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. Author manuscript; available in PMC: 2020 Apr 1.
Published in final edited form as: Eat Behav. 2019 Mar 1;33:34–39. doi: 10.1016/j.eatbeh.2019.02.005

Self-efficacy and cooking confidence are associated with fruit and vegetable intake in a cross-sectional study with rural women

Brian K Lo a, Christine Loui a, Sara C Folta b, Angela Flickinger c, Leah M Connor a, Evelyn Liu a, Sarah Megiel a, Rebecca A Seguin a
PMCID: PMC6655530  NIHMSID: NIHMS1524042  PMID: 30878765

Abstract

Background

In comparison to their urban and suburban counterparts, midlife and older rural women are less likely to consume adequate fruit and vegetables (F&V). The present study aimed to examine the relationships between psychological, social, and environmental factors and F&V intake among midlife and older rural women in the United States.

Methods

This cross-sectional study utilized data from 513 midlife and older rural women (mean age = 67.0, mean BMI = 26.8) living in 22 states. Linear regression models were used to examine the associations between women’s daily F&V intake and cooking confidence, healthy eating self-efficacy, perceived stress, healthy eating social support, and perceived food environment.

Results

Cooking confidence (p < 0.001) and healthy eating self-efficacy (p < 0.001) were positively associated with F&V intake. Perceived stress, healthy eating social support, and perceived food environment were not associated with F&V intake (p > 0.05). When all the independent variables were analyzed simultaneously, only healthy eating self-efficacy remained positively associated with F&V intake (p < 0.001).

Conclusions

Findings from our study provide important information on the influences of rural women’s healthy eating self-efficacy and cooking confidence on their F&V intake. Our results may be useful to inform and evaluate targeted strategies to improve the dietary health of rural women.

Keywords: Rural health, nutrition, psychosocial factors, older adults

1. INTRODUCTION

Despite ongoing efforts to increase fruit and vegetable (F&V) intake in the United States, national F&V intake has declined steadily over the past decade, most precipitously among midlife (45–65) and older (65+) adults (Produce for Better Health Foundation, 2015). In comparison to their urban and suburban counterparts, rural residents are even less likely to consume adequate F&V. Among sixty million rural residents in the country (U.S. Census Bureau, 2010), only 25% consume five or more daily servings of F&V compared to 40% of the general population (one serving = one whole fruit, ½ cup of cut-up fruit, ¾ cup fruit juices, one cup raw leafy, or ½ cup of other vegetables) (Lutfiyya, Chang, & Lipsky, 2012).

Although limited access to affordable healthy foods in rural areas may partially hinder rural residents’ adequate F&V intakes (Bailey, 2010; Dean & Sharkey, 2011; Liese, Weis, Pluto, Smith, & Lawson, 2007), a small but growing body of literature suggests that rural midlife and older women’s poorer psychosocial well-being may further prevent them from eating enough F&V for their physical well-being in comparison to their non-rural counterparts (Smith & Ansa, 2016). For instance, rural women are reported to have high caregiving expectations, few employment opportunities, and restricted social contact with others (U.S. Department of Health and Human Services, 2013). In terms of healthy eating, they are also recorded to have low levels of self-efficacy, self-discipline, motivation, and fewer coping resources due to high levels of social stress (Guillaumie, Godin, & Vezina-Im, 2010). Furthermore, some qualitative studies have also discovered that familiarity with community food sources and support from and accountability to family and friends are also critical facilitators of healthy eating behaviors among older adults living in small, isolated rural communities (Dean, Sharkey, & Johnson, 2011; Quandt, McDonald, Arcury, Bell, & Vitolins, 2000; Souter & Keller, 2002).

To date, despite disproportionately low levels of F&V intake among rural populations and increased attention to mitigating rural-urban health disparities, rural women still remain under-represented in health promotion research (UyBico, Pavel, & Gross, 2007). Health promotion research has focused largely on urban and suburban populations, with questionable transferability to rural populations. Since rural dietary behaviors are different than urban dietary behaviors, and limited funding remains a major challenge in implementing rural interventions, it is important to gain a better understanding of the modifiable influences of healthy eating behaviors among rural women so that more relevant and targeted health promotion strategies can be developed.

