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Satiety and healthy eating habits

Satiety and healthy eating habits

Springer Nature Food allergy labeling neutral with regard habkts jurisdictional claims in published maps Satiety and healthy eating habits institutional hanits. Pros and cons Can healthh use food and qnd as medicine? My podcast changed me Eatig 'biological race' explain disparities in health? Benefits of Intuitive Eating Intuitive eating h elps establish a mind-body connection to recognize and respond to hunger and to know when to stop eating. Dairy and weight loss hypothesis: an evaluation of the clinical trials. In general, does [name of the child]… 2 …refuse to eat the right food? Lanou AJ, Barnard ND.

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Satiety and healthy eating habits -

It also may identify situations when you feel hunger, but you cannot respond to it or only respond in a limited way. Here is more on intuitive eating from University Hospitals Clinical Nutrition Services. Intuitive eating h elps establish a mind-body connection to recognize and respond to hunger and to know when to stop eating.

It also reduces the likelihood that under-eating and over-eating occur due to increased awareness of physical and mental signs and symptoms. Intuitive eating starts with identifying early signs of hunger, which may occur four to five hours after eating a balanced meal.

Early signs of hunger may include:. When you feel early signs of hunger , you are more likely to achieve satiety when you eat a meal. Satiety may take some time at meals, so it is important to eat slowly and enjoy your food.

It may take 20 minutes for your mind to feel better after you start to eat, so chew your food thoroughly and drink water during the meal. You also can feel satiety more readily felt when you eat a balanced meal, so make sure meals are complete with protein, vegetable, grains or starch, and other nutritious foods.

Here are the signs of satiety:. Many people think of feeling full to describe the end of the meal, but this is different than satiety. The primary differences between fullness and satiety are the physical and mental components of each. Fullness is the physical signal your body sends when your stomach is physically full of food and reaching capacity.

Satiety is a feeling of contentment and overall nourishment that creates a sense of relief and gives you the ability to stop thinking about food and move on with your day.

To leave a meal without overeating or obsessing over the next, meals need to made up of foods that will satiate your stomach and your mind. With intuitive eating, leaving meals feeling satiated is the primary goal.

Strive to not allow yourself to get too hungry. Metrics details. Eating behaviors may contribute to differences in body weight and diet over time. Our study aims to examine how eating behaviors of young adults relate to their current weight status and dietary patterns and to explore longitudinal associations with eating behaviors in early childhood.

At age 22, eating behaviors were assessed using the Adult Eating Behavior Questionnaire. Dietary patterns were derived from information collected by food frequency questions. Weight status was based on self-reported data.

Information on eating behaviors in childhood had been collected when participants were 2. Simple and multivariate linear regression analyses were used to examine associations between eating behaviors and dietary patterns at age 22, and longitudinal associations with behaviors in early childhood.

Ordinal logistic regression analyses were used to assess associations between overeating and fussy eating in childhood and weight status at age Body mass index was positively correlated with Emotional overeating, Enjoyment of food, and Food responsiveness and negatively correlated with Satiety responsiveness, Emotional undereating, Slowness in eating and Hunger.

A Healthy dietary pattern was positively associated with both Enjoyment of food and Hunger, and negatively associated with Food fussiness. Inversely, a Beverage-rich dietary pattern was negatively associated with Enjoyment of food and positively associated with Food fussiness.

A Protein-rich pattern was positively associated with Enjoyment of food, while a High energy density pattern was positively associated with Food fussiness. Young adults with higher scores for fussy eating in early childhood were more likely to manifest Food fussiness and Emotional undereating, and less likely to adopt a Healthy dietary pattern.

Young adults with higher scores for overeating in early childhood were less likely to show traits such as Slowness in eating and more likely to be overweight.

Our findings suggest that eating behaviors in childhood have long-term influence on diet and weight status, thereby reinforcing the importance of early interventions that promote healthy eating.

Diet is recognized as one of the key modifiable factors for obesity prevention [ 1 ]. In developed countries such as Canada, many young people now reach adulthood overweight or obese [ 2 ], a condition that puts them at higher risk for premature death from chronic disease [ 3 , 4 ].

This developmental stage requires that they learn how to choose, buy, and prepare food and meals daily, activities that can pose dietary and nutritional challenges [ 5 , 6 ]. When compared to childhood and adolescence, health-enhancing behaviors e. This oversight is critical because emerging adulthood offers opportunities for interventions targeting excess weight and, more broadly, for obesity prevention [ 5 , 6 ].

Indeed, as young adults construct their personal, familial, and social identities, they typically become more receptive than older adults to adopting lifelong, healthy lifestyles [ 5 ]. Designing evidence-based preventive interventions among young adults would benefit from a keen understanding of eating behaviors that contribute to body weight and dietary habits over time.

