Effect of lifestyle intervention on mobilization of fat storage pools in individuals with abdominal obesity: a prospective study

doi:10.21203/rs.3.rs-4891348/v1

Objective

The effect of lifestyle intervention on the reduction of fat in specific body areas for individuals with abdominal obesity has not been thoroughly studied. In this study, we evaluate if lifestyle intervention can uniquely influence various fat storage areas and to explore the relationships between fat loss in specific locations and health results.

Methods

In this prospective cohort study conducted at a single center, 39 individuals with abdominal obesity participated in a lifestyle intervention from October 18, 2022, to April 20, 2023. Magnetic resonance imaging was used to measure subcutaneous fat area (SFA), visceral fat area (VFA), and the proton density fat fraction (PDFF) of the liver and pancreas at the baseline and six months post-intervention. This study's protocol was documented on clinicaltrials.gov.

Results

Out of 39 individuals, the median age was 28.0 years with an interquartile range (IQR) of 22.0 to 37.5 years. The median body mass index (BMI) was 30.4 kg/m2, with an IQR of 28.5 to 33.2 kg/m2, and 41.0% of the participants were female. The median (IQR) reduction in hepatic PDFF was highest after lifestyle intervention at 46.5% (28.8%-68.4%), followed by pancreatic PDFF reduction at 24.9% (10.4%-45.0%), VFA reduction at 19.5% (7.2%-32.3%), and SFA reduction at 12.2% (6.7%-18.9%) (P < 0.001). Using the Pearson correlation coefficient, positive relationships were identified between variations in VFA and alterations in fasting glucose and HOMA-IR (r = 0.401, P = 0.01; r = 0.830, P < 0.001), as well as between changes in hepatic PDFF and HOMA-IR (r = 0.520, P < 0.001).

Conclusion

Lifestyle intervention primarily reduced liver fat, then pancreatic fat and visceral fat, while subcutaneous fat was the least affected in individuals with abdominal obesity. Decreases in VAT and liver fat are independently linked to the improvement of glucose metabolism following lifestyle intervention.

Lifestyle intervention

Fat mobilization

Body fat

MRI

glucose metabolism

There is a growing interest regarding how weight reduction influence the targeted breakdown of fat [1–3]. Excess visceral fat and ectopic fat deposits are crucial in the development and progression of obesity-associated issues and abnormal glucose metabolism, potentially through processes beyond body mass index[4–6]. In comparison, subcutaneous adipose tissue (SAT) might function as a neutral or even beneficial fat storage site that helps reduce cardio-metabolic risk [7–9]. Hence, the positive metabolic effects of a weight reduction plan might be to linked to reducing ectopic and visceral fat rather than subcutaneous fat; essentially, the optimal weight loss approach should focus on targeting visceral and ectopic fat before subcutaneous fat.

Moreover, due to the prevalent obesity epidemic, metabolically associated fatty liver disease (MAFLD) has emerged as a significant public health issue, impacting 30% of people worldwide. On the other hand, intrapancreatic fat accumulation(IPFD) appears not to be solely related to elevated body mass index, occurring even more often than type 2 diabetes mellitus (T2DM) and acute pancreatitis[11]. Nonetheless, no medications have been sanctioned to reduce fat in the liver or pancreas, and the available treatments for MAFLD and intra-pancreatic fat deposition are still scarce. Consequently, it is crucial to discover effective therapies for MAFLD and IPFD.

Lifestyle intervention is a safer treatment than bariatric surgery and medication. However, whether lifestyle interventions can induce different mobilizations of fat storage or deposits at specific sites with different metabolic characteristics (i.e., visceral, subcutaneous, liver, and pancreas) has not been well studied. It remains unclear if the metabolic advantages of a lifestyle change are specifically due to a decrease in fat at a particular location, rather than merely a drop in body mass index or overall weight.

The objective of our research was to evaluate if lifestyle changes can uniquely influence particular fat storage areas and to explore the relationships between fat loss in specific regions and health outcomes.

2.1 Study Design and Participants

For this prospective study, obese patients listed for lifestyle intervention were enrolled from a single center from 18 October 2022 to 25 April 2023, with a 6-month follow-up. This research examined how lifestyle changes affect the reduction of fat in specific areas and the relationship between targeted fat loss and health results. The research plan received approval from our hospital's Institutional Review Board and was listed on Clinical Trials.gov. Every participant gave formal written consent, and all the information was anonymized. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines for cohort studies.

