Preoperative Quality of Life Predicting Weight Loss After Laparoscopic Sleeve Gastrectomy

Abstract

Introduction:

Several factors can influence the response to laparoscopic sleeve gastrectomy (LSG). However, preoperative quality of life (QOL) as a predictor for weight loss postbariatric surgery has been scarcely studied. The purpose of this study was to evaluate the impact of preoperative QOL and other factors to determine success, in terms of percentage of excess weight loss (%EWL) after LSG.

Methods:

A retrospective analysis of patients operated for LSG was performed. The primary variable for analysis was %EWL, which was categorized as <20%, between 21–49%, 50–75%, and >75%. All the variables (demographics, comorbidities, QOL, and nutritional habits) were paired with %EWL and analyzed.

Results:

A total of 134 patients were evaluated. The mean follow-up and %EWL was 24.4 months and 83.3%, respectively. Patients between 18 and 40 years, patients with baseline body mass index (BMI) between 30 and 39.9 kg/m², patients without high blood pressure, and those with less impaired QOL previous to surgery had significantly (p = 0.013, 0.01, 0.026, and 0.01) better results in terms of %EWL.

Conclusions:

Our analysis shows that younger patients, those with less BMI, and those without HPB have a greater chance of losing weight after LSD. In addition, less impaired preoperative QOL could be a predictor of success in terms of weight loss.

Introduction

Obesity continues to be a significant problem worldwide, especially in western countries, including Mexico. Bariatric surgery is currently considered the most effective therapy for weight loss and preventing obesity-related comorbidities in patients with severe obesity.¹

In recent years, the number of bariatric surgeries performed globally has significantly increased, and the risk–benefit balance for successful surgeries is clearly in favor of performing the surgery in most cases. This is partly because these surgeries reduce weight in addition to reducing the number and severity of obesity-related comorbidities.² Laparoscopic sleeve gastrectomy (LSG) is the most common bariatric procedure performed worldwide. LSG has several advantages over malabsorptive procedures, including short surgical time, technical ease, less probability of complications, and comparable long-term results in terms of weight loss.³ However, a small proportion of patients may not achieve the targeted weight or may even gain weight following LSG.⁴

Such patients with poor responses to LSG require individualized long-term multidisciplinary interventions to reach and maintain the proposed goals. After LSG, the percentage of excess weight loss (%EWL) is probably the most common parameter evaluated to determine success.

Several factors can influence the response to bariatric surgery, including baseline body mass index (BMI), presence of comorbidities, nutritional habits, demographics, and preoperative psychological status.^5–7 However, preoperative quality of life (QOL) as a predictor for weight loss postbariatric surgery has been scarcely studied, and most articles focused on the impact of bariatric surgery on QOL in postoperative patients. In addition, the characterization of the predominant risk factors affecting weight loss post-LSG is poorly performed. Identifying the prevailing risk factors for success or failure in terms of weight loss may allow for better screening and counseling of potential candidates for surgery, as well as formulating the proper interventions when the expected success is not predicted. The purpose of this study was to evaluate the impact of preoperative QOL and other factors to determine success, in terms of %EWL after LSG.

Methods

We performed a retrospective analysis of the medical files of patients operated for LSG from January 2019 to January 2020 in Bariatric and Metabolic Surgery Center, Obesity Health at Veracruz, Mexico. An ethics approval was obtained from the regional ethics committee. We included patients with LSG, with at least 1-year follow-up history. All surgeries were primarily performed by a single surgeon in one institution. All the patients signed informed consent about the surgical procedure and were evaluated before the surgery by a multidisciplinary team. Preoperative assessment of the patient included consultation with the principal surgeon, a dietician, an internist, and a psychologist. If noneligible cases were detected, these issues were addressed and fully treated before surgery was considered. In some cases, other specialists contributed to the preoperative evaluation (such as psychiatry, endocrinology, or cardiology).

In our center, consultations were free of charge before the surgery and 1 year after the surgery. Recommendations were given to attend physical consultations. However, when patients could not attend, we offered online interventions, using instruments such as phone calls or webinars. During the preoperative education and consent processes, patients were informed that consultations were essential and required adequate patient care and factors related to success in the process.

