Category: 8. Health

The Target Malaria project aims to eradicate malaria using the controversial gene drive technology. In 2019, the project released genetically modified, GM, mosquitoes in one village of the Burkina Faso, West Africa, but the local residents oppose further releases. Several scientific papers had highlighted major technical problems that are hampering the project advancement.

The Target Malaria project claims to be able to eradicate malaria by using gene drive technology to eliminate Anopheles mosquitoes, the malaria vectors. There are several gene drive projects around the world, targeting different species (insects, mammals, fungi, etc.), using different types of gene drives, and having different stages of the technology readiness. The details of these projects are provided in the Table 2 of the Gene Drives report, produced by ENSSER, the European Network of Scientists for Social and Environmental Responsibility. The Target Malaria project, using the CRISPR/Cas9 system for the Anopheles gambiae elimination, is the most advanced project.

The project was conceived in Great Britain, at Imperial College London, in the laboratory led by Andrea Crisanti. The project experimental protocol is very complex: it comprises three phases, each phase focusing on a particular type (strain) of GM mosquitoes. Only the third phase is aiming to fight against malaria, and only this phase is based on the use of the gene drive technology. All the strains are produced by Crisanti’s team and must be imported to Burkina Faso for field trials. After importation, the mosquitoes are managed by the local Target Malaria team led by Abdoulaye Diabate; each phase should normally end with mosquito release by Diabate’s team.

The project is moving forward rapidly, thanks to huge capital injections, coming primarily from the Bill Gates Foundation. The project is strongly supported by the NEPAD, New Partnership for Africa’s Development, an African Union agency. The NEPAD, which favors gene drives, has appointed ABNE, the African Biosafety Network of Expertise, to oversee Target Malaria experiment. The ABNE is funded by the Bill Gates Foundation, and the NEPAD  – by the Open Philanthropy Project, one of Target Malaria’s funding sources.

In 2019, within the framework of the first project phase, Target Malaria released 6,400 GM mosquitoes in the Bana village of the Burkina Faso, despite the Burkinabe civil society protests. The project is currently in its second phase, which began in March 2022, following the importation of the second-phase strain into Burkina Faso. Normally, before importing a strain for field trials, the Crisanti team conducts numerous tests to ensure the strain’s quality, and only the strain that meets all the criteria defined by the experimenter is accepted for importation. However, the project has encountered setbacks.

A few months after the importation of the second-phase strain, several scientific articles were published reporting the detection of technical problems encountered during the strain obtention process. Unfortunately, this was a late detection, which occurred after importation.

In October 2022, Andrea Crisanti, the project designer, published a co-authored article showing that the second-phase strain has significant defects that, according to the article, could have “multiple implications for disease transmission as well as ecological adaptation.” This article is a kind of self-criticism on the part of the project designer.

The production of GM mosquitoes involves two steps:

• The transfer of the targeted gene into the mosquito’s genetic material (using genetic transformation). A gene is a hereditary unit that controls a trait.
• The repeated crosses of the resulting product to the local mosquitoes (using the backcross technique). The backcross phase serves to ensure the GM strain’s adaptation to the local environment.

The article explains, that in the case of the Target Malaria experiment, the backcross phase did not work well, which led to the defects in the second-phase strain. The article provides explanations for the lack of backcross effectiveness: the project did not take into account the complexity of the studied phenomena. More specifically, it did not take into account the presence of some genetic phenomena, such as the chromosomal inversions, the genes that determine malaria transmission capacity, the genes that determine adaptation to humidity/aridity, etc.

Another project problem stems from the fact that the project did not control mosquito rearing conditions, particularly with regard to humidity. The mosquitoes were kept under standard mosquito rearing conditions at the temperature of 28 ± 1°C and 80% ± 10% of relative humidity, which is quite humid. The article attributes the ineffectiveness of the backcross procedure, at least in part, to the humid conditions of the experiment.

This explanation is linked to a very recent information showing that humidity can influence backcross result. This information is coming from the study of Riehle et al. 2017, which discovered that each mosquito population has two categories of individuals:

• the mosquitoes resting inside houses (because they are adapted to arid conditions), this category has a low capacity to transmit malaria, and
• the mosquitoes resting outside (because they are adapted to humidity) and have a high capacity to transmit malaria.

The implication of this information is very important for the malaria transmission capacity of mosquitoes. Regarding the project, the mosquito rearing, carried out in humid conditions, favors the selection of mosquitoes that, on the one hand, are adapted to humidity, and on the other hand, have a high capacity to transmit malaria (the two traits are inherited together).

The complexity of the studied phenomena (the inheritance of gene drives, the interactions at the ecosystem level, etc.), as well as the lack of knowledge on these issues, constitute one of the major criticisms raised by the opponents of gene drive tests in open environment. The second phase of the project does not yet concern gene drive, but even at this stage, the research work is becoming too complex.

Moreover, scientist Andrea Crisanti, the author of over 100 scientific publications, is also a politician, a member of the Italian Senate, and for several years now, he has not been very active in Target Malaria.

Other criticisms of the second phase were made by Vitale et al., who are the also the Target Malaria researchers, and by the TESTBIOTECH research group. Despite all these critical publications, and contrary to any logic, the local Target Malaria team sought, in 2024,  an agreement with the Burkinabe civil society for releases of the second phase strain, while remaining completely silent about the strain’s problems and the publications that reported them. On August 6, 2024, Abdoulaye Diabaté, the head of the local team, gave an interview to the Burkinabe daily Sidwaya, stating that the project was going well and that “we are gradually moving towards the third phase,” based on gene drive.

This attempt to obtain the agreement for releases failed, following the opposition from the Burkinabe population, worried about the releases consequences on health and ecosystems. On May 30, 2024, in the press conference, the Coalition for Monitoring Biotechnology Activities in Burkina Faso, composed of COPAGEN, COASP, AfriTap, FIAN Burkina Faso, Terre à Vie and CNABio, expressed its firm opposition to the release of second-phase GM mosquitoes and for the gene drive tests in Burkina Faso and in Africa. The Coalition asked the ANB, National Biosafety Agency, to “refuse to grant a new authorization for the release of mosquitoes.”

In response to criticism, during the audience with Burkinabe local authorities (special municipal delegation of Bobo-Dioulasso town), held on March 27, 2025, the ANB representatives affirmed that “all measures have being taken to ensure the safe use of genetically modified mosquitoes.”

The third project phase, the phase yet under preparation in London, has been also criticized: the WHO expert report 2022 (World Health Organization) identified several technical problems:

The gene drive model used by Target Malaria does not work; in particular, the genetic construct has become unstable following a mutation, which compromises the model’s effectiveness.

The project has a difficulty to define the mosquito species that should be targeted by gene drive technology. The project aims to eliminate malaria-carrying mosquitoes, but there are several species of Anopheles mosquitoes that carry malaria. At this stage, the project has not yet been able to define all the Anopheles species that should be targeted.

These technical problems demonstrate that gene drive technology is not yet ready for use and that the goal of malaria eradication, as defined by the project, is difficult to achieve. Moreover, there are suspicions that malaria eradication is merely a pretext for conducting gene drive test in an open environment. For the Coalition for Monitoring Biotechnology Activities in Burkina Faso, if the real goal of the Target Malaria project was to end the malaria in Burkina Faso, there are less risky solutions than biotechnology to achieve this goal: the sound environmental management policy, the promotion of artemesia, a well-known plant in Burkina Faso, etc.

The discovery by Riehle et al. 2017, confirmed by other researchers, is of great interest for improving the conventional methods of the malaria fighting, which until now have primarily targeted the mosquitoes that remain indoors, through the use of mosquito nets and insecticides. This discovery demonstrated the interest to change strategies by focusing on the insects that primarily remain outdoors.

Gene drive is a high-risk experiment! The international scientific community is very concerned about gene drive experiment. The Target Malaria project is seeking to conduct the world’s first open environment gene drive trial, choosing Burkina Faso as its testing ground.