An ecological framework, developed by Story, Kaphingst, Robinson-O’Brien, & Glanz (2008), identifies three levels of influence on people’s dietary behaviors: individual, social, and physical environmental influences. At the individual level, factors include motivations, self-efficacy, and behavioral capabilities. At the social level, influencers include social support from family, friends, peers, and others in the community. At the physical environment level, factors include access to and availability of foods. Although these factors are proposed to influence dietary behaviors, little is known about their magnitude and which factors are more influential among rural midlife and older women with respect to F&V intake. Therefore, the present study aimed to explore the relationships between individual, social, and environmental factors and F&V intake of midlife and older rural women. We hypothesized that higher healthy eating self-efficacy, cooking confidence, social support, and better food environment perception would be associated with higher amounts of F&V intake.

To our knowledge, our study is the first to examine psychological, social, and environmental factors together, in relation to F&V intake among rural midlife and older women. Since the population of midlife and older adults living in rural areas is projected to increase (Centers for Disease Control and Prevention, 2003) and women are often gatekeepers of their families’ diet (Crawford, Ball, Mishra, Salmon, & Timperio, 2007; Hamrick & Shelley, 2005), the findings of the present study will be useful for informing the development of relevant strategies for improving the overall health and well-being of rural women and their families.

2. MATERIALS AND METHODS

2.1. Procedure

The present study included 513 rural women from 22 states across the United States who participated in the StrongWomen Follow-Up Study (SWFUS) in 2013. One of the primary goals of SWFUS was to longitudinally examine individual (e.g. self-efficacy and health status), social (e.g. social support from family and friends), and environmental perception factors (e.g. perceived access to healthy foods and physical activity facilities) related to long-term maintenance of healthy eating and physical activity behaviors among midlife and older rural women who participated in the StrongWomen Program (SWP) (Seguin et al., 2008), a community-based health promotion program primarily focused on physical activity but that also includes healthy eating guidelines and discussion. A contact database that contains information of SWP participants was utilized for survey distribution. In August 2013, an online survey link was sent to eligible participants (n=187) through Qualtrics. Where email addresses were not available, paper surveys were mailed to participants (n=570). Five hundred and eighteen participants completed the study (n=518; response rate 68.4%). Participants were excluded from these analyses if they resided outside of the United States (n=5), yielding a sample total of 513 respondents. The study was approved by the Institutional Review Board at Cornell University. Written informed consent was obtained from each participant.

The SWFUS survey contained a set of instruments to measure participants’ healthy eating self-efficacy, cooking confidence, perceived stress, healthy eating social support, and perceived food environment. Before administration, the SWFUS survey was reviewed and edited by experts in the fields of public health, nutrition, and the social sciences as well as midlife and older women. Prior to data analyses in the present study, Cronbach’s α was calculated for each independent variable, in which a value ≥0.7 indicates an acceptable internal reliability of constructs (George & Mallery, 2003).

2.2. Independent Variables

Cooking confidence.

A ten-item survey instrument developed by Condrasky et al. (2011) was used to assess the extent to which participants felt confident about performing various cooking techniques, including F&V preparation. A scale score was calculated by taking the mean of the ten survey items. High scores indicate a high confidence in cooking. Cronbach’s α for the constructs in the present study was high (0.91).

Healthy eating efficacy.

Healthy eating self-efficacy was measured by a 16-item survey instrument developed by Sallis, Pinski, Grossman, Patterson, and Nader (1988). High mean scale scores indicate a high self-efficacy for consuming a healthy diet. Cronbach’s α for the constructs in the present study was high (0.90).

Perceived stress.

Perceived stress was measured using the ten-item Perceived Stress Scale (PSS) (Cohen, Kamarck, & Mermelstein, 1983; Cohen & Williamson, 1988), with a high sum score indicating a high level of perceived stress. Cronbach’s α for the PSS in the present study was high (0.87).

Healthy eating social support.

The Social Support and Eating Habits Survey was used to assess participants’ social support for healthy eating with four subscales: family encouragement, family discouragement, friend encouragement, and friend discouragement (Sallis, Grossman, Pinski, Patterson, & Nader, 1987). A score for each subscale was calculated by taking the mean of the items in each subscale, with a high score indicating greater family and friend encouragement or discouragement. Cronbach’s αs were high for the four subscales (between 0.70 and 0.85).

