Latent profile analysis of physical activity and sedentary behavior with mortality risk: A 15‐year follow‐up

Patterns of daily ambulatory activity and the onset of metabolic syndrome in middle-aged and older Japanese women: the Toon Health Study

BACKGROUND

This cohort study aimed to identify the accumulation patterns of objectively measured ambulatory activity (AA) variables in the middle-aged and older Japanese women and examine the relationship of these derivative patterns with onset of metabolic syndrome (MetS).

METHODS

A total of 794 women (mean age: 56.2 years) provided objectively assessed AA data using a uniaxial accelerometer. The number of steps, time accumulated in light-intensity AA (LIAA) and moderate-to-vigorous intensity AA (MVAA) and the ratio of MVAA to total AA (LIAA + MVAA) were calculated. Latent profile analysis was used to identify participant groups based on their distinct AA patterns. Logistic regression models were used to assess the association of groups with the onset of MetS after adjusting for age, sex, education, alcohol habit, smoking habit, energy intake, and the number of MetS components present at baseline.

RESULTS

Four distinct groups were identified: Group A had low levels of the AA variable; group B accumulated a certain number or more steps primarily through MVAA; group C accumulated a certain number or more steps primarily through LIAA; and group D had high level of the AA variables. Over the course of the 5-year follow-up period, 61 participants (7.7%) developed MetS. The multivariate-adjusted odds ratio (95% confidence interval) for onset of MetS in groups B, C, and D relative to group A were 0.416 (0.166-1.218), 0.451 (0.223-0.914), and 0.933 (0.365-2.382), respectively. Group C had a significantly lower odds ratio of MetS onset than group A.

CONCLUSION

AA patterns accumulating a certain number or more steps, regardless of the intensity of AA, may help reduce the risk of MetS compared to inactive AA patterns.

A latent profile analysis of rest-activity behavior patterns among community-dwelling older adults and its relationship with intrinsic capacity

Rest-activity behavior clusters within individuals to form patterns are of significant importance to their intrinsic capacity (IC), yet they have rarely been studied. A total of 1253 community-dwelling older adults were recruited between July and December 2021 based on the baseline survey database of the Fujian Prospective Cohort Study on Aging. Latent profile analysis was used to identify profiles of participants based on rest-activity behaviors, whereas logistic regression analysis was carried out to investigate the relationship between profiles and IC. We identified three latent profiles including: (1) Profile 1-labeled "Gorillas": High physical activity (PA), moderate sedentary behaviors (SB), screen time (ST) and sleep (n = 154, 12%), (2) Profile 2-labeled as "Zebras": Moderate PA, low SB, ST and high sleep (n = 779, 62%), and (3) Profile 3-labeled as"Koalas": High SB, ST, low PA and sleep (n = 320, 26%). Logistic regression revealed a negative correlation between low IC and the "Gorillas" profile (β = - 0.945, P < 0.001) as well as the "Zebras" profile (β = - 0.693, P < 0.001) among community-dwelling older adults, with the "Koalas" profile showing the weakest IC compared to the other profiles. The demographic traits i.e., female, older age, living alone, and low educational level also correlated with low IC. Identifying trends of rest-activity behaviors may help in drawing focus on older adults at risk of decreasing IC, and develop personalized improvement plans for IC.

Physical Behavior Profiles Among Older Adults and Their Associations With Physical Capacity and Life-Space Mobility

We identified data-driven multidimensional physical activity (PA) profiles using several novel accelerometer-derived metrics. Participants aged 75, 80, and 85 (n = 441) wore triaxial accelerometers for 3-7 days. PA profiles were formed with k-means cluster analysis based on PA minutes, intensity, fragmentation, sit-to-stand transitions, and gait bouts for men and women. Associations with physical capacity and life-space mobility were examined using age-adjusted general linear models. Three profiles emerged: "Exercisers" and "actives" accumulated relatively high PA minutes, with actives engaging in lighter intensity PA. "Inactives" had the highest activity fragmentation and lowest PA volume, intensity, and gait bouts. Inactives showed lower scores in physical capacity and life-space mobility compared with exercisers and actives. Exercisers and actives had similar physical capacity and life-space mobility, except female exercisers had higher walking speed in the 6-min walk test. Our findings demonstrate the importance of assessing PA as multidimensional behavior rather than focusing on a single metric.

Association between profiles of accelerometer-measured daily movement behaviour and mortality risk: a prospective cohort study of British older adults

Objectives

We identified profiles of wake-time movement behaviours (sedentary behaviours, light intensity physical activity and moderate-to-vigorous physical activity) based on accelerometer-derived features among older adults and then examined their association with all-cause mortality.