Gene drive is a new technology that is still poorly understood. The first experiment (in cages), demonstrating the feasibility of gene drive application to Anopheles mosquitoes was conducted in 2018 by Andrea Crisanti and his team.

Gene drive is a very powerful technology that causes profound and unprecedented changes in nature. By circumventing the laws of heredity (known as Mendel’s laws), the gene drive is capable to rapidly wipe out an entire species.

Normally, a mutation is inherited, according to Mendel’s laws, by 50% of offspring. However, in the case of gene drive, a mutation is inherited by nearly 100% of the offspring. The project involves production of the mutations that disrupt the reproduction of the Anopheles gambiae species, leading to the birth of the only male individuals. Thus, the dissemination of these forced genes will cause the disappearance of the entire species.

Gene drive is a highly controversial technology that was the subject of calls for a global moratorium during the CBD (Convention on Biological Diversity) negotiations in 2016 and in 2018. The scientists emphasize that gene drive still exists only in laboratory and is not ready for field testing due to its high degree of uncertainty. Mosquitoes are important components of ecosystems, their role is not yet well understood, and ecosystems have a high capacity to adapt and to resist to the changes imposed by humans. Mosquitoes are pollinators and important components of the food chain. Eliminating of the anopheles mosquito species, vectors of malaria, the strategy chosen by Target Malaria to eradicate malaria, may not necessarily solve the problem since other malaria vectors can emerge to fill an empty ecological niche. This suppression can also have the unexpected negative impacts on the ecosystems.

Despite the concerns of the scientific community, Abdoulaye Diabaté, head of the local Target Malaria team, in his explanations intended for the general public, trivializes the gene drive use. For him, the gene drive is “a specific system that we have and that we attach to the mosquito, and this will mean that we no longer need to release too many mosquitoes. For example, once in a village, we can just release a few mosquitoes, and these mosquitoes will do the work. It will no longer be necessary to release them in other surrounding villages. The mosquitoes will take care of taking the gene of interest to other mosquitoes. And this could go even beyond Burkina Faso. That’s what makes this technology so beautiful.”

However, where Diabate sees beauty, others see danger. Several scientific publications highlighted that the gene drive mosquitoes have the potential to spread over vast geographical areas; this means that, once released in a given country, they can spread beyond national borders, causing multiple political and ecological problems. Unlike the first-generation GM organisms, such as Bt cotton, well-known in Burkina Faso (mostly known for its failure), these organisms can spread autonomously and persist in the environment, making them difficult to contain.

Irina Vekcha is Professor of genetics at ENSA (University of Agriculture, Senegal) and scientific advisor at the NGO Terre à Vie (Burkina Faso).

Introduction

Inflammatory bowel disease (IBD) is a chronic, non-specific inflammatory condition affecting the gastrointestinal tract, primarily encompassing Crohn’s disease (CD) and ulcerative colitis (UC). Pediatric patients represent approximately 20–25% of the total IBD population, with a significant annual increase in incidence rates observed among children in emerging industrialized regions of Asia, Africa, and South America. In Asia, the incidence rate ranges from 0.5 to 21.6 per 100,000 individuals per year.¹ In children, the clinical manifestation of IBD is characterized by symptoms such as abdominal pain, diarrhea, and the presence of blood and mucus in stools. As children are in a crucial phase of growth and development, those with IBD face an elevated risk of growth retardation, bone metabolism disorders, delayed puberty, and an increased susceptibility to colon cancer.² The poor prognosis and prolonged treatment duration associated with IBD impose a substantial burden on affected children, their families, and society at large. The pathogenesis of IBD remains inadequately understood; however, it is postulated that a multifaceted interaction among genetic predispositions, dietary patterns, physical activity (PA), environmental factors, and host immune responses plays a crucial role in the onset of IBD.³ Within this framework, diet and PA are of particular importance, serving not only as potential precipitants of IBD but also as integral elements in its therapeutic management.⁴

Recent studies have increasingly concentrated on dietary patterns and their role in IBD. The Mediterranean diet (MD) is characterized by a high consumption of vegetables, fruits, whole grains, legumes, and nuts, moderate intake of fish and dairy products, limited consumption of red meat, and the use of virgin olive oil as the primary fat source. Emerging research has demonstrated that adherence to MD patterns is associated with a favorable microbiome composition and reduced inflammation,^5,6 which may be beneficial for children with IBD.⁷

Pediatric patients with IBD frequently exhibit reduced levels of PA. PA has been demonstrated to be advantageous not only for healthy individuals but also for those with autoimmune conditions.⁸ The immature immune system and ongoing gut microbiome development in children may amplify the modulatory effects of MD patterns and PA on mucosal healing. Besides, health behaviors established during childhood show greater longitudinal stability. Cohort studies demonstrated that dietary habits and PA established during childhood and adolescence continue into adulthood.^9,10 Targeting MD adherence and PA in children may thus yield sustained benefits. Nowadays, few reports examined the relationship between pediatric IBD and PA, as well as the impact of PA and dietary pattern on the clinical progression of pediatric IBD. This study aims to investigate the potential effects of MD and PA on the clinical outcomes of pediatric IBD, with the objective of contributing evidence for optimize clinical recommendations.

Materials and Methods

Study Population

This prospective cohort study was conducted at Tianjin Children’s Hospital, Tianjin, China, within the period of October 2021 to June 2024. The inclusion criteria for participant selection were: (1) aged 8–18 years; (2) diagnosed with UC or CD based on clinical, radiological, and endoscopic criteria; (3) active disease stage, indicated by a pediatric ulcerative colitis activity index (PUCAI) greater than 10 for UC¹¹ or a pediatric Crohn’s disease activity index (PCDAI) greater than 10 for CD;¹⁰ (4) receipt of standardized treatment and follow-up; and (5) acceptance of the invitation to participate in the study. The exclusion criteria included: (1) a history of bowel surgery; (2) use of probiotics or nutritional supplements; and (3) a diagnosis of any other condition that could affect PA or diet.

A total of 106 children, aged 8–18 years and diagnosed with either UC or CD were recruited. 18 participants were excluded: 2 children had undergone bowel surgery, 12 children were using probiotics or nutritional supplements, and 4 children were diagnosed with other diseases that could potentially affect PA or diet (Figure 1).

Data Collection

For the children included in the study, demographic data, including age and gender, were documented. Anthropometric measurements, specifically height and weight, were taken, and height for age Z-score (HAZ) and body mass index for age Z-score (BAZ) were calculated using the WHO Anthro software (version 3.1.0). HAZ and BAZ have no units. A score of 0 indicates that the measurement is at the median level of the reference population. Positive values indicate that the measurement is greater than the reference median, while negative values indicate that the measurement is less than the reference median. The lower the score, the poorer the nutritional status. Additionally, information regarding the disease, such as age at diagnosis, disease location, disease duration, and medication use, was collected. Disease activity was assessed using established criteria: for CD, the Pediatric Crohn’s Disease Activity Index (PCDAI) was used, with scores <10.0 indicating remission, 10.0–27.5 indicating mild activity, 30.0–37.5 indicating moderate activity, and 40.0–100.0 indicating severe activity.¹² For UC, the Pediatric Ulcerative Colitis Activity Index (PUCAI) was employed, with scores <10 indicating remission, 10–34 indicating mild activity, 35–64 indicating moderate activity, and ≥65 indicating severe activity.¹¹ Blood test parameters, including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), interleukin (IL) −6, and albumin, as well as fecal calprotectin levels, were assessed.

