MAHPERD Journal 01

The Offi cial Journal of the Mississippi Association of Health, Physical Education, Recreation & Dance

MAHPERD Journal

Volume 01, Issue 01

MAHPERD Editorial Board

John Alvarez

Brandi Shappley

Kathy Tucker

Shane McNeil

Does a Relationship Exist Between Fifth Grade Students’ BMI and GPA

Dock Daniel

Submitted April 21, 2011

Jackson State University Graduate School

Candidate


Grade Point Average & Body Mass Index

ABSTRACT

There is much discussion about the obesity epidemic in our Nation as well as

the academic accountability of our schools. With increased demands put on

schools to perform well on high stakes tests many schools have decreased the

amount of time dedicated to non tested subjects and have reduced the amount

of physical activity that is provided to students thus contributing negatively to

the obesity crisis. Some studies are making a connection between fi tness levels

and academic performance, which could reduce obesity numbers and contribute

to increased academic achievement, which would be a win-win situation for

everyone.

This study examined the grade point average and body mass index numbers

from 121 fi fth grade students at the researchers’ school to determine if there

exists a difference between students with a healthy BMI and those with a high

BMI and their GPA. The fi ndings of this study could be used to help educate

parents, school board members, and administrators about the importance and

impact of healthier students and academics.

Keywords: academic achievement, body mass index, grade point average, fi tness levels, obesity

MAHPERD Journal vol 1 issue 1 | Dock Daniel


INTRODUCTIONMuch discussion can be heard from people who think that our current educational systems are producing young adults that are non-career ready. Many think that we have “watered” down our accountability systems of our schools and they are not teaching young people the basics that they need to be productive workforce employees. We are also at a time in our history that will see this generation of young people become the fi rst to lower life expectancy in our nation for the fi rst time due to obesity related health issues. Are these areas of academics and health related? Some research suggests they might be.

OUR CHANGING EDUCATIONAL SYSTEM Since the 1950’s and the sputnik era the American Government has played an ever-changing and increasing role in shaping our educational systems. In the late 50’s the Russians’ raced America to see which nation would get the fi rst person to the moon. The fact that another country was threatening to beat us in something was enough to cause massive change. The public out-cry for our educational system to focus on math and science was enough for Congress to pass the National Defense Education Act in 1958 (Bybee 1997, Rutherford 1994). In 1983 the National Commission on Excellence in Education released a report titled A Nation at Risk. This report stated that America’s public education system was “a rising tide of mediocrity” (Wiles and Bondi 2011). An onslaught of achievement tests to compare us to other nations began and resulted in accountability legislation. No Child Left Behind (U.S. Dept., 2001) in the early 2000’s brought accountability of schools into greater focus with high stakes testing and failing schools being taken over by that schools state Department of Education. At present time we have changes taking place in our education system that are coming about because of fi nancial cutbacks resulting in reduced personnel, larger class sizes, and no new supplies.

THE DECLINE OF NON ACCOUNTABLE SUBJECTS. With each new reform in our educational system we have also seen a direct impact on reduction of what is termed “non-essential subjects”. These are subjects that are not involved in the high stakes testing game and therefore do not have an impact on the school or districts image as a result of the students test scores. These subjects that are often cut back or eliminated altogether are physical education, art, music, home economics, just to name a few. As a result we have students who are sitting for longer periods of time and being taught to regurgitate information on test day and not much more. The message of our educational system is clear – we want students to perform great on our end of the year tests so that our school will look good. These messages come through loud and clear in the actions of superintendents, school principals, and school boards as well as legislative decisions.

In the past two decades there has been a three-fold increase in overweight conditions of our children and adolescents (Lohan et al. 2004). It is safe to say that we have greatly reduced the amount of physical activity that students get during their school day and this has contributed to the obesity problem. It is also safe to say that all children in our nation must attend school by law, therefore one could conclude that to best tackle the issue of childhood obesity the school setting would be the best and most extensive place to do that. At no other time in the history of our world have we humans been in poorer health. America is the most obese nation in the world and the state of Mississippi has the most concentrated population of obese humans in America. So, one could assume that nowhere else in the world will one see more overweight and obese humans than where we live. Obesity is calculated by using body mass index, a gender specifi c calculation of height/weight and age (2-20 years of age) of an individual. According to the Centers for Disease Control (CDC), overweight is defi ned as someone who has a BMI of 25 or higher and obese is someone who has a BMI of 30 or higher. In the past 30

years the number of obese children ages 2-5 has doubled, children ages 6-11 has tripled, ages 12-19 has more than tripled. According to the National Health and Nutrition Examination Survey (2007) 1-in-6 American children ages 2-19 are obese. Obese children are more likely to become obese adults, which can lead to an increase in numerous preventable health problems such as, type 2 diabetes, coronary heart disease, various cancers, hypertension, dyslipidemia, stroke, liver and gallbladder disease, sleep apnea and respiratory problems, osteoarthritis, and gynecological problems. Obesity related problems has recently overtaken smoking as the number one preventable cause of death. In the past 30 years that childhood obesity has been on the rise, fast food restaurants have been on the rise along with the amount of cheaply produced fast prepared meals, the amount of physical activity has declined in the form of sedentary activities becoming prevalent such as cable television offering hundreds of channels to chose from, video games, computers, and the amount of schools offering daily quality physical education has declined (American Cancer Society). Our students are dealing with an enormous amount of pressure to perform well on standardized tests and are not given the recommended time for daily physical activity during their school day resulting in stressed out students. New brain research is unfolding every week as scientists learn new things about how our brain works. One of the new understandings is the benefi t that exercise gives our brain, it replenishes stale oxygen with fresh oxygen and glucose for energy. Through imaging studies scientists have seen exercise increase blood volume in the dentate gyrus, a constituent of the hippocampus, which is deeply involved in memory formation (Medina 2008). That is pretty signifi cant information teachers and school offi cials need to know.

STATEMENT OF THE PROBLEM Our educational system needs to do a better job of focusing on the whole student and not just specifi c subject areas. When we fail to focus on the student as a whole we create uneven adults resulting in instability either mentally, physically, or emotionally, all of which can be addressed by teaching the whole child during the school years. If we increase the amount of physical education opportunities for students we can increase their energy/concentration levels, changes in motor control and skill affecting increased self-esteem/confi dence, and better behavior, which may all go back to the original reason why physical activity was cut in the fi rst place; to support cognitive learning (Scheuer). The process of determining the effect of physical education on academic achievement is complex and requires control over many extraneous variables. A limited number of in-depth studies have been done on this correlation and have found there to be a positive relationship between higher fi tness levels and higher academic success. This study is designed to discover if a relationship exists between 121 fi fth grade student BMI and GPA scores.

PURPOSE OF THE STUDY The purpose of this study was to determine if there is a relationship between students’ body mass index (BMI) numbers and their grade point average (GPA). If students that are overweight or obese have a lower academic performance than students who have a healthy weight then our academic institutions need to spend quality time examining this connection. Signifi cance of the study

The results of this study will be helpful to school leaders as they initiate programs that can help correct the obesity problems of our youth. This information could be used to educate school boards and administrators that improving BMI numbers through increased physical activity and better nutrition not only contributes to decreasing the obesity epidemic and creates more fi t humans, but it also could lead to improved academics. This could result in quality physical education beginning to increase and increased emphasis on the students as a whole and lead to a more coordinated and holistic approach to our students in our educational system.

RESEARCH HYPOTHESIS



The following null hypothesis helped guide this study. There will be no signifi cant difference between the overweight/obese group and the healthy weight groups’ grade point averages.

RESEARCH PROCEDURE The researcher collected the height, weight, age, and gender of 121 fi fth grade students at the school where the researcher teaches. This information was then put into a Polar Tri-fi t computer program which calculates the BMI for each student and determines them to be a healthy weight, overweight, or obese. GPA is calculated by using the existing computer software program SAM 7 at the researchers’ school. The homeroom teacher inputs homework, quizzes, and tests given in the subjects of science, language arts, math, social studies, and reading. The researcher collected the GPA and the BMI for each student and was able to create two groups based on the students BMI. One group was the group determined to be overweight or obese by their BMI and the other group consisted of the students who have been determined to be at a healthy weight according to their BMI. The researcher then computed the GPA’s for the two different groups to determine if there is a difference between the two.

POPULATION AND SAMPLE The researcher evaluated the BMI and GPA of 121 fi fth grade students. The students attend a public school in a suburban setting. The school houses third, fourth, and fi fth grade students, and is rated at a Successful rating according to the MCT II school rating system. This population of students attends physical education class one time each week for forty minutes and an additional forty minute class every other week. Method of data collection The researcher collected the height and weight of the students during their normal PE class, something that is done twice each year for fi tness testing. This information was then manually put into a Polar Tri-Fit program, which already has the students gender and birth date recorded for calculating purposes. The GPA is determined by the schools SAM 7 software program from the students’ daily homework, quizzes and test grades that the home room teacher collects and puts into the system to be calculated. Once the researcher had all of the students BMI and GPA numbers they were manually put into a T-test statistics program to determine the statistics.

STATISTICAL ANALYSIS The researcher used a total of 121 fi fth grade students. The students BMI numbers were calculated and they were given a BMI number, this BMI number determined if they were at a healthy weight for their height, age, and gender or at an overweight or obese weight for their height, age, and gender. After examination of their BMI the students were divided into one of two groups. One group had BMI numbers indicating they were overweight or obese and the other group was determined to be at a healthy weight according to their BMI. The overweight or obese group numbers were 45 in all and the numbers of students in the healthy BMI group were 76. Once the two BMI groups were created the GPA of the student was matched with their BMI and the two GPA lists could be examined. The researcher was able to input the two groups’ GPA scores into a t-test calculator program to run the stats. The mean GPA for the 45 students with an overweight or obese BMI was 85.6 and the mean GPA for the 76 healthy BMI group was an 84.7 (these statistics are represented in Table: 1). Based on the mean scores the overweight or obese group has a better GPA by .9. The P-value was 0.5258, higher than 0.05 so the researcher failed to reject the null hypothesis. A slight difference between the groups does exist, yet it is not a signifi cant one according to the t-test scores.

TABLE:1 N Mean BMI Mean GPA SD

Healthy BMI group 76 18.7 84.7 8.12

Overweight group 45 27.3 85.6 6.97

Since the researcher did not discover a signifi cant difference in the groups the groups were broken down into small sub-groups. The overweight BMI group consisted of 28 boys who had a mean BMI of 27.3 with a range of 25.1-38.4, and a mean GPA of 84.0, there were 17 girls who averaged a 27.3 BMI with a range of 25.3-33.6 and an 88.9 GPA. The healthy BMI group consisted of 36 boys with a mean BMI of 18.2 with a range of 14.6-22.6 and a GPA of 82.4 and 40 girls who averaged a 19.3 BMI with a range of 14.2-24.1 and 86.9 GPA; these score are represented in Table 2.

