Explore the vast range of titles available.

Background Few studies have examined the relationship between motor skill competence and device-measured physical activity in large samples and none have used non-linear modelling. This study assessed the linear and non-linear associations between motor skill competence and physical activity in children using pooled data from eight studies. Methods Cross-sectional ActiGraph accelerometer and motor skills competence data from 988 children (50.8% boys) aged 3–11 years were included. Total, object control and locomotor skill competence were assessed using the Test of Gross Motor Skill Development. Linear mixed models were fitted to examine linear associations between motor skill competence and physical activity. Then, restricted cubic splines models were used to assess potential non-linear relationships. Interactions by sex and age were assessed. Results There was evidence of positive linear associations between total skill, and object control and locomotor skills, with moderate- and vigorous-intensity physical activity; however, the associations with total skill competence and object control better fitted a non-linear model. Non-linear models indicated associations were positive but relatively weak in the low to mid ranges of TGMD/object control scores but at high ranges (~ > 70 out of 100/ and ~ 35 out of 50) the association strength increased for both moderate- and vigorous-intensity physical activity. There were sex interactions for locomotor skills only, specifically for vigorous activity with boys having a stronger positive association than girls. Conclusions There appears to be a threshold for object control skill proficiency that children need to reach to enhance their physical activity levels which provides support for a motor skill “proficiency barrier”. This provides a tangible benchmark for children to achieve in motor competence programs.

Objective: To examine the long-term effects of having one overweight or obese parent on child weight status and determine whether these effects vary according to parent sex. Design: Prospective study: Longitudinal Study of Australian Children (LSAC). Subjects: Two-parent families ( N =3285) from the LSAC were included if height and weight data were available for both parents and their child at the 2004 and 2008 time points. Measurements: Child weight status category (healthy, overweight, obese) in 2008 when the child was aged 8–9 years. Regression modelling was used to investigate how self-reported parent weight status in 2004 influenced measured child weight status 4 years later. Results: Parent body mass index (BMI) was significantly correlated with child BMI, but there was no evidence of sex-specific associations between parent and child BMI correlations. The results from the regression analysis showed that having an overweight or obese father, but a healthy weight mother, significantly increased the odds of child obesity (odds ratio: 4.18, 95% confidence interval (CI): 1.01–17.33 and odds ratio: 14.88, 95% CI: 2.61–84.77, respectively), but the reverse scenario (overweight or obese mother with a healthy weight father) was not a significant predictor of child overweight or obesity (odds ratio: 2.52, 95% CI: 0.38–16.71 and odds ratio: 2.56, 95% CI: 0.31–21.26, respectively). Conclusions: Children with overweight or obese fathers are at a higher risk of becoming obese. This suggests that interventions are urgently required to test the efficacy of treating overweight fathers as a key strategy for childhood obesity prevention and/or treatment.

BACKGROUND/OBJECTIVES: Obesity prevention during adolescence is a health priority. The ‘Physical Activity 4 Everyone’ (PA4E1) study tested a multi-component physical activity intervention in 10 secondary schools from socio-economically disadvantaged communities. This paper aimed to report the secondary outcomes of the study; to determine whether the intervention impacted on adiposity outcomes (weight, body mass index (BMI), BMI z -score), and whether any effect was moderated by sex, baseline BMI and baseline physical activity level, at 12 and 24 months. SUBJECTS/METHODS: A cluster randomised controlled trial was conducted in New South Wales, Australia. The school-based intervention included seven physical activity strategies targeting the following: curriculum (strategies to maximise physical activity in physical education, student physical activity plans, an enhanced school sport programme); school environment (physical activity during school breaks, modification of school policy); and parents and the community (parent engagement, links with community physical activity providers). Students’ weight (kg), BMI and BMI z -score, were collected at baseline (Grade 7), 12 and 24 months. Linear Mixed Models were used to assess between-group mean difference from baseline to 12 and 24 months. Exploratory sub-analyses were undertaken according to three moderators of energy balance. RESULTS: A total of 1150 students (mean age=12 years) provided outcome data at baseline, 1051 (91%) at 12 months and 985 (86%) at 24 months. At 12 months, there were group-by-time effects for weight (mean difference=–0.90 kg (95% confidence interval (CI)=–1.50, −0.30), P <0.01) and BMI (−0.28 kg m −2 (−0.50, −0.06), P =0.01) in favour of the intervention group, but not for BMI z -score (−0.05 (−0.11; 0.01), P =0.13). These findings were consistent for weight (−0.62 kg (−1.21, 0.03), P =0.01) and BMI (−0.28 kg m −2 (−0.49, −0.06), P =0.01) at 24 months, with group-by-time effects also found for BMI z -score (−0.08 (−0.14; −0.02), P =0.02) favouring the intervention group. CONCLUSION: The PA4E1 school-based intervention achieved moderate reductions in adiposity among adolescents from socio-economically disadvantaged communities. Multi-component interventions that increase adolescents’ engagement in moderate-to-vigorous physical activity (MVPA) may assist in preventing unhealthy weight gain.

