Some analyses included slightly smaller samples due to missing covariate data.aPresentation of descriptive statistics was limited to participants with AUDIT data at all 3 time points.
King WC, Chen J-Y, Mitchell JE. Prevalence of alcohol use disorders before and after bariatric surgery. JAMA. doi:10.1001/jama.2012.6147.
eTable 1. Alcohol Use Disorders Identification Test Items Before and 1 and 2 Years After Bariatric Surgery
eTable 2. Alcohol Use and Related-Problems Before and 1 and 2 years After Bariatric Surgery by Select Surgical Procedures
eFigure. Adjusted Odds Ratio of Alcohol Use Disorder (AUD) in the First or Second Postoperative Year Associated with Having AUD Preoperatively by Age
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King WC, Chen J, Mitchell JE, et al. Prevalence of Alcohol Use Disorders Before and After Bariatric Surgery. JAMA. 2012;307(23):2516–2525. doi:10.1001/jama.2012.6147
Context Anecdotal reports suggest bariatric surgery may increase the risk of alcohol use disorder (AUD), but prospective data are lacking.
Objective To determine the prevalence of preoperative and postoperative AUD, and independent predictors of postoperative AUD.
Design, Setting, and Participants A prospective cohort study (Longitudinal Assessment of Bariatric Surgery-2) of adults who underwent bariatric surgery at 10 US hospitals. Of 2458 participants, 1945 (78.8% female; 87.0% white; median age, 47 years; median body mass index, 45.8) completed preoperative and postoperative (at 1 year and/or 2 years) assessments between 2006 and 2011.
Main Outcome Measure Past year AUD symptoms determined with the Alcohol Use Disorders Identification Test (indication of alcohol-related harm, alcohol dependence symptoms, or score ≥8).
Results The prevalence of AUD symptoms did not significantly differ from 1 year before to 1 year after bariatric surgery (7.6% vs 7.3%; P = .98), but was significantly higher in the second postoperative year (9.6%; P = .01). The following preoperative variables were independently related to an increased odds of AUD after bariatric surgery: male sex (adjusted odds ratio [AOR], 2.14 [95% CI, 1.51-3.01]; P < .001), younger age (age per 10 years younger with preoperative AUD: AOR, 1.31 [95% CI, 1.03-1.68], P = .03; age per 10 years younger without preoperative AUD: AOR, 1.95 [95% CI, 1.65-2.30], P < .001), smoking (AOR, 2.58 [95% CI, 1.19-5.58]; P = .02), regular alcohol consumption (≥ 2 drinks/week: AOR, 6.37 [95% CI, 4.17-9.72]; P < .001), AUD (eg, at age 45, AOR, 11.14 [95% CI, 7.71-16.10]; P < .001), recreational drug use (AOR, 2.38 [95% CI, 1.37-4.14]; P = .01), lower sense of belonging (12-item Interpersonal Support Evaluation List score per 1 point lower: AOR, 1.09 [95% CI, 1.04-1.15]; P = .01), and undergoing a Roux-en-Y gastric bypass procedure (AOR, 2.07 [95% CI, 1.40-3.08]; P < .001; reference category: laparoscopic adjustable gastric band procedure).
Conclusion In this cohort, the prevalence of AUD was greater in the second postoperative year than the year prior to surgery or in the first postoperative year and was associated with male sex and younger age, numerous preoperative variables (smoking, regular alcohol consumption, AUD, recreational drug use, and lower interpersonal support) and undergoing a Roux-en-Y gastric bypass procedure.
As the prevalence of severe obesity increases in the United States,1 it is becoming increasingly common for health care providers and their patients to consider bariatric surgery, which is the most effective and durable treatment for severe obesity.2 Although bariatric surgery may reduce long-term mortality,3,4 and it carries a low risk of short-term serious adverse outcomes,5 safety concerns remain. Anecdotal reports suggest that bariatric surgery may increase the risk for alcohol use disorders (AUD; ie, alcohol abuse and dependence).6 However, only 3 studies have examined AUD before and after bariatric surgery.
