Deep learning of movement behavior profiles and their association with markers of cardiometabolic health.

BACKGROUND: Traditionally, existing studies assessing the health associations of accelerometer-measured movement behaviors have been performed with few averaged values, mainly representing the duration of physical activities and sedentary behaviors. Such averaged values cannot naturally capture the complex interplay between the duration, timing, and patterns of accumulation of movement behaviors, that altogether may be codependently related to health outcomes in adults. In this study, we introduce a novel approach to visually represent recorded movement behaviors as images using original accelerometer outputs. Subsequently, we utilize these images for cluster analysis employing deep convolutional autoencoders. METHODS: Our method involves converting minute-by-minute accelerometer outputs (activity counts) into a 2D image format, capturing the entire spectrum of movement behaviors performed by each participant. By utilizing convolutional autoencoders, we enable the learning of these image-based representations. Subsequently, we apply the K-means algorithm to cluster these learned representations. We used data from 1812 adult (20-65 years) participants in the National Health and Nutrition Examination Survey (NHANES, 2003-2006 cycles) study who worn a hip-worn accelerometer for 7 seven consecutive days and provided valid accelerometer data. RESULTS: Deep convolutional autoencoders were able to learn the image representation, encompassing the entire spectrum of movement behaviors. The images were encoded into 32 latent variables, and cluster analysis based on these learned representations for the movement behavior images resulted in the identification of four distinct movement behavior profiles characterized by varying levels, timing, and patterns of accumulation of movement behaviors. After adjusting for potential covariates, the movement behavior profile characterized as "Early-morning movers" and the profile characterized as "Highest activity" both had lower levels of insulin (P < 0.01 for both), triglycerides (P < 0.05 and P < 0.01, respectively), HOMA-IR (P < 0.01 for both), and plasma glucose (P < 0.05 and P < 0.1, respectively) compared to the "Lowest activity" profile. No significant differences were observed for the "Least sedentary movers" profile compared to the "Lowest activity" profile. CONCLUSIONS: Deep learning of movement behavior profiles revealed that, in addition to duration and patterns of movement behaviors, the timing of physical activity may also be crucial for gaining additional health benefits.

Associations between insomnia and pregnancy and perinatal outcomes: Evidence from mendelian randomization and multivariable regression analyses.

BACKGROUND: Insomnia is common and associated with adverse pregnancy and perinatal outcomes in observational studies. However, those associations could be vulnerable to residual confounding or reverse causality. Our aim was to estimate the association of insomnia with stillbirth, miscarriage, gestational diabetes (GD), hypertensive disorders of pregnancy (HDP), perinatal depression, preterm birth (PTB), and low/high offspring birthweight (LBW/HBW). METHODS AND FINDINGS: We used 2-sample mendelian randomization (MR) with 81 single-nucleotide polymorphisms (SNPs) instrumenting for a lifelong predisposition to insomnia. Our outcomes included ever experiencing stillbirth, ever experiencing miscarriage, GD, HDP, perinatal depression, PTB (gestational age <37 completed weeks), LBW (<2,500 grams), and HBW (>4,500 grams). We used data from women of European descent (N = 356,069, mean ages at delivery 25.5 to 30.0 years) from UK Biobank (UKB), FinnGen, Avon Longitudinal Study of Parents and Children (ALSPAC), Born in Bradford (BiB), and the Norwegian Mother, Father and Child Cohort (MoBa). Main MR analyses used inverse variance weighting (IVW), with weighted median and MR-Egger as sensitivity analyses. We compared MR estimates with multivariable regression of insomnia in pregnancy on outcomes in ALSPAC (N = 11,745). IVW showed evidence of an association of genetic susceptibility to insomnia with miscarriage (odds ratio (OR): 1.60, 95% confidence interval (CI): 1.18, 2.17, p = 0.002), perinatal depression (OR 3.56, 95% CI: 1.49, 8.54, p = 0.004), and LBW (OR 3.17, 95% CI: 1.69, 5.96, p < 0.001). IVW results did not support associations of insomnia with stillbirth, GD, HDP, PTB, and HBW, with wide CIs including the null. Associations of genetic susceptibility to insomnia with miscarriage, perinatal depression, and LBW were not observed in weighted median or MR-Egger analyses. Results from these sensitivity analyses were directionally consistent with IVW results for all outcomes, with the exception of GD, perinatal depression, and PTB in MR-Egger. Multivariable regression showed associations of insomnia at 18 weeks of gestation with perinatal depression (OR 2.96, 95% CI: 2.42, 3.63, p < 0.001), but not with LBW (OR 0.92, 95% CI: 0.69, 1.24, p = 0.60). Multivariable regression with miscarriage and stillbirth was not possible due to small numbers in index pregnancies. Key limitations are potential horizontal pleiotropy (particularly for perinatal depression) and low statistical power in MR, and residual confounding in multivariable regression. CONCLUSIONS: In this study, we observed some evidence in support of a possible causal relationship between genetically predicted insomnia and miscarriage, perinatal depression, and LBW. Our study also found observational evidence in support of an association between insomnia in pregnancy and perinatal depression, with no clear multivariable evidence of an association with LBW. Our findings highlight the importance of healthy sleep in women of reproductive age, though replication in larger studies, including with genetic instruments specific to insomnia in pregnancy are important.

