Christine Delisle Nyström

Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations

BackgroundAccelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.ObjectivesThe purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.MethodsTwo independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.ResultsThe present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.ConclusionThis review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.PROSPERO registration numberCRD42016039991.

Prevalence of overweight/obesity and fitness level in preschool children from the north compared with the south of Europe: an exploration with two countries

North–south differences in the prevalence of obesity and fitness levels have been found in European adolescents, yet it is unknown if such differences already exist in very young children.

A Mobile Phone Based Method to Assess Energy and Food Intake in Young Children: A Validation Study against the Doubly Labelled Water Method and 24 h Dietary Recalls

Mobile phones are becoming important instruments for assessing diet and energy intake. We developed the Tool for Energy Balance in Children (TECH), which uses a mobile phone to assess energy and food intake in pre-school children. The aims of this study were: (a) to compare energy intake (EI) using TECH with total energy expenditure (TEE) measured via doubly labelled water (DLW); and (b) to compare intakes of fruits, vegetables, fruit juice, sweetened beverages, candy, ice cream, and bakery products using TECH with intakes acquired by 24 h dietary recalls. Participants were 39 healthy, Swedish children (5.5 ± 0.5 years) within the ongoing Mobile-based Intervention Intended to Stop Obesity in Preschoolers (MINISTOP) obesity prevention trial. Energy and food intakes were assessed during four days using TECH and 24 h telephone dietary recalls. Mean EI (TECH) was not statistically different from TEE (DLW) (5820 ± 820 kJ/24 h and 6040 ± 680kJ/24 h, respectively). No significant differences in the average food intakes using TECH and 24 h dietary recalls were found. All food intakes were correlated between TECH and the 24 h dietary recalls (ρ = 0.665–0.896, p < 0.001). In conclusion, TECH accurately estimated the average intakes of energy and selected foods and thus has the potential to be a useful tool for dietary studies in pre-school children, for example obesity prevention trials.

Mobile-based intervention intended to stop obesity in preschool-aged children: the MINISTOP randomized controlled trial

Background: Traditional obesity prevention programs are time- and cost-intensive. Mobile phone technology has been successful in changing behaviors and managing weight; however, to our knowledge, its potential in young children has yet to be examined.Objective: We assessed the effectiveness of a mobile health (mHealth) obesity prevention program on body fat, dietary habits, and physical activity in healthy Swedish children aged 4.5 y.Design: From 2014 to 2015, 315 children were randomly assigned to an intervention or control group. Parents in the intervention group received a 6-mo mHealth program. The primary outcome was fat mass index (FMI), whereas the secondary outcomes were intakes of fruits, vegetables, candy, and sweetened beverages and time spent sedentary and in moderate-to-vigorous physical activity. Composite scores for the primary and secondary outcomes were computed.Results: No statistically significant intervention effect was observed for FMI between the intervention and control group (mean ± SD: -0.23 ± 0.56 compared with -0.20 ± 0.49 kg/m2). However, the intervention group increased their mean composite score from baseline to follow-up, whereas the control group did not (+0.36 ± 1.47 compared with -0.06 ± 1.33 units; P = 0.021). This improvement was more pronounced among the children with an FMI above the median (4.11 kg/m2) (P = 0.019). The odds of increasing the composite score for the 6 dietary and physical activity behaviors were 99% higher for the intervention group than the control group (P = 0.008).Conclusions: This mHealth obesity prevention study in preschool-aged children found no difference between the intervention and control group for FMI. However, the intervention group showed a considerably higher postintervention composite score (a secondary outcome) than the control group, especially in children with a higher FMI. Further studies targeting specific obesity classes within preschool-aged children are warranted. This trial was registered at clinicaltrials.gov as NCT02021786.

Associations of Fat Mass and Fat-Free Mass with Physical Fitness in 4-Year-Old Children: Results from the MINISTOP Trial

