1053 eligible participants, we found an interaction between the physical behaviour composition and age. Age-stratified analyses (i.e., </≥65 years; 773 adults, 280 older adults) indicated that less sedentary behaviour and more walking was associated with lower SBP among older adults only. For less sedentary behaviour and more HIPA, the results i) indicated an association with a lower SBP irrespective of age, ii) showed an association with a smaller WC among adults, and iii) showed an association with a lower LDL-C in both age groups.

Conclusions

Less sedentary behaviour and more walking seems to be associated with lower CVD risk among older adults, while HIPA types are associated with lower risk among adults. Therefore, to reduce CVD risk, the modifying effect of age should be considered in future physical activity-promoting initiatives.