The eligibility for LSG was the standard NIH criteria, including BMI >40 kg/m², BMI >35 kg/m² with at least one comorbidity associated with obesity, or BMI >30 kg/m² with uncontrolled diabetes. Patients with uncontrollable psychiatric disorders were not eligible for LSG. To determine %EWL, the ideal weight was set at BMI of 25 kg/m². The study was performed in accordance with the principles of the Declaration of Helsinki revised in 2013.

Variables

The primary variable for analysis was %EWL. It was categorized into bad, moderate, good, and excellent categories according to the following %EWL: <20%, between 21–49%, 50–75%, and >75%, respectively. All the preoperative variables (demographics, comorbidities, QOL evaluation, and nutritional habits) were paired with %EWL to determine the grade of success of LSG.

Demographics were analyzed as follows: Patients were divided into two groups according to gender (female and male), BMI (30–39.9 and >40 kg/m²), age (18–40 and >40 years), place of residency (local or foreign), and occupation (sedentary or active). The patients were also investigated for the presence or absence of the following comorbidities, diabetes mellitus, high blood pressure (HBP), hypothyroidism, dyslipidemia, smoking, back pain, knee pain, and chronic fatigue. QOL before surgery was evaluated using the Bariatric Analysis and Reporting Outcome System (BAROS), and nutritional habits were evaluated through simple questions as part of the nutritional evaluation before surgery.

Among the working activities, sitting most of the time was considered sedentary. Diagnosis of diabetes, HBP, hypothyroidism, and dyslipidemia were considered according to international criteria. Smoking was considered for patients who smoked >20 cigarettes per week. Chronic fatigue, knee, and back pain were considered if the patient positively answered the following question: Do you feel any pain in your knees or back? And do you feel fatigued most of the day and the week?

Surgical technique

The LSG technique performed in this study is essentially like previous reports, with some details: (1) we used a 38F Bogie, and (2) greater curvature division starts at 5–6 cm from the pylorus.

Statistical analysis

Statistical analysis was performed using IBM® SPSS Statistics for Mac, version 26.0 (IBM, Armonk, NY). Variables were expressed as mean ± standard deviation or as median (range), depending on their distribution. Categorical variables were expressed as frequencies and percentages. Chi-square with Yates' correction and t-test was used for comparison of groups concerning EWL%. The strength of association of the significant parameters was analyzed with multivariate linear regression. The statistical results were presented with 95% confidence interval. A value of p < 0.05 was deemed statistically significant.

Results

A total of 134 patients were evaluated. Of them, 97 (72.4%) were female and 37 (27.6%) were male. The mean age of the patients was 40.5 ± 9.5 years (range = 19–66 years). The preoperative mean weight and BMI were 110.4 ± 25.1 kg (range = 63.2–189 kg) and 40.4 ± 7.5 kg/m² (30–74), respectively. The mean preoperative QOL was −2.4 ± 0.8 (range = −1.0 to −4.5). The mean follow-up was 24.4 ± 12.0 months (range = 12–68 months). The mean %EWL was 83.3% ± 29.7 (range = 13.0–180.2%).

Results show that patients between 18 and 40 years (38.1%) demonstrated better results (%EWL >75%) than those >40 years (21.6%, p = 0.013) (Table 1). Patients with baseline BMI between 30 and 39.9 kg/m² (38.1%) had significantly better results (%EWL >75%) than those with initial BMI >40 kg/m² (21.6%, p = 0.001) (Tables 1 and 6). Furthermore, patients without HBP (41.8%) had significantly better results (%EWL >75%) that those with HBP (17.8%, p = 0.026) (Table 3). We next investigated the associations of QOL with favorable outcomes in patients with LSG. At baseline, patients with better QOL at baseline (BAROS −2.5 to −1) (47%) had significantly better results (%EWL >75%) than those with worse QOL (BAROS −2.7 to −4.0) (p = 0.01; Table 5).

Conversely, %EWL did not show any significant association with gender, occupation, place of residency, smoking, presence of diabetes, hypothyroidism, dyslipidemia, back pain, knee pain, fatigue, and nutritional habits (Tables 1 –6).

A multivariate linear regression analysis was conducted for EWL >75% as a dependent variable and other independent variables having a significant correlation with 95% confidence interval, for age (OR = 0.159, p = 0.047), BMI (OR = −0.269, p = 0.002), HBP (OR = −0.193, p = 0.28), and QOL (OR = 0.221, p = 0.010).

