Applied Research and Evaluation
Social Cognitive Maternal-Mediated Nutritional Correlates of Childhood Obesity
International Quarterly of Community Health Education 2015, Vol. 35(2) 177–191 ! The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0272684X15569678 qch.sagepub.com
Adam P. Knowlden1 and Manoj Sharma2
Abstract The purpose of this investigation was to examine the extent to which the maternalfacilitated, social cognitive theory constructs of environment, emotional coping, expectations, self-control, and self-efficacy predicted child fruit and vegetable consumption and sugar-free beverage intake. Instrumentation comprised three stages of data collection and analysis. Stage 1 included item generation, face and content validity by a panel of six experts, and readability by Flesch Reading Ease and Flesch–Kincaid Grade Level tests. Stage 2 assessed stability of the theoretical constructs using the test–retest procedure with 30 participants. Structural equation modeling was used during Stage 3 to conduct confirmatory factor analysis and to establish predictive validity of the models. A total of 224 respondents participated in this study. Maternal-facilitated home environment and self-efficacy were significant predictors of child fruit and vegetable consumption while maternal-mediated home environment and emotional coping were significant predictors of child sugar-free beverage intake. Keywords childhood obesity, social cognitive theory, mother–child dyad, fruit and vegetable consumption, sugar-sweetened beverage intake
1
Department of Health Science, The University of Alabama, Tuscaloosa, AL, USA Health Promotion & Education Program & Public Health Sciences, The University of Cincinnati, OH, USA
2
Corresponding Author: Adam P. Knowlden, Department of Health Science, The University of Alabama, Russell Hall 457A, P.O. Box 870311, Tuscaloosa, AL 35487-0311, USA. Email: [email protected]
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Introduction In the United States, body mass index prevalence rates suggest 31.8% of children aged 2 to 19 are overweight, with 16.9% of this proportion being of obese status [1]. In children, obesity has been associated with numerous medical comorbidities including asthma, metabolic risk factors, and dental health [2]. Childhood obesity also carries psychological comorbidities including attention deficit hyperactivity disorder, internalizing and externalizing disorders, and sleep apnea [2]. Obesity tracks with age [3], which may make targeting young children particularly important for curtailing the current obesity epidemic [4]. Two behaviors that protect against childhood obesity include adequate consumption of fruits and vegetables and minimal intake of sugar-sweetened beverages [5]. Obesity is a consequence of excessive caloric consumption [6]. Fruits and vegetables contain fiber and enhance satiation, which can lead to an overall reduction in total calories consumed [7]. Additionally, fruits and vegetables are high in nutrients and can help protect against a variety of chronic diseases [8]. For prevention and treatment of obesity, the American Medical Association Obesity Expert Committee on the Assessment, Prevention, and Treatment of Child and Adolescent Overweight and Obesity recommend children to consume at least five cups of fruits and vegetables each day [5]. Soft drinks are a primary source of sugar-sweetened beverages in the United States and contribute to weight gain due to their poor satiation abilities and high caloric content [9]. In regard to sugar-sweetened beverages, the Expert Committee recommends limited consumption, with zero consumption being ideal [5]. To reduce sugarsweetened beverage intake, a recommended strategy is to replace sugar-sweetened beverages with sugar-free beverages [10].
Theoretical Framework In children, the introduction of fruits, vegetables, and sugar-free beverages by parental role models at a young age may increase preference for healthier foods later in life [11]. The home environment offers the most direct context for parental modeling of health behaviors [12]. Subsequently, home-based interventions that incorporate parents as mediators of child fruit, vegetable, and sugar-free beverage intake may reduce a child’s overall risk for obesity [13]. Social cognitive theory has been a staple in developing interventions for increasing fruit and vegetable consumption and decreasing sugar-sweetened beverage intake in children [14, 15]. Social cognitive theory operates on the premise of reciprocal determinism; a causal model that assumes behaviors are influenced by personal and environmental factors [16]. Social cognitive theory may be an optimal model for family- and home-based interventions as the theory can account for social and physical environmental factors that influence the health behaviors of young children [17].
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An advantage of social cognitive theory is its comprehensive nature. Combined, the constructs of social cognitive theory can account for a significant amount of the interaction that occurs between the personal factors and environments within which a behavior is performed [18]. A limitation of social cognitive theory is its large ensemble of constructs, which can make full reification of the framework difficult to apply for intervention purposes. Due to practical limitations, interventionists will typically select from the available social cognitive theory constructs based on those which are likely to have the strongest influence on the behavior they are targeting [14]. In the current study, maternal-facilitated home environment, emotional coping, expectations, self-control, and self-efficacy constructs were selected for testing. Selfefficacy entails the confidence to perform a specific behavior [19]. Bandura [20] has identified self-efficacy as the most salient determinant of behavior change. Sharma et al. [21] identified self-efficacy as a primary predictor for adequate consumption of fruits and vegetables among fifth-grade school children. Self-control, or self-regulation, involves setting goals, developing rewards, monitoring progress, and restructuring influential environments [22]. Self-control works in tandem with self-efficacy to promote behavior change and is important for actualizing self-efficacy. Expectations perform an integral role in motivation to modify a behavior [23]. Using a sample of third-grade students, Resnicow et al. [24] identified expectations as a predictor for fruit and vegetable consumption while Sharma et al. [21] found expectations were associated with increased sugar-free beverage intake. The ability to cope with behavior change is important for maximizing self-efficacy [22]. Young children may experience stress when mothers attempt to modify their diet [25, 26]. The emotional coping construct was operationalized to account for child distress from modifying fruit and vegetable consumption and sugar-free beverage intake [19]. The environment construct was selected as availability and accessibility to resources, as well as parental role modeling, play a critical role in child fruit and vegetable consumption and sugar-free beverage intake [27]. Cullen et al. [28] found child-reported availability of fruits and vegetables and parent-reported accessibility to these foods were significant predictors of child consumption. Given this backdrop, the purpose of this study was to examine the extent to which the selected maternal-facilitated, social cognitive theory constructs of environment, emotional coping, expectations, self-control, and self-efficacy could predict child fruit and vegetable consumption and sugar-free beverage intake.
