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ASSOCIATIONS OF PHYSICAL ACTIVITY, SEDENTARY BEHAVIOR, AND ENJOYMENT OF PHYSICAL ACTIVITY WITH CHILDREN'S LITERACY.

Obesity is a significant problem in the United States. Vulnerable groups such as those with low literacy, low incomes, and minorities exhibit the highest obesity rates (Mokdad et al., 2003). Indeed, 61% of overweight and obese adult patients believed their weight impacted their health; however, adults with low literacy of health terms as measured by the Rapid Estimate of Adult Literacy in Medicine (REALM) were less likely to be aware of this relationship and were less likely to indicate a need to lose weight (Kennen et al., 2005).

While the rise in prevalence of obesity in the past 35 years in the U.S. is due to multiple factors, declining physical activity among youth must be considered. In addition to the impact of low physical activity on various chronic diseases, Hillman, Kamijo, and Scudder (2011) point to the impact that physical inactivity may have on cognitive function and brain health. Evidence of a positive effect of aerobic fitness on cognition and brain health in preadolescent children has been demonstrated on reaction time and response accuracy tasks (Hillman, Kramer, Belopolsky, and Smith, 2006). Tine (2014) found that a 12-minute bout of running in place in which participants maintained a heart rate of 70-80% of their age-predicted maximum improved the selective visual attention (SVA) of both low- and high-income adolescents. Furthermore, this benefit persisted for 45 minutes after the acute bout of aerobic exercise. Similar results were found with sixth- and seventh-grade children (Tine & Butler, 2012).

There are few studies on the effects of chronic physical activity on literacy. A 2003 study of children with dyslexia utilized a six-month home-based motor skill intervention consisting of balance board activity, throwing and catching, dual tasking, and a range of stretching and coordination exercises (Reynolds, Nicolson, & Hambly, 2003). Compared to a control group the intervention group improved in dexterity, reading, verbal fluency and semantic fluency. The treatment group also improved from their previous year's scores on national standardized tests of reading, writing, and comprehension. Due to a host of design, methodological, and potential competing financial interest issues (conflicts of interest), findings from the Reynolds, Nicolson and Hamby study have been criticized by some researchers as scientifically untenable (Singleton & Stuart, 2003).

A recent study utilizing active classroom equipment with first-graders, found that scores on the Dynamic Indicators of Basic Early Literary Skills (DIBELS) improved more over a five-month period compared to their peers who did not use the equipment (McCrady-Spitzer, Moanohar, Koepp, & Levine, 2015). Due to the design of the study, however, it was uncertain if literacy improved because of the intervention or if improvement was due to maturation that would naturally occur during the school year.

While evidence exists that physical activity may contribute to cognitive function, a significant percentage of children are inactive. It is intuitive that enjoyment of physical activity should predict sport and physical activity involvement, because enjoyment of the activity may indicate intrinsic motivation to be active. Intrinsic motivation is related to habit formation and potential long-term habitual physical activity (Remmers, Sleddens, Kremers, & Thijs, 2015). Motl et al. (2001) demonstrated the relationship between enjoyment of physical activity and physical activity behavior in adolescent girls using a validated instrument called the Physical Activity Enjoyment Scale (PACES). Similarly, a recent study using PACES found that physical activity enjoyment was significantly related to physical activity (combination of all intensities) but not related to light physical activity or moderate-to-vigorous physical activity (MVPA) (Remmers et al., 2015).

In addition to the effects of physical activity on health and literacy, the impact of time spent in sedentary activity should also be considered (Bassett, Freedson, & Kozey, 2010). Sedentary behavior is a construct distinct from lack of moderate-to-vigorous physical activity and should be considered an independent predictor of disease (Owen, Healy, Matthews, & Dunstan, 2010). It makes sense to consider the potential impact of sedentary behavior on literacy.

The purpose, therefore, of this study was to examine the relationships between objectively measured physical activity, sedentary behavior, and enjoyment of physical activity with reading scores in a sample of children participating in a community literacy program. We hypothesize that moderate-to-vigorous physical activity and enjoyment of physical activity will be positively related to literacy scores, whereas, sedentary behavior will be negatively correlated with reading scores.

Methods

The methods and procedures were approved by the Institutional Review Board of Augusta University.

