Next Article in Journal
Going High to Keep Body Mass Low: How Post-Exercise Exposure to a Simulated High Altitude Influences Energy Balance—A Proof-of-Concept Pilot Study
Previous Article in Journal
A Comparison of the Efficacy of Online HAPIFED versus Online Cognitive Behavioural Therapy for Binge Eating Disorder: A Randomized Controlled Trial
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Communication

Quality of Life in Patients with Obesity: The Role of Multidisciplinary Rehabilitation Medicine

1
Department of Rehabilitation, Nutrition and Obesity, Berck Maritime Hospital, Paris University Hospitals, 62600 Berck, France
2
Department of Psychiatry, University Lille, Inserm, CHU Lille, U1172—LilNCog—59000 Lille Neuroscience & Cognition, F-59000 Lille, France
3
Department of Biostatistics, Amiens University, 80000 Amiens, France
*
Author to whom correspondence should be addressed.
Obesities 2024, 4(2), 160-168; https://doi.org/10.3390/obesities4020015
Submission received: 26 May 2024 / Revised: 10 June 2024 / Accepted: 13 June 2024 / Published: 18 June 2024

Abstract

:
Background: Little is known about the role of rehabilitation medicine in obesity. Objective: to examine the benefits of a multidisciplinary rehabilitation program on the quality of life in patients with severe obesity. Methodology: We included 124 patients with obesity (mean age: 57 years; BMI ≥30), in an 8-week in-hospital multidisciplinary supervised program combining physiotherapy, nutrition and psychological support. Clinical, bio-psychological and functional parameters, as well as an obesity-specific quality-of-life score, were acquired at 0 and 8 weeks. Results: The quality-of-life score improved significantly at 8 weeks, from 60.8 to 68.8 (p < 0.0001), and was positively correlated with cardio-respiratory function (r = 0.47; p < 0.0001). Conclusions: Our results highlight the important role of multidisciplinary rehabilitation medicine and its integrated approach to improve the quality of life of people with obesity.

1. Introduction

According to the World Health Organization, the worldwide prevalence of obesity (defined as a BMI  ≥  30 kg/m2) has nearly tripled since 1975, affecting 650 million adults [1]. The prevalence of obesity is generally higher in women than in men in all age groups. In France, recent surveys have found obesity to have an estimated prevalence of 15% [2].
Obesity can affect all physiological body functions. People with obesity exhibit significant adverse health outcomes, including cardio-metabolic and respiratory disorders, type 2 diabetes and musculoskeletal problems [3,4,5]. Additionally, a decline in muscle mass and strength, known as sarcopenia, is very common among patients with obesity [6]. These conditions can rapidly lead to a loss of functional independence, psychosocial issues, diminished quality of life and reduced lifespan [7,8].
Current obesity management include dietetics, bariatric surgery and, more recently, incretin-based therapy [9,10,11]. In addition, rehabilitation centers have been developed in recent years. They offer multidisciplinary intensive lifestyle intervention programs based on a combination of physical therapy, nutrition and psychological support [12,13] and are associated with a 5–8% weight loss and an improvement in cardiovascular risk [14,15,16]. However, little is known about their impact on the quality of life. The aim of this study was to assess the specific effects of a dedicated rehabilitation program on the quality of life in patients with obesity.

2. Patients and Methods

2.1. Setting and Study Population

This prospective study was conducted between April 2017 and August 2018 in the Physical Medicine and Functional Rehabilitation Department, which specializes in the care of patients with severe obesity, at the Maritime Hospital (Greater Paris University Hospitals, AP-HP, Berck, France). The protocol conformed to the principles outlined by the Declaration of Helsinki and was in accordance with the French CNIL requirements (National Committee for the Protection of Privacy and Personal Data). All participants provided written informed consent.
Patients were eligible if they were between 18 and 65 years, had a BMI ≥ 30 kg/m2, and had at least one comorbidity (hypertension, type 2 diabetes, sleep apnea, cardiovascular disease, osteoarthritis) and had been on stable medication for at least 3 months prior to enrollment. The patients were referred by endocrinology departments and family doctors. They were then hospitalized in our unit for a mean duration of 8 weeks.
The exclusion criteria were severe cardiac or pulmonary disease, musculoskeletal disorders that precluded exercise training, and significant cognitive disorders. Candidates were also excluded if they were unable to participate in the proposed therapeutic program. Each participant acted as his or her own control.
Patients received a standardized clinical examination and were then assessed by each interdisciplinary team member. All data were collected on admission to the program.