Physical fitness is a powerful marker of health in youth. Studies in adolescents and adults suggest that higher fat mass is related to worse physical fitness. However, there is limited knowledge whether fat mass and fat-free mass are associated with physical fitness already in preschoolers. Baseline data from the MINISTOP (Mobile-based INtervention Intended to STop Obesity in Preschoolers) trial was utilized for this cross-sectional analysis. Body composition was assessed using air-displacement plethysmography. Fat mass index [fat mass (kg)/height2 (m)] and fat-free mass index [fat-free mass (kg)/height2 (m)] were used to provide height-adjusted measures of body composition. Physical fitness was measured using the PREFIT (FITness testing in PREschool children) battery, which assesses cardiorespiratory fitness, upper-body and lower-body muscular strength as well as motor fitness. In total, this study included 303 children (168 boys and 135 girls), who were on average 4.48 ± 0.15 years old. Higher fat mass index was associated with worse cardiorespiratory fitness (standardized β = −0.17, p = 0.002), lower-body muscular strength (β = −0.17, p = 0.003) and motor fitness (β = −0.21, p < 0.001) in regression analyses adjusted for age, sex and mutually adjusted for fat-mass index and fat-free mass index. Conversely, higher fat-free mass index was associated with better cardiorespiratory fitness (β = 0.18, p = 0.002), upper-body muscular strength (β = 0.39, p < 0.001), lower-body muscular strength (β = 0.22, p < 0.001) and motor fitness (β = 0.17, p = 0.004). Thus, fat mass and fat-free mass in preschoolers appear to have joint but opposite associations with physical fitness, an important marker for current and future health.

Longitudinal Physical Activity, Body Composition, and Physical Fitness in Preschoolers

Purpose This study aimed to investigate longitudinal associations of objectively measured physical activity (PA) and sedentary behavior (SB) with body composition and physical fitness at a 12-month follow-up in healthy Swedish 4-yr-old children. Methods The data from the population-based MINISTOP trial were collected between 2014 and 2016, and this study included the 138 children who were in the control group. PA and SB were assessed using the wrist-worn ActiGraph (wGT3x-BT) accelerometer during seven 24-h periods and, subsequently, defined as SB, light-intensity PA, moderate-intensity PA, vigorous-intensity PA (VPA), and moderate-to-vigorous PA (MVPA). Body composition was measured using air-displacement plethysmography and physical fitness (cardiorespiratory fitness, lower and upper muscular strength as well as motor fitness) by the PREFIT fitness battery. Linear regression and isotemporal substitution models were applied. Results Greater VPA and MVPA at the age of 4.5 yr were associated with higher fat-free mass index (FFMI) at 5.5 yr (P < 0.001 and P = 0.044, respectively). Furthermore, greater VPA and MVPA at the age of 4.5 yr were associated with higher scores for cardiorespiratory fitness, lower body muscular strength, and motor fitness at 12-month follow-up (P = 0.001 to P = 0.031). Substituting 5 min·d−1 of SB, light-intensity PA, or moderate-intensity PA for VPA at the age of 4.5 yr were associated with higher FFMI, and with greater upper and lower muscular strength at 12-month follow-up (P < 0.001 to P = 0.046). Conclusion Higher VPA and MVPA at the age of 4.5 yr were significantly associated with higher FFMI and better physical fitness at 12-month follow-up. Our results indicate that promoting high-intensity PA at young ages may have long-term beneficial effects on childhood body composition and physical fitness, in particular muscular strength.

The Tanita SC-240 to Assess Body Composition in Pre-School Children: An Evaluation against the Three Component Model

Quick, easy-to-use, and valid body composition measurement options for young children are needed. Therefore, we evaluated the ability of the bioelectrical impedance (BIA) device, Tanita SC-240, to measure fat mass (FM), fat free mass (FFM) and body fatness (BF%) in 40 healthy, Swedish 5.5 years old children against the three component model (3C model). Average BF%, FM, and FFM for BIA were: 19.4% ± 3.9%, 4.1 ± 1.9 kg, and 16.4 ± 2.4 kg and were all significantly different (p < 0.001) from corresponding values for the 3C model (25.1% ± 5.5%, 5.3 ± 2.5 kg, and 15.2 ± 2.0 kg). Bland and Altman plots had wide limits of agreement for all body composition variables. Significant correlations ranging from 0.81 to 0.96 (p < 0.001) were found for BF%, FM, and FFM between BIA and the 3C model. When dividing the children into tertiles for BF%, 60% of children were classified correctly by means of BIA. In conclusion, the Tanita SC-240 underestimated BF% in comparison to the 3C model and had wide limits of agreement. Further work is needed in order to find accurate and easy-to-use methods for assessing body composition in pre-school children.

Associations of Parental Self-Efficacy with Diet, Physical Activity, Body Composition, and Cardiorespiratory Fitness in Swedish Preschoolers: Results from the MINISTOP Trial.