Background Whole-of-school programs have demonstrated success in improving student physical activity levels, but few have progressed beyond efficacy testing to implementation at-scale. The purpose of our study was to evaluate the scale-up of the ‘Internet-based Professional Learning to help teachers promote Activity in Youth’ (iPLAY) intervention in primary schools using the RE-AIM framework. Methods We conducted a type 3 hybrid implementation-effectiveness study and collected data between April 2016 and June 2021, in New South Wales (NSW), Australia. RE-AIM was operationalised as: (i) Reach: Number and representativeness of students exposed to iPLAY; (ii) Effectiveness: Impact of iPLAY in a sub-sample of students ( n  = 5,959); (iii) Adoption: Number and representativeness of schools that received iPLAY; (iv) Implementation: Extent to which the three curricular and three non-curricular components of iPLAY were delivered as intended; (v) Maintenance: Extent to which iPLAY was sustained in schools. We conducted 43 semi-structured interviews with teachers ( n  = 14), leaders ( n  = 19), and principals ( n  = 10) from 18 schools (11 from urban and 7 from rural locations) to determine program maintenance. Results Reach: iPLAY reached ~ 31,000 students from a variety of socio-economic strata (35% of students were in the bottom quartile, almost half in the middle two quartiles, and 20% in the top quartile). Effectiveness: We observed small positive intervention effects for enjoyment of PE/sport (0.12 units, 95% CI: 0.05 to 0.20, d = 0.17), perceptions of need support from teachers (0.26 units, 95% CI: 0.16 to 0.53, d = 0.40), physical activity participation (0.28 units, 95% CI: 0.10 to 0.47, d = 0.14), and subjective well-being (0.82 units, 95% CI: 0.32 to 1.32, d = 0.12) at 24-months. Adoption: 115 schools received iPLAY. Implementation: Most schools implemented the curricular (59%) and non-curricular (55%) strategies as intended. Maintenance: Based on our qualitative data, changes in teacher practices and school culture resulting from iPLAY were sustained. Conclusions iPLAY had extensive reach and adoption in NSW primary schools. Most of the schools implemented iPLAY as intended and effectiveness data suggest the positive effects observed in our cluster RCT were sustained when the intervention was delivered at-scale. Trial registration ACTRN12621001132831.

Objective: To evaluate the feasibility and efficacy of the ‘Healthy Dads, Healthy Kids’ (HDHK) program, which was designed to help overweight fathers lose weight and be a role model of positive health behaviors for their children. Design: Randomized controlled trial. Participants: A total of 53 overweight/obese men (mean (s.d.) age=40.6 (7.1) years; body mass index (BMI)=33.2 (3.9)) and their primary school-aged children (n=71, 54% boys; mean (s.d.) age=8.2 (2.0) years) were randomly assigned (family unit) to either (i) the HDHK program (n=27 fathers, n=39 children) or (ii) a wait-list control group (n=26 fathers, n=32 children). Intervention: Fathers in the 3-month program attended eight face-to-face education sessions. Children attended three of these sessions. Outcomes: The primary outcome was fathers’ weight. Fathers and their children were assessed at baseline, and at 3- and 6-month follow-up, for weight, waist circumference, BMI, blood pressure, resting heart rate (RHR), objectively measured physical activity and self-reported dietary intake. Results: Intention-to-treat analysis revealed significant between-group differences at 6 months for weight loss (P<0.001), with HDHK fathers losing more weight (−7.6kg; 95% confidence interval (CI) −9.2, −6.0; d=0.54) than control group fathers (0.0kg; 95% CI −1.4, 1.6). Significant treatment effects (P<0.05) were also found for waist circumference (d=0.62), BMI (d=0.53), systolic blood pressure (d=0.92), RHR (d=0.66) and physical activity (d=0.91), but not for dietary intake. In children, significant treatment effects (P<0.05) were found for physical activity (d=0.74), RHR (d=0.51) and dietary intake (d=0.84). Conclusion: The HDHK program resulted in significant weight loss and improved health-related outcomes in fathers and improved eating and physical activity among children. Targeting fathers is a novel and efficacious approach to improving health behavior in their children.

