If material is Personalized weight management included in the Cancer prevention properties Creative Commons licence and your intended weigh is Personalized weight management permitted by statutory regulation or exceeds the permitted use, you wweight need to obtain Perwonalized directly Managfment the Enhance skin texture holder. Our list of most effective weight loss programs covers healthier eating and exercise, but what if you want to go a step further? SMOKE is a binary indicator of smoking and contains two levels: Yes smoke and No never smoke. On this page Our picks Our criteria How they compare How to choose FAQ Bottom line. Figure 1. That's why we are dedicated to creating customized plans that are designed just for you.

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Diet-to-Go meals are delivered ready-to-eat, which means all you have to do is heat them up for a few minutes in the oven or microwave. Our SI Showcase team member, Ellie Baldini, tested Diet-to-Go. She liked that the service provided fresh produce, but wished the food was more flavorful.

The Mediterranean diet also has benefits that can relieve PCOS symptoms, as well as support heart health, blood sugar levels and weight loss. Diet-to-Go bills and delivers on a weekly schedule. The weekly cost depends on your meal choices and frequency.

You can cancel or pause your subscription at any time with no fees. Read our Diet-to-Go Review for more information on this healthy meal delivery service. Related Post: Best Weight Loss Programs for Women. There are over different meals, and all of the food is designed by a team of dietitians and nutritionists for effective weight loss for people with diabetes.

The Diet-to-Go Balance-D plan is designed to help control blood sugar levels, lower the risk of heart disease and help you lose weight at the same time. Every meal has a limited amount of carbs, calories and fat, all of which can affect blood glucose.

The weekly cost for your Diet-to-Go subscription depends on which meal you choose. You can cancel or pause your deliveries at any time with no extra fees. WW, formerly known as Weight Watchers, aims to help you achieve sustainable, long-term weight loss by tracking points and staying within your daily point budget.

The program starts by asking you a series of questions about yourself and your lifestyle. Then, its "PersonalPoints Engine" creates a personalized food list and point budget. Points are assigned per food based on protein, fiber, fats, sugar and calories. What you can eat and how much you can eat depends on your daily point budget.

No foods are off-limits, but WW discourages eating highly processed foods or foods high in added sugar and saturated fats like candy, sugary drinks, chips and processed meats. Your membership grants you access to the WW app, which includes healthy habit tracking : think exercise, water consumption and sleep.

WW is our pick for the best weight loss plan with community support, thanks to its robust social network that provides advice and encouragement during your weight loss journey. According to registered dietitian and health education coordinator Sara Schoen, what makes WW unique is that it focuses on community by offering in-person and virtual group support.

Members can join a minute group workshop every week, in-person or online, to communicate with coaches and fellow members about their roadblocks, challenges and victories. Studies have shown that community support can be helpful for diet adherence.

WW also acknowledges that social factors like family, culture and celebrations impact our diets and eating habits, so it offers a guide to dining out.

Check out our WW Review for more information on this weight loss program. Does it work? According to a study published in the Annals of Internal Medicine, WW participants are more likely to lose weight than those who received weight loss education alone.

WW has been around for over four decades, which means there are large amounts of anecdotal evidence saying it works. There are also small studies that suggest WW is over twice as effective as dieting on your own.

At the end of the day, weight loss is different for everyone, but WW has a long history of success. WW often runs promotions, but be sure to read the fine print regarding startup and early termination fees.

All memberships include access to the WW app. Related Post: Noom vs WW: Which Weight Loss Program is Right for You? Nutrisystem is our pick for the best weight loss program with personalized meal plans because the service delivers pre-cooked meals to your door, making portion control and tracking calories easier.

This diet helps with weight loss by using a combination of high-protein meal plans and lower-glycemic nutrition to control hunger.

We like that you can select a plan with meals that cater to your lifestyle, age or dietary restrictions, such as diabetes-friendly and vegetarian. Your meals are delivered every four weeks, and you can repeat the program as many times as you want. Doing this is meant to help you learn how to eat a balanced diet on your own and create a lifestyle change to maintain your weight loss after you finish the program.

Our tester, Molly Stout, found success with Nutrisystem but said the meals get repetitive after a few months. Read our Nutrisystem Review for more information on this weight loss program. According to a study published in the Annals of Internal Medicine, Nutrisystem participants are more likely to lose weight in three months than those who just receive weight loss education.