Methods

Data were drawn from a prospective cohort of 3991 Whitehall II accelerometer substudy participants aged 60-83 years in 2012-2013. Daily movement behaviour profiles were identified using k-means cluster analysis based on 13 accelerometer-assessed features characterising total duration, frequency, bout duration, timing and activity intensity distribution of movement behaviour. Cox regression models were used to assess the association between derived profiles and mortality risk.

Results

Over a mean follow-up of 8.1 (SD 1.3) years, a total of 410 deaths were recorded. Five distinct profiles were identified and labelled as 'active' (healthiest), 'active sitters', 'light movers', 'prolonged sitters', and 'most sedentary' (most deleterious). In model adjusted for sociodemographic, lifestyle, and health-related factors, compared with the 'active' profile, 'active sitters' (HR 1.57, 95% CI 1.01 to 2.44), 'light movers' (HR 1.75, 95% CI 1.17 to 2.63), 'prolonged sitters' (HR 1.67, 95% CI 1.11 to 2.51), 'most sedentary' (HR 3.25, 95% CI 2.10 to 5.02) profiles were all associated with a higher risk of mortality.

Conclusion

Given the threefold higher mortality risk among those with a 'most sedentary' profile, public health interventions may target this group wherein any improvement in physical activity and sedentary behaviour might be beneficial.

Data-driven physical actigraphy patterns relate to cognitive and vascular health in older adults

Health benefits of physical activity (PA) are well known; however, specific PA patterns that relate most strongly to cognitive aging outcomes are poorly understood. We characterized latent profiles of PA among older adults and examined associations with cognition and vascular burden. 124 functionally normal older adults wore a Fitbit™ for 30 days. Daily average step count, sedentary time (0 steps/min), and high-intensity time (≥120 steps/min) were calculated. Participants completed neurocognitive testing assessing cognitive domains of executive functioning and memory; medical history, from which vascular burden (i.e., a count of cardiovascular conditions) was calculated; and brain MRI (n = 44). Subgroups with similar PA patterns were identified via latent profile analysis. Three latent PA classes emerged: Class 1Low PA (n = 49), Class 2Average PA (n = 59), and Class 3High-intensity PA (n = 16). PA class related to executive functioning and vascular burden, driven by better outcomes in Class 3 than Class 1. Sex-stratified analyses revealed these associations were strongest in males. Post hoc analyses showed a positive association between high-intensity PA and white matter integrity among males. High-intensity PA related to better cognitive and vascular health, particularly among males. Findings inform physical activity-specific and person-specific recommendations for optimal cognitive aging.

Analysis of the 24-h activity cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought study

The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure. We apply these approaches to assess an association with a cognitive outcome in a cohort of older adults, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. We compare the use of the isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) to analyze 24HAC. We illustrate each method by exploring cross-sectional associations with cognition in 1,034 older adults (Mean age = 77; Age range = 65-100; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7-days. For each method, we fit a multivariable regression model to examine the cross-sectional association between the 24HAC and Cognitive Abilities Screening Instrument item response theory (CASI-IRT) score, adjusting for baseline characteristics. We highlight differences in assumptions and the scientific questions addressable by each approach. ISM is easiest to apply and interpret; however, the typical ISM assumes a linear association. CoDA uses an isometric log-ratio transformation to directly model the compositional exposure but can be more challenging to apply and interpret. LPA can serve as an exploratory analysis tool to classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications, which is often ignored. Analyses using the three methods did not suggest that less time spent on SB and more in PA was associated with better cognitive function. The three standard analytical approaches for 24HAC each have advantages and limitations, and selection of the most appropriate method should be guided by the scientific questions of interest and applicability of each model's assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.

Latent profile analysis approach to the relationship between daily ambulatory activity patterns and metabolic syndrome in middle-aged and elderly Japanese individuals: The Toon Health Study

BACKGROUND

This cross-sectional study aimed to identify the accumulation patterns of objectively measured ambulatory activity (AA) variables in the Japanese middle-aged and elderly individuals and examine the relationship of these derivative patterns with metabolic syndrome (MetS).

METHODS

A total of 1850 participants (66.1% women, mean age: 57.7 years) provided objectively assessed AA data using a uniaxial accelerometer. The number of steps, time accumulated in light-intensity AA (LIAA) and moderate-to-vigorous intensity AA (MVAA), and the ratio of MVAA to total AA (LIAA + MVAA) were calculated. Latent profile analysis was used to identify groups of participants based on their distinct AA patterns. Logistic regression models were used to assess the association of groups with MetS after adjusting for age, sex, alcohol intake, and cigarette smoking.

