Finding Clinical Practice Variables to Prevent Weight Regain After Bariatric Surgery
– Stronger control of eating 3 months later predicted successful weight loss at 1 year
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Sleeve gastrectomy (SG) is one of the most performed bariatric procedures in the U.S. and worldwide, with a frequency that is rising rapidly. However, there are multiple internal and external factors -- both challenging and obscure -- that can influence the effectiveness.
To improve the effectiveness of metabolic bariatric surgery (MBS), improved and aggressive measures are necessary to identify suboptimal responders early in the postoperative course. A recent study in aimed to assess and quantify the association between control of eating and weight loss outcomes. It is important to identify the Control of Eating (CoE), which is a validated psychometric instrument during the early postoperative period, that may predict good responders (GRs) versus poor responders (PRs) to SG at 1 year.
The participants were selected from the bariatric surgery program. The prospective longitudinal pre-post cohort study was designed as a series of surveys before and after SG. The study validated the 21-item Control of Eating Questionnaire (CoEQ) at the initial pre-surgical visit (baseline), and then at 3, 6, and 12-month timepoints after the surgical procedure. Primary outcomes were changes in selected CoE attributes, and percent of total weight loss (%TWL) 12 months post-surgery, with TWL ≥25% set as a successful target.
The CoEQ is a 21-item questionnaire designed to measure eating control over the previous 7 days and has been shown to have good psychometric properties, including internal consistency, reliability, construct, and predictive validity. The questionnaire is divided into six sections, measuring satiety, mood, general and specific cravings, and perceived ability to resist certain foods. Except for one question requiring a narrative response, the items are assessed using a 100-mm visual analogue scale (VAS). Nine of the CoEQ items were selected for analysis as they were thought to be more direct measures of CoE attributes.
The dynamics of CoEQ measures were assessed by comparing the VAS at each postoperative timepoint to the baseline. Percent TWL was defined as total weight loss at each defined timepoint (using initial weight as a reference) divided by initial weight, and TWL of 25% (25% TWL) at 12 months was used. Percent excess weight loss (%EWL) was defined as total weight loss at each time point divided by excess weight at the initial visit (initial weight -- ideal weight (corresponding to a body mass index of 25), and EWL of 50% (50%EWL) at 12 months was used as the cut-off value for adequate weight loss.
Stratification into GRs and PRs was performed based on %TWL at 12 months, with those who lost ≥25%TWL considered GRs. Diagnosis of adiposity-related complications was established according to the most up-to-date guidelines.
Dyslipidemia and obstructive sleep apnea (OSA) diagnosis were established using overnight polysomnography along with apnea-hypopnea index (AHI) ≥15 or an AHI ≥5 associated with symptoms, such as excessive daytime sleepiness, fatigue, impaired cognition, mood disorders, insomnia, hypertension, ischemic heart disease, or history of stroke.
Hypertension was defined as a systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥80 mmHg, based on an average of ≥2 careful readings obtained on ≥2 occasions, or treatment with an anti-hypertensive medication(s).
The results showed that out of 767 screened participants, 461 completed the baseline CoEQ. The first 41 patients who completed surveys at all four timepoints were included in the analysis. The mean age of the participants was 41.7±10.6 years, 80.5% (n=33) were female, and 51.2% (n=21) were Hispanic. The baseline BMI was 43.6 (35.2–66.3). The most common adiposity-related complications were dyslipidemia (78.0%, n=32), OSA (56.1%, n=23), and hypertension (41.5%, n=17).
At baseline, there were no substantial differences between GRs and PRs in all CoE attributes, except for "Desire for sweet foods," which was significantly lower among GRs (44 [0-90] vs 75 [9-100], P=0.026). At 3 months, "Difficulty to control eating" was the first and only CoE attribute to reveal a significant difference between the GR and PR groups (7 [0-50] vs 17 [5-63], P=0.006).
The aim of the study was to identify CoE attributes that may predict longer-term weight loss outcomes post-SG. Focusing on the measures capturing eating behaviors, compared with PRs, participants who lost ≥25%TWL reported greater differences compared with their baseline scores.
At 3 months, question 19 -- "Generally, how difficult has it been to control your eating?" corresponding to the "Difficulty to control eating" CoE attribute -- seemed to best predict weight loss at 1 year after surgery and distinguish between GRs and PRs. Although optimization of lifestyle behaviors with any weight loss intervention is desirable and important, biological changes after metabolic bariatric surgery may be more relevant.
Overall, eating behavior individualities post-SG are a result of a complex interplay between the restrictive nature of this procedure, neurohormonal changes affecting the gut-brain axis, and neurobehavioral factors, such as pre-prandial hedonic motivation, disinhibition, cognitive preoccupation, and coping mechanisms. The challenge, however, is that analyses of these physiologic effects are not practical, available, or useful in routine clinical settings. Obstacles in utilizing hormone levels diagnostically depend on individual variability resulting from factors such as diet, physical activity, stress, and anxiety.
In conclusion, the study demonstrates that the "Difficulty to control eating" score measured at 3 months post-SG serves as an independent early predictor of optimal response (i.e., achieving a successful total weight loss target of ≥25% at 1 year).
These results provide strong evidence and open avenues for using a convenient, validated tool to help with predicting the effectiveness of sleeve gastrectomy. Still, more research is needed to confirm the validity, generalizability, and potential for implementation as a clinical tool in current practice.
Shagun Bindlish, MD, is a Diabetologist/Internal Medicine Physician in Dublin, California; she is also Medical and Scientific Committee Chair for the American Diabetes Association of Northern California and a Wellness Champion for the American College of Physicians.
Read the study here and an interview about it here.
Primary Source
Obesity Pillars
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