Plasma Zinc Concentration,Body Composition and Physical Activity in Obese Preschool Children

Zinc (Zn) deficiency and obesity can be observed together in some developing countries. Zn deficiency may enhance fat deposition and decrease lean mass accrual, which in turn, appears to influence physical activity (PA), although this has not yet been evaluated in obese children. The objective of the study was to find out the association between measurements of plasma Zn and serum leptin, body composition, and PA in Chilean obese preschool children. Seventy-two 18- to 36-month-old obese children [weight-for-length/height z score (WHZ) > 2.0 SD], belonging to low socioeconomic communities, participated in the study. Plasma Zn, serum leptin, weight, waist circumference, height, total body water (TBW) assessed by deuterium isotopic dilution technique and daily activity, measured by registering 48 h with an accelerometer, were evaluated. We found 82% of children with WHZ > 3 SD. The geometric mean Zn intake was 6.2 ± 2.5 mg/day. The mean plasma Zn was 91.8 ± 11.4 μg/dL, with 10% of the children having levels <80 μg/dL. No correlation was found between plasma Zn concentrations and either weight, WHZ, or waist circumference. Serum leptin was lower in males than in females (2.9 ± 2.8 vs 6.8 ± 5.0 ng/mL, respectively; p < 0.001). TBW was different between males and females (56.2 ± 5.4 vs 52.8 ± 4.3% body weight, respectively; p = 0.004), but no significant association was found between TBW and plasma Zn. Moderate + intense PA, (as percentage of wake time), was greater in males than in females (6.3 ± 3.1% vs 3.4 ± 2.3%, respectively; p < 0.001), but it was not significantly correlated to plasma Zn. In conclusion, plasma Zn was not associated with body composition as assessed by TBW, serum leptin, or with the magnitude of physical activity in Chilean overweight preschool children.     

Associations of TV Viewing Duration,Meals and Snacks Eaten When Watching TV,and a TV in the Bedroom with Child Adiposity

Objective

This study aimed to examine the associations of TV parameters with adiposity in early life.

Methods

Data were collected as part of the Born in Bradford (BiB) longitudinal birth cohort study. Child TV viewing duration was parent reported, and BMI, the sum of triceps and subscapular skinfolds, and waist circumference were measured at ~12, 18, 24, and 36 months of age in 1,338 children. Mixed effects models were used to quantify adjusted associations of TV viewing duration with adiposity markers, incorporating data from all time points. Linear regression was used to investigate differences in adiposity levels across frequencies of eating meals and snacks while watching TV at age ~24 months and between children who did and did not have a TV in their bedroom at age ~36 months.

Results

Every 1 h/d of TV viewing was associated with a 0.075‐cm larger (95% CI: 0.0034‐0.15) waist circumference, independent of covariates including sleep duration, dietary factors, and physical activity level. There was no evidence for any other associations.

Conclusions

TV viewing duration is independently associated with abdominal adiposity in young children. Limiting TV viewing from an early age may be important for primary prevention of obesity.     

The Associations of Objectively Measured Physical Activity and Sedentary Time with Cognitive Functions in School-Aged Children

Low levels of physical activity among children have raised concerns over the effects of a physically inactive lifestyle, not only on physical health but also on cognitive prerequisites of learning. This study examined how objectively measured and self-reported physical activity and sedentary behavior are associated with cognitive functions in school-aged children. The study population consisted of 224 children from five schools in the Jyväskylä school district in Finland (mean age 12.2 years; 56% girls), who participated in the study in the spring of 2011. Physical activity and sedentary time were measured objectively for seven consecutive days using the ActiGraph GT1M/GT3X accelerometer. Self-reported moderate to vigorous physical activity (MVPA) and screen time were evaluated with the questions used in the “WHO Health Behavior in School-aged Children” study. Cognitive functions including visual memory, executive functions and attention were evaluated with a computerized Cambridge Neuropsychological Test Automated Battery by using five different tests. Structural equation modeling was applied to examine how objectively measured and self-reported MVPA and sedentary behavior were associated with cognitive functions. High levels of objectively measured MVPA were associated with good performance in the reaction time test. High levels of objectively measured sedentary time were associated with good performance in the sustained attention test. Objectively measured MVPA and sedentary time were not associated with other measures of cognitive functions. High amount of self-reported computer/video game play was associated with weaker performance in working memory test, whereas high amount of computer use was associated with weaker performance in test measuring shifting and flexibility of attention. Self-reported physical activity and total screen time were not associated with any measures of cognitive functions. The results of the present study propose that physical activity may benefit attentional processes. However, excessive video game play and computer use may have unfavorable influence on cognitive functions.     

