Alimentação intuitiva na juventude: sua relação com o estado nutricional

rn Revista de Nutrição Rev Nutr 1415-5273 1678-9865 Pontifícia Universidade Católica de Campinas RESUMO Objetivo Determinar a alimentação intuitiva em adultos jovens e os efeitos de fatores como sexo, índice de massa corporal, ingestão alimentar e adequação da dieta na alimentação intuitiva. Métodos Este estudo transversal foi realizado em estudantes da Universidade de Gazi, em Ancara (N=665; 17,6% homens; 82,4% mulheres). O questionário, incluindo as características gerais, medidas antropométricas, Escala de Alimentação Intuitiva 2 e recordatório alimentar de 24 horas foi aplicado aos participantes. Para a avaliação da dieta, foram utilizados o Índice de Adequação de Nutrientes e a Razão de Adequação Média. Resultados A Escala Média de Escala de Comportamento Intuitivo-2 foi de 3,2±0,33, dos homens e das mulheres, foi de 3,3±0,37 e 3,2±0,32, respectivamente (p<0,05). De acordo com a análise de regressão linear, sexo, idade a Razão de Adequação Média tiveram efeito no modelo formado pelo escore (p<0,05). Além disso, houve uma correlação negativa entre os escores da Escala de Alimentação Intuitiva-2 e os valores do índice de massa corporal nas mulheres (rp=-0,095, p=0,026). Conclusão Os escores alimentares intuitivos variaram de acordo com o gênero, com adequação da dieta e com a idade. A alimentação intuitiva pode ser eficaz na formação de mudanças a longo prazo no comportamento, o que é benéfico para o tratamento da obesidade. O resultado deste estudo pode encorajar o desenvolvimento deste comportamento em grupos (talvez variar de acordo com o gênero) que é considerado efetivo considerando-se as mudanças do comportamento alimentar intuitivo. INTRODUCTION In recent years, obesity as a result of unhealthy eating habits, and sedentary lifestyle have become a major public health problem especially in young adults in Turkey as well as worldwide [1,2]. The primary approach to treat obesity is to provide the patient with weight loss through diet and exercise [3]. However, increasing evidence suggests that the efficacy of this treatment method is questionable in long term [4]. As an alternative to energy-restricted diets, the movement to shape eating based on the intuition of individuals began in the 1980s and has continued to the present day. This movement defends the limited effectiveness of diet restriction (restrictive eating, avoiding food, limiting energy intake) in the long run [5]. Tribole & Resch [6] developed the concept of "intuitive eating" based on the philosophy of nutrition to define healthy eating and behaviors. Intuitive eating is a new dietary approach that rejects the dieting mentality [7]. Intuitive eating is defined as the way of eating food by listening to and adapting to physical hunger, satiety, and satiety signals naturally given by the individual’s body. The concept of intuitive eating is also characterized by concepts such as normal eating, adaptive eating, wisdom eating and conscious eating [8]. The Intuitive Eating Scale (IES) was first introduced to the scientific literature by Hawks et al. [9]. The scale was then developed and the Intuitive Eating Scale-2 (IES 2) was developed [10]. Baş et al. [11] determined the validity and reliability of IES-2 in Turkish university students. According to the results presented in a literature review assessing the relationship between intuitive eating and health measures, it is stated that there is a positive relationship among intuitive eating, psychological health measures and positive eating behaviors, but a negative one between intuitive eating and the body mass index (BMI) [4]. Similarly, most current work on intuitive eating has shown that it was related to lower rigid control, lower psychological distress, higher psychological adjustment, and lower BMI [12]. Clinical studies have shown that intuitive eating does not have much effect on body weight loss, but it is effective in terms of weight maintenance, improved psychological health, positive physical health indicators (e.g. blood pressure, cholesterol level etc.) and diet intake and/or eating behaviors [13-16]. In addition to these findings, studies assessing the relationship