Another study suggests that using commercial weight loss plans like Nutrisystem can result in greater long-term weight loss than simply dieting on your own. Related Post: Best Weight Loss Programs for Men. Nutrisystem offers some variety in its plans, which affects the cost.

Studies back the effectiveness of ketogenic diets, especially for people who are seeking not just to lose weight but to also improve other health indicators, like controlling their blood sugar and managing cholesterol.

But many of us have experienced a lifetime of being told that high-fat foods are the enemy, so the idea of adopting a high-fat, high-protein diet can feel like too much to chew. Thankfully, an app like Keto Cycle can make the idea of embracing the keto lifestyle a lot easier to digest.

The sign-up process for Keto Cycle takes important personalization factors into consideration, including your sex, how physically active you are, your familiarity with keto, how much time you have for meal prep and your food preferences. From there, you get a fully furnished meal plan with loads of keto recipes.

In an assessment of 11 studies, researchers found that people on a ketogenic diet lost more weight than those on a low-fat diet. Not only that: People who followed a very low-carb ketogenic diet also had lower levels of fat in their blood and lower blood pressure.

So all in all, ketogenic seems to be a fantastic option as weight loss program. The tricky part is compliance with the diet, which is where an app like Keto Cycle steps in. Keto Cycle furnishes many services to add on as well, including an exercise plan and monthly protein powder deliveries.

If you've struggled with the exercise portion of a weight loss program, the Future app may be able to help. To start, you'll fill out a questionnaire that asks about your previous workout experience, current limitations and preferences.

The app will also ask questions about what you're looking for in a coach such as gender, energy level, intensity and more.

It'll then suggest a few coaches to choose from. You can either pick one of these or peruse the complete list of coaches to make your own choice. Once you're matched with a coach, they'll schedule an introductory video call to get acquainted and learn more about your goals.

Then, they'll create a customized workout plan for you. You'll receive an updated plan every week with new exercises and explanations on how to do them with the correct form.

You'll be able to reach out to your coach at any time for clarification or to check in about how you're handling the workouts. If you're not sure about your form, you can even send videos of you doing the moves for feedback.

This ensures that you're doing the moves correctly so you can stay injury-free and motivated. Boxplots showing adherence data for the high-carbohydrate diet a , c , e and the high-fat diet b , d , f.

There were 4 adverse or serious adverse events in total. Two adverse events occurred among fat-responders on a high-carbohydrate diet unrelated to the study , and there were 2 serious adverse events 1 among fat-responders on a high-carbohydrate diet, 1 among fat-responders on a high-fat diet that required hospitalization unrelated to study.

We found no difference in WL between individuals on the genotype-concordant vs. genotype-discordant diet. Further, insulin levels or HOMA-IR were not associated with WL. Food cravings tended to decrease among carbohydrate-responders on a high-fat diet compared to those on a high-carbohydrate diet.

Finally, fat-responders on a high-carbohydrate diet tended to decrease resting SBP. The lack of significant and clinically meaningful differences in WL ~0. In contrast to the well-conducted Gardner et al. study non-significant difference in WL of 0.

carbohydrate-responsive genotypes based on 3 SNPs that were predictive in a preliminary retrospective analysis 8 , we determined fat- or carbohydrate-responsive genotypes based on an algorithm involving 10 SNPs. Supported by a recent-meta-analysis 8 trials with 91 SNPs and 63 genetic loci 11 , our results suggest that with the current ability to genotype individuals as fat or carbohydrate-responders, there is no evidence that genotype-concordant diets result in greater WL.

We did not limit recruitment to achieve equal numbers of participants in each genotype-diet group, and this distribution reflects the prevalence in our population.

Future studies with larger samples should verify if this uneven distribution between carbohydrate-responders and fat-responders is representative of the general population and further investigate the potential effect on WL among carbohydrate-responders.

Future studies could also consider assigning participants to genotype-concordant diets without specific energy intake targets and examine the diet effects not only on WL but also on cardiovascular risk factors.

Previously, a low-carbohydrate diet without energy intake target resulted in greater improvements in body composition, blood lipids, and estimated year coronary heart disease risk compared to a low-fat diet It would be insightful to investigate whether genotype plays a role in cardiovascular risk reduction following a low-carbohydrate vs.

low-fat diet without calorie restriction. Fasting insulin levels and HOMA-IR did not predict WL. However, these studies involved relatively small sample sizes, and findings of the influence of insulin sensitivity 21 and insulin secretion 9 , 14 on WL via a low-fat vs.

a low-carbohydrate diet are inconsistent. WL can reduce food cravings, particularly for foods restricted on specific diets 22 , contributing to the hypothesis that food cravings are a conditioned expression of hunger due to stimuli paired with eating certain foods Consequently, cravings can be reduced by eliminating or restricting the intake of craved foods.