Methods Participants and Instrumentation Participants for this study were recruited from childcare centers and health-care organizations between March and August 2012 in the Cincinnati Ohio and
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Columbus Ohio regions. Inclusion criteria for participation were mothers at least 18 years of age with at least one child between 4 and 6 years of age. These inclusion criteria were selected as mothers are posited to be primary mediators of behavior change in young children and is an impressionable age for these behaviors [4, 29–32]. Children between 4 and 6 years of age were selected as this age range has important implications for a child’s future health and is the most impressionable age for these behaviors [4, 33]. Three stages of data collection were used to develop the instrument. Stage 1 included assessment of face and content validity of the instrument using a panel of experts. Stage 2 evaluated the stability of the instrument through test–retest. The final stage modeled the data through structural equation modeling to determine the reliability and validity of the instrument. Prior to collecting data from participants, institutional review board approval was sought and obtained to carry out the investigation. Stage 1 procedures. Initial items were modified from a previously validated instrument examining social cognitive theory predictors of childhood obesity. [21]. The original instrument was designed to be completed by fifth-grade students; therefore, the items were modified to meet the needs of the current investigation. First, the items for each construct were adjusted so that the items would reflect maternal-facilitated expectations, self-control, and self-efficacy for child fruit and vegetable consumption and sugar-free beverage intake. Two new constructs, maternal-facilitated environment and emotional coping, were added to the instrument. Second, the behaviors of the children were assessed using proxyself report. That is, mothers self-reported their child’s fruit, vegetable, and beverage behaviors. After modifying the items, the instrument was delivered to a panel of six experts for the evaluation of readability as well as face and content validity. The panel comprised two population experts, two social cognitive theory experts, and two measurement experts. Two rounds of review occurred, resulting in the removal of one item from the environment subscale. Additional recommendations included rewording of several of the subscale items. Two rounds of review resulted in unanimous agreement of the instrument’s face and content validity. The final instrument contained 52 items. Flesch Reading Ease Test (73.1) and the Flesch–Kincaid Grade Level Test (5.7) scores suggested the instrument was fairly easy in terms of reading ease [34] and near a sixth-grade reading level by U.S. educational standards [35]. Based on the panel of experts’ subjective opinion of the instrument’s readability as well as the objective readability scores, the instrument was considered acceptable for the population sampled in this study [36]. The first group of items asked about child fruit, vegetable, sugar-free beverage, and sugar-sweetened beverage behaviors. The first two items asked participants to proxy-recall the past 24 hours and write the exact number of cups of
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fruits and vegetables their child consumed. Pictures of one-half cup and one-cup servings of fruits and vegetables were provided to improve accuracy of proxyrecall of child fruit and vegetable consumption. The next two items asked participants to proxy-recall the past 24 hours and write the exact number of 8-ounce glasses of sugar-free beverages and sugar-sweetened beverages their child consumed. For the purposes of this study, sugar-free beverages were operationalized as beverages that did not contain added sugar or caloric sweeteners. Conversely, sugar-sweetened beverages were operationalized as beverages that did not include added sugar or other caloric sweeteners. A life-size picture of an 8-ounce glass was provided to improve accuracy of proxy-recall of child beverage intake. Examples of commonly consumed sugar-sweetened and sugar-free beverages were also listed. The second group of items asked about the maternal-facilitated home environment for child fruit and vegetable consumption and sugar-free beverage intake. The first three items evaluated the maternal-facilitated home environment for child fruit and vegetable consumption. The next three items evaluated the maternal-facilitated home environment for child sugar-free beverages intake. The stem statement for both subscales was “how often do you.” Both subscales used ratings of never (0), hardly ever (1), sometimes (2), almost always (3), and always (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable environment subscale included, “have enough fruits and vegetables at home for your child to be able to eat five cups every day,” and “eat at least five cups of fruits and vegetables with your child at home every day?” Sample items from the sugar-free beverages environment subscale included “have sugar-free drinks at home for your child to drink,” and “drink sugar-free drinks with your child at home?” The third group of items asked about the maternal-facilitated emotional coping for child fruit and vegetable consumption and sugar-free beverage intake. The first three items evaluated maternal-facilitated emotional coping for child fruit and vegetable consumption. The next three items evaluated maternal-facilitated emotional coping for child sugar-free beverage intake. The stem statement for both subscales asked, “how sure are you that you can help your child.” Both subscales used ratings of not at all sure (0), slightly sure (1), moderately sure (2), very sure (3), and completely sure (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable emotional coping subscale included, “adjust to eating at least five cups of fruits and vegetables every day,” and “manage any negative emotions from your child when you encourage him or her to eat fruits and vegetables?” Sample items from the sugar-free beverage emotional coping subscale included, “drink sugar-free drinks when sugarsweetened drinks are available,” and “manage any negative emotions from your child when you replace sugar-sweetened drinks with sugar-free drinks?” The fourth group of items was about maternal-facilitated outcome expectations of fruit and vegetable consumption and sugar-free beverage intake. The
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first four items evaluated maternal-facilitated outcome expectations for child fruit and vegetable consumption. The stem statement for the subscale asked, “if your child eats five cups of fruits and vegetables every day they will.” Items for maternal-facilitated outcome expectations for child fruit and vegetable consumption subscale included, “not get sick as often,” “have more energy,” “have a better weight,” and “feel better.” The next four items evaluated maternalfacilitated outcome expectations for child sugar-free beverage intake. The stem statement for the subscale asked, “if your child drinks sugar-free drinks instead of sugar-sweetened drinks they will.” Items for the maternal-facilitated outcome expectations for sugar-free beverages subscale included “be more relaxed,” “have more energy,” “have a better weight,” and “feel better.” Both subscales used ratings of never (0), hardly ever (1), sometimes (2), almost always (3), and always (4) for possible score ranges of 0 to 16. The fifth group of items was about maternal-facilitated outcome expectancies of fruit and vegetable consumption and sugar-free beverage intake. The first four items evaluated maternal-facilitated outcome expectancies for child fruit and vegetable consumption. The next four items evaluated maternal-facilitated outcome expectancies for child sugar-free beverage intake. The stem statement for both subscales asked, “overall, how important is it to you that your child will.” Both subscales used ratings of not at all important (0), slightly important (1), moderately important (2), very important (3), and extremely important (4). Each subscale had a range of 0 to 16. Items corresponded to outcome expectations and followed the same construction as the outcome expectations subscales. Expectations for each behavior were calculated by multiplying the four outcome expectations with the four corresponding outcome expectancies and then summating each of the pairs for a possible score range of 0 to 64. The sixth group of items asked about maternal-facilitated self-control for child fruit and vegetable consumption and sugar-free beverage intake. The first three items evaluated maternal-facilitated self-control for child fruit and vegetable consumption. The next three items evaluated maternal-facilitated self-control for child sugar-free beverage intake. The stem statement for both subscales asked, “how sure are you that you can.” Both subscales used ratings of not at all sure (0), slightly sure (1), moderately sure (2), very sure (3), and completely sure (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable self-control subscale included, “set goals to have your child eat five cups of fruits and vegetables every day,” and “plan to have your child eat five cups of fruits and vegetables every day?” Sample items from the sugar-free beverage self-control subscale included, “plan to replace your child’s sugar-sweetened drinks with sugar-free drinks,” and “set goals to replace your child’s sugar-sweetened drinks with sugar-free drinks?” The seventh group of items asked about the maternal-facilitated self-efficacy for child fruit and vegetable consumption and sugar-free beverage intake. The
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first three items evaluated maternal-facilitated self-control for child fruit and vegetable consumption. The next three items evaluated maternal-facilitated self-control for child sugar-free beverage intake. The stem statement for both subscales asked, “how confident are you that you can get your child to.” Both subscales used ratings of not at all confident (0), slightly confident (1), moderately confident (2), very confident (3), and completely confident (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable self-efficacy subscale included, “eat five cups of fruits and vegetables every day,” and “eat five cups of fruits and vegetables every day, even if they do not like them?” Sample items from the sugar-free beverage self-efficacy subscale included, “drink more sugarfree drinks,” and “drink sugar-free drinks every day instead of sugar-sweetened drinks?” The final eight items on the instrument were about demographics and included information on mother/child age, mother/child gender, and mother/ child race. Stage 2 procedures. For test–retest recruitment, 30 respondents who participated in Stage 3 were requested to complete the instrument a second time, 2 weeks following the first administration. Correlations between test–retest constructs were calculated using Pearson’s r, with accepted coefficient values set a priori at .70. The sample size for the two-tailed, matched pairs test–retest procedure was determined using G*Power statistical power analysis software inputting an effect size of 0.55, and alpha of .05, and a power of 0.80 [37]. Data for stage 2 were analyzed using IBM SPSS Statistics Faculty Pack version 22.0. Stage 3 procedures. Stage 3 evaluated construct and predictive validity of the instrument through structural equation modeling. Child fruit and vegetable consumption and child sugar-free beverage intake were modeled separately. Applying a participant-to-parameter ratio of 5:1 with an estimated 40 parameters, a sample size of 200 was required to build the models [38]. Construct validity was determined through confirmatory factor analysis using model Chi-square (2) test, goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), normed fit index (NFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA) values. Goodness-of-fit indices were set a priori with 2 value of p > .05, GFI, AGFI, NFI, and CFI > 0.90, and RMSEA < 0.80 [39]. Convergent validity was assessed through factor loadings, construct reliability, and average variance extracted (AVE) values. Factor loading values less than 0.50 were considered for removal. AVE was set a priori at no less than 0.50, and construct reliability was set at no less than 0.70 [39]. Data for Stage 3 were analyzed using IBM AMOS version 21.0.Construct reliability and AVE were calculated manually by computing formulas developed by Fornell and Larcker [40] with Microsoft Excel 2010.
