The Choose Myplate Supertracker Educational Tool Has Been Designed To

Nutritional Considerations for the Pediatric Dental Patient

Laura M. Romito , James L. McDonaldJr., in McDonald and Avery's Dentistry for the Child and Adolescent (Tenth Edition), 2016

Myplate Food Guidance System

The MyPlate Food Guidance System is a pictorial representation of the USDA's daily food recommendations. Released in 2012, MyPlate replaced the nation's previously well-known nutrition education tool, MyPyramid (2005). In MyPlate, the five food groups are visually represented by a place setting in which each of the food groups (fruits, vegetables, proteins, dairy, and grains) is depicted proportionally according to the current recommendations. In addition, the website ChooseMyPlate.gov offers numerous educational resources and practical guidance for consumers, educators, and health professionals in building a healthful diet. For example, one can develop an individualized nutrition plan based on personal factors such as age, gender, and physical activity by utilizing the online tools, such as SuperTracker, and the Daily Food Plan and Worksheets ⁶ (http://choosemyplate.gov). The site offers several food plans for special populations, such as vegetarians, moms, and preschoolers. The SuperTracker tool can help plan, analyze, and track one's diet, weight, and physical activity; it can also be further personalized by using the goal setting, virtual coaching, and journaling features. Health and nutrition information for children over the age of 5 years is also provided on the site and includes activities, coloring pages, and interactive games as well as tips for caregivers concerning children's nutrition and meal planning (Fig. 8-1).

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Obesity therapy

Jahangir Moini , ... Mohtashem Samsam , in Global Health Complications of Obesity, 2020

Low-fat diets

The Dietary Guidelines for Americans and the MyPlate program provide examples of low-fat diets. Eating a diet that consists of 20%–35% fats helps manage weight, promote health, and reduce risks of chronic disease. Foods to reduce include saturated and trans fats, cholesterol, sodium, added sugar, refined grains, and alcohol. Foods to increase include fruits, vegetables, whole grains, low-fat dairy and protein foods, and oils. This helps maximize nutrient content and the health promotion potential of the diet. Additional low-fat diets include the DASH diet and the diets recommended by the American Diabetes Association, American Heart Association, and American Cancer Society. The commercial Weight Watchers program is also a low-fat diet.

Focus on the Dietary Guidelines for Americans

The Dietary Guidelines for Americans is now in its eighth edition and consists of five suggestions that should be followed. They are as follows:

1.: Follow a healthy eating pattern across the life span. Maintain a healthy weight, support nutrient adequacy, and reduce risks of chronic disease.
2.: Focus on variety, nutrient density, and amount. Meet nutrient needs, but stay within calorie limits.
3.: Limit calories from added sugars and saturated fats, and reduce sodium intake. These include sodas, snacks, desserts, sandwiches, and pizza.
4.: Shift to healthier food and beverage choices. For example, instead of fried chicken, eat chicken baked with herbs. Instead of canned peaches in syrup, eat fresh or frozen peaches without added sugars.
5.: Support healthy eating patterns for all. Work with others to encourage better diet at home, at school, or in the workplace.

Focus on MyPlate

The US government's MyPlate program suggests that each meal should consist of the following:

•: 50%—approximately 20% fruits and 30% vegetables—vary your vegetables, and focus on whole fruits. Whole fruits can be fresh, frozen, dried, or canned in 100% juice. Eat colorful fruits and vegetables because they provide more vitamins and minerals and are usually lower in calories. Fruits can be eaten with meals, as snacks, or as desserts. Fresh, frozen, or canned vegetables are acceptable, and they can be steamed, sautéed, roasted, or raw.
•: 50%—approximately 20% proteins and 30% grains—mix up protein foods to include seafood, beans, peas, unsalted nuts and seeds, soy products, lean meats, and poultry. Make half your grains whole grains, which should be listed first or second on the ingredients list—such as oatmeal, whole-grain bread, and brown rice. Limit grain-based desserts and snacks, such as cakes, cookies, and pastries.
•: Drink low-fat or fat-free milk, or eat similar types of yogurt. Soymilk is also great. Replace sour cream, cream, and regular cheese with low-fat yogurt, milk, and cheese. Drink beverages that have less sodium, saturated fat, and added sugars. For oils, use vegetable oils instead of butter, and oil-based sauces and dips instead of those with butter, cream, or cheese. Drink water as much as possible, and avoid nondiet soda, energy or sports drinks, and other sugar-sweetened drinks.

