1
April Barabash
CBSE 7201T
Seminar in Applied Theory and Research I
Fall 2012
Tuesdays: 6:05- 9:35 p.m.
Room: 2104J
Instructor: Dr. Sharon A. O’Connor-Petruso
Mode: Hybrid: Classes will be online and onsite
Wiki #2
Due: 10/9/12
Submit at least “six” annotations, cited in APA: 6th ed. format (this is the beginning of
your Reference List) on Wikispaces before Class #5.
1. Tomporowski, P. Davis, C. Miller, P. Nagliericite, J. (2008). Exercise and children’s
intelligence, cognition, and academic achievement. Educational Psychology
Review. 2008 June 1. 20(2): 111–131. doi: 10.1007/s10648-007-9057-0
-MY WRITING
There were many studies peer reviewed in this article. Students were given a pre-test and a
post- test on a computer. The test was a matching test. The students got more answers
correct on the post-test AFTER they exercised in PE. In another study there was no gain in
number correct on the post-test in the area of what is called general mental functioning.
- But, the one mental function that was positively affected, after exercising, in all the
studies, was the area of the brain that does executive functioning. Children who had
exercise first, and then did a test for only executive functioning of the brain all improved
after exercise.
- Executive function is a term that psychologists and medical professionals use to describe
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the higher functions of our brain that help us control and self-manage ourselves. Here’s
one technical definition: “The administrative portion of the brain that coordinates and
regulates organization, time management and perception, deferred gratification,
prioritization, attention, impulse control and persistence at tasks.” (Edge Foundation Blog.
The Role of ADHD and Your Brain’s Executive Function)
- Although in all the tests, all aspects of executive functioning improved after exercise, the
question remains – Was executive functioning sustained hours later or was it tied
immediately to the exercise? More studies need to be done.
-This study suggests that higher levels of physical fitness in children, just as it has been
proven in adults, may be associated with improved neurocognitive processing [12], and
increased physical activity may enhance school 'on-task' behavior [13]. Increased physical
activity may therefore provide cognitive and educational benefits across childhood and
adolescence.
- The study lasted a term of PE.
-There were 2 groups. There was a lack of emphasis on aerobic activities in the control
group, which they hoped would increase the contrast between intervention and control
groups.
- Academic tests were administered 3 weeks before the study began, in the middle of the 10
weeks and at the end of the 10 weeks.
- Researchers could not count on the fact that children had an hour of activity in PE.
- There are so many problems with the study that the researchers advocate to more studies.
- I can learn two important points to teach from this article. If I can encourage students to
become self-motivated to exercise at home, (maybe even a run before doing homework
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instead of eating junk food) they will be mentally healthier. The second point is that I have
to become an advocate for more gym. We in NY need the DOE to be in compliance with
federal regulations and this is the science-backed part of our demand to help our children
stay mentally sharper.
........................................................................................
Article:
Tomporowski, P. Davis, C. Miller, P. Nagliericite, J. (2008). Exercise and children’s
intelligence, cognition, and academic achievement. Educ Psychol Rev. 2008 June
1. 20(2): 111–131. doi: 10.1007/s10648-007-9057-0
Abstract
Studies that examine the effects of exercise on children’s intelligence, cognition, or
academic achievement were reviewed and results were discussed in light of (a)
contemporary cognitive theory development directed toward exercise, (b) recent research
demonstrating the salutary effects of exercise on adults’ cognitive functioning, and (c)
studies conducted with animals that have linked physical activity to changes in
neurological development and behavior. Similar to adults, exercise facilitates children’s
executive function (i.e., processes required to select, organize, and properly initiate goaldirected actions). Exercise may prove to be a simple, yet important, method of enhancing
those aspects of children’s mental functioning central to cognitive development.
Conclusions
Evidence accrued from research conducted over the past few years suggests that gains in
children’s mental functioning due to exercise training are seen most clearly on tasks that
involve executive functions. Executive functions are involved in performing goal-directed
actions in complex stimulus environments, especially novel ones, in which elements are
constantly changing. Behaviors such as these have long been seen as important for
children’s adaptive functioning. Exercise training programs may prove to be simple, yet
important, methods of enhancing aspects of children’s mental functioning that are central
to cognitive and social development. Many questions concerning the relation between
exercise and children’s cognitive functioning remain unanswered, however. It is unknown
whether improvements in cognition caused by exercise are maintained following the
termination of physical activity or if they decline. Further, it remains to be determined, for
instance, if the benefits obtained are related to the type, duration, or intensity of exercise
training programs. Answers to these questions will be attained through systematic
research designed around contemporary exercise science and cognitive theory. At this
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time, no theory has been proposed that satisfactorily addresses the relation between
exercise and cognition. Several biological hypotheses have been presented that describe
how exercise affects brain structure and function (Colcombe et al. 2004a, b; Vaynman and
Gomez-Pinilla 2006). While intriguing, these hypotheses are limited to the study of
physiological adaptations to exercise training. The merits of attempting to relate brain
structure and function to children’s cognitive development and educational psychology
have been the focus of considerable discussion (Byrnes and Fox 1998; Mayer 1998;
O’Boyle and Gill 1998). Comprehensive theories have yet to be formulated that address
numerous contextual and psycho-social factors that may moderate or mediate the relation
between exercise and children’s cognitive function.
Research that addresses the impact of physical activity on children’s physical health,
mental function, and psychological well being is of critical importance. Authorities note that
school administrators, who are faced with the demands of preparing children for
standardized tests, have reduced children’s time spent in systematic physical activity
programs. The time spent engaged in physical activity and recess by grade-school
children in schools in the United States has declined significantly over the past decade
(Allegrante 2004). Pleas to maintain physical activity in school curricula have been made
by several researchers who provide evidence that participation in physical activity
programs does not negatively impact children’s academic performance (Sallis et al. 1999;
Shephard 1997; Sibley and Etnier 2003). The present review of research findings
suggests that systematic exercise programs may actually enhance the development of
specific types of mental processing known to be important for meeting challenges
encountered both in academics and throughout the lifespan.][‘
References
Allegrante JP. Unfit to learn. Education Week. 2004;24(14):38.
Alonso-Alonso M, Pascual-Leone A. The right brain hypothesis for obesity. Journal of the American Medical Association.
2007;297(16):1819–1822. [PubMed]
Amso D, Casey BJ. Beyond what develops when. Current Directions in Psychological Science. 2006;15(1):24–29.
Baddeley A. Working memory. New York: Oxford; 1986.
Barde YA. Trophic factors and neuronal survival. Neuron. 1989;2:1525–1534. [PubMed]
Barkley R. Linkages between attention and executive functions. In: Lyon GR, Krasnegor NA, editors. Attention, memory, and
executive function. Baltimore, MD: Brooks; 1996. pp. 307–325.
Black JE, Isaacs KR, Anderson BJ, Alcantara AA, Greenough WT. Learning causes synaptogenesis, whereas activity causes
angiogenesis in cerebellar cortex of adult rats. Proceedings of the National Academy of Science. 1990;87:5568–5572.
Black JE, Jones TA, Nelson CA, Greenough WT. Neuronal plasticity and the developing brain. In: Eth S, editor. Handbook of child
and adolescent psychiatry: Basic psychiatric science and treatment. Vol. 6. New York: Wiley; 1998. pp. 31–53.
Brisswalter JB, Collardeau M, Arcelin R. Effects of acute physical exercise on cognitive performance. Sports Medicine.
2002;32:555–566. [PubMed]
Brody N. Intelligence. 2. San Diego, CA: Academic; 1992.
Brooks GA, Fahey TD, White TP. Exercise physiology. 2. Mountain View: CA: Mayfield; 1996.
Brown BJ. The effect of an isometric strength program on the intellectual and social development of trainable retarded males.
American Corrective Therapy Journal. 1967;31:44–48. [PubMed]
Byrnes JP, Fox NA. The educational relevance of research in cognitive neuroscience. Educational Psychology Review. 1998;10:297–
342.
California Department of Education. A study of the relationship between physical fitness and academic achievement in California
using 2004 test results. Sacramento, CA: California Department of Education; 2005.
Campos ALR, Sigulem DM, Moraes DEB, Escrivaco AM, Fishberg M. Intelligent quotient of obese children and adolescents by the
Weschler scale. Revista de Saude Publica. 1996;30:85–90. [PubMed]
Casey BJ, Galvan A, Hare TA. Changes in cerebral functional organization during cognitive development. Current Opinion in
Neurobiology. 2005;15(2):239–244. [PubMed]
Casey BJ, Giedd JN, Thomas KM. Structural and functional brain development and its relation to cognitive development. Biological
Psychology. 2000;54:241–257. [PubMed]
Castelli DM, Hillman CH, Buck SM, Erwin HE. Physical fitness and academic achievement in third- and fifth-grade students. Journal
of Sport & Exercise Psychology. 2007;29(2):239–252. [PubMed]
Chodzko-Zajko WJ, Moore KA. Physical fitness and cognitive functioning in aging. Exercise and Sport Science Reviews.
1994;22:195–220.
Coe DP, Pivarnik JM, Womack CJ, Reeves MJ, Malina RM. Effect of physical education and activity levels on academic
achievement in children. Medicine and Science in Sports and Exercise. 2006;38:1515–1519. [PubMed]
Colcombe SJ, Kramer AF. Fitness effects on the cognitive function of older adults: A meta-analytic study. Psychological Science.
5
2003;14:125–130. [PubMed]
Colcombe SJ, Kramer AF, Erickson KI, Scalf P, McAuley E, Cohen NJ, et al. Cardiovascular fitness, cortical plasticity, and aging.
Proceedings of the National Academy of Science. 2004a;101(9):3316–3321.
Colcombe SJ, Kramer AF, McAuley E, Erickson KI, Scalf P. Neurocognitive ageing and cardiovascular fitness. Journal of Molecular
Neuroscience. 2004b;24:9–14. [PubMed]
Corder WO. Effects of physical education on the intellectual, physical, and social development of educable mentally retarded boys.
Exceptional Children. 1966;32:357–364. [PubMed]
Cunningham WR. Intellectual abilities and age. In: Schaie KW, Eisdorfer C, editors. Annual review of gerontology and geriatrics.
Vol. 7. New York: Springer; 1987. pp. 117–134.
Das JP, Naglieri JA, Kirby JR. Assessment of cognitive processes. Needham Heights, MA: Allyn and Bacon; 1994.
Datar A, Sturm R, Magnabosco JL. Childhood overweight and academic performance: national study of kindergartners and firstgraders. Obesity Research. 2004;12:58–68. [PubMed]
Davis CL, Tomporowski PD, Boyle CA, Waller JL, Miller PH, Naglieri JA, et al. Effects of aerobic exercise on overweight children’s
cognitive functioning: A randomized controlled trial. Research Quarterly for Exercise and Sport 2007
Davranche K, Audiffren M. Facilitating effects of exercise on information processing. Journal of Sports Sciences. 2004;22:419–428.
[PubMed]
Diamond A. Normal development of prefrontal cortex from birth to young adulthood: cognitive functions, anatomy, and
biochemistry. In: Stuss DT, Knight RT, editors. Principles of frontal lobe function. New York: Oxford University Press; 2002.
pp. 466–503.
Dishman RK, Berthound HR, Booth FW, Cotman CW, Edgerton R, Fleshner MR, et al. Neurobiology of exercise. Obesity.
2006;14(3):345–356. [PubMed]
Dustman RE, Emmerson R, Shearer D. Physical activity, age, and cognitive-neuropsychological function. Journal of Aging and
Physical Activity. 1994;2:143–181.
Dwyer T, Coonan WE, Leitch DR, Hetzel BS, Baghurst PA. An investigation of the effects of daily physical activity on the health of
primary school students in South Australia. International Journal of Epidemiology. 1983;12:308–313. [PubMed]
Dwyer T, Sallis JF, Blizzard L, Lazarus R, Dean K. Relation of academic performance to physical activity and fitness in children.
Pediatric Exercise Science. 2001;13:225–237.
Ellis NR. A behavioral research strategy in mental retardation: defense and critique. American Journal of Mental Deficiency.
1969;73:557–566. [PubMed]
Ellis HC, Hunt RR. Fundamentals of cognitive psychology. 5. Madison, WI: Brown and Benchmark; 1993.
Etnier JL, Nowell PM, Landers DM, Sibley BA. A meta-regression to examine the relationship between aerobic fitness and cognitive
performance. Brain Research Reviews. 2006;52:119–130. [PubMed]
Falkner NH, Neumark-Sztainer D, Story M, Jeffery RW, Beuhring T, Resnick MD. Social, educational, and psychological correlates
of weight status in adolescents. Obesity Research. 2001;9:32–42. [PubMed]
Folkins CH, Sime WE. Physical fitness training and mental health. American Psychologist. 1981;36:373–389. [PubMed]
Gabler-Halle D, Halle JW, Chung YB. The effects of aerobic exercise on psychological and behavioral variables of individuals with
developmental disabilities: A critical review. Research in Developmental Disabilities. 1993;14:359–386. [PubMed]
Garlick D. Understanding the nature of the general factor of intelligence: The role of individual differences in neural plasticity as an
explanatory mechanism. Psychological Review. 2002;109:116–136. [PubMed]
Giedd JN, Blumenthal J, Jeffries NO, Castellanos FX, Liu H, Zijdenbos A, et al. Brain development during childhood and
adolescence: A longitudinal MRI study. Nature Neuroscience. 1999;2(10):861–863.
Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein D, Vaituzis AC, et al. Dynamic mapping of human cortical development
during childhood through early adulthood. Proceedings of the National Academy of Science. 2004;101:8174–8179.
Greenough WT, Black JE. Induction of brain structure by experience: Substrates for cognitive development. In: Nelson CA, editor.
Developmental behavioral neuroscience. Vol. 24. Hillsdale, NJ: Erlbaum; 1992. pp. 155–200.
Hall CD, Smith AL, Keele SW. The impact of aerobic activity on cognitive function in older adults: A new synthesis based on the
concept of executive control. European Journal of Cognitive Psychology. 2001;13:279–300.
Hillman CH, Castelli D, Buck SM. Physical fitness and neurocognitive function in healthy preadolescent children. Medicine &
Science in Sports & Exercise. 2005;37:1967–1974. [PubMed]
Hillman CH, Kramer AF, Belopolsky AV, Smith DP. A cross-sectional examination of age and physical activity on performance and
event-related potentials in a task switching paradigm. International Journal of Psychophysiology. 2006;59:30–39. [PubMed]
Hinkle JS, Tuckman BW, Sampson JP. The psychology, physiology, and the creativity of middle school aerobic exercises.
Elementary School Guidance & Counseling. 1993;28(2):133–145.
Hughes C. Executive functions and development: Emerging themes. Infant and Child Development. 2002;11:201–209.
Huttenlocher PR. Synaptogenesis, synaptic elimination, and neural plasticity in human cerebral cortex. In: Nelson CA, editor. Threats
to optimal development: Integrating biological, psychological, and social risk factors. Hillsdale, NJ: Erlbaum; 1994. pp. 35–
54.
Huttenlocher PR, Dabholkar AS. Regional differences in synaptogenesis in human cerebral cortex. Journal of Comparative
Neurology. 1997;387:167–178. [PubMed]
Ismail AH. The effects of a well-organized physical education programme on intellectual performance. Research in Physical
Education. 1967;1:31–38.
Jensen AR. The g factor. Westport, CT: Praeger; 1998.
Kahneman D. Attention and effort. Englewood Cliffs, NJ: Prentice-Hall; 1973.
Kail R. Longitudinal evidence that increases in processing speed and working memory enhance children’s reasoning. Psychological
Science. 2007;18(4):312–313. [PubMed]
Keays JJ, Allison KR. The effects of regular moderate to vigorous physical activity on student outcomes. Canadian Journal of Public
Health. 1995;86:62–65.
Kirkendall DR. Effects of physical activity on intellectual development and academic performance. In: Lee M, Eckert HM, Stull GA,
editors. Effects of physical activity on children: A special tribute to Mabel Lee. Champaign, IL: Human Kinetics; 1986. pp.
49–63.
6
Kramer AF, Hahn S, Cohen NJ, Banich MT, McAuley E, Harrison CR, et al. Ageing, fitness and neurocognitive function. Nature.
1999a;400:418–419. [PubMed]
Kramer AF, Hahn S, Gopher D. Task coordination and aging: explorations of executive control processes in the task switching
paradigm. Acta Psychologica. 1999b;1010:339–378.
Kramer AF, Hahn S, McAuley E. Influence of aerobic fitness on the neurocognitive function of older adults. Journal of Aging and
Physical Activity. 2000;8:379–385.
Lareau A. Social class and the daily lives of children: A study from the United States. Childhood: A Global Journal of Child
Research. 2000;7(2):155–171.
Lezak MD, Howieson DB, Loring DW. Neuropsychological assessment. 4. New York: Oxford University Press; 2004.
Li X. A study of intelligence and personality in children with simple obesity. International Journal of Obesity Related Metabolic
Disorders. 1995;19:355–357.
Lipsey MW. Design sensitivity: statistical power for experimental research. Newbury Park, CA: Sage; 1990.
Lyon GR. The need for conceptual and theoretical clarity in the study of attention, memory, and executive function. In: Krasnegor
NA, editor. Attention, memory, and executive function. London: Brooks; 1996. pp. 3–9.
Mackintosh NJ. IQ and human intelligence. Oxford, England: Oxford University Press; 1998.
Mayer RE. Does the brain have a place in educational psychology? Educational Psychology Review. 1998;10:389–396.
McMorris T, Graydon J. The effect of incremental exercise on cognitive performance. International Journal of Sport Psychology.
2000;31:66–81.
Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. The unity and diversity of executive functions and their
contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology. 2000;41:49–100. [PubMed]
Morgan WP. Psychological benefits of physical activity. In: Nagle FJ, Montoye HJ, editors. Exercise, health, and disease. Springfield,
IL: Charles Corbin; 1981. pp. 299–314.
Morgan WP, Roberts JA, Brand FR, Feinerman AD. Psychological effects of chronic physical activity. Medicine and Science in
Sports. 1970;2:213–217. [PubMed]
Naglieri JA. Current advances and intervention for children with learning disabilities. In: Mastropoeri A, editor. Advances in learning
and behavioral disabilities: Volume 16. Identification and assessment. 2003. pp. 163–190.
Naglieri JA, Das JP. Cognitive assessment system. Itasca, IL: Riverside; 1997.
Naglieri JA, Kaufman JC. Understanding intelligence, giftedness and creativity using PASS theory. Roeper Review. 2001;23(3):151–
156.
Nelson CA. Neural plasticity and human development. Current Directions in Psychological Science. 1999;8:42–45.
Nelson CA. The neurobiological bases of early intervention. In: Shonkoff JP, Meisels SJ, editors. Handbook of early childhood
intervention. 2. Cambridge: Cambridge University Press; 2000. pp. 204–227.
O’Boyle MW, Gill HS. On the relevance of research findings in cognitive neuroscience to educational practice. Educational
Psychology Review. 1998;10:397–409.
Pate RR, Long BJ, Heath GW. Descriptive epidemiology of physical activity in adolescents. Pediatric Exercise Science. 1994;6:434–
447.
Pellis SM, Pellis VC. Rough-and-tumble play and the development of the social brain. Current directions in psychological science.
2007;16(2):95–98.
Pereira AC, Huddleston DE, Brickman AM, Sosunov AA, Hen R, McKhann GM, et al. An in vivo correlate of exercise-induced
neurogenesis in adult dentate gyrus. Proceedings of the National Academy of Science. 2007;104(13):5638–5643.
Plante TG, Rodin J. Physical fitness and enhanced psychological health. Current Psychology: Research & Reviews. 1990;9:3–24.
Sallis JF, McKenzie TL, Kolody B, Lewis M, Marshall S, Rosengard P. Effects of health-related physical education on academic
achievement: Project SPARK. Research Quarterly for Exercise and Sport. 1999;70:127–134. [PubMed]
Sanders AF. Elements of human performance. Mahwah, NJ: Lawrence Erlbaum; 1998.
Shephard RJ. Curricular physical activity and academic performance. Pediatric Exercise Science. 1997;9:113–126.
Shephard RJ, Volle M, Lavallee H, LaBarre R, Jequier JC, Rajic M. Required physical activity and academic grades: A controlled
longitudinal study. In: Valimaki I, editor. Children and sport. Berlin: Springer; 1984. pp. 58–63.
Sibley BA, Etnier JL. The relationship between physical activity and cognition in children: A meta-analysis. Pediatric Exercise
Science. 2003;15:243–256.
Sowell ER, Thompson PM, Holmes CJ, Batth R, Jernigan TI, Toga AW. Localizing age-related changes in brain structure between
childhood and adolescence using statistical parametric mapping. NeuroImage. 1999;9:587–597. [PubMed]
Sowell ER, Thompson PM, Leonard DM, Welcome SE, Kan F, Toga AW. Longitudinal mapping of cortical thickness and brain
growth in normal children. Journal of Neuroscience. 2004;24:8223–8231. [PubMed]
Spirduso WW, Clifford P. Replication of age and physical activity effects on reaction and movement time. Journal of Gerontology.
1978;33:26–30. [PubMed]
St Clair-Thompson HL, Gathercole SE. Executive functions and achievements in school: Shifting, updating, inhibition, and working
memory. Quarterly Journal of Experimental Psychology. 2006;59(4):745–759.
Stockman IJ. A theoretical framework for clinical intervention with pervasive developmental disorders. In: Stockman IJ, editor.
Movement and action in learning and development: clinical implications for pervasive developmental disorders. New York:
Elsevier; 2004. pp. 21–31.
Stones MJ, Kozma A. Age, exercise, and coding performance. Psychology and Aging. 1989;4:190–194. [PubMed]
Taras H. Physical activity and student performance at school. Journal of School Health. 2005;75:214–218. [PubMed]
Taras H, Potts-Datema W. Obesity and student performance at school. Journal of School Health. 2005;75(8):291–295. [PubMed]
Thalheimer W, Cook S. How to calculate effect sizes from published research articles: A simplified methodology. 2002. http://worklearning.com/effect_sizes.htm.
Thelen E. The central role of action in typical and atypical development: A dynamical systems perspective. In: Stockman IJ, editor.
Movement and action in learning and development: Clinical implications for pervasive developmental disorders. New York:
Elsevier; 2004.
Tomporowski PD. Cognitive and behavioral responses to acute exercise in youth: A review. Pediatric Exercise Science.
2003a;15:348–359.
7
Tomporowski PD. Effects of acute bouts of exercise on cognition. Acta Psychologica. 2003b;112:297–324. [PubMed]
Tomporowski PD. Physical activity, cognition, and aging: A review of reviews. In: Poon LW, Chodzko-Zajko WJ, Tomporowski PD,
editors. Active living, cognitive functioning, and aging. Champaign, IL: Human Kinetics; 2006. pp. 15–32.
Tomporowski PD, Ellis NR. Effects of exercise on the physical fitness, intelligence, and adaptive behavior of institutionalized
mentally retarded adults. Applied Research in Mental Retardation. 1984;5:329–337. [PubMed]
Tomporowski PD, Ellis NR. The effects of exercise training on the health, intelligence, and adaptive behavior of institutionalized
mentally retarded adults: A systematic replication. Applied Research in Mental Retardation. 1985;6:456–473.
Tomporowski PD, Ellis NR. The effects of exercise on cognitive processes: A review. Psychological Bulletin. 1986;99:338–346.
Tremblay MS, Inman JW, Willms JD. The relationship between physical activity, self-esteem, and academic achievement. Pediatric
Exercise Science. 2000;12:312–323.
Tuckman BW. The effects of exercise on children and adolescents. In: Hersen M, editor. Handbook of pediatric and adolescent
health. Boston: Allyn and Bacon; 1999. pp. 275–286.
Tuckman BW, Hinkle JS. An experimental study of the physical and psychological effects of aerobic exercise on schoolchildren.
Health Psychology. 1986;5(3):197–207. [PubMed]
Vaynman S, Gomez-Pinilla F. Revenge of the “Sit”: How lifestyle impacts neuronal and cognitive health through molecular systems
that interface energy metabolism with neuronal plasticity. Journal of Neuroscience Research. 2006;84:699–715. [PubMed]
Welk GJ, Morrow JRJ, Falls HB. Fitnessgram reference guide. Dallas, TX: The Cooper Institute; 2002.
Welsh MC, Pennington BF, Groisser DB. A normative-developmental study of executive function: A window on prefrontal function
in children. Developmental Neuropsychology. 1991;7(2):131–149.
Will B, Galani R, Kelche C, Rosenzweig MR. Recovery from brain injury in animal: Relative efficacy of environmental enrichment,
physical exercise or formal training (1990–2002) Progress in Neurobiology. 2004;72:167–182. [PubMed]
Wilmore JH, Costill DL. Physiology of sport and exercise. 3. Champaign, IL: Human Kinetics; 2004.
Wolf SA, Kronenberg G, Lehmann K, Blankenship A, Overall R, Staufenbiel M, et al. Cognitive and physical activity differently
modulate disease progression in the amyloid precursor protein (APP)-23 model of Alzheimer’s disease. Biological Psychiatry.
2006;60:1314–1323. [PubMed]
Zervas Y, Apostolos D, Klissouras V. Influence of physical exertion on mental performance with reference to training. Perceptual and
Motor Skills. 1991;73:1215–1221. [PubMed]
........................................................................................
2.Watson, K. Baranowski, T. Thompson, D. (2012). Item response modeling: an
evaluation of the children's fruit and vegetable self-efficacy questionnaire. Health
Education Research. 21(1); i47-i57.
http://www.ars.usda.gov/research/publications/publications.htm?seq_no_115=2049
45
- MY WRITING
-A test with 24-items (five-point scale) FVSEQ (Fruit, Vegetable, Self Efficacy
Questionnaire) was administered to 1578 fourth graders from 26 Houston schools.
- The researchers found little to no significant difference in the way boys and girls
8
answered the questions in the study. However, there was significant difference by ethnic
groups in 10 items or answers.
- The way that children perceived their own power (self-efficacy) (SE) [4] to make choices
in eating fruit and vegetables is the key. Any intervention lessons have to empower the
children in their own eating patterns[5, 6].
- There is concern because young children do not eat fruit/veggies (FV) in healthy
quantities. An intervention program is suggested and the kind of program suggested is to
get children to want to eat FV on their own, without nagging or punishment. (eat your
veggies or no ice cream)
- A few studies have noted gender [27] and ethnic [28] differences in the eating habits of
adults, this is the first study that has analyzed the item choice, or the response of the
children and included an analysis of their ethnic or gender identity.
- There was a control group who were given the test, without lessons and while the
experimental group was given lessons. The lessons included a psycho educational
interactive multimedia game delivered in 10 sessions over a 5-week period. Each session
lasted ∼25 min. The program used social cognitive theory to attempt to increase (i) fruit,
juice and vegetable (FJV) preferences, (ii) asking behaviors for FJV and (iii) skills in FJV
preparation. The program also attempted to associate fun with consumption of FJV. The
important word here is fun – the children were encouraged to associate fun with eating
well. This is something I intend to include in my lessons and I am glad to see a study on
fun and veggies!
- Several items exhibited differing responses across ethnic groups. White children found it
significantly easier than Black and Hispanic children to ‘ask” their parents to serve or buy
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more FV. Blacks and Hispanics found it significantly easier than Whites to eat what their
parents or the school cafeteria served them without complaint. According to the
researchers, this difference was most likely due to ethnic differences in such as family
structure or cultural differences and family dynamics. For example, Cullen et al. [28]
showed that Whites were in families with greater meal planning practices. This difference
provided additional insight into tailoring interventions for ethnic groups that incorporate
the cultural differences of family dynamics.
- More work is necessary to clarify ethnic differences.
- One issue the researchers did not investigate is economic level. A child from a middle
class family can more easily ask a parent to buy something while a poorer child learned
very early in life not to ask for things – food, toys etc. This does not have a footnote except
in real life observations.
- The questionnaire could be improved. The researcher were interested in finding students
with high efficacy and a question like - ‘I can eat a vegetable that is served for school
lunch’ might be modified for greater difficulty as ‘I can eat any vegetable that is served in
the school lunch.”- The middle answer “not sure” could indicate a child with high
motivation or willingness to eat different f/v or one less self-motivated. Better wording
might make the analysis stronger.
-I will make my own questionnaire, being considerate of parents economic ability- and try
to make eating F/V fun.
........................................................................................