Independent associations of sleep timing, duration and quality with adiposity and weight status in a national sample of adolescents: The UK Millennium Cohort Study.

Short sleep appears to elevate obesity risk in youth; however, sleep is a multidimensional construct, and few studies have investigated parameters beyond duration. The objective of this study was to investigate if sleep onset time, duration, latency and night waking frequency are independently associated with adiposity and weight status in UK adolescents. This was a cross-sectional observational study of 10,619, 13-15 years olds. Adjusted linear and logistic regressions were used to investigate associations of self-reported sleep characteristics with adiposity markers (body mass index z-score and percent body fat) and weight status. Compared with a sleep onset before 10pm, later sleep timing was associated with higher adiposity and higher likelihood of overweight and obesity in boys (after midnight, odds ratio [95% confidence interval]: 1.76 [1.19-2.60]) and girls (between 11pm and 11:59pm: 1.36 [1.17-1.65]). Sleeping ≤ 8 hr, compared with > 9-10 hr, was associated with higher odds of overweight and obesity in both sexes (boys: 1.80 [1.38-2.35]; girls: 1.38 [1.06-1.79]), and so too was sleeping > 10 hr in girls (1.31 [1.06-1.62]), indicating evidence for a U-shaped association. Also in girls, compared to a sleep latency of 16-30 min, sleep latencies ≥ 46 min were associated with higher adiposity (46-60 min, beta coefficient [95% confidence interval], percent body fat: 1.47 [0.57-2.36]) and higher likelihood of overweight and obesity (46-60 min: 1.39 [1.05-1.83]), and often as opposed to never waking in the night was associated with higher adiposity (body mass index z-score: 0.24 [0.08-0.41]; percent body fat: 1.44 [0.44-2.44]). Sleep duration and timing in both sexes, and sleep quality in girls, appear to be independently associated with adiposity and weight status in adolescence, and may be important targets for obesity prevention.

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.

Physical activity can attenuate, but not eliminate, the negative relationships of high TV viewing with some chronic diseases: findings from a cohort of 60 202 Brazilian adults.

BACKGROUND: This study examined the joint associations of leisure time physical activity and television (TV) viewing time with the prevalence of chronic diseases among Brazilian adults. METHODS: Data from the Brazilian Health Survey, a nationally representative survey conducted in 2013 (n = 60 202; ≥18 years), were used. Time spent in TV viewing and leisure physical activity, physician diagnoses of diabetes, hypertension and heart disease and information on co-variables (chronological age, education, ethnicity, candies/sweets consumption, sodium intake and tobacco smoking) were collected via interview. Descriptive statistics (mean and 95% confidence interval) and logistic regression models were used for etiological analyses. RESULTS: Physical activity attenuated but did not eliminate the risk associated with high TV viewing for at least one chronic disease in the general population [odds ratio [OR]: 1.29 (1.11-1.50)] and among women [OR: 1.31 (1.09-1.60)], adults [OR: 1.24 (1.05-1.46)] and older adults [OR: 1.63 (1.05-2.53)]. On the other hand, physical activity eliminated the risk associated with high TV viewing for at least one chronic disease among men [OR: 1.24 (0.98-1.58)]. CONCLUSIONS: We conclude that physical activity can attenuate but not eliminate the negative effects of high TV viewing on chronic disease among subgroups of Brazilian adults.