TABLE:2 N Mean BMI Mean GPA Range

Healthy BMI Boys 36 18.2 82.4 14.6-22.6

Healthy BMI girls 40 19.3 86.9 14.2-24.1

Overweight BMI Boys 28 27.3 84.0 25.1-38.4

Overweight BMI Girls 17 27.3 88.9 25.3-33.6

Upon reviewing the numbers of the different groups, some alarming information was uncovered. Overall the boys’ total numbers are 64, 36 in the healthy BMI group and 28 in the overweight/obese group. This indicates that 43% of our fi fth grade boys are overweight or obese. The girl’s total numbers are 57, 40 in the healthy BMI group and 17 in the overweight/obese group. This indicates that 30% of our fi fth grade girls are overweight or obese. These numbers indicate high overweight or obesity in our fi fth grade boys, this could lead to major health problems or low quality of life if this is not addressed.

DEFINITION OF TERMS Body Mass Index (BMI) is defi ned by the Centers for Disease Control as reliable indicator of body fat as a value calculated from a person’s weight and height. No Child Left Behind Act (NCLB) is the federal program and legislation affecting kindergarten through high school. NCLB is built on four principles such as accountability, choices for parents, greater local control and fl exibility, and an emphasis on scientifi c research when making education policy

Obesity is defi ned by the Centers for Disease Control as an adult having body mass index (BMI) greater than or equal to 30.

Overweight is defi ned by the Centers for Disease Control as an adult having a body mass index (BMI) from 25 to 29.9.

Review of Literature In 300 B.C., Herophiles (the “father of anatomy”) stated, “When health is absent, wisdom cannot reveal itself, art cannot become manifest, strength cannot be exerted, wealth is useless, and reason is powerless” (Physical Best Teacher’s Guide). This is from over two thousand years ago yet we still are in need of justifying physical health as important. There have been



numerous studies done in recent years that have challenged the notion of physical fi tness not being an integral part of students’ educational experience. Physical fi tness and testing is done through many different venues. Some require no equipment and others are done in state of the art laboratories. Most of the studies involve some sort of simple fi tness tests such as FITNESSGRAM or the President’s Physical Fitness Challenge as a whole or in sections. Likewise different types of academic standards are used, GPA’s, exams, and state standardized tests. One such study done in California used 884,715 students from grades 5, 7, and 9. It used the FITNESGRAM physical test and compared them to reading and math scores of the Stanford Achievement Test 9th edition and discovered that as overall fi tness scores improved mean achievement scores also improved (Grissom, J. 2005).

It has been determined that taking time from physical education does not result in more learning in other areas, but it does detract from accomplishing important physical education goals. Studies have shown that physical education enhances academic performance (Sallis et al., 1999; Shepard, Lavallee, Volle, Labarre, & Beaucage, 1994, 1997) and does not have a negative effect on classroom academics (Dwyer, Coonan, Leitch, Hetzel, & Baghurst, 1983; Sallis et al., 1999). Research has shown that physical activity sessions as short as 30 minute physical education classes with children and 20 minutes with college students has increased cognitive performance (Le Masurier 2006). A study done by a second grade teacher who allowed her students to exercise vigorously for 30 minutes every day showed signifi cant gains in test scores compared to the other classes who only went to pe class for a total of 50 minutes every six weeks (Baskshi 2008), thus showing that reduced time to academics did not affect test scores. Some studies have connected the positive health benefi ts from physical activity to improved academics. Some of the benefi ts from physical activity are improved fi tness levels, reduced BMI, decrease in chronic disease, outlet for stress which can lead to better relationships, improved mood, more likely to try new things and gain new experiences, decline in drug use, and improved self-esteem (Smith, Nicole 2009). It is believed that these factors can very likely result in higher academic standards and achievement. One such study done with third graders found results that indicated the BMI of students, as well as the opportunity for physical activity within the school day affected the students’ performance in both reading and mathematics achievement (Byrd 2007).

RESEARCH METHODOLOGY The researcher examined 121 fi fth grade students at the school were the researcher teaches because of ease of access and to better inform the fi fth grade teachers of the results. The researcher only looked at BMI numbers to determine which group the students would be placed in, the overweight/obese BMI group or the healthy BMI group. Once students were placed into one of the two BMI groups the researcher was then able to examine the GPA of the students. The researcher did not fi nd a signifi cant difference between the two BMI groups and their GPA. The researcher then broke the groups down into groups based on gender to examine the breakdown of BMI and GPA to determine if any differences could be discovered. These were the only criteria of the study; the researcher did not break down statistics based on race, socioeconomic status or any other factors outside of BMI and GPA, no standardized test scores were used.

LIMITATIONS OF THE STUDY Limitations of this study were many in number. This study did have a time limit on it due to the fact that this research was done for graduate course work in the researchers’ class. This time constraint limited using more in-depth methods of examining the relationship between BMI and GPA. Most studies that have determined that a relationship does exist between high fi tness levels and lower academic achievement have used standardized test results and not GPA. The researcher would have had to

wait until the standardized test scores came back to the school in early July to use this method. The researcher examined only the BMI and not fi tness levels as a whole, such as Fitness Gram or The President’s Physical Fitness Challenge, again time did not allow for this. BMI is a fairly accurate measurement to assess peoples overall state of fi tness, however it is most accurate on pre-pubescent children rather than after the stages of puberty have been reached. This study is also limited to fi fth grade students.

Another limitation of the study was that only the amount of physical education for physical activity is given. The amount of time the students spend participating in vigorous activity outside of school or during recess is not considered but does have an overall impact on the students individual BMI as does the students diet.

CONCLUSIONS President John F. Kennedy once warned in a 1960 Sports Illustrated article that our Nation was becoming soft and this would lead to undesirable outcomes. He stated “But the harsh fact of the matter is that there is also an increasingly large number of young Americans who are neglecting their bodies—whose physical fi tness is not what it should be—who are getting soft. And such softness on the part of individual citizens can help to strip and destroy the vitality of a nation.” He went on to connect the body and mind “The relationship between the soundness of the body and the activities of the mind is subtle and complex. Much is not yet understood. But we do know what the Greeks knew: that intelligence and skill can only function at the peak of their capacity when the body is healthy and strong; that hardy spirits and tough minds usually inhabit sound bodies.” The current research was set to learn more about the connections of the body in fi tness and the mind in academics. Although this study did not fi nd a signifi cant difference between the fi fth grade students BMI and GPA the researcher believes that having a fi t body does impact the self-confi dence and mental outlook of our students and a more confi dent student is better prepared to handle life’s adversity.

Our educational system leaders need to begin to seriously question our current focus and role in what is most important in our students lives. In the past decades our academic standards have slipped and our achievements as a nation have not really increased like they were hoping and our health and overall well being has slid downhill at a rapid clip. Our educational systems must recognize that the body and mind are connected and need we need to ensure that students are given the best opportunity for achieving all that they can.

RECOMMENDATIONS With our Nation facing unknown territory in relation to children and obesity it is strongly recommended that our current educational system look for ways to increase physical activity and education of our students K-12. By examining more closely the relationship between physical fi tness levels and the impact that physical activity has on the brain and the way we learn we could begin to embrace more time for students to achieve moderate to vigorous physical activity in their school day rather than reduce it and focus more time on academics only. Some studies do show that increased time devoted to pe and physical activity does not adversely affect academics. More research is needed to better determine the role that physical fi tness levels have on academic performance. Particular attention should be devoted to lower performing school districts and poverty areas to determine the relationship between improved fi tness levels and activity time to academic performance.

It would be recommended that the researcher for this study look into why the boys have a much higher incidence of overweight and obesity. The researcher has seen a sharp increase in the prevalence of overweight and obese students at this school. Four years ago the average was 33% and now it is 37%. If the 37% of students who have a BMI indicating they are overweight or obese had a better BMI number would their grades be improved if they felt better physically and had higher self-confi dence? It is also



recommended that the researcher share this information with teachers, administrators and parents to better inform everyone of the high prevalence of overweight and obese students.

REFERENCES Bybee, Rodger W. (1997). The Sputnik Era: Why is this educational

reform different from all the other reforms? Prepared for the

Symposium “Refl ecting on Sputnik”. Washington, D.C.

Wiles, Jon W., Bondi, Joseph C. (2011). Curriculum

Development (eighth edition). Pearson Higher Ed.

Byrd, Jimmy (2007). The Impact of Physical Activity and Obesity

on Academic Achievement Among Elementary Students.

Sallis, JF, McKenzie, TL, Kolody, B., Lewis, M., Marshall, S., Rosengard P.(1999).

Effects of health-related physical education on academic achievement: SPARK.

Research Quarterly for Exercise and Sport. 1999. Vol. 70, No.2, pp.127-134

Lohan, TG., Going S.B., and Metcalf, L. (2004). Seeing

ourselves through the obesity epidemic. President’s Council

on Physical Fitness and Sports Research Digest.

U.S. Department of Education. (2001) Public Law print of

PL 107-110, the No Child Left Behind Act of 2001.

Rutherford, James B. (1994). Sputnik and Science Education.

American Association for the Advancement of Science.

Medina, John. (2008). Brain Rules. Pear Press, Seattle, Washington.

Smith, Nicole J.; Lounsbery, Monica. (2009). Promoting physical

education: the link to academic achievement, study data

can make your advocacy efforts more compelling. JOPERD –

Journal of Physical Education, Recreation and Dance.

Le Masurier, G., and Corbin, C. (2006). Top ten reasons for Quality Physical

Education. JOPERD – Journal of Physical Education, Recreation and Dance.

Bakshi, Lisa. (2008). Will CrossFit Make American Kids Smarter?

The CrossFit Journal. Active Living Research, A national

program of the Robert Wood Johnson Foundation. (2007).

Active Education- Physical Education, Physical

Activity and Academic Performance.

Grissom, James B. (2005). Physical Fitness and Academic

Achievement. Journal of Exercise Physiology online (ASEP).

Garrison, Lori; Yant. Lora; et.al. (2010). Clearwater R-I School

District Results and Impact of the Tiger Fitness Challenge. A

study funded by the Missouri Foundation for Health.

Castelli, Darla M. et. al. (2007). Physical Fitness and Academic Achievement

in Third- and Fifth-Grade Students. Journal of Sport and Exercise Psychology.

Scheuer, Leslee J.; Dr. Mitchell Debbie. Does Physical Activity

Infl uence Academic Performance? University of Central Florida.

Centers for Disease Control and Prevention: National Health & Nutrition

Examination Survey (2007) website: http://www.cdc.gov/nchs/nhanes.htm

Shepard, R. J., Lavallee, H., Volle, M., LaBarre, R,. &Beaucage,, C.