Participants had to meet these criteria: (1) be between 18 and 80 years old, (2) have a BMI greater than 28.0 kg/m2, and (3) exhibit abdominal obesity, defined as a waist circumference of at least 90 cm for men and 85 cm for women. The criteria for exclusion were: (1) a prior history of pancreatic diseases; (2) severe complications from type 2 diabetes or other significant diseases; (3) usage of drugs affecting body weight, insulin sensitivity, or metabolic-associated fatty liver disease (such as insulin, glucocorticoids, thiazolidinediones, metformin, SGLT-2 inhibitors, or GLP-1 receptor agonists); and (4) alcohol dependence, defined as ethanol intake exceeding 140 g/week for men and 70 g/week for women.

2.2 Procedures

The registered subjects were examined initially and again six months following the lifestyle changes. OGTT-0 h, OGTT-0.5 h, OGTT-1 h, and OGTT-2 h were tested before and after the consumption of 82.5 g of glucose monohydrate. A specialized case manager took anthropometric measurements; lab tests evaluated glucolipid metabolism; and MRI scans quantified the subcutaneous and visceral fat areas in the abdomen, as well as the fat fractions in the liver and pancreas. Every lab test was conducted following a 10-hour fast overnight.

A team of nutritionists conducted all the lifestyle interventions. An InBody 770 bioimpedance analyzer was used to test the actual and target weights. The energy-restricted balanced diet was formulated as 1200 kcal and 1500 kcal for women and men, respectively. The recommended daily caloric intake includes 50–60% carbohydrates, 20–30% fats, and 15–25% proteins. The participants were recommended to exercise for a minimum of 30 minutes 5 or more days per week.

A portable stadiometer (Leicester Height Measure, Seca) was used to measure height (± 0.01 m) without footwear. BMI was determined by taking the weight in kilograms and dividing it by the height in meters squared. Waist circumference (WC) (± 0.1 cm) was taken at the navel, while hip circumference (HC) (± 0.1 cm) was recorded at the broadest part of the hips using a inflexible tapeline. Blood pressure was taken using a device from A&D, Japan.

2.3 Outcome Measurements

The main objective of the research was the targeted fat mobilization, defined by the MRI-based percentage of fat loss, which was calculated as (initial measure minus follow-up measure)/(initial measure)×100 and scheduled to be evaluated at the 6-month follow-up.

Magnetic resonance imaging was conducted using the INGENIA ELITION X system from Philips Medical Systems Nederland B.V. Using Slice-O-Matic software to outline the subcutaneous and visceral fat at the level of the transverse process of the L3 vertebra in the T2WI sequence[12]. Visceral fat area (VFA) refers to the sum of fat regions located within the peritoneal and retroperitoneal spaces [13]. Fat buildup in the pancreas and liver was assessed using pancreatic PDFF and liver PDFF, respectively. The sequence of pulses measured in this research was an mDIXON Quant (Philips Medical Systems Nederland B.V.). Regions of interest (ROIs) were delineated to measure the liver and pancreatic PDFF; eight ROIs were manually drawn in various areas of the liver [14, 15], and three ROIs were positioned in different areas of the pancreas, which were then averaged to calculate the final liver and pancreatic PDFF, reducing bias from uneven fat distribution [16].

2.4 Sample size

We calculated the sample size based on these assumptions: (1) a two-tailed significance level of 0.05, (2) a minimum power of 90%, and (3) an initial hypothesis that lifestyle changes primarily reduce liver fat, then pancreatic fat, visceral fat tissue, and subcutaneous fat tissue [17]. The ultimate analysis included a minimum of 39 individuals. The sample volume was estimated via PASS software version 20 (NCSS, LLC). To account for a 10% dropout rate, we increased the initial enrollment numbers to guarantee that the final sample size would satisfy the study's requirements [18–20].

2.5 Statistical analysis

Continuous data were shown as means ± standard deviations, or medians (interquartile ranges [IQRs]), according to the normality tests. Categorical data were represented as counts (percentages). Absolute variations in continuous data were labeled as Δweight, ΔBMI, ΔWHR, Δhepatic PDFF and so on.

Paired t tests or Wilcoxon signed-rank tests were performed to compare changes from baseline to 6 months after lifestyle intervention. Independent t tests or Mann‒Whitney U tests were performed for comparisons between two groups; ANOVA or Kruskal‒Wallis H tests was used for comparison among three or four groups. The planned subgroup analyses encompassed gender, body mass index, and health condition. The relationship between localized fat reduction and clinical results was examined using the Pearson correlation coefficient. A two-sided P value below 0.05 was deemed to be of statistical significance. Analysis was conducted using R software version 3.5.3 (http://www.r-project.org/).

