Russell R Pate

University of South Carolina, Columbia, SC, United States

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Publications (378)961.03 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Background The study provides evidence of the longitudinal association between screen time with hemoglobin A1c (HbA1c) and cardiovascular risk markers among youth with type 1 diabetes (T1D) and type 2 diabetes (T2D).Objective To examine the longitudinal relationship of screen time with HbA1c and serum lipids among youth with diabetes.SubjectsYouth with T1D and T2D.Methods We followed up 1049 youth (≥10 yr old) with recently diagnosed T1D and T2D participating in the SEARCH for Diabetes in Youth Study.ResultsIncreased television watching on weekdays and during the week over time was associated with larger increases in HbA1c among youth with T1D and T2D (p-value <0.05). Among youth with T1D, significant longitudinal associations were observed between television watching and TG (p-value <0.05) (week days and whole week), and low-density lipoprotein cholesterol (LDL-c, p-value <0.05) (whole week). For example, for youth who watched 1 h of television per weekday at the outset and 3 h per weekday 5 yr later, the longitudinal model predicted greater absolute increases in HbA1c (2.19% for T1D and 2.16% for T2D); whereas for youth who watched television 3 h per weekday at the outset and 1 h per weekday 5 yr later, the model predicted lesser absolute increases in HbA1c (2.08% for T1D and 1.06% for T2D).Conclusions Youth with T2D who increased their television watching over time vs. those who decreased it had larger increases in HbA1c over 5 yr. Youth with T1D who increased their television watching over time had increases in LDL-c, TG, and to a lesser extent HbA1c.
    Pediatric Diabetes 07/2014; · 2.08 Impact Factor
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    ABSTRACT: Abstract Obesity is a topic on which many views are strongly held in the absence of scientific evidence to support those views, and some views are strongly held despite evidence to contradict those views. We refer to the former as "presumptions" and the latter as "myths". Here we present nine myths and ten presumptions surrounding the effects of rapid weight loss; setting realistic goals in weight loss therapy; stage of change or readiness to lose weight; physical education classes; breast-feeding; daily self-weighing; genetic contribution to obesity; the "Freshman 15"; food deserts; regularly eating (versus skipping) breakfast; eating close to bedtime; eating more fruits and vegetables; weight cycling (i.e. yo-yo dieting); snacking; built environment; reducing screen time in childhood obesity; portion size; participation in family mealtime; and drinking water as a means of weight-loss. For each of these, we describe the belief and present evidence that the belief is widely held or stated, reasons to support the conjecture that the belief might be true, evidence to directly support or refute the belief, and findings from randomized controlled trials, if available. We conclude with a discussion of the implications of these determinations, conjecture on why so many myths and presumptions exist, and suggestions for limiting the spread of these and other unsubstantiated beliefs about obesity domain.
    Critical reviews in food science and nutrition. 06/2014;
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    ABSTRACT: To determine the subjective responses of teachers and students to classroom exercise breaks, and how responses varied by duration.
