Purpose:   Accurate, culturally and linguistically appropriate measures are important for research and addressing health disparities. In 2013, the Institute of Medicine concluded only 1 in 5 measures were specifically developed or adapted for children and their families at high risk for obesity. Literature suggests three ways to use measures in high-risk populations: apply or adapt an existing instrument or develop a new instrument. Little guidance exists on when each approach is best. To assist researchers and practitioners in accurately measuring high-risk populations, this abstract describes a new resource the National Collaborative on Childhood Obesity Research (NCCOR) created to address this gap.

Methods: NCCOR screened references in NCCOR's Measures Registry, a searchable database of 1,400 individual and environmental dietary and physical activity measures relevant to childhood obesity research, from January 2013 to September 2017 ( n=351) and abstracted information of 38 individual and environmental measures developed for, adapted for, or applied to high-risk populations or settings. Abstraction included, measure type, study population, adaptation and validation methods, and psychometric properties. Next, NCCOR compiled methods and considerations for adapting and validating measures among high-risk populations from systematic reviews. Finally, NCCOR hosted a workshop on the topic in 2019 to develop guidance and recommendations.

Results/Findings: As a result, NCCOR developed a decision tree to walk users through a series of questions regarding whether to develop, adapt, or apply an instrument for obesity measures in high-risk populations. Examples of topics covered include how to involve community stakeholders, determine whether populations are meaningfully different, and determine whether modifications to instruments require revalidation. The decision tree also provides 5 real-world case scenarios that describe the rationale for choosing a measurement approach.

Conclusions: This project fills a research gap that will help researchers and practitioners determine which measures to apply, adapt, or develop when assessing children and families at high risk for obesity. This resource will help to promote rigorous strategies for measuring high-risk populations which will allow for more standardization across the field. We hope this freely available resource encourages the development of sound measures to use in high-risk populations and increase adoption of these strategies. 

Purpose: Tummy time is an important form of physical activity for infants, and along with the inclusion of this behaviour in recent guidelines, research on tummy time is growing. Most epidemiological studies have assessed tummy time using subjective measures, though none of these measures have been tested for validity. As such, this study examined the concurrent validity of a tummy time questionnaire and time-use diary against a validated accelerometer measure. 

Methods: Participants were 29 parents and their 6-month-old infants from the Early Movers project in Edmonton, Canada. Tummy time was concurrently measured using a parental questionnaire, a 3 day/night time-use diary, and a previously validated GENEActiv accelerometer. In participants with complete data on all measures (n=26), relative concurrent validity was examined using Spearman’s rank correlations. Absolute concurrent validity was examined using Wilcoxon signed-rank tests and Bland-Altman plots.

Results: Median tummy times assessed by the questionnaire, time-use diary, and accelerometer were 96min/d, 56min/d, and 54min/d, respectively. Both the questionnaire (r_s=0.60,p=0.001) and time-use diary (r_s=0.80,p<0.001) measures of tummy time were significantly correlated with the accelerometer measure. Compared to the accelerometer measure, the questionnaire measure had a significantly higher mean rank of tummy time (p=0.001), however, no significant differences were observed for the time-use diary measure (p=0.829). Bland-Altman plots showed a significant mean difference in tummy time for the questionnaire measure (vs. accelerometer measure:42min/d; 95% limits of agreement:-73,157min/d) but not for the time-use diary measure (vs. accelerometer measure:2 min/d; 95% limits of agreement:-47,51min/d). In both plots, low variance of individual-level differences was observed below 30min/d and higher variance was observed above 30min/d.

Conclusion: Large effect sizes (r>0.50) were observed for relative concurrent validity of the tummy time questionnaire and time-use diary compared to the accelerometer measure. Therefore, these subjective measures appear most appropriate for infant studies examining associations with tummy time and/or comparing tummy time between samples. For absolute concurrent validity, the questionnaire tended to overestimate tummy time compared to the accelerometer. However, the time-use diary may provide a relatively precise estimate of tummy time in prevalence studies among infants.

Purpose: Childcare centers are important for children’s behaviors. This study aimed to examine the cross-sectional associations between structure and processes quality of the childcare environment and physical activity and sedentary time in children.

Methods: Participants were 124 toddlers and 118 preschoolers from 19 centers in Alberta and Ontario, Canada in the supporting Healthy physical AcTive Childcare setting (HATCH) study. In-care physical activity and sedentary time were assessed using Actigraph accelerometers. Childcare environments, including structure (e.g., resources) and process (e.g., activities) quality, were measured using three instruments: (i) Environment and Policy Assessment and Observation and (ii) the Children’s Physical Environments Rating Scale, and (iii) Movement Environment Rating Scale. Mixed models were performed to examine the associations between environmental characteristics and children’s sedentary time, light physical activity and moderate-to-vigorous physical activity (MVPA).