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Results Descriptive and Convergent Validity Statistics Participants were predominantly Caucasian (72%), married (70%), unemployed/homemakers (49%), with a mean age of 33.2 (SD ¼ 6.8). Results found the majority of the observed social cognitive theory construct scores were in the upper-middle portion of the possible range. Descriptive statistics, including ranges, means, and standard deviations, for child fruit and vegetable behavior, maternal-facilitated fruit and vegetable social cognitive theory constructs, child beverage behaviors, and maternal-facilitated sugar-free beverage social cognitive theory constructs are summarized in Table 1. In terms of convergent validity, results found factor loadings, construct reliability, and AVE values exceeded the a priori standards for all social cognitive theory constructs. For test–retest reliability, two constructs from the fruit and vegetable model, child fruit and vegetable consumption (r ¼ .64) and maternal-facilitated emotional coping (r ¼ .67), fell below the a priori minimum. An additional construct from the sugar-free beverage model, expectations (r ¼ .66), fell below the a priori minimum. Convergent validity statistics, including construct reliability, AVE, and test– retest reliability, are summarized in Table 1. Measurement model fit statistics are provided in the notes section of Table 1.
Maternal-Facilitated Child Fruit and Vegetable Predictive Model Normality of the fruit and vegetable outcome variable residuals was confirmed through the Kolmogorov–Smirnov (K-S) test which retained the null hypothesis that the standardized residuals were normal (D(224) ¼ 0.832, p ¼ .493). Maternal-facilitated fruit and vegetable emotional coping (p ¼ .238), expectations (p ¼ .370), and self-control (p ¼ .294) had nonsignificant direct effects on child fruit and vegetable consumption. Significant direct paths between maternal-facilitated fruit and vegetable environment (p < .001) and self-efficacy (p ¼ .011) on child fruit and vegetable consumption were identified. Combined, the constructs accounted for 24% of the variance in child fruit and vegetable consumption. Fit indices for the final model were satisfactory (2 ¼ 20.423, df ¼ 13, p ¼ .059; GFI ¼ 0.975, AGFI ¼ 0.942, NFI ¼ 0.973, CFI ¼ 0.988, RMSEA ¼ 0.056). Figure 1 provides an illustration of the maternal-facilitated child fruit and vegetable consumption model with standardized regression weights.
Maternal-Facilitated Child Sugar-Free Beverage Predictive Model Normality of the sugar-free beverage outcome variable residuals was confirmed through the K-S test which retained the null hypothesis that the standardized
a
0.00–9.00 1.00–12.00 2.00–12.00 0.00–64.00 1.00–12.00 0.00–12.00 0.00–11.00 0.00–12.00 0.00–12.00 2.00–64.00 3.00–12.00 0.00–12.00
0.00–12.00 0.00–12.00 0.00–12.00 0.00–64.00 0.00–12.00 0.00–12.00
Observed range
0.00–12.00 0.00–12.00 0.00–12.00 0.00–64.00 0.00–12.00 0.00–12.00
Possible range
2.45 9.43 9.83 48.13 10.12 9.75
2.80 8.43 9.29 50.81 9.58 8.39
M
2.02 3.04 2.63 15.43 2.25 2.56
1.73 2.47 2.43 14.15 2.33 3.01
SD
n/a 0.86 0.93 0.90 0.88 0.91
n/a 0.82 0.86 0.88 0.85 0.90
Construct reliability
n/a 68.0 81.1 69.4 70.7 76.8
n/a 59.8 67.9 65.9 66.5 74.1
AVE (%)
Reliability statistics
.71 .76 .71 .66 .74 .70
.64 .71 .67 .88 .71 .76
Pearson’s r
Abbreviations: AGFI, adjusted goodness-of-fit index; AVE, average variance extracted; FV, fruit and vegetable; GFI, goodness-of-fit index; MF, maternal-facilitated; NFI, normed fit index; SFB, sugar-free beverage. a Fit statistics for the maternal-facilitated child FV intake predictive model measurement model: 2 ¼ 195.157, df ¼ 94, p < .001; GFI ¼ 0.900, AGFI ¼ 0.854, NFI ¼ 0.920, CFI ¼ 0.957, and RMSEA ¼ 0.069. The model 2 test did not satisfy the a priori criteria of p-value greater than .05; applying Kline’s alternative (2010), model fit was satisfactory (195.157/94 ¼ 2.06). b Fit statistics for the maternal-facilitated child SFB intake predictive model measurement model: 2 ¼ 164.283, df ¼ 94, p < .001; GFI ¼ 0.916, AGFI ¼ 0.878, NFI ¼ 0.949, CFI ¼ 0.977, and RMSEA ¼ 0.058. The model 2 test did not satisfy the a priori criteria of p-value greater than .05; applying Kline’s alternative (2010), model fit was satisfactory (164.283/94 ¼ 1.74).
MF child FV intake model 1. Child FV intake 2. MF home environment 3. MF emotional coping 4. MF expectations 5. MF self-control 6. MF self-efficacy MF child SFB intake modelb 1. Child SFB intake 2. MF home environment 3. MF emotional coping 4. MF expectations 5. MF self-control 6. MF self-efficacy
Construct
Descriptive statistics
Table 1. Descriptive and Convergent Validity Statistics of the Social Cognitive Theory Constructs for the Sample of Mothers (n ¼ 224).
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Figure 1. Maternal-facilitated child fruit and vegetable intake model with standardized regression weights for the sample of mothers (n ¼ 224). Abbreviations: FV, fruits and vegetables; MF, maternal-facilitated.