    American journal of health behavior 06/2014; 38(5):681-689. · 1.31 Impact Factor
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    ABSTRACT: Practitioners and researchers are interested in assessing children's dietary intake and physical activity together to maximize resources and minimize subject burden. Our aim was to investigate differences in dietary and/or physical activity recall accuracy by content (diet only; physical activity only; diet and physical activity), retention interval (same-day recalls in the afternoon; previous-day recalls in the morning), and grade (third; fifth). Children (n=144; 66% African American, 13% white, 12% Hispanic, 9% other; 50% girls) from four schools were randomly selected for interviews about one of three contents. Each content group was equally divided by retention interval, each equally divided by grade, each equally divided by sex. Information concerning diet and physical activity at school was validated with school-provided breakfast and lunch observations, and accelerometry, respectively. Dietary accuracy measures were food-item omission and intrusion rates, and kilocalorie correspondence rate and inflation ratio. Physical activity accuracy measures were absolute and arithmetic differences for moderate to vigorous physical activity minutes. For each accuracy measure, linear models determined effects of content, retention interval, grade, and their two-way and three-way interactions; ethnicity and sex were control variables. Content was significant within four interactions: intrusion rate (content×retention-interval×grade; P=0.0004), correspondence rate (content×grade; P=0.0004), inflation ratio (content×grade; P=0.0104), and arithmetic difference (content×retention-interval×grade; P=0.0070). Retention interval was significant for correspondence rate (P=0.0004), inflation ratio (P=0.0014), and three interactions: omission rate (retention-interval×grade; P=0.0095), intrusion rate, and arithmetic difference (both already mentioned). Grade was significant for absolute difference (P=0.0233) and five interactions mentioned. Content effects depended on other factors. Grade effects were mixed. Dietary accuracy was better with same-day than previous-day retention interval. Results do not support integrating dietary intake and physical activity in children's recalls, but do support using shorter rather than longer retention intervals to yield more accurate dietary recalls. Additional validation studies need to clarify age effects and identify evidence-based practices to improve children's accuracy for recalling dietary intake and/or physical activity.
    Journal of the American Academy of Nutrition and Dietetics 04/2014; · 3.80 Impact Factor
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    ABSTRACT: Despite evidence that preschoolers spend the majority of their time in sedentary activities, few physical activity interventions have focused on preschool-age children. Health promotion interventions that can be integrated into the daily routines of a school or other setting are more likely to be implemented. The Study of Health and Activity in Preschool Environments employed a flexible approach to increasing physical activity opportunities in preschools' daily schedules through recess, indoor physical activity and physical activity integrated into academic lessons. Eight preschools were randomly assigned to receive the study's physical activity intervention. Teachers in these schools partnered with university-based interventionists across 3 years to design and implement a flexible and adaptive intervention. The intervention approach included trainings and workshops, site visits and feedback from intervention personnel, newsletters, and physical activity equipment and materials. Teachers reported a high acceptability of the intervention. The purpose of this article is to describe the evolution of a multi-component physical activity intervention in preschools, including (i) a description of the intervention components, (ii) an explanation of the intervention process and approach, and (iii) a report of teachers' perceptions of barriers to implementation.
    Health Education Research 03/2014; · 1.66 Impact Factor
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    ABSTRACT: In 2011, the U.S. Young Men's Christian Association (YMCA) adopted activity standards recommending that afterschool programs (ASPs) ensure all children engage in a minimum of 30 minutes of moderate to vigorous physical activity (MVPA) daily during the ASP. ASPs decide how to accomplish this standard, for which few effective strategies exist. To evaluate strategies designed to help ASPs meet the MVPA standard. Single group intervention with pretest and three follow-up measures repeated-cross-sectional design with a subsample cohort. Four large-scale YMCA ASPs, serving approximately 500 children each day. Community-based participatory development of strategies focused on modification of program schedules, professional development training, and weekly checklists to evaluate activity opportunities. Accelerometry-derived MVPA classified as meet or fail-to-meet the 30 minutes' MVPA/day standard collected over a minimum of 4 nonconsecutive days at baseline (fall 2011) and three follow-up assessments (spring 2012, fall 2012, spring 2013). Random intercept logistic regression models evaluated the probability of meeting the standard for boys and girls, separately (analyzed summer 2013). A total of 895 children (aged 5-12 years, 48.4% girls) representing 3654 daily measures were collected across the four assessments. The percentage of girls and boys meeting the MVPA standard at baseline was 13.3% and 28.0%, respectively. By spring 2013, this increased to 29.3% and 49.6%. These changes represented an increase in the odds of meeting the 30 minutes' MVPA/day standard by 1.5 (95% CI=1.1, 2.0) and 2.4 (95% CI=1.2, 4.8) for girls and boys, respectively. The strategies developed herein represent an effective approach to enhancing current practice within YMCA ASPs to achieve existing MVPA standards. Additional work is necessary to evaluate the scalability of the strategies in a larger sample of ASPs.
