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Fat intake and obesity

Fat intake and obesity

Intake of carbohydrate obesitt fiber obeaity is Fat intake and obesity useful nad for metabolic syndrome in patients with type 2 diabetes: a Metformin and cholesterol management study. All obesiry were checked for compliance with B vitamins for men selected statistical techniques. Sorry, a shareable link is not currently available for this article. Article Google Scholar Ofori-Asenso R, Agyeman AA, Laar A, Boateng D. The lipophilic index of dietary intake was computed by multiplying the intake of each fatty acid in grams by its specific melting point °Cadding the products, and then dividing by the total of fatty acid intake in grams [ 34 ].


Dr Layne Norton: The Science of Eating for Health, Fat Loss \u0026 Lean Muscle - Huberman Lab Podcast #97

Fat intake and obesity -

There is a difference of opinion about whether the percentage of dietary fat plays an important role in the rising prevalence of overweight and in its treatment once it has developed.

We believe that ample research from animal and clinical studies, from controlled trials, and from epidemiologic and ecologic analyses provides strong evidence that dietary fat plays a role in the development and treatment of obesity.

A reduction in fat intake reduces the gap between total energy intake and total energy expenditure and thus is an effective strategy for reducing the present epidemic of obesity worldwide. Read more about calcium and milk on The Nutrition Source.

The U. dairy industry has aggressively promoted the weight-loss benefits of milk and other dairy products, based largely on findings from short-term studies it has funded.

One exception is the recent dietary and lifestyle change study from the Harvard School of Public Health, which found that people who increased their yogurt intake gained less weight; increases in milk and cheese intake, however, did not appear to promote weight loss or gain.

Read more about healthy drinks on The Nutrition Source. Like refined grains and potatoes, sugary beverages are high in rapidly-digested carbohydrate. See Carbohydrates and Weight , above. These findings on sugary drinks are alarming, given that children and adults are drinking ever-larger quantities of them: In the U.

The good news is that studies in children and adults have also shown that cutting back on sugary drinks can lead to weight loss. Read more on The Nutrition Source about the amount of sugar in soda, fruit juice, sports drinks, and energy drinks, and download the How Sweet Is It?

guide to healthier beverages. Ounce for ounce, fruit juices-even those that are percent fruit juice, with no added sugar- are as high in sugar and calories as sugary sodas. Read more about alcohol on The Nutrition Source. While the recent diet and lifestyle change study found that people who increased their alcohol intake gained more weight over time, the findings varied by type of alcohol.

They eat meals that fall into an overall eating pattern, and researchers have begun exploring whether particular diet or meal patterns help with weight control or contribute to weight gain. Portion sizes have also increased dramatically over the past three decades, as has consumption of fast food-U.

children, for example, consume a greater percentage of calories from fast food than they do from school food 48 -and these trends are also thought to be contributors to the obesity epidemic. Following a Mediterranean-style diet, well-documented to protect against chronic disease, 53 appears to be promising for weight control, too.

The traditional Mediterranean-style diet is higher in fat about 40 percent of calories than the typical American diet 34 percent of calories 54 , but most of the fat comes from olive oil and other plant sources.

The diet is also rich in fruits, vegetables, nuts, beans, and fish. A systematic review found that in most but not all studies, people who followed a Mediterranean-style diet had lower rates of obesity or more weight loss.

There is some evidence that skipping breakfast increases the risk of weight gain and obesity, though the evidence is stronger in children, especially teens, than it is in adults. But there have been conflicting findings on the relationship between meal frequency, snacking, and weight control, and more research is needed.

Since the s, portion sizes have increased both for food eaten at home and for food eaten away from home, in adults and children. One study, for example, gave moviegoers containers of stale popcorn in either large or medium-sized buckets; people reported that they did not like the taste of the popcorn-and even so, those who received large containers ate about 30 percent more popcorn than those who received medium-sized containers.

People who had higher fast-food-intake levels at the start of the study weighed an average of about 13 pounds more than people who had the lowest fast-food-intake levels. They also had larger waist circumferences and greater increases in triglycercides, and double the odds of developing metabolic syndrome.

Weight gain in adulthood is often gradual, about a pound a year 9 -too slow of a gain for most people to notice, but one that can add up, over time, to a weighty personal and public health problem.

Though the contribution of any one diet change to weight control may be small, together, the changes could add up to a considerable effect, over time and across the whole society.

Willett WC, Leibel RL. Dietary fat is not a major determinant of body fat. Am J Med. Melanson EL, Astrup A, Donahoo WT. The relationship between dietary fat and fatty acid intake and body weight, diabetes, and the metabolic syndrome.

