| Literature DB >> 35457352 |
Fabiana Lopes Nalon de Queiroz1, António Raposo2, Heesup Han3, Martín Nader4, Antonio Ariza-Montes5, Renata Puppin Zandonadi1.
Abstract
Eating Competence (EC) is one behavioral perspective of eating practices that has been associated with a healthy lifestyle. It emphasizes eating pleasure, self-regulation of eating, body weight satisfaction, and regular meal frequency that includes food variety without focusing on dietary guidelines. EC is composed of four components (Eating Attitude, Food Acceptance, Internal Regulation, and Contextual Skill), and its assessment is performed using the Eating Competence Satter Inventory (ecSI2.0™), developed and validated in English for an adult population. EC has been associated with diet quality and health indicators for various population groups and the development of skills that increase EC might be a strategy to improve nutritional health, and prevent obesity and other chronic diseases. In this sense, this study presents an overview of the background, concepts, features, and possible associations among EC, food consumption, and health outcomes. The high prevalence of diseases associated with food/nutrition draws attention to the necessity to broaden the view on food and its relationship with health and well-being, considering not only nutrients and food combinations but also the behavioral dimensions of eating practices. Healthy nutritional recommendations that take into account attitudes and behaviors are in accordance with the EC behavioral model. Studies on eating behavior emphasize the need to better understand attitudes towards food and eating in the general population using validated instruments. In this context, measuring EC and its association with health outcomes seems to be relevant to nutritional health. The complexity of food choices has been examined in social, behavioral, and biological sciences, representing a great challenge for applying unique and simple theoretical models. Multiple methods are required, as no single theory can fully explain food selection.Entities:
Keywords: eating behavior; eating competence; health; nutrition
Mesh:
Year: 2022 PMID: 35457352 PMCID: PMC9027558 DOI: 10.3390/ijerph19084484
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Figure 1The four components of Eating Competence.
Characterization of the studies that evaluated eating competence (EC) using the Ellyn Satter inventory (ecSI) in different populations.
| Author/Year/Country | Number and Characterization of Participants | Study Objective | Main Findings |
|---|---|---|---|
| Lohse et al., 2007 [ | 832 (78.7% female; mean age 36.2 ± 13.4 years) | Examine ecSI psychometric properties and assess its validity to measure EC. | The ecSI is a valid tool to measure EC. Individuals with higher ecSI scores had better diet quality. Persons unsatisfied with weight had lower EC and showed higher feelings of cognitive restraint, disinhibition, hunger, weight management, and psychosocial characteristics related to disordered eating. |
| Stotts and Lohse, 2007 [ | 259 white females (food secure, with some college education; 26.9 ± 10.4 years) | Evaluate the ecSI reliability to measure EC. | The ecSI may be used to evaluate nutrition education designed to improve eating competence; however, some ecSI items may require revision. |
| Psota et al., 2007 [ | 48 (19 male and 29 female; 21–70 years old; LDL ≥ 110 mg/dL) | Explore the relationship between EC and the risk for cardiovascular disease. | Individuals with higher EC had lower cardiovascular risk. EC was positively correlated with HDL-cholesterol and inversely associated with blood pressure. Non-competent eaters showed higher cardiovascular risk. |
| Stotts Krall and Lohse, 2009 [ | 70 low-income adults in Pennsylvania (78.6% females; 31.7 ± 9.6 years) | Evaluate the congruence of the ecSatter model with the cognitive eating behaviors of a low-income audience. | EC was low for this low-income sample (mean 28.8 ± 8.3). |
| Stotts Krall and Lohse, 2010 [ | 25 low-income females (18–49 years old) | Examine the validity of EC self-report measures with low-income women. | Results provided a rationale for modifying the ecSI * and the development of the ecSI/LI for better use among low-income women. |
| Lohse et al., 2010 [ | 638 elderly (62% women, ±67 years), at cardiovascular risk, recruited into the Spanish Trial PREDIMED. | Assess cross-sectional associations of EC with cardiovascular risk biomarkers and explore its relationships with the Mediterranean food pattern. | Individuals with higher EC ingested more fruit and fish, consumed fewer dairy products, and consistently adhered to the Mediterranean diet. |
| Clifford et al., 2010 [ | 1720 college students (67.9% female; 23.79 ± 7.8 years) | Determine whether BMI or attitudes about body weight were most predictive of EC in college students. | Students who were eating competent were more satisfied with their body weight, less likely to report the desire to lose weight, and had lower BMIs than students who were not eating competent. |
| Krall and Lohse, 2011 [ | 507 low-income females (18 to 45 years) | Evaluate the construct validity of a version of the ecSI, as adapted for use in a low-income population. | Food acceptance, FV intake, food management, and self-reported physical activity were positively related to ecSI/LI scores. |
| Lohse et al., 2012 [ | 149 women (56% white, 64% food secure, 86% 18–50 y) | Determine if EC is associated with dietary intake and diet patterns among low-income women. | Competent eaters (EC ≥ 32) showed better diet quality. The healthful dietary pattern showed a positive relationship with EC. The pattern characterized by foods higher in fat, salt, and sugar, was inversely related to EC. |
| Lohse and Cunningham-Sabo, 2012 [ | 339 Parents (37.2 ± 7.7 years; 78% Hispanic; 89% female) of 4th graders. | Determine if EC was a moderator of parents FV-related eating behaviors that mediate healthful eating in 4th-grade children. | Eating-competent parents demonstrated more modeling behaviors related to food preparation and fruits/vegetables; greater self-efficacy/outcome expectancies and greater in-home fruit/vegetable availability. |