Figure 2. Maternal-facilitated sugar-free beverage intake model with standardized regression weights for the sample of mothers (n ¼ 224). Abbreviations: MF, maternal-facilitated; SFB, sugar-free beverage.
residuals of the construct were normal (D(224) ¼ 0.934, p ¼ .348). Maternalfacilitated sugar-free beverage expectations (p ¼ .896), self-control (p ¼ .991), and self-efficacy (p ¼ .621) had nonsignificant direct effects on child sugar-free
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beverage intake. Significant direct paths between maternal-facilitated sugar-free beverage environment (p < .001) and emotional coping (p ¼ .006) on child sugarfree beverage intake were identified. Combined, the constructs accounted for 25% of the variance in child sugar-free beverage intake. Fit indices for the final model were satisfactory (2 ¼ 12.300, df ¼ 12, p ¼ .422; GFI ¼ 0.985, AGFI ¼ 0.964, NFI ¼ 0.988, CFI ¼ 1.000, RMSEA ¼ 0.011). Figure 2 provides an illustration of the maternal-facilitated child sugar-free beverage intake model with standardized regression weights.
Conclusions The purpose of this study was to examine the extent to which the maternalfacilitated, social cognitive theory constructs of environment, emotional coping, expectations, self-control, and self-efficacy could predict child fruit and vegetable consumption and sugar-free beverage intake using accepted standards for these two behaviors. Results suggested maternal-facilitated environment and self-efficacy predicted 24% of the variance in child fruit and vegetable consumption. Findings further identified maternal-facilitated environment and emotional coping predicted 25% of the variance in child sugar-free beverage intake. The mean amount of fruits and vegetables consumed by the sample was 2.80 cups, with 92.9% consuming less than the desired amount of five or more cups of fruits and vegetables as defined by this study. Maternal-facilitated environment and self-efficacy were significant predictors of child fruit and vegetable consumption. Analysis of the standardized regression weights found that when maternalfacilitated environment increased by one standard deviation, total cups of child fruits and vegetables consumed increased by 0.369 standard deviations. Further analysis found that when maternal-facilitated self-efficacy increased by one standard deviation, total cups of child fruits and vegetables consumed increased by 0.191 standard deviations. The maternal-facilitated fruit and vegetable constructs of emotional coping, expectations, and self-control were not significant predictors. To the best the authors’ knowledge, no interventions seeking to modify these constructs were implemented in the sample during the time of data collection. Absence of such interventions could help explain the inability of these constructs to predict child fruit and vegetable behavior. It is also possible that measurement error occurred and/or that mothers have limited influence on these constructs. The mean amount of child beverages consumed was 4.65 cups. The mean amount of sugar-sweetened beverages consumed by the sample was 1.23 cups, with 68.7% consuming less than the desired amount of zero sugar-sweetened beverages. The mean amount of sugar-free beverages consumed by the sample was 2.45 cups. Maternal-facilitated emotional coping and environment were significant predictors of child sugar-free beverages intake. Analysis of the
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standardized regression weights found that when maternal-facilitated environment increased by one standard deviation, total glasses of child sugar-free beverage intake increased by 0.395 standard deviations. Further analysis found that when maternal-facilitated emotional coping increased by one standard deviation, total glasses of child sugar-free beverage intake increased by 0.154 standard deviations. The maternal-facilitated sugar-free beverage constructs of expectations, self-control, and self-efficacy were not significant predictors. To the best the authors’ knowledge, no interventions seeking to modify these constructs were implemented in the sample during the time of data collection. Absence of such interventions could help explain the inability of these constructs to predict child sugar-free beverage behavior. It is also possible that measurement error occurred and/or that mothers have limited influence on these constructs. There are limitations that should be considered when interpreting the findings of this research. Concerning construct stability, child fruit and vegetable consumption, maternal-facilitated emotional coping for child fruit and vegetable consumption, and maternal-facilitated expectations for child sugar-free beverage intake fell below the a priori minimum of 0.70. One explanation is that dietary behaviors can naturally fluctuate from day-to-day [41]. To increase precision, future research should consider conducting more than two rounds of test–retest for behaviors with higher fluctuation rates. In addition to measurement limitations, there were also limitations related to the behaviors analyzed in this study. Specific types of fruits, vegetables, and beverages consumed were not requested and instead global data pertaining to these behaviors were collected. Measurement could be improved by requesting that participants complete more in-depth food and beverage inventories, such as standardized food frequency questionnaires. The current model only accounted for some factors known to influence dietary behaviors in the home environment. Other important variables related to fruit, vegetable, and beverage consumption, including family meals, portion sizes, parenting styles, additional parents and/or guardians, and informal child caregivers (e.g., grandparents), were not evaluated in the current study. As well, large-scale studies that account for environments external to the home, such as secondary child care (e.g., day care), organizational factors (e.g., workplace policies on assisting parents with childcare), and public policies (e.g., supplemental nutrition programs such as women, infants, and children) on nutrition behaviors would provide a more precise model of the influence of the home environment on child fruit, vegetable, and beverage intake.
Authors’ Note Portions of this paper were presented at the 2012 American Public Health Association Annual Meeting.
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Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by a University of Cincinnati Graduate School Summer Research Fellowship.
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15. Baranowski T, Cullen KW, Nicklas T, et al. Are current health behavioral change models helpful in guiding prevention of weight gain efforts?. Obesity 2003; 11: 23S–43S. 16. Bandura A. Social cognitive theory. In: Vasta R (ed.) Annals of child development. Greenwich, CT: JAI Press, 1989, pp.1–60. 17. Knowlden AP and Sharma M. Process evaluation of the Enabling Mothers to Prevent Pediatric Obesity Through Web-Based Learning and Reciprocal Determinism (EMPOWER) randomized control trial. Health Promot Pract 2014; 15: 685–694. 18. McAlister AL, Perry CL and Parcel GS. How individuals, environments, and health behaviours interact. In: Glanz K, Rimer BK and Viswanath K (eds) Health behavior and health education: theory, research, and practice. San Franciso, CA: Josey Bass, 2008, pp.169–188. 19. Bandura A. Health promotion by social cognitive means. Health Educ Behav 2004; 31: 143–164. 20. Bandura A. Guide for constructing self-efficacy scales. In: Pajares F and Urdan T (eds) Self-efficacy beliefs of adolescents. Charlotte, NC: Information Age Publishing, 2006, pp.307–337. 21. Sharma M, Wagner DI and Wilkerson J. Predicting childhood obesity prevention behaviors using social cognitive theory. Int Q Commun Health Educ 2005; 24: 191–203. 22. Byrd-Bredbenner C, Abbot JM and Cussler E. Relationship of social cognitive theory concepts to mothers’ dietary intake and BMI. Matern Child Nutr 2011; 7: 241–252. 23. Bandura A. Social cogntive theory: an agentic perspective. Ann Rev Psychol 2001; 52: 1–26. 24. Resnicow K, Davis-Hearn M, Smith M, et al. Social-cognitive predictors of fruit and vegetable intake in children. Health Psychol 1997; 16: 272. 25. Birch LL. Psychological influences on the childhood diet. J Nutr 1998; 128: 407S–410S. 26. Galloway AT, Fiorito LM, Francis LA, et al. ‘Finish your soup’: counterproductive effects of pressuring children to eat on intake and affect. Appetite 2006; 46: 318–323. 27. Spurrier NJ, Magarey AA, Golley R, et al. Relationships between the home environment and physical activity. Int J Behav Nutr Phys Activity 2008; 5: 31. 28. Cullen KW, Baranowski T, Owens E, et al. Availability, accessibility, and preferences for fruit, 100% fruit juice, and vegetables influence children’s dietary behavior. Health Educ Behav 2003; 30: 615–626. 29. Ayala GX, Elder JP, Campbell NR, et al. Longitudinal intervention effects on parenting of the Aventuras para Nin˜os study. Am J Prevent Med 2010; 38: 154–162. 30. Clark HR, Goyder E, Bissell P, et al. How do parents’ child-feeding behaviours influence child weight? Implications for childhood obesity policy. J Public Health 2007; 29: 132–141. 31. Harvey-Berino J and Rourke J. Obesity prevention in preschool native-american children: a pilot study using home visiting. Obes Res 2003; 11: 606–611. 32. Jain A, Sherman SN, Chamberlin D, et al. Why don’t low-income mothers worry about their preschoolers being overweight?. Pediatrics 2001; 107: 1138.