Participants

Children (n = 30) aged seven to eleven years who received tutoring from a community literacy center in the southeast United States were recruited to participate in this study. Consent was obtained from the child and each child's parent or guardian. Due to failure to wear the ActiGraph for at least 8 hours per day for two school days and one weekend day or holiday, ten children were dropped from the analysis leaving 20 participants. Data were collected in March, April, and May of 2016.

Measurements

Assessment of physical activity and sedentary behavior. Children wore an ActiGraph WGT3X-BT (Actigraph LLC, Pensacola, FL) triaxial accelerometer for two week days and one weekend day or school holiday. The ActiGraph was worn at the waist on an elasticized belt on the right mid-axillary line. Participants were asked to put on the ActiGraph in the morning shortly after waking and remove it just before bed time. The parent or guardian was trained to help the child apply and take off the device. During the day, the ActiGraph was only to be removed for water-related activities. Accelerometer data for each child were uploaded to the ActiLife software program (v6.13.2). Data were analyzed for minutes spent in moderate-to-vigorous physical activity (MVPA), and percentage of time spent in sedentary activity (ST) using cut points established by Evenson, Catallier, Gill, Ondrak, and McMurray (2008). A review on accelerometer methods in youth (Cain, Sallis, Conway, Van Dyck, & Calhoon, 2013) found that the Evenson et al., (2008) cut points were best for classification at all intensities including sedentary activity. Also reported is the number of steps per minute (SPM) for participants.

Accelerometers were set to record data in 10 second epochs. Wear time validation was conducted for each day's data using the Troiano algorithm as described in a 2008 paper (Troiano. Berrigani, Dodd, Masse, Tilert, & McDowell). Eight hours (480 min) of valid accelerometer data per day for each day were required for inclusion in the analysis. Cases with less than 480 minutes of valid wear time for any day were excluded from analysis. Participants had to have three valid days, two school days and one weekend/holiday day to be included in the analysis.

Attitudes toward physical activity. Children's attitudes toward physical activity were assessed using the Physical Activity Enjoyment Scale (PACES) (Motl et al., 2001). Participants were asked to respond to 16 statements using a 5-point Likert-type scale ranging from 1 (disagree a lot) to 5 (agree a lot). A study by Moore et al. (2009) provided support for PACES as a valid measure of enjoyment of physical activity in elementary school age children.

Reading assessment Participants in the literacy center were administered the Gray Diagnostic Reading Tests-second edition, by literacy center personnel, as part of their program (Bryant, Wiederholt, & Bryant, 2004). This test assesses specific abilities and weaknesses in children who have difficulty reading continuous print. Included are four core subtests and three supplemental subtests. Three composites are derived from these subtests: decoding (DC), comprehension (COMP), and general reading (GR). Composite scores for participants were obtained from the literacy center files. These values were converted to z-scores and included in the data analysis. Composite scores were not available for two of the participants. One participant progressed through the program quickly reaching grade-12 reading level before having an opportunity to take the reading test. Another participant was having such difficulty reading that literacy center staff decided to delay his test to avoid discouraging him.

Height and body mass. Body height was measured using a portable stadiometer (nearest 0.5 cm). Body mass was determined using a portable scale (nearest 0.1 kg). Both measures were taken without shoes. Body mass index (kg [m.sup.-2]) and body mass index z-scores (BMI-z) were calculated.

Data Collection

All data collection occurred at the literacy center. On the participant's initial visit with the investigator, the participant and parent were briefed on the study. Subsequently both parent and child completed consent forms. Body mass and height measures were then acquired. Participants then completed the Physical Activity Enjoyment Scale (PACES). Finally with the parent present, the participant was given an ActiGraph accelerometer and instructed on the proper way to wear the device and asked to wear the device for the waking hours on two school days and one weekend day/holiday. About a week later, the investigator collected the ActiGraph from the participant at the literacy center. Independent of this study, all literacy center participants are administered the Gray Diagnostic Reading Tests-second edition each academic year by literacy center personnel. The investigator acquired this information on each participant from the literacy center files.

Data Analysis

Means and standard deviations of all variables were computed. Correlations were computed to examine associations between MVPA, ST, PACES, SPM, DC, COMP, GR, and BMI-z.