2.2. The Multidisciplinary Rehabilitation Program

2.2.1. Exercise Intervention

The training program involved aerobic exercise (5 days per week). Each patient performed 2 h of exercise per day. Patients had 1 h session of land-based exercise in the morning, in the training room, and one 1 h session of aquatic-exercise (indoor swimming pool) in the afternoon. All sessions included 5 min of warm-up, 30–40 min of main work, 5 min of cooldown and 10 min of stretching. Groups of 4–8 participants performed exercise with a focus on improving muscle strength, endurance ability (walking, cycling, swimming), balance and flexibility (Pilates-inspired exercises), with adjustments according to individual perception of effort or pain. During each session, exercise, intensity and volume were individualized. All sessions were supervised by physiotherapists and certified trainers.

2.2.2. Nutrition Program

All participants had an initial nutritional assessment (24 h dietary recall and diet history), during a one-on-one consultation with a dietician. The estimated individual daily total energy requirements were calculated using the Harris–Benedict equation [17]. Each patient received an individualized diet plan. The balanced diet approximately comprised 55% carbohydrates, 30% fats, and 15% protein (1 g of protein/kg of the ideal body weight). All meals were provided in our ward during the 8-week program. Additionally, weekly group-based educational meetings were organized to empower individual skills in nutrition and improve eating habits.

2.2.3. Psychological Support

A clinical psychologist assessed key clinical characteristics using interviews (1 h session) to collect data about each participant’s life history, and the participants completed a series of self-ratings. Individual and group-based psychological interventions were delivered weekly (1 h session), targeting an improvement in general well-being, perception of physical ability, eating behavior, self-esteem and body image.

2.3. Outcome Measures

2.3.1. Anthropometric and Cardiometabolic Measurements

Clinical and biological measures, as well as body composition parameters, were measured at baseline and at the end of the 8-week program.
Height, weight and waist circumference (WC) were measured by the same investigator following standard procedures. Body mass index (BMI) was calculated as weight (kg)/height (m2). Blood pressure and heart rate were measured using a sphygmomanometer with cuffs of appropriate size, according to standard procedures.
Body composition was obtained by bioelectrical impedance analysis (Tanita BC-418 MA, Tanita Corporation, Tokyo, Japan).
Plasma glucose, glycated hemoglobin A1c (HbA1c), lipoprotein levels, creatinine and albuminemia were measured in fasting blood samples using standard methods.
All of the assessments described below were conducted at baseline and repeated at the completion of the program.

2.3.2. Physical Fitness Assessment

Physical performance and cardiorespiratory fitness were assessed by the same physiotherapist by applying the 6 min walk test (6MWT), according to international guidelines and validated in obesity [18]. The 6MWT was performed along a 100 m corridor in the ward. Pulse and oxygen saturation are measured before the start and at the end of the test. The patient may walk as fast as possible and is allowed to stop or rest during the test if needed.

2.3.3. Pain Assessment

We used the Numeric Rating Scale (NRS-11) to evaluate the severity of musculoskeletal pain. The patient is asked to rate the pain on a scale from 0 to 10, where 0 represents “no pain at all” and 10 represents “the worst pain a person has ever experienced”.

2.3.4. Psychiatric Assessment

Given that anxiety disorders and depression are frequently linked to obesity, the Hospital Anxiety and Depression Scale (HADS) was administered to all study patients. This self-questionnaire is a simple, widely used tool for the detection of anxiety and depression in individuals with relevant physical health problems. The 14 items of the HADS are scored on a Likert scale from 0 (low symptom frequency) to 3 (high symptom frequency). The final score of each subscale (anxiety and depression) ranges from 0 (best) to 21 (worst).

