Quantity versus quality of objectively measured sleep in relation to body mass index in children: cross-sectional and longitudinal analyses.

BACKGROUND/OBJECTIVES: Although sleep duration is well established as a risk factor for child obesity, how measures of sleep quality relate to body size is less certain. The aim of this study was to determine how objectively measured sleep duration, sleep timing, and sleep quality were related to body mass index (BMI) cross-sectionally and longitudinally in school-aged children. SUBJECTS/METHODS: All measures were obtained at baseline, 12 and 24 months in 823 children (51% female, 53% European, 18% Maori, 12% Pacific, 9% Asian) aged 6-10 years at baseline. Sleep duration, timing, and quality were measured using actigraphy over 7 days, height and weight were measured using standard techniques, and parents completed questionnaires on demographics (baseline only), dietary intake, and television usage. Data were analysed using imputation; mixed models, with random effects for person and age, estimated both a cross-sectional effect and a longitudinal effect on BMI z-score, adjusted for multiple confounders. RESULTS: The estimate of the effect on BMI z-score for each additional hour of sleep was -0.22 (95% CI: -0.33, -0.11) in cross-sectional analyses and -0.05 (-0.10, -0.004) in longitudinal analyses. A greater effect was observed for weekday sleep duration than weekend sleep duration but variability in duration was not related to BMI z-score. While sleep timing (onset or midpoint of sleep) was not related to BMI, children who were awake in the night more frequently (0.19; 0.06, 0.32) or for longer periods (0.18; 0.06, 0.36) had significantly higher BMI z-scores cross-sectionally, but only the estimates for total time awake (minutes) were significant longitudinally (increase in BMI z-score of 0.04 for each additional hour awake). CONCLUSION: The beneficial effect of a longer sleep duration on BMI was consistent in children, whereas evidence for markers of sleep quality and timing were more variable.

Twenty-Four-Hour Diet recall and Diet records compared with 24-hour urinary excretion to predict an individual's sodium consumption: A Systematic Review.

This systematic literature review aimed to investigate whether 24 hour diet recall and diet records are reliable and valid ways to measure usual dietary sodium intake compared with 24 hour urinary assessment. We searched electronic databases Medline, Embase, Cinahl, Lilacs, Google Scholar and the Cochrane Library using pre-defined terms Studies were eligible for inclusion if they assessed adult humans in free-living settings, and if they included dietary assessment and 24 hours urinary collection for assessment of sodium intake in the same participants. Studies that included populations with an active disease state that might interfere with normal sodium metabolism were excluded. Results of 20 studies using 24 hour diet recall recall (including 14 validation studies) and 10 studies using food records (including six validation studies) are included in this review. Correlations between estimates from dietary assessment and urinary excretion ranged from 0.16 to 0.72 for 24 hour diet recall, and 0.11 to 0.49 for food diaries. Bland-Altman analysis in two studies of 24 hour diet recall showed poor agreement with 24 hours urinary sodium excretion. These results show that 24 hour diet recall and diet records inaccurately measure dietary sodium intake in individuals compared with the gold standard 24 hours urinary excretion. Validation studies of dietary assessment methods should include multiple days of assessment and 24 hours urine collection, use relevant food composition databases and Bland-Altman methods of analysis.

Sleep patterns in children differ by ethnicity: cross-sectional and longitudinal analyses using actigraphy.

OBJECTIVES: To determine whether sleep patterns (duration, timing, efficiency) differ by ethnicity. DESIGN: Longitudinal study. SETTING: Dunedin, New Zealand. PARTICIPANTS: A total of 939 children (48% male) aged 4-12 years (572 European, 181 Maori, 111 Pacific, 75 Asian). MEASUREMENTS: All measurements were obtained at months 0, 12, and 24. Anthropometry was obtained using standard techniques, and parents completed questionnaires assessing demographics, dietary intake, and television habits of children. Sleep and physical activity were measured using Actigraph accelerometers over 1 week. Differences in sleep outcomes according to ethnicity were adjusted for demographics, weight status, and behavioral variables using mixed models. RESULTS: Pacific children had greater body mass index and were more likely to live in deprived areas than children from other ethnic groups (all P<.001), but few differences were observed in behavioral variables. Pacific Island children slept 16 (95% confidence interval, 7-25) minutes less per night than New Zealand European children, predominantly as a result of later bedtimes (29; 20-38 minutes). By contrast, sleep efficiency did not differ by ethnicity or over time (all P≥.118). Maori children did not show the same relative deficits in sleep, displaying similar results to European children. Sleep duration decreased by 8 minutes (95% confidence interval, 6-10) a night each year over 2 years, and change over time did not differ by ethnicity (all P≥.165). CONCLUSIONS: From a young age, Pacific children had poorer sleep patterns than European children, and these patterns were maintained over 2 years.