(1994). Academic Skills and Required Physical Education: The

Trois Rivieres Experience. CAHPER Research Supplement.

Shepard, R. J., Lavallee, H., Volle, M., LaBarre, R,. &Beaucage,,

C. (1997). Curricular Physical Activity and Academic

Performance. Pediatric Exercise Science.

Kennedy, John F. (1960). The Soft American, Sports

Illustrated, December 26, 1960.

Christina L.L. Martin, Ph.D., Corresponding authorTroy UniversityAssistant Professor of Sport and Fitness ManagementDepartment of Kinesiology and Health Promotion Collegeview 155Troy, AL 36082O: (334) [email protected]

Nancy M. Speed, Ph.D.School of Human Performance and Recreation, The University of Southern Mississippi, Hattiesburg, [email protected]

Trenton E. Gould, Ph.D.School of Human Performance and Recreation, The University of Southern Mississippi, Hattiesburg, [email protected]

Physical Education Content Knowledge and Physical Activity BehaviorsExamining a Link between Knowledge,

Activity, and Behaviors of Mississippi High

School Students School Students

Submitted April 21, 2011

Jackson State University Graduate School

Candidate

PE Content Knowledge and Physical Activity


ABSTRACT

Background: This study investigated physical education content knowledge,

physical activity behaviors, and body mass indexes of 386 Mississippi ninth

(n=236) and twelfth (n=150) grade students with a goal of establishing

evidence-based needs to modify physical education curricula. Methods: An

exploratory design was applied; and, a stratifi ed, random, statewide sample was

obtained. Results: Results indicated a signifi cant, direct relationship existed in

the Assessment of Sub-disciplinary Knowledge in Physical Education: Exercise

Physiology (Ask-PE:EXP) scores and scores from the Modifi able Activity

Questionnaire for Adolescents (MAQ-A) for ninth and twelfth graders. Findings

also suggested that physical education content knowledge was more likely to

contribute to twelfth graders’ reported physical activity scores versus ninth

graders’ scores. However, ninth graders were more active than twelfth graders.

As a whole, results indicated that Mississippi ninth and twelfth graders’ average

content knowledge score was lower (M = 53%, SD = .22) than students in 16

other states (M = 62%, SD = 7.65). Further, students who scored higher were

more likely to be active on a weekly basis compared to those who scored lower.

Conclusions: Evidence-based recommendations were made for Mississippi high

schools to revise the physical education curriculum.

Manuscript Type: Original ResearchKey Words: Relationship of BMI, Activity and PE Knowledge



INTRODUCTIONRecently, the Trust for America’s Health Foundation (TFAH) revealed that 85% of Americans believe obesity is an epidemic1. Increasing prevalence rates, which can be defi ned as ratios representative of the number of occurrences of a disease at a given time period to the number of units at risk in the population2, have helped to justify an obesity “epidemic”. According to the Center for Disease Control and Prevention (CDC)3, the obesity trend has increased dramatically. For example, the CDC reported that in 1991 four states, Louisiana, Michigan, Mississippi, and West Virginia, had obesity prevalence rates of 15% to 19% and no states had rates at or above 20% 3(¶1). As of 2005, the CDC reported that four states had obesity prevalence rates less than 20%, while 17 states had prevalence rates equal to or greater than 25%, with three of those states, Louisiana, Mississippi, and West Virginia, having prevalence rates equal to or greater than 30% 3(¶3). In 2005 and 2006, the state of Mississippi was listed at the bottom of the healthiest states, ranking 49th and 50th respectively 1, 4. Additionally, Mississippi has been labeled as the “fattest state” 1, 3 and was noted as the fi rst state to acquire an adult obesity prevalence rate of greater than 30% 5. In an attempt to combat Mississippi’s health issues Senate Bill 2369, the “Mississippi Healthy Students Act” 6 was passed, paving the way for more time in physical education (PE). Specifi cally, the bill requires schools, effective academic year 2007, to provide at least 150 minutes of physical activity-based instruction as well as 45 minutes of health education per week for students in kindergarten through eighth grade 6(¶4). Additionally, the bill requires that students in ninth through twelfth grades complete one-half of a Carnegie unit, or approximately 60 hours, of physical education or related activity to meet graduation criterion 6(¶4). Though this act is movement in the right direction to contend with health issues, the plan has one major gap. Students in grades nine through twelve are only required to take one-half of a Carnegie unit in physical education, (i.e. complete 60 hours of PE from the time they enter ninth grade through their fi nal semester of twelfth grade). Beyond this, Mississippi high school students have no physical education obligation. This is problematic because research suggests that physically active adolescents are more likely to remain physically active into adulthood3,7. Additionally, some studies show a relationship exists among fi tness knowledge and physical activity, 9,10,11,12. Therefore, if educators can expose students to physical education concepts and practices throughout high school, students may make healthier choices. Efforts to increase physical activity among youth have led the CDC, the National Association for Sport and Physical Education (NASPE), and the American Heart Association (AHA) to propose comprehensive daily physical education for children K-1213. For many youth, the only preparation for active lifestyles stems from the promotion of physical activity and fi tness through physical education. Emphasis for physical education should be placed on preparing youth to make healthy choices, thereby providing students the necessary knowledge and skills to make such decisions. In accordance with this belief, NASPE has a fundamental goal to teach quality physical education that focuses on teaching skills and concepts to make lifelong healthy choices14. Much of the literature focused on quality physical education emphasizes the “education” aspect with a goal of preparing students to make lifelong healthy decisions14, 15, 16, 17. Mississippi Governor Haley Barbour stated that, “By teaching our children the importance of good nutrition and physical activity, we are taking the necessary actions to ensure the benefi ts of a healthier lifestyle—lower costs, more job creation, mental clarity, and a longer and better quality of life”6( ¶5). Similarly, the mission of the Council on Physical Education for Children (COPEC) reads: “COPEC is committed to helping children develop motor skills, healthy lifestyles, and positive attitudes for lifelong physical activity through the development, review, and dissemination of information that enhances and promotes quality physical education”14( ¶1). Numerous articles support this notion16, 18, 19 and studies make the link between knowledge and behaviors 8, 9,

10, 11, 12. However, no studies report what students know relative to the fi eld of physical education and the impact of such knowledge on physical activity 16 and obesity. Furthermore, Ayers16 suggests that no research exists on whether or not physical educators are teaching the essential physical education concepts that students should know upon graduating. With developed physical education philosophies, students should be progressing towards healthy lifestyles. However, inactivity and obesity are escalating and accounting for a nation that is approximately two-thirds overweight1. Though numerous genetic, environmental, and behavioral factors contribute to being overweight and obese3, 20, 21, 22 the focus for this research project was centered on two behavioral factors of obesity: cognitive domain of physical education and physical activity behaviors.

METHODS

Research DesignA non-experimental, exploratory design was selected for this study, so that the scope of selected Mississippi high school students’ physical education content knowledge and its impact on activity levels and body mass index (BMI) could be evaluated. Eleven null hypotheses guided this project and are noted in Table 1. By implementing this design, the strength and direction of relationships among selected variables were determined. The study was approved by the Institutional Review Board.

Sample Size DeterminationSample sizes for each hypothesis, noted in Table 1, were predetermined and based on alpha level, power, effect size, and type of statistical test. The alpha and power levels were aligned with social science convention and set at .05 and .80 respectively for all hypotheses. Due to limited research in the area of physical education curricular trends, medium effect sizes were subjectively decided upon by the researcher as it was determined that medium group differences would warrant recommendations. A state-wide sample was desired. Thus, schools were randomly selected throughout Mississippi. The chosen methods of project implementation required that multiple high school administrators and personnel administer, collect, and return data. Therefore, the fi nal response rate was expected to be lower than observed, comparable studies. The expected response rate was 10%. Estimating that 10% of the sample would return the study’s instruments, 3,560 Mississippi high school ninth and twelfth grade students were targeted for the project. Sampling details are provided in Table 1.

Sampling ProceduresThe sampling frame for this study included all ninth and twelfth graders attending public high schools (excluding vocational and alternative schools) in Mississippi and is noted in Table 2. A multi-stage sampling technique was employed to obtain a random sample of ninth and twelfth graders with an approximate age range of 14-20. Three stages were utilized to ensure that schools from all areas of the state had an equal chance of being selected for representation based on the percentage of ninth and twelfth graders in each geographical area.

Stage One: Stratifi ed Sampling. The initial sampling procedure involved dividing the state of Mississippi into seven geographic regions to ensure that schools from all areas of the state had an equal chance of being selected for representation based on the percentage of ninth and twelfth graders in each geographic area. The seven geographic regions included were the Northeast, North Central, Northwest, East Central, West Central, Southeast and Southwest. Information obtained via the Mississippi Department of Education’s (MDE) website, http://www.mde.k12.ms.us/, allowed each region to be dissected to determine the number of high schools and the number of ninth and twelfth graders that comprised each area. Thus, the state



was divided by seven geographical regions, and each region was examined by the counties comprising each area. Once information was examined at a county level, it was checked for accuracy by viewing the district-level data. Information was recorded into an Excel spreadsheet

Stage Two: Cluster Sampling. Once the total percentage of ninth and twelfth graders comprising each geographical area was determined, schools were randomly selected to represent the complimentary percentage of total students in each area. Each high school in each geographical area had a one in ten chance of being selected for the study. Additionally, a balance of students attending schools with academic ratings of “Level 2, 3, 4, and 5” was desired for the total sample. Therefore, as every tenth school appeared in the sampling pool, it was reviewed by the researcher to determine if the criterion was achieved across all desired levels. If the criteria were met, the school was selected for the study.

Stage Three: Inclusive Sampling. At the fi nal stage of sampling, all ninth and twelfth graders from the randomly-selected schools were included in the sample

ParticipantsA total of 386 students (females = 198 and males = 188) in grades nine (n=224) and twelve (n=147) participated in the study. The sample was representative of fi ve geographical regions throughout Mississippi. Participant profi les are noted in Table 3.

InstrumentationThe Assessment of Sub-disciplinary Knowledge in Physical Education Battery. The Ask-PE Battery16 is a combination of seven test areas and is utilized to measure physical education content knowledge 16. The Ask-PE Battery is inclusive of: motor learning, motor development, biomechanics, exercise physiology, historical perspectives, social psychology, and aesthetic experiences. Though utilizing questions from all sub-disciplinary sections would provide a more accurate examination of total physical education content knowledge, this study only included 38 adapted questions from the Ask-PE:EXP, as this sub-disciplinary area is most relevant to physical activity. Ayers16 reported a KR20 value of .91 for the Exercise Physiology sub-disciplinary section of the Ask-PE:EXP, while this project yielded a comparable KR20 value of .89.The Modifi able Activity Questionnaire for Adolescents. The Modifi able Activity Questionnaire for Adolescents(23) (MAQ-A) assesses past-year activity behaviors, specifi c to type of activity or activities, as well as the time spent partaking in each activity, by asking students to provide details of activities over the past year. Formulas are provided to account for physical activity in hours per week, MET hours per week, and vigorous hours per week. For the purpose of this study, calculations for hours per week and total hours per week were utilized: H/week = (Past year/mo) x (4.3wk/mo) x (days/wk) x (min/day) / (60 min/h) / (52wk/yr).The hours for all activities are summed to determine the total past-year activity levels of adolescents23. Permission to use the MAQ-A was provided to the researcher.