Association of Family Environment with Children's Television Viewing and with Low Level of Physical Activity

Objective: This study examined associations between the family environment and children's television (TV) viewing and likelihood of being low‐active. Research Methods and Procedures: In 2001, children were recruited from 19 primary schools in Melbourne, Australia. Parents completed a questionnaire about their child's TV viewing and the family environment. Children also completed a questionnaire and wore an accelerometer for 8 days. Movement counts were used to identify low‐active children (lowest quartile). Data were analyzed in May 2004. Results: The sample consisted of 878 children (mean age = 11.5 ± 0.6 yrs). Multiple logistic regression revealed that socioeconomic status [adjusted odds ratios (AOR) = 0.4 boys], frequency families watched TV together (AOR = 2.0 boys), mothers’ (AOR = 1.8 boys; AOR = 2.5 girls) and fathers’ (AOR = 2.6 boys; AOR = 2.8 girls) TV viewing, and rules prohibiting TV during mealtimes (AOR = 0.6 boys; AOR = 0.6 girls) related to children watching TV ≥2 h/d. Variables associated with low‐level physical activity included self‐reported enjoyment of Internet use (AOR = 1.7 boys) and preference for watching TV (AOR = 2.3 girls), perception that mother uses computer a lot (AOR = 1.9 boys) and likes using the computer (AOR = 0.6 girls), fathers’ reported computer/electronic games use (AOR = 1.7 girls), frequency families used computer together (AOR = 0.4 girls), rules that TV viewing must be supervised (AOR = 1.9 boys; AOR = 0.6 girls), and having pay TV (AOR = 0.6 boys) and electronic games at home (AOR = 2.6 boys). Discussion: These findings suggest that the relationships between the family environment and TV viewing and low‐level activity are complex and that these behaviors are distinct.     

Physical Activity,TV Viewing,and Weight in U.S. Youth: 1999 Youth Risk Behavior Survey

Objective: To examine the relationship between physical activity, TV watching, and weight in U.S. youth ages 14 to 18 years. Research Methods and Procedures: Data from a nationally representative sample of 15,143 U.S. high‐school students participating in the 1999 Centers for Disease Control and Prevention (CDC) Youth Risk Behavior Survey were examined. Prevalence rates of participation in moderate physical activity (MPA), vigorous physical activity (VPA), and television watching (TV) were determined. The association between MPA, VPA, TV and the body mass index (BMI) and overweight status (BMI ≥85th percentile of age‐ and sex‐specific CDC/National Center for Health Statistics reference values) were examined by analysis of covariance and logistic regression. Results: Overall, 45% reported participating in MPA ≥3 d/wk, 65% reported participating in VPA ≥3 d/wk, and 25% reported watching TV ≥4 h/school day. Boys reporting six to seven bouts of MPA had a significantly lower BMI compared with boys reporting three to five or less than two. The mean BMI differed significantly between the lowest and highest levels of MPA groups in girls. The mean BMI was significantly lower in the highest VPA group compared with the other two groups in both sexes. There was a significant graded response for BMI across all levels of TV. Decreased levels of MPA and 3 to 4 days of VPA were significantly associated with an increased risk of overweight in boys when compared with those engaging in 6 to 7 d/wk (odds ratio = 1.26 to 1.37). A graded response existed between TV and overweight in both sexes. Boys and girls were ～20% to 25% less likely to be classified as overweight if they reported 2 to 3 hours of TV per day and ～40% less likely to be classified as overweight if they reported ≤1 hour of TV per day compared with those who watched ≥4 hours of TV. In general, youth who engaged in less physical activity watched more TV per week. Discussion: Increased levels of physical activity are associated with a lower BMI and less TV watching. However, the relationship between TV watching and weight status is more pronounced.     