We provided guidance to the parents of the children, advising them to implement the MD for their children. Specifically, this diet emphasizes the consumption of ample vegetables, fruits, whole grains, legumes, and nuts, while recommending the limitation of red meat intake and the minimization of food processing. In culinary practices, parents were advised to substitute animal fats, which contain saturated fatty acids, with vegetable oils rich in unsaturated fatty acids, such as olive oil, and to avoid various artificial margarines. Additionally, parents were instructed to document their children’s PA (in the absence of abdominal symptoms) and adherence to the MD throughout the year, along with any abdominal symptoms (including abdominal pain, bloody stools, stool consistency, 24-hour stool frequency, nocturnal defecation, and activity limitations) on a weekly basis.

After one year, the child underwent a follow-up examination, during which the same blood test parameters and fecal calprotectin levels were re-evaluated. We reassessed HAZ, BAZ, and disease activity. Based on parental records of the child’s weekly abdominal symptoms, the duration of annual abdominal symptom-free and the annual recurrence frequency were evaluated.

Assessment of PA

Parents were instructed to use the validated Physical Activity Questionnaire (PAQ) including Physical Activity Questionnaire for Older Children (PAQ-C) and the Physical Activity Questionnaire for Adolescents (PAQ-A) to assess the PA levels of children with IBD weekly during symptom-free periods.¹³ The average PAQ score for children during the symptom-free period over the course of a year was calculated. The PAQ-C is administered to children aged 8–14, while the PAQ-A is designed for adolescents aged 15–18. The PAQ-C comprises nine questions addressing the types and frequencies of PA, with each question scored on a scale from 1 to 5. The final score is the mean of the nine items. PAQ-A has the same scoring scheme, except that PAQ-A does not include questions about PA during recess.

Assessment of the Adherence to the MD

The adherence to MD among children with IBD was evaluated using the KIDMED questionnaire.¹² Parents of the participants were instructed to accurately record their children’s KIDMED scores on a weekly basis. Subsequently, an annual average KIDMED score was computed. The KIDMED questionnaire comprises 16 items designed to assess children’s dietary habits, each requiring a “yes” or “no” response, scored from −1 (indicating a negative connotation) and +1 (indicating a positive connotation). The questionnaire includes four items that reflect a negative connotation to the MD (consumption of fast food, soft drinks, processed breakfast items, and industrial pastries) and twelve items that reflect a positive connotation (consumption of fish, fruits, vegetables, cereals, nuts, pulses, olive oil, fresh food, dairy products, plant-based foods, unprocessed breakfast items, and cooking methods). The total KIDMED scores range from 0 to 12 and are categorized as follows: scores of ≥8 indicate good adherence, scores of 4–7 indicate average adherence, and scores of ≤3 indicate poor adherence to the MD.

Outcomes

The primary outcome assessed was the duration of abdominal symptom-free periods within one year. Secondary outcomes included the frequency of relapses within the same timeframe, changes in HAZ and BAZ after one year (calculated as ΔHAZ: HAZ at one year minus baseline HAZ; ΔBAZ: BAZ at one year minus baseline BAZ), disease activity at the study endpoint, laboratory indicators at the endpoint (including CRP, ESR, IL-6, albumin, and fecal calprotectin levels). Trained clinical physicians assessed the duration of abdominal symptom-free and the incidence of relapses over the year, based on the parental records of weekly abdominal symptoms in children.

Statistics Analysis

Descriptive statistics were presented as frequencies (proportions) for categorical variables, means ± standard deviations for continuous variables conforming to a normal distribution, and medians (interquartile ranges) for continuous variables not conforming to a normal distribution. To evaluate differences in participants’ characteristics across varying levels of MD adherence and PA, categorical variables were analyzed using the chi-square test, continuous variables that followed a normal distribution were assessed using the t-test, while those not conforming to normal distribution were evaluated using the Mann–Whitney test. To examine the characteristics associated with the duration of annual abdominal symptom-free, linear regression analysis was employed to investigate the relationship among MD adherence, PA, and the duration of annual abdominal symptom-free.

Statistical significance was determined at a two-sided P-value of less than 0.05. All statistical analyses were performed using R software (version 2024.12.1+563).

Results

Characteristics of Participants

The final study cohort comprised 88 children, including 43 males (48.9%), with a average age of 12.8 ± 2.4 years. Within this cohort, 52 participants were diagnosed with UC and 36 with CD. The mean duration of annual abdominal symptom-free was 37.0 ± 11.2 weeks, and the recurrence rate within one year was 1.5 ± 1.1 episodes. Over the year, the average KIDMED score was 6.8 ± 1.5. In the absence of abdominal symptoms within one year, the mean PAQ score was 2.1 ± 0.4. The KIDMED scores were categorized based on established threshold values recorded in the literature.¹⁴ Among the 88 children, 66 demonstrated average adherence to the MD, while 22 exhibited good adherence. The PAQ scores were dichotomized using the median value, resulting in 41 children classified as having low PA and 47 as having high PA.

The results revealed statistically significant differences between the average and good MD adherence groups concerning baseline disease activity, ΔBAZ, the duration of annual abdominal symptom-free, annual recurrence rates, disease activity after one year, laboratory indicators after one year (CRP, calprotectin, and IL-6). Compared to the average MD adherence group, children with good MD adherence experienced less reduction in BAZ, longer symptom-free period, fewer recurrence rates, lower disease activity, and reduced levels of CRP, calprotectin, and IL-6. In comparing the low and high PA groups, significant differences were observed in the duration of annual abdominal symptom-free, CRP, ESR, calprotectin, IL-6, and albumin levels at the endpoint. Children in the high PA group, relative to those in the low PA group, had shorter symptom-free periods, and lower levels of CRP, ESR, calprotectin, and IL-6, but higher albumin levels at the endpoint (P < 0.05), as shown in Table 1.

Table 1 Characteristics of Participants

Correlation Between Mean KIDMED Score, Mean PAQ Score, and the Duration of Annual Abdominal Symptom-Free

The correlation between the mean KIDMED score and the duration of annual abdominal symptom-free is illustrated in Figure 2, while the correlation between the mean PAQ score and the duration of annual abdominal symptom-free is depicted in Figure 3. A prolonged annual abdominal symptom-free period was significantly correlated with higher mean KIDMED scores (r = 0.529, P < 0.001) and higher mean PAQ scores (r = 0.337, P < 0.001).

Figure 2 Scatter plots and linear trend line of duration of annual abdominal symptom-free in association with mean KIDMED score.

Figure 3 Scatter plots and linear trend line of duration of annual abdominal symptom-free in association with mean PAQ score.

Association Among MD Adherence, PA, and Duration of Annual Abdominal Symptom-Free

The association among MD adherence, PA, and the duration of annual abdominal symptom-free is presented in Table 2. The results of simple linear regression analysis indicated that, compared to children with average adherence, those with good adherence experienced a longer period without abdominal symptoms annually (β: 8.364, 95% CI: 3.171, 13.556, P<0.005). Additionally, higher KIDMED scores were associated with an extended period without abdominal symptoms per year (β: 3.868, 95% CI: 2.537, 5.199, P<0.001). After adjusting for confounding factors such as age, sex, disease location, disease duration, medication use, and baseline disease activity, good adherence and higher KIDMED scores remained significantly associated with a longer period of no abdominal symptoms annually.

Table 2 Association Among MD Adherence, PA and the Duration of Annual Abdominal Symptom-Free

The findings from the univariate linear regression analysis indicated that, in comparison to children with low PA, those with high PA experienced a longer duration without abdominal symptoms annually (β: 5.349, 95% CI: 0.721, 9.978, P<0.05). Furthermore, elevated scores on the PAQ were correlated with an extended period free from abdominal symptoms each year (β: 9.532, 95% CI: 3.827, 15.236, P<0.005). Upon adjusting for potential confounders, including age, sex, and disease location, the association between PAQ scores and the duration without abdominal symptoms remained significant (β: 6.073, 95% CI: 0.544, 11.603, P<0.05). However, when medication use and baseline disease activity were incorporated into the adjustments, the association between PAQ scores and symptom-free duration was no longer significant.