RESULTSThe response rate of high school students was 11% (386/3,560). Of 17 schools, 6 completed the study, yielding a school response rate of 35%. Data was screened for missing values. Due to computational formulas being applied to data, all missing data for the MAQ-A and Ask-PE:EXP were assigned values of zero. Other data fi elds remained as provided by the participants. Distributions were checked for normality by viewing histogram charts. Histogram charts with the applied normal curve, revealed that most variables (i.e. grade, sex, race, Ask-PE:EXP scores) were normally distributed but average weekly physical activity was skewed. Thus, modifi cations were made. For example, non parametric analog was used for the violation of normal distribution of physical activity scores. Therefore, Spearman’s correlations were used instead of Pearson’s correlations for all relationship-testing hypotheses

containing average weekly physical activity as a variable. Additionally, a Games Howell post hoc analysis was employed to account for the violation of homogeneity of variance for the representation of schools based on academic ratings. A Spearman Rank-order Correlation Coeffi cient was calculated for the relationship between participants’ physical education content knowledge and average total weekly activity. Moderate positive correlations existed for ninth graders (rs (203) = .237, p<.01, Cohen’s q =.06) and twelfth graders (rs (136) = .415, p<.01, Cohen’s q =.17), indicating a signifi cant, direct relationship between the two variables. Therefore, HO1 and HO2 were rejected, with results suggesting that individuals who score higher on the Ask-PE:EXP tend to be more active on a weekly basis. Though signifi cant results were found, the level of meaningfulness is minimized due to the small effect as physical education content knowledge accounts for about 6% of physical activity scores for ninth graders and 17% in twelfth graders. An independent-samples t-test was employed to determine if differences existed between ninth and twelfth graders’ physical education content knowledge scores. Results indicated no signifi cant difference between the means on the Ask-PE:EXP (t(369) = -1.774, p=.077). Though no difference existed, it was notable that on average twelfth graders (M= .57 SD = .21) scored only slightly higher than ninth graders (M = .52, SD = .27) on the Ask-PE:EXP. Thus, HO3 was accepted, and no signifi cant differences in physical education conceptual knowledge of ninth and twelfth graders existed. Due to an imbalance of groups, power was decreased, and the chance for a Type II error did exist, Ð = .95. An independent-samples t-test was employed and determined that no signifi cant differences existed between ninth and twelfth graders’ physical activity behaviors, (t(369) = 1.557, p=.12). Although, no signifi cant fi ndings were revealed, it was noted that the mean physical activity score for ninth graders was higher (M = 7.7, SD = 10.21) than twelfth graders’ (M = 6.06, SD = 9.45). Thereby, HO4 was accepted, and no signifi cant differences in physical activity behaviors of ninth and twelfth graders existed. Due to an imbalance of groups, power was decreased, and the chance for a Type II error did exist, Ð = .86. A one-way ANOVA was employed and yielded signifi cant differences in physical education concept knowledge between schools based on academic ratings, (F(3, 382) = 10.83, p<.01, d =.085). Also, a signifi cant Levene’s statistic, p<.01, supported the use of a Games-Howell post hoc analysis. A Games-Howell analysis revealed differences existed between Level 3 schools and all other levels. Level 3 schools had a signifi cantly lower average Ask-PE:EXP Score (M = .29, SD = .15) than Level 2 schools (M = .56, SD = .19), Level 4 schools (M = .58, SD= .21), and Level 5 schools (M = .53, SD= .22). Therefore, H05 was rejected as signifi cant differences in students’ Ask-PE:EXP scores existed based on school’s academic rating. Although signifi cant, the result was deemed not meaningful as the effect was small; school attended only accounted for 8% of Ask-PE:EXP score. Also, although a Games-Howell post hoc analysis was selected to accommodate for the imbalance of groups, Level 3 participants made up 5% of the sample compared to 23% (Level 2), 25% (Level 3), and 47% (Level 5) of other schools, and this potentially impacted fi ndings. A Pearson correlation was calculated examining the relationship between participants’ Ask-PE:EXP scores and self-reported BMI. It was determined that no statistically signifi cant relationship existed for ninth (r (203) = -.03, p=.7) and twelfth graders (r (136) = .03, p=.7). Therefore, HO6 and HO7 were accepted, and results suggested that Ask-PE:EXP score had no relationship with reported BMI. Though no signifi cant results existed, it was noted that a high probability for a Type II error could have occurred for ninth, Ð = .95, and twelfth graders, Ð = .44. A Spearman Rank-order Correlation Coeffi cient was calculated to examine the relationship between participants’ average physical activity behavior and self-reported BMI. An insignifi cant correlation was determined for ninth graders (rs (203) = -.01, p=.9) while a signifi cant, but weak, inverse correlation, p=.034, existed for twelfth graders (rs (136) = -.181, p<.05, Cohen’s q=.033). Therefore,



HO8 was accepted for ninth graders, indicating that no relationship existed between physical activity behavior and self-reported BMI, Ð = .80. However, HO9 was rejected for twelfth graders, suggesting that twelfth graders who were more active on a weekly basis tended to have lower BMI scores. Though this result was deemed signifi cant, physical activity scores only accounted for 3% of BMI classifi cations of twelfth graders. A Chi-Square Goodness of Fit test was calculated comparing the observed distribution of Ask-PE:EXP scores above and below 62%, a research-based, cutoff value. It was hypothesized that an equal distribution of scores would be greater than and less than 62%. Signifi cant deviations from the hypothesized values were determined, (x2(1) = 19.16, p <.01, w=.223). The analysis further revealed that 236 participants performed below and 150 participants performed above the cutoff. Grade specifi c analyses revealed that ninth graders signifi cantly deviated from the hypothesized value (x2(1) = 17.16, p <.01) with 143 students performing below 62% and 81 students performing above 62%. No signifi cant deviations existed for twelfth graders (x2(1) = 1.53, p=.22), where 81 students performed below 62% and 66 students performed above 62%. Each of these analyses revealed that majority of ninth and twelfth graders were performing below the established, research-based passing cutoff score of 62%.

DISCUSSIONResults sought to identify physical education in combination with physical activity, as key components related to physical activity behaviors, thus having the possibility of attacking the obesity epidemic. The ninth and twelfth grade populations were identifi ed to explore gaps in physical education knowledge and physical activity behaviors. Though these fi ndings added value to the existing research and assisted in providing areas for future research, several limitations existed. For example, the lack of manipulation and control of the independent variables did not allow for cause and effect fi ndings. Also, the distribution and collection of all instruments were the responsibility of numerous individuals, thus response rate was not controllable. Several uncontrollable factors existed such as the accuracy of student recall rates for physical activity and self-reported BMI scores. Further, total physical education knowledge was not addressed, as only the Exercise Physiology subsection of the Ask-PE Battery was used. It appears that overall Mississippi students are performing lower than students in 16 other states on the Exercise Physiology sub-disciplinary section of the Ask-PE:EXP. Further, the majority are performing signifi cantly below the established, research-based cutoff score of 62%. This is notable because fi ndings suggested that students who scored above 62% on the Ask-PE:EXP were more likely to be active during a weekly basis compared to those who scored below a 62%. This is consistent with research fi ndings which suggest that physical education knowledge or fi tness knowledge can infl uence physical activity behaviors9, 10. Currently the Mississippi physical education guidelines require that students in grades nine through twelve earn one half of a Carnegie unit 6. The requirements do not hold students accountable throughout their high school careers, nor do they necessarily require physical education, but instead recommend it or a related” activity. Therefore, some students are not being exposed to cognitive principles of physical education after the eighth grade. This was refl ected in the study’s fi ndings which suggested no signifi cant differences existed in the amount of physical education knowledge between ninth and twelfth graders. Twelfth graders only scored an average of 5% higher on the Ask-PE:EXP when compared to ninth graders. Of particular interest was that Mississippi ninth and twelfth graders performed at levels lower than students in 16 other states. Considering these fi ndings, twelfth graders are not graduating high school with much more physical education knowledge than ninth graders. This is interesting given that such knowledge can help account for 17% of physical activity in twelfth graders. Knowing that there was only a 5% difference in Ask-PE:EXP scores between ninth and twelfth graders and, also, that twelfth

graders’ physical activity scores were impacted more by physical education knowledge, might explain why the twelfth graders were less active than ninth graders by an average of one hour per week. Though results from this study indicated that physical education knowledge had a signifi cant relationship with physical activity for both ninth and twelfth graders, neither group had a signifi cant relationship with Ask-PE:EXP scores and self-reported BMI. Additionally, reported physical activity score had no signifi cant relationship with reported BMI for ninth graders. This is aligned with research fi ndings which suggested that physical education active time does not affect BMI or weight classifi cation in high schoolers24. However, a signifi cant, inverse relationship did exist among twelfth graders’ self-reported scores of physical activity and BMI. Though, the result was signifi cant, it had a small effect indicating that physical activity accounted for 3% of BMI for twelfth graders. For both ninth and twelfth graders, the lack of or weak relationship can possibly be explained by Kolbo et al.25, who suggested that self-reported BMI scores can be misleading. Kolbo et al.25 found self-reported body measures to be more conservative when compared to actual assessments. Also, for this project, activity levels were not defi ned by intensity levels. So, though Ask-PE:EXP score did have a relationship with physical activity score, indicating students who had more knowledge were more likely to be active, knowledge did not correlate with BMI. This might be explained by further examining intensity levels of physical activity. A fi nal fi nding from this study was that there were signifi cant differences in students’ Ask-PE:EXP scores based on the school’s academic ratings. Results indicated that Level 3 schools had a signifi cantly lower average Ask-PE:EXP score than Level 2, Level 4, and Level 5 schools. Additionally, the difference in Ask-PE:EXP scores had a small effect indicating school attended accounted for 8% of Ask-PE:EXP score. Conclusions and Recommendations In a time when youth obesity and physical inactivity are escalating, attention should be given to possible interventions, particularly in school environments, and more specifi cally in physical education. However, due to the implementation of No Child Left Behind, many physical education environments have been hindered. This has advanced physical education challenges, and in some cases, caused the elimination of such programs, thus limiting the possible avenues for which students have to gain necessary knowledge to make lifelong, healthy decisions. Findings from this study did suggest a direct, relationship between physical education knowledge scores and physical activity levels. Additionally, results indicated that physical education knowledge is more closely correlated with twelfth graders’ likelihood of physical activity. This is notable as twelfth graders only score an average of 5% higher than ninth graders on the Ask-PE:EXP. Twelfth graders were also found to be less active than ninth graders. However, for those twelfth graders who are physically active, a signifi cant, inverse relationship existed with their BMI. Therefore, if students in grades nine through twelve experience progressive knowledge on physical education components, they may tend to be more active, and possibly at intensity levels that positively impact BMI. The high school career is seemingly a critical point because for many, approximately 71%, this is their fi nal opportunity to gain valuable knowledge to make healthy lifestyle decisions as only about 29% of Mississippians between the ages of 18 and 24 were reported to have been enrolled in college during 200626. Therefore, in conclusion, schools should evaluate their physical education programs on a more stringent level, and provide students more time to acquire knowledge that could contribute to healthy lifestyle decisions. For example, high schools should require all students to participate in a comprehensive health and physical education program throughout their high school careers, learning cognitive and practical components that could contribute to healthier lifestyles. Additionally, students, physical educators, and administrators should be held accountable for physical education knowledge. With developments in physical education curricula,