There has been more in-depth study of low-fat diets than on any other type of diet. In many studies, low-fat diets have shown significantly greater weight loss than people who did not follow these diet plans. Low-fat diets also provided improvements in hemoglobin A1c (HbA1c), blood pressure (BP), high-density lipoprotein (HDL), and triacylglycerides (TAG). The Women's Health Initiative Dietary Modification Trial revealed that a low-fat diet without any instructions for calorie restriction helped maintain weight loss slightly better than following a diet that was higher in fat. Therefore it can be stated that a low-fat diet is an effective weight control strategy over any length of time, as long as it is followed correctly.

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Obesity in the elderly

Jahangir Moini , ... Mohtashem Samsam , in Global Health Complications of Obesity, 2020

Overnutrition in the elderly

Overnutrition is described as excess nutrient and energy intake over time. It is a form of malnutrition if it leads to morbid obesity. Overnutrition is identified by a BMI of 25.1–29.9 (overweight) or over 30 (obese). It is linked to increases in all causes of mortality, along with morbidity that is related to dyslipidemia, hypertension, type 2 diabetes, and various chronic diseases. There are, however, some studies suggesting that the mortality risk of obesity may actually decrease with age. There may be a small advantage to being overweight for men and women who are aged 65 or older. Recommendations for older adults about weight loss are made on an individual basis. Any patient who has a high-risk profile for cardiovascular disease or diabetes, or if there is a decrease in quality of life because of excessive weight, will probably benefit from weight loss. This must be accomplished with caution. The patient must receive enough calcium and vitamin D via supplements, along with exercise to prevent decreases in bone density and loss of muscle mass.

According to nutrition scientists at Tufts University, a MyPlate for Older Adults has been constructed that includes important age-specific components as follows:

•: bright-colored vegetables (broccoli, carrots)
•: deep-colored fruits (berries, peaches)
•: whole, enriched, and fortified grains and cereals (brown rice, 100% whole wheat bread)
•: low-fat and nonfat dairy products (yogurt, low-lactose milk)
•: dry beans and nuts
•: fish
•: poultry
•: lean meat
•: eggs
•: liquid vegetable oils
•: soft spreads that are low in saturated fats
•: spices instead of salt
•: fluids (water and fat-free milk)
•: physical activity (walking, resistance training, light house cleaning)

The MyPlate for Older Adults recommendations take into account the needs for exercise, adequate fluid intake, and requirements for vitamin B12 and D. This MyPlate can be adopted for vegetarians as well. Vegetable subgroups include dark green (such as kale and broccoli), starchy (such as corn and plantains), red/orange (such as sweet potatoes and carrots), beans/peas (soy beans and split peas), and "others" (onions, green peppers, cucumbers, mushrooms, and beets). Grains and fruits are also included in the MyPlate for vegetarians. Proteins include legumes, nuts, and seeds. There is less dairy included in this diet, and many people use calcium-fortified soy milk instead of cow milk.

Focus on avoiding overnutrition in the elderly

Elderly people should be educated about what each meal should contain. At least half of each meal should be fruits and vegetables, and at least half of grains that are consumed must be whole grains. Smaller portions of foods are important, and foods that can potentially have extremely high levels of sodium—such as bread, soup, and frozen meals—must be replaced with low-sodium choices. The basics of avoiding overnutrition are simple. The Dietary Approach to Stop Hypertension diet, for example, includes the following basic daily recommendations: grains (7–8 oz), meat and beans (6 oz or less of chicken, other meat, and fish plus 4–5 servings of nuts, seeds, and/or dried beans per week), milk (2–3 cups), vegetables (2–2.5 cups), fruits (2–2.5 cups), and oils (2 teaspoons).