Subgroup Analysis Stratified by Different MD Adherence and PA’s Duration of Annual Abdominal Symptom-Free

Mann–Whitney tests were performed separately for each category of MD adherence and PA. The results, depicted in Figure 4, reveal that among children with average MD adherence, the high PA subgroup had a significantly longer symptom-free period compared to the low PA subgroup (P = 0.021). Conversely, among children with good MD adherence, no significant difference was observed in the symptom-free duration between the low and high PA subgroups (P = 0.807).

Figure 4 Subgroup analysis stratified by different MD adherence and PA’s duration of annual abdominal symptom-free.

In the group with low PA, individuals with good adherence to the MD exhibited a significantly longer duration without abdominal symptoms compared to those with average MD adherence (P = 0.012). Conversely, in the high PA group, no statistically significant difference was observed in the duration without abdominal symptoms between the good and average MD adherence subgroups (P = 0.137).

The black vertical lines indicate the median. The left and the right borders of the box mark the first and the third quartiles. The error bars indicate the 5th and 95th percentiles. The black solid circle indicates the individual whose values were outside the 5th or 95th percentiles.

Discussion

IBD encompasses a group of disorders characterized by chronic inflammation of the intestinal tract, with CD and UC being the primary conditions. Despite differences in their pathological mechanisms and clinical presentations, both diseases involve persistent inflammation of the intestinal mucosa, leading to symptoms such as abdominal pain, diarrhea, and bloody stools. Malnutrition and sarcopenia are prevalent among IBD patients and frequently co-occur, adversely affecting quality of life.¹⁵ Research indicates a positive correlation between insufficient lean body mass and increased disease activity.¹⁶ The symptoms of IBD in pediatric populations may be more severe compared to adults, with children exhibiting a higher susceptibility to extraintestinal manifestations that significantly affect their quality of life and psychological development.¹⁷ Lifestyle factors, particularly diet and PA, may influence the onset and progression of IBD.¹⁸

Our study identified a positive correlation between adherence to the MD, as defined by the KIDMED score, and the duration of symptom-free periods annually. The KIDMED score, originally developed by Serra-Majem et al, assesses the adherence of children and adolescents to the MD.¹⁹ Recently, López-Gajardo update the questionnaire,¹⁴ and its validity for research applications among children and adolescents has been established.^20–24 A randomized controlled trial demonstrated that children with IBD who achieved a KIDMED score of 8 exhibited significantly lower disease activity scores (PCDAI and PUCAI) and reduced levels of inflammatory markers (CRP, calprotectin, TNF-α, IL-17, IL-12, and IL-13) compared to those with KIDMED scores of 7 or lower,⁷ aligning with our findings.

Several mechanisms may underlie the beneficial effects of the MD in managing IBD. The MD is rich in anti-inflammatory and antioxidant compounds, including minerals, vitamins, omega-3 fatty acids, and polyphenols. Additionally, the MD provides a substantial amount of prebiotics, which, upon fermentation in the intestinal tract, are converted into short-chain fatty acids (SCFAs). These SCFAs are thought to play a crucial role in maintaining intestinal flora balance. Research by Haskey et al demonstrated that individuals adhering to the MD exhibited elevated levels of total fecal SCFAs, acetic acid, and butyric acid. Moreover, the MD was associated with changes in microbial species that are protective against colitis, such as Alistipes finegoldii and Flavonifractor plautii, and with the production of SCFAs by Ruminococcus bromii.⁵ Similarly, Williams reported that a diet resembling the MD was significantly correlated with a specific microbial composition, characterized by an increased presence of fiber-degrading bacteria like Ruminococcus and Faecalibacterium.⁶ These microbiotas are capable of modulating the host’s immune response, enhancing the integrity of the intestinal mucosal barrier, and reducing the translocation of inflammatory mediators, thereby mitigating intestinal inflammation.^25–27

In this study, the outcomes of univariate analysis and linear regression, adjusted for age and gender, indicated that higher levels of PA were associated with an extended duration without abdominal symptoms. Upon incorporating disease location and disease duration into the regression model, the continuous variable of the PAQ score maintained a positive correlation with the duration without abdominal symptoms. Nevertheless, this association was not observed after adjusting for medication use and baseline disease activity. Recent studies have suggested that PA exerts anti-inflammatory effects on certain autoimmune diseases.^8,28 The existing literature definitively indicates that PA increases the risk of IBD. A Mendelian randomization study, which analyzed 458,109 participants, identified PA as a significant predictor of the development of CD and UC.²⁹ Furthermore, a meta-analysis suggests that PA is inversely associated with the risk of developing IBD, with a more pronounced effect observed in CD compared to UC.³⁰

The relationship between PA and symptom relief in IBD remains inconclusive. Some studies have demonstrated an association between PA and symptom alleviation in IBD. For instance, a study with a small sample size indicated that an 8-week moderate-intensity exercise intervention led to reductions in ESR, CRP, and platelet count in children with IBD.³¹ Additionally, a cross-sectional study found that IBD patients with low levels of PA reported the poorest health-related quality of life and highest disease activity, including symptoms such as depression, pain interference, fatigue, sleep disorders, social dissatisfaction, and increased CD’s disease activity, compared to those in moderate and high PA groups.³² Conversely, some studies have not observed a reduction in inflammatory markers in IBD patients due to PA, yet they have reported other potential benefits. For example, a prospective randomized controlled trial revealed that a 10-week moderate-intensity exercise regimen improved the quality of life for IBD patients, although it did not result in changes in CRP levels, fecal calprotectin, or disease activity index.³³

Cronin et al found that moderate-intensity exercise increased muscle tissue quality, but there were no significant changes in disease activity index and pro-inflammatory cytokines (IL-8, IL-10, IL-6).³⁴ Mila et al observed an increase in lean mass, bone density, aerobic fitness, and vigorous PA levels in IBD children, but no change in inflammation or muscle strength.³⁵ Vanhelst et al discovered that PA improved the bone health of children with IBD.³⁶

Several studies have reported that 45% of patients with IBD reduce their PA following diagnosis.³⁷ In the present study, the PAQ scores of children were assessed in the absence of abdominal symptoms. The findings indicated that the average PAQ scores among participants ranged from 2.8 to 1.0, with a median score of 2.15, which is considered relatively low on the PAQ scale of 0–5. This suggests that even in the absence of abdominal symptoms, children engage in PA infrequently. Previous research has demonstrated that moderate-intensity PA can be beneficial for managing intestinal inflammation and IBD.^31,33 Additionally, some studies have identified a positive correlation between increased moderate-to-vigorous PA and enhanced quality of life in IBD patients.³⁸ Whereas, an animal study demonstrated that repetitive vigorous exercise can trigger systemic inflammatory responses and multi-organ damage in rats, with intestinal manifestations such as mucosal shedding and necrosis.³⁹ Some researchers argue that intense PA may not be feasible or acceptable for patients with IBD because it could exacerbate intestinal symptoms, worsen existing fatigue, or lead to uncontrolled bowel movements.⁴⁰ This suggests that further investigation is needed to understand the relationship between IBD and PA, as well as to determine the appropriate intensity of exercise for IBD patients.

Due to factors such as inflammatory depletion, poor nutrient absorption, and vitamin D deficiency, individuals with IBD frequently experience sarcopenia.⁴¹ Liao et al reported a sarcopenia prevalence of 25.2% among IBD patients and found that low muscle mass at the initiation of anti-tumor necrosis factor treatment was associated with early treatment failure.¹⁵

Both diet and PA influence the enhancement of muscle mass. Consequently, we investigated the combined impact of dietary patterns and PA on the duration of symptom-free periods in the abdomen. This investigation is instrumental in determining whether the MD and PA might contribute to the progression of IBD through mechanisms related to muscle mass. Previous research has involved a 12-week intervention focusing on a healthy diet and PA in children with IBD. With drug treatments held constant, the intervention group exhibited a significant reduction in disease activity index and fecal calprotectin levels, alongside an improvement in quality of life scores, compared to the control group.⁴² Furthermore, some studies have demonstrated that the combined additive effect of low adherence to the MD and low PA on all-cause mortality surpasses the impact of each risk factor individually.⁴³ Our study identified that at low levels of PA, an increase in adherence to the MD was correlated with a prolonged period without abdominal symptoms. Conversely, when MD adherence was at an average level, an increase in PA was associated with an extended duration free from abdominal symptoms. These findings imply that in situations where children are unable to maintain high levels of MD adherence or PA, enhancing another factor may be beneficial for alleviating abdominal symptoms.

