Obesity is often a multi-factorial condition (2) therefore the answer isn’t as simple as correcting a Calorie In-Calorie Out imbalance (CICO). Many obese people have unhealthy relationships with eating/drinking and also need someone to assist to exam their habits and possible triggers. While behavior is a major factor to be addressed, the latest research on the pathophysiology of obesity suggests the CICO model is flawed. This research and clinic trials show that what has been named the Carbohydrate-Insulin Model of Obesity (CIM) better explains not only the weight gain but explains the difficulty obese people have losing weight using a CICO methodology (16) as CICO doesn’t address the root cause, insulin resistance.

Obese patients that develop metabolic syndrome, in the majority of cases, and for the most part, are not suffering from a complete lack of self control and/or are lazy. While habits, behavior and relationships with food/drink must be addressed, unhealthy, obese individuals in most cases hyper produce insulin and through years of poor choices have developed insulin resistance. This obese phenotype when persistently exposed to triggers of insulin will, with high probability develop pathologies of insulin resistance; hypertension, dyslipidemia, central adiposity, and hyperglycemia. Lifestyle modifications, including dietary changes, to reduce the triggers of insulin, once implemented, will address the physiological issues of the disease and will often push these associated conditions into remission. One of the primary modifications is a habitual diet of real, whole food, with little to no processing, with a very-low to low glycemic load and very-low to low insulin load. While educating the patient on this way of eating will address the physiology of obesity counseling to address habits, behaviors and relationships with eating and drinking may need long term counseling and accountability.

Calorie reduction leads to hunger and hunger can only be overcome in the short term. Long-term calorie restriction can also permanently decrease resting metabolic rate contributing to metabolic issues (20). While most obese individuals are inactive and may over-eat many suffering with obesity have a hormonal regulatory disorder complicating their condition. One should consider whether the habits are driving the weight gain or the hormonal disorder is helping to drive the hunger and inactivity. Primarily the hormonal complication involves hyperinsulinemia, satiety regulation  and conditions associated with metabolic syndrome. When obesity is complicated with hyperinsulinemia and insulin resistance this hormonal response to foods must be addressed. This hormonal response to poor food choices is responsible for metabolic maladaptation and must be addressed with a proper nutritional intervention if long term success is to be achieved. (1) Some obese patients are not insulin resistant but this phenotype is in the minority. Well Formulated Ketogenic Diets (WFKD), along with low carbohydrate diets, which address hyperinsulinemia, have proven to be highly effective, safe and are accepted in the standard of care for weight loss and in the treatment of other conditions such as type II diabetes (2, 3, 16, 19). Possibly more important  in the discuss of weight loss is the fact that compared to a calorie reduction dietary approach low carbohydrate approach out performs CICO in not only weight loss but also drastically improves metabolic disease risk markers (3, 17, 19). Below is a list of nine different meta-analysis’ showing that low carbohydrate diets out perform low fat, calorie restrictive diets both in the short and long term (6-15).

Providers that identify obesity in association with the risk factors for metabolic syndrome should counsel patients on the need to change as soon as any of these conditions present and refer patients to a specific structured lifestyle modification program focusing on insulin resistance (18). Providers should know that most patients will need to be supported during this modification process. A few words in clinic by the  provider with a handout or two will usually be unsuccessful in motivating or helping the patient be successful (19). Providers must make a strong statement regarding the need to change in an effort to fully inform them as to their current health trajectory (4) and use primary care-referable resources to help support patients during the change process if reversal of these conditions is to be expected (5). Recent research also suggests referral to a “specific” program rather than general comments about the need to lose weight are far more effective in helping the patient (21).