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Dietary Fiber and Wheat Bran in Childhood Constipation and Health

Helga Verena Leoni Maffei , in Wheat and Rice in Disease Prevention and Health, 2014

Dietary Treatment of Constipation

Due to lack of details about DF intake in CFC guidelines, the author's dietary advice is based on theoretical knowledge about the effects of DF on bowel habits, ^73,74 other literature data, ^{1,12,13,41,46–48,78,79,99–102} and clinical experience. ^7,67 Thus, the recommended diet is that according to the Food Guide Pyramid/MyPlate for all food groups, ^46,90 with an emphasis on fruits with peel/bagasse, and on pulses, vegetables, seeds, and nuts. At least five daily portions of fruits/vegetables, one of non-sifted pulses and of seeds/nuts, are recommended. A written leaflet listing the DF-dense foods within each food group is provided, while those with almost no DF, such as melon, watermelon, and cucumber without skin, are also indicated. Non-refined cereals are included in the advice, but, apart from corn, these are relatively expensive in Brazil. Therefore, taking into account that whole grain foods like bread, pasta, and rice are not part of the usual Brazilian diet, plain wheat bran is recommended in approximate amounts: 5–10 g per day for age < 1 year, 10–20 g per day for ages 1–2 years, and 20 g per day for older children. Wheat bran is cheap and tested by governmental entities for food security in Brazil, and it has the best weight/weight ratio among foods (g food intake/g increase in fecal weight). ⁷³ It can be used – in the proportion 2 parts of refined flour to 1 part of bran – to prepare bread, desserts, cakes, pancakes, and "farofa" (manioc flour roasted with varied ingredients, which is very popular in the country). Otherwise, it can be slightly roasted and added to a humid (but solid) food constituent. Bran is usually not well accepted in fluids such as soups and beverages. Adequate fluid intake has to be ensured, but this is not usually a problem. Fruit juice is allowed, as long as it contains the whole fruit, is non-sifted, and has no added sugar. Suggestions for "good" snacks (between meals) and for "good" sweets (after meals) are given: olives, popcorn, mixed nuts, dried fruits, coconut-filled chocolate, pumpkin compote, passion fruit mousse with seeds, and so forth. Gaseous beverages and junk food are discouraged. A decrease in protein intake is advised whenever excess is reported. ¹⁰³ A prospective evaluation throughout 24 months confirmed that this recommendation is a feasible, cheap, and effective tool for treating constipated children (along with the other treatment tools) in everyday clinical attendance. ¹⁰³

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Artificial Intelligence in Subspecialties

Anthony C. Chang , ... Benjamin Fine, an engineer-turned-radiologist who is an expert in improvement science and machine learning, authored this commentary on the concept of an AI-enabled health care manager to monitor real-time health system data to execute the best course of action., in Intelligence-Based Medicine, 2020

Published reviews and selected works

There is significant academic activity focusing on AI in this burgeoning domain. A recent review on AI utilization in precision medicine discussed the importance of data quality and relevance [209]. The authors contend that much of the effort to advance AI in precision medicine has been focused on algorithms and generation of genomic sequence data and EHR but should also be on physiological genomic readouts in disease-relevant tissues as well. Another review discussed advances in ML and AI are vital for the understanding of epigenetic processes, specifically DL for the generation and simultaneous computation of novel genomic features [210]. Grapov et al. reviewed DL in the context of omics and EHR and astutely pointed out that the challenges of DL is akin to those observed in biological message relay systems such as gene, protein, and metabolite networks [211]. In biomedical diagnostics, medical geneticists are often frustrated by the tedious nature of genotype-phenotype interrelationships among syndromes, especially for extremely rare syndromes. Now, medical geneticists are able to use a visual diagnostic system that employs ML algorithms and digital imaging processing techniques in a hybrid approach for automated diagnosis in medical genetics, especially in rare diseases [212]. One such proposal is the BioIntelligence Framework proposed by Farley et al. [213]. In this model a scalable computational framework leverages a hypergraph-based data model and query language that may be suited for representing complex multilateral, multiscalar, and multidimensional relationships. This hypergraph-like store of public knowledge is coupled with an individual's genomic and other patient information (such as imaging data) to drive a personalized genome-based knowledge store for clinical translation and discovery. Patients of very similar genomic and clinical elements can be discovered and matched for diagnostic and therapeutic strategies (see Fig. 8.16) [214].