Background. High parental self-efficacy (PSE) has been associated with healthy diets and higher levels of physical activity (PA) in children; however, data on PSE in relation to body weight and body composition are scarce. The objective of this study was to investigate associations of PSE with measures of diet, PA, body composition, and physical fitness in early childhood. Method. We used baseline data from the MINISTOP trial in healthy Swedish children (n = 301; 4.5 ± 0.15 years). PSE was assessed using a questionnaire, dietary data were collected using a mobile technology–assisted methodology, and PA was obtained (sedentary behavior and moderate-to-vigorous) by accelerometry. Body composition was measured using the pediatric option for BodPod and cardiorespiratory fitness by the 20 m shuttle run. Linear regression was conducted to evaluate cross-sectional associations of the outcomes in relation to total PSE and scores computed for the individual PSE factors: (1) diet, (2) limit setting of unhealthful behaviors, and (3) PA. Results. Higher scores of total PSE and the diet factor were associated with higher fruit intake (β = 0.82 g/point and 1.99 g/point; p = .014 and .009, respectively) and lower consumption of unhealthy snacks (β = −0.42 g/point and −0.89 g/point; p = .012 and .020, respectively) after adjustment for parental body mass index and education, respondent, and child’s sex and age. No associations were observed between PSE and PA, body composition, or cardiorespiratory fitness. Conclusions. Our study noted that PSE should be considered in conjunction with other strategies for a sustainable impact on childhood obesity.

Does Cardiorespiratory Fitness Attenuate the Adverse Effects of Severe/Morbid Obesity on Cardiometabolic Risk and Insulin Resistance in Children? A Pooled Analysis

OBJECTIVE To investigate 1) differences in cardiometabolic risk and HOMA of insulin resistance (HOMA-IR) across BMI categories (underweight to morbid obesity), 2) whether fit children have lower cardiometabolic risk/HOMA-IR than unfit children in each BMI category, and 3) differences in cardiometabolic risk/HOMA-IR in normal-weight unfit children and obese fit children. RESEARCH DESIGN AND METHODS A pooled study including cross-sectional data from three projects (n = 1,247 children aged 8–11 years). Cardiometabolic risk was assessed using the sum of the sex- and age-specific z scores for triglycerides, HDL cholesterol, glucose, and the average of systolic and diastolic blood pressure and HOMA-IR. RESULTS A significant linear association was observed between the risk score and BMI categories (P trend ≤0.001), with every incremental rise in BMI category being associated with a 0.5 SD higher risk score (standardized β = 0.474, P < 0.001). A trend was found showing that as BMI categories rose, cardiorespiratory fitness (CRF) attenuated the risk score, with the biggest differences observed in the most obese children (−0.8 SD); however, this attenuation was significant only in mild obesity (−0.2 SD, P = 0.048). Normal-weight unfit children had a significantly lower risk score than obese fit children (P < 0.001); however, a significant reduction in the risk score was found in obese fit compared with unfit children (−0.4 SD, P = 0.027). Similar results were obtained for HOMA-IR. CONCLUSIONS As BMI categories rose so did cardiometabolic risk and HOMA-IR, which highlights the need for obesity prevention/treatment programs in childhood. Furthermore, CRF may play an important role in lowering the risk of cardiometabolic diseases in obese children.

Validation of an Online Food Frequency Questionnaire against Doubly Labelled Water and 24 h Dietary Recalls in Pre-School Children

The development of easy-to-use and accurate methods to assess the intake of energy, foods and nutrients in pre-school children is needed. KidMeal-Q is an online food frequency questionnaire developed for the LifeGene prospective cohort study in Sweden. The aims of this study were to compare: (i) energy intake (EI) obtained using KidMeal-Q to total energy expenditure (TEE) measured via doubly labelled water and (ii) the intake of certain foods measured using KidMeal-Q to intakes acquired by means of 24 h dietary recalls in 38 children aged 5.5 years. The mean EI calculated using KidMeal-Q was statistically different (p < 0.001) from TEE (4670 ± 1430 kJ/24 h and 6070 ± 690 kJ/24 h, respectively). Significant correlations were observed for vegetables, fruit juice and candy between KidMeal-Q and 24 h dietary recalls. Only sweetened beverage consumption was significantly different in mean intake (p < 0.001), as measured by KidMeal-Q and 24 h dietary recalls. In conclusion, KidMeal-Q had a relatively short answering time and comparative validity to other food frequency questionnaires. However, its accuracy needs to be improved before it can be used in studies in pre-school children.