Here at Restore Medical Fitness Center we have been highly effective helping people not only lose weight but correct other markers of metabolic health. Patients enrolled in our 12 week program that began with a BMI equal to or greater than 30 have lost 7.6% of their body weight in the first 12 weeks and have continued to lose weight. During this first 12 weeks they have also decreased their Total Cholesterol to HDL ratio 44.1%, decreased triglycerides 40.6%, decreased resting blood pressure 15.2% and 17%, decreased their waist circumference (marker of visceral fat) 6.8% and increased their MET maximum fitness 21.8%. They also saw a reduction in hypertension and glucose control medication. n=238

Recently, we have begun a very-low glycemic load and insulinogenic dietary approach for type II diabetics. We have real-time monitoring and communication with patients using HIPAA compliant texting services and medical management of medications via telehealth. The results are nothing short of amazing with all patients drastically reducing glucose control medications while lowering blood glucose readings.  Lipid panels have shown drastic improvements with increased HDL and drastically reduced triglycerides while hypertension medication has also been reduced and in many cases eliminated in this group of patients. Weight loss is much better than above mentioned results and patient satisfaction with the approach is extremely high. n=13


1 – Knell, et. al., Mayo Clinic Proceedings, 2018, – Long-Term Weight Loss (LTWL) and Metabolic Health in Adults Concerned with Maintaining or Losing Weight: Findings from NHANES

Discussion: Study findings indicate that, among a population-based sample of historically overweight or obese individuals who aimed to lose or maintain weight, successful LTWL (>5%) is associated with a more favorable metabolic disease risk profile. Results additionally indicate that although a clear incremental pattern was not apparent, reaching the 15% LTWL threshold is associated with even lower odds for metabolic syndrome and a lower metabolic risk z score. When considering the individual components of metabolic syndrome, all levels of LTWL were associated with a lower likelihood of dyslipidemia (ie, elevated triglyceride levels and lower HDL-C levels). Interestingly, LTWL was not associated with hypertension. This finding requires further study considering the well-established beneficial effects of weight loss on hypertension.

Conclusion: In sum, the current study uses clinical measures of cardiometabolic risk as well as historical information on weight change from a large, population-based sample of adults to assess the relationship between LTWL and metabolic health among those attempting to lose or maintain their weight. Study findings suggest that higher levels of LTWL might provide more protection against metabolic disease risk, though further longitudinal research is needed to substantiate these findings. Future research should continue to examine strategies leading to LTWL to reduce cardiovascular disease risk factors and subsequent morbidity and mortality.

2 – Obesity Medicine Association Obesity Algorithm – Obesitymedicine.org, 2016-2017

3 – Hallberg, et.al., Diabetes Therapy, Feb 2018 – Effectiveness and Safety of a Novel Care Model for the Management of Type 2 Diabetes at 1 Year: An Open-Labeled, Non-Randomized, Controlled Study

Conclusions: This study demonstrated that a T2D intervention combining technology-enabled continuous remote care with individualized care plans encouraging nutritional ketosis can significantly reduce HbA1c, medication use, and weight within 70 days [23], and that these outcomes can be maintained or improved through 1 year. Most intervention participants with HbA1c reported at 1 year achieved glycemic control in the sub-diabetes range with either no medication or the use of metformin alone. Related health parameters improved including blood pressure, lipid-lipoprotein profile, inflammation, and liver function. Ongoing research will determine the continued sustainability, effectiveness, and safety of these behavioral and metabolic changes.

4 – Washburn, P.J., International Journal of User-Driven Healthcare, 6, 1, 2016 – Health Ballistics: Multiple Reference Point Informed Probability Theory

Conclusion: If an individual is afflicted with a chronic disease and does not know the realistic end point of their current health trajectory, they will never be fully ready, willing, motivated or able to make an informed, reliable, accurate and precise healthy behavioral decision in their current state of partially health informed reality. Alteration of health reality is accomplished by health informing the individual about the negatives of unhealthy behavior and the positives of healthy behavior.

5 – Curry et. al., Annals of Internal Medicine, 160, 6, 2014 – Behavioral Counseling Research and Evidence-Based Practice Recommendations: U.S. Preventive Services Task Force Perspectives

Conclusion: Behavioral counseling interventions are important primary and secondary preventive care strategies, and the USPSTF is committed to developing and disseminating recommendations to ensure that effective interventions achieve the broadest reach into health care delivery. Effective synthesis and incorporation of evidence for behavioral counseling interventions into USPSTF recommendations is challenged by gaps in the current evidence base. The behavioral science community can better align primary care–based intervention studies with the key questions that guide the development of evidence-based recommendations. This commentary joins other voices calling for careful attention to study populations and the pragmatic aspects of intervention protocols in the design and dissemination of research, for greater consistency in key behavioral measures, and for further research that links behavior change to health outcomes.