RESULTS

Four distinct groups were identified: Group A had few steps and low levels of LIAA and MVAA; group B had a certain number of steps and recommended level of MVAA but low level of LIAA; group C had a certain number or more of steps, high level of LIAA, and recommended level of MVAA; group D had an extremely high number of steps and high levels of both LIAA and MVAA. The multivariate-adjusted odds ratio (95% CI) for MetS in groups B, C, and D relative to group A were 0.857 (0.611-1.201), 0.679 (0.500-0.922), and 0.434 (0.259-0.730), respectively. Groups C and D had significantly lower odds ratio of MetS compared to group A.

CONCLUSION

AA pattern involving a certain number or greater of steps accumulated through not only MVAA but also LIAA may help reduce the risk of MetS compared to inactive AA pattern.

Accelerometer-Measured Latent Physical Activity Profiles and Neurocognition Among Middle-Aged and Older Hispanic/Latino Adults in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

OBJECTIVES

Derive latent profiles of accelerometry-measured moderate-vigorous physical activity (MVPA) for Hispanic/Latino adults, examine associations between latent MVPA profiles and neurocognition, and describe profiles via self-reported MVPA.

METHODS

Complex survey design methods were applied to cross-sectional data from 7,672 adults ages 45-74 years in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL; 2008-2011). MVPA was measured via hip-worn accelerometers. Latent profile analysis was applied to derive latent MVPA profiles (minutes/day of week). Neurocognition was assessed with the Brief-Spanish English Verbal Learning Test (B-SEVLT) Sum, B-SEVLT Recall, Controlled Oral Word Association Test (word fluency), and Digit Symbol Substitution (DSS) test. All tests were z-scored, and a global neurocognition score was generated by averaging across scores. Survey linear regression models were used to examine associations between latent MVPA profiles and neurocognitive measures. Self-reported MVPA domains were estimated (occupational, transportation, and recreational) for each latent profile.

RESULTS

Four latent MVPA profiles from the overall adult target population (18-74 years) were derived and putatively labeled: No MVPA, low, moderate, and high. Only the high MVPA profile (compared to moderate) was associated with lower global neurocognition. Sensitivity analyses using latent MVPA profiles with only participants aged 45-74 years showed similar profiles, but no associations between latent MVPA profiles and neurocognition. The occupational MVPA domain led in all latent MVPA profiles.

DISCUSSION

We found no consistent evidence to link accelerometry-measured MVPA profiles to neurocognitive function. Research to better characterize the role of high occupational MVPA in relation to neurocognition among Hispanic/Latino adults are needed.

Joint Profiles of Sedentary Time and Physical Activity in Adults and Their Associations with Cardiometabolic Health

PURPOSE

This study aimed to identify and characterize joint profiles of sedentary time and physical activity among adults and to investigate how these profiles are associated with markers of cardiometabolic health.

METHODS

The participants included 3702 of the Northern Finland Birth Cohort 1966 at age 46 yr, who wore a hip-worn accelerometer during waking hours and provided seven consecutive days of valid data. Sedentary time, light-intensity physical activity, and moderate- to vigorous-intensity physical activity on each valid day were obtained, and a data-driven clustering approach ("KmL3D") was used to characterize distinct joint profiles of sedentary time and physical activity intensities. Participants self-reported their sleep duration and performed a submaximal step test with continuous heart rate measurement to estimate their cardiorespiratory fitness (peak heart rate). Linear regression was used to determine the association between joint profiles of sedentary time and physical activities with cardiometabolic health markers, including adiposity markers and blood lipid, glucose, and insulin levels.

RESULTS

Four distinct groups were identified: "active couch potatoes" ( n = 1173), "sedentary light movers" ( n = 1199), "sedentary exercisers" ( n = 694), and "movers" ( n = 636). Although sufficiently active, active couch potatoes had the highest daily sedentary time (>10 h) and lowest light-intensity physical activity. Compared with active couch potatoes, sedentary light movers, sedentary exercisers, and movers spent less time in sedentary by performing more physical activity at light-intensity upward and had favorable differences in their cardiometabolic health markers after accounting for potential confounders (1.1%-25.0% lower values depending on the health marker and profile).

CONCLUSIONS

After accounting for sleep duration and cardiorespiratory fitness, waking activity profiles characterized by performing more physical activity at light-intensity upward, resulting in less time spent in sedentary, were associated with better cardiometabolic health.