Article:
10
Watson, K. Baranowski, T. Thompson, D. (2012). Item response modeling: an
evaluation of the children's fruit and vegetable self-efficacy questionnaire. Health
Education Research. 21(1); i47-i57.
http://www.ars.usda.gov/research/publications/publications.htm?seq_no_115=2049
45
Abstract
Perceived self-efficacy (SE) for eating fruit and vegetables (FV) is a key variable mediating
FV change in interventions. This study applies item response modeling (IRM) to a fruit,
juice and vegetable self-efficacy questionnaire (FVSEQ) previously validated with classical
test theory (CTT) procedures. The 24-item (five-point Likert scale) FVSEQ was
administered to 1578 fourth graders from 26 Houston schools. The IRM partial credit
model indicated the five-point response options were not fully utilized. The questionnaire
exhibited acceptable (>0.70) reliability except at the extremes of the SE scale. Differential
item functioning (DIF) analyses revealed no response bias due to gender. However, DIF
was detected by ethnic groups in 10 items. IRM of this scale expanded what was known
from CTT methods in three ways: (i) areas of the scale were identified that were not as
reliable, (ii) limitations were found in the response format and (c) areas of the SE scale
levels were not measured. The FVSEQ can be improved by including items at the extreme
levels of difficulty. DIF analyses identified areas where IRM can be useful to improve the
functioning of measures.
Discussion
The aim of this study was to evaluate the psychometric properties of the FVSEQ items and
their stability across gender and ethnic groups using IRM [29]. CTT results showed that
the FVSEQ scale had high internal consistency, the item difficulties were moderately easy
to difficult and the items were discriminating. IRM complemented the results from CTT by
showing (i) the scale yielded adequate reliability except for participants with very low or
high levels of SE, (ii) the scale did not appear to adequately assess participants with high
levels of SE and (iii) the five-point response format was not fully utilized. Additional
information provided by IRM showed no gender DIF, but several items exhibited DIF
across ethnic groups. Whites found it significantly easier than Blacks and Hispanics to
perform ‘asking’ tasks, while Blacks and Hispanics found it significantly easier than Whites
to perform intake behaviors such as eating a vegetable that is served. Examination by
experts suggested this difference was more likely due to real ethnic differences in factors
such as family structure, cultural differences in the activity or family dynamics. For
example, Cullen et al. [28] showed that Hispanics were in families with a permissive style
of parenting and Whites were in families with greater meal planning practices. This DIF
likely provided additional insight into tailoring interventions to ethnic groups to incorporate
cultural differences in family dynamics. More work is necessary to clarify ethnic
differences.
Results from IRM provided more in-depth information about the scale and identified areas
in which the FVSEQ could be improved. For example, to target participants with high
levels of SE, an item of average difficulty such as ‘I can eat a vegetable that is served for
11
school lunch’ might be modified for greater difficulty as ‘I can eat any vegetable that is
served for school lunch every day’. Newer possibilities need to be explored, e.g. ‘I can
make myself learn to like any vegetable’ or ‘I can problem solve to overcome any barrier to
eating more vegetables’. Also, the current five-point scale should be replaced with fewer
response options, or the response options should be changed so that responses will be
more uniform.
The strengths of this study include (i) ample sample size necessary to perform IRM, and
more specifically, DIF analyses and (ii) the use of an existing and previously validated
instrument to measure FVSE. The limitations of this study include the disregard of possible
clustering within schools and the determination of ethnicity via school roster instead of
self-report. Additional limitations include the use of ‘not sure’ as a neutral category, i.e.
some error in estimating the true level of SE may be associated with the assumption that
those who are ‘not sure’ reflect more positivity than ‘disagree’.
In summary, IRM provided (i) difficulty estimates that were not dependent on this sample,
(ii) the ability estimates of FV SE were not specific to the items on the instrument and (iii)
measurement error was a function of ability. The major practical value of applying IRM
was that although the test was adequately reliable, it was not measuring the full range of
the construct. The scale was not able to provide discrimination among participants with
higher levels of SE, thus indicating a need to revise the instrument. Although some items
exhibited minor DIF, this can probably be ignored. Closer examination of these items in
future studies should be performed to ensure that the items are not biased. A
questionnaire revised to assess the full range of SE difficulty estimates should correlate
better with FV intake. This work remains to be done.
References
.
1.↵ Center for Disease Control and Prevention. Guidelines for school health programs to promote lifelong healthy eating. Morb
Mortal Wkly 1996;45:1-33.
.
2. US Department of Health and Human Services, Centers for Disease Control and Prevention. Assessing Health Risk Behaviors
Among Young People: Youth Risk Behavior Surveillance System 2004. Atlanta, GA: National Center for Chronic Disease
Prevention and Health Promotion; 2004.
.
3.↵ US Department of Health and Human Services, Centers for Disease Control and Prevention. Physical Activity and Good
Nutrition: Essential Elements to Prevent Chronic Disease and Obesity 2003. National Center for Chronic Disease Prevention
and Health Promotion; 2003.
.
.
4.↵ Bandura A. Foundations for Thoughts and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice
Hall; 1986. Search Google Scholar
.
.
5.↵ Reynolds KD, Yaroch AL, Franklin FA, et al. Testing mediating variables in a school-based nutrition
intervention program. Health Psychol 2002;21:51-60. CrossRefMedlineWeb of Science
.
.
6.↵ Strecher VJ, DeVellis BM, Becker MH, et al. The role of self-efficacy in achieving health behavior change.
Health Educ Q 1986;13:73-92. MedlineWeb of Science
.
.
7.↵ Baranowski T, Davis M, Resnicow K, et al. Gimme 5 fruit, juice, and vegetables for fun and health: outcome
evaluation. Health Educ Behav 2000;27:96-111. [Erratum appears in Health Educ Behav 2000; 27: 390]. Abstract/FREE Full
Text
.
.
8.↵ Edmundson E, Parcel GS, Feldman HA, et al. The effects of the Child and Adolescent Trial for Cardiovascular
Health upon psychosocial determinants of diet and physical activity behavior. Prev Med 1996;25:442-54.
CrossRefMedlineWeb of Science
.
.
9.↵ Long JD, Stevens KR. Using technology to promote self-efficacy for healthy eating in adolescents. J Nurs
Scholarsh 2004;36:134-9. CrossRefMedlineWeb of Science
12
.
.
10.↵ Neumark-Sztainer D, Wall M, Perry C, et al. Correlates of fruit and vegetable intake among adolescents.
Findings from Project EAT. Prev Med 2003;37:198-208. CrossRefMedlineWeb of Science
.
.
11.↵ Resnicow K, Davis-Hearn M, Smith M, et al. Social-cognitive predictors of fruit and vegetable intake in
children. Health Psychol 1997;16:272-6. CrossRefMedlineWeb of Science
.
.
12.↵ Saksvig BI, Gittelsohn J, Harris SB, et al. A pilot school-based healthy eating and physical activity
intervention improves diet, food knowledge, and self-efficacy for native Canadian children. J Nutr 2005;135:2392-8.
Abstract/FREE Full Text
.
.
13.↵ Stevens J, Story M, Ring K, et al. The impact of the Pathways intervention on psychosocial variables related
to diet and physical activity in American Indian schoolchildren. Prev Med 2003;37:S70-9. CrossRefMedlineWeb of Science
.
.
14.↵ Wilson DK, Friend R, Teasley N, et al. Motivational versus social cognitive interventions for promoting fruit
and vegetable intake and physical activity in African American adolescents. Ann Behav Med 2002;24:310-9.
CrossRefMedlineWeb of Science
.
.
15.↵ Domel SB, Baranowski T, Davis HC, et al. Psychosocial predictors of fruit and vegetable consumption
among elementary school children. Health Educ Res Theory Pract 1996;11:299-308. Abstract/FREE Full Text
.
.
16.↵ Parcel GS, Simons-Morton B, O'Hara NM, et al. School promotion of healthful diet and physical activity:
impact on learning outcomes and self-reported behavior. Health Educ Q 1989;16:181-99. MedlineWeb of Science
.
.
17.↵ Granner ML, Sargent RG, Calderon KS, et al. Factors of fruit and vegetable intake by race, gender, and age
among young adolescents. J Nutr Educ Behav 2004;36:173-80. CrossRefMedlineWeb of Science
.
.
18.↵ Hagler AS, Norman GJ, Radick LR, et al. Comparability and reliability of paper- and computer-based
measures of psychosocial constructs for adolescent fruit and vegetable and dietary fat intake. J Am Diet Assoc
2005;105:1758-64. CrossRefMedlineWeb of Science
.
.
19.↵ Zabinski MF, Daly T, Norman GJ, et al. Psychosocial correlates of fruit, vegetable, and dietary fat intake
among adolescent boys and girls. J Am Diet Assoc 2006;106:814-21. CrossRefMedlineWeb of Science
.
.
20.↵ Sallis JF, Pinski RB, Grossman RM, et al. The development of self-efficacy scales for health related diet and
exercise behaviors. Health Educ Res 1988;3:283-92. Abstract/FREE Full Text
.
.
21.↵ Cusatis DC, Shannon BM. Influences on adolescent eating behavior. J Adolesc Health 1996;18:27-34.
CrossRefMedlineWeb of Science
.
.
22.↵ Monge-Rojas R, Nunez HP, Garita C, et al. Psychosocial aspects of Costa Rican adolescents' eating and
physical activity patterns. J Adolesc Health 2002;31:212-9. CrossRefMedlineWeb of Science
.
.
23.↵ Mangunkusumo RT, Duisterhout JS, de Graaff N, et al. Internet versus paper mode of health and health
behavior questionnaires in elementary schools: asthma and fruit as examples. J Sch Health 2006;76:80-6.
CrossRefMedlineWeb of Science
.
.
24.↵ Reynolds KD, Killen JD, Bryson SW, et al. Psychosocial predictors of physical activity in adolescents. Prev
Med 1990;19:541-51. CrossRefMedlineWeb of Science
.
.
25.↵ Vereecken CA, Van Damme W, Maes L. Measuring attitudes, self-efficacy, and social and environmental
influences on fruit and vegetable consumption of 11- and 12-year-old children: reliability and validity. [See comment.]. J Am
Diet Assoc 2005;105:257-61. CrossRefMedlineWeb of Science
.
.
26.↵ Crocker L, Algina J. Introduction to Classical and Modern Test Theory. New York: Holt, Rinehart, and
Winston, Inc.; 1986. Search Google Scholar
.
.
27.↵ Backman DR, Haddad EH, Lee JW, et al. Psychosocial predictors of healthful dietary behavior in
adolescents. J Nutr Educ Behav 2002;34:184-92. CrossRefMedlineWeb of Science
.
.
28.↵ Cullen KW, Baranowski T, Owens E, et al. Ethnic differences in social correlates of diet. Health Educ Res
2002;17:7-18. Abstract/FREE Full Text
.
.
29.↵ Hambleton RK, Swaminathan H, Rogers HJ. Fundamentals of Item Response Theory. Thousand Oaks, CA:
13
Sage Publications, Inc; 1991. Search Google Scholar
.
.
30.↵ Wilson M, Allen D, Li JC. Improving measurement in health education and health behavior research using
item response modeling: introducing item response modeling. Health Educ Res 2006;21 Suppl 1:i4-i18. Abstract/FREE Full
Text
.
.
31.↵ Wilson M, Allen D, Li JC. Improving measurement in health education and health behavior research using
item response modeling: comparison with the classical test theory approach. Health Educ Res 2006;21 Suppl 1:i19-i32.
Abstract/FREE Full Text
.
.
32. Lord F. Applications of Item Response Theory to Practical Testing Problems. Hillsdale, NJ: Lawrence
Erlbaum Associates; 1980. Search Google Scholar
.
.
33. Lord F, Novick MR. Statistical Theories of Mental Test Scores. Reading, MA: Addison-Wesley; 1968. Search
Google Scholar
.
.
34.↵ Rasch G. Probabilistic Models for Some Intelligence and Attainment Tests. Chicago, IL: University of
Chicago Press; 1980. Search Google Scholar
.
.
35.↵ Masse LC, Dassa C, Gauvin L, et al. Emerging measurement and statistical methods in physical activity
research. Am J Prev Med 2002;23:44-55. CrossRefMedlineWeb of Science
.
.
36.↵ Swaminathan H, Rogers H. Detecting differential item functioning using logistic regression procedures. J
Educ Meas 1990;27:361-70. CrossRef
.
.
37.↵ Wilson M. Constructing Measures: An Item Response Modeling Approach. Mahwah, NJ: Lawrence Erlbaum
Associates; 2005. Search Google Scholar
.
.
38.↵ Baranowski T, Baranowski J, Cullen KW, et al. Squire's Quest! Dietary outcome evaluation of a multimedia
game. Am J Prev Med 2003;24:52-61. CrossRefMedlineWeb of Science
.
.
.
39.↵ Nunnally JC, Bernstein IH. Psychometric Theory. New York: McGraw-Hill; 1994. Search Google Scholar
40.↵ SPSS Inc. SPSS for Windows Release 11.0.1. Chicago, IL: SPSS Inc.; 2001.
.
.
41.↵ Bond TG, Fox CM. Applying the Rasch Model: Fundamental Measurement in the Human Sciences.
Mahwah, NJ: Lawrence Erlbaum Associates, Publishers; 2001. Search Google Scholar
.
.
42.↵ Reise SP, Yu J. Parameter recovery in the graded response model using MULTILOG. J Educ Meas
1990;27:133-44. CrossRef
.
.
43.↵ Orlando M, Marshall GN. Differential item functioning in a Spanish translation of the PTSD checklist:
detection and evaluation of impact. Psychol Assess 2002;14:50-9. CrossRefMedlineWeb of Science
.
.
44.↵ Teresi J. Conference on Improving Health Outcomes Assessment Based on Modern Measurement Theory
and Computerized Adaptive Testing. Bethesda, MD; 2004. Differential item functioning and health assessment. Search
Google Scholar
.
.
45.↵ Bolt DM. A Monte Carlo comparison of parametric and nonparametric polytomous DIF detection methods.
Appl Meas Educ 2002;15:113-41. CrossRef
.
.
46.↵ Andrich D. A rating formulation for ordered response categories. Psychometrika 1978;43:561-73.
CrossRefWeb of Science
.
.
Science
47.↵ Masters GN. A Rasch model for partial credit scoring. Psychometrika 1982;47:149-74. CrossRefWeb of
.
.
48.↵ Wu M. Plausible values. Rasch Meas Trans 2004;18:976-78. Search Google Scholar
.
.
49.↵ Wu M, Adams R, Haldane S. ConQuest. Berkeley, CA: Australian Council for Educational Research
University of California; 2003. Search Google Scholar
14
.
.
50.↵ Shepard LA. Definition of bias. In: Berk RA, Baltimore MD, editors. Handbook of Methods for Detecting
Test Bias. Baltimore, MD: Johns Hopkins University Press; 1982. p. 9-30. Search Google Scholar
.
.
51.↵ Smith RM. Detecting item bias with the Rasch model. In: Smith EV, Smith RM, editors. Introduction to
Rasch measurement. Maple Grove, MN: JAM Press; 2004. p. 391-418. Search Google Scholar
.
.
52.↵ Orlando M. Conference on Improving Health Outcomes Assessment Based on Modern Measurement Theory
and Computerized Adaptive Testing. Bethesda, MD: Hyatt; 2004. Critical issues to address when applying item response
theory (IRT) models. Search Google Scholar
.
.
53.↵ Paek I. Unpublished PhD Dissertation. Berkeley, CA: University of California; 2002. Investigation of
differential item function: comparisons among approaches, and extension to a multidimensional context. Search Google
Scholar
.
.
54.↵ Angoff WH. Perspectives on differential item functioning methodology. In: Holland PW, Wainer H, editors.
Differential Item Functioning. Hillsdale, NJ: Lawrence Erlbaum and Associates; 1993. p. 3-24. Search Google Scholar
.
.
55.↵ Baranowski T, Allen D, Masse LC, et al. Does participation in an intervention affect the responses on selfreport questionnaires? Health Educ Res 2006;21 Suppl 1:i98-i109. Abstract/FREE Full Text
........................................................................................
3 Gruber, K. & Halderman, L.(2009). Using the Family to Combat Childhood and Adult
Obesity. Preventive Chronic Disease. 6(3):A106.
http://www.cdc.gov/pcd/issues/2009/
-MY WRITING
-This article lays out all the toughest problems I will face teaching students who are
overweight how to become; “Fit for Life.”
- The family shapes children's dietary intake and eating habits (11-13) and their physical
activity patterns (14).
- If everyone in the family is overweight, but the parents do not think anyone is overweight,
they may refuse to support their children in a weight lose diet. The authors in one study
analyzed by Gruber and Halderman,- Borra S, Kelly L, Shirrefs M, Neville K, and Geiger
C - are concerned about improving communication skills between parents, students and
15
teachers so that overweight students can develop healthier lifestyles and prevent obesity.
- Obesity tends to run in families and the most effective way to intervene and help children
lose weight is to influence and educate parents. ‘Some parents believe that actions that
could help their children lose weight are ill-advised, so they refuse to support their
engaging in strenuous activity.
- Parental influence is a critical determinant of children's food preferences (60,61). Though
the data are limited, research does suggest that some food preferences developed in early
childhood persist into adulthood (62).
- Evidence indicates that direct involvement of at least 1 parent improves a child's weight
management (15).
- Parental involvement has been identified as an important determinant influencing young
girls to be physically active (14,67,68).
- Results revealed that reinforcing weight loss for both the parent and the child produced
the greatest weight loss over a 5-year period.
- The authors share the perspective of Baranowski and Nader (74) who suggest that rather
than pit an individual approach and a family-oriented approach against each other,
involving the entire family may be helpful in determining how to best promote behavior
change among all its members.
- Teaching in a NYC public school is not an ideal environment. Ideally, my PE department
should be able to attend a PTA meeting that is packed with parents, and we should be able
to inspire all the parents (average and overweight) to get behind the idea that their children
should join a team or exercise on a regular basis. Ideally, my department should be able to
hire a social worker and a nutritionist who will meet on a monthly basis with the parents
16
and talk about health and wellness through diet.
- In reality, I can only hope that a few of the less physically fit children have parents that
remember to visit me on Open School Night so that I can gently tell them that their children
may not pass gym if they do not wear sneakers and shorts to class. I will, of course, teach
about fitness and eating healthy to the best of my ability no matter what circumstances I
have at school.
......................................................................................
Article:
Gruber, K. & Halderman, L.(2009). Using the Family to Combat Childhood and Adult
Obesity. Preventive Chronic Disease. 6(3):A106.
http://www.cdc.gov/pcd/issues/2009/
Abstract
The purpose of this article is to emphasize the value of the family as a source of behavior
change, particularly with respect to attaining achievable goals of weight loss and regular
physical activity for youth and their families. We present a review of the literature,
providing support for the value of the family in influencing children to form good diet and
exercise behaviors and as a source of support and motivation for individuals seeking to
lose or control their weight and to start and maintain a physically active lifestyle.
Recognizing the importance of family behavior in the development of weight control and
weight loss activities is essential. Future work should focus on identifying measurable
parameters of family-level weight control behaviors and ways to apply those parameters to
help create new interventions that use the strengths of the family for achieving weight
control goals.
Back to top
Introduction
The extensiveness of the obesity issue and the potential for obesity to affect the quality of
life of individuals and families underscore the urgent need for actions that can produce
safe weight loss and result in effective weight management (1). The solution seems simple
17
— take in fewer calories than you expend — but for most people this remedy is
challenging. Diets and exercise routines can fail for many reasons. In part, this failure
occurs because achieving weight loss through dieting or exercise requires maintenance of
behavior change, which is difficult to sustain unless people have support (2-4). Support
occurs most readily in a social environment that facilitates healthy eating and healthpromoting exercise. Many efforts that help people to achieve weight loss fail to establish
the supportive social and interpersonal context that can reinforce and help maintain weight
loss–related behavior (5). Effective approaches should include these contextual influences
and focus on making changes in the environment rather than in the individual. The social
context most likely to support making healthy behavior changes is the family.
Back to top
References
Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States,
1999-2004. JAMA 2006;295(13):1549-55.
Kelsey K, Earp JL, Kirkley BG. Is social support beneficial for dietary change? A review of the literature. Fam Community Health
1997;20(3):70-82.
Okun MA, Ruehlman L, Karoly P, Lutz R, Fairholme C, Schaub R. Social support and social norms: do both contribute to predicting
leisure-time exercise? Am J Behav 2003;27(5):493-507.
Wing RR, Jeffrey RW. Benefits of recruiting participants with friends and increasing social support for weight loss and maintenance.
J Consult Clin Psychol 1999;67(1):132-38.
Soubhi H, Potvin L, Paradis G. Family process and parent’s leisure time physical activity. Am J Health Behav 2004;28(3):218-30.
Sallis JF, Nader PR. Family determinants of health behaviors. In: Gochman DS, editor. Health behavior: emerging research
perspectives. New York (NY): Plenum Press; 1988. pp. 107-24.
Medalie JH, Cole-Kelly K. The clinical importance of defining family. Am Fam Physician 2002;65(7):1277-9.
Tilson EC, McBride CM, Brouwer RN. Formative development of an intervention to stop family tobacco use: the Parents and
Children Talking (PACT) intervention. J Health Comm 2005;10(6):491-508.
Epstein LH, Wing RR, Koeske R, Valoski A. Long-term effects of family-based treatment of childhood obesity. J Consult Clin
Psychol 1987;58(1):91-5.
Crockett SJ, Mullis RM, Perry CL. Parent nutrition education: a conceptual model. J Sch Health 1988;58(2):53-7.
Cullen KW, Baranowski T, Rittenberry L, Cosart C, Hebert D, de Moor C. Child-reported family and peer influences on fruit, juice
and vegetable consumption: reliability and validity of measures. Health Education Res 2001;16(2):187-200.
Cullen KW, Klesges LM, Sherwood NE, Baranowski T, Beech B, Pratt C, et al. Measurement characteristics of diet-related
psychosocial questionnaires among African-American parents and their 8- to 10-year old daughters: results from the Girls’
Health Enrichment Multi-site Studies. Prev Med 2004;38(Suppl 1):S34-42.
Savage JS, Fisher JO, Birch LL. Parental influence on eating behavior: conception to adolescence. J Law Med Ethics 2007;35(1):2234.
Davison KK, Cutting TM, Birch LL. Parents’ activity-related parenting practices predict girls’ physical activity. Med Sci Sport Exerc
2003;35(9):1589-95.
Epstein LH. Family-based behavioural intervention for obese children. Int J Obes 1996;20(Suppl 1):S14-21.
Golan M, Weitzman A. Familial approach to the treatment of childhood obesity: conceptual mode. J Nutr Educ 2001;33(2):102-7.
Robinson TN. Behavioural treatment of childhood and adolescent obesity. Int J Obes 1999;23(Suppl 2):S52-57.
van Dam HA, van der Horst FG, Knoops L, Ryckman RM, Crebolder HFJM, van den Borner BHW. Social support in diabetes: a
systematic review of controlled intervention studies. Pat Educ Couns 2005;59(1):1-12.
Epstein LH, McCurley J, Wing RR, Valoski A. Five-year follow-up of family-based behavioral treatments for childhood obesity. J
Consult Clin Psychol 1990;58(5):661-4.
Epstein LH, Valoski A, Wing RR, McCurley J. Ten-year follow-up of behavioral family-based treatment for obese children. JAMA
1990;264(19):2519-23.
Golan M, Crow S. Targeting parents exclusively in the treatment of childhood obesity: long-term results. Obes Res 2004;12(2):35761.
Nader PR, Sallis JF, Patterson TL, Abramson IS, Rupp JW, Senn KL, et al. A family approach to cardiovascular risk reduction:
results from the San Diego Family Health Project. Health Educ Q 1989;16(2):229-44.
Perry CL, Crockett SJ, Pirie P. Influencing parental health behavior: implications of community assessments. Health Education
1987;Oct/Nov:68-77.
Perry CL, Luepker RV, Murray DM, Kurth C, Mullis R, Crockett S, et al. Parent involvement with children’s health promotion: the
Minnesota home team. Am J Public Health 1988;78(9):1156-60.
Bandura A. Social foundations for thought and action: a social cognitive theory. Englewood Cliffs (NJ): Prentice Hall; 1986.
Wrotniak BH, Epstein LH, Paluch RA, Roemmich JN. Parent weight change as a predictor of child weight change in family-based
behavioral obesity treatment. Arch Pediatr Adolesc Med 2004;158(4):342-7.
Blackwell BS, Reed MD. Power-control as a between- and within-family model: reconsidering the unit of analysis. J Youth Adolesc
2003;32(5):385-99.
Bonomi AE, Boudreau DM, Fishman PA, Meenan RT, Revicki DA. Is a family equal to the sum of its parts? Estimating family-level
well-being for cost-effectiveness analysis. Qual Life Res 2005;14(4):1127-33.
18
Chao J, Zyzanski S, Flocke S. Choosing a family level indicator of family function. Fam Syst Health 1998;16(4):367-74.
De Bourdeaudhuij I, Brug J. Tailoring dietary feedback to reduce fat intake: an intervention at the family level. Health Educ Res
2000;15(4):449-62.
Bluestein D, Bach PL. Working with families in long-term care. J Am Med Dir Assoc 2007;8(4):265-70.
Gable S, Chang Y, Krull JL. Television watching and frequency of family meals are predictive of overweight onset and persistence in
a national sample of school-aged children. J Am Diet Assoc 2007;107(1):53-61.
Gillman MW, Rifas-Shiman SL, Frazier AL, Rockett HRH, Camargo CA, Field AE, et al. Family dinner and diet quality among older
children and adolescents. Arch Fam Med 2000;9(3):235-40.
Larson NI, Neumark-Sztainer D, Hannan PJ, Story M. Family meals during adolescence are associated with higher diet quality and
healthful meal patterns during young adulthood. J Am Diet Assoc 2007;107(9):1502-10.
Rockett HRH. Family dinner: more than just a meal. J Am Diet Assoc 2007;107(9):1498-501.
De Bourdeaudhuij I. Resemblance in health behaviors between family members. Arch Public Health 1996;54(7-8):251-73.
Patterson TL, Rupp JW, Sallis JF, Atkins CJ, Nader, PR. Aggregation of dietary calories, fats, and sodium in Mexican-American and
Anglo families. Am J Prev Med 1988;4(2):75-82.
Sallis JF, Patterson TL, Buono MJ, Atkins CJ, Nader PR. Aggregation of physical activity habits in Mexican-American and Anglo
families. J Behav Med 1988;11(1):31-41.
Wardle J, Guthrie C, Sanderson S, Birch L, Plomin R. Food and activity preferences in children of lean and obese parents. Int J Obes
2001;25(7):971-7.
Connor SL, Connor WE, Henry H, Sexton G, Keenan EJ. The effects of familial relationships, age, body weight, and diet on blood
pressure and the 24 hour urinary excretion of sodium, potassium, and creatinine in men, women, and children of randomly
selected families. Circulation 1984;70(1):76-85.
Patterson TL, Kaplan RM, Sallis JF, Nader PR. Aggregation of blood pressure in Anglo-American and Mexican-American families.
Prev Med 1987;16(5):616-25.
Wilson DK, Klesges LM, Klesges RC, Eck LH, Hackett-Renner CA, Alpert BS, et al. A prospective study of familial aggregation of
blood pressure in young children. J Clin Epidemiol 1992;45(9):959-69.
Fogleman M, Nuutinen O, Pasanen E, Myohanen E, Saatela T. Parent-child relationship of physical activity patterns and obesity. Int J
Obes 1999;23(12):1262-8.
Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parental
obesity. N Engl J Med 1997;13(25):869-73.
Birch LL, Fisher JO. Mothers’ child-feeding practices influence daughters’ eating and weight. Am J Clin Nutr 2000;71(5):1054-61.
Treuth MS, Butte NF, Ellis KJ, Martin LJ, Couzzie AG. Familial resemblance of body composition in prepubertal girls and their
biological parents. Am J Clin Nutr 2001;74(4):529-33.
Pérusse L, Tremblay A, Leblanc C, Bouchard C. Genetic and environmental influences on level of habitual physical activity and
exercise participation. Am J Epidemiol 1989;29(5):1012-22.
Mulvaney-Day NE, Alegria M, Scribney W. Social cohesion, social support, and health among Latinos in the United States. Soc Sci
Med 2007;64(2):477-95.
Shields CA, Spink KS, Chad K, Muhajarine N, Humbert L, Odnokon PJ. Youth and adolescent physical activity lapsers: examining
self-efficacy as a mediator of the relationship between family social influence and physical activity. Health Psych
2008;13(1):121-30.
Wilson DK, Ampey-Thornhill G. The role of gender and family support on dietary compliance in an African American Adolescent
Hypertension Prevention Study. Ann Behav Med 2001;23(1):59-67.
Heitman LK. The influence of social support on cardiovascular health in families. Fam Community Health 2006;29(2):131-42.
Bull S, Eakin E, Reeves M, Riley K. Multi-level support for physical activity and healthy eating. J Adv Nurs 2006;54(5):585-93.
Eyler AE, Wilcox S, Matson-Koffman D, Evenson KR, Sanderson B, Thompson J, et al. Correlates of physical activity among
women from diverse racial/ethnic groups. J Womens Health Gend Based Med 2002;11(3):239-53.
Cousins JH, Rubovits DS, Dunn JK, Reeves RS, Ramirez AG, Foreyt JP. Family versus individually oriented intervention for weight
loss in Mexican American women. Public Health Rep 1992;107(5):549-55.