between BMI and intuitive eating have found negative correlations between the two [5,17]. To the best of our knowledge, this study is important in that it is the first study in Turkey after the validity and reliability study. Corroborating the study of Baş et al. [11], the present study offers: the relationship between intuitive eating and BMI, dietary intake and dietary adequacy. METHODS This cross-sectional study was conducted with 665 university students in Gazi University between the ages of 18-25 years, who agreed to participate in the study voluntarily (September-November 2017) and live in Ankara, the capital city of Turkey (the response rate of the study was 75%). Because some of the individuals participating in the research could not be reached, participants were selected by probabilistic sampling. GPower version 3.1.9.2 (University of Düsseldorf, Düsseldorf, Germany) was used to perform calculations on sample size within an 85% confidence interval at a 0.05 significance level, and sample size calculation indicated a sample size of 615 individuals. The questionnaire form was applied to the participants using the face-to-face interview method. Verbal or written consents of individuals participating in the research were obtained by the voluntary consent form in accordance with the Helsinki declaration. This study was approved by the Research Ethics Committee of Gazi University. The questionnaire consists of general characteristics, anthropometric measures, Intuitive Eating Scale-2, and 24-h dietary recall (for 2 days, weekday and weekend) sections. In order to assess the intuitive eating score, the Turkish version of the Intuitive Eating Scale-2 (5-point Likert scale instrument with twenty-three items), developed by Baş et al. [11], was used. In this validity and reliability study, Bartlett’s test of sphericity yielded a value of X2=9043.49 (p<0.001), while the Kaiser-Meyer-Olkin index was 0.87. The IES-2 consists of four subscales: 1. Unconditional permission to eat (UPE; 6 items; e.g., “If I’m craving a certain food, I allow myself to have it”), Eating for physical reasons (EPR; 8 items; e.g., “I mostly eat foods that make my body perform efficiently (well)”), Reliance on hunger and satiety cues (RHSC; 6 items; e.g., “I rely on my hunger signals to tell me when to eat”), and Body-food choice congruence (B-FCC; 3 items) (e.g., “I mostly eat foods that give my body energy and stamina”) was used for each item, participants respond using a 5-point scale that ranges from 1 (strongly disagree) to 5 (strongly agree). To score the IES-2, negative items are reverse coded and then added to a composite score, which is then divided by the number of items to obtain a mean score. The researchers asked the participants to talk about their dietary intake over a 2-day period (weekday and weekend) using the 24-h dietary recall method. Nutrition Information Systems (Beslenme Bilgi Sistemi-BeBiS/The German Food Code and Nutrient Data Base, BLS II.3, 1999) which is a food software program in compliance with Turkish food, was used to assess energy (kcal), macronutrients, and micronutrients. For the evaluation of dietary adequacy, the Nutrient Adequacy Ratio (NAR) and Mean Adequacy Ratio (MAR), which is measured by NAR, were used. Nutrient Adequacy Ratio (NAR) NAR was calculated using the daily intake ratio of a nutrient and Dietary Reference Intake (DRI) framework categorized according to age and gender. In this study, NAR were obtained for a total of twelve nutrients (protein, fiber, vitamin B6, folate, vitamin B12, vitamin C, calcium, phosphor, potassium, magnesium, iron and zinc) [18]. NAR ( % ) = Daily intake of a nutrient x 100 DRI amount of the nutrient Mean Adequacy Ratio (MAR) MAR was obtained by ratio of the total NARs divided by the number of nutrients (for twelve nutrients). For both NAR and MAR, a value of 100% is the ideal since it means that the intake is the same as the requirement [18]. MAR ( % ) = ∑ NAR ( % ) Nummber of nutrients Participants’ weight and height measurements were taken by the researchers in accordance with the measurement techniques [19]. Body mass index is calculated as the weight (kg) divided by squared height (m2). The World Health Classification (WHO) reference values were used in the classification of BMI [20]. The obtained data were evaluated using SPSS 22.0 statistic package program (SPSS Inc., Chicago, Illinois, United States). Baseline sample characteristics, including sociodemographic data, dietary intake, NAR, MAR, total IES-2 score and its subscales, and the BMI were analyzed using descriptive statistics and are presented as means and standard deviation for continuous variables and as percentages for categorical variables. Chi-square was used to compare categorical variables. One-way Anova (with Tukey’s (HSD) – Honestly Significant Difference test – for post hoc comparison) and Student’s t-test were used for statistical analysis. To identify the correlation among the parameters, Pearson correlation analysis was used. Linear regression was used to determine the relationships of IES-2 score with gender, age, BMI, energy, and MAR. The results were evaluated within a 95% confidence interval and at p<0.01 and p<0.05 significance level. RESULTS This study was conducted with 665 university students (17.6% men; 82.4% women) whose mean age was 20.9±1.76 (between 18-25 years). The mean BMI was found for men was 23.3±2.67kg/m2 and 21.5±2.89kg/m2 for women (p<0.001). Most men (68.4%) and women (72.8%) had normal BMI. There were no significant differences between energy and macronutrient intake (carbohydrates, protein, fat) in men and women. The mean energy intake was 2235.8±1058.9kcal/day (men: 2318.3±940.6; women: 2218.2±1082.49kcal/day). Overall, the mean IES-2 score was 3.2±0.33, men’s score was 3.3±0.37, while women’s score was 3.2±0.32. Regarding gender, the total IES-2 scores and its subscale scores were found to be significantly different (p<0.05) (Table 1). The mean MAR was 83.8±14.1 (men: 83.2±13.8, women: 83.9±14, p>0.05) (Table 2). Table 1 Descriptive data of the individuals. Ankara, Turkey, 2017. Characteristics of the individuals Men (n:117) Women (n:548) Total (N:665) Mean SD Mean SD p * Mean SD Age (years) 21.3 1.68 20.8 1.77 0.012* 20.9 1.76 BMI (kg/m2) 23.3 2.67 21.5 2.89 0.000* 21.8 2.94 Energy (kcal) 2318.3 940.61 2218.2 1082.49 0.354 2235.8 1058.90 Carbohydrates (g) 270.3 114.36 252.4 111.19 0.116 255.5 111.87 Protein (g) 81.8 36.83 74.8 37.34 0.063 76.0 37.32 Fat (g) 97.8 43.66 98.3 78.70 0.941 98.2 73.72 Eating for Physical Rather than Emotional Reasons 3.3 0.49 3.1 0.51 0.001* 3.1 0.51 Unconditional Permission to Eat 3.1 0.49 3.0 0.50 0.002* 3.0 0.50 Reliance on Hunger and Satiety Cues 3.1 0.92 3.3 0.61 0.039* 3.3 0.67 Body-Food Choice Congruence 3.8 0.81 3.6 0.86 0.015* 3.6 0.86 Total IES-2 score 3.3 0.37 3.2 0.32 0.001* 3.2 0.33 BMI classification n % n % p β n % Underweight 4 3.40 81 14.80 0.000β 85 12.80 Normal 80 68.40 399 72.80 479 72.00 Overweight 32 27.40 62 11.30 94 14.10 Obese 1 0.80 6 1.10 7 1.10 Note: Independent Sample t-test p * <0.05; Chi-square: p β <0.01. BMI: Body Mass Index (kg/m2); IES-2: Intuitive Eating Scale-2; SD: Standard Deviation. Table 2 Mean and Standart Deviation values of daily nutrients intakes, NAR, and MAR score. Ankara, Turkey, 2017. Energy and Nutrients Men (n:117) Women (n:548) Total (N:665) Intake Amount NAR% Intake Amount NAR % p * Intake Amount NAR% M ± SD M ± SD M ± SD M ± SD M ± SD M ± SD Protein (g) 81.8 ± 36.8 95.2 ± 12.2 74.7 ± 37.3 91.3 ± 14.4 0.063 76.0 ± 37.3 91.9 ± 14.2 Fiber (g) 24.5 ± 12.5 60.8 ± 24.5 24.8 ± 12.8 80.2 ± 21.3 0.771 24.8 ± 12.7 76.8 ± 23.1 Vitamin B6 (mg) 1.8 ± 0.9 92.8 ± 15.6 1.7 ± 0.9 90.8 ± 15.7 0.258 1.7 ± 0.8 91.2 ± 15.7 Folate (mcg) 380.0 ± 198.1 78.0 ± 21.2 355.3 ± 179.2 75.3 ± 22.6 0.183 165.7 ± 86.7 75.7 ± 22.4 Vitamin B12 (mcg) 4.7 ± 3.1 92.8 ± 18.4 4.3 ± 3.2 89.4 ± 19.9 0.320 4.4 ± 3.2 90.0 ± 19.8 Vitamin C (mg) 120.6 ± 106.7 76.1 ± 29.2 127.1 ± 98.5 86.6 ± 23.6 0.528 125.9 ± 99.9 84.7 ± 24.9 Calcium (mg) 682.2 ± 403.1 99.8 ± 01.6 753.1 ± 422.8 99.9 ± 00.3 0.098 740.6 ± 420.0 99.9 ± 0.7 Phosphor (mg) 1311.9 ± 622.9 98.2 ± 08.0 1276.9 ± 628.2 97.6 ± 07.8 0.585 1283.1 ± 626.9 97.7 ± 7.9 Potassium (mg) 2794.1 ± 1523.1 56.3 ± 25.4 2820.0 ± 1449.9 57.3 ± 24.7 0.862 2815.1 ± 1461.9 57.2 ± 24.8 Magnesium (mg) 304.3 ± 160.9 68.1 ± 23.9 310.3 ± 158.7 80.4 ± 21.1 0.710 309.2 ± 158.9 78.2 ± 22.1 Iron (mg) 14.2 ± 7.3 