Mitchell et al7 attempted to contact 100 patients who had received the Roux-en-Y gastric bypass (RYGB) procedure in the prior 13 to 15 years. Of 8 deaths, 1 was attributed to complications due to alcoholism. Of 78 patients who agreed to a diagnostic interview, 10 (12.8%) reported AUD prior to surgery and 6 (7.7%) reported AUD after surgery. Ertelt et al8 mailed a survey to 250 patients 6 to 10 years after RYGB was performed. Of 70 respondents, the number who had AUD symptoms was similar prior to surgery (n = 6; 8.6%) and after surgery (n = 7; 10.0%). Importantly, the majority (71.4%) who had AUD symptoms postoperatively also had AUD symptoms preoperatively. Suzuki et al9 recruited 51 of 530 targeted patients who had RYGB or laparoscopic adjustable gastric banding (LAGB) in the prior 2 or more years. Preoperative AUD was determined by retrospectively examining clinical psychiatric evaluations. Postoperative AUD was determined by diagnostic interview. No patients met the criteria for current preoperative AUD, and none who received LAGB (n = 23) reported current postoperative AUD. However, 6 of the 28 patients (21.4%) who received RYGB reported current AUD; 83.3% of whom had a history of preoperative AUD with remission at time of surgery.9 Given the limitations of these studies (low participation rate,8,9 small sample size,7-9 retrospective assessments of AUD,7-9 and different time frames7,8 and assessment methods9 for preoperative and postoperative periods), it remains unclear whether bariatric surgery influences risk of AUD.
There is evidence that some bariatric surgical procedures (ie, RYGB and sleeve gastrectomy) alter the pharmacokinetics of alcohol. Given a standardized quantity of alcohol, patients reach a higher peak alcohol level after surgery compared with case-controls10,11 or their preoperative levels.12,13 In addition, some studies have shown that patients reach peak alcohol level more quickly after surgery,11 or take more time to return to a sober state.10,12,13 Patient surveys have revealed similar changes in alcohol sensitivity following RYGB (feeling intoxicated more rapidly, after drinking less, for longer8,14), as well as more difficulty controlling alcohol intake.14 Alcohol sensitivity studies have not been performed in patients who have received LAGB, most likely because the anatomical and physiological changes from this procedure are less likely to affect alcohol absorption and metabolism.
To address limitations in the literature, this study aimed to determine whether the prevalence of AUD changed following bariatric surgery in a large multicenter observational study, comparing reported AUD in the year prior to surgery with the first and second years after surgery. In addition, this study aimed to identify independent predictors of postoperative AUD. We hypothesized that preoperative AUD and undergoing RYGB would increase the likelihood of postoperative AUD. In addition, we hypothesized that many of the factors associated with AUD in the general population15 would be associated with increased odds of postoperative AUD.
An observational study, the Longitudinal Assessment of Bariatric Surgery-2 (LABS-2) was designed to assess the risks and benefits of bariatric surgery.16 Patients who were at least 18 years old and seeking a first bariatric surgical procedure from participating surgeons at 10 centers throughout the United States were recruited between February 2006 and February 2009. All participating centers had institutional review board approval and all participants provided written informed consent. By study enrollment closure (April 2009), 2458 participants attended a preoperative research visit, which occurred after the surgery approval process was complete and within 30 days of their scheduled surgery date, and underwent a bariatric surgical procedure (RYGB, LAGB, sleeve gastrectomy, biliopancreatic diversion with duodenal switch, or banded gastric bypass) as part of clinical care (Figure).
Measures were collected independently of the surgery approval process and clinical care. Participants were informed that their responses were confidential, although the informed consent document specified that investigators could take steps to prevent serious harm (eg, if suicidal ideation was reported).