2.3.5. Health-Related Quality of Life (QoL) Assessment

Health-related quality of life was assessed with the validated French version of the Quality Of Life Obesity and Dietetics scale (QOLOD) [19]. The QOLOD is a 36-item scale that includes 5 dimensions—physical impact, psychosocial impact, impact on sex life, food rebalancing, and nutritional well-being. Each item is rated on a 5-point scale, and the results are expressed as percentages, with higher scores indicating a better QoL.

3. Statistical Analysis

For descriptive analysis, categorical variables are presented as frequencies/percentages and compared using the Pearson χ2 test or Fisher’s exact test, as appropriate. Continuous variables are presented as the mean ± standard deviation or median [range]. The efficacy of the rehabilitation program was tested with Student’s t test for quantitative variables collected at the beginning and at the end of the program. The associations between the QoL score and changes in variables of interest were assessed using Spearman’s correlation coefficient.
We used a simple linear model to assess the associations between changes in variables of interest and the change in QoL. Variables associated with QoL at 10% α-risk in the univariate analyses were used to build a multiple linear model with backward selection. Before modeling, we used a multiple imputation technique with 10 replications to impute missing data, resulting in 10 backward selected linear models. Finally, a multiple full linear model was fitted using all the variables that were selected more than five times among the ten replicated backward models. A two-sided p value < 5% indicated statistical significance.
The analyses were performed with R software, version 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria; www.r-projet.org, accessed on 22 December 2020).

4. Results

4.1. Demographics and Medical Conditions of the Participants

The 124 patients had a mean (SD) age of 57 ± 12 years, and 65% were women. The mean BMI at baseline was 46.2 ± 10 (kg/m2). The prevalence of obesity-related comorbidities is detailed in Table 1.

4.2. Change in Parameters after the Rehabilitation Program

4.2.1. Anthropometric Parameters

After rehabilitation, the group showed significant weight loss (mean: −9 kg), an improved BMI from 46.2 to 42.8 and a decreased waist circumference and fat mass (p < 0.05) (see Table 2).

4.2.2. Functional Parameters

The mean walk distance measured by the 6 min walk test increased from 324 m to 441 m, corresponding to a gain of +43% (p < 0.0001). The mean intensity of musculoskeletal pain significantly decreased from 6 to 3.6 (p < 0.0001).

4.2.3. Quality of Life and Psychiatric Symptoms

The global score of QoL significantly rose (see Table 3). Improvement in QoL was positively correlated with the increase in the 6 min walk test (r = 0.47; (p < 0.0001)). Both the anxiety and depression symptoms scores significantly decreased (p < 0.001). In the multivariate analysis, the reduction in the anxiety and depression scores were associated with QoL (see Table 4).