96.9 ± 10.2 13.2 ± 6.3 67.2 ± 23.6 0.152 13.4 ± 6.5 72.5 ± 24.6 Zinc (mg) 11.2 ± 5.4 82.6 ± 20.1 10.5 ± 5.1 90.7 ± 14.7 0.168 10.6 ± 5.2 89.3 ± 16.1 MAR% 83.2±13.8 83.9±14.1 0.605 83.8±14.1 Note: p * Significance level of the difference between the mean values of intake amounts of groups. M: Mean; SD: Standard Deviation; NAR: Nutrient Adequacy Ratio; MAR: Mean Adequacy Ratio. There was no relationship between the IES-2 score and its subscales and daily total energy, macronutrient intake and MAR (p>0.05) (data not shown). Negative correlations were found between the IES-2 score, Unconditional Permission to Eat score and BMI for women (r=-0.095, p=0.026; r=-0.108, p=0.011, respectively). Body-Food Choice Congruence score was negatively associated with BMI in both women and in total (p<0.05). There was a negative relationship between MAR and BMI for both genders, but these were not statistically significant (Table 3). Table 3 Correlation of BMI with dietary intake, MAR and IES-2. Ankara, Turkey, 2017. Dietary intake Men (n=117) Women (n=548) Total (N=665) r p r p r p Energy (kcal) -0.098 0.294 -0.082 0.056 -0.073 0.061 Carbohydrate (g) -0.142 0.128 -0.083 0.053 -0.075 0.054 Protein (g) -0.102 0.273 -0.070 0.104 -0.055 0.157 Fat (g) -0.029 0.755 -0.057 0.185 -0.052 0.177 MAR -0.105 0.261 -0.049 0.254 -0.061 0.117 Eating for Physical Rather than Emotional Reasons -0.035 0.705 -0.061 0.154 -0.023 0.547 Unconditional Permission to Eat -0.062 0.508 -0.108 0.011* -0.046 0.236 Reliance on Hunger and Satiety Cues -0.071 0.449 -0.066 0.124 -0.044 0.257 Body-Food Choice Congruence -0.021 0.819 -0.152 0.000* -0.098 0.012* Total IES-2 score -0.064 0.491 -0.095 0.026* -0.032 0.406 Note: Pearson Correlation p<0.05. IES-2: Intuitive Eating Scale-2; BMI: Body Mass Index; MAR: Mean Adequacy Ratio. The difference between the mean scores of the IES-2 scores and its subscales according to the BMI classification was found to be significant only for the Body-Food Choice Congruence score (p=0.026). This score was significantly higher in underweight individuals than in normal individuals (3.9±0.82; 3.6±0.84, respectively; p=0.15) (data not shown). When factors that could affect the IES-2 score (age, gender, energy, MAR, and BMI) were evaluated using linear regression analysis, models were deemed important (R2:0.030) p<0.01). Although, BMI and energy were not significantly related to the IES-2 score (p>0.05), age, gender and MAR had an effect in the model for the score (p<0.05) (Table 4). Table 4 Total IES-2 score linear regression analysis. Ankara, Turkey, 2017. Model Beta t p Total IES-2 score Age (year) -0.078 -2.017 0.044 Gender -0.135 -3.397 0.001 BMI (kg/m2) -0.064 -1.618 0.106 Energy (kcal/day) -0.061 -1.222 0.222 MAR% -0.098 -1.969 0.049 Note: R2=0.030; p=0.001. BMI: Body Mass Index (kg/m2); MAR: Mean Adequacy Ratio. DISCUSSION The results of this study showed that the intuitive eating score varied according to gender. The total IES-2 score and its subscales (except for Reliance on Hunger and Satiety Cues score) for women were significantly lower. Similarly, Tylka et al. [12] reported that men scored significantly higher in the IES-2 when compared to women. In one study, adolescent sex differences for intuitive eating has been examined, reporting that girls were more likely than boys to manage their emotions through eating [21]. In another study of college undergraduates, women scored lower on Eating for Physical Reasons; they were also less attuned to their bodies' signals about hunger and fullness than men [10]. However, this study shows that women remain more attuned to their bodies regarding hunger and fullness than men. This can be explained by the fact that girls learn at a young age to associate eating with relief from negative emotions, which may be caused by the pressures they experience from parents regarding what, when, and how much to consume [22], On the other hand, in some studies, gender was not related to the intuitive eating score [23-25]. Although this study was conducted on undergraduates, age was found to be an important factor for intuitive eating. In a study, participants over the age of 22 tended to score higher on intuitive eating; on the other hand, it has