Category: Diet

Macronutrient distribution

Macronutrient distribution

Maconutrient Rev Endocrinol 10— Article Macronutrient distribution Google Scholar Larsen, T. Low-carbohydrate diets and all-cause mortality: a systematic review and meta-analysis of observational studies.

Macronutrient distribution -

The position of the American Diabetes Association ADA on MNT is that each person with diabetes should receive an individualized eating plan 4. ADA has received numerous criticisms because it does not recommend one specific mix of macronutrients for everyone with diabetes.

The previous literature review conducted by ADA in supported the idea that there was not one ideal macronutrient distribution for all people with diabetes. This review focuses on literature that has been published since that date 5.

This systematic review will be one source of information considered when updating the current ADA Nutrition Position Statement 4. Other systematic reviews and key research studies that may not be included in this review will also be considered. When attempting to tease out the role of macronutrients from other dietary and lifestyle factors, two critical components of MNT—energy balance and a healthful eating pattern—are not addressed.

While both are critical components in the management of diabetes as well as the secondary prevention of complications and promotion of health, these topics are beyond the scope of this particular review. The following questions are addressed in this review:.

What aspects of macronutrient quantity and quality impact glycemic control and cardiovascular disease CVD risk in people with diabetes? How do macronutrients combine in whole foods and eating patterns to affect health in people with diabetes?

Is there an optimal macronutrient ratio for glycemic management and CVD risk reduction in people with diabetes? Certain terms relevant to nutrition therapy in the management of diabetes were not included in the search terms. These terms include trans fatty acids, monounsaturated fatty acids MUFAs , polyunsaturated fatty acids PUFAs , sucrose, and sugars.

The literature search was limited to articles published in English, and multiple publications from the same study were limited to the primary study results article.

Studies included in the systematic review were conducted in people already diagnosed with diabetes; conducted in outpatient ambulatory care settings; contained a sample size of 10 or more participants in each study group; and one of the following study designs: clinical trials controlled and randomized controlled [RCT] , prospective observational studies, cross-sectional observational studies, or case-control studies.

Studies were excluded if they were published before January or after October ; were conducted in acute care or inpatient settings, in women with gestational diabetes, children under 2 years of age, or individuals without diabetes or at risk for diabetes; had less than 10 participants in any study group; were studies lasting only 1 or 2 days; or were not in one of the study designs previously listed.

Weight loss is a confounder in some of the studies and is noted in Supplementary Table 1. This information can be found in Supplementary Table 1. An initial PubMed database search found studies after excluding by title and abstract review. An additional 18 studies were found from bibliography review.

Of these, 72 studies were excluded for not meeting inclusion criteria. The most common reasons for exclusion were for results not applicable to the research question, not published in a major journal, small sample size, review articles, and duplicates.

Isolating the effects of dietary macronutrient composition on glycemic control and CVD risk is difficult due to confounding, especially by weight loss and medication changes.

Furthermore, altering the level of one macronutrient affects the proportion of other macronutrients, making it difficult to isolate the true exposure.

Additional study design issues include the difficulty blinding study participants, investigators, and clinicians. These issues were addressed by reporting the entire macronutrient composition of diet approaches and potential confounders when this information was available.

Based on the studies in this systematic review, the following definitions are used:. These definitions are not all-inclusive e. The comparison diets referred to as conventional or traditional throughout this review are higher in carbohydrate than those generally consumed by people with diabetes.

Eleven clinical trials examined the effects of lowering total carbohydrate intake on glycemic control in individuals with diabetes. The carbohydrate content goal of the diet was very low in 7 studies 10 — 16 and moderately low in 4 studies 17 — All studies included adults with type 2 diabetes, duration of follow-up ranged from 14 days to 1 year, and sample sizes ranged from 10 to 55 participants per study group.

Designs included two feeding trials one crossover clinical trial and one RCT 10 , 18 and nine outpatient nutrition counseling interventions two single-arm clinical trials, one crossover RCT, and six parallel RCTs 11 — 17 , 19 , A1C decreased with a lower-carbohydrate diet in 6 of 10 studies in which it was measured 10 , 14 — 17 , Three RCTs found no statistically significant changes in A1C with a very-low-carbohydrate diet 11 — 13 and one found no difference with a moderately low—carbohydrate diet Other glycemic parameters such as fasting blood glucose FBG , h blood glucose, h insulin 10 , and fasting insulin levels 18 decreased significantly, and insulin sensitivity increased significantly 10 on the lower-carbohydrate diet.

Glucose-lowering medications were decreased for individuals following the lower-carbohydrate diet 10 — 12 , 14 , 17 or were more frequently decreased than in the comparison diet Each of the 11 clinical trials reported at least one serum lipoprotein. The most notable results were that HDL cholesterol increased significantly more in one very-low-carbohydrate diet group 16 and two moderately low—carbohydrate diet groups 18 , 20 compared with the higher-carbohydrate control diet.

Also, triglycerides TGs decreased more in one moderately low—carbohydrate diet group 20 compared with the higher-carbohydrate control diet. Otherwise, mean changes in serum lipoproteins resulting from a lower-carbohydrate diet were typically beneficial but occurred without a comparison arm or were not statistically greater than the comparison arm.

In studies reducing total carbohydrate intake, markers of glycemic control and insulin sensitivity improved, but studies were small, of short duration, and in some cases were not randomized or had high dropout rates.

Serum lipoproteins typically improved with reduction of total carbohydrate intake but, with the exception of HDL cholesterol, were not statistically greater than with the comparison diet. The contribution of weight loss to the results was not clear in some of these studies.

Seven clinical trials and two meta-analyses examined the effects of moderate- or high-carbohydrate diets on glycemic control in patients with type 2 diabetes 21 — 28 or type 1 diabetes Durations of follow-up ranged from 5 to 74 weeks, and sample sizes of participants completing follow-up ranged from 10 to All seven studies were RCTs and analyzed participants according to treatment assignment.

Only one of the studies blinded participants to diet treatment 22 , and none blinded the outcome assessors. Four studies found no significant differences in glycemic control when comparing moderate- or high-carbohydrate diets with conventional diets 21 — The intent-to-treat analyses, however, showed no significant differences between groups.

