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Review

Evaluation of Dietary Assessment Tools Used in Bariatric Population

by
Marianne Legault
1,2,
Vicky Leblanc
2,
Geneviève B. Marchand
2,
Sylvain Iceta
1,2,
Virginie Drolet-Labelle
1,2,
Simone Lemieux
2,
Benoît Lamarche
2 and
Andréanne Michaud
1,2,*
1
Quebec Heart and Lung Institute Research Centre, Université Laval, Québec City, QC G1V 4G5, Canada
2
Centre Nutrition, Santé et Société (NUTRISS), Institut sur la Nutrition et les Aliments Fonctionnels (INAF), Université Laval, Québec City, QC G1V 0A6, Canada
*
Author to whom correspondence should be addressed.
Nutrients 2021, 13(7), 2250; https://doi.org/10.3390/nu13072250
Submission received: 13 May 2021 / Revised: 24 June 2021 / Accepted: 28 June 2021 / Published: 29 June 2021
(This article belongs to the Section Nutrition Methodology & Assessment)
Browse Figures
Versions Notes

Abstract

:
Severe obesity is associated with major health issues and bariatric surgery is still the only treatment to offer significant and durable weight loss. Assessment of dietary intakes is an important component of the bariatric surgery process. Objective: To document the dietary assessment tools that have been used with patients targeted for bariatric surgery and patients who had bariatric surgery and explore the extent to which these tools have been validated. Methods: A literature search was conducted to identify studies that used a dietary assessment tool with patients targeted for bariatric surgery or who had bariatric surgery. Results: 108 studies were included. Among all studies included, 27 used a dietary assessment tool that had been validated either as part of the study per se (n = 11) or in a previous study (n = 16). Every tool validated per se in the cited studies was validated among a bariatric population, while none of the tools validated in previous studies were validated in this population. Conclusion: Few studies in bariatric populations used a dietary assessment tool that had been validated in this population. Additional studies are needed to develop valid and robust dietary assessment tools to improve the quality of nutritional studies among bariatric patients.

1. Introduction

Obesity is a common, complex chronic disease and its prevalence has increased over the past several years, making it a major public health concern [1]. More importantly, the prevalence of severe obesity (BMI ≥ 35 kg/m2) has increased dramatically in Canada [2]. Severe obesity is associated with major health issues such as an increased risk of hypertension, type 2 diabetes, sleep apnea and cancer [2]. Bariatric surgery is the only treatment for severe obesity to offer significant and durable weight loss as well as improvement of metabolic diseases [3]. Multiple types of surgery exist and are usually classified as restrictive, malabsorptive or mixed-procedures. Restrictive surgery limits the amount of food consumed by reducing stomach size, while malabsorptive surgery limits nutrient absorption by bypassing or reorganizing parts of the small intestine. Mixed-procedures, the most common surgeries, combine both gastric restriction and intestinal malabsorption [4,5]. Assessment of dietary intakes and eating behaviors are important components of the bariatric surgery process especially after surgery, since diet quality of bariatric patients is most likely to impact their risk of developing nutritional deficiencies [6] and their food preferences and choices could impact the success of their weight loss [7].
Many dietary assessment tools are used in nutritional research, especially self-report tools because they are often easier to use and less expensive as opposed to using controlled feeding environments, direct observation or measurements of biomarkers. The most common self-reported tools are food records (FR), 24-h dietary recalls (24HR) and food frequency questionnaires (FFQ). Over the last years, these tools have been adapted for a web-based use, such as self-administered web-based 24HR [8,9] or a web-based FFQ [10,11], to increase cost-efficiency and therefore the applicability to large cohort studies. The FR is a dietary assessment tool where respondents have to report all the foods and beverages consumed during the current day with as many details as possible (portion size, brand, method of cooking, time of the day, location of the eating occasion, etc.), for a variable number of days (often between 3 and 7) [12]. The 24HR consists of listing detailed information about everything the respondent ate and drank from midnight to midnight the previous day, or over the past 24-h period [12]. Finally, FFQ is a fixed-sequence questionnaire based on a predetermined series of foods and beverages consumed over a given period of time, which can be the previous week, month or year. The number and size of portions are often asked subsequently [12]. Of all these dietary assessment tools, the 24HR has been hypothesized as the least biased dietary assessment tool, since FR is more associated to reactivity biases such as a tendency to modify the usual diet for a more socially desirable manner or to simplify the recording task, and FFQ is known to encompass more important systematic biases than 24HR (does not capture the entire diet due to difficulty of the recall task) [12].
One reason explaining the difficulty to select the most appropriate dietary assessment tool with patients targeted for bariatric surgery and patients who had bariatric surgery is the relative lack of validation of these tools within those specific populations. Validity of an instrument is the degree to which an instrument measures what it is supposed to measure [12]. To determine the validity of an instrument, it is often compared with another instrument measuring the same concept and known to be accurate or considered as a gold standard [12]. Validation of dietary assessment is conducted to determine how accurately self-report instruments measure true dietary intakes [13]. It is crucial to develop and use tools that provide an accurate and precise measure of dietary intakes to optimize treatment and the nutritional care provided to patients targeted for or who had bariatric surgery [6,14]. Moreover, as patients who have undergone bariatric surgery have a higher risk of developing nutritional deficiencies [6], it is also essential to select dietary assessment tools validated for global intakes, particularly protein intakes since it is the major macronutrient deficiency after bariatric surgery [14,15].
The aim of this review was to document the dietary assessment tools that have been used in research involving patients targeted for bariatric surgery and patients who had bariatric surgery, and to explore the extent to which these tools have been validated.

2. Methods

2.1. Search Strategy

A literature search was conducted for all articles published on Pubmed up to January 2021 to identify studies that used dietary assessment tool with patients targeted for bariatric surgery or who had bariatric surgery. The search strategy was done using this keywords combination: “food intake”[All Fields] OR “food intake evaluation”[All Fields] OR “dietary intake”[All Fields] OR “dietary intake evaluation”[All Fields] OR “dietary assessment”[All Fields] OR “dietary assessment evaluation” [All Fields] OR “food assessment” [All Fields] OR “food assessment evaluation” [All Fields] AND bariatric [All Fields].

2.2. Selection of Studies

The literature search was performed independently by three authors (G.B.M., M.L., V.L.) and included all studies published on Pubmed up to 2021. Studies were found and retained in three stages: (i) the first stage was a screening done directly on Pubmed according to the title and abstract, (ii) the second one was the complete reading of the articles, and (iii) the third stage was a screening of the references of the retained articles. Inclusion and exclusion criteria that were used are presented in Table 1. Only original studies were included in this review, based on the inclusion and exclusion criteria.

2.3. Data Extraction

The following data were extracted by three authors (M.L., G.B.M., V.D.-L.) for each study: (a) bibliographical data (author, publication year, country); (b) sample characteristics (sample size, type of surgery, mean and standard deviation (SD) for age, sex and body mass index); (c) study design features (objective, study design and dietary assessment tool); (d) outcomes (self-reported energy and nutrient intakes, information on the validity of the dietary assessment tool, if available) (Table 2). Information regarding the validity of the dietary assessment tool was also extracted, such as the reference method used for validation, the population in which the validation has been performed, and information about the validation process (Table 3).