particularly cognitive components, schools can provide students with knowledge to make healthy choices. Multiple recommendations were developed based on study’s fi ndings. Schools should formulate an intervention to focus on cognitive components of physical education with a goal of improving Ask-PE:EXP scores and additionally, evaluating the relationship of the knowledge component on physical activity and BMI. Also, due to Ask-PE:EXP scores relating directly, but weakly to physical activity scores, the total Ask-PE Battery should be used in future studies, to determine what other sub-disciplinary areas, if any, account for variance in the physical activity relationship. Another factor that should be accounted for is the intensity level of activity. Students’ activity levels should be analyzed to determine if physical education (exercise physiology or total discipline) knowledge has any relationship with the intensity level of activity.

ACKNOWLEDGEMENTSThe authors wish to express their utmost appreciation and support of Dr. Suzan Ayers’ of Western Michigan University for her dedication to the development of quality assessments in physical education. It should be noted that this article was originally part of a dissertation at The University of Southern Mississippi. A special thanks is owed to all committee members including: Dr. Nancy Speed (Dissertation Chair), Dr. Trent Gould, Dr. Gary Krebs, Dr. Dennis Phillips all of the University of Southern Mississippi and Dr. Lindsey Blom of Ball State University. Also, I would like to thank Dr. Candice Howard-Shaughnessy for her expertise and thorough review of the manuscript.

FUNDINGThis project was funded through the University of Southern Mississippi’s

Doctoral Dissertation Grant Program. Total funds received equaled to an amount of $500.00.

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5. Segal L. Mississippi adults 1st most obese in country; youth 8th most overweight. Trust for America’s Health Foundation. Available at: http://healthyamericans.org/reports/obesity2007 Accessed 9/5/2007.

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7. Telama R, Yang X, Hirvensalo M, Raitakari O. Participation in

organized youth sport as a predictor of adult physical activity: A 21-year longitudinal study. Pediatric Exercise Science. 2006; 17: 76-88.

8. Adams II TM, Graves MM, Adams HJ. The effectiveness of a university level conceptually-based health-related fi tness course on health-related fi tness knowledge. Physical Educator. 2006; 63: 104-112.

9. Cason K, Logan B. Educational intervention improves 4th-grade school-children’s nutrition and physical activity knowledge and behaviors. Topics in Clinical Nutrition. 2006; 21: 234-240.

10. DiLorenzo TM, Stuckey-Ropp RC, Vander Wal JS, Gotham HJ. Determinants of exercise among children: A longitudinal analysis. Prev Med. 1998; 27:470-477.11. Lubans D, Sylva K. Controlled evaluation of a physical activity intervention for senior school students: Effects of the lifetime activity program. Journal of Sport and Exercise Psychology. 2006; 28:252-268.

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14. National association for sport and physical education. Available at: http://www.aahperd.org/Naspe/. Accessed 6/20/2007.

15. Ayers S. Developing quality multiple-choice tests for physical education. Journal of Physical Education, Recreation, and Dance. 2001;72: 21-28.

16. Ayers S. High school students’ PE conceptual knowledge. Res Q Exerc Sport. 2004; 75:272-287.

17. Mohnsen B. Concepts and principles of physical education: What every student needs to know (2nd ed.). Reston, VA: AAPHERD Publications; 2003.

18. Irwin C, Symons C, Kerr D. The dilemmas of obesity: How can physical educators help? Journal of Physical Education, Recreation, and Dance. 2003;74:33-38.

19. Wallhead T, Buckworth J. The role of physical education. The National Association for Kinesiology and Physical Education in Higher Education. 2004;56:285-301.

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25. Kolbo J, Penman A, Meyer MK, Speed N, Molaison E, Zhang, L. Prevalence of overweight among elementary and middle school students in Mississippi compared with prevalence data from the Youth Risk Behavior Surveillance. Preventing Chronic Disease. Available at: http://www.cdc.gov/PCD/issues2006/jul/05_0150.htm. Accessed 5/2/2008

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MAHPERD Journa





FITNESS AMONG MISSISSIPPI STUDENTS

Geoffrey M. Hudson, PhD, CSCSThe University of Southern Mississippi118 College Drive Box 5142Hattiesburg, MS [email protected]

John Alvarez, PhDDelta State University

Lindsey C Blom, EdDBall State University

Lei Zhang, PhD, MBAMississippi State Health Department

Jerome R. Kolbo, PhD, ACSWThe University of Southern Mississippi

The Association between Fitness and School Test Scores, Attendance, and Discipline among Mississippi Students


ABSTRACT

Between 2008 and 2010, a number of elementary and middle schools from

across the state of Mississippi participated in the Health is Academic Quality

Physical Education Program. As a part of the program, the schools implemented

the Physical Best curriculum in their Physical Education (PE) classes. During

each of the three spring semesters, the participating schools conducted fi tness

tests, and collected, recorded, and submitted their data through Fitnessgram

software. Statistically signifi cant correlations were found between fi tness and

both Language Arts and Math scores, as well as in absences. While a trend

towards fi tness and fewer disciplinary incidents was observed, the fi ndings were

not statistically signifi cant. Additional analysis indicated statistically signifi cant

increases in the percentage of students in these schools that had higher

Language Arts and Math scores and that achieved more Fitnessgram healthy

fi tness zones. Also, statistically signifi cant decreases in absences and disciplinary

incidents were observed over the three years. These fi ndings suggest that

investments in fi tness and increasing the number of Mississippi students who

are fi t may likely result in improved test scores, fewer absences, and fewer

disciplinary incidents in schools.


INTRODUCTIONA growing number of investigations have recently found a strong link between a child’s fi tness (irrespective of weight status) and academic performance (Blom, Alvarez, Zhang, & Kolbo, 2011; Castelli, Hillman, Buck, & Erwin, 2007; Chomitz, et al., 2009; Coe, Pivarnick, Womack, Reeves, & Malina, 2007; Dwyer, Sallis, Blizzard, Lazarus, & Dean, 2001; Eveland-Sayers, Farley, Fuller, Morgan, & Caputo, 2009; Roberts, Freed, & McCarthy, 2010; Sallis, et al., 1999; Stevens, To, Stevenson, Lochbaum, 2008; Welk, et al., 2010). Chomitz et al. (2009) found that a student’s odds of passing the Math portion of the Massachusetts Comprehen-sive Assessment System (MCAS) increased by 38% for every increase in fi tness units achieved with the Fitnessgram (Cooper Institute for Aerobic Research, 2007). Similarly, they also found a 24% increase in the odds of passing the English MCAS portion for each fi tness unit achieved (Chomitz et al., 2009). Coe et al. (2006) found that higher grades were positively associated with students participating in vigor-ous physical activity. Additionally, Eveland-Sayers et al. (2009) found that as 1-mile run time and muscular fi tness improved, so did Math scores on the Terra-Nova achievement test. Furthermore, Castelli et al. (2007) found a positive association between aerobic fi tness and academic achievement and an inverse relationship between academic achievement and body mass index (BMI). In a study of elementary, middle, and high schools in Texas, Welk and colleagues (2010) also found a positive relationship between fi tness and academic achieve-ment. This study also demonstrated that students with higher fi tness levels had fewer absences and fewer reported delinquency problems (Welk et al., 2010). While these cross-sectional studies have been able to demonstrate some positive associations, a longitudinal intervention performed by Sallis et al. (1999) provides some of the most compel-ling evidence. In the Project SPARK study, researchers found that dou-bling a child’s time in Physical Education (PE) in the SPARK program resulted in increased academic performance (Sallis et al., 1999). Under the pressures of ever-shrinking budgets and increased national emphasis on standardized testing, it is now commonplace for school administrators to substitute PE programs for increased time in math or language courses (Centers for Disease Control and Prevention [CDC], 2004; Pearlman, Dowling, Byuk, Cullinen, & Thacher, 2005). Despite the assumptions implied by this trend, a systematic review of literature by Murray, Low, Hollis, Cross, & Davis (2007) revealed that there is a lack of evidence that substituting time in a PE class for an academic class would negatively affect academic performance. Specif-ically, Welk and coauthors (2010) also found that higher fi tness rates increased the odds of schools achieving exemplary/recognized school status within the state of Texas. Furthermore, longitudinal studies like Project SPARK (Sallis et al., 1999) establish that increasing PE time can potentially lead to increases in testing scores. A recent review of the literature by the CDC also strongly supports the positive relationship between school-based physical activity and academic performance (CDC, 2010). Moreover, research on the Action Schools! BC interven-tion in Canada demonstrated that increasing physical activity time by 47 minutes per week did not signifi cantly affect academic perfor-mance scores (Ahamed, et al,, 2007). While this study did not demon-strate an improvement in academic performance, it is still important evidence for administrators to note that replacing time in the class-room with an extra six to seven minutes a day of physical activity did not have a negative impact on the children’s academic performance.Despite numerous studies around the United States (U.S.) demonstrat-ing a positive relationship between fi tness and academics, limited re-search has been conducted in Mississippi. Blom et al. (2011) reported the fi ndings of the fi rst of three years of data on 22 Mississippi schools in 2008 that implemented the Physical Best curriculum and assessed student fi tness with the Fitnessgram battery of tests. The researchers found statistically signifi cant correlations between fi tness and both Language Arts and Math Scores and in absences even after control-ling for age, gender, race, and socio-economic status (SES). It should be noted that while a trend towards fi tness and fewer disciplinary incidents was observed, the fi ndings were not statistically signifi cant. The researchers suggested that investments in fi tness and increasing the number of students who were fi t and were fi t in more areas would

likely result in improved test scores, fewer absences, and fewer disci-plinary incidents (Blom et al., 2011). Therefore, the purpose of the current study was twofold. First, the study was designed to analyze the data on the students in these same Mississippi schools during the second and third years (spring semesters of 2009 and 2010) of the Physical Best curriculum to again assess the relationship between fi tness and absences, disci-plinary incidents, and test scores. Secondly, the purpose was to ana-lyze the data over the term of the project (2008, 2009, and 2010) to determine if over the three years, higher percentages of students were fi t in more areas, whether Language Arts and Math scores improved, and whether absences and disciplinary incidents declined.