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33. Gardner DSL, Hosking J, Metcalf BS, et al. Contribution of early weight gain to childhood overweight and metabolic health: a longitudinal study. Pediatrics 2009; 123: e67–e73. 34. Flesch R. A new readability yardstick. J Appl Psychol 1948; 32: 221–233. 35. Woodmansey K. Readability of educational materials for endodontic patients. J Endodont 2010; 36: 1703–1706. 36. Freda MC. The readability of American Academy of Pediatrics patient education brochures. J Pediatr Health Care 2005; 19: 151–156. 37. Faul F, Erdfelder E, Buchner A, et al. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods 2009; 41: 1149–1160. 38. Bentler PM and Chou C-P. Practical issues in structural modeling. Sociol Methods Res 1987; 16: 78–117. 39. Hoe SL. Issues and procedures in adopting structural equation modeling technique. J Appl Quant Methods 2008; 3: 76–83. 40. Fornell C and Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Market Res 1981; 18: 39–50. 41. Yen M and Lo L-H. Examining test-retest reliability: an intra-class correlation approach. Nurs Res 2002; 51: 59–62.
Author Biographies Adam P. Knowlden, MBA, PhD, is a professor of health science at The University of Alabama. Dr. Knowlden specializes in the development of behavioral prediction models and the evaluation of theory-based interventions. Manoj Sharma holds a PhD in Preventive Medicine from The Ohio State University. He is currently a tenured Full Professor in Behavioral and Environmental Health at Jackson State University. His research interests are in theory-based health behavior research, community-based participatory research, childhood obesity, and integrative systems of medicine including mind-body interventions.
Social Cognitive Maternal-Mediated Nutritional Correlates of Childhood Obesity
International Quarterly of Community Health Education 2015, Vol. 35(2) 177–191 ! The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0272684X15569678 qch.sagepub.com
Adam P. Knowlden1 and Manoj Sharma2
Abstract The purpose of this investigation was to examine the extent to which the maternalfacilitated, social cognitive theory constructs of environment, emotional coping, expectations, self-control, and self-efficacy predicted child fruit and vegetable consumption and sugar-free beverage intake. Instrumentation comprised three stages of data collection and analysis. Stage 1 included item generation, face and content validity by a panel of six experts, and readability by Flesch Reading Ease and Flesch–Kincaid Grade Level tests. Stage 2 assessed stability of the theoretical constructs using the test–retest procedure with 30 participants. Structural equation modeling was used during Stage 3 to conduct confirmatory factor analysis and to establish predictive validity of the models. A total of 224 respondents participated in this study. Maternal-facilitated home environment and self-efficacy were significant predictors of child fruit and vegetable consumption while maternal-mediated home environment and emotional coping were significant predictors of child sugar-free beverage intake. Keywords childhood obesity, social cognitive theory, mother–child dyad, fruit and vegetable consumption, sugar-sweetened beverage intake
1
Department of Health Science, The University of Alabama, Tuscaloosa, AL, USA Health Promotion & Education Program & Public Health Sciences, The University of Cincinnati, OH, USA
2
Corresponding Author: Adam P. Knowlden, Department of Health Science, The University of Alabama, Russell Hall 457A, P.O. Box 870311, Tuscaloosa, AL 35487-0311, USA. Email: [email protected]
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Introduction In the United States, body mass index prevalence rates suggest 31.8% of children aged 2 to 19 are overweight, with 16.9% of this proportion being of obese status [1]. In children, obesity has been associated with numerous medical comorbidities including asthma, metabolic risk factors, and dental health [2]. Childhood obesity also carries psychological comorbidities including attention deficit hyperactivity disorder, internalizing and externalizing disorders, and sleep apnea [2]. Obesity tracks with age [3], which may make targeting young children particularly important for curtailing the current obesity epidemic [4]. Two behaviors that protect against childhood obesity include adequate consumption of fruits and vegetables and minimal intake of sugar-sweetened beverages [5]. Obesity is a consequence of excessive caloric consumption [6]. Fruits and vegetables contain fiber and enhance satiation, which can lead to an overall reduction in total calories consumed [7]. Additionally, fruits and vegetables are high in nutrients and can help protect against a variety of chronic diseases [8]. For prevention and treatment of obesity, the American Medical Association Obesity Expert Committee on the Assessment, Prevention, and Treatment of Child and Adolescent Overweight and Obesity recommend children to consume at least five cups of fruits and vegetables each day [5]. Soft drinks are a primary source of sugar-sweetened beverages in the United States and contribute to weight gain due to their poor satiation abilities and high caloric content [9]. In regard to sugar-sweetened beverages, the Expert Committee recommends limited consumption, with zero consumption being ideal [5]. To reduce sugarsweetened beverage intake, a recommended strategy is to replace sugar-sweetened beverages with sugar-free beverages [10].
Theoretical Framework In children, the introduction of fruits, vegetables, and sugar-free beverages by parental role models at a young age may increase preference for healthier foods later in life [11]. The home environment offers the most direct context for parental modeling of health behaviors [12]. Subsequently, home-based interventions that incorporate parents as mediators of child fruit, vegetable, and sugar-free beverage intake may reduce a child’s overall risk for obesity [13]. Social cognitive theory has been a staple in developing interventions for increasing fruit and vegetable consumption and decreasing sugar-sweetened beverage intake in children [14, 15]. Social cognitive theory operates on the premise of reciprocal determinism; a causal model that assumes behaviors are influenced by personal and environmental factors [16]. Social cognitive theory may be an optimal model for family- and home-based interventions as the theory can account for social and physical environmental factors that influence the health behaviors of young children [17].
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An advantage of social cognitive theory is its comprehensive nature. Combined, the constructs of social cognitive theory can account for a significant amount of the interaction that occurs between the personal factors and environments within which a behavior is performed [18]. A limitation of social cognitive theory is its large ensemble of constructs, which can make full reification of the framework difficult to apply for intervention purposes. Due to practical limitations, interventionists will typically select from the available social cognitive theory constructs based on those which are likely to have the strongest influence on the behavior they are targeting [14]. In the current study, maternal-facilitated home environment, emotional coping, expectations, self-control, and self-efficacy constructs were selected for testing. Selfefficacy entails the confidence to perform a specific behavior [19]. Bandura [20] has identified self-efficacy as the most salient determinant of behavior change. Sharma et al. [21] identified self-efficacy as a primary predictor for adequate consumption of fruits and vegetables among fifth-grade school children. Self-control, or self-regulation, involves setting goals, developing rewards, monitoring progress, and restructuring influential environments [22]. Self-control works in tandem with self-efficacy to promote behavior change and is important for actualizing self-efficacy. Expectations perform an integral role in motivation to modify a behavior [23]. Using a sample of third-grade students, Resnicow et al. [24] identified expectations as a predictor for fruit and vegetable consumption while Sharma et al. [21] found expectations were associated with increased sugar-free beverage intake. The ability to cope with behavior change is important for maximizing self-efficacy [22]. Young children may experience stress when mothers attempt to modify their diet [25, 26]. The emotional coping construct was operationalized to account for child distress from modifying fruit and vegetable consumption and sugar-free beverage intake [19]. The environment construct was selected as availability and accessibility to resources, as well as parental role modeling, play a critical role in child fruit and vegetable consumption and sugar-free beverage intake [27]. Cullen et al. [28] found child-reported availability of fruits and vegetables and parent-reported accessibility to these foods were significant predictors of child consumption. Given this backdrop, the purpose of this study was to examine the extent to which the selected maternal-facilitated, social cognitive theory constructs of environment, emotional coping, expectations, self-control, and self-efficacy could predict child fruit and vegetable consumption and sugar-free beverage intake.