3. Results

3.1. General Overview

As shown in Figure 1, a total of 800 references were generated by the search strategy in Pubmed, and 108 original studies were included in this review by fulfilling our inclusion and exclusion criteria. Table 2 shows an exhaustive description of the 108 studies included. Studies were published between 1989 and 2021 and were conducted in many countries. These studies represented a total of 10 046 participants (74% females). Twenty five studies (23%) included more than 100 participants, including one with 1695 participants. The mean BMI was 46.0 kg/m2 (between 29.2 and 55 kg/m2) with a mean age of 44 years (between 33 and 65 years old). Among studies, 75 (69%) included Roux-en-Y gastric bypass (RYGB), 26 (24%) sleeve gastrectomy (SG), 19 (17%) gastric banding (GB) and 4 (4%) biliopancreatic diversion (BPD). Thirty-three (31%) studies included more than one type of surgery, and 8 (7%) studies did not specify the type of surgery performed. Almost all studies were classified as prospective (n = 32), cross-sectional (n = 26), retrospective (n = 22) or longitudinal (n = 18).
To assess dietary intakes, 38 studies used FR [16,19,20,21,24,27,31,36,39,41,42,43,46,51,52,53,57,58,59,61,62,63,68,70,72,74,80,81,91,94,99,100,105,107,111,112,118,121], 32 used 24HR [23,25,32,35,37,44,45,49,60,64,67,73,77,78,79,85,86,87,88,89,90,92,95,96,97,98,106,110,115,119,122,123], 16 used FFQ [18,26,40,48,50,65,76,84,101,102,103,104,108,109,114,117], 8 used questionnaires (6 were inspired by FFQ [29,66,69,71,93,120] and 2 did not provide details [22,55]), 2 used other dietary assessment methods (photo-assisted capture method and food and symptom diary) [17,75], and 12 studies used combined tools [28,30,33,34,38,47,54,56,82,83,113,116] (Table 2). Among all studies included, 27 used a dietary assessment tool that had been validated either as part of the study per se (n = 11) or in a previous study (n = 16) (Figure 2). Table 3 presents the 27 studies included in this review that used a validated dietary assessment tool. Every tool validated per se in the cited studies was validated among a bariatric population, while none of the tools validated in previous studies were validated in this population. Among the 11 studies, 3 validated their tool pre- and post-surgery, 5 validated it only pre-surgery and 3 post-surgery only (Figure 2).

3.2. Validation of Dietary Assessment Tools in Bariatric Population

3.2.1. Food Records (FR)

Of the three studies having tested the validity of the FR per se in their bariatric population, two studies [27,63] used indirect calorimetry as a reference and one study [121] used plasma concentrations biomarkers (vitamin A, D, E and C) as reference (Table 3). Regarding the validity of the tools, Bobbioni-Harsh et al. [27] found that the mean self-reported energy intake from their 3-day FR was 17.2% lower than energy requirement evaluated with indirect calorimetry pre-surgery. Golzarand et al. [63] found that protein and carbohydrate oxidation were significantly decreased post-surgery. Wolf et al. [121] found no correlation between self-reported dietary intakes obtained from a 3-day FR pre-surgery and corresponding serum concentrations biomarkers of intake (25-hydroxycholecalciferol, retinol, ascorbic acid, tocopherol/cholesterol ratio, β-carotene, calcium, magnesium, phosphate).

3.2.2. 24-h Dietary Recall (24HR)

Four studies tested the validity of the 24HR per se in their bariatric population [67,92,97,115] (Table 3). In two of those studies, indirect calorimetry (resting metabolic rate, energy requirement) pre-surgery [97] and pre- and post-surgery [115] was used as a reference. Total daily energy intake assessed by 24HR was below measured resting metabolic rate pre-surgery by 8% in Verger et al.’ study [115], while Quesada et al. [97] found that 55 to 97% of their participants underreported their intake compared to resting metabolic rate. Another study [67] tested the validity of their 24HR using 24-h urine recovery biomarker data as a reference for protein intake pre-surgery, and another one [92] used FR post-surgery as a reference (energy, macro and micronutrient intakes). Kops et al. [67] concluded that approximately 37% of bariatric patients underreported protein intakes pre-surgery assessed with 24HR compared to 24-h urinary recovery biomarker data, while 25% overreported it. Novais et al. [92] validated their 24HR by comparing it with a 3-day FR and found a high level of agreement between both tools for energy and nutrient intakes.

3.2.3. FFQ

One study [34] directly tested FFQ validity using a 24HR as a reference in post-surgery patients and found a difference of 150 kcal between the two methods (1230 kcal with the FFQ vs. 1083 kcal with the 24HR) (Table 3).

3.2.4. Questionnaires

None of the studies that used a questionnaire to assess mean daily energy intake used a questionnaire validated in bariatric population. It is important to mention that little information was available about the form of questionnaires used. Five studies [66,69,71,93,120] used the Swedish Obese Subjects (SOS) study questionnaire [132] (Table 3), which was adapted from a simplified dietary history interview and was previously validated using a 4-day FR, nitrogen urinary excretion and 24 h energy expenditure measured by indirect calorimetry in obese and non-obese population, but not in bariatric population.

3.2.5. Other Dietary Assessment Methods

Al-Ozairi et al. [17] used a photo-assisted diet capture method to assess energy intake in post-surgery (Table 3). They found that after SG, patients reported a higher energy intake with the 24HR compared to estimations obtained using photographs, but they suggested that digital photography was more reliable and accurate for measuring energy intake in this specific population than 24HR [17].

3.2.6. Mixed Methods

Two studies validated the use of mixed methods to assess dietary intakes among bariatric population [28,33] (Table 3). Casagrande et al. [33] used both FFQ and 24HR to assess dietary intakes pre-surgery. Protein, cholesterol and sodium intakes were lower with the FFQ than with the 24HR, while calcium intake was higher [33]. To assess the accuracy of the estimated mean dietary intake found with the 24HR, Brolin et al. [28] used a 1-week FFQ to compare both dietary intakes pre-surgery. They found statistically significant correlations between the tools for total energy intake and intake of milk and ice cream products, sweet/soda and nonliquid sweets [28].

