Marsha Dowda

Purpose : To examine the associations of race/ethnicity with the developmental pattern for physical activity (PA) as children transition from infancy to preschool age, and to examine the influence of race/ethnicity on the associations between parent-reported contextual factors and children’s PA. Method : Participants included 125 mother/child dyads (n = 38 Black, n = 25 Latino, n = 62 White) completing assessments at 6, 12, 18, 24, 30, and 36 months of age. Child PA was measured with ActiGraph GT3X accelerometers and mothers completed a survey. Adjusted growth curve models examined the associations of race/ethnicity with the developmental patterns for PA and explored whether the association between change in the contextual variables and PA varied by race/ethnicity. Results : Overall, White ( P < .001) and Latino ( P < .05) children engaged in significantly more PA compared with Black children. Boys accumulated more PA per hour than their female counterparts ( P < .001). Race/ethnicity significantly influenced the associations between the PA patterns and television viewing/screen media use, PA equipment in the home, and mothers’ report of stressful life events ( P < .05). Conclusion : This study presents an initial attempt to examine these relationships; more longitudinal research with larger samples are needed. Such knowledge is critical to inform PA interventions to promote PA in children of diverse racial/ethnic backgrounds.

Purpose : This study examined longitudinal associations between physical activity (PA) in infants at 6 months of age and motor development status at 12 months. Methods : Path analysis was used to examine the associations between PA measured objectively at 6 months, using accelerometers worn at the waist, and two indicators of motor development status at 12 months, using the Locomotion and Stationary Control subtests of the Peabody Motor Development Scales. Social and environmental factors were also included in the path analysis to examine additional factors that influenced the longitudinal associations between PA and motor development. Results : Complete data were available for 123 participants (52% male, 34% Black, 44% White). There were significant direct paths between PA at 6 months and both Locomotion ( β = 0.30, p < .001) and Stationary Control subtests ( β = 0.20, p < .05) at 12 months. There was also a significant path between “mom plays with child” ( β = 0.24, p < .05) and the Locomotion subtest at 12 months. “Tummy time” ( β = 0.26, p < .01) and “PA resources” ( β = 0.26, <.01) were significantly related to PA at 6 months. Conclusions : Results demonstrate that more PA and greater exposure to factors that support PA are associated with more advanced motor development status during infancy.

Background: There is a pressing need to understand developmental patterns of adiposity as well as factors that influence it. Group-based trajectories, usually based on body mass index (BMI), have been used in adults and children to investigate adiposity trajectories. The objectives of this study were to identify sex-specific groups with similar longitudinal trajectories for fat mass index (FMI) and to compare sex-specific longitudinal trajectory groups on demographic and behavioral characteristics. Methods: This study employed a longitudinal design to examine patterns of age-related change in FMI-assessed adiposity in children transitioning from elementary to high school. FMI, moderate-to-vigorous physical activity (MVPA), sedentary behavior, and diet quality were measured at 5 ^th , 6 ^th ,7 ^th , 9 ^th , and 11 ^th grades when the children were 10–16 years of age. Sex-specific group-based trajectory analyses were conducted for FMI, and repeated ANOVAs were used to compare behaviors between trajectories. Results: Both boys’ ( n = 320) and girls’ ( n = 389) group-based trajectory analysis resulted in three groups, each with a low FMI and stable trajectory. In girls, two trajectories increased from 10 to 16 years of age, while in boys, one trajectory increased, and one decreased over time. In girls only, the groups differed by race and parent education. There were also group differences in MVPA for boys and in diet quality for girls. Conclusions: An accurate assessment of adiposity, FMI, was used to establish the trajectories in this study. The characteristics of the groups provide valuable information about when and for whom to target obesity prevention efforts.

Purpose: To determine 24-hour physical activity (PA) clusters in children 6–36 months of age, factors associated with the clusters, and their agreement across time. Method: A longitudinal study followed 150 infants from South Carolina up to 36 months of age. Measures included 24-hour PA and demographic data. Functional clustering was used to obtain the clusters. The association between cluster membership and infant/parent characteristics was examined by Kruskal–Wallis and chi-squared tests. Concordance was measured with the kappa coefficient and percent agreement. Results: At each follow-up, 3 clusters were optimal, identified as late activity (cluster 1), high activity (cluster 2), and medium activity (cluster 3). The defining feature of the late activity cluster was that their physical activity (PA) activity was shifted to later in the day versus children in clusters 2 and 3. At 6 months, the clusters were associated with race (Conclusion: Twenty-four-hour PA can be clustered into medium, high, and late PA. Further research is needed into the consequences of late sleeping in children at this age. Clusters are associated with household and childcare factors, and cluster membership is dynamic across time.