Two meta-analyses compared lower-carbohydrate diets with conventional carbohydrate diets 27 , Of the 19 studies reviewed in the article by Kodama et al. The seven studies are included in this review. Six of the seven interventions reviewed above reported lipoproteins.

Three studies 22 — 24 found no significant differences between comparison diets. RCTs presenting information on moderate- and high-carbohydrate diets are diverse in terms of fat and protein content as well as length of study.

Only two RCTs found significant differences in A1C between groups, with one study finding significantly lower A1C with the higher-carbohydrate diet only in a subgroup analysis, and the other study finding significantly lower A1C with the lower-carbohydrate diet.

In terms of CVD risk factors, LDL cholesterol improved more with a high-carbohydrate diet in one study, whereas two studies found TGs improved more with a lower-carbohydrate diet.

The meta-analyses almost all studies used were published before found that the average low GI was 65, and the average high GI was 82, but both had wide ranges. This is further complicated by the two bases glucose or white bread that have been used to determine GI values for individual foods.

Five RCTs 19 , 31 — 34 compared lower-GI diets with higher-GI diets in individuals with type 2 diabetes. Duration of follow-up ranged from 4 to 6 weeks and sample sizes were small in four studies 12—14 in three of the studies, 45 in the other , whereas the fifth study lasted for 1 year and included subjects in the analysis Results were mixed with two studies finding A1C was significantly reduced with the lower-GI versus higher-GI diets 32 , 33 and the others finding no differences in glycemic measures 19 , 31 , Three parallel RCTs 16 , 35 , 36 compared a lower-GI diet with diets other than those designated as higher GI high-fiber diet, traditional diet, very-low-carbohydrate diet in individuals with type 2 diabetes.

Compared with a higher-fiber diet, the lower-GI diet decreased A1C and FBG significantly When the lower-GI weight-loss diet was compared with a conventional weight-loss diet 36 , both groups lowered A1C significantly with no significant differences between groups.

The lower-GI diet reduced A1C significantly less than the very-low-carbohydrate diet A study in youth with type 1 diabetes 37 found that individuals advised to follow a lower-GI diet had significant reductions in A1C compared with individuals advised to follow a carbohydrate-exchange diet, despite the fact that the mean GI for the two diet groups was not significantly different.

Two studies indicated that education can change food selection and may 38 or may not 39 affect the GI of the diet. Three meta-analyses 40 — 42 evaluated GI. Anderson et al. These three studies from the meta-analyses are included above 32 , 33 , Mixed results were found for the five RCTs comparing low-GI with high-GI diets for lipoprotein measures.

Two studies found a significant reduction in total cholesterol 31 , 32 with one of the two reporting a significant reduction in LDL cholesterol and apolipoprotein apoB 32 for the lower-GI diet. The other three studies found no significant changes between groups 19 , 33 , Results were mixed in studies comparing lower GI with other dietary approaches.

Significantly increased HDL cholesterol was found with lower GI versus higher-cereal fiber but no significant differences in other measured CVD risk markers Total cholesterol was significantly lowered with both a lower-GI diet and a traditional diet without significant differences between groups; however, LDL cholesterol was significantly higher with the lower-GI diet versus the traditional diet A very-low-carbohydrate diet reduced TGs significantly and increased HDL cholesterol significantly compared with a lower-GI, reduced-calorie diet, with no significant differences in total cholesterol and LDL cholesterol A cross-sectional study 43 of men with type 2 diabetes described a statistically significant trend toward decreasing adiponectin with increasing quintiles of GI.

In general, there is little difference in glycemic control and CVD risk factors between low-GI and high-GI or other diets. A slight improvement in glycemia may result from a lower-GI diet; however, confounding by higher fiber 16 , 33 , 35 must be accounted for in some of these studies.

Furthermore, standardized definitions of low GI need to be developed and low retention rates on lower-GI diets must be addressed 16 , 33 , The Institute of Medicine defines dietary fiber as consisting of nondigestible not digested in the human small intestine carbohydrates and lignin that are intrinsic and intact in plants Quantification of the dietary fiber in research studies may be on the basis of dietary recommendations, grams per 1, kcals, the amount added, or its distribution within the study population.

Functional fibers are beyond the scope of this systematic review, and thus functional fiber and total fiber were not included in this review. Durations of follow-up ranged from 4 to 12 weeks, and sample sizes were small 12—60 participants in the fiber intervention.

In general, these studies support the idea that fiber supplements may improve postprandial glycemia; however, little improvement in A1C was observed.

Two dietary counseling RCTs examined the effects of dietary fiber as part of an intervention diet. In the first study, individuals on the low-GI diet showed small but significant improvements in A1C after controlling for weight loss, fiber, or carbohydrate and FBG at 6 months compared with those on the high—cereal fiber diet Markers of improved insulin sensitivity adiponectin or inflammation C-reactive protein [CRP], tumor necrosis factor-R2 [TNF-R2] were assessed in three cross-sectional reports 43 , 53 , Higher cereal or fruit fiber intakes were associated with higher levels of adiponectin 43 , 53 , 54 and lower levels of CRP 53 , 54 or TNF-R2 53 , Another cross-sectional study 55 , using a 3-day weighed diet, found that individuals with type 2 diabetes and the metabolic syndrome had significantly lower intakes of total dietary fiber specifically whole grains and fruits than those with diabetes but without the metabolic syndrome; however, there were no associations between fiber intake and A1C or FBG in either group.

The time period of the meta-analysis by Anderson et al. All RCTs described above assessed lipoproteins 35 , 45 — Four studies found no significant difference between intervention and control groups for these measures 46 , 48 — One study found that psyllium vs.

cellulose supplements 45 significantly improved HDL cholesterol; a second study found that a higher-fiber, lower-fat, and lower-GI diet versus a lower-fiber, higher-fat diet produced significantly lower total cholesterol, LDL cholesterol, and HDL cholesterol In addition, one cross-sectional study found that a diet higher in soluble fiber from whole grains was associated with a lower TG level In contrast, Jenkins et al.

The majority of the reviewed evidence indicates that adding fiber supplements in moderate amounts 4—19 g to a daily diet leads to little improvement in glycemia and CVD risk markers.

