1. Background image: Old Main
Identifying Fitness Level Disparities for Minority, Low Socioeconomic Status Children
Lila M. Gutuskey1, Mariane M. Fahlman1, Heather Hall2
Wayne State University1, Elmhurst College2
Background/Purpose: There is a strong link between childhood cardiovascular fitness, healthy body
composition, and cardiovascular disease later in life. Morbidity and mortality related to cardiovascular
disease disproportionally impact non-white minorities and people of low socioeconomic status (SES).
The purpose of this research was to determine whether urban minority 4th graders of low SES differed in
measures of health related fitness or self-efficacy related to physical activity when compared to non-
minority children who were not identified as low SES.
Method: This was a quasi-experimental design involving 1,432 fourth graders who self-identified as
Black, Hispanic or White and were coded as either high socioeconomic status (H-SES) or low
socioeconomic (L-SES) based on eligibility for free or reduced lunches. A valid and reliable seven item
perceived self-efficacy to perform physical activity scale was used to measure self-efficacy. Health
related components of physical fitness were tested using the FitnessgramR.
Statistics on boys and girls were run separately. A 2 (H-SES vs L-SES) by 3 (Hispanic, African
American, White) MANOVA was run on the dependent variables. ANOVAs were conducted on
dependent variables by ethnicity. When significance was found, a Tukey post hoc was performed.
Independent samples t-tests were run to determine dependent variables that differed based on SES.
Analysis/Results: Among girls, significant main effects were found for ethnicity F (2, 698) = 2.779, p <
0.001; and SES t = 5.891, p < 0.001. Post hoc analysis revealed significant ethnic differences on the
following dependent variables: mile run, curl-ups, push-ups, body mass index and self-efficacy. Students
identified as low SES scored lower than those identified as high in the variables mile run, curl-ups, push-
ups, BMI, and self-efficacy.
Among boys, significant main effects were found for ethnicity F (2, 714) = 3.174, p < 0.001; and SES t =
5.024, p < 0.001. Post hoc analysis revealed significant ethnic differences on the following dependent
variables: mile run, curl-ups, push-ups, BMI, trunk extension and self-efficacy. Students identified as
low SES scored lower than those identified as high in the variables mile run, curl-ups, push-ups, BMI,
and self-efficacy.
Conclusion: This study identified disparities in physical fitness and physical activity self-efficacy
between low income, minority children and their higher income, white peers. Health interventions
focused on increasing minority children’s fitness levels could help reduce incidences of obesity and
associated deleterious health effects and might narrow the existing health gap between segments of
society based on income and ethnicity.
ABSTRACT
• Morbidity and mortality related to cardiovascular disease disproportionately impact nonwhite
minorities and people of low socio-economic status (SES; Delva, O'Malley, & Johnston, 2006).
Urban populations are particularly rife with factors that contribute to poor health outcomes, including
large minority populations living in poverty.
• While multiple factors contribute to cardiovascular disease, a key component is a lack of physical
activity (PA) that tracks back to childhood (Janz, Dawson, & Mahoney, 2000), particularly in non-
white populations.
• Since multiple body systems are required to perform that activity, levels of “physical fitness” are
significant markers of health as well as potential predictors of future morbidity and mortality (Ortega,
Ruiz, Castillo, & Msjostrom, 2008). Ruiz et al. (2009) concluded that there is strong evidence for the
link between childhood cardiovascular fitness, healthy body composition and cardiovascular health
later in life.
• There are multiple studies that support the fact that fitness levels demonstrate patterns similar to
activity levels; they decrease with age, and this decrease is more prevalent in minorities and people of
low SES. Non-Hispanic Blacks have been found to have significantly lower measures of
cardiorespiratory fitness than other races (Caeser, Fitzhugh, Thompson & Bassett, 2013; Duncan, Li &
Zhou, 2005; Sanders & Duncan, 2006), and given the protective effects of cardiovascular fitness,
increasing cardiovascular fitness could significantly impact future disease rates (Sanders & Duncan,
2006).
• The purpose of this research was to determine whether urban minority fourth and fifth graders of low
socio-economic status differed in measures of health related fitness or self-efficacy related to physical
activity when compared to suburban non-minority children who were not identified as low
socioeconomic status.
INTRODUCTION
Participants
The original sample consisted of 1,632 fourth and fifth grade boys and girls enrolled in elementary
schools in a large Midwestern city and suburb. The final sample consisted of 1,432 (87%) students who
completed all aspects of the study.
Table 1. Demographic Information
Instruments
• A valid and reliable seven item perceived self-efficacy to perform physical activity scale was used to
measure self-efficacy (Martin & McCaughtry, 2008). The internal reliability coefficient was .82.
• Health related components of physical fitness were tested using the FitnessgramR (Cooper Institute
for Aerobics, 1994). The test was conducted by trained technicians and students were familiarized
with the procedure for each test prior to recording the data. The following areas were tested: aerobic
capacity (one-mile run), abdominal strength and endurance (curl-ups), upper body strength and
endurance (push-up), hamstring flexibility (back-saver sit and reach), and trunk extensor strength and
flexibility.
