Intuitive eating: associations with physical activity motivation and BMI.

For individual use only. Duplication or distribution prohibited by law.

Physical Activity; Nutrition

Intuitive Eating: Associations With Physical Activity Motivation and BMI Julie Gast, PhD, MCHES; Amy Campbell Nielson, MS; Anne Hunt, ScD; Jason J. Leiker, PhD Abstract Purpose. To determine whether university women who demonstrated internal motivation related to eating behavior may also be internally motivated to participate in regular physical activity (PA) and have a lower body mass index (BMI) when controlling for age. Traditional approaches for health promotion related to healthy weight include restrictive eating and exercise prescription. Examining motivation for eating and PA may prove an effective alternative for achieving or maintaining healthy weight for university women. Design. Design was a cross-sectional study. Setting. Study setting was a large, public university in the western United States. Subjects. Study subjects were 200 undergraduate women with a mean age of 19 years, mostly white (90%) and of healthy weight (69%, with a BMI range of 18.5–24.9). Measures. Study measures were the Intuitive Eating Scale and the Behavioral Regulation in Exercise Questionnaire. Analysis. Correlations and regression models were used. Intuitive eating was examined in the sample as a whole and among subgroups of respondents grouped based on tertile rankings of intuitive eating scores. Results. There was evidence that women who demonstrated internal motivation related to eating were also internally motivated to participate in regular PA. Women who reported being internally motivated to eat were significantly more likely to engage in PA for pleasure and to view PA as part of their self-concept. Women who reported high levels of intuitive eating had significantly lower BMI scores than those reporting medium or low levels when controlling for age. Conclusion. For women to achieve or maintain a healthy weight, it may be best for health professionals to examine motivation for eating and PA rather than the encouragement of restrictive eating and exercise prescriptions. (Am J Health Promot 2015;29[3]:e91–e99.) Key Words: Obesity, Body Mass Index, Intuitive Eating, Self-determination Theory, Exercise Motivation, Prevention Research. Manuscript format: research; Research purpose: modeling/relationship testing; Study design: nonexperimental; Outcome measure: behavioral; Setting: school; Health focus: nutrition, fitness/ physical activity, weight control; Strategy: skill building/behavior change; Target population age: adults; Target population circumstances: education/income level

PURPOSE Restrictive eating, or dieting, has long been a popular tool to control weight. Extensive research has looked at relationships among restrictive eating and weight-loss maintenance,1–4 physical complications associated with restrictive eating,5–7 and negative behaviors associated with restrictive eating.5,7 Research on restrictive eating consistently shows that those who adopt this behavior for weight-loss purposes typically gain the weight back over time.8,9 Findings also suggest that restrictive eating may be too psychologically taxing to maintain for extended periods of time.10 It has been reported that individuals who try to restrict their eating may experience large weight fluctuations,11 depressive symptoms,12 low self-esteem,13–15 and eating disorder symptoms.16 Because of these risks, restrictive eating practices do not appear to be conducive to the maintenance of a long-term healthy lifestyle for most people. Intuitive eating, an alternative to restrictive eating or dieting, encourages individuals to eat only when physiologically hungry.17 Other components of intuitive eating include avoiding food consumption for emotional, so-

Julie Gast, PhD, MCHES, is with the Department of Health, Physical Education and Recreation, Utah State University, Logan, Utah. Amy Campbell Nielson, MS, is with the Utah Department of Health, Salt Lake City, Utah. Anne Hunt, ScD, is with the Office of Methodological Sciences, Emma Eccles Jones College of Education and Human Services, Utah State University, Logan, Utah. Jason J. Leiker, PhD, is with the Department of Sociology, Social Work and Anthropology, Utah State University, Logan, Utah. Send reprint requests to Julie Gast, PhD, MCHES, Department of Health, Physical Education and Recreation, Utah State University, 7000 Old Main Hill, Logan, UT 84322-7000; [email protected]. This manuscript was submitted March 5, 2013; revisions were requested May 9, September 11, and October 15, 2013; the manuscript was accepted for publication October 24, 2013. Copyright Ó 2015 by American Journal of Health Promotion, Inc. 0890-1171/15/$5.00 þ 0 DOI: 10.4278/ajhp.130305-QUAN-97