Table 1.

Demographics Compared with Percentage of Excess Weight Loss

Gender
%EWL	Female, n (%)	Male, n (%)	p
<20%	1 (0.8)	0 (0)	0.525
21–49%	12 (8.9)	4 (3.0)	0.750
50–75%	30 (22.4)	7 (5.2)	0.134
>75%	53 (39.5)	27 (20.2)	0.091
Total	96 (71.6)	38 (28.4)

Age
	18–40 Years, n (%)	>40 Years, n (%)	p
<20%	0 (0)	1 (0.8)	0.251
21–49%	9 (6.7)	7 (5.2)	0.967
50–75%	16 (11.9)	21 (15.7)	0.051
>75%	51 (38.1)	29 (21.6)	0.013
Total	76 (56.7)	58 (43.3)

	BMI
%EWL	30–39.9 kg/m², n (%)	>40 kg/m², n (%)	p
<20%	1 (0.8)	0 (0)	0.329
21–49%	6 (4.4)	10 (7.5)	0.232
50–75%	11 (8.2)	26 (19.4)	0.001
>75%	51 (38.1)	29 (21.6)	0.001
Total	69 (51.5)	65 (48.5)

BMI, body mass index; %EWL, percentage of excess weight loss.

The italicized values are statistically significant.

Table 2.

Lifestyle Compared with Percentage of Excess Weight Loss

Occupation style
%EWL	Sedentary, n (%)	Active, n (%)	p
<20%	0 (0)	1 (0.8)	0.351
21–49%	8 (6.0)	8 (6.0)	0.749
50–75%	18 (13.5)	19 (14.1)	0.732
>75%	36 (26.8)	44 (32.8)	0.719
Total	62 (46.3)	72 (53.7)

Place of residence
%EWL	Local, n (%)	Foreigner, n (%)	p
<20%	0 (0)	1 (0.8)	0.050
21–49%	4 (3.0)	12 (8.9)	0.913
50–75%	8 (6.0)	29 (21.6)	0.464
>75%	23 (17.2)	57 (42.5)	0.398
Total	35 (26.2)	99 (73.8)

Smoking
Smoking	Smoker, n (%)	Nonsmoker, n (%)	p
<20%	0 (0)	1 (0.8)	0.581
21–49%	4 (3.0)	12 (8.9)	0.850
50–75%	7 (5.2)	30 (22.4)	0.474
>75%	20 (14.9)	60 (44.8)	0.533
Total	31 (23.1)	103 (76.9)

Table 3.

Comorbidities Compared with Percentage of Excess Weight Loss

%EWL	Yes, n (%)	No, n (%)	p
T2DM
<20%	0 (0)	1 (0.8)	0.737
21–49%	3 (2.3)	13 (9.7)	0.437
50–75%	2 (1.5)	35 (26.1)	0.117
>75%	12 (8.9)	68 (50.7)	0.327
Total	17(12.7)	117 (87.3)
HBP
<20%	1 (0.8)	0 (0)	0.129
21–49%	1 (0.8)	15 (11.2)	0.024
50–75%	15 (11.2)	22 (16.4)	0.122
>75%	24 (17.8)	56 (41.8)	0.026
Total	41 (30.6)	93 (69.4)
Hypothyroidism
<20%	1 (0.8)	0 (0)	0.099
21–49%	4 (3.0)	12 (8.9)	0.148
50–75%	6 (4.4)	31 (23.2)	0.559
>75%	7 (5.2)	73 (54.5)	0.537
Total	18 (13.4)	116 (86.6)
Dyslipidemias
<20%	0 (0)	1 (0.8)	0.351
21–49%	8 (6.0)	8 (6.0)	0.749
50–75%	14 (10.4)	23 (17.2)	0.226
>75%	40 (29.8)	40 (29.8)	0.291
Total	62 (46.2)	72 (53.8)

HBP, high blood pressure; T2DM, type 2 diabetes mellitus.

The italicized values are statistically significant.

Table 4.