Analysis
• Eight dependent variables in this study: seven measures of health related fitness and self-efficacy for
physical activity.
• Independent samples t-tests were run to determine if dependent variables differed based on gender.
Since there were significant gender differences in several of the dependent variables, boys and girls
were run separately for the rest of the analysis.
• Due to the interaction between ethnicity and SES, separate logistic regression analyses were
conducted for each dependent variable with ethnicity and SES entered as covariates.
• Since ethnicity proved to be an independent predictor in all but three instances, separate univariate
ANOVAs were conducted on the dependent variables by ethnicity.
• Independent samples t-tests were run to determine dependent variables that differed based on SES.
• Due to the number of dependent variables, a Bonferroni correction factor was applied and the
significance level was set at 0.006.
THEORETICAL FRAMEWORK
Girls
Among girls, significant main effects were found for ethnicity (F (2, 698) = 2.779, p < 0.001); and SES
(t = 5.891, p < 0.001). Subsequent post hoc analysis revealed significant ethnic differences on the
following dependent variables mile run (F(2,672) = 23.7, p < 0.001); curl-ups (F(2,699) = 26.3, p <
0.001); push-ups (F(2,699) = 22.5, p < 0.001); body mass index (F(2,710) = 10.3, p < 0.001); (Table 2).
There was also a significant difference in self-efficacy (F(2,701) = 16.2, p < 0.001); (Table 3). Students
who were identified as low SES scored lower than those identified as high in the variables mile run, curl-
ups, push-ups, BMI, and self-efficacy (Table 4). The logistic regression analysis revealed that ethnicity
was a separate predictor for the variables mile run, curl-ups, push-ups, BMI, trunk lift, and self-efficacy.
SES was a separate predictor for the variables mile run, curl-ups, push-ups, BMI, and self-efficacy.
Table 2. Dependent variables by race/ethnicity in girls (mean  SEM)
RESULTS
• Both minority status and low SES were independent factors contributing to the fact that urban
students scored lower than their suburban counterparts on both fitness measures and self-efficacy to
perform physical activity.
• This study identifies that these discrepancies are now occurring as early as ten years of age,
especially when past research provides strong support for the notion that physical activity declines
with age and obesity levels carry over into adulthood with severe health consequences.
• We believe that urban school-based interventions have great potential for improving student health
behaviors and changing the patterns of unhealthy eating and low physical activity that lead to dire
consequences in adulthood.
• School-based health interventions, grounded in Social Cognitive Theory, specifically focused on
increasing minority children’s fitness levels and promoting healthy eating behaviors could help
reduce incidences of obesity and associated deleterious health effects, and might, in fact, narrow the
existing health gaps between segments of society based on income and ethnicity.
CONCLUSIONS
Black Hispanic White
Low SES High SES Low SES High SES Low SES High SES
Girls (n=712) 206 32 207 30 27 210
Boys (n=720) 215 20 203 37 23 222
METHODS
• Bandura’s Social Cognitive Theory, specifically self-efficacy, has been used to explain declines in
physical activity as students age (Bandura, 1986).
• Students who feel more confident in their ability to perform regular exercise are more likely to develop
regular exercise habits.
• Whitehead (1995) observed that physical self-perceptions of body, sport competence, physical
conditioning and general physical self-worth were all related to several indicators of anaerobic fitness,
aerobic fitness, and muscular strength in seventh and eighth graders.
• Several studies have reported that self-efficacy is related to exercise behavior specifically in minority
children (Hausenblas, Nigg, Downs, Fleming, & Connaughton, 2002; Martin & McCaughtry, 2008;
Trost et al., 2002).
Variable Black Hispanic White F p
Mile run (seconds) 833.4  26.6 1 913.6  41.0 2 705.6  13.0 1,2 23.7 <0.001
Curl-ups (#) 23.0  2.3 1,2 10.5  1.5 1,3 37.1  2.1 2,3 26.3 <0.001
Push-ups (#) 04.7  0.7 1 04.2  0.9 2 11.7  0.7 1,2 22.5 <0.001
BMI (kg/m2) 22.7  6.0 1 24.7 24.5 2 16.4 + 0.3 2,3 10.3 <0.001
Trunk extension (inches) 11.1  0.0 10.3  0.3 10.8  0.2 1.8 0.168
Sit and reach (R) (inches) 9.3  0.7 8.3  0.9 9.6 0.3 1.5 0.225
Sit and reach (L) (inches) 9.4  0.7 8.5  0.9 9.9  0.3 1.6 0.231
Self-efficacy 12.5  0.4 9.4  0.4 17.4  0.3 16.2 <0.001
How sure are you that you can: Black Hispanic White
do physical activities on Saturday mornings 1.9  0.2 1 1.3  0.6 2 2.7  0.1 1,2
be good at physical activities 1.9  0.6 1 1.1  0.4 1,2 2.5  0.6 1,2
do physical activities when you have lots of homework 1.9  0.6 1 1.7  0.5 2 1.0  0.5 1,2
do physical activities when you arrive home late after school 1.5  0.5 1 1.4  0.4 2 2.7  0.4 1,2
do physical activities when your parents want you to do
something else
1.6  0.4 1.5  0.5 1.9  0.8
do physical activities when it is very cold outside 1.8  0.3 1.4  0.6 2.8  0.6
do physical activities when you don’t feel like it 1.9  0.6 1,2 1.3  0.6 1,3 2.7  0.6 2,3
Total subscale score 12.5 + 0.41 9.4 + 0.42 16.4 + 0.3 2,3
Table 3. Self-efficacy question responses from girls
Like numbers (1,2,3) indicate significant difference between race/ethnicities (p < 0.004).