    American journal of preventive medicine 03/2014; 46(3):281-8. · 4.24 Impact Factor
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    ABSTRACT: Background: Efforts to increase population levels of physical activity are increasingly taking the form of strategic plans at national, state/regional, and local levels. The processes employed for developing such plans have not been described previously. The purpose of this article is to chronicle the processes employed in and lessons learned from developing the US National Physical Activity Plan (NPAP). Methods: The Coordinating Committee oversaw development of the NPAP. Key steps in the process included creating a private-public coalition based in the private sector, organizing the NPAP around 8 societal sectors, reviewing the evidence base for promotion of physical activity in each sector, conducting a national conference to initiate development of the NPAP's core content, ensuring broad participation in developing and refining the NPAP, and launching the NPAP through a press event that attracted national attention. Results and Conclusion: The 3-year effort to develop the NPAP was guided by a private-public collaborative partnership involving private sector organizations and government agencies. Launched in May 2010, the NPAP included more than 250 evidence-based recommendations for changes to policy and practice at the national, state, and local levels across 8 societal sectors.
    Journal of Physical Activity and Health 03/2014; 11(3):463-9. · 1.95 Impact Factor
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    ABSTRACT: The purpose of this study was to determine the minimum number of days of accelerometry required to estimate accurately MVPA and total PA in 3- to 5-year-old children. The study examined these metrics for all days, weekdays, and in-school activities. Study participants were 204 children attending 22 preschools who wore accelerometers for at least 6 hr per day for up to 12 days during most waking hours. The primary analysis considered the intraclass correlation coefficient (ICC) for each metric to estimate the number of days required to attain a specified reliability. The ICC estimates are 0.81 for MVPA-all days, 0.78 for total PA-all days, 0.83 for MVPA weekdays, 0.80 for total PA-weekdays, 0.81 for in-school MVPA, and 0.84 for in-school total PA. We recommend a full seven days of measurement whenever possible, but researchers can achieve acceptable reliability with fewer days, as indicated by the Spearman-Brown prophecy: 3-4 days for any weekday measure and 5-6 days for the all-days measures.
    Pediatric exercise science 02/2014; 26(1):103-9. · 1.57 Impact Factor
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    ABSTRACT: Background Practitioners and researchers are interested in assessing children's dietary intake and physical activity together to maximize resources and minimize subject burden. Objective Our aim was to investigate differences in dietary and/or physical activity recall accuracy by content (diet only; physical activity only; diet and physical activity), retention interval (same-day recalls in the afternoon; previous-day recalls in the morning), and grade (third; fifth). Design Children (n=144; 66% African American, 13% white, 12% Hispanic, 9% other; 50% girls) from four schools were randomly selected for interviews about one of three contents. Each content group was equally divided by retention interval, each equally divided by grade, each equally divided by sex. Information concerning diet and physical activity at school was validated with school-provided breakfast and lunch observations, and accelerometry, respectively. Dietary accuracy measures were food-item omission and intrusion rates, and kilocalorie correspondence rate and inflation ratio. Physical activity accuracy measures were absolute and arithmetic differences for moderate to vigorous physical activity minutes. Statistical analyses performed For each accuracy measure, linear models determined effects of content, retention interval, grade, and their two-way and three-way interactions; ethnicity and sex were control variables. Results Content was significant within four interactions: intrusion rate (content×retention-interval×grade; P=0.0004), correspondence rate (content×grade; P=0.0004), inflation ratio (content×grade; P=0.0104), and arithmetic difference (content×retention-interval×grade; P=0.0070). Retention interval was significant for correspondence rate (P=0.0004), inflation ratio (P=0.0014), and three interactions: omission rate (retention-interval×grade; P=0.0095), intrusion rate, and arithmetic difference (both already mentioned). Grade was significant for absolute difference (P=0.0233) and five interactions mentioned. Content effects depended on other factors. Grade effects were mixed. Dietary accuracy was better with same-day than previous-day retention interval. Conclusions Results do not support integrating dietary intake and physical activity in children's recalls, but do support using shorter rather than longer retention intervals to yield more accurate dietary recalls. Additional validation studies need to clarify age effects and identify evidence-based practices to improve children's accuracy for recalling dietary intake and/or physical activity.