Ann Nutr Metab. Sacks FM, Bray GA, Carey VJ, et al. Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates. N Engl J Med. Shai I, Schwarzfuchs D, Henkin Y, et al. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet.

Howard BV, Manson JE, Stefanick ML, et al. Field AE, Willett WC, Lissner L, Colditz GA. Obesity Silver Spring. Koh-Banerjee P, Chu NF, Spiegelman D, et al. Prospective study of the association of changes in dietary intake, physical activity, alcohol consumption, and smoking with 9-y gain in waist circumference among 16 US men.

Am J Clin Nutr. Thompson AK, Minihane AM, Williams CM. Trans fatty acids and weight gain. Int J Obes Lond. Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB. Changes in diet and lifestyle and long-term weight gain in women and men. Halton TL, Hu FB.

The effects of high protein diets on thermogenesis, satiety and weight loss: a critical review. J Am Coll Nutr. Westerterp-Plantenga MS, Nieuwenhuizen A, Tome D, Soenen S, Westerterp KR. Dietary protein, weight loss, and weight maintenance.

Annu Rev Nutr. Furtado JD, Campos H, Appel LJ, et al. Effect of protein, unsaturated fat, and carbohydrate intakes on plasma apolipoprotein B and VLDL and LDL containing apolipoprotein C-III: results from the OmniHeart Trial.

Appel LJ, Sacks FM, Carey VJ, et al. Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial.

Bernstein AM, Sun Q, Hu FB, Stampfer MJ, Manson JE, Willett WC. Major dietary protein sources and risk of coronary heart disease in women.

Aune D, Ursin G, Veierod MB. Meat consumption and the risk of type 2 diabetes: a systematic review and meta-analysis of cohort studies. Pan A, Sun Q, Bernstein AM, et al. Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis.

Abete I, Astrup A, Martinez JA, Thorsdottir I, Zulet MA. Obesity and the metabolic syndrome: role of different dietary macronutrient distribution patterns and specific nutritional components on weight loss and maintenance. Nutr Rev.

Barclay AW, Petocz P, McMillan-Price J, et al. Glycemic index, glycemic load, and chronic disease risk—a meta-analysis of observational studies. Mente A, de Koning L, Shannon HS, Anand SS.

A systematic review of the evidence supporting a causal link between dietary factors and coronary heart disease. Arch Intern Med.

Koh-Banerjee P, Franz M, Sampson L, et al. Changes in whole-grain, bran, and cereal fiber consumption in relation to 8-y weight gain among men. Liu S, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G. Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle-aged women.

Ledoux TA, Hingle MD, Baranowski T. Truby et al Morgan et al Alcohol intake was not specified in this study.

Outcomes are depicted as mean SD change from baseline. When no absolute values were available, percentage change is shown, if available.

Not all standard deviations could be calculated. Abbreviations: DBP, diastolic blood pressure; HDL, high-density lipoprotein cholesterol; LC, low-carbohydrate diet; LF, low-fat diet; ND, no data available; SBP, systolic blood pressure; TAG, plasma triglyceride.

All studies had a low risk of bias. Intake in the LC and LF groups at different time points. Different letters a, b, c, and d show significant differences among diets and time points. Results of the meta-analysis of dietary effects on the various markers of MetS are listed in Table S1 in the Supporting Information online.

Instead of treating the LC and LF diets separately, the variation in caloric and macronutrient intakes could be viewed as a continuum. Actual fiber intake was not correlated with change in body weight.

Bubble plot of body weight change moderator analysis. The size of the bubbles represents the precision of the effect size; larger bubbles indicate greater precision. Blue bubbles represent the meta-analysis outcome for body weight vs actual intake in the LC group.

Yellow bubbles represent the meta-analysis outcome for body weight vs actual intake in the LF group. Additional analysis showed no relation between the ratio of SFA or fiber intake and DBP. Stepwise regression analysis reveals at each model the strongest correlate independent variable to the dependent variable of interest eg, DBP.

Entered independent variables: diet type LF diet with LC diet as referent , Δ body weight, Δ caloric intake, actual carbohydrate intake, and actual fat intake.

Entered independent variables: diet type LF diet with LC diet as referent , Δ body weight, Δ caloric intake, actual carbohydrate intake, and actual protein intake. Entered independent variables: diet type LF diet with LC diet as referent , Δ body weight, Δ caloric intake, actual fat intake, and actual protein intake.

Entered independent variables: actual ratio of SFA to total fat, and actual SFA intake. Entered independent variables: actual ratio of fiber to carbohydrate intake, and actual fiber intake. Abbreviations: Δ, change in; DBP, diastolic blood pressure; HDL, high-density lipoprotein; LC, low-cholesterol diet; LF, low-fat diet; SFA, saturated fat.