3.1 Participants and Clinical Outcomes

Out of 44 individuals initially considered suitable for the study, 5 were later excluded due to refusal to undergo the baseline MRI (2 participants) or the 6-month MRI scans (3 participants). In the end, we managed to include 39 individuals in the concluding analysis (see Figure 1). Among the 39 individuals, the median age was 28 years (IQR: 22 to 37.5), with 59% being male. Additionally, 61.5% had diabetes or prediabetes, and 84.6% were diagnosed with MAFLD. The medians (IQRs) or means ± SDs of baseline weight, BMI, WC, fasting glucose, FINS, HOMA-IR, and HOMA-β were 88.8 ± 13.4 kg, 30.4 (4.7) kg/m², 99.0 (7.5) cm², 5.7 ± 0.7 mmol/L, 23.7 (9.3) uU/ml, 6.2 (2.8) and 241.1 (161.7), respectively. After lifestyle intervention of six months, weight dropped to 80.8 ± 13.7 kg, BMI was 28.3 (4.4) kg/m2, waist circumference measured 92.9 (9.6) cm², fasting glucose levels were 5.2 ± 0.6 mmol/L, fasting insulin was 12.6 (7.1) uU/ml, HOMA-IR at 2.9 (1.8), and HOMA-β was 161.6 (145.9), with all reductions being statistically significant (P < 0.05). Table 1 provides a summary of all baseline and post-intervention anthropometric and laboratory data.

Figure 1. Flowchart of patient enrollment.

Table 1. Anthropometric and lab measurements before and after lifestyle intervention.

	Baseline	6 months	P value
n	39
age, median (IQR)	28.0 (15.5)
gender, n (%)
female	16 (41.0%)
male	23 (59.0%)
glucometabolic states	39		0.31
diabetes	5	4
prediabetes	19	13
normal glucose tolerance	15	22
MAFLD	33	22	0.006
Weight, mean ± SD, kg	88.8 ± 13.4	80.8 ± 13.7	< 0.001
BMI, median (IQR)	30.4 (4.7)	28.3 (4.4)	< 0.001
WC, median (IQR), cm	99.0 (7.5)	92.9 (9.6)	< 0.001
HC, median (IQR), cm	103.5 (6.5)	97.9 (7.2)	< 0.001
WHR, mean ± SD	0.97 ± 0.05	0.96 ± 0.06	0.32
SBP, mean ± SD, mmHg	126.7 ± 9.3	118.6 ± 7.7	< 0.001
DBP, median (IQR), mmHg	73.0 (14)	70.0 (11)	< 0.001
TG, median (IQR)	2.3 (1.0)	1.1 (0.4)	< 0.001
LDL-C, mean ± SD	2.9 ± 0.8	2.9 ± 0.7	0.96
TC, mean ± SD	5.2 ± 0.8	4.6 ± 0.9	0.006
HDL-C, median (IQR)	0.96 (0.27)	1.16 (0.34)	0.010
UA, median (IQR)	436 (76.5)	349 (178)	0.04
ALT, median (IQR)	36.0 (29.5)	19.0 (21.0)	0.009
AST, mean ± SD	34.9 ± 17.4	22.4 ± 9.3	0.004
TBIL, median (IQR)	10.6 (6.1)	11.2 (7.8)	0.47
DBIL, median (IQR)	3.2 (1.5)	3.8 (3.6)	0.05
Crea, mean ± SD	69.0 ± 14.6	64.2 ± 14.1	0.297
Glu0, mean ± SD	5.7 ± 0.7	5.2 ± 0.6	0.005
FINS, median (IQR)	23.7 (9.3)	12.6 (7.1)	<0.001
Glu30, mean ± SD	10.0 ± 1.93	9.2 ± 1.6	0.13
Glu60, median (IQR)	10.3 (4.8)	9.7 (2.8)	0.27
Glu120, median (IQR)	8.0 (3.8)	7.1 (3.5)	0.23
HbA1c%, mean ± SD	5.8 ± 0.3	5.6 ± 0.4	0.16
HOMA-IR, median (IQR)	6.2 (2.8)	2.9 (1.8)	< 0.001
HOMA-β(%), median (IQR)	241.1 (161.7)	161.6 (145.9)	0.0001
△I30/△G30, median (IQR)	16.8 (31.4)	29.6 (29.3)	0.20
AUCI60-120/G60-120, median (IQR)	17.9 (14.7)	12.1 (5.8)	0.33
ISI, median (IQR)	23.3 (12.2)	51.2 (27.2)	0
DI60-120, median (IQR)	569.9 (295.0)	576.2 (232.0)	0.32
SFA, median (IQR)	229.1(118.2)	205.1 (118.4)	<0.001
VFA, median (IQR)	109.0 (28.2)	92.1 (47.8)	<0.001
Hepatic PDFF, median (IQR)	14.6 (15.1)	8.1 (8.5)	<0.001
Pancreatic PDFF, median (IQR)	9.6 (7.6)	6.7 (6.9)	<0.001