Artificial intelligence (AI) and nutrition—a personalized diet strategy

Since the proverb "An apple a day keeps the doctor away" originated in the 19th century [1], almost every child has come across it since parents use it as a rule of thumb to encourage fruit and vegetable consumption. To promote consumption the United States Department of Agriculture issues food guides. Eight guides have released since 1916 [2] , including the well-known "Food Guide Pyramid" published in 1992. The most recent food guide "MyPlate" issued in 2011 illustrates fruits, grains, vegetables, protein, and dairy as five food groups that are building blocks for a healthy diet using a familiar mealtime symbol. "My" in "MyPlate" emphasizes the personalization approach to finding a lifelong healthy, balanced eating style shaped by many factors and choices. Other popular diet and nutrition planning approaches exist including a reduced calorie diet, ketogenic diet, intermittent fasting, Whole30, and Paleo [3]. Some of these approaches require elimination of entire food groups that may cause serious nutrient deficiencies over time. The emergence of meal plan varieties and personal diet planning tools point to an increasing awareness that no universal diet plan fits all. AI has started to play a significant role in this field. Recent findings suggest the way we build models and collect data can push the edge of diet planning to be more personal than ever.

AI strengthens the ability of scientific studies in gathering, analyzing, interpreting, and eventually predicting the best diet plan a person needs to achieve a certain health goal. While we know a model is not a perfect description or a prediction of reality, we are getting closer to reality with data science, ML, and more thoughtful interpretation. For example, Habit is a company that looks at 70+ health markers and uses ML algorithms to inform users how their body handles macronutrients. Users learn what their ideal plate looks like and receive a personalized food guide and list of recipes. Passio, an ML company that uses image recognition to provide real-time on-device food recognition, enables users to have seamless food tracking and nutrition insights.

Currently, most diet planning service providers use AI technologies that quantify each participant who contributes to their research as a number in a dataset; the sample of one participant is likely to be evened out by thousands of other participants. Predictions from participant data will be made based on general results of the pros and cons of a food type to a group of people with a certain biomarker type. Data predictions cannot include every factor or measure some factors that may influence the user's actual reaction to different food types. Or, how a user's health condition changes over time, including lifestyle, medical conditions, immune system, anatomy, physiology, medications, and environment. It is possible that a typical diet plan would miss out on these factors. One example of a medical condition in a study shows a postmeal evaluation can be as important as premeal planning.

Research conducted by Weizmann Institute "Personalized Nutrition by Prediction of Glycemic Responses" [4] found people eating identical meals present high variability in postmeal blood glucose response. Personalized diets created with the help of an accurate predictor of blood glucose response that integrate parameters such as dietary, habits, physical activity, and gut microbiota may successfully lower postmeal blood glucose and its long-term metabolic consequences. In this study, 800 healthy and prediabetic individuals were continuously monitored and responses measured to 46,898 meals. Participants were also measured with other blood parameters, anthropometrics, physical activity, self-reported lifestyle behaviors, and gut microbiota composition and function. The research group devised a machine-learning algorithm that accurately predicted personalized postprandial glycemic response to real-life meals. Weizmann Institute validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration (Fig. 1). A recent study "Assessment of a Personalized Approach to Predicting Postprandial Glycemic Responses to Food Among Individuals Without Diabetes" [5] conducted by Mayo Clinic echoed this finding.

In these studies, one person is no longer a single data in a dataset; they become the center of new data generated over time. By using a key indicator that reflects potential factors that may affect one person's unique relationship to a type of food, feeding this second set of user's individual data into the model after predictions based on a dataset from the population sample, diet planning for each user is differentiated. In other words the same usage of ML can generate a more personalized selection of diet components if we add a tier of algorithm modification with the user's personal response data over time.