| Lohse et al., 2013 [ | 512 low-income women (30.7 ± 7.5 years) | Compare EC between women who perceive being physically active with those who do not, and examine their responses to an online physical activity program. | EC was higher for physically active women. The perception of being physically active was higher in eating competent low-income women. |
| Brown et al., 2013 [ | 557 students (67.6% females; 343 ages 18–20 years; 180 ages 21–26 years) | Describe EC in students enrolled in an introductory nutrition course. | A total of 47.4% were classified as eating competent. Mean EC scores were higher for males than females and for students who never had an eating disorder. |
| Tylka et al., 2013 [ | 180 mothers of 2- to 5-year-old children | Identify the adaptive maternal eating behaviors that contribute incrementally to their child feeding practices. | Mothers who had greater EC and engaged in intuitive eating reported better feeding practices. Interventions to develop EC and skills to eat intuitively may favor positive feeding environments for children. |
| Quick et al., 2014 [ | 1252 college students (59% female; 18–24 years; 80% white) | Examine the relationships between sleep, eating, and exercise behaviors; work time pressures; and weight of young adults. | Lower EC was significantly associated with overweight/obesity. |
| Lohse et al., 2015 [ | 288 low-income women (30.7 ± 7.8 years) | Produce and evaluate an online program for low-income women following the ecSatter model. | ecSI2.0 demonstrated good internal consistency. Only 39% of the sample was categorized as competent eaters. |
| Lohse, 2015 [ | 127 parents (35.8 ± 5.3 years) of preschool-age children; 75.5% not considered low-income. | Determine if the ecSI/LI could be applied to a general audience. | Eating competence can be accurately measured with the ecSI2.0 (formerly called the ecSI/LI), regardless of income. |
| Quick et al., 2015 [ | 1035 college students (61% female; 18–24 years) | To explore the associations of EC with sleep behavior and quality. | Competent eaters (EC ≥ 32) are more likely to have better overall sleep quality and fewer sleep-related problems. |
| Tilles-Tirkkonen et al., 2015 [ | 976 Finnish adolescents (10–17 years old) | Explore a Finnish translation of the ecSI2.0 for evaluating EC and its association with food selection, meal patterns, and related psychobehavioral factors. | EC was associated with diet quality and more health-promoting family eating patterns. Competent eaters more often perceived their body size as appropriate and had less often tried to lose weight. |
| Quick et al., 2016 [ | 1252 college students (59% female; 18–24 years old) | To describe sleep behaviors and examine associations of sleep duration with eating and physical activity. | Those who slept < 8 h/night had significantly more negative eating attitudes, poorer internal regulation of food, and greater binge eating scores. |
| Lohse et al., 2018 [ | 101 women (premenopausal, mostly college-educated, body mass index >25) | To examine changes in EC in a 12-month weight-loss intervention. | Weight loss interventions that introduce concerns about eating attitudes, behaviors, and foods can reduce EC. Extending the measurement range is more appropriate as it allows sufficient time for the individual to acquire self-efficacy, better reflecting the intervention’s impact on EC. |
| Godleski et al., 2019 [ | 2010 from demographically heterogeneous samples | Examine the structural validity of the ecSI 2.0. | Findings supported retaining all 16 items and migration of 1 item from the Internal Regulation to Eating Attitudes subscales. The psychometric integrity of the 16-item ecSI 2.0 was affirmed. |
| Tilles-Tirkkonen et al., 2020 [ | 3147 Finnish adults (18–74 years) at an increased risk for type 2 diabetes, participated in the StopDia study. | Investigate whether EC is associated with diet or risk factors and the prevalence of type 2 diabetes in individuals with type 2 diabetes risk. | EC was associated with diet quality and lower prevalence of previously undiagnosed type 2 diabetes, abdominal obesity, metabolic syndrome, hypertriglyceridemia, and better insulin sensitivity. |
| Queiroz et al., 2020 [ | 662 Brazilian adults (74.9% female, 40.33 ± 12.55 years, high schooling and income) | Translate and validate the ecSI2.0 from English to Brazilian-Portuguese. | The ecSI2.0BR is a useful tool designed to measure EC in the Brazilian population, showing good reproducibility and internal consistency. |
| Queiroz et al., 2020 [ | 1810 Brazilian adults (75% females, mostly up to 40 years old, with a high education level and income) | Associate EC with food consumption and health outcomes in the Brazilian adult population. | EC was inversely associated with BMI. EC did not differ among males and females, and respondents up to 40 years old presented a lower total score. |
| Queiroz et al., 2021 [ | 302 Brazilian adults (76.82% females) | Compare EC among Brazilian adults before and during the coronavirus pandemic. | EC total score lowered during the pandemic and the decrease was worst among individuals who reported weight gain, decreased FV consumption, and an increase in sugar consumption. |
| Aittola et al., 2021 [ | 2291 adults at increased risk of type 2 diabetes. | Investigate the associations of changes in EC with changes in lifestyle, anthropometrics and biomarkers of glucose and lipid metabolism. | EC was associated with an increase in diet quality, high-density lipoprotein cholesterol, and with decreased BMI and waist circumference. EC could be a potential target in lifestyle interventions to improve the cardiometabolic health of people at type 2 diabetes risk. |
* ecSI: eating competence Satter Inventory; ** EC: eating competence; ecSI/LI: eating competence Satter Inventory for Low Income audience; ecSI2.0: the new version of eating competence Satter Inventory; ecSI2.0/BR: the Brazilian version of the eating competence Satter Inventory; FV: fruits and vegetable; and BMI: Body Mass Index.