Associations between pre-COVID-19 physical activity profiles and mental wellbeing and quality of life during COVID-19 lockdown among adults

The COVID-19 pandemic has been detrimental to the physical and mental health and wellbeing of people across the globe. Regular physical activity has consistently demonstrated an array of health benefits, but the impact of regular physical activity habits pre-pandemic on health and wellbeing during the pandemic is largely unknown. The purpose of this study was to identify distinct pre-COVID-19 lockdown physical activity profiles [i.e., walking, leisure-time moderate-vigorous physical activity (MVPA), domestic MVPA and muscle strengthening exercise] and assess whether these profiles were associated with mental wellbeing and quality of life during COVID-19 lockdown. A total of 442 adults (Mage = 43.97 ± 13.85; 75.6% female) from Melbourne, Australia completed an online questionnaire measuring pre-COVID-19 physical activity, including walking habits, leisure-time MVPA, domestic MVPA, and muscle strengthening exercise - and completed measures of mental wellbeing and health related quality of life. Latent profile analysis identified five distinct profiles that differed in terms of levels of walking, leisure-time MVPA, domestic MVPA and muscle strengthening exercise. Based on the observed pre-COVID-19 lockdown profiles, it appears that high levels of MVPA and muscle strengthening exercise may serve as a protective factor against the potential negative impact of a global pandemic lockdown on mental wellbeing and quality of life.

Associations of Device-Measured Physical Activity, Sedentary Behavior, and Executive Function in Preadolescents: A Latent Profile Approach

PURPOSE

This study investigated the associations between physical activity (PA), sedentary behavior, and executive function in preadolescents.

METHODS

One hundred and twenty preadolescents were recruited from 2 Hong Kong primary schools. PA and sedentary behavior were recorded for 7 consecutive days by accelerometer. Executive function performance, including inhibition (Stroop task and Flanker task) and working memory (Sternberg paradigm task), were measured. Body mass index and cardiorespiratory fitness (multistage fitness test) were tested. Latent profile analysis explored the profiles of PA and sedentary behavior in preadolescents.

RESULTS

Three distinct profiles were identified: low activity, average activity, and high activity. Participants in low activity performed worse in the accuracy of Stroop task (vs average activity, P = .03; vs high activity, P < .01), Flanker task (vs average activity, P = .02; vs high activity, P < .001), and Sternberg paradigm task (vs average activity, P < .01; vs high activity, P < .01). No significant difference was observed between participants with average and high activities. No significant association was observed for profiles on body mass index and cardiorespiratory fitness.

CONCLUSION

Supplementing the consensus of the literature that moderate to vigorous PA benefits cognition, the authors conclude that light PA may also enhance preadolescents' executive functioning.

Catch me if you can! How French adolescents seize social occasions and opportunities to be active

BACKGROUND

Following an ecological framework, the aim of this study was to highlight the way adolescents invested their time in opportunities to engage in moderate to vigorous physical activity (MVPA) according to whether they were profiled as more or less active. This study's innovation lies in the analysis of MVPA according to social occasions which are understood as opportunities to be active throughout the day (e.g. home, school, transport).

METHODS

PA data measured by accelerometry (ActiGraph GT3X) for seven consecutive days were compiled, with adolescents' social occasions during the week recorded in a daily digital diary (n = 135). The opportunity ratio of MVPA at each social time is the ratio between time spent in MVPA and the duration of a corresponding social occasion. Following the literature, participants were categorised into three profiles according to their reported amount of MVPA: HEPA active, minimally active and inactive. Non-parametric Wilcoxon signed rank and Kruskal Wallis tests were performed to determine the relative intensity of PA performed at different social occasions, and to investigate whether intensities differed between adolescents with various activity profiles.

RESULTS

Results showed that engagement in MVPA at different social occasions differed according to participant profiles. Mismatch was noticed between the opportunity ratio and the duration of the most and least favorable social occasions for MVPA. For all three profiles, the social occasion "physical education lesson" revealed an opportunity ratio of MVPA (23.6% vs 17.0% vs 13.8%) significantly higher than the overall opportunity ratio of the week (6.9% vs 2.9% vs 1.2%), but of lower duration. Conversely, "home" (5.3% vs 0.0% vs 0.0%) and "school" (outside of PE time) (2.4% vs 0.0% vs 0.0%) represented the two least opportune social occasions for PA in an adolescent's week.

CONCLUSIONS

Rethinking engagement with MVPA in the context of temporal opportunities would allow potential ways to intervene within an educational supervised setting to help young people adopt a physically active lifestyle at the end of the key period of adolescence. These results reinforced the importance of context in interventions for PA promotion, opening for "time education" in people.