McArthur LH, Anguiabo RPV, Nocetti D. Maintenance and change in the diet of Hispanic immigrants in Eastern North Carolina.
Fam Consum Sci Res J 2001;29(4):309-35.
Nader PR, Sallis JF, Rupp J, Atkins C, Patterson T, Abramson I. The San Diego Family Health Project: reaching families through the
schools. J Sch Health 1986;56(6):227-31.
Nader PR, Sallis JF, Patterson TL, Abramson IS, Rupp JW, Senn KL, et al. A family approach to cardiovascular risk reduction:
results from the San Diego Family Health Project. Health Educ Q 1989;16(2):229-44.
Evenson KR, Samiento OL, Macon ML, Tawney KW, Ammerman AS. Environmental, policy, and cultural factors related to physical
activity among Latina immigrants. Women Health 2002;36(2):43-56.
Golan M, Weizman A, Apter A, Fainaru M. Parents as the exclusive agents of change in the treatment of childhood obesity. Am J
Clin Nutr 1998;67(6):1130-5.
Benton D. Role of parents in the determination of the food preferences of children and the development of obesity. Int J Obes
2004;28(7):858-69.
Contento IR, Williams SS, Michela JL, Franklin AB. Understanding the food choice process of adolescents in the context of family
and friends. J Adolesc Health 2006;38(5):575-82.
Haire-Joshu D, Kreuter MK, Holt C, Steger-May K. Estimates of fruit and vegetable intake in childhood and adult dietary behaviors
of African American women. J Nutr Educ Behav 2004;36(6):309-14.
Kohl HW, Hobbs KE. Development of physical activity behaviors among children and adolescents. Pediatrics 1998;101(Suppl
1):549-54.
Horn TS, Horn JL. Family influences on children’s sport and physical activity participation, behavior, and psychosocial responses. In:
Tenebaum G, Eklund RC, editors. Handbook of sport psychology. (3rd ed). Somerset (NJ): John Wiley and Sons; 2007.
Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc
2000;32(5):963-75.
Trost G, Sallis JF, Pate RR, Freedson PS, Taylor WC, Dowda M. Evaluating a model of parental influence on youth physical activity.
19
Am J Prev Med 2003;25(4):277-82.
Sallis JF, Prochaska JJ, Taylor WC, Hill JO, Geraci JC. Correlates of physical activity in a national sample of girls and boys in
Grades 4 through 12. Health Psych 1999;18(4):410-5.
Thompson VJ, Baranowski T, Cullen KW, Rittenberry L, Baranowski J, Taylor WC, et al. Influences on diet and physical activity
among middle-class African American 8- to 10 year-old girls at risk of becoming obese. J Nutr Educ Behav 2003;35(3):11523.
Stang J, Rehorst J, Golicic M. Parental feeding practices and risk of childhood overweight in girls: Implications for dietetics practice.
J Am Diet Assoc 2004;104(7):1076-9.
Spruijt-Metz D, Lindquist CH, Birch LL, Fisher JO, Goran MI. Relation between mothers’ child-feeding practices and children’s
adiposity. Am J Clin Nutr 2002;75(3):581-6.
Neumark-Sztainer D, Hannan PJ, Story M, Croll J, Perry C. Family meal patterns: associations with sociodemographic characteristics
and improved dietary intake among adolescents. J Am Diet Assoc 2003;103(3):317-22.
Ayala GX, Baquero B, Arredondo EM, Campbell N, Larios S, Elder JP. Association between family variables and Mexican American
children’s dietary behaviors. J Nutr Educ Behav 2007;39(2):62-9.
Golan M, Fainaru M, Weizman A. Role of behavior modification in the treatment of childhood obesity with the parents as the
exclusive agents of change. Int J Obes 1998;22(12):1217-24.
Baranowski T, Nader PR. Family involvement in health behavior change programs. In: Turk DC, Kerns RD, editors. Health, illness,
and families. New York: John Wiley and Sons; 1985. pp. 81-107.
Lindsay AC, Sussner KM, Kim J, Gortmaker SL. The role of parents in preventing childhood obesity. Future Child 2006;16(1):16986.
Chatterjee N, Blakely DE, Barton C. Perspectives on obesity and barriers to control from workers at a community center serving lowincome Hispanic children and families. J Community Health Nurs 2005;22(1):23-36.
American Academy of Pediatrics. Prevention of pediatric overweight and obesity. Pediatrics 2003;112(2):424-30.
Sothern MS. Obesity prevention in children: physical activity and nutrition. Nutr 2004;20(7-8):704-8.
American Dietetic Association. Position of the American Dietetic Association: dietary guidance for healthy children ages 2 to 11
years. J Am Diet Assoc 2004;104(4):660-77.
Kirk S, Scott BJ, Daniels SR. Pediatric obesity epidemic: treatment options. J Am Diet Assoc 2005;105(Suppl 1):S44-51.
Gustafson SL, Rhodes RE. Parental correlates of physical activity in children and early adolescents. Sport Med 2006;36(1):79-97.
Gortmaker SL, Cheung LWY, Peterson KE, Chomitz G, Cradle JH, Dart H, et al. Impact of a school-based interdisciplinary
intervention on diet and physical activity among urban primary school children. Arch Pediatr Adolesc Med 1999;153(9):97583.
Hawley SR, Beckman H, Bishop T. Development of an obesity prevention and management program for children and adolescents in
a rural setting. J Community Health Nurs 2006;23(2):69-80.
Müller MJ, Danilezik S, Pust S. School- and family-based interventions to prevent overweight in children. Proc Nutr Soc
2005;64(2):249-54.
Peterson KE, Fox MK. Addressing the epidemic of childhood obesity through school-based interventions: what has been done and
where do we go from here? J Law Med Ethics 2007;35(1):113-30.
Slawta J, Bentley J, Smith J, Kelly J, Syman-Degler L. Promoting healthy lifestyles in children: a pilot program of Be A Fit Kid.
Health Promot Pract 2008;9(3):305-12.
Beech BM, Klesges RC, Kumanyika SK, Murray DM, Klesges L, McClanahan B, et al. Child- and parent-targeted interventions: the
Memphis GEMS Pilot Study. Ethn Dis 2003;13(Suppl 1):40-53.
Ford BS, McDonald TE, Owens AS, Robinson TN. Primary care interventions to reduce television viewing in African-American
children. Am J Prev Med 2002;22(2):106-9.
Golley RK, Magarey AM, Baur LA, Steinbeck KS, Daniels LA. Twelve-month effectiveness of a parent-led family-focused weightmanagement program for prepubertal children: a randomized, controlled trial. Pediatrics 2007;119(3):517-25.
Rodearmel SJ, Wyatt HR, Barry MJ, Dong F, Pan D, Israel RG, et al. A family-based approach to preventing excessive weight gain.
Obesity 2006;14(8):1392-1401.
Coleman KJ, Tiller CL, Sanchez J, Heath EM, Sy O, Milliken G, et al. Prevention of the epidemic increase in child risk of overweight
in low-income schools. Arch Pediatr Adolesc Med 2005;159(3):217-24.
Fitzgibbon ML, Stolley MR, Schiffer L, Van Horn L, Kauferchrisoffel K, Dyer A. Two-year follow-up results for Hip-Hop to Health
Jr.: a randomized controlled trial for overweight prevention in preschool minority children. J Pediatrics 2005;146(5):618-25.
Engels HJ, Gretebek RJ, Gretebek KA, Jiménez L. Promoting healthful diets and exercise: efficacy of a 12-week after-school
program in urban African Americans. J Am Diet Assoc 2005;105(3):721-8.
Borra ST, Kelly L, Shirreffs MB, Neville K, Geiger CJ. Developing health messages: qualitative studies with children, parents, and
teachers help identify communications opportunities for healthful lifestyles and the prevention of obesity. J Am Diet Assoc
2003;103(6):721-8.
Neumark-Sztainer D, Wall M, Story M, van den Berg P. Accurate parental classification of overweight adolescents’ status: does it
matter? Pediatrics 2008;121(6):e1495-e1502.
Eckstein KC, Mikhail LM, Ariza AJ, Thomson JS, Millard SC, Binns HJ, et al. Parents’ perceptions of their child’s weight and
health. Pediatrics 2006;117(3):681-90.
Contento IR, Basch C, Zybert P. Body image, weight, and food choices of Latina women and their young children. J Nutr Educ
Behav 2003;35(5):236-48.
Jain A, Sherman SN, Chamberlin LA, Carter Y, Powers SW, Whitaker RC. Why don’t low-income mothers worry about their
preschoolers being overweight? Pediatrics 2001;107(50):1138-46.
Laroche HH, Davis MM, Forman J, Palmisano G, Heisler M. What about the children? The experience of families involved in an
adult-focused diabetes intervention. Public Health Nutr 2008;11(4):427-36.
Paisley J, Beanlands H, Goldman J, Evers S, Chappell J. Dietary change: what are the responses and roles of significant others? J
Nutr Educ Behav 2008;40(2):80-8.
Roos E, Sarlio-Lähteenkorva S, Laauka T, Lahelma E. Associations of work-family conflicts with food habits and physical activity.
20
Public Health Nutr 2007;10(3):2229
........................................................................................
4.Fisher, A. Boyle, J. Paton, J. Tomporowski, P. Watson, C. McColl, J. Reilly, J. (2011).
Effects of a physical education intervention on cognitive function in young
children: randomized controlled pilot study. BMC Pediatrics. 11:97
doi:10.1186/1471-2431-11-97.
-MY WRITING
- This study suggests that higher levels of physical fitness in children, just as it has been
proven in adults, may be associated with improved neurocognitive processing [12], and
increased physical activity may enhance school 'on-task' behavior [13]. Increased physical
activity may therefore provide cognitive and educational benefits across childhood and
adolescence.
- The researchers could not conclude what an optimal dose of exercise might be. Meters
connected to the children during the study from the hours of 7 AM – 11 PM daily.
- The study lasted a term of PE.
- There were 2 groups. There was a lack of emphasis on aerobic activities in the control
group which they hoped would increase the contrast between intervention and control
groups.
- Academic tests were administered 3 weeks before the study began, in the middle of the 10
weeks and at the end of the 10 weeks.
21
- Researchers could not count on the fact that the children actually moved for a full hour of
PE.
- There are so many problems with the study that the researchers advocate to more studies.
-Tests used :
- The Cognitive Assessment System (CAS;[19]);
- The Cambridge Neuropsychological Test Battery (CANTAB http://www.cantab.com);
-The Attention Network Test (ANT) [20].
- High reliability of measurements in children under age 7 has been reported in one study
for the CAS [19], but such data are not available for the ANT or the CANTAB and so
reliability data for the ANT and CANTAB were collected in the present study prior to the
exploratory RCT.
-I have one research study that concluded that the executive function of the brain improves
with exercise but mental function, in general, did not improve. This is study comes to the
part of the conclusion that,” Exercise and Children’s Intelligence, Cognition and Academic
Achievement” concluded.
- Both studies agree that exercise is important. The questions are – how much is effective
and how powerful is the effect of exercise on mental ability.
........................................................................................
Article:
Fisher, A. Boyle, J. Paton, J. Tomporowski, P. Watson, C. McColl, J. Reilly, J. (2011).
Effects of a physical education intervention on cognitive function in young
children: randomized controlled pilot study. BMC Pediatrics. 11:97
22
doi:10.1186/1471-2431-11-97.
Abstract
Background
Randomized controlled trials (RCT) are required to test relationships between physical
activity and cognition in children, but these must be informed by exploratory studies. This
study aimed to inform future RCT by: conducting practical utility and reliability studies to
identify appropriate cognitive outcome measures; piloting an RCT of a 10 week physical
education (PE) intervention which involved 2 hours per week of aerobically intense PE
compared to 2 hours of standard PE (control).
Methods
64 healthy children (mean age 6.2 yrs SD 0.3; 33 boys) recruited from 6 primary schools.
Outcome measures were the Cambridge Neuropsychological Test Battery (CANTAB), the
Attention Network Test (ANT), the Cognitive Assessment System (CAS) and the short
form of the Connor's Parent Rating Scale (CPRS:S). Physical activity was measured
habitually and during PE sessions using the Actigraph accelerometer.
Results
Test- retest intraclass correlations from CANTAB Spatial Span (r 0.51) and Spatial
Working Memory Errors (0.59) and ANT Reaction Time (0.37) and ANT Accuracy (0.60)
were significant, but low. Physical activity was significantly higher during intervention vs.
control PE sessions (p < 0.0001). There were no significant differences between
intervention and control group changes in CAS scores. Differences between intervention
and control groups favoring the intervention were observed for CANTAB Spatial Span,
CANTAB Spatial Working Memory Errors, and ANT Accuracy.
Conclusions
The present study has identified practical and age-appropriate cognitive and behavioral
outcome measures for future RCT, and identified that schools are willing to increase PE
time.
Trial registration number
ISRCTN70853932 (http://www.controlled-trials.com)
Background
There has been a resurgence of interest in the relationship between physical activity and
human cognitive function in recent years [1-5]. Animal evidence suggests that increased
physical activity can enhance brain function [6]. Research, largely in older adults, supports
the notion that aerobic exercise can enhance human brain structure, prevent age-related
brain tissue loss, and improve cognitive performance [7-9]. Aerobic activity may influence
executive function specifically [2,7-9].
The literature is consistent in reporting that increased time spent on physical education in
23
schools has no detrimental effect on more 'academic' subjects and may even enhance
academic attainment [10-13]. Higher levels of physical fitness in children may be
associated with improved neurocognitive processing [12], and increased physical activity
may enhance school 'on-task' behavior [13]. Increased physical activity may therefore
provide cognitive and educational benefits across childhood and adolescence.
Experimental evidence in children is very limited [3,5]: < 1% of published exercise and
cognition studies have involved child participants, and experimental evidence from preschool children is absent. There is therefore a need for randomized trials in children to
establish definitively the presence of any cognitive effects of physical activity and to
identify their nature (e.g. dose-response effects; specificity to particular cognitive
processes). The UK Medical Research Council framework for complex interventions
suggests that prior to carrying out full RCT it is important to carry out exploratory trials to
examine: acceptability of study measurements; feasibility of the proposed trial; likely
retention of participants and missing data [14].
The measurement of executive function is especially problematic in younger children [15].
Testing for effects of exercise on executive function in children is also problematic
because of the difficulty of establishing exercise programs that effectively increase the
levels of physical activity [16-18]. Carrying out well designed and adequately powered
RCT to test for relationships between physical activity and executive function in young
children therefore presents researchers with a number of major challenges. Future RCT in
this area will have to be informed by exploratory studies. These studies need to establish
which interventions are practical and what is the optimal 'dose' of physical activity. They
will also need to establish the practical utility and reliability of potential measures of
executive function (outcome measures) in young children. Finally, they will need to provide
information on effect sizes to calculate sample size and ensure adequate power of future
large scale RCT.
The present study therefore aimed to collect the data necessary to design and power a
future school-based RCT on the influence of aerobic activity on executive function in 5-6
year olds. All cognitive measures were specified a priori as candidate measures potentially
sensitive to changes in physical activity.
References
Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States,
1999-2004. JAMA 2006;295(13):1549-55.
Kelsey K, Earp JL, Kirkley BG. Is social support beneficial for dietary change? A review of the literature. Fam Community Health
1997;20(3):70-82.
Okun MA, Ruehlman L, Karoly P, Lutz R, Fairholme C, Schaub R. Social support and social norms: do both contribute to predicting
leisure-time exercise? Am J Behav 2003;27(5):493-507.
Wing RR, Jeffrey RW. Benefits of recruiting participants with friends and increasing social support for weight loss and maintenance.
J Consult Clin Psychol 1999;67(1):132-38.
Soubhi H, Potvin L, Paradis G. Family process and parent’s leisure time physical activity. Am J Health Behav 2004;28(3):218-30.
Sallis JF, Nader PR. Family determinants of health behaviors. In: Gochman DS, editor. Health behavior: emerging research
perspectives. New York (NY): Plenum Press; 1988. pp. 107-24.
Medalie JH, Cole-Kelly K. The clinical importance of defining family. Am Fam Physician 2002;65(7):1277-9.
Tilson EC, McBride CM, Brouwer RN. Formative development of an intervention to stop family tobacco use: the Parents and
Children Talking (PACT) intervention. J Health Comm 2005;10(6):491-508.
Epstein LH, Wing RR, Koeske R, Valoski A. Long-term effects of family-based treatment of childhood obesity. J Consult Clin
Psychol 1987;58(1):91-5.
24
Crockett SJ, Mullis RM, Perry CL. Parent nutrition education: a conceptual model. J Sch Health 1988;58(2):53-7.
Cullen KW, Baranowski T, Rittenberry L, Cosart C, Hebert D, de Moor C. Child-reported family and peer influences on fruit, juice
and vegetable consumption: reliability and validity of measures. Health Education Res 2001;16(2):187-200.
Cullen KW, Klesges LM, Sherwood NE, Baranowski T, Beech B, Pratt C, et al. Measurement characteristics of diet-related
psychosocial questionnaires among African-American parents and their 8- to 10-year old daughters: results from the Girls’
Health Enrichment Multi-site Studies. Prev Med 2004;38(Suppl 1):S34-42.
Savage JS, Fisher JO, Birch LL. Parental influence on eating behavior: conception to adolescence. J Law Med Ethics 2007;35(1):2234.
Davison KK, Cutting TM, Birch LL. Parents’ activity-related parenting practices predict girls’ physical activity. Med Sci Sport Exerc
2003;35(9):1589-95.
Epstein LH. Family-based behavioural intervention for obese children. Int J Obes 1996;20(Suppl 1):S14-21.
Golan M, Weitzman A. Familial approach to the treatment of childhood obesity: conceptual mode. J Nutr Educ 2001;33(2):102-7.
Robinson TN. Behavioural treatment of childhood and adolescent obesity. Int J Obes 1999;23(Suppl 2):S52-57.
van Dam HA, van der Horst FG, Knoops L, Ryckman RM, Crebolder HFJM, van den Borner BHW. Social support in diabetes: a
systematic review of controlled intervention studies. Pat Educ Couns 2005;59(1):1-12.
Epstein LH, McCurley J, Wing RR, Valoski A. Five-year follow-up of family-based behavioral treatments for childhood obesity. J
Consult Clin Psychol 1990;58(5):661-4.
Epstein LH, Valoski A, Wing RR, McCurley J. Ten-year follow-up of behavioral family-based treatment for obese children. JAMA
1990;264(19):2519-23.
Golan M, Crow S. Targeting parents exclusively in the treatment of childhood obesity: long-term results. Obes Res 2004;12(2):35761.
Nader PR, Sallis JF, Patterson TL, Abramson IS, Rupp JW, Senn KL, et al. A family approach to cardiovascular risk reduction:
results from the San Diego Family Health Project. Health Educ Q 1989;16(2):229-44.
Perry CL, Crockett SJ, Pirie P. Influencing parental health behavior: implications of community assessments. Health Education
1987;Oct/Nov:68-77.
Perry CL, Luepker RV, Murray DM, Kurth C, Mullis R, Crockett S, et al. Parent involvement with children’s health promotion: the
Minnesota home team. Am J Public Health 1988;78(9):1156-60.
Bandura A. Social foundations for thought and action: a social cognitive theory. Englewood Cliffs (NJ): Prentice Hall; 1986.
Wrotniak BH, Epstein LH, Paluch RA, Roemmich JN. Parent weight change as a predictor of child weight change in family-based
behavioral obesity treatment. Arch Pediatr Adolesc Med 2004;158(4):342-7.
Blackwell BS, Reed MD. Power-control as a between- and within-family model: reconsidering the unit of analysis. J Youth Adolesc
2003;32(5):385-99.
Bonomi AE, Boudreau DM, Fishman PA, Meenan RT, Revicki DA. Is a family equal to the sum of its parts? Estimating family-level
well-being for cost-effectiveness analysis. Qual Life Res 2005;14(4):1127-33.
Chao J, Zyzanski S, Flocke S. Choosing a family level indicator of family function. Fam Syst Health 1998;16(4):367-74.
De Bourdeaudhuij I, Brug J. Tailoring dietary feedback to reduce fat intake: an intervention at the family level. Health Educ Res
2000;15(4):449-62.
Bluestein D, Bach PL. Working with families in long-term care. J Am Med Dir Assoc 2007;8(4):265-70.
Gable S, Chang Y, Krull JL. Television watching and frequency of family meals are predictive of overweight onset and persistence in
a national sample of school-aged children. J Am Diet Assoc 2007;107(1):53-61.
Gillman MW, Rifas-Shiman SL, Frazier AL, Rockett HRH, Camargo CA, Field AE, et al. Family dinner and diet quality among older
children and adolescents. Arch Fam Med 2000;9(3):235-40.
Larson NI, Neumark-Sztainer D, Hannan PJ, Story M. Family meals during adolescence are associated with higher diet quality and
healthful meal patterns during young adulthood. J Am Diet Assoc 2007;107(9):1502-10.
Rockett HRH. Family dinner: more than just a meal. J Am Diet Assoc 2007;107(9):1498-501.
De Bourdeaudhuij I. Resemblance in health behaviors between family members. Arch Public Health 1996;54(7-8):251-73.
Patterson TL, Rupp JW, Sallis JF, Atkins CJ, Nader, PR. Aggregation of dietary calories, fats, and sodium in Mexican-American and
Anglo families. Am J Prev Med 1988;4(2):75-82.
Sallis JF, Patterson TL, Buono MJ, Atkins CJ, Nader PR. Aggregation of physical activity habits in Mexican-American and Anglo
families. J Behav Med 1988;11(1):31-41.
Wardle J, Guthrie C, Sanderson S, Birch L, Plomin R. Food and activity preferences in children of lean and obese parents. Int J Obes
2001;25(7):971-7.
Connor SL, Connor WE, Henry H, Sexton G, Keenan EJ. The effects of familial relationships, age, body weight, and diet on blood
pressure and the 24 hour urinary excretion of sodium, potassium, and creatinine in men, women, and children of randomly
selected families. Circulation 1984;70(1):76-85.
Patterson TL, Kaplan RM, Sallis JF, Nader PR. Aggregation of blood pressure in Anglo-American and Mexican-American families.
Prev Med 1987;16(5):616-25.
Wilson DK, Klesges LM, Klesges RC, Eck LH, Hackett-Renner CA, Alpert BS, et al. A prospective study of familial aggregation of
blood pressure in young children. J Clin Epidemiol 1992;45(9):959-69.
Fogleman M, Nuutinen O, Pasanen E, Myohanen E, Saatela T. Parent-child relationship of physical activity patterns and obesity. Int J
Obes 1999;23(12):1262-8.
Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parental
obesity. N Engl J Med 1997;13(25):869-73.
Birch LL, Fisher JO. Mothers’ child-feeding practices influence daughters’ eating and weight. Am J Clin Nutr 2000;71(5):1054-61.
Treuth MS, Butte NF, Ellis KJ, Martin LJ, Couzzie AG. Familial resemblance of body composition in prepubertal girls and their
biological parents. Am J Clin Nutr 2001;74(4):529-33.
Pérusse L, Tremblay A, Leblanc C, Bouchard C. Genetic and environmental influences on level of habitual physical activity and
exercise participation. Am J Epidemiol 1989;29(5):1012-22.
Mulvaney-Day NE, Alegria M, Scribney W. Social cohesion, social support, and health among Latinos in the United States. Soc Sci
Med 2007;64(2):477-95.
25
Shields CA, Spink KS, Chad K, Muhajarine N, Humbert L, Odnokon PJ. Youth and adolescent physical activity lapsers: examining
self-efficacy as a mediator of the relationship between family social influence and physical activity. Health Psych
2008;13(1):121-30.
Wilson DK, Ampey-Thornhill G. The role of gender and family support on dietary compliance in an African American Adolescent
Hypertension Prevention Study. Ann Behav Med 2001;23(1):59-67.
Heitman LK. The influence of social support on cardiovascular health in families. Fam Community Health 2006;29(2):131-42.
Bull S, Eakin E, Reeves M, Riley K. Multi-level support for physical activity and healthy eating. J Adv Nurs 2006;54(5):585-93.
Eyler AE, Wilcox S, Matson-Koffman D, Evenson KR, Sanderson B, Thompson J, et al. Correlates of physical activity among
women from diverse racial/ethnic groups. J Womens Health Gend Based Med 2002;11(3):239-53.
Cousins JH, Rubovits DS, Dunn JK, Reeves RS, Ramirez AG, Foreyt JP. Family versus individually oriented intervention for weight
loss in Mexican American women. Public Health Rep 1992;107(5):549-55.
McArthur LH, Anguiabo RPV, Nocetti D. Maintenance and change in the diet of Hispanic immigrants in Eastern North Carolina.
Fam Consum Sci Res J 2001;29(4):309-35.
Nader PR, Sallis JF, Rupp J, Atkins C, Patterson T, Abramson I. The San Diego Family Health Project: reaching families through the
schools. J Sch Health 1986;56(6):227-31.
Nader PR, Sallis JF, Patterson TL, Abramson IS, Rupp JW, Senn KL, et al. A family approach to cardiovascular risk reduction:
results from the San Diego Family Health Project. Health Educ Q 1989;16(2):229-44.
Evenson KR, Samiento OL, Macon ML, Tawney KW, Ammerman AS. Environmental, policy, and cultural factors related to physical
activity among Latina immigrants. Women Health 2002;36(2):43-56.
Golan M, Weizman A, Apter A, Fainaru M. Parents as the exclusive agents of change in the treatment of childhood obesity. Am J
Clin Nutr 1998;67(6):1130-5.
Benton D. Role of parents in the determination of the food preferences of children and the development of obesity. Int J Obes
2004;28(7):858-69.
Contento IR, Williams SS, Michela JL, Franklin AB. Understanding the food choice process of adolescents in the context of family
and friends. J Adolesc Health 2006;38(5):575-82.
Haire-Joshu D, Kreuter MK, Holt C, Steger-May K. Estimates of fruit and vegetable intake in childhood and adult dietary behaviors
of African American women. J Nutr Educ Behav 2004;36(6):309-14.
Kohl HW, Hobbs KE. Development of physical activity behaviors among children and adolescents. Pediatrics 1998;101(Suppl
1):549-54.
Horn TS, Horn JL. Family influences on children’s sport and physical activity participation, behavior, and psychosocial responses. In:
Tenebaum G, Eklund RC, editors. Handbook of sport psychology. (3rd ed). Somerset (NJ): John Wiley and Sons; 2007.
Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc
2000;32(5):963-75.
Trost G, Sallis JF, Pate RR, Freedson PS, Taylor WC, Dowda M. Evaluating a model of parental influence on youth physical activity.
Am J Prev Med 2003;25(4):277-82.
Sallis JF, Prochaska JJ, Taylor WC, Hill JO, Geraci JC. Correlates of physical activity in a national sample of girls and boys in
Grades 4 through 12. Health Psych 1999;18(4):410-5.
Thompson VJ, Baranowski T, Cullen KW, Rittenberry L, Baranowski J, Taylor WC, et al. Influences on diet and physical activity
among middle-class African American 8- to 10 year-old girls at risk of becoming obese. J Nutr Educ Behav 2003;35(3):11523.
Stang J, Rehorst J, Golicic M. Parental feeding practices and risk of childhood overweight in girls: Implications for dietetics practice.
J Am Diet Assoc 2004;104(7):1076-9.
Spruijt-Metz D, Lindquist CH, Birch LL, Fisher JO, Goran MI. Relation between mothers’ child-feeding practices and children’s
adiposity. Am J Clin Nutr 2002;75(3):581-6.
Neumark-Sztainer D, Hannan PJ, Story M, Croll J, Perry C. Family meal patterns: associations with sociodemographic characteristics
and improved dietary intake among adolescents. J Am Diet Assoc 2003;103(3):317-22.
Ayala GX, Baquero B, Arredondo EM, Campbell N, Larios S, Elder JP. Association between family variables and Mexican American
children’s dietary behaviors. J Nutr Educ Behav 2007;39(2):62-9.
Golan M, Fainaru M, Weizman A. Role of behavior modification in the treatment of childhood obesity with the parents as the
exclusive agents of change. Int J Obes 1998;22(12):1217-24.
Baranowski T, Nader PR. Family involvement in health behavior change programs. In: Turk DC, Kerns RD, editors. Health, illness,
and families. New York: John Wiley and Sons; 1985. pp. 81-107.
Lindsay AC, Sussner KM, Kim J, Gortmaker SL. The role of parents in preventing childhood obesity. Future Child 2006;16(1):16986.
Chatterjee N, Blakely DE, Barton C. Perspectives on obesity and barriers to control from workers at a community center serving lowincome Hispanic children and families. J Community Health Nurs 2005;22(1):23-36.
American Academy of Pediatrics. Prevention of pediatric overweight and obesity. Pediatrics 2003;112(2):424-30.
Sothern MS. Obesity prevention in children: physical activity and nutrition. Nutr 2004;20(7-8):704-8.
American Dietetic Association. Position of the American Dietetic Association: dietary guidance for healthy children ages 2 to 11
years. J Am Diet Assoc 2004;104(4):660-77.