5. Discussion

As expected, in our population of patients, a personalized normal-calorie diet combined with a training program resulted in significant weight loss, mainly due to a reduction in fat mass and an improvement in fat distribution (i.e., a reduction in visceral adiposity as indicated by a reduction in waist circumference). However, the lean mass (which reflects muscle mass) remained stable in our patients. Our results corroborate those of Colleluori et al., affirming that, unlike weight loss induced by a restrictive hypocaloric diet alone (resulting in a reduction in fat mass and also muscle mass), a program combining nutrition and physical activity may prevent sarcopenia and may improve the QoL of obese patients [6]. Additionally, Fontana et al. demonstrated that a 4-week multidisciplinary rehabilitation protocol for patients with obesity and a post-COVID-19 condition was effective on physical performance, reduction in pain and improvement in psychological well-being [20].
In our study, the increase in 6MWT was positively correlated with the improvement in the QoL of our patients, thus highlighting the major role of functional rehabilitation in terms of quality of life [21].
Regarding psychological status, a reduction in the anxiety and depression scores after the therapeutic program was significantly associated with an improvement in QoL. It is well established that physical exercise positively affects mental health [22]. There are also consistent positive effects of dietary interventions on anxiety and depression symptoms [23]. Given the potentially cumulative effects of diet, exercise and psychological care, we believe that the physical and psychological amelioration observed in our patients contributed to improved functional capacities and, consequently, an improved QoL.
Despite the increased understanding of the complex pathophysiology of obesity (e.g., regarding genetics, inflammation, neuro-endocrine disorders, psychiatric conditions and a myriad of environmental factors), traditional approaches in obesity management have mainly focused on weight loss achievement (i.e., obtaining a negative energy balance through dietary changes and exercise or bariatric surgery). By contrast, in our study, we focused on outcomes that are often considered secondary, such as quality of life (QoL). Indeed, as a chronic disease, obesity is characterized by slow progression and long duration, which affects several dimensions of overall health, such as one’s physical and psychological capabilities, cardio-metabolic status, mobility and psycho-social well-being, thus creating a large variety of bio-psycho-social phenotypes of obesity [24]. Interestingly, in a large longitudinal study including 4265 patients suffering from osteoarthritis (70% with overweight) who received a multidisciplinary program combining patient education and physiotherapy exercises (lasting 6–12 weeks), it was shown that in addition to significant weight loss over the 2-year follow-up period, 80% of the participants improved their quality of life and their activity limitations [25].
Therefore, taking into account the real-life difficulties experienced by patients with obesity (e.g., chronic pain, cardiorespiratory, mobility and affective disorders), QoL has become a primary therapeutic target and is an exciting opportunity through which to exert beneficial effects [26]. Thus, multidisciplinary obesity centers that provide an integrated approach are needed.

Strengths and Limitations

This study presents two main strengths. First, it involved a rare, onsite, supervised program that accurately investigated the relationships between QoL and psycho-physical performance levels in patients with obesity. Second, our intervention program applied a multidisciplinary therapy for obesity treatment, including nutrition, exercise, psychological support and therapeutic patient education, which is in line with the recent clinical guidelines for the treatment of obesity that recommend a comprehensive and patient-centered approach [27].
Several limitations must be mentioned. First, our 124 participants may constitute a relatively small sample, and the short follow-up period of 8 weeks may appear insufficient for reaching definitive conclusions. A longer follow-up period, including outpatient assessment with visits at 6- and 12-month points, would be helpful to evaluate the long-term effectiveness and sustainability of this rehabilitation program. Additionally, in this study, the patients sought help for obesity at a specialized center, and therefore may not be representative of all patients with obesity. In the future, a control group with patients receiving ambulatory obesity care may be useful to precisely study the role of a hospital-based program. Second, we must recall that our intervention is an intensive hospital program, which requires outpatient monitoring to remain effective, in order to maintain the benefits over the long term. Indeed, a mixed inpatient and outpatient obesity management program, with professionals trained in Therapeutic Patient Education, demonstrated its effectiveness on favorable weight change in 70% of participants after 5 years [28]. Third, despite our methodology efforts to precisely characterize the participants, confounding factors such as medication changes and psychological support outside the program might have influenced the outcomes. Finally, this work did not include a cost-effectiveness analysis. However, when the healthcare system or patient preferences exclude bariatric surgery as an option, intensive behavioral multidisciplinary weight management programs appear to be valuable cost-effective interventions [29,30].

6. Conclusions

The associations between obesity, mobility disability, cardiometabolic disorders and psychological distress suggest the need for a global and integrative approach to health care. Our study highlights the role of a multidisciplinary rehabilitation program in patients with obesity to improve their QoL and abilities to perform activities of daily living.