Complaints Compared with Percentage of Excess Weight Loss

%EWL	Yes, n (%)	No, n (%)	p
Back pain
<20%	0 (0)	1 (0.8)	0.221
21–49%	9 (6.7)	7 (5.2)	0.764
50–75%	23 (17.2)	14 (10.4)	0.719
>75%	48 (35.8)	32 (23.9)	0.931
Total	80 (59.7)	54 (40.3)
Knee pain
<20%	0 (0)	1 (0.8)	0.214
21–49%	10 (7.5)	6 (4.5)	0.858
50–75%	26 (19.4)	11 (8.2)	0.150
>75%	45 (33.5)	35 (26.1)	0.226
Total	81 (60.4)	53 (39.6)
Fatigue
<20%	1 (0.8)	0	0.388
21–49%	9 (6.7)	7 (5.2)	0.917
50–75%	22 (16.4)	15 (11.2)	0.773
>75%	45 (33.6)	35 (26.1)	0.730
Total	77 (57.5)	57 (42.5)

Table 5.

Quality of Life Compared with Percentage of Excess Weight Loss

QOL score
%EWL	−2.7 to −4.0, n (%)	−2.5 to −1, n (%)	p
<20%	1 (0.8)	0	0.158
21–49%	5 (3.7)	11 (8.2)	0.359
50–75%	9 (6.7)	28 (20.9)	0.061
>75%	17 (12.7)	63 (47.0)	0.010
Total	32 (23.9)	102 (76.1)

QOL, quality of life.

The italicized values are statistically significant.

Table 6.

Nutritional Habits Compared with Percentage of Excess Weight Loss

%EWL	Breakfast, n (%)	Lunch, n (%)	Dinner, n (%)	p
Which is the largest meal of the day?
<20%	1 (0.8)	0	0	0.123
21–49%	4 (3.0)	7 (5.2)	5 (3.7)	0.609
50–75%	8 (5.9)	11 (8.2)	18 (13.5)	0.470
>75%	13 (9.7)	33 (24.6)	34 (25.4)	0.461
	26 (19.4)	51 (38.0)	57 (42.6)
Do you snack junk food?
<20%	1 (0.8)	0		0.308
21–49%	8 (5.9	8 (5.9)		0.949
50–75%	16 (12.0)	21 (15.7)		0.390
>75%	41 (30.6)	39 (29.1)		0.574
	66 (49.3)	68 (50.7)
Do you eat large amount of food?
<20%	0	1 (0.8)		0.243
21–49%	7 (5.2)	9 (6.7)		0.237
50–75%	26 (19.4)	11 (8.2)		0.064
>75%	44 (32.9)	36 (26.8)		0.483
	77 (57.5)	57 (42.5)
Do you eat processed carbs?
<20%	1 (0.8)	0		0.243
21–49%	6 (4.5)	10 (7.5)		0.237
50–75%	16 (11.8)	21 (15.7)		0.064
>75%	44 (32.9)	36 (26.8)		0.483
	67 (50.0)	67 (50.0)
Do you eat more in anxiety?
<20%	1 (0.8)	0		0.381
21–49%	11 (8.2)	5 (3.7)		0.301
50–75%	20 (14.9)	17 (12.7)		0.701
>75%	44 (32.8)	36 (26.9)		0.625
	76 (56.7)	58 (43.3)

Discussion

Most models study the correlation between gastric bypass and future weight loss. However, only a few studies have investigated the association of sleeve gastrectomy on weight loss in the context of several health, demographic, and related variables. Knowing why patients fail to achieve adequate weight loss after LSG can help surgeons propose better candidates, warn patients of the estimated weight loss, and improve perioperative interventions in patients who are estimated to have worse results. In this study, we found that advancing age, high BMI, presence of HBP, and poor QOL can significantly affect the %EWL in obese patients following LSG. A trend was found in patients who ate a large amount of food at a specific time and those who ate refined carbs compared with %EWL. No association was found with gender, occupation style, place of residence, smoking, diabetes, hypothyroidism, dyslipidemia, back pain, knee pain, fatigue, and other nutritional habits.

Association between age and weight loss following bariatric surgery is extensively reported in the literature, showing an increased %EWL in younger than older patients. These reports are consistent with our findings, as we found that the younger patients (between 18 and 40 years) had better results than the patients >40 years. A similar association is reported in several other papers. For example, in an analysis of 337 patients, Contreras et al concluded that patients younger than 45 lost a greater amount of excess BMI than older patients after bariatric surgery.⁸ This tendency was found in both bypass and sleeve gastrectomy.