4. Discussion

The objective of this review was to document the dietary assessment tools used among patients targeted for bariatric surgery and those who have undergone bariatric surgery. A total of 108 studies were included in this review; only 27 (25%) validated their dietary assessment tool or used a tool that had been previously validated, and only 11 (10%) were validated in bariatric population. Of these 11 studies, only 3 of them validated the dietary assessment tool before and after surgery, 5 validated it only before surgery, and 3 only after surgery.
The validation process of dietary assessment tools is complex but is imperative in order to evaluate usual dietary intakes and also provide an adequate estimation of nutrient intakes and potential deficiencies following bariatric surgery [6]. As previously mentioned, the dietary assessment tool of interest is often compared with another tool measuring the same concept and known to be accurate or considered as a gold standard to determine the validity [3,4]. Direct observation, which refers to objective assessment of foods and beverages consumed, is also frequently used in a clinical setting [5]. This method remains the best option to exclude risk of estimation bias, which could be present with another dietary assessment tool [2], but it is not representative of usual intakes and can cause other biases such as response bias since participants are being observed. No study using direct observation were found for this review. Most of validation studies included in this review used the comparison with another dietary assessment tool (n = 4; 1 FR, 2 24HR, 1 FFQ) or used indirect calorimetry (n = 4) to assess energy expenditure and macronutrient’s oxidation. Indirect calorimetry is less biased than self-report dietary assessment tools [12], however the later are more commonly selected as they are more accessible [12]. In the general population, FR are the most commonly used self-report tools to validate dietary intakes [8]. In order to improve quality of the validation process, the dietary assessment tool needs to be tested and compared, by direct observation or with a reference method, within the same population [6,7]. In the current review, we found that only 10% of the validated tools were validated in a bariatric population, showing a clear lack of studies that used a tool validated in that specific population. Moreover, conclusions about validity of the tools varied considerably among studies (as seen in Table 3). However, in general, FR were found as acceptable as a dietary assessment tool [27,124]. Authors found underreporting of dietary intake while validating their 24HR [97,115], but it was still deemed appropriate [67,92], particularly when used within epidemiological studies [125]. Studies examining the validation of FFQs found almost the same conclusion, namely more accurate with groups than individuals [127,129] and with a reasonable validity [128,130,131]. The only validated questionnaire had the tendency to report higher dietary intake than FR or nitrogen excretion [132]. Finally, digital photography seems to be a reliable and accurate tool for dietary intakes assessment [17], but more studies are needed to confirm these results.
Factors characterizing the bariatric population such as bias and stigmatization, dietary requirements pre- versus post-surgery and type of surgery might influence the choice of the dietary assessment tool and need to be considered in the validation process. Inclusion of patients who will have bariatric surgery and patients who have undergone bariatric surgery in the same study can be questioned as characteristics of patients and susceptible biases in reporting dietary intakes can broadly differ. For instance, social desirability biases and stigmatization can be stronger prior to than after bariatric surgery [133] since patients want to be eligible for the surgery and do not want to be excluded based on some inadequate eating habits. In addition, because several types of bariatric surgeries exist and have different impact on energy restriction and nutrient’s absorption, the need to categorize individuals according to the type of surgery, more specifically post-surgery, should also be considered in the validation process. Some studies included in this review evaluated a cohort longitudinally and assessed dietary intakes pre- and post-surgery using the same dietary assessment tool, but none of them differentiated the validity of the tool to measure dietary intakes prior to and after surgery.
This review has strength and limitations. It showed an important lack of studies that used a tool validated in bariatric population and the need to conduct research to address this concern. Indeed, a considerable number of studies used a dietary assessment tool that had been previously validated in a non-bariatric population, such as the Swedish Obese Subjects study questionnaire. Furthermore, only a few studies included in this review specifically aimed to validate the dietary assessment tool used to assess dietary intakes in bariatric population, another indicator of the lack of literature. The interpretation of the results remained difficult considering the limited availability of information regarding the validation process and conclusions about the validity in most studies, and the high level of methodological differences between studies.
Identification of the most relevant dietary assessment tools validated prior to and after bariatric surgery would allow to characterize dietary intakes more accurately while improving nutritional interventions among these patients. Validity of dietary assessment tools should be tested for total daily energy intake and in terms of diet quality. Indeed, quality of dietary intakes of patients targeted for bariatric surgery can impact their risk of developing nutritional deficiencies after the surgery [6] and the success of their weight loss [93]. Moreover, web-based and technology-assisted assessment methods have opened the way to a new wave of self-administered automatic tools [8,9]. Considering that the web-based 24HR has been associated with reduced desirability bias compared to standard administrated questionnaires at least in the general population [8], such tools could be an interesting approach to assess dietary intake in bariatric population. The potential benefits and risks associated with these web-based tools need to be evaluated in bariatric population. More studies about the validation of dietary assessment tools in bariatric population are needed, taking into account potential biases in this population.

5. Conclusions

In conclusion, few studies included in the review validated their dietary assessment tool. Additional studies are needed in order to develop valid and robust dietary assessment tools among bariatric population. These tools are essential in evaluating efficacy of nutritional interventions conducted in this population.