Author Contributions

Conceptualization, Y.K. and R.L. and C.M.; methodology, Y.K., R.L., A.A. and C.M.; formal analysis, M.D. and A.A.; investigation, Y.K., R.L., C.M. and I.D.; data curation, Y.K. and C.M.; writing—original draft preparation, Y.K.; writing—review and editing, Y.K. and A.A.; project administration, Y.K. and R.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Paris University Hospitals (62600 BERCK).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Acknowledgments

The authors warmly thank all of the staff of the rehabilitation unit of Maritime Hospital in Berck and all of the participants.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Obesity and Overweight. Available online: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed on 25 March 2020).
  2. Matta, J.; Carette, C.; Rives Lange, C.; Czernichow, S. French and worldwide epidemiology of obesity. Presse Medicale 2018, 47, 434–438. [Google Scholar] [CrossRef] [PubMed]
  3. Bhupathiraju, S.N.; Hu, F.B. Epidemiology of Obesity and Diabetes and Their Cardiovascular Complications. Circ. Res. 2016, 118, 1723–1735. [Google Scholar] [CrossRef] [PubMed]
  4. Duclos, M. Osteoarthritis, obesity and type 2 diabetes: The weight of waist circumference. Ann. Phys. Rehabil. Med. 2016, 59, 157–160. [Google Scholar] [CrossRef] [PubMed]
  5. Sarwer, D.B.; Polonsky, H.M. The Psychosocial Burden of Obesity. Endocrinol. Metab. Clin. N. Am. 2016, 45, 677–688. [Google Scholar] [CrossRef] [PubMed]
  6. Colleluori, G.; Villareal, D.T. Aging, obesity, sarcopenia and the effect of diet and exercise intervention. Exp. Gerontol. 2021, 155, 111561. [Google Scholar] [CrossRef] [PubMed]
  7. Kolotkin, R.L.; Andersen, J.R. A systematic review of reviews: Exploring the relationship between obesity, weight loss and health-related quality of life. Clin. Obes. 2017, 7, 273–289. [Google Scholar] [CrossRef] [PubMed]
  8. Wang, C.; Chan, J.S.Y.; Ren, L.; Yan, J.H. Obesity Reduces Cognitive and Motor Functions across the Lifespan. Neural Plast. 2016, 2016, 2473081. [Google Scholar] [CrossRef] [PubMed]
  9. Kushner, R.F. Weight Loss Strategies for Treatment of Obesity: Lifestyle Management and Pharmacotherapy. Prog. Cardiovasc. Dis. 2018, 61, 246–252. [Google Scholar] [CrossRef] [PubMed]
  10. Belle, S.H.; Berk, P.D.; Courcoulas, A.P.; Flum, D.R.; Miles, C.W.; Mitchell, J.E.; Pories, W.J.; Wolfe, B.M.; Yanovski, S.Z.; Longitudinal Assessment of Bariatric Surgery Consortium Writing Group. The Safety and Efficacy of Bariatric Surgery: The Longitudinal Assessment of Bariatric Surgery (LABS). Surg. Obes. Relat. Dis. Off. J. Am. Soc. Bariatr. Surg. 2007, 3, 116–126. [Google Scholar] [CrossRef] [PubMed]
  11. Drucker, D.J. GLP-1 physiology informs the pharmacotherapy of obesity. Mol. Metab. 2022, 57, 101351. [Google Scholar] [CrossRef]
  12. Kouidrat, Y.; Diouf, M.; Desailloud, R.; Louhou, R. Effects of a diet plus exercise program on thyroid function in patients with obesity. Metab. Open. 2019, 2, 100008. [Google Scholar] [CrossRef] [PubMed]