To some extent, these eating behaviors reflect family attitudes and customs, as well as tastes and preferences developed earlier in life [ 8 , 9 ]. They may also be influenced by genetic factors underpinning food intake regulation and taste predispositions [ 10 , 11 ].

Previous research by our team indicated that preschool-aged children who were perceived as fussy by their mothers tended to under-consume certain types of food, such as fruit, vegetables, and meat and alternatives [ 16 ].

Young children perceived as eating too much or too fast had higher energy intake and higher BMI [ 15 ]. Such eating behaviors tend to persist throughout childhood [ 17 , 18 ], although evidence for continued persistence into adulthood remains limited [ 9 , 19 ].

Identifying how past and current eating behaviors relates to diet and weight status among young adults would deepen our understanding of the behavioral aspects of diet. Accordingly, the first objective of this study was to examine the extent to which eating behaviors of young adults relate to their current weight status and dietary patterns.

A secondary objective was to document the predictive associations between eating behaviors in early childhood, as reported by parents, and both eating habits i.

Study participants were young adults taking part in the ongoing Quebec Longitudinal Study of Child Development QLSCD. Under the direction of the Institut de la Statistique du Québec ISQ [ 20 ], the QLSCD is a birth cohort study that was initiated in the late s.

The children of this cohort constituted a representative sample of more than 75, singleton births in Quebec that year. Details about the QLSCD are available elsewhere [ 21 ]. Twenty-two years later, participants agreed to take part in a dietary study in which information on food consumption, eating behaviors, anthropometric data, and sociodemographic factors was collected using an online self-administered questionnaire.

Data collection took place in the spring of from March through June inclusively. Eating behaviors at age 22 were assessed using the Adult Eating Behavior Questionnaire AEBQ [ 22 ]. The AEBQ, recently developed and based on the well-known Child Eating Behavior Questionnaire CEBQ [ 23 ], assesses a broad array of eating traits related to appetite and food acceptance.

More specifically, this questionnaire includes 35 items measuring 8 eating traits. These refer to four food approach scales Hunger [5 items], Food responsiveness [4 items], Emotional overeating [5 items], Enjoyment of food [3 items] and four food avoidance scales Satiety responsiveness [4 items], Emotional undereating [5 items], Food fussiness [5 items], Slowness in eating [4 items] [ 22 ].

The AEBQ has been translated into several languages, including French, and was found to be a valid and reliable instrument for assessing eating traits in different adult populations [ 22 , 24 , 25 , 26 , 27 , 28 ].

In published validation studies, various factor structures of the AEBQ have been compared. Although some studies have suggested that a 7-factor structure excluding the Hunger scale might be appropriate [ 25 , 26 , 28 ], the validation study conducted in Quebec supported the original 8-factor structure of the questionnaire [ 24 ], which was used in the present study.

For each item, a score from 1 to 5 was derived from responses on a 5-point Likert scale Strongly disagree, Disagree, Neither agree nor disagree, Agree, Strongly agree.

For each participant, the scores of all items related to a given trait were summed and then divided by the number of items for that trait in order to obtain a mean score for each of the 8 eating traits.

In earlier rounds of the QLSCD study, specific eating behaviors have been documented at five points in time i. Questions were based on those used in the Avon Longitudinal Study of Parents and Children [ 29 ], then translated and slightly adjusted to reflect the context of the QLSCD.

In general, does [name of the child]… 2 …refuse to eat the right food? For each participant, at each data collection point between age 2. It is worth mentioning that all participants had data available at least once over the five data collection rounds.

Participants were asked to think about a typical week or 7-day period, before the COVID-period that was just beginning at the time and to indicate if they were consuming each food item listed. If so, they were asked to indicate how often whether by day or by week and in what quantities based on three common portion sizes.

Answers specifying frequencies per week were converted into frequencies per day to yield a common frequency unit. For smaller, average and larger suggested portions sizes specific to each food item , we assigned factors of 0. Relative quantities of the 60 food items consumed were determined by multiplying frequency per day by portion size factor.

Relative quantities of each food group were determined by calculating the sum of relative quantities of individual food items included in a given group. Correction equations, based on Canadian data for adult men and women of various age groups, were applied to adjust self-reported data in order to improve accuracy relative to measured data [ 30 ].

Because two participants had missing data for BMI, analyses that included BMI refer to participants. Sex of the participant, maternal education, and family income had already been collected in earlier rounds of the QLSCD study and were used as covariates in longitudinal analyses.

As part of the dietary study at age 22, participants were questioned about their usual living situation e. We used exploratory factor analysis to derive dietary patterns that summarize how various food groups combine to characterize various types of food consumption in our sample. Since consumption of individual food groups did not follow a normal distribution, the principal axis method of estimation, which does not require distribution assumptions, was used.

Parallel analysis scree plots suggested the optimal number of factors to be 4. This analysis confirmed that a 4-factor solution best described eating patterns in our sample.