While our findings highlight the beneficial association between MD adherence, PA, and prolonged annual symptom-free duration in pediatric IBD, caution is warranted when extrapolating these conclusions to adult populations due to fundamental pathophysiological and behavioral differences. The developing gut microbiome in children exhibits greater modifiability by dietary interventions compared to the relatively stable adult microbiome. Prospective studies comparing parallel pediatric/adult cohorts are needed to validate these findings across age spectra.

This study has several limitations. The sample size was relatively small, and subgroup analyses for children with CD and UC were not conducted, limiting the understanding of disease-specific effects. External validation was not performed, restricting the generalizability of the findings to other settings. Furthermore, despite parental training on the KIDMED and PAQ questionnaires at baseline and the implementation of monthly follow-ups, assessment errors were still observed. Additionally, no mechanistic research was conducted to elucidate the underlying pathways.

Future research should focus on multi-center studies with large sample sizes to validate our findings and more objectively assess MD adherence and PA levels. Additionally, it is imperative to investigate the underlying mechanisms through which MD and PA influence IBD.

Conclusion

The univariate linear regression analysis indicated that both MD adherence and PA were correlated with the duration of annual abdominal symptoms-free. Even after adjusting for variables such as age, sex, disease location, disease duration, medication use, and baseline disease activity, good adherence to the MD remained positively associated with the annual symptom-free duration. However, PA did not demonstrate a significant association with this outcome. Within the group with average MD adherence, the subgroup with high PA levels experienced a significantly longer annual duration without abdominal symptoms compared to the low PA subgroup. Conversely, within the low PA group, those with good MD adherence had a significantly longer symptom-free duration than those with average MD adherence. These findings could inform the development of dietary and exercise interventions for pediatric IBD patients.

Abbreviations

BAZ, body mass index for age Z-score; CD, Crohn’s disease; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; HAZ, height for age Z-score; IBD, inflammatory bowel disease; IL, interleukin; MD, Mediterranean diet; PA, physical activity; PAQ, physical activity questionnaire; PAQ-A, physical activity questionnaire for adolescents; PAQ-C, physical activity questionnaire for older children; PCDAI, pediatric Crohn’s disease activity index; PUCAI, pediatric ulcerative colitis activity index; SCFAs, short-chain fatty acids; UC, ulcerative colitis.

Data Sharing Statement

The data that support this study are not openly available due to the ongoing follow-up of the cohort, and are available from the corresponding author upon reasonable request.

Ethics Approval and Informed Consent

The study was conducted in compliance with the ethical principles outlined in the “Declaration of Helsinki” and received approval from the Ethics Committee of Tianjin Children’s Hospital (Approval No.: L2021-010). Informed consent was obtained from the parents or legal guardians of all pediatric participants included in this study. In addition to parental consent, assent was obtained from children who were capable of understanding the study. The study was explained to the children in an age-appropriate manner, and their willingness to participate was confirmed.

Consent for Publication

All participants gave consent for publication.

Acknowledgments

We appreciate all of participants who enrolled in this study.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This work was sponsored by Tianjin Health Research Project (Grant No.: TJWJ2024MS036) and Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-040A).

Disclosure

The authors report no conflicts of interest in this work.

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Introduction

China and the rest of the world are facing the challenge of increasing obesity year by year.^1,2 According to the World Obesity Map 2023, the global population with overweight and obesity reached 2.6 billion in 2020, and it is expected to reach half of the global population by 2035.³ Obesity can lead to other systemic diseases, such as fatty liver, diabetes, and sleep apnea syndrome, which bring serious harm to individuals with obesity.^4,5 However, traditional weight loss methods, such as diet control and exercise, are ineffective for weight loss and are prone to recurrent weight gain.^6,7 Bariatric surgery plays a key role in addressing this issue. Among all bariatric surgeries, laparoscopic sleeve gastrectomy (LSG) has gained popularity at home and abroad due to its ease of operation and significant and long-lasting weight loss effect.^8,9

Sarcopenic obesity (SO) is a challenging public health problem. It is a clinical condition in which sarcopenia and obesity coexist.⁸ The synergistic effect of sarcopenia and obesity leads to a severe chronic inflammatory response, insulin resistance, and other abnormalities. This results in a decline in muscle mass and function, while also promoting the synthesis of adipose tissue, leading to obesity.⁹ It not only increases the incidence of cardiovascular diseases and malignant tumors but also significantly raises the risk of dysfunction and death.¹⁰

As the global aging and population with obesity continues to grow, SO is becoming increasingly common among elderly individuals and individuals with obesity.^11,12 Consequently, bariatric surgeons are encountering a higher number of patients with SO. Some studies have found the existence of some factors affecting the weight loss effect of LSG,¹³ but the analysis of the effects of SO on weight loss outcomes and recurrent weight gain after LSG is lacking. Hence, the purpose of this study was to investigate the possibility of SO affecting weight loss outcomes and recurrent weight gain following LSG using retrospective analysis of clinical data from 104 patients with obesity.

Materials and Methods

General Information

This study was a retrospective cohort analysis that gathered clinical data of 104 patients with obesity who underwent LSG in Nanchang University’s First Affiliated Hospital between January 2020 and September 2023. The ratio of fat mass to lean mass ≥0.8 was calculated as SO based on preoperative third lumbar spine CT images. Among them, the SO group (n=34) and non-sarcopenic obesity (NSO) group (n=70). And SO’s impact on weight loss outcomes and postoperative recurrent weight gain was compared.

Inclusion criteria: 1. Surgical indications as per the guidelines for weight loss surgery;¹⁴ 2. Acceptance of LSG surgery; 3. Completion of postoperative follow-up on time with complete data. Exclusion criteria: 1. Missing clinical data and loss of postoperative visits; 2. Patients who underwent other types of bariatric surgery or those with poor baseline conditions were unable to stand the operation. This study received approval from the Ethics Committee of the First Affiliated Hospital of Nanchang University (Ethics number: IIT [2024] Clinical Ethics Review No. 209) and adhered to the Declaration of Helsinki. The committee waived the requirement for informed consent because this study was retrospective and the patient data were used solely for research purposes. Additionally, all patient data were anonymized and handled with strict confidentiality to ensure patient privacy.

Perioperative Management

Before surgery, all patients with obesity should have a comprehensive assessment involving various medical professionals such as endocrinologists, dietitians, and psychiatrists if there is a history of psychiatric illness. They should also undergo routine pre-surgical examinations, including gastroscopy, abdominal CT scans, sleep apnea monitoring, and so on. The LSG procedure can be performed after excluding contraindications to surgery.

After successful anesthesia, the surgeon inserted a 32 Fr gastric tube as an intragastric support tube in the patient with obesity. The procedure was generally performed using a three-hole approach to perforation. Further, the surgeon used an ultrasonic knife to completely free the gastric curvature and fundus along the direction of the gastric curvature starting from 2–6 cm from the pylorus. The starting point of cutting was 2–6 cm from the pylorus. The surgeon completely resected the fundus and most of the gastric curvature along the gastric support tube. Then, the omentum and the gastric wall are reinforced with surgical sutures. Afterward, the surgeon cleaned up the abdominal cavity, took out the specimen, and removed the intragastric support tube.

