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Increased Health and Wellbeing in Preschools (DAGIS) Study—Differences in Children’s Energy Balance-Related Behaviors (EBRBs) and in Long-Term Stress by Parental Educational Level

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      Abstract

      This paper describes the Increased Health and Wellbeing in Preschools (DAGIS) survey process and socioeconomic status (SES) differences in children’s energy balance-related behaviors (EBRBs), meaning physical activity, sedentary and dietary behaviors, and long-term stress that serve as the basis for the intervention development. A cross-sectional survey was conducted during 2015–2016 in 66 Finnish preschools in eight municipalities involving 864 children (3–6 years old). Parents, preschool personnel, and principals assessed environmental factors at home and preschool with questionnaires. Measurement of children’s EBRBs involved three-day food records, food frequency questionnaires (FFQ), seven-day accelerometer data, and seven-day sedentary behavior diaries. Children’s long-term stress was measured by hair cortisol concentration. Parental educational level (PEL) served as an indicator of SES. Children with low PEL had more screen time, more frequent consumption of sugary beverages and lower consumption of vegetables, fruit, and berries (VFB) than those with high PEL. Children with middle PEL had a higher risk of consuming sugary everyday foods than children with high PEL. No PEL differences were found in children’s physical activity, sedentary time, or long-term stress. The DAGIS intervention, aiming to diminish SES differences in preschool children’s EBRBs, needs to have a special focus on screen time and consumption of sugary foods and beverages, and VFB.

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      A calibration study was conducted to determine the threshold counts for two commonly used accelerometers, the ActiGraph and the Actical, to classify activities by intensity in children 5 to 8 years of age. Thirty-three children wore both accelerometers and a COSMED portable metabolic system during 15 min of rest and then performed up to nine different activities for 7 min each, on two separate days in the laboratory. Oxygen consumption was measured on a breath-by-breath basis, and accelerometer data were collected in 15-s epochs. Using receiver operating characteristic curve (ROC) analysis, cutpoints that maximised both sensitivity and specificity were determined for sedentary, moderate and vigorous activities. For both accelerometers, discrimination of sedentary behaviour was almost perfect, with the area under the ROC curve at or exceeding 0.98. For both the ActiGraph and Actical, the discrimination of moderate (0.85 and 0.86, respectively) and vigorous activity (0.83 and 0.86, respectively) was acceptable, but not as precise as for sedentary behaviour. This calibration study, using indirect calorimetry, suggests that the two accelerometers can be used to distinguish differing levels of physical activity intensity as well as inactivity among children 5 to 8 years of age.
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        Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity.

        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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          Comparison of accelerometer cut points for predicting activity intensity in youth.

          The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and V˙O2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). Across all four intensity levels, the EV (κ=0.68) and FT (κ=0.66) cut points exhibited significantly better agreement than TR (κ=0.62), MT (κ=0.54), and PU (κ=0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate- to vigorous-intensity physical activity (ROC-AUC=0.90) than TR, PU, or MT cut points (ROC-AUC=0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC=0.90). On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents.
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            Author and article information

            Affiliations
            [1 ]Folkhälsan Research Center, Topeliuksenkatu 20, 00250 Helsinki, Finland; carola.ray@ 123456folkhalsan.fi (C.R.); reetta.lehto@ 123456folkhalsan.fi (R.L.); riikka.kaukonen@ 123456folkhalsan.fi (R.K.); eva.roos@ 123456folkhalsan.fi (E.R.)
            [2 ]Faculty of Educational Sciences, University of Helsinki, P.O. Box 9, 00100 Helsinki, Finland; eira.suhonen@ 123456helsinki.fi (E.S.); nina.sajaniemi@ 123456helsinki.fi (N.S.)
            [3 ]Department of Food and Nutrition, University of Helsinki, P.O. Box 66, 00100 Helsinki, Finland; henna.vepsalainen@ 123456helsinki.fi (H.V.); liisa.korkalo@ 123456helsinki.fi (L.K.); essi.skaffari@ 123456helsinki.fi (E.S.); maijaliisa.erkkola@ 123456helsinki.fi (M.E.)
            [4 ]Department of Early Childhood Education, The Education University of Hong Kong, 10 Lo Ping Road, New Territories, Hong Kong; manislin@ 123456eduhk.hk
            [5 ]School of Food and Agriculture, Seinäjoki University of Applied Sciences, P.O. Box 412, 60320 Seinäjoki, Finland; kaija.nissinen@ 123456seamk.fi
            [6 ]Department of Social Research, Faculty of Social Sciences, University of Turku, Assistentinkatu 7, 20500 Turku, Finland; leeko@ 123456utu.fi
            Author notes
            [* ]Correspondence: elviira.lehto@ 123456helsinki.fi ; Tel.: +358-44-7881067
            Journal
            Int J Environ Res Public Health
            Int J Environ Res Public Health
            ijerph
            International Journal of Environmental Research and Public Health
            MDPI
            1661-7827
            1660-4601
            21 October 2018
            October 2018
            : 15
            : 10
            30347875
            6210204
            10.3390/ijerph15102313
            ijerph-15-02313
            © 2018 by the authors.

            Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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