American Journal of Health Promotion

January/February 2015, Vol. 29, No. 3

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For individual use only. Duplication or distribution prohibited by law. cial, or environmental cues; rejecting a dieting mentality; participating in consistent enjoyable physical activity; being mindful of the body’s satiety level, and accepting one’s body size.18 The intuitive eating approach is unique in that it focuses on motivation for eating (e.g., internal, external, or emotional cues) and how such an approach correlates with health. For example, previous research has found that for adolescent girls, emotional eating was associated with being overweight, whereas for adolescent boys, external eating motivation was associated with being overweight.19 Although much of intuitive eating is focused on eating cues and motivation, as noted above, physical activity is also part of intuitive eating, and one is encouraged to find activities that are enjoyable and to avoid exercise with the intent of losing weight or burning calories. Previous studies that have been conducted on intuitive eating and motivation for eating have examined eating disorder symptomatology,20 development of intuitive eating measurement scales,21,22 exploration of an Acceptance Model of Intuitive Eating,22 Western cultural influence on intuitive eating in Asian countries,23 and adherence to an intuitive eating vs. a calorie-restrictive intervention.12 Researchers that have investigated intuitive eating have found positive outcomes for those who practice this eating style, in that individuals experience less emotional eating, better body image, lower body mass index (BMI), and improved self-esteem.24–26 Although eating behavior is often the focus of research on weight and health, physical activity is also an important component. For individuals to reap the benefits of physical activity, however, they must maintain it as part of their lifestyle, which requires a certain level of motivation.27,28 Researchers have applied the Self-Determination Theory (SDT)29 to better understand this relationship between motivation and physical activity.30 The SDT postulates that motivation is experienced in varying degrees, which can be represented on a continuum.31 Three categories exist on this continuum that range from the lowest amount of motivation to the highest. Amotivation, or the complete

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lack of motivation to engage in an activity, is on the left side of the continuum. Extrinsic motivation, or motivation that exists due to external pressures to engage in an activity, is in the middle of the continuum. Intrinsic motivation, or motivation that exists when an individual participates in an activity out of enjoyment or pleasure, is on the farthest right. Within the extrinsic category of the SDT continuum are four additional categories of motivation: external, introjected, identified, and integrated. External motivation depends on external demands or rewards to engage in the activity. Introjected motivation is when an individual engages in activity due to guilt and shame, but it is not yet part of the self. Identified motivation is when a person values a goal or activity. Finally, integrated motivation is the most autonomous on the extrinsic scale, where one feels pleasure from physical activity. As individuals move from the low end of the continuum to the high end, their level of self-determined motivation increases. SDT research has shown that when they are intrinsically motivated, individuals are more likely to maintain their motivation to continue with physical activity over extended periods of time.32,33 Intrinsic motivation of physical activity and the intuitive eating paradigm are similar, with the ideologic emphasis on health adherence for satisfaction and enjoyment, rather than an emphasis on external factors, such as body weight or food avoidance. Studies that have examined eating style and physical activity motivation have found a positive relationship between an intrinsic motivation to engage in physical activity and a self-regulated style of eating.28,34 However, this relationship has not been examined specifically using an intuitive eating approach, which would allow a more in-depth look at the relationship between eating style and physical activity motivation. Age has been linked to declines in physical activity and increased weight and BMI in college women.35,36 A recent literature review found that women ages 18 to 36 years gain more weight than either younger or older age categories of women.37 The review found that weight gain was associated with contraception use, eating fast

food and high-fat diets, quitting smoking, decreases in physical activity, and university transitions. Based on current evidence, age appears to be an important aspect of changes in weight, BMI, and physical activity for college women. Individuals who have learned to eat intuitively have been able to increase and maintain their physical activity significantly when compared with those who participated in a traditional restrictive eating program.12 However, this correlation does not explain the interaction between intuitive eating and physical activity motivation. This relationship has been investigated in male college students,25 but more research is needed to understand how eating style and physical activity motivation interact in female college students, because this population is at risk for unhealthy eating behaviors, weight gain, and disordered eating behaviors.38 The purpose of the study was to examine whether motivations for eating were correlated with motivations for physical activity in university women. A secondary purpose was to examine the relationship between intuitive eating scores and BMI when controlling for age in university women.

