Overweight and obesity prevalence in children based on 6- or 12- month IOTF cut-points: does interval size matter?

The International Obesity Taskforce (IOTF) recommends using age- and gender-specific body mass index (BMI) cut-points for defining the prevalence of overweight and obesity in children. These are given in both 6- and 12-month age intervals. Since the BMI-for-age curves are nonlinear, a degree of bias will be introduced when age intervals are wide. We aimed to quantify this bias in prevalence estimates in 2178 Australian children aged 4-12 years using 12- versus 6-month age intervals. Using the 12-month interval, the prevalence of overweight and obesity was underestimated by 1.4% compared to the 6-month interval estimates; however, this was age-dependent. It overestimated prevalence for 4-year olds, but underestimated it for older ages by up to 2.6%. Overweight prevalence was generally affected more than obesity prevalence. The use of different age intervals for IOTF cut-points introduces a small but systematic bias in prevalence estimates of overweight and obesity.

Small rural emergency departments are not simply cut-down large urban emergency departments

 It is important to understand how small rural emergency departments work. They are a significant fraction of a state’s medical system. Although they each see only a few thousand patients a year, as a group they are likely to treat more emergency patients than the largest city hospital. It is a myth that they only deal with minor ailments. 

Cut-points for waist circumference in Europids and South Asians

There is little strong evidence that currently recommended higher waist circumference cut-points for Europids compared with South Asians are associated with similar risk for type 2 diabetes. This study was designed to provide such evidence. Longitudinal studies over 5 years were conducted among 5,515 Europid and 2,214 ethnically South Asian participants. Age-standardized diabetes incidence at different levels of waist circumference and incidence difference relative to a reference value were calculated. The Youden Index was used to determine waist circumference cut-points. At currently recommended cut-points, estimated annual diabetes incidence for a 50-year-old Europid was <0.6% for both sexes, and for a 50-year-old South Asian, 5.8% for men and 2.1% for women. Annual diabetes incidence of 1% was observed for a 50 year old at a waist circumference 35–40 cm greater in Europid compared to South Asian men and women. Incidence difference between recommended cut-points and a reference value (80 cm in men, 70 cm in women) was 0.3 and 4.4% per year for Europid and South Asian men, and 0.2 and 0.8% per year for Europid and South Asian women, respectively. Waist circumference cut-points chosen using the Youden Index were shown to be dependent on obesity levels in the population. The much higher observed risk of diabetes in South Asians compared to Europids at the respective recommended waist circumference cut-points suggests that differences between them should be greater. Approaches that use the Youden Index to select waist circumference cut-points are inappropriate and should not be used for this purpose.

New enhancements to cut, fade, and dissolve detection processes in video segmentation

We present improved algorithms for cut, fade, and dissolve detection which are fundamental steps in digital video analysis. In particular, we propose a new adaptive threshold determination method that is shown to reduce artifacts created by noise and motion in scene cut detection. We also describe new two-step algorithms for fade and dissolve detection, and introduce a method for eliminating false positives from a list of detected candidate transitions. In our detailed study of these gradual shot transitions, our objective has been to accurately classify the type of transitions (fade-in, fade-out, and dissolve) and to precisely locate the boundary of the transitions. This distinguishes our work from other early work in scene change detection which tends to focus primarily on identifying the existence of a transition rather than its precise temporal extent. We evaluate our improved algorithms against two other commonly used shot detection techniques on a comprehensive data set, and demonstrate the improved performance due to our enhancements.

A calibration protocol for population-specific accelerometer cut-points in children

Purpose

To test a field-based protocol using intermittent activities representative of children's physical activity behaviours, to generate behaviourally valid, population-specific accelerometer cut-points for sedentary behaviour, moderate, and vigorous physical activity.
Methods

Twenty-eight children (46% boys) aged 10–11 years wore a hip-mounted uniaxial GT1M ActiGraph and engaged in 6 activities representative of children's play. A validated direct observation protocol was used as the criterion measure of physical activity. Receiver Operating Characteristics (ROC) curve analyses were conducted with four semi-structured activities to determine the accelerometer cut-points. To examine classification differences, cut-points were cross-validated with free-play and DVD viewing activities.
Results

Cut-points of ≤372, >2160 and >4806 counts•min−1 representing sedentary, moderate and vigorous intensity thresholds, respectively, provided the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of the activity). Cross-validation data demonstrated that these values yielded the best overall kappa scores (0.97; 0.71; 0.62), and a high classification agreement (98.6%; 89.0%; 87.2%), respectively. Specificity values of 96–97% showed that the developed cut-points accurately detected physical activity, and sensitivity values (89–99%) indicated that minutes of activity were seldom incorrectly classified as inactivity.
Conclusion

The development of an inexpensive and replicable field-based protocol to generate behaviourally valid and population-specific accelerometer cut-points may improve the classification of physical activity levels in children, which could enhance subsequent intervention and observational studies.

Comparing different accelerometer cut-points for sedentary time in children

Actigraph accelerometers are hypothesized to be valid measurements for assessing children's sedentary time. However, there is considerable variation in accelerometer cut-points used. Therefore, we compared the most common accelerometer sedentary cut-points of children performing sedentary behaviors. Actigraph Actitrainer uniaxial accelerometers were used to measure children's activity intensity (29 children, 5-11 years old) during different activities, namely playing computer games, nonelectronic sedentary games, watching television and playing outdoors. A structured protocol was the criterion for assessing the validity of four common cut-points (100, 300, 800, 1100 counts/minute). The median counts during all sedentary behaviors were below the lowest comparison cut-point of 100 cpm. The 75th percentile values for the sedentary behaviors were always below the cut-point of 300 cpm. Our results suggest that the cut-point of <100 cpm is the most appropriate.

Predictive validity and classification accuracy of ActiGraph energy expenditure equations and cut-points in young children

Objectives
Evaluate the predictive validity of ActiGraph energy expenditure equations and the classification accuracy of physical activity intensity cut-points in preschoolers.

Methods
Forty children aged 4–6 years (5.3±1.0 years) completed a ~150-min room calorimeter protocol involving age-appropriate sedentary, light and moderate-to vigorous-intensity physical activities. Children wore an ActiGraph GT3X on the right mid-axillary line of the hip. Energy expenditure measured by room calorimetry and physical activity intensity classified using direct observation were the criterion methods. Energy expenditure was predicted using Pate and Puyau equations. Physical activity intensity was classified using Evenson, Sirard, Van Cauwenberghe, Pate, Puyau, and Reilly, ActiGraph cut-points.

Results
The Pate equation significantly overestimated VO2 during sedentary behaviors, light physical activities and total VO2 (P<0.001). No difference was found between measured and predicted VO2 during moderate-to vigorous-intensity physical activities (P = 0.072). The Puyau equation significantly underestimated activity energy expenditure during moderate-to vigorous-intensity physical activities, light-intensity physical activities and total activity energy expenditure (P<0.0125). However, no overestimation of activity energy expenditure during sedentary behavior was found. The Evenson cut-point demonstrated significantly higher accuracy for classifying sedentary behaviors and light-intensity physical activities than others. Classification accuracy for moderate-to vigorous-intensity physical activities was significantly higher for Pate than others.

Conclusion
Available ActiGraph equations do not provide accurate estimates of energy expenditure across physical activity intensities in preschoolers. Cut-points of ≤25counts⋅15 s−1 and ≥420 counts⋅15 s−1 for classifying sedentary behaviors and moderate-to vigorous-intensity physical activities, respectively, are recommended.