Body Mass Index, Physical Activity, Sedentary Behavior, Sleep, and Gross Motor Skill Proficiency in Preschool Children From a Low- to Middle-Income Urban Setting

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Abstract

Background: Limited research reports on the relationship between body mass index (BMI) and physical activity (PA), sedentary behavior (SB), sleep, and gross motor skills (GMS) in low- and middle-income countries. The aim of this study was to (1) describe BMI, PA, SB, sleep duration, and GMS proficiency in South African preschool children and (2) identify relationships between variables. Methods: BMI, including z scores for height, weight, and BMI were determined. Seven-day PA, SB, and sleep were measured using accelerometry. GMS were assessed using the Test of Gross Motor Development (second edition). Associations were explored by comparing sleep, PA, SB, and GMS between BMI tertiles using the Kruskal–Wallis test. Results: Most (86%) children (n = 78, 50% boys) had a healthy BMI (15.7 [1.3] kg/m ²). Children spent 560.5 (52.9) minutes per day in light- to vigorous-intensity PA and 90.9 (30.0) minutes per day in moderate- to vigorous-intensity PA; most (83%) met the current PA guideline. Nocturnal sleep duration was low (9.28 [0.80] h/d). Although daytime naps increased 24-hour sleep duration (10.17 [0.71] h/d), 38% were classified as short sleepers. Around half (54.9%) of participants complied with both PA and sleep guidelines. No associations between variables were found. Conclusion: Despite being lean, sufficiently active, and having adequate GMS, many children were short sleepers, highlighting a possible area for intervention.

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Max Hirshkowitz, Kaitlyn Whiton, Steven Albert … (2015)

The objective was to conduct a scientifically rigorous update to the National Sleep Foundation's sleep duration recommendations.

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T. J. Cole, T. Lobstein (2012)

The international (International Obesity Task Force; IOTF) body mass index (BMI) cut-offs are widely used to assess the prevalence of child overweight, obesity and thinness. Based on data from six countries fitted by the LMS method, they link BMI values at 18 years (16, 17, 18.5, 25 and 30 kg m(-2)) to child centiles, which are averaged across the countries. Unlike other BMI references, e.g. the World Health Organization (WHO) standard, these cut-offs cannot be expressed as centiles (e.g. 85th). To address this, we averaged the previously unpublished L, M and S curves for the six countries, and used them to derive new cut-offs defined in terms of the centiles at 18 years corresponding to each BMI value. These new cut-offs were compared with the originals, and with the WHO standard and reference, by measuring their prevalence rates based on US and Chinese data. The new cut-offs were virtually identical to the originals, giving prevalence rates differing by < 0.2% on average. The discrepancies were smaller for overweight and obesity than for thinness. The international and WHO prevalences were systematically different before/after age 5. Defining the international cut-offs in terms of the underlying LMS curves has several benefits. New cut-offs are easy to derive (e.g. BMI 35 for morbid obesity), and they can be expressed as BMI centiles (e.g. boys obesity = 98.9th centile), allowing them to be compared with other BMI references. For WHO, median BMI is relatively low in early life and high at older ages, probably due to its method of construction. © 2012 The Authors. Pediatric Obesity © 2012 International Association for the Study of Obesity.

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The purpose of this study was to develop and validate automatic scoring methods to distinguish sleep from wakefulness based on wrist activity. Forty-one subjects (18 normals and 23 with sleep or psychiatric disorders) wore a wrist actigraph during overnight polysomnography. In a randomly selected subsample of 20 subjects, candidate sleep/wake prediction algorithms were iteratively optimized against standard sleep/wake scores. The optimal algorithms obtained for various data collection epoch lengths were then prospectively tested on the remaining 21 subjects. The final algorithms correctly distinguished sleep from wakefulness approximately 88% of the time. Actigraphic sleep percentage and sleep latency estimates correlated 0.82 and 0.90, respectively, with corresponding parameters scored from the polysomnogram (p < 0.0001). Automatic scoring of wrist activity provides valuable information about sleep and wakefulness that could be useful in both clinical and research applications.