Objectively-measured sedentary time and physical activity in a bi-ethnic sample of young children: variation by socio-demographic, temporal and perinatal factors.

BACKGROUND: Evidence suggests that South Asian school-aged children and adults are less active compared to the white British population. It is unknown if this generalises to young children. We aimed to describe variability in levels of physical activity and sedentary time in a bi-ethnic sample of young children from a deprived location. METHODS: This observational study included 202 South Asian and 140 white British children aged 1.5 to 5y, who provided 3181 valid days of triaxial accelerometry (Actigraph GT3X+). Variability in sedentary time and physical activity levels were analysed by linear multilevel modelling. Logistic multilevel regression was used to identify factors associated with physical inactivity (failing to perform ≥180 min of total physical activity including ≥60 min moderate-to-vigorous physical activity (MVPA) per day). RESULTS: There were no significant ethnic differences in the overall levels of behaviours; South Asian and white British children spent half of daily time sedentary, just over 40% in light physical activity, and the remaining 7.5 to 8% of time in MVPA. Sedentary time was lower and physical activity levels were higher in older children, and levels of MVPA and vector magnitude counts per minute (CPM) were higher on weekends compared to weekdays. In South Asian children, sedentary time was lower on weekends. Sedentary time was lower and physical activity levels were higher in spring compared to winter in white British children, and in all seasons compared to winter in South Asian children. South Asian children born at high birth weight performed more MVPA, and in both ethnicities there was some evidence that children with older mothers were more sedentary and less active. Sedentary time was higher and light physical activity was lower in South Asian children in the highest compared to the lowest income families. South Asian girls performed less MVPA, registered fewer vector magnitude CPM, and were 3.5 times more likely to be physically inactive than South Asian boys. CONCLUSIONS: Sedentary time and physical activity levels vary by socio-demographic, temporal and perinatal characteristics in young children from a deprived location. South Asian girls have the most to gain from efforts to increase physical activity levels. TRIAL REGISTRATION: The Pre-schoolers in the Playground (PiP) pilot randomized controlled trial is registered with the ISRCTN (ISRCTN54165860; http://www.isrctn.com).

Physical activity maintenance and metabolic risk in adolescents.

Aim: Examine the association between child and adolescent physical activity maintenance categories and metabolic profile in adolescence. Methods: This cross-sectional study was conducted with 1152 adolescents (57.4% female) aged 10-16 years from Londrina, Brazil. Physical activity was self-reported in childhood (7-10 years old, retrospective data) and adolescence through questionnaires. Cardiorespiratory fitness (20 m shuttle-run test), body fat (skinfolds), waist circumference, blood pressure (automatic instrument) and blood variables (fasting glucose, HDL-cholesterol and triglycerides) were measured at adolescence. Results: Frequency of physical activity in childhood and adolescence was 50.3 and 17.2%, respectively, and only 25.7% of boys and 10.9% of girls were active at both ages. Adolescents who were physically active in childhood alone were less likely [OR = 0.71 (95% CI: 0.52-0.97)] to present low cardiorespiratory fitness in adolescence compared to those who were non-active in childhood. Regardless of controlled, actives in childhood and adolescence were less likely to present low cardiorespiratory fitness [OR = 0.50 (95% CI: 0.34-0.73)], high blood pressure [OR = 0.52 (95% CI: 0.32-0.85)] and high metabolic risk score [OR = 0.44 (95% CI: 0.22-0.90)] compared to the non-actives at both ages. Conclusions: Actives through childhood to adolescence are less likely to present low cardiorespiratory fitness, high blood pressure and high metabolic risk.

Prevalence, trajectories, and determinants of television viewing time in an ethnically diverse sample of young children from the UK.