Assessment of dietary sodium intake using a food frequency questionnaire and 24-hour urinary sodium excretion: a systematic literature review.

Food frequency questionnaires (FFQs) are often used to assess dietary sodium intake, although 24-hour urinary excretion is the most accurate measure of intake. The authors conducted a systematic review to investigate whether FFQs are a reliable and valid way of measuring usual dietary sodium intake. Results from 18 studies are described in this review, including 16 validation studies. The methods of study design and analysis varied widely with respect to FFQ instrument, number of 24-hour urine collections collected per participant, methods used to assess completeness of urine collections, and statistical analysis. Overall, there was poor agreement between estimates from FFQ and 24-hour urine. The authors suggest a framework for validation and reporting based on a consensus statement (2004), and recommend that all FFQs used to estimate dietary sodium intake undergo validation against multiple 24-hour urine collections.

Change of School Playground Environment on Bullying: A Randomized Controlled Trial.

OBJECTIVE: To investigate whether increasing risk and challenge in primary school playgrounds influences interactions between children. METHODS: In a 2-year cluster-randomized controlled trial, 8 control schools were asked to not change their play environment, whereas 8 intervention schools increased opportunities for risk and challenge (eg, rough-and-tumble play), reduced rules, and added loose parts (eg, tires). Children (n = 840), parents (n = 635), and teachers (n = 90) completed bullying questionnaires at baseline, 1 (postintervention), and 2 (follow-up) years. RESULTS: Intervention children reported higher odds of being happy at school (at 2 years, odds ratio [OR]: 1.64; 95% confidence interval [CI]: 1.20-2.25) and playing with more children (at 1 year, OR: 1.66; 95% CI: 1.29-2.15) than control children. Although intervention children indicated they were pushed/shoved more (OR: 1.33; 95% CI: 1.03-1.71), they were less likely to tell a teacher (OR: 0.69; 95% CI: 0.52-0.92) at 2 years. No significant group differences were observed in parents reporting whether children had "ever" been bullied at school (1 year: P = .23; 2 years: P = .07). Intervention school teachers noticed more bullying in break time at 1 year (difference in scores: 0.20; 95% CI: 0.06-0.34; P = .009), with no corresponding increase in children reporting bullying to teachers (both time points, P ≥ .26). CONCLUSIONS: Few negative outcomes were reported by children or parents, except for greater pushing/shoving in intervention schools. Whether this indicates increased resilience as indicated by lower reporting of bullying to teachers may be an unanticipated benefit.

The stability of sleep patterns in children 3 to 7 years of age.

OBJECTIVE: To determine the reliability and stability of sleep (duration and quality) over time in young children using repeated accelerometer estimates of sleep. STUDY DESIGN: One hundred ninety-four children wore Actical accelerometers for 5-day periods (24-hour monitoring) at 3, 4, 5, 5.5, 6.5, and 7 years of age. Sleep variables of interest (duration, onset, offset, latency, efficiency, and wake after sleep onset) were estimated using the Sadeh algorithm within a commercial data reduction program (ActiLife). Children were divided into various groups according to sleep stability, and demographic and behavioral differences were compared across groups by ANOVA. RESULTS: All measures of sleep quantity and quality required 4-7 days of accelerometry to obtain acceptable reliability estimates, except morning wake time (2-4 days), and sleep latency (11-21 days). Average year-to-year correlations were only moderate for most measures (r = 0.41-0.51), but considerably higher than those observed for sleep latency, efficiency, and wake after onset (r = 0.15-0.24). Only 29 children were classified as sleep-stable over the 4 years. These children were less likely to be from ethnic minority groups (P = .017) and had higher levels of day-time physical activity (P = .032). CONCLUSIONS: Sleep patterns in children are not particularly stable, showing considerable variation both within a week and across the years. Few children exhibit stable sleep patterns over time, yet characterization of these children might provide further information regarding how sleep benefits health.