Validation of the TracmorD Triaxial Accelerometer to Assess Physical Activity in Preschool Children

Objectives: To assess validity evidence of Tracmor_D to determine energy used for physical activity in 3‐4‐year‐old children. Design and Methods: Participants were randomly selected from GECKO Drenthe cohort (n = 30, age 3.4 ± 0.3 years). Total energy expenditure (TEE) was measured using the doubly labeled water method. Sleeping metabolic rate (SMR) was measured by indirect calorimetry (Deltatrac). TEE and SMR were used to calculate physical activity level (PAL) and activity energy expenditure (AEE). Physical activity was monitored using a DirectLife triaxial accelerometer, Tracmor_D with activity counts per minute (ACM) and activity counts per day (ACD) as outcome measures. Results: The best predictor for PAL was ACM with gender and weight, the best predictor for AEE was ACM alone (backward regression, R² = 0.50, P = 0.010 and R² = 0.31, P = 0.011, respectively). With ACD, the prediction model for PAL included ACD, height, gender, and sleep duration (R² = 0.48, P = 0.033), the prediction model for AEE included ACD, gender and sleep duration (R² = 0.39, P = 0.042). The accelerometer was worn for 5 days, but 3 days did not give a different estimated PAL. Conclusion: Tracmor_D provides moderate‐to‐strong validity evidence that supports its use to evaluate energy used for physical activity in 3‐4‐year‐old children.     

Rhinitis Symptoms and Asthma among Parents of Preschool Children in Relation to the Home Environment in Chongqing,China

Risk factors for rhinitis and asthma in the home environment were studied by a questionnaire survey. Parents of 4530 1–8 year old children (one parent per child) from randomly selected kindergartens in Chongqing, China participated. 70.4% were females; 47.1% had rhinitis symptoms in the last three months (current rhinitis, CR); 1.6% reported a history of allergic asthma (AA); 2.7% reported a history of allergic rhinitis (AR); 16.4% were current smokers; 50.8% males and 2.4% females were current smokers. Stuffy odor, unpleasant odor, tobacco smoke odor and dry air were associated with CR (adjustment for gender, current smoking and other perceptions of odor or humidity). Associations between home environment and CR, AR, and AA were studied by multiple logistic regression analyses, adjusting for gender, current smoking and other significant home factors. Living near a main road or highway was a risk factor for both CR (OR(95%CI): 1.31(1.13,1.52)) and AR (OR(95%CI): 2.44(1.48,4.03)). Other risk factors for CR included living in rural areas (OR(95%CI): 1.43(1.10,1.85)), new furniture (OR(95%CI): 1.28(1.11,1.49)), water damage (OR(95%CI): 1.68(1.29,2.18)), cockroaches (OR(95%CI): 1.46(1.23,1.73)), and keeping pets (OR(95%CI): 1.24(1.04,1.49)). Other risk factors for AR included redecoration (OR(95%CI): 2.14(1.34,3.41)), mold spots (OR(95%CI): 2.23(1.06,4.68)), window pane condensation (OR(95%CI): 2.04(1.28,3.26)). Water damage was the only home factor associated with AA (2.56(1.34,4.86)). Frequently put bedding to sunshine was protective for CR (OR(95%CI): 0.79(0.68,0.92); cleaning every day was protective for AR (OR(95%CI): 0.40(0.22,0.71)). In conclusion, parents'' CR and AR were related to a number of factors of the home environment.     

Associations of Sedentary Behaviour,Physical Activity,Blood Pressure and Anthropometric Measures with Cardiorespiratory Fitness in Children with Cerebral Palsy

Background

Children with cerebral palsy (CP) have poor cardiorespiratory fitness in comparison to their peers with typical development, which may be due to low levels of physical activity. Poor cardiorespiratory fitness may contribute to increased cardiometabolic risk.

Purpose

The aim of this study was to determine the association between sedentary behaviour, physical activity and cardiorespiratory fitness in children with CP. An objective was to determine the association between cardiorespiratory fitness, anthropometric measures and blood pressure in children with CP.