Author Contributions

Conceptualization, G.B.M., M.L., V.L., B.L. and A.M.; methodology, G.B.M., S.I.; literature search, G.B.M., M.L. and V.L.; data extraction: M.L., V.D.-L. and G.B.M.; writing—original draft preparation, M.L. and G.B.M.; writing—review and editing, V.L, G.B.M., V.D.-L., S.L., S.I., B.L., A.M.; supervision, A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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Nutrients 13 02250 g001 550
Figure 1. Flowchart for selection of included references.
Figure 1. Flowchart for selection of included references.
Nutrients 13 02250 g001
Nutrients 13 02250 g002 550
Figure 2. (a) Number of tools validated and not validated; (b) Number of tools validated within a bariatric population; (c) Number of tools validated pre- and post- bariatric surgery.
Figure 2. (a) Number of tools validated and not validated; (b) Number of tools validated within a bariatric population; (c) Number of tools validated pre- and post- bariatric surgery.
Nutrients 13 02250 g002
Table
Table 1. Inclusion and exclusion criteria.
Table 1. Inclusion and exclusion criteria.
Inclusion CriteriaExclusion Criteria
(i)
Population: n ≥10
(ii)
Adult population
(iii)
Bariatric population (pre and post surgery)
(iv)
Use of a dietary assessment tool
(v)
Original research in English or French
(i)
Animal studies
(ii)
Studies evaluating disorders only
(iii)
Case report
(iv)
Review
(v)
Studies analyzing a cohort already included in the present review
(vi)
Studies related to pregnancy
Table
Table 2. Exhaustive description of included articles.
Table 2. Exhaustive description of included articles.
StudyYearCountryPMIDPopulationDietary AssessmentSurgery TypeObjectiveStudy Design
NAge ± SD SexBMI ± SDToolValidation
Al Assal et al. [16]2020Brazil319731302545.8 ± 7.9100% women46.4 ± 5.5Food record (7 days)NoneRYGBAssess the gut microbiota profile before and after RYGB and the correlation with food intake and postoperative type 2 diabetes remission.Prospective
Al-Ozairi et al. [17]2019Kuwait307562965038.8 ± 9.184% women29.2 ± 6.2Photo-assisted diet capture methodYesSGEvaluate the use of digital food photography in comparison to conventional methods among patients after sleeve gastrectomy.Cross-sectional
Amundsen et al. [18]2017Norway27914028494682% women44.1FFQYesGBCompare GB patients experiencing suboptimal weight loss or significant weigh regain with successful controls, regarding postoperative food intake, eating behavior, physical activity, and psychometrics.Case-control
Andersen and Larsen [19]1989Denmark25569111835 89% womenN/DFood record (7 days)NoneGastroplastyEvaluate diet compliance and nutritional safety.Longitudinal
Anderson et al. [20]2007United-states1755798384AA: 41 ± 10; white: 43 ± 1076% womenAA: 55 ± 10; white: 53 ± 11Food record (N/D)NoneRYGBCompare weight loss between AA and white severely obese patients after RYGB and examined differences in dietary intake and cardiovascular risk factors before and after weight loss.Retrospective
Andreu et al. [21]2010Spain2082093710143.275% women47.7Food record (3 days)NoneRYGB (66%) or SG (34%)Examine the accomplishment of the recommended protein intake, and the influence of protein intake on free fat mass and protein status following bariatric surgery.Longitudinal
Anthone et al. [22]2003United States1453073370142.3 ± 10.478% women52.3 ± 9.6QuestionnaireNoneDSDetermine the safety and efficacy of the duodenal switch procedure as surgical treatment of morbid obesity.Prospective
Aron-Wisnewsky et al. [23]2016France2689112322GBP: 40.5; AGB 40.5100% womenGBP 46.3; AGB 42.83 × 24-h dietary recallYesGBP or AGBAnalyze the effect of food restriction on nutritional parameters in the short-term (≤3 months) period after bariatric surgery in morbid obesity.Prospective
Barnadas et al. [24]2021Spain334357514149.7 ± 1075% women44.3 ± 6.2Food record (7 days)NoneSGStudy the alterations of the circadian rhythmicity due to morbid obesity and the recovery of the circadian pattern after weight loss in a cohort of patients who underwent sleeve gastrectomy.Prospective
Bavaresco et al. [25]2010Brazil189318844841.985% women51.924-h dietary recallNoneRYGBAssess the metabolic and nutritional profile of grade III obese patients for a period of 12 months after bariatric surgery.Longitudinal
Benaiges et al. [26]2019Spain312889886043.1 ± 7.971.7% women44.1 ± 4.9FFQYesRYGB (43%)Evaluate dietary modifications during the preoperative and postoperative periods of bariatric surgery.Observational, prospective
Bobbioni-Harsch et al. [27]2002Switzerland120326565038.4100% women45.2Food record (3 days)YesRYGBEvaluate whether or not the individual differences in the substrates content of the diet had any impact on body weight loss and, consequently, could contribute to its variability.Longitudinal
Brolin et al. [28]1994United-states7986146138VBG: 39 ± 9; RYGB: 38 ± 1085% womenVBG: 42 ± 4; RYGB: 43 ± 4Dietary history + 24-h dietary recallYesVBG (30) or RYGB (108)Determine whether assessment of preoperative eating patterns and food preferences can be used to predict weight loss outcome after surgery.Prospective longitudinal
Buzga et al. [29]2014Czech Republic255619933743.578% women43QuestionnaireNoneSGAssess changes in dietary habits in obese patients 6 and 12 months after SG, compare changes in hormonal levels and dietary habits after this procedure.Longitudinal
Carrasco et al. [30]2007Chile176580193836.389% women44FFQ + Food record (3 days)NoneRYGBDetect metabolic or behavioral parameters that could predict the reduction in weight, the loss in body fat and the improvement in cardiovascular risk factors.Longitudinal
Carrasco et al. [31]2012Chile223055365037.6 ± 10.2100% women43.8 ± 4.8Food record (3 days)NoneGBPEvaluate the relation between weight loss and food intake and between weight loss and changes in serum ghrelin concentrations 1 y after GBP with resection of the bypassed stomach and without resection.Prospective
Carvalho et al. [32]2020Brazil3272883912233 77% womenN/D2 × 24-h dietary recallYesRYGB or SGEvaluate the association between social jet lag, a measure of circadian misalignment, and anthropometric, metabolic and food intake outcomes 6 months after bariatric surgery.Longitudinal, observational
Casagrande et al. [33]2010Brazil204113503335.9100% women43.2FFQ + 24-h dietary recallYesRYGBEvaluate bone metabolism/mineral density and nutritional profile in morbidly obese women before surgery.Prospective longitudinal
Chou et al. [34] 2017Taiwan285895294033.5 ± 9.775% women37.9 ± 6.6FFQ + 24-h dietary recallYesSGInvestigate long-term dietary intake and weight status after SG. Retrospective
Coluzzi et al. [35]2016Italy26744284303573% women43.924-h dietary recallNoneSGEvaluate the quantitative reduction and qualitative changes in food intake post surgery and analyzed the association between weight loss and changes in eating behavior.Prospective longitudinal
Cooper et al. [36]1999Australia1034081626 23–5996% women31.6–52.7Food record (4 days)NoneMLVGPerform detailed dietary analyses together with anthropometric, haematological and food intolerance assessment of a group of subjects undergoing MLVG, who received preoperative dietary education and regular postoperative followup, with some dietary advice over the subsequent year.Longitudinal
Correia Horvath et al. [37]2014Brazil245283447744.565% women48.824-h dietary recallNoneN/DAssess food consumption by severely obese patients and describe their main nutritional deficiencies on the basis of dietary reference intake.Cross-sectional
Coupaye et al. [38]2014France2412266186SG: 45 ± 11; RYGB: 44 ± 9 72% womenSG = 48.5 ± 9.6; RYGB = 48.6 ± 7.8Food record (4 days) + interviewNoneRYGB or SGCompare nutritional status after SG and RYGB in subjects matched for postoperative weightProspective
Custodio et al. [39]2012Brazil231655532237.9 ± 9.1100% women44.3 ± 5.4Food record (3 days)NoneRYGBEvaluate the influence of changes in food intake on body composition and some hematologic and biochemical variables in the period of eight weeks after RYGB.Prospective