Do more active children sleep more? A repeated cross-sectional analysis using accelerometry.

AIM: To determine whether levels of daytime physical activity are associated with sleep duration and night waking in children assessed using accelerometry, and if these associations change over time. METHODS: 24-hour accelerometry data were obtained from 234 children at 3, 5 and 7 years of age for at least 5 days at each time. Sleep duration was estimated using the Sadeh algorithm. Time spent in sedentary, light and moderate-vigorous (MVPA) activity was established using published cut-points. Appropriate statistical techniques were utilised to account for the closed nature of the data (24-hour periods). RESULTS: Time spent asleep was related more to sedentary or light activity and not to MVPA. The most active (95th percentile) children spent 55-84 fewer minutes asleep and 16-19 more minutes awake at night compared to the least active (5th percentile) children. Children with later bedtimes slept less at night (30-40 minutes) and undertook more sedentary (10-15 minutes) but also more light (18-23 minutes) activity during the day. However, no differences in MVPA were apparent according to bedtime. Children slept slightly less on weekend nights (11 minutes) compared with week-nights, but only at 3 years of age. Most relationships were broadly similar at 3, 5 and 7 years of age. CONCLUSION: Children who are more physically active during the day have shorter total sleep time and are more awake at night than less active children. The protective effect of sleep on obesity does not appear to be mediated by increased physical activity.

Changes in physical activity over time in young children: a longitudinal study using accelerometers.

Previous research has suggested that marked declines in physical activity occur during the preschool years, and across the transition into school. However, longitudinal studies using objective measures of activity have been limited by sample size and length of follow-up. The aims of this study were to determine how overall activity and time in different intensities of activity change in children followed from 3 to 7 years. Children (n = 242) wore Actical accelerometers at 3, 4, 5, 5.5, 6.5 and 7 years of age during all waking and sleeping hours for a minimum of 5 days. Time in sedentary (S), light (L), moderate (M), and vigorous (V) physical activity was determined using available cut points. Data were analyzed using a mixed model and expressed as counts per minute (cpm, overall activity) and the ratio of active time to sedentary time (LMV:S), adjusted for multiple confounders including sex, age, time worn, and weather. At 5 years, physical activity had declined substantially to around half that observed at 3 years. Although starting school was associated with a further short-term (6-month) decline in activity (cpm) in both boys (difference; 95% CI: -98; -149, -46) and girls (-124; -174, -74, both P<0.001), this proved to be relatively transient; activity levels were similar at 6-7 years as they were just prior to starting school. Boys were more physically active than girls as indicated by an overall 12% (95% CI: 2, 22%) higher ratio of active to sedentary time (P = 0.014), but the pattern of this difference did not change from 3 to 7 years. Time worn and weather variables were significant predictors of activity. In conclusion, both boys and girls show a marked decline in activity from 3 to 4 years of age, a decrease that is essentially maintained through to 7 years of age. Factors driving this marked decrease need to be determined to enable the development of targeted interventions.

School playgrounds and physical activity policies as predictors of school and home time activity.

BACKGROUND: Previous work has suggested that the number of permanent play facilities in school playgrounds and school-based policies on physical activity can influence physical activity in children. However, few comparable studies have used objective measures of physical activity or have had little adjustment for multiple confounders. METHODS: Physical activity was measured by accelerometry over 5 recess periods and 3 full school days in 441 children from 16 primary schools in Dunedin, New Zealand. The number of permanent play facilities (swing, fort, slide, obstacle course, climbing wall etc) in each school playground was counted on three occasions by three researchers following a standardized protocol. Information on school policies pertaining to physical activity and participation in organized sport was collected by questionnaire. RESULTS: Measurement of school playgrounds proved to be reliable (ICC 0.89) and consistent over time. Boys were significantly more active than girls (P < 0.001), but little time overall was spent in moderate-vigorous physical activity (MVPA). Boys engaged in MVPA for 32 (SD 17) minutes each day of which 17 (10) took place at school compared with 23 (14) and 11 (7) minutes respectively in girls. Each additional 10-unit increase in play facilities was associated with 3.2% (95% CI 0.0-6.4%) more total activity and 8.3% (0.8-16.3%) more MVPA during recess. By contrast, school policy score was not associated with physical activity in children. CONCLUSION: The number of permanent play facilities in school playgrounds is associated with higher physical activity in children, whereas no relationship was observed for school policies relating to physical activity. Increasing the number of permanent play facilities may offer a cost-effective long-term approach to increasing activity levels in children.