Methods

This study included 55 ambulatory children with CP [mean (SD) age 11.3 (0.2) yr, range 6-17 yr; Gross Motor Function Classification System (GMFCS) levels I and II]. Anthropometric measures (BMI, waist circumference and waist-height ratio) and blood pressure were taken. Cardiorespiratory fitness was measured using a 10 m shuttle run test. Children were classified as low, middle and high fitness according to level achieved on the test using reference curves. Physical activity was measured by accelerometry over 7 days. In addition to total activity, time in sedentary behaviour and light, moderate, vigorous, and sustained moderate-to-vigorous activity (≥10 min bouts) were calculated.

Results

Multiple regression analyses revealed that vigorous activity (β = 0.339, p<0.01), sustained moderate-to-vigorous activity (β = 0.250, p<0.05) and total activity (β = 0.238, p<0.05) were associated with level achieved on the shuttle run test after adjustment for age, sex and GMFCS level. Children with high fitness spent more time in vigorous activity than children with middle fitness (p<0.05). Shuttle run test level was negatively associated with BMI (r² = -0.451, p<0.01), waist circumference (r² = -0.560, p<0.001), waist-height ratio (r² = -0.560, p<0.001) and systolic blood pressure (r² = -0.306, p<0.05) after adjustment for age, sex and GMFCS level.

Conclusions

Participation in physical activity, particularly at a vigorous intensity, is associated with high cardiorespiratory fitness in children with CP. Low cardiorespiratory fitness is associated with increased cardiometabolic risk.     

Two‐Year Changes in Child Weight Status,Diet, and Activity by Neighborhood Nutrition and Physical Activity Environment

Objective

The aim of this study was to examine 2‐year changes in weight status and behaviors among children living in neighborhoods differing on nutrition and activity environments.

Methods

A prospective observational study, the Neighborhood Impact on Kids study, was conducted in King County, Washington, and San Diego County, California. Children 6 to 12 years old and a parent or caregiver completed Time 1 (n = 681) and Time 2 (n = 618) assessments. Children lived in neighborhoods characterized as “high/favorable” or “low/unfavorable” in nutrition and activity environments, respectively (four neighborhood types). Child BMI z score and overweight or obesity status were primary outcomes, with diet and activity behaviors as behavioral outcomes.

Results

After adjusting for sociodemographics and Time 1 values, children living in two of the three less environmentally supportive neighborhoods had significantly less favorable BMI z score changes (+0.11, 95% CI: 0.01‐0.21; + 0.12, 95% CI: 0.03‐0.21), and all three less supportive neighborhoods had higher overweight or obesity (relative risks, 1.41‐1.49; 95% CI: 1.13‐1.80) compared with children in the most environmentally supportive neighborhoods. Changes in daily energy intake and sedentary behavior by neighborhood type were consistent with observed weight status changes, with unexpected findings for physical activity.

Conclusions

More walkable and recreation‐supportive environments with better nutrition access were associated with better child weight outcomes and related behavior changes.     

Energy Intake and Meal Portions: Associations with BMI Percentile in U.S. Children

Objective: We examined relationships of eating patterns and reported energy intake (rEI) with BMI percentile in U.S. children. Research Methods and Procedures: Two 24‐hour dietary recalls from the Continuing Surveys of Food Intakes by Individuals 1994 to 1996 and 1998 (1005 boys, 990 girls) were averaged, and children were categorized into three age groups: 3 to 5 years (n = 1077), 6 to 11 years (n = 537), and 12 to 19 years (n = 381). Physiologically implausible reports due to reporting bias or abnormal intake (rEI outside ±18% to 23% of predicted energy requirements; pER) were identified. Results: rEI averaged 109 ± 34% and 100 ± 10% of pER in the total and plausible samples, respectively. EI was overreported more in younger children and underreported more in overweight older children. Children with plausible rEI (45.3% of sample) averaged 4.7 eating occasions/d, 589 kcal/meal, 223 kcal/snack, and 2038 kcal/d. rEI was not associated with BMI percentile in the total sample. In the plausible sample, rEI, meal portion size, and meal energy were positively associated with BMI percentile in boys 6 to 11 years and in children 12 to 19 years. No relationships were found in children 3 to 5 years and girls 6 to 11 years. Relationships were more consistent and stronger in the plausible compared with the total sample. Discussion: Excluding implausible dietary reports may be necessary for discerning dietary associations with BMI percentile. EI and meal, but not snack, patterns may play a quantitatively greater role in weight regulation as children age.     