Abbreviations: IQR, interquartile range; MAFLD, metabolically associated fatty liver disease; BMI, body mass index; WC, waist circumference; HC, hip circumference;WHR, waist-to-hip ratio, SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; TC, total cholesterol; HDL-C stands for high-density lipoprotein cholesterol; UA, uric acid; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TBIL, total bilirubin; DBIL, direct bilirubin; Crea, creatinine; FINS, fasting insulin; HbA1c, glycated hemoglobin;HOMA-IR, an index for evaluating insulin resistance through the homeostatic model; HOMA-β, homeostatic model assessment of β-cell function; △I30/△G30, the first phase of insulin response to glucose challenge; AUCI60-120/G60-120, late insulin secretion to glucose challenge; ISI, insulin sensitivity index; DI60-120, late insulin secretion; PDFF, proton density fat fraction; VFA, visceral fat area; SFA, subcutaneous fat area.

The baseline SFA, VFA, hepatic PDFF and pancreatic PDFF were 229.1 (193.5--311.7) cm2, 109.0 (102.6--130.8) cm2, 14.6 (9.6--24.7)%, and 9.6 (6.6--14.2)%, respectively. After lifestyle intervention of six months, the subcutaneous fat area reduced to 205.1 (168.4–286.8) cm2, the visceral fat area dropped to 92.1 (70.3–118.0) cm2, the liver proton density fat fraction decreased to 8.1 (3.0–11.5)%, and the pancreatic PDFF fell to 6.7 (3.4–10.3)%; all these declines were statistical significance (P < 0.001). Figure 2 illustrates the decreases in abdominal fat and intraorgan PDFF caused by the treatment.

Figure 2. Effect of 6 months lifestyle intervention on mobilization of fat storage pools. (a) changes in hepatic proton density fat fraction (PDFF); (b) changes in pancreatic PDFF; (c) changes in subcutaneous fat area; and (d) changes in visceral fat area.

After lifestyle intervention of six months, hepatic PDFF saw the highest reduction at 46.5% (28.8%-68.4%), with pancreatic PDFF decreasing by 24.9% (10.4%-45.0%), VFA by 19.5% (7.2%-32.3%), and SFA by 12.2% (6.7%-18.9%) (P <0.001). Figure 3a. shows the treatment-caused varying mobilization of specific body fat areas. A typical example of site-specific fat mobilization after lifestyle intervention is shown in Figure 3 b-d.

Figure 3. Changes in specific body fat areas from the baseline to six months after lifestyle intervention. (a) Comparative analysis of percentage reductions in localized body fat deposits. (b)-(d) A typical example of site-specific fat mobilization after lifestyle intervention (21 years, female, and BMI 30.8 kg/m2). (b) Decrease in belly fat area due to treatment. The visceral fat area (VFA) is highlighted in red, while the subcutaneous fat area (SFA) is marked in green. (c) Decrease in liver proton density fat fraction (PDFF) due to treatment. (d) Decrease in pancreatic PDFF due to treatment. ROI, region of interest.

Furthermore, an analysis of subgroups categorized by gender, body mass index, and glycometabolic status also showed comparable variations in fat mobilization (see Supplemental Fig.S1-3).

3.2 Relationships between localized fat reduction and metabolic indicator

Table 2 provides a summary of the Pearson correlation coefficients for changes in weight, BMI, waist circumference, hip circumference, waist-to-hip ratio, subcutaneous fat area, visceral fat area, and pancreatic PDFF; hepatic PDFF; as well as fasting plasma glucose, fasting plasma insulin, HOMA-IR, HOMA-β, ISI, triglycerides, LDL-C, HDL-C, systolic blood pressure, and diastolic blood pressure. The observed positive relationships included: changes in weight and LDL-C (r = 0.432, P = 0.01), changes in BMI and LDL-C (r = 0.385, P = 0.03), changes in VFA and glucose (r = 0.401, P = 0.01), changes in VFA and HOMA-IR (r = 0.830, P < 0.001), changes in VFA and TG (r = 0.688, P = 0), changes in hepatic PDFF and HOMA-IR (r = 0.520, P < 0.001), changes in hepatic PDFF and TG (r = 0.630, P < 0.001), and changes in pancreatic PDFF and LDL-C (r = 0.409, P = 0.02).