BACKGROUND: Excessive screen viewing in early childhood is associated with poor physical and psycho-social health and poor cognitive development. This study aimed to understand the prevalence, trajectory and determinants of television viewing time in early childhood to inform intervention development. METHODS: In this prospective longitudinal study, mothers of 1558 children (589 white British, 757 Pakistani heritage, 212 other ethnicities) completed questionnaires when their children were approximately 6, 12, 18, 24 and 36 months old. Mothers answered questions about their own and their child's TV-time. TV-time trajectories were estimated by linear longitudinal multilevel modeling, potential determinants were considered in models. RESULTS: The modelled trajectory estimated that 75% of children aged 12 months exceeded guidelines of zero screen-time. At 12 months of age an accelerated increase in TV-time was observed (<1 h/day at 14 months, >2 h/day by 30 months old). For every hour of mothers' TV-time and every hour the TV was on in the home, children's TV-time was 8 min and 1 min higher respectively at 6 months old (P < 0.05), and 15 min and 3 min higher respectively at 36 months old (P < 0.05). Children whose mothers did not agree that it was important their child did not watch too much TV, had 17 min more TV-time than their counterparts (P < 0.05). Children of first time mothers had 6 min more TV-time (P < 0.05). At 12 months of age, children of mothers experiencing stress watched 8 min more TV (P < 0.05). By 36 months, children of Pakistani heritage mothers had 22 min more TV-time than those of white British mothers (P < 0.05), and an additional 35 min of TV-time if their mother was not born in the UK (P < 0.05). CONCLUSIONS: High levels of TV-time were prevalent. Intervention developers should consider targeting interventions before 12 months of age. Modifiable determinants included mothers' own TV-time, the time the television is on in the home and mothers' attitude towards child TV-time. These behaviours may be key components to address in interventions for parents. Mothers experiencing stress, first time mothers, and Pakistani heritage mothers (particularly those born outside of the UK), may be priority groups for intervention.

Family history of cardiovascular disease and parental lifestyle behaviors are associated with offspring cardiovascular disease risk markers in childhood.

INTRODUCTION: Cardiovascular disease risk markers have become more prevalent in childhood. To provide increased understanding of the etiology of this public health issue, we investigated associations between family characteristics with cardiovascular disease risk markers in adolescents from a developing nation. METHODS: In this cross-sectional study data for fasting glucose, lipoproteins (LDL-C and HDL-C), triglycerides, and total cholesterol were collected from 991 adolescents aged 10-17 who were recruited from public schools in Londrina city, Southern Brazil. Family history of cardiovascular disease and parental engagement in risk behavior (alcohol consumption and tobacco smoking) were collected using a self-reported parental questionnaire. Socioeconomic status, adolescent physical activity (estimated by Baecke questionnaire), self-reported tobacco and alcohol intake, and somatic maturation (age at peak height velocity) were used as covariates. Logistic regression was used for the main analyses. RESULTS: Independent of adolescent lifestyle behaviors, associations (ORadj [95% CI]) were found between: (1) paternal family history of cardiovascular disease with increased likelihood of high adolescent offspring BMI (1.53 [1.01 to 2.32]) and high triglycerides (2.93 [1.04 to 8.27]); (2) maternal family history of cardiovascular disease with heightened odds of high adolescent offspring triglycerides (2.84 [1.02 to 7.91]); (3) maternal cardiovascular disease with higher odds of high fasting glucose (2.16 [1.13 to 4.14]), and (4) maternal smoking with increased odds of high LDL-C (1.78 [1.14 to 2.79]) and high total cholesterol (1.77 [1.01 to 3.10]) in adolescent offspring. CONCLUSION: Family history of cardiovascular disease and maternal tobacco smoking are related to increased cardiovascular risk in adolescents, potentially independent of their own lifestyle behaviors.

Cardiorespiratory fitness effect may be under-estimated in 'fat but fit' hypothesis studies.

BACKGROUND: Both cardiorespiratory fitness and body fat have been independently related to metabolic syndrome in adolescents; however, the strength of these relationships seems to be dependent on the outcome composition. AIM: To analyse the relationship between cardiorespiratory fitness and body fat combined with different indicators of metabolic risk in adolescents. SUBJECTS AND METHODS: The sample was composed of 957 adolescents (58.7% girls). Cardiorespiratory fitness was obtained using the 20-metre shuttle run test and skinfold thickness was collected for body fat estimation. Metabolic risk score was calculated from waist circumference, systolic and diastolic blood pressure, glucose, HDL cholesterol and triglycerides measurements and an alternative outcome without the central obesity indicator was adopted. Chronological age and somatic maturity were used as covariates. RESULTS: Higher metabolic risk was observed in the highest fat/lowest fit adolescents (p < .05), regardless of sex and outcome. In the regression models, for full metabolic risk score, body fat presented higher coefficients compared to cardiorespiratory fitness in both sexes (boys: 0.501 vs -0.097; girls: 0.485 vs -0.087); however, in the metabolic risk without waist circumference, the coefficients became closer (boys: 0.290 vs -0.146; girls: 0.265 vs -0.120), with a concomitant decrease in body fat and increase in cardiorespiratory fitness coefficients. CONCLUSION: These findings suggest that body fat is strongly related to cardiovascular risk, but, when the outcome is calculated without the central obesity indicator, cardiorespiratory fitness becomes more related to metabolic risk.