Relationship of the Perceived Social and Physical Environment with Mental Health-Related Quality of Life in Middle-Aged and Older Adults: Mediating Effects of Physical Activity

Background

Mental health conditions are among the leading non-fatal diseases in middle-aged and older adults in Australia. Proximal and distal social environmental factors and physical environmental factors have been associated with mental health, but the underlying mechanisms explaining these associations remain unclear. The study objective was to examine the contribution of different types of physical activity in mediating the relationship of social and physical environmental factors with mental health-related quality of life in middle-aged and older adults.

Methods

Baseline data from the Wellbeing, Eating and Exercise for a Long Life (WELL) study were used. WELL is a prospective cohort study, conducted in Victoria, Australia. Baseline data collection took place in 2010. In total, 3,965 middle-aged and older adults (55–65 years, 47.4% males) completed the SF-36 Health Survey, the International Physical Activity Questionnaire, and a questionnaire on socio-demographic, social and physical environmental attributes. Mediation analyses were conducted using the MacKinnon product-of-coefficients test.

Results

Personal safety, the neighbourhood physical activity environment, social support for physical activity from family or friends, and neighbourhood social cohesion were positively associated with mental health-related quality of life. Active transportation and leisure-time physical activity mediated 32.9% of the association between social support for physical activity from family or friends and mental health-related quality of life. These physical activity behaviours also mediated 11.0%, 3.4% and 2.3% respectively, of the relationship between the neighbourhood physical activity environment, personal safety and neighbourhood social cohesion and mental health-related quality of life.

Conclusions

If these results are replicated in future longitudinal studies, tailored interventions to improve mental health-related quality of life in middle-aged and older adults should use a combined strategy, focusing on increasing physical activity as well as social and physical environmental attributes.     

Associations between Family-Related Factors,Breakfast Consumption and BMI among 10- to 12-Year-Old European Children: The Cross-Sectional ENERGY-Study

Objective

To investigate associations of family-related factors with children’s breakfast consumption and BMI-z-score and to examine whether children’s breakfast consumption mediates associations between family-related factors and children’s BMI-z-score.

Subjects

Ten- to twelve-year-old children (n = 6374; mean age = 11.6±0.7 years, 53.2% girls, mean BMI-z-score = 0.4±1.2) and one of their parents (n = 6374; mean age = 41.4±5.3 years, 82.7% female, mean BMI = 24.5±4.2 kg/m²) were recruited from schools in eight European countries (Belgium, Greece, Hungary, the Netherlands, Norway, Slovenia, Spain, and Switzerland). The children self-reported their breakfast frequency per week. The body weight and height of the children were objectively measured. The parents responded to items on family factors related to breakfast (automaticity, availability, encouragement, paying attention, permissiveness, negotiating, communicating health beliefs, parental self-efficacy to address children’s nagging, praising, and family breakfast frequency). Mediation analyses were performed using multi-level regression analyses (child-school-country).

Results

Three of the eleven family-related variables were significantly associated with children’s BMI-z-score. The family breakfast frequency was negatively associated with the BMI-z-score; permissiveness concerning skipping breakfast and negotiating about breakfast were positively associated with the BMI-z-score. Children’s breakfast consumption was found to be a mediator of the two associations. All family-related variables except for negotiating, praising and communicating health beliefs, were significantly associated with children’s breakfast consumption.

Conclusions

Future breakfast promotion and obesity prevention interventions should focus on family-related factors including the physical home environment and parenting practices. Nevertheless, more longitudinal research and intervention studies to support these findings between family-related factors and both children’s breakfast consumption and BMI-z-score are needed.     