This study examined individual variation in change over time in sedentary behaviour and factors associated with higher or lower sedentary behaviour and change in sedentary behaviour in 110 toddlers from 18 to 36 months of age. Mother/child dyads were recruited into the study when children were 6 months of age. Mothers completed surveys, and children were measured at 6-month intervals to 36 months. Children wore accelerometers for one week at each time point, and height and weight were measured. Growth curve modelling examined relationships between demographic, early life, and environmental factors and sedentary behaviour from 18 to 36 months. Fifty-one percent of the children were boys. The trajectory of sedentary behaviour increased from 18 to 24 months then declined. Children with higher sedentary behaviour were less likely to be enrolled in daycare (p < 0.05), and they engaged in higher TV/electronic media use (p < 0.05). Children with lower sedentary behaviour were more likely to have been breastfed (p < 0.05). Children with higher locomotion scores at 6 months were less sedentary at 18 months (p < 0.05), but this difference diminished over time. Mothers should be encouraged to breastfeed, limit their child's TV/electronic media use, and provide opportunities for their young children to be physically active.

Background: Effective physical activity (PA) interventions are needed to counter the insufficient and declining levels of PA in youth. These require an updated, comprehensive planning framework that consolidates recent decades of progress in promoting PA in young children, children, and adolescents. Effective PA interventions require program planning and conceptual model development that target a coordinated and multilevel set of age-specific PA determinants. Accordingly, this paper presents a comprehensive planning framework that researchers can use to design intervention research to promote PA in youth. Methods: The first author conducted targeted searches through Google Scholar to compile PA models/frameworks/guides applicable to youth, a comprehensive set of PA determinants, and determinant-linked strategies to promote PA focusing on review articles. The information was summarized in tables, synthesized, and used to create a planning framework, all of which were reviewed by coauthors. Results: The APPLE Framework for Planning PA Opportunities for Youth (APPLE = Age, PA focus, Place and time, Leverage relevant influences and strategies, and ensure Enjoyable PA opportunities) incorporated all core elements from targeted reviews to create a comprehensive planning framework. The APPLE Planning Framework has a set of questions/prompts that guide the intervention planning process and conceptual model templates to organize planning efforts for designing intervention research. Conclusions: The APPLE Framework for Planning PA Opportunities for Youth will enable researchers to develop comprehensive conceptual models to guide the design of PA interventions for youth. Future research should refine the model and its components to enable PA intervention research in youth to move forward.

Background/Objectives Childhood obesity rates have increased in recent years. The effectiveness of future public health interventions to reduce childhood obesity will be enhanced by a better understanding of behavioral factors that influence adiposity in children as they transition from childhood to adolescence. The purpose of this study was to examine whether initial weight status modifies the longitudinal associations of physical activity, sedentary behavior, and diet quality with changes in adiposity over time. Subjects/Methods A total of 658 children (45% boys) were stratified into 3 groups based on 5th grade BMI percentiles ( < 85th, 85–95th, > 95th) and followed from 5th grade to 6th and/or 7th grade. Study variables, including fat-mass-index (FMI), moderate-to-vigorous physical activity (MVPA), diet quality, and sedentary behavior, were measured at 5th, 6th, and/or 7th grades. Separate growth curve models were conducted within each weight status group to examine the associations between MVPA, sedentary behavior, diet quality and adiposity, operationalized as FMI. All models controlled for sex, maturity offset, race, and parent education. Results Of the 658 children, 53% were classified with normal weight at baseline, 18% with overweight, and 29% with obesity. Associations between MVPA, sedentary behavior, diet quality and FMI varied within each weight status group. MVPA was negatively associated with adiposity (FMI) for all weight status groups. Diet quality and sedentary behavior were associated with adiposity only in children with obesity at baseline; neither diet quality nor sedentary behavior was associated with FMI for those with overweight. Conclusions MVPA was negatively associated with adiposity (FMI) in all weight status groups, suggesting that MVPA may protect against higher adiposity. Sedentary behavior and diet quality were associated with adiposity only in children with obesity at baseline; neither sedentary behavior nor diet quality was associated with FMI for children with overweight.

Schools are well-positioned to provide physical activity opportunities to help youth achieve the recommended 60 or more daily minutes of moderate-to-vigorous physical activity. The Children’s Physical Activity Research Group (CPARG) at the University of South Carolina has focused on understanding physical activity in school-aged youth for 30+ years. The purpose of this article was to critically review (CPARG) contributions to the field in school settings and school-age youth. We reviewed 127 published CPARG articles from six research projects conducted between 1993–2019. The review was guided by questions in five categories: measurement of physical activity and its determinants, characteristics of physical activity behavior, correlates/determinants of physical activity, physical activity interventions, and race/ethnicity and physical activity. Results were summarized by question and synthesized across categories. CPARG contributions included assessing physical activity levels, patterns, forms, and contexts; identifying and measuring physical activity correlates/determinants; and conducting school-based physical activity interventions. Identifying multiple domains of physical activity determinants enables researchers and practitioners to select/design age-appropriate, valid, and reliable instruments to assess determinants. Focusing on determinants enables them to create effective physical activity interventions, environments, programs, and policies in schools. These efforts must address race/ethnicity differences, ensuring that measurement instruments and intervention strategies are culturally appropriate.