METHODS

Participants In this study, fi tness data were collected and analyzed on 13,311 Missis-sippi public school children in grades 3-8. The students were from 22 different schools between 2008 and 2010. Fitness data collected and recorded on students in these schools were then matched by the Mis-sissippi Department of Education (MDE) with student records within the Mississippi Student Information System (MSIS). Many records were not able to be matched or had missing data that were necessary for the analysis. A fi nal data set consisting of 6,492 students with all necessary data was produced.

InstrumentsPhysical fi tness, standardized Language Arts and Math test scores, absences, disciplinary incidents, and socio-demographic information of gender, race/ethnicity, and SES (via lunch status) were included in the analysis. More information on each of these measures is described below. Physical fi tness data were collected through the Fitnessgram, which is a physical fi tness test battery developed by the Cooper Insti-tute (Cooper Institute for Aerobic Research, 2007). The Fitnessgram was used in tandem with the Physical Best curriculum developed by the National Association for Sport and Physical Education (NASPE). The Physical Best curriculum is a guide for best practice for develop-ing health-related physical fi tness in the K-12 physical education set-ting. The Fitnessgram is a commonly used means of assessment for six components of health-related fi tness that includes: PACER (Progres-sive Aerobic Cardiovascular Endurance Run) test, curl-up endurance test, push-up endurance test, trunk lift, sit and reach, and skinfold/ BMI. Under the Fitnessgram guidelines, each fi tness component has a specifi c range of criterion-referenced standards that constitutes a healthy fi tness zone. The healthy fi tness zones are considered to be the minimal level of performance associated with good health or decreased risk (Welk & Meredith, 2008). Students’ overall fi tness level was determined by the number of healthy fi tness zones they achieved on the test battery. These scores could range from zero to six healthy fi tness zones achieved. Academic achievement data (i.e., standardized Language Arts and Math scores) were collected through the second version of the Mississippi Curriculum Test (MCT2). This assessment comprises Language Arts and Mathematics and is administered annually to all Mississippi students in grades 3-8. The MCT2 has four levels of achievement, (a) minimal: students inconsistently demonstrated the content area knowledge and skills required for success at the next grade, (b) basic: students demonstrated partial mastery of the content area knowledge and skills required for success at the next grade, (c) profi cient: students demonstrated solid academic performance, and (d) advanced: students demonstrated academic performance clearly beyond the requirements to be successful at the next grade (Bounds, Sewell, Kaase, & Simmons, 2007; Mississippi Department of Education, 2010). For this study, students were grouped into either a low academ-ic achievement group (students at minimal and basic levels) or a high academic achievement group (students at profi cient and advanced levels).


Academic behavioral data were collected through reports gener-ated by Mississippi Department of Education (MDE) on absences and disciplinary actions on each student in K-12. For this study, absence was measured by the number of days students were absent over the course of a year and categorized into three groups: few (0-3 absenc-es), often (4-7 absences), and frequent (8 or more absences). Data on disciplinary incidents are reported similarly to absences. In this study, either In-School Suspensions or Out-of-School Suspensions were cat-egorized into two groups: students with at least one reported suspen-sion or those with no reported suspension. Socio-demographic data ([SES]; i.e. race/ethnicity) were recorded and coded exactly as provided by the MDE. Based on whether or not stu-dents were qualifi ed for free or reduced price lunch, three groups (i.e., free lunch, reduced price lunch, and paid lunch) determined their SES.

ProceduresThis study received Institutional Review Board approval through the Human Subjects Committee at The University of Southern Mississippi (USM). Due to the sensitive nature of using and merging student re-cords, a Memorandum of Understanding (MOU) regarding the protec-tion of the data was established between MDE and USM. All data were handled electronically and were password protected. During spring semesters 2008, 2009, and 2010, over 20 elementary and middle schools from across the state of Mississippi received funding from the Bower Foundation as part of the Health is Academic Quality Physical Education Program. As part of their funding, each school received the Physical Best Curriculum and the Fitnessgram testing battery with reporting software. Each of the schools sent representatives to training sessions in which they received training on the implementation of Physical Best curriculum and the use of the Fit-nessgram software by certifi ed trainers. During the spring semesters of 2008, 2009, and 2010, schools were able to implement the cur-riculum in their PE classes. They also conducted the fi tness tests, and collected, recorded, and submitted their data through the Fitnessgram software. Test administration was handled by the PE teachers at each school under the supervision of those receiving the training to ensure that the Fitnessgram would be administered in a consistent manner.

Data ManagementThe participating PE teachers entered all demographic, bio-statisti-cal, and fi tness data into the Fitnessgram software as instructed in the training sessions and then exported the data directly from the software. Each case in the fi les included student name, date of birth, gender, grade level, and the six fi tness test scores. The data fi le with all students’ data from each school was submitted to the MDE. It was then merged with student records within the MDE MSIS, which in-cluded student information regarding race/ethnicity, lunch status (free, reduced price, or paid lunch), absences, disciplinary incidents, and Language Arts and Math test scores.

Data AnalysisSAS 9.2 was used for all statistical analysis. Chi-square analyses were used to assess the statistical signifi cance of observed differences in academic test scores, absences, and disciplinary incidents. Chi-square test for trend was used to investigate if the students’ test scores, ab-sences, and disciplinary incidents changed during the three years of the project (2008-2010).

RESULTSAs with the fi ndings reported by Blom et al. (2011) regarding the fi rst year of the project (i.e. 2008), signifi cant linear trends (p < 0.0001) were also observed between fi tness and both Language Arts and Math scores in both 2009 and 2010. This indicates that the percent of high test scores increased with the number of healthy fi tness zones achieved (Figures 1 and 2). Signifi cant relationships were also observed with the be-havioral variables collected. As in 2008, signifi cant linear trends (p < 0.0001) were observed between fi tness and absences in 2009 (Figure


3), but not 2010. In 2009 and 2010, there was no relationship between number of disciplinary incidents and number of healthy fi t zones achieved. This fi nding is also consistent with the data from 2008. As for trends over the three years of the project, changes were noted in the distribution of the number of fi t zones achieved. The percent of students who achieved lower numbers of fi t zones de-creased and the percent of students who achieved higher numbers of fi t zones increased over the three year period. This change is statisti-cally signifi cant (p < 0.0001) (Figure 4). As for changes in Language Arts and Math scores, the percent of students with high performance showed an upward trend over the three years of the project. This change is statistically signifi cant for both Language Arts (p < 0.0001) and Math (p < 0.0001) (Figure 5). Data on behavioral parameters provided several interesting fi ndings. Over the past three years, the percent of students with 0 – 3 absences increased, while students with 4 – 7 absences remained unchanged, and students with 8 or more absences decreased. The overall change was statistically signifi cant (p = 0.015) (Figure 6). While the relationship between fi tness and disciplinary incidents was not sta-tistically signifi cant in the analysis of each individual year, the percent of students with one or more disciplinary incidents showed a statisti-cally signifi cant downward linear trend (p < 0.0001) (Figure 7).

DISCUSSIONThese fi ndings are consistent with and support prior research within Mississippi (Blom et al., 2011) and beyond (e.g., Castelli et al., 2007; Chomitz et al., 2009; Eveland-Sayers et al., 2009; Roberts et al., 2010; Welk et al., 2010). Similar statistically signifi cant fi ndings over three separate years and over a three year period indicate that the relation-ship between fi tness and academic performance is strong and provide additional confi dence that these fi ndings are worth careful consider-ation. These fi ndings suggest that investments in fi tness and increas-ing the number of students who achieve more healthy fi tness zones may likely result in improved test scores, fewer absences, and fewer disciplinary incidents in schools. The design of this study does possess limitations, however. First, since this is a cross-sectional study, it cannot be concluded that

increased fi tness caused improved test scores and decreased absenc-es or disciplinary incidents. It is possible that the students that score better on both academic and fi tness tests are simply more motivated to go to school, stay out of trouble and do well on tests. Secondly, with the current research design, it was not possible to track the prog-ress of each child longitudinally over the three year period. It is also important to note that by the third year, only 16 of the original schools submitted data. It is possible that schools and the students in those schools that remained in the project were different than those that had dropped out of the project. However, it should be noted the each individual year of the project (2008, 2009, and 2010) found statisti-cally signifi cant fi ndings regardless of which schools submitted data.In future studies, it would be useful to examine whether an improve-ment in each student’s fi tness would lead to similar academic im-provements. Moreover, it would be valuable to determine the impact of grade level (elementary and middle vs. high school), student and parent motivation for academic success, and the modes of delivery that are used and times involved in each mode (e.g. PE class, recess, after-school programs). These fi ndings and the limitations of this current project suggest that future studies that longitudinally track students individually over several years are warranted to better deter-mine whether changes in fi tness and academic performance, as well as absences and discipline, are causally related. To the authors’ knowledge, this study is the fi rst of its kind to repeatedly investigate the relationship between fi tness and academic performance and to do so over time in Mississippi. These results are then of great signifi cance to teachers and administrators in Mississippi and perhaps across the nation. As previous evidence has illustrated the importance of exercise with childhood obesity, this study also illus-trates that elementary and middle school students in Mississippi who are more physically fi t also have higher scores in Math and Language Arts and have fewer absences. These fi ndings could be used by physi-cal education professionals as well as administrators in the state to combat the temptation to sacrifi ce PE instructional time for additional academic instruction. In doing so, it is more likely that the schools can also further aid in the reversal of the childhood obesity epidemic in the state while still maintaining and possibly improving their academic performance measures.

REFERENCESAhamed, Y., Macdonald, H., Reed, K., Naylor, P-J., Liu-Ambrose, T., & McKay, H. (2007). School-based physical activity does not compro-mise children’s academic performance. Medicine & Science in Sports & Exercise, 39(2), 371-376.

Blom, L.C., Alvarez, J., Zhang, L., & Kolbo, J. (2011). Associations be-tween health-related physical fi tness, academic achievement and se-lected academic behaviors of elementary and middle school students in the state of Mississippi. ICHPER-SD Journal of Research, 6(1), 28-34.