Results

Characteristics of the participants who met the wear time requirement for inclusion in the analysis (n = 20) are shown in Table 1. The mean age of those retained in the study was 9.5 years (SD = 1.5). A more even gender mix was found for the retained sample (45% female, 55% male) compared to the total sample (33% female, 67% male).

Table 2 shows accelerometer values. The average wear time for participants was 2233.8 minutes for the three days or 744.6 minutes (12 hours and 25 minutes) per day. On average, children engaged in 50.9 minutes per day of moderate-to-vigorous physical activity (MVPA), thus falling short of the recommended 60 minutes daily (Physical Activity Guidelines Advisory Committee, 2008). Examination of individual participant data revealed seven of the 20 children (35%) averaged 60 minutes of MVPA across the three days.

Scores on PACES, and the Grays Diagnostic Reading Tests-second edition are presented in Table 3. The PACES scores were quite high as the mean was 72.9 (SD = 6.4) out of a possible score of 80. Scores on the Gray Diagnostic Reading Tests indicate that participants performed slightly better than average on DC and COMP while they were below average on GR.

Table 4 presents correlations between variables. Correlations between the subscales of the Gray Diagnostic Reading Tests-second edition were high (.80-.94) as expected. Also strong were the relationships between steps per minute and minutes of moderate-to-vigorous physical activity (.59), and sedentary time (-.60). The strongest relationship between physical activity and reading variables was steps per minute to GR (.33). COMP was mildly correlated with SPM (.274). As one would predict, BMI-z was inversely related to SPM (-.36) and MVPA-M (-.30). There was also a mild inverse relationship between BMI-z and both reading comprehension score (-.21) and general reading score (-.17).

An inverse relationship was found between PACES and ST (-.31). Enjoyment of physical activity (PACES) was not related to MVPA-M (.09) and SPM (.07). These findings parallel those found in similar aged children (8-9 years) from the Netherlands (Remmers et al., 2015).

Conclusion

Most of the children did not meet the Physical Activity Guidelines for Americans (Physical Activity Guidelines Advisory Committee, 2008). Only 35% of the children averaged at least 60 minutes of MVPA across the three days. This is slightly lower than the 42% of 7-11-year-olds who met this requirement in the 2003-2004 National Health and Nutritional Examination Survey (NHANES) (Troiano. Berrigani, Dodd, Masse, Tilert, & McDowell, 2008).

While the relationships between reading and physical activity variables were modest, the data indicate a positive correlation between steps per minute and both general reading and reading comprehension. A mild negative relationship was found between percentage of time spent in sedentary activity (ST) and reading comprehension (RC), and general reading (GR) scores. Also, the relationships between the Gray Diagnostic Tests scores and BMI-z were negative suggesting scores are lower for children who are more overweight. These findings fall in line with the growing body of literature indicating positive relationships between physical activity and cognitive function.

Enjoyment of physical activity (PACES) was inversely related to percentage of time spent in sedentary behavior. This would be expected for a valid indicator of pleasure derived from PA.

A strength of our approach is the use of an accelerometer brand that has a large body of evidence to support its use (Cain et al., 2013). Furthermore, variables used in collecting accelerometer data are reported and are within the range of values recommended for studying children (Cain et al., 2013). We used an epoch length, 10 seconds, that is very common in studies of children (Cain et al., 2013). Daily accelerometer data were submitted to wear time analysis, and a valid day was defined as a minimum of 8 wearing hours. Participants were required to have two valid school days and one valid weekend day to be subjected to data analysis, thus meeting recommendations that suggest at least three days including at least one weekend day to obtain "usual" activity (Cain et al., 2013). Cut points defined by Evenson et al., (2008) were used to determine MVPA and sedentary activity. The sample was racially mixed (45% African-American) and was only slightly weighted toward more male participants (55%).

We acknowledge limitations of this study. Our study used a small number of children who agreed to wear an accelerometer to school for two days and to wear it for one weekend day. This may have been a barrier to some children and part of the reason ten children did not meet the wear time requirement. No data were collected on socioeconomic status. Such information would be valuable in investigating literacy in underserved groups. The small variability of scores on PACES (range = 60-80; mean = 72.9, SD = 6.4) was unexpected and may have limited its use as a predictor variable in the present study. We suspect that even though children were told that there were no right or wrong answers and that they should circle the number that best corresponded to how they felt about the statement, they may have responded in such a way to please the principal investigator who was administering the instrument. Also, it is apparent that our sample was not totally made up of poor readers as DC and COMP scores were better than average. The present study is cross-sectional in nature, therefore, causality between physical activity or, sedentary behavior and indicators of literacy cannot be determined.