Physical Activity Patterns among Individuals with Prediabetes or Type 2 Diabetes across Two Years-A Longitudinal Latent Class Analysis

BACKGROUND

This study aimed to identify distinct profiles of physical activity (PA) patterns among individuals with prediabetes or type 2 diabetes participating in a two-year PA trial and to investigate predictors of the profiles.

METHODS

Data (n = 168, collected 2013-2020) from the cohort of a randomized trial aimed at increasing PA in individuals with prediabetes and type 2 diabetes were used. PA and sedentary behaviours were assessed by waist-worn ActiGraph GT1M accelerometers at baseline and at 6, 12, 18 and 24 months. Fifteen PA and sedentary variables were entered into a latent class mixed model for multivariate longitudinal outcomes. Multinominal regression analysis modelled profile membership based on baseline activity level, age, gender, BMI, disease status and group randomisation.

RESULTS

Two profiles of PA patterns were identified: "Increased activity" (n = 37, 22%) included participants increasing time in PA and decreasing sedentary time. "No change in activity" (n = 131, 78%) included participants with no or minor changes. "Increased activity" were younger (p = 0.003) and more active at baseline (p = 0.011), compared to "No change in activity". No other predictor was associated with profile membership.

CONCLUSIONS

A majority of participants maintained PA and sedentary patterns over two years despite being part of a PA intervention. Individuals improving PA patterns were younger and more active at baseline.

Accumulation patterns of sedentary time and breaks and their association with cardiometabolic health markers in adults

Breaking up sedentary time with physical activity (PA) could modify the detrimental cardiometabolic health effects of sedentary time. Our aim was to identify profiles according to distinct accumulation patterns of sedentary time and breaks in adults, and to investigate how these profiles are associated with cardiometabolic outcomes. Participants (n = 4439) of the Northern Finland Birth Cohort 1966 at age 46 years wore a hip-worn accelerometer for 7 consecutive days during waking hours. Uninterrupted ≥1-min sedentary bouts were identified, and non-sedentary bouts in between two consecutive sedentary bouts were considered as sedentary breaks. K-means clustering was performed with 65 variables characterizing how sedentary time was accumulated and interrupted. Linear regression was used to determine the association of accumulation patterns with cardiometabolic health markers. Four distinct groups were formed as follows: "Couch potatoes" (n = 1222), "Prolonged sitters" (n = 1179), "Shortened sitters" (n = 1529), and "Breakers" (n = 509). Couch potatoes had the highest level of sedentariness and the shortest sedentary breaks. Prolonged sitters, accumulating sedentary time in bouts of ≥15-30 min, had no differences in cardiometabolic outcomes compared with Couch potatoes. Shortened sitters accumulated sedentary time in bouts lasting <15 min and performed more light-intensity PA in their sedentary breaks, and Breakers performed more light-intensity and moderate-to-vigorous PA. These latter two profiles had lower levels of adiposity, blood lipids, and insulin sensitivity, compared with Couch potatoes (1.1-25.0% lower values depending on the cardiometabolic health outcome, group, and adjustments for potential confounders). Avoiding uninterrupted sedentary time with any active behavior from light-intensity upwards could be beneficial for cardiometabolic health in adults.

Is Sitting Always Inactive and Standing Always Active? A Simultaneous Free-Living activPal and ActiGraph Analysis

Sedentary Behavior (SB), defined as sitting with minimal physical activity, is an emergent public health topic. However, the measurement of SB considers either posture (e.g., activPal) or physical activity (e.g., ActiGraph), and thus neglects either active sitting or inactive standing. The aim of this study was to determine the true amount of active sitting and inactive standing in daily life, and to analyze by how much these behaviors falsify the single sensors' sedentary estimates. Sedentary time of 100 office workers estimated with activPal and ActiGraph was therefore compared with Bland-Altman statistics to a combined sensor analysis, the posture and physical activity index (POPAI). POPAI classified each activPal sitting and standing event into inactive or active using the ActiGraph counts. Participants spent 45.0% [32.2%-59.1%] of the waking hours inactive sitting (equal to SB), 13.7% [7.8%-21.6%] active sitting, and 12.0% [5.7%-24.1%] inactive standing (mean [5th-95th percentile]). The activPal overestimated sedentary time by 30.3% [12.3%-48.4%] and the ActiGraph by 22.5% [3.2%-41.8%] (bias [95% limit-of-agreement]). The results showed that sitting is not always inactive, and standing is not always active. Caution should therefore be paid when interpreting the activPal (ignoring active sitting) and ActiGraph (ignoring inactive standing) measured time as SB.