    Journal of the American Academy of Nutrition and Dietetics 01/2014; · 3.80 Impact Factor
  • Erin Kaye Howie, Michael W. Beets, Russell R. Pate
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    ABSTRACT: This study was the first to directly compare the acute effects of 5, 10, and 20 minutes of classroom exercise breaks on on-task behavior. Methods In this within-subject experiment, 96 4th and 5th grade students, in 5 classroom groups, participated in each of four conditions: 10 minutes of sedentary classroom activity and 5, 10, 20 minutes of classroom exercise breaks led by research staff. On-task behavior was directly and systematically observed from videotapes before and after each condition. The post-test time-on-task scores were compared using a repeated measures mixed ANCOVA, adjusted for age, classroom, and the time-varying pre-test time-on-task. Results Time-on-task was significantly higher in students after 10 minutes of classroom exercise breaks compared to a sedentary attention control (87.6% vs 77.1%, d=0.45, p=.004). Conclusions Ten minutes of classroom exercise breaks improved on-task behavior in children.
    Mental Health and Physical Activity 01/2014;
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    ABSTRACT: The purpose of this article was to highlight important research needs related to physical activity in 3- to 5-year-old children. We identified research needs in 3 major categories: health effects, patterns of physical activity, and interventions and policies. The top research needs include identifying the health effects of physical activity, the effects of physical activity on the development of healthy weight, the effects of physical activity on learning and behavior, and the health implications of sedentary behavior. Research questions concerning patterns of physical activity include determining the prevalence of 3- to 5-year-olds meeting the current physical activity guidelines; the social and environmental factors that influence physical activity in home, preschool, and community settings; and how physical activity tracks into later childhood, adolescence, and adulthood. Research questions about interventions and policies include identifying the most effective strategies to promote physical activity in home, child care, and community settings and to reach diverse populations of young children, identifying effective intervention implementation and dissemination strategies, and determining the effectiveness of national, state, local, and institutional policies for increasing physical activity. In conclusion, research is needed to establish a full understanding of the health implications of physical activity in 3- to 5-year-old children, to better understand the nature of physical activity behavior in this group, and to learn how to promote physical activity in young children.
    Research quarterly for exercise and sport 12/2013; 84(4):448-55. · 1.11 Impact Factor
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    ABSTRACT: The purpose of this study was to evaluate the validity and inter-rater reliability of the Observation System for Recording Activity in Children: Youth Sports (OSRAC:YS). Children (N=29) participating in a parks and recreation soccer program were observed during regularly scheduled practices. Physical activity (PA) intensity and contextual factors were recorded by momentary time-sampling procedures (10-sec observe, 20-sec record). Two observers simultaneously observed and recorded children's PA intensity, practice context, social context, coach behavior, and coach proximity. Inter-rater reliability was based on agreement (Kappa) between the observer's coding for each category, and the Intraclass Correlation Coefficient (ICC) for percent of time spent in MVPA. Validity was assessed by calculating the correlation between OSRAC:YS estimated and objectively measured MVPA. Kappa statistics for each category demonstrated substantial to almost perfect inter-observer agreement (Κappa = 0.67 to 0.93). The ICC for percent time in MVPA was 0.76 (95% C.I. = 0.49 - 0.90). A significant correlation (r = 0.73) was observed for MVPA recorded by observation and MVPA measured via accelerometry. The results indicate the OSRAC:YS is a reliable and valid tool for measuring children's PA and contextual factors during a youth soccer practice.
