Carol Maher

Evidence that the prevalence of childhood overweight is plateauing: data from nine countries

Until quite recently, there has been a widespread belief in the popular media and scientific literature that the prevalence of childhood obesity is rapidly increasing. However, high quality evidence has emerged from several countries suggesting that the rise in the prevalence has slowed appreciably, or even plateaued. This review brings together such data from nine countries (Australia, China, England, France, Netherlands, New Zealand, Sweden, Switzerland and USA), with data from 467,294 children aged 2-19 years. The mean unweighted rate of change in prevalence of overweight and obesity was +0.00 (0.49)% per year across all age ×sex groups and all countries between 1995 and 2008. For overweight alone, the figure was +0.01 (0.56)%, and for obesity alone -0.01 (0.24)%. Rates of change differed by sex, age, socioeconomic status and ethnicity. While the prevalence of overweight and obesity appears to be stabilizing at different levels in different countries, it remains high, and a significant public health issue. Possible reasons for the apparent flattening are hypothesised.

Trends in the prevalence of childhood overweight and obesity in Australia between 1985 and 2008

Background:Popular media, health experts and researchers talk about a paediatric ‘obesity epidemic’ with exponentially increasing rates of obesity and overweight. However, some recent reports suggest that prevalence may have plateaued. This study examined trends in the prevalence of Australian childhood overweight and obesity since 1985. Specifically, it aimed to determine whether there have been (a) overall increases in average body mass index (BMI), (b) differential patterns of change within age groups and (c) increases in BMI within each weight-status category.Method:Forty-one Australian studies of childhood weight status conducted between 1985 and 2008 were reviewed. The studies included data on 264 905 Australians aged 2–18 years, with raw data being available on 70 758 children (27%). Children were classified as overweight or obese based on BMI using the criteria of Cole et al. (BMJ, 2000). The prevalence estimates were adjusted for age and sex, and plotted against measurement year using Lowess plots and two-linear-segment models. Where raw data were available, BMI z-scores (UK 1990 standard) were plotted against measurement year for all children and children in various age groups. Lowess plots and two-linear-segment models were used to assess secular trends in BMI z-scores pre- and post-1996 within age, gender and weight-status categories.Results:There has been a plateau, or only slight increase, in the percentage of boys and girls classified as overweight or obese, with almost no change over the last 10 years. In boys and girls, prevalence rates have settled around 21–25% for overweight and obesity together, and 5–6% for obesity alone. Similar trends were found for BMI z-scores. These patterns were fairly consistent across the age span. Within each weight-status category, average BMI has not increased.Conclusions:Although levels of Australian paediatric overweight remain high, the prevalence of overweight and obesity seems to have flattened and has not followed the anticipated exponential trajectory.

Are health behavior change interventions that use online social networks effective? A systematic review /

Background The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change. Objective The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions. Methods Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where “population” included child or adult populations, including healthy and disease populations; “intervention” involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; “comparator” was either a control group or within subject in the case of pre-post study designs; “outcomes” included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and “study design” included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen’s d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized. Results A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from −0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity). Conclusions To date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided.

Physical and sedentary activity in adolescents with cerebral palsy

Participation in regular physical activity (PA) provides health, psychological, and physiological benefits for people with and without a physical disability. This study investigated the physical and sedentary activity patterns of adolescents with cerebral palsy (CP). A cross‐sectional, descriptive, postal survey was used, consisting of the Physical Activity Questionnaire for Adolescents (PAQ‐A), self‐reported level of gross motor function (based on the Gross Motor Function Classification System [GMFCS]), and specific questions regarding weekly sedentary activities. Following piloting to determine test‐retest reliability (intraclass correlation [ICC] for PA=0.90; total weekly sedentary time=0.84) and concurrent validity (survey PA score vs pedometry, Pearsons r=0.24; survey PA score vs accelerometry, r=‐0.21; survey weekly sedentary time vs logbook, r=0.38), the survey was mailed to all adolescents with CP in South Australia registered with Novita Childrens Services (n=219). One hundred and twelve valid surveys were returned (76 males, 36 females; age range 11‐17y, mean age 13y 11mo [SD 23mo]; GMFCS Level I, n=42; Level II, n=27; Level III, n=10; Level IV, n=17; Level V, n=15; level not reported, n=1). Results were compared with recent normative age‐ and sex‐matched data sets. Key findings were that PA level of adolescents with CP was related to level of gross motor function and inversely related to age, and that adolescents with CP were less physically active than their peers without disability. Comparisons with normative data sets suggested that adolescents with CP tend to participate in less structured and lower intensity PA compared with non‐disabled adolescents, though sedentary activity patterns (TV and computer use) of adolescents with and without CP were similar.