Methods Participants and Instrumentation Participants for this study were recruited from childcare centers and health-care organizations between March and August 2012 in the Cincinnati Ohio and
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Columbus Ohio regions. Inclusion criteria for participation were mothers at least 18 years of age with at least one child between 4 and 6 years of age. These inclusion criteria were selected as mothers are posited to be primary mediators of behavior change in young children and is an impressionable age for these behaviors [4, 29–32]. Children between 4 and 6 years of age were selected as this age range has important implications for a child’s future health and is the most impressionable age for these behaviors [4, 33]. Three stages of data collection were used to develop the instrument. Stage 1 included assessment of face and content validity of the instrument using a panel of experts. Stage 2 evaluated the stability of the instrument through test–retest. The final stage modeled the data through structural equation modeling to determine the reliability and validity of the instrument. Prior to collecting data from participants, institutional review board approval was sought and obtained to carry out the investigation. Stage 1 procedures. Initial items were modified from a previously validated instrument examining social cognitive theory predictors of childhood obesity. [21]. The original instrument was designed to be completed by fifth-grade students; therefore, the items were modified to meet the needs of the current investigation. First, the items for each construct were adjusted so that the items would reflect maternal-facilitated expectations, self-control, and self-efficacy for child fruit and vegetable consumption and sugar-free beverage intake. Two new constructs, maternal-facilitated environment and emotional coping, were added to the instrument. Second, the behaviors of the children were assessed using proxyself report. That is, mothers self-reported their child’s fruit, vegetable, and beverage behaviors. After modifying the items, the instrument was delivered to a panel of six experts for the evaluation of readability as well as face and content validity. The panel comprised two population experts, two social cognitive theory experts, and two measurement experts. Two rounds of review occurred, resulting in the removal of one item from the environment subscale. Additional recommendations included rewording of several of the subscale items. Two rounds of review resulted in unanimous agreement of the instrument’s face and content validity. The final instrument contained 52 items. Flesch Reading Ease Test (73.1) and the Flesch–Kincaid Grade Level Test (5.7) scores suggested the instrument was fairly easy in terms of reading ease [34] and near a sixth-grade reading level by U.S. educational standards [35]. Based on the panel of experts’ subjective opinion of the instrument’s readability as well as the objective readability scores, the instrument was considered acceptable for the population sampled in this study [36]. The first group of items asked about child fruit, vegetable, sugar-free beverage, and sugar-sweetened beverage behaviors. The first two items asked participants to proxy-recall the past 24 hours and write the exact number of cups of
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fruits and vegetables their child consumed. Pictures of one-half cup and one-cup servings of fruits and vegetables were provided to improve accuracy of proxyrecall of child fruit and vegetable consumption. The next two items asked participants to proxy-recall the past 24 hours and write the exact number of 8-ounce glasses of sugar-free beverages and sugar-sweetened beverages their child consumed. For the purposes of this study, sugar-free beverages were operationalized as beverages that did not contain added sugar or caloric sweeteners. Conversely, sugar-sweetened beverages were operationalized as beverages that did not include added sugar or other caloric sweeteners. A life-size picture of an 8-ounce glass was provided to improve accuracy of proxy-recall of child beverage intake. Examples of commonly consumed sugar-sweetened and sugar-free beverages were also listed. The second group of items asked about the maternal-facilitated home environment for child fruit and vegetable consumption and sugar-free beverage intake. The first three items evaluated the maternal-facilitated home environment for child fruit and vegetable consumption. The next three items evaluated the maternal-facilitated home environment for child sugar-free beverages intake. The stem statement for both subscales was “how often do you.” Both subscales used ratings of never (0), hardly ever (1), sometimes (2), almost always (3), and always (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable environment subscale included, “have enough fruits and vegetables at home for your child to be able to eat five cups every day,” and “eat at least five cups of fruits and vegetables with your child at home every day?” Sample items from the sugar-free beverages environment subscale included “have sugar-free drinks at home for your child to drink,” and “drink sugar-free drinks with your child at home?” The third group of items asked about the maternal-facilitated emotional coping for child fruit and vegetable consumption and sugar-free beverage intake. The first three items evaluated maternal-facilitated emotional coping for child fruit and vegetable consumption. The next three items evaluated maternal-facilitated emotional coping for child sugar-free beverage intake. The stem statement for both subscales asked, “how sure are you that you can help your child.” Both subscales used ratings of not at all sure (0), slightly sure (1), moderately sure (2), very sure (3), and completely sure (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable emotional coping subscale included, “adjust to eating at least five cups of fruits and vegetables every day,” and “manage any negative emotions from your child when you encourage him or her to eat fruits and vegetables?” Sample items from the sugar-free beverage emotional coping subscale included, “drink sugar-free drinks when sugarsweetened drinks are available,” and “manage any negative emotions from your child when you replace sugar-sweetened drinks with sugar-free drinks?” The fourth group of items was about maternal-facilitated outcome expectations of fruit and vegetable consumption and sugar-free beverage intake. The
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first four items evaluated maternal-facilitated outcome expectations for child fruit and vegetable consumption. The stem statement for the subscale asked, “if your child eats five cups of fruits and vegetables every day they will.” Items for maternal-facilitated outcome expectations for child fruit and vegetable consumption subscale included, “not get sick as often,” “have more energy,” “have a better weight,” and “feel better.” The next four items evaluated maternalfacilitated outcome expectations for child sugar-free beverage intake. The stem statement for the subscale asked, “if your child drinks sugar-free drinks instead of sugar-sweetened drinks they will.” Items for the maternal-facilitated outcome expectations for sugar-free beverages subscale included “be more relaxed,” “have more energy,” “have a better weight,” and “feel better.” Both subscales used ratings of never (0), hardly ever (1), sometimes (2), almost always (3), and always (4) for possible score ranges of 0 to 16. The fifth group of items was about maternal-facilitated outcome expectancies of fruit and vegetable consumption and sugar-free beverage intake. The first four items evaluated maternal-facilitated outcome expectancies for child fruit and vegetable consumption. The next four items evaluated maternal-facilitated outcome expectancies for child sugar-free beverage intake. The stem statement for both subscales asked, “overall, how important is it to you that your child will.” Both subscales used ratings of not at all important (0), slightly important (1), moderately important (2), very important (3), and extremely important (4). Each subscale had a range of 0 to 16. Items corresponded to outcome expectations and followed the same construction as the outcome expectations subscales. Expectations for each behavior were calculated by multiplying the four outcome expectations with the four corresponding outcome expectancies and then summating each of the pairs for a possible score range of 0 to 64. The sixth group of items asked about maternal-facilitated self-control for child fruit and vegetable consumption and sugar-free beverage intake. The first three items evaluated maternal-facilitated self-control for child fruit and vegetable consumption. The next three items evaluated maternal-facilitated self-control for child sugar-free beverage intake. The stem statement for both subscales asked, “how sure are you that you can.” Both subscales used ratings of not at all sure (0), slightly sure (1), moderately sure (2), very sure (3), and completely sure (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable self-control subscale included, “set goals to have your child eat five cups of fruits and vegetables every day,” and “plan to have your child eat five cups of fruits and vegetables every day?” Sample items from the sugar-free beverage self-control subscale included, “plan to replace your child’s sugar-sweetened drinks with sugar-free drinks,” and “set goals to replace your child’s sugar-sweetened drinks with sugar-free drinks?” The seventh group of items asked about the maternal-facilitated self-efficacy for child fruit and vegetable consumption and sugar-free beverage intake. The