Many AI-based diet planning services are trying to improve their algorithms by collecting more data from more users. However, for each individual, a person's unique connection to foods may be more effective in building diet planning. For example, Whisk's Culinary Coach uses AI to provide personalized food recommendations based on flavor preferences and food avoidance. Another example is Plant Jammer, a recipe-generating app, that uses AI to help users build personalized recipes and improve low kitchen confidence by pairing ingredients together based on factors (e.g., food likes/dislikes) and setting different filters (e.g., season and region). Although AI is smart enough to perform calculations that humans cannot compete with, its utility highly depends on where it was built in a hypothesis. AI may give a better explanation about a view of how a mechanism runs, but it cannot create the view for us. In diet planning, volume and quality of data are critical, but another dimension to consider is data validity to the individual case. The time horizon of each data generator may be too valuable to ignore.

In 100 years, we have evolved from static food guides to automated nutrition planning. AI's role and value as a tool in the future of personalized nutrition and meal planning to help people live healthier and balanced lifestyles will increase.

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Design of human centered augmented reality for managing chronic health conditions

Anne Collins McLaughlin , ... Maribeth Gandy Coleman , in Aging, Technology and Health, 2018

Information visualization across interfaces

Evaluation of AR visualization techniques has often focused on perception (e.g., depth and spatial perception; Avery, Sandor, & Thomas, 2009; Sandor, Cunningham, Dey, & Mattila, 2010). Mendez and Schmalstieg (2009) developed a variety of techniques to create visualizations and warned against "naive" augmentations, designed to reveal hidden structures inside a physical object that inadvertently obscure context or lack depth cues. They concluded that an effective augmentation considers what parts of the physical world should be occluded by the virtual content and then controls the information added to the physical scene. Similarly, Kalkofen, Mendez, and Schmalstieg (2009) framed the relationship of real and virtual objects in AR visualization as one of focus+context; the goal is to either provide virtual context to a physical object or for the user to focus on a virtual object embedded in a physical context. For example, an empty plate could have overlaid virtual representations for the portion size of fruits, grains, vegetables, and proteins, as recommended by MyPlate ( www.choosemyplate.gov; USDA, 2017), giving user a virtual context to guide their physical portioning. In almost the same task, a virtual food item could be shown alongside actual food already on a plate to encourage the right choices, using the physical context of other foods to add more meaning to the virtual content. And these augmentations approaches can adapt throughout the experience, changing as the user interacts with the physical and virtual content and explore it in different ways (e.g., adding more food to the plate, pointing at a virtual or physical item, moving the plate closer to the camera etc.). Others such as Zollmann et al. (2012) have used these "focus+context" interaction techniques to guide the design of 4-D AR elements that show changes over time.

AR visualization techniques have been explored in the medical domain, ranging from a full-body system to teach ultrasound techniques (Blum, Heining, Kutter, & Navab, 2009), to delicate needle biopsies (State et al., 1996), down to laparoscopy (Bichlmeier, Heining, Rustaee, & Navab, 2007). The results have shown that virtual augmentations situated on the body at a variety of scales are an effective presentation method for physiological information and that medical professionals and trainees can use AR systems efficiently. For example, Navab, Mitschke, and Schütz (1999) first demonstrated the use of AR for more accuracy using a C-arm, which is a device used to guide a needle to a specific area of the body. Traditionally, to do this, physicians watch an ultrasound screen to see where the needle is in relation to the body. Providing the context of the body with AR allowed for higher accuracy and lower time to perform the procedure. Additional iterations on the design later revealed that users experienced increased depth perception when the virtual content was reduced to a small virtual "window" that allowed the user to look through the person's body (Erat et al., 2013). This work highlighted the importance of not overwhelming the user with virtual augmentations, but rather striking a delicate balance with the visual design between the virtual imagery and critical physical context.