Associations among Active Transportation,Physical Activity,and Weight Status in Young Adults

Objective: To describe prevalence of active, public, and car transit by overweight status and amount of leisure‐time physical activity in a nationally representative cohort of ethnically diverse young adults. Research Methods and Procedures: Questionnaire data on patterns of transportation were collected from U.S. adolescents enrolled in Wave III (2001) of the National Longitudinal Study of Adolescent Health (N = 10, 771). Measured height and weight data were used to calculate BMI and classify adults by overweight status (BMI ≥ 25). Self‐reported physical activity data were used to classify adults into those who achieved ≥ 5 bouts of weekly moderate‐vigorous physical activity and those who did not. Results were stratified by overweight and physical activity status. Results: The vast majority of young adults used car transit (work, 90.4%; school, 74.7%). A small proportion of young adults used active means of transportation to work (8.1%) and school (26.7%), and fewer used public transportation to work or school (<10%). The proportion of individuals using active transportation was higher among the nonoverweight traveling to work (9.2%) and school (29.7%) and among the more active traveling to work (15.2%) and school (37.0%) relative to the overweight and less active young adults. Discussion: The vast majority of young adults of all racial/ethnic backgrounds, particularly blacks and Hispanics, did not use active transportation to school and/or work. Active transportation was more common among nonoverweight and more active young adults, of high socioeconomic status, particularly full‐time students. Population‐level efforts (and environmental supports) to increase non‐leisure physical activity, particularly active transportation, are sorely needed as a means of supporting and promoting overall physical activity.     

Associations of Objectively Assessed Physical Activity and Sedentary Time with All-Cause Mortality in US Adults: The NHANES Study

Background

Sedentary behavior is related to increased mortality risk. Whether such elevated risk can be offset by enhanced physical activity has not been examined using accelerometry data.

Materials and Methods

We examined the relations of sedentary time and physical activity to mortality from any cause using accelerometry data among 1,677 women and men aged 50 years or older from the National Health and Nutrition Examination Survey (NHANES) 2003–2004 cycle with follow-up through December 31, 2006.

Results

During an average follow-up of 34.67 months and 4,845.42 person-years, 112 deaths occurred. In multivariate Cox proportional hazard models, greater sedentary time (≥ median of 8.60 hours/day) was associated with increased risk of mortality from any cause (relative risk (RR) = 2.03; 95% confidence interval (CI) = 1.09-3.81). Low level of moderate to vigorous physical activity (< median of 6.60 minutes/day) was also related to enhanced all-cause mortality risk (RR = 3.30; 95% CI = 1.33-8.17). In combined analyses, greater time spent sedentary and low levels of moderate to vigorous physical activity predicted a substantially elevated all-cause mortality risk. As compared with the combination of a low sedentary level and a high level of moderate to vigorous physical activity, the risks of mortality from all causes were 4.38 (95% CI = 1.26-15.16) for low levels of both sedentary time and physical activity, 2.79 (95% CI = 0.77-10.12) for greater time spent sedentary and high physical activity level, and 7.79 (95% CI = 2.26-26.82) for greater time spent sedentary and low physical activity level. The interaction term between sedentary time and moderate to vigorous physical activity was not statistically significant (p = 0.508).

Conclusions

Both high levels of sedentary time and low levels of moderate to vigorous physical activity are strong and independent predictors of early death from any cause. Whether a high physical activity level removes the increased risk of all-cause mortality related to sedentariness requires further investigation.     

Physical Activity versus Sedentary Behavior: Associations with Lipoprotein Particle Subclass Concentrations in Healthy Adults

Background

Physical activity (PA) and sedentary behavior (SED) may have independent effects on health and disease. This might be due to PA and SED having distinct effects on lipoprotein metabolism. The aim of this study was to determine associations between lipoprotein subclass particle concentrations (-P) and accelerometer-measured SED and moderate-to-vigorous PA (MVPA) in a sample of healthy adult subjects.

Methods

Lipoprotein subclass particle concentrations were determined by proton nuclear magnetic resonance spectroscopy, whereas SED and MVPA were measured using Agtigraph GT1M and GT3X+ accelerometers. We obtained valid data in 73 subjects (30 men and 43 women, age 40.5 ± 10.6 years; body mass index 24.0 ± 2.8). Multiple regression analysis was used to determine associations (partial correlations) with lipoproteins.