Alcohol Use and AUD. The Alcohol Use Disorders Identification Test (AUDIT)17 is a 10-item instrument developed by the World Health Organization to assess alcohol use and alcohol-related consequences in the prior 12 months, and has well-established validity and reliability.18 A total score (range: 0-40) is calculated using all 10
items (eTable 1), with a higher score reflecting greater severity of AUD. Additionally, subsets of items indicate whether respondents are positive for consumption at a hazardous level (typically consuming ≥ 3 drinks per occasion or ever having ≥ 6 drinks on 1 occasion), symptoms of alcohol dependence (not being able to stop drinking once started, needing a drink in the morning to get going, or failing to meet normal expectations because of drinking), and alcohol-related harm (not being able to remember events, feeling guilt, injuring someone, or eliciting concern from others due to drinking behavior). For this analysis, participants were categorized as having AUD symptoms (referred to as AUD throughout) if their total AUDIT score was at least 817 or if they were positive for symptoms of alcohol dependence or alcohol-related harm.
Other Measures. Anthropometric measurements were made using standardized protocols.19 Body mass index was calculated as weight in kilograms divided by height in meters squared. Sociodemographics were self-reported; race was set to missing for participants who did not self-report their race as 1 or more of the investigator-defined categories (ie, white, black, Asian, American Indian/Alaska Native, Native Hawaiian/other Pacific Islander). For this analysis, race categories other than white and black were combined as other race due to low representation (Table 1).
Perceived social support was measured using 3 domain scores (appraisal, belonging, and tangible) from the 12-item Interpersonal Support Evaluation List (ISEL-12), with higher scores (range: 4-16) indicating greater availability of support.20 Physical and mental health were measured using the norm-based physical component and mental component scores from the Medical Outcomes Study 36-item Short-Form Health Survey (SF-36), with higher scores (range: 0-100) indicating better functioning.21 Depressive symptoms were measured with the Beck Depression Inventory version 1, with a higher score (range: 0-63) indicating greater severity.22
Use of recreational drugs, smoking status, and binge eating disorder were assessed with the LABS-2 behavioral form,16 which included questions to assess all 5 criteria for binge eating disorder.23 Treatment for psychiatric or emotional problems (hospitalization or outpatient treatment in the past 12 months or current medication use) was assessed with the LABS-2 psychiatric and emotional test survey.16 Several LABS-2 forms (subsequent surgery form, surgeon's questionnaire, surgical procedure–specific forms, and health care utilization form) were used to collect information on surgical revisions, reversals, and new bariatric procedures that occurred after the initial bariatric procedure and before the 2-year assessment.
Potential selection bias was examined by comparing the preoperative characteristics of participants in the LABS-2 analysis sample (N = 1945) with those excluded (n = 513) for failure to complete the AUDIT preoperatively or during one of the postoperative time points. The Pearson χ2 test was used for categorical variables and the Wilcoxon rank sum test was used for continuous variables. Descriptive statistics of alcohol-related measures were limited to participants with AUDIT data at all 3 time points (n = 1400). Data were assumed to be missing at random (ie, the probability of missing depends only on the observed data).24 Differences in distributions of alcohol-related measures over time were tested using generalized linear mixed models and all available observations. Pair-wise comparisons (P < .05) were made between each combination of the 3 time points.