Bounds, H.M., Sewell, B., Kaase, K., & Simmons, C. (2007). Mississippi performance level descriptors for the 2006 Mississippi language arts framework revised, 2007 Mississippi mathematics framework revised, and 2001 Mississippi science framework. Retrieved from Mississippi Department of Education website: http://www.mde.k12.ms.us/ACAD/osa/pld/Performance_Level_Descriptors.pdf

Castelli, D.M., Hillman, C.H., Buck, S.M., & Erwin, H.E. (2007). Physical fi tness and academic achievement in third- and fi fth-grade students. Journal of Sport & Exercise Psychology, 29, 239-252.

Centers for Disease Control and Prevention. (2004). Participation in high school physical education – United States, 1991-2003. Morbidity and Mortality Weekly Reports, 53(36), 844-847.

Centers for Disease Control and Prevention. (2010). The association


between school-based physical activity, including physical education, and academic performance. Atlanta, GA: U.S. Department of Health and Human Services. Chomitz, V.R., Slining, M.M., McGowan, R.J., Mitchell, S.E., Dawson, G.F., & Hacker, K.A. (2009). Is there a relationship between physical fi tness and academic achievement? Positive results from public school children in the Northeastern United States. Journal of School Health, 79(1), 30-37. Coe, D.P., Pivarnik, J.M., Womack, C.J., Reeves, M.J., & Malina, R.M. (2006). Effect of physical education and activity levels on academic achievement in children. Medicine & Science in Sports & Exercise, 38(8), 1515-1519. Cooper Institute for Aerobic Research. (2007). Fitnessgram/Activi-tygram Test Administration Manual (4th ed.). Champaign, IL: Human Kinetics. Dwyer, T., Sallis, J.F., Blizzard, L., Lazarus, R., & Dean, K. (2001). Rela-tion of academic performance to physical activity and fi tness in chil-dren. Pediatric Exercise Science, 13, 225-237. Eveland-Sayers, B.M., Farley, R.S., Fuller, D.K., Morgan, D.W., & Caputo, J.L. (2009). Physical fi tness and academic achievement in elementary school children. Journal of Physical Activity and Health, 6, 99-104. Mississippi Department of Education. (2010). Mississippi curriculum test (2nd edition): Interpretive guide. Iowa City, Iowa: Pearson, Inc. Murray, N.G., Low, B.J., Hollis, C., Cross, A.W., & Davis, S.M. (2007). Coordinated school health programs and academic achievement: A systematic review of the literature. Journal of School Health, 77(9), 589-600. Pearlman, D.N., Dowling, E., Byuk, C., Cullinen, K., & Thacher, A.K. (2005). From concept to practice: using the School Health Index to create healthy school environments in Rhode Island elementary schools. Preventing Chronic Diseases, Nov. V.2: Special Issue. Roberts, C.K., Freed, B.F., & McCarthy, W.J. (2010). Low aerobic fi tness and obesity are associated with lower standardized test scores in children. Journal of Pediatrics, 156(5), 711-718. Sallis, J.F., McKenzie, T.L., Kolody, B., Lewis, M., Marshall, S., & Rosen-gard, P. (1999). Effects of health-related physical education on aca-demic achievement: Project SPARK. Research Quarterly for Exercise and Sport, 70(2), 127-134. Stevens, T.A., To, Y., Stevenson, S.J., & Lochbaum, M.R. (2008). The im-portance of physical activity and physical education in the prediction of academic achievement. Journal of Sport Behavior, 31(4), 368-388. Welk, G.J. & Meredith, M.D. (Eds.). (2008). Fitnessgram/Activitygram Reference Guide. Dallas, TX: The Cooper Institute. Welk, G.J., Jackson, A.W., Morrow, J.R., Haskell, W.H., Meredith, M.D. & Cooper, K.H. (2010). The association of health-related fi tness with indi-cators of academic performance in Texas schools. Research Quarterly for Exercise and Sport, 81(3), S16-S23.

Scott Owens, Ph.D. University of Mississippi, Oxford, MS

Elizabeth Mumaw, B.S. University of Mississippi, Oxford, MS

Mark Hughey, B.S. University of Mississippi, Oxford, MS

Evaluation of the physical education and physical activity components of Mississippi public school wellness policies

MISSISSIPPI SCHOOL WELLNESS POLICIES

ABSTRACT

Federal legislation requires all school agencies that participate in the National

School Lunch Program to establish school wellness policies that address

nutrition education, nutrition standards for foods available within schools,

and physical education and physical activity. The purpose of this study was to

evaluate the comprehensiveness and strength of the physical education and

physical activity components contained in the wellness policies of a statewide,

random sample of public schools in the state of Mississippi. Wellness policies

were submitted by 123 Mississippi public schools participating in an ongoing

project evaluating the compliance level of Mississippi schools with nutrition goals

outlined in the Mississippi Healthy Student Act. The policies were evaluated for

the comprehensiveness and strength of their physical education and physical

activity components utilizing the School Wellness Policy Evaluation Tool, an

instrument developed by the Robert Wood Johnson Foundation’s Healthy

Eating Research Program. Mississippi public school wellness policies tended to

score higher on comprehensiveness than strength. Strong statements regarding

physical education items were more common than strong statements regarding

physical activity items. Comparisons with wellness policies from other states

suggest Mississippi public school wellness policies are not as strong, especially

regarding physical activity items. Additional research is needed using a common

metric so national standards and benchmarks can be established against which

individual schools and school districts can compare their wellness policies.

KEYWORDS: HEALTH POLICY, PHYSICAL FITNESS AND SPORTS, CHILD AND ADOLESCENT HEALTH


INTRODUCTIONThe Child Nutrition and Women, Infants and Children (WIC) Reauthorization Act of 2004 (Public Law 108-265) requires all local education agencies participating in the National School Lunch Program to create a school wellness policy that includes goals for nutrition education, physical education, and physical activity (USDA Food and Nutrition Service). Evaluation of these policies emerged in a nationwide survey as a key concern among school leaders (Agron, Berends, Ellis, & Gonzalez, 2010). To assist schools in this regard, a comprehensive coding system to measure the quality of school wellness policies was published in 2009 (Schwartz et al., 2009). To date, there have been few statewide reports on the use of this coding system to evaluate the physical education and physical activity components of school wellness policies. The purpose of this study was to evaluate the comprehensiveness and strength of the physical education and physical activity components of a statewide random sample of Mississippi public school wellness policies. Given that Mississippi has the nation’s highest rate of childhood obesity (Levi, Vinter, St. Laurent, & Segal, 2010), evaluation of the physical education and physical activity components of the state’s school wellness policies is critical.

METHODS

SampleWellness policies were obtained from 123 randomly selected Mississippi public schools, which represented 13.7% of all public schools in the state. The schools were part of a larger cross-sectional study evaluating the nutrition environments in Mississippi schools, specifi cally focusing on compliance with the Mississippi Healthy Student Act. A copy of each school’s wellness policy was requested at the time the onsite evaluation of the school environment was conducted. A sampling frame was derived from the MS NEEDS investigators from the Mississippi Department of Education (MDE) Student enrollment database for the specifi ed academic year. Schools were selected using simple random sampling stratifi ed by school level. Per MDE classifi cation, elementary schools serve any grade from kindergarten (K) through the fi fth grade; middle schools serve any grade 6 through 8; and high schools serve any grade 9 through 12. Schools serving more than one level were represented as appropriate (Mississippi School Nutrition Environment Evaluation Data System (MS NEEDS): Technical One Year (2008-2009) Outcomes). Among the 895 eligible schools, 50 elementary schools, 50 middle schools, and 50 high schools were selected as the study sample, representing 144 unique schools. Of the 144 randomly selected schools, 133 agreed to participate (92.4% participation rate) including 20 elementary schools, 13 middle schools, 31 high schools, and 69 schools serving more than one level. School wellness policies were obtained from 123 of these schools, which represented the fi nal sample size for the current study.

InstrumentsA working group within The Robert Wood Johnson Foundation developed the School Wellness Policy Evaluation Tool (School Wellness Policy Evaluation Tool, 2010). The purpose in developing this coding system was to provide a universal system for comparability among wellness policy research studies. A comprehensive coding system for measuring the quality of school wellness policies, published in 2009 (Schwartz et al., 2009), served as the framework for the development of the above mentioned tool. The 96-item evaluation tool is designed to evaluate school wellness policies based on their attention to the following categories: nutrition education, standards for the US Department of Agriculture child nutrition programs and school meals, nutrition standards for competitive and other foods and beverages, physical education, physical activity, communication, promotion, and evaluation. The 14 policy items related to physical education and physical activity are the focus of the present study. Refer to Table 1 for descriptions of these items. School wellness policy statements relative to physical education and physical activity are evaluated based on a 0 to 2

scale. A rating of “0” means a policy item is not included in the text of the school’s wellness policy. A rating of “1” means a policy item is mentioned but is considered to be a weak statement. A rating of “2” means a policy item is mentioned and is considered to be a strong statement, that is, it meets or exceeds expectations. To establish the validity and reliability of the original coding system, pairs of researchers from four different states coded a sample of 60 wellness policies between July 2007 and July 2008. The results found the coding system to be both reliable and valid. The system is internally reliable with a Cronbach’s alpha of 0.60-0.93. Interrater reliability for total comprehensiveness and strength had an intraclass correlation coeffi cient (ICC) of 0.82, sub scale scores ICC 0.70, and individual items ICC 0.72. Construct validity was established but not criterion validity.

ProceduresIn the current study, two of the co-authors independently applied the School Wellness Policy Evaluation Tool to a random sample of fi ve school wellness policies. Interrater reliability was determined by interobserver agreement and intraclass correlation (Thomas & Nelson, 2001). The co-authors agreed (applied the same numeric score) 63 out of 70 times (90%) across the fi ve policies (5 policies x 14 items = 70 possibilities for agreement/disagreement). Ninety percent interobserver agreement is considered good on evaluation tools of this type (Riffe, Lacy, & Fico, 1998). Any disagreements were discussed and a consensus was reached as to the reason for the disagreement. Intraclass correlation associated with the evaluation of these fi ve policies was 0.87 (p < .001). The remaining 118 school wellness policies were placed in random order and numbered consecutively. One-half of the 118 policies (odd numbered) were evaluated by one co-author and the other half (even numbered) were evaluated by the second co-author. One week after completing the 59 policy evaluations, each co-author re-evaluated a random sample of three previously evaluated wellness policies. Test-retest reliability was 100% for both co-authors.