Eight clinical trials examined low-fat eating patterns 21 — 23 , 29 , 57 — One trial studied adults with type 1 diabetes 29 , whereas the rest studied adults with type 2 diabetes; duration of follow-up ranged from 3 days to 74 weeks, and sample sizes of participants completing follow-up ranged from 10 to 48 participants per study group.

All eight trials were outpatient nutrition counseling interventions: one single-arm 57 , two crossover RCTs 22 , 29 , and five parallel RCTs. A1C decreased with a low-fat diet in one of seven studies in which it was measured In that study 58 , intensive dietary advice for a lower-fat, moderate-carbohydrate, higher-fiber diet in adults with poor glycemic control significantly decreased A1C compared with the control group.

Insulin sensitivity by euglycemic-hyperinsulinemic clamp improved in the lower-fat diet compared with the conventional diet in one study Two weight-loss RCTs by the same group compared meal replacements versus conventional diets 59 , 60 and found significant reductions in FBG over short durations with meal replacements.

One study carried out for 12 months showed no persistent difference in FBG between groups, although significantly more subjects in the meal replacement group had reductions in diabetic medications In addition to the information from the clinical trials, a cross-sectional study 61 found that higher-fat intake correlated with significantly higher A1C.

Of the seven studies that measured CVD risk factors, only one had significant findings. The cross-sectional study 61 found that higher-fat intake correlated with higher levels of total cholesterol and LDL cholesterol as well as coronary artery calcium.

Lowering total fat intake infrequently improved glycemic control or CVD risk factors in clinical trials involving individuals with diabetes. Lowering fat intake in individuals with diabetes may improve total cholesterol and LDL cholesterol but may also lower HDL cholesterol.

For this review, the type of fat refers to the proportion of total energy from a specific fatty acid or fatty acid category.

Categorization may be on the basis of the number of, the location of, or the configuration of double bonds. Saturated fatty acids SFAs may be assessed based on distribution within the study population or recommended dietary levels.

Omega-3 fatty acids are usually evaluated as milligrams per day or as a distribution within the population rather than on the basis of percent of energy intake. One RCT in individuals with type 2 diabetes compared glycemic control outcomes for SFAs versus MUFAs with the total fat remaining equal 62 and did not find a significant difference between diets for postprandial glucose or insulin response.

An intriguing idea for future research is that lowering SFA or increasing MUFA may increase glucagon-like peptide-1 activity, thereby reducing postprandial TG.

Three blinded RCTs in individuals with type 2 diabetes 63 — 65 found that omega-3 fatty acid supplements may increase FBG by a small but significant amount. However, a fourth blinded RCT 66 observed a significant decrease in A1C with supplementation compared with controls.

In the meta-analysis by Hartweg et al. One of these studies 64 also found a decrease in the HDL-3 fraction with EPA supplementation. One study 73 focused on whole-food omega-3 intake in a prospective cohort and found that baseline marine omega-3 fatty acid intake was inversely associated with TG.

Overall it appears that supplementation with omega-3 fatty acids does not improve glycemic control but may have beneficial effects on CVD risk biomarkers among individuals with type 2 diabetes by reducing TGs in some but not all studies.

Other benefits e. This section reviews studies examining the effects of varying the amount of daily protein intake or the source of protein intake and further distinguishes those studies that included individuals with diabetic kidney disease DKD. Durations of follow-up ranged from 4 to 16 weeks, and sample sizes were small range 12—29 participants in the higher-protein intervention.

A 5-week weight-maintenance study 25 observed a significant reduction in A1C and h glucose response and significantly lower fasting TGs on the higher- versus lower-protein eating patterns. A study of 8 weeks of weight loss followed by 4 weeks of weight maintenance 74 found no significant differences between higher- and lower-protein groups for A1C; however, significant decreases in serum total cholesterol and LDL cholesterol were observed on the higher- versus lower-protein diets.

Another study 23 and a 1-year follow-up of the Parker and colleagues study 24 reported no significant differences between groups in glycemic control or CVD risk factors. Four parallel RCTs examined the effects of lower versus usual protein intake on glycemic control, CVD risk factors, and renal function markers in individuals with types 1 and 2 diabetes and microalbuminuria 75 , macroalbuminuria 76 , 77 , or both One study blinded physicians to diet treatment Two studies achieved lower protein intakes of 0.

None of the studies found significant differences between groups for glycemia, CVD risk factors, or renal function glomerular filtration rate [GFR], various measures of proteinuria.

At the levels of protein achieved, no reduction in serum albumin was noted. Two meta-analyses addressed protein restriction in people with diabetes and micro- and macroalbuminuria. The meta-analysis by Pan et al.

These four studies 75 — 78 are included above. Four RCTs examined the effects of source of protein intake on glycemic control, CVD risk factors, and renal function in individuals with type 2 diabetes and microalbuminuria 81 or macroalbuminuria 82 — Durations of follow-up ranged from 4 weeks to 4 years, and sample sizes were small 14—20 participants in the designated source interventions.

The nutrition source focus for two RCTs was soy. HDL cholesterol increased significantly and urinary albumin-to-creatinine ratio decreased significantly with soy powder versus casein powder supplementation For individuals with DKD and either micro- or macroalbuminuria, reducing the amount of protein from normal levels does not appear to alter glycemic measures, CVD risk measures, or the course of GFR.

For individuals with DKD and macroalbuminuria, changing the source of protein to be more soy based may improve CVD risk measures but does not appear to alter proteinuria.

The high MUFA content of most tree nuts and peanuts and high PUFA content of walnuts and pine nuts lends support to the investigation of potential effects of nuts on glycemic control and CVD risk in individuals with diabetes.

Since , three RCTs and two reports from the NHS have been published on this topic 30 , 85 — This may take some trial and error. To lose weight, find a ratio you can stick with, focus on healthy foods and eat fewer calories than you burn. Our experts continually monitor the health and wellness space, and we update our articles when new information becomes available.

VIEW ALL HISTORY. Eating fewer calories than you burn is needed to lose weight. Here is a detailed guide that explains how to count calories for weight loss.