Similarly, a systematic review performed a multivariate analysis to examine the impact of age on weight loss in patients with LSG.⁹ This study included 14 studies, among those, 7 studies found that age can affect weight loss, whereas seven studies did not find such effects. The studies that did find that age affects weight loss were consistent in reporting age as a negative predictor. This article is also consistent with our results.

These findings could be explained by the fact that aging is associated with a progressive decline in the quantity and quality of muscular tissue and reduced basal metabolic rate and energy requirements. These metabolic changes could influence the response to bariatric surgery in such patients.

Regarding preoperative BMI, we report that patients with BMI between 30 and 39.9 kg/m² had increased %EWL than those with BMI >40 kg/m². Although heavier patients tend to lose more weight after surgery, because they have a more significant amount of weight to lose at baseline, this study suggests that excellent results are seen in patients with lower BMI. The better results seen in lighter bariatric patients are one of the most reported prognostic factors for weight loss after bariatric surgery. Similar to our findings, the study by Steinbeisser et al, with 204 patients, showed better weight loss in patients with lower BMI.¹⁰ These findings are consistent with the data from the Roux-en-Y population.^11,12

When comorbidities were evaluated, a strong correlation was found between HBP and weight loss after surgery. Patients with HBP had reduced weight loss compared with patients without HBP. In a systematic review by Cottam et al, HBP was investigated in eight articles with multivariate analyses.⁹ HBP was found to predict weight loss in three studies, including two studies that reported HBP as a negative predictor of weight loss. The same tendency was found in another study where patients with HBP were associated with impaired postoperative weight loss compared with patients without HBP.¹⁰ This effect can partly be explained by the downregulation of β-adrenergic receptors in patients with HBP, because β-adrenergic receptors mediate increases in energy expenditure. Therefore, hypertensive patients have a reduced ability to dissipate calories.¹³

QOL, defined as the impact of health on an individual's daily functioning, encompassing physical, psychological, and social wellbeing, is highly subjective and relies on personal experiences, beliefs, and expectations.¹⁴ Preoperative QOL has scarcely been evaluated as a predictor of weight loss. Some studies have evaluated the impact of preoperative psychological status as a predictor of weight loss,^15,16 and some have reported that greater postoperative QOL is strongly associated with maintenance of weight loss in patients with RYGBP.¹⁷ However, we did not find articles that evaluate preoperative QOL as a prognosis factor for weight loss.

In this series, the preoperative QOL demonstrated a negative score in every case, ranking from −1 to −4.5, with a mean score of −2.4. Although every patient reported impaired QOL, we divided them into two groups, including those with deep and mild impaired QOL. We found that the patients with mildly impaired QOL before surgery exhibited greater excellent results in terms of %EWL. Thus, our findings show that the measurement of QOL could be a predictor of weight loss after bariatric surgery. Thus, we may conclude that other QOL scores could predict weight loss after bariatric surgery. It appears that patients with more impaired QOL have intrinsic or extrinsic elements that do not allow them to lose the necessary weight, increasing the vicious circle. In this scenario, focusing efforts to improve the QOL before bariatric surgery could be a critical intervention before the surgery.

The primary limitation of our study is its retrospective design. In conclusion, our analysis shows that younger patients, those with less BMI, and those without HPB have a greater chance of losing weight after LSD. In addition, this article shows that less impaired preoperative QOL could be a predictor of success, in terms of weight loss, after LSG. Other comorbidities, including demographics and feeding habits, did not show any relationship with the %EWL post-LSG.

Footnotes

Acknowledgment

The authors thank Health Care System Covadonga.

Authors' Contributions

P.B.D.A.: Conceptualization (equal), formal analysis (supporting), investigation (supporting), supervision (supporting), validation (lead); M.D.-R.: Data curation (equal), methodology (equal), project administration (lead), software (supporting), visualization (lead), writing original draft (lead); K.G.-A.: Data curation (equal), methodology (equal), project administration (supporting), software (lead), visualization (equal); R.J.R.: Conceptualization (lead), formal analysis (lead), funding acquisition (lead), investigation (lead), methodology (lead), resources (lead), supervision (lead), validation (supporting), visualization (equal), writing review and editing (lead).

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

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