Caution must be taken in assuming these medical visualization studies will apply directly to older adults' understanding of medicine and health. The target user in those systems was typically a medical expert, such as a doctor, nurse, or technician. The systems were designed either to train these experts or for use during live procedures. As a result, the virtual representations needed to be realistic and absolutely precise in registration representation. For example, one such study examined the use of VR and AR for a specific medical imaging procedure in 52 live surgeries (Okur, Ahmadi, Bigdelou, Wendler, & Navab, 2011). This visualization was used to guide medical professionals to specific areas in which a radioactive material was present to allow for a more accurate SPECT scan. These researchers found that AR visualization was used more often than VR visualization; however, they also noted that AR was used for more "big-picture" visualizations of what was happening in the body and more precise tasks were associated with more VR use.

Such system requirements differ from those for older adults managing health conditions, where the goal is for the user to gain a general understanding of their condition and knowledge and skills that will help them manage the condition. However, the medical domain does provide examples of proven techniques for conveying complex visual data of bodily process via AR and which rendering techniques work well in that context. For example, the Mirracle system is an AR mirror for teaching anatomy. The user sees a volumetric rendering of a CT dataset overlaid on their body and gestures to browse through "slices" of the self, augmented with 3D models of organs, text information, and images (Blum, Kleeberger, Bichlmeier, & Navab, 2012). This system works with the camera from the Kinect but is still a proof of concept rather than a system tested to see if it helps anatomy students learn. However, users were successful in interacting with the system to browse their body, showing that the interaction techniques were sound.

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Promoting Health and Wellness in the Geriatric Patient

Melissa Bernstein PhD, RD, LD, FAND , in Physical Medicine and Rehabilitation Clinics of North America, 2017

Dietary guidelines for Americans and MyPlate

Lifelong dietary patterns affect the likelihood of age-related chronic disease. Regardless of age, eating healthful foods and limiting poor food choices should be a priority. For adults of every age, low-fat dairy, lean meats, adequate fiber, whole grains, fruits, and vegetables should be emphasized. Trans fats, sodium, sugar, and excess calories should be minimized. The 2015-2020 Dietary Guidelines for Americans (the Dietary Guidelines ) and MyPlate offer dietary guidance for whole foods and food groups rather than individual nutrients. ^1,2 For older adults, eating nutritious food without overconsuming calories can be a challenge in the face of functional dependence, frailty, and illness. Tufts University's MyPlate for Older Adults highlights the unique dietary needs of adults older than 70 years by additionally emphasizing fluid intake, and nutrient-dense food choices such as protein-rich foods, vegetables, fruits, whole grains, healthy oils, and low-fat dairy choices. ³ The topic area of "older adults" is new for Healthy People 2020 and was developed in response to the rapidly aging American population. The aim of the older adult initiative is to "improve the health, function, and quality of life of older adults." ⁴

As an older individual's health declines, the need to individualize nutritional recommendations is of significant importance, especially in the presence of multiple disease conditions. Older adults at risk of malnutrition or undesirable weight loss should have their diets liberalized if possible to promote adequate food and nutrient intake. Strict restrictions such as a low-salt diet, for example, may actually decrease food intake because of lack of flavor.

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Breastfeeding Updates for the Pediatrician

Christina J. Valentine MD, MS, RD , Carol L. Wagner MD , in Pediatric Clinics of North America, 2013

Nutrient requirements during lactation

Nutritional demands are higher for the mother while nursing. These metabolic demands translate into the requirements for an additional 300 calories and a total of 71 g of protein per day. ⁶⁰ Table 1 shows the recommendations for nutrients during lactation. Nutrient intakes for the average woman are best achieved by a diet consisting of a variety of foods.