Kirk S, Scott BJ, Daniels SR. Pediatric obesity epidemic: treatment options. J Am Diet Assoc 2005;105(Suppl 1):S44-51.
Gustafson SL, Rhodes RE. Parental correlates of physical activity in children and early adolescents. Sport Med 2006;36(1):79-97.
Gortmaker SL, Cheung LWY, Peterson KE, Chomitz G, Cradle JH, Dart H, et al. Impact of a school-based interdisciplinary
intervention on diet and physical activity among urban primary school children. Arch Pediatr Adolesc Med 1999;153(9):97583.
Hawley SR, Beckman H, Bishop T. Development of an obesity prevention and management program for children and adolescents in
a rural setting. J Community Health Nurs 2006;23(2):69-80.
Müller MJ, Danilezik S, Pust S. School- and family-based interventions to prevent overweight in children. Proc Nutr Soc
2005;64(2):249-54.
Peterson KE, Fox MK. Addressing the epidemic of childhood obesity through school-based interventions: what has been done and
26
where do we go from here? J Law Med Ethics 2007;35(1):113-30.
Slawta J, Bentley J, Smith J, Kelly J, Syman-Degler L. Promoting healthy lifestyles in children: a pilot program of Be A Fit Kid.
Health Promot Pract 2008;9(3):305-12.
Beech BM, Klesges RC, Kumanyika SK, Murray DM, Klesges L, McClanahan B, et al. Child- and parent-targeted interventions: the
Memphis GEMS Pilot Study. Ethn Dis 2003;13(Suppl 1):40-53.
Ford BS, McDonald TE, Owens AS, Robinson TN. Primary care interventions to reduce television viewing in African-American
children. Am J Prev Med 2002;22(2):106-9.
Golley RK, Magarey AM, Baur LA, Steinbeck KS, Daniels LA. Twelve-month effectiveness of a parent-led family-focused weightmanagement program for prepubertal children: a randomized, controlled trial. Pediatrics 2007;119(3):517-25.
Rodearmel SJ, Wyatt HR, Barry MJ, Dong F, Pan D, Israel RG, et al. A family-based approach to preventing excessive weight gain.
Obesity 2006;14(8):1392-1401.
Coleman KJ, Tiller CL, Sanchez J, Heath EM, Sy O, Milliken G, et al. Prevention of the epidemic increase in child risk of overweight
in low-income schools. Arch Pediatr Adolesc Med 2005;159(3):217-24.
Fitzgibbon ML, Stolley MR, Schiffer L, Van Horn L, Kauferchrisoffel K, Dyer A. Two-year follow-up results for Hip-Hop to Health
Jr.: a randomized controlled trial for overweight prevention in preschool minority children. J Pediatrics 2005;146(5):618-25.
Engels HJ, Gretebek RJ, Gretebek KA, Jiménez L. Promoting healthful diets and exercise: efficacy of a 12-week after-school
program in urban African Americans. J Am Diet Assoc 2005;105(3):721-8.
Borra ST, Kelly L, Shirreffs MB, Neville K, Geiger CJ. Developing health messages: qualitative studies with children, parents, and
teachers help identify communications opportunities for healthful lifestyles and the prevention of obesity. J Am Diet Assoc
2003;103(6):721-8.
Neumark-Sztainer D, Wall M, Story M, van den Berg P. Accurate parental classification of overweight adolescents’ status: does it
matter? Pediatrics 2008;121(6):e1495-e1502.
Eckstein KC, Mikhail LM, Ariza AJ, Thomson JS, Millard SC, Binns HJ, et al. Parents’ perceptions of their child’s weight and
health. Pediatrics 2006;117(3):681-90.
Contento IR, Basch C, Zybert P. Body image, weight, and food choices of Latina women and their young children. J Nutr Educ
Behav 2003;35(5):236-48.
Jain A, Sherman SN, Chamberlin LA, Carter Y, Powers SW, Whitaker RC. Why don’t low-income mothers worry about their
preschoolers being overweight? Pediatrics 2001;107(50):1138-46.
Laroche HH, Davis MM, Forman J, Palmisano G, Heisler M. What about the children? The experience of families involved in an
adult-focused diabetes intervention. Public Health Nutr 2008;11(4):427-36.
Paisley J, Beanlands H, Goldman J, Evers S, Chappell J. Dietary change: what are the responses and roles of significant others? J
Nutr Educ Behav 2008;40(2):80-8.
Roos E, Sarlio-Lähteenkorva S, Laauka T, Lahelma E. Associations of work-family conflicts with food habits and physical activity.
Public Health Nutr 2007;10(3):222-9.
........................................................................................
5 Mancino, L. Todd, J. Guthrie, J. & Lin, B. (July, 2009). How Food Away From Home
Affects Children’s Diet Quality. Paper Presented at the Agricultural & Applied
Economics Association’s AAEA & ACCI Joint Annual Meeting. Milwaukee, WI.
http://ageconsearch.umn.edu/bitstream/49251/2/Mancino,%20Todd%20&%20Lin.pdf
- MY WRITING
-This study was based on 2 days of recorded food by elementary, junior high and high
school students. Among younger children, who are more likely than older children to eat a
USDA school meal and face a more healthful school food environment, the effect of food
27
from school on caloric intake and diet quality does not differ significantly from that of food
from home.
- This only means that students who eat school meals eat healthy foods. If the parents or
guardians buy unhealthy food for children – that is what they eat.
- According to the researchers, children eat too much unhealthy, high calorie food and they
have noted a rise in consumption based on 2 days of study.
- Based on 2 days of dietary data and panel data methods, this study includes estimates of
how each child’s consumption of food away from home, food from school (which includes
all foods available for purchase at schools, not only those offered as part of USDA
reimbursable meals), and caloric sweetened beverages affects that child’s diet quality and
calorie consumption.
- Compared with meals and snacks prepared at home, food prepared away from home
increases caloric intake of children, especially older children.
-Each food-away-from-home meal adds 108 more calories to daily total intake among
children ages 13-18 than a snack or meal from home; all food from school is estimated to
add 145 more calories. Both food away from home and all food from school also lower the
daily diet quality of older children (as measured by the 2005 Healthy Eating Index).
........................................................................................
Article:
Mancino, L. Todd, J. Guthrie, J. & Lin, B. (July, 2009). How Food Away From Home Affects
Children’s Diet Quality. Paper Presented at the Agricultural & Applied Economics
Association’s AAEA & ACCI Joint Annual Meeting. Milwaukee, WI.
http://ageconsearch.umn.edu/bitstream/49251/2/Mancino,%20Todd%20&%20Lin.pdf
Abstract
28
This study confirms that eating food away from home (FAFH) adversely affects dietary
intake. By looking at changes within individuals’ dietary intake over two days, thus
controlling for self- selection issues, we find that FAFH causes increased caloric intake
and reduced diet quality. Our estimates on the effect of specific meals show that lunch and
dinner consumed away from home have the largest effect on total daily caloric intake, but
that breakfast has the largest negative effect on total diet quality. In particular, eating
breakfast away from home decreases intake of fruit, whole grains and dairy and increases
the percent of calories from saturated fats and solid fats, alcohol and added sugar. Eating
lunch and dinner away from home also reduce diet quality, affecting similar dietary
components, with dinner away from home also reducing vegetable intake. Unlike past
studies based on correlation analyses, this study shows how FAFH can have a causal
impact on weight gain.
Introduction
Despite enduring public health messages about the importance of a healthy diet and
lifestyle, most Americans continue to choose low quality diets and obesity rates continue
to rise. One oft cited reason for persistently poor diets may be that today’s food
environment offers many opportunities to select unhealthy foods. Busy schedules may
also affect the quality of the food we eat, by changing the regularity with which we eat, the
time available for meal preparation, and the consumption of foods prepared away from
home. Consumers today spend an increasing share of total food expenditures of food
away from home (FAFH). In 2007, families spent nearly 42 % of their food dollars on foods
outside the home, up from 25% in 1970 (Clauson and Leibtag, 2008).
Noting that the share of calories from FAFH increased from 18 to 32% between 1977 and
1996, Guthrie et al (2002), examined the differences in the nutritional quality of food
prepared at home (FAH) and FAFH. They found that FAFH was higher in total fat and
saturated fat and lower in dietary fiber, calcium, and iron. Others have documented that
diet quality is lower, or
1that body mass index (BMI)1 is higher, among individuals who eat FAFH as compared to
those who do not, suggesting that FAFH contributes to the obesity epidemic and
decreases diet quality (Binkley 2008, Binkley 2000; Jeffery and French 1998; Bowman et
al 2004; Bowman and Vinyard 2004; Clemens et al 1999; Paeratakul et al 2003).
However, such cross-sectional comparisons fail to account for the fact that the choice of
where to eat is not exogenously determined. Rather, this choice is based on preferences,
prices, time constraints and other factors--the same factors that affect food choices, diet
quality, and body weight. It may be that individuals who consume a high share of FAFH
also prefer lower nutritional quality foods when eating at home. Or if the time demands of
family and work raise demand for convenient foods, both at and away from home, and
also reduce time available for physical activity, then BMI levels among individuals who eat
more convenient foods would likely be higher than those who do not. Thus not accounting
for these unobservable factors will bias the estimated impact of FAFH on caloric intake
and diet-quality.
Other studies have attempted to overcome the issue of bias due to unobservables by
estimating the effect of access or proximity to restaurants. Chou et al. (2004) take an
historical approach and find the state-level growth in availability of restaurants explains the
majority of the growth in weight over time. However, the study does not account for the
fact that the growth in the number of restaurants is largely demand-driven and thus, is
most likely correlated with diet preferences and other factors affecting food choice.
Anderson and Matsa (2007) use instrumental variables and find that access to restaurants
has little to no effect on weight. However, their study is limited to rural areas in a small
number of states.
1 Body Mass Index is a measure of height (in meters) divided by weight (in kilograms),
29
squared.
2
The objective of this study is to provide more precise estimates on how food away from
home affects both caloric intake and diet quality. We overcome the selection issue by
employing a first-difference, or fixed-effects, estimator utilizing two days of dietary intake
data. We assume that individual’s preferences for diet quality are fixed over a short time –
frame within individuals, but day-to-day variation in activities and other constraints affects
consumption of FAFH. Because the two days of dietary recalls are typically collected 7 to
10 days apart, this is a reasonable assumption. This allows us to directly identify FAFH’s
daily effect on diet quality and energy consumption and thus, its potential impact on
bodyweight and obesity.
While some past studies have attempted to control for the selection issue using fixed
effects estimation (Bowman and Vinyard, 2004; Bowman et al 2004; Paeratakul et al,
2003; and Binkley, 2008), these studies limited FAFH consumption measures to either a
dichotomous or frequency measure, only considered consumption of fast food (or a
specific form of food away from home) and usually limited their sample to individuals that
consume FAFH on one, but not both days of dietary recall. We improve on past studies by
using a continuous measure of FAFH consumption, which provides an estimate of the
marginal effect of increasing consumption of FAFH and allows us to include all sample
individuals with two days of dietary recall. We also add to the literature by testing for
differences in the effect by meal occasion, across the two periods covered by our data
(1994-96 and 2003-04), as well as across various population subgroups, including gender,
weight status and whether or not an individual was dieting.
The remainder of this report is structured as follows. Section 2 presents a brief review of
previous research on the effect of FAFH on diet quality, Section 3 describes the data,
sample and variable construction, section 4 describes the first difference estimator and
section 5 presents the results. The paper concludes with a discussion of the results and
their policy implications.
References
Behrman, Jere R., and Anil B. Deolalikar. (1990). “The Intrahousehold Demand for Nutrients in Rural South India: Individual Estimates,
Fixed Effects, and Permanent Income,” The Journal of Human Resources, Vol. 25(4): 665-96.
Bleich, S.N., Y.C. Wang, Y. Wang, and S.L. Gortmaker. (2009). “Increasing Consumption of Sugar-Sweetened Beverages Among U.S.
Adults: 1988- 1994 to 1999-2004,” American Journal of Clinical Nutrition, Vol. 89(1): 372-381.
Block, Jason P., Richard A. Scribner, and Karen B. DeSalvo. (2004). “Fast Food, Race/Ethnicity, and Income: A Geographic Analysis,”
American Journal of Preventive Medicine, Vol. 27(3): 211-217.
Bowman, Shanthy A., Steven L. Gortmaker, Cara B. Ebbeling, Mark A. Pereira, and David S. Ludwig. (2004a). “Effects of Fast-Food
Consumption on Energy Intake and Diet Quality Among Children in a National Household Survey,” Pediatrics, Vol. 113(1): 112-118.
Bowman, S.A., J.E. Friday, and A. Moshfegh. (2008). MyPyramid Equivalents Database, 2.0 for USDA Survey Foods, 2003-2004, U.S.
Department of Agriculture, Agricultural Research Service, Food Surveys Research Group, www.ars.usda.gov/ba/bhnrc/fsrg/
Bowman, Shanthy A., and Bryan T. Vinyard. (2004b). “Fast Food Consumption of U.S. Adults: Impact on Energy and Nutrient Intakes
and Overweight Status,” Journal of the American College of Nutrition, Vol. 23(2): 163-168.
Briefel, Ronette, Mary Kay Crepinsek, Charlotte Cabili, Ander Wilson, and Philip Gleason. (2009). “School Food Environments and
Practices Affect Dietary Behaviors of U.S. Public School Children,” Journal of American Dietetic Association, Supplement 1, Vol.
109(2): S91-S107
Brownell, K.D., and T.R. Frieden. (2009). “Ounces of Prevention—The Public Policy Case for Taxes on Sugared Beverages, New
England Journal of Medicine, 360(18):1805-1808.
Burdette, Hillary L., and Robert C. Whitaker. (2004). “Neighborhood Playgrounds, Fast Food Restaurants and Crime: Relationships to
Overweight in Low-Income Preschool Children,” Preventive Medicine, Vol. 38: 57-63.
Carlson, Andrea, Mark Lino, WenYen Juan, Kenneth Hanson, and Peter Basiotis. (2007). Thrifty Food Plan, 2006, CNPP-19, U.S.
Department of Agriculture, Center for Nutrition Policy and Promotion.
Centers for Disease Control and Prevention (CDC), Division of Adolescent and School Health. (2007). School Health Policies and
Programs Study, 2006: Changes Between 2000 and 2006, www.cdc.gov/HealthyYouth/
shpps/2006/factsheets/pdf/FS_Trends_SHPPS2006.pdf
30
Centers for Disease Control and Prevention (CDC). (2009). Overweight and Obesity: Obesity Trends—NHANES Surveys (1976-1980
and 2003-2006), www.cdc.gov/nccdphp/dnpa/obesity/childhood/prevalence.htm
Centers for Disease Control and Prevention (CDC), Division of Nutrition and Physical Activity. (2006). Research to Practices Series No.
3: Does Drinking Beverages with Added Sugars Increase the Risk of Overweight?
www.cdc.gov/nccdphp/dnpa/nutrition/pdf/r2p_sweetend_beverages.pdf
Chaloupka, F.J., L.M. Powell, and J.F. Chriqui. (2009). Sugar-Sweetened Beverage Taxes and Public Health, Research Brief, Robert
Wood Johnson Foundation and School of Public Health, University of Minnesota, July.
Condon, Elizabeth M., Mary Kay Crepinsek, and Mary Kay Fox. (2009). “School Meals: Types of Foods Offered to and Consumed by
Children at Lunch and Breakfast,” Journal of the American Dietetic Association, Vol. 109: S67-S78.
Crepinsek, Mary Kay, Anne R. Gordon, Patricia M. McKinney, Elizabeth M. Condon, and Ander Wilson. (2009). “Meals Offered and
Served in U.S. Public Schools: Do They Meet Nutrient Standards?” Journal of the American Dietetic Association, Vol. 109: S31-S43.
Currie, Janet, Stefano DellaVigna, Enrico Moretti, and Vikram Pathania. (2009). “The Effect of Fast Food Restaurants on Obesity and
Weight Gain,” NBER Working Paper Series, Working Paper 14721, www.nber. org/papers/w14721
Ebbeling, Cara B., Kelly B. Sinclair, Mark A. Pereira, Erica Garcia-Lago, Henry A. Feldman, and David S. Ludwig. (2004).
“Compensation for Energy Intake From Fast Food Among Overweight and Lean Adolescents,” Journal of the American Medical
Association, 291(23): 2828-2833.
Finkelstein, Daniel M., Elaine L. Hill, and Robert C. Whitaker. (2008). “School Food Environments and Policies in U.S. Public
Schools,” Pediatrics, Vol. 122(1): e251-e259.
Food Research and Action Center (FRAC). (2009). School Breakfast Scorecard: School Year 2008-2009,
www.frac.org/pdf/breakfast09.pdf
Fox, Mary Kay, Anne Gordon, Renee Nogales, and Ander Wilson. (2009). “Availability and Consumption of Competitive Foods in U.S.
Public Schools,” Journal of the American Dietetic Association, Vol. 109: S57-S66.
French, S.A., M. Story, D. Neumark-Sztainer, J.A. Fulkerson, and P. Hannan. (2001). “Fast Food Restaurant Use Among Adolescents:
Associations With Nutrient Intake, Food Choices and Behavioral and Psychosocial Variables,” International Journal of Obesity, Vol. 25:
1823-1833.
Friday, J.E., and S.A. Bowman. (2006). MyPyramid Equivalents Database for USDA Survey Food Codes, 1994-2002 Version 1.0. U.S.
Department of Agriculture, Agricultural Research Service, Community Nutrition Research Group, www.ars.usda.gov/ba/bhnrc/fsrg/
Fungwe, Thomas, Patricia Guenther, Wen Yen Juan, Hazel Hiza, and Mark Lino. (2009). The Quality of Children’s Diets in 2003-2004
as Measured by the Healthy Eating Index-2005, Nutrition Insight 43, U.S. Department of Agriculture, Center for Nutrition Policy and
Promotion.
Gable, Sara, Jo Britt-Rankin, and Jennifer L. Krull. (2008). Ecological Predictors and Developmental Outcomes of Persistent Childhood
Overweight, Contractor and Cooperator Report No. 42, U.S. Department of Agriculture, Economic Research Service.
Gillis, Linda J., and Oded Bar-Or. (2003). “Food Away from Home, Sugar- Sweetened Drink Consumption and Juvenile Obesity,”
Journal of the American College of Nutrition, Vol. 22(6): 539-545.
Gordon, A., Mary Kay Fox, Melissa Clark, Rénee Nogales, Elizabeth Condon, Philip Gleason, and Ankur Sarin. (2007). School Nutrition
Dietary Assessment Study-III: Vol. II: Student Participation and Dietary Intakes, U.S. Department of Agriculture, Food and Nutrition
Service, Office of Research, Nutrition and Analysis.
Guenther, Patricia M., Jill Reedy, and Susan M. Krebs-Smith. (2008). “Development and Evaluation of the Healthy Eating Index-2005,”
Journal of the American Dietetic Association, Vol. 108(11): 1896-1901.
Guenther, Patricia, Wen Yen Juan, Mark Lino, Hazel Hiza, Thomas Fungwe, and Richard Lucas. (2009). Diet Quality of Low-Income
and Higher Income Americans in 2003-2004 as Measured by the Healthy Eating Index-2005, Nutrition Insight 42, U.S. Department of
Agriculture, Center for Nutrition Policy and Promotion.
Guthrie, Joanne F., Biing-Hwan Lin, and Elizabeth Frazao. (2002). “Role of Food Prepared Away from Home in the American Diet,
1977-78 Versus 1994-96: Changes and Consequences,” Journal of Nutrition Education and Behavior, Vol. 34(3): 140-150.
Hersch, Joni, and Leslie S. Stratton. (1997).“Housework, Fixed Effects, and Wages of Married Workers,” The Journal of Human
Resources 32(2): 285-307.
Institute of Medicine, Committee on Nutrition Standards for National School Lunch and Breakfast Programs (IOM). (2009). School
Meals: Building Blocks for Healthy Children, Washington, DC: National Academies Press.
Institute of Medicine, Committee on Prevention of Obesity in Children and Youth (IOM). (2005). Preventing Childhood Obesity: Health
in the Balance, J.P. Koplan, C.T. Liverman, and V.I. Kraak (eds.). Washington, DC: National Academies Press.
Kelder, S.H., C.L. Perry, K.I. Klepp, and L.L. Lytle. (1994). “Longitudinal Tracking of Adolescent Smoking, Physical Activity, and
Food Choice Behaviors,” American Journal of Public Health, Vol. 84(7): 1121-1126.
Lin, Biing-Hwan, Joanne Guthrie, and Elizabeth Frazao. (2001). “American Children’s Diets Not Making the Grade,” FoodReview, Vol.
24 (2):8-17.
Ludwig David, K. Peterson, and S. Gortmaker. (2001). “Relation Between Consumption of Sugar-Sweetened Drinks and Childhood
Obesity: A Prospective, Observational Analysis,” The Lancet, Vol. 357(9255): 505-508.
Malik, V.S., M.B. Schulze, and F.B. Hu. (2006). “Intake of Sugar-Sweetened Beverages and Weight Gain: A Systematic Review,”
American Journal of Clinical Nutrition, Vol. 84(2): 274-288.
Mancino, Lisa, Jessica Todd, and Biing-Hwan Lin. (2009). “Separating What We Eat From Where: Measuring the Effect of Food Away
From Home on Diet Quality,” Food Policy, Vol. 34 (6): 557-562.
Mattes, Richard D. (1996). “Dietary Compensation by Humans for Supplemental Energy Provided as Ethanol or Carbohydrate in
Fluids,” Physiology and Behavior, Vol. 59: 179-187.
Newman, Constance, Joanne Guthrie, Lisa Mancino, Katherine Ralston, and Melissa Musiker. (2009). Meeting Total Fat Requirements
for School Lunches: Influence of School Policies and Characteristics, Economic Research Report No. 87, U.S. Department of
31
Agriculture, Economic Research Service, www.ers.usda.gov/publications/err87/
Paeratakul, S., D. Ferdinand, C. Champagne, D. Ryan, and G. Bray. (2003). “Fast-Food Consumption Among U.S. Adults and Children:
Dietary and Nutrient Intake Profile,” Journal of the American Dietetic Association, Vol. 103(10): 1332-1338.
Powell, Lisa M., and Yanjun Bao. (2009). “Food Prices, Access to Food Outlets, and Child Weight,” Economics and Human Biology,
Vol. 7: 64-72.
Ralston, Katherine, Constance Newman, Annette Clauson, Joanne Guthrie, and Jean Buzby. (2008). The National School Lunch
Program: Background, Trends, and Issues, Economic Research Report No. 61, U.S. Department of Agriculture, Economic Research
Service, www.ers.usda. gov/publications/err61/
Rosenheck, R. (2008). “Fast Food Consumption and Increased Caloric Intake: A Systematic Review of a Trajectory Towards Weight
Gain and Obesity Risk,” Obesity Reviews, Vol. 9: 535-547.
Sebastian, Rhonda, Cecilia Wilkinson Enns, and Josephs D. Goldman. (2009). “U.S. Adolescents and MyPyramid: Associations Between
Fast-Food Consumption and Lower Likelihood of Meeting Recommendations,” Journal of the American Dietetic Association, Vol. 109:
226-235.
Stang J., and M. Story (eds.). (2005). Guidelines for Adolescent Nutrition Services, University of Minnesota, School of Public Health,
Division of Epidemiology and Community Health, Center for Leadership, Education and Training in Maternal and Child Nutrition.
Sturm, R., and A. Datar. (2005). “Body Mass Index in Elementary School Children, Metropolitan Area Food Prices and Food Outlet
Density,” Journal of the Royal Institute of Public Health, Vol. 119: 1059-1068.
Todd, Jessica, Lisa Mancino, and Biing-Hwan Lin. (2010). The Impact of Food Away From Home on Adult Diet Quality, Economic
Research Report No. 90, U.S. Department of Agriculture, Economic Research Service, February, www.ers.usda.gov/publications/err90/
Trust for America’s Health. (2009). Supplement to “F as in Fat: How Obesity Policies Are Failing in America, 2009”: Obesity-Related
Legislation Action in States, Update, http://healthyamericans.org/reports/obesity2009/ StateSupplement2009.pdf
U.S. Department of Agriculture, Office of Communications. (2009). USDA- Commissioned Report from Institute of Medicine (IOM) of
the National Academies Highlights Ways To Improve National School Lunch and Breakfast Programs, Office of Communications
Release No. 0516.09.
U.S. Department of Health and Human Services (USDHHS). (2000). Healthy People 2010: Leading Health Indicators,
www.healthypeople.gov/ Document/html/uih/uih_4.htm
U.S. Department of Health and Human Services. (2007). “The Surgeon General’s Call to Action to Prevent and Decrease Overweight
and Obesity,” www.surgeongeneral.gov/topics/obesity/calltoaction/fact_ adolescents.htm
U.S. Department of Health and Human Services and U.S. Department of Agriculture (USDHHS/USDA). Dietary Guidelines for
Americans, 2005, www.health.gov/dietaryguidelines/dga2005/document/pdf/DGA2005.pdf.
Vartanian, L.R., M.B. Schwartz, and K.D. Brownell. (2007). “Effects of Soft Drink Consumption on Nutrition and Health: A Systematic
Review and Meta-Analysis,” American Journal of Public Health, 97(4): 667-675.
Wang, Y. Claire, Sara N. Bleich, and Steven L. Gortmaker. (2008). “Increasing Caloric Contribution From Sugar-Sweetened Beverages
and 100% Fruit Juices Among U.S. Children and Adolescents, 1988-2004,” Pediatrics, Vol. 121 (June): e1604 -e1614.
........................................................................................
6. Graser, S. Sampson, B. Pennington, T. Prusak, K. (2011). Children's Perceptions of
Fitness Self-Testing, the Purpose of Fitness Testing, and Personal Health. Physical
Educator. v68 n4 p175-187
-MY WRITING
-In gym class it is important to encourage students' to self-test, in other words, take care of
their own physical fitness. This article is inspiring for me. My overall plan – Fit for Lifecan begin right in the classroom, and students can inspire and help each other do the
exercises.
32
-The students did self-testing and were told the purpose of the research.
-The researchers used FITNESSGRAM. FITNESSGRAM is
http://www.fitnessgram.net/overview/
-The students were given questionnaires and interviews on an ongoing basis. This is
another important element I will add to my class – continuous evaluation by the students of
their own progress will enable me to create a positive inter-active atmosphere. I do not
want my students to feel oppressed or nervous that they can’t do an activity perfectly.
- I want each one to judge him or her self by comparing their own progress. (Findings
revealed that children enjoyed a self-testing format, understood the purpose of fitness selftesting, and connected their FITNESSGRAM results to their overall health lending support
to the use of a fitness self-testing approach in PE.)
-FITNESSGRAM was developed by the Cooper Institutes (Meredith & Welk, 2004).
Unlike norm-referenced fitness tests, FITNESSGRAM is a criterion-referenced test battery
that relates performance outcomes to indicators associated with one's health.
-This might be ideal for my “Fit for Life” curriculum plan. I would hope my supervisor
would allow me to make any changes in the FITNESSGRAM for research purposes.
- The researcher emphasized that there are two important reasons why students do not like
fitness testing; one is when students have to reach to a standard level – regardless of how
physically fit they were when at the beginning of the term. The second is that they dislike a
public display of their abilities or inabilities. In my class, I will not compare students
against each other or against a norm. The research tells me that only 15% of children ever
reach the norm. I will compare them to their own progress. I will not make an issue of their
performance in front of other students. Everyone will be evaluated without any public
33
announcements of their abilities. I expect to take on the role of cheerleader/coach –
encouraging and supportive toward all my students.
........................................................................................
Article:
Graser, S. Sampson, B. Pennington, T. Prusak, K. (2011). Children's Perceptions of
Fitness Self-Testing, the Purpose of Fitness Testing, and Personal Health.
Physical Educator. v68 n4 p175-187
Flohr and Williams (1997) emphasized the importance of assessing students' attitudes
about fitness testing as it contributes to effective, positive, and motivating physical
education (PE) classes. The purpose of this qualitative study was to identify fifth and sixth
graders' perceptions of fitness testing using FITNESSGRAM in a self-testing format.
Specifically, this study evaluated (a) children's perceptions of FITNESSGRAM,
administered in a self-testing format, (b) children's understanding of the purpose of fitness
self-testing, and (c) the effects of participation in FITNESSGRAM self-testing on children s
perceptions of personal health. This study used questionnaires (n = 78) and follow-up
interviews (n = 45) to identify children's perceptions of their experience. Using inductive
content analysis (Lincoln & Guba, 1985) of student perceptions, three main categories
emerged: (a) self-testing procedures, (b) cognitive understanding, and (c) overall influence
of fitness testing. Findings revealed that children enjoyed a self-testing format, understood
the purpose of fitness self-testing, and connected their FITNESSGRAM results to their
overall health lending support to the use of a fitness self-testing approach in PE.