Perceived food environment.

Perceived food environment was ascertained using three survey items developed by Echeverria et al. (2004). Participants were asked to indicate their agreement with three statements on the availability, variety, and quality of F&V in their community. High mean scale scores indicate better perceived access to F&V. Cronbach’s α for the constructs was high (0.92).

2.3. Dependent Variable

F&V intake was self-reported by participants using the National Cancer Institute Fruit and Vegetable Screener (Subar et al., 2001; Thompson et al., 2000). Based on the 2005 MyPyramid cup equivalents, average number of cups of F&V eaten per day were then calculated for the present analysis (one cup equivalent = one whole fruit, one cup of cut-up fruit, one cup fruit juices, two cups raw leafy, or one cup of other vegetables) (National Cancer Institute, 2016).

2.4. Participant Characteristics

Participants reported their age, weight, height, race/ethnicity, marital status, annual household income, education, and employment status.

2.5. Statistical Analysis

Analyses were performed using SPSS version 25 (SPSS Inc., Chicago, USA).

Because almost all study participants self-identified as white (98.4%), race was regrouped into categories of white and non-white. Marital status was dichotomized into “partnered or married” and “other.” Similarly, employment status was dichotomized into “yes” and “no.”

Linear regression models were used to examine the associations between the dependent variable (total daily F&V cups consumed) and the independent variables (cooking confidence, self-efficacy, perceived stress, social support, and perceived food environment). Each independent variable was first analyzed in a separate model to examine each independent variable’s relationship with participants’ F&V intake; the final model was comprised of all the independent variables with the aim of comparing each independent variable’s contribution to participants’ F&V intake. Collinearity diagnostics indicated no violations among the independent variables in the present study (Field, 2009): correlations between the independent variables ranged between - 0.36 and 0.49, and variance inflation factors (VIFs) for all the independent variables in Model 6 ranged between 1.04 and 1.51 with the observed data. All analyses controlled for participants’ age, body mass index (BMI), marital status, and education. Interaction terms were examined; none were significant or included in the analyses presented here. The type I error rate was set at 0.05, and model assumptions were met.

Examination of missing data indicated that about 12% of the social support data and 14% of the annual household income data were missing due to non-response. The Little’s Missing Completely At Random (MCAR) test indicated that our data were not missing completely at random (p < 0.001). Chi-square tests found that participants who were not partnered or married, had a lower income, or had a lower education level were more likely to skip questions related to perceived social support and perceived food access (p < 0.05). Multiple imputation via the regression method was used to create ten imputed datasets with missing data replaced with imputed values (Sterne, 2009). Pooled estimates from the ten imputed datasets are presented for the hierarchical regression analysis.

3. RESULTS

Table 1 shows the description of demographics, psychosocial and environmental measures, and F&V intake of the study sample. Participants had a mean age of 67.0 years (SD 9.9), and the majority were 65 years or older (69.4%). The mean BMI was 26.8 (SD 5.5). The majority of the participants were white (98.4%). More than half of the participants were partnered or married (69.2%), were not employed (67.7%), were a college graduate (58.5%), and had a moderate to high income (60.2% with an annual household income of or above US$50,000).

Table 1.