    Pediatric exercise science 11/2013; · 1.57 Impact Factor
  • Russell R Pate, Gregory J Welk, Kerry L McIver
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    ABSTRACT: No abstract available for this article.
    Pediatric exercise science 11/2013; 25(4):515-523. · 1.57 Impact Factor
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    ABSTRACT: Abstract Background: An understanding of the context surrounding screen- and non-screen-based sedentary behavior would facilitate efforts to reduce children's overall sedentary behavior. This study examined the prevalence of specific types of sedentary behavior in children, the social and physical contexts surrounding these behaviors, and differences by gender. Methods: Participants included 686 fifth graders participating in the Transitions and Activity Changes in Kids Study (TRACK). The Physical Activity Choices instrument measured child participation in seven sedentary behaviors, the social (i.e., with whom) and physical (i.e., where) contexts, and perceptions (i.e., why) of those behaviors. Analysis included mixed-model regression adjusted for race/ethnicity, BMI, and socioeconomic status. Results: Children participated in both screen- and non-screen-based sedentary behaviors at very high frequencies. The most popular activities included watching television or videos, listening to music, playing video games (boys only), and talking on the phone or texting (girls only). Children engaged in sedentary behaviors most often at home, at school, or in their neighborhood. In general, the patterns of social context for the behaviors were similar for boys and girls, with the exception of video game playing. Girls perceived listening to music and talking on the phone or texting to be more fun than boys; children did not differ in their other perceptions (i.e., how much choice or how important) of the behaviors. Conclusions: Multi-level interventions that target reducing sedentary behavior in the home, neighborhood, and school context may be most effective; however, the approach needed will likely differ by gender.
    Childhood obesity (Print). 10/2013;
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    ABSTRACT: Objective: To examine associations among age, physical activity (PA), and birth cohort on body mass index (BMI) percentiles in men. Design and Methods: Longitudinal analyses using quantile regression were conducted among men with ≥ two examinations between 1970 and 2006 from the Aerobics Center Longitudinal Study (n=17,759). Height and weight were measured; men reported their PA and were categorized as inactive, moderately or highly active at each visit. Analyses allowed for longitudinal changes in PA. Results: BMI was greater in older than younger men and in those born in 1960 than those born in 1940. Inactive men gained weight significantly more rapidly than active men. At the 10(th) percentile, increases in BMI among inactive, moderately active, and highly active men were 0.092, 0.078, and 0.069 kg/m(2) per year of age, respectively. The 10(th) percentile increased by 0.081 kg/m(2) per birth year and by 0.180 kg/m(2) at the 90(th) percentile, controlling for age. Conclusion: Although BMI increased with age, PA reduced the magnitude of the gradient among active compared to inactive men. Regular PA had an important, protective effect against weight gain. This study provides evidence of the utility of quantile regression to examine the specific causes of the obesity epidemic.
    Obesity 09/2013; · 3.92 Impact Factor
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    ABSTRACT: Ideal cardiovascular health is a new construct defined by the American Heart Association as part of its 2020 Impact Goal. The purpose of this study was to examine whether the simultaneous presence of ideal cardiovascular health behaviors and factors could reduce the odds of developing depressive symptoms. Participants from the Aerobics Center Longitudinal Study, who did not have any mental disorder/condition at baseline, were examined between 1987 and 1998, and they were followed up for a mean period of 6.1 years. Ideal cardiovascular health behaviors (never smoking, body mass index <25kg/m(2), physical activity at goal, and appropriate diet consistent with guideline recommendations) and factors (total cholesterol <200mg/dL, blood pressure <120/80mm Hg, and fasting blood glucose <100mg/dL) were measured at baseline. Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale in 1990, 1995, or 1999. Of the 5110 participants, 641 reported depressive symptoms. Participants meeting 3-4 or 5-7 ideal cardiovascular health components had 28% (odds ratio = 0.72; 95% confidence interval 0.59-0.87) and 36% (odds ratio = 0.64; confidence interval 0.50-0.82) decreased odds of depressive symptoms, respectively, when compared with those meeting 0-2 ideal components. Ideal behaviors were associated with lower odds of depressive symptoms in participants meeting 2 or 3-4 ideal behaviors, compared with those meeting 0-1 (odds ratio = 0.81; confidence interval 0.67-0.98 and odds ratio = 0.72; confidence interval 0.57-0.91). Ideal factors were not associated with depressive symptoms. Ideal cardiovascular health components, especially health behaviors, present an inverse relationship with depressive symptoms.