Generalized linear mixed models also were used to determine predictors of postoperative AUD, using all available observations by modeling AUD as the dependent variable over time (ie, yes or no at 1 year and yes or no at 2 years). Independent variables were selected according to the alcohol literature: sex15,25,26; age15,25,26; race15,25,26; ethnicity15,25,26; marital status15; education25,26; employment status25,26; household income27; body mass index28; ISEL-12 appraisal, belonging, and tangible support scores23; SF-36 physical and mental component scores15; Beck Depression Inventory score29; binge eating6; treatment for psychiatric or emotional problems29; smoking status26; regular alcohol consumption (ie, ≥2 times/week); recreational drug use26; surgical procedure10,11,13; and percentage of weight loss.30
The following model-fitting strategies were adopted. First, preoperative characteristics and surgical procedure were considered, with site as a random effect. Variables that were not significant in the model (ie, P ≥ .05) were removed by using backward elimination. Because backward elimination can lead to biased models and to overfitting of data, the analysis was confirmed using forward selection. Next, to assess associations between postoperative characteristics (ie, SF-36 physical and mental component scores; Beck Depression Inventory score; binge eating; treatment for psychiatric or emotional problems; ISEL-12 appraisal, belonging, and tangible support scores; smoking status; recreational drug use; and percentage of weight loss) and postoperative AUD, a separate generalized linear mixed model was fit for each postoperative characteristic, controlling for its preoperative value (data not shown). Then, postoperative characteristics that were significantly associated with postoperative AUD and their preoperative values were added to the best preoperative multivariable generalized linear mixed model. Again, backward elimination and forward selection were used for model selection; variables that were significantly related to postoperative AUD (P < .05), and their preoperative values were retained. Once the independent variables were determined, all potential interactions were evaluated.
Sample sizes for generalized linear mixed models predicting postoperative AUD reflect the exclusion of participants with indeterminate preoperative AUD (n = 4), participants who had a reversal of their surgical procedure (n = 4) or a new surgical procedure (n = 4) before their 1-year assessment, and participants missing covariate data (n = 20-97, depending on the model). Participants who had a reversal (n = 4) or new procedure (n = 5) between their first and second assessment were retained. However, their 2-year data were censored. All tests were 2-sided. Adjusted odds ratios and 95% confidence intervals are reported. Statistical analyses were performed using SAS software version 9.2 (SAS Institute Inc).
Of 2458 participants in the LABS-2 study, 2280 completed at least some self-assessment forms at the preoperative visit; 2265 completed the AUDIT. The current analysis is limited to 1945 of these 2265 participants (86%) who completed the AUDIT at the 1-year postoperative assessment (n = 1763) or 2-year postoperative assessment (n = 1582) between 2006 and 2011 (Figure). Characteristics of the LABS-2 study participants included in this analysis are shown in Table 1. Compared with those excluded from these analyses, those included were older (median: 47 years vs 42 years; P < .001), a greater percentage were white (87.0% vs 82.0%; P = .01), and a smaller percentage were smokers (2.2% vs 4.1%; P = .02) prior to surgery. There were no significant differences between groups with respect to other characteristics.
Table 2 presents select AUDIT item responses and summary measures, as well as alcohol and drug abuse treatment in the year prior to surgery and in the first and second postoperative years (all AUDIT item responses by time point are shown in
eTable 1). The number of alcoholic drinks consumed on a typical drinking day was significantly higher in the year prior to surgery and in the second postoperative year than in the first postoperative year. Alcohol consumption at a hazardous level was significantly more common prior to surgery than after surgery. However, there was a significant increase between the first and second postoperative years. Frequency of alcohol consumption and AUD (and all 3 of its components: dependence symptoms, alcohol-related harm, and AUDIT score ≥8) significantly increased in the second postoperative year compared with the year prior to surgery or the first postoperative year.
More than half (66/106; 62.3% [95% CI, 53.0%-71.5%]) of those reporting AUD at the preoperative assessment continued to have or had recurrent AUD within the first 2 postoperative years. In contrast, 7.9% (95% CI, 6.4%-9.4%; 101/1283) of participants not reporting AUD at the preoperative assessment had postoperative AUD. Nonetheless, more than half (101/167; 60.5% [95% CI, 53.1%-67.9%]) of postoperative AUD was reported by those not reporting AUD at the preoperative assessment.
Male sex, younger age, smoking, regular alcohol consumption, AUD, recreational drug use, and lower score on the ISEL-12 for belonging at the preoperative assessment and undergoing a RYGB were independently related to an increased likelihood of AUD after surgery (Table 3). The adjusted odds ratio for AUD in the second compared with the first postoperative year was 1.57 (95% CI, 1.26-1.96; P < .001). There was an interaction between preoperative AUD and age such that the adjusted odds ratio for postoperative AUD associated with preoperative AUD increased
with age (eFigure).