METHODS Sample The sample for this study consisted of 200 female undergraduate students at a large public university in the western United States. Previous research studies on intuitive eating were conducted using similar convenience samples of university students.21,26,39 Women who were participants in collegiate athletics were excluded in the study due to their training schedules. Pregnant women were also excluded because of the possibility for restricted physical activity and eating preferences. A statistical power analysis was conducted to determine an adequate sample size for the proposed design. The power analysis revealed that with an alpha of .05 and an estimated power of .8, a sample size of 158 would provide adequate power to detect a medium effect size (d ¼ .35). A sensitivity analysis indicated that with the final study sample of 200 analyzed,



Table 1 Descriptive Statistics for Demographics, Intuitive Eating Scale (IES), Behavioral Regulation in Exercise Questionnaire (BREQ), and Overall Subscales Demographic Characteristics and Variables Age Race White Hispanic Asian Native American Pacific Islander Black Class Freshman Sophomore Junior Senior BMI Underweight Healthy weight Overweight Obese BMI adjusted* IE Low IE Medium IE High IE IES (possible range) Intrinsic (1–5) Extrinsic (1–5) Antidieting (1–5) Self-care (1–5) Total BREQ (possible range) External regulation (0–4) Introjected regulation (0–4) Identified regulation (0–4) Intrinsic regulation (0–4)

No. 200 200 180 8 6 3 1 2 200 124 49 23 4 200 13 138 35 14

Percentage 100

Mean (SD) 19.58 (2.42)

90 4 3 1.5 0.5 1.0 62 24.5 11.5 2 23.23 (4.95) 6.5 69 17.5 7 23.09 (4.17)

200 69 58 73

34.5 29.0 36.5

200 200 200 200 200 200 200 200 200 200

2.87 2.72 3.37 3.50 85.94

(0.64) (0.76) (0.82) (0.83) (15.51)

1.03 1.96 2.78 2.84

(0.80) (1.12) (0.94) (0.97)

BMI indicates body mass index; and IE, intuitive eater. * Trimmed means were employed for outlier BMI z scores greater than j3.5j.

a small to medium effect could be detected (d ¼ .35). Procedures and Design The study used a cross-sectional design using a pen-and-paper selfreport survey. University institutional review board approval was granted prior to data collection. Data collection took place during undergraduate introductory English, sociology, and psychology courses; the data collection instruments and informed consent documents were given to all students in attendance on a specific day. Participants had the opportunity to receive one of three $20 university bookstore


gift certificates through a random drawing. Participants were given the option to complete the instruments in class or at home and return them at the following scheduled class time. Measures Two standardized measures and demographic items were used to assess study variables. These included the Intuitive Eating Scale (IES)21 and the Behavioral Regulation in Exercise Questionnaire (BREQ).40 The IES is an instrument developed to measure the levels of intuitive eating behaviors and cognitions present in individual eating styles. This instrument consists

of 27 items answered on a five-point Likert-type scale, with answers ranging from strongly agree (5) to strongly disagree (1). Individuals who scored higher on the IES instrument indicated stronger adherence to an intuitive eating style. Subscales include antidieting (rejection of dieting mentality; 13 questions), intrinsic eating (internal eating focus; 4 questions), extrinsic eating (limits environmental and emotional eating; 6 questions), and self-care (body acceptance and health orientation for eating and physical activity; 4 questions). Reliability for the total IES score was very good (.877) and similar to previous studies. Reliability coefficients for the subscales were also similar to previous studies,21 with minimal reliability for the intrinsic eating d (.431) and self-care (.684) subscales, good reliability for the antidieting (.886) subscale, and acceptable reliability for the extrinsic eating (.763) subscale in the present study. Face, content, and convergent validity have been established for the IES in previous research.21 The BREQ was developed to test SDT in relation to physical activity.40 This instrument consists of 15 questions on a Likert-type scale of ‘‘not true for me’’ (0) to ‘‘very true for me’’ (4). Items are split into the following subscales: external regulation (engages in physical activity because of external pressures; four questions), introjected regulation (engages in physical activity because of guilt or shame; three questions), identified regulation (values physical activity; four questions), and intrinsic regulation (feels pleasure in physical activity; four questions). Subscale reliability for the present study was consistent with past research and indicates very good reliability.37 Cronbach a values were as follows for the present study: external regulation (.800), introjected regulation (.846), identified regulation (.869), and intrinsic regulation (.918). Only the BREQ subscales were used in the data analysis. Previous research established acceptable levels of goodness of fit, internal consistency, and validity of the BREQ.40 Self-reported weight and height data were collected to determine participant BMI along with age, race, and college class year. BMI z scores ex-


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Table 2 Correlations Among Intuitive Eating Scale Subscales and Behavioral Regulation in Exercise Questionnaire Subscales (N ¼ 200)

External regulation Introjected regulation Identified regulation Intrinsic regulation