Calories matter, but counting them is not at all necessary to lose weight. Here are 7 scientifically proven ways to lose fat on "autopilot. Protein is incredibly important for your health, weight loss, and body composition.

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Nutrition Evidence Based The Best Macronutrient Ratio for Weight Loss. Medically reviewed by Amy Richter, RD , Nutrition — By Gavin Van De Walle, MS, RD — Updated on February 6, Calories vs Macros Calorie vs Calorie Diet Quality Macro Ratio Bottom Line When it comes to weight loss, research shows that how much you eat may matter more than the amount of carbs, fat, and protein in your diet.

Calorie Intake Matters More Than Macronutrient Ratio for Fat Loss. Share on Pinterest. The Importance of Diet Quality. The Best Macronutrient Ratio Is the One You Can Stick To. The Bottom Line. Excessive or deficient macronutrient intake is associated with adverse health outcomes in the general population and may originate from inadequate consumption of an individual macronutrient or an overall excessive or deficient energy intake.

Sufficient protein intake is essential for health and well-being at all ages. In children, adequate protein intake is essential for growth and development. The repercussions of protein malnutrition range from mild to life-threatening, depending on individual characteristics, the degree of deficiency, and the presence of exacerbating factors such as concurrent illness and insufficient energy intake.

Consequences of protein deficiency can be unspecific and include stunting, anemia, intrauterine growth restriction, impaired nutrient absorption, cardiovascular dysfunction, muscle wasting, immunodeficiency, hypoalbuminemia, edema, loss of bone mass, skin atrophy, and impaired hormone production, particularly of growth and thyroid hormones and insulin.

Classical forms of protein deficiency include marasmus, a protein-calorie deficiency, and kwashiorkor, a protein deficiency within an energy-sufficient diet. Marasmus is characterized by dry and wrinkled skin, extreme muscle wasting, loss of subcutaneous fat, and atrophy of internal organs with preserved histology.

Kwashiorkor is characterized by severe edema that is more pronounced in the hands and feet, wasting, diarrhea, irritability, skin depigmentation, fatty liver, and organ dysfunction.

While these conditions are usually described as distinct entities, there is significant clinical overlap, and many patients exhibit features of both conditions, termed marasmic-kwashiorkor. Unlike protein deficiency, which is common in the general population, lipid and carbohydrate deficiencies are extremely rare.

However, a low intake of lipids or carbohydrates can have important implications for health and disease. Strictly speaking, carbohydrates are not considered essential nutrients because the body can synthesize carbohydrates endogenously and use alternative energy sources.

Moreover, the absence of dietary carbohydrates does not result in a characteristic deficiency. However, nutrient-dense sources of carbohydrates, such as whole grains, fruits, and vegetables, contain nutrients and bioactive compounds associated with many health benefits and are unavailable in other food sources.

The human body can also endogenously synthesize various forms of lipids. However, in contrast to carbohydrates, lipids are an essential macronutrient. They must be sufficient in the diet to provide essential fatty acids and allow for the absorption of fat-soluble vitamins.

Findings suggestive of essential fatty acid deficiency include dermatitis, alopecia, liver dysfunction due to mitochondrial dysfunction, and increased susceptibility to infections. While macronutrients are not directly toxic, even when consumed in large amounts, chronic macronutrient overconsumption can be a cause for concern.

Chronic excess energy intake from carbohydrates and fats has been associated with weight gain, obesity, type 2 diabetes, hypertension, and other adverse health outcomes associated with increased adiposity. However, excess consumption of a single macronutrient in a calorie-appropriate diet implies that another macronutrient is being displaced to remain within calorie limits.

If chronic, this practice can also result in nutrient deficiencies. There has been considerable debate concerning the safety of high-protein diets, with particular attention to kidney function. Some authors have proposed that high-protein diets may lead to kidney damage and disease.

This concern was initially proposed after scientists discovered that high-protein diets cause a compensatory increase in the glomerular filtration rate GFR , originally thought to result from nephron loss. Macronutrient requirements can vary widely between individuals depending on several factors such as age, body weight, physical activity levels, and associated medical conditions.

In general, recommendations for macronutrient intake and distribution provide a great deal of flexibility. Provided that essential macronutrient and micronutrient needs are covered and appropriate calorie numbers are consumed, macronutrient distribution may be adapted to fit individual preferences and goals.

Adequate protein intake is key in preventing age-related loss of muscle strength and muscle mass sarcopenia. In other words, the RDA is the minimal amount needed to prevent a deficiency in most people. While an optimal lower limit for protein intake has not been established, some authors have reported significantly lower age-related decreases in skeletal muscle with a daily protein intake of 1.

Unlike protein, dietary recommendations for carbohydrates and lipids are more flexible. With obesity rates on the rise, efforts have been made to characterize the role of macronutrient intake in promoting weight gain and facilitating weight loss.

Historically, carbohydrates and fats have been theorized to be responsible for the rising prevalence of obesity, and low-carbohydrate and low-fat diets have been proposed as promising solutions. Because obesity is a complex condition that stems from excess total energy intake rather than any individual macronutrient, focusing interventions on macronutrient restriction is unlikely to be effective.

Moreover, studies have shown that public health interventions aiming to reduce sugar intake can result in a paradoxical increase in fat consumption. A multitude of conditions and situations can influence nutritional requirements.

In the case of macronutrient intake, special consideration is warranted at certain life stages and for people with certain medical conditions.

Such scenarios include childhood, pregnancy, athletes, and people with specific medical conditions like chronic kidney disease or liver disease. Due to the metabolic demands of growth and development, children and adolescents have higher relative energy and protein requirements than adults.

Pregnancy and lactation greatly increase metabolic demands for energy and protein to cover the needs of the gravida while supporting fetal development. In the context of disease, protein intake is important in managing various conditions, such as chronic kidney disease CKD and chronic liver disease CLD.

In patients with CKD, protein intake must be carefully balanced to prevent malnutrition while delaying disease progression. Protein restriction may be warranted in patients with a high risk of progression to end-stage kidney disease, while low-risk patients may benefit from a higher protein intake.

However, studies have shown that protein restriction in patients with CLD compromises their nutritional status and results in worse outcomes than normal-protein diets. For this reason, current guidelines do not recommend protein restriction. While healthcare professionals need to know about these special situations and their influence on nutrient requirements, patients with special requirements should be referred to a specialist for optimal and timely nutritional management.