Results: For toddlers, a few structure quality characteristics related to childcare policy (i.e., “screen time policy”, “outdoor play and learning policy”) and indoor environment (i.e., “modified open-plan space”) were associated with higher physical activity and lower sedentary time. For preschoolers, the overall structure quality (B=0.04; 95%CI:0.003,0.08) and process quality (B=0.08; 95%CI:0.02,0.15) of the childcare environment were associated with log MVPA. In particular, structure quality characteristics of the outdoor environment (i.e., “outdoor play time”, “outdoor play and learning education and professional development”, “play yard providing functional needs”, “play yards providing developmental needs”) and physical activity time were generally shown to be associated with higher physical activity and lower sedentary time. Similar associations were also observed for process quality characteristics: “curriculum, environment, and resources for physical development” and “pedagogy for physical development”.

Discussion and Conclusion: Enhancing structure quality related to childcare policy and the indoor environment seems promising in promoting physical activity and less sedentary time in childcare for toddlers. For preschoolers, overall structure quality of the environment, in particular the outdoor environment, and overall process quality of the environment, in particular curriculum and pedagogy, appear important for physical activity and sedentary time. Given the different pattern of associations observed between toddlers and preschoolers, stratified analysis is recommended for future research in this area.

Purpose: Despite effectiveness of action and coping planning in previous digital health interventions to promote PA, attrition rates in such interventions remained high. Indeed, support to make plans is often abstract, generic and the same for each individual. Nevertheless, people are different, and context varies between individuals. Tailored support at the operational level, involving suggestions of specific plans that are personalised to the individual, is needed. The aim of this study was to identify user types that relate to specific action and coping plans using clustering algorithms, in order to provide personalised suggestions in a later phase.

Methods: Data of 59 healthy adults, including 222 action plans and 204 coping plans, were used for this study and were collected as part of a digital health intervention to promote physical activity. Clusters of action plans, and clusters of combinations of action plans and barriers of coping plans were identified using hierarchical clustering. Associations with specific user information (i.e. gender, age, intention, etc) were examined using chi² –tests and analyses of variance.

Findings: Three clusters of action plans were identified, each characterized by different aspects. Cluster 1 was characterized by outdoor activities (walking, biking and running) which could be performed on every day of the week. Cluster 2 by household activities which mainly took place on Saturdays. Cluster 3 by active transport and different sport activities (swimming, fitness, etc) which mainly took place in the evening. Cluster 1 could be associated to a higher BMI, cluster 2 to women and users that didn’t perform PA regularly, and cluster 3 to younger adults. Furthermore, eight clusters of combinations of action plans and barriers of coping plans were identified (e.g. cluster 4 was characterized by outdoor activities on weekdays with bad weather as a barrier). Here, associations with user information were not straightforward.

Conclusions: Some associations of action plans with user information were found, however user types that relate to specific action plans and coping plans could not be identified. To conclude, other strategies are needed to provide personalised suggestions, notwithstanding that associations found in this study can be used as a starting point.

Purpose: Over the last two decades, metabolic health of urban Ugandans, mostly women has increasingly become suboptimal. As women are strategic for family behavioural change and as their dietary and physical activity (PA) patterns do not align with WHO recommendations, there is an urgent need for science-based interventions allowing to tackle these unhealthy dietary and PA behaviors. Objective: To develop a food literacy and PA intervention optimising metabolic health among women of reproductive age in urban Uganda.   

Methodology: Steps 1-4 of the intervention mapping protocol were used to design the intervention.

Results: Notable determinants from Step 1 are socio-cultural misconceptions around PA, fruits and vegetables, and gaps in knowledge, skills, self-efficacy and nutrition information evaluation.Due to the complexity of the determinants, we decided to go for gradual changes rather than changing the overall existing behaviours towards WHO healthy guidelines in one intervention. Hence in step 2, three behavioural intervention objectives were formulated to increase; 1) women’s ability to evaluate nutrition information, 2) fruit and vegetables consumption, and 3) engagement in moderate PA. Performance objectives and matrices of change objectives were formulated for each intervention objective. In step 3; motivational interviewing, information, skills training, goal setting, role modelling, feedback and social support through exchanging ideas were selected and translated into practical strategies. In step 4, an intervention consisting of five interactive group sessions was developed. Sessions are: i) benefits of PA and healthy diet, healthy recommendations, and personal health risk assessment; ii) planning and setting personal weekly PA, fruit and vegetable goals; iii) Evaluation of nutrition information and vegetable preparation techniques; iv) review and adaptation of goals; v) review and adaptation of goals. A booklet of vegetable recipes and practical tips is provided. The intervention is currently being evaluated through a cluster-randomized controlled trial (https://clinicaltrials.gov/ct2/show/NCT04635332). By the time of the conference, preliminary results will be presented. 

Conclusion: The intervention is novel as personal goals are linked to personal metabolic health profile. If the intervention is effective, a well-developed intervention will become available for reference in urban Uganda.