In conclusion, modest relationships between physical activity as indicated by steps per minute and literacy values were found. The correlations between both MVPA-M and MVPA-P with literacy scores were lower than expected. Also lower than expected were the correlations between ST and literacy scores. Enjoyment of physical activity (PACES) was not correlated with Gray Reading Test scores. Based on our findings, we suggest further study on physical activity and reading focus less on physical activity intensity and more on total activity. Perhaps a holistic approach to improving literacy in children that includes physical activity along with traditional tutorial methods is warranted.

Summary

There is an increasing body of research on the relationship between physical activity, sedentary behavior, attitudes toward physical activity, and literacy. This study found a modest correlation between steps per minute (SPM) and literacy measurements. In addition, there was a mild correlation among BMI-z, comprehension (COMP), and general reading (GR). Finally, inverse correlations were found between COMP and SPM; and Physical Activity Enjoyment Scale (PACES) and Sedentary Behavior (ST). These results imply that there is an interrelationship amid physical activity and literacy; and that further study is needed to understand these interactions.

References

Bassett, D. R., Freedson, P., & Kozey, S. (2010). Medical hazards of prolonged sitting. Exercise Sport Science Rev, 38(3), 101-102.

Bryant, B., Wiederholt, J. L., & Bryant, D. P. (2004). Gray diagnostic reading tests: Second edition. Austin, TX: ProEd Publishing.

Cain, K. L., Sallis, J. F., Conway, T. L., Van Dyck, D., & Calhoon, L. (2013). Using accelerometers in youth physical activity studies: A review of methods. JPAH, 10, 437-450.

Evenson, K. R., Catellier, D. J., Gill, K., Ondrak, K. S., & McMurray, R. G. (2008). Calibration of two objective measures of physical activity for children. Journal of Sports Science, 26(14): 1557-65.

Hillman, C. H., Kamijo, K., & Scudder, M. (2011). A review of chronic and acute physical activity participation on neuroelectric measures of brain health and cognition during childhood. Prev Med, 52S, S21-S28.

Hillman, C. H., Kramer, A. R, Belopolsky, A. V, & Smith, D. P. (2006). A cross-sectional examination of age and physical activity on performance and event-related potentials in a task switching paradigm. International Journal Psychophysiology, 59, 30-39.

Kennen, E. M, Davis, T. C, Huang, J., Yu, H., Garden, D., Bass, R., & Arnold, C. (2005). Tipping the scales: The effect of literacy on obese patients' knowledge and readiness to lose weight. Southern Medical Journal, 98, 15-19.

McCrady-Spitzer, S. K., Moanohar, C. U., Koepp, G.A., & Levine, J. A. (2015). Low-cost and scalable classroom equipment to promote physical activity and improve education. JPAH, 12, 1259-1263.

Mokdad, A. H., Ford E. S., Bowman, B. A., Dietz, W. H., Vinicor, R, Bales, V. S., & Marks, J. S. (2003). Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA, 289, 76-79.

Moore, J. B., Yin, Z., Hanes, J., Duda, J., Gutin, B., & Barbeau. P. (2009). Measuring enjoyment of physical activity in children: Validation of the physical activity enjoyment scale. Journal of Applied Sport Psychology, 21(Sl), S116-S129.

Motl, R. W., Dishman, R. K., Saunders, R., Dowda, M., Felton, G., & Pate, R. R. (2001). Measuring enjoyment of physical activity in adolescent girls. American Journal of Preventive Medicine, 21(2), 110-117.

Owen, N., Healy, G. N., Matthews, C. E., & Dunstan, D. W. (2010). Too much sitting: The population health science of sedentary behavior. Exercise Sport Science Rev. 38(3), 105-113.

Physical Activity Guidelines Advisory Committee. (2008). Physical Activity Guidelines for Americans. Washington, DC: U.S. Department of Health and Human Services.