Table 2. Relationships between specific fat reduction and metabolic indicator.

Pearson correlation	△FPG	△insulin	△HOMA-IR	△HOMA-β	△ISI	△TG	△LDL-C	△HDL-C	△SBP	△DBP
△Weight	-0.015	-0.238	-0.134	-0.023	-0.044	-0.106	0.432*	-0.001	0.084	0.264
△BMI	-0.019	-0.218	-0.144	-0.010	-0.083	-0.050	0.385*	-0.040	0.010	0.200
△WC	-0.235	-0.115	-0.405	0.100	0.078	-0.452	0.177	0.157	0.086	0.137
△HC	-0.122	-0.171	-0.419	0.032	0.383	-0.149	0.090	0.201	0.236	-0.083
△WHR	-0.165	0.017	-0.061	0.053	-0.144	-0.305	0.046	0.041	-0.031	0.255
△SFA	-0.274	0.332	0.101	0.306	0.061	0.144	0.057	0.045	0.023	0.306
△VFA	0.401*	0.177	0.830**	-0.215	-0.272	0.688*	-0.312	-0.177	-0.119	0.226
△Pancreatic PDFF	-0.139	0.030	-0.284	0.210	-0.172	-0.215	0.409*	-0.178	0.106	-0.093
△Hepatic PDFF	0.206	0.174	0.520**	-0.073	0.077	0.630**	-0.164	-0.129	-0.211	-0.004

Abbreviations: BMI (body mass index), WC (waist circumference), HC (hip circumference), WHR (waist-to-hip ratio), SFA (subcutaneous fat area), VFA (visceral fat area), PDFF (proton density fat fraction), FPG (fasting plasma glucose), HOMA-IR (homeostatic model assessment of insulin resistance), HOMA-β (homeostatic model assessment of β-cell function), ISI (insulin sensitivity index), TG (triglycerides), LDL-C (low-density lipoprotein cholesterol), HDL-C (high-density lipoprotein cholesterol), SBP (systolic blood pressure), DBP (diastolic blood pressure).

Lifestyle intervention is a successful approach for treating obese individuals, leading to weight reduction, alleviation of obesity-related issues, enhanced metabolic functions, improved quality of life, and increased lifespan [21-27]. Nevertheless, the impact of lifestyle changes on fat distribution in particular areas for individuals with abdominal obesity remains largely unexplored. As far as we are aware, this research is the forward-looking study to thoroughly examine the varied reduction of visceral, liver, pancreatic, and subcutaneous fat after lifestyle changes. The research demonstrated that lifestyle changes primarily reduced liver fat, then pancreatic fat and visceral adipose tissue, with subcutaneous adipose tissue being the least affected. Our research offers further proof of the metabolic benefits of lifestyle changes, particularly in relation to targeted fat reduction. Previous studies indicated that fat stored in the liver and pancreas were pathological and had a greater impact on metabolic diseases than body mass index [28-30].

Recently, it was found that increased fat in the liver and pancreas was strongly associated with type 2 diabetes mellitus, with odds ratios of 2.16 [2.02-2.31] and 1.42 [1.34-1.51] per standard deviation increase, respectively [31]. A Mendelian randomization study additionally indicated a causal link between liver fat and the risk of type 2 diabetes mellitus, showing a 27% higher risk (1.27 [1.08, 1.49]) [32]. While earlier research indicated a decrease in liver and pancreatic fat due to lifestyle changes [32,33], they could not verify the specific reduction in visceral or subcutaneous fat, liver, or pancreatic fat. This distinction is crucial for healthcare providers and patients to evaluate the effectiveness of lifestyle modifications for treating NAFLD and IPFD, particularly when ectopic fat levels do not correlate with body mass index. It appears that there is an adversarial association between the VAT and SAT. Compared with VAT, SAT provides a secure lipid storage site because of its improved expansion ability, thus limiting abnormal lipid accumulation, whereas VAT has a greater extent to lipidolysis and secretion of additional inflammatory factors [34].