The quality of diabetes care: a comparison between patients enrolled and not enrolled on a regional diabetes register.

AIMS: To determine whether diabetic patients enrolled on a regional diabetes register that provides annual general practitioner audit and recall reports receive better care than diabetic patients not enrolled. METHODS: Regional diabetes register enrolment status, demographic, clinical and laboratory data for the 2005 year were collected for identified diabetic patients attending 108 of 123 participating general practitioners. Means and standard deviations, or frequencies and percentages were calculated for the two study populations. Characteristics were compared with t-tests or the Chi square test. RESULTS: 3646 of 4749 identified diabetic patients were enrolled on the register and 1103 were not. The non-register population was younger by 1.8 years and for more than half of this population smoking status was unknown. Statistically significantly higher proportions of the register population had most recommended process measures (height, weight, feet, retina, urine ACR) completed within the audit interval. Higher proportions of the register population were prescribed ACE inhibitors (55 vs 47%), other antihypertensives (32 vs 27%) or lipid modifying medication (61 vs 54%). Co-morbidities were common in both groups. CONCLUSIONS: Well-organised centralised diabetes registers provide additional benefits for people with diabetes care. Up to date primary care registers with good call-recall systems are necessary for the delivery of effective structured diabetes care.

Economic evaluation of a community-based obesity prevention program in children: the APPLE project.

Effective strategies are urgently required to reduce the prevalence of obesity during growth. Determining which strategies are most successful should also include analysis of their relative costs. To date, few obesity prevention studies in children have reported data concerning cost-effectiveness. The aim of this study was to assess the costs and health benefits of implementing the APPLE (A Pilot Program for Lifestyle and Exercise) project, a 2-year controlled community-based obesity prevention initiative utilizing activity coordinators (ACs) in schools and nutrition promotion in New Zealand children (5-12 years). The marginal costs of the project in 2006 prices were estimated and compared with the kilograms (kg) of weight-gain prevented for children in the intervention relative to the control arm. The children's health-related quality of life (HRQoL) was also measured using the Health Utilities Index (HUI). The total project cost was NZ$357,490, or NZ$1,281 per intervention child for 2 years (NZ$1 = US$0.67 = UK pound 0.35 = EUR euro 0.52). Weight z-score was reduced by 0.18 (0.13, 0.22) units at 2 years and 0.17 (0.11, 0.23) units at 4 years in intervention relative to control children. Mean HUI values did not differ between intervention and control participants. The reduction in weight z-score observed is equivalent to 2.0 kg of weight-gain prevented at 15 years of age. The relatively simple intervention approach employed by the APPLE project was successful in significantly reducing the rate of excessive weight gain in children, with implementation costs of NZ$664-1,708 per kg of weight-gain prevented over 4 years.

Determining optimal approaches for weight maintenance: a randomized controlled trial.