    Psychosomatics 09/2013; · 1.73 Impact Factor
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    ABSTRACT: Physical inactivity is a recognized public health concern. Inadequate proportions of children in the U.S, including those of preschool age, are meeting physical activity recommendations. In response to low numbers of preschool children attaining appropriate physical activity levels, combined with the large number of young children who attend preschool, researchers have identified the need to devise interventions to increase physical activity at preschools. However, few multi-component interventions to increase physical activity in preschool children exist. The aims of this study were to observe the effects of a multi-component intervention on physical activity, sedentary behavior, and physical activity energy expenditure in 3-5 year-old children; identify factors that associate with change in those variables; and evaluate the process of implementing the multi-component intervention. The purpose of this manuscript is to describe the study design and intervention protocol.Methods/design: The overall design of the Study of Health and Activity in Preschool Environments (SHAPES) was a two-year randomized trial (nested cohort design), with two conditions, two measurement occasions, and preschool serving as the unit of analysis. Sixteen schools (eight intervention and eight control) were enrolled. The intervention protocol was based on the social ecological model and included four main components: (a) indoor physical activity ("move inside"), (b) recess ("move outside"), (c) daily lessons ("move to learn"), and (d) social environment. Components were implemented using teacher and administrator trainings and workshops, site support visits, newsletters, and self-monitoring methods. Outcomes included accelerometer assessment of physical activity, sedentary behavior, and physical activity energy expenditure; weight status; and demographic factors; family/home social and physical environment; and parental characteristics. An extensive process evaluation battery was also used to monitor dose delivered by interventionists, completeness of intervention component delivery by teachers, and fidelity of teachers' implementation. The study will address important gaps relative to increasing physical activity in preschool children. Few studies to date have incorporated a multi-component approach, rigorous measurement protocol, and thorough evaluation of intervention implementation.Trial registration: NCT01885325.
    BMC Public Health 08/2013; 13(1):728. · 2.08 Impact Factor
  • New England Journal of Medicine 06/2013; 368(23):2236-7. · 51.66 Impact Factor
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    ABSTRACT: Little is known about how screen-based sedentary behavior at home and in preschool influences children's health and activity patterns. The current study examined the individual and cumulative influence of TV viewing at home and in preschool on children's physical activity (PA) and weight status. Children (n = 339) attending 16 preschools in South Carolina were grouped into high and low TV groups based on parent report of children's TV viewing at home and director report of TV use/rules in preschool. T-tests and mixed model ANOVAs examined differences in weight status and PA (min/hr) by high and low TV groups. Results revealed that children who were classified as High TV both at home and in preschool had significantly lower levels of moderate-to-vigorous PA compared with their Low TV counterparts (8.3 (0.3) min/hr vs. 7.6 (0.2) min/hr, p < .05). However, there were no significant differences in weight status or physical activity between the high and low TV groups at home or in preschool when examined individually. These findings demonstrate the importance of total environmental TV exposure on preschooler's PA. Longitudinal and observational research to assess preschoolers' cumulative screen-based sedentary behavior and its relationship with PA and weight status is needed.