Results

Positive associations were detected between SED and small VLDL-P, large LDL-P and TG (partial r = 0.24 to 0.25, p < .047). Corresponding associations were non-significant for MVPA (partial r = -0.12 to 0.04, p > .355). On the contrary, MVPA was positively associated with large HDL-P, average HDL size, Apo A1 and HDL-cholesterol (partial r = 0.28 to 0.50, p < .027), whereas SED was not (partial r = -0.06 to 0.07, p > .607).

Conclusion

There might be a specific effect of SED versus MVPA on lipoprotein metabolism. However, our results must be interpreted carefully due to possible effect-modification by gender and a low sample size. Thus, our findings should be viewed as preliminary.     

Validation and Calibration of Physical Activity Monitors in Children

Objective: This study was designed to validate accelerometer-based activity monitors against energy expenditure (EE) in children; to compare monitor placement sites; to field-test the monitors; and to establish sedentary, light, moderate, and vigorous threshold counts. Research Methods and Procedures: Computer Science and Applications Actigraph (CSA) and Mini-Mitter Actiwatch (MM) monitors, on the hip or lower leg, were validated and calibrated against 6-hour EE measurements by room respiration calorimetry, activity by microwave detector, and heart rate by telemetry in 26 children, 6 to 16 years old. During the 6 hours, the children performed structured activities, including resting metabolic rate (RMR), Nintendo, arts and crafts, aerobic warm-up, Tae Bo, treadmill walking and running, and games. Activity energy expenditure (AEE) computed as EE − RMR was regressed against counts to derive threshold counts. Results: The mean correlations between EE or AEE and counts were slightly higher for MM-hip (r = 0.78 ± 0.06) and MM-leg (r = 0.80 ± 0.05) than CSA-hip (r = 0.66 ± 0.08) and CSA-leg (r = 0.73 ± 0.07). CSA and MM performed similarly on the hip (inter-instrument r = 0.88) and on the lower leg (inter-instrument r = 0.89). Threshold counts for the CSA-hip were <800, <3200, <8200, and ≥8200 for sedentary, light, moderate, and vigorous categories, respectively. For the MM-hip, the threshold counts were <100, <900, <2200, and ≥2200, respectively. Discussion: The validation of the CSA and MM monitors against AEE and their calibration for sedentary, light, moderate, and vigorous thresholds certify these monitors as valid, useful devices for the assessment of physical activity in children.     

Sleep Duration,Schedule and Quality among Urban Chinese Children and Adolescents: Associations with Routine After-School Activities

Background

With rapid urbanization accompanied by lifestyle changes, children and adolescents living in metropolitan areas are faced with many time use choices that compete with sleep. This study reports on the sleep hygiene of urban Chinese school students, and investigates the relationship between habitual after-school activities and sleep duration, schedule and quality on a regular school day.

Methods

Cross-sectional, school-based survey of school children (Grades 4–8) living in Shanghai, China, conducted in 2011. Self-reported data were collected on students’ sleep duration and timing, sleep quality, habitual after-school activities (i.e. homework, leisure-time physical activity, recreational screen time and school commuting time), and potential correlates.

Results

Mean sleep duration of this sample (mean age: 11.5-years; 48.6% girls) was 9 hours. Nearly 30% of students reported daytime tiredness. On school nights, girls slept less (p<0.001) and went to bed later (p<0.001), a sex difference that was more pronounced in older students. Age by sex interactions were observed for both sleep duration (p=0.005) and bedtime (p=0.002). Prolonged time spent on homework and mobile phone playing was related to shorter sleep duration and later bedtime. Adjusting for all other factors, with each additional hour of mobile phone playing, the odds of daytime tiredness and having difficulty maintaining sleep increased by 30% and 27% among secondary students, respectively.

Conclusion

There are sex differences in sleep duration, schedule and quality. Habitual activities had small but significant associations with sleep hygiene outcomes especially among secondary school students. Intervention strategies such as limiting children’s use of electronic screen devices after school are implicated.