These carbohydrates are composed of sugars such as fructose and glucose which have simple chemical structures composed of only one sugar monosaccharides or two sugars disaccharides. Simple carbohydrates are easily and quickly utilized for energy by the body because of their simple chemical structure, often leading to a faster rise in blood sugar and insulin secretion from the pancreas — which can have negative health effects.
These carbohydrates have more complex chemical structures, with three or more sugars linked together known as oligosaccharides and polysaccharides. Many complex carbohydrate foods contain fiber, vitamins and minerals, and they take longer to digest — which means they have less of an immediate impact on blood sugar, causing it to rise more slowly.
But other so called complex carbohydrate foods such as white bread and white potatoes contain mostly starch but little fiber or other beneficial nutrients. Dividing carbohydrates into simple and complex, however, does not account for the effect of carbohydrates on blood sugar and chronic diseases. To explain how different kinds of carbohydrate-rich foods directly affect blood sugar, the glycemic index was developed and is considered a better way of categorizing carbohydrates, especially starchy foods.
The glycemic index ranks carbohydrates on a scale from 0 to based on how quickly and how much they raise blood sugar levels after eating. Foods with a high glycemic index, like white bread, are rapidly digested and cause substantial fluctuations in blood sugar. Foods with a low glycemic index, like whole oats, are digested more slowly, prompting a more gradual rise in blood sugar.
Numerous epidemiologic studies have shown a positive association between higher dietary glycemic index and increased risk of type 2 diabetes and coronary heart disease. However, the relationship between glycemic index and body weight is less well studied and remains controversial. This measure is called the glycemic load. In general, a glycemic load of 20 or more is high, 11 to 19 is medium, and 10 or under is low. The glycemic load has been used to study whether or not high-glycemic load diets are associated with increased risks for type 2 diabetes risk and cardiac events.
In a large meta-analysis of 24 prospective cohort studies, researchers concluded that people who consumed lower-glycemic load diets were at a lower risk of developing type 2 diabetes than those who ate a diet of higher-glycemic load foods.tedehuramgarm.gq/success-on-the-inside.php
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Here is a listing of low, medium, and high glycemic load foods. For good health, choose foods that have a low or medium glycemic load, and limit foods that have a high glycemic load. Whole grain, bran, and germ intake and risk of type 2 diabetes: a prospective cohort study and systematic review. PLoS Med. High dietary glycemic load and glycemic index increase risk of cardiovascular disease among middle-aged women: a population-based follow-up study. J Am Coll Cardiol.
Low-carbohydrate-diet score and the risk of coronary heart disease in women. N Engl J Med. However, you might be able to achieve the same health benefits by eating a healthy diet, maintaining a healthy weight and getting enough exercise. Check with your doctor or health care provider before starting any weight-loss diet, especially if you have any health conditions, including diabetes.
The GI principle was first developed as a strategy for guiding food choices for people with diabetes. The database contains the results of studies conducted there and at other research facilities around the world. A basic overview of carbohydrates, blood sugar and GI values is helpful for understanding glycemic index diets. Carbohydrates, or carbs, are a type of nutrient in foods. The three basic forms are sugars, starches and fiber. When you eat or drink something with carbs, your body breaks down the sugars and starches into a type of sugar called glucose, the main source of energy for cells in your body.
Fiber passes through your body undigested. Two main hormones from your pancreas help regulate glucose in your bloodstream. The hormone insulin moves glucose from your blood into your cells. The hormone glucagon helps release glucose stored in your liver when your blood sugar blood glucose level is low.
What is the Glycaemic Index?
This process helps keep your body fueled and ensures a natural balance in blood glucose. Different types of carbohydrate foods have properties that affect how quickly your body digests them and how quickly glucose enters your bloodstream. There are various research methods for assigning a GI value to food. In general, the number is based on how much a food item raises blood glucose levels compared with how much pure glucose raises blood glucose. GI values are generally divided into three categories:. Comparing these values, therefore, can help guide healthier food choices.
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For example, an English muffin made with white wheat flour has a GI value of A whole-wheat English muffin has a GI value of One limitation of GI values is that they don't reflect the likely quantity you would eat of a particular food. For example, watermelon has a GI value of 80, which would put it in the category of food to avoid. But watermelon has relatively few digestible carbohydrates in a typical serving.
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In other words, you have to eat a lot of watermelon to significantly raise your blood glucose level. To address this problem, researchers have developed the idea of glycemic load GL , a numerical value that indicates the change in blood glucose levels when you eat a typical serving of the food. For example, a 4. For comparison, a 2. The values are generally grouped in the following manner:.
A GI value tells us nothing about other nutritional information. For example, whole milk has a GI value of 31 and a GL value of 4 for a 1-cup milliliter serving. But because of its high fat content, whole milk is not the best choice for weight loss or weight control. The published GI database is not an exhaustive list of foods, but a list of those foods that have been studied. Many healthy foods with low GI values are not in the database.
The GI value of any food item is affected by several factors, including how the food is prepared, how it is processed and what other foods are eaten at the same time. Also, there can be a range in GI values for the same foods, and some would argue it makes it an unreliable guide to determine food choices. A GI diet prescribes meals primarily of foods that have low values. Examples of foods with low, middle and high GI values include the following:.