Table 1. Maternal daily recommended intakes of micronutrients during lactation ^a

Nutrients (Unit)	Maternal Age
Nutrients (Unit)	14–18 y	19–50 y
Water-Soluble Vitamins
B1 (mg)	1.4	1.4
B2 (mg)	1.6	1.6
B3 (mg)	17	17
B6 (mg)	2	2
B12 (μg)	2.8	2.8
Pantothenic acid (mg)	7	7
Biotin (μg)	35	35
Vitamin C (mg)	115	120
Folate (μg)	500	500
Fat-Soluble Vitamins
A (μg)	1200	1300
D (IU) ^b	600	600
E (mg)	19	19
K (μg)	75	90
Minerals
Calcium ^b (mg)	1300	1000
Phosphorus (mg)	1250	700
Zinc (mg)	13	12
Iron (mg)	10	9

a: Dietary reference intakes as recommended by the Institute of Medicine, 2005.
b: Calcium and vitamin D intake as recommended by the Institute of Medicine, 2010.

Minimum Daily Food Intakes Suggested to Meet Maternal Nutrient Requirements

Box 1 summarizes the minimum daily food intakes suggested to meet nutritional needs during lactation. Vegetarians, women with dietary restrictions, or those with a history of intestinal or gastric surgery should consult with a registered dietitian to critically evaluate their intake and receive a specialized dietary plan to ensure that vitamin B12, iron, and zinc intakes are adequate. In addition, consumers can design their own individual menu plans on www.myplate.gov.

Box 1

Suggested minimum food sources for the lactating mother

Dairy Group: 3 one-cup servings: High in vitamins A and D: milk, yogurt

Protein: 6.5 oz (184 g): Iron, zinc, potassium: lean meats, chicken, beans, peas, nuts, seeds

ω-3–Rich fish sources: salmon, trout, herring, sardines; ω-3 rich eggs

(do not eat shark, swordfish, kingfish, which can be high in mercury)

Grains: 8 half-cup or 1-slice servings: Make sure grains fortified with folic acid and iron

Vegetables: 3 one-cup raw servings: High in vitamins A and K: carrots, pumpkin, squash, sweet potatoes, cooked greens, tomatoes, red sweet peppers

Fruits: 2 one-cup servings: Cantaloupe, mango, apricots, bananas, honeydew melon, oranges

Dietary Supplements for the Mother

Food sources should provide the majority of nutrients for the nursing mother, but for some nutrients supplementation is important. The IOM recommends supplementation with 600 IU/d of vitamin D if sun exposure and baseline vitamin D concentrations are low in the mother. ³⁷ Often North American dietary intake of salmon or fatty fish is low, ^39,41 requiring some source of supplementation. Additional DHA/ω-3 may be achieved by dietary supplements or by consumption of 4 ω-3–enriched eggs per week. ⁷¹ In women unable to eat fish or egg sources, a dietary supplement may be needed to achieve a daily intake of 300 mg to 1 g per day.

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Advances in the Diagnosis and Treatment of Autism Spectrum Disorder-2

T. Lindsey Burrell PhD , ... Lawrence Scahill MSN, PhD , in Seminars in Pediatric Neurology, 2020

Treatment Group: CHANGE Program

The 4-month CHANGE program consisted of 12, 1-hour sessions that included the parent and the child. The treatment sessions focused on 4 areas: nutrition education; calorie reduction (eg, reduction in sweetened beverages); physical activity; and behavior management strategies to address compliance with treatment components. A hierarchical decision matrix (Fig. 1) was used to determine the choice and order of intervention components.

The aim of the nutritional component of CHANGE was to promote the US Department of Agriculture's MyPlate guidelines for well-balanced nutrition. ¹³ Strategies involved diluting sweetened beverages, grazing reduction, increasing fruit and vegetable intake, and reducing portions.

In behavior modules, the psychologist identified barriers to exercise and physical activities to construct weekly exercise goals. The goal was to increase exercise gradually to 60 minutes per day (420 minutes per week) in line with the US Department of Health and Human Services recommendations. ¹³ The psychologist engaged the parent in motivational interviewing to assess readiness for change, reduce barriers of active participation, and to foster intake of healthy foods through the application of behavioral strategies (eg, setting small goals, reinforcing meeting goals). Behavior management strategies included gradual increases in home and clinic-based physical activity; reasonable expectations and demands; and reinforcement. During each session, the treatment team monitored the child's physical activity, food intake, and height and weight, provided education and practiced relevant skills, and established goals for the week.

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