  13. Jakobsen, G.S.; Småstuen, M.C.; Sandbu, R.; Nordstrand, N.; Hofsø, D.; Lindberg, M.; Hertel, J.K.; Hjelmesæth, J. Association of Bariatric Surgery vs Medical Obesity Treatment With Long-term Medical Complications and Obesity-Related Comorbidities. JAMA 2018, 319, 291–301. [Google Scholar] [CrossRef] [PubMed]
  14. Ghroubi, S.; Kossemtini, W.; Mahersi, S.; Elleuch, W.; Chaabene, M.; Elleuch, M.H. Contribution of isokinetic muscle strengthening in the rehabilitation of obese subjects. Ann. Phys. Rehabil. Med. 2016, 59, 87–93. [Google Scholar] [CrossRef] [PubMed]
  15. Giordano, F.; Berteotti, M.; Budui, S.; Calgaro, N.; Franceschini, L.; Gilli, F.; Masiero, M.; Raschella, G.; Salvetti, S.; Taddei, M.; et al. Multidimensional improvements induced by an intensive obesity inpatients rehabilitation programme. Eat. Weight. Disord. EWD 2017, 22, 329–338. [Google Scholar] [CrossRef] [PubMed]
  16. American College of Cardiology/American Heart Association Task Force on Practice Guidelines, Obesity Expert Panel, 2013. Executive summary: Guidelines (2013) for the management of overweight and obesity in adults: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Obesity Society published by the Obesity Society and American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Based on a systematic review from the The Obesity Expert Panel, 2013. Obesity 2014, 22 (Suppl. S2), S5–S39. [Google Scholar]
  17. Bendavid, I.; Lobo, D.N.; Barazzoni, R.; Cederholm, T.; Coëffier, M.; de van der Schueren, M.; Fontaine, E.; Hiesmayr, M.; Laviano, A.; Pichard, C.; et al. The centenary of the Harris-Benedict equations: How to assess energy requirements best? Recommendations from the ESPEN expert group. Clin. Nutr. Edinb. Scotl. 2021, 40, 690–701. [Google Scholar] [CrossRef] [PubMed]
  18. Larsson, U.E.; Reynisdottir, S. The six-minute walk test in outpatients with obesity: Reproducibility and known group validity. Physiother. Res. Int. 2008, 13, 84–93. [Google Scholar] [CrossRef] [PubMed]
  19. Ziegler, O.; Filipecki, J.; Girod, I.; Guillemin, F. Development and validation of a French obesity-specific quality of life questionnaire: Quality of Life, Obesity and Dietetics (QOLOD) rating scale. Diabetes Metab. 2005, 31, 273–283. [Google Scholar] [CrossRef] [PubMed]
  20. Fontana, J.M.; Alito, A.; Piterà, P.; Verme, F.; Cattaldo, S.; Cornacchia, M.; Mai, S.; Brunani, A.; Capodaglio, P. Whole-Body Cryostimulation in Post-COVID Rehabilitation for Patients with Obesity: A Multidisciplinary Feasibility Study. Biomedicines 2023, 11, 3092. [Google Scholar] [CrossRef] [PubMed]
  21. Jakicic, J.M.; Rogers, R.J.; Davis, K.K.; Collins, K.A. Role of Physical Activity and Exercise in Treating Patients with Overweight and Obesity. Clin. Chem. 2018, 64, 99–107. [Google Scholar] [CrossRef]
  22. Schuch, F.B.; Vancampfort, D.; Rosenbaum, S.; Richards, J.; Ward, P.B.; Stubbs, B. Exercise improves physical and psychological quality of life in people with depression: A meta-analysis including the evaluation of control group response. Psychiatry Res. 2016, 241, 47–54. [Google Scholar] [CrossRef] [PubMed]
  23. Firth, J.; Marx, W.; Dash, S.; Carney, R.; Teasdale, S.B.; Solmi, M.; Stubbs, B.; Schuch, F.B.; Carvalho, A.F.; Jacka, F.; et al. The Effects of Dietary Improvement on Symptoms of Depression and Anxiety: A Meta-Analysis of Randomized Controlled Trials. Psychosom. Med. 2019, 81, 265–280. [Google Scholar] [CrossRef]