Intrinsic, r/p values

Extrinsic, r/p values

Antidieting, r/p values

Self-care, r/p values

0.022/0.76 0.026/0.72 0.164/0.02 0.183/0.01

0.141/0.05 0.482/,0.0001* 0.103/0.15 0.088/0.21

0.348/,0.0001* 0.563/,0.0001* 0.070/0.33 0.206/0.003*

0.151/0.03 0.227/0.001* 0.291/,0.0001* 0.433/0.0001*

* Significant at p , 0.05 alpha level and significant after Bonferroni adjustment for multiple correlations.

ceeding j3.5j were trimmed to the closest adjacent score to minimize the impact of extreme outliers.41 Analysis The IES, the BREQ, and demographic data obtained from participants were coded and entered into SPSS version 20. Descriptive statistics were calculated for demographic data, IES overall and subscales scores, and the BREQ subscale scores (Table 1). Pearson correlation coefficient analysis was then conducted to investigate the relationship between intuitive eating and BREQ subscales (Table 2), with Bonferroni adjustments for multiple correlations applied and an adjusted alpha level of .0003. To test the research hypotheses of a possible significant relationship between IES and the primary and secondary dependent BREQ and BMI measures, these outcomes were regressed on the independent intuitive eating measure, using general linear modeling (Tables 3–6). An exploratory correlation analysis showed age to be significantly correlated with BMI and with the antidieting and self-care subscales in this study, and previous

research25 showed an age correlation with the external regulation BREQ subscale; age was included in these models as a covariate. Because of the lack of variability in race in this sample (90% white non-Hispanic), race was not included in the analysis. Intuitive eating was examined first as a continuous score to assess its overall relationship to the BREQ and BMI outcomes, and then with tertiles to determine whether the impact of intuitive eating varied by level nonlinearly. Prior research used the median value to identify eaters as either intuitive or not.21,25 With this definition, a score of 86, for example in our sample, would be categorized as a nonintuitive eater, whereas one of 87 would be considered an intuitive eater. By using tertiles rather than a dichotomy—the one-third of respondents with the lowest scores (0–79) were classified as low intuitive eaters, the one-third of respondents with the midrange scores (80–92) were classified as medium intuitive eaters, and the respondents with the upper onethird of scores (93–126) were classified as high intuitive eaters—a greater level

of discernment was provided across the sample.

RESULTS Sample Demographics There were 231 participants who returned the survey; however, 31 were ineligible because of pregnancy, collegiate sport participation, or missing data. The mean age in years of the final sample was 19.6, with an SD of 2.42. A total of 69% of study participants were considered healthy weight (BMI ¼ 18.5–24.9), 6.5% were considered underweight (BMI ,18.5), 17.5% were considered overweight (BMI ¼ 25– 29.9), and 7% were considered obese (BMI .30).27 A total of 90% of the sample reported being white nonHispanic, whereas the remaining 10% were of other races/ethnicities, which was similar to the university population as a whole. As expected, the sample was primarily freshman students (62%), because data collection took place in introductory general education courses. In sum, 69 of the participants (34.5%) were considered low intuitive eaters, 58 (29%) were considered medium intuitive eaters, and 73

Table 3 Regression Coefficients for Intuitive Eating Scale (IES) Predicting Behavioral Regulation in Exercise Questionnaire Subscales, Adjusted for Age (N ¼ 200)

IES Age Constant R2 adjusted No./df

External Regulation b (p)

Introjected Regulation b (p)

Identified Regulation b (p)

Intrinsic Regulation b (p)

0.008 (,0.0001)* 0.02 (0.07) 1.75 0.11 200/2

0.04 (0.0001)* 0.023 (0.39) 6.00 0.34 200/2

0.0001 (0.80) 0.002 (0.08) 1.23 0.0001 200/2

0.005 (0.001)* 0.006 (0.48) 1.05 0.09 200/2

* Significant at p , 0.05 alpha level.

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Table 4 Comparison of Mean Scores (With 95% Confidence Intervals [CIs]) for Behavioral Regulation in Exercise Questionnaire Subscales by Level of Intuitive Eating, Adjusted for Age (N ¼ 200)

Subscale External regulation Introjected regulation Identified regulation Intrinsic regulation

Low Intuitive Eater, Mean (CI) 1.30 2.65 2.74 2.56

(1.10, (2.43, (2.50, (2.33,

1.52) 2.88) 3.00) 2.80)

Medium Intuitive Eater, Mean (CI) 1.11 1.98 2.73 2.76

(0.91, (1.73, (2.47, (2.50,

1.32) 2.23) 3.02) 3.04)

High Intuitive Eater, Mean (CI) 0.70 1.29 2.85 3.16

(0.56, (1.07, (2.61, (2.90,

0.86) 1.51) 3.14) 3.43)

Omnibus p

Low vs. Medium p

Low vs. High p

Medium vs. High p

,0.0001* ,0.0001* 0.77 0.005*

0.19 ,0.0001*† 0.95 0.28

,0.0001*† ,0.0001*† 0.54 0.001*†

0.002*† ,0.0001*† 0.52 0.04

* Significant at p , 0.05 alpha level. † Significant after Bonferroni adjustment for multiple comparisons.