Meeting nutrient requirements is essential at all stages of life. However, promoting a holistic perspective that ensures nutritional adequacy through a whole-food approach is imperative.

Healthy sources of carbohydrates include legumes, whole grains, fruits, and vegetables. Dietary proteins can be found in both plant-based and animal-based food sources.

Animal-based sources of protein include meat, dairy, fish, and eggs. An essential amino acid cannot be synthesized endogenously and must be obtained through the diet.

In contrast, plant-based foods tend to be labeled as incomplete proteins due to the frequent lack of one or more essential amino acids. However, it is important to note that protein and essential amino acid needs can be met through plant-based sources by combining various food sources with different amino acid profiles, which offsets the lack of an essential amino acid in a given food source.

Dietary fats can be obtained from various sources and are classified as monounsaturated, polyunsaturated, saturated, and trans-unsaturated fats. Unsaturated fats can be found in fish, plant oils, nuts, and seeds.

Saturated fats are more common in animal foodstuffs, and trans-unsaturated fats are found in processed vegetable oils. Unsaturated fats are associated with decreased cardiovascular risk and mortality, while trans-unsaturated and saturated fats are associated with adverse effects on health.

A healthy dietary pattern containing nutrient-dense food sources in adequate amounts is fundamental for health maintenance and disease prevention at all stages of life. Macronutrients are nutrients the body needs in large quantities to support energy needs and meet physiologic requirements.

Per USDA recommendations, nutrient requirements should be met primarily through whole foods and beverages rather than supplements and include a variety of foods from different groups, including fruits, vegetables, legumes, whole grains, nuts, and seeds, while limiting the intake of added sugars and saturated fats.

Deficient or excessive consumption of macronutrients may lead to adverse health effects and should be avoided. In particular, chronic excess calorie intake and weight gain should be avoided to reduce the risk of obesity and its associated conditions.

Optimal protein intake should be ensured to minimize the risk of sarcopenia, especially among aging populations. Maintaining an adequate diet and macronutrient intake is key for maintaining health throughout the lifespan. Yet only a small portion of the population adheres to current dietary recommendations.

Healthcare practitioners, nurses, dietitians, and other healthcare professionals should work together to identify patients with suboptimal dietary patterns and provide timely nutritional advice to prevent the development of adverse health outcomes associated with macronutrient deficiencies or excess intake.

Physicians, advanced practice providers, and nurses can identify and manage conditions associated with excess or deficient macronutrient intake during routine care and provide timely referrals to a dietitian.

Dietitians can further assess patients' nutritional status, provide individualized dietary advice, and adjust as needed. Behavioral therapists can help patients improve their relationship with food, optimize dietary adherence, and identify barriers to behavioral change.

Healthcare providers should follow evidence-based nutrition guidelines and promote balanced and sustainable dietary patterns that fit individual needs and preferences.

Patients should be educated on the importance of maintaining an adequate dietary pattern that includes sufficient protein, fats, and carbohydrates from nutrient-dense sources without exceeding calorie limits. Disclosure: Santiago Espinosa-Salas declares no relevant financial relationships with ineligible companies.

Disclosure: Mauricio Gonzalez-Arias declares no relevant financial relationships with ineligible companies. This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

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Thank you for visiting nature. You are using a Ddistribution version with limited support for CSS. Macronurrient obtain distriution best experience, we Weight management for sports you use a more Macronutrient Balancing for Sports Performance Sugar consumption and gut health date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. The relative contributions of different aetiological factors to obesity remain to be fully defined, although the importance of different dietary macronutrients, physical activity patterns and genetics is acknowledged. Improved understanding of the mechanisms of weight gain and obesity might lead to comprehensive and efficient strategies to prevent and ameliorate this global epidemic.

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A healthy diet is also about choosing a variety of wholesome foods that deliver a range of other nutrients, including vitamins and minerals. Sharon Liao is a freelance writer and editor specializing in health, nutrition, and fitness.

She lives in Redondo Beach, California. This article was reviewed for accuracy in July by Angela Goscilo, MS, RD, CDN , manager of nutrition at WeightWatchers®. The WW Science Team is a dedicated group of experts who ensure all our solutions are rooted in the best possible research.

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Prescription Medication. Do I Qualify? Find a Workshop. A diet with a balanced distribution of macronutrients—meaning fat, protein, and carbs—may help reduce disease risk and support lasting weight loss. By Sharon Liao. Published October 1, Biomarkers of nutrient bioactivity and efficacy: a route toward personalized nutrition.

Hendriks, H. Use of nutrigenomics endpoints in dietary interventions. Hesketh, J. Personalised nutrition: how far has nutrigenomics progressed? Download references. and S. are grateful to CIBERobn CIBER of Physiopathology of Obesity, Instituto de Salud Carlos III, 28, Madrid, Spain for financial support of their research.

Nutrition and Toxicology Research Institute Maastricht NUTRIM , Maastricht University Medical Centre, P. Box , Maastricht, MD, Netherlands. Department of Nutrition, Exercise and Sports NEXS , Faculty of Science, University of Copenhagen, Rolighedsvej 26, Frederiksberg C, DK, Denmark.

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declares that he has acted as a consultant for Nutrition and Santé, is a member of the advisory boards of Food for Health and International Life Sciences Institute Research Foundation, is a member of review panels for INRA French National Institute for Agricultural Research , MRC Medical Research Council and NordForsk, and that he is employed part-time as Corporate Scientist in Nutrition at Dutch States Mines.

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Skip to main content Thank you for visiting nature. nature nature reviews endocrinology review articles article. Subjects Metabolism Nutrigenomics Nutrition Obesity. Key Points The relative contributions of different aetiological factors to obesity remain to be fully defined, although the importance of different dietary macronutrients, physical activity patterns and genetics is acknowledged Improved understanding of the mechanisms of weight gain and obesity might lead to comprehensive and efficient strategies to prevent and ameliorate this global epidemic Studies of the roles of individual macronutrients in weight management are needed to define whether diets of similar calorific content but different composition differentially affect energy yield and utilization Experts generally agree that weight-loss strategies should aim to not only reduce body fat in the short term, but also achieve long-term maintenance of healthy body weight The study of gene—nutrient interactions and the differential effects of genotype on macronutrient utilization might identify personalized strategies for effective weight loss and maintenance of healthy body weight.