Demographics, psychosocial and environmental measures, and F&V intake

Mean ± SD or N (%)
Age (years) (n=506) 67.0 ± 9.9
BMI (kg/m2) (n=499) 26.8 ± 5.5
Race/ethnicity (n=506)
White 498 (98.4)
Non-White 8 (1.6)
Marital Status (n=507)
Partnered or married 351 (69.2)
Other 156 (30.8)
Employment (n=502)
Yes 162 (32.3)
No 340 (67.7)
Education (n=506)
Some college or below 210 (41.5)
College or higher 296 (58.5)
Annual Household Income (n=439)
≤ $24,999 53 (12.1)
$25,000 to $49,999 122 (27.8)
$50,000 to $74,999 129 (29.4)
≥ $75,000 135 (30.8)
Total Daily F&V Intake (cups per day, n=504) 3.4 ± 2.2
Cooking Confidence (on a scale between 1 and 5, n=506) 4.3 ± 0.7
Healthy Eating Self-efficacy (on a scale between 1 and 5, n=500) 3.7 ± 0.7
Perceived Stress (on a scale between 0 and 40, n=497) 10.4 ± 5.9
Healthy Eating Social Support (on a scale between 1 and 5)
 Family Encouragement for Healthy Eating (n=458) 1.7 ± 0.9
 Family Discouragement for Healthy Eating (n=458) 1.7 ± 0.7
 Friends Encouragement for Healthy Eating (n=454) 1.5 ± 0.7
 Friends Discouragement for Healthy Eating (n=454) 1.4 ± 0.5
Perceived Food Environment (on a scale between 1 and 5, n=505) 4.4 ± 0.8
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The mean daily intake of F&V was 3.4 cups (SD 2.2). Participants were confident in cooking (mean score out of 5 = 4.3, SD 0.7). The mean score for healthy eating self-efficacy was 3.7 out of 5 (SD 0.7) and the mean score for perceived stress was 10.4 out of 40 (SD 5.9). While participants perceived low social support for healthy eating from family and friends (mean family encouragement score: 1.7 out of 5, SD 0.9; mean friends encouragement score: 1.5 out of 5, SD 0.7), they also indicated that friends and family were not discouraging them from eating healthfully (mean family discouragement score: 1.7 out of 5, SD 0.7; mean friends discouragement score: 1.4 out of 5, SD 0.5). On average, participants perceived a good food environment in their community (4.4 out of 5, SD 0.8).

Table 2 summarizes the pooled estimates of the hierarchical regression analysis for predicting daily F&V intake from the ten imputed datasets.

Table 2.

Summary of Hierarchical Regression Analysis for predicting daily F&V intake (n=513)a

Independent variable Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
β (SE) P value β (SE) P value β (SE) P value β (SE) p value β (SE) p value β (SE) p value
Psychological Factors
Cooking confidence 0.59 (0.14) <0.001 ** 0.26 (0.15) 0.08
Healthy eating self-efficacy 1.00 (0.13) <0.001 ** 0.96 (0.15) <0.001 **
Perceived stress −0.02 (0.02) 0.36 0.03 (0.02) 0.14
Social Factors
Family encouragement 0.12 (0.15) 0.43 0.18 (0.13) 0.18
Family discouragement −0.15 (0.16) 0.36 −0.05 (0.15) 0.73
Friends encouragement −0.05 (0.20) 0.79 −0.12 (0.18) 0.51
Friends discouragement 0.36 (0.23) 0.12 0.34 (0.22) 0.12
Environmental Factors
Perceived food environment 0.14 (0.13) 0.28 0.01 (0.12) 0.96
Demographics
Age 0.01 (0.01) 0.35 0.00 (0.01) 0.69 0.01 (0.01) 0.50 0.01 (0.01) 0.44 0.01 (0.01) 0.54 0.01 (0.01) 0.51
BMI −0.02 (0.02) 0.20 −0.01 (0.02) 0.71 −0.03 (0.02) 0.15 −0.03 (0.02) 0.14 −0.02 (0.02) 0.17 −0.01 (0.02) 0.66
Education
Some college or below −0.65 (0.19) 0.001* −0.66 (0.19) <0.001** −0.69 (0.20) 0.001* −0.69 (0.20) 0.001* −0.65 (0.20) 0.001* −0.65 (0.19) 0.001*
College or higher Ref. . Ref. . Ref. . Ref. . Ref. . Ref. .
Marital status
Partnered or married −0.19 (0.25) 0.44 −0.25 (0.24) 0.30 −0.05 (0.25) 0.84 0.02 (0.26) 0.95 −0.05 (0.25) 0.86 −0.28 (0.26) 0.28
Others Ref. . Ref. . Ref. . Ref. . Ref. . Ref. .
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a

Pooled estimates from ten imputed datasets

*

p < 0.01.

**

p < 0.001.