Correlates of sports practice, occupational and leisure-time physical activity in Brazilian adolescents.

OBJECTIVES: To analyze the relationship between different physical activity (PA) domains and sociodemographic, psychological, behavioral and biological factors in Brazilian adolescents. METHODS: 1,220 adolescents (55.1% female) aged between 10 and 16 years-old participated in this study. The Baecke questionnaire was used to evaluate different PA domains, namely occupational, sports and leisure-time. Socioeconomic status, number of siblings, friendships satisfaction, mother's and father's PA level and previous experience with sports were self-reported. Cardiorespiratory fitness, waist circumference, and somatic maturity were estimated by objective indicators. Linear regression was used for the main statistical analysis. RESULTS: The variables consistently related to all of the PA domains were gender (boys more active), friendship satisfaction (positive with sports and leisure-time PA and negative with occupational PA) and cardiorespiratory fitness (positive). There were also domain-specific relationships for occupational (number of siblings [ß = 0.02] and father's PA [ß = 0.13]), sport practice (previous experience with sports [ß = 0.33], waist circumference [ß = 0.01] and somatic maturity [ß = -0.12]) and leisure-time PA (chronological age [ß = -0.15], mother's PA [ß = 0.47] and previous experience with sports [ß = 0.17]). CONCLUSIONS: The different domains of PA are related to specific variables in adolescence. This information may be helpful in formulating strategies for physical activity promotion, particularly in adolescents from low-to-middle income countries.

Magnitude and determinants of change in objectively-measured physical activity, sedentary time and sleep duration from ages 15 to 17.5y in UK adolescents: the ROOTS study.

BACKGROUND: Self-reported physical activity (PA) and sleep duration (SLP) change markedly throughout adolescence. We sought to quantify changes in objectively-measured PA, sedentary time (ST) and SLP through adolescence, and to investigate baseline body composition and baseline activity levels as determinants of change. METHODS: Individually calibrated combined heart rate and movement sensing was used to estimate PA energy expenditure (PAEE), SLP, daily ST and time in light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous physical activity (MVPA) in 144 adolescents (50% boys) of mean age 15.1(±0.3)y at baseline and 17.5(±0.3)y at follow-up. Changes in PA (ΔPA), ST (ΔST) and SLP (ΔSLP) were calculated as follow-up minus baseline values. Waist circumference (WC) was measured at baseline and follow-up, as was fat mass index (FMI) and fat-free mass index (FFMI) by a pooled estimation method including bio-impedance. Comparison of baseline and follow-up activity was made by mixed-model ANOVA. Linear regression adjusted for baseline demographics, total and weekend hours of monitor wear time and the seasons of activity measurements, was used to investigate baseline body composition as determinants of ΔPA, ΔST and ΔSLP. A further model adjusted for baseline of the outcome assessed baseline activity as a predictor of behaviour change, and investigated associations for baseline body composition independent of the baseline level of the outcome. RESULTS: From baseline to follow-up levels of MPA and VPA declined (p ≤ 0.039). The annual decline in MVPA was equivalent to -4.5 and -3.0 min/d in boys and girls, respectively. Baseline FMI, FFMI and WC were positively associated with ΔLPA and negatively associated with ΔST in boys when adjusted for baseline of the outcome (p ≤ 0.037 for all). SLP increased from baseline to follow-up (p = 0.004) but ΔSLP was not associated with baseline body composition (p ≥ 0.13). For all variables, higher baseline levels were associated with greater declines over time (p ≤ 0.003). CONCLUSIONS: Levels of higher-intensity PA decline from mid-to-late adolescence, whereas the duration of sleep increases. Changes in LPA and ST may be associated with baseline body composition, but the baseline level of the outcome is consistently the strongest predictor of changes in adolescent activity.

Levels and patterns of objectively-measured physical activity volume and intensity distribution in UK adolescents: the ROOTS study.