Dagan et al. [40]2016Israel2679771810041.960% women42.3FFQNoneSGEvaluate and compare between genders dietary intake and micronutrient deficiencies among 100 candidates for surgery. Cross-sectional
Dagan et al. [41]2017Israel283035047743.157% women42.1Food record (3 days)NoneSGEvaluate adherence to dietary and lifestyle recommendations and its relation to weight post surgery.Prospective
Davies et al. [42]2020New Zealand3244763444RYGB: 48.5  ±  5.5 SG: 47.7  ±  6.952% womenRYGB: 38.2  ±  5.7; SG: 40.0  ±  5.9Food record (5 days)NoneRYGB or SGIdentify whether there were surgery-specific changes in gut microbiota among obese people with Type 2 diabetes randomised to either SG or RYGB and whether there were common taxa and gut microbiota functional capacity changes among those who achieved T2D remission, irrespective of surgery type.Prospective
da Silva et al. [43]2014Brazil255180271046.5 ± 6.6100% women45.7 ± 4.1Food record (7 days)N/DRYGBCompare the Virtual Nutri Plus®® and Dietpro 5i®® software systems in assessing nutrient intake in obese patients with type 2 diabetes mellitus who underwent a RYGB.Prospective
da Silva et al. [44]2016Brazil27544005804688.8% women49.8 ± 9.3 2 × 24-h dietary recallNoneRYGBInvestigate factors associated with weight regain long after RYGB.Retrospective
Dias et al. [45]2006Brazil166803244042.5 ± 10.8100% women51.9 ± 11.824-h dietary recallNoneRYGBSystematically document nutrient intake at 3-month intervals, during the first 12 months after uncomplicated RYGB.Prospective
Duffey et al. [46]2007United States182895664547.0 ± 10.571% women49.5 ± 9.1Food record (1 day)NoneN/DEvaluate baseline risk factors for stone formation in a group of morbidly obese patients presenting for gastric bypass surgery and the changes that may occur after bariatric surgery.Cross-sectional
El Labban et al. [47]2015Lebanon2598280360RYGB: 39.6  ±  11.3; SG: 33.0  ±  12.360% womenRYGB: 42.7  ±  5.2; SG: 41.2  ±  4.1FFQ + 3 × 24-h dietary recallYesRYGB or SGCompare dietary intake, food preferences, and gastro-intestinal symptoms in subjects with extreme obesity after RYGB and SG.Cross-sectional
Ernst et al. [48]2009Germany19034589121RYGB: 40.2  ±  1.5; GB: 44.0  ±  1.279% womenRYGB: 46.5  ±  0.7; GB: 44.6  ±  0.5FFQNoneGBP (48) or GB (73) + 45 obese controlsAssesse dietary habits in patients who have underwent a bariatric surgery and compare their data with those of an obese as well as a nonobese control group.Cross-sectional
Faria et al. [49]2014Brazil2540996560N/D87% womenN/D3 × 24-h dietary recallNoneRYGBCompare weight loss, consumption of macronutrients and the frequency of vomiting among patients who underwent RYGB with and without the placement of a constriction ring around the pouch.Retrospective
Farias et al. [50]2020Brazil322002673240.1 ± 10.194% women43.9 ± 1.1FFQYesRYGBAnalyze the contribution of unprocessed, processed, and ultra-processed foods 2 years after RYGB.Prospective
Federico et al. [51]2016Italy271070922826–6371% womenWomen: 48.6 ± 8.1; Men: 54.3 ± 18.5Food record (7 days)NoneBIEvaluate the dietary intake, the nutritional status, as well as plasma levels of a number of gastrointestinal peptides that regulate food intake and fecal microbiota in severely obese patients and healthy non-obese control subjects and evaluate whether bariatric surgery affected gastrointestinal peptides plasma levels and fecal microbiota.Prospective longitudinal
Forbes et al. [52]2016United-states263285331836.6  ±  2.3100% women44.0  ±  1.0Food record (3 days)NoneRYGB (13) or AGB (5)Describe compositional changes in plasma phospholipids during 6 months following bariatric surgery procedures.Longitudinal
Freeth et al. [53]2012United-states227148241518–80 (min-max)N/DN/DFood record (3 days)NoneRYGB (6) or GB (9)Comprehensively analyze selenium intake before and after bariatric surgery while simultaneous looking at the serum selenium level and functional measurement of selenium.Prospective longitudinal
Freeman et al. [54]2013Australia24743015130Control: 47; AGB 46; RYGB 58; SG 50 68% womenControl 43.2; AGB 45.5; RYGB 42.4; SG 43.2 Questionnaire + 24-h dietary recallNoneAGB, SG or RYGBAssess food tolerance and diet quality in AGB, SG and RYGBP patients 2–4 years post-surgery, comparing findings with an obese control group.Prospective, cross-sectional
Furet et al. [55]2010France 2087671930nDb: 42 ± 2; Db: 49 ± 590% womennDb: 48.3 ± 1.6; Db: 45.4 ± 3.5QuestionnaireNoneRYGBExamine the association between gut microbiota changes and a range of body composition, metabolic, and inflammatory markers.Prospective longitudinal
Furtado et al. [56]2018Brazil30307293105Succes group 43.3 ± 11.4; Failure group 43.4 ± 10.784% womenSG 48.8 ± 8.4; Failure group 49.9 ± 6.624-h dietary recall + food record (3 days) + FFQNoneRYGBAnalyse wheter feeding behavior, evaluated by caloric intake, dietary preferences and tolerance, can be considered as a determinant factor for weight loss in obese patients submitted to RYGB.Cross-sectional
Gesquiere et al. [57]2017Belgium27591033544861% women40.4Food record (2 days)NoneRYGBStudy dietary and supplement intake of micronutrients before and after RYGB and examine the association between the total micronutrient intakes and status markers.Prospective longitudinal
Gimenes et al. [58]2017Brazil281024952535.7100% women50.1 ± 6.5Food record (1 day)NoneRYGBEvaluate nutritional and biochemical indicators of women who became pregnant after RYGB.Retrospective
Giusti et al. [59] 2015Switzerland266757751639.4 ± 2.4100% women44.1 ± 1.6Food record (7 days)NoneRYGBEvaluate energy and macronutrient intakes, body composition, and the basal metabolic rate in obese female patients during the initial 3 y after an RYGB.Observational
Gobato et al. [60]2014Brazil252643343637.775% women44.224-h dietary recallNoneRYGBEvaluate the nutritional status of minerals and vitamins and the food consumption in patients before and after RYGB. Evaluate the overall effect of RYGB by monitoring additional risk factors of related chronic diseases. Prospective longitudinal
Gobato et al. [61]2018Brazil303065007538 ± 1089% women43.94 ± 5.89Food record (3 days)NoneRYGBEvaluate the food intolerance after banded RYGB, correlating the data of food ingestion.Observational, prospective
Golpaie et al. [62]2011Iran222661003032.570% women44.1 ± 4.9Food record (3 days)NoneAGB (15) or (16) TGVPInvestigate the possible short-term effects of surgery on vaspin and other metabolic variables relevant to insulin sensitivity and evaluate the possible relationship between dietary intake and serum vaspin.Longitudinal
Golzarand et al. [63]2018Iran3025109843N/DN/DRYGB: 45.9 ± 4.6 SG: 39.5 ± 4.2Food record (3 days)YesRYGB or SGCompare the changes in body composition, dietary intake, and substrate oxidation 6 months post-sugery in obese patients who underwent RYGB and SG.Prospective
Jastrzębska-Mierzyńska et al. [64]2012Poland2325602027Women: 40.4 ± 13.9; Men: 39.6 ±12.768% womenW: 45.9 ± 6.8; M: 48.1 ± 7.724-h dietary recallNoneN/AAssess dietary habits, nutritional status and biochemical parameters of blood in patients being prepared for different bariatric procedures.Cross-sectional
Johnson et al. [65]2013Norway231109167242.6 ± 1169% women46.2 ± 5.9FFQYesRYGBCompare changes in the dietary patterns of morbidly obese patients undergoing either laparoscopic gastric bypass surgery or a comprehensive lifestyle intervention program.Interventional (clinical trial)
Kanerva et al. [66]2017Sweden28756049169547.3 ± 5.969.8% women42.5 ± 4.5QuestionnaireYesLAGB OR VBG OR RYGBExplore whether pre-surgical sociodemographic and lifestyle characteristics, together with the type of surgery, could predict 10-year changes in dietary intake following bariatric surgery.Prospective, matched, non-randomized, surgical intervention trial