For every one-unit increase in confidence in cooking, participants consumed an additional 0.59 cups of F&V (p < 0.001) (Model 1). Similarly, for every one-unit increase in healthy eating self-efficacy, participants consumed an additional 1.00 cup of F&V (p < 0.001) (Model 2). In contrast, the perceived stress model (Model 3) indicated that the participants’ perceived stress was not associated with their F&V intake (β = −0.02, p = 0.36). The social support model (Model 4) showed that neither family encouragement (β = 0.12, p = 0.43) or discouragement (β = −0.15, p = 0.36) nor friends encouragement (β = −0.05, p = 0.79) or discouragement (β = 0.36, p = 0.12) had effects on F&V intake. Similarly, the perceived food environment model (Model 5) showed that participants’ perceptions of the food environment were not associated with F&V intake (β = 0.14, p = 0.28). The combined model (Model 6) indicated that only healthy eating self-efficacy remained significantly associated with F&V intake: for every one-unit increase in healthy eating self-efficacy, participants consumed an additional 0.96 cups of F&V intake (p < 0.001). Cooking confidence was no longer associated with F&V intake in the combined model (p > 0.05).

In addition, we also ran a complete case analysis with the observed data (i.e. without any imputation). Results were identical in direction and similar in magnitude between the complete case and multiple imputation analyses. Therefore, missing values in our data were not deemed to be a source of bias. Supplementary Table 1 contains the results from the complete case analysis.

4. DISCUSSION

The present study used an ecological framework to examine the relationship between individual, social, and environmental factors and F&V intake among midlife and older rural women. Findings indicated that cooking confidence and healthy eating self-efficacy were positively associated with F&V intake. When all factors were examined together, only healthy eating self-efficacy remained positively associated with F&V intake.

Our findings are similar to other studies where individuals who were less motivated and had less cooking confidence were less likely to adopt healthy eating behaviors (Brug, Kremers, Lenthe, Ball, & Crawford, 2008; Williams, Thornton, & Crawford, 2012). Since enhancing one’s self-efficacy and cooking skills are often incorporated into nutrition programs and are shown to be effective in facilitating F&V intake (Luszczynska, Tryburcy, & Schwarzer, 2007; Reicks, Trofholz, Stang, & Laska, 2014), our results further emphasize the importance of focusing on skill- and confidence-building to improve diet quality. The disappearance of the association between cooking confidence and F&V intake in the combined model could be due to the stronger association of self-efficacy with F&V intake in our sample.

The findings in this study on the impact of perceived stress on F&V intake are in contrast to studies that showed that low levels of perceived stress were associated with high F&V intake among non-rural older adults (Ferranti et al., 2013; Payne, Steck, George, & Steffens, 2012). The lack of association could be due to the low variance in stress reported by participants; 71.3% of the participants self-rated as having low stress and only three out of the 513 participants reported having high stress. Furthermore, even though rural women’s poorer diet (Bloom et al., 2017; Harrington, Lutomski, Molcho, & Perry, 2009; Schulz & Sherwood, 2008) could be related to their higher caregiving responsibilities, greater financial burdens, and higher likelihood of being socially isolated (Probst et al., 2006; Weaver, Himle, Taylor, Matusko, & Abelson, 2015), most of our participants were older and may not have had as many caregiving responsibilities as their younger rural counterparts. In addition, more than half of our participants were retired (61.8%), had an annual household income of or higher than $50,000 (60.2%), and were partnered or married (69.2%). These may have contributed to their low stress levels reported in this study.

Social support did not correlate with F&V intake. In our study, participants rated both positive and negative support from family and friends as low. As such, it was challenging to understand the lack of association between the influence of family and friends and F&V intake. Participants’ low perceived social influences might only indicate a weak social network or simply a lower level of social influence that may not translate into actual influence on F&V intake. Our findings do not concur with previous studies that found that positive support from family and friends can be helpful for improving diet quality among rural women (Walker, Pullen, Hertzog, Boeckner, & Hageman, 2006; Yates et al., 2012). Similarly, although negative social influences such as nagging or unhelpful advice may be barriers to healthy eating, the present study did not find such a relationship. The conflicting findings of the present study may partially result from differences in various contextual factors related to one’s social support, such as sex, health status, socioeconomic status, and geographic location, as well as the tools used to assess social support and diet in this study compared to those used in previous studies. Another explanation for the lack of association between social support for healthy eating and F&V intake in the present study could be that the survey items used in our study did not ask specifically about social influence of F&V intake. Further research is needed to examine the associations between different types of social support and the dietary intake of rural women. Findings from such investigations might be useful for developing effective rural nutrition programming. For example, some interventional and qualitative studies have found that social support from family and friends is an important factor in fostering positive behavioral changes (Anderson, Winett, Wojcik, & Williams, 2010; Winston et al., 2015; Sriram, Morgan, Graham, Folta, & Seguin, 2018).