Data ManagementA “comprehensiveness” score refl ects the extent to which physical education and physical activity content items are mentioned in a wellness policy. The maximum number of items is 14; however, in certain situations the number may be less. For example, policy item #3 applies to middle schools and item #4 to high schools, and are not included in the evaluation of an elementary school, thus the total number of items is 12. Also, certain policy items (#2, 10, & 14) apply only to elementary schools; therefore, when evaluating a middle or high school the total number of items is 11. The number of “1” and “2” responses are totaled and divided by the total number of items. This answer is then multiplied by 100, which results in a comprehensiveness score. A “strength” score describes how strongly the content is stated. It is calculated by counting the number of items rated as “2,” then dividing that number by the number of relevant content items. The resulting number is multiplied by 100, which is the strength score. Determining the number of relevant content items is the same as described above for calculating comprehensiveness. Both the comprehensiveness and strength scores can range from 0-100, with lower scores indicating less content and weaker language.The mean of the comprehensiveness and strength scores was calculated across all 118 wellness policies and also when the policies were categorized by school type (elementary, middle, high school, combined middle + high school, and combined elementary + middle + high school). A paired-samples t-test was used to determine whether schools scored higher on comprehensiveness as compared to strength. Additionally, the percentage of schools scoring “0,” “1,” or “2,” was analyzed for each of the 14 physical education and physical activity policy items.

RESULTSComprehensiveness scores, ranging from 0 to 83, were signifi cantly


higher (t= 9.3, p< 0.001) than strength scores, which ranged from 0 to 75. Table 2 displays the 14 physical education and physical activity policy items and the percentage of schools scoring “0,” “1,” or “2” on each item.

DISCUSSIONResults in Table 2 indicate that Mississippi public school wellness policies are much stronger documents relative to physical education issues than issues related to physical activity. Nine of the 14 policy items in the evaluation tool relate to physical education, and on 7 of the 9 items more than 80% of the wellness policies scored a “2” (strong language). The two physical education items that typically did not have strong language related to districts providing physical education training for physical education instructors (Item 8) and addressing physical education waiver requirements (Item 9). Only small percentages of wellness policies contained strong language regarding physical activity (fi ve policy items). Part of the explanation for weaker language relative to physical activity issues may be one of historical perspective. That is, physical education has long been part of school curriculum and its implementation and evaluation have a considerable history. Physical activity as a standalone policy issue separate from physical education is a newer concept that has only recently garnered attention, largely in response to the growing childhood obesity epidemic. Policy evaluations such as this help highlight the need for greater attention to physical activity issues Another possible explanation for weakness in school wellness policies may be related to school funding. Increased stress is being placed on student success in the classroom leaving less time and money for attention to physical activity opportunities. Because recess is not a graded subject and takes place during the school day, it is often excluded from physical education or after-school funding opportunities (Ramstetter, Murray, & Garner, 2010). Thirdly, state requirements may affect the attention that is paid to particular wellness policy items. The state of Virginia has standardized testing for students known as the Standards of Learning (SOLs), which are expectations for student learning and achievement in grades K-12 (http://www.doe.virginia.gov/testing/sol/standards_docs/index.shtml). SOLs are in place for health and physical education for all students in grades K-12. According to the Mississippi Department of Education, standardized tests are not given to students in Mississippi for health or physical education (http://www.mde.k12.ms.us/ACAD/osa/satp.html). Although this wellness policy evaluation tool has not been used to assess the school systems in Virginia, it is possible if Mississippi implemented standardized testing in these areas, the policy items would be strengthened. Given this appears to be the fi rst statewide report using the School Wellness Policy Evaluation Tool to evaluate the comprehensiveness and strength of the physical education and physical activity components of school wellness policies, direct comparison of results with other studies is problematic; however, some indirect comparisons may be useful. Mean comprehensiveness and strength values calculated in the present study are similar to those reported by Schwartz et al. (2009) in their tool development study. The mean (SD) comprehensiveness score in the present study was 52.0 (15.7) and the mean strength score was 47.2 (16.4). This is comparable to the results from the Schwartz et al. (2009) study in which the mean comprehensiveness score was 53.0 (15.0) and the mean strength score was 36.0 (15). These fi ndings (Schwartz et al., 2009) indicate that policies consistently scored higher on comprehensiveness than strength. Such a fi nding supports the theory that comprehensiveness and strength are two levels of policy quality, with strength the more diffi cult to achieve. In another study, a statewide sample of school wellness policies from Utah was evaluated by Metos & Nanney (2007). Researchers developed a model for assessing school wellness policies that addressed specifi cs of policy content including: mandate

language and several items relative to physical education and physical activity. While this is a completely different evaluation tool, it is worth mentioning here because of its focus on physical education and physical activity. Metos & Nanney (2007) reported that 14% of the wellness polices in Utah schools “recommended” and 86% “mandated” the inclusion of at least two recess periods with active play each day in elementary school. In the sample of Mississippi wellness policies, 81% did not mention the provision of daily recess in elementary school while 19% scored a “1” or “2” on this item (Item 14), meaning less attention was given to the provision of recess. Secondly, in Utah, 66% of wellness polices recommended and 33% mandated restricting the use of recess as a reward or withholding recess as a punishment. In the present sample from Mississippi, 93.2% of wellness policies failed to mention not restricting physical activity as punishment and only 6.8% scored a “2” on the item (Item 13). A fi nal comparison point is, in Utah, 62% of wellness policies recommended and 38% mandated including and promoting intramural sports and fi tness activities. In Mississippi, 31.6% did not mention, 39.3% scored a “1,” and 29.1% scored a “2” on Item 11 which addressed “structured physical activity before or after school through clubs, classes, intramurals or interscholastic activities.” Another wellness policy study worth noting was conducted by Probart et al. (2008) involving 499 public schools in Pennsylvania. Several Mississippi vs Pennsylvania comparisons can be made, including use of physical activity as punishment (PA 54%, MS 6.8%), access to school facilities for physical activity after school hours (PA 59.1%, MS 4.2%), professional development for PE staff/physical education training for staff (PA 56.5%, MS 5.0%), classroom physical activity breaks for elementary students (PA 45.7%, MS 41.9%), and teacher-to-student ratio in physical education (PA- 31.3%, MS 86.4%). In these comparisons Pennsylvania scores much higher on 4 of the 5 selected wellness policy items. One possible explanation for the differences is the nature of the policy evaluation tools used. Another explanation may be that Pennsylvania, like Virginia, has standardized testing for health, safety, and physical education (http://www.portal.state.pa.us/portal/server.pt/community/state_academic_standards/19721). A fi nal comparison can be made with the Moag-Stahlberg, Howley, & Luscri (2009) evaluation of a nationwide sample of 256 school wellness policies. They reported that only 9% of the policies addressed teacher-to-student ratio in physical education classes as compared to 86.4% of Mississippi policies. Nationwide, 48% of policies addressed recess requirements as compared to 19% in Mississippi. Thus, wellness policy evaluations between Mississippi and other states resulted in mixed fi ndings. Differences may be in part due to lack of a universal wellness policy evaluation tool and suggest the importance of establishing a common instrument to assess school wellness policies. If the School Wellness Policy Evaluation Tool were to serve this purpose, benchmark values would emerge against which individual schools and states could assess the relative strength of their wellness policies.

LIMITATIONSThis study was limited to a sample of school wellness policies from Mississippi public schools. Generalizability of results to schools in other states, or to non-public schools, is unknown. The small scoring range of the evaluation tool may also limit the results of the study. Because there are only three scores “0,” “1,” or “2” that a school can score on a particular wellness policy item, the results are going to be much more homogeneous.

CONCLUSIONMississippi public school wellness policies contained strong language relative to most physical education related policy items. The policies were much weaker in attention to physical activity related policy items. Attention should be paid to policy items that were not present in the majority of the Mississippi wellness policies, for example, Item 8 (District provides physical education training for physical education


teachers). Indirect comparisons with other states suggest Mississippi public school wellness policies are not as strong at addressing physical education and, especially, physical activity policy items. Further research is warranted to examine school wellness policies of other states using the School Wellness Policy Evaluation Tool.

REFERENCESAgron, P., Berends, V., Ellis, K., & Gonzalez, M. (2010). School wellness policies: perceptions, barriers, and needs among school leaders and wellness advocates. Journal of School Health, 80, 527-535.

Levi, J., Vinter, S., St. Laurent, R., & Segal, L.M. (2010). F as in Fat: How Obesity Threatens America’s Future, 2010. Trust for America’s Health & Robert Wood Johnson Foundation, p. 16.

Metos, J. & Nanney, M.S. (2007). The strength of school wellness policies: one state’s experience. Journal of School Health, 77, 367-372.

Moag-Stahlberg, A., Howley, N., & Luscri, L. (2008). A national snapshot of local school wellness policies. Journal of School Health, 78, 562-568.

Mississippi School Nutrition Environment Evaluation Data System (MS NEEDS): Technical One Year (2008-2009) Outcomes. (2010). Center for Mississippi Health Policy. Retrieved January 3, 2011, from http://www.mshealthpolicy.com/documents/MSNEEDSYearOne_Report1-1-2010.pdf

Probart, C., McDonnell, E., Weirich, J.E., Schilling, L., & Fekete, V. (2008). Statewide assessment of local wellness policies in Pennsylvania public school districts. Journal of the American Dietetic Association, 108, 1497-1502.

Ramstetter, C.L., Murray, R., & Garner, A.S. (2010). The crucial role of recess in schools. Journal of School Health, 80, 517-526.

Riffe, D., Lacy, S., & Fico G. (1998). Analyzing Media Messages: Using Quantitative Content Analysis in Research. Mahwah, NJ: Lawrence Erlbaum. p. 131.

School Wellness Policy Evaluation Tool. (2010). Robert Wood Johnson Foundation Healthy Eating Research Group, Working Group 1, Retrieved January 3, 2011, from http://www.yaleruddcenter.org/resources/upload/docs/what/communities/SchoolWellnessPolicyEvaluationTool.pdf

Schwartz, M.B., Lund, A.E., Grow, H.M., McDonnell, E., Probart, C., Samuelson, A., & Lytle, L. (2009). A comprehensive coding system to measure the quality of school wellness policies. Journal of the American Dietetic Association, 109, 1256-1262.

State Academic Standards. (2011). Pennsylvania Department of Education. Retrieved September 22, 2011 from, http://www.portal.state.pa.us/portal/server.pt/community/state_academic_standards/19721

Subject Area Testing Program (SATP). Mississippi Department of Education. Retrieved September 22, 2011, from http://www.mde.k12.ms.us/ACAD/osa/satp.html

The Standards & SOL-Based Instructional Resources. (2011). Virginia Department of Education. Retrieved September 22, 2011, from http://www.doe.virginia.gov/testing/sol/standards_docs/index.shtml

Thomas, J., & Nelson, K. (2001). Research Methods in Physical Activity (4th ed.). Champaign, IL: Human Kinetics.

USDA Food and Nutrition Service. The Child Nutrition and Women Infants and Children (WIC) Reauthorization Act of 2004 (Sec. 204 of P.L. 108-205). Accessed December 31, 2010.


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MAHPERD Journal 01

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