After surgery, the vital signs of patients were regularly supervised, and their diet was gradually adjusted based on their recovery progress. Typically, the patient was discharged three days after the surgery. At the time of discharge, the patient received dietary counseling, which included the following instructions: (1) strictly adhering to dietary guidelines and consuming approximately 2000 mL of water per day; (2) taking oral gastric medication for two weeks post-discharge and continuing with long-term supplementation of adequate multivitamins, and proteins,¹⁵ followed by regular hospital visits to monitor nutritional levels.¹⁶

Research Indicators

The study indicators were collected by reviewing cases, image data, and telephone records, including (1) baseline indicators: gender, weight, body mass index (BMI), grip strength etc.; (2) body composition and SO: lean mass, fat mass, skeletal muscle area (SMA), and SO; (3) perioperative indicators: operation time, intraoperative bleeding, and postoperative complications; (4) Indicators for assessing weight loss effect and postoperative recurrent weight gain: excess body mass index (EMBI), excess body mass reduction percentage (EWL%), percentage of total weight loss (TWL%) etc.

Diagnosis of SO

In 2022, the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) established an expert consensus on the definition and diagnostic criteria for SO.¹⁷ According to this consensus, diagnosing SO involves two stages: screening and diagnosis. A positive screening test indicates the presence of both clinical signs or suspected factors of sarcopenia and specific indicators of obesity. The clinical signs of sarcopenia include muscle weakness and fatigue. The suspected factors that contribute to sarcopenia are being over 70 years old, having chronic diseases (such as inflammatory diseases or depression), and experiencing recent acute illness or nutrition-related events (like major surgeries, reduced food intake, or weight loss). Additionally, the indicators of obesity consist of having a high BMI or elevated waist circumference measurements.

When a patient with suspected obesity screens positive and advances to diagnosis, the first step is to evaluate skeletal muscle function through a grip strength test. If the results indicate abnormal skeletal muscle function (with grip strength less than 28.0 kg for males or less than 18.0 kg for females¹⁸), the next step in the assessment of body composition is required. Current expert consensus recommends using both SMA and fat mass for this evaluation.¹⁷ Research has demonstrated that the ratio of fat mass to lean mass offers a more accurate assessment of the risk for adverse outcomes associated with altered body composition.¹⁹ Furthermore, this ratio is a superior indicator of body composition compared to BMI and abdominal circumference.^19,20 The ratio of fat mass to lean mass greater than 0.8 indicates more severe metabolic and cognitive abnormalities. Therefore, many studies utilize a ratio above 0.8 as a diagnostic criterion for SO.^19–22

Expert consensus indicates that using abdominal CT or MRI provides an accurate assessment of skeletal muscle and fat content in the body.^23,24 Research has shown that the distribution of skeletal muscle and fat at the level of the third lumbar vertebra can effectively reflect overall body composition.²⁵ Therefore, in this study, we collected preoperative CT imaging data at the level of the third lumbar vertebra. We utilized Sliceomatic 5.0 software,²⁶ which applies different ranges of Hounsfield Units values for various tissue types,²⁷ to calculate the cross-sectional SMA at the third lumbar vertebra, as well as the subcutaneous adipose tissue area (SATA) and visceral adipose tissue area (VATA). Finally, we calculated the ratio of fat mass to lean mass using these formulas:²⁸ lean mass = 0.3 × SMA (cm²) + 6.06, and fat mass = 0.042 × total fat area at L3 (cm²) + 11.2.

Assessment of Surgical Weight Loss Effect and Postoperative Recurrent Weight Gain

One way of assessing surgical weight loss effect was by measuring changes in weight, BMI, EMBI, TWL% and EWL% of patients with obesity perioperatively, and another way was by using evaluation criteria. The evaluation criteria include the following:²⁹ (1) BMI ≥37.5 kg/m² is classified as obesity of degree III. (2) EBMI: EBMI = follow-up BMI – ideal BMI; ideal BMI =25 kg/m². (3) EWL%: EWL% = (preoperative BMI-follow-up BMI) / (preoperative BMI-ideal BMI) ×100%. (4) TWL%: TWL% = (preoperative BMI-follow-up BMI) / (preoperative BMI) ×100%. (5) Evaluation criteria of weight loss effect: EWL%≥100% defined as optimal weight loss; EWL%≥80% as good weight loss; 50%≤EWL%<80% as effective weight loss, and EWL%<50% as poor weight loss. (5) The definition of co-morbid remission: 1. Diabetes remission is characterized by a glycated hemoglobin level of less than 6.5% that is maintained for at least three months after discontinuing glucose-lowering medications. Additionally, improvement in diabetes is indicated by a reduced need for antidiabetic medications to maintain normal blood sugar levels. This includes either discontinuation of insulin or an oral medication or a reduction of glucose-lowering medications by half their original dose and maintaining this blood glucose level for at least three months. 2. Hypertension remission is defined by a sustained systolic blood pressure of less than 140 mmHg and a sustained diastolic blood pressure of less than 90 mmHg after stopping antihypertensive medications for at least three months. Improvement in hypertension is characterized by either a decrease in the dosage or number of antihypertensive medications required to maintain normal blood pressure or a significant reduction in systolic or diastolic blood pressure while on the same medications, with these changes lasting for three months. 3. Obstructive sleep apnea (OSA) remission is assessed through polysomnography, which must show an apnea-hypopnea index (AHI) of fewer than 5 breaths per hour, maintained for at least three months after stopping treatment with continuous positive airway pressure (CPAP) ventilation. Furthermore, improvement in OSA is demonstrated by a reduction in the pressure settings of CPAP therapy needed to maintain a normal lifestyle or a postoperative assessment, indicating that the AHI has significantly improved but does not meet the criteria for remission. This improvement should also last for about three months. 4. If there is no change in diabetes, hypertension, or OSA, it is defined by the disease severity and the intensity of treatment remaining similar to the preoperative situation.

Postoperative recurrent weight gain was evaluated as weight gain >10 kg after weight loss to the nadir in patients with obesity.³⁰

Follow-up and Statistical Methods

Within one year of surgery, patients with obesity were advised to come to Bariatric Surgery Clinic for review at the 1st, 3rd, 6th, and 12th months after surgery, where they would be weighed, followed by appropriate nutritional assessment and clinical examination. Annual follow-up is recommended after the first year of surgery. Patients who did not come to the outpatient clinic for review were regularly followed up via telephone and WeChat.

This study used SPSS 25.0, GraphPad Prism 9.5.0 statistical software for statistical analysis of data, normal distribution of measurement data expressed as x ± s, t-test was used for comparison between groups; comparisons between groups with skewed distributions were conducted using nonparametric tests; count data expressed as absolute numbers, χ²-test was used for comparison between groups; according to the principle of statistical significance, single-factor and multi-factorial analyses were used to find out the risk factors for postoperative recurrent weight gain; P<0.05 indicated that the difference was statistically significant.

Results

Baseline Data Analysis

Among the 104 patients with obesity studied, there were more females than males, with 27 female patients (79.4%) in the SO group and 45 female patients (64.3%) in the NSO group. In addition, a majority of the patients also had OSA, with 64.7% in the SO group and 72.9% in the NSO group (Table 1).

As shown in Table 1, compared to NSO patients, the average preoperative BMI and fat mass of SO patients were higher; However, the average lean mass was lower for SO patients, and these differences were statistically significant (P<0.001). Moreover, the SO group had a significantly higher percentage of patients with grade III obesity compared to the NSO group (76.5% vs 35.7%, P<0.05). Additionally, SO patients exhibited a significantly higher mean SATA but a lower mean SMA compared to NSO patients, with both differences being statistically significant (P<0.001). There was no statistically significant difference between SO and NSO patients on VATA (P=0.185), despite SO patients having a greater mean value than NSO patients. Furthermore, diabetes, hypertension, and hepatorenal function were not statistically significantly different between the two groups (P>0.05).