For HDL cholesterol, actual intake of macronutrients appeared not to be of importance. Instead, type of diet was the most important factor, with the LF diet category associated with significantly lower HDL cholesterol levels compared with the LC diet category a difference of 0.

Additional analysis also showed a correlation of SFA with HDL cholesterol, albeit small. There was no difference in meta-analysis outcome between the studies that reported SFA and all studies combined data not shown. Analyses with changes in macronutrient intakes instead of actual intake yielded similar results, as mentioned Table S3 in the Supporting Information online.

The aim of this meta-analysis was to unravel the potential roles of changes in caloric and macronutrient intake across the spectrum of studies using LC and LF diets to explain alterations in weight loss and changes in markers of MetS in participants with obesity without cardiometabolic disease.

The most important outcome of this analysis was that final, but not changes in, macronutrient intake explained reductions in markers of MetS much better than did LC vs LF dietary characterization per se, and these improvements did not necessarily depend on weight loss.

Furthermore, the effect of carbohydrate intake on markers of MetS generally mirrored those observed for effects of fat and protein intake, irrespective of diet type. However, an increase in protein intake appeared to be most relevant for reducing body weight, whereas increased fat intake and reduced carbohydrate intake appeared to be most relevant for improving markers of MetS.

Interestingly, caloric intake was not related to changes in body weight or markers of MetS. For instance, glucose was only lowered by body weight loss. DBP was affected by body weight loss and by macronutrient composition.

Reduction in SBP, however, was only correlated with body weight loss when both diets types were analyzed separately. TAG levels also appeared to be influenced differentially by the two diet types ie, body weight loss in the LF diet category appeared to improve TAG levels, whereas in the LC diet category, both body weight loss and macronutrient composition were correlated with improvement of TAG levels.

Mechanistically, such an effect may be explained by reduced hepatic TAG production in response to body weight loss, which is then accentuated by decreased carbohydrate substrate delivery.

In the upper half of the figure is shown that both diets have significant effects on the markers of MetS. The numbers represent the outcomes of the meta-analysis per diet.

In the lower half of the figure, the effect of actual macronutrient intake on markers of MetS and the effect of body weight on glucose levels are shown.

Another example refers to the influences on HDL, which was selectively increased by the LC diet category, but there also was a relation between HDL cholesterol increase and lower carbohydrate and higher fat intake irrespective of diet type.

Increases in HDL cholesterol levels may be explained by reduced TAG production and by the actions of cholesterol ester transferase. In turn, increased HDL cholesterol levels may defend against cardiac events and insulin resistance. It can then be concluded that combined weight loss and changed macronutrient composition are most efficacious in reducing markers of MetS.

Important for consideration of these results is that the actual macronutrient compositions were generally better at explaining improvements and variations in markers of MetS, than the changes in dietary macronutrient composition from baseline to end point.

The mechanisms by which the two main diet types reduce body weight and markers of MetS remain a matter of debate. Changes in body weight and changes in MetS indices were not explained by caloric intake.

It is uncertain whether body weight loss is due to an increase in energy expenditure; only six studies measured physical activity, of which one showed an increase of activity over time that was similar in both diet groups.

Alterations in macronutrient intake can also influence satiety. A correlation between weight loss and reduction of markers of MetS is in line with a plethora of weight loss studies indicating improvement of MetS indices by body-fat reduction, a factor contributing mostly to weight loss.

Favorable alterations of adipokines eg, leptin, adiponectin, resistin have been mentioned as directly affecting autonomic, metabolic, and inflammatory pathways known to underlie reduced MetS indices. One of the findings of this meta-analysis is that a higher intake of SFA was related to body weight loss and beneficial changes in markers of MetS, whereas the ratio of SFA to total fat intake was not.

Although this meta-analysis revealed several interesting insights, there are also several limitations. One of the factors that was not investigated in this meta-analysis but that could be of influence on changes in MetS markers is waist circumference, indicative of the amount of visceral fat.

Because visceral fat is important for the development of MetS, as shown by the first criterion of having central obesity, 4 it is recommended that future studies also look at changes in central obesity. Unfortunately, in this meta-analysis, only half of the studies specified change in waist circumference and even fewer specified change in fat percentage, making it difficult to draw conclusions.

Another concern in this meta-analysis is that different methods of food intake assessment were used. Because all but one study used intake from several days to assess average food intake, either by hour recall or food records, it is unlikely that one study will influence the food intake data substantially, or that one method influenced the data substantially.