This hypothesis is partially supported by our results as, among carbohydrate-responders, cravings tended to decrease for high-carbohydrate foods on the high-fat diet.

Nonetheless, cravings also decreased modestly for high-fat foods, which is to be expected as the amount of all foods was restricted, and cravings for specific foods correlate with each other Among fat-responders, a high-carbohydrate diet tended to decrease resting SBP. Nonetheless, these individuals had the highest mean SBP of the 4 genotype-diet groups at baseline.

Thus, this effect could be explained, in whole or partially, by regression to the mean. Also, all 4 genotype-diet groups had relatively well-controlled blood pressure, leaving little room for improvement through dietary changes, making the non-significant improvements potentially more meaningful.

This trial has some limitations. First, the genetic algorithm to classify individuals as fat- or carbohydrate-responders was created based on published literature 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , However, these mostly retrospective studies generally had modest sample sizes, and some of the genotype × diet interactions, which may be false positives, have not been independently replicated.

Further, WL is determined by multiple modifiable and non-modifiable e. More comprehensive knowledge of the role of genetics in WL is needed and should be obtained from genome-wide association studies; however, the sample size and experimental design required to generate that essential information are beyond reach at this time.

Additional limitations of the present study include the relatively small sample size, single-center design, and short time frame.

A longer timeframe 6—month follow-up may have increased the amount and differential weight loss between diets. A larger sample size might have also allowed for detecting differences in clinically important secondary outcomes such as changes in body fat and SBP.

Further, we did not provide meals in this study, which may have affected dietary adherence high-fat vs. However, this choice was made by design, as our study was designed as a pragmatic effectiveness trial with real-world conditions rather than an efficacy trial. Additionally, the adherence data albeit limited suggests that diet adherence was overall satisfactory.

Further, when assessing a potential effect modification by insulin resistance status, using an oral glucose tolerance test AUC or INS rather than HOMA-IR to quantify insulin resistance might have been a better option, as HOMA-IR has limited sensitivity due to its reliance on fasting insulin and glucose levels and it does not reflect differences between tissues e.

Additionally, the assessment of percent body fat via BIA is a limitation as BIA does not provide information on body fat distribution. Therefore, in our study, participants may have responded better to their assigned diets regardless of their genotype matching, obscuring the specific nutrigenomics effects.

In conclusion, in this week RCT, there was no difference in WL between individuals with an a priori determined fat- or carbohydrate-responsive genotype on a high-carbohydrate vs.

high-fat diet with specific energy targets and the same level of energy restriction across diets. The Personalized Nutrition Study POINTS, ClinicalTrials. gov identifier: NCT was a week, single-site, parallel-arm WL trial that was approved by the institutional review board IRB FWA of the Pennington Biomedical Research Center PBRC, Baton Rouge, LA.

Participants were enrolled between October 7, and September 8, Participants were identified a priori as carbohydrate-responders and fat-responders based on their combined genotypes at 10 genetic variant loci and randomized to either a high-carbohydrate or high-fat diet, yielding the following groups: 1 fat-responders receiving a high-fat diet, 2 fat-responders receiving a high-carbohydrate diet, 3 carbohydrate-responders receiving a high-fat diet, and 4 carbohydrate-responders receiving a high-carbohydrate diet.

Participants were recruited from the community. Eligible participants were 18—75 years old, had a BMI of Finally, a genetic profile indicating a predisposition to respond favorably to a high-carbohydrate or high-fat WL diet based on specific SNPs see below was required.

in the last 3 months, being pregnant or breastfeeding, conditions, diseases, or medications that affect body weight or metabolism or could affect risk or study completion, and a genotype indicating a predisposition to respond favorably to neither or both of the specified diets. The study included 1 orientation visit, 2 clinic visits one before and one after the intervention , and weekly intervention sessions.

Carbohydrate- and fat-responders were identified a priori based on their combined genotypes at the following genetic variants: 1 FGF21rs 25 , 2 TCF7L2rs 26 , 43 , 3 IRS1rs 28 , 4 APOA5rs 30 , 31 , 44 , 5 PLIN1rs 27 , 32 , 6 APOA2rs 29 , 33 , 7 FTOrs 34 , 35 , 8 PPARGrs 36 , 9 GIPRrs 37 , and 10 GYS2rs The genetic information was accessed via the raw data from the genealogy tests.