The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study

BackgroundTechnological advances have seen a burgeoning industry for accelerometer-based wearable activity monitors targeted at the consumer market. The purpose of this study was to determine the convergent validity of a selection of consumer-level accelerometer-based activity monitors.Methods21 healthy adults wore seven consumer-level activity monitors (Fitbit One, Fitbit Zip, Jawbone UP, Misfit Shine, Nike Fuelband, Striiv Smart Pedometer and Withings Pulse) and two research-grade accelerometers/multi-sensor devices (BodyMedia SenseWear, and ActiGraph GT3X+) for 48-hours. Participants went about their daily life in free-living conditions during data collection. The validity of the consumer-level activity monitors relative to the research devices for step count, moderate to vigorous physical activity (MVPA), sleep and total daily energy expenditure (TDEE) was quantified using Bland-Altman analysis, median absolute difference and Pearson’s correlation.ResultsAll consumer-level activity monitors correlated strongly (r > 0.8) with research-grade devices for step count and sleep time, but only moderately-to-strongly for TDEE (r = 0.74-0.81) and MVPA (r = 0.52-0.91). Median absolute differences were generally modest for sleep and steps (<10% of research device mean values for the majority of devices) moderate for TDEE (<30% of research device mean values), and large for MVPA (26-298%). Across the constructs examined, the Fitbit One, Fitbit Zip and Withings Pulse performed most strongly.ConclusionsIn free-living conditions, the consumer-level activity monitors showed strong validity for the measurement of steps and sleep duration, and moderate valid for measurement of TDEE and MVPA. Validity for each construct ranged widely between devices, with the Fitbit One, Fitbit Zip and Withings Pulse being the strongest performers.

The International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): design and methods

BackgroundThe primary aim of the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) was to determine the relationships between lifestyle behaviours and obesity in a multi-national study of children, and to investigate the influence of higher-order characteristics such as behavioural settings, and the physical, social and policy environments, on the observed relationships within and between countries.Methods/designThe targeted sample included 6000 10-year old children from 12 countries in five major geographic regions of the world (Europe, Africa, the Americas, South-East Asia, and the Western Pacific). The protocol included procedures to collect data at the individual level (lifestyle, diet and physical activity questionnaires, accelerometry), family and neighborhood level (parental questionnaires), and the school environment (school administrator questionnaire and school audit tool). A standard study protocol was developed for implementation in all regions of the world. A rigorous system of training and certification of study personnel was developed and implemented, including web-based training modules and regional in-person training meetings.DiscussionThe results of this study will provide a robust examination of the correlates of adiposity and obesity in children, focusing on both sides of the energy balance equation. The results will also provide important new information that will inform the development of lifestyle, environmental, and policy interventions to address and prevent childhood obesity that may be culturally adapted for implementation around the world. ISCOLE represents a multi-national collaboration among all world regions, and represents a global effort to increase research understanding, capacity and infrastructure in childhood obesity.

The six-minute walk test for children with cerebral palsy.

The 6-min walk test (6MWT) is increasingly being used as a measure of ‘functional ability’ in young people with cerebral palsy, despite a lack of published evidence that it is reliable for this population. This study aimed to determine the test–retest reliability of the 6MWT for ambulant 11–17-year-old adolescents with cerebral palsy. Adolescents with cerebral palsy were invited to participate in a single testing session. They performed the 6MWT twice under controlled conditions (standardized 10 m course layout, standardized instructions and encouragement), with a 30-min rest. Forty-one participants (response rate 36.6%) were recruited (26 males, 15 females; mean age 13.6±1.6 years). No significant difference was found between the 6-min walk distance in trials 1 and 2 for the whole group (448.7±96.9 m vs. 449.5±102.1 m; P=0.81) or by sex and gross motor function subsets. The test–retest intraclass correlation coefficient was 0.98. Bland–Altman analyses revealed a bias of only −0.9 m, and that in 95% of cases, the second 6-min walk distance would fall within ±43.1 m of the first 6-min walk distance. All participants successfully managed the testing procedure, appeared to understand what was expected of them, and experienced no ill effects from the 6MWT. These results indicate that, when carried out according to American Thoracic Society guidelines, the 6MWT is a reliable test for young ambulant people with cerebral palsy.

Sleep duration or bedtime? Exploring the relationship between sleep habits and weight status and activity patterns.