(36.5%) were categorized as high intuitive eaters. Demographic characteristics of the study sample are presented in Table 1. Summary Statistics for IES and BREQ Scores The means and SDs for the IES and BREQ subscale scores are presented in Table 1. The highest mean scores for IES subscales were for the self-care (mean ¼ 3.50; SD ¼ .83) and antidieting (mean ¼ 3.37; SD ¼ .82) subscales. The lowest mean score in this analysis was for the extrinsic eating subscale, with a mean score of 2.72 (SD ¼ .76). The BREQ subscale scores reflected the continuum of external regulation to intrinsic regulation for physical activity motivation, with increases in mean scores across each level of the continuum. The mean score for external regulation was 1.03 (SD ¼ .80), that of introjected regulation was 1.96 (SD ¼ 1.12), that of identified regulation was 2.78 (SD ¼ .94), and, finally, that of intrinsic regulation was 2.84 (SD ¼ .97). Correlations of IES Subscales and BREQ Subscales The correlations between IES subscales and BREQ subscales are found in Table 2. There was a significant negative correlation between external regulation and the antidieting (r ¼ .348; p , .0001) subscale. Negative correlations were statistically significant between introjected regulation and the extrinsic eating (r ¼.482; p , .0001), antidieting (r ¼ .563; p , .0001), and self-care (r ¼ .227; p ¼ .001) subscales. A significant positive correlation was found between identi-


fied regulation and the self-care (r ¼ .291; p ¼ .001) subscale. Positive significant correlations were also found between intrinsic regulation and the antidieting (r ¼.206; p ¼ .003) and selfcare (r ¼ .433; p , .0001) subscales. All correlations after Bonferroni adjustment for multiple comparisons are bolded in Table 2. Regression Models for BREQ Subscale Scores and IES Score To better understand the role of intuitive eating on physical activity motivation, we regressed the four BREQ subscales on IES total score, controlling for age (Table 3). The first model, external regulation, revealed that the IES total score was inversely related to external regulation, with a statistically significant .008-point decrease (p , .0001) in external regulation for every unit increase in IES total score. In the second model, the IES total score was also inversely related to introjected regulation, with a .04-point decrease (p ¼ .0001) in this subscale for every point increase in IES. For the identified regulation model, no statistical associations were identified between IES total score and this subscale. For the final intrinsic regulation model, IES total score was significantly related to intrinsic regulation, with a .005-point increase (p ¼ .001) in this subscale for each unit increase in IES score. There were no significant relationships between age and the external regulation subscale, the identified regulation subscale, the introjected regulation, and the intrinsic regulation in the models. To provide further insight into the relationship between levels of intuitive

eating and the BREQ subscales, the intuitive eating scores were then categorized into tertiles in the regression analysis, with post hoc mean comparisons of BREQ subscale scores between the low, medium, and high intuitive eating levels (Table 4). There was a significant difference in mean scores for external regulation between the low (mean ¼ 1.30) vs. high (mean ¼ .70) intuitive eaters (p , .0001), as well as between the medium (mean ¼ 1.11) vs. high (mean ¼ .70) intuitive eaters (p ¼ .002). Introjected regulation showed highly significant mean score difference among all intuitive eater levels (p , .0001), with low, medium, and high means of 2.65, 1.98, and 1.29, respectively. Identified regulation mean scores were not significant, regardless of level of intuitive eater. The intrinsic regulation mean score was significantly different only for low (mean ¼ 2.56) vs. high (mean ¼ 3.16) intuitive eaters (p , .001), after adjustment for multiple comparisons.

Table 5 Regression Coefficients for Intuitive Eating Scale (IES) Score Predicting Body Mass Index (BMI), Adjusted for Age (N ¼ 200) BMI b (p) IES Age Constant R2 adjusted No./df

0.05 (0.03)* 0.43 (0.002)* 19.08 0.08 200/2

* Significant at p , .05 alpha level.