  24. Donini, L.M.; Rosano, A.; Di Lazzaro, L.; Lubrano, C.; Carbonelli, M.; Pinto, A.; Giusti, A.M.; Lenzi, A.; Siervo, M. Impact of Disability, Psychological Status, and Comorbidity on Health-Related Quality of Life Perceived by Subjects with Obesity. Obes. Facts. 2020, 13, 191–200. [Google Scholar] [CrossRef] [PubMed]
  25. Fosdahl, M.A.; Berg, B.; Risberg, M.A.; Øiestad, B.E.; Holm, I. Body Mass Index, Quality of Life and Activity Limitation Trajectories over 2 Years in Patients with Knee or Hip Osteoarthritis: A Dual Trajectory Approach Based on 4265 Patients Included in the AktivA Quality Register. J. Clin. Med. 2023, 12, 7094. [Google Scholar] [CrossRef]
  26. Fontaine, K.R.; Barofsky, I. Obesity and health-related quality of life. Obes. Rev. Off. J. Int. Assoc. Study Obes. 2001, 2, 173–182. [Google Scholar] [CrossRef] [PubMed]
  27. Durrer Schutz, D.; Busetto, L.; Dicker, D.; Farpour-Lambert, N.; Pryke, R.; Toplak, H.; Widmer, D.; Yumuk, V.; Schutz, Y. European Practical and Patient-Centred Guidelines for Adult Obesity Management in Primary Care. Obes. Facts. 2019, 12, 40–66. [Google Scholar] [CrossRef]
  28. Buclin-Thiébaud, S.; Pataky, Z.; Bruchez, V.; Golay, A. New psycho-pedagogic approach to obesity treatment: A 5-year follow-up. Patient Educ. Couns. 2010, 79, 333–337. [Google Scholar] [CrossRef] [PubMed]
  29. Boyers, D.; Retat, L.; Jacobsen, E.; Avenell, A.; Aveyard, P.; Corbould, E.; Jaccard, A.; Cooper, D.; Robertson, C.; Aceves-Martins, M.; et al. Cost-effectiveness of bariatric surgery and non-surgical weight management programmes for adults with severe obesity: A decision analysis model. Int. J. Obes. 2021, 45, 2179–2190. [Google Scholar] [CrossRef]
  30. Dhillon, A.; Mayer, M.; Kysh, L.; Fox, D.S.; Hegedus, E.; Vidmar, A.P. Cost-effectiveness analysis of individual-level obesity treatment in paediatrics: A scoping review. Pediatr. Obes. 2024, 19, e13100. [Google Scholar] [CrossRef]
Table 1. Demographics and medical conditions of the participants.
Table 1. Demographics and medical conditions of the participants.
DemographicsN = 124 (100%)
Gender (M/F)44/80
Age (years) (mean ± SD)57 ± 12
Smoking
Current22 (13%)
Former25 (25%)
Never77 (62%)
Medical conditions
Hypertension, n (%)72 (58%)
Type 2 Diabetes45 (36%)
Dyslipidemia26 (21%)
Obstructive Sleep Apnea69 (56%)
Arthritis95 (77%)
Mood Disorders51 (41%)
Depression score → 7.6 ± 4.5 → 5.8 ± 4 → <0.001, Notes: data presented are the mean  ±  SD or N (%).
Table 2. Baseline and post-intervention measures.
Table 2. Baseline and post-intervention measures.
VariableBaselinePost Interventionp-Value
General measures <0.05
Body weight (kg)125.7 ± 34.5116.8 ± 30.50.0354
BMI (kg/m2)46.2 ± 1042.8 ± 90.0088
Waist circumference, cm129.7 ± 18121.5 ± 170.0013
Systolic blood pressure, mm Hg127 ± 13116 ± 9<0.0001
Diastolic blood pressure, mm Hg70 ± 1065 ± 80.0002
Bioelectrical impedance analysis, mean ± SD
Body fat (%)
Fat mass (kg)57.9 ± 16.951.2 ± 15.30.0031
Lean mass (kg)63.0 ± 15.561.3 ± 15.60.4167
Estimated resting energy expenditure (kcal/day)2040 ± 5061950 ± 5070.1868
Laboratory measures