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first three items evaluated maternal-facilitated self-control for child fruit and vegetable consumption. The next three items evaluated maternal-facilitated self-control for child sugar-free beverage intake. The stem statement for both subscales asked, “how confident are you that you can get your child to.” Both subscales used ratings of not at all confident (0), slightly confident (1), moderately confident (2), very confident (3), and completely confident (4) for possible score ranges of 0 to 12. Sample items from the fruit and vegetable self-efficacy subscale included, “eat five cups of fruits and vegetables every day,” and “eat five cups of fruits and vegetables every day, even if they do not like them?” Sample items from the sugar-free beverage self-efficacy subscale included, “drink more sugarfree drinks,” and “drink sugar-free drinks every day instead of sugar-sweetened drinks?” The final eight items on the instrument were about demographics and included information on mother/child age, mother/child gender, and mother/ child race. Stage 2 procedures. For test–retest recruitment, 30 respondents who participated in Stage 3 were requested to complete the instrument a second time, 2 weeks following the first administration. Correlations between test–retest constructs were calculated using Pearson’s r, with accepted coefficient values set a priori at .70. The sample size for the two-tailed, matched pairs test–retest procedure was determined using G*Power statistical power analysis software inputting an effect size of 0.55, and alpha of .05, and a power of 0.80 [37]. Data for stage 2 were analyzed using IBM SPSS Statistics Faculty Pack version 22.0. Stage 3 procedures. Stage 3 evaluated construct and predictive validity of the instrument through structural equation modeling. Child fruit and vegetable consumption and child sugar-free beverage intake were modeled separately. Applying a participant-to-parameter ratio of 5:1 with an estimated 40 parameters, a sample size of 200 was required to build the models [38]. Construct validity was determined through confirmatory factor analysis using model Chi-square (2) test, goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), normed fit index (NFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA) values. Goodness-of-fit indices were set a priori with 2 value of p > .05, GFI, AGFI, NFI, and CFI > 0.90, and RMSEA < 0.80 [39]. Convergent validity was assessed through factor loadings, construct reliability, and average variance extracted (AVE) values. Factor loading values less than 0.50 were considered for removal. AVE was set a priori at no less than 0.50, and construct reliability was set at no less than 0.70 [39]. Data for Stage 3 were analyzed using IBM AMOS version 21.0.Construct reliability and AVE were calculated manually by computing formulas developed by Fornell and Larcker [40] with Microsoft Excel 2010.
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Results Descriptive and Convergent Validity Statistics Participants were predominantly Caucasian (72%), married (70%), unemployed/homemakers (49%), with a mean age of 33.2 (SD ¼ 6.8). Results found the majority of the observed social cognitive theory construct scores were in the upper-middle portion of the possible range. Descriptive statistics, including ranges, means, and standard deviations, for child fruit and vegetable behavior, maternal-facilitated fruit and vegetable social cognitive theory constructs, child beverage behaviors, and maternal-facilitated sugar-free beverage social cognitive theory constructs are summarized in Table 1. In terms of convergent validity, results found factor loadings, construct reliability, and AVE values exceeded the a priori standards for all social cognitive theory constructs. For test–retest reliability, two constructs from the fruit and vegetable model, child fruit and vegetable consumption (r ¼ .64) and maternal-facilitated emotional coping (r ¼ .67), fell below the a priori minimum. An additional construct from the sugar-free beverage model, expectations (r ¼ .66), fell below the a priori minimum. Convergent validity statistics, including construct reliability, AVE, and test– retest reliability, are summarized in Table 1. Measurement model fit statistics are provided in the notes section of Table 1.
Maternal-Facilitated Child Fruit and Vegetable Predictive Model Normality of the fruit and vegetable outcome variable residuals was confirmed through the Kolmogorov–Smirnov (K-S) test which retained the null hypothesis that the standardized residuals were normal (D(224) ¼ 0.832, p ¼ .493). Maternal-facilitated fruit and vegetable emotional coping (p ¼ .238), expectations (p ¼ .370), and self-control (p ¼ .294) had nonsignificant direct effects on child fruit and vegetable consumption. Significant direct paths between maternal-facilitated fruit and vegetable environment (p < .001) and self-efficacy (p ¼ .011) on child fruit and vegetable consumption were identified. Combined, the constructs accounted for 24% of the variance in child fruit and vegetable consumption. Fit indices for the final model were satisfactory (2 ¼ 20.423, df ¼ 13, p ¼ .059; GFI ¼ 0.975, AGFI ¼ 0.942, NFI ¼ 0.973, CFI ¼ 0.988, RMSEA ¼ 0.056). Figure 1 provides an illustration of the maternal-facilitated child fruit and vegetable consumption model with standardized regression weights.
Maternal-Facilitated Child Sugar-Free Beverage Predictive Model Normality of the sugar-free beverage outcome variable residuals was confirmed through the K-S test which retained the null hypothesis that the standardized
a
0.00–9.00 1.00–12.00 2.00–12.00 0.00–64.00 1.00–12.00 0.00–12.00 0.00–11.00 0.00–12.00 0.00–12.00 2.00–64.00 3.00–12.00 0.00–12.00
0.00–12.00 0.00–12.00 0.00–12.00 0.00–64.00 0.00–12.00 0.00–12.00
Observed range
0.00–12.00 0.00–12.00 0.00–12.00 0.00–64.00 0.00–12.00 0.00–12.00
Possible range
2.45 9.43 9.83 48.13 10.12 9.75
2.80 8.43 9.29 50.81 9.58 8.39
M
2.02 3.04 2.63 15.43 2.25 2.56
1.73 2.47 2.43 14.15 2.33 3.01
SD
n/a 0.86 0.93 0.90 0.88 0.91
n/a 0.82 0.86 0.88 0.85 0.90
Construct reliability
n/a 68.0 81.1 69.4 70.7 76.8
n/a 59.8 67.9 65.9 66.5 74.1
AVE (%)
Reliability statistics
.71 .76 .71 .66 .74 .70
.64 .71 .67 .88 .71 .76
Pearson’s r
Abbreviations: AGFI, adjusted goodness-of-fit index; AVE, average variance extracted; FV, fruit and vegetable; GFI, goodness-of-fit index; MF, maternal-facilitated; NFI, normed fit index; SFB, sugar-free beverage. a Fit statistics for the maternal-facilitated child FV intake predictive model measurement model: 2 ¼ 195.157, df ¼ 94, p < .001; GFI ¼ 0.900, AGFI ¼ 0.854, NFI ¼ 0.920, CFI ¼ 0.957, and RMSEA ¼ 0.069. The model 2 test did not satisfy the a priori criteria of p-value greater than .05; applying Kline’s alternative (2010), model fit was satisfactory (195.157/94 ¼ 2.06). b Fit statistics for the maternal-facilitated child SFB intake predictive model measurement model: 2 ¼ 164.283, df ¼ 94, p < .001; GFI ¼ 0.916, AGFI ¼ 0.878, NFI ¼ 0.949, CFI ¼ 0.977, and RMSEA ¼ 0.058. The model 2 test did not satisfy the a priori criteria of p-value greater than .05; applying Kline’s alternative (2010), model fit was satisfactory (164.283/94 ¼ 1.74).