BACKGROUND: Weight regain often occurs after weight loss in overweight individuals. We aimed to compare the effectiveness of 2 support programs and 2 diets of different macronutrient compositions intended to facilitate long-term weight maintenance. METHODS: Using a 2 x 2 factorial design, we randomly assigned 200 women who had lost 5% or more of their initial body weight to an intensive support program (implemented by nutrition and activity specialists) or to an inexpensive nurse-led program (involving "weigh-ins" and encouragement) that included advice about high-carbohydrate diets or relatively high-monounsaturated-fat diets. RESULTS: In total, 174 (87%) participants were followed-up for 2 years. The average weight loss (about 2 kg) did not differ between those in the support programs (0.1 kg, 95% confidence interval [CI] -1.8 to 1.9, p = 0.95) or diets (0.7 kg, 95% CI -1.1 to 2.4, p = 0.46). Total and low-density lipoprotein (LDL) cholesterol levels were significantly higher among those on the high-monounsaturated-fat diet (total cholesterol: 0.17 mmol/L, 95% CI 0.01 to 0.33; p = 0.040; LDL cholesterol: 0.16 mmol/L, 95% CI 0.01 to 0.31; p = 0.039) than among those on the high-carbohydrate diet. Those on the high-monounsaturated-fat diet also had significantly higher intakes of total fat (5% total energy, 95% CI 3% to 6%, p < 0.001) and saturated fat (2% total energy, 95% CI 1% to 2%, p < 0.001). All of the other clinical and laboratory measures were similar among those in the support programs and diets. INTERPRETATION: A relatively inexpensive program involving nurse support is as effective as a more resource-intensive program for weight maintenance over a 2-year period. Diets of different macronutrient composition produced comparable beneficial effects in terms of weight loss maintenance.

Sustainability of lifestyle changes following an intensive lifestyle intervention in insulin resistant adults: Follow-up at 2-years.

The objective of this study was to determine whether overweight insulin resistant individuals who lost weight and improved cardiovascular risk factors during a 4-month lifestyle intervention could sustain these lifestyle changes in the long-term. Seventy-nine insulin resistant adults were randomised to a control group or either a modest or intensive lifestyle intervention group for 4-months. Thereafter the two intervention groups were combined and all participants were followed-up at 8, 12 and 24 months. Anthropometry, blood pressure, fasting glucose, lipids, insulin and aerobic fitness were measured and dietary intake was assessed. An interview was conducted to determine factors which participants perceived facilitated or hindered maintenance of healthy lifestyle habits. Seventy-two (91.1%), sixty-nine (87.3%) and sixty-two (78.5%) participants were retained at 8, 12 and 24-month respectively. At 4-months the adjusted difference in weight between the modest and control groups was -3.4 kg (95% CI -5.4, -1.3) p=0.002 and intensive and control groups was -4.7 kg (-6.9, -2.4) p=0.0001 respectively. At 2-years there were no significant differences for weight when the initial 3 groups were compared or when the combined intervention group was compared with the control group. At 2-years, 64% of participants reported that more frequent follow-up would have helped them to maintain healthy lifestyle habits. Even intensive counselling for 4-months with 4-monthly and then yearly monitoring were not enough for maintaining lifestyle changes sufficient to sustain weight loss. More frequent monitoring for an indefinite period was perceived by two-thirds of participants as necessary for them to maintain their initial lifestyle changes.

Two-year follow-up of an obesity prevention initiative in children: the APPLE project.

BACKGROUND: In a 2-y intervention targeting increased physical activity and healthy eating in primary school children, the adjusted body mass index (BMI) z score was 0.26 units (95% CI: 0.21, 0.32) lower in intervention than in control children. Few obesity prevention initiatives in children have undertaken follow-up analyses. OBJECTIVE: The objective was to determine whether differences in BMI persisted approximately 2 y after the cessation of the intervention. DESIGN: All children who had at least one measurement of height and weight at any time during the study (baseline and years 1 or 2) were invited to participate in follow-up measurements (height and weight). RESULTS: Five hundred fifty-four of 727 eligible children (76%) participated. Children who refused to participate (n = 14) or had moved from the study area (n = 159) did not differ from the remaining participants in baseline age, sex, or BMI. The mean BMI z score (and 95% CI) remained significantly lower in intervention children at follow-up in the whole group (n = 554; -0.17; -0.25, -0.08) and in the group who underwent at least 1 (n = 389; -0.19; -0.24, -0.13) or 2 (n = 256; -0.21; -0.29, -0.14) full years of intervention. Intervention children were less likely to be overweight, but only in those who were present for the full intervention (n = 256; RR: 0.81; 95% CI: 0.69, 0.94). CONCLUSION: Despite the main intervention initiative (school-based activity coordinators charged with the responsibility of enhancing physical activity and promoting healthy eating) being discontinued at the end of the intervention, continued benefits to BMI remained apparent in intervention children approximately 2 y later.