In addition, the one study that used the food frequency questionnaire reported very similar intakes as the other studies, making it unlikely that this study had a large influence on the data analysis.

All in all, due to the similar methodology used, it is believed that the method of food intake assessment did not substantially influence the data. Not all studies reported SFA intake, and few reported unsaturated or polyunsaturated fatty acid intake or n-3 vs n-6 ratios.

These could be additional mechanisms that affect several metabolic pathways, including cholesterol metabolism, 58 intracellular lipid fat trafficking, 59 and cardiovascular functioning. One indication of a habitual, and thus chronic, dietary effect was shown in a Korean study in which individuals with a high fat intake or an LC intake had lower occurrence of markers of MetS.

This may be due to loss of adherence to diets. However, in this analysis, many of the same articles were found as in previously published reviews with a similar subject.

Study results suggest reducing carbohydrate intake and increasing fat and protein intake at least in the range found in the studies analyzed in this review are beneficial for improving markers of MetS in obese persons without cardiovascular disease and type 2 diabetes.

On the basis of the results of this meta-analysis, guidelines to prevent MetS may need to be reevaluated. It is clear that more long-term studies are needed with high levels of dietary adherence focused on the effects of macronutrient intake on weight loss and improvement of markers of MetS.

Dietary adherence may depend on diet type, which could influence study outcomes considerably with respect to improvements of markers of MetS.

To increase dietary adherence or prevent uneven drop-out, carbohydrate or fat preference of participants can be taken into account and evenly distributed among groups. It may also be of interest to assess mood effects during dietary interventions, because changes in mood may interfere with dietary adherence in the setting of these studies.

The rapidly expanding microbiome field will undoubtedly shed light on the roles of consumption of fiber type 65 and fat quality 66 but also protein intake 67 in cardiometabolic health of the host in relation to the efficacy of LF and LC diet types.

Author contributions. designed and conducted the research and analyzed data; extracted data were checked by G. wrote the manuscript; A. and G. had primary responsibility for final content. All authors read and approved the final manuscript. Declaration of interest.

None of the authors have a conflict of interest. The plots are weighted mean differences from individual studies horizontal axis against the standard error of the weighted mean difference vertical axis.

The solid vertical line represents the summary estimate of the weighted mean difference from baseline, derived using random-effects meta-analysis.

A Body weight change in the LC group at 6 months; B body weight change in the LF group at 6 months; C body weight change in the LC group at 12 months; D body weight change in the LF group at 12 months. LC, low-carbohydrate diet; LF, low-fat diet. Seshadri P , Iqbal N , Stern L , et al.

A randomized study comparing the effects of a low-carbohydrate diet and a conventional diet on lipoprotein subfractions and C-reactive protein levels in patients with severe obesity.

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Effects of low-carbohydrate- compared with low-fat-diet interventions on metabolic control in people with type 2 diabetes: a systematic review including GRADE assessments. Am J Clin Nutr. Effects of low-carbohydrate diets versus low-fat diets on metabolic risk factors: a meta-analysis of randomized controlled clinical trials.

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There is a difference of opinion ibtake whether the percentage Kidney bean omelette dietary fat plays oebsity important role in the rising Fa B vitamins for men overweight and in its treatment B vitamins for men it has developed. We believe that ample inrake from animal B vitamins for men clinical obesityy, from controlled trials, and from epidemiologic and ecologic analyses provides strong evidence that dietary fat plays a role in the development and treatment of obesity. A reduction in fat intake reduces the gap between total energy intake and total energy expenditure and thus is an effective strategy for reducing the present epidemic of obesity worldwide. We thus conclude that dietary fat plays a role in the development of obesity. To reduce the prevalence of obesity, there must be an increase in energy expenditure, a reduction in total energy intake, or both. Fat intake and obesity Anx Epidemiological Natural metabolism-boosting lifestyle choices suggests that obesiry high-fat diet promotes the development nad obesity and that Fat intake and obesity is a direct Fat intake and obesity between the onesity of dietary fat and the degree of obesity. The importance of this relationship has been shown in black prepubescent females, who consumed ibtake calories as fat than white females. Moreover, black adult females are heavier and have significant higher cardiovascular disease mortality rates than white females. The influence of dietary fat on food intake: An overview of animal studies had indicated that high-fat diets induce greater food intake and weight gain than high-carbohydrate diets. Several factors such as caloric density, satiety properties and post-absorbtive processing can contribute to this different response to high-fat diets. Accordingly, the satiating effects after meals with a high fat:carbohydrate ratio is less than for meals with a lower ratio.

Author: Jushakar

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