6- Hession et al. August 2008, https://doi.org/10.1111/j.1467-789X.2008.00518.x, Systematic review of randomized controlled trials of low-carbohydrate vs. low-fat/low-calorie diets in the management of obesity and its commorbidities. 

7 – Castañeda-González et al. Nov-Dec 2011. https://doi.org/10.1590/S0212-16112011000600013, Effects of low carbohydrate diets on weight and glycemic control among type 2 diabetes individuals: a systemic review of RCT greater than 12 weeks. 

8 – Santos et al. August 2012. https://doi.org/10.1111/j.1467-789X.2012.01021.x, Systematic review and meta-analysis of clinical trials of the effects of low carbohydrate diets on cardiovascular risk factors. 

9 – Bueno et al. October 2013. https://doi.org/10.1017/S0007114513000548, Very-low-carbohydrate ketogenic diet v. low-fat diet for long-term weight loss: a meta-analysis of randomized controlled trials. 

10 – SacknerBernstein et al. October 2015, https://doi.org/10.1371/journal.pone.0139817, Dietary Intervention for Overweight and Obese Adults: Comparison of Low-Carbohydrate and Low-Fat Diets. A Meta-Analysis. 

11 – Tobias et al. October 2015. https://doi.org/10.1016/S2213-8587(15)00367-8, Effect of low-fat diet interventions versus other diet interventions on long-term weight change in adults: a systematic review and meta-analysis.

12 – Mansoor et al. December 2015, https://doi.org/10.1017/S0007114515004699, Effects of low-carbohydrate diets v. low-fat diets on body weight and cardiovascular risk factors: a meta-analysis of randomized controlled trials. 

13 – Fan et al. June 2016. http://www.ijcem.com/files/ijcem0023504.pdf, Effects of low carbohydrate diets in individuals with type 2 diabetes: systematic review and meta-analysis. 

14 – Meng et al. July 2017, http://dx.doi.org/10.1016/j.diabres.2017.07.006, Efficacy of low carbohydrate diet for type 2 diabetes mellitus management: A systematic review and meta-analysis of randomized controlled trials. 

15- Yancy, Jr., W.S. et. al., December 2005, Nutrition & Metabolism,  https://nutritionandmetabolism.biomedcentral.com/articles/10.1186/1743-7075-2-34, A low-carbohydrate, ketogenic diet to treat type 2 diabetes

Results: Twenty-one of the 28 participants who were enrolled completed the study. Twenty participants were men; 13 were White, 8 were African-American. The mean [± SD] age was 56.0 ± 7.9 years and BMI was 42.2 ± 5.8 kg/m2. Hemoglobin A1c decreased by 16% from 7.5 ± 1.4% to 6.3 ± 1.0% (p < 0.001) from baseline to week 16. Diabetes medications were discontinued in 7 participants, reduced in 10 participants, and unchanged in 4 participants. The mean body weight decreased by 6.6% from 131.4 ± 18.3 kg to 122.7 ± 18.9 kg (p < 0.001). In linear regression analyses, weight change at 16 weeks did not predict change in hemoglobin A1c. Fasting serum triglyceride decreased 42% from 2.69 ± 2.87 mmol/L to 1.57 ± 1.38 mmol/L (p = 0.001) while other serum lipid measurements did not change significantly.

16- Ebbeling et.al., The British Medical Journal – BMJ 2018;363:k4583 – Effects of a low carbohydrate diet on energy expenditure during weight loss maintenance: randomized trial

Conclusions: Consistent with the carbohydrate-insulin model, lowering dietary carbohydrate increased energy expenditure during weight loss maintenance. This metabolic effect may improve the success of obesity treatment, especially among those with high insulin secretion.