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Table 6 Comparison of Mean Body Mass Index (BMI; With 95% Confidence Intervals [CIs]) by Level of Intuitive Eating, Adjusted for Age (N ¼ 200)

Subscale

Low Intuitive Eater, Mean (CI)

Medium Intuitive Eater, Mean (CI)

High Intuitive Eater, Mean (CI)

Omnibus p

Low vs. Medium p

Low vs. High p

Medium vs. High p

BMI

23.87 (22.88, 24.79)

23.65 (22.49, 24.58)

21.91 (21.10, 22.96)

0.02*

0.68

0.008*†

0.04

* Significant at p , 0.05 alpha level. † Significant after Bonferroni adjustment for multiple comparisons.

Regression Models for BMI and IES Score Regression analysis results indicated that BMI decreased by .05 for every unit increase in total IES score (p ¼ .03). The adjusted R 2 indicates a low predictive value for the model, accounting for only 8% of the variability in BMI. Age was significantly associated with BMI. Specifically, BMI increased by .43 for every point increase in age (p ¼ .002). The results of the final model, which only included IES total score and age, are presented in Table 5. Table 6 presents the model post hoc results when examining the impact of intuitive eating levels on BMI. When comparing the BMI means by level of intuitive eating and adjusting for age, it was found that both low intuitive eaters (mean ¼ 23.87) and medium-level intuitive eaters (mean ¼ 23.65) differed from highly intuitive eaters (mean ¼ 21.91), with p values of .008 and .04 respectively, although the medium-level intuitive eaters did not retain significance after adjustment for multiple comparisons. So although a decreasing trend in BMI was noted with intuitive eating in the continuous model, the tertile analysis shows the relationship is somewhat nonlinear, with highly intuitive eaters showing significantly lower BMI.

DISCUSSION Many pressing health problems are related to both poor diet and lack of physical activity; however, restrictive eating and regular exercise seem to be out of reach for many individuals.42 Thus, it is critical to both examine motivational issues for both eating and physical activity, and, more specifically, learn how these factors are linked. This

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research sought to determine whether motivation for eating, as measured by intuitive eating style, and motivation for physical activity guided by the SDT, were linked. It was expected that those participants who were internally motivated to eat for internal hunger cues may also be internally motivated to engage in physical activity. The second aim of the study was to understand whether BMI and age were related to IES scores. Correlation analysis revealed that individuals who were internally motivated to engage in physical activity were also less likely to engage in restrictive eating behaviors and more likely to practice self-care. Self-care refers to valuing a healthy body over a thin one, body acceptance, and enjoying physical activity. Conversely, those that expressed external motivation for engaging in physical activity were more likely to engage in restrictive eating behaviors. Those that reported feelings of guilt as a motivator for engaging in physical activity (introjected regulation) seemed at particular risk for eating for nonphysiologic reasons, such as emotional or social cues, and also for reporting increased dietingrelated attitudes and behaviors (Table 2). When examining the relationship between age and the BREQ subscales, no significant relationship was established among age and the introjected regulation, intrinsic regulation, external regulation, and identified regulation subscales. Previous research has found that age was significantly related to external regulation in a sample of male college students.25 However, a recent study indicated that young adults tend to be motivated to exercise because of interpersonal reasons compared with older adults, who may be

more motivated by health and psychologic reasons.43 Another possible reason age was not a factor in this study was the lack of variance of the age of the sample. Most of the sample consisted of freshman college students, with a mean age of 19 years (SD ¼ 2.42). The IES total score was inversely related to external regulation and introjected regulation in the continuous models, which indicates that being an intuitive eater made one less likely to be motivated to engage in physical activity because of external factors. It does appear that in this study, a relationship exists between being motivated to eat for internal reasons, such as physiologic hunger, and being physically active because it is part of one’s self-concept and is enjoyable. No such relationship was found between IES total score and identified regulation, but IES total score and intrinsic regulation were positively and statistically significantly associated. In this study, intuitive eaters were more likely to identify with the highest level of physical activity motivation. A previous study found that as participants in an intuitive eating intervention maintained their intuitive eating lifestyle, they also increased significantly regular physical activity.24 This same study noted that from the beginning to the end of the study, individuals who learned the intuitive eating style significantly increased their time spent on moderate, hard, and very hard physical activity compared with controls.24 In another study, researchers found that as individuals experienced higher levels of self-determined motivation, they also engaged in more physical activity.44 Although these two previous studies do not directly examine the relationship between intuitive eating