Abstract A large number of different dietary approaches have been studied in an attempt to achieve healthy, sustainable weight loss among individuals with overweight and obesity.

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This review focuses on literature that has been published since that date 5. This systematic review will be one source of information considered when updating the current ADA Nutrition Position Statement 4.

Other systematic reviews and key research studies that may not be included in this review will also be considered. When attempting to tease out the role of macronutrients from other dietary and lifestyle factors, two critical components of MNT—energy balance and a healthful eating pattern—are not addressed.

While both are critical components in the management of diabetes as well as the secondary prevention of complications and promotion of health, these topics are beyond the scope of this particular review.

The following questions are addressed in this review:. What aspects of macronutrient quantity and quality impact glycemic control and cardiovascular disease CVD risk in people with diabetes? How do macronutrients combine in whole foods and eating patterns to affect health in people with diabetes?

Is there an optimal macronutrient ratio for glycemic management and CVD risk reduction in people with diabetes? Certain terms relevant to nutrition therapy in the management of diabetes were not included in the search terms.

These terms include trans fatty acids, monounsaturated fatty acids MUFAs , polyunsaturated fatty acids PUFAs , sucrose, and sugars. The literature search was limited to articles published in English, and multiple publications from the same study were limited to the primary study results article.

Studies included in the systematic review were conducted in people already diagnosed with diabetes; conducted in outpatient ambulatory care settings; contained a sample size of 10 or more participants in each study group; and one of the following study designs: clinical trials controlled and randomized controlled [RCT] , prospective observational studies, cross-sectional observational studies, or case-control studies.

Studies were excluded if they were published before January or after October ; were conducted in acute care or inpatient settings, in women with gestational diabetes, children under 2 years of age, or individuals without diabetes or at risk for diabetes; had less than 10 participants in any study group; were studies lasting only 1 or 2 days; or were not in one of the study designs previously listed.

Weight loss is a confounder in some of the studies and is noted in Supplementary Table 1. This information can be found in Supplementary Table 1.

An initial PubMed database search found studies after excluding by title and abstract review. An additional 18 studies were found from bibliography review. Of these, 72 studies were excluded for not meeting inclusion criteria.

The most common reasons for exclusion were for results not applicable to the research question, not published in a major journal, small sample size, review articles, and duplicates. Isolating the effects of dietary macronutrient composition on glycemic control and CVD risk is difficult due to confounding, especially by weight loss and medication changes.

Furthermore, altering the level of one macronutrient affects the proportion of other macronutrients, making it difficult to isolate the true exposure. Additional study design issues include the difficulty blinding study participants, investigators, and clinicians.

These issues were addressed by reporting the entire macronutrient composition of diet approaches and potential confounders when this information was available.

Based on the studies in this systematic review, the following definitions are used:. These definitions are not all-inclusive e. The comparison diets referred to as conventional or traditional throughout this review are higher in carbohydrate than those generally consumed by people with diabetes.

Eleven clinical trials examined the effects of lowering total carbohydrate intake on glycemic control in individuals with diabetes. The carbohydrate content goal of the diet was very low in 7 studies 10 — 16 and moderately low in 4 studies 17 — All studies included adults with type 2 diabetes, duration of follow-up ranged from 14 days to 1 year, and sample sizes ranged from 10 to 55 participants per study group.

Designs included two feeding trials one crossover clinical trial and one RCT 10 , 18 and nine outpatient nutrition counseling interventions two single-arm clinical trials, one crossover RCT, and six parallel RCTs 11 — 17 , 19 , A1C decreased with a lower-carbohydrate diet in 6 of 10 studies in which it was measured 10 , 14 — 17 , Three RCTs found no statistically significant changes in A1C with a very-low-carbohydrate diet 11 — 13 and one found no difference with a moderately low—carbohydrate diet Other glycemic parameters such as fasting blood glucose FBG , h blood glucose, h insulin 10 , and fasting insulin levels 18 decreased significantly, and insulin sensitivity increased significantly 10 on the lower-carbohydrate diet.

Glucose-lowering medications were decreased for individuals following the lower-carbohydrate diet 10 — 12 , 14 , 17 or were more frequently decreased than in the comparison diet Each of the 11 clinical trials reported at least one serum lipoprotein.

The most notable results were that HDL cholesterol increased significantly more in one very-low-carbohydrate diet group 16 and two moderately low—carbohydrate diet groups 18 , 20 compared with the higher-carbohydrate control diet.

Also, triglycerides TGs decreased more in one moderately low—carbohydrate diet group 20 compared with the higher-carbohydrate control diet.

Otherwise, mean changes in serum lipoproteins resulting from a lower-carbohydrate diet were typically beneficial but occurred without a comparison arm or were not statistically greater than the comparison arm.

In studies reducing total carbohydrate intake, markers of glycemic control and insulin sensitivity improved, but studies were small, of short duration, and in some cases were not randomized or had high dropout rates.

Serum lipoproteins typically improved with reduction of total carbohydrate intake but, with the exception of HDL cholesterol, were not statistically greater than with the comparison diet.

The contribution of weight loss to the results was not clear in some of these studies. Seven clinical trials and two meta-analyses examined the effects of moderate- or high-carbohydrate diets on glycemic control in patients with type 2 diabetes 21 — 28 or type 1 diabetes Durations of follow-up ranged from 5 to 74 weeks, and sample sizes of participants completing follow-up ranged from 10 to All seven studies were RCTs and analyzed participants according to treatment assignment.

Only one of the studies blinded participants to diet treatment 22 , and none blinded the outcome assessors. Four studies found no significant differences in glycemic control when comparing moderate- or high-carbohydrate diets with conventional diets 21 — The intent-to-treat analyses, however, showed no significant differences between groups.

Two meta-analyses compared lower-carbohydrate diets with conventional carbohydrate diets 27 , Of the 19 studies reviewed in the article by Kodama et al. The seven studies are included in this review. Six of the seven interventions reviewed above reported lipoproteins.