17 – Harvey, et. al., Peer Journal – February 2019 – Low-carbohydrate diets differing in carbohydrate restriction improve cardiometabolic and anthropometric markers in healthy adults: A randomized clinical trial

Conclusions: Low-carbohydrate, high-fat diets have a positive effect on markers of health. Adherence to the allocation of carbohydrate was more easily achieved in MCD, and LCD groups compared to VLCKD and there were comparable improvements in weight loss and waist circumference and greater improvements in HDL-c and TG with greater carbohydrate restriction.

18 -Mechanick, J et. al., Endocrine Practice Vol 24 No. 11 November 2018 – Dysglycemia-Based Chronic Disease (DBCD): An American Association of Clinical Endocrinologists Position Statement

From the Abstract: …In this context, stage 1 represents “insulin resistance,” stage 2 prediabetes,” stage 3 “type 2 diabetes,” and stage 4 “vascular complications.” This model encourages earliest intervention focusing on structured lifestyle change. Further scientific research may eventually reclassify stage 2 DBCD prediabetes from a predisease to a true disease state. This position statement is consistent with a portfolio of AACE endocrine disease care models, including adiposity-based chronic disease, that prioritize patient-centered care, evidence-based medicine, complexity, multimorbid chronic disease, the current health care environment, and a societal mandate for a higher value attributed to good health. Ultimately, transformative changes in diagnostic coding and reimbursement structures for prediabetes and T2D can provide improvements in population-based endocrine health care.

Conclusion: Recognizing and managing prediabetes is a necessary component for an effective personalized and population-based T2D care plan. In order to substantiate this position, AACE has formulated a DBCD multimorbidity care model consisting of four distinct stages in the general context of ABCD (adiposity based chronic disease) and cardiometabolic health and specific context along with insulin resistance-prediabetes-T2D spectrum that are actionable in a preventive care paradiagm.

19- Evert, et. al., Diabetes Care – April 2019 – Nutrition Therapy for Adults with Diabetes or Prediabetes: A Consensus Report

from Page 6 – Reducing overall carbohydrate intake for individuals with diabetes has demonstrated the most evidence for improving glycemia and may be applied in a variety of eating patterns that meet individual needs and preferences. 

20 – Fothergill, et. al., Obesity (2016)24, 1612-1619. doi:10.1002/oby.2153 – Persistent Metabolic Adaptations 6 Years After “The Biggest Loser” Competition

Of the 16 “Biggest Loser” competitors originally investigated, 14 participated in this follow-up study. Weight loss at the end of the competition was (mean 6 SD) 58.36 +/- 24.9 kg (P<0.0001), and RMR decreased by 610 +/- 483 kcal/day (P =0.0004). After 6 years, 41.0 +/- 31.3 kg of the lost weight was regained (P =0.0002), while RMR was 704 +/- 427 kcal/day below baseline (P=<0.0001) and metabolic adaptation was – 499 +/- 207 kcal/day (P<0.0001). Weight regain was not significantly correlated with metabolic adaptation at the competition’s end (r= –0.1, P=0.75), but those subjects maintaining greater weight loss at 6 years also experienced greater concurrent metabolic slowing (r=0.59, P=0.025).
Metabolic adaptation persists over time and is likely a proportional, but incomplete, response to contemporaneous efforts to reduce body weight.
21 – McVay, et. al., Journal of General Internal Medicine – March 2019 – Provider Counseling and Weight Loss Outcomes in a Primary Care-Based Digital Obesity TreatmentKey Results: Participants (n = 134–141) were predominantly female (70%) and African American (55%) with a mean age of 51 years and BMI of 36 kg/m2. Participant-reported provider weight counseling was not associated with weight change. However, participants whose providers documented intervention-specific counseling at any point during the intervention (n = 35) lost 3.1 kg (95% CI 0.4 to 5.7 kg) more than those whose providers documented only general weight counseling (n = 82) and 4.0 kg (95% CI 0.1 to 7.9 kg) more than those whose providers did not document weight counseling (n = 17). Perceptions of provider empathy were associated with greater weight loss from 6 to 12 months (0.8 kg per measure unit, 95% CI 0.07 to 1.5 kg, p = .03).