Perioperative Analysis

Patients in both groups completed LSG with similar intraoperative bleeding and no intraoperative deaths or conversions to the open abdomen. The average postoperative hospital stays for both groups were 3.5 days, and none of the patients were readmitted within 30 days after discharge (Table 2). Additionally, both the SO and NSO groups had one case of abdominal bleeding, which was successfully treated with medication and without other complications. While the mean operating time was longer for NSO patients compared to SO patients, this difference lacked statistical significance (P=0.082).

Table 2 Analysis of Perioperative Indicators After LSG in SO and NSO Patients

Analysis of Surgical Weight Loss Results

All 104 patients with obesity completed postoperative follow-ups at the 1st, 3rd, 6th, and 12th months, with no patients lost to follow-up. Figure 1 shows that the patients’ weight, BMI, and EBMI in both groups consistently decreased within one year after LSG, remaining lower than preoperative levels, accompanied by an increasing EWL% and TWL%. Additionally, SO patients had higher mean BMI and EBMI values and smaller mean EWL% values one year postoperatively than NSO patients, with statistically significant differences (P<0.01). AS shown in Table 3, our study revealed that 103 out of 104 patients with obesity (99%) had a favorable surgical weight loss effect one year after the operation. At the same time, patients in the SO group and the NSO group had a 33% and 32% reduction in total body weight at 1 year after surgery, respectively. Specifically, in the SO group, 70.6% of patients achieved good weight loss, while 82.9% did in the NSO group. Although the percentage of patients with good weight loss was higher in the NSO group, it did not reach statistical significance (P>0.05) Furthermore, our findings indicated that in the SO and NSO groups, 35.3% and 58.6% of patients achieved optimal weight loss separately, demonstrating that there is a statistically significant difference between the two groups (P=0.026).

Table 3 Analysis of the Effectiveness of Weight Loss Following LSG in SO and NSO Patients

Figure 1 Weight loss results within one year after LSG in SO and NSO patients. (A) Changes in weight within one year after LSG in SO and NSO patients. (B) Changes in BMI within one year after LSG in SO and NSO patients. (C) Changes in EBMI within one year after LSG in SO and NSO patients. (D) Changes in EWL% within one year after LSG in SO and NSO patients. (E) Changes in TWL% within one year after LSG in SO and NSO patients. In Figure (D), distinct horizontal lines are added at the EWL% values of 50%, 80%, and 100%. * P<0.05; ** P<0.01; **** P<0.0001; Error bars indicate Standard deviation. Abbreviations: SO, sarcopenic obesity; NSO, non-sarcopenic obesity; LSG, laparoscopic sleeve gastrectomy; BMI, body mass index; EWL%, percentage of excess weight loss; EMBI, excess body mass index; TWL%, percentage of total weight loss; Preop, preoperative.

In addition to this, this study also observed a great degree of remission of combined diabetes, hypertension, and OSA after LSG in both SO and NSO patients (Table 3). Among patients with diabetes, the remission rates in the NSO and SO groups were 100% and 71.4% respectively, this difference was statistically significant (P=0.04). Additionally, we found that the remission rates of hypertension and OSA in the SO group were 100.0% and 87.0%, respectively, whereas the remission rates in the NSO group were 75.0% and 74.5%, but none of the differences were statistically significant (P>0.05).

Postoperative Recurrent Weight Gain and Risk Factor Analysis

In this study, 74 eligible patients with obesity were followed up in the 2nd year after surgery, and no patient was lost to follow-up. According to Table 3, it was found that 27 patients (36.5%) out of 74 patients with obesity had recurrent weight gain within two years after LSG. Among these patients, 6 (26.1%) were in the SO group and 21 (41.2%) were in the NSO group.

As a result, NSO patients had a higher rate of postoperative recurrent weight gain than SO patients, but this difference was not statistically significant (P>0.05).

In addition, the study examined the factors contributing to recurrent weight gain after LSG in patients with obesity. Table 4 demonstrates that diabetes and lean mass was linked to recurrent weight gain after surgery (P<0.05) based on the univariate analysis. Further multifactorial analysis indicated that diabetes was an independent risk factor for postoperative recurrent weight gain in patients with obesity (P=0.042).

Table 4 Univariate and Multivariate Analysis of Factors Associated with Recurrent Weight Gain Within 2 years After LSG in a Whole Group of Patients

Discussion

When analyzing the baseline data, this study observed that the average preoperative BMI, SATA, and the percentage of patients with grade III obesity in the SO patients were higher than in NSO patients, and these differences were statistically significant (P <0.05). These statistically significant indicators suggest that patients in the SO group were more obese. A clinical study involving 972 patients with obesity reached a similar conclusion.³¹ These significant differences observed may stem from the interplay between sarcopenia and obesity. In these conditions, metabolic disturbances—such as chronic inflammation and hormonal imbalances—are more pronounced, resulting in the degradation of lean body tissue and an increase in inflammatory factors. This ultimately promotes the accumulation of adipose tissue.³² Consequently, requiring more attention from clinicians.

By analyzing the perioperative data, our study found similar results for operative time, intraoperative bleeding, postoperative hospital stays, and postoperative complications between patients in the SO and NSO groups. Another cohort study with 245 patients with obesity also showed partially similar results but noted significant differences in the duration of surgery and postoperative hospital stays between the SO and NSO groups²⁰ (P<0.001). Its study attributed the significant difference to the greater area of visceral fat in the SO group. However, there may be individual differences in the body composition characteristics of SO patients.³³ Our study found that the difference in the VATA between the SO and NSO groups was not statistically significant (P=0.185, Table 1). Therefore, our study yielded the opposite result.

Many studies have found that weight reduction and improvement of comorbid diseases tend to stabilize within one year after LSG,³⁴ so we analyzed the weight loss results by examining the follow-up data of patients with obesity during the first year after surgery. Our findings revealed that the weight, BMI, and severity of comorbid diseases of patients with obesity in both groups were lower than the preoperative levels. And the EWL% and TWL% values gradually increased compared to those before the surgery. Similar findings have been reported in other studies; for example, A meta-analysis that included 2300 young patients with obesity found a mean BMI reduction of 17.8 kg/m² in patients with obesity after LSG and some relief from comorbidities such as diabetes and hypertension.³⁵ This reduction may be attributed to the decreased stomach volume and a decrease in the secretion of hunger hormones after surgery, leading to restricted food intake and subsequent weight loss.³⁶ Further, insulin resistance and inflammatory response improve, thereby assisting in the alleviation of diabetes, hypertension, and other co-morbidities.³⁷ Simultaneously, this study identified that SO patients had higher mean BMI, EBMI values, and smaller mean EWL% values one year postoperatively than NSO patients, with statistically significant differences (P<0.01). These results imply that SO probably negatively impacts weight loss outcomes following LSG. Furthermore, another study reported that SO led to a significant elevation in leptin levels among patients with obesity.³⁸ While LSG has the potential to ameliorate leptin resistance in patients with obesity,³⁹ the presence of SO results in persistently elevated leptin levels post-surgery. This exacerbates leptin resistance, subsequently influencing postoperative weight loss.

Some researchers have identified a strong link between SO and various comorbidities, including diabetes, hypertension, and OSA. SO can exacerbate these conditions through mechanisms such as increased insulin resistance, vascular dysfunction, and chronic inflammation.^31,40,41 Our study found that patients in the SO group experienced worse postoperative diabetes remission compared to those in the NSO group, and this difference was statistically significant. This finding aligns with the above studies.

Surprisingly, however, we discovered that patients in the NSO group had lower rates of remission for both hypertension and OSA than those in the SO group, although this difference was not statistically significant (P>0.05). Additionally, a cohort study involving 245 patients with obesity reported similar results.²⁰ Given the limited research on the impact of SO on the treatment of comorbidities in patients with obesity undergoing LSG, as well as the small number of patients included in existing studies with comorbidities, our findings may be subject to bias. Therefore, larger-scale, multicenter clinical studies are necessary to further explore the effect of SO on the efficacy of postoperative relief from comorbidities in patients with obesity. Evidence suggests that nutritional and exercise interventions are effective in mitigating SO;⁴² therefore, patients with obesity with SO require more rigorous nutritional and exercise management.