Three studies 22 — 24 found no significant differences between comparison diets. RCTs presenting information on moderate- and high-carbohydrate diets are diverse in terms of fat and protein content as well as length of study.

Only two RCTs found significant differences in A1C between groups, with one study finding significantly lower A1C with the higher-carbohydrate diet only in a subgroup analysis, and the other study finding significantly lower A1C with the lower-carbohydrate diet.

In terms of CVD risk factors, LDL cholesterol improved more with a high-carbohydrate diet in one study, whereas two studies found TGs improved more with a lower-carbohydrate diet.

The meta-analyses almost all studies used were published before found that the average low GI was 65, and the average high GI was 82, but both had wide ranges. This is further complicated by the two bases glucose or white bread that have been used to determine GI values for individual foods.

Five RCTs 19 , 31 — 34 compared lower-GI diets with higher-GI diets in individuals with type 2 diabetes. Duration of follow-up ranged from 4 to 6 weeks and sample sizes were small in four studies 12—14 in three of the studies, 45 in the other , whereas the fifth study lasted for 1 year and included subjects in the analysis Results were mixed with two studies finding A1C was significantly reduced with the lower-GI versus higher-GI diets 32 , 33 and the others finding no differences in glycemic measures 19 , 31 , Three parallel RCTs 16 , 35 , 36 compared a lower-GI diet with diets other than those designated as higher GI high-fiber diet, traditional diet, very-low-carbohydrate diet in individuals with type 2 diabetes.

Compared with a higher-fiber diet, the lower-GI diet decreased A1C and FBG significantly When the lower-GI weight-loss diet was compared with a conventional weight-loss diet 36 , both groups lowered A1C significantly with no significant differences between groups.

The lower-GI diet reduced A1C significantly less than the very-low-carbohydrate diet A study in youth with type 1 diabetes 37 found that individuals advised to follow a lower-GI diet had significant reductions in A1C compared with individuals advised to follow a carbohydrate-exchange diet, despite the fact that the mean GI for the two diet groups was not significantly different.

Two studies indicated that education can change food selection and may 38 or may not 39 affect the GI of the diet.

Three meta-analyses 40 — 42 evaluated GI. Anderson et al. These three studies from the meta-analyses are included above 32 , 33 , Mixed results were found for the five RCTs comparing low-GI with high-GI diets for lipoprotein measures.

Two studies found a significant reduction in total cholesterol 31 , 32 with one of the two reporting a significant reduction in LDL cholesterol and apolipoprotein apoB 32 for the lower-GI diet. The other three studies found no significant changes between groups 19 , 33 , Results were mixed in studies comparing lower GI with other dietary approaches.

Significantly increased HDL cholesterol was found with lower GI versus higher-cereal fiber but no significant differences in other measured CVD risk markers Total cholesterol was significantly lowered with both a lower-GI diet and a traditional diet without significant differences between groups; however, LDL cholesterol was significantly higher with the lower-GI diet versus the traditional diet A very-low-carbohydrate diet reduced TGs significantly and increased HDL cholesterol significantly compared with a lower-GI, reduced-calorie diet, with no significant differences in total cholesterol and LDL cholesterol A cross-sectional study 43 of men with type 2 diabetes described a statistically significant trend toward decreasing adiponectin with increasing quintiles of GI.

In general, there is little difference in glycemic control and CVD risk factors between low-GI and high-GI or other diets. A slight improvement in glycemia may result from a lower-GI diet; however, confounding by higher fiber 16 , 33 , 35 must be accounted for in some of these studies.

Furthermore, standardized definitions of low GI need to be developed and low retention rates on lower-GI diets must be addressed 16 , 33 , The Institute of Medicine defines dietary fiber as consisting of nondigestible not digested in the human small intestine carbohydrates and lignin that are intrinsic and intact in plants Quantification of the dietary fiber in research studies may be on the basis of dietary recommendations, grams per 1, kcals, the amount added, or its distribution within the study population.

Functional fibers are beyond the scope of this systematic review, and thus functional fiber and total fiber were not included in this review. Durations of follow-up ranged from 4 to 12 weeks, and sample sizes were small 12—60 participants in the fiber intervention.

In general, these studies support the idea that fiber supplements may improve postprandial glycemia; however, little improvement in A1C was observed. Two dietary counseling RCTs examined the effects of dietary fiber as part of an intervention diet.

In the first study, individuals on the low-GI diet showed small but significant improvements in A1C after controlling for weight loss, fiber, or carbohydrate and FBG at 6 months compared with those on the high—cereal fiber diet Markers of improved insulin sensitivity adiponectin or inflammation C-reactive protein [CRP], tumor necrosis factor-R2 [TNF-R2] were assessed in three cross-sectional reports 43 , 53 , Higher cereal or fruit fiber intakes were associated with higher levels of adiponectin 43 , 53 , 54 and lower levels of CRP 53 , 54 or TNF-R2 53 , Another cross-sectional study 55 , using a 3-day weighed diet, found that individuals with type 2 diabetes and the metabolic syndrome had significantly lower intakes of total dietary fiber specifically whole grains and fruits than those with diabetes but without the metabolic syndrome; however, there were no associations between fiber intake and A1C or FBG in either group.

The time period of the meta-analysis by Anderson et al. All RCTs described above assessed lipoproteins 35 , 45 — Four studies found no significant difference between intervention and control groups for these measures 46 , 48 — One study found that psyllium vs.

cellulose supplements 45 significantly improved HDL cholesterol; a second study found that a higher-fiber, lower-fat, and lower-GI diet versus a lower-fiber, higher-fat diet produced significantly lower total cholesterol, LDL cholesterol, and HDL cholesterol In addition, one cross-sectional study found that a diet higher in soluble fiber from whole grains was associated with a lower TG level In contrast, Jenkins et al.

The majority of the reviewed evidence indicates that adding fiber supplements in moderate amounts 4—19 g to a daily diet leads to little improvement in glycemia and CVD risk markers. Eight clinical trials examined low-fat eating patterns 21 — 23 , 29 , 57 — One trial studied adults with type 1 diabetes 29 , whereas the rest studied adults with type 2 diabetes; duration of follow-up ranged from 3 days to 74 weeks, and sample sizes of participants completing follow-up ranged from 10 to 48 participants per study group.