For individual use only. Duplication or distribution prohibited by law. and intrinsic regulation motivation to engage in physical activity, the results suggest that intrinsic regulation motivation may have changed as the individuals who were learning the intuitive eating became less restrictive in their eating style. Perhaps individuals who practice intuitive eating are inherently more appreciative of their bodies and the pleasure that they get from being physically active than are less intuitive eaters. Another possible explanation could be that individuals who eat nonintuitively focus more on completing their physical activity rather than enjoying it for the experience, thus hindering their intrinsic motivation. A unique contribution of this paper is the examination of motivation for physical activity by intuitive eating levels using tertiles. Previous research had used a cutoff score based on median total IES score to divide samples into intuitive and nonintuitive eaters.21,25 Post hoc analysis revealed that those motivated to engage in physical activity because of external factors (e.g., to avoid punishment) demonstrated a significant difference between both low IES and high IES scores (Table 4). This may indicate that consistent intuitive eaters are less likely to be externally motivated to engage in physical activity. A similar relationship was found for introjected regulation, with strong significant differences among all three levels of intuitive eating. Results indicate that more intuitive eaters are less likely to be motivated to be physically active for reasons of guilt or shame. Intrinsic regulation was significantly related to eating motivation between low IES scores and high IES scores. Although medium and high IES scores were significant for intrinsic regulation, they did not remain so after Bonferroni adjustment for multiple comparisons. These findings indicate a strong linear trend for different levels of intuitive eating related to introjected regulation motivation, but a somewhat nonlinear relationship with intrinsic regulation. Identified regulation motivation for physical activity was not significantly related to any level of intuitive eating. This is surprising in that identified motivation is associated with valuing the target behavior and starting to


adopt the behavior as part of one’s selfconcept. It was expected that the more a person eats intuitively, the more one would also be internally motivated to engage in physical activity. In a recent study with male participants, neither identified nor intrinsic regulation was significantly related to eating style using the median cutoff for IES.25 The authors concluded that for men, being an intuitive eater may be an important factor in the initial motivation for physical activity, but it is not sufficient for more advanced levels of motivation. However, due to the cross-sectional nature of the present study, it is difficult to determine which came first, motivation for physical activity or intuitive eating behaviors. Further research should explore whether gender differences exist between eating style and motivation for physical activity. Previous research has found that identified regulation motivation has significantly more influence on physical activity behavior than any other type of motivation.45 These researchers also stated that this was not surprising when one considers that physical activity is not always intrinsically motivating. So, although we found a significant difference between intuitive eating levels (low vs. high) and their level of intrinsic motivation for physical activity, perhaps intuitive eaters rely on identified motivation to engage in physical activity just as much as less intuitive eaters. The second hypothesis for the study was to examine the relationship between IES scores and BMI while controlling for age. BMI was associated with IES total score and indicated that BMI decreased as intuitive eating score increased. However, the relationship was moderate at best, albeit in the expected direction in this model. As found in other studies, in general, as age increased so did BMI.46 However, post hoc results examining levels of intuitive eating indicated that highly intuitive eaters showed significantly lower BMIs compared with the scores of low intuitive eaters. So, although a decreasing trend in BMI was noted with intuitive eating in the continuous model, the tertile analysis shows the relationship is somewhat nonlinear, with highly intuitive eaters showing significantly lower BMI.

Previous research has found that increases in IES score are related to decreases in BMI in both male and female samples.21,23,25,39 Thus, there is an increasing body of literature that supports the finding that people who can self-regulate when and why they eat have healthier BMIs compared with people who lack these skills. An important component of intuitive eating interventions is to educate people about how to recognize hunger and fullness cues and how to avoid restrictive eating practices.17,18 For those who can master these skills, improved health status may also be achieved. It is important to note that while restrictive eating is difficult to maintain for long periods, it too can be related to motivation for physical activity. A previous study found both restrictive eating and physical activity were only successfully maintained by 20% of the original sample.42 However, other research reported that women with greater restrictive eating behaviors engaged in more physical activity compared with those who were not as restrictive.47 Additionally, past research found that women with greater restrictive eating behaviors reported significantly greater physical activity frequency and intensity compared with those who did not restrict their eating behaviors.48 Further research might examine whether intuitive eating and physical activity are sustainable over long periods of time, across genders, and across the lifespan. Limitations of the present study included the fact that all responses were self-reported and from a convenience sample, both of which may have affected the reliability of the responses and generalizability to other studies. Previous research has found that self-reports of height and weight have been shown to be biased.49 The offering of the gift certificate incentive may have also introduced persuasion bias. In addition, the all-female sample was mostly white, young, and overall had a healthy range of BMI scores. More heterogeneous samples may yield different results. Finally, the participants completed the instruments either in class or at home, and the variability in the setting may have increased error. The clinical signifi-