Commercial GI diets may describe foods as having slow carbs or fast carbs. In general, foods with a low GI value are digested and absorbed relatively slowly, and those with high values are absorbed quickly. Commercial GI diets have varying recommendations for portion size, as well as protein and fat consumption. Results of a year study that tracked the diets of , men and women were published in Therefore, RCTs are impractical to provide complex evidence needed for individualized treatment.
This limitation is especially true in nutrition and lifestyle research. Foods do not behave like drugs, and nutrients are rarely consumed in isolation [ 9 ]. A diet or dietary pattern contains multiple bioactive food components and is difficult to eliminate the day-to-day variation in dietary intake [ 10 ]. The effects of food are more subtle and may take a significant amount of time to produce discernible results.
Plus, differences in genetic makeup, metabolic variations, environmental exposure, and even variations in the gut microbiome all potentially affect how an individual absorbs, responds and utilizes the nutrients in a diet [ 11 ]. Specifically, those with the rs A allele benefitted the most from a high-protein weight-loss diet [ 13 ].
Another weight-loss trial in men with obesity found that baseline DNA methylation patterns in CpGs on the WT1 promoter might be used as epigenetic markers that predict outcomes in weight loss [ 14 ]. Other examples of research supporting personalized nutrition approaches have been summarized in our previous review [ 15 ]. In the context of personalized lifestyle medicine, however, the ability to analyze multiomics data is essential.
High-throughput platforms such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics have allowed powerful comprehensive analysis of how complex biological systems are impacted upon an external exposure, whether it is as simple as ingesting a single phytochemical compound or as complex as a new dietary and exercise regimen [ 16 ].
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A seminal, proof-of-principle, work is the integrative personal omics profile iPOP study led by Dr. Snyder from Stanford University School of Medicine [ 17 , 18 ]. This study collected multiomics data and autoantibody profiles from a single individual Dr. Snyder himself over a month period. The researchers believe that iPOP would lead to better personalized healthcare by providing more precise methods of monitoring, targeted treatment, and prevention. As more patients now believe the importance of healthy lifestyle in their health, clinicians and healthcare practitioners have a unique opportunity in advocating lifestyle medicine for NCD prevention and treatment because patients see them as a reliable source of advice [ 19 ].
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Environmental data related to physical activity or nutrition may be collected via personal monitoring devices worn by patients. Studies have demonstrated that patients desire to be active participants in information exchange and the decision-making process, and those who are participatory yield better health outcomes than those who are not [ 21 , 22 ].
Among tens of thousands of newly discovered candidate biomarkers identified through omics research during the last decade, only a hundred or so biomarkers have demonstrated clinical utility [ 23 ]. Information gathered beyond genetic testing, such as that from genomic, proteomic, and metabolomics platforms, increases exponentially in its complexity. Computational tools e. Machine-learning algorithms and new statistical methodologies that can integrate these multidimensional data are also needed. Clinicians also face other practicality issues. What kind of training is required in order to deliver complex omics-based advice?
How would all the sensitive genetic information of the patients be analyzed and stored? Are there programs or cloud-based services that can create a master tracking portal for all patient data? Would all the advanced testing and additional counseling be covered in the care payer systems? Are there reliable, mobile-based diagnostics and wearable technologies that can collect behavior and other health-related data?
Are there nutritional products that can support personalized lifestyle medicine? At the emotional level, although clinicians and health professionals have a key role in delivering personalized lifestyle medicine, the vast amount of information generated from the omics technologies can be overwhelming and technically challenging. Without simplified and clinically relevant recommendations, health professionals may find it difficult to deliver personalized care. Patients may be uncomfortable in disclosing detailed, intimate personal genetic information to clinicians, or they simply may not be motivated to be participatory.
Whether these powerful new technologies and individualized recommendations can motivate patients in taking charge of their own health remains to be seen. Even though the road to personalized lifestyle medicine is challenging, emerging ground-breaking research projects have given us a glimpse of how systems thinking and computational methods may lead to personalized health advice.
A study conducted at the Weizmann Institute of Science Rehovot, Israel collected extensive phenotypic data—week-long monitoring of blood glucose, detailed recording of diet, and lifestyle information via smartphone technology, blood tests, anthropometrics, lifestyle and medical questionnaire, and stool samples for gut microbiome analysis—from individuals. This is an example of how big data are translated into personalized nutritional recommendations. The Pioneer Person Wellness Project P , a month pilot project originated from the Institute for Systems Biology Seattle, USA , aims to optimize wellness by integrating longitudinal information from whole genome sequencing, clinical and functional lab testing, gut microbiome analysis, and quantified self-measures from individuals [ 28 , 29 ].
The goal is to apply what the researchers learned to a much larger population and deliver early personalized healthcare to optimize health and prevent NCDs. The current healthcare system is no longer sufficient in addressing NCD epidemic. Personalized lifestyle medicine will be the key to empower patients to regain control of their health. There are still logistic and technical challenges to overcome in order to deliver personalized advice based on systems thinking, molecular diagnostics, accurate environmental measurements, and advanced computational methods.
Healthcare professionals, geneticists, bioinformaticians, food industry, health industry, and policy makers will all need to work together to strengthen the science, to improve knowledge delivery, and to improve public education in order to create the needed paradigm shift in healthcare. Deanna Minich serves as a consultant to Metagenics, Inc. The authors thank Dr.