STUDY OBJECTIVES To assess the effects of early and late bedtimes and wake up times on use of time and weight status in Australian school-aged children. DESIGN Observational cross-sectional study involving use of time interviews and pedometers. SETTING Free-living Australian adolescents. PARTICIPANTS 2200 9- to 16-year-olds from all states of Australia INTERVENTIONS NA. MEASUREMENTS AND RESULTS Bedtimes and wake times were adjusted for age and sex and classified as early or late using median splits. Adolescents were allocated into 4 sleep-wake pattern groups: Early-bed/Early-rise; Early-bed/Late-rise; Late-bed/Early-rise; Late-bed/Late-rise. The groups were compared for use of time (screen time, physical activity, and study-related time), sociodemographic characteristics, and weight status. Adolescents in the Late-bed/Late-rise category experienced 48 min/d more screen time and 27 min less moderate-to-vigorous physical activity (MVPA) (P<0.0001) than adolescents in the Early-bed/Early-rise category, in spite of similar sleep durations. Late-bed/Late-rise adolescents had a higher BMI z-score (0.66 vs. 0.45, P=0.0015). Late-bed/Late-rise adolescents were 1.47 times more likely to be overweight or obese than Early-bed/Early-rise adolescents, 2.16 times more likely to be obese, 1.77 times more likely to have low MVPA, and 2.92 times more likely to have high screen time. Late-bed/Late-rise adolescents were more likely to come from poorer households, to live in major cities, and have fewer siblings. CONCLUSIONS Late bedtimes and late wake up times are associated with an unfavorable activity and weight status profile, independent of age, sex, household income, geographical remoteness, and sleep duration.

Sleep duration or bedtime? Exploring the association between sleep timing behaviour, diet and BMI in children and adolescents.

Objective:To determine whether sleep timing behaviour is associated with energy intake and diet quality in children and adolescents.Design:Cross-sectional analysis of nationally representative survey data.Sample:A total of 2200 participants of the 2007 Australian National Children’s Nutrition and Physical Activity Survey aged 9–16 years with 2 days of food intake data, 4 days of use of time data and complete anthropometry. Participants were grouped into one of four sleep–wake behaviour categories: early bed–early rise (EE); early bed–late rise (EL); late bed–early rise (LE) and late bed–late rise (LL). The four categories were compared for body mass index (BMI) z-score, energy intake and diet quality assessed using the Dietary Guideline Index for Children and Adolescents. Analyses were adjusted for survey design, sociodemographic characteristics, sleep duration and physical activity level (PAL).Results:In adjusted multivariate regression models with sleep timing behaviour group as the independent variable, the ‘LL’ category compared with the ‘EE’ category had a higher BMI z-score (β=0.20, 95% confidence interval (CI) 0.06 to 0.34, P=0.007), and lower diet quality (β=−4.0, 95% CI −5.7 to −2.3, P<0.001). Children and adolescents who went to bed late also had a higher intake of extra foods (that is, energy-dense, nutrient-poor foods) while those whom went to bed early consumed more fruit and vegetables. Energy intake was associated with sleep duration (β=−4.5 kJ, 95% CI −6.7 to −2.4, P<0.001), but not sleep timing behaviour.Conclusion:Late bedtimes and late wake up times are associated with poorer diet quality, independent of sleep duration, PAL and child and sociodemographic characteristics.

Reconsidering the Sedentary Behaviour Paradigm

Aims Recent literature has posed sedentary behaviour as an independent entity to physical inactivity. This study investigated whether associations between sedentary behaviour and cardio-metabolic biomarkers remain when analyses are adjusted for total physical activity. Methods Cross-sectional analyses were undertaken on 4,618 adults from the 2003/04 and 2005/06 U.S. National Health and Nutrition Examination Survey. Minutes of sedentary behaviour and moderate-to-vigorous physical activity (MVPA), and total physical activity (total daily accelerometer counts minus counts accrued during sedentary minutes) were determined from accelerometry. Associations between sedentary behaviour and cardio-metabolic biomarkers were examined using linear regression. Results Results showed that sedentary behaviour was detrimentally associated with 8/11 cardio-metabolic biomarkers when adjusted for MVPA. However, when adjusted for total physical activity, the associations effectively disappeared, except for C-reactive protein, which showed a very small, favourable association (β = −0.06) and triglycerides, which showed a very small, detrimental association (β = 0.04). Standardised betas suggested that total physical activity was consistently, favourably associated with cardio-metabolic biomarkers (9/11 biomarkers, standardized β = 0.08–0.30) while sedentary behaviour was detrimentally associated with just 1 biomarker (standardized β = 0.12). Conclusion There is virtually no association between sedentary behaviour and cardio-metabolic biomarkers once analyses are adjusted for total physical activity. This suggests that sedentary behaviour may not have health effects independent of physical activity.