BACKGROUND: Few studies have quantified levels of habitual physical activity across the entire intensity range. We aimed to describe variability in total and intensity-specific physical activity levels in UK adolescents across gender, socio-demographic, temporal and body composition strata. METHODS: Physical activity energy expenditure and minutes per day (min/d) spent sedentary and in light, moderate, and vigorous intensity physical activity were assessed in 825 adolescents from the ROOTS study (43.5% boys; mean age 15.0 ± 0.30 years), by 4 days of individually calibrated combined heart rate and movement sensing. Measurement days were classified as weekday or weekend and according to the three school terms: summer (April-July), autumn (September-December), and spring (January-March). Gender and age were self-reported and area-level SES determined by postcode data. Body composition was measured by anthropometry and bio-electrical impedance. Variability in physical activity and sedentary time was analysed by linear multilevel modelling, and logistic multilevel regression was used to determine factors associated with physical inactivity (<60 min moderate-to-vigorous intensity physical activity/d). RESULTS: During awake hours (15.8 ± 0.9 hrs/d), adolescents primarily engaged in light intensity physical activity (517 min/d) and sedentary time (364 min/d). Boys were consistently more physically active and less sedentary than girls, but gender differences were smaller at weekends, as activity levels in boys dropped more markedly when transitioning from weekday to weekend. Boys were more sedentary on both weekend days compared to during the week, whereas girls were more sedentary on Sunday but less sedentary on Saturday. In both genders light intensity physical activity was lower in spring, while moderate physical activity was lower in autumn and spring terms, compared to the summer term; sedentary time was also higher in spring than summer term. Adolescents with higher fatness engaged in less vigorous intensity physical activity. Factors associated with increased odds of physical inactivity were female gender, both weekend days in boys, and specifically Sunday in girls. CONCLUSIONS: Physical activity components vary by gender, temporal factors and body composition in UK adolescents. The available data indicate that in adolescence, girls should be the primary targets of interventions designed to increase physical activity levels.

Objectively measured physical activity in four-year-old British children: a cross-sectional analysis of activity patterns segmented across the day.

BACKGROUND: Little is known about preschool-aged children's levels of physical activity (PA) over the course of the day. Using time-stamped data, we describe the levels and patterns of PA in a population-based sample of four-year-old British children. METHODS: Within the Southampton Women's Survey the PA levels of 593 4-year-old children (51% female) were measured using (Actiheart) accelerometry for up to 7 days. Three outcome measures: minutes spent sedentary (<20 cpm); in light (LPA: ≥20-399 cpm) and in moderate-to-vigorous activity (MVPA: ≥400 cpm) were derived. Average daily activity levels were calculated and then segmented across the day (morning, afternoon and evening). MVPA was log-transformed. Two-level random intercept models were used to analyse associations between activity level and temporal and demographic factors. RESULTS: Children were active for 67% (mean 568.5 SD 79.5 minutes) of their daily registered time on average, with 88% of active time spent in LPA. All children met current UK guidelines of 180 minutes of daily activity. There were no differences in children's average daily levels of sedentary activity and LPA by temporal and demographic factors: differences did emerge when activity was segmented across the day. Sex differences were largest in the morning, with girls being more sedentary, spending fewer minutes in LPA and 18% less time in MVPA than boys. Children were more sedentary and less active (LPA and MVPA) in the morning if they attended childcare full-time compared to part-time, and on weekend mornings compared to weekdays. The reverse was true for weekend afternoons and evenings. Children with more educated mothers were less active in the evenings. Children were less sedentary and did more MVPA on summer evenings compared to winter evenings. CONCLUSIONS: Preschool-aged children meet current physical activity guidelines, but with the majority of their active time spent in LPA, investigation of the importance of activity intensity in younger children is needed. Activity levels over the day differed by demographic and temporal factors, highlighting the need to consider temporality in future interventions. Increasing girls' morning activity and providing opportunities for daytime activity in winter months may be worthwhile.

Arterial stiffness and the reallocation of time between device-measured 24-hour movement behaviours: A compositional data analysis.