Schools, teachers, and students are in an era of outcomes-based education, physical
educators included. For example, states such as California, South Carolina, and Texas
(National Association of Sport and Physical Education & American Heart Association,
2010) mandate annual fitness testing in physical education (PE) classes for the purpose of
providing evidence that PE works--that kids are getting more fit. While fitness testing has a
long history in PE, unfortunately, it tends to also have a bad reputation with teachers and
students alike. Yet, because fitness indicators are closely related to health indicators, the
goals of identifying fitness levels of children are still important. Thus Pate's (1991) queries
about fitness testing have provided valuable guidance for researchers in their examination
of all things in relation to fitness testing in the PE setting. Said Pate,
It would be desirable to know how children respond to participation in these [physical
fitness] tests. Do fitness tests enhance or decrease youngsters' motivation to exercise?
Are tests viewed as fun? Do tests have differential effects on different types of children?
Though relevant from a strict measurement perspective, these issues may determine
appropriateness of fitness testing in the school setting (p. 233).
34
Despite Pate's recommendations some 20 years ago, only limited research has attempted
to answer some of these questions and generally shows that youth (a) do not like fitness
testing because it doesn't seem important to them, (b) don't enjoy the way it is
administered, and (c) it is not fun (Flohr & Williams, 1997; Fox & Biddle, 1988; Keating,
Silverman, & Kulinna, 2002).
Some of the dislike of fitness testing has come from using (a) norm-referenced standards
to assess youth and (b) a format that makes a public display of student abilities or
inabilities. Norm-referenced standards compare a student's scores to a percentile
standard that ranks them among their nationwide peers. This type of standard has given
students an idea of how they fare against their peers but tells them nothing of how their
level of fitness affects their overall health. This type of fitness testing is essentially a
nationwide competition and not a fitness assessment that informs children and youth
about personal fitness and health status. Additionally, norm-referenced standards have
produced a very high failure rate given that only the top 15% of students are considered fit.
The rest often walk away from the experience feeling as though they have failed (Ernst,
Corbin, Beighle, & Pangrazi, 2006). This type of fitness testing experience (normreferenced standards and public display) contributes to youth disliking fitness testing.
Recognizing the need for an approach to fitness testing that would be informative and
instructive to participants, FITNESSGRAM was developed by the Cooper Institutes
(Meredith & Welk, 2004). Unlike norm-referenced fitness tests, FITNESSGRAM is a
criterion-referenced test battery that relates performance outcomes to indicators
associated with one's health. Health-referenced fitness standards allow youth to compare
their performance to criteria that inform them of their personal health status instead of
being compared to their peers. FITNESSGRAM enables students to see if they are within
the Healthy Fitness Zone (HFZ; Meredith & Welk, 2004) in the five components of healthrelated fitness (aerobic capacity, muscular strength, muscular endurance, flexibility, and
body composition). For those students in the HFZ, the instructor helps them develop a
maintenance program and for those with fitness deficiencies, a plan for improvement.
Flohr and Williams (1997) emphasized the importance of assessing students' attitudes
about fitness testing in order to better create an effective, positive, and motivating PE
experience. Since it is unlikely that students benefit from a fitness testing experience that
they dislike, efforts to create a positive fitness testing experience may be critical to
students gaining associated learning outcomes. A positive and educationally informative
fitness testing experience might be described as one where students (a) feel they are in a
safe environment for testing, (b) understand the purpose of the fitness testing, (c) make
connections between their own healthy-fitness levels and their physical activity behaviors,
and (d) conclude the experience feeling positively about fitness testing. Therefore, in an
effort to create a more positive fitness testing experience the present researchers created
and administered FITNESSGRAM in a self-testing format to fifth and sixth grade PE
students. According to Welk & Meredith (2008), the primary purpose of FITNESSGRAM is
that students become self-sufficient with respect to personal fitness, able to test and then
interpret their own results. Pangrazi (2001), and Corbin, Pangrazi, and Welk (1995) favor a
self-testing approach because it focuses on the process of the test, is student-centered,
and focuses less attention on performance scores (i.e., as compared to peers). Fox and
Biddle (1986) and Welk and Meredith (2008) argue that the life-long value of fitness testing
is realized when individuals learn to engage in the process of testing, interpreting, and
making lifestyle decisions and interventions far outweighs their performance scores.
35
Therefore the purpose of this study was to examine (a) children's perceptions of
FITNESSGRAM, administered in a self-testing format (b) children's understanding of the
purpose of fitness self-testing, and (c) the effects of participation in FITNESSGRAM selftesting on children's perceptions of personal health.
References
Adler, P. A., & Adler, P. (1994). Observational techniques. In N. Denzin & Y. Lincoln,
(Eds.), Handbook of qualitative research. Thousand Oaks, CA: Sage.
Bogdan, R. C., & Biklen, S. K. (1998). Qualitative research of education: An introduction
to theory and methods (3rd Ed.). Boston, MA: Allyn & Bacon.
Corbin, C. B., Pangrazi, R. P., & Welk, G. J. (1995). A response to "The horse is dead;
let's dismount." Pediatric Exercise Science, 7, 347-351.
Ernst, M. P., Corbin, C. B., Beighle, A., & Pangrazi, R. P. (2006). Appropriate and
inappropriate uses of FITNESSGRAM: A commentary. Journal of Physical Activity & Health,
3(Suppl. 2), S90-S100.
Flohr, J. A., & Williams, J. A. (1997). Rural fourth graders' perceptions of physical
fitness and fitness testing. Health Source, 54, 78-87.
Fox, K. R., & Biddle, S.J.(l986).Health-related fitness testing in schools: Introduction
and problems of interpretation. Bulletin of Physical Education, 22(3), 54-64.
Fox, K. R., & Biddle. S. J. (1988). The use of fitness tests: Educational and psychological
considerations. Journal of Physical Education, Recreation & Dance, 59(2), 47-53.
Gerdes, D. A., & Conn, J. H. (2001). A user-friendly look at qualitative research methods.
The Physical Educator, 58 (4), 183-190.
Hanson, T., & Newburg, D. (1992). Naturalistic inquiry as a paradigm for doing applied
performance research. A Journal of Qualitative Inquiry, 1, 26-48.
Hopple, C, & Graham. G. (1995). What children think, feel, and know about physical fitness
testing. Journal of Teaching in Physical Education, 14, 408-417.
Keating, X. D. (2003). The current often implemented fitness tests in physical education
programs: Problems and future directions. Quest, 55, 141-160.
Keating, X. D., Silverman, S., & Kulinna, P. H. (2002). Preservice physical education
teacher attitudes toward fitness tests and the factors influencing their attitudes. Journal
of Teaching in Physical Education, 21, 193-207.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park: Sage, 339-344.
Meredeth, M.D. & Welk, G.J. (Eds.). (2004). FITNESSGRAM ACTIVITYGRAM Test administration
manual (3rd ed.) Human Kinetics, Champaign, II.
National Association for Sport and Physical Education & American Heart Association. (2010).
2010 Shape of the nation report: Status of physical education in the USA. Reston, VA:
National Association for Sport and Physical Education.
Pangrazi, R. P. (2001). Dynamic physical education for elementary school children. Boston:
Allyn and Bacon.
Pate, R. (1991). Health-related measures of children's physical fitness. Journal of School
Health, 61, 231-233.
36
Welch, E. (2007). Physical fitness assessment: Is there a better way? Unpublished master's
thesis, Brigham Young University, Provo, UT.
Welk, G. J., & Meredith, M.D. (Eds.). (2008). FITNESSGRAM/ACTIVITYGRAM Reference Guide.
Dallas, TX: The Cooper Institute.
.
http://ehis.ebscohost.com.ez-proxy.brooklyn.cuny.edu:2048/ehost/detail?sid=714f9e485c99-4f92-b4d4c0e7fb7a0046%40sessionmgr14&vid=2&hid=4&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d
%3d#db=a9h&AN=72260562&anchor=AN0072260562-9
........................................................................................
7. Milei, J., Losada, M., Llambí, H., Grana, D., Suárez, D., Azzato, F., & Ambrosio, G.
(2011). Chronic cola drinking induces metabolic and cardiac alterations in rats. US
National Library of Medicine National Institutes of Health World Journal of
Cardiology, 3(4), 111-116. 10.4330/wjc.v3.i4.111
-MY WRITING
-This study was done on 48 rats because their metabolic systems react in similar ways as
humans
-1/3 were allowed to drink soda (diet and regular) and water – and killed after 6 months to
study effects on their organs.
_Other 1/3 allowed soda and water for 6 months –and given water for 6 more months –
then killed to study effects on their organs.
- -Metabolic syndrome is defined as a variety of diseases. This syndrome consists of; type 2
diabetes, cardiovascular disease, stroke and premature death. Soft drinks are the leading
source of added sugar worldwide, and their consumption in this study, and others, has been
linked to obesity, diabetes, and metabolic syndrome.
Skip to main content
- - A recent survey on the dietary habits and nutritional status of 4 to 18 years olds in Great
Britain showed that on average 56% of total fluid intake was in the form of soft drinks.
Skip to navigation
-Body weight gain, hypertension, decreased food intake, hyperglycemia,
hypertriglyceridemia, and a tendency to hypercholesterolemia were found after chronic
37
consumption of regular (sucrose-sweetened) cola beverage in rats[6].
-This means that when children in England drank soda, they did not eat healthier food or
drink enough water– and they had a tendency to become ill.
- The researchers are aware that soft drinks are compound substances, making difficult to
single out the ingredients that are detrimental and beninge. However, they note the statistic
that that soft drink consumption has increased by 300% in the past 20 years, and 56%-85%
of children in school consume at least one soft drink daily. The aim of the study was to
study the effect of chronic cola beverage drinking. Using rats as a mammalian base they
concluded that serious health problems occur when children have a high consumption of
soft drinks.
........................................................................................
Article:
Milei, J., Losada, M., Llambí, H., Grana, D., Suárez, D., Azzato, F., & Ambrosio, G. (2011).
Chronic cola drinking induces metabolic and cardiac alterations in rats. US
National Library of Medicine National Institutes of Health World Journal of
Cardiology, 3(4), 111-116. 10.4330/wjc.v3.i4.111
Abstract
AIM: To investigate the effects of chronic drinking of cola beverages on metabolic and
echocardiographic parameters in rats.
METHODS: Forty-eight male Wistar rats were divided in 3 groups and allowed to drink
regular cola (C), diet cola (L), or tap water (W) ad libitum during 6 mo. After this period,
50% of the animals in each group were euthanized. The remaining rats drank tap water ad
libitum for an additional 6 mo and were then sacrificed. Rat weight, food, and beverage
consumption were measured regularly. Biochemical, echocardiographic and systolic blood
pressure data were obtained at baseline, and at 6 mo (treatment) and 12 mo (washout). A
complete histopathology study was performed after sacrifice.
RESULTS: After 6 mo, C rats had increased body weight (+7%, P < 0.01), increased liquid
consumption (+69%, P < 0.001), and decreased food intake (-31%, P < 0.001). C rats
showed mild hyperglycemia and hypertriglyceridemia. Normoglycemia (+69%, P < 0.01)
and sustained hypertriglyceridemia (+69%, P < 0.01) were observed in C after washout.
Both cola beverages induced an increase in left ventricular diastolic diameter (C: +9%, L:
+7%, P < 0.05 vs W) and volumes (diastolic C: +26%, L: +22%, P < 0.01 vs W; systolic C:
+24%, L: +24%, P < 0.05 vs W) and reduction of relative posterior wall thickness (C: -8%,
L: -10%, P < 0.05 vs W). Cardiac output tended to increase (C: +25%, P < 0.05 vs W; L:
+17%, not significant vs W). Heart rate was not affected. Pathology findings were scarce,
related to aging rather than treatment.
CONCLUSION: This experimental model may prove useful to investigate the
consequences of high consumption of soft drinks.
Keywords: Cola beverages, Echocardiography, Metabolic syndrome, Soft drinks
Go to:
38
INTRODUCTION
Metabolic syndrome has been linked to an increased risk of type 2 diabetes,
cardiovascular disease, stroke and premature death[1]. Soft drinks are the leading source
of added sugar worldwide, and their consumption has been linked to obesity, diabetes,
and metabolic syndrome[2-4]. Epidemiological and experimental evidence indicate that a
greater consumption of sweet carbonated beverages is associated with overweight and
obesity by virtue of the high sugar content, low satiety, and incomplete compensation for
total energy in subsequent meals[5]. The health impact of soft drink consumption is
becoming alarming, particularly among adolescents. A recent survey on the dietary habits
and nutritional status of 4 to 18 years olds in Great Britain showed that on average 56% of
total fluid intake was in the form of soft drinks[2].
Recently, we have demonstrated that most features of metabolic syndrome can be
replicated in an experimental model of soft drink consumption. Body weight gain,
hypertension, decreased food intake, hyperglycemia, hypertriglyceridemia, and a tendency
to hypercholesterolemia were found after chronic consumption of regular (sucrosesweetened) cola beverage in rats[6].
As a logical extension to that earlier report, the present paper aimed to investigate
possible biochemical, echocardiographic and pathological alterations associated with
chronic consumption of cola beverage in rats. This experimental model has the advantage
of being able to dissect out potentially confounding factors usually associated with soft
drinks consumption in human subjects, such as increased smoking, increased junk food
consumption, and sedentary lifestyle, which might all indirectly contribute to development
of metabolic syndrome. Furthermore, compared with previous animal models of metabolic
syndrome[7], this approach has the potential advantage that it lends itself well to a direct
comparison with the situation commonly found in real life.
References
1. Harrington S. The role of sugar-sweetened beverage consumption in adolescent obesity: a review of the literature. J Sch Nurs.
2008;24:3–12. [PubMed]
2. He FJ, Marrero NM, MacGregor GA. Salt intake is related to soft drink consumption in children and adolescents: a link to obesity?
Hypertension. 2008;51:629–634. [PubMed]
3. Dhingra R, Sullivan L, Jacques PF, Wang TJ, Fox CS, Meigs JB, D'Agostino RB, Gaziano JM, Vasan RS. Soft drink consumption and
risk of developing cardiometabolic risk factors and the metabolic syndrome in middle-aged adults in the community. Circulation.
2007;116:480–488. [PubMed]
4. Nseir W, Nassar F, Assy N. Soft drinks consumption and nonalcoholic fatty liver disease. World J Gastroenterol. 2010;16:2579–2588.
[PMC free article] [PubMed]
5. Malik VS, Schulze MB, Hu FB. Intake of sugar-sweetened beverages and weight gain: a systematic review. Am J Clin Nutr.
2006;84:274–288. [PMC free article] [PubMed]
6. Otero-Losada ME, Grana DR, Müller A, Ottaviano G, Ambrosio G, Milei J. Lipid profile and plasma antioxidant status in sweet
carbonated beverage-induced metabolic syndrome in rat. Int J Cardiol. 2011;146:106–109. [PubMed]
7. Oron-Herman M, Kamari Y, Grossman E, Yeger G, Peleg E, Shabtay Z, Shamiss A, Sharabi Y. Metabolic syndrome: comparison of
the two commonly used animal models. Am J Hypertens. 2008;21:1018–1022. [PubMed]
8. Canadian Council on Animal Care 2nd Edition. Guide to the Care and Use of Experimental Animals. 2 vols. (Ottawa, Ontario:
CCAC); 1993. Available from: http://psych.utoronto.ca/users/shannonian/Psych%20369%20Readings/ccacguide.pdf.
9. Kaplan A. Biochemical studies. In: Kaplan A, Jack R, Opheim KE, Toivola B, Lyon AW, et al., editors. Clinical chemistry:
Interpretation and techniques. 4th ed. Philadelphia: Williams and Wilkins; 1995. pp. 220–250.
10. Devereux RB, Reichek N. Echocardiographic determination of left ventricular mass in man. Anatomic validation of the method.
Circulation. 1977;55:613–618. [PubMed]
11. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, Ferrell LD, Liu YC, Torbenson MS, Unalp-Arida A,
Yeh M, McCullough AJ, Sanyal AJ; Nonalcoholic Steatohepatitis Clinical Research Network. Design and validation of a histological
scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41:1313–1321. [PubMed]
12. Mattes RD, Popkin BM. Nonnutritive sweetener consumption in humans: effects on appetite and food intake and their putative
mechanisms. Am J Clin Nutr. 2009;89:1–14. [PMC free article] [PubMed]
13. Miles MV, Morrison JA, Horn PS, Tang PH, Pesce AJ. Coenzyme Q10 changes are associated with metabolic syndrome. Clin Chim
Acta. 2004;344:173–179. [PubMed]
39
14. Ferrara N, Abete P, Ambrosio G, Landino P, Caccese P, Cirillo P, Oradei A, Littarru GP, Chiariello M, Rengo F. Protective role of
chronic ubiquinone administration on acute cardiac oxidative stress. J Pharmacol Exp Ther. 1995;274:858–865. [PubMed]
15. Lass A, Forster MJ, Sohal RS. Effects of coenzyme Q10 and alpha-tocopherol administration on their tissue levels in the mouse:
elevation of mitochondrial alpha-tocopherol by coenzyme Q10. Free Radic Biol Med. 1999;26:1375–1382. [PubMed]
16. Colquhoun DM, Jackson R, Walters M, Hicks BJ, Goldsmith J, Young P, Strakosch C, Kostner KM. Effects of simvastatin on blood
lipids, vitamin E, coenzyme Q10 levels and left ventricular function in humans. Eur J Clin Invest. 2005;35:251–258. [PubMed]
17. Wilson JF, Nugent NR, Baltes JE, Tokunaga S, Canic T, Young BW, Bellinger ER, Delac DT, Golston GA, Hendershot DM. Effects
of low doses of caffeine on aggressive behavior of male rats. Psychol Rep. 2000;86:941–946. [PubMed]
......................................................................................
8. Glazebrook, C., Batty, M., Mullan, N., MacDonald, I., Nathan, D., Sayal, K., Smyth,
A., Yang, M., Boliang, G. & Hollis, C. (2011). Evaluating the effectiveness of a
schools-based programme to promote exercise self-efficacy in children and young
people with risk factors for obesity: Steps to active kids (stak). BioMedCentral
Public Health , 11(830), doi: 10.1186/1471-2458-11-830
- MY WRITING
- This study aims to evaluate the efficacy and feasibility of a schools-based activity
programme suitable for unhealthy children.
-
Targeted group is 325 emotionally insecure or children who are below average in PE
due to asthma or overweight, students aged 9 -11. They will be chosen from schools
in one British neighborhood.
-
-low self esteemed has been redefined as “low self-efficacy”. In this study it applies to
low self efficacy in sports. In the Fruit Veggie study it referred to students who have
do not feel self empowered to eat fruit or veggies.
-
Parents are asked to volunteer their children for the program.
-
The first step is to give students an activity diary and ask them to keep track of the
times they walk anywhere, play in a park, bike etc. The are encouraged to exercise one
hour a day. They are given a ten minute video entitled “Street Dance” and asked to
practice it at home.
-
Step 2 is held in school. They are taught 12 two minute activities – games, throw and
catch a ball with a group opr partner, skipping rope, stepping, trampette technique etc.
circuit training on a few machines. All designed to increase their self esteem or self-
40
efficacy. The classes last for 10 weeks.
-Step 3 Children who are successful (over the 91%) in the class move to step 3. The
children complete two ten-minute sessions with a researcher trained in motivational
interview techniques. In the first session, agreed goals will be set. They are to be reviewed
7 days later during the second session. Progress of these goals will be reviewed during the
4 month follow up.
-If the program is successful, it will be distributed to elementary schools throughout
England.
........................................................................................
Article:
Glazebrook, C., Batty, M., Mullan, N., MacDonald, I., Nathan, D., Sayal, K., Smyth, A.,
Yang, M., Boliang, G. & Hollis, C. (2011). Evaluating the effectiveness of a
schools-based programme to promote exercise self-efficacy in children and young
people with risk factors for obesity: Steps to active kids (stak). BioMedCentral
Public Health , 11(830), doi: 10.1186/1471-2458-11-830
Abstract
Background
Low levels of physical activity in children have been linked
to an increased risk of obesity, but many children lack
confidence in relation to exercise (exercise self-efficacy).
Factors which can impact on confidence include a chronic
health condition such as asthma, poor motor skills and being
overweight. Increasing levels of physical activity have
obvious benefits for children with asthma and children who
are overweight, but few activity interventions with children
specifically target children with low exercise self-efficacy
(ESE). This study aims to evaluate the efficacy and
feasibility of a schools-based activity programme suitable
for children with risk factors for adult obesity, including
asthma, overweight and low exercise self-efficacy.
Methods/Design
A clustered (at the level of school) RCT will be used to
compare a targeted, 10 week, stepped activity programme
(activity diary, dance DVD, circuit-training and motivational
interviewing) designed to promote ESE. We will recruit 20
41
primary schools to participate in the intervention and 9-11
year old children will be screened for low levels of ESE,
asthma and overweight. In order to provide sufficient power
to detect a difference in primary outcomes (Body Mass IndexBMI & ESE at 12 month follow-up) between children in the
intervention schools and control schools, the target sample
size is 396. Assessments of BMI, ESE, waist circumference,
peak flow, activity levels and emotional and behavioural
difficulties will be made at baseline, 4 months and 12 month
follow-up.
Discussion
We aim to increase ESE and levels of physical activity in
children with risk factors for adult obesity. The outcomes of
this study will inform policy makers about the feasibility,
acceptability and effectiveness of delivering targeted health
interventions within a school setting.
Trial Registration
ISRCTN Register no. ISRCTN12650001
Go to:
Background
The increasing prevalence of children and young people
classified as overweight or obese presents a significant
challenge to public health authorities. Obesity is often
chronic and is associated with increased morbidity, including
heart disease and diabetes [1]. Around 10% of the world's
school children are estimated to be overweight, with higher
rates still in countries with well-developed economies [2].
The national child measurement programme in England (2009/10)
found that a third of children in year 6 (age 10 to 11 years)
are currently overweight or obese. The risk of obesity
increases through childhood with 19% of 10 to 11 year olds
above the 95th centile of the 1990 weight charts, compared to
10% in reception classes. The global and national trend of
increasing rates of obesity is mirrored here in the East
Midlands. Children aged 10-11 years have higher levels of
obesity compared to the national average, particularly in
girls [3]. Health status is a key factor in determining
exercise behaviour. In the East Midlands, only 9% of those
with a limiting, longstanding illness reported taking regular
exercise compared to 23% of those without longstanding health
problems [4]. Other evidence suggests that chronic health
conditions act as a barrier to exercise and are a risk factor
for obesity in children and young people [5].
42
The UK has one of the highest rates of childhood asthma in
Europe and the ISAAC study [6] found nearly 1 in 5 12-14 year
olds reported treatment for asthma in the previous year.
Poorly controlled asthma in childhood is associated with
significant psychological and social burden. Data from a
national survey of mental health in 10,438 children aged 5-15
years showed that children with asthma and in poor health
were 3.5 times more likely to receive a diagnosis of
depression or anxiety than children without health problems
[7]. The relationship between asthma and mental health may be
mediated by the impact of the condition on schooling and
recent research has found that children with asthma are more
likely to have missed school in the previous year than their
peers [8]. Children with asthma were found to have specific
social difficulties and were more likely to report not having
a group of friends to socialise with and unhappiness at
school. Increasing physical activity may have particular
benefits for children with health problems such as asthma,
since increased levels of physical activity are associated
with better mental and physical health [9]. Furthermore,
children with asthma who were more active were found to have
fewer emotional and behavioural difficulties [10].
Children attending paediatric clinics for the treatment of
asthma were found to be less active than children attending
other paediatric clinics, with both parents and children
typically perceiving asthma as a significant barrier to
activity. The same study found that children with asthma were
also more likely to be overweight, with 21% being classified
as obese [10]. This represents a significant co-morbidity, as
overweight children are less likely to experience remission
of asthma symptoms in adolescence [11]. In obese adults with
asthma, weight is strongly associated with severity of
symptoms, and a large US study of children aged 4 to 9 years
with asthma found that obese children had more emergency room
visits than their normal weight counterparts [12]. Even
modest weight reductions are associated with improved lung
function [13]. Increasing physical activity can also have
direct benefits for children with asthma by improving lung
function and reducing the symptoms of exercise induced wheeze
[14].
One mechanism by which asthma and other chronic health
conditions such as obesity reduce activity levels is through
their impact on children's confidence in relation to
exercise, or exercise self-efficacy (ESE). For example,
children who performed poorest on a shuttle run task were
those who were both overweight and had low exercise self-
43
efficacy. Exercise self-efficacy (ESE) has been shown to
increase following successful completion of a physical
exercise challenge [15], suggesting that exercise selfefficacy may improve following positive experiences of
physical activity. This is important since exercise selfefficacy is strongly predictive of future levels of physical
activity [16]. Exercise self-efficacy is also a predictor of
perceptions of exercise, independent of the actual nature of
the exercise itself. For example, in a sample of girls aged 8
to 15 years, those with lower exercise self-efficacy rated a
cycling task as harder regardless of their actual energy
expenditure [15]. The aim of present study is to evaluate
whether a targeted intervention to promote exercise selfefficacy in children with risk factors for adult obesity can
be successfully implemented in primary schools and can
improve ESE, BMI, mental health and lung function in
children.
Go to:
Go to:
References
Barlow SE, Dietz WH. Obesity Evaluation and Treatment: Expert Committee Recommendations. Pediatrics. 1998;102(3):e29. doi:
10.1542/peds.102.3.e29. [PubMed] [Cross Ref]
Lobstein T, Baur L, Uauy R. Obesity in children and young people: a crisis in public health. Obesity Reveiws. 2004;5(Supplement
1):4–85.
National Centre for Social Research DoEaPH. Health Survey for England 2003. 2004. p. 25.
Active people survey 2005-2006.
http://www.sportengland.org/research/active_people_survey/active_people_survey_1/regional_results.aspx Accessed 25th
October 2011.
Gannotti M, Veneri D, Roberts D. Weight Status and Physical Activity in Third Graders with Chronic Health Conditions. Pediatric
Physical Therapy. 2007;19(4):301. doi: 10.1097/PEP.0b013e318157da3d. [PubMed] [Cross Ref]
Kaur B, Anderson HR, Austin J, Burr M, Harkins LS, Strachan DP, Warner JO. Prevalence of asthma symptoms, diagnosis, and
treatment in 12-14 year old children across Great Britain (international study of asthma and allergies in childhood, ISAAC
UK) British Medical Journal. 1998;316(7125):118. doi: 10.1136/bmj.316.7125.118. [PMC free article] [PubMed] [Cross Ref]
Calam R, Gregg L, Goodman R. Psychological adjustment and asthma in children and adolescents: the UK Nationwide Mental Health
Survey. Psychosomatic Medicine. 2005;67(1):105. doi: 10.1097/01.psy.0000151490.77622.37. [PubMed] [Cross Ref]
Collins JE, Gill TK, Chittleborough CR, Martin AJ, Taylor AW, Winefield H. Mental, emotional, and social problems among school
children with asthma. Journal of Asthma. 2008;45(6):489–493. doi: 10.1080/02770900802074802. [PubMed] [Cross Ref]
Hallal PC, Victora CG, Azevedo MR, Wells JCK. Adolescent physical activity and health: a systematic review. Sports Medicine.
2006;36(12):1019–1030. doi: 10.2165/00007256-200636120-00003. [PubMed] [Cross Ref]
Glazebrook C, McPherson AC, Macdonald IA, Swift JA, Ramsay C, Newbould R, Smyth A. Asthma as a barrier to children's
physical activity: implications for body mass index and mental health. Pediatrics. 2006;118(6):2443. doi: 10.1542/peds.20061846. [PubMed] [Cross Ref]
Guerra S, Wright AL, Morgan WJ, Sherrill DL, Holberg CJ, Martinez FD. Persistence of asthma symptoms during adolescence: role
of obesity and age at the onset of puberty. American journal of respiratory and critical care medicine. 2004;170(1):78. doi:
10.1164/rccm.200309-1224OC. [PubMed] [Cross Ref]
Akerman MJH, Calacanis CM, Madsen MK. Relationship between asthma severity and obesity. Journal of Asthma. 2004;41(5):521–
526. doi: 10.1081/JAS-120037651. [PubMed] [Cross Ref]
Stenius-Aarniala B, Poussa T, Kvarnström J, Grönlund EL, Ylikahri M, Mustajoki P. Immediate and long term effects of weight
reduction in obese people with asthma: randomised controlled study. Bmj. 2000;320(7238):827. doi:
10.1136/bmj.320.7238.827. [PMC free article] [PubMed] [Cross Ref]
Fanelli A, Cabral ALB, Neder JA, Martins MA, Carvalho CRF. Exercise Training on Disease Control and Quality of Life in
Asthmatic Children. Medicine & Science in Sports & Exercise. 2007;39(9):1474–1480. [PubMed]
Pender NJ, Bar-Or O, Wilk B, Mitchell S. Self-Efficacy and Perceived Exertion of Girls During Exercise. Nursing Research.