    Pediatric exercise science 05/2013; 25(2):262-72. · 1.57 Impact Factor
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    ABSTRACT: The purpose of this review was to examine the factors that predict the development of excessive fatness in children and adolescents. Medline, Web of Science and PubMed were searched to identify prospective cohort studies that evaluated the association between several variables (e.g. physical activity, sedentary behaviour, dietary intake and genetic, physiological, social cognitive, family and peer, school and community factors) and the development of excessive fatness in children and adolescents (5-18 years). Sixty-one studies met the eligibility criteria and were included. There is evidence to support the association between genetic factors and low physical activity with excessive fatness in children and adolescents. Current studies yielded mixed evidence for the contribution of sedentary behaviour, dietary intake, physiological biomarkers, family factors and the community physical activity environment. No conclusions could be drawn about social cognitive factors, peer factors, school nutrition and physical activity environments, and the community nutrition environment. There is a dearth of longitudinal evidence that examines specific factors contributing to the development of excessive fatness in childhood and adolescence. Given that childhood obesity is a worldwide public health concern, the field can benefit from large-scale, long-term prospective studies that use state-of-the-art measures in a diverse sample of children and adolescents.
    Obesity Reviews 04/2013; · 6.87 Impact Factor

Publication Stats

17k Citations
961.03 Total Impact Points

Institutions

  • 1981–2014
    • University of South Carolina
      • • Department of Epidemiology & Biostatistics
      • • Department of Exercise Science
      • • Center for Public Health Preparedness
      • • Department of Health Promotion, Education & Behavior
      • • College of Nursing
      Columbia, SC, United States
  • 2013
    • University of Cambridge
      Cambridge, England, United Kingdom
    • Ball State University
      Muncie, Indiana, United States
  • 2000–2013
    • University of Georgia
      • Department of Kinesiology
      Athens, GA, United States
  • 2012
    • Pennington Biomedical Research Center
      Baton Rouge, Louisiana, United States
  • 2011
    • University of Bath
      • Department for Health
      Bath, England, United Kingdom
  • 2007–2011
    • Michigan State University
      • Department of Kinesiology
      East Lansing, MI, United States
  • 2010
    • UCL Eastman Dental Institute
      Londinium, England, United Kingdom
    • Seoul Women's University
      • Department of Social Welfare
      Seoul, Seoul, South Korea
  • 2009
    • University of Maryland, College Park
      • Department of Kinesiology
      College Park, MD, United States
    • East Carolina University
      • Department of Exercise and Sport Science
      Greenville, NC, United States
  • 2008
    • Duke University Medical Center
      • Department of Community and Family Medicine
      Durham, NC, United States
    • University of Minnesota Twin Cities
      • Division of Epidemiology and Community Health
      Minneapolis, MN, United States
    • Tulane University
      New Orleans, Louisiana, United States
  • 2006–2008
    • University of North Carolina at Chapel Hill
      • Department of Nutrition
      Chapel Hill, NC, United States
  • 2004–2006
    • University of Illinois, Urbana-Champaign
      Urbana, Illinois, United States
    • Johns Hopkins Bloomberg School of Public Health
      Baltimore, Maryland, United States
  • 2005
    • Stanford University
      • Stanford Prevention Research Center
      Stanford, CA, United States
    • Lawrence Berkeley National Laboratory
      • Life Sciences Division
      Berkeley, CA, United States
  • 2001–2005
    • Kansas State University
      Kansas, United States
  • 2001–2003
    • University of Queensland 
      • School of Human Movement Studies
      Brisbane, Queensland, Australia
  • 1996
    • University of Alabama at Birmingham
      • Department of Human Studies
      Birmingham, AL, United States
  • 1994
    • Northern Illinois University
      DeKalb, Illinois, United States
  • 1991
    • Centers for Disease Control and Prevention
      • National Center for Chronic Disease Prevention and Health Promotion
      Atlanta, Michigan, United States
  • 1987
    • University of Wisconsin–Madison
      Madison, Wisconsin, United States
    • Georgia Institute of Technology
      Atlanta, Georgia, United States