BACKGROUND AND AIMS: Arterial stiffness predicts cardiovascular morbidity and mortality. We aimed to quantify the differences in arterial stiffness associated with reallocating time between 24-h movement behaviours. METHODS: This observational cross-sectional study included Luxembourg residents aged 25-79y who each provided ≥4 valid days of triaxial accelerometry (n = 1001). Covariable adjusted compositional isotemporal substitution models were used to examine if theoretical reallocations of time between device-measured sedentariness, the sleep period, light physical activity (PA), and moderate-to-vigorous PA (MVPA) were associated with the percentage difference in carotid-femoral pulse wave velocity (cfPWV). We further investigated if replacing sedentary time accumulated in prolonged (≥30 min) with non-prolonged (<30 min) bouts was associated with arterial stiffness. The results are presented as 30 min time exchanges (ß (95% confidence interval)). RESULTS: Beneficial associations with lower cfPWV were observed when reallocating time to MVPA from the sleep period (-1.38 (-2.63 to -0.12) %), sedentary time (-1.70 (-2.76 to -0.62) %), and light PA (-2.51 (-4.55 to -0.43) %), respectively. Larger associations in the opposite direction were observed when reallocating MVPA to the same behaviours (for example, replacing MVPA with sedentary time: 2.50 (0.85-4.18) %). Replacing prolonged with non-prolonged sedentary time was not associated with cfPWV (-0.27 (-0.86 to 0.32) %). In short sleepers, reallocating sedentary time to the sleep period was favourable (-1.96 (-3.74 to -0.15) %). CONCLUSIONS: Increasing or at least maintaining MVPA appears to be important for arterial health in adults. Extending sleep in habitually short sleepers, specifically by redistributing sedentary time, may also be important.

Sociodemographic, temporal and bedtime routine correlates of sleep timing and duration in South Asian and white children: A Born in Bradford study.

Objective: The study aimed to examine sociodemographic, temporal and bedtime routine correlates of parent-reported sleep duration and timing in a biethnic sample of 18 month and 36 month old children from a disadvantaged location. Methods: Between October 2010 and September 2012, parents completed a bespoke three day sleep diary when their child was approximately 18 months (n = 276) and 36 months of age (n = 262) (45.1% South Asian; 54.9% white). Parents reported their child's overnight sleep duration (h/day), the time their child fell asleep, their wake time and their child's bedtime and napping routines. Data were available at both time points for 135 children. Results: In line with previous literature, South Asian children had shorter overnight sleep duration and later sleep and wake times than white children. In both ethnic groups, children slept and woke up later on weekends, and children went to bed earlier and slept longer in winter. In white children only, napping duration was associated with overnight sleep period. No significant associations were found between napping frequency and overnight sleep duration. Based on parent-reported data, children who consistently adhered to regular bedtimes and had set times for sleeping tended to go to sleep earlier, wake earlier and have longer overnight sleep. Conclusions: The data showed parent-reported variation in sleep patterns between two ethnic groups within a single geographical and deprived area. It is important that researchers, clinicians and early years workers are considerate of cultural norms in sleep practices.

Substituting device-measured sedentary time with alternative 24-hour movement behaviours: compositional associations with adiposity and cardiometabolic risk in the ORISCAV-LUX 2 study.

BACKGROUND: There is a considerable burden of sedentary time in European adults. We aimed to quantify the differences in adiposity and cardiometabolic health associated with theoretically exchanging sedentary time for alternative 24 h movement behaviours. METHODS: This observational cross-sectional study included Luxembourg residents aged 18-79 years who each provided ≥ 4 valid days of triaxial accelerometry (n = 1046). Covariable adjusted compositional isotemporal substitution models were used to examine if statistically replacing device-measured sedentary time with more time in the sleep period, light physical activity (PA), or moderate-to-vigorous PA (MVPA) was associated with adiposity and cardiometabolic health markers. We further investigated the cardiometabolic properties of replacing sedentary time which was accumulated in prolonged (≥ 30 min) with non-prolonged (< 30 min) bouts. RESULTS: Replacing sedentary time with MVPA was favourably associated with adiposity, high-density lipoprotein cholesterol, fasting glucose, insulin, and clustered cardiometabolic risk. Substituting sedentary time with light PA was associated with lower total body fat, fasting insulin, and was the only time-exchange to predict lower triglycerides and a lower apolipoprotein B/A1 ratio. Exchanging sedentary time with more time in the sleep period was associated with lower fasting insulin, and with lower adiposity in short sleepers. There was no significant evidence that replacing prolonged with non-prolonged sedentary time was related to outcomes. CONCLUSIONS: Artificial time-use substitutions indicate that replacing sedentary time with MVPA is beneficially associated with the widest range of cardiometabolic risk factors. Light PA confers some additional and unique metabolic benefit. Extending sleep, by substituting sedentary time with more time in the sleep period, may lower obesity risk in short sleepers.