2002;51(2):86–91. doi: 10.1097/00006199-200203000-00004. [PubMed] [Cross Ref]
Hay JA. Adequacy in and predilection for physical activity in children. Clinical Journal of Sport Medicine. 1992;2(3):192. doi:
10.1097/00042752-199207000-00007. [Cross Ref]
Truby H, Paxton SJ. The Children's Body Image Scale: Reliability and use with international standards for body mass index. British
Journal of Clinical Psychology. 2008;47(1):119–124. doi: 10.1348/014466507X251261. [PubMed] [Cross Ref]
44
Truby H, Paxton SJ. Development of the Children's Body Image Scale. British Journal of Clinical Psychology. 2002;41:185–203. doi:
10.1348/014466502163967. [PubMed] [Cross Ref]
Sallis JF, Strikmiller PK, Harsha DW, Feldman HA, Ehlinger S, Stone EJ, Williston J, Woods S. Validation of interviewer- and selfadministered physical activity checklists for fifth grade students. Medicine & Science in Sports & Exercise. 1996;28(7):840–
851. doi: 10.1097/00005768-199607000-00011. [PubMed] [Cross Ref]
Goodman R. The Strengths and Difficulties Questionnaire: a research note. Journal of Child Psychology and Psychiatry.
1997;38(5):581–586. doi: 10.1111/j.1469-7610.1997.tb01545.x. [PubMed] [Cross Ref]
Cairney J, Hay JA, Faught BE, Wade TJ, Corna L, Flouris A. Developmental coordination disorder, generalized self-efficacy toward
physical activity, and participation in organized and free play activities. The Journal of Pediatrics. 2005;147(4):515–520. doi:
10.1016/j.jpeds.2005.05.013. [PubMed] [Cross Ref]
Hay J. Benefits to physical activity of integrating learning disabled children into the classroom. Pediatric Exercise Science.
1999;11:273.
Physical Activity Guidelines for Children and Young People (5-18 years)
http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/documents/digitalasset/dh_128144.pdf
Bandura A. Self-efficacy: The exercise of control New York. H-Freeman and Company. 1997.
Spybrook J, Raudenbush SW, Congdon R, Martinez A. Optimal Design for Longitudinal and Multilevel Research: Documentation for
the "Optimal Design" Software. Chicago: University of Chicago; 2011.
Goldstein H. Multilevel Statistical Models. Chichester, West Sussex: John Wiley & Sons Ltd; 2011.
.....................................................................................
...
9 Ekeland, E., Heian, F., & Hagen, K. (2005). Can exercise improve self-esteem in
children and young people? a systematic review of randomized controlled trails.
British Journal of Sports Medicine, 39(11), 792–798. doi: 10.1136/bjsm.2004.017707
-MY WRITING
-researchers analyzed a 23 studies that tested to see if self esteem could be elevated by
intense exercise. Some of the studies were graded as “low level” quality trials. All
concluded that intense exercise may have short term positive effect in self-esteem. The
children studied were deemed average, not handicapped or mentally disabled, from ages 3
– 20. Gross motor coordination and energetic activity was studied. The tests varied in time,
but none were less than four weeks.
- issue – researchers of this article studied varied results from all the studies and concluded
that self-esteem was elevated after exercise for only a short time. The evaluative definition
of self esteem was ‘‘the degree to which individuals feel positive about themselves’’
- in all the studies there was a positive effect form physical activity on depression, anxiety,
and behavioural problems in children and adoles- cents.
-Self-esteem was not as equally obviously clear in all studies.
-One study concluded that directed play and/or physical education programs contributed to
the development of self esteem in elementary school age children.11 But the study was
45
flawed due to a lack of a strong systematic approach. Other studies have not bee updated
since they were done.
- Researchers evaluated studies that used exercise with comprehensive intervention versus
no intervention Interventions are defined as teaching skills, counceling sessions and social
environment changes that were created to develop self-esteem.They found that studies with
intervention had a high risk of bias and interventions were personal and not able to be made
into statistics. (See Gilligan)
-This groups without interventions were able to be studied.
The break down of the sports defined as needing teaching verse just letting students
exercise without lessons was also age related. It will not be possible for an elementary
school teacher to NOT INTERVENE in PE.
........................................................................................
Article:
Ekeland, E., Heian, F., & Hagen, K. (2005). Can exercise improve self-esteem in children
and young people? a systematic review of randomized controlled trails. British
Journal of Sports Medicine, 39(11), 792–798. doi: 10.1136/bjsm.2004.017707
Abstract
Twenty three randomised controlled trials were analysed. A synthesis of several small, low
quality trials indicates that exercise may have short term beneficial effects on self esteem
in children and adolescents. However, high quality research on defined populations with
adequate follow up is needed.
Page 1:
Between 10% and 20% of children and adolescents have psychological and beha- vioural
problems and about 7% need psy- chological treatment.1 2 Resilience research has led to
an increasing awareness of positive factors in the environment, social relations, and individuals that protect against the development of problems.3–5 Among individual qualities,
self concept is one of the indicators given most attention. Self concept is defined as an
‘‘orga- nised configuration of prescriptions of the self which are admissible to
awareness’’.6 The eva- luative component of self concept used in this article, self esteem,
is ‘‘the degree to which individuals feel positive about themselves’’.6
Systematic reviews indicate a positive effect of physical activity on depression, anxiety,
and behavioural problems in children and adoles- cents.7–9 The effect of physical activity
on self esteem in children has also been investigated,10 and one meta-analysis concluded
that directed play and/or physical education programmes contributed to the development
of self esteem in elementary school age children.11 This and other reviews have not been
updated and lack description of systematic search and quality assessment of the included
studies.8 9
The aim of this systematic review is to determine if exercise interventions can improve self
esteem among children and young people.
METHOD Searching Searches were conducted in the Cochrane Controlled Trials Register
46
(CENTRAL) (Issue 1, 2004), Medline (1966–2002), Embase (1982– 2002), CINAHL
(1982–2002), PsycINFO (1887– 2002), and ERIC (1965–2002). The search terms were a
wide range of terms about children and young people, physical activity, and self esteem.
The complete search strategy is available in the original publication.12 The authors of
included studies were contacted, and the Journal of the American Academy of Child and
Adolescent Psychiatry was hand searched (1998–2002). There were no language
restrictions.
Selection
Inclusion of studies was restricted to randomised controlled trials and ‘‘quasi-randomised’’
trials— that is, a study that uses methods of allocation that are subject to bias in
assignment, such as alternative allocation, case record numbers, dates of birth—with
children from 3 years of age to young people up to 20 years old. Trials with children and
young people with psychotic or borderline conditions, autism, physical handicap, eating
disorders, and chronic somatic/physical diseases were excluded. The interventions had to
be gross motor, energetic activity with minimum duration four weeks.
Two reviewers judged independently whether the studies fulfilled the inclusion criteria. If
there was uncertainty or disagreement, a third reviewer was consulted.
Validity assessment
Two reviewers independently assigned these five quality criteria to each selected study:13
(1) Concealment of allocation (2) Outcome assessment (assessor unaware of
the assigned treatment when collecting outcome measures) (3) Co-intervention (interventions other than
exercises avoided, or used similarly across
comparison groups) (4) Losses to follow up (5) Intention to treat
Uncertainty or disagreement was resolved by discussion with the third reviewer. Studies
were then grouped as studies with a low risk of bias (all criteria met), studies with a
moderate risk of bias (three to four criteria met), and studies with a high risk of bias (fewer
than three criteria met). As there is no clear evidence that some criteria are more
important than others, they were given equal weight.
Data extraction and study characteristics
Each reviewer independently extracted data on population, age, baseline characteristics,
charac- teristics of activity, compliance, and outcome measures. In cases of missing
information, one author of the paper was contacted.
References
1 Sonuga-Barke EJS, Thompson M, Stevenson J, et al. Patterns of behaviour
problems among pre-school children. Psychol Med 1997;27:909–18.
2 Prior M. Childhood temperament. J Child Psychol Psychiatry
1992;33:249–79.
3 Garmezy N. Stress-resistant children: the search for protective factors. In:
Stevenson JE, ed. Recent research in developmental psychopathology. Oxford/New York:
Pergamon Press, 1985:213–33.
4
Rutter M. Resilience in the face of adversity. Protective factors and resistance to
psychiatric disorder. Br J Psychiatry 1985;36:459–571.
5 Haggerty RJ, Sherrod LR, Garmezy N, et al. Stress, risk and resilience in children and
adolescents. Processes, mechanisms and interventions. Cambridge: Cambridge University
Press, 1996.
6 Sonstroem RJ. Physical self-concept: assessment and external validity. Exerc Sport Sci
Rev 1998;26:133–64.
7 Biddle S. Children, exercise and mental health. Int J Sport Psychol 1993;24:200–16.
8
Calfas KJ, Taylor WC. Effects of physical activity on psychological variables in
adolescents. Pediatric Exercise Science 1994;6:406–23.
9
Mutrie N, Parfitt G. Physical activity and its link with mental, social and moral
health in young people. In: Biddle S, Sallis J, Cavill N, eds. Young and active. London:
Health Education Authority, 1998:49–68.
10
Fox KR. Physical education and the development of children’s self esteem. In: Amstrong
N, eds. New directions in physical education.2. Towards a National Curriculum. Champaign,
47
IL: Human Kinetics, 1992:33–54.
11 Gruber J. Physical activity and self esteem development in children: a meta- analysis.
In: Stull G, Eckern H, eds. Effects of physical activity on children. Champaign, IL: Human
Kinetics, 1986:330–48.
12 Ekeland E, Heian F, Hagen KB, et al. Exercise to improve self esteem in children and
young people. Cochrane Database Syst Rev, 2004.Issue 1.CD003683.
13
In: Alderson P, Green S, Higgins JPT, eds. Cochrane Reviewers’ Handbook 4. 2.2
(updated December 2003).Cochrane Library.Issue 1. Chichester: John Wiley & Sons, Ltd, 2004.
14 Piers EV. Piers-Harris children’s self-concept scale: revised manual. Los Angeles:
Western Psychological Services, 1984.
15 MacMahon JR, Gross RT. Physical and psychological effects of aerobic exercise in
delinquent adolescent males. Am J Dis Child 1988;142:1361–6.
16
Alpert B, Field T, Goldstein S, et al. Aerobics enhances cardiovascular fitness and
agility in preschoolers. Health Psychol 1990;9:48–56.
17 Basile VC, Motta RW, Allison DB. Antecedent exercise as a treatment for disruptive
behavior: testing hypothesized mechanisms of action. Behavioral Interventions 1995;10:119–
40.
18
Bluechardt MHS. Effect of an after-school physical activity program on motor profiency
and social skills of learning disabled children aged 8–11 years. PhD thesis, Department of
Community Health, 1994.
19
Boyd KR, Hrycaiko DW. The effect of a physical activity intervention package on the
self esteem of pre-adolescent and adolescent females. Adolescence 1997;32:693–708.
20 Bruya LD. Effect of selected movement skills on positive self-concept. Percept Mot
Skills 1977;45:252–4.
21 Elstein AE. Effects of physical education on the physical fitness, social adjustment,
and self-concept of learning disabled students. Temple University, Ed D, Education,
special, 1977.
22
Ford HT, Puckett JR, Blessing DL, et al. Effects of selected physical activities on
health-related fitness and psychological well-being. Psychol Rep 1989;64:203–8.
23 Herman-Tofler L, Tuckman B. The effects of aerobic training on children’s creativity,
self-perception, and aerobic power. Child Adolesc Psychiatr Clin N Am 1998;7:773–90.
24 Hilyer JC, Wilson DG, Dillon C, et al. Physical fitness training and counseling as
treatment for youthful offenders. J Couns Psychol 1982;29:292–303.
25
Hilyer JC Jr, Mitchell W. Effect of systematic physical fitness training combined with
counseling on the self-concept of college students. J Couns Psychol 1979;26:427–36.
26 Luebke LLL. A comparison of the effects of two programs of elementary physical education
on the self concept, knowledge of physical activity and physical fitness of third grade
children. Dissertation, Marguette University, 1977.
27 MacMahon JR, Gross RT. Physical and psychological effects of aerobic exercise in boys
with learning disabilities. J Dev Behav Pediatr 1987;8:274–7. 28 Marsh HW, Peart ND.
Competitive and cooperative physical fitness training
programs for girls: effects on physical fitness and multidimensional selfconcepts. Journal of Sport and Exercise Psychology 1988;10:390–407. 29 McGowan RW, Jarman
BO, Pederssen DM. Effects of a competitive
endurance training program on self-concept and peer approval. J Psychol
1974;86:57–60. 30 Munson WW, Baker SB, Lundegren HM. Strength training and leisure
counseling as treatments for institutionalized juvenile delinquests. Adapted Physical
Activity Quarterly 1985;2:65–75.
31 Munson WW. Effects of leisure education versus physical activity or informal discussion
on behaviorally disordered youth offenders. Adapted Physical Activity Quarterly 1988;5:305–
17.
32 Percy LE, Dziuban CD, Martin JB. Analysis of effects of distance running on selfconcepts of elementary students. Percept Mot Skills 1981;52:42.
33 Platzer WS. Effect of perceptual motor training on gross-motor skill and self- concept
of young children. Am J Occup Ther 1976;30:422–8.
34 Salokun SO. Positive change in self-concept as a function of improved performance in
sports. Percept Mot Skills 1994;78:752–4.
35 Smith TL. Self-concepts and movement skills of third grade children after physical
education programs. Percept Mot Skills 1982;54:1145–6.
36 Smith TP. An evaluation of the psychological effects of physical exercise on children.
Diss Abstr Int 1984;7:2260.
37 Tuckman BW, Hinkle JS. An experimental study of the physical and psychological effects
of aerobic exercise on schoolchildren. Health Psychol 1986;5:197–207.
38 Durlak JA, Wells AM. Primarly prevention mental health programs for children and
adolescents: a meta-analytic review. Am J Community Psychol 1997;25:115–52.
39 Cohen J. Statistical power analysis for the behavioral sciences, 2nd ed. Mahwah:
Lawrence Erlbaum Associates, 1988.
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48
10. Thijssen, D., Cable, N., & Green, D. (2012). Impact of exercise training on arterial
wall thickness in humans. US national library of medicine national institutes of
health, 112(Pt7), 311–322. doi: 10.1042/CS20110469
-MY WRITING
-Staying fit through exercise and cardio fitness gives cardioprotection
Intense cardio exercise remodels the caroid artery and peripheral arteries in the lower
limbs.
This means that intense exercise removes plaque from arteries in the neck and the limbs
and prevents heart attacks and stroke.
Moderate exercise is associated with decreased cardiovascular risk . Exercise is associated
with decrease in heart attack risk.
exercise reduces by one half on the risk of heart attacks and strokes.
. The purpose of the present review is to describe the effect of exercise training on
remodelling of the arterial wall in conduit arteries in healthy subjects and in those with
cardiovascular risk factors or disease.
Atherosclerosis (hardening of the arteries) can begin in early life,
Although the process of atherothrombosis
IMT (intima-media thickness), too much IMT in the blood is a positive marker for
hardening of the artieries.
the Rotterdam study established that carotid IMT is associated with increased risk for
adverse cerebral events (e.g. stroke), which is independent of other risk factors.
Carotid IMT (plaque) is a predictor for stroke.
IN general, an increase IMT in the carotid artery leading to stroke is associated with an
increase in age.
The ‘gold-standard’ measure of cardiorespiratory fitness in humans involves direct
assessment of peak or maximal oxygen consumption in response to an exercise test. The
more O2 you take in through aerobic activity the healthier your heart stays.
Arteries of the lower limbs are subject to the development of atherosclerosis, plaque
formation and clinical complications . Indeed, thickening of the arterial wall in older
subjects is even found in arteries of the upper limbs, such as the brachial (arm) artery in
49
which plaque builds up.
Smoking, belly fat and blood pressure effect the amount of plaque that builds up in your
arteries.
Advanced age is associated with the thickening of atherosclerosis-resistant arteries, such as
the brachial artery
. They found a 40% lower 6-year progression of carotid IMT when participants were not on
any statin drugs.
Another study examined the effect of a 4-year lifestyle intervention (PA+diet) (physical
activity) in middle-aged women and found attenuated progression of carotid atherosclerosis
in peri- and post-menopausal women, but not pre-menopausal women [65] (Table 2).
In summary, exercise training appears to have a modest effect on carotid artery
atherosclerosis in young subjects (Figure 1) and changes may require intense exercise or
interventions performed over prolonged time periods.
........................................................................................
Article:
Thijssen, D., Cable, N., & Green, D. (2012). Impact of exercise training on arterial wall
thickness in humans. US national library of medicine national institutes of health,
112(Pt7), 311–322. doi: 10.1042/CS20110469
Abstract
Thickening of the carotid artery wall has been adopted as a surrogate marker of preclinical atherosclerosis, which is strongly related to increased cardiovascular risk. The
cardioprotective effects of exercise training, including direct effects on vascular function
and lumen dimension, have been consistently reported in asymptomatic subjects and
those with cardiovascular risk factors and diseases. In the present review, we summarize
evidence pertaining to the impact of exercise and physical activity on arterial wall
remodelling of the carotid artery and peripheral arteries in the upper and lower limbs. We
consider the potential role of exercise intensity, duration and modality in the context of
putative mechanisms involved in wall remodelling, including haemodynamic forces.
Finally, we discuss the impact of exercise training in terms of primary prevention of wall
thickening in healthy subjects and remodelling of arteries in subjects with existing
cardiovascular disease and risk factors.
One of the first studies to examine the effect of exercise training on atherosclerosis
examined carotid artery IMT in 137 endurance-trained and sedentary men and found no
significant difference between the groups [58]. Subsequent studies performed in younger
[59] or older [60] cohorts also observed no difference in carotid atherosclerosis between
50
endurance-trained subjects and sedentary controls. A recent study [61], however, found a
significantly lower carotid artery IMT in elite squash players compared with less active
controls. The difference in training intensity
Go to:
SUMMARY AND FUTURE DIRECTIONS
Exercise training can decrease arterial wall thickness in healthy asymptomatic subjects as
well as in subjects with cardiovascular risk factors and/or disease that demonstrate
increased arterial wall thickness a priori. However, differences exist between arteries,
since exercise training has more pronounced effects on large peripheral arteries than the
carotids. Modification of carotid wall thickness may require more intense or prolonged
exercise exposure. Changes in arterial wall thickness may contribute to the
cardioprotective effects of exercise, which are not fully explained by effects of traditional
risk factors. However, many questions remain unanswered. Little is known regarding the
duration, type and intensity of exercise training necessary to induce optimal benefits on
the arterial wall and it is unclear whether these effects differ between healthy subjects and
clinical groups. Moreover, the mechanisms that explain changes in the arterial wall as a
result of exercise training are not fully understood. Identifying these stimuli will help in the
design and recommendation of optimal exercise training protocols to attenuate
atherosclerosis burden and risk. Technical advances and newer imaging technologies
[e.g. MRI (magnetic resonance imaging) and strain echography] will assist in answering
important questions regarding the impact of exercise training on arterial structure and
remodelling in future.
References
1. World Health Organization. The Global Burden of Disease: 2004 Update. Geneva: World Health Organization; 2008.
2. Blair S. N., Morris J. N. Healthy hearts: and the universal benefits of being physically active: physical activity and health. Ann.
Epidemiol. 2009;19:253–256. [PubMed]
3. Taylor R. S., Brown A., Ebrahim S., Jolliffe J., Noorani H., Rees K., Skidmore B., Stone J. A., Thompson D. R., Oldridge N.
Exercise-based rehabilitation for patients with coronary heart disease: systematic review and meta-analysis of randomized controlled
trials. Am. J. Med. 2004;116:682–692. [PubMed]
4. Kodama S., Saito K., Tanaka S., Maki M., Yachi Y., Asumi M., Sugawara A., Totsuka K., Shimano H., Ohashi Y., et al.
Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a metaanalysis. JAMA, J. Am. Med. Assoc. 2009;301:2024–2035.
5. Maiorana A., O'Driscoll G., Taylor R., Green D. Exercise and the nitric oxide vasodilator system. Sports Med. 2003;33:1013–1035.
[PubMed]
6. Mora S., Cook N., Buring J. E., Ridker P. M., Lee I. M. Physical activity and reduced risk of cardiovascular events: potential
mediating mechanisms. Circulation. 2007;116:2110–2118. [PMC free article] [PubMed]
7. Joyner M. J., Green D. J. Exercise protects the cardiovascular system: effects beyond traditional risk factors. J. Physiol.
2009;587:5551–5558. [PMC free article] [PubMed]
8. Green D. J., O'Driscoll G., Joyner M. J., Cable N. T. Exercise and cardiovascular risk reduction: time to update the rationale for
exercise? J. Appl. Physiol. 2008;105:766–768. [PubMed]
9. Tuzcu E. M., Kapadia S. R., Tutar E., Ziada K. M., Hobbs R. E., McCarthy P. M., Young J. B., Nissen S. E. High prevalence of
coronary atherosclerosis in asymptomatic teenagers and young adults: evidence from intravascular ultrasound. Circulation.
2001;103:2705–2710. [PubMed]
10. Celermajer D. S., Sorensen K. E., Gooch V. M., Spiegelhalter D. J., Miller O. I., Sullivan I. D., Lloyd J. K., Deanfield J. E. Noninvasive detection of endothelial dysfunction in children and adults at risk of atherosclerosis. Lancet. 1992;340:1111–1115. [PubMed]
11. de Groot E., van Leuven S. I., Duivenvoorden R., Meuwese M. C., Akdim F., Bots M. L., Kastelein J. J. Measurement of carotid
intima-media thickness to assess progression and regression of atherosclerosis. Nat. Clin. Pract. Cardiovasc. Med. 2008;5:280–288.
[PubMed]
12. de Groot E., Hovingh G. K., Wiegman A., Duriez P., Smit A. J., Fruchart J. C., Kastelein J. J. Measurement of arterial wall thickness
as a surrogate marker for atherosclerosis. Circulation. 2004;109:III33–III38. [PubMed]
13. Chambless L. E., Shahar E., Sharrett A. R., Heiss G., Wijnberg L., Paton C. C., Sorlie P., Toole J. F. Association of transient
ischemic attack/stroke symptoms assessed by standardized questionnaire and algorithm with cerebrovascular risk factors and carotid
artery wall thickness. The ARIC Study, 1987–1989. Am. J. Epidemiol. 1996;144:857–866. [PubMed]
14. Heiss G., Sharrett A. R., Barnes R., Chambless L. E., Szklo M., Alzola C. Carotid atherosclerosis measured by B-mode ultrasound in
populations: associations with cardiovascular risk factors in the ARIC study. Am. J. Epidemiol. 1991;134:250–256. [PubMed]
15. Bots M. L., Hoes A. W., Koudstaal P. J., Hofman A., Grobbee D. E. Common carotid intima-media thickness and risk of stroke and
myocardial infarction: the Rotterdam Study. Circulation. 1997;96:1432–1437. [PubMed]
16. Hollander M., Hak A. E., Koudstaal P. J., Bots M. L., Grobbee D. E., Hofman A., Witteman J. C., Breteler M. M. Comparison
between measures of atherosclerosis and risk of stroke: the Rotterdam Study. Stroke. 2003;34:2367–2372. [PubMed]
51
17. Hollander M., Bots M. L., Del Sol A. I., Koudstaal P. J., Witteman J. C., Grobbee D. E., Hofman A., Breteler M. M. Carotid plaques
increase the risk of stroke and subtypes of cerebral infarction in asymptomatic elderly: the Rotterdam Study. Circulation.
2002;105:2872–2877. [PubMed]
18. Ebrahim S., Papacosta O., Whincup P., Wannamethee G., Walker M., Nicolaides A. N., Dhanjil S., Griffin M., Belcaro G., Rumley
A., Lowe G. D. Carotid plaque, intima media thickness, cardiovascular risk factors, and prevalent cardiovascular disease in men and
women: the British Regional Heart Study. Stroke. 1999;30:841–850. [PubMed]
19. O'Leary D. H., Polak J. F., Kronmal R. A., Manolio T. A., Burke G. L., Wolfson S. K., Jr Carotid-artery intima and media thickness
as a risk factor for myocardial infarction and stroke in older adults. N. Engl. J. Med. 1999;340:14–22. [PubMed]
20. Johnsen S. H., Mathiesen E. B., Joakimsen O., Stensland E., Wilsgaard T., Lochen M. L., Njolstad I., Arnesen E. Carotid
atherosclerosis is a stronger predictor of myocardial infarction in women than in men: a 6-year follow-up study of 6226 persons: the
Tromso Study. Stroke. 2007;38:2873–2880. [PubMed]
21. Wattanakit K., Folsom A. R., Selvin E., Weatherley B. D., Pankow J. S., Brancati F. L., Hirsch A. T. Risk factors for peripheral
arterial disease incidence in persons with diabetes: the Atherosclerosis Risk in Communities (ARIC) Study. Atherosclerosis.
2005;180:389–397. [PubMed]
22. Chambless L. E., Folsom A. R., Davis V., Sharrett R., Heiss G., Sorlie P., Szklo M., Howard G., Evans G. W. Risk factors for
progression of common carotid atherosclerosis: the Atherosclerosis Risk in Communities Study, 1987–1998. Am. J. Epidemiol.
2002;155:38–47. [PubMed]
23. Lorenz M. W., Markus H. S., Bots M. L., Rosvall M., Sitzer M. Prediction of clinical cardiovascular events with carotid intimamedia thickness: a systematic review and meta-analysis. Circulation. 2007;115:459–467. [PubMed]
24. Lorenz M. W., Schaefer C., Steinmetz H., Sitzer M. Is carotid intima media thickness useful for individual prediction of
cardiovascular risk? Ten-year results from the Carotid Atherosclerosis Progression Study (CAPS) Eur. Heart J. 2010;31:2041–2048.
[PubMed]
25. Bjarnegard N., Lanne T. Arterial properties along the upper arm in humans: age-related effects and the consequence of anatomical
location. J. Appl. Physiol. 2010;108:34–38. [PubMed]
26. Green D. J., Swart A., Exterkate A., Naylor L. H., Black M. A., Cable N. T., Thijssen D. H. Impact of age, sex and exercise on
brachial and popliteal artery remodelling in humans. Atherosclerosis. 2010;210:525–530. [PubMed]
27. Grobbee D. E., Bots M. L. Carotid artery intima-media thickness as an indicator of generalized atherosclerosis. J. Intern. Med.
1994;236:567–573. [PubMed]
28. Paul T. K., Srinivasan S. R., Chen W., Li S., Bond M. G., Tang R., Berenson G. S. Impact of multiple cardiovascular risk factors on
femoral artery intima-media thickness in asymptomatic young adults (the Bogalusa Heart Study) Am. J. Cardiol. 2005;95:469–473.
[PubMed]
29. Paul T. K., Chen W., Srinivasan S. R., Rice J., Toprak A., He J., Berenson G. S. Framingham risk score is associated with femoral
artery intima-media thickness in asymptomatic young adults (the Bogalusa heart study) Atherosclerosis. 2010;213:627–631. [PMC free
article] [PubMed]
30. Joensuu T., Salonen R., Winblad I., Korpela H., Salonen J. T. Determinants of femoral and carotid artery atherosclerosis. J. Intern.
Med. 1994;236:79–84. [PubMed]
31. Suurkula M., Fagerberg B., Wendelhag I., Agewall S., Wikstrand J. Atherosclerotic disease in the femoral artery in hypertensive
patients at high cardiovascular risk. The value of ultrasonographic assessment of intima-media thickness and plaque occurrence.
Arterioscler. Thromb. Vasc. Biol. 1996;16:971–977. [PubMed]
32. Rietzschel E. R., De Buyzere M. L., Duprez D. A., Clement D. L. Interchangeability of carotid and femoral intima-media thickness in
risk stratification. Int. Angiol. 2001;20:38–46. [PubMed]
33. Novo G., Maniglia D., Corrado E., Muratori I., Sutera F., Evola S., Ferrara F., Hoffmann E., Novo S. Peripheral atherosclerosis is
associated with the occurrence of restenosis after percutaneous coronary intervention. Coron. Artery Dis. 2007;18:627–631. [PubMed]
34. Lekakis J. P., Papamichael C. M., Cimponeriu A. T., Stamatelopoulos K. S., Papaioannou T. G., Kanakakis J., Alevizaki M. K.,
Papapanagiotou A., Kalofoutis A. T., Stamatelopoulos S. F. Atherosclerotic changes of extracoronary arteries are associated with the
extent of coronary atherosclerosis. Am. J. Cardiol. 2000;85:949–952. [PubMed]
35. Agewall S., Henareh L., Jogestrand T. Intima-media complex of both the brachial artery and the common carotid artery are
associated with left ventricular hypertrophy in patients with previous myocardial infarction. J. Hypertens. 2005;23:119–125. [PubMed]
36. Sorensen K. E., Kristensen I. B., Celermajer D. S. Atherosclerosis in the human brachial artery. J. Am. Coll. Cardiol. 1997;29:318–
322. [PubMed]
37. Lind L., Andersson J., Ronn M., Gustavsson T., Holdfelt P., Hulthe J., Elmgren A., Zilmer K., Zilmer M. Brachial artery intimamedia thickness and echogenicity in relation to lipids and markers of oxidative stress in elderly subjects: the prospective investigation of
the vasculature in Uppsala Seniors (PIVUS) Study. Lipids. 2008;43:133–141. [PubMed]
38. Weidinger F., Frick M., Alber H. F., Ulmer H., Schwarzacher S. P., Pachinger O. Association of wall thickness of the brachial artery
measured with high-resolution ultrasound with risk factors and coronary artery disease. Am. J. Cardiol. 2002;89:1025–1029. [PubMed]
39. Frick M., Schwarzacher S. P., Alber H. F., Rinner A., Ulmer H., Pachinger O., Weidinger F. Morphologic rather than functional or
mechanical sonographic parameters of the brachial artery are related to angiographically evident coronary atherosclerosis. J. Am. Coll.