been stated that demographic factors such as age and year in college were less clearly associated with intuitive eating values [26]. This result shows that age has a positive effect on intuitive eating. However, this relationship should also be assessed among older age. It is known that intuitive eating covers the concept of "body wisdom" (the body will instinctively maintain the variety of food needed to sustain health) [4]. Intuitive eaters can be expected to have more nutritious eating habits and more positive eating habits than non-intuitive eaters. Some studies have found that intuitive eating develops positive dietary intake/eating habits [16,27], but it has been determined that there is no effect in another study whose sample size is low and homogeneous [28]. From this point of view, in the present study, intuitive eating was associated with dietary adequacy. Participants with a high IES-2 score have higher dietary adequacy. Intuitive eating has been proposed as a healthier, more effective, and more innate alternative to current weight management strategies. Substantial and consistent associations between intuitive eating and lower BMI have been reported [4,29]. In the present study, it was determined that BMI was inversely related to Body-Food Choice Congruence score. The scores of underweight individuals were significantly higher. These results show that healthy eating habits may be more common in underweight individuals. Furthermore, according to gender, there was a negative relation between the BMI and IES-2 score, specifically Unconditional Permission to Eat and Body-Food Choice Congruence scores in women. On the other hand, there was no significant relationship between BMI and IES-2 score in men unlike the other study conducted by Denny et al. [24]. This can be explained by the low number of men in that study (17.6%). Young people who are becoming aware of their bodies and being influenced by external messages (e.g., parental pressure about food) may be particularly vulnerable to the effects of dieting on intuitive eating, particularly women. These results support the idea that a low IES-2 score in women may negatively affect weight control. CONCLUSION In conclusion, age, gender and dietary adequacy have been shown to be an important factor for determining intuitive eating. Moreover, the results of this study indicate an inverse correlation of intuitive eating with the BMI in women. This study shows that intuitive eating has a positive relationship with dietary adequacy. Thus, obesity prevention and treatment strategies have mainly focused on counteracting detrimental dietary behaviors. Considering adaptive behaviors, such as intuitive eating, could be useful for developing behavioral guidelines insisting on incentives rather than restrictions, particularly regarding gender, as the results of this study have shown. Factors affecting intuitive eating need to be investigated in longitudinal studies in future studies. CONTRIBUTORS S BILICI designed the study and wrote the protocol. B KOCAADAM and H MORTAS conducted literature research and provided summaries of previous research studies. E KOKSAL and Ö KUCUKERDONMEZ conducted the statistical analysis and revised the manuscript. All authors contributed to and have approved the final manuscript. ACKNOWLEDGEMENTS The authors thank the participants for their support with the data collection. The authors alone are responsible for the content and writing of the article. Como citar este artigo/How to cite this article Bilici S, Kocaadam B, Mortas H, Kucukerdonmez O, Koksal E. Intuitive eating in youth: Its relationship with nutritional status. Rev Nutr. 2018;31(6):557-65. http://dx.doi.org/10.1590/1678-98652018000600005 REFERENCES 1 1 Karaoglan D, Tansel A. Determinants of obesity in Turkey: A quantile regression analysis from a developing country. 2017 [cited 2017 Sept 15]. Available from: https://ssrn.com/abstract=2900125 Karaoglan D Tansel A. Determinants of obesity in Turkey: A quantile regression analysis from a developing country 2017 2017 Sept 15 Available from: https://ssrn.com/abstract=2900125 2 2 Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. 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