Low SES (n = 440) High SES (n = 272) t p
Mile run (seconds) 826 + 18.5 699 + 10.5 -5.09 <0.001
Curl-ups (#) 21.0 + 2.3 39.6 + 1.8 6.424 <0.001
Push-ups (#) 4.4 + 0.4 14.3 + 0.8 11.459 <0.001
BMI (kg/m2) 22.8 + 0.5 18.4 + 0.3 -3.499 0.001
Self-efficacy 10.5 + 0.2 16.5 + 0.2 -3.796 <0.001
Table 4. Dependent variables with significant differences based on SES in girls (mean + SEM)
Boys
Among boys, significant main effects were found for ethnicity (F (2, 714) = 3.174, p < 0.001); and
SES (t = 5.004, p < 0.001). Subsequent post hoc analysis revealed significant ethnic differences on the
following dependent variables: mile run (F(2,702) = 13.9, p < 0.001); curl-ups (F(2,708) = 15.5, p <
0.001); push-ups (F(2,708) = 3.3, p = 0.031); body mass index (F(2,714) = 21.7, p < 0.001); trunk
extension (F(2,702) = 10.3, p < 0.001); (Table 5). There was also a significant difference in self-
efficacy (F(2,714) = 18.5, p < 0.001); (Table 6). Students who were identified as low SES scored
lower than those identified as high in the variables mile run, curl-ups, push-ups, BMI, and self-
efficacy (Table 7). The logistic regression analysis revealed that ethnicity was a separate predictor for
the variables mile run, curl-ups, push-ups, BMI, trunk lift, and self-efficacy. SES was a separate
predictor for the variables mile run, curl-ups, push-ups, BMI, and self-efficacy.
Table 5. Dependent variables by race/ethnicity in boys (mean  SEM)
Variable Black Hispanic White F p
Mile run (seconds) 728.3  33.2 1 840.6  40.2 1,2 654.6  14.6 2 13.9 <0.001
Curl-ups (#) 27.5  2.6 1,2 14.4  2.2 1,3 35.9  2.0 2,3 15.5 <0.001
Push-ups (#) 13.1  1.5 1 8.8  1.4 1,2 13.7  0.9 2 3.3 0.031
BMI (kg/m2) 21.8  0.8 24.0  0.9 19.4  0.3 21.7 <0.001
Trunk extension (inches) 11.5  0.1 1 10.5  0.4 9.9  0.2 1 10.3 <0.001
Sit and reach (R) (inches) 8.6  0.7 9.9  0.5 8.2  0.3 2.4 0.097
Sit and reach (L).3
(inches)
8.7  0.7 9.7  0.6 8.3  0.3 1.7 0.190
Self-efficacy 14.3  0.3 9.8  0.4 18.0  0.2 18.5 <0.001
Like numbers (1, 2, 3) indicate significant difference between race/ethnicities.
Table 6. Self-efficacy question responses from boys
How sure are you that you can: Black Hispanic White
do physical activities on Saturday mornings 1.9  0.2 1 1.2  0.5 2 2.7  0.1 1,2
be good at physical activities 2.5  0.6 1 1.1  0.4 1,2 2.5  0.6 2
do physical activities when you have lots of homework 2.0  0.6 1 2.0  0.5 2 1.0  0.5 1,2
do physical activities when you arrive home late after school 1.3  0.2 1 1.2  0.5 2 2.7  0.5 1,2
do physical activities when your parents want you to do
something else
2.0  0.4 1.8  0.5 2.0  0.8
do physical activities when it is very cold outside 2.2  0.3 1 1.4  0.6 1,2 2.3  0.5 2
do physical activities when you don’t feel like it 1.5  0.6 1 1.3  0.6 2 2.7  0.6 1,2
Total subscale score 14.3  0.31 9.8  0.42 18.0  0.2 1,2
Like numbers (1,2,3) indicate significant difference between race/ethnicities (p < 0.004).
Table 7. Dependent variables with significant differences based on SES in boys (mean + SEM)
Low SES (n = 441) High SES (n = 279) t p
Mile run (seconds) 782 + 21.5 669 + 12.2 -3.09 <0.001
Curl-ups (#) 16.0 + 2.3 32.4 + 4.8 10.424 <0.001
Push-ups (#) 7.2 + 0.8 12.3 + 0.7 11.232 <0.001
BMI (kg/m2) 21.8 + 0.5 19.4 + 0.3 -3.499 0.001
Self-efficacy 11.5 + 0.2 17.5 + 0.2 -3.796 <0.001