Cardiol. 2002;40:1825–1830. [PubMed]
40. Frick M., Suessenbacher A., Alber H. F., Dichtl W., Ulmer H., Pachinger O., Weidinger F. Prognostic value of brachial artery
endothelial function and wall thickness. J. Am. Coll. Cardiol. 2005;46:1006–1010. [PubMed]
41. Poelzl G., Frick M., Huegel H., Lackner B., Alber H. F., Mair J., Herold M., Schwarzacher S., Pachinger O., Weidinger F. Chronic
heart failure is associated with vascular remodeling of the brachial artery. Eur. J. Heart Failure. 2005;7:43–48.
42. Juonala M., Viikari J. S., Kahonen M., Taittonen L., Laitinen T., Hutri-Kahonen N., Lehtimaki T., Jula A., Pietikainen M., Jokinen
E., et al. Life-time risk factors and progression of carotid atherosclerosis in young adults: the Cardiovascular Risk in Young Finns study.
Eur. Heart J. 2010;31:1745–1751. [PubMed]
43. Stensland-Bugge E., Bonaa K. H., Joakimsen O. Age and sex differences in the relationship between inherited and lifestyle risk
factors and subclinical carotid atherosclerosis: the Tromso study. Atherosclerosis. 2001;154:437–448. [PubMed]
44. Stensland-Bugge E., Bonaa K. H., Joakimsen O., Njolstad I. Sex differences in the relationship of risk factors to subclinical carotid
atherosclerosis measured 15 years later: the Tromso study. Stroke. 2000;31:574–581. [PubMed]
45. Luedemann J., Schminke U., Berger K., Piek M., Willich S. N., Doring A., John U., Kessler C. Association between behavior-
52
dependent cardiovascular risk factors and asymptomatic carotid atherosclerosis in a general population. Stroke. 2002;33:2929–2935.
[PubMed]
46. Folsom A. R., Eckfeldt J. H., Weitzman S., Ma J., Chambless L. E., Barnes R. W., Cram K. B., Hutchinson R. G. Relation of carotid
artery wall thickness to diabetes mellitus, fasting glucose and insulin, body size and physical activity. Stroke. 1994;25:66–73. [PubMed]
47. Nordstrom C. K., Dwyer K. M., Merz C. N., Shircore A., Dwyer J. H. Leisure time physical activity and early atherosclerosis: the
Los Angeles Atherosclerosis Study. Am. J. Med. 2003;115:19–25. [PubMed]
48. Mikkelsson L., Kaprio J., Kautiainen H., Kujala U. M., Nupponen H. Associations between self-estimated and measured physical
fitness among 40-year-old men and women. Scand. J. Med. Sci. Sports. 2005;15:329–335. [PubMed]
49. Yamada S., Inaba M., Goto H., Nagata-Sakurai M., Kumeda Y., Imanishi Y., Emoto M., Ishimura E., Nishizawa Y. Associations
between physical activity, peripheral atherosclerosis and bone status in healthy Japanese women. Atherosclerosis. 2006;188:196–202.
[PubMed]
50. Hagg U., Wandt B., Bergstrom G., Volkmann R., Gan L. M. Physical exercise capacity is associated with coronary and peripheral
vascular function in healthy young adults. Am. J. Physiol. Heart Circ. Physiol. 2005;289:H1627–H1634. [PubMed]
51. Rauramaa R., Rankinen T., Tuomainen P., Vaisanen S., Mercuri M. Inverse relationship between cardiorespiratory fitness and carotid
atherosclerosis. Atherosclerosis. 1995;112:213–221. [PubMed]
52. Sandrock M., Schulze C., Schmitz D., Dickhuth H. H., Schmidt-Trucksaess A. Physical activity throughout life reduces the
atherosclerotic wall process in the carotid artery. Br. J. Sports Med. 2008;42:839–844. [PubMed]
53. Lee C. D., Jae S. Y., Iribarren C., Pettee K. K., Choi Y. H. Physical fitness and carotid atherosclerosis in men. Int. J. Sports Med.
2009;30:672–676. [PubMed]
54. Hamer M., Kivimaki M., Lahiri A., Yerramasu A., Deanfield J. E., Marmot M. G., Steptoe A. Walking speed and subclinical
atherosclerosis in healthy older adults: the Whitehall II study. Heart. 2010;96:380–384. [PMC free article] [PubMed]
55. Elbaz A., Ripert M., Tavernier B., Fevrier B., Zureik M., Gariepy J., Alperovitch A., Tzourio C. Common carotid artery intimamedia thickness, carotid plaques and walking speed. Stroke. 2005;36:2198–2202. [PubMed]
56. Bertoni A. G., Whitt-Glover M. C., Chung H., Le K. Y., Barr R. G., Mahesh M., Jenny N. S., Burke G. L., Jacobs D. R. The
association between physical activity and subclinical atherosclerosis: the Multi-Ethnic Study of Atherosclerosis. Am. J. Epidemiol.
2009;169:444–454. [PMC free article] [PubMed]
57. Lakka T. A., Laukkanen J. A., Rauramaa R., Salonen R., Lakka H. M., Kaplan G. A., Salonen J. T. Cardiorespiratory fitness and the
progression of carotid atherosclerosis in middle-aged men. Ann. Intern. Med. 2001;134:12–20. [PubMed]
58. Tanaka H., Seals D. R., Monahan K. D., Clevenger C. M., DeSouza C. A., Dinenno F. A. Regular aerobic exercise and the agerelated increase in carotid artery intima-media thickness in healthy men. J. Appl. Physiol. 2002;92:1458–1464. [PubMed]
59. Popovic M., Puchner S., Endler G., Foraschik C., Minar E., Bucek R. A. The effects of endurance and recreational exercise on
subclinical evidence of atherosclerosis in young adults. Am. J. Med. Sci. 2010;339:332–336. [PubMed]
60. Moreau K. L., Donato A. J., Seals D. R., Dinenno F. A., Blackett S. D., Hoetzer G. L., Desouza C. A., Tanaka H. Arterial intimamedia thickness: site-specific associations with HRT and habitual exercise. Am. J. Physiol. Heart Circ. Physiol. 2002;283:H1409–
H1417. [PubMed]
61. Rowley N. J., Dawson E. A., Birk G. K., Cable N. T., George K., Whyte G., Thijssen D. H., Green D. J. Exercise and arterial
adaptation in humans: uncoupling localized and systemic effects. J. Appl. Physiol. 2011;110:1190–1195. [PubMed]
62. Thijssen D. H., de Groot P. C., Smits P., Hopman M. T. Vascular adaptations to 8-week cycling training in older men. Acta Physiol.
2007;190:221–228.
63. Rakobowchuk M., McGowan C. L., de Groot P. C., Hartman J. W., Phillips S. M., MacDonald M. J. Endothelial function of young
healthy males following whole body resistance training. J. Appl. Physiol. 2005;98:2185–2190. [PubMed]
64. Rauramaa R., Halonen P., Vaisanen S. B., Lakka T. A., Schmidt-Trucksass A., Berg A., Penttila I. M., Rankinen T., Bouchard C.
Effects of aerobic physical exercise on inflammation and atherosclerosis in men: the DNASCO Study: a six-year randomized, controlled
trial. Ann. Intern. Med. 2004;140:1007–1014. [PubMed]
65. Wildman R. P., Schott L. L., Brockwell S., Kuller L. H., Sutton-Tyrrell K. A dietary and exercise intervention slows menopauseassociated progression of subclinical atherosclerosis as measured by intima-media thickness of the carotid arteries. J. Am. Coll. Cardiol.
2004;44:579–585. [PubMed]
66. Dinenno F. A., Tanaka H., Monahan K. D., Clevenger C. M., Eskurza I., DeSouza C. A., Seals D. R. Regular endurance exercise
induces expansive arterial remodelling in the trained limbs of healthy men. J. Physiol. 2001;534:287–295. [PMC free article] [PubMed]
67. Moreau K. L., Silver A. E., Dinenno F. A., Seals D. R. Habitual aerobic exercise is associated with smaller femoral artery intimamedia thickness with age in healthy men and women. Eur. J. Cardiovasc. Prev. Rehabil. 2006;13:805–811. [PubMed]
68. van Duijnhoven N. T., Green D. J., Felsenberg D., Belavy D. L., Hopman M. T., Thijssen D. H. Impact of bed rest on conduit artery
remodeling: effect of exercise countermeasures. Hypertension. 2010;56:240–246. [PubMed]
69. Thijssen D. H., Dawson E. A., van den Munckhof I. C., Tinken T. M., den Drijver E., Hopkins N., Cable N. T., Green D. J. Exercisemediated changes in conduit artery wall thickness in humans: role of shear stress. Am. J. Physiol. Heart Circ. Physiol. 2011;301:H241–
H246. [PubMed]
70. Farpour-Lambert N. J., Aggoun Y., Marchand L. M., Martin X. E., Herrmann F. R., Beghetti M. Physical activity reduces systemic
blood pressure and improves early markers of atherosclerosis in pre-pubertal obese children. J. Am. Coll. Cardiol. 2009;54:2396–2406.
[PubMed]
71. Meyer A. A., Kundt G., Lenschow U., Schuff-Werner P., Kienast W. Improvement of early vascular changes and cardiovascular risk
factors in obese children after a six-month exercise program. J. Am. Coll. Cardiol. 2006;48:1865–1870. [PubMed]
72. Woo K. S., Chook P., Yu C. W., Sung R. Y., Qiao M., Leung S. S., Lam C. W., Metreweli C., Celermajer D. S. Effects of diet and
exercise on obesity-related vascular dysfunction in children. Circulation. 2004;109:1981–1986. [PubMed]
73. Skilton M. R., Sieveking D. P., Harmer J. A., Franklin J., Loughnan G., Nakhla S., Sullivan D. R., Caterson I. D., Celermajer D. S.
The effects of obesity and non-pharmacological weight loss on vascular and ventricular function and structure. Diabetes Obes. Metab.
2008;10:874–884. [PubMed]
74. Olson T. P., Dengel D. R., Leon A. S., Schmitz K. H. Moderate resistance training and vascular health in overweight women. Med.
Sci. Sports Exercise. 2006;38:1558–1564.
75. Jae S. Y., Carnethon M. R., Heffernan K. S., Choi Y. H., Lee M. K., Fernhall B. Association between cardiorespiratory fitness and
prevalence of carotid atherosclerosis among men with hypertension. Am. Heart J. 2007;153:1001–1005. [PubMed]
53
76. Palatini P., Puato M., Rattazzi M., Pauletto P. Effect of regular physical activity on carotid intima-media thickness. Results from a 6year prospective study in the early stage of hypertension. Blood Press. 2010;20:37–44. [PubMed]
77. Anderssen S. A., Hjelstuen A. K., Hjermann I., Bjerkan K., Holme I. Fluvastatin and lifestyle modification for reduction of carotid
intima-media thickness and left ventricular mass progression in drug-treated hypertensives. Atherosclerosis. 2005;178:387–397.
[PubMed]
78. Watarai T., Yamasaki Y., Ikeda M., Kubota M., Kodama M., Tsujino T., Kishimoto M., Kawamori R., Hori M. Insulin resistance
contributes to carotid arterial wall thickness in patients with non-insulin-dependent-diabetes mellitus. Endocr. J. 1999;46:629–638.
[PubMed]
79. Kim S. H., Lee S. J., Kang E. S., Kang S., Hur K. Y., Lee H. J., Ahn C. W., Cha B. S., Yoo J. S., Lee H. C. Effects of lifestyle
modification on metabolic parameters and carotid intima-media thickness in patients with type 2 diabetes mellitus. Metab. Clin. Exp.
2006;55:1053–1059. [PubMed]
80. Trigona B., Aggoun Y., Maggio A., Martin X. E., Marchand L. M., Beghetti M., Farpour-Lambert N. J. Preclinical noninvasive
markers of atherosclerosis in children and adolescents with type 1 diabetes are influenced by physical activity. J. Pediatr. 2011;157:533–
539. [PubMed]
81. Seeger J. P., Thijssen D. H., Noordam K., Cranen M. E., Hopman M. T., Nijhuis-van der Sanden M. W. Exercise training improves
physical fitness and vascular function in children with type 1 diabetes. Diabetes Obes. Metab. 2011;13:382–384. [PubMed]
82. Okada K., Maeda N., Tatsukawa M., Shimizu C., Sawayama Y., Hayashi J. The influence of lifestyle modification on carotid artery
intima-media thickness in a suburban Japanese population. Atherosclerosis. 2004;173:329–337. [PubMed]
83. Maiorana A. J., Naylor L. H., Exterkate A., Swart A., Thijssen D. H., Lam K., O'Driscoll G., Green D. J. The impact of exercise
training on conduit artery wall thickness and remodeling in chronic heart failure patients. Hypertension. 2011;57:56–62. [PubMed]
84. Laughlin M. H. Endothelium-mediated control of coronary vascular tone after chronic exercise training. Med. Sci. Sports Exercise.
1995;27:1135–1144.
85. Tinken T. M., Thijssen D. H., Black M. A., Cable N. T., Green D. J. Time course of change in vasodilator function and capacity in
response to exercise training in humans. J. Physiol. 2008;586:5003–5012. [PMC free article] [PubMed]
86. Thijssen D. H., Scholten R. R., van den Munckhof I. C., Benda N., Green D. J., Hopman M. T. Acute change in vascular tone alters
intima-media thickness. Hypertension. 2011;58:240–246. [PubMed]
87. Kozakova M., Palombo C., Morizzo C., Nolan J. J., Konrad T., Balkau B. Effect of sedentary behaviour and vigorous physical
activity on segment-specific carotid wall thickness and its progression in a healthy population. Eur. Heart J. 2010;31:1511–1519.
[PubMed]
88. Kozakova M., Palombo C., Mhamdi L., Konrad T., Nilsson P., Staehr P. B., Paterni M., Balkau B. Habitual physical activity and
vascular aging in a young to middle-age population at low cardiovascular risk. Stroke. 2007;38:2549–2555. [PubMed]
89. Okamoto T., Masuhara M., Ikuta K. Effects of eccentric and concentric resistance training on arterial stiffness. J. Hum. Hypertens.
2006;20:348–354. [PubMed]
90. Maiorana A., O'Driscoll G., Cheetham C., Collis J., Goodman C., Rankin S., Taylor R., Green D. Combined aerobic and resistance
exercise training improves functional capacity and strength in CHF. J. Appl. Physiol. 2000;88:1565–1570. [PubMed]
91. Maiorana A., O'Driscoll G., Dembo L., Cheetham C., Goodman C., Taylor R., Green D. Effect of aerobic and resistance exercise
training on vascular function in heart failure. Am. J. Physiol. Heart Circ. Physiol. 2000;279:H1999–H2005. [PubMed]
92. Langille B. L., O'Donnell F. Reductions in arterial diameter produced by chronic decreases in blood flow are endothelium-dependent.
Science. 1986;231:405–407. [PubMed]
93. Ku D. N., Giddens D. P., Zarins C. K., Glagov S. Pulsatile flow and atherosclerosis in the human carotid bifurcation. Positive
correlation between plaque location and low oscillating shear stress. Arteriosclerosis. 1985;5:293–302. [PubMed]
94. Zarins C. K., Giddens D. P., Bharadvaj B. K., Sottiurai V. S., Mabon R. F., Glagov S. Carotid bifurcation atherosclerosis.
Quantitative correlation of plaque localization with flow velocity profiles and wall shear stress. Circ. Res. 1983;53:502–514. [PubMed]
95. Ziegler T., Bouzourene K., Harrison V. J., Brunner H. R., Hayoz D. Influence of oscillatory and unidirectional flow environments on
the expression of endothelin and nitric oxide synthase in cultured endothelial cells. Arterioscler. Thromb. Vasc. Biol. 1998;18:686–692.
[PubMed]
96. Thijssen D. H., Dawson E. A., Tinken T. M., Cable N. T., Green D. J. Retrograde flow and shear rate acutely impair endothelial
function in humans. Hypertension. 2009;53:986–992. [PubMed]
97. Newcomer S. C., Thijssen D. H., Green D. J. Effects of exercise on endothelium and endothelium/smooth muscle crosstalk: role of
exercise-induced hemodynamics. J. Appl. Physiol. 2011;111:311–320. [PubMed]
98. Laughlin M. H., Newcomer S. C., Bender S. B. Importance of hemodynamic forces as signals for exercise-induced changes in
endothelial cell phenotype. J. Appl. Physiol. 2008;104:588–600. [PMC free article] [PubMed]
99. Thijssen D. H., Dawson E. A., Black M. A., Hopman M. T., Cable N. T., Green D. J. Brachial artery blood flow responses to
different modalities of lower limb exercise. Med. Sci. Sports Exercise. 2009;41:1072–1079.
100. Green D. J., Bilsborough W., Naylor L. H., Reed C., Wright J., O'Driscoll G., Walsh J. H. Comparison of forearm blood flow
responses to incremental handgrip and cycle ergometer exercise: relative contribution of nitric oxide. J. Physiol. 2005;562:617–628.
[PMC free article] [PubMed]
101. Dinenno F. A., Jones P. P., Seals D. R., Tanaka H. Age-associated arterial wall thickening is related to elevations in sympathetic
activity in healthy humans. Am. J. Physiol. Heart Circ. Physiol. 2000;278:H1205–H1210. [PubMed]
102. Tanaka H., Dinenno F. A., Monahan K. D., DeSouza C. A., Seals D. R. Carotid artery wall hypertrophy with age is related to local
systolic blood pressure in healthy men. Arterioscler. Thromb. Vasc. Biol. 2001;21:82–87. [PubMed]
103. Pauletto P., Scannapieco G., Pessina A. C. Sympathetic drive and vascular damage in hypertension and atherosclerosis.
Hypertension. 1991;17:III75–III81. [PubMed]
104. Roveda F., Middlekauff H. R., Rondon M. U., Reis S. F., Souza M., Nastari L., Barretto A. C., Krieger E. M., Negrao C. E. The
effects of exercise training on sympathetic neural activation in advanced heart failure: a randomized controlled trial. J. Am. Coll. Cardiol.
2003;42:854–860. [PubMed]
105. Ray C. A., Hume K. M. Sympathetic neural adaptations to exercise training in humans: insights from microneurography. Med. Sci.
Sports Exercise. 1998;30:387–391.
106. Ng A. V., Callister R., Johnson D. G., Seals D. R. Endurance exercise training is associated with elevated basal sympathetic nerve
activity in healthy older humans. J. Appl. Physiol. 1994;77:1366–1374. [PubMed]
54
107. Sugawara J., Komine H., Hayashi K., Yoshizawa M., Otsuki T., Shimojo N., Miyauchi T., Yokoi T., Maeda S., Tanaka H. Systemic
α-adrenergic and nitric oxide inhibition on basal limb blood flow: effects of endurance training in middle-aged and older adults. Am. J.
Physiol. Heart Circ. Physiol. 2007;293:H1466–H1472. [PubMed]
108. Minuz P., Fava C., Cominacini L. Oxidative stress, antioxidants and vascular damage. Br. J. Clin. Pharmacol. 2006;61:774–777.
[PMC free article] [PubMed]
109. Stocker R., Keaney J. F., Jr Role of oxidative modifications in atherosclerosis. Physiol. Rev. 2004;84:1381–1478. [PubMed]
110. Gomez-Cabrera M. C., Domenech E., Vina J. Moderate exercise is an antioxidant: upregulation of antioxidant genes by training.
Free Radical Biol. Med. 2008;44:126–131. [PubMed]
111. Ait-Oufella H., Taleb S., Mallat Z., Tedgui A. Recent advances on the role of cytokines in atherosclerosis. Arterioscler. Thromb.
Vasc. Biol. 2011;31:969–979. [PubMed]
112. Ribeiro F., Alves A. J., Duarte J. A., Oliveira J. Is exercise training an effective therapy targeting endothelial dysfunction and
vascular wall inflammation? Int. J. Cardiol. 2010;141:214–221. [PubMed]
113. Chan S. Y., Mancini G. B., Burns S., Johnson F. F., Brozic A. P., Kingsbury K., Barr S., Kuramoto L., Schulzer M., Frohlich J.,
Ignaszewski A. Dietary measures and exercise training contribute to improvement of endothelial function and atherosclerosis even in
patients given intensive pharmacologic therapy. J. Cardiopulm. Rehabil. 2006;26:288–293. [PubMed]
..............................................................................................................
11Geus, B., Smet, S., Nijs, J. & Meeusen, R. (2007). Determining the intensity and
energy expenditure during commuter cycling. British Journal Sports Medince.
41(1),8-12.
- Exercise is a key to good health. This study analyzed the effects of biking to work on
adults. The study found that staying physically active improved the health of both men and
women.
The benefits are related to
-Frequency of exercise -20 – 60 minutes each session
-amount of time – 3-5 days a week is ideal
-heart rate – maximum or less than ideal level for cardio-vascular effect
Lower levels of physical activity (less intensity) was shown to reduce some of the risks
for some chronic degenerative diseases and improve metabolic fitness, but lower levels of
may not be sufficient enough to improve maximal oxygen uptake capacity. Maximum
oxygen uptake makes the heart stronger
The results of the study proved that walking and cycling to work enabled a considerable
proportion of the working population to perform regular physical activity and maintain or
attain better health.
55
Based on this study, As a teacher, I will give extra credit to students who exercise at home.
Fortunate students may get a chance to bike or play in a park on the weekends, students
without access to the outside will be given a series of exercises (yoga and/or aerobic). The
exercises time should be at least bout 20 minutes.
Students will have to get an adult to sign off that they students did the exercise. I will put
up a chart on the wall entitled “Olympians of Class ____”. After a student has completed 5
routine exercises there name will go up on the chart. Every 5 routines they will earn a star.
At the end of the term we will have a ceremony for gold, silver and bronze winners.
-At the population level, the substantial health‐ enhancing potential of physical activity can
be accomplished preferentially by incorporating physical activity into the daily routine.
Physically active commuting to work provides a promising mode for such activity.2 Daily
cycling to work has been shown to improve physical performance3,4 and health5 in men
and women.
Many of the health and fitness benefits are related to the total amount of work (volume)
performed.1,7,8,9 The American College of Sports Medicine (ACSM) Position Stand8
makes the following recommendations for the quantity and quality of exercise for
developing and maintaining cardiovascular fitness: frequency, 3–5 days/week; intensity,
55–90% of the maximal heart rate; and duration, 20–60 min of continuous or intermittent
aerobic activity. Lower levels of physical activity (particularly intensity) may reduce the
risk of certain chronic degenerative diseases and improve metabolic fitness, and yet may
not be of sufficient quantity or quality to improve maximal oxygen uptake capacity. Many
of the health benefits from physical activity can be achieved at lower intensities of exercise
if frequency and duration are increased appropriately.8 According to the recommendations
of the Centers for Disease Control and Prevention (CDC) and the ACSM,1 considerable
health benefits can be achieved by engaging in physical activity of moderate intensity for at
least 30 min per session on most, and preferably all, days of the week. Moderate physical
activity is defined as activities performed at an intensity of 3–6 metabolic equivalents
(METs; 3.5–7 kcal/min). For people who are quite unfit, the lower intensity values—that
is, 55–64% of the maximum heart rate—are most applicable.8
Exercise is a key to good health. This study analyzed the effects of biking to work on
adults. The study found that staying physically active improved the health of both men and
women.
………………………………………………………………………
Article:
Geus, B., Smet, S., Nijs, J. & Meeusen, R. (2007). Determining the intensity and energy
expenditure during commuter cycling. British Journal Sports Medince. 41(1),8-12.
Abstract
Objectives
56
To determine the intensity and energy expenditure during commuter cycling, and to
investigate whether cycling to work at a self‐ chosen intensity corresponds to
recommendations of the Centers for Disease Control and Prevention (CDC) and American
College of Sports Medicine (ACSM) for health improvement and ACSM recommendations
for fitness improvement.
Methods
18 healthy, untrained middle‐ aged people, who did not cycle to work, underwent two
maximal exercise tests (MT and MT2) in order to measure their maximal heart rate and
oxygen consumption (VO2). MT2 was performed 24 weeks after MT. Participants were
asked to cycle at least three times a week to their workplace over a one‐ way minimum
distance of 2 km. Data on cycling were recorded in a diary. 12 weeks after MT, a field test
was conducted, where participants had to cycle to or from their workplace. The same
measurements were taken as during MT as markers of exercise intensity. Metabolic
equivalents (METs) and energy expenditure were calculated.
Results
The intensity during the field test was >75% of their maximal aerobic capacity. The mean
(SD) MET value was 6.8 (1.9). The energy expenditure during the field test was 220 (115)
kcal or 540 (139) kcal/h and 1539 (892) kcal/week. Men consumed significantly (p<0.01)
more energy per hour than women.
Conclusion
Commuter cycling at a self‐ selected intensity meets the CDC and ACSM
recommendations for health improvement and the ACSM recommendations for
improvement of cardiorespiratory fitness. However, as the participants cycled faster during
the field test than during daily cycling, the results should be interpreted with caution.
References
1. Pate R R, Pratt M, Blair S N. Physical activity and public health: a recommendation from the Centres for Disease Control and
Prevention and the American College of Sports Medicine. JAMA 1995. 273402–407.407. [PubMed]
2. Oja P, Vuori I, Paronen O. Daily walking and cycling to work: their utility as health‐ enhancing physical activity. Patient Educ
Counsell 1998. 33S87–S94.S94.
3. Hendriksen I J M, Zuiderveld B, Kemper H C G. et al Effect of commuter cycling on physical performance of male and female
employees. Med Sci Sports Exerc 2000. 32504–510.510. [PubMed]
4. Oja P, Mänttäri A, Heinomen A. et al Physiological effects of walking and cycling to work. Scan J Med Sci Sports 1991. 1151–
157.157.
5. Vuori I, Oja P, Paronen O. Physically active commuting to work—testing its potential for exercise promotion. Med Sci Sports Exerc
1994. 26844–850.850. [PubMed]
6. Spelman C C, Pate R R, Macera CA et a l. Self‐ selected exercise intensity of habitual walkers. Med Sci Sports Exerc 1993. 251174–
1179.1179. [PubMed]
7. Haskell W L, Wolffe J B. Memorial lecture. Health consequences of physical activity: understanding and challenges regarding
dose‐ response, Med Sci Sports Exerc 1994. 26649–660.660. [PubMed]
8. Pollock M L, Gaesser G A, Butcher J D. et al The recommended quantity and quality of exercise for developing and maintaining
cardiorespiratory and muscular fitness, and flexibility in healthy adults. Med Sci Sports Exerc 1998. 30975–991.991. [PubMed]
9. US Department of Health and Human Services Physical activity and health: a report of the Surgeon General. Atlanta, GA: US
Department of Health and Human Services, 1996.
10. Lee I M, Skerrett P J. Physical activity and all‐ cause mortality: what is the dose‐ response relation? Med Sci Sports Exerc 2001.
33S459–S471.S471. [PubMed]
11. American College of Sports Medicine Guidelines for exercise testing and prescription. 7th ed. Lippincott Williams and Wilkins,
Philadelphia, Pennsylvania, USA, 2005 .
12. Wasserman K. Principles of exercise testing and interpretation. 3rd ed. Lippincott Williams and Wilkins, Philadelphia, Pennsylvania,
USA, 1999 .
13. Borg G. The reliability and validity of a physical work test. Acta Physiol Scand 1962. 5533–36.36.
14. Kukkonen‐ Harjula K, Oja P, Laukkanen R. et al Kâvellen tai pyöräillen kuljetun työmatkan fysiologinen kuormittavuus. Liikunta Ja
Tiede 1988. 2582–85.85.
57
........................................................................................
12Monyeki, M., Neetens, R., Moss, S., & Twisk, J. (2012). The relationship between
body composition and physical fitness in 14 year old adolescents residing within the
tlokwe local municipality, south africa: The pahl study. BioMedicalCenter Public
Health, 12(374), doi: :10.1186/1471-2458-12-374
The electronic version of this article is the complete one and can be found
online at: http://www.biomedcentral.com/1471-2458/12/374
- MY WRITING
Physical fitness tests
European Test of Physical Fitness - Standing broad jump is designed to
measure explosive strength and the results are expressed
in centimeter. Bent arm hang is designed to measure
static arm strength and is expressed in seconds. Sit-ups,
designed to measure functional strength, is expressed in
the number of situps in 30 seconds.