Initially, only 6 SNPs were included and pilot tested, and the scoring criteria were then modified as few participants were deemed carbohydrate- or fat-responders.

The original and updated scoring criteria, including a specific example for 1 SNP, are provided in the Supplementary Methods, including Supplementary Tables 1 and 2. To facilitate meal plan adherence when preparing or selecting meals, the meal plans included a list of ingredients and their amounts for all meals of each day breakfast, lunch, dinner, and 1 daily snack and instructions for meal preparation and participants were provided a food scale.

Baseline energy requirements were calculated with Mifflin-St. The PBRC biostatistics department created the randomization sequence using SAS 9. REDCap used strata for the inaction of genotype and gender.

To ensure a relatively equal baseline BMI between the 4 genotype-diet groups, a randomization scheme was devised that adjusted for BMI, gender, and genotype. Gender and genotype were used as strata, while BMI was used in an a-priori-created randomization equation.

Within each stratum, this equation used block sizes of 6 for females and 4 for males at the start of the study and ended with block sizes of 4 and 2, respectively, to ensure relative balance of group assignments.

Block sizes were assigned during the study by the biostatistician with access only to information about the enrolment progress percent enrolled. Interventionists administering intervention sessions were blind to genotype patterns but not diet type.

Participants were only informed of their genotype carbohydrate- or fat-responder once they completed the study. The 12 weekly intervention group sessions were diet-specific and had a different focus each week Supplementary Material.

Participants were provided a body weight scale and encouraged to weigh daily throughout the intervention and to send pictures of their weights to their interventionist before each intervention session.

With very few exceptions, the first intervention session was conducted in person. Due to the COVID pandemic, almost all subsequent sessions were conducted virtually via webinar Microsoft Teams.

At W0 and W12, fasting body weight and waist and hip circumference were measured in the PBRC outpatient clinic. Clinic weights were also measured at all intervention visits though not fasting weights.

Fasting serum glucose and insulin were measured at W0, and HOMA-IR was used to quantify insulin resistance. Appetitive traits were measured with the Eating Inventory EI 46 , food cravings were measured with the Food Craving Inventory FCI 24 , and hedonic food preferences were measured with the Food Preference Questionnaire FPQ 47 at W0 and W12 see Supplementary Methods for details on outcome materials.

Data for these questionnaires were collected and managed using REDCap tools. The Diet Personalization Survey Supplementary Methods was completed at W0 and W12, as well as during the intervention session at W6, and the Intervention Satisfaction Survey Supplementary Methods was conducted at W Data for these surveys were collected and managed using REDCap tools.

As stated above, participants were provided with a kitchen scale and could precisely weigh all ingredients specified in the meal plans for the foods consumed at home. Additional foods that were consumed were weighed and added as well. Adherence to the macronutrient content of the assigned diets was assessed for three 7-day periods throughout the intervention W4, W8, W The distribution of variables was evaluated by visual examination and the Shapiro-Wilk test.

The primary outcome was weight change kg at 12 weeks. All other measures were secondary endpoints. We used linear mixed models to determine if changes in outcome variables differed among diets.

Covariates in the models included baseline value of the outcome, sex, and race. The mixed-effect model accounted for the correlation of the subject over time, and least-square means based on the estimate from the mixed-effect model were used to test for differences in weight change between diets.

To evaluate whether baseline insulin levels and HOMA-IR needed to be included as covariates, their effects on WL were tested using a linear mixed model, adjusted for diet group and other known covariates. Neither baseline insulin levels nor HOMA-IR was significantly associated with WL; hence these variables were not included as covariates.

The significance level was set to 0. Multiple testing adjustment was performed for secondary outcomes using the Holm-Bonferroni method All analyses were conducted using SAS Windows version 9. The present study planned to obtain data from up to participants in total, and we aimed to complete 32 participants per genotype-diet group participants in total though we did not limit recruitment to achieve equal numbers of participants in each group.

We hypothesized that participants on a genotype-concordant diet would lose more weight than those on a genotype-discordant diet. Based on previous studies 49 , 50 , we assumed a standard deviation for between-group differences in weight change of 2.

To detect a 2. Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. All of the data needed to recapitulate the analysis found within this study can be found in the manuscript, figures and supplementary information.