Kops et al. [67]2017Brazil28760427120N/DAdherent: 74.4% women; Non adherent 81.8% womenAdherent: 45.8 ± 6.8 Non adherents: 49.1 ± 8.124-h dietary recall (3×)YesN/DEvaluate the possible association between the Thr54 allele and anthropometric and lipid profile of severely obese indivieuals, taking into account the dietary intake of these participants. Cross-sectional
Kruseman et al. [68]2010Switzerland203382781414093% women46Food record (4 days)NoneGBPDocument weight and body composition changes among patients after bariatric surgery and to assess whether dietary, behavior, or psychological factors were associated with long-term weight outcome.Retrospective longitudinal
Laurenius et al. [69]2013Sweden232997134343 ± 1072% women44.3 ± 4.9QuestionnaireYesRYGBTest the hypothesis that dietary energy density decreases after RYGB.Longitudinal
Leite Faria et al. [70]2009Brazil188307807536.8  ±  10.780% women43  ±  5.5Food record (4 days)NoneRYGBAssess postoperative eating patterns, relating them to weight loss.Cross-sectional
Le Roux et al. [71]2011Sweden2173401916N/D69% womenN/DQuestionnaireYesRYGB or VBGInvestigate how RYGB affects intake of and preference for high-fat food in an experimental (rat) study and within a trial setting (human).Prospective
Ledoux et al. [72]2017France27943093784381% women44Food record (4 days)NoneRYGB, SG or AGBExplore whether self-reported preoperative changes in dietary habits and physical activity during a multidisciplinary preparation were predictive of postoperative weight loss.Interventional
Magno et al. [73]2014Brazil2540996230W: 48.4 ± 12.9; M: 49.8 ± 8.173% women50.8 ± 14.524-h dietary recallNoneN/DEvaluate the nutritional profile of the patients included into a multidisciplinary program for the treatment of severe obesity and bariatric presurgery.Retrospective
Marin et al. [74]2017Brazil284217924520–45 100% womenGroup 1: 47.8; Groupe 2: 41.5Food record (3 days) NoneRYGBAssess the effect of two micronutrient supplementation schemes on inflammation and iron metabolism in premenopausal women who had undergone RYGB surgery.Prospective
Marques et Al. [75]2020Portugal3143590117Symptomatic: 46.4  ±  1.7 Control: 42.1  ±  3.494% womenSymptomatic: 39.4  ±  1.8; Control 42.4  ±  1.2Food and symptom diary (FSD)NoneRYGBEvaluate the influence of meal nutritional composition on interstitial fluid glucose profiles and symptom profile after RYGB.Cross-sectional
McLean et al. [76]2018United States2910090020046.3 ± 8.5100% women48.9 ± 5.8FFQNoneRYGB, SG or LAGBIdentify usual dietary habits of black and white women seeking bariatric surgery and examine potential differences between these ethnic groups; to describe participants’plans to change dietary behaviors after surgery. Cross-sectional
Melendez-Araùjo et al. [77]2012Brazil230545693239  ±  10.6N/D41.9  ±  5.224-h dietary recallNoneRYGBEvaluate the impact of intensive and standard nutritional interventions on body weight, energy intake, and eating quality.Retrospective
Melo et al. [78]2017Brazil287240556147.1 ± 9.984% women31.5 ± 6.03 × 24-h dietary recallNoneRYGB or BPDSEvaluate parameters of bone and mineral metabolism after bariatric surgery.Sectional, retrospective
Mercachita et al. [79]2014Portugal239555226041.9 ± 12.265% women42.3 ± 6.724-h dietary recallNoneRYGBQuantify the intake of micronutrients in patients that were submitted to RYGB, determine the micronutrients deficiencies, and verify if the recommended vitamin and mineral supplementation intake would prevent theses deficiencies.Retrospective longitudinal
Miller et al. [80]2014United States247484741747.3 ± 2.294% women53.6 ± 1.7Food record (4 days)NoneRYGBExamine changes in macro- and micronutrients, food groups, and selected foods during 12-months of follow-up in post RYGB individuals.Prospective
Mischler et al. [81]2015United states268067283645 97% women32 Food record (3 days)NoneRYGBExplore the impact of dietary and supplemental sources of iron and absorptive factors on iron status.Cross-sectional
Moizé et al. [82]2011Spain2129850923145.6 ± 9.972.3% women48.2 ± 7.8Food record (4 days) + 24-h dietary recallNone N/DEvaluate the dietetic intake and the prevalence of nutritional deficiencies in obese patients who are candidates for bariatric surgery.Cross-sectional
Moizé et al. [83]2013Spain23438491355SG = 46.4 ± 11.6; RYGB = 45.2 ± 10.675% womenSG = 51.6 ± 6.7; RYGB = 47.4 ± 6.0Food record (3 days) + 24-h dietary recallNoneRYGB or SGProspectively compare dietary changes and nutritional deficiencies in grade 3 obese patients 5 years after SG and RYGB.Longitudinal, prospective, observational
Molin Netto et al. [84]2017Brazil274742304139.4 ± 10.995% women44.6 ± 6.3FFQYesRYGBEvaluate the early post-RYGB changes in the quality of eating patterns and their relationship to weight loss and metabolic parameters.Longitudinal
Moore et al. [85]2015United-states252707942241± 12100% women46.7 ± 824-h dietary recallNoneRYGB (11) or SG (11)Determine the response to 3 months of thiamin, B12, and folate supplementations.Prospective observational
Nicoletti et al. [86]2013Brazil219787508045 ± 1181% women54 ± 824-h dietary recallNoneRYGBCharacterize the eating, anthropometric, and biochemical profile of obese candidates for bariatric surgery at a university hospital and assess their preoperative risk of nutritional deficiency.Retrospective
Nicoletti et al. [87]2015Brazil258517747242 ± 986% women53 ± 824-h dietary recallNoneRYGBEvaluate the influence of red meat intolerance on the dietary pattern, biochemical indicators, and clinical symptoms after Roux-en-Y gastric bypass.Retrospective
Nicoletti et al. [88]2016Brazil2725616415047.2 ± 10.580% women51.3 ± 7.324-h dietary recallNoneRYGBInvestigate the contribution of UCP2 gene variants on energy and macronutrients intake in a population after bariatric surgery.Retrospective
Nicoletti et al. [89]2020Brazil332318196547.2  ±  11.486% women35.5  ±  6.83 × 24-h dietary recallNoneRYGB or VBGInvestigate dietary habits and food intake during COVID-19 quarantine among patients who recently underwent bariatric surgery.Cross-sectional
Nonino et al. [90]2019Brazil3164467344144 ± 1082.7% women50.5 ± 8.024-h dietary recallN/DRYGBInvestigate nutritional status in 10 years follow-up.Longitudinal retrospective
Nosso et al. [91]2017Italy289698832250 ± 954.5% women31 ± 6Food record (7 days)NoneRYGB (11) or SG (11)Evaluate glycemic variability and oxidative stress in patients who achieved type 2 diabetes remission after bariatric surgery.Cross-sectional
Novais et al. [92]2012Brazil2265237214144 ± 9100% women45.9 ± 16.42 × 24-h dietary recallYesRYGBAssess the adequacy of food intake in women two or more years after bariatric surgery according to the excess weight lost.Cross-sectional
Olbers et al. [93]2006Sweden1706076475GB: 37.4 ± 0.4 VGB: 37.4 ± 0.550% womenGB: 42.3 ± 4.5; VBG: 42.6 ± 4.2QuestionnaireYesRYGB(36) or VBG(39)Evaluate the effect of dietary intake of on body composition and energy expenditure after sugery.Prospective longitudinal
Ortega et al. [94]2012Spain2272223610741.8 ± 9.879% women50.7 ± 11.8Food record (3 days)NoneRYGBAnalyze the likelihood of patients undergoing RYGB to recover a normal daily food intake, and the possible influence of dietary and exercise habits on long-term weight loss.Cross-sectional
Papalazarou et al. [95]2010Greece1983446630Usual care: 33.4 ± 2. Lifestyle intervention: 32.7 ± 1.6100% womenUsual Care: 49.8 ± 1.6. Lifestyle intervention:48.5 ± 2.24-h dietary recallNoneVBGEvaluate the 3 year effects of a lifestyle intervention on weight loss and maintenance, dietary, and physical activity habits and eating behavior of patients following VBG.Cross-sectional
Pinto et al. [96]2019Brazil313761335139.34 ± 9.3868.7% women43.0 ± 5.724-h dietary recallNoneRYGBEvaluate changes in dietary intake and predictive factors of obesity remission in the first 12 months after RYGB.Observational, prospective
Quesada et al. [97]2014Brazil2472477310033.3 ± 6.08100% women45.75 ± 6.0524-h dietary recallYesGastroplastyTest 6 variations in the Goldberg equation to evaluate underreporting among obese women on a bariatric surgery waiting list. Cross-sectional
