1. Predictors of Snack Food Consumption Among 4th and 5th Grade Children Using Select Constructs of Social Cognitive Theory: Implications for Health Promoting Interventions
Paul Branscum MS, RD, LD & Dr. Manoj Sharma (advisor)
The University of Cincinnati
Introduction
Childhood overweight has tripled in the past 30 years (Ogden, et al., 2006)
Consequences:
Metabolic (i.e. Type 2 Diabetes, Metabolic Syndrome)
Psychological (i.e. Depression, Social Isolation) (Daniels, et al., 2005)
Increased Health Care Expenditures (Wang, & Dietz, 2002).
Contributing Factors:
Genetics, Environment, Personal Factors (i.e. Diet and Physical Activity) (Daniels, et. al., 2005)
One dietary pattern that has increased among children of all age groups is snacking behaviors.
Youth consume one-fourth to one-third of their daily caloric intake from snack foods.
Snack foods tend to be higher in fat and energy density
Frequent snacking has been associated with higher daily intakes of fat, refined sugar and calories. (Ritchie, Crawford, Woodward-Lopez, Ivey, Masch, & Ikeda, 2001)
One strategy for intervention is through Health-Promoting Interventions, which have the potential to:
Prevent Onset of Overweight
Promote Healthy Lifestyle into Adulthood
Curtail Future Health Care Costs
Social Cognitive Theory has also been noted as the most successful theoretical basis for such interventions.
Critical to have valid / reliable evaluations tools.
The purpose of this research is to (1) determine the validity and reliability of an instrument measuring select constructs of social cognitive theory pertaining to snacking behaviors, and (2) use select constructs to identify predictors of children’s snacking behaviors.
Methods
Aim 1 – Instrument Validity & Reliability
Instrument was administered to 4th & 5th grade school children at select elementary schools in the Princeton City School District, Cincinnati, OH.
A sample size of 197 has been obtained with an alpha of 0.05, power of 0.80 and population correlation coefficient of 0.20 (Polit & Hungler, 1999)
Face & Content Validity
Instrument evaluated by six experts in the fields of: Social Cognitive Theory, Nutrition, Childhood Development and Instrumentation.
Nancy Brody, MS (YMCA Greater Columbus Area), Dr. Randall Cottrell & Dr. Manoj Sharma (The University of Cincinnati), Dr. Jeffrey Martin (Wayne State University), & Dr. Carla Miller & Dr. Rick Petosa (The Ohio State University)
Construct Validity
Confirmatory factor analysis used to determine the following factors :
Self Efficacy for Overcoming Barriers for Choosing Healthy Snack Foods (SEBAR)
Self Efficacy for Choosing Healthy Snack Foods (SEBEH)
Outcome Expectations (EX) / Expectancies (OE) for Choosing Healthy Snack Foods
Self Control for Choosing Healthy Snack Foods (SC)
Internal Consistency Reliability - Cronbach’s alpha of 0.70 (critical limit).
Test-Retest Reliability - A Pearson-product moment correlation of 0.70 (critical limit).
Results
Aim 2 – Predictors of Healthy Snacking Behaviors
*Note: Other social cognitive theory constructs were not significant
Methods (cont.)
Aim 2 – Predictors of Healthy Snacking Behaviors
Children reported all foods eating outside of meals for previous day at time of testing.
USDA National Nutrient Database for Standard Reference, Release 18 used to summate Calories from reported snack foods.
Dependent Variables
Calories from: 1.) Calorically-Dense/Nutrient Poor Snack Foods; 2.) Sugar Sweetened Beverages; 3.) Fruits and Vegetables
Independent Variables
Select Constructs of Social Cognitive Theory
Stepwise multiple regression modeling will be used to evaluate predictors of snacking behaviors.
The a priori criteria to enter the predictor model was set at an alpha of 0.05 and the criteria to be removed from the model was an alpha of 0.10.
Results
Aim 1 – Instrument Validity & Reliability
Means and Standard Deviations of Scores of Social Cognitive Theory Constructs
n Minimum Maximum Mean Standard
Deviation
Self Efficacy for Overcoming Barriers
for Eating Healthy Snack Foods
Self Efficacy for Eating
Healthy Snack Foods
Expectations for Eating
Healthy Snack Foods
Self Control for Eating
Healthy Snack Foods
Parameter estimates from the final regression model for calories from fruits and vegetables as predicted by total self control
(Adjusted R 2 = 0.017) (n=178)
Parameter Unstandardized Standard Standardized t p-value
Coefficient Error Coefficient Beta
Constant
Total Self Control
Child Demographics (n = 212)
Gender
Male (41%) Female (59%)
Age
Mean (SD) = 9.75 (.98)
Ethnicity
White = 39.0% Black =23.3%
Hispanic =18.1% Other = 19.7%
Parameter estimates from the final regression model for calories from sugar sweetened beverages as predicted by total self control
(Adjusted R 2 = 0.022) (n=177)
Parameter Unstandardized Standard Standardized t p-value
Coefficient Error Coefficient Beta
Constant
Total Self Control
SEBAR
Factor Loadings
SEBAR1
SEBAR2
SEBAR3
SEBAR4
SEBAR5
SEBAR6
.479
.582
.506
.525
.685
.752
Cronbach α
α = .79
Test/Retest
=.49
SEBEH
Factor Loadings
SEBEH1
SEBEH2
SEBEH3
SEBEH4
.508
.468
.826
.905
Cronbach α
α = .79
Test/Retest
=.62 EX
Factor Loadings
EX1
EX2
EX3
.603
.565
.680
Cronbach α
α = .64
Test/Retest
=.82 OE
Factor Loadings
OE1
OE2
OE3
.827
.508
.581
Cronbach α
α = .66
Test/Retest
=.65 SC
Factor Loadings
SC1
SC2
SC3
SC4
SC5
SC6
.730
.709
.739
.859
.652
.478
Cronbach α
α = .85
Test/Retest
=.70
Discussion
This instrument appears to have adequate validity and reliability.
No constructs were significant predictors for Calories from Calorically-Dense/Nutrient Poor Snack Foods
Self Control was a significant negative predictor for Calories from Sugar Sweetened Beverages and significant positive predictor for Calories from Fruits and Vegetables.
Suggests SELF CONTROL may be the most important predictor for this dietary behavior.
References
Daniels, S.R., Arnett, D.K., Eckel, R.H., Gidding, S.S., Hayman, L.L., Kumanyika, S., et al. (2005). Overwieght in children and adolescents: Pathophysiology, consequences, prevention and treatment. Circulation, 111,
Ogden, C.L., Carroll, M.D., Curtin, L.R., McDowell, M.A., Tabak, C.J., & Flegal, K.M. (2006). Prevalence of overweight and obesity in the United State Journal of the American Medical Association, 295,
Polit, D. F., & Hungler, B. P. (1999). Nursing research. Principles and methods. (6th ed.). Philadelphia: J. B. Lippincott Company.
Ritchie, L., Crawford, P., Woodward-Lopez, G., Ivey, S., Masch, M., & Ikeda, J. (2001). Pediatric overweight: a review of literature. The Center for Weight and Health Position Paper, University of California at Berkley.
Wang, G., & Dietz, W.H. (2002). Economic burden of obesity in youths aged 6-17 years: Pediatrics, 109, e81