Factor loading estimation for the 4 groups was performed using principal axis factoring with Oblimin rotation to identify the model that best explained the interrelationships among these food groups.

Model fit was satisfactory with a TLI of 0. Using other factor loading estimation methods minimum residuals, ordinary least squares, unweighted least squares did not affect individual factor loadings and fit measures.

Descriptive statistics included frequency and mean SD. Comparisons of AEBQ mean scores, by sex and weight status categories, were performed using one-way ANOVA. For Enjoyment of food and Food fussiness, we used Spearman correlations and the Kruskal-Wallis Rank Sum Test because these variables were not normally distributed.

Tukey multiple comparisons of means were used for factory variables having more than 2 categories when differences were observed. Simple linear regressions analyses were used to test whether eating behavior traits measured by the AEBQ were associated with dietary patterns.

As part of a longitudinal analysis, we used linear regressions to explore bivariate associations between eating behaviors in childhood mean scores for overeating and fussy eating and eating habits i. We also assessed whether eating behaviors in childhood were predictors of weight status at age We tested both crude and adjusted for sex, maternal education, and family income models.

We performed all analyses by using RStudio [ 31 ] with R Statistical Software [ 32 ] version 4. Significance level was set at 0. Bivariate correlations between AEBQ scales are shown in Table 2.

Positive correlations were noted among all food approach scales from r 0. Food avoidance scales also showed positive correlations with one another from r 0. Hunger was one exception, given that this trait showed positive correlations with food avoidance scales from r 0.

Table 2 also presents results of bivariate correlation analyses between BMI and each eating trait. Overall, BMI was positively correlated with three food approach scales Emotional overeating [ r 0. For all appetitive traits but one Food fussiness, which does not differ according to sex , the mean score is higher for women than for men.

Differences according to weight status were also noted, namely for two food approach scales and three food avoidance scales. Exploratory factor analysis suggested four dietary patterns that we identified as Healthy, Beverage-rich, Protein-rich, and High energy density Table 4.

Results of bivariate correlations between appetitive traits and consumption of specific food groups are presented as Supplementary material.

See Supplementary Table 2 for correlations with food approach scales and Supplementary Table 3 for correlations with food avoidance scales. Table 5 presents statistically significant associations between AEBQ scales and dietary patterns in emerging adulthood, based on findings from simple regression analyses presented in Supplementary Table 4.

Both the Protein-rich and the High energy density patterns were found to be negatively associated with Satiety responsiveness in unadjusted models, but these associations disappeared in adjusted models. Although overeating in childhood was found to be positively associated with Satiety responsiveness and with the Beverage-rich pattern in crude models, these predictive associations disappeared in adjusted models.

We detected four significant sex interactions see Supplementary Table 7. Our findings indicate that among young adults, eating traits such as Emotional overeating, Enjoyment of food, and Food responsiveness were positively associated with BMI.

Inversely, traits such as Hunger, Emotional undereating, Satiety responsiveness, and Slowness in eating were negatively associated with BMI.

Food fussiness, Enjoyment of food, and Hunger were associated with certain dietary patterns after adjusting for various potentially confounding factors. Over time, we noted that young adults with higher scores for fussy eating in early childhood were more likely to manifest Food fussiness and Emotional undereating, and less likely to adopt a Healthy dietary pattern.

Overall, the results relative to AEBQ and body weight are consistent with previous studies [ 22 , 24 , 25 , 26 ], suggesting a general tendency toward higher mean scores in food approach scales and lower mean scores in food avoidance scales as BMI increases [ 22 , 25 , 26 ] or in higher compared to lower weight status categories [ 24 ].

Hunger, which was inversely associated with BMI, and Food Fussiness, which was not associated with BMI or weight status, were two exceptions that had previously been reported in various AEBQ validation studies [ 22 , 25 ]. Food fussiness was related only to dietary patterns. To our knowledge, this is the first study linking AEBQ appetitive traits and food consumption.

Some experts have suggested that Food fussiness could reflect tastes and preferences more than appetite [ 24 , 25 ]. Accordingly in the present study, Food fussiness was associated with dietary patterns that gave more prominence to beverages and high-energy foods, including SSB, processed meats, fried foods, cheese, and alcohol.

Moreover, Food fussiness was also associated with lower consumption of healthy foods, such as vegetables and fruit, whole-grain products, legumes, nuts, and seeds. The few studies on food fussiness and picky eating among adults appear to be in line with our findings, suggesting a tendency toward lower-quality diets among selective eaters also known as fussy or picky eaters [ 19 ], particularly when lower consumption levels of vegetables and fruit, and less diversity in food choices, are considered [ 33 , 34 ].