Raatz [98]2020United States324187717244.1 ± 11.781% women47.3 ± 6.92 × 24-h dietary recallNoneRYGBEvaluate the reported macro- and micronutrient intake of adults who underwent RYGB over 7 years after surgery.Longitudinal
Reid et al. [99]2016Canada277447352753.2 ± 8.389% women33.8 ± 8.1Food record (3 days)YesRYGBCompare the differences in dietary intake (caloric and macronutrient) between individuals who have maintained weight loss (maintainers) to those who have regained their lost weight (regainers) on average 12 years after RYGB and examine behaviours/habits between weight regainers and maintainers.Retrospective
Ruiz-Lozano et al. [100]2016Spain2694840027052 ± 1182% women46.5 ± 6Food record (4 days)NoneRYGB (203) or SG (67)Evaluate if food timing is associated with the weight loss effectiveness following bariatric surgery.Observational
Ruiz-Tovar et al. [101]2017Spain292507519345.7 ± 10.878% women46.4 ± 7.9FFQNoneSGEvaluate the changes in the frequency intake of different foods in patients undergoing sleeve gastrectomy and following a strict dietary control.Prospective, observational
Sanchez et al. [102]2016Chile2610863810336 ± 9.6100% women43.1 ±5.3FFQNoneRYGB or SGEvaluate dietary intake and nutritional status of various micronutrients in morbidly obese women prior to bariatric surgery.Cross-sectional
Sarwer et al. [103]2012United-states225515768442 ± 9.963% women51.6 ± 9.2FFQYesRYGB (62) or AGB (16)Evaluate the impact of dietary counselling on weight loss, dietary intake and eating behaviour after surgery.Interventional
Sarwer et al. [104]2008United States1858657120043.2 ± 9.882% women52.1 ± 9.3FFQYesRYGBInvestigate the relationship between preoperative eating behavior, postoperative dietary adherence and weight loss following gastric bypass surgery.Prospective
Schoemacher et al. [105]2019the Netherlands3131323813546.5 ± 9.583.7% women44.6 ± 6.7Food record (2 days)NoneRYGB or SGExplore the relationship between total energy intake and % total body weight loss over a period of 4 years post-surgery.Longitudinal, observational
Seki et al. [106]2019Japan3071144546 64.5 ± 8.147% women31.7 ± 2.224-h dietary recallNoneDBPInvestigate the impact of metabolic surgery for diabetic patients with body mass index < 35 kg/m2 on health-related quality of life, food tolerance, and food satisfaction in a single institution.Retrospective
Shah et al. [107]2013United States241137342349.3 ± 10.591% women41.1 ± 6.2Food record (3 days)NoneGBExamine whether dietary counseling improves micronutrient and macronutrient intakes in GB surgery patients.Prospective
Shai et al. [108]2002Israel125681867534.4 ± 9.481% women41.4 ± 6.0FFQNoneVBGEvaluate the long-term nutritional changes that occur in VBG patients compared with their nutrition before surgery.Retrospective
Soares et al. [109]2014Brazil2450022517242.4  ±  9.092.5% women46.9  ±  6.0FFQNoneRYGBEvaluate the life habits and diet quality of patients who have undergone bariatric surgery (who have been recovering for at least 6 months) based on the specific food pyramid.Retrospective
Solga et al. [110]2004United-states155739087044 ± 989% women55 (median)24-h dietary recallNone RYGBDetermine whether overall calorie intake and diet composition are associated with the severity of NAFLD histopathology.Retrospective
Sovik et al. [111]2013Norway/Sweden2295107860GB: 35.2 ± 7 DS: 36.1 ± 5.2670% womenGB: 54.8 ± 3.24 DS: 55.2 ± 3.49Food record (4 days)NoneBPD (29) or RYGB (31)Evaluate the gastrointestinal side effects, caloric intake, and changes in obesity-specific quality of life 2 years after surgery. Prospective longitudinal
Torres et al. [112]2012Brazil226884684445.4  ±  9.5100% women31.3  ±  4.8Food record (4 days)NoneRYGBEvaluate the nutrient intake of women who had undergone RYGB surgery.Cross-sectional
Trostler et al. [113]1995Israel1073379255RYGB: M: 41± 4/W: 32 ± 4 VBG: M: 32 ± 3/W: 37 ± 273% womenRYGB: 43 ± 4/W:43 ± 6 VGB: M:45± 7/W: 42± 8FFQ + 24-h dietary recallNoneRYGB (19) or VBG (36)Compare 2 surgeries with a low energy diet and dietary counseling. Compare the food intake pattern and nutritional composition of the food consumed over time.Longitudinal
Ullrich et al. [114]2013Switzerland2294133444N/DN/D47.3  ±  1.1FFQNoneRYGBInvestigate changes in the hedonic hunger and dietary habits after RYGB surgeryLongitudinal
Verger et al. [115]2016France2620521552RYGB: 43.5; SG:41.067% womenRYGB: 45.5; SG:43.224-h dietary recallYesRYGB (22) or SG (30)Analyze food restriction effects on the nutritional adequacy of the diet, on macro- and micronutrient intake evolution, as well as their consequences in terms of bioclinical evolution and micronutrient serum level post surgery. Retrospective
Vieira et al. [116]2019Brazil3056510240stable weight 38± 7; weight regain 42 ± 11 100% womenSW 41.7 ± 6.5; WR 41.3 ± 3.5 24-h dietary recall + 2 food record (1 day)NoneRYGBInvestigate the perception of hunger and satiety and its association with nutrient intake in women who regain weight in the postoperative period after bariatric surgery.Cross-sectional
Vieira et al. [117]2020Brazil320221156038.8 ± 9.678% women47.3 ± 6.9FFQNoneN/DEvaluate the association of food consumption with nutritional status, physical activity and sociodemographic factors in the bariatric surgery period preoperativeCross-sectional
Vinolas et al. [118]2019France3110220757RYGB: 42.9 ± 11 SG: 45.2 ± 9.2N/DRYGB: 46.8 ± 6.9 SG: 44.1 ± 9.4Food record (7 days)NoneRYGB or SGEvaluate nutritional status, micro- and macronutrient intake, and oral hydration in patients before and regularly during 1 year after RYGB and SG.Retrospective
Wardé-Kamar et al. [119]2004United States154795967346 ± 1193% women54 ± 1224-h dietary recallNoneRYGBInvestigate self-reported food intake, diet composition and meal patterns, in relation to long-term weight loss outcomes after RYGB. Retrospective, longitudinal
Werling et al. [120]2013Sweden2357324414GB: 59.7; VBG: 50.2100% womenGB: 30.8; VBG: 35.0QuestionnaireYesVGB or GBInvestigate alterations in postprandial EE after gastric bypass and VBG in humans.Cross-sectional
Wolf et al. [121]2015Germany259803314344 ± 1263% women52.6  ± 10.5Food record (3 days)YesN/DAssess the status of micronutrients in morbidly obese patients seeking bariatric surgery and to correlate extra-cellular nutrient levels with the corresponding nutrient intake.Cross-sectional
Zaparolli et al. [122]2018Brazil2997239510648 (20–64y)90.5% women39.6 (32.8–67.8)24-h dietary recallNoneRYGBAnalyze food intake evolution during the first postoperative year of Roux-en-y gastric bypass in patients with type 2 diabetes or glycemic alteration.Retrospective, longitudinal, observational
Ziadlou et al. [123]2020Iran330460205837 ± 871% women44  ±  63 × 24-h dietary recallNoneRYGB or SGAssess the adequacy of dietary nutrient intakes at 6th and 12th month after bariatric surgery.Longitudinal
AA, African American; AGB, adjustable gastric banding; BI, bilio-intestinal bypass; BPD, Biliopancreatic diversion with duodenal switch; Ca, calcium; carb, carbohydrates; chol, cholesterol; Db, diabetic; DS, duodenal switch; eq, equivalent; FFQ, Food frequency questionnaire; GB, Gastric banding; GBP, Gastric bypass; MLVG, modified long vertical gastroplasty; NAFLD, non alcoholic fatty liver disease; nDb, non diabetic; N/D, not defined; RYGB, Roux-en-Y gastric bypass; Se, selenium; SG, Sleeve gastrectomy; TGVP, total gastric vertical plication; VBG, vertical banded gastroplasty.
Table
Table 3. Validation of dietary assessment tools.
Table 3. Validation of dietary assessment tools.
AuthorSurgery TypeReference MethodValidationConclusions About Validity
Bariatric PopulationPre-and/or Post-SurgeryDirectly in the Study
Food records (FR)
Bobbioni-Harsch et al. [27]RYGBIndirect calorimetry (resting energy expenditure; glucose, lipid and protein oxidation) YesPre-surgeryYesThe degree of mis-report averages −17% of the evaluated energy requirements, in pre-surgery conditions; it represents a reasonable degree of inaccuracy [27].
Golzarand et al. [63]RYGB or