Participants’ perceived food environment was not associated with F&V intake. Our null finding contradicts one study that found a significant association between perceived food environment and F&V intake among seniors in rural Texas (Sharkey, Johnson, & Dean, 2010). This variation of results may, however, have been the consequence of a difference in the tools used by the aforementioned and present study in data collection, particularly regarding the usage of different survey questions addressing perceived food environment and F&V intake. Results from similar studies in urban contexts are also mixed (Blitstein, Snider, & Evans, 2012; Flint, Cummins, & Matthews, 2013; Lucan & Mitra, 2012). One potential explanation for the null finding in our study could be due to the fact that rural residents often travel outside of their communities to obtain good quality and affordable foods or shop at locations near their place of employment (Cummins, 2007; Yousefian, Leighton, Fox, & Hartley, 2011). Additionally, participants generally rated their food environment highly, limiting the ability of our data to understand the association between perceived food environment and diet. Future research should focus on investigating the food shopping behaviors of rural residents, as well as on fostering a deeper understanding of the true composition of rural food environments. For example, future consumer food environment assessments should include other important non-traditional food sources that are common in rural settings such as farmers’ markets, mobile food vendors, and other community food distribution networks (e.g. through churches, fire departments, and other community sites) (Lytle, 2009).

Findings from our combined model shed light on the types of resources that nutrition interventionists should consider when developing programs to increase F&V intake. Our findings suggest that building rural older women’s confidence in consuming F&V should be emphasized in parallel with other strategies that focus on increasing social support and improving healthy food access. However, it is important to note that deciding at which levels to intervene is not simple. Our findings do not intend to suggest future interventions focus on capacity building alone since such efforts may run the risk of only benefiting those with lower self-efficacy. Instead, our findings support the integration of capacity building activities with other strategies that aim to improve rural diet quality. For instance, strategies to improve healthy eating self-efficacy are often coupled with other social and environment strategies to achieve greater impacts in previous successful multi-component interventions that were designed to improve diet quality among rural and remote populations (Gittelsohn et al., 2010; Gittelsohn, Kim, He, & Pardilla, 2013; Ho et al., 2008).

The present study has limitations worth noting. Our data were gathered from self-reported surveys. Thus, participants could either over-report or under-report their F&V intake. Second, our study was a cross-sectional analysis in which the associations found cannot be used to suggest causality; longitudinal investigations are needed to more thoroughly understand the relationship between psychosocial factors, perceived food environment, and F&V intake. Third, participants in our study were predominantly white, higher socio-economic status midlife to older women, which limits the generalizability of our findings to other populations. It is also possible that these women had more interest in nutrition than the general population since they had previously participated in the SWP and had also opted to respond to the survey, further limiting the generalizability of this study.

5. CONCLUSIONS

Rural midlife and older women disproportionately experience poorer diet and health outcomes in comparison to their urban counterparts. Balanced diets with adequate F&V intake are crucial to healthy aging and overall wellbeing. Findings from our study provide important information on the relationships between cooking confidence, self-efficacy, and F&V intake. Given that rural communities often face financial constraints in supporting the development and implementation of effective health interventions, our results may be useful to inform and evaluate targeted nutrition programs and strategies to improve the dietary health of rural women.

Supplementary Material

1

Highlights.

  • Little is known on what relates to rural women’s fruit and vegetable (F&V) intake.

  • Cooking confidence and self-efficacy were positively associated with F&V intake.

  • Perceived stress, social support, and perceived food environment were not associated with F&V intake.

Acknowledgements

We are grateful to the women who participated in our study and to Judy Ward (Cornell University) for her work and contributions to this research.

Funding

This work was supported by the National Heart, Lung, and Blood Institute [K01 HL108807].

Footnotes

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Declarations of interest

None.

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