Our current study suggests that lifestyle interventions preferentially mobilize VAT and ectopic fat over SAT. An additional advantage of this research is that Asian individuals, who are more susceptible to ectopic and visceral lipid deposition, get unique benefits after the targeted reduction of body fat stores following lifestyle changes. Cui et al.[35] examined 49 Asian individuals before and three months following bariatric surgery, noting reductions in subcutaneous adipose tissue (23%, 17%-32%), visceral adipose tissue (36%, 30%-42%), liver fat (69%, 47%-80%), and pancreatic fat (51%, 37%-62%). Our study suggested that, compared with bariatric surgery, at 6 months after lifestyle intervention, SAT decreased by 12.2% (6.7%-18.9%), VAT decreased by 19.5% (7.2%-32.3%), hepatic fat decreased by 46.5% (28.8%-68.4%), and pancreatic fat decreased by 24.9% (10.4%-45.0%). The Diabetes Remission Clinical Trial (DiRECT) [33] noted reductions in liver and pancreas fat (13% ± 1% and 0.9% ± 0.2%, respectively; n = 40) after four months on a low-calorie diet during British participants. Despite observing two major sites of ectopic fat deposition, their results did not demonstrate the differential mobilization of site-specific adipose stores.

Furthermore, our studies indicate that the decrease in visceral fat area leads to better fasting glucose, triglycerides (TG), and HOMA-IR levels, while the reduction in liver fat contributes to the improvements in both HOMA-IR and TG levels. This finding aligns with earlier research, which similarly showed that the steady buildup of liver fat and VAT was closely associated with insulin resistance and type 2 diabetes mellitus [28, 36, 37]. However, the decrease in pancreatic fat is just accountable for the improvement in LDL-C. Thus, further research is required to elucidate the connection between pancreatic fat and glucose metabolism.

There were a number of constraints in our research. Initially, as anticipated, the 6-month check-in saw a 7% attrition rate. Nevertheless, our research included a sufficient number of participants to ensure proper statistical power and identify significant differences in the mobilization of specific body fat areas. Secondly, since patient recruitment was limited to one center and one ethnic group, the applicability of our findings might be compromised. Prospective multi-center and multi-ethnic studies are needed in the future. Ultimately, we recognize that variations among participants, including age, gender, and health conditions, could lead to bias.

Supplementary Materials: Figure S1:Analysis of subgroups based on gender and treatment-related changes in specific body fat areas from the baseline to six months post lifestyle intervention; Figure S2: Analysis of subgroups based on BMI and the differential mobilization of specific body fat areas induced by treatment from the baseline to six months post-lifestyle intervention; Figure S3: Analysis of subgroups based on glucose metabolism and treatment-related changes in specific body fat areas from the baseline to six months post lifestyle intervention.

Author Contributions: Conceptualization, H.L.and P.J.; methodology, H.L.and JH.D.; software, H.L.; validation, GP.G., J.L. and YC.L.; formal analysis, M.L.; investigation, H.L.; resources, H.L.; data curation, P.J. and PF.R.; writing—original draft preparation, H.L.; writing—review and editing, H.L.; visualization, H.L.; supervision, P.J. and PF.R.; project administration, P.J. and PF.R.; funding acquisition, P.J. Every author has reviewed and consented to the final version of the manuscript.

Funding: This study received financial support from the Natural Science Foundation of Hunan Province, China (2024JJ9052), as well as from the China International Medical Foundation through grants (YLHR Diabetes Metabolism Research Fund Project, Z-2017-26-2202-4 ).

Ethics Approval: This research adhered to the principles outlined in the Declaration of Helsinki, received approval from the Third Xiangya Hospital's Institutional Review Board (protocol number 22218, approved on October 18, 2022), and was registered on ClinicalTrials.gov (NCT06441409).

Consent Statement: All participants in the research provided their informed consent. Patients provided written consent to authorize the publication of this paper.

Data availability statement: The raw data supporting the conclusions of this article will be made available by the authors upon request.

Acknowledgments: Acknowledges the author contributions.

Conflicts of Interest:The authors state that they do not have any competing interests.

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No competing interests reported.

SupplementaryFigures810.docx

Effect of lifestyle intervention on mobilization of fat storage pools in individuals with abdominal obesity: a prospective study

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Abstract

Objective

Methods

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1. Introduction

2. Materials and methods

2.1 Study Design and Participants

2.2 Procedures

2.3 Outcome Measurements

2.4 Sample size

2.5 Statistical analysis

3. Results

4. Discussion

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References

Additional Declarations

Supplementary Files

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Version 1