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For individual use only. Duplication or distribution prohibited by law. cance of the lower BMI scores associated with intuitive eaters was not measured, and future research should examine this. To conclude, previous research has shown how restrictive eating can negatively impact individuals psychologically, physically, and emotionally.5,6,11 It has also been shown that individuals who practice an intuitive style of eating tend to be healthier psychologically and physically.17,39,50 Preliminary research on intuitive eating seems promising, and it is possible that individuals may experience positive outcomes from practicing an intuitive eating style. A recent study found significant increases in fruit and vegetable consumption in college students who participated in a nondieting approach intervention compared with controls.51 This adds to the evidence that an intuitive eating or a similar approach may be healthier than other diet-based approaches. Besides the above-mentioned benefits for eating intuitively, the findings of the current study indicate a relationship between eating style and physical activity motivation. Specifically, individuals who eat intuitively experience more intrinsic motivation to engage in physical activity. Individuals who are intrinsically motivated to engage in a behavior do so because they enjoy it, they get inherent satisfaction out of doing it, and they are interested in doing it. More importantly, intuitive eating style and internal physical activity motivation may help buffer the effects of age on increases in BMI. The U.S. Department of Agriculture reports that inactivity in Americans is relatively high and little progress has been made in improving rates, even with the increased push for public education on the benefits of physical activity.52 If intuitive eating is a pathway that can lead to physical activity motivation and a reduction in BMI, or, if nothing else, a healthier relationship with food and physical activity, then individuals—and society—may benefit from that knowledge. Health promotion professionals need to incorporate motivational issues related to these pivotal behaviors in their health education efforts.

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SO WHAT? Implications for Health Promotion Practitioners and Researchers What is already known on this topic? To improve or maintain optimal health, individuals should engage in healthy eating practices and regular physical activity. Restrictive eating to reduce or maintain body mass index has proven difficult and may have adverse psychologic and physical consequences. What does this article add? This study is the first to examine the relationship between motivation for eating, as measured by intuitive eating, and motivation for physical activity. This study found that intuitive eaters were more likely to report internal motivation for engaging in physical activity. This study found that lower BMIs were linked to internal motivation for both physical activity and eating. What are the implications for health promotion practice or research? University women should be encouraged by health professionals to focus on nondieting approaches to reach or maintain a healthy weight.

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Are associations between electronic media use and BMI different across levels of physical activity?

Healthy eating and physical activity.

Outside-school physical activity participation and motivation in physical education.

Circadian timing and alignment in healthy adults: associations with BMI, body fat, caloric intake and physical activity.

The Obesogenic Quality of the Home Environment: Associations with Diet, Physical Activity, TV Viewing, and BMI in Preschool Children.

Is level of intuitive eating associated with plate size effects?

Associations between eating occasion characteristics and age, gender, presence of children and BMI among U.S. adults.

Physical activity as a moderator of the association between emotional eating and BMI: evidence from the Swiss Food Panel.

Associations between physical activity and BMI, body fatness, and visceral adiposity in overweight or obese Latino and non-Latino adults.

Physical activity motivation mediates the association between depression symptoms and moderate-to-vigorous physical activity.

Obesity-Related Genetic Variants and their Associations with Physical Activity.

BMI and recommended levels of physical activity in school children.

Validating the Physical Activity and Leisure Motivation Scale (PALMS).

Daily physical activity patterns of children with delayed eating behaviors.

Associations among Elementary School Children's Actual Motor Competence, Perceived Motor Competence, Physical Activity and BMI: A Cross-Sectional Study.

Dieting, exercise, and intuitive eating among early adolescents.

Psychological flexibility and mindfulness explain intuitive eating in overweight adults.

Associations of Monitor-Assessed Activity with Performance-Based Physical Function.

Top 10 research questions related to children physical activity motivation.

Functional neuroanatomy of intuitive physical inference.

Promoting Physical Activity through Priming the Content of Motivation.

Post-traumatic stress disorder, physical activity, and eating behaviors.

The creation of a healthy eating motivation score and its association with food choice and physical activity in a cross sectional sample of Irish adults.

Eating tasty food to cope. Longitudinal association with BMI.