Remmers, T., Sleddens, E. F. C, Kremers, S. P. J., & Thijs C. (2015). Moderators of the relationship between physical activity enjoyment and physical activity in children. JPAH, 12, 1066-1073.

Reynolds, D., Nicolson, R. I., & Hambly, H. (2003). Evaluation of an exercise-based treatment for children with reading difficulties. Dyslexia: An International Journal of Research and Practice. 9(1), 48-71.

Singleton, C., & Stuart, M. (2003). Measurement mischief: a critique of Reynolds, Nicolson and Hambly (2003). Dyslexia: An International Journal of Research and Practice, 9(3), 151-60.

Tine, M. (2014). Acute aerobic exercise: An intervention for the selective visual attention and reading comprehension of low-income adolescents. Frontiers in Psychology, 575(5), 1-10. doi: 10:3389/fpsyg.2014.00575.

Tine, M. T., & Butler, A. G. (2012). Acute aerobic exercise impacts selective attention: an exceptional boost in lower-income children. Education Psychology: An International Journal Experimental Education Psychology, doi: 10.1080/01443410.2012.723612

Troiano, R. P., Berrigani, D., Dodd, K. W., Masse, L. C., Tilert, T., & McDowell, M. (2008). Physical activity in the United States measured by accelerometer. Medicine & Science in Sports & Exercise, 40(1), 181-188.

DR. CHARLES R. DARRACOTT

Augusta University

DR. SHIRLEY H. DARRACOTT

Augusta University

DR. PAULETTE P. HARRIS

Augusta University
Table 1. Participant Characteristics

                          Mean     SD

Age (yrs)
Height (cm)                135.5     8.2
Weight (kg)                 33.1     8.7
BMI                         17.8     3.1
Total Accelerometer wear  2205     313.0
time (min)
African American            40%
White (non Hispanic)        53.3%
Race unreported              6.7%

Table 2. Accelerometer values

                            Weekday 1  Weekday 2  Weekend    Total
                            Mean (SD)  Mean (SD)  Mean (SD)  Mean (SD)

Accelerometer wear time      810.8      722.6       700.3    2233.8
(min)                       (112.8)    (166.0)     (108.4)   (251.9)
MVPA                          51.6       44.8        56.3     152.7
(min)                        (23.2)     (19.7)      (44.1)    (69.7)
Percent of wear time spent    61.1       63.9        59.2      60.5
in Sedentary activity         (9.3)      (8.5)      (12.6)     (9.3)
                              11.0       10.6        11.6      11.0
Steps per minute              (3.0)      (2.4)       (4.7)     (2.7)

Abbreviations: min, minutes; MVPA, moderate-to-vigorous physical
activity; SD, standard deviation

Table 3. Reading Scores and Physical Activity Enjoyment Scale.

Measure          Mean (SD)

Decoding           .027(1.116)
z-score
Comprehension      .130 (.965)
z-score
General reading   -.037 (.918)
z-score
PACES            72.9 (6.4)

Abbreviations: PACES, Physical Activity Enjoyment Scale; REALM-Teen,
Rapid Estimate of Adult Literacy in Medicine-Teen; SD,
standard deviation.

Table 4. Correlations

                  PACES  Decoding  Reading  General  BMI    % Sedentary
                                   Comp     Reading         time

PACES                     .015     -.152     .073    -.021  -.314
Decoding           .015             .795     .908    -.062  -.089
Reading Comp      -.152   .795               .941    -.213  -.131
General Reading   -.073   .908      .941             -.167  -.203
BMI-z             -.007  -.162     -.251    -.249            .066
% Sedentary time  -.314  -.089     -.131    -.203    -.106
MVPA               .093   .127      .249     .279    -.113  -.571
Steps/min          .070   .170      .274     .326    -.238  -.601

                  MVPA   Steps/min


PACES              .093   .070
Decoding           .127   .170
Reading Comp       .249   .274
General Reading    .279   .326
BMI-z             -.301  -.363
% Sedentary time  -.571  -.601
MVPA                      .593
Steps/min          .593

Abbreviations: PACES, Physical Activity Enjoyment Scale; BMI-z,
body mass index z-scores; MVPA, moderate-to-vigorous physical activity
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Author:Darracott, Charles R.; Darracott, Shirley H.; Harris, Paulette P.
Publication:Reading Improvement
Date:Jun 22, 2019
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