All eight trials were outpatient nutrition counseling interventions: one single-arm 57 , two crossover RCTs 22 , 29 , and five parallel RCTs. A1C decreased with a low-fat diet in one of seven studies in which it was measured In that study 58 , intensive dietary advice for a lower-fat, moderate-carbohydrate, higher-fiber diet in adults with poor glycemic control significantly decreased A1C compared with the control group.

Insulin sensitivity by euglycemic-hyperinsulinemic clamp improved in the lower-fat diet compared with the conventional diet in one study Two weight-loss RCTs by the same group compared meal replacements versus conventional diets 59 , 60 and found significant reductions in FBG over short durations with meal replacements.

One study carried out for 12 months showed no persistent difference in FBG between groups, although significantly more subjects in the meal replacement group had reductions in diabetic medications In addition to the information from the clinical trials, a cross-sectional study 61 found that higher-fat intake correlated with significantly higher A1C.

Of the seven studies that measured CVD risk factors, only one had significant findings. The cross-sectional study 61 found that higher-fat intake correlated with higher levels of total cholesterol and LDL cholesterol as well as coronary artery calcium.

Lowering total fat intake infrequently improved glycemic control or CVD risk factors in clinical trials involving individuals with diabetes. Lowering fat intake in individuals with diabetes may improve total cholesterol and LDL cholesterol but may also lower HDL cholesterol.

For this review, the type of fat refers to the proportion of total energy from a specific fatty acid or fatty acid category. Categorization may be on the basis of the number of, the location of, or the configuration of double bonds.

Saturated fatty acids SFAs may be assessed based on distribution within the study population or recommended dietary levels. Omega-3 fatty acids are usually evaluated as milligrams per day or as a distribution within the population rather than on the basis of percent of energy intake.

One RCT in individuals with type 2 diabetes compared glycemic control outcomes for SFAs versus MUFAs with the total fat remaining equal 62 and did not find a significant difference between diets for postprandial glucose or insulin response. An intriguing idea for future research is that lowering SFA or increasing MUFA may increase glucagon-like peptide-1 activity, thereby reducing postprandial TG.

Three blinded RCTs in individuals with type 2 diabetes 63 — 65 found that omega-3 fatty acid supplements may increase FBG by a small but significant amount. However, a fourth blinded RCT 66 observed a significant decrease in A1C with supplementation compared with controls.

In the meta-analysis by Hartweg et al. One of these studies 64 also found a decrease in the HDL-3 fraction with EPA supplementation. One study 73 focused on whole-food omega-3 intake in a prospective cohort and found that baseline marine omega-3 fatty acid intake was inversely associated with TG.

Overall it appears that supplementation with omega-3 fatty acids does not improve glycemic control but may have beneficial effects on CVD risk biomarkers among individuals with type 2 diabetes by reducing TGs in some but not all studies.

Other benefits e. This section reviews studies examining the effects of varying the amount of daily protein intake or the source of protein intake and further distinguishes those studies that included individuals with diabetic kidney disease DKD.

Durations of follow-up ranged from 4 to 16 weeks, and sample sizes were small range 12—29 participants in the higher-protein intervention. A 5-week weight-maintenance study 25 observed a significant reduction in A1C and h glucose response and significantly lower fasting TGs on the higher- versus lower-protein eating patterns.

A study of 8 weeks of weight loss followed by 4 weeks of weight maintenance 74 found no significant differences between higher- and lower-protein groups for A1C; however, significant decreases in serum total cholesterol and LDL cholesterol were observed on the higher- versus lower-protein diets.

Another study 23 and a 1-year follow-up of the Parker and colleagues study 24 reported no significant differences between groups in glycemic control or CVD risk factors.

Four parallel RCTs examined the effects of lower versus usual protein intake on glycemic control, CVD risk factors, and renal function markers in individuals with types 1 and 2 diabetes and microalbuminuria 75 , macroalbuminuria 76 , 77 , or both One study blinded physicians to diet treatment Two studies achieved lower protein intakes of 0.

None of the studies found significant differences between groups for glycemia, CVD risk factors, or renal function glomerular filtration rate [GFR], various measures of proteinuria.

At the levels of protein achieved, no reduction in serum albumin was noted. Two meta-analyses addressed protein restriction in people with diabetes and micro- and macroalbuminuria.

The meta-analysis by Pan et al. These four studies 75 — 78 are included above. Four RCTs examined the effects of source of protein intake on glycemic control, CVD risk factors, and renal function in individuals with type 2 diabetes and microalbuminuria 81 or macroalbuminuria 82 — Durations of follow-up ranged from 4 weeks to 4 years, and sample sizes were small 14—20 participants in the designated source interventions.

The nutrition source focus for two RCTs was soy. HDL cholesterol increased significantly and urinary albumin-to-creatinine ratio decreased significantly with soy powder versus casein powder supplementation For individuals with DKD and either micro- or macroalbuminuria, reducing the amount of protein from normal levels does not appear to alter glycemic measures, CVD risk measures, or the course of GFR.

For individuals with DKD and macroalbuminuria, changing the source of protein to be more soy based may improve CVD risk measures but does not appear to alter proteinuria. The high MUFA content of most tree nuts and peanuts and high PUFA content of walnuts and pine nuts lends support to the investigation of potential effects of nuts on glycemic control and CVD risk in individuals with diabetes.

Since , three RCTs and two reports from the NHS have been published on this topic 30 , 85 — All studies analyzed participants according to treatment assignment, and two studies blinded participants to treatment.

Two RCTs 85 — 87 tested the effects of walnuts against general advice or advice to consume specific PUFA-rich foods. There were no significant differences among groups for glycemic control.

The Food and Nutrition Board of the Institutes of Medicine Weight management for sports recently released energy, macronutrient, and fluid distrigution, which Energy Replenishment Methods for the distribuyion time that active individuals have unique nutritional needs. This is a preview of subscription content, log in via an institution to check access. Rent this article via DeepDyve. Institutional subscriptions. Institute of Medicine: Dietary Reference Intakes. Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride.

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