Hemoglobin A1c, (%)6.73 ± 1.616.43 ± 3.840.5049
Total cholesterol, mg/dL1.9 ± 0.41.7 ± 0.40.0022
HDL cholesterol, mg/dL0.50 ± 0.120.45 ± 0.100.0004
LDL cholesterol, mg/dL1.17 ± 0.371.06 ± 0.330.0155
Triglycerides, mg/dL1.69 ± 0.971.58 ± 0.720.3535
GGT (IU/L)49 [31–97]46 [29.5–75]0.2796
C-reactive protein, mg/L9.6 [5.0–13.8]6.3 [3.0–10.8]0.1455
TSH (mUI/L) (N: 0.4–4)1.72 [1.06–2.39]1.60 [1.02–2.22]0.1133
Serum albuminemia (g/L)35.9 ± 3.036.0 ± 3.30.7358
Serum creatininemia (mg/L)8.14 ± 1.948.17 ± 2.100.9132
Functional Parameters
6MWT, distance walked (m)324 ± 156441 ± 149<0.0001
Pain scale (range: 0–10)5.8 ± 2.43.4 ± 2.2<0.0001
HADS
Anxiety score9.1 ± 4.27.9 ± 4.5<0.001
Depression score7.6 ± 4.55.8 ± 4<0.001
Notes: data presented are the mean  ±  SD or N (%). Abbreviations: BMI, body mass index; GGT, gamma-glutamyl transferase; HDL, high-density lipoprotein cholesterol; 6MWT: six-minute walk test; HADS: Hospital Anxiety and Depression Scale.
Table 3. Measures of quality-of-life scale.
Table 3. Measures of quality-of-life scale.
Quality of Life Scale, Obesity and DieteticsBaselinePost Interventionp Value
Physical impact54.3 ± 15.767.6 ± 16.5<0.0001
Psychosocial impact59.8 ± 19.470.8 ± 18.7<0.0001
Impact on sex life60.9 ± 26.770.8 ± 27,30.0131
Nutritional well-being63.5 ± 19.462.6 ± 18.50.7318
Food rebalancing65.4 ± 19.273.1 ± 17.40.0011
Total score60.8 ± 11.968.8 ± 12.3<0.0001
Table 4. Associations between quality of life and other parameters.
Table 4. Associations between quality of life and other parameters.
Univariate AnalysisMultivariate Analysis
Regression Coefficient (95% CI)p ValueRegression Coefficient (95% CI)p Value
Change in anxiety score−1.01 [−1.46; −0.57]<0.001−0.48 [−0.92; −0.05]0.0327
Change in depression score−1.32 [−1.69; −0.94]<0.001−1.09 [−1.48; −0.70]<0.0001
Change in pain score−0.77 [−1.72; 0.17]0.108
Change in 6MWT−0.01 [−0.05; 0.03]0.733
Change in lean mass−0.37 [−0.62; −0.12]0.005−0.31 [−0.54; −0.08]0.0120
Change in fat mass−0.27 [−0.55; 0.01]0.060−0.25 [−0.48; −0.008]0.0461
Change in weight loss−0.44 [−0.70; −0.17]0.001
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kouidrat, Y.; Louhou, R.; Mondot, C.; Daami, I.; Amad, A.; Diouf, M. Quality of Life in Patients with Obesity: The Role of Multidisciplinary Rehabilitation Medicine. Obesities 2024, 4, 160-168. https://doi.org/10.3390/obesities4020015

AMA Style

Kouidrat Y, Louhou R, Mondot C, Daami I, Amad A, Diouf M. Quality of Life in Patients with Obesity: The Role of Multidisciplinary Rehabilitation Medicine. Obesities. 2024; 4(2):160-168. https://doi.org/10.3390/obesities4020015

Chicago/Turabian Style

Kouidrat, Youssef, Rufin Louhou, Claire Mondot, Imed Daami, Ali Amad, and Momar Diouf. 2024. "Quality of Life in Patients with Obesity: The Role of Multidisciplinary Rehabilitation Medicine" Obesities 4, no. 2: 160-168. https://doi.org/10.3390/obesities4020015

APA Style

Kouidrat, Y., Louhou, R., Mondot, C., Daami, I., Amad, A., & Diouf, M. (2024). Quality of Life in Patients with Obesity: The Role of Multidisciplinary Rehabilitation Medicine. Obesities, 4(2), 160-168. https://doi.org/10.3390/obesities4020015

Article Metrics

Back to TopTop