Our results also suggest that processed foods high in sugar, salt, or fat or any combination of those hold more appeal for those who have greater sensitivity to particular flavors. In the present study, unlike Food fussiness, Enjoyment of food was associated with higher-quality diets.

Thus, those who show more pronounced interests in food and enjoy eating may appreciate a variety of nutrient-dense foods. Interestingly, a study of cultural differences in food perceptions in France versus the United States indicates that Americans tend to associate unhealthy food with tastiness and gustatory pleasure, whereas in France healthy food is perceived as tastier and more gratifying [ 35 ].

This cultural difference may, in part, explain our findings. Our mainly French-speaking North American population maintains strong cultural connections with other francophone cultures. This suggests that, beyond their interest in the quality of food, individuals who enjoy eating may also have, overall, higher energy intakes relative to energy requirements.

It is worth mentioning that differences in Enjoyment of food relative to weight status did not apply to the obese category. Thus, beyond a certain point, excess weight and its potential consequences for health and psychosocial issues may instead be associated with restrictions in dietary intakes i.

Hunger was another trait positively associated with a healthy dietary pattern, but only in relation to consumption of legumes, nuts, and seeds. When vegetarianism was considered in the equation from information collected in the dietary study , the association between Hunger and Healthy dietary pattern vanished.

It may be that Hunger is specifically related to characteristics of vegetarian diets where legumes, nuts, and seeds represent a major source of protein , and not to healthy eating in general.

Hunger was also positively correlated with sweets snacks and desserts, suggesting that there might be a propensity to rely on sources of free sugars in response to feelings of hunger. Overall, the inverse relationship between Hunger and BMI may indicate that higher scores on the Hunger scale reflect lower energy intakes associated with greater awareness of internal hunger signals.

Interestingly, our results show a positive correlation between Hunger and Satiety responsiveness. We also found a negative correlation between Satiety responsiveness and BMI. The other appetitive traits measured in our study were related to weight status, but not to any specific dietary pattern, suggesting that these traits contribute more to quantities of food ingested total energy intake than to types quality of food consumed.

These traits include Emotional overeating and undereating, Food responsiveness, Satiety responsiveness, and Slowness in eating. Indeed, a tendency to overeat or to eat rapidly, a high responsiveness to food cues, or a lack of attention to satiety signals may all lead to excess energy intakes relative to energy needs , and ultimately to excess weight [ 37 ].

Findings of our longitudinal analyses suggest that eating behaviors related to regulation of appetite or food acceptance in the younger years tend to emerge early in life and may persist until adulthood. The authors of the study concluded that several eating traits may be as stable over time as personality traits are.

Until now, healthy satiety was the essential component missing in all diet plans. Although satiety is often confused with fullness, there are important differences between the two phenomena.

Everyone is familiar with the feeling of stomach fullness that is experienced after eating a meal. Fullness is associated with a satisfied feeling in the stomach or, if you overeat, an uncomfortable feeling. The feeling of fullness stimulates a signal to the brain that tells us to stop eating.

Satiety is the feeling of satisfaction, or not being hungry, that lasts long after that initial feeling of fullness has subsided. Satiety is the sensation that keeps us from snacking between meals.

The feeling of satiety involves a number of natural physiological actions that start in the stomach and ultimately affect the appetite center in the brain. The presence of food in the stomach stimulates the release of special proteins in the digestive tract. First they close the valve leading from the stomach into the intestine.

This slows the digestion of food, giving us a feeling of fullness and extinguishing the drive to eat. The second action initiated by the feel-full proteins is to send a signal to the appetite center in the brain.

This also tells us to stop eating, but, more importantly, it is responsible for the extended feeling of fullness that occurs between meals. Not all nutrients produce the same degree of satiety.

Certain types of fat are the most effective, specific types of proteins are second, and carbohydrate has the least effect. Healthy satiety is the selective ingestion of those nutrients, either before a meal or with a meal that will maximize the overall satisfaction you get from the meal.

The initial research on the biology of satiety was conducted at Columbia and Cornell Universities almost 40 years ago.

Additional studies have shown how CCK is released and how it works. Although many large drug companies have intense research efforts to develop drugs that stimulate the feel-full proteins, some of the latest research shows that consuming the right types of nutrients at the right time is also effective.

These discoveries open up enormous possibilities in terms of helping people lose weight and maintain a healthy weight.

International Journal hahits Behavioral Nutrition and Physical Eatign volume 19Article number: Brown rice for toddlers this hqbits. Metrics details. Metabolic rate and overall well-being behaviors may Satiett to Strong Orange Flavor in body weight and diet over time. Our study aims to examine how eating behaviors of young adults relate to their current weight status and dietary patterns and to explore longitudinal associations with eating behaviors in early childhood. At age 22, eating behaviors were assessed using the Adult Eating Behavior Questionnaire. Dietary patterns were derived from information collected by food frequency questions. Satiety and healthy eating habits

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