Girls and boys tested
-
underweight and overweight students were able to do the exercises but on the
whole, there are more underweight boys than girls who could do the exercises well
over and under weight girls had good functional strength to lift weights and do sits
up but face problems in their future due undernourishment due to poverty
_______________________________________________________________________
Abstract
Background: Little is known about the relationship between body composition and physical
fitness in 14 year-old high school adolescents of South Africa. Baseline data from a
longitudinal study on physical activity and health
(PAHLS) may provide valuable information for future studies, hence to inform public health
policy makers. The objectives of this study are to determine the prevalence of
underweight, normal weight and overweight among adolescents aged 14 years in the
Tlokwe Local Municipality of the North West Province of South Africa, and to assess the
association between physical fitness and body composition separately for boys and girls,
adjusted for
race and locality. Methods: Body weight, height and triceps, and subscapular skinfolds of
256 adolescents (100 boys and 156 girls)
aged 14 years were measured, and percentage body fat and body mass index (BMI) were
58
calculated. BMI was used to determine underweight, normal weight and overweight based
on the standard criterion.
Physical fitness was assessed by standing broad jump, bent arm hang and sit-ups
according to the EUROFIT fitness standard procedures. Multinomial logistic regression
analyses stratified for gender and adjusted for race (black or white), and the locality (urban
or township) of the schools were used to analyze the data.
Results: In the total group 35.9% were underweight and 13.7% overweight. Boys were
more underweight (44%)
than girls (30.7%). The prevalence of overweight was 8% in boys and 17.3% in girls. BMI
was strongly (p = 0.01) related with percentage body fat. Strong and significant positive
associations between physical fitness and BMI for
the underweight girls with high physical fitness scores (OR, 10.69 [95%CI: 2.81-40.73],
and overweight girls with high physical fitness scores (OR, 0.11 [95%CI: 0.03-0.50]) were
found. Non-significant weaker positive relationship between
physical fitness and BMI for the underweight boys with high physical fitness scores (OR,
1.80 [95%CI: 0.63-5.09]), and the overweight boys with high physical fitness scores (OR,
0.18 [95%CI: 0.02-1.78]) were found.
Conclusion: Both underweight and overweight among boys and girls in Tlokwe Local
Municipality exist, and their effects on physical fitness performances were also noticed. As
such, strategic physical activity, interventions or
follow-up studies recognizing this relationship particularly in the overweight adolescents
are needed. In addition, authorities in health and education departments dealing with
adolescents should make use of this evidence base
information in policies development.
Keywords: Physical fitness, Body composition, Underweight, Overweight, Adolescents,
PAHL study
Conclusion
Our baseline study of 14 year-old high school adolescents residing within the Tlokwe Local
Municipality indicates the coexistence of both underweight and overweight. In addition, the
results show a strong association between physical fitness and body composition
especially in the overweight girls on the one hand, while on the other hand the
underweight performed better than the normal weight, and than the overweight. The
results show the same trend for boys, but not as strong. The girls were therefore more
affected than the boys. As such, from public health perspectives in a country like South
Africa with a double paradox of weight status, intervention programs with the objective of
low fat mass for overweight and fat-free mass muscular fitness for underweight
adolescents should be the start of the beginning, hence well-structured physical fitness
program for all.
References
1. Malina RM, Little BB, Buschang PH: Estimated body composition and strength, and motor performance of chronologically
undernourished rural boys in South Mexico. In Human Growth, Physical Fitness and Nutrition. Edited by Shephard RJ, Parizkova J.
Basel: Karger; 1991:119–132.
2. Parizkova J: Human growth, physical fitness and nutrition under various environmental conditions. Med Sport Sci 1991, 31:1–18.
3. Martorell R, Khan LK, Hughes ML, Grummer-Srawn LM: Overweight and obesity in preschool children from developing countries.
Inter J Obes 2000, 24:959–967.
4. De Onis M, Blossnet M: Prevalence and trends of overweight among preschool children in developing countries. Am J Clin Nutr
2000, 72:1032–1039.
5. De Onis M, Monteiro C, Acre J, Clugston G: The worldwide magnitude of protein-energy malnutrition: an overview from WHO
Global Database on Child Growth. :[www.who.int/whosis/cgrowth/bulletin.htm, 2002].
6. World Health Organisation: Global strategies on diet, physical activity and health. Geneva, Switzerland: WHO; 2004.
7. Puoane T, Steyn K, Bradshaw D, Laubscher R, Fourie J, Labert V, Mbananga N: Obesity in South Africa: the South African
59
demographic and health survey. Obes Res 2002, 10:1038–1048.
8. Department of Health: South Africa demographic health and health survey 1998. Pretoria, South Africa: Department of Health,
Medical Research Council; 1998.
9. Mamabolo RL, Kruger HS, Lennox A, Monyeki MA, Pienaar AE, Underhay C, Czlapka-Matyasik M: Habitual physical activity and
body composition of black township adolescents residing in the North-West Province South Africa. Public Health Nutr 2007,
10(10):1047–1057.
10. Van Rooyen JM, Kruger HS, Huisman HW, Shutte AE, Malan NT, Schutte R: Early cardiovascular changes in 10- to 15-year-old
stunted children: the transition and health during urbanization in South Africa in children study. Nutr 2005, 21(7):808–814.
11. Pi-Sunyer FX: Obesity and diabetes in blacks. Diab Care 1990,
13:1144–1149.
12. West KM: Overweight and cancer. Ann Intern Med 1978, 9:29–48.
13. Yip R, Scanion K, Trowbridge F: Improving growth status of Asian refugee children in the United States. JAMA 1992, 267:937–940.
14. Lobstein T, Baur L, Uauy R: Obesity in children and young people: a crisis in public health. Obes Rev 2004, 5(Suppl 1, no.1):4–104.
15. Erikson E: Identity, youth and crisis. New York: Norton; 1968.
16. Neerpal R, Renu R: Meaning in life and psychological well-being in preadolescents and adolescents. J Indian Acad Appl Psychol
2007, 33(1):31–38.
17. Saris WH, Blair SN, Van Baak MA, Eaton SB, Davies PS, Di Pietro L, Fogelholm M, Rissauen A, Schoeller D, Swinborn B,
Tremblay A, Westerterp KR, Wyatt H: How much physical activity is enough to prevent unhealthy weight gain? Outcome of the IASO
1st Stock Conference and consensus statement. Obes Rev 2003, 4:101–114.
18. Kelder SH, Perry CL, Lytle LL: Longitudinal tracking of adolescent smoking, physical activity, and food choice behaviors. Am J
Publ Health 1994, 84:1121–1126.
19. Malina RM, Bauchard C, Bar-Or O: Growth, Maturation, and Physical Activity. 2nd edition. Champaign, IL: Human Kinetics; 2004.
20. Donnelly JE, Smith B, Jacobsen MJ, Kirk MJ, Dubose K, Hyder M, Bailey B, Washburn R: The role of exercise for weight loss and
maintenance.Best Pract Res Clin Gastroenterol 2004, 18:1009–1029.
21. Blair SN, Cheng Y, Holder JS: Is physical activity or physical fitness more important in defining health benefits? Med Sci Sport
Exerc 2001,
33(Suppl 6):S370–S399.
22. Kvaavik E, Klep KI, Tell GS, Meyer HE, Batty GD: Physical fitness and physical activity at age 13 years as predictors of
cardiovascular disease risk factors at ages 15, 25, 33, and 40 years: extended follow-up of the Oslo youth study. Pediatr 2009,
123(1):e80–e86.
23. Zahner L, Puder JJ, Roth R, Schmid M, Guldimann R, Puhse U, Knopfli M, BraunFahrlander C, Marti B, Kriemler S: A school-based
physical activity program to improve health and fitness in children aged 6–13 years (“Kinder-Sportstudie KISS”): study design of a
randomized controlled trial. BMC Public Health 2006, 6:147.
24. Kovacs VA, Fajcsak Z, Gabor A, Martos E: School-based exercise program improves fitness, body composition and cardiovascular
risk profile in overweight/obese children. Acta Physiol Hungarica 2009, 96(3):337–347.
25. Perry CL, Stone EJ, Parcel GS, Ellison RC, Nader PR, Webber LS, Luepker LV: School-based cardiovascular health promotion: the
Child and Adolescent Trial for Cardiovascular Health (CATCH). J. School Health 1990, 60:406–413.
26. Twisk JW, Kemper HC, Van Mechelen W: The relationship between physical fitness and physical activity during adolescence and
cardiovascular risk factors at adult age: the Amsterdam growth and health longitudinal study. Int J Sport Med 2002, 23(Suppl 1):S8–S14.
27. Bovet P, Shamlaye C, Gabriel A, Riesen W, Paccaud F: Prevalence of cardiovascular risk factors in a middle-income country and
estimated cost of treatment strategy. BMC Public Health 2006, 6:9.
28. Myers J, Kaykha A, George S, Abella J, Zaheer N, Lear S, Yamazaki T, Froelicher V: Fitness versus physical activity patterns in
predicting mortality in men. Am J Med 2004, 117:912–918.
29. Williams PT: Physical fitness and activity as separate heart disease risk factors: a meta-analysis. Med Sci Sports Exerc 2001, 33:754–
761.
30. Beunnen CL: Biological age in pediatric sport exercise research. In Advances in Pediatric Sport Sciences. IIIth edition. Champaign,
III, USA: Human Kinetics; 1989.
31. Malina RM, Buschang PH: Growth, strength and motor performance of Zatopec children, Oaxaca, Mexico. Hum Bio 1985, 57:163–
181.
32. Kruger R, Kruger HS, MacIntyre UE: The determinants of overweight and obesity among 10- to 15-year-old school children in the
North West Province, South Africa - the THUSA BANA (Transition and Health during Urbanization of South Africa; BANA, Children)
study. Pub Health Nutr 2004, 9(3):351–358.
33. Ding Z, Jiang J, Xu J: Injury of obesity in aerobic capacity in Children. Chinese J Ped 1990, 28(6):341–343.
34. Artero EG, Espana-Romero V, Ortega FB, Jiménez-Pavón D, Ruiz JR, Vicente- Rodríguez G, Bueno M, Marcos A, Gómez-Martínez
S, González-Gross M, Moreno LA, Gutiérrez A, Castillo MJ: Health-related fitness in adolescents: underweight, and not only
overweight, as an influencing factor The AVENA study. Scandinavian J Med Sci Sport 2010, 20(3):418–427.
35. Mararey AM, Daniels LA, Boulton TJ, Cockingto RA: Predicting obesity in early adulthood from childhood and parental obesity. Int
J Obes 2003, 27:505–513.
36. Jerum A, Melnyk BM: Effectiveness of interventions to prevent obesity and obesity-related complications in children and
adolescents. Pediatr Nurs 2001, 27(6):606–610.
37. Monyeki MA, Kemper HCG, Twisk JWR, Monyeki KD, Toriola AL, Steyn NP: Anthropometric indicators of nutritional status and
physical fitness rural primary school children, South Africa. Med Sportiva 2003, 7:E95–E104.
38. Monyeki MA, Koppes LLJ, Kemper HCG, Monyeki KD, Toriola AL, Pienaar AE, Twisk JWR: Body composition and physical
fitness of undernourished South African rural primary school children. Eur J Clin Nutr 2005,
59:877–883.
39. Statistics South Africa: Community Survey, 2007, Basic Results Municipalities. South Africa: Report available on Statistics South
Africa website: www.statssa.gov.za; 2007.
40. Department of Education: National norms and standards for school funding. Government Notice 20. Pretoria: Government Gazette;
2003.
41. Marfell-Jones M, Olds T, Stewart A, Carter L: International Standards for Anthropometric assessment. International Society for the
60
Advancement of Kinanthropometry (ISAK). South Africa: Potchefstroom; 2006.
42. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH: Establishing a standard definition for childoverweight and obesity worldwide:
international survey. Brit Med J 2000, 330:1240–1244.
43. Cole TJ, Flegal KM, Nicholls D, Jackson AA: Body mass index cut offs to define thinness in chidren and adolescents: international
survey. Brit Med J 2007, 335(7612):194–197.
Monyeki et al. BMC Public Health 2012, 12:374 Page 7 of 8
http://www.biomedcentral.com/1471-2458/12/374
44. Slaughter MH, Lohman TG, Boileau RA, Horswill CA, Stillman RJ, Van Loan MD, Bemben DA: Skinfold equations for estimates of
body fatness in children and youth. Hum Biol 1988, 60:709–723.
45. EUROFIT: European test of physical fitness. Rome: Council of European Committee for Development of Sport; 1988.
46. Shang X, Liu A, Li Y, Hu X, Du L, Xu G, Li Y, Guo H, Ma G: The association of weight status with physical fitness among Chinese
children. Int J Pediatr 2010, 2010(2010):1–6.
47. Fahey TD, Insel PM, Roth WT: Fit and well: core concepts and labs in physical fitness and wellness. 3rd edition. London, UK:
Mayfield Publishing; 1998.
48. Warburton DER, Nicol CW, Bredin SSD: Health benefits of physical activity: the evidence. Can Med Ass J 2006, 174(6):801–909.
49. Beunen G, Malina RM, Ostyn M, Renson R, Simons J, Van Gerven D: Fatness, growth and motor fitness of Belgian boys 12 through
20 years of age. Hum Biol 1983, 55:599–613.
50. Malina RM, Katzmarzyk PT, Siegel SR: Overnutrition, undernutrition and the body mass index: implications for strength and motor
fitness Basel: Karger. Med Sport Sci 1998, 43:13–26.
......................................................................................
13.Douglas, S. (2010). Pro & con: Is a ‘soda tax’ a good policy to reduce obesity in the
U.S.?. The Atlanta Journal- Constitution, Retrieved from
http://www.ajc.com/news/news/opinion/pro-con-is-a-soda-tax-a-good-policy-toreduce-obes/nQdxW/
- MY WRITING
The author admits she is overweight but does not want you to notice the excess calories in
her product. But, if you getting fat – drink her low calorie soda
This quote reveals how much a person can be bought – the research is clear that coke soda
is bad for the body and MS. Douglas has no ethicsBut we’re also against obesity. That’s why we joined first lady Michelle Obama in
her goal to end childhood obesity in a generation. We’re for moderation, with
innovations like the 90-calorie mini can, zero-calorie natural sweeteners like Truvia,
and the more than 130 low- and no-calorie products we’ve introduced in the U.S.
during the past decade.
Coke gets into the act. Fearing a lose of revenuve they have innoviated low calorie and
zero calorie soda but they have not eliminated the toxins and chemicals that preserve the
drink and give it flavor. Ms. Obama can’t say or do much against coke.
........................................................................................
Article:
61
Douglas, S. (2010). Pro & con: Is a ‘soda tax’ a good policy to reduce obesity in the u.s.?.
The Atlanta Journal- Constitution, Retrieved from
http://www.ajc.com/news/news/opinion/pro-con-is-a-soda-tax-a-good-policy-toreduce-obes/nQdxW/
Like so many of us, I could stand to lose a few pounds. I know that if I do, I’ll feel better,
have more energy and, as my doctor reminds me, be healthier. Many people tell me
they’re in the same place. We eat on the run and don’t always choose a balanced diet. We
don’t get enough exercise — it seems there’s never enough time in a busy day.
It’s not a simple problem, or a simple solution. Obesity is an issue with myriad causes and
everyone in business, government and civil society should be working together to solve it.
But not everyone sees it that way. Some want to demonize us because our products have
calories. They say no one should enjoy the simple pleasure of a Coca-Cola. They say we
have no role in finding solutions. They shout at lawmakers: “Blame soft drinks! Tax soft
drinks and you’ll not only raise revenues, you’ll lower obesity rates!”
They have loud voices that can drown out the facts, which are:
A beverage tax, such as has been adopted in Arkansas and West Virginia, will not solve
obesity. Science has shown that all calories count — regardless of source — when it
comes to weight gain or loss. Soft drinks, sports drinks, sweetened waters and energy
drinks combined account for only 5.5 percent of the American diet, according to the
National Cancer Institute, which means 94.5 percent of calories come from other foods
and beverages. The two states that tax soft drinks have obesity rates that are among the
highest in the nation.
No one single food or beverage is responsible for obesity. While the volume of regularcalorie soft drinks sold declined 10 percent from 2000 to 2008, according to industry
publication Beverage Digest, obesity trends increased during that same period, according
to the Centers for Disease Control and Prevention.
A beverage tax will eliminate jobs and hurt the economy. A beverage tax would be
regressive and hit hardest people who can least afford it. The beverage industry directly
employs more than 220,000 people in the United States (including nearly 9,500 in the
Coca-Cola System in Georgia), and, through supporting industries, an additional 3 million
people. A beverage tax will cost jobs. Can we really afford that?
The good news is that most Americans can recognize a bad idea. A recent CBS poll found
that 60 percent oppose a food tax. And nearly 9 in 10 say obesity can be controlled
through diet and exercise, not taxation.
We’re against beverage taxes, too. But we’re also against obesity. That’s why we
joined first lady Michelle Obama in her goal to end childhood obesity in a
generation. We’re for moderation, with innovations like the 90-calorie mini can,
zero-calorie natural sweeteners like Truvia, and the more than 130 low- and nocalorie products we’ve introduced in the U.S. during the past decade.
We’re for transparency, as the first beverage company to commit that nearly all our
packages will have calories displayed on the front label. We’re for education, through
support for organizations such as the American Academy of Family Physicians, which is
providing consumers science-based information about sweeteners.
And we’re for active lifestyles, with more than 6 billion Diet Coke packages helping the
National Heart, Lung and Blood Institute remind women about the importance of staying
active and maintaining a healthy weight, and our support of physical activity initiatives like
62
Exercise Is Medicine.
Obesity is a serious problem. But we can overcome it if we all work together. At CocaCola, we’re playing our part in helping develop and support workable solutions. Let’s stop
pointing fingers and start working together productively. I think we’ll discover we burn more
calories that way.
Sandy Douglas is president of Coca-Cola North America.
........................................................................................
141. A brief history of usda food guides. (2011). Retrieved from
http://www.choosemyplate.gov/foodgroups/downloads/MyPlate/ABriefHistoryOfUSDAFoodGuides.pdf
-MY WRITING
-This article is a summary of the knowledge about nutrition that the USDA (US
Department of Agriculture) has created for the public. The requirements of calories, the
need to eat less sugar and fat and the value of balancing a diet with fresh fruit and
vegetables was slow to appear on the national scene.
-There has bee a series of pictures that suggest the best foods to eat. The first was focused
on protecting children by making sure they ate food from all the food groups.
-Each time the USDA produces a graphic they are addressing a specific need – caloric
needs, example less meat and less sugar more grain and vegetables
-The latest stands on the shoulders of al the knowledge the USDA has learned and is the
best one so far that tries to address ways to eat that can prevent obesity.
........................................................................................
Article:
A brief history of USDA food guides. (2011). Retrieved from
http://www.choosemyplate.gov/foodgroups/downloads/MyPlate/ABriefHistoryOfUSDAFoodGuides.pdf
63
The US Department of Agriculture recommendations for balanced and healthy meals
began in 1916. The guidelines’ were suggestions for “protective food”, especially for
children. In the 1970’s the concept of the four food groups was created. Even though
these four groups were presented to the public the USDA did not include guidance on
appropriate fats, sugars, and calorie intake.
By 1984 the “Food Wheel” was developed with five subdivisions of food. By 1992, the
Food Pyramid Daily guide added caloric intake at three levels. Calories were
recommended for men, 2000 calories , women, 1200 calories, and children (1600 - 2200).
In the mid 1980’s, the wheel was renamed the “Food Guide Pyramid” and it was also
adopted by the Red Cross into their programs.
In 2005, the” Food Pyramid” was updated. It now included 12 caloric levels,
recommends eating in moderation, cooking and eating with healthy oils and encouraged
physical activity.
In 2010, First Lady, Michele Obama introduced the Food Plate. The purpose is to grab
consumers’ attention with an easy to see visual cue Icon. The categories are broadprotein has a smaller place than vegetables or friut, grain has one fourth of the plate,
vegetables have the biggest place on the plate, fruit has the second biggest place, and a
small circle Is placed to next the plate signifying a glass or milk or container of yogurt. The
plate allows cultural, ethnic and poorer people to fill in the category with food acceptable
and affordable. For example, the protein part of the plate can be – lean meat, red, white or
black beans, lentils, chick peas or tofu. Ms. Obama recommended we eat food that is in
season and grown locally. These are recommendations that will be comfortable for me to
teach to my students.
In 1984 the government developed a “Food Wheel”. This approach divided food into a
pyramid with 5 levels. The wheel suggested foods to eat that would provide an adequate
amount of good nutrition. In 1992, the : A Pattern for Daily Food Choices
Total diet approach concluded goals for both nutrient adequacy and moderation Five food
groups and amounts formed the basis for the Food Guide Pyramid
Daily amounts of food provided at three calorie levels First illustrated for a Red Cross
nutrition course as a food wheel1992: Food Guide Pyramid
1916 to 1930s: “Food for Young Children” and “How to Select Food”
Established guidance based on food groups and household measures Focus was on
“protective foods”
1940s: A Guide to Good Eating (Basic Seven)
Foundation diet for nutrient adequacy Included daily number of servings needed from each
of seven food groups Lacked specific serving sizes Considered complex
1956 to 1970s: Food for Fitness, A Daily Food Guide (Basic Four)
Foundation diet approach—goals for nutrient adequacy Specified amounts from four food
groups Did not include guidance on appropriate fats, sugars, and calorie intake
1979: Hassle-Free Daily Food Guide
Developed after the 1977 Dietary Goals for the United States were released Based on the
Basic Four, but also included a fifth group to highlight the need to moderate intake of fats,
sweets, and alcohol
1984: Food Wheel: A Pattern for Daily Food Choices
Total diet approach concluded goals for both nutrient adequacy and moderation Five food
groups and amounts formed the basis for the Food Guide Pyramid
Daily amounts of food provided at three calorie levels First illustrated for a Red Cross
nutrition course as a food wheel1992: Food Guide Pyramid
64
Total diet approach—goals for both nutrient adequacy and moderation Developed using
consumer research, to bring awareness to the new food patterns Illustration focused on
concepts of variety, moderation, and proportion Included visualization of added fats and
sugars throughout five food groups and in the tip
Included range for daily amounts of food across three calorie levels
2005: MyPyramid Food Guidance System
Introduced along with updating of Food Guide Pyramid food patterns for the 2005 Dietary
Guidelines for Americans, including daily amounts of food at 12 calorie levels Continued
“pyramid” concept, based on consumer research, but simplified illustration. Detailed
information provided on website “MyPyramid.gov”
Added a band for oils and the concept of physical activity Illustration could be used to
describe concepts of variety, moderation, and proportion
2011: MyPlate
Introduced along with updating of USDA food patterns for the 2010 Dietary Guidelines for
Americans Different shape to help grab consumers’ attention with a new visual cue Icon
that serves as a reminder for healthy eating, not intended to provide specific messages
Visual is linked to food and is a familiar mealtime symbol in consumers’ minds, as
identified through testing “My” continues the personalization approach from MyPyramid
References
The Article is referenced with these articles:
Welsh, S., Davis , C., & Shaw, A. (1992). A brief history of food guides in the United States. Nutrition
Today, 6(11),
Welsh S, Davis C, Shaw A. (1992). Development of the Food Guide Pyramid. Nutrition Today, 12(23),
Haven, J., Burns, A., Britten, P., & Davis, C. (2006). Developing the consumer interface for the mypryamid
food guidance system. Journal of Nutrition Education and Behavior, 38, S124-S135.
........................................................................................
15Neuman, W. (2011, 05 02). Nutrition plate unveiled, replacing food pyramid. The New
York Times. Retrieved from
http://www.nytimes.com/2011/06/03/business/03plate.html
-MY WRITING
-one of the most significant negative comments about MyPlate is that it is not specific
65
enough about the definition of protein. There are proteins in dairy and grains that should be
included in the protein part of the picture.
-as I did my research, I noted that the protein content of beans, lentils, corn, tofu and milk
was explained – but not on the icon.
The USDA (US Department of Agriculture is going to spend 2 million trying to educate the
public about the need to eat more fruit and vegetables.
........................................................................................
Article:
Neuman, W. (2011, 05 02). Nutrition plate unveiled, replacing food pyramid. The New
York Times. Retrieved from
http://www.nytimes.com/2011/06/03/business/03plate.html
Nutritionists often criticized the food pyramid, which was first advanced in 1992, for being
misleading or hard to understand. Some gave the plate cautious praise on Thursday. “It’s
better than the pyramid, but that’s not saying a lot,” said Marion Nestle, a professor of
nutrition at New York University.Dr. Nestle praised the plate for being generally easy to
understand, but she said that labeling a large section of the plate “protein” was confusing
and unnecessary, because grains and dairy products also are important sources of protein
and most Americans get far more protein than they need.But she said the emphasis on
fruits and vegetables was a significant step.“Americans aren’t used to eating this way, so
this is a big change,” Dr. Nestle said. The plate was created by the Agriculture Department
with advice from the first lady’s anti-obesity team and federal health officials. The
Agriculture Department said that it had conducted focus groups with about 4,500 people,
including children, as it developed the plate. The project, with the Web site and related
educational materials, cost about $2 million. That money will also help pay for an
educational campaign about the plate over the next year, officials said.
........................................................................................
16.Presidential youth fitness program adopts the fitnessgram assessment; new fitness
program teaches skills for lifelong physical activity. (2012, 09 11). PRWeb.
Retrieved from: http://www.prweb.com/releases/2012/9/prweb9892195.htm
66
-MY WRITING
- There is a growing body of evidence that suggests a link between physical activity and
improved academic success.
- the President’s Council on Fitness, Sports and Nutrition (PCFSN)
adopts the FITNESSGRAM
. Unlike the older President’s Council Fitness Test, FITNESSGRAM® helps minimize
comparisons between children and instead supports students as they pursue personal
fitness goals for lifelong health
-the FITNESSGRAM emphasizes health over performance and the program will provide
lesson plans professional and materials to help physical educators effectively implement
the program.
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Article:
Presidential youth fitness program adopts the fitnessgram assessment; new fitness
program teaches skills for lifelong physical activity. (2012, 09 11). PRWeb.
Retrieved from: http://www.prweb.com/releases/2012/9/prweb9892195.htm
. Champaign, IL (PRWEB) September 11, 2012
Physical activity is critical to children’s health and well-being. Research shows that
children with better health are in school more days, are better able to learn, have higher
self-esteem and are at lower risk for developing chronic diseases. In an effort to help get
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kids moving, the President’s Council on Fitness, Sports and Nutrition (PCFSN) is
launching the Presidential Youth Fitness Program this month. The new school-based
program will replace the President’s Council Youth Fitness Test, which has been
implemented in schools since 1985.
Although the President’s Council Fitness Test evolved through the years, that test used
physical fitness data from a 1985 National School Population Fitness Survey. The test only
measured how students performed certain activities compared to peers and reported little
about students’ actual health.
Based on the latest science, the PCFSN has teamed up with leaders in the fields of
physical education, fitness, and health including the American Alliance for Health, Physical
Education, Recreation and Dance (AAHPERD), the Amateur Athletic Union (AAU), the
U.S. Centers for Disease Control and Prevention (CDC), and The Cooper Institute to
launch the Presidential Youth Fitness Program, a voluntary school-based program that
promotes health and regular physical activity for America’s kids.
“Schools can play a critical role in inspiring a love of physical activity,” says Shellie Pfohl,
Executive Director of the President’s Council on Fitness Sports and Nutrition. “There is a
growing body of evidence that suggests a link between physical activity and improved
academic success.”
The Presidential Youth Fitness Program has adopted FITNESSGRAM® as its
assessment. FITNESSGRAM® in partnership with NFL PLAY 60 is a health-related,
criterion-based assessment developed by The Cooper Institute. Unlike the President’s
Council Fitness Test, FITNESSGRAM® helps minimize comparisons between children
and instead supports students as they pursue personal fitness goals for lifelong health.
The assessment measures health-related fitness through a variety of items designed to
assess cardiovascular fitness, muscle strength, muscular endurance, flexibility, and body
composition. The Presidential Youth Fitness Program has also adopted Physical Best for
professional development. Human Kinetics publishes FITNESSGRAM® for The Cooper
Institute and Physical Best for AAHPERD.
The Presidential Youth Fitness Program represents the beginning of a new era in youth
fitness assessment, one that emphasizes health over performance. In addition, the
program provides options for professional development and materials to help physical
educators effectively implement the program. The program also provides information to
help parents understand the benefits of regular activity for their children.
More information on the Presidential Youth Fitness Program can be found at
http://www.presidentialyouthfitnessprogram.org.