Associations Between Wearable-Specific Indicators of Physical Activity Behaviour and Insulin Sensitivity and Glycated Haemoglobin in the General Population: Results from the ORISCAV-LUX 2 Study.

BACKGROUND: Parameters derived from an acceleration signal, such as the time accumulated in sedentary behaviour or moderate to vigorous physical activity (MVPA), may not be sufficient to describe physical activity (PA) which is a complex behaviour. Incorporating more advanced wearable-specific indicators of PA behaviour (WIPAB) may be useful when characterising PA profiles and investigating associations with health. We investigated the associations of novel objective measures of PA behaviour with glycated haemoglobin (HbA1c) and insulin sensitivity (Quicki index). METHODS: This observational study included 1026 adults (55% women) aged 18-79y who were recruited from the general population in Luxembourg. Participants provided ≥ 4 valid days of triaxial accelerometry data which was used to derive WIPAB variables related to the activity intensity, accumulation pattern and the temporal correlation and regularity of the acceleration time series. RESULTS: Adjusted general linear models showed that more time spent in MVPA and a higher average acceleration were both associated with a higher insulin sensitivity. More time accumulated in sedentary behaviour was associated with lower insulin sensitivity. With regard to WIPAB variables, parameters that were indicative of higher PA intensity, including a shallower intensity gradient and higher average accelerations registered during the most active 8 h and 15 min of the day, were associated with higher insulin sensitivity. Results for the power law exponent alpha, and the proportion of daily time accumulated in sedentary bouts > 60 min, indicated that activity which was characterised by long sedentary bouts was associated with lower insulin sensitivity. A greater proportion of time spent in MVPA bouts > 10 min was associated with higher insulin sensitivity. A higher scaling exponent alpha at small time scales (< 90 min), which shows greater correlation in the acceleration time series over short durations, was associated with higher insulin sensitivity. When measured over the entirety of the time series, metrics that reflected a more complex, irregular and unpredictable activity profile, such as the sample entropy, were associated with lower HbA1c levels and higher insulin sensitivity. CONCLUSION: Our investigation of novel WIPAB variables shows that parameters related to activity intensity, accumulation pattern, temporal correlation and regularity are associated with insulin sensitivity in an adult general population.

Cross-sectional and prospective associations of sleep duration and bedtimes with adiposity and obesity risk in 15 810 youth from 11 international cohorts.

OBJECTIVES: To investigate associations of bedtimes and sleep durations with adiposity levels in children and adolescents. METHODS: Individual data were pooled for 12 247 children (5819 with follow-up adiposity at 2.3 ± 1.4 years post-baseline) and 3563 adolescents from 11 international studies. Associations between questionnaire-based sleep durations, bedtimes and four groups of combined bedtimes and sleep lengths (later-shorter [reference]/earlier-shorter/later-longer/earlier-longer) with measured adiposity (body mass index [BMI] and waist circumference z-scores) and weight status, were investigated. RESULTS: In children, longer sleep durations were consistently associated with lower adiposity markers, and earlier bedtimes were related to lower BMI z-score. Compared to sleeping <10 h, longer baseline sleep duration favourably predicted Δwaist z-score in girls (≥10 and <11 h (ß-coefficient (95% confidence interval [CI])): -0.06 (-0.12 to -0.01)) and boys (≥11 h: -0.10 [-0.18 to -0.01]). Combined groups that were defined by longer sleep (later-longer and earlier-longer sleep patterns) were associated with lower adiposity, and later-longer sleep favourably predicted Δwaist z-score in girls (-0.09 [-0.15 to -0.02]). In adolescents, longer sleep durations and earlier bedtimes were associated with lower BMI z-score in the whole sample, and also with lower waist z-score in boys. Combined groups that were characterized by earlier bedtimes were associated with the same outcomes. For example, earlier-shorter (-0.22 (-0.43 to -0.01) and earlier-longer (-0.16 (-0.25 to -0.06) sleep were both associated with lower BMI z-score. CONCLUSIONS: If the associations are causal, longer sleep duration and earlier bedtimes should be targeted for obesity prevention, emphasizing longer sleep for children and earlier bedtimes for adolescents.