Source data are provided with this paper. Due to privacy reasons, de-identified data from the study cannot be shared publicly but will be available from the corresponding author christoph. hoechsmann tum. de immediately following the publication of the paper upon reasonable request. The study protocol and statistical analysis plan will also be available.

Fryar, C. Prevalence of overweight, obesity, and severe obesity among adults aged 20 and over: United States, — through — Kopelman, P. Health risks associated with overweight and obesity. PubMed Google Scholar. Tremmel, M. Economic burden of obesity: a systematic literature review.

PubMed PubMed Central Google Scholar. Hruby, A. The epidemiology of obesity: a big picture. Pharmacoeconomics 33 , — Shai, I. et al. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet.

CAS PubMed Google Scholar. Sacks, F. Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates. CAS PubMed PubMed Central Google Scholar.

Johnston, B. Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. Dopler Nelson, M. Genetic phenotypes predict weight loss success: the right diet does matter: Paper presented at: joint conference of the 50th Cardiovascular Disease Epidemiology and Prevention and Nutrition, Physical Activity, and Metabolism; March 2—3, , San Francisco, CA.

Gardner, C. Effect of low-fat vs low-carbohydrate diet on month weight loss in overweight adults and the association with genotype pattern or insulin secretion: The DIETFITS Randomized Clinical Trial. ADS CAS PubMed PubMed Central Google Scholar. Qi, L. Low-fat vs low-carbohydrate diets and weight loss.

Bayer, S. Associations between genotype—diet interactions and weight loss—a systematic review. Cornier, M. Insulin sensitivity determines the effectiveness of dietary macronutrient composition on weight loss in obese women. McClain, A. Adherence to a low-fat vs.

low-carbohydrate diet differs by insulin resistance status. Diabetes Obes. Pittas, A. While premium subscriptions offer additional features, these apps not only rank as the best weight loss apps free of charge but also offer comprehensive features for effective weight management.

Rapid weight loss can lead to a range of issues including muscle loss, nutritional deficiencies, and can negatively impact your overall health. A healthier and more sustainable approach to weight loss involves setting realistic goals, focusing on gradual, steady weight loss — typically 0.

This can be achieved through a balanced diet, regular physical activity, and lifestyle changes that promote overall well-being. Remember, weight loss is a personal journey and what works for one person might not be suitable for another.

Research in suggests that weight loss apps can be effective for weight loss and may even help improve other health markers like blood sugar and blood pressure. Still, keep in mind that the research is limited and inconclusive , with some studies showing no benefit at all.

In turn, these factors could make weight loss apps less effective for certain populations. Finally, keep in mind that while calorie counting can be effective for weight loss, it can also increase the risk of disordered eating in some people. These behaviors may indicate a disordered relationship with food or an eating disorder.

Disordered eating and eating disorders can affect anyone, regardless of gender identity, race, age, socioeconomic status, or other identities. You can feel empowered to talk with a qualified healthcare professional, such as a registered dietitian who specializes in disordered eating , if dieting is becoming obsessive or intense.

Still, keep in mind that while they have several possible benefits, weight loss apps can be:. Many apps offer a free version or free trial, and we recommend experimenting with a few to see which one, if any, works best for you. Our experts continually monitor the health and wellness space, and we update our articles when new information becomes available.

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Thank you for visiting mnaagement. Personalized weight management are using a browser Personalkzed with limited support for CSS. To obtain Perosnalized best experience, we Beta-carotene and healthy pregnancy you use a more Personalized weight management to date Personlaized or mansgement off compatibility managemenr in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Weight loss WL differences between isocaloric high-carbohydrate and high-fat diets are generally small; however, individual WL varies within diet groups. Genotype patterns may modify diet effects, with carbohydrate-responsive genotypes losing more weight on high-carbohydrate diets and vice versa for fat-responsive genotypes. We investigated whether week WL kg, primary outcome differs between genotype-concordant and genotype-discordant diets. Managemeent one-on-one welght Personalized weight management that you deight Bulimia nervosa symptoms Perdonalized and support you need Fasting and insulin sensitivity make lasting changes. This New Managemenh — Choose You! The Bulimia nervosa symptoms Way is a personalized one-on-one approach to help you not only lose weight, but also boost your self-confidence and guide you to a healthier and happier version of yourself. Discover the personalized weight loss plan that will help you achieve the results you desire. We offer expert guidance, customized meal plans, and the support of a dedicated team of professionals who genuinely care about your success. Take the first step towards a healthier, happier you!