There were no other significant interactions between covariates. Race, ethnicity, marital status, education, employment status, household income, body mass index, SF-36 physical and mental component scores, Beck Depression Inventory score, binge eating, treatment for psychiatric or emotional problems, and ISEL-12 appraisal and tangible support scores measured preoperatively were not independently related to postoperative AUD. However, a lower postoperative SF-36 mental component score was independently related to postoperative AUD, as were postoperative smoking, recreational drug use, and treatment for psychiatric or emotional problems (Table 4).
Given the striking relationship between RYGB (vs LAGB) and AUD (Table 3 and Table 4), we repeated the analysis evaluating alcohol consumption and AUD by time point stratifying by surgical procedure (eTable 2). Frequency of alcohol consumption significantly increased in the second postoperative year compared with the year prior to surgery or the first postoperative year among participants who underwent RYGB or LAGB.
Among participants who underwent RYGB, the number of drinks on a typical drinking day was significantly lower during the first postoperative year but not the second postoperative year compared with the year prior to surgery. In addition, the prevalence of AUD significantly increased during the second postoperative year (7.0% [95% CI, 5.4%-8.6%] the year prior to surgery and 7.9% [95% CI, 6.3%-9.8%] in the first postoperative year vs 10.7% [95% CI, 8.8%-12.7%] in the second postoperative year; P < .001). However, there was neither a significant difference in the number of drinks on a typical drinking day by time among participants who underwent LAGB, nor was there a significant change in the prevalence of AUD (9.3% [95% CI, 6.3%-12.3%] prior to surgery and 5.6% [95% CI, 3.2%-8.0%] for the first postoperative year vs 7.0% [95% CI, 4.4%-9.7%] for the second postoperative year; P = .24).
Despite physician31 and patient6 concerns that bariatric surgery increases risk of AUD, to our knowledge, this is the first prospective investigation of AUD before and after bariatric surgery. This study found a significantly higher prevalence of AUD in the second postoperative year overall, and specifically after RYGB, compared with the years immediately before and following surgery. Although the increase in prevalence of AUD from 7.6% prior to surgery to 9.6% at the 2-year postoperative assessment may seem small, that 2% increase potentially represents more than 2000 additional people with AUD in the United States each year,32 with accompanying personal, financial, and societal costs.33
Participants were categorized as having AUD if they reported at least 1 symptom of alcohol-related harm or alcohol dependence, likely identifying some participants who would not meet Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) criteria for AUD.34 Thus, comparisons with prevalence rates of AUD should be made with caution. Nonetheless, in contrast to previous studies in which preoperative prevalence of AUD has been very low (0%-2%)35-39 (whether assessed as part of the surgical evaluation35-37 or independently for research38,39), the preoperative prevalence of AUD identified in this study was high (7.6%), but similar to the prevalence of AUD in the general US population (8.5%15; 6.5% adjusted to match the sex distribution of bariatric surgery patients5).
Given that current AUD is a contraindication for bariatric surgery,40,41 it is unclear whether the prevalence of AUD prior to surgery reflects prior removal of those with current AUD from the surgery pool or underreporting. There is some evidence that prevalence of lifetime AUD is higher among candidates for bariatric surgery (eg, 31%38) compared with the general US population (30%15; 24% if adjusted to match the sex distribution of bariatric surgery patients5), although results are conflicting.35-39
The significant increase in the prevalence of AUD following RYGB, but not LAGB is consistent with observational9 and pharmacokinetic10,11,13 studies. The prevalence of AUD overall, and specifically among participants who underwent RYGB, did not significantly increase until the second postoperative year, when alcohol consumption in general, and consumption at a hazardous level in particular, increased compared with the first postoperative year among participants who underwent RYGB. Therefore it was likely an increase in alcohol sensitivity following RYGB combined with resumption of higher levels of alcohol consumption in the second postoperative year, which led to the increase in AUD.