MF child FV intake model 1. Child FV intake 2. MF home environment 3. MF emotional coping 4. MF expectations 5. MF self-control 6. MF self-efficacy MF child SFB intake modelb 1. Child SFB intake 2. MF home environment 3. MF emotional coping 4. MF expectations 5. MF self-control 6. MF self-efficacy
Construct
Descriptive statistics
Table 1. Descriptive and Convergent Validity Statistics of the Social Cognitive Theory Constructs for the Sample of Mothers (n ¼ 224).
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Figure 1. Maternal-facilitated child fruit and vegetable intake model with standardized regression weights for the sample of mothers (n ¼ 224). Abbreviations: FV, fruits and vegetables; MF, maternal-facilitated.
Figure 2. Maternal-facilitated sugar-free beverage intake model with standardized regression weights for the sample of mothers (n ¼ 224). Abbreviations: MF, maternal-facilitated; SFB, sugar-free beverage.
residuals of the construct were normal (D(224) ¼ 0.934, p ¼ .348). Maternalfacilitated sugar-free beverage expectations (p ¼ .896), self-control (p ¼ .991), and self-efficacy (p ¼ .621) had nonsignificant direct effects on child sugar-free
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beverage intake. Significant direct paths between maternal-facilitated sugar-free beverage environment (p < .001) and emotional coping (p ¼ .006) on child sugarfree beverage intake were identified. Combined, the constructs accounted for 25% of the variance in child sugar-free beverage intake. Fit indices for the final model were satisfactory (2 ¼ 12.300, df ¼ 12, p ¼ .422; GFI ¼ 0.985, AGFI ¼ 0.964, NFI ¼ 0.988, CFI ¼ 1.000, RMSEA ¼ 0.011). Figure 2 provides an illustration of the maternal-facilitated child sugar-free beverage intake model with standardized regression weights.
Conclusions The purpose of this study was to examine the extent to which the maternalfacilitated, social cognitive theory constructs of environment, emotional coping, expectations, self-control, and self-efficacy could predict child fruit and vegetable consumption and sugar-free beverage intake using accepted standards for these two behaviors. Results suggested maternal-facilitated environment and self-efficacy predicted 24% of the variance in child fruit and vegetable consumption. Findings further identified maternal-facilitated environment and emotional coping predicted 25% of the variance in child sugar-free beverage intake. The mean amount of fruits and vegetables consumed by the sample was 2.80 cups, with 92.9% consuming less than the desired amount of five or more cups of fruits and vegetables as defined by this study. Maternal-facilitated environment and self-efficacy were significant predictors of child fruit and vegetable consumption. Analysis of the standardized regression weights found that when maternalfacilitated environment increased by one standard deviation, total cups of child fruits and vegetables consumed increased by 0.369 standard deviations. Further analysis found that when maternal-facilitated self-efficacy increased by one standard deviation, total cups of child fruits and vegetables consumed increased by 0.191 standard deviations. The maternal-facilitated fruit and vegetable constructs of emotional coping, expectations, and self-control were not significant predictors. To the best the authors’ knowledge, no interventions seeking to modify these constructs were implemented in the sample during the time of data collection. Absence of such interventions could help explain the inability of these constructs to predict child fruit and vegetable behavior. It is also possible that measurement error occurred and/or that mothers have limited influence on these constructs. The mean amount of child beverages consumed was 4.65 cups. The mean amount of sugar-sweetened beverages consumed by the sample was 1.23 cups, with 68.7% consuming less than the desired amount of zero sugar-sweetened beverages. The mean amount of sugar-free beverages consumed by the sample was 2.45 cups. Maternal-facilitated emotional coping and environment were significant predictors of child sugar-free beverages intake. Analysis of the
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standardized regression weights found that when maternal-facilitated environment increased by one standard deviation, total glasses of child sugar-free beverage intake increased by 0.395 standard deviations. Further analysis found that when maternal-facilitated emotional coping increased by one standard deviation, total glasses of child sugar-free beverage intake increased by 0.154 standard deviations. The maternal-facilitated sugar-free beverage constructs of expectations, self-control, and self-efficacy were not significant predictors. To the best the authors’ knowledge, no interventions seeking to modify these constructs were implemented in the sample during the time of data collection. Absence of such interventions could help explain the inability of these constructs to predict child sugar-free beverage behavior. It is also possible that measurement error occurred and/or that mothers have limited influence on these constructs. There are limitations that should be considered when interpreting the findings of this research. Concerning construct stability, child fruit and vegetable consumption, maternal-facilitated emotional coping for child fruit and vegetable consumption, and maternal-facilitated expectations for child sugar-free beverage intake fell below the a priori minimum of 0.70. One explanation is that dietary behaviors can naturally fluctuate from day-to-day [41]. To increase precision, future research should consider conducting more than two rounds of test–retest for behaviors with higher fluctuation rates. In addition to measurement limitations, there were also limitations related to the behaviors analyzed in this study. Specific types of fruits, vegetables, and beverages consumed were not requested and instead global data pertaining to these behaviors were collected. Measurement could be improved by requesting that participants complete more in-depth food and beverage inventories, such as standardized food frequency questionnaires. The current model only accounted for some factors known to influence dietary behaviors in the home environment. Other important variables related to fruit, vegetable, and beverage consumption, including family meals, portion sizes, parenting styles, additional parents and/or guardians, and informal child caregivers (e.g., grandparents), were not evaluated in the current study. As well, large-scale studies that account for environments external to the home, such as secondary child care (e.g., day care), organizational factors (e.g., workplace policies on assisting parents with childcare), and public policies (e.g., supplemental nutrition programs such as women, infants, and children) on nutrition behaviors would provide a more precise model of the influence of the home environment on child fruit, vegetable, and beverage intake.
Authors’ Note Portions of this paper were presented at the 2012 American Public Health Association Annual Meeting.
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Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by a University of Cincinnati Graduate School Summer Research Fellowship.
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Author Biographies Adam P. Knowlden, MBA, PhD, is a professor of health science at The University of Alabama. Dr. Knowlden specializes in the development of behavioral prediction models and the evaluation of theory-based interventions. Manoj Sharma holds a PhD in Preventive Medicine from The Ohio State University. He is currently a tenured Full Professor in Behavioral and Environmental Health at Jackson State University. His research interests are in theory-based health behavior research, community-based participatory research, childhood obesity, and integrative systems of medicine including mind-body interventions.