SG		Indirect calorimetry (resting metabolic rate, glucose, lipid and protein oxidation)YesPre- & post-surgeryYesIn accordance with dietary intake reduction, protein and carbohydrate oxidation significantly decreased in both procedures post-surgery, while fat oxidation increased, but was not significant.
Reid et al. [99]RYGB9-days food record (energy, macro and micronutrients)No NoRelative validity of 3-days FR appears to be acceptable as dietary assessment tool [124].
Wolf et al. [121]N/ACorrelation with vitamin A, D, E and C plasmatic valuesYesPre-surgeryYesNo correlations were found between serum/plasma concentrations and nutritional intake nor associations between low concentrations and inadequate intakes.
24-h dietary recall (24HR)
Aron-Wisnewsky et al. [23]RYGB or AGB24HR conducted by a dietitian (food consumption, energy and macro- and micronutrient intakes)No NoAgreement between the two methods was high, although it may have been overestimated because the two assessments were consecutives to one another. The tool may be highly advantageous for large population-based surveys [125].
Carvalho et al. [32]RYGB or
SG		Compared to Behavioral Risk Factor Surveillance System’s Fruit and Vegetable Consumption Module and the National Cancer Institute’s Percentage Energy from Fat Screener.No NoValidity of brief dietary intake measures may vary by demographic characteristics of the sample. Additional measurement work may be needed to accurately measure dietary intake in obese African-American women [126].
Kops et al. [67]N/D24-h urine sample (urinary urea to assess protein intake)YesPre-surgeryYesThe 24HR was accepted as appropriate. Only 37.4% of patients gave an accurate record; another 37.4% underrreported, and 25.2% overreported.
Novais et al. [92]RYGB3-days FR (energy and nutrients)YesPost-surgeryYesThe agreement between the two methods (r = 0.91 to 0.98) evidenced low variability of the meals consumed by the group.
Quesada et al. [97]GPIndirect calorimetry (resting metabolic rate, energy requirement)YesPre-surgeryYesComparing the results obtained for the modified Goldberg equations in this study, there was considerable variation in the proportion of underreporting (55% to 97%).
Verger et al. [115]RYGB or SGIndirect calorimetry (basal metabolic rate)YesPre- & post-surgeryYesValues revealed that patients from both groups underreported their caloric intake by 8% pre-surgery.
Food frequency questionnaire (FFQ)
Amundsen et al. [18]GBDoubly labelled water (total energy expenditure)No NoThe data showed that there was substantial variability in the accuracy of the FFQ at the individual level. Furthermore, the results showed that the questionnaire was more accurate for groups than individuals [127].
Benaiges et al. [26]RYGB (43%)3-day FR (dietary intakes)No NoA reasonable relative validity of the FFQ and 3-day FR for estimating nutrient intake was found [128].
Chou et al. [34]SG24HR (energy and macronutrients intakes)YesPost-surgeryYesThe energy intake according to the dietary questionnaire was 1230 kcal/day 5 years after LSG, and the 24HR method reported a daily energy intake of approximately 1083 kcal/day.
Farias et al. [50]RYGB3x 24HR (energy and macronutrients intakes)No NoFood consumption reports of overweight individuals tend to be underestimated. Despite its limitations, FFQ could be used in epidemiological studies to assess the regular food consumption of overweight individuals [129].
Johnson et al. [65]RYGB14-day FR (energy from fat and sugar) and correlation of fatty acids and Alpha-tocopherol in adipose tissue with serumNo NoOn average, 39% of the men were classified in the same quartile with the two methods, and 3% in the opposite quartile. Very-long chain n-3 fatty acids in adipose tissue and total serum lipids reflect the dietary intake of very-long-chain n-3 fatty acids to the same degree. No associations were observed between intake of alpha-tocopherol and concentration in adipose tissue and serum [130].
Molin Netto et al. [84]RYGB3 × 24HR (energy and macronutrients intakes)No NoIdem Farias et al. 2020 [129].
Sarwer et al. 2012 [103]RYGB or AGB4 and 7-day FR (energy and macronutrients intakes)No NoCorrelations between questionnaire and FR for percent of energy from fat were 0.67 and 0.65 respectively in the two groups; most correlations were similar to those achievable by a single 4-day FR [131].
Sarwer et al. 2008 [104]RYGB4 and 7-day FR (energy and macronutrients intakes)No NoIdem Sarwer et al. 2012 [131].
Questionnaires
Kanerva et al. [66]LAGB or VBG or RYGB4-day FR, 24-h energy expenditure and nitrogen excretion (nutrient intake, basal matabolic rate)No NoPeople with obesity reported energy and protein intakes 35% higher with the questionnaire compared with FR and nitrogen excretion [132].
Laurenius et al. [69]RYGB4-day FR, 24-h energy expenditure and nitrogen excretion (nutrient intake, basal matabolic rate)No NoIdem Kaverna et al. 2017 [132].
Le Roux et al. [71]RYGB or VBG4-day FR, 24-h energy expenditure and nitrogen excretion (nutrient intake, basal matabolic rate)No NoIdem Kaverna et al. 2017 [132].
Olbers et al. [93]RYGB or VBG4-day FR, 24-h energy expenditure and nitrogen excretion (nutrient intake, basal matabolic rate)No NoIdem Kaverna et al. 2017 [132].
Werling et al. [120]GB or VBG4-day FR, 24-h energy expenditure and nitrogen excretion (nutrient intake, basal matabolic rate)No NoIdem Kaverna et al. 2017 [132].
Other dietary assessment methods
Al-Ozairi et al. [17]SG24HR by a dietitian (energy, macronutrients, fiber, total fat, saturated fat, mono- polyinsaturated fat, cholesterol and sodium)YesPost-surgeryYesAfter SG, patients reported higher total energy intake and energy intake from carbohydrates compared to estimations using photographs. Digital photography appears reliable and accurate in adults in measuring energy intake in a cafeteria setting.
Mixed methods
Brolin et al. [28]VBG or RYGB1 week FFQ (energy, protein, carbohydrate and fat intake)YesPre- & post-surgeryYesMultiple tools were used to obtain a mean of energy intake and macronutrients.
Casagrande et al. [33]RYGBFFQ + 24HR (total energy, macro and micronutrients)YesPre-surgeryYesThe FFQ underestimated total energy value intake as compared with the 24HR. Protein and lipid intakes were lower if evaluated by the FFQ as compared to the 24HR. Calcium intake was higher when evaluated by the FFQ as compared with the 24HR.
El Labban [47]RYGB or SGN/DNo NoN/D
AGB, adjustable gastric banding; BDP, biliopancreatic diversion with duodenal switch; FFQ, food frequency questionnaire; GB, Gastric banding; GP; gastroplasty; kcal, Kilocalories; LAGB, Laparoscopic Adjustable Gastric Banding; N/D: Not defined; RYGB, Roux-en-Y gastric bypass; SG, Sleeve gastrectomy; VBG, vertical banded gastroplasty; 24HR, 24-h recall.
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Legault, M.; Leblanc, V.; Marchand, G.B.; Iceta, S.; Drolet-Labelle, V.; Lemieux, S.; Lamarche, B.; Michaud, A. Evaluation of Dietary Assessment Tools Used in Bariatric Population. Nutrients 2021, 13, 2250. https://doi.org/10.3390/nu13072250

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Legault M, Leblanc V, Marchand GB, Iceta S, Drolet-Labelle V, Lemieux S, Lamarche B, Michaud A. Evaluation of Dietary Assessment Tools Used in Bariatric Population. Nutrients. 2021; 13(7):2250. https://doi.org/10.3390/nu13072250

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Legault, Marianne, Vicky Leblanc, Geneviève B. Marchand, Sylvain Iceta, Virginie Drolet-Labelle, Simone Lemieux, Benoît Lamarche, and Andréanne Michaud. 2021. "Evaluation of Dietary Assessment Tools Used in Bariatric Population" Nutrients 13, no. 7: 2250. https://doi.org/10.3390/nu13072250

APA Style

Legault, M., Leblanc, V., Marchand, G. B., Iceta, S., Drolet-Labelle, V., Lemieux, S., Lamarche, B., & Michaud, A. (2021). Evaluation of Dietary Assessment Tools Used in Bariatric Population. Nutrients, 13(7), 2250. https://doi.org/10.3390/nu13072250

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