Alcohol use disorder in the year prior to surgery substantially increased the odds of AUD in the first 2 postoperative years, consistent with the chronic and recurrent nature of AUD.15 Regular alcohol consumption prior to surgery also independently increased the likelihood of postoperative AUD.
A lower sense of belonging measured by the ISEL-12 (ie, availability of people to do things with) prior to surgery was predictive of postoperative AUD, suggesting that interpersonal social support may protect against AUD. Most other predictors of AUD identified in this study (ie, male sex, younger age, smoking, recreational drug use) have been associated with AUD in the general US population.15,26
We did not find a significant association between preoperative mental health, depressive symptoms, binge eating, or past-year treatment for psychiatric or emotional problems, and postoperative AUD. However, worse postoperative mental health and postoperative treatment for psychiatric or emotional problems were significantly associated with AUD, consistent with cross-sectional studies reporting associations between psychiatric disorders and AUD.10,12,13,15 The direction of these relationships is unclear.
Percentage of weight loss was not independently related to postoperative AUD. However, results require replication. Only a few studies, to our knowledge, have investigated the inverse, with various measures of alcohol consumption, alcohol-related problems, and treatment. In a sample of 440 patients who underwent LAGB, there was a significant positive relationship between preoperative alcohol consumption and the percentage of excess weight loss at 1 year (R = 0.23; P = .005).42 In addition, 2 studies (n = 80 for RYGB43 and n = 413 for RYGB, LAGB, and sleeve gastrectomy44) found that a history of preoperative substance use disorder (including AUD and drug abuse or dependence) in remission at time of surgery predicted better postoperative weight loss, whereas 1 study (n = 207 for RYGB45) reported no significant association. In another study, among 160 patients who reported some weight regain after RYGB, those who reported someone had expressed concern about their postoperative alcohol or drug use (<10% of participants) had an increased odds (odds ratio, 12.7 [95% CI, 1.7-93.8]; P = .01) of significant regain.30 Future studies are needed to clarify if and how postoperative weight loss is related to alcohol use and AUD and vice versa.
Although safe levels of alcohol consumption have yet to be established for patients after bariatric surgery, it is concerning that 1 in 8 participants reported consuming at least 3 drinks per typical drinking day and 1 in 6 participants reported consumption at a hazardous level in the second postoperative year, given the negative effect heavy drinking may have on vitamin and mineral status,46 hepatic function,46 and weight loss.30 It is also noteworthy that alcohol or drug abuse treatment was uncommon both prior to surgery and after surgery (eg, 0.5%-0.8%; 7%-10% in those with AUD).
Major strengths of this study include the prospective design, large sample from 10 hospitals throughout the United States, and use of a validated and reliable alcohol screening tool. Some study limitations with respect to interpretation of results should be noted. First, lifetime history of AUD was not assessed. Thus, we were unable to determine whether postoperative AUD was new-onset vs recurrent. Second, while research data were collected independently of the surgery approval process and clinical care, some participants may have underreported their alcohol use due to concerns that their responses would affect their surgery eligibility or social desirability. However, the fact that 7.8% of study participants reported symptoms of AUD at their preoperative research visit indicates that participants who may have withheld symptoms of AUD during their clinical assessment to qualify for surgery did not withhold this same information when completing the AUDIT for research purposes.
Third, a safety protocol was triggered to assess the need for referral when participants reported having at least 5 drinks on a typical drinking day (per AUDIT item 2), which may have led to underreporting of alcohol consumption or problems at future (ie, postoperative) assessments. Fourth, because this study does not have a control group, we cannot rule out the possibility that reporting of AUD would increase independent of surgery 2 years after baseline assessment. However, the relationship between surgical procedure and postoperative AUD (ie, higher likelihood with RYGB vs LAGB) provides evidence that the most common surgical procedure was likely at least partially responsible for the increase in postoperative AUD at 2 years. Fifth, the study was underpowered to determine if the risk of postoperative AUD was related to race or ethnicity or less common surgical procedures.