Current evaluation metrics for surgical weight loss outcomes advocate the use of EWL% or TWL%.⁴³ In contrast to previous research, our study offers a comprehensive analysis of surgical weight loss outcomes in patients with obesity by examining the EWL% in the first postoperative year. Our findings indicate that SO patients exhibited lower rates of optimal weight loss and good weight loss compared to NSO patients. This provides additional evidence that SO negatively impacts short-term weight loss outcomes after LSG.

Numerous studies have indicated that the first year after LSG is characterized by a high prevalence of postoperative recurrent weight gain.⁴⁴ Consequently, in our study, 74 eligible patients with obesity were followed up in the 2nd year after surgery. Our findings revealed a postoperative recurrent weight gain rate of 36.5%. A review examined six different diagnostic criteria for postoperative recurrent weight gain after bariatric surgery. It concluded that the typical range of recurrent weight gain post-surgery is between 9% and 91%.⁴⁵ This suggests that the rate of postoperative recurrent weight gain observed in our study falls within a reasonable range. Furthermore, our study observed that NSO patients had a higher rate of postoperative recurrent weight gain than SO patients, this difference was not statistically significant (P=0.212). This discrepancy may be attributed to the more gradual nature of postoperative weight changes in the SO group, and the time required to achieve minimum body weight was extended in SO patients than NSO patients,²⁰ resulting in a reduced number of cases meeting the criteria for postoperative recurrent weight gain. However, it is possible that the small sample size led to a Type II error, rendering the differences between the two groups statistically insignificant. To date, no scholarly investigations have examined the impact of SO on postoperative recurrent weight gain following LSG in patients with obesity, this study provides a new direction for research in this area. At the same time, Further studies with larger samples are necessary to clarify the impact of SO on recurrent weight gain following LSG.

Additionally, this study investigated the risk factors associated with postoperative recurrent weight gain in the patients with obesity, revealing that diabetes serves as an independent risk factor. The relationship between diabetes and obesity is significant, as they synergistically exacerbate insulin resistance in obese individuals. This interaction is characterized by a marked elevation in insulin levels, subsequently promoting recurrent weight gain.³⁷ Additionally, a more stringent follow-up protocol should be implemented for patients with obesity with diabetes to address and mitigate postoperative recurrent weight gain promptly.

This study also has some limitations. First, this study is a retrospective clinical study, and there may be recall bias or potential confounding bias in the study, which may affect the results; second, the number of cases in this study is not rich enough, especially the cases of co-morbidities and postoperative recurrent weight gain, which may bias the assessment of comorbidities and postoperative recurrent weight gain, and therefore further studies with multi-centers and large sample sizes are needed; Third, the generalizability of the findings may be limited; this study is currently focused on 2-year follow-up after LSG, so it can only investigate the effect of SO in short-term weight loss efficacy after LSG; however, the role on mid- and long-term postoperative weight loss efficacy is still unclear, and longer follow-up observation is needed.

Conclusion

SO adversely affects short-term weight loss outcomes following LSG. However, the effect of SO on postoperative recurrent weight gain was not statistically significant, indicating that further research is needed. Furthermore, diabetes serves as an independent risk factor for postoperative recurrent weight gain in the patients with obesity. Consequently, bariatric surgeons should be taken more stringent dietary and exercise regimens, alongside comprehensive follow-up strategies for patients with obesity with concurrent SO and diabetes.

Acknowledgments

Thanks for the active cooperation of patients with obesity, the mutual help of colleagues, and the guidance of tutor.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This research was funded by the National Natural Science Foundation of China (Project Grant No. 82103165), the Science and Technology Planning Project of the Health Commission of Jiangxi Province (Project Grant No. 202310020), and “the Talent 555 project of Jiangxi Province”, People’s Republic of China.

Disclosure

All authors declare no conflict of interest.

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Study setting, design and period

This retrospective study was conducted at DR-TB TICs located in Addis Ababa, the capital city of Ethiopia.

According to the Central Statistical Agency’s (CSA) population projection, Addis Ababa has a population size of 3.6 million [19]. It has 11 sub-cities and 123 woredas, with 13 public and more than 25 private hospitals.

St. Peter’s and Alert Comprehensive Specialized Hospitals are the only DR-TB TICs in the city.

St. Peter’s specialized hospital was established in 1953. In the 1960 s, the hospital was the first TB treatment and training center in Ethiopia. It was the first DR-TB TIC in Ethiopia. The TIC has 40 beds.

Alert comprehensive specialized hospital was established in 1934. It was the second DR-TB TIC in Addis Ababa. The TIC has 24 beds.

Data was collected from September 20 to October 15, 2022.

Study participants and sampling procedures

Study participants were adults ((age ≥ 18 years) with RR/MDR-TB treated both at Alert and St. Peter’s Specialized Hospitals. Data was extracted retrospectively among patients treated from January 2016 to April 2022.

First, the total number of MDR/RR-TB patients within the study period was obtained from both Alert (n = 380) and St. Peter’s (n = 535) specialized hospitals. The sample size was allocated proportionally; it was 138 and 193 for Alert and St. Peter’s specialized hospitals, respectively. Seven charts without baseline CXRs were excluded from the study (six and one for Alert and St. Peter’s specialized hospitals, respectively). The data was collected from 324 charts.

Operational definition

Drug-resistant TB is resistant to either or both first-or SL-anti-TB drugs confirmed by drug susceptibility testing (DST).

Rifampicin-mono resistant TB: resistance to rifampicin detected using phenotypic or genotypic methods, with or without resistance to other FL-anti-TB drugs except isoniazid.

Multidrug-resistance (MDR): resistance to at least isoniazid and rifampicin.

Anemia: When hemoglobin level is < 12 g/dL for women and < 13 g/dL for men.

Abnormal chest x-rays: are defined as the presence of nodules, cavities, infiltrations, fibrosis, consolidations, fluid collections, masses, enlarged hilar lymph nodes, narrowing or compression of large airways, opacity in lung tissue, miliary mottling, pleural effusion, pericardial effusion, and abnormality of the thoracic vertebra [12, 20].

Normal chest x-ray: is the absence of abnormal CXR findings.

Comorbidities: presence of medical conditions like diabetes mellitus, hypertension, kidney diseases, liver diseases, asthma, heart diseases, and others in addition to DR-TB [21].

Data collection procedure and quality assurance

Data was extracted using a well-organized checklist containing socio-demographics, clinical, chest x-rays, and laboratory variables. The data was collected by reviewing charts, registration books, green cards, and medical profiles of patients.

Before the actual data collection, a preliminary chart review was done to check the quality of the data collection tool at the University of Gondar Comprehensive Specialized Hospital, DR-TB TIC. Based on the feedbacks obtained from the preliminary review, we updated the data collection checklist.

Three data collectors and one supervisor with previous experience were assigned to each DR-TB TIC. Prior to the data collection, training was given for data collectors and supervisors.

Data entry and analysis

Data completeness and consistency were checked first. The data was entered using Epi Data version 4.1 and then exported to SPSS version 25 for data cleaning and analysis. Descriptive statistics were used to summarize the data using tables and figures. For continuous variables, normality distribution tests were computed using both statistical and normality plot tests; the data was not normally distributed. The Hosmer and Lemeshow goodness-of-fit tests were performed; the binary logistic regression model was a good fit at a P-value of 0.85. The binary logistic regression model was computed to identify factors associated with abnormal CXR features. Bivariate logistic regression analysis was done first to control the effect of confounders, then variables with a p-value < 0.2 were taken into the multivariate logistic regression analysis. Variables with a P-value < 0.05 were considered statistically significant.