The acoustic repertoires of long-finned pilot whales ( Globicephala melas ) in the Mediterranean Sea are poorly understood. This study aims to create a catalogue of calls, analyse acoustic parameters, and propose a classification tree for future research. An acoustic database was compiled using recordings from the Alboran Sea, Gulf of Lion and Ligurian Sea (Western Mediterranean Basin) between 2008 and 2022, totalling 640 calls. Using a deep neural network, the calls were clustered based on frequency contour similarities, leading to the identification of 40 distinct call types defining the local population’s vocal repertoire. These categories encompass pulsed calls with varied complexities, from simplistic to highly intricate structures comprising multiple elements and segments. This study marks the initial documentation of the vocal catalogue of long-finned pilot whales in the Mediterranean Sea. Subsequent research should delve deeper into this multifaceted communication system and explore its potential linkages with social structures.

In this paper, we consider the problem of monitoring a linear functional relationship between a response variable and one or more explanatory variables (a linear profile). The design and application of a generalized likelihood ratio (GLR) control chart are discussed. The likelihood ratio test of the GLR chart is generalized over the regression coefficients, the variance of the error term, and the possible change point. The performance of the GLR chart is compared with various existing control charts. We show that the overall performance of the GLR chart is much better than other options in detecting a wide range of shift sizes. The existing control charts designed for certain shifts that may be of particular interest have several chart parameters that need to be specified by the user, which makes the design of such control charts more difficult. The GLR chart is very simple to design, as it is invariant to the choice of design matrix and the values of in-control parameters. Therefore, there is only one design parameter (the control limit) that needs to be specified. Another advantage of the GLR chart is its built-in diagnostic aids that provide estimates of both the change point and the values of linear profile parameters.

Background/objectives: The primary aim of this secondary analysis was to compare changes in dietary intake among participants randomized to two versions of a 12-week commercial web-based weight loss program (basic or enhanced) with a waiting-list control. An additional investigation compared changes in dietary intake of successful participants (weight loss ⩾5%) with those not successful. Subjects/methods: Dietary intake was assessed at baseline and 12 weeks using a validated 120-item semiquantitative food frequency questionnaire. Adults ( n =268, 60% female participants, body mass index 32.1±3.9) classified as plausible reporters of energy intake were included in the analyses. Analysis of covariance with baseline observations carried forward for drop-outs ( n =38) was used. Results: The basic and enhanced groups significantly increased their percentage of energy contribution from fruits and reduced energy-dense, nutrient-poor foods compared with controls ( P <0.001). Successful participants ( n =49) reported superior improvements in dietary intake including greater reductions in the mean daily energy intake ( P <0.001), the percentage of energy from energy-dense, nutrient-poor foods (−12.0% E vs −4.3% E, P <0.001) and greater increases in the energy contribution from fruits ( P <0.001), vegetables ( P =0.003) and breads/cereals ( P =0.02). Conclusions: Use of a commercial web-based weight loss program facilitated some improvements in the dietary intake. The enhanced web-based tools appeared not to have generated greater improvements in reported dietary intake, compared with the basic or control groups. Those who achieved a weight loss of ⩾5% improved their dietary intake in line with the program recommendations and dietary guidelines. Further research to determine web-based components that may improve success and the reasons why programs are successful for some participants is required.

Optimal blocking is explored for experiments, such as those incorporating one or more controls, where not all treatment comparisons are of equal interest. Weighted optimality functions are employed in gaining both analytic and enumerative results; a catalogue of smaller optimal designs is provided. It is shown how design selection based on functions of variances, and on functions of efficiency factors, are both subsumed by the weighted approach.

Optimal incomplete block designs are pursued through the E criterion of minimizing maximal variance. Methodology is developed for design choice based on graphs and an extensive catalog of downloadable designs is compiled. Along with the general methodology, a near complete solution for E-optimal block designs is provided for up to 15 treatments. E optimality is revealed to be a flexible criterion that, depending on the application, can offer many choices for good designs.