In conclusion, the prevalence of AUD was greater in the second postoperative year than prior to surgery or in the first postoperative year; this finding appears to be driven by RYGB, which accounted for 70% of surgeries and doubled the likelihood of postoperative AUD compared with LAGB. Several factors associated with AUD in the general population, including history of AUD and regular alcohol consumption, also increased the likelihood of postoperative AUD in this bariatric surgery sample. Although preoperative AUD greatly increased the likelihood of postoperative AUD, more than half of participants with postoperative AUD did not report AUD in the year prior to surgery.
This study has important implications for the care of patients who undergo bariatric surgery. Regardless of alcohol history, patients should be educated about the potential effects of bariatric surgery, in particular RYGB, to increase the risk of AUD. In addition, alcohol screening and, if indicated, referral should be offered as part of routine preoperative and postoperative clinical care. Further research should examine the long-term effect of bariatric surgery on AUD, and the relationship of AUD to postoperative weight control.
Corresponding Author: Wendy C. King, PhD, University of Pittsburgh, 130 DeSoto St, Office 517, Pittsburgh, PA 15261 (firstname.lastname@example.org).
Published Online: June 18, 2012. doi:10.1001/jama.2012.6147
Author Contributions: Dr King had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: King, Mitchell.
Acquisition of data: Mitchell, Courcoulas, Pories.
Analysis and interpretation of data: King, Chen, Mitchell, Kalarchian, Steffen, Engel, Courcoulas, Pories, Yanovski.
Drafting of the manuscript: King.
Critical revision of the manuscript for important intellectual content: King, Chen, Mitchell, Kalarchian, Steffen, Engel, Courcoulas, Pories, Yanovski.
Statistical analysis: King, Chen.
Obtained funding: Mitchell, Courcoulas, Pories.
Study supervision: Mitchell, Courcoulas, Pories, Yanovski.
Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Courcoulas reported receiving research grants from Allergan, Pfizer, Covidien, and EndoGastric Solutions; and is both a consultant for and serves on the scientific advisory board of Johnson & Johnson's Ethicon Healthcare System. Dr Pories reported serving as a consultant to Johnson & Johnson's Ethicon Endo-Surgery Inc; and receiving research grants from Johnson & Johnson's Ethicon Endo-Surgery Inc and GlaxoSmithKline.
Funding/Support: The Longitudinal Assessment of Bariatric Surgery-2 was funded by a cooperative agreement by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants U01 DK066557 (data coordinating center); U01-DK66667 and UL1-RR024996 (Columbia-Presbyterian in collaboration with Cornell University Medical Center Clinical and Translational Research Center [CTRC]); U01-DK66568 and M01RR-00037 (University of Washington in collaboration with Cornell University Medical Center CTRC); U01-DK66471 (Neuropsychiatric Research Institute); U01-DK66526 (East Carolina University); U01-DK66585 and UL1-RR024153 (University of Pittsburgh Medical Center in collaboration with Cornell University Medical Center CTRC); and U01-DK66555 (Oregon Health & Science University).
Role of the Sponsor: The NIDDK scientists contributed to the design and conduct of the study, which included collection, and management of data. The project scientist from the NIDDK served as a member of the steering committee, along with the principal investigator from each clinical site and the data coordinating center. The data coordinating center housed all data during the study and performed data analyses according to a prespecified plan developed by the data coordinating center biostatistician and approved by the steering committee and independent data and safety monitoring board. The decision to publish was made by the Longitudinal Assessment of Bariatric Surgery-2 steering committee, with no restrictions imposed by the sponsor. As a coauthor, an NIDDK scientist contributed to the interpretation of the data and preparation, review, or approval of the manuscript.
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